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+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/INSTALLER @@ -0,0 +1 @@ +pip diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/LICENSE b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..733963a744c3d6710058de9f0ea316893c5492ca --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/LICENSE @@ -0,0 +1,1250 @@ +BSD 3-Clause License + +Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team +All rights reserved. + +Copyright (c) 2011-2023, Open source contributors. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + 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Kain +orc +Pascal Cuoq +Patrick Oppenlander +Petr Hosek +Petr Skocik +Pierre Carrier +Reini Urban +Rich Felker +Richard Pennington +Ryan Fairfax +Samuel Holland +Segev Finer +Shiz +sin +Solar Designer +Stefan Kristiansson +Stefan O'Rear +Szabolcs Nagy +Timo Teräs +Trutz Behn +Valentin Ochs +Will Dietz +William Haddon +William Pitcock + +Portions of this software are derived from third-party works licensed +under terms compatible with the above MIT license: + +The TRE regular expression implementation (src/regex/reg* and +src/regex/tre*) is Copyright © 2001-2008 Ville Laurikari and licensed +under a 2-clause BSD license (license text in the source files). The +included version has been heavily modified by Rich Felker in 2012, in +the interests of size, simplicity, and namespace cleanliness. + +Much of the math library code (src/math/* and src/complex/*) is +Copyright © 1993,2004 Sun Microsystems or +Copyright © 2003-2011 David Schultz or +Copyright © 2003-2009 Steven G. 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Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND +ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.A. HISTORY OF THE SOFTWARE +========================== + +Python was created in the early 1990s by Guido van Rossum at Stichting +Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands +as a successor of a language called ABC. Guido remains Python's +principal author, although it includes many contributions from others. + +In 1995, Guido continued his work on Python at the Corporation for +National Research Initiatives (CNRI, see https://www.cnri.reston.va.us) +in Reston, Virginia where he released several versions of the +software. + +In May 2000, Guido and the Python core development team moved to +BeOpen.com to form the BeOpen PythonLabs team. In October of the same +year, the PythonLabs team moved to Digital Creations, which became +Zope Corporation. In 2001, the Python Software Foundation (PSF, see +https://www.python.org/psf/) was formed, a non-profit organization +created specifically to own Python-related Intellectual Property. +Zope Corporation was a sponsoring member of the PSF. + +All Python releases are Open Source (see https://opensource.org for +the Open Source Definition). Historically, most, but not all, Python +releases have also been GPL-compatible; the table below summarizes +the various releases. + + Release Derived Year Owner GPL- + from compatible? (1) + + 0.9.0 thru 1.2 1991-1995 CWI yes + 1.3 thru 1.5.2 1.2 1995-1999 CNRI yes + 1.6 1.5.2 2000 CNRI no + 2.0 1.6 2000 BeOpen.com no + 1.6.1 1.6 2001 CNRI yes (2) + 2.1 2.0+1.6.1 2001 PSF no + 2.0.1 2.0+1.6.1 2001 PSF yes + 2.1.1 2.1+2.0.1 2001 PSF yes + 2.1.2 2.1.1 2002 PSF yes + 2.1.3 2.1.2 2002 PSF yes + 2.2 and above 2.1.1 2001-now PSF yes + +Footnotes: + +(1) GPL-compatible doesn't mean that we're distributing Python under + the GPL. All Python licenses, unlike the GPL, let you distribute + a modified version without making your changes open source. The + GPL-compatible licenses make it possible to combine Python with + other software that is released under the GPL; the others don't. + +(2) According to Richard Stallman, 1.6.1 is not GPL-compatible, + because its license has a choice of law clause. According to + CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1 + is "not incompatible" with the GPL. + +Thanks to the many outside volunteers who have worked under Guido's +direction to make these releases possible. + + +B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON +=============================================================== + +Python software and documentation are licensed under the +Python Software Foundation License Version 2. + +Starting with Python 3.8.6, examples, recipes, and other code in +the documentation are dual licensed under the PSF License Version 2 +and the Zero-Clause BSD license. + +Some software incorporated into Python is under different licenses. +The licenses are listed with code falling under that license. + + +PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2 +-------------------------------------------- + +1. This LICENSE AGREEMENT is between the Python Software Foundation +("PSF"), and the Individual or Organization ("Licensee") accessing and +otherwise using this software ("Python") in source or binary form and +its associated documentation. + +2. Subject to the terms and conditions of this License Agreement, PSF hereby +grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce, +analyze, test, perform and/or display publicly, prepare derivative works, +distribute, and otherwise use Python alone or in any derivative version, +provided, however, that PSF's License Agreement and PSF's notice of copyright, +i.e., "Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, +2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 Python Software Foundation; +All Rights Reserved" are retained in Python alone or in any derivative version +prepared by Licensee. + +3. In the event Licensee prepares a derivative work that is based on +or incorporates Python or any part thereof, and wants to make +the derivative work available to others as provided herein, then +Licensee hereby agrees to include in any such work a brief summary of +the changes made to Python. + +4. PSF is making Python available to Licensee on an "AS IS" +basis. PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR +IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND +DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS +FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT +INFRINGE ANY THIRD PARTY RIGHTS. + +5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON +FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS +A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON, +OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF. + +6. This License Agreement will automatically terminate upon a material +breach of its terms and conditions. + +7. Nothing in this License Agreement shall be deemed to create any +relationship of agency, partnership, or joint venture between PSF and +Licensee. This License Agreement does not grant permission to use PSF +trademarks or trade name in a trademark sense to endorse or promote +products or services of Licensee, or any third party. + +8. By copying, installing or otherwise using Python, Licensee +agrees to be bound by the terms and conditions of this License +Agreement. + + +BEOPEN.COM LICENSE AGREEMENT FOR PYTHON 2.0 +------------------------------------------- + +BEOPEN PYTHON OPEN SOURCE LICENSE AGREEMENT VERSION 1 + +1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an +office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the +Individual or Organization ("Licensee") accessing and otherwise using +this software in source or binary form and its associated +documentation ("the Software"). + +2. 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This +Agreement may also be obtained from a proxy server on the internet +using the following URL: http://hdl.handle.net/1895.22/1013". + +3. In the event Licensee prepares a derivative work that is based on +or incorporates Python 1.6.1 or any part thereof, and wants to make +the derivative work available to others as provided herein, then +Licensee hereby agrees to include in any such work a brief summary of +the changes made to Python 1.6.1. + +4. CNRI is making Python 1.6.1 available to Licensee on an "AS IS" +basis. CNRI MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR +IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, CNRI MAKES NO AND +DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS +FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON 1.6.1 WILL NOT +INFRINGE ANY THIRD PARTY RIGHTS. + +5. 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This License Agreement shall be governed by the federal +intellectual property law of the United States, including without +limitation the federal copyright law, and, to the extent such +U.S. federal law does not apply, by the law of the Commonwealth of +Virginia, excluding Virginia's conflict of law provisions. +Notwithstanding the foregoing, with regard to derivative works based +on Python 1.6.1 that incorporate non-separable material that was +previously distributed under the GNU General Public License (GPL), the +law of the Commonwealth of Virginia shall govern this License +Agreement only as to issues arising under or with respect to +Paragraphs 4, 5, and 7 of this License Agreement. Nothing in this +License Agreement shall be deemed to create any relationship of +agency, partnership, or joint venture between CNRI and Licensee. 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IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, +INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM +LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR +OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR +PERFORMANCE OF THIS SOFTWARE. +Copyright (c) 2014, Al Sweigart +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +* Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +* Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +* Neither the name of the {organization} nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.Copyright (c) 2017 Anthony Sottile + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in +all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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IN NO EVENT SHALL ELECTRONIC ARTS INC. BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES +(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; +LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND +ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +---- + +Portions of code from MODP_ASCII - Ascii transformations (upper/lower, etc) +https://github.com/client9/stringencoders + + Copyright 2005, 2006, 2007 + Nick Galbreath -- nickg [at] modp [dot] com + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + + Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + Neither the name of the modp.com nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + This is the standard "new" BSD license: + http://www.opensource.org/licenses/bsd-license.php + +https://github.com/client9/stringencoders/blob/cfd5c1507325ae497ea9bacdacba12c0ffd79d30/COPYING + +---- + +Numeric decoder derived from from TCL library +https://opensource.apple.com/source/tcl/tcl-14/tcl/license.terms + * Copyright (c) 1988-1993 The Regents of the University of California. + * Copyright (c) 1994 Sun Microsystems, Inc. + + This software is copyrighted by the Regents of the University of + California, Sun Microsystems, Inc., Scriptics Corporation, ActiveState + Corporation and other parties. 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Notwithstanding the foregoing, the + authors grant the U.S. Government and others acting in its behalf + permission to use and distribute the software in accordance with the + terms specified in this license.Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. 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Wilcox + Ada Worcester + Alex Dowad + Alex Suykov + Alexander Monakov + Andre McCurdy + Andrew Kelley + Anthony G. Basile + Aric Belsito + Arvid Picciani + Bartosz Brachaczek + Benjamin Peterson + Bobby Bingham + Boris Brezillon + Brent Cook + Chris Spiegel + Clément Vasseur + Daniel Micay + Daniel Sabogal + Daurnimator + David Carlier + David Edelsohn + Denys Vlasenko + Dmitry Ivanov + Dmitry V. Levin + Drew DeVault + Emil Renner Berthing + Fangrui Song + Felix Fietkau + Felix Janda + Gianluca Anzolin + Hauke Mehrtens + He X + Hiltjo Posthuma + Isaac Dunham + Jaydeep Patil + Jens Gustedt + Jeremy Huntwork + Jo-Philipp Wich + Joakim Sindholt + John Spencer + Julien Ramseier + Justin Cormack + Kaarle Ritvanen + Khem Raj + Kylie McClain + Leah Neukirchen + Luca Barbato + Luka Perkov + M Farkas-Dyck (Strake) + Mahesh Bodapati + Markus Wichmann + Masanori Ogino + Michael Clark + Michael Forney + Mikhail Kremnyov + Natanael Copa + Nicholas J. 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Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE + FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL + DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR + SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER + CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, + OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.A. HISTORY OF THE SOFTWARE + ========================== + + Python was created in the early 1990s by Guido van Rossum at Stichting + Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands + as a successor of a language called ABC. Guido remains Python's + principal author, although it includes many contributions from others. + + In 1995, Guido continued his work on Python at the Corporation for + National Research Initiatives (CNRI, see https://www.cnri.reston.va.us) + in Reston, Virginia where he released several versions of the + software. + + In May 2000, Guido and the Python core development team moved to + BeOpen.com to form the BeOpen PythonLabs team. In October of the same + year, the PythonLabs team moved to Digital Creations, which became + Zope Corporation. In 2001, the Python Software Foundation (PSF, see + https://www.python.org/psf/) was formed, a non-profit organization + created specifically to own Python-related Intellectual Property. + Zope Corporation was a sponsoring member of the PSF. + + All Python releases are Open Source (see https://opensource.org for + the Open Source Definition). Historically, most, but not all, Python + releases have also been GPL-compatible; the table below summarizes + the various releases. + + Release Derived Year Owner GPL- + from compatible? (1) + + 0.9.0 thru 1.2 1991-1995 CWI yes + 1.3 thru 1.5.2 1.2 1995-1999 CNRI yes + 1.6 1.5.2 2000 CNRI no + 2.0 1.6 2000 BeOpen.com no + 1.6.1 1.6 2001 CNRI yes (2) + 2.1 2.0+1.6.1 2001 PSF no + 2.0.1 2.0+1.6.1 2001 PSF yes + 2.1.1 2.1+2.0.1 2001 PSF yes + 2.1.2 2.1.1 2002 PSF yes + 2.1.3 2.1.2 2002 PSF yes + 2.2 and above 2.1.1 2001-now PSF yes + + Footnotes: + + (1) GPL-compatible doesn't mean that we're distributing Python under + the GPL. All Python licenses, unlike the GPL, let you distribute + a modified version without making your changes open source. The + GPL-compatible licenses make it possible to combine Python with + other software that is released under the GPL; the others don't. + + (2) According to Richard Stallman, 1.6.1 is not GPL-compatible, + because its license has a choice of law clause. According to + CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1 + is "not incompatible" with the GPL. + + Thanks to the many outside volunteers who have worked under Guido's + direction to make these releases possible. + + + B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON + =============================================================== + + Python software and documentation are licensed under the + Python Software Foundation License Version 2. + + Starting with Python 3.8.6, examples, recipes, and other code in + the documentation are dual licensed under the PSF License Version 2 + and the Zero-Clause BSD license. + + Some software incorporated into Python is under different licenses. + The licenses are listed with code falling under that license. + + + PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2 + -------------------------------------------- + + 1. This LICENSE AGREEMENT is between the Python Software Foundation + ("PSF"), and the Individual or Organization ("Licensee") accessing and + otherwise using this software ("Python") in source or binary form and + its associated documentation. + + 2. Subject to the terms and conditions of this License Agreement, PSF hereby + grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce, + analyze, test, perform and/or display publicly, prepare derivative works, + distribute, and otherwise use Python alone or in any derivative version, + provided, however, that PSF's License Agreement and PSF's notice of copyright, + i.e., "Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, + 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 Python Software Foundation; + All Rights Reserved" are retained in Python alone or in any derivative version + prepared by Licensee. + + 3. In the event Licensee prepares a derivative work that is based on + or incorporates Python or any part thereof, and wants to make + the derivative work available to others as provided herein, then + Licensee hereby agrees to include in any such work a brief summary of + the changes made to Python. + + 4. 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This License Agreement does not grant permission to use PSF + trademarks or trade name in a trademark sense to endorse or promote + products or services of Licensee, or any third party. + + 8. By copying, installing or otherwise using Python, Licensee + agrees to be bound by the terms and conditions of this License + Agreement. + + + BEOPEN.COM LICENSE AGREEMENT FOR PYTHON 2.0 + ------------------------------------------- + + BEOPEN PYTHON OPEN SOURCE LICENSE AGREEMENT VERSION 1 + + 1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an + office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the + Individual or Organization ("Licensee") accessing and otherwise using + this software in source or binary form and its associated + documentation ("the Software"). + + 2. Subject to the terms and conditions of this BeOpen Python License + Agreement, BeOpen hereby grants Licensee a non-exclusive, + royalty-free, world-wide license to reproduce, analyze, test, perform + and/or display publicly, prepare derivative works, distribute, and + otherwise use the Software alone or in any derivative version, + provided, however, that the BeOpen Python License is retained in the + Software, alone or in any derivative version prepared by Licensee. + + 3. BeOpen is making the Software available to Licensee on an "AS IS" + basis. BEOPEN MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR + IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, BEOPEN MAKES NO AND + DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS + FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF THE SOFTWARE WILL NOT + INFRINGE ANY THIRD PARTY RIGHTS. + + 4. 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This + Agreement may also be obtained from a proxy server on the internet + using the following URL: http://hdl.handle.net/1895.22/1013". + + 3. In the event Licensee prepares a derivative work that is based on + or incorporates Python 1.6.1 or any part thereof, and wants to make + the derivative work available to others as provided herein, then + Licensee hereby agrees to include in any such work a brief summary of + the changes made to Python 1.6.1. + + 4. CNRI is making Python 1.6.1 available to Licensee on an "AS IS" + basis. CNRI MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR + IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, CNRI MAKES NO AND + DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS + FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON 1.6.1 WILL NOT + INFRINGE ANY THIRD PARTY RIGHTS. + + 5. 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This License Agreement shall be governed by the federal + intellectual property law of the United States, including without + limitation the federal copyright law, and, to the extent such + U.S. federal law does not apply, by the law of the Commonwealth of + Virginia, excluding Virginia's conflict of law provisions. + Notwithstanding the foregoing, with regard to derivative works based + on Python 1.6.1 that incorporate non-separable material that was + previously distributed under the GNU General Public License (GPL), the + law of the Commonwealth of Virginia shall govern this License + Agreement only as to issues arising under or with respect to + Paragraphs 4, 5, and 7 of this License Agreement. Nothing in this + License Agreement shall be deemed to create any relationship of + agency, partnership, or joint venture between CNRI and Licensee. 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IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, + INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM + LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR + OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR + PERFORMANCE OF THIS SOFTWARE. + Copyright (c) 2014, Al Sweigart + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the name of the {organization} nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" + AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. 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BE LIABLE + FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND + ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ---- + + Portions of code from MODP_ASCII - Ascii transformations (upper/lower, etc) + https://github.com/client9/stringencoders + + Copyright 2005, 2006, 2007 + Nick Galbreath -- nickg [at] modp [dot] com + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + + Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + Neither the name of the modp.com nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. 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+
+
+ +----------------- + +# pandas: powerful Python data analysis toolkit + +| | | +| --- | --- | +| Testing | [![CI - Test](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml/badge.svg)](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml) [![Coverage](https://codecov.io/github/pandas-dev/pandas/coverage.svg?branch=main)](https://codecov.io/gh/pandas-dev/pandas) | +| Package | [![PyPI Latest Release](https://img.shields.io/pypi/v/pandas.svg)](https://pypi.org/project/pandas/) [![PyPI Downloads](https://img.shields.io/pypi/dm/pandas.svg?label=PyPI%20downloads)](https://pypi.org/project/pandas/) [![Conda Latest Release](https://anaconda.org/conda-forge/pandas/badges/version.svg)](https://anaconda.org/conda-forge/pandas) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/pandas.svg?label=Conda%20downloads)](https://anaconda.org/conda-forge/pandas) | +| Meta | [![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3509134.svg)](https://doi.org/10.5281/zenodo.3509134) [![License - BSD 3-Clause](https://img.shields.io/pypi/l/pandas.svg)](https://github.com/pandas-dev/pandas/blob/main/LICENSE) [![Slack](https://img.shields.io/badge/join_Slack-information-brightgreen.svg?logo=slack)](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) | + + +## What is it? + +**pandas** is a Python package that provides fast, flexible, and expressive data +structures designed to make working with "relational" or "labeled" data both +easy and intuitive. It aims to be the fundamental high-level building block for +doing practical, **real world** data analysis in Python. Additionally, it has +the broader goal of becoming **the most powerful and flexible open source data +analysis / manipulation tool available in any language**. It is already well on +its way towards this goal. + +## Table of Contents + +- [Main Features](#main-features) +- [Where to get it](#where-to-get-it) +- [Dependencies](#dependencies) +- [Installation from sources](#installation-from-sources) +- [License](#license) +- [Documentation](#documentation) +- [Background](#background) +- [Getting Help](#getting-help) +- [Discussion and Development](#discussion-and-development) +- [Contributing to pandas](#contributing-to-pandas) + +## Main Features +Here are just a few of the things that pandas does well: + + - Easy handling of [**missing data**][missing-data] (represented as + `NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data + - Size mutability: columns can be [**inserted and + deleted**][insertion-deletion] from DataFrame and higher dimensional + objects + - Automatic and explicit [**data alignment**][alignment]: objects can + be explicitly aligned to a set of labels, or the user can simply + ignore the labels and let `Series`, `DataFrame`, etc. automatically + align the data for you in computations + - Powerful, flexible [**group by**][groupby] functionality to perform + split-apply-combine operations on data sets, for both aggregating + and transforming data + - Make it [**easy to convert**][conversion] ragged, + differently-indexed data in other Python and NumPy data structures + into DataFrame objects + - Intelligent label-based [**slicing**][slicing], [**fancy + indexing**][fancy-indexing], and [**subsetting**][subsetting] of + large data sets + - Intuitive [**merging**][merging] and [**joining**][joining] data + sets + - Flexible [**reshaping**][reshape] and [**pivoting**][pivot-table] of + data sets + - [**Hierarchical**][mi] labeling of axes (possible to have multiple + labels per tick) + - Robust IO tools for loading data from [**flat files**][flat-files] + (CSV and delimited), [**Excel files**][excel], [**databases**][db], + and saving/loading data from the ultrafast [**HDF5 format**][hdfstore] + - [**Time series**][timeseries]-specific functionality: date range + generation and frequency conversion, moving window statistics, + date shifting and lagging + + + [missing-data]: https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html + [insertion-deletion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#column-selection-addition-deletion + [alignment]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html?highlight=alignment#intro-to-data-structures + [groupby]: https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#group-by-split-apply-combine + [conversion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#dataframe + [slicing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#slicing-ranges + [fancy-indexing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#advanced + [subsetting]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#boolean-indexing + [merging]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#database-style-dataframe-or-named-series-joining-merging + [joining]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-on-index + [reshape]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html + [pivot-table]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html + [mi]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#hierarchical-indexing-multiindex + [flat-files]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#csv-text-files + [excel]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#excel-files + [db]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#sql-queries + [hdfstore]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#hdf5-pytables + [timeseries]: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#time-series-date-functionality + +## Where to get it +The source code is currently hosted on GitHub at: +https://github.com/pandas-dev/pandas + +Binary installers for the latest released version are available at the [Python +Package Index (PyPI)](https://pypi.org/project/pandas) and on [Conda](https://docs.conda.io/en/latest/). + +```sh +# conda +conda install -c conda-forge pandas +``` + +```sh +# or PyPI +pip install pandas +``` + +The list of changes to pandas between each release can be found +[here](https://pandas.pydata.org/pandas-docs/stable/whatsnew/index.html). For full +details, see the commit logs at https://github.com/pandas-dev/pandas. + +## Dependencies +- [NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays](https://www.numpy.org) +- [python-dateutil - Provides powerful extensions to the standard datetime module](https://dateutil.readthedocs.io/en/stable/index.html) +- [pytz - Brings the Olson tz database into Python which allows accurate and cross platform timezone calculations](https://github.com/stub42/pytz) + +See the [full installation instructions](https://pandas.pydata.org/pandas-docs/stable/install.html#dependencies) for minimum supported versions of required, recommended and optional dependencies. + +## Installation from sources +To install pandas from source you need [Cython](https://cython.org/) in addition to the normal +dependencies above. Cython can be installed from PyPI: + +```sh +pip install cython +``` + +In the `pandas` directory (same one where you found this file after +cloning the git repo), execute: + +```sh +pip install . +``` + +or for installing in [development mode](https://pip.pypa.io/en/latest/cli/pip_install/#install-editable): + + +```sh +python -m pip install -ve . --no-build-isolation --config-settings=editable-verbose=true +``` + +See the full instructions for [installing from source](https://pandas.pydata.org/docs/dev/development/contributing_environment.html). + +## License +[BSD 3](LICENSE) + +## Documentation +The official documentation is hosted on [PyData.org](https://pandas.pydata.org/pandas-docs/stable/). + +## Background +Work on ``pandas`` started at [AQR](https://www.aqr.com/) (a quantitative hedge fund) in 2008 and +has been under active development since then. + +## Getting Help + +For usage questions, the best place to go to is [StackOverflow](https://stackoverflow.com/questions/tagged/pandas). +Further, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata). + +## Discussion and Development +Most development discussions take place on GitHub in this repo, via the [GitHub issue tracker](https://github.com/pandas-dev/pandas/issues). + +Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions. + +There are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors. + +Additional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page. + +## Contributing to pandas + +[![Open Source Helpers](https://www.codetriage.com/pandas-dev/pandas/badges/users.svg)](https://www.codetriage.com/pandas-dev/pandas) + +All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. + +A detailed overview on how to contribute can be found in the **[contributing guide](https://pandas.pydata.org/docs/dev/development/contributing.html)**. + +If you are simply looking to start working with the pandas codebase, navigate to the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open) and [good first issue](https://github.com/pandas-dev/pandas/issues?labels=good+first+issue&sort=updated&state=open) where you could start out. + +You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas). + +Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’...you can do something about it! + +Feel free to ask questions on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Slack](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack). + +As contributors and maintainers to this project, you are expected to abide by pandas' code of conduct. More information can be found at: [Contributor Code of Conduct](https://github.com/pandas-dev/.github/blob/master/CODE_OF_CONDUCT.md) + +
+ +[Go to Top](#table-of-contents) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/RECORD b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..4e9abf5132c64b421018b3884c1c2b43f584a7e7 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/RECORD @@ -0,0 +1,2929 @@ +pandas-2.3.3.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4 +pandas-2.3.3.dist-info/LICENSE,sha256=HeougO0cvQIz-EzuRIaylonxM7q6zPTSleUcQwUfMhY,62399 +pandas-2.3.3.dist-info/METADATA,sha256=QO6VPcfKFVhAtjmhiB_4RXgHUYf84Kwg7tpVp_oNmpA,91215 +pandas-2.3.3.dist-info/RECORD,, +pandas-2.3.3.dist-info/WHEEL,sha256=ckDH29o6RFuym59_UCOyQWj3go-q-1WckgWoE0uBkag,138 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b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/entry_points.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1b523d70758fbd0080e21ca4c7ce6d9c9d9bd5 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas-2.3.3.dist-info/entry_points.txt @@ -0,0 +1,3 @@ +[pandas_plotting_backends] +matplotlib = pandas:plotting._matplotlib + diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_isin.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_isin.py new file mode 100644 index 0000000000000000000000000000000000000000..f94f67b8cc40a2031cab0791ccaf2fbc207b5023 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_isin.py @@ -0,0 +1,252 @@ +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + Series, + date_range, +) +import pandas._testing as tm +from pandas.core import algorithms +from pandas.core.arrays import PeriodArray + + +class TestSeriesIsIn: + def test_isin(self): + s = Series(["A", "B", "C", "a", "B", "B", "A", "C"]) + + result = s.isin(["A", "C"]) + expected = Series([True, False, True, False, False, False, True, True]) + tm.assert_series_equal(result, expected) + + # GH#16012 + # This specific issue has to have a series over 1e6 in len, but the + # comparison array (in_list) must be large enough so that numpy doesn't + # do a manual masking trick that will avoid this issue altogether + s = Series(list("abcdefghijk" * 10**5)) + # If numpy doesn't do the manual comparison/mask, these + # unorderable mixed types are what cause the exception in numpy + in_list = [-1, "a", "b", "G", "Y", "Z", "E", "K", "E", "S", "I", "R", "R"] * 6 + + assert s.isin(in_list).sum() == 200000 + + def test_isin_with_string_scalar(self): + # GH#4763 + s = Series(["A", "B", "C", "a", "B", "B", "A", "C"]) + msg = ( + r"only list-like objects are allowed to be passed to isin\(\), " + r"you passed a `str`" + ) + with pytest.raises(TypeError, match=msg): + s.isin("a") + + s = Series(["aaa", "b", "c"]) + with pytest.raises(TypeError, match=msg): + s.isin("aaa") + + def test_isin_datetimelike_mismatched_reso(self): + expected = Series([True, True, False, False, False]) + + ser = Series(date_range("jan-01-2013", "jan-05-2013")) + + # fails on dtype conversion in the first place + day_values = np.asarray(ser[0:2].values).astype("datetime64[D]") + result = ser.isin(day_values) + tm.assert_series_equal(result, expected) + + dta = ser[:2]._values.astype("M8[s]") + result = ser.isin(dta) + tm.assert_series_equal(result, expected) + + def test_isin_datetimelike_mismatched_reso_list(self): + expected = Series([True, True, False, False, False]) + + ser = Series(date_range("jan-01-2013", "jan-05-2013")) + + dta = ser[:2]._values.astype("M8[s]") + result = ser.isin(list(dta)) + tm.assert_series_equal(result, expected) + + def test_isin_with_i8(self): + # GH#5021 + + expected = Series([True, True, False, False, False]) + expected2 = Series([False, True, False, False, False]) + + # datetime64[ns] + s = Series(date_range("jan-01-2013", "jan-05-2013")) + + result = s.isin(s[0:2]) + tm.assert_series_equal(result, expected) + + result = s.isin(s[0:2].values) + tm.assert_series_equal(result, expected) + + result = s.isin([s[1]]) + tm.assert_series_equal(result, expected2) + + result = s.isin([np.datetime64(s[1])]) + tm.assert_series_equal(result, expected2) + + result = s.isin(set(s[0:2])) + tm.assert_series_equal(result, expected) + + # timedelta64[ns] + s = Series(pd.to_timedelta(range(5), unit="d")) + result = s.isin(s[0:2]) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("empty", [[], Series(dtype=object), np.array([])]) + def test_isin_empty(self, empty): + # see GH#16991 + s = Series(["a", "b"]) + expected = Series([False, False]) + + result = s.isin(empty) + tm.assert_series_equal(expected, result) + + def test_isin_read_only(self): + # https://github.com/pandas-dev/pandas/issues/37174 + arr = np.array([1, 2, 3]) + arr.setflags(write=False) + s = Series([1, 2, 3]) + result = s.isin(arr) + expected = Series([True, True, True]) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("dtype", [object, None]) + def test_isin_dt64_values_vs_ints(self, dtype): + # GH#36621 dont cast integers to datetimes for isin + dti = date_range("2013-01-01", "2013-01-05") + ser = Series(dti) + + comps = np.asarray([1356998400000000000], dtype=dtype) + + res = dti.isin(comps) + expected = np.array([False] * len(dti), dtype=bool) + tm.assert_numpy_array_equal(res, expected) + + res = ser.isin(comps) + tm.assert_series_equal(res, Series(expected)) + + res = pd.core.algorithms.isin(ser, comps) + tm.assert_numpy_array_equal(res, expected) + + def test_isin_tzawareness_mismatch(self): + dti = date_range("2013-01-01", "2013-01-05") + ser = Series(dti) + + other = dti.tz_localize("UTC") + + res = dti.isin(other) + expected = np.array([False] * len(dti), dtype=bool) + tm.assert_numpy_array_equal(res, expected) + + res = ser.isin(other) + tm.assert_series_equal(res, Series(expected)) + + res = pd.core.algorithms.isin(ser, other) + tm.assert_numpy_array_equal(res, expected) + + def test_isin_period_freq_mismatch(self): + dti = date_range("2013-01-01", "2013-01-05") + pi = dti.to_period("M") + ser = Series(pi) + + # We construct another PeriodIndex with the same i8 values + # but different dtype + dtype = dti.to_period("Y").dtype + other = PeriodArray._simple_new(pi.asi8, dtype=dtype) + + res = pi.isin(other) + expected = np.array([False] * len(pi), dtype=bool) + tm.assert_numpy_array_equal(res, expected) + + res = ser.isin(other) + tm.assert_series_equal(res, Series(expected)) + + res = pd.core.algorithms.isin(ser, other) + tm.assert_numpy_array_equal(res, expected) + + @pytest.mark.parametrize("values", [[-9.0, 0.0], [-9, 0]]) + def test_isin_float_in_int_series(self, values): + # GH#19356 GH#21804 + ser = Series(values) + result = ser.isin([-9, -0.5]) + expected = Series([True, False]) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("dtype", ["boolean", "Int64", "Float64"]) + @pytest.mark.parametrize( + "data,values,expected", + [ + ([0, 1, 0], [1], [False, True, False]), + ([0, 1, 0], [1, pd.NA], [False, True, False]), + ([0, pd.NA, 0], [1, 0], [True, False, True]), + ([0, 1, pd.NA], [1, pd.NA], [False, True, True]), + ([0, 1, pd.NA], [1, np.nan], [False, True, False]), + ([0, pd.NA, pd.NA], [np.nan, pd.NaT, None], [False, False, False]), + ], + ) + def test_isin_masked_types(self, dtype, data, values, expected): + # GH#42405 + ser = Series(data, dtype=dtype) + + result = ser.isin(values) + expected = Series(expected, dtype="boolean") + + tm.assert_series_equal(result, expected) + + +def test_isin_large_series_mixed_dtypes_and_nan(monkeypatch): + # https://github.com/pandas-dev/pandas/issues/37094 + # combination of object dtype for the values + # and > _MINIMUM_COMP_ARR_LEN elements + min_isin_comp = 5 + ser = Series([1, 2, np.nan] * min_isin_comp) + with monkeypatch.context() as m: + m.setattr(algorithms, "_MINIMUM_COMP_ARR_LEN", min_isin_comp) + result = ser.isin({"foo", "bar"}) + expected = Series([False] * 3 * min_isin_comp) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "array,expected", + [ + ( + [0, 1j, 1j, 1, 1 + 1j, 1 + 2j, 1 + 1j], + Series([False, True, True, False, True, True, True], dtype=bool), + ) + ], +) +def test_isin_complex_numbers(array, expected): + # GH 17927 + result = Series(array).isin([1j, 1 + 1j, 1 + 2j]) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "data,is_in", + [([1, [2]], [1]), (["simple str", [{"values": 3}]], ["simple str"])], +) +def test_isin_filtering_with_mixed_object_types(data, is_in): + # GH 20883 + + ser = Series(data) + result = ser.isin(is_in) + expected = Series([True, False]) + + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("data", [[1, 2, 3], [1.0, 2.0, 3.0]]) +@pytest.mark.parametrize("isin", [[1, 2], [1.0, 2.0]]) +def test_isin_filtering_on_iterable(data, isin): + # GH 50234 + + ser = Series(data) + result = ser.isin(i for i in isin) + expected_result = Series([True, True, False]) + + tm.assert_series_equal(result, expected_result) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_isna.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_isna.py new file mode 100644 index 0000000000000000000000000000000000000000..7e324aa86a052246a074950082e272fee7e505e3 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_isna.py @@ -0,0 +1,35 @@ +""" +We also test Series.notna in this file. +""" +import numpy as np + +from pandas import ( + Period, + Series, +) +import pandas._testing as tm + + +class TestIsna: + def test_isna_period_dtype(self): + # GH#13737 + ser = Series([Period("2011-01", freq="M"), Period("NaT", freq="M")]) + + expected = Series([False, True]) + + result = ser.isna() + tm.assert_series_equal(result, expected) + + result = ser.notna() + tm.assert_series_equal(result, ~expected) + + def test_isna(self): + ser = Series([0, 5.4, 3, np.nan, -0.001]) + expected = Series([False, False, False, True, False]) + tm.assert_series_equal(ser.isna(), expected) + tm.assert_series_equal(ser.notna(), ~expected) + + ser = Series(["hi", "", np.nan]) + expected = Series([False, False, True]) + tm.assert_series_equal(ser.isna(), expected) + tm.assert_series_equal(ser.notna(), ~expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_item.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_item.py new file mode 100644 index 0000000000000000000000000000000000000000..8e8c33619d564ef87d51416748b8fdc9058e5a41 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_item.py @@ -0,0 +1,59 @@ +""" +Series.item method, mainly testing that we get python scalars as opposed to +numpy scalars. +""" +import pytest + +from pandas import ( + Series, + Timedelta, + Timestamp, + date_range, +) + + +class TestItem: + def test_item(self): + # We are testing that we get python scalars as opposed to numpy scalars + ser = Series([1]) + result = ser.item() + assert result == 1 + assert result == ser.iloc[0] + assert isinstance(result, int) # i.e. not np.int64 + + ser = Series([0.5], index=[3]) + result = ser.item() + assert isinstance(result, float) + assert result == 0.5 + + ser = Series([1, 2]) + msg = "can only convert an array of size 1" + with pytest.raises(ValueError, match=msg): + ser.item() + + dti = date_range("2016-01-01", periods=2) + with pytest.raises(ValueError, match=msg): + dti.item() + with pytest.raises(ValueError, match=msg): + Series(dti).item() + + val = dti[:1].item() + assert isinstance(val, Timestamp) + val = Series(dti)[:1].item() + assert isinstance(val, Timestamp) + + tdi = dti - dti + with pytest.raises(ValueError, match=msg): + tdi.item() + with pytest.raises(ValueError, match=msg): + Series(tdi).item() + + val = tdi[:1].item() + assert isinstance(val, Timedelta) + val = Series(tdi)[:1].item() + assert isinstance(val, Timedelta) + + # Case where ser[0] would not work + ser = Series(dti, index=[5, 6]) + val = ser.iloc[:1].item() + assert val == dti[0] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_map.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_map.py new file mode 100644 index 0000000000000000000000000000000000000000..f33f5edb5ee66d93a2ec9d8135a81217853970b8 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_map.py @@ -0,0 +1,604 @@ +from collections import ( + Counter, + defaultdict, +) +from decimal import Decimal +import math + +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + bdate_range, + date_range, + isna, + timedelta_range, +) +import pandas._testing as tm + + +def test_series_map_box_timedelta(): + # GH#11349 + ser = Series(timedelta_range("1 day 1 s", periods=5, freq="h")) + + def f(x): + return x.total_seconds() + + ser.map(f) + + +def test_map_callable(datetime_series): + with np.errstate(all="ignore"): + tm.assert_series_equal(datetime_series.map(np.sqrt), np.sqrt(datetime_series)) + + # map function element-wise + tm.assert_series_equal(datetime_series.map(math.exp), np.exp(datetime_series)) + + # empty series + s = Series(dtype=object, name="foo", index=Index([], name="bar")) + rs = s.map(lambda x: x) + tm.assert_series_equal(s, rs) + + # check all metadata (GH 9322) + assert s is not rs + assert s.index is rs.index + assert s.dtype == rs.dtype + assert s.name == rs.name + + # index but no data + s = Series(index=[1, 2, 3], dtype=np.float64) + rs = s.map(lambda x: x) + tm.assert_series_equal(s, rs) + + +def test_map_same_length_inference_bug(): + s = Series([1, 2]) + + def f(x): + return (x, x + 1) + + s = Series([1, 2, 3]) + result = s.map(f) + expected = Series([(1, 2), (2, 3), (3, 4)]) + tm.assert_series_equal(result, expected) + + s = Series(["foo,bar"]) + result = s.map(lambda x: x.split(",")) + expected = Series([("foo", "bar")]) + tm.assert_series_equal(result, expected) + + +def test_series_map_box_timestamps(): + # GH#2689, GH#2627 + ser = Series(date_range("1/1/2000", periods=3)) + + def func(x): + return (x.hour, x.day, x.month) + + result = ser.map(func) + expected = Series([(0, 1, 1), (0, 2, 1), (0, 3, 1)]) + tm.assert_series_equal(result, expected) + + +def test_map_series_stringdtype(any_string_dtype, using_infer_string): + # map test on StringDType, GH#40823 + ser1 = Series( + data=["cat", "dog", "rabbit"], + index=["id1", "id2", "id3"], + dtype=any_string_dtype, + ) + ser2 = Series(["id3", "id2", "id1", "id7000"], dtype=any_string_dtype) + result = ser2.map(ser1) + + item = pd.NA + if ser2.dtype == object: + item = np.nan + + expected = Series(data=["rabbit", "dog", "cat", item], dtype=any_string_dtype) + if using_infer_string and any_string_dtype == "object": + expected = expected.astype("str") + + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "data, expected_dtype", + [(["1-1", "1-1", np.nan], "category"), (["1-1", "1-2", np.nan], "str")], +) +def test_map_categorical_with_nan_values(data, expected_dtype): + # GH 20714 bug fixed in: GH 24275 + def func(val): + return val.split("-")[0] + + s = Series(data, dtype="category") + + result = s.map(func, na_action="ignore") + expected = Series(["1", "1", np.nan], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_map_empty_integer_series(): + # GH52384 + s = Series([], dtype=int) + result = s.map(lambda x: x) + tm.assert_series_equal(result, s) + + +def test_map_empty_integer_series_with_datetime_index(): + # GH 21245 + s = Series([], index=date_range(start="2018-01-01", periods=0), dtype=int) + result = s.map(lambda x: x) + tm.assert_series_equal(result, s) + + +@pytest.mark.parametrize("func", [str, lambda x: str(x)]) +def test_map_simple_str_callables_same_as_astype( + string_series, func, using_infer_string +): + # test that we are evaluating row-by-row first + # before vectorized evaluation + result = string_series.map(func) + expected = string_series.astype(str if not using_infer_string else "str") + tm.assert_series_equal(result, expected) + + +def test_list_raises(string_series): + with pytest.raises(TypeError, match="'list' object is not callable"): + string_series.map([lambda x: x]) + + +def test_map(): + data = { + "A": [0.0, 1.0, 2.0, 3.0, 4.0], + "B": [0.0, 1.0, 0.0, 1.0, 0.0], + "C": ["foo1", "foo2", "foo3", "foo4", "foo5"], + "D": bdate_range("1/1/2009", periods=5), + } + + source = Series(data["B"], index=data["C"]) + target = Series(data["C"][:4], index=data["D"][:4]) + + merged = target.map(source) + + for k, v in merged.items(): + assert v == source[target[k]] + + # input could be a dict + merged = target.map(source.to_dict()) + + for k, v in merged.items(): + assert v == source[target[k]] + + +def test_map_datetime(datetime_series): + # function + result = datetime_series.map(lambda x: x * 2) + tm.assert_series_equal(result, datetime_series * 2) + + +def test_map_category(): + # GH 10324 + a = Series([1, 2, 3, 4]) + b = Series(["even", "odd", "even", "odd"], dtype="category") + c = Series(["even", "odd", "even", "odd"]) + + exp = Series(["odd", "even", "odd", np.nan], dtype="category") + tm.assert_series_equal(a.map(b), exp) + exp = Series(["odd", "even", "odd", np.nan]) + tm.assert_series_equal(a.map(c), exp) + + +def test_map_category_numeric(): + a = Series(["a", "b", "c", "d"]) + b = Series([1, 2, 3, 4], index=pd.CategoricalIndex(["b", "c", "d", "e"])) + c = Series([1, 2, 3, 4], index=Index(["b", "c", "d", "e"])) + + exp = Series([np.nan, 1, 2, 3]) + tm.assert_series_equal(a.map(b), exp) + exp = Series([np.nan, 1, 2, 3]) + tm.assert_series_equal(a.map(c), exp) + + +def test_map_category_string(): + a = Series(["a", "b", "c", "d"]) + b = Series( + ["B", "C", "D", "E"], + dtype="category", + index=pd.CategoricalIndex(["b", "c", "d", "e"]), + ) + c = Series(["B", "C", "D", "E"], index=Index(["b", "c", "d", "e"])) + + exp = Series( + pd.Categorical([np.nan, "B", "C", "D"], categories=["B", "C", "D", "E"]) + ) + tm.assert_series_equal(a.map(b), exp) + exp = Series([np.nan, "B", "C", "D"]) + tm.assert_series_equal(a.map(c), exp) + + +@pytest.mark.filterwarnings(r"ignore:Dtype inference:FutureWarning") +def test_map_empty(request, index): + if isinstance(index, MultiIndex): + request.applymarker( + pytest.mark.xfail( + reason="Initializing a Series from a MultiIndex is not supported" + ) + ) + + s = Series(index) + result = s.map({}) + + expected = Series(np.nan, index=s.index) + tm.assert_series_equal(result, expected) + + +def test_map_compat(): + # related GH 8024 + s = Series([True, True, False], index=[1, 2, 3]) + result = s.map({True: "foo", False: "bar"}) + expected = Series(["foo", "foo", "bar"], index=[1, 2, 3]) + tm.assert_series_equal(result, expected) + + +def test_map_int(): + left = Series({"a": 1.0, "b": 2.0, "c": 3.0, "d": 4}) + right = Series({1: 11, 2: 22, 3: 33}) + + assert left.dtype == np.float64 + assert issubclass(right.dtype.type, np.integer) + + merged = left.map(right) + assert merged.dtype == np.float64 + assert isna(merged["d"]) + assert not isna(merged["c"]) + + +def test_map_type_inference(): + s = Series(range(3)) + s2 = s.map(lambda x: np.where(x == 0, 0, 1)) + assert issubclass(s2.dtype.type, np.integer) + + +def test_map_decimal(string_series): + result = string_series.map(lambda x: Decimal(str(x))) + assert result.dtype == np.object_ + assert isinstance(result.iloc[0], Decimal) + + +def test_map_na_exclusion(): + s = Series([1.5, np.nan, 3, np.nan, 5]) + + result = s.map(lambda x: x * 2, na_action="ignore") + exp = s * 2 + tm.assert_series_equal(result, exp) + + +def test_map_dict_with_tuple_keys(): + """ + Due to new MultiIndex-ing behaviour in v0.14.0, + dicts with tuple keys passed to map were being + converted to a multi-index, preventing tuple values + from being mapped properly. + """ + # GH 18496 + df = DataFrame({"a": [(1,), (2,), (3, 4), (5, 6)]}) + label_mappings = {(1,): "A", (2,): "B", (3, 4): "A", (5, 6): "B"} + + df["labels"] = df["a"].map(label_mappings) + df["expected_labels"] = Series(["A", "B", "A", "B"], index=df.index) + # All labels should be filled now + tm.assert_series_equal(df["labels"], df["expected_labels"], check_names=False) + + +def test_map_counter(): + s = Series(["a", "b", "c"], index=[1, 2, 3]) + counter = Counter() + counter["b"] = 5 + counter["c"] += 1 + result = s.map(counter) + expected = Series([0, 5, 1], index=[1, 2, 3]) + tm.assert_series_equal(result, expected) + + +def test_map_defaultdict(): + s = Series([1, 2, 3], index=["a", "b", "c"]) + default_dict = defaultdict(lambda: "blank") + default_dict[1] = "stuff" + result = s.map(default_dict) + expected = Series(["stuff", "blank", "blank"], index=["a", "b", "c"]) + tm.assert_series_equal(result, expected) + + +def test_map_dict_na_key(): + # https://github.com/pandas-dev/pandas/issues/17648 + # Checks that np.nan key is appropriately mapped + s = Series([1, 2, np.nan]) + expected = Series(["a", "b", "c"]) + result = s.map({1: "a", 2: "b", np.nan: "c"}) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("na_action", [None, "ignore"]) +def test_map_defaultdict_na_key(na_action): + # GH 48813 + s = Series([1, 2, np.nan]) + default_map = defaultdict(lambda: "missing", {1: "a", 2: "b", np.nan: "c"}) + result = s.map(default_map, na_action=na_action) + expected = Series({0: "a", 1: "b", 2: "c" if na_action is None else np.nan}) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("na_action", [None, "ignore"]) +def test_map_defaultdict_missing_key(na_action): + # GH 48813 + s = Series([1, 2, np.nan]) + default_map = defaultdict(lambda: "missing", {1: "a", 2: "b", 3: "c"}) + result = s.map(default_map, na_action=na_action) + expected = Series({0: "a", 1: "b", 2: "missing" if na_action is None else np.nan}) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("na_action", [None, "ignore"]) +def test_map_defaultdict_unmutated(na_action): + # GH 48813 + s = Series([1, 2, np.nan]) + default_map = defaultdict(lambda: "missing", {1: "a", 2: "b", np.nan: "c"}) + expected_default_map = default_map.copy() + s.map(default_map, na_action=na_action) + assert default_map == expected_default_map + + +@pytest.mark.parametrize("arg_func", [dict, Series]) +def test_map_dict_ignore_na(arg_func): + # GH#47527 + mapping = arg_func({1: 10, np.nan: 42}) + ser = Series([1, np.nan, 2]) + result = ser.map(mapping, na_action="ignore") + expected = Series([10, np.nan, np.nan]) + tm.assert_series_equal(result, expected) + + +def test_map_defaultdict_ignore_na(): + # GH#47527 + mapping = defaultdict(int, {1: 10, np.nan: 42}) + ser = Series([1, np.nan, 2]) + result = ser.map(mapping) + expected = Series([10, 42, 0]) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "na_action, expected", + [(None, Series([10.0, 42.0, np.nan])), ("ignore", Series([10, np.nan, np.nan]))], +) +def test_map_categorical_na_ignore(na_action, expected): + # GH#47527 + values = pd.Categorical([1, np.nan, 2], categories=[10, 1, 2]) + ser = Series(values) + result = ser.map({1: 10, np.nan: 42}, na_action=na_action) + tm.assert_series_equal(result, expected) + + +def test_map_dict_subclass_with_missing(): + """ + Test Series.map with a dictionary subclass that defines __missing__, + i.e. sets a default value (GH #15999). + """ + + class DictWithMissing(dict): + def __missing__(self, key): + return "missing" + + s = Series([1, 2, 3]) + dictionary = DictWithMissing({3: "three"}) + result = s.map(dictionary) + expected = Series(["missing", "missing", "three"]) + tm.assert_series_equal(result, expected) + + +def test_map_dict_subclass_without_missing(): + class DictWithoutMissing(dict): + pass + + s = Series([1, 2, 3]) + dictionary = DictWithoutMissing({3: "three"}) + result = s.map(dictionary) + expected = Series([np.nan, np.nan, "three"]) + tm.assert_series_equal(result, expected) + + +def test_map_abc_mapping(non_dict_mapping_subclass): + # https://github.com/pandas-dev/pandas/issues/29733 + # Check collections.abc.Mapping support as mapper for Series.map + s = Series([1, 2, 3]) + not_a_dictionary = non_dict_mapping_subclass({3: "three"}) + result = s.map(not_a_dictionary) + expected = Series([np.nan, np.nan, "three"]) + tm.assert_series_equal(result, expected) + + +def test_map_abc_mapping_with_missing(non_dict_mapping_subclass): + # https://github.com/pandas-dev/pandas/issues/29733 + # Check collections.abc.Mapping support as mapper for Series.map + class NonDictMappingWithMissing(non_dict_mapping_subclass): + def __missing__(self, key): + return "missing" + + s = Series([1, 2, 3]) + not_a_dictionary = NonDictMappingWithMissing({3: "three"}) + result = s.map(not_a_dictionary) + # __missing__ is a dict concept, not a Mapping concept, + # so it should not change the result! + expected = Series([np.nan, np.nan, "three"]) + tm.assert_series_equal(result, expected) + + +def test_map_box_dt64(unit): + vals = [pd.Timestamp("2011-01-01"), pd.Timestamp("2011-01-02")] + ser = Series(vals).dt.as_unit(unit) + assert ser.dtype == f"datetime64[{unit}]" + # boxed value must be Timestamp instance + res = ser.map(lambda x: f"{type(x).__name__}_{x.day}_{x.tz}") + exp = Series(["Timestamp_1_None", "Timestamp_2_None"]) + tm.assert_series_equal(res, exp) + + +def test_map_box_dt64tz(unit): + vals = [ + pd.Timestamp("2011-01-01", tz="US/Eastern"), + pd.Timestamp("2011-01-02", tz="US/Eastern"), + ] + ser = Series(vals).dt.as_unit(unit) + assert ser.dtype == f"datetime64[{unit}, US/Eastern]" + res = ser.map(lambda x: f"{type(x).__name__}_{x.day}_{x.tz}") + exp = Series(["Timestamp_1_US/Eastern", "Timestamp_2_US/Eastern"]) + tm.assert_series_equal(res, exp) + + +def test_map_box_td64(unit): + # timedelta + vals = [pd.Timedelta("1 days"), pd.Timedelta("2 days")] + ser = Series(vals).dt.as_unit(unit) + assert ser.dtype == f"timedelta64[{unit}]" + res = ser.map(lambda x: f"{type(x).__name__}_{x.days}") + exp = Series(["Timedelta_1", "Timedelta_2"]) + tm.assert_series_equal(res, exp) + + +def test_map_box_period(): + # period + vals = [pd.Period("2011-01-01", freq="M"), pd.Period("2011-01-02", freq="M")] + ser = Series(vals) + assert ser.dtype == "Period[M]" + res = ser.map(lambda x: f"{type(x).__name__}_{x.freqstr}") + exp = Series(["Period_M", "Period_M"]) + tm.assert_series_equal(res, exp) + + +@pytest.mark.parametrize("na_action", [None, "ignore"]) +def test_map_categorical(na_action, using_infer_string): + values = pd.Categorical(list("ABBABCD"), categories=list("DCBA"), ordered=True) + s = Series(values, name="XX", index=list("abcdefg")) + + result = s.map(lambda x: x.lower(), na_action=na_action) + exp_values = pd.Categorical(list("abbabcd"), categories=list("dcba"), ordered=True) + exp = Series(exp_values, name="XX", index=list("abcdefg")) + tm.assert_series_equal(result, exp) + tm.assert_categorical_equal(result.values, exp_values) + + result = s.map(lambda x: "A", na_action=na_action) + exp = Series(["A"] * 7, name="XX", index=list("abcdefg")) + tm.assert_series_equal(result, exp) + assert result.dtype == object if not using_infer_string else "str" + + +@pytest.mark.parametrize( + "na_action, expected", + ( + [None, Series(["A", "B", "nan"], name="XX")], + [ + "ignore", + Series( + ["A", "B", np.nan], + name="XX", + dtype=pd.CategoricalDtype(list("DCBA"), True), + ), + ], + ), +) +def test_map_categorical_na_action(na_action, expected): + dtype = pd.CategoricalDtype(list("DCBA"), ordered=True) + values = pd.Categorical(list("AB") + [np.nan], dtype=dtype) + s = Series(values, name="XX") + result = s.map(str, na_action=na_action) + tm.assert_series_equal(result, expected) + + +def test_map_datetimetz(): + values = date_range("2011-01-01", "2011-01-02", freq="h").tz_localize("Asia/Tokyo") + s = Series(values, name="XX") + + # keep tz + result = s.map(lambda x: x + pd.offsets.Day()) + exp_values = date_range("2011-01-02", "2011-01-03", freq="h").tz_localize( + "Asia/Tokyo" + ) + exp = Series(exp_values, name="XX") + tm.assert_series_equal(result, exp) + + result = s.map(lambda x: x.hour) + exp = Series(list(range(24)) + [0], name="XX", dtype=np.int64) + tm.assert_series_equal(result, exp) + + # not vectorized + def f(x): + if not isinstance(x, pd.Timestamp): + raise ValueError + return str(x.tz) + + result = s.map(f) + exp = Series(["Asia/Tokyo"] * 25, name="XX") + tm.assert_series_equal(result, exp) + + +@pytest.mark.parametrize( + "vals,mapping,exp", + [ + (list("abc"), {np.nan: "not NaN"}, [np.nan] * 3 + ["not NaN"]), + (list("abc"), {"a": "a letter"}, ["a letter"] + [np.nan] * 3), + (list(range(3)), {0: 42}, [42] + [np.nan] * 3), + ], +) +def test_map_missing_mixed(vals, mapping, exp): + # GH20495 + s = Series(vals + [np.nan]) + result = s.map(mapping) + exp = Series(exp) + tm.assert_series_equal(result, exp) + + +def test_map_scalar_on_date_time_index_aware_series(): + # GH 25959 + # Calling map on a localized time series should not cause an error + series = Series( + np.arange(10, dtype=np.float64), + index=date_range("2020-01-01", periods=10, tz="UTC"), + name="ts", + ) + result = Series(series.index).map(lambda x: 1) + tm.assert_series_equal(result, Series(np.ones(len(series)), dtype="int64")) + + +def test_map_float_to_string_precision(): + # GH 13228 + ser = Series(1 / 3) + result = ser.map(lambda val: str(val)).to_dict() + expected = {0: "0.3333333333333333"} + assert result == expected + + +def test_map_to_timedelta(): + list_of_valid_strings = ["00:00:01", "00:00:02"] + a = pd.to_timedelta(list_of_valid_strings) + b = Series(list_of_valid_strings).map(pd.to_timedelta) + tm.assert_series_equal(Series(a), b) + + list_of_strings = ["00:00:01", np.nan, pd.NaT, pd.NaT] + + a = pd.to_timedelta(list_of_strings) + ser = Series(list_of_strings) + b = ser.map(pd.to_timedelta) + tm.assert_series_equal(Series(a), b) + + +def test_map_type(): + # GH 46719 + s = Series([3, "string", float], index=["a", "b", "c"]) + result = s.map(type) + expected = Series([int, str, type], index=["a", "b", "c"]) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_matmul.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_matmul.py new file mode 100644 index 0000000000000000000000000000000000000000..4ca3ad3f7031e20b8d6cec36caadbcefef8c4196 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_matmul.py @@ -0,0 +1,82 @@ +import operator + +import numpy as np +import pytest + +from pandas import ( + DataFrame, + Series, +) +import pandas._testing as tm + + +class TestMatmul: + def test_matmul(self): + # matmul test is for GH#10259 + a = Series( + np.random.default_rng(2).standard_normal(4), index=["p", "q", "r", "s"] + ) + b = DataFrame( + np.random.default_rng(2).standard_normal((3, 4)), + index=["1", "2", "3"], + columns=["p", "q", "r", "s"], + ).T + + # Series @ DataFrame -> Series + result = operator.matmul(a, b) + expected = Series(np.dot(a.values, b.values), index=["1", "2", "3"]) + tm.assert_series_equal(result, expected) + + # DataFrame @ Series -> Series + result = operator.matmul(b.T, a) + expected = Series(np.dot(b.T.values, a.T.values), index=["1", "2", "3"]) + tm.assert_series_equal(result, expected) + + # Series @ Series -> scalar + result = operator.matmul(a, a) + expected = np.dot(a.values, a.values) + tm.assert_almost_equal(result, expected) + + # GH#21530 + # vector (1D np.array) @ Series (__rmatmul__) + result = operator.matmul(a.values, a) + expected = np.dot(a.values, a.values) + tm.assert_almost_equal(result, expected) + + # GH#21530 + # vector (1D list) @ Series (__rmatmul__) + result = operator.matmul(a.values.tolist(), a) + expected = np.dot(a.values, a.values) + tm.assert_almost_equal(result, expected) + + # GH#21530 + # matrix (2D np.array) @ Series (__rmatmul__) + result = operator.matmul(b.T.values, a) + expected = np.dot(b.T.values, a.values) + tm.assert_almost_equal(result, expected) + + # GH#21530 + # matrix (2D nested lists) @ Series (__rmatmul__) + result = operator.matmul(b.T.values.tolist(), a) + expected = np.dot(b.T.values, a.values) + tm.assert_almost_equal(result, expected) + + # mixed dtype DataFrame @ Series + a["p"] = int(a.p) + result = operator.matmul(b.T, a) + expected = Series(np.dot(b.T.values, a.T.values), index=["1", "2", "3"]) + tm.assert_series_equal(result, expected) + + # different dtypes DataFrame @ Series + a = a.astype(int) + result = operator.matmul(b.T, a) + expected = Series(np.dot(b.T.values, a.T.values), index=["1", "2", "3"]) + tm.assert_series_equal(result, expected) + + msg = r"Dot product shape mismatch, \(4,\) vs \(3,\)" + # exception raised is of type Exception + with pytest.raises(Exception, match=msg): + a.dot(a.values[:3]) + msg = "matrices are not aligned" + with pytest.raises(ValueError, match=msg): + a.dot(b.T) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_nlargest.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_nlargest.py new file mode 100644 index 0000000000000000000000000000000000000000..e8de1cd89e3974f2dff0d775f35655b8caa02a08 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_nlargest.py @@ -0,0 +1,248 @@ +""" +Note: for naming purposes, most tests are title with as e.g. "test_nlargest_foo" +but are implicitly also testing nsmallest_foo. +""" +from itertools import product + +import numpy as np +import pytest + +import pandas as pd +from pandas import Series +import pandas._testing as tm + +main_dtypes = [ + "datetime", + "datetimetz", + "timedelta", + "int8", + "int16", + "int32", + "int64", + "float32", + "float64", + "uint8", + "uint16", + "uint32", + "uint64", +] + + +@pytest.fixture +def s_main_dtypes(): + """ + A DataFrame with many dtypes + + * datetime + * datetimetz + * timedelta + * [u]int{8,16,32,64} + * float{32,64} + + The columns are the name of the dtype. + """ + df = pd.DataFrame( + { + "datetime": pd.to_datetime(["2003", "2002", "2001", "2002", "2005"]), + "datetimetz": pd.to_datetime( + ["2003", "2002", "2001", "2002", "2005"] + ).tz_localize("US/Eastern"), + "timedelta": pd.to_timedelta(["3d", "2d", "1d", "2d", "5d"]), + } + ) + + for dtype in [ + "int8", + "int16", + "int32", + "int64", + "float32", + "float64", + "uint8", + "uint16", + "uint32", + "uint64", + ]: + df[dtype] = Series([3, 2, 1, 2, 5], dtype=dtype) + + return df + + +@pytest.fixture(params=main_dtypes) +def s_main_dtypes_split(request, s_main_dtypes): + """Each series in s_main_dtypes.""" + return s_main_dtypes[request.param] + + +def assert_check_nselect_boundary(vals, dtype, method): + # helper function for 'test_boundary_{dtype}' tests + ser = Series(vals, dtype=dtype) + result = getattr(ser, method)(3) + expected_idxr = [0, 1, 2] if method == "nsmallest" else [3, 2, 1] + expected = ser.loc[expected_idxr] + tm.assert_series_equal(result, expected) + + +class TestSeriesNLargestNSmallest: + @pytest.mark.parametrize( + "r", + [ + Series([3.0, 2, 1, 2, "5"], dtype="object"), + Series([3.0, 2, 1, 2, 5], dtype="object"), + # not supported on some archs + # Series([3., 2, 1, 2, 5], dtype='complex256'), + Series([3.0, 2, 1, 2, 5], dtype="complex128"), + Series(list("abcde")), + Series(list("abcde"), dtype="category"), + ], + ) + def test_nlargest_error(self, r): + dt = r.dtype + msg = f"Cannot use method 'n(largest|smallest)' with dtype {dt}" + args = 2, len(r), 0, -1 + methods = r.nlargest, r.nsmallest + for method, arg in product(methods, args): + with pytest.raises(TypeError, match=msg): + method(arg) + + def test_nsmallest_nlargest(self, s_main_dtypes_split): + # float, int, datetime64 (use i8), timedelts64 (same), + # object that are numbers, object that are strings + ser = s_main_dtypes_split + + tm.assert_series_equal(ser.nsmallest(2), ser.iloc[[2, 1]]) + tm.assert_series_equal(ser.nsmallest(2, keep="last"), ser.iloc[[2, 3]]) + + empty = ser.iloc[0:0] + tm.assert_series_equal(ser.nsmallest(0), empty) + tm.assert_series_equal(ser.nsmallest(-1), empty) + tm.assert_series_equal(ser.nlargest(0), empty) + tm.assert_series_equal(ser.nlargest(-1), empty) + + tm.assert_series_equal(ser.nsmallest(len(ser)), ser.sort_values()) + tm.assert_series_equal(ser.nsmallest(len(ser) + 1), ser.sort_values()) + tm.assert_series_equal(ser.nlargest(len(ser)), ser.iloc[[4, 0, 1, 3, 2]]) + tm.assert_series_equal(ser.nlargest(len(ser) + 1), ser.iloc[[4, 0, 1, 3, 2]]) + + def test_nlargest_misc(self): + ser = Series([3.0, np.nan, 1, 2, 5]) + result = ser.nlargest() + expected = ser.iloc[[4, 0, 3, 2, 1]] + tm.assert_series_equal(result, expected) + result = ser.nsmallest() + expected = ser.iloc[[2, 3, 0, 4, 1]] + tm.assert_series_equal(result, expected) + + msg = 'keep must be either "first", "last"' + with pytest.raises(ValueError, match=msg): + ser.nsmallest(keep="invalid") + with pytest.raises(ValueError, match=msg): + ser.nlargest(keep="invalid") + + # GH#15297 + ser = Series([1] * 5, index=[1, 2, 3, 4, 5]) + expected_first = Series([1] * 3, index=[1, 2, 3]) + expected_last = Series([1] * 3, index=[5, 4, 3]) + + result = ser.nsmallest(3) + tm.assert_series_equal(result, expected_first) + + result = ser.nsmallest(3, keep="last") + tm.assert_series_equal(result, expected_last) + + result = ser.nlargest(3) + tm.assert_series_equal(result, expected_first) + + result = ser.nlargest(3, keep="last") + tm.assert_series_equal(result, expected_last) + + @pytest.mark.parametrize("n", range(1, 5)) + def test_nlargest_n(self, n): + # GH 13412 + ser = Series([1, 4, 3, 2], index=[0, 0, 1, 1]) + result = ser.nlargest(n) + expected = ser.sort_values(ascending=False).head(n) + tm.assert_series_equal(result, expected) + + result = ser.nsmallest(n) + expected = ser.sort_values().head(n) + tm.assert_series_equal(result, expected) + + def test_nlargest_boundary_integer(self, nselect_method, any_int_numpy_dtype): + # GH#21426 + dtype_info = np.iinfo(any_int_numpy_dtype) + min_val, max_val = dtype_info.min, dtype_info.max + vals = [min_val, min_val + 1, max_val - 1, max_val] + assert_check_nselect_boundary(vals, any_int_numpy_dtype, nselect_method) + + def test_nlargest_boundary_float(self, nselect_method, float_numpy_dtype): + # GH#21426 + dtype_info = np.finfo(float_numpy_dtype) + min_val, max_val = dtype_info.min, dtype_info.max + min_2nd, max_2nd = np.nextafter([min_val, max_val], 0, dtype=float_numpy_dtype) + vals = [min_val, min_2nd, max_2nd, max_val] + assert_check_nselect_boundary(vals, float_numpy_dtype, nselect_method) + + @pytest.mark.parametrize("dtype", ["datetime64[ns]", "timedelta64[ns]"]) + def test_nlargest_boundary_datetimelike(self, nselect_method, dtype): + # GH#21426 + # use int64 bounds and +1 to min_val since true minimum is NaT + # (include min_val/NaT at end to maintain same expected_idxr) + dtype_info = np.iinfo("int64") + min_val, max_val = dtype_info.min, dtype_info.max + vals = [min_val + 1, min_val + 2, max_val - 1, max_val, min_val] + assert_check_nselect_boundary(vals, dtype, nselect_method) + + def test_nlargest_duplicate_keep_all_ties(self): + # see GH#16818 + ser = Series([10, 9, 8, 7, 7, 7, 7, 6]) + result = ser.nlargest(4, keep="all") + expected = Series([10, 9, 8, 7, 7, 7, 7]) + tm.assert_series_equal(result, expected) + + result = ser.nsmallest(2, keep="all") + expected = Series([6, 7, 7, 7, 7], index=[7, 3, 4, 5, 6]) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "data,expected", [([True, False], [True]), ([True, False, True, True], [True])] + ) + def test_nlargest_boolean(self, data, expected): + # GH#26154 : ensure True > False + ser = Series(data) + result = ser.nlargest(1) + expected = Series(expected) + tm.assert_series_equal(result, expected) + + def test_nlargest_nullable(self, any_numeric_ea_dtype): + # GH#42816 + dtype = any_numeric_ea_dtype + if dtype.startswith("UInt"): + # Can't cast from negative float to uint on some platforms + arr = np.random.default_rng(2).integers(1, 10, 10) + else: + arr = np.random.default_rng(2).standard_normal(10) + arr = arr.astype(dtype.lower(), copy=False) + + ser = Series(arr.copy(), dtype=dtype) + ser[1] = pd.NA + result = ser.nlargest(5) + + expected = ( + Series(np.delete(arr, 1), index=ser.index.delete(1)) + .nlargest(5) + .astype(dtype) + ) + tm.assert_series_equal(result, expected) + + def test_nsmallest_nan_when_keep_is_all(self): + # GH#46589 + s = Series([1, 2, 3, 3, 3, None]) + result = s.nsmallest(3, keep="all") + expected = Series([1.0, 2.0, 3.0, 3.0, 3.0]) + tm.assert_series_equal(result, expected) + + s = Series([1, 2, None, None, None]) + result = s.nsmallest(3, keep="all") + expected = Series([1, 2, None, None, None]) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_nunique.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_nunique.py new file mode 100644 index 0000000000000000000000000000000000000000..826132eb28162603d03635add59c3ea3da569256 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_nunique.py @@ -0,0 +1,24 @@ +import numpy as np + +from pandas import ( + Categorical, + Series, +) + + +def test_nunique(): + # basics.rst doc example + series = Series(np.random.default_rng(2).standard_normal(500)) + series[20:500] = np.nan + series[10:20] = 5000 + result = series.nunique() + assert result == 11 + + +def test_nunique_categorical(): + # GH#18051 + ser = Series(Categorical([])) + assert ser.nunique() == 0 + + ser = Series(Categorical([np.nan])) + assert ser.nunique() == 0 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_pct_change.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_pct_change.py new file mode 100644 index 0000000000000000000000000000000000000000..6c80e711c36846e565014c1d1c001ae2ba3cf929 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_pct_change.py @@ -0,0 +1,128 @@ +import numpy as np +import pytest + +from pandas import ( + Series, + date_range, +) +import pandas._testing as tm + + +class TestSeriesPctChange: + def test_pct_change(self, datetime_series): + msg = ( + "The 'fill_method' keyword being not None and the 'limit' keyword in " + "Series.pct_change are deprecated" + ) + + rs = datetime_series.pct_change(fill_method=None) + tm.assert_series_equal(rs, datetime_series / datetime_series.shift(1) - 1) + + rs = datetime_series.pct_change(2) + filled = datetime_series.ffill() + tm.assert_series_equal(rs, filled / filled.shift(2) - 1) + + with tm.assert_produces_warning(FutureWarning, match=msg): + rs = datetime_series.pct_change(fill_method="bfill", limit=1) + filled = datetime_series.bfill(limit=1) + tm.assert_series_equal(rs, filled / filled.shift(1) - 1) + + rs = datetime_series.pct_change(freq="5D") + filled = datetime_series.ffill() + tm.assert_series_equal( + rs, (filled / filled.shift(freq="5D") - 1).reindex_like(filled) + ) + + def test_pct_change_with_duplicate_axis(self): + # GH#28664 + common_idx = date_range("2019-11-14", periods=5, freq="D") + result = Series(range(5), common_idx).pct_change(freq="B") + + # the reason that the expected should be like this is documented at PR 28681 + expected = Series([np.nan, np.inf, np.nan, np.nan, 3.0], common_idx) + + tm.assert_series_equal(result, expected) + + def test_pct_change_shift_over_nas(self): + s = Series([1.0, 1.5, np.nan, 2.5, 3.0]) + + msg = "The default fill_method='pad' in Series.pct_change is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + chg = s.pct_change() + + expected = Series([np.nan, 0.5, 0.0, 2.5 / 1.5 - 1, 0.2]) + tm.assert_series_equal(chg, expected) + + @pytest.mark.parametrize( + "freq, periods, fill_method, limit", + [ + ("5B", 5, None, None), + ("3B", 3, None, None), + ("3B", 3, "bfill", None), + ("7B", 7, "pad", 1), + ("7B", 7, "bfill", 3), + ("14B", 14, None, None), + ], + ) + def test_pct_change_periods_freq( + self, freq, periods, fill_method, limit, datetime_series + ): + msg = ( + "The 'fill_method' keyword being not None and the 'limit' keyword in " + "Series.pct_change are deprecated" + ) + + # GH#7292 + with tm.assert_produces_warning(FutureWarning, match=msg): + rs_freq = datetime_series.pct_change( + freq=freq, fill_method=fill_method, limit=limit + ) + with tm.assert_produces_warning(FutureWarning, match=msg): + rs_periods = datetime_series.pct_change( + periods, fill_method=fill_method, limit=limit + ) + tm.assert_series_equal(rs_freq, rs_periods) + + empty_ts = Series(index=datetime_series.index, dtype=object) + with tm.assert_produces_warning(FutureWarning, match=msg): + rs_freq = empty_ts.pct_change( + freq=freq, fill_method=fill_method, limit=limit + ) + with tm.assert_produces_warning(FutureWarning, match=msg): + rs_periods = empty_ts.pct_change( + periods, fill_method=fill_method, limit=limit + ) + tm.assert_series_equal(rs_freq, rs_periods) + + +@pytest.mark.parametrize("fill_method", ["pad", "ffill", None]) +def test_pct_change_with_duplicated_indices(fill_method): + # GH30463 + s = Series([np.nan, 1, 2, 3, 9, 18], index=["a", "b"] * 3) + + warn = None if fill_method is None else FutureWarning + msg = ( + "The 'fill_method' keyword being not None and the 'limit' keyword in " + "Series.pct_change are deprecated" + ) + with tm.assert_produces_warning(warn, match=msg): + result = s.pct_change(fill_method=fill_method) + + expected = Series([np.nan, np.nan, 1.0, 0.5, 2.0, 1.0], index=["a", "b"] * 3) + tm.assert_series_equal(result, expected) + + +def test_pct_change_no_warning_na_beginning(): + # GH#54981 + ser = Series([None, None, 1, 2, 3]) + result = ser.pct_change() + expected = Series([np.nan, np.nan, np.nan, 1, 0.5]) + tm.assert_series_equal(result, expected) + + +def test_pct_change_empty(): + # GH 57056 + ser = Series([], dtype="float64") + expected = ser.copy() + result = ser.pct_change(periods=0) + tm.assert_series_equal(expected, result) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_pop.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_pop.py new file mode 100644 index 0000000000000000000000000000000000000000..7453f98ab3735e924dd7601622d23b4bafdd2176 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_pop.py @@ -0,0 +1,13 @@ +from pandas import Series +import pandas._testing as tm + + +def test_pop(): + # GH#6600 + ser = Series([0, 4, 0], index=["A", "B", "C"], name=4) + + result = ser.pop("B") + assert result == 4 + + expected = Series([0, 0], index=["A", "C"], name=4) + tm.assert_series_equal(ser, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_quantile.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_quantile.py new file mode 100644 index 0000000000000000000000000000000000000000..fa0563271d7df7cb6fdb3f2f7ad807057313f4c2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_quantile.py @@ -0,0 +1,247 @@ +import numpy as np +import pytest + +from pandas.core.dtypes.common import is_integer + +import pandas as pd +from pandas import ( + Index, + Series, +) +import pandas._testing as tm +from pandas.core.indexes.datetimes import Timestamp + + +class TestSeriesQuantile: + def test_quantile(self, datetime_series): + q = datetime_series.quantile(0.1) + assert q == np.percentile(datetime_series.dropna(), 10) + + q = datetime_series.quantile(0.9) + assert q == np.percentile(datetime_series.dropna(), 90) + + # object dtype + q = Series(datetime_series, dtype=object).quantile(0.9) + assert q == np.percentile(datetime_series.dropna(), 90) + + # datetime64[ns] dtype + dts = datetime_series.index.to_series() + q = dts.quantile(0.2) + assert q == Timestamp("2000-01-10 19:12:00") + + # timedelta64[ns] dtype + tds = dts.diff() + q = tds.quantile(0.25) + assert q == pd.to_timedelta("24:00:00") + + # GH7661 + result = Series([np.timedelta64("NaT")]).sum() + assert result == pd.Timedelta(0) + + msg = "percentiles should all be in the interval \\[0, 1\\]" + for invalid in [-1, 2, [0.5, -1], [0.5, 2]]: + with pytest.raises(ValueError, match=msg): + datetime_series.quantile(invalid) + + s = Series(np.random.default_rng(2).standard_normal(100)) + percentile_array = [-0.5, 0.25, 1.5] + with pytest.raises(ValueError, match=msg): + s.quantile(percentile_array) + + def test_quantile_multi(self, datetime_series, unit): + datetime_series.index = datetime_series.index.as_unit(unit) + qs = [0.1, 0.9] + result = datetime_series.quantile(qs) + expected = Series( + [ + np.percentile(datetime_series.dropna(), 10), + np.percentile(datetime_series.dropna(), 90), + ], + index=qs, + name=datetime_series.name, + ) + tm.assert_series_equal(result, expected) + + dts = datetime_series.index.to_series() + dts.name = "xxx" + result = dts.quantile((0.2, 0.2)) + expected = Series( + [Timestamp("2000-01-10 19:12:00"), Timestamp("2000-01-10 19:12:00")], + index=[0.2, 0.2], + name="xxx", + dtype=f"M8[{unit}]", + ) + tm.assert_series_equal(result, expected) + + result = datetime_series.quantile([]) + expected = Series( + [], name=datetime_series.name, index=Index([], dtype=float), dtype="float64" + ) + tm.assert_series_equal(result, expected) + + def test_quantile_interpolation(self, datetime_series): + # see gh-10174 + + # interpolation = linear (default case) + q = datetime_series.quantile(0.1, interpolation="linear") + assert q == np.percentile(datetime_series.dropna(), 10) + q1 = datetime_series.quantile(0.1) + assert q1 == np.percentile(datetime_series.dropna(), 10) + + # test with and without interpolation keyword + assert q == q1 + + def test_quantile_interpolation_dtype(self): + # GH #10174 + + # interpolation = linear (default case) + q = Series([1, 3, 4]).quantile(0.5, interpolation="lower") + assert q == np.percentile(np.array([1, 3, 4]), 50) + assert is_integer(q) + + q = Series([1, 3, 4]).quantile(0.5, interpolation="higher") + assert q == np.percentile(np.array([1, 3, 4]), 50) + assert is_integer(q) + + def test_quantile_nan(self): + # GH 13098 + ser = Series([1, 2, 3, 4, np.nan]) + result = ser.quantile(0.5) + expected = 2.5 + assert result == expected + + # all nan/empty + s1 = Series([], dtype=object) + cases = [s1, Series([np.nan, np.nan])] + + for ser in cases: + res = ser.quantile(0.5) + assert np.isnan(res) + + res = ser.quantile([0.5]) + tm.assert_series_equal(res, Series([np.nan], index=[0.5])) + + res = ser.quantile([0.2, 0.3]) + tm.assert_series_equal(res, Series([np.nan, np.nan], index=[0.2, 0.3])) + + @pytest.mark.parametrize( + "case", + [ + [ + Timestamp("2011-01-01"), + Timestamp("2011-01-02"), + Timestamp("2011-01-03"), + ], + [ + Timestamp("2011-01-01", tz="US/Eastern"), + Timestamp("2011-01-02", tz="US/Eastern"), + Timestamp("2011-01-03", tz="US/Eastern"), + ], + [pd.Timedelta("1 days"), pd.Timedelta("2 days"), pd.Timedelta("3 days")], + # NaT + [ + Timestamp("2011-01-01"), + Timestamp("2011-01-02"), + Timestamp("2011-01-03"), + pd.NaT, + ], + [ + Timestamp("2011-01-01", tz="US/Eastern"), + Timestamp("2011-01-02", tz="US/Eastern"), + Timestamp("2011-01-03", tz="US/Eastern"), + pd.NaT, + ], + [ + pd.Timedelta("1 days"), + pd.Timedelta("2 days"), + pd.Timedelta("3 days"), + pd.NaT, + ], + ], + ) + def test_quantile_box(self, case): + ser = Series(case, name="XXX") + res = ser.quantile(0.5) + assert res == case[1] + + res = ser.quantile([0.5]) + exp = Series([case[1]], index=[0.5], name="XXX") + tm.assert_series_equal(res, exp) + + def test_datetime_timedelta_quantiles(self): + # covers #9694 + assert pd.isna(Series([], dtype="M8[ns]").quantile(0.5)) + assert pd.isna(Series([], dtype="m8[ns]").quantile(0.5)) + + def test_quantile_nat(self): + res = Series([pd.NaT, pd.NaT]).quantile(0.5) + assert res is pd.NaT + + res = Series([pd.NaT, pd.NaT]).quantile([0.5]) + tm.assert_series_equal(res, Series([pd.NaT], index=[0.5])) + + @pytest.mark.parametrize( + "values, dtype", + [([0, 0, 0, 1, 2, 3], "Sparse[int]"), ([0.0, None, 1.0, 2.0], "Sparse[float]")], + ) + def test_quantile_sparse(self, values, dtype): + ser = Series(values, dtype=dtype) + result = ser.quantile([0.5]) + expected = Series(np.asarray(ser)).quantile([0.5]).astype("Sparse[float]") + tm.assert_series_equal(result, expected) + + def test_quantile_empty_float64(self): + # floats + ser = Series([], dtype="float64") + + res = ser.quantile(0.5) + assert np.isnan(res) + + res = ser.quantile([0.5]) + exp = Series([np.nan], index=[0.5]) + tm.assert_series_equal(res, exp) + + def test_quantile_empty_int64(self): + # int + ser = Series([], dtype="int64") + + res = ser.quantile(0.5) + assert np.isnan(res) + + res = ser.quantile([0.5]) + exp = Series([np.nan], index=[0.5]) + tm.assert_series_equal(res, exp) + + def test_quantile_empty_dt64(self): + # datetime + ser = Series([], dtype="datetime64[ns]") + + res = ser.quantile(0.5) + assert res is pd.NaT + + res = ser.quantile([0.5]) + exp = Series([pd.NaT], index=[0.5], dtype=ser.dtype) + tm.assert_series_equal(res, exp) + + @pytest.mark.parametrize("dtype", [int, float, "Int64"]) + def test_quantile_dtypes(self, dtype): + result = Series([1, 2, 3], dtype=dtype).quantile(np.arange(0, 1, 0.25)) + expected = Series(np.arange(1, 3, 0.5), index=np.arange(0, 1, 0.25)) + if dtype == "Int64": + expected = expected.astype("Float64") + tm.assert_series_equal(result, expected) + + def test_quantile_all_na(self, any_int_ea_dtype): + # GH#50681 + ser = Series([pd.NA, pd.NA], dtype=any_int_ea_dtype) + with tm.assert_produces_warning(None): + result = ser.quantile([0.1, 0.5]) + expected = Series([pd.NA, pd.NA], dtype=any_int_ea_dtype, index=[0.1, 0.5]) + tm.assert_series_equal(result, expected) + + def test_quantile_dtype_size(self, any_int_ea_dtype): + # GH#50681 + ser = Series([pd.NA, pd.NA, 1], dtype=any_int_ea_dtype) + result = ser.quantile([0.1, 0.5]) + expected = Series([1, 1], dtype=any_int_ea_dtype, index=[0.1, 0.5]) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rank.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rank.py new file mode 100644 index 0000000000000000000000000000000000000000..1c3ebe5653ce3d62f5cf7d13dc1be14f86a7de9a --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rank.py @@ -0,0 +1,563 @@ +from itertools import chain +import operator + +import numpy as np +import pytest + +from pandas._libs.algos import ( + Infinity, + NegInfinity, +) +import pandas.util._test_decorators as td + +from pandas import ( + NA, + NaT, + Series, + Timestamp, + date_range, +) +import pandas._testing as tm +from pandas.api.types import CategoricalDtype + + +@pytest.fixture +def ser(): + return Series([1, 3, 4, 2, np.nan, 2, 1, 5, np.nan, 3]) + + +@pytest.fixture( + params=[ + ["average", np.array([1.5, 5.5, 7.0, 3.5, np.nan, 3.5, 1.5, 8.0, np.nan, 5.5])], + ["min", np.array([1, 5, 7, 3, np.nan, 3, 1, 8, np.nan, 5])], + ["max", np.array([2, 6, 7, 4, np.nan, 4, 2, 8, np.nan, 6])], + ["first", np.array([1, 5, 7, 3, np.nan, 4, 2, 8, np.nan, 6])], + ["dense", np.array([1, 3, 4, 2, np.nan, 2, 1, 5, np.nan, 3])], + ], + ids=lambda x: x[0], +) +def results(request): + return request.param + + +@pytest.fixture( + params=[ + "object", + "float64", + "int64", + "Float64", + "Int64", + pytest.param("float64[pyarrow]", marks=td.skip_if_no("pyarrow")), + pytest.param("int64[pyarrow]", marks=td.skip_if_no("pyarrow")), + pytest.param("string[pyarrow]", marks=td.skip_if_no("pyarrow")), + "string[python]", + "str", + ] +) +def dtype(request): + return request.param + + +def expected_dtype(dtype, method, pct=False): + exp_dtype = "float64" + # elif dtype in ["Int64", "Float64", "string[pyarrow]", "string[python]"]: + if dtype in ["string[pyarrow]"]: + exp_dtype = "Float64" + elif dtype in ["float64[pyarrow]", "int64[pyarrow]"]: + if method == "average" or pct: + exp_dtype = "double[pyarrow]" + else: + exp_dtype = "uint64[pyarrow]" + + return exp_dtype + + +class TestSeriesRank: + def test_rank(self, datetime_series): + sp_stats = pytest.importorskip("scipy.stats") + + datetime_series[::2] = np.nan + datetime_series[:10:3] = 4.0 + + ranks = datetime_series.rank() + oranks = datetime_series.astype("O").rank() + + tm.assert_series_equal(ranks, oranks) + + mask = np.isnan(datetime_series) + filled = datetime_series.fillna(np.inf) + + # rankdata returns a ndarray + exp = Series(sp_stats.rankdata(filled), index=filled.index, name="ts") + exp[mask] = np.nan + + tm.assert_series_equal(ranks, exp) + + iseries = Series(np.arange(5).repeat(2)) + + iranks = iseries.rank() + exp = iseries.astype(float).rank() + tm.assert_series_equal(iranks, exp) + iseries = Series(np.arange(5)) + 1.0 + exp = iseries / 5.0 + iranks = iseries.rank(pct=True) + + tm.assert_series_equal(iranks, exp) + + iseries = Series(np.repeat(1, 100)) + exp = Series(np.repeat(0.505, 100)) + iranks = iseries.rank(pct=True) + tm.assert_series_equal(iranks, exp) + + # Explicit cast to float to avoid implicit cast when setting nan + iseries = iseries.astype("float") + iseries[1] = np.nan + exp = Series(np.repeat(50.0 / 99.0, 100)) + exp[1] = np.nan + iranks = iseries.rank(pct=True) + tm.assert_series_equal(iranks, exp) + + iseries = Series(np.arange(5)) + 1.0 + iseries[4] = np.nan + exp = iseries / 4.0 + iranks = iseries.rank(pct=True) + tm.assert_series_equal(iranks, exp) + + iseries = Series(np.repeat(np.nan, 100)) + exp = iseries.copy() + iranks = iseries.rank(pct=True) + tm.assert_series_equal(iranks, exp) + + # Explicit cast to float to avoid implicit cast when setting nan + iseries = Series(np.arange(5), dtype="float") + 1 + iseries[4] = np.nan + exp = iseries / 4.0 + iranks = iseries.rank(pct=True) + tm.assert_series_equal(iranks, exp) + + rng = date_range("1/1/1990", periods=5) + # Explicit cast to float to avoid implicit cast when setting nan + iseries = Series(np.arange(5), rng, dtype="float") + 1 + iseries.iloc[4] = np.nan + exp = iseries / 4.0 + iranks = iseries.rank(pct=True) + tm.assert_series_equal(iranks, exp) + + iseries = Series([1e-50, 1e-100, 1e-20, 1e-2, 1e-20 + 1e-30, 1e-1]) + exp = Series([2, 1, 3, 5, 4, 6.0]) + iranks = iseries.rank() + tm.assert_series_equal(iranks, exp) + + # GH 5968 + iseries = Series(["3 day", "1 day 10m", "-2 day", NaT], dtype="m8[ns]") + exp = Series([3, 2, 1, np.nan]) + iranks = iseries.rank() + tm.assert_series_equal(iranks, exp) + + values = np.array( + [-50, -1, -1e-20, -1e-25, -1e-50, 0, 1e-40, 1e-20, 1e-10, 2, 40], + dtype="float64", + ) + random_order = np.random.default_rng(2).permutation(len(values)) + iseries = Series(values[random_order]) + exp = Series(random_order + 1.0, dtype="float64") + iranks = iseries.rank() + tm.assert_series_equal(iranks, exp) + + def test_rank_categorical(self): + # GH issue #15420 rank incorrectly orders ordered categories + + # Test ascending/descending ranking for ordered categoricals + exp = Series([1.0, 2.0, 3.0, 4.0, 5.0, 6.0]) + exp_desc = Series([6.0, 5.0, 4.0, 3.0, 2.0, 1.0]) + ordered = Series( + ["first", "second", "third", "fourth", "fifth", "sixth"] + ).astype( + CategoricalDtype( + categories=["first", "second", "third", "fourth", "fifth", "sixth"], + ordered=True, + ) + ) + tm.assert_series_equal(ordered.rank(), exp) + tm.assert_series_equal(ordered.rank(ascending=False), exp_desc) + + # Unordered categoricals should be ranked as objects + unordered = Series( + ["first", "second", "third", "fourth", "fifth", "sixth"] + ).astype( + CategoricalDtype( + categories=["first", "second", "third", "fourth", "fifth", "sixth"], + ordered=False, + ) + ) + exp_unordered = Series([2.0, 4.0, 6.0, 3.0, 1.0, 5.0]) + res = unordered.rank() + tm.assert_series_equal(res, exp_unordered) + + unordered1 = Series([1, 2, 3, 4, 5, 6]).astype( + CategoricalDtype([1, 2, 3, 4, 5, 6], False) + ) + exp_unordered1 = Series([1.0, 2.0, 3.0, 4.0, 5.0, 6.0]) + res1 = unordered1.rank() + tm.assert_series_equal(res1, exp_unordered1) + + # Test na_option for rank data + na_ser = Series( + ["first", "second", "third", "fourth", "fifth", "sixth", np.nan] + ).astype( + CategoricalDtype( + ["first", "second", "third", "fourth", "fifth", "sixth", "seventh"], + True, + ) + ) + + exp_top = Series([2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 1.0]) + exp_bot = Series([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0]) + exp_keep = Series([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, np.nan]) + + tm.assert_series_equal(na_ser.rank(na_option="top"), exp_top) + tm.assert_series_equal(na_ser.rank(na_option="bottom"), exp_bot) + tm.assert_series_equal(na_ser.rank(na_option="keep"), exp_keep) + + # Test na_option for rank data with ascending False + exp_top = Series([7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0]) + exp_bot = Series([6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 7.0]) + exp_keep = Series([6.0, 5.0, 4.0, 3.0, 2.0, 1.0, np.nan]) + + tm.assert_series_equal(na_ser.rank(na_option="top", ascending=False), exp_top) + tm.assert_series_equal( + na_ser.rank(na_option="bottom", ascending=False), exp_bot + ) + tm.assert_series_equal(na_ser.rank(na_option="keep", ascending=False), exp_keep) + + # Test invalid values for na_option + msg = "na_option must be one of 'keep', 'top', or 'bottom'" + + with pytest.raises(ValueError, match=msg): + na_ser.rank(na_option="bad", ascending=False) + + # invalid type + with pytest.raises(ValueError, match=msg): + na_ser.rank(na_option=True, ascending=False) + + # Test with pct=True + na_ser = Series(["first", "second", "third", "fourth", np.nan]).astype( + CategoricalDtype(["first", "second", "third", "fourth"], True) + ) + exp_top = Series([0.4, 0.6, 0.8, 1.0, 0.2]) + exp_bot = Series([0.2, 0.4, 0.6, 0.8, 1.0]) + exp_keep = Series([0.25, 0.5, 0.75, 1.0, np.nan]) + + tm.assert_series_equal(na_ser.rank(na_option="top", pct=True), exp_top) + tm.assert_series_equal(na_ser.rank(na_option="bottom", pct=True), exp_bot) + tm.assert_series_equal(na_ser.rank(na_option="keep", pct=True), exp_keep) + + def test_rank_signature(self): + s = Series([0, 1]) + s.rank(method="average") + msg = "No axis named average for object type Series" + with pytest.raises(ValueError, match=msg): + s.rank("average") + + def test_rank_tie_methods(self, ser, results, dtype, using_infer_string): + method, exp = results + if ( + dtype == "int64" + or dtype == "Int64" + or (not using_infer_string and dtype == "str") + ): + pytest.skip("int64/str does not support NaN") + + ser = ser if dtype is None else ser.astype(dtype) + result = ser.rank(method=method) + tm.assert_series_equal(result, Series(exp, dtype=expected_dtype(dtype, method))) + + @pytest.mark.parametrize("ascending", [True, False]) + @pytest.mark.parametrize("method", ["average", "min", "max", "first", "dense"]) + @pytest.mark.parametrize("na_option", ["top", "bottom", "keep"]) + @pytest.mark.parametrize( + "dtype, na_value, pos_inf, neg_inf", + [ + ("object", None, Infinity(), NegInfinity()), + ("float64", np.nan, np.inf, -np.inf), + ("Float64", NA, np.inf, -np.inf), + pytest.param( + "float64[pyarrow]", + NA, + np.inf, + -np.inf, + marks=td.skip_if_no("pyarrow"), + ), + ], + ) + def test_rank_tie_methods_on_infs_nans( + self, method, na_option, ascending, dtype, na_value, pos_inf, neg_inf + ): + pytest.importorskip("scipy") + if dtype == "float64[pyarrow]": + if method == "average": + exp_dtype = "float64[pyarrow]" + else: + exp_dtype = "uint64[pyarrow]" + else: + exp_dtype = "float64" + + chunk = 3 + in_arr = [neg_inf] * chunk + [na_value] * chunk + [pos_inf] * chunk + iseries = Series(in_arr, dtype=dtype) + exp_ranks = { + "average": ([2, 2, 2], [5, 5, 5], [8, 8, 8]), + "min": ([1, 1, 1], [4, 4, 4], [7, 7, 7]), + "max": ([3, 3, 3], [6, 6, 6], [9, 9, 9]), + "first": ([1, 2, 3], [4, 5, 6], [7, 8, 9]), + "dense": ([1, 1, 1], [2, 2, 2], [3, 3, 3]), + } + ranks = exp_ranks[method] + if na_option == "top": + order = [ranks[1], ranks[0], ranks[2]] + elif na_option == "bottom": + order = [ranks[0], ranks[2], ranks[1]] + else: + order = [ranks[0], [np.nan] * chunk, ranks[1]] + expected = order if ascending else order[::-1] + expected = list(chain.from_iterable(expected)) + result = iseries.rank(method=method, na_option=na_option, ascending=ascending) + tm.assert_series_equal(result, Series(expected, dtype=exp_dtype)) + + def test_rank_desc_mix_nans_infs(self): + # GH 19538 + # check descending ranking when mix nans and infs + iseries = Series([1, np.nan, np.inf, -np.inf, 25]) + result = iseries.rank(ascending=False) + exp = Series([3, np.nan, 1, 4, 2], dtype="float64") + tm.assert_series_equal(result, exp) + + @pytest.mark.parametrize("method", ["average", "min", "max", "first", "dense"]) + @pytest.mark.parametrize( + "op, value", + [ + [operator.add, 0], + [operator.add, 1e6], + [operator.mul, 1e-6], + ], + ) + def test_rank_methods_series(self, method, op, value): + sp_stats = pytest.importorskip("scipy.stats") + + xs = np.random.default_rng(2).standard_normal(9) + xs = np.concatenate([xs[i:] for i in range(0, 9, 2)]) # add duplicates + np.random.default_rng(2).shuffle(xs) + + index = [chr(ord("a") + i) for i in range(len(xs))] + vals = op(xs, value) + ts = Series(vals, index=index) + result = ts.rank(method=method) + sprank = sp_stats.rankdata(vals, method if method != "first" else "ordinal") + expected = Series(sprank, index=index).astype("float64") + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "ser, exp", + [ + ([1], [1]), + ([2], [1]), + ([0], [1]), + ([2, 2], [1, 1]), + ([1, 2, 3], [1, 2, 3]), + ([4, 2, 1], [3, 2, 1]), + ([1, 1, 5, 5, 3], [1, 1, 3, 3, 2]), + ([-5, -4, -3, -2, -1], [1, 2, 3, 4, 5]), + ], + ) + def test_rank_dense_method(self, dtype, ser, exp): + if ser[0] < 0 and dtype.startswith("str"): + exp = exp[::-1] + s = Series(ser).astype(dtype) + result = s.rank(method="dense") + expected = Series(exp).astype(expected_dtype(dtype, "dense")) + tm.assert_series_equal(result, expected) + + def test_rank_descending(self, ser, results, dtype, using_infer_string): + method, _ = results + if dtype == "int64" or (not using_infer_string and dtype == "str"): + s = ser.dropna() + else: + s = ser.astype(dtype) + + res = s.rank(ascending=False) + if dtype.startswith("str"): + expected = (s.astype("float64").max() - s.astype("float64")).rank() + else: + expected = (s.max() - s).rank() + tm.assert_series_equal(res, expected.astype(expected_dtype(dtype, "average"))) + + if dtype.startswith("str"): + expected = (s.astype("float64").max() - s.astype("float64")).rank( + method=method + ) + else: + expected = (s.max() - s).rank(method=method) + res2 = s.rank(method=method, ascending=False) + tm.assert_series_equal(res2, expected.astype(expected_dtype(dtype, method))) + + def test_rank_int(self, ser, results): + method, exp = results + s = ser.dropna().astype("i8") + + result = s.rank(method=method) + expected = Series(exp).dropna() + expected.index = result.index + tm.assert_series_equal(result, expected) + + def test_rank_object_bug(self): + # GH 13445 + + # smoke tests + Series([np.nan] * 32).astype(object).rank(ascending=True) + Series([np.nan] * 32).astype(object).rank(ascending=False) + + def test_rank_modify_inplace(self): + # GH 18521 + # Check rank does not mutate series + s = Series([Timestamp("2017-01-05 10:20:27.569000"), NaT]) + expected = s.copy() + + s.rank() + result = s + tm.assert_series_equal(result, expected) + + def test_rank_ea_small_values(self): + # GH#52471 + ser = Series( + [5.4954145e29, -9.791984e-21, 9.3715776e-26, NA, 1.8790257e-28], + dtype="Float64", + ) + result = ser.rank(method="min") + expected = Series([4, 1, 3, np.nan, 2]) + tm.assert_series_equal(result, expected) + + +# GH15630, pct should be on 100% basis when method='dense' + + +@pytest.mark.parametrize( + "ser, exp", + [ + ([1], [1.0]), + ([1, 2], [1.0 / 2, 2.0 / 2]), + ([2, 2], [1.0, 1.0]), + ([1, 2, 3], [1.0 / 3, 2.0 / 3, 3.0 / 3]), + ([1, 2, 2], [1.0 / 2, 2.0 / 2, 2.0 / 2]), + ([4, 2, 1], [3.0 / 3, 2.0 / 3, 1.0 / 3]), + ([1, 1, 5, 5, 3], [1.0 / 3, 1.0 / 3, 3.0 / 3, 3.0 / 3, 2.0 / 3]), + ([1, 1, 3, 3, 5, 5], [1.0 / 3, 1.0 / 3, 2.0 / 3, 2.0 / 3, 3.0 / 3, 3.0 / 3]), + ([-5, -4, -3, -2, -1], [1.0 / 5, 2.0 / 5, 3.0 / 5, 4.0 / 5, 5.0 / 5]), + ], +) +def test_rank_dense_pct(dtype, ser, exp): + if ser[0] < 0 and dtype.startswith("str"): + exp = exp[::-1] + s = Series(ser).astype(dtype) + result = s.rank(method="dense", pct=True) + expected = Series(exp).astype(expected_dtype(dtype, "dense", pct=True)) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "ser, exp", + [ + ([1], [1.0]), + ([1, 2], [1.0 / 2, 2.0 / 2]), + ([2, 2], [1.0 / 2, 1.0 / 2]), + ([1, 2, 3], [1.0 / 3, 2.0 / 3, 3.0 / 3]), + ([1, 2, 2], [1.0 / 3, 2.0 / 3, 2.0 / 3]), + ([4, 2, 1], [3.0 / 3, 2.0 / 3, 1.0 / 3]), + ([1, 1, 5, 5, 3], [1.0 / 5, 1.0 / 5, 4.0 / 5, 4.0 / 5, 3.0 / 5]), + ([1, 1, 3, 3, 5, 5], [1.0 / 6, 1.0 / 6, 3.0 / 6, 3.0 / 6, 5.0 / 6, 5.0 / 6]), + ([-5, -4, -3, -2, -1], [1.0 / 5, 2.0 / 5, 3.0 / 5, 4.0 / 5, 5.0 / 5]), + ], +) +def test_rank_min_pct(dtype, ser, exp): + if ser[0] < 0 and dtype.startswith("str"): + exp = exp[::-1] + s = Series(ser).astype(dtype) + result = s.rank(method="min", pct=True) + expected = Series(exp).astype(expected_dtype(dtype, "min", pct=True)) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "ser, exp", + [ + ([1], [1.0]), + ([1, 2], [1.0 / 2, 2.0 / 2]), + ([2, 2], [1.0, 1.0]), + ([1, 2, 3], [1.0 / 3, 2.0 / 3, 3.0 / 3]), + ([1, 2, 2], [1.0 / 3, 3.0 / 3, 3.0 / 3]), + ([4, 2, 1], [3.0 / 3, 2.0 / 3, 1.0 / 3]), + ([1, 1, 5, 5, 3], [2.0 / 5, 2.0 / 5, 5.0 / 5, 5.0 / 5, 3.0 / 5]), + ([1, 1, 3, 3, 5, 5], [2.0 / 6, 2.0 / 6, 4.0 / 6, 4.0 / 6, 6.0 / 6, 6.0 / 6]), + ([-5, -4, -3, -2, -1], [1.0 / 5, 2.0 / 5, 3.0 / 5, 4.0 / 5, 5.0 / 5]), + ], +) +def test_rank_max_pct(dtype, ser, exp): + if ser[0] < 0 and dtype.startswith("str"): + exp = exp[::-1] + s = Series(ser).astype(dtype) + result = s.rank(method="max", pct=True) + expected = Series(exp).astype(expected_dtype(dtype, "max", pct=True)) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "ser, exp", + [ + ([1], [1.0]), + ([1, 2], [1.0 / 2, 2.0 / 2]), + ([2, 2], [1.5 / 2, 1.5 / 2]), + ([1, 2, 3], [1.0 / 3, 2.0 / 3, 3.0 / 3]), + ([1, 2, 2], [1.0 / 3, 2.5 / 3, 2.5 / 3]), + ([4, 2, 1], [3.0 / 3, 2.0 / 3, 1.0 / 3]), + ([1, 1, 5, 5, 3], [1.5 / 5, 1.5 / 5, 4.5 / 5, 4.5 / 5, 3.0 / 5]), + ([1, 1, 3, 3, 5, 5], [1.5 / 6, 1.5 / 6, 3.5 / 6, 3.5 / 6, 5.5 / 6, 5.5 / 6]), + ([-5, -4, -3, -2, -1], [1.0 / 5, 2.0 / 5, 3.0 / 5, 4.0 / 5, 5.0 / 5]), + ], +) +def test_rank_average_pct(dtype, ser, exp): + if ser[0] < 0 and dtype.startswith("str"): + exp = exp[::-1] + s = Series(ser).astype(dtype) + result = s.rank(method="average", pct=True) + expected = Series(exp).astype(expected_dtype(dtype, "average", pct=True)) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "ser, exp", + [ + ([1], [1.0]), + ([1, 2], [1.0 / 2, 2.0 / 2]), + ([2, 2], [1.0 / 2, 2.0 / 2.0]), + ([1, 2, 3], [1.0 / 3, 2.0 / 3, 3.0 / 3]), + ([1, 2, 2], [1.0 / 3, 2.0 / 3, 3.0 / 3]), + ([4, 2, 1], [3.0 / 3, 2.0 / 3, 1.0 / 3]), + ([1, 1, 5, 5, 3], [1.0 / 5, 2.0 / 5, 4.0 / 5, 5.0 / 5, 3.0 / 5]), + ([1, 1, 3, 3, 5, 5], [1.0 / 6, 2.0 / 6, 3.0 / 6, 4.0 / 6, 5.0 / 6, 6.0 / 6]), + ([-5, -4, -3, -2, -1], [1.0 / 5, 2.0 / 5, 3.0 / 5, 4.0 / 5, 5.0 / 5]), + ], +) +def test_rank_first_pct(dtype, ser, exp): + if ser[0] < 0 and dtype.startswith("str"): + exp = exp[::-1] + s = Series(ser).astype(dtype) + result = s.rank(method="first", pct=True) + expected = Series(exp).astype(expected_dtype(dtype, "first", pct=True)) + tm.assert_series_equal(result, expected) + + +@pytest.mark.single_cpu +def test_pct_max_many_rows(): + # GH 18271 + s = Series(np.arange(2**24 + 1)) + result = s.rank(pct=True).max() + assert result == 1 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reindex.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reindex.py new file mode 100644 index 0000000000000000000000000000000000000000..ecfbecf12bdd3aa07789a79e8ba9383a76f33ed5 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reindex.py @@ -0,0 +1,443 @@ +import numpy as np +import pytest + +import pandas.util._test_decorators as td + +from pandas import ( + NA, + Categorical, + Float64Dtype, + Index, + MultiIndex, + NaT, + Period, + PeriodIndex, + RangeIndex, + Series, + Timedelta, + Timestamp, + date_range, + isna, +) +import pandas._testing as tm + + +def test_reindex(datetime_series, string_series): + identity = string_series.reindex(string_series.index) + + assert tm.shares_memory(string_series.index, identity.index) + + assert identity.index.is_(string_series.index) + assert identity.index.identical(string_series.index) + + subIndex = string_series.index[10:20] + subSeries = string_series.reindex(subIndex) + + for idx, val in subSeries.items(): + assert val == string_series[idx] + + subIndex2 = datetime_series.index[10:20] + subTS = datetime_series.reindex(subIndex2) + + for idx, val in subTS.items(): + assert val == datetime_series[idx] + stuffSeries = datetime_series.reindex(subIndex) + + assert np.isnan(stuffSeries).all() + + # This is extremely important for the Cython code to not screw up + nonContigIndex = datetime_series.index[::2] + subNonContig = datetime_series.reindex(nonContigIndex) + for idx, val in subNonContig.items(): + assert val == datetime_series[idx] + + # return a copy the same index here + result = datetime_series.reindex() + assert result is not datetime_series + + +def test_reindex_nan(): + ts = Series([2, 3, 5, 7], index=[1, 4, np.nan, 8]) + + i, j = [np.nan, 1, np.nan, 8, 4, np.nan], [2, 0, 2, 3, 1, 2] + tm.assert_series_equal(ts.reindex(i), ts.iloc[j]) + + ts.index = ts.index.astype("object") + + # reindex coerces index.dtype to float, loc/iloc doesn't + tm.assert_series_equal(ts.reindex(i), ts.iloc[j], check_index_type=False) + + +def test_reindex_series_add_nat(): + rng = date_range("1/1/2000 00:00:00", periods=10, freq="10s") + series = Series(rng) + + result = series.reindex(range(15)) + assert np.issubdtype(result.dtype, np.dtype("M8[ns]")) + + mask = result.isna() + assert mask[-5:].all() + assert not mask[:-5].any() + + +def test_reindex_with_datetimes(): + rng = date_range("1/1/2000", periods=20) + ts = Series(np.random.default_rng(2).standard_normal(20), index=rng) + + result = ts.reindex(list(ts.index[5:10])) + expected = ts[5:10] + expected.index = expected.index._with_freq(None) + tm.assert_series_equal(result, expected) + + result = ts[list(ts.index[5:10])] + tm.assert_series_equal(result, expected) + + +def test_reindex_corner(datetime_series): + # (don't forget to fix this) I think it's fixed + empty = Series(index=[]) + empty.reindex(datetime_series.index, method="pad") # it works + + # corner case: pad empty series + reindexed = empty.reindex(datetime_series.index, method="pad") + + # pass non-Index + reindexed = datetime_series.reindex(list(datetime_series.index)) + datetime_series.index = datetime_series.index._with_freq(None) + tm.assert_series_equal(datetime_series, reindexed) + + # bad fill method + ts = datetime_series[::2] + msg = ( + r"Invalid fill method\. Expecting pad \(ffill\), backfill " + r"\(bfill\) or nearest\. Got foo" + ) + with pytest.raises(ValueError, match=msg): + ts.reindex(datetime_series.index, method="foo") + + +def test_reindex_pad(): + s = Series(np.arange(10), dtype="int64") + s2 = s[::2] + + reindexed = s2.reindex(s.index, method="pad") + reindexed2 = s2.reindex(s.index, method="ffill") + tm.assert_series_equal(reindexed, reindexed2) + + expected = Series([0, 0, 2, 2, 4, 4, 6, 6, 8, 8]) + tm.assert_series_equal(reindexed, expected) + + +def test_reindex_pad2(): + # GH4604 + s = Series([1, 2, 3, 4, 5], index=["a", "b", "c", "d", "e"]) + new_index = ["a", "g", "c", "f"] + expected = Series([1, 1, 3, 3], index=new_index) + + # this changes dtype because the ffill happens after + result = s.reindex(new_index).ffill() + tm.assert_series_equal(result, expected.astype("float64")) + + msg = "The 'downcast' keyword in ffill is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = s.reindex(new_index).ffill(downcast="infer") + tm.assert_series_equal(result, expected) + + expected = Series([1, 5, 3, 5], index=new_index) + result = s.reindex(new_index, method="ffill") + tm.assert_series_equal(result, expected) + + +def test_reindex_inference(): + # inference of new dtype + s = Series([True, False, False, True], index=list("abcd")) + new_index = "agc" + msg = "Downcasting object dtype arrays on" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = s.reindex(list(new_index)).ffill() + expected = Series([True, True, False], index=list(new_index)) + tm.assert_series_equal(result, expected) + + +def test_reindex_downcasting(): + # GH4618 shifted series downcasting + s = Series(False, index=range(5)) + msg = "Downcasting object dtype arrays on" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = s.shift(1).bfill() + expected = Series(False, index=range(5)) + tm.assert_series_equal(result, expected) + + +def test_reindex_nearest(): + s = Series(np.arange(10, dtype="int64")) + target = [0.1, 0.9, 1.5, 2.0] + result = s.reindex(target, method="nearest") + expected = Series(np.around(target).astype("int64"), target) + tm.assert_series_equal(expected, result) + + result = s.reindex(target, method="nearest", tolerance=0.2) + expected = Series([0, 1, np.nan, 2], target) + tm.assert_series_equal(expected, result) + + result = s.reindex(target, method="nearest", tolerance=[0.3, 0.01, 0.4, 3]) + expected = Series([0, np.nan, np.nan, 2], target) + tm.assert_series_equal(expected, result) + + +def test_reindex_int(datetime_series): + ts = datetime_series[::2] + int_ts = Series(np.zeros(len(ts), dtype=int), index=ts.index) + + # this should work fine + reindexed_int = int_ts.reindex(datetime_series.index) + + # if NaNs introduced + assert reindexed_int.dtype == np.float64 + + # NO NaNs introduced + reindexed_int = int_ts.reindex(int_ts.index[::2]) + assert reindexed_int.dtype == np.dtype(int) + + +def test_reindex_bool(datetime_series): + # A series other than float, int, string, or object + ts = datetime_series[::2] + bool_ts = Series(np.zeros(len(ts), dtype=bool), index=ts.index) + + # this should work fine + reindexed_bool = bool_ts.reindex(datetime_series.index) + + # if NaNs introduced + assert reindexed_bool.dtype == np.object_ + + # NO NaNs introduced + reindexed_bool = bool_ts.reindex(bool_ts.index[::2]) + assert reindexed_bool.dtype == np.bool_ + + +def test_reindex_bool_pad(datetime_series): + # fail + ts = datetime_series[5:] + bool_ts = Series(np.zeros(len(ts), dtype=bool), index=ts.index) + filled_bool = bool_ts.reindex(datetime_series.index, method="pad") + assert isna(filled_bool[:5]).all() + + +def test_reindex_categorical(): + index = date_range("20000101", periods=3) + + # reindexing to an invalid Categorical + s = Series(["a", "b", "c"], dtype="category") + result = s.reindex(index) + expected = Series( + Categorical(values=[np.nan, np.nan, np.nan], categories=["a", "b", "c"]) + ) + expected.index = index + tm.assert_series_equal(result, expected) + + # partial reindexing + expected = Series(Categorical(values=["b", "c"], categories=["a", "b", "c"])) + expected.index = [1, 2] + result = s.reindex([1, 2]) + tm.assert_series_equal(result, expected) + + expected = Series(Categorical(values=["c", np.nan], categories=["a", "b", "c"])) + expected.index = [2, 3] + result = s.reindex([2, 3]) + tm.assert_series_equal(result, expected) + + +def test_reindex_astype_order_consistency(): + # GH#17444 + ser = Series([1, 2, 3], index=[2, 0, 1]) + new_index = [0, 1, 2] + temp_dtype = "category" + new_dtype = str + result = ser.reindex(new_index).astype(temp_dtype).astype(new_dtype) + expected = ser.astype(temp_dtype).reindex(new_index).astype(new_dtype) + tm.assert_series_equal(result, expected) + + +def test_reindex_fill_value(): + # ----------------------------------------------------------- + # floats + floats = Series([1.0, 2.0, 3.0]) + result = floats.reindex([1, 2, 3]) + expected = Series([2.0, 3.0, np.nan], index=[1, 2, 3]) + tm.assert_series_equal(result, expected) + + result = floats.reindex([1, 2, 3], fill_value=0) + expected = Series([2.0, 3.0, 0], index=[1, 2, 3]) + tm.assert_series_equal(result, expected) + + # ----------------------------------------------------------- + # ints + ints = Series([1, 2, 3]) + + result = ints.reindex([1, 2, 3]) + expected = Series([2.0, 3.0, np.nan], index=[1, 2, 3]) + tm.assert_series_equal(result, expected) + + # don't upcast + result = ints.reindex([1, 2, 3], fill_value=0) + expected = Series([2, 3, 0], index=[1, 2, 3]) + assert issubclass(result.dtype.type, np.integer) + tm.assert_series_equal(result, expected) + + # ----------------------------------------------------------- + # objects + objects = Series([1, 2, 3], dtype=object) + + result = objects.reindex([1, 2, 3]) + expected = Series([2, 3, np.nan], index=[1, 2, 3], dtype=object) + tm.assert_series_equal(result, expected) + + result = objects.reindex([1, 2, 3], fill_value="foo") + expected = Series([2, 3, "foo"], index=[1, 2, 3], dtype=object) + tm.assert_series_equal(result, expected) + + # ------------------------------------------------------------ + # bools + bools = Series([True, False, True]) + + result = bools.reindex([1, 2, 3]) + expected = Series([False, True, np.nan], index=[1, 2, 3], dtype=object) + tm.assert_series_equal(result, expected) + + result = bools.reindex([1, 2, 3], fill_value=False) + expected = Series([False, True, False], index=[1, 2, 3]) + tm.assert_series_equal(result, expected) + + +@td.skip_array_manager_not_yet_implemented +@pytest.mark.parametrize("dtype", ["datetime64[ns]", "timedelta64[ns]"]) +@pytest.mark.parametrize("fill_value", ["string", 0, Timedelta(0)]) +def test_reindex_fill_value_datetimelike_upcast(dtype, fill_value, using_array_manager): + # https://github.com/pandas-dev/pandas/issues/42921 + if dtype == "timedelta64[ns]" and fill_value == Timedelta(0): + # use the scalar that is not compatible with the dtype for this test + fill_value = Timestamp(0) + + ser = Series([NaT], dtype=dtype) + + result = ser.reindex([0, 1], fill_value=fill_value) + expected = Series([NaT, fill_value], index=[0, 1], dtype=object) + tm.assert_series_equal(result, expected) + + +def test_reindex_datetimeindexes_tz_naive_and_aware(): + # GH 8306 + idx = date_range("20131101", tz="America/Chicago", periods=7) + newidx = date_range("20131103", periods=10, freq="h") + s = Series(range(7), index=idx) + msg = ( + r"Cannot compare dtypes datetime64\[ns, America/Chicago\] " + r"and datetime64\[ns\]" + ) + with pytest.raises(TypeError, match=msg): + s.reindex(newidx, method="ffill") + + +def test_reindex_empty_series_tz_dtype(): + # GH 20869 + result = Series(dtype="datetime64[ns, UTC]").reindex([0, 1]) + expected = Series([NaT] * 2, dtype="datetime64[ns, UTC]") + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "p_values, o_values, values, expected_values", + [ + ( + [Period("2019Q1", "Q-DEC"), Period("2019Q2", "Q-DEC")], + [Period("2019Q1", "Q-DEC"), Period("2019Q2", "Q-DEC"), "All"], + [1.0, 1.0], + [1.0, 1.0, np.nan], + ), + ( + [Period("2019Q1", "Q-DEC"), Period("2019Q2", "Q-DEC")], + [Period("2019Q1", "Q-DEC"), Period("2019Q2", "Q-DEC")], + [1.0, 1.0], + [1.0, 1.0], + ), + ], +) +def test_reindex_periodindex_with_object(p_values, o_values, values, expected_values): + # GH#28337 + period_index = PeriodIndex(p_values) + object_index = Index(o_values) + + ser = Series(values, index=period_index) + result = ser.reindex(object_index) + expected = Series(expected_values, index=object_index) + tm.assert_series_equal(result, expected) + + +def test_reindex_too_many_args(): + # GH 40980 + ser = Series([1, 2]) + msg = r"reindex\(\) takes from 1 to 2 positional arguments but 3 were given" + with pytest.raises(TypeError, match=msg): + ser.reindex([2, 3], False) + + +def test_reindex_double_index(): + # GH 40980 + ser = Series([1, 2]) + msg = r"reindex\(\) got multiple values for argument 'index'" + with pytest.raises(TypeError, match=msg): + ser.reindex([2, 3], index=[3, 4]) + + +def test_reindex_no_posargs(): + # GH 40980 + ser = Series([1, 2]) + result = ser.reindex(index=[1, 0]) + expected = Series([2, 1], index=[1, 0]) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("values", [[["a"], ["x"]], [[], []]]) +def test_reindex_empty_with_level(values): + # GH41170 + ser = Series( + range(len(values[0])), index=MultiIndex.from_arrays(values), dtype="object" + ) + result = ser.reindex(np.array(["b"]), level=0) + expected = Series( + index=MultiIndex(levels=[["b"], values[1]], codes=[[], []]), dtype="object" + ) + tm.assert_series_equal(result, expected) + + +def test_reindex_missing_category(): + # GH#18185 + ser = Series([1, 2, 3, 1], dtype="category") + msg = r"Cannot setitem on a Categorical with a new category \(-1\)" + with pytest.raises(TypeError, match=msg): + ser.reindex([1, 2, 3, 4, 5], fill_value=-1) + + +def test_reindexing_with_float64_NA_log(): + # GH 47055 + s = Series([1.0, NA], dtype=Float64Dtype()) + s_reindex = s.reindex(range(3)) + result = s_reindex.values._data + expected = np.array([1, np.nan, np.nan]) + tm.assert_numpy_array_equal(result, expected) + with tm.assert_produces_warning(None): + result_log = np.log(s_reindex) + expected_log = Series([0, np.nan, np.nan], dtype=Float64Dtype()) + tm.assert_series_equal(result_log, expected_log) + + +@pytest.mark.parametrize("dtype", ["timedelta64", "datetime64"]) +def test_reindex_expand_nonnano_nat(dtype): + # GH 53497 + ser = Series(np.array([1], dtype=f"{dtype}[s]")) + result = ser.reindex(RangeIndex(2)) + expected = Series( + np.array([1, getattr(np, dtype)("nat", "s")], dtype=f"{dtype}[s]") + ) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reindex_like.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reindex_like.py new file mode 100644 index 0000000000000000000000000000000000000000..7f24c778feb1b4556587773f711e21521efc537c --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reindex_like.py @@ -0,0 +1,41 @@ +from datetime import datetime + +import numpy as np + +from pandas import Series +import pandas._testing as tm + + +def test_reindex_like(datetime_series): + other = datetime_series[::2] + tm.assert_series_equal( + datetime_series.reindex(other.index), datetime_series.reindex_like(other) + ) + + # GH#7179 + day1 = datetime(2013, 3, 5) + day2 = datetime(2013, 5, 5) + day3 = datetime(2014, 3, 5) + + series1 = Series([5, None, None], [day1, day2, day3]) + series2 = Series([None, None], [day1, day3]) + + result = series1.reindex_like(series2, method="pad") + expected = Series([5, np.nan], index=[day1, day3]) + tm.assert_series_equal(result, expected) + + +def test_reindex_like_nearest(): + ser = Series(np.arange(10, dtype="int64")) + + target = [0.1, 0.9, 1.5, 2.0] + other = ser.reindex(target, method="nearest") + expected = Series(np.around(target).astype("int64"), target) + + result = ser.reindex_like(other, method="nearest") + tm.assert_series_equal(expected, result) + + result = ser.reindex_like(other, method="nearest", tolerance=1) + tm.assert_series_equal(expected, result) + result = ser.reindex_like(other, method="nearest", tolerance=[1, 2, 3, 4]) + tm.assert_series_equal(expected, result) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rename.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rename.py new file mode 100644 index 0000000000000000000000000000000000000000..a8f3862d39f07f332243a8e952d72a493ff44daa --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rename.py @@ -0,0 +1,184 @@ +from datetime import datetime +import re + +import numpy as np +import pytest + +from pandas import ( + Index, + MultiIndex, + Series, + array, +) +import pandas._testing as tm + + +class TestRename: + def test_rename(self, datetime_series): + ts = datetime_series + renamer = lambda x: x.strftime("%Y%m%d") + renamed = ts.rename(renamer) + assert renamed.index[0] == renamer(ts.index[0]) + + # dict + rename_dict = dict(zip(ts.index, renamed.index)) + renamed2 = ts.rename(rename_dict) + tm.assert_series_equal(renamed, renamed2) + + def test_rename_partial_dict(self): + # partial dict + ser = Series(np.arange(4), index=["a", "b", "c", "d"], dtype="int64") + renamed = ser.rename({"b": "foo", "d": "bar"}) + tm.assert_index_equal(renamed.index, Index(["a", "foo", "c", "bar"])) + + def test_rename_retain_index_name(self): + # index with name + renamer = Series( + np.arange(4), index=Index(["a", "b", "c", "d"], name="name"), dtype="int64" + ) + renamed = renamer.rename({}) + assert renamed.index.name == renamer.index.name + + def test_rename_by_series(self): + ser = Series(range(5), name="foo") + renamer = Series({1: 10, 2: 20}) + result = ser.rename(renamer) + expected = Series(range(5), index=[0, 10, 20, 3, 4], name="foo") + tm.assert_series_equal(result, expected) + + def test_rename_set_name(self, using_infer_string): + ser = Series(range(4), index=list("abcd")) + for name in ["foo", 123, 123.0, datetime(2001, 11, 11), ("foo",)]: + result = ser.rename(name) + assert result.name == name + if using_infer_string: + tm.assert_extension_array_equal(result.index.values, ser.index.values) + else: + tm.assert_numpy_array_equal(result.index.values, ser.index.values) + assert ser.name is None + + def test_rename_set_name_inplace(self, using_infer_string): + ser = Series(range(3), index=list("abc")) + for name in ["foo", 123, 123.0, datetime(2001, 11, 11), ("foo",)]: + ser.rename(name, inplace=True) + assert ser.name == name + exp = np.array(["a", "b", "c"], dtype=np.object_) + if using_infer_string: + exp = array(exp, dtype="str") + tm.assert_extension_array_equal(ser.index.values, exp) + else: + tm.assert_numpy_array_equal(ser.index.values, exp) + + def test_rename_axis_supported(self): + # Supporting axis for compatibility, detailed in GH-18589 + ser = Series(range(5)) + ser.rename({}, axis=0) + ser.rename({}, axis="index") + + with pytest.raises(ValueError, match="No axis named 5"): + ser.rename({}, axis=5) + + def test_rename_inplace(self, datetime_series): + renamer = lambda x: x.strftime("%Y%m%d") + expected = renamer(datetime_series.index[0]) + + datetime_series.rename(renamer, inplace=True) + assert datetime_series.index[0] == expected + + def test_rename_with_custom_indexer(self): + # GH 27814 + class MyIndexer: + pass + + ix = MyIndexer() + ser = Series([1, 2, 3]).rename(ix) + assert ser.name is ix + + def test_rename_with_custom_indexer_inplace(self): + # GH 27814 + class MyIndexer: + pass + + ix = MyIndexer() + ser = Series([1, 2, 3]) + ser.rename(ix, inplace=True) + assert ser.name is ix + + def test_rename_callable(self): + # GH 17407 + ser = Series(range(1, 6), index=Index(range(2, 7), name="IntIndex")) + result = ser.rename(str) + expected = ser.rename(lambda i: str(i)) + tm.assert_series_equal(result, expected) + + assert result.name == expected.name + + def test_rename_none(self): + # GH 40977 + ser = Series([1, 2], name="foo") + result = ser.rename(None) + expected = Series([1, 2]) + tm.assert_series_equal(result, expected) + + def test_rename_series_with_multiindex(self): + # issue #43659 + arrays = [ + ["bar", "baz", "baz", "foo", "qux"], + ["one", "one", "two", "two", "one"], + ] + + index = MultiIndex.from_arrays(arrays, names=["first", "second"]) + ser = Series(np.ones(5), index=index) + result = ser.rename(index={"one": "yes"}, level="second", errors="raise") + + arrays_expected = [ + ["bar", "baz", "baz", "foo", "qux"], + ["yes", "yes", "two", "two", "yes"], + ] + + index_expected = MultiIndex.from_arrays( + arrays_expected, names=["first", "second"] + ) + series_expected = Series(np.ones(5), index=index_expected) + + tm.assert_series_equal(result, series_expected) + + def test_rename_series_with_multiindex_keeps_ea_dtypes(self): + # GH21055 + arrays = [ + Index([1, 2, 3], dtype="Int64").astype("category"), + Index([1, 2, 3], dtype="Int64"), + ] + mi = MultiIndex.from_arrays(arrays, names=["A", "B"]) + ser = Series(1, index=mi) + result = ser.rename({1: 4}, level=1) + + arrays_expected = [ + Index([1, 2, 3], dtype="Int64").astype("category"), + Index([4, 2, 3], dtype="Int64"), + ] + mi_expected = MultiIndex.from_arrays(arrays_expected, names=["A", "B"]) + expected = Series(1, index=mi_expected) + + tm.assert_series_equal(result, expected) + + def test_rename_error_arg(self): + # GH 46889 + ser = Series(["foo", "bar"]) + match = re.escape("[2] not found in axis") + with pytest.raises(KeyError, match=match): + ser.rename({2: 9}, errors="raise") + + def test_rename_copy_false(self, using_copy_on_write, warn_copy_on_write): + # GH 46889 + ser = Series(["foo", "bar"]) + ser_orig = ser.copy() + shallow_copy = ser.rename({1: 9}, copy=False) + with tm.assert_cow_warning(warn_copy_on_write): + ser[0] = "foobar" + if using_copy_on_write: + assert ser_orig[0] == shallow_copy[0] + assert ser_orig[1] == shallow_copy[9] + else: + assert ser[0] == shallow_copy[0] + assert ser[1] == shallow_copy[9] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rename_axis.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rename_axis.py new file mode 100644 index 0000000000000000000000000000000000000000..58c095d697ede213be5c730e305bf1789810ac4a --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_rename_axis.py @@ -0,0 +1,47 @@ +import pytest + +from pandas import ( + Index, + MultiIndex, + Series, +) +import pandas._testing as tm + + +class TestSeriesRenameAxis: + def test_rename_axis_mapper(self): + # GH 19978 + mi = MultiIndex.from_product([["a", "b", "c"], [1, 2]], names=["ll", "nn"]) + ser = Series(list(range(len(mi))), index=mi) + + result = ser.rename_axis(index={"ll": "foo"}) + assert result.index.names == ["foo", "nn"] + + result = ser.rename_axis(index=str.upper, axis=0) + assert result.index.names == ["LL", "NN"] + + result = ser.rename_axis(index=["foo", "goo"]) + assert result.index.names == ["foo", "goo"] + + with pytest.raises(TypeError, match="unexpected"): + ser.rename_axis(columns="wrong") + + def test_rename_axis_inplace(self, datetime_series): + # GH 15704 + expected = datetime_series.rename_axis("foo") + result = datetime_series + no_return = result.rename_axis("foo", inplace=True) + + assert no_return is None + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("kwargs", [{"mapper": None}, {"index": None}, {}]) + def test_rename_axis_none(self, kwargs): + # GH 25034 + index = Index(list("abc"), name="foo") + ser = Series([1, 2, 3], index=index) + + result = ser.rename_axis(**kwargs) + expected_index = index.rename(None) if kwargs else index + expected = Series([1, 2, 3], index=expected_index) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_repeat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_repeat.py new file mode 100644 index 0000000000000000000000000000000000000000..8ecc8052ff49c150444cf395b68e6163fb761775 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_repeat.py @@ -0,0 +1,40 @@ +import numpy as np +import pytest + +from pandas import ( + MultiIndex, + Series, +) +import pandas._testing as tm + + +class TestRepeat: + def test_repeat(self): + ser = Series(np.random.default_rng(2).standard_normal(3), index=["a", "b", "c"]) + + reps = ser.repeat(5) + exp = Series(ser.values.repeat(5), index=ser.index.values.repeat(5)) + tm.assert_series_equal(reps, exp) + + to_rep = [2, 3, 4] + reps = ser.repeat(to_rep) + exp = Series(ser.values.repeat(to_rep), index=ser.index.values.repeat(to_rep)) + tm.assert_series_equal(reps, exp) + + def test_numpy_repeat(self): + ser = Series(np.arange(3), name="x") + expected = Series( + ser.values.repeat(2), name="x", index=ser.index.values.repeat(2) + ) + tm.assert_series_equal(np.repeat(ser, 2), expected) + + msg = "the 'axis' parameter is not supported" + with pytest.raises(ValueError, match=msg): + np.repeat(ser, 2, axis=0) + + def test_repeat_with_multiindex(self): + # GH#9361, fixed by GH#7891 + m_idx = MultiIndex.from_tuples([(1, 2), (3, 4), (5, 6), (7, 8)]) + data = ["a", "b", "c", "d"] + m_df = Series(data, index=m_idx) + assert m_df.repeat(3).shape == (3 * len(data),) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_replace.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_replace.py new file mode 100644 index 0000000000000000000000000000000000000000..53b95d685dc994e3afce152b9353255f587a26e2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_replace.py @@ -0,0 +1,819 @@ +import re + +import numpy as np +import pytest + +import pandas as pd +import pandas._testing as tm +from pandas.core.arrays import IntervalArray + + +class TestSeriesReplace: + def test_replace_explicit_none(self): + # GH#36984 if the user explicitly passes value=None, give it to them + ser = pd.Series([0, 0, ""], dtype=object) + result = ser.replace("", None) + expected = pd.Series([0, 0, None], dtype=object) + tm.assert_series_equal(result, expected) + + # Cast column 2 to object to avoid implicit cast when setting entry to "" + df = pd.DataFrame(np.zeros((3, 3))).astype({2: object}) + df.iloc[2, 2] = "" + result = df.replace("", None) + expected = pd.DataFrame( + { + 0: np.zeros(3), + 1: np.zeros(3), + 2: np.array([0.0, 0.0, None], dtype=object), + } + ) + assert expected.iloc[2, 2] is None + tm.assert_frame_equal(result, expected) + + # GH#19998 same thing with object dtype + ser = pd.Series([10, 20, 30, "a", "a", "b", "a"]) + result = ser.replace("a", None) + expected = pd.Series([10, 20, 30, None, None, "b", None]) + assert expected.iloc[-1] is None + tm.assert_series_equal(result, expected) + + def test_replace_noop_doesnt_downcast(self): + # GH#44498 + ser = pd.Series([None, None, pd.Timestamp("2021-12-16 17:31")], dtype=object) + res = ser.replace({np.nan: None}) # should be a no-op + tm.assert_series_equal(res, ser) + assert res.dtype == object + + # same thing but different calling convention + res = ser.replace(np.nan, None) + tm.assert_series_equal(res, ser) + assert res.dtype == object + + def test_replace(self): + N = 50 + ser = pd.Series(np.random.default_rng(2).standard_normal(N)) + ser[0:4] = np.nan + ser[6:10] = 0 + + # replace list with a single value + return_value = ser.replace([np.nan], -1, inplace=True) + assert return_value is None + + exp = ser.fillna(-1) + tm.assert_series_equal(ser, exp) + + rs = ser.replace(0.0, np.nan) + ser[ser == 0.0] = np.nan + tm.assert_series_equal(rs, ser) + + ser = pd.Series( + np.fabs(np.random.default_rng(2).standard_normal(N)), + pd.date_range("2020-01-01", periods=N), + dtype=object, + ) + ser[:5] = np.nan + ser[6:10] = "foo" + ser[20:30] = "bar" + + # replace list with a single value + msg = "Downcasting behavior in `replace`" + with tm.assert_produces_warning(FutureWarning, match=msg): + rs = ser.replace([np.nan, "foo", "bar"], -1) + + assert (rs[:5] == -1).all() + assert (rs[6:10] == -1).all() + assert (rs[20:30] == -1).all() + assert (pd.isna(ser[:5])).all() + + # replace with different values + with tm.assert_produces_warning(FutureWarning, match=msg): + rs = ser.replace({np.nan: -1, "foo": -2, "bar": -3}) + + assert (rs[:5] == -1).all() + assert (rs[6:10] == -2).all() + assert (rs[20:30] == -3).all() + assert (pd.isna(ser[:5])).all() + + # replace with different values with 2 lists + with tm.assert_produces_warning(FutureWarning, match=msg): + rs2 = ser.replace([np.nan, "foo", "bar"], [-1, -2, -3]) + tm.assert_series_equal(rs, rs2) + + # replace inplace + with tm.assert_produces_warning(FutureWarning, match=msg): + return_value = ser.replace([np.nan, "foo", "bar"], -1, inplace=True) + assert return_value is None + + assert (ser[:5] == -1).all() + assert (ser[6:10] == -1).all() + assert (ser[20:30] == -1).all() + + def test_replace_nan_with_inf(self): + ser = pd.Series([np.nan, 0, np.inf]) + tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) + + ser = pd.Series([np.nan, 0, "foo", "bar", np.inf, None, pd.NaT]) + tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) + filled = ser.copy() + filled[4] = 0 + tm.assert_series_equal(ser.replace(np.inf, 0), filled) + + def test_replace_listlike_value_listlike_target(self, datetime_series): + ser = pd.Series(datetime_series.index) + tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) + + # malformed + msg = r"Replacement lists must match in length\. Expecting 3 got 2" + with pytest.raises(ValueError, match=msg): + ser.replace([1, 2, 3], [np.nan, 0]) + + # ser is dt64 so can't hold 1 or 2, so this replace is a no-op + result = ser.replace([1, 2], [np.nan, 0]) + tm.assert_series_equal(result, ser) + + ser = pd.Series([0, 1, 2, 3, 4]) + result = ser.replace([0, 1, 2, 3, 4], [4, 3, 2, 1, 0]) + tm.assert_series_equal(result, pd.Series([4, 3, 2, 1, 0])) + + def test_replace_gh5319(self): + # API change from 0.12? + # GH 5319 + ser = pd.Series([0, np.nan, 2, 3, 4]) + expected = ser.ffill() + msg = ( + "Series.replace without 'value' and with non-dict-like " + "'to_replace' is deprecated" + ) + with tm.assert_produces_warning(FutureWarning, match=msg): + result = ser.replace([np.nan]) + tm.assert_series_equal(result, expected) + + ser = pd.Series([0, np.nan, 2, 3, 4]) + expected = ser.ffill() + with tm.assert_produces_warning(FutureWarning, match=msg): + result = ser.replace(np.nan) + tm.assert_series_equal(result, expected) + + def test_replace_datetime64(self): + # GH 5797 + ser = pd.Series(pd.date_range("20130101", periods=5)) + expected = ser.copy() + expected.loc[2] = pd.Timestamp("20120101") + result = ser.replace({pd.Timestamp("20130103"): pd.Timestamp("20120101")}) + tm.assert_series_equal(result, expected) + result = ser.replace(pd.Timestamp("20130103"), pd.Timestamp("20120101")) + tm.assert_series_equal(result, expected) + + def test_replace_nat_with_tz(self): + # GH 11792: Test with replacing NaT in a list with tz data + ts = pd.Timestamp("2015/01/01", tz="UTC") + s = pd.Series([pd.NaT, pd.Timestamp("2015/01/01", tz="UTC")]) + result = s.replace([np.nan, pd.NaT], pd.Timestamp.min) + expected = pd.Series([pd.Timestamp.min, ts], dtype=object) + tm.assert_series_equal(expected, result) + + def test_replace_timedelta_td64(self): + tdi = pd.timedelta_range(0, periods=5) + ser = pd.Series(tdi) + + # Using a single dict argument means we go through replace_list + result = ser.replace({ser[1]: ser[3]}) + + expected = pd.Series([ser[0], ser[3], ser[2], ser[3], ser[4]]) + tm.assert_series_equal(result, expected) + + def test_replace_with_single_list(self): + ser = pd.Series([0, 1, 2, 3, 4]) + msg2 = ( + "Series.replace without 'value' and with non-dict-like " + "'to_replace' is deprecated" + ) + with tm.assert_produces_warning(FutureWarning, match=msg2): + result = ser.replace([1, 2, 3]) + tm.assert_series_equal(result, pd.Series([0, 0, 0, 0, 4])) + + s = ser.copy() + with tm.assert_produces_warning(FutureWarning, match=msg2): + return_value = s.replace([1, 2, 3], inplace=True) + assert return_value is None + tm.assert_series_equal(s, pd.Series([0, 0, 0, 0, 4])) + + # make sure things don't get corrupted when fillna call fails + s = ser.copy() + msg = ( + r"Invalid fill method\. Expecting pad \(ffill\) or backfill " + r"\(bfill\)\. Got crash_cymbal" + ) + msg3 = "The 'method' keyword in Series.replace is deprecated" + with pytest.raises(ValueError, match=msg): + with tm.assert_produces_warning(FutureWarning, match=msg3): + return_value = s.replace([1, 2, 3], inplace=True, method="crash_cymbal") + assert return_value is None + tm.assert_series_equal(s, ser) + + def test_replace_mixed_types(self): + ser = pd.Series(np.arange(5), dtype="int64") + + def check_replace(to_rep, val, expected): + sc = ser.copy() + result = ser.replace(to_rep, val) + return_value = sc.replace(to_rep, val, inplace=True) + assert return_value is None + tm.assert_series_equal(expected, result) + tm.assert_series_equal(expected, sc) + + # 3.0 can still be held in our int64 series, so we do not upcast GH#44940 + tr, v = [3], [3.0] + check_replace(tr, v, ser) + # Note this matches what we get with the scalars 3 and 3.0 + check_replace(tr[0], v[0], ser) + + # MUST upcast to float + e = pd.Series([0, 1, 2, 3.5, 4]) + tr, v = [3], [3.5] + check_replace(tr, v, e) + + # casts to object + e = pd.Series([0, 1, 2, 3.5, "a"]) + tr, v = [3, 4], [3.5, "a"] + check_replace(tr, v, e) + + # again casts to object + e = pd.Series([0, 1, 2, 3.5, pd.Timestamp("20130101")]) + tr, v = [3, 4], [3.5, pd.Timestamp("20130101")] + check_replace(tr, v, e) + + # casts to object + e = pd.Series([0, 1, 2, 3.5, True], dtype="object") + tr, v = [3, 4], [3.5, True] + check_replace(tr, v, e) + + # test an object with dates + floats + integers + strings + dr = pd.Series(pd.date_range("1/1/2001", "1/10/2001", freq="D")) + result = dr.astype(object).replace([dr[0], dr[1], dr[2]], [1.0, 2, "a"]) + expected = pd.Series([1.0, 2, "a"] + dr[3:].tolist(), dtype=object) + tm.assert_series_equal(result, expected) + + def test_replace_bool_with_string_no_op(self): + s = pd.Series([True, False, True]) + result = s.replace("fun", "in-the-sun") + tm.assert_series_equal(s, result) + + def test_replace_bool_with_string(self): + # nonexistent elements + s = pd.Series([True, False, True]) + result = s.replace(True, "2u") + expected = pd.Series(["2u", False, "2u"]) + tm.assert_series_equal(expected, result) + + def test_replace_bool_with_bool(self): + s = pd.Series([True, False, True]) + result = s.replace(True, False) + expected = pd.Series([False] * len(s)) + tm.assert_series_equal(expected, result) + + def test_replace_with_dict_with_bool_keys(self): + s = pd.Series([True, False, True]) + result = s.replace({"asdf": "asdb", True: "yes"}) + expected = pd.Series(["yes", False, "yes"]) + tm.assert_series_equal(result, expected) + + def test_replace_Int_with_na(self, any_int_ea_dtype): + # GH 38267 + result = pd.Series([0, None], dtype=any_int_ea_dtype).replace(0, pd.NA) + expected = pd.Series([pd.NA, pd.NA], dtype=any_int_ea_dtype) + tm.assert_series_equal(result, expected) + result = pd.Series([0, 1], dtype=any_int_ea_dtype).replace(0, pd.NA) + result.replace(1, pd.NA, inplace=True) + tm.assert_series_equal(result, expected) + + def test_replace2(self): + N = 50 + ser = pd.Series( + np.fabs(np.random.default_rng(2).standard_normal(N)), + pd.date_range("2020-01-01", periods=N), + dtype=object, + ) + ser[:5] = np.nan + ser[6:10] = "foo" + ser[20:30] = "bar" + + # replace list with a single value + msg = "Downcasting behavior in `replace`" + with tm.assert_produces_warning(FutureWarning, match=msg): + rs = ser.replace([np.nan, "foo", "bar"], -1) + + assert (rs[:5] == -1).all() + assert (rs[6:10] == -1).all() + assert (rs[20:30] == -1).all() + assert (pd.isna(ser[:5])).all() + + # replace with different values + with tm.assert_produces_warning(FutureWarning, match=msg): + rs = ser.replace({np.nan: -1, "foo": -2, "bar": -3}) + + assert (rs[:5] == -1).all() + assert (rs[6:10] == -2).all() + assert (rs[20:30] == -3).all() + assert (pd.isna(ser[:5])).all() + + # replace with different values with 2 lists + with tm.assert_produces_warning(FutureWarning, match=msg): + rs2 = ser.replace([np.nan, "foo", "bar"], [-1, -2, -3]) + tm.assert_series_equal(rs, rs2) + + # replace inplace + with tm.assert_produces_warning(FutureWarning, match=msg): + return_value = ser.replace([np.nan, "foo", "bar"], -1, inplace=True) + assert return_value is None + assert (ser[:5] == -1).all() + assert (ser[6:10] == -1).all() + assert (ser[20:30] == -1).all() + + @pytest.mark.parametrize("inplace", [True, False]) + def test_replace_cascade(self, inplace): + # Test that replaced values are not replaced again + # GH #50778 + ser = pd.Series([1, 2, 3]) + expected = pd.Series([2, 3, 4]) + + res = ser.replace([1, 2, 3], [2, 3, 4], inplace=inplace) + if inplace: + tm.assert_series_equal(ser, expected) + else: + tm.assert_series_equal(res, expected) + + def test_replace_with_dictlike_and_string_dtype(self, nullable_string_dtype): + # GH 32621, GH#44940 + ser = pd.Series(["one", "two", np.nan], dtype=nullable_string_dtype) + expected = pd.Series(["1", "2", np.nan], dtype=nullable_string_dtype) + result = ser.replace({"one": "1", "two": "2"}) + tm.assert_series_equal(expected, result) + + def test_replace_with_empty_dictlike(self): + # GH 15289 + s = pd.Series(list("abcd")) + tm.assert_series_equal(s, s.replace({})) + + empty_series = pd.Series([]) + tm.assert_series_equal(s, s.replace(empty_series)) + + def test_replace_string_with_number(self): + # GH 15743 + s = pd.Series([1, 2, 3]) + result = s.replace("2", np.nan) + expected = pd.Series([1, 2, 3]) + tm.assert_series_equal(expected, result) + + def test_replace_replacer_equals_replacement(self): + # GH 20656 + # make sure all replacers are matching against original values + s = pd.Series(["a", "b"]) + expected = pd.Series(["b", "a"]) + result = s.replace({"a": "b", "b": "a"}) + tm.assert_series_equal(expected, result) + + def test_replace_unicode_with_number(self): + # GH 15743 + s = pd.Series([1, 2, 3]) + result = s.replace("2", np.nan) + expected = pd.Series([1, 2, 3]) + tm.assert_series_equal(expected, result) + + def test_replace_mixed_types_with_string(self): + # Testing mixed + s = pd.Series([1, 2, 3, "4", 4, 5]) + msg = "Downcasting behavior in `replace`" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = s.replace([2, "4"], np.nan) + expected = pd.Series([1, np.nan, 3, np.nan, 4, 5]) + tm.assert_series_equal(expected, result) + + @pytest.mark.parametrize( + "categorical, numeric", + [ + (pd.Categorical(["A"], categories=["A", "B"]), [1]), + (pd.Categorical(["A", "B"], categories=["A", "B"]), [1, 2]), + ], + ) + def test_replace_categorical(self, categorical, numeric, using_infer_string): + # GH 24971, GH#23305 + ser = pd.Series(categorical) + msg = "Downcasting behavior in `replace`" + msg = "with CategoricalDtype is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = ser.replace({"A": 1, "B": 2}) + expected = pd.Series(numeric).astype("category") + if 2 not in expected.cat.categories: + # i.e. categories should be [1, 2] even if there are no "B"s present + # GH#44940 + expected = expected.cat.add_categories(2) + tm.assert_series_equal(expected, result) + + @pytest.mark.parametrize( + "data, data_exp", [(["a", "b", "c"], ["b", "b", "c"]), (["a"], ["b"])] + ) + def test_replace_categorical_inplace(self, data, data_exp): + # GH 53358 + result = pd.Series(data, dtype="category") + msg = "with CategoricalDtype is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result.replace(to_replace="a", value="b", inplace=True) + expected = pd.Series(data_exp, dtype="category") + tm.assert_series_equal(result, expected) + + def test_replace_categorical_single(self): + # GH 26988 + dti = pd.date_range("2016-01-01", periods=3, tz="US/Pacific") + s = pd.Series(dti) + c = s.astype("category") + + expected = c.copy() + expected = expected.cat.add_categories("foo") + expected[2] = "foo" + expected = expected.cat.remove_unused_categories() + assert c[2] != "foo" + + msg = "with CategoricalDtype is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = c.replace(c[2], "foo") + tm.assert_series_equal(expected, result) + assert c[2] != "foo" # ensure non-inplace call does not alter original + + msg = "with CategoricalDtype is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + return_value = c.replace(c[2], "foo", inplace=True) + assert return_value is None + tm.assert_series_equal(expected, c) + + first_value = c[0] + msg = "with CategoricalDtype is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + return_value = c.replace(c[1], c[0], inplace=True) + assert return_value is None + assert c[0] == c[1] == first_value # test replacing with existing value + + def test_replace_with_no_overflowerror(self): + # GH 25616 + # casts to object without Exception from OverflowError + s = pd.Series([0, 1, 2, 3, 4]) + result = s.replace([3], ["100000000000000000000"]) + expected = pd.Series([0, 1, 2, "100000000000000000000", 4]) + tm.assert_series_equal(result, expected) + + s = pd.Series([0, "100000000000000000000", "100000000000000000001"]) + result = s.replace(["100000000000000000000"], [1]) + expected = pd.Series([0, 1, "100000000000000000001"]) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "ser, to_replace, exp", + [ + ([1, 2, 3], {1: 2, 2: 3, 3: 4}, [2, 3, 4]), + (["1", "2", "3"], {"1": "2", "2": "3", "3": "4"}, ["2", "3", "4"]), + ], + ) + def test_replace_commutative(self, ser, to_replace, exp): + # GH 16051 + # DataFrame.replace() overwrites when values are non-numeric + + series = pd.Series(ser) + + expected = pd.Series(exp) + result = series.replace(to_replace) + + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "ser, exp", [([1, 2, 3], [1, True, 3]), (["x", 2, 3], ["x", True, 3])] + ) + def test_replace_no_cast(self, ser, exp): + # GH 9113 + # BUG: replace int64 dtype with bool coerces to int64 + + series = pd.Series(ser) + result = series.replace(2, True) + expected = pd.Series(exp) + + tm.assert_series_equal(result, expected) + + def test_replace_invalid_to_replace(self): + # GH 18634 + # API: replace() should raise an exception if invalid argument is given + series = pd.Series(["a", "b", "c "]) + msg = ( + r"Expecting 'to_replace' to be either a scalar, array-like, " + r"dict or None, got invalid type.*" + ) + msg2 = ( + "Series.replace without 'value' and with non-dict-like " + "'to_replace' is deprecated" + ) + with pytest.raises(TypeError, match=msg): + with tm.assert_produces_warning(FutureWarning, match=msg2): + series.replace(lambda x: x.strip()) + + @pytest.mark.parametrize("frame", [False, True]) + def test_replace_nonbool_regex(self, frame): + obj = pd.Series(["a", "b", "c "]) + if frame: + obj = obj.to_frame() + + msg = "'to_replace' must be 'None' if 'regex' is not a bool" + with pytest.raises(ValueError, match=msg): + obj.replace(to_replace=["a"], regex="foo") + + @pytest.mark.parametrize("frame", [False, True]) + def test_replace_empty_copy(self, frame): + obj = pd.Series([], dtype=np.float64) + if frame: + obj = obj.to_frame() + + res = obj.replace(4, 5, inplace=True) + assert res is None + + res = obj.replace(4, 5, inplace=False) + tm.assert_equal(res, obj) + assert res is not obj + + def test_replace_only_one_dictlike_arg(self, fixed_now_ts): + # GH#33340 + + ser = pd.Series([1, 2, "A", fixed_now_ts, True]) + to_replace = {0: 1, 2: "A"} + value = "foo" + msg = "Series.replace cannot use dict-like to_replace and non-None value" + with pytest.raises(ValueError, match=msg): + ser.replace(to_replace, value) + + to_replace = 1 + value = {0: "foo", 2: "bar"} + msg = "Series.replace cannot use dict-value and non-None to_replace" + with pytest.raises(ValueError, match=msg): + ser.replace(to_replace, value) + + def test_replace_extension_other(self, frame_or_series): + # https://github.com/pandas-dev/pandas/issues/34530 + obj = frame_or_series(pd.array([1, 2, 3], dtype="Int64")) + result = obj.replace("", "") # no exception + # should not have changed dtype + tm.assert_equal(obj, result) + + def _check_replace_with_method(self, ser: pd.Series): + df = ser.to_frame() + + msg1 = "The 'method' keyword in Series.replace is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg1): + res = ser.replace(ser[1], method="pad") + expected = pd.Series([ser[0], ser[0]] + list(ser[2:]), dtype=ser.dtype) + tm.assert_series_equal(res, expected) + + msg2 = "The 'method' keyword in DataFrame.replace is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg2): + res_df = df.replace(ser[1], method="pad") + tm.assert_frame_equal(res_df, expected.to_frame()) + + ser2 = ser.copy() + with tm.assert_produces_warning(FutureWarning, match=msg1): + res2 = ser2.replace(ser[1], method="pad", inplace=True) + assert res2 is None + tm.assert_series_equal(ser2, expected) + + with tm.assert_produces_warning(FutureWarning, match=msg2): + res_df2 = df.replace(ser[1], method="pad", inplace=True) + assert res_df2 is None + tm.assert_frame_equal(df, expected.to_frame()) + + def test_replace_ea_dtype_with_method(self, any_numeric_ea_dtype): + arr = pd.array([1, 2, pd.NA, 4], dtype=any_numeric_ea_dtype) + ser = pd.Series(arr) + + self._check_replace_with_method(ser) + + @pytest.mark.parametrize("as_categorical", [True, False]) + def test_replace_interval_with_method(self, as_categorical): + # in particular interval that can't hold NA + + idx = pd.IntervalIndex.from_breaks(range(4)) + ser = pd.Series(idx) + if as_categorical: + ser = ser.astype("category") + + self._check_replace_with_method(ser) + + @pytest.mark.parametrize("as_period", [True, False]) + @pytest.mark.parametrize("as_categorical", [True, False]) + def test_replace_datetimelike_with_method(self, as_period, as_categorical): + idx = pd.date_range("2016-01-01", periods=5, tz="US/Pacific") + if as_period: + idx = idx.tz_localize(None).to_period("D") + + ser = pd.Series(idx) + ser.iloc[-2] = pd.NaT + if as_categorical: + ser = ser.astype("category") + + self._check_replace_with_method(ser) + + def test_replace_with_compiled_regex(self): + # https://github.com/pandas-dev/pandas/issues/35680 + s = pd.Series(["a", "b", "c"]) + regex = re.compile("^a$") + result = s.replace({regex: "z"}, regex=True) + expected = pd.Series(["z", "b", "c"]) + tm.assert_series_equal(result, expected) + + def test_pandas_replace_na(self): + # GH#43344 + # GH#56599 + ser = pd.Series(["AA", "BB", "CC", "DD", "EE", "", pd.NA, "AA"], dtype="string") + regex_mapping = { + "AA": "CC", + "BB": "CC", + "EE": "CC", + "CC": "CC-REPL", + } + result = ser.replace(regex_mapping, regex=True) + exp = pd.Series( + ["CC", "CC", "CC-REPL", "DD", "CC", "", pd.NA, "CC"], dtype="string" + ) + tm.assert_series_equal(result, exp) + + @pytest.mark.parametrize( + "dtype, input_data, to_replace, expected_data", + [ + ("bool", [True, False], {True: False}, [False, False]), + ("int64", [1, 2], {1: 10, 2: 20}, [10, 20]), + ("Int64", [1, 2], {1: 10, 2: 20}, [10, 20]), + ("float64", [1.1, 2.2], {1.1: 10.1, 2.2: 20.5}, [10.1, 20.5]), + ("Float64", [1.1, 2.2], {1.1: 10.1, 2.2: 20.5}, [10.1, 20.5]), + ("string", ["one", "two"], {"one": "1", "two": "2"}, ["1", "2"]), + ( + pd.IntervalDtype("int64"), + IntervalArray([pd.Interval(1, 2), pd.Interval(2, 3)]), + {pd.Interval(1, 2): pd.Interval(10, 20)}, + IntervalArray([pd.Interval(10, 20), pd.Interval(2, 3)]), + ), + ( + pd.IntervalDtype("float64"), + IntervalArray([pd.Interval(1.0, 2.7), pd.Interval(2.8, 3.1)]), + {pd.Interval(1.0, 2.7): pd.Interval(10.6, 20.8)}, + IntervalArray([pd.Interval(10.6, 20.8), pd.Interval(2.8, 3.1)]), + ), + ( + pd.PeriodDtype("M"), + [pd.Period("2020-05", freq="M")], + {pd.Period("2020-05", freq="M"): pd.Period("2020-06", freq="M")}, + [pd.Period("2020-06", freq="M")], + ), + ], + ) + def test_replace_dtype(self, dtype, input_data, to_replace, expected_data): + # GH#33484 + ser = pd.Series(input_data, dtype=dtype) + result = ser.replace(to_replace) + expected = pd.Series(expected_data, dtype=dtype) + tm.assert_series_equal(result, expected) + + def test_replace_string_dtype(self): + # GH#40732, GH#44940 + ser = pd.Series(["one", "two", np.nan], dtype="string") + res = ser.replace({"one": "1", "two": "2"}) + expected = pd.Series(["1", "2", np.nan], dtype="string") + tm.assert_series_equal(res, expected) + + # GH#31644 + ser2 = pd.Series(["A", np.nan], dtype="string") + res2 = ser2.replace("A", "B") + expected2 = pd.Series(["B", np.nan], dtype="string") + tm.assert_series_equal(res2, expected2) + + ser3 = pd.Series(["A", "B"], dtype="string") + res3 = ser3.replace("A", pd.NA) + expected3 = pd.Series([pd.NA, "B"], dtype="string") + tm.assert_series_equal(res3, expected3) + + def test_replace_string_dtype_list_to_replace(self): + # GH#41215, GH#44940 + ser = pd.Series(["abc", "def"], dtype="string") + res = ser.replace(["abc", "any other string"], "xyz") + expected = pd.Series(["xyz", "def"], dtype="string") + tm.assert_series_equal(res, expected) + + def test_replace_string_dtype_regex(self): + # GH#31644 + ser = pd.Series(["A", "B"], dtype="string") + res = ser.replace(r".", "C", regex=True) + expected = pd.Series(["C", "C"], dtype="string") + tm.assert_series_equal(res, expected) + + def test_replace_nullable_numeric(self): + # GH#40732, GH#44940 + + floats = pd.Series([1.0, 2.0, 3.999, 4.4], dtype=pd.Float64Dtype()) + assert floats.replace({1.0: 9}).dtype == floats.dtype + assert floats.replace(1.0, 9).dtype == floats.dtype + assert floats.replace({1.0: 9.0}).dtype == floats.dtype + assert floats.replace(1.0, 9.0).dtype == floats.dtype + + res = floats.replace(to_replace=[1.0, 2.0], value=[9.0, 10.0]) + assert res.dtype == floats.dtype + + ints = pd.Series([1, 2, 3, 4], dtype=pd.Int64Dtype()) + assert ints.replace({1: 9}).dtype == ints.dtype + assert ints.replace(1, 9).dtype == ints.dtype + assert ints.replace({1: 9.0}).dtype == ints.dtype + assert ints.replace(1, 9.0).dtype == ints.dtype + + # nullable (for now) raises instead of casting + with pytest.raises(TypeError, match="Invalid value"): + ints.replace({1: 9.5}) + with pytest.raises(TypeError, match="Invalid value"): + ints.replace(1, 9.5) + + @pytest.mark.parametrize("regex", [False, True]) + def test_replace_regex_dtype_series(self, regex): + # GH-48644 + series = pd.Series(["0"], dtype=object) + expected = pd.Series([1]) + msg = "Downcasting behavior in `replace`" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = series.replace(to_replace="0", value=1, regex=regex) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("regex", [False, True]) + def test_replace_regex_dtype_series_string(self, regex): + series = pd.Series(["0"], dtype="str") + expected = pd.Series([1], dtype="int64") + msg = "Downcasting behavior in `replace`" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = series.replace(to_replace="0", value=1, regex=regex) + tm.assert_series_equal(result, expected) + + def test_replace_different_int_types(self, any_int_numpy_dtype): + # GH#45311 + labs = pd.Series([1, 1, 1, 0, 0, 2, 2, 2], dtype=any_int_numpy_dtype) + + maps = pd.Series([0, 2, 1], dtype=any_int_numpy_dtype) + map_dict = dict(zip(maps.values, maps.index)) + + result = labs.replace(map_dict) + expected = labs.replace({0: 0, 2: 1, 1: 2}) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("val", [2, np.nan, 2.0]) + def test_replace_value_none_dtype_numeric(self, val): + # GH#48231 + ser = pd.Series([1, val]) + result = ser.replace(val, None) + expected = pd.Series([1, None], dtype=object) + tm.assert_series_equal(result, expected) + + def test_replace_change_dtype_series(self): + # GH#25797 + df = pd.DataFrame({"Test": ["0.5", True, "0.6"]}, dtype=object) + df["Test"] = df["Test"].replace([True], [np.nan]) + expected = pd.DataFrame({"Test": ["0.5", np.nan, "0.6"]}, dtype=object) + tm.assert_frame_equal(df, expected) + + df = pd.DataFrame({"Test": ["0.5", None, "0.6"]}, dtype=object) + df["Test"] = df["Test"].replace([None], [np.nan]) + tm.assert_frame_equal(df, expected) + + df = pd.DataFrame({"Test": ["0.5", None, "0.6"]}, dtype=object) + df["Test"] = df["Test"].fillna(np.nan) + tm.assert_frame_equal(df, expected) + + @pytest.mark.parametrize("dtype", ["object", "Int64"]) + def test_replace_na_in_obj_column(self, dtype): + # GH#47480 + ser = pd.Series([0, 1, pd.NA], dtype=dtype) + expected = pd.Series([0, 2, pd.NA], dtype=dtype) + result = ser.replace(to_replace=1, value=2) + tm.assert_series_equal(result, expected) + + ser.replace(to_replace=1, value=2, inplace=True) + tm.assert_series_equal(ser, expected) + + @pytest.mark.parametrize("val", [0, 0.5]) + def test_replace_numeric_column_with_na(self, val): + # GH#50758 + ser = pd.Series([val, 1]) + expected = pd.Series([val, pd.NA]) + result = ser.replace(to_replace=1, value=pd.NA) + tm.assert_series_equal(result, expected) + + ser.replace(to_replace=1, value=pd.NA, inplace=True) + tm.assert_series_equal(ser, expected) + + def test_replace_ea_float_with_bool(self): + # GH#55398 + ser = pd.Series([0.0], dtype="Float64") + expected = ser.copy() + result = ser.replace(False, 1.0) + tm.assert_series_equal(result, expected) + + ser = pd.Series([False], dtype="boolean") + expected = ser.copy() + result = ser.replace(0.0, True) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reset_index.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reset_index.py new file mode 100644 index 0000000000000000000000000000000000000000..fa571fa126b38282cd5e132472a3824732446354 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_reset_index.py @@ -0,0 +1,225 @@ +from datetime import datetime + +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + DataFrame, + Index, + MultiIndex, + RangeIndex, + Series, + date_range, + option_context, +) +import pandas._testing as tm + + +class TestResetIndex: + def test_reset_index_dti_round_trip(self): + dti = date_range(start="1/1/2001", end="6/1/2001", freq="D")._with_freq(None) + d1 = DataFrame({"v": np.random.default_rng(2).random(len(dti))}, index=dti) + d2 = d1.reset_index() + assert d2.dtypes.iloc[0] == np.dtype("M8[ns]") + d3 = d2.set_index("index") + tm.assert_frame_equal(d1, d3, check_names=False) + + # GH#2329 + stamp = datetime(2012, 11, 22) + df = DataFrame([[stamp, 12.1]], columns=["Date", "Value"]) + df = df.set_index("Date") + + assert df.index[0] == stamp + assert df.reset_index()["Date"].iloc[0] == stamp + + def test_reset_index(self): + df = DataFrame( + 1.1 * np.arange(120).reshape((30, 4)), + columns=Index(list("ABCD"), dtype=object), + index=Index([f"i-{i}" for i in range(30)], dtype=object), + )[:5] + ser = df.stack(future_stack=True) + ser.index.names = ["hash", "category"] + + ser.name = "value" + df = ser.reset_index() + assert "value" in df + + df = ser.reset_index(name="value2") + assert "value2" in df + + # check inplace + s = ser.reset_index(drop=True) + s2 = ser + return_value = s2.reset_index(drop=True, inplace=True) + assert return_value is None + tm.assert_series_equal(s, s2) + + # level + index = MultiIndex( + levels=[["bar"], ["one", "two", "three"], [0, 1]], + codes=[[0, 0, 0, 0, 0, 0], [0, 1, 2, 0, 1, 2], [0, 1, 0, 1, 0, 1]], + ) + s = Series(np.random.default_rng(2).standard_normal(6), index=index) + rs = s.reset_index(level=1) + assert len(rs.columns) == 2 + + rs = s.reset_index(level=[0, 2], drop=True) + tm.assert_index_equal(rs.index, Index(index.get_level_values(1))) + assert isinstance(rs, Series) + + def test_reset_index_name(self): + s = Series([1, 2, 3], index=Index(range(3), name="x")) + assert s.reset_index().index.name is None + assert s.reset_index(drop=True).index.name is None + + def test_reset_index_level(self): + df = DataFrame([[1, 2, 3], [4, 5, 6]], columns=["A", "B", "C"]) + + for levels in ["A", "B"], [0, 1]: + # With MultiIndex + s = df.set_index(["A", "B"])["C"] + + result = s.reset_index(level=levels[0]) + tm.assert_frame_equal(result, df.set_index("B")) + + result = s.reset_index(level=levels[:1]) + tm.assert_frame_equal(result, df.set_index("B")) + + result = s.reset_index(level=levels) + tm.assert_frame_equal(result, df) + + result = df.set_index(["A", "B"]).reset_index(level=levels, drop=True) + tm.assert_frame_equal(result, df[["C"]]) + + with pytest.raises(KeyError, match="Level E "): + s.reset_index(level=["A", "E"]) + + # With single-level Index + s = df.set_index("A")["B"] + + result = s.reset_index(level=levels[0]) + tm.assert_frame_equal(result, df[["A", "B"]]) + + result = s.reset_index(level=levels[:1]) + tm.assert_frame_equal(result, df[["A", "B"]]) + + result = s.reset_index(level=levels[0], drop=True) + tm.assert_series_equal(result, df["B"]) + + with pytest.raises(IndexError, match="Too many levels"): + s.reset_index(level=[0, 1, 2]) + + # Check that .reset_index([],drop=True) doesn't fail + result = Series(range(4)).reset_index([], drop=True) + expected = Series(range(4)) + tm.assert_series_equal(result, expected) + + def test_reset_index_range(self): + # GH 12071 + s = Series(range(2), name="A", dtype="int64") + series_result = s.reset_index() + assert isinstance(series_result.index, RangeIndex) + series_expected = DataFrame( + [[0, 0], [1, 1]], columns=["index", "A"], index=RangeIndex(stop=2) + ) + tm.assert_frame_equal(series_result, series_expected) + + def test_reset_index_drop_errors(self): + # GH 20925 + + # KeyError raised for series index when passed level name is missing + s = Series(range(4)) + with pytest.raises(KeyError, match="does not match index name"): + s.reset_index("wrong", drop=True) + with pytest.raises(KeyError, match="does not match index name"): + s.reset_index("wrong") + + # KeyError raised for series when level to be dropped is missing + s = Series(range(4), index=MultiIndex.from_product([[1, 2]] * 2)) + with pytest.raises(KeyError, match="not found"): + s.reset_index("wrong", drop=True) + + def test_reset_index_with_drop(self): + arrays = [ + ["bar", "bar", "baz", "baz", "qux", "qux", "foo", "foo"], + ["one", "two", "one", "two", "one", "two", "one", "two"], + ] + tuples = zip(*arrays) + index = MultiIndex.from_tuples(tuples) + data = np.random.default_rng(2).standard_normal(8) + ser = Series(data, index=index) + ser.iloc[3] = np.nan + + deleveled = ser.reset_index() + assert isinstance(deleveled, DataFrame) + assert len(deleveled.columns) == len(ser.index.levels) + 1 + assert deleveled.index.name == ser.index.name + + deleveled = ser.reset_index(drop=True) + assert isinstance(deleveled, Series) + assert deleveled.index.name == ser.index.name + + def test_reset_index_inplace_and_drop_ignore_name(self): + # GH#44575 + ser = Series(range(2), name="old") + ser.reset_index(name="new", drop=True, inplace=True) + expected = Series(range(2), name="old") + tm.assert_series_equal(ser, expected) + + def test_reset_index_drop_infer_string(self): + # GH#56160 + pytest.importorskip("pyarrow") + ser = Series(["a", "b", "c"], dtype=object) + with option_context("future.infer_string", True): + result = ser.reset_index(drop=True) + tm.assert_series_equal(result, ser) + + +@pytest.mark.parametrize( + "array, dtype", + [ + (["a", "b"], object), + ( + pd.period_range("12-1-2000", periods=2, freq="Q-DEC"), + pd.PeriodDtype(freq="Q-DEC"), + ), + ], +) +def test_reset_index_dtypes_on_empty_series_with_multiindex( + array, dtype, using_infer_string +): + # GH 19602 - Preserve dtype on empty Series with MultiIndex + idx = MultiIndex.from_product([[0, 1], [0.5, 1.0], array]) + result = Series(dtype=object, index=idx)[:0].reset_index().dtypes + exp = "str" if using_infer_string else object + expected = Series( + { + "level_0": np.int64, + "level_1": np.float64, + "level_2": exp if dtype == object else dtype, + 0: object, + } + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "names, expected_names", + [ + (["A", "A"], ["A", "A"]), + (["level_1", None], ["level_1", "level_1"]), + ], +) +@pytest.mark.parametrize("allow_duplicates", [False, True]) +def test_column_name_duplicates(names, expected_names, allow_duplicates): + # GH#44755 reset_index with duplicate column labels + s = Series([1], index=MultiIndex.from_arrays([[1], [1]], names=names)) + if allow_duplicates: + result = s.reset_index(allow_duplicates=True) + expected = DataFrame([[1, 1, 1]], columns=expected_names + [0]) + tm.assert_frame_equal(result, expected) + else: + with pytest.raises(ValueError, match="cannot insert"): + s.reset_index() diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_round.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_round.py new file mode 100644 index 0000000000000000000000000000000000000000..a78f77e990ae13eda068e920bfa8e1f4de72af9a --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_round.py @@ -0,0 +1,81 @@ +import numpy as np +import pytest + +import pandas as pd +from pandas import Series +import pandas._testing as tm + + +class TestSeriesRound: + def test_round(self, datetime_series): + datetime_series.index.name = "index_name" + result = datetime_series.round(2) + expected = Series( + np.round(datetime_series.values, 2), index=datetime_series.index, name="ts" + ) + tm.assert_series_equal(result, expected) + assert result.name == datetime_series.name + + def test_round_numpy(self, any_float_dtype): + # See GH#12600 + ser = Series([1.53, 1.36, 0.06], dtype=any_float_dtype) + out = np.round(ser, decimals=0) + expected = Series([2.0, 1.0, 0.0], dtype=any_float_dtype) + tm.assert_series_equal(out, expected) + + msg = "the 'out' parameter is not supported" + with pytest.raises(ValueError, match=msg): + np.round(ser, decimals=0, out=ser) + + def test_round_numpy_with_nan(self, any_float_dtype): + # See GH#14197 + ser = Series([1.53, np.nan, 0.06], dtype=any_float_dtype) + with tm.assert_produces_warning(None): + result = ser.round() + expected = Series([2.0, np.nan, 0.0], dtype=any_float_dtype) + tm.assert_series_equal(result, expected) + + def test_round_builtin(self, any_float_dtype): + ser = Series( + [1.123, 2.123, 3.123], + index=range(3), + dtype=any_float_dtype, + ) + result = round(ser) + expected_rounded0 = Series( + [1.0, 2.0, 3.0], index=range(3), dtype=any_float_dtype + ) + tm.assert_series_equal(result, expected_rounded0) + + decimals = 2 + expected_rounded = Series( + [1.12, 2.12, 3.12], index=range(3), dtype=any_float_dtype + ) + result = round(ser, decimals) + tm.assert_series_equal(result, expected_rounded) + + @pytest.mark.parametrize("method", ["round", "floor", "ceil"]) + @pytest.mark.parametrize("freq", ["s", "5s", "min", "5min", "h", "5h"]) + def test_round_nat(self, method, freq, unit): + # GH14940, GH#56158 + ser = Series([pd.NaT], dtype=f"M8[{unit}]") + expected = Series(pd.NaT, dtype=f"M8[{unit}]") + round_method = getattr(ser.dt, method) + result = round_method(freq) + tm.assert_series_equal(result, expected) + + def test_round_ea_boolean(self): + # GH#55936 + ser = Series([True, False], dtype="boolean") + expected = ser.copy() + result = ser.round(2) + tm.assert_series_equal(result, expected) + result.iloc[0] = False + tm.assert_series_equal(ser, expected) + + def test_round_dtype_object(self): + # GH#61206 + ser = Series([0.2], dtype="object") + msg = "Expected numeric dtype, got object instead." + with pytest.raises(TypeError, match=msg): + ser.round() diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_searchsorted.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_searchsorted.py new file mode 100644 index 0000000000000000000000000000000000000000..239496052b99b42df262262a9ac89b71c93e0a26 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_searchsorted.py @@ -0,0 +1,77 @@ +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + Series, + Timestamp, + date_range, +) +import pandas._testing as tm +from pandas.api.types import is_scalar + + +class TestSeriesSearchSorted: + def test_searchsorted(self): + ser = Series([1, 2, 3]) + + result = ser.searchsorted(1, side="left") + assert is_scalar(result) + assert result == 0 + + result = ser.searchsorted(1, side="right") + assert is_scalar(result) + assert result == 1 + + def test_searchsorted_numeric_dtypes_scalar(self): + ser = Series([1, 2, 90, 1000, 3e9]) + res = ser.searchsorted(30) + assert is_scalar(res) + assert res == 2 + + res = ser.searchsorted([30]) + exp = np.array([2], dtype=np.intp) + tm.assert_numpy_array_equal(res, exp) + + def test_searchsorted_numeric_dtypes_vector(self): + ser = Series([1, 2, 90, 1000, 3e9]) + res = ser.searchsorted([91, 2e6]) + exp = np.array([3, 4], dtype=np.intp) + tm.assert_numpy_array_equal(res, exp) + + def test_searchsorted_datetime64_scalar(self): + ser = Series(date_range("20120101", periods=10, freq="2D")) + val = Timestamp("20120102") + res = ser.searchsorted(val) + assert is_scalar(res) + assert res == 1 + + def test_searchsorted_datetime64_scalar_mixed_timezones(self): + # GH 30086 + ser = Series(date_range("20120101", periods=10, freq="2D", tz="UTC")) + val = Timestamp("20120102", tz="America/New_York") + res = ser.searchsorted(val) + assert is_scalar(res) + assert res == 1 + + def test_searchsorted_datetime64_list(self): + ser = Series(date_range("20120101", periods=10, freq="2D")) + vals = [Timestamp("20120102"), Timestamp("20120104")] + res = ser.searchsorted(vals) + exp = np.array([1, 2], dtype=np.intp) + tm.assert_numpy_array_equal(res, exp) + + def test_searchsorted_sorter(self): + # GH8490 + ser = Series([3, 1, 2]) + res = ser.searchsorted([0, 3], sorter=np.argsort(ser)) + exp = np.array([0, 2], dtype=np.intp) + tm.assert_numpy_array_equal(res, exp) + + def test_searchsorted_dataframe_fail(self): + # GH#49620 + ser = Series([1, 2, 3, 4, 5]) + vals = pd.DataFrame([[1, 2], [3, 4]]) + msg = "Value must be 1-D array-like or scalar, DataFrame is not supported" + with pytest.raises(ValueError, match=msg): + ser.searchsorted(vals) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_set_name.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_set_name.py new file mode 100644 index 0000000000000000000000000000000000000000..cbc8ebde7a8ab79fabe94781123844c856c9c78b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_set_name.py @@ -0,0 +1,21 @@ +from datetime import datetime + +from pandas import Series + + +class TestSetName: + def test_set_name(self): + ser = Series([1, 2, 3]) + ser2 = ser._set_name("foo") + assert ser2.name == "foo" + assert ser.name is None + assert ser is not ser2 + + def test_set_name_attribute(self): + ser = Series([1, 2, 3]) + ser2 = Series([1, 2, 3], name="bar") + for name in [7, 7.0, "name", datetime(2001, 1, 1), (1,), "\u05D0"]: + ser.name = name + assert ser.name == name + ser2.name = name + assert ser2.name == name diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_size.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_size.py new file mode 100644 index 0000000000000000000000000000000000000000..20a454996fa4488501d6f623ad3afc6fa38e5634 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_size.py @@ -0,0 +1,22 @@ +import pytest + +from pandas import Series + + +@pytest.mark.parametrize( + "data, index, expected", + [ + ([1, 2, 3], None, 3), + ({"a": 1, "b": 2, "c": 3}, None, 3), + ([1, 2, 3], ["x", "y", "z"], 3), + ([1, 2, 3, 4, 5], ["x", "y", "z", "w", "n"], 5), + ([1, 2, 3], None, 3), + ([1, 2, 3], ["x", "y", "z"], 3), + ([1, 2, 3, 4], ["x", "y", "z", "w"], 4), + ], +) +def test_series(data, index, expected): + # GH#52897 + ser = Series(data, index=index) + assert ser.size == expected + assert isinstance(ser.size, int) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_sort_index.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_sort_index.py new file mode 100644 index 0000000000000000000000000000000000000000..d6817aa179b7bd040e89468c960b2eb3f0259003 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_sort_index.py @@ -0,0 +1,337 @@ +import numpy as np +import pytest + +from pandas import ( + DatetimeIndex, + IntervalIndex, + MultiIndex, + Series, +) +import pandas._testing as tm + + +@pytest.fixture(params=["quicksort", "mergesort", "heapsort", "stable"]) +def sort_kind(request): + return request.param + + +class TestSeriesSortIndex: + def test_sort_index_name(self, datetime_series): + result = datetime_series.sort_index(ascending=False) + assert result.name == datetime_series.name + + def test_sort_index(self, datetime_series): + datetime_series.index = datetime_series.index._with_freq(None) + + rindex = list(datetime_series.index) + np.random.default_rng(2).shuffle(rindex) + + random_order = datetime_series.reindex(rindex) + sorted_series = random_order.sort_index() + tm.assert_series_equal(sorted_series, datetime_series) + + # descending + sorted_series = random_order.sort_index(ascending=False) + tm.assert_series_equal( + sorted_series, datetime_series.reindex(datetime_series.index[::-1]) + ) + + # compat on level + sorted_series = random_order.sort_index(level=0) + tm.assert_series_equal(sorted_series, datetime_series) + + # compat on axis + sorted_series = random_order.sort_index(axis=0) + tm.assert_series_equal(sorted_series, datetime_series) + + msg = "No axis named 1 for object type Series" + with pytest.raises(ValueError, match=msg): + random_order.sort_values(axis=1) + + sorted_series = random_order.sort_index(level=0, axis=0) + tm.assert_series_equal(sorted_series, datetime_series) + + with pytest.raises(ValueError, match=msg): + random_order.sort_index(level=0, axis=1) + + def test_sort_index_inplace(self, datetime_series): + datetime_series.index = datetime_series.index._with_freq(None) + + # For GH#11402 + rindex = list(datetime_series.index) + np.random.default_rng(2).shuffle(rindex) + + # descending + random_order = datetime_series.reindex(rindex) + result = random_order.sort_index(ascending=False, inplace=True) + + assert result is None + expected = datetime_series.reindex(datetime_series.index[::-1]) + expected.index = expected.index._with_freq(None) + tm.assert_series_equal(random_order, expected) + + # ascending + random_order = datetime_series.reindex(rindex) + result = random_order.sort_index(ascending=True, inplace=True) + + assert result is None + expected = datetime_series.copy() + expected.index = expected.index._with_freq(None) + tm.assert_series_equal(random_order, expected) + + def test_sort_index_level(self): + mi = MultiIndex.from_tuples([[1, 1, 3], [1, 1, 1]], names=list("ABC")) + s = Series([1, 2], mi) + backwards = s.iloc[[1, 0]] + + res = s.sort_index(level="A") + tm.assert_series_equal(backwards, res) + + res = s.sort_index(level=["A", "B"]) + tm.assert_series_equal(backwards, res) + + res = s.sort_index(level="A", sort_remaining=False) + tm.assert_series_equal(s, res) + + res = s.sort_index(level=["A", "B"], sort_remaining=False) + tm.assert_series_equal(s, res) + + @pytest.mark.parametrize("level", ["A", 0]) # GH#21052 + def test_sort_index_multiindex(self, level): + mi = MultiIndex.from_tuples([[1, 1, 3], [1, 1, 1]], names=list("ABC")) + s = Series([1, 2], mi) + backwards = s.iloc[[1, 0]] + + # implicit sort_remaining=True + res = s.sort_index(level=level) + tm.assert_series_equal(backwards, res) + + # GH#13496 + # sort has no effect without remaining lvls + res = s.sort_index(level=level, sort_remaining=False) + tm.assert_series_equal(s, res) + + def test_sort_index_kind(self, sort_kind): + # GH#14444 & GH#13589: Add support for sort algo choosing + series = Series(index=[3, 2, 1, 4, 3], dtype=object) + expected_series = Series(index=[1, 2, 3, 3, 4], dtype=object) + + index_sorted_series = series.sort_index(kind=sort_kind) + tm.assert_series_equal(expected_series, index_sorted_series) + + def test_sort_index_na_position(self): + series = Series(index=[3, 2, 1, 4, 3, np.nan], dtype=object) + expected_series_first = Series(index=[np.nan, 1, 2, 3, 3, 4], dtype=object) + + index_sorted_series = series.sort_index(na_position="first") + tm.assert_series_equal(expected_series_first, index_sorted_series) + + expected_series_last = Series(index=[1, 2, 3, 3, 4, np.nan], dtype=object) + + index_sorted_series = series.sort_index(na_position="last") + tm.assert_series_equal(expected_series_last, index_sorted_series) + + def test_sort_index_intervals(self): + s = Series( + [np.nan, 1, 2, 3], IntervalIndex.from_arrays([0, 1, 2, 3], [1, 2, 3, 4]) + ) + + result = s.sort_index() + expected = s + tm.assert_series_equal(result, expected) + + result = s.sort_index(ascending=False) + expected = Series( + [3, 2, 1, np.nan], IntervalIndex.from_arrays([3, 2, 1, 0], [4, 3, 2, 1]) + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("inplace", [True, False]) + @pytest.mark.parametrize( + "original_list, sorted_list, ascending, ignore_index, output_index", + [ + ([2, 3, 6, 1], [2, 3, 6, 1], True, True, [0, 1, 2, 3]), + ([2, 3, 6, 1], [2, 3, 6, 1], True, False, [0, 1, 2, 3]), + ([2, 3, 6, 1], [1, 6, 3, 2], False, True, [0, 1, 2, 3]), + ([2, 3, 6, 1], [1, 6, 3, 2], False, False, [3, 2, 1, 0]), + ], + ) + def test_sort_index_ignore_index( + self, inplace, original_list, sorted_list, ascending, ignore_index, output_index + ): + # GH 30114 + ser = Series(original_list) + expected = Series(sorted_list, index=output_index) + kwargs = { + "ascending": ascending, + "ignore_index": ignore_index, + "inplace": inplace, + } + + if inplace: + result_ser = ser.copy() + result_ser.sort_index(**kwargs) + else: + result_ser = ser.sort_index(**kwargs) + + tm.assert_series_equal(result_ser, expected) + tm.assert_series_equal(ser, Series(original_list)) + + def test_sort_index_ascending_list(self): + # GH#16934 + + # Set up a Series with a three level MultiIndex + arrays = [ + ["bar", "bar", "baz", "baz", "foo", "foo", "qux", "qux"], + ["one", "two", "one", "two", "one", "two", "one", "two"], + [4, 3, 2, 1, 4, 3, 2, 1], + ] + tuples = zip(*arrays) + mi = MultiIndex.from_tuples(tuples, names=["first", "second", "third"]) + ser = Series(range(8), index=mi) + + # Sort with boolean ascending + result = ser.sort_index(level=["third", "first"], ascending=False) + expected = ser.iloc[[4, 0, 5, 1, 6, 2, 7, 3]] + tm.assert_series_equal(result, expected) + + # Sort with list of boolean ascending + result = ser.sort_index(level=["third", "first"], ascending=[False, True]) + expected = ser.iloc[[0, 4, 1, 5, 2, 6, 3, 7]] + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "ascending", + [ + None, + (True, None), + (False, "True"), + ], + ) + def test_sort_index_ascending_bad_value_raises(self, ascending): + ser = Series(range(10), index=[0, 3, 2, 1, 4, 5, 7, 6, 8, 9]) + match = 'For argument "ascending" expected type bool' + with pytest.raises(ValueError, match=match): + ser.sort_index(ascending=ascending) + + +class TestSeriesSortIndexKey: + def test_sort_index_multiindex_key(self): + mi = MultiIndex.from_tuples([[1, 1, 3], [1, 1, 1]], names=list("ABC")) + s = Series([1, 2], mi) + backwards = s.iloc[[1, 0]] + + result = s.sort_index(level="C", key=lambda x: -x) + tm.assert_series_equal(s, result) + + result = s.sort_index(level="C", key=lambda x: x) # nothing happens + tm.assert_series_equal(backwards, result) + + def test_sort_index_multiindex_key_multi_level(self): + mi = MultiIndex.from_tuples([[1, 1, 3], [1, 1, 1]], names=list("ABC")) + s = Series([1, 2], mi) + backwards = s.iloc[[1, 0]] + + result = s.sort_index(level=["A", "C"], key=lambda x: -x) + tm.assert_series_equal(s, result) + + result = s.sort_index(level=["A", "C"], key=lambda x: x) # nothing happens + tm.assert_series_equal(backwards, result) + + def test_sort_index_key(self): + series = Series(np.arange(6, dtype="int64"), index=list("aaBBca")) + + result = series.sort_index() + expected = series.iloc[[2, 3, 0, 1, 5, 4]] + tm.assert_series_equal(result, expected) + + result = series.sort_index(key=lambda x: x.str.lower()) + expected = series.iloc[[0, 1, 5, 2, 3, 4]] + tm.assert_series_equal(result, expected) + + result = series.sort_index(key=lambda x: x.str.lower(), ascending=False) + expected = series.iloc[[4, 2, 3, 0, 1, 5]] + tm.assert_series_equal(result, expected) + + def test_sort_index_key_int(self): + series = Series(np.arange(6, dtype="int64"), index=np.arange(6, dtype="int64")) + + result = series.sort_index() + tm.assert_series_equal(result, series) + + result = series.sort_index(key=lambda x: -x) + expected = series.sort_index(ascending=False) + tm.assert_series_equal(result, expected) + + result = series.sort_index(key=lambda x: 2 * x) + tm.assert_series_equal(result, series) + + def test_sort_index_kind_key(self, sort_kind, sort_by_key): + # GH #14444 & #13589: Add support for sort algo choosing + series = Series(index=[3, 2, 1, 4, 3], dtype=object) + expected_series = Series(index=[1, 2, 3, 3, 4], dtype=object) + + index_sorted_series = series.sort_index(kind=sort_kind, key=sort_by_key) + tm.assert_series_equal(expected_series, index_sorted_series) + + def test_sort_index_kind_neg_key(self, sort_kind): + # GH #14444 & #13589: Add support for sort algo choosing + series = Series(index=[3, 2, 1, 4, 3], dtype=object) + expected_series = Series(index=[4, 3, 3, 2, 1], dtype=object) + + index_sorted_series = series.sort_index(kind=sort_kind, key=lambda x: -x) + tm.assert_series_equal(expected_series, index_sorted_series) + + def test_sort_index_na_position_key(self, sort_by_key): + series = Series(index=[3, 2, 1, 4, 3, np.nan], dtype=object) + expected_series_first = Series(index=[np.nan, 1, 2, 3, 3, 4], dtype=object) + + index_sorted_series = series.sort_index(na_position="first", key=sort_by_key) + tm.assert_series_equal(expected_series_first, index_sorted_series) + + expected_series_last = Series(index=[1, 2, 3, 3, 4, np.nan], dtype=object) + + index_sorted_series = series.sort_index(na_position="last", key=sort_by_key) + tm.assert_series_equal(expected_series_last, index_sorted_series) + + def test_changes_length_raises(self): + s = Series([1, 2, 3]) + with pytest.raises(ValueError, match="change the shape"): + s.sort_index(key=lambda x: x[:1]) + + def test_sort_values_key_type(self): + s = Series([1, 2, 3], DatetimeIndex(["2008-10-24", "2008-11-23", "2007-12-22"])) + + result = s.sort_index(key=lambda x: x.month) + expected = s.iloc[[0, 1, 2]] + tm.assert_series_equal(result, expected) + + result = s.sort_index(key=lambda x: x.day) + expected = s.iloc[[2, 1, 0]] + tm.assert_series_equal(result, expected) + + result = s.sort_index(key=lambda x: x.year) + expected = s.iloc[[2, 0, 1]] + tm.assert_series_equal(result, expected) + + result = s.sort_index(key=lambda x: x.month_name()) + expected = s.iloc[[2, 1, 0]] + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "ascending", + [ + [True, False], + [False, True], + ], + ) + def test_sort_index_multi_already_monotonic(self, ascending): + # GH 56049 + mi = MultiIndex.from_product([[1, 2], [3, 4]]) + ser = Series(range(len(mi)), index=mi) + result = ser.sort_index(ascending=ascending) + if ascending == [True, False]: + expected = ser.take([1, 0, 3, 2]) + elif ascending == [False, True]: + expected = ser.take([2, 3, 0, 1]) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_sort_values.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_sort_values.py new file mode 100644 index 0000000000000000000000000000000000000000..4808272879071e8530c000daddbe7e9518deaefc --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_sort_values.py @@ -0,0 +1,246 @@ +import numpy as np +import pytest + +from pandas import ( + Categorical, + DataFrame, + Series, +) +import pandas._testing as tm + + +class TestSeriesSortValues: + def test_sort_values(self, datetime_series, using_copy_on_write): + # check indexes are reordered corresponding with the values + ser = Series([3, 2, 4, 1], ["A", "B", "C", "D"]) + expected = Series([1, 2, 3, 4], ["D", "B", "A", "C"]) + result = ser.sort_values() + tm.assert_series_equal(expected, result) + + ts = datetime_series.copy() + ts[:5] = np.nan + vals = ts.values + + result = ts.sort_values() + assert np.isnan(result[-5:]).all() + tm.assert_numpy_array_equal(result[:-5].values, np.sort(vals[5:])) + + # na_position + result = ts.sort_values(na_position="first") + assert np.isnan(result[:5]).all() + tm.assert_numpy_array_equal(result[5:].values, np.sort(vals[5:])) + + # something object-type + ser = Series(["A", "B"], [1, 2]) + # no failure + ser.sort_values() + + # ascending=False + ordered = ts.sort_values(ascending=False) + expected = np.sort(ts.dropna().values)[::-1] + tm.assert_almost_equal(expected, ordered.dropna().values) + ordered = ts.sort_values(ascending=False, na_position="first") + tm.assert_almost_equal(expected, ordered.dropna().values) + + # ascending=[False] should behave the same as ascending=False + ordered = ts.sort_values(ascending=[False]) + expected = ts.sort_values(ascending=False) + tm.assert_series_equal(expected, ordered) + ordered = ts.sort_values(ascending=[False], na_position="first") + expected = ts.sort_values(ascending=False, na_position="first") + tm.assert_series_equal(expected, ordered) + + msg = 'For argument "ascending" expected type bool, received type NoneType.' + with pytest.raises(ValueError, match=msg): + ts.sort_values(ascending=None) + msg = r"Length of ascending \(0\) must be 1 for Series" + with pytest.raises(ValueError, match=msg): + ts.sort_values(ascending=[]) + msg = r"Length of ascending \(3\) must be 1 for Series" + with pytest.raises(ValueError, match=msg): + ts.sort_values(ascending=[1, 2, 3]) + msg = r"Length of ascending \(2\) must be 1 for Series" + with pytest.raises(ValueError, match=msg): + ts.sort_values(ascending=[False, False]) + msg = 'For argument "ascending" expected type bool, received type str.' + with pytest.raises(ValueError, match=msg): + ts.sort_values(ascending="foobar") + + # inplace=True + ts = datetime_series.copy() + return_value = ts.sort_values(ascending=False, inplace=True) + assert return_value is None + tm.assert_series_equal(ts, datetime_series.sort_values(ascending=False)) + tm.assert_index_equal( + ts.index, datetime_series.sort_values(ascending=False).index + ) + + # GH#5856/5853 + # Series.sort_values operating on a view + df = DataFrame(np.random.default_rng(2).standard_normal((10, 4))) + s = df.iloc[:, 0] + + msg = ( + "This Series is a view of some other array, to sort in-place " + "you must create a copy" + ) + if using_copy_on_write: + s.sort_values(inplace=True) + tm.assert_series_equal(s, df.iloc[:, 0].sort_values()) + else: + with pytest.raises(ValueError, match=msg): + s.sort_values(inplace=True) + + def test_sort_values_categorical(self): + c = Categorical(["a", "b", "b", "a"], ordered=False) + cat = Series(c.copy()) + + # sort in the categories order + expected = Series( + Categorical(["a", "a", "b", "b"], ordered=False), index=[0, 3, 1, 2] + ) + result = cat.sort_values() + tm.assert_series_equal(result, expected) + + cat = Series(Categorical(["a", "c", "b", "d"], ordered=True)) + res = cat.sort_values() + exp = np.array(["a", "b", "c", "d"], dtype=np.object_) + tm.assert_numpy_array_equal(res.__array__(), exp) + + cat = Series( + Categorical( + ["a", "c", "b", "d"], categories=["a", "b", "c", "d"], ordered=True + ) + ) + res = cat.sort_values() + exp = np.array(["a", "b", "c", "d"], dtype=np.object_) + tm.assert_numpy_array_equal(res.__array__(), exp) + + res = cat.sort_values(ascending=False) + exp = np.array(["d", "c", "b", "a"], dtype=np.object_) + tm.assert_numpy_array_equal(res.__array__(), exp) + + raw_cat1 = Categorical( + ["a", "b", "c", "d"], categories=["a", "b", "c", "d"], ordered=False + ) + raw_cat2 = Categorical( + ["a", "b", "c", "d"], categories=["d", "c", "b", "a"], ordered=True + ) + s = ["a", "b", "c", "d"] + df = DataFrame( + {"unsort": raw_cat1, "sort": raw_cat2, "string": s, "values": [1, 2, 3, 4]} + ) + + # Cats must be sorted in a dataframe + res = df.sort_values(by=["string"], ascending=False) + exp = np.array(["d", "c", "b", "a"], dtype=np.object_) + tm.assert_numpy_array_equal(res["sort"].values.__array__(), exp) + assert res["sort"].dtype == "category" + + res = df.sort_values(by=["sort"], ascending=False) + exp = df.sort_values(by=["string"], ascending=True) + tm.assert_series_equal(res["values"], exp["values"]) + assert res["sort"].dtype == "category" + assert res["unsort"].dtype == "category" + + # unordered cat, but we allow this + df.sort_values(by=["unsort"], ascending=False) + + # multi-columns sort + # GH#7848 + df = DataFrame( + {"id": [6, 5, 4, 3, 2, 1], "raw_grade": ["a", "b", "b", "a", "a", "e"]} + ) + df["grade"] = Categorical(df["raw_grade"], ordered=True) + df["grade"] = df["grade"].cat.set_categories(["b", "e", "a"]) + + # sorts 'grade' according to the order of the categories + result = df.sort_values(by=["grade"]) + expected = df.iloc[[1, 2, 5, 0, 3, 4]] + tm.assert_frame_equal(result, expected) + + # multi + result = df.sort_values(by=["grade", "id"]) + expected = df.iloc[[2, 1, 5, 4, 3, 0]] + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("inplace", [True, False]) + @pytest.mark.parametrize( + "original_list, sorted_list, ignore_index, output_index", + [ + ([2, 3, 6, 1], [6, 3, 2, 1], True, [0, 1, 2, 3]), + ([2, 3, 6, 1], [6, 3, 2, 1], False, [2, 1, 0, 3]), + ], + ) + def test_sort_values_ignore_index( + self, inplace, original_list, sorted_list, ignore_index, output_index + ): + # GH 30114 + ser = Series(original_list) + expected = Series(sorted_list, index=output_index) + kwargs = {"ignore_index": ignore_index, "inplace": inplace} + + if inplace: + result_ser = ser.copy() + result_ser.sort_values(ascending=False, **kwargs) + else: + result_ser = ser.sort_values(ascending=False, **kwargs) + + tm.assert_series_equal(result_ser, expected) + tm.assert_series_equal(ser, Series(original_list)) + + def test_mergesort_descending_stability(self): + # GH 28697 + s = Series([1, 2, 1, 3], ["first", "b", "second", "c"]) + result = s.sort_values(ascending=False, kind="mergesort") + expected = Series([3, 2, 1, 1], ["c", "b", "first", "second"]) + tm.assert_series_equal(result, expected) + + def test_sort_values_validate_ascending_for_value_error(self): + # GH41634 + ser = Series([23, 7, 21]) + + msg = 'For argument "ascending" expected type bool, received type str.' + with pytest.raises(ValueError, match=msg): + ser.sort_values(ascending="False") + + @pytest.mark.parametrize("ascending", [False, 0, 1, True]) + def test_sort_values_validate_ascending_functional(self, ascending): + # GH41634 + ser = Series([23, 7, 21]) + expected = np.sort(ser.values) + + sorted_ser = ser.sort_values(ascending=ascending) + if not ascending: + expected = expected[::-1] + + result = sorted_ser.values + tm.assert_numpy_array_equal(result, expected) + + +class TestSeriesSortingKey: + def test_sort_values_key(self): + series = Series(np.array(["Hello", "goodbye"])) + + result = series.sort_values(axis=0) + expected = series + tm.assert_series_equal(result, expected) + + result = series.sort_values(axis=0, key=lambda x: x.str.lower()) + expected = series[::-1] + tm.assert_series_equal(result, expected) + + def test_sort_values_key_nan(self): + series = Series(np.array([0, 5, np.nan, 3, 2, np.nan])) + + result = series.sort_values(axis=0) + expected = series.iloc[[0, 4, 3, 1, 2, 5]] + tm.assert_series_equal(result, expected) + + result = series.sort_values(axis=0, key=lambda x: x + 5) + expected = series.iloc[[0, 4, 3, 1, 2, 5]] + tm.assert_series_equal(result, expected) + + result = series.sort_values(axis=0, key=lambda x: -x, ascending=False) + expected = series.iloc[[0, 4, 3, 1, 2, 5]] + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_csv.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_csv.py new file mode 100644 index 0000000000000000000000000000000000000000..ba75c7786ef72095c0888b815a778b5bc1446c03 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_csv.py @@ -0,0 +1,179 @@ +from datetime import datetime +from io import StringIO + +import numpy as np +import pytest + +import pandas as pd +from pandas import Series +import pandas._testing as tm + +from pandas.io.common import get_handle + + +class TestSeriesToCSV: + def read_csv(self, path, **kwargs): + params = {"index_col": 0, "header": None} + params.update(**kwargs) + + header = params.get("header") + out = pd.read_csv(path, **params).squeeze("columns") + + if header is None: + out.name = out.index.name = None + + return out + + def test_from_csv(self, datetime_series, string_series): + # freq doesn't round-trip + datetime_series.index = datetime_series.index._with_freq(None) + + with tm.ensure_clean() as path: + datetime_series.to_csv(path, header=False) + ts = self.read_csv(path, parse_dates=True) + tm.assert_series_equal(datetime_series, ts, check_names=False) + + assert ts.name is None + assert ts.index.name is None + + # see gh-10483 + datetime_series.to_csv(path, header=True) + ts_h = self.read_csv(path, header=0) + assert ts_h.name == "ts" + + string_series.to_csv(path, header=False) + series = self.read_csv(path) + tm.assert_series_equal(string_series, series, check_names=False) + + assert series.name is None + assert series.index.name is None + + string_series.to_csv(path, header=True) + series_h = self.read_csv(path, header=0) + assert series_h.name == "series" + + with open(path, "w", encoding="utf-8") as outfile: + outfile.write("1998-01-01|1.0\n1999-01-01|2.0") + + series = self.read_csv(path, sep="|", parse_dates=True) + check_series = Series( + {datetime(1998, 1, 1): 1.0, datetime(1999, 1, 1): 2.0} + ) + tm.assert_series_equal(check_series, series) + + series = self.read_csv(path, sep="|", parse_dates=False) + check_series = Series({"1998-01-01": 1.0, "1999-01-01": 2.0}) + tm.assert_series_equal(check_series, series) + + def test_to_csv(self, datetime_series): + with tm.ensure_clean() as path: + datetime_series.to_csv(path, header=False) + + with open(path, newline=None, encoding="utf-8") as f: + lines = f.readlines() + assert lines[1] != "\n" + + datetime_series.to_csv(path, index=False, header=False) + arr = np.loadtxt(path) + tm.assert_almost_equal(arr, datetime_series.values) + + def test_to_csv_unicode_index(self): + buf = StringIO() + s = Series(["\u05d0", "d2"], index=["\u05d0", "\u05d1"]) + + s.to_csv(buf, encoding="UTF-8", header=False) + buf.seek(0) + + s2 = self.read_csv(buf, index_col=0, encoding="UTF-8") + tm.assert_series_equal(s, s2) + + def test_to_csv_float_format(self): + with tm.ensure_clean() as filename: + ser = Series([0.123456, 0.234567, 0.567567]) + ser.to_csv(filename, float_format="%.2f", header=False) + + rs = self.read_csv(filename) + xp = Series([0.12, 0.23, 0.57]) + tm.assert_series_equal(rs, xp) + + def test_to_csv_list_entries(self): + s = Series(["jack and jill", "jesse and frank"]) + + split = s.str.split(r"\s+and\s+") + + buf = StringIO() + split.to_csv(buf, header=False) + + def test_to_csv_path_is_none(self): + # GH 8215 + # Series.to_csv() was returning None, inconsistent with + # DataFrame.to_csv() which returned string + s = Series([1, 2, 3]) + csv_str = s.to_csv(path_or_buf=None, header=False) + assert isinstance(csv_str, str) + + @pytest.mark.parametrize( + "s,encoding", + [ + ( + Series([0.123456, 0.234567, 0.567567], index=["A", "B", "C"], name="X"), + None, + ), + # GH 21241, 21118 + (Series(["abc", "def", "ghi"], name="X"), "ascii"), + (Series(["123", "你好", "世界"], name="中文"), "gb2312"), + ( + Series(["123", "Γειά σου", "Κόσμε"], name="Ελληνικά"), # noqa: RUF001 + "cp737", + ), + ], + ) + def test_to_csv_compression(self, s, encoding, compression): + with tm.ensure_clean() as filename: + s.to_csv(filename, compression=compression, encoding=encoding, header=True) + # test the round trip - to_csv -> read_csv + result = pd.read_csv( + filename, + compression=compression, + encoding=encoding, + index_col=0, + ).squeeze("columns") + tm.assert_series_equal(s, result) + + # test the round trip using file handle - to_csv -> read_csv + with get_handle( + filename, "w", compression=compression, encoding=encoding + ) as handles: + s.to_csv(handles.handle, encoding=encoding, header=True) + + result = pd.read_csv( + filename, + compression=compression, + encoding=encoding, + index_col=0, + ).squeeze("columns") + tm.assert_series_equal(s, result) + + # explicitly ensure file was compressed + with tm.decompress_file(filename, compression) as fh: + text = fh.read().decode(encoding or "utf8") + assert s.name in text + + with tm.decompress_file(filename, compression) as fh: + tm.assert_series_equal( + s, + pd.read_csv(fh, index_col=0, encoding=encoding).squeeze("columns"), + ) + + def test_to_csv_interval_index(self, using_infer_string): + # GH 28210 + s = Series(["foo", "bar", "baz"], index=pd.interval_range(0, 3)) + + with tm.ensure_clean("__tmp_to_csv_interval_index__.csv") as path: + s.to_csv(path, header=False) + result = self.read_csv(path, index_col=0) + + # can't roundtrip intervalindex via read_csv so check string repr (GH 23595) + expected = s + expected.index = expected.index.astype("str") + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_dict.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_dict.py new file mode 100644 index 0000000000000000000000000000000000000000..41c01f4537f23fdb90110685d2e774427916aee1 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_dict.py @@ -0,0 +1,38 @@ +import collections + +import numpy as np +import pytest + +from pandas import Series +import pandas._testing as tm + + +class TestSeriesToDict: + @pytest.mark.parametrize( + "mapping", (dict, collections.defaultdict(list), collections.OrderedDict) + ) + def test_to_dict(self, mapping, datetime_series): + # GH#16122 + result = Series(datetime_series.to_dict(into=mapping), name="ts") + expected = datetime_series.copy() + expected.index = expected.index._with_freq(None) + tm.assert_series_equal(result, expected) + + from_method = Series(datetime_series.to_dict(into=collections.Counter)) + from_constructor = Series(collections.Counter(datetime_series.items())) + tm.assert_series_equal(from_method, from_constructor) + + @pytest.mark.parametrize( + "input", + ( + {"a": np.int64(64), "b": 10}, + {"a": np.int64(64), "b": 10, "c": "ABC"}, + {"a": np.uint64(64), "b": 10, "c": "ABC"}, + ), + ) + def test_to_dict_return_types(self, input): + # GH25969 + + d = Series(input).to_dict() + assert isinstance(d["a"], int) + assert isinstance(d["b"], int) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_frame.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_frame.py new file mode 100644 index 0000000000000000000000000000000000000000..0eadf696b34cc034d2be76ce5daba2cff679da74 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_frame.py @@ -0,0 +1,63 @@ +import pytest + +from pandas import ( + DataFrame, + Index, + Series, +) +import pandas._testing as tm + + +class TestToFrame: + def test_to_frame_respects_name_none(self): + # GH#44212 if we explicitly pass name=None, then that should be respected, + # not changed to 0 + # GH-45448 this is first deprecated & enforced in 2.0 + ser = Series(range(3)) + result = ser.to_frame(None) + + exp_index = Index([None], dtype=object) + tm.assert_index_equal(result.columns, exp_index) + + result = ser.rename("foo").to_frame(None) + exp_index = Index([None], dtype=object) + tm.assert_index_equal(result.columns, exp_index) + + def test_to_frame(self, datetime_series): + datetime_series.name = None + rs = datetime_series.to_frame() + xp = DataFrame(datetime_series.values, index=datetime_series.index) + tm.assert_frame_equal(rs, xp) + + datetime_series.name = "testname" + rs = datetime_series.to_frame() + xp = DataFrame( + {"testname": datetime_series.values}, index=datetime_series.index + ) + tm.assert_frame_equal(rs, xp) + + rs = datetime_series.to_frame(name="testdifferent") + xp = DataFrame( + {"testdifferent": datetime_series.values}, index=datetime_series.index + ) + tm.assert_frame_equal(rs, xp) + + @pytest.mark.filterwarnings( + "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning" + ) + def test_to_frame_expanddim(self): + # GH#9762 + + class SubclassedSeries(Series): + @property + def _constructor_expanddim(self): + return SubclassedFrame + + class SubclassedFrame(DataFrame): + pass + + ser = SubclassedSeries([1, 2, 3], name="X") + result = ser.to_frame() + assert isinstance(result, SubclassedFrame) + expected = SubclassedFrame({"X": [1, 2, 3]}) + tm.assert_frame_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_numpy.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_numpy.py new file mode 100644 index 0000000000000000000000000000000000000000..4bc7631090761e720c61049f9b8fd2a7fadd89af --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_to_numpy.py @@ -0,0 +1,49 @@ +import numpy as np +import pytest + +import pandas.util._test_decorators as td + +from pandas import ( + NA, + Series, + Timedelta, +) +import pandas._testing as tm + + +@pytest.mark.parametrize("dtype", ["int64", "float64"]) +def test_to_numpy_na_value(dtype): + # GH#48951 + ser = Series([1, 2, NA, 4]) + result = ser.to_numpy(dtype=dtype, na_value=0) + expected = np.array([1, 2, 0, 4], dtype=dtype) + tm.assert_numpy_array_equal(result, expected) + + +def test_to_numpy_cast_before_setting_na(): + # GH#50600 + ser = Series([1]) + result = ser.to_numpy(dtype=np.float64, na_value=np.nan) + expected = np.array([1.0]) + tm.assert_numpy_array_equal(result, expected) + + +@td.skip_if_no("pyarrow") +def test_to_numpy_arrow_dtype_given(): + # GH#57121 + ser = Series([1, NA], dtype="int64[pyarrow]") + result = ser.to_numpy(dtype="float64") + expected = np.array([1.0, np.nan]) + tm.assert_numpy_array_equal(result, expected) + + +def test_astype_ea_int_to_td_ts(): + # GH#57093 + ser = Series([1, None], dtype="Int64") + result = ser.astype("m8[ns]") + expected = Series([1, Timedelta("nat")], dtype="m8[ns]") + tm.assert_series_equal(result, expected) + + result = ser.astype("M8[ns]") + expected = Series([1, Timedelta("nat")], dtype="M8[ns]") + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_tolist.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_tolist.py new file mode 100644 index 0000000000000000000000000000000000000000..4af473528e23850794139ac563cc04c6d3c54617 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_tolist.py @@ -0,0 +1,36 @@ +import pytest + +import pandas.util._test_decorators as td + +from pandas import ( + Interval, + Period, + Series, + Timedelta, + Timestamp, +) + + +@pytest.mark.parametrize( + "values, dtype, expected_dtype", + ( + ([1], "int64", int), + ([1], "Int64", int), + ([1.0], "float64", float), + ([1.0], "Float64", float), + (["abc"], "object", str), + (["abc"], "string", str), + ([Interval(1, 3)], "interval", Interval), + ([Period("2000-01-01", "D")], "period[D]", Period), + ([Timedelta(days=1)], "timedelta64[ns]", Timedelta), + ([Timestamp("2000-01-01")], "datetime64[ns]", Timestamp), + pytest.param([1], "int64[pyarrow]", int, marks=td.skip_if_no("pyarrow")), + pytest.param([1.0], "float64[pyarrow]", float, marks=td.skip_if_no("pyarrow")), + pytest.param(["abc"], "string[pyarrow]", str, marks=td.skip_if_no("pyarrow")), + ), +) +def test_tolist_scalar_dtype(values, dtype, expected_dtype): + # GH49890 + ser = Series(values, dtype=dtype) + result_dtype = type(ser.tolist()[0]) + assert result_dtype == expected_dtype diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_truncate.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_truncate.py new file mode 100644 index 0000000000000000000000000000000000000000..33eb5c10ae163862e342b1871669d64d74602e4e --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_truncate.py @@ -0,0 +1,67 @@ +from datetime import datetime + +import pytest + +import pandas as pd +from pandas import ( + Series, + date_range, +) +import pandas._testing as tm + + +class TestTruncate: + def test_truncate_datetimeindex_tz(self): + # GH 9243 + idx = date_range("4/1/2005", "4/30/2005", freq="D", tz="US/Pacific") + s = Series(range(len(idx)), index=idx) + with pytest.raises(TypeError, match="Cannot compare tz-naive"): + # GH#36148 as of 2.0 we require tzawareness compat + s.truncate(datetime(2005, 4, 2), datetime(2005, 4, 4)) + + lb = idx[1] + ub = idx[3] + result = s.truncate(lb.to_pydatetime(), ub.to_pydatetime()) + expected = Series([1, 2, 3], index=idx[1:4]) + tm.assert_series_equal(result, expected) + + def test_truncate_periodindex(self): + # GH 17717 + idx1 = pd.PeriodIndex( + [pd.Period("2017-09-02"), pd.Period("2017-09-02"), pd.Period("2017-09-03")] + ) + series1 = Series([1, 2, 3], index=idx1) + result1 = series1.truncate(after="2017-09-02") + + expected_idx1 = pd.PeriodIndex( + [pd.Period("2017-09-02"), pd.Period("2017-09-02")] + ) + tm.assert_series_equal(result1, Series([1, 2], index=expected_idx1)) + + idx2 = pd.PeriodIndex( + [pd.Period("2017-09-03"), pd.Period("2017-09-02"), pd.Period("2017-09-03")] + ) + series2 = Series([1, 2, 3], index=idx2) + result2 = series2.sort_index().truncate(after="2017-09-02") + + expected_idx2 = pd.PeriodIndex([pd.Period("2017-09-02")]) + tm.assert_series_equal(result2, Series([2], index=expected_idx2)) + + def test_truncate_one_element_series(self): + # GH 35544 + series = Series([0.1], index=pd.DatetimeIndex(["2020-08-04"])) + before = pd.Timestamp("2020-08-02") + after = pd.Timestamp("2020-08-04") + + result = series.truncate(before=before, after=after) + + # the input Series and the expected Series are the same + tm.assert_series_equal(result, series) + + def test_truncate_index_only_one_unique_value(self): + # GH 42365 + obj = Series(0, index=date_range("2021-06-30", "2021-06-30")).repeat(5) + + truncated = obj.truncate("2021-06-28", "2021-07-01") + + tm.assert_series_equal(truncated, obj) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_tz_localize.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_tz_localize.py new file mode 100644 index 0000000000000000000000000000000000000000..45620a721f442ee038569cdd69c1341ac56fd858 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_tz_localize.py @@ -0,0 +1,123 @@ +from datetime import timezone + +import pytest +import pytz + +from pandas._libs.tslibs import timezones + +from pandas import ( + DatetimeIndex, + NaT, + Series, + Timestamp, + date_range, +) +import pandas._testing as tm + + +class TestTZLocalize: + def test_series_tz_localize_ambiguous_bool(self): + # make sure that we are correctly accepting bool values as ambiguous + + # GH#14402 + ts = Timestamp("2015-11-01 01:00:03") + expected0 = Timestamp("2015-11-01 01:00:03-0500", tz="US/Central") + expected1 = Timestamp("2015-11-01 01:00:03-0600", tz="US/Central") + + ser = Series([ts]) + expected0 = Series([expected0]) + expected1 = Series([expected1]) + + with tm.external_error_raised(pytz.AmbiguousTimeError): + ser.dt.tz_localize("US/Central") + + result = ser.dt.tz_localize("US/Central", ambiguous=True) + tm.assert_series_equal(result, expected0) + + result = ser.dt.tz_localize("US/Central", ambiguous=[True]) + tm.assert_series_equal(result, expected0) + + result = ser.dt.tz_localize("US/Central", ambiguous=False) + tm.assert_series_equal(result, expected1) + + result = ser.dt.tz_localize("US/Central", ambiguous=[False]) + tm.assert_series_equal(result, expected1) + + def test_series_tz_localize_matching_index(self): + # Matching the index of the result with that of the original series + # GH 43080 + dt_series = Series( + date_range(start="2021-01-01T02:00:00", periods=5, freq="1D"), + index=[2, 6, 7, 8, 11], + dtype="category", + ) + result = dt_series.dt.tz_localize("Europe/Berlin") + expected = Series( + date_range( + start="2021-01-01T02:00:00", periods=5, freq="1D", tz="Europe/Berlin" + ), + index=[2, 6, 7, 8, 11], + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "method, exp", + [ + ["shift_forward", "2015-03-29 03:00:00"], + ["shift_backward", "2015-03-29 01:59:59.999999999"], + ["NaT", NaT], + ["raise", None], + ["foo", "invalid"], + ], + ) + def test_tz_localize_nonexistent(self, warsaw, method, exp, unit): + # GH 8917 + tz = warsaw + n = 60 + dti = date_range(start="2015-03-29 02:00:00", periods=n, freq="min", unit=unit) + ser = Series(1, index=dti) + df = ser.to_frame() + + if method == "raise": + with tm.external_error_raised(pytz.NonExistentTimeError): + dti.tz_localize(tz, nonexistent=method) + with tm.external_error_raised(pytz.NonExistentTimeError): + ser.tz_localize(tz, nonexistent=method) + with tm.external_error_raised(pytz.NonExistentTimeError): + df.tz_localize(tz, nonexistent=method) + + elif exp == "invalid": + msg = ( + "The nonexistent argument must be one of " + "'raise', 'NaT', 'shift_forward', 'shift_backward' " + "or a timedelta object" + ) + with pytest.raises(ValueError, match=msg): + dti.tz_localize(tz, nonexistent=method) + with pytest.raises(ValueError, match=msg): + ser.tz_localize(tz, nonexistent=method) + with pytest.raises(ValueError, match=msg): + df.tz_localize(tz, nonexistent=method) + + else: + result = ser.tz_localize(tz, nonexistent=method) + expected = Series(1, index=DatetimeIndex([exp] * n, tz=tz).as_unit(unit)) + tm.assert_series_equal(result, expected) + + result = df.tz_localize(tz, nonexistent=method) + expected = expected.to_frame() + tm.assert_frame_equal(result, expected) + + res_index = dti.tz_localize(tz, nonexistent=method) + tm.assert_index_equal(res_index, expected.index) + + @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"]) + def test_series_tz_localize_empty(self, tzstr): + # GH#2248 + ser = Series(dtype=object) + + ser2 = ser.tz_localize("utc") + assert ser2.index.tz == timezone.utc + + ser2 = ser.tz_localize(tzstr) + timezones.tz_compare(ser2.index.tz, timezones.maybe_get_tz(tzstr)) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_unique.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_unique.py new file mode 100644 index 0000000000000000000000000000000000000000..14e247332503253ede23e94fe1335e712a2675e7 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_unique.py @@ -0,0 +1,76 @@ +import numpy as np + +from pandas import ( + Categorical, + IntervalIndex, + Series, + date_range, +) +import pandas._testing as tm + + +class TestUnique: + def test_unique_uint64(self): + ser = Series([1, 2, 2**63, 2**63], dtype=np.uint64) + res = ser.unique() + exp = np.array([1, 2, 2**63], dtype=np.uint64) + tm.assert_numpy_array_equal(res, exp) + + def test_unique_data_ownership(self): + # it works! GH#1807 + Series(Series(["a", "c", "b"]).unique()).sort_values() + + def test_unique(self): + # GH#714 also, dtype=float + ser = Series([1.2345] * 100) + ser[::2] = np.nan + result = ser.unique() + assert len(result) == 2 + + # explicit f4 dtype + ser = Series([1.2345] * 100, dtype="f4") + ser[::2] = np.nan + result = ser.unique() + assert len(result) == 2 + + def test_unique_nan_object_dtype(self): + # NAs in object arrays GH#714 + ser = Series(["foo"] * 100, dtype="O") + ser[::2] = np.nan + result = ser.unique() + assert len(result) == 2 + + def test_unique_none(self): + # decision about None + ser = Series([1, 2, 3, None, None, None], dtype=object) + result = ser.unique() + expected = np.array([1, 2, 3, None], dtype=object) + tm.assert_numpy_array_equal(result, expected) + + def test_unique_categorical(self): + # GH#18051 + cat = Categorical([]) + ser = Series(cat) + result = ser.unique() + tm.assert_categorical_equal(result, cat) + + cat = Categorical([np.nan]) + ser = Series(cat) + result = ser.unique() + tm.assert_categorical_equal(result, cat) + + def test_tz_unique(self): + # GH 46128 + dti1 = date_range("2016-01-01", periods=3) + ii1 = IntervalIndex.from_breaks(dti1) + ser1 = Series(ii1) + uni1 = ser1.unique() + tm.assert_interval_array_equal(ser1.array, uni1) + + dti2 = date_range("2016-01-01", periods=3, tz="US/Eastern") + ii2 = IntervalIndex.from_breaks(dti2) + ser2 = Series(ii2) + uni2 = ser2.unique() + tm.assert_interval_array_equal(ser2.array, uni2) + + assert uni1.dtype != uni2.dtype diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_unstack.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_unstack.py new file mode 100644 index 0000000000000000000000000000000000000000..11995260dd0beb3325fb6e95847d6cf630bf9e79 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_unstack.py @@ -0,0 +1,169 @@ +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + date_range, +) +import pandas._testing as tm + + +def test_unstack_preserves_object(): + mi = MultiIndex.from_product([["bar", "foo"], ["one", "two"]]) + + ser = Series(np.arange(4.0), index=mi, dtype=object) + + res1 = ser.unstack() + assert (res1.dtypes == object).all() + + res2 = ser.unstack(level=0) + assert (res2.dtypes == object).all() + + +def test_unstack(): + index = MultiIndex( + levels=[["bar", "foo"], ["one", "three", "two"]], + codes=[[1, 1, 0, 0], [0, 1, 0, 2]], + ) + + s = Series(np.arange(4.0), index=index) + unstacked = s.unstack() + + expected = DataFrame( + [[2.0, np.nan, 3.0], [0.0, 1.0, np.nan]], + index=["bar", "foo"], + columns=["one", "three", "two"], + ) + + tm.assert_frame_equal(unstacked, expected) + + unstacked = s.unstack(level=0) + tm.assert_frame_equal(unstacked, expected.T) + + index = MultiIndex( + levels=[["bar"], ["one", "two", "three"], [0, 1]], + codes=[[0, 0, 0, 0, 0, 0], [0, 1, 2, 0, 1, 2], [0, 1, 0, 1, 0, 1]], + ) + s = Series(np.random.default_rng(2).standard_normal(6), index=index) + exp_index = MultiIndex( + levels=[["one", "two", "three"], [0, 1]], + codes=[[0, 1, 2, 0, 1, 2], [0, 1, 0, 1, 0, 1]], + ) + expected = DataFrame({"bar": s.values}, index=exp_index).sort_index(level=0) + unstacked = s.unstack(0).sort_index() + tm.assert_frame_equal(unstacked, expected) + + # GH5873 + idx = MultiIndex.from_arrays([[101, 102], [3.5, np.nan]]) + ts = Series([1, 2], index=idx) + left = ts.unstack() + right = DataFrame( + [[np.nan, 1], [2, np.nan]], index=[101, 102], columns=[np.nan, 3.5] + ) + tm.assert_frame_equal(left, right) + + idx = MultiIndex.from_arrays( + [ + ["cat", "cat", "cat", "dog", "dog"], + ["a", "a", "b", "a", "b"], + [1, 2, 1, 1, np.nan], + ] + ) + ts = Series([1.0, 1.1, 1.2, 1.3, 1.4], index=idx) + right = DataFrame( + [[1.0, 1.3], [1.1, np.nan], [np.nan, 1.4], [1.2, np.nan]], + columns=["cat", "dog"], + ) + tpls = [("a", 1), ("a", 2), ("b", np.nan), ("b", 1)] + right.index = MultiIndex.from_tuples(tpls) + tm.assert_frame_equal(ts.unstack(level=0), right) + + +def test_unstack_tuplename_in_multiindex(): + # GH 19966 + idx = MultiIndex.from_product( + [["a", "b", "c"], [1, 2, 3]], names=[("A", "a"), ("B", "b")] + ) + ser = Series(1, index=idx) + result = ser.unstack(("A", "a")) + + expected = DataFrame( + [[1, 1, 1], [1, 1, 1], [1, 1, 1]], + columns=MultiIndex.from_tuples([("a",), ("b",), ("c",)], names=[("A", "a")]), + index=Index([1, 2, 3], name=("B", "b")), + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "unstack_idx, expected_values, expected_index, expected_columns", + [ + ( + ("A", "a"), + [[1, 1], [1, 1], [1, 1], [1, 1]], + MultiIndex.from_tuples([(1, 3), (1, 4), (2, 3), (2, 4)], names=["B", "C"]), + MultiIndex.from_tuples([("a",), ("b",)], names=[("A", "a")]), + ), + ( + (("A", "a"), "B"), + [[1, 1, 1, 1], [1, 1, 1, 1]], + Index([3, 4], name="C"), + MultiIndex.from_tuples( + [("a", 1), ("a", 2), ("b", 1), ("b", 2)], names=[("A", "a"), "B"] + ), + ), + ], +) +def test_unstack_mixed_type_name_in_multiindex( + unstack_idx, expected_values, expected_index, expected_columns +): + # GH 19966 + idx = MultiIndex.from_product( + [["a", "b"], [1, 2], [3, 4]], names=[("A", "a"), "B", "C"] + ) + ser = Series(1, index=idx) + result = ser.unstack(unstack_idx) + + expected = DataFrame( + expected_values, columns=expected_columns, index=expected_index + ) + tm.assert_frame_equal(result, expected) + + +def test_unstack_multi_index_categorical_values(): + df = DataFrame( + np.random.default_rng(2).standard_normal((10, 4)), + columns=Index(list("ABCD")), + index=date_range("2000-01-01", periods=10, freq="B"), + ) + mi = df.stack(future_stack=True).index.rename(["major", "minor"]) + ser = Series(["foo"] * len(mi), index=mi, name="category", dtype="category") + + result = ser.unstack() + + dti = ser.index.levels[0] + c = pd.Categorical(["foo"] * len(dti)) + expected = DataFrame( + {"A": c.copy(), "B": c.copy(), "C": c.copy(), "D": c.copy()}, + columns=Index(list("ABCD"), name="minor"), + index=dti.rename("major"), + ) + tm.assert_frame_equal(result, expected) + + +def test_unstack_mixed_level_names(): + # GH#48763 + arrays = [["a", "a"], [1, 2], ["red", "blue"]] + idx = MultiIndex.from_arrays(arrays, names=("x", 0, "y")) + ser = Series([1, 2], index=idx) + result = ser.unstack("x") + expected = DataFrame( + [[1], [2]], + columns=Index(["a"], name="x"), + index=MultiIndex.from_tuples([(1, "red"), (2, "blue")], names=[0, "y"]), + ) + tm.assert_frame_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_update.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_update.py new file mode 100644 index 0000000000000000000000000000000000000000..b09a58e04947fd5ce236e53b1516ca42ef00ffeb --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_update.py @@ -0,0 +1,143 @@ +import numpy as np +import pytest + +from pandas.compat import WARNING_CHECK_DISABLED +import pandas.util._test_decorators as td + +from pandas import ( + CategoricalDtype, + DataFrame, + NaT, + Series, + Timestamp, +) +import pandas._testing as tm + + +class TestUpdate: + def test_update(self, using_copy_on_write): + s = Series([1.5, np.nan, 3.0, 4.0, np.nan]) + s2 = Series([np.nan, 3.5, np.nan, 5.0]) + s.update(s2) + + expected = Series([1.5, 3.5, 3.0, 5.0, np.nan]) + tm.assert_series_equal(s, expected) + + # GH 3217 + df = DataFrame([{"a": 1}, {"a": 3, "b": 2}]) + df["c"] = np.nan + # Cast to object to avoid upcast when setting "foo" + df["c"] = df["c"].astype(object) + df_orig = df.copy() + + if using_copy_on_write: + with tm.raises_chained_assignment_error(): + df["c"].update(Series(["foo"], index=[0])) + expected = df_orig + else: + with tm.assert_produces_warning( + FutureWarning if not WARNING_CHECK_DISABLED else None, + match="inplace method", + ): + df["c"].update(Series(["foo"], index=[0])) + expected = DataFrame( + [[1, np.nan, "foo"], [3, 2.0, np.nan]], columns=["a", "b", "c"] + ) + expected["c"] = expected["c"].astype(object) + tm.assert_frame_equal(df, expected) + + @pytest.mark.parametrize( + "other, dtype, expected, warn", + [ + # other is int + ([61, 63], "int32", Series([10, 61, 12], dtype="int32"), None), + ([61, 63], "int64", Series([10, 61, 12]), None), + ([61, 63], float, Series([10.0, 61.0, 12.0]), None), + ([61, 63], object, Series([10, 61, 12], dtype=object), None), + # other is float, but can be cast to int + ([61.0, 63.0], "int32", Series([10, 61, 12], dtype="int32"), None), + ([61.0, 63.0], "int64", Series([10, 61, 12]), None), + ([61.0, 63.0], float, Series([10.0, 61.0, 12.0]), None), + ([61.0, 63.0], object, Series([10, 61.0, 12], dtype=object), None), + # others is float, cannot be cast to int + ([61.1, 63.1], "int32", Series([10.0, 61.1, 12.0]), FutureWarning), + ([61.1, 63.1], "int64", Series([10.0, 61.1, 12.0]), FutureWarning), + ([61.1, 63.1], float, Series([10.0, 61.1, 12.0]), None), + ([61.1, 63.1], object, Series([10, 61.1, 12], dtype=object), None), + # other is object, cannot be cast + ([(61,), (63,)], "int32", Series([10, (61,), 12]), FutureWarning), + ([(61,), (63,)], "int64", Series([10, (61,), 12]), FutureWarning), + ([(61,), (63,)], float, Series([10.0, (61,), 12.0]), FutureWarning), + ([(61,), (63,)], object, Series([10, (61,), 12]), None), + ], + ) + def test_update_dtypes(self, other, dtype, expected, warn): + ser = Series([10, 11, 12], dtype=dtype) + other = Series(other, index=[1, 3]) + with tm.assert_produces_warning(warn, match="item of incompatible dtype"): + ser.update(other) + + tm.assert_series_equal(ser, expected) + + @pytest.mark.parametrize( + "series, other, expected", + [ + # update by key + ( + Series({"a": 1, "b": 2, "c": 3, "d": 4}), + {"b": 5, "c": np.nan}, + Series({"a": 1, "b": 5, "c": 3, "d": 4}), + ), + # update by position + (Series([1, 2, 3, 4]), [np.nan, 5, 1], Series([1, 5, 1, 4])), + ], + ) + def test_update_from_non_series(self, series, other, expected): + # GH 33215 + series.update(other) + tm.assert_series_equal(series, expected) + + @pytest.mark.parametrize( + "data, other, expected, dtype", + [ + (["a", None], [None, "b"], ["a", "b"], "string[python]"), + pytest.param( + ["a", None], + [None, "b"], + ["a", "b"], + "string[pyarrow]", + marks=td.skip_if_no("pyarrow"), + ), + ([1, None], [None, 2], [1, 2], "Int64"), + ([True, None], [None, False], [True, False], "boolean"), + ( + ["a", None], + [None, "b"], + ["a", "b"], + CategoricalDtype(categories=["a", "b"]), + ), + ( + [Timestamp(year=2020, month=1, day=1, tz="Europe/London"), NaT], + [NaT, Timestamp(year=2020, month=1, day=1, tz="Europe/London")], + [Timestamp(year=2020, month=1, day=1, tz="Europe/London")] * 2, + "datetime64[ns, Europe/London]", + ), + ], + ) + def test_update_extension_array_series(self, data, other, expected, dtype): + result = Series(data, dtype=dtype) + other = Series(other, dtype=dtype) + expected = Series(expected, dtype=dtype) + + result.update(other) + tm.assert_series_equal(result, expected) + + def test_update_with_categorical_type(self): + # GH 25744 + dtype = CategoricalDtype(["a", "b", "c", "d"]) + s1 = Series(["a", "b", "c"], index=[1, 2, 3], dtype=dtype) + s2 = Series(["b", "a"], index=[1, 2], dtype=dtype) + s1.update(s2) + result = s1 + expected = Series(["b", "a", "c"], index=[1, 2, 3], dtype=dtype) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_value_counts.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_value_counts.py new file mode 100644 index 0000000000000000000000000000000000000000..859010d9c79c64fbac70f2f5eaa0033bddb4a0c2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_value_counts.py @@ -0,0 +1,271 @@ +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + Categorical, + CategoricalIndex, + Index, + Series, +) +import pandas._testing as tm + + +class TestSeriesValueCounts: + def test_value_counts_datetime(self, unit): + # most dtypes are tested in tests/base + values = [ + pd.Timestamp("2011-01-01 09:00"), + pd.Timestamp("2011-01-01 10:00"), + pd.Timestamp("2011-01-01 11:00"), + pd.Timestamp("2011-01-01 09:00"), + pd.Timestamp("2011-01-01 09:00"), + pd.Timestamp("2011-01-01 11:00"), + ] + + exp_idx = pd.DatetimeIndex( + ["2011-01-01 09:00", "2011-01-01 11:00", "2011-01-01 10:00"], + name="xxx", + ).as_unit(unit) + exp = Series([3, 2, 1], index=exp_idx, name="count") + + ser = Series(values, name="xxx").dt.as_unit(unit) + tm.assert_series_equal(ser.value_counts(), exp) + # check DatetimeIndex outputs the same result + idx = pd.DatetimeIndex(values, name="xxx").as_unit(unit) + tm.assert_series_equal(idx.value_counts(), exp) + + # normalize + exp = Series(np.array([3.0, 2.0, 1]) / 6.0, index=exp_idx, name="proportion") + tm.assert_series_equal(ser.value_counts(normalize=True), exp) + tm.assert_series_equal(idx.value_counts(normalize=True), exp) + + def test_value_counts_datetime_tz(self, unit): + values = [ + pd.Timestamp("2011-01-01 09:00", tz="US/Eastern"), + pd.Timestamp("2011-01-01 10:00", tz="US/Eastern"), + pd.Timestamp("2011-01-01 11:00", tz="US/Eastern"), + pd.Timestamp("2011-01-01 09:00", tz="US/Eastern"), + pd.Timestamp("2011-01-01 09:00", tz="US/Eastern"), + pd.Timestamp("2011-01-01 11:00", tz="US/Eastern"), + ] + + exp_idx = pd.DatetimeIndex( + ["2011-01-01 09:00", "2011-01-01 11:00", "2011-01-01 10:00"], + tz="US/Eastern", + name="xxx", + ).as_unit(unit) + exp = Series([3, 2, 1], index=exp_idx, name="count") + + ser = Series(values, name="xxx").dt.as_unit(unit) + tm.assert_series_equal(ser.value_counts(), exp) + idx = pd.DatetimeIndex(values, name="xxx").as_unit(unit) + tm.assert_series_equal(idx.value_counts(), exp) + + exp = Series(np.array([3.0, 2.0, 1]) / 6.0, index=exp_idx, name="proportion") + tm.assert_series_equal(ser.value_counts(normalize=True), exp) + tm.assert_series_equal(idx.value_counts(normalize=True), exp) + + def test_value_counts_period(self): + values = [ + pd.Period("2011-01", freq="M"), + pd.Period("2011-02", freq="M"), + pd.Period("2011-03", freq="M"), + pd.Period("2011-01", freq="M"), + pd.Period("2011-01", freq="M"), + pd.Period("2011-03", freq="M"), + ] + + exp_idx = pd.PeriodIndex( + ["2011-01", "2011-03", "2011-02"], freq="M", name="xxx" + ) + exp = Series([3, 2, 1], index=exp_idx, name="count") + + ser = Series(values, name="xxx") + tm.assert_series_equal(ser.value_counts(), exp) + # check DatetimeIndex outputs the same result + idx = pd.PeriodIndex(values, name="xxx") + tm.assert_series_equal(idx.value_counts(), exp) + + # normalize + exp = Series(np.array([3.0, 2.0, 1]) / 6.0, index=exp_idx, name="proportion") + tm.assert_series_equal(ser.value_counts(normalize=True), exp) + tm.assert_series_equal(idx.value_counts(normalize=True), exp) + + def test_value_counts_categorical_ordered(self): + # most dtypes are tested in tests/base + values = Categorical([1, 2, 3, 1, 1, 3], ordered=True) + + exp_idx = CategoricalIndex( + [1, 3, 2], categories=[1, 2, 3], ordered=True, name="xxx" + ) + exp = Series([3, 2, 1], index=exp_idx, name="count") + + ser = Series(values, name="xxx") + tm.assert_series_equal(ser.value_counts(), exp) + # check CategoricalIndex outputs the same result + idx = CategoricalIndex(values, name="xxx") + tm.assert_series_equal(idx.value_counts(), exp) + + # normalize + exp = Series(np.array([3.0, 2.0, 1]) / 6.0, index=exp_idx, name="proportion") + tm.assert_series_equal(ser.value_counts(normalize=True), exp) + tm.assert_series_equal(idx.value_counts(normalize=True), exp) + + def test_value_counts_categorical_not_ordered(self): + values = Categorical([1, 2, 3, 1, 1, 3], ordered=False) + + exp_idx = CategoricalIndex( + [1, 3, 2], categories=[1, 2, 3], ordered=False, name="xxx" + ) + exp = Series([3, 2, 1], index=exp_idx, name="count") + + ser = Series(values, name="xxx") + tm.assert_series_equal(ser.value_counts(), exp) + # check CategoricalIndex outputs the same result + idx = CategoricalIndex(values, name="xxx") + tm.assert_series_equal(idx.value_counts(), exp) + + # normalize + exp = Series(np.array([3.0, 2.0, 1]) / 6.0, index=exp_idx, name="proportion") + tm.assert_series_equal(ser.value_counts(normalize=True), exp) + tm.assert_series_equal(idx.value_counts(normalize=True), exp) + + def test_value_counts_categorical(self): + # GH#12835 + cats = Categorical(list("abcccb"), categories=list("cabd")) + ser = Series(cats, name="xxx") + res = ser.value_counts(sort=False) + + exp_index = CategoricalIndex( + list("cabd"), categories=cats.categories, name="xxx" + ) + exp = Series([3, 1, 2, 0], name="count", index=exp_index) + tm.assert_series_equal(res, exp) + + res = ser.value_counts(sort=True) + + exp_index = CategoricalIndex( + list("cbad"), categories=cats.categories, name="xxx" + ) + exp = Series([3, 2, 1, 0], name="count", index=exp_index) + tm.assert_series_equal(res, exp) + + # check object dtype handles the Series.name as the same + # (tested in tests/base) + ser = Series(["a", "b", "c", "c", "c", "b"], name="xxx") + res = ser.value_counts() + exp = Series([3, 2, 1], name="count", index=Index(["c", "b", "a"], name="xxx")) + tm.assert_series_equal(res, exp) + + def test_value_counts_categorical_with_nan(self): + # see GH#9443 + + # sanity check + ser = Series(["a", "b", "a"], dtype="category") + exp = Series([2, 1], index=CategoricalIndex(["a", "b"]), name="count") + + res = ser.value_counts(dropna=True) + tm.assert_series_equal(res, exp) + + res = ser.value_counts(dropna=True) + tm.assert_series_equal(res, exp) + + # same Series via two different constructions --> same behaviour + series = [ + Series(["a", "b", None, "a", None, None], dtype="category"), + Series( + Categorical(["a", "b", None, "a", None, None], categories=["a", "b"]) + ), + ] + + for ser in series: + # None is a NaN value, so we exclude its count here + exp = Series([2, 1], index=CategoricalIndex(["a", "b"]), name="count") + res = ser.value_counts(dropna=True) + tm.assert_series_equal(res, exp) + + # we don't exclude the count of None and sort by counts + exp = Series( + [3, 2, 1], index=CategoricalIndex([np.nan, "a", "b"]), name="count" + ) + res = ser.value_counts(dropna=False) + tm.assert_series_equal(res, exp) + + # When we aren't sorting by counts, and np.nan isn't a + # category, it should be last. + exp = Series( + [2, 1, 3], index=CategoricalIndex(["a", "b", np.nan]), name="count" + ) + res = ser.value_counts(dropna=False, sort=False) + tm.assert_series_equal(res, exp) + + @pytest.mark.parametrize( + "ser, dropna, exp", + [ + ( + Series([False, True, True, pd.NA]), + False, + Series([2, 1, 1], index=[True, False, pd.NA], name="count"), + ), + ( + Series([False, True, True, pd.NA]), + True, + Series([2, 1], index=Index([True, False], dtype=object), name="count"), + ), + ( + Series(range(3), index=[True, False, np.nan]).index, + False, + Series([1, 1, 1], index=[True, False, np.nan], name="count"), + ), + ], + ) + def test_value_counts_bool_with_nan(self, ser, dropna, exp): + # GH32146 + out = ser.value_counts(dropna=dropna) + tm.assert_series_equal(out, exp) + + @pytest.mark.parametrize( + "input_array,expected", + [ + ( + [1 + 1j, 1 + 1j, 1, 3j, 3j, 3j], + Series( + [3, 2, 1], + index=Index([3j, 1 + 1j, 1], dtype=np.complex128), + name="count", + ), + ), + ( + np.array([1 + 1j, 1 + 1j, 1, 3j, 3j, 3j], dtype=np.complex64), + Series( + [3, 2, 1], + index=Index([3j, 1 + 1j, 1], dtype=np.complex64), + name="count", + ), + ), + ], + ) + def test_value_counts_complex_numbers(self, input_array, expected): + # GH 17927 + result = Series(input_array).value_counts() + tm.assert_series_equal(result, expected) + + def test_value_counts_masked(self): + # GH#54984 + dtype = "Int64" + ser = Series([1, 2, None, 2, None, 3], dtype=dtype) + result = ser.value_counts(dropna=False) + expected = Series( + [2, 2, 1, 1], + index=Index([2, None, 1, 3], dtype=dtype), + dtype=dtype, + name="count", + ) + tm.assert_series_equal(result, expected) + + result = ser.value_counts(dropna=True) + expected = Series( + [2, 1, 1], index=Index([2, 1, 3], dtype=dtype), dtype=dtype, name="count" + ) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_values.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_values.py new file mode 100644 index 0000000000000000000000000000000000000000..cb1595e68264fbe5f07b014be4975657fa2fa8cf --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_values.py @@ -0,0 +1,29 @@ +import numpy as np +import pytest + +from pandas import ( + IntervalIndex, + Series, + period_range, +) +import pandas._testing as tm + + +class TestValues: + @pytest.mark.parametrize( + "data", + [ + period_range("2000", periods=4), + IntervalIndex.from_breaks([1, 2, 3, 4]), + ], + ) + def test_values_object_extension_dtypes(self, data): + # https://github.com/pandas-dev/pandas/issues/23995 + result = Series(data).values + expected = np.array(data.astype(object)) + tm.assert_numpy_array_equal(result, expected) + + def test_values(self, datetime_series): + tm.assert_almost_equal( + datetime_series.values, list(datetime_series), check_dtype=False + ) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_view.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_view.py new file mode 100644 index 0000000000000000000000000000000000000000..7e0ac372cd443cf9a468b469df1c22818f10aad2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/series/methods/test_view.py @@ -0,0 +1,61 @@ +import numpy as np +import pytest + +from pandas import ( + Index, + Series, + array, + date_range, +) +import pandas._testing as tm + +pytestmark = pytest.mark.filterwarnings( + "ignore:Series.view is deprecated and will be removed in a future version.:FutureWarning" # noqa: E501 +) + + +class TestView: + def test_view_i8_to_datetimelike(self): + dti = date_range("2000", periods=4, tz="US/Central") + ser = Series(dti.asi8) + + result = ser.view(dti.dtype) + tm.assert_datetime_array_equal(result._values, dti._data._with_freq(None)) + + pi = dti.tz_localize(None).to_period("D") + ser = Series(pi.asi8) + result = ser.view(pi.dtype) + tm.assert_period_array_equal(result._values, pi._data) + + def test_view_tz(self): + # GH#24024 + ser = Series(date_range("2000", periods=4, tz="US/Central")) + result = ser.view("i8") + expected = Series( + [ + 946706400000000000, + 946792800000000000, + 946879200000000000, + 946965600000000000, + ] + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "first", ["m8[ns]", "M8[ns]", "M8[ns, US/Central]", "period[D]"] + ) + @pytest.mark.parametrize( + "second", ["m8[ns]", "M8[ns]", "M8[ns, US/Central]", "period[D]"] + ) + @pytest.mark.parametrize("box", [Series, Index, array]) + def test_view_between_datetimelike(self, first, second, box): + dti = date_range("2016-01-01", periods=3) + + orig = box(dti) + obj = orig.view(first) + assert obj.dtype == first + tm.assert_numpy_array_equal(np.asarray(obj.view("i8")), dti.asi8) + + res = obj.view(second) + assert res.dtype == second + tm.assert_numpy_array_equal(np.asarray(obj.view("i8")), dti.asi8) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..6c4bec6a2378932b9d49302a04b4f0f80a9e3e3b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/__init__.py @@ -0,0 +1,23 @@ +import numpy as np + +import pandas as pd + + +def is_object_or_nan_string_dtype(dtype): + """ + Check if string-like dtype is following NaN semantics, i.e. is object + dtype or a NaN-variant of the StringDtype. + """ + return (isinstance(dtype, np.dtype) and dtype == "object") or ( + dtype.na_value is np.nan + ) + + +def _convert_na_value(ser, expected): + if ser.dtype != object: + if ser.dtype.na_value is np.nan: + expected = expected.fillna(np.nan) + else: + # GH#18463 + expected = expected.fillna(pd.NA) + return expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/conftest.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/conftest.py new file mode 100644 index 0000000000000000000000000000000000000000..036e4de20ba538bc4dbe6636fc802fb9c8f10e5d --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/conftest.py @@ -0,0 +1,132 @@ +import pytest + +from pandas import Series +from pandas.core.strings.accessor import StringMethods + +_any_string_method = [ + ("cat", (), {"sep": ","}), + ("cat", (Series(list("zyx")),), {"sep": ",", "join": "left"}), + ("center", (10,), {}), + ("contains", ("a",), {}), + ("count", ("a",), {}), + ("decode", ("UTF-8",), {}), + ("encode", ("UTF-8",), {}), + ("endswith", ("a",), {}), + ("endswith", ((),), {}), + ("endswith", (("a",),), {}), + ("endswith", (("a", "b"),), {}), + ("endswith", (("a", "MISSING"),), {}), + ("endswith", ("a",), {"na": True}), + ("endswith", ("a",), {"na": False}), + ("extract", ("([a-z]*)",), {"expand": False}), + ("extract", ("([a-z]*)",), {"expand": True}), + ("extractall", ("([a-z]*)",), {}), + ("find", ("a",), {}), + ("findall", ("a",), {}), + ("get", (0,), {}), + # because "index" (and "rindex") fail intentionally + # if the string is not found, search only for empty string + ("index", ("",), {}), + ("join", (",",), {}), + ("ljust", (10,), {}), + ("match", ("a",), {}), + ("fullmatch", ("a",), {}), + ("normalize", ("NFC",), {}), + ("pad", (10,), {}), + ("partition", (" ",), {"expand": False}), + ("partition", (" ",), {"expand": True}), + ("repeat", (3,), {}), + ("replace", ("a", "z"), {}), + ("rfind", ("a",), {}), + ("rindex", ("",), {}), + ("rjust", (10,), {}), + ("rpartition", (" ",), {"expand": False}), + ("rpartition", (" ",), {"expand": True}), + ("slice", (0, 1), {}), + ("slice_replace", (0, 1, "z"), {}), + ("split", (" ",), {"expand": False}), + ("split", (" ",), {"expand": True}), + ("startswith", ("a",), {}), + ("startswith", (("a",),), {}), + ("startswith", (("a", "b"),), {}), + ("startswith", (("a", "MISSING"),), {}), + ("startswith", ((),), {}), + ("startswith", ("a",), {"na": True}), + ("startswith", ("a",), {"na": False}), + ("removeprefix", ("a",), {}), + ("removesuffix", ("a",), {}), + # translating unicode points of "a" to "d" + ("translate", ({97: 100},), {}), + ("wrap", (2,), {}), + ("zfill", (10,), {}), +] + list( + zip( + [ + # methods without positional arguments: zip with empty tuple and empty dict + "capitalize", + "cat", + "get_dummies", + "isalnum", + "isalpha", + "isdecimal", + "isdigit", + "islower", + "isnumeric", + "isspace", + "istitle", + "isupper", + "len", + "lower", + "lstrip", + "partition", + "rpartition", + "rsplit", + "rstrip", + "slice", + "slice_replace", + "split", + "strip", + "swapcase", + "title", + "upper", + "casefold", + ], + [()] * 100, + [{}] * 100, + ) +) +ids, _, _ = zip(*_any_string_method) # use method name as fixture-id +missing_methods = {f for f in dir(StringMethods) if not f.startswith("_")} - set(ids) + +# test that the above list captures all methods of StringMethods +assert not missing_methods + + +@pytest.fixture(params=_any_string_method, ids=ids) +def any_string_method(request): + """ + Fixture for all public methods of `StringMethods` + + This fixture returns a tuple of the method name and sample arguments + necessary to call the method. + + Returns + ------- + method_name : str + The name of the method in `StringMethods` + args : tuple + Sample values for the positional arguments + kwargs : dict + Sample values for the keyword arguments + + Examples + -------- + >>> def test_something(any_string_method): + ... s = Series(['a', 'b', np.nan, 'd']) + ... + ... method_name, args, kwargs = any_string_method + ... method = getattr(s.str, method_name) + ... # will not raise + ... method(*args, **kwargs) + """ + return request.param diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_api.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_api.py new file mode 100644 index 0000000000000000000000000000000000000000..8987fc36656c591ce865562a65497e72bbac1ab0 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_api.py @@ -0,0 +1,205 @@ +import numpy as np +import pytest + +from pandas import ( + CategoricalDtype, + DataFrame, + Index, + MultiIndex, + Series, + _testing as tm, + option_context, +) +from pandas.core.strings.accessor import StringMethods + +# subset of the full set from pandas/conftest.py +_any_allowed_skipna_inferred_dtype = [ + ("string", ["a", np.nan, "c"]), + ("bytes", [b"a", np.nan, b"c"]), + ("empty", [np.nan, np.nan, np.nan]), + ("empty", []), + ("mixed-integer", ["a", np.nan, 2]), +] +ids, _ = zip(*_any_allowed_skipna_inferred_dtype) # use inferred type as id + + +@pytest.fixture(params=_any_allowed_skipna_inferred_dtype, ids=ids) +def any_allowed_skipna_inferred_dtype(request): + """ + Fixture for all (inferred) dtypes allowed in StringMethods.__init__ + + The covered (inferred) types are: + * 'string' + * 'empty' + * 'bytes' + * 'mixed' + * 'mixed-integer' + + Returns + ------- + inferred_dtype : str + The string for the inferred dtype from _libs.lib.infer_dtype + values : np.ndarray + An array of object dtype that will be inferred to have + `inferred_dtype` + + Examples + -------- + >>> from pandas._libs import lib + >>> + >>> def test_something(any_allowed_skipna_inferred_dtype): + ... inferred_dtype, values = any_allowed_skipna_inferred_dtype + ... # will pass + ... assert lib.infer_dtype(values, skipna=True) == inferred_dtype + ... + ... # constructor for .str-accessor will also pass + ... Series(values).str + """ + inferred_dtype, values = request.param + values = np.array(values, dtype=object) # object dtype to avoid casting + + # correctness of inference tested in tests/dtypes/test_inference.py + return inferred_dtype, values + + +def test_api(any_string_dtype): + # GH 6106, GH 9322 + assert Series.str is StringMethods + assert isinstance(Series([""], dtype=any_string_dtype).str, StringMethods) + + +def test_api_mi_raises(): + # GH 23679 + mi = MultiIndex.from_arrays([["a", "b", "c"]]) + msg = "Can only use .str accessor with Index, not MultiIndex" + with pytest.raises(AttributeError, match=msg): + mi.str + assert not hasattr(mi, "str") + + +@pytest.mark.parametrize("dtype", [object, "category"]) +def test_api_per_dtype(index_or_series, dtype, any_skipna_inferred_dtype): + # one instance of parametrized fixture + box = index_or_series + inferred_dtype, values = any_skipna_inferred_dtype + + t = box(values, dtype=dtype) # explicit dtype to avoid casting + + types_passing_constructor = [ + "string", + "unicode", + "empty", + "bytes", + "mixed", + "mixed-integer", + ] + if inferred_dtype in types_passing_constructor: + # GH 6106 + assert isinstance(t.str, StringMethods) + else: + # GH 9184, GH 23011, GH 23163 + msg = "Can only use .str accessor with string values.*" + with pytest.raises(AttributeError, match=msg): + t.str + assert not hasattr(t, "str") + + +@pytest.mark.parametrize("dtype", [object, "category"]) +def test_api_per_method( + index_or_series, + dtype, + any_allowed_skipna_inferred_dtype, + any_string_method, + request, + using_infer_string, +): + # this test does not check correctness of the different methods, + # just that the methods work on the specified (inferred) dtypes, + # and raise on all others + box = index_or_series + + # one instance of each parametrized fixture + inferred_dtype, values = any_allowed_skipna_inferred_dtype + method_name, args, kwargs = any_string_method + + reason = None + if box is Index and values.size == 0: + if method_name in ["partition", "rpartition"] and kwargs.get("expand", True): + raises = TypeError + reason = "Method cannot deal with empty Index" + elif method_name == "split" and kwargs.get("expand", None): + raises = TypeError + reason = "Split fails on empty Series when expand=True" + elif method_name == "get_dummies": + raises = ValueError + reason = "Need to fortify get_dummies corner cases" + + elif ( + box is Index + and inferred_dtype == "empty" + and dtype == object + and method_name == "get_dummies" + ): + raises = ValueError + reason = "Need to fortify get_dummies corner cases" + + if reason is not None: + mark = pytest.mark.xfail(raises=raises, reason=reason) + request.applymarker(mark) + + t = box(values, dtype=dtype) # explicit dtype to avoid casting + method = getattr(t.str, method_name) + + if using_infer_string and dtype == "category": + string_allowed = method_name not in ["decode"] + else: + string_allowed = True + bytes_allowed = method_name in ["decode", "get", "len", "slice"] + # as of v0.23.4, all methods except 'cat' are very lenient with the + # allowed data types, just returning NaN for entries that error. + # This could be changed with an 'errors'-kwarg to the `str`-accessor, + # see discussion in GH 13877 + mixed_allowed = method_name not in ["cat"] + + allowed_types = ( + ["empty"] + + ["string", "unicode"] * string_allowed + + ["bytes"] * bytes_allowed + + ["mixed", "mixed-integer"] * mixed_allowed + ) + + if inferred_dtype in allowed_types: + # xref GH 23555, GH 23556 + with option_context("future.no_silent_downcasting", True): + method(*args, **kwargs) # works! + else: + # GH 23011, GH 23163 + msg = ( + f"Cannot use .str.{method_name} with values of " + f"inferred dtype {repr(inferred_dtype)}." + "|a bytes-like object is required, not 'str'" + ) + with pytest.raises(TypeError, match=msg): + method(*args, **kwargs) + + +def test_api_for_categorical(any_string_method, any_string_dtype): + # https://github.com/pandas-dev/pandas/issues/10661 + s = Series(list("aabb"), dtype=any_string_dtype) + s = s + " " + s + c = s.astype("category") + c = c.astype(CategoricalDtype(c.dtype.categories.astype("object"))) + assert isinstance(c.str, StringMethods) + + method_name, args, kwargs = any_string_method + + result = getattr(c.str, method_name)(*args, **kwargs) + expected = getattr(s.astype("object").str, method_name)(*args, **kwargs) + + if isinstance(result, DataFrame): + tm.assert_frame_equal(result, expected) + elif isinstance(result, Series): + tm.assert_series_equal(result, expected) + else: + # str.cat(others=None) returns string, for example + assert result == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_case_justify.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_case_justify.py new file mode 100644 index 0000000000000000000000000000000000000000..819556f961fa39fa2e93388fd12d37b0f9aefa4d --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_case_justify.py @@ -0,0 +1,423 @@ +from datetime import datetime +import operator + +import numpy as np +import pytest + +from pandas import ( + Series, + _testing as tm, +) + + +def test_title(any_string_dtype): + s = Series(["FOO", "BAR", np.nan, "Blah", "blurg"], dtype=any_string_dtype) + result = s.str.title() + expected = Series(["Foo", "Bar", np.nan, "Blah", "Blurg"], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_title_mixed_object(): + s = Series(["FOO", np.nan, "bar", True, datetime.today(), "blah", None, 1, 2.0]) + result = s.str.title() + expected = Series( + ["Foo", np.nan, "Bar", np.nan, np.nan, "Blah", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_almost_equal(result, expected) + + +def test_lower_upper(any_string_dtype): + s = Series(["om", np.nan, "nom", "nom"], dtype=any_string_dtype) + + result = s.str.upper() + expected = Series(["OM", np.nan, "NOM", "NOM"], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + result = result.str.lower() + tm.assert_series_equal(result, s) + + +def test_lower_upper_mixed_object(): + s = Series(["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0]) + + result = s.str.upper() + expected = Series( + ["A", np.nan, "B", np.nan, np.nan, "FOO", None, np.nan, np.nan], dtype=object + ) + tm.assert_series_equal(result, expected) + + result = s.str.lower() + expected = Series( + ["a", np.nan, "b", np.nan, np.nan, "foo", None, np.nan, np.nan], dtype=object + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "data, expected", + [ + ( + ["FOO", "BAR", np.nan, "Blah", "blurg"], + ["Foo", "Bar", np.nan, "Blah", "Blurg"], + ), + (["a", "b", "c"], ["A", "B", "C"]), + (["a b", "a bc. de"], ["A b", "A bc. de"]), + ], +) +def test_capitalize(data, expected, any_string_dtype): + s = Series(data, dtype=any_string_dtype) + result = s.str.capitalize() + expected = Series(expected, dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_capitalize_mixed_object(): + s = Series(["FOO", np.nan, "bar", True, datetime.today(), "blah", None, 1, 2.0]) + result = s.str.capitalize() + expected = Series( + ["Foo", np.nan, "Bar", np.nan, np.nan, "Blah", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + +def test_swapcase(any_string_dtype): + s = Series(["FOO", "BAR", np.nan, "Blah", "blurg"], dtype=any_string_dtype) + result = s.str.swapcase() + expected = Series(["foo", "bar", np.nan, "bLAH", "BLURG"], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_swapcase_mixed_object(): + s = Series(["FOO", np.nan, "bar", True, datetime.today(), "Blah", None, 1, 2.0]) + result = s.str.swapcase() + expected = Series( + ["foo", np.nan, "BAR", np.nan, np.nan, "bLAH", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + +def test_casefold(): + # GH25405 + expected = Series(["ss", np.nan, "case", "ssd"]) + s = Series(["ß", np.nan, "case", "ßd"]) + result = s.str.casefold() + + tm.assert_series_equal(result, expected) + + +def test_casemethods(any_string_dtype): + values = ["aaa", "bbb", "CCC", "Dddd", "eEEE"] + s = Series(values, dtype=any_string_dtype) + assert s.str.lower().tolist() == [v.lower() for v in values] + assert s.str.upper().tolist() == [v.upper() for v in values] + assert s.str.title().tolist() == [v.title() for v in values] + assert s.str.capitalize().tolist() == [v.capitalize() for v in values] + assert s.str.swapcase().tolist() == [v.swapcase() for v in values] + + +def test_pad(any_string_dtype): + s = Series(["a", "b", np.nan, "c", np.nan, "eeeeee"], dtype=any_string_dtype) + + result = s.str.pad(5, side="left") + expected = Series( + [" a", " b", np.nan, " c", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + result = s.str.pad(5, side="right") + expected = Series( + ["a ", "b ", np.nan, "c ", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + result = s.str.pad(5, side="both") + expected = Series( + [" a ", " b ", np.nan, " c ", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + +def test_pad_mixed_object(): + s = Series(["a", np.nan, "b", True, datetime.today(), "ee", None, 1, 2.0]) + + result = s.str.pad(5, side="left") + expected = Series( + [" a", np.nan, " b", np.nan, np.nan, " ee", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + result = s.str.pad(5, side="right") + expected = Series( + ["a ", np.nan, "b ", np.nan, np.nan, "ee ", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + result = s.str.pad(5, side="both") + expected = Series( + [" a ", np.nan, " b ", np.nan, np.nan, " ee ", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + +def test_pad_fillchar(any_string_dtype): + s = Series(["a", "b", np.nan, "c", np.nan, "eeeeee"], dtype=any_string_dtype) + + result = s.str.pad(5, side="left", fillchar="X") + expected = Series( + ["XXXXa", "XXXXb", np.nan, "XXXXc", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + result = s.str.pad(5, side="right", fillchar="X") + expected = Series( + ["aXXXX", "bXXXX", np.nan, "cXXXX", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + result = s.str.pad(5, side="both", fillchar="X") + expected = Series( + ["XXaXX", "XXbXX", np.nan, "XXcXX", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + +def test_pad_fillchar_bad_arg_raises(any_string_dtype): + s = Series(["a", "b", np.nan, "c", np.nan, "eeeeee"], dtype=any_string_dtype) + + msg = "fillchar must be a character, not str" + with pytest.raises(TypeError, match=msg): + s.str.pad(5, fillchar="XY") + + msg = "fillchar must be a character, not int" + with pytest.raises(TypeError, match=msg): + s.str.pad(5, fillchar=5) + + +@pytest.mark.parametrize("method_name", ["center", "ljust", "rjust", "zfill", "pad"]) +def test_pad_width_bad_arg_raises(method_name, any_string_dtype): + # see gh-13598 + s = Series(["1", "22", "a", "bb"], dtype=any_string_dtype) + op = operator.methodcaller(method_name, "f") + + msg = "width must be of integer type, not str" + with pytest.raises(TypeError, match=msg): + op(s.str) + + +def test_center_ljust_rjust(any_string_dtype): + s = Series(["a", "b", np.nan, "c", np.nan, "eeeeee"], dtype=any_string_dtype) + + result = s.str.center(5) + expected = Series( + [" a ", " b ", np.nan, " c ", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + result = s.str.ljust(5) + expected = Series( + ["a ", "b ", np.nan, "c ", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + result = s.str.rjust(5) + expected = Series( + [" a", " b", np.nan, " c", np.nan, "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + +def test_center_ljust_rjust_mixed_object(): + s = Series(["a", np.nan, "b", True, datetime.today(), "c", "eee", None, 1, 2.0]) + + result = s.str.center(5) + expected = Series( + [ + " a ", + np.nan, + " b ", + np.nan, + np.nan, + " c ", + " eee ", + None, + np.nan, + np.nan, + ], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + result = s.str.ljust(5) + expected = Series( + [ + "a ", + np.nan, + "b ", + np.nan, + np.nan, + "c ", + "eee ", + None, + np.nan, + np.nan, + ], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + result = s.str.rjust(5) + expected = Series( + [ + " a", + np.nan, + " b", + np.nan, + np.nan, + " c", + " eee", + None, + np.nan, + np.nan, + ], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + +def test_center_ljust_rjust_fillchar(any_string_dtype): + # GH#54533, GH#54792 + s = Series(["a", "bb", "cccc", "ddddd", "eeeeee"], dtype=any_string_dtype) + + result = s.str.center(5, fillchar="X") + expected = Series( + ["XXaXX", "XXbbX", "Xcccc", "ddddd", "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + expected = np.array([v.center(5, "X") for v in np.array(s)], dtype=np.object_) + tm.assert_numpy_array_equal(np.array(result, dtype=np.object_), expected) + + result = s.str.ljust(5, fillchar="X") + expected = Series( + ["aXXXX", "bbXXX", "ccccX", "ddddd", "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + expected = np.array([v.ljust(5, "X") for v in np.array(s)], dtype=np.object_) + tm.assert_numpy_array_equal(np.array(result, dtype=np.object_), expected) + + result = s.str.rjust(5, fillchar="X") + expected = Series( + ["XXXXa", "XXXbb", "Xcccc", "ddddd", "eeeeee"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + expected = np.array([v.rjust(5, "X") for v in np.array(s)], dtype=np.object_) + tm.assert_numpy_array_equal(np.array(result, dtype=np.object_), expected) + + +def test_center_ljust_rjust_fillchar_bad_arg_raises(any_string_dtype): + s = Series(["a", "bb", "cccc", "ddddd", "eeeeee"], dtype=any_string_dtype) + + # If fillchar is not a character, normal str raises TypeError + # 'aaa'.ljust(5, 'XY') + # TypeError: must be char, not str + template = "fillchar must be a character, not {dtype}" + + with pytest.raises(TypeError, match=template.format(dtype="str")): + s.str.center(5, fillchar="XY") + + with pytest.raises(TypeError, match=template.format(dtype="str")): + s.str.ljust(5, fillchar="XY") + + with pytest.raises(TypeError, match=template.format(dtype="str")): + s.str.rjust(5, fillchar="XY") + + with pytest.raises(TypeError, match=template.format(dtype="int")): + s.str.center(5, fillchar=1) + + with pytest.raises(TypeError, match=template.format(dtype="int")): + s.str.ljust(5, fillchar=1) + + with pytest.raises(TypeError, match=template.format(dtype="int")): + s.str.rjust(5, fillchar=1) + + +def test_zfill(any_string_dtype): + s = Series(["1", "22", "aaa", "333", "45678"], dtype=any_string_dtype) + + result = s.str.zfill(5) + expected = Series( + ["00001", "00022", "00aaa", "00333", "45678"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + expected = np.array([v.zfill(5) for v in np.array(s)], dtype=np.object_) + tm.assert_numpy_array_equal(np.array(result, dtype=np.object_), expected) + + result = s.str.zfill(3) + expected = Series(["001", "022", "aaa", "333", "45678"], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + expected = np.array([v.zfill(3) for v in np.array(s)], dtype=np.object_) + tm.assert_numpy_array_equal(np.array(result, dtype=np.object_), expected) + + s = Series(["1", np.nan, "aaa", np.nan, "45678"], dtype=any_string_dtype) + result = s.str.zfill(5) + expected = Series( + ["00001", np.nan, "00aaa", np.nan, "45678"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + +def test_wrap(any_string_dtype): + # test values are: two words less than width, two words equal to width, + # two words greater than width, one word less than width, one word + # equal to width, one word greater than width, multiple tokens with + # trailing whitespace equal to width + s = Series( + [ + "hello world", + "hello world!", + "hello world!!", + "abcdefabcde", + "abcdefabcdef", + "abcdefabcdefa", + "ab ab ab ab ", + "ab ab ab ab a", + "\t", + ], + dtype=any_string_dtype, + ) + + # expected values + expected = Series( + [ + "hello world", + "hello world!", + "hello\nworld!!", + "abcdefabcde", + "abcdefabcdef", + "abcdefabcdef\na", + "ab ab ab ab", + "ab ab ab ab\na", + "", + ], + dtype=any_string_dtype, + ) + + result = s.str.wrap(12, break_long_words=True) + tm.assert_series_equal(result, expected) + + +def test_wrap_unicode(any_string_dtype): + # test with pre and post whitespace (non-unicode), NaN, and non-ascii Unicode + s = Series( + [" pre ", np.nan, "\xac\u20ac\U00008000 abadcafe"], dtype=any_string_dtype + ) + expected = Series( + [" pre", np.nan, "\xac\u20ac\U00008000 ab\nadcafe"], dtype=any_string_dtype + ) + result = s.str.wrap(6) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_cat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_cat.py new file mode 100644 index 0000000000000000000000000000000000000000..c1e7ad6e02779259f37bd6bad57f03428d9c3055 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_cat.py @@ -0,0 +1,427 @@ +import re + +import numpy as np +import pytest + +import pandas.util._test_decorators as td + +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + _testing as tm, + concat, + option_context, +) + + +@pytest.mark.parametrize("other", [None, Series, Index]) +def test_str_cat_name(index_or_series, other): + # GH 21053 + box = index_or_series + values = ["a", "b"] + if other: + other = other(values) + else: + other = values + result = box(values, name="name").str.cat(other, sep=",") + assert result.name == "name" + + +@pytest.mark.parametrize( + "infer_string", [False, pytest.param(True, marks=td.skip_if_no("pyarrow"))] +) +def test_str_cat(index_or_series, infer_string): + with option_context("future.infer_string", infer_string): + box = index_or_series + # test_cat above tests "str_cat" from ndarray; + # here testing "str.cat" from Series/Index to ndarray/list + s = box(["a", "a", "b", "b", "c", np.nan]) + + # single array + result = s.str.cat() + expected = "aabbc" + assert result == expected + + result = s.str.cat(na_rep="-") + expected = "aabbc-" + assert result == expected + + result = s.str.cat(sep="_", na_rep="NA") + expected = "a_a_b_b_c_NA" + assert result == expected + + t = np.array(["a", np.nan, "b", "d", "foo", np.nan], dtype=object) + expected = box(["aa", "a-", "bb", "bd", "cfoo", "--"]) + + # Series/Index with array + result = s.str.cat(t, na_rep="-") + tm.assert_equal(result, expected) + + # Series/Index with list + result = s.str.cat(list(t), na_rep="-") + tm.assert_equal(result, expected) + + # errors for incorrect lengths + rgx = r"If `others` contains arrays or lists \(or other list-likes.*" + z = Series(["1", "2", "3"]) + + with pytest.raises(ValueError, match=rgx): + s.str.cat(z.values) + + with pytest.raises(ValueError, match=rgx): + s.str.cat(list(z)) + + +def test_str_cat_raises_intuitive_error(index_or_series): + # GH 11334 + box = index_or_series + s = box(["a", "b", "c", "d"]) + message = "Did you mean to supply a `sep` keyword?" + with pytest.raises(ValueError, match=message): + s.str.cat("|") + with pytest.raises(ValueError, match=message): + s.str.cat(" ") + + +@pytest.mark.parametrize( + "infer_string", [False, pytest.param(True, marks=td.skip_if_no("pyarrow"))] +) +@pytest.mark.parametrize("sep", ["", None]) +@pytest.mark.parametrize("dtype_target", ["object", "category"]) +@pytest.mark.parametrize("dtype_caller", ["object", "category"]) +def test_str_cat_categorical( + index_or_series, dtype_caller, dtype_target, sep, infer_string +): + box = index_or_series + + with option_context("future.infer_string", infer_string): + s = Index(["a", "a", "b", "a"], dtype=dtype_caller) + s = s if box == Index else Series(s, index=s, dtype=s.dtype) + t = Index(["b", "a", "b", "c"], dtype=dtype_target) + + expected = Index( + ["ab", "aa", "bb", "ac"], dtype=object if dtype_caller == "object" else None + ) + expected = ( + expected + if box == Index + else Series( + expected, index=Index(s, dtype=dtype_caller), dtype=expected.dtype + ) + ) + + # Series/Index with unaligned Index -> t.values + result = s.str.cat(t.values, sep=sep) + tm.assert_equal(result, expected) + + # Series/Index with Series having matching Index + t = Series(t.values, index=Index(s, dtype=dtype_caller)) + result = s.str.cat(t, sep=sep) + tm.assert_equal(result, expected) + + # Series/Index with Series.values + result = s.str.cat(t.values, sep=sep) + tm.assert_equal(result, expected) + + # Series/Index with Series having different Index + t = Series(t.values, index=t.values) + expected = Index( + ["aa", "aa", "bb", "bb", "aa"], + dtype=object if dtype_caller == "object" else None, + ) + dtype = object if dtype_caller == "object" else s.dtype.categories.dtype + expected = ( + expected + if box == Index + else Series( + expected, + index=Index(expected.str[:1], dtype=dtype), + dtype=expected.dtype, + ) + ) + + result = s.str.cat(t, sep=sep) + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "data", + [[1, 2, 3], [0.1, 0.2, 0.3], [1, 2, "b"]], + ids=["integers", "floats", "mixed"], +) +# without dtype=object, np.array would cast [1, 2, 'b'] to ['1', '2', 'b'] +@pytest.mark.parametrize( + "box", + [Series, Index, list, lambda x: np.array(x, dtype=object)], + ids=["Series", "Index", "list", "np.array"], +) +def test_str_cat_wrong_dtype_raises(box, data): + # GH 22722 + s = Series(["a", "b", "c"]) + t = box(data) + + msg = "Concatenation requires list-likes containing only strings.*" + with pytest.raises(TypeError, match=msg): + # need to use outer and na_rep, as otherwise Index would not raise + s.str.cat(t, join="outer", na_rep="-") + + +def test_str_cat_mixed_inputs(index_or_series): + box = index_or_series + s = Index(["a", "b", "c", "d"]) + s = s if box == Index else Series(s, index=s) + + t = Series(["A", "B", "C", "D"], index=s.values) + d = concat([t, Series(s, index=s)], axis=1) + + expected = Index(["aAa", "bBb", "cCc", "dDd"]) + expected = expected if box == Index else Series(expected.values, index=s.values) + + # Series/Index with DataFrame + result = s.str.cat(d) + tm.assert_equal(result, expected) + + # Series/Index with two-dimensional ndarray + result = s.str.cat(d.values) + tm.assert_equal(result, expected) + + # Series/Index with list of Series + result = s.str.cat([t, s]) + tm.assert_equal(result, expected) + + # Series/Index with mixed list of Series/array + result = s.str.cat([t, s.values]) + tm.assert_equal(result, expected) + + # Series/Index with list of Series; different indexes + t.index = ["b", "c", "d", "a"] + expected = box(["aDa", "bAb", "cBc", "dCd"]) + expected = expected if box == Index else Series(expected.values, index=s.values) + result = s.str.cat([t, s]) + tm.assert_equal(result, expected) + + # Series/Index with mixed list; different index + result = s.str.cat([t, s.values]) + tm.assert_equal(result, expected) + + # Series/Index with DataFrame; different indexes + d.index = ["b", "c", "d", "a"] + expected = box(["aDd", "bAa", "cBb", "dCc"]) + expected = expected if box == Index else Series(expected.values, index=s.values) + result = s.str.cat(d) + tm.assert_equal(result, expected) + + # errors for incorrect lengths + rgx = r"If `others` contains arrays or lists \(or other list-likes.*" + z = Series(["1", "2", "3"]) + e = concat([z, z], axis=1) + + # two-dimensional ndarray + with pytest.raises(ValueError, match=rgx): + s.str.cat(e.values) + + # list of list-likes + with pytest.raises(ValueError, match=rgx): + s.str.cat([z.values, s.values]) + + # mixed list of Series/list-like + with pytest.raises(ValueError, match=rgx): + s.str.cat([z.values, s]) + + # errors for incorrect arguments in list-like + rgx = "others must be Series, Index, DataFrame,.*" + # make sure None/NaN do not crash checks in _get_series_list + u = Series(["a", np.nan, "c", None]) + + # mix of string and Series + with pytest.raises(TypeError, match=rgx): + s.str.cat([u, "u"]) + + # DataFrame in list + with pytest.raises(TypeError, match=rgx): + s.str.cat([u, d]) + + # 2-dim ndarray in list + with pytest.raises(TypeError, match=rgx): + s.str.cat([u, d.values]) + + # nested lists + with pytest.raises(TypeError, match=rgx): + s.str.cat([u, [u, d]]) + + # forbidden input type: set + # GH 23009 + with pytest.raises(TypeError, match=rgx): + s.str.cat(set(u)) + + # forbidden input type: set in list + # GH 23009 + with pytest.raises(TypeError, match=rgx): + s.str.cat([u, set(u)]) + + # other forbidden input type, e.g. int + with pytest.raises(TypeError, match=rgx): + s.str.cat(1) + + # nested list-likes + with pytest.raises(TypeError, match=rgx): + s.str.cat(iter([t.values, list(s)])) + + +@pytest.mark.parametrize("join", ["left", "outer", "inner", "right"]) +def test_str_cat_align_indexed(index_or_series, join): + # https://github.com/pandas-dev/pandas/issues/18657 + box = index_or_series + + s = Series(["a", "b", "c", "d"], index=["a", "b", "c", "d"]) + t = Series(["D", "A", "E", "B"], index=["d", "a", "e", "b"]) + sa, ta = s.align(t, join=join) + # result after manual alignment of inputs + expected = sa.str.cat(ta, na_rep="-") + + if box == Index: + s = Index(s) + sa = Index(sa) + expected = Index(expected) + + result = s.str.cat(t, join=join, na_rep="-") + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize("join", ["left", "outer", "inner", "right"]) +def test_str_cat_align_mixed_inputs(join): + s = Series(["a", "b", "c", "d"]) + t = Series(["d", "a", "e", "b"], index=[3, 0, 4, 1]) + d = concat([t, t], axis=1) + + expected_outer = Series(["aaa", "bbb", "c--", "ddd", "-ee"]) + expected = expected_outer.loc[s.index.join(t.index, how=join)] + + # list of Series + result = s.str.cat([t, t], join=join, na_rep="-") + tm.assert_series_equal(result, expected) + + # DataFrame + result = s.str.cat(d, join=join, na_rep="-") + tm.assert_series_equal(result, expected) + + # mixed list of indexed/unindexed + u = np.array(["A", "B", "C", "D"]) + expected_outer = Series(["aaA", "bbB", "c-C", "ddD", "-e-"]) + # joint index of rhs [t, u]; u will be forced have index of s + rhs_idx = ( + t.index.intersection(s.index) + if join == "inner" + else t.index.union(s.index) + if join == "outer" + else t.index.append(s.index.difference(t.index)) + ) + + expected = expected_outer.loc[s.index.join(rhs_idx, how=join)] + result = s.str.cat([t, u], join=join, na_rep="-") + tm.assert_series_equal(result, expected) + + with pytest.raises(TypeError, match="others must be Series,.*"): + # nested lists are forbidden + s.str.cat([t, list(u)], join=join) + + # errors for incorrect lengths + rgx = r"If `others` contains arrays or lists \(or other list-likes.*" + z = Series(["1", "2", "3"]).values + + # unindexed object of wrong length + with pytest.raises(ValueError, match=rgx): + s.str.cat(z, join=join) + + # unindexed object of wrong length in list + with pytest.raises(ValueError, match=rgx): + s.str.cat([t, z], join=join) + + +def test_str_cat_all_na(index_or_series, index_or_series2): + # GH 24044 + box = index_or_series + other = index_or_series2 + + # check that all NaNs in caller / target work + s = Index(["a", "b", "c", "d"]) + s = s if box == Index else Series(s, index=s) + t = other([np.nan] * 4, dtype=object) + # add index of s for alignment + t = t if other == Index else Series(t, index=s) + + # all-NA target + if box == Series: + expected = Series([np.nan] * 4, index=s.index, dtype=s.dtype) + else: # box == Index + # TODO: Strimg option, this should return string dtype + expected = Index([np.nan] * 4, dtype=object) + result = s.str.cat(t, join="left") + tm.assert_equal(result, expected) + + # all-NA caller (only for Series) + if other == Series: + expected = Series([np.nan] * 4, dtype=object, index=t.index) + result = t.str.cat(s, join="left") + tm.assert_series_equal(result, expected) + + +def test_str_cat_special_cases(): + s = Series(["a", "b", "c", "d"]) + t = Series(["d", "a", "e", "b"], index=[3, 0, 4, 1]) + + # iterator of elements with different types + expected = Series(["aaa", "bbb", "c-c", "ddd", "-e-"]) + result = s.str.cat(iter([t, s.values]), join="outer", na_rep="-") + tm.assert_series_equal(result, expected) + + # right-align with different indexes in others + expected = Series(["aa-", "d-d"], index=[0, 3]) + result = s.str.cat([t.loc[[0]], t.loc[[3]]], join="right", na_rep="-") + tm.assert_series_equal(result, expected) + + +def test_cat_on_filtered_index(): + df = DataFrame( + index=MultiIndex.from_product( + [[2011, 2012], [1, 2, 3]], names=["year", "month"] + ) + ) + + df = df.reset_index() + df = df[df.month > 1] + + str_year = df.year.astype("str") + str_month = df.month.astype("str") + str_both = str_year.str.cat(str_month, sep=" ") + + assert str_both.loc[1] == "2011 2" + + str_multiple = str_year.str.cat([str_month, str_month], sep=" ") + + assert str_multiple.loc[1] == "2011 2 2" + + +@pytest.mark.parametrize("klass", [tuple, list, np.array, Series, Index]) +def test_cat_different_classes(klass): + # https://github.com/pandas-dev/pandas/issues/33425 + s = Series(["a", "b", "c"]) + result = s.str.cat(klass(["x", "y", "z"])) + expected = Series(["ax", "by", "cz"]) + tm.assert_series_equal(result, expected) + + +def test_cat_on_series_dot_str(): + # GH 28277 + ps = Series(["AbC", "de", "FGHI", "j", "kLLLm"]) + + message = re.escape( + "others must be Series, Index, DataFrame, np.ndarray " + "or list-like (either containing only strings or " + "containing only objects of type Series/Index/" + "np.ndarray[1-dim])" + ) + with pytest.raises(TypeError, match=message): + ps.str.cat(others=ps.str) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_extract.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_extract.py new file mode 100644 index 0000000000000000000000000000000000000000..77d008c650264889550ec70331a1b98064242d26 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_extract.py @@ -0,0 +1,724 @@ +from datetime import datetime +import re + +import numpy as np +import pytest + +from pandas.core.dtypes.dtypes import ArrowDtype + +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + _testing as tm, +) + + +def test_extract_expand_kwarg_wrong_type_raises(any_string_dtype): + # TODO: should this raise TypeError + values = Series(["fooBAD__barBAD", np.nan, "foo"], dtype=any_string_dtype) + with pytest.raises(ValueError, match="expand must be True or False"): + values.str.extract(".*(BAD[_]+).*(BAD)", expand=None) + + +def test_extract_expand_kwarg(any_string_dtype): + s = Series(["fooBAD__barBAD", np.nan, "foo"], dtype=any_string_dtype) + expected = DataFrame(["BAD__", np.nan, np.nan], dtype=any_string_dtype) + + result = s.str.extract(".*(BAD[_]+).*") + tm.assert_frame_equal(result, expected) + + result = s.str.extract(".*(BAD[_]+).*", expand=True) + tm.assert_frame_equal(result, expected) + + expected = DataFrame( + [["BAD__", "BAD"], [np.nan, np.nan], [np.nan, np.nan]], dtype=any_string_dtype + ) + result = s.str.extract(".*(BAD[_]+).*(BAD)", expand=False) + tm.assert_frame_equal(result, expected) + + +def test_extract_expand_False_mixed_object(): + ser = Series( + ["aBAD_BAD", np.nan, "BAD_b_BAD", True, datetime.today(), "foo", None, 1, 2.0] + ) + + # two groups + result = ser.str.extract(".*(BAD[_]+).*(BAD)", expand=False) + er = [np.nan, np.nan] # empty row + expected = DataFrame( + [["BAD_", "BAD"], er, ["BAD_", "BAD"], er, er, er, er, er, er], dtype=object + ) + tm.assert_frame_equal(result, expected) + + # single group + result = ser.str.extract(".*(BAD[_]+).*BAD", expand=False) + expected = Series( + ["BAD_", np.nan, "BAD_", np.nan, np.nan, np.nan, None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + +def test_extract_expand_index_raises(): + # GH9980 + # Index only works with one regex group since + # multi-group would expand to a frame + idx = Index(["A1", "A2", "A3", "A4", "B5"]) + msg = "only one regex group is supported with Index" + with pytest.raises(ValueError, match=msg): + idx.str.extract("([AB])([123])", expand=False) + + +def test_extract_expand_no_capture_groups_raises(index_or_series, any_string_dtype): + s_or_idx = index_or_series(["A1", "B2", "C3"], dtype=any_string_dtype) + msg = "pattern contains no capture groups" + + # no groups + with pytest.raises(ValueError, match=msg): + s_or_idx.str.extract("[ABC][123]", expand=False) + + # only non-capturing groups + with pytest.raises(ValueError, match=msg): + s_or_idx.str.extract("(?:[AB]).*", expand=False) + + +def test_extract_expand_single_capture_group(index_or_series, any_string_dtype): + # single group renames series/index properly + s_or_idx = index_or_series(["A1", "A2"], dtype=any_string_dtype) + result = s_or_idx.str.extract(r"(?PA)\d", expand=False) + + expected = index_or_series(["A", "A"], name="uno", dtype=any_string_dtype) + if index_or_series == Series: + tm.assert_series_equal(result, expected) + else: + tm.assert_index_equal(result, expected) + + +def test_extract_expand_capture_groups(any_string_dtype): + s = Series(["A1", "B2", "C3"], dtype=any_string_dtype) + # one group, no matches + result = s.str.extract("(_)", expand=False) + expected = Series([np.nan, np.nan, np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + # two groups, no matches + result = s.str.extract("(_)(_)", expand=False) + expected = DataFrame( + [[np.nan, np.nan], [np.nan, np.nan], [np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # one group, some matches + result = s.str.extract("([AB])[123]", expand=False) + expected = Series(["A", "B", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + # two groups, some matches + result = s.str.extract("([AB])([123])", expand=False) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # one named group + result = s.str.extract("(?P[AB])", expand=False) + expected = Series(["A", "B", np.nan], name="letter", dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + # two named groups + result = s.str.extract("(?P[AB])(?P[123])", expand=False) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], + columns=["letter", "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + # mix named and unnamed groups + result = s.str.extract("([AB])(?P[123])", expand=False) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], + columns=[0, "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + # one normal group, one non-capturing group + result = s.str.extract("([AB])(?:[123])", expand=False) + expected = Series(["A", "B", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + # two normal groups, one non-capturing group + s = Series(["A11", "B22", "C33"], dtype=any_string_dtype) + result = s.str.extract("([AB])([123])(?:[123])", expand=False) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # one optional group followed by one normal group + s = Series(["A1", "B2", "3"], dtype=any_string_dtype) + result = s.str.extract("(?P[AB])?(?P[123])", expand=False) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, "3"]], + columns=["letter", "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + # one normal group followed by one optional group + s = Series(["A1", "B2", "C"], dtype=any_string_dtype) + result = s.str.extract("(?P[ABC])(?P[123])?", expand=False) + expected = DataFrame( + [["A", "1"], ["B", "2"], ["C", np.nan]], + columns=["letter", "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +def test_extract_expand_capture_groups_index(index, any_string_dtype): + # https://github.com/pandas-dev/pandas/issues/6348 + # not passing index to the extractor + data = ["A1", "B2", "C"] + + if len(index) == 0: + pytest.skip("Test requires len(index) > 0") + while len(index) < len(data): + index = index.repeat(2) + + index = index[: len(data)] + ser = Series(data, index=index, dtype=any_string_dtype) + + result = ser.str.extract(r"(\d)", expand=False) + expected = Series(["1", "2", np.nan], index=index, dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.extract(r"(?P\D)(?P\d)?", expand=False) + expected = DataFrame( + [["A", "1"], ["B", "2"], ["C", np.nan]], + columns=["letter", "number"], + index=index, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +def test_extract_single_series_name_is_preserved(any_string_dtype): + s = Series(["a3", "b3", "c2"], name="bob", dtype=any_string_dtype) + result = s.str.extract(r"(?P[a-z])", expand=False) + expected = Series(["a", "b", "c"], name="sue", dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_extract_expand_True(any_string_dtype): + # Contains tests like those in test_match and some others. + s = Series(["fooBAD__barBAD", np.nan, "foo"], dtype=any_string_dtype) + + result = s.str.extract(".*(BAD[_]+).*(BAD)", expand=True) + expected = DataFrame( + [["BAD__", "BAD"], [np.nan, np.nan], [np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + +def test_extract_expand_True_mixed_object(): + er = [np.nan, np.nan] # empty row + mixed = Series( + [ + "aBAD_BAD", + np.nan, + "BAD_b_BAD", + True, + datetime.today(), + "foo", + None, + 1, + 2.0, + ] + ) + + result = mixed.str.extract(".*(BAD[_]+).*(BAD)", expand=True) + expected = DataFrame( + [["BAD_", "BAD"], er, ["BAD_", "BAD"], er, er, er, er, er, er], dtype=object + ) + tm.assert_frame_equal(result, expected) + + +def test_extract_expand_True_single_capture_group_raises( + index_or_series, any_string_dtype +): + # these should work for both Series and Index + # no groups + s_or_idx = index_or_series(["A1", "B2", "C3"], dtype=any_string_dtype) + msg = "pattern contains no capture groups" + with pytest.raises(ValueError, match=msg): + s_or_idx.str.extract("[ABC][123]", expand=True) + + # only non-capturing groups + with pytest.raises(ValueError, match=msg): + s_or_idx.str.extract("(?:[AB]).*", expand=True) + + +def test_extract_expand_True_single_capture_group(index_or_series, any_string_dtype): + # single group renames series/index properly + s_or_idx = index_or_series(["A1", "A2"], dtype=any_string_dtype) + result = s_or_idx.str.extract(r"(?PA)\d", expand=True) + expected = DataFrame({"uno": ["A", "A"]}, dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("name", [None, "series_name"]) +def test_extract_series(name, any_string_dtype): + # extract should give the same result whether or not the series has a name. + s = Series(["A1", "B2", "C3"], name=name, dtype=any_string_dtype) + + # one group, no matches + result = s.str.extract("(_)", expand=True) + expected = DataFrame([np.nan, np.nan, np.nan], dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + # two groups, no matches + result = s.str.extract("(_)(_)", expand=True) + expected = DataFrame( + [[np.nan, np.nan], [np.nan, np.nan], [np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # one group, some matches + result = s.str.extract("([AB])[123]", expand=True) + expected = DataFrame(["A", "B", np.nan], dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + # two groups, some matches + result = s.str.extract("([AB])([123])", expand=True) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # one named group + result = s.str.extract("(?P[AB])", expand=True) + expected = DataFrame({"letter": ["A", "B", np.nan]}, dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + # two named groups + result = s.str.extract("(?P[AB])(?P[123])", expand=True) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], + columns=["letter", "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + # mix named and unnamed groups + result = s.str.extract("([AB])(?P[123])", expand=True) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], + columns=[0, "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + # one normal group, one non-capturing group + result = s.str.extract("([AB])(?:[123])", expand=True) + expected = DataFrame(["A", "B", np.nan], dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + +def test_extract_optional_groups(any_string_dtype): + # two normal groups, one non-capturing group + s = Series(["A11", "B22", "C33"], dtype=any_string_dtype) + result = s.str.extract("([AB])([123])(?:[123])", expand=True) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # one optional group followed by one normal group + s = Series(["A1", "B2", "3"], dtype=any_string_dtype) + result = s.str.extract("(?P[AB])?(?P[123])", expand=True) + expected = DataFrame( + [["A", "1"], ["B", "2"], [np.nan, "3"]], + columns=["letter", "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + # one normal group followed by one optional group + s = Series(["A1", "B2", "C"], dtype=any_string_dtype) + result = s.str.extract("(?P[ABC])(?P[123])?", expand=True) + expected = DataFrame( + [["A", "1"], ["B", "2"], ["C", np.nan]], + columns=["letter", "number"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +def test_extract_dataframe_capture_groups_index(index, any_string_dtype): + # GH6348 + # not passing index to the extractor + + data = ["A1", "B2", "C"] + + if len(index) < len(data): + pytest.skip(f"Index needs more than {len(data)} values") + + index = index[: len(data)] + s = Series(data, index=index, dtype=any_string_dtype) + + result = s.str.extract(r"(\d)", expand=True) + expected = DataFrame(["1", "2", np.nan], index=index, dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + result = s.str.extract(r"(?P\D)(?P\d)?", expand=True) + expected = DataFrame( + [["A", "1"], ["B", "2"], ["C", np.nan]], + columns=["letter", "number"], + index=index, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +def test_extract_single_group_returns_frame(any_string_dtype): + # GH11386 extract should always return DataFrame, even when + # there is only one group. Prior to v0.18.0, extract returned + # Series when there was only one group in the regex. + s = Series(["a3", "b3", "c2"], name="series_name", dtype=any_string_dtype) + result = s.str.extract(r"(?P[a-z])", expand=True) + expected = DataFrame({"letter": ["a", "b", "c"]}, dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + +def test_extractall(any_string_dtype): + data = [ + "dave@google.com", + "tdhock5@gmail.com", + "maudelaperriere@gmail.com", + "rob@gmail.com some text steve@gmail.com", + "a@b.com some text c@d.com and e@f.com", + np.nan, + "", + ] + expected_tuples = [ + ("dave", "google", "com"), + ("tdhock5", "gmail", "com"), + ("maudelaperriere", "gmail", "com"), + ("rob", "gmail", "com"), + ("steve", "gmail", "com"), + ("a", "b", "com"), + ("c", "d", "com"), + ("e", "f", "com"), + ] + pat = r""" + (?P[a-z0-9]+) + @ + (?P[a-z]+) + \. + (?P[a-z]{2,4}) + """ + expected_columns = ["user", "domain", "tld"] + s = Series(data, dtype=any_string_dtype) + # extractall should return a DataFrame with one row for each match, indexed by the + # subject from which the match came. + expected_index = MultiIndex.from_tuples( + [(0, 0), (1, 0), (2, 0), (3, 0), (3, 1), (4, 0), (4, 1), (4, 2)], + names=(None, "match"), + ) + expected = DataFrame( + expected_tuples, expected_index, expected_columns, dtype=any_string_dtype + ) + result = s.str.extractall(pat, flags=re.VERBOSE) + tm.assert_frame_equal(result, expected) + + # The index of the input Series should be used to construct the index of the output + # DataFrame: + mi = MultiIndex.from_tuples( + [ + ("single", "Dave"), + ("single", "Toby"), + ("single", "Maude"), + ("multiple", "robAndSteve"), + ("multiple", "abcdef"), + ("none", "missing"), + ("none", "empty"), + ] + ) + s = Series(data, index=mi, dtype=any_string_dtype) + expected_index = MultiIndex.from_tuples( + [ + ("single", "Dave", 0), + ("single", "Toby", 0), + ("single", "Maude", 0), + ("multiple", "robAndSteve", 0), + ("multiple", "robAndSteve", 1), + ("multiple", "abcdef", 0), + ("multiple", "abcdef", 1), + ("multiple", "abcdef", 2), + ], + names=(None, None, "match"), + ) + expected = DataFrame( + expected_tuples, expected_index, expected_columns, dtype=any_string_dtype + ) + result = s.str.extractall(pat, flags=re.VERBOSE) + tm.assert_frame_equal(result, expected) + + # MultiIndexed subject with names. + s = Series(data, index=mi, dtype=any_string_dtype) + s.index.names = ("matches", "description") + expected_index.names = ("matches", "description", "match") + expected = DataFrame( + expected_tuples, expected_index, expected_columns, dtype=any_string_dtype + ) + result = s.str.extractall(pat, flags=re.VERBOSE) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "pat,expected_names", + [ + # optional groups. + ("(?P[AB])?(?P[123])", ["letter", "number"]), + # only one of two groups has a name. + ("([AB])?(?P[123])", [0, "number"]), + ], +) +def test_extractall_column_names(pat, expected_names, any_string_dtype): + s = Series(["", "A1", "32"], dtype=any_string_dtype) + + result = s.str.extractall(pat) + expected = DataFrame( + [("A", "1"), (np.nan, "3"), (np.nan, "2")], + index=MultiIndex.from_tuples([(1, 0), (2, 0), (2, 1)], names=(None, "match")), + columns=expected_names, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +def test_extractall_single_group(any_string_dtype): + s = Series(["a3", "b3", "d4c2"], name="series_name", dtype=any_string_dtype) + expected_index = MultiIndex.from_tuples( + [(0, 0), (1, 0), (2, 0), (2, 1)], names=(None, "match") + ) + + # extractall(one named group) returns DataFrame with one named column. + result = s.str.extractall(r"(?P[a-z])") + expected = DataFrame( + {"letter": ["a", "b", "d", "c"]}, index=expected_index, dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # extractall(one un-named group) returns DataFrame with one un-named column. + result = s.str.extractall(r"([a-z])") + expected = DataFrame( + ["a", "b", "d", "c"], index=expected_index, dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + +def test_extractall_single_group_with_quantifier(any_string_dtype): + # GH#13382 + # extractall(one un-named group with quantifier) returns DataFrame with one un-named + # column. + s = Series(["ab3", "abc3", "d4cd2"], name="series_name", dtype=any_string_dtype) + result = s.str.extractall(r"([a-z]+)") + expected = DataFrame( + ["ab", "abc", "d", "cd"], + index=MultiIndex.from_tuples( + [(0, 0), (1, 0), (2, 0), (2, 1)], names=(None, "match") + ), + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "data, names", + [ + ([], (None,)), + ([], ("i1",)), + ([], (None, "i2")), + ([], ("i1", "i2")), + (["a3", "b3", "d4c2"], (None,)), + (["a3", "b3", "d4c2"], ("i1", "i2")), + (["a3", "b3", "d4c2"], (None, "i2")), + (["a3", "b3", "d4c2"], ("i1", "i2")), + ], +) +def test_extractall_no_matches(data, names, any_string_dtype): + # GH19075 extractall with no matches should return a valid MultiIndex + n = len(data) + if len(names) == 1: + index = Index(range(n), name=names[0]) + else: + tuples = (tuple([i] * (n - 1)) for i in range(n)) + index = MultiIndex.from_tuples(tuples, names=names) + s = Series(data, name="series_name", index=index, dtype=any_string_dtype) + expected_index = MultiIndex.from_tuples([], names=(names + ("match",))) + + # one un-named group. + result = s.str.extractall("(z)") + expected = DataFrame(columns=[0], index=expected_index, dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + # two un-named groups. + result = s.str.extractall("(z)(z)") + expected = DataFrame(columns=[0, 1], index=expected_index, dtype=any_string_dtype) + tm.assert_frame_equal(result, expected) + + # one named group. + result = s.str.extractall("(?Pz)") + expected = DataFrame( + columns=["first"], index=expected_index, dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # two named groups. + result = s.str.extractall("(?Pz)(?Pz)") + expected = DataFrame( + columns=["first", "second"], index=expected_index, dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + # one named, one un-named. + result = s.str.extractall("(z)(?Pz)") + expected = DataFrame( + columns=[0, "second"], index=expected_index, dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + +def test_extractall_stringindex(any_string_dtype): + s = Series(["a1a2", "b1", "c1"], name="xxx", dtype=any_string_dtype) + result = s.str.extractall(r"[ab](?P\d)") + expected = DataFrame( + {"digit": ["1", "2", "1"]}, + index=MultiIndex.from_tuples([(0, 0), (0, 1), (1, 0)], names=[None, "match"]), + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + # index should return the same result as the default index without name thus + # index.name doesn't affect to the result + if any_string_dtype == "object": + for idx in [ + Index(["a1a2", "b1", "c1"], dtype=object), + Index(["a1a2", "b1", "c1"], name="xxx", dtype=object), + ]: + result = idx.str.extractall(r"[ab](?P\d)") + tm.assert_frame_equal(result, expected) + + s = Series( + ["a1a2", "b1", "c1"], + name="s_name", + index=Index(["XX", "yy", "zz"], name="idx_name"), + dtype=any_string_dtype, + ) + result = s.str.extractall(r"[ab](?P\d)") + expected = DataFrame( + {"digit": ["1", "2", "1"]}, + index=MultiIndex.from_tuples( + [("XX", 0), ("XX", 1), ("yy", 0)], names=["idx_name", "match"] + ), + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +def test_extractall_no_capture_groups_raises(any_string_dtype): + # Does not make sense to use extractall with a regex that has no capture groups. + # (it returns DataFrame with one column for each capture group) + s = Series(["a3", "b3", "d4c2"], name="series_name", dtype=any_string_dtype) + with pytest.raises(ValueError, match="no capture groups"): + s.str.extractall(r"[a-z]") + + +def test_extract_index_one_two_groups(): + s = Series(["a3", "b3", "d4c2"], index=["A3", "B3", "D4"], name="series_name") + r = s.index.str.extract(r"([A-Z])", expand=True) + e = DataFrame(["A", "B", "D"]) + tm.assert_frame_equal(r, e) + + # Prior to v0.18.0, index.str.extract(regex with one group) + # returned Index. With more than one group, extract raised an + # error (GH9980). Now extract always returns DataFrame. + r = s.index.str.extract(r"(?P[A-Z])(?P[0-9])", expand=True) + e_list = [("A", "3"), ("B", "3"), ("D", "4")] + e = DataFrame(e_list, columns=["letter", "digit"]) + tm.assert_frame_equal(r, e) + + +def test_extractall_same_as_extract(any_string_dtype): + s = Series(["a3", "b3", "c2"], name="series_name", dtype=any_string_dtype) + + pattern_two_noname = r"([a-z])([0-9])" + extract_two_noname = s.str.extract(pattern_two_noname, expand=True) + has_multi_index = s.str.extractall(pattern_two_noname) + no_multi_index = has_multi_index.xs(0, level="match") + tm.assert_frame_equal(extract_two_noname, no_multi_index) + + pattern_two_named = r"(?P[a-z])(?P[0-9])" + extract_two_named = s.str.extract(pattern_two_named, expand=True) + has_multi_index = s.str.extractall(pattern_two_named) + no_multi_index = has_multi_index.xs(0, level="match") + tm.assert_frame_equal(extract_two_named, no_multi_index) + + pattern_one_named = r"(?P[a-z])" + extract_one_named = s.str.extract(pattern_one_named, expand=True) + has_multi_index = s.str.extractall(pattern_one_named) + no_multi_index = has_multi_index.xs(0, level="match") + tm.assert_frame_equal(extract_one_named, no_multi_index) + + pattern_one_noname = r"([a-z])" + extract_one_noname = s.str.extract(pattern_one_noname, expand=True) + has_multi_index = s.str.extractall(pattern_one_noname) + no_multi_index = has_multi_index.xs(0, level="match") + tm.assert_frame_equal(extract_one_noname, no_multi_index) + + +def test_extractall_same_as_extract_subject_index(any_string_dtype): + # same as above tests, but s has an MultiIndex. + mi = MultiIndex.from_tuples( + [("A", "first"), ("B", "second"), ("C", "third")], + names=("capital", "ordinal"), + ) + s = Series(["a3", "b3", "c2"], index=mi, name="series_name", dtype=any_string_dtype) + + pattern_two_noname = r"([a-z])([0-9])" + extract_two_noname = s.str.extract(pattern_two_noname, expand=True) + has_match_index = s.str.extractall(pattern_two_noname) + no_match_index = has_match_index.xs(0, level="match") + tm.assert_frame_equal(extract_two_noname, no_match_index) + + pattern_two_named = r"(?P[a-z])(?P[0-9])" + extract_two_named = s.str.extract(pattern_two_named, expand=True) + has_match_index = s.str.extractall(pattern_two_named) + no_match_index = has_match_index.xs(0, level="match") + tm.assert_frame_equal(extract_two_named, no_match_index) + + pattern_one_named = r"(?P[a-z])" + extract_one_named = s.str.extract(pattern_one_named, expand=True) + has_match_index = s.str.extractall(pattern_one_named) + no_match_index = has_match_index.xs(0, level="match") + tm.assert_frame_equal(extract_one_named, no_match_index) + + pattern_one_noname = r"([a-z])" + extract_one_noname = s.str.extract(pattern_one_noname, expand=True) + has_match_index = s.str.extractall(pattern_one_noname) + no_match_index = has_match_index.xs(0, level="match") + tm.assert_frame_equal(extract_one_noname, no_match_index) + + +def test_extractall_preserves_dtype(): + # Ensure that when extractall is called on a series with specific dtypes set, that + # the dtype is preserved in the resulting DataFrame's column. + pa = pytest.importorskip("pyarrow") + + result = Series(["abc", "ab"], dtype=ArrowDtype(pa.string())).str.extractall("(ab)") + assert result.dtypes[0] == "string[pyarrow]" diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_find_replace.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_find_replace.py new file mode 100644 index 0000000000000000000000000000000000000000..14c704f4dd1e592b25f2e5b7d4f7ae005f2af85c --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_find_replace.py @@ -0,0 +1,1342 @@ +from datetime import datetime +import re + +import numpy as np +import pytest + +import pandas.util._test_decorators as td + +import pandas as pd +from pandas import ( + Series, + _testing as tm, +) +from pandas.tests.strings import ( + _convert_na_value, + is_object_or_nan_string_dtype, +) + +# -------------------------------------------------------------------------------------- +# str.contains +# -------------------------------------------------------------------------------------- + + +def test_contains(any_string_dtype): + values = np.array( + ["foo", np.nan, "fooommm__foo", "mmm_", "foommm[_]+bar"], dtype=np.object_ + ) + values = Series(values, dtype=any_string_dtype) + pat = "mmm[_]+" + + result = values.str.contains(pat) + if any_string_dtype == "str": + # NaN propagates as False + expected = Series([False, False, True, True, False], dtype=bool) + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series( + np.array([False, np.nan, True, True, False], dtype=np.object_), + dtype=expected_dtype, + ) + + tm.assert_series_equal(result, expected) + + result = values.str.contains(pat, regex=False) + if any_string_dtype == "str": + expected = Series([False, False, False, False, True], dtype=bool) + else: + expected = Series( + np.array([False, np.nan, False, False, True], dtype=np.object_), + dtype=expected_dtype, + ) + tm.assert_series_equal(result, expected) + + values = Series( + np.array(["foo", "xyz", "fooommm__foo", "mmm_"], dtype=object), + dtype=any_string_dtype, + ) + result = values.str.contains(pat) + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series(np.array([False, False, True, True]), dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # case insensitive using regex + values = Series( + np.array(["Foo", "xYz", "fOOomMm__fOo", "MMM_"], dtype=object), + dtype=any_string_dtype, + ) + + result = values.str.contains("FOO|mmm", case=False) + expected = Series(np.array([True, False, True, True]), dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # case insensitive without regex + result = values.str.contains("foo", regex=False, case=False) + expected = Series(np.array([True, False, True, False]), dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # unicode + values = Series( + np.array(["foo", np.nan, "fooommm__foo", "mmm_"], dtype=np.object_), + dtype=any_string_dtype, + ) + pat = "mmm[_]+" + + result = values.str.contains(pat) + if any_string_dtype == "str": + expected = Series([False, False, True, True], dtype=bool) + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series( + np.array([False, np.nan, True, True], dtype=np.object_), + dtype=expected_dtype, + ) + tm.assert_series_equal(result, expected) + + result = values.str.contains(pat, na=False) + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series(np.array([False, False, True, True]), dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + values = Series( + np.array(["foo", "xyz", "fooommm__foo", "mmm_"], dtype=np.object_), + dtype=any_string_dtype, + ) + result = values.str.contains(pat) + expected = Series(np.array([False, False, True, True]), dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_contains_object_mixed(): + mixed = Series( + np.array( + ["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0], + dtype=object, + ) + ) + result = mixed.str.contains("o") + expected = Series( + np.array( + [False, np.nan, False, np.nan, np.nan, True, None, np.nan, np.nan], + dtype=np.object_, + ) + ) + tm.assert_series_equal(result, expected) + + +def test_contains_na_kwarg_for_object_category(): + # gh 22158 + + # na for category + values = Series(["a", "b", "c", "a", np.nan], dtype="category") + result = values.str.contains("a", na=True) + expected = Series([True, False, False, True, True]) + tm.assert_series_equal(result, expected) + + result = values.str.contains("a", na=False) + expected = Series([True, False, False, True, False]) + tm.assert_series_equal(result, expected) + + # na for objects + values = Series(["a", "b", "c", "a", np.nan]) + result = values.str.contains("a", na=True) + expected = Series([True, False, False, True, True]) + tm.assert_series_equal(result, expected) + + result = values.str.contains("a", na=False) + expected = Series([True, False, False, True, False]) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "na, expected", + [ + (None, pd.NA), + (True, True), + (False, False), + (0, False), + (3, True), + (np.nan, pd.NA), + ], +) +@pytest.mark.parametrize("regex", [True, False]) +def test_contains_na_kwarg_for_nullable_string_dtype( + nullable_string_dtype, na, expected, regex +): + # https://github.com/pandas-dev/pandas/pull/41025#issuecomment-824062416 + + values = Series(["a", "b", "c", "a", np.nan], dtype=nullable_string_dtype) + + msg = ( + "Allowing a non-bool 'na' in obj.str.contains is deprecated and " + "will raise in a future version" + ) + warn = None + if not pd.isna(na) and not isinstance(na, bool): + warn = FutureWarning + with tm.assert_produces_warning(warn, match=msg): + result = values.str.contains("a", na=na, regex=regex) + expected = Series([True, False, False, True, expected], dtype="boolean") + tm.assert_series_equal(result, expected) + + +def test_contains_moar(any_string_dtype): + # PR #1179 + s = Series( + ["A", "B", "C", "Aaba", "Baca", "", np.nan, "CABA", "dog", "cat"], + dtype=any_string_dtype, + ) + + result = s.str.contains("a") + if any_string_dtype == "str": + # NaN propagates as False + expected_dtype = bool + na_value = False + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + na_value = np.nan + expected = Series( + [False, False, False, True, True, False, na_value, False, False, True], + dtype=expected_dtype, + ) + tm.assert_series_equal(result, expected) + + result = s.str.contains("a", case=False) + expected = Series( + [True, False, False, True, True, False, na_value, True, False, True], + dtype=expected_dtype, + ) + tm.assert_series_equal(result, expected) + + result = s.str.contains("Aa") + expected = Series( + [False, False, False, True, False, False, na_value, False, False, False], + dtype=expected_dtype, + ) + tm.assert_series_equal(result, expected) + + result = s.str.contains("ba") + expected = Series( + [False, False, False, True, False, False, na_value, False, False, False], + dtype=expected_dtype, + ) + tm.assert_series_equal(result, expected) + + result = s.str.contains("ba", case=False) + expected = Series( + [False, False, False, True, True, False, na_value, True, False, False], + dtype=expected_dtype, + ) + tm.assert_series_equal(result, expected) + + +def test_contains_nan(any_string_dtype): + # PR #14171 + s = Series([np.nan, np.nan, np.nan], dtype=any_string_dtype) + + result = s.str.contains("foo", na=False) + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series([False, False, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = s.str.contains("foo", na=True) + expected = Series([True, True, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # TODO(infer_string) + # this particular combination of events is broken on 2.3 + # would require cherry picking #58483, which in turn requires #57481 + # which introduce many behavioral changes + if not ( + hasattr(any_string_dtype, "storage") + and any_string_dtype.storage == "python" + and any_string_dtype.na_value is np.nan + ): + msg = ( + "Allowing a non-bool 'na' in obj.str.contains is deprecated and " + "will raise in a future version" + ) + with tm.assert_produces_warning(FutureWarning, match=msg): + result = s.str.contains("foo", na="foo") + if any_string_dtype == "object": + expected = Series(["foo", "foo", "foo"], dtype=np.object_) + elif any_string_dtype.na_value is np.nan: + expected = Series([True, True, True], dtype=np.bool_) + else: + expected = Series([True, True, True], dtype="boolean") + tm.assert_series_equal(result, expected) + + result = s.str.contains("foo") + if any_string_dtype == "str": + # NaN propagates as False + expected = Series([False, False, False], dtype=bool) + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series([np.nan, np.nan, np.nan], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_contains_compiled_regex(any_string_dtype): + # GH#61942 + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + + ser = Series(["foo", "bar", "Baz"], dtype=any_string_dtype) + + pat = re.compile("ba.") + result = ser.str.contains(pat) + expected = Series([False, True, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # TODO this currently works for pyarrow-backed dtypes but raises for python + if any_string_dtype == "string" and any_string_dtype.storage == "pyarrow": + result = ser.str.contains(pat, case=False) + expected = Series([False, True, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + else: + with pytest.raises( + ValueError, match="cannot process flags argument with a compiled pattern" + ): + ser.str.contains(pat, case=False) + + pat = re.compile("ba.", flags=re.IGNORECASE) + result = ser.str.contains(pat) + expected = Series([False, True, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # TODO should this be supported? + with pytest.raises( + ValueError, match="cannot process flags argument with a compiled pattern" + ): + ser.str.contains(pat, flags=re.IGNORECASE) + + +def test_contains_compiled_regex_flags(any_string_dtype): + # ensure other (than ignorecase) flags are respected + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + + ser = Series(["foobar", "foo\nbar", "Baz"], dtype=any_string_dtype) + + pat = re.compile("^ba") + result = ser.str.contains(pat) + expected = Series([False, False, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + pat = re.compile("^ba", flags=re.MULTILINE) + result = ser.str.contains(pat) + expected = Series([False, True, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + pat = re.compile("^ba", flags=re.MULTILINE | re.IGNORECASE) + result = ser.str.contains(pat) + expected = Series([False, True, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +# -------------------------------------------------------------------------------------- +# str.startswith +# -------------------------------------------------------------------------------------- + + +def test_startswith_endswith_validate_na(request, any_string_dtype): + if ( + any_string_dtype == "string" + and any_string_dtype.na_value is np.nan + and any_string_dtype.storage == "python" + ): + request.applymarker(pytest.mark.xfail(reason="TODO(infer_string)")) + # GH#59615 + ser = Series( + ["om", np.nan, "foo_nom", "nom", "bar_foo", np.nan, "foo"], + dtype=any_string_dtype, + ) + + msg = "Allowing a non-bool 'na' in obj.str.startswith is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + ser.str.startswith("kapow", na="baz") + msg = "Allowing a non-bool 'na' in obj.str.endswith is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + ser.str.endswith("bar", na="baz") + + +@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning") +@pytest.mark.parametrize("pat", ["foo", ("foo", "baz")]) +@pytest.mark.parametrize("dtype", ["object", "category"]) +@pytest.mark.parametrize("null_value", [None, np.nan, pd.NA]) +@pytest.mark.parametrize("na", [True, False]) +def test_startswith(pat, dtype, null_value, na, using_infer_string): + # add category dtype parametrizations for GH-36241 + values = Series( + ["om", null_value, "foo_nom", "nom", "bar_foo", null_value, "foo"], + dtype=dtype, + ) + + result = values.str.startswith(pat) + exp = Series([False, np.nan, True, False, False, np.nan, True]) + if dtype == "object" and null_value is pd.NA: + # GH#18463 + exp = exp.fillna(null_value) + elif dtype == "object" and null_value is None: + exp[exp.isna()] = None + elif using_infer_string and dtype == "category": + exp = exp.fillna(False).astype(bool) + tm.assert_series_equal(result, exp) + + result = values.str.startswith(pat, na=na) + exp = Series([False, na, True, False, False, na, True]) + tm.assert_series_equal(result, exp) + + # mixed + mixed = np.array( + ["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0], + dtype=np.object_, + ) + rs = Series(mixed).str.startswith("f") + xp = Series([False, np.nan, False, np.nan, np.nan, True, None, np.nan, np.nan]) + tm.assert_series_equal(rs, xp) + + +@pytest.mark.parametrize("na", [None, True, False]) +def test_startswith_string_dtype(any_string_dtype, na): + values = Series( + ["om", None, "foo_nom", "nom", "bar_foo", None, "foo", "regex", "rege."], + dtype=any_string_dtype, + ) + result = values.str.startswith("foo", na=na) + + expected_dtype = ( + (object if na is None else bool) + if is_object_or_nan_string_dtype(any_string_dtype) + else "boolean" + ) + if any_string_dtype == "str": + # NaN propagates as False + expected_dtype = bool + if na is None: + na = False + exp = Series( + [False, na, True, False, False, na, True, False, False], dtype=expected_dtype + ) + tm.assert_series_equal(result, exp) + + result = values.str.startswith("rege.", na=na) + exp = Series( + [False, na, False, False, False, na, False, False, True], dtype=expected_dtype + ) + tm.assert_series_equal(result, exp) + + +# -------------------------------------------------------------------------------------- +# str.endswith +# -------------------------------------------------------------------------------------- + + +@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning") +@pytest.mark.parametrize("pat", ["foo", ("foo", "baz")]) +@pytest.mark.parametrize("dtype", ["object", "category"]) +@pytest.mark.parametrize("null_value", [None, np.nan, pd.NA]) +@pytest.mark.parametrize("na", [True, False]) +def test_endswith(pat, dtype, null_value, na, using_infer_string): + # add category dtype parametrizations for GH-36241 + values = Series( + ["om", null_value, "foo_nom", "nom", "bar_foo", null_value, "foo"], + dtype=dtype, + ) + + result = values.str.endswith(pat) + exp = Series([False, np.nan, False, False, True, np.nan, True]) + if dtype == "object" and null_value is pd.NA: + # GH#18463 + exp = exp.fillna(null_value) + elif dtype == "object" and null_value is None: + exp[exp.isna()] = None + elif using_infer_string and dtype == "category": + exp = exp.fillna(False).astype(bool) + tm.assert_series_equal(result, exp) + + result = values.str.endswith(pat, na=na) + exp = Series([False, na, False, False, True, na, True]) + tm.assert_series_equal(result, exp) + + # mixed + mixed = np.array( + ["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0], + dtype=object, + ) + rs = Series(mixed).str.endswith("f") + xp = Series([False, np.nan, False, np.nan, np.nan, False, None, np.nan, np.nan]) + tm.assert_series_equal(rs, xp) + + +@pytest.mark.parametrize("na", [None, True, False]) +def test_endswith_string_dtype(any_string_dtype, na): + values = Series( + ["om", None, "foo_nom", "nom", "bar_foo", None, "foo", "regex", "rege."], + dtype=any_string_dtype, + ) + result = values.str.endswith("foo", na=na) + expected_dtype = ( + (object if na is None else bool) + if is_object_or_nan_string_dtype(any_string_dtype) + else "boolean" + ) + if any_string_dtype == "str": + # NaN propagates as False + expected_dtype = bool + if na is None: + na = False + exp = Series( + [False, na, False, False, True, na, True, False, False], dtype=expected_dtype + ) + tm.assert_series_equal(result, exp) + + result = values.str.endswith("rege.", na=na) + exp = Series( + [False, na, False, False, False, na, False, False, True], dtype=expected_dtype + ) + tm.assert_series_equal(result, exp) + + +# -------------------------------------------------------------------------------------- +# str.replace +# -------------------------------------------------------------------------------------- + + +def test_replace(any_string_dtype): + ser = Series(["fooBAD__barBAD", np.nan], dtype=any_string_dtype) + + result = ser.str.replace("BAD[_]*", "", regex=True) + expected = Series(["foobar", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_replace_max_replacements(any_string_dtype): + ser = Series(["fooBAD__barBAD", np.nan], dtype=any_string_dtype) + + expected = Series(["foobarBAD", np.nan], dtype=any_string_dtype) + result = ser.str.replace("BAD[_]*", "", n=1, regex=True) + tm.assert_series_equal(result, expected) + + expected = Series(["foo__barBAD", np.nan], dtype=any_string_dtype) + result = ser.str.replace("BAD", "", n=1, regex=False) + tm.assert_series_equal(result, expected) + + +def test_replace_mixed_object(): + ser = Series( + ["aBAD", np.nan, "bBAD", True, datetime.today(), "fooBAD", None, 1, 2.0] + ) + result = Series(ser).str.replace("BAD[_]*", "", regex=True) + expected = Series( + ["a", np.nan, "b", np.nan, np.nan, "foo", None, np.nan, np.nan], dtype=object + ) + tm.assert_series_equal(result, expected) + + +def test_replace_unicode(any_string_dtype): + ser = Series([b"abcd,\xc3\xa0".decode("utf-8")], dtype=any_string_dtype) + expected = Series([b"abcd, \xc3\xa0".decode("utf-8")], dtype=any_string_dtype) + result = ser.str.replace(r"(?<=\w),(?=\w)", ", ", flags=re.UNICODE, regex=True) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("repl", [None, 3, {"a": "b"}]) +@pytest.mark.parametrize("data", [["a", "b", None], ["a", "b", "c", "ad"]]) +def test_replace_wrong_repl_type_raises(any_string_dtype, index_or_series, repl, data): + # https://github.com/pandas-dev/pandas/issues/13438 + msg = "repl must be a string or callable" + obj = index_or_series(data, dtype=any_string_dtype) + with pytest.raises(TypeError, match=msg): + obj.str.replace("a", repl) + + +def test_replace_callable(any_string_dtype): + # GH 15055 + ser = Series(["fooBAD__barBAD", np.nan], dtype=any_string_dtype) + + # test with callable + repl = lambda m: m.group(0).swapcase() + result = ser.str.replace("[a-z][A-Z]{2}", repl, n=2, regex=True) + expected = Series(["foObaD__baRbaD", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "repl", [lambda: None, lambda m, x: None, lambda m, x, y=None: None] +) +def test_replace_callable_raises(any_string_dtype, repl): + # GH 15055 + values = Series(["fooBAD__barBAD", np.nan], dtype=any_string_dtype) + + # test with wrong number of arguments, raising an error + msg = ( + r"((takes)|(missing)) (?(2)from \d+ to )?\d+ " + r"(?(3)required )positional arguments?" + ) + with pytest.raises(TypeError, match=msg): + values.str.replace("a", repl, regex=True) + + +@pytest.mark.parametrize( + "repl, expected_list", + [ + ( + r"\g \g \g", + ["Three Two One", "Baz Bar Foo"], + ), + ( + r"\g<3> \g<2> \g<1>", + ["Three Two One", "Baz Bar Foo"], + ), + ( + r"\g<2>0", + ["Two0", "Bar0"], + ), + ( + r"\g<2>0 \1", + ["Two0 One", "Bar0 Foo"], + ), + ], + ids=[ + "named_groups_full_swap", + "numbered_groups_full_swap", + "single_group_with_literal", + "mixed_group_reference_with_literal", + ], +) +@pytest.mark.parametrize("use_compile", [True, False]) +def test_replace_named_groups_regex_swap( + any_string_dtype, use_compile, repl, expected_list +): + # GH#57636 + ser = Series(["One Two Three", "Foo Bar Baz"], dtype=any_string_dtype) + pattern = r"(?P\w+) (?P\w+) (?P\w+)" + if use_compile: + pattern = re.compile(pattern) + result = ser.str.replace(pattern, repl, regex=True) + expected = Series(expected_list, dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "repl", + [ + r"\g<20>", + r"\20", + ], +) +@pytest.mark.parametrize("use_compile", [True, False]) +def test_replace_named_groups_regex_swap_expected_fail( + any_string_dtype, repl, use_compile +): + # GH#57636 + pattern = r"(?P\w+) (?P\w+) (?P\w+)" + if use_compile: + pattern = re.compile(pattern) + ser = Series(["One Two Three", "Foo Bar Baz"], dtype=any_string_dtype) + + with pytest.raises(re.error, match="invalid group reference"): + ser.str.replace(pattern, repl, regex=True) + + +def test_replace_callable_named_groups(any_string_dtype): + # test regex named groups + ser = Series(["Foo Bar Baz", np.nan], dtype=any_string_dtype) + pat = r"(?P\w+) (?P\w+) (?P\w+)" + repl = lambda m: m.group("middle").swapcase() + result = ser.str.replace(pat, repl, regex=True) + expected = Series(["bAR", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_replace_compiled_regex(any_string_dtype): + # GH 15446 + ser = Series(["fooBAD__barBAD", np.nan], dtype=any_string_dtype) + + # test with compiled regex + pat = re.compile(r"BAD_*") + result = ser.str.replace(pat, "", regex=True) + expected = Series(["foobar", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.replace(pat, "", n=1, regex=True) + expected = Series(["foobarBAD", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_replace_compiled_regex_mixed_object(): + pat = re.compile(r"BAD_*") + ser = Series( + ["aBAD", np.nan, "bBAD", True, datetime.today(), "fooBAD", None, 1, 2.0] + ) + result = Series(ser).str.replace(pat, "", regex=True) + expected = Series( + ["a", np.nan, "b", np.nan, np.nan, "foo", None, np.nan, np.nan], dtype=object + ) + tm.assert_series_equal(result, expected) + + +def test_replace_compiled_regex_unicode(any_string_dtype): + ser = Series([b"abcd,\xc3\xa0".decode("utf-8")], dtype=any_string_dtype) + expected = Series([b"abcd, \xc3\xa0".decode("utf-8")], dtype=any_string_dtype) + pat = re.compile(r"(?<=\w),(?=\w)", flags=re.UNICODE) + result = ser.str.replace(pat, ", ", regex=True) + tm.assert_series_equal(result, expected) + + +def test_replace_compiled_regex_raises(any_string_dtype): + # case and flags provided to str.replace will have no effect + # and will produce warnings + ser = Series(["fooBAD__barBAD__bad", np.nan], dtype=any_string_dtype) + pat = re.compile(r"BAD_*") + + msg = "case and flags cannot be set when pat is a compiled regex" + + with pytest.raises(ValueError, match=msg): + ser.str.replace(pat, "", flags=re.IGNORECASE, regex=True) + + with pytest.raises(ValueError, match=msg): + ser.str.replace(pat, "", case=False, regex=True) + + with pytest.raises(ValueError, match=msg): + ser.str.replace(pat, "", case=True, regex=True) + + +def test_replace_compiled_regex_callable(any_string_dtype): + # test with callable + ser = Series(["fooBAD__barBAD", np.nan], dtype=any_string_dtype) + repl = lambda m: m.group(0).swapcase() + pat = re.compile("[a-z][A-Z]{2}") + result = ser.str.replace(pat, repl, n=2, regex=True) + expected = Series(["foObaD__baRbaD", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "regex,expected", [(True, ["bao", "bao", np.nan]), (False, ["bao", "foo", np.nan])] +) +def test_replace_literal(regex, expected, any_string_dtype): + # GH16808 literal replace (regex=False vs regex=True) + ser = Series(["f.o", "foo", np.nan], dtype=any_string_dtype) + expected = Series(expected, dtype=any_string_dtype) + result = ser.str.replace("f.", "ba", regex=regex) + tm.assert_series_equal(result, expected) + + +def test_replace_literal_callable_raises(any_string_dtype): + ser = Series([], dtype=any_string_dtype) + repl = lambda m: m.group(0).swapcase() + + msg = "Cannot use a callable replacement when regex=False" + with pytest.raises(ValueError, match=msg): + ser.str.replace("abc", repl, regex=False) + + +def test_replace_literal_compiled_raises(any_string_dtype): + ser = Series([], dtype=any_string_dtype) + pat = re.compile("[a-z][A-Z]{2}") + + msg = "Cannot use a compiled regex as replacement pattern with regex=False" + with pytest.raises(ValueError, match=msg): + ser.str.replace(pat, "", regex=False) + + +def test_replace_moar(any_string_dtype): + # PR #1179 + ser = Series( + ["A", "B", "C", "Aaba", "Baca", "", np.nan, "CABA", "dog", "cat"], + dtype=any_string_dtype, + ) + + result = ser.str.replace("A", "YYY") + expected = Series( + ["YYY", "B", "C", "YYYaba", "Baca", "", np.nan, "CYYYBYYY", "dog", "cat"], + dtype=any_string_dtype, + ) + tm.assert_series_equal(result, expected) + + result = ser.str.replace("A", "YYY", case=False) + expected = Series( + [ + "YYY", + "B", + "C", + "YYYYYYbYYY", + "BYYYcYYY", + "", + np.nan, + "CYYYBYYY", + "dog", + "cYYYt", + ], + dtype=any_string_dtype, + ) + tm.assert_series_equal(result, expected) + + result = ser.str.replace("^.a|dog", "XX-XX ", case=False, regex=True) + expected = Series( + [ + "A", + "B", + "C", + "XX-XX ba", + "XX-XX ca", + "", + np.nan, + "XX-XX BA", + "XX-XX ", + "XX-XX t", + ], + dtype=any_string_dtype, + ) + tm.assert_series_equal(result, expected) + + +def test_replace_not_case_sensitive_not_regex(any_string_dtype): + # https://github.com/pandas-dev/pandas/issues/41602 + ser = Series(["A.", "a.", "Ab", "ab", np.nan], dtype=any_string_dtype) + + result = ser.str.replace("a", "c", case=False, regex=False) + expected = Series(["c.", "c.", "cb", "cb", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.replace("a.", "c.", case=False, regex=False) + expected = Series(["c.", "c.", "Ab", "ab", np.nan], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_replace_regex(any_string_dtype): + # https://github.com/pandas-dev/pandas/pull/24809 + s = Series(["a", "b", "ac", np.nan, ""], dtype=any_string_dtype) + result = s.str.replace("^.$", "a", regex=True) + expected = Series(["a", "a", "ac", np.nan, ""], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("regex", [True, False]) +def test_replace_regex_single_character(regex, any_string_dtype): + # https://github.com/pandas-dev/pandas/pull/24809, enforced in 2.0 + # GH 24804 + s = Series(["a.b", ".", "b", np.nan, ""], dtype=any_string_dtype) + + result = s.str.replace(".", "a", regex=regex) + if regex: + expected = Series(["aaa", "a", "a", np.nan, ""], dtype=any_string_dtype) + else: + expected = Series(["aab", "a", "b", np.nan, ""], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +# -------------------------------------------------------------------------------------- +# str.match +# -------------------------------------------------------------------------------------- + + +def test_match(any_string_dtype): + if any_string_dtype == "str": + # NaN propagates as False + expected_dtype = bool + na_value = False + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + na_value = np.nan + + values = Series(["fooBAD__barBAD", np.nan, "foo"], dtype=any_string_dtype) + result = values.str.match(".*(BAD[_]+).*(BAD)") + expected = Series([True, na_value, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + values = Series( + ["fooBAD__barBAD", "BAD_BADleroybrown", np.nan, "foo"], dtype=any_string_dtype + ) + result = values.str.match(".*BAD[_]+.*BAD") + expected = Series([True, True, na_value, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = values.str.match("BAD[_]+.*BAD") + expected = Series([False, True, na_value, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + values = Series( + ["fooBAD__barBAD", "^BAD_BADleroybrown", np.nan, "foo"], dtype=any_string_dtype + ) + result = values.str.match("^BAD[_]+.*BAD") + expected = Series([False, False, na_value, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = values.str.match("\\^BAD[_]+.*BAD") + expected = Series([False, True, na_value, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_match_mixed_object(): + mixed = Series( + [ + "aBAD_BAD", + np.nan, + "BAD_b_BAD", + True, + datetime.today(), + "foo", + None, + 1, + 2.0, + ] + ) + result = Series(mixed).str.match(".*(BAD[_]+).*(BAD)") + expected = Series([True, np.nan, True, np.nan, np.nan, False, None, np.nan, np.nan]) + assert isinstance(result, Series) + tm.assert_series_equal(result, expected) + + +def test_match_na_kwarg(any_string_dtype): + # GH #6609 + s = Series(["a", "b", np.nan], dtype=any_string_dtype) + + result = s.str.match("a", na=False) + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series([True, False, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = s.str.match("a") + if any_string_dtype == "str": + # NaN propagates as False + expected_dtype = bool + na_value = False + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + na_value = np.nan + + expected = Series([True, False, na_value], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_match_case_kwarg(any_string_dtype): + values = Series(["ab", "AB", "abc", "ABC"], dtype=any_string_dtype) + result = values.str.match("ab", case=False) + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series([True, True, True, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_match_compiled_regex(any_string_dtype): + # GH#61952 + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + + values = Series(["ab", "AB", "abc", "ABC"], dtype=any_string_dtype) + + result = values.str.match(re.compile("ab")) + expected = Series([True, False, True, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # TODO this currently works for pyarrow-backed dtypes but raises for python + if any_string_dtype == "string" and any_string_dtype.storage == "pyarrow": + result = values.str.match(re.compile("ab"), case=False) + expected = Series([True, True, True, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + else: + with pytest.raises( + ValueError, match="cannot process flags argument with a compiled pattern" + ): + values.str.match(re.compile("ab"), case=False) + + result = values.str.match(re.compile("ab", flags=re.IGNORECASE)) + expected = Series([True, True, True, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + with pytest.raises( + ValueError, match="cannot process flags argument with a compiled pattern" + ): + values.str.match(re.compile("ab"), flags=re.IGNORECASE) + + +@pytest.mark.parametrize( + "pat, case, exp", + [ + ["ab", False, [True, False]], + ["Ab", True, [False, False]], + ["bc", True, [False, False]], + ["a[a-z]{1}", False, [True, False]], + ["A[a-z]{1}", True, [False, False]], + # https://github.com/pandas-dev/pandas/issues/61072 + ["(bc)|(ab)", True, [True, False]], + ["((bc)|(ab))", True, [True, False]], + ], +) +def test_str_match_extra_cases(any_string_dtype, pat, case, exp): + ser = Series(["abc", "Xab"], dtype=any_string_dtype) + result = ser.str.match(pat, case=case) + + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series(exp, dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +# -------------------------------------------------------------------------------------- +# str.fullmatch +# -------------------------------------------------------------------------------------- + + +def test_fullmatch(any_string_dtype): + # GH 32806 + ser = Series( + ["fooBAD__barBAD", "BAD_BADleroybrown", np.nan, "foo"], dtype=any_string_dtype + ) + result = ser.str.fullmatch(".*BAD[_]+.*BAD") + if any_string_dtype == "str": + # NaN propagates as False + expected = Series([True, False, False, False], dtype=bool) + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series([True, False, np.nan, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_fullmatch_dollar_literal(any_string_dtype): + # GH 56652 + ser = Series(["foo", "foo$foo", np.nan, "foo$"], dtype=any_string_dtype) + result = ser.str.fullmatch("foo\\$") + if any_string_dtype == "str": + # NaN propagates as False + expected = Series([False, False, False, True], dtype=bool) + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series([False, False, np.nan, True], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_fullmatch_na_kwarg(any_string_dtype): + ser = Series( + ["fooBAD__barBAD", "BAD_BADleroybrown", np.nan, "foo"], dtype=any_string_dtype + ) + result = ser.str.fullmatch(".*BAD[_]+.*BAD", na=False) + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series([True, False, False, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_fullmatch_case_kwarg(any_string_dtype): + ser = Series(["ab", "AB", "abc", "ABC"], dtype=any_string_dtype) + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + + expected = Series([True, False, False, False], dtype=expected_dtype) + + result = ser.str.fullmatch("ab", case=True) + tm.assert_series_equal(result, expected) + + expected = Series([True, True, False, False], dtype=expected_dtype) + + result = ser.str.fullmatch("ab", case=False) + tm.assert_series_equal(result, expected) + + result = ser.str.fullmatch("ab", flags=re.IGNORECASE) + tm.assert_series_equal(result, expected) + + +def test_fullmatch_compiled_regex(any_string_dtype): + # GH#61952 + expected_dtype = ( + np.bool_ if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + + values = Series(["ab", "AB", "abc", "ABC"], dtype=any_string_dtype) + + result = values.str.fullmatch(re.compile("ab")) + expected = Series([True, False, False, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + # TODO this currently works for pyarrow-backed dtypes but raises for python + if any_string_dtype == "string" and any_string_dtype.storage == "pyarrow": + result = values.str.fullmatch(re.compile("ab"), case=False) + expected = Series([True, True, False, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + else: + with pytest.raises( + ValueError, match="cannot process flags argument with a compiled pattern" + ): + values.str.fullmatch(re.compile("ab"), case=False) + + result = values.str.fullmatch(re.compile("ab", flags=re.IGNORECASE)) + expected = Series([True, True, False, False], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + with pytest.raises( + ValueError, match="cannot process flags argument with a compiled pattern" + ): + values.str.fullmatch(re.compile("ab"), flags=re.IGNORECASE) + + +@pytest.mark.parametrize( + "pat, case, na, exp", + # Note: keep cases in sync with + # pandas/tests/extension/test_arrow.py::test_str_fullmatch + [ + ["abc", False, None, [True, False, False, None]], + ["Abc", True, None, [False, False, False, None]], + ["bc", True, None, [False, False, False, None]], + ["ab", False, None, [False, False, False, None]], + ["a[a-z]{2}", False, None, [True, False, False, None]], + ["A[a-z]{1}", True, None, [False, False, False, None]], + # GH Issue: #56652 + ["abc$", False, None, [True, False, False, None]], + ["abc\\$", False, None, [False, True, False, None]], + ["Abc$", True, None, [False, False, False, None]], + ["Abc\\$", True, None, [False, False, False, None]], + # https://github.com/pandas-dev/pandas/issues/61072 + ["(abc)|(abx)", True, None, [True, False, False, None]], + ["((abc)|(abx))", True, None, [True, False, False, None]], + ], +) +def test_str_fullmatch_extra_cases(any_string_dtype, pat, case, na, exp): + ser = Series(["abc", "abc$", "$abc", None], dtype=any_string_dtype) + result = ser.str.fullmatch(pat, case=case, na=na) + + if any_string_dtype == "str": + # NaN propagates as False + exp[-1] = False + expected_dtype = bool + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series(exp, dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +# -------------------------------------------------------------------------------------- +# str.findall +# -------------------------------------------------------------------------------------- + + +def test_findall(any_string_dtype): + ser = Series(["fooBAD__barBAD", np.nan, "foo", "BAD"], dtype=any_string_dtype) + result = ser.str.findall("BAD[_]*") + expected = Series([["BAD__", "BAD"], np.nan, [], ["BAD"]]) + expected = _convert_na_value(ser, expected) + tm.assert_series_equal(result, expected) + + +def test_findall_mixed_object(): + ser = Series( + [ + "fooBAD__barBAD", + np.nan, + "foo", + True, + datetime.today(), + "BAD", + None, + 1, + 2.0, + ] + ) + + result = ser.str.findall("BAD[_]*") + expected = Series( + [ + ["BAD__", "BAD"], + np.nan, + [], + np.nan, + np.nan, + ["BAD"], + None, + np.nan, + np.nan, + ] + ) + + tm.assert_series_equal(result, expected) + + +# -------------------------------------------------------------------------------------- +# str.find +# -------------------------------------------------------------------------------------- + + +def test_find(any_string_dtype): + ser = Series( + ["ABCDEFG", "BCDEFEF", "DEFGHIJEF", "EFGHEF", "XXXX"], dtype=any_string_dtype + ) + expected_dtype = ( + np.int64 if is_object_or_nan_string_dtype(any_string_dtype) else "Int64" + ) + + result = ser.str.find("EF") + expected = Series([4, 3, 1, 0, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + expected = np.array([v.find("EF") for v in np.array(ser)], dtype=np.int64) + tm.assert_numpy_array_equal(np.array(result, dtype=np.int64), expected) + + result = ser.str.rfind("EF") + expected = Series([4, 5, 7, 4, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + expected = np.array([v.rfind("EF") for v in np.array(ser)], dtype=np.int64) + tm.assert_numpy_array_equal(np.array(result, dtype=np.int64), expected) + + result = ser.str.find("EF", 3) + expected = Series([4, 3, 7, 4, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + expected = np.array([v.find("EF", 3) for v in np.array(ser)], dtype=np.int64) + tm.assert_numpy_array_equal(np.array(result, dtype=np.int64), expected) + + result = ser.str.rfind("EF", 3) + expected = Series([4, 5, 7, 4, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + expected = np.array([v.rfind("EF", 3) for v in np.array(ser)], dtype=np.int64) + tm.assert_numpy_array_equal(np.array(result, dtype=np.int64), expected) + + result = ser.str.find("EF", 3, 6) + expected = Series([4, 3, -1, 4, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + expected = np.array([v.find("EF", 3, 6) for v in np.array(ser)], dtype=np.int64) + tm.assert_numpy_array_equal(np.array(result, dtype=np.int64), expected) + + result = ser.str.rfind("EF", 3, 6) + expected = Series([4, 3, -1, 4, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + expected = np.array([v.rfind("EF", 3, 6) for v in np.array(ser)], dtype=np.int64) + tm.assert_numpy_array_equal(np.array(result, dtype=np.int64), expected) + + +def test_find_bad_arg_raises(any_string_dtype): + ser = Series([], dtype=any_string_dtype) + with pytest.raises(TypeError, match="expected a string object, not int"): + ser.str.find(0) + + with pytest.raises(TypeError, match="expected a string object, not int"): + ser.str.rfind(0) + + +def test_find_nan(any_string_dtype): + ser = Series( + ["ABCDEFG", np.nan, "DEFGHIJEF", np.nan, "XXXX"], dtype=any_string_dtype + ) + expected_dtype = ( + np.float64 if is_object_or_nan_string_dtype(any_string_dtype) else "Int64" + ) + + result = ser.str.find("EF") + expected = Series([4, np.nan, 1, np.nan, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.rfind("EF") + expected = Series([4, np.nan, 7, np.nan, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.find("EF", 3) + expected = Series([4, np.nan, 7, np.nan, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.rfind("EF", 3) + expected = Series([4, np.nan, 7, np.nan, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.find("EF", 3, 6) + expected = Series([4, np.nan, -1, np.nan, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + result = ser.str.rfind("EF", 3, 6) + expected = Series([4, np.nan, -1, np.nan, -1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +# -------------------------------------------------------------------------------------- +# str.translate +# -------------------------------------------------------------------------------------- + + +@pytest.mark.parametrize( + "infer_string", [False, pytest.param(True, marks=td.skip_if_no("pyarrow"))] +) +def test_translate(index_or_series, any_string_dtype, infer_string): + obj = index_or_series( + ["abcdefg", "abcc", "cdddfg", "cdefggg"], dtype=any_string_dtype + ) + table = str.maketrans("abc", "cde") + result = obj.str.translate(table) + expected = index_or_series( + ["cdedefg", "cdee", "edddfg", "edefggg"], dtype=any_string_dtype + ) + tm.assert_equal(result, expected) + + +def test_translate_mixed_object(): + # Series with non-string values + s = Series(["a", "b", "c", 1.2]) + table = str.maketrans("abc", "cde") + expected = Series(["c", "d", "e", np.nan], dtype=object) + result = s.str.translate(table) + tm.assert_series_equal(result, expected) + + +# -------------------------------------------------------------------------------------- + + +def test_flags_kwarg(any_string_dtype): + data = { + "Dave": "dave@google.com", + "Steve": "steve@gmail.com", + "Rob": "rob@gmail.com", + "Wes": np.nan, + } + data = Series(data, dtype=any_string_dtype) + + pat = r"([A-Z0-9._%+-]+)@([A-Z0-9.-]+)\.([A-Z]{2,4})" + + result = data.str.extract(pat, flags=re.IGNORECASE, expand=True) + assert result.iloc[0].tolist() == ["dave", "google", "com"] + + result = data.str.match(pat, flags=re.IGNORECASE) + assert result.iloc[0] + + result = data.str.fullmatch(pat, flags=re.IGNORECASE) + assert result.iloc[0] + + result = data.str.findall(pat, flags=re.IGNORECASE) + assert result.iloc[0][0] == ("dave", "google", "com") + + result = data.str.count(pat, flags=re.IGNORECASE) + assert result.iloc[0] == 1 + + msg = "has match groups" + with tm.assert_produces_warning(UserWarning, match=msg): + result = data.str.contains(pat, flags=re.IGNORECASE) + assert result.iloc[0] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_get_dummies.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_get_dummies.py new file mode 100644 index 0000000000000000000000000000000000000000..31386e4e342ae3676a5468cfff5035686821fd52 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_get_dummies.py @@ -0,0 +1,53 @@ +import numpy as np + +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + _testing as tm, +) + + +def test_get_dummies(any_string_dtype): + s = Series(["a|b", "a|c", np.nan], dtype=any_string_dtype) + result = s.str.get_dummies("|") + expected = DataFrame([[1, 1, 0], [1, 0, 1], [0, 0, 0]], columns=list("abc")) + tm.assert_frame_equal(result, expected) + + s = Series(["a;b", "a", 7], dtype=any_string_dtype) + result = s.str.get_dummies(";") + expected = DataFrame([[0, 1, 1], [0, 1, 0], [1, 0, 0]], columns=list("7ab")) + tm.assert_frame_equal(result, expected) + + +def test_get_dummies_index(): + # GH9980, GH8028 + idx = Index(["a|b", "a|c", "b|c"]) + result = idx.str.get_dummies("|") + + expected = MultiIndex.from_tuples( + [(1, 1, 0), (1, 0, 1), (0, 1, 1)], names=("a", "b", "c") + ) + tm.assert_index_equal(result, expected) + + +def test_get_dummies_with_name_dummy(any_string_dtype): + # GH 12180 + # Dummies named 'name' should work as expected + s = Series(["a", "b,name", "b"], dtype=any_string_dtype) + result = s.str.get_dummies(",") + expected = DataFrame([[1, 0, 0], [0, 1, 1], [0, 1, 0]], columns=["a", "b", "name"]) + tm.assert_frame_equal(result, expected) + + +def test_get_dummies_with_name_dummy_index(): + # GH 12180 + # Dummies named 'name' should work as expected + idx = Index(["a|b", "name|c", "b|name"]) + result = idx.str.get_dummies("|") + + expected = MultiIndex.from_tuples( + [(1, 1, 0, 0), (0, 0, 1, 1), (0, 1, 0, 1)], names=("a", "b", "c", "name") + ) + tm.assert_index_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_split_partition.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_split_partition.py new file mode 100644 index 0000000000000000000000000000000000000000..423993e881b98436ad9f632ebad73678b08a9d8b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_split_partition.py @@ -0,0 +1,734 @@ +from datetime import datetime +import re + +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + _testing as tm, +) +from pandas.tests.strings import ( + _convert_na_value, + is_object_or_nan_string_dtype, +) + + +@pytest.mark.parametrize("method", ["split", "rsplit"]) +def test_split(any_string_dtype, method): + values = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype) + + result = getattr(values.str, method)("_") + exp = Series([["a", "b", "c"], ["c", "d", "e"], np.nan, ["f", "g", "h"]]) + exp = _convert_na_value(values, exp) + tm.assert_series_equal(result, exp) + + +@pytest.mark.parametrize("method", ["split", "rsplit"]) +def test_split_more_than_one_char(any_string_dtype, method): + # more than one char + values = Series(["a__b__c", "c__d__e", np.nan, "f__g__h"], dtype=any_string_dtype) + result = getattr(values.str, method)("__") + exp = Series([["a", "b", "c"], ["c", "d", "e"], np.nan, ["f", "g", "h"]]) + exp = _convert_na_value(values, exp) + tm.assert_series_equal(result, exp) + + result = getattr(values.str, method)("__", expand=False) + tm.assert_series_equal(result, exp) + + +def test_split_more_regex_split(any_string_dtype): + # regex split + values = Series(["a,b_c", "c_d,e", np.nan, "f,g,h"], dtype=any_string_dtype) + result = values.str.split("[,_]") + exp = Series([["a", "b", "c"], ["c", "d", "e"], np.nan, ["f", "g", "h"]]) + exp = _convert_na_value(values, exp) + tm.assert_series_equal(result, exp) + + +def test_split_regex(any_string_dtype): + # GH 43563 + # explicit regex = True split + values = Series("xxxjpgzzz.jpg", dtype=any_string_dtype) + result = values.str.split(r"\.jpg", regex=True) + exp = Series([["xxxjpgzzz", ""]]) + tm.assert_series_equal(result, exp) + + +def test_split_regex_explicit(any_string_dtype): + # explicit regex = True split with compiled regex + regex_pat = re.compile(r".jpg") + values = Series("xxxjpgzzz.jpg", dtype=any_string_dtype) + result = values.str.split(regex_pat) + exp = Series([["xx", "zzz", ""]]) + tm.assert_series_equal(result, exp) + + # explicit regex = False split + result = values.str.split(r"\.jpg", regex=False) + exp = Series([["xxxjpgzzz.jpg"]]) + tm.assert_series_equal(result, exp) + + # non explicit regex split, pattern length == 1 + result = values.str.split(r".") + exp = Series([["xxxjpgzzz", "jpg"]]) + tm.assert_series_equal(result, exp) + + # non explicit regex split, pattern length != 1 + result = values.str.split(r".jpg") + exp = Series([["xx", "zzz", ""]]) + tm.assert_series_equal(result, exp) + + # regex=False with pattern compiled regex raises error + with pytest.raises( + ValueError, + match="Cannot use a compiled regex as replacement pattern with regex=False", + ): + values.str.split(regex_pat, regex=False) + + +@pytest.mark.parametrize("expand", [None, False]) +@pytest.mark.parametrize("method", ["split", "rsplit"]) +def test_split_object_mixed(expand, method): + mixed = Series(["a_b_c", np.nan, "d_e_f", True, datetime.today(), None, 1, 2.0]) + result = getattr(mixed.str, method)("_", expand=expand) + exp = Series( + [ + ["a", "b", "c"], + np.nan, + ["d", "e", "f"], + np.nan, + np.nan, + None, + np.nan, + np.nan, + ] + ) + assert isinstance(result, Series) + tm.assert_almost_equal(result, exp) + + +@pytest.mark.parametrize("method", ["split", "rsplit"]) +@pytest.mark.parametrize("n", [None, 0]) +def test_split_n(any_string_dtype, method, n): + s = Series(["a b", pd.NA, "b c"], dtype=any_string_dtype) + expected = Series([["a", "b"], pd.NA, ["b", "c"]]) + result = getattr(s.str, method)(" ", n=n) + expected = _convert_na_value(s, expected) + tm.assert_series_equal(result, expected) + + +def test_rsplit(any_string_dtype): + # regex split is not supported by rsplit + values = Series(["a,b_c", "c_d,e", np.nan, "f,g,h"], dtype=any_string_dtype) + result = values.str.rsplit("[,_]") + exp = Series([["a,b_c"], ["c_d,e"], np.nan, ["f,g,h"]]) + exp = _convert_na_value(values, exp) + tm.assert_series_equal(result, exp) + + +def test_rsplit_max_number(any_string_dtype): + # setting max number of splits, make sure it's from reverse + values = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype) + result = values.str.rsplit("_", n=1) + exp = Series([["a_b", "c"], ["c_d", "e"], np.nan, ["f_g", "h"]]) + exp = _convert_na_value(values, exp) + tm.assert_series_equal(result, exp) + + +def test_split_blank_string(any_string_dtype): + # expand blank split GH 20067 + values = Series([""], name="test", dtype=any_string_dtype) + result = values.str.split(expand=True) + exp = DataFrame([[]], dtype=any_string_dtype) # NOTE: this is NOT an empty df + tm.assert_frame_equal(result, exp) + + +def test_split_blank_string_with_non_empty(any_string_dtype): + values = Series(["a b c", "a b", "", " "], name="test", dtype=any_string_dtype) + result = values.str.split(expand=True) + exp = DataFrame( + [ + ["a", "b", "c"], + ["a", "b", None], + [None, None, None], + [None, None, None], + ], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, exp) + + +@pytest.mark.parametrize("method", ["split", "rsplit"]) +def test_split_noargs(any_string_dtype, method): + # #1859 + s = Series(["Wes McKinney", "Travis Oliphant"], dtype=any_string_dtype) + result = getattr(s.str, method)() + expected = ["Travis", "Oliphant"] + assert result[1] == expected + + +@pytest.mark.parametrize( + "data, pat", + [ + (["bd asdf jfg", "kjasdflqw asdfnfk"], None), + (["bd asdf jfg", "kjasdflqw asdfnfk"], "asdf"), + (["bd_asdf_jfg", "kjasdflqw_asdfnfk"], "_"), + ], +) +@pytest.mark.parametrize("n", [-1, 0]) +def test_split_maxsplit(data, pat, any_string_dtype, n): + # re.split 0, str.split -1 + s = Series(data, dtype=any_string_dtype) + + result = s.str.split(pat=pat, n=n) + xp = s.str.split(pat=pat) + tm.assert_series_equal(result, xp) + + +@pytest.mark.parametrize( + "data, pat, expected", + [ + ( + ["split once", "split once too!"], + None, + Series({0: ["split", "once"], 1: ["split", "once too!"]}), + ), + ( + ["split_once", "split_once_too!"], + "_", + Series({0: ["split", "once"], 1: ["split", "once_too!"]}), + ), + ], +) +def test_split_no_pat_with_nonzero_n(data, pat, expected, any_string_dtype): + s = Series(data, dtype=any_string_dtype) + result = s.str.split(pat=pat, n=1) + tm.assert_series_equal(expected, result, check_index_type=False) + + +def test_split_to_dataframe_no_splits(any_string_dtype): + s = Series(["nosplit", "alsonosplit"], dtype=any_string_dtype) + result = s.str.split("_", expand=True) + exp = DataFrame({0: Series(["nosplit", "alsonosplit"], dtype=any_string_dtype)}) + tm.assert_frame_equal(result, exp) + + +def test_split_to_dataframe(any_string_dtype): + s = Series(["some_equal_splits", "with_no_nans"], dtype=any_string_dtype) + result = s.str.split("_", expand=True) + exp = DataFrame( + {0: ["some", "with"], 1: ["equal", "no"], 2: ["splits", "nans"]}, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, exp) + + +def test_split_to_dataframe_unequal_splits(any_string_dtype): + s = Series( + ["some_unequal_splits", "one_of_these_things_is_not"], dtype=any_string_dtype + ) + result = s.str.split("_", expand=True) + exp = DataFrame( + { + 0: ["some", "one"], + 1: ["unequal", "of"], + 2: ["splits", "these"], + 3: [None, "things"], + 4: [None, "is"], + 5: [None, "not"], + }, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, exp) + + +def test_split_to_dataframe_with_index(any_string_dtype): + s = Series( + ["some_splits", "with_index"], index=["preserve", "me"], dtype=any_string_dtype + ) + result = s.str.split("_", expand=True) + exp = DataFrame( + {0: ["some", "with"], 1: ["splits", "index"]}, + index=["preserve", "me"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, exp) + + with pytest.raises(ValueError, match="expand must be"): + s.str.split("_", expand="not_a_boolean") + + +def test_split_to_multiindex_expand_no_splits(): + # https://github.com/pandas-dev/pandas/issues/23677 + + idx = Index(["nosplit", "alsonosplit", np.nan]) + result = idx.str.split("_", expand=True) + exp = idx + tm.assert_index_equal(result, exp) + assert result.nlevels == 1 + + +def test_split_to_multiindex_expand(): + idx = Index(["some_equal_splits", "with_no_nans", np.nan, None]) + result = idx.str.split("_", expand=True) + exp = MultiIndex.from_tuples( + [ + ("some", "equal", "splits"), + ("with", "no", "nans"), + [np.nan, np.nan, np.nan], + [None, None, None], + ] + ) + tm.assert_index_equal(result, exp) + assert result.nlevels == 3 + + +def test_split_to_multiindex_expand_unequal_splits(): + idx = Index(["some_unequal_splits", "one_of_these_things_is_not", np.nan, None]) + result = idx.str.split("_", expand=True) + exp = MultiIndex.from_tuples( + [ + ("some", "unequal", "splits", np.nan, np.nan, np.nan), + ("one", "of", "these", "things", "is", "not"), + (np.nan, np.nan, np.nan, np.nan, np.nan, np.nan), + (None, None, None, None, None, None), + ] + ) + tm.assert_index_equal(result, exp) + assert result.nlevels == 6 + + with pytest.raises(ValueError, match="expand must be"): + idx.str.split("_", expand="not_a_boolean") + + +def test_rsplit_to_dataframe_expand_no_splits(any_string_dtype): + s = Series(["nosplit", "alsonosplit"], dtype=any_string_dtype) + result = s.str.rsplit("_", expand=True) + exp = DataFrame({0: Series(["nosplit", "alsonosplit"])}, dtype=any_string_dtype) + tm.assert_frame_equal(result, exp) + + +def test_rsplit_to_dataframe_expand(any_string_dtype): + s = Series(["some_equal_splits", "with_no_nans"], dtype=any_string_dtype) + result = s.str.rsplit("_", expand=True) + exp = DataFrame( + {0: ["some", "with"], 1: ["equal", "no"], 2: ["splits", "nans"]}, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, exp) + + result = s.str.rsplit("_", expand=True, n=2) + exp = DataFrame( + {0: ["some", "with"], 1: ["equal", "no"], 2: ["splits", "nans"]}, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, exp) + + result = s.str.rsplit("_", expand=True, n=1) + exp = DataFrame( + {0: ["some_equal", "with_no"], 1: ["splits", "nans"]}, dtype=any_string_dtype + ) + tm.assert_frame_equal(result, exp) + + +def test_rsplit_to_dataframe_expand_with_index(any_string_dtype): + s = Series( + ["some_splits", "with_index"], index=["preserve", "me"], dtype=any_string_dtype + ) + result = s.str.rsplit("_", expand=True) + exp = DataFrame( + {0: ["some", "with"], 1: ["splits", "index"]}, + index=["preserve", "me"], + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, exp) + + +def test_rsplit_to_multiindex_expand_no_split(): + idx = Index(["nosplit", "alsonosplit"]) + result = idx.str.rsplit("_", expand=True) + exp = idx + tm.assert_index_equal(result, exp) + assert result.nlevels == 1 + + +def test_rsplit_to_multiindex_expand(): + idx = Index(["some_equal_splits", "with_no_nans"]) + result = idx.str.rsplit("_", expand=True) + exp = MultiIndex.from_tuples([("some", "equal", "splits"), ("with", "no", "nans")]) + tm.assert_index_equal(result, exp) + assert result.nlevels == 3 + + +def test_rsplit_to_multiindex_expand_n(): + idx = Index(["some_equal_splits", "with_no_nans"]) + result = idx.str.rsplit("_", expand=True, n=1) + exp = MultiIndex.from_tuples([("some_equal", "splits"), ("with_no", "nans")]) + tm.assert_index_equal(result, exp) + assert result.nlevels == 2 + + +def test_split_nan_expand(any_string_dtype): + # gh-18450 + s = Series(["foo,bar,baz", np.nan], dtype=any_string_dtype) + result = s.str.split(",", expand=True) + exp = DataFrame( + [["foo", "bar", "baz"], [np.nan, np.nan, np.nan]], dtype=any_string_dtype + ) + tm.assert_frame_equal(result, exp) + + # check that these are actually np.nan/pd.NA and not None + # TODO see GH 18463 + # tm.assert_frame_equal does not differentiate + if is_object_or_nan_string_dtype(any_string_dtype): + assert all(np.isnan(x) for x in result.iloc[1]) + else: + assert all(x is pd.NA for x in result.iloc[1]) + + +def test_split_with_name_series(any_string_dtype): + # GH 12617 + + # should preserve name + s = Series(["a,b", "c,d"], name="xxx", dtype=any_string_dtype) + res = s.str.split(",") + exp = Series([["a", "b"], ["c", "d"]], name="xxx") + tm.assert_series_equal(res, exp) + + res = s.str.split(",", expand=True) + exp = DataFrame([["a", "b"], ["c", "d"]], dtype=any_string_dtype) + tm.assert_frame_equal(res, exp) + + +def test_split_with_name_index(): + # GH 12617 + idx = Index(["a,b", "c,d"], name="xxx") + res = idx.str.split(",") + exp = Index([["a", "b"], ["c", "d"]], name="xxx") + assert res.nlevels == 1 + tm.assert_index_equal(res, exp) + + res = idx.str.split(",", expand=True) + exp = MultiIndex.from_tuples([("a", "b"), ("c", "d")]) + assert res.nlevels == 2 + tm.assert_index_equal(res, exp) + + +@pytest.mark.parametrize( + "method, exp", + [ + [ + "partition", + [ + ("a", "__", "b__c"), + ("c", "__", "d__e"), + np.nan, + ("f", "__", "g__h"), + None, + ], + ], + [ + "rpartition", + [ + ("a__b", "__", "c"), + ("c__d", "__", "e"), + np.nan, + ("f__g", "__", "h"), + None, + ], + ], + ], +) +def test_partition_series_more_than_one_char(method, exp, any_string_dtype): + # https://github.com/pandas-dev/pandas/issues/23558 + # more than one char + s = Series(["a__b__c", "c__d__e", np.nan, "f__g__h", None], dtype=any_string_dtype) + result = getattr(s.str, method)("__", expand=False) + expected = Series(exp) + expected = _convert_na_value(s, expected) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method, exp", + [ + [ + "partition", + [("a", " ", "b c"), ("c", " ", "d e"), np.nan, ("f", " ", "g h"), None], + ], + [ + "rpartition", + [("a b", " ", "c"), ("c d", " ", "e"), np.nan, ("f g", " ", "h"), None], + ], + ], +) +def test_partition_series_none(any_string_dtype, method, exp): + # https://github.com/pandas-dev/pandas/issues/23558 + # None + s = Series(["a b c", "c d e", np.nan, "f g h", None], dtype=any_string_dtype) + result = getattr(s.str, method)(expand=False) + expected = Series(exp) + expected = _convert_na_value(s, expected) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method, exp", + [ + [ + "partition", + [("abc", "", ""), ("cde", "", ""), np.nan, ("fgh", "", ""), None], + ], + [ + "rpartition", + [("", "", "abc"), ("", "", "cde"), np.nan, ("", "", "fgh"), None], + ], + ], +) +def test_partition_series_not_split(any_string_dtype, method, exp): + # https://github.com/pandas-dev/pandas/issues/23558 + # Not split + s = Series(["abc", "cde", np.nan, "fgh", None], dtype=any_string_dtype) + result = getattr(s.str, method)("_", expand=False) + expected = Series(exp) + expected = _convert_na_value(s, expected) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method, exp", + [ + [ + "partition", + [("a", "_", "b_c"), ("c", "_", "d_e"), np.nan, ("f", "_", "g_h")], + ], + [ + "rpartition", + [("a_b", "_", "c"), ("c_d", "_", "e"), np.nan, ("f_g", "_", "h")], + ], + ], +) +def test_partition_series_unicode(any_string_dtype, method, exp): + # https://github.com/pandas-dev/pandas/issues/23558 + # unicode + s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype) + + result = getattr(s.str, method)("_", expand=False) + expected = Series(exp) + expected = _convert_na_value(s, expected) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("method", ["partition", "rpartition"]) +def test_partition_series_stdlib(any_string_dtype, method): + # https://github.com/pandas-dev/pandas/issues/23558 + # compare to standard lib + s = Series(["A_B_C", "B_C_D", "E_F_G", "EFGHEF"], dtype=any_string_dtype) + result = getattr(s.str, method)("_", expand=False).tolist() + assert result == [getattr(v, method)("_") for v in s] + + +@pytest.mark.parametrize( + "method, expand, exp, exp_levels", + [ + [ + "partition", + False, + np.array( + [("a", "_", "b_c"), ("c", "_", "d_e"), ("f", "_", "g_h"), np.nan, None], + dtype=object, + ), + 1, + ], + [ + "rpartition", + False, + np.array( + [("a_b", "_", "c"), ("c_d", "_", "e"), ("f_g", "_", "h"), np.nan, None], + dtype=object, + ), + 1, + ], + ], +) +def test_partition_index(method, expand, exp, exp_levels): + # https://github.com/pandas-dev/pandas/issues/23558 + + values = Index(["a_b_c", "c_d_e", "f_g_h", np.nan, None]) + + result = getattr(values.str, method)("_", expand=expand) + exp = Index(exp) + tm.assert_index_equal(result, exp) + assert result.nlevels == exp_levels + + +@pytest.mark.parametrize( + "method, exp", + [ + [ + "partition", + { + 0: ["a", "c", np.nan, "f", None], + 1: ["_", "_", np.nan, "_", None], + 2: ["b_c", "d_e", np.nan, "g_h", None], + }, + ], + [ + "rpartition", + { + 0: ["a_b", "c_d", np.nan, "f_g", None], + 1: ["_", "_", np.nan, "_", None], + 2: ["c", "e", np.nan, "h", None], + }, + ], + ], +) +def test_partition_to_dataframe(any_string_dtype, method, exp): + # https://github.com/pandas-dev/pandas/issues/23558 + + s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h", None], dtype=any_string_dtype) + result = getattr(s.str, method)("_") + expected = DataFrame( + exp, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "method, exp", + [ + [ + "partition", + { + 0: ["a", "c", np.nan, "f", None], + 1: ["_", "_", np.nan, "_", None], + 2: ["b_c", "d_e", np.nan, "g_h", None], + }, + ], + [ + "rpartition", + { + 0: ["a_b", "c_d", np.nan, "f_g", None], + 1: ["_", "_", np.nan, "_", None], + 2: ["c", "e", np.nan, "h", None], + }, + ], + ], +) +def test_partition_to_dataframe_from_series(any_string_dtype, method, exp): + # https://github.com/pandas-dev/pandas/issues/23558 + s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h", None], dtype=any_string_dtype) + result = getattr(s.str, method)("_", expand=True) + expected = DataFrame( + exp, + dtype=any_string_dtype, + ) + tm.assert_frame_equal(result, expected) + + +def test_partition_with_name(any_string_dtype): + # GH 12617 + + s = Series(["a,b", "c,d"], name="xxx", dtype=any_string_dtype) + result = s.str.partition(",") + expected = DataFrame( + {0: ["a", "c"], 1: [",", ","], 2: ["b", "d"]}, dtype=any_string_dtype + ) + tm.assert_frame_equal(result, expected) + + +def test_partition_with_name_expand(any_string_dtype): + # GH 12617 + # should preserve name + s = Series(["a,b", "c,d"], name="xxx", dtype=any_string_dtype) + result = s.str.partition(",", expand=False) + expected = Series([("a", ",", "b"), ("c", ",", "d")], name="xxx") + tm.assert_series_equal(result, expected) + + +def test_partition_index_with_name(): + idx = Index(["a,b", "c,d"], name="xxx") + result = idx.str.partition(",") + expected = MultiIndex.from_tuples([("a", ",", "b"), ("c", ",", "d")]) + assert result.nlevels == 3 + tm.assert_index_equal(result, expected) + + +def test_partition_index_with_name_expand_false(): + idx = Index(["a,b", "c,d"], name="xxx") + # should preserve name + result = idx.str.partition(",", expand=False) + expected = Index(np.array([("a", ",", "b"), ("c", ",", "d")]), name="xxx") + assert result.nlevels == 1 + tm.assert_index_equal(result, expected) + + +@pytest.mark.parametrize("method", ["partition", "rpartition"]) +def test_partition_sep_kwarg(any_string_dtype, method): + # GH 22676; depr kwarg "pat" in favor of "sep" + s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype) + + expected = getattr(s.str, method)(sep="_") + result = getattr(s.str, method)("_") + tm.assert_frame_equal(result, expected) + + +def test_get(): + ser = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"]) + result = ser.str.split("_").str.get(1) + expected = Series(["b", "d", np.nan, "g"], dtype=object) + tm.assert_series_equal(result, expected) + + +def test_get_mixed_object(): + ser = Series(["a_b_c", np.nan, "c_d_e", True, datetime.today(), None, 1, 2.0]) + result = ser.str.split("_").str.get(1) + expected = Series( + ["b", np.nan, "d", np.nan, np.nan, None, np.nan, np.nan], dtype=object + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("idx", [2, -3]) +def test_get_bounds(idx): + ser = Series(["1_2_3_4_5", "6_7_8_9_10", "11_12"]) + result = ser.str.split("_").str.get(idx) + expected = Series(["3", "8", np.nan], dtype=object) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "idx, exp", [[2, [3, 3, np.nan, "b"]], [-1, [3, 3, np.nan, np.nan]]] +) +def test_get_complex(idx, exp): + # GH 20671, getting value not in dict raising `KeyError` + ser = Series([(1, 2, 3), [1, 2, 3], {1, 2, 3}, {1: "a", 2: "b", 3: "c"}]) + + result = ser.str.get(idx) + expected = Series(exp) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("to_type", [tuple, list, np.array]) +def test_get_complex_nested(to_type): + ser = Series([to_type([to_type([1, 2])])]) + + result = ser.str.get(0) + expected = Series([to_type([1, 2])]) + tm.assert_series_equal(result, expected) + + result = ser.str.get(1) + expected = Series([np.nan]) + tm.assert_series_equal(result, expected) + + +def test_get_strings(any_string_dtype): + ser = Series(["a", "ab", np.nan, "abc"], dtype=any_string_dtype) + result = ser.str.get(2) + expected = Series([np.nan, np.nan, np.nan, "c"], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_string_array.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_string_array.py new file mode 100644 index 0000000000000000000000000000000000000000..cd3c51232813942b63b2c522dd8c13deb485b4bc --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_string_array.py @@ -0,0 +1,111 @@ +import numpy as np +import pytest + +from pandas._libs import lib + +from pandas import ( + NA, + DataFrame, + Series, + _testing as tm, + option_context, +) + + +def test_string_array(nullable_string_dtype, any_string_method): + method_name, args, kwargs = any_string_method + + data = ["a", "bb", np.nan, "ccc"] + a = Series(data, dtype=object) + b = Series(data, dtype=nullable_string_dtype) + + if method_name == "decode": + with pytest.raises(TypeError, match="a bytes-like object is required"): + getattr(b.str, method_name)(*args, **kwargs) + return + + expected = getattr(a.str, method_name)(*args, **kwargs) + result = getattr(b.str, method_name)(*args, **kwargs) + + if isinstance(expected, Series): + if expected.dtype == "object" and lib.is_string_array( + expected.dropna().values, + ): + assert result.dtype == nullable_string_dtype + result = result.astype(object) + + elif expected.dtype == "object" and lib.is_bool_array( + expected.values, skipna=True + ): + assert result.dtype == "boolean" + expected = expected.astype("boolean") + + elif expected.dtype == "bool": + assert result.dtype == "boolean" + result = result.astype("bool") + + elif expected.dtype == "float" and expected.isna().any(): + assert result.dtype == "Int64" + result = result.astype("float") + + if expected.dtype == object: + # GH#18463 + expected[expected.isna()] = NA + + elif isinstance(expected, DataFrame): + columns = expected.select_dtypes(include="object").columns + assert all(result[columns].dtypes == nullable_string_dtype) + result[columns] = result[columns].astype(object) + with option_context("future.no_silent_downcasting", True): + expected[columns] = expected[columns].fillna(NA) # GH#18463 + + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "method,expected", + [ + ("count", [2, None]), + ("find", [0, None]), + ("index", [0, None]), + ("rindex", [2, None]), + ], +) +def test_string_array_numeric_integer_array(nullable_string_dtype, method, expected): + s = Series(["aba", None], dtype=nullable_string_dtype) + result = getattr(s.str, method)("a") + expected = Series(expected, dtype="Int64") + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method,expected", + [ + ("isdigit", [False, None, True]), + ("isalpha", [True, None, False]), + ("isalnum", [True, None, True]), + ("isnumeric", [False, None, True]), + ], +) +def test_string_array_boolean_array(nullable_string_dtype, method, expected): + s = Series(["a", None, "1"], dtype=nullable_string_dtype) + result = getattr(s.str, method)() + expected = Series(expected, dtype="boolean") + tm.assert_series_equal(result, expected) + + +def test_string_array_extract(nullable_string_dtype): + # https://github.com/pandas-dev/pandas/issues/30969 + # Only expand=False & multiple groups was failing + + a = Series(["a1", "b2", "cc"], dtype=nullable_string_dtype) + b = Series(["a1", "b2", "cc"], dtype="object") + pat = r"(\w)(\d)" + + result = a.str.extract(pat, expand=False) + expected = b.str.extract(pat, expand=False) + expected = expected.fillna(NA) # GH#18463 + assert all(result.dtypes == nullable_string_dtype) + + result = result.astype(object) + tm.assert_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_strings.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_strings.py new file mode 100644 index 0000000000000000000000000000000000000000..5ac343b45c0c6d07cebb404b647cd71271b184bf --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/strings/test_strings.py @@ -0,0 +1,846 @@ +from datetime import ( + datetime, + timedelta, +) +from pathlib import Path + +import numpy as np +import pytest + +from pandas.compat import pa_version_under21p0 + +from pandas import ( + NA, + DataFrame, + Index, + MultiIndex, + Series, + StringDtype, +) +import pandas._testing as tm +from pandas.core.strings.accessor import StringMethods +from pandas.tests.strings import is_object_or_nan_string_dtype + + +@pytest.mark.parametrize("pattern", [0, True, Series(["foo", "bar"])]) +def test_startswith_endswith_non_str_patterns(pattern): + # GH3485 + ser = Series(["foo", "bar"]) + msg = f"expected a string or tuple, not {type(pattern).__name__}" + with pytest.raises(TypeError, match=msg): + ser.str.startswith(pattern) + with pytest.raises(TypeError, match=msg): + ser.str.endswith(pattern) + + +def test_iter_raises(): + # GH 54173 + ser = Series(["foo", "bar"]) + with pytest.raises(TypeError, match="'StringMethods' object is not iterable"): + iter(ser.str) + + +# test integer/float dtypes (inferred by constructor) and mixed + + +def test_count(any_string_dtype): + ser = Series(["foo", "foofoo", np.nan, "foooofooofommmfoo"], dtype=any_string_dtype) + result = ser.str.count("f[o]+") + expected_dtype = ( + np.float64 if is_object_or_nan_string_dtype(any_string_dtype) else "Int64" + ) + expected = Series([1, 2, np.nan, 4], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_count_mixed_object(): + ser = Series( + ["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0], + dtype=object, + ) + result = ser.str.count("a") + expected = Series([1, np.nan, 0, np.nan, np.nan, 0, np.nan, np.nan, np.nan]) + tm.assert_series_equal(result, expected) + + +def test_repeat(any_string_dtype): + ser = Series(["a", "b", np.nan, "c", np.nan, "d"], dtype=any_string_dtype) + + result = ser.str.repeat(3) + expected = Series( + ["aaa", "bbb", np.nan, "ccc", np.nan, "ddd"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + result = ser.str.repeat([1, 2, 3, 4, 5, 6]) + expected = Series( + ["a", "bb", np.nan, "cccc", np.nan, "dddddd"], dtype=any_string_dtype + ) + tm.assert_series_equal(result, expected) + + +def test_repeat_mixed_object(): + ser = Series(["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0]) + result = ser.str.repeat(3) + expected = Series( + ["aaa", np.nan, "bbb", np.nan, np.nan, "foofoofoo", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("arg, repeat", [[None, 4], ["b", None]]) +def test_repeat_with_null(any_string_dtype, arg, repeat): + # GH: 31632 + ser = Series(["a", arg], dtype=any_string_dtype) + result = ser.str.repeat([3, repeat]) + expected = Series(["aaa", None], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_empty_str_methods(any_string_dtype): + empty_str = empty = Series(dtype=any_string_dtype) + empty_inferred_str = Series(dtype="str") + if is_object_or_nan_string_dtype(any_string_dtype): + empty_int = Series(dtype="int64") + empty_bool = Series(dtype=bool) + else: + empty_int = Series(dtype="Int64") + empty_bool = Series(dtype="boolean") + empty_object = Series(dtype=object) + empty_bytes = Series(dtype=object) + empty_df = DataFrame() + + # GH7241 + # (extract) on empty series + + tm.assert_series_equal(empty_str, empty.str.cat(empty)) + assert "" == empty.str.cat() + tm.assert_series_equal(empty_str, empty.str.title()) + tm.assert_series_equal(empty_int, empty.str.count("a")) + tm.assert_series_equal(empty_bool, empty.str.contains("a")) + tm.assert_series_equal(empty_bool, empty.str.startswith("a")) + tm.assert_series_equal(empty_bool, empty.str.endswith("a")) + tm.assert_series_equal(empty_str, empty.str.lower()) + tm.assert_series_equal(empty_str, empty.str.upper()) + tm.assert_series_equal(empty_str, empty.str.replace("a", "b")) + tm.assert_series_equal(empty_str, empty.str.repeat(3)) + tm.assert_series_equal(empty_bool, empty.str.match("^a")) + tm.assert_frame_equal( + DataFrame(columns=[0], dtype=any_string_dtype), + empty.str.extract("()", expand=True), + ) + tm.assert_frame_equal( + DataFrame(columns=[0, 1], dtype=any_string_dtype), + empty.str.extract("()()", expand=True), + ) + tm.assert_series_equal(empty_str, empty.str.extract("()", expand=False)) + tm.assert_frame_equal( + DataFrame(columns=[0, 1], dtype=any_string_dtype), + empty.str.extract("()()", expand=False), + ) + tm.assert_frame_equal(empty_df.set_axis([], axis=1), empty.str.get_dummies()) + tm.assert_series_equal(empty_str, empty_str.str.join("")) + tm.assert_series_equal(empty_int, empty.str.len()) + tm.assert_series_equal(empty_object, empty_str.str.findall("a")) + tm.assert_series_equal(empty_int, empty.str.find("a")) + tm.assert_series_equal(empty_int, empty.str.rfind("a")) + tm.assert_series_equal(empty_str, empty.str.pad(42)) + tm.assert_series_equal(empty_str, empty.str.center(42)) + tm.assert_series_equal(empty_object, empty.str.split("a")) + tm.assert_series_equal(empty_object, empty.str.rsplit("a")) + tm.assert_series_equal(empty_object, empty.str.partition("a", expand=False)) + tm.assert_frame_equal(empty_df, empty.str.partition("a")) + tm.assert_series_equal(empty_object, empty.str.rpartition("a", expand=False)) + tm.assert_frame_equal(empty_df, empty.str.rpartition("a")) + tm.assert_series_equal(empty_str, empty.str.slice(stop=1)) + tm.assert_series_equal(empty_str, empty.str.slice(step=1)) + tm.assert_series_equal(empty_str, empty.str.strip()) + tm.assert_series_equal(empty_str, empty.str.lstrip()) + tm.assert_series_equal(empty_str, empty.str.rstrip()) + tm.assert_series_equal(empty_str, empty.str.wrap(42)) + tm.assert_series_equal(empty_str, empty.str.get(0)) + tm.assert_series_equal(empty_inferred_str, empty_bytes.str.decode("ascii")) + tm.assert_series_equal(empty_bytes, empty.str.encode("ascii")) + # ismethods should always return boolean (GH 29624) + tm.assert_series_equal(empty_bool, empty.str.isalnum()) + tm.assert_series_equal(empty_bool, empty.str.isalpha()) + tm.assert_series_equal(empty_bool, empty.str.isdigit()) + tm.assert_series_equal(empty_bool, empty.str.isspace()) + tm.assert_series_equal(empty_bool, empty.str.islower()) + tm.assert_series_equal(empty_bool, empty.str.isupper()) + tm.assert_series_equal(empty_bool, empty.str.istitle()) + tm.assert_series_equal(empty_bool, empty.str.isnumeric()) + tm.assert_series_equal(empty_bool, empty.str.isdecimal()) + tm.assert_series_equal(empty_str, empty.str.capitalize()) + tm.assert_series_equal(empty_str, empty.str.swapcase()) + tm.assert_series_equal(empty_str, empty.str.normalize("NFC")) + + table = str.maketrans("a", "b") + tm.assert_series_equal(empty_str, empty.str.translate(table)) + + +@pytest.mark.parametrize( + "method, expected", + [ + ("isalnum", [True, True, True, True, True, False, True, True, False, False]), + ("isalpha", [True, True, True, False, False, False, True, False, False, False]), + ( + "isdigit", + [False, False, False, True, False, False, False, True, False, False], + ), + ( + "isnumeric", + [False, False, False, True, False, False, False, True, False, False], + ), + ( + "isspace", + [False, False, False, False, False, False, False, False, False, True], + ), + ( + "islower", + [False, True, False, False, False, False, False, False, False, False], + ), + ( + "isupper", + [True, False, False, False, True, False, True, False, False, False], + ), + ( + "istitle", + [True, False, True, False, True, False, False, False, False, False], + ), + ], +) +def test_ismethods(method, expected, any_string_dtype): + ser = Series( + ["A", "b", "Xy", "4", "3A", "", "TT", "55", "-", " "], dtype=any_string_dtype + ) + expected_dtype = ( + "bool" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series(expected, dtype=expected_dtype) + result = getattr(ser.str, method)() + tm.assert_series_equal(result, expected) + + # compare with standard library + expected_stdlib = [getattr(item, method)() for item in ser] + assert list(result) == expected_stdlib + + # with missing value + ser.iloc[[1, 2, 3, 4]] = np.nan + result = getattr(ser.str, method)() + if ser.dtype == "object": + expected = expected.astype(object) + expected.iloc[[1, 2, 3, 4]] = np.nan + elif ser.dtype == "str": + # NaN propagates as False + expected.iloc[[1, 2, 3, 4]] = False + else: + # nullable dtypes propagate NaN + expected.iloc[[1, 2, 3, 4]] = np.nan + + +@pytest.mark.parametrize( + "method, expected", + [ + ("isnumeric", [False, True, True, True, False, True, True, False]), + ("isdecimal", [False, True, False, False, False, False, True, False]), + ("isdigit", [False, True, True, False, False, False, True, False]), + ], +) +def test_isnumeric_unicode(method, expected, any_string_dtype): + # 0x00bc: ¼ VULGAR FRACTION ONE QUARTER + # 0x2605: ★ not number + # 0x1378: ፸ ETHIOPIC NUMBER SEVENTY + # 0xFF13: ３ Em 3 # noqa: RUF003 + ser = Series( + ["A", "3", "³", "¼", "★", "፸", "３", "four"], # noqa: RUF001 + dtype=any_string_dtype, + ) + expected_dtype = ( + "bool" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series(expected, dtype=expected_dtype) + if ( + method == "isdigit" + and isinstance(ser.dtype, StringDtype) + and ser.dtype.storage == "pyarrow" + and not pa_version_under21p0 + ): + # known difference in behavior between python and pyarrow unicode handling + # pyarrow 21+ considers ¼ and ፸ as a digit, while python does not + expected.iloc[3] = True + expected.iloc[5] = True + + result = getattr(ser.str, method)() + tm.assert_series_equal(result, expected) + + # compare with standard library + # (only for non-pyarrow storage given the above differences) + if any_string_dtype == "object" or ( + isinstance(any_string_dtype, StringDtype) + and any_string_dtype.storage == "python" + ): + expected = [getattr(item, method)() for item in ser] + assert list(result) == expected + + +@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning") +@pytest.mark.parametrize( + "method, expected", + [ + ("isnumeric", [False, np.nan, True, False, np.nan, True, False]), + ("isdecimal", [False, np.nan, False, False, np.nan, True, False]), + ], +) +def test_isnumeric_unicode_missing(method, expected, any_string_dtype): + values = ["A", np.nan, "¼", "★", np.nan, "３", "four"] # noqa: RUF001 + ser = Series(values, dtype=any_string_dtype) + if any_string_dtype == "str": + # NaN propagates as False + expected = Series(expected, dtype=object).fillna(False).astype(bool) + else: + expected_dtype = ( + "object" if is_object_or_nan_string_dtype(any_string_dtype) else "boolean" + ) + expected = Series(expected, dtype=expected_dtype) + result = getattr(ser.str, method)() + tm.assert_series_equal(result, expected) + + +def test_spilt_join_roundtrip(any_string_dtype): + ser = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype) + result = ser.str.split("_").str.join("_") + expected = ser.astype(object) + tm.assert_series_equal(result, expected) + + +def test_spilt_join_roundtrip_mixed_object(): + ser = Series( + ["a_b", np.nan, "asdf_cas_asdf", True, datetime.today(), "foo", None, 1, 2.0] + ) + result = ser.str.split("_").str.join("_") + expected = Series( + ["a_b", np.nan, "asdf_cas_asdf", np.nan, np.nan, "foo", None, np.nan, np.nan], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + +def test_len(any_string_dtype): + ser = Series( + ["foo", "fooo", "fooooo", np.nan, "fooooooo", "foo\n", "あ"], + dtype=any_string_dtype, + ) + result = ser.str.len() + expected_dtype = ( + "float64" if is_object_or_nan_string_dtype(any_string_dtype) else "Int64" + ) + expected = Series([3, 4, 6, np.nan, 8, 4, 1], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_len_mixed(): + ser = Series( + ["a_b", np.nan, "asdf_cas_asdf", True, datetime.today(), "foo", None, 1, 2.0] + ) + result = ser.str.len() + expected = Series([3, np.nan, 13, np.nan, np.nan, 3, np.nan, np.nan, np.nan]) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method,sub,start,end,expected", + [ + ("index", "EF", None, None, [4, 3, 1, 0]), + ("rindex", "EF", None, None, [4, 5, 7, 4]), + ("index", "EF", 3, None, [4, 3, 7, 4]), + ("rindex", "EF", 3, None, [4, 5, 7, 4]), + ("index", "E", 4, 8, [4, 5, 7, 4]), + ("rindex", "E", 0, 5, [4, 3, 1, 4]), + ], +) +def test_index(method, sub, start, end, index_or_series, any_string_dtype, expected): + obj = index_or_series( + ["ABCDEFG", "BCDEFEF", "DEFGHIJEF", "EFGHEF"], dtype=any_string_dtype + ) + expected_dtype = ( + np.int64 if is_object_or_nan_string_dtype(any_string_dtype) else "Int64" + ) + expected = index_or_series(expected, dtype=expected_dtype) + + result = getattr(obj.str, method)(sub, start, end) + + if index_or_series is Series: + tm.assert_series_equal(result, expected) + else: + tm.assert_index_equal(result, expected) + + # compare with standard library + expected = [getattr(item, method)(sub, start, end) for item in obj] + assert list(result) == expected + + +def test_index_not_found_raises(index_or_series, any_string_dtype): + obj = index_or_series( + ["ABCDEFG", "BCDEFEF", "DEFGHIJEF", "EFGHEF"], dtype=any_string_dtype + ) + with pytest.raises(ValueError, match="substring not found"): + obj.str.index("DE") + + +@pytest.mark.parametrize("method", ["index", "rindex"]) +def test_index_wrong_type_raises(index_or_series, any_string_dtype, method): + obj = index_or_series([], dtype=any_string_dtype) + msg = "expected a string object, not int" + + with pytest.raises(TypeError, match=msg): + getattr(obj.str, method)(0) + + +@pytest.mark.parametrize( + "method, exp", + [ + ["index", [1, 1, 0]], + ["rindex", [3, 1, 2]], + ], +) +def test_index_missing(any_string_dtype, method, exp): + ser = Series(["abcb", "ab", "bcbe", np.nan], dtype=any_string_dtype) + expected_dtype = ( + np.float64 if is_object_or_nan_string_dtype(any_string_dtype) else "Int64" + ) + + result = getattr(ser.str, method)("b") + expected = Series(exp + [np.nan], dtype=expected_dtype) + tm.assert_series_equal(result, expected) + + +def test_pipe_failures(any_string_dtype): + # #2119 + ser = Series(["A|B|C"], dtype=any_string_dtype) + + result = ser.str.split("|") + expected = Series([["A", "B", "C"]], dtype=object) + tm.assert_series_equal(result, expected) + + result = ser.str.replace("|", " ", regex=False) + expected = Series(["A B C"], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "start, stop, step, expected", + [ + (2, 5, None, ["foo", "bar", np.nan, "baz"]), + (0, 3, -1, ["", "", np.nan, ""]), + (None, None, -1, ["owtoofaa", "owtrabaa", np.nan, "xuqzabaa"]), + (None, 2, -1, ["owtoo", "owtra", np.nan, "xuqza"]), + (3, 10, 2, ["oto", "ato", np.nan, "aqx"]), + (3, 0, -1, ["ofa", "aba", np.nan, "aba"]), + ], +) +def test_slice(start, stop, step, expected, any_string_dtype): + ser = Series(["aafootwo", "aabartwo", np.nan, "aabazqux"], dtype=any_string_dtype) + result = ser.str.slice(start, stop, step) + expected = Series(expected, dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "start, stop, step, expected", + [ + (2, 5, None, ["foo", np.nan, "bar", np.nan, np.nan, None, np.nan, np.nan]), + (4, 1, -1, ["oof", np.nan, "rab", np.nan, np.nan, None, np.nan, np.nan]), + ], +) +def test_slice_mixed_object(start, stop, step, expected): + ser = Series(["aafootwo", np.nan, "aabartwo", True, datetime.today(), None, 1, 2.0]) + result = ser.str.slice(start, stop, step) + expected = Series(expected, dtype=object) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "start,stop,repl,expected", + [ + (2, 3, None, ["shrt", "a it longer", "evnlongerthanthat", "", np.nan]), + (2, 3, "z", ["shzrt", "a zit longer", "evznlongerthanthat", "z", np.nan]), + (2, 2, "z", ["shzort", "a zbit longer", "evzenlongerthanthat", "z", np.nan]), + (2, 1, "z", ["shzort", "a zbit longer", "evzenlongerthanthat", "z", np.nan]), + (-1, None, "z", ["shorz", "a bit longez", "evenlongerthanthaz", "z", np.nan]), + (None, -2, "z", ["zrt", "zer", "zat", "z", np.nan]), + (6, 8, "z", ["shortz", "a bit znger", "evenlozerthanthat", "z", np.nan]), + (-10, 3, "z", ["zrt", "a zit longer", "evenlongzerthanthat", "z", np.nan]), + ], +) +def test_slice_replace(start, stop, repl, expected, any_string_dtype): + ser = Series( + ["short", "a bit longer", "evenlongerthanthat", "", np.nan], + dtype=any_string_dtype, + ) + expected = Series(expected, dtype=any_string_dtype) + result = ser.str.slice_replace(start, stop, repl) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method, exp", + [ + ["strip", ["aa", "bb", np.nan, "cc"]], + ["lstrip", ["aa ", "bb \n", np.nan, "cc "]], + ["rstrip", [" aa", " bb", np.nan, "cc"]], + ], +) +def test_strip_lstrip_rstrip(any_string_dtype, method, exp): + ser = Series([" aa ", " bb \n", np.nan, "cc "], dtype=any_string_dtype) + + result = getattr(ser.str, method)() + expected = Series(exp, dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method, exp", + [ + ["strip", ["aa", np.nan, "bb"]], + ["lstrip", ["aa ", np.nan, "bb \t\n"]], + ["rstrip", [" aa", np.nan, " bb"]], + ], +) +def test_strip_lstrip_rstrip_mixed_object(method, exp): + ser = Series([" aa ", np.nan, " bb \t\n", True, datetime.today(), None, 1, 2.0]) + + result = getattr(ser.str, method)() + expected = Series(exp + [np.nan, np.nan, None, np.nan, np.nan], dtype=object) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method, exp", + [ + ["strip", ["ABC", " BNSD", "LDFJH "]], + ["lstrip", ["ABCxx", " BNSD", "LDFJH xx"]], + ["rstrip", ["xxABC", "xx BNSD", "LDFJH "]], + ], +) +def test_strip_lstrip_rstrip_args(any_string_dtype, method, exp): + ser = Series(["xxABCxx", "xx BNSD", "LDFJH xx"], dtype=any_string_dtype) + + result = getattr(ser.str, method)("x") + expected = Series(exp, dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "prefix, expected", [("a", ["b", " b c", "bc"]), ("ab", ["", "a b c", "bc"])] +) +def test_removeprefix(any_string_dtype, prefix, expected): + ser = Series(["ab", "a b c", "bc"], dtype=any_string_dtype) + result = ser.str.removeprefix(prefix) + ser_expected = Series(expected, dtype=any_string_dtype) + tm.assert_series_equal(result, ser_expected) + + +@pytest.mark.parametrize( + "suffix, expected", [("c", ["ab", "a b ", "b"]), ("bc", ["ab", "a b c", ""])] +) +def test_removesuffix(any_string_dtype, suffix, expected): + ser = Series(["ab", "a b c", "bc"], dtype=any_string_dtype) + result = ser.str.removesuffix(suffix) + ser_expected = Series(expected, dtype=any_string_dtype) + tm.assert_series_equal(result, ser_expected) + + +def test_string_slice_get_syntax(any_string_dtype): + ser = Series( + ["YYY", "B", "C", "YYYYYYbYYY", "BYYYcYYY", np.nan, "CYYYBYYY", "dog", "cYYYt"], + dtype=any_string_dtype, + ) + + result = ser.str[0] + expected = ser.str.get(0) + tm.assert_series_equal(result, expected) + + result = ser.str[:3] + expected = ser.str.slice(stop=3) + tm.assert_series_equal(result, expected) + + result = ser.str[2::-1] + expected = ser.str.slice(start=2, step=-1) + tm.assert_series_equal(result, expected) + + +def test_string_slice_out_of_bounds_nested(): + ser = Series([(1, 2), (1,), (3, 4, 5)]) + result = ser.str[1] + expected = Series([2, np.nan, 4]) + tm.assert_series_equal(result, expected) + + +def test_string_slice_out_of_bounds(any_string_dtype): + ser = Series(["foo", "b", "ba"], dtype=any_string_dtype) + result = ser.str[1] + expected = Series(["o", np.nan, "a"], dtype=any_string_dtype) + tm.assert_series_equal(result, expected) + + +def test_encode_decode(any_string_dtype): + ser = Series(["a", "b", "a\xe4"], dtype=any_string_dtype).str.encode("utf-8") + result = ser.str.decode("utf-8") + expected = Series(["a", "b", "a\xe4"], dtype="str") + tm.assert_series_equal(result, expected) + + +def test_encode_errors_kwarg(any_string_dtype): + ser = Series(["a", "b", "a\x9d"], dtype=any_string_dtype) + + msg = ( + r"'charmap' codec can't encode character '\\x9d' in position 1: " + "character maps to " + ) + with pytest.raises(UnicodeEncodeError, match=msg): + ser.str.encode("cp1252") + + result = ser.str.encode("cp1252", "ignore") + expected = ser.map(lambda x: x.encode("cp1252", "ignore")) + tm.assert_series_equal(result, expected) + + +def test_decode_errors_kwarg(): + ser = Series([b"a", b"b", b"a\x9d"]) + + msg = ( + "'charmap' codec can't decode byte 0x9d in position 1: " + "character maps to " + ) + with pytest.raises(UnicodeDecodeError, match=msg): + ser.str.decode("cp1252") + + result = ser.str.decode("cp1252", "ignore") + expected = ser.map(lambda x: x.decode("cp1252", "ignore")).astype("str") + tm.assert_series_equal(result, expected) + + +def test_decode_string_dtype(string_dtype): + # https://github.com/pandas-dev/pandas/pull/60940 + ser = Series([b"a", b"b"]) + result = ser.str.decode("utf-8", dtype=string_dtype) + expected = Series(["a", "b"], dtype=string_dtype) + tm.assert_series_equal(result, expected) + + +def test_decode_object_dtype(object_dtype): + # https://github.com/pandas-dev/pandas/pull/60940 + ser = Series([b"a", rb"\ud800"]) + result = ser.str.decode("utf-8", dtype=object_dtype) + expected = Series(["a", r"\ud800"], dtype=object_dtype) + tm.assert_series_equal(result, expected) + + +def test_decode_bad_dtype(): + # https://github.com/pandas-dev/pandas/pull/60940 + ser = Series([b"a", b"b"]) + msg = "dtype must be string or object, got dtype='int64'" + with pytest.raises(ValueError, match=msg): + ser.str.decode("utf-8", dtype="int64") + + +@pytest.mark.parametrize( + "form, expected", + [ + ("NFKC", ["ABC", "ABC", "123", np.nan, "アイエ"]), + ("NFC", ["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"]), # noqa: RUF001 + ], +) +def test_normalize(form, expected, any_string_dtype): + ser = Series( + ["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"], # noqa: RUF001 + index=["a", "b", "c", "d", "e"], + dtype=any_string_dtype, + ) + expected = Series(expected, index=["a", "b", "c", "d", "e"], dtype=any_string_dtype) + result = ser.str.normalize(form) + tm.assert_series_equal(result, expected) + + +def test_normalize_bad_arg_raises(any_string_dtype): + ser = Series( + ["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"], # noqa: RUF001 + index=["a", "b", "c", "d", "e"], + dtype=any_string_dtype, + ) + with pytest.raises(ValueError, match="invalid normalization form"): + ser.str.normalize("xxx") + + +def test_normalize_index(): + idx = Index(["ＡＢＣ", "１２３", "ｱｲｴ"]) # noqa: RUF001 + expected = Index(["ABC", "123", "アイエ"]) + result = idx.str.normalize("NFKC") + tm.assert_index_equal(result, expected) + + +@pytest.mark.parametrize( + "values,inferred_type", + [ + (["a", "b"], "string"), + (["a", "b", 1], "mixed-integer"), + (["a", "b", 1.3], "mixed"), + (["a", "b", 1.3, 1], "mixed-integer"), + (["aa", datetime(2011, 1, 1)], "mixed"), + ], +) +def test_index_str_accessor_visibility(values, inferred_type, index_or_series): + obj = index_or_series(values) + if index_or_series is Index: + assert obj.inferred_type == inferred_type + + assert isinstance(obj.str, StringMethods) + + +@pytest.mark.parametrize( + "values,inferred_type", + [ + ([1, np.nan], "floating"), + ([datetime(2011, 1, 1)], "datetime64"), + ([timedelta(1)], "timedelta64"), + ], +) +def test_index_str_accessor_non_string_values_raises( + values, inferred_type, index_or_series +): + obj = index_or_series(values) + if index_or_series is Index: + assert obj.inferred_type == inferred_type + + msg = "Can only use .str accessor with string values" + with pytest.raises(AttributeError, match=msg): + obj.str + + +def test_index_str_accessor_multiindex_raises(): + # MultiIndex has mixed dtype, but not allow to use accessor + idx = MultiIndex.from_tuples([("a", "b"), ("a", "b")]) + assert idx.inferred_type == "mixed" + + msg = "Can only use .str accessor with Index, not MultiIndex" + with pytest.raises(AttributeError, match=msg): + idx.str + + +def test_str_accessor_no_new_attributes(any_string_dtype): + # https://github.com/pandas-dev/pandas/issues/10673 + ser = Series(list("aabbcde"), dtype=any_string_dtype) + with pytest.raises(AttributeError, match="You cannot add any new attribute"): + ser.str.xlabel = "a" + + +def test_cat_on_bytes_raises(): + lhs = Series(np.array(list("abc"), "S1").astype(object)) + rhs = Series(np.array(list("def"), "S1").astype(object)) + msg = "Cannot use .str.cat with values of inferred dtype 'bytes'" + with pytest.raises(TypeError, match=msg): + lhs.str.cat(rhs) + + +def test_str_accessor_in_apply_func(): + # https://github.com/pandas-dev/pandas/issues/38979 + df = DataFrame(zip("abc", "def")) + expected = Series(["A/D", "B/E", "C/F"]) + result = df.apply(lambda f: "/".join(f.str.upper()), axis=1) + tm.assert_series_equal(result, expected) + + +def test_zfill(): + # https://github.com/pandas-dev/pandas/issues/20868 + value = Series(["-1", "1", "1000", 10, np.nan]) + expected = Series(["-01", "001", "1000", np.nan, np.nan], dtype=object) + tm.assert_series_equal(value.str.zfill(3), expected) + + value = Series(["-2", "+5"]) + expected = Series(["-0002", "+0005"]) + tm.assert_series_equal(value.str.zfill(5), expected) + + +def test_zfill_with_non_integer_argument(): + value = Series(["-2", "+5"]) + wid = "a" + msg = f"width must be of integer type, not {type(wid).__name__}" + with pytest.raises(TypeError, match=msg): + value.str.zfill(wid) + + +def test_zfill_with_leading_sign(): + value = Series(["-cat", "-1", "+dog"]) + expected = Series(["-0cat", "-0001", "+0dog"]) + tm.assert_series_equal(value.str.zfill(5), expected) + + +def test_get_with_dict_label(): + # GH47911 + s = Series( + [ + {"name": "Hello", "value": "World"}, + {"name": "Goodbye", "value": "Planet"}, + {"value": "Sea"}, + ] + ) + result = s.str.get("name") + expected = Series(["Hello", "Goodbye", None], dtype=object) + tm.assert_series_equal(result, expected) + result = s.str.get("value") + expected = Series(["World", "Planet", "Sea"], dtype=object) + tm.assert_series_equal(result, expected) + + +def test_series_str_decode(): + # GH 22613 + result = Series([b"x", b"y"]).str.decode(encoding="UTF-8", errors="strict") + expected = Series(["x", "y"], dtype="str") + tm.assert_series_equal(result, expected) + + +def test_reversed_logical_ops(any_string_dtype): + # GH#60234 + dtype = any_string_dtype + warn = None if dtype == object else DeprecationWarning + left = Series([True, False, False, True]) + right = Series(["", "", "b", "c"], dtype=dtype) + + msg = "operations between boolean dtype and" + with tm.assert_produces_warning(warn, match=msg): + result = left | right + expected = left | right.astype(bool) + tm.assert_series_equal(result, expected) + + with tm.assert_produces_warning(warn, match=msg): + result = left & right + expected = left & right.astype(bool) + tm.assert_series_equal(result, expected) + + with tm.assert_produces_warning(warn, match=msg): + result = left ^ right + expected = left ^ right.astype(bool) + tm.assert_series_equal(result, expected) + + +def test_pathlib_path_division(any_string_dtype, request): + # GH#61940 + if any_string_dtype == object: + mark = pytest.mark.xfail( + reason="with NA present we go through _masked_arith_op which " + "raises TypeError bc Path is not recognized by lib.is_scalar." + ) + request.applymarker(mark) + + item = Path("/Users/Irv/") + ser = Series(["A", "B", NA], dtype=any_string_dtype) + + result = item / ser + expected = Series([item / "A", item / "B", ser.dtype.na_value], dtype=object) + tm.assert_series_equal(result, expected) + + result = ser / item + expected = Series(["A" / item, "B" / item, ser.dtype.na_value], dtype=object) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_datetime.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_datetime.py new file mode 100644 index 0000000000000000000000000000000000000000..e226dac88b8824b68136b6e2efcba738e799c193 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_datetime.py @@ -0,0 +1,3926 @@ +""" test to_datetime """ + +import calendar +from collections import deque +from datetime import ( + date, + datetime, + timedelta, + timezone, +) +from decimal import Decimal +import locale + +from dateutil.parser import parse +from dateutil.tz.tz import tzoffset +import numpy as np +import pytest +import pytz + +from pandas._libs import tslib +from pandas._libs.tslibs import ( + iNaT, + parsing, +) +from pandas.compat import PY314 +from pandas.errors import ( + OutOfBoundsDatetime, + OutOfBoundsTimedelta, +) +import pandas.util._test_decorators as td + +from pandas.core.dtypes.common import is_datetime64_ns_dtype + +import pandas as pd +from pandas import ( + DataFrame, + DatetimeIndex, + Index, + NaT, + Series, + Timestamp, + date_range, + isna, + to_datetime, +) +import pandas._testing as tm +from pandas.core.arrays import DatetimeArray +from pandas.core.tools import datetimes as tools +from pandas.core.tools.datetimes import start_caching_at + +PARSING_ERR_MSG = ( + r"You might want to try:\n" + r" - passing `format` if your strings have a consistent format;\n" + r" - passing `format=\'ISO8601\'` if your strings are all ISO8601 " + r"but not necessarily in exactly the same format;\n" + r" - passing `format=\'mixed\'`, and the format will be inferred " + r"for each element individually. You might want to use `dayfirst` " + r"alongside this." +) + +if PY314: + NOT_99 = ", not 99" + DAY_IS_OUT_OF_RANGE = ( + r"day \d{1,2} must be in range 1\.\.\d{1,2} for month \d{1,2} in year \d{4}" + ", at position 0" + ) +else: + NOT_99 = "" + DAY_IS_OUT_OF_RANGE = "day is out of range for month, at position 0" + + +pytestmark = pytest.mark.filterwarnings( + "ignore:errors='ignore' is deprecated:FutureWarning" +) + + +@pytest.fixture(params=[True, False]) +def cache(request): + """ + cache keyword to pass to to_datetime. + """ + return request.param + + +class TestTimeConversionFormats: + @pytest.mark.parametrize("readonly", [True, False]) + def test_to_datetime_readonly(self, readonly): + # GH#34857 + arr = np.array([], dtype=object) + if readonly: + arr.setflags(write=False) + result = to_datetime(arr) + expected = to_datetime([]) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "format, expected", + [ + [ + "%d/%m/%Y", + [Timestamp("20000101"), Timestamp("20000201"), Timestamp("20000301")], + ], + [ + "%m/%d/%Y", + [Timestamp("20000101"), Timestamp("20000102"), Timestamp("20000103")], + ], + ], + ) + def test_to_datetime_format(self, cache, index_or_series, format, expected): + values = index_or_series(["1/1/2000", "1/2/2000", "1/3/2000"]) + result = to_datetime(values, format=format, cache=cache) + expected = index_or_series(expected) + tm.assert_equal(result, expected) + + @pytest.mark.parametrize( + "arg, expected, format", + [ + ["1/1/2000", "20000101", "%d/%m/%Y"], + ["1/1/2000", "20000101", "%m/%d/%Y"], + ["1/2/2000", "20000201", "%d/%m/%Y"], + ["1/2/2000", "20000102", "%m/%d/%Y"], + ["1/3/2000", "20000301", "%d/%m/%Y"], + ["1/3/2000", "20000103", "%m/%d/%Y"], + ], + ) + def test_to_datetime_format_scalar(self, cache, arg, expected, format): + result = to_datetime(arg, format=format, cache=cache) + expected = Timestamp(expected) + assert result == expected + + def test_to_datetime_format_YYYYMMDD(self, cache): + ser = Series([19801222, 19801222] + [19810105] * 5) + expected = Series([Timestamp(x) for x in ser.apply(str)]) + + result = to_datetime(ser, format="%Y%m%d", cache=cache) + tm.assert_series_equal(result, expected) + + result = to_datetime(ser.apply(str), format="%Y%m%d", cache=cache) + tm.assert_series_equal(result, expected) + + def test_to_datetime_format_YYYYMMDD_with_nat(self, cache): + # Explicit cast to float to explicit cast when setting np.nan + ser = Series([19801222, 19801222] + [19810105] * 5, dtype="float") + # with NaT + expected = Series( + [Timestamp("19801222"), Timestamp("19801222")] + [Timestamp("19810105")] * 5 + ) + expected[2] = np.nan + ser[2] = np.nan + + result = to_datetime(ser, format="%Y%m%d", cache=cache) + tm.assert_series_equal(result, expected) + + # string with NaT + ser2 = ser.apply(str) + ser2[2] = "nat" + with pytest.raises( + ValueError, + match=( + 'unconverted data remains when parsing with format "%Y%m%d": ".0", ' + "at position 0" + ), + ): + # https://github.com/pandas-dev/pandas/issues/50051 + to_datetime(ser2, format="%Y%m%d", cache=cache) + + def test_to_datetime_format_YYYYMM_with_nat(self, cache): + # https://github.com/pandas-dev/pandas/issues/50237 + # Explicit cast to float to explicit cast when setting np.nan + ser = Series([198012, 198012] + [198101] * 5, dtype="float") + expected = Series( + [Timestamp("19801201"), Timestamp("19801201")] + [Timestamp("19810101")] * 5 + ) + expected[2] = np.nan + ser[2] = np.nan + result = to_datetime(ser, format="%Y%m", cache=cache) + tm.assert_series_equal(result, expected) + + def test_to_datetime_format_YYYYMMDD_ignore(self, cache): + # coercion + # GH 7930, GH 14487 + ser = Series([20121231, 20141231, 99991231]) + result = to_datetime(ser, format="%Y%m%d", errors="ignore", cache=cache) + expected = Series( + [20121231, 20141231, 99991231], + dtype=object, + ) + tm.assert_series_equal(result, expected) + + def test_to_datetime_format_YYYYMMDD_ignore_with_outofbounds(self, cache): + # https://github.com/pandas-dev/pandas/issues/26493 + result = to_datetime( + ["15010101", "20150101", np.nan], + format="%Y%m%d", + errors="ignore", + cache=cache, + ) + expected = Index(["15010101", "20150101", np.nan], dtype=object) + tm.assert_index_equal(result, expected) + + def test_to_datetime_format_YYYYMMDD_coercion(self, cache): + # coercion + # GH 7930 + ser = Series([20121231, 20141231, 99991231]) + result = to_datetime(ser, format="%Y%m%d", errors="coerce", cache=cache) + expected = Series(["20121231", "20141231", "NaT"], dtype="M8[ns]") + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "input_s", + [ + # Null values with Strings + ["19801222", "20010112", None], + ["19801222", "20010112", np.nan], + ["19801222", "20010112", NaT], + ["19801222", "20010112", "NaT"], + # Null values with Integers + [19801222, 20010112, None], + [19801222, 20010112, np.nan], + [19801222, 20010112, NaT], + [19801222, 20010112, "NaT"], + ], + ) + def test_to_datetime_format_YYYYMMDD_with_none(self, input_s): + # GH 30011 + # format='%Y%m%d' + # with None + expected = Series([Timestamp("19801222"), Timestamp("20010112"), NaT]) + result = Series(to_datetime(input_s, format="%Y%m%d")) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "input_s, expected", + [ + # NaN before strings with invalid date values + [ + Series(["19801222", np.nan, "20010012", "10019999"]), + Series([Timestamp("19801222"), np.nan, np.nan, np.nan]), + ], + # NaN after strings with invalid date values + [ + Series(["19801222", "20010012", "10019999", np.nan]), + Series([Timestamp("19801222"), np.nan, np.nan, np.nan]), + ], + # NaN before integers with invalid date values + [ + Series([20190813, np.nan, 20010012, 20019999]), + Series([Timestamp("20190813"), np.nan, np.nan, np.nan]), + ], + # NaN after integers with invalid date values + [ + Series([20190813, 20010012, np.nan, 20019999]), + Series([Timestamp("20190813"), np.nan, np.nan, np.nan]), + ], + ], + ) + def test_to_datetime_format_YYYYMMDD_overflow(self, input_s, expected): + # GH 25512 + # format='%Y%m%d', errors='coerce' + result = to_datetime(input_s, format="%Y%m%d", errors="coerce") + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "data, format, expected", + [ + ([pd.NA], "%Y%m%d%H%M%S", DatetimeIndex(["NaT"])), + ([pd.NA], None, DatetimeIndex(["NaT"])), + ( + [pd.NA, "20210202202020"], + "%Y%m%d%H%M%S", + DatetimeIndex(["NaT", "2021-02-02 20:20:20"]), + ), + (["201010", pd.NA], "%y%m%d", DatetimeIndex(["2020-10-10", "NaT"])), + (["201010", pd.NA], "%d%m%y", DatetimeIndex(["2010-10-20", "NaT"])), + ([None, np.nan, pd.NA], None, DatetimeIndex(["NaT", "NaT", "NaT"])), + ([None, np.nan, pd.NA], "%Y%m%d", DatetimeIndex(["NaT", "NaT", "NaT"])), + ], + ) + def test_to_datetime_with_NA(self, data, format, expected): + # GH#42957 + result = to_datetime(data, format=format) + tm.assert_index_equal(result, expected) + + def test_to_datetime_with_NA_with_warning(self): + # GH#42957 + result = to_datetime(["201010", pd.NA]) + expected = DatetimeIndex(["2010-10-20", "NaT"]) + tm.assert_index_equal(result, expected) + + def test_to_datetime_format_integer(self, cache): + # GH 10178 + ser = Series([2000, 2001, 2002]) + expected = Series([Timestamp(x) for x in ser.apply(str)]) + + result = to_datetime(ser, format="%Y", cache=cache) + tm.assert_series_equal(result, expected) + + ser = Series([200001, 200105, 200206]) + expected = Series([Timestamp(x[:4] + "-" + x[4:]) for x in ser.apply(str)]) + + result = to_datetime(ser, format="%Y%m", cache=cache) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "int_date, expected", + [ + # valid date, length == 8 + [20121030, datetime(2012, 10, 30)], + # short valid date, length == 6 + [199934, datetime(1999, 3, 4)], + # long integer date partially parsed to datetime(2012,1,1), length > 8 + [2012010101, 2012010101], + # invalid date partially parsed to datetime(2012,9,9), length == 8 + [20129930, 20129930], + # short integer date partially parsed to datetime(2012,9,9), length < 8 + [2012993, 2012993], + # short invalid date, length == 4 + [2121, 2121], + ], + ) + def test_int_to_datetime_format_YYYYMMDD_typeerror(self, int_date, expected): + # GH 26583 + result = to_datetime(int_date, format="%Y%m%d", errors="ignore") + assert result == expected + + def test_to_datetime_format_microsecond(self, cache): + month_abbr = calendar.month_abbr[4] + val = f"01-{month_abbr}-2011 00:00:01.978" + + format = "%d-%b-%Y %H:%M:%S.%f" + result = to_datetime(val, format=format, cache=cache) + exp = datetime.strptime(val, format) + assert result == exp + + @pytest.mark.parametrize( + "value, format, dt", + [ + ["01/10/2010 15:20", "%m/%d/%Y %H:%M", Timestamp("2010-01-10 15:20")], + ["01/10/2010 05:43", "%m/%d/%Y %I:%M", Timestamp("2010-01-10 05:43")], + [ + "01/10/2010 13:56:01", + "%m/%d/%Y %H:%M:%S", + Timestamp("2010-01-10 13:56:01"), + ], + # The 3 tests below are locale-dependent. + # They pass, except when the machine locale is zh_CN or it_IT . + pytest.param( + "01/10/2010 08:14 PM", + "%m/%d/%Y %I:%M %p", + Timestamp("2010-01-10 20:14"), + marks=pytest.mark.xfail( + locale.getlocale()[0] in ("zh_CN", "it_IT"), + reason="fail on a CI build with LC_ALL=zh_CN.utf8/it_IT.utf8", + strict=False, + ), + ), + pytest.param( + "01/10/2010 07:40 AM", + "%m/%d/%Y %I:%M %p", + Timestamp("2010-01-10 07:40"), + marks=pytest.mark.xfail( + locale.getlocale()[0] in ("zh_CN", "it_IT"), + reason="fail on a CI build with LC_ALL=zh_CN.utf8/it_IT.utf8", + strict=False, + ), + ), + pytest.param( + "01/10/2010 09:12:56 AM", + "%m/%d/%Y %I:%M:%S %p", + Timestamp("2010-01-10 09:12:56"), + marks=pytest.mark.xfail( + locale.getlocale()[0] in ("zh_CN", "it_IT"), + reason="fail on a CI build with LC_ALL=zh_CN.utf8/it_IT.utf8", + strict=False, + ), + ), + ], + ) + def test_to_datetime_format_time(self, cache, value, format, dt): + assert to_datetime(value, format=format, cache=cache) == dt + + @td.skip_if_not_us_locale + def test_to_datetime_with_non_exact(self, cache): + # GH 10834 + # 8904 + # exact kw + ser = Series( + ["19MAY11", "foobar19MAY11", "19MAY11:00:00:00", "19MAY11 00:00:00Z"] + ) + result = to_datetime(ser, format="%d%b%y", exact=False, cache=cache) + expected = to_datetime( + ser.str.extract(r"(\d+\w+\d+)", expand=False), format="%d%b%y", cache=cache + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "format, expected", + [ + ("%Y-%m-%d", Timestamp(2000, 1, 3)), + ("%Y-%d-%m", Timestamp(2000, 3, 1)), + ("%Y-%m-%d %H", Timestamp(2000, 1, 3, 12)), + ("%Y-%d-%m %H", Timestamp(2000, 3, 1, 12)), + ("%Y-%m-%d %H:%M", Timestamp(2000, 1, 3, 12, 34)), + ("%Y-%d-%m %H:%M", Timestamp(2000, 3, 1, 12, 34)), + ("%Y-%m-%d %H:%M:%S", Timestamp(2000, 1, 3, 12, 34, 56)), + ("%Y-%d-%m %H:%M:%S", Timestamp(2000, 3, 1, 12, 34, 56)), + ("%Y-%m-%d %H:%M:%S.%f", Timestamp(2000, 1, 3, 12, 34, 56, 123456)), + ("%Y-%d-%m %H:%M:%S.%f", Timestamp(2000, 3, 1, 12, 34, 56, 123456)), + ( + "%Y-%m-%d %H:%M:%S.%f%z", + Timestamp(2000, 1, 3, 12, 34, 56, 123456, tz="UTC+01:00"), + ), + ( + "%Y-%d-%m %H:%M:%S.%f%z", + Timestamp(2000, 3, 1, 12, 34, 56, 123456, tz="UTC+01:00"), + ), + ], + ) + def test_non_exact_doesnt_parse_whole_string(self, cache, format, expected): + # https://github.com/pandas-dev/pandas/issues/50412 + # the formats alternate between ISO8601 and non-ISO8601 to check both paths + result = to_datetime( + "2000-01-03 12:34:56.123456+01:00", format=format, exact=False + ) + assert result == expected + + @pytest.mark.parametrize( + "arg", + [ + "2012-01-01 09:00:00.000000001", + "2012-01-01 09:00:00.000001", + "2012-01-01 09:00:00.001", + "2012-01-01 09:00:00.001000", + "2012-01-01 09:00:00.001000000", + ], + ) + def test_parse_nanoseconds_with_formula(self, cache, arg): + # GH8989 + # truncating the nanoseconds when a format was provided + expected = to_datetime(arg, cache=cache) + result = to_datetime(arg, format="%Y-%m-%d %H:%M:%S.%f", cache=cache) + assert result == expected + + @pytest.mark.parametrize( + "value,fmt,expected", + [ + ["2009324", "%Y%W%w", Timestamp("2009-08-13")], + ["2013020", "%Y%U%w", Timestamp("2013-01-13")], + ], + ) + def test_to_datetime_format_weeks(self, value, fmt, expected, cache): + assert to_datetime(value, format=fmt, cache=cache) == expected + + @pytest.mark.parametrize( + "fmt,dates,expected_dates", + [ + [ + "%Y-%m-%d %H:%M:%S %Z", + ["2010-01-01 12:00:00 UTC"] * 2, + [Timestamp("2010-01-01 12:00:00", tz="UTC")] * 2, + ], + [ + "%Y-%m-%d %H:%M:%S%z", + ["2010-01-01 12:00:00+0100"] * 2, + [ + Timestamp( + "2010-01-01 12:00:00", tzinfo=timezone(timedelta(minutes=60)) + ) + ] + * 2, + ], + [ + "%Y-%m-%d %H:%M:%S %z", + ["2010-01-01 12:00:00 +0100"] * 2, + [ + Timestamp( + "2010-01-01 12:00:00", tzinfo=timezone(timedelta(minutes=60)) + ) + ] + * 2, + ], + [ + "%Y-%m-%d %H:%M:%S %z", + ["2010-01-01 12:00:00 Z", "2010-01-01 12:00:00 Z"], + [ + Timestamp( + "2010-01-01 12:00:00", tzinfo=pytz.FixedOffset(0) + ), # pytz coerces to UTC + Timestamp("2010-01-01 12:00:00", tzinfo=pytz.FixedOffset(0)), + ], + ], + ], + ) + def test_to_datetime_parse_tzname_or_tzoffset(self, fmt, dates, expected_dates): + # GH 13486 + result = to_datetime(dates, format=fmt) + expected = Index(expected_dates) + tm.assert_equal(result, expected) + + @pytest.mark.parametrize( + "fmt,dates,expected_dates", + [ + [ + "%Y-%m-%d %H:%M:%S %Z", + [ + "2010-01-01 12:00:00 UTC", + "2010-01-01 12:00:00 GMT", + "2010-01-01 12:00:00 US/Pacific", + ], + [ + Timestamp("2010-01-01 12:00:00", tz="UTC"), + Timestamp("2010-01-01 12:00:00", tz="GMT"), + Timestamp("2010-01-01 12:00:00", tz="US/Pacific"), + ], + ], + [ + "%Y-%m-%d %H:%M:%S %z", + ["2010-01-01 12:00:00 +0100", "2010-01-01 12:00:00 -0100"], + [ + Timestamp( + "2010-01-01 12:00:00", tzinfo=timezone(timedelta(minutes=60)) + ), + Timestamp( + "2010-01-01 12:00:00", tzinfo=timezone(timedelta(minutes=-60)) + ), + ], + ], + ], + ) + def test_to_datetime_parse_tzname_or_tzoffset_utc_false_deprecated( + self, fmt, dates, expected_dates + ): + # GH 13486, 50887 + msg = "parsing datetimes with mixed time zones will raise an error" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_datetime(dates, format=fmt) + expected = Index(expected_dates) + tm.assert_equal(result, expected) + + def test_to_datetime_parse_tzname_or_tzoffset_different_tz_to_utc(self): + # GH 32792 + dates = [ + "2010-01-01 12:00:00 +0100", + "2010-01-01 12:00:00 -0100", + "2010-01-01 12:00:00 +0300", + "2010-01-01 12:00:00 +0400", + ] + expected_dates = [ + "2010-01-01 11:00:00+00:00", + "2010-01-01 13:00:00+00:00", + "2010-01-01 09:00:00+00:00", + "2010-01-01 08:00:00+00:00", + ] + fmt = "%Y-%m-%d %H:%M:%S %z" + + result = to_datetime(dates, format=fmt, utc=True) + expected = DatetimeIndex(expected_dates) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "offset", ["+0", "-1foo", "UTCbar", ":10", "+01:000:01", ""] + ) + def test_to_datetime_parse_timezone_malformed(self, offset): + fmt = "%Y-%m-%d %H:%M:%S %z" + date = "2010-01-01 12:00:00 " + offset + + msg = "|".join( + [ + r'^time data ".*" doesn\'t match format ".*", at position 0. ' + f"{PARSING_ERR_MSG}$", + r'^unconverted data remains when parsing with format ".*": ".*", ' + f"at position 0. {PARSING_ERR_MSG}$", + ] + ) + with pytest.raises(ValueError, match=msg): + to_datetime([date], format=fmt) + + def test_to_datetime_parse_timezone_keeps_name(self): + # GH 21697 + fmt = "%Y-%m-%d %H:%M:%S %z" + arg = Index(["2010-01-01 12:00:00 Z"], name="foo") + result = to_datetime(arg, format=fmt) + expected = DatetimeIndex(["2010-01-01 12:00:00"], tz="UTC", name="foo") + tm.assert_index_equal(result, expected) + + +class TestToDatetime: + @pytest.mark.filterwarnings("ignore:Could not infer format") + def test_to_datetime_overflow(self): + # we should get an OutOfBoundsDatetime, NOT OverflowError + # TODO: Timestamp raises ValueError("could not convert string to Timestamp") + # can we make these more consistent? + arg = "08335394550" + msg = 'Parsing "08335394550" to datetime overflows, at position 0' + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(arg) + + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime([arg]) + + res = to_datetime(arg, errors="coerce") + assert res is NaT + res = to_datetime([arg], errors="coerce") + tm.assert_index_equal(res, Index([NaT])) + + res = to_datetime(arg, errors="ignore") + assert isinstance(res, str) and res == arg + res = to_datetime([arg], errors="ignore") + tm.assert_index_equal(res, Index([arg], dtype=object)) + + def test_to_datetime_mixed_datetime_and_string(self): + # GH#47018 adapted old doctest with new behavior + d1 = datetime(2020, 1, 1, 17, tzinfo=timezone(-timedelta(hours=1))) + d2 = datetime(2020, 1, 1, 18, tzinfo=timezone(-timedelta(hours=1))) + res = to_datetime(["2020-01-01 17:00 -0100", d2]) + expected = to_datetime([d1, d2]).tz_convert(timezone(timedelta(minutes=-60))) + tm.assert_index_equal(res, expected) + + def test_to_datetime_mixed_string_and_numeric(self): + # GH#55780 np.array(vals) would incorrectly cast the number to str + vals = ["2016-01-01", 0] + expected = DatetimeIndex([Timestamp(x) for x in vals]) + result = to_datetime(vals, format="mixed") + result2 = to_datetime(vals[::-1], format="mixed")[::-1] + result3 = DatetimeIndex(vals) + result4 = DatetimeIndex(vals[::-1])[::-1] + + tm.assert_index_equal(result, expected) + tm.assert_index_equal(result2, expected) + tm.assert_index_equal(result3, expected) + tm.assert_index_equal(result4, expected) + + @pytest.mark.parametrize( + "format", ["%Y-%m-%d", "%Y-%d-%m"], ids=["ISO8601", "non-ISO8601"] + ) + def test_to_datetime_mixed_date_and_string(self, format): + # https://github.com/pandas-dev/pandas/issues/50108 + d1 = date(2020, 1, 2) + res = to_datetime(["2020-01-01", d1], format=format) + expected = DatetimeIndex(["2020-01-01", "2020-01-02"], dtype="M8[ns]") + tm.assert_index_equal(res, expected) + + @pytest.mark.parametrize( + "fmt", + ["%Y-%d-%m %H:%M:%S%z", "%Y-%m-%d %H:%M:%S%z"], + ids=["non-ISO8601 format", "ISO8601 format"], + ) + @pytest.mark.parametrize( + "utc, args, expected", + [ + pytest.param( + True, + ["2000-01-01 01:00:00-08:00", "2000-01-01 02:00:00-08:00"], + DatetimeIndex( + ["2000-01-01 09:00:00+00:00", "2000-01-01 10:00:00+00:00"], + dtype="datetime64[ns, UTC]", + ), + id="all tz-aware, with utc", + ), + pytest.param( + False, + ["2000-01-01 01:00:00+00:00", "2000-01-01 02:00:00+00:00"], + DatetimeIndex( + ["2000-01-01 01:00:00+00:00", "2000-01-01 02:00:00+00:00"], + ), + id="all tz-aware, without utc", + ), + pytest.param( + True, + ["2000-01-01 01:00:00-08:00", "2000-01-01 02:00:00+00:00"], + DatetimeIndex( + ["2000-01-01 09:00:00+00:00", "2000-01-01 02:00:00+00:00"], + dtype="datetime64[ns, UTC]", + ), + id="all tz-aware, mixed offsets, with utc", + ), + pytest.param( + True, + ["2000-01-01 01:00:00", "2000-01-01 02:00:00+00:00"], + DatetimeIndex( + ["2000-01-01 01:00:00+00:00", "2000-01-01 02:00:00+00:00"], + dtype="datetime64[ns, UTC]", + ), + id="tz-aware string, naive pydatetime, with utc", + ), + ], + ) + @pytest.mark.parametrize( + "constructor", + [Timestamp, lambda x: Timestamp(x).to_pydatetime()], + ) + def test_to_datetime_mixed_datetime_and_string_with_format( + self, fmt, utc, args, expected, constructor + ): + # https://github.com/pandas-dev/pandas/issues/49298 + # https://github.com/pandas-dev/pandas/issues/50254 + # note: ISO8601 formats go down a fastpath, so we need to check both + # a ISO8601 format and a non-ISO8601 one + ts1 = constructor(args[0]) + ts2 = args[1] + result = to_datetime([ts1, ts2], format=fmt, utc=utc) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "fmt", + ["%Y-%d-%m %H:%M:%S%z", "%Y-%m-%d %H:%M:%S%z"], + ids=["non-ISO8601 format", "ISO8601 format"], + ) + @pytest.mark.parametrize( + "constructor", + [Timestamp, lambda x: Timestamp(x).to_pydatetime()], + ) + def test_to_datetime_mixed_datetime_and_string_with_format_mixed_offsets_utc_false( + self, fmt, constructor + ): + # https://github.com/pandas-dev/pandas/issues/49298 + # https://github.com/pandas-dev/pandas/issues/50254 + # note: ISO8601 formats go down a fastpath, so we need to check both + # a ISO8601 format and a non-ISO8601 one + args = ["2000-01-01 01:00:00", "2000-01-01 02:00:00+00:00"] + ts1 = constructor(args[0]) + ts2 = args[1] + msg = "parsing datetimes with mixed time zones will raise an error" + + expected = Index( + [ + Timestamp("2000-01-01 01:00:00"), + Timestamp("2000-01-01 02:00:00+0000", tz="UTC"), + ], + ) + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_datetime([ts1, ts2], format=fmt, utc=False) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "fmt, expected", + [ + pytest.param( + "%Y-%m-%d %H:%M:%S%z", + Index( + [ + Timestamp("2000-01-01 09:00:00+0100", tz="UTC+01:00"), + Timestamp("2000-01-02 02:00:00+0200", tz="UTC+02:00"), + NaT, + ] + ), + id="ISO8601, non-UTC", + ), + pytest.param( + "%Y-%d-%m %H:%M:%S%z", + Index( + [ + Timestamp("2000-01-01 09:00:00+0100", tz="UTC+01:00"), + Timestamp("2000-02-01 02:00:00+0200", tz="UTC+02:00"), + NaT, + ] + ), + id="non-ISO8601, non-UTC", + ), + ], + ) + def test_to_datetime_mixed_offsets_with_none_tz(self, fmt, expected): + # https://github.com/pandas-dev/pandas/issues/50071 + msg = "parsing datetimes with mixed time zones will raise an error" + + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_datetime( + ["2000-01-01 09:00:00+01:00", "2000-01-02 02:00:00+02:00", None], + format=fmt, + utc=False, + ) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "fmt, expected", + [ + pytest.param( + "%Y-%m-%d %H:%M:%S%z", + DatetimeIndex( + ["2000-01-01 08:00:00+00:00", "2000-01-02 00:00:00+00:00", "NaT"], + dtype="datetime64[ns, UTC]", + ), + id="ISO8601, UTC", + ), + pytest.param( + "%Y-%d-%m %H:%M:%S%z", + DatetimeIndex( + ["2000-01-01 08:00:00+00:00", "2000-02-01 00:00:00+00:00", "NaT"], + dtype="datetime64[ns, UTC]", + ), + id="non-ISO8601, UTC", + ), + ], + ) + def test_to_datetime_mixed_offsets_with_none(self, fmt, expected): + # https://github.com/pandas-dev/pandas/issues/50071 + result = to_datetime( + ["2000-01-01 09:00:00+01:00", "2000-01-02 02:00:00+02:00", None], + format=fmt, + utc=True, + ) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "fmt", + ["%Y-%d-%m %H:%M:%S%z", "%Y-%m-%d %H:%M:%S%z"], + ids=["non-ISO8601 format", "ISO8601 format"], + ) + @pytest.mark.parametrize( + "args", + [ + pytest.param( + ["2000-01-01 01:00:00-08:00", "2000-01-01 02:00:00-07:00"], + id="all tz-aware, mixed timezones, without utc", + ), + ], + ) + @pytest.mark.parametrize( + "constructor", + [Timestamp, lambda x: Timestamp(x).to_pydatetime()], + ) + def test_to_datetime_mixed_datetime_and_string_with_format_raises( + self, fmt, args, constructor + ): + # https://github.com/pandas-dev/pandas/issues/49298 + # note: ISO8601 formats go down a fastpath, so we need to check both + # a ISO8601 format and a non-ISO8601 one + ts1 = constructor(args[0]) + ts2 = constructor(args[1]) + with pytest.raises( + ValueError, match="cannot be converted to datetime64 unless utc=True" + ): + to_datetime([ts1, ts2], format=fmt, utc=False) + + def test_to_datetime_np_str(self): + # GH#32264 + # GH#48969 + value = np.str_("2019-02-04 10:18:46.297000+0000") + + ser = Series([value]) + + exp = Timestamp("2019-02-04 10:18:46.297000", tz="UTC") + + assert to_datetime(value) == exp + assert to_datetime(ser.iloc[0]) == exp + + res = to_datetime([value]) + expected = Index([exp]) + tm.assert_index_equal(res, expected) + + res = to_datetime(ser) + expected = Series(expected) + tm.assert_series_equal(res, expected) + + @pytest.mark.parametrize( + "s, _format, dt", + [ + ["2015-1-1", "%G-%V-%u", datetime(2014, 12, 29, 0, 0)], + ["2015-1-4", "%G-%V-%u", datetime(2015, 1, 1, 0, 0)], + ["2015-1-7", "%G-%V-%u", datetime(2015, 1, 4, 0, 0)], + ], + ) + def test_to_datetime_iso_week_year_format(self, s, _format, dt): + # See GH#16607 + assert to_datetime(s, format=_format) == dt + + @pytest.mark.parametrize( + "msg, s, _format", + [ + [ + "ISO week directive '%V' is incompatible with the year directive " + "'%Y'. Use the ISO year '%G' instead.", + "1999 50", + "%Y %V", + ], + [ + "ISO year directive '%G' must be used with the ISO week directive " + "'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 51", + "%G %V", + ], + [ + "ISO year directive '%G' must be used with the ISO week directive " + "'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 Monday", + "%G %A", + ], + [ + "ISO year directive '%G' must be used with the ISO week directive " + "'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 Mon", + "%G %a", + ], + [ + "ISO year directive '%G' must be used with the ISO week directive " + "'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 6", + "%G %w", + ], + [ + "ISO year directive '%G' must be used with the ISO week directive " + "'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 6", + "%G %u", + ], + [ + "ISO year directive '%G' must be used with the ISO week directive " + "'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", + "2051", + "%G", + ], + [ + "Day of the year directive '%j' is not compatible with ISO year " + "directive '%G'. Use '%Y' instead.", + "1999 51 6 256", + "%G %V %u %j", + ], + [ + "ISO week directive '%V' is incompatible with the year directive " + "'%Y'. Use the ISO year '%G' instead.", + "1999 51 Sunday", + "%Y %V %A", + ], + [ + "ISO week directive '%V' is incompatible with the year directive " + "'%Y'. Use the ISO year '%G' instead.", + "1999 51 Sun", + "%Y %V %a", + ], + [ + "ISO week directive '%V' is incompatible with the year directive " + "'%Y'. Use the ISO year '%G' instead.", + "1999 51 1", + "%Y %V %w", + ], + [ + "ISO week directive '%V' is incompatible with the year directive " + "'%Y'. Use the ISO year '%G' instead.", + "1999 51 1", + "%Y %V %u", + ], + [ + "ISO week directive '%V' must be used with the ISO year directive " + "'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", + "20", + "%V", + ], + [ + "ISO week directive '%V' must be used with the ISO year directive " + "'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 51 Sunday", + "%V %A", + ], + [ + "ISO week directive '%V' must be used with the ISO year directive " + "'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 51 Sun", + "%V %a", + ], + [ + "ISO week directive '%V' must be used with the ISO year directive " + "'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 51 1", + "%V %w", + ], + [ + "ISO week directive '%V' must be used with the ISO year directive " + "'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", + "1999 51 1", + "%V %u", + ], + [ + "Day of the year directive '%j' is not compatible with ISO year " + "directive '%G'. Use '%Y' instead.", + "1999 50", + "%G %j", + ], + [ + "ISO week directive '%V' must be used with the ISO year directive " + "'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", + "20 Monday", + "%V %A", + ], + ], + ) + @pytest.mark.parametrize("errors", ["raise", "coerce", "ignore"]) + def test_error_iso_week_year(self, msg, s, _format, errors): + # See GH#16607, GH#50308 + # This test checks for errors thrown when giving the wrong format + # However, as discussed on PR#25541, overriding the locale + # causes a different error to be thrown due to the format being + # locale specific, but the test data is in english. + # Therefore, the tests only run when locale is not overwritten, + # as a sort of solution to this problem. + if locale.getlocale() != ("zh_CN", "UTF-8") and locale.getlocale() != ( + "it_IT", + "UTF-8", + ): + with pytest.raises(ValueError, match=msg): + to_datetime(s, format=_format, errors=errors) + + @pytest.mark.parametrize("tz", [None, "US/Central"]) + def test_to_datetime_dtarr(self, tz): + # DatetimeArray + dti = date_range("1965-04-03", periods=19, freq="2W", tz=tz) + arr = dti._data + + result = to_datetime(arr) + assert result is arr + + # Doesn't work on Windows since tzpath not set correctly + @td.skip_if_windows + @pytest.mark.parametrize("arg_class", [Series, Index]) + @pytest.mark.parametrize("utc", [True, False]) + @pytest.mark.parametrize("tz", [None, "US/Central"]) + def test_to_datetime_arrow(self, tz, utc, arg_class): + pa = pytest.importorskip("pyarrow") + + dti = date_range("1965-04-03", periods=19, freq="2W", tz=tz) + dti = arg_class(dti) + + dti_arrow = dti.astype(pd.ArrowDtype(pa.timestamp(unit="ns", tz=tz))) + + result = to_datetime(dti_arrow, utc=utc) + expected = to_datetime(dti, utc=utc).astype( + pd.ArrowDtype(pa.timestamp(unit="ns", tz=tz if not utc else "UTC")) + ) + if not utc and arg_class is not Series: + # Doesn't hold for utc=True, since that will astype + # to_datetime also returns a new object for series + assert result is dti_arrow + if arg_class is Series: + tm.assert_series_equal(result, expected) + else: + tm.assert_index_equal(result, expected) + + def test_to_datetime_pydatetime(self): + actual = to_datetime(datetime(2008, 1, 15)) + assert actual == datetime(2008, 1, 15) + + def test_to_datetime_YYYYMMDD(self): + actual = to_datetime("20080115") + assert actual == datetime(2008, 1, 15) + + def test_to_datetime_unparsable_ignore(self): + # unparsable + ser = "Month 1, 1999" + assert to_datetime(ser, errors="ignore") == ser + + @td.skip_if_windows # `tm.set_timezone` does not work in windows + def test_to_datetime_now(self): + # See GH#18666 + with tm.set_timezone("US/Eastern"): + # GH#18705 + now = Timestamp("now").as_unit("ns") + pdnow = to_datetime("now") + pdnow2 = to_datetime(["now"])[0] + + # These should all be equal with infinite perf; this gives + # a generous margin of 10 seconds + assert abs(pdnow._value - now._value) < 1e10 + assert abs(pdnow2._value - now._value) < 1e10 + + assert pdnow.tzinfo is None + assert pdnow2.tzinfo is None + + @td.skip_if_windows # `tm.set_timezone` does not work in windows + @pytest.mark.parametrize("tz", ["Pacific/Auckland", "US/Samoa"]) + def test_to_datetime_today(self, tz): + # See GH#18666 + # Test with one timezone far ahead of UTC and another far behind, so + # one of these will _almost_ always be in a different day from UTC. + # Unfortunately this test between 12 and 1 AM Samoa time + # this both of these timezones _and_ UTC will all be in the same day, + # so this test will not detect the regression introduced in #18666. + with tm.set_timezone(tz): + nptoday = np.datetime64("today").astype("datetime64[ns]").astype(np.int64) + pdtoday = to_datetime("today") + pdtoday2 = to_datetime(["today"])[0] + + tstoday = Timestamp("today").as_unit("ns") + tstoday2 = Timestamp.today().as_unit("ns") + + # These should all be equal with infinite perf; this gives + # a generous margin of 10 seconds + assert abs(pdtoday.normalize()._value - nptoday) < 1e10 + assert abs(pdtoday2.normalize()._value - nptoday) < 1e10 + assert abs(pdtoday._value - tstoday._value) < 1e10 + assert abs(pdtoday._value - tstoday2._value) < 1e10 + + assert pdtoday.tzinfo is None + assert pdtoday2.tzinfo is None + + @pytest.mark.parametrize("arg", ["now", "today"]) + def test_to_datetime_today_now_unicode_bytes(self, arg): + to_datetime([arg]) + + @pytest.mark.parametrize( + "format, expected_ds", + [ + ("%Y-%m-%d %H:%M:%S%z", "2020-01-03"), + ("%Y-%d-%m %H:%M:%S%z", "2020-03-01"), + (None, "2020-01-03"), + ], + ) + @pytest.mark.parametrize( + "string, attribute", + [ + ("now", "utcnow"), + ("today", "today"), + ], + ) + def test_to_datetime_now_with_format(self, format, expected_ds, string, attribute): + # https://github.com/pandas-dev/pandas/issues/50359 + result = to_datetime(["2020-01-03 00:00:00Z", string], format=format, utc=True) + expected = DatetimeIndex( + [expected_ds, getattr(Timestamp, attribute)()], dtype="datetime64[ns, UTC]" + ) + assert (expected - result).max().total_seconds() < 1 + + @pytest.mark.parametrize( + "dt", [np.datetime64("2000-01-01"), np.datetime64("2000-01-02")] + ) + def test_to_datetime_dt64s(self, cache, dt): + assert to_datetime(dt, cache=cache) == Timestamp(dt) + + @pytest.mark.parametrize( + "arg, format", + [ + ("2001-01-01", "%Y-%m-%d"), + ("01-01-2001", "%d-%m-%Y"), + ], + ) + def test_to_datetime_dt64s_and_str(self, arg, format): + # https://github.com/pandas-dev/pandas/issues/50036 + result = to_datetime([arg, np.datetime64("2020-01-01")], format=format) + expected = DatetimeIndex(["2001-01-01", "2020-01-01"]) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "dt", [np.datetime64("1000-01-01"), np.datetime64("5000-01-02")] + ) + @pytest.mark.parametrize("errors", ["raise", "ignore", "coerce"]) + def test_to_datetime_dt64s_out_of_ns_bounds(self, cache, dt, errors): + # GH#50369 We cast to the nearest supported reso, i.e. "s" + ts = to_datetime(dt, errors=errors, cache=cache) + assert isinstance(ts, Timestamp) + assert ts.unit == "s" + assert ts.asm8 == dt + + ts = Timestamp(dt) + assert ts.unit == "s" + assert ts.asm8 == dt + + @pytest.mark.skip_ubsan + def test_to_datetime_dt64d_out_of_bounds(self, cache): + dt64 = np.datetime64(np.iinfo(np.int64).max, "D") + + msg = "Out of bounds second timestamp: 25252734927768524-07-27" + with pytest.raises(OutOfBoundsDatetime, match=msg): + Timestamp(dt64) + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(dt64, errors="raise", cache=cache) + + assert to_datetime(dt64, errors="coerce", cache=cache) is NaT + + @pytest.mark.parametrize("unit", ["s", "D"]) + def test_to_datetime_array_of_dt64s(self, cache, unit): + # https://github.com/pandas-dev/pandas/issues/31491 + # Need at least 50 to ensure cache is used. + dts = [ + np.datetime64("2000-01-01", unit), + np.datetime64("2000-01-02", unit), + ] * 30 + # Assuming all datetimes are in bounds, to_datetime() returns + # an array that is equal to Timestamp() parsing + result = to_datetime(dts, cache=cache) + if cache: + # FIXME: behavior should not depend on cache + expected = DatetimeIndex([Timestamp(x).asm8 for x in dts], dtype="M8[s]") + else: + expected = DatetimeIndex([Timestamp(x).asm8 for x in dts], dtype="M8[ns]") + + tm.assert_index_equal(result, expected) + + # A list of datetimes where the last one is out of bounds + dts_with_oob = dts + [np.datetime64("9999-01-01")] + + # As of GH#51978 we do not raise in this case + to_datetime(dts_with_oob, errors="raise") + + result = to_datetime(dts_with_oob, errors="coerce", cache=cache) + if not cache: + # FIXME: shouldn't depend on cache! + expected = DatetimeIndex( + [Timestamp(dts_with_oob[0]).asm8, Timestamp(dts_with_oob[1]).asm8] * 30 + + [NaT], + ) + else: + expected = DatetimeIndex(np.array(dts_with_oob, dtype="M8[s]")) + tm.assert_index_equal(result, expected) + + # With errors='ignore', out of bounds datetime64s + # are converted to their .item(), which depending on the version of + # numpy is either a python datetime.datetime or datetime.date + result = to_datetime(dts_with_oob, errors="ignore", cache=cache) + if not cache: + # FIXME: shouldn't depend on cache! + expected = Index(dts_with_oob) + tm.assert_index_equal(result, expected) + + def test_out_of_bounds_errors_ignore(self): + # https://github.com/pandas-dev/pandas/issues/50587 + result = to_datetime(np.datetime64("9999-01-01"), errors="ignore") + expected = np.datetime64("9999-01-01") + assert result == expected + + def test_out_of_bounds_errors_ignore2(self): + # GH#12424 + msg = "errors='ignore' is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + res = to_datetime(Series(["2362-01-01", np.nan]), errors="ignore") + exp = Series(["2362-01-01", np.nan]) + tm.assert_series_equal(res, exp) + + def test_to_datetime_tz(self, cache): + # xref 8260 + # uniform returns a DatetimeIndex + arr = [ + Timestamp("2013-01-01 13:00:00-0800", tz="US/Pacific"), + Timestamp("2013-01-02 14:00:00-0800", tz="US/Pacific"), + ] + result = to_datetime(arr, cache=cache) + expected = DatetimeIndex( + ["2013-01-01 13:00:00", "2013-01-02 14:00:00"], tz="US/Pacific" + ) + tm.assert_index_equal(result, expected) + + def test_to_datetime_tz_mixed(self, cache): + # mixed tzs will raise if errors='raise' + # https://github.com/pandas-dev/pandas/issues/50585 + arr = [ + Timestamp("2013-01-01 13:00:00", tz="US/Pacific"), + Timestamp("2013-01-02 14:00:00", tz="US/Eastern"), + ] + msg = ( + "Tz-aware datetime.datetime cannot be " + "converted to datetime64 unless utc=True" + ) + with pytest.raises(ValueError, match=msg): + to_datetime(arr, cache=cache) + + depr_msg = "errors='ignore' is deprecated" + with tm.assert_produces_warning(FutureWarning, match=depr_msg): + result = to_datetime(arr, cache=cache, errors="ignore") + expected = Index( + [ + Timestamp("2013-01-01 13:00:00-08:00"), + Timestamp("2013-01-02 14:00:00-05:00"), + ], + dtype="object", + ) + tm.assert_index_equal(result, expected) + result = to_datetime(arr, cache=cache, errors="coerce") + expected = DatetimeIndex( + ["2013-01-01 13:00:00-08:00", "NaT"], dtype="datetime64[ns, US/Pacific]" + ) + tm.assert_index_equal(result, expected) + + def test_to_datetime_different_offsets(self, cache): + # inspired by asv timeseries.ToDatetimeNONISO8601 benchmark + # see GH-26097 for more + ts_string_1 = "March 1, 2018 12:00:00+0400" + ts_string_2 = "March 1, 2018 12:00:00+0500" + arr = [ts_string_1] * 5 + [ts_string_2] * 5 + expected = Index([parse(x) for x in arr]) + msg = "parsing datetimes with mixed time zones will raise an error" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_datetime(arr, cache=cache) + tm.assert_index_equal(result, expected) + + def test_to_datetime_tz_pytz(self, cache): + # see gh-8260 + us_eastern = pytz.timezone("US/Eastern") + arr = np.array( + [ + us_eastern.localize( + datetime(year=2000, month=1, day=1, hour=3, minute=0) + ), + us_eastern.localize( + datetime(year=2000, month=6, day=1, hour=3, minute=0) + ), + ], + dtype=object, + ) + result = to_datetime(arr, utc=True, cache=cache) + expected = DatetimeIndex( + ["2000-01-01 08:00:00+00:00", "2000-06-01 07:00:00+00:00"], + dtype="datetime64[ns, UTC]", + freq=None, + ) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "init_constructor, end_constructor", + [ + (Index, DatetimeIndex), + (list, DatetimeIndex), + (np.array, DatetimeIndex), + (Series, Series), + ], + ) + def test_to_datetime_utc_true(self, cache, init_constructor, end_constructor): + # See gh-11934 & gh-6415 + data = ["20100102 121314", "20100102 121315"] + expected_data = [ + Timestamp("2010-01-02 12:13:14", tz="utc"), + Timestamp("2010-01-02 12:13:15", tz="utc"), + ] + + result = to_datetime( + init_constructor(data), format="%Y%m%d %H%M%S", utc=True, cache=cache + ) + expected = end_constructor(expected_data) + tm.assert_equal(result, expected) + + @pytest.mark.parametrize( + "scalar, expected", + [ + ["20100102 121314", Timestamp("2010-01-02 12:13:14", tz="utc")], + ["20100102 121315", Timestamp("2010-01-02 12:13:15", tz="utc")], + ], + ) + def test_to_datetime_utc_true_scalar(self, cache, scalar, expected): + # Test scalar case as well + result = to_datetime(scalar, format="%Y%m%d %H%M%S", utc=True, cache=cache) + assert result == expected + + def test_to_datetime_utc_true_with_series_single_value(self, cache): + # GH 15760 UTC=True with Series + ts = 1.5e18 + result = to_datetime(Series([ts]), utc=True, cache=cache) + expected = Series([Timestamp(ts, tz="utc")]) + tm.assert_series_equal(result, expected) + + def test_to_datetime_utc_true_with_series_tzaware_string(self, cache): + ts = "2013-01-01 00:00:00-01:00" + expected_ts = "2013-01-01 01:00:00" + data = Series([ts] * 3) + result = to_datetime(data, utc=True, cache=cache) + expected = Series([Timestamp(expected_ts, tz="utc")] * 3) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "date, dtype", + [ + ("2013-01-01 01:00:00", "datetime64[ns]"), + ("2013-01-01 01:00:00", "datetime64[ns, UTC]"), + ], + ) + def test_to_datetime_utc_true_with_series_datetime_ns(self, cache, date, dtype): + expected = Series( + [Timestamp("2013-01-01 01:00:00", tz="UTC")], dtype="M8[ns, UTC]" + ) + result = to_datetime(Series([date], dtype=dtype), utc=True, cache=cache) + tm.assert_series_equal(result, expected) + + def test_to_datetime_tz_psycopg2(self, request, cache): + # xref 8260 + psycopg2_tz = pytest.importorskip("psycopg2.tz") + + # misc cases + tz1 = psycopg2_tz.FixedOffsetTimezone(offset=-300, name=None) + tz2 = psycopg2_tz.FixedOffsetTimezone(offset=-240, name=None) + arr = np.array( + [ + datetime(2000, 1, 1, 3, 0, tzinfo=tz1), + datetime(2000, 6, 1, 3, 0, tzinfo=tz2), + ], + dtype=object, + ) + + result = to_datetime(arr, errors="coerce", utc=True, cache=cache) + expected = DatetimeIndex( + ["2000-01-01 08:00:00+00:00", "2000-06-01 07:00:00+00:00"], + dtype="datetime64[ns, UTC]", + freq=None, + ) + tm.assert_index_equal(result, expected) + + # dtype coercion + i = DatetimeIndex( + ["2000-01-01 08:00:00"], + tz=psycopg2_tz.FixedOffsetTimezone(offset=-300, name=None), + ) + assert is_datetime64_ns_dtype(i) + + # tz coercion + result = to_datetime(i, errors="coerce", cache=cache) + tm.assert_index_equal(result, i) + + result = to_datetime(i, errors="coerce", utc=True, cache=cache) + expected = DatetimeIndex(["2000-01-01 13:00:00"], dtype="datetime64[ns, UTC]") + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize("arg", [True, False]) + def test_datetime_bool(self, cache, arg): + # GH13176 + msg = r"dtype bool cannot be converted to datetime64\[ns\]" + with pytest.raises(TypeError, match=msg): + to_datetime(arg) + assert to_datetime(arg, errors="coerce", cache=cache) is NaT + assert to_datetime(arg, errors="ignore", cache=cache) is arg + + def test_datetime_bool_arrays_mixed(self, cache): + msg = f"{type(cache)} is not convertible to datetime" + with pytest.raises(TypeError, match=msg): + to_datetime([False, datetime.today()], cache=cache) + with pytest.raises( + ValueError, + match=( + r'^time data "True" doesn\'t match format "%Y%m%d", ' + f"at position 1. {PARSING_ERR_MSG}$" + ), + ): + to_datetime(["20130101", True], cache=cache) + tm.assert_index_equal( + to_datetime([0, False, NaT, 0.0], errors="coerce", cache=cache), + DatetimeIndex( + [to_datetime(0, cache=cache), NaT, NaT, to_datetime(0, cache=cache)] + ), + ) + + @pytest.mark.parametrize("arg", [bool, to_datetime]) + def test_datetime_invalid_datatype(self, arg): + # GH13176 + msg = "is not convertible to datetime" + with pytest.raises(TypeError, match=msg): + to_datetime(arg) + + @pytest.mark.parametrize("errors", ["coerce", "raise", "ignore"]) + def test_invalid_format_raises(self, errors): + # https://github.com/pandas-dev/pandas/issues/50255 + with pytest.raises( + ValueError, match="':' is a bad directive in format 'H%:M%:S%" + ): + to_datetime(["00:00:00"], format="H%:M%:S%", errors=errors) + + @pytest.mark.parametrize("value", ["a", "00:01:99"]) + @pytest.mark.parametrize("format", [None, "%H:%M:%S"]) + def test_datetime_invalid_scalar(self, value, format): + # GH24763 + res = to_datetime(value, errors="ignore", format=format) + assert res == value + + res = to_datetime(value, errors="coerce", format=format) + assert res is NaT + + msg = "|".join( + [ + r'^time data "a" doesn\'t match format "%H:%M:%S", at position 0. ' + f"{PARSING_ERR_MSG}$", + r'^Given date string "a" not likely a datetime, at position 0$', + r'^unconverted data remains when parsing with format "%H:%M:%S": "9", ' + f"at position 0. {PARSING_ERR_MSG}$", + rf"^second must be in 0..59{NOT_99}: 00:01:99, at position 0$", + ] + ) + with pytest.raises(ValueError, match=msg): + to_datetime(value, errors="raise", format=format) + + @pytest.mark.parametrize("value", ["3000/12/11 00:00:00"]) + @pytest.mark.parametrize("format", [None, "%H:%M:%S"]) + def test_datetime_outofbounds_scalar(self, value, format): + # GH24763 + res = to_datetime(value, errors="ignore", format=format) + assert res == value + + res = to_datetime(value, errors="coerce", format=format) + assert res is NaT + + if format is not None: + msg = r'^time data ".*" doesn\'t match format ".*", at position 0.' + with pytest.raises(ValueError, match=msg): + to_datetime(value, errors="raise", format=format) + else: + msg = "^Out of bounds .*, at position 0$" + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(value, errors="raise", format=format) + + @pytest.mark.parametrize( + ("values"), [(["a"]), (["00:01:99"]), (["a", "b", "99:00:00"])] + ) + @pytest.mark.parametrize("format", [(None), ("%H:%M:%S")]) + def test_datetime_invalid_index(self, values, format): + # GH24763 + # Not great to have logic in tests, but this one's hard to + # parametrise over + if format is None and len(values) > 1: + warn = UserWarning + else: + warn = None + with tm.assert_produces_warning( + warn, match="Could not infer format", raise_on_extra_warnings=False + ): + res = to_datetime(values, errors="ignore", format=format) + tm.assert_index_equal( + res, Index(values, dtype="object" if format is None else "str") + ) + + with tm.assert_produces_warning( + warn, match="Could not infer format", raise_on_extra_warnings=False + ): + res = to_datetime(values, errors="coerce", format=format) + tm.assert_index_equal(res, DatetimeIndex([NaT] * len(values))) + + msg = "|".join( + [ + r'^Given date string "a" not likely a datetime, at position 0$', + r'^time data "a" doesn\'t match format "%H:%M:%S", at position 0. ' + f"{PARSING_ERR_MSG}$", + r'^unconverted data remains when parsing with format "%H:%M:%S": "9", ' + f"at position 0. {PARSING_ERR_MSG}$", + rf"^second must be in 0..59{NOT_99}: 00:01:99, at position 0$", + ] + ) + with pytest.raises(ValueError, match=msg): + with tm.assert_produces_warning( + warn, match="Could not infer format", raise_on_extra_warnings=False + ): + to_datetime(values, errors="raise", format=format) + + @pytest.mark.parametrize("utc", [True, None]) + @pytest.mark.parametrize("format", ["%Y%m%d %H:%M:%S", None]) + @pytest.mark.parametrize("constructor", [list, tuple, np.array, Index, deque]) + def test_to_datetime_cache(self, utc, format, constructor): + date = "20130101 00:00:00" + test_dates = [date] * 10**5 + data = constructor(test_dates) + + result = to_datetime(data, utc=utc, format=format, cache=True) + expected = to_datetime(data, utc=utc, format=format, cache=False) + + tm.assert_index_equal(result, expected) + + def test_to_datetime_from_deque(self): + # GH 29403 + result = to_datetime(deque([Timestamp("2010-06-02 09:30:00")] * 51)) + expected = to_datetime([Timestamp("2010-06-02 09:30:00")] * 51) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize("utc", [True, None]) + @pytest.mark.parametrize("format", ["%Y%m%d %H:%M:%S", None]) + def test_to_datetime_cache_series(self, utc, format): + date = "20130101 00:00:00" + test_dates = [date] * 10**5 + data = Series(test_dates) + result = to_datetime(data, utc=utc, format=format, cache=True) + expected = to_datetime(data, utc=utc, format=format, cache=False) + tm.assert_series_equal(result, expected) + + def test_to_datetime_cache_scalar(self): + date = "20130101 00:00:00" + result = to_datetime(date, cache=True) + expected = Timestamp("20130101 00:00:00") + assert result == expected + + @pytest.mark.parametrize( + "datetimelikes,expected_values", + ( + ( + (None, np.nan) + (NaT,) * start_caching_at, + (NaT,) * (start_caching_at + 2), + ), + ( + (None, Timestamp("2012-07-26")) + (NaT,) * start_caching_at, + (NaT, Timestamp("2012-07-26")) + (NaT,) * start_caching_at, + ), + ( + (None,) + + (NaT,) * start_caching_at + + ("2012 July 26", Timestamp("2012-07-26")), + (NaT,) * (start_caching_at + 1) + + (Timestamp("2012-07-26"), Timestamp("2012-07-26")), + ), + ), + ) + def test_convert_object_to_datetime_with_cache( + self, datetimelikes, expected_values + ): + # GH#39882 + ser = Series( + datetimelikes, + dtype="object", + ) + result_series = to_datetime(ser, errors="coerce") + expected_series = Series( + expected_values, + dtype="datetime64[ns]", + ) + tm.assert_series_equal(result_series, expected_series) + + @pytest.mark.parametrize("cache", [True, False]) + @pytest.mark.parametrize( + "input", + [ + Series([NaT] * 20 + [None] * 20, dtype="object"), + Series([NaT] * 60 + [None] * 60, dtype="object"), + Series([None] * 20), + Series([None] * 60), + Series([""] * 20), + Series([""] * 60), + Series([pd.NA] * 20), + Series([pd.NA] * 60), + Series([np.nan] * 20), + Series([np.nan] * 60), + ], + ) + def test_to_datetime_converts_null_like_to_nat(self, cache, input): + # GH35888 + expected = Series([NaT] * len(input), dtype="M8[ns]") + result = to_datetime(input, cache=cache) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "date, format", + [ + ("2017-20", "%Y-%W"), + ("20 Sunday", "%W %A"), + ("20 Sun", "%W %a"), + ("2017-21", "%Y-%U"), + ("20 Sunday", "%U %A"), + ("20 Sun", "%U %a"), + ], + ) + def test_week_without_day_and_calendar_year(self, date, format): + # GH16774 + + msg = "Cannot use '%W' or '%U' without day and year" + with pytest.raises(ValueError, match=msg): + to_datetime(date, format=format) + + def test_to_datetime_coerce(self): + # GH 26122 + ts_strings = [ + "March 1, 2018 12:00:00+0400", + "March 1, 2018 12:00:00+0500", + "20100240", + ] + msg = "parsing datetimes with mixed time zones will raise an error" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_datetime(ts_strings, errors="coerce") + expected = Index( + [ + datetime(2018, 3, 1, 12, 0, tzinfo=tzoffset(None, 14400)), + datetime(2018, 3, 1, 12, 0, tzinfo=tzoffset(None, 18000)), + NaT, + ] + ) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "string_arg, format", + [("March 1, 2018", "%B %d, %Y"), ("2018-03-01", "%Y-%m-%d")], + ) + @pytest.mark.parametrize( + "outofbounds", + [ + datetime(9999, 1, 1), + date(9999, 1, 1), + np.datetime64("9999-01-01"), + "January 1, 9999", + "9999-01-01", + ], + ) + def test_to_datetime_coerce_oob(self, string_arg, format, outofbounds): + # https://github.com/pandas-dev/pandas/issues/50255 + ts_strings = [string_arg, outofbounds] + result = to_datetime(ts_strings, errors="coerce", format=format) + expected = DatetimeIndex([datetime(2018, 3, 1), NaT]) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "errors, expected", + [ + ("coerce", Index([NaT, NaT])), + ("ignore", Index(["200622-12-31", "111111-24-11"], dtype=object)), + ], + ) + def test_to_datetime_malformed_no_raise(self, errors, expected): + # GH 28299 + # GH 48633 + ts_strings = ["200622-12-31", "111111-24-11"] + with tm.assert_produces_warning( + UserWarning, match="Could not infer format", raise_on_extra_warnings=False + ): + result = to_datetime(ts_strings, errors=errors) + tm.assert_index_equal(result, expected) + + def test_to_datetime_malformed_raise(self): + # GH 48633 + ts_strings = ["200622-12-31", "111111-24-11"] + msg = ( + 'Parsed string "200622-12-31" gives an invalid tzoffset, which must ' + r"be between -timedelta\(hours=24\) and timedelta\(hours=24\), " + "at position 0" + ) + with pytest.raises( + ValueError, + match=msg, + ): + with tm.assert_produces_warning( + UserWarning, match="Could not infer format" + ): + to_datetime( + ts_strings, + errors="raise", + ) + + def test_iso_8601_strings_with_same_offset(self): + # GH 17697, 11736 + ts_str = "2015-11-18 15:30:00+05:30" + result = to_datetime(ts_str) + expected = Timestamp(ts_str) + assert result == expected + + expected = DatetimeIndex([Timestamp(ts_str)] * 2) + result = to_datetime([ts_str] * 2) + tm.assert_index_equal(result, expected) + + result = DatetimeIndex([ts_str] * 2) + tm.assert_index_equal(result, expected) + + def test_iso_8601_strings_with_different_offsets(self): + # GH 17697, 11736, 50887 + ts_strings = ["2015-11-18 15:30:00+05:30", "2015-11-18 16:30:00+06:30", NaT] + msg = "parsing datetimes with mixed time zones will raise an error" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_datetime(ts_strings) + expected = np.array( + [ + datetime(2015, 11, 18, 15, 30, tzinfo=tzoffset(None, 19800)), + datetime(2015, 11, 18, 16, 30, tzinfo=tzoffset(None, 23400)), + NaT, + ], + dtype=object, + ) + # GH 21864 + expected = Index(expected) + tm.assert_index_equal(result, expected) + + def test_iso_8601_strings_with_different_offsets_utc(self): + ts_strings = ["2015-11-18 15:30:00+05:30", "2015-11-18 16:30:00+06:30", NaT] + result = to_datetime(ts_strings, utc=True) + expected = DatetimeIndex( + [Timestamp(2015, 11, 18, 10), Timestamp(2015, 11, 18, 10), NaT], tz="UTC" + ) + tm.assert_index_equal(result, expected) + + def test_mixed_offsets_with_native_datetime_raises(self): + # GH 25978 + + vals = [ + "nan", + Timestamp("1990-01-01"), + "2015-03-14T16:15:14.123-08:00", + "2019-03-04T21:56:32.620-07:00", + None, + "today", + "now", + ] + ser = Series(vals) + assert all(ser[i] is vals[i] for i in range(len(vals))) # GH#40111 + + now = Timestamp("now") + today = Timestamp("today") + msg = "parsing datetimes with mixed time zones will raise an error" + with tm.assert_produces_warning(FutureWarning, match=msg): + mixed = to_datetime(ser) + expected = Series( + [ + "NaT", + Timestamp("1990-01-01"), + Timestamp("2015-03-14T16:15:14.123-08:00").to_pydatetime(), + Timestamp("2019-03-04T21:56:32.620-07:00").to_pydatetime(), + None, + ], + dtype=object, + ) + tm.assert_series_equal(mixed[:-2], expected) + # we'll check mixed[-1] and mixed[-2] match now and today to within + # call-timing tolerances + assert (now - mixed.iloc[-1]).total_seconds() <= 0.1 + assert (today - mixed.iloc[-2]).total_seconds() <= 0.1 + + with pytest.raises(ValueError, match="Tz-aware datetime.datetime"): + to_datetime(mixed) + + def test_non_iso_strings_with_tz_offset(self): + result = to_datetime(["March 1, 2018 12:00:00+0400"] * 2) + expected = DatetimeIndex( + [datetime(2018, 3, 1, 12, tzinfo=timezone(timedelta(minutes=240)))] * 2 + ) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "ts, expected", + [ + (Timestamp("2018-01-01"), Timestamp("2018-01-01", tz="UTC")), + ( + Timestamp("2018-01-01", tz="US/Pacific"), + Timestamp("2018-01-01 08:00", tz="UTC"), + ), + ], + ) + def test_timestamp_utc_true(self, ts, expected): + # GH 24415 + result = to_datetime(ts, utc=True) + assert result == expected + + @pytest.mark.parametrize("dt_str", ["00010101", "13000101", "30000101", "99990101"]) + def test_to_datetime_with_format_out_of_bounds(self, dt_str): + # GH 9107 + msg = "Out of bounds nanosecond timestamp" + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(dt_str, format="%Y%m%d") + + def test_to_datetime_utc(self): + arr = np.array([parse("2012-06-13T01:39:00Z")], dtype=object) + + result = to_datetime(arr, utc=True) + assert result.tz is timezone.utc + + def test_to_datetime_fixed_offset(self): + from pandas.tests.indexes.datetimes.test_timezones import FixedOffset + + fixed_off = FixedOffset(-420, "-07:00") + + dates = [ + datetime(2000, 1, 1, tzinfo=fixed_off), + datetime(2000, 1, 2, tzinfo=fixed_off), + datetime(2000, 1, 3, tzinfo=fixed_off), + ] + result = to_datetime(dates) + assert result.tz == fixed_off + + @pytest.mark.parametrize( + "date", + [ + ["2020-10-26 00:00:00+06:00", "2020-10-26 00:00:00+01:00"], + ["2020-10-26 00:00:00+06:00", Timestamp("2018-01-01", tz="US/Pacific")], + [ + "2020-10-26 00:00:00+06:00", + datetime(2020, 1, 1, 18, tzinfo=pytz.timezone("Australia/Melbourne")), + ], + ], + ) + def test_to_datetime_mixed_offsets_with_utc_false_deprecated(self, date): + # GH 50887 + msg = "parsing datetimes with mixed time zones will raise an error" + with tm.assert_produces_warning(FutureWarning, match=msg): + to_datetime(date, utc=False) + + +class TestToDatetimeUnit: + @pytest.mark.parametrize("unit", ["Y", "M"]) + @pytest.mark.parametrize("item", [150, float(150)]) + def test_to_datetime_month_or_year_unit_int(self, cache, unit, item, request): + # GH#50870 Note we have separate tests that pd.Timestamp gets these right + ts = Timestamp(item, unit=unit) + expected = DatetimeIndex([ts], dtype="M8[ns]") + + result = to_datetime([item], unit=unit, cache=cache) + tm.assert_index_equal(result, expected) + + result = to_datetime(np.array([item], dtype=object), unit=unit, cache=cache) + tm.assert_index_equal(result, expected) + + result = to_datetime(np.array([item]), unit=unit, cache=cache) + tm.assert_index_equal(result, expected) + + # with a nan! + result = to_datetime(np.array([item, np.nan]), unit=unit, cache=cache) + assert result.isna()[1] + tm.assert_index_equal(result[:1], expected) + + @pytest.mark.parametrize("unit", ["Y", "M"]) + def test_to_datetime_month_or_year_unit_non_round_float(self, cache, unit): + # GH#50301 + # Match Timestamp behavior in disallowing non-round floats with + # Y or M unit + warn_msg = "strings will be parsed as datetime strings" + msg = f"Conversion of non-round float with unit={unit} is ambiguous" + with pytest.raises(ValueError, match=msg): + to_datetime([1.5], unit=unit, errors="raise") + with pytest.raises(ValueError, match=msg): + to_datetime(np.array([1.5]), unit=unit, errors="raise") + with pytest.raises(ValueError, match=msg): + with tm.assert_produces_warning(FutureWarning, match=warn_msg): + to_datetime(["1.5"], unit=unit, errors="raise") + + # with errors="ignore" we also end up raising within the Timestamp + # constructor; this may not be ideal + with pytest.raises(ValueError, match=msg): + to_datetime([1.5], unit=unit, errors="ignore") + + res = to_datetime([1.5], unit=unit, errors="coerce") + expected = Index([NaT], dtype="M8[ns]") + tm.assert_index_equal(res, expected) + + with tm.assert_produces_warning(FutureWarning, match=warn_msg): + res = to_datetime(["1.5"], unit=unit, errors="coerce") + tm.assert_index_equal(res, expected) + + # round floats are OK + res = to_datetime([1.0], unit=unit) + expected = to_datetime([1], unit=unit) + tm.assert_index_equal(res, expected) + + def test_unit(self, cache): + # GH 11758 + # test proper behavior with errors + msg = "cannot specify both format and unit" + with pytest.raises(ValueError, match=msg): + to_datetime([1], unit="D", format="%Y%m%d", cache=cache) + + def test_unit_str(self, cache): + # GH 57051 + # Test that strs aren't dropping precision to 32-bit accidentally. + with tm.assert_produces_warning(FutureWarning): + res = to_datetime(["1704660000"], unit="s", origin="unix") + expected = to_datetime([1704660000], unit="s", origin="unix") + tm.assert_index_equal(res, expected) + + def test_unit_array_mixed_nans(self, cache): + values = [11111111111111111, 1, 1.0, iNaT, NaT, np.nan, "NaT", ""] + result = to_datetime(values, unit="D", errors="ignore", cache=cache) + expected = Index( + [ + 11111111111111111, + Timestamp("1970-01-02"), + Timestamp("1970-01-02"), + NaT, + NaT, + NaT, + NaT, + NaT, + ], + dtype=object, + ) + tm.assert_index_equal(result, expected) + + result = to_datetime(values, unit="D", errors="coerce", cache=cache) + expected = DatetimeIndex( + ["NaT", "1970-01-02", "1970-01-02", "NaT", "NaT", "NaT", "NaT", "NaT"], + dtype="M8[ns]", + ) + tm.assert_index_equal(result, expected) + + msg = "cannot convert input 11111111111111111 with the unit 'D'" + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(values, unit="D", errors="raise", cache=cache) + + def test_unit_array_mixed_nans_large_int(self, cache): + values = [1420043460000000000000000, iNaT, NaT, np.nan, "NaT"] + + result = to_datetime(values, errors="ignore", unit="s", cache=cache) + expected = Index([1420043460000000000000000, NaT, NaT, NaT, NaT], dtype=object) + tm.assert_index_equal(result, expected) + + result = to_datetime(values, errors="coerce", unit="s", cache=cache) + expected = DatetimeIndex(["NaT", "NaT", "NaT", "NaT", "NaT"], dtype="M8[ns]") + tm.assert_index_equal(result, expected) + + msg = "cannot convert input 1420043460000000000000000 with the unit 's'" + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(values, errors="raise", unit="s", cache=cache) + + def test_to_datetime_invalid_str_not_out_of_bounds_valuerror(self, cache): + # if we have a string, then we raise a ValueError + # and NOT an OutOfBoundsDatetime + msg = "non convertible value foo with the unit 's'" + with pytest.raises(ValueError, match=msg): + to_datetime("foo", errors="raise", unit="s", cache=cache) + + @pytest.mark.parametrize("error", ["raise", "coerce", "ignore"]) + def test_unit_consistency(self, cache, error): + # consistency of conversions + expected = Timestamp("1970-05-09 14:25:11") + result = to_datetime(11111111, unit="s", errors=error, cache=cache) + assert result == expected + assert isinstance(result, Timestamp) + + @pytest.mark.parametrize("errors", ["ignore", "raise", "coerce"]) + @pytest.mark.parametrize("dtype", ["float64", "int64"]) + def test_unit_with_numeric(self, cache, errors, dtype): + # GH 13180 + # coercions from floats/ints are ok + expected = DatetimeIndex( + ["2015-06-19 05:33:20", "2015-05-27 22:33:20"], dtype="M8[ns]" + ) + arr = np.array([1.434692e18, 1.432766e18]).astype(dtype) + result = to_datetime(arr, errors=errors, cache=cache) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "exp, arr, warning", + [ + [ + ["NaT", "2015-06-19 05:33:20", "2015-05-27 22:33:20"], + ["foo", 1.434692e18, 1.432766e18], + UserWarning, + ], + [ + ["2015-06-19 05:33:20", "2015-05-27 22:33:20", "NaT", "NaT"], + [1.434692e18, 1.432766e18, "foo", "NaT"], + None, + ], + ], + ) + def test_unit_with_numeric_coerce(self, cache, exp, arr, warning): + # but we want to make sure that we are coercing + # if we have ints/strings + expected = DatetimeIndex(exp, dtype="M8[ns]") + with tm.assert_produces_warning(warning, match="Could not infer format"): + result = to_datetime(arr, errors="coerce", cache=cache) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "arr", + [ + [Timestamp("20130101"), 1.434692e18, 1.432766e18], + [1.434692e18, 1.432766e18, Timestamp("20130101")], + ], + ) + def test_unit_mixed(self, cache, arr): + # GH#50453 pre-2.0 with mixed numeric/datetimes and errors="coerce" + # the numeric entries would be coerced to NaT, was never clear exactly + # why. + # mixed integers/datetimes + expected = Index([Timestamp(x) for x in arr], dtype="M8[ns]") + result = to_datetime(arr, errors="coerce", cache=cache) + tm.assert_index_equal(result, expected) + + # GH#49037 pre-2.0 this raised, but it always worked with Series, + # was never clear why it was disallowed + result = to_datetime(arr, errors="raise", cache=cache) + tm.assert_index_equal(result, expected) + + result = DatetimeIndex(arr) + tm.assert_index_equal(result, expected) + + def test_unit_rounding(self, cache): + # GH 14156 & GH 20445: argument will incur floating point errors + # but no premature rounding + value = 1434743731.8770001 + result = to_datetime(value, unit="s", cache=cache) + expected = Timestamp("2015-06-19 19:55:31.877000093") + assert result == expected + + alt = Timestamp(value, unit="s") + assert alt == result + + def test_unit_ignore_keeps_name(self, cache): + # GH 21697 + expected = Index([15e9] * 2, name="name") + result = to_datetime(expected, errors="ignore", unit="s", cache=cache) + tm.assert_index_equal(result, expected) + + def test_to_datetime_errors_ignore_utc_true(self): + # GH#23758 + result = to_datetime([1], unit="s", utc=True, errors="ignore") + expected = DatetimeIndex(["1970-01-01 00:00:01"], dtype="M8[ns, UTC]") + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize("dtype", [int, float]) + def test_to_datetime_unit(self, dtype): + epoch = 1370745748 + ser = Series([epoch + t for t in range(20)]).astype(dtype) + result = to_datetime(ser, unit="s") + expected = Series( + [ + Timestamp("2013-06-09 02:42:28") + timedelta(seconds=t) + for t in range(20) + ], + dtype="M8[ns]", + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("null", [iNaT, np.nan]) + def test_to_datetime_unit_with_nulls(self, null): + epoch = 1370745748 + ser = Series([epoch + t for t in range(20)] + [null]) + result = to_datetime(ser, unit="s") + expected = Series( + [Timestamp("2013-06-09 02:42:28") + timedelta(seconds=t) for t in range(20)] + + [NaT], + dtype="M8[ns]", + ) + tm.assert_series_equal(result, expected) + + def test_to_datetime_unit_fractional_seconds(self): + # GH13834 + epoch = 1370745748 + ser = Series([epoch + t for t in np.arange(0, 2, 0.25)] + [iNaT]).astype(float) + result = to_datetime(ser, unit="s") + expected = Series( + [ + Timestamp("2013-06-09 02:42:28") + timedelta(seconds=t) + for t in np.arange(0, 2, 0.25) + ] + + [NaT], + dtype="M8[ns]", + ) + # GH20455 argument will incur floating point errors but no premature rounding + result = result.round("ms") + tm.assert_series_equal(result, expected) + + def test_to_datetime_unit_na_values(self): + result = to_datetime([1, 2, "NaT", NaT, np.nan], unit="D") + expected = DatetimeIndex( + [Timestamp("1970-01-02"), Timestamp("1970-01-03")] + ["NaT"] * 3, + dtype="M8[ns]", + ) + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize("bad_val", ["foo", 111111111]) + def test_to_datetime_unit_invalid(self, bad_val): + msg = f"{bad_val} with the unit 'D'" + with pytest.raises(ValueError, match=msg): + to_datetime([1, 2, bad_val], unit="D") + + @pytest.mark.parametrize("bad_val", ["foo", 111111111]) + def test_to_timestamp_unit_coerce(self, bad_val): + # coerce we can process + expected = DatetimeIndex( + [Timestamp("1970-01-02"), Timestamp("1970-01-03")] + ["NaT"] * 1, + dtype="M8[ns]", + ) + result = to_datetime([1, 2, bad_val], unit="D", errors="coerce") + tm.assert_index_equal(result, expected) + + def test_float_to_datetime_raise_near_bounds(self): + # GH50183 + msg = "cannot convert input with unit 'D'" + oneday_in_ns = 1e9 * 60 * 60 * 24 + tsmax_in_days = 2**63 / oneday_in_ns # 2**63 ns, in days + # just in bounds + should_succeed = Series( + [0, tsmax_in_days - 0.005, -tsmax_in_days + 0.005], dtype=float + ) + expected = (should_succeed * oneday_in_ns).astype(np.int64) + for error_mode in ["raise", "coerce", "ignore"]: + result1 = to_datetime(should_succeed, unit="D", errors=error_mode) + # Cast to `np.float64` so that `rtol` and inexact checking kick in + # (`check_exact` doesn't take place for integer dtypes) + tm.assert_almost_equal( + result1.astype(np.int64).astype(np.float64), + expected.astype(np.float64), + rtol=1e-10, + ) + # just out of bounds + should_fail1 = Series([0, tsmax_in_days + 0.005], dtype=float) + should_fail2 = Series([0, -tsmax_in_days - 0.005], dtype=float) + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(should_fail1, unit="D", errors="raise") + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(should_fail2, unit="D", errors="raise") + + +class TestToDatetimeDataFrame: + @pytest.fixture + def df(self): + return DataFrame( + { + "year": [2015, 2016], + "month": [2, 3], + "day": [4, 5], + "hour": [6, 7], + "minute": [58, 59], + "second": [10, 11], + "ms": [1, 1], + "us": [2, 2], + "ns": [3, 3], + } + ) + + def test_dataframe(self, df, cache): + result = to_datetime( + {"year": df["year"], "month": df["month"], "day": df["day"]}, cache=cache + ) + expected = Series( + [Timestamp("20150204 00:00:00"), Timestamp("20160305 00:0:00")] + ) + tm.assert_series_equal(result, expected) + + # dict-like + result = to_datetime(df[["year", "month", "day"]].to_dict(), cache=cache) + tm.assert_series_equal(result, expected) + + def test_dataframe_dict_with_constructable(self, df, cache): + # dict but with constructable + df2 = df[["year", "month", "day"]].to_dict() + df2["month"] = 2 + result = to_datetime(df2, cache=cache) + expected2 = Series( + [Timestamp("20150204 00:00:00"), Timestamp("20160205 00:0:00")] + ) + tm.assert_series_equal(result, expected2) + + @pytest.mark.parametrize( + "unit", + [ + { + "year": "years", + "month": "months", + "day": "days", + "hour": "hours", + "minute": "minutes", + "second": "seconds", + }, + { + "year": "year", + "month": "month", + "day": "day", + "hour": "hour", + "minute": "minute", + "second": "second", + }, + ], + ) + def test_dataframe_field_aliases_column_subset(self, df, cache, unit): + # unit mappings + result = to_datetime(df[list(unit.keys())].rename(columns=unit), cache=cache) + expected = Series( + [Timestamp("20150204 06:58:10"), Timestamp("20160305 07:59:11")], + dtype="M8[ns]", + ) + tm.assert_series_equal(result, expected) + + def test_dataframe_field_aliases(self, df, cache): + d = { + "year": "year", + "month": "month", + "day": "day", + "hour": "hour", + "minute": "minute", + "second": "second", + "ms": "ms", + "us": "us", + "ns": "ns", + } + + result = to_datetime(df.rename(columns=d), cache=cache) + expected = Series( + [ + Timestamp("20150204 06:58:10.001002003"), + Timestamp("20160305 07:59:11.001002003"), + ] + ) + tm.assert_series_equal(result, expected) + + def test_dataframe_str_dtype(self, df, cache): + # coerce back to int + result = to_datetime(df.astype(str), cache=cache) + expected = Series( + [ + Timestamp("20150204 06:58:10.001002003"), + Timestamp("20160305 07:59:11.001002003"), + ] + ) + tm.assert_series_equal(result, expected) + + def test_dataframe_coerce(self, cache): + # passing coerce + df2 = DataFrame({"year": [2015, 2016], "month": [2, 20], "day": [4, 5]}) + + msg = ( + r'^cannot assemble the datetimes: time data ".+" doesn\'t ' + r'match format "%Y%m%d", at position 1\.' + ) + with pytest.raises(ValueError, match=msg): + to_datetime(df2, cache=cache) + + result = to_datetime(df2, errors="coerce", cache=cache) + expected = Series([Timestamp("20150204 00:00:00"), NaT]) + tm.assert_series_equal(result, expected) + + def test_dataframe_extra_keys_raisesm(self, df, cache): + # extra columns + msg = r"extra keys have been passed to the datetime assemblage: \[foo\]" + with pytest.raises(ValueError, match=msg): + df2 = df.copy() + df2["foo"] = 1 + to_datetime(df2, cache=cache) + + @pytest.mark.parametrize( + "cols", + [ + ["year"], + ["year", "month"], + ["year", "month", "second"], + ["month", "day"], + ["year", "day", "second"], + ], + ) + def test_dataframe_missing_keys_raises(self, df, cache, cols): + # not enough + msg = ( + r"to assemble mappings requires at least that \[year, month, " + r"day\] be specified: \[.+\] is missing" + ) + with pytest.raises(ValueError, match=msg): + to_datetime(df[cols], cache=cache) + + def test_dataframe_duplicate_columns_raises(self, cache): + # duplicates + msg = "cannot assemble with duplicate keys" + df2 = DataFrame({"year": [2015, 2016], "month": [2, 20], "day": [4, 5]}) + df2.columns = ["year", "year", "day"] + with pytest.raises(ValueError, match=msg): + to_datetime(df2, cache=cache) + + df2 = DataFrame( + {"year": [2015, 2016], "month": [2, 20], "day": [4, 5], "hour": [4, 5]} + ) + df2.columns = ["year", "month", "day", "day"] + with pytest.raises(ValueError, match=msg): + to_datetime(df2, cache=cache) + + def test_dataframe_int16(self, cache): + # GH#13451 + df = DataFrame({"year": [2015, 2016], "month": [2, 3], "day": [4, 5]}) + + # int16 + result = to_datetime(df.astype("int16"), cache=cache) + expected = Series( + [Timestamp("20150204 00:00:00"), Timestamp("20160305 00:00:00")] + ) + tm.assert_series_equal(result, expected) + + def test_dataframe_mixed(self, cache): + # mixed dtypes + df = DataFrame({"year": [2015, 2016], "month": [2, 3], "day": [4, 5]}) + df["month"] = df["month"].astype("int8") + df["day"] = df["day"].astype("int8") + result = to_datetime(df, cache=cache) + expected = Series( + [Timestamp("20150204 00:00:00"), Timestamp("20160305 00:00:00")] + ) + tm.assert_series_equal(result, expected) + + def test_dataframe_float(self, cache): + # float + df = DataFrame({"year": [2000, 2001], "month": [1.5, 1], "day": [1, 1]}) + msg = ( + r"^cannot assemble the datetimes: unconverted data remains when parsing " + r'with format ".*": "1", at position 0.' + ) + with pytest.raises(ValueError, match=msg): + to_datetime(df, cache=cache) + + def test_dataframe_utc_true(self): + # GH#23760 + df = DataFrame({"year": [2015, 2016], "month": [2, 3], "day": [4, 5]}) + result = to_datetime(df, utc=True) + expected = Series( + np.array(["2015-02-04", "2016-03-05"], dtype="datetime64[ns]") + ).dt.tz_localize("UTC") + tm.assert_series_equal(result, expected) + + +class TestToDatetimeMisc: + def test_to_datetime_barely_out_of_bounds(self): + # GH#19529 + # GH#19382 close enough to bounds that dropping nanos would result + # in an in-bounds datetime + arr = np.array(["2262-04-11 23:47:16.854775808"], dtype=object) + + msg = "^Out of bounds nanosecond timestamp: .*, at position 0" + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime(arr) + + @pytest.mark.parametrize( + "arg, exp_str", + [ + ["2012-01-01 00:00:00", "2012-01-01 00:00:00"], + ["20121001", "2012-10-01"], # bad iso 8601 + ], + ) + def test_to_datetime_iso8601(self, cache, arg, exp_str): + result = to_datetime([arg], cache=cache) + exp = Timestamp(exp_str) + assert result[0] == exp + + @pytest.mark.parametrize( + "input, format", + [ + ("2012", "%Y-%m"), + ("2012-01", "%Y-%m-%d"), + ("2012-01-01", "%Y-%m-%d %H"), + ("2012-01-01 10", "%Y-%m-%d %H:%M"), + ("2012-01-01 10:00", "%Y-%m-%d %H:%M:%S"), + ("2012-01-01 10:00:00", "%Y-%m-%d %H:%M:%S.%f"), + ("2012-01-01 10:00:00.123", "%Y-%m-%d %H:%M:%S.%f%z"), + (0, "%Y-%m-%d"), + ], + ) + @pytest.mark.parametrize("exact", [True, False]) + def test_to_datetime_iso8601_fails(self, input, format, exact): + # https://github.com/pandas-dev/pandas/issues/12649 + # `format` is longer than the string, so this fails regardless of `exact` + with pytest.raises( + ValueError, + match=( + rf"time data \"{input}\" doesn't match format " + rf"\"{format}\", at position 0" + ), + ): + to_datetime(input, format=format, exact=exact) + + @pytest.mark.parametrize( + "input, format", + [ + ("2012-01-01", "%Y-%m"), + ("2012-01-01 10", "%Y-%m-%d"), + ("2012-01-01 10:00", "%Y-%m-%d %H"), + ("2012-01-01 10:00:00", "%Y-%m-%d %H:%M"), + (0, "%Y-%m-%d"), + ], + ) + def test_to_datetime_iso8601_exact_fails(self, input, format): + # https://github.com/pandas-dev/pandas/issues/12649 + # `format` is shorter than the date string, so only fails with `exact=True` + msg = "|".join( + [ + '^unconverted data remains when parsing with format ".*": ".*"' + f", at position 0. {PARSING_ERR_MSG}$", + f'^time data ".*" doesn\'t match format ".*", at position 0. ' + f"{PARSING_ERR_MSG}$", + ] + ) + with pytest.raises( + ValueError, + match=(msg), + ): + to_datetime(input, format=format) + + @pytest.mark.parametrize( + "input, format", + [ + ("2012-01-01", "%Y-%m"), + ("2012-01-01 00", "%Y-%m-%d"), + ("2012-01-01 00:00", "%Y-%m-%d %H"), + ("2012-01-01 00:00:00", "%Y-%m-%d %H:%M"), + ], + ) + def test_to_datetime_iso8601_non_exact(self, input, format): + # https://github.com/pandas-dev/pandas/issues/12649 + expected = Timestamp(2012, 1, 1) + result = to_datetime(input, format=format, exact=False) + assert result == expected + + @pytest.mark.parametrize( + "input, format", + [ + ("2020-01", "%Y/%m"), + ("2020-01-01", "%Y/%m/%d"), + ("2020-01-01 00", "%Y/%m/%dT%H"), + ("2020-01-01T00", "%Y/%m/%d %H"), + ("2020-01-01 00:00", "%Y/%m/%dT%H:%M"), + ("2020-01-01T00:00", "%Y/%m/%d %H:%M"), + ("2020-01-01 00:00:00", "%Y/%m/%dT%H:%M:%S"), + ("2020-01-01T00:00:00", "%Y/%m/%d %H:%M:%S"), + ], + ) + def test_to_datetime_iso8601_separator(self, input, format): + # https://github.com/pandas-dev/pandas/issues/12649 + with pytest.raises( + ValueError, + match=( + rf"time data \"{input}\" doesn\'t match format " + rf"\"{format}\", at position 0" + ), + ): + to_datetime(input, format=format) + + @pytest.mark.parametrize( + "input, format", + [ + ("2020-01", "%Y-%m"), + ("2020-01-01", "%Y-%m-%d"), + ("2020-01-01 00", "%Y-%m-%d %H"), + ("2020-01-01T00", "%Y-%m-%dT%H"), + ("2020-01-01 00:00", "%Y-%m-%d %H:%M"), + ("2020-01-01T00:00", "%Y-%m-%dT%H:%M"), + ("2020-01-01 00:00:00", "%Y-%m-%d %H:%M:%S"), + ("2020-01-01T00:00:00", "%Y-%m-%dT%H:%M:%S"), + ("2020-01-01T00:00:00.000", "%Y-%m-%dT%H:%M:%S.%f"), + ("2020-01-01T00:00:00.000000", "%Y-%m-%dT%H:%M:%S.%f"), + ("2020-01-01T00:00:00.000000000", "%Y-%m-%dT%H:%M:%S.%f"), + ], + ) + def test_to_datetime_iso8601_valid(self, input, format): + # https://github.com/pandas-dev/pandas/issues/12649 + expected = Timestamp(2020, 1, 1) + result = to_datetime(input, format=format) + assert result == expected + + @pytest.mark.parametrize( + "input, format", + [ + ("2020-1", "%Y-%m"), + ("2020-1-1", "%Y-%m-%d"), + ("2020-1-1 0", "%Y-%m-%d %H"), + ("2020-1-1T0", "%Y-%m-%dT%H"), + ("2020-1-1 0:0", "%Y-%m-%d %H:%M"), + ("2020-1-1T0:0", "%Y-%m-%dT%H:%M"), + ("2020-1-1 0:0:0", "%Y-%m-%d %H:%M:%S"), + ("2020-1-1T0:0:0", "%Y-%m-%dT%H:%M:%S"), + ("2020-1-1T0:0:0.000", "%Y-%m-%dT%H:%M:%S.%f"), + ("2020-1-1T0:0:0.000000", "%Y-%m-%dT%H:%M:%S.%f"), + ("2020-1-1T0:0:0.000000000", "%Y-%m-%dT%H:%M:%S.%f"), + ], + ) + def test_to_datetime_iso8601_non_padded(self, input, format): + # https://github.com/pandas-dev/pandas/issues/21422 + expected = Timestamp(2020, 1, 1) + result = to_datetime(input, format=format) + assert result == expected + + @pytest.mark.parametrize( + "input, format", + [ + ("2020-01-01T00:00:00.000000000+00:00", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2020-01-01T00:00:00+00:00", "%Y-%m-%dT%H:%M:%S%z"), + ("2020-01-01T00:00:00Z", "%Y-%m-%dT%H:%M:%S%z"), + ], + ) + def test_to_datetime_iso8601_with_timezone_valid(self, input, format): + # https://github.com/pandas-dev/pandas/issues/12649 + expected = Timestamp(2020, 1, 1, tzinfo=pytz.UTC) + result = to_datetime(input, format=format) + assert result == expected + + def test_to_datetime_default(self, cache): + rs = to_datetime("2001", cache=cache) + xp = datetime(2001, 1, 1) + assert rs == xp + + @pytest.mark.xfail(reason="fails to enforce dayfirst=True, which would raise") + def test_to_datetime_respects_dayfirst(self, cache): + # dayfirst is essentially broken + + # The msg here is not important since it isn't actually raised yet. + msg = "Invalid date specified" + with pytest.raises(ValueError, match=msg): + # if dayfirst is respected, then this would parse as month=13, which + # would raise + with tm.assert_produces_warning(UserWarning, match="Provide format"): + to_datetime("01-13-2012", dayfirst=True, cache=cache) + + def test_to_datetime_on_datetime64_series(self, cache): + # #2699 + ser = Series(date_range("1/1/2000", periods=10)) + + result = to_datetime(ser, cache=cache) + assert result[0] == ser[0] + + def test_to_datetime_with_space_in_series(self, cache): + # GH 6428 + ser = Series(["10/18/2006", "10/18/2008", " "]) + msg = ( + r'^time data " " doesn\'t match format "%m/%d/%Y", ' + rf"at position 2. {PARSING_ERR_MSG}$" + ) + with pytest.raises(ValueError, match=msg): + to_datetime(ser, errors="raise", cache=cache) + result_coerce = to_datetime(ser, errors="coerce", cache=cache) + expected_coerce = Series([datetime(2006, 10, 18), datetime(2008, 10, 18), NaT]) + tm.assert_series_equal(result_coerce, expected_coerce) + result_ignore = to_datetime(ser, errors="ignore", cache=cache) + tm.assert_series_equal(result_ignore, ser) + + @td.skip_if_not_us_locale + def test_to_datetime_with_apply(self, cache): + # this is only locale tested with US/None locales + # GH 5195 + # with a format and coerce a single item to_datetime fails + td = Series(["May 04", "Jun 02", "Dec 11"], index=[1, 2, 3]) + expected = to_datetime(td, format="%b %y", cache=cache) + result = td.apply(to_datetime, format="%b %y", cache=cache) + tm.assert_series_equal(result, expected) + + def test_to_datetime_timezone_name(self): + # https://github.com/pandas-dev/pandas/issues/49748 + result = to_datetime("2020-01-01 00:00:00UTC", format="%Y-%m-%d %H:%M:%S%Z") + expected = Timestamp(2020, 1, 1).tz_localize("UTC") + assert result == expected + + @td.skip_if_not_us_locale + @pytest.mark.parametrize("errors", ["raise", "coerce", "ignore"]) + def test_to_datetime_with_apply_with_empty_str(self, cache, errors): + # this is only locale tested with US/None locales + # GH 5195, GH50251 + # with a format and coerce a single item to_datetime fails + td = Series(["May 04", "Jun 02", ""], index=[1, 2, 3]) + expected = to_datetime(td, format="%b %y", errors=errors, cache=cache) + + result = td.apply( + lambda x: to_datetime(x, format="%b %y", errors="coerce", cache=cache) + ) + tm.assert_series_equal(result, expected) + + def test_to_datetime_empty_stt(self, cache): + # empty string + result = to_datetime("", cache=cache) + assert result is NaT + + def test_to_datetime_empty_str_list(self, cache): + result = to_datetime(["", ""], cache=cache) + assert isna(result).all() + + def test_to_datetime_zero(self, cache): + # ints + result = Timestamp(0) + expected = to_datetime(0, cache=cache) + assert result == expected + + def test_to_datetime_strings(self, cache): + # GH 3888 (strings) + expected = to_datetime(["2012"], cache=cache)[0] + result = to_datetime("2012", cache=cache) + assert result == expected + + def test_to_datetime_strings_variation(self, cache): + array = ["2012", "20120101", "20120101 12:01:01"] + expected = [to_datetime(dt_str, cache=cache) for dt_str in array] + result = [Timestamp(date_str) for date_str in array] + tm.assert_almost_equal(result, expected) + + @pytest.mark.parametrize("result", [Timestamp("2012"), to_datetime("2012")]) + def test_to_datetime_strings_vs_constructor(self, result): + expected = Timestamp(2012, 1, 1) + assert result == expected + + def test_to_datetime_unprocessable_input(self, cache): + # GH 4928 + # GH 21864 + result = to_datetime([1, "1"], errors="ignore", cache=cache) + + expected = Index(np.array([1, "1"], dtype="O")) + tm.assert_equal(result, expected) + msg = '^Given date string "1" not likely a datetime, at position 1$' + with pytest.raises(ValueError, match=msg): + to_datetime([1, "1"], errors="raise", cache=cache) + + def test_to_datetime_unhashable_input(self, cache): + series = Series([["a"]] * 100) + result = to_datetime(series, errors="ignore", cache=cache) + tm.assert_series_equal(series, result) + + def test_to_datetime_other_datetime64_units(self): + # 5/25/2012 + scalar = np.int64(1337904000000000).view("M8[us]") + as_obj = scalar.astype("O") + + index = DatetimeIndex([scalar]) + assert index[0] == scalar.astype("O") + + value = Timestamp(scalar) + assert value == as_obj + + def test_to_datetime_list_of_integers(self): + rng = date_range("1/1/2000", periods=20) + rng = DatetimeIndex(rng.values) + + ints = list(rng.asi8) + + result = DatetimeIndex(ints) + + tm.assert_index_equal(rng, result) + + def test_to_datetime_overflow(self): + # gh-17637 + # we are overflowing Timedelta range here + msg = "Cannot cast 139999 days 00:00:00 to unit='ns' without overflow" + with pytest.raises(OutOfBoundsTimedelta, match=msg): + date_range(start="1/1/1700", freq="B", periods=100000) + + def test_string_invalid_operation(self, cache): + invalid = np.array(["87156549591102612381000001219H5"], dtype=object) + # GH #51084 + + with pytest.raises(ValueError, match="Unknown datetime string format"): + to_datetime(invalid, errors="raise", cache=cache) + + def test_string_na_nat_conversion(self, cache): + # GH #999, #858 + + strings = np.array(["1/1/2000", "1/2/2000", np.nan, "1/4/2000"], dtype=object) + + expected = np.empty(4, dtype="M8[ns]") + for i, val in enumerate(strings): + if isna(val): + expected[i] = iNaT + else: + expected[i] = parse(val) + + result = tslib.array_to_datetime(strings)[0] + tm.assert_almost_equal(result, expected) + + result2 = to_datetime(strings, cache=cache) + assert isinstance(result2, DatetimeIndex) + tm.assert_numpy_array_equal(result, result2.values) + + def test_string_na_nat_conversion_malformed(self, cache): + malformed = np.array(["1/100/2000", np.nan], dtype=object) + + # GH 10636, default is now 'raise' + msg = r"Unknown datetime string format" + with pytest.raises(ValueError, match=msg): + to_datetime(malformed, errors="raise", cache=cache) + + result = to_datetime(malformed, errors="ignore", cache=cache) + # GH 21864 + expected = Index(malformed, dtype=object) + tm.assert_index_equal(result, expected) + + with pytest.raises(ValueError, match=msg): + to_datetime(malformed, errors="raise", cache=cache) + + def test_string_na_nat_conversion_with_name(self, cache): + idx = ["a", "b", "c", "d", "e"] + series = Series( + ["1/1/2000", np.nan, "1/3/2000", np.nan, "1/5/2000"], index=idx, name="foo" + ) + dseries = Series( + [ + to_datetime("1/1/2000", cache=cache), + np.nan, + to_datetime("1/3/2000", cache=cache), + np.nan, + to_datetime("1/5/2000", cache=cache), + ], + index=idx, + name="foo", + ) + + result = to_datetime(series, cache=cache) + dresult = to_datetime(dseries, cache=cache) + + expected = Series(np.empty(5, dtype="M8[ns]"), index=idx) + for i in range(5): + x = series.iloc[i] + if isna(x): + expected.iloc[i] = NaT + else: + expected.iloc[i] = to_datetime(x, cache=cache) + + tm.assert_series_equal(result, expected, check_names=False) + assert result.name == "foo" + + tm.assert_series_equal(dresult, expected, check_names=False) + assert dresult.name == "foo" + + @pytest.mark.parametrize( + "unit", + ["h", "m", "s", "ms", "us", "ns"], + ) + def test_dti_constructor_numpy_timeunits(self, cache, unit): + # GH 9114 + dtype = np.dtype(f"M8[{unit}]") + base = to_datetime(["2000-01-01T00:00", "2000-01-02T00:00", "NaT"], cache=cache) + + values = base.values.astype(dtype) + + if unit in ["h", "m"]: + # we cast to closest supported unit + unit = "s" + exp_dtype = np.dtype(f"M8[{unit}]") + expected = DatetimeIndex(base.astype(exp_dtype)) + assert expected.dtype == exp_dtype + + tm.assert_index_equal(DatetimeIndex(values), expected) + tm.assert_index_equal(to_datetime(values, cache=cache), expected) + + def test_dayfirst(self, cache): + # GH 5917 + arr = ["10/02/2014", "11/02/2014", "12/02/2014"] + expected = DatetimeIndex( + [datetime(2014, 2, 10), datetime(2014, 2, 11), datetime(2014, 2, 12)] + ) + idx1 = DatetimeIndex(arr, dayfirst=True) + idx2 = DatetimeIndex(np.array(arr), dayfirst=True) + idx3 = to_datetime(arr, dayfirst=True, cache=cache) + idx4 = to_datetime(np.array(arr), dayfirst=True, cache=cache) + idx5 = DatetimeIndex(Index(arr), dayfirst=True) + idx6 = DatetimeIndex(Series(arr), dayfirst=True) + tm.assert_index_equal(expected, idx1) + tm.assert_index_equal(expected, idx2) + tm.assert_index_equal(expected, idx3) + tm.assert_index_equal(expected, idx4) + tm.assert_index_equal(expected, idx5) + tm.assert_index_equal(expected, idx6) + + def test_dayfirst_warnings_valid_input(self): + # GH 12585 + warning_msg = ( + "Parsing dates in .* format when dayfirst=.* was specified. " + "Pass `dayfirst=.*` or specify a format to silence this warning." + ) + + # CASE 1: valid input + arr = ["31/12/2014", "10/03/2011"] + expected = DatetimeIndex( + ["2014-12-31", "2011-03-10"], dtype="datetime64[ns]", freq=None + ) + + # A. dayfirst arg correct, no warning + res1 = to_datetime(arr, dayfirst=True) + tm.assert_index_equal(expected, res1) + + # B. dayfirst arg incorrect, warning + with tm.assert_produces_warning(UserWarning, match=warning_msg): + res2 = to_datetime(arr, dayfirst=False) + tm.assert_index_equal(expected, res2) + + def test_dayfirst_warnings_invalid_input(self): + # CASE 2: invalid input + # cannot consistently process with single format + # ValueError *always* raised + + # first in DD/MM/YYYY, second in MM/DD/YYYY + arr = ["31/12/2014", "03/30/2011"] + + with pytest.raises( + ValueError, + match=( + r'^time data "03/30/2011" doesn\'t match format ' + rf'"%d/%m/%Y", at position 1. {PARSING_ERR_MSG}$' + ), + ): + to_datetime(arr, dayfirst=True) + + @pytest.mark.parametrize("klass", [DatetimeIndex, DatetimeArray._from_sequence]) + def test_to_datetime_dta_tz(self, klass): + # GH#27733 + dti = date_range("2015-04-05", periods=3).rename("foo") + expected = dti.tz_localize("UTC") + + obj = klass(dti) + expected = klass(expected) + + result = to_datetime(obj, utc=True) + tm.assert_equal(result, expected) + + +class TestGuessDatetimeFormat: + @pytest.mark.parametrize( + "test_list", + [ + [ + "2011-12-30 00:00:00.000000", + "2011-12-30 00:00:00.000000", + "2011-12-30 00:00:00.000000", + ], + [np.nan, np.nan, "2011-12-30 00:00:00.000000"], + ["", "2011-12-30 00:00:00.000000"], + ["NaT", "2011-12-30 00:00:00.000000"], + ["2011-12-30 00:00:00.000000", "random_string"], + ["now", "2011-12-30 00:00:00.000000"], + ["today", "2011-12-30 00:00:00.000000"], + ], + ) + def test_guess_datetime_format_for_array(self, test_list): + expected_format = "%Y-%m-%d %H:%M:%S.%f" + test_array = np.array(test_list, dtype=object) + assert tools._guess_datetime_format_for_array(test_array) == expected_format + + @td.skip_if_not_us_locale + def test_guess_datetime_format_for_array_all_nans(self): + format_for_string_of_nans = tools._guess_datetime_format_for_array( + np.array([np.nan, np.nan, np.nan], dtype="O") + ) + assert format_for_string_of_nans is None + + +class TestToDatetimeInferFormat: + @pytest.mark.parametrize( + "test_format", ["%m-%d-%Y", "%m/%d/%Y %H:%M:%S.%f", "%Y-%m-%dT%H:%M:%S.%f"] + ) + def test_to_datetime_infer_datetime_format_consistent_format( + self, cache, test_format + ): + ser = Series(date_range("20000101", periods=50, freq="h")) + + s_as_dt_strings = ser.apply(lambda x: x.strftime(test_format)) + + with_format = to_datetime(s_as_dt_strings, format=test_format, cache=cache) + without_format = to_datetime(s_as_dt_strings, cache=cache) + + # Whether the format is explicitly passed, or + # it is inferred, the results should all be the same + tm.assert_series_equal(with_format, without_format) + + def test_to_datetime_inconsistent_format(self, cache): + data = ["01/01/2011 00:00:00", "01-02-2011 00:00:00", "2011-01-03T00:00:00"] + ser = Series(np.array(data)) + msg = ( + r'^time data "01-02-2011 00:00:00" doesn\'t match format ' + rf'"%m/%d/%Y %H:%M:%S", at position 1. {PARSING_ERR_MSG}$' + ) + with pytest.raises(ValueError, match=msg): + to_datetime(ser, cache=cache) + + def test_to_datetime_consistent_format(self, cache): + data = ["Jan/01/2011", "Feb/01/2011", "Mar/01/2011"] + ser = Series(np.array(data)) + result = to_datetime(ser, cache=cache) + expected = Series( + ["2011-01-01", "2011-02-01", "2011-03-01"], dtype="datetime64[ns]" + ) + tm.assert_series_equal(result, expected) + + def test_to_datetime_series_with_nans(self, cache): + ser = Series( + np.array( + ["01/01/2011 00:00:00", np.nan, "01/03/2011 00:00:00", np.nan], + dtype=object, + ) + ) + result = to_datetime(ser, cache=cache) + expected = Series( + ["2011-01-01", NaT, "2011-01-03", NaT], dtype="datetime64[ns]" + ) + tm.assert_series_equal(result, expected) + + def test_to_datetime_series_start_with_nans(self, cache): + ser = Series( + np.array( + [ + np.nan, + np.nan, + "01/01/2011 00:00:00", + "01/02/2011 00:00:00", + "01/03/2011 00:00:00", + ], + dtype=object, + ) + ) + + result = to_datetime(ser, cache=cache) + expected = Series( + [NaT, NaT, "2011-01-01", "2011-01-02", "2011-01-03"], dtype="datetime64[ns]" + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "tz_name, offset", + [("UTC", 0), ("UTC-3", 180), ("UTC+3", -180)], + ) + def test_infer_datetime_format_tz_name(self, tz_name, offset): + # GH 33133 + ser = Series([f"2019-02-02 08:07:13 {tz_name}"]) + result = to_datetime(ser) + tz = timezone(timedelta(minutes=offset)) + expected = Series([Timestamp("2019-02-02 08:07:13").tz_localize(tz)]) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "ts,zero_tz", + [ + ("2019-02-02 08:07:13", "Z"), + ("2019-02-02 08:07:13", ""), + ("2019-02-02 08:07:13.012345", "Z"), + ("2019-02-02 08:07:13.012345", ""), + ], + ) + def test_infer_datetime_format_zero_tz(self, ts, zero_tz): + # GH 41047 + ser = Series([ts + zero_tz]) + result = to_datetime(ser) + tz = pytz.utc if zero_tz == "Z" else None + expected = Series([Timestamp(ts, tz=tz)]) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("format", [None, "%Y-%m-%d"]) + def test_to_datetime_iso8601_noleading_0s(self, cache, format): + # GH 11871 + ser = Series(["2014-1-1", "2014-2-2", "2015-3-3"]) + expected = Series( + [ + Timestamp("2014-01-01"), + Timestamp("2014-02-02"), + Timestamp("2015-03-03"), + ] + ) + result = to_datetime(ser, format=format, cache=cache) + tm.assert_series_equal(result, expected) + + def test_parse_dates_infer_datetime_format_warning(self): + # GH 49024 + with tm.assert_produces_warning( + UserWarning, + match="The argument 'infer_datetime_format' is deprecated", + ): + to_datetime(["10-10-2000"], infer_datetime_format=True) + + +class TestDaysInMonth: + # tests for issue #10154 + + @pytest.mark.parametrize( + "arg, format", + [ + ["2015-02-29", None], + ["2015-02-29", "%Y-%m-%d"], + ["2015-02-32", "%Y-%m-%d"], + ["2015-04-31", "%Y-%m-%d"], + ], + ) + def test_day_not_in_month_coerce(self, cache, arg, format): + assert isna(to_datetime(arg, errors="coerce", format=format, cache=cache)) + + def test_day_not_in_month_raise(self, cache): + if PY314: + msg = "day 29 must be in range 1..28 for month 2 in year 2015: 2015-02-29" + else: + msg = "day is out of range for month: 2015-02-29" + with pytest.raises(ValueError, match=msg): + to_datetime("2015-02-29", errors="raise", cache=cache) + + @pytest.mark.parametrize( + "arg, format, msg", + [ + ( + "2015-02-29", + "%Y-%m-%d", + f"^{DAY_IS_OUT_OF_RANGE}. {PARSING_ERR_MSG}$", + ), + ( + "2015-29-02", + "%Y-%d-%m", + f"^{DAY_IS_OUT_OF_RANGE}. {PARSING_ERR_MSG}$", + ), + ( + "2015-02-32", + "%Y-%m-%d", + '^unconverted data remains when parsing with format "%Y-%m-%d": "2", ' + f"at position 0. {PARSING_ERR_MSG}$", + ), + ( + "2015-32-02", + "%Y-%d-%m", + '^time data "2015-32-02" doesn\'t match format "%Y-%d-%m", ' + f"at position 0. {PARSING_ERR_MSG}$", + ), + ( + "2015-04-31", + "%Y-%m-%d", + f"^{DAY_IS_OUT_OF_RANGE}. {PARSING_ERR_MSG}$", + ), + ( + "2015-31-04", + "%Y-%d-%m", + f"^{DAY_IS_OUT_OF_RANGE}. {PARSING_ERR_MSG}$", + ), + ], + ) + def test_day_not_in_month_raise_value(self, cache, arg, format, msg): + # https://github.com/pandas-dev/pandas/issues/50462 + with pytest.raises(ValueError, match=msg): + to_datetime(arg, errors="raise", format=format, cache=cache) + + @pytest.mark.parametrize( + "expected, format", + [ + ["2015-02-29", None], + ["2015-02-29", "%Y-%m-%d"], + ["2015-02-29", "%Y-%m-%d"], + ["2015-04-31", "%Y-%m-%d"], + ], + ) + def test_day_not_in_month_ignore(self, cache, expected, format): + result = to_datetime(expected, errors="ignore", format=format, cache=cache) + assert result == expected + + +class TestDatetimeParsingWrappers: + @pytest.mark.parametrize( + "date_str, expected", + [ + ("2011-01-01", datetime(2011, 1, 1)), + ("2Q2005", datetime(2005, 4, 1)), + ("2Q05", datetime(2005, 4, 1)), + ("2005Q1", datetime(2005, 1, 1)), + ("05Q1", datetime(2005, 1, 1)), + ("2011Q3", datetime(2011, 7, 1)), + ("11Q3", datetime(2011, 7, 1)), + ("3Q2011", datetime(2011, 7, 1)), + ("3Q11", datetime(2011, 7, 1)), + # quarterly without space + ("2000Q4", datetime(2000, 10, 1)), + ("00Q4", datetime(2000, 10, 1)), + ("4Q2000", datetime(2000, 10, 1)), + ("4Q00", datetime(2000, 10, 1)), + ("2000q4", datetime(2000, 10, 1)), + ("2000-Q4", datetime(2000, 10, 1)), + ("00-Q4", datetime(2000, 10, 1)), + ("4Q-2000", datetime(2000, 10, 1)), + ("4Q-00", datetime(2000, 10, 1)), + ("00q4", datetime(2000, 10, 1)), + ("2005", datetime(2005, 1, 1)), + ("2005-11", datetime(2005, 11, 1)), + ("2005 11", datetime(2005, 11, 1)), + ("11-2005", datetime(2005, 11, 1)), + ("11 2005", datetime(2005, 11, 1)), + ("200511", datetime(2020, 5, 11)), + ("20051109", datetime(2005, 11, 9)), + ("20051109 10:15", datetime(2005, 11, 9, 10, 15)), + ("20051109 08H", datetime(2005, 11, 9, 8, 0)), + ("2005-11-09 10:15", datetime(2005, 11, 9, 10, 15)), + ("2005-11-09 08H", datetime(2005, 11, 9, 8, 0)), + ("2005/11/09 10:15", datetime(2005, 11, 9, 10, 15)), + ("2005/11/09 10:15:32", datetime(2005, 11, 9, 10, 15, 32)), + ("2005/11/09 10:15:32 AM", datetime(2005, 11, 9, 10, 15, 32)), + ("2005/11/09 10:15:32 PM", datetime(2005, 11, 9, 22, 15, 32)), + ("2005/11/09 08H", datetime(2005, 11, 9, 8, 0)), + ("Thu Sep 25 10:36:28 2003", datetime(2003, 9, 25, 10, 36, 28)), + ("Thu Sep 25 2003", datetime(2003, 9, 25)), + ("Sep 25 2003", datetime(2003, 9, 25)), + ("January 1 2014", datetime(2014, 1, 1)), + # GH#10537 + ("2014-06", datetime(2014, 6, 1)), + ("06-2014", datetime(2014, 6, 1)), + ("2014-6", datetime(2014, 6, 1)), + ("6-2014", datetime(2014, 6, 1)), + ("20010101 12", datetime(2001, 1, 1, 12)), + ("20010101 1234", datetime(2001, 1, 1, 12, 34)), + ("20010101 123456", datetime(2001, 1, 1, 12, 34, 56)), + ], + ) + def test_parsers(self, date_str, expected, cache): + # dateutil >= 2.5.0 defaults to yearfirst=True + # https://github.com/dateutil/dateutil/issues/217 + yearfirst = True + + result1, _ = parsing.parse_datetime_string_with_reso( + date_str, yearfirst=yearfirst + ) + result2 = to_datetime(date_str, yearfirst=yearfirst) + result3 = to_datetime([date_str], yearfirst=yearfirst) + # result5 is used below + result4 = to_datetime( + np.array([date_str], dtype=object), yearfirst=yearfirst, cache=cache + ) + result6 = DatetimeIndex([date_str], yearfirst=yearfirst) + # result7 is used below + result8 = DatetimeIndex(Index([date_str]), yearfirst=yearfirst) + result9 = DatetimeIndex(Series([date_str]), yearfirst=yearfirst) + + for res in [result1, result2]: + assert res == expected + for res in [result3, result4, result6, result8, result9]: + exp = DatetimeIndex([Timestamp(expected)]) + tm.assert_index_equal(res, exp) + + # these really need to have yearfirst, but we don't support + if not yearfirst: + result5 = Timestamp(date_str) + assert result5 == expected + result7 = date_range(date_str, freq="S", periods=1, yearfirst=yearfirst) + assert result7 == expected + + def test_na_values_with_cache( + self, cache, unique_nulls_fixture, unique_nulls_fixture2 + ): + # GH22305 + expected = Index([NaT, NaT], dtype="datetime64[ns]") + result = to_datetime([unique_nulls_fixture, unique_nulls_fixture2], cache=cache) + tm.assert_index_equal(result, expected) + + def test_parsers_nat(self): + # Test that each of several string-accepting methods return pd.NaT + result1, _ = parsing.parse_datetime_string_with_reso("NaT") + result2 = to_datetime("NaT") + result3 = Timestamp("NaT") + result4 = DatetimeIndex(["NaT"])[0] + assert result1 is NaT + assert result2 is NaT + assert result3 is NaT + assert result4 is NaT + + @pytest.mark.parametrize( + "date_str, dayfirst, yearfirst, expected", + [ + ("10-11-12", False, False, datetime(2012, 10, 11)), + ("10-11-12", True, False, datetime(2012, 11, 10)), + ("10-11-12", False, True, datetime(2010, 11, 12)), + ("10-11-12", True, True, datetime(2010, 12, 11)), + ("20/12/21", False, False, datetime(2021, 12, 20)), + ("20/12/21", True, False, datetime(2021, 12, 20)), + ("20/12/21", False, True, datetime(2020, 12, 21)), + ("20/12/21", True, True, datetime(2020, 12, 21)), + ], + ) + def test_parsers_dayfirst_yearfirst( + self, cache, date_str, dayfirst, yearfirst, expected + ): + # OK + # 2.5.1 10-11-12 [dayfirst=0, yearfirst=0] -> 2012-10-11 00:00:00 + # 2.5.2 10-11-12 [dayfirst=0, yearfirst=1] -> 2012-10-11 00:00:00 + # 2.5.3 10-11-12 [dayfirst=0, yearfirst=0] -> 2012-10-11 00:00:00 + + # OK + # 2.5.1 10-11-12 [dayfirst=0, yearfirst=1] -> 2010-11-12 00:00:00 + # 2.5.2 10-11-12 [dayfirst=0, yearfirst=1] -> 2010-11-12 00:00:00 + # 2.5.3 10-11-12 [dayfirst=0, yearfirst=1] -> 2010-11-12 00:00:00 + + # bug fix in 2.5.2 + # 2.5.1 10-11-12 [dayfirst=1, yearfirst=1] -> 2010-11-12 00:00:00 + # 2.5.2 10-11-12 [dayfirst=1, yearfirst=1] -> 2010-12-11 00:00:00 + # 2.5.3 10-11-12 [dayfirst=1, yearfirst=1] -> 2010-12-11 00:00:00 + + # OK + # 2.5.1 10-11-12 [dayfirst=1, yearfirst=0] -> 2012-11-10 00:00:00 + # 2.5.2 10-11-12 [dayfirst=1, yearfirst=0] -> 2012-11-10 00:00:00 + # 2.5.3 10-11-12 [dayfirst=1, yearfirst=0] -> 2012-11-10 00:00:00 + + # OK + # 2.5.1 20/12/21 [dayfirst=0, yearfirst=0] -> 2021-12-20 00:00:00 + # 2.5.2 20/12/21 [dayfirst=0, yearfirst=0] -> 2021-12-20 00:00:00 + # 2.5.3 20/12/21 [dayfirst=0, yearfirst=0] -> 2021-12-20 00:00:00 + + # OK + # 2.5.1 20/12/21 [dayfirst=0, yearfirst=1] -> 2020-12-21 00:00:00 + # 2.5.2 20/12/21 [dayfirst=0, yearfirst=1] -> 2020-12-21 00:00:00 + # 2.5.3 20/12/21 [dayfirst=0, yearfirst=1] -> 2020-12-21 00:00:00 + + # revert of bug in 2.5.2 + # 2.5.1 20/12/21 [dayfirst=1, yearfirst=1] -> 2020-12-21 00:00:00 + # 2.5.2 20/12/21 [dayfirst=1, yearfirst=1] -> month must be in 1..12 + # 2.5.3 20/12/21 [dayfirst=1, yearfirst=1] -> 2020-12-21 00:00:00 + + # OK + # 2.5.1 20/12/21 [dayfirst=1, yearfirst=0] -> 2021-12-20 00:00:00 + # 2.5.2 20/12/21 [dayfirst=1, yearfirst=0] -> 2021-12-20 00:00:00 + # 2.5.3 20/12/21 [dayfirst=1, yearfirst=0] -> 2021-12-20 00:00:00 + + # str : dayfirst, yearfirst, expected + + # compare with dateutil result + dateutil_result = parse(date_str, dayfirst=dayfirst, yearfirst=yearfirst) + assert dateutil_result == expected + + result1, _ = parsing.parse_datetime_string_with_reso( + date_str, dayfirst=dayfirst, yearfirst=yearfirst + ) + + # we don't support dayfirst/yearfirst here: + if not dayfirst and not yearfirst: + result2 = Timestamp(date_str) + assert result2 == expected + + result3 = to_datetime( + date_str, dayfirst=dayfirst, yearfirst=yearfirst, cache=cache + ) + + result4 = DatetimeIndex([date_str], dayfirst=dayfirst, yearfirst=yearfirst)[0] + + assert result1 == expected + assert result3 == expected + assert result4 == expected + + @pytest.mark.parametrize( + "date_str, exp_def", + [["10:15", datetime(1, 1, 1, 10, 15)], ["9:05", datetime(1, 1, 1, 9, 5)]], + ) + def test_parsers_timestring(self, date_str, exp_def): + # must be the same as dateutil result + exp_now = parse(date_str) + + result1, _ = parsing.parse_datetime_string_with_reso(date_str) + result2 = to_datetime(date_str) + result3 = to_datetime([date_str]) + result4 = Timestamp(date_str) + result5 = DatetimeIndex([date_str])[0] + # parse time string return time string based on default date + # others are not, and can't be changed because it is used in + # time series plot + assert result1 == exp_def + assert result2 == exp_now + assert result3 == exp_now + assert result4 == exp_now + assert result5 == exp_now + + @pytest.mark.parametrize( + "dt_string, tz, dt_string_repr", + [ + ( + "2013-01-01 05:45+0545", + timezone(timedelta(minutes=345)), + "Timestamp('2013-01-01 05:45:00+0545', tz='UTC+05:45')", + ), + ( + "2013-01-01 05:30+0530", + timezone(timedelta(minutes=330)), + "Timestamp('2013-01-01 05:30:00+0530', tz='UTC+05:30')", + ), + ], + ) + def test_parsers_timezone_minute_offsets_roundtrip( + self, cache, dt_string, tz, dt_string_repr + ): + # GH11708 + base = to_datetime("2013-01-01 00:00:00", cache=cache) + base = base.tz_localize("UTC").tz_convert(tz) + dt_time = to_datetime(dt_string, cache=cache) + assert base == dt_time + assert dt_string_repr == repr(dt_time) + + +@pytest.fixture(params=["D", "s", "ms", "us", "ns"]) +def units(request): + """Day and some time units. + + * D + * s + * ms + * us + * ns + """ + return request.param + + +@pytest.fixture +def epoch_1960(): + """Timestamp at 1960-01-01.""" + return Timestamp("1960-01-01") + + +@pytest.fixture +def units_from_epochs(): + return list(range(5)) + + +@pytest.fixture(params=["timestamp", "pydatetime", "datetime64", "str_1960"]) +def epochs(epoch_1960, request): + """Timestamp at 1960-01-01 in various forms. + + * Timestamp + * datetime.datetime + * numpy.datetime64 + * str + """ + assert request.param in {"timestamp", "pydatetime", "datetime64", "str_1960"} + if request.param == "timestamp": + return epoch_1960 + elif request.param == "pydatetime": + return epoch_1960.to_pydatetime() + elif request.param == "datetime64": + return epoch_1960.to_datetime64() + else: + return str(epoch_1960) + + +@pytest.fixture +def julian_dates(): + return date_range("2014-1-1", periods=10).to_julian_date().values + + +class TestOrigin: + def test_origin_and_unit(self): + # GH#42624 + ts = to_datetime(1, unit="s", origin=1) + expected = Timestamp("1970-01-01 00:00:02") + assert ts == expected + + ts = to_datetime(1, unit="s", origin=1_000_000_000) + expected = Timestamp("2001-09-09 01:46:41") + assert ts == expected + + def test_julian(self, julian_dates): + # gh-11276, gh-11745 + # for origin as julian + + result = Series(to_datetime(julian_dates, unit="D", origin="julian")) + expected = Series( + to_datetime(julian_dates - Timestamp(0).to_julian_date(), unit="D") + ) + tm.assert_series_equal(result, expected) + + def test_unix(self): + result = Series(to_datetime([0, 1, 2], unit="D", origin="unix")) + expected = Series( + [Timestamp("1970-01-01"), Timestamp("1970-01-02"), Timestamp("1970-01-03")], + dtype="M8[ns]", + ) + tm.assert_series_equal(result, expected) + + def test_julian_round_trip(self): + result = to_datetime(2456658, origin="julian", unit="D") + assert result.to_julian_date() == 2456658 + + # out-of-bounds + msg = "1 is Out of Bounds for origin='julian'" + with pytest.raises(ValueError, match=msg): + to_datetime(1, origin="julian", unit="D") + + def test_invalid_unit(self, units, julian_dates): + # checking for invalid combination of origin='julian' and unit != D + if units != "D": + msg = "unit must be 'D' for origin='julian'" + with pytest.raises(ValueError, match=msg): + to_datetime(julian_dates, unit=units, origin="julian") + + @pytest.mark.parametrize("unit", ["ns", "D"]) + def test_invalid_origin(self, unit): + # need to have a numeric specified + msg = "it must be numeric with a unit specified" + with pytest.raises(ValueError, match=msg): + to_datetime("2005-01-01", origin="1960-01-01", unit=unit) + + @pytest.mark.parametrize( + "epochs", + [ + Timestamp(1960, 1, 1), + datetime(1960, 1, 1), + "1960-01-01", + np.datetime64("1960-01-01"), + ], + ) + def test_epoch(self, units, epochs): + epoch_1960 = Timestamp(1960, 1, 1) + units_from_epochs = np.arange(5, dtype=np.int64) + expected = Series( + [pd.Timedelta(x, unit=units) + epoch_1960 for x in units_from_epochs] + ) + + result = Series(to_datetime(units_from_epochs, unit=units, origin=epochs)) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "origin, exc", + [ + ("random_string", ValueError), + ("epoch", ValueError), + ("13-24-1990", ValueError), + (datetime(1, 1, 1), OutOfBoundsDatetime), + ], + ) + def test_invalid_origins(self, origin, exc, units, units_from_epochs): + msg = "|".join( + [ + f"origin {origin} is Out of Bounds", + f"origin {origin} cannot be converted to a Timestamp", + "Cannot cast .* to unit='ns' without overflow", + ] + ) + with pytest.raises(exc, match=msg): + to_datetime(units_from_epochs, unit=units, origin=origin) + + def test_invalid_origins_tzinfo(self): + # GH16842 + with pytest.raises(ValueError, match="must be tz-naive"): + to_datetime(1, unit="D", origin=datetime(2000, 1, 1, tzinfo=pytz.utc)) + + def test_incorrect_value_exception(self): + # GH47495 + msg = ( + "Unknown datetime string format, unable to parse: yesterday, at position 1" + ) + with pytest.raises(ValueError, match=msg): + to_datetime(["today", "yesterday"]) + + @pytest.mark.parametrize( + "format, warning", + [ + (None, UserWarning), + ("%Y-%m-%d %H:%M:%S", None), + ("%Y-%d-%m %H:%M:%S", None), + ], + ) + def test_to_datetime_out_of_bounds_with_format_arg(self, format, warning): + # see gh-23830 + msg = r"^Out of bounds nanosecond timestamp: 2417-10-10 00:00:00, at position 0" + with pytest.raises(OutOfBoundsDatetime, match=msg): + to_datetime("2417-10-10 00:00:00", format=format) + + @pytest.mark.parametrize( + "arg, origin, expected_str", + [ + [200 * 365, "unix", "2169-11-13 00:00:00"], + [200 * 365, "1870-01-01", "2069-11-13 00:00:00"], + [300 * 365, "1870-01-01", "2169-10-20 00:00:00"], + ], + ) + def test_processing_order(self, arg, origin, expected_str): + # make sure we handle out-of-bounds *before* + # constructing the dates + + result = to_datetime(arg, unit="D", origin=origin) + expected = Timestamp(expected_str) + assert result == expected + + result = to_datetime(200 * 365, unit="D", origin="1870-01-01") + expected = Timestamp("2069-11-13 00:00:00") + assert result == expected + + result = to_datetime(300 * 365, unit="D", origin="1870-01-01") + expected = Timestamp("2169-10-20 00:00:00") + assert result == expected + + @pytest.mark.parametrize( + "offset,utc,exp", + [ + ["Z", True, "2019-01-01T00:00:00.000Z"], + ["Z", None, "2019-01-01T00:00:00.000Z"], + ["-01:00", True, "2019-01-01T01:00:00.000Z"], + ["-01:00", None, "2019-01-01T00:00:00.000-01:00"], + ], + ) + def test_arg_tz_ns_unit(self, offset, utc, exp): + # GH 25546 + arg = "2019-01-01T00:00:00.000" + offset + result = to_datetime([arg], unit="ns", utc=utc) + expected = to_datetime([exp]).as_unit("ns") + tm.assert_index_equal(result, expected) + + +class TestShouldCache: + @pytest.mark.parametrize( + "listlike,do_caching", + [ + ([1, 2, 3, 4, 5, 6, 7, 8, 9, 0], False), + ([1, 1, 1, 1, 4, 5, 6, 7, 8, 9], True), + ], + ) + def test_should_cache(self, listlike, do_caching): + assert ( + tools.should_cache(listlike, check_count=len(listlike), unique_share=0.7) + == do_caching + ) + + @pytest.mark.parametrize( + "unique_share,check_count, err_message", + [ + (0.5, 11, r"check_count must be in next bounds: \[0; len\(arg\)\]"), + (10, 2, r"unique_share must be in next bounds: \(0; 1\)"), + ], + ) + def test_should_cache_errors(self, unique_share, check_count, err_message): + arg = [5] * 10 + + with pytest.raises(AssertionError, match=err_message): + tools.should_cache(arg, unique_share, check_count) + + @pytest.mark.parametrize( + "listlike", + [ + (deque([Timestamp("2010-06-02 09:30:00")] * 51)), + ([Timestamp("2010-06-02 09:30:00")] * 51), + (tuple([Timestamp("2010-06-02 09:30:00")] * 51)), + ], + ) + def test_no_slicing_errors_in_should_cache(self, listlike): + # GH#29403 + assert tools.should_cache(listlike) is True + + +def test_nullable_integer_to_datetime(): + # Test for #30050 + ser = Series([1, 2, None, 2**61, None]) + ser = ser.astype("Int64") + ser_copy = ser.copy() + + res = to_datetime(ser, unit="ns") + + expected = Series( + [ + np.datetime64("1970-01-01 00:00:00.000000001"), + np.datetime64("1970-01-01 00:00:00.000000002"), + np.datetime64("NaT"), + np.datetime64("2043-01-25 23:56:49.213693952"), + np.datetime64("NaT"), + ] + ) + tm.assert_series_equal(res, expected) + # Check that ser isn't mutated + tm.assert_series_equal(ser, ser_copy) + + +@pytest.mark.parametrize("klass", [np.array, list]) +def test_na_to_datetime(nulls_fixture, klass): + if isinstance(nulls_fixture, Decimal): + with pytest.raises(TypeError, match="not convertible to datetime"): + to_datetime(klass([nulls_fixture])) + + else: + result = to_datetime(klass([nulls_fixture])) + + assert result[0] is NaT + + +@pytest.mark.parametrize("errors", ["raise", "coerce", "ignore"]) +@pytest.mark.parametrize( + "args, format", + [ + (["03/24/2016", "03/25/2016", ""], "%m/%d/%Y"), + (["2016-03-24", "2016-03-25", ""], "%Y-%m-%d"), + ], + ids=["non-ISO8601", "ISO8601"], +) +def test_empty_string_datetime(errors, args, format): + # GH13044, GH50251 + td = Series(args) + + # coerce empty string to pd.NaT + result = to_datetime(td, format=format, errors=errors) + expected = Series(["2016-03-24", "2016-03-25", NaT], dtype="datetime64[ns]") + tm.assert_series_equal(expected, result) + + +def test_empty_string_datetime_coerce__unit(): + # GH13044 + # coerce empty string to pd.NaT + result = to_datetime([1, ""], unit="s", errors="coerce") + expected = DatetimeIndex(["1970-01-01 00:00:01", "NaT"], dtype="datetime64[ns]") + tm.assert_index_equal(expected, result) + + # verify that no exception is raised even when errors='raise' is set + result = to_datetime([1, ""], unit="s", errors="raise") + tm.assert_index_equal(expected, result) + + +@pytest.mark.parametrize("cache", [True, False]) +def test_to_datetime_monotonic_increasing_index(cache): + # GH28238 + cstart = start_caching_at + times = date_range(Timestamp("1980"), periods=cstart, freq="YS") + times = times.to_frame(index=False, name="DT").sample(n=cstart, random_state=1) + times.index = times.index.to_series().astype(float) / 1000 + result = to_datetime(times.iloc[:, 0], cache=cache) + expected = times.iloc[:, 0] + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "series_length", + [40, start_caching_at, (start_caching_at + 1), (start_caching_at + 5)], +) +def test_to_datetime_cache_coerce_50_lines_outofbounds(series_length): + # GH#45319 + ser = Series( + [datetime.fromisoformat("1446-04-12 00:00:00+00:00")] + + ([datetime.fromisoformat("1991-10-20 00:00:00+00:00")] * series_length), + dtype=object, + ) + result1 = to_datetime(ser, errors="coerce", utc=True) + + expected1 = Series( + [NaT] + ([Timestamp("1991-10-20 00:00:00+00:00")] * series_length) + ) + + tm.assert_series_equal(result1, expected1) + + result2 = to_datetime(ser, errors="ignore", utc=True) + + expected2 = Series( + [datetime.fromisoformat("1446-04-12 00:00:00+00:00")] + + ([datetime.fromisoformat("1991-10-20 00:00:00+00:00")] * series_length) + ) + + tm.assert_series_equal(result2, expected2) + + with pytest.raises(OutOfBoundsDatetime, match="Out of bounds nanosecond timestamp"): + to_datetime(ser, errors="raise", utc=True) + + +def test_to_datetime_format_f_parse_nanos(): + # GH 48767 + timestamp = "15/02/2020 02:03:04.123456789" + timestamp_format = "%d/%m/%Y %H:%M:%S.%f" + result = to_datetime(timestamp, format=timestamp_format) + expected = Timestamp( + year=2020, + month=2, + day=15, + hour=2, + minute=3, + second=4, + microsecond=123456, + nanosecond=789, + ) + assert result == expected + + +def test_to_datetime_mixed_iso8601(): + # https://github.com/pandas-dev/pandas/issues/50411 + result = to_datetime(["2020-01-01", "2020-01-01 05:00:00"], format="ISO8601") + expected = DatetimeIndex(["2020-01-01 00:00:00", "2020-01-01 05:00:00"]) + tm.assert_index_equal(result, expected) + + +def test_to_datetime_mixed_other(): + # https://github.com/pandas-dev/pandas/issues/50411 + result = to_datetime(["01/11/2000", "12 January 2000"], format="mixed") + expected = DatetimeIndex(["2000-01-11", "2000-01-12"]) + tm.assert_index_equal(result, expected) + + +@pytest.mark.parametrize("exact", [True, False]) +@pytest.mark.parametrize("format", ["ISO8601", "mixed"]) +def test_to_datetime_mixed_or_iso_exact(exact, format): + msg = "Cannot use 'exact' when 'format' is 'mixed' or 'ISO8601'" + with pytest.raises(ValueError, match=msg): + to_datetime(["2020-01-01"], exact=exact, format=format) + + +def test_to_datetime_mixed_not_necessarily_iso8601_raise(): + # https://github.com/pandas-dev/pandas/issues/50411 + with pytest.raises( + ValueError, match="Time data 01-01-2000 is not ISO8601 format, at position 1" + ): + to_datetime(["2020-01-01", "01-01-2000"], format="ISO8601") + + +@pytest.mark.parametrize( + ("errors", "expected"), + [ + ("coerce", DatetimeIndex(["2020-01-01 00:00:00", NaT])), + ("ignore", Index(["2020-01-01", "01-01-2000"], dtype="str")), + ], +) +def test_to_datetime_mixed_not_necessarily_iso8601_coerce(errors, expected): + # https://github.com/pandas-dev/pandas/issues/50411 + result = to_datetime(["2020-01-01", "01-01-2000"], format="ISO8601", errors=errors) + tm.assert_index_equal(result, expected) + + +def test_ignoring_unknown_tz_deprecated(): + # GH#18702, GH#51476 + dtstr = "2014 Jan 9 05:15 FAKE" + msg = 'un-recognized timezone "FAKE". Dropping unrecognized timezones is deprecated' + with tm.assert_produces_warning(FutureWarning, match=msg): + res = Timestamp(dtstr) + assert res == Timestamp(dtstr[:-5]) + + with tm.assert_produces_warning(FutureWarning): + res = to_datetime(dtstr) + assert res == to_datetime(dtstr[:-5]) + with tm.assert_produces_warning(FutureWarning): + res = to_datetime([dtstr]) + tm.assert_index_equal(res, to_datetime([dtstr[:-5]])) + + +def test_from_numeric_arrow_dtype(any_numeric_ea_dtype): + # GH 52425 + pytest.importorskip("pyarrow") + ser = Series([1, 2], dtype=f"{any_numeric_ea_dtype.lower()}[pyarrow]") + result = to_datetime(ser) + expected = Series([1, 2], dtype="datetime64[ns]") + tm.assert_series_equal(result, expected) + + +def test_to_datetime_with_empty_str_utc_false_format_mixed(): + # GH 50887 + vals = ["2020-01-01 00:00+00:00", ""] + result = to_datetime(vals, format="mixed") + expected = Index([Timestamp("2020-01-01 00:00+00:00"), "NaT"], dtype="M8[ns, UTC]") + tm.assert_index_equal(result, expected) + + # Check that a couple of other similar paths work the same way + alt = to_datetime(vals) + tm.assert_index_equal(alt, expected) + alt2 = DatetimeIndex(vals) + tm.assert_index_equal(alt2, expected) + + +def test_to_datetime_with_empty_str_utc_false_offsets_and_format_mixed(): + # GH 50887 + msg = "parsing datetimes with mixed time zones will raise an error" + + with tm.assert_produces_warning(FutureWarning, match=msg): + to_datetime( + ["2020-01-01 00:00+00:00", "2020-01-01 00:00+02:00", ""], format="mixed" + ) + + +def test_to_datetime_mixed_tzs_mixed_types(): + # GH#55793, GH#55693 mismatched tzs but one is str and other is + # datetime object + ts = Timestamp("2016-01-02 03:04:05", tz="US/Pacific") + dtstr = "2023-10-30 15:06+01" + arr = [ts, dtstr] + + msg = ( + "Mixed timezones detected. pass utc=True in to_datetime or tz='UTC' " + "in DatetimeIndex to convert to a common timezone" + ) + with pytest.raises(ValueError, match=msg): + to_datetime(arr) + with pytest.raises(ValueError, match=msg): + to_datetime(arr, format="mixed") + with pytest.raises(ValueError, match=msg): + DatetimeIndex(arr) + + +def test_to_datetime_mixed_types_matching_tzs(): + # GH#55793 + dtstr = "2023-11-01 09:22:03-07:00" + ts = Timestamp(dtstr) + arr = [ts, dtstr] + res1 = to_datetime(arr) + res2 = to_datetime(arr[::-1])[::-1] + res3 = to_datetime(arr, format="mixed") + res4 = DatetimeIndex(arr) + + expected = DatetimeIndex([ts, ts]) + tm.assert_index_equal(res1, expected) + tm.assert_index_equal(res2, expected) + tm.assert_index_equal(res3, expected) + tm.assert_index_equal(res4, expected) + + +dtstr = "2020-01-01 00:00+00:00" +ts = Timestamp(dtstr) + + +@pytest.mark.filterwarnings("ignore:Could not infer format:UserWarning") +@pytest.mark.parametrize( + "aware_val", + [dtstr, Timestamp(dtstr)], + ids=lambda x: type(x).__name__, +) +@pytest.mark.parametrize( + "naive_val", + [dtstr[:-6], ts.tz_localize(None), ts.date(), ts.asm8, ts.value, float(ts.value)], + ids=lambda x: type(x).__name__, +) +@pytest.mark.parametrize("naive_first", [True, False]) +def test_to_datetime_mixed_awareness_mixed_types(aware_val, naive_val, naive_first): + # GH#55793, GH#55693 + # Empty string parses to NaT + vals = [aware_val, naive_val, ""] + + vec = vals + if naive_first: + # alas, the behavior is order-dependent, so we test both ways + vec = [naive_val, aware_val, ""] + + # both_strs-> paths that were previously already deprecated with warning + # issued in _array_to_datetime_object + both_strs = isinstance(aware_val, str) and isinstance(naive_val, str) + has_numeric = isinstance(naive_val, (int, float)) + + depr_msg = "In a future version of pandas, parsing datetimes with mixed time zones" + + first_non_null = next(x for x in vec if x != "") + # if first_non_null is a not a string, _guess_datetime_format_for_array + # doesn't guess a format so we don't go through array_strptime + if not isinstance(first_non_null, str): + # that case goes through array_strptime which has different behavior + msg = "Cannot mix tz-aware with tz-naive values" + if naive_first and isinstance(aware_val, Timestamp): + if isinstance(naive_val, Timestamp): + msg = "Tz-aware datetime.datetime cannot be converted to datetime64" + with pytest.raises(ValueError, match=msg): + to_datetime(vec) + else: + with pytest.raises(ValueError, match=msg): + to_datetime(vec) + + # No warning/error with utc=True + to_datetime(vec, utc=True) + + elif has_numeric and vec.index(aware_val) < vec.index(naive_val): + msg = "time data .* doesn't match format" + with pytest.raises(ValueError, match=msg): + to_datetime(vec) + with pytest.raises(ValueError, match=msg): + to_datetime(vec, utc=True) + + elif both_strs and vec.index(aware_val) < vec.index(naive_val): + msg = r"time data \"2020-01-01 00:00\" doesn't match format" + with pytest.raises(ValueError, match=msg): + to_datetime(vec) + with pytest.raises(ValueError, match=msg): + to_datetime(vec, utc=True) + + elif both_strs and vec.index(naive_val) < vec.index(aware_val): + msg = "unconverted data remains when parsing with format" + with pytest.raises(ValueError, match=msg): + to_datetime(vec) + with pytest.raises(ValueError, match=msg): + to_datetime(vec, utc=True) + + else: + with tm.assert_produces_warning(FutureWarning, match=depr_msg): + to_datetime(vec) + + # No warning/error with utc=True + to_datetime(vec, utc=True) + + if both_strs: + with tm.assert_produces_warning(FutureWarning, match=depr_msg): + to_datetime(vec, format="mixed") + with tm.assert_produces_warning(FutureWarning, match=depr_msg): + msg = "DatetimeIndex has mixed timezones" + with pytest.raises(TypeError, match=msg): + DatetimeIndex(vec) + else: + msg = "Cannot mix tz-aware with tz-naive values" + if naive_first and isinstance(aware_val, Timestamp): + if isinstance(naive_val, Timestamp): + msg = "Tz-aware datetime.datetime cannot be converted to datetime64" + with pytest.raises(ValueError, match=msg): + to_datetime(vec, format="mixed") + with pytest.raises(ValueError, match=msg): + DatetimeIndex(vec) + else: + with pytest.raises(ValueError, match=msg): + to_datetime(vec, format="mixed") + with pytest.raises(ValueError, match=msg): + DatetimeIndex(vec) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_numeric.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_numeric.py new file mode 100644 index 0000000000000000000000000000000000000000..c452382ec572bd24cf704c445f24f9af87947141 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_numeric.py @@ -0,0 +1,978 @@ +import decimal + +import numpy as np +from numpy import iinfo +import pytest + +import pandas.util._test_decorators as td + +import pandas as pd +from pandas import ( + ArrowDtype, + DataFrame, + Index, + Series, + option_context, + to_numeric, +) +import pandas._testing as tm + + +@pytest.fixture(params=[None, "ignore", "raise", "coerce"]) +def errors(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def signed(request): + return request.param + + +@pytest.fixture(params=[lambda x: x, str], ids=["identity", "str"]) +def transform(request): + return request.param + + +@pytest.fixture(params=[47393996303418497800, 100000000000000000000]) +def large_val(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def multiple_elts(request): + return request.param + + +@pytest.fixture( + params=[ + (lambda x: Index(x, name="idx"), tm.assert_index_equal), + (lambda x: Series(x, name="ser"), tm.assert_series_equal), + (lambda x: np.array(Index(x).values), tm.assert_numpy_array_equal), + ] +) +def transform_assert_equal(request): + return request.param + + +@pytest.mark.parametrize( + "input_kwargs,result_kwargs", + [ + ({}, {"dtype": np.int64}), + ({"errors": "coerce", "downcast": "integer"}, {"dtype": np.int8}), + ], +) +def test_empty(input_kwargs, result_kwargs): + # see gh-16302 + ser = Series([], dtype=object) + result = to_numeric(ser, **input_kwargs) + + expected = Series([], **result_kwargs) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "infer_string", [False, pytest.param(True, marks=td.skip_if_no("pyarrow"))] +) +@pytest.mark.parametrize("last_val", ["7", 7]) +def test_series(last_val, infer_string): + with option_context("future.infer_string", infer_string): + ser = Series(["1", "-3.14", last_val]) + result = to_numeric(ser) + + expected = Series([1, -3.14, 7]) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "data", + [ + [1, 3, 4, 5], + [1.0, 3.0, 4.0, 5.0], + # Bool is regarded as numeric. + [True, False, True, True], + ], +) +def test_series_numeric(data): + ser = Series(data, index=list("ABCD"), name="EFG") + + result = to_numeric(ser) + tm.assert_series_equal(result, ser) + + +@pytest.mark.parametrize( + "data,msg", + [ + ([1, -3.14, "apple"], 'Unable to parse string "apple" at position 2'), + ( + ["orange", 1, -3.14, "apple"], + 'Unable to parse string "orange" at position 0', + ), + ], +) +def test_error(data, msg): + ser = Series(data) + + with pytest.raises(ValueError, match=msg): + to_numeric(ser, errors="raise") + + +@pytest.mark.parametrize( + "errors,exp_data", [("ignore", [1, -3.14, "apple"]), ("coerce", [1, -3.14, np.nan])] +) +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_ignore_error(errors, exp_data): + ser = Series([1, -3.14, "apple"]) + result = to_numeric(ser, errors=errors) + + expected = Series(exp_data) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "errors,exp", + [ + ("raise", 'Unable to parse string "apple" at position 2'), + ("ignore", [True, False, "apple"]), + # Coerces to float. + ("coerce", [1.0, 0.0, np.nan]), + ], +) +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_bool_handling(errors, exp): + ser = Series([True, False, "apple"]) + + if isinstance(exp, str): + with pytest.raises(ValueError, match=exp): + to_numeric(ser, errors=errors) + else: + result = to_numeric(ser, errors=errors) + expected = Series(exp) + + tm.assert_series_equal(result, expected) + + +def test_list(): + ser = ["1", "-3.14", "7"] + res = to_numeric(ser) + + expected = np.array([1, -3.14, 7]) + tm.assert_numpy_array_equal(res, expected) + + +@pytest.mark.parametrize( + "data,arr_kwargs", + [ + ([1, 3, 4, 5], {"dtype": np.int64}), + ([1.0, 3.0, 4.0, 5.0], {}), + # Boolean is regarded as numeric. + ([True, False, True, True], {}), + ], +) +def test_list_numeric(data, arr_kwargs): + result = to_numeric(data) + expected = np.array(data, **arr_kwargs) + tm.assert_numpy_array_equal(result, expected) + + +@pytest.mark.parametrize("kwargs", [{"dtype": "O"}, {}]) +def test_numeric(kwargs): + data = [1, -3.14, 7] + + ser = Series(data, **kwargs) + result = to_numeric(ser) + + expected = Series(data) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "columns", + [ + # One column. + "a", + # Multiple columns. + ["a", "b"], + ], +) +def test_numeric_df_columns(columns): + # see gh-14827 + df = DataFrame( + { + "a": [1.2, decimal.Decimal(3.14), decimal.Decimal("infinity"), "0.1"], + "b": [1.0, 2.0, 3.0, 4.0], + } + ) + + expected = DataFrame({"a": [1.2, 3.14, np.inf, 0.1], "b": [1.0, 2.0, 3.0, 4.0]}) + + df_copy = df.copy() + df_copy[columns] = df_copy[columns].apply(to_numeric) + + tm.assert_frame_equal(df_copy, expected) + + +@pytest.mark.parametrize( + "data,exp_data", + [ + ( + [[decimal.Decimal(3.14), 1.0], decimal.Decimal(1.6), 0.1], + [[3.14, 1.0], 1.6, 0.1], + ), + ([np.array([decimal.Decimal(3.14), 1.0]), 0.1], [[3.14, 1.0], 0.1]), + ], +) +def test_numeric_embedded_arr_likes(data, exp_data): + # Test to_numeric with embedded lists and arrays + df = DataFrame({"a": data}) + df["a"] = df["a"].apply(to_numeric) + + expected = DataFrame({"a": exp_data}) + tm.assert_frame_equal(df, expected) + + +def test_all_nan(): + ser = Series(["a", "b", "c"]) + result = to_numeric(ser, errors="coerce") + + expected = Series([np.nan, np.nan, np.nan]) + tm.assert_series_equal(result, expected) + + +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_type_check(errors): + # see gh-11776 + df = DataFrame({"a": [1, -3.14, 7], "b": ["4", "5", "6"]}) + kwargs = {"errors": errors} if errors is not None else {} + with pytest.raises(TypeError, match="1-d array"): + to_numeric(df, **kwargs) + + +@pytest.mark.parametrize("val", [1, 1.1, 20001]) +def test_scalar(val, signed, transform): + val = -val if signed else val + assert to_numeric(transform(val)) == float(val) + + +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_really_large_scalar(large_val, signed, transform, errors): + # see gh-24910 + kwargs = {"errors": errors} if errors is not None else {} + val = -large_val if signed else large_val + + val = transform(val) + val_is_string = isinstance(val, str) + + if val_is_string and errors in (None, "raise"): + msg = "Integer out of range. at position 0" + with pytest.raises(ValueError, match=msg): + to_numeric(val, **kwargs) + else: + expected = float(val) if (errors == "coerce" and val_is_string) else val + tm.assert_almost_equal(to_numeric(val, **kwargs), expected) + + +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_really_large_in_arr(large_val, signed, transform, multiple_elts, errors): + # see gh-24910 + kwargs = {"errors": errors} if errors is not None else {} + val = -large_val if signed else large_val + val = transform(val) + + extra_elt = "string" + arr = [val] + multiple_elts * [extra_elt] + + val_is_string = isinstance(val, str) + coercing = errors == "coerce" + + if errors in (None, "raise") and (val_is_string or multiple_elts): + if val_is_string: + msg = "Integer out of range. at position 0" + else: + msg = 'Unable to parse string "string" at position 1' + + with pytest.raises(ValueError, match=msg): + to_numeric(arr, **kwargs) + else: + result = to_numeric(arr, **kwargs) + + exp_val = float(val) if (coercing and val_is_string) else val + expected = [exp_val] + + if multiple_elts: + if coercing: + expected.append(np.nan) + exp_dtype = float + else: + expected.append(extra_elt) + exp_dtype = object + else: + exp_dtype = float if isinstance(exp_val, (int, float)) else object + + tm.assert_almost_equal(result, np.array(expected, dtype=exp_dtype)) + + +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_really_large_in_arr_consistent(large_val, signed, multiple_elts, errors): + # see gh-24910 + # + # Even if we discover that we have to hold float, does not mean + # we should be lenient on subsequent elements that fail to be integer. + kwargs = {"errors": errors} if errors is not None else {} + arr = [str(-large_val if signed else large_val)] + + if multiple_elts: + arr.insert(0, large_val) + + if errors in (None, "raise"): + index = int(multiple_elts) + msg = f"Integer out of range. at position {index}" + + with pytest.raises(ValueError, match=msg): + to_numeric(arr, **kwargs) + else: + result = to_numeric(arr, **kwargs) + + if errors == "coerce": + expected = [float(i) for i in arr] + exp_dtype = float + else: + expected = arr + exp_dtype = object + + tm.assert_almost_equal(result, np.array(expected, dtype=exp_dtype)) + + +@pytest.mark.parametrize( + "errors,checker", + [ + ("raise", 'Unable to parse string "fail" at position 0'), + ("ignore", lambda x: x == "fail"), + ("coerce", lambda x: np.isnan(x)), + ], +) +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_scalar_fail(errors, checker): + scalar = "fail" + + if isinstance(checker, str): + with pytest.raises(ValueError, match=checker): + to_numeric(scalar, errors=errors) + else: + assert checker(to_numeric(scalar, errors=errors)) + + +@pytest.mark.parametrize("data", [[1, 2, 3], [1.0, np.nan, 3, np.nan]]) +def test_numeric_dtypes(data, transform_assert_equal): + transform, assert_equal = transform_assert_equal + data = transform(data) + + result = to_numeric(data) + assert_equal(result, data) + + +@pytest.mark.parametrize( + "data,exp", + [ + (["1", "2", "3"], np.array([1, 2, 3], dtype="int64")), + (["1.5", "2.7", "3.4"], np.array([1.5, 2.7, 3.4])), + ], +) +def test_str(data, exp, transform_assert_equal): + transform, assert_equal = transform_assert_equal + result = to_numeric(transform(data)) + + expected = transform(exp) + assert_equal(result, expected) + + +def test_datetime_like(tz_naive_fixture, transform_assert_equal): + transform, assert_equal = transform_assert_equal + idx = pd.date_range("20130101", periods=3, tz=tz_naive_fixture) + + result = to_numeric(transform(idx)) + expected = transform(idx.asi8) + assert_equal(result, expected) + + +def test_timedelta(transform_assert_equal): + transform, assert_equal = transform_assert_equal + idx = pd.timedelta_range("1 days", periods=3, freq="D") + + result = to_numeric(transform(idx)) + expected = transform(idx.asi8) + assert_equal(result, expected) + + +def test_period(request, transform_assert_equal): + transform, assert_equal = transform_assert_equal + + idx = pd.period_range("2011-01", periods=3, freq="M", name="") + inp = transform(idx) + + if not isinstance(inp, Index): + request.applymarker( + pytest.mark.xfail(reason="Missing PeriodDtype support in to_numeric") + ) + result = to_numeric(inp) + expected = transform(idx.asi8) + assert_equal(result, expected) + + +@pytest.mark.parametrize( + "errors,expected", + [ + ("raise", "Invalid object type at position 0"), + ("ignore", Series([[10.0, 2], 1.0, "apple"])), + ("coerce", Series([np.nan, 1.0, np.nan])), + ], +) +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_non_hashable(errors, expected): + # see gh-13324 + ser = Series([[10.0, 2], 1.0, "apple"]) + + if isinstance(expected, str): + with pytest.raises(TypeError, match=expected): + to_numeric(ser, errors=errors) + else: + result = to_numeric(ser, errors=errors) + tm.assert_series_equal(result, expected) + + +def test_downcast_invalid_cast(): + # see gh-13352 + data = ["1", 2, 3] + invalid_downcast = "unsigned-integer" + msg = "invalid downcasting method provided" + + with pytest.raises(ValueError, match=msg): + to_numeric(data, downcast=invalid_downcast) + + +def test_errors_invalid_value(): + # see gh-26466 + data = ["1", 2, 3] + invalid_error_value = "invalid" + msg = "invalid error value specified" + + with pytest.raises(ValueError, match=msg): + to_numeric(data, errors=invalid_error_value) + + +@pytest.mark.parametrize( + "data", + [ + ["1", 2, 3], + [1, 2, 3], + np.array(["1970-01-02", "1970-01-03", "1970-01-04"], dtype="datetime64[D]"), + ], +) +@pytest.mark.parametrize( + "kwargs,exp_dtype", + [ + # Basic function tests. + ({}, np.int64), + ({"downcast": None}, np.int64), + # Support below np.float32 is rare and far between. + ({"downcast": "float"}, np.dtype(np.float32).char), + # Basic dtype support. + ({"downcast": "unsigned"}, np.dtype(np.typecodes["UnsignedInteger"][0])), + ], +) +def test_downcast_basic(data, kwargs, exp_dtype): + # see gh-13352 + result = to_numeric(data, **kwargs) + expected = np.array([1, 2, 3], dtype=exp_dtype) + tm.assert_numpy_array_equal(result, expected) + + +@pytest.mark.parametrize("signed_downcast", ["integer", "signed"]) +@pytest.mark.parametrize( + "data", + [ + ["1", 2, 3], + [1, 2, 3], + np.array(["1970-01-02", "1970-01-03", "1970-01-04"], dtype="datetime64[D]"), + ], +) +def test_signed_downcast(data, signed_downcast): + # see gh-13352 + smallest_int_dtype = np.dtype(np.typecodes["Integer"][0]) + expected = np.array([1, 2, 3], dtype=smallest_int_dtype) + + res = to_numeric(data, downcast=signed_downcast) + tm.assert_numpy_array_equal(res, expected) + + +def test_ignore_downcast_invalid_data(): + # If we can't successfully cast the given + # data to a numeric dtype, do not bother + # with the downcast parameter. + data = ["foo", 2, 3] + expected = np.array(data, dtype=object) + + msg = "errors='ignore' is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + res = to_numeric(data, errors="ignore", downcast="unsigned") + tm.assert_numpy_array_equal(res, expected) + + +def test_ignore_downcast_neg_to_unsigned(): + # Cannot cast to an unsigned integer + # because we have a negative number. + data = ["-1", 2, 3] + expected = np.array([-1, 2, 3], dtype=np.int64) + + res = to_numeric(data, downcast="unsigned") + tm.assert_numpy_array_equal(res, expected) + + +# Warning in 32 bit platforms +@pytest.mark.filterwarnings("ignore:invalid value encountered in cast:RuntimeWarning") +@pytest.mark.parametrize("downcast", ["integer", "signed", "unsigned"]) +@pytest.mark.parametrize( + "data,expected", + [ + (["1.1", 2, 3], np.array([1.1, 2, 3], dtype=np.float64)), + ( + [10000.0, 20000, 3000, 40000.36, 50000, 50000.00], + np.array( + [10000.0, 20000, 3000, 40000.36, 50000, 50000.00], dtype=np.float64 + ), + ), + ], +) +def test_ignore_downcast_cannot_convert_float(data, expected, downcast): + # Cannot cast to an integer (signed or unsigned) + # because we have a float number. + res = to_numeric(data, downcast=downcast) + tm.assert_numpy_array_equal(res, expected) + + +@pytest.mark.parametrize( + "downcast,expected_dtype", + [("integer", np.int16), ("signed", np.int16), ("unsigned", np.uint16)], +) +def test_downcast_not8bit(downcast, expected_dtype): + # the smallest integer dtype need not be np.(u)int8 + data = ["256", 257, 258] + + expected = np.array([256, 257, 258], dtype=expected_dtype) + res = to_numeric(data, downcast=downcast) + tm.assert_numpy_array_equal(res, expected) + + +@pytest.mark.parametrize( + "dtype,downcast,min_max", + [ + ("int8", "integer", [iinfo(np.int8).min, iinfo(np.int8).max]), + ("int16", "integer", [iinfo(np.int16).min, iinfo(np.int16).max]), + ("int32", "integer", [iinfo(np.int32).min, iinfo(np.int32).max]), + ("int64", "integer", [iinfo(np.int64).min, iinfo(np.int64).max]), + ("uint8", "unsigned", [iinfo(np.uint8).min, iinfo(np.uint8).max]), + ("uint16", "unsigned", [iinfo(np.uint16).min, iinfo(np.uint16).max]), + ("uint32", "unsigned", [iinfo(np.uint32).min, iinfo(np.uint32).max]), + ("uint64", "unsigned", [iinfo(np.uint64).min, iinfo(np.uint64).max]), + ("int16", "integer", [iinfo(np.int8).min, iinfo(np.int8).max + 1]), + ("int32", "integer", [iinfo(np.int16).min, iinfo(np.int16).max + 1]), + ("int64", "integer", [iinfo(np.int32).min, iinfo(np.int32).max + 1]), + ("int16", "integer", [iinfo(np.int8).min - 1, iinfo(np.int16).max]), + ("int32", "integer", [iinfo(np.int16).min - 1, iinfo(np.int32).max]), + ("int64", "integer", [iinfo(np.int32).min - 1, iinfo(np.int64).max]), + ("uint16", "unsigned", [iinfo(np.uint8).min, iinfo(np.uint8).max + 1]), + ("uint32", "unsigned", [iinfo(np.uint16).min, iinfo(np.uint16).max + 1]), + ("uint64", "unsigned", [iinfo(np.uint32).min, iinfo(np.uint32).max + 1]), + ], +) +def test_downcast_limits(dtype, downcast, min_max): + # see gh-14404: test the limits of each downcast. + series = to_numeric(Series(min_max), downcast=downcast) + assert series.dtype == dtype + + +def test_downcast_float64_to_float32(): + # GH-43693: Check float64 preservation when >= 16,777,217 + series = Series([16777217.0, np.finfo(np.float64).max, np.nan], dtype=np.float64) + result = to_numeric(series, downcast="float") + + assert series.dtype == result.dtype + + +@pytest.mark.parametrize( + "ser,expected", + [ + ( + Series([0, 9223372036854775808]), + Series([0, 9223372036854775808], dtype=np.uint64), + ) + ], +) +def test_downcast_uint64(ser, expected): + # see gh-14422: + # BUG: to_numeric doesn't work uint64 numbers + + result = to_numeric(ser, downcast="unsigned") + + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "data,exp_data", + [ + ( + [200, 300, "", "NaN", 30000000000000000000], + [200, 300, np.nan, np.nan, 30000000000000000000], + ), + ( + ["12345678901234567890", "1234567890", "ITEM"], + [12345678901234567890, 1234567890, np.nan], + ), + ], +) +def test_coerce_uint64_conflict(data, exp_data): + # see gh-17007 and gh-17125 + # + # Still returns float despite the uint64-nan conflict, + # which would normally force the casting to object. + result = to_numeric(Series(data), errors="coerce") + expected = Series(exp_data, dtype=float) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "errors,exp", + [ + ("ignore", Series(["12345678901234567890", "1234567890", "ITEM"])), + ("raise", "Unable to parse string"), + ], +) +@pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") +def test_non_coerce_uint64_conflict(errors, exp): + # see gh-17007 and gh-17125 + # + # For completeness. + ser = Series(["12345678901234567890", "1234567890", "ITEM"]) + + if isinstance(exp, str): + with pytest.raises(ValueError, match=exp): + to_numeric(ser, errors=errors) + else: + result = to_numeric(ser, errors=errors) + tm.assert_series_equal(result, ser) + + +@pytest.mark.parametrize("dc1", ["integer", "float", "unsigned"]) +@pytest.mark.parametrize("dc2", ["integer", "float", "unsigned"]) +def test_downcast_empty(dc1, dc2): + # GH32493 + + tm.assert_numpy_array_equal( + to_numeric([], downcast=dc1), + to_numeric([], downcast=dc2), + check_dtype=False, + ) + + +def test_failure_to_convert_uint64_string_to_NaN(): + # GH 32394 + result = to_numeric("uint64", errors="coerce") + assert np.isnan(result) + + ser = Series([32, 64, np.nan]) + result = to_numeric(Series(["32", "64", "uint64"]), errors="coerce") + tm.assert_series_equal(result, ser) + + +@pytest.mark.parametrize( + "strrep", + [ + "243.164", + "245.968", + "249.585", + "259.745", + "265.742", + "272.567", + "279.196", + "280.366", + "275.034", + "271.351", + "272.889", + "270.627", + "280.828", + "290.383", + "308.153", + "319.945", + "336.0", + "344.09", + "351.385", + "356.178", + "359.82", + "361.03", + "367.701", + "380.812", + "387.98", + "391.749", + "391.171", + "385.97", + "385.345", + "386.121", + "390.996", + "399.734", + "413.073", + "421.532", + "430.221", + "437.092", + "439.746", + "446.01", + "451.191", + "460.463", + "469.779", + "472.025", + "479.49", + "474.864", + "467.54", + "471.978", + ], +) +def test_precision_float_conversion(strrep): + # GH 31364 + result = to_numeric(strrep) + + assert result == float(strrep) + + +@pytest.mark.parametrize( + "values, expected", + [ + (["1", "2", None], Series([1, 2, np.nan], dtype="Int64")), + (["1", "2", "3"], Series([1, 2, 3], dtype="Int64")), + (["1", "2", 3], Series([1, 2, 3], dtype="Int64")), + (["1", "2", 3.5], Series([1, 2, 3.5], dtype="Float64")), + (["1", None, 3.5], Series([1, np.nan, 3.5], dtype="Float64")), + (["1", "2", "3.5"], Series([1, 2, 3.5], dtype="Float64")), + ], +) +def test_to_numeric_from_nullable_string(values, nullable_string_dtype, expected): + # https://github.com/pandas-dev/pandas/issues/37262 + s = Series(values, dtype=nullable_string_dtype) + result = to_numeric(s) + tm.assert_series_equal(result, expected) + + +def test_to_numeric_from_nullable_string_coerce(nullable_string_dtype): + # GH#52146 + values = ["a", "1"] + ser = Series(values, dtype=nullable_string_dtype) + result = to_numeric(ser, errors="coerce") + expected = Series([pd.NA, 1], dtype="Int64") + tm.assert_series_equal(result, expected) + + +def test_to_numeric_from_nullable_string_ignore(nullable_string_dtype): + # GH#52146 + values = ["a", "1"] + ser = Series(values, dtype=nullable_string_dtype) + expected = ser.copy() + msg = "errors='ignore' is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_numeric(ser, errors="ignore") + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "data, input_dtype, downcast, expected_dtype", + ( + ([1, 1], "Int64", "integer", "Int8"), + ([1.0, pd.NA], "Float64", "integer", "Int8"), + ([1.0, 1.1], "Float64", "integer", "Float64"), + ([1, pd.NA], "Int64", "integer", "Int8"), + ([450, 300], "Int64", "integer", "Int16"), + ([1, 1], "Float64", "integer", "Int8"), + ([np.iinfo(np.int64).max - 1, 1], "Int64", "integer", "Int64"), + ([1, 1], "Int64", "signed", "Int8"), + ([1.0, 1.0], "Float32", "signed", "Int8"), + ([1.0, 1.1], "Float64", "signed", "Float64"), + ([1, pd.NA], "Int64", "signed", "Int8"), + ([450, -300], "Int64", "signed", "Int16"), + ([np.iinfo(np.uint64).max - 1, 1], "UInt64", "signed", "UInt64"), + ([1, 1], "Int64", "unsigned", "UInt8"), + ([1.0, 1.0], "Float32", "unsigned", "UInt8"), + ([1.0, 1.1], "Float64", "unsigned", "Float64"), + ([1, pd.NA], "Int64", "unsigned", "UInt8"), + ([450, -300], "Int64", "unsigned", "Int64"), + ([-1, -1], "Int32", "unsigned", "Int32"), + ([1, 1], "Float64", "float", "Float32"), + ([1, 1.1], "Float64", "float", "Float32"), + ([1, 1], "Float32", "float", "Float32"), + ([1, 1.1], "Float32", "float", "Float32"), + ), +) +def test_downcast_nullable_numeric(data, input_dtype, downcast, expected_dtype): + arr = pd.array(data, dtype=input_dtype) + result = to_numeric(arr, downcast=downcast) + expected = pd.array(data, dtype=expected_dtype) + tm.assert_extension_array_equal(result, expected) + + +def test_downcast_nullable_mask_is_copied(): + # GH38974 + + arr = pd.array([1, 2, pd.NA], dtype="Int64") + + result = to_numeric(arr, downcast="integer") + expected = pd.array([1, 2, pd.NA], dtype="Int8") + tm.assert_extension_array_equal(result, expected) + + arr[1] = pd.NA # should not modify result + tm.assert_extension_array_equal(result, expected) + + +def test_to_numeric_scientific_notation(): + # GH 15898 + result = to_numeric("1.7e+308") + expected = np.float64(1.7e308) + assert result == expected + + +@pytest.mark.parametrize("val", [9876543210.0, 2.0**128]) +def test_to_numeric_large_float_not_downcast_to_float_32(val): + # GH 19729 + expected = Series([val]) + result = to_numeric(expected, downcast="float") + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "val, dtype", [(1, "Int64"), (1.5, "Float64"), (True, "boolean")] +) +def test_to_numeric_dtype_backend(val, dtype): + # GH#50505 + ser = Series([val], dtype=object) + result = to_numeric(ser, dtype_backend="numpy_nullable") + expected = Series([val], dtype=dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "val, dtype", + [ + (1, "Int64"), + (1.5, "Float64"), + (True, "boolean"), + (1, "int64[pyarrow]"), + (1.5, "float64[pyarrow]"), + (True, "bool[pyarrow]"), + ], +) +def test_to_numeric_dtype_backend_na(val, dtype): + # GH#50505 + if "pyarrow" in dtype: + pytest.importorskip("pyarrow") + dtype_backend = "pyarrow" + else: + dtype_backend = "numpy_nullable" + ser = Series([val, None], dtype=object) + result = to_numeric(ser, dtype_backend=dtype_backend) + expected = Series([val, pd.NA], dtype=dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "val, dtype, downcast", + [ + (1, "Int8", "integer"), + (1.5, "Float32", "float"), + (1, "Int8", "signed"), + (1, "int8[pyarrow]", "integer"), + (1.5, "float[pyarrow]", "float"), + (1, "int8[pyarrow]", "signed"), + ], +) +def test_to_numeric_dtype_backend_downcasting(val, dtype, downcast): + # GH#50505 + if "pyarrow" in dtype: + pytest.importorskip("pyarrow") + dtype_backend = "pyarrow" + else: + dtype_backend = "numpy_nullable" + ser = Series([val, None], dtype=object) + result = to_numeric(ser, dtype_backend=dtype_backend, downcast=downcast) + expected = Series([val, pd.NA], dtype=dtype) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "smaller, dtype_backend", + [["UInt8", "numpy_nullable"], ["uint8[pyarrow]", "pyarrow"]], +) +def test_to_numeric_dtype_backend_downcasting_uint(smaller, dtype_backend): + # GH#50505 + if dtype_backend == "pyarrow": + pytest.importorskip("pyarrow") + ser = Series([1, pd.NA], dtype="UInt64") + result = to_numeric(ser, dtype_backend=dtype_backend, downcast="unsigned") + expected = Series([1, pd.NA], dtype=smaller) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "dtype", + [ + "Int64", + "UInt64", + "Float64", + "boolean", + "int64[pyarrow]", + "uint64[pyarrow]", + "float64[pyarrow]", + "bool[pyarrow]", + ], +) +def test_to_numeric_dtype_backend_already_nullable(dtype): + # GH#50505 + if "pyarrow" in dtype: + pytest.importorskip("pyarrow") + ser = Series([1, pd.NA], dtype=dtype) + result = to_numeric(ser, dtype_backend="numpy_nullable") + expected = Series([1, pd.NA], dtype=dtype) + tm.assert_series_equal(result, expected) + + +def test_to_numeric_dtype_backend_error(dtype_backend): + # GH#50505 + ser = Series(["a", "b", ""]) + expected = ser.copy() + with pytest.raises(ValueError, match="Unable to parse string"): + to_numeric(ser, dtype_backend=dtype_backend) + + msg = "errors='ignore' is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_numeric(ser, dtype_backend=dtype_backend, errors="ignore") + tm.assert_series_equal(result, expected) + + result = to_numeric(ser, dtype_backend=dtype_backend, errors="coerce") + if dtype_backend == "pyarrow": + dtype = "double[pyarrow]" + else: + dtype = "Float64" + expected = Series([np.nan, np.nan, np.nan], dtype=dtype) + tm.assert_series_equal(result, expected) + + +def test_invalid_dtype_backend(): + ser = Series([1, 2, 3]) + msg = ( + "dtype_backend numpy is invalid, only 'numpy_nullable' and " + "'pyarrow' are allowed." + ) + with pytest.raises(ValueError, match=msg): + to_numeric(ser, dtype_backend="numpy") + + +def test_coerce_pyarrow_backend(): + # GH 52588 + pa = pytest.importorskip("pyarrow") + ser = Series(list("12x"), dtype=ArrowDtype(pa.string())) + result = to_numeric(ser, errors="coerce", dtype_backend="pyarrow") + expected = Series([1, 2, None], dtype=ArrowDtype(pa.int64())) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_time.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_time.py new file mode 100644 index 0000000000000000000000000000000000000000..b673bd9c2ec7168971ae0ed802336e4f03ff63a7 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_time.py @@ -0,0 +1,72 @@ +from datetime import time +import locale + +import numpy as np +import pytest + +from pandas.compat import PY311 + +from pandas import Series +import pandas._testing as tm +from pandas.core.tools.times import to_time + +# The tests marked with this are locale-dependent. +# They pass, except when the machine locale is zh_CN or it_IT. +fails_on_non_english = pytest.mark.xfail( + locale.getlocale()[0] in ("zh_CN", "it_IT"), + reason="fail on a CI build with LC_ALL=zh_CN.utf8/it_IT.utf8", + strict=False, +) + + +class TestToTime: + @pytest.mark.parametrize( + "time_string", + [ + "14:15", + "1415", + pytest.param("2:15pm", marks=fails_on_non_english), + pytest.param("0215pm", marks=fails_on_non_english), + "14:15:00", + "141500", + pytest.param("2:15:00pm", marks=fails_on_non_english), + pytest.param("021500pm", marks=fails_on_non_english), + time(14, 15), + ], + ) + def test_parsers_time(self, time_string): + # GH#11818 + assert to_time(time_string) == time(14, 15) + + def test_odd_format(self): + new_string = "14.15" + msg = r"Cannot convert arg \['14\.15'\] to a time" + if not PY311: + with pytest.raises(ValueError, match=msg): + to_time(new_string) + assert to_time(new_string, format="%H.%M") == time(14, 15) + + def test_arraylike(self): + arg = ["14:15", "20:20"] + expected_arr = [time(14, 15), time(20, 20)] + assert to_time(arg) == expected_arr + assert to_time(arg, format="%H:%M") == expected_arr + assert to_time(arg, infer_time_format=True) == expected_arr + assert to_time(arg, format="%I:%M%p", errors="coerce") == [None, None] + + msg = "errors='ignore' is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + res = to_time(arg, format="%I:%M%p", errors="ignore") + tm.assert_numpy_array_equal(res, np.array(arg, dtype=np.object_)) + + msg = "Cannot convert.+to a time with given format" + with pytest.raises(ValueError, match=msg): + to_time(arg, format="%I:%M%p", errors="raise") + + tm.assert_series_equal( + to_time(Series(arg, name="test")), Series(expected_arr, name="test") + ) + + res = to_time(np.array(arg)) + assert isinstance(res, list) + assert res == expected_arr diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_timedelta.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_timedelta.py new file mode 100644 index 0000000000000000000000000000000000000000..b67694f1c58c7016221ed629358e8867b2a1534a --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tools/test_to_timedelta.py @@ -0,0 +1,340 @@ +from datetime import ( + time, + timedelta, +) + +import numpy as np +import pytest + +from pandas.compat import IS64 +from pandas.errors import OutOfBoundsTimedelta + +import pandas as pd +from pandas import ( + Series, + TimedeltaIndex, + isna, + to_timedelta, +) +import pandas._testing as tm +from pandas.core.arrays import TimedeltaArray + + +class TestTimedeltas: + def test_to_timedelta_dt64_raises(self): + # Passing datetime64-dtype data to TimedeltaIndex is no longer + # supported GH#29794 + msg = r"dtype datetime64\[ns\] cannot be converted to timedelta64\[ns\]" + + ser = Series([pd.NaT]) + with pytest.raises(TypeError, match=msg): + to_timedelta(ser) + with pytest.raises(TypeError, match=msg): + ser.to_frame().apply(to_timedelta) + + @pytest.mark.parametrize("readonly", [True, False]) + def test_to_timedelta_readonly(self, readonly): + # GH#34857 + arr = np.array([], dtype=object) + if readonly: + arr.setflags(write=False) + result = to_timedelta(arr) + expected = to_timedelta([]) + tm.assert_index_equal(result, expected) + + def test_to_timedelta_null(self): + result = to_timedelta(["", ""]) + assert isna(result).all() + + def test_to_timedelta_same_np_timedelta64(self): + # pass thru + result = to_timedelta(np.array([np.timedelta64(1, "s")])) + expected = pd.Index(np.array([np.timedelta64(1, "s")])) + tm.assert_index_equal(result, expected) + + def test_to_timedelta_series(self): + # Series + expected = Series([timedelta(days=1), timedelta(days=1, seconds=1)]) + result = to_timedelta(Series(["1d", "1days 00:00:01"])) + tm.assert_series_equal(result, expected) + + def test_to_timedelta_units(self): + # with units + result = TimedeltaIndex( + [np.timedelta64(0, "ns"), np.timedelta64(10, "s").astype("m8[ns]")] + ) + expected = to_timedelta([0, 10], unit="s") + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + "dtype, unit", + [ + ["int64", "s"], + ["int64", "m"], + ["int64", "h"], + ["timedelta64[s]", "s"], + ["timedelta64[D]", "D"], + ], + ) + def test_to_timedelta_units_dtypes(self, dtype, unit): + # arrays of various dtypes + arr = np.array([1] * 5, dtype=dtype) + result = to_timedelta(arr, unit=unit) + exp_dtype = "m8[ns]" if dtype == "int64" else "m8[s]" + expected = TimedeltaIndex([np.timedelta64(1, unit)] * 5, dtype=exp_dtype) + tm.assert_index_equal(result, expected) + + def test_to_timedelta_oob_non_nano(self): + arr = np.array([pd.NaT._value + 1], dtype="timedelta64[m]") + + msg = ( + "Cannot convert -9223372036854775807 minutes to " + r"timedelta64\[s\] without overflow" + ) + with pytest.raises(OutOfBoundsTimedelta, match=msg): + to_timedelta(arr) + + with pytest.raises(OutOfBoundsTimedelta, match=msg): + TimedeltaIndex(arr) + + with pytest.raises(OutOfBoundsTimedelta, match=msg): + TimedeltaArray._from_sequence(arr, dtype="m8[s]") + + @pytest.mark.parametrize( + "arg", [np.arange(10).reshape(2, 5), pd.DataFrame(np.arange(10).reshape(2, 5))] + ) + @pytest.mark.parametrize("errors", ["ignore", "raise", "coerce"]) + @pytest.mark.filterwarnings("ignore:errors='ignore' is deprecated:FutureWarning") + def test_to_timedelta_dataframe(self, arg, errors): + # GH 11776 + with pytest.raises(TypeError, match="1-d array"): + to_timedelta(arg, errors=errors) + + def test_to_timedelta_invalid_errors(self): + # bad value for errors parameter + msg = "errors must be one of" + with pytest.raises(ValueError, match=msg): + to_timedelta(["foo"], errors="never") + + @pytest.mark.parametrize("arg", [[1, 2], 1]) + def test_to_timedelta_invalid_unit(self, arg): + # these will error + msg = "invalid unit abbreviation: foo" + with pytest.raises(ValueError, match=msg): + to_timedelta(arg, unit="foo") + + def test_to_timedelta_time(self): + # time not supported ATM + msg = ( + "Value must be Timedelta, string, integer, float, timedelta or convertible" + ) + with pytest.raises(ValueError, match=msg): + to_timedelta(time(second=1)) + assert to_timedelta(time(second=1), errors="coerce") is pd.NaT + + def test_to_timedelta_bad_value(self): + msg = "Could not convert 'foo' to NumPy timedelta" + with pytest.raises(ValueError, match=msg): + to_timedelta(["foo", "bar"]) + + def test_to_timedelta_bad_value_coerce(self): + tm.assert_index_equal( + TimedeltaIndex([pd.NaT, pd.NaT]), + to_timedelta(["foo", "bar"], errors="coerce"), + ) + + tm.assert_index_equal( + TimedeltaIndex(["1 day", pd.NaT, "1 min"]), + to_timedelta(["1 day", "bar", "1 min"], errors="coerce"), + ) + + def test_to_timedelta_invalid_errors_ignore(self): + # gh-13613: these should not error because errors='ignore' + msg = "errors='ignore' is deprecated" + invalid_data = "apple" + + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_timedelta(invalid_data, errors="ignore") + assert invalid_data == result + + invalid_data = ["apple", "1 days"] + expected = np.array(invalid_data, dtype=object) + + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_timedelta(invalid_data, errors="ignore") + tm.assert_numpy_array_equal(expected, result) + + invalid_data = pd.Index(["apple", "1 days"]) + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_timedelta(invalid_data, errors="ignore") + tm.assert_index_equal(invalid_data, result) + + invalid_data = Series(["apple", "1 days"]) + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_timedelta(invalid_data, errors="ignore") + tm.assert_series_equal(invalid_data, result) + + @pytest.mark.parametrize( + "val, errors", + [ + ("1M", True), + ("1 M", True), + ("1Y", True), + ("1 Y", True), + ("1y", True), + ("1 y", True), + ("1m", False), + ("1 m", False), + ("1 day", False), + ("2day", False), + ], + ) + def test_unambiguous_timedelta_values(self, val, errors): + # GH36666 Deprecate use of strings denoting units with 'M', 'Y', 'm' or 'y' + # in pd.to_timedelta + msg = "Units 'M', 'Y' and 'y' do not represent unambiguous timedelta" + if errors: + with pytest.raises(ValueError, match=msg): + to_timedelta(val) + else: + # check it doesn't raise + to_timedelta(val) + + def test_to_timedelta_via_apply(self): + # GH 5458 + expected = Series([np.timedelta64(1, "s")]) + result = Series(["00:00:01"]).apply(to_timedelta) + tm.assert_series_equal(result, expected) + + result = Series([to_timedelta("00:00:01")]) + tm.assert_series_equal(result, expected) + + def test_to_timedelta_inference_without_warning(self): + # GH#41731 inference produces a warning in the Series constructor, + # but _not_ in to_timedelta + vals = ["00:00:01", pd.NaT] + with tm.assert_produces_warning(None): + result = to_timedelta(vals) + + expected = TimedeltaIndex([pd.Timedelta(seconds=1), pd.NaT]) + tm.assert_index_equal(result, expected) + + def test_to_timedelta_on_missing_values(self): + # GH5438 + timedelta_NaT = np.timedelta64("NaT") + + actual = to_timedelta(Series(["00:00:01", np.nan])) + expected = Series( + [np.timedelta64(1000000000, "ns"), timedelta_NaT], + dtype=f"{tm.ENDIAN}m8[ns]", + ) + tm.assert_series_equal(actual, expected) + + ser = Series(["00:00:01", pd.NaT], dtype="m8[ns]") + actual = to_timedelta(ser) + tm.assert_series_equal(actual, expected) + + @pytest.mark.parametrize("val", [np.nan, pd.NaT, pd.NA]) + def test_to_timedelta_on_missing_values_scalar(self, val): + actual = to_timedelta(val) + assert actual._value == np.timedelta64("NaT").astype("int64") + + @pytest.mark.parametrize("val", [np.nan, pd.NaT, pd.NA]) + def test_to_timedelta_on_missing_values_list(self, val): + actual = to_timedelta([val]) + assert actual[0]._value == np.timedelta64("NaT").astype("int64") + + @pytest.mark.xfail(not IS64, reason="Floating point error") + def test_to_timedelta_float(self): + # https://github.com/pandas-dev/pandas/issues/25077 + arr = np.arange(0, 1, 1e-6)[-10:] + result = to_timedelta(arr, unit="s") + expected_asi8 = np.arange(999990000, 10**9, 1000, dtype="int64") + tm.assert_numpy_array_equal(result.asi8, expected_asi8) + + def test_to_timedelta_coerce_strings_unit(self): + arr = np.array([1, 2, "error"], dtype=object) + result = to_timedelta(arr, unit="ns", errors="coerce") + expected = to_timedelta([1, 2, pd.NaT], unit="ns") + tm.assert_index_equal(result, expected) + + def test_to_timedelta_ignore_strings_unit(self): + arr = np.array([1, 2, "error"], dtype=object) + msg = "errors='ignore' is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = to_timedelta(arr, unit="ns", errors="ignore") + tm.assert_numpy_array_equal(result, arr) + + @pytest.mark.parametrize( + "expected_val, result_val", [[timedelta(days=2), 2], [None, None]] + ) + def test_to_timedelta_nullable_int64_dtype(self, expected_val, result_val): + # GH 35574 + expected = Series([timedelta(days=1), expected_val]) + result = to_timedelta(Series([1, result_val], dtype="Int64"), unit="days") + + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + ("input", "expected"), + [ + ("8:53:08.71800000001", "8:53:08.718"), + ("8:53:08.718001", "8:53:08.718001"), + ("8:53:08.7180000001", "8:53:08.7180000001"), + ("-8:53:08.71800000001", "-8:53:08.718"), + ("8:53:08.7180000089", "8:53:08.718000008"), + ], + ) + @pytest.mark.parametrize("func", [pd.Timedelta, to_timedelta]) + def test_to_timedelta_precision_over_nanos(self, input, expected, func): + # GH: 36738 + expected = pd.Timedelta(expected) + result = func(input) + assert result == expected + + def test_to_timedelta_zerodim(self, fixed_now_ts): + # ndarray.item() incorrectly returns int for dt64[ns] and td64[ns] + dt64 = fixed_now_ts.to_datetime64() + arg = np.array(dt64) + + msg = ( + "Value must be Timedelta, string, integer, float, timedelta " + "or convertible, not datetime64" + ) + with pytest.raises(ValueError, match=msg): + to_timedelta(arg) + + arg2 = arg.view("m8[ns]") + result = to_timedelta(arg2) + assert isinstance(result, pd.Timedelta) + assert result._value == dt64.view("i8") + + def test_to_timedelta_numeric_ea(self, any_numeric_ea_dtype): + # GH#48796 + ser = Series([1, pd.NA], dtype=any_numeric_ea_dtype) + result = to_timedelta(ser) + expected = Series([pd.Timedelta(1, unit="ns"), pd.NaT]) + tm.assert_series_equal(result, expected) + + def test_to_timedelta_fraction(self): + result = to_timedelta(1.0 / 3, unit="h") + expected = pd.Timedelta("0 days 00:19:59.999999998") + assert result == expected + + +def test_from_numeric_arrow_dtype(any_numeric_ea_dtype): + # GH 52425 + pytest.importorskip("pyarrow") + ser = Series([1, 2], dtype=f"{any_numeric_ea_dtype.lower()}[pyarrow]") + result = to_timedelta(ser) + expected = Series([1, 2], dtype="timedelta64[ns]") + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("unit", ["ns", "ms"]) +def test_from_timedelta_arrow_dtype(unit): + # GH 54298 + pytest.importorskip("pyarrow") + expected = Series([timedelta(1)], dtype=f"duration[{unit}][pyarrow]") + result = to_timedelta(expected) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_freq_code.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_freq_code.py new file mode 100644 index 0000000000000000000000000000000000000000..16b7190753ee2c5beaa1179b8318732f546f9bf6 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_freq_code.py @@ -0,0 +1,69 @@ +import numpy as np +import pytest + +from pandas._libs.tslibs import ( + Period, + to_offset, +) + + +@pytest.mark.parametrize( + "freqstr,exp_freqstr", + [("D", "D"), ("W", "D"), ("ME", "D"), ("s", "s"), ("min", "s"), ("h", "s")], +) +def test_get_to_timestamp_base(freqstr, exp_freqstr): + off = to_offset(freqstr) + per = Period._from_ordinal(1, off) + exp_code = to_offset(exp_freqstr)._period_dtype_code + + result_code = per._dtype._get_to_timestamp_base() + assert result_code == exp_code + + +@pytest.mark.parametrize( + "args,expected", + [ + ((1.5, "min"), (90, "s")), + ((62.4, "min"), (3744, "s")), + ((1.04, "h"), (3744, "s")), + ((1, "D"), (1, "D")), + ((0.342931, "h"), (1234551600, "us")), + ((1.2345, "D"), (106660800, "ms")), + ], +) +def test_resolution_bumping(args, expected): + # see gh-14378 + off = to_offset(str(args[0]) + args[1]) + assert off.n == expected[0] + assert off._prefix == expected[1] + + +@pytest.mark.parametrize( + "args", + [ + (0.5, "ns"), + # Too much precision in the input can prevent. + (0.3429324798798269273987982, "h"), + ], +) +def test_cat(args): + msg = "Invalid frequency" + + with pytest.raises(ValueError, match=msg): + to_offset(str(args[0]) + args[1]) + + +@pytest.mark.parametrize( + "freqstr,expected", + [ + ("1h", "2021-01-01T09:00:00"), + ("1D", "2021-01-02T08:00:00"), + ("1W", "2021-01-03T08:00:00"), + ("1ME", "2021-01-31T08:00:00"), + ("1YE", "2021-12-31T08:00:00"), + ], +) +def test_compatibility(freqstr, expected): + ts_np = np.datetime64("2021-01-01T08:00:00.00") + do = to_offset(freqstr) + assert ts_np + do == np.datetime64(expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_frequencies.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_frequencies.py new file mode 100644 index 0000000000000000000000000000000000000000..f0af290b2fb69d57b448898e9a9d8635e529e7bc --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_frequencies.py @@ -0,0 +1,29 @@ +import pytest + +from pandas._libs.tslibs import offsets + +from pandas.tseries.frequencies import ( + is_subperiod, + is_superperiod, +) + + +@pytest.mark.parametrize( + "p1,p2,expected", + [ + # Input validation. + (offsets.MonthEnd(), None, False), + (offsets.YearEnd(), None, False), + (None, offsets.YearEnd(), False), + (None, offsets.MonthEnd(), False), + (None, None, False), + (offsets.YearEnd(), offsets.MonthEnd(), True), + (offsets.Hour(), offsets.Minute(), True), + (offsets.Second(), offsets.Milli(), True), + (offsets.Milli(), offsets.Micro(), True), + (offsets.Micro(), offsets.Nano(), True), + ], +) +def test_super_sub_symmetry(p1, p2, expected): + assert is_superperiod(p1, p2) is expected + assert is_subperiod(p2, p1) is expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_inference.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_inference.py new file mode 100644 index 0000000000000000000000000000000000000000..99a504f4188c16718587b70634736dce08bfd444 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/frequencies/test_inference.py @@ -0,0 +1,558 @@ +from datetime import ( + datetime, + timedelta, +) + +import numpy as np +import pytest + +from pandas._libs.tslibs.ccalendar import ( + DAYS, + MONTHS, +) +from pandas._libs.tslibs.offsets import _get_offset +from pandas._libs.tslibs.period import INVALID_FREQ_ERR_MSG +from pandas.compat import is_platform_windows + +from pandas import ( + DatetimeIndex, + Index, + RangeIndex, + Series, + Timestamp, + date_range, + period_range, +) +import pandas._testing as tm +from pandas.core.arrays import ( + DatetimeArray, + TimedeltaArray, +) +from pandas.core.tools.datetimes import to_datetime + +from pandas.tseries import ( + frequencies, + offsets, +) + + +@pytest.fixture( + params=[ + (timedelta(1), "D"), + (timedelta(hours=1), "h"), + (timedelta(minutes=1), "min"), + (timedelta(seconds=1), "s"), + (np.timedelta64(1, "ns"), "ns"), + (timedelta(microseconds=1), "us"), + (timedelta(microseconds=1000), "ms"), + ] +) +def base_delta_code_pair(request): + return request.param + + +freqs = ( + [f"QE-{month}" for month in MONTHS] + + [f"{annual}-{month}" for annual in ["YE", "BYE"] for month in MONTHS] + + ["ME", "BME", "BMS"] + + [f"WOM-{count}{day}" for count in range(1, 5) for day in DAYS] + + [f"W-{day}" for day in DAYS] +) + + +@pytest.mark.parametrize("freq", freqs) +@pytest.mark.parametrize("periods", [5, 7]) +def test_infer_freq_range(periods, freq): + freq = freq.upper() + + gen = date_range("1/1/2000", periods=periods, freq=freq) + index = DatetimeIndex(gen.values) + + if not freq.startswith("QE-"): + assert frequencies.infer_freq(index) == gen.freqstr + else: + inf_freq = frequencies.infer_freq(index) + is_dec_range = inf_freq == "QE-DEC" and gen.freqstr in ( + "QE", + "QE-DEC", + "QE-SEP", + "QE-JUN", + "QE-MAR", + ) + is_nov_range = inf_freq == "QE-NOV" and gen.freqstr in ( + "QE-NOV", + "QE-AUG", + "QE-MAY", + "QE-FEB", + ) + is_oct_range = inf_freq == "QE-OCT" and gen.freqstr in ( + "QE-OCT", + "QE-JUL", + "QE-APR", + "QE-JAN", + ) + assert is_dec_range or is_nov_range or is_oct_range + + +def test_raise_if_period_index(): + index = period_range(start="1/1/1990", periods=20, freq="M") + msg = "Check the `freq` attribute instead of using infer_freq" + + with pytest.raises(TypeError, match=msg): + frequencies.infer_freq(index) + + +def test_raise_if_too_few(): + index = DatetimeIndex(["12/31/1998", "1/3/1999"]) + msg = "Need at least 3 dates to infer frequency" + + with pytest.raises(ValueError, match=msg): + frequencies.infer_freq(index) + + +def test_business_daily(): + index = DatetimeIndex(["01/01/1999", "1/4/1999", "1/5/1999"]) + assert frequencies.infer_freq(index) == "B" + + +def test_business_daily_look_alike(): + # see gh-16624 + # + # Do not infer "B when "weekend" (2-day gap) in wrong place. + index = DatetimeIndex(["12/31/1998", "1/3/1999", "1/4/1999"]) + assert frequencies.infer_freq(index) is None + + +def test_day_corner(): + index = DatetimeIndex(["1/1/2000", "1/2/2000", "1/3/2000"]) + assert frequencies.infer_freq(index) == "D" + + +def test_non_datetime_index(): + dates = to_datetime(["1/1/2000", "1/2/2000", "1/3/2000"]) + assert frequencies.infer_freq(dates) == "D" + + +def test_fifth_week_of_month_infer(): + # see gh-9425 + # + # Only attempt to infer up to WOM-4. + index = DatetimeIndex(["2014-03-31", "2014-06-30", "2015-03-30"]) + assert frequencies.infer_freq(index) is None + + +def test_week_of_month_fake(): + # All of these dates are on same day + # of week and are 4 or 5 weeks apart. + index = DatetimeIndex(["2013-08-27", "2013-10-01", "2013-10-29", "2013-11-26"]) + assert frequencies.infer_freq(index) != "WOM-4TUE" + + +def test_fifth_week_of_month(): + # see gh-9425 + # + # Only supports freq up to WOM-4. + msg = ( + "Of the four parameters: start, end, periods, " + "and freq, exactly three must be specified" + ) + + with pytest.raises(ValueError, match=msg): + date_range("2014-01-01", freq="WOM-5MON") + + +def test_monthly_ambiguous(): + rng = DatetimeIndex(["1/31/2000", "2/29/2000", "3/31/2000"]) + assert rng.inferred_freq == "ME" + + +def test_annual_ambiguous(): + rng = DatetimeIndex(["1/31/2000", "1/31/2001", "1/31/2002"]) + assert rng.inferred_freq == "YE-JAN" + + +@pytest.mark.parametrize("count", range(1, 5)) +def test_infer_freq_delta(base_delta_code_pair, count): + b = Timestamp(datetime.now()) + base_delta, code = base_delta_code_pair + + inc = base_delta * count + index = DatetimeIndex([b + inc * j for j in range(3)]) + + exp_freq = f"{count:d}{code}" if count > 1 else code + assert frequencies.infer_freq(index) == exp_freq + + +@pytest.mark.parametrize( + "constructor", + [ + lambda now, delta: DatetimeIndex( + [now + delta * 7] + [now + delta * j for j in range(3)] + ), + lambda now, delta: DatetimeIndex( + [now + delta * j for j in range(3)] + [now + delta * 7] + ), + ], +) +def test_infer_freq_custom(base_delta_code_pair, constructor): + b = Timestamp(datetime.now()) + base_delta, _ = base_delta_code_pair + + index = constructor(b, base_delta) + assert frequencies.infer_freq(index) is None + + +@pytest.mark.parametrize( + "freq,expected", [("Q", "QE-DEC"), ("Q-NOV", "QE-NOV"), ("Q-OCT", "QE-OCT")] +) +def test_infer_freq_index(freq, expected): + rng = period_range("1959Q2", "2009Q3", freq=freq) + with tm.assert_produces_warning(FutureWarning, match="Dtype inference"): + rng = Index(rng.to_timestamp("D", how="e").astype(object)) + + assert rng.inferred_freq == expected + + +@pytest.mark.parametrize( + "expected,dates", + list( + { + "YS-JAN": ["2009-01-01", "2010-01-01", "2011-01-01", "2012-01-01"], + "QE-OCT": ["2009-01-31", "2009-04-30", "2009-07-31", "2009-10-31"], + "ME": ["2010-11-30", "2010-12-31", "2011-01-31", "2011-02-28"], + "W-SAT": ["2010-12-25", "2011-01-01", "2011-01-08", "2011-01-15"], + "D": ["2011-01-01", "2011-01-02", "2011-01-03", "2011-01-04"], + "h": [ + "2011-12-31 22:00", + "2011-12-31 23:00", + "2012-01-01 00:00", + "2012-01-01 01:00", + ], + }.items() + ), +) +@pytest.mark.parametrize("unit", ["s", "ms", "us", "ns"]) +def test_infer_freq_tz(tz_naive_fixture, expected, dates, unit): + # see gh-7310, GH#55609 + tz = tz_naive_fixture + idx = DatetimeIndex(dates, tz=tz).as_unit(unit) + assert idx.inferred_freq == expected + + +def test_infer_freq_tz_series(tz_naive_fixture): + # infer_freq should work with both tz-naive and tz-aware series. See gh-52456 + tz = tz_naive_fixture + idx = date_range("2021-01-01", "2021-01-04", tz=tz) + series = idx.to_series().reset_index(drop=True) + inferred_freq = frequencies.infer_freq(series) + assert inferred_freq == "D" + + +@pytest.mark.parametrize( + "date_pair", + [ + ["2013-11-02", "2013-11-5"], # Fall DST + ["2014-03-08", "2014-03-11"], # Spring DST + ["2014-01-01", "2014-01-03"], # Regular Time + ], +) +@pytest.mark.parametrize( + "freq", + ["h", "3h", "10min", "3601s", "3600001ms", "3600000001us", "3600000000001ns"], +) +def test_infer_freq_tz_transition(tz_naive_fixture, date_pair, freq): + # see gh-8772 + tz = tz_naive_fixture + idx = date_range(date_pair[0], date_pair[1], freq=freq, tz=tz) + assert idx.inferred_freq == freq + + +def test_infer_freq_tz_transition_custom(): + index = date_range("2013-11-03", periods=5, freq="3h").tz_localize( + "America/Chicago" + ) + assert index.inferred_freq is None + + +@pytest.mark.parametrize( + "data,expected", + [ + # Hourly freq in a day must result in "h" + ( + [ + "2014-07-01 09:00", + "2014-07-01 10:00", + "2014-07-01 11:00", + "2014-07-01 12:00", + "2014-07-01 13:00", + "2014-07-01 14:00", + ], + "h", + ), + ( + [ + "2014-07-01 09:00", + "2014-07-01 10:00", + "2014-07-01 11:00", + "2014-07-01 12:00", + "2014-07-01 13:00", + "2014-07-01 14:00", + "2014-07-01 15:00", + "2014-07-01 16:00", + "2014-07-02 09:00", + "2014-07-02 10:00", + "2014-07-02 11:00", + ], + "bh", + ), + ( + [ + "2014-07-04 09:00", + "2014-07-04 10:00", + "2014-07-04 11:00", + "2014-07-04 12:00", + "2014-07-04 13:00", + "2014-07-04 14:00", + "2014-07-04 15:00", + "2014-07-04 16:00", + "2014-07-07 09:00", + "2014-07-07 10:00", + "2014-07-07 11:00", + ], + "bh", + ), + ( + [ + "2014-07-04 09:00", + "2014-07-04 10:00", + "2014-07-04 11:00", + "2014-07-04 12:00", + "2014-07-04 13:00", + "2014-07-04 14:00", + "2014-07-04 15:00", + "2014-07-04 16:00", + "2014-07-07 09:00", + "2014-07-07 10:00", + "2014-07-07 11:00", + "2014-07-07 12:00", + "2014-07-07 13:00", + "2014-07-07 14:00", + "2014-07-07 15:00", + "2014-07-07 16:00", + "2014-07-08 09:00", + "2014-07-08 10:00", + "2014-07-08 11:00", + "2014-07-08 12:00", + "2014-07-08 13:00", + "2014-07-08 14:00", + "2014-07-08 15:00", + "2014-07-08 16:00", + ], + "bh", + ), + ], +) +def test_infer_freq_business_hour(data, expected): + # see gh-7905 + idx = DatetimeIndex(data) + assert idx.inferred_freq == expected + + +def test_not_monotonic(): + rng = DatetimeIndex(["1/31/2000", "1/31/2001", "1/31/2002"]) + rng = rng[::-1] + + assert rng.inferred_freq == "-1YE-JAN" + + +def test_non_datetime_index2(): + rng = DatetimeIndex(["1/31/2000", "1/31/2001", "1/31/2002"]) + vals = rng.to_pydatetime() + + result = frequencies.infer_freq(vals) + assert result == rng.inferred_freq + + +@pytest.mark.parametrize( + "idx", + [ + Index(np.arange(5), dtype=np.int64), + Index(np.arange(5), dtype=np.float64), + period_range("2020-01-01", periods=5), + RangeIndex(5), + ], +) +def test_invalid_index_types(idx): + # see gh-48439 + msg = "|".join( + [ + "cannot infer freq from a non-convertible", + "Check the `freq` attribute instead of using infer_freq", + ] + ) + + with pytest.raises(TypeError, match=msg): + frequencies.infer_freq(idx) + + +@pytest.mark.skipif(is_platform_windows(), reason="see gh-10822: Windows issue") +def test_invalid_index_types_unicode(): + # see gh-10822 + # + # Odd error message on conversions to datetime for unicode. + msg = "Unknown datetime string format" + + with pytest.raises(ValueError, match=msg): + frequencies.infer_freq(Index(["ZqgszYBfuL"])) + + +def test_string_datetime_like_compat(): + # see gh-6463 + data = ["2004-01", "2004-02", "2004-03", "2004-04"] + + expected = frequencies.infer_freq(data) + result = frequencies.infer_freq(Index(data)) + + assert result == expected + + +def test_series(): + # see gh-6407 + s = Series(date_range("20130101", "20130110")) + inferred = frequencies.infer_freq(s) + assert inferred == "D" + + +@pytest.mark.parametrize("end", [10, 10.0]) +def test_series_invalid_type(end): + # see gh-6407 + msg = "cannot infer freq from a non-convertible dtype on a Series" + s = Series(np.arange(end)) + + with pytest.raises(TypeError, match=msg): + frequencies.infer_freq(s) + + +def test_series_inconvertible_string(using_infer_string): + # see gh-6407 + if using_infer_string: + msg = "cannot infer freq from" + + with pytest.raises(TypeError, match=msg): + frequencies.infer_freq(Series(["foo", "bar"])) + else: + msg = "Unknown datetime string format" + + with pytest.raises(ValueError, match=msg): + frequencies.infer_freq(Series(["foo", "bar"])) + + +@pytest.mark.parametrize("freq", [None, "ms"]) +def test_series_period_index(freq): + # see gh-6407 + # + # Cannot infer on PeriodIndex + msg = "cannot infer freq from a non-convertible dtype on a Series" + s = Series(period_range("2013", periods=10, freq=freq)) + + with pytest.raises(TypeError, match=msg): + frequencies.infer_freq(s) + + +@pytest.mark.parametrize("freq", ["ME", "ms", "s"]) +def test_series_datetime_index(freq): + s = Series(date_range("20130101", periods=10, freq=freq)) + inferred = frequencies.infer_freq(s) + assert inferred == freq + + +@pytest.mark.parametrize( + "offset_func", + [ + _get_offset, + lambda freq: date_range("2011-01-01", periods=5, freq=freq), + ], +) +@pytest.mark.parametrize( + "freq", + [ + "WEEKDAY", + "EOM", + "W@MON", + "W@TUE", + "W@WED", + "W@THU", + "W@FRI", + "W@SAT", + "W@SUN", + "QE@JAN", + "QE@FEB", + "QE@MAR", + "YE@JAN", + "YE@FEB", + "YE@MAR", + "YE@APR", + "YE@MAY", + "YE@JUN", + "YE@JUL", + "YE@AUG", + "YE@SEP", + "YE@OCT", + "YE@NOV", + "YE@DEC", + "YE@JAN", + "WOM@1MON", + "WOM@2MON", + "WOM@3MON", + "WOM@4MON", + "WOM@1TUE", + "WOM@2TUE", + "WOM@3TUE", + "WOM@4TUE", + "WOM@1WED", + "WOM@2WED", + "WOM@3WED", + "WOM@4WED", + "WOM@1THU", + "WOM@2THU", + "WOM@3THU", + "WOM@4THU", + "WOM@1FRI", + "WOM@2FRI", + "WOM@3FRI", + "WOM@4FRI", + ], +) +def test_legacy_offset_warnings(offset_func, freq): + with pytest.raises(ValueError, match=INVALID_FREQ_ERR_MSG): + offset_func(freq) + + +def test_ms_vs_capital_ms(): + left = _get_offset("ms") + right = _get_offset("MS") + + assert left == offsets.Milli() + assert right == offsets.MonthBegin() + + +def test_infer_freq_non_nano(): + arr = np.arange(10).astype(np.int64).view("M8[s]") + dta = DatetimeArray._simple_new(arr, dtype=arr.dtype) + res = frequencies.infer_freq(dta) + assert res == "s" + + arr2 = arr.view("m8[ms]") + tda = TimedeltaArray._simple_new(arr2, dtype=arr2.dtype) + res2 = frequencies.infer_freq(tda) + assert res2 == "ms" + + +def test_infer_freq_non_nano_tzaware(tz_aware_fixture): + tz = tz_aware_fixture + + dti = date_range("2016-01-01", periods=365, freq="B", tz=tz) + dta = dti._data.as_unit("s") + + res = frequencies.infer_freq(dta) + assert res == "B" diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_calendar.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_calendar.py new file mode 100644 index 0000000000000000000000000000000000000000..99829857e68363ec845dd9dff3d90917c31adaa0 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_calendar.py @@ -0,0 +1,119 @@ +from datetime import datetime + +import pytest + +from pandas import ( + DatetimeIndex, + offsets, + to_datetime, +) +import pandas._testing as tm + +from pandas.tseries.holiday import ( + AbstractHolidayCalendar, + Holiday, + Timestamp, + USFederalHolidayCalendar, + USLaborDay, + USThanksgivingDay, + get_calendar, +) + + +@pytest.mark.parametrize( + "transform", [lambda x: x, lambda x: x.strftime("%Y-%m-%d"), lambda x: Timestamp(x)] +) +def test_calendar(transform): + start_date = datetime(2012, 1, 1) + end_date = datetime(2012, 12, 31) + + calendar = USFederalHolidayCalendar() + holidays = calendar.holidays(transform(start_date), transform(end_date)) + + expected = [ + datetime(2012, 1, 2), + datetime(2012, 1, 16), + datetime(2012, 2, 20), + datetime(2012, 5, 28), + datetime(2012, 7, 4), + datetime(2012, 9, 3), + datetime(2012, 10, 8), + datetime(2012, 11, 12), + datetime(2012, 11, 22), + datetime(2012, 12, 25), + ] + + assert list(holidays.to_pydatetime()) == expected + + +def test_calendar_caching(): + # see gh-9552. + + class TestCalendar(AbstractHolidayCalendar): + def __init__(self, name=None, rules=None) -> None: + super().__init__(name=name, rules=rules) + + jan1 = TestCalendar(rules=[Holiday("jan1", year=2015, month=1, day=1)]) + jan2 = TestCalendar(rules=[Holiday("jan2", year=2015, month=1, day=2)]) + + # Getting holidays for Jan 1 should not alter results for Jan 2. + expected = DatetimeIndex(["01-Jan-2015"]).as_unit("ns") + tm.assert_index_equal(jan1.holidays(), expected) + + expected2 = DatetimeIndex(["02-Jan-2015"]).as_unit("ns") + tm.assert_index_equal(jan2.holidays(), expected2) + + +def test_calendar_observance_dates(): + # see gh-11477 + us_fed_cal = get_calendar("USFederalHolidayCalendar") + holidays0 = us_fed_cal.holidays( + datetime(2015, 7, 3), datetime(2015, 7, 3) + ) # <-- same start and end dates + holidays1 = us_fed_cal.holidays( + datetime(2015, 7, 3), datetime(2015, 7, 6) + ) # <-- different start and end dates + holidays2 = us_fed_cal.holidays( + datetime(2015, 7, 3), datetime(2015, 7, 3) + ) # <-- same start and end dates + + # These should all produce the same result. + # + # In addition, calling with different start and end + # dates should not alter the output if we call the + # function again with the same start and end date. + tm.assert_index_equal(holidays0, holidays1) + tm.assert_index_equal(holidays0, holidays2) + + +def test_rule_from_name(): + us_fed_cal = get_calendar("USFederalHolidayCalendar") + assert us_fed_cal.rule_from_name("Thanksgiving Day") == USThanksgivingDay + + +def test_calendar_2031(): + # See gh-27790 + # + # Labor Day 2031 is on September 1. Saturday before is August 30. + # Next working day after August 30 ought to be Tuesday, September 2. + + class testCalendar(AbstractHolidayCalendar): + rules = [USLaborDay] + + cal = testCalendar() + workDay = offsets.CustomBusinessDay(calendar=cal) + Sat_before_Labor_Day_2031 = to_datetime("2031-08-30") + next_working_day = Sat_before_Labor_Day_2031 + 0 * workDay + assert next_working_day == to_datetime("2031-09-02") + + +def test_no_holidays_calendar(): + # Test for issue #31415 + + class NoHolidaysCalendar(AbstractHolidayCalendar): + pass + + cal = NoHolidaysCalendar() + holidays = cal.holidays(Timestamp("01-Jan-2020"), Timestamp("01-Jan-2021")) + empty_index = DatetimeIndex([]) # Type is DatetimeIndex since return_name=False + tm.assert_index_equal(holidays, empty_index) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_federal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_federal.py new file mode 100644 index 0000000000000000000000000000000000000000..2565877f8a2a44071f96cef0f670c23842a364b6 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_federal.py @@ -0,0 +1,58 @@ +from datetime import datetime + +from pandas import DatetimeIndex +import pandas._testing as tm + +from pandas.tseries.holiday import ( + AbstractHolidayCalendar, + USFederalHolidayCalendar, + USMartinLutherKingJr, + USMemorialDay, +) + + +def test_no_mlk_before_1986(): + # see gh-10278 + class MLKCalendar(AbstractHolidayCalendar): + rules = [USMartinLutherKingJr] + + holidays = MLKCalendar().holidays(start="1984", end="1988").to_pydatetime().tolist() + + # Testing to make sure holiday is not incorrectly observed before 1986. + assert holidays == [datetime(1986, 1, 20, 0, 0), datetime(1987, 1, 19, 0, 0)] + + +def test_memorial_day(): + class MemorialDay(AbstractHolidayCalendar): + rules = [USMemorialDay] + + holidays = MemorialDay().holidays(start="1971", end="1980").to_pydatetime().tolist() + + # Fixes 5/31 error and checked manually against Wikipedia. + assert holidays == [ + datetime(1971, 5, 31, 0, 0), + datetime(1972, 5, 29, 0, 0), + datetime(1973, 5, 28, 0, 0), + datetime(1974, 5, 27, 0, 0), + datetime(1975, 5, 26, 0, 0), + datetime(1976, 5, 31, 0, 0), + datetime(1977, 5, 30, 0, 0), + datetime(1978, 5, 29, 0, 0), + datetime(1979, 5, 28, 0, 0), + ] + + +def test_federal_holiday_inconsistent_returntype(): + # GH 49075 test case + # Instantiate two calendars to rule out _cache + cal1 = USFederalHolidayCalendar() + cal2 = USFederalHolidayCalendar() + + results_2018 = cal1.holidays(start=datetime(2018, 8, 1), end=datetime(2018, 8, 31)) + results_2019 = cal2.holidays(start=datetime(2019, 8, 1), end=datetime(2019, 8, 31)) + expected_results = DatetimeIndex([], dtype="datetime64[ns]", freq=None) + + # Check against expected results to ensure both date + # ranges generate expected results as per GH49075 submission + tm.assert_index_equal(results_2018, expected_results) + tm.assert_index_equal(results_2019, expected_results) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_holiday.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_holiday.py new file mode 100644 index 0000000000000000000000000000000000000000..b2eefd04ef93b159140ae72ae3d96d8adf071719 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_holiday.py @@ -0,0 +1,332 @@ +from datetime import datetime + +import pytest +from pytz import utc + +from pandas import ( + DatetimeIndex, + Series, +) +import pandas._testing as tm + +from pandas.tseries.holiday import ( + MO, + SA, + AbstractHolidayCalendar, + DateOffset, + EasterMonday, + GoodFriday, + Holiday, + HolidayCalendarFactory, + Timestamp, + USColumbusDay, + USFederalHolidayCalendar, + USLaborDay, + USMartinLutherKingJr, + USMemorialDay, + USPresidentsDay, + USThanksgivingDay, + get_calendar, + next_monday, +) + + +@pytest.mark.parametrize( + "holiday,start_date,end_date,expected", + [ + ( + USMemorialDay, + datetime(2011, 1, 1), + datetime(2020, 12, 31), + [ + datetime(2011, 5, 30), + datetime(2012, 5, 28), + datetime(2013, 5, 27), + datetime(2014, 5, 26), + datetime(2015, 5, 25), + datetime(2016, 5, 30), + datetime(2017, 5, 29), + datetime(2018, 5, 28), + datetime(2019, 5, 27), + datetime(2020, 5, 25), + ], + ), + ( + Holiday("July 4th Eve", month=7, day=3), + "2001-01-01", + "2003-03-03", + [Timestamp("2001-07-03 00:00:00"), Timestamp("2002-07-03 00:00:00")], + ), + ( + Holiday("July 4th Eve", month=7, day=3, days_of_week=(0, 1, 2, 3)), + "2001-01-01", + "2008-03-03", + [ + Timestamp("2001-07-03 00:00:00"), + Timestamp("2002-07-03 00:00:00"), + Timestamp("2003-07-03 00:00:00"), + Timestamp("2006-07-03 00:00:00"), + Timestamp("2007-07-03 00:00:00"), + ], + ), + ( + EasterMonday, + datetime(2011, 1, 1), + datetime(2020, 12, 31), + [ + Timestamp("2011-04-25 00:00:00"), + Timestamp("2012-04-09 00:00:00"), + Timestamp("2013-04-01 00:00:00"), + Timestamp("2014-04-21 00:00:00"), + Timestamp("2015-04-06 00:00:00"), + Timestamp("2016-03-28 00:00:00"), + Timestamp("2017-04-17 00:00:00"), + Timestamp("2018-04-02 00:00:00"), + Timestamp("2019-04-22 00:00:00"), + Timestamp("2020-04-13 00:00:00"), + ], + ), + ( + GoodFriday, + datetime(2011, 1, 1), + datetime(2020, 12, 31), + [ + Timestamp("2011-04-22 00:00:00"), + Timestamp("2012-04-06 00:00:00"), + Timestamp("2013-03-29 00:00:00"), + Timestamp("2014-04-18 00:00:00"), + Timestamp("2015-04-03 00:00:00"), + Timestamp("2016-03-25 00:00:00"), + Timestamp("2017-04-14 00:00:00"), + Timestamp("2018-03-30 00:00:00"), + Timestamp("2019-04-19 00:00:00"), + Timestamp("2020-04-10 00:00:00"), + ], + ), + ( + USThanksgivingDay, + datetime(2011, 1, 1), + datetime(2020, 12, 31), + [ + datetime(2011, 11, 24), + datetime(2012, 11, 22), + datetime(2013, 11, 28), + datetime(2014, 11, 27), + datetime(2015, 11, 26), + datetime(2016, 11, 24), + datetime(2017, 11, 23), + datetime(2018, 11, 22), + datetime(2019, 11, 28), + datetime(2020, 11, 26), + ], + ), + ], +) +def test_holiday_dates(holiday, start_date, end_date, expected): + assert list(holiday.dates(start_date, end_date)) == expected + + # Verify that timezone info is preserved. + assert list( + holiday.dates( + utc.localize(Timestamp(start_date)), utc.localize(Timestamp(end_date)) + ) + ) == [utc.localize(dt) for dt in expected] + + +@pytest.mark.parametrize( + "holiday,start,expected", + [ + (USMemorialDay, datetime(2015, 7, 1), []), + (USMemorialDay, "2015-05-25", [Timestamp("2015-05-25")]), + (USLaborDay, datetime(2015, 7, 1), []), + (USLaborDay, "2015-09-07", [Timestamp("2015-09-07")]), + (USColumbusDay, datetime(2015, 7, 1), []), + (USColumbusDay, "2015-10-12", [Timestamp("2015-10-12")]), + (USThanksgivingDay, datetime(2015, 7, 1), []), + (USThanksgivingDay, "2015-11-26", [Timestamp("2015-11-26")]), + (USMartinLutherKingJr, datetime(2015, 7, 1), []), + (USMartinLutherKingJr, "2015-01-19", [Timestamp("2015-01-19")]), + (USPresidentsDay, datetime(2015, 7, 1), []), + (USPresidentsDay, "2015-02-16", [Timestamp("2015-02-16")]), + (GoodFriday, datetime(2015, 7, 1), []), + (GoodFriday, "2015-04-03", [Timestamp("2015-04-03")]), + (EasterMonday, "2015-04-06", [Timestamp("2015-04-06")]), + (EasterMonday, datetime(2015, 7, 1), []), + (EasterMonday, "2015-04-05", []), + ("New Year's Day", "2015-01-01", [Timestamp("2015-01-01")]), + ("New Year's Day", "2010-12-31", [Timestamp("2010-12-31")]), + ("New Year's Day", datetime(2015, 7, 1), []), + ("New Year's Day", "2011-01-01", []), + ("Independence Day", "2015-07-03", [Timestamp("2015-07-03")]), + ("Independence Day", datetime(2015, 7, 1), []), + ("Independence Day", "2015-07-04", []), + ("Veterans Day", "2012-11-12", [Timestamp("2012-11-12")]), + ("Veterans Day", datetime(2015, 7, 1), []), + ("Veterans Day", "2012-11-11", []), + ("Christmas Day", "2011-12-26", [Timestamp("2011-12-26")]), + ("Christmas Day", datetime(2015, 7, 1), []), + ("Christmas Day", "2011-12-25", []), + ("Juneteenth National Independence Day", "2020-06-19", []), + ( + "Juneteenth National Independence Day", + "2021-06-18", + [Timestamp("2021-06-18")], + ), + ("Juneteenth National Independence Day", "2022-06-19", []), + ( + "Juneteenth National Independence Day", + "2022-06-20", + [Timestamp("2022-06-20")], + ), + ], +) +def test_holidays_within_dates(holiday, start, expected): + # see gh-11477 + # + # Fix holiday behavior where holiday.dates returned dates outside + # start/end date, or observed rules could not be applied because the + # holiday was not in the original date range (e.g., 7/4/2015 -> 7/3/2015). + if isinstance(holiday, str): + calendar = get_calendar("USFederalHolidayCalendar") + holiday = calendar.rule_from_name(holiday) + + assert list(holiday.dates(start, start)) == expected + + # Verify that timezone info is preserved. + assert list( + holiday.dates(utc.localize(Timestamp(start)), utc.localize(Timestamp(start))) + ) == [utc.localize(dt) for dt in expected] + + +@pytest.mark.parametrize( + "transform", [lambda x: x.strftime("%Y-%m-%d"), lambda x: Timestamp(x)] +) +def test_argument_types(transform): + start_date = datetime(2011, 1, 1) + end_date = datetime(2020, 12, 31) + + holidays = USThanksgivingDay.dates(start_date, end_date) + holidays2 = USThanksgivingDay.dates(transform(start_date), transform(end_date)) + tm.assert_index_equal(holidays, holidays2) + + +@pytest.mark.parametrize( + "name,kwargs", + [ + ("One-Time", {"year": 2012, "month": 5, "day": 28}), + ( + "Range", + { + "month": 5, + "day": 28, + "start_date": datetime(2012, 1, 1), + "end_date": datetime(2012, 12, 31), + "offset": DateOffset(weekday=MO(1)), + }, + ), + ], +) +def test_special_holidays(name, kwargs): + base_date = [datetime(2012, 5, 28)] + holiday = Holiday(name, **kwargs) + + start_date = datetime(2011, 1, 1) + end_date = datetime(2020, 12, 31) + + assert base_date == holiday.dates(start_date, end_date) + + +def test_get_calendar(): + class TestCalendar(AbstractHolidayCalendar): + rules = [] + + calendar = get_calendar("TestCalendar") + assert TestCalendar == type(calendar) + + +def test_factory(): + class_1 = HolidayCalendarFactory( + "MemorialDay", AbstractHolidayCalendar, USMemorialDay + ) + class_2 = HolidayCalendarFactory( + "Thanksgiving", AbstractHolidayCalendar, USThanksgivingDay + ) + class_3 = HolidayCalendarFactory("Combined", class_1, class_2) + + assert len(class_1.rules) == 1 + assert len(class_2.rules) == 1 + assert len(class_3.rules) == 2 + + +def test_both_offset_observance_raises(): + # see gh-10217 + msg = "Cannot use both offset and observance" + with pytest.raises(NotImplementedError, match=msg): + Holiday( + "Cyber Monday", + month=11, + day=1, + offset=[DateOffset(weekday=SA(4))], + observance=next_monday, + ) + + +def test_half_open_interval_with_observance(): + # Prompted by GH 49075 + # Check for holidays that have a half-open date interval where + # they have either a start_date or end_date defined along + # with a defined observance pattern to make sure that the return type + # for Holiday.dates() remains consistent before & after the year that + # marks the 'edge' of the half-open date interval. + + holiday_1 = Holiday( + "Arbitrary Holiday - start 2022-03-14", + start_date=datetime(2022, 3, 14), + month=3, + day=14, + observance=next_monday, + ) + holiday_2 = Holiday( + "Arbitrary Holiday 2 - end 2022-03-20", + end_date=datetime(2022, 3, 20), + month=3, + day=20, + observance=next_monday, + ) + + class TestHolidayCalendar(AbstractHolidayCalendar): + rules = [ + USMartinLutherKingJr, + holiday_1, + holiday_2, + USLaborDay, + ] + + start = Timestamp("2022-08-01") + end = Timestamp("2022-08-31") + year_offset = DateOffset(years=5) + expected_results = DatetimeIndex([], dtype="datetime64[ns]", freq=None) + test_cal = TestHolidayCalendar() + + date_interval_low = test_cal.holidays(start - year_offset, end - year_offset) + date_window_edge = test_cal.holidays(start, end) + date_interval_high = test_cal.holidays(start + year_offset, end + year_offset) + + tm.assert_index_equal(date_interval_low, expected_results) + tm.assert_index_equal(date_window_edge, expected_results) + tm.assert_index_equal(date_interval_high, expected_results) + + +def test_holidays_with_timezone_specified_but_no_occurences(): + # GH 54580 + # _apply_rule() in holiday.py was silently dropping timezones if you passed it + # an empty list of holiday dates that had timezone information + start_date = Timestamp("2018-01-01", tz="America/Chicago") + end_date = Timestamp("2018-01-11", tz="America/Chicago") + test_case = USFederalHolidayCalendar().holidays( + start_date, end_date, return_name=True + ) + expected_results = Series("New Year's Day", index=[start_date]) + expected_results.index = expected_results.index.as_unit("ns") + + tm.assert_equal(test_case, expected_results) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_observance.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_observance.py new file mode 100644 index 0000000000000000000000000000000000000000..83038ad254b77daee6667bd269a8775016649d39 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/holiday/test_observance.py @@ -0,0 +1,105 @@ +from datetime import datetime + +import pytest + +from pandas.tseries.holiday import ( + after_nearest_workday, + before_nearest_workday, + nearest_workday, + next_monday, + next_monday_or_tuesday, + next_workday, + previous_friday, + previous_workday, + sunday_to_monday, + weekend_to_monday, +) + +_WEDNESDAY = datetime(2014, 4, 9) +_THURSDAY = datetime(2014, 4, 10) +_FRIDAY = datetime(2014, 4, 11) +_SATURDAY = datetime(2014, 4, 12) +_SUNDAY = datetime(2014, 4, 13) +_MONDAY = datetime(2014, 4, 14) +_TUESDAY = datetime(2014, 4, 15) +_NEXT_WEDNESDAY = datetime(2014, 4, 16) + + +@pytest.mark.parametrize("day", [_SATURDAY, _SUNDAY]) +def test_next_monday(day): + assert next_monday(day) == _MONDAY + + +@pytest.mark.parametrize( + "day,expected", [(_SATURDAY, _MONDAY), (_SUNDAY, _TUESDAY), (_MONDAY, _TUESDAY)] +) +def test_next_monday_or_tuesday(day, expected): + assert next_monday_or_tuesday(day) == expected + + +@pytest.mark.parametrize("day", [_SATURDAY, _SUNDAY]) +def test_previous_friday(day): + assert previous_friday(day) == _FRIDAY + + +def test_sunday_to_monday(): + assert sunday_to_monday(_SUNDAY) == _MONDAY + + +@pytest.mark.parametrize( + "day,expected", [(_SATURDAY, _FRIDAY), (_SUNDAY, _MONDAY), (_MONDAY, _MONDAY)] +) +def test_nearest_workday(day, expected): + assert nearest_workday(day) == expected + + +@pytest.mark.parametrize( + "day,expected", [(_SATURDAY, _MONDAY), (_SUNDAY, _MONDAY), (_MONDAY, _MONDAY)] +) +def test_weekend_to_monday(day, expected): + assert weekend_to_monday(day) == expected + + +@pytest.mark.parametrize( + "day,expected", + [ + (_WEDNESDAY, _THURSDAY), + (_THURSDAY, _FRIDAY), + (_SATURDAY, _MONDAY), + (_SUNDAY, _MONDAY), + (_MONDAY, _TUESDAY), + (_TUESDAY, _NEXT_WEDNESDAY), # WED is same week as TUE + ], +) +def test_next_workday(day, expected): + assert next_workday(day) == expected + + +@pytest.mark.parametrize( + "day,expected", [(_SATURDAY, _FRIDAY), (_SUNDAY, _FRIDAY), (_TUESDAY, _MONDAY)] +) +def test_previous_workday(day, expected): + assert previous_workday(day) == expected + + +@pytest.mark.parametrize( + "day,expected", + [ + (_THURSDAY, _WEDNESDAY), + (_FRIDAY, _THURSDAY), + (_SATURDAY, _THURSDAY), + (_SUNDAY, _FRIDAY), + (_MONDAY, _FRIDAY), # last week Friday + (_TUESDAY, _MONDAY), + (_NEXT_WEDNESDAY, _TUESDAY), # WED is same week as TUE + ], +) +def test_before_nearest_workday(day, expected): + assert before_nearest_workday(day) == expected + + +@pytest.mark.parametrize( + "day,expected", [(_SATURDAY, _MONDAY), (_SUNDAY, _TUESDAY), (_FRIDAY, _MONDAY)] +) +def test_after_nearest_workday(day, expected): + assert after_nearest_workday(day) == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/common.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/common.py new file mode 100644 index 0000000000000000000000000000000000000000..efb010addad225cda407d55c47dc804645cf3999 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/common.py @@ -0,0 +1,37 @@ +""" +Assertion helpers and base class for offsets tests +""" +from __future__ import annotations + + +def assert_offset_equal(offset, base, expected): + actual = offset + base + actual_swapped = base + offset + actual_apply = offset._apply(base) + try: + assert actual == expected + assert actual_swapped == expected + assert actual_apply == expected + except AssertionError as err: + raise AssertionError( + f"\nExpected: {expected}\nActual: {actual}\nFor Offset: {offset})" + f"\nAt Date: {base}" + ) from err + + +def assert_is_on_offset(offset, date, expected): + actual = offset.is_on_offset(date) + assert actual == expected, ( + f"\nExpected: {expected}\nActual: {actual}\nFor Offset: {offset})" + f"\nAt Date: {date}" + ) + + +class WeekDay: + MON = 0 + TUE = 1 + WED = 2 + THU = 3 + FRI = 4 + SAT = 5 + SUN = 6 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_day.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_day.py new file mode 100644 index 0000000000000000000000000000000000000000..7db1921369023eaf05c65bf537c259de3f2a81cb --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_day.py @@ -0,0 +1,236 @@ +""" +Tests for offsets.BDay +""" +from __future__ import annotations + +from datetime import ( + date, + datetime, + timedelta, +) + +import numpy as np +import pytest + +from pandas._libs.tslibs.offsets import ( + ApplyTypeError, + BDay, + BMonthEnd, +) + +from pandas import ( + DatetimeIndex, + Timedelta, + _testing as tm, +) +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries import offsets + + +@pytest.fixture +def dt(): + return datetime(2008, 1, 1) + + +@pytest.fixture +def _offset(): + return BDay + + +@pytest.fixture +def offset(_offset): + return _offset() + + +@pytest.fixture +def offset2(_offset): + return _offset(2) + + +class TestBusinessDay: + def test_different_normalize_equals(self, _offset, offset2): + # GH#21404 changed __eq__ to return False when `normalize` does not match + offset = _offset() + offset2 = _offset(normalize=True) + assert offset != offset2 + + def test_repr(self, offset, offset2): + assert repr(offset) == "" + assert repr(offset2) == "<2 * BusinessDays>" + + expected = "" + assert repr(offset + timedelta(1)) == expected + + def test_with_offset(self, dt, offset): + offset = offset + timedelta(hours=2) + + assert (dt + offset) == datetime(2008, 1, 2, 2) + + @pytest.mark.parametrize( + "td", + [ + Timedelta(hours=2), + Timedelta(hours=2).to_pytimedelta(), + Timedelta(hours=2).to_timedelta64(), + ], + ids=lambda x: type(x), + ) + def test_with_offset_index(self, td, dt, offset): + dti = DatetimeIndex([dt]) + expected = DatetimeIndex([datetime(2008, 1, 2, 2)]) + + result = dti + (td + offset) + tm.assert_index_equal(result, expected) + + result = dti + (offset + td) + tm.assert_index_equal(result, expected) + + def test_eq(self, offset2): + assert offset2 == offset2 + + def test_hash(self, offset2): + assert hash(offset2) == hash(offset2) + + def test_add_datetime(self, dt, offset2): + assert offset2 + dt == datetime(2008, 1, 3) + assert offset2 + np.datetime64("2008-01-01 00:00:00") == datetime(2008, 1, 3) + + def testRollback1(self, dt, _offset): + assert _offset(10).rollback(dt) == dt + + def testRollback2(self, _offset): + assert _offset(10).rollback(datetime(2008, 1, 5)) == datetime(2008, 1, 4) + + def testRollforward1(self, dt, _offset): + assert _offset(10).rollforward(dt) == dt + + def testRollforward2(self, _offset): + assert _offset(10).rollforward(datetime(2008, 1, 5)) == datetime(2008, 1, 7) + + def test_roll_date_object(self, offset): + dt = date(2012, 9, 15) + + result = offset.rollback(dt) + assert result == datetime(2012, 9, 14) + + result = offset.rollforward(dt) + assert result == datetime(2012, 9, 17) + + offset = offsets.Day() + result = offset.rollback(dt) + assert result == datetime(2012, 9, 15) + + result = offset.rollforward(dt) + assert result == datetime(2012, 9, 15) + + @pytest.mark.parametrize( + "dt, expected", + [ + (datetime(2008, 1, 1), True), + (datetime(2008, 1, 5), False), + ], + ) + def test_is_on_offset(self, offset, dt, expected): + assert_is_on_offset(offset, dt, expected) + + apply_cases: list[tuple[int, dict[datetime, datetime]]] = [ + ( + 1, + { + datetime(2008, 1, 1): datetime(2008, 1, 2), + datetime(2008, 1, 4): datetime(2008, 1, 7), + datetime(2008, 1, 5): datetime(2008, 1, 7), + datetime(2008, 1, 6): datetime(2008, 1, 7), + datetime(2008, 1, 7): datetime(2008, 1, 8), + }, + ), + ( + 2, + { + datetime(2008, 1, 1): datetime(2008, 1, 3), + datetime(2008, 1, 4): datetime(2008, 1, 8), + datetime(2008, 1, 5): datetime(2008, 1, 8), + datetime(2008, 1, 6): datetime(2008, 1, 8), + datetime(2008, 1, 7): datetime(2008, 1, 9), + }, + ), + ( + -1, + { + datetime(2008, 1, 1): datetime(2007, 12, 31), + datetime(2008, 1, 4): datetime(2008, 1, 3), + datetime(2008, 1, 5): datetime(2008, 1, 4), + datetime(2008, 1, 6): datetime(2008, 1, 4), + datetime(2008, 1, 7): datetime(2008, 1, 4), + datetime(2008, 1, 8): datetime(2008, 1, 7), + }, + ), + ( + -2, + { + datetime(2008, 1, 1): datetime(2007, 12, 28), + datetime(2008, 1, 4): datetime(2008, 1, 2), + datetime(2008, 1, 5): datetime(2008, 1, 3), + datetime(2008, 1, 6): datetime(2008, 1, 3), + datetime(2008, 1, 7): datetime(2008, 1, 3), + datetime(2008, 1, 8): datetime(2008, 1, 4), + datetime(2008, 1, 9): datetime(2008, 1, 7), + }, + ), + ( + 0, + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 1, 4): datetime(2008, 1, 4), + datetime(2008, 1, 5): datetime(2008, 1, 7), + datetime(2008, 1, 6): datetime(2008, 1, 7), + datetime(2008, 1, 7): datetime(2008, 1, 7), + }, + ), + ] + + @pytest.mark.parametrize("case", apply_cases) + def test_apply(self, case, _offset): + n, cases = case + offset = _offset(n) + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + def test_apply_large_n(self, _offset): + dt = datetime(2012, 10, 23) + + result = dt + _offset(10) + assert result == datetime(2012, 11, 6) + + result = dt + _offset(100) - _offset(100) + assert result == dt + + off = _offset() * 6 + rs = datetime(2012, 1, 1) - off + xp = datetime(2011, 12, 23) + assert rs == xp + + st = datetime(2011, 12, 18) + rs = st + off + xp = datetime(2011, 12, 26) + assert rs == xp + + off = _offset() * 10 + rs = datetime(2014, 1, 5) + off # see #5890 + xp = datetime(2014, 1, 17) + assert rs == xp + + def test_apply_corner(self, _offset): + if _offset is BDay: + msg = "Only know how to combine business day with datetime or timedelta" + else: + msg = ( + "Only know how to combine trading day " + "with datetime, datetime64 or timedelta" + ) + with pytest.raises(ApplyTypeError, match=msg): + _offset()._apply(BMonthEnd()) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_hour.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_hour.py new file mode 100644 index 0000000000000000000000000000000000000000..2779100f5355cf7475b10d3de6bf7ceebc92af96 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_hour.py @@ -0,0 +1,1445 @@ +""" +Tests for offsets.BusinessHour +""" +from __future__ import annotations + +from datetime import ( + datetime, + time as dt_time, +) + +import pytest + +from pandas._libs.tslibs import ( + Timedelta, + Timestamp, +) +from pandas._libs.tslibs.offsets import ( + BDay, + BusinessHour, + Nano, +) + +from pandas import ( + DatetimeIndex, + _testing as tm, + date_range, +) +from pandas.tests.tseries.offsets.common import assert_offset_equal + + +@pytest.fixture +def dt(): + return datetime(2014, 7, 1, 10, 00) + + +@pytest.fixture +def _offset(): + return BusinessHour + + +@pytest.fixture +def offset1(): + return BusinessHour() + + +@pytest.fixture +def offset2(): + return BusinessHour(n=3) + + +@pytest.fixture +def offset3(): + return BusinessHour(n=-1) + + +@pytest.fixture +def offset4(): + return BusinessHour(n=-4) + + +@pytest.fixture +def offset5(): + return BusinessHour(start=dt_time(11, 0), end=dt_time(14, 30)) + + +@pytest.fixture +def offset6(): + return BusinessHour(start="20:00", end="05:00") + + +@pytest.fixture +def offset7(): + return BusinessHour(n=-2, start=dt_time(21, 30), end=dt_time(6, 30)) + + +@pytest.fixture +def offset8(): + return BusinessHour(start=["09:00", "13:00"], end=["12:00", "17:00"]) + + +@pytest.fixture +def offset9(): + return BusinessHour(n=3, start=["09:00", "22:00"], end=["13:00", "03:00"]) + + +@pytest.fixture +def offset10(): + return BusinessHour(n=-1, start=["23:00", "13:00"], end=["02:00", "17:00"]) + + +class TestBusinessHour: + @pytest.mark.parametrize( + "start,end,match", + [ + ( + dt_time(11, 0, 5), + "17:00", + "time data must be specified only with hour and minute", + ), + ("AAA", "17:00", "time data must match '%H:%M' format"), + ("14:00:05", "17:00", "time data must match '%H:%M' format"), + ([], "17:00", "Must include at least 1 start time"), + ("09:00", [], "Must include at least 1 end time"), + ( + ["09:00", "11:00"], + "17:00", + "number of starting time and ending time must be the same", + ), + ( + ["09:00", "11:00"], + ["10:00"], + "number of starting time and ending time must be the same", + ), + ( + ["09:00", "11:00"], + ["12:00", "20:00"], + r"invalid starting and ending time\(s\): opening hours should not " + "touch or overlap with one another", + ), + ( + ["12:00", "20:00"], + ["09:00", "11:00"], + r"invalid starting and ending time\(s\): opening hours should not " + "touch or overlap with one another", + ), + ], + ) + def test_constructor_errors(self, start, end, match): + with pytest.raises(ValueError, match=match): + BusinessHour(start=start, end=end) + + def test_different_normalize_equals(self, _offset): + # GH#21404 changed __eq__ to return False when `normalize` does not match + offset = _offset() + offset2 = _offset(normalize=True) + assert offset != offset2 + + def test_repr( + self, + offset1, + offset2, + offset3, + offset4, + offset5, + offset6, + offset7, + offset8, + offset9, + offset10, + ): + assert repr(offset1) == "" + assert repr(offset2) == "<3 * BusinessHours: bh=09:00-17:00>" + assert repr(offset3) == "<-1 * BusinessHour: bh=09:00-17:00>" + assert repr(offset4) == "<-4 * BusinessHours: bh=09:00-17:00>" + + assert repr(offset5) == "" + assert repr(offset6) == "" + assert repr(offset7) == "<-2 * BusinessHours: bh=21:30-06:30>" + assert repr(offset8) == "" + assert repr(offset9) == "<3 * BusinessHours: bh=09:00-13:00,22:00-03:00>" + assert repr(offset10) == "<-1 * BusinessHour: bh=13:00-17:00,23:00-02:00>" + + def test_with_offset(self, dt): + expected = Timestamp("2014-07-01 13:00") + + assert dt + BusinessHour() * 3 == expected + assert dt + BusinessHour(n=3) == expected + + @pytest.mark.parametrize( + "offset_name", + ["offset1", "offset2", "offset3", "offset4", "offset8", "offset9", "offset10"], + ) + def test_eq_attribute(self, offset_name, request): + offset = request.getfixturevalue(offset_name) + assert offset == offset + + @pytest.mark.parametrize( + "offset1,offset2", + [ + (BusinessHour(start="09:00"), BusinessHour()), + ( + BusinessHour(start=["23:00", "13:00"], end=["12:00", "17:00"]), + BusinessHour(start=["13:00", "23:00"], end=["17:00", "12:00"]), + ), + ], + ) + def test_eq(self, offset1, offset2): + assert offset1 == offset2 + + @pytest.mark.parametrize( + "offset1,offset2", + [ + (BusinessHour(), BusinessHour(-1)), + (BusinessHour(start="09:00"), BusinessHour(start="09:01")), + ( + BusinessHour(start="09:00", end="17:00"), + BusinessHour(start="17:00", end="09:01"), + ), + ( + BusinessHour(start=["13:00", "23:00"], end=["18:00", "07:00"]), + BusinessHour(start=["13:00", "23:00"], end=["17:00", "12:00"]), + ), + ], + ) + def test_neq(self, offset1, offset2): + assert offset1 != offset2 + + @pytest.mark.parametrize( + "offset_name", + ["offset1", "offset2", "offset3", "offset4", "offset8", "offset9", "offset10"], + ) + def test_hash(self, offset_name, request): + offset = request.getfixturevalue(offset_name) + assert offset == offset + + def test_add_datetime( + self, + dt, + offset1, + offset2, + offset3, + offset4, + offset8, + offset9, + offset10, + ): + assert offset1 + dt == datetime(2014, 7, 1, 11) + assert offset2 + dt == datetime(2014, 7, 1, 13) + assert offset3 + dt == datetime(2014, 6, 30, 17) + assert offset4 + dt == datetime(2014, 6, 30, 14) + assert offset8 + dt == datetime(2014, 7, 1, 11) + assert offset9 + dt == datetime(2014, 7, 1, 22) + assert offset10 + dt == datetime(2014, 7, 1, 1) + + def test_sub(self, dt, offset2, _offset): + off = offset2 + msg = "Cannot subtract datetime from offset" + with pytest.raises(TypeError, match=msg): + off - dt + assert 2 * off - off == off + + assert dt - offset2 == dt + _offset(-3) + + def test_multiply_by_zero(self, dt, offset1, offset2): + assert dt - 0 * offset1 == dt + assert dt + 0 * offset1 == dt + assert dt - 0 * offset2 == dt + assert dt + 0 * offset2 == dt + + def testRollback1( + self, + dt, + _offset, + offset1, + offset2, + offset3, + offset4, + offset5, + offset6, + offset7, + offset8, + offset9, + offset10, + ): + assert offset1.rollback(dt) == dt + assert offset2.rollback(dt) == dt + assert offset3.rollback(dt) == dt + assert offset4.rollback(dt) == dt + assert offset5.rollback(dt) == datetime(2014, 6, 30, 14, 30) + assert offset6.rollback(dt) == datetime(2014, 7, 1, 5, 0) + assert offset7.rollback(dt) == datetime(2014, 7, 1, 6, 30) + assert offset8.rollback(dt) == dt + assert offset9.rollback(dt) == dt + assert offset10.rollback(dt) == datetime(2014, 7, 1, 2) + + datet = datetime(2014, 7, 1, 0) + assert offset1.rollback(datet) == datetime(2014, 6, 30, 17) + assert offset2.rollback(datet) == datetime(2014, 6, 30, 17) + assert offset3.rollback(datet) == datetime(2014, 6, 30, 17) + assert offset4.rollback(datet) == datetime(2014, 6, 30, 17) + assert offset5.rollback(datet) == datetime(2014, 6, 30, 14, 30) + assert offset6.rollback(datet) == datet + assert offset7.rollback(datet) == datet + assert offset8.rollback(datet) == datetime(2014, 6, 30, 17) + assert offset9.rollback(datet) == datet + assert offset10.rollback(datet) == datet + + assert _offset(5).rollback(dt) == dt + + def testRollback2(self, _offset): + assert _offset(-3).rollback(datetime(2014, 7, 5, 15, 0)) == datetime( + 2014, 7, 4, 17, 0 + ) + + def testRollforward1( + self, + dt, + _offset, + offset1, + offset2, + offset3, + offset4, + offset5, + offset6, + offset7, + offset8, + offset9, + offset10, + ): + assert offset1.rollforward(dt) == dt + assert offset2.rollforward(dt) == dt + assert offset3.rollforward(dt) == dt + assert offset4.rollforward(dt) == dt + assert offset5.rollforward(dt) == datetime(2014, 7, 1, 11, 0) + assert offset6.rollforward(dt) == datetime(2014, 7, 1, 20, 0) + assert offset7.rollforward(dt) == datetime(2014, 7, 1, 21, 30) + assert offset8.rollforward(dt) == dt + assert offset9.rollforward(dt) == dt + assert offset10.rollforward(dt) == datetime(2014, 7, 1, 13) + + datet = datetime(2014, 7, 1, 0) + assert offset1.rollforward(datet) == datetime(2014, 7, 1, 9) + assert offset2.rollforward(datet) == datetime(2014, 7, 1, 9) + assert offset3.rollforward(datet) == datetime(2014, 7, 1, 9) + assert offset4.rollforward(datet) == datetime(2014, 7, 1, 9) + assert offset5.rollforward(datet) == datetime(2014, 7, 1, 11) + assert offset6.rollforward(datet) == datet + assert offset7.rollforward(datet) == datet + assert offset8.rollforward(datet) == datetime(2014, 7, 1, 9) + assert offset9.rollforward(datet) == datet + assert offset10.rollforward(datet) == datet + + assert _offset(5).rollforward(dt) == dt + + def testRollforward2(self, _offset): + assert _offset(-3).rollforward(datetime(2014, 7, 5, 16, 0)) == datetime( + 2014, 7, 7, 9 + ) + + def test_roll_date_object(self): + offset = BusinessHour() + + dt = datetime(2014, 7, 6, 15, 0) + + result = offset.rollback(dt) + assert result == datetime(2014, 7, 4, 17) + + result = offset.rollforward(dt) + assert result == datetime(2014, 7, 7, 9) + + normalize_cases = [] + normalize_cases.append( + ( + BusinessHour(normalize=True), + { + datetime(2014, 7, 1, 8): datetime(2014, 7, 1), + datetime(2014, 7, 1, 17): datetime(2014, 7, 2), + datetime(2014, 7, 1, 16): datetime(2014, 7, 2), + datetime(2014, 7, 1, 23): datetime(2014, 7, 2), + datetime(2014, 7, 1, 0): datetime(2014, 7, 1), + datetime(2014, 7, 4, 15): datetime(2014, 7, 4), + datetime(2014, 7, 4, 15, 59): datetime(2014, 7, 4), + datetime(2014, 7, 4, 16, 30): datetime(2014, 7, 7), + datetime(2014, 7, 5, 23): datetime(2014, 7, 7), + datetime(2014, 7, 6, 10): datetime(2014, 7, 7), + }, + ) + ) + + normalize_cases.append( + ( + BusinessHour(-1, normalize=True), + { + datetime(2014, 7, 1, 8): datetime(2014, 6, 30), + datetime(2014, 7, 1, 17): datetime(2014, 7, 1), + datetime(2014, 7, 1, 16): datetime(2014, 7, 1), + datetime(2014, 7, 1, 10): datetime(2014, 6, 30), + datetime(2014, 7, 1, 0): datetime(2014, 6, 30), + datetime(2014, 7, 7, 10): datetime(2014, 7, 4), + datetime(2014, 7, 7, 10, 1): datetime(2014, 7, 7), + datetime(2014, 7, 5, 23): datetime(2014, 7, 4), + datetime(2014, 7, 6, 10): datetime(2014, 7, 4), + }, + ) + ) + + normalize_cases.append( + ( + BusinessHour(1, normalize=True, start="17:00", end="04:00"), + { + datetime(2014, 7, 1, 8): datetime(2014, 7, 1), + datetime(2014, 7, 1, 17): datetime(2014, 7, 1), + datetime(2014, 7, 1, 23): datetime(2014, 7, 2), + datetime(2014, 7, 2, 2): datetime(2014, 7, 2), + datetime(2014, 7, 2, 3): datetime(2014, 7, 2), + datetime(2014, 7, 4, 23): datetime(2014, 7, 5), + datetime(2014, 7, 5, 2): datetime(2014, 7, 5), + datetime(2014, 7, 7, 2): datetime(2014, 7, 7), + datetime(2014, 7, 7, 17): datetime(2014, 7, 7), + }, + ) + ) + + @pytest.mark.parametrize("case", normalize_cases) + def test_normalize(self, case): + offset, cases = case + for dt, expected in cases.items(): + assert offset._apply(dt) == expected + + on_offset_cases = [] + on_offset_cases.append( + ( + BusinessHour(), + { + datetime(2014, 7, 1, 9): True, + datetime(2014, 7, 1, 8, 59): False, + datetime(2014, 7, 1, 8): False, + datetime(2014, 7, 1, 17): True, + datetime(2014, 7, 1, 17, 1): False, + datetime(2014, 7, 1, 18): False, + datetime(2014, 7, 5, 9): False, + datetime(2014, 7, 6, 12): False, + }, + ) + ) + + on_offset_cases.append( + ( + BusinessHour(start="10:00", end="15:00"), + { + datetime(2014, 7, 1, 9): False, + datetime(2014, 7, 1, 10): True, + datetime(2014, 7, 1, 15): True, + datetime(2014, 7, 1, 15, 1): False, + datetime(2014, 7, 5, 12): False, + datetime(2014, 7, 6, 12): False, + }, + ) + ) + + on_offset_cases.append( + ( + BusinessHour(start="19:00", end="05:00"), + { + datetime(2014, 7, 1, 9, 0): False, + datetime(2014, 7, 1, 10, 0): False, + datetime(2014, 7, 1, 15): False, + datetime(2014, 7, 1, 15, 1): False, + datetime(2014, 7, 5, 12, 0): False, + datetime(2014, 7, 6, 12, 0): False, + datetime(2014, 7, 1, 19, 0): True, + datetime(2014, 7, 2, 0, 0): True, + datetime(2014, 7, 4, 23): True, + datetime(2014, 7, 5, 1): True, + datetime(2014, 7, 5, 5, 0): True, + datetime(2014, 7, 6, 23, 0): False, + datetime(2014, 7, 7, 3, 0): False, + }, + ) + ) + + on_offset_cases.append( + ( + BusinessHour(start=["09:00", "13:00"], end=["12:00", "17:00"]), + { + datetime(2014, 7, 1, 9): True, + datetime(2014, 7, 1, 8, 59): False, + datetime(2014, 7, 1, 8): False, + datetime(2014, 7, 1, 17): True, + datetime(2014, 7, 1, 17, 1): False, + datetime(2014, 7, 1, 18): False, + datetime(2014, 7, 5, 9): False, + datetime(2014, 7, 6, 12): False, + datetime(2014, 7, 1, 12, 30): False, + }, + ) + ) + + on_offset_cases.append( + ( + BusinessHour(start=["19:00", "23:00"], end=["21:00", "05:00"]), + { + datetime(2014, 7, 1, 9, 0): False, + datetime(2014, 7, 1, 10, 0): False, + datetime(2014, 7, 1, 15): False, + datetime(2014, 7, 1, 15, 1): False, + datetime(2014, 7, 5, 12, 0): False, + datetime(2014, 7, 6, 12, 0): False, + datetime(2014, 7, 1, 19, 0): True, + datetime(2014, 7, 2, 0, 0): True, + datetime(2014, 7, 4, 23): True, + datetime(2014, 7, 5, 1): True, + datetime(2014, 7, 5, 5, 0): True, + datetime(2014, 7, 6, 23, 0): False, + datetime(2014, 7, 7, 3, 0): False, + datetime(2014, 7, 4, 22): False, + }, + ) + ) + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, cases = case + for dt, expected in cases.items(): + assert offset.is_on_offset(dt) == expected + + apply_cases = [ + ( + BusinessHour(), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 12), + datetime(2014, 7, 1, 13): datetime(2014, 7, 1, 14), + datetime(2014, 7, 1, 15): datetime(2014, 7, 1, 16), + datetime(2014, 7, 1, 19): datetime(2014, 7, 2, 10), + datetime(2014, 7, 1, 16): datetime(2014, 7, 2, 9), + datetime(2014, 7, 1, 16, 30, 15): datetime(2014, 7, 2, 9, 30, 15), + datetime(2014, 7, 1, 17): datetime(2014, 7, 2, 10), + datetime(2014, 7, 2, 11): datetime(2014, 7, 2, 12), + # out of business hours + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 10), + datetime(2014, 7, 2, 19): datetime(2014, 7, 3, 10), + datetime(2014, 7, 2, 23): datetime(2014, 7, 3, 10), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 10), + # saturday + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 10), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 10), + datetime(2014, 7, 4, 16, 30): datetime(2014, 7, 7, 9, 30), + datetime(2014, 7, 4, 16, 30, 30): datetime(2014, 7, 7, 9, 30, 30), + }, + ), + ( + BusinessHour(4), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 15), + datetime(2014, 7, 1, 13): datetime(2014, 7, 2, 9), + datetime(2014, 7, 1, 15): datetime(2014, 7, 2, 11), + datetime(2014, 7, 1, 16): datetime(2014, 7, 2, 12), + datetime(2014, 7, 1, 17): datetime(2014, 7, 2, 13), + datetime(2014, 7, 2, 11): datetime(2014, 7, 2, 15), + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 13), + datetime(2014, 7, 2, 19): datetime(2014, 7, 3, 13), + datetime(2014, 7, 2, 23): datetime(2014, 7, 3, 13), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 13), + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 13), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 13), + datetime(2014, 7, 4, 16, 30): datetime(2014, 7, 7, 12, 30), + datetime(2014, 7, 4, 16, 30, 30): datetime(2014, 7, 7, 12, 30, 30), + }, + ), + ( + BusinessHour(-1), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 10), + datetime(2014, 7, 1, 13): datetime(2014, 7, 1, 12), + datetime(2014, 7, 1, 15): datetime(2014, 7, 1, 14), + datetime(2014, 7, 1, 16): datetime(2014, 7, 1, 15), + datetime(2014, 7, 1, 10): datetime(2014, 6, 30, 17), + datetime(2014, 7, 1, 16, 30, 15): datetime(2014, 7, 1, 15, 30, 15), + datetime(2014, 7, 1, 9, 30, 15): datetime(2014, 6, 30, 16, 30, 15), + datetime(2014, 7, 1, 17): datetime(2014, 7, 1, 16), + datetime(2014, 7, 1, 5): datetime(2014, 6, 30, 16), + datetime(2014, 7, 2, 11): datetime(2014, 7, 2, 10), + # out of business hours + datetime(2014, 7, 2, 8): datetime(2014, 7, 1, 16), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 16), + datetime(2014, 7, 2, 23): datetime(2014, 7, 2, 16), + datetime(2014, 7, 3, 0): datetime(2014, 7, 2, 16), + # saturday + datetime(2014, 7, 5, 15): datetime(2014, 7, 4, 16), + datetime(2014, 7, 7, 9): datetime(2014, 7, 4, 16), + datetime(2014, 7, 7, 9, 30): datetime(2014, 7, 4, 16, 30), + datetime(2014, 7, 7, 9, 30, 30): datetime(2014, 7, 4, 16, 30, 30), + }, + ), + ( + BusinessHour(-4), + { + datetime(2014, 7, 1, 11): datetime(2014, 6, 30, 15), + datetime(2014, 7, 1, 13): datetime(2014, 6, 30, 17), + datetime(2014, 7, 1, 15): datetime(2014, 7, 1, 11), + datetime(2014, 7, 1, 16): datetime(2014, 7, 1, 12), + datetime(2014, 7, 1, 17): datetime(2014, 7, 1, 13), + datetime(2014, 7, 2, 11): datetime(2014, 7, 1, 15), + datetime(2014, 7, 2, 8): datetime(2014, 7, 1, 13), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 13), + datetime(2014, 7, 2, 23): datetime(2014, 7, 2, 13), + datetime(2014, 7, 3, 0): datetime(2014, 7, 2, 13), + datetime(2014, 7, 5, 15): datetime(2014, 7, 4, 13), + datetime(2014, 7, 4, 18): datetime(2014, 7, 4, 13), + datetime(2014, 7, 7, 9, 30): datetime(2014, 7, 4, 13, 30), + datetime(2014, 7, 7, 9, 30, 30): datetime(2014, 7, 4, 13, 30, 30), + }, + ), + ( + BusinessHour(start="13:00", end="16:00"), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 14), + datetime(2014, 7, 1, 13): datetime(2014, 7, 1, 14), + datetime(2014, 7, 1, 15): datetime(2014, 7, 2, 13), + datetime(2014, 7, 1, 19): datetime(2014, 7, 2, 14), + datetime(2014, 7, 1, 16): datetime(2014, 7, 2, 14), + datetime(2014, 7, 1, 15, 30, 15): datetime(2014, 7, 2, 13, 30, 15), + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 14), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 14), + }, + ), + ( + BusinessHour(n=2, start="13:00", end="16:00"), + { + datetime(2014, 7, 1, 17): datetime(2014, 7, 2, 15), + datetime(2014, 7, 2, 14): datetime(2014, 7, 3, 13), + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 15), + datetime(2014, 7, 2, 19): datetime(2014, 7, 3, 15), + datetime(2014, 7, 2, 14, 30): datetime(2014, 7, 3, 13, 30), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 15), + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 15), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 15), + datetime(2014, 7, 4, 14, 30): datetime(2014, 7, 7, 13, 30), + datetime(2014, 7, 4, 14, 30, 30): datetime(2014, 7, 7, 13, 30, 30), + }, + ), + ( + BusinessHour(n=-1, start="13:00", end="16:00"), + { + datetime(2014, 7, 2, 11): datetime(2014, 7, 1, 15), + datetime(2014, 7, 2, 13): datetime(2014, 7, 1, 15), + datetime(2014, 7, 2, 14): datetime(2014, 7, 1, 16), + datetime(2014, 7, 2, 15): datetime(2014, 7, 2, 14), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 15), + datetime(2014, 7, 2, 16): datetime(2014, 7, 2, 15), + datetime(2014, 7, 2, 13, 30, 15): datetime(2014, 7, 1, 15, 30, 15), + datetime(2014, 7, 5, 15): datetime(2014, 7, 4, 15), + datetime(2014, 7, 7, 11): datetime(2014, 7, 4, 15), + }, + ), + ( + BusinessHour(n=-3, start="10:00", end="16:00"), + { + datetime(2014, 7, 1, 17): datetime(2014, 7, 1, 13), + datetime(2014, 7, 2, 14): datetime(2014, 7, 2, 11), + datetime(2014, 7, 2, 8): datetime(2014, 7, 1, 13), + datetime(2014, 7, 2, 13): datetime(2014, 7, 1, 16), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 13), + datetime(2014, 7, 2, 11, 30): datetime(2014, 7, 1, 14, 30), + datetime(2014, 7, 3, 0): datetime(2014, 7, 2, 13), + datetime(2014, 7, 4, 10): datetime(2014, 7, 3, 13), + datetime(2014, 7, 5, 15): datetime(2014, 7, 4, 13), + datetime(2014, 7, 4, 16): datetime(2014, 7, 4, 13), + datetime(2014, 7, 4, 12, 30): datetime(2014, 7, 3, 15, 30), + datetime(2014, 7, 4, 12, 30, 30): datetime(2014, 7, 3, 15, 30, 30), + }, + ), + ( + BusinessHour(start="19:00", end="05:00"), + { + datetime(2014, 7, 1, 17): datetime(2014, 7, 1, 20), + datetime(2014, 7, 2, 14): datetime(2014, 7, 2, 20), + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 20), + datetime(2014, 7, 2, 13): datetime(2014, 7, 2, 20), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 20), + datetime(2014, 7, 2, 4, 30): datetime(2014, 7, 2, 19, 30), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 1), + datetime(2014, 7, 4, 10): datetime(2014, 7, 4, 20), + datetime(2014, 7, 4, 23): datetime(2014, 7, 5, 0), + datetime(2014, 7, 5, 0): datetime(2014, 7, 5, 1), + datetime(2014, 7, 5, 4): datetime(2014, 7, 7, 19), + datetime(2014, 7, 5, 4, 30): datetime(2014, 7, 7, 19, 30), + datetime(2014, 7, 5, 4, 30, 30): datetime(2014, 7, 7, 19, 30, 30), + }, + ), + ( + BusinessHour(n=-1, start="19:00", end="05:00"), + { + datetime(2014, 7, 1, 17): datetime(2014, 7, 1, 4), + datetime(2014, 7, 2, 14): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 13): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 20): datetime(2014, 7, 2, 5), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 19, 30): datetime(2014, 7, 2, 4, 30), + datetime(2014, 7, 3, 0): datetime(2014, 7, 2, 23), + datetime(2014, 7, 3, 6): datetime(2014, 7, 3, 4), + datetime(2014, 7, 4, 23): datetime(2014, 7, 4, 22), + datetime(2014, 7, 5, 0): datetime(2014, 7, 4, 23), + datetime(2014, 7, 5, 4): datetime(2014, 7, 5, 3), + datetime(2014, 7, 7, 19, 30): datetime(2014, 7, 5, 4, 30), + datetime(2014, 7, 7, 19, 30, 30): datetime(2014, 7, 5, 4, 30, 30), + }, + ), + ( + BusinessHour(n=4, start="00:00", end="23:00"), + { + datetime(2014, 7, 3, 22): datetime(2014, 7, 4, 3), + datetime(2014, 7, 4, 22): datetime(2014, 7, 7, 3), + datetime(2014, 7, 3, 22, 30): datetime(2014, 7, 4, 3, 30), + datetime(2014, 7, 3, 22, 20): datetime(2014, 7, 4, 3, 20), + datetime(2014, 7, 4, 22, 30, 30): datetime(2014, 7, 7, 3, 30, 30), + datetime(2014, 7, 4, 22, 30, 20): datetime(2014, 7, 7, 3, 30, 20), + }, + ), + ( + BusinessHour(n=-4, start="00:00", end="23:00"), + { + datetime(2014, 7, 4, 3): datetime(2014, 7, 3, 22), + datetime(2014, 7, 7, 3): datetime(2014, 7, 4, 22), + datetime(2014, 7, 4, 3, 30): datetime(2014, 7, 3, 22, 30), + datetime(2014, 7, 4, 3, 20): datetime(2014, 7, 3, 22, 20), + datetime(2014, 7, 7, 3, 30, 30): datetime(2014, 7, 4, 22, 30, 30), + datetime(2014, 7, 7, 3, 30, 20): datetime(2014, 7, 4, 22, 30, 20), + }, + ), + ( + BusinessHour(start=["09:00", "14:00"], end=["12:00", "18:00"]), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 14), + datetime(2014, 7, 1, 15): datetime(2014, 7, 1, 16), + datetime(2014, 7, 1, 19): datetime(2014, 7, 2, 10), + datetime(2014, 7, 1, 16): datetime(2014, 7, 1, 17), + datetime(2014, 7, 1, 16, 30, 15): datetime(2014, 7, 1, 17, 30, 15), + datetime(2014, 7, 1, 17): datetime(2014, 7, 2, 9), + datetime(2014, 7, 2, 11): datetime(2014, 7, 2, 14), + # out of business hours + datetime(2014, 7, 1, 13): datetime(2014, 7, 1, 15), + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 10), + datetime(2014, 7, 2, 19): datetime(2014, 7, 3, 10), + datetime(2014, 7, 2, 23): datetime(2014, 7, 3, 10), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 10), + # saturday + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 10), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 9), + datetime(2014, 7, 4, 17, 30): datetime(2014, 7, 7, 9, 30), + datetime(2014, 7, 4, 17, 30, 30): datetime(2014, 7, 7, 9, 30, 30), + }, + ), + ( + BusinessHour(n=4, start=["09:00", "14:00"], end=["12:00", "18:00"]), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 17), + datetime(2014, 7, 1, 13): datetime(2014, 7, 2, 9), + datetime(2014, 7, 1, 15): datetime(2014, 7, 2, 10), + datetime(2014, 7, 1, 16): datetime(2014, 7, 2, 11), + datetime(2014, 7, 1, 17): datetime(2014, 7, 2, 14), + datetime(2014, 7, 2, 11): datetime(2014, 7, 2, 17), + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 15), + datetime(2014, 7, 2, 19): datetime(2014, 7, 3, 15), + datetime(2014, 7, 2, 23): datetime(2014, 7, 3, 15), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 15), + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 15), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 14), + datetime(2014, 7, 4, 16, 30): datetime(2014, 7, 7, 11, 30), + datetime(2014, 7, 4, 16, 30, 30): datetime(2014, 7, 7, 11, 30, 30), + }, + ), + ( + BusinessHour(n=-4, start=["09:00", "14:00"], end=["12:00", "18:00"]), + { + datetime(2014, 7, 1, 11): datetime(2014, 6, 30, 16), + datetime(2014, 7, 1, 13): datetime(2014, 6, 30, 17), + datetime(2014, 7, 1, 15): datetime(2014, 6, 30, 18), + datetime(2014, 7, 1, 16): datetime(2014, 7, 1, 10), + datetime(2014, 7, 1, 17): datetime(2014, 7, 1, 11), + datetime(2014, 7, 2, 11): datetime(2014, 7, 1, 16), + datetime(2014, 7, 2, 8): datetime(2014, 7, 1, 12), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 12), + datetime(2014, 7, 2, 23): datetime(2014, 7, 2, 12), + datetime(2014, 7, 3, 0): datetime(2014, 7, 2, 12), + datetime(2014, 7, 5, 15): datetime(2014, 7, 4, 12), + datetime(2014, 7, 4, 18): datetime(2014, 7, 4, 12), + datetime(2014, 7, 7, 9, 30): datetime(2014, 7, 4, 14, 30), + datetime(2014, 7, 7, 9, 30, 30): datetime(2014, 7, 4, 14, 30, 30), + }, + ), + ( + BusinessHour(n=-1, start=["19:00", "03:00"], end=["01:00", "05:00"]), + { + datetime(2014, 7, 1, 17): datetime(2014, 7, 1, 4), + datetime(2014, 7, 2, 14): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 8): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 13): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 20): datetime(2014, 7, 2, 5), + datetime(2014, 7, 2, 19): datetime(2014, 7, 2, 4), + datetime(2014, 7, 2, 4): datetime(2014, 7, 2, 1), + datetime(2014, 7, 2, 19, 30): datetime(2014, 7, 2, 4, 30), + datetime(2014, 7, 3, 0): datetime(2014, 7, 2, 23), + datetime(2014, 7, 3, 6): datetime(2014, 7, 3, 4), + datetime(2014, 7, 4, 23): datetime(2014, 7, 4, 22), + datetime(2014, 7, 5, 0): datetime(2014, 7, 4, 23), + datetime(2014, 7, 5, 4): datetime(2014, 7, 5, 0), + datetime(2014, 7, 7, 3, 30): datetime(2014, 7, 5, 0, 30), + datetime(2014, 7, 7, 19, 30): datetime(2014, 7, 7, 4, 30), + datetime(2014, 7, 7, 19, 30, 30): datetime(2014, 7, 7, 4, 30, 30), + }, + ), + ] + + # long business hours (see gh-26381) + + # multiple business hours + + @pytest.mark.parametrize("case", apply_cases) + def test_apply(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + apply_large_n_cases = [ + ( + # A week later + BusinessHour(40), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 8, 11), + datetime(2014, 7, 1, 13): datetime(2014, 7, 8, 13), + datetime(2014, 7, 1, 15): datetime(2014, 7, 8, 15), + datetime(2014, 7, 1, 16): datetime(2014, 7, 8, 16), + datetime(2014, 7, 1, 17): datetime(2014, 7, 9, 9), + datetime(2014, 7, 2, 11): datetime(2014, 7, 9, 11), + datetime(2014, 7, 2, 8): datetime(2014, 7, 9, 9), + datetime(2014, 7, 2, 19): datetime(2014, 7, 10, 9), + datetime(2014, 7, 2, 23): datetime(2014, 7, 10, 9), + datetime(2014, 7, 3, 0): datetime(2014, 7, 10, 9), + datetime(2014, 7, 5, 15): datetime(2014, 7, 14, 9), + datetime(2014, 7, 4, 18): datetime(2014, 7, 14, 9), + datetime(2014, 7, 7, 9, 30): datetime(2014, 7, 14, 9, 30), + datetime(2014, 7, 7, 9, 30, 30): datetime(2014, 7, 14, 9, 30, 30), + }, + ), + ( + # 3 days and 1 hour before + BusinessHour(-25), + { + datetime(2014, 7, 1, 11): datetime(2014, 6, 26, 10), + datetime(2014, 7, 1, 13): datetime(2014, 6, 26, 12), + datetime(2014, 7, 1, 9): datetime(2014, 6, 25, 16), + datetime(2014, 7, 1, 10): datetime(2014, 6, 25, 17), + datetime(2014, 7, 3, 11): datetime(2014, 6, 30, 10), + datetime(2014, 7, 3, 8): datetime(2014, 6, 27, 16), + datetime(2014, 7, 3, 19): datetime(2014, 6, 30, 16), + datetime(2014, 7, 3, 23): datetime(2014, 6, 30, 16), + datetime(2014, 7, 4, 9): datetime(2014, 6, 30, 16), + datetime(2014, 7, 5, 15): datetime(2014, 7, 1, 16), + datetime(2014, 7, 6, 18): datetime(2014, 7, 1, 16), + datetime(2014, 7, 7, 9, 30): datetime(2014, 7, 1, 16, 30), + datetime(2014, 7, 7, 10, 30, 30): datetime(2014, 7, 2, 9, 30, 30), + }, + ), + ( + # 5 days and 3 hours later + BusinessHour(28, start="21:00", end="02:00"), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 9, 0), + datetime(2014, 7, 1, 22): datetime(2014, 7, 9, 1), + datetime(2014, 7, 1, 23): datetime(2014, 7, 9, 21), + datetime(2014, 7, 2, 2): datetime(2014, 7, 10, 0), + datetime(2014, 7, 3, 21): datetime(2014, 7, 11, 0), + datetime(2014, 7, 4, 1): datetime(2014, 7, 11, 23), + datetime(2014, 7, 4, 2): datetime(2014, 7, 12, 0), + datetime(2014, 7, 4, 3): datetime(2014, 7, 12, 0), + datetime(2014, 7, 5, 1): datetime(2014, 7, 14, 23), + datetime(2014, 7, 5, 15): datetime(2014, 7, 15, 0), + datetime(2014, 7, 6, 18): datetime(2014, 7, 15, 0), + datetime(2014, 7, 7, 1): datetime(2014, 7, 15, 0), + datetime(2014, 7, 7, 23, 30): datetime(2014, 7, 15, 21, 30), + }, + ), + ( + # large n for multiple opening hours (3 days and 1 hour before) + BusinessHour(n=-25, start=["09:00", "14:00"], end=["12:00", "19:00"]), + { + datetime(2014, 7, 1, 11): datetime(2014, 6, 26, 10), + datetime(2014, 7, 1, 13): datetime(2014, 6, 26, 11), + datetime(2014, 7, 1, 9): datetime(2014, 6, 25, 18), + datetime(2014, 7, 1, 10): datetime(2014, 6, 25, 19), + datetime(2014, 7, 3, 11): datetime(2014, 6, 30, 10), + datetime(2014, 7, 3, 8): datetime(2014, 6, 27, 18), + datetime(2014, 7, 3, 19): datetime(2014, 6, 30, 18), + datetime(2014, 7, 3, 23): datetime(2014, 6, 30, 18), + datetime(2014, 7, 4, 9): datetime(2014, 6, 30, 18), + datetime(2014, 7, 5, 15): datetime(2014, 7, 1, 18), + datetime(2014, 7, 6, 18): datetime(2014, 7, 1, 18), + datetime(2014, 7, 7, 9, 30): datetime(2014, 7, 1, 18, 30), + datetime(2014, 7, 7, 10, 30, 30): datetime(2014, 7, 2, 9, 30, 30), + }, + ), + ( + # 5 days and 3 hours later + BusinessHour(28, start=["21:00", "03:00"], end=["01:00", "04:00"]), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 9, 0), + datetime(2014, 7, 1, 22): datetime(2014, 7, 9, 3), + datetime(2014, 7, 1, 23): datetime(2014, 7, 9, 21), + datetime(2014, 7, 2, 2): datetime(2014, 7, 9, 23), + datetime(2014, 7, 3, 21): datetime(2014, 7, 11, 0), + datetime(2014, 7, 4, 1): datetime(2014, 7, 11, 23), + datetime(2014, 7, 4, 2): datetime(2014, 7, 11, 23), + datetime(2014, 7, 4, 3): datetime(2014, 7, 11, 23), + datetime(2014, 7, 4, 21): datetime(2014, 7, 12, 0), + datetime(2014, 7, 5, 0): datetime(2014, 7, 14, 22), + datetime(2014, 7, 5, 1): datetime(2014, 7, 14, 23), + datetime(2014, 7, 5, 15): datetime(2014, 7, 14, 23), + datetime(2014, 7, 6, 18): datetime(2014, 7, 14, 23), + datetime(2014, 7, 7, 1): datetime(2014, 7, 14, 23), + datetime(2014, 7, 7, 23, 30): datetime(2014, 7, 15, 21, 30), + }, + ), + ] + + @pytest.mark.parametrize("case", apply_large_n_cases) + def test_apply_large_n(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + def test_apply_nanoseconds(self): + tests = [ + ( + BusinessHour(), + { + Timestamp("2014-07-04 15:00") + + Nano(5): Timestamp("2014-07-04 16:00") + + Nano(5), + Timestamp("2014-07-04 16:00") + + Nano(5): Timestamp("2014-07-07 09:00") + + Nano(5), + Timestamp("2014-07-04 16:00") + - Nano(5): Timestamp("2014-07-04 17:00") + - Nano(5), + }, + ), + ( + BusinessHour(-1), + { + Timestamp("2014-07-04 15:00") + + Nano(5): Timestamp("2014-07-04 14:00") + + Nano(5), + Timestamp("2014-07-04 10:00") + + Nano(5): Timestamp("2014-07-04 09:00") + + Nano(5), + Timestamp("2014-07-04 10:00") + - Nano(5): Timestamp("2014-07-03 17:00") + - Nano(5), + }, + ), + ] + + for offset, cases in tests: + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + @pytest.mark.parametrize("td_unit", ["s", "ms", "us", "ns"]) + @pytest.mark.parametrize("unit", ["s", "ms", "us", "ns"]) + def test_bday_ignores_timedeltas(self, unit, td_unit): + # GH#55608 + idx = date_range("2010/02/01", "2010/02/10", freq="12h", unit=unit) + td = Timedelta(3, unit="h").as_unit(td_unit) + off = BDay(offset=td) + t1 = idx + off + + exp_unit = tm.get_finest_unit(td.unit, idx.unit) + + expected = DatetimeIndex( + [ + "2010-02-02 03:00:00", + "2010-02-02 15:00:00", + "2010-02-03 03:00:00", + "2010-02-03 15:00:00", + "2010-02-04 03:00:00", + "2010-02-04 15:00:00", + "2010-02-05 03:00:00", + "2010-02-05 15:00:00", + "2010-02-08 03:00:00", + "2010-02-08 15:00:00", + "2010-02-08 03:00:00", + "2010-02-08 15:00:00", + "2010-02-08 03:00:00", + "2010-02-08 15:00:00", + "2010-02-09 03:00:00", + "2010-02-09 15:00:00", + "2010-02-10 03:00:00", + "2010-02-10 15:00:00", + "2010-02-11 03:00:00", + ], + freq=None, + ).as_unit(exp_unit) + tm.assert_index_equal(t1, expected) + + # TODO(GH#55564): as_unit will be unnecessary + pointwise = DatetimeIndex([x + off for x in idx]).as_unit(exp_unit) + tm.assert_index_equal(pointwise, expected) + + def test_add_bday_offset_nanos(self): + # GH#55608 + idx = date_range("2010/02/01", "2010/02/10", freq="12h", unit="ns") + off = BDay(offset=Timedelta(3, unit="ns")) + + result = idx + off + expected = DatetimeIndex([x + off for x in idx]) + tm.assert_index_equal(result, expected) + + +class TestOpeningTimes: + # opening time should be affected by sign of n, not by n's value and end + opening_time_cases = [ + ( + [ + BusinessHour(), + BusinessHour(n=2), + BusinessHour(n=4), + BusinessHour(end="10:00"), + BusinessHour(n=2, end="4:00"), + BusinessHour(n=4, end="15:00"), + ], + { + datetime(2014, 7, 1, 11): ( + datetime(2014, 7, 2, 9), + datetime(2014, 7, 1, 9), + ), + datetime(2014, 7, 1, 18): ( + datetime(2014, 7, 2, 9), + datetime(2014, 7, 1, 9), + ), + datetime(2014, 7, 1, 23): ( + datetime(2014, 7, 2, 9), + datetime(2014, 7, 1, 9), + ), + datetime(2014, 7, 2, 8): ( + datetime(2014, 7, 2, 9), + datetime(2014, 7, 1, 9), + ), + # if timestamp is on opening time, next opening time is + # as it is + datetime(2014, 7, 2, 9): ( + datetime(2014, 7, 2, 9), + datetime(2014, 7, 2, 9), + ), + datetime(2014, 7, 2, 10): ( + datetime(2014, 7, 3, 9), + datetime(2014, 7, 2, 9), + ), + # 2014-07-05 is saturday + datetime(2014, 7, 5, 10): ( + datetime(2014, 7, 7, 9), + datetime(2014, 7, 4, 9), + ), + datetime(2014, 7, 4, 10): ( + datetime(2014, 7, 7, 9), + datetime(2014, 7, 4, 9), + ), + datetime(2014, 7, 4, 23): ( + datetime(2014, 7, 7, 9), + datetime(2014, 7, 4, 9), + ), + datetime(2014, 7, 6, 10): ( + datetime(2014, 7, 7, 9), + datetime(2014, 7, 4, 9), + ), + datetime(2014, 7, 7, 5): ( + datetime(2014, 7, 7, 9), + datetime(2014, 7, 4, 9), + ), + datetime(2014, 7, 7, 9, 1): ( + datetime(2014, 7, 8, 9), + datetime(2014, 7, 7, 9), + ), + }, + ), + ( + [ + BusinessHour(start="11:15"), + BusinessHour(n=2, start="11:15"), + BusinessHour(n=3, start="11:15"), + BusinessHour(start="11:15", end="10:00"), + BusinessHour(n=2, start="11:15", end="4:00"), + BusinessHour(n=3, start="11:15", end="15:00"), + ], + { + datetime(2014, 7, 1, 11): ( + datetime(2014, 7, 1, 11, 15), + datetime(2014, 6, 30, 11, 15), + ), + datetime(2014, 7, 1, 18): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 11, 15), + ), + datetime(2014, 7, 1, 23): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 11, 15), + ), + datetime(2014, 7, 2, 8): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 11, 15), + ), + datetime(2014, 7, 2, 9): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 11, 15), + ), + datetime(2014, 7, 2, 10): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 11, 15), + ), + datetime(2014, 7, 2, 11, 15): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 2, 11, 15), + ), + datetime(2014, 7, 2, 11, 15, 1): ( + datetime(2014, 7, 3, 11, 15), + datetime(2014, 7, 2, 11, 15), + ), + datetime(2014, 7, 5, 10): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 11, 15), + ), + datetime(2014, 7, 4, 10): ( + datetime(2014, 7, 4, 11, 15), + datetime(2014, 7, 3, 11, 15), + ), + datetime(2014, 7, 4, 23): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 11, 15), + ), + datetime(2014, 7, 6, 10): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 11, 15), + ), + datetime(2014, 7, 7, 5): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 11, 15), + ), + datetime(2014, 7, 7, 9, 1): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 11, 15), + ), + }, + ), + ( + [ + BusinessHour(-1), + BusinessHour(n=-2), + BusinessHour(n=-4), + BusinessHour(n=-1, end="10:00"), + BusinessHour(n=-2, end="4:00"), + BusinessHour(n=-4, end="15:00"), + ], + { + datetime(2014, 7, 1, 11): ( + datetime(2014, 7, 1, 9), + datetime(2014, 7, 2, 9), + ), + datetime(2014, 7, 1, 18): ( + datetime(2014, 7, 1, 9), + datetime(2014, 7, 2, 9), + ), + datetime(2014, 7, 1, 23): ( + datetime(2014, 7, 1, 9), + datetime(2014, 7, 2, 9), + ), + datetime(2014, 7, 2, 8): ( + datetime(2014, 7, 1, 9), + datetime(2014, 7, 2, 9), + ), + datetime(2014, 7, 2, 9): ( + datetime(2014, 7, 2, 9), + datetime(2014, 7, 2, 9), + ), + datetime(2014, 7, 2, 10): ( + datetime(2014, 7, 2, 9), + datetime(2014, 7, 3, 9), + ), + datetime(2014, 7, 5, 10): ( + datetime(2014, 7, 4, 9), + datetime(2014, 7, 7, 9), + ), + datetime(2014, 7, 4, 10): ( + datetime(2014, 7, 4, 9), + datetime(2014, 7, 7, 9), + ), + datetime(2014, 7, 4, 23): ( + datetime(2014, 7, 4, 9), + datetime(2014, 7, 7, 9), + ), + datetime(2014, 7, 6, 10): ( + datetime(2014, 7, 4, 9), + datetime(2014, 7, 7, 9), + ), + datetime(2014, 7, 7, 5): ( + datetime(2014, 7, 4, 9), + datetime(2014, 7, 7, 9), + ), + datetime(2014, 7, 7, 9): ( + datetime(2014, 7, 7, 9), + datetime(2014, 7, 7, 9), + ), + datetime(2014, 7, 7, 9, 1): ( + datetime(2014, 7, 7, 9), + datetime(2014, 7, 8, 9), + ), + }, + ), + ( + [ + BusinessHour(start="17:00", end="05:00"), + BusinessHour(n=3, start="17:00", end="03:00"), + ], + { + datetime(2014, 7, 1, 11): ( + datetime(2014, 7, 1, 17), + datetime(2014, 6, 30, 17), + ), + datetime(2014, 7, 1, 18): ( + datetime(2014, 7, 2, 17), + datetime(2014, 7, 1, 17), + ), + datetime(2014, 7, 1, 23): ( + datetime(2014, 7, 2, 17), + datetime(2014, 7, 1, 17), + ), + datetime(2014, 7, 2, 8): ( + datetime(2014, 7, 2, 17), + datetime(2014, 7, 1, 17), + ), + datetime(2014, 7, 2, 9): ( + datetime(2014, 7, 2, 17), + datetime(2014, 7, 1, 17), + ), + datetime(2014, 7, 4, 17): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 4, 17), + ), + datetime(2014, 7, 5, 10): ( + datetime(2014, 7, 7, 17), + datetime(2014, 7, 4, 17), + ), + datetime(2014, 7, 4, 10): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 3, 17), + ), + datetime(2014, 7, 4, 23): ( + datetime(2014, 7, 7, 17), + datetime(2014, 7, 4, 17), + ), + datetime(2014, 7, 6, 10): ( + datetime(2014, 7, 7, 17), + datetime(2014, 7, 4, 17), + ), + datetime(2014, 7, 7, 5): ( + datetime(2014, 7, 7, 17), + datetime(2014, 7, 4, 17), + ), + datetime(2014, 7, 7, 17, 1): ( + datetime(2014, 7, 8, 17), + datetime(2014, 7, 7, 17), + ), + }, + ), + ( + [ + BusinessHour(-1, start="17:00", end="05:00"), + BusinessHour(n=-2, start="17:00", end="03:00"), + ], + { + datetime(2014, 7, 1, 11): ( + datetime(2014, 6, 30, 17), + datetime(2014, 7, 1, 17), + ), + datetime(2014, 7, 1, 18): ( + datetime(2014, 7, 1, 17), + datetime(2014, 7, 2, 17), + ), + datetime(2014, 7, 1, 23): ( + datetime(2014, 7, 1, 17), + datetime(2014, 7, 2, 17), + ), + datetime(2014, 7, 2, 8): ( + datetime(2014, 7, 1, 17), + datetime(2014, 7, 2, 17), + ), + datetime(2014, 7, 2, 9): ( + datetime(2014, 7, 1, 17), + datetime(2014, 7, 2, 17), + ), + datetime(2014, 7, 2, 16, 59): ( + datetime(2014, 7, 1, 17), + datetime(2014, 7, 2, 17), + ), + datetime(2014, 7, 5, 10): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 17), + ), + datetime(2014, 7, 4, 10): ( + datetime(2014, 7, 3, 17), + datetime(2014, 7, 4, 17), + ), + datetime(2014, 7, 4, 23): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 17), + ), + datetime(2014, 7, 6, 10): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 17), + ), + datetime(2014, 7, 7, 5): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 17), + ), + datetime(2014, 7, 7, 18): ( + datetime(2014, 7, 7, 17), + datetime(2014, 7, 8, 17), + ), + }, + ), + ( + [ + BusinessHour(start=["11:15", "15:00"], end=["13:00", "20:00"]), + BusinessHour(n=3, start=["11:15", "15:00"], end=["12:00", "20:00"]), + BusinessHour(start=["11:15", "15:00"], end=["13:00", "17:00"]), + BusinessHour(n=2, start=["11:15", "15:00"], end=["12:00", "03:00"]), + BusinessHour(n=3, start=["11:15", "15:00"], end=["13:00", "16:00"]), + ], + { + datetime(2014, 7, 1, 11): ( + datetime(2014, 7, 1, 11, 15), + datetime(2014, 6, 30, 15), + ), + datetime(2014, 7, 1, 18): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 15), + ), + datetime(2014, 7, 1, 23): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 15), + ), + datetime(2014, 7, 2, 8): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 15), + ), + datetime(2014, 7, 2, 9): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 15), + ), + datetime(2014, 7, 2, 10): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 1, 15), + ), + datetime(2014, 7, 2, 11, 15): ( + datetime(2014, 7, 2, 11, 15), + datetime(2014, 7, 2, 11, 15), + ), + datetime(2014, 7, 2, 11, 15, 1): ( + datetime(2014, 7, 2, 15), + datetime(2014, 7, 2, 11, 15), + ), + datetime(2014, 7, 5, 10): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 15), + ), + datetime(2014, 7, 4, 10): ( + datetime(2014, 7, 4, 11, 15), + datetime(2014, 7, 3, 15), + ), + datetime(2014, 7, 4, 23): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 15), + ), + datetime(2014, 7, 6, 10): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 15), + ), + datetime(2014, 7, 7, 5): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 15), + ), + datetime(2014, 7, 7, 9, 1): ( + datetime(2014, 7, 7, 11, 15), + datetime(2014, 7, 4, 15), + ), + datetime(2014, 7, 7, 12): ( + datetime(2014, 7, 7, 15), + datetime(2014, 7, 7, 11, 15), + ), + }, + ), + ( + [ + BusinessHour(n=-1, start=["17:00", "08:00"], end=["05:00", "10:00"]), + BusinessHour(n=-2, start=["08:00", "17:00"], end=["10:00", "03:00"]), + ], + { + datetime(2014, 7, 1, 11): ( + datetime(2014, 7, 1, 8), + datetime(2014, 7, 1, 17), + ), + datetime(2014, 7, 1, 18): ( + datetime(2014, 7, 1, 17), + datetime(2014, 7, 2, 8), + ), + datetime(2014, 7, 1, 23): ( + datetime(2014, 7, 1, 17), + datetime(2014, 7, 2, 8), + ), + datetime(2014, 7, 2, 8): ( + datetime(2014, 7, 2, 8), + datetime(2014, 7, 2, 8), + ), + datetime(2014, 7, 2, 9): ( + datetime(2014, 7, 2, 8), + datetime(2014, 7, 2, 17), + ), + datetime(2014, 7, 2, 16, 59): ( + datetime(2014, 7, 2, 8), + datetime(2014, 7, 2, 17), + ), + datetime(2014, 7, 5, 10): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 8), + ), + datetime(2014, 7, 4, 10): ( + datetime(2014, 7, 4, 8), + datetime(2014, 7, 4, 17), + ), + datetime(2014, 7, 4, 23): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 8), + ), + datetime(2014, 7, 6, 10): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 8), + ), + datetime(2014, 7, 7, 5): ( + datetime(2014, 7, 4, 17), + datetime(2014, 7, 7, 8), + ), + datetime(2014, 7, 7, 18): ( + datetime(2014, 7, 7, 17), + datetime(2014, 7, 8, 8), + ), + }, + ), + ] + + @pytest.mark.parametrize("case", opening_time_cases) + def test_opening_time(self, case): + _offsets, cases = case + for offset in _offsets: + for dt, (exp_next, exp_prev) in cases.items(): + assert offset._next_opening_time(dt) == exp_next + assert offset._prev_opening_time(dt) == exp_prev diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_month.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_month.py new file mode 100644 index 0000000000000000000000000000000000000000..a14451e60aa89f3a74f52add62a53759027edd21 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_month.py @@ -0,0 +1,217 @@ +""" +Tests for the following offsets: +- BMonthBegin +- BMonthEnd +""" +from __future__ import annotations + +from datetime import datetime + +import pytest + +import pandas as pd +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries.offsets import ( + BMonthBegin, + BMonthEnd, +) + + +@pytest.mark.parametrize("n", [-2, 1]) +@pytest.mark.parametrize( + "cls", + [ + BMonthBegin, + BMonthEnd, + ], +) +def test_apply_index(cls, n): + offset = cls(n=n) + rng = pd.date_range(start="1/1/2000", periods=100000, freq="min") + ser = pd.Series(rng) + + res = rng + offset + assert res.freq is None # not retained + assert res[0] == rng[0] + offset + assert res[-1] == rng[-1] + offset + res2 = ser + offset + # apply_index is only for indexes, not series, so no res2_v2 + assert res2.iloc[0] == ser.iloc[0] + offset + assert res2.iloc[-1] == ser.iloc[-1] + offset + + +class TestBMonthBegin: + def test_offsets_compare_equal(self): + # root cause of #456 + offset1 = BMonthBegin() + offset2 = BMonthBegin() + assert not offset1 != offset2 + + offset_cases = [] + offset_cases.append( + ( + BMonthBegin(), + { + datetime(2008, 1, 1): datetime(2008, 2, 1), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2006, 12, 29): datetime(2007, 1, 1), + datetime(2006, 12, 31): datetime(2007, 1, 1), + datetime(2006, 9, 1): datetime(2006, 10, 2), + datetime(2007, 1, 1): datetime(2007, 2, 1), + datetime(2006, 12, 1): datetime(2007, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + BMonthBegin(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2006, 10, 2): datetime(2006, 10, 2), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2006, 12, 29): datetime(2007, 1, 1), + datetime(2006, 12, 31): datetime(2007, 1, 1), + datetime(2006, 9, 15): datetime(2006, 10, 2), + }, + ) + ) + + offset_cases.append( + ( + BMonthBegin(2), + { + datetime(2008, 1, 1): datetime(2008, 3, 3), + datetime(2008, 1, 15): datetime(2008, 3, 3), + datetime(2006, 12, 29): datetime(2007, 2, 1), + datetime(2006, 12, 31): datetime(2007, 2, 1), + datetime(2007, 1, 1): datetime(2007, 3, 1), + datetime(2006, 11, 1): datetime(2007, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + BMonthBegin(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 1), + datetime(2008, 6, 30): datetime(2008, 6, 2), + datetime(2008, 6, 1): datetime(2008, 5, 1), + datetime(2008, 3, 10): datetime(2008, 3, 3), + datetime(2008, 12, 31): datetime(2008, 12, 1), + datetime(2006, 12, 29): datetime(2006, 12, 1), + datetime(2006, 12, 30): datetime(2006, 12, 1), + datetime(2007, 1, 1): datetime(2006, 12, 1), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (BMonthBegin(), datetime(2007, 12, 31), False), + (BMonthBegin(), datetime(2008, 1, 1), True), + (BMonthBegin(), datetime(2001, 4, 2), True), + (BMonthBegin(), datetime(2008, 3, 3), True), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + +class TestBMonthEnd: + def test_normalize(self): + dt = datetime(2007, 1, 1, 3) + + result = dt + BMonthEnd(normalize=True) + expected = dt.replace(hour=0) + BMonthEnd() + assert result == expected + + def test_offsets_compare_equal(self): + # root cause of #456 + offset1 = BMonthEnd() + offset2 = BMonthEnd() + assert not offset1 != offset2 + + offset_cases = [] + offset_cases.append( + ( + BMonthEnd(), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 2, 29), + datetime(2006, 12, 29): datetime(2007, 1, 31), + datetime(2006, 12, 31): datetime(2007, 1, 31), + datetime(2007, 1, 1): datetime(2007, 1, 31), + datetime(2006, 12, 1): datetime(2006, 12, 29), + }, + ) + ) + + offset_cases.append( + ( + BMonthEnd(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 1, 31), + datetime(2006, 12, 29): datetime(2006, 12, 29), + datetime(2006, 12, 31): datetime(2007, 1, 31), + datetime(2007, 1, 1): datetime(2007, 1, 31), + }, + ) + ) + + offset_cases.append( + ( + BMonthEnd(2), + { + datetime(2008, 1, 1): datetime(2008, 2, 29), + datetime(2008, 1, 31): datetime(2008, 3, 31), + datetime(2006, 12, 29): datetime(2007, 2, 28), + datetime(2006, 12, 31): datetime(2007, 2, 28), + datetime(2007, 1, 1): datetime(2007, 2, 28), + datetime(2006, 11, 1): datetime(2006, 12, 29), + }, + ) + ) + + offset_cases.append( + ( + BMonthEnd(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 29), + datetime(2008, 6, 30): datetime(2008, 5, 30), + datetime(2008, 12, 31): datetime(2008, 11, 28), + datetime(2006, 12, 29): datetime(2006, 11, 30), + datetime(2006, 12, 30): datetime(2006, 12, 29), + datetime(2007, 1, 1): datetime(2006, 12, 29), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (BMonthEnd(), datetime(2007, 12, 31), True), + (BMonthEnd(), datetime(2008, 1, 1), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_quarter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_quarter.py new file mode 100644 index 0000000000000000000000000000000000000000..6d7a115054b7f20e3ab024eb31f266c18920f2c5 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_quarter.py @@ -0,0 +1,315 @@ +""" +Tests for the following offsets: +- BQuarterBegin +- BQuarterEnd +""" +from __future__ import annotations + +from datetime import datetime + +import pytest + +import pandas._testing as tm +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries.offsets import ( + BQuarterBegin, + BQuarterEnd, +) + + +def test_quarterly_dont_normalize(): + date = datetime(2012, 3, 31, 5, 30) + + offsets = (BQuarterEnd, BQuarterBegin) + + for klass in offsets: + result = date + klass() + assert result.time() == date.time() + + +@pytest.mark.parametrize("offset", [BQuarterBegin(), BQuarterEnd()]) +def test_on_offset(offset): + dates = [ + datetime(2016, m, d) + for m in [10, 11, 12] + for d in [1, 2, 3, 28, 29, 30, 31] + if not (m == 11 and d == 31) + ] + for date in dates: + res = offset.is_on_offset(date) + slow_version = date == (date + offset) - offset + assert res == slow_version + + +class TestBQuarterBegin: + def test_repr(self): + expected = "" + assert repr(BQuarterBegin()) == expected + expected = "" + assert repr(BQuarterBegin(startingMonth=3)) == expected + expected = "" + assert repr(BQuarterBegin(startingMonth=1)) == expected + + def test_is_anchored(self): + msg = "BQuarterBegin.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert BQuarterBegin(startingMonth=1).is_anchored() + assert BQuarterBegin().is_anchored() + assert not BQuarterBegin(2, startingMonth=1).is_anchored() + + def test_offset_corner_case(self): + # corner + offset = BQuarterBegin(n=-1, startingMonth=1) + assert datetime(2007, 4, 3) + offset == datetime(2007, 4, 2) + + offset_cases = [] + offset_cases.append( + ( + BQuarterBegin(startingMonth=1), + { + datetime(2008, 1, 1): datetime(2008, 4, 1), + datetime(2008, 1, 31): datetime(2008, 4, 1), + datetime(2008, 2, 15): datetime(2008, 4, 1), + datetime(2008, 2, 29): datetime(2008, 4, 1), + datetime(2008, 3, 15): datetime(2008, 4, 1), + datetime(2008, 3, 31): datetime(2008, 4, 1), + datetime(2008, 4, 15): datetime(2008, 7, 1), + datetime(2007, 3, 15): datetime(2007, 4, 2), + datetime(2007, 2, 28): datetime(2007, 4, 2), + datetime(2007, 1, 1): datetime(2007, 4, 2), + datetime(2007, 4, 15): datetime(2007, 7, 2), + datetime(2007, 7, 1): datetime(2007, 7, 2), + datetime(2007, 4, 1): datetime(2007, 4, 2), + datetime(2007, 4, 2): datetime(2007, 7, 2), + datetime(2008, 4, 30): datetime(2008, 7, 1), + }, + ) + ) + + offset_cases.append( + ( + BQuarterBegin(startingMonth=2), + { + datetime(2008, 1, 1): datetime(2008, 2, 1), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2008, 1, 15): datetime(2008, 2, 1), + datetime(2008, 2, 29): datetime(2008, 5, 1), + datetime(2008, 3, 15): datetime(2008, 5, 1), + datetime(2008, 3, 31): datetime(2008, 5, 1), + datetime(2008, 4, 15): datetime(2008, 5, 1), + datetime(2008, 8, 15): datetime(2008, 11, 3), + datetime(2008, 9, 15): datetime(2008, 11, 3), + datetime(2008, 11, 1): datetime(2008, 11, 3), + datetime(2008, 4, 30): datetime(2008, 5, 1), + }, + ) + ) + + offset_cases.append( + ( + BQuarterBegin(startingMonth=1, n=0), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2007, 12, 31): datetime(2008, 1, 1), + datetime(2008, 2, 15): datetime(2008, 4, 1), + datetime(2008, 2, 29): datetime(2008, 4, 1), + datetime(2008, 1, 15): datetime(2008, 4, 1), + datetime(2008, 2, 27): datetime(2008, 4, 1), + datetime(2008, 3, 15): datetime(2008, 4, 1), + datetime(2007, 4, 1): datetime(2007, 4, 2), + datetime(2007, 4, 2): datetime(2007, 4, 2), + datetime(2007, 7, 1): datetime(2007, 7, 2), + datetime(2007, 4, 15): datetime(2007, 7, 2), + datetime(2007, 7, 2): datetime(2007, 7, 2), + }, + ) + ) + + offset_cases.append( + ( + BQuarterBegin(startingMonth=1, n=-1), + { + datetime(2008, 1, 1): datetime(2007, 10, 1), + datetime(2008, 1, 31): datetime(2008, 1, 1), + datetime(2008, 2, 15): datetime(2008, 1, 1), + datetime(2008, 2, 29): datetime(2008, 1, 1), + datetime(2008, 3, 15): datetime(2008, 1, 1), + datetime(2008, 3, 31): datetime(2008, 1, 1), + datetime(2008, 4, 15): datetime(2008, 4, 1), + datetime(2007, 7, 3): datetime(2007, 7, 2), + datetime(2007, 4, 3): datetime(2007, 4, 2), + datetime(2007, 7, 2): datetime(2007, 4, 2), + datetime(2008, 4, 1): datetime(2008, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + BQuarterBegin(startingMonth=1, n=2), + { + datetime(2008, 1, 1): datetime(2008, 7, 1), + datetime(2008, 1, 15): datetime(2008, 7, 1), + datetime(2008, 2, 29): datetime(2008, 7, 1), + datetime(2008, 3, 15): datetime(2008, 7, 1), + datetime(2007, 3, 31): datetime(2007, 7, 2), + datetime(2007, 4, 15): datetime(2007, 10, 1), + datetime(2008, 4, 30): datetime(2008, 10, 1), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + +class TestBQuarterEnd: + def test_repr(self): + expected = "" + assert repr(BQuarterEnd()) == expected + expected = "" + assert repr(BQuarterEnd(startingMonth=3)) == expected + expected = "" + assert repr(BQuarterEnd(startingMonth=1)) == expected + + def test_is_anchored(self): + msg = "BQuarterEnd.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert BQuarterEnd(startingMonth=1).is_anchored() + assert BQuarterEnd().is_anchored() + assert not BQuarterEnd(2, startingMonth=1).is_anchored() + + def test_offset_corner_case(self): + # corner + offset = BQuarterEnd(n=-1, startingMonth=1) + assert datetime(2010, 1, 31) + offset == datetime(2010, 1, 29) + + offset_cases = [] + offset_cases.append( + ( + BQuarterEnd(startingMonth=1), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 4, 30), + datetime(2008, 2, 15): datetime(2008, 4, 30), + datetime(2008, 2, 29): datetime(2008, 4, 30), + datetime(2008, 3, 15): datetime(2008, 4, 30), + datetime(2008, 3, 31): datetime(2008, 4, 30), + datetime(2008, 4, 15): datetime(2008, 4, 30), + datetime(2008, 4, 30): datetime(2008, 7, 31), + }, + ) + ) + + offset_cases.append( + ( + BQuarterEnd(startingMonth=2), + { + datetime(2008, 1, 1): datetime(2008, 2, 29), + datetime(2008, 1, 31): datetime(2008, 2, 29), + datetime(2008, 2, 15): datetime(2008, 2, 29), + datetime(2008, 2, 29): datetime(2008, 5, 30), + datetime(2008, 3, 15): datetime(2008, 5, 30), + datetime(2008, 3, 31): datetime(2008, 5, 30), + datetime(2008, 4, 15): datetime(2008, 5, 30), + datetime(2008, 4, 30): datetime(2008, 5, 30), + }, + ) + ) + + offset_cases.append( + ( + BQuarterEnd(startingMonth=1, n=0), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 1, 31), + datetime(2008, 2, 15): datetime(2008, 4, 30), + datetime(2008, 2, 29): datetime(2008, 4, 30), + datetime(2008, 3, 15): datetime(2008, 4, 30), + datetime(2008, 3, 31): datetime(2008, 4, 30), + datetime(2008, 4, 15): datetime(2008, 4, 30), + datetime(2008, 4, 30): datetime(2008, 4, 30), + }, + ) + ) + + offset_cases.append( + ( + BQuarterEnd(startingMonth=1, n=-1), + { + datetime(2008, 1, 1): datetime(2007, 10, 31), + datetime(2008, 1, 31): datetime(2007, 10, 31), + datetime(2008, 2, 15): datetime(2008, 1, 31), + datetime(2008, 2, 29): datetime(2008, 1, 31), + datetime(2008, 3, 15): datetime(2008, 1, 31), + datetime(2008, 3, 31): datetime(2008, 1, 31), + datetime(2008, 4, 15): datetime(2008, 1, 31), + datetime(2008, 4, 30): datetime(2008, 1, 31), + }, + ) + ) + + offset_cases.append( + ( + BQuarterEnd(startingMonth=1, n=2), + { + datetime(2008, 1, 31): datetime(2008, 7, 31), + datetime(2008, 2, 15): datetime(2008, 7, 31), + datetime(2008, 2, 29): datetime(2008, 7, 31), + datetime(2008, 3, 15): datetime(2008, 7, 31), + datetime(2008, 3, 31): datetime(2008, 7, 31), + datetime(2008, 4, 15): datetime(2008, 7, 31), + datetime(2008, 4, 30): datetime(2008, 10, 31), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (BQuarterEnd(1, startingMonth=1), datetime(2008, 1, 31), True), + (BQuarterEnd(1, startingMonth=1), datetime(2007, 12, 31), False), + (BQuarterEnd(1, startingMonth=1), datetime(2008, 2, 29), False), + (BQuarterEnd(1, startingMonth=1), datetime(2007, 3, 30), False), + (BQuarterEnd(1, startingMonth=1), datetime(2007, 3, 31), False), + (BQuarterEnd(1, startingMonth=1), datetime(2008, 4, 30), True), + (BQuarterEnd(1, startingMonth=1), datetime(2008, 5, 30), False), + (BQuarterEnd(1, startingMonth=1), datetime(2007, 6, 29), False), + (BQuarterEnd(1, startingMonth=1), datetime(2007, 6, 30), False), + (BQuarterEnd(1, startingMonth=2), datetime(2008, 1, 31), False), + (BQuarterEnd(1, startingMonth=2), datetime(2007, 12, 31), False), + (BQuarterEnd(1, startingMonth=2), datetime(2008, 2, 29), True), + (BQuarterEnd(1, startingMonth=2), datetime(2007, 3, 30), False), + (BQuarterEnd(1, startingMonth=2), datetime(2007, 3, 31), False), + (BQuarterEnd(1, startingMonth=2), datetime(2008, 4, 30), False), + (BQuarterEnd(1, startingMonth=2), datetime(2008, 5, 30), True), + (BQuarterEnd(1, startingMonth=2), datetime(2007, 6, 29), False), + (BQuarterEnd(1, startingMonth=2), datetime(2007, 6, 30), False), + (BQuarterEnd(1, startingMonth=3), datetime(2008, 1, 31), False), + (BQuarterEnd(1, startingMonth=3), datetime(2007, 12, 31), True), + (BQuarterEnd(1, startingMonth=3), datetime(2008, 2, 29), False), + (BQuarterEnd(1, startingMonth=3), datetime(2007, 3, 30), True), + (BQuarterEnd(1, startingMonth=3), datetime(2007, 3, 31), False), + (BQuarterEnd(1, startingMonth=3), datetime(2008, 4, 30), False), + (BQuarterEnd(1, startingMonth=3), datetime(2008, 5, 30), False), + (BQuarterEnd(1, startingMonth=3), datetime(2007, 6, 29), True), + (BQuarterEnd(1, startingMonth=3), datetime(2007, 6, 30), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_year.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_year.py new file mode 100644 index 0000000000000000000000000000000000000000..3b7a1025cc19c9c1c966b9448ceffdb12dcd8159 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_business_year.py @@ -0,0 +1,215 @@ +""" +Tests for the following offsets: +- BYearBegin +- BYearEnd +""" +from __future__ import annotations + +from datetime import datetime + +import pytest + +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries.offsets import ( + BYearBegin, + BYearEnd, +) + + +class TestBYearBegin: + def test_misspecified(self): + msg = "Month must go from 1 to 12" + with pytest.raises(ValueError, match=msg): + BYearBegin(month=13) + with pytest.raises(ValueError, match=msg): + BYearEnd(month=13) + + offset_cases = [] + offset_cases.append( + ( + BYearBegin(), + { + datetime(2008, 1, 1): datetime(2009, 1, 1), + datetime(2008, 6, 30): datetime(2009, 1, 1), + datetime(2008, 12, 31): datetime(2009, 1, 1), + datetime(2011, 1, 1): datetime(2011, 1, 3), + datetime(2011, 1, 3): datetime(2012, 1, 2), + datetime(2005, 12, 30): datetime(2006, 1, 2), + datetime(2005, 12, 31): datetime(2006, 1, 2), + }, + ) + ) + + offset_cases.append( + ( + BYearBegin(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 6, 30): datetime(2009, 1, 1), + datetime(2008, 12, 31): datetime(2009, 1, 1), + datetime(2005, 12, 30): datetime(2006, 1, 2), + datetime(2005, 12, 31): datetime(2006, 1, 2), + }, + ) + ) + + offset_cases.append( + ( + BYearBegin(-1), + { + datetime(2007, 1, 1): datetime(2006, 1, 2), + datetime(2009, 1, 4): datetime(2009, 1, 1), + datetime(2009, 1, 1): datetime(2008, 1, 1), + datetime(2008, 6, 30): datetime(2008, 1, 1), + datetime(2008, 12, 31): datetime(2008, 1, 1), + datetime(2006, 12, 29): datetime(2006, 1, 2), + datetime(2006, 12, 30): datetime(2006, 1, 2), + datetime(2006, 1, 1): datetime(2005, 1, 3), + }, + ) + ) + + offset_cases.append( + ( + BYearBegin(-2), + { + datetime(2007, 1, 1): datetime(2005, 1, 3), + datetime(2007, 6, 30): datetime(2006, 1, 2), + datetime(2008, 12, 31): datetime(2007, 1, 1), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + +class TestBYearEnd: + offset_cases = [] + offset_cases.append( + ( + BYearEnd(), + { + datetime(2008, 1, 1): datetime(2008, 12, 31), + datetime(2008, 6, 30): datetime(2008, 12, 31), + datetime(2008, 12, 31): datetime(2009, 12, 31), + datetime(2005, 12, 30): datetime(2006, 12, 29), + datetime(2005, 12, 31): datetime(2006, 12, 29), + }, + ) + ) + + offset_cases.append( + ( + BYearEnd(0), + { + datetime(2008, 1, 1): datetime(2008, 12, 31), + datetime(2008, 6, 30): datetime(2008, 12, 31), + datetime(2008, 12, 31): datetime(2008, 12, 31), + datetime(2005, 12, 31): datetime(2006, 12, 29), + }, + ) + ) + + offset_cases.append( + ( + BYearEnd(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 29), + datetime(2008, 6, 30): datetime(2007, 12, 31), + datetime(2008, 12, 31): datetime(2007, 12, 31), + datetime(2006, 12, 29): datetime(2005, 12, 30), + datetime(2006, 12, 30): datetime(2006, 12, 29), + datetime(2007, 1, 1): datetime(2006, 12, 29), + }, + ) + ) + + offset_cases.append( + ( + BYearEnd(-2), + { + datetime(2007, 1, 1): datetime(2005, 12, 30), + datetime(2008, 6, 30): datetime(2006, 12, 29), + datetime(2008, 12, 31): datetime(2006, 12, 29), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (BYearEnd(), datetime(2007, 12, 31), True), + (BYearEnd(), datetime(2008, 1, 1), False), + (BYearEnd(), datetime(2006, 12, 31), False), + (BYearEnd(), datetime(2006, 12, 29), True), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + +class TestBYearEndLagged: + def test_bad_month_fail(self): + msg = "Month must go from 1 to 12" + with pytest.raises(ValueError, match=msg): + BYearEnd(month=13) + with pytest.raises(ValueError, match=msg): + BYearEnd(month=0) + + offset_cases = [] + offset_cases.append( + ( + BYearEnd(month=6), + { + datetime(2008, 1, 1): datetime(2008, 6, 30), + datetime(2007, 6, 30): datetime(2008, 6, 30), + }, + ) + ) + + offset_cases.append( + ( + BYearEnd(n=-1, month=6), + { + datetime(2008, 1, 1): datetime(2007, 6, 29), + datetime(2007, 6, 30): datetime(2007, 6, 29), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + def test_roll(self): + offset = BYearEnd(month=6) + date = datetime(2009, 11, 30) + + assert offset.rollforward(date) == datetime(2010, 6, 30) + assert offset.rollback(date) == datetime(2009, 6, 30) + + on_offset_cases = [ + (BYearEnd(month=2), datetime(2007, 2, 28), True), + (BYearEnd(month=6), datetime(2007, 6, 30), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_common.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_common.py new file mode 100644 index 0000000000000000000000000000000000000000..aa4e22f71ad66147d5b9893ead4dc250d1de0ed3 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_common.py @@ -0,0 +1,268 @@ +from datetime import datetime + +from dateutil.tz.tz import tzlocal +import pytest + +from pandas._libs.tslibs import ( + OutOfBoundsDatetime, + Timestamp, +) +from pandas.compat import ( + IS64, + is_platform_windows, +) + +from pandas.tseries.offsets import ( + FY5253, + BDay, + BMonthBegin, + BMonthEnd, + BQuarterBegin, + BQuarterEnd, + BusinessHour, + BYearBegin, + BYearEnd, + CBMonthBegin, + CBMonthEnd, + CDay, + CustomBusinessHour, + DateOffset, + FY5253Quarter, + LastWeekOfMonth, + MonthBegin, + MonthEnd, + QuarterEnd, + SemiMonthBegin, + SemiMonthEnd, + Week, + WeekOfMonth, + YearBegin, + YearEnd, +) + + +def _get_offset(klass, value=1, normalize=False): + # create instance from offset class + if klass is FY5253: + klass = klass( + n=value, + startingMonth=1, + weekday=1, + variation="last", + normalize=normalize, + ) + elif klass is FY5253Quarter: + klass = klass( + n=value, + startingMonth=1, + weekday=1, + qtr_with_extra_week=1, + variation="last", + normalize=normalize, + ) + elif klass is LastWeekOfMonth: + klass = klass(n=value, weekday=5, normalize=normalize) + elif klass is WeekOfMonth: + klass = klass(n=value, week=1, weekday=5, normalize=normalize) + elif klass is Week: + klass = klass(n=value, weekday=5, normalize=normalize) + elif klass is DateOffset: + klass = klass(days=value, normalize=normalize) + else: + klass = klass(value, normalize=normalize) + return klass + + +@pytest.fixture( + params=[ + BDay, + BusinessHour, + BMonthEnd, + BMonthBegin, + BQuarterEnd, + BQuarterBegin, + BYearEnd, + BYearBegin, + CDay, + CustomBusinessHour, + CBMonthEnd, + CBMonthBegin, + MonthEnd, + MonthBegin, + SemiMonthBegin, + SemiMonthEnd, + QuarterEnd, + LastWeekOfMonth, + WeekOfMonth, + Week, + YearBegin, + YearEnd, + FY5253, + FY5253Quarter, + DateOffset, + ] +) +def _offset(request): + return request.param + + +@pytest.fixture +def dt(_offset): + if _offset in (CBMonthBegin, CBMonthEnd, BDay): + return Timestamp(2008, 1, 1) + elif _offset is (CustomBusinessHour, BusinessHour): + return Timestamp(2014, 7, 1, 10, 00) + return Timestamp(2008, 1, 2) + + +def test_apply_out_of_range(request, tz_naive_fixture, _offset): + tz = tz_naive_fixture + + # try to create an out-of-bounds result timestamp; if we can't create + # the offset skip + try: + if _offset in (BusinessHour, CustomBusinessHour): + # Using 10000 in BusinessHour fails in tz check because of DST + # difference + offset = _get_offset(_offset, value=100000) + else: + offset = _get_offset(_offset, value=10000) + + result = Timestamp("20080101") + offset + assert isinstance(result, datetime) + assert result.tzinfo is None + + # Check tz is preserved + t = Timestamp("20080101", tz=tz) + result = t + offset + assert isinstance(result, datetime) + if tz is not None: + assert t.tzinfo is not None + + if isinstance(tz, tzlocal) and not IS64 and _offset is not DateOffset: + # If we hit OutOfBoundsDatetime on non-64 bit machines + # we'll drop out of the try clause before the next test + request.applymarker( + pytest.mark.xfail(reason="OverflowError inside tzlocal past 2038") + ) + elif ( + isinstance(tz, tzlocal) + and is_platform_windows() + and _offset in (QuarterEnd, BQuarterBegin, BQuarterEnd) + ): + request.applymarker( + pytest.mark.xfail(reason="After GH#49737 t.tzinfo is None on CI") + ) + assert str(t.tzinfo) == str(result.tzinfo) + + except OutOfBoundsDatetime: + pass + except (ValueError, KeyError): + # we are creating an invalid offset + # so ignore + pass + + +def test_offsets_compare_equal(_offset): + # root cause of GH#456: __ne__ was not implemented + offset1 = _offset() + offset2 = _offset() + assert not offset1 != offset2 + assert offset1 == offset2 + + +@pytest.mark.parametrize( + "date, offset2", + [ + [Timestamp(2008, 1, 1), BDay(2)], + [Timestamp(2014, 7, 1, 10, 00), BusinessHour(n=3)], + [ + Timestamp(2014, 7, 1, 10), + CustomBusinessHour( + holidays=["2014-06-27", Timestamp(2014, 6, 30), Timestamp("2014-07-02")] + ), + ], + [Timestamp(2008, 1, 2), SemiMonthEnd(2)], + [Timestamp(2008, 1, 2), SemiMonthBegin(2)], + [Timestamp(2008, 1, 2), Week(2)], + [Timestamp(2008, 1, 2), WeekOfMonth(2)], + [Timestamp(2008, 1, 2), LastWeekOfMonth(2)], + ], +) +def test_rsub(date, offset2): + assert date - offset2 == (-offset2)._apply(date) + + +@pytest.mark.parametrize( + "date, offset2", + [ + [Timestamp(2008, 1, 1), BDay(2)], + [Timestamp(2014, 7, 1, 10, 00), BusinessHour(n=3)], + [ + Timestamp(2014, 7, 1, 10), + CustomBusinessHour( + holidays=["2014-06-27", Timestamp(2014, 6, 30), Timestamp("2014-07-02")] + ), + ], + [Timestamp(2008, 1, 2), SemiMonthEnd(2)], + [Timestamp(2008, 1, 2), SemiMonthBegin(2)], + [Timestamp(2008, 1, 2), Week(2)], + [Timestamp(2008, 1, 2), WeekOfMonth(2)], + [Timestamp(2008, 1, 2), LastWeekOfMonth(2)], + ], +) +def test_radd(date, offset2): + assert date + offset2 == offset2 + date + + +@pytest.mark.parametrize( + "date, offset_box, offset2", + [ + [Timestamp(2008, 1, 1), BDay, BDay(2)], + [Timestamp(2008, 1, 2), SemiMonthEnd, SemiMonthEnd(2)], + [Timestamp(2008, 1, 2), SemiMonthBegin, SemiMonthBegin(2)], + [Timestamp(2008, 1, 2), Week, Week(2)], + [Timestamp(2008, 1, 2), WeekOfMonth, WeekOfMonth(2)], + [Timestamp(2008, 1, 2), LastWeekOfMonth, LastWeekOfMonth(2)], + ], +) +def test_sub(date, offset_box, offset2): + off = offset2 + msg = "Cannot subtract datetime from offset" + with pytest.raises(TypeError, match=msg): + off - date + + assert 2 * off - off == off + assert date - offset2 == date + offset_box(-2) + assert date - offset2 == date - (2 * off - off) + + +@pytest.mark.parametrize( + "offset_box, offset1", + [ + [BDay, BDay()], + [LastWeekOfMonth, LastWeekOfMonth()], + [WeekOfMonth, WeekOfMonth()], + [Week, Week()], + [SemiMonthBegin, SemiMonthBegin()], + [SemiMonthEnd, SemiMonthEnd()], + [CustomBusinessHour, CustomBusinessHour(weekmask="Tue Wed Thu Fri")], + [BusinessHour, BusinessHour()], + ], +) +def test_Mult1(offset_box, offset1): + dt = Timestamp(2008, 1, 2) + assert dt + 10 * offset1 == dt + offset_box(10) + assert dt + 5 * offset1 == dt + offset_box(5) + + +def test_compare_str(_offset): + # GH#23524 + # comparing to strings that cannot be cast to DateOffsets should + # not raise for __eq__ or __ne__ + off = _get_offset(_offset) + + assert not off == "infer" + assert off != "foo" + # Note: inequalities are only implemented for Tick subclasses; + # tests for this are in test_ticks diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_day.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_day.py new file mode 100644 index 0000000000000000000000000000000000000000..519fb712d041534b6e96e41539fb7660e6c14114 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_day.py @@ -0,0 +1,98 @@ +""" +Tests for offsets.CustomBusinessDay / CDay +""" +from datetime import ( + datetime, + timedelta, +) + +import numpy as np +import pytest + +from pandas._libs.tslibs.offsets import CDay + +from pandas import ( + _testing as tm, + read_pickle, +) +from pandas.tests.tseries.offsets.common import assert_offset_equal + +from pandas.tseries.holiday import USFederalHolidayCalendar + + +@pytest.fixture +def offset(): + return CDay() + + +@pytest.fixture +def offset2(): + return CDay(2) + + +class TestCustomBusinessDay: + def test_repr(self, offset, offset2): + assert repr(offset) == "" + assert repr(offset2) == "<2 * CustomBusinessDays>" + + expected = "" + assert repr(offset + timedelta(1)) == expected + + def test_holidays(self): + # Define a TradingDay offset + holidays = ["2012-05-01", datetime(2013, 5, 1), np.datetime64("2014-05-01")] + tday = CDay(holidays=holidays) + for year in range(2012, 2015): + dt = datetime(year, 4, 30) + xp = datetime(year, 5, 2) + rs = dt + tday + assert rs == xp + + def test_weekmask(self): + weekmask_saudi = "Sat Sun Mon Tue Wed" # Thu-Fri Weekend + weekmask_uae = "1111001" # Fri-Sat Weekend + weekmask_egypt = [1, 1, 1, 1, 0, 0, 1] # Fri-Sat Weekend + bday_saudi = CDay(weekmask=weekmask_saudi) + bday_uae = CDay(weekmask=weekmask_uae) + bday_egypt = CDay(weekmask=weekmask_egypt) + dt = datetime(2013, 5, 1) + xp_saudi = datetime(2013, 5, 4) + xp_uae = datetime(2013, 5, 2) + xp_egypt = datetime(2013, 5, 2) + assert xp_saudi == dt + bday_saudi + assert xp_uae == dt + bday_uae + assert xp_egypt == dt + bday_egypt + xp2 = datetime(2013, 5, 5) + assert xp2 == dt + 2 * bday_saudi + assert xp2 == dt + 2 * bday_uae + assert xp2 == dt + 2 * bday_egypt + + def test_weekmask_and_holidays(self): + weekmask_egypt = "Sun Mon Tue Wed Thu" # Fri-Sat Weekend + holidays = ["2012-05-01", datetime(2013, 5, 1), np.datetime64("2014-05-01")] + bday_egypt = CDay(holidays=holidays, weekmask=weekmask_egypt) + dt = datetime(2013, 4, 30) + xp_egypt = datetime(2013, 5, 5) + assert xp_egypt == dt + 2 * bday_egypt + + @pytest.mark.filterwarnings("ignore:Non:pandas.errors.PerformanceWarning") + def test_calendar(self): + calendar = USFederalHolidayCalendar() + dt = datetime(2014, 1, 17) + assert_offset_equal(CDay(calendar=calendar), dt, datetime(2014, 1, 21)) + + def test_roundtrip_pickle(self, offset, offset2): + def _check_roundtrip(obj): + unpickled = tm.round_trip_pickle(obj) + assert unpickled == obj + + _check_roundtrip(offset) + _check_roundtrip(offset2) + _check_roundtrip(offset * 2) + + def test_pickle_compat_0_14_1(self, datapath): + hdays = [datetime(2013, 1, 1) for ele in range(4)] + pth = datapath("tseries", "offsets", "data", "cday-0.14.1.pickle") + cday0_14_1 = read_pickle(pth) + cday = CDay(holidays=hdays) + assert cday == cday0_14_1 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_hour.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_hour.py new file mode 100644 index 0000000000000000000000000000000000000000..55a184f95c2d8681fca77d74827dd248a20587f1 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_hour.py @@ -0,0 +1,329 @@ +""" +Tests for offsets.CustomBusinessHour +""" +from __future__ import annotations + +from datetime import ( + datetime, + time as dt_time, +) + +import numpy as np +import pytest + +from pandas._libs.tslibs import Timestamp +from pandas._libs.tslibs.offsets import ( + BusinessHour, + CustomBusinessHour, + Nano, +) + +from pandas.tests.tseries.offsets.common import assert_offset_equal + +from pandas.tseries.holiday import USFederalHolidayCalendar + +holidays = ["2014-06-27", datetime(2014, 6, 30), np.datetime64("2014-07-02")] + + +@pytest.fixture +def dt(): + return datetime(2014, 7, 1, 10, 00) + + +@pytest.fixture +def _offset(): + return CustomBusinessHour + + +# 2014 Calendar to check custom holidays +# Sun Mon Tue Wed Thu Fri Sat +# 6/22 23 24 25 26 27 28 +# 29 30 7/1 2 3 4 5 +# 6 7 8 9 10 11 12 +@pytest.fixture +def offset1(): + return CustomBusinessHour(weekmask="Tue Wed Thu Fri") + + +@pytest.fixture +def offset2(): + return CustomBusinessHour(holidays=holidays) + + +class TestCustomBusinessHour: + def test_constructor_errors(self): + msg = "time data must be specified only with hour and minute" + with pytest.raises(ValueError, match=msg): + CustomBusinessHour(start=dt_time(11, 0, 5)) + msg = "time data must match '%H:%M' format" + with pytest.raises(ValueError, match=msg): + CustomBusinessHour(start="AAA") + msg = "time data must match '%H:%M' format" + with pytest.raises(ValueError, match=msg): + CustomBusinessHour(start="14:00:05") + + def test_different_normalize_equals(self, _offset): + # GH#21404 changed __eq__ to return False when `normalize` does not match + offset = _offset() + offset2 = _offset(normalize=True) + assert offset != offset2 + + def test_repr(self, offset1, offset2): + assert repr(offset1) == "" + assert repr(offset2) == "" + + def test_with_offset(self, dt): + expected = Timestamp("2014-07-01 13:00") + + assert dt + CustomBusinessHour() * 3 == expected + assert dt + CustomBusinessHour(n=3) == expected + + def test_eq(self, offset1, offset2): + for offset in [offset1, offset2]: + assert offset == offset + + assert CustomBusinessHour() != CustomBusinessHour(-1) + assert CustomBusinessHour(start="09:00") == CustomBusinessHour() + assert CustomBusinessHour(start="09:00") != CustomBusinessHour(start="09:01") + assert CustomBusinessHour(start="09:00", end="17:00") != CustomBusinessHour( + start="17:00", end="09:01" + ) + + assert CustomBusinessHour(weekmask="Tue Wed Thu Fri") != CustomBusinessHour( + weekmask="Mon Tue Wed Thu Fri" + ) + assert CustomBusinessHour(holidays=["2014-06-27"]) != CustomBusinessHour( + holidays=["2014-06-28"] + ) + + def test_hash(self, offset1, offset2): + assert hash(offset1) == hash(offset1) + assert hash(offset2) == hash(offset2) + + def test_add_dateime(self, dt, offset1, offset2): + assert offset1 + dt == datetime(2014, 7, 1, 11) + assert offset2 + dt == datetime(2014, 7, 1, 11) + + def testRollback1(self, dt, offset1, offset2): + assert offset1.rollback(dt) == dt + assert offset2.rollback(dt) == dt + + d = datetime(2014, 7, 1, 0) + + # 2014/07/01 is Tuesday, 06/30 is Monday(holiday) + assert offset1.rollback(d) == datetime(2014, 6, 27, 17) + + # 2014/6/30 and 2014/6/27 are holidays + assert offset2.rollback(d) == datetime(2014, 6, 26, 17) + + def testRollback2(self, _offset): + assert _offset(-3).rollback(datetime(2014, 7, 5, 15, 0)) == datetime( + 2014, 7, 4, 17, 0 + ) + + def testRollforward1(self, dt, offset1, offset2): + assert offset1.rollforward(dt) == dt + assert offset2.rollforward(dt) == dt + + d = datetime(2014, 7, 1, 0) + assert offset1.rollforward(d) == datetime(2014, 7, 1, 9) + assert offset2.rollforward(d) == datetime(2014, 7, 1, 9) + + def testRollforward2(self, _offset): + assert _offset(-3).rollforward(datetime(2014, 7, 5, 16, 0)) == datetime( + 2014, 7, 7, 9 + ) + + def test_roll_date_object(self): + offset = BusinessHour() + + dt = datetime(2014, 7, 6, 15, 0) + + result = offset.rollback(dt) + assert result == datetime(2014, 7, 4, 17) + + result = offset.rollforward(dt) + assert result == datetime(2014, 7, 7, 9) + + normalize_cases = [ + ( + CustomBusinessHour(normalize=True, holidays=holidays), + { + datetime(2014, 7, 1, 8): datetime(2014, 7, 1), + datetime(2014, 7, 1, 17): datetime(2014, 7, 3), + datetime(2014, 7, 1, 16): datetime(2014, 7, 3), + datetime(2014, 7, 1, 23): datetime(2014, 7, 3), + datetime(2014, 7, 1, 0): datetime(2014, 7, 1), + datetime(2014, 7, 4, 15): datetime(2014, 7, 4), + datetime(2014, 7, 4, 15, 59): datetime(2014, 7, 4), + datetime(2014, 7, 4, 16, 30): datetime(2014, 7, 7), + datetime(2014, 7, 5, 23): datetime(2014, 7, 7), + datetime(2014, 7, 6, 10): datetime(2014, 7, 7), + }, + ), + ( + CustomBusinessHour(-1, normalize=True, holidays=holidays), + { + datetime(2014, 7, 1, 8): datetime(2014, 6, 26), + datetime(2014, 7, 1, 17): datetime(2014, 7, 1), + datetime(2014, 7, 1, 16): datetime(2014, 7, 1), + datetime(2014, 7, 1, 10): datetime(2014, 6, 26), + datetime(2014, 7, 1, 0): datetime(2014, 6, 26), + datetime(2014, 7, 7, 10): datetime(2014, 7, 4), + datetime(2014, 7, 7, 10, 1): datetime(2014, 7, 7), + datetime(2014, 7, 5, 23): datetime(2014, 7, 4), + datetime(2014, 7, 6, 10): datetime(2014, 7, 4), + }, + ), + ( + CustomBusinessHour( + 1, normalize=True, start="17:00", end="04:00", holidays=holidays + ), + { + datetime(2014, 7, 1, 8): datetime(2014, 7, 1), + datetime(2014, 7, 1, 17): datetime(2014, 7, 1), + datetime(2014, 7, 1, 23): datetime(2014, 7, 2), + datetime(2014, 7, 2, 2): datetime(2014, 7, 2), + datetime(2014, 7, 2, 3): datetime(2014, 7, 3), + datetime(2014, 7, 4, 23): datetime(2014, 7, 5), + datetime(2014, 7, 5, 2): datetime(2014, 7, 5), + datetime(2014, 7, 7, 2): datetime(2014, 7, 7), + datetime(2014, 7, 7, 17): datetime(2014, 7, 7), + }, + ), + ] + + @pytest.mark.parametrize("norm_cases", normalize_cases) + def test_normalize(self, norm_cases): + offset, cases = norm_cases + for dt, expected in cases.items(): + assert offset._apply(dt) == expected + + @pytest.mark.parametrize( + "dt, expected", + [ + [datetime(2014, 7, 1, 9), False], + [datetime(2014, 7, 1, 10), True], + [datetime(2014, 7, 1, 15), True], + [datetime(2014, 7, 1, 15, 1), False], + [datetime(2014, 7, 5, 12), False], + [datetime(2014, 7, 6, 12), False], + ], + ) + def test_is_on_offset(self, dt, expected): + offset = CustomBusinessHour(start="10:00", end="15:00", holidays=holidays) + assert offset.is_on_offset(dt) == expected + + apply_cases = [ + ( + CustomBusinessHour(holidays=holidays), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 12), + datetime(2014, 7, 1, 13): datetime(2014, 7, 1, 14), + datetime(2014, 7, 1, 15): datetime(2014, 7, 1, 16), + datetime(2014, 7, 1, 19): datetime(2014, 7, 3, 10), + datetime(2014, 7, 1, 16): datetime(2014, 7, 3, 9), + datetime(2014, 7, 1, 16, 30, 15): datetime(2014, 7, 3, 9, 30, 15), + datetime(2014, 7, 1, 17): datetime(2014, 7, 3, 10), + datetime(2014, 7, 2, 11): datetime(2014, 7, 3, 10), + # out of business hours + datetime(2014, 7, 2, 8): datetime(2014, 7, 3, 10), + datetime(2014, 7, 2, 19): datetime(2014, 7, 3, 10), + datetime(2014, 7, 2, 23): datetime(2014, 7, 3, 10), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 10), + # saturday + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 10), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 10), + datetime(2014, 7, 4, 16, 30): datetime(2014, 7, 7, 9, 30), + datetime(2014, 7, 4, 16, 30, 30): datetime(2014, 7, 7, 9, 30, 30), + }, + ), + ( + CustomBusinessHour(4, holidays=holidays), + { + datetime(2014, 7, 1, 11): datetime(2014, 7, 1, 15), + datetime(2014, 7, 1, 13): datetime(2014, 7, 3, 9), + datetime(2014, 7, 1, 15): datetime(2014, 7, 3, 11), + datetime(2014, 7, 1, 16): datetime(2014, 7, 3, 12), + datetime(2014, 7, 1, 17): datetime(2014, 7, 3, 13), + datetime(2014, 7, 2, 11): datetime(2014, 7, 3, 13), + datetime(2014, 7, 2, 8): datetime(2014, 7, 3, 13), + datetime(2014, 7, 2, 19): datetime(2014, 7, 3, 13), + datetime(2014, 7, 2, 23): datetime(2014, 7, 3, 13), + datetime(2014, 7, 3, 0): datetime(2014, 7, 3, 13), + datetime(2014, 7, 5, 15): datetime(2014, 7, 7, 13), + datetime(2014, 7, 4, 17): datetime(2014, 7, 7, 13), + datetime(2014, 7, 4, 16, 30): datetime(2014, 7, 7, 12, 30), + datetime(2014, 7, 4, 16, 30, 30): datetime(2014, 7, 7, 12, 30, 30), + }, + ), + ] + + @pytest.mark.parametrize("apply_case", apply_cases) + def test_apply(self, apply_case): + offset, cases = apply_case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + nano_cases = [ + ( + CustomBusinessHour(holidays=holidays), + { + Timestamp("2014-07-01 15:00") + + Nano(5): Timestamp("2014-07-01 16:00") + + Nano(5), + Timestamp("2014-07-01 16:00") + + Nano(5): Timestamp("2014-07-03 09:00") + + Nano(5), + Timestamp("2014-07-01 16:00") + - Nano(5): Timestamp("2014-07-01 17:00") + - Nano(5), + }, + ), + ( + CustomBusinessHour(-1, holidays=holidays), + { + Timestamp("2014-07-01 15:00") + + Nano(5): Timestamp("2014-07-01 14:00") + + Nano(5), + Timestamp("2014-07-01 10:00") + + Nano(5): Timestamp("2014-07-01 09:00") + + Nano(5), + Timestamp("2014-07-01 10:00") + - Nano(5): Timestamp("2014-06-26 17:00") + - Nano(5), + }, + ), + ] + + @pytest.mark.parametrize("nano_case", nano_cases) + def test_apply_nanoseconds(self, nano_case): + offset, cases = nano_case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + def test_us_federal_holiday_with_datetime(self): + # GH 16867 + bhour_us = CustomBusinessHour(calendar=USFederalHolidayCalendar()) + t0 = datetime(2014, 1, 17, 15) + result = t0 + bhour_us * 8 + expected = Timestamp("2014-01-21 15:00:00") + assert result == expected + + +@pytest.mark.parametrize( + "weekmask, expected_time, mult", + [ + ["Mon Tue Wed Thu Fri Sat", "2018-11-10 09:00:00", 10], + ["Tue Wed Thu Fri Sat", "2018-11-13 08:00:00", 18], + ], +) +def test_custom_businesshour_weekmask_and_holidays(weekmask, expected_time, mult): + # GH 23542 + holidays = ["2018-11-09"] + bh = CustomBusinessHour( + start="08:00", end="17:00", weekmask=weekmask, holidays=holidays + ) + result = Timestamp("2018-11-08 08:00") + mult * bh + expected = Timestamp(expected_time) + assert result == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_month.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_month.py new file mode 100644 index 0000000000000000000000000000000000000000..d226302e042d325d78a953a651b24f85ad4f0468 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_custom_business_month.py @@ -0,0 +1,437 @@ +""" +Tests for the following offsets: +- CustomBusinessMonthBase +- CustomBusinessMonthBegin +- CustomBusinessMonthEnd +""" +from __future__ import annotations + +from datetime import ( + date, + datetime, + timedelta, +) + +import numpy as np +import pytest + +from pandas._libs.tslibs.offsets import ( + CBMonthBegin, + CBMonthEnd, + CDay, +) + +import pandas._testing as tm +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries import offsets + + +@pytest.fixture +def dt(): + return datetime(2008, 1, 1) + + +class TestCommonCBM: + @pytest.mark.parametrize("offset2", [CBMonthBegin(2), CBMonthEnd(2)]) + def test_eq(self, offset2): + assert offset2 == offset2 + + @pytest.mark.parametrize("offset2", [CBMonthBegin(2), CBMonthEnd(2)]) + def test_hash(self, offset2): + assert hash(offset2) == hash(offset2) + + @pytest.mark.parametrize("_offset", [CBMonthBegin, CBMonthEnd]) + def test_roundtrip_pickle(self, _offset): + def _check_roundtrip(obj): + unpickled = tm.round_trip_pickle(obj) + assert unpickled == obj + + _check_roundtrip(_offset()) + _check_roundtrip(_offset(2)) + _check_roundtrip(_offset() * 2) + + @pytest.mark.parametrize("_offset", [CBMonthBegin, CBMonthEnd]) + def test_copy(self, _offset): + # GH 17452 + off = _offset(weekmask="Mon Wed Fri") + assert off == off.copy() + + +class TestCustomBusinessMonthBegin: + @pytest.fixture + def _offset(self): + return CBMonthBegin + + @pytest.fixture + def offset(self): + return CBMonthBegin() + + @pytest.fixture + def offset2(self): + return CBMonthBegin(2) + + def test_different_normalize_equals(self, _offset): + # GH#21404 changed __eq__ to return False when `normalize` does not match + offset = _offset() + offset2 = _offset(normalize=True) + assert offset != offset2 + + def test_repr(self, offset, offset2): + assert repr(offset) == "" + assert repr(offset2) == "<2 * CustomBusinessMonthBegins>" + + def test_add_datetime(self, dt, offset2): + assert offset2 + dt == datetime(2008, 3, 3) + + def testRollback1(self): + assert CDay(10).rollback(datetime(2007, 12, 31)) == datetime(2007, 12, 31) + + def testRollback2(self, dt): + assert CBMonthBegin(10).rollback(dt) == datetime(2008, 1, 1) + + def testRollforward1(self, dt): + assert CBMonthBegin(10).rollforward(dt) == datetime(2008, 1, 1) + + def test_roll_date_object(self): + offset = CBMonthBegin() + + dt = date(2012, 9, 15) + + result = offset.rollback(dt) + assert result == datetime(2012, 9, 3) + + result = offset.rollforward(dt) + assert result == datetime(2012, 10, 1) + + offset = offsets.Day() + result = offset.rollback(dt) + assert result == datetime(2012, 9, 15) + + result = offset.rollforward(dt) + assert result == datetime(2012, 9, 15) + + on_offset_cases = [ + (CBMonthBegin(), datetime(2008, 1, 1), True), + (CBMonthBegin(), datetime(2008, 1, 31), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + apply_cases = [ + ( + CBMonthBegin(), + { + datetime(2008, 1, 1): datetime(2008, 2, 1), + datetime(2008, 2, 7): datetime(2008, 3, 3), + }, + ), + ( + 2 * CBMonthBegin(), + { + datetime(2008, 1, 1): datetime(2008, 3, 3), + datetime(2008, 2, 7): datetime(2008, 4, 1), + }, + ), + ( + -CBMonthBegin(), + { + datetime(2008, 1, 1): datetime(2007, 12, 3), + datetime(2008, 2, 8): datetime(2008, 2, 1), + }, + ), + ( + -2 * CBMonthBegin(), + { + datetime(2008, 1, 1): datetime(2007, 11, 1), + datetime(2008, 2, 9): datetime(2008, 1, 1), + }, + ), + ( + CBMonthBegin(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 1, 7): datetime(2008, 2, 1), + }, + ), + ] + + @pytest.mark.parametrize("case", apply_cases) + def test_apply(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + def test_apply_large_n(self): + dt = datetime(2012, 10, 23) + + result = dt + CBMonthBegin(10) + assert result == datetime(2013, 8, 1) + + result = dt + CDay(100) - CDay(100) + assert result == dt + + off = CBMonthBegin() * 6 + rs = datetime(2012, 1, 1) - off + xp = datetime(2011, 7, 1) + assert rs == xp + + st = datetime(2011, 12, 18) + rs = st + off + + xp = datetime(2012, 6, 1) + assert rs == xp + + def test_holidays(self): + # Define a TradingDay offset + holidays = ["2012-02-01", datetime(2012, 2, 2), np.datetime64("2012-03-01")] + bm_offset = CBMonthBegin(holidays=holidays) + dt = datetime(2012, 1, 1) + + assert dt + bm_offset == datetime(2012, 1, 2) + assert dt + 2 * bm_offset == datetime(2012, 2, 3) + + @pytest.mark.parametrize( + "case", + [ + ( + CBMonthBegin(n=1, offset=timedelta(days=5)), + { + datetime(2021, 3, 1): datetime(2021, 4, 1) + timedelta(days=5), + datetime(2021, 4, 17): datetime(2021, 5, 3) + timedelta(days=5), + }, + ), + ( + CBMonthBegin(n=2, offset=timedelta(days=40)), + { + datetime(2021, 3, 10): datetime(2021, 5, 3) + timedelta(days=40), + datetime(2021, 4, 30): datetime(2021, 6, 1) + timedelta(days=40), + }, + ), + ( + CBMonthBegin(n=1, offset=timedelta(days=-5)), + { + datetime(2021, 3, 1): datetime(2021, 4, 1) - timedelta(days=5), + datetime(2021, 4, 11): datetime(2021, 5, 3) - timedelta(days=5), + }, + ), + ( + -2 * CBMonthBegin(n=1, offset=timedelta(days=10)), + { + datetime(2021, 3, 1): datetime(2021, 1, 1) + timedelta(days=10), + datetime(2021, 4, 3): datetime(2021, 3, 1) + timedelta(days=10), + }, + ), + ( + CBMonthBegin(n=0, offset=timedelta(days=1)), + { + datetime(2021, 3, 2): datetime(2021, 4, 1) + timedelta(days=1), + datetime(2021, 4, 1): datetime(2021, 4, 1) + timedelta(days=1), + }, + ), + ( + CBMonthBegin( + n=1, holidays=["2021-04-01", "2021-04-02"], offset=timedelta(days=1) + ), + { + datetime(2021, 3, 2): datetime(2021, 4, 5) + timedelta(days=1), + }, + ), + ], + ) + def test_apply_with_extra_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + +class TestCustomBusinessMonthEnd: + @pytest.fixture + def _offset(self): + return CBMonthEnd + + @pytest.fixture + def offset(self): + return CBMonthEnd() + + @pytest.fixture + def offset2(self): + return CBMonthEnd(2) + + def test_different_normalize_equals(self, _offset): + # GH#21404 changed __eq__ to return False when `normalize` does not match + offset = _offset() + offset2 = _offset(normalize=True) + assert offset != offset2 + + def test_repr(self, offset, offset2): + assert repr(offset) == "" + assert repr(offset2) == "<2 * CustomBusinessMonthEnds>" + + def test_add_datetime(self, dt, offset2): + assert offset2 + dt == datetime(2008, 2, 29) + + def testRollback1(self): + assert CDay(10).rollback(datetime(2007, 12, 31)) == datetime(2007, 12, 31) + + def testRollback2(self, dt): + assert CBMonthEnd(10).rollback(dt) == datetime(2007, 12, 31) + + def testRollforward1(self, dt): + assert CBMonthEnd(10).rollforward(dt) == datetime(2008, 1, 31) + + def test_roll_date_object(self): + offset = CBMonthEnd() + + dt = date(2012, 9, 15) + + result = offset.rollback(dt) + assert result == datetime(2012, 8, 31) + + result = offset.rollforward(dt) + assert result == datetime(2012, 9, 28) + + offset = offsets.Day() + result = offset.rollback(dt) + assert result == datetime(2012, 9, 15) + + result = offset.rollforward(dt) + assert result == datetime(2012, 9, 15) + + on_offset_cases = [ + (CBMonthEnd(), datetime(2008, 1, 31), True), + (CBMonthEnd(), datetime(2008, 1, 1), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + apply_cases = [ + ( + CBMonthEnd(), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 2, 7): datetime(2008, 2, 29), + }, + ), + ( + 2 * CBMonthEnd(), + { + datetime(2008, 1, 1): datetime(2008, 2, 29), + datetime(2008, 2, 7): datetime(2008, 3, 31), + }, + ), + ( + -CBMonthEnd(), + { + datetime(2008, 1, 1): datetime(2007, 12, 31), + datetime(2008, 2, 8): datetime(2008, 1, 31), + }, + ), + ( + -2 * CBMonthEnd(), + { + datetime(2008, 1, 1): datetime(2007, 11, 30), + datetime(2008, 2, 9): datetime(2007, 12, 31), + }, + ), + ( + CBMonthEnd(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 2, 7): datetime(2008, 2, 29), + }, + ), + ] + + @pytest.mark.parametrize("case", apply_cases) + def test_apply(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + def test_apply_large_n(self): + dt = datetime(2012, 10, 23) + + result = dt + CBMonthEnd(10) + assert result == datetime(2013, 7, 31) + + result = dt + CDay(100) - CDay(100) + assert result == dt + + off = CBMonthEnd() * 6 + rs = datetime(2012, 1, 1) - off + xp = datetime(2011, 7, 29) + assert rs == xp + + st = datetime(2011, 12, 18) + rs = st + off + xp = datetime(2012, 5, 31) + assert rs == xp + + def test_holidays(self): + # Define a TradingDay offset + holidays = ["2012-01-31", datetime(2012, 2, 28), np.datetime64("2012-02-29")] + bm_offset = CBMonthEnd(holidays=holidays) + dt = datetime(2012, 1, 1) + assert dt + bm_offset == datetime(2012, 1, 30) + assert dt + 2 * bm_offset == datetime(2012, 2, 27) + + @pytest.mark.parametrize( + "case", + [ + ( + CBMonthEnd(n=1, offset=timedelta(days=5)), + { + datetime(2021, 3, 1): datetime(2021, 3, 31) + timedelta(days=5), + datetime(2021, 4, 17): datetime(2021, 4, 30) + timedelta(days=5), + }, + ), + ( + CBMonthEnd(n=2, offset=timedelta(days=40)), + { + datetime(2021, 3, 10): datetime(2021, 4, 30) + timedelta(days=40), + datetime(2021, 4, 30): datetime(2021, 6, 30) + timedelta(days=40), + }, + ), + ( + CBMonthEnd(n=1, offset=timedelta(days=-5)), + { + datetime(2021, 3, 1): datetime(2021, 3, 31) - timedelta(days=5), + datetime(2021, 4, 11): datetime(2021, 4, 30) - timedelta(days=5), + }, + ), + ( + -2 * CBMonthEnd(n=1, offset=timedelta(days=10)), + { + datetime(2021, 3, 1): datetime(2021, 1, 29) + timedelta(days=10), + datetime(2021, 4, 3): datetime(2021, 2, 26) + timedelta(days=10), + }, + ), + ( + CBMonthEnd(n=0, offset=timedelta(days=1)), + { + datetime(2021, 3, 2): datetime(2021, 3, 31) + timedelta(days=1), + datetime(2021, 4, 1): datetime(2021, 4, 30) + timedelta(days=1), + }, + ), + ( + CBMonthEnd(n=1, holidays=["2021-03-31"], offset=timedelta(days=1)), + { + datetime(2021, 3, 2): datetime(2021, 3, 30) + timedelta(days=1), + }, + ), + ], + ) + def test_apply_with_extra_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_dst.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_dst.py new file mode 100644 index 0000000000000000000000000000000000000000..b22dc0b33081794cef587f0bbcf3271d35fd687b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_dst.py @@ -0,0 +1,260 @@ +""" +Tests for DateOffset additions over Daylight Savings Time +""" +from datetime import timedelta + +import pytest +import pytz + +from pandas._libs.tslibs import Timestamp +from pandas._libs.tslibs.offsets import ( + BMonthBegin, + BMonthEnd, + BQuarterBegin, + BQuarterEnd, + BYearBegin, + BYearEnd, + CBMonthBegin, + CBMonthEnd, + CustomBusinessDay, + DateOffset, + Day, + MonthBegin, + MonthEnd, + QuarterBegin, + QuarterEnd, + SemiMonthBegin, + SemiMonthEnd, + Week, + YearBegin, + YearEnd, +) +from pandas.errors import PerformanceWarning + +from pandas import DatetimeIndex +import pandas._testing as tm +from pandas.util.version import Version + +# error: Module has no attribute "__version__" +pytz_version = Version(pytz.__version__) # type: ignore[attr-defined] + + +def get_utc_offset_hours(ts): + # take a Timestamp and compute total hours of utc offset + o = ts.utcoffset() + return (o.days * 24 * 3600 + o.seconds) / 3600.0 + + +class TestDST: + # one microsecond before the DST transition + ts_pre_fallback = "2013-11-03 01:59:59.999999" + ts_pre_springfwd = "2013-03-10 01:59:59.999999" + + # test both basic names and dateutil timezones + timezone_utc_offsets = { + "US/Eastern": {"utc_offset_daylight": -4, "utc_offset_standard": -5}, + "dateutil/US/Pacific": {"utc_offset_daylight": -7, "utc_offset_standard": -8}, + } + valid_date_offsets_singular = [ + "weekday", + "day", + "hour", + "minute", + "second", + "microsecond", + ] + valid_date_offsets_plural = [ + "weeks", + "days", + "hours", + "minutes", + "seconds", + "milliseconds", + "microseconds", + ] + + def _test_all_offsets(self, n, **kwds): + valid_offsets = ( + self.valid_date_offsets_plural + if n > 1 + else self.valid_date_offsets_singular + ) + + for name in valid_offsets: + self._test_offset(offset_name=name, offset_n=n, **kwds) + + def _test_offset(self, offset_name, offset_n, tstart, expected_utc_offset): + offset = DateOffset(**{offset_name: offset_n}) + + if ( + offset_name in ["hour", "minute", "second", "microsecond"] + and offset_n == 1 + and tstart == Timestamp("2013-11-03 01:59:59.999999-0500", tz="US/Eastern") + ): + # This addition results in an ambiguous wall time + err_msg = { + "hour": "2013-11-03 01:59:59.999999", + "minute": "2013-11-03 01:01:59.999999", + "second": "2013-11-03 01:59:01.999999", + "microsecond": "2013-11-03 01:59:59.000001", + }[offset_name] + with pytest.raises(pytz.AmbiguousTimeError, match=err_msg): + tstart + offset + # While we're here, let's check that we get the same behavior in a + # vectorized path + dti = DatetimeIndex([tstart]) + warn_msg = "Non-vectorized DateOffset" + with pytest.raises(pytz.AmbiguousTimeError, match=err_msg): + with tm.assert_produces_warning(PerformanceWarning, match=warn_msg): + dti + offset + return + + t = tstart + offset + if expected_utc_offset is not None: + assert get_utc_offset_hours(t) == expected_utc_offset + + if offset_name == "weeks": + # dates should match + assert t.date() == timedelta(days=7 * offset.kwds["weeks"]) + tstart.date() + # expect the same day of week, hour of day, minute, second, ... + assert ( + t.dayofweek == tstart.dayofweek + and t.hour == tstart.hour + and t.minute == tstart.minute + and t.second == tstart.second + ) + elif offset_name == "days": + # dates should match + assert timedelta(offset.kwds["days"]) + tstart.date() == t.date() + # expect the same hour of day, minute, second, ... + assert ( + t.hour == tstart.hour + and t.minute == tstart.minute + and t.second == tstart.second + ) + elif offset_name in self.valid_date_offsets_singular: + # expect the singular offset value to match between tstart and t + datepart_offset = getattr( + t, offset_name if offset_name != "weekday" else "dayofweek" + ) + assert datepart_offset == offset.kwds[offset_name] + else: + # the offset should be the same as if it was done in UTC + assert t == (tstart.tz_convert("UTC") + offset).tz_convert("US/Pacific") + + def _make_timestamp(self, string, hrs_offset, tz): + if hrs_offset >= 0: + offset_string = f"{hrs_offset:02d}00" + else: + offset_string = f"-{(hrs_offset * -1):02}00" + return Timestamp(string + offset_string).tz_convert(tz) + + def test_springforward_plural(self): + # test moving from standard to daylight savings + for tz, utc_offsets in self.timezone_utc_offsets.items(): + hrs_pre = utc_offsets["utc_offset_standard"] + hrs_post = utc_offsets["utc_offset_daylight"] + self._test_all_offsets( + n=3, + tstart=self._make_timestamp(self.ts_pre_springfwd, hrs_pre, tz), + expected_utc_offset=hrs_post, + ) + + def test_fallback_singular(self): + # in the case of singular offsets, we don't necessarily know which utc + # offset the new Timestamp will wind up in (the tz for 1 month may be + # different from 1 second) so we don't specify an expected_utc_offset + for tz, utc_offsets in self.timezone_utc_offsets.items(): + hrs_pre = utc_offsets["utc_offset_standard"] + self._test_all_offsets( + n=1, + tstart=self._make_timestamp(self.ts_pre_fallback, hrs_pre, tz), + expected_utc_offset=None, + ) + + def test_springforward_singular(self): + for tz, utc_offsets in self.timezone_utc_offsets.items(): + hrs_pre = utc_offsets["utc_offset_standard"] + self._test_all_offsets( + n=1, + tstart=self._make_timestamp(self.ts_pre_springfwd, hrs_pre, tz), + expected_utc_offset=None, + ) + + offset_classes = { + MonthBegin: ["11/2/2012", "12/1/2012"], + MonthEnd: ["11/2/2012", "11/30/2012"], + BMonthBegin: ["11/2/2012", "12/3/2012"], + BMonthEnd: ["11/2/2012", "11/30/2012"], + CBMonthBegin: ["11/2/2012", "12/3/2012"], + CBMonthEnd: ["11/2/2012", "11/30/2012"], + SemiMonthBegin: ["11/2/2012", "11/15/2012"], + SemiMonthEnd: ["11/2/2012", "11/15/2012"], + Week: ["11/2/2012", "11/9/2012"], + YearBegin: ["11/2/2012", "1/1/2013"], + YearEnd: ["11/2/2012", "12/31/2012"], + BYearBegin: ["11/2/2012", "1/1/2013"], + BYearEnd: ["11/2/2012", "12/31/2012"], + QuarterBegin: ["11/2/2012", "12/1/2012"], + QuarterEnd: ["11/2/2012", "12/31/2012"], + BQuarterBegin: ["11/2/2012", "12/3/2012"], + BQuarterEnd: ["11/2/2012", "12/31/2012"], + Day: ["11/4/2012", "11/4/2012 23:00"], + }.items() + + @pytest.mark.parametrize("tup", offset_classes) + def test_all_offset_classes(self, tup): + offset, test_values = tup + + first = Timestamp(test_values[0], tz="US/Eastern") + offset() + second = Timestamp(test_values[1], tz="US/Eastern") + assert first == second + + +@pytest.mark.parametrize( + "original_dt, target_dt, offset, tz", + [ + pytest.param( + Timestamp("1900-01-01"), + Timestamp("1905-07-01"), + MonthBegin(66), + "Africa/Lagos", + marks=pytest.mark.xfail( + pytz_version < Version("2020.5") or pytz_version == Version("2022.2"), + reason="GH#41906: pytz utc transition dates changed", + ), + ), + ( + Timestamp("2021-10-01 01:15"), + Timestamp("2021-10-31 01:15"), + MonthEnd(1), + "Europe/London", + ), + ( + Timestamp("2010-12-05 02:59"), + Timestamp("2010-10-31 02:59"), + SemiMonthEnd(-3), + "Europe/Paris", + ), + ( + Timestamp("2021-10-31 01:20"), + Timestamp("2021-11-07 01:20"), + CustomBusinessDay(2, weekmask="Sun Mon"), + "US/Eastern", + ), + ( + Timestamp("2020-04-03 01:30"), + Timestamp("2020-11-01 01:30"), + YearBegin(1, month=11), + "America/Chicago", + ), + ], +) +def test_nontick_offset_with_ambiguous_time_error(original_dt, target_dt, offset, tz): + # .apply for non-Tick offsets throws AmbiguousTimeError when the target dt + # is dst-ambiguous + localized_dt = original_dt.tz_localize(tz) + + msg = f"Cannot infer dst time from {target_dt}, try using the 'ambiguous' argument" + with pytest.raises(pytz.AmbiguousTimeError, match=msg): + localized_dt + offset diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_easter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_easter.py new file mode 100644 index 0000000000000000000000000000000000000000..d11a72cc1b9d54387a37d8e4102249c415c4b46e --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_easter.py @@ -0,0 +1,33 @@ +""" +Tests for the following offsets: +- Easter +""" +from __future__ import annotations + +from datetime import datetime + +import pytest + +from pandas.tests.tseries.offsets.common import assert_offset_equal + +from pandas.tseries.offsets import Easter + + +class TestEaster: + @pytest.mark.parametrize( + "offset,date,expected", + [ + (Easter(), datetime(2010, 1, 1), datetime(2010, 4, 4)), + (Easter(), datetime(2010, 4, 5), datetime(2011, 4, 24)), + (Easter(2), datetime(2010, 1, 1), datetime(2011, 4, 24)), + (Easter(), datetime(2010, 4, 4), datetime(2011, 4, 24)), + (Easter(2), datetime(2010, 4, 4), datetime(2012, 4, 8)), + (-Easter(), datetime(2011, 1, 1), datetime(2010, 4, 4)), + (-Easter(), datetime(2010, 4, 5), datetime(2010, 4, 4)), + (-Easter(2), datetime(2011, 1, 1), datetime(2009, 4, 12)), + (-Easter(), datetime(2010, 4, 4), datetime(2009, 4, 12)), + (-Easter(2), datetime(2010, 4, 4), datetime(2008, 3, 23)), + ], + ) + def test_offset(self, offset, date, expected): + assert_offset_equal(offset, date, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_fiscal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_fiscal.py new file mode 100644 index 0000000000000000000000000000000000000000..824e66a1ddef1b31708e53075949a9bba0114190 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_fiscal.py @@ -0,0 +1,656 @@ +""" +Tests for Fiscal Year and Fiscal Quarter offset classes +""" +from datetime import datetime + +from dateutil.relativedelta import relativedelta +import pytest + +from pandas import Timestamp +import pandas._testing as tm +from pandas.tests.tseries.offsets.common import ( + WeekDay, + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries.offsets import ( + FY5253, + FY5253Quarter, +) + + +def makeFY5253LastOfMonthQuarter(*args, **kwds): + return FY5253Quarter(*args, variation="last", **kwds) + + +def makeFY5253NearestEndMonthQuarter(*args, **kwds): + return FY5253Quarter(*args, variation="nearest", **kwds) + + +def makeFY5253NearestEndMonth(*args, **kwds): + return FY5253(*args, variation="nearest", **kwds) + + +def makeFY5253LastOfMonth(*args, **kwds): + return FY5253(*args, variation="last", **kwds) + + +def test_get_offset_name(): + assert ( + makeFY5253LastOfMonthQuarter( + weekday=1, startingMonth=3, qtr_with_extra_week=4 + ).freqstr + == "REQ-L-MAR-TUE-4" + ) + assert ( + makeFY5253NearestEndMonthQuarter( + weekday=1, startingMonth=3, qtr_with_extra_week=3 + ).freqstr + == "REQ-N-MAR-TUE-3" + ) + + +class TestFY5253LastOfMonth: + offset_lom_sat_aug = makeFY5253LastOfMonth(1, startingMonth=8, weekday=WeekDay.SAT) + offset_lom_sat_sep = makeFY5253LastOfMonth(1, startingMonth=9, weekday=WeekDay.SAT) + + on_offset_cases = [ + # From Wikipedia (see: + # https://en.wikipedia.org/wiki/4%E2%80%934%E2%80%935_calendar#Last_Saturday_of_the_month_at_fiscal_year_end) + (offset_lom_sat_aug, datetime(2006, 8, 26), True), + (offset_lom_sat_aug, datetime(2007, 8, 25), True), + (offset_lom_sat_aug, datetime(2008, 8, 30), True), + (offset_lom_sat_aug, datetime(2009, 8, 29), True), + (offset_lom_sat_aug, datetime(2010, 8, 28), True), + (offset_lom_sat_aug, datetime(2011, 8, 27), True), + (offset_lom_sat_aug, datetime(2012, 8, 25), True), + (offset_lom_sat_aug, datetime(2013, 8, 31), True), + (offset_lom_sat_aug, datetime(2014, 8, 30), True), + (offset_lom_sat_aug, datetime(2015, 8, 29), True), + (offset_lom_sat_aug, datetime(2016, 8, 27), True), + (offset_lom_sat_aug, datetime(2017, 8, 26), True), + (offset_lom_sat_aug, datetime(2018, 8, 25), True), + (offset_lom_sat_aug, datetime(2019, 8, 31), True), + (offset_lom_sat_aug, datetime(2006, 8, 27), False), + (offset_lom_sat_aug, datetime(2007, 8, 28), False), + (offset_lom_sat_aug, datetime(2008, 8, 31), False), + (offset_lom_sat_aug, datetime(2009, 8, 30), False), + (offset_lom_sat_aug, datetime(2010, 8, 29), False), + (offset_lom_sat_aug, datetime(2011, 8, 28), False), + (offset_lom_sat_aug, datetime(2006, 8, 25), False), + (offset_lom_sat_aug, datetime(2007, 8, 24), False), + (offset_lom_sat_aug, datetime(2008, 8, 29), False), + (offset_lom_sat_aug, datetime(2009, 8, 28), False), + (offset_lom_sat_aug, datetime(2010, 8, 27), False), + (offset_lom_sat_aug, datetime(2011, 8, 26), False), + (offset_lom_sat_aug, datetime(2019, 8, 30), False), + # From GMCR (see for example: + # http://yahoo.brand.edgar-online.com/Default.aspx? + # companyid=3184&formtypeID=7) + (offset_lom_sat_sep, datetime(2010, 9, 25), True), + (offset_lom_sat_sep, datetime(2011, 9, 24), True), + (offset_lom_sat_sep, datetime(2012, 9, 29), True), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + def test_apply(self): + offset_lom_aug_sat = makeFY5253LastOfMonth(startingMonth=8, weekday=WeekDay.SAT) + offset_lom_aug_sat_1 = makeFY5253LastOfMonth( + n=1, startingMonth=8, weekday=WeekDay.SAT + ) + + date_seq_lom_aug_sat = [ + datetime(2006, 8, 26), + datetime(2007, 8, 25), + datetime(2008, 8, 30), + datetime(2009, 8, 29), + datetime(2010, 8, 28), + datetime(2011, 8, 27), + datetime(2012, 8, 25), + datetime(2013, 8, 31), + datetime(2014, 8, 30), + datetime(2015, 8, 29), + datetime(2016, 8, 27), + ] + + tests = [ + (offset_lom_aug_sat, date_seq_lom_aug_sat), + (offset_lom_aug_sat_1, date_seq_lom_aug_sat), + (offset_lom_aug_sat, [datetime(2006, 8, 25)] + date_seq_lom_aug_sat), + (offset_lom_aug_sat_1, [datetime(2006, 8, 27)] + date_seq_lom_aug_sat[1:]), + ( + makeFY5253LastOfMonth(n=-1, startingMonth=8, weekday=WeekDay.SAT), + list(reversed(date_seq_lom_aug_sat)), + ), + ] + for test in tests: + offset, data = test + current = data[0] + for datum in data[1:]: + current = current + offset + assert current == datum + + +class TestFY5253NearestEndMonth: + def test_get_year_end(self): + assert makeFY5253NearestEndMonth( + startingMonth=8, weekday=WeekDay.SAT + ).get_year_end(datetime(2013, 1, 1)) == datetime(2013, 8, 31) + assert makeFY5253NearestEndMonth( + startingMonth=8, weekday=WeekDay.SUN + ).get_year_end(datetime(2013, 1, 1)) == datetime(2013, 9, 1) + assert makeFY5253NearestEndMonth( + startingMonth=8, weekday=WeekDay.FRI + ).get_year_end(datetime(2013, 1, 1)) == datetime(2013, 8, 30) + + offset_n = FY5253(weekday=WeekDay.TUE, startingMonth=12, variation="nearest") + assert offset_n.get_year_end(datetime(2012, 1, 1)) == datetime(2013, 1, 1) + assert offset_n.get_year_end(datetime(2012, 1, 10)) == datetime(2013, 1, 1) + + assert offset_n.get_year_end(datetime(2013, 1, 1)) == datetime(2013, 12, 31) + assert offset_n.get_year_end(datetime(2013, 1, 2)) == datetime(2013, 12, 31) + assert offset_n.get_year_end(datetime(2013, 1, 3)) == datetime(2013, 12, 31) + assert offset_n.get_year_end(datetime(2013, 1, 10)) == datetime(2013, 12, 31) + + JNJ = FY5253(n=1, startingMonth=12, weekday=6, variation="nearest") + assert JNJ.get_year_end(datetime(2006, 1, 1)) == datetime(2006, 12, 31) + + offset_lom_aug_sat = makeFY5253NearestEndMonth( + 1, startingMonth=8, weekday=WeekDay.SAT + ) + offset_lom_aug_thu = makeFY5253NearestEndMonth( + 1, startingMonth=8, weekday=WeekDay.THU + ) + offset_n = FY5253(weekday=WeekDay.TUE, startingMonth=12, variation="nearest") + + on_offset_cases = [ + # From Wikipedia (see: + # https://en.wikipedia.org/wiki/4%E2%80%934%E2%80%935_calendar + # #Saturday_nearest_the_end_of_month) + # 2006-09-02 2006 September 2 + # 2007-09-01 2007 September 1 + # 2008-08-30 2008 August 30 (leap year) + # 2009-08-29 2009 August 29 + # 2010-08-28 2010 August 28 + # 2011-09-03 2011 September 3 + # 2012-09-01 2012 September 1 (leap year) + # 2013-08-31 2013 August 31 + # 2014-08-30 2014 August 30 + # 2015-08-29 2015 August 29 + # 2016-09-03 2016 September 3 (leap year) + # 2017-09-02 2017 September 2 + # 2018-09-01 2018 September 1 + # 2019-08-31 2019 August 31 + (offset_lom_aug_sat, datetime(2006, 9, 2), True), + (offset_lom_aug_sat, datetime(2007, 9, 1), True), + (offset_lom_aug_sat, datetime(2008, 8, 30), True), + (offset_lom_aug_sat, datetime(2009, 8, 29), True), + (offset_lom_aug_sat, datetime(2010, 8, 28), True), + (offset_lom_aug_sat, datetime(2011, 9, 3), True), + (offset_lom_aug_sat, datetime(2016, 9, 3), True), + (offset_lom_aug_sat, datetime(2017, 9, 2), True), + (offset_lom_aug_sat, datetime(2018, 9, 1), True), + (offset_lom_aug_sat, datetime(2019, 8, 31), True), + (offset_lom_aug_sat, datetime(2006, 8, 27), False), + (offset_lom_aug_sat, datetime(2007, 8, 28), False), + (offset_lom_aug_sat, datetime(2008, 8, 31), False), + (offset_lom_aug_sat, datetime(2009, 8, 30), False), + (offset_lom_aug_sat, datetime(2010, 8, 29), False), + (offset_lom_aug_sat, datetime(2011, 8, 28), False), + (offset_lom_aug_sat, datetime(2006, 8, 25), False), + (offset_lom_aug_sat, datetime(2007, 8, 24), False), + (offset_lom_aug_sat, datetime(2008, 8, 29), False), + (offset_lom_aug_sat, datetime(2009, 8, 28), False), + (offset_lom_aug_sat, datetime(2010, 8, 27), False), + (offset_lom_aug_sat, datetime(2011, 8, 26), False), + (offset_lom_aug_sat, datetime(2019, 8, 30), False), + # From Micron, see: + # http://google.brand.edgar-online.com/?sym=MU&formtypeID=7 + (offset_lom_aug_thu, datetime(2012, 8, 30), True), + (offset_lom_aug_thu, datetime(2011, 9, 1), True), + (offset_n, datetime(2012, 12, 31), False), + (offset_n, datetime(2013, 1, 1), True), + (offset_n, datetime(2013, 1, 2), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + def test_apply(self): + date_seq_nem_8_sat = [ + datetime(2006, 9, 2), + datetime(2007, 9, 1), + datetime(2008, 8, 30), + datetime(2009, 8, 29), + datetime(2010, 8, 28), + datetime(2011, 9, 3), + ] + + JNJ = [ + datetime(2005, 1, 2), + datetime(2006, 1, 1), + datetime(2006, 12, 31), + datetime(2007, 12, 30), + datetime(2008, 12, 28), + datetime(2010, 1, 3), + datetime(2011, 1, 2), + datetime(2012, 1, 1), + datetime(2012, 12, 30), + ] + + DEC_SAT = FY5253(n=-1, startingMonth=12, weekday=5, variation="nearest") + + tests = [ + ( + makeFY5253NearestEndMonth(startingMonth=8, weekday=WeekDay.SAT), + date_seq_nem_8_sat, + ), + ( + makeFY5253NearestEndMonth(n=1, startingMonth=8, weekday=WeekDay.SAT), + date_seq_nem_8_sat, + ), + ( + makeFY5253NearestEndMonth(startingMonth=8, weekday=WeekDay.SAT), + [datetime(2006, 9, 1)] + date_seq_nem_8_sat, + ), + ( + makeFY5253NearestEndMonth(n=1, startingMonth=8, weekday=WeekDay.SAT), + [datetime(2006, 9, 3)] + date_seq_nem_8_sat[1:], + ), + ( + makeFY5253NearestEndMonth(n=-1, startingMonth=8, weekday=WeekDay.SAT), + list(reversed(date_seq_nem_8_sat)), + ), + ( + makeFY5253NearestEndMonth(n=1, startingMonth=12, weekday=WeekDay.SUN), + JNJ, + ), + ( + makeFY5253NearestEndMonth(n=-1, startingMonth=12, weekday=WeekDay.SUN), + list(reversed(JNJ)), + ), + ( + makeFY5253NearestEndMonth(n=1, startingMonth=12, weekday=WeekDay.SUN), + [datetime(2005, 1, 2), datetime(2006, 1, 1)], + ), + ( + makeFY5253NearestEndMonth(n=1, startingMonth=12, weekday=WeekDay.SUN), + [datetime(2006, 1, 2), datetime(2006, 12, 31)], + ), + (DEC_SAT, [datetime(2013, 1, 15), datetime(2012, 12, 29)]), + ] + for test in tests: + offset, data = test + current = data[0] + for datum in data[1:]: + current = current + offset + assert current == datum + + +class TestFY5253LastOfMonthQuarter: + def test_is_anchored(self): + msg = "FY5253Quarter.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert makeFY5253LastOfMonthQuarter( + startingMonth=1, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ).is_anchored() + assert makeFY5253LastOfMonthQuarter( + weekday=WeekDay.SAT, startingMonth=3, qtr_with_extra_week=4 + ).is_anchored() + assert not makeFY5253LastOfMonthQuarter( + 2, startingMonth=1, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ).is_anchored() + + def test_equality(self): + assert makeFY5253LastOfMonthQuarter( + startingMonth=1, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) == makeFY5253LastOfMonthQuarter( + startingMonth=1, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + assert makeFY5253LastOfMonthQuarter( + startingMonth=1, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) != makeFY5253LastOfMonthQuarter( + startingMonth=1, weekday=WeekDay.SUN, qtr_with_extra_week=4 + ) + assert makeFY5253LastOfMonthQuarter( + startingMonth=1, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) != makeFY5253LastOfMonthQuarter( + startingMonth=2, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + + def test_offset(self): + offset = makeFY5253LastOfMonthQuarter( + 1, startingMonth=9, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + offset2 = makeFY5253LastOfMonthQuarter( + 2, startingMonth=9, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + offset4 = makeFY5253LastOfMonthQuarter( + 4, startingMonth=9, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + + offset_neg1 = makeFY5253LastOfMonthQuarter( + -1, startingMonth=9, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + offset_neg2 = makeFY5253LastOfMonthQuarter( + -2, startingMonth=9, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + + GMCR = [ + datetime(2010, 3, 27), + datetime(2010, 6, 26), + datetime(2010, 9, 25), + datetime(2010, 12, 25), + datetime(2011, 3, 26), + datetime(2011, 6, 25), + datetime(2011, 9, 24), + datetime(2011, 12, 24), + datetime(2012, 3, 24), + datetime(2012, 6, 23), + datetime(2012, 9, 29), + datetime(2012, 12, 29), + datetime(2013, 3, 30), + datetime(2013, 6, 29), + ] + + assert_offset_equal(offset, base=GMCR[0], expected=GMCR[1]) + assert_offset_equal( + offset, base=GMCR[0] + relativedelta(days=-1), expected=GMCR[0] + ) + assert_offset_equal(offset, base=GMCR[1], expected=GMCR[2]) + + assert_offset_equal(offset2, base=GMCR[0], expected=GMCR[2]) + assert_offset_equal(offset4, base=GMCR[0], expected=GMCR[4]) + + assert_offset_equal(offset_neg1, base=GMCR[-1], expected=GMCR[-2]) + assert_offset_equal( + offset_neg1, base=GMCR[-1] + relativedelta(days=+1), expected=GMCR[-1] + ) + assert_offset_equal(offset_neg2, base=GMCR[-1], expected=GMCR[-3]) + + date = GMCR[0] + relativedelta(days=-1) + for expected in GMCR: + assert_offset_equal(offset, date, expected) + date = date + offset + + date = GMCR[-1] + relativedelta(days=+1) + for expected in reversed(GMCR): + assert_offset_equal(offset_neg1, date, expected) + date = date + offset_neg1 + + lomq_aug_sat_4 = makeFY5253LastOfMonthQuarter( + 1, startingMonth=8, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + lomq_sep_sat_4 = makeFY5253LastOfMonthQuarter( + 1, startingMonth=9, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + + on_offset_cases = [ + # From Wikipedia + (lomq_aug_sat_4, datetime(2006, 8, 26), True), + (lomq_aug_sat_4, datetime(2007, 8, 25), True), + (lomq_aug_sat_4, datetime(2008, 8, 30), True), + (lomq_aug_sat_4, datetime(2009, 8, 29), True), + (lomq_aug_sat_4, datetime(2010, 8, 28), True), + (lomq_aug_sat_4, datetime(2011, 8, 27), True), + (lomq_aug_sat_4, datetime(2019, 8, 31), True), + (lomq_aug_sat_4, datetime(2006, 8, 27), False), + (lomq_aug_sat_4, datetime(2007, 8, 28), False), + (lomq_aug_sat_4, datetime(2008, 8, 31), False), + (lomq_aug_sat_4, datetime(2009, 8, 30), False), + (lomq_aug_sat_4, datetime(2010, 8, 29), False), + (lomq_aug_sat_4, datetime(2011, 8, 28), False), + (lomq_aug_sat_4, datetime(2006, 8, 25), False), + (lomq_aug_sat_4, datetime(2007, 8, 24), False), + (lomq_aug_sat_4, datetime(2008, 8, 29), False), + (lomq_aug_sat_4, datetime(2009, 8, 28), False), + (lomq_aug_sat_4, datetime(2010, 8, 27), False), + (lomq_aug_sat_4, datetime(2011, 8, 26), False), + (lomq_aug_sat_4, datetime(2019, 8, 30), False), + # From GMCR + (lomq_sep_sat_4, datetime(2010, 9, 25), True), + (lomq_sep_sat_4, datetime(2011, 9, 24), True), + (lomq_sep_sat_4, datetime(2012, 9, 29), True), + (lomq_sep_sat_4, datetime(2013, 6, 29), True), + (lomq_sep_sat_4, datetime(2012, 6, 23), True), + (lomq_sep_sat_4, datetime(2012, 6, 30), False), + (lomq_sep_sat_4, datetime(2013, 3, 30), True), + (lomq_sep_sat_4, datetime(2012, 3, 24), True), + (lomq_sep_sat_4, datetime(2012, 12, 29), True), + (lomq_sep_sat_4, datetime(2011, 12, 24), True), + # INTC (extra week in Q1) + # See: http://www.intc.com/releasedetail.cfm?ReleaseID=542844 + ( + makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ), + datetime(2011, 4, 2), + True, + ), + # see: http://google.brand.edgar-online.com/?sym=INTC&formtypeID=7 + ( + makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ), + datetime(2012, 12, 29), + True, + ), + ( + makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ), + datetime(2011, 12, 31), + True, + ), + ( + makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ), + datetime(2010, 12, 25), + True, + ), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + def test_year_has_extra_week(self): + # End of long Q1 + assert makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ).year_has_extra_week(datetime(2011, 4, 2)) + + # Start of long Q1 + assert makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ).year_has_extra_week(datetime(2010, 12, 26)) + + # End of year before year with long Q1 + assert not makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ).year_has_extra_week(datetime(2010, 12, 25)) + + for year in [ + x for x in range(1994, 2011 + 1) if x not in [2011, 2005, 2000, 1994] + ]: + assert not makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ).year_has_extra_week(datetime(year, 4, 2)) + + # Other long years + assert makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ).year_has_extra_week(datetime(2005, 4, 2)) + + assert makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ).year_has_extra_week(datetime(2000, 4, 2)) + + assert makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ).year_has_extra_week(datetime(1994, 4, 2)) + + def test_get_weeks(self): + sat_dec_1 = makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=1 + ) + sat_dec_4 = makeFY5253LastOfMonthQuarter( + 1, startingMonth=12, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + + assert sat_dec_1.get_weeks(datetime(2011, 4, 2)) == [14, 13, 13, 13] + assert sat_dec_4.get_weeks(datetime(2011, 4, 2)) == [13, 13, 13, 14] + assert sat_dec_1.get_weeks(datetime(2010, 12, 25)) == [13, 13, 13, 13] + + +class TestFY5253NearestEndMonthQuarter: + offset_nem_sat_aug_4 = makeFY5253NearestEndMonthQuarter( + 1, startingMonth=8, weekday=WeekDay.SAT, qtr_with_extra_week=4 + ) + offset_nem_thu_aug_4 = makeFY5253NearestEndMonthQuarter( + 1, startingMonth=8, weekday=WeekDay.THU, qtr_with_extra_week=4 + ) + offset_n = FY5253(weekday=WeekDay.TUE, startingMonth=12, variation="nearest") + + on_offset_cases = [ + # From Wikipedia + (offset_nem_sat_aug_4, datetime(2006, 9, 2), True), + (offset_nem_sat_aug_4, datetime(2007, 9, 1), True), + (offset_nem_sat_aug_4, datetime(2008, 8, 30), True), + (offset_nem_sat_aug_4, datetime(2009, 8, 29), True), + (offset_nem_sat_aug_4, datetime(2010, 8, 28), True), + (offset_nem_sat_aug_4, datetime(2011, 9, 3), True), + (offset_nem_sat_aug_4, datetime(2016, 9, 3), True), + (offset_nem_sat_aug_4, datetime(2017, 9, 2), True), + (offset_nem_sat_aug_4, datetime(2018, 9, 1), True), + (offset_nem_sat_aug_4, datetime(2019, 8, 31), True), + (offset_nem_sat_aug_4, datetime(2006, 8, 27), False), + (offset_nem_sat_aug_4, datetime(2007, 8, 28), False), + (offset_nem_sat_aug_4, datetime(2008, 8, 31), False), + (offset_nem_sat_aug_4, datetime(2009, 8, 30), False), + (offset_nem_sat_aug_4, datetime(2010, 8, 29), False), + (offset_nem_sat_aug_4, datetime(2011, 8, 28), False), + (offset_nem_sat_aug_4, datetime(2006, 8, 25), False), + (offset_nem_sat_aug_4, datetime(2007, 8, 24), False), + (offset_nem_sat_aug_4, datetime(2008, 8, 29), False), + (offset_nem_sat_aug_4, datetime(2009, 8, 28), False), + (offset_nem_sat_aug_4, datetime(2010, 8, 27), False), + (offset_nem_sat_aug_4, datetime(2011, 8, 26), False), + (offset_nem_sat_aug_4, datetime(2019, 8, 30), False), + # From Micron, see: + # http://google.brand.edgar-online.com/?sym=MU&formtypeID=7 + (offset_nem_thu_aug_4, datetime(2012, 8, 30), True), + (offset_nem_thu_aug_4, datetime(2011, 9, 1), True), + # See: http://google.brand.edgar-online.com/?sym=MU&formtypeID=13 + (offset_nem_thu_aug_4, datetime(2013, 5, 30), True), + (offset_nem_thu_aug_4, datetime(2013, 2, 28), True), + (offset_nem_thu_aug_4, datetime(2012, 11, 29), True), + (offset_nem_thu_aug_4, datetime(2012, 5, 31), True), + (offset_nem_thu_aug_4, datetime(2007, 3, 1), True), + (offset_nem_thu_aug_4, datetime(1994, 3, 3), True), + (offset_n, datetime(2012, 12, 31), False), + (offset_n, datetime(2013, 1, 1), True), + (offset_n, datetime(2013, 1, 2), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + def test_offset(self): + offset = makeFY5253NearestEndMonthQuarter( + 1, startingMonth=8, weekday=WeekDay.THU, qtr_with_extra_week=4 + ) + + MU = [ + datetime(2012, 5, 31), + datetime(2012, 8, 30), + datetime(2012, 11, 29), + datetime(2013, 2, 28), + datetime(2013, 5, 30), + ] + + date = MU[0] + relativedelta(days=-1) + for expected in MU: + assert_offset_equal(offset, date, expected) + date = date + offset + + assert_offset_equal(offset, datetime(2012, 5, 31), datetime(2012, 8, 30)) + assert_offset_equal(offset, datetime(2012, 5, 30), datetime(2012, 5, 31)) + + offset2 = FY5253Quarter( + weekday=5, startingMonth=12, variation="last", qtr_with_extra_week=4 + ) + + assert_offset_equal(offset2, datetime(2013, 1, 15), datetime(2013, 3, 30)) + + +def test_bunched_yearends(): + # GH#14774 cases with two fiscal year-ends in the same calendar-year + fy = FY5253(n=1, weekday=5, startingMonth=12, variation="nearest") + dt = Timestamp("2004-01-01") + assert fy.rollback(dt) == Timestamp("2002-12-28") + assert (-fy)._apply(dt) == Timestamp("2002-12-28") + assert dt - fy == Timestamp("2002-12-28") + + assert fy.rollforward(dt) == Timestamp("2004-01-03") + assert fy._apply(dt) == Timestamp("2004-01-03") + assert fy + dt == Timestamp("2004-01-03") + assert dt + fy == Timestamp("2004-01-03") + + # Same thing, but starting from a Timestamp in the previous year. + dt = Timestamp("2003-12-31") + assert fy.rollback(dt) == Timestamp("2002-12-28") + assert (-fy)._apply(dt) == Timestamp("2002-12-28") + assert dt - fy == Timestamp("2002-12-28") + + +def test_fy5253_last_onoffset(): + # GH#18877 dates on the year-end but not normalized to midnight + offset = FY5253(n=-5, startingMonth=5, variation="last", weekday=0) + ts = Timestamp("1984-05-28 06:29:43.955911354+0200", tz="Europe/San_Marino") + fast = offset.is_on_offset(ts) + slow = (ts + offset) - offset == ts + assert fast == slow + + +def test_fy5253_nearest_onoffset(): + # GH#18877 dates on the year-end but not normalized to midnight + offset = FY5253(n=3, startingMonth=7, variation="nearest", weekday=2) + ts = Timestamp("2032-07-28 00:12:59.035729419+0000", tz="Africa/Dakar") + fast = offset.is_on_offset(ts) + slow = (ts + offset) - offset == ts + assert fast == slow + + +def test_fy5253qtr_onoffset_nearest(): + # GH#19036 + ts = Timestamp("1985-09-02 23:57:46.232550356-0300", tz="Atlantic/Bermuda") + offset = FY5253Quarter( + n=3, qtr_with_extra_week=1, startingMonth=2, variation="nearest", weekday=0 + ) + fast = offset.is_on_offset(ts) + slow = (ts + offset) - offset == ts + assert fast == slow + + +def test_fy5253qtr_onoffset_last(): + # GH#19036 + offset = FY5253Quarter( + n=-2, qtr_with_extra_week=1, startingMonth=7, variation="last", weekday=2 + ) + ts = Timestamp("2011-01-26 19:03:40.331096129+0200", tz="Africa/Windhoek") + slow = (ts + offset) - offset == ts + fast = offset.is_on_offset(ts) + assert fast == slow diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_index.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_index.py new file mode 100644 index 0000000000000000000000000000000000000000..7a62944556d11b536f7a64e49d4a9ff11e90ec0e --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_index.py @@ -0,0 +1,57 @@ +""" +Tests for offset behavior with indices. +""" +import pytest + +from pandas import ( + Series, + date_range, +) + +from pandas.tseries.offsets import ( + BMonthBegin, + BMonthEnd, + BQuarterBegin, + BQuarterEnd, + BYearBegin, + BYearEnd, + MonthBegin, + MonthEnd, + QuarterBegin, + QuarterEnd, + YearBegin, + YearEnd, +) + + +@pytest.mark.parametrize("n", [-2, 1]) +@pytest.mark.parametrize( + "cls", + [ + MonthBegin, + MonthEnd, + BMonthBegin, + BMonthEnd, + QuarterBegin, + QuarterEnd, + BQuarterBegin, + BQuarterEnd, + YearBegin, + YearEnd, + BYearBegin, + BYearEnd, + ], +) +def test_apply_index(cls, n): + offset = cls(n=n) + rng = date_range(start="1/1/2000", periods=100000, freq="min") + ser = Series(rng) + + res = rng + offset + assert res.freq is None # not retained + assert res[0] == rng[0] + offset + assert res[-1] == rng[-1] + offset + res2 = ser + offset + # apply_index is only for indexes, not series, so no res2_v2 + assert res2.iloc[0] == ser.iloc[0] + offset + assert res2.iloc[-1] == ser.iloc[-1] + offset diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_month.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_month.py new file mode 100644 index 0000000000000000000000000000000000000000..2b643999c3ad34057156f4dc9f382dd3950e35c5 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_month.py @@ -0,0 +1,666 @@ +""" +Tests for the following offsets: +- SemiMonthBegin +- SemiMonthEnd +- MonthBegin +- MonthEnd +""" +from __future__ import annotations + +from datetime import datetime + +import pytest + +from pandas._libs.tslibs import Timestamp +from pandas._libs.tslibs.offsets import ( + MonthBegin, + MonthEnd, + SemiMonthBegin, + SemiMonthEnd, +) + +from pandas import ( + DatetimeIndex, + Series, + _testing as tm, +) +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + + +class TestSemiMonthEnd: + def test_offset_whole_year(self): + dates = ( + datetime(2007, 12, 31), + datetime(2008, 1, 15), + datetime(2008, 1, 31), + datetime(2008, 2, 15), + datetime(2008, 2, 29), + datetime(2008, 3, 15), + datetime(2008, 3, 31), + datetime(2008, 4, 15), + datetime(2008, 4, 30), + datetime(2008, 5, 15), + datetime(2008, 5, 31), + datetime(2008, 6, 15), + datetime(2008, 6, 30), + datetime(2008, 7, 15), + datetime(2008, 7, 31), + datetime(2008, 8, 15), + datetime(2008, 8, 31), + datetime(2008, 9, 15), + datetime(2008, 9, 30), + datetime(2008, 10, 15), + datetime(2008, 10, 31), + datetime(2008, 11, 15), + datetime(2008, 11, 30), + datetime(2008, 12, 15), + datetime(2008, 12, 31), + ) + + for base, exp_date in zip(dates[:-1], dates[1:]): + assert_offset_equal(SemiMonthEnd(), base, exp_date) + + # ensure .apply_index works as expected + shift = DatetimeIndex(dates[:-1]) + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = SemiMonthEnd() + shift + + exp = DatetimeIndex(dates[1:]) + tm.assert_index_equal(result, exp) + + offset_cases = [] + offset_cases.append( + ( + SemiMonthEnd(), + { + datetime(2008, 1, 1): datetime(2008, 1, 15), + datetime(2008, 1, 15): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 2, 15), + datetime(2006, 12, 14): datetime(2006, 12, 15), + datetime(2006, 12, 29): datetime(2006, 12, 31), + datetime(2006, 12, 31): datetime(2007, 1, 15), + datetime(2007, 1, 1): datetime(2007, 1, 15), + datetime(2006, 12, 1): datetime(2006, 12, 15), + datetime(2006, 12, 15): datetime(2006, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + SemiMonthEnd(day_of_month=20), + { + datetime(2008, 1, 1): datetime(2008, 1, 20), + datetime(2008, 1, 15): datetime(2008, 1, 20), + datetime(2008, 1, 21): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 2, 20), + datetime(2006, 12, 14): datetime(2006, 12, 20), + datetime(2006, 12, 29): datetime(2006, 12, 31), + datetime(2006, 12, 31): datetime(2007, 1, 20), + datetime(2007, 1, 1): datetime(2007, 1, 20), + datetime(2006, 12, 1): datetime(2006, 12, 20), + datetime(2006, 12, 15): datetime(2006, 12, 20), + }, + ) + ) + + offset_cases.append( + ( + SemiMonthEnd(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 15), + datetime(2008, 1, 16): datetime(2008, 1, 31), + datetime(2008, 1, 15): datetime(2008, 1, 15), + datetime(2008, 1, 31): datetime(2008, 1, 31), + datetime(2006, 12, 29): datetime(2006, 12, 31), + datetime(2006, 12, 31): datetime(2006, 12, 31), + datetime(2007, 1, 1): datetime(2007, 1, 15), + }, + ) + ) + + offset_cases.append( + ( + SemiMonthEnd(0, day_of_month=16), + { + datetime(2008, 1, 1): datetime(2008, 1, 16), + datetime(2008, 1, 16): datetime(2008, 1, 16), + datetime(2008, 1, 15): datetime(2008, 1, 16), + datetime(2008, 1, 31): datetime(2008, 1, 31), + datetime(2006, 12, 29): datetime(2006, 12, 31), + datetime(2006, 12, 31): datetime(2006, 12, 31), + datetime(2007, 1, 1): datetime(2007, 1, 16), + }, + ) + ) + + offset_cases.append( + ( + SemiMonthEnd(2), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 2, 29), + datetime(2006, 12, 29): datetime(2007, 1, 15), + datetime(2006, 12, 31): datetime(2007, 1, 31), + datetime(2007, 1, 1): datetime(2007, 1, 31), + datetime(2007, 1, 16): datetime(2007, 2, 15), + datetime(2006, 11, 1): datetime(2006, 11, 30), + }, + ) + ) + + offset_cases.append( + ( + SemiMonthEnd(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 31), + datetime(2008, 6, 30): datetime(2008, 6, 15), + datetime(2008, 12, 31): datetime(2008, 12, 15), + datetime(2006, 12, 29): datetime(2006, 12, 15), + datetime(2006, 12, 30): datetime(2006, 12, 15), + datetime(2007, 1, 1): datetime(2006, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + SemiMonthEnd(-1, day_of_month=4), + { + datetime(2007, 1, 1): datetime(2006, 12, 31), + datetime(2007, 1, 4): datetime(2006, 12, 31), + datetime(2008, 6, 30): datetime(2008, 6, 4), + datetime(2008, 12, 31): datetime(2008, 12, 4), + datetime(2006, 12, 5): datetime(2006, 12, 4), + datetime(2006, 12, 30): datetime(2006, 12, 4), + datetime(2007, 1, 1): datetime(2006, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + SemiMonthEnd(-2), + { + datetime(2007, 1, 1): datetime(2006, 12, 15), + datetime(2008, 6, 30): datetime(2008, 5, 31), + datetime(2008, 3, 15): datetime(2008, 2, 15), + datetime(2008, 12, 31): datetime(2008, 11, 30), + datetime(2006, 12, 29): datetime(2006, 11, 30), + datetime(2006, 12, 14): datetime(2006, 11, 15), + datetime(2007, 1, 1): datetime(2006, 12, 15), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + @pytest.mark.parametrize("case", offset_cases) + def test_apply_index(self, case): + # https://github.com/pandas-dev/pandas/issues/34580 + offset, cases = case + shift = DatetimeIndex(cases.keys()) + exp = DatetimeIndex(cases.values()) + + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = offset + shift + tm.assert_index_equal(result, exp) + + on_offset_cases = [ + (datetime(2007, 12, 31), True), + (datetime(2007, 12, 15), True), + (datetime(2007, 12, 14), False), + (datetime(2007, 12, 1), False), + (datetime(2008, 2, 29), True), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + dt, expected = case + assert_is_on_offset(SemiMonthEnd(), dt, expected) + + @pytest.mark.parametrize("klass", [Series, DatetimeIndex]) + def test_vectorized_offset_addition(self, klass): + shift = klass( + [ + Timestamp("2000-01-15 00:15:00", tz="US/Central"), + Timestamp("2000-02-15", tz="US/Central"), + ], + name="a", + ) + + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = shift + SemiMonthEnd() + result2 = SemiMonthEnd() + shift + + exp = klass( + [ + Timestamp("2000-01-31 00:15:00", tz="US/Central"), + Timestamp("2000-02-29", tz="US/Central"), + ], + name="a", + ) + tm.assert_equal(result, exp) + tm.assert_equal(result2, exp) + + shift = klass( + [ + Timestamp("2000-01-01 00:15:00", tz="US/Central"), + Timestamp("2000-02-01", tz="US/Central"), + ], + name="a", + ) + + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = shift + SemiMonthEnd() + result2 = SemiMonthEnd() + shift + + exp = klass( + [ + Timestamp("2000-01-15 00:15:00", tz="US/Central"), + Timestamp("2000-02-15", tz="US/Central"), + ], + name="a", + ) + tm.assert_equal(result, exp) + tm.assert_equal(result2, exp) + + +class TestSemiMonthBegin: + def test_offset_whole_year(self): + dates = ( + datetime(2007, 12, 15), + datetime(2008, 1, 1), + datetime(2008, 1, 15), + datetime(2008, 2, 1), + datetime(2008, 2, 15), + datetime(2008, 3, 1), + datetime(2008, 3, 15), + datetime(2008, 4, 1), + datetime(2008, 4, 15), + datetime(2008, 5, 1), + datetime(2008, 5, 15), + datetime(2008, 6, 1), + datetime(2008, 6, 15), + datetime(2008, 7, 1), + datetime(2008, 7, 15), + datetime(2008, 8, 1), + datetime(2008, 8, 15), + datetime(2008, 9, 1), + datetime(2008, 9, 15), + datetime(2008, 10, 1), + datetime(2008, 10, 15), + datetime(2008, 11, 1), + datetime(2008, 11, 15), + datetime(2008, 12, 1), + datetime(2008, 12, 15), + ) + + for base, exp_date in zip(dates[:-1], dates[1:]): + assert_offset_equal(SemiMonthBegin(), base, exp_date) + + # ensure .apply_index works as expected + shift = DatetimeIndex(dates[:-1]) + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = SemiMonthBegin() + shift + + exp = DatetimeIndex(dates[1:]) + tm.assert_index_equal(result, exp) + + offset_cases = [ + ( + SemiMonthBegin(), + { + datetime(2008, 1, 1): datetime(2008, 1, 15), + datetime(2008, 1, 15): datetime(2008, 2, 1), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2006, 12, 14): datetime(2006, 12, 15), + datetime(2006, 12, 29): datetime(2007, 1, 1), + datetime(2006, 12, 31): datetime(2007, 1, 1), + datetime(2007, 1, 1): datetime(2007, 1, 15), + datetime(2006, 12, 1): datetime(2006, 12, 15), + datetime(2006, 12, 15): datetime(2007, 1, 1), + }, + ), + ( + SemiMonthBegin(day_of_month=20), + { + datetime(2008, 1, 1): datetime(2008, 1, 20), + datetime(2008, 1, 15): datetime(2008, 1, 20), + datetime(2008, 1, 21): datetime(2008, 2, 1), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2006, 12, 14): datetime(2006, 12, 20), + datetime(2006, 12, 29): datetime(2007, 1, 1), + datetime(2006, 12, 31): datetime(2007, 1, 1), + datetime(2007, 1, 1): datetime(2007, 1, 20), + datetime(2006, 12, 1): datetime(2006, 12, 20), + datetime(2006, 12, 15): datetime(2006, 12, 20), + }, + ), + ( + SemiMonthBegin(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 1, 16): datetime(2008, 2, 1), + datetime(2008, 1, 15): datetime(2008, 1, 15), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2006, 12, 29): datetime(2007, 1, 1), + datetime(2006, 12, 2): datetime(2006, 12, 15), + datetime(2007, 1, 1): datetime(2007, 1, 1), + }, + ), + ( + SemiMonthBegin(0, day_of_month=16), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 1, 16): datetime(2008, 1, 16), + datetime(2008, 1, 15): datetime(2008, 1, 16), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2006, 12, 29): datetime(2007, 1, 1), + datetime(2006, 12, 31): datetime(2007, 1, 1), + datetime(2007, 1, 5): datetime(2007, 1, 16), + datetime(2007, 1, 1): datetime(2007, 1, 1), + }, + ), + ( + SemiMonthBegin(2), + { + datetime(2008, 1, 1): datetime(2008, 2, 1), + datetime(2008, 1, 31): datetime(2008, 2, 15), + datetime(2006, 12, 1): datetime(2007, 1, 1), + datetime(2006, 12, 29): datetime(2007, 1, 15), + datetime(2006, 12, 15): datetime(2007, 1, 15), + datetime(2007, 1, 1): datetime(2007, 2, 1), + datetime(2007, 1, 16): datetime(2007, 2, 15), + datetime(2006, 11, 1): datetime(2006, 12, 1), + }, + ), + ( + SemiMonthBegin(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 15), + datetime(2008, 6, 30): datetime(2008, 6, 15), + datetime(2008, 6, 14): datetime(2008, 6, 1), + datetime(2008, 12, 31): datetime(2008, 12, 15), + datetime(2006, 12, 29): datetime(2006, 12, 15), + datetime(2006, 12, 15): datetime(2006, 12, 1), + datetime(2007, 1, 1): datetime(2006, 12, 15), + }, + ), + ( + SemiMonthBegin(-1, day_of_month=4), + { + datetime(2007, 1, 1): datetime(2006, 12, 4), + datetime(2007, 1, 4): datetime(2007, 1, 1), + datetime(2008, 6, 30): datetime(2008, 6, 4), + datetime(2008, 12, 31): datetime(2008, 12, 4), + datetime(2006, 12, 5): datetime(2006, 12, 4), + datetime(2006, 12, 30): datetime(2006, 12, 4), + datetime(2006, 12, 2): datetime(2006, 12, 1), + datetime(2007, 1, 1): datetime(2006, 12, 4), + }, + ), + ( + SemiMonthBegin(-2), + { + datetime(2007, 1, 1): datetime(2006, 12, 1), + datetime(2008, 6, 30): datetime(2008, 6, 1), + datetime(2008, 6, 14): datetime(2008, 5, 15), + datetime(2008, 12, 31): datetime(2008, 12, 1), + datetime(2006, 12, 29): datetime(2006, 12, 1), + datetime(2006, 12, 15): datetime(2006, 11, 15), + datetime(2007, 1, 1): datetime(2006, 12, 1), + }, + ), + ] + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + @pytest.mark.parametrize("case", offset_cases) + def test_apply_index(self, case): + offset, cases = case + shift = DatetimeIndex(cases.keys()) + + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = offset + shift + + exp = DatetimeIndex(cases.values()) + tm.assert_index_equal(result, exp) + + on_offset_cases = [ + (datetime(2007, 12, 1), True), + (datetime(2007, 12, 15), True), + (datetime(2007, 12, 14), False), + (datetime(2007, 12, 31), False), + (datetime(2008, 2, 15), True), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + dt, expected = case + assert_is_on_offset(SemiMonthBegin(), dt, expected) + + @pytest.mark.parametrize("klass", [Series, DatetimeIndex]) + def test_vectorized_offset_addition(self, klass): + shift = klass( + [ + Timestamp("2000-01-15 00:15:00", tz="US/Central"), + Timestamp("2000-02-15", tz="US/Central"), + ], + name="a", + ) + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = shift + SemiMonthBegin() + result2 = SemiMonthBegin() + shift + + exp = klass( + [ + Timestamp("2000-02-01 00:15:00", tz="US/Central"), + Timestamp("2000-03-01", tz="US/Central"), + ], + name="a", + ) + tm.assert_equal(result, exp) + tm.assert_equal(result2, exp) + + shift = klass( + [ + Timestamp("2000-01-01 00:15:00", tz="US/Central"), + Timestamp("2000-02-01", tz="US/Central"), + ], + name="a", + ) + with tm.assert_produces_warning(None): + # GH#22535 check that we don't get a FutureWarning from adding + # an integer array to PeriodIndex + result = shift + SemiMonthBegin() + result2 = SemiMonthBegin() + shift + + exp = klass( + [ + Timestamp("2000-01-15 00:15:00", tz="US/Central"), + Timestamp("2000-02-15", tz="US/Central"), + ], + name="a", + ) + tm.assert_equal(result, exp) + tm.assert_equal(result2, exp) + + +class TestMonthBegin: + offset_cases = [] + # NOTE: I'm not entirely happy with the logic here for Begin -ss + # see thread 'offset conventions' on the ML + offset_cases.append( + ( + MonthBegin(), + { + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2008, 2, 1): datetime(2008, 3, 1), + datetime(2006, 12, 31): datetime(2007, 1, 1), + datetime(2006, 12, 1): datetime(2007, 1, 1), + datetime(2007, 1, 31): datetime(2007, 2, 1), + }, + ) + ) + + offset_cases.append( + ( + MonthBegin(0), + { + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2006, 12, 3): datetime(2007, 1, 1), + datetime(2007, 1, 31): datetime(2007, 2, 1), + }, + ) + ) + + offset_cases.append( + ( + MonthBegin(2), + { + datetime(2008, 2, 29): datetime(2008, 4, 1), + datetime(2008, 1, 31): datetime(2008, 3, 1), + datetime(2006, 12, 31): datetime(2007, 2, 1), + datetime(2007, 12, 28): datetime(2008, 2, 1), + datetime(2007, 1, 1): datetime(2007, 3, 1), + datetime(2006, 11, 1): datetime(2007, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + MonthBegin(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 1), + datetime(2008, 5, 31): datetime(2008, 5, 1), + datetime(2008, 12, 31): datetime(2008, 12, 1), + datetime(2006, 12, 29): datetime(2006, 12, 1), + datetime(2006, 1, 2): datetime(2006, 1, 1), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + +class TestMonthEnd: + def test_day_of_month(self): + dt = datetime(2007, 1, 1) + offset = MonthEnd() + + result = dt + offset + assert result == Timestamp(2007, 1, 31) + + result = result + offset + assert result == Timestamp(2007, 2, 28) + + def test_normalize(self): + dt = datetime(2007, 1, 1, 3) + + result = dt + MonthEnd(normalize=True) + expected = dt.replace(hour=0) + MonthEnd() + assert result == expected + + offset_cases = [] + offset_cases.append( + ( + MonthEnd(), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 2, 29), + datetime(2006, 12, 29): datetime(2006, 12, 31), + datetime(2006, 12, 31): datetime(2007, 1, 31), + datetime(2007, 1, 1): datetime(2007, 1, 31), + datetime(2006, 12, 1): datetime(2006, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + MonthEnd(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 1, 31), + datetime(2006, 12, 29): datetime(2006, 12, 31), + datetime(2006, 12, 31): datetime(2006, 12, 31), + datetime(2007, 1, 1): datetime(2007, 1, 31), + }, + ) + ) + + offset_cases.append( + ( + MonthEnd(2), + { + datetime(2008, 1, 1): datetime(2008, 2, 29), + datetime(2008, 1, 31): datetime(2008, 3, 31), + datetime(2006, 12, 29): datetime(2007, 1, 31), + datetime(2006, 12, 31): datetime(2007, 2, 28), + datetime(2007, 1, 1): datetime(2007, 2, 28), + datetime(2006, 11, 1): datetime(2006, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + MonthEnd(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 31), + datetime(2008, 6, 30): datetime(2008, 5, 31), + datetime(2008, 12, 31): datetime(2008, 11, 30), + datetime(2006, 12, 29): datetime(2006, 11, 30), + datetime(2006, 12, 30): datetime(2006, 11, 30), + datetime(2007, 1, 1): datetime(2006, 12, 31), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (MonthEnd(), datetime(2007, 12, 31), True), + (MonthEnd(), datetime(2008, 1, 1), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_offsets.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_offsets.py new file mode 100644 index 0000000000000000000000000000000000000000..62afb8b83d576a7a16565840b6c3f61cfd26e9e1 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_offsets.py @@ -0,0 +1,1185 @@ +""" +Tests of pandas.tseries.offsets +""" +from __future__ import annotations + +from datetime import ( + datetime, + timedelta, +) + +import numpy as np +import pytest + +from pandas._libs.tslibs import ( + NaT, + Timedelta, + Timestamp, + conversion, + timezones, +) +import pandas._libs.tslibs.offsets as liboffsets +from pandas._libs.tslibs.offsets import ( + _get_offset, + _offset_map, + to_offset, +) +from pandas._libs.tslibs.period import INVALID_FREQ_ERR_MSG +from pandas.errors import PerformanceWarning + +from pandas import ( + DataFrame, + DatetimeIndex, + Series, + date_range, +) +import pandas._testing as tm +from pandas.tests.tseries.offsets.common import WeekDay + +from pandas.tseries import offsets +from pandas.tseries.offsets import ( + FY5253, + BDay, + BMonthEnd, + BusinessHour, + CustomBusinessDay, + CustomBusinessHour, + CustomBusinessMonthBegin, + CustomBusinessMonthEnd, + DateOffset, + Easter, + FY5253Quarter, + LastWeekOfMonth, + MonthBegin, + Nano, + Tick, + Week, + WeekOfMonth, +) + +_ARITHMETIC_DATE_OFFSET = [ + "years", + "months", + "weeks", + "days", + "hours", + "minutes", + "seconds", + "milliseconds", + "microseconds", +] + + +def _create_offset(klass, value=1, normalize=False): + # create instance from offset class + if klass is FY5253: + klass = klass( + n=value, + startingMonth=1, + weekday=1, + variation="last", + normalize=normalize, + ) + elif klass is FY5253Quarter: + klass = klass( + n=value, + startingMonth=1, + weekday=1, + qtr_with_extra_week=1, + variation="last", + normalize=normalize, + ) + elif klass is LastWeekOfMonth: + klass = klass(n=value, weekday=5, normalize=normalize) + elif klass is WeekOfMonth: + klass = klass(n=value, week=1, weekday=5, normalize=normalize) + elif klass is Week: + klass = klass(n=value, weekday=5, normalize=normalize) + elif klass is DateOffset: + klass = klass(days=value, normalize=normalize) + else: + klass = klass(value, normalize=normalize) + return klass + + +@pytest.fixture( + params=[ + getattr(offsets, o) + for o in offsets.__all__ + if issubclass(getattr(offsets, o), liboffsets.MonthOffset) + and o != "MonthOffset" + ] +) +def month_classes(request): + """ + Fixture for month based datetime offsets available for a time series. + """ + return request.param + + +@pytest.fixture( + params=[ + getattr(offsets, o) for o in offsets.__all__ if o not in ("Tick", "BaseOffset") + ] +) +def offset_types(request): + """ + Fixture for all the datetime offsets available for a time series. + """ + return request.param + + +@pytest.fixture +def dt(): + return Timestamp(datetime(2008, 1, 2)) + + +@pytest.fixture +def expecteds(): + # executed value created by _create_offset + # are applied to 2011/01/01 09:00 (Saturday) + # used for .apply and .rollforward + return { + "Day": Timestamp("2011-01-02 09:00:00"), + "DateOffset": Timestamp("2011-01-02 09:00:00"), + "BusinessDay": Timestamp("2011-01-03 09:00:00"), + "CustomBusinessDay": Timestamp("2011-01-03 09:00:00"), + "CustomBusinessMonthEnd": Timestamp("2011-01-31 09:00:00"), + "CustomBusinessMonthBegin": Timestamp("2011-01-03 09:00:00"), + "MonthBegin": Timestamp("2011-02-01 09:00:00"), + "BusinessMonthBegin": Timestamp("2011-01-03 09:00:00"), + "MonthEnd": Timestamp("2011-01-31 09:00:00"), + "SemiMonthEnd": Timestamp("2011-01-15 09:00:00"), + "SemiMonthBegin": Timestamp("2011-01-15 09:00:00"), + "BusinessMonthEnd": Timestamp("2011-01-31 09:00:00"), + "YearBegin": Timestamp("2012-01-01 09:00:00"), + "BYearBegin": Timestamp("2011-01-03 09:00:00"), + "YearEnd": Timestamp("2011-12-31 09:00:00"), + "BYearEnd": Timestamp("2011-12-30 09:00:00"), + "QuarterBegin": Timestamp("2011-03-01 09:00:00"), + "BQuarterBegin": Timestamp("2011-03-01 09:00:00"), + "QuarterEnd": Timestamp("2011-03-31 09:00:00"), + "BQuarterEnd": Timestamp("2011-03-31 09:00:00"), + "BusinessHour": Timestamp("2011-01-03 10:00:00"), + "CustomBusinessHour": Timestamp("2011-01-03 10:00:00"), + "WeekOfMonth": Timestamp("2011-01-08 09:00:00"), + "LastWeekOfMonth": Timestamp("2011-01-29 09:00:00"), + "FY5253Quarter": Timestamp("2011-01-25 09:00:00"), + "FY5253": Timestamp("2011-01-25 09:00:00"), + "Week": Timestamp("2011-01-08 09:00:00"), + "Easter": Timestamp("2011-04-24 09:00:00"), + "Hour": Timestamp("2011-01-01 10:00:00"), + "Minute": Timestamp("2011-01-01 09:01:00"), + "Second": Timestamp("2011-01-01 09:00:01"), + "Milli": Timestamp("2011-01-01 09:00:00.001000"), + "Micro": Timestamp("2011-01-01 09:00:00.000001"), + "Nano": Timestamp("2011-01-01T09:00:00.000000001"), + } + + +class TestCommon: + def test_immutable(self, offset_types): + # GH#21341 check that __setattr__ raises + offset = _create_offset(offset_types) + msg = "objects is not writable|DateOffset objects are immutable" + with pytest.raises(AttributeError, match=msg): + offset.normalize = True + with pytest.raises(AttributeError, match=msg): + offset.n = 91 + + def test_return_type(self, offset_types): + offset = _create_offset(offset_types) + + # make sure that we are returning a Timestamp + result = Timestamp("20080101") + offset + assert isinstance(result, Timestamp) + + # make sure that we are returning NaT + assert NaT + offset is NaT + assert offset + NaT is NaT + + assert NaT - offset is NaT + assert (-offset)._apply(NaT) is NaT + + def test_offset_n(self, offset_types): + offset = _create_offset(offset_types) + assert offset.n == 1 + + neg_offset = offset * -1 + assert neg_offset.n == -1 + + mul_offset = offset * 3 + assert mul_offset.n == 3 + + def test_offset_timedelta64_arg(self, offset_types): + # check that offset._validate_n raises TypeError on a timedelt64 + # object + off = _create_offset(offset_types) + + td64 = np.timedelta64(4567, "s") + with pytest.raises(TypeError, match="argument must be an integer"): + type(off)(n=td64, **off.kwds) + + def test_offset_mul_ndarray(self, offset_types): + off = _create_offset(offset_types) + + expected = np.array([[off, off * 2], [off * 3, off * 4]]) + + result = np.array([[1, 2], [3, 4]]) * off + tm.assert_numpy_array_equal(result, expected) + + result = off * np.array([[1, 2], [3, 4]]) + tm.assert_numpy_array_equal(result, expected) + + def test_offset_freqstr(self, offset_types): + offset = _create_offset(offset_types) + + freqstr = offset.freqstr + if freqstr not in ("", "", "LWOM-SAT"): + code = _get_offset(freqstr) + assert offset.rule_code == code + + def _check_offsetfunc_works(self, offset, funcname, dt, expected, normalize=False): + if normalize and issubclass(offset, Tick): + # normalize=True disallowed for Tick subclasses GH#21427 + return + + offset_s = _create_offset(offset, normalize=normalize) + func = getattr(offset_s, funcname) + + result = func(dt) + assert isinstance(result, Timestamp) + assert result == expected + + result = func(Timestamp(dt)) + assert isinstance(result, Timestamp) + assert result == expected + + # see gh-14101 + ts = Timestamp(dt) + Nano(5) + # test nanosecond is preserved + with tm.assert_produces_warning(None): + result = func(ts) + + assert isinstance(result, Timestamp) + if normalize is False: + assert result == expected + Nano(5) + else: + assert result == expected + + if isinstance(dt, np.datetime64): + # test tz when input is datetime or Timestamp + return + + for tz in [ + None, + "UTC", + "Asia/Tokyo", + "US/Eastern", + "dateutil/Asia/Tokyo", + "dateutil/US/Pacific", + ]: + expected_localize = expected.tz_localize(tz) + tz_obj = timezones.maybe_get_tz(tz) + dt_tz = conversion.localize_pydatetime(dt, tz_obj) + + result = func(dt_tz) + assert isinstance(result, Timestamp) + assert result == expected_localize + + result = func(Timestamp(dt, tz=tz)) + assert isinstance(result, Timestamp) + assert result == expected_localize + + # see gh-14101 + ts = Timestamp(dt, tz=tz) + Nano(5) + # test nanosecond is preserved + with tm.assert_produces_warning(None): + result = func(ts) + assert isinstance(result, Timestamp) + if normalize is False: + assert result == expected_localize + Nano(5) + else: + assert result == expected_localize + + def test_apply(self, offset_types, expecteds): + sdt = datetime(2011, 1, 1, 9, 0) + ndt = np.datetime64("2011-01-01 09:00") + + expected = expecteds[offset_types.__name__] + expected_norm = Timestamp(expected.date()) + + for dt in [sdt, ndt]: + self._check_offsetfunc_works(offset_types, "_apply", dt, expected) + + self._check_offsetfunc_works( + offset_types, "_apply", dt, expected_norm, normalize=True + ) + + def test_rollforward(self, offset_types, expecteds): + expecteds = expecteds.copy() + + # result will not be changed if the target is on the offset + no_changes = [ + "Day", + "MonthBegin", + "SemiMonthBegin", + "YearBegin", + "Week", + "Hour", + "Minute", + "Second", + "Milli", + "Micro", + "Nano", + "DateOffset", + ] + for n in no_changes: + expecteds[n] = Timestamp("2011/01/01 09:00") + + expecteds["BusinessHour"] = Timestamp("2011-01-03 09:00:00") + expecteds["CustomBusinessHour"] = Timestamp("2011-01-03 09:00:00") + + # but be changed when normalize=True + norm_expected = expecteds.copy() + for k in norm_expected: + norm_expected[k] = Timestamp(norm_expected[k].date()) + + normalized = { + "Day": Timestamp("2011-01-02 00:00:00"), + "DateOffset": Timestamp("2011-01-02 00:00:00"), + "MonthBegin": Timestamp("2011-02-01 00:00:00"), + "SemiMonthBegin": Timestamp("2011-01-15 00:00:00"), + "YearBegin": Timestamp("2012-01-01 00:00:00"), + "Week": Timestamp("2011-01-08 00:00:00"), + "Hour": Timestamp("2011-01-01 00:00:00"), + "Minute": Timestamp("2011-01-01 00:00:00"), + "Second": Timestamp("2011-01-01 00:00:00"), + "Milli": Timestamp("2011-01-01 00:00:00"), + "Micro": Timestamp("2011-01-01 00:00:00"), + } + norm_expected.update(normalized) + + sdt = datetime(2011, 1, 1, 9, 0) + ndt = np.datetime64("2011-01-01 09:00") + + for dt in [sdt, ndt]: + expected = expecteds[offset_types.__name__] + self._check_offsetfunc_works(offset_types, "rollforward", dt, expected) + expected = norm_expected[offset_types.__name__] + self._check_offsetfunc_works( + offset_types, "rollforward", dt, expected, normalize=True + ) + + def test_rollback(self, offset_types): + expecteds = { + "BusinessDay": Timestamp("2010-12-31 09:00:00"), + "CustomBusinessDay": Timestamp("2010-12-31 09:00:00"), + "CustomBusinessMonthEnd": Timestamp("2010-12-31 09:00:00"), + "CustomBusinessMonthBegin": Timestamp("2010-12-01 09:00:00"), + "BusinessMonthBegin": Timestamp("2010-12-01 09:00:00"), + "MonthEnd": Timestamp("2010-12-31 09:00:00"), + "SemiMonthEnd": Timestamp("2010-12-31 09:00:00"), + "BusinessMonthEnd": Timestamp("2010-12-31 09:00:00"), + "BYearBegin": Timestamp("2010-01-01 09:00:00"), + "YearEnd": Timestamp("2010-12-31 09:00:00"), + "BYearEnd": Timestamp("2010-12-31 09:00:00"), + "QuarterBegin": Timestamp("2010-12-01 09:00:00"), + "BQuarterBegin": Timestamp("2010-12-01 09:00:00"), + "QuarterEnd": Timestamp("2010-12-31 09:00:00"), + "BQuarterEnd": Timestamp("2010-12-31 09:00:00"), + "BusinessHour": Timestamp("2010-12-31 17:00:00"), + "CustomBusinessHour": Timestamp("2010-12-31 17:00:00"), + "WeekOfMonth": Timestamp("2010-12-11 09:00:00"), + "LastWeekOfMonth": Timestamp("2010-12-25 09:00:00"), + "FY5253Quarter": Timestamp("2010-10-26 09:00:00"), + "FY5253": Timestamp("2010-01-26 09:00:00"), + "Easter": Timestamp("2010-04-04 09:00:00"), + } + + # result will not be changed if the target is on the offset + for n in [ + "Day", + "MonthBegin", + "SemiMonthBegin", + "YearBegin", + "Week", + "Hour", + "Minute", + "Second", + "Milli", + "Micro", + "Nano", + "DateOffset", + ]: + expecteds[n] = Timestamp("2011/01/01 09:00") + + # but be changed when normalize=True + norm_expected = expecteds.copy() + for k in norm_expected: + norm_expected[k] = Timestamp(norm_expected[k].date()) + + normalized = { + "Day": Timestamp("2010-12-31 00:00:00"), + "DateOffset": Timestamp("2010-12-31 00:00:00"), + "MonthBegin": Timestamp("2010-12-01 00:00:00"), + "SemiMonthBegin": Timestamp("2010-12-15 00:00:00"), + "YearBegin": Timestamp("2010-01-01 00:00:00"), + "Week": Timestamp("2010-12-25 00:00:00"), + "Hour": Timestamp("2011-01-01 00:00:00"), + "Minute": Timestamp("2011-01-01 00:00:00"), + "Second": Timestamp("2011-01-01 00:00:00"), + "Milli": Timestamp("2011-01-01 00:00:00"), + "Micro": Timestamp("2011-01-01 00:00:00"), + } + norm_expected.update(normalized) + + sdt = datetime(2011, 1, 1, 9, 0) + ndt = np.datetime64("2011-01-01 09:00") + + for dt in [sdt, ndt]: + expected = expecteds[offset_types.__name__] + self._check_offsetfunc_works(offset_types, "rollback", dt, expected) + + expected = norm_expected[offset_types.__name__] + self._check_offsetfunc_works( + offset_types, "rollback", dt, expected, normalize=True + ) + + def test_is_on_offset(self, offset_types, expecteds): + dt = expecteds[offset_types.__name__] + offset_s = _create_offset(offset_types) + assert offset_s.is_on_offset(dt) + + # when normalize=True, is_on_offset checks time is 00:00:00 + if issubclass(offset_types, Tick): + # normalize=True disallowed for Tick subclasses GH#21427 + return + offset_n = _create_offset(offset_types, normalize=True) + assert not offset_n.is_on_offset(dt) + + if offset_types in (BusinessHour, CustomBusinessHour): + # In default BusinessHour (9:00-17:00), normalized time + # cannot be in business hour range + return + date = datetime(dt.year, dt.month, dt.day) + assert offset_n.is_on_offset(date) + + def test_add(self, offset_types, tz_naive_fixture, expecteds): + tz = tz_naive_fixture + dt = datetime(2011, 1, 1, 9, 0) + + offset_s = _create_offset(offset_types) + expected = expecteds[offset_types.__name__] + + result_dt = dt + offset_s + result_ts = Timestamp(dt) + offset_s + for result in [result_dt, result_ts]: + assert isinstance(result, Timestamp) + assert result == expected + + expected_localize = expected.tz_localize(tz) + result = Timestamp(dt, tz=tz) + offset_s + assert isinstance(result, Timestamp) + assert result == expected_localize + + # normalize=True, disallowed for Tick subclasses GH#21427 + if issubclass(offset_types, Tick): + return + offset_s = _create_offset(offset_types, normalize=True) + expected = Timestamp(expected.date()) + + result_dt = dt + offset_s + result_ts = Timestamp(dt) + offset_s + for result in [result_dt, result_ts]: + assert isinstance(result, Timestamp) + assert result == expected + + expected_localize = expected.tz_localize(tz) + result = Timestamp(dt, tz=tz) + offset_s + assert isinstance(result, Timestamp) + assert result == expected_localize + + def test_add_empty_datetimeindex(self, offset_types, tz_naive_fixture): + # GH#12724, GH#30336 + offset_s = _create_offset(offset_types) + + dti = DatetimeIndex([], tz=tz_naive_fixture).as_unit("ns") + + warn = None + if isinstance( + offset_s, + ( + Easter, + WeekOfMonth, + LastWeekOfMonth, + CustomBusinessDay, + BusinessHour, + CustomBusinessHour, + CustomBusinessMonthBegin, + CustomBusinessMonthEnd, + FY5253, + FY5253Quarter, + ), + ): + # We don't have an optimized apply_index + warn = PerformanceWarning + + # stacklevel checking is slow, and we have ~800 of variants of this + # test, so let's only check the stacklevel in a subset of them + check_stacklevel = tz_naive_fixture is None + with tm.assert_produces_warning(warn, check_stacklevel=check_stacklevel): + result = dti + offset_s + tm.assert_index_equal(result, dti) + with tm.assert_produces_warning(warn, check_stacklevel=check_stacklevel): + result = offset_s + dti + tm.assert_index_equal(result, dti) + + dta = dti._data + with tm.assert_produces_warning(warn, check_stacklevel=check_stacklevel): + result = dta + offset_s + tm.assert_equal(result, dta) + with tm.assert_produces_warning(warn, check_stacklevel=check_stacklevel): + result = offset_s + dta + tm.assert_equal(result, dta) + + def test_pickle_roundtrip(self, offset_types): + off = _create_offset(offset_types) + res = tm.round_trip_pickle(off) + assert off == res + if type(off) is not DateOffset: + for attr in off._attributes: + if attr == "calendar": + # np.busdaycalendar __eq__ will return False; + # we check holidays and weekmask attrs so are OK + continue + # Make sure nothings got lost from _params (which __eq__) is based on + assert getattr(off, attr) == getattr(res, attr) + + def test_pickle_dateoffset_odd_inputs(self): + # GH#34511 + off = DateOffset(months=12) + res = tm.round_trip_pickle(off) + assert off == res + + base_dt = datetime(2020, 1, 1) + assert base_dt + off == base_dt + res + + def test_offsets_hashable(self, offset_types): + # GH: 37267 + off = _create_offset(offset_types) + assert hash(off) is not None + + # TODO: belongs in arithmetic tests? + @pytest.mark.filterwarnings( + "ignore:Non-vectorized DateOffset being applied to Series or DatetimeIndex" + ) + @pytest.mark.parametrize("unit", ["s", "ms", "us"]) + def test_add_dt64_ndarray_non_nano(self, offset_types, unit): + # check that the result with non-nano matches nano + off = _create_offset(offset_types) + + dti = date_range("2016-01-01", periods=35, freq="D", unit=unit) + + result = (dti + off)._with_freq(None) + + exp_unit = unit + if isinstance(off, Tick) and off._creso > dti._data._creso: + # cast to higher reso like we would with Timedelta scalar + exp_unit = Timedelta(off).unit + # TODO(GH#55564): as_unit will be unnecessary + expected = DatetimeIndex([x + off for x in dti]).as_unit(exp_unit) + + tm.assert_index_equal(result, expected) + + +class TestDateOffset: + def setup_method(self): + _offset_map.clear() + + def test_repr(self): + repr(DateOffset()) + repr(DateOffset(2)) + repr(2 * DateOffset()) + repr(2 * DateOffset(months=2)) + + def test_mul(self): + assert DateOffset(2) == 2 * DateOffset(1) + assert DateOffset(2) == DateOffset(1) * 2 + + @pytest.mark.parametrize("kwd", sorted(liboffsets._relativedelta_kwds)) + def test_constructor(self, kwd, request): + if kwd == "millisecond": + request.applymarker( + pytest.mark.xfail( + raises=NotImplementedError, + reason="Constructing DateOffset object with `millisecond` is not " + "yet supported.", + ) + ) + offset = DateOffset(**{kwd: 2}) + assert offset.kwds == {kwd: 2} + assert getattr(offset, kwd) == 2 + + def test_default_constructor(self, dt): + assert (dt + DateOffset(2)) == datetime(2008, 1, 4) + + def test_is_anchored(self): + msg = "DateOffset.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert not DateOffset(2).is_anchored() + assert DateOffset(1).is_anchored() + + def test_copy(self): + assert DateOffset(months=2).copy() == DateOffset(months=2) + assert DateOffset(milliseconds=1).copy() == DateOffset(milliseconds=1) + + @pytest.mark.parametrize( + "arithmatic_offset_type, expected", + zip( + _ARITHMETIC_DATE_OFFSET, + [ + "2009-01-02", + "2008-02-02", + "2008-01-09", + "2008-01-03", + "2008-01-02 01:00:00", + "2008-01-02 00:01:00", + "2008-01-02 00:00:01", + "2008-01-02 00:00:00.001000000", + "2008-01-02 00:00:00.000001000", + ], + ), + ) + def test_add(self, arithmatic_offset_type, expected, dt): + assert DateOffset(**{arithmatic_offset_type: 1}) + dt == Timestamp(expected) + assert dt + DateOffset(**{arithmatic_offset_type: 1}) == Timestamp(expected) + + @pytest.mark.parametrize( + "arithmatic_offset_type, expected", + zip( + _ARITHMETIC_DATE_OFFSET, + [ + "2007-01-02", + "2007-12-02", + "2007-12-26", + "2008-01-01", + "2008-01-01 23:00:00", + "2008-01-01 23:59:00", + "2008-01-01 23:59:59", + "2008-01-01 23:59:59.999000000", + "2008-01-01 23:59:59.999999000", + ], + ), + ) + def test_sub(self, arithmatic_offset_type, expected, dt): + assert dt - DateOffset(**{arithmatic_offset_type: 1}) == Timestamp(expected) + with pytest.raises(TypeError, match="Cannot subtract datetime from offset"): + DateOffset(**{arithmatic_offset_type: 1}) - dt + + @pytest.mark.parametrize( + "arithmatic_offset_type, n, expected", + zip( + _ARITHMETIC_DATE_OFFSET, + range(1, 10), + [ + "2009-01-02", + "2008-03-02", + "2008-01-23", + "2008-01-06", + "2008-01-02 05:00:00", + "2008-01-02 00:06:00", + "2008-01-02 00:00:07", + "2008-01-02 00:00:00.008000000", + "2008-01-02 00:00:00.000009000", + ], + ), + ) + def test_mul_add(self, arithmatic_offset_type, n, expected, dt): + assert DateOffset(**{arithmatic_offset_type: 1}) * n + dt == Timestamp(expected) + assert n * DateOffset(**{arithmatic_offset_type: 1}) + dt == Timestamp(expected) + assert dt + DateOffset(**{arithmatic_offset_type: 1}) * n == Timestamp(expected) + assert dt + n * DateOffset(**{arithmatic_offset_type: 1}) == Timestamp(expected) + + @pytest.mark.parametrize( + "arithmatic_offset_type, n, expected", + zip( + _ARITHMETIC_DATE_OFFSET, + range(1, 10), + [ + "2007-01-02", + "2007-11-02", + "2007-12-12", + "2007-12-29", + "2008-01-01 19:00:00", + "2008-01-01 23:54:00", + "2008-01-01 23:59:53", + "2008-01-01 23:59:59.992000000", + "2008-01-01 23:59:59.999991000", + ], + ), + ) + def test_mul_sub(self, arithmatic_offset_type, n, expected, dt): + assert dt - DateOffset(**{arithmatic_offset_type: 1}) * n == Timestamp(expected) + assert dt - n * DateOffset(**{arithmatic_offset_type: 1}) == Timestamp(expected) + + def test_leap_year(self): + d = datetime(2008, 1, 31) + assert (d + DateOffset(months=1)) == datetime(2008, 2, 29) + + def test_eq(self): + offset1 = DateOffset(days=1) + offset2 = DateOffset(days=365) + + assert offset1 != offset2 + + assert DateOffset(milliseconds=3) != DateOffset(milliseconds=7) + + @pytest.mark.parametrize( + "offset_kwargs, expected_arg", + [ + ({"microseconds": 1, "milliseconds": 1}, "2022-01-01 00:00:00.001001"), + ({"seconds": 1, "milliseconds": 1}, "2022-01-01 00:00:01.001"), + ({"minutes": 1, "milliseconds": 1}, "2022-01-01 00:01:00.001"), + ({"hours": 1, "milliseconds": 1}, "2022-01-01 01:00:00.001"), + ({"days": 1, "milliseconds": 1}, "2022-01-02 00:00:00.001"), + ({"weeks": 1, "milliseconds": 1}, "2022-01-08 00:00:00.001"), + ({"months": 1, "milliseconds": 1}, "2022-02-01 00:00:00.001"), + ({"years": 1, "milliseconds": 1}, "2023-01-01 00:00:00.001"), + ], + ) + def test_milliseconds_combination(self, offset_kwargs, expected_arg): + # GH 49897 + offset = DateOffset(**offset_kwargs) + ts = Timestamp("2022-01-01") + result = ts + offset + expected = Timestamp(expected_arg) + + assert result == expected + + def test_offset_invalid_arguments(self): + msg = "^Invalid argument/s or bad combination of arguments" + with pytest.raises(ValueError, match=msg): + DateOffset(picoseconds=1) + + +class TestOffsetNames: + def test_get_offset_name(self): + assert BDay().freqstr == "B" + assert BDay(2).freqstr == "2B" + assert BMonthEnd().freqstr == "BME" + assert Week(weekday=0).freqstr == "W-MON" + assert Week(weekday=1).freqstr == "W-TUE" + assert Week(weekday=2).freqstr == "W-WED" + assert Week(weekday=3).freqstr == "W-THU" + assert Week(weekday=4).freqstr == "W-FRI" + + assert LastWeekOfMonth(weekday=WeekDay.SUN).freqstr == "LWOM-SUN" + + +def test_get_offset(): + with pytest.raises(ValueError, match=INVALID_FREQ_ERR_MSG): + _get_offset("gibberish") + with pytest.raises(ValueError, match=INVALID_FREQ_ERR_MSG): + _get_offset("QS-JAN-B") + + pairs = [ + ("B", BDay()), + ("b", BDay()), + ("bme", BMonthEnd()), + ("Bme", BMonthEnd()), + ("W-MON", Week(weekday=0)), + ("W-TUE", Week(weekday=1)), + ("W-WED", Week(weekday=2)), + ("W-THU", Week(weekday=3)), + ("W-FRI", Week(weekday=4)), + ] + + for name, expected in pairs: + offset = _get_offset(name) + assert offset == expected, ( + f"Expected {repr(name)} to yield {repr(expected)} " + f"(actual: {repr(offset)})" + ) + + +def test_get_offset_legacy(): + pairs = [("w@Sat", Week(weekday=5))] + for name, expected in pairs: + with pytest.raises(ValueError, match=INVALID_FREQ_ERR_MSG): + _get_offset(name) + + +class TestOffsetAliases: + def setup_method(self): + _offset_map.clear() + + def test_alias_equality(self): + for k, v in _offset_map.items(): + if v is None: + continue + assert k == v.copy() + + def test_rule_code(self): + lst = ["ME", "MS", "BME", "BMS", "D", "B", "h", "min", "s", "ms", "us"] + for k in lst: + assert k == _get_offset(k).rule_code + # should be cached - this is kind of an internals test... + assert k in _offset_map + assert k == (_get_offset(k) * 3).rule_code + + suffix_lst = ["MON", "TUE", "WED", "THU", "FRI", "SAT", "SUN"] + base = "W" + for v in suffix_lst: + alias = "-".join([base, v]) + assert alias == _get_offset(alias).rule_code + assert alias == (_get_offset(alias) * 5).rule_code + + suffix_lst = [ + "JAN", + "FEB", + "MAR", + "APR", + "MAY", + "JUN", + "JUL", + "AUG", + "SEP", + "OCT", + "NOV", + "DEC", + ] + base_lst = ["YE", "YS", "BYE", "BYS", "QE", "QS", "BQE", "BQS"] + for base in base_lst: + for v in suffix_lst: + alias = "-".join([base, v]) + assert alias == _get_offset(alias).rule_code + assert alias == (_get_offset(alias) * 5).rule_code + + +def test_freq_offsets(): + off = BDay(1, offset=timedelta(0, 1800)) + assert off.freqstr == "B+30Min" + + off = BDay(1, offset=timedelta(0, -1800)) + assert off.freqstr == "B-30Min" + + +class TestReprNames: + def test_str_for_named_is_name(self): + # look at all the amazing combinations! + month_prefixes = ["YE", "YS", "BYE", "BYS", "QE", "BQE", "BQS", "QS"] + names = [ + prefix + "-" + month + for prefix in month_prefixes + for month in [ + "JAN", + "FEB", + "MAR", + "APR", + "MAY", + "JUN", + "JUL", + "AUG", + "SEP", + "OCT", + "NOV", + "DEC", + ] + ] + days = ["MON", "TUE", "WED", "THU", "FRI", "SAT", "SUN"] + names += ["W-" + day for day in days] + names += ["WOM-" + week + day for week in ("1", "2", "3", "4") for day in days] + _offset_map.clear() + for name in names: + offset = _get_offset(name) + assert offset.freqstr == name + + +# --------------------------------------------------------------------- + + +def test_valid_default_arguments(offset_types): + # GH#19142 check that the calling the constructors without passing + # any keyword arguments produce valid offsets + cls = offset_types + cls() + + +@pytest.mark.parametrize("kwd", sorted(liboffsets._relativedelta_kwds)) +def test_valid_month_attributes(kwd, month_classes): + # GH#18226 + cls = month_classes + # check that we cannot create e.g. MonthEnd(weeks=3) + msg = rf"__init__\(\) got an unexpected keyword argument '{kwd}'" + with pytest.raises(TypeError, match=msg): + cls(**{kwd: 3}) + + +def test_month_offset_name(month_classes): + # GH#33757 off.name with n != 1 should not raise AttributeError + obj = month_classes(1) + obj2 = month_classes(2) + assert obj2.name == obj.name + + +@pytest.mark.parametrize("kwd", sorted(liboffsets._relativedelta_kwds)) +def test_valid_relativedelta_kwargs(kwd, request): + if kwd == "millisecond": + request.applymarker( + pytest.mark.xfail( + raises=NotImplementedError, + reason="Constructing DateOffset object with `millisecond` is not " + "yet supported.", + ) + ) + # Check that all the arguments specified in liboffsets._relativedelta_kwds + # are in fact valid relativedelta keyword args + DateOffset(**{kwd: 1}) + + +@pytest.mark.parametrize("kwd", sorted(liboffsets._relativedelta_kwds)) +def test_valid_tick_attributes(kwd, tick_classes): + # GH#18226 + cls = tick_classes + # check that we cannot create e.g. Hour(weeks=3) + msg = rf"__init__\(\) got an unexpected keyword argument '{kwd}'" + with pytest.raises(TypeError, match=msg): + cls(**{kwd: 3}) + + +def test_validate_n_error(): + with pytest.raises(TypeError, match="argument must be an integer"): + DateOffset(n="Doh!") + + with pytest.raises(TypeError, match="argument must be an integer"): + MonthBegin(n=timedelta(1)) + + with pytest.raises(TypeError, match="argument must be an integer"): + BDay(n=np.array([1, 2], dtype=np.int64)) + + +def test_require_integers(offset_types): + cls = offset_types + with pytest.raises(ValueError, match="argument must be an integer"): + cls(n=1.5) + + +def test_tick_normalize_raises(tick_classes): + # check that trying to create a Tick object with normalize=True raises + # GH#21427 + cls = tick_classes + msg = "Tick offset with `normalize=True` are not allowed." + with pytest.raises(ValueError, match=msg): + cls(n=3, normalize=True) + + +@pytest.mark.parametrize( + "offset_kwargs, expected_arg", + [ + ({"nanoseconds": 1}, "1970-01-01 00:00:00.000000001"), + ({"nanoseconds": 5}, "1970-01-01 00:00:00.000000005"), + ({"nanoseconds": -1}, "1969-12-31 23:59:59.999999999"), + ({"microseconds": 1}, "1970-01-01 00:00:00.000001"), + ({"microseconds": -1}, "1969-12-31 23:59:59.999999"), + ({"seconds": 1}, "1970-01-01 00:00:01"), + ({"seconds": -1}, "1969-12-31 23:59:59"), + ({"minutes": 1}, "1970-01-01 00:01:00"), + ({"minutes": -1}, "1969-12-31 23:59:00"), + ({"hours": 1}, "1970-01-01 01:00:00"), + ({"hours": -1}, "1969-12-31 23:00:00"), + ({"days": 1}, "1970-01-02 00:00:00"), + ({"days": -1}, "1969-12-31 00:00:00"), + ({"weeks": 1}, "1970-01-08 00:00:00"), + ({"weeks": -1}, "1969-12-25 00:00:00"), + ({"months": 1}, "1970-02-01 00:00:00"), + ({"months": -1}, "1969-12-01 00:00:00"), + ({"years": 1}, "1971-01-01 00:00:00"), + ({"years": -1}, "1969-01-01 00:00:00"), + ], +) +def test_dateoffset_add_sub(offset_kwargs, expected_arg): + offset = DateOffset(**offset_kwargs) + ts = Timestamp(0) + result = ts + offset + expected = Timestamp(expected_arg) + assert result == expected + result -= offset + assert result == ts + result = offset + ts + assert result == expected + + +def test_dateoffset_add_sub_timestamp_with_nano(): + offset = DateOffset(minutes=2, nanoseconds=9) + ts = Timestamp(4) + result = ts + offset + expected = Timestamp("1970-01-01 00:02:00.000000013") + assert result == expected + result -= offset + assert result == ts + result = offset + ts + assert result == expected + + offset2 = DateOffset(minutes=2, nanoseconds=9, hour=1) + assert offset2._use_relativedelta + with tm.assert_produces_warning(None): + # no warning about Discarding nonzero nanoseconds + result2 = ts + offset2 + expected2 = Timestamp("1970-01-01 01:02:00.000000013") + assert result2 == expected2 + + +@pytest.mark.parametrize( + "attribute", + [ + "hours", + "days", + "weeks", + "months", + "years", + ], +) +def test_dateoffset_immutable(attribute): + offset = DateOffset(**{attribute: 0}) + msg = "DateOffset objects are immutable" + with pytest.raises(AttributeError, match=msg): + setattr(offset, attribute, 5) + + +def test_dateoffset_misc(): + oset = offsets.DateOffset(months=2, days=4) + # it works + oset.freqstr + + assert not offsets.DateOffset(months=2) == 2 + + +@pytest.mark.parametrize("n", [-1, 1, 3]) +def test_construct_int_arg_no_kwargs_assumed_days(n): + # GH 45890, 45643 + offset = DateOffset(n) + assert offset._offset == timedelta(1) + result = Timestamp(2022, 1, 2) + offset + expected = Timestamp(2022, 1, 2 + n) + assert result == expected + + +@pytest.mark.parametrize( + "offset, expected", + [ + ( + DateOffset(minutes=7, nanoseconds=18), + Timestamp("2022-01-01 00:07:00.000000018"), + ), + (DateOffset(nanoseconds=3), Timestamp("2022-01-01 00:00:00.000000003")), + ], +) +def test_dateoffset_add_sub_timestamp_series_with_nano(offset, expected): + # GH 47856 + start_time = Timestamp("2022-01-01") + teststamp = start_time + testseries = Series([start_time]) + testseries = testseries + offset + assert testseries[0] == expected + testseries -= offset + assert testseries[0] == teststamp + testseries = offset + testseries + assert testseries[0] == expected + + +@pytest.mark.parametrize( + "n_months, scaling_factor, start_timestamp, expected_timestamp", + [ + (1, 2, "2020-01-30", "2020-03-30"), + (2, 1, "2020-01-30", "2020-03-30"), + (1, 0, "2020-01-30", "2020-01-30"), + (2, 0, "2020-01-30", "2020-01-30"), + (1, -1, "2020-01-30", "2019-12-30"), + (2, -1, "2020-01-30", "2019-11-30"), + ], +) +def test_offset_multiplication( + n_months, scaling_factor, start_timestamp, expected_timestamp +): + # GH 47953 + mo1 = DateOffset(months=n_months) + + startscalar = Timestamp(start_timestamp) + startarray = Series([startscalar]) + + resultscalar = startscalar + (mo1 * scaling_factor) + resultarray = startarray + (mo1 * scaling_factor) + + expectedscalar = Timestamp(expected_timestamp) + expectedarray = Series([expectedscalar]) + assert resultscalar == expectedscalar + + tm.assert_series_equal(resultarray, expectedarray) + + +def test_dateoffset_operations_on_dataframes(): + # GH 47953 + df = DataFrame({"T": [Timestamp("2019-04-30")], "D": [DateOffset(months=1)]}) + frameresult1 = df["T"] + 26 * df["D"] + df2 = DataFrame( + { + "T": [Timestamp("2019-04-30"), Timestamp("2019-04-30")], + "D": [DateOffset(months=1), DateOffset(months=1)], + } + ) + expecteddate = Timestamp("2021-06-30") + with tm.assert_produces_warning(PerformanceWarning): + frameresult2 = df2["T"] + 26 * df2["D"] + + assert frameresult1[0] == expecteddate + assert frameresult2[0] == expecteddate + + +def test_is_yqm_start_end(): + freq_m = to_offset("ME") + bm = to_offset("BME") + qfeb = to_offset("QE-FEB") + qsfeb = to_offset("QS-FEB") + bq = to_offset("BQE") + bqs_apr = to_offset("BQS-APR") + as_nov = to_offset("YS-NOV") + + tests = [ + (freq_m.is_month_start(Timestamp("2013-06-01")), 1), + (bm.is_month_start(Timestamp("2013-06-01")), 0), + (freq_m.is_month_start(Timestamp("2013-06-03")), 0), + (bm.is_month_start(Timestamp("2013-06-03")), 1), + (qfeb.is_month_end(Timestamp("2013-02-28")), 1), + (qfeb.is_quarter_end(Timestamp("2013-02-28")), 1), + (qfeb.is_year_end(Timestamp("2013-02-28")), 1), + (qfeb.is_month_start(Timestamp("2013-03-01")), 1), + (qfeb.is_quarter_start(Timestamp("2013-03-01")), 1), + (qfeb.is_year_start(Timestamp("2013-03-01")), 1), + (qsfeb.is_month_end(Timestamp("2013-03-31")), 1), + (qsfeb.is_quarter_end(Timestamp("2013-03-31")), 0), + (qsfeb.is_year_end(Timestamp("2013-03-31")), 0), + (qsfeb.is_month_start(Timestamp("2013-02-01")), 1), + (qsfeb.is_quarter_start(Timestamp("2013-02-01")), 1), + (qsfeb.is_year_start(Timestamp("2013-02-01")), 1), + (bq.is_month_end(Timestamp("2013-06-30")), 0), + (bq.is_quarter_end(Timestamp("2013-06-30")), 0), + (bq.is_year_end(Timestamp("2013-06-30")), 0), + (bq.is_month_end(Timestamp("2013-06-28")), 1), + (bq.is_quarter_end(Timestamp("2013-06-28")), 1), + (bq.is_year_end(Timestamp("2013-06-28")), 0), + (bqs_apr.is_month_end(Timestamp("2013-06-30")), 0), + (bqs_apr.is_quarter_end(Timestamp("2013-06-30")), 0), + (bqs_apr.is_year_end(Timestamp("2013-06-30")), 0), + (bqs_apr.is_month_end(Timestamp("2013-06-28")), 1), + (bqs_apr.is_quarter_end(Timestamp("2013-06-28")), 1), + (bqs_apr.is_year_end(Timestamp("2013-03-29")), 1), + (as_nov.is_year_start(Timestamp("2013-11-01")), 1), + (as_nov.is_year_end(Timestamp("2013-10-31")), 1), + (Timestamp("2012-02-01").days_in_month, 29), + (Timestamp("2013-02-01").days_in_month, 28), + ] + + for ts, value in tests: + assert ts == value diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_offsets_properties.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_offsets_properties.py new file mode 100644 index 0000000000000000000000000000000000000000..1b4fa9292c4031c8c2acec0e1f34fd871bcb50bd --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_offsets_properties.py @@ -0,0 +1,60 @@ +""" +Behavioral based tests for offsets and date_range. + +This file is adapted from https://github.com/pandas-dev/pandas/pull/18761 - +which was more ambitious but less idiomatic in its use of Hypothesis. + +You may wish to consult the previous version for inspiration on further +tests, or when trying to pin down the bugs exposed by the tests below. +""" +from hypothesis import ( + assume, + given, +) +import pytest +import pytz + +import pandas as pd +from pandas._testing._hypothesis import ( + DATETIME_JAN_1_1900_OPTIONAL_TZ, + YQM_OFFSET, +) + +# ---------------------------------------------------------------- +# Offset-specific behaviour tests + + +@pytest.mark.arm_slow +@given(DATETIME_JAN_1_1900_OPTIONAL_TZ, YQM_OFFSET) +def test_on_offset_implementations(dt, offset): + assume(not offset.normalize) + # check that the class-specific implementations of is_on_offset match + # the general case definition: + # (dt + offset) - offset == dt + try: + compare = (dt + offset) - offset + except (pytz.NonExistentTimeError, pytz.AmbiguousTimeError): + # When dt + offset does not exist or is DST-ambiguous, assume(False) to + # indicate to hypothesis that this is not a valid test case + # DST-ambiguous example (GH41906): + # dt = datetime.datetime(1900, 1, 1, tzinfo=pytz.timezone('Africa/Kinshasa')) + # offset = MonthBegin(66) + assume(False) + + assert offset.is_on_offset(dt) == (compare == dt) + + +@given(YQM_OFFSET) +def test_shift_across_dst(offset): + # GH#18319 check that 1) timezone is correctly normalized and + # 2) that hour is not incorrectly changed by this normalization + assume(not offset.normalize) + + # Note that dti includes a transition across DST boundary + dti = pd.date_range( + start="2017-10-30 12:00:00", end="2017-11-06", freq="D", tz="US/Eastern" + ) + assert (dti.hour == 12).all() # we haven't screwed up yet + + res = dti + offset + assert (res.hour == 12).all() diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_quarter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_quarter.py new file mode 100644 index 0000000000000000000000000000000000000000..5fd3ba0a5fb87996a4e07fd25569e7161cb08930 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_quarter.py @@ -0,0 +1,303 @@ +""" +Tests for the following offsets: +- QuarterBegin +- QuarterEnd +""" +from __future__ import annotations + +from datetime import datetime + +import pytest + +import pandas._testing as tm +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries.offsets import ( + QuarterBegin, + QuarterEnd, +) + + +@pytest.mark.parametrize("klass", (QuarterBegin, QuarterEnd)) +def test_quarterly_dont_normalize(klass): + date = datetime(2012, 3, 31, 5, 30) + result = date + klass() + assert result.time() == date.time() + + +@pytest.mark.parametrize("offset", [QuarterBegin(), QuarterEnd()]) +@pytest.mark.parametrize( + "date", + [ + datetime(2016, m, d) + for m in [10, 11, 12] + for d in [1, 2, 3, 28, 29, 30, 31] + if not (m == 11 and d == 31) + ], +) +def test_on_offset(offset, date): + res = offset.is_on_offset(date) + slow_version = date == (date + offset) - offset + assert res == slow_version + + +class TestQuarterBegin: + def test_repr(self): + expected = "" + assert repr(QuarterBegin()) == expected + expected = "" + assert repr(QuarterBegin(startingMonth=3)) == expected + expected = "" + assert repr(QuarterBegin(startingMonth=1)) == expected + + def test_is_anchored(self): + msg = "QuarterBegin.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert QuarterBegin(startingMonth=1).is_anchored() + assert QuarterBegin().is_anchored() + assert not QuarterBegin(2, startingMonth=1).is_anchored() + + def test_offset_corner_case(self): + # corner + offset = QuarterBegin(n=-1, startingMonth=1) + assert datetime(2010, 2, 1) + offset == datetime(2010, 1, 1) + + offset_cases = [] + offset_cases.append( + ( + QuarterBegin(startingMonth=1), + { + datetime(2007, 12, 1): datetime(2008, 1, 1), + datetime(2008, 1, 1): datetime(2008, 4, 1), + datetime(2008, 2, 15): datetime(2008, 4, 1), + datetime(2008, 2, 29): datetime(2008, 4, 1), + datetime(2008, 3, 15): datetime(2008, 4, 1), + datetime(2008, 3, 31): datetime(2008, 4, 1), + datetime(2008, 4, 15): datetime(2008, 7, 1), + datetime(2008, 4, 1): datetime(2008, 7, 1), + }, + ) + ) + + offset_cases.append( + ( + QuarterBegin(startingMonth=2), + { + datetime(2008, 1, 1): datetime(2008, 2, 1), + datetime(2008, 1, 31): datetime(2008, 2, 1), + datetime(2008, 1, 15): datetime(2008, 2, 1), + datetime(2008, 2, 29): datetime(2008, 5, 1), + datetime(2008, 3, 15): datetime(2008, 5, 1), + datetime(2008, 3, 31): datetime(2008, 5, 1), + datetime(2008, 4, 15): datetime(2008, 5, 1), + datetime(2008, 4, 30): datetime(2008, 5, 1), + }, + ) + ) + + offset_cases.append( + ( + QuarterBegin(startingMonth=1, n=0), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 12, 1): datetime(2009, 1, 1), + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 2, 15): datetime(2008, 4, 1), + datetime(2008, 2, 29): datetime(2008, 4, 1), + datetime(2008, 3, 15): datetime(2008, 4, 1), + datetime(2008, 3, 31): datetime(2008, 4, 1), + datetime(2008, 4, 15): datetime(2008, 7, 1), + datetime(2008, 4, 30): datetime(2008, 7, 1), + }, + ) + ) + + offset_cases.append( + ( + QuarterBegin(startingMonth=1, n=-1), + { + datetime(2008, 1, 1): datetime(2007, 10, 1), + datetime(2008, 1, 31): datetime(2008, 1, 1), + datetime(2008, 2, 15): datetime(2008, 1, 1), + datetime(2008, 2, 29): datetime(2008, 1, 1), + datetime(2008, 3, 15): datetime(2008, 1, 1), + datetime(2008, 3, 31): datetime(2008, 1, 1), + datetime(2008, 4, 15): datetime(2008, 4, 1), + datetime(2008, 4, 30): datetime(2008, 4, 1), + datetime(2008, 7, 1): datetime(2008, 4, 1), + }, + ) + ) + + offset_cases.append( + ( + QuarterBegin(startingMonth=1, n=2), + { + datetime(2008, 1, 1): datetime(2008, 7, 1), + datetime(2008, 2, 15): datetime(2008, 7, 1), + datetime(2008, 2, 29): datetime(2008, 7, 1), + datetime(2008, 3, 15): datetime(2008, 7, 1), + datetime(2008, 3, 31): datetime(2008, 7, 1), + datetime(2008, 4, 15): datetime(2008, 10, 1), + datetime(2008, 4, 1): datetime(2008, 10, 1), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + +class TestQuarterEnd: + def test_repr(self): + expected = "" + assert repr(QuarterEnd()) == expected + expected = "" + assert repr(QuarterEnd(startingMonth=3)) == expected + expected = "" + assert repr(QuarterEnd(startingMonth=1)) == expected + + def test_is_anchored(self): + msg = "QuarterEnd.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert QuarterEnd(startingMonth=1).is_anchored() + assert QuarterEnd().is_anchored() + assert not QuarterEnd(2, startingMonth=1).is_anchored() + + def test_offset_corner_case(self): + # corner + offset = QuarterEnd(n=-1, startingMonth=1) + assert datetime(2010, 2, 1) + offset == datetime(2010, 1, 31) + + offset_cases = [] + offset_cases.append( + ( + QuarterEnd(startingMonth=1), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 4, 30), + datetime(2008, 2, 15): datetime(2008, 4, 30), + datetime(2008, 2, 29): datetime(2008, 4, 30), + datetime(2008, 3, 15): datetime(2008, 4, 30), + datetime(2008, 3, 31): datetime(2008, 4, 30), + datetime(2008, 4, 15): datetime(2008, 4, 30), + datetime(2008, 4, 30): datetime(2008, 7, 31), + }, + ) + ) + + offset_cases.append( + ( + QuarterEnd(startingMonth=2), + { + datetime(2008, 1, 1): datetime(2008, 2, 29), + datetime(2008, 1, 31): datetime(2008, 2, 29), + datetime(2008, 2, 15): datetime(2008, 2, 29), + datetime(2008, 2, 29): datetime(2008, 5, 31), + datetime(2008, 3, 15): datetime(2008, 5, 31), + datetime(2008, 3, 31): datetime(2008, 5, 31), + datetime(2008, 4, 15): datetime(2008, 5, 31), + datetime(2008, 4, 30): datetime(2008, 5, 31), + }, + ) + ) + + offset_cases.append( + ( + QuarterEnd(startingMonth=1, n=0), + { + datetime(2008, 1, 1): datetime(2008, 1, 31), + datetime(2008, 1, 31): datetime(2008, 1, 31), + datetime(2008, 2, 15): datetime(2008, 4, 30), + datetime(2008, 2, 29): datetime(2008, 4, 30), + datetime(2008, 3, 15): datetime(2008, 4, 30), + datetime(2008, 3, 31): datetime(2008, 4, 30), + datetime(2008, 4, 15): datetime(2008, 4, 30), + datetime(2008, 4, 30): datetime(2008, 4, 30), + }, + ) + ) + + offset_cases.append( + ( + QuarterEnd(startingMonth=1, n=-1), + { + datetime(2008, 1, 1): datetime(2007, 10, 31), + datetime(2008, 1, 31): datetime(2007, 10, 31), + datetime(2008, 2, 15): datetime(2008, 1, 31), + datetime(2008, 2, 29): datetime(2008, 1, 31), + datetime(2008, 3, 15): datetime(2008, 1, 31), + datetime(2008, 3, 31): datetime(2008, 1, 31), + datetime(2008, 4, 15): datetime(2008, 1, 31), + datetime(2008, 4, 30): datetime(2008, 1, 31), + datetime(2008, 7, 1): datetime(2008, 4, 30), + }, + ) + ) + + offset_cases.append( + ( + QuarterEnd(startingMonth=1, n=2), + { + datetime(2008, 1, 31): datetime(2008, 7, 31), + datetime(2008, 2, 15): datetime(2008, 7, 31), + datetime(2008, 2, 29): datetime(2008, 7, 31), + datetime(2008, 3, 15): datetime(2008, 7, 31), + datetime(2008, 3, 31): datetime(2008, 7, 31), + datetime(2008, 4, 15): datetime(2008, 7, 31), + datetime(2008, 4, 30): datetime(2008, 10, 31), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (QuarterEnd(1, startingMonth=1), datetime(2008, 1, 31), True), + (QuarterEnd(1, startingMonth=1), datetime(2007, 12, 31), False), + (QuarterEnd(1, startingMonth=1), datetime(2008, 2, 29), False), + (QuarterEnd(1, startingMonth=1), datetime(2007, 3, 30), False), + (QuarterEnd(1, startingMonth=1), datetime(2007, 3, 31), False), + (QuarterEnd(1, startingMonth=1), datetime(2008, 4, 30), True), + (QuarterEnd(1, startingMonth=1), datetime(2008, 5, 30), False), + (QuarterEnd(1, startingMonth=1), datetime(2008, 5, 31), False), + (QuarterEnd(1, startingMonth=1), datetime(2007, 6, 29), False), + (QuarterEnd(1, startingMonth=1), datetime(2007, 6, 30), False), + (QuarterEnd(1, startingMonth=2), datetime(2008, 1, 31), False), + (QuarterEnd(1, startingMonth=2), datetime(2007, 12, 31), False), + (QuarterEnd(1, startingMonth=2), datetime(2008, 2, 29), True), + (QuarterEnd(1, startingMonth=2), datetime(2007, 3, 30), False), + (QuarterEnd(1, startingMonth=2), datetime(2007, 3, 31), False), + (QuarterEnd(1, startingMonth=2), datetime(2008, 4, 30), False), + (QuarterEnd(1, startingMonth=2), datetime(2008, 5, 30), False), + (QuarterEnd(1, startingMonth=2), datetime(2008, 5, 31), True), + (QuarterEnd(1, startingMonth=2), datetime(2007, 6, 29), False), + (QuarterEnd(1, startingMonth=2), datetime(2007, 6, 30), False), + (QuarterEnd(1, startingMonth=3), datetime(2008, 1, 31), False), + (QuarterEnd(1, startingMonth=3), datetime(2007, 12, 31), True), + (QuarterEnd(1, startingMonth=3), datetime(2008, 2, 29), False), + (QuarterEnd(1, startingMonth=3), datetime(2007, 3, 30), False), + (QuarterEnd(1, startingMonth=3), datetime(2007, 3, 31), True), + (QuarterEnd(1, startingMonth=3), datetime(2008, 4, 30), False), + (QuarterEnd(1, startingMonth=3), datetime(2008, 5, 30), False), + (QuarterEnd(1, startingMonth=3), datetime(2008, 5, 31), False), + (QuarterEnd(1, startingMonth=3), datetime(2007, 6, 29), False), + (QuarterEnd(1, startingMonth=3), datetime(2007, 6, 30), True), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_ticks.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_ticks.py new file mode 100644 index 0000000000000000000000000000000000000000..399b7038d3426a9f3e4916927bd7e38ac3996531 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_ticks.py @@ -0,0 +1,405 @@ +""" +Tests for offsets.Tick and subclasses +""" +from datetime import ( + datetime, + timedelta, +) + +from hypothesis import ( + assume, + example, + given, +) +import numpy as np +import pytest + +from pandas._libs.tslibs.offsets import delta_to_tick +from pandas.errors import OutOfBoundsTimedelta + +from pandas import ( + Timedelta, + Timestamp, +) +import pandas._testing as tm +from pandas._testing._hypothesis import INT_NEG_999_TO_POS_999 +from pandas.tests.tseries.offsets.common import assert_offset_equal + +from pandas.tseries import offsets +from pandas.tseries.offsets import ( + Hour, + Micro, + Milli, + Minute, + Nano, + Second, +) + +# --------------------------------------------------------------------- +# Test Helpers + +tick_classes = [Hour, Minute, Second, Milli, Micro, Nano] + + +# --------------------------------------------------------------------- + + +def test_apply_ticks(): + result = offsets.Hour(3) + offsets.Hour(4) + exp = offsets.Hour(7) + assert result == exp + + +def test_delta_to_tick(): + delta = timedelta(3) + + tick = delta_to_tick(delta) + assert tick == offsets.Day(3) + + td = Timedelta(nanoseconds=5) + tick = delta_to_tick(td) + assert tick == Nano(5) + + +@pytest.mark.parametrize("cls", tick_classes) +@example(n=2, m=3) +@example(n=800, m=300) +@example(n=1000, m=5) +@given(n=INT_NEG_999_TO_POS_999, m=INT_NEG_999_TO_POS_999) +def test_tick_add_sub(cls, n, m): + # For all Tick subclasses and all integers n, m, we should have + # tick(n) + tick(m) == tick(n+m) + # tick(n) - tick(m) == tick(n-m) + left = cls(n) + right = cls(m) + expected = cls(n + m) + + assert left + right == expected + + expected = cls(n - m) + assert left - right == expected + + +@pytest.mark.arm_slow +@pytest.mark.parametrize("cls", tick_classes) +@example(n=2, m=3) +@given(n=INT_NEG_999_TO_POS_999, m=INT_NEG_999_TO_POS_999) +def test_tick_equality(cls, n, m): + assume(m != n) + # tick == tock iff tick.n == tock.n + left = cls(n) + right = cls(m) + assert left != right + + right = cls(n) + assert left == right + assert not left != right + + if n != 0: + assert cls(n) != cls(-n) + + +# --------------------------------------------------------------------- + + +def test_Hour(): + assert_offset_equal(Hour(), datetime(2010, 1, 1), datetime(2010, 1, 1, 1)) + assert_offset_equal(Hour(-1), datetime(2010, 1, 1, 1), datetime(2010, 1, 1)) + assert_offset_equal(2 * Hour(), datetime(2010, 1, 1), datetime(2010, 1, 1, 2)) + assert_offset_equal(-1 * Hour(), datetime(2010, 1, 1, 1), datetime(2010, 1, 1)) + + assert Hour(3) + Hour(2) == Hour(5) + assert Hour(3) - Hour(2) == Hour() + + assert Hour(4) != Hour(1) + + +def test_Minute(): + assert_offset_equal(Minute(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 1)) + assert_offset_equal(Minute(-1), datetime(2010, 1, 1, 0, 1), datetime(2010, 1, 1)) + assert_offset_equal(2 * Minute(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 2)) + assert_offset_equal(-1 * Minute(), datetime(2010, 1, 1, 0, 1), datetime(2010, 1, 1)) + + assert Minute(3) + Minute(2) == Minute(5) + assert Minute(3) - Minute(2) == Minute() + assert Minute(5) != Minute() + + +def test_Second(): + assert_offset_equal(Second(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 0, 1)) + assert_offset_equal(Second(-1), datetime(2010, 1, 1, 0, 0, 1), datetime(2010, 1, 1)) + assert_offset_equal( + 2 * Second(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 0, 2) + ) + assert_offset_equal( + -1 * Second(), datetime(2010, 1, 1, 0, 0, 1), datetime(2010, 1, 1) + ) + + assert Second(3) + Second(2) == Second(5) + assert Second(3) - Second(2) == Second() + + +def test_Millisecond(): + assert_offset_equal( + Milli(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 0, 0, 1000) + ) + assert_offset_equal( + Milli(-1), datetime(2010, 1, 1, 0, 0, 0, 1000), datetime(2010, 1, 1) + ) + assert_offset_equal( + Milli(2), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 0, 0, 2000) + ) + assert_offset_equal( + 2 * Milli(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 0, 0, 2000) + ) + assert_offset_equal( + -1 * Milli(), datetime(2010, 1, 1, 0, 0, 0, 1000), datetime(2010, 1, 1) + ) + + assert Milli(3) + Milli(2) == Milli(5) + assert Milli(3) - Milli(2) == Milli() + + +def test_MillisecondTimestampArithmetic(): + assert_offset_equal( + Milli(), Timestamp("2010-01-01"), Timestamp("2010-01-01 00:00:00.001") + ) + assert_offset_equal( + Milli(-1), Timestamp("2010-01-01 00:00:00.001"), Timestamp("2010-01-01") + ) + + +def test_Microsecond(): + assert_offset_equal(Micro(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 0, 0, 1)) + assert_offset_equal( + Micro(-1), datetime(2010, 1, 1, 0, 0, 0, 1), datetime(2010, 1, 1) + ) + + assert_offset_equal( + 2 * Micro(), datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 0, 0, 2) + ) + assert_offset_equal( + -1 * Micro(), datetime(2010, 1, 1, 0, 0, 0, 1), datetime(2010, 1, 1) + ) + + assert Micro(3) + Micro(2) == Micro(5) + assert Micro(3) - Micro(2) == Micro() + + +def test_NanosecondGeneric(): + timestamp = Timestamp(datetime(2010, 1, 1)) + assert timestamp.nanosecond == 0 + + result = timestamp + Nano(10) + assert result.nanosecond == 10 + + reverse_result = Nano(10) + timestamp + assert reverse_result.nanosecond == 10 + + +def test_Nanosecond(): + timestamp = Timestamp(datetime(2010, 1, 1)) + assert_offset_equal(Nano(), timestamp, timestamp + np.timedelta64(1, "ns")) + assert_offset_equal(Nano(-1), timestamp + np.timedelta64(1, "ns"), timestamp) + assert_offset_equal(2 * Nano(), timestamp, timestamp + np.timedelta64(2, "ns")) + assert_offset_equal(-1 * Nano(), timestamp + np.timedelta64(1, "ns"), timestamp) + + assert Nano(3) + Nano(2) == Nano(5) + assert Nano(3) - Nano(2) == Nano() + + # GH9284 + assert Nano(1) + Nano(10) == Nano(11) + assert Nano(5) + Micro(1) == Nano(1005) + assert Micro(5) + Nano(1) == Nano(5001) + + +@pytest.mark.parametrize( + "kls, expected", + [ + (Hour, Timedelta(hours=5)), + (Minute, Timedelta(hours=2, minutes=3)), + (Second, Timedelta(hours=2, seconds=3)), + (Milli, Timedelta(hours=2, milliseconds=3)), + (Micro, Timedelta(hours=2, microseconds=3)), + (Nano, Timedelta(hours=2, nanoseconds=3)), + ], +) +def test_tick_addition(kls, expected): + offset = kls(3) + td = Timedelta(hours=2) + + for other in [td, td.to_pytimedelta(), td.to_timedelta64()]: + result = offset + other + assert isinstance(result, Timedelta) + assert result == expected + + result = other + offset + assert isinstance(result, Timedelta) + assert result == expected + + +def test_tick_delta_overflow(): + # GH#55503 raise OutOfBoundsTimedelta, not OverflowError + tick = offsets.Day(10**9) + msg = "Cannot cast 1000000000 days 00:00:00 to unit='ns' without overflow" + depr_msg = "Day.delta is deprecated" + with pytest.raises(OutOfBoundsTimedelta, match=msg): + with tm.assert_produces_warning(FutureWarning, match=depr_msg): + tick.delta + + +@pytest.mark.parametrize("cls", tick_classes) +def test_tick_division(cls): + off = cls(10) + + assert off / cls(5) == 2 + assert off / 2 == cls(5) + assert off / 2.0 == cls(5) + + assert off / off._as_pd_timedelta == 1 + assert off / off._as_pd_timedelta.to_timedelta64() == 1 + + assert off / Nano(1) == off._as_pd_timedelta / Nano(1)._as_pd_timedelta + + if cls is not Nano: + # A case where we end up with a smaller class + result = off / 1000 + assert isinstance(result, offsets.Tick) + assert not isinstance(result, cls) + assert result._as_pd_timedelta == off._as_pd_timedelta / 1000 + + if cls._nanos_inc < Timedelta(seconds=1)._value: + # Case where we end up with a bigger class + result = off / 0.001 + assert isinstance(result, offsets.Tick) + assert not isinstance(result, cls) + assert result._as_pd_timedelta == off._as_pd_timedelta / 0.001 + + +def test_tick_mul_float(): + off = Micro(2) + + # Case where we retain type + result = off * 1.5 + expected = Micro(3) + assert result == expected + assert isinstance(result, Micro) + + # Case where we bump up to the next type + result = off * 1.25 + expected = Nano(2500) + assert result == expected + assert isinstance(result, Nano) + + +@pytest.mark.parametrize("cls", tick_classes) +def test_tick_rdiv(cls): + off = cls(10) + delta = off._as_pd_timedelta + td64 = delta.to_timedelta64() + instance__type = ".".join([cls.__module__, cls.__name__]) + msg = ( + "unsupported operand type\\(s\\) for \\/: 'int'|'float' and " + f"'{instance__type}'" + ) + + with pytest.raises(TypeError, match=msg): + 2 / off + with pytest.raises(TypeError, match=msg): + 2.0 / off + + assert (td64 * 2.5) / off == 2.5 + + if cls is not Nano: + # skip pytimedelta for Nano since it gets dropped + assert (delta.to_pytimedelta() * 2) / off == 2 + + result = np.array([2 * td64, td64]) / off + expected = np.array([2.0, 1.0]) + tm.assert_numpy_array_equal(result, expected) + + +@pytest.mark.parametrize("cls1", tick_classes) +@pytest.mark.parametrize("cls2", tick_classes) +def test_tick_zero(cls1, cls2): + assert cls1(0) == cls2(0) + assert cls1(0) + cls2(0) == cls1(0) + + if cls1 is not Nano: + assert cls1(2) + cls2(0) == cls1(2) + + if cls1 is Nano: + assert cls1(2) + Nano(0) == cls1(2) + + +@pytest.mark.parametrize("cls", tick_classes) +def test_tick_equalities(cls): + assert cls() == cls(1) + + +@pytest.mark.parametrize("cls", tick_classes) +def test_tick_offset(cls): + msg = f"{cls.__name__}.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert not cls().is_anchored() + + +@pytest.mark.parametrize("cls", tick_classes) +def test_compare_ticks(cls): + three = cls(3) + four = cls(4) + + assert three < cls(4) + assert cls(3) < four + assert four > cls(3) + assert cls(4) > three + assert cls(3) == cls(3) + assert cls(3) != cls(4) + + +@pytest.mark.parametrize("cls", tick_classes) +def test_compare_ticks_to_strs(cls): + # GH#23524 + off = cls(19) + + # These tests should work with any strings, but we particularly are + # interested in "infer" as that comparison is convenient to make in + # Datetime/Timedelta Array/Index constructors + assert not off == "infer" + assert not "foo" == off + + instance_type = ".".join([cls.__module__, cls.__name__]) + msg = ( + "'<'|'<='|'>'|'>=' not supported between instances of " + f"'str' and '{instance_type}'|'{instance_type}' and 'str'" + ) + + for left, right in [("infer", off), (off, "infer")]: + with pytest.raises(TypeError, match=msg): + left < right + with pytest.raises(TypeError, match=msg): + left <= right + with pytest.raises(TypeError, match=msg): + left > right + with pytest.raises(TypeError, match=msg): + left >= right + + +@pytest.mark.parametrize("cls", tick_classes) +def test_compare_ticks_to_timedeltalike(cls): + off = cls(19) + + td = off._as_pd_timedelta + + others = [td, td.to_timedelta64()] + if cls is not Nano: + others.append(td.to_pytimedelta()) + + for other in others: + assert off == other + assert not off != other + assert not off < other + assert not off > other + assert off <= other + assert off >= other diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_week.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_week.py new file mode 100644 index 0000000000000000000000000000000000000000..0cd6f769769ae3c3ae39f6b4a8f10641cd297715 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_week.py @@ -0,0 +1,351 @@ +""" +Tests for the following offsets: +- Week +- WeekOfMonth +- LastWeekOfMonth +""" +from __future__ import annotations + +from datetime import ( + datetime, + timedelta, +) + +import pytest + +from pandas._libs.tslibs import Timestamp +from pandas._libs.tslibs.offsets import ( + Day, + LastWeekOfMonth, + Week, + WeekOfMonth, +) + +import pandas._testing as tm +from pandas.tests.tseries.offsets.common import ( + WeekDay, + assert_is_on_offset, + assert_offset_equal, +) + + +class TestWeek: + def test_repr(self): + assert repr(Week(weekday=0)) == "" + assert repr(Week(n=-1, weekday=0)) == "<-1 * Week: weekday=0>" + assert repr(Week(n=-2, weekday=0)) == "<-2 * Weeks: weekday=0>" + + def test_corner(self): + with pytest.raises(ValueError, match="Day must be"): + Week(weekday=7) + + with pytest.raises(ValueError, match="Day must be"): + Week(weekday=-1) + + def test_is_anchored(self): + msg = "Week.is_anchored is deprecated " + + with tm.assert_produces_warning(FutureWarning, match=msg): + assert Week(weekday=0).is_anchored() + assert not Week().is_anchored() + assert not Week(2, weekday=2).is_anchored() + assert not Week(2).is_anchored() + + offset_cases = [] + # not business week + offset_cases.append( + ( + Week(), + { + datetime(2008, 1, 1): datetime(2008, 1, 8), + datetime(2008, 1, 4): datetime(2008, 1, 11), + datetime(2008, 1, 5): datetime(2008, 1, 12), + datetime(2008, 1, 6): datetime(2008, 1, 13), + datetime(2008, 1, 7): datetime(2008, 1, 14), + }, + ) + ) + + # Mon + offset_cases.append( + ( + Week(weekday=0), + { + datetime(2007, 12, 31): datetime(2008, 1, 7), + datetime(2008, 1, 4): datetime(2008, 1, 7), + datetime(2008, 1, 5): datetime(2008, 1, 7), + datetime(2008, 1, 6): datetime(2008, 1, 7), + datetime(2008, 1, 7): datetime(2008, 1, 14), + }, + ) + ) + + # n=0 -> roll forward. Mon + offset_cases.append( + ( + Week(0, weekday=0), + { + datetime(2007, 12, 31): datetime(2007, 12, 31), + datetime(2008, 1, 4): datetime(2008, 1, 7), + datetime(2008, 1, 5): datetime(2008, 1, 7), + datetime(2008, 1, 6): datetime(2008, 1, 7), + datetime(2008, 1, 7): datetime(2008, 1, 7), + }, + ) + ) + + # n=0 -> roll forward. Mon + offset_cases.append( + ( + Week(-2, weekday=1), + { + datetime(2010, 4, 6): datetime(2010, 3, 23), + datetime(2010, 4, 8): datetime(2010, 3, 30), + datetime(2010, 4, 5): datetime(2010, 3, 23), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + @pytest.mark.parametrize("weekday", range(7)) + def test_is_on_offset(self, weekday): + offset = Week(weekday=weekday) + + for day in range(1, 8): + date = datetime(2008, 1, day) + expected = day % 7 == weekday + assert_is_on_offset(offset, date, expected) + + @pytest.mark.parametrize( + "n,date", + [ + (2, "1862-01-13 09:03:34.873477378+0210"), + (-2, "1856-10-24 16:18:36.556360110-0717"), + ], + ) + def test_is_on_offset_weekday_none(self, n, date): + # GH 18510 Week with weekday = None, normalize = False + # should always be is_on_offset + offset = Week(n=n, weekday=None) + ts = Timestamp(date, tz="Africa/Lusaka") + fast = offset.is_on_offset(ts) + slow = (ts + offset) - offset == ts + assert fast == slow + + def test_week_add_invalid(self): + # Week with weekday should raise TypeError and _not_ AttributeError + # when adding invalid offset + offset = Week(weekday=1) + other = Day() + with pytest.raises(TypeError, match="Cannot add"): + offset + other + + +class TestWeekOfMonth: + def test_constructor(self): + with pytest.raises(ValueError, match="^Week"): + WeekOfMonth(n=1, week=4, weekday=0) + + with pytest.raises(ValueError, match="^Week"): + WeekOfMonth(n=1, week=-1, weekday=0) + + with pytest.raises(ValueError, match="^Day"): + WeekOfMonth(n=1, week=0, weekday=-1) + + with pytest.raises(ValueError, match="^Day"): + WeekOfMonth(n=1, week=0, weekday=-7) + + def test_repr(self): + assert ( + repr(WeekOfMonth(weekday=1, week=2)) == "" + ) + + def test_offset(self): + date1 = datetime(2011, 1, 4) # 1st Tuesday of Month + date2 = datetime(2011, 1, 11) # 2nd Tuesday of Month + date3 = datetime(2011, 1, 18) # 3rd Tuesday of Month + date4 = datetime(2011, 1, 25) # 4th Tuesday of Month + + # see for loop for structure + test_cases = [ + (-2, 2, 1, date1, datetime(2010, 11, 16)), + (-2, 2, 1, date2, datetime(2010, 11, 16)), + (-2, 2, 1, date3, datetime(2010, 11, 16)), + (-2, 2, 1, date4, datetime(2010, 12, 21)), + (-1, 2, 1, date1, datetime(2010, 12, 21)), + (-1, 2, 1, date2, datetime(2010, 12, 21)), + (-1, 2, 1, date3, datetime(2010, 12, 21)), + (-1, 2, 1, date4, datetime(2011, 1, 18)), + (0, 0, 1, date1, datetime(2011, 1, 4)), + (0, 0, 1, date2, datetime(2011, 2, 1)), + (0, 0, 1, date3, datetime(2011, 2, 1)), + (0, 0, 1, date4, datetime(2011, 2, 1)), + (0, 1, 1, date1, datetime(2011, 1, 11)), + (0, 1, 1, date2, datetime(2011, 1, 11)), + (0, 1, 1, date3, datetime(2011, 2, 8)), + (0, 1, 1, date4, datetime(2011, 2, 8)), + (0, 0, 1, date1, datetime(2011, 1, 4)), + (0, 1, 1, date2, datetime(2011, 1, 11)), + (0, 2, 1, date3, datetime(2011, 1, 18)), + (0, 3, 1, date4, datetime(2011, 1, 25)), + (1, 0, 0, date1, datetime(2011, 2, 7)), + (1, 0, 0, date2, datetime(2011, 2, 7)), + (1, 0, 0, date3, datetime(2011, 2, 7)), + (1, 0, 0, date4, datetime(2011, 2, 7)), + (1, 0, 1, date1, datetime(2011, 2, 1)), + (1, 0, 1, date2, datetime(2011, 2, 1)), + (1, 0, 1, date3, datetime(2011, 2, 1)), + (1, 0, 1, date4, datetime(2011, 2, 1)), + (1, 0, 2, date1, datetime(2011, 1, 5)), + (1, 0, 2, date2, datetime(2011, 2, 2)), + (1, 0, 2, date3, datetime(2011, 2, 2)), + (1, 0, 2, date4, datetime(2011, 2, 2)), + (1, 2, 1, date1, datetime(2011, 1, 18)), + (1, 2, 1, date2, datetime(2011, 1, 18)), + (1, 2, 1, date3, datetime(2011, 2, 15)), + (1, 2, 1, date4, datetime(2011, 2, 15)), + (2, 2, 1, date1, datetime(2011, 2, 15)), + (2, 2, 1, date2, datetime(2011, 2, 15)), + (2, 2, 1, date3, datetime(2011, 3, 15)), + (2, 2, 1, date4, datetime(2011, 3, 15)), + ] + + for n, week, weekday, dt, expected in test_cases: + offset = WeekOfMonth(n, week=week, weekday=weekday) + assert_offset_equal(offset, dt, expected) + + # try subtracting + result = datetime(2011, 2, 1) - WeekOfMonth(week=1, weekday=2) + assert result == datetime(2011, 1, 12) + + result = datetime(2011, 2, 3) - WeekOfMonth(week=0, weekday=2) + assert result == datetime(2011, 2, 2) + + on_offset_cases = [ + (0, 0, datetime(2011, 2, 7), True), + (0, 0, datetime(2011, 2, 6), False), + (0, 0, datetime(2011, 2, 14), False), + (1, 0, datetime(2011, 2, 14), True), + (0, 1, datetime(2011, 2, 1), True), + (0, 1, datetime(2011, 2, 8), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + week, weekday, dt, expected = case + offset = WeekOfMonth(week=week, weekday=weekday) + assert offset.is_on_offset(dt) == expected + + @pytest.mark.parametrize( + "n,week,date,tz", + [ + (2, 2, "1916-05-15 01:14:49.583410462+0422", "Asia/Qyzylorda"), + (-3, 1, "1980-12-08 03:38:52.878321185+0500", "Asia/Oral"), + ], + ) + def test_is_on_offset_nanoseconds(self, n, week, date, tz): + # GH 18864 + # Make sure that nanoseconds don't trip up is_on_offset (and with it apply) + offset = WeekOfMonth(n=n, week=week, weekday=0) + ts = Timestamp(date, tz=tz) + fast = offset.is_on_offset(ts) + slow = (ts + offset) - offset == ts + assert fast == slow + + +class TestLastWeekOfMonth: + def test_constructor(self): + with pytest.raises(ValueError, match="^N cannot be 0"): + LastWeekOfMonth(n=0, weekday=1) + + with pytest.raises(ValueError, match="^Day"): + LastWeekOfMonth(n=1, weekday=-1) + + with pytest.raises(ValueError, match="^Day"): + LastWeekOfMonth(n=1, weekday=7) + + def test_offset(self): + # Saturday + last_sat = datetime(2013, 8, 31) + next_sat = datetime(2013, 9, 28) + offset_sat = LastWeekOfMonth(n=1, weekday=5) + + one_day_before = last_sat + timedelta(days=-1) + assert one_day_before + offset_sat == last_sat + + one_day_after = last_sat + timedelta(days=+1) + assert one_day_after + offset_sat == next_sat + + # Test On that day + assert last_sat + offset_sat == next_sat + + # Thursday + + offset_thur = LastWeekOfMonth(n=1, weekday=3) + last_thurs = datetime(2013, 1, 31) + next_thurs = datetime(2013, 2, 28) + + one_day_before = last_thurs + timedelta(days=-1) + assert one_day_before + offset_thur == last_thurs + + one_day_after = last_thurs + timedelta(days=+1) + assert one_day_after + offset_thur == next_thurs + + # Test on that day + assert last_thurs + offset_thur == next_thurs + + three_before = last_thurs + timedelta(days=-3) + assert three_before + offset_thur == last_thurs + + two_after = last_thurs + timedelta(days=+2) + assert two_after + offset_thur == next_thurs + + offset_sunday = LastWeekOfMonth(n=1, weekday=WeekDay.SUN) + assert datetime(2013, 7, 31) + offset_sunday == datetime(2013, 8, 25) + + on_offset_cases = [ + (WeekDay.SUN, datetime(2013, 1, 27), True), + (WeekDay.SAT, datetime(2013, 3, 30), True), + (WeekDay.MON, datetime(2013, 2, 18), False), # Not the last Mon + (WeekDay.SUN, datetime(2013, 2, 25), False), # Not a SUN + (WeekDay.MON, datetime(2013, 2, 25), True), + (WeekDay.SAT, datetime(2013, 11, 30), True), + (WeekDay.SAT, datetime(2006, 8, 26), True), + (WeekDay.SAT, datetime(2007, 8, 25), True), + (WeekDay.SAT, datetime(2008, 8, 30), True), + (WeekDay.SAT, datetime(2009, 8, 29), True), + (WeekDay.SAT, datetime(2010, 8, 28), True), + (WeekDay.SAT, datetime(2011, 8, 27), True), + (WeekDay.SAT, datetime(2019, 8, 31), True), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + weekday, dt, expected = case + offset = LastWeekOfMonth(weekday=weekday) + assert offset.is_on_offset(dt) == expected + + @pytest.mark.parametrize( + "n,weekday,date,tz", + [ + (4, 6, "1917-05-27 20:55:27.084284178+0200", "Europe/Warsaw"), + (-4, 5, "2005-08-27 05:01:42.799392561-0500", "America/Rainy_River"), + ], + ) + def test_last_week_of_month_on_offset(self, n, weekday, date, tz): + # GH 19036, GH 18977 _adjust_dst was incorrect for LastWeekOfMonth + offset = LastWeekOfMonth(n=n, weekday=weekday) + ts = Timestamp(date, tz=tz) + slow = (ts + offset) - offset == ts + fast = offset.is_on_offset(ts) + assert fast == slow + + def test_repr(self): + assert ( + repr(LastWeekOfMonth(n=2, weekday=1)) == "<2 * LastWeekOfMonths: weekday=1>" + ) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_year.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_year.py new file mode 100644 index 0000000000000000000000000000000000000000..28cbdcf6abeccbbc02827d63c76aaa2f22b3c945 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tseries/offsets/test_year.py @@ -0,0 +1,339 @@ +""" +Tests for the following offsets: +- YearBegin +- YearEnd +""" +from __future__ import annotations + +from datetime import datetime + +import numpy as np +import pytest + +from pandas import Timestamp +from pandas.tests.tseries.offsets.common import ( + assert_is_on_offset, + assert_offset_equal, +) + +from pandas.tseries.offsets import ( + YearBegin, + YearEnd, +) + + +class TestYearBegin: + def test_misspecified(self): + with pytest.raises(ValueError, match="Month must go from 1 to 12"): + YearBegin(month=13) + + offset_cases = [] + offset_cases.append( + ( + YearBegin(), + { + datetime(2008, 1, 1): datetime(2009, 1, 1), + datetime(2008, 6, 30): datetime(2009, 1, 1), + datetime(2008, 12, 31): datetime(2009, 1, 1), + datetime(2005, 12, 30): datetime(2006, 1, 1), + datetime(2005, 12, 31): datetime(2006, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(0), + { + datetime(2008, 1, 1): datetime(2008, 1, 1), + datetime(2008, 6, 30): datetime(2009, 1, 1), + datetime(2008, 12, 31): datetime(2009, 1, 1), + datetime(2005, 12, 30): datetime(2006, 1, 1), + datetime(2005, 12, 31): datetime(2006, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(3), + { + datetime(2008, 1, 1): datetime(2011, 1, 1), + datetime(2008, 6, 30): datetime(2011, 1, 1), + datetime(2008, 12, 31): datetime(2011, 1, 1), + datetime(2005, 12, 30): datetime(2008, 1, 1), + datetime(2005, 12, 31): datetime(2008, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(-1), + { + datetime(2007, 1, 1): datetime(2006, 1, 1), + datetime(2007, 1, 15): datetime(2007, 1, 1), + datetime(2008, 6, 30): datetime(2008, 1, 1), + datetime(2008, 12, 31): datetime(2008, 1, 1), + datetime(2006, 12, 29): datetime(2006, 1, 1), + datetime(2006, 12, 30): datetime(2006, 1, 1), + datetime(2007, 1, 1): datetime(2006, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(-2), + { + datetime(2007, 1, 1): datetime(2005, 1, 1), + datetime(2008, 6, 30): datetime(2007, 1, 1), + datetime(2008, 12, 31): datetime(2007, 1, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(month=4), + { + datetime(2007, 4, 1): datetime(2008, 4, 1), + datetime(2007, 4, 15): datetime(2008, 4, 1), + datetime(2007, 3, 1): datetime(2007, 4, 1), + datetime(2007, 12, 15): datetime(2008, 4, 1), + datetime(2012, 1, 31): datetime(2012, 4, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(0, month=4), + { + datetime(2007, 4, 1): datetime(2007, 4, 1), + datetime(2007, 3, 1): datetime(2007, 4, 1), + datetime(2007, 12, 15): datetime(2008, 4, 1), + datetime(2012, 1, 31): datetime(2012, 4, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(4, month=4), + { + datetime(2007, 4, 1): datetime(2011, 4, 1), + datetime(2007, 4, 15): datetime(2011, 4, 1), + datetime(2007, 3, 1): datetime(2010, 4, 1), + datetime(2007, 12, 15): datetime(2011, 4, 1), + datetime(2012, 1, 31): datetime(2015, 4, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(-1, month=4), + { + datetime(2007, 4, 1): datetime(2006, 4, 1), + datetime(2007, 3, 1): datetime(2006, 4, 1), + datetime(2007, 12, 15): datetime(2007, 4, 1), + datetime(2012, 1, 31): datetime(2011, 4, 1), + }, + ) + ) + + offset_cases.append( + ( + YearBegin(-3, month=4), + { + datetime(2007, 4, 1): datetime(2004, 4, 1), + datetime(2007, 3, 1): datetime(2004, 4, 1), + datetime(2007, 12, 15): datetime(2005, 4, 1), + datetime(2012, 1, 31): datetime(2009, 4, 1), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (YearBegin(), datetime(2007, 1, 3), False), + (YearBegin(), datetime(2008, 1, 1), True), + (YearBegin(), datetime(2006, 12, 31), False), + (YearBegin(), datetime(2006, 1, 2), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + +class TestYearEnd: + def test_misspecified(self): + with pytest.raises(ValueError, match="Month must go from 1 to 12"): + YearEnd(month=13) + + offset_cases = [] + offset_cases.append( + ( + YearEnd(), + { + datetime(2008, 1, 1): datetime(2008, 12, 31), + datetime(2008, 6, 30): datetime(2008, 12, 31), + datetime(2008, 12, 31): datetime(2009, 12, 31), + datetime(2005, 12, 30): datetime(2005, 12, 31), + datetime(2005, 12, 31): datetime(2006, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + YearEnd(0), + { + datetime(2008, 1, 1): datetime(2008, 12, 31), + datetime(2008, 6, 30): datetime(2008, 12, 31), + datetime(2008, 12, 31): datetime(2008, 12, 31), + datetime(2005, 12, 30): datetime(2005, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + YearEnd(-1), + { + datetime(2007, 1, 1): datetime(2006, 12, 31), + datetime(2008, 6, 30): datetime(2007, 12, 31), + datetime(2008, 12, 31): datetime(2007, 12, 31), + datetime(2006, 12, 29): datetime(2005, 12, 31), + datetime(2006, 12, 30): datetime(2005, 12, 31), + datetime(2007, 1, 1): datetime(2006, 12, 31), + }, + ) + ) + + offset_cases.append( + ( + YearEnd(-2), + { + datetime(2007, 1, 1): datetime(2005, 12, 31), + datetime(2008, 6, 30): datetime(2006, 12, 31), + datetime(2008, 12, 31): datetime(2006, 12, 31), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (YearEnd(), datetime(2007, 12, 31), True), + (YearEnd(), datetime(2008, 1, 1), False), + (YearEnd(), datetime(2006, 12, 31), True), + (YearEnd(), datetime(2006, 12, 29), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + +class TestYearEndDiffMonth: + offset_cases = [] + offset_cases.append( + ( + YearEnd(month=3), + { + datetime(2008, 1, 1): datetime(2008, 3, 31), + datetime(2008, 2, 15): datetime(2008, 3, 31), + datetime(2008, 3, 31): datetime(2009, 3, 31), + datetime(2008, 3, 30): datetime(2008, 3, 31), + datetime(2005, 3, 31): datetime(2006, 3, 31), + datetime(2006, 7, 30): datetime(2007, 3, 31), + }, + ) + ) + + offset_cases.append( + ( + YearEnd(0, month=3), + { + datetime(2008, 1, 1): datetime(2008, 3, 31), + datetime(2008, 2, 28): datetime(2008, 3, 31), + datetime(2008, 3, 31): datetime(2008, 3, 31), + datetime(2005, 3, 30): datetime(2005, 3, 31), + }, + ) + ) + + offset_cases.append( + ( + YearEnd(-1, month=3), + { + datetime(2007, 1, 1): datetime(2006, 3, 31), + datetime(2008, 2, 28): datetime(2007, 3, 31), + datetime(2008, 3, 31): datetime(2007, 3, 31), + datetime(2006, 3, 29): datetime(2005, 3, 31), + datetime(2006, 3, 30): datetime(2005, 3, 31), + datetime(2007, 3, 1): datetime(2006, 3, 31), + }, + ) + ) + + offset_cases.append( + ( + YearEnd(-2, month=3), + { + datetime(2007, 1, 1): datetime(2005, 3, 31), + datetime(2008, 6, 30): datetime(2007, 3, 31), + datetime(2008, 3, 31): datetime(2006, 3, 31), + }, + ) + ) + + @pytest.mark.parametrize("case", offset_cases) + def test_offset(self, case): + offset, cases = case + for base, expected in cases.items(): + assert_offset_equal(offset, base, expected) + + on_offset_cases = [ + (YearEnd(month=3), datetime(2007, 3, 31), True), + (YearEnd(month=3), datetime(2008, 1, 1), False), + (YearEnd(month=3), datetime(2006, 3, 31), True), + (YearEnd(month=3), datetime(2006, 3, 29), False), + ] + + @pytest.mark.parametrize("case", on_offset_cases) + def test_is_on_offset(self, case): + offset, dt, expected = case + assert_is_on_offset(offset, dt, expected) + + +def test_add_out_of_pydatetime_range(): + # GH#50348 don't raise in Timestamp.replace + ts = Timestamp(np.datetime64("-20000-12-31")) + off = YearEnd() + + result = ts + off + # TODO(cython3): "arg: datetime" annotation will impose + # datetime limitations on Timestamp. The fused type below works in cy3 + # ctypedef fused datetimelike: + # _Timestamp + # datetime + # expected = Timestamp(np.datetime64("-19999-12-31")) + # assert result == expected + assert result.year in (-19999, 1973) + assert result.month == 12 + assert result.day == 31 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_api.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_api.py new file mode 100644 index 0000000000000000000000000000000000000000..42d055326c2a54f5fcd6ba2257201eaec2a3122b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_api.py @@ -0,0 +1,65 @@ +"""Tests that the tslibs API is locked down""" + +from pandas._libs import tslibs + + +def test_namespace(): + submodules = [ + "base", + "ccalendar", + "conversion", + "dtypes", + "fields", + "nattype", + "np_datetime", + "offsets", + "parsing", + "period", + "strptime", + "vectorized", + "timedeltas", + "timestamps", + "timezones", + "tzconversion", + ] + + api = [ + "BaseOffset", + "NaT", + "NaTType", + "iNaT", + "nat_strings", + "OutOfBoundsDatetime", + "OutOfBoundsTimedelta", + "Period", + "IncompatibleFrequency", + "Resolution", + "Tick", + "Timedelta", + "dt64arr_to_periodarr", + "Timestamp", + "is_date_array_normalized", + "ints_to_pydatetime", + "normalize_i8_timestamps", + "get_resolution", + "delta_to_nanoseconds", + "ints_to_pytimedelta", + "localize_pydatetime", + "tz_convert_from_utc", + "tz_convert_from_utc_single", + "to_offset", + "tz_compare", + "is_unitless", + "astype_overflowsafe", + "get_unit_from_dtype", + "periods_per_day", + "periods_per_second", + "guess_datetime_format", + "add_overflowsafe", + "get_supported_dtype", + "is_supported_dtype", + ] + + expected = set(submodules + api) + names = [x for x in dir(tslibs) if not x.startswith("__")] + assert set(names) == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_array_to_datetime.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_array_to_datetime.py new file mode 100644 index 0000000000000000000000000000000000000000..82175c67764f84355dfb6d10a0477e9e0344e296 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_array_to_datetime.py @@ -0,0 +1,337 @@ +from datetime import ( + date, + datetime, + timedelta, + timezone, +) + +from dateutil.tz.tz import tzoffset +import numpy as np +import pytest + +from pandas._libs import ( + NaT, + iNaT, + tslib, +) +from pandas._libs.tslibs.dtypes import NpyDatetimeUnit +from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime + +from pandas import Timestamp +import pandas._testing as tm + +creso_infer = NpyDatetimeUnit.NPY_FR_GENERIC.value + + +class TestArrayToDatetimeResolutionInference: + # TODO: tests that include tzs, ints + + def test_infer_all_nat(self): + arr = np.array([NaT, np.nan], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + assert result.dtype == "M8[s]" + + def test_infer_homogeoneous_datetimes(self): + dt = datetime(2023, 10, 27, 18, 3, 5, 678000) + arr = np.array([dt, dt, dt], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + expected = np.array([dt, dt, dt], dtype="M8[us]") + tm.assert_numpy_array_equal(result, expected) + + def test_infer_homogeoneous_date_objects(self): + dt = datetime(2023, 10, 27, 18, 3, 5, 678000) + dt2 = dt.date() + arr = np.array([None, dt2, dt2, dt2], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + expected = np.array([np.datetime64("NaT"), dt2, dt2, dt2], dtype="M8[s]") + tm.assert_numpy_array_equal(result, expected) + + def test_infer_homogeoneous_dt64(self): + dt = datetime(2023, 10, 27, 18, 3, 5, 678000) + dt64 = np.datetime64(dt, "ms") + arr = np.array([None, dt64, dt64, dt64], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + expected = np.array([np.datetime64("NaT"), dt64, dt64, dt64], dtype="M8[ms]") + tm.assert_numpy_array_equal(result, expected) + + def test_infer_homogeoneous_timestamps(self): + dt = datetime(2023, 10, 27, 18, 3, 5, 678000) + ts = Timestamp(dt).as_unit("ns") + arr = np.array([None, ts, ts, ts], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + expected = np.array([np.datetime64("NaT")] + [ts.asm8] * 3, dtype="M8[ns]") + tm.assert_numpy_array_equal(result, expected) + + def test_infer_homogeoneous_datetimes_strings(self): + item = "2023-10-27 18:03:05.678000" + arr = np.array([None, item, item, item], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + expected = np.array([np.datetime64("NaT"), item, item, item], dtype="M8[us]") + tm.assert_numpy_array_equal(result, expected) + + def test_infer_heterogeneous(self): + dtstr = "2023-10-27 18:03:05.678000" + + arr = np.array([dtstr, dtstr[:-3], dtstr[:-7], None], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + expected = np.array(arr, dtype="M8[us]") + tm.assert_numpy_array_equal(result, expected) + + result, tz = tslib.array_to_datetime(arr[::-1], creso=creso_infer) + assert tz is None + tm.assert_numpy_array_equal(result, expected[::-1]) + + @pytest.mark.parametrize( + "item", [float("nan"), NaT.value, float(NaT.value), "NaT", ""] + ) + def test_infer_with_nat_int_float_str(self, item): + # floats/ints get inferred to nanos *unless* they are NaN/iNaT, + # similar NaT string gets treated like NaT scalar (ignored for resolution) + dt = datetime(2023, 11, 15, 15, 5, 6) + + arr = np.array([dt, item], dtype=object) + result, tz = tslib.array_to_datetime(arr, creso=creso_infer) + assert tz is None + expected = np.array([dt, np.datetime64("NaT")], dtype="M8[us]") + tm.assert_numpy_array_equal(result, expected) + + result2, tz2 = tslib.array_to_datetime(arr[::-1], creso=creso_infer) + assert tz2 is None + tm.assert_numpy_array_equal(result2, expected[::-1]) + + +class TestArrayToDatetimeWithTZResolutionInference: + def test_array_to_datetime_with_tz_resolution(self): + tz = tzoffset("custom", 3600) + vals = np.array(["2016-01-01 02:03:04.567", NaT], dtype=object) + res = tslib.array_to_datetime_with_tz(vals, tz, False, False, creso_infer) + assert res.dtype == "M8[ms]" + + vals2 = np.array([datetime(2016, 1, 1, 2, 3, 4), NaT], dtype=object) + res2 = tslib.array_to_datetime_with_tz(vals2, tz, False, False, creso_infer) + assert res2.dtype == "M8[us]" + + vals3 = np.array([NaT, np.datetime64(12345, "s")], dtype=object) + res3 = tslib.array_to_datetime_with_tz(vals3, tz, False, False, creso_infer) + assert res3.dtype == "M8[s]" + + def test_array_to_datetime_with_tz_resolution_all_nat(self): + tz = tzoffset("custom", 3600) + vals = np.array(["NaT"], dtype=object) + res = tslib.array_to_datetime_with_tz(vals, tz, False, False, creso_infer) + assert res.dtype == "M8[s]" + + vals2 = np.array([NaT, NaT], dtype=object) + res2 = tslib.array_to_datetime_with_tz(vals2, tz, False, False, creso_infer) + assert res2.dtype == "M8[s]" + + +@pytest.mark.parametrize( + "data,expected", + [ + ( + ["01-01-2013", "01-02-2013"], + [ + "2013-01-01T00:00:00.000000000", + "2013-01-02T00:00:00.000000000", + ], + ), + ( + ["Mon Sep 16 2013", "Tue Sep 17 2013"], + [ + "2013-09-16T00:00:00.000000000", + "2013-09-17T00:00:00.000000000", + ], + ), + ], +) +def test_parsing_valid_dates(data, expected): + arr = np.array(data, dtype=object) + result, _ = tslib.array_to_datetime(arr) + + expected = np.array(expected, dtype="M8[ns]") + tm.assert_numpy_array_equal(result, expected) + + +@pytest.mark.parametrize( + "dt_string, expected_tz", + [ + ["01-01-2013 08:00:00+08:00", 480], + ["2013-01-01T08:00:00.000000000+0800", 480], + ["2012-12-31T16:00:00.000000000-0800", -480], + ["12-31-2012 23:00:00-01:00", -60], + ], +) +def test_parsing_timezone_offsets(dt_string, expected_tz): + # All of these datetime strings with offsets are equivalent + # to the same datetime after the timezone offset is added. + arr = np.array(["01-01-2013 00:00:00"], dtype=object) + expected, _ = tslib.array_to_datetime(arr) + + arr = np.array([dt_string], dtype=object) + result, result_tz = tslib.array_to_datetime(arr) + + tm.assert_numpy_array_equal(result, expected) + assert result_tz == timezone(timedelta(minutes=expected_tz)) + + +def test_parsing_non_iso_timezone_offset(): + dt_string = "01-01-2013T00:00:00.000000000+0000" + arr = np.array([dt_string], dtype=object) + + with tm.assert_produces_warning(None): + # GH#50949 should not get tzlocal-deprecation warning here + result, result_tz = tslib.array_to_datetime(arr) + expected = np.array([np.datetime64("2013-01-01 00:00:00.000000000")]) + + tm.assert_numpy_array_equal(result, expected) + assert result_tz is timezone.utc + + +def test_parsing_different_timezone_offsets(): + # see gh-17697 + data = ["2015-11-18 15:30:00+05:30", "2015-11-18 15:30:00+06:30"] + data = np.array(data, dtype=object) + + msg = "parsing datetimes with mixed time zones will raise an error" + with tm.assert_produces_warning(FutureWarning, match=msg): + result, result_tz = tslib.array_to_datetime(data) + expected = np.array( + [ + datetime(2015, 11, 18, 15, 30, tzinfo=tzoffset(None, 19800)), + datetime(2015, 11, 18, 15, 30, tzinfo=tzoffset(None, 23400)), + ], + dtype=object, + ) + + tm.assert_numpy_array_equal(result, expected) + assert result_tz is None + + +@pytest.mark.parametrize( + "data", [["-352.737091", "183.575577"], ["1", "2", "3", "4", "5"]] +) +def test_number_looking_strings_not_into_datetime(data): + # see gh-4601 + # + # These strings don't look like datetimes, so + # they shouldn't be attempted to be converted. + arr = np.array(data, dtype=object) + result, _ = tslib.array_to_datetime(arr, errors="ignore") + + tm.assert_numpy_array_equal(result, arr) + + +@pytest.mark.parametrize( + "invalid_date", + [ + date(1000, 1, 1), + datetime(1000, 1, 1), + "1000-01-01", + "Jan 1, 1000", + np.datetime64("1000-01-01"), + ], +) +@pytest.mark.parametrize("errors", ["coerce", "raise"]) +def test_coerce_outside_ns_bounds(invalid_date, errors): + arr = np.array([invalid_date], dtype="object") + kwargs = {"values": arr, "errors": errors} + + if errors == "raise": + msg = "^Out of bounds nanosecond timestamp: .*, at position 0$" + + with pytest.raises(OutOfBoundsDatetime, match=msg): + tslib.array_to_datetime(**kwargs) + else: # coerce. + result, _ = tslib.array_to_datetime(**kwargs) + expected = np.array([iNaT], dtype="M8[ns]") + + tm.assert_numpy_array_equal(result, expected) + + +def test_coerce_outside_ns_bounds_one_valid(): + arr = np.array(["1/1/1000", "1/1/2000"], dtype=object) + result, _ = tslib.array_to_datetime(arr, errors="coerce") + + expected = [iNaT, "2000-01-01T00:00:00.000000000"] + expected = np.array(expected, dtype="M8[ns]") + + tm.assert_numpy_array_equal(result, expected) + + +@pytest.mark.parametrize("errors", ["ignore", "coerce"]) +def test_coerce_of_invalid_datetimes(errors): + arr = np.array(["01-01-2013", "not_a_date", "1"], dtype=object) + kwargs = {"values": arr, "errors": errors} + + if errors == "ignore": + # Without coercing, the presence of any invalid + # dates prevents any values from being converted. + result, _ = tslib.array_to_datetime(**kwargs) + tm.assert_numpy_array_equal(result, arr) + else: # coerce. + # With coercing, the invalid dates becomes iNaT + result, _ = tslib.array_to_datetime(arr, errors="coerce") + expected = ["2013-01-01T00:00:00.000000000", iNaT, iNaT] + + tm.assert_numpy_array_equal(result, np.array(expected, dtype="M8[ns]")) + + +def test_to_datetime_barely_out_of_bounds(): + # see gh-19382, gh-19529 + # + # Close enough to bounds that dropping nanos + # would result in an in-bounds datetime. + arr = np.array(["2262-04-11 23:47:16.854775808"], dtype=object) + msg = "^Out of bounds nanosecond timestamp: 2262-04-11 23:47:16, at position 0$" + + with pytest.raises(tslib.OutOfBoundsDatetime, match=msg): + tslib.array_to_datetime(arr) + + +@pytest.mark.parametrize( + "timestamp", + [ + # Close enough to bounds that scaling micros to nanos overflows + # but adding nanos would result in an in-bounds datetime. + "1677-09-21T00:12:43.145224193", + "1677-09-21T00:12:43.145224999", + # this always worked + "1677-09-21T00:12:43.145225000", + ], +) +def test_to_datetime_barely_inside_bounds(timestamp): + # see gh-57150 + result, _ = tslib.array_to_datetime(np.array([timestamp], dtype=object)) + tm.assert_numpy_array_equal(result, np.array([timestamp], dtype="M8[ns]")) + + +class SubDatetime(datetime): + pass + + +@pytest.mark.parametrize( + "data,expected", + [ + ([SubDatetime(2000, 1, 1)], ["2000-01-01T00:00:00.000000000"]), + ([datetime(2000, 1, 1)], ["2000-01-01T00:00:00.000000000"]), + ([Timestamp(2000, 1, 1)], ["2000-01-01T00:00:00.000000000"]), + ], +) +def test_datetime_subclass(data, expected): + # GH 25851 + # ensure that subclassed datetime works with + # array_to_datetime + + arr = np.array(data, dtype=object) + result, _ = tslib.array_to_datetime(arr) + + expected = np.array(expected, dtype="M8[ns]") + tm.assert_numpy_array_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_ccalendar.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_ccalendar.py new file mode 100644 index 0000000000000000000000000000000000000000..8dd1bd47e4728d1b35e84b14f29e0a255178ec9b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_ccalendar.py @@ -0,0 +1,63 @@ +from datetime import ( + date, + datetime, +) + +from hypothesis import given +import numpy as np +import pytest + +from pandas._libs.tslibs import ccalendar + +from pandas._testing._hypothesis import DATETIME_IN_PD_TIMESTAMP_RANGE_NO_TZ + + +@pytest.mark.parametrize( + "date_tuple,expected", + [ + ((2001, 3, 1), 60), + ((2004, 3, 1), 61), + ((1907, 12, 31), 365), # End-of-year, non-leap year. + ((2004, 12, 31), 366), # End-of-year, leap year. + ], +) +def test_get_day_of_year_numeric(date_tuple, expected): + assert ccalendar.get_day_of_year(*date_tuple) == expected + + +def test_get_day_of_year_dt(): + dt = datetime.fromordinal(1 + np.random.default_rng(2).integers(365 * 4000)) + result = ccalendar.get_day_of_year(dt.year, dt.month, dt.day) + + expected = (dt - dt.replace(month=1, day=1)).days + 1 + assert result == expected + + +@pytest.mark.parametrize( + "input_date_tuple, expected_iso_tuple", + [ + [(2020, 1, 1), (2020, 1, 3)], + [(2019, 12, 31), (2020, 1, 2)], + [(2019, 12, 30), (2020, 1, 1)], + [(2009, 12, 31), (2009, 53, 4)], + [(2010, 1, 1), (2009, 53, 5)], + [(2010, 1, 3), (2009, 53, 7)], + [(2010, 1, 4), (2010, 1, 1)], + [(2006, 1, 1), (2005, 52, 7)], + [(2005, 12, 31), (2005, 52, 6)], + [(2008, 12, 28), (2008, 52, 7)], + [(2008, 12, 29), (2009, 1, 1)], + ], +) +def test_dt_correct_iso_8601_year_week_and_day(input_date_tuple, expected_iso_tuple): + result = ccalendar.get_iso_calendar(*input_date_tuple) + expected_from_date_isocalendar = date(*input_date_tuple).isocalendar() + assert result == expected_from_date_isocalendar + assert result == expected_iso_tuple + + +@given(DATETIME_IN_PD_TIMESTAMP_RANGE_NO_TZ) +def test_isocalendar(dt): + expected = dt.isocalendar() + result = ccalendar.get_iso_calendar(dt.year, dt.month, dt.day) + assert result == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_conversion.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_conversion.py new file mode 100644 index 0000000000000000000000000000000000000000..9d7a5e906c3c3771a7d909f0ded9397e5cee0d64 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_conversion.py @@ -0,0 +1,160 @@ +from datetime import datetime + +import numpy as np +import pytest +from pytz import UTC + +from pandas._libs.tslibs import ( + OutOfBoundsTimedelta, + astype_overflowsafe, + conversion, + iNaT, + timezones, + tz_convert_from_utc, + tzconversion, +) + +from pandas import ( + Timestamp, + date_range, +) +import pandas._testing as tm + + +def _compare_utc_to_local(tz_didx): + def f(x): + return tzconversion.tz_convert_from_utc_single(x, tz_didx.tz) + + result = tz_convert_from_utc(tz_didx.asi8, tz_didx.tz) + expected = np.vectorize(f)(tz_didx.asi8) + + tm.assert_numpy_array_equal(result, expected) + + +def _compare_local_to_utc(tz_didx, naive_didx): + # Check that tz_localize behaves the same vectorized and pointwise. + err1 = err2 = None + try: + result = tzconversion.tz_localize_to_utc(naive_didx.asi8, tz_didx.tz) + err1 = None + except Exception as err: + err1 = err + + try: + expected = naive_didx.map(lambda x: x.tz_localize(tz_didx.tz)).asi8 + except Exception as err: + err2 = err + + if err1 is not None: + assert type(err1) == type(err2) + else: + assert err2 is None + tm.assert_numpy_array_equal(result, expected) + + +def test_tz_localize_to_utc_copies(): + # GH#46460 + arr = np.arange(5, dtype="i8") + result = tz_convert_from_utc(arr, tz=UTC) + tm.assert_numpy_array_equal(result, arr) + assert not np.shares_memory(arr, result) + + result = tz_convert_from_utc(arr, tz=None) + tm.assert_numpy_array_equal(result, arr) + assert not np.shares_memory(arr, result) + + +def test_tz_convert_single_matches_tz_convert_hourly(tz_aware_fixture): + tz = tz_aware_fixture + tz_didx = date_range("2014-03-01", "2015-01-10", freq="h", tz=tz) + naive_didx = date_range("2014-03-01", "2015-01-10", freq="h") + + _compare_utc_to_local(tz_didx) + _compare_local_to_utc(tz_didx, naive_didx) + + +@pytest.mark.parametrize("freq", ["D", "YE"]) +def test_tz_convert_single_matches_tz_convert(tz_aware_fixture, freq): + tz = tz_aware_fixture + tz_didx = date_range("2018-01-01", "2020-01-01", freq=freq, tz=tz) + naive_didx = date_range("2018-01-01", "2020-01-01", freq=freq) + + _compare_utc_to_local(tz_didx) + _compare_local_to_utc(tz_didx, naive_didx) + + +@pytest.mark.parametrize( + "arr", + [ + pytest.param(np.array([], dtype=np.int64), id="empty"), + pytest.param(np.array([iNaT], dtype=np.int64), id="all_nat"), + ], +) +def test_tz_convert_corner(arr): + result = tz_convert_from_utc(arr, timezones.maybe_get_tz("Asia/Tokyo")) + tm.assert_numpy_array_equal(result, arr) + + +def test_tz_convert_readonly(): + # GH#35530 + arr = np.array([0], dtype=np.int64) + arr.setflags(write=False) + result = tz_convert_from_utc(arr, UTC) + tm.assert_numpy_array_equal(result, arr) + + +@pytest.mark.parametrize("copy", [True, False]) +@pytest.mark.parametrize("dtype", ["M8[ns]", "M8[s]"]) +def test_length_zero_copy(dtype, copy): + arr = np.array([], dtype=dtype) + result = astype_overflowsafe(arr, copy=copy, dtype=np.dtype("M8[ns]")) + if copy: + assert not np.shares_memory(result, arr) + elif arr.dtype == result.dtype: + assert result is arr + else: + assert not np.shares_memory(result, arr) + + +def test_ensure_datetime64ns_bigendian(): + # GH#29684 + arr = np.array([np.datetime64(1, "ms")], dtype=">M8[ms]") + result = astype_overflowsafe(arr, dtype=np.dtype("M8[ns]")) + + expected = np.array([np.datetime64(1, "ms")], dtype="M8[ns]") + tm.assert_numpy_array_equal(result, expected) + + +def test_ensure_timedelta64ns_overflows(): + arr = np.arange(10).astype("m8[Y]") * 100 + msg = r"Cannot convert 300 years to timedelta64\[ns\] without overflow" + with pytest.raises(OutOfBoundsTimedelta, match=msg): + astype_overflowsafe(arr, dtype=np.dtype("m8[ns]")) + + +class SubDatetime(datetime): + pass + + +@pytest.mark.parametrize( + "dt, expected", + [ + pytest.param( + Timestamp("2000-01-01"), Timestamp("2000-01-01", tz=UTC), id="timestamp" + ), + pytest.param( + datetime(2000, 1, 1), datetime(2000, 1, 1, tzinfo=UTC), id="datetime" + ), + pytest.param( + SubDatetime(2000, 1, 1), + SubDatetime(2000, 1, 1, tzinfo=UTC), + id="subclassed_datetime", + ), + ], +) +def test_localize_pydatetime_dt_types(dt, expected): + # GH 25851 + # ensure that subclassed datetime works with + # localize_pydatetime + result = conversion.localize_pydatetime(dt, UTC) + assert result == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_fields.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_fields.py new file mode 100644 index 0000000000000000000000000000000000000000..da67c093b8f4dbaffba9e02f395bb830de33b489 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_fields.py @@ -0,0 +1,40 @@ +import numpy as np +import pytest + +from pandas._libs.tslibs import fields + +import pandas._testing as tm + + +@pytest.fixture +def dtindex(): + dtindex = np.arange(5, dtype=np.int64) * 10**9 * 3600 * 24 * 32 + dtindex.flags.writeable = False + return dtindex + + +def test_get_date_name_field_readonly(dtindex): + # https://github.com/vaexio/vaex/issues/357 + # fields functions shouldn't raise when we pass read-only data + result = fields.get_date_name_field(dtindex, "month_name") + expected = np.array(["January", "February", "March", "April", "May"], dtype=object) + tm.assert_numpy_array_equal(result, expected) + + +def test_get_date_field_readonly(dtindex): + result = fields.get_date_field(dtindex, "Y") + expected = np.array([1970, 1970, 1970, 1970, 1970], dtype=np.int32) + tm.assert_numpy_array_equal(result, expected) + + +def test_get_start_end_field_readonly(dtindex): + result = fields.get_start_end_field(dtindex, "is_month_start", None) + expected = np.array([True, False, False, False, False], dtype=np.bool_) + tm.assert_numpy_array_equal(result, expected) + + +def test_get_timedelta_field_readonly(dtindex): + # treat dtindex as timedeltas for this next one + result = fields.get_timedelta_field(dtindex, "seconds") + expected = np.array([0] * 5, dtype=np.int32) + tm.assert_numpy_array_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_libfrequencies.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_libfrequencies.py new file mode 100644 index 0000000000000000000000000000000000000000..effd3b4b8b4e5fa113f1b20506997efc54d3c9d2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_libfrequencies.py @@ -0,0 +1,27 @@ +import pytest + +from pandas._libs.tslibs.parsing import get_rule_month + +from pandas.tseries import offsets + + +@pytest.mark.parametrize( + "obj,expected", + [ + ("W", "DEC"), + (offsets.Week().freqstr, "DEC"), + ("D", "DEC"), + (offsets.Day().freqstr, "DEC"), + ("Q", "DEC"), + (offsets.QuarterEnd(startingMonth=12).freqstr, "DEC"), + ("Q-JAN", "JAN"), + (offsets.QuarterEnd(startingMonth=1).freqstr, "JAN"), + ("Y-DEC", "DEC"), + (offsets.YearEnd().freqstr, "DEC"), + ("Y-MAY", "MAY"), + (offsets.YearEnd(month=5).freqstr, "MAY"), + ], +) +def test_get_rule_month(obj, expected): + result = get_rule_month(obj) + assert result == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_liboffsets.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_liboffsets.py new file mode 100644 index 0000000000000000000000000000000000000000..c189a431146a7172862586ea3a015ad4f2676cf2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_liboffsets.py @@ -0,0 +1,173 @@ +""" +Tests for helper functions in the cython tslibs.offsets +""" +from datetime import datetime + +import pytest + +from pandas._libs.tslibs.ccalendar import ( + get_firstbday, + get_lastbday, +) +import pandas._libs.tslibs.offsets as liboffsets +from pandas._libs.tslibs.offsets import roll_qtrday + +from pandas import Timestamp + + +@pytest.fixture(params=["start", "end", "business_start", "business_end"]) +def day_opt(request): + return request.param + + +@pytest.mark.parametrize( + "dt,exp_week_day,exp_last_day", + [ + (datetime(2017, 11, 30), 3, 30), # Business day. + (datetime(1993, 10, 31), 6, 29), # Non-business day. + ], +) +def test_get_last_bday(dt, exp_week_day, exp_last_day): + assert dt.weekday() == exp_week_day + assert get_lastbday(dt.year, dt.month) == exp_last_day + + +@pytest.mark.parametrize( + "dt,exp_week_day,exp_first_day", + [ + (datetime(2017, 4, 1), 5, 3), # Non-weekday. + (datetime(1993, 10, 1), 4, 1), # Business day. + ], +) +def test_get_first_bday(dt, exp_week_day, exp_first_day): + assert dt.weekday() == exp_week_day + assert get_firstbday(dt.year, dt.month) == exp_first_day + + +@pytest.mark.parametrize( + "months,day_opt,expected", + [ + (0, 15, datetime(2017, 11, 15)), + (0, None, datetime(2017, 11, 30)), + (1, "start", datetime(2017, 12, 1)), + (-145, "end", datetime(2005, 10, 31)), + (0, "business_end", datetime(2017, 11, 30)), + (0, "business_start", datetime(2017, 11, 1)), + ], +) +def test_shift_month_dt(months, day_opt, expected): + dt = datetime(2017, 11, 30) + assert liboffsets.shift_month(dt, months, day_opt=day_opt) == expected + + +@pytest.mark.parametrize( + "months,day_opt,expected", + [ + (1, "start", Timestamp("1929-06-01")), + (-3, "end", Timestamp("1929-02-28")), + (25, None, Timestamp("1931-06-5")), + (-1, 31, Timestamp("1929-04-30")), + ], +) +def test_shift_month_ts(months, day_opt, expected): + ts = Timestamp("1929-05-05") + assert liboffsets.shift_month(ts, months, day_opt=day_opt) == expected + + +def test_shift_month_error(): + dt = datetime(2017, 11, 15) + day_opt = "this should raise" + + with pytest.raises(ValueError, match=day_opt): + liboffsets.shift_month(dt, 3, day_opt=day_opt) + + +@pytest.mark.parametrize( + "other,expected", + [ + # Before March 1. + (datetime(2017, 2, 10), {2: 1, -7: -7, 0: 0}), + # After March 1. + (Timestamp("2014-03-15", tz="US/Eastern"), {2: 2, -7: -6, 0: 1}), + ], +) +@pytest.mark.parametrize("n", [2, -7, 0]) +def test_roll_qtrday_year(other, expected, n): + month = 3 + day_opt = "start" # `other` will be compared to March 1. + + assert roll_qtrday(other, n, month, day_opt, modby=12) == expected[n] + + +@pytest.mark.parametrize( + "other,expected", + [ + # Before June 30. + (datetime(1999, 6, 29), {5: 4, -7: -7, 0: 0}), + # After June 30. + (Timestamp(2072, 8, 24, 6, 17, 18), {5: 5, -7: -6, 0: 1}), + ], +) +@pytest.mark.parametrize("n", [5, -7, 0]) +def test_roll_qtrday_year2(other, expected, n): + month = 6 + day_opt = "end" # `other` will be compared to June 30. + + assert roll_qtrday(other, n, month, day_opt, modby=12) == expected[n] + + +def test_get_day_of_month_error(): + # get_day_of_month is not directly exposed. + # We test it via roll_qtrday. + dt = datetime(2017, 11, 15) + day_opt = "foo" + + with pytest.raises(ValueError, match=day_opt): + # To hit the raising case we need month == dt.month and n > 0. + roll_qtrday(dt, n=3, month=11, day_opt=day_opt, modby=12) + + +@pytest.mark.parametrize( + "month", + [3, 5], # (other.month % 3) < (month % 3) # (other.month % 3) > (month % 3) +) +@pytest.mark.parametrize("n", [4, -3]) +def test_roll_qtr_day_not_mod_unequal(day_opt, month, n): + expected = {3: {-3: -2, 4: 4}, 5: {-3: -3, 4: 3}} + + other = Timestamp(2072, 10, 1, 6, 17, 18) # Saturday. + assert roll_qtrday(other, n, month, day_opt, modby=3) == expected[month][n] + + +@pytest.mark.parametrize( + "other,month,exp_dict", + [ + # Monday. + (datetime(1999, 5, 31), 2, {-1: {"start": 0, "business_start": 0}}), + # Saturday. + ( + Timestamp(2072, 10, 1, 6, 17, 18), + 4, + {2: {"end": 1, "business_end": 1, "business_start": 1}}, + ), + # First business day. + ( + Timestamp(2072, 10, 3, 6, 17, 18), + 4, + {2: {"end": 1, "business_end": 1}, -1: {"start": 0}}, + ), + ], +) +@pytest.mark.parametrize("n", [2, -1]) +def test_roll_qtr_day_mod_equal(other, month, exp_dict, n, day_opt): + # All cases have (other.month % 3) == (month % 3). + expected = exp_dict.get(n, {}).get(day_opt, n) + assert roll_qtrday(other, n, month, day_opt, modby=3) == expected + + +@pytest.mark.parametrize( + "n,expected", [(42, {29: 42, 1: 42, 31: 41}), (-4, {29: -4, 1: -3, 31: -4})] +) +@pytest.mark.parametrize("compare", [29, 1, 31]) +def test_roll_convention(n, expected, compare): + assert liboffsets.roll_convention(29, n, compare) == expected[compare] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_np_datetime.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_np_datetime.py new file mode 100644 index 0000000000000000000000000000000000000000..02edf1a09387766d71097ea0baedc2640cfb824b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_np_datetime.py @@ -0,0 +1,222 @@ +import numpy as np +import pytest + +from pandas._libs.tslibs.dtypes import NpyDatetimeUnit +from pandas._libs.tslibs.np_datetime import ( + OutOfBoundsDatetime, + OutOfBoundsTimedelta, + astype_overflowsafe, + is_unitless, + py_get_unit_from_dtype, + py_td64_to_tdstruct, +) + +import pandas._testing as tm + + +def test_is_unitless(): + dtype = np.dtype("M8[ns]") + assert not is_unitless(dtype) + + dtype = np.dtype("datetime64") + assert is_unitless(dtype) + + dtype = np.dtype("m8[ns]") + assert not is_unitless(dtype) + + dtype = np.dtype("timedelta64") + assert is_unitless(dtype) + + msg = "dtype must be datetime64 or timedelta64" + with pytest.raises(ValueError, match=msg): + is_unitless(np.dtype(np.int64)) + + msg = "Argument 'dtype' has incorrect type" + with pytest.raises(TypeError, match=msg): + is_unitless("foo") + + +def test_get_unit_from_dtype(): + # datetime64 + assert py_get_unit_from_dtype(np.dtype("M8[Y]")) == NpyDatetimeUnit.NPY_FR_Y.value + assert py_get_unit_from_dtype(np.dtype("M8[M]")) == NpyDatetimeUnit.NPY_FR_M.value + assert py_get_unit_from_dtype(np.dtype("M8[W]")) == NpyDatetimeUnit.NPY_FR_W.value + # B has been deprecated and removed -> no 3 + assert py_get_unit_from_dtype(np.dtype("M8[D]")) == NpyDatetimeUnit.NPY_FR_D.value + assert py_get_unit_from_dtype(np.dtype("M8[h]")) == NpyDatetimeUnit.NPY_FR_h.value + assert py_get_unit_from_dtype(np.dtype("M8[m]")) == NpyDatetimeUnit.NPY_FR_m.value + assert py_get_unit_from_dtype(np.dtype("M8[s]")) == NpyDatetimeUnit.NPY_FR_s.value + assert py_get_unit_from_dtype(np.dtype("M8[ms]")) == NpyDatetimeUnit.NPY_FR_ms.value + assert py_get_unit_from_dtype(np.dtype("M8[us]")) == NpyDatetimeUnit.NPY_FR_us.value + assert py_get_unit_from_dtype(np.dtype("M8[ns]")) == NpyDatetimeUnit.NPY_FR_ns.value + assert py_get_unit_from_dtype(np.dtype("M8[ps]")) == NpyDatetimeUnit.NPY_FR_ps.value + assert py_get_unit_from_dtype(np.dtype("M8[fs]")) == NpyDatetimeUnit.NPY_FR_fs.value + assert py_get_unit_from_dtype(np.dtype("M8[as]")) == NpyDatetimeUnit.NPY_FR_as.value + + # timedelta64 + assert py_get_unit_from_dtype(np.dtype("m8[Y]")) == NpyDatetimeUnit.NPY_FR_Y.value + assert py_get_unit_from_dtype(np.dtype("m8[M]")) == NpyDatetimeUnit.NPY_FR_M.value + assert py_get_unit_from_dtype(np.dtype("m8[W]")) == NpyDatetimeUnit.NPY_FR_W.value + # B has been deprecated and removed -> no 3 + assert py_get_unit_from_dtype(np.dtype("m8[D]")) == NpyDatetimeUnit.NPY_FR_D.value + assert py_get_unit_from_dtype(np.dtype("m8[h]")) == NpyDatetimeUnit.NPY_FR_h.value + assert py_get_unit_from_dtype(np.dtype("m8[m]")) == NpyDatetimeUnit.NPY_FR_m.value + assert py_get_unit_from_dtype(np.dtype("m8[s]")) == NpyDatetimeUnit.NPY_FR_s.value + assert py_get_unit_from_dtype(np.dtype("m8[ms]")) == NpyDatetimeUnit.NPY_FR_ms.value + assert py_get_unit_from_dtype(np.dtype("m8[us]")) == NpyDatetimeUnit.NPY_FR_us.value + assert py_get_unit_from_dtype(np.dtype("m8[ns]")) == NpyDatetimeUnit.NPY_FR_ns.value + assert py_get_unit_from_dtype(np.dtype("m8[ps]")) == NpyDatetimeUnit.NPY_FR_ps.value + assert py_get_unit_from_dtype(np.dtype("m8[fs]")) == NpyDatetimeUnit.NPY_FR_fs.value + assert py_get_unit_from_dtype(np.dtype("m8[as]")) == NpyDatetimeUnit.NPY_FR_as.value + + +def test_td64_to_tdstruct(): + val = 12454636234 # arbitrary value + + res1 = py_td64_to_tdstruct(val, NpyDatetimeUnit.NPY_FR_ns.value) + exp1 = { + "days": 0, + "hrs": 0, + "min": 0, + "sec": 12, + "ms": 454, + "us": 636, + "ns": 234, + "seconds": 12, + "microseconds": 454636, + "nanoseconds": 234, + } + assert res1 == exp1 + + res2 = py_td64_to_tdstruct(val, NpyDatetimeUnit.NPY_FR_us.value) + exp2 = { + "days": 0, + "hrs": 3, + "min": 27, + "sec": 34, + "ms": 636, + "us": 234, + "ns": 0, + "seconds": 12454, + "microseconds": 636234, + "nanoseconds": 0, + } + assert res2 == exp2 + + res3 = py_td64_to_tdstruct(val, NpyDatetimeUnit.NPY_FR_ms.value) + exp3 = { + "days": 144, + "hrs": 3, + "min": 37, + "sec": 16, + "ms": 234, + "us": 0, + "ns": 0, + "seconds": 13036, + "microseconds": 234000, + "nanoseconds": 0, + } + assert res3 == exp3 + + # Note this out of bounds for nanosecond Timedelta + res4 = py_td64_to_tdstruct(val, NpyDatetimeUnit.NPY_FR_s.value) + exp4 = { + "days": 144150, + "hrs": 21, + "min": 10, + "sec": 34, + "ms": 0, + "us": 0, + "ns": 0, + "seconds": 76234, + "microseconds": 0, + "nanoseconds": 0, + } + assert res4 == exp4 + + +class TestAstypeOverflowSafe: + def test_pass_non_dt64_array(self): + # check that we raise, not segfault + arr = np.arange(5) + dtype = np.dtype("M8[ns]") + + msg = ( + "astype_overflowsafe values.dtype and dtype must be either " + "both-datetime64 or both-timedelta64" + ) + with pytest.raises(TypeError, match=msg): + astype_overflowsafe(arr, dtype, copy=True) + + with pytest.raises(TypeError, match=msg): + astype_overflowsafe(arr, dtype, copy=False) + + def test_pass_non_dt64_dtype(self): + # check that we raise, not segfault + arr = np.arange(5, dtype="i8").view("M8[D]") + dtype = np.dtype("m8[ns]") + + msg = ( + "astype_overflowsafe values.dtype and dtype must be either " + "both-datetime64 or both-timedelta64" + ) + with pytest.raises(TypeError, match=msg): + astype_overflowsafe(arr, dtype, copy=True) + + with pytest.raises(TypeError, match=msg): + astype_overflowsafe(arr, dtype, copy=False) + + def test_astype_overflowsafe_dt64(self): + dtype = np.dtype("M8[ns]") + + dt = np.datetime64("2262-04-05", "D") + arr = dt + np.arange(10, dtype="m8[D]") + + # arr.astype silently overflows, so this + wrong = arr.astype(dtype) + roundtrip = wrong.astype(arr.dtype) + assert not (wrong == roundtrip).all() + + msg = "Out of bounds nanosecond timestamp" + with pytest.raises(OutOfBoundsDatetime, match=msg): + astype_overflowsafe(arr, dtype) + + # But converting to microseconds is fine, and we match numpy's results. + dtype2 = np.dtype("M8[us]") + result = astype_overflowsafe(arr, dtype2) + expected = arr.astype(dtype2) + tm.assert_numpy_array_equal(result, expected) + + def test_astype_overflowsafe_td64(self): + dtype = np.dtype("m8[ns]") + + dt = np.datetime64("2262-04-05", "D") + arr = dt + np.arange(10, dtype="m8[D]") + arr = arr.view("m8[D]") + + # arr.astype silently overflows, so this + wrong = arr.astype(dtype) + roundtrip = wrong.astype(arr.dtype) + assert not (wrong == roundtrip).all() + + msg = r"Cannot convert 106752 days to timedelta64\[ns\] without overflow" + with pytest.raises(OutOfBoundsTimedelta, match=msg): + astype_overflowsafe(arr, dtype) + + # But converting to microseconds is fine, and we match numpy's results. + dtype2 = np.dtype("m8[us]") + result = astype_overflowsafe(arr, dtype2) + expected = arr.astype(dtype2) + tm.assert_numpy_array_equal(result, expected) + + def test_astype_overflowsafe_disallow_rounding(self): + arr = np.array([-1500, 1500], dtype="M8[ns]") + dtype = np.dtype("M8[us]") + + msg = "Cannot losslessly cast '-1500 ns' to us" + with pytest.raises(ValueError, match=msg): + astype_overflowsafe(arr, dtype, round_ok=False) + + result = astype_overflowsafe(arr, dtype, round_ok=True) + expected = arr.astype(dtype) + tm.assert_numpy_array_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_npy_units.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_npy_units.py new file mode 100644 index 0000000000000000000000000000000000000000..6d05dc79fbb2cf52688547b672365802463ce6f2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_npy_units.py @@ -0,0 +1,27 @@ +import numpy as np + +from pandas._libs.tslibs.dtypes import abbrev_to_npy_unit +from pandas._libs.tslibs.vectorized import is_date_array_normalized + +# a datetime64 ndarray which *is* normalized +day_arr = np.arange(10, dtype="i8").view("M8[D]") + + +class TestIsDateArrayNormalized: + def test_is_date_array_normalized_day(self): + arr = day_arr + abbrev = "D" + unit = abbrev_to_npy_unit(abbrev) + result = is_date_array_normalized(arr.view("i8"), None, unit) + assert result is True + + def test_is_date_array_normalized_seconds(self): + abbrev = "s" + arr = day_arr.astype(f"M8[{abbrev}]") + unit = abbrev_to_npy_unit(abbrev) + result = is_date_array_normalized(arr.view("i8"), None, unit) + assert result is True + + arr[0] += np.timedelta64(1, abbrev) + result2 = is_date_array_normalized(arr.view("i8"), None, unit) + assert result2 is False diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_parse_iso8601.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_parse_iso8601.py new file mode 100644 index 0000000000000000000000000000000000000000..1992faae2ea6a687f8bd74b4e1e10ba53bb9e901 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_parse_iso8601.py @@ -0,0 +1,119 @@ +from datetime import datetime + +import pytest + +from pandas._libs import tslib + +from pandas import Timestamp + + +@pytest.mark.parametrize( + "date_str, exp", + [ + ("2011-01-02", datetime(2011, 1, 2)), + ("2011-1-2", datetime(2011, 1, 2)), + ("2011-01", datetime(2011, 1, 1)), + ("2011-1", datetime(2011, 1, 1)), + ("2011 01 02", datetime(2011, 1, 2)), + ("2011.01.02", datetime(2011, 1, 2)), + ("2011/01/02", datetime(2011, 1, 2)), + ("2011\\01\\02", datetime(2011, 1, 2)), + ("2013-01-01 05:30:00", datetime(2013, 1, 1, 5, 30)), + ("2013-1-1 5:30:00", datetime(2013, 1, 1, 5, 30)), + ("2013-1-1 5:30:00+01:00", Timestamp(2013, 1, 1, 5, 30, tz="UTC+01:00")), + ], +) +def test_parsers_iso8601(date_str, exp): + # see gh-12060 + # + # Test only the ISO parser - flexibility to + # different separators and leading zero's. + actual = tslib._test_parse_iso8601(date_str) + assert actual == exp + + +@pytest.mark.parametrize( + "date_str", + [ + "2011-01/02", + "2011=11=11", + "201401", + "201111", + "200101", + # Mixed separated and unseparated. + "2005-0101", + "200501-01", + "20010101 12:3456", + "20010101 1234:56", + # HHMMSS must have two digits in + # each component if unseparated. + "20010101 1", + "20010101 123", + "20010101 12345", + "20010101 12345Z", + ], +) +def test_parsers_iso8601_invalid(date_str): + msg = f'Error parsing datetime string "{date_str}"' + + with pytest.raises(ValueError, match=msg): + tslib._test_parse_iso8601(date_str) + + +def test_parsers_iso8601_invalid_offset_invalid(): + date_str = "2001-01-01 12-34-56" + msg = f'Timezone hours offset out of range in datetime string "{date_str}"' + + with pytest.raises(ValueError, match=msg): + tslib._test_parse_iso8601(date_str) + + +def test_parsers_iso8601_leading_space(): + # GH#25895 make sure isoparser doesn't overflow with long input + date_str, expected = ("2013-1-1 5:30:00", datetime(2013, 1, 1, 5, 30)) + actual = tslib._test_parse_iso8601(" " * 200 + date_str) + assert actual == expected + + +@pytest.mark.parametrize( + "date_str, timespec, exp", + [ + ("2023-01-01 00:00:00", "auto", "2023-01-01T00:00:00"), + ("2023-01-01 00:00:00", "seconds", "2023-01-01T00:00:00"), + ("2023-01-01 00:00:00", "milliseconds", "2023-01-01T00:00:00.000"), + ("2023-01-01 00:00:00", "microseconds", "2023-01-01T00:00:00.000000"), + ("2023-01-01 00:00:00", "nanoseconds", "2023-01-01T00:00:00.000000000"), + ("2023-01-01 00:00:00.001", "auto", "2023-01-01T00:00:00.001000"), + ("2023-01-01 00:00:00.001", "seconds", "2023-01-01T00:00:00"), + ("2023-01-01 00:00:00.001", "milliseconds", "2023-01-01T00:00:00.001"), + ("2023-01-01 00:00:00.001", "microseconds", "2023-01-01T00:00:00.001000"), + ("2023-01-01 00:00:00.001", "nanoseconds", "2023-01-01T00:00:00.001000000"), + ("2023-01-01 00:00:00.000001", "auto", "2023-01-01T00:00:00.000001"), + ("2023-01-01 00:00:00.000001", "seconds", "2023-01-01T00:00:00"), + ("2023-01-01 00:00:00.000001", "milliseconds", "2023-01-01T00:00:00.000"), + ("2023-01-01 00:00:00.000001", "microseconds", "2023-01-01T00:00:00.000001"), + ("2023-01-01 00:00:00.000001", "nanoseconds", "2023-01-01T00:00:00.000001000"), + ("2023-01-01 00:00:00.000000001", "auto", "2023-01-01T00:00:00.000000001"), + ("2023-01-01 00:00:00.000000001", "seconds", "2023-01-01T00:00:00"), + ("2023-01-01 00:00:00.000000001", "milliseconds", "2023-01-01T00:00:00.000"), + ("2023-01-01 00:00:00.000000001", "microseconds", "2023-01-01T00:00:00.000000"), + ( + "2023-01-01 00:00:00.000000001", + "nanoseconds", + "2023-01-01T00:00:00.000000001", + ), + ("2023-01-01 00:00:00.000001001", "auto", "2023-01-01T00:00:00.000001001"), + ("2023-01-01 00:00:00.000001001", "seconds", "2023-01-01T00:00:00"), + ("2023-01-01 00:00:00.000001001", "milliseconds", "2023-01-01T00:00:00.000"), + ("2023-01-01 00:00:00.000001001", "microseconds", "2023-01-01T00:00:00.000001"), + ( + "2023-01-01 00:00:00.000001001", + "nanoseconds", + "2023-01-01T00:00:00.000001001", + ), + ], +) +def test_iso8601_formatter(date_str: str, timespec: str, exp: str): + # GH#53020 + ts = Timestamp(date_str) + assert ts.isoformat(timespec=timespec) == exp diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_parsing.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_parsing.py new file mode 100644 index 0000000000000000000000000000000000000000..2a3cc623e48acc4fddc435f5c46ed0bdcbaa16d1 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_parsing.py @@ -0,0 +1,416 @@ +""" +Tests for Timestamp parsing, aimed at pandas/_libs/tslibs/parsing.pyx +""" +from datetime import datetime +import re + +from dateutil.parser import parse as du_parse +from dateutil.tz import tzlocal +from hypothesis import given +import numpy as np +import pytest + +from pandas._libs.tslibs import ( + parsing, + strptime, +) +from pandas._libs.tslibs.parsing import parse_datetime_string_with_reso +from pandas.compat import ( + ISMUSL, + is_platform_arm, + is_platform_windows, +) +import pandas.util._test_decorators as td + +import pandas._testing as tm +from pandas._testing._hypothesis import DATETIME_NO_TZ + + +@pytest.mark.skipif( + is_platform_windows() or ISMUSL or is_platform_arm(), + reason="TZ setting incorrect on Windows and MUSL Linux", +) +def test_parsing_tzlocal_deprecated(): + # GH#50791 + msg = ( + "Parsing 'EST' as tzlocal.*" + "Pass the 'tz' keyword or call tz_localize after construction instead" + ) + dtstr = "Jan 15 2004 03:00 EST" + + with tm.set_timezone("US/Eastern"): + with tm.assert_produces_warning(FutureWarning, match=msg): + res, _ = parse_datetime_string_with_reso(dtstr) + + assert isinstance(res.tzinfo, tzlocal) + + with tm.assert_produces_warning(FutureWarning, match=msg): + res = parsing.py_parse_datetime_string(dtstr) + assert isinstance(res.tzinfo, tzlocal) + + +def test_parse_datetime_string_with_reso(): + (parsed, reso) = parse_datetime_string_with_reso("4Q1984") + (parsed_lower, reso_lower) = parse_datetime_string_with_reso("4q1984") + + assert reso == reso_lower + assert parsed == parsed_lower + + +def test_parse_datetime_string_with_reso_nanosecond_reso(): + # GH#46811 + parsed, reso = parse_datetime_string_with_reso("2022-04-20 09:19:19.123456789") + assert reso == "nanosecond" + + +def test_parse_datetime_string_with_reso_invalid_type(): + # Raise on invalid input, don't just return it + msg = "Argument 'date_string' has incorrect type (expected str, got tuple)" + with pytest.raises(TypeError, match=re.escape(msg)): + parse_datetime_string_with_reso((4, 5)) + + +@pytest.mark.parametrize( + "dashed,normal", [("1988-Q2", "1988Q2"), ("2Q-1988", "2Q1988")] +) +def test_parse_time_quarter_with_dash(dashed, normal): + # see gh-9688 + (parsed_dash, reso_dash) = parse_datetime_string_with_reso(dashed) + (parsed, reso) = parse_datetime_string_with_reso(normal) + + assert parsed_dash == parsed + assert reso_dash == reso + + +@pytest.mark.parametrize("dashed", ["-2Q1992", "2-Q1992", "4-4Q1992"]) +def test_parse_time_quarter_with_dash_error(dashed): + msg = f"Unknown datetime string format, unable to parse: {dashed}" + + with pytest.raises(parsing.DateParseError, match=msg): + parse_datetime_string_with_reso(dashed) + + +@pytest.mark.parametrize( + "date_string,expected", + [ + ("123.1234", False), + ("-50000", False), + ("999", False), + ("m", False), + ("T", False), + ("Mon Sep 16, 2013", True), + ("2012-01-01", True), + ("01/01/2012", True), + ("01012012", True), + ("0101", True), + ("1-1", True), + ], +) +def test_does_not_convert_mixed_integer(date_string, expected): + assert parsing._does_string_look_like_datetime(date_string) is expected + + +@pytest.mark.parametrize( + "date_str,kwargs,msg", + [ + ( + "2013Q5", + {}, + ( + "Incorrect quarterly string is given, " + "quarter must be between 1 and 4: 2013Q5" + ), + ), + # see gh-5418 + ( + "2013Q1", + {"freq": "INVLD-L-DEC-SAT"}, + ( + "Unable to retrieve month information " + "from given freq: INVLD-L-DEC-SAT" + ), + ), + ], +) +def test_parsers_quarterly_with_freq_error(date_str, kwargs, msg): + with pytest.raises(parsing.DateParseError, match=msg): + parsing.parse_datetime_string_with_reso(date_str, **kwargs) + + +@pytest.mark.parametrize( + "date_str,freq,expected", + [ + ("2013Q2", None, datetime(2013, 4, 1)), + ("2013Q2", "Y-APR", datetime(2012, 8, 1)), + ("2013-Q2", "Y-DEC", datetime(2013, 4, 1)), + ], +) +def test_parsers_quarterly_with_freq(date_str, freq, expected): + result, _ = parsing.parse_datetime_string_with_reso(date_str, freq=freq) + assert result == expected + + +@pytest.mark.parametrize( + "date_str", ["2Q 2005", "2Q-200Y", "2Q-200", "22Q2005", "2Q200.", "6Q-20"] +) +def test_parsers_quarter_invalid(date_str): + if date_str == "6Q-20": + msg = ( + "Incorrect quarterly string is given, quarter " + f"must be between 1 and 4: {date_str}" + ) + else: + msg = f"Unknown datetime string format, unable to parse: {date_str}" + + with pytest.raises(ValueError, match=msg): + parsing.parse_datetime_string_with_reso(date_str) + + +@pytest.mark.parametrize( + "date_str,expected", + [("201101", datetime(2011, 1, 1, 0, 0)), ("200005", datetime(2000, 5, 1, 0, 0))], +) +def test_parsers_month_freq(date_str, expected): + result, _ = parsing.parse_datetime_string_with_reso(date_str, freq="ME") + assert result == expected + + +@td.skip_if_not_us_locale +@pytest.mark.parametrize( + "string,fmt", + [ + ("20111230", "%Y%m%d"), + ("201112300000", "%Y%m%d%H%M"), + ("20111230000000", "%Y%m%d%H%M%S"), + ("20111230T00", "%Y%m%dT%H"), + ("20111230T0000", "%Y%m%dT%H%M"), + ("20111230T000000", "%Y%m%dT%H%M%S"), + ("2011-12-30", "%Y-%m-%d"), + ("2011", "%Y"), + ("2011-01", "%Y-%m"), + ("30-12-2011", "%d-%m-%Y"), + ("2011-12-30 00:00:00", "%Y-%m-%d %H:%M:%S"), + ("2011-12-30T00:00:00", "%Y-%m-%dT%H:%M:%S"), + ("2011-12-30T00:00:00UTC", "%Y-%m-%dT%H:%M:%S%Z"), + ("2011-12-30T00:00:00Z", "%Y-%m-%dT%H:%M:%S%z"), + ("2011-12-30T00:00:00+9", "%Y-%m-%dT%H:%M:%S%z"), + ("2011-12-30T00:00:00+09", "%Y-%m-%dT%H:%M:%S%z"), + ("2011-12-30T00:00:00+090", None), + ("2011-12-30T00:00:00+0900", "%Y-%m-%dT%H:%M:%S%z"), + ("2011-12-30T00:00:00-0900", "%Y-%m-%dT%H:%M:%S%z"), + ("2011-12-30T00:00:00+09:00", "%Y-%m-%dT%H:%M:%S%z"), + ("2011-12-30T00:00:00+09:000", None), + ("2011-12-30T00:00:00+9:0", "%Y-%m-%dT%H:%M:%S%z"), + ("2011-12-30T00:00:00+09:", None), + ("2011-12-30T00:00:00.000000UTC", "%Y-%m-%dT%H:%M:%S.%f%Z"), + ("2011-12-30T00:00:00.000000Z", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2011-12-30T00:00:00.000000+9", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2011-12-30T00:00:00.000000+09", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2011-12-30T00:00:00.000000+090", None), + ("2011-12-30T00:00:00.000000+0900", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2011-12-30T00:00:00.000000-0900", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2011-12-30T00:00:00.000000+09:00", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2011-12-30T00:00:00.000000+09:000", None), + ("2011-12-30T00:00:00.000000+9:0", "%Y-%m-%dT%H:%M:%S.%f%z"), + ("2011-12-30T00:00:00.000000+09:", None), + ("2011-12-30 00:00:00.000000", "%Y-%m-%d %H:%M:%S.%f"), + ("Tue 24 Aug 2021 01:30:48", "%a %d %b %Y %H:%M:%S"), + ("Tuesday 24 Aug 2021 01:30:48", "%A %d %b %Y %H:%M:%S"), + ("Tue 24 Aug 2021 01:30:48 AM", "%a %d %b %Y %I:%M:%S %p"), + ("Tuesday 24 Aug 2021 01:30:48 AM", "%A %d %b %Y %I:%M:%S %p"), + ("27.03.2003 14:55:00.000", "%d.%m.%Y %H:%M:%S.%f"), # GH50317 + ], +) +def test_guess_datetime_format_with_parseable_formats(string, fmt): + with tm.maybe_produces_warning( + UserWarning, fmt is not None and re.search(r"%d.*%m", fmt) + ): + result = parsing.guess_datetime_format(string) + assert result == fmt + + +@pytest.mark.parametrize("dayfirst,expected", [(True, "%d/%m/%Y"), (False, "%m/%d/%Y")]) +def test_guess_datetime_format_with_dayfirst(dayfirst, expected): + ambiguous_string = "01/01/2011" + result = parsing.guess_datetime_format(ambiguous_string, dayfirst=dayfirst) + assert result == expected + + +@td.skip_if_not_us_locale +@pytest.mark.parametrize( + "string,fmt", + [ + ("30/Dec/2011", "%d/%b/%Y"), + ("30/December/2011", "%d/%B/%Y"), + ("30/Dec/2011 00:00:00", "%d/%b/%Y %H:%M:%S"), + ], +) +def test_guess_datetime_format_with_locale_specific_formats(string, fmt): + result = parsing.guess_datetime_format(string) + assert result == fmt + + +@pytest.mark.parametrize( + "invalid_dt", + [ + "01/2013", + "12:00:00", + "1/1/1/1", + "this_is_not_a_datetime", + "51a", + "13/2019", + "202001", # YYYYMM isn't ISO8601 + "2020/01", # YYYY/MM isn't ISO8601 either + "87156549591102612381000001219H5", + ], +) +def test_guess_datetime_format_invalid_inputs(invalid_dt): + # A datetime string must include a year, month and a day for it to be + # guessable, in addition to being a string that looks like a datetime. + assert parsing.guess_datetime_format(invalid_dt) is None + + +@pytest.mark.parametrize("invalid_type_dt", [9, datetime(2011, 1, 1)]) +def test_guess_datetime_format_wrong_type_inputs(invalid_type_dt): + # A datetime string must include a year, month and a day for it to be + # guessable, in addition to being a string that looks like a datetime. + with pytest.raises( + TypeError, + match=r"^Argument 'dt_str' has incorrect type \(expected str, got .*\)$", + ): + parsing.guess_datetime_format(invalid_type_dt) + + +@pytest.mark.parametrize( + "string,fmt,dayfirst,warning", + [ + ("2011-1-1", "%Y-%m-%d", False, None), + ("2011-1-1", "%Y-%d-%m", True, None), + ("1/1/2011", "%m/%d/%Y", False, None), + ("1/1/2011", "%d/%m/%Y", True, None), + ("30-1-2011", "%d-%m-%Y", False, UserWarning), + ("30-1-2011", "%d-%m-%Y", True, None), + ("2011-1-1 0:0:0", "%Y-%m-%d %H:%M:%S", False, None), + ("2011-1-1 0:0:0", "%Y-%d-%m %H:%M:%S", True, None), + ("2011-1-3T00:00:0", "%Y-%m-%dT%H:%M:%S", False, None), + ("2011-1-3T00:00:0", "%Y-%d-%mT%H:%M:%S", True, None), + ("2011-1-1 00:00:00", "%Y-%m-%d %H:%M:%S", False, None), + ("2011-1-1 00:00:00", "%Y-%d-%m %H:%M:%S", True, None), + ], +) +def test_guess_datetime_format_no_padding(string, fmt, dayfirst, warning): + # see gh-11142 + msg = ( + rf"Parsing dates in {fmt} format when dayfirst=False \(the default\) " + "was specified. " + "Pass `dayfirst=True` or specify a format to silence this warning." + ) + with tm.assert_produces_warning(warning, match=msg): + result = parsing.guess_datetime_format(string, dayfirst=dayfirst) + assert result == fmt + + +def test_try_parse_dates(): + arr = np.array(["5/1/2000", "6/1/2000", "7/1/2000"], dtype=object) + result = parsing.try_parse_dates(arr, parser=lambda x: du_parse(x, dayfirst=True)) + + expected = np.array([du_parse(d, dayfirst=True) for d in arr]) + tm.assert_numpy_array_equal(result, expected) + + +def test_parse_datetime_string_with_reso_check_instance_type_raise_exception(): + # issue 20684 + msg = "Argument 'date_string' has incorrect type (expected str, got tuple)" + with pytest.raises(TypeError, match=re.escape(msg)): + parse_datetime_string_with_reso((1, 2, 3)) + + result = parse_datetime_string_with_reso("2019") + expected = (datetime(2019, 1, 1), "year") + assert result == expected + + +@pytest.mark.parametrize( + "fmt,expected", + [ + ("%Y %m %d %H:%M:%S", True), + ("%Y/%m/%d %H:%M:%S", True), + (r"%Y\%m\%d %H:%M:%S", True), + ("%Y-%m-%d %H:%M:%S", True), + ("%Y.%m.%d %H:%M:%S", True), + ("%Y%m%d %H:%M:%S", True), + ("%Y-%m-%dT%H:%M:%S", True), + ("%Y-%m-%dT%H:%M:%S%z", True), + ("%Y-%m-%dT%H:%M:%S%Z", False), + ("%Y-%m-%dT%H:%M:%S.%f", True), + ("%Y-%m-%dT%H:%M:%S.%f%z", True), + ("%Y-%m-%dT%H:%M:%S.%f%Z", False), + ("%Y%m%d", True), + ("%Y%m", False), + ("%Y", True), + ("%Y-%m-%d", True), + ("%Y-%m", True), + ], +) +def test_is_iso_format(fmt, expected): + # see gh-41047 + result = strptime._test_format_is_iso(fmt) + assert result == expected + + +@pytest.mark.parametrize( + "input", + [ + "2018-01-01T00:00:00.123456789", + "2018-01-01T00:00:00.123456", + "2018-01-01T00:00:00.123", + ], +) +def test_guess_datetime_format_f(input): + # https://github.com/pandas-dev/pandas/issues/49043 + result = parsing.guess_datetime_format(input) + expected = "%Y-%m-%dT%H:%M:%S.%f" + assert result == expected + + +def _helper_hypothesis_delimited_date(call, date_string, **kwargs): + msg, result = None, None + try: + result = call(date_string, **kwargs) + except ValueError as err: + msg = str(err) + return msg, result + + +@given(DATETIME_NO_TZ) +@pytest.mark.parametrize("delimiter", list(" -./")) +@pytest.mark.parametrize("dayfirst", [True, False]) +@pytest.mark.parametrize( + "date_format", + ["%d %m %Y", "%m %d %Y", "%m %Y", "%Y %m %d", "%y %m %d", "%Y%m%d", "%y%m%d"], +) +def test_hypothesis_delimited_date( + request, date_format, dayfirst, delimiter, test_datetime +): + if date_format == "%m %Y" and delimiter == ".": + request.applymarker( + pytest.mark.xfail( + reason="parse_datetime_string cannot reliably tell whether " + "e.g. %m.%Y is a float or a date", + strict=False, + ) + ) + date_string = test_datetime.strftime(date_format.replace(" ", delimiter)) + + except_out_dateutil, result = _helper_hypothesis_delimited_date( + parsing.py_parse_datetime_string, date_string, dayfirst=dayfirst + ) + except_in_dateutil, expected = _helper_hypothesis_delimited_date( + du_parse, + date_string, + default=datetime(1, 1, 1), + dayfirst=dayfirst, + yearfirst=False, + ) + + assert except_out_dateutil == except_in_dateutil + assert result == expected diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_period.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_period.py new file mode 100644 index 0000000000000000000000000000000000000000..715e2d3da88dbc69fd6a376f21b7bba78a46ca9f --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_period.py @@ -0,0 +1,123 @@ +import numpy as np +import pytest + +from pandas._libs.tslibs import ( + iNaT, + to_offset, +) +from pandas._libs.tslibs.period import ( + extract_ordinals, + get_period_field_arr, + period_asfreq, + period_ordinal, +) + +import pandas._testing as tm + + +def get_freq_code(freqstr: str) -> int: + off = to_offset(freqstr, is_period=True) + # error: "BaseOffset" has no attribute "_period_dtype_code" + code = off._period_dtype_code # type: ignore[attr-defined] + return code + + +@pytest.mark.parametrize( + "freq1,freq2,expected", + [ + ("D", "h", 24), + ("D", "min", 1440), + ("D", "s", 86400), + ("D", "ms", 86400000), + ("D", "us", 86400000000), + ("D", "ns", 86400000000000), + ("h", "min", 60), + ("h", "s", 3600), + ("h", "ms", 3600000), + ("h", "us", 3600000000), + ("h", "ns", 3600000000000), + ("min", "s", 60), + ("min", "ms", 60000), + ("min", "us", 60000000), + ("min", "ns", 60000000000), + ("s", "ms", 1000), + ("s", "us", 1000000), + ("s", "ns", 1000000000), + ("ms", "us", 1000), + ("ms", "ns", 1000000), + ("us", "ns", 1000), + ], +) +def test_intra_day_conversion_factors(freq1, freq2, expected): + assert ( + period_asfreq(1, get_freq_code(freq1), get_freq_code(freq2), False) == expected + ) + + +@pytest.mark.parametrize( + "freq,expected", [("Y", 0), ("M", 0), ("W", 1), ("D", 0), ("B", 0)] +) +def test_period_ordinal_start_values(freq, expected): + # information for Jan. 1, 1970. + assert period_ordinal(1970, 1, 1, 0, 0, 0, 0, 0, get_freq_code(freq)) == expected + + +@pytest.mark.parametrize( + "dt,expected", + [ + ((1970, 1, 4, 0, 0, 0, 0, 0), 1), + ((1970, 1, 5, 0, 0, 0, 0, 0), 2), + ((2013, 10, 6, 0, 0, 0, 0, 0), 2284), + ((2013, 10, 7, 0, 0, 0, 0, 0), 2285), + ], +) +def test_period_ordinal_week(dt, expected): + args = dt + (get_freq_code("W"),) + assert period_ordinal(*args) == expected + + +@pytest.mark.parametrize( + "day,expected", + [ + # Thursday (Oct. 3, 2013). + (3, 11415), + # Friday (Oct. 4, 2013). + (4, 11416), + # Saturday (Oct. 5, 2013). + (5, 11417), + # Sunday (Oct. 6, 2013). + (6, 11417), + # Monday (Oct. 7, 2013). + (7, 11417), + # Tuesday (Oct. 8, 2013). + (8, 11418), + ], +) +def test_period_ordinal_business_day(day, expected): + # 5000 is PeriodDtypeCode for BusinessDay + args = (2013, 10, day, 0, 0, 0, 0, 0, 5000) + assert period_ordinal(*args) == expected + + +class TestExtractOrdinals: + def test_extract_ordinals_raises(self): + # with non-object, make sure we raise TypeError, not segfault + arr = np.arange(5) + freq = to_offset("D") + with pytest.raises(TypeError, match="values must be object-dtype"): + extract_ordinals(arr, freq) + + def test_extract_ordinals_2d(self): + freq = to_offset("D") + arr = np.empty(10, dtype=object) + arr[:] = iNaT + + res = extract_ordinals(arr, freq) + res2 = extract_ordinals(arr.reshape(5, 2), freq) + tm.assert_numpy_array_equal(res, res2.reshape(-1)) + + +def test_get_period_field_array_raises_on_out_of_range(): + msg = "Buffer dtype mismatch, expected 'const int64_t' but got 'double'" + with pytest.raises(ValueError, match=msg): + get_period_field_arr(-1, np.empty(1), 0) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_resolution.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_resolution.py new file mode 100644 index 0000000000000000000000000000000000000000..690962f1daa5eebd047d11297914eb36b494e0dc --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_resolution.py @@ -0,0 +1,57 @@ +import numpy as np +import pytest +import pytz + +from pandas._libs.tslibs import ( + Resolution, + get_resolution, +) +from pandas._libs.tslibs.dtypes import NpyDatetimeUnit + +import pandas._testing as tm + + +def test_get_resolution_nano(): + # don't return the fallback RESO_DAY + arr = np.array([1], dtype=np.int64) + res = get_resolution(arr) + assert res == Resolution.RESO_NS + + +def test_get_resolution_non_nano_data(): + arr = np.array([1], dtype=np.int64) + res = get_resolution(arr, None, NpyDatetimeUnit.NPY_FR_us.value) + assert res == Resolution.RESO_US + + res = get_resolution(arr, pytz.UTC, NpyDatetimeUnit.NPY_FR_us.value) + assert res == Resolution.RESO_US + + +@pytest.mark.parametrize( + "freqstr,expected", + [ + ("Y", "year"), + ("Q", "quarter"), + ("M", "month"), + ("D", "day"), + ("h", "hour"), + ("min", "minute"), + ("s", "second"), + ("ms", "millisecond"), + ("us", "microsecond"), + ("ns", "nanosecond"), + ], +) +def test_get_attrname_from_abbrev(freqstr, expected): + reso = Resolution.get_reso_from_freqstr(freqstr) + assert reso.attr_abbrev == freqstr + assert reso.attrname == expected + + +@pytest.mark.parametrize("freq", ["A", "H", "T", "S", "L", "U", "N"]) +def test_units_A_H_T_S_L_U_N_deprecated_from_attrname_to_abbrevs(freq): + # GH#52536 + msg = f"'{freq}' is deprecated and will be removed in a future version." + + with tm.assert_produces_warning(FutureWarning, match=msg): + Resolution.get_reso_from_freqstr(freq) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_strptime.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_strptime.py new file mode 100644 index 0000000000000000000000000000000000000000..d726006b03f6d43cb94a91518daabb2b29b757e0 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_strptime.py @@ -0,0 +1,110 @@ +from datetime import ( + datetime, + timezone, +) + +import numpy as np +import pytest + +from pandas._libs.tslibs.dtypes import NpyDatetimeUnit +from pandas._libs.tslibs.strptime import array_strptime + +from pandas import ( + NaT, + Timestamp, +) +import pandas._testing as tm + +creso_infer = NpyDatetimeUnit.NPY_FR_GENERIC.value + + +class TestArrayStrptimeResolutionInference: + def test_array_strptime_resolution_all_nat(self): + arr = np.array([NaT, np.nan], dtype=object) + + fmt = "%Y-%m-%d %H:%M:%S" + res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer) + assert res.dtype == "M8[s]" + + res, _ = array_strptime(arr, fmt=fmt, utc=True, creso=creso_infer) + assert res.dtype == "M8[s]" + + @pytest.mark.parametrize("tz", [None, timezone.utc]) + def test_array_strptime_resolution_inference_homogeneous_strings(self, tz): + dt = datetime(2016, 1, 2, 3, 4, 5, 678900, tzinfo=tz) + + fmt = "%Y-%m-%d %H:%M:%S" + dtstr = dt.strftime(fmt) + arr = np.array([dtstr] * 3, dtype=object) + expected = np.array([dt.replace(tzinfo=None)] * 3, dtype="M8[s]") + + res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer) + tm.assert_numpy_array_equal(res, expected) + + fmt = "%Y-%m-%d %H:%M:%S.%f" + dtstr = dt.strftime(fmt) + arr = np.array([dtstr] * 3, dtype=object) + expected = np.array([dt.replace(tzinfo=None)] * 3, dtype="M8[us]") + + res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer) + tm.assert_numpy_array_equal(res, expected) + + fmt = "ISO8601" + res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer) + tm.assert_numpy_array_equal(res, expected) + + @pytest.mark.parametrize("tz", [None, timezone.utc]) + def test_array_strptime_resolution_mixed(self, tz): + dt = datetime(2016, 1, 2, 3, 4, 5, 678900, tzinfo=tz) + + ts = Timestamp(dt).as_unit("ns") + + arr = np.array([dt, ts], dtype=object) + expected = np.array( + [Timestamp(dt).as_unit("ns").asm8, ts.asm8], + dtype="M8[ns]", + ) + + fmt = "%Y-%m-%d %H:%M:%S" + res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer) + tm.assert_numpy_array_equal(res, expected) + + fmt = "ISO8601" + res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer) + tm.assert_numpy_array_equal(res, expected) + + def test_array_strptime_resolution_todaynow(self): + # specifically case where today/now is the *first* item + vals = np.array(["today", np.datetime64("2017-01-01", "us")], dtype=object) + + now = Timestamp("now").asm8 + res, _ = array_strptime(vals, fmt="%Y-%m-%d", utc=False, creso=creso_infer) + res2, _ = array_strptime( + vals[::-1], fmt="%Y-%m-%d", utc=False, creso=creso_infer + ) + + # 1s is an arbitrary cutoff for call overhead; in local testing the + # actual difference is about 250us + tolerance = np.timedelta64(1, "s") + + assert res.dtype == "M8[us]" + assert abs(res[0] - now) < tolerance + assert res[1] == vals[1] + + assert res2.dtype == "M8[us]" + assert abs(res2[1] - now) < tolerance * 2 + assert res2[0] == vals[1] + + def test_array_strptime_str_outside_nano_range(self): + vals = np.array(["2401-09-15"], dtype=object) + expected = np.array(["2401-09-15"], dtype="M8[s]") + fmt = "ISO8601" + res, _ = array_strptime(vals, fmt=fmt, creso=creso_infer) + tm.assert_numpy_array_equal(res, expected) + + # non-iso -> different path + vals2 = np.array(["Sep 15, 2401"], dtype=object) + expected2 = np.array(["2401-09-15"], dtype="M8[s]") + fmt2 = "%b %d, %Y" + res2, _ = array_strptime(vals2, fmt=fmt2, creso=creso_infer) + tm.assert_numpy_array_equal(res2, expected2) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_timedeltas.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_timedeltas.py new file mode 100644 index 0000000000000000000000000000000000000000..4784a6d0d600dcc77e359fb3d7d56301f78270d2 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_timedeltas.py @@ -0,0 +1,149 @@ +import re + +import numpy as np +import pytest + +from pandas._libs.tslibs.timedeltas import ( + array_to_timedelta64, + delta_to_nanoseconds, + ints_to_pytimedelta, +) + +from pandas import ( + Timedelta, + offsets, +) +import pandas._testing as tm + + +@pytest.mark.parametrize( + "obj,expected", + [ + (np.timedelta64(14, "D"), 14 * 24 * 3600 * 1e9), + (Timedelta(minutes=-7), -7 * 60 * 1e9), + (Timedelta(minutes=-7).to_pytimedelta(), -7 * 60 * 1e9), + (Timedelta(seconds=1234e-9), 1234), # GH43764, GH40946 + ( + Timedelta(seconds=1e-9, milliseconds=1e-5, microseconds=1e-1), + 111, + ), # GH43764 + ( + Timedelta(days=1, seconds=1e-9, milliseconds=1e-5, microseconds=1e-1), + 24 * 3600e9 + 111, + ), # GH43764 + (offsets.Nano(125), 125), + ], +) +def test_delta_to_nanoseconds(obj, expected): + result = delta_to_nanoseconds(obj) + assert result == expected + + +def test_delta_to_nanoseconds_error(): + obj = np.array([123456789], dtype="m8[ns]") + + with pytest.raises(TypeError, match=""): + delta_to_nanoseconds(obj) + + with pytest.raises(TypeError, match="float"): + delta_to_nanoseconds(1.5) + with pytest.raises(TypeError, match="int"): + delta_to_nanoseconds(1) + with pytest.raises(TypeError, match="int"): + delta_to_nanoseconds(np.int64(2)) + with pytest.raises(TypeError, match="int"): + delta_to_nanoseconds(np.int32(3)) + + +def test_delta_to_nanoseconds_td64_MY_raises(): + msg = ( + "delta_to_nanoseconds does not support Y or M units, " + "as their duration in nanoseconds is ambiguous" + ) + + td = np.timedelta64(1234, "Y") + + with pytest.raises(ValueError, match=msg): + delta_to_nanoseconds(td) + + td = np.timedelta64(1234, "M") + + with pytest.raises(ValueError, match=msg): + delta_to_nanoseconds(td) + + +@pytest.mark.parametrize("unit", ["Y", "M"]) +def test_unsupported_td64_unit_raises(unit): + # GH 52806 + with pytest.raises( + ValueError, + match=f"Unit {unit} is not supported. " + "Only unambiguous timedelta values durations are supported. " + "Allowed units are 'W', 'D', 'h', 'm', 's', 'ms', 'us', 'ns'", + ): + Timedelta(np.timedelta64(1, unit)) + + +def test_huge_nanoseconds_overflow(): + # GH 32402 + assert delta_to_nanoseconds(Timedelta(1e10)) == 1e10 + assert delta_to_nanoseconds(Timedelta(nanoseconds=1e10)) == 1e10 + + +@pytest.mark.parametrize( + "kwargs", [{"Seconds": 1}, {"seconds": 1, "Nanoseconds": 1}, {"Foo": 2}] +) +def test_kwarg_assertion(kwargs): + err_message = ( + "cannot construct a Timedelta from the passed arguments, " + "allowed keywords are " + "[weeks, days, hours, minutes, seconds, " + "milliseconds, microseconds, nanoseconds]" + ) + + with pytest.raises(ValueError, match=re.escape(err_message)): + Timedelta(**kwargs) + + +class TestArrayToTimedelta64: + def test_array_to_timedelta64_string_with_unit_2d_raises(self): + # check the 'unit is not None and errors != "coerce"' path + # in array_to_timedelta64 raises correctly with 2D values + values = np.array([["1", 2], [3, "4"]], dtype=object) + with pytest.raises(ValueError, match="unit must not be specified"): + array_to_timedelta64(values, unit="s") + + def test_array_to_timedelta64_non_object_raises(self): + # check we raise, not segfault + values = np.arange(5) + + msg = "'values' must have object dtype" + with pytest.raises(TypeError, match=msg): + array_to_timedelta64(values) + + +@pytest.mark.parametrize("unit", ["s", "ms", "us"]) +def test_ints_to_pytimedelta(unit): + # tests for non-nanosecond cases + arr = np.arange(6, dtype=np.int64).view(f"m8[{unit}]") + + res = ints_to_pytimedelta(arr, box=False) + # For non-nanosecond, .astype(object) gives pytimedelta objects + # instead of integers + expected = arr.astype(object) + tm.assert_numpy_array_equal(res, expected) + + res = ints_to_pytimedelta(arr, box=True) + expected = np.array([Timedelta(x) for x in arr], dtype=object) + tm.assert_numpy_array_equal(res, expected) + + +@pytest.mark.parametrize("unit", ["Y", "M", "ps", "fs", "as"]) +def test_ints_to_pytimedelta_unsupported(unit): + arr = np.arange(6, dtype=np.int64).view(f"m8[{unit}]") + + with pytest.raises(NotImplementedError, match=r"\d{1,2}"): + ints_to_pytimedelta(arr, box=False) + msg = "Only resolutions 's', 'ms', 'us', 'ns' are supported" + with pytest.raises(NotImplementedError, match=msg): + ints_to_pytimedelta(arr, box=True) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_timezones.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_timezones.py new file mode 100644 index 0000000000000000000000000000000000000000..28e4889983fb964167dd74623c8e4c4585c99a96 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_timezones.py @@ -0,0 +1,168 @@ +from datetime import ( + datetime, + timedelta, + timezone, +) + +import dateutil.tz +import pytest +import pytz + +from pandas._libs.tslibs import ( + conversion, + timezones, +) +from pandas.compat import is_platform_windows + +from pandas import Timestamp + + +def test_is_utc(utc_fixture): + tz = timezones.maybe_get_tz(utc_fixture) + assert timezones.is_utc(tz) + + +@pytest.mark.parametrize("tz_name", list(pytz.common_timezones)) +def test_cache_keys_are_distinct_for_pytz_vs_dateutil(tz_name): + tz_p = timezones.maybe_get_tz(tz_name) + tz_d = timezones.maybe_get_tz("dateutil/" + tz_name) + + if tz_d is None: + pytest.skip(tz_name + ": dateutil does not know about this one") + + if not (tz_name == "UTC" and is_platform_windows()): + # they both end up as tzwin("UTC") on windows + assert timezones._p_tz_cache_key(tz_p) != timezones._p_tz_cache_key(tz_d) + + +def test_tzlocal_repr(): + # see gh-13583 + ts = Timestamp("2011-01-01", tz=dateutil.tz.tzlocal()) + assert ts.tz == dateutil.tz.tzlocal() + assert "tz='tzlocal()')" in repr(ts) + + +def test_tzlocal_maybe_get_tz(): + # see gh-13583 + tz = timezones.maybe_get_tz("tzlocal()") + assert tz == dateutil.tz.tzlocal() + + +def test_tzlocal_offset(): + # see gh-13583 + # + # Get offset using normal datetime for test. + ts = Timestamp("2011-01-01", tz=dateutil.tz.tzlocal()) + + offset = dateutil.tz.tzlocal().utcoffset(datetime(2011, 1, 1)) + offset = offset.total_seconds() + + assert ts._value + offset == Timestamp("2011-01-01")._value + + +def test_tzlocal_is_not_utc(): + # even if the machine running the test is localized to UTC + tz = dateutil.tz.tzlocal() + assert not timezones.is_utc(tz) + + assert not timezones.tz_compare(tz, dateutil.tz.tzutc()) + + +def test_tz_compare_utc(utc_fixture, utc_fixture2): + tz = timezones.maybe_get_tz(utc_fixture) + tz2 = timezones.maybe_get_tz(utc_fixture2) + assert timezones.tz_compare(tz, tz2) + + +@pytest.fixture( + params=[ + (pytz.timezone("US/Eastern"), lambda tz, x: tz.localize(x)), + (dateutil.tz.gettz("US/Eastern"), lambda tz, x: x.replace(tzinfo=tz)), + ] +) +def infer_setup(request): + eastern, localize = request.param + + start_naive = datetime(2001, 1, 1) + end_naive = datetime(2009, 1, 1) + + start = localize(eastern, start_naive) + end = localize(eastern, end_naive) + + return eastern, localize, start, end, start_naive, end_naive + + +def test_infer_tz_compat(infer_setup): + eastern, _, start, end, start_naive, end_naive = infer_setup + + assert ( + timezones.infer_tzinfo(start, end) + is conversion.localize_pydatetime(start_naive, eastern).tzinfo + ) + assert ( + timezones.infer_tzinfo(start, None) + is conversion.localize_pydatetime(start_naive, eastern).tzinfo + ) + assert ( + timezones.infer_tzinfo(None, end) + is conversion.localize_pydatetime(end_naive, eastern).tzinfo + ) + + +def test_infer_tz_utc_localize(infer_setup): + _, _, start, end, start_naive, end_naive = infer_setup + utc = pytz.utc + + start = utc.localize(start_naive) + end = utc.localize(end_naive) + + assert timezones.infer_tzinfo(start, end) is utc + + +@pytest.mark.parametrize("ordered", [True, False]) +def test_infer_tz_mismatch(infer_setup, ordered): + eastern, _, _, _, start_naive, end_naive = infer_setup + msg = "Inputs must both have the same timezone" + + utc = pytz.utc + start = utc.localize(start_naive) + end = conversion.localize_pydatetime(end_naive, eastern) + + args = (start, end) if ordered else (end, start) + + with pytest.raises(AssertionError, match=msg): + timezones.infer_tzinfo(*args) + + +def test_maybe_get_tz_invalid_types(): + with pytest.raises(TypeError, match=""): + timezones.maybe_get_tz(44.0) + + with pytest.raises(TypeError, match=""): + timezones.maybe_get_tz(pytz) + + msg = "" + with pytest.raises(TypeError, match=msg): + timezones.maybe_get_tz(Timestamp("2021-01-01", tz="UTC")) + + +def test_maybe_get_tz_offset_only(): + # see gh-36004 + + # timezone.utc + tz = timezones.maybe_get_tz(timezone.utc) + assert tz == timezone(timedelta(hours=0, minutes=0)) + + # without UTC+- prefix + tz = timezones.maybe_get_tz("+01:15") + assert tz == timezone(timedelta(hours=1, minutes=15)) + + tz = timezones.maybe_get_tz("-01:15") + assert tz == timezone(-timedelta(hours=1, minutes=15)) + + # with UTC+- prefix + tz = timezones.maybe_get_tz("UTC+02:45") + assert tz == timezone(timedelta(hours=2, minutes=45)) + + tz = timezones.maybe_get_tz("UTC-02:45") + assert tz == timezone(-timedelta(hours=2, minutes=45)) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_to_offset.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_to_offset.py new file mode 100644 index 0000000000000000000000000000000000000000..8ca55648f3780e6f31621f7b5cfdcd1435b1a231 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_to_offset.py @@ -0,0 +1,219 @@ +import re + +import pytest + +from pandas._libs.tslibs import ( + Timedelta, + offsets, + to_offset, +) + + +@pytest.mark.parametrize( + "freq_input,expected", + [ + (to_offset("10us"), offsets.Micro(10)), + (offsets.Hour(), offsets.Hour()), + ("2h30min", offsets.Minute(150)), + ("2h 30min", offsets.Minute(150)), + ("2h30min15s", offsets.Second(150 * 60 + 15)), + ("2h 60min", offsets.Hour(3)), + ("2h 20.5min", offsets.Second(8430)), + ("1.5min", offsets.Second(90)), + ("0.5s", offsets.Milli(500)), + ("15ms500us", offsets.Micro(15500)), + ("10s75ms", offsets.Milli(10075)), + ("1s0.25ms", offsets.Micro(1000250)), + ("1s0.25ms", offsets.Micro(1000250)), + ("2800ns", offsets.Nano(2800)), + ("2SME", offsets.SemiMonthEnd(2)), + ("2SME-16", offsets.SemiMonthEnd(2, day_of_month=16)), + ("2SMS-14", offsets.SemiMonthBegin(2, day_of_month=14)), + ("2SMS-15", offsets.SemiMonthBegin(2)), + ], +) +def test_to_offset(freq_input, expected): + result = to_offset(freq_input) + assert result == expected + + +@pytest.mark.parametrize( + "freqstr,expected", [("-1s", -1), ("-2SME", -2), ("-1SMS", -1), ("-5min10s", -310)] +) +def test_to_offset_negative(freqstr, expected): + result = to_offset(freqstr) + assert result.n == expected + + +@pytest.mark.filterwarnings("ignore:.*'m' is deprecated.*:FutureWarning") +@pytest.mark.parametrize( + "freqstr", + [ + "2h20m", + "us1", + "-us", + "3us1", + "-2-3us", + "-2D:3h", + "1.5.0s", + "2SMS-15-15", + "2SMS-15D", + "100foo", + # Invalid leading +/- signs. + "+-1d", + "-+1h", + "+1", + "-7", + "+d", + "-m", + # Invalid shortcut anchors. + "SME-0", + "SME-28", + "SME-29", + "SME-FOO", + "BSM", + "SME--1", + "SMS-1", + "SMS-28", + "SMS-30", + "SMS-BAR", + "SMS-BYR", + "BSMS", + "SMS--2", + ], +) +def test_to_offset_invalid(freqstr): + # see gh-13930 + + # We escape string because some of our + # inputs contain regex special characters. + msg = re.escape(f"Invalid frequency: {freqstr}") + with pytest.raises(ValueError, match=msg): + to_offset(freqstr) + + +def test_to_offset_no_evaluate(): + msg = str(("", "")) + with pytest.raises(TypeError, match=msg): + to_offset(("", "")) + + +def test_to_offset_tuple_unsupported(): + with pytest.raises(TypeError, match="pass as a string instead"): + to_offset((5, "T")) + + +@pytest.mark.parametrize( + "freqstr,expected", + [ + ("2D 3h", offsets.Hour(51)), + ("2 D3 h", offsets.Hour(51)), + ("2 D 3 h", offsets.Hour(51)), + (" 2 D 3 h ", offsets.Hour(51)), + (" h ", offsets.Hour()), + (" 3 h ", offsets.Hour(3)), + ], +) +def test_to_offset_whitespace(freqstr, expected): + result = to_offset(freqstr) + assert result == expected + + +@pytest.mark.parametrize( + "freqstr,expected", [("00h 00min 01s", 1), ("-00h 03min 14s", -194)] +) +def test_to_offset_leading_zero(freqstr, expected): + result = to_offset(freqstr) + assert result.n == expected + + +@pytest.mark.parametrize("freqstr,expected", [("+1d", 1), ("+2h30min", 150)]) +def test_to_offset_leading_plus(freqstr, expected): + result = to_offset(freqstr) + assert result.n == expected + + +@pytest.mark.parametrize( + "kwargs,expected", + [ + ({"days": 1, "seconds": 1}, offsets.Second(86401)), + ({"days": -1, "seconds": 1}, offsets.Second(-86399)), + ({"hours": 1, "minutes": 10}, offsets.Minute(70)), + ({"hours": 1, "minutes": -10}, offsets.Minute(50)), + ({"weeks": 1}, offsets.Day(7)), + ({"hours": 1}, offsets.Hour(1)), + ({"hours": 1}, to_offset("60min")), + ({"microseconds": 1}, offsets.Micro(1)), + ({"microseconds": 0}, offsets.Nano(0)), + ], +) +def test_to_offset_pd_timedelta(kwargs, expected): + # see gh-9064 + td = Timedelta(**kwargs) + result = to_offset(td) + assert result == expected + + +@pytest.mark.parametrize( + "shortcut,expected", + [ + ("W", offsets.Week(weekday=6)), + ("W-SUN", offsets.Week(weekday=6)), + ("QE", offsets.QuarterEnd(startingMonth=12)), + ("QE-DEC", offsets.QuarterEnd(startingMonth=12)), + ("QE-MAY", offsets.QuarterEnd(startingMonth=5)), + ("SME", offsets.SemiMonthEnd(day_of_month=15)), + ("SME-15", offsets.SemiMonthEnd(day_of_month=15)), + ("SME-1", offsets.SemiMonthEnd(day_of_month=1)), + ("SME-27", offsets.SemiMonthEnd(day_of_month=27)), + ("SMS-2", offsets.SemiMonthBegin(day_of_month=2)), + ("SMS-27", offsets.SemiMonthBegin(day_of_month=27)), + ], +) +def test_anchored_shortcuts(shortcut, expected): + result = to_offset(shortcut) + assert result == expected + + +@pytest.mark.parametrize( + "freq_depr", + [ + "2ye-mar", + "2ys", + "2qe", + "2qs-feb", + "2bqs", + "2sms", + "2bms", + "2cbme", + "2me", + "2w", + ], +) +def test_to_offset_lowercase_frequency_deprecated(freq_depr): + # GH#54939 + depr_msg = f"'{freq_depr[1:]}' is deprecated and will be removed in a " + f"future version, please use '{freq_depr.upper()[1:]}' instead." + + with pytest.raises(FutureWarning, match=depr_msg): + to_offset(freq_depr) + + +@pytest.mark.parametrize( + "freq_depr", + [ + "2H", + "2BH", + "2MIN", + "2S", + "2Us", + "2NS", + ], +) +def test_to_offset_uppercase_frequency_deprecated(freq_depr): + # GH#54939 + depr_msg = f"'{freq_depr[1:]}' is deprecated and will be removed in a " + f"future version, please use '{freq_depr.lower()[1:]}' instead." + + with pytest.raises(FutureWarning, match=depr_msg): + to_offset(freq_depr) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_tzconversion.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_tzconversion.py new file mode 100644 index 0000000000000000000000000000000000000000..c1a56ffb71b020df338721e44d56d7e03479fef6 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/tslibs/test_tzconversion.py @@ -0,0 +1,23 @@ +import numpy as np +import pytest +import pytz + +from pandas._libs.tslibs.tzconversion import tz_localize_to_utc + + +class TestTZLocalizeToUTC: + def test_tz_localize_to_utc_ambiguous_infer(self): + # val is a timestamp that is ambiguous when localized to US/Eastern + val = 1_320_541_200_000_000_000 + vals = np.array([val, val - 1, val], dtype=np.int64) + + with pytest.raises(pytz.AmbiguousTimeError, match="2011-11-06 01:00:00"): + tz_localize_to_utc(vals, pytz.timezone("US/Eastern"), ambiguous="infer") + + with pytest.raises(pytz.AmbiguousTimeError, match="are no repeated times"): + tz_localize_to_utc(vals[:1], pytz.timezone("US/Eastern"), ambiguous="infer") + + vals[1] += 1 + msg = "There are 2 dst switches when there should only be 1" + with pytest.raises(pytz.AmbiguousTimeError, match=msg): + tz_localize_to_utc(vals, pytz.timezone("US/Eastern"), ambiguous="infer") diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/conftest.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/conftest.py new file mode 100644 index 0000000000000000000000000000000000000000..b68bcc93431d015a5b9bdc47bdd7e46dd531b703 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/conftest.py @@ -0,0 +1,26 @@ +import pytest + + +@pytest.fixture(params=[True, False]) +def check_dtype(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def check_exact(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def check_index_type(request): + return request.param + + +@pytest.fixture(params=[0.5e-3, 0.5e-5]) +def rtol(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def check_categorical(request): + return request.param diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_almost_equal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_almost_equal.py new file mode 100644 index 0000000000000000000000000000000000000000..4e692084f7352f873b8c7354e7651b432058a1a5 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_almost_equal.py @@ -0,0 +1,586 @@ +import numpy as np +import pytest + +from pandas import ( + NA, + DataFrame, + Index, + NaT, + Series, + Timestamp, +) +import pandas._testing as tm + + +def _assert_almost_equal_both(a, b, **kwargs): + """ + Check that two objects are approximately equal. + + This check is performed commutatively. + + Parameters + ---------- + a : object + The first object to compare. + b : object + The second object to compare. + **kwargs + The arguments passed to `tm.assert_almost_equal`. + """ + tm.assert_almost_equal(a, b, **kwargs) + tm.assert_almost_equal(b, a, **kwargs) + + +def _assert_not_almost_equal(a, b, **kwargs): + """ + Check that two objects are not approximately equal. + + Parameters + ---------- + a : object + The first object to compare. + b : object + The second object to compare. + **kwargs + The arguments passed to `tm.assert_almost_equal`. + """ + try: + tm.assert_almost_equal(a, b, **kwargs) + msg = f"{a} and {b} were approximately equal when they shouldn't have been" + pytest.fail(reason=msg) + except AssertionError: + pass + + +def _assert_not_almost_equal_both(a, b, **kwargs): + """ + Check that two objects are not approximately equal. + + This check is performed commutatively. + + Parameters + ---------- + a : object + The first object to compare. + b : object + The second object to compare. + **kwargs + The arguments passed to `tm.assert_almost_equal`. + """ + _assert_not_almost_equal(a, b, **kwargs) + _assert_not_almost_equal(b, a, **kwargs) + + +@pytest.mark.parametrize( + "a,b", + [ + (1.1, 1.1), + (1.1, 1.100001), + (np.int16(1), 1.000001), + (np.float64(1.1), 1.1), + (np.uint32(5), 5), + ], +) +def test_assert_almost_equal_numbers(a, b): + _assert_almost_equal_both(a, b) + + +@pytest.mark.parametrize( + "a,b", + [ + (1.1, 1), + (1.1, True), + (1, 2), + (1.0001, np.int16(1)), + # The following two examples are not "almost equal" due to tol. + (0.1, 0.1001), + (0.0011, 0.0012), + ], +) +def test_assert_not_almost_equal_numbers(a, b): + _assert_not_almost_equal_both(a, b) + + +@pytest.mark.parametrize( + "a,b", + [ + (1.1, 1.1), + (1.1, 1.100001), + (1.1, 1.1001), + (0.000001, 0.000005), + (1000.0, 1000.0005), + # Testing this example, as per #13357 + (0.000011, 0.000012), + ], +) +def test_assert_almost_equal_numbers_atol(a, b): + # Equivalent to the deprecated check_less_precise=True, enforced in 2.0 + _assert_almost_equal_both(a, b, rtol=0.5e-3, atol=0.5e-3) + + +@pytest.mark.parametrize("a,b", [(1.1, 1.11), (0.1, 0.101), (0.000011, 0.001012)]) +def test_assert_not_almost_equal_numbers_atol(a, b): + _assert_not_almost_equal_both(a, b, atol=1e-3) + + +@pytest.mark.parametrize( + "a,b", + [ + (1.1, 1.1), + (1.1, 1.100001), + (1.1, 1.1001), + (1000.0, 1000.0005), + (1.1, 1.11), + (0.1, 0.101), + ], +) +def test_assert_almost_equal_numbers_rtol(a, b): + _assert_almost_equal_both(a, b, rtol=0.05) + + +@pytest.mark.parametrize("a,b", [(0.000011, 0.000012), (0.000001, 0.000005)]) +def test_assert_not_almost_equal_numbers_rtol(a, b): + _assert_not_almost_equal_both(a, b, rtol=0.05) + + +@pytest.mark.parametrize( + "a,b,rtol", + [ + (1.00001, 1.00005, 0.001), + (-0.908356 + 0.2j, -0.908358 + 0.2j, 1e-3), + (0.1 + 1.009j, 0.1 + 1.006j, 0.1), + (0.1001 + 2.0j, 0.1 + 2.001j, 0.01), + ], +) +def test_assert_almost_equal_complex_numbers(a, b, rtol): + _assert_almost_equal_both(a, b, rtol=rtol) + _assert_almost_equal_both(np.complex64(a), np.complex64(b), rtol=rtol) + _assert_almost_equal_both(np.complex128(a), np.complex128(b), rtol=rtol) + + +@pytest.mark.parametrize( + "a,b,rtol", + [ + (0.58310768, 0.58330768, 1e-7), + (-0.908 + 0.2j, -0.978 + 0.2j, 0.001), + (0.1 + 1j, 0.1 + 2j, 0.01), + (-0.132 + 1.001j, -0.132 + 1.005j, 1e-5), + (0.58310768j, 0.58330768j, 1e-9), + ], +) +def test_assert_not_almost_equal_complex_numbers(a, b, rtol): + _assert_not_almost_equal_both(a, b, rtol=rtol) + _assert_not_almost_equal_both(np.complex64(a), np.complex64(b), rtol=rtol) + _assert_not_almost_equal_both(np.complex128(a), np.complex128(b), rtol=rtol) + + +@pytest.mark.parametrize("a,b", [(0, 0), (0, 0.0), (0, np.float64(0)), (0.00000001, 0)]) +def test_assert_almost_equal_numbers_with_zeros(a, b): + _assert_almost_equal_both(a, b) + + +@pytest.mark.parametrize("a,b", [(0.001, 0), (1, 0)]) +def test_assert_not_almost_equal_numbers_with_zeros(a, b): + _assert_not_almost_equal_both(a, b) + + +@pytest.mark.parametrize("a,b", [(1, "abc"), (1, [1]), (1, object())]) +def test_assert_not_almost_equal_numbers_with_mixed(a, b): + _assert_not_almost_equal_both(a, b) + + +@pytest.mark.parametrize( + "left_dtype", ["M8[ns]", "m8[ns]", "float64", "int64", "object"] +) +@pytest.mark.parametrize( + "right_dtype", ["M8[ns]", "m8[ns]", "float64", "int64", "object"] +) +def test_assert_almost_equal_edge_case_ndarrays(left_dtype, right_dtype): + # Empty compare. + _assert_almost_equal_both( + np.array([], dtype=left_dtype), + np.array([], dtype=right_dtype), + check_dtype=False, + ) + + +def test_assert_almost_equal_sets(): + # GH#51727 + _assert_almost_equal_both({1, 2, 3}, {1, 2, 3}) + + +def test_assert_almost_not_equal_sets(): + # GH#51727 + msg = r"{1, 2, 3} != {1, 2, 4}" + with pytest.raises(AssertionError, match=msg): + _assert_almost_equal_both({1, 2, 3}, {1, 2, 4}) + + +def test_assert_almost_equal_dicts(): + _assert_almost_equal_both({"a": 1, "b": 2}, {"a": 1, "b": 2}) + + +@pytest.mark.parametrize( + "a,b", + [ + ({"a": 1, "b": 2}, {"a": 1, "b": 3}), + ({"a": 1, "b": 2}, {"a": 1, "b": 2, "c": 3}), + ({"a": 1}, 1), + ({"a": 1}, "abc"), + ({"a": 1}, [1]), + ], +) +def test_assert_not_almost_equal_dicts(a, b): + _assert_not_almost_equal_both(a, b) + + +@pytest.mark.parametrize("val", [1, 2]) +def test_assert_almost_equal_dict_like_object(val): + dict_val = 1 + real_dict = {"a": val} + + class DictLikeObj: + def keys(self): + return ("a",) + + def __getitem__(self, item): + if item == "a": + return dict_val + + func = ( + _assert_almost_equal_both if val == dict_val else _assert_not_almost_equal_both + ) + func(real_dict, DictLikeObj(), check_dtype=False) + + +def test_assert_almost_equal_strings(): + _assert_almost_equal_both("abc", "abc") + + +@pytest.mark.parametrize( + "a,b", [("abc", "abcd"), ("abc", "abd"), ("abc", 1), ("abc", [1])] +) +def test_assert_not_almost_equal_strings(a, b): + _assert_not_almost_equal_both(a, b) + + +@pytest.mark.parametrize( + "a,b", [([1, 2, 3], [1, 2, 3]), (np.array([1, 2, 3]), np.array([1, 2, 3]))] +) +def test_assert_almost_equal_iterables(a, b): + _assert_almost_equal_both(a, b) + + +@pytest.mark.parametrize( + "a,b", + [ + # Class is different. + (np.array([1, 2, 3]), [1, 2, 3]), + # Dtype is different. + (np.array([1, 2, 3]), np.array([1.0, 2.0, 3.0])), + # Can't compare generators. + (iter([1, 2, 3]), [1, 2, 3]), + ([1, 2, 3], [1, 2, 4]), + ([1, 2, 3], [1, 2, 3, 4]), + ([1, 2, 3], 1), + ], +) +def test_assert_not_almost_equal_iterables(a, b): + _assert_not_almost_equal(a, b) + + +def test_assert_almost_equal_null(): + _assert_almost_equal_both(None, None) + + +@pytest.mark.parametrize("a,b", [(None, np.nan), (None, 0), (np.nan, 0)]) +def test_assert_not_almost_equal_null(a, b): + _assert_not_almost_equal(a, b) + + +@pytest.mark.parametrize( + "a,b", + [ + (np.inf, np.inf), + (np.inf, float("inf")), + (np.array([np.inf, np.nan, -np.inf]), np.array([np.inf, np.nan, -np.inf])), + ], +) +def test_assert_almost_equal_inf(a, b): + _assert_almost_equal_both(a, b) + + +objs = [NA, np.nan, NaT, None, np.datetime64("NaT"), np.timedelta64("NaT")] + + +@pytest.mark.parametrize("left", objs) +@pytest.mark.parametrize("right", objs) +def test_mismatched_na_assert_almost_equal_deprecation(left, right): + left_arr = np.array([left], dtype=object) + right_arr = np.array([right], dtype=object) + + msg = "Mismatched null-like values" + + if left is right: + _assert_almost_equal_both(left, right, check_dtype=False) + tm.assert_numpy_array_equal(left_arr, right_arr) + tm.assert_index_equal( + Index(left_arr, dtype=object), Index(right_arr, dtype=object) + ) + tm.assert_series_equal( + Series(left_arr, dtype=object), Series(right_arr, dtype=object) + ) + tm.assert_frame_equal( + DataFrame(left_arr, dtype=object), DataFrame(right_arr, dtype=object) + ) + + else: + with tm.assert_produces_warning(FutureWarning, match=msg): + _assert_almost_equal_both(left, right, check_dtype=False) + + # TODO: to get the same deprecation in assert_numpy_array_equal we need + # to change/deprecate the default for strict_nan to become True + # TODO: to get the same deprecation in assert_index_equal we need to + # change/deprecate array_equivalent_object to be stricter, as + # assert_index_equal uses Index.equal which uses array_equivalent. + with tm.assert_produces_warning(FutureWarning, match=msg): + tm.assert_series_equal( + Series(left_arr, dtype=object), Series(right_arr, dtype=object) + ) + with tm.assert_produces_warning(FutureWarning, match=msg): + tm.assert_frame_equal( + DataFrame(left_arr, dtype=object), DataFrame(right_arr, dtype=object) + ) + + +def test_assert_not_almost_equal_inf(): + _assert_not_almost_equal_both(np.inf, 0) + + +@pytest.mark.parametrize( + "a,b", + [ + (Index([1.0, 1.1]), Index([1.0, 1.100001])), + (Series([1.0, 1.1]), Series([1.0, 1.100001])), + (np.array([1.1, 2.000001]), np.array([1.1, 2.0])), + (DataFrame({"a": [1.0, 1.1]}), DataFrame({"a": [1.0, 1.100001]})), + ], +) +def test_assert_almost_equal_pandas(a, b): + _assert_almost_equal_both(a, b) + + +def test_assert_almost_equal_object(): + a = [Timestamp("2011-01-01"), Timestamp("2011-01-01")] + b = [Timestamp("2011-01-01"), Timestamp("2011-01-01")] + _assert_almost_equal_both(a, b) + + +def test_assert_almost_equal_value_mismatch(): + msg = "expected 2\\.00000 but got 1\\.00000, with rtol=1e-05, atol=1e-08" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(1, 2) + + +@pytest.mark.parametrize( + "a,b,klass1,klass2", + [(np.array([1]), 1, "ndarray", "int"), (1, np.array([1]), "int", "ndarray")], +) +def test_assert_almost_equal_class_mismatch(a, b, klass1, klass2): + msg = f"""numpy array are different + +numpy array classes are different +\\[left\\]: {klass1} +\\[right\\]: {klass2}""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(a, b) + + +def test_assert_almost_equal_value_mismatch1(): + msg = """numpy array are different + +numpy array values are different \\(66\\.66667 %\\) +\\[left\\]: \\[nan, 2\\.0, 3\\.0\\] +\\[right\\]: \\[1\\.0, nan, 3\\.0\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(np.array([np.nan, 2, 3]), np.array([1, np.nan, 3])) + + +def test_assert_almost_equal_value_mismatch2(): + msg = """numpy array are different + +numpy array values are different \\(50\\.0 %\\) +\\[left\\]: \\[1, 2\\] +\\[right\\]: \\[1, 3\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(np.array([1, 2]), np.array([1, 3])) + + +def test_assert_almost_equal_value_mismatch3(): + msg = """numpy array are different + +numpy array values are different \\(16\\.66667 %\\) +\\[left\\]: \\[\\[1, 2\\], \\[3, 4\\], \\[5, 6\\]\\] +\\[right\\]: \\[\\[1, 3\\], \\[3, 4\\], \\[5, 6\\]\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal( + np.array([[1, 2], [3, 4], [5, 6]]), np.array([[1, 3], [3, 4], [5, 6]]) + ) + + +def test_assert_almost_equal_value_mismatch4(): + msg = """numpy array are different + +numpy array values are different \\(25\\.0 %\\) +\\[left\\]: \\[\\[1, 2\\], \\[3, 4\\]\\] +\\[right\\]: \\[\\[1, 3\\], \\[3, 4\\]\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(np.array([[1, 2], [3, 4]]), np.array([[1, 3], [3, 4]])) + + +def test_assert_almost_equal_shape_mismatch_override(): + msg = """Index are different + +Index shapes are different +\\[left\\]: \\(2L*,\\) +\\[right\\]: \\(3L*,\\)""" + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(np.array([1, 2]), np.array([3, 4, 5]), obj="Index") + + +def test_assert_almost_equal_unicode(): + # see gh-20503 + msg = """numpy array are different + +numpy array values are different \\(33\\.33333 %\\) +\\[left\\]: \\[á, à, ä\\] +\\[right\\]: \\[á, à, å\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(np.array(["á", "à", "ä"]), np.array(["á", "à", "å"])) + + +def test_assert_almost_equal_timestamp(): + a = np.array([Timestamp("2011-01-01"), Timestamp("2011-01-01")]) + b = np.array([Timestamp("2011-01-01"), Timestamp("2011-01-02")]) + + msg = """numpy array are different + +numpy array values are different \\(50\\.0 %\\) +\\[left\\]: \\[2011-01-01 00:00:00, 2011-01-01 00:00:00\\] +\\[right\\]: \\[2011-01-01 00:00:00, 2011-01-02 00:00:00\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal(a, b) + + +def test_assert_almost_equal_iterable_length_mismatch(): + msg = """Iterable are different + +Iterable length are different +\\[left\\]: 2 +\\[right\\]: 3""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal([1, 2], [3, 4, 5]) + + +def test_assert_almost_equal_iterable_values_mismatch(): + msg = """Iterable are different + +Iterable values are different \\(50\\.0 %\\) +\\[left\\]: \\[1, 2\\] +\\[right\\]: \\[1, 3\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_almost_equal([1, 2], [1, 3]) + + +subarr = np.empty(2, dtype=object) +subarr[:] = [np.array([None, "b"], dtype=object), np.array(["c", "d"], dtype=object)] + +NESTED_CASES = [ + # nested array + ( + np.array([np.array([50, 70, 90]), np.array([20, 30])], dtype=object), + np.array([np.array([50, 70, 90]), np.array([20, 30])], dtype=object), + ), + # >1 level of nesting + ( + np.array( + [ + np.array([np.array([50, 70]), np.array([90])], dtype=object), + np.array([np.array([20, 30])], dtype=object), + ], + dtype=object, + ), + np.array( + [ + np.array([np.array([50, 70]), np.array([90])], dtype=object), + np.array([np.array([20, 30])], dtype=object), + ], + dtype=object, + ), + ), + # lists + ( + np.array([[50, 70, 90], [20, 30]], dtype=object), + np.array([[50, 70, 90], [20, 30]], dtype=object), + ), + # mixed array/list + ( + np.array([np.array([1, 2, 3]), np.array([4, 5])], dtype=object), + np.array([[1, 2, 3], [4, 5]], dtype=object), + ), + ( + np.array( + [ + np.array([np.array([1, 2, 3]), np.array([4, 5])], dtype=object), + np.array( + [np.array([6]), np.array([7, 8]), np.array([9])], dtype=object + ), + ], + dtype=object, + ), + np.array([[[1, 2, 3], [4, 5]], [[6], [7, 8], [9]]], dtype=object), + ), + # same-length lists + ( + np.array([subarr, None], dtype=object), + np.array([[[None, "b"], ["c", "d"]], None], dtype=object), + ), + # dicts + ( + np.array([{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object), + np.array([{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object), + ), + ( + np.array([{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object), + np.array([{"f1": 1, "f2": ["a", "b"]}], dtype=object), + ), + # array/list of dicts + ( + np.array( + [ + np.array( + [{"f1": 1, "f2": np.array(["a", "b"], dtype=object)}], dtype=object + ), + np.array([], dtype=object), + ], + dtype=object, + ), + np.array([[{"f1": 1, "f2": ["a", "b"]}], []], dtype=object), + ), +] + + +@pytest.mark.filterwarnings("ignore:elementwise comparison failed:DeprecationWarning") +@pytest.mark.parametrize("a,b", NESTED_CASES) +def test_assert_almost_equal_array_nested(a, b): + _assert_almost_equal_both(a, b) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_attr_equal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_attr_equal.py new file mode 100644 index 0000000000000000000000000000000000000000..bbbb0bf2172b12f93c9f0f6a97751854d1566a99 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_attr_equal.py @@ -0,0 +1,33 @@ +from types import SimpleNamespace + +import pytest + +from pandas.core.dtypes.common import is_float + +import pandas._testing as tm + + +def test_assert_attr_equal(nulls_fixture): + obj = SimpleNamespace() + obj.na_value = nulls_fixture + tm.assert_attr_equal("na_value", obj, obj) + + +def test_assert_attr_equal_different_nulls(nulls_fixture, nulls_fixture2): + obj = SimpleNamespace() + obj.na_value = nulls_fixture + + obj2 = SimpleNamespace() + obj2.na_value = nulls_fixture2 + + if nulls_fixture is nulls_fixture2: + tm.assert_attr_equal("na_value", obj, obj2) + elif is_float(nulls_fixture) and is_float(nulls_fixture2): + # we consider float("nan") and np.float64("nan") to be equivalent + tm.assert_attr_equal("na_value", obj, obj2) + elif type(nulls_fixture) is type(nulls_fixture2): + # e.g. Decimal("NaN") + tm.assert_attr_equal("na_value", obj, obj2) + else: + with pytest.raises(AssertionError, match='"na_value" are different'): + tm.assert_attr_equal("na_value", obj, obj2) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_categorical_equal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_categorical_equal.py new file mode 100644 index 0000000000000000000000000000000000000000..d07bbcbc460a19ec943c1f8727e25835803cf0e4 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_categorical_equal.py @@ -0,0 +1,90 @@ +import pytest + +from pandas import Categorical +import pandas._testing as tm + + +@pytest.mark.parametrize( + "c", + [Categorical([1, 2, 3, 4]), Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4, 5])], +) +def test_categorical_equal(c): + tm.assert_categorical_equal(c, c) + + +@pytest.mark.parametrize("check_category_order", [True, False]) +def test_categorical_equal_order_mismatch(check_category_order): + c1 = Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4]) + c2 = Categorical([1, 2, 3, 4], categories=[4, 3, 2, 1]) + kwargs = {"check_category_order": check_category_order} + + if check_category_order: + msg = """Categorical\\.categories are different + +Categorical\\.categories values are different \\(100\\.0 %\\) +\\[left\\]: Index\\(\\[1, 2, 3, 4\\], dtype='int64'\\) +\\[right\\]: Index\\(\\[4, 3, 2, 1\\], dtype='int64'\\)""" + with pytest.raises(AssertionError, match=msg): + tm.assert_categorical_equal(c1, c2, **kwargs) + else: + tm.assert_categorical_equal(c1, c2, **kwargs) + + +def test_categorical_equal_categories_mismatch(): + msg = """Categorical\\.categories are different + +Categorical\\.categories values are different \\(25\\.0 %\\) +\\[left\\]: Index\\(\\[1, 2, 3, 4\\], dtype='int64'\\) +\\[right\\]: Index\\(\\[1, 2, 3, 5\\], dtype='int64'\\)""" + + c1 = Categorical([1, 2, 3, 4]) + c2 = Categorical([1, 2, 3, 5]) + + with pytest.raises(AssertionError, match=msg): + tm.assert_categorical_equal(c1, c2) + + +def test_categorical_equal_codes_mismatch(): + categories = [1, 2, 3, 4] + msg = """Categorical\\.codes are different + +Categorical\\.codes values are different \\(50\\.0 %\\) +\\[left\\]: \\[0, 1, 3, 2\\] +\\[right\\]: \\[0, 1, 2, 3\\]""" + + c1 = Categorical([1, 2, 4, 3], categories=categories) + c2 = Categorical([1, 2, 3, 4], categories=categories) + + with pytest.raises(AssertionError, match=msg): + tm.assert_categorical_equal(c1, c2) + + +def test_categorical_equal_ordered_mismatch(): + data = [1, 2, 3, 4] + msg = """Categorical are different + +Attribute "ordered" are different +\\[left\\]: False +\\[right\\]: True""" + + c1 = Categorical(data, ordered=False) + c2 = Categorical(data, ordered=True) + + with pytest.raises(AssertionError, match=msg): + tm.assert_categorical_equal(c1, c2) + + +@pytest.mark.parametrize("obj", ["index", "foo", "pandas"]) +def test_categorical_equal_object_override(obj): + data = [1, 2, 3, 4] + msg = f"""{obj} are different + +Attribute "ordered" are different +\\[left\\]: False +\\[right\\]: True""" + + c1 = Categorical(data, ordered=False) + c2 = Categorical(data, ordered=True) + + with pytest.raises(AssertionError, match=msg): + tm.assert_categorical_equal(c1, c2, obj=obj) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_extension_array_equal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_extension_array_equal.py new file mode 100644 index 0000000000000000000000000000000000000000..674e9307d8bb982826f7c92da798ba8d1eee9fde --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_extension_array_equal.py @@ -0,0 +1,126 @@ +import numpy as np +import pytest + +from pandas import ( + Timestamp, + array, +) +import pandas._testing as tm +from pandas.core.arrays.sparse import SparseArray + + +@pytest.mark.parametrize( + "kwargs", + [ + {}, # Default is check_exact=False + {"check_exact": False}, + {"check_exact": True}, + ], +) +def test_assert_extension_array_equal_not_exact(kwargs): + # see gh-23709 + arr1 = SparseArray([-0.17387645482451206, 0.3414148016424936]) + arr2 = SparseArray([-0.17387645482451206, 0.3414148016424937]) + + if kwargs.get("check_exact", False): + msg = """\ +ExtensionArray are different + +ExtensionArray values are different \\(50\\.0 %\\) +\\[left\\]: \\[-0\\.17387645482.*, 0\\.341414801642.*\\] +\\[right\\]: \\[-0\\.17387645482.*, 0\\.341414801642.*\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_extension_array_equal(arr1, arr2, **kwargs) + else: + tm.assert_extension_array_equal(arr1, arr2, **kwargs) + + +@pytest.mark.parametrize("decimals", range(10)) +def test_assert_extension_array_equal_less_precise(decimals): + rtol = 0.5 * 10**-decimals + arr1 = SparseArray([0.5, 0.123456]) + arr2 = SparseArray([0.5, 0.123457]) + + if decimals >= 5: + msg = """\ +ExtensionArray are different + +ExtensionArray values are different \\(50\\.0 %\\) +\\[left\\]: \\[0\\.5, 0\\.123456\\] +\\[right\\]: \\[0\\.5, 0\\.123457\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_extension_array_equal(arr1, arr2, rtol=rtol) + else: + tm.assert_extension_array_equal(arr1, arr2, rtol=rtol) + + +def test_assert_extension_array_equal_dtype_mismatch(check_dtype): + end = 5 + kwargs = {"check_dtype": check_dtype} + + arr1 = SparseArray(np.arange(end, dtype="int64")) + arr2 = SparseArray(np.arange(end, dtype="int32")) + + if check_dtype: + msg = """\ +ExtensionArray are different + +Attribute "dtype" are different +\\[left\\]: Sparse\\[int64, 0\\] +\\[right\\]: Sparse\\[int32, 0\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_extension_array_equal(arr1, arr2, **kwargs) + else: + tm.assert_extension_array_equal(arr1, arr2, **kwargs) + + +def test_assert_extension_array_equal_missing_values(): + arr1 = SparseArray([np.nan, 1, 2, np.nan]) + arr2 = SparseArray([np.nan, 1, 2, 3]) + + msg = """\ +ExtensionArray NA mask are different + +ExtensionArray NA mask values are different \\(25\\.0 %\\) +\\[left\\]: \\[True, False, False, True\\] +\\[right\\]: \\[True, False, False, False\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_extension_array_equal(arr1, arr2) + + +@pytest.mark.parametrize("side", ["left", "right"]) +def test_assert_extension_array_equal_non_extension_array(side): + numpy_array = np.arange(5) + extension_array = SparseArray(numpy_array) + + msg = f"{side} is not an ExtensionArray" + args = ( + (numpy_array, extension_array) + if side == "left" + else (extension_array, numpy_array) + ) + + with pytest.raises(AssertionError, match=msg): + tm.assert_extension_array_equal(*args) + + +@pytest.mark.parametrize("right_dtype", ["Int32", "int64"]) +def test_assert_extension_array_equal_ignore_dtype_mismatch(right_dtype): + # https://github.com/pandas-dev/pandas/issues/35715 + left = array([1, 2, 3], dtype="Int64") + right = array([1, 2, 3], dtype=right_dtype) + tm.assert_extension_array_equal(left, right, check_dtype=False) + + +def test_assert_extension_array_equal_time_units(): + # https://github.com/pandas-dev/pandas/issues/55730 + timestamp = Timestamp("2023-11-04T12") + naive = array([timestamp], dtype="datetime64[ns]") + utc = array([timestamp], dtype="datetime64[ns, UTC]") + + tm.assert_extension_array_equal(naive, utc, check_dtype=False) + tm.assert_extension_array_equal(utc, naive, check_dtype=False) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_frame_equal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_frame_equal.py new file mode 100644 index 0000000000000000000000000000000000000000..dd5218ab9404f35b009cf5f81c09f9d58c78bb18 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_frame_equal.py @@ -0,0 +1,393 @@ +import pytest + +import pandas as pd +from pandas import DataFrame +import pandas._testing as tm + + +@pytest.fixture(params=[True, False]) +def by_blocks_fixture(request): + return request.param + + +@pytest.fixture(params=["DataFrame", "Series"]) +def obj_fixture(request): + return request.param + + +def _assert_frame_equal_both(a, b, **kwargs): + """ + Check that two DataFrame equal. + + This check is performed commutatively. + + Parameters + ---------- + a : DataFrame + The first DataFrame to compare. + b : DataFrame + The second DataFrame to compare. + kwargs : dict + The arguments passed to `tm.assert_frame_equal`. + """ + tm.assert_frame_equal(a, b, **kwargs) + tm.assert_frame_equal(b, a, **kwargs) + + +@pytest.mark.parametrize("check_like", [True, False]) +def test_frame_equal_row_order_mismatch(check_like, obj_fixture): + df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"]) + df2 = DataFrame({"A": [3, 2, 1], "B": [6, 5, 4]}, index=["c", "b", "a"]) + + if not check_like: # Do not ignore row-column orderings. + msg = f"{obj_fixture}.index are different" + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture) + else: + _assert_frame_equal_both(df1, df2, check_like=check_like, obj=obj_fixture) + + +@pytest.mark.parametrize( + "df1,df2", + [ + (DataFrame({"A": [1, 2, 3]}), DataFrame({"A": [1, 2, 3, 4]})), + (DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), DataFrame({"A": [1, 2, 3]})), + ], +) +def test_frame_equal_shape_mismatch(df1, df2, obj_fixture): + msg = f"{obj_fixture} are different" + + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, obj=obj_fixture) + + +@pytest.mark.parametrize( + "df1,df2,msg", + [ + # Index + ( + DataFrame.from_records({"a": [1, 2], "c": ["l1", "l2"]}, index=["a"]), + DataFrame.from_records({"a": [1.0, 2.0], "c": ["l1", "l2"]}, index=["a"]), + "DataFrame\\.index are different", + ), + # MultiIndex + ( + DataFrame.from_records( + {"a": [1, 2], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"] + ), + DataFrame.from_records( + {"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"] + ), + "MultiIndex level \\[0\\] are different", + ), + ], +) +def test_frame_equal_index_dtype_mismatch(df1, df2, msg, check_index_type): + kwargs = {"check_index_type": check_index_type} + + if check_index_type: + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, **kwargs) + else: + tm.assert_frame_equal(df1, df2, **kwargs) + + +def test_empty_dtypes(check_dtype): + columns = ["col1", "col2"] + df1 = DataFrame(columns=columns) + df2 = DataFrame(columns=columns) + + kwargs = {"check_dtype": check_dtype} + df1["col1"] = df1["col1"].astype("int64") + + if check_dtype: + msg = r"Attributes of DataFrame\..* are different" + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, **kwargs) + else: + tm.assert_frame_equal(df1, df2, **kwargs) + + +@pytest.mark.parametrize("check_like", [True, False]) +def test_frame_equal_index_mismatch(check_like, obj_fixture, using_infer_string): + if using_infer_string: + dtype = "str" + else: + dtype = "object" + msg = f"""{obj_fixture}\\.index are different + +{obj_fixture}\\.index values are different \\(33\\.33333 %\\) +\\[left\\]: Index\\(\\['a', 'b', 'c'\\], dtype='{dtype}'\\) +\\[right\\]: Index\\(\\['a', 'b', 'd'\\], dtype='{dtype}'\\) +At positional index 2, first diff: c != d""" + + df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"]) + df2 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "d"]) + + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture) + + +@pytest.mark.parametrize("check_like", [True, False]) +def test_frame_equal_columns_mismatch(check_like, obj_fixture, using_infer_string): + if using_infer_string: + dtype = "str" + else: + dtype = "object" + msg = f"""{obj_fixture}\\.columns are different + +{obj_fixture}\\.columns values are different \\(50\\.0 %\\) +\\[left\\]: Index\\(\\['A', 'B'\\], dtype='{dtype}'\\) +\\[right\\]: Index\\(\\['A', 'b'\\], dtype='{dtype}'\\)""" + + df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"]) + df2 = DataFrame({"A": [1, 2, 3], "b": [4, 5, 6]}, index=["a", "b", "c"]) + + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture) + + +def test_frame_equal_block_mismatch(by_blocks_fixture, obj_fixture): + obj = obj_fixture + msg = f"""{obj}\\.iloc\\[:, 1\\] \\(column name="B"\\) are different + +{obj}\\.iloc\\[:, 1\\] \\(column name="B"\\) values are different \\(33\\.33333 %\\) +\\[index\\]: \\[0, 1, 2\\] +\\[left\\]: \\[4, 5, 6\\] +\\[right\\]: \\[4, 5, 7\\]""" + + df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) + df2 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 7]}) + + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, by_blocks=by_blocks_fixture, obj=obj_fixture) + + +@pytest.mark.parametrize( + "df1,df2,msg", + [ + ( + DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "ë"]}), + DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "e̊"]}), + """{obj}\\.iloc\\[:, 1\\] \\(column name="E"\\) are different + +{obj}\\.iloc\\[:, 1\\] \\(column name="E"\\) values are different \\(33\\.33333 %\\) +\\[index\\]: \\[0, 1, 2\\] +\\[left\\]: \\[é, è, ë\\] +\\[right\\]: \\[é, è, e̊\\]""", + ), + ( + DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "ë"]}), + DataFrame({"A": ["a", "a", "a"], "E": ["e", "e", "e"]}), + """{obj}\\.iloc\\[:, 0\\] \\(column name="A"\\) are different + +{obj}\\.iloc\\[:, 0\\] \\(column name="A"\\) values are different \\(100\\.0 %\\) +\\[index\\]: \\[0, 1, 2\\] +\\[left\\]: \\[á, à, ä\\] +\\[right\\]: \\[a, a, a\\]""", + ), + ], +) +def test_frame_equal_unicode(df1, df2, msg, by_blocks_fixture, obj_fixture): + # see gh-20503 + # + # Test ensures that `tm.assert_frame_equals` raises the right exception + # when comparing DataFrames containing differing unicode objects. + msg = msg.format(obj=obj_fixture) + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(df1, df2, by_blocks=by_blocks_fixture, obj=obj_fixture) + + +def test_assert_frame_equal_extension_dtype_mismatch(): + # https://github.com/pandas-dev/pandas/issues/32747 + left = DataFrame({"a": [1, 2, 3]}, dtype="Int64") + right = left.astype(int) + + msg = ( + "Attributes of DataFrame\\.iloc\\[:, 0\\] " + '\\(column name="a"\\) are different\n\n' + 'Attribute "dtype" are different\n' + "\\[left\\]: Int64\n" + "\\[right\\]: int[32|64]" + ) + + tm.assert_frame_equal(left, right, check_dtype=False) + + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(left, right, check_dtype=True) + + +def test_assert_frame_equal_interval_dtype_mismatch(): + # https://github.com/pandas-dev/pandas/issues/32747 + left = DataFrame({"a": [pd.Interval(0, 1)]}, dtype="interval") + right = left.astype(object) + + msg = ( + "Attributes of DataFrame\\.iloc\\[:, 0\\] " + '\\(column name="a"\\) are different\n\n' + 'Attribute "dtype" are different\n' + "\\[left\\]: interval\\[int64, right\\]\n" + "\\[right\\]: object" + ) + + tm.assert_frame_equal(left, right, check_dtype=False) + + with pytest.raises(AssertionError, match=msg): + tm.assert_frame_equal(left, right, check_dtype=True) + + +def test_assert_frame_equal_ignore_extension_dtype_mismatch(): + # https://github.com/pandas-dev/pandas/issues/35715 + left = DataFrame({"a": [1, 2, 3]}, dtype="Int64") + right = DataFrame({"a": [1, 2, 3]}, dtype="Int32") + tm.assert_frame_equal(left, right, check_dtype=False) + + +def test_assert_frame_equal_ignore_extension_dtype_mismatch_cross_class(): + # https://github.com/pandas-dev/pandas/issues/35715 + left = DataFrame({"a": [1, 2, 3]}, dtype="Int64") + right = DataFrame({"a": [1, 2, 3]}, dtype="int64") + tm.assert_frame_equal(left, right, check_dtype=False) + + +@pytest.mark.parametrize( + "dtype", + [ + ("timedelta64[ns]"), + ("datetime64[ns, UTC]"), + ("Period[D]"), + ], +) +def test_assert_frame_equal_datetime_like_dtype_mismatch(dtype): + df1 = DataFrame({"a": []}, dtype=dtype) + df2 = DataFrame({"a": []}) + tm.assert_frame_equal(df1, df2, check_dtype=False) + + +def test_allows_duplicate_labels(): + left = DataFrame() + right = DataFrame().set_flags(allows_duplicate_labels=False) + tm.assert_frame_equal(left, left) + tm.assert_frame_equal(right, right) + tm.assert_frame_equal(left, right, check_flags=False) + tm.assert_frame_equal(right, left, check_flags=False) + + with pytest.raises(AssertionError, match="\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_numpy_array_equal(a, b) + + +def test_numpy_array_equal_identical_na(nulls_fixture): + a = np.array([nulls_fixture], dtype=object) + + tm.assert_numpy_array_equal(a, a) + + # matching but not the identical object + if hasattr(nulls_fixture, "copy"): + other = nulls_fixture.copy() + else: + other = copy.copy(nulls_fixture) + b = np.array([other], dtype=object) + tm.assert_numpy_array_equal(a, b) + + +def test_numpy_array_equal_different_na(): + a = np.array([np.nan], dtype=object) + b = np.array([pd.NA], dtype=object) + + msg = """numpy array are different + +numpy array values are different \\(100.0 %\\) +\\[left\\]: \\[nan\\] +\\[right\\]: \\[\\]""" + + with pytest.raises(AssertionError, match=msg): + tm.assert_numpy_array_equal(a, b) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_produces_warning.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_produces_warning.py new file mode 100644 index 0000000000000000000000000000000000000000..5c27a3ee79d4a82bce83eec56ab9d88e10dc06cd --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_produces_warning.py @@ -0,0 +1,241 @@ +"""" +Test module for testing ``pandas._testing.assert_produces_warning``. +""" +import warnings + +import pytest + +from pandas.errors import ( + DtypeWarning, + PerformanceWarning, +) + +import pandas._testing as tm + + +@pytest.fixture( + params=[ + RuntimeWarning, + ResourceWarning, + UserWarning, + FutureWarning, + DeprecationWarning, + PerformanceWarning, + DtypeWarning, + ], +) +def category(request): + """ + Return unique warning. + + Useful for testing behavior of tm.assert_produces_warning with various categories. + """ + return request.param + + +@pytest.fixture( + params=[ + (RuntimeWarning, UserWarning), + (UserWarning, FutureWarning), + (FutureWarning, RuntimeWarning), + (DeprecationWarning, PerformanceWarning), + (PerformanceWarning, FutureWarning), + (DtypeWarning, DeprecationWarning), + (ResourceWarning, DeprecationWarning), + (FutureWarning, DeprecationWarning), + ], + ids=lambda x: type(x).__name__, +) +def pair_different_warnings(request): + """ + Return pair or different warnings. + + Useful for testing how several different warnings are handled + in tm.assert_produces_warning. + """ + return request.param + + +def f(): + warnings.warn("f1", FutureWarning) + warnings.warn("f2", RuntimeWarning) + + +@pytest.mark.filterwarnings("ignore:f1:FutureWarning") +def test_assert_produces_warning_honors_filter(): + # Raise by default. + msg = r"Caused unexpected warning\(s\)" + with pytest.raises(AssertionError, match=msg): + with tm.assert_produces_warning(RuntimeWarning): + f() + + with tm.assert_produces_warning(RuntimeWarning, raise_on_extra_warnings=False): + f() + + +@pytest.mark.parametrize( + "message, match", + [ + ("", None), + ("", ""), + ("Warning message", r".*"), + ("Warning message", "War"), + ("Warning message", r"[Ww]arning"), + ("Warning message", "age"), + ("Warning message", r"age$"), + ("Message 12-234 with numbers", r"\d{2}-\d{3}"), + ("Message 12-234 with numbers", r"^Mes.*\d{2}-\d{3}"), + ("Message 12-234 with numbers", r"\d{2}-\d{3}\s\S+"), + ("Message, which we do not match", None), + ], +) +def test_catch_warning_category_and_match(category, message, match): + with tm.assert_produces_warning(category, match=match): + warnings.warn(message, category) + + +def test_fail_to_match_runtime_warning(): + category = RuntimeWarning + match = "Did not see this warning" + unmatched = ( + r"Did not see warning 'RuntimeWarning' matching 'Did not see this warning'. " + r"The emitted warning messages are " + r"\[RuntimeWarning\('This is not a match.'\), " + r"RuntimeWarning\('Another unmatched warning.'\)\]" + ) + with pytest.raises(AssertionError, match=unmatched): + with tm.assert_produces_warning(category, match=match): + warnings.warn("This is not a match.", category) + warnings.warn("Another unmatched warning.", category) + + +def test_fail_to_match_future_warning(): + category = FutureWarning + match = "Warning" + unmatched = ( + r"Did not see warning 'FutureWarning' matching 'Warning'. " + r"The emitted warning messages are " + r"\[FutureWarning\('This is not a match.'\), " + r"FutureWarning\('Another unmatched warning.'\)\]" + ) + with pytest.raises(AssertionError, match=unmatched): + with tm.assert_produces_warning(category, match=match): + warnings.warn("This is not a match.", category) + warnings.warn("Another unmatched warning.", category) + + +def test_fail_to_match_resource_warning(): + category = ResourceWarning + match = r"\d+" + unmatched = ( + r"Did not see warning 'ResourceWarning' matching '\\d\+'. " + r"The emitted warning messages are " + r"\[ResourceWarning\('This is not a match.'\), " + r"ResourceWarning\('Another unmatched warning.'\)\]" + ) + with pytest.raises(AssertionError, match=unmatched): + with tm.assert_produces_warning(category, match=match): + warnings.warn("This is not a match.", category) + warnings.warn("Another unmatched warning.", category) + + +def test_fail_to_catch_actual_warning(pair_different_warnings): + expected_category, actual_category = pair_different_warnings + match = "Did not see expected warning of class" + with pytest.raises(AssertionError, match=match): + with tm.assert_produces_warning(expected_category): + warnings.warn("warning message", actual_category) + + +def test_ignore_extra_warning(pair_different_warnings): + expected_category, extra_category = pair_different_warnings + with tm.assert_produces_warning(expected_category, raise_on_extra_warnings=False): + warnings.warn("Expected warning", expected_category) + warnings.warn("Unexpected warning OK", extra_category) + + +def test_raise_on_extra_warning(pair_different_warnings): + expected_category, extra_category = pair_different_warnings + match = r"Caused unexpected warning\(s\)" + with pytest.raises(AssertionError, match=match): + with tm.assert_produces_warning(expected_category): + warnings.warn("Expected warning", expected_category) + warnings.warn("Unexpected warning NOT OK", extra_category) + + +def test_same_category_different_messages_first_match(): + category = UserWarning + with tm.assert_produces_warning(category, match=r"^Match this"): + warnings.warn("Match this", category) + warnings.warn("Do not match that", category) + warnings.warn("Do not match that either", category) + + +def test_same_category_different_messages_last_match(): + category = DeprecationWarning + with tm.assert_produces_warning(category, match=r"^Match this"): + warnings.warn("Do not match that", category) + warnings.warn("Do not match that either", category) + warnings.warn("Match this", category) + + +def test_match_multiple_warnings(): + # https://github.com/pandas-dev/pandas/issues/47829 + category = (FutureWarning, UserWarning) + with tm.assert_produces_warning(category, match=r"^Match this"): + warnings.warn("Match this", FutureWarning) + warnings.warn("Match this too", UserWarning) + + +def test_right_category_wrong_match_raises(pair_different_warnings): + target_category, other_category = pair_different_warnings + with pytest.raises(AssertionError, match="Did not see warning.*matching"): + with tm.assert_produces_warning(target_category, match=r"^Match this"): + warnings.warn("Do not match it", target_category) + warnings.warn("Match this", other_category) + + +@pytest.mark.parametrize("false_or_none", [False, None]) +class TestFalseOrNoneExpectedWarning: + def test_raise_on_warning(self, false_or_none): + msg = r"Caused unexpected warning\(s\)" + with pytest.raises(AssertionError, match=msg): + with tm.assert_produces_warning(false_or_none): + f() + + def test_no_raise_without_warning(self, false_or_none): + with tm.assert_produces_warning(false_or_none): + pass + + def test_no_raise_with_false_raise_on_extra(self, false_or_none): + with tm.assert_produces_warning(false_or_none, raise_on_extra_warnings=False): + f() + + +def test_raises_during_exception(): + msg = "Did not see expected warning of class 'UserWarning'" + with pytest.raises(AssertionError, match=msg): + with tm.assert_produces_warning(UserWarning): + raise ValueError + + with pytest.raises(AssertionError, match=msg): + with tm.assert_produces_warning(UserWarning): + warnings.warn("FutureWarning", FutureWarning) + raise IndexError + + msg = "Caused unexpected warning" + with pytest.raises(AssertionError, match=msg): + with tm.assert_produces_warning(None): + warnings.warn("FutureWarning", FutureWarning) + raise SystemError + + +def test_passes_during_exception(): + with pytest.raises(SyntaxError, match="Error"): + with tm.assert_produces_warning(None): + raise SyntaxError("Error") + + with pytest.raises(ValueError, match="Error"): + with tm.assert_produces_warning(FutureWarning, match="FutureWarning"): + warnings.warn("FutureWarning", FutureWarning) + raise ValueError("Error") diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_series_equal.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_series_equal.py new file mode 100644 index 0000000000000000000000000000000000000000..9cc9fb924ed67b5f4e9a3ac26acda3f346681d23 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_assert_series_equal.py @@ -0,0 +1,475 @@ +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + Categorical, + DataFrame, + Series, +) +import pandas._testing as tm + + +def _assert_series_equal_both(a, b, **kwargs): + """ + Check that two Series equal. + + This check is performed commutatively. + + Parameters + ---------- + a : Series + The first Series to compare. + b : Series + The second Series to compare. + kwargs : dict + The arguments passed to `tm.assert_series_equal`. + """ + tm.assert_series_equal(a, b, **kwargs) + tm.assert_series_equal(b, a, **kwargs) + + +def _assert_not_series_equal(a, b, **kwargs): + """ + Check that two Series are not equal. + + Parameters + ---------- + a : Series + The first Series to compare. + b : Series + The second Series to compare. + kwargs : dict + The arguments passed to `tm.assert_series_equal`. + """ + try: + tm.assert_series_equal(a, b, **kwargs) + msg = "The two Series were equal when they shouldn't have been" + + pytest.fail(msg=msg) + except AssertionError: + pass + + +def _assert_not_series_equal_both(a, b, **kwargs): + """ + Check that two Series are not equal. + + This check is performed commutatively. + + Parameters + ---------- + a : Series + The first Series to compare. + b : Series + The second Series to compare. + kwargs : dict + The arguments passed to `tm.assert_series_equal`. + """ + _assert_not_series_equal(a, b, **kwargs) + _assert_not_series_equal(b, a, **kwargs) + + +@pytest.mark.parametrize("data", [range(3), list("abc"), list("áàä")]) +def test_series_equal(data): + _assert_series_equal_both(Series(data), Series(data)) + + +@pytest.mark.parametrize( + "data1,data2", + [ + (range(3), range(1, 4)), + (list("abc"), list("xyz")), + (list("áàä"), list("éèë")), + (list("áàä"), list(b"aaa")), + (range(3), range(4)), + ], +) +def test_series_not_equal_value_mismatch(data1, data2): + _assert_not_series_equal_both(Series(data1), Series(data2)) + + +@pytest.mark.parametrize( + "kwargs", + [ + {"dtype": "float64"}, # dtype mismatch + {"index": [1, 2, 4]}, # index mismatch + {"name": "foo"}, # name mismatch + ], +) +def test_series_not_equal_metadata_mismatch(kwargs): + data = range(3) + s1 = Series(data) + + s2 = Series(data, **kwargs) + _assert_not_series_equal_both(s1, s2) + + +@pytest.mark.parametrize("data1,data2", [(0.12345, 0.12346), (0.1235, 0.1236)]) +@pytest.mark.parametrize("dtype", ["float32", "float64", "Float32"]) +@pytest.mark.parametrize("decimals", [0, 1, 2, 3, 5, 10]) +def test_less_precise(data1, data2, dtype, decimals): + rtol = 10**-decimals + s1 = Series([data1], dtype=dtype) + s2 = Series([data2], dtype=dtype) + + if decimals in (5, 10) or (decimals >= 3 and abs(data1 - data2) >= 0.0005): + msg = "Series values are different" + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s2, rtol=rtol) + else: + _assert_series_equal_both(s1, s2, rtol=rtol) + + +@pytest.mark.parametrize( + "s1,s2,msg", + [ + # Index + ( + Series(["l1", "l2"], index=[1, 2]), + Series(["l1", "l2"], index=[1.0, 2.0]), + "Series\\.index are different", + ), + # MultiIndex + ( + DataFrame.from_records( + {"a": [1, 2], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"] + ).c, + DataFrame.from_records( + {"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"] + ).c, + "MultiIndex level \\[0\\] are different", + ), + ], +) +def test_series_equal_index_dtype(s1, s2, msg, check_index_type): + kwargs = {"check_index_type": check_index_type} + + if check_index_type: + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s2, **kwargs) + else: + tm.assert_series_equal(s1, s2, **kwargs) + + +@pytest.mark.parametrize("check_like", [True, False]) +def test_series_equal_order_mismatch(check_like): + s1 = Series([1, 2, 3], index=["a", "b", "c"]) + s2 = Series([3, 2, 1], index=["c", "b", "a"]) + + if not check_like: # Do not ignore index ordering. + with pytest.raises(AssertionError, match="Series.index are different"): + tm.assert_series_equal(s1, s2, check_like=check_like) + else: + _assert_series_equal_both(s1, s2, check_like=check_like) + + +@pytest.mark.parametrize("check_index", [True, False]) +def test_series_equal_index_mismatch(check_index): + s1 = Series([1, 2, 3], index=["a", "b", "c"]) + s2 = Series([1, 2, 3], index=["c", "b", "a"]) + + if check_index: # Do not ignore index. + with pytest.raises(AssertionError, match="Series.index are different"): + tm.assert_series_equal(s1, s2, check_index=check_index) + else: + _assert_series_equal_both(s1, s2, check_index=check_index) + + +def test_series_invalid_param_combination(): + left = Series(dtype=object) + right = Series(dtype=object) + with pytest.raises( + ValueError, match="check_like must be False if check_index is False" + ): + tm.assert_series_equal(left, right, check_index=False, check_like=True) + + +def test_series_equal_length_mismatch(rtol): + msg = """Series are different + +Series length are different +\\[left\\]: 3, RangeIndex\\(start=0, stop=3, step=1\\) +\\[right\\]: 4, RangeIndex\\(start=0, stop=4, step=1\\)""" + + s1 = Series([1, 2, 3]) + s2 = Series([1, 2, 3, 4]) + + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s2, rtol=rtol) + + +def test_series_equal_numeric_values_mismatch(rtol): + msg = """Series are different + +Series values are different \\(33\\.33333 %\\) +\\[index\\]: \\[0, 1, 2\\] +\\[left\\]: \\[1, 2, 3\\] +\\[right\\]: \\[1, 2, 4\\]""" + + s1 = Series([1, 2, 3]) + s2 = Series([1, 2, 4]) + + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s2, rtol=rtol) + + +def test_series_equal_categorical_values_mismatch(rtol, using_infer_string): + dtype = "str" if using_infer_string else "object" + msg = f"""Series are different + +Series values are different \\(66\\.66667 %\\) +\\[index\\]: \\[0, 1, 2\\] +\\[left\\]: \\['a', 'b', 'c'\\] +Categories \\(3, {dtype}\\): \\['a', 'b', 'c'\\] +\\[right\\]: \\['a', 'c', 'b'\\] +Categories \\(3, {dtype}\\): \\['a', 'b', 'c'\\]""" + + s1 = Series(Categorical(["a", "b", "c"])) + s2 = Series(Categorical(["a", "c", "b"])) + + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s2, rtol=rtol) + + +def test_series_equal_datetime_values_mismatch(rtol): + msg = """Series are different + +Series values are different \\(100.0 %\\) +\\[index\\]: \\[0, 1, 2\\] +\\[left\\]: \\[1514764800000000000, 1514851200000000000, 1514937600000000000\\] +\\[right\\]: \\[1549065600000000000, 1549152000000000000, 1549238400000000000\\]""" + + s1 = Series(pd.date_range("2018-01-01", periods=3, freq="D")) + s2 = Series(pd.date_range("2019-02-02", periods=3, freq="D")) + + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s2, rtol=rtol) + + +def test_series_equal_categorical_mismatch(check_categorical, using_infer_string): + if using_infer_string: + dtype = "str" + else: + dtype = "object" + msg = f"""Attributes of Series are different + +Attribute "dtype" are different +\\[left\\]: CategoricalDtype\\(categories=\\['a', 'b'\\], ordered=False, \ +categories_dtype={dtype}\\) +\\[right\\]: CategoricalDtype\\(categories=\\['a', 'b', 'c'\\], \ +ordered=False, categories_dtype={dtype}\\)""" + + s1 = Series(Categorical(["a", "b"])) + s2 = Series(Categorical(["a", "b"], categories=list("abc"))) + + if check_categorical: + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s2, check_categorical=check_categorical) + else: + _assert_series_equal_both(s1, s2, check_categorical=check_categorical) + + +def test_assert_series_equal_extension_dtype_mismatch(): + # https://github.com/pandas-dev/pandas/issues/32747 + left = Series(pd.array([1, 2, 3], dtype="Int64")) + right = left.astype(int) + + msg = """Attributes of Series are different + +Attribute "dtype" are different +\\[left\\]: Int64 +\\[right\\]: int[32|64]""" + + tm.assert_series_equal(left, right, check_dtype=False) + + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(left, right, check_dtype=True) + + +def test_assert_series_equal_interval_dtype_mismatch(): + # https://github.com/pandas-dev/pandas/issues/32747 + left = Series([pd.Interval(0, 1)], dtype="interval") + right = left.astype(object) + + msg = """Attributes of Series are different + +Attribute "dtype" are different +\\[left\\]: interval\\[int64, right\\] +\\[right\\]: object""" + + tm.assert_series_equal(left, right, check_dtype=False) + + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(left, right, check_dtype=True) + + +def test_series_equal_series_type(): + class MySeries(Series): + pass + + s1 = Series([1, 2]) + s2 = Series([1, 2]) + s3 = MySeries([1, 2]) + + tm.assert_series_equal(s1, s2, check_series_type=False) + tm.assert_series_equal(s1, s2, check_series_type=True) + + tm.assert_series_equal(s1, s3, check_series_type=False) + tm.assert_series_equal(s3, s1, check_series_type=False) + + with pytest.raises(AssertionError, match="Series classes are different"): + tm.assert_series_equal(s1, s3, check_series_type=True) + + with pytest.raises(AssertionError, match="Series classes are different"): + tm.assert_series_equal(s3, s1, check_series_type=True) + + +def test_series_equal_exact_for_nonnumeric(): + # https://github.com/pandas-dev/pandas/issues/35446 + s1 = Series(["a", "b"]) + s2 = Series(["a", "b"]) + s3 = Series(["b", "a"]) + + tm.assert_series_equal(s1, s2, check_exact=True) + tm.assert_series_equal(s2, s1, check_exact=True) + + msg = """Series are different + +Series values are different \\(100\\.0 %\\) +\\[index\\]: \\[0, 1\\] +\\[left\\]: \\[a, b\\] +\\[right\\]: \\[b, a\\]""" + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s1, s3, check_exact=True) + + msg = """Series are different + +Series values are different \\(100\\.0 %\\) +\\[index\\]: \\[0, 1\\] +\\[left\\]: \\[b, a\\] +\\[right\\]: \\[a, b\\]""" + with pytest.raises(AssertionError, match=msg): + tm.assert_series_equal(s3, s1, check_exact=True) + + +def test_assert_series_equal_ignore_extension_dtype_mismatch(): + # https://github.com/pandas-dev/pandas/issues/35715 + left = Series([1, 2, 3], dtype="Int64") + right = Series([1, 2, 3], dtype="Int32") + tm.assert_series_equal(left, right, check_dtype=False) + + +def test_assert_series_equal_ignore_extension_dtype_mismatch_cross_class(): + # https://github.com/pandas-dev/pandas/issues/35715 + left = Series([1, 2, 3], dtype="Int64") + right = Series([1, 2, 3], dtype="int64") + tm.assert_series_equal(left, right, check_dtype=False) + + +def test_allows_duplicate_labels(): + left = Series([1]) + right = Series([1]).set_flags(allows_duplicate_labels=False) + tm.assert_series_equal(left, left) + tm.assert_series_equal(right, right) + tm.assert_series_equal(left, right, check_flags=False) + tm.assert_series_equal(right, left, check_flags=False) + + with pytest.raises(AssertionError, match=">> cumavg([1, 2, 3]) + 2 + """ + ), + method="cumavg", + operation="average", +) +def cumavg(whatever): + pass + + +@doc(cumsum, method="cummax", operation="maximum") +def cummax(whatever): + pass + + +@doc(cummax, method="cummin", operation="minimum") +def cummin(whatever): + pass + + +def test_docstring_formatting(): + docstr = dedent( + """ + This is the cumsum method. + + It computes the cumulative sum. + """ + ) + assert cumsum.__doc__ == docstr + + +def test_docstring_appending(): + docstr = dedent( + """ + This is the cumavg method. + + It computes the cumulative average. + + Examples + -------- + + >>> cumavg([1, 2, 3]) + 2 + """ + ) + assert cumavg.__doc__ == docstr + + +def test_doc_template_from_func(): + docstr = dedent( + """ + This is the cummax method. + + It computes the cumulative maximum. + """ + ) + assert cummax.__doc__ == docstr + + +def test_inherit_doc_template(): + docstr = dedent( + """ + This is the cummin method. + + It computes the cumulative minimum. + """ + ) + assert cummin.__doc__ == docstr diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_hashing.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_hashing.py new file mode 100644 index 0000000000000000000000000000000000000000..1e7fdd920e365cd49abf22732c573ca696d3b3d7 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_hashing.py @@ -0,0 +1,417 @@ +import numpy as np +import pytest + +import pandas as pd +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + period_range, + timedelta_range, +) +import pandas._testing as tm +from pandas.core.util.hashing import hash_tuples +from pandas.util import ( + hash_array, + hash_pandas_object, +) + + +@pytest.fixture( + params=[ + Series([1, 2, 3] * 3, dtype="int32"), + Series([None, 2.5, 3.5] * 3, dtype="float32"), + Series(["a", "b", "c"] * 3, dtype="category"), + Series(["d", "e", "f"] * 3), + Series([True, False, True] * 3), + Series(pd.date_range("20130101", periods=9)), + Series(pd.date_range("20130101", periods=9, tz="US/Eastern")), + Series(timedelta_range("2000", periods=9)), + ] +) +def series(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def index(request): + return request.param + + +def test_consistency(): + # Check that our hash doesn't change because of a mistake + # in the actual code; this is the ground truth. + result = hash_pandas_object(Index(["foo", "bar", "baz"])) + expected = Series( + np.array( + [3600424527151052760, 1374399572096150070, 477881037637427054], + dtype="uint64", + ), + index=["foo", "bar", "baz"], + ) + tm.assert_series_equal(result, expected) + + +def test_hash_array(series): + arr = series.values + tm.assert_numpy_array_equal(hash_array(arr), hash_array(arr)) + + +@pytest.mark.parametrize("dtype", ["U", object]) +def test_hash_array_mixed(dtype): + result1 = hash_array(np.array(["3", "4", "All"])) + result2 = hash_array(np.array([3, 4, "All"], dtype=dtype)) + + tm.assert_numpy_array_equal(result1, result2) + + +@pytest.mark.parametrize("val", [5, "foo", pd.Timestamp("20130101")]) +def test_hash_array_errors(val): + msg = "must pass a ndarray-like" + with pytest.raises(TypeError, match=msg): + hash_array(val) + + +def test_hash_array_index_exception(): + # GH42003 TypeError instead of AttributeError + obj = pd.DatetimeIndex(["2018-10-28 01:20:00"], tz="Europe/Berlin") + + msg = "Use hash_pandas_object instead" + with pytest.raises(TypeError, match=msg): + hash_array(obj) + + +def test_hash_tuples(): + tuples = [(1, "one"), (1, "two"), (2, "one")] + result = hash_tuples(tuples) + + expected = hash_pandas_object(MultiIndex.from_tuples(tuples)).values + tm.assert_numpy_array_equal(result, expected) + + # We only need to support MultiIndex and list-of-tuples + msg = "|".join(["object is not iterable", "zip argument #1 must support iteration"]) + with pytest.raises(TypeError, match=msg): + hash_tuples(tuples[0]) + + +@pytest.mark.parametrize("val", [5, "foo", pd.Timestamp("20130101")]) +def test_hash_tuples_err(val): + msg = "must be convertible to a list-of-tuples" + with pytest.raises(TypeError, match=msg): + hash_tuples(val) + + +def test_multiindex_unique(): + mi = MultiIndex.from_tuples([(118, 472), (236, 118), (51, 204), (102, 51)]) + assert mi.is_unique is True + + result = hash_pandas_object(mi) + assert result.is_unique is True + + +def test_multiindex_objects(): + mi = MultiIndex( + levels=[["b", "d", "a"], [1, 2, 3]], + codes=[[0, 1, 0, 2], [2, 0, 0, 1]], + names=["col1", "col2"], + ) + recons = mi._sort_levels_monotonic() + + # These are equal. + assert mi.equals(recons) + assert Index(mi.values).equals(Index(recons.values)) + + +@pytest.mark.parametrize( + "obj", + [ + Series([1, 2, 3]), + Series([1.0, 1.5, 3.2]), + Series([1.0, 1.5, np.nan]), + Series([1.0, 1.5, 3.2], index=[1.5, 1.1, 3.3]), + Series(["a", "b", "c"]), + Series(["a", np.nan, "c"]), + Series(["a", None, "c"]), + Series([True, False, True]), + Series(dtype=object), + DataFrame({"x": ["a", "b", "c"], "y": [1, 2, 3]}), + DataFrame(), + DataFrame(np.full((10, 4), np.nan)), + DataFrame( + { + "A": [0.0, 1.0, 2.0, 3.0, 4.0], + "B": [0.0, 1.0, 0.0, 1.0, 0.0], + "C": Index(["foo1", "foo2", "foo3", "foo4", "foo5"], dtype=object), + "D": pd.date_range("20130101", periods=5), + } + ), + DataFrame(range(5), index=pd.date_range("2020-01-01", periods=5)), + Series(range(5), index=pd.date_range("2020-01-01", periods=5)), + Series(period_range("2020-01-01", periods=10, freq="D")), + Series(pd.date_range("20130101", periods=3, tz="US/Eastern")), + ], +) +def test_hash_pandas_object(obj, index): + a = hash_pandas_object(obj, index=index) + b = hash_pandas_object(obj, index=index) + tm.assert_series_equal(a, b) + + +@pytest.mark.parametrize( + "obj", + [ + Series([1, 2, 3]), + Series([1.0, 1.5, 3.2]), + Series([1.0, 1.5, np.nan]), + Series([1.0, 1.5, 3.2], index=[1.5, 1.1, 3.3]), + Series(["a", "b", "c"]), + Series(["a", np.nan, "c"]), + Series(["a", None, "c"]), + Series([True, False, True]), + DataFrame({"x": ["a", "b", "c"], "y": [1, 2, 3]}), + DataFrame(np.full((10, 4), np.nan)), + DataFrame( + { + "A": [0.0, 1.0, 2.0, 3.0, 4.0], + "B": [0.0, 1.0, 0.0, 1.0, 0.0], + "C": Index(["foo1", "foo2", "foo3", "foo4", "foo5"], dtype=object), + "D": pd.date_range("20130101", periods=5), + } + ), + DataFrame(range(5), index=pd.date_range("2020-01-01", periods=5)), + Series(range(5), index=pd.date_range("2020-01-01", periods=5)), + Series(period_range("2020-01-01", periods=10, freq="D")), + Series(pd.date_range("20130101", periods=3, tz="US/Eastern")), + ], +) +def test_hash_pandas_object_diff_index_non_empty(obj): + a = hash_pandas_object(obj, index=True) + b = hash_pandas_object(obj, index=False) + assert not (a == b).all() + + +@pytest.mark.parametrize( + "obj", + [ + Index([1, 2, 3]), + Index([True, False, True]), + timedelta_range("1 day", periods=2), + period_range("2020-01-01", freq="D", periods=2), + MultiIndex.from_product( + [range(5), ["foo", "bar", "baz"], pd.date_range("20130101", periods=2)] + ), + MultiIndex.from_product([pd.CategoricalIndex(list("aabc")), range(3)]), + ], +) +def test_hash_pandas_index(obj, index): + a = hash_pandas_object(obj, index=index) + b = hash_pandas_object(obj, index=index) + tm.assert_series_equal(a, b) + + +def test_hash_pandas_series(series, index): + a = hash_pandas_object(series, index=index) + b = hash_pandas_object(series, index=index) + tm.assert_series_equal(a, b) + + +def test_hash_pandas_series_diff_index(series): + a = hash_pandas_object(series, index=True) + b = hash_pandas_object(series, index=False) + assert not (a == b).all() + + +@pytest.mark.parametrize( + "obj", [Series([], dtype="float64"), Series([], dtype="object"), Index([])] +) +def test_hash_pandas_empty_object(obj, index): + # These are by-definition the same with + # or without the index as the data is empty. + a = hash_pandas_object(obj, index=index) + b = hash_pandas_object(obj, index=index) + tm.assert_series_equal(a, b) + + +@pytest.mark.parametrize( + "s1", + [ + Series(["a", "b", "c", "d"]), + Series([1000, 2000, 3000, 4000]), + Series(pd.date_range(0, periods=4)), + ], +) +@pytest.mark.parametrize("categorize", [True, False]) +def test_categorical_consistency(s1, categorize): + # see gh-15143 + # + # Check that categoricals hash consistent with their values, + # not codes. This should work for categoricals of any dtype. + s2 = s1.astype("category").cat.set_categories(s1) + s3 = s2.cat.set_categories(list(reversed(s1))) + + # These should all hash identically. + h1 = hash_pandas_object(s1, categorize=categorize) + h2 = hash_pandas_object(s2, categorize=categorize) + h3 = hash_pandas_object(s3, categorize=categorize) + + tm.assert_series_equal(h1, h2) + tm.assert_series_equal(h1, h3) + + +def test_categorical_with_nan_consistency(): + c = pd.Categorical.from_codes( + [-1, 0, 1, 2, 3, 4], categories=pd.date_range("2012-01-01", periods=5, name="B") + ) + expected = hash_array(c, categorize=False) + + c = pd.Categorical.from_codes([-1, 0], categories=[pd.Timestamp("2012-01-01")]) + result = hash_array(c, categorize=False) + + assert result[0] in expected + assert result[1] in expected + + +def test_pandas_errors(): + msg = "Unexpected type for hashing" + with pytest.raises(TypeError, match=msg): + hash_pandas_object(pd.Timestamp("20130101")) + + +def test_hash_keys(): + # Using different hash keys, should have + # different hashes for the same data. + # + # This only matters for object dtypes. + obj = Series(list("abc")) + + a = hash_pandas_object(obj, hash_key="9876543210123456") + b = hash_pandas_object(obj, hash_key="9876543210123465") + + assert (a != b).all() + + +def test_df_hash_keys(): + # DataFrame version of the test_hash_keys. + # https://github.com/pandas-dev/pandas/issues/41404 + obj = DataFrame({"x": np.arange(3), "y": list("abc")}) + + a = hash_pandas_object(obj, hash_key="9876543210123456") + b = hash_pandas_object(obj, hash_key="9876543210123465") + + assert (a != b).all() + + +def test_df_encoding(): + # Check that DataFrame recognizes optional encoding. + # https://github.com/pandas-dev/pandas/issues/41404 + # https://github.com/pandas-dev/pandas/pull/42049 + obj = DataFrame({"x": np.arange(3), "y": list("a+c")}) + + a = hash_pandas_object(obj, encoding="utf8") + b = hash_pandas_object(obj, encoding="utf7") + + # Note that the "+" is encoded as "+-" in utf-7. + assert a[0] == b[0] + assert a[1] != b[1] + assert a[2] == b[2] + + +def test_invalid_key(): + # This only matters for object dtypes. + msg = "key should be a 16-byte string encoded" + + with pytest.raises(ValueError, match=msg): + hash_pandas_object(Series(list("abc")), hash_key="foo") + + +def test_already_encoded(index): + # If already encoded, then ok. + obj = Series(list("abc")).str.encode("utf8") + a = hash_pandas_object(obj, index=index) + b = hash_pandas_object(obj, index=index) + tm.assert_series_equal(a, b) + + +def test_alternate_encoding(index): + obj = Series(list("abc")) + a = hash_pandas_object(obj, index=index) + b = hash_pandas_object(obj, index=index) + tm.assert_series_equal(a, b) + + +@pytest.mark.parametrize("l_exp", range(8)) +@pytest.mark.parametrize("l_add", [0, 1]) +def test_same_len_hash_collisions(l_exp, l_add): + length = 2 ** (l_exp + 8) + l_add + idx = np.array([str(i) for i in range(length)], dtype=object) + + result = hash_array(idx, "utf8") + assert not result[0] == result[1] + + +def test_hash_collisions(): + # Hash collisions are bad. + # + # https://github.com/pandas-dev/pandas/issues/14711#issuecomment-264885726 + hashes = [ + "Ingrid-9Z9fKIZmkO7i7Cn51Li34pJm44fgX6DYGBNj3VPlOH50m7HnBlPxfIwFMrcNJNMP6PSgLmwWnInciMWrCSAlLEvt7JkJl4IxiMrVbXSa8ZQoVaq5xoQPjltuJEfwdNlO6jo8qRRHvD8sBEBMQASrRa6TsdaPTPCBo3nwIBpE7YzzmyH0vMBhjQZLx1aCT7faSEx7PgFxQhHdKFWROcysamgy9iVj8DO2Fmwg1NNl93rIAqC3mdqfrCxrzfvIY8aJdzin2cHVzy3QUJxZgHvtUtOLxoqnUHsYbNTeq0xcLXpTZEZCxD4PGubIuCNf32c33M7HFsnjWSEjE2yVdWKhmSVodyF8hFYVmhYnMCztQnJrt3O8ZvVRXd5IKwlLexiSp4h888w7SzAIcKgc3g5XQJf6MlSMftDXm9lIsE1mJNiJEv6uY6pgvC3fUPhatlR5JPpVAHNSbSEE73MBzJrhCAbOLXQumyOXigZuPoME7QgJcBalliQol7YZ9", + "Tim-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", + ] + + # These should be different. + result1 = hash_array(np.asarray(hashes[0:1], dtype=object), "utf8") + expected1 = np.array([14963968704024874985], dtype=np.uint64) + tm.assert_numpy_array_equal(result1, expected1) + + result2 = hash_array(np.asarray(hashes[1:2], dtype=object), "utf8") + expected2 = np.array([16428432627716348016], dtype=np.uint64) + tm.assert_numpy_array_equal(result2, expected2) + + result = hash_array(np.asarray(hashes, dtype=object), "utf8") + tm.assert_numpy_array_equal(result, np.concatenate([expected1, expected2], axis=0)) + + +@pytest.mark.parametrize( + "data, result_data", + [ + [[tuple("1"), tuple("2")], [10345501319357378243, 8331063931016360761]], + [[(1,), (2,)], [9408946347443669104, 3278256261030523334]], + ], +) +def test_hash_with_tuple(data, result_data): + # GH#28969 array containing a tuple raises on call to arr.astype(str) + # apparently a numpy bug github.com/numpy/numpy/issues/9441 + + df = DataFrame({"data": data}) + result = hash_pandas_object(df) + expected = Series(result_data, dtype=np.uint64) + tm.assert_series_equal(result, expected) + + +def test_hashable_tuple_args(): + # require that the elements of such tuples are themselves hashable + + df3 = DataFrame( + { + "data": [ + ( + 1, + [], + ), + ( + 2, + {}, + ), + ] + } + ) + with pytest.raises(TypeError, match="unhashable type: 'list'"): + hash_pandas_object(df3) + + +def test_hash_object_none_key(): + # https://github.com/pandas-dev/pandas/issues/30887 + result = pd.util.hash_pandas_object(Series(["a", "b"]), hash_key=None) + expected = Series([4578374827886788867, 17338122309987883691], dtype="uint64") + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_numba.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_numba.py new file mode 100644 index 0000000000000000000000000000000000000000..27b68ff0f60447e6695d786de9a72ecbb59f7884 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_numba.py @@ -0,0 +1,12 @@ +import pytest + +import pandas.util._test_decorators as td + +from pandas import option_context + + +@td.skip_if_installed("numba") +def test_numba_not_installed_option_context(): + with pytest.raises(ImportError, match="Missing optional"): + with option_context("compute.use_numba", True): + pass diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_rewrite_warning.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_rewrite_warning.py new file mode 100644 index 0000000000000000000000000000000000000000..f847a06d8ea8d7fa75aac1de9025a5bd29bedf37 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_rewrite_warning.py @@ -0,0 +1,39 @@ +import warnings + +import pytest + +from pandas.util._exceptions import rewrite_warning + +import pandas._testing as tm + + +@pytest.mark.parametrize( + "target_category, target_message, hit", + [ + (FutureWarning, "Target message", True), + (FutureWarning, "Target", True), + (FutureWarning, "get mess", True), + (FutureWarning, "Missed message", False), + (DeprecationWarning, "Target message", False), + ], +) +@pytest.mark.parametrize( + "new_category", + [ + None, + DeprecationWarning, + ], +) +def test_rewrite_warning(target_category, target_message, hit, new_category): + new_message = "Rewritten message" + if hit: + expected_category = new_category if new_category else target_category + expected_message = new_message + else: + expected_category = FutureWarning + expected_message = "Target message" + with tm.assert_produces_warning(expected_category, match=expected_message): + with rewrite_warning( + target_message, target_category, new_message, new_category + ): + warnings.warn(message="Target message", category=FutureWarning) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_shares_memory.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_shares_memory.py new file mode 100644 index 0000000000000000000000000000000000000000..8f1ac93b40247050418a5c488a2035f41e6eb0a4 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_shares_memory.py @@ -0,0 +1,32 @@ +import numpy as np + +import pandas.util._test_decorators as td + +import pandas as pd +import pandas._testing as tm + + +def test_shares_memory_interval(): + obj = pd.interval_range(1, 5) + + assert tm.shares_memory(obj, obj) + assert tm.shares_memory(obj, obj._data) + assert tm.shares_memory(obj, obj[::-1]) + assert tm.shares_memory(obj, obj[:2]) + + assert not tm.shares_memory(obj, obj._data.copy()) + + +@td.skip_if_no("pyarrow") +def test_shares_memory_string(): + # GH#55823 + import pyarrow as pa + + obj = pd.array(["a", "b"], dtype=pd.StringDtype("pyarrow", na_value=pd.NA)) + assert tm.shares_memory(obj, obj) + + obj = pd.array(["a", "b"], dtype=pd.StringDtype("pyarrow", na_value=np.nan)) + assert tm.shares_memory(obj, obj) + + obj = pd.array(["a", "b"], dtype=pd.ArrowDtype(pa.string())) + assert tm.shares_memory(obj, obj) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_show_versions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_show_versions.py new file mode 100644 index 0000000000000000000000000000000000000000..72c9db23b210880793f37227c99e99e804800f08 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_show_versions.py @@ -0,0 +1,81 @@ +import json +import os +import re + +from pandas.util._print_versions import ( + _get_dependency_info, + _get_sys_info, +) + +import pandas as pd + + +def test_show_versions(tmpdir): + # GH39701 + as_json = os.path.join(tmpdir, "test_output.json") + + pd.show_versions(as_json=as_json) + + with open(as_json, encoding="utf-8") as fd: + # check if file output is valid JSON, will raise an exception if not + result = json.load(fd) + + # Basic check that each version element is found in output + expected = { + "system": _get_sys_info(), + "dependencies": _get_dependency_info(), + } + + assert result == expected + + +def test_show_versions_console_json(capsys): + # GH39701 + pd.show_versions(as_json=True) + stdout = capsys.readouterr().out + + # check valid json is printed to the console if as_json is True + result = json.loads(stdout) + + # Basic check that each version element is found in output + expected = { + "system": _get_sys_info(), + "dependencies": _get_dependency_info(), + } + + assert result == expected + + +def test_show_versions_console(capsys): + # gh-32041 + # gh-32041 + pd.show_versions(as_json=False) + result = capsys.readouterr().out + + # check header + assert "INSTALLED VERSIONS" in result + + # check full commit hash + assert re.search(r"commit\s*:\s[0-9a-f]{40}\n", result) + + # check required dependency + # 2020-12-09 npdev has "dirty" in the tag + # 2022-05-25 npdev released with RC wo/ "dirty". + # Just ensure we match [0-9]+\..* since npdev version is variable + assert re.search(r"numpy\s*:\s[0-9]+\..*\n", result) + + # check optional dependency + assert re.search(r"pyarrow\s*:\s([0-9]+.*|None)\n", result) + + +def test_json_output_match(capsys, tmpdir): + # GH39701 + pd.show_versions(as_json=True) + result_console = capsys.readouterr().out + + out_path = os.path.join(tmpdir, "test_json.json") + pd.show_versions(as_json=out_path) + with open(out_path, encoding="utf-8") as out_fd: + result_file = out_fd.read() + + assert result_console == result_file diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_util.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_util.py new file mode 100644 index 0000000000000000000000000000000000000000..dfb8587d3924e1441ac9da0aeeaa5585c6b4fe6c --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_util.py @@ -0,0 +1,58 @@ +import os + +import pytest + +from pandas import ( + array, + compat, +) +import pandas._testing as tm + + +def test_numpy_err_state_is_default(): + expected = {"over": "warn", "divide": "warn", "invalid": "warn", "under": "ignore"} + import numpy as np + + # The error state should be unchanged after that import. + assert np.geterr() == expected + + +def test_convert_rows_list_to_csv_str(): + rows_list = ["aaa", "bbb", "ccc"] + ret = tm.convert_rows_list_to_csv_str(rows_list) + + if compat.is_platform_windows(): + expected = "aaa\r\nbbb\r\nccc\r\n" + else: + expected = "aaa\nbbb\nccc\n" + + assert ret == expected + + +@pytest.mark.parametrize("strict_data_files", [True, False]) +def test_datapath_missing(datapath): + with pytest.raises(ValueError, match="Could not find file"): + datapath("not_a_file") + + +def test_datapath(datapath): + args = ("io", "data", "csv", "iris.csv") + + result = datapath(*args) + expected = os.path.join(os.path.dirname(os.path.dirname(__file__)), *args) + + assert result == expected + + +def test_external_error_raised(): + with tm.external_error_raised(TypeError): + raise TypeError("Should not check this error message, so it will pass") + + +def test_is_sorted(): + arr = array([1, 2, 3], dtype="Int64") + tm.assert_is_sorted(arr) + + arr = array([4, 2, 3], dtype="Int64") + with pytest.raises(AssertionError, match="ExtensionArray are different"): + tm.assert_is_sorted(arr) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_args.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_args.py new file mode 100644 index 0000000000000000000000000000000000000000..eef0931ec28efd02e3db7a85b0b3260742c1ff2d --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_args.py @@ -0,0 +1,70 @@ +import pytest + +from pandas.util._validators import validate_args + + +@pytest.fixture +def _fname(): + return "func" + + +def test_bad_min_fname_arg_count(_fname): + msg = "'max_fname_arg_count' must be non-negative" + + with pytest.raises(ValueError, match=msg): + validate_args(_fname, (None,), -1, "foo") + + +def test_bad_arg_length_max_value_single(_fname): + args = (None, None) + compat_args = ("foo",) + + min_fname_arg_count = 0 + max_length = len(compat_args) + min_fname_arg_count + actual_length = len(args) + min_fname_arg_count + msg = ( + rf"{_fname}\(\) takes at most {max_length} " + rf"argument \({actual_length} given\)" + ) + + with pytest.raises(TypeError, match=msg): + validate_args(_fname, args, min_fname_arg_count, compat_args) + + +def test_bad_arg_length_max_value_multiple(_fname): + args = (None, None) + compat_args = {"foo": None} + + min_fname_arg_count = 2 + max_length = len(compat_args) + min_fname_arg_count + actual_length = len(args) + min_fname_arg_count + msg = ( + rf"{_fname}\(\) takes at most {max_length} " + rf"arguments \({actual_length} given\)" + ) + + with pytest.raises(TypeError, match=msg): + validate_args(_fname, args, min_fname_arg_count, compat_args) + + +@pytest.mark.parametrize("i", range(1, 3)) +def test_not_all_defaults(i, _fname): + bad_arg = "foo" + msg = ( + f"the '{bad_arg}' parameter is not supported " + rf"in the pandas implementation of {_fname}\(\)" + ) + + compat_args = {"foo": 2, "bar": -1, "baz": 3} + arg_vals = (1, -1, 3) + + with pytest.raises(ValueError, match=msg): + validate_args(_fname, arg_vals[:i], 2, compat_args) + + +def test_validation(_fname): + # No exceptions should be raised. + validate_args(_fname, (None,), 2, {"out": None}) + + compat_args = {"axis": 1, "out": None} + validate_args(_fname, (1, None), 2, compat_args) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_args_and_kwargs.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_args_and_kwargs.py new file mode 100644 index 0000000000000000000000000000000000000000..215026d648471c04cb8751506c03626fda73fc68 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_args_and_kwargs.py @@ -0,0 +1,84 @@ +import pytest + +from pandas.util._validators import validate_args_and_kwargs + + +@pytest.fixture +def _fname(): + return "func" + + +def test_invalid_total_length_max_length_one(_fname): + compat_args = ("foo",) + kwargs = {"foo": "FOO"} + args = ("FoO", "BaZ") + + min_fname_arg_count = 0 + max_length = len(compat_args) + min_fname_arg_count + actual_length = len(kwargs) + len(args) + min_fname_arg_count + + msg = ( + rf"{_fname}\(\) takes at most {max_length} " + rf"argument \({actual_length} given\)" + ) + + with pytest.raises(TypeError, match=msg): + validate_args_and_kwargs(_fname, args, kwargs, min_fname_arg_count, compat_args) + + +def test_invalid_total_length_max_length_multiple(_fname): + compat_args = ("foo", "bar", "baz") + kwargs = {"foo": "FOO", "bar": "BAR"} + args = ("FoO", "BaZ") + + min_fname_arg_count = 2 + max_length = len(compat_args) + min_fname_arg_count + actual_length = len(kwargs) + len(args) + min_fname_arg_count + + msg = ( + rf"{_fname}\(\) takes at most {max_length} " + rf"arguments \({actual_length} given\)" + ) + + with pytest.raises(TypeError, match=msg): + validate_args_and_kwargs(_fname, args, kwargs, min_fname_arg_count, compat_args) + + +@pytest.mark.parametrize("args,kwargs", [((), {"foo": -5, "bar": 2}), ((-5, 2), {})]) +def test_missing_args_or_kwargs(args, kwargs, _fname): + bad_arg = "bar" + min_fname_arg_count = 2 + + compat_args = {"foo": -5, bad_arg: 1} + + msg = ( + rf"the '{bad_arg}' parameter is not supported " + rf"in the pandas implementation of {_fname}\(\)" + ) + + with pytest.raises(ValueError, match=msg): + validate_args_and_kwargs(_fname, args, kwargs, min_fname_arg_count, compat_args) + + +def test_duplicate_argument(_fname): + min_fname_arg_count = 2 + + compat_args = {"foo": None, "bar": None, "baz": None} + kwargs = {"foo": None, "bar": None} + args = (None,) # duplicate value for "foo" + + msg = rf"{_fname}\(\) got multiple values for keyword argument 'foo'" + + with pytest.raises(TypeError, match=msg): + validate_args_and_kwargs(_fname, args, kwargs, min_fname_arg_count, compat_args) + + +def test_validation(_fname): + # No exceptions should be raised. + compat_args = {"foo": 1, "bar": None, "baz": -2} + kwargs = {"baz": -2} + + args = (1, None) + min_fname_arg_count = 2 + + validate_args_and_kwargs(_fname, args, kwargs, min_fname_arg_count, compat_args) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_inclusive.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_inclusive.py new file mode 100644 index 0000000000000000000000000000000000000000..c1254c614ab305c447090b148ea6a036569f76e6 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_inclusive.py @@ -0,0 +1,40 @@ +import numpy as np +import pytest + +from pandas.util._validators import validate_inclusive + +import pandas as pd + + +@pytest.mark.parametrize( + "invalid_inclusive", + ( + "ccc", + 2, + object(), + None, + np.nan, + pd.NA, + pd.DataFrame(), + ), +) +def test_invalid_inclusive(invalid_inclusive): + with pytest.raises( + ValueError, + match="Inclusive has to be either 'both', 'neither', 'left' or 'right'", + ): + validate_inclusive(invalid_inclusive) + + +@pytest.mark.parametrize( + "valid_inclusive, expected_tuple", + ( + ("left", (True, False)), + ("right", (False, True)), + ("both", (True, True)), + ("neither", (False, False)), + ), +) +def test_valid_inclusive(valid_inclusive, expected_tuple): + resultant_tuple = validate_inclusive(valid_inclusive) + assert expected_tuple == resultant_tuple diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_kwargs.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_kwargs.py new file mode 100644 index 0000000000000000000000000000000000000000..dba447e30cf579c9f2f5c0bd917a4e0837143ed3 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/util/test_validate_kwargs.py @@ -0,0 +1,69 @@ +import pytest + +from pandas.util._validators import ( + validate_bool_kwarg, + validate_kwargs, +) + + +@pytest.fixture +def _fname(): + return "func" + + +def test_bad_kwarg(_fname): + good_arg = "f" + bad_arg = good_arg + "o" + + compat_args = {good_arg: "foo", bad_arg + "o": "bar"} + kwargs = {good_arg: "foo", bad_arg: "bar"} + + msg = rf"{_fname}\(\) got an unexpected keyword argument '{bad_arg}'" + + with pytest.raises(TypeError, match=msg): + validate_kwargs(_fname, kwargs, compat_args) + + +@pytest.mark.parametrize("i", range(1, 3)) +def test_not_all_none(i, _fname): + bad_arg = "foo" + msg = ( + rf"the '{bad_arg}' parameter is not supported " + rf"in the pandas implementation of {_fname}\(\)" + ) + + compat_args = {"foo": 1, "bar": "s", "baz": None} + + kwarg_keys = ("foo", "bar", "baz") + kwarg_vals = (2, "s", None) + + kwargs = dict(zip(kwarg_keys[:i], kwarg_vals[:i])) + + with pytest.raises(ValueError, match=msg): + validate_kwargs(_fname, kwargs, compat_args) + + +def test_validation(_fname): + # No exceptions should be raised. + compat_args = {"f": None, "b": 1, "ba": "s"} + + kwargs = {"f": None, "b": 1} + validate_kwargs(_fname, kwargs, compat_args) + + +@pytest.mark.parametrize("name", ["inplace", "copy"]) +@pytest.mark.parametrize("value", [1, "True", [1, 2, 3], 5.0]) +def test_validate_bool_kwarg_fail(name, value): + msg = ( + f'For argument "{name}" expected type bool, ' + f"received type {type(value).__name__}" + ) + + with pytest.raises(ValueError, match=msg): + validate_bool_kwarg(value, name) + + +@pytest.mark.parametrize("name", ["inplace", "copy"]) +@pytest.mark.parametrize("value", [True, False, None]) +def test_validate_bool_kwarg(name, value): + assert validate_bool_kwarg(value, name) == value diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/conftest.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/conftest.py new file mode 100644 index 0000000000000000000000000000000000000000..73ab470ab97a77a65001d62aa05be7d372fbc1f5 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/conftest.py @@ -0,0 +1,146 @@ +from datetime import ( + datetime, + timedelta, +) + +import numpy as np +import pytest + +import pandas.util._test_decorators as td + +from pandas import ( + DataFrame, + Series, + bdate_range, +) + + +@pytest.fixture(params=[True, False]) +def raw(request): + """raw keyword argument for rolling.apply""" + return request.param + + +@pytest.fixture( + params=[ + "sum", + "mean", + "median", + "max", + "min", + "var", + "std", + "kurt", + "skew", + "count", + "sem", + ] +) +def arithmetic_win_operators(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def center(request): + return request.param + + +@pytest.fixture(params=[None, 1]) +def min_periods(request): + return request.param + + +@pytest.fixture(params=[True, False]) +def parallel(request): + """parallel keyword argument for numba.jit""" + return request.param + + +# Can parameterize nogil & nopython over True | False, but limiting per +# https://github.com/pandas-dev/pandas/pull/41971#issuecomment-860607472 + + +@pytest.fixture(params=[False]) +def nogil(request): + """nogil keyword argument for numba.jit""" + return request.param + + +@pytest.fixture(params=[True]) +def nopython(request): + """nopython keyword argument for numba.jit""" + return request.param + + +@pytest.fixture(params=[True, False]) +def adjust(request): + """adjust keyword argument for ewm""" + return request.param + + +@pytest.fixture(params=[True, False]) +def ignore_na(request): + """ignore_na keyword argument for ewm""" + return request.param + + +@pytest.fixture(params=[True, False]) +def numeric_only(request): + """numeric_only keyword argument""" + return request.param + + +@pytest.fixture( + params=[ + pytest.param("numba", marks=[td.skip_if_no("numba"), pytest.mark.single_cpu]), + "cython", + ] +) +def engine(request): + """engine keyword argument for rolling.apply""" + return request.param + + +@pytest.fixture( + params=[ + pytest.param( + ("numba", True), marks=[td.skip_if_no("numba"), pytest.mark.single_cpu] + ), + ("cython", True), + ("cython", False), + ] +) +def engine_and_raw(request): + """engine and raw keyword arguments for rolling.apply""" + return request.param + + +@pytest.fixture(params=["1 day", timedelta(days=1), np.timedelta64(1, "D")]) +def halflife_with_times(request): + """Halflife argument for EWM when times is specified.""" + return request.param + + +@pytest.fixture +def series(): + """Make mocked series as fixture.""" + arr = np.random.default_rng(2).standard_normal(100) + locs = np.arange(20, 40) + arr[locs] = np.nan + series = Series(arr, index=bdate_range(datetime(2009, 1, 1), periods=100)) + return series + + +@pytest.fixture +def frame(): + """Make mocked frame as fixture.""" + return DataFrame( + np.random.default_rng(2).standard_normal((100, 10)), + index=bdate_range(datetime(2009, 1, 1), periods=100), + ) + + +@pytest.fixture(params=[None, 1, 2, 5, 10]) +def step(request): + """step keyword argument for rolling window operations.""" + return request.param diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/conftest.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/conftest.py new file mode 100644 index 0000000000000000000000000000000000000000..fccf80c3c7a58d691b818709e51a9f6642956a33 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/conftest.py @@ -0,0 +1,72 @@ +import itertools + +import numpy as np +import pytest + +from pandas import ( + DataFrame, + Series, + notna, +) + + +def create_series(): + return [ + Series(dtype=np.float64, name="a"), + Series([np.nan] * 5), + Series([1.0] * 5), + Series(range(5, 0, -1)), + Series(range(5)), + Series([np.nan, 1.0, np.nan, 1.0, 1.0]), + Series([np.nan, 1.0, np.nan, 2.0, 3.0]), + Series([np.nan, 1.0, np.nan, 3.0, 2.0]), + ] + + +def create_dataframes(): + return [ + DataFrame(columns=["a", "a"]), + DataFrame(np.arange(15).reshape((5, 3)), columns=["a", "a", 99]), + ] + [DataFrame(s) for s in create_series()] + + +def is_constant(x): + values = x.values.ravel("K") + return len(set(values[notna(values)])) == 1 + + +@pytest.fixture( + params=( + obj + for obj in itertools.chain(create_series(), create_dataframes()) + if is_constant(obj) + ), +) +def consistent_data(request): + return request.param + + +@pytest.fixture(params=create_series()) +def series_data(request): + return request.param + + +@pytest.fixture(params=itertools.chain(create_series(), create_dataframes())) +def all_data(request): + """ + Test: + - Empty Series / DataFrame + - All NaN + - All consistent value + - Monotonically decreasing + - Monotonically increasing + - Monotonically consistent with NaNs + - Monotonically increasing with NaNs + - Monotonically decreasing with NaNs + """ + return request.param + + +@pytest.fixture(params=[0, 2]) +def min_periods(request): + return request.param diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_ewm.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_ewm.py new file mode 100644 index 0000000000000000000000000000000000000000..49dee50954f4f42365d1ee4525fa48a3e18877fe --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_ewm.py @@ -0,0 +1,243 @@ +import numpy as np +import pytest + +from pandas import ( + DataFrame, + Series, + concat, +) +import pandas._testing as tm + + +def create_mock_weights(obj, com, adjust, ignore_na): + if isinstance(obj, DataFrame): + if not len(obj.columns): + return DataFrame(index=obj.index, columns=obj.columns) + w = concat( + [ + create_mock_series_weights( + obj.iloc[:, i], com=com, adjust=adjust, ignore_na=ignore_na + ) + for i in range(len(obj.columns)) + ], + axis=1, + ) + w.index = obj.index + w.columns = obj.columns + return w + else: + return create_mock_series_weights(obj, com, adjust, ignore_na) + + +def create_mock_series_weights(s, com, adjust, ignore_na): + w = Series(np.nan, index=s.index, name=s.name) + alpha = 1.0 / (1.0 + com) + if adjust: + count = 0 + for i in range(len(s)): + if s.iat[i] == s.iat[i]: + w.iat[i] = pow(1.0 / (1.0 - alpha), count) + count += 1 + elif not ignore_na: + count += 1 + else: + sum_wts = 0.0 + prev_i = -1 + count = 0 + for i in range(len(s)): + if s.iat[i] == s.iat[i]: + if prev_i == -1: + w.iat[i] = 1.0 + else: + w.iat[i] = alpha * sum_wts / pow(1.0 - alpha, count - prev_i) + sum_wts += w.iat[i] + prev_i = count + count += 1 + elif not ignore_na: + count += 1 + return w + + +def test_ewm_consistency_mean(all_data, adjust, ignore_na, min_periods): + com = 3.0 + + result = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).mean() + weights = create_mock_weights(all_data, com=com, adjust=adjust, ignore_na=ignore_na) + expected = all_data.multiply(weights).cumsum().divide(weights.cumsum()).ffill() + expected[ + all_data.expanding().count() < (max(min_periods, 1) if min_periods else 1) + ] = np.nan + tm.assert_equal(result, expected.astype("float64")) + + +def test_ewm_consistency_consistent(consistent_data, adjust, ignore_na, min_periods): + com = 3.0 + + count_x = consistent_data.expanding().count() + mean_x = consistent_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).mean() + # check that correlation of a series with itself is either 1 or NaN + corr_x_x = consistent_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).corr(consistent_data) + exp = ( + consistent_data.max() + if isinstance(consistent_data, Series) + else consistent_data.max().max() + ) + + # check mean of constant series + expected = consistent_data * np.nan + expected[count_x >= max(min_periods, 1)] = exp + tm.assert_equal(mean_x, expected) + + # check correlation of constant series with itself is NaN + expected[:] = np.nan + tm.assert_equal(corr_x_x, expected) + + +def test_ewm_consistency_var_debiasing_factors( + all_data, adjust, ignore_na, min_periods +): + com = 3.0 + + # check variance debiasing factors + var_unbiased_x = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).var(bias=False) + var_biased_x = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).var(bias=True) + + weights = create_mock_weights(all_data, com=com, adjust=adjust, ignore_na=ignore_na) + cum_sum = weights.cumsum().ffill() + cum_sum_sq = (weights * weights).cumsum().ffill() + numerator = cum_sum * cum_sum + denominator = numerator - cum_sum_sq + denominator[denominator <= 0.0] = np.nan + var_debiasing_factors_x = numerator / denominator + + tm.assert_equal(var_unbiased_x, var_biased_x * var_debiasing_factors_x) + + +@pytest.mark.parametrize("bias", [True, False]) +def test_moments_consistency_var(all_data, adjust, ignore_na, min_periods, bias): + com = 3.0 + + mean_x = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).mean() + var_x = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).var(bias=bias) + assert not (var_x < 0).any().any() + + if bias: + # check that biased var(x) == mean(x^2) - mean(x)^2 + mean_x2 = ( + (all_data * all_data) + .ewm(com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na) + .mean() + ) + tm.assert_equal(var_x, mean_x2 - (mean_x * mean_x)) + + +@pytest.mark.parametrize("bias", [True, False]) +def test_moments_consistency_var_constant( + consistent_data, adjust, ignore_na, min_periods, bias +): + com = 3.0 + count_x = consistent_data.expanding(min_periods=min_periods).count() + var_x = consistent_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).var(bias=bias) + + # check that variance of constant series is identically 0 + assert not (var_x > 0).any().any() + expected = consistent_data * np.nan + expected[count_x >= max(min_periods, 1)] = 0.0 + if not bias: + expected[count_x < 2] = np.nan + tm.assert_equal(var_x, expected) + + +@pytest.mark.parametrize("bias", [True, False]) +def test_ewm_consistency_std(all_data, adjust, ignore_na, min_periods, bias): + com = 3.0 + var_x = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).var(bias=bias) + assert not (var_x < 0).any().any() + + std_x = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).std(bias=bias) + assert not (std_x < 0).any().any() + + # check that var(x) == std(x)^2 + tm.assert_equal(var_x, std_x * std_x) + + cov_x_x = all_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).cov(all_data, bias=bias) + assert not (cov_x_x < 0).any().any() + + # check that var(x) == cov(x, x) + tm.assert_equal(var_x, cov_x_x) + + +@pytest.mark.parametrize("bias", [True, False]) +def test_ewm_consistency_series_cov_corr( + series_data, adjust, ignore_na, min_periods, bias +): + com = 3.0 + + var_x_plus_y = ( + (series_data + series_data) + .ewm(com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na) + .var(bias=bias) + ) + var_x = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).var(bias=bias) + var_y = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).var(bias=bias) + cov_x_y = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).cov(series_data, bias=bias) + # check that cov(x, y) == (var(x+y) - var(x) - + # var(y)) / 2 + tm.assert_equal(cov_x_y, 0.5 * (var_x_plus_y - var_x - var_y)) + + # check that corr(x, y) == cov(x, y) / (std(x) * + # std(y)) + corr_x_y = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).corr(series_data) + std_x = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).std(bias=bias) + std_y = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).std(bias=bias) + tm.assert_equal(corr_x_y, cov_x_y / (std_x * std_y)) + + if bias: + # check that biased cov(x, y) == mean(x*y) - + # mean(x)*mean(y) + mean_x = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).mean() + mean_y = series_data.ewm( + com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na + ).mean() + mean_x_times_y = ( + (series_data * series_data) + .ewm(com=com, min_periods=min_periods, adjust=adjust, ignore_na=ignore_na) + .mean() + ) + tm.assert_equal(cov_x_y, mean_x_times_y - (mean_x * mean_y)) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_expanding.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_expanding.py new file mode 100644 index 0000000000000000000000000000000000000000..7d2fa1ad5d21175dcfafe9a57dd8169fc4413360 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_expanding.py @@ -0,0 +1,144 @@ +import numpy as np +import pytest + +from pandas import Series +import pandas._testing as tm + + +def no_nans(x): + return x.notna().all().all() + + +def all_na(x): + return x.isnull().all().all() + + +@pytest.mark.parametrize("f", [lambda v: Series(v).sum(), np.nansum, np.sum]) +def test_expanding_apply_consistency_sum_nans(request, all_data, min_periods, f): + if f is np.sum: + if not no_nans(all_data) and not ( + all_na(all_data) and not all_data.empty and min_periods > 0 + ): + request.applymarker( + pytest.mark.xfail(reason="np.sum has different behavior with NaNs") + ) + expanding_f_result = all_data.expanding(min_periods=min_periods).sum() + expanding_apply_f_result = all_data.expanding(min_periods=min_periods).apply( + func=f, raw=True + ) + tm.assert_equal(expanding_f_result, expanding_apply_f_result) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_moments_consistency_var(all_data, min_periods, ddof): + var_x = all_data.expanding(min_periods=min_periods).var(ddof=ddof) + assert not (var_x < 0).any().any() + + if ddof == 0: + # check that biased var(x) == mean(x^2) - mean(x)^2 + mean_x2 = (all_data * all_data).expanding(min_periods=min_periods).mean() + mean_x = all_data.expanding(min_periods=min_periods).mean() + tm.assert_equal(var_x, mean_x2 - (mean_x * mean_x)) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_moments_consistency_var_constant(consistent_data, min_periods, ddof): + count_x = consistent_data.expanding(min_periods=min_periods).count() + var_x = consistent_data.expanding(min_periods=min_periods).var(ddof=ddof) + + # check that variance of constant series is identically 0 + assert not (var_x > 0).any().any() + expected = consistent_data * np.nan + expected[count_x >= max(min_periods, 1)] = 0.0 + if ddof == 1: + expected[count_x < 2] = np.nan + tm.assert_equal(var_x, expected) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_expanding_consistency_var_std_cov(all_data, min_periods, ddof): + var_x = all_data.expanding(min_periods=min_periods).var(ddof=ddof) + assert not (var_x < 0).any().any() + + std_x = all_data.expanding(min_periods=min_periods).std(ddof=ddof) + assert not (std_x < 0).any().any() + + # check that var(x) == std(x)^2 + tm.assert_equal(var_x, std_x * std_x) + + cov_x_x = all_data.expanding(min_periods=min_periods).cov(all_data, ddof=ddof) + assert not (cov_x_x < 0).any().any() + + # check that var(x) == cov(x, x) + tm.assert_equal(var_x, cov_x_x) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_expanding_consistency_series_cov_corr(series_data, min_periods, ddof): + var_x_plus_y = ( + (series_data + series_data).expanding(min_periods=min_periods).var(ddof=ddof) + ) + var_x = series_data.expanding(min_periods=min_periods).var(ddof=ddof) + var_y = series_data.expanding(min_periods=min_periods).var(ddof=ddof) + cov_x_y = series_data.expanding(min_periods=min_periods).cov(series_data, ddof=ddof) + # check that cov(x, y) == (var(x+y) - var(x) - + # var(y)) / 2 + tm.assert_equal(cov_x_y, 0.5 * (var_x_plus_y - var_x - var_y)) + + # check that corr(x, y) == cov(x, y) / (std(x) * + # std(y)) + corr_x_y = series_data.expanding(min_periods=min_periods).corr(series_data) + std_x = series_data.expanding(min_periods=min_periods).std(ddof=ddof) + std_y = series_data.expanding(min_periods=min_periods).std(ddof=ddof) + tm.assert_equal(corr_x_y, cov_x_y / (std_x * std_y)) + + if ddof == 0: + # check that biased cov(x, y) == mean(x*y) - + # mean(x)*mean(y) + mean_x = series_data.expanding(min_periods=min_periods).mean() + mean_y = series_data.expanding(min_periods=min_periods).mean() + mean_x_times_y = ( + (series_data * series_data).expanding(min_periods=min_periods).mean() + ) + tm.assert_equal(cov_x_y, mean_x_times_y - (mean_x * mean_y)) + + +def test_expanding_consistency_mean(all_data, min_periods): + result = all_data.expanding(min_periods=min_periods).mean() + expected = ( + all_data.expanding(min_periods=min_periods).sum() + / all_data.expanding(min_periods=min_periods).count() + ) + tm.assert_equal(result, expected.astype("float64")) + + +def test_expanding_consistency_constant(consistent_data, min_periods): + count_x = consistent_data.expanding().count() + mean_x = consistent_data.expanding(min_periods=min_periods).mean() + # check that correlation of a series with itself is either 1 or NaN + corr_x_x = consistent_data.expanding(min_periods=min_periods).corr(consistent_data) + + exp = ( + consistent_data.max() + if isinstance(consistent_data, Series) + else consistent_data.max().max() + ) + + # check mean of constant series + expected = consistent_data * np.nan + expected[count_x >= max(min_periods, 1)] = exp + tm.assert_equal(mean_x, expected) + + # check correlation of constant series with itself is NaN + expected[:] = np.nan + tm.assert_equal(corr_x_x, expected) + + +def test_expanding_consistency_var_debiasing_factors(all_data, min_periods): + # check variance debiasing factors + var_unbiased_x = all_data.expanding(min_periods=min_periods).var() + var_biased_x = all_data.expanding(min_periods=min_periods).var(ddof=0) + var_debiasing_factors_x = all_data.expanding().count() / ( + all_data.expanding().count() - 1.0 + ).replace(0.0, np.nan) + tm.assert_equal(var_unbiased_x, var_biased_x * var_debiasing_factors_x) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_rolling.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_rolling.py new file mode 100644 index 0000000000000000000000000000000000000000..be22338c00cb28fb4fbd1bfe7f4b6163e239a432 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/moments/test_moments_consistency_rolling.py @@ -0,0 +1,244 @@ +import numpy as np +import pytest + +from pandas import Series +import pandas._testing as tm + + +def no_nans(x): + return x.notna().all().all() + + +def all_na(x): + return x.isnull().all().all() + + +@pytest.fixture(params=[(1, 0), (5, 1)]) +def rolling_consistency_cases(request): + """window, min_periods""" + return request.param + + +@pytest.mark.parametrize("f", [lambda v: Series(v).sum(), np.nansum, np.sum]) +def test_rolling_apply_consistency_sum( + request, all_data, rolling_consistency_cases, center, f +): + window, min_periods = rolling_consistency_cases + + if f is np.sum: + if not no_nans(all_data) and not ( + all_na(all_data) and not all_data.empty and min_periods > 0 + ): + request.applymarker( + pytest.mark.xfail(reason="np.sum has different behavior with NaNs") + ) + rolling_f_result = all_data.rolling( + window=window, min_periods=min_periods, center=center + ).sum() + rolling_apply_f_result = all_data.rolling( + window=window, min_periods=min_periods, center=center + ).apply(func=f, raw=True) + tm.assert_equal(rolling_f_result, rolling_apply_f_result) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_moments_consistency_var(all_data, rolling_consistency_cases, center, ddof): + window, min_periods = rolling_consistency_cases + + var_x = all_data.rolling(window=window, min_periods=min_periods, center=center).var( + ddof=ddof + ) + assert not (var_x < 0).any().any() + + if ddof == 0: + # check that biased var(x) == mean(x^2) - mean(x)^2 + mean_x = all_data.rolling( + window=window, min_periods=min_periods, center=center + ).mean() + mean_x2 = ( + (all_data * all_data) + .rolling(window=window, min_periods=min_periods, center=center) + .mean() + ) + tm.assert_equal(var_x, mean_x2 - (mean_x * mean_x)) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_moments_consistency_var_constant( + consistent_data, rolling_consistency_cases, center, ddof +): + window, min_periods = rolling_consistency_cases + + count_x = consistent_data.rolling( + window=window, min_periods=min_periods, center=center + ).count() + var_x = consistent_data.rolling( + window=window, min_periods=min_periods, center=center + ).var(ddof=ddof) + + # check that variance of constant series is identically 0 + assert not (var_x > 0).any().any() + expected = consistent_data * np.nan + expected[count_x >= max(min_periods, 1)] = 0.0 + if ddof == 1: + expected[count_x < 2] = np.nan + tm.assert_equal(var_x, expected) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_rolling_consistency_var_std_cov( + all_data, rolling_consistency_cases, center, ddof +): + window, min_periods = rolling_consistency_cases + + var_x = all_data.rolling(window=window, min_periods=min_periods, center=center).var( + ddof=ddof + ) + assert not (var_x < 0).any().any() + + std_x = all_data.rolling(window=window, min_periods=min_periods, center=center).std( + ddof=ddof + ) + assert not (std_x < 0).any().any() + + # check that var(x) == std(x)^2 + tm.assert_equal(var_x, std_x * std_x) + + cov_x_x = all_data.rolling( + window=window, min_periods=min_periods, center=center + ).cov(all_data, ddof=ddof) + assert not (cov_x_x < 0).any().any() + + # check that var(x) == cov(x, x) + tm.assert_equal(var_x, cov_x_x) + + +@pytest.mark.parametrize("ddof", [0, 1]) +def test_rolling_consistency_series_cov_corr( + series_data, rolling_consistency_cases, center, ddof +): + window, min_periods = rolling_consistency_cases + + var_x_plus_y = ( + (series_data + series_data) + .rolling(window=window, min_periods=min_periods, center=center) + .var(ddof=ddof) + ) + var_x = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).var(ddof=ddof) + var_y = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).var(ddof=ddof) + cov_x_y = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).cov(series_data, ddof=ddof) + # check that cov(x, y) == (var(x+y) - var(x) - + # var(y)) / 2 + tm.assert_equal(cov_x_y, 0.5 * (var_x_plus_y - var_x - var_y)) + + # check that corr(x, y) == cov(x, y) / (std(x) * + # std(y)) + corr_x_y = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).corr(series_data) + std_x = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).std(ddof=ddof) + std_y = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).std(ddof=ddof) + tm.assert_equal(corr_x_y, cov_x_y / (std_x * std_y)) + + if ddof == 0: + # check that biased cov(x, y) == mean(x*y) - + # mean(x)*mean(y) + mean_x = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).mean() + mean_y = series_data.rolling( + window=window, min_periods=min_periods, center=center + ).mean() + mean_x_times_y = ( + (series_data * series_data) + .rolling(window=window, min_periods=min_periods, center=center) + .mean() + ) + tm.assert_equal(cov_x_y, mean_x_times_y - (mean_x * mean_y)) + + +def test_rolling_consistency_mean(all_data, rolling_consistency_cases, center): + window, min_periods = rolling_consistency_cases + + result = all_data.rolling( + window=window, min_periods=min_periods, center=center + ).mean() + expected = ( + all_data.rolling(window=window, min_periods=min_periods, center=center) + .sum() + .divide( + all_data.rolling( + window=window, min_periods=min_periods, center=center + ).count() + ) + ) + tm.assert_equal(result, expected.astype("float64")) + + +def test_rolling_consistency_constant( + consistent_data, rolling_consistency_cases, center +): + window, min_periods = rolling_consistency_cases + + count_x = consistent_data.rolling( + window=window, min_periods=min_periods, center=center + ).count() + mean_x = consistent_data.rolling( + window=window, min_periods=min_periods, center=center + ).mean() + # check that correlation of a series with itself is either 1 or NaN + corr_x_x = consistent_data.rolling( + window=window, min_periods=min_periods, center=center + ).corr(consistent_data) + + exp = ( + consistent_data.max() + if isinstance(consistent_data, Series) + else consistent_data.max().max() + ) + + # check mean of constant series + expected = consistent_data * np.nan + expected[count_x >= max(min_periods, 1)] = exp + tm.assert_equal(mean_x, expected) + + # check correlation of constant series with itself is NaN + expected[:] = np.nan + tm.assert_equal(corr_x_x, expected) + + +def test_rolling_consistency_var_debiasing_factors( + all_data, rolling_consistency_cases, center +): + window, min_periods = rolling_consistency_cases + + # check variance debiasing factors + var_unbiased_x = all_data.rolling( + window=window, min_periods=min_periods, center=center + ).var() + var_biased_x = all_data.rolling( + window=window, min_periods=min_periods, center=center + ).var(ddof=0) + var_debiasing_factors_x = ( + all_data.rolling(window=window, min_periods=min_periods, center=center) + .count() + .divide( + ( + all_data.rolling( + window=window, min_periods=min_periods, center=center + ).count() + - 1.0 + ).replace(0.0, np.nan) + ) + ) + tm.assert_equal(var_unbiased_x, var_biased_x * var_debiasing_factors_x) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_api.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_api.py new file mode 100644 index 0000000000000000000000000000000000000000..948565be36b5be4e729eba034367b91b4b5fc64e --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_api.py @@ -0,0 +1,398 @@ +import numpy as np +import pytest + +from pandas.errors import ( + DataError, + SpecificationError, +) + +from pandas import ( + DataFrame, + Index, + MultiIndex, + Period, + Series, + Timestamp, + concat, + date_range, + timedelta_range, +) +import pandas._testing as tm + + +def test_getitem(step): + frame = DataFrame(np.random.default_rng(2).standard_normal((5, 5))) + r = frame.rolling(window=5, step=step) + tm.assert_index_equal(r._selected_obj.columns, frame[::step].columns) + + r = frame.rolling(window=5, step=step)[1] + assert r._selected_obj.name == frame[::step].columns[1] + + # technically this is allowed + r = frame.rolling(window=5, step=step)[1, 3] + tm.assert_index_equal(r._selected_obj.columns, frame[::step].columns[[1, 3]]) + + r = frame.rolling(window=5, step=step)[[1, 3]] + tm.assert_index_equal(r._selected_obj.columns, frame[::step].columns[[1, 3]]) + + +def test_select_bad_cols(): + df = DataFrame([[1, 2]], columns=["A", "B"]) + g = df.rolling(window=5) + with pytest.raises(KeyError, match="Columns not found: 'C'"): + g[["C"]] + with pytest.raises(KeyError, match="^[^A]+$"): + # A should not be referenced as a bad column... + # will have to rethink regex if you change message! + g[["A", "C"]] + + +def test_attribute_access(): + df = DataFrame([[1, 2]], columns=["A", "B"]) + r = df.rolling(window=5) + tm.assert_series_equal(r.A.sum(), r["A"].sum()) + msg = "'Rolling' object has no attribute 'F'" + with pytest.raises(AttributeError, match=msg): + r.F + + +def tests_skip_nuisance(step): + df = DataFrame({"A": range(5), "B": range(5, 10), "C": "foo"}) + r = df.rolling(window=3, step=step) + result = r[["A", "B"]].sum() + expected = DataFrame( + {"A": [np.nan, np.nan, 3, 6, 9], "B": [np.nan, np.nan, 18, 21, 24]}, + columns=list("AB"), + )[::step] + tm.assert_frame_equal(result, expected) + + +def test_sum_object_str_raises(step): + df = DataFrame({"A": range(5), "B": range(5, 10), "C": "foo"}) + r = df.rolling(window=3, step=step) + with pytest.raises( + DataError, match="Cannot aggregate non-numeric type: object|str" + ): + # GH#42738, enforced in 2.0 + r.sum() + + +def test_agg(step): + df = DataFrame({"A": range(5), "B": range(0, 10, 2)}) + + r = df.rolling(window=3, step=step) + a_mean = r["A"].mean() + a_std = r["A"].std() + a_sum = r["A"].sum() + b_mean = r["B"].mean() + b_std = r["B"].std() + + with tm.assert_produces_warning(FutureWarning, match="using Rolling.[mean|std]"): + result = r.aggregate([np.mean, np.std]) + expected = concat([a_mean, a_std, b_mean, b_std], axis=1) + expected.columns = MultiIndex.from_product([["A", "B"], ["mean", "std"]]) + tm.assert_frame_equal(result, expected) + + with tm.assert_produces_warning(FutureWarning, match="using Rolling.[mean|std]"): + result = r.aggregate({"A": np.mean, "B": np.std}) + + expected = concat([a_mean, b_std], axis=1) + tm.assert_frame_equal(result, expected, check_like=True) + + result = r.aggregate({"A": ["mean", "std"]}) + expected = concat([a_mean, a_std], axis=1) + expected.columns = MultiIndex.from_tuples([("A", "mean"), ("A", "std")]) + tm.assert_frame_equal(result, expected) + + result = r["A"].aggregate(["mean", "sum"]) + expected = concat([a_mean, a_sum], axis=1) + expected.columns = ["mean", "sum"] + tm.assert_frame_equal(result, expected) + + msg = "nested renamer is not supported" + with pytest.raises(SpecificationError, match=msg): + # using a dict with renaming + r.aggregate({"A": {"mean": "mean", "sum": "sum"}}) + + with pytest.raises(SpecificationError, match=msg): + r.aggregate( + {"A": {"mean": "mean", "sum": "sum"}, "B": {"mean2": "mean", "sum2": "sum"}} + ) + + result = r.aggregate({"A": ["mean", "std"], "B": ["mean", "std"]}) + expected = concat([a_mean, a_std, b_mean, b_std], axis=1) + + exp_cols = [("A", "mean"), ("A", "std"), ("B", "mean"), ("B", "std")] + expected.columns = MultiIndex.from_tuples(exp_cols) + tm.assert_frame_equal(result, expected, check_like=True) + + +@pytest.mark.parametrize( + "func", [["min"], ["mean", "max"], {"b": "sum"}, {"b": "prod", "c": "median"}] +) +def test_multi_axis_1_raises(func): + # GH#46904 + df = DataFrame({"a": [1, 1, 2], "b": [3, 4, 5], "c": [6, 7, 8]}) + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + r = df.rolling(window=3, axis=1) + with pytest.raises(NotImplementedError, match="axis other than 0 is not supported"): + r.agg(func) + + +def test_agg_apply(raw): + # passed lambda + df = DataFrame({"A": range(5), "B": range(0, 10, 2)}) + + r = df.rolling(window=3) + a_sum = r["A"].sum() + + with tm.assert_produces_warning(FutureWarning, match="using Rolling.[sum|std]"): + result = r.agg({"A": np.sum, "B": lambda x: np.std(x, ddof=1)}) + rcustom = r["B"].apply(lambda x: np.std(x, ddof=1), raw=raw) + expected = concat([a_sum, rcustom], axis=1) + tm.assert_frame_equal(result, expected, check_like=True) + + +def test_agg_consistency(step): + df = DataFrame({"A": range(5), "B": range(0, 10, 2)}) + r = df.rolling(window=3, step=step) + + with tm.assert_produces_warning(FutureWarning, match="using Rolling.[sum|mean]"): + result = r.agg([np.sum, np.mean]).columns + expected = MultiIndex.from_product([list("AB"), ["sum", "mean"]]) + tm.assert_index_equal(result, expected) + + with tm.assert_produces_warning(FutureWarning, match="using Rolling.[sum|mean]"): + result = r["A"].agg([np.sum, np.mean]).columns + expected = Index(["sum", "mean"]) + tm.assert_index_equal(result, expected) + + with tm.assert_produces_warning(FutureWarning, match="using Rolling.[sum|mean]"): + result = r.agg({"A": [np.sum, np.mean]}).columns + expected = MultiIndex.from_tuples([("A", "sum"), ("A", "mean")]) + tm.assert_index_equal(result, expected) + + +def test_agg_nested_dicts(): + # API change for disallowing these types of nested dicts + df = DataFrame({"A": range(5), "B": range(0, 10, 2)}) + r = df.rolling(window=3) + + msg = "nested renamer is not supported" + with pytest.raises(SpecificationError, match=msg): + r.aggregate({"r1": {"A": ["mean", "sum"]}, "r2": {"B": ["mean", "sum"]}}) + + expected = concat( + [r["A"].mean(), r["A"].std(), r["B"].mean(), r["B"].std()], axis=1 + ) + expected.columns = MultiIndex.from_tuples( + [("ra", "mean"), ("ra", "std"), ("rb", "mean"), ("rb", "std")] + ) + with pytest.raises(SpecificationError, match=msg): + r[["A", "B"]].agg({"A": {"ra": ["mean", "std"]}, "B": {"rb": ["mean", "std"]}}) + + with pytest.raises(SpecificationError, match=msg): + r.agg({"A": {"ra": ["mean", "std"]}, "B": {"rb": ["mean", "std"]}}) + + +def test_count_nonnumeric_types(step): + # GH12541 + cols = [ + "int", + "float", + "string", + "datetime", + "timedelta", + "periods", + "fl_inf", + "fl_nan", + "str_nan", + "dt_nat", + "periods_nat", + ] + dt_nat_col = [Timestamp("20170101"), Timestamp("20170203"), Timestamp(None)] + + df = DataFrame( + { + "int": [1, 2, 3], + "float": [4.0, 5.0, 6.0], + "string": list("abc"), + "datetime": date_range("20170101", periods=3), + "timedelta": timedelta_range("1 s", periods=3, freq="s"), + "periods": [ + Period("2012-01"), + Period("2012-02"), + Period("2012-03"), + ], + "fl_inf": [1.0, 2.0, np.inf], + "fl_nan": [1.0, 2.0, np.nan], + "str_nan": ["aa", "bb", np.nan], + "dt_nat": dt_nat_col, + "periods_nat": [ + Period("2012-01"), + Period("2012-02"), + Period(None), + ], + }, + columns=cols, + ) + + expected = DataFrame( + { + "int": [1.0, 2.0, 2.0], + "float": [1.0, 2.0, 2.0], + "string": [1.0, 2.0, 2.0], + "datetime": [1.0, 2.0, 2.0], + "timedelta": [1.0, 2.0, 2.0], + "periods": [1.0, 2.0, 2.0], + "fl_inf": [1.0, 2.0, 2.0], + "fl_nan": [1.0, 2.0, 1.0], + "str_nan": [1.0, 2.0, 1.0], + "dt_nat": [1.0, 2.0, 1.0], + "periods_nat": [1.0, 2.0, 1.0], + }, + columns=cols, + )[::step] + + result = df.rolling(window=2, min_periods=0, step=step).count() + tm.assert_frame_equal(result, expected) + + result = df.rolling(1, min_periods=0, step=step).count() + expected = df.notna().astype(float)[::step] + tm.assert_frame_equal(result, expected) + + +def test_preserve_metadata(): + # GH 10565 + s = Series(np.arange(100), name="foo") + + s2 = s.rolling(30).sum() + s3 = s.rolling(20).sum() + assert s2.name == "foo" + assert s3.name == "foo" + + +@pytest.mark.parametrize( + "func,window_size,expected_vals", + [ + ( + "rolling", + 2, + [ + [np.nan, np.nan, np.nan, np.nan], + [15.0, 20.0, 25.0, 20.0], + [25.0, 30.0, 35.0, 30.0], + [np.nan, np.nan, np.nan, np.nan], + [20.0, 30.0, 35.0, 30.0], + [35.0, 40.0, 60.0, 40.0], + [60.0, 80.0, 85.0, 80], + ], + ), + ( + "expanding", + None, + [ + [10.0, 10.0, 20.0, 20.0], + [15.0, 20.0, 25.0, 20.0], + [20.0, 30.0, 30.0, 20.0], + [10.0, 10.0, 30.0, 30.0], + [20.0, 30.0, 35.0, 30.0], + [26.666667, 40.0, 50.0, 30.0], + [40.0, 80.0, 60.0, 30.0], + ], + ), + ], +) +def test_multiple_agg_funcs(func, window_size, expected_vals): + # GH 15072 + df = DataFrame( + [ + ["A", 10, 20], + ["A", 20, 30], + ["A", 30, 40], + ["B", 10, 30], + ["B", 30, 40], + ["B", 40, 80], + ["B", 80, 90], + ], + columns=["stock", "low", "high"], + ) + + f = getattr(df.groupby("stock"), func) + if window_size: + window = f(window_size) + else: + window = f() + + index = MultiIndex.from_tuples( + [("A", 0), ("A", 1), ("A", 2), ("B", 3), ("B", 4), ("B", 5), ("B", 6)], + names=["stock", None], + ) + columns = MultiIndex.from_tuples( + [("low", "mean"), ("low", "max"), ("high", "mean"), ("high", "min")] + ) + expected = DataFrame(expected_vals, index=index, columns=columns) + + result = window.agg({"low": ["mean", "max"], "high": ["mean", "min"]}) + + tm.assert_frame_equal(result, expected) + + +def test_dont_modify_attributes_after_methods( + arithmetic_win_operators, closed, center, min_periods, step +): + # GH 39554 + roll_obj = Series(range(1)).rolling( + 1, center=center, closed=closed, min_periods=min_periods, step=step + ) + expected = {attr: getattr(roll_obj, attr) for attr in roll_obj._attributes} + getattr(roll_obj, arithmetic_win_operators)() + result = {attr: getattr(roll_obj, attr) for attr in roll_obj._attributes} + assert result == expected + + +def test_centered_axis_validation(step): + # ok + msg = "The 'axis' keyword in Series.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + Series(np.ones(10)).rolling(window=3, center=True, axis=0, step=step).mean() + + # bad axis + msg = "No axis named 1 for object type Series" + with pytest.raises(ValueError, match=msg): + Series(np.ones(10)).rolling(window=3, center=True, axis=1, step=step).mean() + + # ok ok + df = DataFrame(np.ones((10, 10))) + msg = "The 'axis' keyword in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + df.rolling(window=3, center=True, axis=0, step=step).mean() + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + df.rolling(window=3, center=True, axis=1, step=step).mean() + + # bad axis + msg = "No axis named 2 for object type DataFrame" + with pytest.raises(ValueError, match=msg): + (df.rolling(window=3, center=True, axis=2, step=step).mean()) + + +def test_rolling_min_min_periods(step): + a = Series([1, 2, 3, 4, 5]) + result = a.rolling(window=100, min_periods=1, step=step).min() + expected = Series(np.ones(len(a)))[::step] + tm.assert_series_equal(result, expected) + msg = "min_periods 5 must be <= window 3" + with pytest.raises(ValueError, match=msg): + Series([1, 2, 3]).rolling(window=3, min_periods=5, step=step).min() + + +def test_rolling_max_min_periods(step): + a = Series([1, 2, 3, 4, 5], dtype=np.float64) + result = a.rolling(window=100, min_periods=1, step=step).max() + expected = a[::step] + tm.assert_almost_equal(result, expected) + msg = "min_periods 5 must be <= window 3" + with pytest.raises(ValueError, match=msg): + Series([1, 2, 3]).rolling(window=3, min_periods=5, step=step).max() diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_apply.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_apply.py new file mode 100644 index 0000000000000000000000000000000000000000..136f81632cb0ad1f8847379e656ff5e3bf028cd3 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_apply.py @@ -0,0 +1,328 @@ +import numpy as np +import pytest + +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + Timestamp, + concat, + date_range, + isna, + notna, +) +import pandas._testing as tm + +from pandas.tseries import offsets + +# suppress warnings about empty slices, as we are deliberately testing +# with a 0-length Series +pytestmark = pytest.mark.filterwarnings( + "ignore:.*(empty slice|0 for slice).*:RuntimeWarning" +) + + +def f(x): + return x[np.isfinite(x)].mean() + + +@pytest.mark.parametrize("bad_raw", [None, 1, 0]) +def test_rolling_apply_invalid_raw(bad_raw): + with pytest.raises(ValueError, match="raw parameter must be `True` or `False`"): + Series(range(3)).rolling(1).apply(len, raw=bad_raw) + + +def test_rolling_apply_out_of_bounds(engine_and_raw): + # gh-1850 + engine, raw = engine_and_raw + + vals = Series([1, 2, 3, 4]) + + result = vals.rolling(10).apply(np.sum, engine=engine, raw=raw) + assert result.isna().all() + + result = vals.rolling(10, min_periods=1).apply(np.sum, engine=engine, raw=raw) + expected = Series([1, 3, 6, 10], dtype=float) + tm.assert_almost_equal(result, expected) + + +@pytest.mark.parametrize("window", [2, "2s"]) +def test_rolling_apply_with_pandas_objects(window): + # 5071 + df = DataFrame( + { + "A": np.random.default_rng(2).standard_normal(5), + "B": np.random.default_rng(2).integers(0, 10, size=5), + }, + index=date_range("20130101", periods=5, freq="s"), + ) + + # we have an equal spaced timeseries index + # so simulate removing the first period + def f(x): + if x.index[0] == df.index[0]: + return np.nan + return x.iloc[-1] + + result = df.rolling(window).apply(f, raw=False) + expected = df.iloc[2:].reindex_like(df) + tm.assert_frame_equal(result, expected) + + with tm.external_error_raised(AttributeError): + df.rolling(window).apply(f, raw=True) + + +def test_rolling_apply(engine_and_raw, step): + engine, raw = engine_and_raw + + expected = Series([], dtype="float64") + result = expected.rolling(10, step=step).apply( + lambda x: x.mean(), engine=engine, raw=raw + ) + tm.assert_series_equal(result, expected) + + # gh-8080 + s = Series([None, None, None]) + result = s.rolling(2, min_periods=0, step=step).apply( + lambda x: len(x), engine=engine, raw=raw + ) + expected = Series([1.0, 2.0, 2.0])[::step] + tm.assert_series_equal(result, expected) + + result = s.rolling(2, min_periods=0, step=step).apply(len, engine=engine, raw=raw) + tm.assert_series_equal(result, expected) + + +def test_all_apply(engine_and_raw): + engine, raw = engine_and_raw + + df = ( + DataFrame( + {"A": date_range("20130101", periods=5, freq="s"), "B": range(5)} + ).set_index("A") + * 2 + ) + er = df.rolling(window=1) + r = df.rolling(window="1s") + + result = r.apply(lambda x: 1, engine=engine, raw=raw) + expected = er.apply(lambda x: 1, engine=engine, raw=raw) + tm.assert_frame_equal(result, expected) + + +def test_ragged_apply(engine_and_raw): + engine, raw = engine_and_raw + + df = DataFrame({"B": range(5)}) + df.index = [ + Timestamp("20130101 09:00:00"), + Timestamp("20130101 09:00:02"), + Timestamp("20130101 09:00:03"), + Timestamp("20130101 09:00:05"), + Timestamp("20130101 09:00:06"), + ] + + f = lambda x: 1 + result = df.rolling(window="1s", min_periods=1).apply(f, engine=engine, raw=raw) + expected = df.copy() + expected["B"] = 1.0 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).apply(f, engine=engine, raw=raw) + expected = df.copy() + expected["B"] = 1.0 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).apply(f, engine=engine, raw=raw) + expected = df.copy() + expected["B"] = 1.0 + tm.assert_frame_equal(result, expected) + + +def test_invalid_engine(): + with pytest.raises(ValueError, match="engine must be either 'numba' or 'cython'"): + Series(range(1)).rolling(1).apply(lambda x: x, engine="foo") + + +def test_invalid_engine_kwargs_cython(): + with pytest.raises(ValueError, match="cython engine does not accept engine_kwargs"): + Series(range(1)).rolling(1).apply( + lambda x: x, engine="cython", engine_kwargs={"nopython": False} + ) + + +def test_invalid_raw_numba(): + with pytest.raises( + ValueError, match="raw must be `True` when using the numba engine" + ): + Series(range(1)).rolling(1).apply(lambda x: x, raw=False, engine="numba") + + +@pytest.mark.parametrize("args_kwargs", [[None, {"par": 10}], [(10,), None]]) +def test_rolling_apply_args_kwargs(args_kwargs): + # GH 33433 + def numpysum(x, par): + return np.sum(x + par) + + df = DataFrame({"gr": [1, 1], "a": [1, 2]}) + + idx = Index(["gr", "a"]) + expected = DataFrame([[11.0, 11.0], [11.0, 12.0]], columns=idx) + + result = df.rolling(1).apply(numpysum, args=args_kwargs[0], kwargs=args_kwargs[1]) + tm.assert_frame_equal(result, expected) + + midx = MultiIndex.from_tuples([(1, 0), (1, 1)], names=["gr", None]) + expected = Series([11.0, 12.0], index=midx, name="a") + + gb_rolling = df.groupby("gr")["a"].rolling(1) + + result = gb_rolling.apply(numpysum, args=args_kwargs[0], kwargs=args_kwargs[1]) + tm.assert_series_equal(result, expected) + + +def test_nans(raw): + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = obj.rolling(50, min_periods=30).apply(f, raw=raw) + tm.assert_almost_equal(result.iloc[-1], np.mean(obj[10:-10])) + + # min_periods is working correctly + result = obj.rolling(20, min_periods=15).apply(f, raw=raw) + assert isna(result.iloc[23]) + assert not isna(result.iloc[24]) + + assert not isna(result.iloc[-6]) + assert isna(result.iloc[-5]) + + obj2 = Series(np.random.default_rng(2).standard_normal(20)) + result = obj2.rolling(10, min_periods=5).apply(f, raw=raw) + assert isna(result.iloc[3]) + assert notna(result.iloc[4]) + + result0 = obj.rolling(20, min_periods=0).apply(f, raw=raw) + result1 = obj.rolling(20, min_periods=1).apply(f, raw=raw) + tm.assert_almost_equal(result0, result1) + + +def test_center(raw): + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = obj.rolling(20, min_periods=15, center=True).apply(f, raw=raw) + expected = ( + concat([obj, Series([np.nan] * 9)]) + .rolling(20, min_periods=15) + .apply(f, raw=raw) + .iloc[9:] + .reset_index(drop=True) + ) + tm.assert_series_equal(result, expected) + + +def test_series(raw, series): + result = series.rolling(50).apply(f, raw=raw) + assert isinstance(result, Series) + tm.assert_almost_equal(result.iloc[-1], np.mean(series[-50:])) + + +def test_frame(raw, frame): + result = frame.rolling(50).apply(f, raw=raw) + assert isinstance(result, DataFrame) + tm.assert_series_equal( + result.iloc[-1, :], + frame.iloc[-50:, :].apply(np.mean, axis=0, raw=raw), + check_names=False, + ) + + +def test_time_rule_series(raw, series): + win = 25 + minp = 10 + ser = series[::2].resample("B").mean() + series_result = ser.rolling(window=win, min_periods=minp).apply(f, raw=raw) + last_date = series_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_series = series[::2].truncate(prev_date, last_date) + tm.assert_almost_equal(series_result.iloc[-1], np.mean(trunc_series)) + + +def test_time_rule_frame(raw, frame): + win = 25 + minp = 10 + frm = frame[::2].resample("B").mean() + frame_result = frm.rolling(window=win, min_periods=minp).apply(f, raw=raw) + last_date = frame_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_frame = frame[::2].truncate(prev_date, last_date) + tm.assert_series_equal( + frame_result.xs(last_date), + trunc_frame.apply(np.mean, raw=raw), + check_names=False, + ) + + +@pytest.mark.parametrize("minp", [0, 99, 100]) +def test_min_periods(raw, series, minp, step): + result = series.rolling(len(series) + 1, min_periods=minp, step=step).apply( + f, raw=raw + ) + expected = series.rolling(len(series), min_periods=minp, step=step).apply( + f, raw=raw + ) + nan_mask = isna(result) + tm.assert_series_equal(nan_mask, isna(expected)) + + nan_mask = ~nan_mask + tm.assert_almost_equal(result[nan_mask], expected[nan_mask]) + + +def test_center_reindex_series(raw, series): + # shifter index + s = [f"x{x:d}" for x in range(12)] + minp = 10 + + series_xp = ( + series.reindex(list(series.index) + s) + .rolling(window=25, min_periods=minp) + .apply(f, raw=raw) + .shift(-12) + .reindex(series.index) + ) + series_rs = series.rolling(window=25, min_periods=minp, center=True).apply( + f, raw=raw + ) + tm.assert_series_equal(series_xp, series_rs) + + +def test_center_reindex_frame(raw): + # shifter index + frame = DataFrame(range(100), index=date_range("2020-01-01", freq="D", periods=100)) + s = [f"x{x:d}" for x in range(12)] + minp = 10 + + frame_xp = ( + frame.reindex(list(frame.index) + s) + .rolling(window=25, min_periods=minp) + .apply(f, raw=raw) + .shift(-12) + .reindex(frame.index) + ) + frame_rs = frame.rolling(window=25, min_periods=minp, center=True).apply(f, raw=raw) + tm.assert_frame_equal(frame_xp, frame_rs) + + +def test_axis1(raw): + # GH 45912 + df = DataFrame([1, 2]) + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(window=1, axis=1).apply(np.sum, raw=raw) + expected = DataFrame([1.0, 2.0]) + tm.assert_frame_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_base_indexer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_base_indexer.py new file mode 100644 index 0000000000000000000000000000000000000000..104acc1d527cb8dbd92b20211fb760dd413a0757 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_base_indexer.py @@ -0,0 +1,519 @@ +import numpy as np +import pytest + +from pandas import ( + DataFrame, + MultiIndex, + Series, + concat, + date_range, +) +import pandas._testing as tm +from pandas.api.indexers import ( + BaseIndexer, + FixedForwardWindowIndexer, +) +from pandas.core.indexers.objects import ( + ExpandingIndexer, + FixedWindowIndexer, + VariableOffsetWindowIndexer, +) + +from pandas.tseries.offsets import BusinessDay + + +def test_bad_get_window_bounds_signature(): + class BadIndexer(BaseIndexer): + def get_window_bounds(self): + return None + + indexer = BadIndexer() + with pytest.raises(ValueError, match="BadIndexer does not implement"): + Series(range(5)).rolling(indexer) + + +def test_expanding_indexer(): + s = Series(range(10)) + indexer = ExpandingIndexer() + result = s.rolling(indexer).mean() + expected = s.expanding().mean() + tm.assert_series_equal(result, expected) + + +def test_indexer_constructor_arg(): + # Example found in computation.rst + use_expanding = [True, False, True, False, True] + df = DataFrame({"values": range(5)}) + + class CustomIndexer(BaseIndexer): + def get_window_bounds(self, num_values, min_periods, center, closed, step): + start = np.empty(num_values, dtype=np.int64) + end = np.empty(num_values, dtype=np.int64) + for i in range(num_values): + if self.use_expanding[i]: + start[i] = 0 + end[i] = i + 1 + else: + start[i] = i + end[i] = i + self.window_size + return start, end + + indexer = CustomIndexer(window_size=1, use_expanding=use_expanding) + result = df.rolling(indexer).sum() + expected = DataFrame({"values": [0.0, 1.0, 3.0, 3.0, 10.0]}) + tm.assert_frame_equal(result, expected) + + +def test_indexer_accepts_rolling_args(): + df = DataFrame({"values": range(5)}) + + class CustomIndexer(BaseIndexer): + def get_window_bounds(self, num_values, min_periods, center, closed, step): + start = np.empty(num_values, dtype=np.int64) + end = np.empty(num_values, dtype=np.int64) + for i in range(num_values): + if ( + center + and min_periods == 1 + and closed == "both" + and step == 1 + and i == 2 + ): + start[i] = 0 + end[i] = num_values + else: + start[i] = i + end[i] = i + self.window_size + return start, end + + indexer = CustomIndexer(window_size=1) + result = df.rolling( + indexer, center=True, min_periods=1, closed="both", step=1 + ).sum() + expected = DataFrame({"values": [0.0, 1.0, 10.0, 3.0, 4.0]}) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "func,np_func,expected,np_kwargs", + [ + ("count", len, [3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 2.0, np.nan], {}), + ("min", np.min, [0.0, 1.0, 2.0, 3.0, 4.0, 6.0, 6.0, 7.0, 8.0, np.nan], {}), + ( + "max", + np.max, + [2.0, 3.0, 4.0, 100.0, 100.0, 100.0, 8.0, 9.0, 9.0, np.nan], + {}, + ), + ( + "std", + np.std, + [ + 1.0, + 1.0, + 1.0, + 55.71654452, + 54.85739087, + 53.9845657, + 1.0, + 1.0, + 0.70710678, + np.nan, + ], + {"ddof": 1}, + ), + ( + "var", + np.var, + [ + 1.0, + 1.0, + 1.0, + 3104.333333, + 3009.333333, + 2914.333333, + 1.0, + 1.0, + 0.500000, + np.nan, + ], + {"ddof": 1}, + ), + ( + "median", + np.median, + [1.0, 2.0, 3.0, 4.0, 6.0, 7.0, 7.0, 8.0, 8.5, np.nan], + {}, + ), + ], +) +def test_rolling_forward_window( + frame_or_series, func, np_func, expected, np_kwargs, step +): + # GH 32865 + values = np.arange(10.0) + values[5] = 100.0 + + indexer = FixedForwardWindowIndexer(window_size=3) + + match = "Forward-looking windows can't have center=True" + with pytest.raises(ValueError, match=match): + rolling = frame_or_series(values).rolling(window=indexer, center=True) + getattr(rolling, func)() + + match = "Forward-looking windows don't support setting the closed argument" + with pytest.raises(ValueError, match=match): + rolling = frame_or_series(values).rolling(window=indexer, closed="right") + getattr(rolling, func)() + + rolling = frame_or_series(values).rolling(window=indexer, min_periods=2, step=step) + result = getattr(rolling, func)() + + # Check that the function output matches the explicitly provided array + expected = frame_or_series(expected)[::step] + tm.assert_equal(result, expected) + + # Check that the rolling function output matches applying an alternative + # function to the rolling window object + expected2 = frame_or_series(rolling.apply(lambda x: np_func(x, **np_kwargs))) + tm.assert_equal(result, expected2) + + # Check that the function output matches applying an alternative function + # if min_periods isn't specified + # GH 39604: After count-min_periods deprecation, apply(lambda x: len(x)) + # is equivalent to count after setting min_periods=0 + min_periods = 0 if func == "count" else None + rolling3 = frame_or_series(values).rolling(window=indexer, min_periods=min_periods) + result3 = getattr(rolling3, func)() + expected3 = frame_or_series(rolling3.apply(lambda x: np_func(x, **np_kwargs))) + tm.assert_equal(result3, expected3) + + +def test_rolling_forward_skewness(frame_or_series, step): + values = np.arange(10.0) + values[5] = 100.0 + + indexer = FixedForwardWindowIndexer(window_size=5) + rolling = frame_or_series(values).rolling(window=indexer, min_periods=3, step=step) + result = rolling.skew() + + expected = frame_or_series( + [ + 0.0, + 2.232396, + 2.229508, + 2.228340, + 2.229091, + 2.231989, + 0.0, + 0.0, + np.nan, + np.nan, + ] + )[::step] + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "func,expected", + [ + ("cov", [2.0, 2.0, 2.0, 97.0, 2.0, -93.0, 2.0, 2.0, np.nan, np.nan]), + ( + "corr", + [ + 1.0, + 1.0, + 1.0, + 0.8704775290207161, + 0.018229084250926637, + -0.861357304646493, + 1.0, + 1.0, + np.nan, + np.nan, + ], + ), + ], +) +def test_rolling_forward_cov_corr(func, expected): + values1 = np.arange(10).reshape(-1, 1) + values2 = values1 * 2 + values1[5, 0] = 100 + values = np.concatenate([values1, values2], axis=1) + + indexer = FixedForwardWindowIndexer(window_size=3) + rolling = DataFrame(values).rolling(window=indexer, min_periods=3) + # We are interested in checking only pairwise covariance / correlation + result = getattr(rolling, func)().loc[(slice(None), 1), 0] + result = result.reset_index(drop=True) + expected = Series(expected).reset_index(drop=True) + expected.name = result.name + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "closed,expected_data", + [ + ["right", [0.0, 1.0, 2.0, 3.0, 7.0, 12.0, 6.0, 7.0, 8.0, 9.0]], + ["left", [0.0, 0.0, 1.0, 2.0, 5.0, 9.0, 5.0, 6.0, 7.0, 8.0]], + ], +) +def test_non_fixed_variable_window_indexer(closed, expected_data): + index = date_range("2020", periods=10) + df = DataFrame(range(10), index=index) + offset = BusinessDay(1) + indexer = VariableOffsetWindowIndexer(index=index, offset=offset) + result = df.rolling(indexer, closed=closed).sum() + expected = DataFrame(expected_data, index=index) + tm.assert_frame_equal(result, expected) + + +def test_variableoffsetwindowindexer_not_dti(): + # GH 54379 + with pytest.raises(ValueError, match="index must be a DatetimeIndex."): + VariableOffsetWindowIndexer(index="foo", offset=BusinessDay(1)) + + +def test_variableoffsetwindowindexer_not_offset(): + # GH 54379 + idx = date_range("2020", periods=10) + with pytest.raises(ValueError, match="offset must be a DateOffset-like object."): + VariableOffsetWindowIndexer(index=idx, offset="foo") + + +def test_fixed_forward_indexer_count(step): + # GH: 35579 + df = DataFrame({"b": [None, None, None, 7]}) + indexer = FixedForwardWindowIndexer(window_size=2) + result = df.rolling(window=indexer, min_periods=0, step=step).count() + expected = DataFrame({"b": [0.0, 0.0, 1.0, 1.0]})[::step] + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + ("end_value", "values"), [(1, [0.0, 1, 1, 3, 2]), (-1, [0.0, 1, 0, 3, 1])] +) +@pytest.mark.parametrize(("func", "args"), [("median", []), ("quantile", [0.5])]) +def test_indexer_quantile_sum(end_value, values, func, args): + # GH 37153 + class CustomIndexer(BaseIndexer): + def get_window_bounds(self, num_values, min_periods, center, closed, step): + start = np.empty(num_values, dtype=np.int64) + end = np.empty(num_values, dtype=np.int64) + for i in range(num_values): + if self.use_expanding[i]: + start[i] = 0 + end[i] = max(i + end_value, 1) + else: + start[i] = i + end[i] = i + self.window_size + return start, end + + use_expanding = [True, False, True, False, True] + df = DataFrame({"values": range(5)}) + + indexer = CustomIndexer(window_size=1, use_expanding=use_expanding) + result = getattr(df.rolling(indexer), func)(*args) + expected = DataFrame({"values": values}) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "indexer_class", [FixedWindowIndexer, FixedForwardWindowIndexer, ExpandingIndexer] +) +@pytest.mark.parametrize("window_size", [1, 2, 12]) +@pytest.mark.parametrize( + "df_data", + [ + {"a": [1, 1], "b": [0, 1]}, + {"a": [1, 2], "b": [0, 1]}, + {"a": [1] * 16, "b": [np.nan, 1, 2, np.nan] + list(range(4, 16))}, + ], +) +def test_indexers_are_reusable_after_groupby_rolling( + indexer_class, window_size, df_data +): + # GH 43267 + df = DataFrame(df_data) + num_trials = 3 + indexer = indexer_class(window_size=window_size) + original_window_size = indexer.window_size + for i in range(num_trials): + df.groupby("a")["b"].rolling(window=indexer, min_periods=1).mean() + assert indexer.window_size == original_window_size + + +@pytest.mark.parametrize( + "window_size, num_values, expected_start, expected_end", + [ + (1, 1, [0], [1]), + (1, 2, [0, 1], [1, 2]), + (2, 1, [0], [1]), + (2, 2, [0, 1], [2, 2]), + (5, 12, range(12), list(range(5, 12)) + [12] * 5), + (12, 5, range(5), [5] * 5), + (0, 0, np.array([]), np.array([])), + (1, 0, np.array([]), np.array([])), + (0, 1, [0], [0]), + ], +) +def test_fixed_forward_indexer_bounds( + window_size, num_values, expected_start, expected_end, step +): + # GH 43267 + indexer = FixedForwardWindowIndexer(window_size=window_size) + start, end = indexer.get_window_bounds(num_values=num_values, step=step) + + tm.assert_numpy_array_equal( + start, np.array(expected_start[::step]), check_dtype=False + ) + tm.assert_numpy_array_equal(end, np.array(expected_end[::step]), check_dtype=False) + assert len(start) == len(end) + + +@pytest.mark.parametrize( + "df, window_size, expected", + [ + ( + DataFrame({"b": [0, 1, 2], "a": [1, 2, 2]}), + 2, + Series( + [0, 1.5, 2.0], + index=MultiIndex.from_arrays([[1, 2, 2], range(3)], names=["a", None]), + name="b", + dtype=np.float64, + ), + ), + ( + DataFrame( + { + "b": [np.nan, 1, 2, np.nan] + list(range(4, 18)), + "a": [1] * 7 + [2] * 11, + "c": range(18), + } + ), + 12, + Series( + [ + 3.6, + 3.6, + 4.25, + 5.0, + 5.0, + 5.5, + 6.0, + 12.0, + 12.5, + 13.0, + 13.5, + 14.0, + 14.5, + 15.0, + 15.5, + 16.0, + 16.5, + 17.0, + ], + index=MultiIndex.from_arrays( + [[1] * 7 + [2] * 11, range(18)], names=["a", None] + ), + name="b", + dtype=np.float64, + ), + ), + ], +) +def test_rolling_groupby_with_fixed_forward_specific(df, window_size, expected): + # GH 43267 + indexer = FixedForwardWindowIndexer(window_size=window_size) + result = df.groupby("a")["b"].rolling(window=indexer, min_periods=1).mean() + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "group_keys", + [ + (1,), + (1, 2), + (2, 1), + (1, 1, 2), + (1, 2, 1), + (1, 1, 2, 2), + (1, 2, 3, 2, 3), + (1, 1, 2) * 4, + (1, 2, 3) * 5, + ], +) +@pytest.mark.parametrize("window_size", [1, 2, 3, 4, 5, 8, 20]) +def test_rolling_groupby_with_fixed_forward_many(group_keys, window_size): + # GH 43267 + df = DataFrame( + { + "a": np.array(list(group_keys)), + "b": np.arange(len(group_keys), dtype=np.float64) + 17, + "c": np.arange(len(group_keys), dtype=np.int64), + } + ) + + indexer = FixedForwardWindowIndexer(window_size=window_size) + result = df.groupby("a")["b"].rolling(window=indexer, min_periods=1).sum() + result.index.names = ["a", "c"] + + groups = df.groupby("a")[["a", "b", "c"]] + manual = concat( + [ + g.assign( + b=[ + g["b"].iloc[i : i + window_size].sum(min_count=1) + for i in range(len(g)) + ] + ) + for _, g in groups + ] + ) + manual = manual.set_index(["a", "c"])["b"] + + tm.assert_series_equal(result, manual) + + +def test_unequal_start_end_bounds(): + class CustomIndexer(BaseIndexer): + def get_window_bounds(self, num_values, min_periods, center, closed, step): + return np.array([1]), np.array([1, 2]) + + indexer = CustomIndexer() + roll = Series(1).rolling(indexer) + match = "start" + with pytest.raises(ValueError, match=match): + roll.mean() + + with pytest.raises(ValueError, match=match): + next(iter(roll)) + + with pytest.raises(ValueError, match=match): + roll.corr(pairwise=True) + + with pytest.raises(ValueError, match=match): + roll.cov(pairwise=True) + + +def test_unequal_bounds_to_object(): + # GH 44470 + class CustomIndexer(BaseIndexer): + def get_window_bounds(self, num_values, min_periods, center, closed, step): + return np.array([1]), np.array([2]) + + indexer = CustomIndexer() + roll = Series([1, 1]).rolling(indexer) + match = "start and end" + with pytest.raises(ValueError, match=match): + roll.mean() + + with pytest.raises(ValueError, match=match): + next(iter(roll)) + + with pytest.raises(ValueError, match=match): + roll.corr(pairwise=True) + + with pytest.raises(ValueError, match=match): + roll.cov(pairwise=True) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_cython_aggregations.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_cython_aggregations.py new file mode 100644 index 0000000000000000000000000000000000000000..c60cb6ea74ec0aa90cf089841c853c657e1b4c00 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_cython_aggregations.py @@ -0,0 +1,111 @@ +from functools import partial +import sys + +import numpy as np +import pytest + +import pandas._libs.window.aggregations as window_aggregations + +from pandas import Series +import pandas._testing as tm + + +def _get_rolling_aggregations(): + # list pairs of name and function + # each function has this signature: + # (const float64_t[:] values, ndarray[int64_t] start, + # ndarray[int64_t] end, int64_t minp) -> np.ndarray + named_roll_aggs = ( + [ + ("roll_sum", window_aggregations.roll_sum), + ("roll_mean", window_aggregations.roll_mean), + ] + + [ + (f"roll_var({ddof})", partial(window_aggregations.roll_var, ddof=ddof)) + for ddof in [0, 1] + ] + + [ + ("roll_skew", window_aggregations.roll_skew), + ("roll_kurt", window_aggregations.roll_kurt), + ("roll_median_c", window_aggregations.roll_median_c), + ("roll_max", window_aggregations.roll_max), + ("roll_min", window_aggregations.roll_min), + ] + + [ + ( + f"roll_quantile({quantile},{interpolation})", + partial( + window_aggregations.roll_quantile, + quantile=quantile, + interpolation=interpolation, + ), + ) + for quantile in [0.0001, 0.5, 0.9999] + for interpolation in window_aggregations.interpolation_types + ] + + [ + ( + f"roll_rank({percentile},{method},{ascending})", + partial( + window_aggregations.roll_rank, + percentile=percentile, + method=method, + ascending=ascending, + ), + ) + for percentile in [True, False] + for method in window_aggregations.rolling_rank_tiebreakers.keys() + for ascending in [True, False] + ] + ) + # unzip to a list of 2 tuples, names and functions + unzipped = list(zip(*named_roll_aggs)) + return {"ids": unzipped[0], "params": unzipped[1]} + + +_rolling_aggregations = _get_rolling_aggregations() + + +@pytest.fixture( + params=_rolling_aggregations["params"], ids=_rolling_aggregations["ids"] +) +def rolling_aggregation(request): + """Make a rolling aggregation function as fixture.""" + return request.param + + +def test_rolling_aggregation_boundary_consistency(rolling_aggregation): + # GH-45647 + minp, step, width, size, selection = 0, 1, 3, 11, [2, 7] + values = np.arange(1, 1 + size, dtype=np.float64) + end = np.arange(width, size, step, dtype=np.int64) + start = end - width + selarr = np.array(selection, dtype=np.int32) + result = Series(rolling_aggregation(values, start[selarr], end[selarr], minp)) + expected = Series(rolling_aggregation(values, start, end, minp)[selarr]) + tm.assert_equal(expected, result) + + +def test_rolling_aggregation_with_unused_elements(rolling_aggregation): + # GH-45647 + minp, width = 0, 5 # width at least 4 for kurt + size = 2 * width + 5 + values = np.arange(1, size + 1, dtype=np.float64) + values[width : width + 2] = sys.float_info.min + values[width + 2] = np.nan + values[width + 3 : width + 5] = sys.float_info.max + start = np.array([0, size - width], dtype=np.int64) + end = np.array([width, size], dtype=np.int64) + loc = np.array( + [j for i in range(len(start)) for j in range(start[i], end[i])], + dtype=np.int32, + ) + result = Series(rolling_aggregation(values, start, end, minp)) + compact_values = np.array(values[loc], dtype=np.float64) + compact_start = np.arange(0, len(start) * width, width, dtype=np.int64) + compact_end = compact_start + width + expected = Series( + rolling_aggregation(compact_values, compact_start, compact_end, minp) + ) + assert np.isfinite(expected.values).all(), "Not all expected values are finite" + tm.assert_equal(expected, result) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_dtypes.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_dtypes.py new file mode 100644 index 0000000000000000000000000000000000000000..4007320b5de332ee4aef40b1ad1be9092eeb3347 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_dtypes.py @@ -0,0 +1,173 @@ +import numpy as np +import pytest + +from pandas.errors import DataError + +from pandas.core.dtypes.common import pandas_dtype + +from pandas import ( + NA, + DataFrame, + Series, +) +import pandas._testing as tm + +# gh-12373 : rolling functions error on float32 data +# make sure rolling functions works for different dtypes +# +# further note that we are only checking rolling for fully dtype +# compliance (though both expanding and ewm inherit) + + +def get_dtype(dtype, coerce_int=None): + if coerce_int is False and "int" in dtype: + return None + return pandas_dtype(dtype) + + +@pytest.fixture( + params=[ + "object", + "category", + "int8", + "int16", + "int32", + "int64", + "uint8", + "uint16", + "uint32", + "uint64", + "float16", + "float32", + "float64", + "m8[ns]", + "M8[ns]", + "datetime64[ns, UTC]", + ] +) +def dtypes(request): + """Dtypes for window tests""" + return request.param + + +@pytest.mark.parametrize( + "method, data, expected_data, coerce_int, min_periods", + [ + ("count", np.arange(5), [1, 2, 2, 2, 2], True, 0), + ("count", np.arange(10, 0, -2), [1, 2, 2, 2, 2], True, 0), + ("count", [0, 1, 2, np.nan, 4], [1, 2, 2, 1, 1], False, 0), + ("max", np.arange(5), [np.nan, 1, 2, 3, 4], True, None), + ("max", np.arange(10, 0, -2), [np.nan, 10, 8, 6, 4], True, None), + ("max", [0, 1, 2, np.nan, 4], [np.nan, 1, 2, np.nan, np.nan], False, None), + ("min", np.arange(5), [np.nan, 0, 1, 2, 3], True, None), + ("min", np.arange(10, 0, -2), [np.nan, 8, 6, 4, 2], True, None), + ("min", [0, 1, 2, np.nan, 4], [np.nan, 0, 1, np.nan, np.nan], False, None), + ("sum", np.arange(5), [np.nan, 1, 3, 5, 7], True, None), + ("sum", np.arange(10, 0, -2), [np.nan, 18, 14, 10, 6], True, None), + ("sum", [0, 1, 2, np.nan, 4], [np.nan, 1, 3, np.nan, np.nan], False, None), + ("mean", np.arange(5), [np.nan, 0.5, 1.5, 2.5, 3.5], True, None), + ("mean", np.arange(10, 0, -2), [np.nan, 9, 7, 5, 3], True, None), + ("mean", [0, 1, 2, np.nan, 4], [np.nan, 0.5, 1.5, np.nan, np.nan], False, None), + ("std", np.arange(5), [np.nan] + [np.sqrt(0.5)] * 4, True, None), + ("std", np.arange(10, 0, -2), [np.nan] + [np.sqrt(2)] * 4, True, None), + ( + "std", + [0, 1, 2, np.nan, 4], + [np.nan] + [np.sqrt(0.5)] * 2 + [np.nan] * 2, + False, + None, + ), + ("var", np.arange(5), [np.nan, 0.5, 0.5, 0.5, 0.5], True, None), + ("var", np.arange(10, 0, -2), [np.nan, 2, 2, 2, 2], True, None), + ("var", [0, 1, 2, np.nan, 4], [np.nan, 0.5, 0.5, np.nan, np.nan], False, None), + ("median", np.arange(5), [np.nan, 0.5, 1.5, 2.5, 3.5], True, None), + ("median", np.arange(10, 0, -2), [np.nan, 9, 7, 5, 3], True, None), + ( + "median", + [0, 1, 2, np.nan, 4], + [np.nan, 0.5, 1.5, np.nan, np.nan], + False, + None, + ), + ], +) +def test_series_dtypes( + method, data, expected_data, coerce_int, dtypes, min_periods, step +): + ser = Series(data, dtype=get_dtype(dtypes, coerce_int=coerce_int)) + rolled = ser.rolling(2, min_periods=min_periods, step=step) + + if dtypes in ("m8[ns]", "M8[ns]", "datetime64[ns, UTC]") and method != "count": + msg = "No numeric types to aggregate" + with pytest.raises(DataError, match=msg): + getattr(rolled, method)() + else: + result = getattr(rolled, method)() + expected = Series(expected_data, dtype="float64")[::step] + tm.assert_almost_equal(result, expected) + + +def test_series_nullable_int(any_signed_int_ea_dtype, step): + # GH 43016 + ser = Series([0, 1, NA], dtype=any_signed_int_ea_dtype) + result = ser.rolling(2, step=step).mean() + expected = Series([np.nan, 0.5, np.nan])[::step] + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "method, expected_data, min_periods", + [ + ("count", {0: Series([1, 2, 2, 2, 2]), 1: Series([1, 2, 2, 2, 2])}, 0), + ( + "max", + {0: Series([np.nan, 2, 4, 6, 8]), 1: Series([np.nan, 3, 5, 7, 9])}, + None, + ), + ( + "min", + {0: Series([np.nan, 0, 2, 4, 6]), 1: Series([np.nan, 1, 3, 5, 7])}, + None, + ), + ( + "sum", + {0: Series([np.nan, 2, 6, 10, 14]), 1: Series([np.nan, 4, 8, 12, 16])}, + None, + ), + ( + "mean", + {0: Series([np.nan, 1, 3, 5, 7]), 1: Series([np.nan, 2, 4, 6, 8])}, + None, + ), + ( + "std", + { + 0: Series([np.nan] + [np.sqrt(2)] * 4), + 1: Series([np.nan] + [np.sqrt(2)] * 4), + }, + None, + ), + ( + "var", + {0: Series([np.nan, 2, 2, 2, 2]), 1: Series([np.nan, 2, 2, 2, 2])}, + None, + ), + ( + "median", + {0: Series([np.nan, 1, 3, 5, 7]), 1: Series([np.nan, 2, 4, 6, 8])}, + None, + ), + ], +) +def test_dataframe_dtypes(method, expected_data, dtypes, min_periods, step): + df = DataFrame(np.arange(10).reshape((5, 2)), dtype=get_dtype(dtypes)) + rolled = df.rolling(2, min_periods=min_periods, step=step) + + if dtypes in ("m8[ns]", "M8[ns]", "datetime64[ns, UTC]") and method != "count": + msg = "Cannot aggregate non-numeric type" + with pytest.raises(DataError, match=msg): + getattr(rolled, method)() + else: + result = getattr(rolled, method)() + expected = DataFrame(expected_data, dtype="float64")[::step] + tm.assert_frame_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_ewm.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_ewm.py new file mode 100644 index 0000000000000000000000000000000000000000..058e5ce36e53e8fc43355ffc86a2336316ab09a4 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_ewm.py @@ -0,0 +1,727 @@ +import numpy as np +import pytest + +from pandas import ( + DataFrame, + DatetimeIndex, + Series, + date_range, +) +import pandas._testing as tm + + +def test_doc_string(): + df = DataFrame({"B": [0, 1, 2, np.nan, 4]}) + df + df.ewm(com=0.5).mean() + + +def test_constructor(frame_or_series): + c = frame_or_series(range(5)).ewm + + # valid + c(com=0.5) + c(span=1.5) + c(alpha=0.5) + c(halflife=0.75) + c(com=0.5, span=None) + c(alpha=0.5, com=None) + c(halflife=0.75, alpha=None) + + # not valid: mutually exclusive + msg = "comass, span, halflife, and alpha are mutually exclusive" + with pytest.raises(ValueError, match=msg): + c(com=0.5, alpha=0.5) + with pytest.raises(ValueError, match=msg): + c(span=1.5, halflife=0.75) + with pytest.raises(ValueError, match=msg): + c(alpha=0.5, span=1.5) + + # not valid: com < 0 + msg = "comass must satisfy: comass >= 0" + with pytest.raises(ValueError, match=msg): + c(com=-0.5) + + # not valid: span < 1 + msg = "span must satisfy: span >= 1" + with pytest.raises(ValueError, match=msg): + c(span=0.5) + + # not valid: halflife <= 0 + msg = "halflife must satisfy: halflife > 0" + with pytest.raises(ValueError, match=msg): + c(halflife=0) + + # not valid: alpha <= 0 or alpha > 1 + msg = "alpha must satisfy: 0 < alpha <= 1" + for alpha in (-0.5, 1.5): + with pytest.raises(ValueError, match=msg): + c(alpha=alpha) + + +def test_ewma_times_not_datetime_type(): + msg = r"times must be datetime64 dtype." + with pytest.raises(ValueError, match=msg): + Series(range(5)).ewm(times=np.arange(5)) + + +def test_ewma_times_not_same_length(): + msg = "times must be the same length as the object." + with pytest.raises(ValueError, match=msg): + Series(range(5)).ewm(times=np.arange(4).astype("datetime64[ns]")) + + +def test_ewma_halflife_not_correct_type(): + msg = "halflife must be a timedelta convertible object" + with pytest.raises(ValueError, match=msg): + Series(range(5)).ewm(halflife=1, times=np.arange(5).astype("datetime64[ns]")) + + +def test_ewma_halflife_without_times(halflife_with_times): + msg = "halflife can only be a timedelta convertible argument if times is not None." + with pytest.raises(ValueError, match=msg): + Series(range(5)).ewm(halflife=halflife_with_times) + + +@pytest.mark.parametrize( + "times", + [ + np.arange(10).astype("datetime64[D]").astype("datetime64[ns]"), + date_range("2000", freq="D", periods=10), + date_range("2000", freq="D", periods=10).tz_localize("UTC"), + ], +) +@pytest.mark.parametrize("min_periods", [0, 2]) +def test_ewma_with_times_equal_spacing(halflife_with_times, times, min_periods): + halflife = halflife_with_times + data = np.arange(10.0) + data[::2] = np.nan + df = DataFrame({"A": data}) + result = df.ewm(halflife=halflife, min_periods=min_periods, times=times).mean() + expected = df.ewm(halflife=1.0, min_periods=min_periods).mean() + tm.assert_frame_equal(result, expected) + + +def test_ewma_with_times_variable_spacing(tz_aware_fixture, unit): + tz = tz_aware_fixture + halflife = "23 days" + times = ( + DatetimeIndex(["2020-01-01", "2020-01-10T00:04:05", "2020-02-23T05:00:23"]) + .tz_localize(tz) + .as_unit(unit) + ) + data = np.arange(3) + df = DataFrame(data) + result = df.ewm(halflife=halflife, times=times).mean() + expected = DataFrame([0.0, 0.5674161888241773, 1.545239952073459]) + tm.assert_frame_equal(result, expected) + + +def test_ewm_with_nat_raises(halflife_with_times): + # GH#38535 + ser = Series(range(1)) + times = DatetimeIndex(["NaT"]) + with pytest.raises(ValueError, match="Cannot convert NaT values to integer"): + ser.ewm(com=0.1, halflife=halflife_with_times, times=times) + + +def test_ewm_with_times_getitem(halflife_with_times): + # GH 40164 + halflife = halflife_with_times + data = np.arange(10.0) + data[::2] = np.nan + times = date_range("2000", freq="D", periods=10) + df = DataFrame({"A": data, "B": data}) + result = df.ewm(halflife=halflife, times=times)["A"].mean() + expected = df.ewm(halflife=1.0)["A"].mean() + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("arg", ["com", "halflife", "span", "alpha"]) +def test_ewm_getitem_attributes_retained(arg, adjust, ignore_na): + # GH 40164 + kwargs = {arg: 1, "adjust": adjust, "ignore_na": ignore_na} + ewm = DataFrame({"A": range(1), "B": range(1)}).ewm(**kwargs) + expected = {attr: getattr(ewm, attr) for attr in ewm._attributes} + ewm_slice = ewm["A"] + result = {attr: getattr(ewm, attr) for attr in ewm_slice._attributes} + assert result == expected + + +def test_ewma_times_adjust_false_raises(): + # GH 40098 + with pytest.raises( + NotImplementedError, match="times is not supported with adjust=False." + ): + Series(range(1)).ewm( + 0.1, adjust=False, times=date_range("2000", freq="D", periods=1) + ) + + +@pytest.mark.parametrize( + "func, expected", + [ + [ + "mean", + DataFrame( + { + 0: range(5), + 1: range(4, 9), + 2: [7.428571, 9, 10.571429, 12.142857, 13.714286], + }, + dtype=float, + ), + ], + [ + "std", + DataFrame( + { + 0: [np.nan] * 5, + 1: [4.242641] * 5, + 2: [4.6291, 5.196152, 5.781745, 6.380775, 6.989788], + } + ), + ], + [ + "var", + DataFrame( + { + 0: [np.nan] * 5, + 1: [18.0] * 5, + 2: [21.428571, 27, 33.428571, 40.714286, 48.857143], + } + ), + ], + ], +) +def test_float_dtype_ewma(func, expected, float_numpy_dtype): + # GH#42452 + + df = DataFrame( + {0: range(5), 1: range(6, 11), 2: range(10, 20, 2)}, dtype=float_numpy_dtype + ) + msg = "Support for axis=1 in DataFrame.ewm is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + e = df.ewm(alpha=0.5, axis=1) + result = getattr(e, func)() + + tm.assert_frame_equal(result, expected) + + +def test_times_string_col_raises(): + # GH 43265 + df = DataFrame( + {"A": np.arange(10.0), "time_col": date_range("2000", freq="D", periods=10)} + ) + with pytest.raises(ValueError, match="times must be datetime64"): + df.ewm(halflife="1 day", min_periods=0, times="time_col") + + +def test_ewm_sum_adjust_false_notimplemented(): + data = Series(range(1)).ewm(com=1, adjust=False) + with pytest.raises(NotImplementedError, match="sum is not"): + data.sum() + + +@pytest.mark.parametrize( + "expected_data, ignore", + [[[10.0, 5.0, 2.5, 11.25], False], [[10.0, 5.0, 5.0, 12.5], True]], +) +def test_ewm_sum(expected_data, ignore): + # xref from Numbagg tests + # https://github.com/numbagg/numbagg/blob/v0.2.1/numbagg/test/test_moving.py#L50 + data = Series([10, 0, np.nan, 10]) + result = data.ewm(alpha=0.5, ignore_na=ignore).sum() + expected = Series(expected_data) + tm.assert_series_equal(result, expected) + + +def test_ewma_adjust(): + vals = Series(np.zeros(1000)) + vals[5] = 1 + result = vals.ewm(span=100, adjust=False).mean().sum() + assert np.abs(result - 1) < 1e-2 + + +def test_ewma_cases(adjust, ignore_na): + # try adjust/ignore_na args matrix + + s = Series([1.0, 2.0, 4.0, 8.0]) + + if adjust: + expected = Series([1.0, 1.6, 2.736842, 4.923077]) + else: + expected = Series([1.0, 1.333333, 2.222222, 4.148148]) + + result = s.ewm(com=2.0, adjust=adjust, ignore_na=ignore_na).mean() + tm.assert_series_equal(result, expected) + + +def test_ewma_nan_handling(): + s = Series([1.0] + [np.nan] * 5 + [1.0]) + result = s.ewm(com=5).mean() + tm.assert_series_equal(result, Series([1.0] * len(s))) + + s = Series([np.nan] * 2 + [1.0] + [np.nan] * 2 + [1.0]) + result = s.ewm(com=5).mean() + tm.assert_series_equal(result, Series([np.nan] * 2 + [1.0] * 4)) + + +@pytest.mark.parametrize( + "s, adjust, ignore_na, w", + [ + ( + Series([np.nan, 1.0, 101.0]), + True, + False, + [np.nan, (1.0 - (1.0 / (1.0 + 2.0))), 1.0], + ), + ( + Series([np.nan, 1.0, 101.0]), + True, + True, + [np.nan, (1.0 - (1.0 / (1.0 + 2.0))), 1.0], + ), + ( + Series([np.nan, 1.0, 101.0]), + False, + False, + [np.nan, (1.0 - (1.0 / (1.0 + 2.0))), (1.0 / (1.0 + 2.0))], + ), + ( + Series([np.nan, 1.0, 101.0]), + False, + True, + [np.nan, (1.0 - (1.0 / (1.0 + 2.0))), (1.0 / (1.0 + 2.0))], + ), + ( + Series([1.0, np.nan, 101.0]), + True, + False, + [(1.0 - (1.0 / (1.0 + 2.0))) ** 2, np.nan, 1.0], + ), + ( + Series([1.0, np.nan, 101.0]), + True, + True, + [(1.0 - (1.0 / (1.0 + 2.0))), np.nan, 1.0], + ), + ( + Series([1.0, np.nan, 101.0]), + False, + False, + [(1.0 - (1.0 / (1.0 + 2.0))) ** 2, np.nan, (1.0 / (1.0 + 2.0))], + ), + ( + Series([1.0, np.nan, 101.0]), + False, + True, + [(1.0 - (1.0 / (1.0 + 2.0))), np.nan, (1.0 / (1.0 + 2.0))], + ), + ( + Series([np.nan, 1.0, np.nan, np.nan, 101.0, np.nan]), + True, + False, + [np.nan, (1.0 - (1.0 / (1.0 + 2.0))) ** 3, np.nan, np.nan, 1.0, np.nan], + ), + ( + Series([np.nan, 1.0, np.nan, np.nan, 101.0, np.nan]), + True, + True, + [np.nan, (1.0 - (1.0 / (1.0 + 2.0))), np.nan, np.nan, 1.0, np.nan], + ), + ( + Series([np.nan, 1.0, np.nan, np.nan, 101.0, np.nan]), + False, + False, + [ + np.nan, + (1.0 - (1.0 / (1.0 + 2.0))) ** 3, + np.nan, + np.nan, + (1.0 / (1.0 + 2.0)), + np.nan, + ], + ), + ( + Series([np.nan, 1.0, np.nan, np.nan, 101.0, np.nan]), + False, + True, + [ + np.nan, + (1.0 - (1.0 / (1.0 + 2.0))), + np.nan, + np.nan, + (1.0 / (1.0 + 2.0)), + np.nan, + ], + ), + ( + Series([1.0, np.nan, 101.0, 50.0]), + True, + False, + [ + (1.0 - (1.0 / (1.0 + 2.0))) ** 3, + np.nan, + (1.0 - (1.0 / (1.0 + 2.0))), + 1.0, + ], + ), + ( + Series([1.0, np.nan, 101.0, 50.0]), + True, + True, + [ + (1.0 - (1.0 / (1.0 + 2.0))) ** 2, + np.nan, + (1.0 - (1.0 / (1.0 + 2.0))), + 1.0, + ], + ), + ( + Series([1.0, np.nan, 101.0, 50.0]), + False, + False, + [ + (1.0 - (1.0 / (1.0 + 2.0))) ** 3, + np.nan, + (1.0 - (1.0 / (1.0 + 2.0))) * (1.0 / (1.0 + 2.0)), + (1.0 / (1.0 + 2.0)) + * ((1.0 - (1.0 / (1.0 + 2.0))) ** 2 + (1.0 / (1.0 + 2.0))), + ], + ), + ( + Series([1.0, np.nan, 101.0, 50.0]), + False, + True, + [ + (1.0 - (1.0 / (1.0 + 2.0))) ** 2, + np.nan, + (1.0 - (1.0 / (1.0 + 2.0))) * (1.0 / (1.0 + 2.0)), + (1.0 / (1.0 + 2.0)), + ], + ), + ], +) +def test_ewma_nan_handling_cases(s, adjust, ignore_na, w): + # GH 7603 + expected = (s.multiply(w).cumsum() / Series(w).cumsum()).ffill() + result = s.ewm(com=2.0, adjust=adjust, ignore_na=ignore_na).mean() + + tm.assert_series_equal(result, expected) + if ignore_na is False: + # check that ignore_na defaults to False + result = s.ewm(com=2.0, adjust=adjust).mean() + tm.assert_series_equal(result, expected) + + +def test_ewm_alpha(): + # GH 10789 + arr = np.random.default_rng(2).standard_normal(100) + locs = np.arange(20, 40) + arr[locs] = np.nan + + s = Series(arr) + a = s.ewm(alpha=0.61722699889169674).mean() + b = s.ewm(com=0.62014947789973052).mean() + c = s.ewm(span=2.240298955799461).mean() + d = s.ewm(halflife=0.721792864318).mean() + tm.assert_series_equal(a, b) + tm.assert_series_equal(a, c) + tm.assert_series_equal(a, d) + + +def test_ewm_domain_checks(): + # GH 12492 + arr = np.random.default_rng(2).standard_normal(100) + locs = np.arange(20, 40) + arr[locs] = np.nan + + s = Series(arr) + msg = "comass must satisfy: comass >= 0" + with pytest.raises(ValueError, match=msg): + s.ewm(com=-0.1) + s.ewm(com=0.0) + s.ewm(com=0.1) + + msg = "span must satisfy: span >= 1" + with pytest.raises(ValueError, match=msg): + s.ewm(span=-0.1) + with pytest.raises(ValueError, match=msg): + s.ewm(span=0.0) + with pytest.raises(ValueError, match=msg): + s.ewm(span=0.9) + s.ewm(span=1.0) + s.ewm(span=1.1) + + msg = "halflife must satisfy: halflife > 0" + with pytest.raises(ValueError, match=msg): + s.ewm(halflife=-0.1) + with pytest.raises(ValueError, match=msg): + s.ewm(halflife=0.0) + s.ewm(halflife=0.1) + + msg = "alpha must satisfy: 0 < alpha <= 1" + with pytest.raises(ValueError, match=msg): + s.ewm(alpha=-0.1) + with pytest.raises(ValueError, match=msg): + s.ewm(alpha=0.0) + s.ewm(alpha=0.1) + s.ewm(alpha=1.0) + with pytest.raises(ValueError, match=msg): + s.ewm(alpha=1.1) + + +@pytest.mark.parametrize("method", ["mean", "std", "var"]) +def test_ew_empty_series(method): + vals = Series([], dtype=np.float64) + + ewm = vals.ewm(3) + result = getattr(ewm, method)() + tm.assert_almost_equal(result, vals) + + +@pytest.mark.parametrize("min_periods", [0, 1]) +@pytest.mark.parametrize("name", ["mean", "var", "std"]) +def test_ew_min_periods(min_periods, name): + # excluding NaNs correctly + arr = np.random.default_rng(2).standard_normal(50) + arr[:10] = np.nan + arr[-10:] = np.nan + s = Series(arr) + + # check min_periods + # GH 7898 + result = getattr(s.ewm(com=50, min_periods=2), name)() + assert result[:11].isna().all() + assert not result[11:].isna().any() + + result = getattr(s.ewm(com=50, min_periods=min_periods), name)() + if name == "mean": + assert result[:10].isna().all() + assert not result[10:].isna().any() + else: + # ewm.std, ewm.var (with bias=False) require at least + # two values + assert result[:11].isna().all() + assert not result[11:].isna().any() + + # check series of length 0 + result = getattr(Series(dtype=object).ewm(com=50, min_periods=min_periods), name)() + tm.assert_series_equal(result, Series(dtype="float64")) + + # check series of length 1 + result = getattr(Series([1.0]).ewm(50, min_periods=min_periods), name)() + if name == "mean": + tm.assert_series_equal(result, Series([1.0])) + else: + # ewm.std, ewm.var with bias=False require at least + # two values + tm.assert_series_equal(result, Series([np.nan])) + + # pass in ints + result2 = getattr(Series(np.arange(50)).ewm(span=10), name)() + assert result2.dtype == np.float64 + + +@pytest.mark.parametrize("name", ["cov", "corr"]) +def test_ewm_corr_cov(name): + A = Series(np.random.default_rng(2).standard_normal(50), index=range(50)) + B = A[2:] + np.random.default_rng(2).standard_normal(48) + + A[:10] = np.nan + B.iloc[-10:] = np.nan + + result = getattr(A.ewm(com=20, min_periods=5), name)(B) + assert np.isnan(result.values[:14]).all() + assert not np.isnan(result.values[14:]).any() + + +@pytest.mark.parametrize("min_periods", [0, 1, 2]) +@pytest.mark.parametrize("name", ["cov", "corr"]) +def test_ewm_corr_cov_min_periods(name, min_periods): + # GH 7898 + A = Series(np.random.default_rng(2).standard_normal(50), index=range(50)) + B = A[2:] + np.random.default_rng(2).standard_normal(48) + + A[:10] = np.nan + B.iloc[-10:] = np.nan + + result = getattr(A.ewm(com=20, min_periods=min_periods), name)(B) + # binary functions (ewmcov, ewmcorr) with bias=False require at + # least two values + assert np.isnan(result.values[:11]).all() + assert not np.isnan(result.values[11:]).any() + + # check series of length 0 + empty = Series([], dtype=np.float64) + result = getattr(empty.ewm(com=50, min_periods=min_periods), name)(empty) + tm.assert_series_equal(result, empty) + + # check series of length 1 + result = getattr(Series([1.0]).ewm(com=50, min_periods=min_periods), name)( + Series([1.0]) + ) + tm.assert_series_equal(result, Series([np.nan])) + + +@pytest.mark.parametrize("name", ["cov", "corr"]) +def test_different_input_array_raise_exception(name): + A = Series(np.random.default_rng(2).standard_normal(50), index=range(50)) + A[:10] = np.nan + + msg = "other must be a DataFrame or Series" + # exception raised is Exception + with pytest.raises(ValueError, match=msg): + getattr(A.ewm(com=20, min_periods=5), name)( + np.random.default_rng(2).standard_normal(50) + ) + + +@pytest.mark.parametrize("name", ["var", "std", "mean"]) +def test_ewma_series(series, name): + series_result = getattr(series.ewm(com=10), name)() + assert isinstance(series_result, Series) + + +@pytest.mark.parametrize("name", ["var", "std", "mean"]) +def test_ewma_frame(frame, name): + frame_result = getattr(frame.ewm(com=10), name)() + assert isinstance(frame_result, DataFrame) + + +def test_ewma_span_com_args(series): + A = series.ewm(com=9.5).mean() + B = series.ewm(span=20).mean() + tm.assert_almost_equal(A, B) + msg = "comass, span, halflife, and alpha are mutually exclusive" + with pytest.raises(ValueError, match=msg): + series.ewm(com=9.5, span=20) + + msg = "Must pass one of comass, span, halflife, or alpha" + with pytest.raises(ValueError, match=msg): + series.ewm().mean() + + +def test_ewma_halflife_arg(series): + A = series.ewm(com=13.932726172912965).mean() + B = series.ewm(halflife=10.0).mean() + tm.assert_almost_equal(A, B) + msg = "comass, span, halflife, and alpha are mutually exclusive" + with pytest.raises(ValueError, match=msg): + series.ewm(span=20, halflife=50) + with pytest.raises(ValueError, match=msg): + series.ewm(com=9.5, halflife=50) + with pytest.raises(ValueError, match=msg): + series.ewm(com=9.5, span=20, halflife=50) + msg = "Must pass one of comass, span, halflife, or alpha" + with pytest.raises(ValueError, match=msg): + series.ewm() + + +def test_ewm_alpha_arg(series): + # GH 10789 + s = series + msg = "Must pass one of comass, span, halflife, or alpha" + with pytest.raises(ValueError, match=msg): + s.ewm() + + msg = "comass, span, halflife, and alpha are mutually exclusive" + with pytest.raises(ValueError, match=msg): + s.ewm(com=10.0, alpha=0.5) + with pytest.raises(ValueError, match=msg): + s.ewm(span=10.0, alpha=0.5) + with pytest.raises(ValueError, match=msg): + s.ewm(halflife=10.0, alpha=0.5) + + +@pytest.mark.parametrize("func", ["cov", "corr"]) +def test_ewm_pairwise_cov_corr(func, frame): + result = getattr(frame.ewm(span=10, min_periods=5), func)() + result = result.loc[(slice(None), 1), 5] + result.index = result.index.droplevel(1) + expected = getattr(frame[1].ewm(span=10, min_periods=5), func)(frame[5]) + tm.assert_series_equal(result, expected, check_names=False) + + +def test_numeric_only_frame(arithmetic_win_operators, numeric_only): + # GH#46560 + kernel = arithmetic_win_operators + df = DataFrame({"a": [1], "b": 2, "c": 3}) + df["c"] = df["c"].astype(object) + ewm = df.ewm(span=2, min_periods=1) + op = getattr(ewm, kernel, None) + if op is not None: + result = op(numeric_only=numeric_only) + + columns = ["a", "b"] if numeric_only else ["a", "b", "c"] + expected = df[columns].agg([kernel]).reset_index(drop=True).astype(float) + assert list(expected.columns) == columns + + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("kernel", ["corr", "cov"]) +@pytest.mark.parametrize("use_arg", [True, False]) +def test_numeric_only_corr_cov_frame(kernel, numeric_only, use_arg): + # GH#46560 + df = DataFrame({"a": [1, 2, 3], "b": 2, "c": 3}) + df["c"] = df["c"].astype(object) + arg = (df,) if use_arg else () + ewm = df.ewm(span=2, min_periods=1) + op = getattr(ewm, kernel) + result = op(*arg, numeric_only=numeric_only) + + # Compare result to op using float dtypes, dropping c when numeric_only is True + columns = ["a", "b"] if numeric_only else ["a", "b", "c"] + df2 = df[columns].astype(float) + arg2 = (df2,) if use_arg else () + ewm2 = df2.ewm(span=2, min_periods=1) + op2 = getattr(ewm2, kernel) + expected = op2(*arg2, numeric_only=numeric_only) + + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("dtype", [int, object]) +def test_numeric_only_series(arithmetic_win_operators, numeric_only, dtype): + # GH#46560 + kernel = arithmetic_win_operators + ser = Series([1], dtype=dtype) + ewm = ser.ewm(span=2, min_periods=1) + op = getattr(ewm, kernel, None) + if op is None: + # Nothing to test + pytest.skip("No op to test") + if numeric_only and dtype is object: + msg = f"ExponentialMovingWindow.{kernel} does not implement numeric_only" + with pytest.raises(NotImplementedError, match=msg): + op(numeric_only=numeric_only) + else: + result = op(numeric_only=numeric_only) + expected = ser.agg([kernel]).reset_index(drop=True).astype(float) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("kernel", ["corr", "cov"]) +@pytest.mark.parametrize("use_arg", [True, False]) +@pytest.mark.parametrize("dtype", [int, object]) +def test_numeric_only_corr_cov_series(kernel, use_arg, numeric_only, dtype): + # GH#46560 + ser = Series([1, 2, 3], dtype=dtype) + arg = (ser,) if use_arg else () + ewm = ser.ewm(span=2, min_periods=1) + op = getattr(ewm, kernel) + if numeric_only and dtype is object: + msg = f"ExponentialMovingWindow.{kernel} does not implement numeric_only" + with pytest.raises(NotImplementedError, match=msg): + op(*arg, numeric_only=numeric_only) + else: + result = op(*arg, numeric_only=numeric_only) + + ser2 = ser.astype(float) + arg2 = (ser2,) if use_arg else () + ewm2 = ser2.ewm(span=2, min_periods=1) + op2 = getattr(ewm2, kernel) + expected = op2(*arg2, numeric_only=numeric_only) + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_expanding.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_expanding.py new file mode 100644 index 0000000000000000000000000000000000000000..aebb9e86c763f265b740e79e3e1e76e7ffe2dd94 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_expanding.py @@ -0,0 +1,723 @@ +import numpy as np +import pytest + +from pandas import ( + DataFrame, + DatetimeIndex, + Index, + MultiIndex, + Series, + isna, + notna, +) +import pandas._testing as tm + + +def test_doc_string(): + df = DataFrame({"B": [0, 1, 2, np.nan, 4]}) + df + df.expanding(2).sum() + + +def test_constructor(frame_or_series): + # GH 12669 + + c = frame_or_series(range(5)).expanding + + # valid + c(min_periods=1) + + +@pytest.mark.parametrize("w", [2.0, "foo", np.array([2])]) +def test_constructor_invalid(frame_or_series, w): + # not valid + + c = frame_or_series(range(5)).expanding + msg = "min_periods must be an integer" + with pytest.raises(ValueError, match=msg): + c(min_periods=w) + + +@pytest.mark.parametrize( + "expander", + [ + 1, + pytest.param( + "ls", + marks=pytest.mark.xfail( + reason="GH#16425 expanding with offset not supported" + ), + ), + ], +) +def test_empty_df_expanding(expander): + # GH 15819 Verifies that datetime and integer expanding windows can be + # applied to empty DataFrames + + expected = DataFrame() + result = DataFrame().expanding(expander).sum() + tm.assert_frame_equal(result, expected) + + # Verifies that datetime and integer expanding windows can be applied + # to empty DataFrames with datetime index + expected = DataFrame(index=DatetimeIndex([])) + result = DataFrame(index=DatetimeIndex([])).expanding(expander).sum() + tm.assert_frame_equal(result, expected) + + +def test_missing_minp_zero(): + # https://github.com/pandas-dev/pandas/pull/18921 + # minp=0 + x = Series([np.nan]) + result = x.expanding(min_periods=0).sum() + expected = Series([0.0]) + tm.assert_series_equal(result, expected) + + # minp=1 + result = x.expanding(min_periods=1).sum() + expected = Series([np.nan]) + tm.assert_series_equal(result, expected) + + +def test_expanding_axis(axis_frame): + # see gh-23372. + df = DataFrame(np.ones((10, 20))) + axis = df._get_axis_number(axis_frame) + + if axis == 0: + msg = "The 'axis' keyword in DataFrame.expanding is deprecated" + expected = DataFrame( + {i: [np.nan] * 2 + [float(j) for j in range(3, 11)] for i in range(20)} + ) + else: + # axis == 1 + msg = "Support for axis=1 in DataFrame.expanding is deprecated" + expected = DataFrame([[np.nan] * 2 + [float(i) for i in range(3, 21)]] * 10) + + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.expanding(3, axis=axis_frame).sum() + tm.assert_frame_equal(result, expected) + + +def test_expanding_count_with_min_periods(frame_or_series): + # GH 26996 + result = frame_or_series(range(5)).expanding(min_periods=3).count() + expected = frame_or_series([np.nan, np.nan, 3.0, 4.0, 5.0]) + tm.assert_equal(result, expected) + + +def test_expanding_count_default_min_periods_with_null_values(frame_or_series): + # GH 26996 + values = [1, 2, 3, np.nan, 4, 5, 6] + expected_counts = [1.0, 2.0, 3.0, 3.0, 4.0, 5.0, 6.0] + + result = frame_or_series(values).expanding().count() + expected = frame_or_series(expected_counts) + tm.assert_equal(result, expected) + + +def test_expanding_count_with_min_periods_exceeding_series_length(frame_or_series): + # GH 25857 + result = frame_or_series(range(5)).expanding(min_periods=6).count() + expected = frame_or_series([np.nan, np.nan, np.nan, np.nan, np.nan]) + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "df,expected,min_periods", + [ + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]), + ], + 3, + ), + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]), + ], + 2, + ), + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]), + ], + 1, + ), + (DataFrame({"A": [1], "B": [4]}), [], 2), + (DataFrame(), [({}, [])], 1), + ( + DataFrame({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}), + [ + ({"A": [1.0], "B": [np.nan]}, [0]), + ({"A": [1, np.nan], "B": [np.nan, 5]}, [0, 1]), + ({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}, [0, 1, 2]), + ], + 3, + ), + ( + DataFrame({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}), + [ + ({"A": [1.0], "B": [np.nan]}, [0]), + ({"A": [1, np.nan], "B": [np.nan, 5]}, [0, 1]), + ({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}, [0, 1, 2]), + ], + 2, + ), + ( + DataFrame({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}), + [ + ({"A": [1.0], "B": [np.nan]}, [0]), + ({"A": [1, np.nan], "B": [np.nan, 5]}, [0, 1]), + ({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}, [0, 1, 2]), + ], + 1, + ), + ], +) +def test_iter_expanding_dataframe(df, expected, min_periods): + # GH 11704 + expected = [DataFrame(values, index=index) for (values, index) in expected] + + for expected, actual in zip(expected, df.expanding(min_periods)): + tm.assert_frame_equal(actual, expected) + + +@pytest.mark.parametrize( + "ser,expected,min_periods", + [ + (Series([1, 2, 3]), [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], 3), + (Series([1, 2, 3]), [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], 2), + (Series([1, 2, 3]), [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], 1), + (Series([1, 2]), [([1], [0]), ([1, 2], [0, 1])], 2), + (Series([np.nan, 2]), [([np.nan], [0]), ([np.nan, 2], [0, 1])], 2), + (Series([], dtype="int64"), [], 2), + ], +) +def test_iter_expanding_series(ser, expected, min_periods): + # GH 11704 + expected = [Series(values, index=index) for (values, index) in expected] + + for expected, actual in zip(expected, ser.expanding(min_periods)): + tm.assert_series_equal(actual, expected) + + +def test_center_invalid(): + # GH 20647 + df = DataFrame() + with pytest.raises(TypeError, match=".* got an unexpected keyword"): + df.expanding(center=True) + + +def test_expanding_sem(frame_or_series): + # GH: 26476 + obj = frame_or_series([0, 1, 2]) + result = obj.expanding().sem() + if isinstance(result, DataFrame): + result = Series(result[0].values) + expected = Series([np.nan] + [0.707107] * 2) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("method", ["skew", "kurt"]) +def test_expanding_skew_kurt_numerical_stability(method): + # GH: 6929 + s = Series(np.random.default_rng(2).random(10)) + expected = getattr(s.expanding(3), method)() + s = s + 5000 + result = getattr(s.expanding(3), method)() + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("window", [1, 3, 10, 20]) +@pytest.mark.parametrize("method", ["min", "max", "average"]) +@pytest.mark.parametrize("pct", [True, False]) +@pytest.mark.parametrize("ascending", [True, False]) +@pytest.mark.parametrize("test_data", ["default", "duplicates", "nans"]) +def test_rank(window, method, pct, ascending, test_data): + length = 20 + if test_data == "default": + ser = Series(data=np.random.default_rng(2).random(length)) + elif test_data == "duplicates": + ser = Series(data=np.random.default_rng(2).choice(3, length)) + elif test_data == "nans": + ser = Series( + data=np.random.default_rng(2).choice( + [1.0, 0.25, 0.75, np.nan, np.inf, -np.inf], length + ) + ) + + expected = ser.expanding(window).apply( + lambda x: x.rank(method=method, pct=pct, ascending=ascending).iloc[-1] + ) + result = ser.expanding(window).rank(method=method, pct=pct, ascending=ascending) + + tm.assert_series_equal(result, expected) + + +def test_expanding_corr(series): + A = series.dropna() + B = (A + np.random.default_rng(2).standard_normal(len(A)))[:-5] + + result = A.expanding().corr(B) + + rolling_result = A.rolling(window=len(A), min_periods=1).corr(B) + + tm.assert_almost_equal(rolling_result, result) + + +def test_expanding_count(series): + result = series.expanding(min_periods=0).count() + tm.assert_almost_equal( + result, series.rolling(window=len(series), min_periods=0).count() + ) + + +def test_expanding_quantile(series): + result = series.expanding().quantile(0.5) + + rolling_result = series.rolling(window=len(series), min_periods=1).quantile(0.5) + + tm.assert_almost_equal(result, rolling_result) + + +def test_expanding_cov(series): + A = series + B = (A + np.random.default_rng(2).standard_normal(len(A)))[:-5] + + result = A.expanding().cov(B) + + rolling_result = A.rolling(window=len(A), min_periods=1).cov(B) + + tm.assert_almost_equal(rolling_result, result) + + +def test_expanding_cov_pairwise(frame): + result = frame.expanding().cov() + + rolling_result = frame.rolling(window=len(frame), min_periods=1).cov() + + tm.assert_frame_equal(result, rolling_result) + + +def test_expanding_corr_pairwise(frame): + result = frame.expanding().corr() + + rolling_result = frame.rolling(window=len(frame), min_periods=1).corr() + tm.assert_frame_equal(result, rolling_result) + + +@pytest.mark.parametrize( + "func,static_comp", + [ + ("sum", np.sum), + ("mean", lambda x: np.mean(x, axis=0)), + ("max", lambda x: np.max(x, axis=0)), + ("min", lambda x: np.min(x, axis=0)), + ], + ids=["sum", "mean", "max", "min"], +) +def test_expanding_func(func, static_comp, frame_or_series): + data = frame_or_series(np.array(list(range(10)) + [np.nan] * 10)) + + msg = "The 'axis' keyword in (Series|DataFrame).expanding is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + obj = data.expanding(min_periods=1, axis=0) + result = getattr(obj, func)() + assert isinstance(result, frame_or_series) + + msg = "The behavior of DataFrame.sum with axis=None is deprecated" + warn = None + if frame_or_series is DataFrame and static_comp is np.sum: + warn = FutureWarning + with tm.assert_produces_warning(warn, match=msg, check_stacklevel=False): + expected = static_comp(data[:11]) + if frame_or_series is Series: + tm.assert_almost_equal(result[10], expected) + else: + tm.assert_series_equal(result.iloc[10], expected, check_names=False) + + +@pytest.mark.parametrize( + "func,static_comp", + [("sum", np.sum), ("mean", np.mean), ("max", np.max), ("min", np.min)], + ids=["sum", "mean", "max", "min"], +) +def test_expanding_min_periods(func, static_comp): + ser = Series(np.random.default_rng(2).standard_normal(50)) + + msg = "The 'axis' keyword in Series.expanding is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = getattr(ser.expanding(min_periods=30, axis=0), func)() + assert result[:29].isna().all() + tm.assert_almost_equal(result.iloc[-1], static_comp(ser[:50])) + + # min_periods is working correctly + with tm.assert_produces_warning(FutureWarning, match=msg): + result = getattr(ser.expanding(min_periods=15, axis=0), func)() + assert isna(result.iloc[13]) + assert notna(result.iloc[14]) + + ser2 = Series(np.random.default_rng(2).standard_normal(20)) + with tm.assert_produces_warning(FutureWarning, match=msg): + result = getattr(ser2.expanding(min_periods=5, axis=0), func)() + assert isna(result[3]) + assert notna(result[4]) + + # min_periods=0 + with tm.assert_produces_warning(FutureWarning, match=msg): + result0 = getattr(ser.expanding(min_periods=0, axis=0), func)() + with tm.assert_produces_warning(FutureWarning, match=msg): + result1 = getattr(ser.expanding(min_periods=1, axis=0), func)() + tm.assert_almost_equal(result0, result1) + + with tm.assert_produces_warning(FutureWarning, match=msg): + result = getattr(ser.expanding(min_periods=1, axis=0), func)() + tm.assert_almost_equal(result.iloc[-1], static_comp(ser[:50])) + + +def test_expanding_apply(engine_and_raw, frame_or_series): + engine, raw = engine_and_raw + data = frame_or_series(np.array(list(range(10)) + [np.nan] * 10)) + result = data.expanding(min_periods=1).apply( + lambda x: x.mean(), raw=raw, engine=engine + ) + assert isinstance(result, frame_or_series) + + if frame_or_series is Series: + tm.assert_almost_equal(result[9], np.mean(data[:11], axis=0)) + else: + tm.assert_series_equal( + result.iloc[9], np.mean(data[:11], axis=0), check_names=False + ) + + +def test_expanding_min_periods_apply(engine_and_raw): + engine, raw = engine_and_raw + ser = Series(np.random.default_rng(2).standard_normal(50)) + + result = ser.expanding(min_periods=30).apply( + lambda x: x.mean(), raw=raw, engine=engine + ) + assert result[:29].isna().all() + tm.assert_almost_equal(result.iloc[-1], np.mean(ser[:50])) + + # min_periods is working correctly + result = ser.expanding(min_periods=15).apply( + lambda x: x.mean(), raw=raw, engine=engine + ) + assert isna(result.iloc[13]) + assert notna(result.iloc[14]) + + ser2 = Series(np.random.default_rng(2).standard_normal(20)) + result = ser2.expanding(min_periods=5).apply( + lambda x: x.mean(), raw=raw, engine=engine + ) + assert isna(result[3]) + assert notna(result[4]) + + # min_periods=0 + result0 = ser.expanding(min_periods=0).apply( + lambda x: x.mean(), raw=raw, engine=engine + ) + result1 = ser.expanding(min_periods=1).apply( + lambda x: x.mean(), raw=raw, engine=engine + ) + tm.assert_almost_equal(result0, result1) + + result = ser.expanding(min_periods=1).apply( + lambda x: x.mean(), raw=raw, engine=engine + ) + tm.assert_almost_equal(result.iloc[-1], np.mean(ser[:50])) + + +@pytest.mark.parametrize( + "f", + [ + lambda x: (x.expanding(min_periods=5).cov(x, pairwise=True)), + lambda x: (x.expanding(min_periods=5).corr(x, pairwise=True)), + ], +) +def test_moment_functions_zero_length_pairwise(f): + df1 = DataFrame() + df2 = DataFrame(columns=Index(["a"], name="foo"), index=Index([], name="bar")) + df2["a"] = df2["a"].astype("float64") + + df1_expected = DataFrame(index=MultiIndex.from_product([df1.index, df1.columns])) + df2_expected = DataFrame( + index=MultiIndex.from_product([df2.index, df2.columns], names=["bar", "foo"]), + columns=Index(["a"], name="foo"), + dtype="float64", + ) + + df1_result = f(df1) + tm.assert_frame_equal(df1_result, df1_expected) + + df2_result = f(df2) + tm.assert_frame_equal(df2_result, df2_expected) + + +@pytest.mark.parametrize( + "f", + [ + lambda x: x.expanding().count(), + lambda x: x.expanding(min_periods=5).cov(x, pairwise=False), + lambda x: x.expanding(min_periods=5).corr(x, pairwise=False), + lambda x: x.expanding(min_periods=5).max(), + lambda x: x.expanding(min_periods=5).min(), + lambda x: x.expanding(min_periods=5).sum(), + lambda x: x.expanding(min_periods=5).mean(), + lambda x: x.expanding(min_periods=5).std(), + lambda x: x.expanding(min_periods=5).var(), + lambda x: x.expanding(min_periods=5).skew(), + lambda x: x.expanding(min_periods=5).kurt(), + lambda x: x.expanding(min_periods=5).quantile(0.5), + lambda x: x.expanding(min_periods=5).median(), + lambda x: x.expanding(min_periods=5).apply(sum, raw=False), + lambda x: x.expanding(min_periods=5).apply(sum, raw=True), + ], +) +def test_moment_functions_zero_length(f): + # GH 8056 + s = Series(dtype=np.float64) + s_expected = s + df1 = DataFrame() + df1_expected = df1 + df2 = DataFrame(columns=["a"]) + df2["a"] = df2["a"].astype("float64") + df2_expected = df2 + + s_result = f(s) + tm.assert_series_equal(s_result, s_expected) + + df1_result = f(df1) + tm.assert_frame_equal(df1_result, df1_expected) + + df2_result = f(df2) + tm.assert_frame_equal(df2_result, df2_expected) + + +def test_expanding_apply_empty_series(engine_and_raw): + engine, raw = engine_and_raw + ser = Series([], dtype=np.float64) + tm.assert_series_equal( + ser, ser.expanding().apply(lambda x: x.mean(), raw=raw, engine=engine) + ) + + +def test_expanding_apply_min_periods_0(engine_and_raw): + # GH 8080 + engine, raw = engine_and_raw + s = Series([None, None, None]) + result = s.expanding(min_periods=0).apply(lambda x: len(x), raw=raw, engine=engine) + expected = Series([1.0, 2.0, 3.0]) + tm.assert_series_equal(result, expected) + + +def test_expanding_cov_diff_index(): + # GH 7512 + s1 = Series([1, 2, 3], index=[0, 1, 2]) + s2 = Series([1, 3], index=[0, 2]) + result = s1.expanding().cov(s2) + expected = Series([None, None, 2.0]) + tm.assert_series_equal(result, expected) + + s2a = Series([1, None, 3], index=[0, 1, 2]) + result = s1.expanding().cov(s2a) + tm.assert_series_equal(result, expected) + + s1 = Series([7, 8, 10], index=[0, 1, 3]) + s2 = Series([7, 9, 10], index=[0, 2, 3]) + result = s1.expanding().cov(s2) + expected = Series([None, None, None, 4.5]) + tm.assert_series_equal(result, expected) + + +def test_expanding_corr_diff_index(): + # GH 7512 + s1 = Series([1, 2, 3], index=[0, 1, 2]) + s2 = Series([1, 3], index=[0, 2]) + result = s1.expanding().corr(s2) + expected = Series([None, None, 1.0]) + tm.assert_series_equal(result, expected) + + s2a = Series([1, None, 3], index=[0, 1, 2]) + result = s1.expanding().corr(s2a) + tm.assert_series_equal(result, expected) + + s1 = Series([7, 8, 10], index=[0, 1, 3]) + s2 = Series([7, 9, 10], index=[0, 2, 3]) + result = s1.expanding().corr(s2) + expected = Series([None, None, None, 1.0]) + tm.assert_series_equal(result, expected) + + +def test_expanding_cov_pairwise_diff_length(): + # GH 7512 + df1 = DataFrame([[1, 5], [3, 2], [3, 9]], columns=Index(["A", "B"], name="foo")) + df1a = DataFrame( + [[1, 5], [3, 9]], index=[0, 2], columns=Index(["A", "B"], name="foo") + ) + df2 = DataFrame( + [[5, 6], [None, None], [2, 1]], columns=Index(["X", "Y"], name="foo") + ) + df2a = DataFrame( + [[5, 6], [2, 1]], index=[0, 2], columns=Index(["X", "Y"], name="foo") + ) + # TODO: xref gh-15826 + # .loc is not preserving the names + result1 = df1.expanding().cov(df2, pairwise=True).loc[2] + result2 = df1.expanding().cov(df2a, pairwise=True).loc[2] + result3 = df1a.expanding().cov(df2, pairwise=True).loc[2] + result4 = df1a.expanding().cov(df2a, pairwise=True).loc[2] + expected = DataFrame( + [[-3.0, -6.0], [-5.0, -10.0]], + columns=Index(["A", "B"], name="foo"), + index=Index(["X", "Y"], name="foo"), + ) + tm.assert_frame_equal(result1, expected) + tm.assert_frame_equal(result2, expected) + tm.assert_frame_equal(result3, expected) + tm.assert_frame_equal(result4, expected) + + +def test_expanding_corr_pairwise_diff_length(): + # GH 7512 + df1 = DataFrame( + [[1, 2], [3, 2], [3, 4]], columns=["A", "B"], index=Index(range(3), name="bar") + ) + df1a = DataFrame( + [[1, 2], [3, 4]], index=Index([0, 2], name="bar"), columns=["A", "B"] + ) + df2 = DataFrame( + [[5, 6], [None, None], [2, 1]], + columns=["X", "Y"], + index=Index(range(3), name="bar"), + ) + df2a = DataFrame( + [[5, 6], [2, 1]], index=Index([0, 2], name="bar"), columns=["X", "Y"] + ) + result1 = df1.expanding().corr(df2, pairwise=True).loc[2] + result2 = df1.expanding().corr(df2a, pairwise=True).loc[2] + result3 = df1a.expanding().corr(df2, pairwise=True).loc[2] + result4 = df1a.expanding().corr(df2a, pairwise=True).loc[2] + expected = DataFrame( + [[-1.0, -1.0], [-1.0, -1.0]], columns=["A", "B"], index=Index(["X", "Y"]) + ) + tm.assert_frame_equal(result1, expected) + tm.assert_frame_equal(result2, expected) + tm.assert_frame_equal(result3, expected) + tm.assert_frame_equal(result4, expected) + + +def test_expanding_apply_args_kwargs(engine_and_raw): + def mean_w_arg(x, const): + return np.mean(x) + const + + engine, raw = engine_and_raw + + df = DataFrame(np.random.default_rng(2).random((20, 3))) + + expected = df.expanding().apply(np.mean, engine=engine, raw=raw) + 20.0 + + result = df.expanding().apply(mean_w_arg, engine=engine, raw=raw, args=(20,)) + tm.assert_frame_equal(result, expected) + + result = df.expanding().apply(mean_w_arg, raw=raw, kwargs={"const": 20}) + tm.assert_frame_equal(result, expected) + + +def test_numeric_only_frame(arithmetic_win_operators, numeric_only): + # GH#46560 + kernel = arithmetic_win_operators + df = DataFrame({"a": [1], "b": 2, "c": 3}) + df["c"] = df["c"].astype(object) + expanding = df.expanding() + op = getattr(expanding, kernel, None) + if op is not None: + result = op(numeric_only=numeric_only) + + columns = ["a", "b"] if numeric_only else ["a", "b", "c"] + expected = df[columns].agg([kernel]).reset_index(drop=True).astype(float) + assert list(expected.columns) == columns + + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("kernel", ["corr", "cov"]) +@pytest.mark.parametrize("use_arg", [True, False]) +def test_numeric_only_corr_cov_frame(kernel, numeric_only, use_arg): + # GH#46560 + df = DataFrame({"a": [1, 2, 3], "b": 2, "c": 3}) + df["c"] = df["c"].astype(object) + arg = (df,) if use_arg else () + expanding = df.expanding() + op = getattr(expanding, kernel) + result = op(*arg, numeric_only=numeric_only) + + # Compare result to op using float dtypes, dropping c when numeric_only is True + columns = ["a", "b"] if numeric_only else ["a", "b", "c"] + df2 = df[columns].astype(float) + arg2 = (df2,) if use_arg else () + expanding2 = df2.expanding() + op2 = getattr(expanding2, kernel) + expected = op2(*arg2, numeric_only=numeric_only) + + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("dtype", [int, object]) +def test_numeric_only_series(arithmetic_win_operators, numeric_only, dtype): + # GH#46560 + kernel = arithmetic_win_operators + ser = Series([1], dtype=dtype) + expanding = ser.expanding() + op = getattr(expanding, kernel) + if numeric_only and dtype is object: + msg = f"Expanding.{kernel} does not implement numeric_only" + with pytest.raises(NotImplementedError, match=msg): + op(numeric_only=numeric_only) + else: + result = op(numeric_only=numeric_only) + expected = ser.agg([kernel]).reset_index(drop=True).astype(float) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("kernel", ["corr", "cov"]) +@pytest.mark.parametrize("use_arg", [True, False]) +@pytest.mark.parametrize("dtype", [int, object]) +def test_numeric_only_corr_cov_series(kernel, use_arg, numeric_only, dtype): + # GH#46560 + ser = Series([1, 2, 3], dtype=dtype) + arg = (ser,) if use_arg else () + expanding = ser.expanding() + op = getattr(expanding, kernel) + if numeric_only and dtype is object: + msg = f"Expanding.{kernel} does not implement numeric_only" + with pytest.raises(NotImplementedError, match=msg): + op(*arg, numeric_only=numeric_only) + else: + result = op(*arg, numeric_only=numeric_only) + + ser2 = ser.astype(float) + arg2 = (ser2,) if use_arg else () + expanding2 = ser2.expanding() + op2 = getattr(expanding2, kernel) + expected = op2(*arg2, numeric_only=numeric_only) + tm.assert_series_equal(result, expected) + + +def test_keyword_quantile_deprecated(): + # GH #52550 + ser = Series([1, 2, 3, 4]) + with tm.assert_produces_warning(FutureWarning): + ser.expanding().quantile(quantile=0.5) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_groupby.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_groupby.py new file mode 100644 index 0000000000000000000000000000000000000000..400bf10817ab871abafcfc39baf57c340d3cbb0a --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_groupby.py @@ -0,0 +1,1318 @@ +import numpy as np +import pytest + +from pandas import ( + DataFrame, + DatetimeIndex, + Index, + MultiIndex, + Series, + Timestamp, + date_range, + to_datetime, +) +import pandas._testing as tm +from pandas.api.indexers import BaseIndexer +from pandas.core.groupby.groupby import get_groupby + + +@pytest.fixture +def times_frame(): + """Frame for testing times argument in EWM groupby.""" + return DataFrame( + { + "A": ["a", "b", "c", "a", "b", "c", "a", "b", "c", "a"], + "B": [0, 0, 0, 1, 1, 1, 2, 2, 2, 3], + "C": to_datetime( + [ + "2020-01-01", + "2020-01-01", + "2020-01-01", + "2020-01-02", + "2020-01-10", + "2020-01-22", + "2020-01-03", + "2020-01-23", + "2020-01-23", + "2020-01-04", + ] + ), + } + ) + + +@pytest.fixture +def roll_frame(): + return DataFrame({"A": [1] * 20 + [2] * 12 + [3] * 8, "B": np.arange(40)}) + + +class TestRolling: + def test_groupby_unsupported_argument(self, roll_frame): + msg = r"groupby\(\) got an unexpected keyword argument 'foo'" + with pytest.raises(TypeError, match=msg): + roll_frame.groupby("A", foo=1) + + def test_getitem(self, roll_frame): + g = roll_frame.groupby("A") + g_mutated = get_groupby(roll_frame, by="A") + + expected = g_mutated.B.apply(lambda x: x.rolling(2).mean()) + + result = g.rolling(2).mean().B + tm.assert_series_equal(result, expected) + + result = g.rolling(2).B.mean() + tm.assert_series_equal(result, expected) + + result = g.B.rolling(2).mean() + tm.assert_series_equal(result, expected) + + result = roll_frame.B.groupby(roll_frame.A).rolling(2).mean() + tm.assert_series_equal(result, expected) + + def test_getitem_multiple(self, roll_frame): + # GH 13174 + g = roll_frame.groupby("A") + r = g.rolling(2, min_periods=0) + g_mutated = get_groupby(roll_frame, by="A") + expected = g_mutated.B.apply(lambda x: x.rolling(2, min_periods=0).count()) + + result = r.B.count() + tm.assert_series_equal(result, expected) + + result = r.B.count() + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "f", + [ + "sum", + "mean", + "min", + "max", + "count", + "kurt", + "skew", + ], + ) + def test_rolling(self, f, roll_frame): + g = roll_frame.groupby("A", group_keys=False) + r = g.rolling(window=4) + + result = getattr(r, f)() + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(lambda x: getattr(x.rolling(4), f)()) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([roll_frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("f", ["std", "var"]) + def test_rolling_ddof(self, f, roll_frame): + g = roll_frame.groupby("A", group_keys=False) + r = g.rolling(window=4) + + result = getattr(r, f)(ddof=1) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(lambda x: getattr(x.rolling(4), f)(ddof=1)) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([roll_frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize( + "interpolation", ["linear", "lower", "higher", "midpoint", "nearest"] + ) + def test_rolling_quantile(self, interpolation, roll_frame): + g = roll_frame.groupby("A", group_keys=False) + r = g.rolling(window=4) + + result = r.quantile(0.4, interpolation=interpolation) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply( + lambda x: x.rolling(4).quantile(0.4, interpolation=interpolation) + ) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([roll_frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("f, expected_val", [["corr", 1], ["cov", 0.5]]) + def test_rolling_corr_cov_other_same_size_as_groups(self, f, expected_val): + # GH 42915 + df = DataFrame( + {"value": range(10), "idx1": [1] * 5 + [2] * 5, "idx2": [1, 2, 3, 4, 5] * 2} + ).set_index(["idx1", "idx2"]) + other = DataFrame({"value": range(5), "idx2": [1, 2, 3, 4, 5]}).set_index( + "idx2" + ) + result = getattr(df.groupby(level=0).rolling(2), f)(other) + expected_data = ([np.nan] + [expected_val] * 4) * 2 + expected = DataFrame( + expected_data, + columns=["value"], + index=MultiIndex.from_arrays( + [ + [1] * 5 + [2] * 5, + [1] * 5 + [2] * 5, + list(range(1, 6)) * 2, + ], + names=["idx1", "idx1", "idx2"], + ), + ) + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("f", ["corr", "cov"]) + def test_rolling_corr_cov_other_diff_size_as_groups(self, f, roll_frame): + g = roll_frame.groupby("A") + r = g.rolling(window=4) + + result = getattr(r, f)(roll_frame) + + def func(x): + return getattr(x.rolling(4), f)(roll_frame) + + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(func) + # GH 39591: The grouped column should be all np.nan + # (groupby.apply inserts 0s for cov) + expected["A"] = np.nan + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("f", ["corr", "cov"]) + def test_rolling_corr_cov_pairwise(self, f, roll_frame): + g = roll_frame.groupby("A") + r = g.rolling(window=4) + + result = getattr(r.B, f)(pairwise=True) + + def func(x): + return getattr(x.B.rolling(4), f)(pairwise=True) + + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(func) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "func, expected_values", + [("cov", [[1.0, 1.0], [1.0, 4.0]]), ("corr", [[1.0, 0.5], [0.5, 1.0]])], + ) + def test_rolling_corr_cov_unordered(self, func, expected_values): + # GH 43386 + df = DataFrame( + { + "a": ["g1", "g2", "g1", "g1"], + "b": [0, 0, 1, 2], + "c": [2, 0, 6, 4], + } + ) + rol = df.groupby("a").rolling(3) + result = getattr(rol, func)() + expected = DataFrame( + { + "b": 4 * [np.nan] + expected_values[0] + 2 * [np.nan], + "c": 4 * [np.nan] + expected_values[1] + 2 * [np.nan], + }, + index=MultiIndex.from_tuples( + [ + ("g1", 0, "b"), + ("g1", 0, "c"), + ("g1", 2, "b"), + ("g1", 2, "c"), + ("g1", 3, "b"), + ("g1", 3, "c"), + ("g2", 1, "b"), + ("g2", 1, "c"), + ], + names=["a", None, None], + ), + ) + tm.assert_frame_equal(result, expected) + + def test_rolling_apply(self, raw, roll_frame): + g = roll_frame.groupby("A", group_keys=False) + r = g.rolling(window=4) + + # reduction + result = r.apply(lambda x: x.sum(), raw=raw) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(lambda x: x.rolling(4).apply(lambda y: y.sum(), raw=raw)) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([roll_frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + def test_rolling_apply_mutability(self): + # GH 14013 + df = DataFrame({"A": ["foo"] * 3 + ["bar"] * 3, "B": [1] * 6}) + g = df.groupby("A") + + mi = MultiIndex.from_tuples( + [("bar", 3), ("bar", 4), ("bar", 5), ("foo", 0), ("foo", 1), ("foo", 2)] + ) + + mi.names = ["A", None] + # Grouped column should not be a part of the output + expected = DataFrame([np.nan, 2.0, 2.0] * 2, columns=["B"], index=mi) + + result = g.rolling(window=2).sum() + tm.assert_frame_equal(result, expected) + + # Call an arbitrary function on the groupby + g.sum() + + # Make sure nothing has been mutated + result = g.rolling(window=2).sum() + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("expected_value,raw_value", [[1.0, True], [0.0, False]]) + def test_groupby_rolling(self, expected_value, raw_value): + # GH 31754 + + def isnumpyarray(x): + return int(isinstance(x, np.ndarray)) + + df = DataFrame({"id": [1, 1, 1], "value": [1, 2, 3]}) + result = df.groupby("id").value.rolling(1).apply(isnumpyarray, raw=raw_value) + expected = Series( + [expected_value] * 3, + index=MultiIndex.from_tuples(((1, 0), (1, 1), (1, 2)), names=["id", None]), + name="value", + ) + tm.assert_series_equal(result, expected) + + def test_groupby_rolling_center_center(self): + # GH 35552 + series = Series(range(1, 6)) + result = series.groupby(series).rolling(center=True, window=3).mean() + expected = Series( + [np.nan] * 5, + index=MultiIndex.from_tuples(((1, 0), (2, 1), (3, 2), (4, 3), (5, 4))), + ) + tm.assert_series_equal(result, expected) + + series = Series(range(1, 5)) + result = series.groupby(series).rolling(center=True, window=3).mean() + expected = Series( + [np.nan] * 4, + index=MultiIndex.from_tuples(((1, 0), (2, 1), (3, 2), (4, 3))), + ) + tm.assert_series_equal(result, expected) + + df = DataFrame({"a": ["a"] * 5 + ["b"] * 6, "b": range(11)}) + result = df.groupby("a").rolling(center=True, window=3).mean() + expected = DataFrame( + [np.nan, 1, 2, 3, np.nan, np.nan, 6, 7, 8, 9, np.nan], + index=MultiIndex.from_tuples( + ( + ("a", 0), + ("a", 1), + ("a", 2), + ("a", 3), + ("a", 4), + ("b", 5), + ("b", 6), + ("b", 7), + ("b", 8), + ("b", 9), + ("b", 10), + ), + names=["a", None], + ), + columns=["b"], + ) + tm.assert_frame_equal(result, expected) + + df = DataFrame({"a": ["a"] * 5 + ["b"] * 5, "b": range(10)}) + result = df.groupby("a").rolling(center=True, window=3).mean() + expected = DataFrame( + [np.nan, 1, 2, 3, np.nan, np.nan, 6, 7, 8, np.nan], + index=MultiIndex.from_tuples( + ( + ("a", 0), + ("a", 1), + ("a", 2), + ("a", 3), + ("a", 4), + ("b", 5), + ("b", 6), + ("b", 7), + ("b", 8), + ("b", 9), + ), + names=["a", None], + ), + columns=["b"], + ) + tm.assert_frame_equal(result, expected) + + def test_groupby_rolling_center_on(self): + # GH 37141 + df = DataFrame( + data={ + "Date": date_range("2020-01-01", "2020-01-10"), + "gb": ["group_1"] * 6 + ["group_2"] * 4, + "value": range(10), + } + ) + result = ( + df.groupby("gb") + .rolling(6, on="Date", center=True, min_periods=1) + .value.mean() + ) + mi = MultiIndex.from_arrays([df["gb"], df["Date"]], names=["gb", "Date"]) + expected = Series( + [1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 7.0, 7.5, 7.5, 7.5], + name="value", + index=mi, + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("min_periods", [5, 4, 3]) + def test_groupby_rolling_center_min_periods(self, min_periods): + # GH 36040 + df = DataFrame({"group": ["A"] * 10 + ["B"] * 10, "data": range(20)}) + + window_size = 5 + result = ( + df.groupby("group") + .rolling(window_size, center=True, min_periods=min_periods) + .mean() + ) + result = result.reset_index()[["group", "data"]] + + grp_A_mean = [1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 7.5, 8.0] + grp_B_mean = [x + 10.0 for x in grp_A_mean] + + num_nans = max(0, min_periods - 3) # For window_size of 5 + nans = [np.nan] * num_nans + grp_A_expected = nans + grp_A_mean[num_nans : 10 - num_nans] + nans + grp_B_expected = nans + grp_B_mean[num_nans : 10 - num_nans] + nans + + expected = DataFrame( + {"group": ["A"] * 10 + ["B"] * 10, "data": grp_A_expected + grp_B_expected} + ) + + tm.assert_frame_equal(result, expected) + + def test_groupby_subselect_rolling(self): + # GH 35486 + df = DataFrame( + {"a": [1, 2, 3, 2], "b": [4.0, 2.0, 3.0, 1.0], "c": [10, 20, 30, 20]} + ) + result = df.groupby("a")[["b"]].rolling(2).max() + expected = DataFrame( + [np.nan, np.nan, 2.0, np.nan], + columns=["b"], + index=MultiIndex.from_tuples( + ((1, 0), (2, 1), (2, 3), (3, 2)), names=["a", None] + ), + ) + tm.assert_frame_equal(result, expected) + + result = df.groupby("a")["b"].rolling(2).max() + expected = Series( + [np.nan, np.nan, 2.0, np.nan], + index=MultiIndex.from_tuples( + ((1, 0), (2, 1), (2, 3), (3, 2)), names=["a", None] + ), + name="b", + ) + tm.assert_series_equal(result, expected) + + def test_groupby_rolling_custom_indexer(self): + # GH 35557 + class SimpleIndexer(BaseIndexer): + def get_window_bounds( + self, + num_values=0, + min_periods=None, + center=None, + closed=None, + step=None, + ): + min_periods = self.window_size if min_periods is None else 0 + end = np.arange(num_values, dtype=np.int64) + 1 + start = end.copy() - self.window_size + start[start < 0] = min_periods + return start, end + + df = DataFrame( + {"a": [1.0, 2.0, 3.0, 4.0, 5.0] * 3}, index=[0] * 5 + [1] * 5 + [2] * 5 + ) + result = ( + df.groupby(df.index) + .rolling(SimpleIndexer(window_size=3), min_periods=1) + .sum() + ) + expected = df.groupby(df.index).rolling(window=3, min_periods=1).sum() + tm.assert_frame_equal(result, expected) + + def test_groupby_rolling_subset_with_closed(self): + # GH 35549 + df = DataFrame( + { + "column1": range(8), + "column2": range(8), + "group": ["A"] * 4 + ["B"] * 4, + "date": [ + Timestamp(date) + for date in ["2019-01-01", "2019-01-01", "2019-01-02", "2019-01-02"] + ] + * 2, + } + ) + result = ( + df.groupby("group").rolling("1D", on="date", closed="left")["column1"].sum() + ) + expected = Series( + [np.nan, np.nan, 1.0, 1.0, np.nan, np.nan, 9.0, 9.0], + index=MultiIndex.from_frame( + df[["group", "date"]], + names=["group", "date"], + ), + name="column1", + ) + tm.assert_series_equal(result, expected) + + def test_groupby_subset_rolling_subset_with_closed(self): + # GH 35549 + df = DataFrame( + { + "column1": range(8), + "column2": range(8), + "group": ["A"] * 4 + ["B"] * 4, + "date": [ + Timestamp(date) + for date in ["2019-01-01", "2019-01-01", "2019-01-02", "2019-01-02"] + ] + * 2, + } + ) + + result = ( + df.groupby("group")[["column1", "date"]] + .rolling("1D", on="date", closed="left")["column1"] + .sum() + ) + expected = Series( + [np.nan, np.nan, 1.0, 1.0, np.nan, np.nan, 9.0, 9.0], + index=MultiIndex.from_frame( + df[["group", "date"]], + names=["group", "date"], + ), + name="column1", + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize("func", ["max", "min"]) + def test_groupby_rolling_index_changed(self, func): + # GH: #36018 nlevels of MultiIndex changed + ds = Series( + [1, 2, 2], + index=MultiIndex.from_tuples( + [("a", "x"), ("a", "y"), ("c", "z")], names=["1", "2"] + ), + name="a", + ) + + result = getattr(ds.groupby(ds).rolling(2), func)() + expected = Series( + [np.nan, np.nan, 2.0], + index=MultiIndex.from_tuples( + [(1, "a", "x"), (2, "a", "y"), (2, "c", "z")], names=["a", "1", "2"] + ), + name="a", + ) + tm.assert_series_equal(result, expected) + + def test_groupby_rolling_empty_frame(self): + # GH 36197 + expected = DataFrame({"s1": []}) + result = expected.groupby("s1").rolling(window=1).sum() + # GH 32262 + expected = expected.drop(columns="s1") + # GH-38057 from_tuples gives empty object dtype, we now get float/int levels + # expected.index = MultiIndex.from_tuples([], names=["s1", None]) + expected.index = MultiIndex.from_product( + [Index([], dtype="float64"), Index([], dtype="int64")], names=["s1", None] + ) + tm.assert_frame_equal(result, expected) + + expected = DataFrame({"s1": [], "s2": []}) + result = expected.groupby(["s1", "s2"]).rolling(window=1).sum() + # GH 32262 + expected = expected.drop(columns=["s1", "s2"]) + expected.index = MultiIndex.from_product( + [ + Index([], dtype="float64"), + Index([], dtype="float64"), + Index([], dtype="int64"), + ], + names=["s1", "s2", None], + ) + tm.assert_frame_equal(result, expected) + + def test_groupby_rolling_string_index(self): + # GH: 36727 + df = DataFrame( + [ + ["A", "group_1", Timestamp(2019, 1, 1, 9)], + ["B", "group_1", Timestamp(2019, 1, 2, 9)], + ["Z", "group_2", Timestamp(2019, 1, 3, 9)], + ["H", "group_1", Timestamp(2019, 1, 6, 9)], + ["E", "group_2", Timestamp(2019, 1, 20, 9)], + ], + columns=["index", "group", "eventTime"], + ).set_index("index") + + groups = df.groupby("group") + df["count_to_date"] = groups.cumcount() + rolling_groups = groups.rolling("10d", on="eventTime") + result = rolling_groups.apply(lambda df: df.shape[0]) + expected = DataFrame( + [ + ["A", "group_1", Timestamp(2019, 1, 1, 9), 1.0], + ["B", "group_1", Timestamp(2019, 1, 2, 9), 2.0], + ["H", "group_1", Timestamp(2019, 1, 6, 9), 3.0], + ["Z", "group_2", Timestamp(2019, 1, 3, 9), 1.0], + ["E", "group_2", Timestamp(2019, 1, 20, 9), 1.0], + ], + columns=["index", "group", "eventTime", "count_to_date"], + ).set_index(["group", "index"]) + tm.assert_frame_equal(result, expected) + + def test_groupby_rolling_no_sort(self): + # GH 36889 + result = ( + DataFrame({"foo": [2, 1], "bar": [2, 1]}) + .groupby("foo", sort=False) + .rolling(1) + .min() + ) + expected = DataFrame( + np.array([[2.0, 2.0], [1.0, 1.0]]), + columns=["foo", "bar"], + index=MultiIndex.from_tuples([(2, 0), (1, 1)], names=["foo", None]), + ) + # GH 32262 + expected = expected.drop(columns="foo") + tm.assert_frame_equal(result, expected) + + def test_groupby_rolling_count_closed_on(self, unit): + # GH 35869 + df = DataFrame( + { + "column1": range(6), + "column2": range(6), + "group": 3 * ["A", "B"], + "date": date_range(end="20190101", periods=6, unit=unit), + } + ) + result = ( + df.groupby("group") + .rolling("3d", on="date", closed="left")["column1"] + .count() + ) + dti = DatetimeIndex( + [ + "2018-12-27", + "2018-12-29", + "2018-12-31", + "2018-12-28", + "2018-12-30", + "2019-01-01", + ], + dtype=f"M8[{unit}]", + ) + mi = MultiIndex.from_arrays( + [ + ["A", "A", "A", "B", "B", "B"], + dti, + ], + names=["group", "date"], + ) + expected = Series( + [np.nan, 1.0, 1.0, np.nan, 1.0, 1.0], + name="column1", + index=mi, + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + ("func", "kwargs"), + [("rolling", {"window": 2, "min_periods": 1}), ("expanding", {})], + ) + def test_groupby_rolling_sem(self, func, kwargs): + # GH: 26476 + df = DataFrame( + [["a", 1], ["a", 2], ["b", 1], ["b", 2], ["b", 3]], columns=["a", "b"] + ) + result = getattr(df.groupby("a"), func)(**kwargs).sem() + expected = DataFrame( + {"a": [np.nan] * 5, "b": [np.nan, 0.70711, np.nan, 0.70711, 0.70711]}, + index=MultiIndex.from_tuples( + [("a", 0), ("a", 1), ("b", 2), ("b", 3), ("b", 4)], names=["a", None] + ), + ) + # GH 32262 + expected = expected.drop(columns="a") + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize( + ("rollings", "key"), [({"on": "a"}, "a"), ({"on": None}, "index")] + ) + def test_groupby_rolling_nans_in_index(self, rollings, key): + # GH: 34617 + df = DataFrame( + { + "a": to_datetime(["2020-06-01 12:00", "2020-06-01 14:00", np.nan]), + "b": [1, 2, 3], + "c": [1, 1, 1], + } + ) + if key == "index": + df = df.set_index("a") + with pytest.raises(ValueError, match=f"{key} values must not have NaT"): + df.groupby("c").rolling("60min", **rollings) + + @pytest.mark.parametrize("group_keys", [True, False]) + def test_groupby_rolling_group_keys(self, group_keys): + # GH 37641 + # GH 38523: GH 37641 actually was not a bug. + # group_keys only applies to groupby.apply directly + arrays = [["val1", "val1", "val2"], ["val1", "val1", "val2"]] + index = MultiIndex.from_arrays(arrays, names=("idx1", "idx2")) + + s = Series([1, 2, 3], index=index) + result = s.groupby(["idx1", "idx2"], group_keys=group_keys).rolling(1).mean() + expected = Series( + [1.0, 2.0, 3.0], + index=MultiIndex.from_tuples( + [ + ("val1", "val1", "val1", "val1"), + ("val1", "val1", "val1", "val1"), + ("val2", "val2", "val2", "val2"), + ], + names=["idx1", "idx2", "idx1", "idx2"], + ), + ) + tm.assert_series_equal(result, expected) + + def test_groupby_rolling_index_level_and_column_label(self): + # The groupby keys should not appear as a resulting column + arrays = [["val1", "val1", "val2"], ["val1", "val1", "val2"]] + index = MultiIndex.from_arrays(arrays, names=("idx1", "idx2")) + + df = DataFrame({"A": [1, 1, 2], "B": range(3)}, index=index) + result = df.groupby(["idx1", "A"]).rolling(1).mean() + expected = DataFrame( + {"B": [0.0, 1.0, 2.0]}, + index=MultiIndex.from_tuples( + [ + ("val1", 1, "val1", "val1"), + ("val1", 1, "val1", "val1"), + ("val2", 2, "val2", "val2"), + ], + names=["idx1", "A", "idx1", "idx2"], + ), + ) + tm.assert_frame_equal(result, expected) + + def test_groupby_rolling_resulting_multiindex(self): + # a few different cases checking the created MultiIndex of the result + # https://github.com/pandas-dev/pandas/pull/38057 + + # grouping by 1 columns -> 2-level MI as result + df = DataFrame({"a": np.arange(8.0), "b": [1, 2] * 4}) + result = df.groupby("b").rolling(3).mean() + expected_index = MultiIndex.from_tuples( + [(1, 0), (1, 2), (1, 4), (1, 6), (2, 1), (2, 3), (2, 5), (2, 7)], + names=["b", None], + ) + tm.assert_index_equal(result.index, expected_index) + + def test_groupby_rolling_resulting_multiindex2(self): + # grouping by 2 columns -> 3-level MI as result + df = DataFrame({"a": np.arange(12.0), "b": [1, 2] * 6, "c": [1, 2, 3, 4] * 3}) + result = df.groupby(["b", "c"]).rolling(2).sum() + expected_index = MultiIndex.from_tuples( + [ + (1, 1, 0), + (1, 1, 4), + (1, 1, 8), + (1, 3, 2), + (1, 3, 6), + (1, 3, 10), + (2, 2, 1), + (2, 2, 5), + (2, 2, 9), + (2, 4, 3), + (2, 4, 7), + (2, 4, 11), + ], + names=["b", "c", None], + ) + tm.assert_index_equal(result.index, expected_index) + + def test_groupby_rolling_resulting_multiindex3(self): + # grouping with 1 level on dataframe with 2-level MI -> 3-level MI as result + df = DataFrame({"a": np.arange(8.0), "b": [1, 2] * 4, "c": [1, 2, 3, 4] * 2}) + df = df.set_index("c", append=True) + result = df.groupby("b").rolling(3).mean() + expected_index = MultiIndex.from_tuples( + [ + (1, 0, 1), + (1, 2, 3), + (1, 4, 1), + (1, 6, 3), + (2, 1, 2), + (2, 3, 4), + (2, 5, 2), + (2, 7, 4), + ], + names=["b", None, "c"], + ) + tm.assert_index_equal(result.index, expected_index, exact="equiv") + + def test_groupby_rolling_object_doesnt_affect_groupby_apply(self, roll_frame): + # GH 39732 + g = roll_frame.groupby("A", group_keys=False) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(lambda x: x.rolling(4).sum()).index + _ = g.rolling(window=4) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = g.apply(lambda x: x.rolling(4).sum()).index + tm.assert_index_equal(result, expected) + + @pytest.mark.parametrize( + ("window", "min_periods", "closed", "expected"), + [ + (2, 0, "left", [None, 0.0, 1.0, 1.0, None, 0.0, 1.0, 1.0]), + (2, 2, "left", [None, None, 1.0, 1.0, None, None, 1.0, 1.0]), + (4, 4, "left", [None, None, None, None, None, None, None, None]), + (4, 4, "right", [None, None, None, 5.0, None, None, None, 5.0]), + ], + ) + def test_groupby_rolling_var(self, window, min_periods, closed, expected): + df = DataFrame([1, 2, 3, 4, 5, 6, 7, 8]) + result = ( + df.groupby([1, 2, 1, 2, 1, 2, 1, 2]) + .rolling(window=window, min_periods=min_periods, closed=closed) + .var(0) + ) + expected_result = DataFrame( + np.array(expected, dtype="float64"), + index=MultiIndex( + levels=[np.array([1, 2]), [0, 1, 2, 3, 4, 5, 6, 7]], + codes=[[0, 0, 0, 0, 1, 1, 1, 1], [0, 2, 4, 6, 1, 3, 5, 7]], + ), + ) + tm.assert_frame_equal(result, expected_result) + + @pytest.mark.parametrize( + "columns", [MultiIndex.from_tuples([("A", ""), ("B", "C")]), ["A", "B"]] + ) + def test_by_column_not_in_values(self, columns): + # GH 32262 + df = DataFrame([[1, 0]] * 20 + [[2, 0]] * 12 + [[3, 0]] * 8, columns=columns) + g = df.groupby("A") + original_obj = g.obj.copy(deep=True) + r = g.rolling(4) + result = r.sum() + assert "A" not in result.columns + tm.assert_frame_equal(g.obj, original_obj) + + def test_groupby_level(self): + # GH 38523, 38787 + arrays = [ + ["Falcon", "Falcon", "Parrot", "Parrot"], + ["Captive", "Wild", "Captive", "Wild"], + ] + index = MultiIndex.from_arrays(arrays, names=("Animal", "Type")) + df = DataFrame({"Max Speed": [390.0, 350.0, 30.0, 20.0]}, index=index) + result = df.groupby(level=0)["Max Speed"].rolling(2).sum() + expected = Series( + [np.nan, 740.0, np.nan, 50.0], + index=MultiIndex.from_tuples( + [ + ("Falcon", "Falcon", "Captive"), + ("Falcon", "Falcon", "Wild"), + ("Parrot", "Parrot", "Captive"), + ("Parrot", "Parrot", "Wild"), + ], + names=["Animal", "Animal", "Type"], + ), + name="Max Speed", + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "by, expected_data", + [ + [["id"], {"num": [100.0, 150.0, 150.0, 200.0]}], + [ + ["id", "index"], + { + "date": [ + Timestamp("2018-01-01"), + Timestamp("2018-01-02"), + Timestamp("2018-01-01"), + Timestamp("2018-01-02"), + ], + "num": [100.0, 200.0, 150.0, 250.0], + }, + ], + ], + ) + def test_as_index_false(self, by, expected_data, unit): + # GH 39433 + data = [ + ["A", "2018-01-01", 100.0], + ["A", "2018-01-02", 200.0], + ["B", "2018-01-01", 150.0], + ["B", "2018-01-02", 250.0], + ] + df = DataFrame(data, columns=["id", "date", "num"]) + df["date"] = df["date"].astype(f"M8[{unit}]") + df = df.set_index(["date"]) + + gp_by = [getattr(df, attr) for attr in by] + result = ( + df.groupby(gp_by, as_index=False).rolling(window=2, min_periods=1).mean() + ) + + expected = {"id": ["A", "A", "B", "B"]} + expected.update(expected_data) + expected = DataFrame( + expected, + index=df.index, + ) + if "date" in expected_data: + expected["date"] = expected["date"].astype(f"M8[{unit}]") + tm.assert_frame_equal(result, expected) + + def test_nan_and_zero_endpoints(self, any_int_numpy_dtype): + # https://github.com/twosigma/pandas/issues/53 + typ = np.dtype(any_int_numpy_dtype).type + size = 1000 + idx = np.repeat(typ(0), size) + idx[-1] = 1 + + val = 5e25 + arr = np.repeat(val, size) + arr[0] = np.nan + arr[-1] = 0 + + df = DataFrame( + { + "index": idx, + "adl2": arr, + } + ).set_index("index") + result = df.groupby("index")["adl2"].rolling(window=10, min_periods=1).mean() + expected = Series( + arr, + name="adl2", + index=MultiIndex.from_arrays( + [ + Index([0] * 999 + [1], dtype=typ, name="index"), + Index([0] * 999 + [1], dtype=typ, name="index"), + ], + ), + ) + tm.assert_series_equal(result, expected) + + def test_groupby_rolling_non_monotonic(self): + # GH 43909 + + shuffled = [3, 0, 1, 2] + sec = 1_000 + df = DataFrame( + [{"t": Timestamp(2 * x * sec), "x": x + 1, "c": 42} for x in shuffled] + ) + with pytest.raises(ValueError, match=r".* must be monotonic"): + df.groupby("c").rolling(on="t", window="3s") + + def test_groupby_monotonic(self): + # GH 15130 + # we don't need to validate monotonicity when grouping + + # GH 43909 we should raise an error here to match + # behaviour of non-groupby rolling. + + data = [ + ["David", "1/1/2015", 100], + ["David", "1/5/2015", 500], + ["David", "5/30/2015", 50], + ["David", "7/25/2015", 50], + ["Ryan", "1/4/2014", 100], + ["Ryan", "1/19/2015", 500], + ["Ryan", "3/31/2016", 50], + ["Joe", "7/1/2015", 100], + ["Joe", "9/9/2015", 500], + ["Joe", "10/15/2015", 50], + ] + + df = DataFrame(data=data, columns=["name", "date", "amount"]) + df["date"] = to_datetime(df["date"]) + df = df.sort_values("date") + + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = ( + df.set_index("date") + .groupby("name") + .apply(lambda x: x.rolling("180D")["amount"].sum()) + ) + result = df.groupby("name").rolling("180D", on="date")["amount"].sum() + tm.assert_series_equal(result, expected) + + def test_datelike_on_monotonic_within_each_group(self): + # GH 13966 (similar to #15130, closed by #15175) + + # superseded by 43909 + # GH 46061: OK if the on is monotonic relative to each each group + + dates = date_range(start="2016-01-01 09:30:00", periods=20, freq="s") + df = DataFrame( + { + "A": [1] * 20 + [2] * 12 + [3] * 8, + "B": np.concatenate((dates, dates)), + "C": np.arange(40), + } + ) + + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = ( + df.set_index("B") + .groupby("A") + .apply(lambda x: x.rolling("4s")["C"].mean()) + ) + result = df.groupby("A").rolling("4s", on="B").C.mean() + tm.assert_series_equal(result, expected) + + def test_datelike_on_not_monotonic_within_each_group(self): + # GH 46061 + df = DataFrame( + { + "A": [1] * 3 + [2] * 3, + "B": [Timestamp(year, 1, 1) for year in [2020, 2021, 2019]] * 2, + "C": range(6), + } + ) + with pytest.raises(ValueError, match="Each group within B must be monotonic."): + df.groupby("A").rolling("365D", on="B") + + +class TestExpanding: + @pytest.fixture + def frame(self): + return DataFrame({"A": [1] * 20 + [2] * 12 + [3] * 8, "B": np.arange(40)}) + + @pytest.mark.parametrize( + "f", ["sum", "mean", "min", "max", "count", "kurt", "skew"] + ) + def test_expanding(self, f, frame): + g = frame.groupby("A", group_keys=False) + r = g.expanding() + + result = getattr(r, f)() + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(lambda x: getattr(x.expanding(), f)()) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("f", ["std", "var"]) + def test_expanding_ddof(self, f, frame): + g = frame.groupby("A", group_keys=False) + r = g.expanding() + + result = getattr(r, f)(ddof=0) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(lambda x: getattr(x.expanding(), f)(ddof=0)) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize( + "interpolation", ["linear", "lower", "higher", "midpoint", "nearest"] + ) + def test_expanding_quantile(self, interpolation, frame): + g = frame.groupby("A", group_keys=False) + r = g.expanding() + + result = r.quantile(0.4, interpolation=interpolation) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply( + lambda x: x.expanding().quantile(0.4, interpolation=interpolation) + ) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("f", ["corr", "cov"]) + def test_expanding_corr_cov(self, f, frame): + g = frame.groupby("A") + r = g.expanding() + + result = getattr(r, f)(frame) + + def func_0(x): + return getattr(x.expanding(), f)(frame) + + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(func_0) + # GH 39591: groupby.apply returns 1 instead of nan for windows + # with all nan values + null_idx = list(range(20, 61)) + list(range(72, 113)) + expected.iloc[null_idx, 1] = np.nan + # GH 39591: The grouped column should be all np.nan + # (groupby.apply inserts 0s for cov) + expected["A"] = np.nan + tm.assert_frame_equal(result, expected) + + result = getattr(r.B, f)(pairwise=True) + + def func_1(x): + return getattr(x.B.expanding(), f)(pairwise=True) + + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply(func_1) + tm.assert_series_equal(result, expected) + + def test_expanding_apply(self, raw, frame): + g = frame.groupby("A", group_keys=False) + r = g.expanding() + + # reduction + result = r.apply(lambda x: x.sum(), raw=raw) + msg = "DataFrameGroupBy.apply operated on the grouping columns" + with tm.assert_produces_warning(FutureWarning, match=msg): + expected = g.apply( + lambda x: x.expanding().apply(lambda y: y.sum(), raw=raw) + ) + # groupby.apply doesn't drop the grouped-by column + expected = expected.drop("A", axis=1) + # GH 39732 + expected_index = MultiIndex.from_arrays([frame["A"], range(40)]) + expected.index = expected_index + tm.assert_frame_equal(result, expected) + + +class TestEWM: + @pytest.mark.parametrize( + "method, expected_data", + [ + ["mean", [0.0, 0.6666666666666666, 1.4285714285714286, 2.2666666666666666]], + ["std", [np.nan, 0.707107, 0.963624, 1.177164]], + ["var", [np.nan, 0.5, 0.9285714285714286, 1.3857142857142857]], + ], + ) + def test_methods(self, method, expected_data): + # GH 16037 + df = DataFrame({"A": ["a"] * 4, "B": range(4)}) + result = getattr(df.groupby("A").ewm(com=1.0), method)() + expected = DataFrame( + {"B": expected_data}, + index=MultiIndex.from_tuples( + [ + ("a", 0), + ("a", 1), + ("a", 2), + ("a", 3), + ], + names=["A", None], + ), + ) + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize( + "method, expected_data", + [["corr", [np.nan, 1.0, 1.0, 1]], ["cov", [np.nan, 0.5, 0.928571, 1.385714]]], + ) + def test_pairwise_methods(self, method, expected_data): + # GH 16037 + df = DataFrame({"A": ["a"] * 4, "B": range(4)}) + result = getattr(df.groupby("A").ewm(com=1.0), method)() + expected = DataFrame( + {"B": expected_data}, + index=MultiIndex.from_tuples( + [ + ("a", 0, "B"), + ("a", 1, "B"), + ("a", 2, "B"), + ("a", 3, "B"), + ], + names=["A", None, None], + ), + ) + tm.assert_frame_equal(result, expected) + + expected = df.groupby("A")[["B"]].apply( + lambda x: getattr(x.ewm(com=1.0), method)() + ) + tm.assert_frame_equal(result, expected) + + def test_times(self, times_frame): + # GH 40951 + halflife = "23 days" + # GH#42738 + times = times_frame.pop("C") + result = times_frame.groupby("A").ewm(halflife=halflife, times=times).mean() + expected = DataFrame( + { + "B": [ + 0.0, + 0.507534, + 1.020088, + 1.537661, + 0.0, + 0.567395, + 1.221209, + 0.0, + 0.653141, + 1.195003, + ] + }, + index=MultiIndex.from_tuples( + [ + ("a", 0), + ("a", 3), + ("a", 6), + ("a", 9), + ("b", 1), + ("b", 4), + ("b", 7), + ("c", 2), + ("c", 5), + ("c", 8), + ], + names=["A", None], + ), + ) + tm.assert_frame_equal(result, expected) + + def test_times_array(self, times_frame): + # GH 40951 + halflife = "23 days" + times = times_frame.pop("C") + gb = times_frame.groupby("A") + result = gb.ewm(halflife=halflife, times=times).mean() + expected = gb.ewm(halflife=halflife, times=times.values).mean() + tm.assert_frame_equal(result, expected) + + def test_dont_mutate_obj_after_slicing(self): + # GH 43355 + df = DataFrame( + { + "id": ["a", "a", "b", "b", "b"], + "timestamp": date_range("2021-9-1", periods=5, freq="h"), + "y": range(5), + } + ) + grp = df.groupby("id").rolling("1h", on="timestamp") + result = grp.count() + expected_df = DataFrame( + { + "timestamp": date_range("2021-9-1", periods=5, freq="h"), + "y": [1.0] * 5, + }, + index=MultiIndex.from_arrays( + [["a", "a", "b", "b", "b"], list(range(5))], names=["id", None] + ), + ) + tm.assert_frame_equal(result, expected_df) + + result = grp["y"].count() + expected_series = Series( + [1.0] * 5, + index=MultiIndex.from_arrays( + [ + ["a", "a", "b", "b", "b"], + date_range("2021-9-1", periods=5, freq="h"), + ], + names=["id", "timestamp"], + ), + name="y", + ) + tm.assert_series_equal(result, expected_series) + # This is the key test + result = grp.count() + tm.assert_frame_equal(result, expected_df) + + +def test_rolling_corr_with_single_integer_in_index(): + # GH 44078 + df = DataFrame({"a": [(1,), (1,), (1,)], "b": [4, 5, 6]}) + gb = df.groupby(["a"]) + result = gb.rolling(2).corr(other=df) + index = MultiIndex.from_tuples([((1,), 0), ((1,), 1), ((1,), 2)], names=["a", None]) + expected = DataFrame( + {"a": [np.nan, np.nan, np.nan], "b": [np.nan, 1.0, 1.0]}, index=index + ) + tm.assert_frame_equal(result, expected) + + +def test_rolling_corr_with_tuples_in_index(): + # GH 44078 + df = DataFrame( + { + "a": [ + ( + 1, + 2, + ), + ( + 1, + 2, + ), + ( + 1, + 2, + ), + ], + "b": [4, 5, 6], + } + ) + gb = df.groupby(["a"]) + result = gb.rolling(2).corr(other=df) + index = MultiIndex.from_tuples( + [((1, 2), 0), ((1, 2), 1), ((1, 2), 2)], names=["a", None] + ) + expected = DataFrame( + {"a": [np.nan, np.nan, np.nan], "b": [np.nan, 1.0, 1.0]}, index=index + ) + tm.assert_frame_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_numba.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_numba.py new file mode 100644 index 0000000000000000000000000000000000000000..9ee7ed0c2f3e66935a8b2de3f8af75da8f49c773 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_numba.py @@ -0,0 +1,465 @@ +import numpy as np +import pytest + +from pandas.compat import is_platform_arm +from pandas.errors import NumbaUtilError +import pandas.util._test_decorators as td + +from pandas import ( + DataFrame, + Series, + option_context, + to_datetime, +) +import pandas._testing as tm +from pandas.util.version import Version + +pytestmark = [pytest.mark.single_cpu] + +numba = pytest.importorskip("numba") +pytestmark.append( + pytest.mark.skipif( + Version(numba.__version__) == Version("0.61") and is_platform_arm(), + reason=f"Segfaults on ARM platforms with numba {numba.__version__}", + ) +) + + +@pytest.fixture(params=["single", "table"]) +def method(request): + """method keyword in rolling/expanding/ewm constructor""" + return request.param + + +@pytest.fixture( + params=[ + ["sum", {}], + ["mean", {}], + ["median", {}], + ["max", {}], + ["min", {}], + ["var", {}], + ["var", {"ddof": 0}], + ["std", {}], + ["std", {"ddof": 0}], + ] +) +def arithmetic_numba_supported_operators(request): + return request.param + + +@td.skip_if_no("numba") +@pytest.mark.filterwarnings("ignore") +# Filter warnings when parallel=True and the function can't be parallelized by Numba +class TestEngine: + @pytest.mark.parametrize("jit", [True, False]) + def test_numba_vs_cython_apply(self, jit, nogil, parallel, nopython, center, step): + def f(x, *args): + arg_sum = 0 + for arg in args: + arg_sum += arg + return np.mean(x) + arg_sum + + if jit: + import numba + + f = numba.jit(f) + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + args = (2,) + + s = Series(range(10)) + result = s.rolling(2, center=center, step=step).apply( + f, args=args, engine="numba", engine_kwargs=engine_kwargs, raw=True + ) + expected = s.rolling(2, center=center, step=step).apply( + f, engine="cython", args=args, raw=True + ) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "data", + [ + DataFrame(np.eye(5)), + DataFrame( + [ + [5, 7, 7, 7, np.nan, np.inf, 4, 3, 3, 3], + [5, 7, 7, 7, np.nan, np.inf, 7, 3, 3, 3], + [np.nan, np.nan, 5, 6, 7, 5, 5, 5, 5, 5], + ] + ).T, + Series(range(5), name="foo"), + Series([20, 10, 10, np.inf, 1, 1, 2, 3]), + Series([20, 10, 10, np.nan, 10, 1, 2, 3]), + ], + ) + def test_numba_vs_cython_rolling_methods( + self, + data, + nogil, + parallel, + nopython, + arithmetic_numba_supported_operators, + step, + ): + method, kwargs = arithmetic_numba_supported_operators + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + roll = data.rolling(3, step=step) + result = getattr(roll, method)( + engine="numba", engine_kwargs=engine_kwargs, **kwargs + ) + expected = getattr(roll, method)(engine="cython", **kwargs) + tm.assert_equal(result, expected) + + @pytest.mark.parametrize( + "data", [DataFrame(np.eye(5)), Series(range(5), name="foo")] + ) + def test_numba_vs_cython_expanding_methods( + self, data, nogil, parallel, nopython, arithmetic_numba_supported_operators + ): + method, kwargs = arithmetic_numba_supported_operators + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + data = DataFrame(np.eye(5)) + expand = data.expanding() + result = getattr(expand, method)( + engine="numba", engine_kwargs=engine_kwargs, **kwargs + ) + expected = getattr(expand, method)(engine="cython", **kwargs) + tm.assert_equal(result, expected) + + @pytest.mark.parametrize("jit", [True, False]) + def test_cache_apply(self, jit, nogil, parallel, nopython, step): + # Test that the functions are cached correctly if we switch functions + def func_1(x): + return np.mean(x) + 4 + + def func_2(x): + return np.std(x) * 5 + + if jit: + import numba + + func_1 = numba.jit(func_1) + func_2 = numba.jit(func_2) + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + roll = Series(range(10)).rolling(2, step=step) + result = roll.apply( + func_1, engine="numba", engine_kwargs=engine_kwargs, raw=True + ) + expected = roll.apply(func_1, engine="cython", raw=True) + tm.assert_series_equal(result, expected) + + result = roll.apply( + func_2, engine="numba", engine_kwargs=engine_kwargs, raw=True + ) + expected = roll.apply(func_2, engine="cython", raw=True) + tm.assert_series_equal(result, expected) + # This run should use the cached func_1 + result = roll.apply( + func_1, engine="numba", engine_kwargs=engine_kwargs, raw=True + ) + expected = roll.apply(func_1, engine="cython", raw=True) + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "window,window_kwargs", + [ + ["rolling", {"window": 3, "min_periods": 0}], + ["expanding", {}], + ], + ) + def test_dont_cache_args( + self, window, window_kwargs, nogil, parallel, nopython, method + ): + # GH 42287 + + def add(values, x): + return np.sum(values) + x + + engine_kwargs = {"nopython": nopython, "nogil": nogil, "parallel": parallel} + df = DataFrame({"value": [0, 0, 0]}) + result = getattr(df, window)(method=method, **window_kwargs).apply( + add, raw=True, engine="numba", engine_kwargs=engine_kwargs, args=(1,) + ) + expected = DataFrame({"value": [1.0, 1.0, 1.0]}) + tm.assert_frame_equal(result, expected) + + result = getattr(df, window)(method=method, **window_kwargs).apply( + add, raw=True, engine="numba", engine_kwargs=engine_kwargs, args=(2,) + ) + expected = DataFrame({"value": [2.0, 2.0, 2.0]}) + tm.assert_frame_equal(result, expected) + + def test_dont_cache_engine_kwargs(self): + # If the user passes a different set of engine_kwargs don't return the same + # jitted function + nogil = False + parallel = True + nopython = True + + def func(x): + return nogil + parallel + nopython + + engine_kwargs = {"nopython": nopython, "nogil": nogil, "parallel": parallel} + df = DataFrame({"value": [0, 0, 0]}) + result = df.rolling(1).apply( + func, raw=True, engine="numba", engine_kwargs=engine_kwargs + ) + expected = DataFrame({"value": [2.0, 2.0, 2.0]}) + tm.assert_frame_equal(result, expected) + + parallel = False + engine_kwargs = {"nopython": nopython, "nogil": nogil, "parallel": parallel} + result = df.rolling(1).apply( + func, raw=True, engine="numba", engine_kwargs=engine_kwargs + ) + expected = DataFrame({"value": [1.0, 1.0, 1.0]}) + tm.assert_frame_equal(result, expected) + + +@td.skip_if_no("numba") +class TestEWM: + @pytest.mark.parametrize( + "grouper", [lambda x: x, lambda x: x.groupby("A")], ids=["None", "groupby"] + ) + @pytest.mark.parametrize("method", ["mean", "sum"]) + def test_invalid_engine(self, grouper, method): + df = DataFrame({"A": ["a", "b", "a", "b"], "B": range(4)}) + with pytest.raises(ValueError, match="engine must be either"): + getattr(grouper(df).ewm(com=1.0), method)(engine="foo") + + @pytest.mark.parametrize( + "grouper", [lambda x: x, lambda x: x.groupby("A")], ids=["None", "groupby"] + ) + @pytest.mark.parametrize("method", ["mean", "sum"]) + def test_invalid_engine_kwargs(self, grouper, method): + df = DataFrame({"A": ["a", "b", "a", "b"], "B": range(4)}) + with pytest.raises(ValueError, match="cython engine does not"): + getattr(grouper(df).ewm(com=1.0), method)( + engine="cython", engine_kwargs={"nopython": True} + ) + + @pytest.mark.parametrize("grouper", ["None", "groupby"]) + @pytest.mark.parametrize("method", ["mean", "sum"]) + def test_cython_vs_numba( + self, grouper, method, nogil, parallel, nopython, ignore_na, adjust + ): + df = DataFrame({"B": range(4)}) + if grouper == "None": + grouper = lambda x: x + else: + df["A"] = ["a", "b", "a", "b"] + grouper = lambda x: x.groupby("A") + if method == "sum": + adjust = True + ewm = grouper(df).ewm(com=1.0, adjust=adjust, ignore_na=ignore_na) + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + result = getattr(ewm, method)(engine="numba", engine_kwargs=engine_kwargs) + expected = getattr(ewm, method)(engine="cython") + + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("grouper", ["None", "groupby"]) + def test_cython_vs_numba_times(self, grouper, nogil, parallel, nopython, ignore_na): + # GH 40951 + + df = DataFrame({"B": [0, 0, 1, 1, 2, 2]}) + if grouper == "None": + grouper = lambda x: x + else: + grouper = lambda x: x.groupby("A") + df["A"] = ["a", "b", "a", "b", "b", "a"] + + halflife = "23 days" + times = to_datetime( + [ + "2020-01-01", + "2020-01-01", + "2020-01-02", + "2020-01-10", + "2020-02-23", + "2020-01-03", + ] + ) + ewm = grouper(df).ewm( + halflife=halflife, adjust=True, ignore_na=ignore_na, times=times + ) + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + result = ewm.mean(engine="numba", engine_kwargs=engine_kwargs) + expected = ewm.mean(engine="cython") + + tm.assert_frame_equal(result, expected) + + +@td.skip_if_no("numba") +def test_use_global_config(): + def f(x): + return np.mean(x) + 2 + + s = Series(range(10)) + with option_context("compute.use_numba", True): + result = s.rolling(2).apply(f, engine=None, raw=True) + expected = s.rolling(2).apply(f, engine="numba", raw=True) + tm.assert_series_equal(expected, result) + + +@td.skip_if_no("numba") +def test_invalid_kwargs_nopython(): + with pytest.raises(NumbaUtilError, match="numba does not support kwargs with"): + Series(range(1)).rolling(1).apply( + lambda x: x, kwargs={"a": 1}, engine="numba", raw=True + ) + + +@td.skip_if_no("numba") +@pytest.mark.slow +@pytest.mark.filterwarnings("ignore") +# Filter warnings when parallel=True and the function can't be parallelized by Numba +class TestTableMethod: + def test_table_series_valueerror(self): + def f(x): + return np.sum(x, axis=0) + 1 + + with pytest.raises( + ValueError, match="method='table' not applicable for Series objects." + ): + Series(range(1)).rolling(1, method="table").apply( + f, engine="numba", raw=True + ) + + def test_table_method_rolling_methods( + self, + axis, + nogil, + parallel, + nopython, + arithmetic_numba_supported_operators, + step, + ): + method, kwargs = arithmetic_numba_supported_operators + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + df = DataFrame(np.eye(3)) + roll_table = df.rolling(2, method="table", axis=axis, min_periods=0, step=step) + if method in ("var", "std"): + with pytest.raises(NotImplementedError, match=f"{method} not supported"): + getattr(roll_table, method)( + engine_kwargs=engine_kwargs, engine="numba", **kwargs + ) + else: + roll_single = df.rolling( + 2, method="single", axis=axis, min_periods=0, step=step + ) + result = getattr(roll_table, method)( + engine_kwargs=engine_kwargs, engine="numba", **kwargs + ) + expected = getattr(roll_single, method)( + engine_kwargs=engine_kwargs, engine="numba", **kwargs + ) + tm.assert_frame_equal(result, expected) + + def test_table_method_rolling_apply(self, axis, nogil, parallel, nopython, step): + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + def f(x): + return np.sum(x, axis=0) + 1 + + df = DataFrame(np.eye(3)) + result = df.rolling( + 2, method="table", axis=axis, min_periods=0, step=step + ).apply(f, raw=True, engine_kwargs=engine_kwargs, engine="numba") + expected = df.rolling( + 2, method="single", axis=axis, min_periods=0, step=step + ).apply(f, raw=True, engine_kwargs=engine_kwargs, engine="numba") + tm.assert_frame_equal(result, expected) + + def test_table_method_rolling_weighted_mean(self, step): + def weighted_mean(x): + arr = np.ones((1, x.shape[1])) + arr[:, :2] = (x[:, :2] * x[:, 2]).sum(axis=0) / x[:, 2].sum() + return arr + + df = DataFrame([[1, 2, 0.6], [2, 3, 0.4], [3, 4, 0.2], [4, 5, 0.7]]) + result = df.rolling(2, method="table", min_periods=0, step=step).apply( + weighted_mean, raw=True, engine="numba" + ) + expected = DataFrame( + [ + [1.0, 2.0, 1.0], + [1.8, 2.0, 1.0], + [3.333333, 2.333333, 1.0], + [1.555556, 7, 1.0], + ] + )[::step] + tm.assert_frame_equal(result, expected) + + def test_table_method_expanding_apply(self, axis, nogil, parallel, nopython): + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + def f(x): + return np.sum(x, axis=0) + 1 + + df = DataFrame(np.eye(3)) + result = df.expanding(method="table", axis=axis).apply( + f, raw=True, engine_kwargs=engine_kwargs, engine="numba" + ) + expected = df.expanding(method="single", axis=axis).apply( + f, raw=True, engine_kwargs=engine_kwargs, engine="numba" + ) + tm.assert_frame_equal(result, expected) + + def test_table_method_expanding_methods( + self, axis, nogil, parallel, nopython, arithmetic_numba_supported_operators + ): + method, kwargs = arithmetic_numba_supported_operators + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + df = DataFrame(np.eye(3)) + expand_table = df.expanding(method="table", axis=axis) + if method in ("var", "std"): + with pytest.raises(NotImplementedError, match=f"{method} not supported"): + getattr(expand_table, method)( + engine_kwargs=engine_kwargs, engine="numba", **kwargs + ) + else: + expand_single = df.expanding(method="single", axis=axis) + result = getattr(expand_table, method)( + engine_kwargs=engine_kwargs, engine="numba", **kwargs + ) + expected = getattr(expand_single, method)( + engine_kwargs=engine_kwargs, engine="numba", **kwargs + ) + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize("data", [np.eye(3), np.ones((2, 3)), np.ones((3, 2))]) + @pytest.mark.parametrize("method", ["mean", "sum"]) + def test_table_method_ewm(self, data, method, axis, nogil, parallel, nopython): + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + df = DataFrame(data) + + result = getattr(df.ewm(com=1, method="table", axis=axis), method)( + engine_kwargs=engine_kwargs, engine="numba" + ) + expected = getattr(df.ewm(com=1, method="single", axis=axis), method)( + engine_kwargs=engine_kwargs, engine="numba" + ) + tm.assert_frame_equal(result, expected) + + +@td.skip_if_no("numba") +def test_npfunc_no_warnings(): + df = DataFrame({"col1": [1, 2, 3, 4, 5]}) + with tm.assert_produces_warning(False): + df.col1.rolling(2).apply(np.prod, raw=True, engine="numba") diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_online.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_online.py new file mode 100644 index 0000000000000000000000000000000000000000..43d55a7992b3ce52255a6813e8b9e93b82a45324 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_online.py @@ -0,0 +1,112 @@ +import numpy as np +import pytest + +from pandas.compat import is_platform_arm + +from pandas import ( + DataFrame, + Series, +) +import pandas._testing as tm +from pandas.util.version import Version + +pytestmark = [pytest.mark.single_cpu] + +numba = pytest.importorskip("numba") +pytestmark.append( + pytest.mark.skipif( + Version(numba.__version__) == Version("0.61") and is_platform_arm(), + reason=f"Segfaults on ARM platforms with numba {numba.__version__}", + ) +) + + +@pytest.mark.filterwarnings("ignore") +# Filter warnings when parallel=True and the function can't be parallelized by Numba +class TestEWM: + def test_invalid_update(self): + df = DataFrame({"a": range(5), "b": range(5)}) + online_ewm = df.head(2).ewm(0.5).online() + with pytest.raises( + ValueError, + match="Must call mean with update=None first before passing update", + ): + online_ewm.mean(update=df.head(1)) + + @pytest.mark.slow + @pytest.mark.parametrize( + "obj", [DataFrame({"a": range(5), "b": range(5)}), Series(range(5), name="foo")] + ) + def test_online_vs_non_online_mean( + self, obj, nogil, parallel, nopython, adjust, ignore_na + ): + expected = obj.ewm(0.5, adjust=adjust, ignore_na=ignore_na).mean() + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + + online_ewm = ( + obj.head(2) + .ewm(0.5, adjust=adjust, ignore_na=ignore_na) + .online(engine_kwargs=engine_kwargs) + ) + # Test resetting once + for _ in range(2): + result = online_ewm.mean() + tm.assert_equal(result, expected.head(2)) + + result = online_ewm.mean(update=obj.tail(3)) + tm.assert_equal(result, expected.tail(3)) + + online_ewm.reset() + + @pytest.mark.xfail(raises=NotImplementedError) + @pytest.mark.parametrize( + "obj", [DataFrame({"a": range(5), "b": range(5)}), Series(range(5), name="foo")] + ) + def test_update_times_mean( + self, obj, nogil, parallel, nopython, adjust, ignore_na, halflife_with_times + ): + times = Series( + np.array( + ["2020-01-01", "2020-01-05", "2020-01-07", "2020-01-17", "2020-01-21"], + dtype="datetime64[ns]", + ) + ) + expected = obj.ewm( + 0.5, + adjust=adjust, + ignore_na=ignore_na, + times=times, + halflife=halflife_with_times, + ).mean() + + engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython} + online_ewm = ( + obj.head(2) + .ewm( + 0.5, + adjust=adjust, + ignore_na=ignore_na, + times=times.head(2), + halflife=halflife_with_times, + ) + .online(engine_kwargs=engine_kwargs) + ) + # Test resetting once + for _ in range(2): + result = online_ewm.mean() + tm.assert_equal(result, expected.head(2)) + + result = online_ewm.mean(update=obj.tail(3), update_times=times.tail(3)) + tm.assert_equal(result, expected.tail(3)) + + online_ewm.reset() + + @pytest.mark.parametrize("method", ["aggregate", "std", "corr", "cov", "var"]) + def test_ewm_notimplementederror_raises(self, method): + ser = Series(range(10)) + kwargs = {} + if method == "aggregate": + kwargs["func"] = lambda x: x + + with pytest.raises(NotImplementedError, match=".* is not implemented."): + getattr(ser.ewm(1).online(), method)(**kwargs) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_pairwise.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_pairwise.py new file mode 100644 index 0000000000000000000000000000000000000000..3ceb58756bac6cbc5f3b1862523d4185c1ad8b47 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_pairwise.py @@ -0,0 +1,445 @@ +import numpy as np +import pytest + +from pandas.compat import IS64 + +from pandas import ( + DataFrame, + Index, + MultiIndex, + Series, + date_range, +) +import pandas._testing as tm +from pandas.core.algorithms import safe_sort + + +@pytest.fixture( + params=[ + DataFrame([[2, 4], [1, 2], [5, 2], [8, 1]], columns=[1, 0]), + DataFrame([[2, 4], [1, 2], [5, 2], [8, 1]], columns=[1, 1]), + DataFrame([[2, 4], [1, 2], [5, 2], [8, 1]], columns=["C", "C"]), + DataFrame([[2, 4], [1, 2], [5, 2], [8, 1]], columns=[1.0, 0]), + DataFrame([[2, 4], [1, 2], [5, 2], [8, 1]], columns=[0.0, 1]), + DataFrame([[2, 4], [1, 2], [5, 2], [8, 1]], columns=["C", 1]), + DataFrame([[2.0, 4.0], [1.0, 2.0], [5.0, 2.0], [8.0, 1.0]], columns=[1, 0.0]), + DataFrame([[2, 4.0], [1, 2.0], [5, 2.0], [8, 1.0]], columns=[0, 1.0]), + DataFrame([[2, 4], [1, 2], [5, 2], [8, 1.0]], columns=[1.0, "X"]), + ] +) +def pairwise_frames(request): + """Pairwise frames test_pairwise""" + return request.param + + +@pytest.fixture +def pairwise_target_frame(): + """Pairwise target frame for test_pairwise""" + return DataFrame([[2, 4], [1, 2], [5, 2], [8, 1]], columns=[0, 1]) + + +@pytest.fixture +def pairwise_other_frame(): + """Pairwise other frame for test_pairwise""" + return DataFrame( + [[None, 1, 1], [None, 1, 2], [None, 3, 2], [None, 8, 1]], + columns=["Y", "Z", "X"], + ) + + +def test_rolling_cov(series): + A = series + B = A + np.random.default_rng(2).standard_normal(len(A)) + + result = A.rolling(window=50, min_periods=25).cov(B) + tm.assert_almost_equal(result.iloc[-1], np.cov(A[-50:], B[-50:])[0, 1]) + + +def test_rolling_corr(series): + A = series + B = A + np.random.default_rng(2).standard_normal(len(A)) + + result = A.rolling(window=50, min_periods=25).corr(B) + tm.assert_almost_equal(result.iloc[-1], np.corrcoef(A[-50:], B[-50:])[0, 1]) + + +def test_rolling_corr_bias_correction(): + # test for correct bias correction + a = Series( + np.arange(20, dtype=np.float64), index=date_range("2020-01-01", periods=20) + ) + b = a.copy() + a[:5] = np.nan + b[:10] = np.nan + + result = a.rolling(window=len(a), min_periods=1).corr(b) + tm.assert_almost_equal(result.iloc[-1], a.corr(b)) + + +@pytest.mark.parametrize("func", ["cov", "corr"]) +def test_rolling_pairwise_cov_corr(func, frame): + result = getattr(frame.rolling(window=10, min_periods=5), func)() + result = result.loc[(slice(None), 1), 5] + result.index = result.index.droplevel(1) + expected = getattr(frame[1].rolling(window=10, min_periods=5), func)(frame[5]) + tm.assert_series_equal(result, expected, check_names=False) + + +@pytest.mark.parametrize("method", ["corr", "cov"]) +def test_flex_binary_frame(method, frame): + series = frame[1] + + res = getattr(series.rolling(window=10), method)(frame) + res2 = getattr(frame.rolling(window=10), method)(series) + exp = frame.apply(lambda x: getattr(series.rolling(window=10), method)(x)) + + tm.assert_frame_equal(res, exp) + tm.assert_frame_equal(res2, exp) + + frame2 = frame.copy() + frame2 = DataFrame( + np.random.default_rng(2).standard_normal(frame2.shape), + index=frame2.index, + columns=frame2.columns, + ) + + res3 = getattr(frame.rolling(window=10), method)(frame2) + exp = DataFrame( + {k: getattr(frame[k].rolling(window=10), method)(frame2[k]) for k in frame} + ) + tm.assert_frame_equal(res3, exp) + + +@pytest.mark.parametrize("window", range(7)) +def test_rolling_corr_with_zero_variance(window): + # GH 18430 + s = Series(np.zeros(20)) + other = Series(np.arange(20)) + + assert s.rolling(window=window).corr(other=other).isna().all() + + +def test_corr_sanity(): + # GH 3155 + df = DataFrame( + np.array( + [ + [0.87024726, 0.18505595], + [0.64355431, 0.3091617], + [0.92372966, 0.50552513], + [0.00203756, 0.04520709], + [0.84780328, 0.33394331], + [0.78369152, 0.63919667], + ] + ) + ) + + res = df[0].rolling(5, center=True).corr(df[1]) + assert all(np.abs(np.nan_to_num(x)) <= 1 for x in res) + + df = DataFrame(np.random.default_rng(2).random((30, 2))) + res = df[0].rolling(5, center=True).corr(df[1]) + assert all(np.abs(np.nan_to_num(x)) <= 1 for x in res) + + +def test_rolling_cov_diff_length(): + # GH 7512 + s1 = Series([1, 2, 3], index=[0, 1, 2]) + s2 = Series([1, 3], index=[0, 2]) + result = s1.rolling(window=3, min_periods=2).cov(s2) + expected = Series([None, None, 2.0]) + tm.assert_series_equal(result, expected) + + s2a = Series([1, None, 3], index=[0, 1, 2]) + result = s1.rolling(window=3, min_periods=2).cov(s2a) + tm.assert_series_equal(result, expected) + + +def test_rolling_corr_diff_length(): + # GH 7512 + s1 = Series([1, 2, 3], index=[0, 1, 2]) + s2 = Series([1, 3], index=[0, 2]) + result = s1.rolling(window=3, min_periods=2).corr(s2) + expected = Series([None, None, 1.0]) + tm.assert_series_equal(result, expected) + + s2a = Series([1, None, 3], index=[0, 1, 2]) + result = s1.rolling(window=3, min_periods=2).corr(s2a) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "f", + [ + lambda x: (x.rolling(window=10, min_periods=5).cov(x, pairwise=True)), + lambda x: (x.rolling(window=10, min_periods=5).corr(x, pairwise=True)), + ], +) +def test_rolling_functions_window_non_shrinkage_binary(f): + # corr/cov return a MI DataFrame + df = DataFrame( + [[1, 5], [3, 2], [3, 9], [-1, 0]], + columns=Index(["A", "B"], name="foo"), + index=Index(range(4), name="bar"), + ) + df_expected = DataFrame( + columns=Index(["A", "B"], name="foo"), + index=MultiIndex.from_product([df.index, df.columns], names=["bar", "foo"]), + dtype="float64", + ) + df_result = f(df) + tm.assert_frame_equal(df_result, df_expected) + + +@pytest.mark.parametrize( + "f", + [ + lambda x: (x.rolling(window=10, min_periods=5).cov(x, pairwise=True)), + lambda x: (x.rolling(window=10, min_periods=5).corr(x, pairwise=True)), + ], +) +def test_moment_functions_zero_length_pairwise(f): + df1 = DataFrame() + df2 = DataFrame(columns=Index(["a"], name="foo"), index=Index([], name="bar")) + df2["a"] = df2["a"].astype("float64") + + df1_expected = DataFrame(index=MultiIndex.from_product([df1.index, df1.columns])) + df2_expected = DataFrame( + index=MultiIndex.from_product([df2.index, df2.columns], names=["bar", "foo"]), + columns=Index(["a"], name="foo"), + dtype="float64", + ) + + df1_result = f(df1) + tm.assert_frame_equal(df1_result, df1_expected) + + df2_result = f(df2) + tm.assert_frame_equal(df2_result, df2_expected) + + +class TestPairwise: + # GH 7738 + @pytest.mark.parametrize("f", [lambda x: x.cov(), lambda x: x.corr()]) + def test_no_flex(self, pairwise_frames, pairwise_target_frame, f): + # DataFrame methods (which do not call flex_binary_moment()) + + result = f(pairwise_frames) + tm.assert_index_equal(result.index, pairwise_frames.columns) + tm.assert_index_equal(result.columns, pairwise_frames.columns) + expected = f(pairwise_target_frame) + # since we have sorted the results + # we can only compare non-nans + result = result.dropna().values + expected = expected.dropna().values + + tm.assert_numpy_array_equal(result, expected, check_dtype=False) + + @pytest.mark.parametrize( + "f", + [ + lambda x: x.expanding().cov(pairwise=True), + lambda x: x.expanding().corr(pairwise=True), + lambda x: x.rolling(window=3).cov(pairwise=True), + lambda x: x.rolling(window=3).corr(pairwise=True), + lambda x: x.ewm(com=3).cov(pairwise=True), + lambda x: x.ewm(com=3).corr(pairwise=True), + ], + ) + def test_pairwise_with_self(self, pairwise_frames, pairwise_target_frame, f): + # DataFrame with itself, pairwise=True + # note that we may construct the 1st level of the MI + # in a non-monotonic way, so compare accordingly + result = f(pairwise_frames) + tm.assert_index_equal( + result.index.levels[0], pairwise_frames.index, check_names=False + ) + tm.assert_index_equal( + safe_sort(result.index.levels[1]), + safe_sort(pairwise_frames.columns.unique()), + ) + tm.assert_index_equal(result.columns, pairwise_frames.columns) + expected = f(pairwise_target_frame) + # since we have sorted the results + # we can only compare non-nans + result = result.dropna().values + expected = expected.dropna().values + + tm.assert_numpy_array_equal(result, expected, check_dtype=False) + + @pytest.mark.parametrize( + "f", + [ + lambda x: x.expanding().cov(pairwise=False), + lambda x: x.expanding().corr(pairwise=False), + lambda x: x.rolling(window=3).cov(pairwise=False), + lambda x: x.rolling(window=3).corr(pairwise=False), + lambda x: x.ewm(com=3).cov(pairwise=False), + lambda x: x.ewm(com=3).corr(pairwise=False), + ], + ) + def test_no_pairwise_with_self(self, pairwise_frames, pairwise_target_frame, f): + # DataFrame with itself, pairwise=False + result = f(pairwise_frames) + tm.assert_index_equal(result.index, pairwise_frames.index) + tm.assert_index_equal(result.columns, pairwise_frames.columns) + expected = f(pairwise_target_frame) + # since we have sorted the results + # we can only compare non-nans + result = result.dropna().values + expected = expected.dropna().values + + tm.assert_numpy_array_equal(result, expected, check_dtype=False) + + @pytest.mark.parametrize( + "f", + [ + lambda x, y: x.expanding().cov(y, pairwise=True), + lambda x, y: x.expanding().corr(y, pairwise=True), + lambda x, y: x.rolling(window=3).cov(y, pairwise=True), + # TODO: We're missing a flag somewhere in meson + pytest.param( + lambda x, y: x.rolling(window=3).corr(y, pairwise=True), + marks=pytest.mark.xfail( + not IS64, reason="Precision issues on 32 bit", strict=False + ), + ), + lambda x, y: x.ewm(com=3).cov(y, pairwise=True), + lambda x, y: x.ewm(com=3).corr(y, pairwise=True), + ], + ) + def test_pairwise_with_other( + self, pairwise_frames, pairwise_target_frame, pairwise_other_frame, f + ): + # DataFrame with another DataFrame, pairwise=True + result = f(pairwise_frames, pairwise_other_frame) + tm.assert_index_equal( + result.index.levels[0], pairwise_frames.index, check_names=False + ) + tm.assert_index_equal( + safe_sort(result.index.levels[1]), + safe_sort(pairwise_other_frame.columns.unique()), + ) + expected = f(pairwise_target_frame, pairwise_other_frame) + # since we have sorted the results + # we can only compare non-nans + result = result.dropna().values + expected = expected.dropna().values + + tm.assert_numpy_array_equal(result, expected, check_dtype=False) + + @pytest.mark.filterwarnings("ignore:RuntimeWarning") + @pytest.mark.parametrize( + "f", + [ + lambda x, y: x.expanding().cov(y, pairwise=False), + lambda x, y: x.expanding().corr(y, pairwise=False), + lambda x, y: x.rolling(window=3).cov(y, pairwise=False), + lambda x, y: x.rolling(window=3).corr(y, pairwise=False), + lambda x, y: x.ewm(com=3).cov(y, pairwise=False), + lambda x, y: x.ewm(com=3).corr(y, pairwise=False), + ], + ) + def test_no_pairwise_with_other(self, pairwise_frames, pairwise_other_frame, f): + # DataFrame with another DataFrame, pairwise=False + result = ( + f(pairwise_frames, pairwise_other_frame) + if pairwise_frames.columns.is_unique + else None + ) + if result is not None: + # we can have int and str columns + expected_index = pairwise_frames.index.union(pairwise_other_frame.index) + expected_columns = pairwise_frames.columns.union( + pairwise_other_frame.columns + ) + tm.assert_index_equal(result.index, expected_index) + tm.assert_index_equal(result.columns, expected_columns) + else: + with pytest.raises(ValueError, match="'arg1' columns are not unique"): + f(pairwise_frames, pairwise_other_frame) + with pytest.raises(ValueError, match="'arg2' columns are not unique"): + f(pairwise_other_frame, pairwise_frames) + + @pytest.mark.parametrize( + "f", + [ + lambda x, y: x.expanding().cov(y), + lambda x, y: x.expanding().corr(y), + lambda x, y: x.rolling(window=3).cov(y), + lambda x, y: x.rolling(window=3).corr(y), + lambda x, y: x.ewm(com=3).cov(y), + lambda x, y: x.ewm(com=3).corr(y), + ], + ) + def test_pairwise_with_series(self, pairwise_frames, pairwise_target_frame, f): + # DataFrame with a Series + result = f(pairwise_frames, Series([1, 1, 3, 8])) + tm.assert_index_equal(result.index, pairwise_frames.index) + tm.assert_index_equal(result.columns, pairwise_frames.columns) + expected = f(pairwise_target_frame, Series([1, 1, 3, 8])) + # since we have sorted the results + # we can only compare non-nans + result = result.dropna().values + expected = expected.dropna().values + tm.assert_numpy_array_equal(result, expected, check_dtype=False) + + result = f(Series([1, 1, 3, 8]), pairwise_frames) + tm.assert_index_equal(result.index, pairwise_frames.index) + tm.assert_index_equal(result.columns, pairwise_frames.columns) + expected = f(Series([1, 1, 3, 8]), pairwise_target_frame) + # since we have sorted the results + # we can only compare non-nans + result = result.dropna().values + expected = expected.dropna().values + tm.assert_numpy_array_equal(result, expected, check_dtype=False) + + def test_corr_freq_memory_error(self): + # GH 31789 + s = Series(range(5), index=date_range("2020", periods=5)) + result = s.rolling("12h").corr(s) + expected = Series([np.nan] * 5, index=date_range("2020", periods=5)) + tm.assert_series_equal(result, expected) + + def test_cov_mulittindex(self): + # GH 34440 + + columns = MultiIndex.from_product([list("ab"), list("xy"), list("AB")]) + index = range(3) + df = DataFrame(np.arange(24).reshape(3, 8), index=index, columns=columns) + + result = df.ewm(alpha=0.1).cov() + + index = MultiIndex.from_product([range(3), list("ab"), list("xy"), list("AB")]) + columns = MultiIndex.from_product([list("ab"), list("xy"), list("AB")]) + expected = DataFrame( + np.vstack( + ( + np.full((8, 8), np.nan), + np.full((8, 8), 32.000000), + np.full((8, 8), 63.881919), + ) + ), + index=index, + columns=columns, + ) + + tm.assert_frame_equal(result, expected) + + def test_multindex_columns_pairwise_func(self): + # GH 21157 + columns = MultiIndex.from_arrays([["M", "N"], ["P", "Q"]], names=["a", "b"]) + df = DataFrame(np.ones((5, 2)), columns=columns) + result = df.rolling(3).corr() + expected = DataFrame( + np.nan, + index=MultiIndex.from_arrays( + [ + np.repeat(np.arange(5, dtype=np.int64), 2), + ["M", "N"] * 5, + ["P", "Q"] * 5, + ], + names=[None, "a", "b"], + ), + columns=columns, + ) + tm.assert_frame_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling.py new file mode 100644 index 0000000000000000000000000000000000000000..f353a7fa2f0fe5f0480c31b40a2907943ff5a5c6 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling.py @@ -0,0 +1,1979 @@ +from datetime import ( + datetime, + timedelta, +) + +import numpy as np +import pytest + +from pandas.compat import ( + IS64, + is_platform_arm, + is_platform_power, +) + +from pandas import ( + DataFrame, + DatetimeIndex, + MultiIndex, + Series, + Timedelta, + Timestamp, + date_range, + period_range, + to_datetime, + to_timedelta, +) +import pandas._testing as tm +from pandas.api.indexers import BaseIndexer +from pandas.core.indexers.objects import VariableOffsetWindowIndexer + +from pandas.tseries.offsets import BusinessDay + + +def test_doc_string(): + df = DataFrame({"B": [0, 1, 2, np.nan, 4]}) + df + df.rolling(2).sum() + df.rolling(2, min_periods=1).sum() + + +def test_constructor(frame_or_series): + # GH 12669 + + c = frame_or_series(range(5)).rolling + + # valid + c(0) + c(window=2) + c(window=2, min_periods=1) + c(window=2, min_periods=1, center=True) + c(window=2, min_periods=1, center=False) + + # GH 13383 + + msg = "window must be an integer 0 or greater" + + with pytest.raises(ValueError, match=msg): + c(-1) + + +@pytest.mark.parametrize("w", [2.0, "foo", np.array([2])]) +def test_invalid_constructor(frame_or_series, w): + # not valid + + c = frame_or_series(range(5)).rolling + + msg = "|".join( + [ + "window must be an integer", + "passed window foo is not compatible with a datetimelike index", + ] + ) + with pytest.raises(ValueError, match=msg): + c(window=w) + + msg = "min_periods must be an integer" + with pytest.raises(ValueError, match=msg): + c(window=2, min_periods=w) + + msg = "center must be a boolean" + with pytest.raises(ValueError, match=msg): + c(window=2, min_periods=1, center=w) + + +@pytest.mark.parametrize( + "window", + [ + timedelta(days=3), + Timedelta(days=3), + "3D", + VariableOffsetWindowIndexer( + index=date_range("2015-12-25", periods=5), offset=BusinessDay(1) + ), + ], +) +def test_freq_window_not_implemented(window): + # GH 15354 + df = DataFrame( + np.arange(10), + index=date_range("2015-12-24", periods=10, freq="D"), + ) + with pytest.raises( + NotImplementedError, match="^step (not implemented|is not supported)" + ): + df.rolling(window, step=3).sum() + + +@pytest.mark.parametrize("agg", ["cov", "corr"]) +def test_step_not_implemented_for_cov_corr(agg): + # GH 15354 + roll = DataFrame(range(2)).rolling(1, step=2) + with pytest.raises(NotImplementedError, match="step not implemented"): + getattr(roll, agg)() + + +@pytest.mark.parametrize("window", [timedelta(days=3), Timedelta(days=3)]) +def test_constructor_with_timedelta_window(window): + # GH 15440 + n = 10 + df = DataFrame( + {"value": np.arange(n)}, + index=date_range("2015-12-24", periods=n, freq="D"), + ) + expected_data = np.append([0.0, 1.0], np.arange(3.0, 27.0, 3)) + + result = df.rolling(window=window).sum() + expected = DataFrame( + {"value": expected_data}, + index=date_range("2015-12-24", periods=n, freq="D"), + ) + tm.assert_frame_equal(result, expected) + expected = df.rolling("3D").sum() + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("window", [timedelta(days=3), Timedelta(days=3), "3D"]) +def test_constructor_timedelta_window_and_minperiods(window, raw): + # GH 15305 + n = 10 + df = DataFrame( + {"value": np.arange(n)}, + index=date_range("2017-08-08", periods=n, freq="D"), + ) + expected = DataFrame( + {"value": np.append([np.nan, 1.0], np.arange(3.0, 27.0, 3))}, + index=date_range("2017-08-08", periods=n, freq="D"), + ) + result_roll_sum = df.rolling(window=window, min_periods=2).sum() + result_roll_generic = df.rolling(window=window, min_periods=2).apply(sum, raw=raw) + tm.assert_frame_equal(result_roll_sum, expected) + tm.assert_frame_equal(result_roll_generic, expected) + + +def test_closed_fixed(closed, arithmetic_win_operators): + # GH 34315 + func_name = arithmetic_win_operators + df_fixed = DataFrame({"A": [0, 1, 2, 3, 4]}) + df_time = DataFrame({"A": [0, 1, 2, 3, 4]}, index=date_range("2020", periods=5)) + + result = getattr( + df_fixed.rolling(2, closed=closed, min_periods=1), + func_name, + )() + expected = getattr( + df_time.rolling("2D", closed=closed, min_periods=1), + func_name, + )().reset_index(drop=True) + + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "closed, window_selections", + [ + ( + "both", + [ + [True, True, False, False, False], + [True, True, True, False, False], + [False, True, True, True, False], + [False, False, True, True, True], + [False, False, False, True, True], + ], + ), + ( + "left", + [ + [True, False, False, False, False], + [True, True, False, False, False], + [False, True, True, False, False], + [False, False, True, True, False], + [False, False, False, True, True], + ], + ), + ( + "right", + [ + [True, True, False, False, False], + [False, True, True, False, False], + [False, False, True, True, False], + [False, False, False, True, True], + [False, False, False, False, True], + ], + ), + ( + "neither", + [ + [True, False, False, False, False], + [False, True, False, False, False], + [False, False, True, False, False], + [False, False, False, True, False], + [False, False, False, False, True], + ], + ), + ], +) +def test_datetimelike_centered_selections( + closed, window_selections, arithmetic_win_operators +): + # GH 34315 + func_name = arithmetic_win_operators + df_time = DataFrame( + {"A": [0.0, 1.0, 2.0, 3.0, 4.0]}, index=date_range("2020", periods=5) + ) + + expected = DataFrame( + {"A": [getattr(df_time["A"].iloc[s], func_name)() for s in window_selections]}, + index=date_range("2020", periods=5), + ) + + if func_name == "sem": + kwargs = {"ddof": 0} + else: + kwargs = {} + + result = getattr( + df_time.rolling("2D", closed=closed, min_periods=1, center=True), + func_name, + )(**kwargs) + + tm.assert_frame_equal(result, expected, check_dtype=False) + + +@pytest.mark.parametrize( + "window,closed,expected", + [ + ("3s", "right", [3.0, 3.0, 3.0]), + ("3s", "both", [3.0, 3.0, 3.0]), + ("3s", "left", [3.0, 3.0, 3.0]), + ("3s", "neither", [3.0, 3.0, 3.0]), + ("2s", "right", [3.0, 2.0, 2.0]), + ("2s", "both", [3.0, 3.0, 3.0]), + ("2s", "left", [1.0, 3.0, 3.0]), + ("2s", "neither", [1.0, 2.0, 2.0]), + ], +) +def test_datetimelike_centered_offset_covers_all( + window, closed, expected, frame_or_series +): + # GH 42753 + + index = [ + Timestamp("20130101 09:00:01"), + Timestamp("20130101 09:00:02"), + Timestamp("20130101 09:00:02"), + ] + df = frame_or_series([1, 1, 1], index=index) + + result = df.rolling(window, closed=closed, center=True).sum() + expected = frame_or_series(expected, index=index) + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "window,closed,expected", + [ + ("2D", "right", [4, 4, 4, 4, 4, 4, 2, 2]), + ("2D", "left", [2, 2, 4, 4, 4, 4, 4, 4]), + ("2D", "both", [4, 4, 6, 6, 6, 6, 4, 4]), + ("2D", "neither", [2, 2, 2, 2, 2, 2, 2, 2]), + ], +) +def test_datetimelike_nonunique_index_centering( + window, closed, expected, frame_or_series +): + index = DatetimeIndex( + [ + "2020-01-01", + "2020-01-01", + "2020-01-02", + "2020-01-02", + "2020-01-03", + "2020-01-03", + "2020-01-04", + "2020-01-04", + ] + ) + + df = frame_or_series([1] * 8, index=index, dtype=float) + expected = frame_or_series(expected, index=index, dtype=float) + + result = df.rolling(window, center=True, closed=closed).sum() + + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "closed,expected", + [ + ("left", [np.nan, np.nan, 1, 1, 1, 10, 14, 14, 18, 21]), + ("neither", [np.nan, np.nan, 1, 1, 1, 9, 5, 5, 13, 8]), + ("right", [0, 1, 3, 6, 10, 14, 11, 18, 21, 17]), + ("both", [0, 1, 3, 6, 10, 15, 20, 27, 26, 30]), + ], +) +def test_variable_window_nonunique(closed, expected, frame_or_series): + # GH 20712 + index = DatetimeIndex( + [ + "2011-01-01", + "2011-01-01", + "2011-01-02", + "2011-01-02", + "2011-01-02", + "2011-01-03", + "2011-01-04", + "2011-01-04", + "2011-01-05", + "2011-01-06", + ] + ) + + df = frame_or_series(range(10), index=index, dtype=float) + expected = frame_or_series(expected, index=index, dtype=float) + + result = df.rolling("2D", closed=closed).sum() + + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "closed,expected", + [ + ("left", [np.nan, np.nan, 1, 1, 1, 10, 15, 15, 18, 21]), + ("neither", [np.nan, np.nan, 1, 1, 1, 10, 15, 15, 13, 8]), + ("right", [0, 1, 3, 6, 10, 15, 21, 28, 21, 17]), + ("both", [0, 1, 3, 6, 10, 15, 21, 28, 26, 30]), + ], +) +def test_variable_offset_window_nonunique(closed, expected, frame_or_series): + # GH 20712 + index = DatetimeIndex( + [ + "2011-01-01", + "2011-01-01", + "2011-01-02", + "2011-01-02", + "2011-01-02", + "2011-01-03", + "2011-01-04", + "2011-01-04", + "2011-01-05", + "2011-01-06", + ] + ) + + df = frame_or_series(range(10), index=index, dtype=float) + expected = frame_or_series(expected, index=index, dtype=float) + + offset = BusinessDay(2) + indexer = VariableOffsetWindowIndexer(index=index, offset=offset) + result = df.rolling(indexer, closed=closed, min_periods=1).sum() + + tm.assert_equal(result, expected) + + +def test_even_number_window_alignment(): + # see discussion in GH 38780 + s = Series(range(3), index=date_range(start="2020-01-01", freq="D", periods=3)) + + # behavior of index- and datetime-based windows differs here! + # s.rolling(window=2, min_periods=1, center=True).mean() + + result = s.rolling(window="2D", min_periods=1, center=True).mean() + + expected = Series([0.5, 1.5, 2], index=s.index) + + tm.assert_series_equal(result, expected) + + +def test_closed_fixed_binary_col(center, step): + # GH 34315 + data = [0, 1, 1, 0, 0, 1, 0, 1] + df = DataFrame( + {"binary_col": data}, + index=date_range(start="2020-01-01", freq="min", periods=len(data)), + ) + + if center: + expected_data = [2 / 3, 0.5, 0.4, 0.5, 0.428571, 0.5, 0.571429, 0.5] + else: + expected_data = [np.nan, 0, 0.5, 2 / 3, 0.5, 0.4, 0.5, 0.428571] + + expected = DataFrame( + expected_data, + columns=["binary_col"], + index=date_range(start="2020-01-01", freq="min", periods=len(expected_data)), + )[::step] + + rolling = df.rolling( + window=len(df), closed="left", min_periods=1, center=center, step=step + ) + result = rolling.mean() + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("closed", ["neither", "left"]) +def test_closed_empty(closed, arithmetic_win_operators): + # GH 26005 + func_name = arithmetic_win_operators + ser = Series(data=np.arange(5), index=date_range("2000", periods=5, freq="2D")) + roll = ser.rolling("1D", closed=closed) + + result = getattr(roll, func_name)() + expected = Series([np.nan] * 5, index=ser.index) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("func", ["min", "max"]) +def test_closed_one_entry(func): + # GH24718 + ser = Series(data=[2], index=date_range("2000", periods=1)) + result = getattr(ser.rolling("10D", closed="left"), func)() + tm.assert_series_equal(result, Series([np.nan], index=ser.index)) + + +@pytest.mark.parametrize("func", ["min", "max"]) +def test_closed_one_entry_groupby(func): + # GH24718 + ser = DataFrame( + data={"A": [1, 1, 2], "B": [3, 2, 1]}, + index=date_range("2000", periods=3), + ) + result = getattr( + ser.groupby("A", sort=False)["B"].rolling("10D", closed="left"), func + )() + exp_idx = MultiIndex.from_arrays(arrays=[[1, 1, 2], ser.index], names=("A", None)) + expected = Series(data=[np.nan, 3, np.nan], index=exp_idx, name="B") + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("input_dtype", ["int", "float"]) +@pytest.mark.parametrize( + "func,closed,expected", + [ + ("min", "right", [0.0, 0, 0, 1, 2, 3, 4, 5, 6, 7]), + ("min", "both", [0.0, 0, 0, 0, 1, 2, 3, 4, 5, 6]), + ("min", "neither", [np.nan, 0, 0, 1, 2, 3, 4, 5, 6, 7]), + ("min", "left", [np.nan, 0, 0, 0, 1, 2, 3, 4, 5, 6]), + ("max", "right", [0.0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), + ("max", "both", [0.0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), + ("max", "neither", [np.nan, 0, 1, 2, 3, 4, 5, 6, 7, 8]), + ("max", "left", [np.nan, 0, 1, 2, 3, 4, 5, 6, 7, 8]), + ], +) +def test_closed_min_max_datetime(input_dtype, func, closed, expected): + # see gh-21704 + ser = Series( + data=np.arange(10).astype(input_dtype), + index=date_range("2000", periods=10), + ) + + result = getattr(ser.rolling("3D", closed=closed), func)() + expected = Series(expected, index=ser.index) + tm.assert_series_equal(result, expected) + + +def test_closed_uneven(): + # see gh-21704 + ser = Series(data=np.arange(10), index=date_range("2000", periods=10)) + + # uneven + ser = ser.drop(index=ser.index[[1, 5]]) + result = ser.rolling("3D", closed="left").min() + expected = Series([np.nan, 0, 0, 2, 3, 4, 6, 6], index=ser.index) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "func,closed,expected", + [ + ("min", "right", [np.nan, 0, 0, 1, 2, 3, 4, 5, np.nan, np.nan]), + ("min", "both", [np.nan, 0, 0, 0, 1, 2, 3, 4, 5, np.nan]), + ("min", "neither", [np.nan, np.nan, 0, 1, 2, 3, 4, 5, np.nan, np.nan]), + ("min", "left", [np.nan, np.nan, 0, 0, 1, 2, 3, 4, 5, np.nan]), + ("max", "right", [np.nan, 1, 2, 3, 4, 5, 6, 6, np.nan, np.nan]), + ("max", "both", [np.nan, 1, 2, 3, 4, 5, 6, 6, 6, np.nan]), + ("max", "neither", [np.nan, np.nan, 1, 2, 3, 4, 5, 6, np.nan, np.nan]), + ("max", "left", [np.nan, np.nan, 1, 2, 3, 4, 5, 6, 6, np.nan]), + ], +) +def test_closed_min_max_minp(func, closed, expected): + # see gh-21704 + ser = Series(data=np.arange(10), index=date_range("2000", periods=10)) + # Explicit cast to float to avoid implicit cast when setting nan + ser = ser.astype("float") + ser[ser.index[-3:]] = np.nan + result = getattr(ser.rolling("3D", min_periods=2, closed=closed), func)() + expected = Series(expected, index=ser.index) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "closed,expected", + [ + ("right", [0, 0.5, 1, 2, 3, 4, 5, 6, 7, 8]), + ("both", [0, 0.5, 1, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5]), + ("neither", [np.nan, 0, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5]), + ("left", [np.nan, 0, 0.5, 1, 2, 3, 4, 5, 6, 7]), + ], +) +def test_closed_median_quantile(closed, expected): + # GH 26005 + ser = Series(data=np.arange(10), index=date_range("2000", periods=10)) + roll = ser.rolling("3D", closed=closed) + expected = Series(expected, index=ser.index) + + result = roll.median() + tm.assert_series_equal(result, expected) + + result = roll.quantile(0.5) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("roller", ["1s", 1]) +def tests_empty_df_rolling(roller): + # GH 15819 Verifies that datetime and integer rolling windows can be + # applied to empty DataFrames + expected = DataFrame() + result = DataFrame().rolling(roller).sum() + tm.assert_frame_equal(result, expected) + + # Verifies that datetime and integer rolling windows can be applied to + # empty DataFrames with datetime index + expected = DataFrame(index=DatetimeIndex([])) + result = DataFrame(index=DatetimeIndex([])).rolling(roller).sum() + tm.assert_frame_equal(result, expected) + + +def test_empty_window_median_quantile(): + # GH 26005 + expected = Series([np.nan, np.nan, np.nan]) + roll = Series(np.arange(3)).rolling(0) + + result = roll.median() + tm.assert_series_equal(result, expected) + + result = roll.quantile(0.1) + tm.assert_series_equal(result, expected) + + +def test_missing_minp_zero(): + # https://github.com/pandas-dev/pandas/pull/18921 + # minp=0 + x = Series([np.nan]) + result = x.rolling(1, min_periods=0).sum() + expected = Series([0.0]) + tm.assert_series_equal(result, expected) + + # minp=1 + result = x.rolling(1, min_periods=1).sum() + expected = Series([np.nan]) + tm.assert_series_equal(result, expected) + + +def test_missing_minp_zero_variable(): + # https://github.com/pandas-dev/pandas/pull/18921 + x = Series( + [np.nan] * 4, + index=DatetimeIndex(["2017-01-01", "2017-01-04", "2017-01-06", "2017-01-07"]), + ) + result = x.rolling(Timedelta("2d"), min_periods=0).sum() + expected = Series(0.0, index=x.index) + tm.assert_series_equal(result, expected) + + +def test_multi_index_names(): + # GH 16789, 16825 + cols = MultiIndex.from_product([["A", "B"], ["C", "D", "E"]], names=["1", "2"]) + df = DataFrame(np.ones((10, 6)), columns=cols) + result = df.rolling(3).cov() + + tm.assert_index_equal(result.columns, df.columns) + assert result.index.names == [None, "1", "2"] + + +def test_rolling_axis_sum(axis_frame): + # see gh-23372. + df = DataFrame(np.ones((10, 20))) + axis = df._get_axis_number(axis_frame) + + if axis == 0: + msg = "The 'axis' keyword in DataFrame.rolling" + expected = DataFrame({i: [np.nan] * 2 + [3.0] * 8 for i in range(20)}) + else: + # axis == 1 + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + expected = DataFrame([[np.nan] * 2 + [3.0] * 18] * 10) + + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(3, axis=axis_frame).sum() + tm.assert_frame_equal(result, expected) + + +def test_rolling_axis_count(axis_frame): + # see gh-26055 + df = DataFrame({"x": range(3), "y": range(3)}) + + axis = df._get_axis_number(axis_frame) + + if axis in [0, "index"]: + msg = "The 'axis' keyword in DataFrame.rolling" + expected = DataFrame({"x": [1.0, 2.0, 2.0], "y": [1.0, 2.0, 2.0]}) + else: + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + expected = DataFrame({"x": [1.0, 1.0, 1.0], "y": [2.0, 2.0, 2.0]}) + + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(2, axis=axis_frame, min_periods=0).count() + tm.assert_frame_equal(result, expected) + + +def test_readonly_array(): + # GH-27766 + arr = np.array([1, 3, np.nan, 3, 5]) + arr.setflags(write=False) + result = Series(arr).rolling(2).mean() + expected = Series([np.nan, 2, np.nan, np.nan, 4]) + tm.assert_series_equal(result, expected) + + +def test_rolling_datetime(axis_frame, tz_naive_fixture): + # GH-28192 + tz = tz_naive_fixture + df = DataFrame( + {i: [1] * 2 for i in date_range("2019-8-01", "2019-08-03", freq="D", tz=tz)} + ) + + if axis_frame in [0, "index"]: + msg = "The 'axis' keyword in DataFrame.rolling" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.T.rolling("2D", axis=axis_frame).sum().T + else: + msg = "Support for axis=1 in DataFrame.rolling" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling("2D", axis=axis_frame).sum() + expected = DataFrame( + { + **{ + i: [1.0] * 2 + for i in date_range("2019-8-01", periods=1, freq="D", tz=tz) + }, + **{ + i: [2.0] * 2 + for i in date_range("2019-8-02", "2019-8-03", freq="D", tz=tz) + }, + } + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("center", [True, False]) +def test_rolling_window_as_string(center): + # see gh-22590 + date_today = datetime.now() + days = date_range(date_today, date_today + timedelta(365), freq="D") + + data = np.ones(len(days)) + df = DataFrame({"DateCol": days, "metric": data}) + + df.set_index("DateCol", inplace=True) + result = df.rolling(window="21D", min_periods=2, closed="left", center=center)[ + "metric" + ].agg("max") + + index = days.rename("DateCol") + index = index._with_freq(None) + expected_data = np.ones(len(days), dtype=np.float64) + if not center: + expected_data[:2] = np.nan + expected = Series(expected_data, index=index, name="metric") + tm.assert_series_equal(result, expected) + + +def test_min_periods1(): + # GH#6795 + df = DataFrame([0, 1, 2, 1, 0], columns=["a"]) + result = df["a"].rolling(3, center=True, min_periods=1).max() + expected = Series([1.0, 2.0, 2.0, 2.0, 1.0], name="a") + tm.assert_series_equal(result, expected) + + +def test_rolling_count_with_min_periods(frame_or_series): + # GH 26996 + result = frame_or_series(range(5)).rolling(3, min_periods=3).count() + expected = frame_or_series([np.nan, np.nan, 3.0, 3.0, 3.0]) + tm.assert_equal(result, expected) + + +def test_rolling_count_default_min_periods_with_null_values(frame_or_series): + # GH 26996 + values = [1, 2, 3, np.nan, 4, 5, 6] + expected_counts = [1.0, 2.0, 3.0, 2.0, 2.0, 2.0, 3.0] + + # GH 31302 + result = frame_or_series(values).rolling(3, min_periods=0).count() + expected = frame_or_series(expected_counts) + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "df,expected,window,min_periods", + [ + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]), + ], + 3, + None, + ), + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [2, 3], "B": [5, 6]}, [1, 2]), + ], + 2, + 1, + ), + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [2, 3], "B": [5, 6]}, [1, 2]), + ], + 2, + 2, + ), + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [2], "B": [5]}, [1]), + ({"A": [3], "B": [6]}, [2]), + ], + 1, + 1, + ), + ( + DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [2], "B": [5]}, [1]), + ({"A": [3], "B": [6]}, [2]), + ], + 1, + 0, + ), + (DataFrame({"A": [1], "B": [4]}), [], 2, None), + (DataFrame({"A": [1], "B": [4]}), [], 2, 1), + (DataFrame(), [({}, [])], 2, None), + ( + DataFrame({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}), + [ + ({"A": [1.0], "B": [np.nan]}, [0]), + ({"A": [1, np.nan], "B": [np.nan, 5]}, [0, 1]), + ({"A": [1, np.nan, 3], "B": [np.nan, 5, 6]}, [0, 1, 2]), + ], + 3, + 2, + ), + ], +) +def test_iter_rolling_dataframe(df, expected, window, min_periods): + # GH 11704 + expected = [DataFrame(values, index=index) for (values, index) in expected] + + for expected, actual in zip(expected, df.rolling(window, min_periods=min_periods)): + tm.assert_frame_equal(actual, expected) + + +@pytest.mark.parametrize( + "expected,window", + [ + ( + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [2, 3], "B": [5, 6]}, [1, 2]), + ], + "2D", + ), + ( + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [1, 2], "B": [4, 5]}, [0, 1]), + ({"A": [1, 2, 3], "B": [4, 5, 6]}, [0, 1, 2]), + ], + "3D", + ), + ( + [ + ({"A": [1], "B": [4]}, [0]), + ({"A": [2], "B": [5]}, [1]), + ({"A": [3], "B": [6]}, [2]), + ], + "1D", + ), + ], +) +def test_iter_rolling_on_dataframe(expected, window): + # GH 11704, 40373 + df = DataFrame( + { + "A": [1, 2, 3, 4, 5], + "B": [4, 5, 6, 7, 8], + "C": date_range(start="2016-01-01", periods=5, freq="D"), + } + ) + + expected = [ + DataFrame(values, index=df.loc[index, "C"]) for (values, index) in expected + ] + for expected, actual in zip(expected, df.rolling(window, on="C")): + tm.assert_frame_equal(actual, expected) + + +def test_iter_rolling_on_dataframe_unordered(): + # GH 43386 + df = DataFrame({"a": ["x", "y", "x"], "b": [0, 1, 2]}) + results = list(df.groupby("a").rolling(2)) + expecteds = [df.iloc[idx, [1]] for idx in [[0], [0, 2], [1]]] + for result, expected in zip(results, expecteds): + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "ser,expected,window, min_periods", + [ + ( + Series([1, 2, 3]), + [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], + 3, + None, + ), + ( + Series([1, 2, 3]), + [([1], [0]), ([1, 2], [0, 1]), ([1, 2, 3], [0, 1, 2])], + 3, + 1, + ), + ( + Series([1, 2, 3]), + [([1], [0]), ([1, 2], [0, 1]), ([2, 3], [1, 2])], + 2, + 1, + ), + ( + Series([1, 2, 3]), + [([1], [0]), ([1, 2], [0, 1]), ([2, 3], [1, 2])], + 2, + 2, + ), + (Series([1, 2, 3]), [([1], [0]), ([2], [1]), ([3], [2])], 1, 0), + (Series([1, 2, 3]), [([1], [0]), ([2], [1]), ([3], [2])], 1, 1), + (Series([1, 2]), [([1], [0]), ([1, 2], [0, 1])], 2, 0), + (Series([], dtype="int64"), [], 2, 1), + ], +) +def test_iter_rolling_series(ser, expected, window, min_periods): + # GH 11704 + expected = [Series(values, index=index) for (values, index) in expected] + + for expected, actual in zip(expected, ser.rolling(window, min_periods=min_periods)): + tm.assert_series_equal(actual, expected) + + +@pytest.mark.parametrize( + "expected,expected_index,window", + [ + ( + [[0], [1], [2], [3], [4]], + [ + date_range("2020-01-01", periods=1, freq="D"), + date_range("2020-01-02", periods=1, freq="D"), + date_range("2020-01-03", periods=1, freq="D"), + date_range("2020-01-04", periods=1, freq="D"), + date_range("2020-01-05", periods=1, freq="D"), + ], + "1D", + ), + ( + [[0], [0, 1], [1, 2], [2, 3], [3, 4]], + [ + date_range("2020-01-01", periods=1, freq="D"), + date_range("2020-01-01", periods=2, freq="D"), + date_range("2020-01-02", periods=2, freq="D"), + date_range("2020-01-03", periods=2, freq="D"), + date_range("2020-01-04", periods=2, freq="D"), + ], + "2D", + ), + ( + [[0], [0, 1], [0, 1, 2], [1, 2, 3], [2, 3, 4]], + [ + date_range("2020-01-01", periods=1, freq="D"), + date_range("2020-01-01", periods=2, freq="D"), + date_range("2020-01-01", periods=3, freq="D"), + date_range("2020-01-02", periods=3, freq="D"), + date_range("2020-01-03", periods=3, freq="D"), + ], + "3D", + ), + ], +) +def test_iter_rolling_datetime(expected, expected_index, window): + # GH 11704 + ser = Series(range(5), index=date_range(start="2020-01-01", periods=5, freq="D")) + + expected = [ + Series(values, index=idx) for (values, idx) in zip(expected, expected_index) + ] + + for expected, actual in zip(expected, ser.rolling(window)): + tm.assert_series_equal(actual, expected) + + +@pytest.mark.parametrize( + "grouping,_index", + [ + ( + {"level": 0}, + MultiIndex.from_tuples( + [(0, 0), (0, 0), (1, 1), (1, 1), (1, 1)], names=[None, None] + ), + ), + ( + {"by": "X"}, + MultiIndex.from_tuples( + [(0, 0), (1, 0), (2, 1), (3, 1), (4, 1)], names=["X", None] + ), + ), + ], +) +def test_rolling_positional_argument(grouping, _index, raw): + # GH 34605 + + def scaled_sum(*args): + if len(args) < 2: + raise ValueError("The function needs two arguments") + array, scale = args + return array.sum() / scale + + df = DataFrame(data={"X": range(5)}, index=[0, 0, 1, 1, 1]) + + expected = DataFrame(data={"X": [0.0, 0.5, 1.0, 1.5, 2.0]}, index=_index) + # GH 40341 + if "by" in grouping: + expected = expected.drop(columns="X", errors="ignore") + result = df.groupby(**grouping).rolling(1).apply(scaled_sum, raw=raw, args=(2,)) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("add", [0.0, 2.0]) +def test_rolling_numerical_accuracy_kahan_mean(add, unit): + # GH: 36031 implementing kahan summation + dti = DatetimeIndex( + [ + Timestamp("19700101 09:00:00"), + Timestamp("19700101 09:00:03"), + Timestamp("19700101 09:00:06"), + ] + ).as_unit(unit) + df = DataFrame( + {"A": [3002399751580331.0 + add, -0.0, -0.0]}, + index=dti, + ) + result = ( + df.resample("1s").ffill().rolling("3s", closed="left", min_periods=3).mean() + ) + dates = date_range("19700101 09:00:00", periods=7, freq="s", unit=unit) + expected = DataFrame( + { + "A": [ + np.nan, + np.nan, + np.nan, + 3002399751580330.5, + 2001599834386887.25, + 1000799917193443.625, + 0.0, + ] + }, + index=dates, + ) + tm.assert_frame_equal(result, expected) + + +def test_rolling_numerical_accuracy_kahan_sum(): + # GH: 13254 + df = DataFrame([2.186, -1.647, 0.0, 0.0, 0.0, 0.0], columns=["x"]) + result = df["x"].rolling(3).sum() + expected = Series([np.nan, np.nan, 0.539, -1.647, 0.0, 0.0], name="x") + tm.assert_series_equal(result, expected) + + +def test_rolling_numerical_accuracy_jump(): + # GH: 32761 + index = date_range(start="2020-01-01", end="2020-01-02", freq="60s").append( + DatetimeIndex(["2020-01-03"]) + ) + data = np.random.default_rng(2).random(len(index)) + + df = DataFrame({"data": data}, index=index) + result = df.rolling("60s").mean() + tm.assert_frame_equal(result, df[["data"]]) + + +def test_rolling_numerical_accuracy_small_values(): + # GH: 10319 + s = Series( + data=[0.00012456, 0.0003, -0.0, -0.0], + index=date_range("1999-02-03", "1999-02-06"), + ) + result = s.rolling(1).mean() + tm.assert_series_equal(result, s) + + +def test_rolling_numerical_too_large_numbers(): + # GH: 11645 + dates = date_range("2015-01-01", periods=10, freq="D") + ds = Series(data=range(10), index=dates, dtype=np.float64) + ds.iloc[2] = -9e33 + result = ds.rolling(5).mean() + expected = Series( + [ + np.nan, + np.nan, + np.nan, + np.nan, + -1.8e33, + -1.8e33, + -1.8e33, + 5.0, + 6.0, + 7.0, + ], + index=dates, + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + ("func", "value"), + [("sum", 2.0), ("max", 1.0), ("min", 1.0), ("mean", 1.0), ("median", 1.0)], +) +def test_rolling_mixed_dtypes_axis_1(func, value): + # GH: 20649 + df = DataFrame(1, index=[1, 2], columns=["a", "b", "c"]) + df["c"] = 1.0 + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + roll = df.rolling(window=2, min_periods=1, axis=1) + result = getattr(roll, func)() + expected = DataFrame( + {"a": [1.0, 1.0], "b": [value, value], "c": [value, value]}, + index=[1, 2], + ) + tm.assert_frame_equal(result, expected) + + +def test_rolling_axis_one_with_nan(): + # GH: 35596 + df = DataFrame( + [ + [0, 1, 2, 4, np.nan, np.nan, np.nan], + [0, 1, 2, np.nan, np.nan, np.nan, np.nan], + [0, 2, 2, np.nan, 2, np.nan, 1], + ] + ) + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(window=7, min_periods=1, axis="columns").sum() + expected = DataFrame( + [ + [0.0, 1.0, 3.0, 7.0, 7.0, 7.0, 7.0], + [0.0, 1.0, 3.0, 3.0, 3.0, 3.0, 3.0], + [0.0, 2.0, 4.0, 4.0, 6.0, 6.0, 7.0], + ] + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + "value", + ["test", to_datetime("2019-12-31"), to_timedelta("1 days 06:05:01.00003")], +) +def test_rolling_axis_1_non_numeric_dtypes(value): + # GH: 20649 + df = DataFrame({"a": [1, 2]}) + df["b"] = value + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(window=2, min_periods=1, axis=1).sum() + expected = DataFrame({"a": [1.0, 2.0]}) + tm.assert_frame_equal(result, expected) + + +def test_rolling_on_df_transposed(): + # GH: 32724 + df = DataFrame({"A": [1, None], "B": [4, 5], "C": [7, 8]}) + expected = DataFrame({"A": [1.0, np.nan], "B": [5.0, 5.0], "C": [11.0, 13.0]}) + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(min_periods=1, window=2, axis=1).sum() + tm.assert_frame_equal(result, expected) + + result = df.T.rolling(min_periods=1, window=2).sum().T + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + ("index", "window"), + [ + ( + period_range(start="2020-01-01 08:00", end="2020-01-01 08:08", freq="min"), + "2min", + ), + ( + period_range( + start="2020-01-01 08:00", end="2020-01-01 12:00", freq="30min" + ), + "1h", + ), + ], +) +@pytest.mark.parametrize( + ("func", "values"), + [ + ("min", [np.nan, 0, 0, 1, 2, 3, 4, 5, 6]), + ("max", [np.nan, 0, 1, 2, 3, 4, 5, 6, 7]), + ("sum", [np.nan, 0, 1, 3, 5, 7, 9, 11, 13]), + ], +) +def test_rolling_period_index(index, window, func, values): + # GH: 34225 + ds = Series([0, 1, 2, 3, 4, 5, 6, 7, 8], index=index) + result = getattr(ds.rolling(window, closed="left"), func)() + expected = Series(values, index=index) + tm.assert_series_equal(result, expected) + + +def test_rolling_sem(frame_or_series): + # GH: 26476 + obj = frame_or_series([0, 1, 2]) + result = obj.rolling(2, min_periods=1).sem() + if isinstance(result, DataFrame): + result = Series(result[0].values) + expected = Series([np.nan] + [0.7071067811865476] * 2) + tm.assert_series_equal(result, expected) + + +@pytest.mark.xfail( + is_platform_arm() or is_platform_power(), + reason="GH 38921", +) +@pytest.mark.parametrize( + ("func", "third_value", "values"), + [ + ("var", 1, [5e33, 0, 0.5, 0.5, 2, 0]), + ("std", 1, [7.071068e16, 0, 0.7071068, 0.7071068, 1.414214, 0]), + ("var", 2, [5e33, 0.5, 0, 0.5, 2, 0]), + ("std", 2, [7.071068e16, 0.7071068, 0, 0.7071068, 1.414214, 0]), + ], +) +def test_rolling_var_numerical_issues(func, third_value, values): + # GH: 37051 + ds = Series([99999999999999999, 1, third_value, 2, 3, 1, 1]) + result = getattr(ds.rolling(2), func)() + expected = Series([np.nan] + values) + tm.assert_series_equal(result, expected) + # GH 42064 + # new `roll_var` will output 0.0 correctly + tm.assert_series_equal(result == 0, expected == 0) + + +def test_timeoffset_as_window_parameter_for_corr(unit): + # GH: 28266 + dti = DatetimeIndex( + [ + Timestamp("20130101 09:00:00"), + Timestamp("20130102 09:00:02"), + Timestamp("20130103 09:00:03"), + Timestamp("20130105 09:00:05"), + Timestamp("20130106 09:00:06"), + ] + ).as_unit(unit) + mi = MultiIndex.from_product([dti, ["B", "A"]]) + + exp = DataFrame( + { + "B": [ + np.nan, + np.nan, + 0.9999999999999998, + -1.0, + 1.0, + -0.3273268353539892, + 0.9999999999999998, + 1.0, + 0.9999999999999998, + 1.0, + ], + "A": [ + np.nan, + np.nan, + -1.0, + 1.0000000000000002, + -0.3273268353539892, + 0.9999999999999966, + 1.0, + 1.0000000000000002, + 1.0, + 1.0000000000000002, + ], + }, + index=mi, + ) + + df = DataFrame( + {"B": [0, 1, 2, 4, 3], "A": [7, 4, 6, 9, 3]}, + index=dti, + ) + + res = df.rolling(window="3d").corr() + + tm.assert_frame_equal(exp, res) + + +@pytest.mark.parametrize("method", ["var", "sum", "mean", "skew", "kurt", "min", "max"]) +def test_rolling_decreasing_indices(method): + """ + Make sure that decreasing indices give the same results as increasing indices. + + GH 36933 + """ + df = DataFrame({"values": np.arange(-15, 10) ** 2}) + df_reverse = DataFrame({"values": df["values"][::-1]}, index=df.index[::-1]) + + increasing = getattr(df.rolling(window=5), method)() + decreasing = getattr(df_reverse.rolling(window=5), method)() + + assert np.abs(decreasing.values[::-1][:-4] - increasing.values[4:]).max() < 1e-12 + + +@pytest.mark.parametrize( + "window,closed,expected", + [ + ("2s", "right", [1.0, 3.0, 5.0, 3.0]), + ("2s", "left", [0.0, 1.0, 3.0, 5.0]), + ("2s", "both", [1.0, 3.0, 6.0, 5.0]), + ("2s", "neither", [0.0, 1.0, 2.0, 3.0]), + ("3s", "right", [1.0, 3.0, 6.0, 5.0]), + ("3s", "left", [1.0, 3.0, 6.0, 5.0]), + ("3s", "both", [1.0, 3.0, 6.0, 5.0]), + ("3s", "neither", [1.0, 3.0, 6.0, 5.0]), + ], +) +def test_rolling_decreasing_indices_centered(window, closed, expected, frame_or_series): + """ + Ensure that a symmetrical inverted index return same result as non-inverted. + """ + # GH 43927 + + index = date_range("2020", periods=4, freq="1s") + df_inc = frame_or_series(range(4), index=index) + df_dec = frame_or_series(range(4), index=index[::-1]) + + expected_inc = frame_or_series(expected, index=index) + expected_dec = frame_or_series(expected, index=index[::-1]) + + result_inc = df_inc.rolling(window, closed=closed, center=True).sum() + result_dec = df_dec.rolling(window, closed=closed, center=True).sum() + + tm.assert_equal(result_inc, expected_inc) + tm.assert_equal(result_dec, expected_dec) + + +@pytest.mark.parametrize( + "window,expected", + [ + ("1ns", [1.0, 1.0, 1.0, 1.0]), + ("3ns", [2.0, 3.0, 3.0, 2.0]), + ], +) +def test_rolling_center_nanosecond_resolution( + window, closed, expected, frame_or_series +): + index = date_range("2020", periods=4, freq="1ns") + df = frame_or_series([1, 1, 1, 1], index=index, dtype=float) + expected = frame_or_series(expected, index=index, dtype=float) + result = df.rolling(window, closed=closed, center=True).sum() + tm.assert_equal(result, expected) + + +@pytest.mark.parametrize( + "method,expected", + [ + ( + "var", + [ + float("nan"), + 43.0, + float("nan"), + 136.333333, + 43.5, + 94.966667, + 182.0, + 318.0, + ], + ), + ( + "mean", + [float("nan"), 7.5, float("nan"), 21.5, 6.0, 9.166667, 13.0, 17.5], + ), + ( + "sum", + [float("nan"), 30.0, float("nan"), 86.0, 30.0, 55.0, 91.0, 140.0], + ), + ( + "skew", + [ + float("nan"), + 0.709296, + float("nan"), + 0.407073, + 0.984656, + 0.919184, + 0.874674, + 0.842418, + ], + ), + ( + "kurt", + [ + float("nan"), + -0.5916711736073559, + float("nan"), + -1.0028993131317954, + -0.06103844629409494, + -0.254143227116194, + -0.37362637362637585, + -0.45439658241367054, + ], + ), + ], +) +def test_rolling_non_monotonic(method, expected): + """ + Make sure the (rare) branch of non-monotonic indices is covered by a test. + + output from 1.1.3 is assumed to be the expected output. Output of sum/mean has + manually been verified. + + GH 36933. + """ + # Based on an example found in computation.rst + use_expanding = [True, False, True, False, True, True, True, True] + df = DataFrame({"values": np.arange(len(use_expanding)) ** 2}) + + class CustomIndexer(BaseIndexer): + def get_window_bounds(self, num_values, min_periods, center, closed, step): + start = np.empty(num_values, dtype=np.int64) + end = np.empty(num_values, dtype=np.int64) + for i in range(num_values): + if self.use_expanding[i]: + start[i] = 0 + end[i] = i + 1 + else: + start[i] = i + end[i] = i + self.window_size + return start, end + + indexer = CustomIndexer(window_size=4, use_expanding=use_expanding) + + result = getattr(df.rolling(indexer), method)() + expected = DataFrame({"values": expected}) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize( + ("index", "window"), + [ + ([0, 1, 2, 3, 4], 2), + (date_range("2001-01-01", freq="D", periods=5), "2D"), + ], +) +def test_rolling_corr_timedelta_index(index, window): + # GH: 31286 + x = Series([1, 2, 3, 4, 5], index=index) + y = x.copy() + x.iloc[0:2] = 0.0 + result = x.rolling(window).corr(y) + expected = Series([np.nan, np.nan, 1, 1, 1], index=index) + tm.assert_almost_equal(result, expected) + + +def test_groupby_rolling_nan_included(): + # GH 35542 + data = {"group": ["g1", np.nan, "g1", "g2", np.nan], "B": [0, 1, 2, 3, 4]} + df = DataFrame(data) + result = df.groupby("group", dropna=False).rolling(1, min_periods=1).mean() + expected = DataFrame( + {"B": [0.0, 2.0, 3.0, 1.0, 4.0]}, + # GH-38057 from_tuples puts the NaNs in the codes, result expects them + # to be in the levels, at the moment + # index=MultiIndex.from_tuples( + # [("g1", 0), ("g1", 2), ("g2", 3), (np.nan, 1), (np.nan, 4)], + # names=["group", None], + # ), + index=MultiIndex( + [["g1", "g2", np.nan], [0, 1, 2, 3, 4]], + [[0, 0, 1, 2, 2], [0, 2, 3, 1, 4]], + names=["group", None], + ), + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("method", ["skew", "kurt"]) +def test_rolling_skew_kurt_numerical_stability(method): + # GH#6929 + ser = Series(np.random.default_rng(2).random(10)) + ser_copy = ser.copy() + expected = getattr(ser.rolling(3), method)() + tm.assert_series_equal(ser, ser_copy) + ser = ser + 50000 + result = getattr(ser.rolling(3), method)() + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + ("method", "values"), + [ + ("skew", [2.0, 0.854563, 0.0, 1.999984]), + ("kurt", [4.0, -1.289256, -1.2, 3.999946]), + ], +) +def test_rolling_skew_kurt_large_value_range(method, values): + # GH: 37557 + s = Series([3000000, 1, 1, 2, 3, 4, 999]) + result = getattr(s.rolling(4), method)() + expected = Series([np.nan] * 3 + values) + tm.assert_series_equal(result, expected) + + +def test_invalid_method(): + with pytest.raises(ValueError, match="method must be 'table' or 'single"): + Series(range(1)).rolling(1, method="foo") + + +@pytest.mark.parametrize("window", [1, "1d"]) +def test_rolling_descending_date_order_with_offset(window, frame_or_series): + # GH#40002 + idx = date_range(start="2020-01-01", end="2020-01-03", freq="1d") + obj = frame_or_series(range(1, 4), index=idx) + result = obj.rolling("1d", closed="left").sum() + expected = frame_or_series([np.nan, 1, 2], index=idx) + tm.assert_equal(result, expected) + + result = obj.iloc[::-1].rolling("1d", closed="left").sum() + idx = date_range(start="2020-01-03", end="2020-01-01", freq="-1d") + expected = frame_or_series([np.nan, 3, 2], index=idx) + tm.assert_equal(result, expected) + + +def test_rolling_var_floating_artifact_precision(): + # GH 37051 + s = Series([7, 5, 5, 5]) + result = s.rolling(3).var() + expected = Series([np.nan, np.nan, 4 / 3, 0]) + tm.assert_series_equal(result, expected, atol=1.0e-15, rtol=1.0e-15) + # GH 42064 + # new `roll_var` will output 0.0 correctly + tm.assert_series_equal(result == 0, expected == 0) + + +def test_rolling_std_small_values(): + # GH 37051 + s = Series( + [ + 0.00000054, + 0.00000053, + 0.00000054, + ] + ) + result = s.rolling(2).std() + expected = Series([np.nan, 7.071068e-9, 7.071068e-9]) + tm.assert_series_equal(result, expected, atol=1.0e-15, rtol=1.0e-15) + + +@pytest.mark.parametrize( + "start, exp_values", + [ + (1, [0.03, 0.0155, 0.0155, 0.011, 0.01025]), + (2, [0.001, 0.001, 0.0015, 0.00366666]), + ], +) +def test_rolling_mean_all_nan_window_floating_artifacts(start, exp_values): + # GH#41053 + df = DataFrame( + [ + 0.03, + 0.03, + 0.001, + np.nan, + 0.002, + 0.008, + np.nan, + np.nan, + np.nan, + np.nan, + np.nan, + np.nan, + 0.005, + 0.2, + ] + ) + + values = exp_values + [ + 0.00366666, + 0.005, + 0.005, + 0.008, + np.nan, + np.nan, + 0.005, + 0.102500, + ] + expected = DataFrame( + values, + index=list(range(start, len(values) + start)), + ) + result = df.iloc[start:].rolling(5, min_periods=0).mean() + tm.assert_frame_equal(result, expected) + + +def test_rolling_sum_all_nan_window_floating_artifacts(): + # GH#41053 + df = DataFrame([0.002, 0.008, 0.005, np.nan, np.nan, np.nan]) + result = df.rolling(3, min_periods=0).sum() + expected = DataFrame([0.002, 0.010, 0.015, 0.013, 0.005, 0.0]) + tm.assert_frame_equal(result, expected) + + +def test_rolling_zero_window(): + # GH 22719 + s = Series(range(1)) + result = s.rolling(0).min() + expected = Series([np.nan]) + tm.assert_series_equal(result, expected) + + +def test_rolling_float_dtype(float_numpy_dtype): + # GH#42452 + df = DataFrame({"A": range(5), "B": range(10, 15)}, dtype=float_numpy_dtype) + expected = DataFrame( + {"A": [np.nan] * 5, "B": range(10, 20, 2)}, + dtype=float_numpy_dtype, + ) + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(2, axis=1).sum() + tm.assert_frame_equal(result, expected, check_dtype=False) + + +def test_rolling_numeric_dtypes(): + # GH#41779 + df = DataFrame(np.arange(40).reshape(4, 10), columns=list("abcdefghij")).astype( + { + "a": "float16", + "b": "float32", + "c": "float64", + "d": "int8", + "e": "int16", + "f": "int32", + "g": "uint8", + "h": "uint16", + "i": "uint32", + "j": "uint64", + } + ) + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(window=2, min_periods=1, axis=1).min() + expected = DataFrame( + { + "a": range(0, 40, 10), + "b": range(0, 40, 10), + "c": range(1, 40, 10), + "d": range(2, 40, 10), + "e": range(3, 40, 10), + "f": range(4, 40, 10), + "g": range(5, 40, 10), + "h": range(6, 40, 10), + "i": range(7, 40, 10), + "j": range(8, 40, 10), + }, + dtype="float64", + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("window", [1, 3, 10, 20]) +@pytest.mark.parametrize("method", ["min", "max", "average"]) +@pytest.mark.parametrize("pct", [True, False]) +@pytest.mark.parametrize("ascending", [True, False]) +@pytest.mark.parametrize("test_data", ["default", "duplicates", "nans"]) +def test_rank(window, method, pct, ascending, test_data): + length = 20 + if test_data == "default": + ser = Series(data=np.random.default_rng(2).random(length)) + elif test_data == "duplicates": + ser = Series(data=np.random.default_rng(2).choice(3, length)) + elif test_data == "nans": + ser = Series( + data=np.random.default_rng(2).choice( + [1.0, 0.25, 0.75, np.nan, np.inf, -np.inf], length + ) + ) + + expected = ser.rolling(window).apply( + lambda x: x.rank(method=method, pct=pct, ascending=ascending).iloc[-1] + ) + result = ser.rolling(window).rank(method=method, pct=pct, ascending=ascending) + + tm.assert_series_equal(result, expected) + + +def test_rolling_quantile_np_percentile(): + # #9413: Tests that rolling window's quantile default behavior + # is analogous to Numpy's percentile + row = 10 + col = 5 + idx = date_range("20100101", periods=row, freq="B") + df = DataFrame( + np.random.default_rng(2).random(row * col).reshape((row, -1)), index=idx + ) + + df_quantile = df.quantile([0.25, 0.5, 0.75], axis=0) + np_percentile = np.percentile(df, [25, 50, 75], axis=0) + + tm.assert_almost_equal(df_quantile.values, np.array(np_percentile)) + + +@pytest.mark.parametrize("quantile", [0.0, 0.1, 0.45, 0.5, 1]) +@pytest.mark.parametrize( + "interpolation", ["linear", "lower", "higher", "nearest", "midpoint"] +) +@pytest.mark.parametrize( + "data", + [ + [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0], + [8.0, 1.0, 3.0, 4.0, 5.0, 2.0, 6.0, 7.0], + [0.0, np.nan, 0.2, np.nan, 0.4], + [np.nan, np.nan, np.nan, np.nan], + [np.nan, 0.1, np.nan, 0.3, 0.4, 0.5], + [0.5], + [np.nan, 0.7, 0.6], + ], +) +def test_rolling_quantile_interpolation_options(quantile, interpolation, data): + # Tests that rolling window's quantile behavior is analogous to + # Series' quantile for each interpolation option + s = Series(data) + + q1 = s.quantile(quantile, interpolation) + q2 = s.expanding(min_periods=1).quantile(quantile, interpolation).iloc[-1] + + if np.isnan(q1): + assert np.isnan(q2) + else: + if not IS64: + # Less precision on 32-bit + assert np.allclose([q1], [q2], rtol=1e-07, atol=0) + else: + assert q1 == q2 + + +def test_invalid_quantile_value(): + data = np.arange(5) + s = Series(data) + + msg = "Interpolation 'invalid' is not supported" + with pytest.raises(ValueError, match=msg): + s.rolling(len(data), min_periods=1).quantile(0.5, interpolation="invalid") + + +def test_rolling_quantile_param(): + ser = Series([0.0, 0.1, 0.5, 0.9, 1.0]) + msg = "quantile value -0.1 not in \\[0, 1\\]" + with pytest.raises(ValueError, match=msg): + ser.rolling(3).quantile(-0.1) + + msg = "quantile value 10.0 not in \\[0, 1\\]" + with pytest.raises(ValueError, match=msg): + ser.rolling(3).quantile(10.0) + + msg = "must be real number, not str" + with pytest.raises(TypeError, match=msg): + ser.rolling(3).quantile("foo") + + +def test_rolling_std_1obs(): + vals = Series([1.0, 2.0, 3.0, 4.0, 5.0]) + + result = vals.rolling(1, min_periods=1).std() + expected = Series([np.nan] * 5) + tm.assert_series_equal(result, expected) + + result = vals.rolling(1, min_periods=1).std(ddof=0) + expected = Series([0.0] * 5) + tm.assert_series_equal(result, expected) + + result = Series([np.nan, np.nan, 3, 4, 5]).rolling(3, min_periods=2).std() + assert np.isnan(result[2]) + + +def test_rolling_std_neg_sqrt(): + # unit test from Bottleneck + + # Test move_nanstd for neg sqrt. + + a = Series( + [ + 0.0011448196318903589, + 0.00028718669878572767, + 0.00028718669878572767, + 0.00028718669878572767, + 0.00028718669878572767, + ] + ) + b = a.rolling(window=3).std() + assert np.isfinite(b[2:]).all() + + b = a.ewm(span=3).std() + assert np.isfinite(b[2:]).all() + + +def test_step_not_integer_raises(): + with pytest.raises(ValueError, match="step must be an integer"): + DataFrame(range(2)).rolling(1, step="foo") + + +def test_step_not_positive_raises(): + with pytest.raises(ValueError, match="step must be >= 0"): + DataFrame(range(2)).rolling(1, step=-1) + + +@pytest.mark.parametrize( + ["values", "window", "min_periods", "expected"], + [ + [ + [20, 10, 10, np.inf, 1, 1, 2, 3], + 3, + 1, + [np.nan, 50, 100 / 3, 0, 40.5, 0, 1 / 3, 1], + ], + [ + [20, 10, 10, np.nan, 10, 1, 2, 3], + 3, + 1, + [np.nan, 50, 100 / 3, 0, 0, 40.5, 73 / 3, 1], + ], + [ + [np.nan, 5, 6, 7, 5, 5, 5], + 3, + 3, + [np.nan] * 3 + [1, 1, 4 / 3, 0], + ], + [ + [5, 7, 7, 7, np.nan, np.inf, 4, 3, 3, 3], + 3, + 3, + [np.nan] * 2 + [4 / 3, 0] + [np.nan] * 4 + [1 / 3, 0], + ], + [ + [5, 7, 7, 7, np.nan, np.inf, 7, 3, 3, 3], + 3, + 3, + [np.nan] * 2 + [4 / 3, 0] + [np.nan] * 4 + [16 / 3, 0], + ], + [ + [5, 7] * 4, + 3, + 3, + [np.nan] * 2 + [4 / 3] * 6, + ], + [ + [5, 7, 5, np.nan, 7, 5, 7], + 3, + 2, + [np.nan, 2, 4 / 3] + [2] * 3 + [4 / 3], + ], + ], +) +def test_rolling_var_same_value_count_logic(values, window, min_periods, expected): + # GH 42064. + + expected = Series(expected) + sr = Series(values) + + # With new algo implemented, result will be set to .0 in rolling var + # if sufficient amount of consecutively same values are found. + result_var = sr.rolling(window, min_periods=min_periods).var() + + # use `assert_series_equal` twice to check for equality, + # because `check_exact=True` will fail in 32-bit tests due to + # precision loss. + + # 1. result should be close to correct value + # non-zero values can still differ slightly from "truth" + # as the result of online algorithm + tm.assert_series_equal(result_var, expected) + # 2. zeros should be exactly the same since the new algo takes effect here + tm.assert_series_equal(expected == 0, result_var == 0) + + # std should also pass as it's just a sqrt of var + result_std = sr.rolling(window, min_periods=min_periods).std() + tm.assert_series_equal(result_std, np.sqrt(expected)) + tm.assert_series_equal(expected == 0, result_std == 0) + + +def test_rolling_mean_sum_floating_artifacts(): + # GH 42064. + + sr = Series([1 / 3, 4, 0, 0, 0, 0, 0]) + r = sr.rolling(3) + result = r.mean() + assert (result[-3:] == 0).all() + result = r.sum() + assert (result[-3:] == 0).all() + + +def test_rolling_skew_kurt_floating_artifacts(): + # GH 42064 46431 + + sr = Series([1 / 3, 4, 0, 0, 0, 0, 0]) + r = sr.rolling(4) + result = r.skew() + assert (result[-2:] == 0).all() + result = r.kurt() + assert (result[-2:] == -3).all() + + +def test_numeric_only_frame(arithmetic_win_operators, numeric_only): + # GH#46560 + kernel = arithmetic_win_operators + df = DataFrame({"a": [1], "b": 2, "c": 3}) + df["c"] = df["c"].astype(object) + rolling = df.rolling(2, min_periods=1) + op = getattr(rolling, kernel) + result = op(numeric_only=numeric_only) + + columns = ["a", "b"] if numeric_only else ["a", "b", "c"] + expected = df[columns].agg([kernel]).reset_index(drop=True).astype(float) + assert list(expected.columns) == columns + + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("kernel", ["corr", "cov"]) +@pytest.mark.parametrize("use_arg", [True, False]) +def test_numeric_only_corr_cov_frame(kernel, numeric_only, use_arg): + # GH#46560 + df = DataFrame({"a": [1, 2, 3], "b": 2, "c": 3}) + df["c"] = df["c"].astype(object) + arg = (df,) if use_arg else () + rolling = df.rolling(2, min_periods=1) + op = getattr(rolling, kernel) + result = op(*arg, numeric_only=numeric_only) + + # Compare result to op using float dtypes, dropping c when numeric_only is True + columns = ["a", "b"] if numeric_only else ["a", "b", "c"] + df2 = df[columns].astype(float) + arg2 = (df2,) if use_arg else () + rolling2 = df2.rolling(2, min_periods=1) + op2 = getattr(rolling2, kernel) + expected = op2(*arg2, numeric_only=numeric_only) + + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("dtype", [int, object]) +def test_numeric_only_series(arithmetic_win_operators, numeric_only, dtype): + # GH#46560 + kernel = arithmetic_win_operators + ser = Series([1], dtype=dtype) + rolling = ser.rolling(2, min_periods=1) + op = getattr(rolling, kernel) + if numeric_only and dtype is object: + msg = f"Rolling.{kernel} does not implement numeric_only" + with pytest.raises(NotImplementedError, match=msg): + op(numeric_only=numeric_only) + else: + result = op(numeric_only=numeric_only) + expected = ser.agg([kernel]).reset_index(drop=True).astype(float) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("kernel", ["corr", "cov"]) +@pytest.mark.parametrize("use_arg", [True, False]) +@pytest.mark.parametrize("dtype", [int, object]) +def test_numeric_only_corr_cov_series(kernel, use_arg, numeric_only, dtype): + # GH#46560 + ser = Series([1, 2, 3], dtype=dtype) + arg = (ser,) if use_arg else () + rolling = ser.rolling(2, min_periods=1) + op = getattr(rolling, kernel) + if numeric_only and dtype is object: + msg = f"Rolling.{kernel} does not implement numeric_only" + with pytest.raises(NotImplementedError, match=msg): + op(*arg, numeric_only=numeric_only) + else: + result = op(*arg, numeric_only=numeric_only) + + ser2 = ser.astype(float) + arg2 = (ser2,) if use_arg else () + rolling2 = ser2.rolling(2, min_periods=1) + op2 = getattr(rolling2, kernel) + expected = op2(*arg2, numeric_only=numeric_only) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("unit", ["s", "ms", "us", "ns"]) +@pytest.mark.parametrize("tz", [None, "UTC", "Europe/Prague"]) +def test_rolling_timedelta_window_non_nanoseconds(unit, tz): + # Test Sum, GH#55106 + df_time = DataFrame( + {"A": range(5)}, index=date_range("2013-01-01", freq="1s", periods=5, tz=tz) + ) + sum_in_nanosecs = df_time.rolling("1s").sum() + # microseconds / milliseconds should not break the correct rolling + df_time.index = df_time.index.as_unit(unit) + sum_in_microsecs = df_time.rolling("1s").sum() + sum_in_microsecs.index = sum_in_microsecs.index.as_unit("ns") + tm.assert_frame_equal(sum_in_nanosecs, sum_in_microsecs) + + # Test max, GH#55026 + ref_dates = date_range("2023-01-01", "2023-01-10", unit="ns", tz=tz) + ref_series = Series(0, index=ref_dates) + ref_series.iloc[0] = 1 + ref_max_series = ref_series.rolling(Timedelta(days=4)).max() + + dates = date_range("2023-01-01", "2023-01-10", unit=unit, tz=tz) + series = Series(0, index=dates) + series.iloc[0] = 1 + max_series = series.rolling(Timedelta(days=4)).max() + + ref_df = DataFrame(ref_max_series) + df = DataFrame(max_series) + df.index = df.index.as_unit("ns") + + tm.assert_frame_equal(ref_df, df) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_functions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_functions.py new file mode 100644 index 0000000000000000000000000000000000000000..5906ff52db098dfca00d8fdc0a5fa1460b7a35f1 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_functions.py @@ -0,0 +1,532 @@ +from datetime import datetime + +import numpy as np +import pytest + +import pandas.util._test_decorators as td + +from pandas import ( + DataFrame, + DatetimeIndex, + Series, + concat, + isna, + notna, +) +import pandas._testing as tm + +from pandas.tseries import offsets + + +@pytest.mark.parametrize( + "compare_func, roll_func, kwargs", + [ + [np.mean, "mean", {}], + [np.nansum, "sum", {}], + [ + lambda x: np.isfinite(x).astype(float).sum(), + "count", + {}, + ], + [np.median, "median", {}], + [np.min, "min", {}], + [np.max, "max", {}], + [lambda x: np.std(x, ddof=1), "std", {}], + [lambda x: np.std(x, ddof=0), "std", {"ddof": 0}], + [lambda x: np.var(x, ddof=1), "var", {}], + [lambda x: np.var(x, ddof=0), "var", {"ddof": 0}], + ], +) +def test_series(series, compare_func, roll_func, kwargs, step): + result = getattr(series.rolling(50, step=step), roll_func)(**kwargs) + assert isinstance(result, Series) + end = range(0, len(series), step or 1)[-1] + 1 + tm.assert_almost_equal(result.iloc[-1], compare_func(series[end - 50 : end])) + + +@pytest.mark.parametrize( + "compare_func, roll_func, kwargs", + [ + [np.mean, "mean", {}], + [np.nansum, "sum", {}], + [ + lambda x: np.isfinite(x).astype(float).sum(), + "count", + {}, + ], + [np.median, "median", {}], + [np.min, "min", {}], + [np.max, "max", {}], + [lambda x: np.std(x, ddof=1), "std", {}], + [lambda x: np.std(x, ddof=0), "std", {"ddof": 0}], + [lambda x: np.var(x, ddof=1), "var", {}], + [lambda x: np.var(x, ddof=0), "var", {"ddof": 0}], + ], +) +def test_frame(raw, frame, compare_func, roll_func, kwargs, step): + result = getattr(frame.rolling(50, step=step), roll_func)(**kwargs) + assert isinstance(result, DataFrame) + end = range(0, len(frame), step or 1)[-1] + 1 + tm.assert_series_equal( + result.iloc[-1, :], + frame.iloc[end - 50 : end, :].apply(compare_func, axis=0, raw=raw), + check_names=False, + ) + + +@pytest.mark.parametrize( + "compare_func, roll_func, kwargs, minp", + [ + [np.mean, "mean", {}, 10], + [np.nansum, "sum", {}, 10], + [lambda x: np.isfinite(x).astype(float).sum(), "count", {}, 0], + [np.median, "median", {}, 10], + [np.min, "min", {}, 10], + [np.max, "max", {}, 10], + [lambda x: np.std(x, ddof=1), "std", {}, 10], + [lambda x: np.std(x, ddof=0), "std", {"ddof": 0}, 10], + [lambda x: np.var(x, ddof=1), "var", {}, 10], + [lambda x: np.var(x, ddof=0), "var", {"ddof": 0}, 10], + ], +) +def test_time_rule_series(series, compare_func, roll_func, kwargs, minp): + win = 25 + ser = series[::2].resample("B").mean() + series_result = getattr(ser.rolling(window=win, min_periods=minp), roll_func)( + **kwargs + ) + last_date = series_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_series = series[::2].truncate(prev_date, last_date) + tm.assert_almost_equal(series_result.iloc[-1], compare_func(trunc_series)) + + +@pytest.mark.parametrize( + "compare_func, roll_func, kwargs, minp", + [ + [np.mean, "mean", {}, 10], + [np.nansum, "sum", {}, 10], + [lambda x: np.isfinite(x).astype(float).sum(), "count", {}, 0], + [np.median, "median", {}, 10], + [np.min, "min", {}, 10], + [np.max, "max", {}, 10], + [lambda x: np.std(x, ddof=1), "std", {}, 10], + [lambda x: np.std(x, ddof=0), "std", {"ddof": 0}, 10], + [lambda x: np.var(x, ddof=1), "var", {}, 10], + [lambda x: np.var(x, ddof=0), "var", {"ddof": 0}, 10], + ], +) +def test_time_rule_frame(raw, frame, compare_func, roll_func, kwargs, minp): + win = 25 + frm = frame[::2].resample("B").mean() + frame_result = getattr(frm.rolling(window=win, min_periods=minp), roll_func)( + **kwargs + ) + last_date = frame_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_frame = frame[::2].truncate(prev_date, last_date) + tm.assert_series_equal( + frame_result.xs(last_date), + trunc_frame.apply(compare_func, raw=raw), + check_names=False, + ) + + +@pytest.mark.parametrize( + "compare_func, roll_func, kwargs", + [ + [np.mean, "mean", {}], + [np.nansum, "sum", {}], + [np.median, "median", {}], + [np.min, "min", {}], + [np.max, "max", {}], + [lambda x: np.std(x, ddof=1), "std", {}], + [lambda x: np.std(x, ddof=0), "std", {"ddof": 0}], + [lambda x: np.var(x, ddof=1), "var", {}], + [lambda x: np.var(x, ddof=0), "var", {"ddof": 0}], + ], +) +def test_nans(compare_func, roll_func, kwargs): + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = getattr(obj.rolling(50, min_periods=30), roll_func)(**kwargs) + tm.assert_almost_equal(result.iloc[-1], compare_func(obj[10:-10])) + + # min_periods is working correctly + result = getattr(obj.rolling(20, min_periods=15), roll_func)(**kwargs) + assert isna(result.iloc[23]) + assert not isna(result.iloc[24]) + + assert not isna(result.iloc[-6]) + assert isna(result.iloc[-5]) + + obj2 = Series(np.random.default_rng(2).standard_normal(20)) + result = getattr(obj2.rolling(10, min_periods=5), roll_func)(**kwargs) + assert isna(result.iloc[3]) + assert notna(result.iloc[4]) + + if roll_func != "sum": + result0 = getattr(obj.rolling(20, min_periods=0), roll_func)(**kwargs) + result1 = getattr(obj.rolling(20, min_periods=1), roll_func)(**kwargs) + tm.assert_almost_equal(result0, result1) + + +def test_nans_count(): + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + result = obj.rolling(50, min_periods=30).count() + tm.assert_almost_equal( + result.iloc[-1], np.isfinite(obj[10:-10]).astype(float).sum() + ) + + +@pytest.mark.parametrize( + "roll_func, kwargs", + [ + ["mean", {}], + ["sum", {}], + ["median", {}], + ["min", {}], + ["max", {}], + ["std", {}], + ["std", {"ddof": 0}], + ["var", {}], + ["var", {"ddof": 0}], + ], +) +@pytest.mark.parametrize("minp", [0, 99, 100]) +def test_min_periods(series, minp, roll_func, kwargs, step): + result = getattr( + series.rolling(len(series) + 1, min_periods=minp, step=step), roll_func + )(**kwargs) + expected = getattr( + series.rolling(len(series), min_periods=minp, step=step), roll_func + )(**kwargs) + nan_mask = isna(result) + tm.assert_series_equal(nan_mask, isna(expected)) + + nan_mask = ~nan_mask + tm.assert_almost_equal(result[nan_mask], expected[nan_mask]) + + +def test_min_periods_count(series, step): + result = series.rolling(len(series) + 1, min_periods=0, step=step).count() + expected = series.rolling(len(series), min_periods=0, step=step).count() + nan_mask = isna(result) + tm.assert_series_equal(nan_mask, isna(expected)) + + nan_mask = ~nan_mask + tm.assert_almost_equal(result[nan_mask], expected[nan_mask]) + + +@pytest.mark.parametrize( + "roll_func, kwargs, minp", + [ + ["mean", {}, 15], + ["sum", {}, 15], + ["count", {}, 0], + ["median", {}, 15], + ["min", {}, 15], + ["max", {}, 15], + ["std", {}, 15], + ["std", {"ddof": 0}, 15], + ["var", {}, 15], + ["var", {"ddof": 0}, 15], + ], +) +def test_center(roll_func, kwargs, minp): + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = getattr(obj.rolling(20, min_periods=minp, center=True), roll_func)( + **kwargs + ) + expected = ( + getattr( + concat([obj, Series([np.nan] * 9)]).rolling(20, min_periods=minp), roll_func + )(**kwargs) + .iloc[9:] + .reset_index(drop=True) + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize( + "roll_func, kwargs, minp, fill_value", + [ + ["mean", {}, 10, None], + ["sum", {}, 10, None], + ["count", {}, 0, 0], + ["median", {}, 10, None], + ["min", {}, 10, None], + ["max", {}, 10, None], + ["std", {}, 10, None], + ["std", {"ddof": 0}, 10, None], + ["var", {}, 10, None], + ["var", {"ddof": 0}, 10, None], + ], +) +def test_center_reindex_series(series, roll_func, kwargs, minp, fill_value): + # shifter index + s = [f"x{x:d}" for x in range(12)] + + series_xp = ( + getattr( + series.reindex(list(series.index) + s).rolling(window=25, min_periods=minp), + roll_func, + )(**kwargs) + .shift(-12) + .reindex(series.index) + ) + series_rs = getattr( + series.rolling(window=25, min_periods=minp, center=True), roll_func + )(**kwargs) + if fill_value is not None: + series_xp = series_xp.fillna(fill_value) + tm.assert_series_equal(series_xp, series_rs) + + +@pytest.mark.parametrize( + "roll_func, kwargs, minp, fill_value", + [ + ["mean", {}, 10, None], + ["sum", {}, 10, None], + ["count", {}, 0, 0], + ["median", {}, 10, None], + ["min", {}, 10, None], + ["max", {}, 10, None], + ["std", {}, 10, None], + ["std", {"ddof": 0}, 10, None], + ["var", {}, 10, None], + ["var", {"ddof": 0}, 10, None], + ], +) +def test_center_reindex_frame(frame, roll_func, kwargs, minp, fill_value): + # shifter index + s = [f"x{x:d}" for x in range(12)] + + frame_xp = ( + getattr( + frame.reindex(list(frame.index) + s).rolling(window=25, min_periods=minp), + roll_func, + )(**kwargs) + .shift(-12) + .reindex(frame.index) + ) + frame_rs = getattr( + frame.rolling(window=25, min_periods=minp, center=True), roll_func + )(**kwargs) + if fill_value is not None: + frame_xp = frame_xp.fillna(fill_value) + tm.assert_frame_equal(frame_xp, frame_rs) + + +@pytest.mark.parametrize( + "f", + [ + lambda x: x.rolling(window=10, min_periods=5).cov(x, pairwise=False), + lambda x: x.rolling(window=10, min_periods=5).corr(x, pairwise=False), + lambda x: x.rolling(window=10, min_periods=5).max(), + lambda x: x.rolling(window=10, min_periods=5).min(), + lambda x: x.rolling(window=10, min_periods=5).sum(), + lambda x: x.rolling(window=10, min_periods=5).mean(), + lambda x: x.rolling(window=10, min_periods=5).std(), + lambda x: x.rolling(window=10, min_periods=5).var(), + lambda x: x.rolling(window=10, min_periods=5).skew(), + lambda x: x.rolling(window=10, min_periods=5).kurt(), + lambda x: x.rolling(window=10, min_periods=5).quantile(q=0.5), + lambda x: x.rolling(window=10, min_periods=5).median(), + lambda x: x.rolling(window=10, min_periods=5).apply(sum, raw=False), + lambda x: x.rolling(window=10, min_periods=5).apply(sum, raw=True), + pytest.param( + lambda x: x.rolling(win_type="boxcar", window=10, min_periods=5).mean(), + marks=td.skip_if_no("scipy"), + ), + ], +) +def test_rolling_functions_window_non_shrinkage(f): + # GH 7764 + s = Series(range(4)) + s_expected = Series(np.nan, index=s.index) + df = DataFrame([[1, 5], [3, 2], [3, 9], [-1, 0]], columns=["A", "B"]) + df_expected = DataFrame(np.nan, index=df.index, columns=df.columns) + + s_result = f(s) + tm.assert_series_equal(s_result, s_expected) + + df_result = f(df) + tm.assert_frame_equal(df_result, df_expected) + + +def test_rolling_max_gh6297(step): + """Replicate result expected in GH #6297""" + indices = [datetime(1975, 1, i) for i in range(1, 6)] + # So that we can have 2 datapoints on one of the days + indices.append(datetime(1975, 1, 3, 6, 0)) + series = Series(range(1, 7), index=indices) + # Use floats instead of ints as values + series = series.map(lambda x: float(x)) + # Sort chronologically + series = series.sort_index() + + expected = Series( + [1.0, 2.0, 6.0, 4.0, 5.0], + index=DatetimeIndex([datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"), + )[::step] + x = series.resample("D").max().rolling(window=1, step=step).max() + tm.assert_series_equal(expected, x) + + +def test_rolling_max_resample(step): + indices = [datetime(1975, 1, i) for i in range(1, 6)] + # So that we can have 3 datapoints on last day (4, 10, and 20) + indices.append(datetime(1975, 1, 5, 1)) + indices.append(datetime(1975, 1, 5, 2)) + series = Series(list(range(5)) + [10, 20], index=indices) + # Use floats instead of ints as values + series = series.map(lambda x: float(x)) + # Sort chronologically + series = series.sort_index() + + # Default how should be max + expected = Series( + [0.0, 1.0, 2.0, 3.0, 20.0], + index=DatetimeIndex([datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"), + )[::step] + x = series.resample("D").max().rolling(window=1, step=step).max() + tm.assert_series_equal(expected, x) + + # Now specify median (10.0) + expected = Series( + [0.0, 1.0, 2.0, 3.0, 10.0], + index=DatetimeIndex([datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"), + )[::step] + x = series.resample("D").median().rolling(window=1, step=step).max() + tm.assert_series_equal(expected, x) + + # Now specify mean (4+10+20)/3 + v = (4.0 + 10.0 + 20.0) / 3.0 + expected = Series( + [0.0, 1.0, 2.0, 3.0, v], + index=DatetimeIndex([datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"), + )[::step] + x = series.resample("D").mean().rolling(window=1, step=step).max() + tm.assert_series_equal(expected, x) + + +def test_rolling_min_resample(step): + indices = [datetime(1975, 1, i) for i in range(1, 6)] + # So that we can have 3 datapoints on last day (4, 10, and 20) + indices.append(datetime(1975, 1, 5, 1)) + indices.append(datetime(1975, 1, 5, 2)) + series = Series(list(range(5)) + [10, 20], index=indices) + # Use floats instead of ints as values + series = series.map(lambda x: float(x)) + # Sort chronologically + series = series.sort_index() + + # Default how should be min + expected = Series( + [0.0, 1.0, 2.0, 3.0, 4.0], + index=DatetimeIndex([datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"), + )[::step] + r = series.resample("D").min().rolling(window=1, step=step) + tm.assert_series_equal(expected, r.min()) + + +def test_rolling_median_resample(): + indices = [datetime(1975, 1, i) for i in range(1, 6)] + # So that we can have 3 datapoints on last day (4, 10, and 20) + indices.append(datetime(1975, 1, 5, 1)) + indices.append(datetime(1975, 1, 5, 2)) + series = Series(list(range(5)) + [10, 20], index=indices) + # Use floats instead of ints as values + series = series.map(lambda x: float(x)) + # Sort chronologically + series = series.sort_index() + + # Default how should be median + expected = Series( + [0.0, 1.0, 2.0, 3.0, 10], + index=DatetimeIndex([datetime(1975, 1, i, 0) for i in range(1, 6)], freq="D"), + ) + x = series.resample("D").median().rolling(window=1).median() + tm.assert_series_equal(expected, x) + + +def test_rolling_median_memory_error(): + # GH11722 + n = 20000 + Series(np.random.default_rng(2).standard_normal(n)).rolling( + window=2, center=False + ).median() + Series(np.random.default_rng(2).standard_normal(n)).rolling( + window=2, center=False + ).median() + + +@pytest.mark.parametrize( + "data_type", + [np.dtype(f"f{width}") for width in [4, 8]] + + [np.dtype(f"{sign}{width}") for width in [1, 2, 4, 8] for sign in "ui"], +) +def test_rolling_min_max_numeric_types(data_type): + # GH12373 + + # Just testing that these don't throw exceptions and that + # the return type is float64. Other tests will cover quantitative + # correctness + result = DataFrame(np.arange(20, dtype=data_type)).rolling(window=5).max() + assert result.dtypes[0] == np.dtype("f8") + result = DataFrame(np.arange(20, dtype=data_type)).rolling(window=5).min() + assert result.dtypes[0] == np.dtype("f8") + + +@pytest.mark.parametrize( + "f", + [ + lambda x: x.rolling(window=10, min_periods=0).count(), + lambda x: x.rolling(window=10, min_periods=5).cov(x, pairwise=False), + lambda x: x.rolling(window=10, min_periods=5).corr(x, pairwise=False), + lambda x: x.rolling(window=10, min_periods=5).max(), + lambda x: x.rolling(window=10, min_periods=5).min(), + lambda x: x.rolling(window=10, min_periods=5).sum(), + lambda x: x.rolling(window=10, min_periods=5).mean(), + lambda x: x.rolling(window=10, min_periods=5).std(), + lambda x: x.rolling(window=10, min_periods=5).var(), + lambda x: x.rolling(window=10, min_periods=5).skew(), + lambda x: x.rolling(window=10, min_periods=5).kurt(), + lambda x: x.rolling(window=10, min_periods=5).quantile(0.5), + lambda x: x.rolling(window=10, min_periods=5).median(), + lambda x: x.rolling(window=10, min_periods=5).apply(sum, raw=False), + lambda x: x.rolling(window=10, min_periods=5).apply(sum, raw=True), + pytest.param( + lambda x: x.rolling(win_type="boxcar", window=10, min_periods=5).mean(), + marks=td.skip_if_no("scipy"), + ), + ], +) +def test_moment_functions_zero_length(f): + # GH 8056 + s = Series(dtype=np.float64) + s_expected = s + df1 = DataFrame() + df1_expected = df1 + df2 = DataFrame(columns=["a"]) + df2["a"] = df2["a"].astype("float64") + df2_expected = df2 + + s_result = f(s) + tm.assert_series_equal(s_result, s_expected) + + df1_result = f(df1) + tm.assert_frame_equal(df1_result, df1_expected) + + df2_result = f(df2) + tm.assert_frame_equal(df2_result, df2_expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_quantile.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_quantile.py new file mode 100644 index 0000000000000000000000000000000000000000..d5a7010923563c99b335fd9a309a1d8762d21651 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_quantile.py @@ -0,0 +1,182 @@ +from functools import partial + +import numpy as np +import pytest + +from pandas import ( + DataFrame, + Series, + concat, + isna, + notna, +) +import pandas._testing as tm + +from pandas.tseries import offsets + + +def scoreatpercentile(a, per): + values = np.sort(a, axis=0) + + idx = int(per / 1.0 * (values.shape[0] - 1)) + + if idx == values.shape[0] - 1: + retval = values[-1] + + else: + qlow = idx / (values.shape[0] - 1) + qhig = (idx + 1) / (values.shape[0] - 1) + vlow = values[idx] + vhig = values[idx + 1] + retval = vlow + (vhig - vlow) * (per - qlow) / (qhig - qlow) + + return retval + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_series(series, q, step): + compare_func = partial(scoreatpercentile, per=q) + result = series.rolling(50, step=step).quantile(q) + assert isinstance(result, Series) + end = range(0, len(series), step or 1)[-1] + 1 + tm.assert_almost_equal(result.iloc[-1], compare_func(series[end - 50 : end])) + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_frame(raw, frame, q, step): + compare_func = partial(scoreatpercentile, per=q) + result = frame.rolling(50, step=step).quantile(q) + assert isinstance(result, DataFrame) + end = range(0, len(frame), step or 1)[-1] + 1 + tm.assert_series_equal( + result.iloc[-1, :], + frame.iloc[end - 50 : end, :].apply(compare_func, axis=0, raw=raw), + check_names=False, + ) + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_time_rule_series(series, q): + compare_func = partial(scoreatpercentile, per=q) + win = 25 + ser = series[::2].resample("B").mean() + series_result = ser.rolling(window=win, min_periods=10).quantile(q) + last_date = series_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_series = series[::2].truncate(prev_date, last_date) + tm.assert_almost_equal(series_result.iloc[-1], compare_func(trunc_series)) + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_time_rule_frame(raw, frame, q): + compare_func = partial(scoreatpercentile, per=q) + win = 25 + frm = frame[::2].resample("B").mean() + frame_result = frm.rolling(window=win, min_periods=10).quantile(q) + last_date = frame_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_frame = frame[::2].truncate(prev_date, last_date) + tm.assert_series_equal( + frame_result.xs(last_date), + trunc_frame.apply(compare_func, raw=raw), + check_names=False, + ) + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_nans(q): + compare_func = partial(scoreatpercentile, per=q) + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = obj.rolling(50, min_periods=30).quantile(q) + tm.assert_almost_equal(result.iloc[-1], compare_func(obj[10:-10])) + + # min_periods is working correctly + result = obj.rolling(20, min_periods=15).quantile(q) + assert isna(result.iloc[23]) + assert not isna(result.iloc[24]) + + assert not isna(result.iloc[-6]) + assert isna(result.iloc[-5]) + + obj2 = Series(np.random.default_rng(2).standard_normal(20)) + result = obj2.rolling(10, min_periods=5).quantile(q) + assert isna(result.iloc[3]) + assert notna(result.iloc[4]) + + result0 = obj.rolling(20, min_periods=0).quantile(q) + result1 = obj.rolling(20, min_periods=1).quantile(q) + tm.assert_almost_equal(result0, result1) + + +@pytest.mark.parametrize("minp", [0, 99, 100]) +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_min_periods(series, minp, q, step): + result = series.rolling(len(series) + 1, min_periods=minp, step=step).quantile(q) + expected = series.rolling(len(series), min_periods=minp, step=step).quantile(q) + nan_mask = isna(result) + tm.assert_series_equal(nan_mask, isna(expected)) + + nan_mask = ~nan_mask + tm.assert_almost_equal(result[nan_mask], expected[nan_mask]) + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_center(q): + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = obj.rolling(20, center=True).quantile(q) + expected = ( + concat([obj, Series([np.nan] * 9)]) + .rolling(20) + .quantile(q) + .iloc[9:] + .reset_index(drop=True) + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_center_reindex_series(series, q): + # shifter index + s = [f"x{x:d}" for x in range(12)] + + series_xp = ( + series.reindex(list(series.index) + s) + .rolling(window=25) + .quantile(q) + .shift(-12) + .reindex(series.index) + ) + + series_rs = series.rolling(window=25, center=True).quantile(q) + tm.assert_series_equal(series_xp, series_rs) + + +@pytest.mark.parametrize("q", [0.0, 0.1, 0.5, 0.9, 1.0]) +def test_center_reindex_frame(frame, q): + # shifter index + s = [f"x{x:d}" for x in range(12)] + + frame_xp = ( + frame.reindex(list(frame.index) + s) + .rolling(window=25) + .quantile(q) + .shift(-12) + .reindex(frame.index) + ) + frame_rs = frame.rolling(window=25, center=True).quantile(q) + tm.assert_frame_equal(frame_xp, frame_rs) + + +def test_keyword_quantile_deprecated(): + # GH #52550 + s = Series([1, 2, 3, 4]) + with tm.assert_produces_warning(FutureWarning): + s.rolling(2).quantile(quantile=0.4) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_skew_kurt.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_skew_kurt.py new file mode 100644 index 0000000000000000000000000000000000000000..79c14f243e7cc93b395ea84e05ec6bc79942b79b --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_rolling_skew_kurt.py @@ -0,0 +1,227 @@ +from functools import partial + +import numpy as np +import pytest + +from pandas import ( + DataFrame, + Series, + concat, + isna, + notna, +) +import pandas._testing as tm + +from pandas.tseries import offsets + + +@pytest.mark.parametrize("sp_func, roll_func", [["kurtosis", "kurt"], ["skew", "skew"]]) +def test_series(series, sp_func, roll_func): + sp_stats = pytest.importorskip("scipy.stats") + + compare_func = partial(getattr(sp_stats, sp_func), bias=False) + result = getattr(series.rolling(50), roll_func)() + assert isinstance(result, Series) + tm.assert_almost_equal(result.iloc[-1], compare_func(series[-50:])) + + +@pytest.mark.parametrize("sp_func, roll_func", [["kurtosis", "kurt"], ["skew", "skew"]]) +def test_frame(raw, frame, sp_func, roll_func): + sp_stats = pytest.importorskip("scipy.stats") + + compare_func = partial(getattr(sp_stats, sp_func), bias=False) + result = getattr(frame.rolling(50), roll_func)() + assert isinstance(result, DataFrame) + tm.assert_series_equal( + result.iloc[-1, :], + frame.iloc[-50:, :].apply(compare_func, axis=0, raw=raw), + check_names=False, + ) + + +@pytest.mark.parametrize("sp_func, roll_func", [["kurtosis", "kurt"], ["skew", "skew"]]) +def test_time_rule_series(series, sp_func, roll_func): + sp_stats = pytest.importorskip("scipy.stats") + + compare_func = partial(getattr(sp_stats, sp_func), bias=False) + win = 25 + ser = series[::2].resample("B").mean() + series_result = getattr(ser.rolling(window=win, min_periods=10), roll_func)() + last_date = series_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_series = series[::2].truncate(prev_date, last_date) + tm.assert_almost_equal(series_result.iloc[-1], compare_func(trunc_series)) + + +@pytest.mark.parametrize("sp_func, roll_func", [["kurtosis", "kurt"], ["skew", "skew"]]) +def test_time_rule_frame(raw, frame, sp_func, roll_func): + sp_stats = pytest.importorskip("scipy.stats") + + compare_func = partial(getattr(sp_stats, sp_func), bias=False) + win = 25 + frm = frame[::2].resample("B").mean() + frame_result = getattr(frm.rolling(window=win, min_periods=10), roll_func)() + last_date = frame_result.index[-1] + prev_date = last_date - 24 * offsets.BDay() + + trunc_frame = frame[::2].truncate(prev_date, last_date) + tm.assert_series_equal( + frame_result.xs(last_date), + trunc_frame.apply(compare_func, raw=raw), + check_names=False, + ) + + +@pytest.mark.parametrize("sp_func, roll_func", [["kurtosis", "kurt"], ["skew", "skew"]]) +def test_nans(sp_func, roll_func): + sp_stats = pytest.importorskip("scipy.stats") + + compare_func = partial(getattr(sp_stats, sp_func), bias=False) + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = getattr(obj.rolling(50, min_periods=30), roll_func)() + tm.assert_almost_equal(result.iloc[-1], compare_func(obj[10:-10])) + + # min_periods is working correctly + result = getattr(obj.rolling(20, min_periods=15), roll_func)() + assert isna(result.iloc[23]) + assert not isna(result.iloc[24]) + + assert not isna(result.iloc[-6]) + assert isna(result.iloc[-5]) + + obj2 = Series(np.random.default_rng(2).standard_normal(20)) + result = getattr(obj2.rolling(10, min_periods=5), roll_func)() + assert isna(result.iloc[3]) + assert notna(result.iloc[4]) + + result0 = getattr(obj.rolling(20, min_periods=0), roll_func)() + result1 = getattr(obj.rolling(20, min_periods=1), roll_func)() + tm.assert_almost_equal(result0, result1) + + +@pytest.mark.parametrize("minp", [0, 99, 100]) +@pytest.mark.parametrize("roll_func", ["kurt", "skew"]) +def test_min_periods(series, minp, roll_func, step): + result = getattr( + series.rolling(len(series) + 1, min_periods=minp, step=step), roll_func + )() + expected = getattr( + series.rolling(len(series), min_periods=minp, step=step), roll_func + )() + nan_mask = isna(result) + tm.assert_series_equal(nan_mask, isna(expected)) + + nan_mask = ~nan_mask + tm.assert_almost_equal(result[nan_mask], expected[nan_mask]) + + +@pytest.mark.parametrize("roll_func", ["kurt", "skew"]) +def test_center(roll_func): + obj = Series(np.random.default_rng(2).standard_normal(50)) + obj[:10] = np.nan + obj[-10:] = np.nan + + result = getattr(obj.rolling(20, center=True), roll_func)() + expected = ( + getattr(concat([obj, Series([np.nan] * 9)]).rolling(20), roll_func)() + .iloc[9:] + .reset_index(drop=True) + ) + tm.assert_series_equal(result, expected) + + +@pytest.mark.parametrize("roll_func", ["kurt", "skew"]) +def test_center_reindex_series(series, roll_func): + # shifter index + s = [f"x{x:d}" for x in range(12)] + + series_xp = ( + getattr( + series.reindex(list(series.index) + s).rolling(window=25), + roll_func, + )() + .shift(-12) + .reindex(series.index) + ) + series_rs = getattr(series.rolling(window=25, center=True), roll_func)() + tm.assert_series_equal(series_xp, series_rs) + + +@pytest.mark.slow +@pytest.mark.parametrize("roll_func", ["kurt", "skew"]) +def test_center_reindex_frame(frame, roll_func): + # shifter index + s = [f"x{x:d}" for x in range(12)] + + frame_xp = ( + getattr( + frame.reindex(list(frame.index) + s).rolling(window=25), + roll_func, + )() + .shift(-12) + .reindex(frame.index) + ) + frame_rs = getattr(frame.rolling(window=25, center=True), roll_func)() + tm.assert_frame_equal(frame_xp, frame_rs) + + +def test_rolling_skew_edge_cases(step): + expected = Series([np.nan] * 4 + [0.0])[::step] + # yields all NaN (0 variance) + d = Series([1] * 5) + x = d.rolling(window=5, step=step).skew() + # index 4 should be 0 as it contains 5 same obs + tm.assert_series_equal(expected, x) + + expected = Series([np.nan] * 5)[::step] + # yields all NaN (window too small) + d = Series(np.random.default_rng(2).standard_normal(5)) + x = d.rolling(window=2, step=step).skew() + tm.assert_series_equal(expected, x) + + # yields [NaN, NaN, NaN, 0.177994, 1.548824] + d = Series([-1.50837035, -0.1297039, 0.19501095, 1.73508164, 0.41941401]) + expected = Series([np.nan, np.nan, np.nan, 0.177994, 1.548824])[::step] + x = d.rolling(window=4, step=step).skew() + tm.assert_series_equal(expected, x) + + +def test_rolling_kurt_edge_cases(step): + expected = Series([np.nan] * 4 + [-3.0])[::step] + + # yields all NaN (0 variance) + d = Series([1] * 5) + x = d.rolling(window=5, step=step).kurt() + tm.assert_series_equal(expected, x) + + # yields all NaN (window too small) + expected = Series([np.nan] * 5)[::step] + d = Series(np.random.default_rng(2).standard_normal(5)) + x = d.rolling(window=3, step=step).kurt() + tm.assert_series_equal(expected, x) + + # yields [NaN, NaN, NaN, 1.224307, 2.671499] + d = Series([-1.50837035, -0.1297039, 0.19501095, 1.73508164, 0.41941401]) + expected = Series([np.nan, np.nan, np.nan, 1.224307, 2.671499])[::step] + x = d.rolling(window=4, step=step).kurt() + tm.assert_series_equal(expected, x) + + +def test_rolling_skew_eq_value_fperr(step): + # #18804 all rolling skew for all equal values should return Nan + # #46717 update: all equal values should return 0 instead of NaN + a = Series([1.1] * 15).rolling(window=10, step=step).skew() + assert (a[a.index >= 9] == 0).all() + assert a[a.index < 9].isna().all() + + +def test_rolling_kurt_eq_value_fperr(step): + # #18804 all rolling kurt for all equal values should return Nan + # #46717 update: all equal values should return -3 instead of NaN + a = Series([1.1] * 15).rolling(window=10, step=step).kurt() + assert (a[a.index >= 9] == -3).all() + assert a[a.index < 9].isna().all() diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_timeseries_window.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_timeseries_window.py new file mode 100644 index 0000000000000000000000000000000000000000..bd0fadeb3e47565b6bad3e2e96dd7962b0b31d07 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_timeseries_window.py @@ -0,0 +1,715 @@ +import numpy as np +import pytest + +import pandas.util._test_decorators as td + +from pandas import ( + DataFrame, + DatetimeIndex, + Index, + MultiIndex, + NaT, + Series, + Timestamp, + date_range, +) +import pandas._testing as tm + +from pandas.tseries import offsets + + +@pytest.fixture +def regular(): + return DataFrame( + {"A": date_range("20130101", periods=5, freq="s"), "B": range(5)} + ).set_index("A") + + +@pytest.fixture +def ragged(): + df = DataFrame({"B": range(5)}) + df.index = [ + Timestamp("20130101 09:00:00"), + Timestamp("20130101 09:00:02"), + Timestamp("20130101 09:00:03"), + Timestamp("20130101 09:00:05"), + Timestamp("20130101 09:00:06"), + ] + return df + + +class TestRollingTS: + # rolling time-series friendly + # xref GH13327 + + def test_doc_string(self): + df = DataFrame( + {"B": [0, 1, 2, np.nan, 4]}, + index=[ + Timestamp("20130101 09:00:00"), + Timestamp("20130101 09:00:02"), + Timestamp("20130101 09:00:03"), + Timestamp("20130101 09:00:05"), + Timestamp("20130101 09:00:06"), + ], + ) + df + df.rolling("2s").sum() + + def test_invalid_window_non_int(self, regular): + # not a valid freq + msg = "passed window foobar is not compatible with a datetimelike index" + with pytest.raises(ValueError, match=msg): + regular.rolling(window="foobar") + # not a datetimelike index + msg = "window must be an integer" + with pytest.raises(ValueError, match=msg): + regular.reset_index().rolling(window="foobar") + + @pytest.mark.parametrize("freq", ["2MS", offsets.MonthBegin(2)]) + def test_invalid_window_nonfixed(self, freq, regular): + # non-fixed freqs + msg = "\\<2 \\* MonthBegins\\> is a non-fixed frequency" + with pytest.raises(ValueError, match=msg): + regular.rolling(window=freq) + + @pytest.mark.parametrize("freq", ["1D", offsets.Day(2), "2ms"]) + def test_valid_window(self, freq, regular): + regular.rolling(window=freq) + + @pytest.mark.parametrize("minp", [1.0, "foo", np.array([1, 2, 3])]) + def test_invalid_minp(self, minp, regular): + # non-integer min_periods + msg = ( + r"local variable 'minp' referenced before assignment|" + "min_periods must be an integer" + ) + with pytest.raises(ValueError, match=msg): + regular.rolling(window="1D", min_periods=minp) + + def test_on(self, regular): + df = regular + + # not a valid column + msg = ( + r"invalid on specified as foobar, must be a column " + "\\(of DataFrame\\), an Index or None" + ) + with pytest.raises(ValueError, match=msg): + df.rolling(window="2s", on="foobar") + + # column is valid + df = df.copy() + df["C"] = date_range("20130101", periods=len(df)) + df.rolling(window="2d", on="C").sum() + + # invalid columns + msg = "window must be an integer" + with pytest.raises(ValueError, match=msg): + df.rolling(window="2d", on="B") + + # ok even though on non-selected + df.rolling(window="2d", on="C").B.sum() + + def test_monotonic_on(self): + # on/index must be monotonic + df = DataFrame( + {"A": date_range("20130101", periods=5, freq="s"), "B": range(5)} + ) + + assert df.A.is_monotonic_increasing + df.rolling("2s", on="A").sum() + + df = df.set_index("A") + assert df.index.is_monotonic_increasing + df.rolling("2s").sum() + + def test_non_monotonic_on(self): + # GH 19248 + df = DataFrame( + {"A": date_range("20130101", periods=5, freq="s"), "B": range(5)} + ) + df = df.set_index("A") + non_monotonic_index = df.index.to_list() + non_monotonic_index[0] = non_monotonic_index[3] + df.index = non_monotonic_index + + assert not df.index.is_monotonic_increasing + + msg = "index values must be monotonic" + with pytest.raises(ValueError, match=msg): + df.rolling("2s").sum() + + df = df.reset_index() + + msg = ( + r"invalid on specified as A, must be a column " + "\\(of DataFrame\\), an Index or None" + ) + with pytest.raises(ValueError, match=msg): + df.rolling("2s", on="A").sum() + + def test_frame_on(self): + df = DataFrame( + {"B": range(5), "C": date_range("20130101 09:00:00", periods=5, freq="3s")} + ) + + df["A"] = [ + Timestamp("20130101 09:00:00"), + Timestamp("20130101 09:00:02"), + Timestamp("20130101 09:00:03"), + Timestamp("20130101 09:00:05"), + Timestamp("20130101 09:00:06"), + ] + + # we are doing simulating using 'on' + expected = df.set_index("A").rolling("2s").B.sum().reset_index(drop=True) + + result = df.rolling("2s", on="A").B.sum() + tm.assert_series_equal(result, expected) + + # test as a frame + # we should be ignoring the 'on' as an aggregation column + # note that the expected is setting, computing, and resetting + # so the columns need to be switched compared + # to the actual result where they are ordered as in the + # original + expected = ( + df.set_index("A").rolling("2s")[["B"]].sum().reset_index()[["B", "A"]] + ) + + result = df.rolling("2s", on="A")[["B"]].sum() + tm.assert_frame_equal(result, expected) + + def test_frame_on2(self, unit): + # using multiple aggregation columns + dti = DatetimeIndex( + [ + Timestamp("20130101 09:00:00"), + Timestamp("20130101 09:00:02"), + Timestamp("20130101 09:00:03"), + Timestamp("20130101 09:00:05"), + Timestamp("20130101 09:00:06"), + ] + ).as_unit(unit) + df = DataFrame( + { + "A": [0, 1, 2, 3, 4], + "B": [0, 1, 2, np.nan, 4], + "C": dti, + }, + columns=["A", "C", "B"], + ) + + expected1 = DataFrame( + {"A": [0.0, 1, 3, 3, 7], "B": [0, 1, 3, np.nan, 4], "C": df["C"]}, + columns=["A", "C", "B"], + ) + + result = df.rolling("2s", on="C").sum() + expected = expected1 + tm.assert_frame_equal(result, expected) + + expected = Series([0, 1, 3, np.nan, 4], name="B") + result = df.rolling("2s", on="C").B.sum() + tm.assert_series_equal(result, expected) + + expected = expected1[["A", "B", "C"]] + result = df.rolling("2s", on="C")[["A", "B", "C"]].sum() + tm.assert_frame_equal(result, expected) + + def test_basic_regular(self, regular): + df = regular.copy() + + df.index = date_range("20130101", periods=5, freq="D") + expected = df.rolling(window=1, min_periods=1).sum() + result = df.rolling(window="1D").sum() + tm.assert_frame_equal(result, expected) + + df.index = date_range("20130101", periods=5, freq="2D") + expected = df.rolling(window=1, min_periods=1).sum() + result = df.rolling(window="2D", min_periods=1).sum() + tm.assert_frame_equal(result, expected) + + expected = df.rolling(window=1, min_periods=1).sum() + result = df.rolling(window="2D", min_periods=1).sum() + tm.assert_frame_equal(result, expected) + + expected = df.rolling(window=1).sum() + result = df.rolling(window="2D").sum() + tm.assert_frame_equal(result, expected) + + def test_min_periods(self, regular): + # compare for min_periods + df = regular + + # these slightly different + expected = df.rolling(2, min_periods=1).sum() + result = df.rolling("2s").sum() + tm.assert_frame_equal(result, expected) + + expected = df.rolling(2, min_periods=1).sum() + result = df.rolling("2s", min_periods=1).sum() + tm.assert_frame_equal(result, expected) + + def test_closed(self, regular, unit): + # xref GH13965 + + dti = DatetimeIndex( + [ + Timestamp("20130101 09:00:01"), + Timestamp("20130101 09:00:02"), + Timestamp("20130101 09:00:03"), + Timestamp("20130101 09:00:04"), + Timestamp("20130101 09:00:06"), + ] + ).as_unit(unit) + + df = DataFrame( + {"A": [1] * 5}, + index=dti, + ) + + # closed must be 'right', 'left', 'both', 'neither' + msg = "closed must be 'right', 'left', 'both' or 'neither'" + with pytest.raises(ValueError, match=msg): + regular.rolling(window="2s", closed="blabla") + + expected = df.copy() + expected["A"] = [1.0, 2, 2, 2, 1] + result = df.rolling("2s", closed="right").sum() + tm.assert_frame_equal(result, expected) + + # default should be 'right' + result = df.rolling("2s").sum() + tm.assert_frame_equal(result, expected) + + expected = df.copy() + expected["A"] = [1.0, 2, 3, 3, 2] + result = df.rolling("2s", closed="both").sum() + tm.assert_frame_equal(result, expected) + + expected = df.copy() + expected["A"] = [np.nan, 1.0, 2, 2, 1] + result = df.rolling("2s", closed="left").sum() + tm.assert_frame_equal(result, expected) + + expected = df.copy() + expected["A"] = [np.nan, 1.0, 1, 1, np.nan] + result = df.rolling("2s", closed="neither").sum() + tm.assert_frame_equal(result, expected) + + def test_ragged_sum(self, ragged): + df = ragged + result = df.rolling(window="1s", min_periods=1).sum() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).sum() + expected = df.copy() + expected["B"] = [0.0, 1, 3, 3, 7] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=2).sum() + expected = df.copy() + expected["B"] = [np.nan, np.nan, 3, np.nan, 7] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="3s", min_periods=1).sum() + expected = df.copy() + expected["B"] = [0.0, 1, 3, 5, 7] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="3s").sum() + expected = df.copy() + expected["B"] = [0.0, 1, 3, 5, 7] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="4s", min_periods=1).sum() + expected = df.copy() + expected["B"] = [0.0, 1, 3, 6, 9] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="4s", min_periods=3).sum() + expected = df.copy() + expected["B"] = [np.nan, np.nan, 3, 6, 9] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).sum() + expected = df.copy() + expected["B"] = [0.0, 1, 3, 6, 10] + tm.assert_frame_equal(result, expected) + + def test_ragged_mean(self, ragged): + df = ragged + result = df.rolling(window="1s", min_periods=1).mean() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).mean() + expected = df.copy() + expected["B"] = [0.0, 1, 1.5, 3.0, 3.5] + tm.assert_frame_equal(result, expected) + + def test_ragged_median(self, ragged): + df = ragged + result = df.rolling(window="1s", min_periods=1).median() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).median() + expected = df.copy() + expected["B"] = [0.0, 1, 1.5, 3.0, 3.5] + tm.assert_frame_equal(result, expected) + + def test_ragged_quantile(self, ragged): + df = ragged + result = df.rolling(window="1s", min_periods=1).quantile(0.5) + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).quantile(0.5) + expected = df.copy() + expected["B"] = [0.0, 1, 1.5, 3.0, 3.5] + tm.assert_frame_equal(result, expected) + + def test_ragged_std(self, ragged): + df = ragged + result = df.rolling(window="1s", min_periods=1).std(ddof=0) + expected = df.copy() + expected["B"] = [0.0] * 5 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="1s", min_periods=1).std(ddof=1) + expected = df.copy() + expected["B"] = [np.nan] * 5 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="3s", min_periods=1).std(ddof=0) + expected = df.copy() + expected["B"] = [0.0] + [0.5] * 4 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).std(ddof=1) + expected = df.copy() + expected["B"] = [np.nan, 0.707107, 1.0, 1.0, 1.290994] + tm.assert_frame_equal(result, expected) + + def test_ragged_var(self, ragged): + df = ragged + result = df.rolling(window="1s", min_periods=1).var(ddof=0) + expected = df.copy() + expected["B"] = [0.0] * 5 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="1s", min_periods=1).var(ddof=1) + expected = df.copy() + expected["B"] = [np.nan] * 5 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="3s", min_periods=1).var(ddof=0) + expected = df.copy() + expected["B"] = [0.0] + [0.25] * 4 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).var(ddof=1) + expected = df.copy() + expected["B"] = [np.nan, 0.5, 1.0, 1.0, 1 + 2 / 3.0] + tm.assert_frame_equal(result, expected) + + def test_ragged_skew(self, ragged): + df = ragged + result = df.rolling(window="3s", min_periods=1).skew() + expected = df.copy() + expected["B"] = [np.nan] * 5 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).skew() + expected = df.copy() + expected["B"] = [np.nan] * 2 + [0.0, 0.0, 0.0] + tm.assert_frame_equal(result, expected) + + def test_ragged_kurt(self, ragged): + df = ragged + result = df.rolling(window="3s", min_periods=1).kurt() + expected = df.copy() + expected["B"] = [np.nan] * 5 + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).kurt() + expected = df.copy() + expected["B"] = [np.nan] * 4 + [-1.2] + tm.assert_frame_equal(result, expected) + + def test_ragged_count(self, ragged): + df = ragged + result = df.rolling(window="1s", min_periods=1).count() + expected = df.copy() + expected["B"] = [1.0, 1, 1, 1, 1] + tm.assert_frame_equal(result, expected) + + df = ragged + result = df.rolling(window="1s").count() + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).count() + expected = df.copy() + expected["B"] = [1.0, 1, 2, 1, 2] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=2).count() + expected = df.copy() + expected["B"] = [np.nan, np.nan, 2, np.nan, 2] + tm.assert_frame_equal(result, expected) + + def test_regular_min(self): + df = DataFrame( + {"A": date_range("20130101", periods=5, freq="s"), "B": [0.0, 1, 2, 3, 4]} + ).set_index("A") + result = df.rolling("1s").min() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + df = DataFrame( + {"A": date_range("20130101", periods=5, freq="s"), "B": [5, 4, 3, 4, 5]} + ).set_index("A") + + tm.assert_frame_equal(result, expected) + result = df.rolling("2s").min() + expected = df.copy() + expected["B"] = [5.0, 4, 3, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling("5s").min() + expected = df.copy() + expected["B"] = [5.0, 4, 3, 3, 3] + tm.assert_frame_equal(result, expected) + + def test_ragged_min(self, ragged): + df = ragged + + result = df.rolling(window="1s", min_periods=1).min() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).min() + expected = df.copy() + expected["B"] = [0.0, 1, 1, 3, 3] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).min() + expected = df.copy() + expected["B"] = [0.0, 0, 0, 1, 1] + tm.assert_frame_equal(result, expected) + + def test_perf_min(self): + N = 10000 + + dfp = DataFrame( + {"B": np.random.default_rng(2).standard_normal(N)}, + index=date_range("20130101", periods=N, freq="s"), + ) + expected = dfp.rolling(2, min_periods=1).min() + result = dfp.rolling("2s").min() + assert ((result - expected) < 0.01).all().all() + + expected = dfp.rolling(200, min_periods=1).min() + result = dfp.rolling("200s").min() + assert ((result - expected) < 0.01).all().all() + + def test_ragged_max(self, ragged): + df = ragged + + result = df.rolling(window="1s", min_periods=1).max() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="2s", min_periods=1).max() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + result = df.rolling(window="5s", min_periods=1).max() + expected = df.copy() + expected["B"] = [0.0, 1, 2, 3, 4] + tm.assert_frame_equal(result, expected) + + @pytest.mark.parametrize( + "freq, op, result_data", + [ + ("ms", "min", [0.0] * 10), + ("ms", "mean", [0.0] * 9 + [2.0 / 9]), + ("ms", "max", [0.0] * 9 + [2.0]), + ("s", "min", [0.0] * 10), + ("s", "mean", [0.0] * 9 + [2.0 / 9]), + ("s", "max", [0.0] * 9 + [2.0]), + ("min", "min", [0.0] * 10), + ("min", "mean", [0.0] * 9 + [2.0 / 9]), + ("min", "max", [0.0] * 9 + [2.0]), + ("h", "min", [0.0] * 10), + ("h", "mean", [0.0] * 9 + [2.0 / 9]), + ("h", "max", [0.0] * 9 + [2.0]), + ("D", "min", [0.0] * 10), + ("D", "mean", [0.0] * 9 + [2.0 / 9]), + ("D", "max", [0.0] * 9 + [2.0]), + ], + ) + def test_freqs_ops(self, freq, op, result_data): + # GH 21096 + index = date_range(start="2018-1-1 01:00:00", freq=f"1{freq}", periods=10) + # Explicit cast to float to avoid implicit cast when setting nan + s = Series(data=0, index=index, dtype="float") + s.iloc[1] = np.nan + s.iloc[-1] = 2 + result = getattr(s.rolling(window=f"10{freq}"), op)() + expected = Series(data=result_data, index=index) + + tm.assert_series_equal(result, expected) + + @pytest.mark.parametrize( + "f", + [ + "sum", + "mean", + "count", + "median", + "std", + "var", + "kurt", + "skew", + "min", + "max", + ], + ) + def test_all(self, f, regular): + # simple comparison of integer vs time-based windowing + df = regular * 2 + er = df.rolling(window=1) + r = df.rolling(window="1s") + + result = getattr(r, f)() + expected = getattr(er, f)() + tm.assert_frame_equal(result, expected) + + result = r.quantile(0.5) + expected = er.quantile(0.5) + tm.assert_frame_equal(result, expected) + + def test_all2(self, arithmetic_win_operators): + f = arithmetic_win_operators + # more sophisticated comparison of integer vs. + # time-based windowing + df = DataFrame( + {"B": np.arange(50)}, index=date_range("20130101", periods=50, freq="h") + ) + # in-range data + dft = df.between_time("09:00", "16:00") + + r = dft.rolling(window="5h") + + result = getattr(r, f)() + + # we need to roll the days separately + # to compare with a time-based roll + # finally groupby-apply will return a multi-index + # so we need to drop the day + def agg_by_day(x): + x = x.between_time("09:00", "16:00") + return getattr(x.rolling(5, min_periods=1), f)() + + expected = ( + df.groupby(df.index.day).apply(agg_by_day).reset_index(level=0, drop=True) + ) + + tm.assert_frame_equal(result, expected) + + def test_rolling_cov_offset(self): + # GH16058 + + idx = date_range("2017-01-01", periods=24, freq="1h") + ss = Series(np.arange(len(idx)), index=idx) + + result = ss.rolling("2h").cov() + expected = Series([np.nan] + [0.5] * (len(idx) - 1), index=idx) + tm.assert_series_equal(result, expected) + + expected2 = ss.rolling(2, min_periods=1).cov() + tm.assert_series_equal(result, expected2) + + result = ss.rolling("3h").cov() + expected = Series([np.nan, 0.5] + [1.0] * (len(idx) - 2), index=idx) + tm.assert_series_equal(result, expected) + + expected2 = ss.rolling(3, min_periods=1).cov() + tm.assert_series_equal(result, expected2) + + def test_rolling_on_decreasing_index(self, unit): + # GH-19248, GH-32385 + index = DatetimeIndex( + [ + Timestamp("20190101 09:00:30"), + Timestamp("20190101 09:00:27"), + Timestamp("20190101 09:00:20"), + Timestamp("20190101 09:00:18"), + Timestamp("20190101 09:00:10"), + ] + ).as_unit(unit) + + df = DataFrame({"column": [3, 4, 4, 5, 6]}, index=index) + result = df.rolling("5s").min() + expected = DataFrame({"column": [3.0, 3.0, 4.0, 4.0, 6.0]}, index=index) + tm.assert_frame_equal(result, expected) + + def test_rolling_on_empty(self): + # GH-32385 + df = DataFrame({"column": []}, index=[]) + result = df.rolling("5s").min() + expected = DataFrame({"column": []}, index=[]) + tm.assert_frame_equal(result, expected) + + def test_rolling_on_multi_index_level(self): + # GH-15584 + df = DataFrame( + {"column": range(6)}, + index=MultiIndex.from_product( + [date_range("20190101", periods=3), range(2)], names=["date", "seq"] + ), + ) + result = df.rolling("10d", on=df.index.get_level_values("date")).sum() + expected = DataFrame( + {"column": [0.0, 1.0, 3.0, 6.0, 10.0, 15.0]}, index=df.index + ) + tm.assert_frame_equal(result, expected) + + +@pytest.mark.parametrize("msg, axis", [["column", 1], ["index", 0]]) +def test_nat_axis_error(msg, axis): + idx = [Timestamp("2020"), NaT] + kwargs = {"columns" if axis == 1 else "index": idx} + df = DataFrame(np.eye(2), **kwargs) + warn_msg = "The 'axis' keyword in DataFrame.rolling is deprecated" + if axis == 1: + warn_msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with pytest.raises(ValueError, match=f"{msg} values must not have NaT"): + with tm.assert_produces_warning(FutureWarning, match=warn_msg): + df.rolling("D", axis=axis).mean() + + +@td.skip_if_no("pyarrow") +def test_arrow_datetime_axis(): + # GH 55849 + expected = Series( + np.arange(5, dtype=np.float64), + index=Index( + date_range("2020-01-01", periods=5), dtype="timestamp[ns][pyarrow]" + ), + ) + result = expected.rolling("1D").sum() + tm.assert_series_equal(result, expected) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_win_type.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_win_type.py new file mode 100644 index 0000000000000000000000000000000000000000..5052019ddb7264c4f81e99ccdd79d88d86865ec4 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tests/window/test_win_type.py @@ -0,0 +1,688 @@ +import numpy as np +import pytest + +from pandas import ( + DataFrame, + Series, + Timedelta, + concat, + date_range, +) +import pandas._testing as tm +from pandas.api.indexers import BaseIndexer + + +@pytest.fixture( + params=[ + "triang", + "blackman", + "hamming", + "bartlett", + "bohman", + "blackmanharris", + "nuttall", + "barthann", + ] +) +def win_types(request): + return request.param + + +@pytest.fixture(params=["kaiser", "gaussian", "general_gaussian", "exponential"]) +def win_types_special(request): + return request.param + + +def test_constructor(frame_or_series): + # GH 12669 + pytest.importorskip("scipy") + c = frame_or_series(range(5)).rolling + + # valid + c(win_type="boxcar", window=2, min_periods=1) + c(win_type="boxcar", window=2, min_periods=1, center=True) + c(win_type="boxcar", window=2, min_periods=1, center=False) + + +@pytest.mark.parametrize("w", [2.0, "foo", np.array([2])]) +def test_invalid_constructor(frame_or_series, w): + # not valid + pytest.importorskip("scipy") + c = frame_or_series(range(5)).rolling + with pytest.raises(ValueError, match="min_periods must be an integer"): + c(win_type="boxcar", window=2, min_periods=w) + with pytest.raises(ValueError, match="center must be a boolean"): + c(win_type="boxcar", window=2, min_periods=1, center=w) + + +@pytest.mark.parametrize("wt", ["foobar", 1]) +def test_invalid_constructor_wintype(frame_or_series, wt): + pytest.importorskip("scipy") + c = frame_or_series(range(5)).rolling + with pytest.raises(ValueError, match="Invalid win_type"): + c(win_type=wt, window=2) + + +def test_constructor_with_win_type(frame_or_series, win_types): + # GH 12669 + pytest.importorskip("scipy") + c = frame_or_series(range(5)).rolling + c(win_type=win_types, window=2) + + +@pytest.mark.parametrize("arg", ["median", "kurt", "skew"]) +def test_agg_function_support(arg): + pytest.importorskip("scipy") + df = DataFrame({"A": np.arange(5)}) + roll = df.rolling(2, win_type="triang") + + msg = f"'{arg}' is not a valid function for 'Window' object" + with pytest.raises(AttributeError, match=msg): + roll.agg(arg) + + with pytest.raises(AttributeError, match=msg): + roll.agg([arg]) + + with pytest.raises(AttributeError, match=msg): + roll.agg({"A": arg}) + + +def test_invalid_scipy_arg(): + # This error is raised by scipy + pytest.importorskip("scipy") + msg = r"boxcar\(\) got an unexpected" + with pytest.raises(TypeError, match=msg): + Series(range(3)).rolling(1, win_type="boxcar").mean(foo="bar") + + +def test_constructor_with_win_type_invalid(frame_or_series): + # GH 13383 + pytest.importorskip("scipy") + c = frame_or_series(range(5)).rolling + + msg = "window must be an integer 0 or greater" + + with pytest.raises(ValueError, match=msg): + c(-1, win_type="boxcar") + + +def test_window_with_args(step): + # make sure that we are aggregating window functions correctly with arg + pytest.importorskip("scipy") + r = Series(np.random.default_rng(2).standard_normal(100)).rolling( + window=10, min_periods=1, win_type="gaussian", step=step + ) + expected = concat([r.mean(std=10), r.mean(std=0.01)], axis=1) + expected.columns = ["", ""] + result = r.aggregate([lambda x: x.mean(std=10), lambda x: x.mean(std=0.01)]) + tm.assert_frame_equal(result, expected) + + def a(x): + return x.mean(std=10) + + def b(x): + return x.mean(std=0.01) + + expected = concat([r.mean(std=10), r.mean(std=0.01)], axis=1) + expected.columns = ["a", "b"] + result = r.aggregate([a, b]) + tm.assert_frame_equal(result, expected) + + +def test_win_type_with_method_invalid(): + pytest.importorskip("scipy") + with pytest.raises( + NotImplementedError, match="'single' is the only supported method type." + ): + Series(range(1)).rolling(1, win_type="triang", method="table") + + +@pytest.mark.parametrize("arg", [2000000000, "2s", Timedelta("2s")]) +def test_consistent_win_type_freq(arg): + # GH 15969 + pytest.importorskip("scipy") + s = Series(range(1)) + with pytest.raises(ValueError, match="Invalid win_type freq"): + s.rolling(arg, win_type="freq") + + +def test_win_type_freq_return_none(): + # GH 48838 + freq_roll = Series(range(2), index=date_range("2020", periods=2)).rolling("2s") + assert freq_roll.win_type is None + + +def test_win_type_not_implemented(): + pytest.importorskip("scipy") + + class CustomIndexer(BaseIndexer): + def get_window_bounds(self, num_values, min_periods, center, closed, step): + return np.array([0, 1]), np.array([1, 2]) + + df = DataFrame({"values": range(2)}) + indexer = CustomIndexer() + with pytest.raises(NotImplementedError, match="BaseIndexer subclasses not"): + df.rolling(indexer, win_type="boxcar") + + +def test_cmov_mean(step): + # GH 8238 + pytest.importorskip("scipy") + vals = np.array([6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, 9.48, 10.63, 14.48]) + result = Series(vals).rolling(5, center=True, step=step).mean() + expected_values = [ + np.nan, + np.nan, + 9.962, + 11.27, + 11.564, + 12.516, + 12.818, + 12.952, + np.nan, + np.nan, + ] + expected = Series(expected_values)[::step] + tm.assert_series_equal(expected, result) + + +def test_cmov_window(step): + # GH 8238 + pytest.importorskip("scipy") + vals = np.array([6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, 9.48, 10.63, 14.48]) + result = Series(vals).rolling(5, win_type="boxcar", center=True, step=step).mean() + expected_values = [ + np.nan, + np.nan, + 9.962, + 11.27, + 11.564, + 12.516, + 12.818, + 12.952, + np.nan, + np.nan, + ] + expected = Series(expected_values)[::step] + tm.assert_series_equal(expected, result) + + +def test_cmov_window_corner(step): + # GH 8238 + # all nan + pytest.importorskip("scipy") + vals = Series([np.nan] * 10) + result = vals.rolling(5, center=True, win_type="boxcar", step=step).mean() + assert np.isnan(result).all() + + # empty + vals = Series([], dtype=object) + result = vals.rolling(5, center=True, win_type="boxcar", step=step).mean() + assert len(result) == 0 + + # shorter than window + vals = Series(np.random.default_rng(2).standard_normal(5)) + result = vals.rolling(10, win_type="boxcar", step=step).mean() + assert np.isnan(result).all() + assert len(result) == len(range(0, 5, step or 1)) + + +@pytest.mark.parametrize( + "f,xp", + [ + ( + "mean", + [ + [np.nan, np.nan], + [np.nan, np.nan], + [9.252, 9.392], + [8.644, 9.906], + [8.87, 10.208], + [6.81, 8.588], + [7.792, 8.644], + [9.05, 7.824], + [np.nan, np.nan], + [np.nan, np.nan], + ], + ), + ( + "std", + [ + [np.nan, np.nan], + [np.nan, np.nan], + [3.789706, 4.068313], + [3.429232, 3.237411], + [3.589269, 3.220810], + [3.405195, 2.380655], + [3.281839, 2.369869], + [3.676846, 1.801799], + [np.nan, np.nan], + [np.nan, np.nan], + ], + ), + ( + "var", + [ + [np.nan, np.nan], + [np.nan, np.nan], + [14.36187, 16.55117], + [11.75963, 10.48083], + [12.88285, 10.37362], + [11.59535, 5.66752], + [10.77047, 5.61628], + [13.51920, 3.24648], + [np.nan, np.nan], + [np.nan, np.nan], + ], + ), + ( + "sum", + [ + [np.nan, np.nan], + [np.nan, np.nan], + [46.26, 46.96], + [43.22, 49.53], + [44.35, 51.04], + [34.05, 42.94], + [38.96, 43.22], + [45.25, 39.12], + [np.nan, np.nan], + [np.nan, np.nan], + ], + ), + ], +) +def test_cmov_window_frame(f, xp, step): + # Gh 8238 + pytest.importorskip("scipy") + df = DataFrame( + np.array( + [ + [12.18, 3.64], + [10.18, 9.16], + [13.24, 14.61], + [4.51, 8.11], + [6.15, 11.44], + [9.14, 6.21], + [11.31, 10.67], + [2.94, 6.51], + [9.42, 8.39], + [12.44, 7.34], + ] + ) + ) + xp = DataFrame(np.array(xp))[::step] + + roll = df.rolling(5, win_type="boxcar", center=True, step=step) + rs = getattr(roll, f)() + + tm.assert_frame_equal(xp, rs) + + +@pytest.mark.parametrize("min_periods", [0, 1, 2, 3, 4, 5]) +def test_cmov_window_na_min_periods(step, min_periods): + pytest.importorskip("scipy") + vals = Series(np.random.default_rng(2).standard_normal(10)) + vals[4] = np.nan + vals[8] = np.nan + + xp = vals.rolling(5, min_periods=min_periods, center=True, step=step).mean() + rs = vals.rolling( + 5, win_type="boxcar", min_periods=min_periods, center=True, step=step + ).mean() + tm.assert_series_equal(xp, rs) + + +def test_cmov_window_regular(win_types, step): + # GH 8238 + pytest.importorskip("scipy") + vals = np.array([6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, 9.48, 10.63, 14.48]) + xps = { + "hamming": [ + np.nan, + np.nan, + 8.71384, + 9.56348, + 12.38009, + 14.03687, + 13.8567, + 11.81473, + np.nan, + np.nan, + ], + "triang": [ + np.nan, + np.nan, + 9.28667, + 10.34667, + 12.00556, + 13.33889, + 13.38, + 12.33667, + np.nan, + np.nan, + ], + "barthann": [ + np.nan, + np.nan, + 8.4425, + 9.1925, + 12.5575, + 14.3675, + 14.0825, + 11.5675, + np.nan, + np.nan, + ], + "bohman": [ + np.nan, + np.nan, + 7.61599, + 9.1764, + 12.83559, + 14.17267, + 14.65923, + 11.10401, + np.nan, + np.nan, + ], + "blackmanharris": [ + np.nan, + np.nan, + 6.97691, + 9.16438, + 13.05052, + 14.02156, + 15.10512, + 10.74574, + np.nan, + np.nan, + ], + "nuttall": [ + np.nan, + np.nan, + 7.04618, + 9.16786, + 13.02671, + 14.03559, + 15.05657, + 10.78514, + np.nan, + np.nan, + ], + "blackman": [ + np.nan, + np.nan, + 7.73345, + 9.17869, + 12.79607, + 14.20036, + 14.57726, + 11.16988, + np.nan, + np.nan, + ], + "bartlett": [ + np.nan, + np.nan, + 8.4425, + 9.1925, + 12.5575, + 14.3675, + 14.0825, + 11.5675, + np.nan, + np.nan, + ], + } + + xp = Series(xps[win_types])[::step] + rs = Series(vals).rolling(5, win_type=win_types, center=True, step=step).mean() + tm.assert_series_equal(xp, rs) + + +def test_cmov_window_regular_linear_range(win_types, step): + # GH 8238 + pytest.importorskip("scipy") + vals = np.array(range(10), dtype=float) + xp = vals.copy() + xp[:2] = np.nan + xp[-2:] = np.nan + xp = Series(xp)[::step] + + rs = Series(vals).rolling(5, win_type=win_types, center=True, step=step).mean() + tm.assert_series_equal(xp, rs) + + +def test_cmov_window_regular_missing_data(win_types, step): + # GH 8238 + pytest.importorskip("scipy") + vals = np.array( + [6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, np.nan, 10.63, 14.48] + ) + xps = { + "bartlett": [ + np.nan, + np.nan, + 9.70333, + 10.5225, + 8.4425, + 9.1925, + 12.5575, + 14.3675, + 15.61667, + 13.655, + ], + "blackman": [ + np.nan, + np.nan, + 9.04582, + 11.41536, + 7.73345, + 9.17869, + 12.79607, + 14.20036, + 15.8706, + 13.655, + ], + "barthann": [ + np.nan, + np.nan, + 9.70333, + 10.5225, + 8.4425, + 9.1925, + 12.5575, + 14.3675, + 15.61667, + 13.655, + ], + "bohman": [ + np.nan, + np.nan, + 8.9444, + 11.56327, + 7.61599, + 9.1764, + 12.83559, + 14.17267, + 15.90976, + 13.655, + ], + "hamming": [ + np.nan, + np.nan, + 9.59321, + 10.29694, + 8.71384, + 9.56348, + 12.38009, + 14.20565, + 15.24694, + 13.69758, + ], + "nuttall": [ + np.nan, + np.nan, + 8.47693, + 12.2821, + 7.04618, + 9.16786, + 13.02671, + 14.03673, + 16.08759, + 13.65553, + ], + "triang": [ + np.nan, + np.nan, + 9.33167, + 9.76125, + 9.28667, + 10.34667, + 12.00556, + 13.82125, + 14.49429, + 13.765, + ], + "blackmanharris": [ + np.nan, + np.nan, + 8.42526, + 12.36824, + 6.97691, + 9.16438, + 13.05052, + 14.02175, + 16.1098, + 13.65509, + ], + } + + xp = Series(xps[win_types])[::step] + rs = Series(vals).rolling(5, win_type=win_types, min_periods=3, step=step).mean() + tm.assert_series_equal(xp, rs) + + +def test_cmov_window_special(win_types_special, step): + # GH 8238 + pytest.importorskip("scipy") + kwds = { + "kaiser": {"beta": 1.0}, + "gaussian": {"std": 1.0}, + "general_gaussian": {"p": 2.0, "sig": 2.0}, + "exponential": {"tau": 10}, + } + + vals = np.array([6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, 9.48, 10.63, 14.48]) + + xps = { + "gaussian": [ + np.nan, + np.nan, + 8.97297, + 9.76077, + 12.24763, + 13.89053, + 13.65671, + 12.01002, + np.nan, + np.nan, + ], + "general_gaussian": [ + np.nan, + np.nan, + 9.85011, + 10.71589, + 11.73161, + 13.08516, + 12.95111, + 12.74577, + np.nan, + np.nan, + ], + "kaiser": [ + np.nan, + np.nan, + 9.86851, + 11.02969, + 11.65161, + 12.75129, + 12.90702, + 12.83757, + np.nan, + np.nan, + ], + "exponential": [ + np.nan, + np.nan, + 9.83364, + 11.10472, + 11.64551, + 12.66138, + 12.92379, + 12.83770, + np.nan, + np.nan, + ], + } + + xp = Series(xps[win_types_special])[::step] + rs = ( + Series(vals) + .rolling(5, win_type=win_types_special, center=True, step=step) + .mean(**kwds[win_types_special]) + ) + tm.assert_series_equal(xp, rs) + + +def test_cmov_window_special_linear_range(win_types_special, step): + # GH 8238 + pytest.importorskip("scipy") + kwds = { + "kaiser": {"beta": 1.0}, + "gaussian": {"std": 1.0}, + "general_gaussian": {"p": 2.0, "sig": 2.0}, + "slepian": {"width": 0.5}, + "exponential": {"tau": 10}, + } + + vals = np.array(range(10), dtype=float) + xp = vals.copy() + xp[:2] = np.nan + xp[-2:] = np.nan + xp = Series(xp)[::step] + + rs = ( + Series(vals) + .rolling(5, win_type=win_types_special, center=True, step=step) + .mean(**kwds[win_types_special]) + ) + tm.assert_series_equal(xp, rs) + + +def test_weighted_var_big_window_no_segfault(win_types, center): + # GitHub Issue #46772 + pytest.importorskip("scipy") + x = Series(0) + result = x.rolling(window=16, center=center, win_type=win_types).var() + expected = Series(np.nan) + + tm.assert_series_equal(result, expected) + + +def test_rolling_center_axis_1(): + pytest.importorskip("scipy") + df = DataFrame( + {"a": [1, 1, 0, 0, 0, 1], "b": [1, 0, 0, 1, 0, 0], "c": [1, 0, 0, 1, 0, 1]} + ) + + msg = "Support for axis=1 in DataFrame.rolling is deprecated" + with tm.assert_produces_warning(FutureWarning, match=msg): + result = df.rolling(window=3, axis=1, win_type="boxcar", center=True).sum() + + expected = DataFrame( + {"a": [np.nan] * 6, "b": [3.0, 1.0, 0.0, 2.0, 0.0, 2.0], "c": [np.nan] * 6} + ) + + tm.assert_frame_equal(result, expected, check_dtype=True) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e361726dc6f80d41cb4975641b44624427b489d6 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/__init__.py @@ -0,0 +1,12 @@ +# ruff: noqa: TCH004 +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + # import modules that have public classes/functions: + from pandas.tseries import ( + frequencies, + offsets, + ) + + # and mark only those modules as public + __all__ = ["frequencies", "offsets"] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/api.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/api.py new file mode 100644 index 0000000000000000000000000000000000000000..ec2d7d230483947d78f737af42684effa3e60514 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/api.py @@ -0,0 +1,10 @@ +""" +Timeseries API +""" + +from pandas._libs.tslibs.parsing import guess_datetime_format + +from pandas.tseries import offsets +from pandas.tseries.frequencies import infer_freq + +__all__ = ["infer_freq", "offsets", "guess_datetime_format"] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/frequencies.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/frequencies.py new file mode 100644 index 0000000000000000000000000000000000000000..4a1a668426b36ef10f56352653121b6420070882 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/frequencies.py @@ -0,0 +1,602 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np + +from pandas._libs import lib +from pandas._libs.algos import unique_deltas +from pandas._libs.tslibs import ( + Timestamp, + get_unit_from_dtype, + periods_per_day, + tz_convert_from_utc, +) +from pandas._libs.tslibs.ccalendar import ( + DAYS, + MONTH_ALIASES, + MONTH_NUMBERS, + MONTHS, + int_to_weekday, +) +from pandas._libs.tslibs.dtypes import ( + OFFSET_TO_PERIOD_FREQSTR, + freq_to_period_freqstr, +) +from pandas._libs.tslibs.fields import ( + build_field_sarray, + month_position_check, +) +from pandas._libs.tslibs.offsets import ( + DateOffset, + Day, + to_offset, +) +from pandas._libs.tslibs.parsing import get_rule_month +from pandas.util._decorators import cache_readonly + +from pandas.core.dtypes.common import is_numeric_dtype +from pandas.core.dtypes.dtypes import ( + DatetimeTZDtype, + PeriodDtype, +) +from pandas.core.dtypes.generic import ( + ABCIndex, + ABCSeries, +) + +from pandas.core.algorithms import unique + +if TYPE_CHECKING: + from pandas._typing import npt + + from pandas import ( + DatetimeIndex, + Series, + TimedeltaIndex, + ) + from pandas.core.arrays.datetimelike import DatetimeLikeArrayMixin +# -------------------------------------------------------------------- +# Offset related functions + +_need_suffix = ["QS", "BQE", "BQS", "YS", "BYE", "BYS"] + +for _prefix in _need_suffix: + for _m in MONTHS: + key = f"{_prefix}-{_m}" + OFFSET_TO_PERIOD_FREQSTR[key] = OFFSET_TO_PERIOD_FREQSTR[_prefix] + +for _prefix in ["Y", "Q"]: + for _m in MONTHS: + _alias = f"{_prefix}-{_m}" + OFFSET_TO_PERIOD_FREQSTR[_alias] = _alias + +for _d in DAYS: + OFFSET_TO_PERIOD_FREQSTR[f"W-{_d}"] = f"W-{_d}" + + +def get_period_alias(offset_str: str) -> str | None: + """ + Alias to closest period strings BQ->Q etc. + """ + return OFFSET_TO_PERIOD_FREQSTR.get(offset_str, None) + + +# --------------------------------------------------------------------- +# Period codes + + +def infer_freq( + index: DatetimeIndex | TimedeltaIndex | Series | DatetimeLikeArrayMixin, +) -> str | None: + """ + Infer the most likely frequency given the input index. + + Parameters + ---------- + index : DatetimeIndex, TimedeltaIndex, Series or array-like + If passed a Series will use the values of the series (NOT THE INDEX). + + Returns + ------- + str or None + None if no discernible frequency. + + Raises + ------ + TypeError + If the index is not datetime-like. + ValueError + If there are fewer than three values. + + Examples + -------- + >>> idx = pd.date_range(start='2020/12/01', end='2020/12/30', periods=30) + >>> pd.infer_freq(idx) + 'D' + """ + from pandas.core.api import DatetimeIndex + + if isinstance(index, ABCSeries): + values = index._values + if not ( + lib.is_np_dtype(values.dtype, "mM") + or isinstance(values.dtype, DatetimeTZDtype) + or values.dtype == object + ): + raise TypeError( + "cannot infer freq from a non-convertible dtype " + f"on a Series of {index.dtype}" + ) + index = values + + inferer: _FrequencyInferer + + if not hasattr(index, "dtype"): + pass + elif isinstance(index.dtype, PeriodDtype): + raise TypeError( + "PeriodIndex given. Check the `freq` attribute " + "instead of using infer_freq." + ) + elif lib.is_np_dtype(index.dtype, "m"): + # Allow TimedeltaIndex and TimedeltaArray + inferer = _TimedeltaFrequencyInferer(index) + return inferer.get_freq() + + elif is_numeric_dtype(index.dtype): + raise TypeError( + f"cannot infer freq from a non-convertible index of dtype {index.dtype}" + ) + + if not isinstance(index, DatetimeIndex): + index = DatetimeIndex(index) + + inferer = _FrequencyInferer(index) + return inferer.get_freq() + + +class _FrequencyInferer: + """ + Not sure if I can avoid the state machine here + """ + + def __init__(self, index) -> None: + self.index = index + self.i8values = index.asi8 + + # For get_unit_from_dtype we need the dtype to the underlying ndarray, + # which for tz-aware is not the same as index.dtype + if isinstance(index, ABCIndex): + # error: Item "ndarray[Any, Any]" of "Union[ExtensionArray, + # ndarray[Any, Any]]" has no attribute "_ndarray" + self._creso = get_unit_from_dtype( + index._data._ndarray.dtype # type: ignore[union-attr] + ) + else: + # otherwise we have DTA/TDA + self._creso = get_unit_from_dtype(index._ndarray.dtype) + + # This moves the values, which are implicitly in UTC, to the + # the timezone so they are in local time + if hasattr(index, "tz"): + if index.tz is not None: + self.i8values = tz_convert_from_utc( + self.i8values, index.tz, reso=self._creso + ) + + if len(index) < 3: + raise ValueError("Need at least 3 dates to infer frequency") + + self.is_monotonic = ( + self.index._is_monotonic_increasing or self.index._is_monotonic_decreasing + ) + + @cache_readonly + def deltas(self) -> npt.NDArray[np.int64]: + return unique_deltas(self.i8values) + + @cache_readonly + def deltas_asi8(self) -> npt.NDArray[np.int64]: + # NB: we cannot use self.i8values here because we may have converted + # the tz in __init__ + return unique_deltas(self.index.asi8) + + @cache_readonly + def is_unique(self) -> bool: + return len(self.deltas) == 1 + + @cache_readonly + def is_unique_asi8(self) -> bool: + return len(self.deltas_asi8) == 1 + + def get_freq(self) -> str | None: + """ + Find the appropriate frequency string to describe the inferred + frequency of self.i8values + + Returns + ------- + str or None + """ + if not self.is_monotonic or not self.index._is_unique: + return None + + delta = self.deltas[0] + ppd = periods_per_day(self._creso) + if delta and _is_multiple(delta, ppd): + return self._infer_daily_rule() + + # Business hourly, maybe. 17: one day / 65: one weekend + if self.hour_deltas in ([1, 17], [1, 65], [1, 17, 65]): + return "bh" + + # Possibly intraday frequency. Here we use the + # original .asi8 values as the modified values + # will not work around DST transitions. See #8772 + if not self.is_unique_asi8: + return None + + delta = self.deltas_asi8[0] + pph = ppd // 24 + ppm = pph // 60 + pps = ppm // 60 + if _is_multiple(delta, pph): + # Hours + return _maybe_add_count("h", delta / pph) + elif _is_multiple(delta, ppm): + # Minutes + return _maybe_add_count("min", delta / ppm) + elif _is_multiple(delta, pps): + # Seconds + return _maybe_add_count("s", delta / pps) + elif _is_multiple(delta, (pps // 1000)): + # Milliseconds + return _maybe_add_count("ms", delta / (pps // 1000)) + elif _is_multiple(delta, (pps // 1_000_000)): + # Microseconds + return _maybe_add_count("us", delta / (pps // 1_000_000)) + else: + # Nanoseconds + return _maybe_add_count("ns", delta) + + @cache_readonly + def day_deltas(self) -> list[int]: + ppd = periods_per_day(self._creso) + return [x / ppd for x in self.deltas] + + @cache_readonly + def hour_deltas(self) -> list[int]: + pph = periods_per_day(self._creso) // 24 + return [x / pph for x in self.deltas] + + @cache_readonly + def fields(self) -> np.ndarray: # structured array of fields + return build_field_sarray(self.i8values, reso=self._creso) + + @cache_readonly + def rep_stamp(self) -> Timestamp: + return Timestamp(self.i8values[0], unit=self.index.unit) + + def month_position_check(self) -> str | None: + return month_position_check(self.fields, self.index.dayofweek) + + @cache_readonly + def mdiffs(self) -> npt.NDArray[np.int64]: + nmonths = self.fields["Y"] * 12 + self.fields["M"] + return unique_deltas(nmonths.astype("i8")) + + @cache_readonly + def ydiffs(self) -> npt.NDArray[np.int64]: + return unique_deltas(self.fields["Y"].astype("i8")) + + def _infer_daily_rule(self) -> str | None: + annual_rule = self._get_annual_rule() + if annual_rule: + nyears = self.ydiffs[0] + month = MONTH_ALIASES[self.rep_stamp.month] + alias = f"{annual_rule}-{month}" + return _maybe_add_count(alias, nyears) + + quarterly_rule = self._get_quarterly_rule() + if quarterly_rule: + nquarters = self.mdiffs[0] / 3 + mod_dict = {0: 12, 2: 11, 1: 10} + month = MONTH_ALIASES[mod_dict[self.rep_stamp.month % 3]] + alias = f"{quarterly_rule}-{month}" + return _maybe_add_count(alias, nquarters) + + monthly_rule = self._get_monthly_rule() + if monthly_rule: + return _maybe_add_count(monthly_rule, self.mdiffs[0]) + + if self.is_unique: + return self._get_daily_rule() + + if self._is_business_daily(): + return "B" + + wom_rule = self._get_wom_rule() + if wom_rule: + return wom_rule + + return None + + def _get_daily_rule(self) -> str | None: + ppd = periods_per_day(self._creso) + days = self.deltas[0] / ppd + if days % 7 == 0: + # Weekly + wd = int_to_weekday[self.rep_stamp.weekday()] + alias = f"W-{wd}" + return _maybe_add_count(alias, days / 7) + else: + return _maybe_add_count("D", days) + + def _get_annual_rule(self) -> str | None: + if len(self.ydiffs) > 1: + return None + + if len(unique(self.fields["M"])) > 1: + return None + + pos_check = self.month_position_check() + + if pos_check is None: + return None + else: + return {"cs": "YS", "bs": "BYS", "ce": "YE", "be": "BYE"}.get(pos_check) + + def _get_quarterly_rule(self) -> str | None: + if len(self.mdiffs) > 1: + return None + + if not self.mdiffs[0] % 3 == 0: + return None + + pos_check = self.month_position_check() + + if pos_check is None: + return None + else: + return {"cs": "QS", "bs": "BQS", "ce": "QE", "be": "BQE"}.get(pos_check) + + def _get_monthly_rule(self) -> str | None: + if len(self.mdiffs) > 1: + return None + pos_check = self.month_position_check() + + if pos_check is None: + return None + else: + return {"cs": "MS", "bs": "BMS", "ce": "ME", "be": "BME"}.get(pos_check) + + def _is_business_daily(self) -> bool: + # quick check: cannot be business daily + if self.day_deltas != [1, 3]: + return False + + # probably business daily, but need to confirm + first_weekday = self.index[0].weekday() + shifts = np.diff(self.i8values) + ppd = periods_per_day(self._creso) + shifts = np.floor_divide(shifts, ppd) + weekdays = np.mod(first_weekday + np.cumsum(shifts), 7) + + return bool( + np.all( + ((weekdays == 0) & (shifts == 3)) + | ((weekdays > 0) & (weekdays <= 4) & (shifts == 1)) + ) + ) + + def _get_wom_rule(self) -> str | None: + weekdays = unique(self.index.weekday) + if len(weekdays) > 1: + return None + + week_of_months = unique((self.index.day - 1) // 7) + # Only attempt to infer up to WOM-4. See #9425 + week_of_months = week_of_months[week_of_months < 4] + if len(week_of_months) == 0 or len(week_of_months) > 1: + return None + + # get which week + week = week_of_months[0] + 1 + wd = int_to_weekday[weekdays[0]] + + return f"WOM-{week}{wd}" + + +class _TimedeltaFrequencyInferer(_FrequencyInferer): + def _infer_daily_rule(self): + if self.is_unique: + return self._get_daily_rule() + + +def _is_multiple(us, mult: int) -> bool: + return us % mult == 0 + + +def _maybe_add_count(base: str, count: float) -> str: + if count != 1: + assert count == int(count) + count = int(count) + return f"{count}{base}" + else: + return base + + +# ---------------------------------------------------------------------- +# Frequency comparison + + +def is_subperiod(source, target) -> bool: + """ + Returns True if downsampling is possible between source and target + frequencies + + Parameters + ---------- + source : str or DateOffset + Frequency converting from + target : str or DateOffset + Frequency converting to + + Returns + ------- + bool + """ + if target is None or source is None: + return False + source = _maybe_coerce_freq(source) + target = _maybe_coerce_freq(target) + + if _is_annual(target): + if _is_quarterly(source): + return _quarter_months_conform( + get_rule_month(source), get_rule_month(target) + ) + return source in {"D", "C", "B", "M", "h", "min", "s", "ms", "us", "ns"} + elif _is_quarterly(target): + return source in {"D", "C", "B", "M", "h", "min", "s", "ms", "us", "ns"} + elif _is_monthly(target): + return source in {"D", "C", "B", "h", "min", "s", "ms", "us", "ns"} + elif _is_weekly(target): + return source in {target, "D", "C", "B", "h", "min", "s", "ms", "us", "ns"} + elif target == "B": + return source in {"B", "h", "min", "s", "ms", "us", "ns"} + elif target == "C": + return source in {"C", "h", "min", "s", "ms", "us", "ns"} + elif target == "D": + return source in {"D", "h", "min", "s", "ms", "us", "ns"} + elif target == "h": + return source in {"h", "min", "s", "ms", "us", "ns"} + elif target == "min": + return source in {"min", "s", "ms", "us", "ns"} + elif target == "s": + return source in {"s", "ms", "us", "ns"} + elif target == "ms": + return source in {"ms", "us", "ns"} + elif target == "us": + return source in {"us", "ns"} + elif target == "ns": + return source in {"ns"} + else: + return False + + +def is_superperiod(source, target) -> bool: + """ + Returns True if upsampling is possible between source and target + frequencies + + Parameters + ---------- + source : str or DateOffset + Frequency converting from + target : str or DateOffset + Frequency converting to + + Returns + ------- + bool + """ + if target is None or source is None: + return False + source = _maybe_coerce_freq(source) + target = _maybe_coerce_freq(target) + + if _is_annual(source): + if _is_annual(target): + return get_rule_month(source) == get_rule_month(target) + + if _is_quarterly(target): + smonth = get_rule_month(source) + tmonth = get_rule_month(target) + return _quarter_months_conform(smonth, tmonth) + return target in {"D", "C", "B", "M", "h", "min", "s", "ms", "us", "ns"} + elif _is_quarterly(source): + return target in {"D", "C", "B", "M", "h", "min", "s", "ms", "us", "ns"} + elif _is_monthly(source): + return target in {"D", "C", "B", "h", "min", "s", "ms", "us", "ns"} + elif _is_weekly(source): + return target in {source, "D", "C", "B", "h", "min", "s", "ms", "us", "ns"} + elif source == "B": + return target in {"D", "C", "B", "h", "min", "s", "ms", "us", "ns"} + elif source == "C": + return target in {"D", "C", "B", "h", "min", "s", "ms", "us", "ns"} + elif source == "D": + return target in {"D", "C", "B", "h", "min", "s", "ms", "us", "ns"} + elif source == "h": + return target in {"h", "min", "s", "ms", "us", "ns"} + elif source == "min": + return target in {"min", "s", "ms", "us", "ns"} + elif source == "s": + return target in {"s", "ms", "us", "ns"} + elif source == "ms": + return target in {"ms", "us", "ns"} + elif source == "us": + return target in {"us", "ns"} + elif source == "ns": + return target in {"ns"} + else: + return False + + +def _maybe_coerce_freq(code) -> str: + """we might need to coerce a code to a rule_code + and uppercase it + + Parameters + ---------- + source : str or DateOffset + Frequency converting from + + Returns + ------- + str + """ + assert code is not None + if isinstance(code, DateOffset): + code = freq_to_period_freqstr(1, code.name) + if code in {"h", "min", "s", "ms", "us", "ns"}: + return code + else: + return code.upper() + + +def _quarter_months_conform(source: str, target: str) -> bool: + snum = MONTH_NUMBERS[source] + tnum = MONTH_NUMBERS[target] + return snum % 3 == tnum % 3 + + +def _is_annual(rule: str) -> bool: + rule = rule.upper() + return rule == "Y" or rule.startswith("Y-") + + +def _is_quarterly(rule: str) -> bool: + rule = rule.upper() + return rule == "Q" or rule.startswith(("Q-", "BQ")) + + +def _is_monthly(rule: str) -> bool: + rule = rule.upper() + return rule in ("M", "BM") + + +def _is_weekly(rule: str) -> bool: + rule = rule.upper() + return rule == "W" or rule.startswith("W-") + + +__all__ = [ + "Day", + "get_period_alias", + "infer_freq", + "is_subperiod", + "is_superperiod", + "to_offset", +] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/holiday.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/holiday.py new file mode 100644 index 0000000000000000000000000000000000000000..3c429a960b45181c831055cb3e877dbc4cad3b30 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/holiday.py @@ -0,0 +1,634 @@ +from __future__ import annotations + +from datetime import ( + datetime, + timedelta, +) +import warnings + +from dateutil.relativedelta import ( + FR, + MO, + SA, + SU, + TH, + TU, + WE, +) +import numpy as np + +from pandas.errors import PerformanceWarning + +from pandas import ( + DateOffset, + DatetimeIndex, + Series, + Timestamp, + concat, + date_range, +) + +from pandas.tseries.offsets import ( + Day, + Easter, +) + + +def next_monday(dt: datetime) -> datetime: + """ + If holiday falls on Saturday, use following Monday instead; + if holiday falls on Sunday, use Monday instead + """ + if dt.weekday() == 5: + return dt + timedelta(2) + elif dt.weekday() == 6: + return dt + timedelta(1) + return dt + + +def next_monday_or_tuesday(dt: datetime) -> datetime: + """ + For second holiday of two adjacent ones! + If holiday falls on Saturday, use following Monday instead; + if holiday falls on Sunday or Monday, use following Tuesday instead + (because Monday is already taken by adjacent holiday on the day before) + """ + dow = dt.weekday() + if dow in (5, 6): + return dt + timedelta(2) + if dow == 0: + return dt + timedelta(1) + return dt + + +def previous_friday(dt: datetime) -> datetime: + """ + If holiday falls on Saturday or Sunday, use previous Friday instead. + """ + if dt.weekday() == 5: + return dt - timedelta(1) + elif dt.weekday() == 6: + return dt - timedelta(2) + return dt + + +def sunday_to_monday(dt: datetime) -> datetime: + """ + If holiday falls on Sunday, use day thereafter (Monday) instead. + """ + if dt.weekday() == 6: + return dt + timedelta(1) + return dt + + +def weekend_to_monday(dt: datetime) -> datetime: + """ + If holiday falls on Sunday or Saturday, + use day thereafter (Monday) instead. + Needed for holidays such as Christmas observation in Europe + """ + if dt.weekday() == 6: + return dt + timedelta(1) + elif dt.weekday() == 5: + return dt + timedelta(2) + return dt + + +def nearest_workday(dt: datetime) -> datetime: + """ + If holiday falls on Saturday, use day before (Friday) instead; + if holiday falls on Sunday, use day thereafter (Monday) instead. + """ + if dt.weekday() == 5: + return dt - timedelta(1) + elif dt.weekday() == 6: + return dt + timedelta(1) + return dt + + +def next_workday(dt: datetime) -> datetime: + """ + returns next weekday used for observances + """ + dt += timedelta(days=1) + while dt.weekday() > 4: + # Mon-Fri are 0-4 + dt += timedelta(days=1) + return dt + + +def previous_workday(dt: datetime) -> datetime: + """ + returns previous weekday used for observances + """ + dt -= timedelta(days=1) + while dt.weekday() > 4: + # Mon-Fri are 0-4 + dt -= timedelta(days=1) + return dt + + +def before_nearest_workday(dt: datetime) -> datetime: + """ + returns previous workday after nearest workday + """ + return previous_workday(nearest_workday(dt)) + + +def after_nearest_workday(dt: datetime) -> datetime: + """ + returns next workday after nearest workday + needed for Boxing day or multiple holidays in a series + """ + return next_workday(nearest_workday(dt)) + + +class Holiday: + """ + Class that defines a holiday with start/end dates and rules + for observance. + """ + + start_date: Timestamp | None + end_date: Timestamp | None + days_of_week: tuple[int, ...] | None + + def __init__( + self, + name: str, + year=None, + month=None, + day=None, + offset=None, + observance=None, + start_date=None, + end_date=None, + days_of_week=None, + ) -> None: + """ + Parameters + ---------- + name : str + Name of the holiday , defaults to class name + offset : array of pandas.tseries.offsets or + class from pandas.tseries.offsets + computes offset from date + observance: function + computes when holiday is given a pandas Timestamp + days_of_week: + provide a tuple of days e.g (0,1,2,3,) for Monday Through Thursday + Monday=0,..,Sunday=6 + + Examples + -------- + >>> from dateutil.relativedelta import MO + + >>> USMemorialDay = pd.tseries.holiday.Holiday( + ... "Memorial Day", month=5, day=31, offset=pd.DateOffset(weekday=MO(-1)) + ... ) + >>> USMemorialDay + Holiday: Memorial Day (month=5, day=31, offset=) + + >>> USLaborDay = pd.tseries.holiday.Holiday( + ... "Labor Day", month=9, day=1, offset=pd.DateOffset(weekday=MO(1)) + ... ) + >>> USLaborDay + Holiday: Labor Day (month=9, day=1, offset=) + + >>> July3rd = pd.tseries.holiday.Holiday("July 3rd", month=7, day=3) + >>> July3rd + Holiday: July 3rd (month=7, day=3, ) + + >>> NewYears = pd.tseries.holiday.Holiday( + ... "New Years Day", month=1, day=1, + ... observance=pd.tseries.holiday.nearest_workday + ... ) + >>> NewYears # doctest: +SKIP + Holiday: New Years Day ( + month=1, day=1, observance= + ) + + >>> July3rd = pd.tseries.holiday.Holiday( + ... "July 3rd", month=7, day=3, + ... days_of_week=(0, 1, 2, 3) + ... ) + >>> July3rd + Holiday: July 3rd (month=7, day=3, ) + """ + if offset is not None and observance is not None: + raise NotImplementedError("Cannot use both offset and observance.") + + self.name = name + self.year = year + self.month = month + self.day = day + self.offset = offset + self.start_date = ( + Timestamp(start_date) if start_date is not None else start_date + ) + self.end_date = Timestamp(end_date) if end_date is not None else end_date + self.observance = observance + assert days_of_week is None or type(days_of_week) == tuple + self.days_of_week = days_of_week + + def __repr__(self) -> str: + info = "" + if self.year is not None: + info += f"year={self.year}, " + info += f"month={self.month}, day={self.day}, " + + if self.offset is not None: + info += f"offset={self.offset}" + + if self.observance is not None: + info += f"observance={self.observance}" + + repr = f"Holiday: {self.name} ({info})" + return repr + + def dates( + self, start_date, end_date, return_name: bool = False + ) -> Series | DatetimeIndex: + """ + Calculate holidays observed between start date and end date + + Parameters + ---------- + start_date : starting date, datetime-like, optional + end_date : ending date, datetime-like, optional + return_name : bool, optional, default=False + If True, return a series that has dates and holiday names. + False will only return dates. + + Returns + ------- + Series or DatetimeIndex + Series if return_name is True + """ + start_date = Timestamp(start_date) + end_date = Timestamp(end_date) + + filter_start_date = start_date + filter_end_date = end_date + + if self.year is not None: + dt = Timestamp(datetime(self.year, self.month, self.day)) + dti = DatetimeIndex([dt]) + if return_name: + return Series(self.name, index=dti) + else: + return dti + + dates = self._reference_dates(start_date, end_date) + holiday_dates = self._apply_rule(dates) + if self.days_of_week is not None: + holiday_dates = holiday_dates[ + np.isin( + # error: "DatetimeIndex" has no attribute "dayofweek" + holiday_dates.dayofweek, # type: ignore[attr-defined] + self.days_of_week, + ).ravel() + ] + + if self.start_date is not None: + filter_start_date = max( + self.start_date.tz_localize(filter_start_date.tz), filter_start_date + ) + if self.end_date is not None: + filter_end_date = min( + self.end_date.tz_localize(filter_end_date.tz), filter_end_date + ) + holiday_dates = holiday_dates[ + (holiday_dates >= filter_start_date) & (holiday_dates <= filter_end_date) + ] + if return_name: + return Series(self.name, index=holiday_dates) + return holiday_dates + + def _reference_dates( + self, start_date: Timestamp, end_date: Timestamp + ) -> DatetimeIndex: + """ + Get reference dates for the holiday. + + Return reference dates for the holiday also returning the year + prior to the start_date and year following the end_date. This ensures + that any offsets to be applied will yield the holidays within + the passed in dates. + """ + if self.start_date is not None: + start_date = self.start_date.tz_localize(start_date.tz) + + if self.end_date is not None: + end_date = self.end_date.tz_localize(start_date.tz) + + year_offset = DateOffset(years=1) + reference_start_date = Timestamp( + datetime(start_date.year - 1, self.month, self.day) + ) + + reference_end_date = Timestamp( + datetime(end_date.year + 1, self.month, self.day) + ) + # Don't process unnecessary holidays + dates = date_range( + start=reference_start_date, + end=reference_end_date, + freq=year_offset, + tz=start_date.tz, + ) + + return dates + + def _apply_rule(self, dates: DatetimeIndex) -> DatetimeIndex: + """ + Apply the given offset/observance to a DatetimeIndex of dates. + + Parameters + ---------- + dates : DatetimeIndex + Dates to apply the given offset/observance rule + + Returns + ------- + Dates with rules applied + """ + if dates.empty: + return dates.copy() + + if self.observance is not None: + return dates.map(lambda d: self.observance(d)) + + if self.offset is not None: + if not isinstance(self.offset, list): + offsets = [self.offset] + else: + offsets = self.offset + for offset in offsets: + # if we are adding a non-vectorized value + # ignore the PerformanceWarnings: + with warnings.catch_warnings(): + warnings.simplefilter("ignore", PerformanceWarning) + dates += offset + return dates + + +holiday_calendars = {} + + +def register(cls) -> None: + try: + name = cls.name + except AttributeError: + name = cls.__name__ + holiday_calendars[name] = cls + + +def get_calendar(name: str): + """ + Return an instance of a calendar based on its name. + + Parameters + ---------- + name : str + Calendar name to return an instance of + """ + return holiday_calendars[name]() + + +class HolidayCalendarMetaClass(type): + def __new__(cls, clsname: str, bases, attrs): + calendar_class = super().__new__(cls, clsname, bases, attrs) + register(calendar_class) + return calendar_class + + +class AbstractHolidayCalendar(metaclass=HolidayCalendarMetaClass): + """ + Abstract interface to create holidays following certain rules. + """ + + rules: list[Holiday] = [] + start_date = Timestamp(datetime(1970, 1, 1)) + end_date = Timestamp(datetime(2200, 12, 31)) + _cache = None + + def __init__(self, name: str = "", rules=None) -> None: + """ + Initializes holiday object with a given set a rules. Normally + classes just have the rules defined within them. + + Parameters + ---------- + name : str + Name of the holiday calendar, defaults to class name + rules : array of Holiday objects + A set of rules used to create the holidays. + """ + super().__init__() + if not name: + name = type(self).__name__ + self.name = name + + if rules is not None: + self.rules = rules + + def rule_from_name(self, name: str): + for rule in self.rules: + if rule.name == name: + return rule + + return None + + def holidays(self, start=None, end=None, return_name: bool = False): + """ + Returns a curve with holidays between start_date and end_date + + Parameters + ---------- + start : starting date, datetime-like, optional + end : ending date, datetime-like, optional + return_name : bool, optional + If True, return a series that has dates and holiday names. + False will only return a DatetimeIndex of dates. + + Returns + ------- + DatetimeIndex of holidays + """ + if self.rules is None: + raise Exception( + f"Holiday Calendar {self.name} does not have any rules specified" + ) + + if start is None: + start = AbstractHolidayCalendar.start_date + + if end is None: + end = AbstractHolidayCalendar.end_date + + start = Timestamp(start) + end = Timestamp(end) + + # If we don't have a cache or the dates are outside the prior cache, we + # get them again + if self._cache is None or start < self._cache[0] or end > self._cache[1]: + pre_holidays = [ + rule.dates(start, end, return_name=True) for rule in self.rules + ] + if pre_holidays: + # error: Argument 1 to "concat" has incompatible type + # "List[Union[Series, DatetimeIndex]]"; expected + # "Union[Iterable[DataFrame], Mapping[, DataFrame]]" + holidays = concat(pre_holidays) # type: ignore[arg-type] + else: + # error: Incompatible types in assignment (expression has type + # "Series", variable has type "DataFrame") + holidays = Series( + index=DatetimeIndex([]), dtype=object + ) # type: ignore[assignment] + + self._cache = (start, end, holidays.sort_index()) + + holidays = self._cache[2] + holidays = holidays[start:end] + + if return_name: + return holidays + else: + return holidays.index + + @staticmethod + def merge_class(base, other): + """ + Merge holiday calendars together. The base calendar + will take precedence to other. The merge will be done + based on each holiday's name. + + Parameters + ---------- + base : AbstractHolidayCalendar + instance/subclass or array of Holiday objects + other : AbstractHolidayCalendar + instance/subclass or array of Holiday objects + """ + try: + other = other.rules + except AttributeError: + pass + + if not isinstance(other, list): + other = [other] + other_holidays = {holiday.name: holiday for holiday in other} + + try: + base = base.rules + except AttributeError: + pass + + if not isinstance(base, list): + base = [base] + base_holidays = {holiday.name: holiday for holiday in base} + + other_holidays.update(base_holidays) + return list(other_holidays.values()) + + def merge(self, other, inplace: bool = False): + """ + Merge holiday calendars together. The caller's class + rules take precedence. The merge will be done + based on each holiday's name. + + Parameters + ---------- + other : holiday calendar + inplace : bool (default=False) + If True set rule_table to holidays, else return array of Holidays + """ + holidays = self.merge_class(self, other) + if inplace: + self.rules = holidays + else: + return holidays + + +USMemorialDay = Holiday( + "Memorial Day", month=5, day=31, offset=DateOffset(weekday=MO(-1)) +) +USLaborDay = Holiday("Labor Day", month=9, day=1, offset=DateOffset(weekday=MO(1))) +USColumbusDay = Holiday( + "Columbus Day", month=10, day=1, offset=DateOffset(weekday=MO(2)) +) +USThanksgivingDay = Holiday( + "Thanksgiving Day", month=11, day=1, offset=DateOffset(weekday=TH(4)) +) +USMartinLutherKingJr = Holiday( + "Birthday of Martin Luther King, Jr.", + start_date=datetime(1986, 1, 1), + month=1, + day=1, + offset=DateOffset(weekday=MO(3)), +) +USPresidentsDay = Holiday( + "Washington's Birthday", month=2, day=1, offset=DateOffset(weekday=MO(3)) +) +GoodFriday = Holiday("Good Friday", month=1, day=1, offset=[Easter(), Day(-2)]) + +EasterMonday = Holiday("Easter Monday", month=1, day=1, offset=[Easter(), Day(1)]) + + +class USFederalHolidayCalendar(AbstractHolidayCalendar): + """ + US Federal Government Holiday Calendar based on rules specified by: + https://www.opm.gov/policy-data-oversight/pay-leave/federal-holidays/ + """ + + rules = [ + Holiday("New Year's Day", month=1, day=1, observance=nearest_workday), + USMartinLutherKingJr, + USPresidentsDay, + USMemorialDay, + Holiday( + "Juneteenth National Independence Day", + month=6, + day=19, + start_date="2021-06-18", + observance=nearest_workday, + ), + Holiday("Independence Day", month=7, day=4, observance=nearest_workday), + USLaborDay, + USColumbusDay, + Holiday("Veterans Day", month=11, day=11, observance=nearest_workday), + USThanksgivingDay, + Holiday("Christmas Day", month=12, day=25, observance=nearest_workday), + ] + + +def HolidayCalendarFactory(name: str, base, other, base_class=AbstractHolidayCalendar): + rules = AbstractHolidayCalendar.merge_class(base, other) + calendar_class = type(name, (base_class,), {"rules": rules, "name": name}) + return calendar_class + + +__all__ = [ + "after_nearest_workday", + "before_nearest_workday", + "FR", + "get_calendar", + "HolidayCalendarFactory", + "MO", + "nearest_workday", + "next_monday", + "next_monday_or_tuesday", + "next_workday", + "previous_friday", + "previous_workday", + "register", + "SA", + "SU", + "sunday_to_monday", + "TH", + "TU", + "WE", + "weekend_to_monday", +] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/offsets.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/offsets.py new file mode 100644 index 0000000000000000000000000000000000000000..169c9cc18a7fde6289a112ba5932cbb634eb3714 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/tseries/offsets.py @@ -0,0 +1,91 @@ +from __future__ import annotations + +from pandas._libs.tslibs.offsets import ( + FY5253, + BaseOffset, + BDay, + BMonthBegin, + BMonthEnd, + BQuarterBegin, + BQuarterEnd, + BusinessDay, + BusinessHour, + BusinessMonthBegin, + BusinessMonthEnd, + BYearBegin, + BYearEnd, + CBMonthBegin, + CBMonthEnd, + CDay, + CustomBusinessDay, + CustomBusinessHour, + CustomBusinessMonthBegin, + CustomBusinessMonthEnd, + DateOffset, + Day, + Easter, + FY5253Quarter, + Hour, + LastWeekOfMonth, + Micro, + Milli, + Minute, + MonthBegin, + MonthEnd, + Nano, + QuarterBegin, + QuarterEnd, + Second, + SemiMonthBegin, + SemiMonthEnd, + Tick, + Week, + WeekOfMonth, + YearBegin, + YearEnd, +) + +__all__ = [ + "Day", + "BaseOffset", + "BusinessDay", + "BusinessMonthBegin", + "BusinessMonthEnd", + "BDay", + "CustomBusinessDay", + "CustomBusinessMonthBegin", + "CustomBusinessMonthEnd", + "CDay", + "CBMonthEnd", + "CBMonthBegin", + "MonthBegin", + "BMonthBegin", + "MonthEnd", + "BMonthEnd", + "SemiMonthEnd", + "SemiMonthBegin", + "BusinessHour", + "CustomBusinessHour", + "YearBegin", + "BYearBegin", + "YearEnd", + "BYearEnd", + "QuarterBegin", + "BQuarterBegin", + "QuarterEnd", + "BQuarterEnd", + "LastWeekOfMonth", + "FY5253Quarter", + "FY5253", + "Week", + "WeekOfMonth", + "Easter", + "Tick", + "Hour", + "Minute", + "Second", + "Milli", + "Micro", + "Nano", + "DateOffset", +] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..82b3aa56c653cd1241872c67e9d9016df04a6c5a --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/__init__.py @@ -0,0 +1,29 @@ +def __getattr__(key: str): + # These imports need to be lazy to avoid circular import errors + if key == "hash_array": + from pandas.core.util.hashing import hash_array + + return hash_array + if key == "hash_pandas_object": + from pandas.core.util.hashing import hash_pandas_object + + return hash_pandas_object + if key == "Appender": + from pandas.util._decorators import Appender + + return Appender + if key == "Substitution": + from pandas.util._decorators import Substitution + + return Substitution + + if key == "cache_readonly": + from pandas.util._decorators import cache_readonly + + return cache_readonly + + raise AttributeError(f"module 'pandas.util' has no attribute '{key}'") + + +def capitalize_first_letter(s): + return s[:1].upper() + s[1:] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_decorators.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_decorators.py new file mode 100644 index 0000000000000000000000000000000000000000..4e8189e72c427d75da0367532edfe04d0a7581e8 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_decorators.py @@ -0,0 +1,508 @@ +from __future__ import annotations + +from functools import wraps +import inspect +from textwrap import dedent +from typing import ( + TYPE_CHECKING, + Any, + Callable, + cast, +) +import warnings + +from pandas._libs.properties import cache_readonly +from pandas._typing import ( + F, + T, +) +from pandas.util._exceptions import find_stack_level + +if TYPE_CHECKING: + from collections.abc import Mapping + + +def deprecate( + name: str, + alternative: Callable[..., Any], + version: str, + alt_name: str | None = None, + klass: type[Warning] | None = None, + stacklevel: int = 2, + msg: str | None = None, +) -> Callable[[F], F]: + """ + Return a new function that emits a deprecation warning on use. + + To use this method for a deprecated function, another function + `alternative` with the same signature must exist. The deprecated + function will emit a deprecation warning, and in the docstring + it will contain the deprecation directive with the provided version + so it can be detected for future removal. + + Parameters + ---------- + name : str + Name of function to deprecate. + alternative : func + Function to use instead. + version : str + Version of pandas in which the method has been deprecated. + alt_name : str, optional + Name to use in preference of alternative.__name__. + klass : Warning, default FutureWarning + stacklevel : int, default 2 + msg : str + The message to display in the warning. + Default is '{name} is deprecated. Use {alt_name} instead.' + """ + alt_name = alt_name or alternative.__name__ + klass = klass or FutureWarning + warning_msg = msg or f"{name} is deprecated, use {alt_name} instead." + + @wraps(alternative) + def wrapper(*args, **kwargs) -> Callable[..., Any]: + warnings.warn(warning_msg, klass, stacklevel=stacklevel) + return alternative(*args, **kwargs) + + # adding deprecated directive to the docstring + msg = msg or f"Use `{alt_name}` instead." + doc_error_msg = ( + "deprecate needs a correctly formatted docstring in " + "the target function (should have a one liner short " + "summary, and opening quotes should be in their own " + f"line). Found:\n{alternative.__doc__}" + ) + + # when python is running in optimized mode (i.e. `-OO`), docstrings are + # removed, so we check that a docstring with correct formatting is used + # but we allow empty docstrings + if alternative.__doc__: + if alternative.__doc__.count("\n") < 3: + raise AssertionError(doc_error_msg) + empty1, summary, empty2, doc_string = alternative.__doc__.split("\n", 3) + if empty1 or empty2 and not summary: + raise AssertionError(doc_error_msg) + wrapper.__doc__ = dedent( + f""" + {summary.strip()} + + .. deprecated:: {version} + {msg} + + {dedent(doc_string)}""" + ) + # error: Incompatible return value type (got "Callable[[VarArg(Any), KwArg(Any)], + # Callable[...,Any]]", expected "Callable[[F], F]") + return wrapper # type: ignore[return-value] + + +def deprecate_kwarg( + old_arg_name: str, + new_arg_name: str | None, + mapping: Mapping[Any, Any] | Callable[[Any], Any] | None = None, + stacklevel: int = 2, +) -> Callable[[F], F]: + """ + Decorator to deprecate a keyword argument of a function. + + Parameters + ---------- + old_arg_name : str + Name of argument in function to deprecate + new_arg_name : str or None + Name of preferred argument in function. Use None to raise warning that + ``old_arg_name`` keyword is deprecated. + mapping : dict or callable + If mapping is present, use it to translate old arguments to + new arguments. A callable must do its own value checking; + values not found in a dict will be forwarded unchanged. + + Examples + -------- + The following deprecates 'cols', using 'columns' instead + + >>> @deprecate_kwarg(old_arg_name='cols', new_arg_name='columns') + ... def f(columns=''): + ... print(columns) + ... + >>> f(columns='should work ok') + should work ok + + >>> f(cols='should raise warning') # doctest: +SKIP + FutureWarning: cols is deprecated, use columns instead + warnings.warn(msg, FutureWarning) + should raise warning + + >>> f(cols='should error', columns="can\'t pass do both") # doctest: +SKIP + TypeError: Can only specify 'cols' or 'columns', not both + + >>> @deprecate_kwarg('old', 'new', {'yes': True, 'no': False}) + ... def f(new=False): + ... print('yes!' if new else 'no!') + ... + >>> f(old='yes') # doctest: +SKIP + FutureWarning: old='yes' is deprecated, use new=True instead + warnings.warn(msg, FutureWarning) + yes! + + To raise a warning that a keyword will be removed entirely in the future + + >>> @deprecate_kwarg(old_arg_name='cols', new_arg_name=None) + ... def f(cols='', another_param=''): + ... print(cols) + ... + >>> f(cols='should raise warning') # doctest: +SKIP + FutureWarning: the 'cols' keyword is deprecated and will be removed in a + future version please takes steps to stop use of 'cols' + should raise warning + >>> f(another_param='should not raise warning') # doctest: +SKIP + should not raise warning + + >>> f(cols='should raise warning', another_param='') # doctest: +SKIP + FutureWarning: the 'cols' keyword is deprecated and will be removed in a + future version please takes steps to stop use of 'cols' + should raise warning + """ + if mapping is not None and not hasattr(mapping, "get") and not callable(mapping): + raise TypeError( + "mapping from old to new argument values must be dict or callable!" + ) + + def _deprecate_kwarg(func: F) -> F: + @wraps(func) + def wrapper(*args, **kwargs) -> Callable[..., Any]: + old_arg_value = kwargs.pop(old_arg_name, None) + + if old_arg_value is not None: + if new_arg_name is None: + msg = ( + f"the {repr(old_arg_name)} keyword is deprecated and " + "will be removed in a future version. Please take " + f"steps to stop the use of {repr(old_arg_name)}" + ) + warnings.warn(msg, FutureWarning, stacklevel=stacklevel) + kwargs[old_arg_name] = old_arg_value + return func(*args, **kwargs) + + elif mapping is not None: + if callable(mapping): + new_arg_value = mapping(old_arg_value) + else: + new_arg_value = mapping.get(old_arg_value, old_arg_value) + msg = ( + f"the {old_arg_name}={repr(old_arg_value)} keyword is " + "deprecated, use " + f"{new_arg_name}={repr(new_arg_value)} instead." + ) + else: + new_arg_value = old_arg_value + msg = ( + f"the {repr(old_arg_name)} keyword is deprecated, " + f"use {repr(new_arg_name)} instead." + ) + + warnings.warn(msg, FutureWarning, stacklevel=stacklevel) + if kwargs.get(new_arg_name) is not None: + msg = ( + f"Can only specify {repr(old_arg_name)} " + f"or {repr(new_arg_name)}, not both." + ) + raise TypeError(msg) + kwargs[new_arg_name] = new_arg_value + return func(*args, **kwargs) + + return cast(F, wrapper) + + return _deprecate_kwarg + + +def _format_argument_list(allow_args: list[str]) -> str: + """ + Convert the allow_args argument (either string or integer) of + `deprecate_nonkeyword_arguments` function to a string describing + it to be inserted into warning message. + + Parameters + ---------- + allowed_args : list, tuple or int + The `allowed_args` argument for `deprecate_nonkeyword_arguments`, + but None value is not allowed. + + Returns + ------- + str + The substring describing the argument list in best way to be + inserted to the warning message. + + Examples + -------- + `format_argument_list([])` -> '' + `format_argument_list(['a'])` -> "except for the arguments 'a'" + `format_argument_list(['a', 'b'])` -> "except for the arguments 'a' and 'b'" + `format_argument_list(['a', 'b', 'c'])` -> + "except for the arguments 'a', 'b' and 'c'" + """ + if "self" in allow_args: + allow_args.remove("self") + if not allow_args: + return "" + elif len(allow_args) == 1: + return f" except for the argument '{allow_args[0]}'" + else: + last = allow_args[-1] + args = ", ".join(["'" + x + "'" for x in allow_args[:-1]]) + return f" except for the arguments {args} and '{last}'" + + +def future_version_msg(version: str | None) -> str: + """Specify which version of pandas the deprecation will take place in.""" + if version is None: + return "In a future version of pandas" + else: + return f"Starting with pandas version {version}" + + +def deprecate_nonkeyword_arguments( + version: str | None, + allowed_args: list[str] | None = None, + name: str | None = None, +) -> Callable[[F], F]: + """ + Decorator to deprecate a use of non-keyword arguments of a function. + + Parameters + ---------- + version : str, optional + The version in which positional arguments will become + keyword-only. If None, then the warning message won't + specify any particular version. + + allowed_args : list, optional + In case of list, it must be the list of names of some + first arguments of the decorated functions that are + OK to be given as positional arguments. In case of None value, + defaults to list of all arguments not having the + default value. + + name : str, optional + The specific name of the function to show in the warning + message. If None, then the Qualified name of the function + is used. + """ + + def decorate(func): + old_sig = inspect.signature(func) + + if allowed_args is not None: + allow_args = allowed_args + else: + allow_args = [ + p.name + for p in old_sig.parameters.values() + if p.kind in (p.POSITIONAL_ONLY, p.POSITIONAL_OR_KEYWORD) + and p.default is p.empty + ] + + new_params = [ + p.replace(kind=p.KEYWORD_ONLY) + if ( + p.kind in (p.POSITIONAL_ONLY, p.POSITIONAL_OR_KEYWORD) + and p.name not in allow_args + ) + else p + for p in old_sig.parameters.values() + ] + new_params.sort(key=lambda p: p.kind) + new_sig = old_sig.replace(parameters=new_params) + + num_allow_args = len(allow_args) + msg = ( + f"{future_version_msg(version)} all arguments of " + f"{name or func.__qualname__}{{arguments}} will be keyword-only." + ) + + @wraps(func) + def wrapper(*args, **kwargs): + if len(args) > num_allow_args: + warnings.warn( + msg.format(arguments=_format_argument_list(allow_args)), + FutureWarning, + stacklevel=find_stack_level(), + ) + return func(*args, **kwargs) + + # error: "Callable[[VarArg(Any), KwArg(Any)], Any]" has no + # attribute "__signature__" + wrapper.__signature__ = new_sig # type: ignore[attr-defined] + return wrapper + + return decorate + + +def doc(*docstrings: None | str | Callable, **params) -> Callable[[F], F]: + """ + A decorator to take docstring templates, concatenate them and perform string + substitution on them. + + This decorator will add a variable "_docstring_components" to the wrapped + callable to keep track the original docstring template for potential usage. + If it should be consider as a template, it will be saved as a string. + Otherwise, it will be saved as callable, and later user __doc__ and dedent + to get docstring. + + Parameters + ---------- + *docstrings : None, str, or callable + The string / docstring / docstring template to be appended in order + after default docstring under callable. + **params + The string which would be used to format docstring template. + """ + + def decorator(decorated: F) -> F: + # collecting docstring and docstring templates + docstring_components: list[str | Callable] = [] + if decorated.__doc__: + docstring_components.append(dedent(decorated.__doc__)) + + for docstring in docstrings: + if docstring is None: + continue + if hasattr(docstring, "_docstring_components"): + docstring_components.extend( + docstring._docstring_components # pyright: ignore[reportGeneralTypeIssues] + ) + elif isinstance(docstring, str) or docstring.__doc__: + docstring_components.append(docstring) + + params_applied = [ + component.format(**params) + if isinstance(component, str) and len(params) > 0 + else component + for component in docstring_components + ] + + decorated.__doc__ = "".join( + [ + component + if isinstance(component, str) + else dedent(component.__doc__ or "") + for component in params_applied + ] + ) + + # error: "F" has no attribute "_docstring_components" + decorated._docstring_components = ( # type: ignore[attr-defined] + docstring_components + ) + return decorated + + return decorator + + +# Substitution and Appender are derived from matplotlib.docstring (1.1.0) +# module https://matplotlib.org/users/license.html + + +class Substitution: + """ + A decorator to take a function's docstring and perform string + substitution on it. + + This decorator should be robust even if func.__doc__ is None + (for example, if -OO was passed to the interpreter) + + Usage: construct a docstring.Substitution with a sequence or + dictionary suitable for performing substitution; then + decorate a suitable function with the constructed object. e.g. + + sub_author_name = Substitution(author='Jason') + + @sub_author_name + def some_function(x): + "%(author)s wrote this function" + + # note that some_function.__doc__ is now "Jason wrote this function" + + One can also use positional arguments. + + sub_first_last_names = Substitution('Edgar Allen', 'Poe') + + @sub_first_last_names + def some_function(x): + "%s %s wrote the Raven" + """ + + def __init__(self, *args, **kwargs) -> None: + if args and kwargs: + raise AssertionError("Only positional or keyword args are allowed") + + self.params = args or kwargs + + def __call__(self, func: F) -> F: + func.__doc__ = func.__doc__ and func.__doc__ % self.params + return func + + def update(self, *args, **kwargs) -> None: + """ + Update self.params with supplied args. + """ + if isinstance(self.params, dict): + self.params.update(*args, **kwargs) + + +class Appender: + """ + A function decorator that will append an addendum to the docstring + of the target function. + + This decorator should be robust even if func.__doc__ is None + (for example, if -OO was passed to the interpreter). + + Usage: construct a docstring.Appender with a string to be joined to + the original docstring. An optional 'join' parameter may be supplied + which will be used to join the docstring and addendum. e.g. + + add_copyright = Appender("Copyright (c) 2009", join='\n') + + @add_copyright + def my_dog(has='fleas'): + "This docstring will have a copyright below" + pass + """ + + addendum: str | None + + def __init__(self, addendum: str | None, join: str = "", indents: int = 0) -> None: + if indents > 0: + self.addendum = indent(addendum, indents=indents) + else: + self.addendum = addendum + self.join = join + + def __call__(self, func: T) -> T: + func.__doc__ = func.__doc__ if func.__doc__ else "" + self.addendum = self.addendum if self.addendum else "" + docitems = [func.__doc__, self.addendum] + func.__doc__ = dedent(self.join.join(docitems)) + return func + + +def indent(text: str | None, indents: int = 1) -> str: + if not text or not isinstance(text, str): + return "" + jointext = "".join(["\n"] + [" "] * indents) + return jointext.join(text.split("\n")) + + +__all__ = [ + "Appender", + "cache_readonly", + "deprecate", + "deprecate_kwarg", + "deprecate_nonkeyword_arguments", + "doc", + "future_version_msg", + "Substitution", +] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_doctools.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_doctools.py new file mode 100644 index 0000000000000000000000000000000000000000..12619abf4baaf336dfd3d5ae78a9bc2133f310c0 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_doctools.py @@ -0,0 +1,202 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np + +import pandas as pd + +if TYPE_CHECKING: + from collections.abc import Iterable + + +class TablePlotter: + """ + Layout some DataFrames in vertical/horizontal layout for explanation. + Used in merging.rst + """ + + def __init__( + self, + cell_width: float = 0.37, + cell_height: float = 0.25, + font_size: float = 7.5, + ) -> None: + self.cell_width = cell_width + self.cell_height = cell_height + self.font_size = font_size + + def _shape(self, df: pd.DataFrame) -> tuple[int, int]: + """ + Calculate table shape considering index levels. + """ + row, col = df.shape + return row + df.columns.nlevels, col + df.index.nlevels + + def _get_cells(self, left, right, vertical) -> tuple[int, int]: + """ + Calculate appropriate figure size based on left and right data. + """ + if vertical: + # calculate required number of cells + vcells = max(sum(self._shape(df)[0] for df in left), self._shape(right)[0]) + hcells = max(self._shape(df)[1] for df in left) + self._shape(right)[1] + else: + vcells = max([self._shape(df)[0] for df in left] + [self._shape(right)[0]]) + hcells = sum([self._shape(df)[1] for df in left] + [self._shape(right)[1]]) + return hcells, vcells + + def plot(self, left, right, labels: Iterable[str] = (), vertical: bool = True): + """ + Plot left / right DataFrames in specified layout. + + Parameters + ---------- + left : list of DataFrames before operation is applied + right : DataFrame of operation result + labels : list of str to be drawn as titles of left DataFrames + vertical : bool, default True + If True, use vertical layout. If False, use horizontal layout. + """ + from matplotlib import gridspec + import matplotlib.pyplot as plt + + if not isinstance(left, list): + left = [left] + left = [self._conv(df) for df in left] + right = self._conv(right) + + hcells, vcells = self._get_cells(left, right, vertical) + + if vertical: + figsize = self.cell_width * hcells, self.cell_height * vcells + else: + # include margin for titles + figsize = self.cell_width * hcells, self.cell_height * vcells + fig = plt.figure(figsize=figsize) + + if vertical: + gs = gridspec.GridSpec(len(left), hcells) + # left + max_left_cols = max(self._shape(df)[1] for df in left) + max_left_rows = max(self._shape(df)[0] for df in left) + for i, (_left, _label) in enumerate(zip(left, labels)): + ax = fig.add_subplot(gs[i, 0:max_left_cols]) + self._make_table(ax, _left, title=_label, height=1.0 / max_left_rows) + # right + ax = plt.subplot(gs[:, max_left_cols:]) + self._make_table(ax, right, title="Result", height=1.05 / vcells) + fig.subplots_adjust(top=0.9, bottom=0.05, left=0.05, right=0.95) + else: + max_rows = max(self._shape(df)[0] for df in left + [right]) + height = 1.0 / np.max(max_rows) + gs = gridspec.GridSpec(1, hcells) + # left + i = 0 + for df, _label in zip(left, labels): + sp = self._shape(df) + ax = fig.add_subplot(gs[0, i : i + sp[1]]) + self._make_table(ax, df, title=_label, height=height) + i += sp[1] + # right + ax = plt.subplot(gs[0, i:]) + self._make_table(ax, right, title="Result", height=height) + fig.subplots_adjust(top=0.85, bottom=0.05, left=0.05, right=0.95) + + return fig + + def _conv(self, data): + """ + Convert each input to appropriate for table outplot. + """ + if isinstance(data, pd.Series): + if data.name is None: + data = data.to_frame(name="") + else: + data = data.to_frame() + data = data.fillna("NaN") + return data + + def _insert_index(self, data): + # insert is destructive + data = data.copy() + idx_nlevels = data.index.nlevels + if idx_nlevels == 1: + data.insert(0, "Index", data.index) + else: + for i in range(idx_nlevels): + data.insert(i, f"Index{i}", data.index._get_level_values(i)) + + col_nlevels = data.columns.nlevels + if col_nlevels > 1: + col = data.columns._get_level_values(0) + values = [ + data.columns._get_level_values(i)._values for i in range(1, col_nlevels) + ] + col_df = pd.DataFrame(values) + data.columns = col_df.columns + data = pd.concat([col_df, data]) + data.columns = col + return data + + def _make_table(self, ax, df, title: str, height: float | None = None) -> None: + if df is None: + ax.set_visible(False) + return + + from pandas import plotting + + idx_nlevels = df.index.nlevels + col_nlevels = df.columns.nlevels + # must be convert here to get index levels for colorization + df = self._insert_index(df) + tb = plotting.table(ax, df, loc=9) + tb.set_fontsize(self.font_size) + + if height is None: + height = 1.0 / (len(df) + 1) + + props = tb.properties() + for (r, c), cell in props["celld"].items(): + if c == -1: + cell.set_visible(False) + elif r < col_nlevels and c < idx_nlevels: + cell.set_visible(False) + elif r < col_nlevels or c < idx_nlevels: + cell.set_facecolor("#AAAAAA") + cell.set_height(height) + + ax.set_title(title, size=self.font_size) + ax.axis("off") + + +def main() -> None: + import matplotlib.pyplot as plt + + p = TablePlotter() + + df1 = pd.DataFrame({"A": [10, 11, 12], "B": [20, 21, 22], "C": [30, 31, 32]}) + df2 = pd.DataFrame({"A": [10, 12], "C": [30, 32]}) + + p.plot([df1, df2], pd.concat([df1, df2]), labels=["df1", "df2"], vertical=True) + plt.show() + + df3 = pd.DataFrame({"X": [10, 12], "Z": [30, 32]}) + + p.plot( + [df1, df3], pd.concat([df1, df3], axis=1), labels=["df1", "df2"], vertical=False + ) + plt.show() + + idx = pd.MultiIndex.from_tuples( + [(1, "A"), (1, "B"), (1, "C"), (2, "A"), (2, "B"), (2, "C")] + ) + column = pd.MultiIndex.from_tuples([(1, "A"), (1, "B")]) + df3 = pd.DataFrame({"v1": [1, 2, 3, 4, 5, 6], "v2": [5, 6, 7, 8, 9, 10]}, index=idx) + df3.columns = column + p.plot(df3, df3, labels=["df3"]) + plt.show() + + +if __name__ == "__main__": + main() diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_exceptions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_exceptions.py new file mode 100644 index 0000000000000000000000000000000000000000..5f50838d373154868ff7414775763a1c66853c65 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_exceptions.py @@ -0,0 +1,103 @@ +from __future__ import annotations + +import contextlib +import inspect +import os +import re +from typing import TYPE_CHECKING +import warnings + +if TYPE_CHECKING: + from collections.abc import Generator + from types import FrameType + + +@contextlib.contextmanager +def rewrite_exception(old_name: str, new_name: str) -> Generator[None, None, None]: + """ + Rewrite the message of an exception. + """ + try: + yield + except Exception as err: + if not err.args: + raise + msg = str(err.args[0]) + msg = msg.replace(old_name, new_name) + args: tuple[str, ...] = (msg,) + if len(err.args) > 1: + args = args + err.args[1:] + err.args = args + raise + + +def find_stack_level() -> int: + """ + Find the first place in the stack that is not inside pandas + (tests notwithstanding). + """ + + import pandas as pd + + pkg_dir = os.path.dirname(pd.__file__) + test_dir = os.path.join(pkg_dir, "tests") + + # https://stackoverflow.com/questions/17407119/python-inspect-stack-is-slow + frame: FrameType | None = inspect.currentframe() + try: + n = 0 + while frame: + filename = inspect.getfile(frame) + if filename.startswith(pkg_dir) and not filename.startswith(test_dir): + frame = frame.f_back + n += 1 + else: + break + finally: + # See note in + # https://docs.python.org/3/library/inspect.html#inspect.Traceback + del frame + return n + + +@contextlib.contextmanager +def rewrite_warning( + target_message: str, + target_category: type[Warning], + new_message: str, + new_category: type[Warning] | None = None, +) -> Generator[None, None, None]: + """ + Rewrite the message of a warning. + + Parameters + ---------- + target_message : str + Warning message to match. + target_category : Warning + Warning type to match. + new_message : str + New warning message to emit. + new_category : Warning or None, default None + New warning type to emit. When None, will be the same as target_category. + """ + if new_category is None: + new_category = target_category + with warnings.catch_warnings(record=True) as record: + yield + if len(record) > 0: + match = re.compile(target_message) + for warning in record: + if warning.category is target_category and re.search( + match, str(warning.message) + ): + category = new_category + message: Warning | str = new_message + else: + category, message = warning.category, warning.message + warnings.warn_explicit( + message=message, + category=category, + filename=warning.filename, + lineno=warning.lineno, + ) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_print_versions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_print_versions.py new file mode 100644 index 0000000000000000000000000000000000000000..2d8df330f1aaedcc3b0504d366007014a6750356 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_print_versions.py @@ -0,0 +1,157 @@ +from __future__ import annotations + +import json +import locale +import os +import platform +import struct +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from pandas._typing import JSONSerializable + +from pandas.compat._optional import ( + VERSIONS, + get_version, + import_optional_dependency, +) + + +def _get_commit_hash() -> str | None: + """ + Use vendored versioneer code to get git hash, which handles + git worktree correctly. + """ + try: + from pandas._version_meson import ( # pyright: ignore [reportMissingImports] + __git_version__, + ) + + return __git_version__ + except ImportError: + from pandas._version import get_versions + + versions = get_versions() + return versions["full-revisionid"] + + +def _get_sys_info() -> dict[str, JSONSerializable]: + """ + Returns system information as a JSON serializable dictionary. + """ + uname_result = platform.uname() + language_code, encoding = locale.getlocale() + return { + "commit": _get_commit_hash(), + "python": platform.python_version(), + "python-bits": struct.calcsize("P") * 8, + "OS": uname_result.system, + "OS-release": uname_result.release, + "Version": uname_result.version, + "machine": uname_result.machine, + "processor": uname_result.processor, + "byteorder": sys.byteorder, + "LC_ALL": os.environ.get("LC_ALL"), + "LANG": os.environ.get("LANG"), + "LOCALE": {"language-code": language_code, "encoding": encoding}, + } + + +def _get_dependency_info() -> dict[str, JSONSerializable]: + """ + Returns dependency information as a JSON serializable dictionary. + """ + deps = [ + "pandas", + # required + "numpy", + "pytz", + "dateutil", + # install / build, + "pip", + "Cython", + # docs + "sphinx", + # Other, not imported. + "IPython", + ] + # Optional dependencies + deps.extend(list(VERSIONS)) + + result: dict[str, JSONSerializable] = {} + for modname in deps: + try: + mod = import_optional_dependency(modname, errors="ignore") + except Exception: + # Dependency conflicts may cause a non ImportError + result[modname] = "N/A" + else: + result[modname] = get_version(mod) if mod else None + return result + + +def show_versions(as_json: str | bool = False) -> None: + """ + Provide useful information, important for bug reports. + + It comprises info about hosting operation system, pandas version, + and versions of other installed relative packages. + + Parameters + ---------- + as_json : str or bool, default False + * If False, outputs info in a human readable form to the console. + * If str, it will be considered as a path to a file. + Info will be written to that file in JSON format. + * If True, outputs info in JSON format to the console. + + Examples + -------- + >>> pd.show_versions() # doctest: +SKIP + Your output may look something like this: + INSTALLED VERSIONS + ------------------ + commit : 37ea63d540fd27274cad6585082c91b1283f963d + python : 3.10.6.final.0 + python-bits : 64 + OS : Linux + OS-release : 5.10.102.1-microsoft-standard-WSL2 + Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022 + machine : x86_64 + processor : x86_64 + byteorder : little + LC_ALL : None + LANG : en_GB.UTF-8 + LOCALE : en_GB.UTF-8 + pandas : 2.0.1 + numpy : 1.24.3 + ... + """ + sys_info = _get_sys_info() + deps = _get_dependency_info() + + if as_json: + j = {"system": sys_info, "dependencies": deps} + + if as_json is True: + sys.stdout.writelines(json.dumps(j, indent=2)) + else: + assert isinstance(as_json, str) # needed for mypy + with open(as_json, "w", encoding="utf-8") as f: + json.dump(j, f, indent=2) + + else: + assert isinstance(sys_info["LOCALE"], dict) # needed for mypy + language_code = sys_info["LOCALE"]["language-code"] + encoding = sys_info["LOCALE"]["encoding"] + sys_info["LOCALE"] = f"{language_code}.{encoding}" + + maxlen = max(len(x) for x in deps) + print("\nINSTALLED VERSIONS") + print("------------------") + for k, v in sys_info.items(): + print(f"{k:<{maxlen}}: {v}") + print("") + for k, v in deps.items(): + print(f"{k:<{maxlen}}: {v}") diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_test_decorators.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_test_decorators.py new file mode 100644 index 0000000000000000000000000000000000000000..2c1912bce856dd2694447d820ea2c5124be9c1a0 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_test_decorators.py @@ -0,0 +1,173 @@ +""" +This module provides decorator functions which can be applied to test objects +in order to skip those objects when certain conditions occur. A sample use case +is to detect if the platform is missing ``matplotlib``. If so, any test objects +which require ``matplotlib`` and decorated with ``@td.skip_if_no("matplotlib")`` +will be skipped by ``pytest`` during the execution of the test suite. + +To illustrate, after importing this module: + +import pandas.util._test_decorators as td + +The decorators can be applied to classes: + +@td.skip_if_no("package") +class Foo: + ... + +Or individual functions: + +@td.skip_if_no("package") +def test_foo(): + ... + +For more information, refer to the ``pytest`` documentation on ``skipif``. +""" +from __future__ import annotations + +import locale +from typing import ( + TYPE_CHECKING, + Callable, +) + +import pytest + +from pandas._config import get_option + +if TYPE_CHECKING: + from pandas._typing import F + +from pandas._config.config import _get_option + +from pandas.compat import ( + IS64, + is_platform_windows, +) +from pandas.compat._optional import import_optional_dependency + + +def skip_if_installed(package: str) -> pytest.MarkDecorator: + """ + Skip a test if a package is installed. + + Parameters + ---------- + package : str + The name of the package. + + Returns + ------- + pytest.MarkDecorator + a pytest.mark.skipif to use as either a test decorator or a + parametrization mark. + """ + return pytest.mark.skipif( + bool(import_optional_dependency(package, errors="ignore")), + reason=f"Skipping because {package} is installed.", + ) + + +def skip_if_no(package: str, min_version: str | None = None) -> pytest.MarkDecorator: + """ + Generic function to help skip tests when required packages are not + present on the testing system. + + This function returns a pytest mark with a skip condition that will be + evaluated during test collection. An attempt will be made to import the + specified ``package`` and optionally ensure it meets the ``min_version`` + + The mark can be used as either a decorator for a test class or to be + applied to parameters in pytest.mark.parametrize calls or parametrized + fixtures. Use pytest.importorskip if an imported moduled is later needed + or for test functions. + + If the import and version check are unsuccessful, then the test function + (or test case when used in conjunction with parametrization) will be + skipped. + + Parameters + ---------- + package: str + The name of the required package. + min_version: str or None, default None + Optional minimum version of the package. + + Returns + ------- + pytest.MarkDecorator + a pytest.mark.skipif to use as either a test decorator or a + parametrization mark. + """ + msg = f"Could not import '{package}'" + if min_version: + msg += f" satisfying a min_version of {min_version}" + return pytest.mark.skipif( + not bool( + import_optional_dependency( + package, errors="ignore", min_version=min_version + ) + ), + reason=msg, + ) + + +skip_if_32bit = pytest.mark.skipif(not IS64, reason="skipping for 32 bit") +skip_if_windows = pytest.mark.skipif(is_platform_windows(), reason="Running on Windows") +skip_if_not_us_locale = pytest.mark.skipif( + locale.getlocale()[0] != "en_US", + reason=f"Set local {locale.getlocale()[0]} is not en_US", +) + + +def parametrize_fixture_doc(*args) -> Callable[[F], F]: + """ + Intended for use as a decorator for parametrized fixture, + this function will wrap the decorated function with a pytest + ``parametrize_fixture_doc`` mark. That mark will format + initial fixture docstring by replacing placeholders {0}, {1} etc + with parameters passed as arguments. + + Parameters + ---------- + args: iterable + Positional arguments for docstring. + + Returns + ------- + function + The decorated function wrapped within a pytest + ``parametrize_fixture_doc`` mark + """ + + def documented_fixture(fixture): + fixture.__doc__ = fixture.__doc__.format(*args) + return fixture + + return documented_fixture + + +def mark_array_manager_not_yet_implemented(request) -> None: + mark = pytest.mark.xfail(reason="Not yet implemented for ArrayManager") + request.applymarker(mark) + + +skip_array_manager_not_yet_implemented = pytest.mark.xfail( + _get_option("mode.data_manager", silent=True) == "array", + reason="Not yet implemented for ArrayManager", +) + +skip_array_manager_invalid_test = pytest.mark.skipif( + _get_option("mode.data_manager", silent=True) == "array", + reason="Test that relies on BlockManager internals or specific behaviour", +) + +skip_copy_on_write_not_yet_implemented = pytest.mark.xfail( + get_option("mode.copy_on_write") is True, + reason="Not yet implemented/adapted for Copy-on-Write mode", +) + +skip_copy_on_write_invalid_test = pytest.mark.skipif( + get_option("mode.copy_on_write") is True, + reason="Test not valid for Copy-on-Write mode", +) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_tester.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_tester.py new file mode 100644 index 0000000000000000000000000000000000000000..7cfddef7ddff87275ebf31eb7ec10e65d26f8668 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_tester.py @@ -0,0 +1,53 @@ +""" +Entrypoint for testing from the top-level namespace. +""" +from __future__ import annotations + +import os +import sys + +from pandas.compat._optional import import_optional_dependency + +PKG = os.path.dirname(os.path.dirname(__file__)) + + +def test(extra_args: list[str] | None = None, run_doctests: bool = False) -> None: + """ + Run the pandas test suite using pytest. + + By default, runs with the marks -m "not slow and not network and not db" + + Parameters + ---------- + extra_args : list[str], default None + Extra marks to run the tests. + run_doctests : bool, default False + Whether to only run the Python and Cython doctests. If you would like to run + both doctests/regular tests, just append "--doctest-modules"/"--doctest-cython" + to extra_args. + + Examples + -------- + >>> pd.test() # doctest: +SKIP + running: pytest... + """ + pytest = import_optional_dependency("pytest") + import_optional_dependency("hypothesis") + cmd = ["-m not slow and not network and not db"] + if extra_args: + if not isinstance(extra_args, list): + extra_args = [extra_args] + cmd = extra_args + if run_doctests: + cmd = [ + "--doctest-modules", + "--doctest-cython", + f"--ignore={os.path.join(PKG, 'tests')}", + ] + cmd += [PKG] + joined = " ".join(cmd) + print(f"running: pytest {joined}") + sys.exit(pytest.main(cmd)) + + +__all__ = ["test"] diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_validators.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_validators.py new file mode 100644 index 0000000000000000000000000000000000000000..cb0b4d549f49ea972d50c97986c60be64c021c3c --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/_validators.py @@ -0,0 +1,456 @@ +""" +Module that contains many useful utilities +for validating data or function arguments +""" +from __future__ import annotations + +from collections.abc import ( + Iterable, + Sequence, +) +from typing import ( + TypeVar, + overload, +) + +import numpy as np + +from pandas._libs import lib + +from pandas.core.dtypes.common import ( + is_bool, + is_integer, +) + +BoolishT = TypeVar("BoolishT", bool, int) +BoolishNoneT = TypeVar("BoolishNoneT", bool, int, None) + + +def _check_arg_length(fname, args, max_fname_arg_count, compat_args) -> None: + """ + Checks whether 'args' has length of at most 'compat_args'. Raises + a TypeError if that is not the case, similar to in Python when a + function is called with too many arguments. + """ + if max_fname_arg_count < 0: + raise ValueError("'max_fname_arg_count' must be non-negative") + + if len(args) > len(compat_args): + max_arg_count = len(compat_args) + max_fname_arg_count + actual_arg_count = len(args) + max_fname_arg_count + argument = "argument" if max_arg_count == 1 else "arguments" + + raise TypeError( + f"{fname}() takes at most {max_arg_count} {argument} " + f"({actual_arg_count} given)" + ) + + +def _check_for_default_values(fname, arg_val_dict, compat_args) -> None: + """ + Check that the keys in `arg_val_dict` are mapped to their + default values as specified in `compat_args`. + + Note that this function is to be called only when it has been + checked that arg_val_dict.keys() is a subset of compat_args + """ + for key in arg_val_dict: + # try checking equality directly with '=' operator, + # as comparison may have been overridden for the left + # hand object + try: + v1 = arg_val_dict[key] + v2 = compat_args[key] + + # check for None-ness otherwise we could end up + # comparing a numpy array vs None + if (v1 is not None and v2 is None) or (v1 is None and v2 is not None): + match = False + else: + match = v1 == v2 + + if not is_bool(match): + raise ValueError("'match' is not a boolean") + + # could not compare them directly, so try comparison + # using the 'is' operator + except ValueError: + match = arg_val_dict[key] is compat_args[key] + + if not match: + raise ValueError( + f"the '{key}' parameter is not supported in " + f"the pandas implementation of {fname}()" + ) + + +def validate_args(fname, args, max_fname_arg_count, compat_args) -> None: + """ + Checks whether the length of the `*args` argument passed into a function + has at most `len(compat_args)` arguments and whether or not all of these + elements in `args` are set to their default values. + + Parameters + ---------- + fname : str + The name of the function being passed the `*args` parameter + args : tuple + The `*args` parameter passed into a function + max_fname_arg_count : int + The maximum number of arguments that the function `fname` + can accept, excluding those in `args`. Used for displaying + appropriate error messages. Must be non-negative. + compat_args : dict + A dictionary of keys and their associated default values. + In order to accommodate buggy behaviour in some versions of `numpy`, + where a signature displayed keyword arguments but then passed those + arguments **positionally** internally when calling downstream + implementations, a dict ensures that the original + order of the keyword arguments is enforced. + + Raises + ------ + TypeError + If `args` contains more values than there are `compat_args` + ValueError + If `args` contains values that do not correspond to those + of the default values specified in `compat_args` + """ + _check_arg_length(fname, args, max_fname_arg_count, compat_args) + + # We do this so that we can provide a more informative + # error message about the parameters that we are not + # supporting in the pandas implementation of 'fname' + kwargs = dict(zip(compat_args, args)) + _check_for_default_values(fname, kwargs, compat_args) + + +def _check_for_invalid_keys(fname, kwargs, compat_args) -> None: + """ + Checks whether 'kwargs' contains any keys that are not + in 'compat_args' and raises a TypeError if there is one. + """ + # set(dict) --> set of the dictionary's keys + diff = set(kwargs) - set(compat_args) + + if diff: + bad_arg = next(iter(diff)) + raise TypeError(f"{fname}() got an unexpected keyword argument '{bad_arg}'") + + +def validate_kwargs(fname, kwargs, compat_args) -> None: + """ + Checks whether parameters passed to the **kwargs argument in a + function `fname` are valid parameters as specified in `*compat_args` + and whether or not they are set to their default values. + + Parameters + ---------- + fname : str + The name of the function being passed the `**kwargs` parameter + kwargs : dict + The `**kwargs` parameter passed into `fname` + compat_args: dict + A dictionary of keys that `kwargs` is allowed to have and their + associated default values + + Raises + ------ + TypeError if `kwargs` contains keys not in `compat_args` + ValueError if `kwargs` contains keys in `compat_args` that do not + map to the default values specified in `compat_args` + """ + kwds = kwargs.copy() + _check_for_invalid_keys(fname, kwargs, compat_args) + _check_for_default_values(fname, kwds, compat_args) + + +def validate_args_and_kwargs( + fname, args, kwargs, max_fname_arg_count, compat_args +) -> None: + """ + Checks whether parameters passed to the *args and **kwargs argument in a + function `fname` are valid parameters as specified in `*compat_args` + and whether or not they are set to their default values. + + Parameters + ---------- + fname: str + The name of the function being passed the `**kwargs` parameter + args: tuple + The `*args` parameter passed into a function + kwargs: dict + The `**kwargs` parameter passed into `fname` + max_fname_arg_count: int + The minimum number of arguments that the function `fname` + requires, excluding those in `args`. Used for displaying + appropriate error messages. Must be non-negative. + compat_args: dict + A dictionary of keys that `kwargs` is allowed to + have and their associated default values. + + Raises + ------ + TypeError if `args` contains more values than there are + `compat_args` OR `kwargs` contains keys not in `compat_args` + ValueError if `args` contains values not at the default value (`None`) + `kwargs` contains keys in `compat_args` that do not map to the default + value as specified in `compat_args` + + See Also + -------- + validate_args : Purely args validation. + validate_kwargs : Purely kwargs validation. + + """ + # Check that the total number of arguments passed in (i.e. + # args and kwargs) does not exceed the length of compat_args + _check_arg_length( + fname, args + tuple(kwargs.values()), max_fname_arg_count, compat_args + ) + + # Check there is no overlap with the positional and keyword + # arguments, similar to what is done in actual Python functions + args_dict = dict(zip(compat_args, args)) + + for key in args_dict: + if key in kwargs: + raise TypeError( + f"{fname}() got multiple values for keyword argument '{key}'" + ) + + kwargs.update(args_dict) + validate_kwargs(fname, kwargs, compat_args) + + +def validate_bool_kwarg( + value: BoolishNoneT, + arg_name: str, + none_allowed: bool = True, + int_allowed: bool = False, +) -> BoolishNoneT: + """ + Ensure that argument passed in arg_name can be interpreted as boolean. + + Parameters + ---------- + value : bool + Value to be validated. + arg_name : str + Name of the argument. To be reflected in the error message. + none_allowed : bool, default True + Whether to consider None to be a valid boolean. + int_allowed : bool, default False + Whether to consider integer value to be a valid boolean. + + Returns + ------- + value + The same value as input. + + Raises + ------ + ValueError + If the value is not a valid boolean. + """ + good_value = is_bool(value) + if none_allowed: + good_value = good_value or (value is None) + + if int_allowed: + good_value = good_value or isinstance(value, int) + + if not good_value: + raise ValueError( + f'For argument "{arg_name}" expected type bool, received ' + f"type {type(value).__name__}." + ) + return value # pyright: ignore[reportGeneralTypeIssues] + + +def validate_fillna_kwargs(value, method, validate_scalar_dict_value: bool = True): + """ + Validate the keyword arguments to 'fillna'. + + This checks that exactly one of 'value' and 'method' is specified. + If 'method' is specified, this validates that it's a valid method. + + Parameters + ---------- + value, method : object + The 'value' and 'method' keyword arguments for 'fillna'. + validate_scalar_dict_value : bool, default True + Whether to validate that 'value' is a scalar or dict. Specifically, + validate that it is not a list or tuple. + + Returns + ------- + value, method : object + """ + from pandas.core.missing import clean_fill_method + + if value is None and method is None: + raise ValueError("Must specify a fill 'value' or 'method'.") + if value is None and method is not None: + method = clean_fill_method(method) + + elif value is not None and method is None: + if validate_scalar_dict_value and isinstance(value, (list, tuple)): + raise TypeError( + '"value" parameter must be a scalar or dict, but ' + f'you passed a "{type(value).__name__}"' + ) + + elif value is not None and method is not None: + raise ValueError("Cannot specify both 'value' and 'method'.") + + return value, method + + +def validate_percentile(q: float | Iterable[float]) -> np.ndarray: + """ + Validate percentiles (used by describe and quantile). + + This function checks if the given float or iterable of floats is a valid percentile + otherwise raises a ValueError. + + Parameters + ---------- + q: float or iterable of floats + A single percentile or an iterable of percentiles. + + Returns + ------- + ndarray + An ndarray of the percentiles if valid. + + Raises + ------ + ValueError if percentiles are not in given interval([0, 1]). + """ + q_arr = np.asarray(q) + # Don't change this to an f-string. The string formatting + # is too expensive for cases where we don't need it. + msg = "percentiles should all be in the interval [0, 1]" + if q_arr.ndim == 0: + if not 0 <= q_arr <= 1: + raise ValueError(msg) + else: + if not all(0 <= qs <= 1 for qs in q_arr): + raise ValueError(msg) + return q_arr + + +@overload +def validate_ascending(ascending: BoolishT) -> BoolishT: + ... + + +@overload +def validate_ascending(ascending: Sequence[BoolishT]) -> list[BoolishT]: + ... + + +def validate_ascending( + ascending: bool | int | Sequence[BoolishT], +) -> bool | int | list[BoolishT]: + """Validate ``ascending`` kwargs for ``sort_index`` method.""" + kwargs = {"none_allowed": False, "int_allowed": True} + if not isinstance(ascending, Sequence): + return validate_bool_kwarg(ascending, "ascending", **kwargs) + + return [validate_bool_kwarg(item, "ascending", **kwargs) for item in ascending] + + +def validate_endpoints(closed: str | None) -> tuple[bool, bool]: + """ + Check that the `closed` argument is among [None, "left", "right"] + + Parameters + ---------- + closed : {None, "left", "right"} + + Returns + ------- + left_closed : bool + right_closed : bool + + Raises + ------ + ValueError : if argument is not among valid values + """ + left_closed = False + right_closed = False + + if closed is None: + left_closed = True + right_closed = True + elif closed == "left": + left_closed = True + elif closed == "right": + right_closed = True + else: + raise ValueError("Closed has to be either 'left', 'right' or None") + + return left_closed, right_closed + + +def validate_inclusive(inclusive: str | None) -> tuple[bool, bool]: + """ + Check that the `inclusive` argument is among {"both", "neither", "left", "right"}. + + Parameters + ---------- + inclusive : {"both", "neither", "left", "right"} + + Returns + ------- + left_right_inclusive : tuple[bool, bool] + + Raises + ------ + ValueError : if argument is not among valid values + """ + left_right_inclusive: tuple[bool, bool] | None = None + + if isinstance(inclusive, str): + left_right_inclusive = { + "both": (True, True), + "left": (True, False), + "right": (False, True), + "neither": (False, False), + }.get(inclusive) + + if left_right_inclusive is None: + raise ValueError( + "Inclusive has to be either 'both', 'neither', 'left' or 'right'" + ) + + return left_right_inclusive + + +def validate_insert_loc(loc: int, length: int) -> int: + """ + Check that we have an integer between -length and length, inclusive. + + Standardize negative loc to within [0, length]. + + The exceptions we raise on failure match np.insert. + """ + if not is_integer(loc): + raise TypeError(f"loc must be an integer between -{length} and {length}") + + if loc < 0: + loc += length + if not 0 <= loc <= length: + raise IndexError(f"loc must be an integer between -{length} and {length}") + return loc # pyright: ignore[reportGeneralTypeIssues] + + +def check_dtype_backend(dtype_backend) -> None: + if dtype_backend is not lib.no_default: + if dtype_backend not in ["numpy_nullable", "pyarrow"]: + raise ValueError( + f"dtype_backend {dtype_backend} is invalid, only 'numpy_nullable' and " + f"'pyarrow' are allowed.", + ) diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/version/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/version/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3a5efbbb09c1e5085bf0564d819be345edd8c827 --- /dev/null +++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pandas/util/version/__init__.py @@ -0,0 +1,579 @@ +# Vendored from https://github.com/pypa/packaging/blob/main/packaging/_structures.py +# and https://github.com/pypa/packaging/blob/main/packaging/_structures.py +# changeset ae891fd74d6dd4c6063bb04f2faeadaac6fc6313 +# 04/30/2021 + +# This file is dual licensed under the terms of the Apache License, Version +# 2.0, and the BSD License. Licence at LICENSES/PACKAGING_LICENSE +from __future__ import annotations + +import collections +from collections.abc import Iterator +import itertools +import re +from typing import ( + Callable, + SupportsInt, + Tuple, + Union, +) +import warnings + +__all__ = ["parse", "Version", "LegacyVersion", "InvalidVersion", "VERSION_PATTERN"] + + +class InfinityType: + def __repr__(self) -> str: + return "Infinity" + + def __hash__(self) -> int: + return hash(repr(self)) + + def __lt__(self, other: object) -> bool: + return False + + def __le__(self, other: object) -> bool: + return False + + def __eq__(self, other: object) -> bool: + return isinstance(other, type(self)) + + def __ne__(self, other: object) -> bool: + return not isinstance(other, type(self)) + + def __gt__(self, other: object) -> bool: + return True + + def __ge__(self, other: object) -> bool: + return True + + def __neg__(self: object) -> NegativeInfinityType: + return NegativeInfinity + + +Infinity = InfinityType() + + +class NegativeInfinityType: + def __repr__(self) -> str: + return "-Infinity" + + def __hash__(self) -> int: + return hash(repr(self)) + + def __lt__(self, other: object) -> bool: + return True + + def __le__(self, other: object) -> bool: + return True + + def __eq__(self, other: object) -> bool: + return isinstance(other, type(self)) + + def __ne__(self, other: object) -> bool: + return not isinstance(other, type(self)) + + def __gt__(self, other: object) -> bool: + return False + + def __ge__(self, other: object) -> bool: + return False + + def __neg__(self: object) -> InfinityType: + return Infinity + + +NegativeInfinity = NegativeInfinityType() + + +InfiniteTypes = Union[InfinityType, NegativeInfinityType] +PrePostDevType = Union[InfiniteTypes, tuple[str, int]] +SubLocalType = Union[InfiniteTypes, int, str] +LocalType = Union[ + NegativeInfinityType, + tuple[ + Union[ + SubLocalType, + tuple[SubLocalType, str], + tuple[NegativeInfinityType, SubLocalType], + ], + ..., + ], +] +CmpKey = tuple[ + int, tuple[int, ...], PrePostDevType, PrePostDevType, PrePostDevType, LocalType +] +LegacyCmpKey = tuple[int, tuple[str, ...]] +VersionComparisonMethod = Callable[ + [Union[CmpKey, LegacyCmpKey], Union[CmpKey, LegacyCmpKey]], bool +] + +_Version = collections.namedtuple( + "_Version", ["epoch", "release", "dev", "pre", "post", "local"] +) + + +def parse(version: str) -> LegacyVersion | Version: + """ + Parse the given version string and return either a :class:`Version` object + or a :class:`LegacyVersion` object depending on if the given version is + a valid PEP 440 version or a legacy version. + """ + try: + return Version(version) + except InvalidVersion: + return LegacyVersion(version) + + +class InvalidVersion(ValueError): + """ + An invalid version was found, users should refer to PEP 440. + + Examples + -------- + >>> pd.util.version.Version('1.') + Traceback (most recent call last): + InvalidVersion: Invalid version: '1.' + """ + + +class _BaseVersion: + _key: CmpKey | LegacyCmpKey + + def __hash__(self) -> int: + return hash(self._key) + + # Please keep the duplicated `isinstance` check + # in the six comparisons hereunder + # unless you find a way to avoid adding overhead function calls. + def __lt__(self, other: _BaseVersion) -> bool: + if not isinstance(other, _BaseVersion): + return NotImplemented + + return self._key < other._key + + def __le__(self, other: _BaseVersion) -> bool: + if not isinstance(other, _BaseVersion): + return NotImplemented + + return self._key <= other._key + + def __eq__(self, other: object) -> bool: + if not isinstance(other, _BaseVersion): + return NotImplemented + + return self._key == other._key + + def __ge__(self, other: _BaseVersion) -> bool: + if not isinstance(other, _BaseVersion): + return NotImplemented + + return self._key >= other._key + + def __gt__(self, other: _BaseVersion) -> bool: + if not isinstance(other, _BaseVersion): + return NotImplemented + + return self._key > other._key + + def __ne__(self, other: object) -> bool: + if not isinstance(other, _BaseVersion): + return NotImplemented + + return self._key != other._key + + +class LegacyVersion(_BaseVersion): + def __init__(self, version: str) -> None: + self._version = str(version) + self._key = _legacy_cmpkey(self._version) + + warnings.warn( + "Creating a LegacyVersion has been deprecated and will be " + "removed in the next major release.", + DeprecationWarning, + ) + + def __str__(self) -> str: + return self._version + + def __repr__(self) -> str: + return f"" + + @property + def public(self) -> str: + return self._version + + @property + def base_version(self) -> str: + return self._version + + @property + def epoch(self) -> int: + return -1 + + @property + def release(self) -> None: + return None + + @property + def pre(self) -> None: + return None + + @property + def post(self) -> None: + return None + + @property + def dev(self) -> None: + return None + + @property + def local(self) -> None: + return None + + @property + def is_prerelease(self) -> bool: + return False + + @property + def is_postrelease(self) -> bool: + return False + + @property + def is_devrelease(self) -> bool: + return False + + +_legacy_version_component_re = re.compile(r"(\d+ | [a-z]+ | \.| -)", re.VERBOSE) + +_legacy_version_replacement_map = { + "pre": "c", + "preview": "c", + "-": "final-", + "rc": "c", + "dev": "@", +} + + +def _parse_version_parts(s: str) -> Iterator[str]: + for part in _legacy_version_component_re.split(s): + mapped_part = _legacy_version_replacement_map.get(part, part) + + if not mapped_part or mapped_part == ".": + continue + + if mapped_part[:1] in "0123456789": + # pad for numeric comparison + yield mapped_part.zfill(8) + else: + yield "*" + mapped_part + + # ensure that alpha/beta/candidate are before final + yield "*final" + + +def _legacy_cmpkey(version: str) -> LegacyCmpKey: + # We hardcode an epoch of -1 here. A PEP 440 version can only have a epoch + # greater than or equal to 0. This will effectively put the LegacyVersion, + # which uses the defacto standard originally implemented by setuptools, + # as before all PEP 440 versions. + epoch = -1 + + # This scheme is taken from pkg_resources.parse_version setuptools prior to + # it's adoption of the packaging library. + parts: list[str] = [] + for part in _parse_version_parts(version.lower()): + if part.startswith("*"): + # remove "-" before a prerelease tag + if part < "*final": + while parts and parts[-1] == "*final-": + parts.pop() + + # remove trailing zeros from each series of numeric parts + while parts and parts[-1] == "00000000": + parts.pop() + + parts.append(part) + + return epoch, tuple(parts) + + +# Deliberately not anchored to the start and end of the string, to make it +# easier for 3rd party code to reuse +VERSION_PATTERN = r""" + v? + (?: + (?:(?P[0-9]+)!)? # epoch + (?P[0-9]+(?:\.[0-9]+)*) # release segment + (?P
                                          # pre-release
+            [-_\.]?
+            (?P(a|b|c|rc|alpha|beta|pre|preview))
+            [-_\.]?
+            (?P[0-9]+)?
+        )?
+        (?P                                         # post release
+            (?:-(?P[0-9]+))
+            |
+            (?:
+                [-_\.]?
+                (?Ppost|rev|r)
+                [-_\.]?
+                (?P[0-9]+)?
+            )
+        )?
+        (?P                                          # dev release
+            [-_\.]?
+            (?Pdev)
+            [-_\.]?
+            (?P[0-9]+)?
+        )?
+    )
+    (?:\+(?P[a-z0-9]+(?:[-_\.][a-z0-9]+)*))?       # local version
+"""
+
+
+class Version(_BaseVersion):
+    _regex = re.compile(r"^\s*" + VERSION_PATTERN + r"\s*$", re.VERBOSE | re.IGNORECASE)
+
+    def __init__(self, version: str) -> None:
+        # Validate the version and parse it into pieces
+        match = self._regex.search(version)
+        if not match:
+            raise InvalidVersion(f"Invalid version: '{version}'")
+
+        # Store the parsed out pieces of the version
+        self._version = _Version(
+            epoch=int(match.group("epoch")) if match.group("epoch") else 0,
+            release=tuple(int(i) for i in match.group("release").split(".")),
+            pre=_parse_letter_version(match.group("pre_l"), match.group("pre_n")),
+            post=_parse_letter_version(
+                match.group("post_l"), match.group("post_n1") or match.group("post_n2")
+            ),
+            dev=_parse_letter_version(match.group("dev_l"), match.group("dev_n")),
+            local=_parse_local_version(match.group("local")),
+        )
+
+        # Generate a key which will be used for sorting
+        self._key = _cmpkey(
+            self._version.epoch,
+            self._version.release,
+            self._version.pre,
+            self._version.post,
+            self._version.dev,
+            self._version.local,
+        )
+
+    def __repr__(self) -> str:
+        return f""
+
+    def __str__(self) -> str:
+        parts = []
+
+        # Epoch
+        if self.epoch != 0:
+            parts.append(f"{self.epoch}!")
+
+        # Release segment
+        parts.append(".".join([str(x) for x in self.release]))
+
+        # Pre-release
+        if self.pre is not None:
+            parts.append("".join([str(x) for x in self.pre]))
+
+        # Post-release
+        if self.post is not None:
+            parts.append(f".post{self.post}")
+
+        # Development release
+        if self.dev is not None:
+            parts.append(f".dev{self.dev}")
+
+        # Local version segment
+        if self.local is not None:
+            parts.append(f"+{self.local}")
+
+        return "".join(parts)
+
+    @property
+    def epoch(self) -> int:
+        _epoch: int = self._version.epoch
+        return _epoch
+
+    @property
+    def release(self) -> tuple[int, ...]:
+        _release: tuple[int, ...] = self._version.release
+        return _release
+
+    @property
+    def pre(self) -> tuple[str, int] | None:
+        _pre: tuple[str, int] | None = self._version.pre
+        return _pre
+
+    @property
+    def post(self) -> int | None:
+        return self._version.post[1] if self._version.post else None
+
+    @property
+    def dev(self) -> int | None:
+        return self._version.dev[1] if self._version.dev else None
+
+    @property
+    def local(self) -> str | None:
+        if self._version.local:
+            return ".".join([str(x) for x in self._version.local])
+        else:
+            return None
+
+    @property
+    def public(self) -> str:
+        return str(self).split("+", 1)[0]
+
+    @property
+    def base_version(self) -> str:
+        parts = []
+
+        # Epoch
+        if self.epoch != 0:
+            parts.append(f"{self.epoch}!")
+
+        # Release segment
+        parts.append(".".join([str(x) for x in self.release]))
+
+        return "".join(parts)
+
+    @property
+    def is_prerelease(self) -> bool:
+        return self.dev is not None or self.pre is not None
+
+    @property
+    def is_postrelease(self) -> bool:
+        return self.post is not None
+
+    @property
+    def is_devrelease(self) -> bool:
+        return self.dev is not None
+
+    @property
+    def major(self) -> int:
+        return self.release[0] if len(self.release) >= 1 else 0
+
+    @property
+    def minor(self) -> int:
+        return self.release[1] if len(self.release) >= 2 else 0
+
+    @property
+    def micro(self) -> int:
+        return self.release[2] if len(self.release) >= 3 else 0
+
+
+def _parse_letter_version(
+    letter: str, number: str | bytes | SupportsInt
+) -> tuple[str, int] | None:
+    if letter:
+        # We consider there to be an implicit 0 in a pre-release if there is
+        # not a numeral associated with it.
+        if number is None:
+            number = 0
+
+        # We normalize any letters to their lower case form
+        letter = letter.lower()
+
+        # We consider some words to be alternate spellings of other words and
+        # in those cases we want to normalize the spellings to our preferred
+        # spelling.
+        if letter == "alpha":
+            letter = "a"
+        elif letter == "beta":
+            letter = "b"
+        elif letter in ["c", "pre", "preview"]:
+            letter = "rc"
+        elif letter in ["rev", "r"]:
+            letter = "post"
+
+        return letter, int(number)
+    if not letter and number:
+        # We assume if we are given a number, but we are not given a letter
+        # then this is using the implicit post release syntax (e.g. 1.0-1)
+        letter = "post"
+
+        return letter, int(number)
+
+    return None
+
+
+_local_version_separators = re.compile(r"[\._-]")
+
+
+def _parse_local_version(local: str) -> LocalType | None:
+    """
+    Takes a string like abc.1.twelve and turns it into ("abc", 1, "twelve").
+    """
+    if local is not None:
+        return tuple(
+            part.lower() if not part.isdigit() else int(part)
+            for part in _local_version_separators.split(local)
+        )
+    return None
+
+
+def _cmpkey(
+    epoch: int,
+    release: tuple[int, ...],
+    pre: tuple[str, int] | None,
+    post: tuple[str, int] | None,
+    dev: tuple[str, int] | None,
+    local: tuple[SubLocalType] | None,
+) -> CmpKey:
+    # When we compare a release version, we want to compare it with all of the
+    # trailing zeros removed. So we'll use a reverse the list, drop all the now
+    # leading zeros until we come to something non zero, then take the rest
+    # re-reverse it back into the correct order and make it a tuple and use
+    # that for our sorting key.
+    _release = tuple(
+        reversed(list(itertools.dropwhile(lambda x: x == 0, reversed(release))))
+    )
+
+    # We need to "trick" the sorting algorithm to put 1.0.dev0 before 1.0a0.
+    # We'll do this by abusing the pre segment, but we _only_ want to do this
+    # if there is not a pre or a post segment. If we have one of those then
+    # the normal sorting rules will handle this case correctly.
+    if pre is None and post is None and dev is not None:
+        _pre: PrePostDevType = NegativeInfinity
+    # Versions without a pre-release (except as noted above) should sort after
+    # those with one.
+    elif pre is None:
+        _pre = Infinity
+    else:
+        _pre = pre
+
+    # Versions without a post segment should sort before those with one.
+    if post is None:
+        _post: PrePostDevType = NegativeInfinity
+
+    else:
+        _post = post
+
+    # Versions without a development segment should sort after those with one.
+    if dev is None:
+        _dev: PrePostDevType = Infinity
+
+    else:
+        _dev = dev
+
+    if local is None:
+        # Versions without a local segment should sort before those with one.
+        _local: LocalType = NegativeInfinity
+    else:
+        # Versions with a local segment need that segment parsed to implement
+        # the sorting rules in PEP440.
+        # - Alpha numeric segments sort before numeric segments
+        # - Alpha numeric segments sort lexicographically
+        # - Numeric segments sort numerically
+        # - Shorter versions sort before longer versions when the prefixes
+        #   match exactly
+        _local = tuple(
+            (i, "") if isinstance(i, int) else (NegativeInfinity, i) for i in local
+        )
+
+    return epoch, _release, _pre, _post, _dev, _local
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/INSTALLER b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/LICENSE b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..261eeb9e9f8b2b4b0d119366dda99c6fd7d35c64
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/LICENSE
@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
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diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/METADATA b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..d7de7c5b4be6129938a34cabfa9c88961c9c1d08
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft-0.15.2.dist-info/METADATA
@@ -0,0 +1,233 @@
+Metadata-Version: 2.2
+Name: peft
+Version: 0.15.2
+Summary: Parameter-Efficient Fine-Tuning (PEFT)
+Home-page: https://github.com/huggingface/peft
+Author: The HuggingFace team
+Author-email: benjamin@huggingface.co
+License: Apache
+Keywords: deep learning
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: Apache Software License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Requires-Python: >=3.9.0
+Description-Content-Type: text/markdown
+License-File: LICENSE
+Requires-Dist: numpy>=1.17
+Requires-Dist: packaging>=20.0
+Requires-Dist: psutil
+Requires-Dist: pyyaml
+Requires-Dist: torch>=1.13.0
+Requires-Dist: transformers
+Requires-Dist: tqdm
+Requires-Dist: accelerate>=0.21.0
+Requires-Dist: safetensors
+Requires-Dist: huggingface_hub>=0.25.0
+Provides-Extra: quality
+Requires-Dist: black; extra == "quality"
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+Requires-Dist: ruff~=0.9.2; extra == "quality"
+Provides-Extra: docs-specific
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+Provides-Extra: dev
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+Provides-Extra: test
+Requires-Dist: black; extra == "test"
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+Requires-Dist: pytest; extra == "test"
+Requires-Dist: pytest-cov; extra == "test"
+Requires-Dist: pytest-xdist; extra == "test"
+Requires-Dist: parameterized; extra == "test"
+Requires-Dist: datasets; extra == "test"
+Requires-Dist: diffusers; extra == "test"
+Requires-Dist: scipy; extra == "test"
+Requires-Dist: protobuf; extra == "test"
+Requires-Dist: sentencepiece; extra == "test"
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: description-content-type
+Dynamic: home-page
+Dynamic: keywords
+Dynamic: license
+Dynamic: provides-extra
+Dynamic: requires-dist
+Dynamic: requires-python
+Dynamic: summary
+
+
+
+
 
🤗 PEFT

+

+    
State-of-the-art Parameter-Efficient Fine-Tuning (PEFT) methods

+

+
+Fine-tuning large pretrained models is often prohibitively costly due to their scale. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters. This significantly decreases the computational and storage costs. Recent state-of-the-art PEFT techniques achieve performance comparable to fully fine-tuned models.
+
+PEFT is integrated with Transformers for easy model training and inference, Diffusers for conveniently managing different adapters, and Accelerate for distributed training and inference for really big models.
+
+> [!TIP]
+> Visit the [PEFT](https://huggingface.co/PEFT) organization to read about the PEFT methods implemented in the library and to see notebooks demonstrating how to apply these methods to a variety of downstream tasks. Click the "Watch repos" button on the organization page to be notified of newly implemented methods and notebooks!
+
+Check the PEFT Adapters API Reference section for a list of supported PEFT methods, and read the [Adapters](https://huggingface.co/docs/peft/en/conceptual_guides/adapter), [Soft prompts](https://huggingface.co/docs/peft/en/conceptual_guides/prompting), and [IA3](https://huggingface.co/docs/peft/en/conceptual_guides/ia3) conceptual guides to learn more about how these methods work.
+
+## Quickstart
+
+Install PEFT from pip:
+
+```bash
+pip install peft
+```
+
+Prepare a model for training with a PEFT method such as LoRA by wrapping the base model and PEFT configuration with `get_peft_model`. For the bigscience/mt0-large model, you're only training 0.19% of the parameters!
+
+```python
+from transformers import AutoModelForSeq2SeqLM
+from peft import get_peft_config, get_peft_model, LoraConfig, TaskType
+model_name_or_path = "bigscience/mt0-large"
+tokenizer_name_or_path = "bigscience/mt0-large"
+
+peft_config = LoraConfig(
+    task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1
+)
+
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+model = get_peft_model(model, peft_config)
+model.print_trainable_parameters()
+"trainable params: 2359296 || all params: 1231940608 || trainable%: 0.19151053100118282"
+```
+
+To load a PEFT model for inference:
+
+```py
+from peft import AutoPeftModelForCausalLM
+from transformers import AutoTokenizer
+import torch
+
+model = AutoPeftModelForCausalLM.from_pretrained("ybelkada/opt-350m-lora").to("cuda")
+tokenizer = AutoTokenizer.from_pretrained("facebook/opt-350m")
+
+model.eval()
+inputs = tokenizer("Preheat the oven to 350 degrees and place the cookie dough", return_tensors="pt")
+
+outputs = model.generate(input_ids=inputs["input_ids"].to("cuda"), max_new_tokens=50)
+print(tokenizer.batch_decode(outputs, skip_special_tokens=True)[0])
+
+"Preheat the oven to 350 degrees and place the cookie dough in the center of the oven. In a large bowl, combine the flour, baking powder, baking soda, salt, and cinnamon. In a separate bowl, combine the egg yolks, sugar, and vanilla."
+```
+
+## Why you should use PEFT
+
+There are many benefits of using PEFT but the main one is the huge savings in compute and storage, making PEFT applicable to many different use cases.
+
+### High performance on consumer hardware
+
+Consider the memory requirements for training the following models on the [ought/raft/twitter_complaints](https://huggingface.co/datasets/ought/raft/viewer/twitter_complaints) dataset with an A100 80GB GPU with more than 64GB of CPU RAM.
+
+|   Model         | Full Finetuning | PEFT-LoRA PyTorch  | PEFT-LoRA DeepSpeed with CPU Offloading |
+| --------- | ---- | ---- | ---- |
+| bigscience/T0_3B (3B params) | 47.14GB GPU / 2.96GB CPU  | 14.4GB GPU / 2.96GB CPU | 9.8GB GPU / 17.8GB CPU |
+| bigscience/mt0-xxl (12B params) | OOM GPU | 56GB GPU / 3GB CPU | 22GB GPU / 52GB CPU |
+| bigscience/bloomz-7b1 (7B params) | OOM GPU | 32GB GPU / 3.8GB CPU | 18.1GB GPU / 35GB CPU |
+
+With LoRA you can fully finetune a 12B parameter model that would've otherwise run out of memory on the 80GB GPU, and comfortably fit and train a 3B parameter model. When you look at the 3B parameter model's performance, it is comparable to a fully finetuned model at a fraction of the GPU memory.
+
+|   Submission Name        | Accuracy |
+| --------- | ---- |
+| Human baseline (crowdsourced) |	0.897 |
+| Flan-T5 | 0.892 |
+| lora-t0-3b | 0.863 |
+
+> [!TIP]
+> The bigscience/T0_3B model performance isn't optimized in the table above. You can squeeze even more performance out of it by playing around with the input instruction templates, LoRA hyperparameters, and other training related hyperparameters. The final checkpoint size of this model is just 19MB compared to 11GB of the full bigscience/T0_3B model. Learn more about the advantages of finetuning with PEFT in this [blog post](https://www.philschmid.de/fine-tune-flan-t5-peft).
+
+### Quantization
+
+Quantization is another method for reducing the memory requirements of a model by representing the data in a lower precision. It can be combined with PEFT methods to make it even easier to train and load LLMs for inference.
+
+* Learn how to finetune [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) with QLoRA and the [TRL](https://huggingface.co/docs/trl/index) library on a 16GB GPU in the [Finetune LLMs on your own consumer hardware using tools from PyTorch and Hugging Face ecosystem](https://pytorch.org/blog/finetune-llms/) blog post.
+* Learn how to finetune a [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) model for multilingual automatic speech recognition with LoRA and 8-bit quantization in this [notebook](https://colab.research.google.com/drive/1DOkD_5OUjFa0r5Ik3SgywJLJtEo2qLxO?usp=sharing) (see this [notebook](https://colab.research.google.com/drive/1vhF8yueFqha3Y3CpTHN6q9EVcII9EYzs?usp=sharing) instead for an example of streaming a dataset).
+
+### Save compute and storage
+
+PEFT can help you save storage by avoiding full finetuning of models on each of downstream task or dataset. In many cases, you're only finetuning a very small fraction of a model's parameters and each checkpoint is only a few MBs in size (instead of GBs). These smaller PEFT adapters demonstrate performance comparable to a fully finetuned model. If you have many datasets, you can save a lot of storage with a PEFT model and not have to worry about catastrophic forgetting or overfitting the backbone or base model.
+
+## PEFT integrations
+
+PEFT is widely supported across the Hugging Face ecosystem because of the massive efficiency it brings to training and inference.
+
+### Diffusers
+
+The iterative diffusion process consumes a lot of memory which can make it difficult to train. PEFT can help reduce the memory requirements and reduce the storage size of the final model checkpoint. For example, consider the memory required for training a Stable Diffusion model with LoRA on an A100 80GB GPU with more than 64GB of CPU RAM. The final model checkpoint size is only 8.8MB!
+
+|   Model         | Full Finetuning | PEFT-LoRA  | PEFT-LoRA with Gradient Checkpointing  |
+| --------- | ---- | ---- | ---- |
+| CompVis/stable-diffusion-v1-4 | 27.5GB GPU / 3.97GB CPU | 15.5GB GPU / 3.84GB CPU | 8.12GB GPU / 3.77GB CPU | 
+
+> [!TIP]
+> Take a look at the [examples/lora_dreambooth/train_dreambooth.py](examples/lora_dreambooth/train_dreambooth.py) training script to try training your own Stable Diffusion model with LoRA, and play around with the [smangrul/peft-lora-sd-dreambooth](https://huggingface.co/spaces/smangrul/peft-lora-sd-dreambooth) Space which is running on a T4 instance. Learn more about the PEFT integration in Diffusers in this [tutorial](https://huggingface.co/docs/peft/main/en/tutorial/peft_integrations#diffusers).
+
+### Accelerate
+
+[Accelerate](https://huggingface.co/docs/accelerate/index) is a library for distributed training and inference on various training setups and hardware (GPUs, TPUs, Apple Silicon, etc.). PEFT models work with Accelerate out of the box, making it really convenient to train really large models or use them for inference on consumer hardware with limited resources.
+
+### TRL
+
+PEFT can also be applied to training LLMs with RLHF components such as the ranker and policy. Get started by reading:
+
+* [Fine-tune a Mistral-7b model with Direct Preference Optimization](https://towardsdatascience.com/fine-tune-a-mistral-7b-model-with-direct-preference-optimization-708042745aac) with PEFT and the [TRL](https://huggingface.co/docs/trl/index) library to learn more about the Direct Preference Optimization (DPO) method and how to apply it to a LLM.
+* [Fine-tuning 20B LLMs with RLHF on a 24GB consumer GPU](https://huggingface.co/blog/trl-peft) with PEFT and the [TRL](https://huggingface.co/docs/trl/index) library, and then try out the [gpt2-sentiment_peft.ipynb](https://github.com/huggingface/trl/blob/main/examples/notebooks/gpt2-sentiment.ipynb) notebook to optimize GPT2 to generate positive movie reviews.
+* [StackLLaMA: A hands-on guide to train LLaMA with RLHF](https://huggingface.co/blog/stackllama) with PEFT, and then try out the [stack_llama/scripts](https://github.com/huggingface/trl/tree/main/examples/research_projects/stack_llama/scripts) for supervised finetuning, reward modeling, and RL finetuning.
+
+## Model support
+
+Use this [Space](https://stevhliu-peft-methods.hf.space) or check out the [docs](https://huggingface.co/docs/peft/main/en/index) to find which models officially support a PEFT method out of the box. Even if you don't see a model listed below, you can manually configure the model config to enable PEFT for a model. Read the [New transformers architecture](https://huggingface.co/docs/peft/main/en/developer_guides/custom_models#new-transformers-architectures) guide to learn how.
+
+## Contribute
+
+If you would like to contribute to PEFT, please check out our [contribution guide](https://huggingface.co/docs/peft/developer_guides/contributing).
+
+## Citing 🤗 PEFT
+
+To use 🤗 PEFT in your publication, please cite it by using the following BibTeX entry.
+
+```bibtex
+@Misc{peft,
+  title =        {PEFT: State-of-the-art Parameter-Efficient Fine-Tuning methods},
+  author =       {Sourab Mangrulkar and Sylvain Gugger and Lysandre Debut and Younes Belkada and Sayak Paul and Benjamin Bossan},
+  howpublished = {\url{https://github.com/huggingface/peft}},
+  year =         {2022}
+}
+```
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diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..abf6496b1ce7733d1c0883fd694f062889d85bf8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/__init__.py
@@ -0,0 +1,206 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+__version__ = "0.15.2"
+
+from .auto import (
+    MODEL_TYPE_TO_PEFT_MODEL_MAPPING,
+    AutoPeftModel,
+    AutoPeftModelForCausalLM,
+    AutoPeftModelForFeatureExtraction,
+    AutoPeftModelForQuestionAnswering,
+    AutoPeftModelForSeq2SeqLM,
+    AutoPeftModelForSequenceClassification,
+    AutoPeftModelForTokenClassification,
+)
+from .config import PeftConfig, PromptLearningConfig
+from .mapping import (
+    PEFT_TYPE_TO_CONFIG_MAPPING,
+    PEFT_TYPE_TO_MIXED_MODEL_MAPPING,
+    PEFT_TYPE_TO_TUNER_MAPPING,
+    get_peft_config,
+    inject_adapter_in_model,
+)
+from .mapping_func import get_peft_model
+from .mixed_model import PeftMixedModel
+from .peft_model import (
+    PeftModel,
+    PeftModelForCausalLM,
+    PeftModelForFeatureExtraction,
+    PeftModelForQuestionAnswering,
+    PeftModelForSeq2SeqLM,
+    PeftModelForSequenceClassification,
+    PeftModelForTokenClassification,
+    get_layer_status,
+    get_model_status,
+)
+from .tuners import (
+    AdaLoraConfig,
+    AdaLoraModel,
+    AdaptionPromptConfig,
+    AdaptionPromptModel,
+    BOFTConfig,
+    BOFTModel,
+    BoneConfig,
+    BoneModel,
+    CPTConfig,
+    CPTEmbedding,
+    EvaConfig,
+    FourierFTConfig,
+    FourierFTModel,
+    HRAConfig,
+    HRAModel,
+    IA3Config,
+    IA3Model,
+    LNTuningConfig,
+    LNTuningModel,
+    LoftQConfig,
+    LoHaConfig,
+    LoHaModel,
+    LoKrConfig,
+    LoKrModel,
+    LoraConfig,
+    LoraModel,
+    LoraRuntimeConfig,
+    MultitaskPromptTuningConfig,
+    MultitaskPromptTuningInit,
+    OFTConfig,
+    OFTModel,
+    PolyConfig,
+    PolyModel,
+    PrefixEncoder,
+    PrefixTuningConfig,
+    PromptEmbedding,
+    PromptEncoder,
+    PromptEncoderConfig,
+    PromptEncoderReparameterizationType,
+    PromptTuningConfig,
+    PromptTuningInit,
+    TrainableTokensConfig,
+    TrainableTokensModel,
+    VBLoRAConfig,
+    VBLoRAModel,
+    VeraConfig,
+    VeraModel,
+    XLoraConfig,
+    XLoraModel,
+    get_eva_state_dict,
+    initialize_lora_eva_weights,
+)
+from .utils import (
+    TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING,
+    PeftType,
+    TaskType,
+    bloom_model_postprocess_past_key_value,
+    cast_mixed_precision_params,
+    get_peft_model_state_dict,
+    load_peft_weights,
+    prepare_model_for_kbit_training,
+    replace_lora_weights_loftq,
+    set_peft_model_state_dict,
+    shift_tokens_right,
+)
+
+
+__all__ = [
+    "MODEL_TYPE_TO_PEFT_MODEL_MAPPING",
+    "PEFT_TYPE_TO_CONFIG_MAPPING",
+    "PEFT_TYPE_TO_MIXED_MODEL_MAPPING",
+    "PEFT_TYPE_TO_TUNER_MAPPING",
+    "TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING",
+    "AdaLoraConfig",
+    "AdaLoraModel",
+    "AdaptionPromptConfig",
+    "AdaptionPromptModel",
+    "AutoPeftModel",
+    "AutoPeftModelForCausalLM",
+    "AutoPeftModelForFeatureExtraction",
+    "AutoPeftModelForQuestionAnswering",
+    "AutoPeftModelForSeq2SeqLM",
+    "AutoPeftModelForSequenceClassification",
+    "AutoPeftModelForTokenClassification",
+    "BOFTConfig",
+    "BOFTModel",
+    "BoneConfig",
+    "BoneModel",
+    "CPTConfig",
+    "CPTEmbedding",
+    "EvaConfig",
+    "FourierFTConfig",
+    "FourierFTModel",
+    "HRAConfig",
+    "HRAModel",
+    "IA3Config",
+    "IA3Model",
+    "LNTuningConfig",
+    "LNTuningModel",
+    "LoHaConfig",
+    "LoHaModel",
+    "LoKrConfig",
+    "LoKrModel",
+    "LoftQConfig",
+    "LoraConfig",
+    "LoraModel",
+    "LoraRuntimeConfig",
+    "MultitaskPromptTuningConfig",
+    "MultitaskPromptTuningInit",
+    "OFTConfig",
+    "OFTModel",
+    "PeftConfig",
+    "PeftMixedModel",
+    "PeftModel",
+    "PeftModelForCausalLM",
+    "PeftModelForFeatureExtraction",
+    "PeftModelForQuestionAnswering",
+    "PeftModelForSeq2SeqLM",
+    "PeftModelForSequenceClassification",
+    "PeftModelForTokenClassification",
+    "PeftType",
+    "PolyConfig",
+    "PolyModel",
+    "PrefixEncoder",
+    "PrefixTuningConfig",
+    "PromptEmbedding",
+    "PromptEncoder",
+    "PromptEncoderConfig",
+    "PromptEncoderReparameterizationType",
+    "PromptLearningConfig",
+    "PromptTuningConfig",
+    "PromptTuningInit",
+    "TaskType",
+    "TrainableTokensConfig",
+    "TrainableTokensModel",
+    "VBLoRAConfig",
+    "VBLoRAConfig",
+    "VBLoRAModel",
+    "VeraConfig",
+    "VeraModel",
+    "XLoraConfig",
+    "XLoraModel",
+    "bloom_model_postprocess_past_key_value",
+    "cast_mixed_precision_params",
+    "get_eva_state_dict",
+    "get_layer_status",
+    "get_model_status",
+    "get_peft_config",
+    "get_peft_model",
+    "get_peft_model_state_dict",
+    "initialize_lora_eva_weights",
+    "inject_adapter_in_model",
+    "load_peft_weights",
+    "prepare_model_for_kbit_training",
+    "replace_lora_weights_loftq",
+    "set_peft_model_state_dict",
+    "shift_tokens_right",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/auto.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/auto.py
new file mode 100644
index 0000000000000000000000000000000000000000..613f67c707e344eab1a5281565fb0fdb3d827d01
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/auto.py
@@ -0,0 +1,184 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import importlib
+import os
+from typing import Optional
+
+from transformers import (
+    AutoModel,
+    AutoModelForCausalLM,
+    AutoModelForQuestionAnswering,
+    AutoModelForSeq2SeqLM,
+    AutoModelForSequenceClassification,
+    AutoModelForTokenClassification,
+    AutoTokenizer,
+)
+
+from .config import PeftConfig
+from .peft_model import (
+    PeftModel,
+    PeftModelForCausalLM,
+    PeftModelForFeatureExtraction,
+    PeftModelForQuestionAnswering,
+    PeftModelForSeq2SeqLM,
+    PeftModelForSequenceClassification,
+    PeftModelForTokenClassification,
+)
+from .utils.constants import TOKENIZER_CONFIG_NAME
+from .utils.other import check_file_exists_on_hf_hub
+
+
+MODEL_TYPE_TO_PEFT_MODEL_MAPPING: dict[str, type[PeftModel]] = {
+    "SEQ_CLS": PeftModelForSequenceClassification,
+    "SEQ_2_SEQ_LM": PeftModelForSeq2SeqLM,
+    "CAUSAL_LM": PeftModelForCausalLM,
+    "TOKEN_CLS": PeftModelForTokenClassification,
+    "QUESTION_ANS": PeftModelForQuestionAnswering,
+    "FEATURE_EXTRACTION": PeftModelForFeatureExtraction,
+}
+
+
+class _BaseAutoPeftModel:
+    _target_class = None
+    _target_peft_class = None
+
+    def __init__(self, *args, **kwargs):
+        # For consistency with transformers: https://github.com/huggingface/transformers/blob/91d7df58b6537d385e90578dac40204cb550f706/src/transformers/models/auto/auto_factory.py#L400
+        raise EnvironmentError(  # noqa: UP024
+            f"{self.__class__.__name__} is designed to be instantiated "
+            f"using the `{self.__class__.__name__}.from_pretrained(pretrained_model_name_or_path)` or "
+            f"`{self.__class__.__name__}.from_config(config)` methods."
+        )
+
+    @classmethod
+    def from_pretrained(
+        cls,
+        pretrained_model_name_or_path,
+        adapter_name: str = "default",
+        is_trainable: bool = False,
+        config: Optional[PeftConfig] = None,
+        revision: Optional[str] = None,
+        **kwargs,
+    ):
+        r"""
+        A wrapper around all the preprocessing steps a user needs to perform in order to load a PEFT model. The kwargs
+        are passed along to `PeftConfig` that automatically takes care of filtering the kwargs of the Hub methods and
+        the config object init.
+        """
+        peft_config = PeftConfig.from_pretrained(pretrained_model_name_or_path, revision=revision, **kwargs)
+        base_model_path = peft_config.base_model_name_or_path
+        base_model_revision = peft_config.revision
+
+        task_type = getattr(peft_config, "task_type", None)
+
+        if cls._target_class is not None:
+            target_class = cls._target_class
+        elif cls._target_class is None and task_type is not None:
+            # this is only in the case where we use `AutoPeftModel`
+            raise ValueError(
+                "Cannot use `AutoPeftModel` with a task type, please use a specific class for your task type. (e.g. `AutoPeftModelForCausalLM` for `task_type='CAUSAL_LM'`)"
+            )
+
+        if task_type is not None:
+            expected_target_class = MODEL_TYPE_TO_PEFT_MODEL_MAPPING[task_type]
+            if cls._target_peft_class.__name__ != expected_target_class.__name__:
+                raise ValueError(
+                    f"Expected target PEFT class: {expected_target_class.__name__}, but you have asked for: {cls._target_peft_class.__name__}"
+                    " make sure that you are loading the correct model for your task type."
+                )
+        elif task_type is None and getattr(peft_config, "auto_mapping", None) is not None:
+            auto_mapping = getattr(peft_config, "auto_mapping", None)
+            base_model_class = auto_mapping["base_model_class"]
+            parent_library_name = auto_mapping["parent_library"]
+
+            parent_library = importlib.import_module(parent_library_name)
+            target_class = getattr(parent_library, base_model_class)
+        else:
+            raise ValueError(
+                "Cannot infer the auto class from the config, please make sure that you are loading the correct model for your task type."
+            )
+
+        base_model = target_class.from_pretrained(base_model_path, revision=base_model_revision, **kwargs)
+
+        tokenizer_exists = False
+        if os.path.exists(os.path.join(pretrained_model_name_or_path, TOKENIZER_CONFIG_NAME)):
+            tokenizer_exists = True
+        else:
+            token = kwargs.get("token", None)
+            if token is None:
+                token = kwargs.get("use_auth_token", None)
+
+            tokenizer_exists = check_file_exists_on_hf_hub(
+                repo_id=pretrained_model_name_or_path,
+                filename=TOKENIZER_CONFIG_NAME,
+                revision=revision,
+                repo_type=kwargs.get("repo_type", None),
+                token=token,
+            )
+
+        if tokenizer_exists and hasattr(base_model, "get_input_embeddings"):
+            tokenizer = AutoTokenizer.from_pretrained(
+                pretrained_model_name_or_path, trust_remote_code=kwargs.get("trust_remote_code", False)
+            )
+            embedding_size = base_model.get_input_embeddings().weight.shape[0]
+            if len(tokenizer) > embedding_size:
+                # only resize if the tokenizer has a larger vocab size than there are embeddings
+                base_model.resize_token_embeddings(len(tokenizer))
+
+        return cls._target_peft_class.from_pretrained(
+            base_model,
+            pretrained_model_name_or_path,
+            adapter_name=adapter_name,
+            is_trainable=is_trainable,
+            config=config,
+            **kwargs,
+        )
+
+
+class AutoPeftModel(_BaseAutoPeftModel):
+    _target_class = None
+    _target_peft_class = PeftModel
+
+
+class AutoPeftModelForCausalLM(_BaseAutoPeftModel):
+    _target_class = AutoModelForCausalLM
+    _target_peft_class = PeftModelForCausalLM
+
+
+class AutoPeftModelForSeq2SeqLM(_BaseAutoPeftModel):
+    _target_class = AutoModelForSeq2SeqLM
+    _target_peft_class = PeftModelForSeq2SeqLM
+
+
+class AutoPeftModelForSequenceClassification(_BaseAutoPeftModel):
+    _target_class = AutoModelForSequenceClassification
+    _target_peft_class = PeftModelForSequenceClassification
+
+
+class AutoPeftModelForTokenClassification(_BaseAutoPeftModel):
+    _target_class = AutoModelForTokenClassification
+    _target_peft_class = PeftModelForTokenClassification
+
+
+class AutoPeftModelForQuestionAnswering(_BaseAutoPeftModel):
+    _target_class = AutoModelForQuestionAnswering
+    _target_peft_class = PeftModelForQuestionAnswering
+
+
+class AutoPeftModelForFeatureExtraction(_BaseAutoPeftModel):
+    _target_class = AutoModel
+    _target_peft_class = PeftModelForFeatureExtraction
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..4b5488d877ebbe3c6e95c98c2c1f155d0d32e00a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/config.py
@@ -0,0 +1,342 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import inspect
+import json
+import os
+import warnings
+from dataclasses import asdict, dataclass, field
+from typing import Dict, Optional, Union
+
+from huggingface_hub import hf_hub_download
+from transformers.utils import PushToHubMixin
+
+from .utils import CONFIG_NAME, PeftType, TaskType
+
+
+# we expect at least these keys to be present in a PEFT adapter_config.json
+MIN_EXPECTED_CONFIG_KEYS = {"peft_type"}
+
+
+def _check_and_remove_unused_kwargs(cls, kwargs):
+    """Make PEFT configs forward-compatible by removing unused kwargs that were added in later PEFT versions.
+
+    This assumes that removing the unused kwargs will not affect the default behavior.
+
+    Returns the filtered kwargs and the set of removed keys.
+    """
+    # it's not pretty but eh
+    signature_parameters = inspect.signature(cls.__init__).parameters
+    unexpected_kwargs = set(kwargs.keys()) - set(signature_parameters.keys())
+    for key in unexpected_kwargs:
+        del kwargs[key]
+    return kwargs, unexpected_kwargs
+
+
+@dataclass
+class PeftConfigMixin(PushToHubMixin):
+    r"""
+    This is the base configuration class for PEFT adapter models. It contains all the methods that are common to all
+    PEFT adapter models. This class inherits from [`~transformers.utils.PushToHubMixin`] which contains the methods to
+    push your model to the Hub. The method `save_pretrained` will save the configuration of your adapter model in a
+    directory. The method `from_pretrained` will load the configuration of your adapter model from a directory.
+
+    Args:
+        peft_type (Union[[`~peft.utils.config.PeftType`], `str`]): The type of Peft method to use.
+    """
+
+    task_type: Optional[TaskType] = field(default=None, metadata={"help": "The type of task."})
+    peft_type: Optional[PeftType] = field(default=None, metadata={"help": "The type of PEFT model."})
+    auto_mapping: Optional[dict] = field(
+        default=None, metadata={"help": "An auto mapping dict to help retrieve the base model class if needed."}
+    )
+
+    def __post_init__(self):
+        # check for invalid task type
+        if (self.task_type is not None) and (self.task_type not in list(TaskType)):
+            raise ValueError(
+                f"Invalid task type: '{self.task_type}'. Must be one of the following task types: {', '.join(TaskType)}."
+            )
+
+    def to_dict(self) -> Dict:
+        r"""
+        Returns the configuration for your adapter model as a dictionary.
+        """
+        return asdict(self)
+
+    def save_pretrained(self, save_directory: str, **kwargs) -> None:
+        r"""
+        This method saves the configuration of your adapter model in a directory.
+
+        Args:
+            save_directory (`str`):
+                The directory where the configuration will be saved.
+            kwargs (additional keyword arguments, *optional*):
+                Additional keyword arguments passed along to the [`~transformers.utils.PushToHubMixin.push_to_hub`]
+                method.
+        """
+        if os.path.isfile(save_directory):
+            raise AssertionError(f"Provided path ({save_directory}) should be a directory, not a file")
+
+        os.makedirs(save_directory, exist_ok=True)
+        auto_mapping_dict = kwargs.pop("auto_mapping_dict", None)
+
+        output_dict = self.to_dict()
+        # converting set type to list
+        for key, value in output_dict.items():
+            if isinstance(value, set):
+                output_dict[key] = list(value)
+
+        output_path = os.path.join(save_directory, CONFIG_NAME)
+
+        # Add auto mapping details for custom models.
+        if auto_mapping_dict is not None:
+            output_dict["auto_mapping"] = auto_mapping_dict
+
+        # save it
+        with open(output_path, "w") as writer:
+            writer.write(json.dumps(output_dict, indent=2, sort_keys=True))
+
+    @classmethod
+    def from_peft_type(cls, **kwargs):
+        r"""
+        This method loads the configuration of your adapter model from a set of kwargs.
+
+        The appropriate configuration type is determined by the `peft_type` argument. If `peft_type` is not provided,
+        the calling class type is instantiated.
+
+        Args:
+            kwargs (configuration keyword arguments):
+                Keyword arguments passed along to the configuration initialization.
+        """
+        # Avoid circular dependency .. TODO: fix this with a larger refactor
+        from peft.mapping import PEFT_TYPE_TO_CONFIG_MAPPING
+
+        # TODO: this hack is needed to fix the following issue (on commit 702f937):
+        # if someone saves a default config and loads it back with `PeftConfig` class it yields to
+        # not loading the correct config class.
+        #
+        # from peft import AdaLoraConfig, PeftConfig
+        # peft_config = AdaLoraConfig()
+        # print(peft_config)
+        # >>> AdaLoraConfig(peft_type=, auto_mapping=None, base_model_name_or_path=None,
+        # revision=None, task_type=None, inference_mode=False, r=8, target_modules=None, lora_alpha=8, lora_dropout=0.0, ...
+        #
+        # peft_config.save_pretrained("./test_config")
+        # peft_config = PeftConfig.from_pretrained("./test_config")
+        # print(peft_config)
+        # >>> PeftConfig(peft_type='ADALORA', auto_mapping=None, base_model_name_or_path=None, revision=None, task_type=None, inference_mode=False)
+
+        if "peft_type" in kwargs:
+            peft_type = kwargs["peft_type"]
+            config_cls = PEFT_TYPE_TO_CONFIG_MAPPING[peft_type]
+        else:
+            config_cls = cls
+
+        try:
+            config = config_cls(**kwargs)
+        except TypeError as exc:
+            # Here we potentially handle forward compatibility. Sometimes new keywords are added to configs, which makes
+            # new configs incompatible with older PEFT versions. We catch these and remove them to allow the program to
+            # continue, but warn the user about it.
+
+            # First check if the error is due to unexpected keyword arguments, we don't want to accidentally catch
+            # other TypeErrors.
+            if "got an unexpected keyword argument" not in str(exc):
+                raise exc
+
+            filtered_kwargs, unexpected_kwargs = _check_and_remove_unused_kwargs(config_cls, kwargs)
+            if not MIN_EXPECTED_CONFIG_KEYS.issubset(set(filtered_kwargs.keys())):
+                raise TypeError(
+                    f"The {cls.__name__} config that is trying to be loaded is missing required keys: "
+                    f"{MIN_EXPECTED_CONFIG_KEYS}."
+                )
+
+            warnings.warn(
+                f"Unexpected keyword arguments {sorted(unexpected_kwargs)} for class {config_cls.__name__}, these are "
+                "ignored. This probably means that you're loading a configuration file that was saved using a "
+                "higher version of the library and additional parameters have been introduced since. It is "
+                "highly recommended to upgrade the PEFT version before continuing (e.g. by running `pip install "
+                "-U peft`)."
+            )
+            config = config_cls.from_peft_type(**filtered_kwargs)
+        return config
+
+    @classmethod
+    def from_pretrained(cls, pretrained_model_name_or_path: str, subfolder: Optional[str] = None, **kwargs):
+        r"""
+        This method loads the configuration of your adapter model from a directory.
+
+        Args:
+            pretrained_model_name_or_path (`str`):
+                The directory or the Hub repository id where the configuration is saved.
+            kwargs (additional keyword arguments, *optional*):
+                Additional keyword arguments passed along to the child class initialization.
+        """
+        path = (
+            os.path.join(pretrained_model_name_or_path, subfolder)
+            if subfolder is not None
+            else pretrained_model_name_or_path
+        )
+
+        hf_hub_download_kwargs, class_kwargs, _ = cls._split_kwargs(kwargs)
+
+        if os.path.isfile(os.path.join(path, CONFIG_NAME)):
+            config_file = os.path.join(path, CONFIG_NAME)
+        else:
+            try:
+                config_file = hf_hub_download(
+                    pretrained_model_name_or_path, CONFIG_NAME, subfolder=subfolder, **hf_hub_download_kwargs
+                )
+            except Exception as exc:
+                raise ValueError(f"Can't find '{CONFIG_NAME}' at '{pretrained_model_name_or_path}'") from exc
+
+        loaded_attributes = cls.from_json_file(config_file)
+        kwargs = {**class_kwargs, **loaded_attributes}
+        kwargs = cls.check_kwargs(**kwargs)
+        return cls.from_peft_type(**kwargs)
+
+    @classmethod
+    def from_json_file(cls, path_json_file: str, **kwargs):
+        r"""
+        Loads a configuration file from a json file.
+
+        Args:
+            path_json_file (`str`):
+                The path to the json file.
+        """
+        with open(path_json_file) as file:
+            json_object = json.load(file)
+
+        # Sanity check that config does not contain a runtime_config
+        if "runtime_config" in json_object:
+            warnings.warn(
+                "The configuration file contains a `runtime_config` key. This is ignored. Runtime configurations are only valid at runtime."
+            )
+            del json_object["runtime_config"]
+
+        return json_object
+
+    @classmethod
+    def _split_kwargs(cls, kwargs):
+        hf_hub_download_kwargs = {}
+        class_kwargs = {}
+        other_kwargs = {}
+
+        for key, value in kwargs.items():
+            if key in inspect.signature(hf_hub_download).parameters:
+                hf_hub_download_kwargs[key] = value
+            elif key in list(cls.__annotations__):
+                class_kwargs[key] = value
+            else:
+                other_kwargs[key] = value
+
+        return hf_hub_download_kwargs, class_kwargs, other_kwargs
+
+    @classmethod
+    def _get_peft_type(
+        cls,
+        model_id: str,
+        **hf_hub_download_kwargs,
+    ):
+        subfolder = hf_hub_download_kwargs.get("subfolder", None)
+
+        path = os.path.join(model_id, subfolder) if subfolder is not None else model_id
+
+        if os.path.isfile(os.path.join(path, CONFIG_NAME)):
+            config_file = os.path.join(path, CONFIG_NAME)
+        else:
+            try:
+                config_file = hf_hub_download(
+                    model_id,
+                    CONFIG_NAME,
+                    **hf_hub_download_kwargs,
+                )
+            except Exception:
+                raise ValueError(f"Can't find '{CONFIG_NAME}' at '{model_id}'")
+
+        loaded_attributes = cls.from_json_file(config_file)
+        return loaded_attributes["peft_type"]
+
+    @classmethod
+    def check_kwargs(cls, **kwargs):
+        """Check kwargs before initializing the config instance.
+
+        Subclasses can override this method to add specific checks.
+
+        """
+        return kwargs
+
+    @property
+    def is_prompt_learning(self) -> bool:
+        r"""
+        Utility method to check if the configuration is for prompt learning.
+        """
+        return False
+
+    @property
+    def is_adaption_prompt(self) -> bool:
+        """Return True if this is an adaption prompt config."""
+        return False
+
+
+@dataclass
+class PeftConfig(PeftConfigMixin):
+    """
+    This is the base configuration class to store the configuration of a [`PeftModel`].
+
+    Args:
+        peft_type (Union[[`~peft.utils.config.PeftType`], `str`]): The type of Peft method to use.
+        task_type (Union[[`~peft.utils.config.TaskType`], `str`]): The type of task to perform.
+        inference_mode (`bool`, defaults to `False`): Whether to use the Peft model in inference mode.
+    """
+
+    base_model_name_or_path: Optional[str] = field(
+        default=None, metadata={"help": "The name of the base model to use."}
+    )
+    revision: Optional[str] = field(default=None, metadata={"help": "The specific base model version to use."})
+    peft_type: Optional[Union[str, PeftType]] = field(default=None, metadata={"help": "Peft type"})
+    task_type: Optional[Union[str, TaskType]] = field(default=None, metadata={"help": "Task type"})
+    inference_mode: bool = field(default=False, metadata={"help": "Whether to use inference mode"})
+
+
+@dataclass
+class PromptLearningConfig(PeftConfig):
+    """
+    This is the base configuration class to store the configuration of [`PrefixTuning`], [`PromptEncoder`], or
+    [`PromptTuning`].
+
+    Args:
+        num_virtual_tokens (`int`): The number of virtual tokens to use.
+        token_dim (`int`): The hidden embedding dimension of the base transformer model.
+        num_transformer_submodules (`int`): The number of transformer submodules in the base transformer model.
+        num_attention_heads (`int`): The number of attention heads in the base transformer model.
+        num_layers (`int`): The number of layers in the base transformer model.
+    """
+
+    num_virtual_tokens: int = field(default=None, metadata={"help": "Number of virtual tokens"})
+    token_dim: int = field(
+        default=None, metadata={"help": "The hidden embedding dimension of the base transformer model"}
+    )
+    num_transformer_submodules: Optional[int] = field(
+        default=None, metadata={"help": "Number of transformer submodules"}
+    )
+    num_attention_heads: Optional[int] = field(default=None, metadata={"help": "Number of attention heads"})
+    num_layers: Optional[int] = field(default=None, metadata={"help": "Number of transformer layers"})
+
+    @property
+    def is_prompt_learning(self) -> bool:
+        r"""
+        Utility method to check if the configuration is for prompt learning.
+        """
+        return True
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/helpers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..225bc5003fa665a9f4dff0ba099f1ab4992d952c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/helpers.py
@@ -0,0 +1,252 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import inspect
+from contextlib import contextmanager
+from copy import deepcopy
+from functools import update_wrapper
+from types import MethodType
+
+from torch import nn
+
+from .peft_model import PeftConfig, PeftModel
+from .tuners.lora import LoraLayer
+
+
+def update_forward_signature(model: PeftModel) -> None:
+    """
+    Updates the forward signature of the PeftModel to include parents class signature
+        model (`PeftModel`): Peft model to update the forward signature
+
+    Example:
+
+    ```python
+    >>> from transformers import WhisperForConditionalGeneration
+    >>> from peft import get_peft_model, LoraConfig, update_forward_signature
+
+    >>> model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
+    >>> peft_config = LoraConfig(r=8, lora_alpha=32, lora_dropout=0.1, target_modules=["q_proj", "v_proj"])
+
+    >>> peft_model = get_peft_model(model, peft_config)
+    >>> update_forward_signature(peft_model)
+    ```
+    """
+
+    # Only update signature when the current forward signature only has *args and **kwargs
+    current_signature = inspect.signature(model.forward)
+    if (
+        len(current_signature.parameters) == 2
+        and "args" in current_signature.parameters
+        and "kwargs" in current_signature.parameters
+    ):
+        forward = deepcopy(model.forward.__func__)
+        update_wrapper(
+            forward, type(model.get_base_model()).forward, assigned=("__doc__", "__name__", "__annotations__")
+        )
+        model.forward = MethodType(forward, model)
+
+
+def update_generate_signature(model: PeftModel) -> None:
+    """
+    Updates the generate signature of a PeftModel with overriding generate to include parents class signature
+        model (`PeftModel`): Peft model to update the generate signature
+
+    Example:
+
+    ```python
+    >>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+    >>> from peft import get_peft_model, LoraConfig, TaskType, update_generate_signature
+
+    >>> model_name_or_path = "bigscience/mt0-large"
+    >>> tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
+    >>> model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+
+    >>> peft_config = LoraConfig(
+    ...     task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1
+    ... )
+    >>> peft_model = get_peft_model(model, peft_config)
+    >>> update_generate_signature(peft_model)
+    >>> help(peft_model.generate)
+    ```
+    """
+    if not hasattr(model, "generate"):
+        return
+    current_signature = inspect.signature(model.generate)
+    if (
+        len(current_signature.parameters) == 2
+        and "args" in current_signature.parameters
+        and "kwargs" in current_signature.parameters
+    ) or (len(current_signature.parameters) == 1 and "kwargs" in current_signature.parameters):
+        generate = deepcopy(model.generate.__func__)
+        update_wrapper(
+            generate,
+            type(model.get_base_model()).generate,
+            assigned=("__doc__", "__name__", "__annotations__"),
+        )
+        model.generate = MethodType(generate, model)
+
+
+def update_signature(model: PeftModel, method: str = "all") -> None:
+    """
+    Updates the signature of a PeftModel include parents class signature for forward or generate method
+        model (`PeftModel`): Peft model to update generate or forward signature method (`str`): method to update
+        signature choose one of "forward", "generate", "all"
+
+    Example:
+    ```python
+    >>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+    >>> from peft import get_peft_model, LoraConfig, TaskType, update_signature
+
+    >>> model_name_or_path = "bigscience/mt0-large"
+    >>> tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
+    >>> model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+
+    >>> peft_config = LoraConfig(
+    ...     task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1
+    ... )
+    >>> peft_model = get_peft_model(model, peft_config)
+    >>> update_signature(peft_model)
+    >>> help(peft_model.generate)
+    ```
+    """
+    if method == "forward":
+        update_forward_signature(model)
+    elif method == "generate":
+        update_generate_signature(model)
+    elif method == "all":
+        update_forward_signature(model)
+        update_generate_signature(model)
+    else:
+        raise ValueError(f"method {method} is not supported please choose one of ['forward', 'generate', 'all']")
+
+
+def check_if_peft_model(model_name_or_path: str) -> bool:
+    """
+    Check if the model is a PEFT model.
+
+    Args:
+        model_name_or_path (`str`):
+            Model id to check, can be local or on the Hugging Face Hub.
+
+    Returns:
+        `bool`: True if the model is a PEFT model, False otherwise.
+    """
+    is_peft_model = True
+    try:
+        PeftConfig.from_pretrained(model_name_or_path)
+    except Exception:
+        # allow broad exceptions so that this works even if new exceptions are added on HF Hub side
+        is_peft_model = False
+
+    return is_peft_model
+
+
+@contextmanager
+def rescale_adapter_scale(model, multiplier):
+    """
+    Context manager to temporarily rescale the scaling of the LoRA adapter in a model.
+
+    The original scaling values are restored when the context manager exits. This context manager works with the
+    transformers and diffusers models that have directly loaded LoRA adapters.
+
+    For LoRA, applying this context manager with multiplier in [0, 1] is strictly equivalent to applying
+    [wise-ft](https://arxiv.org/abs/2109.01903) (see [#1940](https://github.com/huggingface/peft/issues/1940) for
+    details). It can improve the performances of the model if there is a distribution shiftbetween the training data
+    used for fine-tuning, and the test data used during inference.
+
+    Warning: It has been reported that when using Apple's MPS backend for PyTorch, it is necessary to add a short sleep
+        time after exiting the context before the scales are fully restored.
+
+    Args:
+        model: The model containing `LoraLayer` modules whose scaling is to be adjusted.
+        multiplier (float or int):
+            The multiplier that rescales the `scaling` attribute. Must be of type float or int.
+
+    Raises:
+        ValueError: If the model does not contain any `LoraLayer`
+            instances, indicating that the model does not support scaling.
+
+    Example:
+
+    ```python
+    >>> model = ModelWithLoraLayer()
+    >>> multiplier = 0.5
+    >>> with rescale_adapter_scale(model, multiplier):
+    ...     outputs = model(**inputs)  # Perform operations with the scaled model
+    >>> outputs = model(**inputs)  # The original scaling values are restored here
+    ```
+    """
+    # check if multiplier has a valid data type
+    if not isinstance(multiplier, (float, int)):
+        raise TypeError(f"Argument multiplier should be of type float, got {type(multiplier)}")
+
+    # iterate on the model's modules and grab the original scaling attribute
+    # from the lora layers if present
+    original_scaling = {}
+    for module in model.modules():
+        if isinstance(module, LoraLayer):
+            original_scaling[module] = module.scaling.copy()
+            module.scaling = {k: v * multiplier for k, v in module.scaling.items()}
+
+    # check whether scaling is prohibited on model
+    # the original scaling dictionary should be empty
+    # if there were no lora layers
+    if not original_scaling:
+        raise ValueError("scaling is only supported for models with `LoraLayer`s")
+    try:
+        yield
+
+    finally:
+        # restore original scaling values after exiting the context
+        for module, scaling in original_scaling.items():
+            module.scaling = scaling
+
+
+@contextmanager
+def disable_input_dtype_casting(model: nn.Module, active: bool = True):
+    """
+    Context manager disables input dtype casting to the dtype of the weight.
+
+    Currently specifically works for LoRA.
+
+    Parameters:
+        model (nn.Module):
+            The model containing PEFT modules whose input dtype casting is to be adjusted.
+        active (bool):
+            Whether the context manager is active (default) or inactive.
+
+    """
+    # Additional info: Normally, the dtype of the weight and input need to match, which is why the dtype is cast.
+    # However, in certain circumustances, this is handled by forward hooks, e.g. when using layerwise casting in
+    # diffusers. In that case, PEFT casting the dtype interferes with the layerwise casting, which is why the option to
+    # disable it is given.
+    if not active:
+        yield
+        return
+
+    original_values = {}
+    for name, module in model.named_modules():
+        if not isinstance(module, LoraLayer):
+            continue
+        original_values[name] = module.cast_input_dtype_enabled
+        module.cast_input_dtype_enabled = False
+
+    try:
+        yield
+    finally:
+        for name, module in model.named_modules():
+            if not isinstance(module, LoraLayer):
+                continue
+            if name in original_values:
+                module.cast_input_dtype_enabled = original_values[name]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/import_utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/import_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..525a11e4064af189d99b3600629cebd983c6a2eb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/import_utils.py
@@ -0,0 +1,167 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import importlib
+import importlib.metadata as importlib_metadata
+import platform
+from functools import lru_cache
+
+import packaging.version
+import torch
+
+
+@lru_cache
+def is_bnb_available() -> bool:
+    return importlib.util.find_spec("bitsandbytes") is not None
+
+
+@lru_cache
+def is_bnb_4bit_available() -> bool:
+    if not is_bnb_available():
+        return False
+
+    import bitsandbytes as bnb
+
+    return hasattr(bnb.nn, "Linear4bit")
+
+
+@lru_cache
+def is_auto_gptq_available():
+    if importlib.util.find_spec("auto_gptq") is not None:
+        AUTOGPTQ_MINIMUM_VERSION = packaging.version.parse("0.5.0")
+        version_autogptq = packaging.version.parse(importlib_metadata.version("auto_gptq"))
+        if AUTOGPTQ_MINIMUM_VERSION <= version_autogptq:
+            return True
+        else:
+            raise ImportError(
+                f"Found an incompatible version of auto-gptq. Found version {version_autogptq}, "
+                f"but only versions above {AUTOGPTQ_MINIMUM_VERSION} are supported"
+            )
+
+
+@lru_cache
+def is_gptqmodel_available():
+    if importlib.util.find_spec("gptqmodel") is not None:
+        GPTQMODEL_MINIMUM_VERSION = packaging.version.parse("2.0.0")
+        OPTIMUM_MINIMUM_VERSION = packaging.version.parse("1.24.0")
+        version_gptqmodel = packaging.version.parse(importlib_metadata.version("gptqmodel"))
+        if GPTQMODEL_MINIMUM_VERSION <= version_gptqmodel:
+            if is_optimum_available():
+                version_optimum = packaging.version.parse(importlib_metadata.version("optimum"))
+                if OPTIMUM_MINIMUM_VERSION <= version_optimum:
+                    return True
+                else:
+                    raise ImportError(
+                        f"gptqmodel requires optimum version `{OPTIMUM_MINIMUM_VERSION}` or higher. Found version `{version_optimum}`, "
+                        f"but only versions above `{OPTIMUM_MINIMUM_VERSION}` are supported"
+                    )
+            else:
+                raise ImportError(
+                    f"gptqmodel requires optimum version `{OPTIMUM_MINIMUM_VERSION}` or higher to be installed."
+                )
+        else:
+            raise ImportError(
+                f"Found an incompatible version of gptqmodel. Found version `{version_gptqmodel}`, "
+                f"but only versions above `{GPTQMODEL_MINIMUM_VERSION}` are supported"
+            )
+
+
+@lru_cache
+def is_optimum_available() -> bool:
+    return importlib.util.find_spec("optimum") is not None
+
+
+@lru_cache
+def is_torch_tpu_available(check_device=True):
+    "Checks if `torch_xla` is installed and potentially if a TPU is in the environment"
+    if importlib.util.find_spec("torch_xla") is not None:
+        if check_device:
+            # We need to check if `xla_device` can be found, will raise a RuntimeError if not
+            try:
+                import torch_xla.core.xla_model as xm
+
+                _ = xm.xla_device()
+                return True
+            except RuntimeError:
+                return False
+        return True
+    return False
+
+
+@lru_cache
+def is_aqlm_available():
+    return importlib.util.find_spec("aqlm") is not None
+
+
+@lru_cache
+def is_auto_awq_available():
+    return importlib.util.find_spec("awq") is not None
+
+
+@lru_cache
+def is_eetq_available():
+    return importlib.util.find_spec("eetq") is not None
+
+
+@lru_cache
+def is_hqq_available():
+    return importlib.util.find_spec("hqq") is not None
+
+
+@lru_cache
+def is_torchao_available():
+    if importlib.util.find_spec("torchao") is None:
+        return False
+
+    TORCHAO_MINIMUM_VERSION = packaging.version.parse("0.4.0")
+    try:
+        torchao_version = packaging.version.parse(importlib_metadata.version("torchao"))
+    except importlib_metadata.PackageNotFoundError:
+        # Same idea as in diffusers:
+        # https://github.com/huggingface/diffusers/blob/9f06a0d1a4a998ac6a463c5be728c892f95320a8/src/diffusers/utils/import_utils.py#L351-L357
+        # It's not clear under what circumstances `importlib_metadata.version("torchao")` can raise an error even
+        # though `importlib.util.find_spec("torchao") is not None` but it has been observed, so adding this for
+        # precaution.
+        return False
+
+    if torchao_version < TORCHAO_MINIMUM_VERSION:
+        raise ImportError(
+            f"Found an incompatible version of torchao. Found version {torchao_version}, "
+            f"but only versions above {TORCHAO_MINIMUM_VERSION} are supported"
+        )
+    return True
+
+
+@lru_cache
+def is_xpu_available(check_device=False):
+    """
+    Checks if XPU acceleration is available and potentially if a XPU is in the environment
+    """
+
+    system = platform.system()
+    if system == "Darwin":
+        return False
+    else:
+        if check_device:
+            try:
+                # Will raise a RuntimeError if no XPU is found
+                _ = torch.xpu.device_count()
+                return torch.xpu.is_available()
+            except RuntimeError:
+                return False
+        return hasattr(torch, "xpu") and torch.xpu.is_available()
+
+
+@lru_cache
+def is_diffusers_available():
+    return importlib.util.find_spec("diffusers") is not None
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mapping.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mapping.py
new file mode 100644
index 0000000000000000000000000000000000000000..a92b28f8589cda791d5887a141f95e1408d42b34
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mapping.py
@@ -0,0 +1,78 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any
+
+import torch
+
+from .utils import PeftType
+
+
+if TYPE_CHECKING:
+    from .config import PeftConfig
+    from .tuners.tuners_utils import BaseTuner
+
+
+# these will be filled by the register_peft_method function
+PEFT_TYPE_TO_CONFIG_MAPPING: dict[PeftType, type[PeftConfig]] = {}
+PEFT_TYPE_TO_TUNER_MAPPING: dict[PeftType, type[BaseTuner]] = {}
+PEFT_TYPE_TO_MIXED_MODEL_MAPPING: dict[PeftType, type[BaseTuner]] = {}
+PEFT_TYPE_TO_PREFIX_MAPPING: dict[PeftType, str] = {}
+
+
+def get_peft_config(config_dict: dict[str, Any]) -> PeftConfig:
+    """
+    Returns a Peft config object from a dictionary.
+
+    Args:
+        config_dict (`Dict[str, Any]`): Dictionary containing the configuration parameters.
+    """
+
+    return PEFT_TYPE_TO_CONFIG_MAPPING[config_dict["peft_type"]](**config_dict)
+
+
+def inject_adapter_in_model(
+    peft_config: PeftConfig, model: torch.nn.Module, adapter_name: str = "default", low_cpu_mem_usage: bool = False
+) -> torch.nn.Module:
+    r"""
+    A simple API to create and inject adapter in-place into a model. Currently the API does not support prompt learning
+    methods and adaption prompt. Make sure to have the correct `target_names` set in the `peft_config` object. The API
+    calls `get_peft_model` under the hood but would be restricted only to non-prompt learning methods.
+
+    Args:
+        peft_config (`PeftConfig`):
+            Configuration object containing the parameters of the Peft model.
+        model (`torch.nn.Module`):
+            The input model where the adapter will be injected.
+        adapter_name (`str`, `optional`, defaults to `"default"`):
+            The name of the adapter to be injected, if not provided, the default adapter name is used ("default").
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+    """
+    if peft_config.is_prompt_learning or peft_config.is_adaption_prompt:
+        raise ValueError("`create_and_replace` does not support prompt learning and adaption prompt yet.")
+
+    if peft_config.peft_type not in PEFT_TYPE_TO_TUNER_MAPPING.keys():
+        raise ValueError(
+            f"`inject_adapter_in_model` does not support {peft_config.peft_type} yet. Please use `get_peft_model`."
+        )
+
+    tuner_cls = PEFT_TYPE_TO_TUNER_MAPPING[peft_config.peft_type]
+
+    # By instantiating a peft model we are injecting randomly initialized LoRA layers into the model's modules.
+    peft_model = tuner_cls(model, peft_config, adapter_name=adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    return peft_model.model
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mapping_func.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mapping_func.py
new file mode 100644
index 0000000000000000000000000000000000000000..279ce499d1e857d68d963467c01b5b272a3369e6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mapping_func.py
@@ -0,0 +1,129 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import warnings
+from typing import Optional
+
+from transformers import PreTrainedModel
+
+from .auto import MODEL_TYPE_TO_PEFT_MODEL_MAPPING
+from .config import PeftConfig
+from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING, PEFT_TYPE_TO_PREFIX_MAPPING
+from .mixed_model import PeftMixedModel
+from .peft_model import PeftModel
+from .tuners.tuners_utils import BaseTuner, BaseTunerLayer
+from .utils import _prepare_prompt_learning_config
+
+
+def get_peft_model(
+    model: PreTrainedModel,
+    peft_config: PeftConfig,
+    adapter_name: str = "default",
+    mixed: bool = False,
+    autocast_adapter_dtype: bool = True,
+    revision: Optional[str] = None,
+    low_cpu_mem_usage: bool = False,
+) -> PeftModel | PeftMixedModel:
+    """
+    Returns a Peft model object from a model and a config, where the model will be modified in-place.
+
+    Args:
+        model ([`transformers.PreTrainedModel`]):
+            Model to be wrapped.
+        peft_config ([`PeftConfig`]):
+            Configuration object containing the parameters of the Peft model.
+        adapter_name (`str`, `optional`, defaults to `"default"`):
+            The name of the adapter to be injected, if not provided, the default adapter name is used ("default").
+        mixed (`bool`, `optional`, defaults to `False`):
+            Whether to allow mixing different (compatible) adapter types.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 or bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+        revision (`str`, `optional`, defaults to `main`):
+            The revision of the base model. If this isn't set, the saved peft model will load the `main` revision for
+            the base model
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process. Leave this setting as
+            False if you intend on training the model, unless the adapter weights will be replaced by different weights
+            before training starts.
+    """
+    model_config = BaseTuner.get_model_config(model)
+    old_name = peft_config.base_model_name_or_path
+    new_name = model.__dict__.get("name_or_path", None)
+    peft_config.base_model_name_or_path = new_name
+
+    # Especially in notebook environments there could be a case that a user wants to experiment with different
+    # configuration values. However, it is likely that there won't be any changes for new configs on an already
+    # initialized PEFT model. The best we can do is warn the user about it.
+    if any(isinstance(module, BaseTunerLayer) for module in model.modules()):
+        warnings.warn(
+            "You are trying to modify a model with PEFT for a second time. If you want to reload the model with a "
+            "different config, make sure to call `.unload()` before."
+        )
+
+    if (old_name is not None) and (old_name != new_name):
+        warnings.warn(
+            f"The PEFT config's `base_model_name_or_path` was renamed from '{old_name}' to '{new_name}'. "
+            "Please ensure that the correct base model is loaded when loading this checkpoint."
+        )
+
+    if revision is not None:
+        if peft_config.revision is not None and peft_config.revision != revision:
+            warnings.warn(
+                f"peft config has already set base model revision to {peft_config.revision}, overwriting with revision {revision}"
+            )
+        peft_config.revision = revision
+
+    if (
+        (isinstance(peft_config, PEFT_TYPE_TO_CONFIG_MAPPING["LORA"]))
+        and (peft_config.init_lora_weights == "eva")
+        and not low_cpu_mem_usage
+    ):
+        warnings.warn(
+            "lora with eva initialization used with low_cpu_mem_usage=False. "
+            "Setting low_cpu_mem_usage=True can improve the maximum batch size possible for eva initialization."
+        )
+
+    prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(peft_config.peft_type)
+    if prefix and adapter_name in prefix:
+        warnings.warn(
+            f"Adapter name {adapter_name} should not be contained in the prefix {prefix}."
+            "This may lead to reinitialization of the adapter weights during loading."
+        )
+
+    if mixed:
+        # note: PeftMixedModel does not support autocast_adapter_dtype, so don't pass it
+        return PeftMixedModel(model, peft_config, adapter_name=adapter_name)
+
+    if peft_config.task_type not in MODEL_TYPE_TO_PEFT_MODEL_MAPPING.keys() and not peft_config.is_prompt_learning:
+        return PeftModel(
+            model,
+            peft_config,
+            adapter_name=adapter_name,
+            autocast_adapter_dtype=autocast_adapter_dtype,
+            low_cpu_mem_usage=low_cpu_mem_usage,
+        )
+
+    if peft_config.is_prompt_learning:
+        peft_config = _prepare_prompt_learning_config(peft_config, model_config)
+    return MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type](
+        model,
+        peft_config,
+        adapter_name=adapter_name,
+        autocast_adapter_dtype=autocast_adapter_dtype,
+        low_cpu_mem_usage=low_cpu_mem_usage,
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mixed_model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mixed_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..5aa1e58a4e050a23bcdd3dea2c994effd76e58e5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/mixed_model.py
@@ -0,0 +1,465 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import os
+from contextlib import contextmanager
+from typing import Any, Optional, Union
+
+import torch
+from accelerate.hooks import remove_hook_from_submodules
+from torch import nn
+from transformers.utils import PushToHubMixin
+
+from peft.utils.constants import DUMMY_MODEL_CONFIG
+
+from .config import PeftConfig
+from .peft_model import PeftModel
+from .tuners import MixedModel
+from .utils import _set_adapter, _set_trainable
+
+
+def _prepare_model_for_gradient_checkpointing(model: nn.Module) -> None:
+    r"""
+    Prepares the model for gradient checkpointing if necessary
+    """
+    # Note: same as PeftModel._prepare_model_for_gradient_checkpointing
+    if not getattr(model, "is_gradient_checkpointing", True):
+        return model
+
+    if not (
+        getattr(model, "is_loaded_in_8bit", False)
+        or getattr(model, "is_loaded_in_4bit", False)
+        or getattr(model, "is_quantized", False)
+    ):
+        if hasattr(model, "enable_input_require_grads"):
+            model.enable_input_require_grads()
+        elif hasattr(model, "get_input_embeddings"):
+
+            def make_inputs_require_grad(module, input, output):
+                output.requires_grad_(True)
+
+            model.get_input_embeddings().register_forward_hook(make_inputs_require_grad)
+
+
+def _check_config_compatible(peft_config: PeftConfig) -> None:
+    from .tuners.mixed import COMPATIBLE_TUNER_TYPES
+
+    if peft_config.peft_type not in COMPATIBLE_TUNER_TYPES:
+        raise ValueError(
+            f"The provided `peft_type` '{peft_config.peft_type.value}' is not compatible with the `PeftMixedModel`. "
+            f"Compatible types are: {COMPATIBLE_TUNER_TYPES}"
+        )
+
+
+class PeftMixedModel(PushToHubMixin, torch.nn.Module):
+    """
+    PeftMixedModel for loading mixing different types of adapters for inference.
+
+    This class does not support loading/saving, and it shouldn't usually be initialized directly. Instead, use
+    `get_peft_model` with the argument `mixed=True`.
+
+    
+
+    Read the [Mixed adapter types](https://huggingface.co/docs/peft/en/developer_guides/mixed_models) guide to learn
+    more about using different adapter types.
+
+    
+
+    Example:
+
+    ```py
+    >>> base_model = ...  # load the base model, e.g. from transformers
+    >>> peft_model = PeftMixedModel.from_pretrained(base_model, path_to_adapter1, "adapter1").eval()
+    >>> peft_model.load_adapter(path_to_adapter2, "adapter2")
+    >>> peft_model.set_adapter(["adapter1", "adapter2"])  # activate both adapters
+    >>> peft_model(data)  # forward pass using both adapters
+    ```
+
+    Args:
+        model (`torch.nn.Module`):
+            The model to be tuned.
+        config (`PeftConfig`):
+            The config of the model to be tuned. The adapter type must be compatible.
+        adapter_name (`str`, `optional`, defaults to `"default"`):
+            The name of the first adapter.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+    """
+
+    def __init__(self, model: nn.Module, peft_config: PeftConfig, adapter_name: str = "default") -> None:
+        super().__init__()
+        _check_config_compatible(peft_config)
+        _prepare_model_for_gradient_checkpointing(model)
+        self.modules_to_save = None
+        self.base_model = MixedModel(model, {adapter_name: peft_config}, adapter_name)
+        self.set_modules_to_save(peft_config, adapter_name)
+
+        self.config = getattr(model, "config", DUMMY_MODEL_CONFIG)
+
+        # the `pretraining_tp` is set for some models to simulate Tensor Parallelism during inference to avoid
+        # numerical differences, https://github.com/pytorch/pytorch/issues/76232 - to avoid any unexpected
+        # behavior we disable that in this line.
+        if hasattr(self.base_model, "config") and hasattr(self.base_model.config, "pretraining_tp"):
+            self.base_model.config.pretraining_tp = 1
+
+    @property
+    def peft_config(self) -> dict[str, PeftConfig]:
+        return self.base_model.peft_config
+
+    @property
+    def active_adapter(self) -> str:
+        return self.base_model.active_adapter
+
+    @property
+    def active_adapters(self) -> list[str]:
+        return self.base_model.active_adapters
+
+    def get_nb_trainable_parameters(self):
+        r"""
+        Returns the number of trainable parameters and number of all parameters in the model.
+        """
+        # note: same as PeftModel.get_nb_trainable_parameters
+        trainable_params = 0
+        all_param = 0
+        for _, param in self.named_parameters():
+            num_params = param.numel()
+            # if using DS Zero 3 and the weights are initialized empty
+            if num_params == 0 and hasattr(param, "ds_numel"):
+                num_params = param.ds_numel
+
+            # Due to the design of 4bit linear layers from bitsandbytes
+            # one needs to multiply the number of parameters by 2 to get
+            # the correct number of parameters
+            if param.__class__.__name__ == "Params4bit":
+                num_params = num_params * 2
+
+            all_param += num_params
+            if param.requires_grad:
+                trainable_params += num_params
+
+        return trainable_params, all_param
+
+    def print_trainable_parameters(self):
+        """
+        Prints the number of trainable parameters in the model.
+
+        Note: print_trainable_parameters() uses get_nb_trainable_parameters() which is different from
+        num_parameters(only_trainable=True) from huggingface/transformers. get_nb_trainable_parameters() returns
+        (trainable parameters, all parameters) of the Peft Model which includes modified backbone transformer model.
+        For techniques like LoRA, the backbone transformer model is modified in place with LoRA modules. However, for
+        prompt tuning, the backbone transformer model is unmodified. num_parameters(only_trainable=True) returns number
+        of trainable parameters of the backbone transformer model which can be different.
+        """
+        # note: same as PeftModel.print_trainable_parameters
+        trainable_params, all_param = self.get_nb_trainable_parameters()
+
+        print(
+            f"trainable params: {trainable_params:,d} || "
+            f"all params: {all_param:,d} || "
+            f"trainable%: {100 * trainable_params / all_param:.4f}"
+        )
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "base_model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.base_model, name)
+
+    def forward(self, *args: Any, **kwargs: Any):
+        """
+        Forward pass of the model.
+        """
+        return self.base_model(*args, **kwargs)
+
+    def generate(self, *args: Any, **kwargs: Any):
+        """
+        Generate output.
+        """
+        return self.base_model.generate(*args, **kwargs)
+
+    @contextmanager
+    def disable_adapter(self):
+        """
+        Disables the adapter module.
+        """
+        try:
+            self.base_model.disable_adapter_layers()
+            yield
+        finally:
+            self.base_model.enable_adapter_layers()
+
+    def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None:
+        """
+        Add an adapter to the model based on the passed configuration.
+
+        This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`].
+
+        The name for the new adapter should be unique.
+
+        The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active
+        adapter.
+
+        Args:
+            adapter_name (`str`):
+                The name of the adapter to be added.
+            peft_config ([`PeftConfig`]):
+                The configuration of the adapter to be added.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device. Useful to speed up the process when loading saved
+                adapters.
+
+                
+
+                Don't use `low_cpu_mem_usage=True` when creating a new PEFT adapter for training (training is untested
+                and discouraged for PeftMixedModel in general).
+
+                
+        """
+        _check_config_compatible(peft_config)
+
+        try:
+            self.peft_config[adapter_name] = peft_config
+            self.base_model.inject_adapter(self, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+        except Exception:  # something went wrong, roll back
+            if adapter_name in self.peft_config:
+                del self.peft_config[adapter_name]
+            raise
+
+        self.set_modules_to_save(peft_config, adapter_name)
+
+    def set_modules_to_save(self, peft_config: PeftConfig, adapter_name: str) -> None:
+        if (modules_to_save := getattr(peft_config, "modules_to_save", None)) is None:
+            return
+
+        if self.modules_to_save is None:
+            self.modules_to_save = set(modules_to_save)
+        else:
+            self.modules_to_save.update(modules_to_save)
+        _set_trainable(self, adapter_name, module_names=peft_config.modules_to_save)
+
+    def set_adapter(self, adapter_name: Union[str, list[str]]) -> None:
+        """
+        Sets the active adapter(s) for the model.
+
+        Note that the order in which the adapters are applied during the forward pass may not be the same as the order
+        in which they are passed to this function. Instead, the order during the forward pass is determined by the
+        order in which the adapters were loaded into the model. The active adapters only determine which adapters are
+        active during the forward pass, but not the order in which they are applied.
+
+        Additionally, this function will set the specified adapters to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str` or `List[str]`):
+                The name of the adapter(s) to be activated.
+        """
+        if isinstance(adapter_name, str):
+            adapter_name = [adapter_name]
+
+        mismatched = set(adapter_name) - set(self.peft_config.keys())
+        if mismatched:
+            raise ValueError(
+                f"Adapter(s) {sorted(mismatched)} not found, available adapters: {sorted(self.peft_config.keys())}"
+            )
+
+        self.base_model.set_adapter(adapter_name)
+        _set_adapter(self, adapter_name)
+
+    def delete_adapter(self, adapter_name: Union[str, list[str]]) -> None:
+        if isinstance(adapter_name, str):
+            adapter_name = [adapter_name]
+
+        mismatched = set(adapter_name) - set(self.peft_config.keys())
+        if mismatched:
+            raise ValueError(
+                f"Adapter(s) {sorted(mismatched)} not found, available adapters: {sorted(self.peft_config.keys())}"
+            )
+
+        self.base_model.delete_adapter(adapter_name)
+
+    def merge_and_unload(self, *args: Any, **kwargs: Any):
+        r"""
+        This method merges the adapter layers into the base model. This is needed if someone wants to use the base
+        model as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        return self.base_model.merge_and_unload(*args, **kwargs)
+
+    def unload(self, *args: Any, **kwargs: Any):
+        """
+        Gets back the base model by removing all the adapter modules without merging. This gives back the original base
+        model.
+        """
+        return self.base_model.unload(*args, **kwargs)
+
+    def get_layer_status(self):
+        raise TypeError(f"get_layer_status is not supported for {self.__class__.__name__}.")
+
+    def get_model_status(self):
+        raise TypeError(f"get_model_status is not supported for {self.__class__.__name__}.")
+
+    @classmethod
+    def _split_kwargs(cls, kwargs: dict[str, Any]):
+        return PeftModel._split_kwargs(kwargs)
+
+    def _check_new_adapter_config(self, peft_config: PeftConfig, is_trainable: bool) -> None:
+        return PeftModel._check_new_adapter_config(self, peft_config, is_trainable=is_trainable)
+
+    def load_adapter(self, model_id: str, adapter_name: str, *args: Any, **kwargs: Any):
+        """
+        Load a trained adapter into the model.
+
+        The name for the new adapter should be unique.
+
+        The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active
+        adapter.
+
+        Args:
+            adapter_name (`str`):
+                The name of the adapter to be added.
+            peft_config ([`PeftConfig`]):
+                The configuration of the adapter to be added.
+            is_trainable (`bool`, *optional*, defaults to `False`):
+                Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and can only be
+                used for inference.
+            torch_device (`str`, *optional*, defaults to None):
+                The device to load the adapter on. If `None`, the device will be inferred.
+            autocast_adapter_dtype (`bool`, *optional*, defaults to `True`):
+                Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter
+                weights using float16 and bfloat16 to float32, as this is typically required for stable training, and
+                only affect select PEFT tuners.
+            ephemeral_gpu_offload (`bool`, *optional*, defaults to `False`):
+                Whether to use ephemeral GPU offloading for partially loaded modules. Defaults to `False`.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the
+                process.
+            kwargs: (`optional`):
+                Additional arguments to modify the way the adapter is loaded, e.g. the token for Hugging Face Hub.
+        """
+        # the low_cpu_mem_usage option is handled through kwargs
+        output = PeftModel.load_adapter(self, model_id, adapter_name, *args, **kwargs)
+        # TODO: not quite clear why this is necessary but tests fail without it
+        self.set_adapter(self.active_adapters)
+        return output
+
+    def create_or_update_model_card(self, output_dir: str):
+        raise NotImplementedError(f"Model card creation is not supported for {self.__class__.__name__} (yet).")
+
+    def save_pretrained(
+        self,
+        save_directory: str,
+        safe_serialization: bool = False,
+        selected_adapters: Optional[list[str]] = None,
+        **kwargs: Any,
+    ):
+        raise NotImplementedError(f"Saving is not supported for {self.__class__.__name__} (yet).")
+
+    @classmethod
+    def from_pretrained(
+        cls,
+        model: nn.Module,
+        model_id: str | os.PathLike,
+        adapter_name: str = "default",
+        is_trainable: bool = False,
+        config: Optional[PeftConfig] = None,
+        **kwargs: Any,
+    ):
+        r"""
+        Instantiate a PEFT mixed model from a pretrained model and loaded PEFT weights.
+
+        Note that the passed `model` may be modified inplace.
+
+        Args:
+            model (`nn.Module`):
+                The model to be adapted.
+            model_id (`str` or `os.PathLike`):
+                The name of the PEFT configuration to use. Can be either:
+                    - A string, the `model id` of a PEFT configuration hosted inside a model repo on the Hugging Face
+                      Hub.
+                    - A path to a directory containing a PEFT configuration file saved using the `save_pretrained`
+                      method (`./my_peft_config_directory/`).
+            adapter_name (`str`, *optional*, defaults to `"default"`):
+                The name of the adapter to be loaded. This is useful for loading multiple adapters.
+            is_trainable (`bool`, *optional*, defaults to `False`):
+                Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and use for
+                inference
+            config ([`~peft.PeftConfig`], *optional*):
+                The configuration object to use instead of an automatically loaded configuration. This configuration
+                object is mutually exclusive with `model_id` and `kwargs`. This is useful when configuration is already
+                loaded before calling `from_pretrained`.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the
+                process.
+            kwargs: (`optional`):
+                Additional keyword arguments passed along to the specific PEFT configuration class.
+        """
+        # note: adapted from PeftModel.from_pretrained
+        from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING, PEFT_TYPE_TO_MIXED_MODEL_MAPPING
+
+        # load the config
+        if config is None:
+            config = PEFT_TYPE_TO_CONFIG_MAPPING[
+                PeftConfig._get_peft_type(
+                    model_id,
+                    subfolder=kwargs.get("subfolder", None),
+                    revision=kwargs.get("revision", None),
+                    cache_dir=kwargs.get("cache_dir", None),
+                    use_auth_token=kwargs.get("use_auth_token", None),
+                )
+            ].from_pretrained(model_id, **kwargs)
+        elif isinstance(config, PeftConfig):
+            config.inference_mode = not is_trainable
+        else:
+            raise ValueError(f"The input config must be a PeftConfig, got {config.__class__}")
+
+        # note: this is different from PeftModel.from_pretrained
+        if config.peft_type not in PEFT_TYPE_TO_MIXED_MODEL_MAPPING:
+            raise ValueError(f"Adapter of type {config.peft_type} is not supported for mixed models.")
+
+        if (getattr(model, "hf_device_map", None) is not None) and len(
+            set(model.hf_device_map.values()).intersection({"cpu", "disk"})
+        ) > 0:
+            remove_hook_from_submodules(model)
+
+        if config.is_prompt_learning and is_trainable:
+            # note: should not be possible to reach, but just in case
+            raise ValueError("Cannot set a prompt learning adapter to trainable when loading pretrained adapter.")
+        else:
+            config.inference_mode = not is_trainable
+
+        # note: this is different from PeftModel.from_pretrained, we always return a PeftMixedModel
+        model = cls(model, config, adapter_name)
+        # the low_cpu_mem_usage option is handled through kwargs
+        model.load_adapter(model_id, adapter_name, is_trainable=is_trainable, **kwargs)
+        return model
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/optimizers/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/optimizers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..98ad65c55432934af97b77c69626ac4f757c6a6a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/optimizers/__init__.py
@@ -0,0 +1,18 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from .loraplus import create_loraplus_optimizer
+
+
+__all__ = ["create_loraplus_optimizer"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/optimizers/loraplus.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/optimizers/loraplus.py
new file mode 100644
index 0000000000000000000000000000000000000000..0c4bd7d1e0b238bba692055f050e60b740f58107
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/optimizers/loraplus.py
@@ -0,0 +1,121 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+This module contains the implementation of the LoraPlus optimizer.
+"""
+
+from __future__ import annotations
+
+from operator import attrgetter
+
+import torch.nn as nn
+from torch.optim import Optimizer
+from transformers.pytorch_utils import ALL_LAYERNORM_LAYERS
+from transformers.trainer_pt_utils import get_parameter_names
+
+from ..peft_model import PeftModel
+from ..tuners.lora.layer import Embedding
+
+
+def create_loraplus_optimizer(
+    model: PeftModel, optimizer_cls: type[Optimizer], *, lr: float, loraplus_lr_ratio: float, **kwargs
+) -> Optimizer:
+    """
+    Creates a LoraPlus optimizer.
+
+    Efficient Low Rank Adaptation of Large Models: https://arxiv.org/abs/2402.12354
+
+    Reference: https://github.com/nikhil-ghosh-berkeley/loraplus/
+
+    Args:
+        model (`torch.nn.Module`): The model to be optimized.
+        optimizer_cls (`torch.optim.Optimizer`): The optimizer class to be used.
+        lr (`float`): The learning rate to be used for the optimizer.
+        loraplus_lr_ratio (`float`):
+            The ratio of learning ηB/ηA where ηA (lr) is passed in as the optimizer learning rate. Should be ≥1. Should
+            be set in tandem with the optimizer learning rate (lr); should be larger when the task is more difficult
+            and the model needs to update its features to learn well. In this case, it helps to make the learning rate
+            slightly smaller (e.g., by a factor of 2) than typical vanilla LoRA learning rates
+        loraplus_lr_embedding (optional `float`):
+            If LoRA modules are added to embedding layers your can specify a different learning rate for them. Default
+            value 1e-6.
+        kwargs (`dict`): Additional keyword arguments to be passed to the optimizer.
+
+    Returns:
+        `torch.optim.Optimizer`: An instance of the specified optimizer class configured with the model's parameters
+        organized into groups with custom learning rates.
+    """
+
+    decay_parameters = get_parameter_names(model, ALL_LAYERNORM_LAYERS)
+    decay_parameters = [name for name in decay_parameters if "bias" not in name]
+    param_groups = {
+        "groupA": {},
+        "groupB": {},
+        "groupB_no_decay": {},
+        "embedding": {},
+    }
+
+    for name, param in model.named_parameters():
+        if not param.requires_grad:
+            continue
+
+        module = attrgetter(name)(model)
+        if isinstance(module, Embedding):
+            param_groups["embedding"][name] = param
+        elif "lora_B" in name or param.ndim == 1:
+            if name in decay_parameters:
+                param_groups["groupB"][name] = param
+            else:
+                param_groups["groupB_no_decay"][name] = param
+        else:
+            param_groups["groupA"][name] = param
+
+    kwargs["lr"] = lr
+    loraplus_weight_decay = kwargs.pop("loraplus_weight_decay", 0.0)
+    loraplus_lr_embedding = kwargs.pop("loraplus_lr_embedding", 1e-6)
+
+    optimizer_grouped_parameters = [
+        {
+            "params": list(param_groups["groupA"].values()),
+            "weight_decay": loraplus_weight_decay,
+            "lr": lr,
+        },
+        {
+            "params": list(param_groups["embedding"].values()),
+            "weight_decay": loraplus_weight_decay,
+            "lr": loraplus_lr_embedding,
+        },
+        {
+            "params": list(param_groups["groupB"].values()),
+            "weight_decay": loraplus_weight_decay,
+            "lr": lr * loraplus_lr_ratio,
+        },
+        {
+            "params": list(param_groups["groupB_no_decay"].values()),
+            "weight_decay": 0.0,
+            "lr": lr * loraplus_lr_ratio,
+        },
+    ]
+
+    optimizer = optimizer_cls(optimizer_grouped_parameters, **kwargs)
+    eight_bit_names = ["Adam8bit", "AdamW8bit", "PagedAdam8bit", "PagedAdamW8bit"]
+    if optimizer_cls.__name__ in eight_bit_names:
+        import bitsandbytes
+
+        manager = bitsandbytes.optim.GlobalOptimManager.get_instance()
+        for module in model.modules():
+            if isinstance(module, nn.Embedding):
+                manager.register_module_override(module, "weight", {"optim_bits": 32})
+    return optimizer
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/peft_model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/peft_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..61020ae47f65a5ee023be25810dfa0ae5d1b4ad2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/peft_model.py
@@ -0,0 +1,3099 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import collections
+import copy
+import inspect
+import os
+import warnings
+from contextlib import contextmanager, nullcontext
+from copy import deepcopy
+from dataclasses import dataclass
+from typing import Any, Literal, Optional, Union
+
+import packaging.version
+import torch
+import transformers
+from accelerate import dispatch_model, infer_auto_device_map
+from accelerate.hooks import AlignDevicesHook, add_hook_to_module, remove_hook_from_submodules
+from accelerate.utils import get_balanced_memory, named_module_tensors
+from huggingface_hub import HfFileSystem, ModelCard, ModelCardData, hf_hub_download
+from safetensors import safe_open
+from safetensors.torch import save_file as safe_save_file
+from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
+from transformers import Cache, DynamicCache, EncoderDecoderCache, PreTrainedModel
+from transformers.modeling_outputs import QuestionAnsweringModelOutput, SequenceClassifierOutput, TokenClassifierOutput
+from transformers.utils import PushToHubMixin
+
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer
+from peft.utils.constants import DUMMY_MODEL_CONFIG
+from peft.utils.integrations import init_empty_weights
+from peft.utils.other import TrainableTokensWrapper
+
+from . import __version__
+from .config import PeftConfig
+from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING, PEFT_TYPE_TO_PREFIX_MAPPING, PEFT_TYPE_TO_TUNER_MAPPING
+from .utils import (
+    SAFETENSORS_WEIGHTS_NAME,
+    TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING,
+    WEIGHTS_NAME,
+    PeftType,
+    TaskType,
+    _get_batch_size,
+    _get_input_embeddings_name,
+    _prepare_prompt_learning_config,
+    _set_adapter,
+    _set_trainable,
+    get_peft_model_state_dict,
+    id_tensor_storage,
+    infer_device,
+    load_peft_weights,
+    map_cache_to_layer_device_map,
+    set_peft_model_state_dict,
+    shift_tokens_right,
+)
+
+
+class PeftModel(PushToHubMixin, torch.nn.Module):
+    """
+    Base model encompassing various Peft methods.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): The base transformer model used for Peft.
+        peft_config ([`PeftConfig`]): The configuration of the Peft model.
+        adapter_name (`str`,  *optional*): The name of the adapter, defaults to `"default"`.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading loading process.
+
+            
+
+            Don't use `low_cpu_mem_usage=True` when creating a new PEFT adapter for training.
+
+            
+
+    **Attributes**:
+        - **base_model** ([`torch.nn.Module`]) -- The base transformer model used for Peft.
+        - **peft_config** ([`PeftConfig`]) -- The configuration of the Peft model.
+        - **modules_to_save** (`list` of `str`) -- The list of sub-module names to save when
+            saving the model.
+        - **prompt_encoder** ([`PromptEncoder`]) -- The prompt encoder used for Peft if
+            using [`PromptLearningConfig`].
+        - **prompt_tokens** (`torch.Tensor`) -- The virtual prompt tokens used for Peft if
+            using [`PromptLearningConfig`].
+        - **transformer_backbone_name** (`str`) -- The name of the transformer
+            backbone in the base model if using [`PromptLearningConfig`].
+        - **word_embeddings** (`torch.nn.Embedding`) -- The word embeddings of the transformer backbone
+            in the base model if using [`PromptLearningConfig`].
+    """
+
+    def __init__(
+        self,
+        model: PreTrainedModel,
+        peft_config: PeftConfig,
+        adapter_name: str = "default",
+        autocast_adapter_dtype: bool = True,
+        low_cpu_mem_usage: bool = False,
+    ) -> None:
+        super().__init__()
+        self.modules_to_save = None
+        self.active_adapter = adapter_name
+        self.peft_type = peft_config.peft_type
+        # These args are special PEFT arguments that users can pass. They need to be removed before passing them to
+        # forward.
+        self.special_peft_forward_args = {"adapter_names"}
+
+        self._is_prompt_learning = peft_config.is_prompt_learning
+        if self._is_prompt_learning:
+            self._peft_config = {adapter_name: peft_config}
+            self.base_model = model
+            self.add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage)
+        else:
+            self._peft_config = None
+            cls = PEFT_TYPE_TO_TUNER_MAPPING[peft_config.peft_type]
+            ctx = init_empty_weights if low_cpu_mem_usage else nullcontext
+            with ctx():
+                self.base_model = cls(model, {adapter_name: peft_config}, adapter_name)
+
+        self.set_additional_trainable_modules(peft_config, adapter_name)
+
+        if hasattr(self.base_model, "_cast_adapter_dtype"):
+            self.base_model._cast_adapter_dtype(
+                adapter_name=adapter_name, autocast_adapter_dtype=autocast_adapter_dtype
+            )
+
+        if getattr(model, "is_gradient_checkpointing", True):
+            model = self._prepare_model_for_gradient_checkpointing(model)
+
+        # the `pretraining_tp` is set for some models to simulate Tensor Parallelism during inference to avoid
+        # numerical differences, https://github.com/pytorch/pytorch/issues/76232 - to avoid any unexpected
+        # behavior we disable that in this line.
+        if hasattr(self.base_model, "config") and hasattr(self.base_model.config, "pretraining_tp"):
+            self.base_model.config.pretraining_tp = 1
+
+    @property
+    def peft_config(self) -> dict[str, PeftConfig]:
+        if self._is_prompt_learning:
+            return self._peft_config
+        return self.base_model.peft_config
+
+    @property
+    def active_adapters(self) -> list[str]:
+        try:
+            adapters = self.base_model.active_adapters
+            if not isinstance(adapters, list):
+                # Base model is probably a transformers model, see:
+                # https://github.com/huggingface/transformers/pull/30790#issuecomment-2253808249
+                # Unfortunately, transformers models also have an active_adapters method but it's 1) not a property and
+                # 2) calling it fails because the base model (usually) has no loaded adapter. The base model can be a
+                # transformers model for prompt learning, where the base model is not wrapped in a LoraModel or similar.
+                adapters = self.active_adapter
+                if isinstance(adapters, str):
+                    adapters = [adapters]
+        except AttributeError:
+            adapters = self.active_adapter
+            if isinstance(adapters, str):
+                adapters = [adapters]
+        return adapters
+
+    @peft_config.setter
+    def peft_config(self, value: dict[str, PeftConfig]):
+        if self._is_prompt_learning:
+            self._peft_config = value
+        else:
+            self.base_model.peft_config = value
+
+    def save_pretrained(
+        self,
+        save_directory: str,
+        safe_serialization: bool = True,
+        selected_adapters: Optional[list[str]] = None,
+        save_embedding_layers: Union[str, bool] = "auto",
+        is_main_process: bool = True,
+        path_initial_model_for_weight_conversion: Optional[str] = None,
+        **kwargs: Any,
+    ) -> None:
+        r"""
+        This function saves the adapter model and the adapter configuration files to a directory, so that it can be
+        reloaded using the [`PeftModel.from_pretrained`] class method, and also used by the [`PeftModel.push_to_hub`]
+        method.
+
+        Args:
+            save_directory (`str`):
+                Directory where the adapter model and configuration files will be saved (will be created if it does not
+                exist).
+            safe_serialization (`bool`, *optional*):
+                Whether to save the adapter files in safetensors format, defaults to `True`.
+            selected_adapters (`List[str]`,  *optional*):
+                A list of adapters to be saved. If `None`, will default to all adapters.
+            save_embedding_layers (`Union[bool, str]`, *optional*, defaults to `"auto"`):
+                If `True`, save the embedding layers in addition to adapter weights. If `auto`, checks the common
+                embedding layers `peft.utils.other.EMBEDDING_LAYER_NAMES` in config's `target_modules` when available.
+                and automatically sets the boolean flag. This only works for 🤗 transformers models.
+            is_main_process (`bool`, *optional*):
+                Whether the process calling this is the main process or not. Will default to `True`. Will not save the
+                checkpoint if not on the main process, which is important for multi device setups (e.g. DDP).
+            path_initial_model_for_weight_conversion (`str, *optional*`):
+                The path to the initialized adapter, which is obtained after initializing the model with
+                PiSSA/CorDA/OLoRA and before performing any training. When `path_initial_model_for_weight_conversion`
+                is not None, the difference in adapter before and after fine-tuning is calculated. This difference can
+                be represented as the parameters of a standard LoRA adapter. Using this converted adapter does not
+                require changes to the base model, thus conveniently allowing the use of multiple PiSSA/CorDA/OLoRA
+                adapters with LoRA adapters, and the activation or deactivation of any adapters. Note that this
+                conversion is not supported if `rslora` is used in combination with `rank_pattern` or `alpha_pattern`.
+            kwargs (additional keyword arguments, *optional*):
+                Additional keyword arguments passed along to the `push_to_hub` method.
+
+        """
+        if os.path.isfile(save_directory):
+            raise ValueError(f"Provided path ({save_directory}) should be a directory, not a file")
+
+        if selected_adapters is None:
+            selected_adapters = list(self.peft_config.keys())
+        else:
+            if any(
+                selected_adapter_name not in list(self.peft_config.keys())
+                for selected_adapter_name in selected_adapters
+            ):
+                raise ValueError(
+                    f"You passed an invalid `selected_adapters` arguments, current supported adapter names are"
+                    f" {list(self.peft_config.keys())} - got {selected_adapters}."
+                )
+
+        def save_mutated_as_lora(peft_config, path_initial_model_for_weight_conversion, output_state_dict, kwargs):
+            if peft_config.use_rslora and (peft_config.rank_pattern or peft_config.alpha_pattern):
+                msg = (
+                    "Passing `path_initial_model_for_weight_conversion` to `save_pretrained` is not supported when "
+                    "using `rank_pattern` or `alpha_pattern` at the same time as `use_rslora=True`."
+                )
+                raise ValueError(msg)
+
+            if not any(
+                str(peft_config.init_lora_weights).lower().startswith(prefix)
+                for prefix in ["pissa", "corda", "olora", "true"]
+            ):
+                warnings.warn(
+                    "`path_initial_model_for_weight_conversion` only works for converting a PiSSA/CorDA/OLoRA adapter to "
+                    "a LoRA adapter"
+                )
+            initial_adapter_name = os.path.basename(path_initial_model_for_weight_conversion)
+            try:
+                self.load_adapter(
+                    os.path.dirname(path_initial_model_for_weight_conversion),
+                    subfolder=initial_adapter_name,
+                    adapter_name=initial_adapter_name,
+                )
+                is_pissa = str(self.peft_config[initial_adapter_name].init_lora_weights).lower().startswith("pissa")
+                is_corda = str(self.peft_config[initial_adapter_name].init_lora_weights).lower() == "corda"
+                is_olora = str(self.peft_config[initial_adapter_name].init_lora_weights).lower() == "olora"
+                if is_pissa or is_corda or is_olora:
+                    raise ValueError(
+                        "The `init_lora_weights` parameter of the initial adapter should be set to `True`. "
+                        "Otherwise, `self.load_adapter` will subtract the decomposed values again based on the "
+                        "residual model."
+                    )
+                output_state_dict = self.base_model.subtract_mutated_init(
+                    output_state_dict, initial_adapter_name, kwargs
+                )
+            finally:
+                self.delete_adapter(initial_adapter_name)
+            return output_state_dict
+
+        if is_main_process:
+            os.makedirs(save_directory, exist_ok=True)
+            self.create_or_update_model_card(save_directory)
+
+        for adapter_name in selected_adapters:
+            peft_config = self.peft_config[adapter_name]
+            # save only the trainable weights
+            output_state_dict = get_peft_model_state_dict(
+                self,
+                state_dict=kwargs.get("state_dict", None),
+                adapter_name=adapter_name,
+                save_embedding_layers=save_embedding_layers,
+            )
+            output_dir = os.path.join(save_directory, adapter_name) if adapter_name != "default" else save_directory
+            os.makedirs(output_dir, exist_ok=True)
+
+            if is_main_process and safe_serialization:
+                # Section copied from: https://github.com/huggingface/transformers/blob/main/src/transformers/modeling_utils.py#L2111-L2134
+                # Safetensors does not allow tensor aliasing.
+                # We're going to remove aliases before saving
+                ptrs = collections.defaultdict(list)
+                for name, tensor in output_state_dict.items():
+                    # Sometimes in the state_dict we have non-tensor objects.
+                    # e.g. in bitsandbytes we have some `str` objects in the state_dict
+                    if isinstance(tensor, torch.Tensor):
+                        ptrs[id_tensor_storage(tensor)].append(name)
+                    else:
+                        # In the non-tensor case, fall back to the pointer of the object itself
+                        ptrs[id(tensor)].append(name)
+
+                # These are all the pointers of shared tensors.
+                shared_ptrs = {ptr: names for ptr, names in ptrs.items() if len(names) > 1}
+
+                for _, names in shared_ptrs.items():
+                    # Here we just clone the shared tensors to avoid tensor aliasing which is
+                    # not supported in safetensors.
+                    for shared_tensor_name in names[1:]:
+                        output_state_dict[shared_tensor_name] = output_state_dict[shared_tensor_name].clone()
+                if path_initial_model_for_weight_conversion is not None:
+                    peft_config = copy.deepcopy(peft_config)
+                    peft_config.init_lora_weights = True
+                    peft_config.save_pretrained(path_initial_model_for_weight_conversion)
+                    output_state_dict = save_mutated_as_lora(
+                        peft_config, path_initial_model_for_weight_conversion, output_state_dict, kwargs
+                    )
+                safe_save_file(
+                    output_state_dict,
+                    os.path.join(output_dir, SAFETENSORS_WEIGHTS_NAME),
+                    metadata={"format": "pt"},
+                )
+            elif is_main_process:
+                if path_initial_model_for_weight_conversion is not None:
+                    peft_config = copy.deepcopy(peft_config)
+                    peft_config.init_lora_weights = True
+                    peft_config.save_pretrained(path_initial_model_for_weight_conversion)
+                    output_state_dict = save_mutated_as_lora(
+                        peft_config, path_initial_model_for_weight_conversion, output_state_dict, kwargs
+                    )
+                torch.save(output_state_dict, os.path.join(output_dir, WEIGHTS_NAME))
+
+            # save the config and change the inference mode to `True`
+            if peft_config.base_model_name_or_path is None:
+                peft_config.base_model_name_or_path = (
+                    self.base_model.__dict__.get("name_or_path", None)
+                    if peft_config.is_prompt_learning
+                    else self.base_model.model.__dict__.get("name_or_path", None)
+                )
+            inference_mode = peft_config.inference_mode
+            peft_config.inference_mode = True
+
+            if peft_config.task_type is None:
+                # deal with auto mapping
+                base_model_class = self._get_base_model_class(
+                    is_prompt_tuning=peft_config.is_prompt_learning,
+                )
+                parent_library = base_model_class.__module__
+
+                auto_mapping_dict = {
+                    "base_model_class": base_model_class.__name__,
+                    "parent_library": parent_library,
+                }
+            else:
+                auto_mapping_dict = None
+
+            if is_main_process:
+                if path_initial_model_for_weight_conversion is not None:
+                    peft_config.init_lora_weights = True
+                    peft_config.r *= 2
+                    if not peft_config.use_rslora:
+                        peft_config.lora_alpha *= 2
+                    else:
+                        # with rslora, we have scaling = alpha / sqrt(r), we thus adjust alpha to keep the same scaling
+                        peft_config.lora_alpha *= 2**0.5
+
+                    if peft_config.rank_pattern:
+                        peft_config.rank_pattern = {key: 2 * val for key, val in peft_config.rank_pattern.items()}
+                    if peft_config.alpha_pattern:
+                        peft_config.alpha_pattern = {key: 2 * val for key, val in peft_config.alpha_pattern.items()}
+
+                peft_config.save_pretrained(output_dir, auto_mapping_dict=auto_mapping_dict)
+            peft_config.inference_mode = inference_mode
+
+    @classmethod
+    def from_pretrained(
+        cls,
+        model: torch.nn.Module,
+        model_id: Union[str, os.PathLike],
+        adapter_name: str = "default",
+        is_trainable: bool = False,
+        config: Optional[PeftConfig] = None,
+        autocast_adapter_dtype: bool = True,
+        ephemeral_gpu_offload: bool = False,
+        low_cpu_mem_usage: bool = False,
+        **kwargs: Any,
+    ) -> PeftModel:
+        r"""
+        Instantiate a PEFT model from a pretrained model and loaded PEFT weights.
+
+        Note that the passed `model` may be modified inplace.
+
+        Args:
+            model ([`torch.nn.Module`]):
+                The model to be adapted. For 🤗 Transformers models, the model should be initialized with the
+                [`~transformers.PreTrainedModel.from_pretrained`].
+            model_id (`str` or `os.PathLike`):
+                The name of the PEFT configuration to use. Can be either:
+                    - A string, the `model id` of a PEFT configuration hosted inside a model repo on the Hugging Face
+                      Hub.
+                    - A path to a directory containing a PEFT configuration file saved using the `save_pretrained`
+                      method (`./my_peft_config_directory/`).
+            adapter_name (`str`, *optional*, defaults to `"default"`):
+                The name of the adapter to be loaded. This is useful for loading multiple adapters.
+            is_trainable (`bool`, *optional*, defaults to `False`):
+                Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and can only be
+                used for inference.
+            config ([`~peft.PeftConfig`], *optional*):
+                The configuration object to use instead of an automatically loaded configuration. This configuration
+                object is mutually exclusive with `model_id` and `kwargs`. This is useful when configuration is already
+                loaded before calling `from_pretrained`.
+            autocast_adapter_dtype (`bool`, *optional*):
+                Whether to autocast the adapter dtype. Defaults to `True`. Only relevant for specific adapter types.
+            ephemeral_gpu_offload (`bool`, *optional*):
+                Whether to use ephemeral GPU offloading for partially loaded modules. Defaults to `False`. This is
+                useful when parts of the model and/or components (such as adapters) are kept in CPU memory until they
+                are needed. Rather than perform expensive operations on small data, the data is transferred to the GPU
+                on-demand, the operation(s) performed, and the results moved back to CPU memory. This brings a slight
+                momentary VRAM overhead but gives orders of magnitude speedup in certain cases.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the
+                process.
+            torch_device (`str`, *optional*, defaults to None):
+                The device to load the adapter on. If `None`, the device will be inferred.
+            kwargs: (`optional`):
+                Additional keyword arguments passed along to the specific PEFT configuration class.
+        """
+        from .auto import MODEL_TYPE_TO_PEFT_MODEL_MAPPING
+        from .tuners import XLoraConfig, XLoraModel
+
+        # load the config
+        if config is None:
+            config = PEFT_TYPE_TO_CONFIG_MAPPING[
+                PeftConfig._get_peft_type(
+                    model_id,
+                    subfolder=kwargs.get("subfolder", None),
+                    revision=kwargs.get("revision", None),
+                    cache_dir=kwargs.get("cache_dir", None),
+                    use_auth_token=kwargs.get("use_auth_token", None),
+                    token=kwargs.get("token", None),
+                )
+            ].from_pretrained(model_id, **kwargs)
+        elif isinstance(config, PeftConfig):
+            config.inference_mode = not is_trainable
+        else:
+            raise ValueError(f"The input config must be a PeftConfig, got {config.__class__}")
+
+        # Runtime configuration, if supported
+        if hasattr(config, "runtime_config"):
+            config.runtime_config.ephemeral_gpu_offload = ephemeral_gpu_offload
+        else:
+            if ephemeral_gpu_offload:
+                warnings.warn("Ephemeral GPU offloading is not supported for this model. Ignoring.")
+
+        if hasattr(model, "hf_device_map"):
+            weight_map = dict(named_module_tensors(model, recurse=True))
+
+            # recreate the offload_index for disk-offloaded modules: we need to know the location in storage of each weight
+            # before the offload hook is removed from the model
+            disk_modules = set()
+            index = None
+            for name, module in model.named_modules():
+                if hasattr(module, "_hf_hook") and hasattr(module._hf_hook, "original_devices"):
+                    if hasattr(module._hf_hook.weights_map, "dataset"):
+                        index = module._hf_hook.weights_map.dataset.index
+                    for key in module._hf_hook.original_devices.keys():
+                        if module._hf_hook.original_devices[key] == torch.device("meta"):
+                            disk_modules.add(str(name) + "." + str(key))
+
+            if disk_modules and not kwargs.get("use_safetensors", True):
+                raise ValueError("Disk offloading currently only supported for safetensors")
+
+            if index:
+                offload_index = {
+                    p: {
+                        "safetensors_file": index[p]["safetensors_file"],
+                        "weight_name": p,
+                        "dtype": str(weight_map[p].dtype).replace("torch.", ""),
+                    }
+                    for p in weight_map.keys()
+                    if p in disk_modules
+                }
+                kwargs["offload_index"] = offload_index
+
+        if (getattr(model, "hf_device_map", None) is not None) and len(
+            set(model.hf_device_map.values()).intersection({"cpu", "disk"})
+        ) > 0:
+            remove_hook_from_submodules(model)
+
+        if config.is_prompt_learning and is_trainable:
+            raise ValueError("Cannot set a prompt learning adapter to trainable when loading pretrained adapter.")
+        else:
+            config.inference_mode = not is_trainable
+        if isinstance(getattr(model, "base_model", None), XLoraModel):
+            if not isinstance(config, XLoraConfig):
+                raise TypeError(f"Expected 'XLoraConfig', got '{type(config)}' instead.")
+            if "adapters" in kwargs:
+                config.adapters = kwargs["adapters"]
+            else:
+                # If the path is on HF hub, then we get the adapter names to create a subfolders list which tells
+                # `load_adapter` where the adapters are.
+                if not os.path.exists(model_id):
+                    s = HfFileSystem()
+
+                    # The names of the adapters which must be in folders
+                    adapter_names = [
+                        file["name"][len(model_id) + 1 :] for file in s.ls(model_id) if file["type"] == "directory"
+                    ]
+                    # Prepare a dict of adapter paths, which really just point to the hf id; we will use the subfolders
+                    adapter_paths = {}
+                    for adapter_name in adapter_names:
+                        adapter_paths[adapter_name] = os.path.join(model_id, model_id)
+                    config.adapters = adapter_paths
+                    config._subfolders = adapter_names
+                else:
+                    if "adapters" not in kwargs:
+                        raise ValueError("If model_id is a local path, then `adapters` must be passed in kwargs.")
+
+        if config.task_type not in MODEL_TYPE_TO_PEFT_MODEL_MAPPING.keys():
+            model = cls(
+                model,
+                config,
+                adapter_name,
+                autocast_adapter_dtype=autocast_adapter_dtype,
+                low_cpu_mem_usage=low_cpu_mem_usage,
+            )
+        else:
+            model = MODEL_TYPE_TO_PEFT_MODEL_MAPPING[config.task_type](
+                model,
+                config,
+                adapter_name,
+                autocast_adapter_dtype=autocast_adapter_dtype,
+                low_cpu_mem_usage=low_cpu_mem_usage,
+            )
+
+        load_result = model.load_adapter(
+            model_id,
+            adapter_name,
+            is_trainable=is_trainable,
+            autocast_adapter_dtype=autocast_adapter_dtype,
+            low_cpu_mem_usage=low_cpu_mem_usage,
+            **kwargs,
+        )
+
+        # 1. Remove VB-LoRA vector bank, since it's a shared parameter set via the VBLoRAModel
+        # 2. Remove the prompt encoder, as it does not need to be part of the checkpoint
+        missing_keys = [
+            k for k in load_result.missing_keys if "vblora_vector_bank" not in k and "prompt_encoder" not in k
+        ]
+        if missing_keys:
+            # Let's warn here since (in contrast to load_adapter) we don't return the load result, so it could be quite
+            # difficult for users to even notice that something might have gone wrong here. As we filter out non PEFT
+            # keys from the missing keys, this gives no false positives.
+
+            warn_message = f"Found missing adapter keys while loading the checkpoint: {missing_keys}."
+
+            prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(config.peft_type)
+            if prefix and adapter_name in prefix:
+                warn_message += (
+                    f"Adapter name {adapter_name} should not be contained in the prefix {prefix}."
+                    "This could be the potential reason for missing adapter keys."
+                )
+
+            warnings.warn(warn_message)
+
+        return model
+
+    def _setup_prompt_encoder(self, adapter_name: str):
+        config = self.peft_config[adapter_name]
+        if not hasattr(self, "prompt_encoder"):
+            self.prompt_encoder = torch.nn.ModuleDict({})
+            self.prompt_tokens = {}
+        transformer_backbone = None
+        for name, module in self.base_model.named_children():
+            for param in module.parameters():
+                param.requires_grad = False
+            if isinstance(module, PreTrainedModel):
+                # Make sure to freeze Tranformers model
+                if transformer_backbone is None:
+                    transformer_backbone = module
+                    self.transformer_backbone_name = name
+        if transformer_backbone is None:
+            transformer_backbone = self.base_model
+
+        if config.num_transformer_submodules is None:
+            config.num_transformer_submodules = 2 if config.task_type == TaskType.SEQ_2_SEQ_LM else 1
+
+        # determine the word embeddings
+        word_embeddings = None
+        try:
+            # First try to find the word embeddings based on the module name, this should work for models like Bert,
+            # Roberta, Deberta, etc.
+            word_embeddings = self.base_model.get_submodule("embeddings.word_embeddings")
+        except AttributeError:
+            pass
+
+        if word_embeddings is None:
+            # Word embeddings could not be determined. Next try to guess them by checking which parameter has the size
+            # of the vocab.
+            for named_param, value in list(transformer_backbone.named_parameters()):
+                # for ZeRO-3, the tensor is sharded across accelerators and deepspeed modifies it to a tensor with shape
+                # [0] the actual unsharded shape is stored in "ds_shape" attribute special handling is needed in case
+                # the model is initialized in deepspeed.zero.Init() context or HfDeepSpeedConfig has been called before
+                # For reference refer to issue: https://github.com/huggingface/peft/issues/996
+                deepspeed_distributed_tensor_shape = getattr(value, "ds_shape", None)
+
+                if value.shape[0] == self.base_model.config.vocab_size or (
+                    deepspeed_distributed_tensor_shape is not None
+                    and deepspeed_distributed_tensor_shape[0] == self.base_model.config.vocab_size
+                ):
+                    word_embeddings = transformer_backbone.get_submodule(named_param.replace(".weight", ""))
+                    break
+
+        self.word_embeddings = word_embeddings
+        model_cls = PEFT_TYPE_TO_TUNER_MAPPING[config.peft_type]
+
+        if config.peft_type in (PeftType.PROMPT_TUNING, PeftType.MULTITASK_PROMPT_TUNING, PeftType.CPT):
+            prompt_encoder = model_cls(config, self.word_embeddings)
+        elif config.peft_type == PeftType.P_TUNING:
+            prompt_encoder = model_cls(config)
+        elif config.peft_type == PeftType.PREFIX_TUNING:
+            # prefix tuning now uses Cache but that won't work with gradient checkpointing
+            if any(getattr(module, "gradient_checkpointing", False) for module in self.get_base_model().modules()):
+                raise ValueError("Prefix tuning does not work with gradient checkpointing.")
+            prompt_encoder = model_cls(config)
+        else:
+            raise ValueError("Not supported")
+
+        prompt_encoder = prompt_encoder.to(self.device)
+        self.prompt_encoder.update(torch.nn.ModuleDict({adapter_name: prompt_encoder}))
+        self.prompt_tokens[adapter_name] = torch.arange(
+            config.num_virtual_tokens * config.num_transformer_submodules
+        ).long()
+
+    def _prepare_model_for_gradient_checkpointing(self, model: PreTrainedModel):
+        r"""
+        Prepares the model for gradient checkpointing if necessary
+        """
+        if not (
+            getattr(model, "is_loaded_in_8bit", False)
+            or getattr(model, "is_loaded_in_4bit", False)
+            or getattr(model, "is_quantized", False)
+        ):
+            if hasattr(model, "enable_input_require_grads"):
+                model.enable_input_require_grads()
+            elif hasattr(model, "get_input_embeddings"):
+
+                def make_inputs_require_grad(module, input, output):
+                    output.requires_grad_(True)
+
+                model.get_input_embeddings().register_forward_hook(make_inputs_require_grad)
+        return model
+
+    def get_prompt_embedding_to_save(self, adapter_name: str) -> torch.Tensor:
+        """
+        Returns the prompt embedding to save when saving the model. Only applicable when using a prompt learning
+        method.
+        """
+        prompt_encoder = self.prompt_encoder[adapter_name]
+        prompt_tokens = (
+            self.prompt_tokens[adapter_name].unsqueeze(0).expand(1, -1).to(prompt_encoder.embedding.weight.device)
+        )
+        peft_type = self.peft_config[adapter_name].peft_type
+        if self.peft_config[adapter_name].peft_type == PeftType.PREFIX_TUNING:
+            prompt_tokens = prompt_tokens[:, : self.peft_config[adapter_name].num_virtual_tokens]
+
+        if self.peft_config[adapter_name].peft_type == PeftType.MULTITASK_PROMPT_TUNING:
+            prompt_embedding_cls = PEFT_TYPE_TO_TUNER_MAPPING[peft_type]
+            prompt_embeddings = super(prompt_embedding_cls, prompt_encoder).forward(prompt_tokens)
+        else:
+            prompt_embeddings = prompt_encoder(prompt_tokens)
+
+        return prompt_embeddings[0].detach().cpu()
+
+    def get_prompt(self, batch_size: int, task_ids: Optional[torch.Tensor] = None) -> torch.Tensor:
+        """
+        Returns the virtual prompts to use for Peft. Only applicable when using a prompt learning method.
+        """
+        peft_config = self.active_peft_config
+        prompt_encoder = self.prompt_encoder[self.active_adapter]
+        prompt_tokens = (
+            self.prompt_tokens[self.active_adapter]
+            .unsqueeze(0)
+            .expand(batch_size, -1)
+            .to(prompt_encoder.embedding.weight.device)
+        )
+        if peft_config.peft_type == PeftType.PREFIX_TUNING:
+            prompt_tokens = prompt_tokens[:, : peft_config.num_virtual_tokens]
+            if peft_config.inference_mode:
+                past_key_values = prompt_encoder.embedding.weight.repeat(batch_size, 1, 1)
+            else:
+                past_key_values = prompt_encoder(prompt_tokens)
+            if self.base_model_torch_dtype is not None:
+                past_key_values = past_key_values.to(self.base_model_torch_dtype)
+            past_key_values = past_key_values.view(
+                batch_size,
+                peft_config.num_virtual_tokens,
+                peft_config.num_layers * 2,
+                peft_config.num_attention_heads,
+                peft_config.token_dim // peft_config.num_attention_heads,
+            )
+            if peft_config.num_transformer_submodules == 2:
+                past_key_values = torch.cat([past_key_values, past_key_values], dim=2)
+            past_key_values = past_key_values.permute([2, 0, 3, 1, 4]).split(
+                peft_config.num_transformer_submodules * 2
+            )
+            if TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING.get(self.config.model_type, None) is not None:
+                post_process_fn = TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING[self.config.model_type]
+                past_key_values = post_process_fn(past_key_values)
+            elif peft_config.num_transformer_submodules == 1:
+                # Dont' apply this to encoder-decoder models and not to models requiring special processing.
+                # local import in case users use a very old transformers version
+                past_key_values = DynamicCache.from_legacy_cache(past_key_values)
+            elif peft_config.num_transformer_submodules == 2 and self.base_model._supports_cache_class:
+                # Dont' apply this to encoder-decoder models that don't support new Cachc format yet
+                # If we don't apply this, prefix-tuning fails to update cross-attn cache
+                past_key_values = EncoderDecoderCache.from_legacy_cache(past_key_values)
+                past_key_values.cross_attention_cache = DynamicCache()
+                past_key_values.is_updated = {
+                    layer_idx: False for layer_idx in range(len(past_key_values.cross_attention_cache.key_cache))
+                }
+            map_cache_to_layer_device_map(self.get_base_model(), past_key_values)  # no-op if not a Cache instance
+            return past_key_values
+        else:
+            if peft_config.peft_type == PeftType.MULTITASK_PROMPT_TUNING:
+                prompts = prompt_encoder(prompt_tokens, task_ids)
+            else:
+                if peft_config.inference_mode:
+                    prompts = prompt_encoder.embedding.weight
+                else:
+                    # Take only one prompt token sample and expand the output instead of expanding the input, see:
+                    # https://github.com/huggingface/peft/issues/2043#issuecomment-2321522577
+                    prompt_tokens = prompt_tokens[:1]
+                    prompts = prompt_encoder(prompt_tokens)
+                prompts = prompts.repeat(batch_size, 1, 1)
+            return prompts
+
+    def get_nb_trainable_parameters(self) -> tuple[int, int]:
+        r"""
+        Returns the number of trainable parameters and the number of all parameters in the model.
+        """
+        trainable_params = 0
+        all_param = 0
+        for _, param in self.named_parameters():
+            num_params = param.numel()
+            # if using DS Zero 3 and the weights are initialized empty
+            if num_params == 0 and hasattr(param, "ds_numel"):
+                num_params = param.ds_numel
+
+            # Due to the design of 4bit linear layers from bitsandbytes
+            # one needs to multiply the number of parameters by 2 to get
+            # the correct number of parameters
+            if param.__class__.__name__ == "Params4bit":
+                if hasattr(param, "element_size"):
+                    num_bytes = param.element_size()
+                elif not hasattr(param, "quant_storage"):
+                    num_bytes = 1
+                else:
+                    num_bytes = param.quant_storage.itemsize
+                num_params = num_params * 2 * num_bytes
+
+            all_param += num_params
+            if param.requires_grad:
+                trainable_params += num_params
+
+        return trainable_params, all_param
+
+    def print_trainable_parameters(self) -> None:
+        """
+        Prints the number of trainable parameters in the model.
+
+        Note: print_trainable_parameters() uses get_nb_trainable_parameters() which is different from
+        num_parameters(only_trainable=True) from huggingface/transformers. get_nb_trainable_parameters() returns
+        (trainable parameters, all parameters) of the Peft Model which includes modified backbone transformer model.
+        For techniques like LoRA, the backbone transformer model is modified in place with LoRA modules. However, for
+        prompt tuning, the backbone transformer model is unmodified. num_parameters(only_trainable=True) returns number
+        of trainable parameters of the backbone transformer model which can be different.
+        """
+        trainable_params, all_param = self.get_nb_trainable_parameters()
+
+        print(
+            f"trainable params: {trainable_params:,d} || all params: {all_param:,d} || trainable%: {100 * trainable_params / all_param:.4f}"
+        )
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "base_model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.base_model, name)
+
+    @contextmanager
+    def _enable_peft_forward_hooks(self, *args, **kwargs):
+        # If the base model has a method called _enable_peft_forward_hooks, it is invoked as a context. Otherwise, this
+        # runs without any changes
+        if hasattr(self.base_model, "_enable_peft_forward_hooks"):
+            with self.base_model._enable_peft_forward_hooks(*args, **kwargs):
+                yield
+            return
+        else:
+            # nothing to enable
+            yield
+            return
+
+    def forward(self, *args: Any, **kwargs: Any):
+        """
+        Forward pass of the model.
+        """
+        with self._enable_peft_forward_hooks(*args, **kwargs):
+            kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+            return self.get_base_model()(*args, **kwargs)
+
+    def generate(self, *args, **kwargs):
+        with self._enable_peft_forward_hooks(*args, **kwargs):
+            kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+            return self.get_base_model().generate(*args, **kwargs)
+
+    def _get_base_model_class(self, is_prompt_tuning=False):
+        """
+        Returns the base model class.
+        """
+        if not is_prompt_tuning:
+            return self.base_model.model.__class__
+        return self.base_model.__class__
+
+    @contextmanager
+    def disable_adapter(self):
+        """
+        Context manager that disables the adapter module. Use this to run inference on the base model.
+
+        Example:
+
+        ```py
+        >>> with model.disable_adapter():
+        ...     model(inputs)
+        ```
+        """
+        if self.peft_config[self.active_adapter].is_prompt_learning:
+            try:
+                # TODO: consider replacing this patching of methods with a more robust mechanism: setting a flag and
+                # letting the underlying methods deal with it, same as how LoRA does it.
+                old_forward = self.forward
+                self.forward = self.base_model.forward
+                old_prepare_inputs_for_generation = self.prepare_inputs_for_generation
+                self.prepare_inputs_for_generation = self.base_model.prepare_inputs_for_generation
+                yield
+            finally:
+                self.forward = old_forward
+                self.prepare_inputs_for_generation = old_prepare_inputs_for_generation
+
+        elif self.peft_config[self.active_adapter].is_adaption_prompt:
+            try:
+                self.base_model.disable_adapter_layers()
+                yield
+            finally:
+                self.base_model.enable_adapter_layers()
+
+        else:  # LoRA, LoHa, etc.
+            model_status = self.get_model_status()
+            if model_status.enabled == "irregular":
+                warnings.warn(
+                    "The model contains some adapter layers that are enabled and others that are disabled. "
+                    "This is most likely unintentional. After exiting the disable_adapter context, all adapters "
+                    "will be enabled"
+                )
+            try:
+                self.base_model.disable_adapter_layers()
+                yield
+            finally:
+                if model_status.enabled is not False:
+                    # model_status.enabled is `True` or `"irregular"`
+                    self.base_model.enable_adapter_layers()
+
+    def get_base_model(self) -> torch.nn.Module:
+        """
+        Returns the base model.
+        """
+        return (
+            self.base_model
+            if (self.active_peft_config.is_prompt_learning or self.peft_type == PeftType.POLY)
+            else self.base_model.model
+        )
+
+    def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None:
+        """
+        Add an adapter to the model based on the passed configuration.
+
+        This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`].
+
+        The name for the new adapter should be unique.
+
+        The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active
+        adapter.
+
+        Args:
+            adapter_name (`str`):
+                The name of the adapter to be added.
+            peft_config ([`PeftConfig`]):
+                The configuration of the adapter to be added.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device. Useful to speed up the process when loading saved
+                adapters. Don't use this option when creating a new PEFT adapter for training.
+
+        """
+        prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(peft_config.peft_type)
+        if prefix and adapter_name in prefix:
+            warnings.warn(
+                f"Adapter name {adapter_name} should not be contained in the prefix {prefix}."
+                "This may lead to reinitialization of the adapter weights during loading."
+            )
+
+        if peft_config.peft_type != self.peft_type:
+            raise ValueError(
+                f"Cannot combine adapters with different peft types. "
+                f"Found {self.peft_type} and {peft_config.peft_type}."
+            )
+
+        try:
+            if peft_config.is_prompt_learning:
+                self.peft_config[adapter_name] = peft_config
+                if hasattr(self.config, "to_dict"):
+                    dict_config = self.config.to_dict()
+                else:
+                    dict_config = self.config
+
+                peft_config = _prepare_prompt_learning_config(peft_config, dict_config)
+                self._setup_prompt_encoder(adapter_name)
+            elif peft_config.is_adaption_prompt:
+                self.base_model.add_adapter(adapter_name, peft_config)
+            else:
+                self.peft_config[adapter_name] = peft_config
+                self.base_model.inject_adapter(
+                    self.base_model.model, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage
+                )
+        except Exception:  # something went wrong, roll back
+            if adapter_name in self.peft_config:
+                del self.peft_config[adapter_name]
+            raise
+
+        self.set_additional_trainable_modules(peft_config, adapter_name)
+
+    def set_additional_trainable_modules(self, peft_config, adapter_name):
+        if getattr(peft_config, "modules_to_save", None) is not None:
+            if self.modules_to_save is None:
+                self.modules_to_save = set(peft_config.modules_to_save)
+            else:
+                self.modules_to_save.update(peft_config.modules_to_save)
+            # this may add a new ModulesToSaveWrapper
+            _set_trainable(self, adapter_name, module_names=getattr(peft_config, "modules_to_save", None))
+
+        if getattr(peft_config, "trainable_token_indices", None) is not None:
+            if isinstance(peft_config.trainable_token_indices, dict):
+                target_layers = peft_config.trainable_token_indices
+            else:
+                layer_name = _get_input_embeddings_name(self.model, "embed_tokens")
+                target_layers = {layer_name: peft_config.trainable_token_indices}
+
+            if self.modules_to_save:
+                for target_layer in target_layers:
+                    if target_layer in self.modules_to_save:
+                        raise ValueError(
+                            "The embedding layer is already marked to be trained fully, either specify "
+                            f'`modules_to_save=[..., "{target_layer}", ...]` or '
+                            f"`trainable_tokens={{'{target_layer}': x}}` but not both."
+                        )
+
+            # we are not adding these module names to `self.modules_to_save` as this is strictly reserved for the
+            # `ModulesToSaveWrapper`.
+
+            for target_layer, token_indices in target_layers.items():
+                _set_trainable(
+                    self,
+                    adapter_name,
+                    module_names=[target_layer],
+                    strict_module_check=True,
+                    wrapper_cls=TrainableTokensWrapper,
+                    token_indices=token_indices,
+                )
+
+            # There might be the possibility that we have output weights that are tied to the input weights.
+            # In that case we will tie any module that wants tied weights to the token adapter to make sure that
+            # any modification is reflected in the tied layers as well.
+            model_config = BaseTuner.get_model_config(self)
+            if (
+                model_config.get("tie_word_embeddings", False)
+                # some models may be misconfigured to have weight tying enabled but don't define tied weights keys
+                and self.model._tied_weights_keys is not None
+                and isinstance(self.model.get_input_embeddings(), TrainableTokensWrapper)
+            ):
+                # the embedding layer is modified and we want weight tying.
+                module_keys = [".".join(n.split(".")[:-1]) for n in self.model._tied_weights_keys]
+
+                token_adapter = self.model.get_input_embeddings().token_adapter
+                _set_trainable(
+                    self,
+                    adapter_name,
+                    module_names=module_keys,
+                    strict_module_check=True,
+                    wrapper_cls=TrainableTokensWrapper,
+                    token_indices=token_adapter.token_indices[adapter_name],
+                    tied_adapter=self.model.get_input_embeddings().token_adapter,
+                )
+
+    def get_layer_status(self) -> list[TunerLayerStatus]:
+        """Get the status of each adapter layer in the model.
+
+        This method returns a list of `TunerLayerStatus` dataclass instances, each of which contains the following
+        attributes:
+
+        - `name` (`str`):
+           The name of the adapter layer, e.g. `model.encoder.block.0.layer.0.SelfAttention.q`.
+        - `module_type` (`str`):
+           The type of the adapter layer, e.g. `lora.Linear`.
+        - `enabled` (`bool`):
+           Whether the adapter layer is enabled.
+        - `active_adapters` (`list[str]`):
+           The names of the active adapters, if any, e.g. `["default"]`.
+        - `merged_adapters` (`list[str]`):
+           The names of the merged adapters, if any, e.g. `["default"]`.
+        - `available_adapters` (`list[str]`):
+           The names of the available adapters, e.g. `["default"]`.
+
+        Args:
+            model ([`~PeftModel`]):
+                The model to get the adapter layer status from.
+
+        Returns:
+            list[`peft.peft_model.TunerLayerStatus`]:
+                A list of dataclasses, each containing the status of the corresponding adapter layer.
+
+        """
+        return get_layer_status(self)
+
+    def get_model_status(self) -> TunerModelStatus:
+        """Get the status of tuners of the model.
+
+        This method returns a `TunerModelStatus` dataclass instance, which contains the following attributes:
+
+        - `base_model_type` (`str`):
+           The type of the base model, e.g. `T5Model`.
+        - `adapter_model_type` (`str`):
+           The type of the adapter model, e.g. `LoraModel`.
+        - `peft_types` (`dict[str, str]`):
+           The mapping of adapter name to adapter type, e.g. `{"default": "LORA"}`.
+        - `trainable_params` (`int`):
+           The number of trainable parameters in the model.
+        - `total_params` (`int`):
+           The total number of parameters in the model.
+        - `num_adapter_layers` (`int`):
+           The number of adapter layers in the model.
+        - `enabled` (`bool`, `Literal["irregular"]`):
+           Whether all adapter layers are enabled. If some are enabled and some are not, this will be `"irregular"`.
+           This means that your model is in an inconsistent state and might not work as expected.
+        - `active_adapters` (`list[str]`, `Literal["irregular"]`):
+           The names of the active adapters. If the active adapters are not consistent across all layers, this will be
+           `"irregular"`, which means that your model is in an inconsistent state and might not work as expected.
+        - `merged_adapters` (`list[str]`, `Literal["irregular"]`):
+           The names of the merged adapters. If the merged adapters are not consistent across all layers, this will be
+           `"irregular"`, which means that your model is in an inconsistent state and might not work as expected.
+        - `available_adapters` (`list[str]`):
+           The names of the available adapters, e.g. `["default"]`.
+
+        Args:
+            model ([`~PeftModel`]):
+                The model to get the adapter layer status from.
+
+        Returns:
+            `peft.peft_model.TunerModelStatus`:
+                A dataclass containing the status of the model.
+
+        """
+        return get_model_status(self)
+
+    @classmethod
+    def _split_kwargs(cls, kwargs: dict[str, Any]):
+        _kwargs_not_in_hf_hub_download_signature = ("use_auth_token",)
+        hf_hub_download_kwargs = {}
+        other_kwargs = {}
+
+        for key, value in kwargs.items():
+            if key in inspect.signature(hf_hub_download).parameters or key in _kwargs_not_in_hf_hub_download_signature:
+                hf_hub_download_kwargs[key] = value
+            else:
+                other_kwargs[key] = value
+
+        return hf_hub_download_kwargs, other_kwargs
+
+    def _update_offload(self, offload_index: dict[str, dict[str, str]], adapters_weights: dict[str, torch.tensor]):
+        """
+        Update the offload_index and safetensors files for loading and mergine PeftModels with disk-offloaded modules.
+
+        Args:
+            offload_index (Dict[str: str]):
+                Dictionary of disk-offloaded modules with their metadata and safetensors filenames
+            adapters_weights (Dict[str: torch.tensor]):
+                Dictionary of Peft adapter module names and weights
+        """
+
+        if not offload_index:
+            return offload_index
+
+        prefix = "base_model.model."
+        # rename offload index weight and model names
+        adapter_names = list(self.peft_config.keys())
+        for adapter_name in adapter_names:
+            keys = list(offload_index.keys())
+            block_id = keys[0].split(".")[0] + "."  # for writing safetensors key,
+
+            # replace original offload index keys with PeftModel keys
+            for key in keys:
+                suffix_pos = key.rfind(".")
+                extended_prefix = prefix + key[:suffix_pos]
+                module = dict(self.named_modules())[extended_prefix]
+                if isinstance(module, BaseTunerLayer):
+                    new_key = prefix + key[:suffix_pos] + ".base_layer" + key[suffix_pos:]
+                else:
+                    new_key = prefix + key
+                offload_index[key]["weight_name"] = new_key
+                offload_index[new_key] = offload_index[key]
+                del offload_index[key]
+
+            files_seen = set()
+            # rename safetensors for dispatch
+            for new_key in list(offload_index.keys()):
+                fname = offload_index[new_key]["safetensors_file"]
+
+                # make a new file name
+                new_fname_list = list(fname.split(os.sep))
+                for i, name in enumerate(new_fname_list):
+                    if "--" in name:
+                        new_fname_list[i] += "-peft"
+                        break
+                new_fname = os.path.join(*new_fname_list)
+
+                if fname in files_seen:
+                    continue
+                safe_dict = {}
+                with safe_open(fname, framework="pt") as f:
+                    for safe_key in f.keys():
+                        safe_tensor = f.get_tensor(safe_key)
+                        metadata = f.metadata()
+                        suffix_pos = safe_key.rfind(".")
+                        extended_prefix = prefix + block_id + safe_key[:suffix_pos]
+                        safe_module = dict(self.named_modules())[extended_prefix]
+                        if isinstance(safe_module, BaseTunerLayer):
+                            final_key = extended_prefix + ".base_layer" + safe_key[suffix_pos:]
+                            lora_dict = {key: val for key, val in adapters_weights.items() if extended_prefix in key}
+
+                            # add LoRA keys and values to disk offload
+                            for lora_key, lora_val in lora_dict.items():
+                                divide = lora_key.rfind(".")
+                                new_key = lora_key[:divide] + f".{adapter_name}" + lora_key[divide:]
+                                safe_dict[new_key] = lora_val
+                        else:
+                            final_key = prefix + block_id + safe_key
+                        safe_dict[final_key] = safe_tensor
+                    files_seen.add(new_fname)
+
+                    # avoid overwriting original safetensors
+                    for key in safe_dict.keys():
+                        offload_index[key] = {"safetensors_file": new_fname, "weight_name": key}
+
+                    base_name = os.path.dirname(new_fname)
+                    if not os.path.exists(base_name):
+                        os.makedirs(base_name)
+                    safe_save_file(safe_dict, new_fname, metadata=metadata)
+
+    def _check_new_adapter_config(self, peft_config: PeftConfig, is_trainable: bool) -> None:
+        """Perform checks on newly added PEFT configs to ensure integrity."""
+        if peft_config.is_prompt_learning and is_trainable:
+            raise ValueError("Cannot set a prompt learning adapter to trainable when loading pretrained adapter.")
+
+        # Since PiSSA/CorDA/OLoRA modifies the base weights, it should not be combined with other adapters.
+        all_configs = [peft_config] + list(self.peft_config.values())
+        if len(all_configs) > 1:
+            if any(getattr(config, "init_lora_weights", None) == "pissa" for config in all_configs):
+                msg = (
+                    "PiSSA changes the base weights of the model and should thus not be used with other adapters. "
+                    "Consider converting the PiSSA adapter into a normal LoRA adapter: "
+                    "https://github.com/huggingface/peft/tree/main/examples/pissa_finetuning#convert-pissa-to-lora"
+                )
+                warnings.warn(msg)
+            elif any(getattr(config, "init_lora_weights", None) == "corda" for config in all_configs):
+                msg = (
+                    "CorDA changes the base weights of the model and should thus not be used with other adapters. "
+                    "Consider converting the CorDA adapter into a normal LoRA adapter: "
+                    "https://github.com/huggingface/peft/tree/main/examples/corda_finetuning#convert-corda-to-lora"
+                )
+                warnings.warn(msg)
+            elif any(getattr(config, "init_lora_weights", None) == "olora" for config in all_configs):
+                msg = (
+                    "OLoRA changes the base weights of the model and should thus not be used with other adapters. "
+                    "Consider converting the OLoRA adapter into a normal LoRA adapter: "
+                    "https://github.com/huggingface/peft/tree/main/examples/olora_finetuning#olora-and-lora"
+                )
+                warnings.warn(msg)
+
+    def load_adapter(
+        self,
+        model_id: Union[str, os.PathLike],
+        adapter_name: str,
+        is_trainable: bool = False,
+        torch_device: Optional[str] = None,
+        autocast_adapter_dtype: bool = True,
+        ephemeral_gpu_offload: bool = False,
+        low_cpu_mem_usage: bool = False,
+        **kwargs: Any,
+    ):
+        """
+        Load a trained adapter into the model.
+
+        The name for the new adapter should be unique.
+
+        The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active
+        adapter.
+
+        Args:
+            model_id (`str` or `os.PathLike`):
+                The name of the PEFT configuration to use. Can be either:
+                    - A string, the `model id` of a PEFT configuration hosted inside a model repo on the Hugging Face
+                      Hub.
+                    - A path to a directory containing a PEFT configuration file saved using the `save_pretrained`
+                      method (`./my_peft_config_directory/`).
+            adapter_name (`str`):
+                The name of the adapter to be added.
+            is_trainable (`bool`, *optional*, defaults to `False`):
+                Whether the adapter should be trainable or not. If `False`, the adapter will be frozen and can only be
+                used for inference.
+            torch_device (`str`, *optional*, defaults to None):
+                The device to load the adapter on. If `None`, the device will be inferred.
+            autocast_adapter_dtype (`bool`, *optional*, defaults to `True`):
+                Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter
+                weights using float16 and bfloat16 to float32, as this is typically required for stable training, and
+                only affect select PEFT tuners.
+            ephemeral_gpu_offload (`bool`, *optional*, defaults to `False`):
+                Whether to use ephemeral GPU offloading for partially loaded modules. Defaults to `False`.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device before loading the saved weights. Useful to speed up the
+                process.
+            kwargs: (`optional`):
+                Additional arguments to modify the way the adapter is loaded, e.g. the token for Hugging Face Hub.
+        """
+        from .mapping import PEFT_TYPE_TO_CONFIG_MAPPING
+
+        hf_hub_download_kwargs, kwargs = self._split_kwargs(kwargs)
+        if torch_device is None:
+            torch_device = infer_device()
+
+        if adapter_name not in self.peft_config:
+            # load the config
+            peft_config = PEFT_TYPE_TO_CONFIG_MAPPING[
+                PeftConfig._get_peft_type(
+                    model_id,
+                    **hf_hub_download_kwargs,
+                )
+            ].from_pretrained(
+                model_id,
+                ephemeral_gpu_offload=ephemeral_gpu_offload,
+                **hf_hub_download_kwargs,
+            )
+            self._check_new_adapter_config(peft_config, is_trainable=is_trainable)
+            peft_config.inference_mode = not is_trainable
+            self.add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage)
+
+        adapters_weights = load_peft_weights(model_id, device=torch_device, **hf_hub_download_kwargs)
+
+        # load the weights into the model
+        ignore_mismatched_sizes = kwargs.get("ignore_mismatched_sizes", False)
+        load_result = set_peft_model_state_dict(
+            self,
+            adapters_weights,
+            adapter_name=adapter_name,
+            ignore_mismatched_sizes=ignore_mismatched_sizes,
+            low_cpu_mem_usage=low_cpu_mem_usage,
+        )
+
+        tuner = self.peft_config[adapter_name].peft_type
+        tuner_prefix = PEFT_TYPE_TO_PREFIX_MAPPING.get(tuner, "")
+        adapter_missing_keys = []
+
+        # Filter missing keys specific to the current adapter and tuner prefix.
+        for key in load_result.missing_keys:
+            if tuner_prefix in key and adapter_name in key:
+                adapter_missing_keys.append(key)
+
+        load_result.missing_keys.clear()
+        load_result.missing_keys.extend(adapter_missing_keys)
+
+        if (
+            (getattr(self, "hf_device_map", None) is not None)
+            and (len(set(self.hf_device_map.values()).intersection({"cpu", "disk"})) > 0)
+            and len(self.peft_config) == 1
+        ):
+            device_map = kwargs.get("device_map", "auto")
+            max_memory = kwargs.get("max_memory", None)
+            offload_dir = kwargs.get("offload_folder", None)
+            offload_index = kwargs.get("offload_index", None)
+
+            dispatch_model_kwargs = {}
+            # Safety checker for previous `accelerate` versions
+            # `offload_index` was introduced in https://github.com/huggingface/accelerate/pull/873/
+            if "offload_index" in inspect.signature(dispatch_model).parameters:
+                dispatch_model_kwargs["offload_index"] = offload_index
+
+            no_split_module_classes = self._no_split_modules
+
+            if device_map != "sequential":
+                max_memory = get_balanced_memory(
+                    self,
+                    max_memory=max_memory,
+                    no_split_module_classes=no_split_module_classes,
+                    low_zero=(device_map == "balanced_low_0"),
+                )
+
+            if isinstance(device_map, str):
+                device_map = infer_auto_device_map(
+                    self, max_memory=max_memory, no_split_module_classes=no_split_module_classes
+                )
+
+            self._update_offload(offload_index, adapters_weights)
+            dispatch_model_kwargs["offload_index"] = offload_index
+
+            dispatch_model(
+                self,
+                device_map=device_map,
+                offload_dir=offload_dir,
+                **dispatch_model_kwargs,
+            )
+
+            hook = AlignDevicesHook(io_same_device=True)
+            if self.peft_config[adapter_name].is_prompt_learning:
+                remove_hook_from_submodules(self.prompt_encoder)
+            add_hook_to_module(self.get_base_model(), hook)
+
+        if hasattr(self.base_model, "_cast_adapter_dtype"):
+            self.base_model._cast_adapter_dtype(
+                adapter_name=adapter_name, autocast_adapter_dtype=autocast_adapter_dtype
+            )
+
+        # Set model in evaluation mode to deactivate Dropout modules by default
+        if not is_trainable:
+            self.eval()
+        return load_result
+
+    def set_adapter(self, adapter_name: str) -> None:
+        """
+        Sets the active adapter.
+
+        Only one adapter can be active at a time.
+
+        Additionally, this function will set the specified adapter to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str`):
+                The name of the adapter to be set as active. The adapter must be loaded first.
+        """
+        if adapter_name not in self.peft_config:
+            raise ValueError(f"Adapter {adapter_name} not found.")
+        self.active_adapter = adapter_name
+        if not self.peft_config[adapter_name].is_prompt_learning:
+            self.base_model.set_adapter(adapter_name)
+        _set_adapter(self, adapter_name)
+
+    @property
+    def base_model_torch_dtype(self):
+        return getattr(self.base_model, "dtype", None)
+
+    @property
+    def active_peft_config(self):
+        return self.peft_config[self.active_adapter]
+
+    def create_or_update_model_card(self, output_dir: str):
+        """
+        Updates or create model card to include information about peft:
+        1. Adds `peft` library tag
+        2. Adds peft version
+        3. Adds base model info
+        4. Adds quantization information if it was used
+        """
+
+        filename = os.path.join(output_dir, "README.md")
+
+        card = ModelCard.load(filename) if os.path.exists(filename) else ModelCard.from_template(ModelCardData())
+
+        card.data["library_name"] = "peft"
+
+        model_config = BaseTuner.get_model_config(self)
+        model_config = None if model_config == DUMMY_MODEL_CONFIG else model_config
+        if model_config is not None and "_name_or_path" in model_config:
+            card.data["base_model"] = model_config["_name_or_path"]
+
+        lines = card.text.splitlines()
+
+        quantization_config = None
+        if hasattr(model_config, "quantization_config"):
+            quantization_config = self.config.quantization_config.to_dict()
+        training_config_text = ""
+        quantization_prefix = "The following `bitsandbytes` quantization config was used during training:"
+        # Adds quantization information if it was used
+        if quantization_config is not None:
+            training_config_text += f"\n{quantization_prefix}\n"
+            training_config_text += "\n".join([f"- {name}: {value}" for name, value in quantization_config.items()])
+            training_config_text += "\n"
+
+        training_procedure_heading = "## Training procedure"
+        if quantization_prefix not in lines and bool(training_config_text):
+            if training_procedure_heading in lines:
+                lines.insert(lines.index(training_procedure_heading) + 2, training_config_text)
+            else:
+                lines.append(f"{training_procedure_heading}\n{training_config_text}")
+
+        # Adds peft version
+        framework_block_heading = "### Framework versions"
+        if f"- PEFT {__version__}" not in lines:
+            if framework_block_heading in lines:
+                lines.insert(lines.index(framework_block_heading) + 2, f"- PEFT {__version__}")
+            else:
+                lines.append(f"{framework_block_heading}\n\n- PEFT {__version__}")
+
+        card.text = "\n".join(lines)
+        card.save(filename)
+
+
+class PeftModelForSequenceClassification(PeftModel):
+    """
+    Peft model for sequence classification tasks.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): Base transformer model.
+        peft_config ([`PeftConfig`]): Peft config.
+        adapter_name (`str`,  *optional*): The name of the adapter, defaults to `"default"`.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+
+    **Attributes**:
+        - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model.
+        - **cls_layer_name** (`str`) -- The name of the classification layer.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForSequenceClassification
+        >>> from peft import PeftModelForSequenceClassification, get_peft_config
+
+        >>> config = {
+        ...     "peft_type": "PREFIX_TUNING",
+        ...     "task_type": "SEQ_CLS",
+        ...     "inference_mode": False,
+        ...     "num_virtual_tokens": 20,
+        ...     "token_dim": 768,
+        ...     "num_transformer_submodules": 1,
+        ...     "num_attention_heads": 12,
+        ...     "num_layers": 12,
+        ...     "encoder_hidden_size": 768,
+        ...     "prefix_projection": False,
+        ...     "postprocess_past_key_value_function": None,
+        ... }
+
+        >>> peft_config = get_peft_config(config)
+        >>> model = AutoModelForSequenceClassification.from_pretrained("bert-base-cased")
+        >>> peft_model = PeftModelForSequenceClassification(model, peft_config)
+        >>> peft_model.print_trainable_parameters()
+        trainable params: 370178 || all params: 108680450 || trainable%: 0.3406113979101117
+        ```
+    """
+
+    def __init__(
+        self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs
+    ) -> None:
+        super().__init__(model, peft_config, adapter_name, **kwargs)
+
+        classifier_module_names = ["classifier", "score"]
+        if self.modules_to_save is None:
+            self.modules_to_save = set(classifier_module_names)
+        else:
+            self.modules_to_save.update(classifier_module_names)
+
+        if hasattr(peft_config, "modules_to_save"):
+            if peft_config.modules_to_save is None:
+                peft_config.modules_to_save = classifier_module_names[:]
+            else:
+                peft_config.modules_to_save.extend(classifier_module_names)
+
+        if self.modules_to_save:
+            for name, _ in self.base_model.named_children():
+                if any(module_name in name for module_name in self.modules_to_save):
+                    self.cls_layer_name = name
+                    break
+
+        # to make sure classifier layer is trainable; this may add a new ModulesToSaveWrapper
+        _set_trainable(self, adapter_name, module_names=getattr(peft_config, "modules_to_save", None))
+
+    def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None:
+        """
+        Add an adapter to the model based on the passed configuration.
+
+        This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`].
+
+        The name for the new adapter should be unique.
+
+        The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active
+        adapter.
+
+        Args:
+            adapter_name (`str`):
+                The name of the adapter to be added.
+            peft_config ([`PeftConfig`]):
+                The configuration of the adapter to be added.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device. Useful to speed up the process when loading saved
+                adapters. Don't use this option when creating a new PEFT adapter for training.
+
+        """
+        # ensure that additional adapters also add the classifier layer to modules_to_save
+        if hasattr(peft_config, "modules_to_save"):
+            classifier_module_names = ["classifier", "score"]
+            if peft_config.modules_to_save is None:
+                peft_config.modules_to_save = classifier_module_names[:]
+            else:
+                peft_config.modules_to_save.extend(classifier_module_names)
+
+        return super().add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        labels=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        task_ids=None,
+        **kwargs,
+    ):
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+        peft_config = self.active_peft_config
+        if not peft_config.is_prompt_learning:
+            with self._enable_peft_forward_hooks(**kwargs):
+                kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                if peft_config.peft_type == PeftType.POLY:
+                    kwargs["task_ids"] = task_ids
+                return self.base_model(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    inputs_embeds=inputs_embeds,
+                    labels=labels,
+                    output_attentions=output_attentions,
+                    output_hidden_states=output_hidden_states,
+                    return_dict=return_dict,
+                    **kwargs,
+                )
+
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        if attention_mask is not None:
+            # concat prompt attention mask
+            prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device)
+            attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1)
+        if kwargs.get("position_ids", None) is not None:
+            warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.")
+            kwargs["position_ids"] = None
+        kwargs.update(
+            {
+                "attention_mask": attention_mask,
+                "labels": labels,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+            }
+        )
+
+        if peft_config.peft_type == PeftType.PREFIX_TUNING:
+            return self._prefix_tuning_forward(input_ids=input_ids, **kwargs)
+        else:
+            if kwargs.get("token_type_ids", None) is not None:
+                kwargs["token_type_ids"] = torch.cat(
+                    (
+                        torch.zeros(batch_size, peft_config.num_virtual_tokens).to(self.word_embeddings.weight.device),
+                        kwargs["token_type_ids"],
+                    ),
+                    dim=1,
+                ).long()
+            if inputs_embeds is None:
+                inputs_embeds = self.word_embeddings(input_ids)
+            prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids)
+            prompts = prompts.to(inputs_embeds.dtype)
+            inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1)
+            return self.base_model(inputs_embeds=inputs_embeds, **kwargs)
+
+    def _prefix_tuning_forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        labels=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        **kwargs,
+    ):
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        past_key_values = self.get_prompt(batch_size)
+        fwd_params = list(inspect.signature(self.base_model.forward).parameters.keys())
+        kwargs.update(
+            {
+                "input_ids": input_ids,
+                "attention_mask": attention_mask,
+                "inputs_embeds": inputs_embeds,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+                "past_key_values": past_key_values,
+            }
+        )
+        if "past_key_values" in fwd_params:
+            return self.base_model(labels=labels, **kwargs)
+        else:
+            transformer_backbone_name = self.base_model.get_submodule(self.transformer_backbone_name)
+            fwd_params = list(inspect.signature(transformer_backbone_name.forward).parameters.keys())
+            if "past_key_values" not in fwd_params:
+                raise ValueError("Model does not support past key values which are required for prefix tuning.")
+            outputs = transformer_backbone_name(**kwargs)
+            pooled_output = outputs[1] if len(outputs) > 1 else outputs[0]
+            if "dropout" in [name for name, _ in list(self.base_model.named_children())]:
+                pooled_output = self.base_model.dropout(pooled_output)
+            logits = self.base_model.get_submodule(self.cls_layer_name)(pooled_output)
+
+            loss = None
+            if labels is not None:
+                if self.config.problem_type is None:
+                    if self.base_model.num_labels == 1:
+                        self.config.problem_type = "regression"
+                    elif self.base_model.num_labels > 1 and (labels.dtype == torch.long or labels.dtype == torch.int):
+                        self.config.problem_type = "single_label_classification"
+                    else:
+                        self.config.problem_type = "multi_label_classification"
+
+                if self.config.problem_type == "regression":
+                    loss_fct = MSELoss()
+                    if self.base_model.num_labels == 1:
+                        loss = loss_fct(logits.squeeze(), labels.squeeze())
+                    else:
+                        loss = loss_fct(logits, labels)
+                elif self.config.problem_type == "single_label_classification":
+                    loss_fct = CrossEntropyLoss()
+                    loss = loss_fct(logits.view(-1, self.base_model.num_labels), labels.view(-1))
+                elif self.config.problem_type == "multi_label_classification":
+                    loss_fct = BCEWithLogitsLoss()
+                    loss = loss_fct(logits, labels)
+            if not return_dict:
+                output = (logits,) + outputs[2:]
+                return ((loss,) + output) if loss is not None else output
+
+            return SequenceClassifierOutput(
+                loss=loss,
+                logits=logits,
+                hidden_states=outputs.hidden_states,
+                attentions=outputs.attentions,
+            )
+
+
+class PeftModelForCausalLM(PeftModel):
+    """
+    Peft model for causal language modeling.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): Base transformer model.
+        peft_config ([`PeftConfig`]): Peft config.
+        adapter_name (`str`,  *optional*): The name of the adapter, defaults to `"default"`.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import PeftModelForCausalLM, get_peft_config
+
+        >>> config = {
+        ...     "peft_type": "PREFIX_TUNING",
+        ...     "task_type": "CAUSAL_LM",
+        ...     "inference_mode": False,
+        ...     "num_virtual_tokens": 20,
+        ...     "token_dim": 1280,
+        ...     "num_transformer_submodules": 1,
+        ...     "num_attention_heads": 20,
+        ...     "num_layers": 36,
+        ...     "encoder_hidden_size": 1280,
+        ...     "prefix_projection": False,
+        ...     "postprocess_past_key_value_function": None,
+        ... }
+
+        >>> peft_config = get_peft_config(config)
+        >>> model = AutoModelForCausalLM.from_pretrained("gpt2-large")
+        >>> peft_model = PeftModelForCausalLM(model, peft_config)
+        >>> peft_model.print_trainable_parameters()
+        trainable params: 1843200 || all params: 775873280 || trainable%: 0.23756456724479544
+        ```
+    """
+
+    def __init__(
+        self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs
+    ) -> None:
+        super().__init__(model, peft_config, adapter_name, **kwargs)
+        self.base_model_prepare_inputs_for_generation = self.base_model.prepare_inputs_for_generation
+
+    def forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        labels=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        task_ids=None,
+        **kwargs,
+    ):
+        peft_config = self.active_peft_config
+        if not peft_config.is_prompt_learning:
+            if self.base_model.config.model_type == "mpt":
+                if inputs_embeds is not None:
+                    raise AssertionError("forward in MPTForCausalLM does not support inputs_embeds")
+                return self.base_model(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    labels=labels,
+                    output_attentions=output_attentions,
+                    output_hidden_states=output_hidden_states,
+                    return_dict=return_dict,
+                    **kwargs,
+                )
+
+            if peft_config.peft_type == PeftType.POLY:
+                kwargs["task_ids"] = task_ids
+
+            with self._enable_peft_forward_hooks(**kwargs):
+                kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                return self.base_model(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    inputs_embeds=inputs_embeds,
+                    labels=labels,
+                    output_attentions=output_attentions,
+                    output_hidden_states=output_hidden_states,
+                    return_dict=return_dict,
+                    **kwargs,
+                )
+
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        if attention_mask is not None:
+            # concat prompt attention mask
+            prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device)
+            attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1)
+
+        if kwargs.get("position_ids", None) is not None:
+            warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.")
+            kwargs["position_ids"] = None
+        if kwargs.get("token_type_ids", None) is not None:
+            warnings.warn("Token type ids are not supported for parameter efficient tuning. Ignoring token type ids")
+            kwargs["token_type_ids"] = None
+        kwargs.update(
+            {
+                "attention_mask": attention_mask,
+                "labels": labels,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+            }
+        )
+
+        if peft_config.peft_type == PeftType.PREFIX_TUNING:
+            # overwrite past_kv in kwargs
+            kwargs["past_key_values"] = self.get_prompt(batch_size)
+            return self.base_model(input_ids=input_ids, inputs_embeds=inputs_embeds, **kwargs)
+        elif peft_config.peft_type == PeftType.CPT:
+            return self._cpt_forward(input_ids, inputs_embeds, peft_config, task_ids, batch_size, **kwargs)
+        else:
+            if inputs_embeds is None:
+                inputs_embeds = self.word_embeddings(input_ids)
+            # concat prompt labels
+            if labels is not None:
+                prefix_labels = torch.full((batch_size, peft_config.num_virtual_tokens), -100).to(labels.device)
+                kwargs["labels"] = torch.cat((prefix_labels, labels), dim=1)
+            prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids)
+            prompts = prompts.to(inputs_embeds.dtype)
+            inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1)
+            return self.base_model(inputs_embeds=inputs_embeds, **kwargs)
+
+    def _cpt_forward(self, input_ids, inputs_embeds, peft_config, task_ids, batch_size, **kwargs):
+        # Extract labels from kwargs
+        labels = kwargs.pop("labels")
+        device = [i.device for i in [input_ids, inputs_embeds, labels] if i is not None][0]
+        # Extract input_type_mask from kwargs and move it to the same device as labels
+        if "input_type_mask" in kwargs.keys():
+            input_type_mask = kwargs.pop("input_type_mask").to(device)
+        else:
+            if input_ids is None:
+                N_tokens = inputs_embeds.shape[1]
+            else:
+                N_tokens = input_ids.shape[1]
+            input_type_mask = torch.ones((batch_size, N_tokens)).to(device) * 4
+
+        cpt_token_ids = peft_config.cpt_token_ids
+        cpt_tokens_type_mask = peft_config.cpt_tokens_type_mask
+
+        # Generate embeddings if not provided
+        if inputs_embeds is None:
+            inputs_embeds = self.word_embeddings(input_ids)
+        # Get prompt and concatenate with input embeddings
+        prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids)
+        prompts = prompts.to(inputs_embeds.dtype)
+        inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1)
+        # If labels are provided, generate prefix labels and type mask
+        cpt_labels = None
+        if labels is not None:
+            # Generate prefix labels and concatenate with the input labels
+            prefix_labels = torch.Tensor(cpt_token_ids).long().view(1, -1)
+            prefix_labels = prefix_labels.repeat(batch_size, 1).to(labels.device)
+            cpt_labels = torch.cat((prefix_labels, labels), dim=1)
+            # Generate prefix type mask and shift input type mask values to avoid conflicts
+            prefix_type_mask = torch.Tensor(cpt_tokens_type_mask).long().view(1, -1)
+            prefix_type_mask = prefix_type_mask.repeat(batch_size, 1).to(labels.device)
+            adjusted_input_type_mask = input_type_mask
+            adjusted_input_type_mask[adjusted_input_type_mask > 0] += prefix_type_mask.max()
+            # Concatenate prefix and shifted input type masks
+            cpt_type_mask = torch.cat((prefix_type_mask, adjusted_input_type_mask), dim=1)
+            # Identify valid label positions and mask invalid ones with -100
+            labels_idx = (cpt_type_mask > 0) & (cpt_type_mask % 4 == 0)
+            cpt_labels[~labels_idx] = -100
+            # Update kwargs with the modified labels
+
+        kwargs["labels"] = cpt_labels
+        # Pass the modified inputs to the base model
+        base_model_output = self.base_model(inputs_embeds=inputs_embeds, **kwargs)
+        if labels is None:
+            return base_model_output
+        else:
+            # Calculate the loss using the custom CPT loss function
+            cpt_embedding = PEFT_TYPE_TO_TUNER_MAPPING[peft_config.peft_type]
+            base_model_output = cpt_embedding.calculate_loss(
+                base_model_output, cpt_labels, cpt_type_mask, self.peft_config["default"]
+            )
+            return base_model_output
+
+    def generate(self, *args, **kwargs):
+        peft_config = self.active_peft_config
+        self.base_model.prepare_inputs_for_generation = self.prepare_inputs_for_generation
+        if hasattr(self.base_model, "model"):
+            self.base_model.model.generation_config = self.generation_config
+        else:
+            self.base_model.generation_config = self.generation_config
+        try:
+            if not peft_config.is_prompt_learning:
+                with self._enable_peft_forward_hooks(*args, **kwargs):
+                    kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                    outputs = self.base_model.generate(*args, **kwargs)
+            else:
+                outputs = self.base_model.generate(**kwargs)
+        except:
+            self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation
+            raise
+        else:
+            self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation
+            return outputs
+
+    def prepare_inputs_for_generation(self, *args, task_ids: Optional[torch.Tensor] = None, **kwargs):
+        peft_config = self.active_peft_config
+        model_kwargs = self.base_model_prepare_inputs_for_generation(*args, **kwargs)
+
+        # https://github.com/huggingface/transformers/pull/26681/ introduced new cache format
+        # for some architectures which requires a special fix for prompt tuning etc.
+        # TODO: starting with transformers 4.38, all architectures should support caching.
+        uses_transformers_4_38 = packaging.version.parse(transformers.__version__) >= packaging.version.parse("4.38.0")
+        uses_transformers_4_36 = packaging.version.parse(transformers.__version__) >= packaging.version.parse("4.36.0")
+        transformers_new_cache_archs = ["llama", "mistral", "persimmon", "phi"]
+        if packaging.version.parse(transformers.__version__) > packaging.version.parse("4.43.3"):
+            # https://github.com/huggingface/transformers/pull/31445
+            transformers_new_cache_archs.append("bloom")
+
+        uses_cache = uses_transformers_4_38 or (
+            uses_transformers_4_36 and self.base_model.config.model_type in transformers_new_cache_archs
+        )
+
+        if peft_config.peft_type == PeftType.POLY:
+            model_kwargs["task_ids"] = task_ids
+        if peft_config.is_prompt_learning:
+            if uses_cache and (model_kwargs.get("past_key_values", None) is not None):
+                # change in the logic of `prepare_inputs_for_generation` makes the below code necessary
+                # In prompt learning methods, past key values are longer when compared to the `input_ids`.
+                # As such only consider the last input ids in the autogressive generation phase.
+                past_key_values = model_kwargs["past_key_values"]
+                if isinstance(past_key_values, (tuple, list)):
+                    seq_len = past_key_values[0][0].shape[-2]
+                else:  # using transformers kv cache
+                    seq_len = past_key_values.get_seq_length()
+                if seq_len >= model_kwargs["input_ids"].shape[1]:
+                    model_kwargs["input_ids"] = model_kwargs["input_ids"][:, -1:]
+
+            if model_kwargs.get("attention_mask", None) is not None:
+                size = model_kwargs["input_ids"].shape[0], peft_config.num_virtual_tokens
+                prefix_attention_mask = torch.ones(size).to(model_kwargs["input_ids"].device)
+                model_kwargs["attention_mask"] = torch.cat(
+                    (prefix_attention_mask, model_kwargs["attention_mask"]), dim=1
+                )
+
+            if model_kwargs.get("position_ids", None) is not None:
+                warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.")
+                model_kwargs["position_ids"] = None
+
+            if kwargs.get("token_type_ids", None) is not None:
+                warnings.warn(
+                    "Token type ids are not supported for parameter efficient tuning. Ignoring token type ids"
+                )
+                kwargs["token_type_ids"] = None
+
+            # no past_key_values or past_key_values empty cache
+            requires_prompt_injection = (model_kwargs.get("past_key_values", None) is None) or (
+                isinstance(model_kwargs["past_key_values"], transformers.Cache)
+                and not model_kwargs["past_key_values"].get_seq_length()
+            )
+
+            if requires_prompt_injection and peft_config.peft_type == PeftType.PREFIX_TUNING:
+                new_past_key_values = self.get_prompt(batch_size=model_kwargs["input_ids"].shape[0])
+                model_kwargs["past_key_values"] = new_past_key_values
+            elif requires_prompt_injection:
+                inputs_embeds = self.word_embeddings(model_kwargs["input_ids"])
+                prompts = self.get_prompt(batch_size=model_kwargs["input_ids"].shape[0], task_ids=task_ids)
+                prompts = prompts.to(inputs_embeds.dtype)
+                model_kwargs["inputs_embeds"] = torch.cat((prompts, inputs_embeds), dim=1)
+                model_kwargs["input_ids"] = None
+
+        # For transformers>=4.38.0 - for some architectures such as Llama, `cache_position` is
+        # passed in the forward pass to keep track of the position ids of the cache. We have to
+        # pop that from `model_kwargs` as `cache_position` is properly created by the model, using the passed
+        # `inputs_embeds`: https://github.com/huggingface/transformers/blob/593230f0a1150ea9c0477b9d859f25daf73c8c33/src/transformers/models/llama/modeling_llama.py#L956
+        _ = model_kwargs.pop("cache_position", None)
+
+        return model_kwargs
+
+
+class PeftModelForSeq2SeqLM(PeftModel):
+    """
+    Peft model for sequence-to-sequence language modeling.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): Base transformer model.
+        peft_config ([`PeftConfig`]): Peft config.
+        adapter_name (`str`,  *optional*): The name of the adapter, defaults to `"default"`.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForSeq2SeqLM
+        >>> from peft import PeftModelForSeq2SeqLM, get_peft_config
+
+        >>> config = {
+        ...     "peft_type": "LORA",
+        ...     "task_type": "SEQ_2_SEQ_LM",
+        ...     "inference_mode": False,
+        ...     "r": 8,
+        ...     "target_modules": ["q", "v"],
+        ...     "lora_alpha": 32,
+        ...     "lora_dropout": 0.1,
+        ...     "fan_in_fan_out": False,
+        ...     "enable_lora": None,
+        ...     "bias": "none",
+        ... }
+
+        >>> peft_config = get_peft_config(config)
+        >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
+        >>> peft_model = PeftModelForSeq2SeqLM(model, peft_config)
+        >>> peft_model.print_trainable_parameters()
+        trainable params: 884736 || all params: 223843584 || trainable%: 0.3952474242013566
+        ```
+    """
+
+    def __init__(
+        self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs
+    ) -> None:
+        super().__init__(model, peft_config, adapter_name, **kwargs)
+        self.base_model_prepare_inputs_for_generation = self.base_model.prepare_inputs_for_generation
+        self.base_model_prepare_encoder_decoder_kwargs_for_generation = (
+            self.base_model._prepare_encoder_decoder_kwargs_for_generation
+        )
+
+    def forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        decoder_input_ids=None,
+        decoder_attention_mask=None,
+        decoder_inputs_embeds=None,
+        labels=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        task_ids=None,
+        **kwargs,
+    ):
+        peft_config = self.active_peft_config
+        if not peft_config.is_prompt_learning:
+            if peft_config.peft_type == PeftType.POLY:
+                kwargs["task_ids"] = task_ids
+
+            with self._enable_peft_forward_hooks(**kwargs):
+                kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                return self.base_model(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    inputs_embeds=inputs_embeds,
+                    decoder_input_ids=decoder_input_ids,
+                    decoder_attention_mask=decoder_attention_mask,
+                    decoder_inputs_embeds=decoder_inputs_embeds,
+                    labels=labels,
+                    output_attentions=output_attentions,
+                    output_hidden_states=output_hidden_states,
+                    return_dict=return_dict,
+                    **kwargs,
+                )
+
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        if decoder_attention_mask is not None:
+            # concat prompt attention mask
+            prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(
+                decoder_attention_mask.device
+            )
+            if peft_config.peft_type not in [PeftType.PROMPT_TUNING, PeftType.P_TUNING]:
+                decoder_attention_mask = torch.cat((prefix_attention_mask, decoder_attention_mask), dim=1)
+
+        if kwargs.get("position_ids", None) is not None:
+            warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.")
+            kwargs["position_ids"] = None
+        if kwargs.get("token_type_ids", None) is not None:
+            warnings.warn("Token type ids are not supported for parameter efficient tuning. Ignoring token type ids")
+            kwargs["token_type_ids"] = None
+        kwargs.update(
+            {
+                "attention_mask": attention_mask,
+                "decoder_attention_mask": decoder_attention_mask,
+                "labels": labels,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+            }
+        )
+
+        if peft_config.peft_type == PeftType.PREFIX_TUNING:
+            # overwrite past_kv in kwargs
+            kwargs["past_key_values"] = self.get_prompt(batch_size)
+            return self.base_model(
+                input_ids=input_ids,
+                decoder_input_ids=decoder_input_ids,
+                decoder_inputs_embeds=decoder_inputs_embeds,
+                **kwargs,
+            )
+        elif peft_config.peft_type in [PeftType.PROMPT_TUNING, PeftType.P_TUNING]:
+            if inputs_embeds is None:
+                inputs_embeds = self.word_embeddings(input_ids)
+
+            if attention_mask is not None:
+                # concat prompt attention mask
+                prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(
+                    attention_mask.device
+                )
+                kwargs["attention_mask"] = torch.cat((prefix_attention_mask, attention_mask), dim=1)
+
+            prompts = self.get_prompt(batch_size=batch_size)
+            prompts = prompts.to(inputs_embeds.dtype)
+            inputs_embeds = torch.cat((prompts[:, : peft_config.num_virtual_tokens], inputs_embeds), dim=1)
+
+            return self.base_model(
+                inputs_embeds=inputs_embeds,
+                decoder_input_ids=decoder_input_ids,
+                decoder_inputs_embeds=decoder_inputs_embeds,
+                **kwargs,
+            )
+        else:
+            if inputs_embeds is None:
+                inputs_embeds = self.word_embeddings(input_ids)
+            if decoder_inputs_embeds is None and decoder_input_ids is None:
+                decoder_input_ids = shift_tokens_right(
+                    labels, self.config.pad_token_id, self.config.decoder_start_token_id
+                )
+                decoder_inputs_embeds = self.word_embeddings(decoder_input_ids)
+
+            if attention_mask is not None:
+                # concat prompt attention mask
+                prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(
+                    attention_mask.device
+                )
+                kwargs["attention_mask"] = torch.cat((prefix_attention_mask, attention_mask), dim=1)
+            # concat prompt labels
+            if labels is not None:
+                if peft_config.num_transformer_submodules == 1:
+                    kwargs["labels"] = labels
+                elif peft_config.num_transformer_submodules == 2:
+                    prefix_labels = torch.full((batch_size, peft_config.num_virtual_tokens), -100).to(labels.device)
+                    kwargs["labels"] = torch.cat((prefix_labels, labels), dim=1)
+            prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids)
+            prompts = prompts.to(inputs_embeds.dtype)
+            inputs_embeds = torch.cat((prompts[:, : peft_config.num_virtual_tokens], inputs_embeds), dim=1)
+            if peft_config.num_transformer_submodules == 1:
+                return self.base_model(inputs_embeds=inputs_embeds, **kwargs)
+            elif peft_config.num_transformer_submodules == 2:
+                decoder_inputs_embeds = torch.cat(
+                    (prompts[:, peft_config.num_virtual_tokens :], decoder_inputs_embeds), dim=1
+                )
+                return self.base_model(
+                    inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, **kwargs
+                )
+
+    def generate(self, **kwargs):
+        peft_config = self.active_peft_config
+        self.base_model.prepare_inputs_for_generation = self.prepare_inputs_for_generation
+        self.base_model._prepare_encoder_decoder_kwargs_for_generation = (
+            self._prepare_encoder_decoder_kwargs_for_generation
+        )
+        try:
+            if not peft_config.is_prompt_learning:
+                with self._enable_peft_forward_hooks(**kwargs):
+                    kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                    outputs = self.base_model.generate(**kwargs)
+            else:
+                if "input_ids" not in kwargs:
+                    raise ValueError("input_ids must be provided for Peft model generation")
+                if kwargs.get("position_ids", None) is not None:
+                    warnings.warn(
+                        "Position ids are not supported for parameter efficient tuning. Ignoring position ids."
+                    )
+                    kwargs["position_ids"] = None
+                if kwargs.get("token_type_ids", None) is not None:
+                    warnings.warn(
+                        "Token type ids are not supported for parameter efficient tuning. Ignoring token type ids"
+                    )
+                    kwargs["token_type_ids"] = None
+
+                if peft_config.peft_type == PeftType.PREFIX_TUNING:
+                    outputs = self.base_model.generate(**kwargs)
+                elif peft_config.peft_type in [
+                    PeftType.PROMPT_TUNING,
+                    PeftType.P_TUNING,
+                    PeftType.MULTITASK_PROMPT_TUNING,
+                ]:
+                    kwargs = deepcopy(kwargs)
+
+                    if "encoder_outputs" in kwargs:
+                        del kwargs["encoder_outputs"]
+                        warnings.warn(
+                            "`encoder_outputs` should not be passed to `generate` when using prompt tuning. Ignoring it."
+                        )
+
+                    input_ids = kwargs.pop("input_ids")
+                    inputs_embeds = self.word_embeddings(input_ids)
+                    batch_size = inputs_embeds.shape[0]
+                    prompts = self.get_prompt(batch_size=batch_size, task_ids=kwargs.pop("task_ids", None))
+                    prompts = prompts.to(inputs_embeds.dtype)
+
+                    inputs_embeds = torch.cat((prompts[:, : peft_config.num_virtual_tokens], inputs_embeds), dim=1)
+                    kwargs["inputs_embeds"] = inputs_embeds
+
+                    if "attention_mask" in kwargs:
+                        prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(
+                            kwargs["attention_mask"].device
+                        )
+                        kwargs["attention_mask"] = torch.cat((prefix_attention_mask, kwargs["attention_mask"]), dim=1)
+
+                    return self.base_model.generate(**kwargs)
+                else:
+                    raise NotImplementedError
+        except:
+            self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation
+            self.base_model._prepare_encoder_decoder_kwargs_for_generation = (
+                self.base_model_prepare_encoder_decoder_kwargs_for_generation
+            )
+            raise
+        else:
+            self.base_model.prepare_inputs_for_generation = self.base_model_prepare_inputs_for_generation
+            self.base_model._prepare_encoder_decoder_kwargs_for_generation = (
+                self.base_model_prepare_encoder_decoder_kwargs_for_generation
+            )
+            return outputs
+
+    def prepare_inputs_for_generation(self, *args, task_ids: torch.Tensor = None, **kwargs):
+        peft_config = self.active_peft_config
+        model_kwargs = self.base_model_prepare_inputs_for_generation(*args, **kwargs)
+        if peft_config.peft_type == PeftType.POLY:
+            model_kwargs["task_ids"] = task_ids
+        elif peft_config.peft_type == PeftType.PREFIX_TUNING:
+            past_key_values = model_kwargs.get("past_key_values", None)
+            cache_position = model_kwargs.get("cache_position", [None])
+            # check prefill stage
+            is_prefill_stage = (
+                # old cache implementation
+                (past_key_values is None)
+                # new cache implementation
+                or (isinstance(past_key_values, Cache) and (cache_position[0] == 0))
+            )
+            if is_prefill_stage:
+                batch_size = model_kwargs["decoder_input_ids"].shape[0]
+                new_past_key_values = self.get_prompt(batch_size)
+                model_kwargs["past_key_values"] = new_past_key_values
+
+        return model_kwargs
+
+
+class PeftModelForTokenClassification(PeftModel):
+    """
+    Peft model for token classification tasks.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): Base transformer model.
+        peft_config ([`PeftConfig`]): Peft config.
+        adapter_name (`str`,  *optional*): The name of the adapter, defaults to `"default"`.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+
+    **Attributes**:
+        - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model.
+        - **cls_layer_name** (`str`) -- The name of the classification layer.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForSequenceClassification
+        >>> from peft import PeftModelForTokenClassification, get_peft_config
+
+        >>> config = {
+        ...     "peft_type": "PREFIX_TUNING",
+        ...     "task_type": "TOKEN_CLS",
+        ...     "inference_mode": False,
+        ...     "num_virtual_tokens": 20,
+        ...     "token_dim": 768,
+        ...     "num_transformer_submodules": 1,
+        ...     "num_attention_heads": 12,
+        ...     "num_layers": 12,
+        ...     "encoder_hidden_size": 768,
+        ...     "prefix_projection": False,
+        ...     "postprocess_past_key_value_function": None,
+        ... }
+
+        >>> peft_config = get_peft_config(config)
+        >>> model = AutoModelForTokenClassification.from_pretrained("bert-base-cased")
+        >>> peft_model = PeftModelForTokenClassification(model, peft_config)
+        >>> peft_model.print_trainable_parameters()
+        trainable params: 370178 || all params: 108680450 || trainable%: 0.3406113979101117
+        ```
+    """
+
+    def __init__(
+        self, model: torch.nn.Module, peft_config: PeftConfig = None, adapter_name: str = "default", **kwargs
+    ) -> None:
+        super().__init__(model, peft_config, adapter_name, **kwargs)
+
+        classifier_module_names = ["classifier", "score"]
+        if self.modules_to_save is None:
+            self.modules_to_save = set(classifier_module_names)
+        else:
+            self.modules_to_save.update(classifier_module_names)
+
+        if hasattr(peft_config, "modules_to_save"):
+            if peft_config.modules_to_save is None:
+                peft_config.modules_to_save = classifier_module_names[:]
+            else:
+                peft_config.modules_to_save.extend(classifier_module_names)
+
+        if self.modules_to_save is not None:
+            for name, _ in self.base_model.named_children():
+                if any(module_name in name for module_name in self.modules_to_save):
+                    self.cls_layer_name = name
+                    break
+
+        # to make sure classifier layer is trainable; this may add a new ModulesToSaveWrapper
+        _set_trainable(self, adapter_name, module_names=getattr(peft_config, "modules_to_save", None))
+
+    def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None:
+        """
+        Add an adapter to the model based on the passed configuration.
+
+        This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`].
+
+        The name for the new adapter should be unique.
+
+        The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active
+        adapter.
+
+        Args:
+            adapter_name (`str`):
+                The name of the adapter to be added.
+            peft_config ([`PeftConfig`]):
+                The configuration of the adapter to be added.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device. Useful to speed up the process when loading saved
+                adapters. Don't use this option when creating a new PEFT adapter for training.
+
+        """
+        # ensure that additional adapters also add the classifier layer to modules_to_save
+        if hasattr(peft_config, "modules_to_save"):
+            classifier_module_names = ["classifier", "score"]
+            if peft_config.modules_to_save is None:
+                peft_config.modules_to_save = classifier_module_names[:]
+            else:
+                peft_config.modules_to_save.extend(classifier_module_names)
+
+        return super().add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        labels=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        task_ids=None,
+        **kwargs,
+    ):
+        peft_config = self.active_peft_config
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        if not peft_config.is_prompt_learning:
+            with self._enable_peft_forward_hooks(**kwargs):
+                kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                if peft_config.peft_type == PeftType.POLY:
+                    kwargs["task_ids"] = task_ids
+                return self.base_model(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    inputs_embeds=inputs_embeds,
+                    labels=labels,
+                    output_attentions=output_attentions,
+                    output_hidden_states=output_hidden_states,
+                    return_dict=return_dict,
+                    **kwargs,
+                )
+
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        if attention_mask is not None:
+            # concat prompt attention mask
+            prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device)
+            attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1)
+        if kwargs.get("position_ids", None) is not None:
+            warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.")
+            kwargs["position_ids"] = None
+        kwargs.update(
+            {
+                "attention_mask": attention_mask,
+                "labels": labels,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+            }
+        )
+
+        if peft_config.peft_type == PeftType.PREFIX_TUNING:
+            return self._prefix_tuning_forward(input_ids=input_ids, **kwargs)
+        else:
+            if kwargs.get("token_type_ids", None) is not None:
+                kwargs["token_type_ids"] = torch.cat(
+                    (
+                        torch.zeros(batch_size, peft_config.num_virtual_tokens).to(self.word_embeddings.weight.device),
+                        kwargs["token_type_ids"],
+                    ),
+                    dim=1,
+                ).long()
+            if inputs_embeds is None:
+                inputs_embeds = self.word_embeddings(input_ids)
+            prompts = self.get_prompt(batch_size=batch_size, task_ids=task_ids)
+            prompts = prompts.to(inputs_embeds.dtype)
+            inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1)
+            return self.base_model(inputs_embeds=inputs_embeds, **kwargs)
+
+    def _prefix_tuning_forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        labels=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        **kwargs,
+    ):
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        past_key_values = self.get_prompt(batch_size)
+        fwd_params = list(inspect.signature(self.base_model.forward).parameters.keys())
+        kwargs.update(
+            {
+                "input_ids": input_ids,
+                "attention_mask": attention_mask,
+                "inputs_embeds": inputs_embeds,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+                "past_key_values": past_key_values,
+            }
+        )
+        if "past_key_values" in fwd_params:
+            return self.base_model(labels=labels, **kwargs)
+        else:
+            transformer_backbone_name = self.base_model.get_submodule(self.transformer_backbone_name)
+            fwd_params = list(inspect.signature(transformer_backbone_name.forward).parameters.keys())
+            if "past_key_values" not in fwd_params:
+                raise ValueError("Model does not support past key values which are required for prefix tuning.")
+            outputs = transformer_backbone_name(**kwargs)
+            sequence_output = outputs[0]
+            if "dropout" in [name for name, _ in list(self.base_model.named_children())]:
+                sequence_output = self.base_model.dropout(sequence_output)
+            logits = self.base_model.get_submodule(self.cls_layer_name)(sequence_output)
+
+            loss = None
+            if labels is not None:
+                loss_fct = CrossEntropyLoss()
+                loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1))
+
+            if not return_dict:
+                output = (logits,) + outputs[2:]
+                return ((loss,) + output) if loss is not None else output
+
+            return TokenClassifierOutput(
+                loss=loss,
+                logits=logits,
+                hidden_states=outputs.hidden_states,
+                attentions=outputs.attentions,
+            )
+
+
+class PeftModelForQuestionAnswering(PeftModel):
+    """
+    Peft model for extractive question answering.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): Base transformer model.
+        peft_config ([`PeftConfig`]): Peft config.
+        adapter_name (`str`,  *optional*): The name of the adapter, defaults to `"default"`.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+
+    **Attributes**:
+        - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model.
+        - **cls_layer_name** (`str`) -- The name of the classification layer.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForQuestionAnswering
+        >>> from peft import PeftModelForQuestionAnswering, get_peft_config
+
+        >>> config = {
+        ...     "peft_type": "LORA",
+        ...     "task_type": "QUESTION_ANS",
+        ...     "inference_mode": False,
+        ...     "r": 16,
+        ...     "target_modules": ["query", "value"],
+        ...     "lora_alpha": 32,
+        ...     "lora_dropout": 0.05,
+        ...     "fan_in_fan_out": False,
+        ...     "bias": "none",
+        ... }
+
+        >>> peft_config = get_peft_config(config)
+        >>> model = AutoModelForQuestionAnswering.from_pretrained("bert-base-cased")
+        >>> peft_model = PeftModelForQuestionAnswering(model, peft_config)
+        >>> peft_model.print_trainable_parameters()
+        trainable params: 592900 || all params: 108312580 || trainable%: 0.5473971721475013
+        ```
+    """
+
+    def __init__(
+        self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs
+    ) -> None:
+        super().__init__(model, peft_config, adapter_name, **kwargs)
+
+        qa_module_names = ["qa_outputs"]
+        if self.modules_to_save is None:
+            self.modules_to_save = set(qa_module_names)
+        else:
+            self.modules_to_save.update(qa_module_names)
+
+        if hasattr(peft_config, "modules_to_save"):
+            if peft_config.modules_to_save is None:
+                peft_config.modules_to_save = qa_module_names[:]
+            else:
+                peft_config.modules_to_save.extend(qa_module_names)
+
+        for name, _ in self.base_model.named_children():
+            if any(module_name in name for module_name in self.modules_to_save):
+                self.cls_layer_name = name
+                break
+
+        # to make sure classifier layer is trainable; this may add a new ModulesToSaveWrapper
+        _set_trainable(self, adapter_name, module_names=getattr(peft_config, "modules_to_save", None))
+
+    def add_adapter(self, adapter_name: str, peft_config: PeftConfig, low_cpu_mem_usage: bool = False) -> None:
+        """
+        Add an adapter to the model based on the passed configuration.
+
+        This adapter is not trained. To load a trained adapter, check out [`PeftModel.load_adapter`].
+
+        The name for the new adapter should be unique.
+
+        The new adapter is not automatically set as the active adapter. Use [`PeftModel.set_adapter`] to set the active
+        adapter.
+
+        Args:
+            adapter_name (`str`):
+                The name of the adapter to be added.
+            peft_config ([`PeftConfig`]):
+                The configuration of the adapter to be added.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device. Useful to speed up the process when loading saved
+                adapters. Don't use this option when creating a new PEFT adapter for training.
+
+        """
+        # ensure that additional adapters also add the classifier layer to modules_to_save
+        if hasattr(peft_config, "modules_to_save"):
+            qa_module_names = ["qa_outputs"]
+            if peft_config.modules_to_save is None:
+                peft_config.modules_to_save = qa_module_names[:]
+            else:
+                peft_config.modules_to_save.extend(qa_module_names)
+
+        return super().add_adapter(adapter_name, peft_config, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        token_type_ids=None,
+        position_ids=None,
+        inputs_embeds=None,
+        start_positions=None,
+        end_positions=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        task_ids=None,
+        **kwargs,
+    ):
+        peft_config = self.active_peft_config
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        if not peft_config.is_prompt_learning:
+            if peft_config.peft_type == PeftType.POLY:
+                kwargs["task_ids"] = task_ids
+
+            with self._enable_peft_forward_hooks(**kwargs):
+                kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                return self.base_model(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    inputs_embeds=inputs_embeds,
+                    start_positions=start_positions,
+                    end_positions=end_positions,
+                    output_attentions=output_attentions,
+                    output_hidden_states=output_hidden_states,
+                    return_dict=return_dict,
+                    **kwargs,
+                )
+
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        if attention_mask is not None:
+            # concat prompt attention mask
+            prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device)
+            attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1)
+        if kwargs.get("position_ids", None) is not None:
+            warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.")
+            kwargs["position_ids"] = None
+        kwargs.update(
+            {
+                "attention_mask": attention_mask,
+                "start_positions": start_positions,
+                "end_positions": end_positions,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+            }
+        )
+
+        if peft_config.peft_type == PeftType.PREFIX_TUNING:
+            return self._prefix_tuning_forward(input_ids=input_ids, **kwargs)
+        else:
+            if kwargs.get("token_type_ids", None) is not None:
+                kwargs["token_type_ids"] = torch.cat(
+                    (
+                        torch.zeros(batch_size, peft_config.num_virtual_tokens).to(self.word_embeddings.weight.device),
+                        kwargs["token_type_ids"],
+                    ),
+                    dim=1,
+                ).long()
+            if inputs_embeds is None:
+                inputs_embeds = self.word_embeddings(input_ids)
+            prompts = self.get_prompt(batch_size=batch_size)
+            prompts = prompts.to(inputs_embeds.dtype)
+            inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1)
+            return self.base_model(inputs_embeds=inputs_embeds, **kwargs)
+
+    def _prefix_tuning_forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        start_positions=None,
+        end_positions=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        **kwargs,
+    ):
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        past_key_values = self.get_prompt(batch_size)
+        fwd_params = list(inspect.signature(self.base_model.forward).parameters.keys())
+        kwargs.update(
+            {
+                "input_ids": input_ids,
+                "attention_mask": attention_mask,
+                "inputs_embeds": inputs_embeds,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+                "past_key_values": past_key_values,
+            }
+        )
+        if "past_key_values" in fwd_params:
+            return self.base_model(start_positions=start_positions, end_positions=end_positions, **kwargs)
+        else:
+            transformer_backbone_name = self.base_model.get_submodule(self.transformer_backbone_name)
+            fwd_params = list(inspect.signature(transformer_backbone_name.forward).parameters.keys())
+            if "past_key_values" not in fwd_params:
+                raise ValueError("Model does not support past key values which are required for prefix tuning.")
+            outputs = transformer_backbone_name(**kwargs)
+            sequence_output = outputs[0]
+            if "dropout" in [name for name, _ in list(self.base_model.named_children())]:
+                sequence_output = self.base_model.dropout(sequence_output)
+            logits = self.base_model.get_submodule(self.cls_layer_name)(sequence_output)
+            start_logits, end_logits = logits.split(1, dim=-1)
+            start_logits = start_logits.squeeze(-1).contiguous()
+            end_logits = end_logits.squeeze(-1).contiguous()
+
+            total_loss = None
+            if start_positions is not None and end_positions is not None:
+                # If we are on multi-GPU, split add a dimension
+                if len(start_positions.size()) > 1:
+                    start_positions = start_positions.squeeze(-1)
+                if len(end_positions.size()) > 1:
+                    end_positions = end_positions.squeeze(-1)
+                # sometimes the start/end positions are outside our model inputs, we ignore these terms
+                ignored_index = start_logits.size(1)
+                start_positions = start_positions.clamp(0, ignored_index)
+                end_positions = end_positions.clamp(0, ignored_index)
+
+                loss_fct = CrossEntropyLoss(ignore_index=ignored_index)
+                start_loss = loss_fct(start_logits, start_positions)
+                end_loss = loss_fct(end_logits, end_positions)
+                total_loss = (start_loss + end_loss) / 2
+
+            if not return_dict:
+                output = (start_logits, end_logits) + outputs[2:]
+                return ((total_loss,) + output) if total_loss is not None else output
+
+            return QuestionAnsweringModelOutput(
+                loss=total_loss,
+                start_logits=start_logits,
+                end_logits=end_logits,
+                hidden_states=outputs.hidden_states,
+                attentions=outputs.attentions,
+            )
+
+
+class PeftModelForFeatureExtraction(PeftModel):
+    """
+    Peft model for extracting features/embeddings from transformer models
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): Base transformer model.
+        peft_config ([`PeftConfig`]): Peft config.
+        adapter_name (`str`,  *optional*): The name of the adapter, defaults to `"default"`.
+        autocast_adapter_dtype (`bool`, *optional*):
+            Whether to autocast the adapter dtype. Defaults to `True`. Right now, this will only cast adapter weights
+            using float16 and bfloat16 to float32, as this is typically required for stable training, and only affect
+            select PEFT tuners.
+
+    **Attributes**:
+        - **config** ([`~transformers.PretrainedConfig`]) -- The configuration object of the base model.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModel
+        >>> from peft import PeftModelForFeatureExtraction, get_peft_config
+
+        >>> config = {
+        ...     "peft_type": "LORA",
+        ...     "task_type": "FEATURE_EXTRACTION",
+        ...     "inference_mode": False,
+        ...     "r": 16,
+        ...     "target_modules": ["query", "value"],
+        ...     "lora_alpha": 32,
+        ...     "lora_dropout": 0.05,
+        ...     "fan_in_fan_out": False,
+        ...     "bias": "none",
+        ... }
+        >>> peft_config = get_peft_config(config)
+        >>> model = AutoModel.from_pretrained("bert-base-cased")
+        >>> peft_model = PeftModelForFeatureExtraction(model, peft_config)
+        >>> peft_model.print_trainable_parameters()
+        ```
+    """
+
+    def __init__(self, model: torch.nn.Module, peft_config: PeftConfig, adapter_name: str = "default", **kwargs):
+        super().__init__(model, peft_config, adapter_name, **kwargs)
+
+    def forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+        task_ids=None,
+        **kwargs,
+    ):
+        peft_config = self.active_peft_config
+        if not peft_config.is_prompt_learning:
+            if peft_config.peft_type == PeftType.POLY:
+                kwargs["task_ids"] = task_ids
+
+            with self._enable_peft_forward_hooks(**kwargs):
+                kwargs = {k: v for k, v in kwargs.items() if k not in self.special_peft_forward_args}
+                return self.base_model(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    inputs_embeds=inputs_embeds,
+                    output_attentions=output_attentions,
+                    output_hidden_states=output_hidden_states,
+                    return_dict=return_dict,
+                    **kwargs,
+                )
+
+        batch_size = _get_batch_size(input_ids, inputs_embeds)
+        if attention_mask is not None:
+            # concat prompt attention mask
+            prefix_attention_mask = torch.ones(batch_size, peft_config.num_virtual_tokens).to(attention_mask.device)
+            attention_mask = torch.cat((prefix_attention_mask, attention_mask), dim=1)
+
+        if kwargs.get("position_ids", None) is not None:
+            warnings.warn("Position ids are not supported for parameter efficient tuning. Ignoring position ids.")
+            kwargs["position_ids"] = None
+        if kwargs.get("token_type_ids", None) is not None:
+            warnings.warn("Token type ids are not supported for parameter efficient tuning. Ignoring token type ids")
+            kwargs["token_type_ids"] = None
+        kwargs.update(
+            {
+                "attention_mask": attention_mask,
+                "output_attentions": output_attentions,
+                "output_hidden_states": output_hidden_states,
+                "return_dict": return_dict,
+            }
+        )
+
+        if peft_config.peft_type == PeftType.PREFIX_TUNING:
+            # overwrite past_kv in kwargs
+            kwargs["past_key_values"] = self.get_prompt(batch_size)
+            return self.base_model(input_ids=input_ids, **kwargs)
+        else:
+            if inputs_embeds is None:
+                inputs_embeds = self.word_embeddings(input_ids)
+            prompts = self.get_prompt(batch_size=batch_size)
+            prompts = prompts.to(inputs_embeds.dtype)
+            inputs_embeds = torch.cat((prompts, inputs_embeds), dim=1)
+            return self.base_model(inputs_embeds=inputs_embeds, **kwargs)
+
+
+@dataclass
+class TunerLayerStatus:
+    name: str
+    module_type: str
+    enabled: bool
+    active_adapters: list[str]
+    merged_adapters: list[str]
+    requires_grad: dict[str, bool | Literal["irregular"]]
+    available_adapters: list[str]
+    devices: dict[str, list[str]]
+
+
+def get_layer_status(model: torch.nn.Module) -> list[TunerLayerStatus]:
+    """Get the status of each adapter layer in the model.
+
+    This function returns a list of `TunerLayerStatus` dataclass instances, each of which contains the following
+    attributes:
+
+    - `name` (`str`):
+       The name of the adapter layer, e.g. `model.encoder.block.0.layer.0.SelfAttention.q`.
+    - `module_type` (`str`):
+       The type of the adapter layer, e.g. `lora.Linear`.
+    - `enabled` (`bool`):
+       Whether the adapter layer is enabled.
+    - `active_adapters` (`list[str]`):
+       The names of the active adapters, if any, e.g. `["default"]`.
+    - `merged_adapters` (`list[str]`):
+       The names of the merged adapters, if any, e.g. `["default"]`.
+    - requires_grad : dict[str, bool | Literal["irregular"]]
+       The requires_grad status of the parameters for each adapter module. Ideally, it should be either `True` or
+       `False`. If the requires_grad status is not consistent across all parameters, the value will be set to
+       `"irregular"`.
+    - `available_adapters` (`list[str]`):
+       The names of the available adapters, e.g. `["default"]`.
+    - `devices` (`dict[str, list[str]]`):
+       The devices where the parameters of the given adapter are stored, e.g. `["cuda"]`.
+
+    Args:
+        model ([Union[`~PeftModel`, `~transformers.PreTrainedModel`, `nn.Module`]]):
+            The model to get the adapter layer status from.
+
+    Returns:
+        list[`peft.peft_model.TunerLayerStatus`]:
+            A list of dataclasses, each containing the status of the corresponding adapter layer.
+
+    """
+    if isinstance(model, PeftModel):
+        base_model = model.base_model
+        if not isinstance(base_model, BaseTuner):
+            raise TypeError(
+                "get_layer_status() got an invalid PeftModel instance; prefix tuning and adaption prompt are not "
+                "supported."
+            )
+    else:
+        base_model = model
+
+    layer_status: list[TunerLayerStatus] = []
+    for name, module in base_model.named_modules():
+        if not isinstance(module, BaseTunerLayer):
+            continue
+
+        # determine if all submodules/parameters if this module require grad or not
+        mapping_requires_grad_list: dict[str, list[bool]] = collections.defaultdict(list)
+        for adapter_module_name in module.adapter_layer_names:
+            adapter_module = getattr(module, adapter_module_name)
+            if isinstance(adapter_module, torch.nn.ModuleDict):
+                for key, submodule in adapter_module.items():
+                    for param in submodule.parameters():
+                        mapping_requires_grad_list[key].append(param.requires_grad)
+            elif isinstance(adapter_module, torch.nn.ParameterDict):
+                for key, param in adapter_module.items():
+                    mapping_requires_grad_list[key].append(param.requires_grad)
+            else:
+                # strange, we don't know how to handle this, ignore for now
+                pass
+
+        def check_irrgular(vals: list[bool]) -> bool | Literal["irregular"]:
+            if all(vals):
+                return True
+            if not any(vals):
+                return False
+            return "irregular"
+
+        requires_grad = {key: check_irrgular(vals) for key, vals in mapping_requires_grad_list.items()}
+
+        devices_dd = collections.defaultdict(list)
+        for adapter_module_name in module.adapter_layer_names + module.other_param_names:
+            adapter_module = getattr(module, adapter_module_name)
+            if isinstance(adapter_module, torch.nn.ModuleDict):
+                for key, submodule in adapter_module.items():
+                    devices_dd[key].extend([param.device.type for param in submodule.parameters()])
+            elif isinstance(adapter_module, torch.nn.ParameterDict) or (
+                adapter_module.__class__.__name__ == "BufferDict"
+            ):  # VeRA
+                for key, param in adapter_module.items():
+                    devices_dd[key].append(param.device.type)
+        devices = {key: sorted(set(val)) for key, val in devices_dd.items()}
+
+        status = TunerLayerStatus(
+            name=name,
+            module_type=repr(module).partition("(")[0],
+            enabled=not module.disable_adapters,
+            active_adapters=module.active_adapters,
+            merged_adapters=module.merged_adapters,
+            requires_grad=requires_grad,
+            available_adapters=sorted(module._get_available_adapters()),
+            devices=devices,
+        )
+        layer_status.append(status)
+
+    if not layer_status:
+        raise ValueError(
+            "No adapter layers found in the model, please ensure that it's a PEFT model or that you have PEFT adapters "
+            "injected in the model."
+        )
+
+    return layer_status
+
+
+@dataclass
+class TunerModelStatus:
+    base_model_type: str
+    adapter_model_type: str
+    peft_types: dict[str, str]
+    trainable_params: int
+    total_params: int
+    num_adapter_layers: int
+    enabled: bool | Literal["irregular"]
+    active_adapters: list[str] | Literal["irregular"]
+    merged_adapters: list[str] | Literal["irregular"]
+    requires_grad: dict[str, bool | Literal["irregular"]]
+    available_adapters: list[str]
+    devices: dict[str, list[str]]
+
+
+def get_model_status(model: torch.nn.Module) -> TunerModelStatus:
+    """Get the status of tuners of the model.
+
+    This function returns a `TunerModelStatus` dataclass instance, which contains the following attributes:
+
+    - `base_model_type` (`str`):
+       The type of the base model, e.g. `T5Model`.
+    - `adapter_model_type` (`str`):
+       The type of the adapter model, e.g. `LoraModel`.
+    - `peft_types` (`dict[str, str]`):
+       The mapping of adapter name to adapter type, e.g. `{"default": "LORA"}`.
+    - `trainable_params` (`int`):
+       The number of trainable parameters in the model.
+    - `total_params` (`int`):
+       The total number of parameters in the model.
+    - `num_adapter_layers` (`int`):
+       The number of adapter layers in the model.
+    - `enabled` (`bool`, `Literal["irregular"]`):
+       Whether all adapter layers are enabled. If some are enabled and some are not, this will be `"irregular"`. This
+       means that your model is in an inconsistent state and might not work as expected.
+    - `active_adapters` (`list[str]`, `Literal["irregular"]`):
+       The names of the active adapters. If the active adapters are not consistent across all layers, this will be
+       `"irregular"`, which means that your model is in an inconsistent state and might not work as expected.
+    - `merged_adapters` (`list[str]`, `Literal["irregular"]`):
+       The names of the merged adapters. If the merged adapters are not consistent across all layers, this will be
+       `"irregular"`, which means that your model is in an inconsistent state and might not work as expected.
+    - `requires_grad` (`dict[str, bool | Literal["irregular"]]`):
+       Whether for the given adapter, all adapter layers have `requires_grad` set to `True` or `False`. If there is a
+       mix, this will be set to `"irregular"`, which means that your model is in an inconsistent state and might not
+       work as expected.
+    - `available_adapters` (`list[str]`):
+       The names of the available adapters, e.g. `["default"]`.
+    - `devices` (`dict[str, list[str]]`):
+       The devices where the parameters of the given adapter are stored, e.g. `["cuda"]`.
+
+    Args:
+        model ([Union[`~PeftModel`, `~transformers.PreTrainedModel`, `nn.Module`]]):
+            The model to get the adapter layer status from.
+
+    Returns:
+        `peft.peft_model.TunerModelStatus`:
+            A dataclass containing the status of the model.
+
+    """
+    if isinstance(model, PeftModel):
+        if not isinstance(model.base_model, BaseTuner):
+            raise TypeError(
+                "get_model_status() got an invalid PeftModel instance; prefix tuning and adaption prompt are not "
+                "supported."
+            )
+        base_model_type = model.get_base_model().__class__.__name__
+        trainable_params, total_params = model.get_nb_trainable_parameters()
+        base_model = model.base_model
+        peft_types = {key: str(config.peft_type).partition(".")[-1] for key, config in base_model.peft_config.items()}
+        adapter_model_type = base_model.__class__.__name__
+    elif isinstance(model, PreTrainedModel):
+        base_model_type = model.__class__.__name__
+        trainable_params, total_params = PeftModel.get_nb_trainable_parameters(model)
+        base_model = model
+        peft_types = {}
+        adapter_model_type = "None"
+    else:
+        base_model_type = "other"
+        trainable_params, total_params = PeftModel.get_nb_trainable_parameters(model)
+        base_model = model
+        peft_types = {}
+        adapter_model_type = "None"
+
+    layer_status = get_layer_status(model)
+    num_adapter_layers = len(layer_status)
+
+    enabled_set: set[bool] = {status.enabled for status in layer_status}  # must be {True}, {False}, or {True, False}
+    enabled: bool | Literal["irregular"]
+    if len(enabled_set) == 1:
+        enabled = enabled_set.pop()
+    else:
+        enabled = "irregular"
+
+    available_adapters: list[str] = sorted(set().union(*(status.available_adapters for status in layer_status)))
+
+    # ideally, active adapters should be consistent across all layers of the model, but we cannot guarantee it
+    all_active_adapters: set[tuple[str, ...]] = {tuple(status.active_adapters) for status in layer_status}
+    active_adapters: list[str] | Literal["irregular"]
+    if not all_active_adapters:
+        active_adapters = []
+    elif len(all_active_adapters) == 1:
+        active_adapters = list(all_active_adapters.pop())
+    else:
+        active_adapters = "irregular"
+
+    # Here we determine what adapters are merged. This is not trivial because multiple adapters can be merged or not at
+    # the same time. Some layers may only have adapter A, some only adapter B, so it's not as easy as just checking
+    # which adapters are merged on each layer.
+
+    # First, determine all adapters that are merged on at least on module.
+    merged_all: set[str] = set()
+    for status in layer_status:
+        merged_all.update(status.merged_adapters)
+
+    # Next, check if on any layer, on of these adapters is not merged.
+    merged_adapters: list[str] | Literal["irregular"] = sorted(merged_all)
+    for status in layer_status:
+        unmerged = set(status.available_adapters) - set(status.merged_adapters)
+        if unmerged & merged_all:
+            # there is overlap between unmerged adapters and adapters that should be merged
+            merged_adapters = "irregular"
+            break
+
+    # check status of requires_grad
+    # first, merge the values for all layers
+    requires_grad_all: dict[str, list[bool | Literal["irregular"]]] = collections.defaultdict(list)
+    for status in layer_status:
+        for key, val in status.requires_grad.items():
+            requires_grad_all[key].append(val)
+
+    # then, check if the values are consistent
+    def check_irrgular(vals: list[bool | Literal["irregular"]]) -> bool | Literal["irregular"]:
+        if all(val is True for val in vals):
+            return True
+        if all(val is False for val in vals):
+            return False
+        return "irregular"
+
+    requires_grad = {key: check_irrgular(vals) for key, vals in requires_grad_all.items()}
+
+    devices_dd = collections.defaultdict(list)
+    for status in layer_status:
+        for key, val in status.devices.items():
+            devices_dd[key].extend(val)
+    devices = {key: sorted(set(val)) for key, val in devices_dd.items()}
+
+    adapter_model_status = TunerModelStatus(
+        base_model_type=base_model_type,
+        adapter_model_type=adapter_model_type,
+        peft_types=peft_types,
+        trainable_params=trainable_params,
+        total_params=total_params,
+        num_adapter_layers=num_adapter_layers,
+        enabled=enabled,
+        active_adapters=active_adapters,
+        merged_adapters=merged_adapters,
+        requires_grad=requires_grad,
+        available_adapters=available_adapters,
+        devices=devices,
+    )
+    return adapter_model_status
+
+
+def __getattr__(name):
+    if name == "PEFT_TYPE_TO_MODEL_MAPPING":
+        # This is for backwards compatibility: In #2282, PEFT_TYPE_TO_MODEL_MAPPING was removed as it was redundant with
+        # PEFT_TYPE_TO_TUNER_MAPPING. However, third party code could still use this mapping, e.g.:
+        # https://github.com/AutoGPTQ/AutoGPTQ/blob/6689349625de973b9ee3016c28c11f32acf7f02c/auto_gptq/utils/peft_utils.py#L8
+        # TODO: Remove after 2026-01
+        msg = (
+            "PEFT_TYPE_TO_MODEL_MAPPING is deprecated, please use `from peft import PEFT_TYPE_TO_TUNER_MAPPING` instead. "
+            "The deprecated variable will be removed in 2026."
+        )
+        warnings.warn(msg, category=DeprecationWarning)
+        return PEFT_TYPE_TO_TUNER_MAPPING
+
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/py.typed b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..65abbd4046feaa01fddc5578c1490a60f95fa155
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/__init__.py
@@ -0,0 +1,102 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from .adalora import AdaLoraConfig, AdaLoraModel
+from .adaption_prompt import AdaptionPromptConfig, AdaptionPromptModel
+from .boft import BOFTConfig, BOFTModel
+from .bone import BoneConfig, BoneModel
+from .cpt import CPTConfig, CPTEmbedding
+from .fourierft import FourierFTConfig, FourierFTModel
+from .hra import HRAConfig, HRAModel
+from .ia3 import IA3Config, IA3Model
+from .ln_tuning import LNTuningConfig, LNTuningModel
+from .loha import LoHaConfig, LoHaModel
+from .lokr import LoKrConfig, LoKrModel
+from .lora import (
+    EvaConfig,
+    LoftQConfig,
+    LoraConfig,
+    LoraModel,
+    LoraRuntimeConfig,
+    get_eva_state_dict,
+    initialize_lora_eva_weights,
+)
+from .mixed import MixedModel
+from .multitask_prompt_tuning import MultitaskPromptEmbedding, MultitaskPromptTuningConfig, MultitaskPromptTuningInit
+from .oft import OFTConfig, OFTModel
+from .p_tuning import PromptEncoder, PromptEncoderConfig, PromptEncoderReparameterizationType
+from .poly import PolyConfig, PolyModel
+from .prefix_tuning import PrefixEncoder, PrefixTuningConfig
+from .prompt_tuning import PromptEmbedding, PromptTuningConfig, PromptTuningInit
+from .trainable_tokens import TrainableTokensConfig, TrainableTokensModel
+from .vblora import VBLoRAConfig, VBLoRAModel
+from .vera import VeraConfig, VeraModel
+from .xlora import XLoraConfig, XLoraModel
+
+
+__all__ = [
+    "AdaLoraConfig",
+    "AdaLoraModel",
+    "AdaptionPromptConfig",
+    "AdaptionPromptModel",
+    "BOFTConfig",
+    "BOFTModel",
+    "BoneConfig",
+    "BoneModel",
+    "CPTConfig",
+    "CPTEmbedding",
+    "EvaConfig",
+    "FourierFTConfig",
+    "FourierFTModel",
+    "HRAConfig",
+    "HRAModel",
+    "IA3Config",
+    "IA3Model",
+    "LNTuningConfig",
+    "LNTuningModel",
+    "LoHaConfig",
+    "LoHaModel",
+    "LoKrConfig",
+    "LoKrModel",
+    "LoftQConfig",
+    "LoraConfig",
+    "LoraModel",
+    "LoraRuntimeConfig",
+    "MixedModel",
+    "MultitaskPromptEmbedding",
+    "MultitaskPromptTuningConfig",
+    "MultitaskPromptTuningInit",
+    "OFTConfig",
+    "OFTModel",
+    "PolyConfig",
+    "PolyModel",
+    "PrefixEncoder",
+    "PrefixTuningConfig",
+    "PromptEmbedding",
+    "PromptEncoder",
+    "PromptEncoderConfig",
+    "PromptEncoderReparameterizationType",
+    "PromptTuningConfig",
+    "PromptTuningInit",
+    "TrainableTokensConfig",
+    "TrainableTokensModel",
+    "VBLoRAConfig",
+    "VBLoRAModel",
+    "VeraConfig",
+    "VeraModel",
+    "XLoraConfig",
+    "XLoraModel",
+    "get_eva_state_dict",
+    "initialize_lora_eva_weights",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/_buffer_dict.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/_buffer_dict.py
new file mode 100644
index 0000000000000000000000000000000000000000..62b81147c2c35410e4fcbea70a3596ffef001c26
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/_buffer_dict.py
@@ -0,0 +1,158 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+#
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+# Adapted from https://botorch.org/api/_modules/botorch/utils/torch.html
+
+# TODO: To be removed once (if) https://github.com/pytorch/pytorch/pull/37385 lands
+
+from __future__ import annotations
+
+import collections
+from collections import OrderedDict
+
+import torch
+from torch.nn import Module
+
+
+class BufferDict(Module):
+    r"""
+    Holds buffers in a dictionary.
+
+    BufferDict can be indexed like a regular Python dictionary, but buffers it contains are properly registered, and
+    will be visible by all Module methods. `torch.nn.BufferDict` is an **ordered** dictionary that respects
+
+    * the order of insertion, and
+    * in `torch.nn.BufferDict.update`, the order of the merged `OrderedDict` or another `torch.nn.BufferDict` (the
+      argument to `torch.nn.BufferDict.update`).
+
+    Note that `torch.nn.BufferDict.update` with other unordered mapping types (e.g., Python's plain `dict`) does not
+    preserve the order of the merged mapping.
+
+    Args:
+        buffers (iterable, optional):
+            a mapping (dictionary) of (string : `torch.Tensor`) or an iterable of key-value pairs of type (string,
+            `torch.Tensor`)
+
+    ```python
+    class MyModule(nn.Module):
+        def __init__(self):
+            super().__init__()
+            self.buffers = nn.BufferDict({"left": torch.randn(5, 10), "right": torch.randn(5, 10)})
+
+        def forward(self, x, choice):
+            x = self.buffers[choice].mm(x)
+            return x
+    ```
+    """
+
+    def __init__(self, buffers=None, persistent: bool = False):
+        r"""
+        Args:
+            buffers (`dict`):
+                A mapping (dictionary) from string to `torch.Tensor`, or an iterable of key-value pairs of type
+                (string, `torch.Tensor`).
+        """
+        super().__init__()
+        self.persistent = persistent
+
+        if buffers is not None:
+            self.update(buffers)
+
+    def __getitem__(self, key):
+        return self._buffers[key]
+
+    def __setitem__(self, key, buffer):
+        self.register_buffer(key, buffer, persistent=self.persistent)
+
+    def __delitem__(self, key):
+        del self._buffers[key]
+
+    def __len__(self):
+        return len(self._buffers)
+
+    def __iter__(self):
+        return iter(self._buffers.keys())
+
+    def __contains__(self, key):
+        return key in self._buffers
+
+    def clear(self):
+        """Remove all items from the BufferDict."""
+        self._buffers.clear()
+
+    def pop(self, key):
+        r"""Remove key from the BufferDict and return its buffer.
+
+        Args:
+            key (`str`):
+                Key to pop from the BufferDict
+        """
+        v = self[key]
+        del self[key]
+        return v
+
+    def keys(self):
+        r"""Return an iterable of the BufferDict keys."""
+        return self._buffers.keys()
+
+    def items(self):
+        r"""Return an iterable of the BufferDict key/value pairs."""
+        return self._buffers.items()
+
+    def values(self):
+        r"""Return an iterable of the BufferDict values."""
+        return self._buffers.values()
+
+    def update(self, buffers):
+        r"""
+        Update the `torch.nn.BufferDict` with the key-value pairs from a mapping or an iterable, overwriting existing
+        keys.
+
+        Note:
+            If `buffers` is an `OrderedDict`, a `torch.nn.BufferDict`, or an iterable of key-value pairs, the order of
+            new elements in it is preserved.
+
+        Args:
+            buffers (iterable):
+                a mapping (dictionary) from string to `torch.Tensor`, or an iterable of key-value pairs of type
+                (string, `torch.Tensor`).
+        """
+        if not isinstance(buffers, collections.abc.Iterable):
+            raise TypeError(
+                "BuffersDict.update should be called with an "
+                "iterable of key/value pairs, but got " + type(buffers).__name__
+            )
+
+        if isinstance(buffers, (OrderedDict, BufferDict)):
+            for key, buffer in buffers.items():
+                self[key] = buffer
+        elif isinstance(buffers, collections.abc.Mapping):
+            for key, buffer in sorted(buffers.items()):
+                self[key] = buffer
+        else:
+            for j, p in enumerate(buffers):
+                if not isinstance(p, collections.abc.Iterable):
+                    raise TypeError(
+                        "BufferDict update sequence element #" + str(j) + " should be Iterable; is" + type(p).__name__
+                    )
+                if not len(p) == 2:
+                    raise ValueError(
+                        "BufferDict update sequence element "
+                        "#" + str(j) + " has length " + str(len(p)) + "; 2 is required"
+                    )
+                self[p[0]] = p[1]
+
+    def extra_repr(self):
+        child_lines = []
+        for k, p in self._buffers.items():
+            size_str = "x".join(str(size) for size in p.size())
+            device_str = "" if not p.is_cuda else f" (GPU {p.get_device()})"
+            parastr = f"Buffer containing: [{torch.typename(p)} of size {size_str}{device_str}]"
+            child_lines.append("  (" + k + "): " + parastr)
+        tmpstr = "\n".join(child_lines)
+        return tmpstr
+
+    def __call__(self, input):
+        raise RuntimeError("BufferDict should not be called.")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..64d5f3e5ce6ba3c5873f01ee88f4c4766e1fde75
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/__init__.py
@@ -0,0 +1,43 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.utils import register_peft_method
+
+from .config import AdaLoraConfig
+from .gptq import SVDQuantLinear
+from .layer import AdaLoraLayer, RankAllocator, SVDLinear
+from .model import AdaLoraModel
+
+
+__all__ = ["AdaLoraConfig", "AdaLoraLayer", "AdaLoraModel", "RankAllocator", "SVDLinear", "SVDQuantLinear"]
+
+
+register_peft_method(
+    name="adalora", config_cls=AdaLoraConfig, model_cls=AdaLoraModel, prefix="lora_", is_mixed_compatible=True
+)
+
+
+def __getattr__(name):
+    if (name == "SVDLinear8bitLt") and is_bnb_available():
+        from .bnb import SVDLinear8bitLt
+
+        return SVDLinear8bitLt
+
+    if (name == "SVDLinear4bit") and is_bnb_4bit_available():
+        from .bnb import SVDLinear4bit
+
+        return SVDLinear4bit
+
+    raise AttributeError(f"module {__name__} has no attribute {name}")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/bnb.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/bnb.py
new file mode 100644
index 0000000000000000000000000000000000000000..fef3d25e65c459d20855e49832aabe56881734c0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/bnb.py
@@ -0,0 +1,143 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Any
+
+import torch
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+
+from .layer import AdaLoraLayer
+
+
+if is_bnb_available():
+
+    class SVDLinear8bitLt(torch.nn.Module, AdaLoraLayer):
+        # Low-rank matrix for SVD-based adaptation
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            r: int = 0,
+            lora_alpha: int = 1,
+            lora_dropout: float = 0.0,
+            init_lora_weights: bool = True,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            AdaLoraLayer.__init__(self, base_layer)
+            # Freezing the pre-trained weight matrix
+            self.get_base_layer().weight.requires_grad = False
+
+            self._active_adapter = adapter_name
+            self.update_layer(adapter_name, r, lora_alpha, lora_dropout, init_lora_weights)
+
+        def forward(self, x: torch.Tensor) -> torch.Tensor:
+            # note: no check for self.merged because merging is not supported (yet)
+            result = self.base_layer(x)
+
+            if self.disable_adapters:
+                return result
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+                requires_conversion = not torch.is_autocast_enabled()
+                if requires_conversion:
+                    expected_dtype = result.dtype
+                    if x.dtype != torch.float32:
+                        x = x.float()
+
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                lora_E = self.lora_E[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+                ranknum = self.ranknum[active_adapter] + 1e-5
+
+                output = dropout(x) @ (lora_A * lora_E).T @ lora_B.T
+                if requires_conversion:
+                    output = output.to(expected_dtype)
+                output = output * scaling / ranknum
+                # inplace operation on view is forbidden for MatMul8bitLtBackward, so avoid it
+                result = result + output
+            return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "adalora." + rep
+
+
+if is_bnb_4bit_available():
+
+    class SVDLinear4bit(torch.nn.Module, AdaLoraLayer):
+        # Low-rank matrix for SVD-based adaptation
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            r: int = 0,
+            lora_alpha: int = 1,
+            lora_dropout: float = 0.0,
+            init_lora_weights: bool = True,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            AdaLoraLayer.__init__(self, base_layer)
+            # Freezing the pre-trained weight matrix
+            self.get_base_layer().weight.requires_grad = False
+
+            self._active_adapter = adapter_name
+            self.update_layer(adapter_name, r, lora_alpha, lora_dropout, init_lora_weights)
+
+        def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+            # note: no check for self.merged because merging is not supported (yet)
+            result = self.base_layer(x, *args, **kwargs)
+
+            if self.disable_adapters:
+                return result
+
+            # As per Tim Dettmers, for 4bit, we need to defensively clone here.
+            # The reason is that in some cases, an error can occur that backprop
+            # does not work on a manipulated view. This issue may be solved with
+            # newer PyTorch versions but this would need extensive testing to be
+            # sure.
+            result = result.clone()
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                lora_E = self.lora_E[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+                ranknum = self.ranknum[active_adapter] + 1e-5
+
+                requires_conversion = not torch.is_autocast_enabled()
+                if requires_conversion:
+                    expected_dtype = result.dtype
+                    x = self._cast_input_dtype(x, lora_A.dtype)
+
+                output = dropout(x) @ (lora_A * lora_E).T @ lora_B.T
+                if requires_conversion:
+                    output = output.to(expected_dtype)
+                output = output * scaling / ranknum
+                result += output
+            return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "adalora." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..004c26b0fe5ecf88212bd11de062baec2f10de83
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/config.py
@@ -0,0 +1,108 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from dataclasses import dataclass, field
+from typing import Optional
+
+from peft.tuners.lora import LoraConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class AdaLoraConfig(LoraConfig):
+    """
+    This is the configuration class to store the configuration of a [`~peft.AdaLora`].
+
+    AdaLoRA has three phases defined by `tinit`, `tfinal` and `total_step`.
+
+    The initial phase can be understood as a step for pre-training the adapters so that when reducing their rank, there
+    is already some information encoded that can be reduced instead of random matrices. This phase is defined by
+    supplying `tinit`.
+
+    After the initial phase is over (`tinit` steps have passed) and the final phase has not begun, AdaLoRA reduces the
+    budget of how much rank each layer is allowed to have with each step. This is where the reduction of rank is
+    happening. This goes on until `total_step - tfinal` steps are reached.
+
+    The last phase, beginning once `total_step - tfinal` steps are reached, does not change the layer ranks anymore but
+    fine-tunes the reduced-rank layers that resulted from the previous phase.
+
+    A practical example: `tinit` is 10, `tfinal` is 20, `total_step` is 100. We spend 10 steps doing pre-training
+    without rank reduction because our budget is constant (init phase), then we spend 80 (100-20) steps in the
+    reduction phase where our budget decreases step-wise and, finally, 20 steps in the final fine-tuning stage without
+    reduction.
+
+    Args:
+        target_r (`int`): The target average rank of incremental matrix.
+        init_r (`int`): The initial rank for each incremental matrix.
+        tinit (`int`): The steps of initial fine-tuning warmup.
+        tfinal (`int`): The number of steps of final fine-tuning.
+        deltaT (`int`): The time internval between two budget allocations.
+        beta1 (`float`): The hyperparameter of EMA for sensitivity smoothing.
+        beta2 (`float`): The hyperparameter of EMA for undertainty quantification.
+        orth_reg_weight (`float`): The coefficient of orthogonal regularization.
+        total_step (`int`): The total training steps that should be specified before training.
+        rank_pattern (`list`): The allocated rank for each weight matrix by RankAllocator.
+    """
+
+    target_r: int = field(default=8, metadata={"help": "Target Lora matrix dimension."})
+    init_r: int = field(default=12, metadata={"help": "Initial Lora matrix dimension."})
+    tinit: int = field(default=0, metadata={"help": "The steps of initial warmup."})
+    tfinal: int = field(default=0, metadata={"help": "The steps of final warmup."})
+    deltaT: int = field(default=1, metadata={"help": "Step interval of rank allocation."})
+    beta1: float = field(default=0.85, metadata={"help": "Hyperparameter of EMA."})
+    beta2: float = field(default=0.85, metadata={"help": "Hyperparameter of EMA."})
+    orth_reg_weight: float = field(default=0.5, metadata={"help": "The orthogonal regularization coefficient."})
+    total_step: Optional[int] = field(default=None, metadata={"help": "The total training steps."})
+    rank_pattern: Optional[dict] = field(default=None, metadata={"help": "The saved rank pattern."})
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.ADALORA
+
+        if self.use_dora:
+            raise ValueError(f"{self.peft_type} does not support DoRA.")
+
+        if self.loftq_config:
+            raise ValueError(f"{self.peft_type} does not support LOFTQ.")
+
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # if target_modules is a regex expression, then layers_to_transform should be None
+        if isinstance(self.target_modules, str) and self.layers_to_transform is not None:
+            raise ValueError("`layers_to_transform` cannot be used when `target_modules` is a str.")
+
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
+
+        # Check if 'r' has been set to a non-default value
+        if self.r != 8:  # 8 is the default value for 'r' in LoraConfig
+            warnings.warn(
+                "Note that `r` is not used in AdaLora and will be ignored."
+                "If you intended to set the initial rank, use `init_r` instead."
+            )
+
+        if self.total_step is None or self.total_step <= 0:
+            raise ValueError("AdaLoRA does not work when `total_step` is None, supply a value > 0.")
+
+        if self.tinit >= (self.total_step - self.tfinal):
+            raise ValueError(
+                "The supplied schedule values don't allow for a budgeting phase. Decrease `tfinal`/`tinit` or "
+                "increase `total_step`."
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/gptq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/gptq.py
new file mode 100644
index 0000000000000000000000000000000000000000..bed1a0a7ca8dabb9d068bcf2470a97e34ec348fe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/gptq.py
@@ -0,0 +1,71 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import torch
+
+from .layer import AdaLoraLayer
+
+
+class SVDQuantLinear(torch.nn.Module, AdaLoraLayer):
+    def __init__(
+        self,
+        base_layer,
+        adapter_name,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        init_lora_weights: bool = True,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        AdaLoraLayer.__init__(self, base_layer)
+
+        # self.base_layer and self.quant_linear_module are the same; we need the former for consistency and the latter
+        # for backwards compatibility
+        self.quant_linear_module = base_layer
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, lora_alpha, lora_dropout, init_lora_weights)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        result = self.quant_linear_module(x)
+
+        if self.disable_adapters:
+            return result
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.lora_A.keys():
+                continue
+            lora_A = self.lora_A[active_adapter]
+            lora_B = self.lora_B[active_adapter]
+            lora_E = self.lora_E[active_adapter]
+            dropout = self.lora_dropout[active_adapter]
+            scaling = self.scaling[active_adapter]
+            ranknum = self.ranknum[active_adapter] + 1e-5
+
+            requires_conversion = not torch.is_autocast_enabled()
+            if requires_conversion:
+                expected_dtype = result.dtype
+                x = self._cast_input_dtype(x, torch.float32)
+
+            output = (dropout(x) @ (lora_A * lora_E).T @ lora_B.T) * scaling / ranknum
+            # TODO: here, the dtype conversion is applied on the *whole expression*,
+            # not the intermediate result, unlike for SVDLinear8bitLT and
+            # SVDLinear4bit, is that correct?
+            if requires_conversion:
+                output = output.to(expected_dtype)
+            result += output
+        return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "adalora." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..ea142c512f45073de282aeea52531ef08a82f248
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/layer.py
@@ -0,0 +1,358 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from typing import Any, List, Optional
+
+import packaging
+import torch
+import transformers
+from torch import nn
+
+from peft.tuners.lora import LoraLayer
+from peft.tuners.tuners_utils import check_adapters_to_merge
+from peft.utils import transpose
+
+
+if packaging.version.parse(transformers.__version__) >= packaging.version.parse("4.33.0"):
+    from transformers.integrations import deepspeed_config
+else:
+    from transformers.deepspeed import deepspeed_config
+
+
+class AdaLoraLayer(LoraLayer):
+    # List all names of layers that may contain adapter weights
+    # Note: ranknum doesn't need to be included as it is not an nn.Module
+    adapter_layer_names = ("lora_A", "lora_B", "lora_E", "lora_embedding_A", "lora_embedding_B")
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("r", "lora_alpha", "scaling", "lora_dropout", "ranknum")
+
+    def __init__(self, base_layer: nn.Module) -> None:
+        super().__init__(base_layer)
+        self.lora_E = nn.ParameterDict({})
+        self.lora_A = nn.ParameterDict({})
+        self.lora_B = nn.ParameterDict({})
+        self.ranknum = nn.ParameterDict({})
+
+    def update_layer(self, adapter_name, r, lora_alpha, lora_dropout, init_lora_weights):
+        if r < 0:
+            # note: r == 0 is allowed for AdaLora, see #1539
+            raise ValueError(f"`r` should be a positive integer or 0, but the value passed is {r}")
+
+        self.r[adapter_name] = r
+        self.lora_alpha[adapter_name] = lora_alpha
+        if lora_dropout > 0.0:
+            lora_dropout_layer = nn.Dropout(p=lora_dropout)
+        else:
+            lora_dropout_layer = nn.Identity()
+
+        self.lora_dropout[adapter_name] = lora_dropout_layer
+        # Actual trainable parameters
+        # Right singular vectors
+        self.lora_A[adapter_name] = nn.Parameter(torch.randn(r, self.in_features))
+        # Singular values
+        self.lora_E[adapter_name] = nn.Parameter(torch.randn(r, 1))
+        # Left singular vectors
+        self.lora_B[adapter_name] = nn.Parameter(torch.randn(self.out_features, r))
+        # The current rank
+        self.ranknum[adapter_name] = nn.Parameter(torch.randn(1), requires_grad=False)
+        self.ranknum[adapter_name].data.fill_(float(r))
+        self.ranknum[adapter_name].requires_grad = False
+        self.scaling[adapter_name] = lora_alpha if lora_alpha > 0 else float(r)
+        if init_lora_weights:
+            self.reset_lora_parameters(adapter_name)
+
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_lora_parameters(self, adapter_name):
+        if adapter_name in self.lora_A.keys():
+            nn.init.zeros_(self.lora_E[adapter_name])
+            nn.init.normal_(self.lora_A[adapter_name], mean=0.0, std=0.02)
+            nn.init.normal_(self.lora_B[adapter_name], mean=0.0, std=0.02)
+
+
+class SVDLinear(nn.Module, AdaLoraLayer):
+    # SVD-based adaptation by a dense layer
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        fan_in_fan_out: bool = False,
+        init_lora_weights: bool = True,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        AdaLoraLayer.__init__(self, base_layer)
+        # Freezing the pre-trained weight matrix
+        self.get_base_layer().weight.requires_grad = False
+
+        self.fan_in_fan_out = fan_in_fan_out
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, lora_alpha, lora_dropout, init_lora_weights)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            base_layer = self.get_base_layer()
+            if active_adapter in self.lora_A.keys():
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    orig_weights += self.get_delta_weight(active_adapter)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights
+                else:
+                    base_layer.weight.data += self.get_delta_weight(active_adapter)
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.lora_A.keys():
+                self.get_base_layer().weight.data -= self.get_delta_weight(active_adapter)
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        return (
+            transpose(self.lora_B[adapter] @ (self.lora_A[adapter] * self.lora_E[adapter]), self.fan_in_fan_out)
+            * self.scaling[adapter]
+            / (self.ranknum[adapter] + 1e-5)
+        )
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                lora_E = self.lora_E[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+                ranknum = self.ranknum[active_adapter] + 1e-5
+
+                x = self._cast_input_dtype(x, lora_A.dtype)
+                result += (dropout(x) @ (lora_A * lora_E).T @ lora_B.T) * scaling / ranknum
+
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "adalora." + rep
+
+
+class RankAllocator:
+    """
+    The RankAllocator for AdaLoraModel. Paper: https://openreview.net/pdf?id=lq62uWRJjiY
+
+    Args:
+        config ([`AdaLoraConfig`]): The configuration of the AdaLora model.
+        model: the model that we apply AdaLoRA to.
+
+    """
+
+    def __init__(self, model, peft_config, adapter_name):
+        self.peft_config = peft_config
+        self.adapter_name = adapter_name
+        self.beta1 = peft_config.beta1
+        self.beta2 = peft_config.beta2
+        assert self.beta1 > 0 and self.beta1 < 1
+        assert self.beta2 > 0 and self.beta2 < 1
+
+        self.reset_ipt()
+        self._set_budget_scheduler(model)
+
+    def set_total_step(self, total_step):
+        self.peft_config.total_step = total_step
+
+    def reset_ipt(self):
+        self.ipt = {}
+        self.exp_avg_ipt = {}
+        self.exp_avg_unc = {}
+
+    def _set_budget_scheduler(self, model):
+        self.init_bgt = 0
+        self.name_set = set()
+        for n, p in model.named_parameters():
+            if f"lora_A.{self.adapter_name}" in n:
+                self.init_bgt += p.size(0)
+                self.name_set.add(n.replace("lora_A", "%s"))
+        self.name_set = sorted(self.name_set)
+        # The total final rank budget
+        self.target_bgt = self.peft_config.target_r * len(self.name_set)
+
+    def budget_schedule(self, step: int):
+        tinit = self.peft_config.tinit
+        tfinal = self.peft_config.tfinal
+        total_step = self.peft_config.total_step
+        # Initial warmup
+        if step <= tinit:
+            budget = self.init_bgt
+            mask_ind = False
+        # Final fine-tuning
+        elif step > total_step - tfinal:
+            budget = self.target_bgt
+            mask_ind = True
+        else:
+            # Budget decreasing with a cubic scheduler
+            mul_coeff = 1 - (step - tinit) / (total_step - tfinal - tinit)
+            budget = int((self.init_bgt - self.target_bgt) * (mul_coeff**3) + self.target_bgt)
+            mask_ind = True if step % self.peft_config.deltaT == 0 else False
+        return budget, mask_ind
+
+    def update_ipt(self, model):
+        # Update the sensitivity and uncertainty for every weight
+        for n, p in model.named_parameters():
+            if "lora_" in n and self.adapter_name in n:
+                if n not in self.ipt:
+                    self.ipt[n] = torch.zeros_like(p)
+                    self.exp_avg_ipt[n] = torch.zeros_like(p)
+                    self.exp_avg_unc[n] = torch.zeros_like(p)
+                with torch.no_grad():
+                    if deepspeed_config() is not None:
+                        import deepspeed
+
+                        grad = deepspeed.utils.safe_get_full_grad(p)
+                        self.ipt[n] = (p * grad).abs().detach()
+                    else:
+                        self.ipt[n] = (p * p.grad).abs().detach()
+                    # Sensitivity smoothing
+                    self.exp_avg_ipt[n] = self.beta1 * self.exp_avg_ipt[n] + (1 - self.beta1) * self.ipt[n]
+                    # Uncertainty quantification
+                    self.exp_avg_unc[n] = (
+                        self.beta2 * self.exp_avg_unc[n] + (1 - self.beta2) * (self.ipt[n] - self.exp_avg_ipt[n]).abs()
+                    )
+
+    def _element_score(self, n):
+        return self.exp_avg_ipt[n] * self.exp_avg_unc[n]
+
+    def _combine_ipt(self, ipt_E, ipt_AB):
+        ipt_AB = ipt_AB.sum(dim=1, keepdim=False)
+        sum_ipt = ipt_E.view(-1) + ipt_AB.view(-1)
+        return sum_ipt
+
+    def mask_to_budget(self, model, budget):
+        value_ipt = {}
+        vector_ipt = {}
+        triplet_ipt = {}
+        # Get the importance score for A, E, B
+        for n, p in model.named_parameters():
+            if f"lora_A.{self.adapter_name}" in n:
+                entry_ipt = self._element_score(n)
+                comb_ipt = torch.mean(entry_ipt, dim=1, keepdim=True)
+                name_m = n.replace("lora_A", "%s")
+                if name_m not in vector_ipt:
+                    vector_ipt[name_m] = [comb_ipt]
+                else:
+                    vector_ipt[name_m].append(comb_ipt)
+            if f"lora_B.{self.adapter_name}" in n:
+                entry_ipt = self._element_score(n)
+                comb_ipt = torch.mean(entry_ipt, dim=0, keepdim=False).view(-1, 1)
+                name_m = n.replace("lora_B", "%s")
+                if name_m not in vector_ipt:
+                    vector_ipt[name_m] = [comb_ipt]
+                else:
+                    vector_ipt[name_m].append(comb_ipt)
+            if f"lora_E.{self.adapter_name}" in n:
+                entry_ipt = self._element_score(n)
+                name_m = n.replace("lora_E", "%s")
+                value_ipt[name_m] = entry_ipt
+
+        all_score = []
+        # Calculate the score for each triplet
+        for name_m in vector_ipt:
+            ipt_E = value_ipt[name_m]
+            ipt_AB = torch.cat(vector_ipt[name_m], dim=1)
+            sum_ipt = self._combine_ipt(ipt_E, ipt_AB)
+            name_E = name_m % "lora_E"
+            triplet_ipt[name_E] = sum_ipt.view(-1, 1)
+            all_score.append(sum_ipt.view(-1))
+
+        # Get the threshold by ranking ipt
+        mask_threshold = torch.kthvalue(
+            torch.cat(all_score),
+            k=self.init_bgt - budget,
+        )[0].item()
+
+        rank_pattern = {}
+        # Mask the unimportant triplets
+        with torch.no_grad():
+            for n, p in model.named_parameters():
+                if f"lora_E.{self.adapter_name}" in n:
+                    p.masked_fill_(triplet_ipt[n] <= mask_threshold, 0.0)
+                    rank_pattern[n] = (~(triplet_ipt[n] <= mask_threshold)).view(-1).tolist()
+        return rank_pattern
+
+    def update_and_allocate(self, model, global_step, force_mask=False):
+        # # Update the importance score and allocate the budget
+        if global_step < self.peft_config.total_step - self.peft_config.tfinal:
+            self.update_ipt(model)
+        budget, mask_ind = self.budget_schedule(global_step)
+        # Allocate the budget according to importance scores
+        if mask_ind or force_mask:
+            rank_pattern = self.mask_to_budget(model, budget)
+        else:
+            rank_pattern = None
+        return budget, rank_pattern
+
+    def mask_using_rank_pattern(self, model, rank_pattern):
+        # Mask the unimportant triplets
+        is_adapter_name_truncated = False
+        if self.adapter_name not in next(iter(rank_pattern.keys())):
+            is_adapter_name_truncated = True
+
+        with torch.no_grad():
+            for n, p in model.named_parameters():
+                if f"lora_E.{self.adapter_name}" in n:
+                    key = n if not is_adapter_name_truncated else n.replace(f".{self.adapter_name}", "")
+                    mask = torch.Tensor(rank_pattern[key]).unsqueeze(-1).to(p.device)
+                    p.masked_fill_(~mask.bool(), 0.0)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..3c52ecdf2f9117d073998d58f4b3510e0cfbf58a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adalora/model.py
@@ -0,0 +1,364 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+
+import torch
+from transformers.pytorch_utils import Conv1D
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available, is_gptqmodel_available
+from peft.tuners.lora import LoraConfig, LoraModel
+from peft.tuners.tuners_utils import BaseTunerLayer
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING,
+    _freeze_adapter,
+    _get_submodules,
+    get_auto_gptq_quant_linear,
+    get_gptqmodel_quant_linear,
+    get_quantization_config,
+)
+from peft.utils.integrations import gather_params_ctx
+
+from .gptq import SVDQuantLinear
+from .layer import AdaLoraLayer, RankAllocator, SVDLinear
+
+
+class AdaLoraModel(LoraModel):
+    """
+    Creates AdaLoRA (Adaptive LoRA) model from a pretrained transformers model. Paper:
+    https://openreview.net/forum?id=lq62uWRJjiY
+
+    Args:
+        model ([`transformers.PreTrainedModel`]): The model to be adapted.
+        config ([`AdaLoraConfig`]): The configuration of the AdaLora model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The AdaLora model.
+
+    Example::
+
+        >>> from transformers import AutoModelForSeq2SeqLM >>> from peft import LoraConfig, AdaLoraModel, AdaLoraConfig
+        >>> config = AdaLoraConfig(
+                peft_type="ADALORA", task_type="SEQ_2_SEQ_LM", init_r=12, lora_alpha=32, target_modules=["q", "v"],
+                lora_dropout=0.01,
+            )
+        >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base") >>> model = AdaLoraModel(model, config, "default")
+
+    **Attributes**:
+        - **model** ([`transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`AdaLoraConfig`]): The configuration of the AdaLora model.
+    """
+
+    # Note: don't redefine prefix here, it should be inherited from LoraModel
+
+    def __init__(self, model, config, adapter_name):
+        super().__init__(model, config, adapter_name)
+
+        traininable_mode_counter = 0
+        for config in self.peft_config.values():
+            if not config.inference_mode:
+                traininable_mode_counter += 1
+
+        if traininable_mode_counter > 1:
+            raise ValueError(
+                "AdaLoraModel supports only 1 trainable adapter. "
+                "When using multiple adapters, set inference_mode to True for all adapters except the one you want to train."
+            )
+
+        if self.peft_config[adapter_name].inference_mode:
+            _freeze_adapter(self.model, adapter_name)
+        else:
+            self.trainable_adapter_name = adapter_name
+            self.rankallocator = RankAllocator(self.model, self.peft_config[adapter_name], self.trainable_adapter_name)
+
+    def _check_new_adapter_config(self, config: LoraConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        super()._check_new_adapter_config(config)
+
+        traininable_mode_counter = 0
+        for config_ in self.peft_config.values():
+            if not config_.inference_mode:
+                traininable_mode_counter += 1
+
+        if traininable_mode_counter > 1:
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 trainable adapter. "
+                "When using multiple adapters, set inference_mode to True for all adapters except the one "
+                "you want to train."
+            )
+
+    def _create_and_replace(
+        self,
+        lora_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+    ):
+        kwargs = {
+            "r": lora_config.init_r,
+            "lora_alpha": lora_config.lora_alpha,
+            "lora_dropout": lora_config.lora_dropout,
+            "fan_in_fan_out": lora_config.fan_in_fan_out,
+            "init_lora_weights": lora_config.init_lora_weights,
+            "loaded_in_8bit": getattr(self.model, "is_loaded_in_8bit", False),
+            "loaded_in_4bit": getattr(self.model, "is_loaded_in_4bit", False),
+        }
+        if (kwargs["loaded_in_8bit"] or kwargs["loaded_in_4bit"]) and not is_bnb_available():
+            raise ImportError(
+                "To use AdaLora with 8-bit quantization, please install the `bitsandbytes` package. "
+                "You can install it with `pip install bitsandbytes`."
+            )
+
+        quantization_config = get_quantization_config(self.model, method="gptq")
+        if quantization_config is not None:
+            kwargs["gptq_quantization_config"] = quantization_config
+
+        # If it is not an AdaLoraLayer, create a new module, else update it with new adapters
+        if not isinstance(target, AdaLoraLayer):
+            device_map = self.model.hf_device_map if hasattr(self.model, "hf_device_map") else None
+            new_module = self._create_new_module(lora_config, adapter_name, target, device_map=device_map, **kwargs)
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+        else:
+            target.update_layer(
+                adapter_name,
+                lora_config.init_r,
+                lora_config.lora_alpha,
+                lora_config.lora_dropout,
+                lora_config.init_lora_weights,
+            )
+
+    @staticmethod
+    def _create_new_module(lora_config, adapter_name, target, device_map=None, **kwargs):
+        # avoid eager bnb import
+        if is_bnb_available():
+            import bitsandbytes as bnb
+
+            from .bnb import SVDLinear8bitLt
+        if is_bnb_4bit_available():
+            from .bnb import SVDLinear4bit
+
+        gptq_quantization_config = kwargs.get("gptq_quantization_config", None)
+
+        if is_gptqmodel_available():
+            QuantLinear = get_gptqmodel_quant_linear(gptq_quantization_config, device_map=device_map)
+        else:
+            QuantLinear = get_auto_gptq_quant_linear(gptq_quantization_config)
+
+        loaded_in_8bit = kwargs.pop("loaded_in_8bit", False)
+        loaded_in_4bit = kwargs.pop("loaded_in_4bit", False)
+
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if loaded_in_8bit and isinstance(target_base_layer, bnb.nn.Linear8bitLt):
+            kwargs.update(
+                {
+                    "has_fp16_weights": target_base_layer.state.has_fp16_weights,
+                    "threshold": target_base_layer.state.threshold,
+                    "index": target_base_layer.index,
+                }
+            )
+            new_module = SVDLinear8bitLt(target, adapter_name, **kwargs)
+        elif loaded_in_4bit and is_bnb_4bit_available() and isinstance(target_base_layer, bnb.nn.Linear4bit):
+            fourbit_kwargs = kwargs.copy()
+            fourbit_kwargs.update(
+                {
+                    "compute_dtype": target_base_layer.compute_dtype,
+                    "compress_statistics": target_base_layer.weight.compress_statistics,
+                    "quant_type": target_base_layer.weight.quant_type,
+                }
+            )
+            new_module = SVDLinear4bit(target, adapter_name, **fourbit_kwargs)
+        elif QuantLinear is not None and isinstance(target, QuantLinear):
+            new_module = SVDQuantLinear(target, adapter_name, **kwargs)
+        else:
+            if isinstance(target_base_layer, torch.nn.Linear):
+                if kwargs["fan_in_fan_out"]:
+                    warnings.warn(
+                        "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                        "Setting fan_in_fan_out to False."
+                    )
+                    kwargs["fan_in_fan_out"] = lora_config.fan_in_fan_out = False
+            elif isinstance(target_base_layer, Conv1D):
+                if not kwargs["fan_in_fan_out"]:
+                    warnings.warn(
+                        "fan_in_fan_out is set to False but the target module is `Conv1D`. "
+                        "Setting fan_in_fan_out to True."
+                    )
+                    kwargs["fan_in_fan_out"] = lora_config.fan_in_fan_out = True
+            else:
+                raise ValueError(
+                    f"Target module {target} is not supported. "
+                    f"Currently, only `torch.nn.Linear` and `Conv1D` are supported."
+                )
+            new_module = SVDLinear(target, adapter_name, **kwargs)
+
+        return new_module
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING[
+                model_config["model_type"]
+            ]
+        return peft_config
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def forward(self, *args, **kwargs):
+        outputs = self.model.forward(*args, **kwargs)
+
+        if (getattr(outputs, "loss", None) is not None) and isinstance(outputs.loss, torch.Tensor):
+            # Calculate the orthogonal regularization
+            orth_reg_weight = self.peft_config[self.trainable_adapter_name].orth_reg_weight
+
+            if orth_reg_weight <= 0:
+                raise ValueError("orth_reg_weight should be greater than 0. ")
+
+            regu_loss = 0
+            num_param = 0
+            for n, p in self.model.named_parameters():
+                if ("lora_A" in n or "lora_B" in n) and self.trainable_adapter_name in n:
+                    if p.shape == torch.Size([0]):
+                        with gather_params_ctx(p, fwd_module=self):
+                            para_cov = p @ p.T if "lora_A" in n else p.T @ p
+                    else:
+                        para_cov = p @ p.T if "lora_A" in n else p.T @ p
+                    I = torch.eye(*para_cov.size(), out=torch.empty_like(para_cov))  # noqa: E741
+                    I.requires_grad = False
+                    num_param += 1
+                    regu_loss += torch.norm(para_cov - I, p="fro")
+            if num_param > 0:
+                regu_loss = regu_loss / num_param
+            else:
+                regu_loss = 0
+            outputs.loss += orth_reg_weight * regu_loss
+        return outputs
+
+    def resize_modules_by_rank_pattern(self, rank_pattern, adapter_name):
+        lora_config = self.peft_config[adapter_name]
+        for name, rank_idx in rank_pattern.items():
+            if isinstance(rank_idx, list):
+                rank = sum(rank_idx)
+            elif isinstance(rank_idx, torch.Tensor):
+                rank_idx = rank_idx.view(-1)
+                rank = rank_idx.sum().item()
+            else:
+                raise ValueError("Unexpected type of rank_idx")
+            key = ".".join(name.split(".")[0:-2]) if adapter_name in name else ".".join(name.split(".")[0:-1])
+            _, target, _ = _get_submodules(self.model, key)
+            lora_E_weights = target.lora_E[adapter_name][rank_idx]
+            lora_A_weights = target.lora_A[adapter_name][rank_idx]
+            lora_B_weights = target.lora_B[adapter_name][:, rank_idx]
+            ranknum = target.ranknum[adapter_name]
+            target.update_layer(
+                adapter_name,
+                rank,
+                lora_config.lora_alpha,
+                lora_config.lora_dropout,
+                lora_config.init_lora_weights,
+            )
+            with torch.no_grad():
+                if rank > 0:
+                    target.lora_E[adapter_name].copy_(lora_E_weights)
+                    target.lora_A[adapter_name].copy_(lora_A_weights)
+                    target.lora_B[adapter_name].copy_(lora_B_weights)
+                    # The scaling is exactly as the previous
+                    target.ranknum[adapter_name].copy_(ranknum)
+
+    def resize_state_dict_by_rank_pattern(self, rank_pattern, state_dict, adapter_name):
+        for name, rank_idx in rank_pattern.items():
+            rank = sum(rank_idx)
+            prefix = ".".join(name.split(".")[0:-2]) if adapter_name in name else ".".join(name.split(".")[0:-1])
+            for layer in ["lora_E", "lora_A", "lora_B"]:
+                key = f"base_model.model.{prefix}.{layer}.{adapter_name}"
+                if layer != "lora_B":
+                    state_dict[key] = (
+                        state_dict[key][rank_idx] if rank != state_dict[key].shape[0] else state_dict[key]
+                    )
+                else:
+                    state_dict[key] = (
+                        state_dict[key][:, rank_idx] if rank != state_dict[key].shape[1] else state_dict[key]
+                    )
+        return state_dict
+
+    def update_and_allocate(self, global_step):
+        """
+        This method updates Adalora budget and mask.
+
+        This should be called in every training step after `loss.backward()` and before `zero_grad()`.
+
+        `tinit`, `tfinal` and `deltaT` are handled with in the method.
+
+        Args:
+            global_step (`int`): The current training step, it is used to calculate adalora budget.
+
+        Example:
+
+        ```python
+        >>> loss = model(**input).loss
+        >>> loss.backward()
+        >>> optimizer.step()
+        >>> model.base_model.update_and_allocate(i_step)
+        >>> optimizer.zero_grad()
+        ```
+        """
+        lora_config = self.peft_config[self.trainable_adapter_name]
+        # Update the importance score and allocate the budget
+        if global_step < lora_config.total_step - lora_config.tfinal:
+            _, rank_pattern = self.rankallocator.update_and_allocate(self.model, global_step)
+            if rank_pattern:
+                lora_config.rank_pattern = rank_pattern
+        # Finalize the budget allocation
+        elif global_step == lora_config.total_step - lora_config.tfinal:
+            _, rank_pattern = self.rankallocator.update_and_allocate(self.model, global_step, force_mask=True)
+            # for some reason, this freezes the trainable parameters and nothing gets updates
+            # self.resize_modules_by_rank_pattern(rank_pattern, self.trainable_adapter_name)
+            lora_config.rank_pattern = rank_pattern
+            self.rankallocator.reset_ipt()
+        # Currently using inefficient way to mask the unimportant weights using the rank pattern
+        #  due to problem mentioned above
+        elif global_step > lora_config.total_step - lora_config.tfinal:
+            self.rankallocator.mask_using_rank_pattern(self.model, lora_config.rank_pattern)
+        # Pass the function and do forward propagation
+        else:
+            return None
+
+    def add_weighted_adapter(self, *args, **kwargs):
+        """This method is not supported for AdaLoRA, use LoRA instead."""
+        raise TypeError(f"{self.__class__.__name__} does not support add_weighted_adapter method.")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..68882a222625eedc770d28816a3a0646964739bb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/__init__.py
@@ -0,0 +1,23 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from peft.utils import register_peft_method
+
+from .config import AdaptionPromptConfig
+from .layer import AdaptedAttention
+from .model import AdaptionPromptModel
+
+
+__all__ = ["AdaptedAttention", "AdaptionPromptConfig", "AdaptionPromptModel"]
+
+register_peft_method(name="adaption_prompt", config_cls=AdaptionPromptConfig, model_cls=AdaptionPromptModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..52a405cebe821d68ba446d1a3e7a844c07b135de
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/config.py
@@ -0,0 +1,81 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from collections import namedtuple
+from dataclasses import dataclass, field
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+from .utils import llama_compute_query_states
+
+
+@dataclass
+class AdaptionPromptConfig(PeftConfig):
+    """Stores the configuration of an [`AdaptionPromptModel`]."""
+
+    target_modules: str = field(
+        default=None, metadata={"help": "Name of the attention submodules to insert adaption prompts into."}
+    )
+    adapter_len: int = field(default=None, metadata={"help": "Number of adapter tokens to insert"})
+    adapter_layers: int = field(default=None, metadata={"help": "Number of adapter layers (from the top)"})
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.ADAPTION_PROMPT
+
+    @property
+    def is_adaption_prompt(self) -> bool:
+        """Return True if this is an adaption prompt config."""
+        return True
+
+
+# Contains the config that is specific to a transformers model type.
+ModelTypeConfig = namedtuple(
+    "ModelTypeConfig", ["compute_query_states", "target_modules", "k_proj_layer", "v_proj_layer", "o_proj_layer"]
+)
+
+# Mapping of transformers model types to their specific configuration.
+TRANSFORMERS_MODEL_CONFIG = {
+    "llama": ModelTypeConfig(
+        compute_query_states=llama_compute_query_states,
+        target_modules="self_attn",
+        k_proj_layer="k_proj",
+        v_proj_layer="v_proj",
+        o_proj_layer="o_proj",
+    ),
+    "mistral": ModelTypeConfig(  # same as llama,
+        compute_query_states=llama_compute_query_states,
+        target_modules="self_attn",
+        k_proj_layer="k_proj",
+        v_proj_layer="v_proj",
+        o_proj_layer="o_proj",
+    ),
+}
+
+
+def prepare_config(
+    peft_config: AdaptionPromptConfig,
+    model,
+) -> AdaptionPromptConfig:
+    """Prepare the config based on the llama model type."""
+    if model.config.model_type not in TRANSFORMERS_MODEL_CONFIG:
+        raise ValueError("Unsupported model type for adaption prompt: '{model.config.model_type}'.")
+
+    model_config = TRANSFORMERS_MODEL_CONFIG[model.config.model_type]
+
+    if peft_config.target_modules is None:
+        peft_config.target_modules = model_config.target_modules
+
+    return peft_config
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..e15439de0507db5d1fc00189260eb97906bb4759
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/layer.py
@@ -0,0 +1,138 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import math
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from .config import TRANSFORMERS_MODEL_CONFIG
+
+
+class AdaptedAttention(nn.Module):
+    """This module wraps a LLamaAttention module and injects adaption prompts."""
+
+    def __init__(self, model_type: str, adapter_len: int, model):
+        """
+        Initialize object.
+
+        Args:
+            model_type: The transformer model type. This is used to retrieve the right method to
+                compute query states.
+            adapter_len: The length of the adaption prompt to insert.
+            model: The original transformer attention module that is being wrapped.
+        """
+        assert not isinstance(model, AdaptedAttention)
+        super().__init__()
+        self.model_type = model_type
+        self.model = model
+        self.adapter_len = adapter_len
+        # Assume all parameters of the attention model we are wrapping are on the same device.
+        device = next(model.parameters()).device
+        # Don't think this was specified in the paper, but we follow the official repo which used an Embedding
+        # which initializes the tokens with standard normal values.
+        # https://github.com/ZrrSkywalker/LLaMA-Adapter/blob/41c3546fe1997ab8a65809dc8d8f9252b19d9faf/llama/model.py#L234
+        # (bsz, adapter_len, hidden_size)
+        target_dtype = (
+            model.q_proj.weight.dtype if model.q_proj.weight.dtype not in [torch.int8, torch.uint8] else torch.float32
+        )
+        if hasattr(self.model, "hidden_size"):
+            # TODO: remove this clause after 2026-01-01
+            hidden_size = self.model.hidden_size
+        else:  # changed in https://github.com/huggingface/transformers/pull/35235
+            hidden_size = self.model.config.hidden_size
+        self.adaption_prompt = nn.Parameter(
+            torch.empty(1, adapter_len, hidden_size, device=device, dtype=target_dtype).normal_()
+        )
+        # Initialize the gate to 0 as this is "zero-init".
+        self.adaption_gate = nn.Parameter(torch.zeros(1, device=device, dtype=target_dtype))
+
+    def forward(self, **kwargs):
+        """
+        Forward pass for the adapter which wraps the original LlamaAttention module.
+
+        "Official" paper implementation:
+        https://github.com/ZrrSkywalker/LLaMA-Adapter/blob/41c3546fe1997ab8a65809dc8d8f9252b19d9faf/llama/model.py#L141
+
+        Args:
+            kwargs: See the original LlamaAttention module.
+        """
+        if kwargs.get("output_attention", False):
+            raise NotImplementedError("output_attention is not currently supported.")
+
+        output, *_ = self.model(**kwargs)
+        bsz = output.shape[0]
+        q_len = output.shape[1]
+        embed_dim = output.shape[2]
+        k_proj_layer = TRANSFORMERS_MODEL_CONFIG[self.model_type].k_proj_layer
+        v_proj_layer = TRANSFORMERS_MODEL_CONFIG[self.model_type].v_proj_layer
+        o_proj_layer = TRANSFORMERS_MODEL_CONFIG[self.model_type].o_proj_layer
+        factor = (
+            self.model.k_proj.in_features // self.model.k_proj.out_features
+        )  # Mistral has different input and output dimension for k_proj and v_proj layers
+
+        if k_proj_layer == v_proj_layer:
+            _, key, value = getattr(self.model, k_proj_layer)(self.adaption_prompt).split(embed_dim, dim=2)
+        else:
+            key = getattr(self.model, k_proj_layer)(self.adaption_prompt)
+            value = getattr(self.model, v_proj_layer)(self.adaption_prompt)
+
+        if hasattr(self.model, "num_heads"):
+            # TODO: remove this clause after 2026-01-01
+            num_heads = self.model.num_heads
+        else:  # changed in https://github.com/huggingface/transformers/pull/35235
+            num_heads = self.model.config.num_attention_heads
+        # (bsz, num_key_value_heads, adapter_len, head_dim)
+        adapter_k = (
+            key.view(1, self.adapter_len, (num_heads // factor), self.model.head_dim)
+            .repeat(bsz, 1, 1, 1)
+            .transpose(1, 2)
+        )
+        adapter_v = (
+            value.view(1, self.adapter_len, (num_heads // factor), self.model.head_dim)
+            .repeat(bsz, 1, 1, 1)
+            .transpose(1, 2)
+        )
+        # Below is taken from https://github.com/huggingface/transformers/blob/e547458c43dfdbbb8f6a7757237e234c44e20a8f/src/transformers/models/mistral/modeling_mistral.py#L181
+        # (bsz, num_heads, adapter_len, head_dim)
+        adapter_k = torch.repeat_interleave(adapter_k, repeats=factor, dim=1)
+        adapter_v = torch.repeat_interleave(adapter_v, repeats=factor, dim=1)
+        # Recompute query states.
+        compute_query_states = TRANSFORMERS_MODEL_CONFIG[self.model_type].compute_query_states
+        # (bsz, num_heads, q_len, head_dim)
+        query_states = compute_query_states(model=self.model, **kwargs)
+
+        previous_dtype = query_states.dtype
+
+        # (bsz, num_heads, q_len, adapter_len)
+        scores = torch.matmul(query_states, adapter_k.transpose(2, 3).to(previous_dtype)) / math.sqrt(
+            self.model.head_dim
+        )
+        # Upcast attention to fp32
+        # (bsz, num_heads, q_len, adapter_len)
+        scores = self.adaption_gate * F.softmax(scores, dim=-1, dtype=torch.float32).to(previous_dtype)
+        # (bsz, q_len, num_heads * head_dim)
+        adapter_output = torch.matmul(scores, adapter_v).transpose(1, 2).reshape(bsz, q_len, -1)
+
+        # (bsz, q_len, hidden_size)
+        if o_proj_layer is not None:
+            adapter_output = getattr(self.model, o_proj_layer)(adapter_output)
+
+        # Add adaption prompt output to original output.
+        output = output + adapter_output
+
+        # Restore original dtype.
+        output = output.to(previous_dtype)
+        return output, *_
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ee98cd8fbdb28f19a0a382199941255b602309f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/model.py
@@ -0,0 +1,162 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Dict, List
+
+import torch.nn as nn
+
+from peft.utils import _freeze_adapter, _get_submodules
+
+from .config import AdaptionPromptConfig, prepare_config
+from .layer import AdaptedAttention
+from .utils import is_adaption_prompt_trainable
+
+
+class AdaptionPromptModel(nn.Module):
+    """
+    Implements adaption prompts as described in https://arxiv.org/pdf/2303.16199.pdf.
+
+    The top L attention modules are replaced with AdaptedAttention modules that wrap the original ones, but insert
+    trainable prompts with gates (for zero init).
+
+    Notes on the multi-adapter pattern:
+    - We store the states of different adapters by keeping a dictionary of AdaptedAttention modules indexed by adapter
+      name.
+    - Every time we switch adapters, we remove the modules of the currently active adapter from the model, store them
+      in the dictionary, and replace them with the modules of the new adapter.
+    - To avoid duplicated and potentially inconsistent state, the currently active adapter is always removed from the
+      dictionary.
+    - Disabling the adapter would also result in the modules being removed from the model.
+    """
+
+    def __init__(self, model, configs: Dict, adapter_name: str):
+        super().__init__()
+        self.model = model
+        # Store adapter configs by name.
+        self.peft_config: Dict[str, AdaptionPromptConfig] = {}
+        # Store lists of the parents of the affected attention modules by adapter name.
+        # We keep references to the parents so we can swap the adapters in-and-out of the model.
+        self._parents: Dict[str, List[nn.Module]] = {}
+        # Store lists of cached AdaptedAttention modules by name.
+        self._cached_adapters: Dict[str, List] = {}
+        # The name of the currently active adapter.
+        self._active_adapter = None
+        # Whether the adapter is enabled.
+        self._enabled = True
+        self.forward = self.model.forward
+        self.add_adapter(adapter_name, configs[adapter_name])
+        self._mark_only_adaption_prompts_as_trainable(self.model)
+
+    def add_adapter(self, adapter_name: str, config: AdaptionPromptConfig) -> None:
+        """Add an adapter with the given name and config."""
+        config = prepare_config(config, self.model)
+        if adapter_name in self.peft_config:
+            raise ValueError(f"Adapter with name '{adapter_name}' already exists.")
+
+        parents = []
+        for name, _ in self.model.named_modules():
+            if name.endswith(config.target_modules):
+                par, _, _ = _get_submodules(self.model, name)
+                parents.append(par)
+        if len(parents) < config.adapter_layers:
+            raise ValueError(
+                f"Config specifies more adapter layers '{config.adapter_layers}' than the model has '{len(parents)}'."
+            )
+        # Note that if the target modules are not in Sequential, ModuleList, or
+        # some other PyTorch ordered container, the behavior is undefined as we
+        # assume here that the order of the modules is the same as the order of
+        # the transformer decoder layers.
+        parents = parents[-config.adapter_layers :]
+        self._parents[adapter_name] = parents
+
+        # It is only None during initialization.
+        # If it is disabled, we don't have to remove the modules.
+        if self._active_adapter is not None and self._enabled:
+            self._remove_adapted_attentions(self._active_adapter)
+        self._active_adapter = adapter_name
+        self.peft_config[adapter_name] = config
+        self._create_adapted_attentions(config, parents)
+        if not self._enabled:
+            self._remove_adapted_attentions(self._active_adapter)
+
+        if config.inference_mode:
+            _freeze_adapter(self.model, adapter_name)
+
+    def set_adapter(self, adapter_name: str) -> None:
+        """Set the model to use the adapter with the given name."""
+        if self._active_adapter == adapter_name:
+            return
+        if adapter_name not in self.peft_config:
+            raise ValueError(f"Adapter with name '{adapter_name}' does not exist.")
+
+        if self._enabled:
+            self._remove_adapted_attentions(self._active_adapter)
+            self._set_adapted_attentions(adapter_name)
+
+        self._active_adapter = adapter_name
+
+    def enable_adapter_layers(self):
+        """Enable adapter layers by swapping in cached AdaptedAttention modules."""
+        self._enabled = True
+        self._set_adapted_attentions(self._active_adapter)
+
+    def disable_adapter_layers(self):
+        """Disable adapter layers by swapping out AdaptedAttention modules."""
+        self._enabled = False
+        self._remove_adapted_attentions(self._active_adapter)
+
+    def _create_adapted_attentions(self, config: AdaptionPromptConfig, parents: List[nn.Module]) -> None:
+        """Wrap LlamaAttention modules with newly created AdaptedAttention modules."""
+        for par in parents:
+            attn = AdaptedAttention(
+                model_type=self.model.config.model_type,
+                adapter_len=config.adapter_len,
+                model=getattr(par, config.target_modules),
+            )
+            setattr(par, config.target_modules, attn)
+
+    def _set_adapted_attentions(self, adapter_name: str) -> None:
+        """Replace LlamaAttention modules with cached AdaptedAttention modules."""
+        cached = self._cached_adapters[adapter_name]
+        del self._cached_adapters[adapter_name]
+        config = self.peft_config[adapter_name]
+        for i, par in enumerate(self._parents[adapter_name]):
+            setattr(par, config.target_modules, cached[i])
+
+    def _remove_adapted_attentions(self, adapter_name: str) -> None:
+        """Remove AdaptedAttention modules from the model and store them in the cache."""
+        config = self.peft_config[adapter_name]
+        adapted_attentions = []
+        for par in self._parents[adapter_name]:
+            attn = getattr(par, config.target_modules)
+            adapted_attentions.append(attn)
+            setattr(par, config.target_modules, attn.model)
+        self._cached_adapters[adapter_name] = adapted_attentions
+
+    def _mark_only_adaption_prompts_as_trainable(self, model: nn.Module) -> None:
+        """Freeze all parameters of the model except the adaption prompts."""
+        for n, p in model.named_parameters():
+            if not is_adaption_prompt_trainable(n):
+                p.requires_grad = False
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            # This is necessary as e.g. causal models have various methods that we
+            # don't want to re-implement here.
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..3058c4ef2fd5350e33e87b1746aaf3b9b6d5ef01
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/adaption_prompt/utils.py
@@ -0,0 +1,132 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import inspect
+
+import torch
+import torch.nn as nn
+
+
+def llama_rotate_half(x: torch.Tensor) -> torch.Tensor:
+    """
+    Rotate half the hidden dims of the input.
+
+    This function was duplicated verbatim from:
+    https://github.com/huggingface/transformers/blob/1de8ce9ee1191ba761a593ac15d9ccbf5851bfc5/src/transformers/models/llama/modeling_llama.py#L126
+
+    This was done to eliminate the Llama transformers implementation as a dependency of this file. Note that some other
+    functions were also adapted from the transformers implementation but were modified.
+    """
+    x1 = x[..., : x.shape[-1] // 2]
+    x2 = x[..., x.shape[-1] // 2 :]
+    return torch.cat((-x2, x1), dim=-1)
+
+
+def llama_apply_rotary_pos_emb(q, cos, sin, position_ids):
+    """
+    Apply rotary position embedding to query states in the Llama model.
+
+    This function was adapted from:
+    https://github.com/huggingface/transformers/blob/1de8ce9ee1191ba761a593ac15d9ccbf5851bfc5/src/transformers/models/llama/modeling_llama.py#L133
+
+    It was modified to remove unnecessary processing of key states. The method is compatible with transformers <=
+    4.34.2 and also with the latest version (>=4.35).
+    """
+    # In previous transformers version cos/sin cached had a shape of 4D
+    if len(cos.shape) == 4:
+        gather_indices = position_ids[:, None, :, None]  # [bs, 1, seq_len, 1]
+        gather_indices = gather_indices.repeat(1, cos.shape[1], 1, cos.shape[3])
+        cos = torch.gather(cos.repeat(gather_indices.shape[0], 1, 1, 1), 2, gather_indices)
+        sin = torch.gather(sin.repeat(gather_indices.shape[0], 1, 1, 1), 2, gather_indices)
+    # In the new version, it is 2D so we fall back to the new implementation
+    # https://github.com/huggingface/transformers/blame/eef7ea98c31a333bacdc7ae7a2372bde772be8e4/src/transformers/models/llama/modeling_llama.py#L222-L226
+    else:
+        cos = cos[position_ids].unsqueeze(1)
+        sin = sin[position_ids].unsqueeze(1)
+    q_embed = (q * cos) + (llama_rotate_half(q) * sin)
+    return q_embed
+
+
+def llama_compute_query_states(model: nn.Module, **kwargs) -> torch.Tensor:
+    """
+    Compute query states for Llama models specifically. They need to be recomputed as the forward() method of the
+    original LlamaModel in the transformers library does not return them. See the related discussion in the PR:
+    https://github.com/huggingface/peft/pull/268
+    """
+    hidden_states = kwargs.get("hidden_states")
+    position_ids = kwargs.get("position_ids")
+    past_key_value = kwargs.get("past_key_value")
+    bsz, q_len, _ = hidden_states.size()
+    if hasattr(model, "num_heads"):
+        # TODO: remove this clause after 2026-01-01
+        num_heads = model.num_heads
+    else:  # changed in https://github.com/huggingface/transformers/pull/35235
+        num_heads = model.config.num_attention_heads
+    query_states = model.q_proj(hidden_states).view(bsz, q_len, num_heads, model.head_dim).transpose(1, 2)
+
+    factor = model.k_proj.in_features // model.k_proj.out_features
+    value_states = model.v_proj(hidden_states).view(bsz, q_len, (num_heads // factor), model.head_dim).transpose(1, 2)
+
+    seq_len = q_len
+
+    if past_key_value is not None:
+        if isinstance(past_key_value, tuple):
+            # for transformers <= 4.35
+            seq_len += past_key_value[0].shape[-2]
+        else:
+            # since transformers 4.36, this is a DynamicCache instance
+            seq_len += past_key_value.get_seq_length(model.layer_idx)
+
+    # model.rotary_emb is deprecated and will be removed in transformers > 4.47.0. Instead, the position embeddings are
+    # passed via the kwargs
+    if "position_embeddings" in kwargs:
+        cos, sin = kwargs["position_embeddings"]
+        cos = cos.unsqueeze(1)
+        sin = sin.unsqueeze(1)
+        return (query_states * cos) + (llama_rotate_half(query_states) * sin)
+
+    # For transformers > 4.37.2 `position_ids` became a required arguments in the rotary embedding's forward pass.
+    if "position_ids" not in inspect.signature(model.rotary_emb.forward).parameters:
+        # TODO we assume that position_ids is not None here, not sure if that is safe but the old code also did that
+        cos, sin = model.rotary_emb(value_states, seq_len=seq_len)
+        return llama_apply_rotary_pos_emb(query_states, cos, sin, position_ids)
+
+    past_seen_tokens = 0
+    if position_ids is None:
+        # Compute position_ids, since they are required for transformers > 4.37.2
+        if past_key_value is None:
+            new_cache_positions = torch.arange(q_len, q_len + q_len, device=value_states.device)
+        else:
+            past_seen_tokens = past_key_value.get_usable_length(q_len, model.layer_idx)
+            new_cache_positions = torch.arange(past_seen_tokens, past_seen_tokens + q_len, device=value_states.device)
+        position_ids = new_cache_positions.unsqueeze(0)
+
+    rotary_emb_kwargs = {"position_ids": position_ids}
+    # The `seq_len` argument has been officially removed in transformers >= 4.39.0
+    if "seq_len" in inspect.signature(model.rotary_emb.forward).parameters:
+        rotary_emb_kwargs["seq_len"] = q_len + past_seen_tokens
+
+    cos, sin = model.rotary_emb(value_states, **rotary_emb_kwargs)
+
+    # For batched inference unsqueeze it on the correct dim
+    # since: https://github.com/huggingface/transformers/pull/29109
+    if len(cos.shape) == 3:
+        cos = cos.unsqueeze(1)
+        sin = sin.unsqueeze(1)
+
+    return (query_states * cos) + (llama_rotate_half(query_states) * sin)
+
+
+def is_adaption_prompt_trainable(params: str) -> bool:
+    """Return True if module is trainable under adaption prompt fine-tuning."""
+    return params.split(".")[-1].startswith("adaption_")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..c84b8358da8fc52d3f332c195f22b8b9620c665f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import BOFTConfig
+from .layer import BOFTLayer
+from .model import BOFTModel
+
+
+__all__ = ["BOFTConfig", "BOFTLayer", "BOFTModel"]
+
+register_peft_method(name="boft", config_cls=BOFTConfig, model_cls=BOFTModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..bedd915664c9d9970cd1da91978415e32b173008
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/config.py
@@ -0,0 +1,160 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# The implementation is based on "Parameter-Efficient Orthogonal Finetuning
+# via Butterfly Factorization" (https://arxiv.org/abs/2311.06243) in ICLR 2024.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class BOFTConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`BOFTModel`].
+
+    Args:
+        boft_block_size (`int`): BOFT block size across different layers.
+        boft_block_num (`int`): Number of BOFT blocks per injected layer.
+        boft_n_butterfly_factor (`int`): Number of butterfly factors across different layers.
+        target_modules (`Union[List[str],str]`): The names of the modules to apply the adapter to.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        boft_dropout (`float`):
+            The multiplicative dropout probability, by setting OFT blocks to identity during training, similar to the
+            dropout layer in LoRA.
+        fan_in_fan_out (`bool`): Set this to True if the layer to replace stores weight like (fan_in, fan_out).
+            For example, gpt-2 uses `Conv1D` which stores weights like (fan_in, fan_out) and hence this should be set
+            to `True`.
+        bias (`str`): Bias type for BOFT. Can be 'none', 'all' or 'boft_only'. If 'all' or 'boft_only', the
+            corresponding biases will be updated during training. Be aware that this means that, even when disabling
+            the adapters, the model will not produce the same output as the base model would have without adaptation.
+        modules_to_save (`List[str]`):List of modules apart from BOFT layers to be set as trainable
+            and saved in the final checkpoint.
+        layers_to_transform (`Union[List[int],int]`):
+            The layer indexes to transform, if this argument is specified, it will apply the BOFT transformations on
+            the layer indexes that are specified in this list. If a single integer is passed, it will apply the BOFT
+            transformations on the layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None` and if the layer
+            pattern is not in the common layers pattern. This should target the `nn.ModuleList` of the model, which is
+            often called `'layers'` or `'h'`.
+    """
+
+    boft_block_size: int = field(
+        default=4,
+        metadata={
+            "help": "BOFT block size across different layers.",
+            "note": "You can only specify either boft_block_size or boft_block_num, but not both simultaneously, because boft_block_size x boft_block_num = layer dimension.",
+        },
+    )
+    boft_block_num: int = field(
+        default=0,
+        metadata={
+            "help": "Number of BOFT blocks per injected layer.",
+            "note": "You can only specify either boft_block_size or boft_block_num, but not both simultaneously, because boft_block_size x boft_block_num = layer dimension.",
+        },
+    )
+    boft_n_butterfly_factor: int = field(
+        default=1,
+        metadata={
+            "help": "Number of butterfly factors.",
+            "note": (
+                "for example, boft_n_butterfly_factor=2, the effective block size of OFT becomes twice as big and the number of blocks become half.",
+                "note: for boft_n_butterfly_factor=1, BOFT is the same as vanilla OFT.",
+            ),
+        },
+    )
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or regex expression of the module names to replace with BOFT.",
+            "example": "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$' ",
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from BOFT."},
+    )
+    boft_dropout: float = field(
+        default=0.0,
+        metadata={
+            "help": "BOFT multiplicative dropout, randomly setting blocks of OFT to be identity matrix, similar to the dropout layer in LoRA."
+        },
+    )
+    fan_in_fan_out: bool = field(
+        default=False,
+        metadata={"help": "Set this to True if the layer to replace stores weight like (fan_in, fan_out)"},
+    )
+    bias: str = field(default="none", metadata={"help": "Bias type for BOFT. Can be 'none', 'all' or 'boft_only'"})
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from BOFT layers to be set as trainable and saved in the final checkpoint. ",
+            "note": (
+                "For example, in Sequence Classification or Token Classification tasks, ",
+                "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved.",
+            ),
+        },
+    )
+    init_weights: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the BOFT layers with their default initialization. Don't change ",
+                "this setting, except if you know exactly what you're doing.",
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index."
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern. "
+            "This should target the `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`."
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.BOFT
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
+        if self.boft_block_size == 0 and self.boft_block_num == 0:
+            raise ValueError(
+                f"Either `boft_block_size` or `boft_block_num` must be non-zero. Currently, boft_block_size = {self.boft_block_size} and boft_block_num = {self.boft_block_num}."
+            )
+        if not (self.boft_block_size != 0) ^ (self.boft_block_num != 0):
+            raise ValueError(
+                f"You can only specify either boft_block_size ({self.boft_block_size}) or boft_block_num ({self.boft_block_num}), but not both simultaneously, because boft_block_size x boft_block_num == in_features."
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/fbd_cuda.cpp b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/fbd_cuda.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..d63111b04083f3b1359aba0a9de9656060a4d515
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/fbd_cuda.cpp
@@ -0,0 +1,28 @@
+#include 
+#include 
+#include 
+#include 
+
+std::vector forward_fast_block_diag_cuda(
+        at::Tensor input);
+
+std::vector forward_fast_block_diag(
+        at::Tensor input
+        ) {
+    return forward_fast_block_diag_cuda(input);
+}
+
+std::vector backward_fast_block_diag_cuda(
+        at::Tensor grad_output, 
+        at::Tensor input);
+std::vector backward_fast_block_diag(
+        at::Tensor grad_output,
+        at::Tensor input
+        ) {
+    return backward_fast_block_diag_cuda(grad_output, input);
+}
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    m.def("forward", &forward_fast_block_diag, "FAST BLOCK DIAG (CUDA)");
+    m.def("backward", &backward_fast_block_diag, "FAST BLOCK DIAG backward (CUDA)");
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/fbd_cuda_kernel.cu b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/fbd_cuda_kernel.cu
new file mode 100644
index 0000000000000000000000000000000000000000..9f307455349e6ea8067d47ebf8a39b98ba452d09
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/fbd/fbd_cuda_kernel.cu
@@ -0,0 +1,109 @@
+// Author: Yao Feng
+// Date: 2023/08
+// Description: cuda kernel for fast block diag
+
+#include 
+
+#include 
+#include 
+#include 
+
+namespace{
+template 
+__global__ void forward_fast_block_diag_cuda_kernel(
+        const scalar_t* __restrict__ input, //[z, N, b, b]
+        scalar_t*  output, //[z, Nxb, Nxb]
+        int z, int N, int b
+    ) {
+
+    const int i = blockIdx.x * blockDim.x + threadIdx.x;
+    if (i >= z*N*b*b) {
+        return;
+    }
+    const int zi = i/(N*b*b);
+    const int Ni = (i%(N*b*b))/(b*b);
+    const int x = ((i%(N*b*b))%(b*b))/b;
+    const int y = ((i%(N*b*b))%(b*b))%b;
+
+    output[zi*N*b*N*b + (Ni*b+x)*N*b + Ni*b + y] = input[zi*N*b*b + Ni*b*b + x*b + y];
+
+}
+
+template 
+__global__ void backward_fast_block_diag_cuda_kernel(
+        const scalar_t* __restrict__ grad_output, 
+        scalar_t*  grad_input, 
+        int z, int N, int b
+    ) {
+
+    const int i = blockIdx.x * blockDim.x + threadIdx.x;
+    if (i >= z*N*b*b) {
+        return;
+    }
+    const int zi = i/(N*b*b);
+    const int Ni = (i%(N*b*b))/(b*b);
+    const int x = ((i%(N*b*b))%(b*b))/b;
+    const int y = ((i%(N*b*b))%(b*b))%b;
+    
+    grad_input[zi*N*b*b + Ni*b*b + x*b + y] = grad_output[zi*N*b*N*b + (Ni*b+x)*N*b + Ni*b + y];
+
+} // namespace
+}
+
+std::vector forward_fast_block_diag_cuda(
+    at::Tensor input
+    ){
+    const auto z = input.size(0);
+    const auto N = input.size(1);
+    const auto b = input.size(2);
+
+    // print(channel_size)
+    const int threads = 512;
+    const dim3 blocks_1 ((z*N*b*b - 1) / threads +1);
+    // initlaize output
+    auto output = at::zeros({z, N*b, N*b}, input.options());
+
+    AT_DISPATCH_FLOATING_TYPES_AND_HALF(input.type(), "forward_fast_block_diag1", ([&] {
+        forward_fast_block_diag_cuda_kernel<<>>(
+        input.data_ptr(),
+        output.data_ptr(),
+        z, N, b);
+      }));
+
+   
+    cudaError_t err = cudaGetLastError();
+    if (err != cudaSuccess) 
+            printf("Error in forward_fast_block_diag_cuda_kernel: %s\n", cudaGetErrorString(err));
+
+    return {output};
+}
+
+std::vector backward_fast_block_diag_cuda(
+    at::Tensor grad_output,
+    at::Tensor input
+    ){
+
+    const auto z = input.size(0);
+    const auto N = input.size(1);
+    const auto b = input.size(2);
+    
+    // print(channel_size)
+    const int threads = 512;
+    const dim3 blocks_1 ((z*N*b*b - 1) / threads +1);
+    
+    // initialize grad input
+    auto grad_input = at::zeros_like(input);
+
+    AT_DISPATCH_FLOATING_TYPES_AND_HALF(grad_output.type(), "backward_fast_block_diag", ([&] {
+        backward_fast_block_diag_cuda_kernel<<>>(
+        grad_output.data_ptr(),
+        grad_input.data_ptr(),
+        z, N, b);
+      }));
+    
+    cudaError_t err = cudaGetLastError();
+    if (err != cudaSuccess) 
+            printf("Error in backward_fast_block_diag_cuda_kernel: %s\n", cudaGetErrorString(err));
+
+    return {grad_input};
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..06f372659c4ce5c04c87ae6d18a98d1407ac2bbb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/layer.py
@@ -0,0 +1,984 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# The implementation is based on "Parameter-Efficient Orthogonal Finetuning
+# via Butterfly Factorization" (https://arxiv.org/abs/2311.06243) in ICLR 2024.
+
+from __future__ import annotations
+
+import math
+import os
+import warnings
+from contextlib import contextmanager
+from typing import Any, Optional, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from torch.autograd import Function
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+
+_FBD_CUDA = None
+
+
+# this function is a 1:1 copy from accelerate
+@contextmanager
+def patch_environment(**kwargs):
+    """
+    A context manager that will add each keyword argument passed to `os.environ` and remove them when exiting.
+
+    Will convert the values in `kwargs` to strings and upper-case all the keys.
+
+    Example:
+
+    ```python
+    >>> import os
+    >>> from accelerate.utils import patch_environment
+
+    >>> with patch_environment(FOO="bar"):
+    ...     print(os.environ["FOO"])  # prints "bar"
+    >>> print(os.environ["FOO"])  # raises KeyError
+    ```
+    """
+    existing_vars = {}
+    for key, value in kwargs.items():
+        key = key.upper()
+        if key in os.environ:
+            existing_vars[key] = os.environ[key]
+        os.environ[key] = str(value)
+
+    yield
+
+    for key in kwargs:
+        key = key.upper()
+        if key in existing_vars:
+            # restore previous value
+            os.environ[key] = existing_vars[key]
+        else:
+            os.environ.pop(key, None)
+
+
+def get_fbd_cuda():
+    global _FBD_CUDA
+
+    if _FBD_CUDA is not None:
+        return _FBD_CUDA
+
+    # This import initializes cuda context and should thus be local, see issue 1877
+    from torch.utils.cpp_extension import load
+
+    curr_dir = os.path.dirname(__file__)
+    # need ninja to build the extension
+    try:
+        with patch_environment(CC="gcc", CXX="gcc"):
+            fbd_cuda = load(
+                name="fbd_cuda",
+                sources=[f"{curr_dir}/fbd/fbd_cuda.cpp", f"{curr_dir}/fbd/fbd_cuda_kernel.cu"],
+                verbose=True,
+                # build_directory='/tmp/'  # for debugging
+            )
+            # extra_cuda_cflags = ['-std=c++14', '-ccbin=$$(which gcc-7)']) # cuda10.2 is not compatible with gcc9. Specify gcc 7
+    except Exception as e:
+        warnings.warn(f"Failed to load the CUDA extension: {e}, check if ninja is available.")
+        warnings.warn("Setting boft_n_butterfly_factor to 1 to speed up the finetuning process.")
+        fbd_cuda = None
+
+    _FBD_CUDA = fbd_cuda
+    return _FBD_CUDA
+
+
+class FastBlockDiag(Function):
+    """
+    Implements a custom autograd Function for a fast block diagonal operation using CUDA.
+
+    This function is optimized for 4D tensors where the last two dimensions are equal, representing block diagonal
+    matrices for efficient computation on CUDA devices.
+    """
+
+    @staticmethod
+    def forward(ctx, input):
+        """
+        The forward method for FastBlockDiag.
+
+        Computes the block diagonal operation on the input tensor using a CUDA-optimized function. This method assumes
+        that the input is a 4D tensor where the last two dimensions are equal, which represent the blocks to be
+        diagonalized.
+
+        Parameters:
+        ctx: A context object that can be used to stash information for backward computation.
+        input (Tensor): The input tensor of shape (N, D, H, H), where `N` is the batch size,
+                        `D` represents one additional dimension (In BOFT, the number of BOFT blocks), and `H` is the
+                        size of the square blocks along the last two dimensions (In BOFT, the block size).
+
+        Returns:
+        Tensor: The resulting tensor after applying the block diagonal operation,
+                will have the shape (N, DxH, DxH).
+        """
+        output = get_fbd_cuda().forward(input)[0]
+        ctx.save_for_backward(input)
+        return output
+
+    @staticmethod
+    def backward(ctx, grad_output):
+        (input,) = ctx.saved_tensors
+        grad_input = get_fbd_cuda().backward(grad_output, input)[0]
+        return grad_input
+
+
+class MultiplicativeDropoutLayer(nn.Module):
+    """
+    Implements the multiplicative dropout layer for BOFT.
+    """
+
+    def __init__(self, p=0.0):
+        """
+        Initializes the multiplicative dropout layer.
+
+        Parameters:
+        p (float): The probability of dropping out a block. Defaults to 0.0.
+        """
+        super().__init__()
+        self.p = p
+
+    def forward(self, x):
+        """
+        Applies multiplicative dropout to the input tensor.
+
+        Parameters:
+        x (Tensor): The input tensor of shape (N, D, H, H), where `N` is the batch size, `D` represents
+                    one additional dimension (In BOFT, the number of BOFT blocks), and `H` is the size of the square
+                    blocks along the last two dimensions (In BOFT, the block size).
+        """
+        if self.training:
+            # Ensure the last two dimensions are the same
+            if x.shape[-1] != x.shape[-2]:
+                raise ValueError("The last two dimensions of input should be the same!")
+
+            N, D, H, _ = x.shape
+
+            # Randomly select one from N
+            n_random = torch.randint(0, N, (1,)).item()
+
+            # Create a mask with 1s for matrices to be replaced with identity and 0s otherwise
+            num_to_replace = int(self.p * D)
+            num_zeros = D - num_to_replace
+
+            # Generate a flat tensor with desired number of 1s and 0s
+            mask = torch.cat([torch.ones(num_to_replace, device=x.device), torch.zeros(num_zeros, device=x.device)])
+
+            # Shuffle and reshape the mask
+            mask = mask[torch.randperm(D)].view(1, D, 1, 1)
+
+            full_mask = torch.zeros(N, D, 1, 1, device=x.device)
+            full_mask[n_random] = mask
+
+            # Use the mask to combine original matrices and identity matrices
+            eye_matrix = torch.eye(H, device=x.device).repeat(N, D, 1, 1)
+            x = (1 - full_mask) * x + full_mask * eye_matrix
+        return x
+
+
+class BOFTLayer(BaseTunerLayer):
+    """
+    Implements the BOFT layer.
+    """
+
+    # All names of layers that may contain (trainable) adapter weights
+    adapter_layer_names = ("boft_R", "boft_s")
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("boft_block_size", "boft_block_num", "boft_dropout")
+
+    def __init__(self, base_layer: nn.Module, **kwargs) -> None:
+        """
+        Initializes the BOFT layer.
+
+        Note, currently only support linear layer and convolutional layer, with further support for other layers to be
+        added soon.
+
+        Parameters:
+        base_layer: the pretrained model layer
+        """
+        self.base_layer = base_layer
+        self.boft_block_size = {}
+        self.boft_block_num = {}
+        self.boft_dropout = nn.ModuleDict({})
+        self.boft_R = nn.ParameterDict({})
+        self.boft_s = nn.ParameterDict({})
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+        self.kwargs = kwargs
+
+        base_layer = self.get_base_layer()
+
+        if isinstance(base_layer, nn.Linear):
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, nn.Conv2d):
+            in_features, out_features = base_layer.in_channels, base_layer.out_channels
+        else:
+            raise ValueError(f"Unsupported layer type {type(base_layer)}")
+
+        self.in_features = in_features
+        self.out_features = out_features
+
+    def set_scale(self, adapter, scale):
+        if adapter not in self.scaling:
+            # Ignore the case where the adapter is not in the layer
+            return
+
+        warnings.warn("Scaling operation for BOFT not supported! Automatically set scale to 1.")
+
+    def scale_layer(self, scale: float) -> None:
+        if scale == 1:
+            return
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.boft_R.keys():
+                continue
+
+            warnings.warn("Scaling operation for BOFT not supported! Automatically set scale to 1.")
+
+    def unscale_layer(self, scale=None) -> None:
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.boft_R.keys():
+                continue
+
+            warnings.warn("Unscaling operation for BOFT not supported! Keeping scale to 1.")
+
+    def update_layer(
+        self, adapter_name, boft_block_size, boft_block_num, boft_n_butterfly_factor, boft_dropout, init_weights
+    ):
+        """
+        Update the linear layer with trainable BOFT weights. Override for other layer types.
+        """
+        # Attempt to load the CUDA extension during model initialization
+        if not get_fbd_cuda():
+            self.fbd_cuda_available = False
+            # If the CUDA extension is not available, set the butterfly factor to 1 to speed up the finetuning process
+            boft_n_butterfly_factor = 1
+        else:
+            self.fbd_cuda_available = True
+
+        # to be consistent with the paper notation
+        boft_n_butterfly_factor = boft_n_butterfly_factor - 1
+        if boft_n_butterfly_factor < 0:
+            raise ValueError(
+                f"You can only specify boft_n_butterfly_factor {boft_n_butterfly_factor + 1} to be a positive integer number."
+            )
+
+        # Initialize the MultiplicativeDropoutLayer for boft_dropout > 0.0.
+        if boft_dropout > 0.0:
+            boft_dropout_layer = MultiplicativeDropoutLayer(p=boft_dropout)
+        else:
+            boft_dropout_layer = nn.Identity()
+        self.boft_dropout.update(nn.ModuleDict({adapter_name: boft_dropout_layer}))
+
+        if boft_block_size == 0 and boft_block_num != 0:
+            if self.in_features % boft_block_num != 0:
+                raise ValueError(
+                    f"in_features ({self.in_features}) must be divisible by boft_block_num ({boft_block_num})!"
+                )
+
+            if boft_n_butterfly_factor != 0:
+                if boft_n_butterfly_factor > int(math.log2(boft_block_num)):
+                    raise ValueError(
+                        f"Invalid combination of boft_n_butterfly_factor ({boft_n_butterfly_factor + 1}) and boft_block_num ({boft_block_num})!"
+                    )
+                if boft_block_num % (2**boft_n_butterfly_factor) != 0:
+                    raise ValueError(
+                        f"boft_block_num ({boft_block_num}) must be a multiple of 2 raised to the power of boft_n_butterfly_factor ({boft_n_butterfly_factor + 1})!"
+                    )
+
+            boft_block_size = int(self.in_features // boft_block_num)
+
+        elif boft_block_size != 0 and boft_block_num == 0:
+            if self.in_features % boft_block_size != 0:
+                raise ValueError(
+                    f"in_features ({self.in_features}) must be divisible by boft_block_size ({boft_block_size})!"
+                )
+
+            if boft_n_butterfly_factor != 0:
+                if self.in_features < (boft_block_size * (2**boft_n_butterfly_factor)):
+                    raise ValueError(
+                        f"Invalid combination of in_features ({self.in_features}), boft_n_butterfly_factor ({boft_n_butterfly_factor + 1}) and boft_block_size ({boft_block_size})!"
+                    )
+                if self.in_features % (boft_block_size * (2**boft_n_butterfly_factor)) != 0:
+                    raise ValueError(
+                        f"Invalid combination of in_features ({self.in_features}), boft_n_butterfly_factor ({boft_n_butterfly_factor + 1}) and boft_block_size ({boft_block_size})!"
+                    )
+
+            boft_block_num = int(self.in_features // boft_block_size)
+
+        else:
+            raise ValueError(
+                "Something went wrong, please report this error: https://github.com/huggingface/peft/issues"
+            )
+
+        # In OFT you can specify the number of blocks to be 1
+        if boft_n_butterfly_factor != 0:
+            if boft_block_num % 2 != 0:
+                raise ValueError(f"boft_block_num ({boft_block_num}) must be an even number!")
+
+            if boft_block_size % 2 != 0:
+                raise ValueError(f"boft_block_size ({boft_block_size}) must be an even number!")
+
+        # If there is no butterfly factor, then permutation matrix P will be an identity matrix.
+        P = torch.empty((boft_n_butterfly_factor + 1, self.in_features, self.in_features))
+        for i in range(boft_n_butterfly_factor + 1):
+            perm = self.block_butterfly_perm(
+                self.in_features, int(boft_block_num / (2 ** (i))), int(boft_block_size / 2), boft_n_butterfly_factor
+            )
+            perm_mat = self.perm2mat(perm)
+            P[i] = perm_mat
+
+        self.register_buffer("boft_P", P, persistent=False)
+
+        self.boft_R[adapter_name] = nn.Parameter(
+            torch.zeros(boft_n_butterfly_factor + 1, boft_block_num, boft_block_size, boft_block_size)
+        )
+        self.boft_s[adapter_name] = nn.Parameter(torch.ones(int(self.out_features), 1))
+
+        self.reset_boft_parameters(adapter_name, init_weights)
+
+        # set the boft block size and number
+        self.boft_block_size[adapter_name] = boft_block_size
+        self.boft_block_num[adapter_name] = boft_block_num
+
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_boft_parameters(self, adapter_name, init_weights):
+        """
+        Reset the BOFT parameters.
+        """
+        if init_weights is False:
+            nn.init.normal_(self.boft_R[adapter_name], mean=0.0, std=0.1)
+            nn.init.normal_(self.boft_s[adapter_name], mean=1.0, std=0.1)
+            return
+
+        if adapter_name in self.boft_R.keys():
+            if init_weights is True:
+                # initialize R to zero
+                nn.init.zeros_(self.boft_R[adapter_name])
+                nn.init.ones_(self.boft_s[adapter_name])
+            else:
+                raise ValueError(f"Unknown initialization {init_weights=}")
+
+    def perm2mat(self, indices):
+        """
+        Convert permutation indices to permutation matrix.
+
+        Args:
+        indices: A list of indices representing the permutation.
+        """
+        # Number of indices determines the size of the square matrix
+        n = len(indices)
+
+        # Initialize a matrix of zeros
+        perm_mat = torch.zeros((n, n))
+
+        # Set the 1s according to the indices
+        for i, idx in enumerate(indices):
+            perm_mat[i, idx] = 1
+
+        return perm_mat
+
+    def block_butterfly_perm(self, n, b, r=3, n_butterfly_factor=1):
+        """
+        Define the permutation matrix for the block butterfly permutation.
+
+        Args:
+        n: size of the permutation matrix
+        b: desired number of blocks after multiplying with the permutation matrix
+        r: base block size of the block diagonal matrix, e.g. 2x2, 3x3, 5x5 etc.
+        """
+
+        if n_butterfly_factor == 0:
+            return torch.arange(n)
+
+        if b * r * 2 > n:
+            raise ValueError("Invalid number of blocks!")
+
+        block_size = int(n // b)
+        indices = torch.arange(n)
+
+        def sort_block(b, r):
+            step = b / r
+            initial_order = torch.arange(b)
+            sorted_order = torch.empty(b, dtype=torch.long)
+
+            evens = torch.arange(0, step, 2)
+            odds = torch.arange(1, step, 2)
+            sorted_seq = torch.cat((evens, odds), dim=0)
+            for i, pos in enumerate(sorted_seq):
+                sorted_order[int(i * r) : int(i * r + r)] = initial_order[int(pos * r) : int(pos * r + r)]
+            return sorted_order
+
+        sorted_order = sort_block(block_size, r)
+
+        for i in range(0, n, block_size):
+            block_end = i + block_size
+            tmp_indices = indices[i:block_end]
+            indices[i:block_end] = tmp_indices[sorted_order]
+        return indices
+
+    def cayley_batch(self, data):
+        """
+        Perform the Cayley parametrization on a batch of skew-symmetric matrices.
+
+        Args:
+            data: A batch of skew-symmetric matrices of shape (b, r, c).
+        """
+        b, r, c = data.shape
+        # Ensure the input matrix is skew-symmetric
+        skew_mat = 0.5 * (data - data.transpose(1, 2))
+        id_mat = torch.eye(r, device=data.device).unsqueeze(0).expand(b, r, c)
+
+        # Perform the Cayley parametrization
+        Q = torch.linalg.solve(id_mat + skew_mat, id_mat - skew_mat, left=False)
+
+        return Q
+
+
+class Linear(nn.Module, BOFTLayer):
+    """
+    BOFT implemented in a dense layer.
+    """
+
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        boft_block_size: int = 8,
+        boft_block_num: int = 0,
+        boft_n_butterfly_factor: int = 0,
+        boft_dropout: float = 0.1,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        init_weights: Union[bool, str] = True,
+        is_target_conv_1d_layer: bool = False,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        BOFTLayer.__init__(self, base_layer, **kwargs)
+        self.fan_in_fan_out = fan_in_fan_out
+
+        self._active_adapter = adapter_name
+
+        self.update_layer(
+            adapter_name, boft_block_size, boft_block_num, boft_n_butterfly_factor, boft_dropout, init_weights
+        )
+        self.is_target_conv_1d_layer = is_target_conv_1d_layer
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.boft_R.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weight = base_layer.weight.data.clone()
+                    butterfly_oft_mat, boft_s = self.get_delta_weight(active_adapter)
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = torch.mm(butterfly_oft_mat, orig_weight)
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = orig_weight * boft_s
+
+                    if not torch.isfinite(orig_weight).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    self.base_layer.weight.data = orig_weight.contiguous()
+                else:
+                    butterfly_oft_mat, boft_s = self.get_delta_weight(active_adapter)
+                    orig_weight = base_layer.weight.data.clone()
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = torch.mm(butterfly_oft_mat, orig_weight)
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = orig_weight * boft_s
+
+                    self.base_layer.weight.data = orig_weight.contiguous()
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.boft_R.keys():
+                butterfly_oft_mat, boft_s = self.get_delta_weight(active_adapter)
+
+                orig_weight = self.get_base_layer().weight.data.clone()
+                orig_weight = torch.transpose(orig_weight, 0, 1)
+                orig_weight = torch.mm(butterfly_oft_mat.t(), orig_weight)
+                orig_weight = torch.transpose(orig_weight, 0, 1)
+
+                self.get_base_layer().weight.data = orig_weight * (1 / boft_s)
+
+    def get_delta_weight(self, adapter) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        boft_R = self.boft_R[adapter]
+        boft_s = self.boft_s[adapter]
+
+        N, D, H, _ = boft_R.shape
+        boft_R = boft_R.view(N * D, H, H)
+        orth_rotate_butterfly = self.cayley_batch(boft_R)
+        orth_rotate_butterfly = orth_rotate_butterfly.view(N, D, H, H)
+        if self.fbd_cuda_available:
+            block_diagonal_butterfly = FastBlockDiag.apply(orth_rotate_butterfly)
+        else:
+            orth_rotate_butterfly = orth_rotate_butterfly.squeeze(0)
+            block_diagonal_butterfly = torch.block_diag(*torch.unbind(orth_rotate_butterfly))
+            block_diagonal_butterfly = block_diagonal_butterfly.unsqueeze(0)
+
+        boft_P = self.boft_P.to(block_diagonal_butterfly.device)
+        butterfly_oft_mat_batch = torch.bmm(block_diagonal_butterfly, boft_P.permute(0, 2, 1))
+        butterfly_oft_mat_batch = torch.bmm(boft_P, butterfly_oft_mat_batch)
+        butterfly_oft_mat = butterfly_oft_mat_batch[0]
+
+        for i in range(1, butterfly_oft_mat_batch.shape[0]):
+            butterfly_oft_mat = butterfly_oft_mat_batch[i] @ butterfly_oft_mat
+
+        return butterfly_oft_mat, boft_s
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            boft_rotation = torch.eye(self.in_features, device=x.device, dtype=previous_dtype)
+            boft_scale = torch.ones((int(self.out_features), 1), device=x.device, dtype=previous_dtype)
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.boft_R.keys():
+                    continue
+                boft_R = self.boft_R[active_adapter]
+                boft_s = self.boft_s[active_adapter]
+                dropout = self.boft_dropout[active_adapter]
+
+                N, D, H, _ = boft_R.shape
+                boft_R = boft_R.view(N * D, H, H)
+                orth_rotate_butterfly = self.cayley_batch(boft_R)
+                orth_rotate_butterfly = orth_rotate_butterfly.view(N, D, H, H)
+                orth_rotate_butterfly = dropout(orth_rotate_butterfly)
+                if self.fbd_cuda_available:
+                    block_diagonal_butterfly = FastBlockDiag.apply(orth_rotate_butterfly)
+                else:
+                    orth_rotate_butterfly = orth_rotate_butterfly.squeeze(0)
+                    block_diagonal_butterfly = torch.block_diag(*torch.unbind(orth_rotate_butterfly))
+                    block_diagonal_butterfly = block_diagonal_butterfly.unsqueeze(0)
+
+                # The BOFT author's cayley_batch, dropout and FastBlockDiag ONLY return fp32 outputs.
+                boft_P = self.boft_P.to(x)
+                block_diagonal_butterfly = block_diagonal_butterfly.to(x)
+                butterfly_oft_mat_batch = torch.bmm(block_diagonal_butterfly, boft_P.permute(0, 2, 1))
+                butterfly_oft_mat_batch = torch.bmm(boft_P, butterfly_oft_mat_batch)
+                butterfly_oft_mat = butterfly_oft_mat_batch[0]
+
+                for i in range(1, butterfly_oft_mat_batch.shape[0]):
+                    butterfly_oft_mat = butterfly_oft_mat_batch[i] @ butterfly_oft_mat
+
+                boft_rotation = butterfly_oft_mat @ boft_rotation
+                boft_scale = boft_s * boft_scale
+
+            x = x.to(self.get_base_layer().weight.data.dtype)
+
+            orig_weight = self.get_base_layer().weight.data
+            orig_weight = torch.transpose(orig_weight, 0, 1)
+            boft_rotation = boft_rotation.to(previous_dtype)
+            orig_weight = orig_weight.to(previous_dtype)
+            rotated_weight = torch.mm(boft_rotation, orig_weight)
+            rotated_weight = torch.transpose(rotated_weight, 0, 1)
+
+            scaled_rotated_weight = rotated_weight * boft_scale
+
+            scaled_rotated_weight = scaled_rotated_weight.to(previous_dtype)
+            if self.base_layer.bias is not None:
+                self.base_layer.bias = self.base_layer.bias.to(previous_dtype)
+            result = F.linear(input=x, weight=scaled_rotated_weight, bias=self.base_layer.bias)
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "boft." + rep
+
+
+class Conv2d(nn.Module, BOFTLayer):
+    """
+    BOFT implemented in a Conv2d layer.
+    """
+
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        boft_block_size: int = 8,
+        boft_block_num: int = 0,
+        boft_n_butterfly_factor: int = 0,
+        boft_dropout: float = 0.1,
+        init_weights: Union[bool, str] = True,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        BOFTLayer.__init__(self, base_layer)
+
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name, boft_block_size, boft_block_num, boft_n_butterfly_factor, boft_dropout, init_weights
+        )
+
+    def update_layer(
+        self, adapter_name, boft_block_size, boft_block_num, boft_n_butterfly_factor, boft_dropout, init_weights
+    ):
+        """
+        Update the conv2d layer with trainable BOFT weights.
+        """
+
+        # Attempt to load the CUDA extension during model initialization
+        if not get_fbd_cuda():
+            self.fbd_cuda_available = False
+            # If the CUDA extension is not available, set the butterfly factor to 1 to speed up the finetuning process
+            boft_n_butterfly_factor = 1
+        else:
+            self.fbd_cuda_available = True
+
+        # to be consistent with the paper notation
+        boft_n_butterfly_factor = boft_n_butterfly_factor - 1
+        if boft_n_butterfly_factor < 0:
+            raise ValueError(
+                f"You can only specify boft_n_butterfly_factor {boft_n_butterfly_factor + 1} to be a positive integer number."
+            )
+
+        # Initialize the MultiplicativeDropoutLayer for boft_dropout > 0.0.
+        if boft_dropout > 0.0:
+            boft_dropout_layer = MultiplicativeDropoutLayer(p=boft_dropout)
+        else:
+            boft_dropout_layer = nn.Identity()
+        self.boft_dropout.update(nn.ModuleDict({adapter_name: boft_dropout_layer}))
+
+        # layer information from the base layer
+        base_layer = self.get_base_layer()
+        conv_filter_dim = self.in_features * base_layer.kernel_size[0] * base_layer.kernel_size[0]
+
+        # Initialize the BOFT parameters.
+        if boft_block_size == 0 and boft_block_num != 0:
+            if conv_filter_dim % boft_block_num != 0:
+                raise ValueError(
+                    f"Convolutional kernel dimension ({conv_filter_dim}) must be divisible by boft_block_num ({boft_block_num})!"
+                )
+
+            if boft_n_butterfly_factor != 0:
+                if boft_n_butterfly_factor > int(math.log2(boft_block_num)):
+                    raise ValueError(
+                        f"Invalid combination of boft_n_butterfly_factor ({boft_n_butterfly_factor + 1}) and boft_block_num ({boft_block_num})!"
+                    )
+                if boft_block_num % (2**boft_n_butterfly_factor) != 0:
+                    raise ValueError(
+                        f"boft_block_num ({boft_block_num}) must be a multiple of 2 raised to the power of boft_n_butterfly_factor ({boft_n_butterfly_factor + 1})!"
+                    )
+
+            boft_block_size = int(conv_filter_dim // boft_block_num)
+
+        elif boft_block_size != 0 and boft_block_num == 0:
+            if conv_filter_dim % boft_block_size != 0:
+                raise ValueError(
+                    f"Convolutional kernel dimension ({conv_filter_dim}) must be divisible by boft_block_size ({boft_block_size})!"
+                )
+
+            if boft_n_butterfly_factor != 0:
+                if conv_filter_dim < (boft_block_size * (2**boft_n_butterfly_factor)):
+                    raise ValueError(
+                        f"Invalid combination of convolutional kernel dimension ({conv_filter_dim}), boft_n_butterfly_factor ({boft_n_butterfly_factor + 1}) and boft_block_size ({boft_block_size})!"
+                    )
+                if conv_filter_dim % (boft_block_size * (2**boft_n_butterfly_factor)) != 0:
+                    raise ValueError(
+                        f"Invalid combination of convolutional kernel dimension ({conv_filter_dim}), boft_n_butterfly_factor ({boft_n_butterfly_factor + 1}) and boft_block_size ({boft_block_size})!"
+                    )
+
+            boft_block_num = int(conv_filter_dim // boft_block_size)
+
+        else:
+            raise ValueError(
+                "Something went wrong, please report this error: https://github.com/huggingface/peft/issues"
+            )
+
+        # In OFT you can specify the number of blocks to be 1
+        if boft_n_butterfly_factor != 0:
+            if boft_block_num % 2 != 0:
+                raise ValueError(f"boft_block_num ({boft_block_num}) must be an even number!")
+
+            if boft_block_size % 2 != 0:
+                raise ValueError(f"boft_block_size ({boft_block_size}) must be an even number!")
+
+        # If there is no butterfly factor, then permutation matrix P will be an identity matrix.
+        P = torch.empty((boft_n_butterfly_factor + 1, conv_filter_dim, conv_filter_dim))
+        for i in range(boft_n_butterfly_factor + 1):
+            perm = self.block_butterfly_perm(
+                conv_filter_dim, int(boft_block_num / (2 ** (i))), int(boft_block_size / 2), boft_n_butterfly_factor
+            )
+            perm_mat = self.perm2mat(perm)
+            P[i] = perm_mat
+
+        self.register_buffer("boft_P", P, persistent=False)
+
+        self.boft_R[adapter_name] = nn.Parameter(
+            torch.zeros(boft_n_butterfly_factor + 1, boft_block_num, boft_block_size, boft_block_size)
+        )
+        self.boft_s[adapter_name] = nn.Parameter(torch.ones(1, int(self.out_features)))
+
+        self.reset_boft_parameters(adapter_name, init_weights)
+
+        # set the boft block size and number
+        self.boft_block_size[adapter_name] = boft_block_size
+        self.boft_block_num[adapter_name] = boft_block_num
+
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.boft_R.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weight = base_layer.weight.data.clone()
+                    butterfly_oft_mat, boft_s = self.get_delta_weight(active_adapter)
+
+                    orig_weight = orig_weight.view(
+                        self.out_features, self.in_features * base_layer.kernel_size[0] * base_layer.kernel_size[0]
+                    )
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = torch.mm(butterfly_oft_mat, orig_weight)
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = orig_weight * boft_s
+                    orig_weight = orig_weight.view(
+                        self.out_features, self.in_features, base_layer.kernel_size[0], base_layer.kernel_size[0]
+                    )
+
+                    self.base_layer.weight.data = orig_weight.contiguous()
+                else:
+                    butterfly_oft_mat, boft_s = self.get_delta_weight(active_adapter)
+
+                    orig_weight = base_layer.weight.data.clone()
+                    orig_weight = orig_weight.view(
+                        self.out_features, self.in_features * base_layer.kernel_size[0] * base_layer.kernel_size[0]
+                    )
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = torch.mm(butterfly_oft_mat, orig_weight)
+                    orig_weight = torch.transpose(orig_weight, 0, 1)
+                    orig_weight = orig_weight * boft_s
+                    orig_weight = orig_weight.view(
+                        self.out_features, self.in_features, base_layer.kernel_size[0], base_layer.kernel_size[0]
+                    )
+
+                    self.base_layer.weight.data = orig_weight.contiguous()
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.boft_R.keys():
+                butterfly_oft_mat, boft_s = self.get_delta_weight(active_adapter)
+
+                orig_weight = self.get_base_layer().weight.data.clone()
+                orig_weight = orig_weight.view(
+                    self.out_features,
+                    self.in_features * self.get_base_layer().kernel_size[0] * self.get_base_layer().kernel_size[0],
+                )
+                orig_weight = torch.transpose(orig_weight, 0, 1)
+                orig_weight = torch.mm(butterfly_oft_mat.t(), orig_weight)
+                orig_weight = torch.transpose(orig_weight, 0, 1)
+                orig_weight = orig_weight * (1 / boft_s)
+                orig_weight = orig_weight.view(
+                    self.out_features,
+                    self.in_features,
+                    self.get_base_layer().kernel_size[0],
+                    self.get_base_layer().kernel_size[0],
+                )
+
+                self.get_base_layer().weight.data = orig_weight
+
+    def get_delta_weight(self, adapter) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+
+        boft_R = self.boft_R[adapter]
+        boft_s = self.boft_s[adapter].transpose(0, 1)
+
+        N, D, H, _ = boft_R.shape
+        boft_R = boft_R.view(N * D, H, H)
+        orth_rotate_butterfly = self.cayley_batch(boft_R)
+        orth_rotate_butterfly = orth_rotate_butterfly.view(N, D, H, H)
+        if self.fbd_cuda_available:
+            block_diagonal_butterfly = FastBlockDiag.apply(orth_rotate_butterfly)
+        else:
+            orth_rotate_butterfly = orth_rotate_butterfly.squeeze(0)
+            block_diagonal_butterfly = torch.block_diag(*torch.unbind(orth_rotate_butterfly))
+            block_diagonal_butterfly = block_diagonal_butterfly.unsqueeze(0)
+
+        boft_P = self.boft_P.to(block_diagonal_butterfly.device)
+        butterfly_oft_mat_batch = torch.bmm(block_diagonal_butterfly, boft_P.permute(0, 2, 1))
+        butterfly_oft_mat_batch = torch.bmm(boft_P, butterfly_oft_mat_batch)
+        butterfly_oft_mat = butterfly_oft_mat_batch[0]
+
+        for i in range(1, butterfly_oft_mat_batch.shape[0]):
+            butterfly_oft_mat = butterfly_oft_mat_batch[i] @ butterfly_oft_mat
+
+        return butterfly_oft_mat, boft_s
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            boft_rotation = torch.eye(
+                self.in_features * self.base_layer.kernel_size[0] * self.base_layer.kernel_size[0],
+                device=x.device,
+                dtype=x.dtype,
+            )
+            boft_scale = torch.ones((int(self.out_features), 1), device=x.device, dtype=x.dtype)
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.boft_R.keys():
+                    continue
+                boft_R = self.boft_R[active_adapter]
+                boft_s = self.boft_s[active_adapter].transpose(0, 1)
+                dropout = self.boft_dropout[active_adapter]
+
+                N, D, H, _ = boft_R.shape
+                boft_R = boft_R.view(N * D, H, H)
+                orth_rotate_butterfly = self.cayley_batch(boft_R)
+                orth_rotate_butterfly = orth_rotate_butterfly.view(N, D, H, H)
+                orth_rotate_butterfly = dropout(orth_rotate_butterfly)
+                if self.fbd_cuda_available:
+                    block_diagonal_butterfly = FastBlockDiag.apply(orth_rotate_butterfly)
+                else:
+                    orth_rotate_butterfly = orth_rotate_butterfly.squeeze(0)
+                    block_diagonal_butterfly = torch.block_diag(*torch.unbind(orth_rotate_butterfly))
+                    block_diagonal_butterfly = block_diagonal_butterfly.unsqueeze(0)
+
+                boft_P = self.boft_P.to(x)
+                block_diagonal_butterfly = block_diagonal_butterfly.to(x)
+                butterfly_oft_mat_batch = torch.bmm(block_diagonal_butterfly, boft_P.permute(0, 2, 1))
+                butterfly_oft_mat_batch = torch.bmm(boft_P, butterfly_oft_mat_batch)
+                butterfly_oft_mat = butterfly_oft_mat_batch[0]
+
+                for i in range(1, butterfly_oft_mat_batch.shape[0]):
+                    butterfly_oft_mat = butterfly_oft_mat_batch[i] @ butterfly_oft_mat
+
+                boft_rotation = butterfly_oft_mat @ boft_rotation
+                boft_scale = boft_s * boft_scale
+
+            x = x.to(self.base_layer.weight.data.dtype)
+
+            orig_weight = self.base_layer.weight.data
+            orig_weight = orig_weight.view(
+                self.out_features,
+                self.in_features * self.base_layer.kernel_size[0] * self.base_layer.kernel_size[0],
+            )
+            orig_weight = torch.transpose(orig_weight, 0, 1)
+            rotated_weight = torch.mm(boft_rotation, orig_weight)
+            rotated_weight = torch.transpose(rotated_weight, 0, 1)
+
+            scaled_rotated_weight = rotated_weight * boft_scale
+
+            scaled_rotated_weight = scaled_rotated_weight.view(
+                self.out_features, self.in_features, self.base_layer.kernel_size[0], self.base_layer.kernel_size[0]
+            )
+            result = F.conv2d(
+                input=x,
+                weight=scaled_rotated_weight,
+                bias=self.base_layer.bias,
+                padding=self.base_layer.padding[0],
+                stride=self.base_layer.stride[0],
+            )
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "boft." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a4bb8158fbf8f30508548d7c0d66161b57ded33
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/boft/model.py
@@ -0,0 +1,353 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# The implementation is based on "Parameter-Efficient Orthogonal Finetuning
+# via Butterfly Factorization" (https://arxiv.org/abs/2311.06243) in ICLR 2024.
+
+import warnings
+from dataclasses import asdict
+from enum import Enum
+from typing import List, Optional
+
+import torch
+from torch import nn
+from tqdm import tqdm
+
+from peft.tuners.tuners_utils import (
+    BaseTuner,
+    BaseTunerLayer,
+    check_target_module_exists,
+    onload_layer,
+)
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    _get_submodules,
+)
+
+from .config import BOFTConfig
+from .layer import BOFTLayer, Conv2d, Linear
+
+
+class BOFTModel(BaseTuner):
+    """
+    Creates BOFT and OFT model from a pretrained transformers model. Paper: https://arxiv.org/abs/2311.06243
+    https://arxiv.org/abs/2306.07280
+
+    Args:
+        model ([`transformers.PreTrainedModel`]): The model to be adapted.
+        config ([`BOFTConfig`]): The configuration of the BOFT model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The BOFT model.
+
+    Example::
+
+        >>> import transformers >>> from transformers import AutoModelForSeq2SeqLM, BOFTConfig >>> from peft import
+        BOFTConfig, get_peft_model
+
+        >>> config = BOFTConfig( ... boft_block_size=8, ... boft_n_butterfly_factor=1, ... target_modules=["query",
+        "value", "key", "output.dense", "mlp.fc1", "mlp.fc2"], ... boft_dropout=0.1, ... bias="boft_only", ...
+        modules_to_save=["classifier"], ... )
+
+        >>> model = transformers.Dinov2ForImageClassification.from_pretrained( ... "facebook/dinov2-large", ...
+        num_labels=100, ... ) >>> boft_model = get_peft_model(model, config)
+
+    **Attributes**:
+        - **model** ([`transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`BOFTConfig`]): The configuration of the BOFT model.
+    """
+
+    prefix: str = "boft_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False) -> None:
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def _check_new_adapter_config(self, config: BOFTConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(boft_config, key):
+        return check_target_module_exists(boft_config, key)
+
+    def _create_and_replace(
+        self,
+        boft_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+        **optional_kwargs,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+
+        bias = hasattr(target, "bias") and target.bias is not None
+        kwargs = {
+            "boft_block_size": boft_config.boft_block_size,
+            "boft_block_num": boft_config.boft_block_num,
+            "boft_n_butterfly_factor": boft_config.boft_n_butterfly_factor,
+            "boft_dropout": boft_config.boft_dropout,
+            "fan_in_fan_out": boft_config.fan_in_fan_out,
+            "init_weights": boft_config.init_weights,
+        }
+        kwargs["bias"] = bias
+
+        # If it is not a BOFTLayer, create a new module, else update it with new adapters
+        if not isinstance(target, BOFTLayer):
+            new_module = self._create_new_module(boft_config, adapter_name, target, **kwargs)
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+        else:
+            target.update_layer(
+                adapter_name,
+                boft_block_size=boft_config.boft_block_size,
+                boft_block_num=boft_config.boft_block_num,
+                boft_n_butterfly_factor=boft_config.boft_n_butterfly_factor,
+                boft_dropout=boft_config.boft_dropout,
+                init_weights=boft_config.init_weights,
+            )
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if self.prefix in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "boft_only":
+                for name, m in model.named_modules():
+                    if isinstance(m, BOFTLayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(boft_config, adapter_name, target, **kwargs):
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Linear):
+            if kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                    "Setting fan_in_fan_out to False."
+                )
+                kwargs["fan_in_fan_out"] = boft_config.fan_in_fan_out = False
+            new_module = Linear(target, adapter_name, **kwargs)
+        elif isinstance(target_base_layer, torch.nn.Conv2d):
+            new_module = Conv2d(target, adapter_name, **kwargs)
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. "
+                "Currently, only `torch.nn.Linear` and `torch.nn.Conv2d` are supported."
+            )
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self):
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self):
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name):
+        for module in self.model.modules():
+            if isinstance(module, BOFTLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[List[str]] = None,
+    ):
+        if merge:
+            self._check_merge_allowed()
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+            with onload_layer(target):
+                if hasattr(target, "base_layer"):
+                    if merge:
+                        target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                    self._replace_module(parent, target_name, target.get_base_layer(), target)
+                elif isinstance(target, ModulesToSaveWrapper):
+                    # save any additional trainable modules part of `modules_to_save`
+                    new_module = target.modules_to_save[target.active_adapter]
+                    if hasattr(new_module, "base_layer"):
+                        # check if the module is itself a tuner layer
+                        if merge:
+                            new_module.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                        new_module = new_module.get_base_layer()
+                    setattr(parent, target_name, new_module)
+
+        return self.model
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, BOFTLayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[List[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the BOFT layers into the base model. This is needed if someone wants to use the base model
+        as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the boft modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..f131e8c17d3d11fa06c11a473cf2a54075cf443a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import BoneConfig
+from .layer import BoneLayer, BoneLinear
+from .model import BoneModel
+
+
+__all__ = ["BoneConfig", "BoneLayer", "BoneLinear", "BoneModel"]
+
+register_peft_method(name="bone", config_cls=BoneConfig, model_cls=BoneModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f6915aa20f52147b01fc0632543013ea358df26
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/config.py
@@ -0,0 +1,123 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Literal, Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class BoneConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`BoneModel`].
+
+    Args:
+        r (`int`):
+            The rank of Bone across different layers. It is best to set 'r' to an even number; otherwise, the default
+            initialization method will not work.
+        target_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear modules are chosen, excluding
+            the output layer. If this is not specified, modules will be chosen according to the model architecture. If
+            the architecture is not known, an error will be raised -- in this case, you should specify the target
+            modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        init_weights (bool | Literal["bat"]):
+            Different initializations correspond to different Bone variants. By default, setting True uses the Bone
+            structure, while "bat" selects the Bat structure.
+        layers_to_transform (`Union[List[int], int]`):
+            The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
+            that are specified in this list. If a single integer is passed, it will apply the transformations on the
+            layer at this index.
+        layers_pattern (`str`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`.
+        modules_to_save (`List[str]`):
+            List of modules apart from adapter layers to be set as trainable and saved in the final checkpoint.
+    """
+
+    r: int = field(
+        default=64,
+        metadata={
+            "help": "The rank of Bone across different layers.",
+            "note": "It is best to set 'r' to an even number; otherwise, the default initialization method will not work.",
+        },
+    )
+
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or regex expression of the module names to replace with Bone.",
+            "example": "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$' ",
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from Bone."},
+    )
+    init_weights: bool | Literal["bat"] = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the Bone layers with their default initialization. Don't change "
+                "this setting, except if you know exactly what you're doing."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index."
+        },
+    )
+    layers_pattern: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern."
+        },
+    )
+    bias: str = field(default="none", metadata={"help": "Bias type for Bone. Can be 'none', 'all' or 'Bone_only'"})
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from Bone layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.BONE
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # if target_modules is a regex expression, then layers_to_transform should be None
+        if isinstance(self.target_modules, str) and self.layers_to_transform is not None:
+            raise ValueError("`layers_to_transform` cannot be used when `target_modules` is a str.")
+
+        # if target_modules is a regex expression, then layers_pattern should be None
+        if isinstance(self.target_modules, str) and self.layers_pattern is not None:
+            raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..5c8b2637102122ee95605850e6be1f6bfed52726
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/layer.py
@@ -0,0 +1,339 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import math
+import warnings
+from typing import Any, List, Optional, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+
+class BoneLayer(BaseTunerLayer):
+    # All names of layers that may contain (trainable) adapter weights
+    adapter_layer_names = ("bone_block",)
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("bone_r",)
+
+    def __init__(self, base_layer: nn.Module, **kwargs) -> None:
+        self.base_layer = base_layer
+        self.bone_r = {}
+        self.bone_block = nn.ParameterDict({})
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+        self.kwargs = kwargs
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            self.in_features, self.out_features = base_layer.in_features, base_layer.out_features
+        else:
+            raise ValueError(f"Unsupported layer type {type(base_layer)}")
+
+    def update_layer(
+        self,
+        adapter_name: str,
+        r: int,
+        init_weights: bool,
+        **kwargs,
+    ) -> None:
+        """Internal function to create bone adapter
+
+        Args:
+            adapter_name (`str`): Name for the adapter to add.
+            r (`int`): Rank for the added adapter.
+            init_weights (`bool`): Whether to initialize weights.
+        """
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+
+        self.bone_r[adapter_name] = r
+
+        # Determine shape of Bone weights
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            self.bone_block[adapter_name] = nn.Parameter(torch.zeros(r, self.out_features), requires_grad=True)
+
+        else:
+            raise TypeError(f"Bone is not implemented for base layers of type {type(base_layer).__name__}")
+
+        # Initialize weights
+        if init_weights == "bat":
+            if self.in_features % r != 0 or self.out_features % r != 0:
+                raise ValueError("The weight matrix must be fully divisible into [r, r] blocks.")
+            self.reset_bat_parameters(adapter_name, r)
+        elif init_weights:
+            self.reset_bone_parameters(adapter_name, r)
+        else:
+            self.reset_bone_parameters_random(adapter_name)
+        # Move new weights to device
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_bone_parameters(self, adapter_name: str, r):
+        self.bone_block[adapter_name] = nn.Parameter(torch.zeros(r, self.out_features), requires_grad=True)
+
+    def reset_bat_parameters(self, adapter_name: str, r):
+        self.bone_block[adapter_name] = nn.Parameter(torch.zeros(self.out_features // r, r, r), requires_grad=True)
+
+    def reset_bone_parameters_random(self, adapter_name: str):
+        nn.init.kaiming_uniform_(self.bone_block[adapter_name], a=math.sqrt(5))
+
+    def scale_layer(self, scale: float) -> None:
+        if scale == 1:
+            return
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.bone_block.keys():
+                continue
+
+            warnings.warn("Scaling operation for Bone not supported! Automatically set scale to 1.")
+
+    def unscale_layer(self, scale=None) -> None:
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.bone_block.keys():
+                continue
+
+            warnings.warn("Unscaling operation for Bone not supported! Keeping scale at 1.")
+
+
+class BoneLinear(nn.Module, BoneLayer):
+    """
+    Bone implemented in a dense layer.
+    """
+
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 0,
+        init_weights: Union[bool, str] = True,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        BoneLayer.__init__(self, base_layer, **kwargs)
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, init_weights, **kwargs)
+        self.bone_fn = init_weights
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If `True`, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If `None`, all active adapters will be merged.
+                Defaults to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.bone_block.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weight = base_layer.weight.data.clone()
+                    if self.bone_fn == "bat":
+                        delta_weight = self.get_delta_weight(active_adapter, orig_weight)
+                        orig_weight += delta_weight
+                    else:
+                        delta_weight = self.get_delta_weight_bone(active_adapter, self.base_layer.weight.data)
+                        orig_weight = delta_weight
+
+                    if not torch.isfinite(orig_weight).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    self.base_layer.weight.data = orig_weight
+                else:
+                    if self.bone_fn == "bat":
+                        delta_weight = self.get_delta_weight(active_adapter, self.base_layer.weight.data)
+                        self.base_layer.weight.data += delta_weight
+                    else:
+                        delta_weight = self.get_delta_weight_bone(active_adapter, self.base_layer.weight.data)
+                        self.base_layer.weight.data = delta_weight
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.bone_block.keys():
+                orig_weight = self.get_base_layer().weight.data.clone()
+                if self.bone_fn == "bat":
+                    delta_weight = self.get_delta_weight(active_adapter, orig_weight, re=True)
+                else:
+                    delta_weight = self.get_delta_weight_bone(active_adapter, orig_weight, re=True)
+
+                self.get_base_layer().weight.data = delta_weight
+
+    def get_delta_weight(self, adapter, orig_weight, re: bool = False) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.bone_block[adapter].device
+        dtype = self.bone_block[adapter].dtype
+        # In case users wants to merge the adapter weights that are in
+        # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+        cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+        weight_bone = self.bone_block[adapter]
+
+        if cast_to_fp32:
+            weight_bone = weight_bone.float()
+
+        r = weight_bone.size(-1)
+        if re:
+            o = orig_weight.reshape(orig_weight.size(0) // r, r, orig_weight.size(1) // r, r).permute(2, 0, 1, 3)
+            one = torch.eye(weight_bone.size(-1)).to(weight_bone.device)
+            inv_I_plus_b = torch.inverse(one + weight_bone)
+            w = (o - weight_bone) @ inv_I_plus_b
+            output_tensor = w.permute(1, 2, 0, 3).reshape(*orig_weight.shape)
+        else:
+            w = (
+                orig_weight.reshape(orig_weight.size(0) // r, r, orig_weight.size(1) // r, r).permute(2, 0, 1, 3)
+                @ weight_bone
+                + weight_bone
+            )
+            output_tensor = w.permute(1, 2, 0, 3).reshape(*orig_weight.shape)
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            self.bone_block[adapter].data = weight_bone.to(dtype)
+
+        return output_tensor
+
+    def get_delta_weight_bone(self, adapter, orig_weight, re: bool = False) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.bone_block[adapter].device
+        dtype = self.bone_block[adapter].dtype
+        # In case users wants to merge the adapter weights that are in
+        # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+        cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+        weight_bone = self.bone_block[adapter]
+
+        if cast_to_fp32:
+            weight_bone = weight_bone.float()
+
+        in_features = orig_weight.size(-1)
+        r = weight_bone.size(0)
+        if in_features % r != 0:
+            last_size = in_features % r
+            n_block = in_features // r
+            n_block_size = n_block * r
+
+            if re:
+                orig_weight[:, :n_block_size] = (
+                    (orig_weight[:, :n_block_size].reshape(-1, n_block, r).permute(1, 2, 0) - weight_bone)
+                    .permute(2, 0, 1)
+                    .reshape(*orig_weight[:, :n_block_size].shape)
+                )
+                orig_weight[:, n_block_size:] = (
+                    orig_weight[:, n_block_size:] - (weight_bone.transpose(0, 1))[:, :last_size]
+                )
+            else:
+                orig_weight[:, :n_block_size] = (
+                    (orig_weight[:, :n_block_size].reshape(-1, n_block, r).permute(1, 2, 0) + weight_bone)
+                    .permute(2, 0, 1)
+                    .reshape(*orig_weight[:, :n_block_size].shape)
+                )
+                orig_weight[:, n_block_size:] = (
+                    orig_weight[:, n_block_size:] + (weight_bone.transpose(0, 1))[:, :last_size]
+                )
+            output_tensor = orig_weight
+
+        else:
+            if re:
+                w = orig_weight.reshape(-1, orig_weight.size(1) // r, r).permute(1, 2, 0) - weight_bone
+                output_tensor = w.permute(2, 0, 1).reshape(*orig_weight.shape)
+            else:
+                w = orig_weight.reshape(-1, orig_weight.size(1) // r, r).permute(1, 2, 0) + weight_bone
+                output_tensor = w.permute(2, 0, 1).reshape(*orig_weight.shape)
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            self.bone_block[adapter].data = weight_bone.to(dtype)
+
+        return output_tensor
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            if self.bone_fn == "bat":
+                orig_weight = self.base_layer.weight.data.clone()
+                for active_adapter in self.active_adapters:
+                    if active_adapter not in self.bone_block.keys():
+                        continue
+                    delta_weight = self.get_delta_weight(active_adapter, orig_weight)
+                    orig_weight = orig_weight + delta_weight
+
+                result = F.linear(input=x, weight=orig_weight, bias=self.base_layer.bias)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+                for active_adapter in self.active_adapters:
+                    if active_adapter not in self.bone_block.keys():
+                        continue
+                    bone = self.bone_block[active_adapter]
+                    r = bone.size(0)
+                    if x.size(-1) % r != 0:
+                        padding_size = (r - x.size(-1) % r) % r
+                        x = F.pad(x, (0, padding_size))
+                    result = result + torch.sum(x.reshape(*x.shape[:-1], x.size(-1) // r, r), dim=-2) @ bone
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "bone." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d6a553436bb6804c137835e4523171b26e1f31e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/bone/model.py
@@ -0,0 +1,336 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from dataclasses import asdict
+from enum import Enum
+from typing import List, Optional
+
+import torch
+from torch import nn
+from tqdm import tqdm
+
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    _get_submodules,
+)
+
+from .config import BoneConfig
+from .layer import BoneLayer, BoneLinear
+
+
+class BoneModel(BaseTuner):
+    """
+    Creates Householder reflection adaptation (Bone) model from a pretrained model. The method is described in
+    https://arxiv.org/abs/2409.15371
+
+    Args:
+        model (`torch.nn.Module`): The model to which the adapter tuner layers will be attached.
+        config ([`BoneConfig`]): The configuration of the Bone model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The Bone model.
+
+    Example:
+        ```py
+        >>> from diffusers import StableDiffusionPipeline
+        >>> from peft import BoneModel, BoneConfig
+
+        >>> config_te = BoneConfig(
+        ...     r=8,
+        ...     target_modules=["k_proj", "q_proj", "v_proj", "out_proj", "fc1", "fc2"],
+        ...     init_weights=True,
+        ... )
+        >>> config_unet = BoneConfig(
+        ...     r=8,
+        ...     target_modules=[
+        ...         "proj_in",
+        ...         "proj_out",
+        ...         "to_k",
+        ...         "to_q",
+        ...         "to_v",
+        ...         "to_out.0",
+        ...         "ff.net.0.proj",
+        ...         "ff.net.2",
+        ...     ],
+        ...     init_weights=True,
+        ... )
+
+        >>> model = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+        >>> model.text_encoder = BoneModel(model.text_encoder, config_te, "default")
+        >>> model.unet = BoneModel(model.unet, config_unet, "default")
+        ```
+
+    **Attributes**:
+        - **model** ([`~torch.nn.Module`]) -- The model to be adapted.
+        - **peft_config** ([`BoneConfig`]): The configuration of the Bone model.
+    """
+
+    prefix: str = "bone_"
+
+    def _check_new_adapter_config(self, config: BoneConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(bone_config, key):
+        return check_target_module_exists(bone_config, key)
+
+    def _create_and_replace(
+        self,
+        bone_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+        **optional_kwargs,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+
+        bias = hasattr(target, "bias") and target.bias is not None
+        kwargs = {
+            "r": bone_config.r,
+            "init_weights": bone_config.init_weights,
+        }
+        kwargs["bias"] = bias
+
+        # If it is not a BoneLayer, create a new module, else update it with new adapters
+        if not isinstance(target, BoneLayer):
+            new_module = self._create_new_module(bone_config, adapter_name, target, **kwargs)
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+        else:
+            target.update_layer(
+                adapter_name,
+                r=bone_config.r,
+                init_weights=bone_config.init_weights,
+            )
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if self.prefix in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "bone_only":
+                for name, m in model.named_modules():
+                    if isinstance(m, BoneLayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(bone_config, adapter_name, target, **kwargs):
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Linear):
+            new_module = BoneLinear(target, adapter_name, **kwargs)
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. Currently, only `torch.nn.Linear` is supported."
+            )
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "base_model":
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self):
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self):
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name):
+        for module in self.model.modules():
+            if isinstance(module, BoneLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[List[str]] = None,
+    ):
+        self._unloading_checks(adapter_names)
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                setattr(parent, target_name, target.modules_to_save[target.active_adapter])
+
+        return self.model
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, BoneLayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[List[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the Bone layers into the base model. This is needed if someone wants to use the base model
+        as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the bone modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..fcd4de85989168ad6834712679c805cba39c1df1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from peft.utils import register_peft_method
+
+from .config import CPTConfig
+from .model import CPTEmbedding
+
+
+__all__ = ["CPTConfig", "CPTEmbedding"]
+
+register_peft_method(name="cpt", config_cls=CPTConfig, model_cls=CPTEmbedding)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..971c30983f20ebabe24f2fe88a24df8f662d6a95
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/config.py
@@ -0,0 +1,98 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from dataclasses import dataclass, field
+from typing import Literal, Optional
+
+from peft.config import PromptLearningConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class CPTConfig(PromptLearningConfig):
+    """
+    CPT Configuration class extending PeftConfig for Context-aware Prompt Tuning (CPT).
+
+    This class introduces additional parameters required for CPT, such as:
+    - Token type masks
+    - Prompt tuning initialization
+    - Loss weighting
+    - Projection settings
+
+    For more details, see the paper: https://arxiv.org/abs/2410.17222
+    """
+
+    # Token-related configurations
+    cpt_token_ids: Optional[list[int]] = field(
+        default=None, metadata={"help": "Tensor of token IDs used for CPT prompts."}
+    )
+    cpt_mask: Optional[list[int]] = field(default=None, metadata={"help": "Tensor mask applied to CPT tokens."})
+    cpt_tokens_type_mask: Optional[list[int]] = field(
+        default=None, metadata={"help": "Mask indicating the type of each CPT token."}
+    )
+
+    # Loss-related configurations
+    opt_weighted_loss_type: Optional[Literal["none", "decay"]] = field(
+        default="none", metadata={"help": "Type of weighted loss: 'none' or 'decay'."}
+    )
+    opt_loss_decay_factor: Optional[float] = field(
+        default=1.0, metadata={"help": "Factor for exponential decay in loss weighting."}
+    )
+
+    # Projection-related configurations
+    opt_projection_epsilon: Optional[float] = field(
+        default=0.1, metadata={"help": "Epsilon value for input projection."}
+    )
+    opt_projection_format_epsilon: Optional[float] = field(
+        default=0.1, metadata={"help": "Epsilon value for format projection."}
+    )
+
+    # Tokenizer configuration
+    tokenizer_name_or_path: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": "The tokenizer to use for prompt tuning initialization. Only used if prompt_tuning_init is `TEXT`"
+        },
+    )
+    # Neet to define CPT-specific static attributes
+    is_prompt_learning = True  # Indicates that CPT is a prompt-learning method.
+
+    def __post_init__(self):
+        """
+        Post-initialization hook to set additional attributes after the config is initialized.
+        """
+        # CPT-specific static attributes
+        self.is_prompt_learning = True  # Indicates that CPT is a prompt-learning method.
+        self.num_layers = None  # Number of layers (optional, not always required).
+        self.token_dim = None  # Dimension of token embeddings.
+        self.num_attention_heads = None  # Number of attention heads (if applicable).
+        self.num_transformer_submodules = 1  # Number of transformer submodules used.
+        self.peft_type = PeftType.CPT  # Specifies that the PEFT type is CPT.
+        self.task_type = "CAUSAL_LM"  # Ensures task type is causal language modeling.
+
+        if self.cpt_token_ids is None:
+            self.cpt_token_ids = [0]
+
+        self.num_virtual_tokens = len(self.cpt_token_ids)
+
+        if self.cpt_mask is None:
+            self.cpt_mask = [1 for _ in self.cpt_token_ids]
+
+        if self.cpt_tokens_type_mask is None:
+            self.cpt_tokens_type_mask = [1 for _ in self.cpt_token_ids]
+
+        if not (
+            len(self.cpt_token_ids) == len(self.cpt_mask) == len(self.cpt_tokens_type_mask) == self.num_virtual_tokens
+        ):
+            raise ValueError("cpt_token_ids, cpt_mask and cpt_tokens_type_mask must have the same length.")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..934a3b7928c125bd433441f36cf4b26de15b535f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/cpt/model.py
@@ -0,0 +1,200 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import copy
+
+import torch
+from torch.nn import CrossEntropyLoss
+
+from peft.utils.integrations import gather_params_ctx
+
+
+class CPTEmbedding(torch.nn.Module):
+    """
+    CPTEmbedding is a custom embedding layer designed for Context-aware Prompt Tuning (CPT) in PEFT. It initializes
+    embeddings, applies prompt-specific projections, and computes loss using label masks.
+    """
+
+    def __init__(self, config, word_embeddings):
+        """
+        Initializes the CPTEmbedding module.
+
+        Args:
+            config (Namespace):
+                Configuration object containing model hyperparameters and CPT-specific settings.
+            word_embeddings (torch.nn.Embedding):
+                The base word embedding layer used to initialize CPT embeddings.
+        """
+        super().__init__()
+        self.config = copy.deepcopy(config)
+        num_virtual_tokens = config.num_virtual_tokens
+
+        # Initialize embeddings with virtual token dimensions
+        self.embedding = torch.nn.Embedding(num_virtual_tokens, config.token_dim)
+
+        # Initialize embeddings using text-based prompt tuning, if configured
+        if not config.inference_mode:
+            assert config.num_virtual_tokens == len(config.cpt_token_ids)
+
+            init_token_ids = torch.LongTensor(config.cpt_token_ids).to(word_embeddings.weight.device)
+            with gather_params_ctx(word_embeddings.parameters()):
+                word_embedding_weights = word_embeddings(init_token_ids).detach().clone()
+            word_embedding_weights = word_embedding_weights.to(torch.float32)
+            self.embedding.weight = torch.nn.Parameter(word_embedding_weights)
+
+        # Initialize delta embedding with zero weights
+        self.delta_embedding = torch.nn.Embedding(num_virtual_tokens, config.token_dim)
+        self.delta_embedding.weight.data = torch.zeros_like(self.delta_embedding.weight).to(torch.float32)
+
+        # Apply hook for backward gradient updates
+        self.set_updated_tokens()
+
+    def forward(self, indices):
+        """
+        Computes the prompt embeddings and applies delta adjustments.
+
+        Args:
+            indices (torch.Tensor):
+                Indices of the tokens to be embedded.
+
+        Returns:
+            torch.Tensor:
+                Sum of prompt embeddings and delta embeddings.
+        """
+        with torch.no_grad():
+            prompt_embeddings = self.embedding(indices)
+
+        self.delta_embedding.weight.data = self.get_projection()  # Apply epsilon-based projection
+
+        delta_prompt_embeddings = self.delta_embedding(indices)
+
+        return prompt_embeddings + delta_prompt_embeddings
+
+    def set_updated_tokens(self):
+        """
+        Sets up a backward hook to selectively update token gradients based on the CPT token type mask.
+        """
+        tensor_ICL_mask = torch.Tensor(self.config.cpt_tokens_type_mask).long()
+        mask_input_template = torch.remainder(tensor_ICL_mask, 4) == 1
+        mask_input = torch.remainder(tensor_ICL_mask, 4) == 2
+        mask_output_template = torch.remainder(tensor_ICL_mask, 4) == 3
+        mask = mask_input_template | mask_input | mask_output_template
+        mask = mask.view(-1, 1)
+
+        def backward_hook(grad):
+            grad = grad * mask.to(grad.device)  # Apply mask to gradients
+            return grad
+
+        self.delta_embedding.weight.register_hook(backward_hook)
+
+    def get_epsilon(self):
+        cpt_tokens_type_mask = self.config.cpt_tokens_type_mask
+
+        MIN_VALUE = 1e-10
+
+        # Calculate normalized epsilon values for input, output, and format tokens
+        normalized_format_eps = self.config.opt_projection_format_epsilon * torch.sqrt(
+            torch.Tensor([self.config.token_dim / 2048])
+        )
+        normalized_input_eps = self.config.opt_projection_epsilon * torch.sqrt(
+            torch.Tensor([self.config.token_dim / 2048])
+        )
+
+        epsilon = torch.ones_like(torch.Tensor(cpt_tokens_type_mask)).to(torch.float32) * MIN_VALUE
+        cpt_tokens_type_mask = torch.Tensor(cpt_tokens_type_mask).long()
+
+        epsilon[(cpt_tokens_type_mask > 0) & (torch.remainder(cpt_tokens_type_mask, 4) == 1)] = normalized_format_eps
+        epsilon[(cpt_tokens_type_mask > 0) & (torch.remainder(cpt_tokens_type_mask, 4) == 3)] = normalized_format_eps
+        epsilon[(cpt_tokens_type_mask > 0) & (torch.remainder(cpt_tokens_type_mask, 4) == 2)] = normalized_input_eps
+
+        return epsilon
+
+    def get_projection(self):
+        """
+        Applies epsilon-based projection to the delta embeddings to control their norm.
+        """
+
+        # Apply projection to control delta embedding norm
+        with torch.no_grad():
+            new_embeddings_weights = self.delta_embedding.weight.clone().to(self.delta_embedding.weight.device)
+            token_norm = torch.norm(new_embeddings_weights, p=2, dim=1)
+
+            projection_mask = token_norm > 0
+            if torch.any(projection_mask):
+                epsilon = self.get_epsilon().to(self.delta_embedding.weight.device)
+                new_embeddings_weights[projection_mask] *= (
+                    epsilon[projection_mask] / (token_norm[projection_mask].clamp(min=epsilon[projection_mask]))
+                ).view(-1, 1)
+            return new_embeddings_weights
+
+    @staticmethod
+    def calculate_loss(base_model_output, labels, cpt_type_mask, config):
+        """
+        Computes the loss for CPT models with optional exponential decay.
+
+        Args:
+            base_model_output (ModelOutput):
+                Output from the base model containing logits.
+            labels (torch.Tensor):
+                Ground-truth labels for the input tokens.
+            cpt_type_mask (torch.Tensor):
+                Token type mask used for filtering valid loss terms.
+            config (Namespace):
+                Configuration object containing loss-related hyperparameters.
+
+        Returns:
+            ModelOutput:
+                The base model output with computed loss.
+        """
+
+        device = base_model_output.logits.device
+
+        lm_logits = base_model_output.logits
+        labels = labels.to(device)
+
+        # Shift logits and labels for token prediction
+        shift_logits = lm_logits[..., :-1, :].contiguous()
+        shift_labels = labels[..., 1:].contiguous()
+        shift_cpt_type_mask = cpt_type_mask[..., 1:].contiguous()
+
+        shift_labels_bool = (shift_labels.clone().detach() != -100).bool()
+        batch_size, seq_length, vocab_size = shift_logits.shape
+
+        # Compute cross-entropy loss
+        loss_fct = CrossEntropyLoss(reduction="none", ignore_index=-100)
+        loss = loss_fct(
+            shift_logits.view(batch_size * seq_length, vocab_size), shift_labels.view(batch_size * seq_length)
+        )
+        loss = loss.view(batch_size, seq_length)
+        # Apply exponential decay weights to the loss
+        shift_labels_weights = shift_labels_bool.clone().detach().float()
+
+        for i in range(batch_size):
+            idx_labels = (shift_cpt_type_mask[i] > 0) & (shift_cpt_type_mask[i] % 4 == 0)
+            labels_ids = shift_cpt_type_mask[i][idx_labels].unique()
+
+            exponential_decay = torch.ones_like(shift_cpt_type_mask[i]).to(device=device).float()
+            decay_value = 1
+            for label_mask_idx in torch.flip(labels_ids, [0]):
+                exponential_decay[shift_cpt_type_mask[i] == label_mask_idx] = decay_value
+                decay_value *= config.opt_loss_decay_factor
+            if config.opt_weighted_loss_type == "decay":
+                shift_labels_weights[i] *= exponential_decay
+
+        # Compute the weighted mean loss
+        loss = (loss[shift_labels_bool] * shift_labels_weights[shift_labels_bool]).mean()
+
+        base_model_output.loss = loss
+
+        return base_model_output
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..dfe3f5d89e36123eefef7fc6e675c6b80bd8d44c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import FourierFTConfig
+from .layer import FourierFTLayer, FourierFTLinear
+from .model import FourierFTModel
+
+
+__all__ = ["FourierFTConfig", "FourierFTLayer", "FourierFTLinear", "FourierFTModel"]
+
+register_peft_method(name="fourierft", model_cls=FourierFTModel, config_cls=FourierFTConfig)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..b8e354a207f4b2af6fad1c89017d6c889f47bf39
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/config.py
@@ -0,0 +1,205 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class FourierFTConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`FourierFTModel`].
+
+    Args:
+        n_frequency (`int`):
+            Num of learnable frequencies for the Discrete Fourier Transform. 'n_frequency' is an integer that is
+            greater than 0 and less than or equal to d^2 (assuming the weight W has dimensions of d by d).
+            Additionally, it is the number of trainable parameters required to update each delta W weight.
+            'n_frequency' will affect the performance and efficiency for PEFT. Specifically, it has little impact on
+            training speed, but higher values of it (typically) result in larger GPU memory costs and better accuracy.
+            With the same `target_modules`, the number of parameters of LoRA is (2*d*r/n_frequency) times that of
+            FourierFT. The following examples of settings regarding 'n_frequency' can be used as reference for users.
+            For NLU tasks with the RoBERTa-large model, adopting 'n_frequency': 1000 can almost achieve similar results
+            as 'r': 8 in LoRA. At this time, the number of parameters of LoRA is about 16 times that of FourierFT. For
+            image classification tasks with Vit-large models, adopting 'n_frequency': 3000 can almost achieve similar
+            results as 'r': 16 in LoRA, where the number of parameters of LoRA is about 11 times that of FourierFT.
+        scaling (`float`):
+            The scaling value for the delta W matrix. This is an important hyperparameter used for scaling, similar to
+            the 'lora_alpha' parameter in the LoRA method. 'scaling' can be determined during the hyperparameter search
+            process. However, if users want to skip this process, one can refer to the settings in the following
+            scenarios. This parameter can be set to 100.0 or 150.0 for both RoBERTa-base and RoBERTa-large models
+            across all NLU (GLUE) tasks. This parameter can be set to 300.0 for both LLaMA family models for all
+            instruction tuning. This parameter can be set to 300.0 for both ViT-base and ViT-large models across all
+            image classification tasks.
+        random_loc_seed (`int`):
+            Seed for the random location of the frequencies, i.e., the spectral entry matrix.
+        target_modules (`Union[list[str],str]`):
+            List of module names or regex expression of the module names to replace with FourierFT. For example, ['q',
+            'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$'. Only linear layers are supported.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        fan_in_fan_out (`bool`):
+            Set this to True if the layer to replace stores weight like (fan_in, fan_out).
+        bias (`str`):
+            Bias type for FourierFT. Can be 'none', 'all' or 'fourier_only'.
+        modules_to_save (`list[str]`):
+            List of modules apart from FourierFT layers to be set as trainable and saved in the final checkpoint. For
+            example, in Sequence Classification or Token Classification tasks, the final layer `classifier/score` are
+            randomly initialized and as such need to be trainable and saved.
+        layers_to_transform (`Union[list[int],int]`):
+            The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes
+            that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at
+            this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is
+            not in the common layers pattern. This should target the `nn.ModuleList` of the model, which is often
+            called `'layers'` or `'h'`.
+        n_frequency_pattern (`dict`):
+            The mapping from layer names or regexp expression to n_frequency which are different from the default
+            specified. For example, `{model.decoder.layers.0.encoder_attn.k_proj: 1000`}.
+        init_weights (`bool`):
+            The initialization of the Fourier weights. Set this to False if the spectrum are initialized to a standard
+            normal distribution. Set this to True if the spectrum are initialized to zeros.
+    """
+
+    n_frequency: int = field(
+        default=1000,
+        metadata={
+            "help": (
+                "Num of learnable frequencies for the Discrete Fourier Transform. 'n_frequency' is an integer that is"
+                "greater than 0 and less than or equal to d^2 (assuming the weight W has dimensions of d by d)."
+                "Additionally, it is the number of trainable parameters required to update each delta W weight."
+                "'n_frequency' will affect the performance and efficiency for PEFT. Specifically, it has little impact on"
+                "training speed, but higher values of it (typically) result in larger GPU memory costs and better accuracy."
+                "With the same `target_modules`, the number of parameters of LoRA is (2*d*r/n_frequency) times that of FourierFT."
+                "The following examples of settings regarding 'n_frequency' can be used as reference for users. For NLU"
+                "tasks with the RoBERTa-large model, adopting 'n_frequency': 1000 can almost achieve similar results as"
+                "'r': 8 in LoRA. At this time, the number of parameters of LoRA is about 16 times that of FourierFT."
+                "For image classification tasks with Vit-large models, adopting 'n_frequency': 3000 can almost achieve"
+                "similar results as 'r': 16 in LoRA, where the number of parameters of LoRA is about 11 times that of FourierFT."
+            )
+        },
+    )
+    scaling: float = field(
+        default=150.0,
+        metadata={
+            "help": (
+                "The scaling value for the delta W matrix. This is an important hyperparameter used for scaling, similar to the"
+                "'lora_alpha' parameter in the LoRA method. 'scaling' can be determined during the hyperparameter search process."
+                "However, if users want to skip this process, one can refer to the settings in the following scenarios."
+                "This parameter can be set to 100.0 or 150.0 for both RoBERTa-base and RoBERTa-large models across all NLU (GLUE) tasks."
+                "This parameter can be set to 300.0 for both LLaMA family models for all instruction tuning."
+                "This parameter can be set to 300.0 for both ViT-base and ViT-large models across all image classification tasks."
+            )
+        },
+    )
+    random_loc_seed: Optional[int] = field(
+        default=777, metadata={"help": "Seed for the random location of the frequencies."}
+    )
+    fan_in_fan_out: bool = field(
+        default=False,
+        metadata={"help": "Set this to True if the layer to replace stores weight like (fan_in, fan_out)"},
+    )
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of module names or regex expression of the module names to replace with FourierFT."
+                "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$'. "
+                "Only linear layers are supported."
+            )
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from fourierft."},
+    )
+    bias: str = field(
+        default="none", metadata={"help": "Bias type for FourierFT. Can be 'none', 'all' or 'fourier_only'."}
+    )
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of modules apart from FourierFT layers to be set as trainable and saved in the final checkpoint. For"
+                " example, in Sequence Classification or Token Classification tasks, the final layer"
+                " `classifier/score` are randomly initialized and as such need to be trainable and saved."
+            )
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers"
+                " indexes that are specified inside this list. If a single integer is passed, PEFT will transform only"
+                " the layer at this index."
+            )
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer"
+                " pattern is not in the common layers pattern. This should target the `nn.ModuleList` of the "
+                "model, which is often called `'layers'` or `'h'`."
+            )
+        },
+    )
+    n_frequency_pattern: Optional[dict] = field(
+        default_factory=dict,
+        metadata={
+            "help": (
+                "The mapping from layer names or regexp expression to n_frequency which are different from the default specified."
+                "For example, `{model.decoder.layers.0.encoder_attn.k_proj: 500`}."
+            )
+        },
+    )
+    init_weights: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "The initialization of the Fourier weights. Set this to False if the spectrum should be initialized to a standard normal distribution."
+                "Set this to True if the spectrum should be initialized to zeros."
+            )
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.FOURIERFT
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # if target_modules is a regex expression, then layers_to_transform should be None
+        if isinstance(self.target_modules, str) and self.layers_to_transform is not None:
+            raise ValueError("`layers_to_transform` cannot be used when `target_modules` is a str.")
+
+        # if target_modules is a regex expression, then layers_pattern should be None
+        if isinstance(self.target_modules, str) and self.layers_pattern is not None:
+            raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..a8f615a989de08fd71d69d65dbb71913026166f4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/layer.py
@@ -0,0 +1,190 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from typing import Any, List, Optional, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+
+class FourierFTLayer(BaseTunerLayer):
+    # All names of layers that may contain (trainable) adapter weights
+    adapter_layer_names = ("fourierft_spectrum",)
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("fourierft_n_frequency", "fourierft_scaling", "fourierft_random_loc_seed")
+
+    def __init__(self, base_layer: nn.Module, **kwargs) -> None:
+        self.base_layer = base_layer
+        self.fourierft_n_frequency = {}
+        self.fourierft_scaling = {}
+        self.fourierft_spectrum = nn.ParameterDict({})
+        self.indices = {}
+        self.fourierft_random_loc_seed = {}
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+        self.kwargs = kwargs
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            self.in_features, self.out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, Conv1D):
+            self.in_features, self.out_features = (
+                base_layer.weight.ds_shape if hasattr(base_layer.weight, "ds_shape") else base_layer.weight.shape
+            )
+        else:
+            raise ValueError(f"Unsupported layer type {type(base_layer)}")
+
+    def update_layer(self, adapter_name, n_frequency, scaling, init_weights, random_loc_seed):
+        if n_frequency <= 0:
+            raise ValueError(f"`n_frequency` should be a positive integer value but the value passed is {n_frequency}")
+        if n_frequency > self.in_features * self.out_features:
+            raise ValueError(
+                f"`n_frequency` should be less than or equal to the product of the input and output dimensions "
+                f"but the value passed is {n_frequency} and the product is {self.in_features * self.out_features}"
+            )
+        self.fourierft_n_frequency[adapter_name] = n_frequency
+        self.fourierft_random_loc_seed[adapter_name] = random_loc_seed
+        self.indices[adapter_name] = torch.randperm(
+            self.out_features * self.in_features,
+            generator=torch.Generator().manual_seed(self.fourierft_random_loc_seed[adapter_name]),
+        )[:n_frequency]
+        self.indices[adapter_name] = torch.stack(
+            [self.indices[adapter_name] // self.in_features, self.indices[adapter_name] % self.in_features], dim=0
+        )
+        self.fourierft_scaling[adapter_name] = scaling
+        # Actual trainable parameters
+        self.fourierft_spectrum[adapter_name] = nn.Parameter(torch.randn(n_frequency), requires_grad=True)
+
+        if init_weights:
+            self.reset_fourier_parameters(adapter_name)
+
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    @torch.no_grad()
+    def reset_fourier_parameters(self, adapter_name):
+        if adapter_name in self.fourierft_spectrum.keys():
+            nn.init.zeros_(self.fourierft_spectrum[adapter_name])
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        spectrum = self.fourierft_spectrum[adapter]
+        indices = self.indices[adapter].to(spectrum.device)
+        dense_spectrum = torch.zeros(self.out_features, self.in_features, device=spectrum.device, dtype=spectrum.dtype)
+        dense_spectrum[indices[0, :], indices[1, :]] = spectrum
+        delta_weight = torch.fft.ifft2(dense_spectrum).real * self.fourierft_scaling[adapter]
+        return delta_weight
+
+
+class FourierFTLinear(nn.Module, FourierFTLayer):
+    # FourierFT implemented in a dense layer
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        n_frequency: int = 1000,
+        scaling: float = 150.0,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        init_weights: Union[bool, str] = False,
+        random_loc_seed: int = 777,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        FourierFTLayer.__init__(self, base_layer, **kwargs)
+        self.fan_in_fan_out = fan_in_fan_out
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, n_frequency, scaling, init_weights, random_loc_seed)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.fourierft_spectrum.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    orig_weights += self.get_delta_weight(active_adapter)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights
+                else:
+                    base_layer.weight.data += self.get_delta_weight(active_adapter)
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.fourierft_spectrum.keys():
+                self.get_base_layer().weight.data -= self.get_delta_weight(active_adapter)
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        return super().get_delta_weight(adapter)
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.fourierft_spectrum.keys():
+                    continue
+
+                delta_w = self.get_delta_weight(active_adapter)
+                x = x.to(delta_w.dtype)
+                result = result + F.linear(x, delta_w)
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "fourierft." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..711c8ffaa2cc4db8d720c618f613814d0fa7714d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/fourierft/model.py
@@ -0,0 +1,349 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import re
+import warnings
+from dataclasses import asdict
+from enum import Enum
+from itertools import chain
+from typing import Optional
+
+import torch
+from tqdm import tqdm
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    _get_submodules,
+)
+
+from .config import FourierFTConfig
+from .layer import FourierFTLayer, FourierFTLinear
+
+
+class FourierFTModel(BaseTuner):
+    """
+    Creates FourierFT model from a pretrained transformers model.
+
+    The method is described in detail in https://arxiv.org/abs/2405.03003.
+
+    Args:
+        model ([`torch.nn.Module`]): The model to be adapted.
+        config ([`FourierFTConfig`]): The configuration of the FourierFT model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The FourierFT model.
+
+    **Attributes**:
+        - **model** ([`~transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`FourierFTConfig`]): The configuration of the Fourier model.
+    """
+
+    prefix: str = "fourierft_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False) -> None:
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def _check_new_adapter_config(self, config: FourierFTConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(fourierft_config, key):
+        return check_target_module_exists(fourierft_config, key)
+
+    def _create_and_replace(
+        self,
+        fourierft_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+        **optional_kwargs,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+        # Regexp matching - Find key which matches current target_name in patterns provided
+        pattern_keys = list(chain(fourierft_config.n_frequency_pattern.keys()))
+        target_name_key = next(filter(lambda key: re.match(rf".*\.{key}$", current_key), pattern_keys), current_key)
+
+        n_frequency = fourierft_config.n_frequency_pattern.get(target_name_key, fourierft_config.n_frequency)
+        scaling = fourierft_config.scaling
+        random_loc_seed = fourierft_config.random_loc_seed
+        bias = hasattr(target, "bias") and target.bias is not None
+        kwargs = {
+            "n_frequency": n_frequency,
+            "scaling": scaling,
+            "fan_in_fan_out": fourierft_config.fan_in_fan_out,
+            "init_weights": fourierft_config.init_weights,
+            "random_loc_seed": fourierft_config.random_loc_seed,
+        }
+        kwargs["bias"] = bias
+        if isinstance(target, FourierFTLayer):
+            target.update_layer(
+                adapter_name,
+                n_frequency,
+                scaling,
+                fourierft_config.init_weights,
+                random_loc_seed,
+            )
+        else:
+            new_module = self._create_new_module(fourierft_config, adapter_name, target, **kwargs)
+            if adapter_name != self.active_adapter:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if "fourierft_" in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: torch.nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "fourier_only":
+                for m in model.modules():
+                    if isinstance(m, FourierFTLayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(fourierft_config, adapter_name, target, **kwargs):
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Linear):
+            if kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                    "Setting fan_in_fan_out to False."
+                )
+                kwargs["fan_in_fan_out"] = fourierft_config.fan_in_fan_out = False
+        elif isinstance(target_base_layer, Conv1D):
+            kwargs["is_target_conv_1d_layer"] = True
+            if not kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to False but the target module is `Conv1D`. Setting fan_in_fan_out to True."
+                )
+                kwargs["fan_in_fan_out"] = fourierft_config.fan_in_fan_out = True
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. Currently, only the following modules are supported: "
+                "`torch.nn.Linear`."
+            )
+
+        new_module = FourierFTLinear(target, adapter_name, **kwargs)
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled: bool = True) -> None:
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self) -> None:
+        """Enable all adapters.
+
+        Call this if you have previously disabled all adapters and want to re-enable them.
+        """
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self) -> None:
+        """Disable all adapters.
+
+        When disabling all adapters, the model output corresponds to the output of the base model.
+        """
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name: str | list[str]) -> None:
+        """Set the active adapter(s).
+
+        Args:
+            adapter_name (`str` or `list[str]`): Name of the adapter(s) to be activated.
+        """
+        for module in self.model.modules():
+            if isinstance(module, FourierFTLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                setattr(parent, target_name, target.modules_to_save[target.active_adapter])
+
+        return self.model
+
+    def delete_adapter(self, adapter_name: str):
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        # we cannot use self.prefix as we want to include non-trainable fourierft parameters
+        key_list = [key for key, _ in self.model.named_modules() if "fourierft" not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, FourierFTLayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapter[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the Fourier layers into the base model. This is needed if someone wants to use the base
+        model as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the Fourier modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f5f6a54435d0fcaa1bd275c623168b5491f2d9e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import HRAConfig
+from .layer import HRAConv2d, HRALayer, HRALinear
+from .model import HRAModel
+
+
+__all__ = ["HRAConfig", "HRAConv2d", "HRALayer", "HRALinear", "HRAModel"]
+
+register_peft_method(name="hra", config_cls=HRAConfig, model_cls=HRAModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..9e6d87cc17c3ba003eac963467bb1253725ebe10
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/config.py
@@ -0,0 +1,133 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class HRAConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`HRAModel`].
+
+    Args:
+        r (`int`):
+            The rank of HRA across different layers. It is best to set 'r' to an even number; otherwise, the default
+            initialization method will not work.
+        apply_GS (`bool`):
+            Whether to apply Gram-Schmidt orthogonalization.
+        target_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear modules are chosen, excluding
+            the output layer. If this is not specified, modules will be chosen according to the model architecture. If
+            the architecture is not known, an error will be raised -- in this case, you should specify the target
+            modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        init_weights (`bool`):
+            Whether to perform initialization of HRA weights.
+        layers_to_transform (`Union[List[int], int]`):
+            The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
+            that are specified in this list. If a single integer is passed, it will apply the transformations on the
+            layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`. This should target the
+            `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`.
+        modules_to_save (`List[str]`):
+            List of modules apart from adapter layers to be set as trainable and saved in the final checkpoint.
+    """
+
+    r: int = field(
+        default=8,
+        metadata={
+            "help": "The rank of HRA across different layers.",
+            "note": "It is best to set 'r' to an even number; otherwise, the default initialization method will not work.",
+        },
+    )
+    apply_GS: bool = field(
+        default=False,
+        metadata={"help": "Whether to apply Gram-Schmidt orthogonalization or not."},
+    )
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or regex expression of the module names to replace with HRA.",
+            "example": "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$' ",
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from HRA."},
+    )
+    init_weights: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the HRA layers with their default initialization. Don't change "
+                "this setting, except if you know exactly what you're doing."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index."
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern. "
+            "This should target the `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`."
+        },
+    )
+    bias: str = field(default="none", metadata={"help": "Bias type for HRA. Can be 'none', 'all' or 'hra_only'"})
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from HRA layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.HRA
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # if target_modules is a regex expression, then layers_to_transform should be None
+        if isinstance(self.target_modules, str) and self.layers_to_transform is not None:
+            raise ValueError("`layers_to_transform` cannot be used when `target_modules` is a str.")
+
+        # if target_modules is a regex expression, then layers_pattern should be None
+        if isinstance(self.target_modules, str) and self.layers_pattern is not None:
+            raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
+
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..2494510c60ad7d5491993612ede1bd6e55f442c7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/layer.py
@@ -0,0 +1,440 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import math
+import warnings
+from typing import Any, List, Optional, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+
+class HRALayer(BaseTunerLayer):
+    # All names of layers that may contain (trainable) adapter weights
+    adapter_layer_names = ("hra_u",)
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("hra_r", "hra_apply_GS")
+
+    def __init__(self, base_layer: nn.Module, **kwargs) -> None:
+        self.base_layer = base_layer
+        self.hra_r = {}
+        self.hra_apply_GS = {}
+        self.hra_u = nn.ParameterDict({})
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+        self.kwargs = kwargs
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            self.in_features, self.out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, nn.Conv2d):
+            self.in_features, self.out_features = base_layer.in_channels, base_layer.out_channels
+        else:
+            raise ValueError(f"Unsupported layer type {type(base_layer)}")
+
+    def update_layer(
+        self,
+        adapter_name: str,
+        r: int,
+        apply_GS: bool,
+        init_weights: bool,
+        **kwargs,
+    ) -> None:
+        """Internal function to create hra adapter
+
+        Args:
+            adapter_name (`str`): Name for the adapter to add.
+            r (`int`): Rank for the added adapter.
+            init_weights (`bool`): Whether to initialize weights.
+            apply_GS (`bool`): Whether to apply Gram-Schmidt orthogonalization or not.
+        """
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+
+        self.hra_r[adapter_name] = r
+        self.hra_apply_GS[adapter_name] = apply_GS
+
+        # Determine shape of HRA weights
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            self.hra_u[adapter_name] = nn.Parameter(torch.empty(self.in_features, r), requires_grad=True)
+        elif isinstance(base_layer, nn.Conv2d):
+            self.hra_u[adapter_name] = nn.Parameter(
+                torch.empty(self.in_features * base_layer.kernel_size[0] * base_layer.kernel_size[0], r),
+                requires_grad=True,
+            )
+        else:
+            raise TypeError(f"HRA is not implemented for base layers of type {type(base_layer).__name__}")
+
+        # Initialize weights
+        if init_weights:
+            self.reset_hra_parameters(adapter_name)
+        else:
+            self.reset_hra_parameters_random(adapter_name)
+
+        # Move new weights to device
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_hra_parameters(self, adapter_name: str):
+        if self.hra_r[adapter_name] % 2 != 0:
+            warnings.warn("The symmetric initialization can NOT be performed when r is odd!")
+            nn.init.kaiming_uniform_(self.hra_u[adapter_name], a=math.sqrt(5))
+        else:
+            shape = self.hra_u[adapter_name].shape
+            half_u = torch.zeros(shape[0], shape[1] // 2)
+            nn.init.kaiming_uniform_(half_u, a=math.sqrt(5))
+            self.hra_u[adapter_name] = nn.Parameter(torch.repeat_interleave(half_u, 2, dim=1))
+
+    def reset_hra_parameters_random(self, adapter_name: str):
+        nn.init.kaiming_uniform_(self.hra_u[adapter_name], a=math.sqrt(5))
+
+    def scale_layer(self, scale: float) -> None:
+        if scale == 1:
+            return
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.hra_u.keys():
+                continue
+
+            warnings.warn("Scaling operation for HRA not supported! Automatically set scale to 1.")
+
+    def unscale_layer(self, scale=None) -> None:
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.hra_u.keys():
+                continue
+
+            warnings.warn("Unscaling operation for HRA not supported! Keeping scale at 1.")
+
+
+class HRALinear(nn.Module, HRALayer):
+    """
+    HRA implemented in a dense layer.
+    """
+
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 0,
+        apply_GS: bool = False,
+        init_weights: Union[bool, str] = True,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        HRALayer.__init__(self, base_layer, **kwargs)
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, apply_GS, init_weights, **kwargs)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If `True`, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If `None`, all active adapters will be merged.
+                Defaults to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.hra_u.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weight = base_layer.weight.data.clone()
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    orig_weight = torch.mm(orig_weight, delta_weight)
+
+                    if not torch.isfinite(orig_weight).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    self.base_layer.weight.data = orig_weight
+                else:
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    self.base_layer.weight.data = torch.mm(self.base_layer.weight.data, delta_weight)
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.hra_u.keys():
+                orig_weight = self.get_base_layer().weight.data.clone()
+                delta_weight = self.get_delta_weight(active_adapter, reverse=True)
+                self.get_base_layer().weight.data = torch.mm(orig_weight, delta_weight)
+
+    def get_delta_weight(self, adapter_name: str, reverse: bool = False) -> torch.Tensor:
+        rank = self.hra_r[adapter_name]
+        apply_GS = self.hra_apply_GS[adapter_name]
+        opt_u = self.hra_u[adapter_name]
+        shape = opt_u.shape
+
+        if apply_GS:
+            weight = [(opt_u[:, 0] / opt_u[:, 0].norm()).view(-1, 1)]
+            for i in range(1, rank):
+                ui = opt_u[:, i].view(-1, 1)
+                for j in range(i):
+                    ui = ui - (weight[j].t() @ ui) * weight[j]
+                weight.append((ui / ui.norm()).view(-1, 1))
+            weight = torch.cat(weight, dim=1)
+            weight = torch.eye(shape[0], device=opt_u.device, dtype=opt_u.dtype) - 2 * weight @ weight.t()
+
+        else:
+            opt_u = opt_u / opt_u.norm(dim=0)
+            weight = torch.eye(shape[0], device=opt_u.device, dtype=opt_u.dtype)
+            if reverse:
+                indices = range(rank - 1, -1, -1)
+            else:
+                indices = range(rank)
+
+            for i in indices:
+                ui = opt_u[:, i].view(-1, 1)
+                weight = weight - 2 * weight @ ui @ ui.t()
+
+        return weight
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            new_weight = torch.eye(self.in_features, device=x.device)
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.hra_u.keys():
+                    continue
+                delta_weight = self.get_delta_weight(active_adapter)
+                new_weight = torch.mm(new_weight, delta_weight)
+
+            x = x.to(self.get_base_layer().weight.data.dtype)
+            orig_weight = self.get_base_layer().weight.data
+            new_weight = torch.mm(orig_weight, new_weight)
+
+            result = F.linear(input=x, weight=new_weight, bias=self.base_layer.bias)
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "hra." + rep
+
+
+class HRAConv2d(nn.Module, HRALayer):
+    """HRA implemented in Conv2d layer"""
+
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 0,
+        apply_GS: bool = False,
+        init_weights: Union[bool, str] = True,
+        **kwargs,
+    ):
+        super().__init__()
+        HRALayer.__init__(self, base_layer)
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, apply_GS, init_weights, **kwargs)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If `True`, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If `None`, all active adapters will be merged.
+                Defaults to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.hra_u.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weight = base_layer.weight.data.clone()
+                    orig_weight = orig_weight.view(
+                        self.out_features,
+                        self.in_features * self.base_layer.kernel_size[0] * self.base_layer.kernel_size[0],
+                    )
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    orig_weight = torch.mm(orig_weight, delta_weight)
+                    orig_weight = orig_weight.view(
+                        self.out_features,
+                        self.in_features,
+                        self.base_layer.kernel_size[0],
+                        self.base_layer.kernel_size[0],
+                    )
+
+                    if not torch.isfinite(orig_weight).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    self.base_layer.weight.data = orig_weight
+                else:
+                    orig_weight = base_layer.weight.data
+                    orig_weight = orig_weight.view(
+                        self.out_features,
+                        self.in_features * self.base_layer.kernel_size[0] * self.base_layer.kernel_size[0],
+                    )
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    orig_weight = torch.mm(orig_weight, delta_weight)
+                    orig_weight = orig_weight.view(
+                        self.out_features,
+                        self.in_features,
+                        self.base_layer.kernel_size[0],
+                        self.base_layer.kernel_size[0],
+                    )
+
+                    self.base_layer.weight.data = orig_weight
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.hra_u.keys():
+                orig_weight = self.get_base_layer().weight.data.clone()
+                orig_weight = orig_weight.view(
+                    self.out_features,
+                    self.in_features * self.base_layer.kernel_size[0] * self.base_layer.kernel_size[0],
+                )
+                delta_weight = self.get_delta_weight(active_adapter, reverse=True)
+                orig_weight = torch.mm(orig_weight, delta_weight)
+                orig_weight = orig_weight.view(
+                    self.out_features, self.in_features, self.base_layer.kernel_size[0], self.base_layer.kernel_size[0]
+                )
+
+                self.get_base_layer().weight.data = orig_weight
+
+    def get_delta_weight(self, adapter_name: str, reverse: bool = False) -> torch.Tensor:
+        rank = self.hra_r[adapter_name]
+        apply_GS = self.hra_apply_GS[adapter_name]
+        opt_u = self.hra_u[adapter_name]
+        shape = opt_u.shape
+
+        if apply_GS:
+            weight = [(opt_u[:, 0] / opt_u[:, 0].norm()).view(-1, 1)]
+            for i in range(1, rank):
+                ui = opt_u[:, i].view(-1, 1)
+                for j in range(i):
+                    ui = ui - (weight[j].t() @ ui) * weight[j]
+                weight.append((ui / ui.norm()).view(-1, 1))
+            weight = torch.cat(weight, dim=1)
+            weight = torch.eye(shape[0], device=opt_u.device, dtype=opt_u.dtype) - 2 * weight @ weight.t()
+
+        else:
+            opt_u = opt_u / opt_u.norm(dim=0)
+            weight = torch.eye(shape[0], device=opt_u.device, dtype=opt_u.dtype)
+            if reverse:
+                indices = range(rank - 1, -1, -1)
+            else:
+                indices = range(rank)
+
+            for i in indices:
+                ui = opt_u[:, i].view(-1, 1)
+                weight = weight - 2 * weight @ ui @ ui.t()
+
+        return weight
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            new_weight = torch.eye(
+                self.in_features * self.base_layer.kernel_size[0] * self.base_layer.kernel_size[0],
+                device=x.device,
+                dtype=previous_dtype,
+            )
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.hra_u.keys():
+                    continue
+                delta_weight = self.get_delta_weight(active_adapter)
+                new_weight = torch.mm(new_weight, delta_weight)
+
+            x = x.to(self.base_layer.weight.data.dtype)
+
+            orig_weight = self.base_layer.weight.data
+            orig_weight = orig_weight.view(
+                self.out_features,
+                self.in_features * self.base_layer.kernel_size[0] * self.base_layer.kernel_size[0],
+            )
+            new_weight = torch.mm(orig_weight, new_weight)
+            new_weight = new_weight.view(
+                self.out_features,
+                self.in_features,
+                self.base_layer.kernel_size[0],
+                self.base_layer.kernel_size[0],
+            )
+
+            result = F.conv2d(
+                input=x,
+                weight=new_weight,
+                bias=self.base_layer.bias,
+                padding=self.base_layer.padding[0],
+                stride=self.base_layer.stride[0],
+            )
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "hra." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..1bfa0f12060542da5801b95cb14268eaaa91105c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/hra/model.py
@@ -0,0 +1,341 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from dataclasses import asdict
+from enum import Enum
+from typing import List, Optional
+
+import torch
+from torch import nn
+from tqdm import tqdm
+
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    _get_submodules,
+)
+
+from .config import HRAConfig
+from .layer import HRAConv2d, HRALayer, HRALinear
+
+
+class HRAModel(BaseTuner):
+    """
+    Creates Householder reflection adaptation (HRA) model from a pretrained model. The method is described in
+    https://arxiv.org/abs/2405.17484
+
+    Args:
+        model (`torch.nn.Module`): The model to which the adapter tuner layers will be attached.
+        config ([`HRAConfig`]): The configuration of the HRA model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The HRA model.
+
+    Example:
+        ```py
+        >>> from diffusers import StableDiffusionPipeline
+        >>> from peft import HRAModel, HRAConfig
+
+        >>> config_te = HRAConfig(
+        ...     r=8,
+        ...     target_modules=["k_proj", "q_proj", "v_proj", "out_proj", "fc1", "fc2"],
+        ...     init_weights=True,
+        ... )
+        >>> config_unet = HRAConfig(
+        ...     r=8,
+        ...     target_modules=[
+        ...         "proj_in",
+        ...         "proj_out",
+        ...         "to_k",
+        ...         "to_q",
+        ...         "to_v",
+        ...         "to_out.0",
+        ...         "ff.net.0.proj",
+        ...         "ff.net.2",
+        ...     ],
+        ...     init_weights=True,
+        ... )
+
+        >>> model = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+        >>> model.text_encoder = HRAModel(model.text_encoder, config_te, "default")
+        >>> model.unet = HRAModel(model.unet, config_unet, "default")
+        ```
+
+    **Attributes**:
+        - **model** ([`~torch.nn.Module`]) -- The model to be adapted.
+        - **peft_config** ([`HRAConfig`]): The configuration of the HRA model.
+    """
+
+    prefix: str = "hra_"
+
+    def _check_new_adapter_config(self, config: HRAConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(hra_config, key):
+        return check_target_module_exists(hra_config, key)
+
+    def _create_and_replace(
+        self,
+        hra_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+        **optional_kwargs,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+
+        bias = hasattr(target, "bias") and target.bias is not None
+        kwargs = {
+            "r": hra_config.r,
+            "apply_GS": hra_config.apply_GS,
+            "init_weights": hra_config.init_weights,
+        }
+        kwargs["bias"] = bias
+
+        # If it is not a HRALayer, create a new module, else update it with new adapters
+        if not isinstance(target, HRALayer):
+            new_module = self._create_new_module(hra_config, adapter_name, target, **kwargs)
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+        else:
+            target.update_layer(
+                adapter_name,
+                r=hra_config.r,
+                apply_GS=hra_config.apply_GS,
+                init_weights=hra_config.init_weights,
+            )
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if self.prefix in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "hra_only":
+                for name, m in model.named_modules():
+                    if isinstance(m, HRALayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(hra_config, adapter_name, target, **kwargs):
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Linear):
+            new_module = HRALinear(target, adapter_name, **kwargs)
+        elif isinstance(target_base_layer, torch.nn.Conv2d):
+            new_module = HRAConv2d(target, adapter_name, **kwargs)
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. "
+                "Currently, only `torch.nn.Linear` and `torch.nn.Conv2d` are supported."
+            )
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "base_model":
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self):
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self):
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name):
+        for module in self.model.modules():
+            if isinstance(module, HRALayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[List[str]] = None,
+    ):
+        self._unloading_checks(adapter_names)
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                setattr(parent, target_name, target.modules_to_save[target.active_adapter])
+
+        return self.model
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, HRALayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[List[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the HRA layers into the base model. This is needed if someone wants to use the base model as
+        a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the hra modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..21cab4d6d8a6437766f395e90079ce6ecd9e4f26
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/__init__.py
@@ -0,0 +1,39 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.utils import register_peft_method
+
+from .config import IA3Config
+from .layer import Conv2d, Conv3d, IA3Layer, Linear
+from .model import IA3Model
+
+
+__all__ = ["Conv2d", "Conv3d", "IA3Config", "IA3Layer", "IA3Model", "Linear"]
+
+register_peft_method(name="ia3", config_cls=IA3Config, model_cls=IA3Model, is_mixed_compatible=True)
+
+
+def __getattr__(name):
+    if (name == "Linear8bitLt") and is_bnb_available():
+        from .bnb import Linear8bitLt
+
+        return Linear8bitLt
+
+    if (name == "Linear4bit") and is_bnb_4bit_available():
+        from .bnb import Linear4bit
+
+        return Linear4bit
+
+    raise AttributeError(f"module {__name__} has no attribute {name}")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/bnb.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/bnb.py
new file mode 100644
index 0000000000000000000000000000000000000000..628e3ce7229528a0b3157da349b2b34153573c51
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/bnb.py
@@ -0,0 +1,129 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Any
+
+import torch
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+
+from .layer import IA3Layer
+
+
+if is_bnb_available():
+
+    class Linear8bitLt(torch.nn.Module, IA3Layer):
+        # (IA)^3 implemented in a dense layer
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            is_feedforward: bool,
+            init_ia3_weights: bool = True,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            IA3Layer.__init__(self, base_layer, is_feedforward=is_feedforward)
+
+            # Freezing the pre-trained weight matrix
+            self.get_base_layer().weight.requires_grad = False
+            self._active_adapter = adapter_name
+            self.update_layer(adapter_name, init_ia3_weights)
+
+        def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+            # note: no check for self.merged because merging is not supported (yet)
+            if self.disable_adapters:
+                return self.base_layer(x)
+
+            ia3_scaling = 1
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.ia3_l.keys():
+                    continue
+                ia3_scaling *= self.ia3_l[active_adapter].flatten()
+
+            requires_conversion = (not torch.is_autocast_enabled()) and (x.dtype != torch.float32)
+            if requires_conversion:
+                x = x.float()
+            if self.is_feedforward:
+                result = self.base_layer(x * ia3_scaling)
+                expected_dtype = result.dtype
+            else:
+                result = self.base_layer(x)
+                expected_dtype = result.dtype
+                result = result * ia3_scaling
+
+            if requires_conversion:
+                result = result.to(expected_dtype)
+
+            return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "ia3." + rep
+
+
+if is_bnb_4bit_available():
+
+    class Linear4bit(torch.nn.Module, IA3Layer):
+        # IA3 implemented in a dense layer
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            is_feedforward: bool,
+            init_ia3_weights: bool = True,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            IA3Layer.__init__(self, base_layer, is_feedforward=is_feedforward)
+
+            # Freezing the pre-trained weight matrix
+            self.get_base_layer().weight.requires_grad = False
+            self._active_adapter = adapter_name
+            self.update_layer(adapter_name, init_ia3_weights)
+
+        def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+            # note: no check for self.merged because merging is not supported (yet)
+            if self.disable_adapters:
+                return self.base_layer(x)
+
+            ia3_scaling = 1
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.ia3_l.keys():
+                    continue
+                ia3_scaling *= self.ia3_l[active_adapter].flatten()
+
+            requires_conversion = (not torch.is_autocast_enabled()) and (x.dtype != torch.float32)
+            if requires_conversion:
+                x = x.float()
+            if self.is_feedforward:
+                result = self.base_layer(x * ia3_scaling)
+                expected_dtype = result.dtype
+            else:
+                result = self.base_layer(x)
+                expected_dtype = result.dtype
+                result = result * ia3_scaling
+
+            result = result.clone()
+            # adalora.py and lora.py both suggest that this is necessary for 4-bit training on older versions of Pytorch.
+            # This has been duplicated here.
+
+            if requires_conversion:
+                result = result.to(expected_dtype)
+
+            return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "ia3." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..1c4161e5ed97998017b800535d4315c66c9d14cd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/config.py
@@ -0,0 +1,112 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class IA3Config(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`IA3Model`].
+
+    Args:
+        target_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear/Conv1D modules are chosen,
+            excluding the output layer. If this is not specified, modules will be chosen according to the model
+            architecture. If the architecture is not known, an error will be raised -- in this case, you should specify
+            the target modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        feedforward_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to be treated as feedforward modules, as in the original paper. These modules will
+            have (IA)³ vectors multiplied to the input, instead of the output. `feedforward_modules` must be a name or
+            a subset of names present in `target_modules`.
+        fan_in_fan_out (`bool`):
+            Set this to True if the layer to replace stores weight like (fan_in, fan_out). For example, gpt-2 uses
+            `Conv1D` which stores weights like (fan_in, fan_out) and hence this should be set to `True`.
+        modules_to_save (`Optional[List[str]]`):
+            List of modules apart from (IA)³ layers to be set as trainable and saved in the final checkpoint.
+        init_ia3_weights (`bool`):
+            Whether to initialize the vectors in the (IA)³ layers, defaults to `True`. Setting this to `False` is
+            discouraged.
+    """
+
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of module names or regex expression of the module names to replace with (IA)³."
+                "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$'."
+                "This can also be a wildcard 'all-linear' which matches all linear/Conv1D layers except the output layer."
+                "If not specified, modules will be chosen according to the model architecture, If the architecture is "
+                "not known, an error will be raised -- in this case, you should specify the target modules manually."
+            ),
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from (IA)³."},
+    )
+    feedforward_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or a regex expression of module names which are feedforward"
+            "For example, ['output.dense']"
+        },
+    )
+    fan_in_fan_out: bool = field(
+        default=False,
+        metadata={"help": "Set this to True if the layer to replace stores weight like (fan_in, fan_out)"},
+    )
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from (IA)^3 layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+    init_ia3_weights: bool = field(
+        default=True,
+        metadata={"help": "Whether to initialize the vectors in the (IA)^3 layers."},
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.IA3
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        self.feedforward_modules = (
+            set(self.feedforward_modules) if isinstance(self.feedforward_modules, list) else self.feedforward_modules
+        )
+
+        # check if feedforward_modules is a subset of target_modules. run the check only if both are sets
+        if isinstance(self.feedforward_modules, set) and isinstance(self.target_modules, set):
+            if not self.feedforward_modules.issubset(self.target_modules):
+                raise ValueError("`feedforward_modules` should be a subset of `target_modules`")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..e941089315e3f01f259fa8366791120db9a9daba
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/layer.py
@@ -0,0 +1,327 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from typing import Any, List, Optional
+
+import torch
+import torch.nn as nn
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+from peft.utils import transpose
+
+
+class IA3Layer(BaseTunerLayer):
+    # All names of layers that may contain adapter weights
+    adapter_layer_names = ("ia3_l",)
+
+    def __init__(self, base_layer: nn.Module, is_feedforward: bool, **kwargs) -> None:
+        self.base_layer = base_layer
+        self.ia3_l = nn.ParameterDict({})
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+        self.is_feedforward = is_feedforward
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, (nn.Conv2d, nn.Conv3d)):
+            in_features, out_features = base_layer.in_channels, base_layer.out_channels
+        elif isinstance(base_layer, nn.Embedding):
+            in_features, out_features = base_layer.num_embeddings, base_layer.embedding_dim
+        elif isinstance(base_layer, Conv1D):
+            in_features, out_features = (
+                base_layer.weight.ds_shape if hasattr(base_layer.weight, "ds_shape") else base_layer.weight.shape
+            )
+        else:
+            raise ValueError(f"Unsupported layer type {type(base_layer)}")
+        self.in_features = in_features
+        self.out_features = out_features
+
+    def update_layer(self, adapter_name, init_ia3_weights):
+        # This code works for linear layers, override for other layer types
+        # Actual trainable parameters
+        if self.is_feedforward:
+            weight = torch.randn((1, self.in_features))
+        else:
+            weight = torch.randn((self.out_features, 1))
+        self.ia3_l[adapter_name] = nn.Parameter(weight)
+        if init_ia3_weights:
+            self.reset_ia3_parameters(adapter_name)
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_ia3_parameters(self, adapter_name):
+        if adapter_name in self.ia3_l.keys():
+            # initialize learned vector with torch.ones
+            nn.init.constant_(self.ia3_l[adapter_name], 1.0)
+
+
+class Linear(nn.Module, IA3Layer):
+    # (IA)^3 implemented in a dense layer
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        is_feedforward: bool = False,  # Set to True if the layer is treated as a feedforward layer
+        is_target_conv_1d_layer: bool = False,  # whether target module is a conv1d layer. useful while unloading later
+        init_ia3_weights: bool = True,  # whether to initialize IA3 weights
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        IA3Layer.__init__(self, base_layer, is_feedforward=is_feedforward)
+        self.fan_in_fan_out = fan_in_fan_out
+        self.is_target_conv_1d_layer = is_target_conv_1d_layer
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, init_ia3_weights)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.ia3_l.keys():
+                base_layer = self.get_base_layer()
+                ia3_l = transpose(self.ia3_l[active_adapter].data, self.fan_in_fan_out)
+                orig_dtype = base_layer.weight.data.dtype
+                if safe_merge:
+                    orig_weights = base_layer.weight.data
+                    orig_weights = torch.mul(orig_weights, ia3_l)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+                    base_layer.weight.data = orig_weights.to(orig_dtype)
+                else:
+                    base_layer.weight.data = torch.mul(base_layer.weight.data, ia3_l).to(orig_dtype)
+
+                if not self.is_feedforward and (base_layer.bias is not None):
+                    scaling = self.ia3_l[active_adapter].reshape(base_layer.bias.shape)
+                    orig_dtype = base_layer.bias.data.dtype
+                    base_layer.bias.data = torch.mul(base_layer.bias.data, scaling.data).to(orig_dtype)
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+
+        warnings.warn("Unmerge result can be inaccurate for (IA)^3.")
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.ia3_l.keys():
+                base_layer = self.get_base_layer()
+                # Add tolerace to avoid division by zero
+                ia3_l = transpose(self.ia3_l[active_adapter].data, self.fan_in_fan_out) + 1e-8
+                orig_dtype = base_layer.weight.data.dtype
+                base_layer.weight.data = torch.div(base_layer.weight.data, ia3_l).to(orig_dtype)
+
+                if not self.is_feedforward and (base_layer.bias is not None):
+                    scaling = self.ia3_l[active_adapter].reshape(base_layer.bias.shape)
+                    orig_dtype = base_layer.bias.data.dtype
+                    base_layer.bias.data = torch.div(base_layer.bias.data, scaling.data + 1e-8).to(orig_dtype)
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        dtype = previous_dtype = x.dtype
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            ia3_scaling = 1
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.ia3_l.keys():
+                    continue
+                dtype = self.ia3_l[active_adapter].dtype
+                ia3_scaling *= self.ia3_l[active_adapter].flatten()
+
+            if self.is_feedforward:
+                x = x.to(dtype)
+                # TODO: weight.dtype can be != self.ia3_l[self.active_adapters].dtype
+                # e.g. bf16 vs fp32. Is that okay?
+                interm = (x * ia3_scaling).to(previous_dtype)
+                result = self.base_layer(interm, *args, **kwargs)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+                result_dtype = result.dtype
+                result = (result * ia3_scaling).to(result_dtype)
+
+        return result
+
+
+class _ConvNd(nn.Module, IA3Layer):
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        is_feedforward: bool = False,  # Set to True if the layer is treated as a feedforward layer
+        init_ia3_weights: bool = True,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        IA3Layer.__init__(self, base_layer, is_feedforward=is_feedforward)
+        self.fan_in_fan_out = fan_in_fan_out
+        self._active_adapter = adapter_name
+        self._kernel_dim = base_layer.weight.dim()
+
+        self.update_layer(adapter_name, init_ia3_weights)
+
+    def update_layer(self, adapter_name, init_ia3_weights):
+        # Actual trainable parameters
+        num_features = self.in_features if self.is_feedforward else self.out_features
+        weights_size = (1, num_features) + (1,) * (self._kernel_dim - 2)
+        weight = torch.randn(weights_size)
+        self.ia3_l[adapter_name] = nn.Parameter(weight)
+        if init_ia3_weights:
+            self.reset_ia3_parameters(adapter_name)
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.ia3_l.keys():
+                base_layer = self.get_base_layer()
+                ia3_scaling = self.ia3_l[active_adapter].data
+                if not self.is_feedforward:
+                    ia3_scaling = ia3_scaling.transpose(0, 1)
+
+                if safe_merge:
+                    output_weight = torch.mul(base_layer.weight.data, ia3_scaling).clone()
+
+                    if not torch.isfinite(output_weight).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = output_weight
+                else:
+                    base_layer.weight.data = torch.mul(base_layer.weight.data, ia3_scaling)
+
+                if not self.is_feedforward and (base_layer.bias is not None):
+                    scaling = self.ia3_l[active_adapter].reshape(base_layer.bias.shape)
+                    base_layer.bias.data = torch.mul(base_layer.bias.data, scaling.data)
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+
+        warnings.warn("Unmerge result can be inaccurate for (IA)^3.")
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.ia3_l.keys():
+                base_layer = self.get_base_layer()
+                # divide by (IA)^3 vector. Add tolerace to avoid division by zero
+                ia3_scaling = self.ia3_l[active_adapter].data
+                if not self.is_feedforward:
+                    ia3_scaling = ia3_scaling.transpose(0, 1)
+                base_layer.weight.data = torch.div(base_layer.weight.data, ia3_scaling + 1e-8)
+
+                if not self.is_feedforward and (base_layer.bias is not None):
+                    scaling = self.ia3_l[active_adapter].reshape(base_layer.bias.shape)
+                    base_layer.bias.data = torch.mul(base_layer.bias.data, scaling.data)
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        dtype = previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            ia3_scaling = 1
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.ia3_l.keys():
+                    continue
+                dtype = self.ia3_l[active_adapter].dtype
+                ia3_scaling *= self.ia3_l[active_adapter]
+
+            if self.is_feedforward:
+                x = x.to(dtype)
+                # TODO: weight.dtype can be != self.ia3_l[self.active_adapters].dtype
+                # e.g. bf16 vs fp32. Is that okay?
+                interm = (x * ia3_scaling).to(self.get_base_layer().weight.dtype)
+                result = self.base_layer(interm, *args, **kwargs)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+                result = result.to(dtype) * ia3_scaling
+
+        result = result.to(previous_dtype)
+        return result
+
+
+class Conv2d(_ConvNd):
+    # IA3 implemented in a 2D convolutional layer
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if not self._kernel_dim == 4:
+            raise ValueError(f"Conv2d layer kernel must have 4 dimensions, not {self._kernel_dim}")
+
+
+class Conv3d(_ConvNd):
+    # IA3 implemented in a 3D convolutional layer
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if not self._kernel_dim == 5:
+            raise ValueError(f"Conv2d layer kernel must have 5 dimensions, not {self._kernel_dim}")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..453b62f3a19d51526465869ecedecc05800ff40b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ia3/model.py
@@ -0,0 +1,496 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import re
+import warnings
+from dataclasses import asdict, replace
+from enum import Enum
+from typing import Optional
+
+import torch
+from torch import nn
+from transformers.pytorch_utils import Conv1D
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    _freeze_adapter,
+    _get_submodules,
+)
+
+from .layer import Conv2d, Conv3d, IA3Layer, Linear
+
+
+class IA3Model(BaseTuner):
+    """
+    Creates a Infused Adapter by Inhibiting and Amplifying Inner Activations ((IA)^3) model from a pretrained
+    transformers model. The method is described in detail in https://arxiv.org/abs/2205.05638
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): The model to be adapted.
+        config ([`IA3Config`]): The configuration of the (IA)^3 model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The (IA)^3 model.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForSeq2SeqLM, ia3Config
+        >>> from peft import IA3Model, IA3Config
+
+        >>> config = IA3Config(
+        ...     peft_type="IA3",
+        ...     task_type="SEQ_2_SEQ_LM",
+        ...     target_modules=["k", "v", "w0"],
+        ...     feedforward_modules=["w0"],
+        ... )
+
+        >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
+        >>> ia3_model = IA3Model(config, model)
+        ```
+
+    **Attributes**:
+        - **model** ([`~transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`ia3Config`]): The configuration of the (IA)^3 model.
+    """
+
+    prefix: str = "ia3_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False):
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    @staticmethod
+    def _create_new_module(ia3_config, adapter_name, target, **kwargs):
+        # avoid eager bnb import
+        if is_bnb_available():
+            import bitsandbytes as bnb
+
+            from .bnb import Linear8bitLt
+
+        if is_bnb_4bit_available():
+            from .bnb import Linear4bit
+
+        loaded_in_8bit = kwargs.pop("loaded_in_8bit", False)
+        loaded_in_4bit = kwargs.pop("loaded_in_4bit", False)
+        is_feedforward = kwargs.pop("is_feedforward", False)
+
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if loaded_in_8bit and isinstance(target_base_layer, bnb.nn.Linear8bitLt):
+            eightbit_kwargs = kwargs.copy()
+            eightbit_kwargs.update(
+                {
+                    "has_fp16_weights": target_base_layer.state.has_fp16_weights,
+                    "threshold": target_base_layer.state.threshold,
+                    "index": target_base_layer.index,
+                }
+            )
+            new_module = Linear8bitLt(target, adapter_name, is_feedforward=is_feedforward, **eightbit_kwargs)
+        elif loaded_in_4bit and isinstance(target_base_layer, bnb.nn.Linear4bit):
+            fourbit_kwargs = kwargs.copy()
+            fourbit_kwargs.update(
+                {
+                    "compute_dtype": target_base_layer.compute_dtype,
+                    "compress_statistics": target_base_layer.weight.compress_statistics,
+                    "quant_type": target_base_layer.weight.quant_type,
+                }
+            )
+            new_module = Linear4bit(target, adapter_name, is_feedforward=is_feedforward, **fourbit_kwargs)
+        elif isinstance(target, torch.nn.Conv2d):
+            new_module = Conv2d(target, adapter_name, is_feedforward=is_feedforward, **kwargs)
+        elif isinstance(target, torch.nn.Conv3d):
+            new_module = Conv3d(target, adapter_name, is_feedforward=is_feedforward, **kwargs)
+        elif isinstance(target_base_layer, torch.nn.Linear):
+            if kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                    "Setting fan_in_fan_out to False."
+                )
+                kwargs["fan_in_fan_out"] = ia3_config.fan_in_fan_out = False
+            new_module = Linear(target, adapter_name, is_feedforward=is_feedforward, **kwargs)
+        elif isinstance(target_base_layer, Conv1D):
+            if not kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to False but the target module is `Conv1D`. Setting fan_in_fan_out to True."
+                )
+                kwargs["fan_in_fan_out"] = ia3_config.fan_in_fan_out = True
+            new_module = Linear(
+                target, adapter_name, is_feedforward=is_feedforward, is_target_conv_1d_layer=True, **kwargs
+            )
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. "
+                f"Currently, only `torch.nn.Linear`, `torch.nn.Conv2d`, and `Conv1D` are supported."
+            )
+        return new_module
+
+    @staticmethod
+    def _check_target_module_exists(ia3_config, key):
+        return check_target_module_exists(ia3_config, key)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+    def _create_and_replace(
+        self,
+        ia3_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+    ):
+        # check if target module is in feedforward_modules
+        is_feedforward = self._check_target_module_feedforward(ia3_config, current_key)
+
+        kwargs = {
+            "fan_in_fan_out": ia3_config.fan_in_fan_out,
+            "init_ia3_weights": ia3_config.init_ia3_weights,
+            "is_feedforward": is_feedforward,
+            "loaded_in_8bit": getattr(self.model, "is_loaded_in_8bit", False),
+            "loaded_in_4bit": getattr(self.model, "is_loaded_in_4bit", False),
+        }
+
+        if isinstance(target, IA3Layer):
+            target.update_layer(
+                adapter_name,
+                ia3_config.init_ia3_weights,
+            )
+        else:
+            new_module = self._create_new_module(ia3_config, adapter_name, target, **kwargs)
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+
+    @staticmethod
+    def _check_target_module_feedforward(ia3_config, key) -> bool:
+        """
+        A helper private method that checks if the target module `key` matches with a feedforward module specified in
+        `ia3_config`
+        """
+        if isinstance(ia3_config.feedforward_modules, str):
+            is_feedforward = bool(re.fullmatch(ia3_config.feedforward_modules, key))
+        else:
+            is_feedforward = any(key.endswith(target_key) for target_key in ia3_config.feedforward_modules)
+        return is_feedforward
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        # layers with base_layer don't need the weight to be copied, as they have a reference already
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if self.prefix in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (IA3Layer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self) -> None:
+        """Enable all adapters.
+
+        Call this if you have previously disabled all adapters and want to re-enable them.
+        """
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self) -> None:
+        """Disable all adapters.
+
+        When disabling all adapters, the model output corresponds to the output of the base model.
+        """
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name: str | list[str]) -> None:
+        """Set the active adapter(s).
+
+        Additionally, this function will set the specified adapters to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str` or `list[str]`): Name of the adapter(s) to be activated.
+        """
+        for module in self.model.modules():
+            if isinstance(module, IA3Layer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        if peft_config.feedforward_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING:
+                raise ValueError("Please specify `feedforward_modules` in `peft_config`")
+            peft_config.feedforward_modules = set(
+                TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self, merge: bool = True, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ):
+        r"""
+        This method merges the (IA)^3 layers into the base model. This is needed if someone wants to use the base model
+        as a standalone model.
+
+        Args:
+            safe_merge (`bool`, `optional`, defaults to `False`):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        if getattr(self.model, "is_loaded_in_8bit", False):
+            raise ValueError("Cannot merge ia3 layers when the model is loaded in 8-bit mode")
+
+        if getattr(self.model, "is_loaded_in_4bit", False):
+            raise ValueError("Cannot merge ia3 layers when the model is loaded in 4-bit mode")
+
+        self._unloading_checks(adapter_names)
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        for key in key_list:
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                new_module = target.modules_to_save[target.active_adapter]
+                if hasattr(new_module, "base_layer"):
+                    # check if the module is itself a tuner layer
+                    if merge:
+                        new_module.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                    new_module = new_module.get_base_layer()
+                setattr(parent, target_name, new_module)
+
+        return self.model
+
+    def merge_and_unload(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> torch.nn.Module:
+        r"""
+        This method merges the IA³ layers into the base model. This is needed if someone wants to use the base model as
+        a standalone model.
+
+        Args:
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import PeftModel
+
+        >>> base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-40b")
+        >>> peft_model_id = "smangrul/falcon-40B-int4-peft-lora-sfttrainer-sample"
+        >>> model = PeftModel.from_pretrained(base_model, peft_model_id)
+        >>> merged_model = model.merge_and_unload()
+        ```
+        """
+        return self._unload_and_optionally_merge(safe_merge=safe_merge, adapter_names=adapter_names)
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the IA³ modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in self.peft_config:
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, IA3Layer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
+
+    def _check_add_weighted_adapter(self, adapters: list[str]) -> tuple[str, str]:
+        """
+        Helper function to check if the arguments to add_weighted_adapter are valid and compatible with the underlying
+        model.
+        """
+        # Validate existence of adapters
+        for adapter in adapters:
+            if adapter not in self.peft_config:
+                raise ValueError(f"Adapter {adapter} does not exist")
+
+        # Check for conflicting modules_to_save
+        modules_to_save_wrappers = [module for module in self.modules() if isinstance(module, ModulesToSaveWrapper)]
+        if any(
+            sum(adapter in wrapper.modules_to_save for adapter in adapters) > 1 for wrapper in modules_to_save_wrappers
+        ):
+            raise ValueError("Cannot add weighted adapters targeting the same module with modules_to_save.")
+
+        # Ensure all adapters have compatible target and feedforward module types
+        target_module_types = {type(self.peft_config[adapter].target_modules) for adapter in adapters}
+        feedforward_module_types = {type(self.peft_config[adapter].feedforward_modules) for adapter in adapters}
+        if len(target_module_types) > 1 or len(feedforward_module_types) > 1:
+            raise ValueError("All adapter configs should have the same type for target and feedforward modules.")
+
+        # Combine target and feedforward modules
+        if str in target_module_types:
+            new_target_modules = "|".join(f"({self.peft_config[adapter].target_modules})" for adapter in adapters)
+        else:
+            new_target_modules = set.union(*(self.peft_config[adapter].target_modules for adapter in adapters))
+
+        if str in feedforward_module_types:
+            new_feedforward_modules = "|".join(
+                f"({self.peft_config[adapter].feedforward_modules})" for adapter in adapters
+            )
+        else:
+            new_feedforward_modules = set.union(
+                *(self.peft_config[adapter].feedforward_modules for adapter in adapters)
+            )
+
+        return new_target_modules, new_feedforward_modules
+
+    def add_weighted_adapter(
+        self,
+        adapters: list[str],
+        weights: list[float],
+        adapter_name: str,
+    ) -> None:
+        """
+        This method adds a new adapter by merging the given adapters with the given weights.
+
+        Args:
+            adapters (`list`):
+                List of adapter names to be merged.
+            weights (`list`):
+                List of weights for each adapter.
+            adapter_name (`str`):
+                Name of the new adapter.
+        """
+        if adapter_name in list(self.peft_config.keys()):
+            return
+
+        new_target_modules, new_feedforward_modules = self._check_add_weighted_adapter(
+            adapters=adapters,
+        )
+
+        self.peft_config[adapter_name] = replace(
+            self.peft_config[adapters[0]],
+            target_modules=new_target_modules,
+            feedforward_modules=new_feedforward_modules,
+        )
+        self.inject_adapter(self.model, adapter_name)
+
+        # Do we really need that?
+        _freeze_adapter(self.model, adapter_name)
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, IA3Layer):
+                if adapter_name in target.ia3_l:
+                    target_ia3_l = target.ia3_l[adapter_name]
+                else:
+                    continue
+
+                target_ia3_l.data = target_ia3_l.data.zero_()
+                for adapter, weight in zip(adapters, weights):
+                    if adapter in target.ia3_l:
+                        current_adapter_ia3_l = target.ia3_l[adapter]
+                    else:
+                        continue
+                    target_ia3_l.data += current_adapter_ia3_l.data * weight
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f90a8fb058cf75450b89166bf2e562f07b835fd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/__init__.py
@@ -0,0 +1,23 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import LNTuningConfig
+from .model import LNTuningModel
+
+
+__all__ = ["LNTuningConfig", "LNTuningModel"]
+
+register_peft_method(name="ln_tuning", config_cls=LNTuningConfig, model_cls=LNTuningModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..127ee9017333bce22706b58b13701049244b1da9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/config.py
@@ -0,0 +1,70 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class LNTuningConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a :class:`~peft.tuners.LNTuningModel`.
+
+    Args:
+        target_modules (`Optional[Union[List[str], str]]`):
+            List of module names or regex expression of the module names to replace with LNTuning. For example,
+            '.*decoder.*' or '.*encoder.*'. If this is not specified, modules will be chosen according to the model
+            architecture. If the architecture is not known, an error will be raised -- in this case, you should specify
+            the target modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        modules_to_save (`Optional[Union[List[str], str]]`):
+            List of modules to be set as trainable and saved in the final checkpoint. For example, in Sequence
+            Classification or Token Classification tasks, the final layer `classifier/score` are randomly initialized
+            and as such need to be trainable and saved.
+    """
+
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of module names or regex expression of the module names to replace with LNTuning."
+                "For example, '.*decoder.*' or '.*encoder.*'. "
+                "If not specified, modules will be chosen according to the model architecture, If the architecture is "
+                "not known, an error will be raised -- in this case, you shoud specify the target modules manually."
+            ),
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from LNTuning."},
+    )
+    modules_to_save: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.LN_TUNING
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..1c90d4b9e618c6c343cad8279cfdfb4e2d4c6122
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/layer.py
@@ -0,0 +1,117 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from copy import deepcopy
+from typing import List, Optional
+
+import torch
+import torch.nn as nn
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+
+class LNTuningLayer(nn.Module, BaseTunerLayer):
+    """
+    Selects a layer from the model.
+    """
+
+    adapter_layer_names = ("ln_tuning_layers",)
+
+    def __init__(self, base_layer: nn.Module, adapter_name: str):
+        super().__init__()
+        self.base_layer = base_layer
+        self.ln_tuning_layers = nn.ModuleDict({})
+        self.update_layer(self.base_layer, adapter_name)
+        self._active_adapter = adapter_name
+        self.merged_adapters = []
+
+    def update_layer(self, layer: nn.Module, adapter_name: str):
+        self.ln_tuning_layers[adapter_name] = deepcopy(layer)
+
+    def enable_adapters(self, enabled: bool) -> None:
+        """Toggle the enabling and disabling of adapters
+
+        Takes care of setting the requires_grad flag for the adapter weights.
+
+        Args:
+            enabled (bool): True to enable adapters, False to disable adapters
+        """
+        if enabled:
+            self.set_adapter(self.active_adapters)
+            self._disable_adapters = False
+        else:
+            if self.merged:
+                self.unmerge()
+            # disable grads on all adapter layers
+            for layer_name in self.adapter_layer_names:
+                layer = getattr(self, layer_name)
+                layer.requires_grad_(False)
+            self._disable_adapters = True
+
+    def merge(self, adapter_names: Optional[List[str]] = None):
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        if len(adapter_names) > 1:
+            raise ValueError(
+                f"Trying to merge {len(adapter_names)} adapters, but LN "
+                f"tuning does not allow merging more than one adapter at a time"
+            )
+        merged_adapters = set(self.merged_adapters)
+        if merged_adapters:
+            warnings.warn(f"Already merged with {merged_adapters}. Unmerging first.")
+            self.unmerge()
+
+        self.base_layer, self.ln_tuning_layers[adapter_names[0]] = (
+            self.ln_tuning_layers[adapter_names[0]],
+            self.base_layer,
+        )
+        self.merged_adapters.append(adapter_names[0])
+
+    def unmerge(self):
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        # popping one element is sufficient because LN
+        # tuning does not allow merging more than one adapter at a time.
+        merged_name = self.merged_adapters.pop()
+        self.base_layer, self.ln_tuning_layers[merged_name] = (
+            self.ln_tuning_layers[merged_name],
+            self.base_layer,
+        )
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            if len(self.active_adapters) != 1:
+                raise ValueError(
+                    f"Trying to run forward with {len(self.active_adapters)} active "
+                    f"adapters, but LN tuning does not allow inference with more than one adapter at a time"
+                )
+            active_adapter = self.active_adapters[0]
+            result = self.ln_tuning_layers[active_adapter](x, *args, **kwargs)
+
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "ln_tuning." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..3e16a7fad492c68e7ba14404f078d4d9c8f16dd2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/ln_tuning/model.py
@@ -0,0 +1,205 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from typing import Optional
+
+from torch import nn
+from torch.nn.modules import Module
+from tqdm import tqdm
+
+from peft.config import PeftConfig
+from peft.tuners.tuners_utils import BaseTuner, _get_submodules, check_target_module_exists
+from peft.utils import TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING, ModulesToSaveWrapper
+
+from .layer import LNTuningLayer
+
+
+class LNTuningModel(BaseTuner):
+    """
+    Creates LayerNorm tuning from a pretrained transformer model.
+
+    The method is described in detail in https://arxiv.org/abs/2312.11420.
+
+    Args:
+        model ([`torch.nn.Module`]): The model to be adapted.
+        config ([`LNTuningConfig`]): The configuration of the Lora model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            This option has no effect on LN tuning but exists for consistency with other PEFT methods.
+
+    Returns:
+        'torch.nn.Module': The adapted model with LayerNorm tuned on.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import get_peft_model, TaskType, LNTuningConfig
+
+        >>> peft_config = LNTuningConfig(
+        ...     task_type=TaskType.CAUSAL_LM,
+        ... )
+
+        >>> model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf")
+        >>> model = get_peft_model(model, peft_config)
+        >>> model.print_trainable_parameters()
+        ```
+
+    **Attributes**:
+        - **model** ([`~transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`LNTuningConfig`]): The configuration of the Lora model.
+    """
+
+    prefix: str = "ln_tuning_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False) -> None:
+        # self.adapter_name = adapter_name
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    # TODO: here need to handle the modules_to_save rather than the target_modules
+    @staticmethod
+    def _prepare_adapter_config(peft_config: PeftConfig, model_config: dict) -> PeftConfig:
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _create_and_replace(
+        self,
+        peft_config: PeftConfig,
+        adapter_name: str,
+        target: Module,
+        target_name: str,
+        parent: Module,
+        current_key: str,
+    ) -> None:
+        # replace the original module with a same new module
+        new_module = self._create_new_module(peft_config, target, adapter_name)
+        if adapter_name != self.active_adapter:
+            new_module.requires_grad_(False)
+        self._replace_module(parent, target_name, new_module, target)
+
+    def _create_new_module(
+        self,
+        peft_config: PeftConfig,
+        target: Module,
+        adapter_name: str,
+    ) -> Module:
+        if not isinstance(target, LNTuningLayer):
+            new_module = LNTuningLayer(target, adapter_name)
+        else:
+            new_module = target
+            new_module.update_layer(target.base_layer, adapter_name)
+        return new_module
+
+    def _replace_module(self, parent: Module, child_name: str, new_module: Module, child: Module) -> None:
+        setattr(parent, child_name, new_module)
+
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        for name, module in new_module.named_modules():
+            weight = child.qweight if hasattr(child, "qweight") else child.weight
+            module.to(weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: Module):
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+            else:
+                p.requires_grad = True
+
+    def _check_target_module_exists(self, peft_config: PeftConfig, key: str) -> bool:
+        return check_target_module_exists(peft_config, key)
+
+    def _set_adapter_layers(self, enabled: bool) -> None:
+        for module in self.model.modules():
+            if isinstance(module, (LNTuningLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self) -> None:
+        """Enable all adapters.
+
+        Call this if you have previously disabled all adapters and want to re-enable them.
+        """
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self) -> None:
+        """Disable all adapters.
+
+        When disabling all adapters, the model output corresponds to the output of the base model.
+        """
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name: str) -> None:
+        for module in self.model.modules():
+            if isinstance(module, LNTuningLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        self._unloading_checks(adapter_names)
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading adapters " + ("and merging " if merge else "") + "model"
+
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(adapter_names)
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+
+        return self.model
+
+    def unload(self):
+        return self._unload_and_optionally_merge(merge=False)
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ) -> nn.Module:
+        return self._unload_and_optionally_merge(merge=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..70dd1545bbd49b0aaa5eafbde05f82b6a04c3d74
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import LoHaConfig
+from .layer import Conv2d, Linear, LoHaLayer
+from .model import LoHaModel
+
+
+__all__ = ["Conv2d", "Linear", "LoHaConfig", "LoHaLayer", "LoHaModel"]
+
+register_peft_method(name="loha", config_cls=LoHaConfig, model_cls=LoHaModel, prefix="hada_", is_mixed_compatible=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..00eacb1301cbe5ff4c5d0e4c17e1bfe66a1e4b4e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/config.py
@@ -0,0 +1,139 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.tuners.lycoris_utils import LycorisConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class LoHaConfig(LycorisConfig):
+    """
+    This is the configuration class to store the configuration of a [`LoHaModel`].
+
+    Args:
+        r (`int`):
+            LoHa rank.
+        alpha (`int`):
+            The alpha parameter for LoHa scaling.
+        rank_dropout (`float`):
+            The dropout probability for rank dimension during training.
+        module_dropout (`float`):
+            The dropout probability for disabling LoHa modules during training.
+        use_effective_conv2d (`bool`):
+            Use parameter effective decomposition for Conv2d with ksize > 1 ("Proposition 3" from FedPara paper).
+        target_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear/Conv1D modules are chosen,
+            excluding the output layer. If this is not specified, modules will be chosen according to the model
+            architecture. If the architecture is not known, an error will be raised -- in this case, you should specify
+            the target modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        init_weights (`bool`):
+            Whether to perform initialization of adapter weights. This defaults to `True`, passing `False` is
+            discouraged.
+        layers_to_transform (`Union[List[int], int]`):
+            The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
+            that are specified in this list. If a single integer is passed, it will apply the transformations on the
+            layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`. This should target the
+            `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`.
+        rank_pattern (`dict`):
+            The mapping from layer names or regexp expression to ranks which are different from the default rank
+            specified by `r`. For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`.
+        alpha_pattern (`dict`):
+            The mapping from layer names or regexp expression to alphas which are different from the default alpha
+            specified by `alpha`. For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`.
+        modules_to_save (`Optional[List[str]]`):
+            List of modules apart from adapter layers to be set as trainable and saved in the final checkpoint.
+    """
+
+    r: int = field(default=8, metadata={"help": "LoHa rank"})
+    alpha: int = field(default=8, metadata={"help": "LoHa alpha"})
+    rank_dropout: float = field(
+        default=0.0, metadata={"help": "The dropout probability for rank dimension during training"}
+    )
+    module_dropout: float = field(
+        default=0.0, metadata={"help": "The dropout probability for disabling LoHa modules during training"}
+    )
+    use_effective_conv2d: bool = field(
+        default=False,
+        metadata={
+            "help": 'Use parameter effective decomposition for Conv2d 3x3 with ksize > 1 ("Proposition 3" from FedPara paper)'
+        },
+    )
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or regex expression of the module names to replace with LoHa."
+            "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$' "
+            "This can also be a wildcard 'all-linear' which matches all linear/Conv1D layers except the output layer."
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from LoHa."},
+    )
+    init_weights: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the LoHa layers with their default initialization. Don't change "
+                "this setting, except if you know exactly what you're doing."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index."
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern. "
+            "This should target the `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`."
+        },
+    )
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from LoHA layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.LOHA
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..6d294af66973a8e316fe1bc74b1b878e6ddd0b34
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/layer.py
@@ -0,0 +1,369 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import math
+from typing import Any, Set, Tuple
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from peft.tuners.lycoris_utils import LycorisLayer
+
+
+class LoHaLayer(nn.Module, LycorisLayer):
+    # All names of layers that may contain adapter weights
+    adapter_layer_names = ("hada_w1_a", "hada_w1_b", "hada_w2_a", "hada_w2_b", "hada_t1", "hada_t2")
+    # other_param_names is defined on parent class
+
+    def __init__(self, base_layer: nn.Module):
+        super().__init__()
+        LycorisLayer.__init__(self, base_layer)
+
+        # LoHa info
+        self.hada_w1_a = nn.ParameterDict({})
+        self.hada_w1_b = nn.ParameterDict({})
+        self.hada_w2_a = nn.ParameterDict({})
+        self.hada_w2_b = nn.ParameterDict({})
+        self.hada_t1 = nn.ParameterDict({})
+        self.hada_t2 = nn.ParameterDict({})
+
+    @property
+    def _available_adapters(self) -> Set[str]:
+        return {*self.hada_w1_a, *self.hada_w1_b, *self.hada_w2_a, *self.hada_w2_b, *self.hada_t1, *self.hada_t2}
+
+    def create_adapter_parameters(self, adapter_name: str, r: int, shape: Tuple[int, ...]):
+        # https://github.com/KohakuBlueleaf/LyCORIS/blob/eb460098187f752a5d66406d3affade6f0a07ece/lycoris/modules/loha.py#L130C9-L143C75
+        if len(shape) == 4:
+            self.hada_t1[adapter_name] = nn.Parameter(torch.empty(r, r, shape[2], shape[3]))
+            self.hada_w1_a[adapter_name] = nn.Parameter(torch.empty(r, shape[0]))  # out_dim, 1-mode
+            self.hada_w1_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1]))  # in_dim , 2-mode
+
+            self.hada_t2[adapter_name] = nn.Parameter(torch.empty(r, r, shape[2], shape[3]))
+            self.hada_w2_a[adapter_name] = nn.Parameter(torch.empty(r, shape[0]))  # out_dim, 1-mode
+            self.hada_w2_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1]))  # in_dim , 2-mode
+        else:
+            self.hada_w1_a[adapter_name] = nn.Parameter(torch.empty(shape[0], r))
+            self.hada_w1_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1]))
+
+            self.hada_w2_a[adapter_name] = nn.Parameter(torch.empty(shape[0], r))
+            self.hada_w2_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1]))
+
+    def reset_adapter_parameters(self, adapter_name: str):
+        # Original implementation performs initialization with normal distribution
+        # https://github.com/KohakuBlueleaf/LyCORIS/blob/3549fdef8f564761d68b695a08ef88b1122fdedc/lycoris/modules/loha.py#L158
+
+        # FedPara paper proposes to perform He initialization, let's stick with it
+        # It is enough to initialize only single matrix with zeros to make adapter do nothing after initialization
+        if adapter_name in self.hada_w1_a.keys():
+            nn.init.kaiming_uniform_(self.hada_w1_a[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.hada_w1_b[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.hada_w2_a[adapter_name], a=math.sqrt(5))
+            nn.init.zeros_(self.hada_w2_b[adapter_name])
+        if adapter_name in self.hada_t1.keys():
+            nn.init.kaiming_uniform_(self.hada_t1[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.hada_t2[adapter_name], a=math.sqrt(5))
+
+    def reset_adapter_parameters_random(self, adapter_name: str):
+        # Original implementation performs initialization with normal distribution
+        # https://github.com/KohakuBlueleaf/LyCORIS/blob/3549fdef8f564761d68b695a08ef88b1122fdedc/lycoris/modules/loha.py#L158
+
+        # FedPara paper proposes to perform He initialization, let's stick with it
+        # It is enough to initialize only single matrix with zeros to make adapter do nothing after initialization
+        if adapter_name in self.hada_w1_a.keys():
+            nn.init.kaiming_uniform_(self.hada_w1_a[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.hada_w1_b[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.hada_w2_a[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.hada_w2_b[adapter_name], a=math.sqrt(5))
+        if adapter_name in self.hada_t1.keys():
+            nn.init.kaiming_uniform_(self.hada_t1[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.hada_t2[adapter_name], a=math.sqrt(5))
+
+    def update_layer(
+        self,
+        adapter_name: str,
+        r: int,
+        alpha: float,
+        rank_dropout: float,
+        module_dropout: float,
+        init_weights: bool,
+        use_effective_conv2d: bool = False,
+        **kwargs,
+    ) -> None:
+        """Internal function to create loha adapter
+
+        Args:
+            adapter_name (`str`): Name for the adapter to add.
+            r (`int`): Rank for the added adapter.
+            alpha (`float`): Alpha for the added adapter.
+            rank_dropout (`float`): The dropout probability for rank dimension during training.
+            module_dropout (`float`): The dropout probability for disabling adapter during training.
+            init_weights (`bool`): Whether to initialize weights.
+            use_effective_conv2d (`bool`, *optional*, defaults to `False`):
+                Use parameter effective decomposition for Conv2d with ksize > 1.
+        """
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+
+        self.r[adapter_name] = r
+        self.alpha[adapter_name] = alpha
+        self.scaling[adapter_name] = alpha / r
+        self.rank_dropout[adapter_name] = rank_dropout
+        self.module_dropout[adapter_name] = module_dropout
+
+        # Determine shape of LoHa weights
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            shape = tuple(base_layer.weight.shape)
+        elif isinstance(base_layer, nn.Conv2d):
+            use_effective_conv2d = use_effective_conv2d and base_layer.kernel_size != (1, 1)
+            if use_effective_conv2d:
+                shape = (base_layer.out_channels, base_layer.in_channels, *base_layer.kernel_size)
+            else:
+                shape = (
+                    base_layer.out_channels,
+                    base_layer.in_channels * base_layer.kernel_size[0] * base_layer.kernel_size[1],
+                )
+        else:
+            raise TypeError(f"LoHa is not implemented for base layers of type {type(base_layer).__name__}")
+
+        # Create weights with provided shape
+        self.create_adapter_parameters(adapter_name, r, shape)
+
+        # Initialize weights
+        if init_weights:
+            self.reset_adapter_parameters(adapter_name)
+        else:
+            self.reset_adapter_parameters_random(adapter_name)
+
+        # Move new weights to device
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def get_delta_weight(self, adapter_name: str) -> torch.Tensor:
+        # https://github.com/KohakuBlueleaf/LyCORIS/blob/eb460098187f752a5d66406d3affade6f0a07ece/lycoris/modules/loha.py#L178
+        if adapter_name in self.hada_t1.keys():
+            weight = make_weight_cp(
+                self.hada_t1[adapter_name],
+                self.hada_w1_a[adapter_name],
+                self.hada_w1_b[adapter_name],
+                self.hada_t2[adapter_name],
+                self.hada_w2_a[adapter_name],
+                self.hada_w2_b[adapter_name],
+                scale=torch.tensor(self.scaling[adapter_name]),
+            )
+        else:
+            weight = make_weight(
+                self.hada_w1_a[adapter_name],
+                self.hada_w1_b[adapter_name],
+                self.hada_w2_a[adapter_name],
+                self.hada_w2_b[adapter_name],
+                scale=torch.tensor(self.scaling[adapter_name]),
+            )
+
+        base_layer = self.get_base_layer()
+        weight = weight.reshape(base_layer.weight.shape)
+
+        # Perform rank dropout during training - drop rows of addition weights
+        rank_dropout = self.rank_dropout[adapter_name]
+        if self.training and rank_dropout:
+            drop = (torch.rand(weight.size(0)) > rank_dropout).to(weight.dtype)
+            drop = drop.view(-1, *[1] * len(weight.shape[1:])).to(weight.device)
+            # TODO: Investigate if there should be a scaler like in normal dropout during training
+            # Original implementation doesn't have it
+            # https://github.com/KohakuBlueleaf/LyCORIS/blob/eb460098187f752a5d66406d3affade6f0a07ece/lycoris/modules/loha.py#L193
+            drop /= drop.mean()
+            weight *= drop
+
+        return weight
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+
+            # Execute all the adapters
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self._available_adapters:
+                    continue
+
+                module_dropout = self.module_dropout[active_adapter]
+
+                # Modify current execution weights
+                if (not self.training) or (self.training and torch.rand(1) > module_dropout):
+                    result = result + self._get_delta_activations(active_adapter, x, *args, **kwargs)
+
+        result = result.to(previous_dtype)
+        return result
+
+
+class Linear(LoHaLayer):
+    """LoHa implemented in Linear layer"""
+
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str = "default",
+        r: int = 0,
+        alpha: float = 0.0,
+        rank_dropout: float = 0.0,
+        module_dropout: float = 0.0,
+        init_weights: bool = True,
+        **kwargs,
+    ):
+        super().__init__(base_layer)
+
+        # Create adapter and set it active
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, alpha, rank_dropout, module_dropout, init_weights, **kwargs)
+
+    def _get_delta_activations(
+        self, adapter_name: str, input: torch.Tensor, *args: Any, **kwargs: Any
+    ) -> torch.Tensor:
+        delta_weight = self.get_delta_weight(adapter_name)
+        # don't add bias here, because the bias is already included in the output of the base_layer
+        return F.linear(input, delta_weight)
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "loha." + rep
+
+
+class Conv2d(LoHaLayer):
+    """LoHa implemented in Conv2d layer"""
+
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str = "default",
+        r: int = 0,
+        alpha: float = 0.0,
+        rank_dropout: float = 0.0,
+        module_dropout: float = 0.0,
+        use_effective_conv2d: bool = False,
+        init_weights: bool = True,
+        **kwargs,
+    ):
+        super().__init__(base_layer)
+
+        # Create adapter and set it active
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name, r, alpha, rank_dropout, module_dropout, init_weights, use_effective_conv2d, **kwargs
+        )
+
+    def _get_delta_activations(
+        self, adapter_name: str, input: torch.Tensor, *args: Any, **kwargs: Any
+    ) -> torch.Tensor:
+        delta_weight = self.get_delta_weight(adapter_name)
+        # don't add bias here, because the bias is already included in the output of the base_layer
+        base_layer = self.get_base_layer()
+        return F.conv2d(
+            input,
+            delta_weight,
+            stride=base_layer.stride,
+            padding=base_layer.padding,
+            dilation=base_layer.dilation,
+            groups=base_layer.groups,
+        )
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "loha." + rep
+
+
+# Below code is a direct copy from https://github.com/KohakuBlueleaf/LyCORIS/blob/eb460098187f752a5d66406d3affade6f0a07ece/lycoris/modules/loha.py#L9
+
+
+class HadaWeight(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, w1a, w1b, w2a, w2b, scale=torch.tensor(1)):
+        ctx.save_for_backward(w1a, w1b, w2a, w2b, scale)
+        diff_weight = ((w1a @ w1b) * (w2a @ w2b)) * scale
+        return diff_weight
+
+    @staticmethod
+    def backward(ctx, grad_out):
+        (w1a, w1b, w2a, w2b, scale) = ctx.saved_tensors
+        grad_out = grad_out * scale
+        temp = grad_out * (w2a @ w2b)
+        grad_w1a = temp @ w1b.T
+        grad_w1b = w1a.T @ temp
+
+        temp = grad_out * (w1a @ w1b)
+        grad_w2a = temp @ w2b.T
+        grad_w2b = w2a.T @ temp
+
+        del temp
+        return grad_w1a, grad_w1b, grad_w2a, grad_w2b, None
+
+
+class HadaWeightCP(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, t1, w1a, w1b, t2, w2a, w2b, scale=torch.tensor(1)):
+        ctx.save_for_backward(t1, w1a, w1b, t2, w2a, w2b, scale)
+
+        rebuild1 = torch.einsum("i j k l, j r, i p -> p r k l", t1, w1b, w1a)
+        rebuild2 = torch.einsum("i j k l, j r, i p -> p r k l", t2, w2b, w2a)
+
+        return rebuild1 * rebuild2 * scale
+
+    @staticmethod
+    def backward(ctx, grad_out):
+        (t1, w1a, w1b, t2, w2a, w2b, scale) = ctx.saved_tensors
+        grad_out = grad_out * scale
+
+        temp = torch.einsum("i j k l, j r -> i r k l", t2, w2b)
+        rebuild = torch.einsum("i j k l, i r -> r j k l", temp, w2a)
+
+        grad_w = rebuild * grad_out
+        del rebuild
+
+        grad_w1a = torch.einsum("r j k l, i j k l -> r i", temp, grad_w)
+        grad_temp = torch.einsum("i j k l, i r -> r j k l", grad_w, w1a.T)
+        del grad_w, temp
+
+        grad_w1b = torch.einsum("i r k l, i j k l -> r j", t1, grad_temp)
+        grad_t1 = torch.einsum("i j k l, j r -> i r k l", grad_temp, w1b.T)
+        del grad_temp
+
+        temp = torch.einsum("i j k l, j r -> i r k l", t1, w1b)
+        rebuild = torch.einsum("i j k l, i r -> r j k l", temp, w1a)
+
+        grad_w = rebuild * grad_out
+        del rebuild
+
+        grad_w2a = torch.einsum("r j k l, i j k l -> r i", temp, grad_w)
+        grad_temp = torch.einsum("i j k l, i r -> r j k l", grad_w, w2a.T)
+        del grad_w, temp
+
+        grad_w2b = torch.einsum("i r k l, i j k l -> r j", t2, grad_temp)
+        grad_t2 = torch.einsum("i j k l, j r -> i r k l", grad_temp, w2b.T)
+        del grad_temp
+        return grad_t1, grad_w1a, grad_w1b, grad_t2, grad_w2a, grad_w2b, None
+
+
+def make_weight(w1a, w1b, w2a, w2b, scale):
+    return HadaWeight.apply(w1a, w1b, w2a, w2b, scale)
+
+
+def make_weight_cp(t1, w1a, w1b, t2, w2a, w2b, scale):
+    return HadaWeightCP.apply(t1, w1a, w1b, t2, w2a, w2b, scale)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..03139e297df1a8afc00d1e313faa3ec4859c8a6c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/loha/model.py
@@ -0,0 +1,112 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Dict, Type, Union
+
+import torch
+from torch import nn
+
+from peft.tuners.lycoris_utils import LycorisConfig, LycorisTuner
+from peft.utils.other import get_pattern_key
+
+from .layer import Conv2d, Linear, LoHaLayer
+
+
+class LoHaModel(LycorisTuner):
+    """
+    Creates Low-Rank Hadamard Product model from a pretrained model. The method is partially described in
+    https://arxiv.org/abs/2108.06098 Current implementation heavily borrows from
+    https://github.com/KohakuBlueleaf/LyCORIS/blob/eb460098187f752a5d66406d3affade6f0a07ece/lycoris/modules/loha.py
+
+    Args:
+        model (`torch.nn.Module`): The model to which the adapter tuner layers will be attached.
+        config ([`LoHaConfig`]): The configuration of the LoHa model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The LoHa model.
+
+    Example:
+        ```py
+        >>> from diffusers import StableDiffusionPipeline
+        >>> from peft import LoHaModel, LoHaConfig
+
+        >>> config_te = LoHaConfig(
+        ...     r=8,
+        ...     lora_alpha=32,
+        ...     target_modules=["k_proj", "q_proj", "v_proj", "out_proj", "fc1", "fc2"],
+        ...     rank_dropout=0.0,
+        ...     module_dropout=0.0,
+        ...     init_weights=True,
+        ... )
+        >>> config_unet = LoHaConfig(
+        ...     r=8,
+        ...     lora_alpha=32,
+        ...     target_modules=[
+        ...         "proj_in",
+        ...         "proj_out",
+        ...         "to_k",
+        ...         "to_q",
+        ...         "to_v",
+        ...         "to_out.0",
+        ...         "ff.net.0.proj",
+        ...         "ff.net.2",
+        ...     ],
+        ...     rank_dropout=0.0,
+        ...     module_dropout=0.0,
+        ...     init_weights=True,
+        ...     use_effective_conv2d=True,
+        ... )
+
+        >>> model = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+        >>> model.text_encoder = LoHaModel(model.text_encoder, config_te, "default")
+        >>> model.unet = LoHaModel(model.unet, config_unet, "default")
+        ```
+
+    **Attributes**:
+        - **model** ([`~torch.nn.Module`]) -- The model to be adapted.
+        - **peft_config** ([`LoHaConfig`]): The configuration of the LoHa model.
+    """
+
+    prefix: str = "hada_"
+    layers_mapping: Dict[Type[torch.nn.Module], Type[LoHaLayer]] = {
+        torch.nn.Conv2d: Conv2d,
+        torch.nn.Linear: Linear,
+    }
+
+    def _create_and_replace(
+        self,
+        config: LycorisConfig,
+        adapter_name: str,
+        target: Union[LoHaLayer, nn.Module],
+        target_name: str,
+        parent: nn.Module,
+        current_key: str,
+    ) -> None:
+        """
+        A private method to create and replace the target module with the adapter module.
+        """
+        r_key = get_pattern_key(config.rank_pattern.keys(), current_key)
+        alpha_key = get_pattern_key(config.alpha_pattern.keys(), current_key)
+        kwargs = config.to_dict()
+        kwargs["r"] = config.rank_pattern.get(r_key, config.r)
+        kwargs["alpha"] = config.alpha_pattern.get(alpha_key, config.alpha)
+
+        if isinstance(target, LoHaLayer):
+            target.update_layer(adapter_name, **kwargs)
+        else:
+            new_module = self._create_new_module(config, adapter_name, target, **kwargs)
+            self._replace_module(parent, target_name, new_module, target)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..f4fe0e92c6eacd0cc276ad3584230ea58ee4a8a6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import LoKrConfig
+from .layer import Conv2d, Linear, LoKrLayer
+from .model import LoKrModel
+
+
+__all__ = ["Conv2d", "Linear", "LoKrConfig", "LoKrLayer", "LoKrModel"]
+
+register_peft_method(name="lokr", config_cls=LoKrConfig, model_cls=LoKrModel, is_mixed_compatible=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..ea8a0e837fed6a7b54ffbe5e5f051916c231b3ff
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/config.py
@@ -0,0 +1,151 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Literal, Optional, Union
+
+from peft.tuners.lycoris_utils import LycorisConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class LoKrConfig(LycorisConfig):
+    """
+    Configuration class of [`LoKrModel`].
+
+    Args:
+        r (`int`):
+            LoKr rank.
+        alpha (`int`):
+            The alpha parameter for LoKr scaling.
+        rank_dropout (`float`):
+            The dropout probability for rank dimension during training.
+        module_dropout (`float`):
+            The dropout probability for disabling LoKr modules during training.
+        use_effective_conv2d (`bool`):
+            Use parameter effective decomposition for Conv2d with ksize > 1 ("Proposition 3" from FedPara paper).
+        decompose_both (`bool`):
+            Perform rank decomposition of left kronecker product matrix.
+        decompose_factor (`int`):
+            Kronecker product decomposition factor.
+        rank_dropout_scale ('bool)
+            Whether to scale the rank dropout while training, defaults to `False`.
+        target_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear/Conv1D modules are chosen,
+            excluding the output layer. If this is not specified, modules will be chosen according to the model
+            architecture. If the architecture is not known, an error will be raised -- in this case, you should specify
+            the target modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        init_weights (`bool`):
+            Whether to perform initialization of adapter weights. This defaults to `True`. Use "lycoris" to initialize
+            weights in the style of the LYCORIS repository. Passing `False` is discouraged.
+        layers_to_transform (`Union[List[int], int]`):
+            The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
+            that are specified in this list. If a single integer is passed, it will apply the transformations on the
+            layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`. This should target the
+            `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`.
+        rank_pattern (`dict`):
+            The mapping from layer names or regexp expression to ranks which are different from the default rank
+            specified by `r`. For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`.
+        alpha_pattern (`dict`):
+            The mapping from layer names or regexp expression to alphas which are different from the default alpha
+            specified by `alpha`. For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`.
+        modules_to_save (`Optional[List[str]]`):
+            List of modules apart from adapter layers to be set as trainable and saved in the final checkpoint.
+    """
+
+    r: int = field(default=8, metadata={"help": "LoKr rank"})
+    alpha: int = field(default=8, metadata={"help": "LoKr alpha"})
+    rank_dropout: float = field(
+        default=0.0, metadata={"help": "The dropout probability for rank dimension during training"}
+    )
+    module_dropout: float = field(
+        default=0.0, metadata={"help": "The dropout probability for disabling LoKr modules during training"}
+    )
+    use_effective_conv2d: bool = field(
+        default=False,
+        metadata={
+            "help": 'Use parameter effective decomposition for Conv2d 3x3 with ksize > 1 ("Proposition 3" from FedPara paper)'
+        },
+    )
+    decompose_both: bool = field(
+        default=False,
+        metadata={"help": "Perform rank decomposition of left kronecker product matrix."},
+    )
+    decompose_factor: int = field(default=-1, metadata={"help": "Kronecker product decomposition factor."})
+    rank_dropout_scale: bool = field(default=False, metadata={"help": "Rank dropout scale"})
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or regex expression of the module names to replace with LoKr."
+            "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$' "
+            "This can also be a wildcard 'all-linear' which matches all linear/Conv1D layers except the output layer."
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from LoKr."},
+    )
+    init_weights: Union[bool, Literal["lycoris"]] = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the LoKr layers with their default initialization. Can be True, False or 'lycoris'."
+                "Default is True. Don't change this setting to False, except if you know exactly what you're doing."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index."
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern. "
+            "This should target the `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`."
+        },
+    )
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from LoKr layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.LOKR
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..1c8cf1bbd984d168c4b8d2e90063e8b1b3bb741d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/layer.py
@@ -0,0 +1,425 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import math
+from typing import Any, Optional, Set, Tuple, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from peft.tuners.lycoris_utils import LycorisLayer
+
+
+class LoKrLayer(nn.Module, LycorisLayer):
+    # All names of layers that may contain adapter weights
+    adapter_layer_names = (
+        "lokr_w1",
+        "lokr_w1_a",
+        "lokr_w1_b",
+        "lokr_w2",
+        "lokr_w2_a",
+        "lokr_w2_b",
+        "lokr_t2",
+    )
+    # other_param_names is defined on parent class
+
+    def __init__(self, base_layer: nn.Module) -> None:
+        super().__init__()
+        LycorisLayer.__init__(self, base_layer)
+
+        # LoKr info
+        self.lokr_w1 = nn.ParameterDict({})
+        self.lokr_w1_a = nn.ParameterDict({})
+        self.lokr_w1_b = nn.ParameterDict({})
+        self.lokr_w2 = nn.ParameterDict({})
+        self.lokr_w2_a = nn.ParameterDict({})
+        self.lokr_w2_b = nn.ParameterDict({})
+        self.lokr_t2 = nn.ParameterDict({})
+
+    @property
+    def _available_adapters(self) -> Set[str]:
+        return {
+            *self.lokr_w1,
+            *self.lokr_w1_a,
+            *self.lokr_w1_b,
+            *self.lokr_w2,
+            *self.lokr_w2_a,
+            *self.lokr_w2_b,
+            *self.lokr_t2,
+        }
+
+    def create_adapter_parameters(
+        self,
+        adapter_name: str,
+        r: int,
+        shape,
+        use_w1: bool,
+        use_w2: bool,
+        use_effective_conv2d: bool,
+    ):
+        if use_w1:
+            self.lokr_w1[adapter_name] = nn.Parameter(torch.empty(shape[0][0], shape[1][0]))
+        else:
+            self.lokr_w1_a[adapter_name] = nn.Parameter(torch.empty(shape[0][0], r))
+            self.lokr_w1_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1][0]))
+
+        if len(shape) == 4:
+            # Conv2d
+            if use_w2:
+                self.lokr_w2[adapter_name] = nn.Parameter(torch.empty(shape[0][1], shape[1][1], *shape[2:]))
+            elif use_effective_conv2d:
+                self.lokr_t2[adapter_name] = nn.Parameter(torch.empty(r, r, shape[2], shape[3]))
+                self.lokr_w2_a[adapter_name] = nn.Parameter(torch.empty(r, shape[0][1]))  # b, 1-mode
+                self.lokr_w2_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1][1]))  # d, 2-mode
+            else:
+                self.lokr_w2_a[adapter_name] = nn.Parameter(torch.empty(shape[0][1], r))
+                self.lokr_w2_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1][1] * shape[2] * shape[3]))
+        else:
+            # Linear
+            if use_w2:
+                self.lokr_w2[adapter_name] = nn.Parameter(torch.empty(shape[0][1], shape[1][1]))
+            else:
+                self.lokr_w2_a[adapter_name] = nn.Parameter(torch.empty(shape[0][1], r))
+                self.lokr_w2_b[adapter_name] = nn.Parameter(torch.empty(r, shape[1][1]))
+
+    def reset_adapter_parameters(self, adapter_name: str):
+        if adapter_name in self.lokr_w1:
+            nn.init.zeros_(self.lokr_w1[adapter_name])
+        else:
+            nn.init.zeros_(self.lokr_w1_a[adapter_name])
+            nn.init.kaiming_uniform_(self.lokr_w1_b[adapter_name], a=math.sqrt(5))
+
+        if adapter_name in self.lokr_w2:
+            nn.init.kaiming_uniform_(self.lokr_w2[adapter_name], a=math.sqrt(5))
+        else:
+            nn.init.kaiming_uniform_(self.lokr_w2_a[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.lokr_w2_b[adapter_name], a=math.sqrt(5))
+
+        if adapter_name in self.lokr_t2:
+            nn.init.kaiming_uniform_(self.lokr_t2[adapter_name], a=math.sqrt(5))
+
+    def reset_adapter_parameters_random(self, adapter_name: str):
+        if adapter_name in self.lokr_w1:
+            nn.init.kaiming_uniform_(self.lokr_w1[adapter_name], a=math.sqrt(5))
+        else:
+            nn.init.kaiming_uniform_(self.lokr_w1_a[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.lokr_w1_b[adapter_name], a=math.sqrt(5))
+
+        if adapter_name in self.lokr_w2:
+            nn.init.kaiming_uniform_(self.lokr_w2[adapter_name], a=math.sqrt(5))
+        else:
+            nn.init.kaiming_uniform_(self.lokr_w2_a[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.lokr_w2_b[adapter_name], a=math.sqrt(5))
+
+        if adapter_name in self.lokr_t2:
+            nn.init.kaiming_uniform_(self.lokr_t2[adapter_name], a=math.sqrt(5))
+
+    # Initializes weight matrices similar to the way initialized in the LyCORIS repository.
+    def reset_adapter_parameters_lycoris_way(self, adapter_name):
+        if adapter_name in self.lokr_w1:
+            nn.init.kaiming_uniform_(self.lokr_w1[adapter_name], a=math.sqrt(5))
+        else:
+            nn.init.kaiming_uniform_(self.lokr_w1_a[adapter_name], a=math.sqrt(5))
+            nn.init.kaiming_uniform_(self.lokr_w1_b[adapter_name], a=math.sqrt(5))
+
+        if adapter_name in self.lokr_w2:
+            nn.init.zeros_(self.lokr_w2[adapter_name])
+        else:
+            nn.init.zeros_(self.lokr_w2_b[adapter_name])
+            nn.init.kaiming_uniform_(self.lokr_w2_a[adapter_name], a=math.sqrt(5))
+
+        if adapter_name in self.lokr_t2:
+            nn.init.kaiming_uniform_(self.lokr_t2[adapter_name], a=math.sqrt(5))
+
+    def update_layer(
+        self,
+        adapter_name: str,
+        r: int,
+        alpha: float,
+        rank_dropout: float,
+        module_dropout: float,
+        init_weights: bool,
+        use_effective_conv2d: bool,
+        decompose_both: bool,
+        decompose_factor: int,
+        **kwargs,
+    ) -> None:
+        """Internal function to create lokr adapter
+
+        Args:
+            adapter_name (`str`): Name for the adapter to add.
+            r (`int`): Rank for the added adapter.
+            alpha (`float`): Alpha for the added adapter.
+            rank_dropout (`float`): The dropout probability for rank dimension during training
+            module_dropout (`float`): The dropout probability for disabling adapter during training.
+            init_weights (`bool`): Whether to initialize adapter weights.
+            use_effective_conv2d (`bool`): Use parameter effective decomposition for Conv2d with ksize > 1.
+            decompose_both (`bool`): Perform rank decomposition of left kronecker product matrix.
+            decompose_factor (`int`): Kronecker product decomposition factor.
+        """
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+
+        self.r[adapter_name] = r
+        self.alpha[adapter_name] = alpha
+        self.scaling[adapter_name] = alpha / r
+        self.rank_dropout[adapter_name] = rank_dropout
+        self.module_dropout[adapter_name] = module_dropout
+        self.rank_dropout_scale[adapter_name] = kwargs["rank_dropout_scale"]
+        base_layer = self.get_base_layer()
+
+        # Determine shape of LoKr weights
+        if isinstance(base_layer, nn.Linear):
+            in_dim, out_dim = base_layer.in_features, base_layer.out_features
+
+            in_m, in_n = factorization(in_dim, decompose_factor)
+            out_l, out_k = factorization(out_dim, decompose_factor)
+            shape = ((out_l, out_k), (in_m, in_n))  # ((a, b), (c, d)), out_dim = a*c, in_dim = b*d
+
+            use_w1 = not (decompose_both and r < max(shape[0][0], shape[1][0]) / 2)
+            use_w2 = not (r < max(shape[0][1], shape[1][1]) / 2)
+            use_effective_conv2d = False
+        elif isinstance(base_layer, nn.Conv2d):
+            in_dim, out_dim = base_layer.in_channels, base_layer.out_channels
+            k_size = base_layer.kernel_size
+
+            in_m, in_n = factorization(in_dim, decompose_factor)
+            out_l, out_k = factorization(out_dim, decompose_factor)
+            shape = ((out_l, out_k), (in_m, in_n), *k_size)  # ((a, b), (c, d), *k_size)
+
+            use_w1 = not (decompose_both and r < max(shape[0][0], shape[1][0]) / 2)
+            use_w2 = r >= max(shape[0][1], shape[1][1]) / 2
+            use_effective_conv2d = use_effective_conv2d and base_layer.kernel_size != (1, 1)
+        else:
+            raise TypeError(f"LoKr is not implemented for base layers of type {type(base_layer).__name__}")
+
+        # Create weights with provided shape
+        self.create_adapter_parameters(adapter_name, r, shape, use_w1, use_w2, use_effective_conv2d)
+
+        # Initialize weights
+        if init_weights:
+            if init_weights == "lycoris":
+                self.reset_adapter_parameters_lycoris_way(adapter_name)
+            else:
+                self.reset_adapter_parameters(adapter_name)
+        else:
+            self.reset_adapter_parameters_random(adapter_name)
+
+        # Move new weights to device
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def get_delta_weight(self, adapter_name: str) -> torch.Tensor:
+        # https://github.com/KohakuBlueleaf/LyCORIS/blob/e4259b870d3354a9615a96be61cb5d07455c58ea/lycoris/modules/lokr.py#L224
+        if adapter_name in self.lokr_w1:
+            w1 = self.lokr_w1[adapter_name]
+        else:
+            w1 = self.lokr_w1_a[adapter_name] @ self.lokr_w1_b[adapter_name]
+
+        if adapter_name in self.lokr_w2:
+            w2 = self.lokr_w2[adapter_name]
+        elif adapter_name in self.lokr_t2:
+            w2 = make_weight_cp(self.lokr_t2[adapter_name], self.lokr_w2_a[adapter_name], self.lokr_w2_b[adapter_name])
+        else:
+            w2 = self.lokr_w2_a[adapter_name] @ self.lokr_w2_b[adapter_name]
+
+        # Make weights with Kronecker product
+        weight = make_kron(w1, w2, self.scaling[adapter_name])
+        weight = weight.reshape(self.get_base_layer().weight.shape)
+
+        # Perform rank dropout during training - drop rows of addition weights
+        rank_dropout = self.rank_dropout[adapter_name]
+        if self.training and rank_dropout:
+            drop = (torch.rand(weight.size(0)) > rank_dropout).float()
+            drop = drop.view(-1, *[1] * len(weight.shape[1:])).to(weight.device)
+            if self.rank_dropout_scale[adapter_name]:
+                drop /= drop.mean()
+            weight *= drop
+
+        return weight
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+
+            # Execute all the adapters
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self._available_adapters:
+                    continue
+
+                module_dropout = self.module_dropout[active_adapter]
+
+                # Modify current execution weights
+                if (not self.training) or (self.training and torch.rand(1) > module_dropout):
+                    result = result + self._get_delta_activations(active_adapter, x, *args, **kwargs)
+
+        result = result.to(previous_dtype)
+        return result
+
+
+class Linear(LoKrLayer):
+    """LoKr implemented in Linear layer"""
+
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        device: Optional[Union[str, torch.device]] = None,
+        dtype: Optional[torch.dtype] = None,
+        adapter_name: str = "default",
+        r: int = 0,
+        alpha: float = 0.0,
+        rank_dropout: float = 0.0,
+        module_dropout: float = 0.0,
+        init_weights: bool = True,
+        **kwargs,
+    ):
+        super().__init__(base_layer)
+
+        # Create adapter and set it active
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, alpha, rank_dropout, module_dropout, init_weights, **kwargs)
+
+    def _get_delta_activations(
+        self, adapter_name: str, input: torch.Tensor, *args: Any, **kwargs: Any
+    ) -> torch.Tensor:
+        delta_weight = self.get_delta_weight(adapter_name)
+        # don't add bias here, because the bias is already included in the output of the base_layer
+        return F.linear(input, delta_weight)
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lokr." + rep
+
+
+class Conv2d(LoKrLayer):
+    """LoKr implemented in Conv2d layer"""
+
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        device: Optional[Union[str, torch.device]] = None,
+        dtype: Optional[torch.dtype] = None,
+        adapter_name: str = "default",
+        r: int = 0,
+        alpha: float = 0.0,
+        rank_dropout: float = 0.0,
+        module_dropout: float = 0.0,
+        use_effective_conv2d: bool = False,
+        init_weights: bool = True,
+        **kwargs,
+    ):
+        super().__init__(base_layer)
+
+        # Create adapter and set it active
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name, r, alpha, rank_dropout, module_dropout, init_weights, use_effective_conv2d, **kwargs
+        )
+
+    def _get_delta_activations(
+        self, adapter_name: str, input: torch.Tensor, *args: Any, **kwargs: Any
+    ) -> torch.Tensor:
+        delta_weight = self.get_delta_weight(adapter_name)
+        # don't add bias here, because the bias is already included in the output of the base_layer
+        base_layer = self.get_base_layer()
+        return F.conv2d(
+            input,
+            delta_weight,
+            stride=base_layer.stride,
+            padding=base_layer.padding,
+            dilation=base_layer.dilation,
+            groups=base_layer.groups,
+        )
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lokr." + rep
+
+
+# Below code is a direct copy from https://github.com/KohakuBlueleaf/LyCORIS/blob/eb460098187f752a5d66406d3affade6f0a07ece/lycoris/modules/lokr.py#L11
+
+
+def factorization(dimension: int, factor: int = -1) -> Tuple[int, int]:
+    """Factorizes the provided number into the product of two numbers
+
+    Args:
+        dimension (`int`): The number that needs to be factorized.
+        factor (`int`, optional):
+            Factorization divider. The algorithm will try to output two numbers, one of each will be as close to the
+            factor as possible. If -1 is provided, the decomposition algorithm would try to search dividers near the
+            square root of the dimension. Defaults to -1.
+
+    Returns:
+        Tuple[`int`, `int`]: A tuple of two numbers, whose product is equal to the provided number. The first number is
+        always less than or equal to the second.
+
+    Example:
+        ```py
+        >>> factorization(256, factor=-1)
+        (16, 16)
+
+        >>> factorization(128, factor=-1)
+        (8, 16)
+
+        >>> factorization(127, factor=-1)
+        (1, 127)
+
+        >>> factorization(128, factor=4)
+        (4, 32)
+        ```
+    """
+
+    if factor > 0 and (dimension % factor) == 0:
+        m = factor
+        n = dimension // factor
+        return m, n
+    if factor == -1:
+        factor = dimension
+    m, n = 1, dimension
+    length = m + n
+    while m < n:
+        new_m = m + 1
+        while dimension % new_m != 0:
+            new_m += 1
+        new_n = dimension // new_m
+        if new_m + new_n > length or new_m > factor:
+            break
+        else:
+            m, n = new_m, new_n
+    if m > n:
+        n, m = m, n
+    return m, n
+
+
+def make_weight_cp(t, wa, wb):
+    rebuild2 = torch.einsum("i j k l, i p, j r -> p r k l", t, wa, wb)  # [c, d, k1, k2]
+    return rebuild2
+
+
+def make_kron(w1, w2, scale=1.0):
+    if len(w2.shape) == 4:
+        w1 = w1.unsqueeze(2).unsqueeze(2)
+    w2 = w2.contiguous()
+    rebuild = torch.kron(w1, w2)
+
+    return rebuild * scale
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..da52086bb2bfb77d4502478212d2f69a085c146f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lokr/model.py
@@ -0,0 +1,114 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Dict, Type, Union
+
+import torch
+from torch import nn
+
+from peft.tuners.lycoris_utils import LycorisConfig, LycorisTuner
+from peft.utils.other import get_pattern_key
+
+from .layer import Conv2d, Linear, LoKrLayer
+
+
+class LoKrModel(LycorisTuner):
+    """
+    Creates Low-Rank Kronecker Product model from a pretrained model. The original method is partially described in
+    https://arxiv.org/abs/2108.06098 and in https://arxiv.org/abs/2309.14859 Current implementation heavily borrows
+    from
+    https://github.com/KohakuBlueleaf/LyCORIS/blob/eb460098187f752a5d66406d3affade6f0a07ece/lycoris/modules/lokr.py
+
+    Args:
+        model (`torch.nn.Module`): The model to which the adapter tuner layers will be attached.
+        config ([`LoKrConfig`]): The configuration of the LoKr model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The LoKr model.
+
+    Example:
+        ```py
+        >>> from diffusers import StableDiffusionPipeline
+        >>> from peft import LoKrModel, LoKrConfig
+
+        >>> config_te = LoKrConfig(
+        ...     r=8,
+        ...     lora_alpha=32,
+        ...     target_modules=["k_proj", "q_proj", "v_proj", "out_proj", "fc1", "fc2"],
+        ...     rank_dropout=0.0,
+        ...     module_dropout=0.0,
+        ...     init_weights=True,
+        ... )
+        >>> config_unet = LoKrConfig(
+        ...     r=8,
+        ...     lora_alpha=32,
+        ...     target_modules=[
+        ...         "proj_in",
+        ...         "proj_out",
+        ...         "to_k",
+        ...         "to_q",
+        ...         "to_v",
+        ...         "to_out.0",
+        ...         "ff.net.0.proj",
+        ...         "ff.net.2",
+        ...     ],
+        ...     rank_dropout=0.0,
+        ...     module_dropout=0.0,
+        ...     init_weights=True,
+        ...     use_effective_conv2d=True,
+        ... )
+
+        >>> model = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+        >>> model.text_encoder = LoKrModel(model.text_encoder, config_te, "default")
+        >>> model.unet = LoKrModel(model.unet, config_unet, "default")
+        ```
+
+    **Attributes**:
+        - **model** ([`~torch.nn.Module`]) -- The model to be adapted.
+        - **peft_config** ([`LoKrConfig`]): The configuration of the LoKr model.
+    """
+
+    prefix: str = "lokr_"
+    layers_mapping: Dict[Type[torch.nn.Module], Type[LoKrLayer]] = {
+        torch.nn.Conv2d: Conv2d,
+        torch.nn.Linear: Linear,
+    }
+
+    def _create_and_replace(
+        self,
+        config: LycorisConfig,
+        adapter_name: str,
+        target: Union[LoKrLayer, nn.Module],
+        target_name: str,
+        parent: nn.Module,
+        current_key: str,
+    ) -> None:
+        """
+        A private method to create and replace the target module with the adapter module.
+        """
+        r_key = get_pattern_key(config.rank_pattern.keys(), current_key)
+        alpha_key = get_pattern_key(config.alpha_pattern.keys(), current_key)
+        kwargs = config.to_dict()
+        kwargs["r"] = config.rank_pattern.get(r_key, config.r)
+        kwargs["alpha"] = config.alpha_pattern.get(alpha_key, config.alpha)
+        kwargs["rank_dropout_scale"] = config.rank_dropout_scale
+
+        if isinstance(target, LoKrLayer):
+            target.update_layer(adapter_name, **kwargs)
+        else:
+            new_module = self._create_new_module(config, adapter_name, target, **kwargs)
+            self._replace_module(parent, target_name, new_module, target)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..70036879d4f29b08c83791569b9b089ce3cee1fd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/__init__.py
@@ -0,0 +1,60 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available, is_eetq_available
+from peft.utils import register_peft_method
+
+from .config import EvaConfig, LoftQConfig, LoraConfig, LoraRuntimeConfig
+from .eva import get_eva_state_dict, initialize_lora_eva_weights
+from .gptq import GPTQLoraLinear
+from .layer import Conv2d, Conv3d, Embedding, Linear, LoraLayer
+from .model import LoraModel
+
+
+__all__ = [
+    "Conv2d",
+    "Conv3d",
+    "Embedding",
+    "EvaConfig",
+    "GPTQLoraLinear",
+    "Linear",
+    "LoftQConfig",
+    "LoraConfig",
+    "LoraLayer",
+    "LoraModel",
+    "LoraRuntimeConfig",
+    "get_eva_state_dict",
+    "initialize_lora_eva_weights",
+]
+
+register_peft_method(name="lora", config_cls=LoraConfig, model_cls=LoraModel, is_mixed_compatible=True)
+
+
+def __getattr__(name):
+    if (name == "Linear8bitLt") and is_bnb_available():
+        from .bnb import Linear8bitLt
+
+        return Linear8bitLt
+
+    if (name == "Linear4bit") and is_bnb_4bit_available():
+        from .bnb import Linear4bit
+
+        return Linear4bit
+
+    if (name == "EetqLoraLinear") and is_eetq_available():
+        from .eetq import EetqLoraLinear
+
+        return EetqLoraLinear
+
+    raise AttributeError(f"module {__name__} has no attribute {name}")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/aqlm.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/aqlm.py
new file mode 100644
index 0000000000000000000000000000000000000000..81c7cdbb4ec45ed4d86fd08ab26f4baab64c0cab
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/aqlm.py
@@ -0,0 +1,114 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Any, Optional
+
+import torch
+
+from peft.import_utils import is_aqlm_available
+from peft.tuners.lora.layer import LoraLayer
+from peft.tuners.tuners_utils import BaseTunerLayer
+
+
+if is_aqlm_available():
+    from aqlm import QuantizedLinear
+
+
+class AqlmLoraLinear(torch.nn.Module, LoraLayer):
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        init_lora_weights: bool = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+        **kwargs,
+    ):
+        if use_dora:
+            raise ValueError(f"{self.__class__.__name__} does not support DoRA yet, please set it to False")
+
+        super().__init__()
+        LoraLayer.__init__(self, base_layer)
+
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name,
+            r,
+            lora_alpha=lora_alpha,
+            lora_dropout=lora_dropout,
+            init_lora_weights=init_lora_weights,
+            use_rslora=use_rslora,
+            use_dora=use_dora,
+            lora_bias=lora_bias,
+        )
+
+    def forward(self, x: torch.Tensor):
+        # note: logic differs from default Linear because merging is not supported
+        result = self.base_layer(x)
+
+        if self.disable_adapters:
+            return result
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.lora_A.keys():
+                continue
+            lora_A = self.lora_A[active_adapter]
+            lora_B = self.lora_B[active_adapter]
+            dropout = self.lora_dropout[active_adapter]
+            scaling = self.scaling[active_adapter]
+
+            requires_conversion = not torch.is_autocast_enabled()
+            if requires_conversion:
+                expected_dtype = result.dtype
+                x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+            output = lora_B(lora_A(dropout(x)))
+            if requires_conversion:
+                output = output.to(expected_dtype)
+            output = output * scaling
+            result += output
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+    # TODO: Check if it is better as suggested by users https://github.com/PanQiWei/AutoGPTQ/pull/102
+    # def reset_lora_parameters(self, adapter_name):
+    #     if adapter_name in self.lora_A.keys():
+    #         torch.nn.init.xavier_uniform_(self.lora_A[adapter_name].weight)
+    #         torch.nn.init.zeros_(self.lora_B[adapter_name].weight)
+
+
+def dispatch_aqlm(
+    target: torch.nn.Module,
+    adapter_name: str,
+    **kwargs: Any,
+) -> Optional[torch.nn.Module]:
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    if is_aqlm_available() and isinstance(target_base_layer, QuantizedLinear):
+        new_module = AqlmLoraLinear(target, adapter_name, **kwargs)
+        target.qweight = target_base_layer.codes
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/awq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/awq.py
new file mode 100644
index 0000000000000000000000000000000000000000..61eb487ad6756e1e31b612ec7a8e4649b860e4c5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/awq.py
@@ -0,0 +1,121 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import importlib.metadata as importlib_metadata
+from typing import Any, Optional
+
+import packaging.version
+import torch
+
+from peft.import_utils import is_auto_awq_available
+from peft.tuners.lora.layer import LoraLayer
+from peft.tuners.tuners_utils import BaseTunerLayer
+
+
+class AwqLoraLinear(torch.nn.Module, LoraLayer):
+    def __init__(
+        self,
+        base_layer,
+        adapter_name,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        init_lora_weights: bool = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+        **kwargs,
+    ):
+        if use_dora:
+            raise ValueError(f"{self.__class__.__name__} does not support DoRA yet, please set it to False")
+
+        super().__init__()
+        LoraLayer.__init__(self, base_layer)
+
+        # self.base_layer and self.quant_linear_module are the same; we need the former for consistency and the latter
+        # for backwards compatibility
+        self.quant_linear_module = base_layer
+
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name,
+            r,
+            lora_alpha=lora_alpha,
+            lora_dropout=lora_dropout,
+            init_lora_weights=init_lora_weights,
+            use_rslora=use_rslora,
+            use_dora=use_dora,
+            lora_bias=lora_bias,
+        )
+
+    def forward(self, x: torch.Tensor):
+        result = self.quant_linear_module(x)
+
+        if self.disable_adapters:
+            return result
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.lora_A.keys():
+                continue
+            lora_A = self.lora_A[active_adapter]
+            lora_B = self.lora_B[active_adapter]
+            dropout = self.lora_dropout[active_adapter]
+            scaling = self.scaling[active_adapter]
+
+            requires_conversion = not torch.is_autocast_enabled()
+            if requires_conversion:
+                expected_dtype = result.dtype
+                x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+            output = lora_B(lora_A(dropout(x)))
+            if requires_conversion:
+                output = output.to(expected_dtype)
+            output = output * scaling
+            result = result + output
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+
+def dispatch_awq(
+    target: torch.nn.Module,
+    adapter_name: str,
+    **kwargs: Any,
+) -> Optional[torch.nn.Module]:
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    if is_auto_awq_available():
+        from awq.modules.linear import WQLinear_GEMM
+
+        if isinstance(target_base_layer, WQLinear_GEMM):
+            # Raise the error only at the dispatch level
+            AUTOAWQ_MINIMUM_VERSION = packaging.version.parse("0.2.0")
+            version_autoawq = packaging.version.parse(importlib_metadata.version("autoawq"))
+
+            if AUTOAWQ_MINIMUM_VERSION > version_autoawq:
+                raise ImportError(
+                    f"Found an incompatible version of auto-awq. Found version {version_autoawq}, "
+                    f"but only versions above {AUTOAWQ_MINIMUM_VERSION} are supported for PEFT."
+                )
+
+            new_module = AwqLoraLinear(target, adapter_name, **kwargs)
+            target.qweight = target_base_layer.qweight
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/bnb.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/bnb.py
new file mode 100644
index 0000000000000000000000000000000000000000..36dcc724682a08b3a23229970f13612c895f7277
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/bnb.py
@@ -0,0 +1,562 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from typing import Any, Optional
+
+import bitsandbytes as bnb
+import torch
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+from peft.utils.integrations import dequantize_bnb_weight
+from peft.utils.other import transpose
+
+from .layer import LoraLayer
+
+
+if is_bnb_available():
+
+    class Linear8bitLt(torch.nn.Module, LoraLayer):
+        # Lora implemented in a dense layer
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            r: int = 0,
+            lora_alpha: int = 1,
+            lora_dropout: float = 0.0,
+            init_lora_weights: bool = True,
+            use_rslora: bool = False,
+            use_dora: bool = False,
+            lora_bias: bool = False,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            LoraLayer.__init__(self, base_layer)
+            self.fan_in_fan_out = False
+
+            self._active_adapter = adapter_name
+            self.update_layer(
+                adapter_name,
+                r,
+                lora_alpha=lora_alpha,
+                lora_dropout=lora_dropout,
+                init_lora_weights=init_lora_weights,
+                use_rslora=use_rslora,
+                use_dora=use_dora,
+                lora_bias=lora_bias,
+            )
+
+        def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+            """
+            Merge the active adapter weights into the base weights
+
+            Args:
+                safe_merge (`bool`, *optional*):
+                    If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                    before merging the weights. This is useful if you want to check if the merge operation will produce
+                    NaNs. Defaults to `False`.
+                adapter_names (`list[str]`, *optional*):
+                    The list of adapter names that should be merged. If None, all active adapters will be merged.
+                    Defaults to `None`.
+            """
+            adapter_names = check_adapters_to_merge(self, adapter_names)
+            if not adapter_names:
+                # no adapter to merge
+                return
+
+            for active_adapter in adapter_names:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                warnings.warn(
+                    "Merge lora module to 8-bit linear may get different generations due to rounding errors."
+                )
+                lora_data = self.get_delta_weight(active_adapter)
+
+                weight = self.get_base_layer().weight
+                state = self.get_base_layer().state
+                if state.SCB is None:
+                    state.SCB = weight.SCB
+
+                # Dequantize the result of identity matrix and int8 weight because bitsandbytes does not support int8
+                # dequantization directly
+                output = dequantize_bnb_weight(weight, state=state)
+                if not self.use_dora[active_adapter]:
+                    w_data = output.to(lora_data.dtype).to(lora_data.device) + lora_data
+                else:
+                    # handle dora
+                    # since output already includes scaling, set it to 1 here
+                    weight_norm = (
+                        self.lora_magnitude_vector[active_adapter]
+                        .get_weight_norm(output, lora_data, scaling=1)
+                        .detach()
+                    )
+                    # We need to cache weight_norm because it has to be based on the original weights. We
+                    # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                    # different value
+                    self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                    dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                    w_data = dora_factor.view(-1, 1) * (output + lora_data)
+
+                if safe_merge and not torch.isfinite(w_data).all():
+                    raise ValueError(
+                        f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                    )
+
+                self.get_base_layer().weight = bnb.nn.Int8Params(
+                    w_data.to("cpu"), requires_grad=False, has_fp16_weights=weight.has_fp16_weights
+                ).to(weight.device)
+                if self.lora_bias[active_adapter]:
+                    bias_data = self.get_base_layer().bias.data + self.lora_B[active_adapter].bias
+                    if safe_merge and not torch.isfinite(bias_data):
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+                    self.get_base_layer().bias.data = bias_data
+
+                state.reset_grads()
+                self.merged_adapters.append(active_adapter)
+
+        def unmerge(self) -> None:
+            """
+            This method unmerges all merged adapter layers from the base weights.
+            """
+            if not self.merged:
+                warnings.warn("Already unmerged. Nothing to do.")
+                return
+
+            while len(self.merged_adapters) > 0:
+                active_adapter = self.merged_adapters.pop()
+                if active_adapter not in self.lora_A.keys():
+                    continue
+                warnings.warn(
+                    "Unmerge lora module to 8-bit linear may get different generations due to rounding errors."
+                )
+                lora_data = self.get_delta_weight(active_adapter)
+
+                weight = self.get_base_layer().weight
+                state = self.get_base_layer().state
+                if state.SCB is None:
+                    state.SCB = weight.SCB
+                output = dequantize_bnb_weight(weight, state=state)
+
+                if not self.use_dora[active_adapter]:
+                    w_data = output.to(lora_data.dtype).to(lora_data.device) - lora_data
+                else:
+                    weight_norm = self._cache_pop(f"{active_adapter}-weight_norm")
+                    dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                    w_data = output.data / dora_factor.view(-1, 1) - lora_data
+
+                self.get_base_layer().weight = bnb.nn.Int8Params(
+                    w_data.to("cpu"), requires_grad=False, has_fp16_weights=weight.has_fp16_weights
+                ).to(weight.device)
+
+                if self.lora_bias[active_adapter]:
+                    self.get_base_layer().bias.data -= self.lora_B[active_adapter].bias
+                state.reset_grads()
+
+        def get_delta_weight(self, adapter):
+            return (
+                transpose(
+                    self.lora_B[adapter].weight @ self.lora_A[adapter].weight,
+                    False,
+                )
+                * self.scaling[adapter]
+            )
+
+        def _mixed_batch_forward(
+            self, x: torch.Tensor, *args: Any, adapter_names: list[str], **kwargs: Any
+        ) -> torch.Tensor:
+            # This is a special method that handles the case when users pass the argument `adapter_names`. This is an
+            # extra argument that allows mixing different adapters in the same batch at inference time.
+            result = self.base_layer(x, *args, **kwargs)
+
+            unique_adapters = set(adapter_names)
+            sub_batch_indices_list = []
+            for adapter in unique_adapters:
+                sub_batch_indices_list.append([index for index, item in enumerate(adapter_names) if item == adapter])
+
+            for i, active_adapter in enumerate(unique_adapters):
+                if active_adapter == "__base__":
+                    continue
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+
+                requires_conversion = not torch.is_autocast_enabled()
+                if requires_conversion:
+                    expected_dtype = result.dtype
+                    x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                # getting the sub-batch, passing it to LoRA layers and updating the corresponding indices of the linear
+                # layer output
+                sub_batch = x[sub_batch_indices_list[i]]
+                output = lora_B(lora_A(dropout(sub_batch))) * scaling
+                if requires_conversion:
+                    output = output.to(expected_dtype)
+                result[sub_batch_indices_list[i]] += output
+
+            return result
+
+        def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+            self._check_forward_args(x, *args, **kwargs)
+            adapter_names = kwargs.pop("adapter_names", None)
+
+            if self.disable_adapters:
+                if self.merged:
+                    self.unmerge()
+                result = self.base_layer(x, *args, **kwargs)
+            elif adapter_names is not None:
+                result = self._mixed_batch_forward(x, *args, adapter_names=adapter_names, **kwargs)
+            elif self.merged:
+                result = self.base_layer(x, *args, **kwargs)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+                for active_adapter in self.active_adapters:
+                    if active_adapter not in self.lora_A.keys():
+                        continue
+                    lora_A = self.lora_A[active_adapter]
+                    lora_B = self.lora_B[active_adapter]
+                    dropout = self.lora_dropout[active_adapter]
+                    scaling = self.scaling[active_adapter]
+
+                    requires_conversion = not torch.is_autocast_enabled()
+                    if requires_conversion:
+                        expected_dtype = result.dtype
+                        x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                    if not self.use_dora[active_adapter]:
+                        output = lora_B(lora_A(dropout(x))) * scaling
+                    else:
+                        if isinstance(dropout, torch.nn.Identity) or not self.training:
+                            base_result = result
+                        else:
+                            x = dropout(x)
+                            base_result = None
+
+                        output = self.lora_magnitude_vector[active_adapter](
+                            x,
+                            lora_A=lora_A,
+                            lora_B=lora_B,
+                            scaling=scaling,
+                            base_layer=self.get_base_layer(),
+                            base_result=base_result,
+                        )
+                    if requires_conversion:
+                        output = output.to(expected_dtype)
+                    result = result + output
+
+            return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "lora." + rep
+
+    def dispatch_bnb_8bit(target: torch.nn.Module, adapter_name: str, **kwargs):
+        new_module = None
+
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        loaded_in_8bit = kwargs.get("loaded_in_8bit", False)
+        if loaded_in_8bit and isinstance(target_base_layer, bnb.nn.Linear8bitLt):
+            eightbit_kwargs = kwargs.copy()
+            eightbit_kwargs.update(
+                {
+                    "has_fp16_weights": target.state.has_fp16_weights,
+                    "threshold": target.state.threshold,
+                    "index": target.index,
+                }
+            )
+            new_module = Linear8bitLt(target, adapter_name, **eightbit_kwargs)
+
+        return new_module
+
+
+if is_bnb_4bit_available():
+
+    class Linear4bit(torch.nn.Module, LoraLayer):
+        # Lora implemented in a dense layer
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            r: int = 0,
+            lora_alpha: int = 1,
+            lora_dropout: float = 0.0,
+            init_lora_weights: bool = True,
+            use_rslora: bool = False,
+            use_dora: bool = False,
+            lora_bias: bool = False,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            LoraLayer.__init__(self, base_layer)
+            self.fan_in_fan_out = False
+
+            self._active_adapter = adapter_name
+            self.update_layer(
+                adapter_name,
+                r,
+                lora_alpha=lora_alpha,
+                lora_dropout=lora_dropout,
+                init_lora_weights=init_lora_weights,
+                use_rslora=use_rslora,
+                use_dora=use_dora,
+                lora_bias=lora_bias,
+            )
+
+        def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+            """
+            Merge the active adapter weights into the base weights
+
+            Args:
+                safe_merge (`bool`, *optional*):
+                    If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                    before merging the weights. This is useful if you want to check if the merge operation will produce
+                    NaNs. Defaults to `False`.
+                adapter_names (`list[str]`, *optional*):
+                    The list of adapter names that should be merged. If None, all active adapters will be merged.
+                    Defaults to `None`.
+            """
+            adapter_names = check_adapters_to_merge(self, adapter_names)
+            if not adapter_names:
+                # no adapter to merge
+                return
+
+            for active_adapter in adapter_names:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                warnings.warn(
+                    "Merge lora module to 4-bit linear may get different generations due to rounding errors."
+                )
+                # Refer to https://gist.github.com/ChrisHayduk/1a53463331f52dca205e55982baf9930
+                weight = self.get_base_layer().weight
+                kwargs = weight.__dict__
+                lora_data = self.get_delta_weight(active_adapter)
+
+                output = dequantize_bnb_weight(weight, state=weight.quant_state)
+                if not self.use_dora[active_adapter]:
+                    w_data = output + lora_data
+                else:
+                    # handle dora
+                    # since output already includes scaling, set it to 1 here
+                    weight_norm = (
+                        self.lora_magnitude_vector[active_adapter]
+                        .get_weight_norm(output, lora_data, scaling=1)
+                        .detach()
+                    )
+                    # We need to cache weight_norm because it has to be based on the original weights. We
+                    # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                    # different value
+                    self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                    dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                    w_data = dora_factor.view(-1, 1) * (output + lora_data)
+
+                if safe_merge and not torch.isfinite(w_data).all():
+                    raise ValueError(
+                        f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                    )
+                if "bnb_quantized" in kwargs:
+                    kwargs["bnb_quantized"] = False
+                kwargs["requires_grad"] = False
+                kwargs.pop("data", None)
+                # torch.compile can introduce attributes preceded by '_', remove them
+                kwargs = {k: v for k, v in kwargs.items() if not k.startswith("_")}
+                self.get_base_layer().weight = bnb.nn.Params4bit(w_data.to("cpu"), **kwargs).to(weight.device)
+                if self.lora_bias[active_adapter]:
+                    bias_data = self.get_base_layer().bias.data + self.lora_B[active_adapter].bias
+                    if safe_merge and not torch.isfinite(bias_data):
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+                    self.get_base_layer().bias.data = bias_data
+
+                self.merged_adapters.append(active_adapter)
+
+        def unmerge(self) -> None:
+            """
+            This method unmerges all merged adapter layers from the base weights.
+            """
+            if not self.merged:
+                warnings.warn("Already unmerged. Nothing to do.")
+                return
+
+            while len(self.merged_adapters) > 0:
+                active_adapter = self.merged_adapters.pop()
+                if active_adapter not in self.lora_A.keys():
+                    continue
+                warnings.warn(
+                    "Unmerge lora module to 4-bit linear may get different generations due to rounding errors."
+                )
+
+                lora_data = self.get_delta_weight(active_adapter)
+                weight = self.get_base_layer().weight
+                kwargs = weight.__dict__
+                output = dequantize_bnb_weight(weight, state=weight.quant_state)
+
+                if not self.use_dora[active_adapter]:
+                    w_data = output - lora_data
+                else:
+                    weight_norm = self._cache_pop(f"{active_adapter}-weight_norm")
+                    dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                    w_data = output.data / dora_factor.view(-1, 1) - lora_data
+
+                if "bnb_quantized" in kwargs:
+                    kwargs["bnb_quantized"] = False
+                kwargs["requires_grad"] = False
+                kwargs.pop("data", None)
+                self.get_base_layer().weight = bnb.nn.Params4bit(w_data.to("cpu"), **kwargs).to(weight.device)
+                if self.lora_bias[active_adapter]:
+                    self.get_base_layer().bias.data -= self.lora_B[active_adapter].bias
+
+        def get_delta_weight(self, adapter):
+            return (
+                transpose(
+                    self.lora_B[adapter].weight @ self.lora_A[adapter].weight,
+                    False,
+                )
+                * self.scaling[adapter]
+            )
+
+        def _mixed_batch_forward(
+            self, x: torch.Tensor, *args: Any, adapter_names: list[str], **kwargs: Any
+        ) -> torch.Tensor:
+            # This is a special method that handles the case when users pass the argument `adapter_names`. This is an
+            # extra argument that allows mixing different adapters in the same batch at inference time.
+            result = self.base_layer(x, *args, **kwargs)
+
+            unique_adapters = set(adapter_names)
+            sub_batch_indices_list = []
+            for adapter in unique_adapters:
+                sub_batch_indices_list.append([index for index, item in enumerate(adapter_names) if item == adapter])
+
+            for i, active_adapter in enumerate(unique_adapters):
+                if active_adapter == "__base__":
+                    continue
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+
+                requires_conversion = not torch.is_autocast_enabled()
+                if requires_conversion:
+                    expected_dtype = result.dtype
+                    x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                # getting the sub-batch, passing it to LoRA layers and updating the corresponding indices of the linear
+                # layer output
+                sub_batch = x[sub_batch_indices_list[i]]
+                output = lora_B(lora_A(dropout(sub_batch))) * scaling
+                if requires_conversion:
+                    output = output.to(expected_dtype)
+                result[sub_batch_indices_list[i]] += output
+
+            return result
+
+        def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+            self._check_forward_args(x, *args, **kwargs)
+            adapter_names = kwargs.pop("adapter_names", None)
+
+            if self.disable_adapters:
+                if self.merged:
+                    self.unmerge()
+                result = self.base_layer(x, *args, **kwargs)
+            elif adapter_names is not None:
+                result = self._mixed_batch_forward(x, *args, adapter_names=adapter_names, **kwargs)
+            elif self.merged:
+                result = self.base_layer(x, *args, **kwargs)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+                # As per Tim Dettmers, for 4bit, we need to defensively clone here.
+                # The reason is that in some cases, an error can occur that backprop
+                # does not work on a manipulated view. This issue may be solved with
+                # newer PyTorch versions but this would need extensive testing to be
+                # sure.
+                result = result.clone()
+
+                for active_adapter in self.active_adapters:
+                    if active_adapter not in self.lora_A.keys():
+                        continue
+                    lora_A = self.lora_A[active_adapter]
+                    lora_B = self.lora_B[active_adapter]
+                    dropout = self.lora_dropout[active_adapter]
+                    scaling = self.scaling[active_adapter]
+
+                    requires_conversion = not torch.is_autocast_enabled()
+                    if requires_conversion:
+                        expected_dtype = result.dtype
+                        x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                    if not self.use_dora[active_adapter]:
+                        output = lora_B(lora_A(dropout(x))) * scaling
+                    else:
+                        if isinstance(dropout, torch.nn.Identity) or not self.training:
+                            base_result = result
+                        else:
+                            x = dropout(x)
+                            base_result = None
+
+                        output = self.lora_magnitude_vector[active_adapter](
+                            x,
+                            lora_A=lora_A,
+                            lora_B=lora_B,
+                            scaling=scaling,
+                            base_layer=self.get_base_layer(),
+                            base_result=base_result,
+                        )
+                    if requires_conversion:
+                        output = output.to(expected_dtype)
+                    result = result + output
+
+            return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "lora." + rep
+
+    def dispatch_bnb_4bit(target: torch.nn.Module, adapter_name: str, **kwargs):
+        new_module = None
+
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        loaded_in_4bit = kwargs.get("loaded_in_4bit", False)
+        if loaded_in_4bit and is_bnb_4bit_available() and isinstance(target_base_layer, bnb.nn.Linear4bit):
+            fourbit_kwargs = kwargs.copy()
+            fourbit_kwargs.update(
+                {
+                    "compute_dtype": target_base_layer.compute_dtype,
+                    "compress_statistics": target_base_layer.weight.compress_statistics,
+                    "quant_type": target_base_layer.weight.quant_type,
+                }
+            )
+            new_module = Linear4bit(target, adapter_name, **fourbit_kwargs)
+
+        return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..9db8ed94e63769058c425de81becf4cd86c8a1d5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/config.py
@@ -0,0 +1,641 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import warnings
+from dataclasses import dataclass, field
+from typing import Literal, Optional, Union
+
+from torch import nn
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class LoraRuntimeConfig:
+    """
+    This is the sub-configuration class to store the runtime configurations for the model.
+
+    Args:
+        ephemeral_gpu_offload (`bool`):
+            Whether to use ephemeral GPU offloading for models partially kept in CPU memory.
+    """
+
+    ephemeral_gpu_offload: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "Whether to use ephemeral GPU offloading for models partially kept in CPU memory. Ephemeral GPU offloading result in "
+                "the data involved in intense operations being momentarily copied over to the GPU, and the results copied "
+                "back to CPU. There is a momentary VRAM overhead, but operations are generally orders of magnitude faster "
+                "compared to performing them on the CPU. This is useful when parts of the model and/or components (such "
+                "as adapters) are kept in CPU memory until they are needed. Rather than perform expensive operations on "
+                "small data, the data is transferred to the GPU on-demand, the operation(s) performed, and the results "
+                "moved back to CPU memory. Currently only affects DoRA initialization."
+            )
+        },
+    )
+
+
+@dataclass
+class LoftQConfig:
+    """
+    This is the sub-configuration class to store the configuration of a [`LoraModel`].
+
+    Args:
+        bits_pattern (`dict`): The mapping from layer names or regexp expression to bits which are different from the
+            default bits specified by `bits`. For example, `{model.decoder.layers.0.encoder_attn.k_proj: 2`}.
+        bits (`int`): Quantization bits for LoftQ.
+        iter (`int`): Alternating iterations for LoftQ.
+        fake (`bool`): True: use fp16/fp32; used for first time to save weights. False: use bitsandbytes 4bit linear
+            models. weights can't be saved. Recommend to set to True, save the weights and load the saved weights in 4
+            bits.
+    """
+
+    loftq_bits: int = field(default=4, metadata={"help": "Quantization bits for LoftQ"})
+    loftq_iter: int = field(default=1, metadata={"help": "Alternating iterations for LoftQ"})
+
+
+@dataclass
+class EvaConfig:
+    """
+    This is the sub-configuration class to store the configuration for a data-driven initialization via EVA. EVA was
+    introduced in Explained Variance Adaptation.
+
+    Args:
+        rho (`float`):
+            Rho value for EVA redistribution (>= 1.0). The maximum rank for a layer is lora_r * rho. Default is 2.0,
+            meaning the maximum rank allowed for a layer is 2r. Increasing rho will allow for a higher degree of
+            redistribution of ranks across layers. Some pre-trained models might be more sensitive to a rank
+            redistribution. It can therefore be beneficial to try rho=1.0 (no redistribution) if the performance is
+            lower than expected.
+        tau (`float`):
+            Cosine similarity threshold for early stopping. Compares the cosine similarity of right-singular vectors
+            between two consecutive SVD steps. If the cosine similarity is above this threshold, the SVD iteration is
+            stopped. Default is 0.99.
+        use_label_mask (`bool`):
+            Use label mask for EVA initialization. This means that positions where labels=label_mask_value are ignored
+            for the SVD computation. Setting use_label_mask=True is preferred in most cases and can be especially
+            beneficial for multi-turn conversations. The default value is True. Filtering out items based on the label
+            mask can sometimes lead to a small batch size and as a result instabilities in the SVD computation. For
+            cases where a large share of batch items would be filtered out, set use_label_mask=False.
+        label_mask_value (`int`):
+            If use_label_mask=True the value to look for to mask out ignored tokens. Default is -100.
+        whiten (`bool`): Apply whitening to singular vectors. Default is False.
+            Whitening has been shown to be beneficial for EVA in the vision domain.
+        adjust_scaling_factors (`bool`):
+            Adjust LoRA scaling factors after the rank redistribution. Setting this to True means the scaling factors
+            are adjusted so that all LoRA gradients have the same scale regardless of their rank. Default is True.
+    """
+
+    rho: float = field(default=2.0, metadata={"help": "Rho value for EVA redistribution"})
+    tau: float = field(default=0.99, metadata={"help": "Cosine similarity threshold for early stopping"})
+    use_label_mask: bool = field(default=True, metadata={"help": "Use label mask for EVA initialization"})
+    label_mask_value: int = field(
+        default=-100, metadata={"help": "if use_label_mask=True the value to look for to mask out ignored tokens"}
+    )
+    whiten: bool = field(default=False, metadata={"help": "Apply whitening to singular vectors"})
+    adjust_scaling_factors: bool = field(
+        default=True,
+        metadata={"help": "Adjust LoRA scaling factors after the rank redistribution"},
+    )
+
+    def __post_init__(self):
+        if self.rho < 1.0:
+            raise ValueError("`rho` must be >= 1.0")
+        if self.tau < 0.0 or self.tau > 1.0:
+            raise ValueError("`tau` must be between 0.0 and 1.0.")
+
+
+@dataclass
+class CordaConfig:
+    """
+    This is the sub-configuration class to store the configuration of a [`LoraModel`].
+
+    Args:
+        cache_file (`Optional[str]`):
+            File to store the SVD cache. The SVD cache is much smaller than the residual model (for example, residual
+            model of Llama-3-8b is 15GB, while SVD cache is 1.4GB), but with SVD cache and original model weights,
+            residual model weights can be built quickly. If you need to reuse residual model weights with limited
+            storage, you can store the SVD cache instead.
+        covariance_file (`Optional[str]`):
+            File to store the covariance matrix. If you wish to train multiple models with different ranks, but they
+            sample from the same dataset, you can store the covariance matrix and reuse it for different ranks. Note
+            that covariance file is usually large (comparable to model size), so you will need sufficient storage.
+        corda_method (`Literal["ipm", "kpm"]`):
+            Method to build adapter. The KPM (Knowledge-Preserved Mode) not only achieves better performance than LoRA
+            on fine-tuning tasks, but also mitigates the catastrophic forgetting of pre-trained world knowledge. When
+            preserving pre-trained knowledge is not a concern, the IPM (Instruction-Previewed Mode) is favored because
+            it can further accelerate convergence and enhance the fine-tuning performance. Defaults to `'ipm'`.
+        verbose (`bool`):
+            If true, prints the progress of CorDA initialization. Defaults to `False`.
+        use_float16_for_covariance (`bool`):
+            If true, uses float16 for the covariance matrix. This can reduce the memory usage of the covariance matrix
+            by half, but may lead to numerical instability. Defaults to `False`.
+        prune_temporary_fields (`bool`):
+            If true, temporary fields generated in CorDA preprocessing will be pruned. Defaults to `True`.
+    """
+
+    cache_file: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": (
+                "File to store the SVD cache. The SVD cache is much smaller than the residual model (for example, "
+                "residual model of Llama-3-8b is 15GB, while SVD cache is 1.4GB), but with SVD cache and original model "
+                "weights, residual model weights can be built quickly. If you need to reuse residual model weights with "
+                "limited storage, you can store the SVD cache instead."
+            )
+        },
+    )
+    covariance_file: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": (
+                "File to store the covariance matrix. If you wish to train multiple models with different ranks, but "
+                "they sample from the same dataset, you can store the covariance matrix and reuse it for different ranks. "
+                "Note that covariance file is usually large (comparable to model size), so you will need sufficient storage."
+            )
+        },
+    )
+    corda_method: Literal["ipm", "kpm"] = field(
+        default="ipm",
+        metadata={
+            "help": (
+                "Method to build adapter. The KPM not only achieves better performance than LoRA on fine-tuning tasks, but "
+                "also mitigates the catastrophic forgetting of pre-trained world knowledge. When preserving pre-trained "
+                "knowledge is not a concern, the IPM is favored because it can further accelerate convergence and enhance "
+                "the fine-tuning performance."
+            )
+        },
+    )
+    verbose: bool = field(default=False, metadata={"help": "If true, prints the progress of CorDA initialization."})
+    use_float16_for_covariance: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "If true, uses float16 for the covariance matrix. This can reduce the memory usage of the covariance matrix "
+                "by half, but may lead to numerical instability."
+            )
+        },
+    )
+    prune_temporary_fields: bool = field(
+        default=True, metadata={"help": "If true, temporary fields generated in CorDA preprocessing will be pruned."}
+    )
+
+
+@dataclass
+class LoraConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`LoraModel`].
+
+    Args:
+        r (`int`):
+            Lora attention dimension (the "rank").
+        target_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear/Conv1D modules are chosen (if
+            the model is a PreTrainedModel, the output layer excluded). If this is not specified, modules will be
+            chosen according to the model architecture. If the architecture is not known, an error will be raised -- in
+            this case, you should specify the target modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        lora_alpha (`int`):
+            The alpha parameter for Lora scaling.
+        lora_dropout (`float`):
+            The dropout probability for Lora layers.
+        fan_in_fan_out (`bool`):
+            Set this to True if the layer to replace stores weight like (fan_in, fan_out). For example, gpt-2 uses
+            `Conv1D` which stores weights like (fan_in, fan_out) and hence this should be set to `True`.
+        bias (`str`):
+            Bias type for LoRA. Can be 'none', 'all' or 'lora_only'. If 'all' or 'lora_only', the corresponding biases
+            will be updated during training. Be aware that this means that, even when disabling the adapters, the model
+            will not produce the same output as the base model would have without adaptation.
+        use_rslora (`bool`):
+            When set to True, uses Rank-Stabilized LoRA which
+            sets the adapter scaling factor to `lora_alpha/math.sqrt(r)`, since it was proven to work better.
+            Otherwise, it will use the original default value of `lora_alpha/r`.
+        modules_to_save (`List[str]`):
+            List of modules apart from adapter layers to be set as trainable and saved in the final checkpoint.
+        init_lora_weights (`bool` | `Literal["gaussian", "eva", "olora", "pissa", "pissa_niter_[number of iters]", "corda", "loftq"]`):
+            How to initialize the weights of the adapter layers. Passing True (default) results in the default
+            initialization from the reference implementation from Microsoft, with the LoRA B weight being set to 0.
+            This means that without further training, the LoRA adapter will be a no-op. Setting the initialization to
+            False leads to random initialization of LoRA A and B, meaning that LoRA is not a no-op before training;
+            this setting is intended for debugging purposes. Passing 'gaussian' results in Gaussian initialization
+            scaled by the LoRA rank for linear and layers. Pass `'loftq'` to use LoftQ initialization. Passing `'eva'`
+            results in a data-driven initialization of Explained Variance
+            Adaptation. EVA initalizes LoRA based on the SVD of layer input activations and achieves SOTA
+            performance due to its ability to adapt to the finetuning data. Pass `'olora'` to use OLoRA initialization.
+            Passing `'pissa'` results in the initialization of Principal
+            Singular values and Singular vectors Adaptation (PiSSA), which converges more rapidly than LoRA and
+            ultimately achieves superior performance. Moreover, PiSSA reduces the quantization error compared to QLoRA,
+            leading to further enhancements. Passing `'pissa_niter_[number of iters]'` initiates Fast-SVD-based PiSSA
+            initialization, where `[number of iters]` indicates the number of subspace iterations to perform FSVD, and
+            must be a nonnegative integer. When `[number of iters]` is set to 16, it can complete the initialization of
+            a 7B model within seconds, and the training effect is approximately equivalent to using SVD. Passing
+            `'corda'` results in the initialization of Context-Oriented
+            Decomposition Adaptation, which converges even more rapidly than PiSSA in Instruction-Previewed Mode,
+            and preserves world knowledge better than LoRA in Knowledge-Preserved Mode.
+        layers_to_transform (`Union[List[int], int]`):
+            The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
+            that are specified in this list. If a single integer is passed, it will apply the transformations on the
+            layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`. This should target the
+            `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`.
+        rank_pattern (`dict`):
+            The mapping from layer names or regexp expression to ranks which are different from the default rank
+            specified by `r`. For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`.
+        alpha_pattern (`dict`):
+            The mapping from layer names or regexp expression to alphas which are different from the default alpha
+            specified by `lora_alpha`. For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`.
+        megatron_config (`Optional[dict]`):
+            The TransformerConfig arguments for Megatron. It is used to create LoRA's parallel linear layer. You can
+            get it like this, `core_transformer_config_from_args(get_args())`, these two functions being from Megatron.
+            The arguments will be used to initialize the TransformerConfig of Megatron. You need to specify this
+            parameter when you want to apply LoRA to the ColumnParallelLinear and RowParallelLinear layers of megatron.
+        megatron_core (`Optional[str]`):
+            The core module from Megatron to use, defaults to `"megatron.core"`.
+        trainable_token_indices (`Optional[Union[List[int], dict[str, List[int]]]]`)
+            Lets you specify which token indices to selectively fine-tune without requiring to re-train the whole
+            embedding matrix using the `peft.TrainableTokensModel` method. You can specify token indices in two ways.
+            Either you specify a list of indices which will then target the model's input embedding layer (or, if not
+            found, `embed_tokens`). Alternatively, you can specify a dictionary where the key is the name of the
+            embedding module and the values are the list of token indices, e.g. `{'embed_tokens': [0, 1, ...]}`. Note
+            that training with FSDP/DeepSpeed might not yet be fully supported with this option enabled.
+        loftq_config (`Optional[LoftQConfig]`):
+            The configuration of LoftQ. If this is not None, then LoftQ will be used to quantize the backbone weights
+            and initialize Lora layers. Also pass `init_lora_weights='loftq'`. Note that you should not pass a
+            quantized model in this case, as LoftQ will quantize the model itself.
+        eva_config (`Optional[EvaConfig]`):
+            The configuration of EVA. At a minimum the dataset argument needs to be set (use the same dataset as for
+            finetuning).
+        corda_config (`Optional[CordaConfig]`):
+            The configuration of CorDA. If this is not None, then CorDA will be used to build the adapter layers. Also
+            pass `init_lora_weights='corda'`.
+        use_dora (`bool`):
+            Enable 'Weight-Decomposed Low-Rank Adaptation' (DoRA). This technique decomposes the updates of the weights
+            into two parts, magnitude and direction. Direction is handled by normal LoRA, whereas the magnitude is
+            handled by a separate learnable parameter. This can improve the performance of LoRA especially at low
+            ranks. Right now, DoRA only supports linear and Conv2D layers. DoRA introduces a bigger overhead than pure
+            LoRA, so it is recommended to merge weights for inference. For more information, see
+            https://arxiv.org/abs/2402.09353.
+        layer_replication (`List[Tuple[int, int]]`):
+            Build a new stack of layers by stacking the original model layers according to the ranges specified. This
+            allows expanding (or shrinking) the model without duplicating the base model weights. The new layers will
+            all have separate LoRA adapters attached to them.
+        runtime_config (`LoraRuntimeConfig`):
+            Runtime configurations (which are not saved or restored).
+        lora_bias (`bool`):
+            Defaults to `False`. Whether to enable the bias term for the LoRA B parameter. Typically, this should be
+            disabled. The main use case for this is when the LoRA weights were extracted from fully fine-tuned
+            parameters so the bias of those parameters can be taken into account.
+    """
+
+    r: int = field(default=8, metadata={"help": "Lora attention dimension"})
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of module names or regex expression of the module names to replace with LoRA."
+                "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$'."
+                "This can also be a wildcard 'all-linear' which matches all linear/Conv1D "
+                "(if the model is a PreTrainedModel, the output layer excluded)."
+                "If not specified, modules will be chosen according to the model architecture, If the architecture is "
+                "not known, an error will be raised -- in this case, you should specify the target modules manually."
+            ),
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from Lora."},
+    )
+    lora_alpha: int = field(default=8, metadata={"help": "Lora alpha"})
+    lora_dropout: float = field(default=0.0, metadata={"help": "Lora dropout"})
+    fan_in_fan_out: bool = field(
+        default=False,
+        metadata={"help": "Set this to True if the layer to replace stores weight like (fan_in, fan_out)"},
+    )
+    bias: Literal["none", "all", "lora_only"] = field(
+        default="none", metadata={"help": "Bias type for Lora. Can be 'none', 'all' or 'lora_only'"}
+    )
+    use_rslora: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "When set to True, uses Rank-Stabilized LoRA"
+                " which sets the adapter scaling factor to `lora_alpha/math.sqrt(r)`, since it"
+                " was proven to work better. Otherwise, it will use the original default"
+                " value of `lora_alpha/r`."
+            )
+        },
+    )
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from LoRA layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+    init_lora_weights: (
+        bool | Literal["gaussian", "eva", "olora", "pissa", "pissa_niter_[number of iters]", "corda", "loftq"]
+    ) = field(
+        default=True,
+        metadata={
+            "help": (
+                "How to initialize the weights of the LoRA layers. "
+                "Passing True (default) results in the default initialization from the reference implementation from "
+                "Microsoft, with the LoRA B weight being set to 0. This means that without further training, the LoRA "
+                "adapter will be a no-op. "
+                "Setting the initialization to False leads to random initialization of LoRA A and B, meaning that LoRA "
+                "is not a no-op before training; this setting is intended for debugging purposes. "
+                "Passing `'gaussian'` results in Gaussian initialization scaled by the LoRA rank for linear and layers. "
+                "Passing `'eva'` results in a data-driven initialization of Explained Variance Adaptation. "
+                "Passing `'olora'` results in OLoRA initialization. "
+                "Passing `'pissa'` results in PiSSA initialization. "
+                "Passing `'pissa_niter_[number of iters]'` initiates Fast-SVD-based PiSSA initialization, where "
+                "[number of iters] indicates the number of subspace iterations to perform fsvd, and must be a "
+                "nonnegative integer. "
+                "Passing `'corda'` results in CorDA initialization. "
+                "Pass `'loftq'` to use LoftQ initialization."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index. "
+            "This only works when target_modules is a list of str."
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern."
+            "This only works when target_modules is a list of str. This should target the `nn.ModuleList` of the "
+            "model, which is often called `'layers'` or `'h'`."
+        },
+    )
+    rank_pattern: Optional[dict] = field(
+        default_factory=dict,
+        metadata={
+            "help": (
+                "The mapping from layer names or regexp expression to ranks which are different from the default rank specified by `r`. "
+                "For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`."
+            )
+        },
+    )
+    alpha_pattern: Optional[dict] = field(
+        default_factory=dict,
+        metadata={
+            "help": (
+                "The mapping from layer names or regexp expression to alphas which are different from the default alpha specified by `lora_alpha`. "
+                "For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`."
+            )
+        },
+    )
+    megatron_config: Optional[dict] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The TransformerConfig from Megatron. It is used to create LoRA's parallel linear layer."
+                "You can get it like this, `core_transformer_config_from_args(get_args())`, "
+                "these two functions being from Megatron."
+                "You need to specify this parameter when you want to apply LoRA to the ColumnParallelLinear and "
+                "RowParallelLinear layers of megatron."
+                "It should be noted that we may not be able to use the `save_pretrained` and `from_pretrained` "
+                "functions, because TransformerConfig may not necessarily be serialized."
+                "But when using megatron, we can use `get_peft_model_state_dict` function and "
+                "megatron's framework, they can also save and load models and configurations."
+            )
+        },
+    )
+    megatron_core: Optional[str] = field(
+        default="megatron.core",
+        metadata={
+            "help": (
+                "The core module from Megatron, it is used to create LoRA's parallel linear layer. "
+                "It only needs to be passed in when you need to use your own modified megatron core module. "
+                "Otherwise, it will use the default value `megatron.core`. "
+            )
+        },
+    )
+    trainable_token_indices: Optional[Union[list[int], dict[str, list[int]]]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "Lets you specify which token indices to selectively fine-tune without requiring to re-train the "
+                "whole embedding matrix using the `peft.TrainableTokensModel` method. You can specify token indices "
+                "in two ways. Either you specify a list of indices which will then target the model's input embedding "
+                "layer (or, if not found, `embed_tokens`). Alternatively, you can specify a dictionary where the key "
+                "is the name of the embedding module and the values are the list of token indices, e.g. "
+                "`{'embed_tokens': [0, 1, ...]}`. "
+                "Note that training with FSDP/DeepSpeed might not yet be fully supported with this option enabled. "
+                "Also note that models using weight-tying are currently not supported."
+            )
+        },
+    )
+    # dict type is used when loading config.json
+    loftq_config: Union[LoftQConfig, dict] = field(
+        default_factory=dict,
+        metadata={
+            "help": (
+                "The configuration of LoftQ. If this is passed, then LoftQ will be used to quantize the backbone "
+                "weights and initialize Lora layers. Also set `init_lora_weights='loftq'` in this case."
+            )
+        },
+    )
+    eva_config: Optional[EvaConfig] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The configuration of EVA. If this is passed, then EVA will be used to intialize the LoRA layers. "
+                "Also set `init_lora_weights='eva'` in this case. "
+            )
+        },
+    )
+    corda_config: Optional[CordaConfig] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The configuration of CorDA. If this is passed, then CorDA will be used to build the adapter layers. "
+                "Also set `init_lora_weights='corda'` in this case."
+            )
+        },
+    )
+    use_dora: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "Enable 'Weight-Decomposed Low-Rank Adaptation' (DoRA). This technique decomposes the updates of the "
+                "weights into two parts, magnitude and direction. Direction is handled by normal LoRA, whereas the "
+                "magnitude is handled by a separate learnable parameter. This can improve the performance of LoRA, "
+                "especially at low ranks. Right now, DoRA only supports linear and Conv2D layers. DoRA introduces a bigger"
+                "overhead than pure LoRA, so it is recommended to merge weights for inference."
+            )
+        },
+    )
+    # Enables replicating layers in a model to expand it to a larger model.
+    layer_replication: Optional[list[tuple[int, int]]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "This enables using LoRA to effectively expand a transformer model to a larger size by repeating some layers. "
+                "The transformation handles models (currently Llama, Bert or Falcon compatible architectures) with "
+                "a module list in the model which it modifies to expand the number of modules. "
+                "Base weights are shared so the memory usage is close to the original model. The intended use is these base weights "
+                "remain fixed during finetuning but each layer has a separate LoRA adapter so the layers can be specialed via "
+                "the adapter layers fit during fine tuning."
+                "The format is a list of [start, end) pairs which specify the layer ranges to stack. For example:\n"
+                "   Original model has 5 layers labelled by their position in the model: `[0, 1, 2, 3, 4]`\n"
+                "   layer_replication: `[[0, 4], [2, 5]]`\n"
+                "   Final model will have this arrangement of original layers: `[0, 1, 2, 3, 2, 3, 4]`\n"
+                "This format is based on what is used for pass-through merges in mergekit. It makes it simple to select sequential "
+                "ranges of a model and stack them while reusing layers at either end of each sequence."
+            )
+        },
+    )
+    runtime_config: LoraRuntimeConfig = field(
+        default_factory=LoraRuntimeConfig, metadata={"help": "Runtime configurations"}
+    )
+    lora_bias: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "Whether to enable the bias term for the LoRA B parameter. Typically, this should be disabled. The "
+                "main use case for this is when the LoRA weights were extracted from fully fine-tuned parameters so "
+                "the bias of those parameters can be taken into account."
+            )
+        },
+    )
+
+    def to_dict(self):
+        """
+        Returns the configuration for your adapter model as a dictionary. Removes runtime configurations.
+        """
+        rv = super().to_dict()
+        rv.pop("runtime_config")
+        return rv
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.LORA
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+
+        # if target_modules is a regex expression, then layers_to_transform should be None
+        if isinstance(self.target_modules, str) and self.layers_to_transform is not None:
+            raise ValueError("`layers_to_transform` cannot be used when `target_modules` is a str.")
+
+        # if target_modules is a regex expression, then layers_pattern should be None
+        if isinstance(self.target_modules, str) and self.layers_pattern is not None:
+            raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
+
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
+
+        if self.use_dora and self.megatron_config:
+            raise ValueError("DoRA does not support megatron_core, please set `use_dora=False`.")
+
+        # handle init_lora_weights and loftq_config
+        if self.init_lora_weights == "loftq":
+            import importlib
+
+            if not importlib.util.find_spec("scipy"):
+                raise ImportError("The required package 'scipy' is not installed. Please install it to continue.")
+            if not self.loftq_config:
+                raise ValueError("`loftq_config` must be specified when `init_lora_weights` is 'loftq'.")
+            if not isinstance(self.loftq_config, dict):
+                # convert loftq_config to dict
+                self.loftq_config = vars(self.loftq_config)
+        elif self.loftq_config:
+            self.loftq_config = {}
+            warnings.warn("`loftq_config` specified but will be ignored when `init_lora_weights` is not 'loftq'.")
+
+        elif self.init_lora_weights == "eva" and self.eva_config is None:
+            warnings.warn("`init_lora_weights` is 'eva' but `eva_config` is not specified. Using default EVA config.")
+            self.eva_config = EvaConfig()
+        elif self.init_lora_weights != "eva" and self.eva_config is not None:
+            warnings.warn("`eva_config` specified but will be ignored when `init_lora_weights` is not 'eva'.")
+
+        elif self.init_lora_weights == "corda" and self.corda_config is None:
+            warnings.warn(
+                "`init_lora_weights` is 'corda' but `corda_config` is not specified. Using default CorDA config."
+            )
+            self.corda_config = CordaConfig()
+        elif self.init_lora_weights != "corda" and self.corda_config is not None:
+            warnings.warn("`corda_config` specified but will be ignored when `init_lora_weights` is not 'corda'.")
+
+        if self.lora_bias:
+            if self.init_lora_weights not in (True, False):
+                raise ValueError(
+                    f"The argument lora_bias=True is only supported with init_lora_weights=True or False, got "
+                    f"init_lora_weights={self.init_lora_weights} instead."
+                )
+            if self.use_dora:
+                raise ValueError("The argument lora_bias=True is not supported for DoRA, please pass use_dora=False")
+
+        # Using post training conversion of modified base weights to restore their initial values PiSSA/CorDA/OLoRA cannot
+        # be correctly done when using rslora + rank_pattern/alpha_pattern. We can't really know if the user intends
+        # this when they'll eventually call save_pretrained (i.e. if they'll pass
+        # path_initial_model_for_weight_conversionl). Therefore, we only warn but don't raise an error here.
+        if (
+            self.use_rslora
+            and (self.rank_pattern or self.alpha_pattern)
+            and (
+                (isinstance(self.init_lora_weights, str) and (self.init_lora_weights.startswith("pissa")))
+                or (self.init_lora_weights == "olora")
+                or (self.init_lora_weights == "corda")
+            )
+        ):
+            msg = (
+                "Using Rank-Stabilized LoRA with rank_pattern/alpha_pattern and post-training conversion of modified "
+                "base weights PiSSA/CorDA/OLoRA means that you won't be able to pass "
+                "`path_initial_model_for_weight_conversion` to `save_pretrained` to restore the initial values of the "
+                "base weights; if you intend to do this, please ensure not to use rslora or rank_pattern/alpha_pattern."
+            )
+            warnings.warn(msg)
+
+        self._custom_modules: Optional[dict[type[nn.Module], type[nn.Module]]] = None
+
+    def _register_custom_module(self, mapping: dict[type[nn.Module], type[nn.Module]]) -> None:
+        """
+        Experimental API to support providing custom LoRA layers.
+
+        This API is subject to change, you should carefully read the docs before deciding to use it:
+
+        https://huggingface.co/docs/peft/developer_guides/custom_models
+
+        To register custom LoRA module types, call this method with a `mapping` argument that is a dict that maps from
+        the target layer type to the custom LoRA layer type. The dict can contain multiple items if you wish to target
+        multiple layer types. The target layer type can be any nn.Module that we currently don't support in PEFT,
+        whether that is an official PyTorch layer type or a custom layer type. The custom LoRA module class has to be
+        implemented by the user and follow the PEFT conventions for LoRA layers.
+
+        """
+        if self._custom_modules is None:
+            self._custom_modules = {}
+        self._custom_modules.update(mapping)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/corda.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/corda.py
new file mode 100644
index 0000000000000000000000000000000000000000..8b991d276e8cccf69d5b3e864bd305c472489d71
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/corda.py
@@ -0,0 +1,359 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Reference code: https://github.com/iboing/CorDA/blob/main/cordalib/decomposition.py
+# Reference paper: https://arxiv.org/abs/2406.05223
+
+import os
+from typing import Any, Callable, Iterable, Optional
+
+import torch
+import torch.nn as nn
+from attr import dataclass
+from tqdm import tqdm
+
+from peft.tuners.lora.config import LoraConfig
+from peft.tuners.lora.model import LoraModel
+from peft.utils.other import get_pattern_key
+
+
+@dataclass
+class CordaEigens:
+    S_WC: torch.Tensor
+    U_WC: torch.Tensor
+    V_WC: torch.Tensor
+
+
+def target_modules(model: nn.Module, config: LoraConfig) -> Iterable[nn.Module]:
+    """
+    Iterate over CorDA target name and modules of a model. A module is a target if its name is in
+    `config.target_modules` and is `nn.Linear`.
+    """
+    for name, module in model.named_modules():
+        if LoraModel._check_target_module_exists(config, name) and isinstance(module, nn.Linear):
+            yield name, module
+
+
+def get_model_device(model: nn.Module) -> str:
+    if hasattr(model, "module"):  # Handle DeepSpeed/DataParallel
+        model = model.module
+    return next(iter(model.parameters())).device.type
+
+
+@torch.no_grad()
+def preprocess_corda(
+    model: nn.Module,
+    lora_config: LoraConfig,
+    run_model: Optional[Callable[[], None]] = None,
+    hooked_model: Optional[nn.Module] = None,
+):
+    """
+    Build necessary CorDA fields for a model.
+
+    For each `M * N` linear layer, a `M * M` covariance matrix will be built temporarily during the preprocessing
+    process, consuming roughly another `2 * MODEL_SIZE` memory for typical LLMs if model weight is FP16 and covariance
+    is FP32. If that's too much, consider specifying `use_float16_for_covariance` in `lora_config.corda_config`.
+
+    Args:
+        model (`nn.Module`):
+            Model to preprocess.
+        lora_config (`LoraConfig`):
+            Lora configuration of the model. `lora_config.corda_config` should be set.
+        run_model (`Optional[Callable[[], None]]`):
+            Callback to run the model when building covariance. Typically you should run model inference on your sample
+            dataset in this callback. Experiments have shown that when token count per sample is 2048, hidden dimension
+            is 4096, collecting 256 distinct samples is enough. If you collect too few or too repetitive samples, the
+            covariance matrix may be low-ranked and unstabilize preprocessing. You can estimate sample count as
+            `HIDDEN_DIM / TOKEN_PER_SAMPLE * 128`. `run_model` can be `None` only if covariance file in
+            `lora_config.corda_config` is already created.
+        hooked_model (`Optional[nn.Module]`):
+            Model to hook when building covariance. If none, original model will be hooked. This is only useful when
+            you want to hook a different model than the one you are training, typically you should leave this `None`.
+
+    Upon completion, the following fields are set for each target module:
+        eigens.S_WC (`torch.Tensor`):
+            Singular values of the weight matrix.
+        eigens.U_WC (`torch.Tensor`):
+            Left singular vectors of the weight matrix.
+        eigens.V_WC (`torch.Tensor`):
+            Right singular vectors of the weight matrix, multiplied by inverse of covariance matrix.
+    """
+    cache_file = lora_config.corda_config.cache_file
+    covariance_file = lora_config.corda_config.covariance_file
+    corda_method = lora_config.corda_config.corda_method
+    verbose = lora_config.corda_config.verbose
+    prune_temporary_fields = lora_config.corda_config.prune_temporary_fields
+
+    # If cache exists, skip building
+    if cache_file is not None and os.path.exists(cache_file) and os.path.getsize(cache_file) > 0:
+        cache = torch.load(cache_file, map_location=get_model_device(model))
+        for name, module in target_modules(model, lora_config):
+            module.eigens = CordaEigens(
+                S_WC=cache[f"{name}.eigens.S_WC"],
+                U_WC=cache[f"{name}.eigens.U_WC"],
+                V_WC=cache[f"{name}.eigens.V_WC"],
+            )
+    else:
+        # Specify CorDA method for each layer
+        if corda_method is None:
+            raise ValueError("corda_method is required when cache_file is not provided.")
+        for name, module in target_modules(model, lora_config):
+            module.corda_method = corda_method
+
+        # Specify CorDA rank for each layer
+        for name, module in target_modules(model, lora_config):
+            r_key = get_pattern_key(lora_config.rank_pattern.keys(), name)
+            module.rank = lora_config.rank_pattern.get(r_key, lora_config.r)
+
+        # Calculate covariance matrix
+        calib_cov_distribution(model, lora_config, run_model, hooked_model, covariance_file)
+
+        # Calculate eigens
+        collect_eigens(model, lora_config, verbose)
+
+        # Crop CorDA eigens so that there's less to save
+        crop_corda_eigens(model, lora_config)
+
+        # Remove redundant fields if exist
+        if prune_temporary_fields:
+            for name, module in target_modules(model, lora_config):
+                if hasattr(module, "sample_count"):
+                    del module.sample_count
+                if hasattr(module, "covariance_matrix"):
+                    del module.covariance_matrix
+                if hasattr(module, "corda_method"):
+                    del module.corda_method
+                if hasattr(module, "rank"):
+                    del module.rank
+
+        # Save cache to disk
+        if cache_file is not None:
+            cache: dict[str, Any] = {}
+            for name, module in target_modules(model, lora_config):
+                cache[f"{name}.eigens.S_WC"] = module.eigens.S_WC
+                cache[f"{name}.eigens.U_WC"] = module.eigens.U_WC
+                cache[f"{name}.eigens.V_WC"] = module.eigens.V_WC
+
+            os.makedirs(os.path.dirname(cache_file), exist_ok=True)
+            torch.save(cache, cache_file)
+
+
+@torch.no_grad()
+def calib_cov_distribution(
+    model: nn.Module,
+    config: LoraConfig,
+    run_model: Optional[Callable[[], None]],
+    hooked_model: Optional[nn.Module],
+    covariance_file: Optional[str],
+):
+    if covariance_file is not None and os.path.exists(covariance_file) and os.path.getsize(covariance_file) > 0:
+        all_covariance_matrix = torch.load(covariance_file, map_location=get_model_device(model))
+        for name, module in target_modules(model, config):
+            module.covariance_matrix = all_covariance_matrix[name]
+        return
+
+    if run_model is None:
+        raise ValueError("run_model must be specified when covariance file and cache file aren't built.")
+    if hooked_model is None:
+        hooked_model = model
+    hooked_model.eval()
+
+    def hook(module, input, output):
+        input = input[0].detach().squeeze(0).data  ## (context_length = 2048, dim)
+        if not config.corda_config.use_float16_for_covariance:
+            input = input.float()
+        input = input / torch.max(input).abs()
+
+        # check if input is valid
+        if torch.isnan(input).any() or torch.isinf(input).any():
+            raise ValueError("Invalid value found in input, please check your input data.")
+
+        # calculate covariance and check if it's valid
+        covariance = input.t().matmul(input)
+        if torch.isnan(covariance).any() or torch.isinf(covariance).any():
+            raise ValueError(
+                "Invalid value found in covariance. Please file an issue at https://github.com/huggingface/peft/issues."
+            )
+
+        # add to module
+        module.sample_count += 1
+        module.covariance_matrix += covariance
+
+        # free memory
+        del covariance, input
+
+    handles = []
+    for name, module in target_modules(hooked_model, config):
+        module.sample_count = 0
+        module.covariance_matrix = 0
+        handles.append(module.register_forward_hook(hook))
+
+    run_model()
+
+    # Clear the hooks
+    for handle in handles:
+        handle.remove()
+
+    # In some edge cases you might need to hook a model different from the model to add adapters,
+    # this case you would specify `hooked_model` and set it to a different model from `model`.
+    if hooked_model is not model:
+        targets = {}
+        for name, module in target_modules(model, config):
+            targets[name] = module
+        for name, module in target_modules(hooked_model, config):
+            # There can be modules used only in inference, but not training
+            # Exclude modules not in target model to prevent KeyError in this case
+            if name in targets:
+                targets[name].sample_count = module.sample_count
+                targets[name].covariance_matrix = module.covariance_matrix
+
+    # Divide by sample count
+    for name, module in target_modules(model, config):
+        module.covariance_matrix /= module.sample_count
+
+    # Save covariance to disk
+    if covariance_file is not None:
+        all_covariance_matrix = {}
+        for name, module in target_modules(model, config):
+            all_covariance_matrix[name] = module.covariance_matrix
+        os.makedirs(os.path.dirname(covariance_file), exist_ok=True)
+        torch.save(all_covariance_matrix, covariance_file)
+
+
+@torch.no_grad()
+def collect_eigens(
+    model: nn.Module,
+    config: LoraConfig,
+    verbose: bool,
+):
+    """Call collect_eigens_for_layer and store result in key `eigens` of each layer."""
+    linear_modules = []
+    for name, module in target_modules(model, config):
+        linear_modules.append((name, module))
+    if verbose:
+        linear_modules = tqdm(linear_modules, desc="Collecting eigens")
+    for name, module in linear_modules:
+        module.eigens = collect_eigens_for_layer(module, config)
+
+
+@torch.no_grad()
+def collect_eigens_for_layer(
+    linear: nn.Linear,
+    config: LoraConfig,
+) -> CordaEigens:
+    w = linear.weight.data.float()
+    out_dim = w.size(0)
+    in_dim = w.size(1)
+    min_dim = min(in_dim, out_dim)
+
+    if not hasattr(linear, "covariance_matrix"):
+        raise ValueError(
+            "Covariance matrix not found in linear module. Please do not call this function directly, "
+            "instead call `preprocess_corda`. If your usage is correct but this error still encounters, "
+            "please file an issue at https://github.com/huggingface/peft/issues."
+        )
+    covariance_matrix = linear.covariance_matrix.float()
+
+    damp = 0.01
+    while True:
+        compensate = torch.diag(
+            torch.ones(covariance_matrix.size(0)).to(covariance_matrix.device)
+            * torch.mean(torch.diag(covariance_matrix))
+            * damp
+        )
+        fix_covariance_matrix = covariance_matrix + compensate
+        cov_inv = torch.linalg.inv(fix_covariance_matrix)
+        inv_error = torch.dist(
+            fix_covariance_matrix @ cov_inv, torch.eye(covariance_matrix.size(0)).to(get_model_device(linear))
+        ).item()
+        if inv_error < 0.05:
+            break
+        else:
+            damp = damp * 2
+    w = w @ fix_covariance_matrix  ## w: out_dim, in_dim; covariance_matrix: in_dim, in_dim
+
+    U, S, Vh = torch.linalg.svd(w, full_matrices=False)
+    V = (Vh @ cov_inv).transpose(0, 1)
+
+    # Sanity check, temporarily U and V are large, they will be crop after rank search
+    r = min_dim
+    if U.size(0) != out_dim or U.size(1) != r:
+        raise ValueError(
+            f"Matrix U size mismatch: {U.size()} vs. ({out_dim}, {r}), "
+            "please file an issue at https://github.com/huggingface/peft/issues."
+        )
+    if S.size(0) != r:
+        raise ValueError(
+            f"Matrix S size mismatch: {S.size()} vs. ({r},), "
+            "please file an issue at https://github.com/huggingface/peft/issues."
+        )
+    if V.size(0) != in_dim or V.size(1) != r:
+        raise ValueError(
+            f"Matrix V size mismatch: {V.size()} vs. ({in_dim}, {r}), "
+            "please file an issue at https://github.com/huggingface/peft/issues."
+        )
+
+    # Offload U and V to CPU, they consume too much memory
+    U = U.cpu()
+    V = V.cpu()
+    return CordaEigens(
+        S_WC=S,
+        U_WC=U,
+        V_WC=V,
+    )
+
+
+@torch.no_grad()
+def crop_corda_eigens(model: nn.Module, config: LoraConfig):
+    for name, module in target_modules(model, config):
+        # We don't expect saving sliced tensor writes the whole tensor to disk,
+        # so it's necessary to copy the tensors.
+        # Reference: https://github.com/pytorch/pytorch/issues/40157
+        if module.corda_method == "ipm":
+            module.eigens.S_WC = module.eigens.S_WC[: module.rank].clone()
+            module.eigens.U_WC = module.eigens.U_WC[:, : module.rank].clone().to(get_model_device(model))
+            module.eigens.V_WC = module.eigens.V_WC[:, : module.rank].clone().to(get_model_device(model))
+        elif module.corda_method == "kpm":
+            module.eigens.S_WC = module.eigens.S_WC[-module.rank :].clone()
+            module.eigens.U_WC = module.eigens.U_WC[:, -module.rank :].clone().to(get_model_device(model))
+            module.eigens.V_WC = module.eigens.V_WC[:, -module.rank :].clone().to(get_model_device(model))
+        else:
+            raise ValueError(f"Invalid corda_method found: {module.corda_method}, it should be 'ipm' or 'kpm'.")
+
+        # Sanity check
+        if module.eigens.S_WC.size(0) != module.rank:
+            raise ValueError(
+                f"rank mismatch: {module.eigens.S_WC.size(0)} vs. {module.rank},"
+                "please file an issue at https://github.com/huggingface/peft/issues."
+            )
+        if module.eigens.U_WC.size(0) != module.weight.size(0):
+            raise ValueError(
+                f"U size mismatch: {module.eigens.U_WC.size(0)} vs. {module.weight.size(0)},"
+                "please file an issue at https://github.com/huggingface/peft/issues."
+            )
+        if module.eigens.U_WC.size(1) != module.rank:
+            raise ValueError(
+                f"U size mismatch: {module.eigens.U_WC.size(1)} vs. {module.rank},"
+                "please file an issue at https://github.com/huggingface/peft/issues."
+            )
+        if module.eigens.V_WC.size(0) != module.weight.size(1):
+            raise ValueError(
+                f"V size mismatch: {module.eigens.V_WC.size(0)} vs. {module.weight.size(1)},"
+                "please file an issue at https://github.com/huggingface/peft/issues."
+            )
+        if module.eigens.V_WC.size(1) != module.rank:
+            raise ValueError(
+                f"V size mismatch: {module.eigens.V_WC.size(1)} vs. {module.rank},"
+                "please file an issue at https://github.com/huggingface/peft/issues."
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/dora.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/dora.py
new file mode 100644
index 0000000000000000000000000000000000000000..3aa66c2be594e23858f79cdc69a1e0c71cb929c2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/dora.py
@@ -0,0 +1,195 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from copy import deepcopy
+
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from peft.utils.integrations import dequantize_module_weight, gather_params_ctx
+from peft.utils.other import transpose
+
+
+class DoraLinearLayer(nn.Module):
+    def __init__(self, fan_in_fan_out):
+        super().__init__()
+        self.fan_in_fan_out = fan_in_fan_out
+
+    def get_weight_norm(self, weight, lora_weight, scaling) -> torch.Tensor:
+        # calculate L2 norm of weight matrix, column-wise
+        weight = transpose(weight, self.fan_in_fan_out)
+        weight = weight + scaling * lora_weight
+        weight_norm = torch.linalg.norm(weight, dim=1).to(weight.dtype)
+        return weight_norm
+
+    def update_layer(self, *, base_layer, lora_A, lora_B, scaling, place_on_cpu=False) -> None:
+        # temporarily convert fp16 to fp32, as fp16 can cause trouble on CPU with PyTorch < 2.2
+        dtype_is_fp16 = lora_A.dtype == torch.float16
+        if dtype_is_fp16:
+            lora_A = lora_A.float()
+            lora_B = lora_B.float()
+
+        with gather_params_ctx(base_layer.parameters()):
+            if base_layer.__class__.__name__ == "Linear4bit":
+                # We have to create a copy of the base layer, otherwise, FSDP will throw an error. 8bit does not work
+                # yet because Int8Params cannot be correctly deep-copied (attributes vanish)
+                base_layer = deepcopy(base_layer)
+
+            weight = dequantize_module_weight(base_layer)
+            if weight.data.ndim >= 4:  # For handling LoRAs applied to Conv layers.
+                lora_weight = torch.mm(lora_B.flatten(start_dim=1), lora_A.flatten(start_dim=1))
+                lora_weight = lora_weight.reshape(weight.shape)
+            else:
+                lora_weight = lora_B @ lora_A
+
+            if dtype_is_fp16:
+                lora_weight = lora_weight.half()
+            weight_norm = self.get_weight_norm(weight.to(lora_A.device), lora_weight, scaling)
+
+        if place_on_cpu:
+            weight_norm = weight_norm.to("cpu")
+        self.weight = nn.Parameter(weight_norm, requires_grad=True)
+
+    def forward(self, x, *, lora_A, lora_B, scaling, base_layer, base_result=None):
+        """
+        For DoRA, calculate the extra output from LoRA with DoRA applied. This should be added on top of the base layer
+        output.
+        """
+        # Don't use `lora_weight = lora_B.weight @ lora_A.weight` because this causes errors with FSDP. Instead,
+        # calculate the same but using forward.
+        x_eye = torch.eye(lora_A.weight.shape[1], device=lora_A.weight.device, dtype=x.dtype)
+        lora_weight = lora_B(lora_A(x_eye)).T
+
+        magnitude = self.weight
+        weight = dequantize_module_weight(base_layer)
+        weight = weight.to(x.dtype)
+        weight_norm = self.get_weight_norm(weight, lora_weight.detach(), scaling)
+        # see section 4.3 of DoRA (https://arxiv.org/abs/2402.09353)
+        # "[...] we suggest treating ||V +∆V ||_c in
+        # Eq. (5) as a constant, thereby detaching it from the gradient
+        # graph. This means that while ||V + ∆V ||_c dynamically
+        # reflects the updates of ∆V , it won’t receive any gradient
+        # during backpropagation"
+        weight_norm = weight_norm.detach()
+        mag_norm_scale = (magnitude / weight_norm).view(1, -1)
+
+        lora_result = lora_B(lora_A(x))
+
+        bias = None
+        if base_result is not None:
+            bias = base_layer.bias
+            if bias is not None:
+                base_result = base_result - bias
+        else:
+            base_result = F.linear(x, transpose(weight, self.fan_in_fan_out))
+
+        result_dora = (mag_norm_scale - 1) * base_result + mag_norm_scale * lora_result * scaling
+
+        return result_dora
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora.dora." + rep
+
+
+class DoraEmbeddingLayer(DoraLinearLayer):
+    def forward(self, x, *, lora_A, lora_B, scaling, base_layer, embed_fn):
+        """
+        For DoRA, calculate the extra output from LoRA with DoRA applied. This should be added on top of the base layer
+        output.
+        """
+        lora_weight = (lora_A @ lora_B).T
+        magnitude = self.weight
+        weight = base_layer.weight
+        weight_norm = self.get_weight_norm(weight, lora_weight.detach(), scaling)
+        # see section 4.3 of DoRA (https://arxiv.org/abs/2402.09353)
+        # "[...] we suggest treating ||V +∆V ||_c in
+        # Eq. (5) as a constant, thereby detaching it from the gradient
+        # graph. This means that while ||V + ∆V ||_c dynamically
+        # reflects the updates of ∆V , it won’t receive any gradient
+        # during backpropagation"
+        weight_norm = weight_norm.detach()
+        mag_norm_scale = magnitude / weight_norm
+        result_dora = mag_norm_scale * (embed_fn(x, lora_A) @ lora_B) * scaling
+        return mag_norm_scale, result_dora
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora.dora." + rep
+
+
+class _DoraConvNdLayer(DoraLinearLayer):
+    def get_weight_norm(self, weight, lora_weight, scaling) -> torch.Tensor:
+        # calculate L2 norm of weight matrix, column-wise
+        weight = weight + scaling * lora_weight
+        # the following is needed to have compatibility with the 4/5D weight tensors of Conv2D/3D
+        dim = tuple(range(1, weight.dim()))
+        weight_norm = weight.norm(p=2, dim=dim, keepdim=True).transpose(1, 0)
+        return weight_norm
+
+    def forward(self, x, *, lora_A, lora_B, scaling, base_layer, base_result=None):
+        """
+        For DoRA, calculate the extra output from LoRA with DoRA applied. This should be added on top of the base layer
+        output.
+        """
+        weight = base_layer.weight
+        lora_weight = torch.mm(lora_B.weight.flatten(start_dim=1), lora_A.weight.flatten(start_dim=1))
+        lora_weight = lora_weight.reshape(weight.shape)
+        magnitude = self.weight
+        weight_norm = self.get_weight_norm(weight, lora_weight.detach(), scaling)
+        # see section 4.3 of DoRA (https://arxiv.org/abs/2402.09353)
+        # "[...] we suggest treating ||V +∆V ||_c in
+        # Eq. (5) as a constant, thereby detaching it from the gradient
+        # graph. This means that while ||V + ∆V ||_c dynamically
+        # reflects the updates of ∆V , it won’t receive any gradient
+        # during backpropagation"
+        weight_norm = weight_norm.detach()
+        mag_norm_scale = magnitude / weight_norm
+
+        if base_result is None:
+            base_result = self.conv_fn(
+                x,
+                weight,
+                bias=None,
+                stride=base_layer.stride,
+                padding=base_layer.padding,
+                dilation=base_layer.dilation,
+                groups=base_layer.groups,
+            )
+        else:
+            bias = base_layer.bias
+            if bias is not None:
+                # reshape bias to (1, -1, 1, ...)
+                bias_shape = (1, -1) + (1,) * (base_result.dim() - 2)
+                base_result = base_result - bias.view(*bias_shape)
+
+        result_dora = (mag_norm_scale - 1) * base_result + mag_norm_scale * lora_B(lora_A(x)) * scaling
+        return result_dora
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora.dora." + rep
+
+
+class DoraConv2dLayer(_DoraConvNdLayer):
+    def __init__(self, fan_in_fan_out):
+        super().__init__(fan_in_fan_out)
+        self.conv_fn = F.conv2d
+
+
+class DoraConv3dLayer(_DoraConvNdLayer):
+    def __init__(self, fan_in_fan_out):
+        super().__init__(fan_in_fan_out)
+        self.conv_fn = F.conv3d
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/eetq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/eetq.py
new file mode 100644
index 0000000000000000000000000000000000000000..e56d58d8565d821f0d41614b337e191c7b833e91
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/eetq.py
@@ -0,0 +1,118 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from typing import Any, List, Optional
+
+import torch
+
+from peft.import_utils import is_eetq_available
+from peft.tuners.lora.layer import LoraLayer
+from peft.tuners.tuners_utils import BaseTunerLayer
+
+
+if is_eetq_available():
+    from eetq import EetqLinear
+
+    class EetqLoraLinear(torch.nn.Module, LoraLayer):
+        def __init__(
+            self,
+            base_layer,
+            adapter_name,
+            r: int = 0,
+            lora_alpha: int = 1,
+            lora_dropout: float = 0.0,
+            init_lora_weights: bool = True,
+            use_rslora: bool = False,
+            use_dora: bool = False,
+            lora_bias: bool = False,
+            **kwargs,
+        ):
+            if use_dora:
+                raise ValueError(f"{self.__class__.__name__} does not support DoRA yet, please set it to False")
+
+            super().__init__()
+            LoraLayer.__init__(self, base_layer)
+
+            # self.base_layer and self.quant_linear_module are the same; we need the former for consistency and the latter
+            # for backwards compatibility
+            self.quant_linear_module = base_layer
+
+            self._active_adapter = adapter_name
+            self.update_layer(
+                adapter_name,
+                r,
+                lora_alpha=lora_alpha,
+                lora_dropout=lora_dropout,
+                init_lora_weights=init_lora_weights,
+                use_rslora=use_rslora,
+                use_dora=use_dora,
+                lora_bias=lora_bias,
+            )
+
+        def forward(self, x: torch.Tensor):
+            result = self.quant_linear_module(x)
+
+            if self.disable_adapters:
+                return result
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+
+                requires_conversion = not torch.is_autocast_enabled()
+                if requires_conversion:
+                    expected_dtype = result.dtype
+                    x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                output = lora_B(lora_A(dropout(x)))
+                if requires_conversion:
+                    output = output.to(expected_dtype)
+                output = output * scaling
+                result = result + output
+            return result
+
+        def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+            raise AttributeError("Merging LoRA layers is not supported for Eetq layers.")
+
+        def unmerge(self) -> None:
+            raise AttributeError("Unmerging LoRA layers is not supported for Eetq layers.")
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "lora." + rep
+
+
+def dispatch_eetq(
+    target: torch.nn.Module,
+    adapter_name: str,
+    **kwargs: Any,
+) -> Optional[torch.nn.Module]:
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    if is_eetq_available() and isinstance(target_base_layer, EetqLinear):
+        new_module = EetqLoraLinear(target, adapter_name, **kwargs)
+        target.weight = target_base_layer.weight
+
+        if hasattr(target, "bias"):
+            target.bias = target_base_layer.bias
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/eva.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/eva.py
new file mode 100644
index 0000000000000000000000000000000000000000..02be2c92d796067a132dcc41cc6b5058f4bec8a7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/eva.py
@@ -0,0 +1,739 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from collections import Counter, defaultdict
+from collections.abc import Mapping
+from contextlib import nullcontext
+from copy import deepcopy
+from functools import partial
+from itertools import cycle
+from typing import Dict, Iterable, Optional, Union
+
+import torch
+import torch.distributed as dist
+from tqdm import tqdm
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import _find_minimal_target_modules, check_target_module_exists
+from peft.utils.constants import MIN_TARGET_MODULES_FOR_OPTIMIZATION
+from peft.utils.incremental_pca import IncrementalPCA
+from peft.utils.other import _get_submodules, get_pattern_key
+
+from .config import LoraConfig
+from .layer import Embedding, LoraLayer, MultiheadAttention, _ConvNd
+
+
+UNSUPPORTED_LORA_MODULES = (Embedding, MultiheadAttention, _ConvNd)
+
+
+class _Hook:
+    """
+    A base class for hooks that prepares layer inputs for EVA.
+    """
+
+    def __init__(
+        self,
+        name: str,
+        prepare_layer_inputs_fn: Optional[callable] = None,
+        gather_distributed_inputs: bool = True,
+    ):
+        self.name = name
+        self.gather_distributed_inputs = gather_distributed_inputs
+        if prepare_layer_inputs_fn is None:
+            self._prepare_layer_inputs_fn = self._prepare_layer_inputs_fn_default
+        else:
+            self._prepare_layer_inputs_fn = prepare_layer_inputs_fn
+        self.model_input = None
+
+    @staticmethod
+    def _prepare_layer_inputs_fn_default(layer_input, model_input, layer_name) -> torch.Tensor:
+        if isinstance(layer_input, torch.Tensor):
+            pass
+        elif isinstance(layer_input, (tuple, list)):
+            layer_input = layer_input[0]
+        else:
+            raise ValueError(
+                f"unsupported input type {type(layer_input)} for prepare_layer_inputs_fn in layer {layer_name}, "
+                "please provide a custom prepare_layer_inputs_fn"
+            )
+        # if the input has more than 2 dimensions, we flatten all but the last dimension
+        if layer_input.ndim > 2:
+            layer_input = layer_input.view(-1, layer_input.size(-1))
+        return layer_input
+
+    @torch.no_grad()
+    def prepare_layer_inputs(self, layer_input):
+        return self._prepare_layer_inputs_fn(layer_input, self.model_input, self.name)
+
+    def gather_layer_inputs(self, layer_input):
+        if dist.is_initialized() and self.gather_distributed_inputs:
+            world_size = dist.get_world_size()
+
+            # First gather sizes from all processes more efficiently
+            local_size = torch.tensor([layer_input.shape[0]], device=layer_input.device)
+            all_sizes = torch.empty(world_size, dtype=local_size.dtype, device=layer_input.device)
+            dist.all_gather_into_tensor(all_sizes, local_size)
+            all_sizes = all_sizes.tolist()
+
+            # Find maximum size and pad tensors
+            padded_input = layer_input.new_zeros((max(all_sizes), *layer_input.shape[1:]))
+            padded_input[: layer_input.shape[0]] = layer_input
+
+            # Gather padded tensors
+            gathered_inputs = [torch.zeros_like(padded_input) for _ in range(world_size)]
+            dist.all_gather(gathered_inputs, padded_input.contiguous())
+
+            # Remove padding for each gathered tensor
+            gathered_inputs = [tensor[:size] for tensor, size in zip(gathered_inputs, all_sizes)]
+
+            # Concatenate along batch dimension
+            return torch.cat(gathered_inputs, dim=0)
+        return layer_input
+
+
+class SVDHook(_Hook):
+    """
+    A forward hook for calculating incremental SVD on layer inputs. The hook is designed to be registered to a PyTorch
+    module using the `register_forward_hook` method.
+
+    This hook performs a step of incremental Singular Value Decomposition (SVD) on the inputs of a specified layer
+    during the forward pass of a neural network. The hook also tracks convergence of the computed components using
+    cosine similarity between the current and previous components.
+
+    Args:
+        name (str): Name of the layer to which this hook is attached.
+        n_components (int): Number of principal components to compute.
+        sim_thresh (Union[float, torch.Tensor]): Similarity threshold for convergence.
+        prepare_layer_inputs_fn (Optional[callable]): Function to prepare layer inputs for SVD.
+    """
+
+    def __init__(
+        self,
+        n_components: int,
+        sim_thresh: Union[float, torch.Tensor],
+        **base_class_kwargs,
+    ):
+        super().__init__(**base_class_kwargs)
+        self.n_components = n_components
+        self.sim_thresh = sim_thresh
+        if isinstance(sim_thresh, torch.Tensor) and len(sim_thresh.shape) > 0:
+            check1 = sim_thresh.size(0) == n_components or sim_thresh.size(0) == 1
+            check2 = len(sim_thresh.shape) == 1
+            if not (check1 and check2):
+                raise ValueError(
+                    "if sim_thresh is a tensor with more than 0 dimensions it must have shape (n_components,) or (1,)"
+                )
+        self.svd = IncrementalPCA(
+            n_components=n_components,
+            copy=True,
+            lowrank=True,
+            lowrank_seed=42,
+        )
+        self.model_input = None
+        self.converged = torch.zeros((n_components,), dtype=torch.bool)
+
+    @torch.no_grad()
+    def __call__(self, model, input, output):
+        previous_components = None
+        if hasattr(self.svd, "components_"):
+            previous_components = self.svd.components_.clone().detach()
+        states = self.prepare_layer_inputs(input)
+        states = self.gather_layer_inputs(states)
+        # check if batch sizes is more than the number of components
+        if states.size(0) < self.n_components:
+            print(f"skipping SVD for {self.name} because there are less than {self.n_components} examples")
+            return
+        self.svd.partial_fit(states.to(torch.float32))
+        # add if statement to check if we are in the first step where previous_components is None
+        if previous_components is None:
+            return
+        components = self.svd.components_
+        if len(components.shape) == 1:
+            components = components.reshape(1, -1)
+            previous_components = previous_components.reshape(1, -1)
+        # consider as converged if enough components have converged via cossim
+        sim = torch.nn.functional.cosine_similarity(components, previous_components)
+        self.converged = sim >= self.sim_thresh
+
+
+# This is used to determine if inputs of two different layers are equal. For such cases, SVD
+# needs to be done for only for one of the equal inputs.
+class HashHook(_Hook):
+    """
+    A forward hook for hashing layer inputs. The hook is designed to be registered to a PyTorch module using the
+    `register_forward_hook` method.
+
+    This hook hashes the inputs of a specified layer during the forward pass of a neural network and stores the hash
+    values for later analysis or comparison.
+
+    Args:
+        name (str): Name of the layer to which this hook is attached. hashed_inputs (list): List of hashed inputs.
+        prepare_layer_inputs_fn (Optional[callable]): Function to prepare layer inputs for hashing.
+    """
+
+    def __init__(self, **base_class_kwargs):
+        super().__init__(**base_class_kwargs)
+        self.hashed_inputs = []
+
+    @staticmethod
+    def hash_fn(tensor):
+        return hash(tuple(tensor.view(-1).tolist()))
+
+    @torch.no_grad()
+    def __call__(self, model, input, output):
+        x = self.prepare_layer_inputs(input)
+        x = self.gather_layer_inputs(x)
+        self.hashed_inputs.append(self.hash_fn(x.cpu()))
+
+
+def find_equal_values(dictionary: dict) -> dict:
+    """
+    Find keys in a dictionary that have the same value.
+
+    This function takes a dictionary and returns a new dictionary containing keys that have the same value. The keys in
+    the output dictionary are the values from the input dictionary, and the values are lists of keys that share the
+    same value.
+    """
+    value_dict = defaultdict(list)
+    for k, v in dictionary.items():
+        value_dict[v].append(k)
+    return {k: v for k, v in value_dict.items() if len(v) > 1}
+
+
+def get_device_with_meta_params(model: torch.nn.Module) -> torch.device:
+    """
+    Get the device of the model's parameters. Useful if some parameters are on meta device.
+    """
+    devices = list({p.device for p in model.parameters() if p.device.type != "meta"})
+    if len(devices) > 1:
+        warnings.warn(f"Could not determine device, model has multiple devices: {devices}")
+        return
+    return devices[0]
+
+
+def move_inputs_to_device(inputs, device: Union[str, torch.device]):
+    """
+    Move the inputs to the specified device. Adapted from hf.Trainer.
+    """
+    if hasattr(inputs, "to"):
+        return inputs.to(device)
+    if isinstance(inputs, Mapping):
+        return type(inputs)({k: move_inputs_to_device(v, device) for k, v in inputs.items()})
+    elif isinstance(inputs, (tuple, list)):
+        return type(inputs)(move_inputs_to_device(v, device) for v in inputs)
+    else:
+        warnings.warn(f"input of type {type(inputs)} could not be moved to the correct device")
+        return inputs
+
+
+def prepare_model_inputs_fn_language_modeling(model_input, peft_config: LoraConfig):
+    """
+    Get the indices of the items that should be used for SVD.
+
+    Attributes:
+        model_input (dict): The model inputs.
+        peft_config (LoraConfig): The configuration for the LoRA layers.
+    """
+    if not isinstance(model_input, dict):
+        raise ValueError("When using `prepare_model_inputs_fn_language_modeling` inputs must be a dictionary")
+    mask = model_input.get("attention_mask", torch.ones_like(model_input["input_ids"])).bool()
+    if peft_config.eva_config.use_label_mask and hasattr(model_input, "labels"):
+        mask = torch.logical_and(mask, model_input["labels"] != peft_config.eva_config.label_mask_value)
+    return mask.nonzero()
+
+
+def prepare_layer_inputs_fn_language_modeling(layer_input, model_input, layer_name) -> torch.Tensor:
+    """
+    if not all items in the input should be used for SVD, this function can be used to get the indices of the items
+    that should be used.
+
+    Attributes:
+        layer_input (torch.Tensor): The layer inputs.
+        model_input (torch.Tensor):
+            The model inputs or if `prepare_model_inputs_fn` is not None the output of this function.
+        layer_name (str): The name of the layer.
+
+    Returns:
+        torch.Tensor: The input to the SVD.
+    """
+    # if layer inputs are not a tensor, we simply get the first item
+    if isinstance(layer_input, torch.Tensor):
+        pass
+    elif isinstance(layer_input, (tuple, list)):
+        layer_input = layer_input[0]
+    else:
+        raise ValueError(
+            f"unsupported input type {type(layer_input)} for prepare_layer_inputs_fn in layer {layer_name}, "
+            "please provide a custom prepare_layer_inputs_fn"
+        )
+    # in this case model_input is the output of `prepare_model_inputs_fn_language_modeling`
+    return layer_input[model_input.T.unbind()]
+
+
+def forward_fn_dict(model, inputs):
+    return model(**inputs)
+
+
+def _get_eva_state_dict(
+    model: torch.nn.Module,
+    dataloader: Iterable,
+    peft_config: Optional[LoraConfig],
+    target_module_check_fn: callable,
+    forward_fn: Optional[callable],
+    prepare_model_inputs_fn: Optional[callable],
+    prepare_layer_inputs_fn: Union[callable, Dict[str, callable], None],
+    gather_distributed_inputs: bool,
+    show_progress_bar: bool,
+) -> dict:
+    # Computes the rank distribution for each layer based on the explained variance ratio.
+    # when rank_pattern flag is False, all values in max_components are the same
+    def _get_rank_distribution(hooks, layer_hook_map, equal_inputs_map, rank_budget, max_components):
+        exp_vars = {k: h[0].svd.explained_variance_ratio_[: max_components[k]] for k, h in hooks.items()}
+        keys, values = zip(*[(k, c) for k, name in layer_hook_map.items() for c in exp_vars[name]])
+        idx = torch.stack(values).argsort(descending=True)
+        counts = Counter([keys[i] for i in idx[:rank_budget]])
+        counts = {k: counts.get(k, 0) for k in layer_hook_map.keys()}  # add layers with 0 rank
+        for k, k_hook in equal_inputs_map.items():
+            # ensure hook layers have the highest rank if they are equal to another layer
+            rank, rank_hook = counts[k], counts[k_hook]
+            if rank_hook >= rank:
+                continue
+            counts[k_hook], counts[k] = rank, rank_hook
+        return counts
+
+    # dataloader is not empty
+    if len(dataloader) == 0:
+        raise ValueError("dataloader is empty")
+
+    # check if dist is initialized
+    if dist.is_initialized() and gather_distributed_inputs:
+        warnings.warn(
+            "torch.distributed is initialized and `gather_distributed_inputs` is True, "
+            "therefore EVA initialization will gather tensors from all ranks. "
+            "Ensure the model does not receive the same inputs on different ranks."
+        )
+
+    # for unusually high rho values, define an upper limit
+    rho_threshold = 1000
+    rho = peft_config.eva_config.rho
+    if rho > rho_threshold:
+        max_dim = max(max(p.shape) for p in model.parameters())
+        rho_ceil = max_dim // peft_config.r
+        rho = min(rho, rho_ceil)
+
+    training = model.training
+    device = get_device_with_meta_params(model)
+    model.eval()
+
+    # get model inputs
+    inputs = next(iter(dataloader))
+    if device is not None:
+        inputs = move_inputs_to_device(inputs, device)
+    if prepare_model_inputs_fn is not None:
+        model_inputs_for_hooks = prepare_model_inputs_fn(inputs, peft_config)
+    else:
+        model_inputs_for_hooks = deepcopy(inputs)
+
+    hooks = {}
+    max_components = {}
+    rank_budget = 0
+    for name, module in model.named_modules():
+        if not target_module_check_fn(name, module):
+            continue
+        if isinstance(prepare_layer_inputs_fn, Mapping):
+            fn = prepare_layer_inputs_fn.pop(name, None)
+        else:
+            fn = prepare_layer_inputs_fn
+        hook = HashHook(name=name, prepare_layer_inputs_fn=fn, gather_distributed_inputs=gather_distributed_inputs)
+        hook.model_input = model_inputs_for_hooks
+        handle = module.register_forward_hook(hook)
+        hooks[name] = (hook, handle)
+        layer_rank = peft_config.rank_pattern.get(
+            get_pattern_key(peft_config.rank_pattern.keys(), name), peft_config.r
+        )
+        max_components[name] = round(layer_rank * rho)
+        rank_budget += layer_rank
+    if isinstance(prepare_layer_inputs_fn, Mapping) and len(prepare_layer_inputs_fn) > 0:
+        raise ValueError(
+            "prepare_layer_inputs_fn is a mapping but the following module names were not found in the model: "
+            f"{prepare_layer_inputs_fn.keys()}"
+        )
+
+    # forward for one batch to check which layer inputs are equal to avoid unneeded svd calculations
+    forward_fn(model, inputs)
+    hash_dict = {k: h[0].hashed_inputs[0] for k, h in hooks.items()}
+    # equal input maps groups layers which receive the same input. One layer is defined as the key and receives an svd
+    # hook. For the remaining layers the svd results can be skipped.
+    equal_inputs = list(find_equal_values(hash_dict).values())
+    equal_inputs_map = {vv: v[0] for v in equal_inputs for vv in v[1:]}
+    # for layers with equal inputs we need to make sure that the max_components are the same
+    for names in equal_inputs:
+        max_value = max(max_components[n] for n in names)
+        for n in names:
+            max_components[n] = max_value
+
+    # initialize svd hooks
+    for name in list(hooks.keys()):
+        hook, handle = hooks.pop(name)
+        handle.remove()
+        if name in equal_inputs_map:
+            continue
+        hook = SVDHook(
+            n_components=max_components[name],
+            sim_thresh=peft_config.eva_config.tau,
+            name=name,
+            prepare_layer_inputs_fn=hook._prepare_layer_inputs_fn,
+            gather_distributed_inputs=gather_distributed_inputs,
+        )
+        module = model.get_submodule(name)
+        handle = module.register_forward_hook(hook)
+        hooks[name] = (hook, handle)  # adding the old handle here so we dont get errors in the first forward pass
+    layer_hook_map = {**dict(zip(hooks.keys(), hooks.keys())), **equal_inputs_map}
+
+    # start svd calculation
+    if show_progress_bar and (not dist.is_initialized() or dist.get_rank() == 0):
+        pbar = tqdm(iter(cycle(dataloader)), position=0, leave=False)
+        use_tqdm = True
+    else:
+        pbar = iter(cycle(dataloader))
+        use_tqdm = False
+    convergence_dict = {k: False for k in hooks.keys()}
+    rank_dist = max_components.copy()
+    for inputs in pbar:
+        if device is not None:
+            inputs = move_inputs_to_device(inputs, device)
+        if prepare_model_inputs_fn is not None:
+            model_inputs_for_hooks = prepare_model_inputs_fn(inputs, peft_config)
+        else:
+            model_inputs_for_hooks = deepcopy(inputs)
+
+        for name in list(hooks.keys()):
+            hook, handle = hooks[name]
+            # check if all components that are needed for the rank distribution have converged
+            converged = torch.all(hook.converged[: rank_dist[name]])
+            # if a layer has switched from not converged to converged in the current step
+            if (not convergence_dict[name]) and converged and handle:
+                handle.remove()
+                handle = None
+                convergence_dict[name] = True
+                continue
+            # if a layer has switched from converged to not converged in the current step
+            elif convergence_dict[name] and not converged:
+                module = model.get_submodule(name)
+                handle = module.register_forward_hook(hook)
+                convergence_dict[name] = False
+            hook.model_input = model_inputs_for_hooks
+            hooks[name] = (hook, handle)
+
+        if use_tqdm:
+            layer_converged = list(convergence_dict.values()) + [
+                convergence_dict[v] for v in equal_inputs_map.values()
+            ]
+            pbar.set_description(f"{sum(layer_converged)}/{len(layer_converged)} layers have converged")
+
+        if all(convergence_dict.values()):
+            break
+
+        forward_fn(model, inputs)
+
+        # in case some hooks have to skip the svd calculation because the number of tokens is less than the number of
+        # components
+        if not all(hasattr(h[0].svd, "components_") for h in hooks.values()):
+            continue
+
+        rank_dist = _get_rank_distribution(hooks, layer_hook_map, equal_inputs_map, rank_budget, max_components)
+
+    # check all custom hooks have been removed
+    remaining_hooks = {n for n, m in model.named_modules() for v in m._forward_hooks.values() if isinstance(v, _Hook)}
+    if len(remaining_hooks) > 0:
+        raise ValueError(
+            f"Found active hooks added by EVA that weren't properly removed: {remaining_hooks}. "
+            "Please report this issue at https://github.com/huggingface/peft/issues"
+        )
+
+    eva_state_dict = {}
+    for name, rank in rank_dist.items():
+        hook = hooks[layer_hook_map[name]][0]
+        if not torch.all(hook.converged[:rank]):
+            raise ValueError(
+                f"Layer {name} has not converged but was assigned rank {rank}. "
+                "Please report this issue at https://github.com/huggingface/peft/issues"
+            )
+        u = hook.svd.components_[:rank]
+        if peft_config.eva_config.whiten:
+            u /= hook.svd.singular_values_[:rank].sqrt().reshape(-1, 1)
+        eva_state_dict[name] = u
+
+    # restore model state
+    model.train(training)
+
+    # move tensors to device
+    if device is not None:
+        eva_state_dict = {k: v.to(device) for k, v in eva_state_dict.items()}
+
+    return eva_state_dict
+
+
+def _load_eva_state_dict(
+    model: torch.nn.Module,
+    eva_state_dict: dict,
+    adapter_name: str,
+):
+    peft_config = model.peft_config[adapter_name]
+    update_layer_kwargs = {
+        "adapter_name": adapter_name,
+        "lora_dropout": peft_config.lora_dropout,
+        "use_rslora": peft_config.use_rslora,
+        "use_dora": peft_config.use_dora,
+        "lora_bias": peft_config.lora_bias,
+    }
+    missing_eva_inits = []
+    new_target_modules = []
+    other_module_names = []
+    rank_pattern = {}
+    alpha_pattern = {}
+    for name, module in model.named_modules():
+        name_in_base_model = name.replace("base_model.model.", "")
+        if not isinstance(module, LoraLayer):
+            other_module_names.append(name_in_base_model)
+            continue
+        # Regexp matching - Find key which matches current target_name in patterns provided
+        r = peft_config.rank_pattern.get(get_pattern_key(peft_config.rank_pattern.keys(), name), peft_config.r)
+        alpha = peft_config.alpha_pattern.get(
+            get_pattern_key(peft_config.alpha_pattern.keys(), name), peft_config.lora_alpha
+        )
+        if name in eva_state_dict:
+            w = eva_state_dict.pop(name)
+            new_rank = w.size(0)
+            if new_rank == 0:
+                parent, _, target_name = _get_submodules(model, name)
+                setattr(parent, target_name, module.get_base_layer())
+                continue
+            elif new_rank != r:
+                if peft_config.eva_config.adjust_scaling_factors:
+                    alpha *= new_rank / r
+            if new_rank != r or module.lora_A[adapter_name].weight.device.type == "meta":
+                module.update_layer(r=new_rank, lora_alpha=alpha, init_lora_weights="eva", **update_layer_kwargs)
+            module.lora_A[adapter_name].weight.copy_(w)
+            new_target_modules.append(name_in_base_model)
+        else:
+            module.update_layer(r=r, lora_alpha=alpha, init_lora_weights=True, **update_layer_kwargs)
+            missing_eva_inits.append(name_in_base_model)
+            new_rank = r
+        # update rank pattern and alpha pattern
+        if new_rank != peft_config.r:
+            rank_pattern[name_in_base_model] = new_rank
+        if alpha != peft_config.lora_alpha:
+            alpha_pattern[name_in_base_model] = alpha
+
+    # update target modules if some lora layers have been removed due to their EVA rank being 0
+    new_target_modules = new_target_modules + missing_eva_inits
+    if len(new_target_modules) >= MIN_TARGET_MODULES_FOR_OPTIMIZATION:
+        new_target_modules = _find_minimal_target_modules(new_target_modules, other_module_names)
+    model.peft_config[adapter_name].target_modules = new_target_modules
+
+    # set rank pattern obtained from EVA
+    model.peft_config[adapter_name].rank_pattern = rank_pattern
+
+    # when adjust_scaling_factors is True, lora scaling factors have been adjusted after the rank redistribution
+    model.peft_config[adapter_name].alpha_pattern = alpha_pattern
+
+    if missing_eva_inits:
+        warnings.warn(
+            "the following layers were initialized with init_lora_weights=True because they "
+            f"were not found in the eva state_dict: {missing_eva_inits}\ncurrently the "
+            f"following lora modules are not supported by EVA: {UNSUPPORTED_LORA_MODULES}"
+        )
+
+
+@torch.no_grad()
+def get_eva_state_dict(
+    model: torch.nn.Module,
+    dataloader: Iterable,
+    peft_config: Optional[LoraConfig] = None,
+    forward_fn: Optional[callable] = forward_fn_dict,
+    prepare_model_inputs_fn: Optional[callable] = prepare_model_inputs_fn_language_modeling,
+    prepare_layer_inputs_fn: Union[callable, Dict[str, callable], None] = prepare_layer_inputs_fn_language_modeling,
+    adapter_name: str = "default",
+    gather_distributed_inputs: bool = True,
+    show_progress_bar: bool = True,
+) -> dict:
+    """
+    Compute the SVD for each layer in the model.
+
+    This function computes the Singular Value Decomposition (SVD) for each layer in the model. It uses the incremental
+    PCA method to compute the SVD components. The function also checks for convergence of the computed components using
+    cosine similarity. The rank distribution for each layer is determined based on the explained variance ratio.
+
+    Args:
+        model (torch.nn.Module): The model to compute the SVD for. Does not need to be a PeftModel.
+        dataloader (Iterable): The dataloader to use for the forward pass.
+        peft_config (Optional[LoraConfig]):
+            The configuration for the LoRA layers. Only required if `model` is not a PeftModel.
+        forward_fn (callable):
+            The forward function to use for the forward pass. Takes two arguments: `model` and `inputs`. Default
+            behavior is `return model(**inputs)`
+        prepare_model_inputs_fn (Optional[callable]):
+            This function receives the model inputs and the peft_config and passes the output to
+            `prepare_layer_inputs_fn`. Can be used to modify the input to the SVD computation based on the original
+            model inputs. For example for language modeling the attention mask is used to determine which indices are
+            padding tokens and should not be used for SVD. Any function defined here expects two arguments:
+            `model_input` and `peft_config`. `peft.tuners.lora.eva.prepare_model_inputs_fn_language_modeling` is used
+            by default.
+        prepare_layer_inputs_fn (Union[callable, Dict[str, callable], None]):
+            This function receives the layer inputs, the model inputs (potentially modified by
+            `prepare_model_inputs_fn`) and the name of the layer and returns the inputs that should be used for SVD for
+            that particular layer. Any custom function defined here expects three arguments: `layer_input`,
+            `model_input`, and `layer_name` and should return a 2d tensor. The default logic can be found in
+            peft.tuners.lora.eva.prepare_layer_inputs_fn_language_modeling and works for language modeling. In this
+            case model_inputs is the mask used to determine which indices should be used for SVD (created by
+            `prepare_model_inputs_fn_language_modeling`).
+        adapter_name (str): The name of the adapter to compute the SVD for.
+        gather_distributed_inputs (bool):
+            Whether to gather the layer inputs from all ranks. Default is True meaning in a distributed setting the
+            layer inputs will be gathered from all ranks for the SVD computation. For non-distributed settings this
+            argument is ignored. Set to False if you are using a non-distributed dataloader in a distributed setting.
+        show_progress_bar (bool): Whether to show a progress bar. Default is True.
+
+    Returns:
+        eva_state_dict (dict): The state dictionary containing the SVD components for each layer.
+    """
+
+    def target_module_check_fn_peft_model(name, module, unsupported_lora_modules):
+        "check if a module is an adapter module via base_layer attribute"
+        return hasattr(module, "base_layer") and not isinstance(module, unsupported_lora_modules)
+
+    def target_module_check_fn_default(name, module, peft_config):
+        "check if a module is an adapter module via target_modules"
+        is_target_module = True
+        if peft_config.target_modules is not None:
+            is_target_module = check_target_module_exists(peft_config, name)
+        # Conv1D for GPT2 support
+        return isinstance(module, (torch.nn.Linear, Conv1D)) and is_target_module
+
+    is_peft_model = hasattr(model, "peft_config")
+
+    # get peft_config
+    if is_peft_model and peft_config is None:
+        peft_config = model.peft_config[adapter_name]
+    elif peft_config is None:
+        raise ValueError("peft_config is required if model is not a PeftModel")
+
+    # setup context and target module check function
+    if is_peft_model:
+        ctx = model.disable_adapter()
+        target_module_check_fn = partial(
+            target_module_check_fn_peft_model, unsupported_lora_modules=UNSUPPORTED_LORA_MODULES
+        )
+    else:
+        ctx = nullcontext()
+        target_module_check_fn = partial(target_module_check_fn_default, peft_config=peft_config)
+
+    with ctx:
+        eva_state_dict = _get_eva_state_dict(
+            model=model,
+            dataloader=dataloader,
+            peft_config=peft_config,
+            target_module_check_fn=target_module_check_fn,
+            forward_fn=forward_fn,
+            prepare_model_inputs_fn=prepare_model_inputs_fn,
+            prepare_layer_inputs_fn=prepare_layer_inputs_fn,
+            gather_distributed_inputs=gather_distributed_inputs,
+            show_progress_bar=show_progress_bar,
+        )
+    return eva_state_dict
+
+
+@torch.no_grad()
+def initialize_lora_eva_weights(
+    model: torch.nn.Module,
+    dataloader: Optional[Iterable] = None,
+    eva_state_dict: Optional[dict] = None,
+    forward_fn: Optional[callable] = forward_fn_dict,
+    prepare_model_inputs_fn: Optional[callable] = prepare_model_inputs_fn_language_modeling,
+    prepare_layer_inputs_fn: Union[callable, Dict[str, callable], None] = prepare_layer_inputs_fn_language_modeling,
+    adapter_name: str = "default",
+    gather_distributed_inputs: bool = True,
+    show_progress_bar: bool = True,
+):
+    """
+    Initialize the weights of the LoRA layers using the EVA method.
+
+    This function initializes the weights of the LoRA layers using the EVA method. It computes the SVD for each adapter
+    layer and updates the weights accordingly.
+
+    Args:
+        model (PeftModel): The peft model to compute the SVD for.
+        dataloader (Optional[Iterable]):
+            The dataloader to use for the forward pass. If None, eva_state_dict needs to be provided.
+        eva_state_dict (Optional[dict]):
+            The state_dict to load into the model. If None, a dataloader needs to be provided and the state_dict will
+            be computed using `get_eva_state_dict`.
+        forward_fn (callable):
+            The forward function to use for the forward pass. Takes two arguments: `model` and `inputs`. Default
+            behavior is `return model(**inputs)`
+        prepare_model_inputs_fn (Optional[callable]):
+            This function receives the model inputs and the peft_config and passes the output to
+            `prepare_layer_inputs_fn`. Can be used to modify the input to the SVD computation based on the original
+            model inputs. For example for language modeling the attention mask is used to determine which indices are
+            padding tokens and should not be used for SVD. Any function defined here expects two arguments:
+            `model_input` and `peft_config`. `peft.tuners.lora.eva.prepare_model_inputs_fn_language_modeling` is used
+            by default.
+        prepare_layer_inputs_fn (Union[callable, Dict[str, callable], None]):
+            This function receives the layer inputs, the model inputs (potentially modified by
+            `prepare_model_inputs_fn`) and the name of the layer and returns the inputs that should be used for SVD for
+            that particular layer. Any custom function defined here expects three arguments: `layer_input`,
+            `model_input`, and `layer_name` and should return a 2d tensor. The default logic can be found in
+            peft.tuners.lora.eva.prepare_layer_inputs_fn_language_modeling and works for language modeling. In this
+            case model_inputs is the mask used to determine which indices should be used for SVD (created by
+            `prepare_model_inputs_fn_language_modeling`).
+        adapter_name (str): The name of the adapter to initialize the weights for.
+        gather_distributed_inputs (bool):
+            Whether to gather the layer inputs from all ranks. Default is True meaning in a distributed setting the
+            layer inputs will be gathered from all ranks for the SVD computation. For non-distributed settings this
+            argument is ignored. Set to False if you are using a non-distributed dataloader in a distributed setting.
+        show_progress_bar (bool): Whether to show a progress bar. Default is True.
+
+    Returns:
+        model (torch.nn.Module): The model with the initialized LoRA weights.
+    """
+    if not hasattr(model, "peft_config"):
+        raise ValueError("model must be a PeftModel")
+
+    # eva currently only works with a single active adapter
+    # Important: when removing this requirement, make sure eva init works correctly if the new rank is 0.
+    if len(model.active_adapters) > 1:
+        raise ValueError("`initialize_lora_eva_weights` currently only works with a single active adapter")
+
+    # initialize_lora_eva_weights only works with `init_lora_weights='eva'`
+    if model.peft_config[adapter_name].init_lora_weights != "eva":
+        raise ValueError("`initialize_lora_eva_weights` can only be used with `init_lora_weights='eva'`")
+
+    # compute svd
+    if eva_state_dict is None:
+        if dataloader is None:
+            raise ValueError("dataloader is required if eva_state_dict is not provided")
+        eva_state_dict = get_eva_state_dict(
+            model=model,
+            dataloader=dataloader,
+            forward_fn=forward_fn,
+            prepare_model_inputs_fn=prepare_model_inputs_fn,
+            prepare_layer_inputs_fn=prepare_layer_inputs_fn,
+            adapter_name=adapter_name,
+            gather_distributed_inputs=gather_distributed_inputs,
+            show_progress_bar=show_progress_bar,
+        )
+
+    _load_eva_state_dict(model, eva_state_dict, adapter_name)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/gptq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/gptq.py
new file mode 100644
index 0000000000000000000000000000000000000000..d16cfffb58bf1145ff3cae89228dd260384eee9f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/gptq.py
@@ -0,0 +1,130 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from typing import Any, Optional
+
+import torch
+
+from peft.import_utils import is_gptqmodel_available
+from peft.tuners.lora.layer import LoraLayer
+from peft.tuners.tuners_utils import BaseTunerLayer
+from peft.utils import get_auto_gptq_quant_linear
+
+
+class GPTQLoraLinear(torch.nn.Module, LoraLayer):
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        init_lora_weights: bool = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+        **kwargs,
+    ):
+        super().__init__()
+        LoraLayer.__init__(self, base_layer)
+
+        if use_dora:
+            raise ValueError(f"{self.__class__.__name__} does not support DoRA yet, please set it to False")
+
+        # self.base_layer and self.quant_linear_module are the same; we need the former for consistency and the latter
+        # for backwards compatibility
+        self.quant_linear_module = base_layer
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name,
+            r,
+            lora_alpha=lora_alpha,
+            lora_dropout=lora_dropout,
+            init_lora_weights=init_lora_weights,
+            use_rslora=use_rslora,
+            use_dora=use_dora,
+            lora_bias=lora_bias,
+        )
+
+    def forward(self, x: torch.Tensor):
+        # note: logic differs from default Linear because merging is not supported
+        result = self.quant_linear_module(x)
+
+        if self.disable_adapters:
+            return result
+
+        lora_A_keys = self.lora_A.keys()
+        for active_adapter in self.active_adapters:
+            if active_adapter not in lora_A_keys:
+                continue
+
+            lora_A = self.lora_A[active_adapter]
+            lora_B = self.lora_B[active_adapter]
+            dropout = self.lora_dropout[active_adapter]
+            scaling = self.scaling[active_adapter]
+
+            requires_conversion = not torch.is_autocast_enabled()
+            if requires_conversion:
+                expected_dtype = result.dtype
+                x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+            output = lora_B(lora_A(dropout(x)))
+
+            if requires_conversion:
+                output = output.to(expected_dtype)
+
+            if scaling != 1:  # skip scaling == 1 no-op
+                output = output * scaling
+
+            result += output
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+    # TODO: Check if it is better as suggested by users https://github.com/PanQiWei/AutoGPTQ/pull/102
+    # def reset_lora_parameters(self, adapter_name):
+    #     if adapter_name in self.lora_A.keys():
+    #         torch.nn.init.xavier_uniform_(self.lora_A[adapter_name].weight)
+    #         torch.nn.init.zeros_(self.lora_B[adapter_name].weight)
+
+
+def dispatch_gptq(
+    target: torch.nn.Module,
+    adapter_name: str,
+    **kwargs: Any,
+) -> Optional[torch.nn.Module]:
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    cfg = kwargs.get("gptq_quantization_config", None)
+
+    if is_gptqmodel_available():
+        from gptqmodel.nn_modules.qlinear import BaseQuantLinear
+
+        if isinstance(target_base_layer, BaseQuantLinear):
+            new_module = GPTQLoraLinear(target, adapter_name, **kwargs)
+            target.qweight = target_base_layer.qweight
+    else:
+        quant_linear = get_auto_gptq_quant_linear(cfg)
+
+        if quant_linear is not None and isinstance(target_base_layer, quant_linear):
+            new_module = GPTQLoraLinear(target, adapter_name, **kwargs)
+            target.qweight = target_base_layer.qweight
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/hqq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/hqq.py
new file mode 100644
index 0000000000000000000000000000000000000000..4f5a1e0f66cc7efecfb96feedca2e82dc15733f0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/hqq.py
@@ -0,0 +1,259 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import copy
+import warnings
+from typing import Any, Optional
+
+import torch
+
+from peft.import_utils import is_hqq_available
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+from peft.utils.other import transpose
+
+from .layer import LoraLayer
+
+
+if is_hqq_available():
+    from hqq.core.quantize import HQQLinear
+
+    class HqqLoraLinear(torch.nn.Module, LoraLayer):
+        # Lora implemented in a dense layer
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            r: int = 0,
+            lora_alpha: int = 1,
+            lora_dropout: float = 0.0,
+            init_lora_weights: bool = True,
+            use_rslora: bool = False,
+            use_dora: bool = False,
+            lora_bias: bool = False,
+            **kwargs,
+        ) -> None:
+            if lora_bias:
+                raise ValueError(f"{self.__class__.__name__} does not support lora_bias yet, set it to False")
+
+            super().__init__()
+            LoraLayer.__init__(self, base_layer)
+            self.fan_in_fan_out = False
+
+            self._active_adapter = adapter_name
+            self.update_layer(
+                adapter_name,
+                r,
+                lora_alpha=lora_alpha,
+                lora_dropout=lora_dropout,
+                init_lora_weights=init_lora_weights,
+                use_rslora=use_rslora,
+                use_dora=use_dora,
+                lora_bias=lora_bias,
+            )
+
+        def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+            """
+            Merge the active adapter weights into the base weights
+
+            Args:
+                safe_merge (`bool`, *optional*):
+                    If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                    before merging the weights. This is useful if you want to check if the merge operation will produce
+                    NaNs. Defaults to `False`.
+                adapter_names (`list[str]`, *optional*):
+                    The list of adapter names that should be merged. If None, all active adapters will be merged.
+                    Defaults to `None`.
+            """
+            adapter_names = check_adapters_to_merge(self, adapter_names)
+            if not adapter_names:
+                # no adapter to merge
+                return
+
+            for active_adapter in adapter_names:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                layer = self.get_base_layer()
+                quant_config = {**copy.deepcopy(layer.quant_config), "offload_meta": layer.offload_meta}
+                lora_data = self.get_delta_weight(active_adapter)
+
+                output = layer.dequantize()
+                if not self.use_dora[active_adapter]:
+                    w_data = output + lora_data
+                else:
+                    # handle dora
+                    # since output already includes scaling, set it to 1 here
+                    weight_norm = self._get_weight_norm(output, lora_data, scaling=1).detach()
+                    # We need to cache weight_norm because it has to be based on the original weights. We
+                    # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                    # different value
+                    self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                    dora_factor = self.lora_magnitude_vector[active_adapter] / weight_norm
+                    w_data = dora_factor.view(-1, 1) * (output + lora_data)
+
+                if safe_merge and not torch.isfinite(w_data).all():
+                    raise ValueError(
+                        f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                    )
+                new_hqq_layer = HQQLinear(None, quant_config, compute_dtype=layer.compute_dtype, device=layer.device)
+                quant_config.pop("offload_meta", None)
+                new_hqq_layer.quantize(w_data, **quant_config)
+                self.base_layer = new_hqq_layer
+                self.merged_adapters.append(active_adapter)
+
+        def unmerge(self) -> None:
+            """
+            This method unmerges all merged adapter layers from the base weights.
+            """
+            if not self.merged:
+                warnings.warn("Already unmerged. Nothing to do.")
+                return
+
+            while len(self.merged_adapters) > 0:
+                active_adapter = self.merged_adapters.pop()
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                lora_data = self.get_delta_weight(active_adapter)
+                layer = self.get_base_layer()
+                quant_config = {**copy.deepcopy(layer.quant_config), "offload_meta": layer.offload_meta}
+                output = layer.dequantize()
+
+                if not self.use_dora[active_adapter]:
+                    w_data = output - lora_data
+                else:
+                    weight_norm = self._cache_pop(f"{active_adapter}-weight_norm")
+                    dora_factor = self.lora_magnitude_vector[active_adapter] / weight_norm
+                    w_data = output.data / dora_factor.view(-1, 1) - lora_data
+
+                new_hqq_layer = HQQLinear(None, quant_config, compute_dtype=layer.compute_dtype, device=layer.device)
+                quant_config.pop("offload_meta", None)
+                new_hqq_layer.quantize(w_data, **quant_config)
+                self.base_layer = new_hqq_layer
+
+        def get_delta_weight(self, adapter):
+            return (
+                transpose(
+                    self.lora_B[adapter].weight @ self.lora_A[adapter].weight,
+                    False,
+                )
+                * self.scaling[adapter]
+            )
+
+        def _mixed_batch_forward(
+            self, x: torch.Tensor, *args: Any, adapter_names: list[str], **kwargs: Any
+        ) -> torch.Tensor:
+            # This is a special method that handles the case when users pass the argument `adapter_names`. This is an
+            # extra argument that allows mixing different adapters in the same batch at inference time.
+            result = self.base_layer(x, *args, **kwargs)
+
+            unique_adapters = set(adapter_names)
+            sub_batch_indices_list = []
+            for adapter in unique_adapters:
+                sub_batch_indices_list.append([index for index, item in enumerate(adapter_names) if item == adapter])
+
+            for i, active_adapter in enumerate(unique_adapters):
+                if active_adapter == "__base__":
+                    continue
+                if active_adapter not in self.lora_A.keys():
+                    continue
+
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+
+                requires_conversion = not torch.is_autocast_enabled()
+                if requires_conversion:
+                    expected_dtype = result.dtype
+                    x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                # getting the sub-batch, passing it to LoRA layers and updating the corresponding indices of the linear
+                # layer output
+                sub_batch = x[sub_batch_indices_list[i]]
+                output = lora_B(lora_A(dropout(sub_batch))) * scaling
+                if requires_conversion:
+                    output = output.to(expected_dtype)
+                result[sub_batch_indices_list[i]] += output
+
+            return result
+
+        def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+            self._check_forward_args(x, *args, **kwargs)
+            adapter_names = kwargs.pop("adapter_names", None)
+
+            if self.disable_adapters:
+                if self.merged:
+                    self.unmerge()
+                result = self.base_layer(x, *args, **kwargs)
+            elif adapter_names is not None:
+                result = self._mixed_batch_forward(x, *args, adapter_names=adapter_names, **kwargs)
+            elif self.merged:
+                result = self.base_layer(x, *args, **kwargs)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+
+                for active_adapter in self.active_adapters:
+                    if active_adapter not in self.lora_A.keys():
+                        continue
+                    lora_A = self.lora_A[active_adapter]
+                    lora_B = self.lora_B[active_adapter]
+                    dropout = self.lora_dropout[active_adapter]
+                    scaling = self.scaling[active_adapter]
+
+                    requires_conversion = not torch.is_autocast_enabled()
+                    if requires_conversion:
+                        expected_dtype = result.dtype
+                        x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                    if not self.use_dora[active_adapter]:
+                        result = result + lora_B(lora_A(dropout(x))) * scaling
+                    else:
+                        if isinstance(dropout, torch.nn.Identity) or not self.training:
+                            base_result = result
+                        else:
+                            x = dropout(x)
+                            base_result = None
+
+                        result = result + self.lora_magnitude_vector[active_adapter](
+                            x,
+                            lora_A=lora_A,
+                            lora_B=lora_B,
+                            scaling=scaling,
+                            base_layer=self.get_base_layer(),
+                            base_result=base_result,
+                        )
+                    if requires_conversion:
+                        result = result.to(expected_dtype)
+
+            return result
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "lora." + rep
+
+
+def dispatch_hqq(target: torch.nn.Module, adapter_name: str, **kwargs):
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    if is_hqq_available() and isinstance(target_base_layer, HQQLinear):
+        new_module = HqqLoraLinear(target_base_layer, adapter_name, **kwargs)
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..0d6cfcb41110fce20337ec0964f11e42febfcb8d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/layer.py
@@ -0,0 +1,1775 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import math
+import warnings
+from typing import Any, Optional, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from accelerate.utils.imports import is_xpu_available
+from torch import svd_lowrank
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+from peft.utils.integrations import (
+    dequantize_module_weight,
+    gather_params_ctx,
+    get_bnb_param_type,
+    skip_init_on_device,
+)
+from peft.utils.other import transpose
+
+from .config import LoraConfig
+from .dora import DoraConv2dLayer, DoraConv3dLayer, DoraEmbeddingLayer, DoraLinearLayer, _DoraConvNdLayer
+
+
+class LoraLayer(BaseTunerLayer):
+    # All names of layers that may contain (trainable) adapter weights
+    adapter_layer_names = ("lora_A", "lora_B", "lora_embedding_A", "lora_embedding_B")
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("r", "lora_alpha", "scaling", "lora_dropout")
+
+    def __init__(self, base_layer: nn.Module, ephemeral_gpu_offload: bool = False, **kwargs) -> None:
+        self.base_layer = base_layer
+        self.r = {}
+        self.lora_alpha = {}
+        self.scaling = {}
+        self.lora_dropout = nn.ModuleDict({})
+        self.lora_A = nn.ModuleDict({})
+        self.lora_B = nn.ModuleDict({})
+        # For Embedding layer
+        self.lora_embedding_A = nn.ParameterDict({})
+        self.lora_embedding_B = nn.ParameterDict({})
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+        self.use_dora: dict[str, bool] = {}
+        self.lora_bias: dict[str, bool] = {}
+        self.lora_magnitude_vector = torch.nn.ModuleDict()  # for DoRA
+        self._caches: dict[str, Any] = {}
+        self.ephemeral_gpu_offload: bool = ephemeral_gpu_offload
+        # flag to enable/disable casting of input to weight dtype during forward call
+        self.cast_input_dtype_enabled: bool = True
+        self.kwargs = kwargs
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, nn.Conv1d):
+            in_features, out_features = base_layer.in_channels, base_layer.out_channels
+        elif isinstance(base_layer, nn.Conv2d):
+            in_features, out_features = base_layer.in_channels, base_layer.out_channels
+        elif isinstance(base_layer, nn.Conv3d):
+            in_features, out_features = base_layer.in_channels, base_layer.out_channels
+        elif isinstance(base_layer, nn.Embedding):
+            in_features, out_features = base_layer.num_embeddings, base_layer.embedding_dim
+        elif isinstance(base_layer, Conv1D):
+            in_features, out_features = (
+                base_layer.weight.ds_shape if hasattr(base_layer.weight, "ds_shape") else base_layer.weight.shape
+            )
+        elif isinstance(base_layer, nn.MultiheadAttention):
+            if not base_layer._qkv_same_embed_dim:
+                raise ValueError(f"Only same dim for query/key/value is supported as of now for {self.__class__}.")
+            in_features, out_features = base_layer.embed_dim, 3 * base_layer.embed_dim
+        elif hasattr(base_layer, "infeatures") and hasattr(base_layer, "outfeatures"):
+            # QuantLinear
+            in_features, out_features = base_layer.infeatures, base_layer.outfeatures
+        elif hasattr(base_layer, "input_size") and hasattr(base_layer, "output_size"):
+            # Megatron ColumnParallelLinear,RowParallelLinear
+            in_features, out_features = base_layer.input_size, base_layer.output_size
+        elif hasattr(base_layer, "codebooks") and base_layer.__class__.__name__ == "QuantizedLinear":
+            # AQLM QuantLinear
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif hasattr(base_layer, "w_bit") and base_layer.__class__.__name__ == "WQLinear_GEMM":
+            # Awq layers
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif base_layer.__class__.__name__ == "EetqLinear":
+            # Eetq layers
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif hasattr(base_layer, "W_q") and base_layer.__class__.__name__ == "HQQLinear":
+            # HQQ layers
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        else:
+            # possibly support user provided custom layer types using dynamic dispatch
+            if hasattr(base_layer, "in_features") and hasattr(base_layer, "out_features"):
+                in_features, out_features = base_layer.in_features, base_layer.out_features
+            else:
+                in_features, out_features = None, None
+            warnings.warn(
+                f"Unsupported layer type '{type(base_layer)}' encountered, proceed at your own risk.", UserWarning
+            )
+
+        self.in_features = in_features
+        self.out_features = out_features
+
+    def update_layer(
+        self,
+        adapter_name,
+        r,
+        lora_alpha,
+        lora_dropout,
+        init_lora_weights,
+        use_rslora,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+    ):
+        # This code works for linear layers, override for other layer types
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+
+        self.r[adapter_name] = r
+        self.lora_alpha[adapter_name] = lora_alpha
+        if lora_dropout > 0.0:
+            lora_dropout_layer = nn.Dropout(p=lora_dropout)
+        else:
+            lora_dropout_layer = nn.Identity()
+
+        self.lora_dropout.update(nn.ModuleDict({adapter_name: lora_dropout_layer}))
+        # Actual trainable parameters
+        self.lora_A[adapter_name] = nn.Linear(self.in_features, r, bias=False)
+        self.lora_B[adapter_name] = nn.Linear(r, self.out_features, bias=lora_bias)
+        self.lora_bias[adapter_name] = lora_bias
+
+        if use_rslora:
+            self.scaling[adapter_name] = lora_alpha / math.sqrt(r)
+        else:
+            self.scaling[adapter_name] = lora_alpha / r
+
+        # for inits that require access to the base weight, use gather_param_ctx so that the weight is gathered when using DeepSpeed
+        if isinstance(init_lora_weights, str) and init_lora_weights.startswith("pissa"):
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.pissa_init(adapter_name, init_lora_weights)
+        elif isinstance(init_lora_weights, str) and init_lora_weights.startswith("corda"):
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.corda_init(adapter_name, init_lora_weights)
+        elif isinstance(init_lora_weights, str) and init_lora_weights.lower() == "olora":
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.olora_init(adapter_name)
+        elif init_lora_weights == "loftq":
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.loftq_init(adapter_name)
+        elif init_lora_weights == "eva":
+            nn.init.zeros_(self.lora_B[adapter_name].weight)
+        elif init_lora_weights:
+            self.reset_lora_parameters(adapter_name, init_lora_weights)
+        # call this before dora_init
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+
+        if use_dora:
+            self.dora_init(adapter_name)
+            self.use_dora[adapter_name] = True
+        else:
+            self.use_dora[adapter_name] = False
+
+        self.set_adapter(self.active_adapters)
+
+    def reset_lora_parameters(self, adapter_name, init_lora_weights):
+        if init_lora_weights is False:
+            return
+
+        if adapter_name in self.lora_A.keys():
+            if init_lora_weights is True:
+                # initialize A the same way as the default for nn.Linear and B to zero
+                # https://github.com/microsoft/LoRA/blob/a0a92e0f26c067cf94747bdbf1ce73793fa44d19/loralib/layers.py#L124
+                nn.init.kaiming_uniform_(self.lora_A[adapter_name].weight, a=math.sqrt(5))
+            elif init_lora_weights.lower() == "gaussian":
+                nn.init.normal_(self.lora_A[adapter_name].weight, std=1 / self.r[adapter_name])
+            else:
+                raise ValueError(f"Unknown initialization {init_lora_weights=}")
+            nn.init.zeros_(self.lora_B[adapter_name].weight)
+            if self.lora_bias[adapter_name]:
+                nn.init.zeros_(self.lora_B[adapter_name].bias)
+        if adapter_name in self.lora_embedding_A.keys():
+            # Initialize A to zeros and B the same way as the default for nn.Embedding, see:
+            # https://github.com/microsoft/LoRA/blob/4c0333854cb905966f8cc4e9a74068c1e507c7b7/loralib/layers.py#L59-L60
+            nn.init.zeros_(self.lora_embedding_A[adapter_name])
+            nn.init.normal_(self.lora_embedding_B[adapter_name])
+            if self.lora_bias[adapter_name]:
+                # embeddings are not supported at the moment, but still adding this for consistency
+                nn.init.zeros_(self.lora_embedding_B[adapter_name].bias)
+
+    def olora_init(self, adapter_name):
+        base_layer = self.get_base_layer()
+        orig_weight = base_layer.weight
+        bnb_param_type = get_bnb_param_type(orig_weight)
+        dtype = orig_weight.dtype
+
+        if bnb_param_type:
+            # check without importing bitsandbytes and robust to bnb_4bit_quant_storage=float*
+            weight_tensor = dequantize_module_weight(base_layer)
+        elif dtype in [torch.float32, torch.float16, torch.bfloat16]:
+            weight_tensor = orig_weight
+        else:
+            raise TypeError(f"Unsupported data type for the base layer. Got {dtype}.")
+
+        scale_factor = self.scaling[adapter_name]
+        r = self.r[adapter_name]
+        weight_tensor = weight_tensor.to(torch.float32)
+        Q, R = torch.linalg.qr(weight_tensor.data)
+
+        Qr, Rr = Q[:, :r], R[:r]
+
+        self.lora_A[adapter_name].weight.data = Rr.contiguous()
+        self.lora_B[adapter_name].weight.data = Qr.contiguous()
+
+        weight_tensor.data -= scale_factor * self.lora_B[adapter_name].weight @ self.lora_A[adapter_name].weight
+        if bnb_param_type == "4bit":
+            weight_tensor = orig_weight.__class__(
+                weight_tensor,
+                quant_type=orig_weight.quant_type,
+                quant_storage=orig_weight.quant_storage,
+                compress_statistics=orig_weight.compress_statistics,
+                module=orig_weight.module,
+            ).to(orig_weight.device)
+            base_layer.weight = weight_tensor
+        elif bnb_param_type == "8bit":
+            weight_tensor = orig_weight.__class__(
+                weight_tensor,
+                requires_grad=orig_weight.requires_grad,
+                has_fp16_weights=orig_weight.has_fp16_weights,
+            ).to(orig_weight.device)
+            base_layer.weight = weight_tensor
+        else:
+            weight_tensor = weight_tensor.to(dtype)
+            base_layer.weight.data = weight_tensor
+
+    def pissa_init(self, adapter_name, init_lora_weights):
+        weight = self.get_base_layer().weight
+        dtype = weight.dtype
+        if dtype not in [torch.float32, torch.float16, torch.bfloat16]:
+            raise TypeError(
+                "Please initialize PiSSA under float32, float16, or bfloat16. "
+                "Subsequently, re-quantize the residual model to help minimize quantization errors."
+            )
+        weight = transpose(weight.to(torch.float32), self.fan_in_fan_out)
+        if init_lora_weights == "pissa":
+            # USV^T = W <-> VSU^T = W^T, where W^T = weight.data in R^{out_channel, in_channel},
+            V, S, Uh = torch.linalg.svd(weight.data, full_matrices=False)
+            Vr = V[:, : self.r[adapter_name]]
+            Sr = S[: self.r[adapter_name]]
+            Sr /= self.scaling[adapter_name]
+            Uhr = Uh[: self.r[adapter_name]]
+        elif len(init_lora_weights.split("_niter_")) == 2:
+            Vr, Sr, Ur = svd_lowrank(
+                weight.data, self.r[adapter_name], niter=int(init_lora_weights.split("_niter_")[-1])
+            )
+            Sr /= self.scaling[adapter_name]
+            Uhr = Ur.t()
+        else:
+            raise ValueError(
+                f"init_lora_weights should be 'pissa' or 'pissa_niter_[number of iters]', got {init_lora_weights} instead."
+            )
+
+        lora_A = torch.diag(torch.sqrt(Sr)) @ Uhr
+        lora_B = Vr @ torch.diag(torch.sqrt(Sr))
+        self.lora_A[adapter_name].weight.data = lora_A
+        self.lora_B[adapter_name].weight.data = lora_B
+        weight = weight.data - self.scaling[adapter_name] * lora_B @ lora_A
+        weight = transpose(weight.to(dtype), self.fan_in_fan_out)
+        self.get_base_layer().weight.data = weight
+
+    def corda_init(self, adapter_name, init_lora_weights):
+        linear = self.get_base_layer()
+        weight = linear.weight
+        dtype = weight.dtype
+        if dtype not in [torch.float32, torch.float16, torch.bfloat16]:
+            raise TypeError(
+                "Please initialize CorDA under float32, float16, or bfloat16. "
+                "Subsequently, re-quantize the residual model to help minimize quantization errors."
+            )
+        weight = weight.to(torch.float32)
+        out_dim = weight.data.size(0)
+        in_dim = weight.data.size(1)
+
+        # Calculate WC from covariance matrix
+        if not hasattr(linear, "eigens"):
+            raise ValueError(
+                "`eigens` attribute not found for layer, please run `preprocess_corda` first. "
+                "More information can be found at examples/corda_finetuning/README.md."
+            )
+        eigens = linear.eigens
+        U = eigens.U_WC
+        S = eigens.S_WC
+        V = eigens.V_WC
+        r = self.r[adapter_name]
+
+        # nan or inf check
+        if torch.isnan(S).any() or torch.isinf(S).any():
+            raise ValueError(
+                "Invalid value found in matrix S. Please file an issue at https://github.com/huggingface/peft/issues."
+            )
+        if torch.isnan(U).any() or torch.isinf(U).any():
+            raise ValueError(
+                "Invalid value found in matrix U. Please file an issue at https://github.com/huggingface/peft/issues."
+            )
+        if torch.isnan(V).any() or torch.isinf(V).any():
+            raise ValueError(
+                "Invalid value found in matrix V. Please file an issue at https://github.com/huggingface/peft/issues."
+            )
+
+        # Sanity check
+        if U.size(0) != out_dim or U.size(1) != r:
+            raise ValueError(
+                f"Matrix U size mismatch: {U.size()} vs. ({out_dim}, {r}). Please make sure the `lora_config` and "
+                "`model` argument of `preprocess_corda` is consistent with `get_peft_model`. If you're using cache "
+                "in `preprocess_corda`, please make sure the cache is built with the same model and LoRA rank."
+            )
+        if S.size(0) != r:
+            raise ValueError(
+                f"Matrix S size mismatch: {S.size()} vs. ({r},). Please make sure the `lora_config` and `model` argument "
+                "of `preprocess_corda` is consistent with `get_peft_model`. If you're using cache in `preprocess_corda`, "
+                "please make sure the cache is built with the same model and LoRA rank."
+            )
+        if V.size(0) != in_dim or V.size(1) != r:
+            raise ValueError(
+                f"Matrix V size mismatch: {V.size()} vs. ({in_dim}, {r}). Please make sure the `lora_config` and "
+                "`model` argument of `preprocess_corda` is consistent with `get_peft_model`. If you're using cache "
+                "in `preprocess_corda`, please make sure the cache is built with the same model and LoRA rank."
+            )
+
+        # Apply alpha
+        S /= self.scaling[adapter_name]
+
+        # Init lora_A and lora_B weights
+        lora_A = V.t().mul(S.sqrt().view(-1, 1)).contiguous()
+        lora_B = U.mul(S.sqrt()).contiguous()
+        self.lora_A[adapter_name].weight.data = lora_A
+        self.lora_B[adapter_name].weight.data = lora_B
+        weight = weight.data - self.scaling[adapter_name] * lora_B @ lora_A
+        weight = weight.to(dtype)
+        self.get_base_layer().weight.data = weight
+
+        # Remove redundant fields
+        del linear.eigens
+
+    def loftq_init(self, adapter_name):
+        from peft.utils.loftq_utils import loftq_init
+
+        weight = self.get_base_layer().weight
+        kwargs = {
+            "num_bits": self.kwargs.get("loftq_bits", 4),
+            "reduced_rank": self.r[adapter_name],
+            "num_iter": self.kwargs.get("loftq_iter", 1),
+        }
+
+        qweight, lora_A, lora_B = loftq_init(weight, **kwargs)
+        if adapter_name in self.lora_A.keys():
+            # initialize A the same way as the default for nn.Linear and B to zero
+            self.lora_A[adapter_name].weight.data = lora_A
+            self.lora_B[adapter_name].weight.data = lora_B
+        if adapter_name in self.lora_embedding_A.keys():
+            # initialize a the same way as the default for nn.linear and b to zero
+            self.lora_embedding_A[adapter_name].weight.data = lora_A
+            self.lora_embedding_B[adapter_name].weight.data = lora_B
+        self.get_base_layer().weight.data = qweight
+
+    def dora_init(self, adapter_name: str) -> None:
+        if not self.lora_magnitude_vector:
+            # first dora layer being added, add lora_magnitude_vector to the list of learnable parameters
+            self.adapter_layer_names = self.adapter_layer_names[:] + ("lora_magnitude_vector",)
+
+        dora_layer = DoraLinearLayer(fan_in_fan_out=getattr(self, "fan_in_fan_out", False))
+        lora_A = self.lora_A[adapter_name].weight
+        lora_B = self.lora_B[adapter_name].weight
+        place_on_cpu = self.ephemeral_gpu_offload and (lora_A.device.type == "cpu" or lora_B.device.type == "cpu")
+        if self.ephemeral_gpu_offload:
+            if lora_A.device.type in ["cuda", "xpu"]:
+                lora_B = lora_B.to(lora_A.device)
+            else:
+                if lora_B.device.type not in ["cuda", "xpu"]:
+                    if is_xpu_available():
+                        lora_B = lora_B.to("xpu")
+                    else:
+                        lora_B = lora_B.to("cuda")
+                lora_A = lora_A.to(lora_B.device)
+        scaling = self.scaling[adapter_name]
+        dora_layer.update_layer(
+            base_layer=self.get_base_layer(), lora_A=lora_A, lora_B=lora_B, scaling=scaling, place_on_cpu=place_on_cpu
+        )
+        self.lora_magnitude_vector[adapter_name] = dora_layer
+
+    def _cache_store(self, key: str, value: Any) -> None:
+        self._caches[key] = value
+
+    def _cache_pop(self, key: str) -> Any:
+        value = self._caches.pop(key)
+        return value
+
+    def set_scale(self, adapter, scale):
+        if adapter not in self.scaling:
+            # Ignore the case where the adapter is not in the layer
+            return
+        self.scaling[adapter] = scale * self.lora_alpha[adapter] / self.r[adapter]
+
+    def scale_layer(self, scale: float) -> None:
+        if scale == 1:
+            return
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.lora_A.keys():
+                continue
+
+            self.scaling[active_adapter] *= scale
+
+    def unscale_layer(self, scale=None) -> None:
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.lora_A.keys():
+                continue
+
+            if scale is None:
+                self.scaling[active_adapter] = self.lora_alpha[active_adapter] / self.r[active_adapter]
+            else:
+                self.scaling[active_adapter] /= scale
+
+    def _check_forward_args(self, x, *args, **kwargs):
+        """Check if the arguments are compatible with the configs and state of the model"""
+        adapter_names = kwargs.get("adapter_names", None)
+        if adapter_names is None:
+            return
+
+        if len(x) != len(adapter_names):
+            msg = (
+                "Length of `adapter_names` should be the same as the number of inputs, but got "
+                f"{len(adapter_names)} and {len(x)} respectively."
+            )
+            raise ValueError(msg)
+
+        if self.merged:
+            # It is unclear what would be the right thing to do if users pass adapter_names and there are merged
+            # adapters. Therefore, it is better to raise an error in this case.
+            msg = "Cannot pass `adapter_names` when there are merged adapters, please call `unmerge_adapter` first."
+            raise ValueError(msg)
+
+        # DoRA is not supported (yet), check that it's not being used. Don't check "__base__", as this is the
+        # placeholder for the base model.
+        unique_adapters = {name for name in adapter_names if name != "__base__"}
+        for adapter_name in unique_adapters:
+            if self.use_dora.get(adapter_name, False):
+                msg = "Cannot pass `adapter_names` when DoRA is enabled."
+                raise ValueError(msg)
+
+    def _mixed_batch_forward(
+        self, x: torch.Tensor, *args: Any, adapter_names: list[str], **kwargs: Any
+    ) -> torch.Tensor:
+        # This is a special method that handles the case when users pass the argument `adapter_names`. This is an
+        # extra argument that allows mixing different adapters in the same batch at inference time.
+        result = self.base_layer(x, *args, **kwargs)
+        torch_result_dtype = result.dtype
+
+        unique_adapters = set(adapter_names)
+        sub_batch_indices_list = []
+        for adapter in unique_adapters:
+            sub_batch_indices_list.append([index for index, item in enumerate(adapter_names) if item == adapter])
+
+        for i, active_adapter in enumerate(unique_adapters):
+            if active_adapter == "__base__":
+                continue
+            if active_adapter not in self.lora_A.keys():
+                continue
+
+            lora_A = self.lora_A[active_adapter]
+            lora_B = self.lora_B[active_adapter]
+            dropout = self.lora_dropout[active_adapter]
+            scaling = self.scaling[active_adapter]
+
+            # getting the sub-batch, passing it to LoRA layers and updating the corresponding indices of the linear
+            # layer output
+            sub_batch = x[sub_batch_indices_list[i]].to(lora_A.weight.dtype)
+            lora_output = lora_B(lora_A(dropout(sub_batch))) * scaling
+            result[sub_batch_indices_list[i]] += lora_output.to(torch_result_dtype)
+
+        return result
+
+    def _cast_input_dtype(self, x: torch.Tensor, dtype: torch.dtype) -> torch.Tensor:
+        """
+        Whether to cast the dtype of the input to the forward method.
+
+        Usually, we want to enable this to align the input dtype with the dtype of the weight, but by setting
+        layer.cast_input_dtype=False, this can be disabled if necessary.
+
+        Enabling or disabling can be managed via the peft.helpers.disable_lora_input_dtype_casting context manager.
+        """
+        if (not self.cast_input_dtype_enabled) or (x.dtype == dtype):
+            return x
+        return x.to(dtype=dtype)
+
+
+# Below code is based on https://github.com/microsoft/LoRA/blob/main/loralib/layers.py
+# and modified to work with PyTorch FSDP
+
+
+#  ------------------------------------------------------------------------------------------
+#  Copyright (c) Microsoft Corporation. All rights reserved.
+#  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.
+#  ------------------------------------------------------------------------------------------
+
+
+class Linear(nn.Module, LoraLayer):
+    # Lora implemented in a dense layer
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        is_target_conv_1d_layer: bool = False,
+        init_lora_weights: Union[bool, str] = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        LoraLayer.__init__(self, base_layer, **kwargs)
+        self.fan_in_fan_out = fan_in_fan_out
+
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name,
+            r,
+            lora_alpha=lora_alpha,
+            lora_dropout=lora_dropout,
+            init_lora_weights=init_lora_weights,
+            use_rslora=use_rslora,
+            use_dora=use_dora,
+            lora_bias=lora_bias,
+        )
+        self.is_target_conv_1d_layer = is_target_conv_1d_layer
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`list[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.lora_A.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    if not self.use_dora[active_adapter]:
+                        orig_weights += delta_weight
+                    else:
+                        # handle dora
+                        # since delta_weight already includes scaling, set it to 1 here
+                        weight_norm = (
+                            self.lora_magnitude_vector[active_adapter]
+                            .get_weight_norm(orig_weights, transpose(delta_weight, self.fan_in_fan_out), scaling=1)
+                            .detach()
+                        )
+                        # We need to cache weight_norm because it has to be based on the original weights. We
+                        # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                        # different value
+                        self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                        dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                        dora_factor = transpose(dora_factor.view(-1, 1), self.fan_in_fan_out)
+                        orig_weights = dora_factor * (orig_weights + delta_weight)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights
+
+                    if self.lora_bias[active_adapter]:
+                        new_bias = base_layer.bias + self.lora_B[active_adapter].bias
+                        if not torch.isfinite(new_bias).all():
+                            raise ValueError(
+                                f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                            )
+                        base_layer.bias.data = new_bias
+
+                else:
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    if not self.use_dora[active_adapter]:
+                        base_layer.weight.data += delta_weight
+                    else:
+                        # handle dora
+                        # since delta_weight already includes scaling, set it to 1 here
+                        weight_norm = (
+                            self.lora_magnitude_vector[active_adapter]
+                            .get_weight_norm(
+                                base_layer.weight, transpose(delta_weight, self.fan_in_fan_out), scaling=1
+                            )
+                            .detach()
+                        )
+                        # We need to cache weight_norm because it has to be based on the original weights. We
+                        # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                        # different value
+                        self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                        dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                        dora_factor = transpose(dora_factor.view(-1, 1), self.fan_in_fan_out)
+                        new_weight = dora_factor * (base_layer.weight.data + delta_weight)
+                        base_layer.weight.data = new_weight
+
+                    if self.lora_bias[active_adapter]:
+                        base_layer.bias.data += self.lora_B[active_adapter].bias
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.lora_A.keys():
+                weight = self.get_base_layer().weight
+                delta_weight = self.get_delta_weight(active_adapter)
+                if not self.use_dora[active_adapter]:
+                    weight.data -= delta_weight
+                else:
+                    weight_norm = self._cache_pop(f"{active_adapter}-weight_norm")
+                    dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                    weight_orig = weight.data / dora_factor.view(-1, 1) - delta_weight
+                    weight.data = weight_orig
+
+                if self.lora_bias[active_adapter]:
+                    self.get_base_layer().bias.data -= self.lora_B[active_adapter].bias
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.lora_B[adapter].weight.device
+        dtype = self.lora_B[adapter].weight.dtype
+
+        # In case users wants to merge the adapter weights that are in
+        # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+        cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+        weight_A = self.lora_A[adapter].weight
+        weight_B = self.lora_B[adapter].weight
+
+        if cast_to_fp32:
+            weight_A = weight_A.float()
+            weight_B = weight_B.float()
+
+        output_tensor = transpose(weight_B @ weight_A, self.fan_in_fan_out) * self.scaling[adapter]
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            self.lora_A[adapter].weight.data = weight_A.to(dtype)
+            self.lora_B[adapter].weight.data = weight_B.to(dtype)
+
+        return output_tensor
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        self._check_forward_args(x, *args, **kwargs)
+        adapter_names = kwargs.pop("adapter_names", None)
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif adapter_names is not None:
+            result = self._mixed_batch_forward(x, *args, adapter_names=adapter_names, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            torch_result_dtype = result.dtype
+
+            lora_A_keys = self.lora_A.keys()
+            for active_adapter in self.active_adapters:
+                if active_adapter not in lora_A_keys:
+                    continue
+
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+                x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                if not self.use_dora[active_adapter]:
+                    result = result + lora_B(lora_A(dropout(x))) * scaling
+                else:
+                    if isinstance(dropout, nn.Identity) or not self.training:
+                        base_result = result
+                    else:
+                        x = dropout(x)
+                        base_result = None
+
+                    result = result + self.lora_magnitude_vector[active_adapter](
+                        x,
+                        lora_A=lora_A,
+                        lora_B=lora_B,
+                        scaling=scaling,
+                        base_layer=self.get_base_layer(),
+                        base_result=base_result,
+                    )
+
+            result = result.to(torch_result_dtype)
+
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+
+class Embedding(nn.Module, LoraLayer):
+    # LoRA implemented in a Embedding layer
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        init_lora_weights: Union[bool, str] = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+        **kwargs,
+    ) -> None:
+        if lora_bias:
+            # lora_bias=True is not supported (yet) for embedding layers, as they use nn.Parameter
+            raise ValueError(f"lora_bias={lora_bias} is not supported for {self.__class__.__name__}.")
+
+        super().__init__()
+        LoraLayer.__init__(self, base_layer)
+
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name,
+            r,
+            lora_alpha=lora_alpha,
+            lora_dropout=lora_dropout,
+            init_lora_weights=init_lora_weights,
+            use_rslora=use_rslora,
+            use_dora=use_dora,
+            lora_bias=lora_bias,
+        )
+
+    def update_layer(
+        self, adapter_name, r, lora_alpha, lora_dropout, init_lora_weights, use_rslora, use_dora, lora_bias
+    ):
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+
+        self.r[adapter_name] = r
+        self.lora_alpha[adapter_name] = lora_alpha
+        if lora_dropout > 0.0:
+            lora_dropout_layer = nn.Dropout(p=lora_dropout)
+        else:
+            lora_dropout_layer = nn.Identity()
+
+        self.lora_dropout[adapter_name] = lora_dropout_layer
+        # Actual trainable parameters
+        weight_A = torch.randn((r, self.in_features))
+        weight_B = torch.randn((self.out_features, r))
+        self.lora_embedding_A[adapter_name] = nn.Parameter(weight_A)
+        self.lora_embedding_B[adapter_name] = nn.Parameter(weight_B)
+        self.lora_bias[adapter_name] = lora_bias
+
+        if use_rslora:
+            self.scaling[adapter_name] = lora_alpha / math.sqrt(r)
+        else:
+            self.scaling[adapter_name] = lora_alpha / r
+
+        if init_lora_weights == "loftq":
+            self.loftq_init(adapter_name)
+        elif init_lora_weights:
+            self.reset_lora_parameters(adapter_name, init_lora_weights)
+
+        # call this before dora_init
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+
+        if use_dora:
+            self.dora_init(adapter_name)
+            self.use_dora[adapter_name] = True
+        else:
+            self.use_dora[adapter_name] = False
+
+        self.set_adapter(self.active_adapters)
+
+    def dora_init(self, adapter_name: str) -> None:
+        if self.lora_magnitude_vector is None:
+            # first dora layer being added, add lora_magnitude_vector to the list of learnable parameters
+            self.adapter_layer_names = self.adapter_layer_names[:] + ("lora_magnitude_vector",)
+
+        dora_layer = DoraEmbeddingLayer(fan_in_fan_out=True)
+        lora_embedding_A = self.lora_embedding_A[adapter_name]
+        lora_embedding_B = self.lora_embedding_B[adapter_name]
+        scaling = self.scaling[adapter_name]
+        dora_layer.update_layer(
+            base_layer=self.get_base_layer(), lora_A=lora_embedding_A, lora_B=lora_embedding_B, scaling=scaling
+        )
+        self.lora_magnitude_vector[adapter_name] = dora_layer
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`list[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.lora_embedding_A.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    orig_weights += self.get_delta_weight(active_adapter)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights
+                else:
+                    base_layer.weight.data += self.get_delta_weight(active_adapter)
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.lora_embedding_A.keys():
+                self.get_base_layer().weight.data -= self.get_delta_weight(active_adapter)
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.lora_embedding_B[adapter].device
+        dtype = self.lora_embedding_A[adapter].dtype
+
+        # In case users wants to merge the adapter weights that are in
+        # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+        cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+        weight_A = self.lora_embedding_A[adapter]
+        weight_B = self.lora_embedding_B[adapter]
+
+        if cast_to_fp32:
+            weight_A = weight_A.float()
+            weight_B = weight_B.float()
+
+        output_tensor = transpose(weight_B @ weight_A, True) * self.scaling[adapter]
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            self.lora_embedding_A[adapter] = weight_A.to(dtype)
+            self.lora_embedding_B[adapter] = weight_B.to(dtype)
+
+        return output_tensor
+
+    def _mixed_batch_forward(
+        self, x: torch.Tensor, *args: Any, adapter_names: list[str], **kwargs: Any
+    ) -> torch.Tensor:
+        # This is a special method that handles the case when users pass the argument `adapter_names`. This is an
+        # extra argument that allows mixing different adapters in the same batch at inference time.
+        result = self.base_layer(x, *args, **kwargs)
+
+        unique_adapters = set(adapter_names)
+        sub_batch_indices_list = []
+        for adapter in unique_adapters:
+            sub_batch_indices_list.append([index for index, item in enumerate(adapter_names) if item == adapter])
+
+        for i, active_adapter in enumerate(unique_adapters):
+            if active_adapter == "__base__":
+                continue
+            if active_adapter not in self.lora_embedding_A.keys():
+                continue
+
+            embedding_A = self.lora_embedding_A[active_adapter].T
+            embedding_B = self.lora_embedding_B[active_adapter].T
+            scaling = self.scaling[active_adapter]
+
+            # getting the sub-batch, passing it to LoRA layers and updating the corresponding indices of the linear
+            # layer output
+            sub_batch = x[sub_batch_indices_list[i]]
+            after_A = self._embed(sub_batch, embedding_A)
+            result[sub_batch_indices_list[i]] += (after_A @ embedding_B) * scaling
+
+        return result
+
+    def _embed(self, input: torch.Tensor, weight: torch.Tensor) -> torch.Tensor:
+        base_layer = self.get_base_layer()
+        return F.embedding(
+            input,
+            weight,
+            padding_idx=base_layer.padding_idx,
+            max_norm=base_layer.max_norm,
+            norm_type=base_layer.norm_type,
+            scale_grad_by_freq=base_layer.scale_grad_by_freq,
+            sparse=base_layer.sparse,
+        )
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        # TODO: no dtype conversion here, unlike in Linear, is that correct?
+        self._check_forward_args(x, *args, **kwargs)
+        adapter_names = kwargs.pop("adapter_names", None)
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif adapter_names is not None:
+            result = self._mixed_batch_forward(x, *args, adapter_names=adapter_names, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            torch_result_dtype = result.dtype
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.lora_embedding_A:
+                    continue
+                embedding_A = self.lora_embedding_A[active_adapter].T
+                embedding_B = self.lora_embedding_B[active_adapter].T
+                scaling = self.scaling[active_adapter]
+
+                if not self.use_dora[active_adapter]:
+                    after_A = self._embed(x, embedding_A)
+                    result = result + (after_A @ embedding_B) * scaling
+                else:
+                    mag_norm_scale, dora_result = self.lora_magnitude_vector[active_adapter](
+                        x,
+                        lora_A=embedding_A,
+                        lora_B=embedding_B,
+                        scaling=scaling,
+                        base_layer=self.get_base_layer(),
+                        embed_fn=self._embed,
+                    )
+                    result = mag_norm_scale * result + dora_result
+            result = result.to(torch_result_dtype)
+
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+
+class _ConvNd(nn.Module, LoraLayer):
+    # Lora implemented in a conv(2,3)d layer
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        init_lora_weights: Union[bool, str] = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        LoraLayer.__init__(self, base_layer)
+
+        self._active_adapter = adapter_name
+        self._kernel_dim = base_layer.weight.dim()
+
+        self.update_layer(
+            adapter_name,
+            r,
+            lora_alpha=lora_alpha,
+            lora_dropout=lora_dropout,
+            init_lora_weights=init_lora_weights,
+            use_rslora=use_rslora,
+            use_dora=use_dora,
+            lora_bias=lora_bias,
+        )
+
+    def update_layer(
+        self, adapter_name, r, lora_alpha, lora_dropout, init_lora_weights, use_rslora, use_dora, lora_bias
+    ):
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+
+        self.r[adapter_name] = r
+        self.lora_alpha[adapter_name] = lora_alpha
+        if lora_dropout > 0.0:
+            lora_dropout_layer = nn.Dropout(p=lora_dropout)
+        else:
+            lora_dropout_layer = nn.Identity()
+
+        self.lora_dropout[adapter_name] = lora_dropout_layer
+        # Actual trainable parameters
+        base_layer = self.get_base_layer()
+        kernel_size = base_layer.kernel_size
+        stride = base_layer.stride
+        padding = base_layer.padding
+        conv_layer = type(base_layer)
+        out_kernel = out_stride = (1,) * (self._kernel_dim - 2)
+        self.lora_A[adapter_name] = conv_layer(self.in_features, r, kernel_size, stride, padding, bias=False)
+        self.lora_B[adapter_name] = conv_layer(r, self.out_features, out_kernel, out_stride, bias=lora_bias)
+        self.lora_bias[adapter_name] = lora_bias
+
+        if use_rslora:
+            self.scaling[adapter_name] = lora_alpha / math.sqrt(r)
+        else:
+            self.scaling[adapter_name] = lora_alpha / r
+
+        if init_lora_weights == "loftq":
+            self.loftq_init(adapter_name)
+        elif init_lora_weights:
+            self.reset_lora_parameters(adapter_name, init_lora_weights)
+
+        # call this before dora_init
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+
+        if use_dora:
+            self.dora_init(adapter_name)
+            self.use_dora[adapter_name] = True
+        else:
+            self.use_dora[adapter_name] = False
+
+        self.set_adapter(self.active_adapters)
+
+    def _get_dora_factor_view(self):
+        return (-1,) + (1,) * (self._kernel_dim - 1)
+
+    def dora_init(self, adapter_name: str) -> None:
+        if self.lora_magnitude_vector is None:
+            # first dora layer being added, add lora_magnitude_vector to the list of learnable parameters
+            self.adapter_layer_names = self.adapter_layer_names[:] + ("lora_magnitude_vector",)
+
+        dora_layer_class = self._get_dora_layer_class()
+        dora_layer = dora_layer_class(fan_in_fan_out=False)
+        lora_A = self.lora_A[adapter_name].weight
+        lora_B = self.lora_B[adapter_name].weight
+        scaling = self.scaling[adapter_name]
+        dora_layer.update_layer(base_layer=self.get_base_layer(), lora_A=lora_A, lora_B=lora_B, scaling=scaling)
+        self.lora_magnitude_vector[adapter_name] = dora_layer
+
+    def _get_dora_layer_class(self) -> type[_DoraConvNdLayer]:
+        # Subclasses should override this method to return the appropriate DoraLayer class
+        raise NotImplementedError
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights inside the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`list[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.lora_A.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    delta_weight = self.get_delta_weight(active_adapter)
+
+                    if not self.use_dora[active_adapter]:
+                        orig_weights += delta_weight
+                    else:
+                        # handle dora
+                        # since delta_weight already includes scaling, set it to 1 here
+                        weight_norm = (
+                            self.lora_magnitude_vector[active_adapter]
+                            .get_weight_norm(orig_weights, delta_weight, scaling=1)
+                            .detach()
+                        )
+                        # We need to cache weight_norm because it has to be based on the original weights. We
+                        # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                        # different value
+                        self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                        dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                        orig_weights = dora_factor.view(*self._get_dora_factor_view()) * (orig_weights + delta_weight)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+                    base_layer.weight.data = orig_weights
+
+                    if self.lora_bias[active_adapter]:
+                        new_bias = base_layer.bias + self.lora_B[active_adapter].bias
+                        if not torch.isfinite(new_bias).all():
+                            raise ValueError(
+                                f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                            )
+                        base_layer.bias.data = new_bias
+
+                else:
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    if not self.use_dora[active_adapter]:
+                        base_layer.weight.data += delta_weight
+                    else:
+                        # handle dora
+                        # since delta_weight already includes scaling, set it to 1 here
+                        weight_norm = (
+                            self.lora_magnitude_vector[active_adapter]
+                            .get_weight_norm(base_layer.weight, delta_weight, scaling=1)
+                            .detach()
+                        )
+                        # We need to cache weight_norm because it has to be based on the original weights. We
+                        # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                        # different value
+                        self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                        dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                        new_weight = dora_factor.view(*self._get_dora_factor_view()) * (
+                            base_layer.weight.data + delta_weight
+                        )
+                        base_layer.weight.data = new_weight
+
+                    if self.lora_bias[active_adapter]:
+                        base_layer.bias.data += self.lora_B[active_adapter].bias
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.lora_A.keys():
+                weight = self.get_base_layer().weight
+                delta_weight = self.get_delta_weight(active_adapter)
+                if not self.use_dora[active_adapter]:
+                    weight.data -= delta_weight
+                else:
+                    weight_norm = self._cache_pop(f"{active_adapter}-weight_norm")
+                    dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                    weight_orig = weight.data / dora_factor.view(*self._get_dora_factor_view()) - delta_weight
+                    weight.data = weight_orig
+
+                if self.lora_bias[active_adapter]:
+                    self.get_base_layer().bias.data -= self.lora_B[active_adapter].bias
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.lora_B[adapter].weight.device
+        dtype = self.lora_A[adapter].weight.dtype
+
+        # In case users wants to merge the adapter weights that are in
+        # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+        cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+        weight_A = self.lora_A[adapter].weight
+        weight_B = self.lora_B[adapter].weight
+
+        if cast_to_fp32:
+            weight_A = weight_A.float()
+            weight_B = weight_B.float()
+
+        # https://github.com/bmaltais/kohya_ss/blob/feb6728762a8f463d15ba936d189d4c3abfaa1ab/networks/lora.py#L117
+        if self.get_base_layer().weight.size()[2:4] == (1, 1):
+            # conv2d 1x1
+            output_tensor = (weight_B.squeeze(3).squeeze(2) @ weight_A.squeeze(3).squeeze(2)).unsqueeze(2).unsqueeze(
+                3
+            ) * self.scaling[adapter]
+        else:
+            output_tensor = (
+                self.conv_fn(
+                    weight_A.transpose(0, 1),
+                    weight_B,
+                ).transpose(0, 1)
+                * self.scaling[adapter]
+            )
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            self.lora_A[adapter].weight.data = weight_A.to(dtype)
+            self.lora_B[adapter].weight.data = weight_B.to(dtype)
+
+        return output_tensor
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        self._check_forward_args(x, *args, **kwargs)
+        adapter_names = kwargs.pop("adapter_names", None)
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif adapter_names is not None:
+            result = self._mixed_batch_forward(x, *args, adapter_names=adapter_names, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            torch_result_dtype = result.dtype
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+                x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                if not self.use_dora[active_adapter]:
+                    result = result + lora_B(lora_A(dropout(x))) * scaling
+                else:
+                    if isinstance(dropout, nn.Identity) or not self.training:
+                        base_result = result
+                    else:
+                        x = dropout(x)
+                        base_result = None
+
+                    result = result + self.lora_magnitude_vector[active_adapter](
+                        x,
+                        lora_A=lora_A,
+                        lora_B=lora_B,
+                        scaling=scaling,
+                        base_layer=self.get_base_layer(),
+                        base_result=base_result,
+                    )
+
+            result = result.to(torch_result_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+
+class Conv2d(_ConvNd):
+    # Lora implemented in a conv2d layer
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if not self._kernel_dim == 4:
+            raise ValueError(f"Conv2d layer kernel must have 4 dimensions, not {self._kernel_dim}")
+        self.conv_fn = F.conv2d
+
+    def _get_dora_layer_class(self):
+        return DoraConv2dLayer
+
+
+class Conv1d(_ConvNd):
+    # Lora implemented in a conv1d layer
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if not self._kernel_dim == 3:
+            raise ValueError(f"Conv1d layer kernel must have 3 dimensions, not {self._kernel_dim}")
+        self.conv_fn = F.conv1d
+
+    def _get_dora_layer_class(self):
+        raise NotImplementedError
+
+
+class Conv3d(_ConvNd):
+    # Lora implemented in a conv3d layer
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if not self._kernel_dim == 5:
+            raise ValueError(f"Conv3d layer kernel must have 5 dimensions, not {self._kernel_dim}")
+        self.conv_fn = F.conv3d
+
+    def _get_dora_layer_class(self):
+        return DoraConv3dLayer
+
+
+class MultiheadAttention(nn.Module, LoraLayer):
+    """LoRA implemented in a multihead attention layer
+
+    This is currently only implemented for the case of `_qkv_same_embed_dim = True`, i.e. query, key, and value having
+    the same dimension.
+
+    Note: LoRA is applied to both the in_proj (query/key/value) and out_proj. There is currently no way to specify only
+    one of them. Don't try to apply LoRA to the out_proj of MultiheadAttention by targeting that layer specifically,
+    since the forward method of that layer is not being used, hence the LoRA adapter would be ignored.
+
+    This is a little bit hacky because of the way that MultiheadAttention is implemented in PyTorch: There are no
+    `nn.Linear` layers which we can hook onto or, in case of output projection, `.forward` is not used. This
+    implementation works around these problems by merging the weights before the forward call and unmerging them after
+    the forward call.
+    """
+
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        init_lora_weights: Union[bool, str] = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        **kwargs,
+    ) -> None:
+        # TODO work with separate weights
+        if not getattr(base_layer, "_qkv_same_embed_dim", True):
+            # default for this value appears to be True:
+            # https://github.com/pytorch/pytorch/blob/701ba5203fe68d55d655bd4d6c008be94cf34ea5/torch/nn/modules/activation.py#L1128-L1130
+            raise ValueError(
+                f"Only same embed for query/key/value is supported as of now for {self.__class__.__name__}."
+            )
+        if use_dora:
+            # TODO: probably not so hard to implement
+            raise ValueError(f"{self.__class__.__name__} does not support DoRA (yet), please set use_dora to False")
+
+        super().__init__()
+        LoraLayer.__init__(self, base_layer, **kwargs)
+
+        # Note: LoRA is applied to both in_proj and out_proj. There is currently no way to only specify one of them.
+        if isinstance(base_layer.out_proj, nn.Linear):
+            self.base_layer.out_proj = Linear(
+                base_layer.out_proj,
+                adapter_name,
+                r=r,
+                lora_alpha=lora_alpha,
+                lora_dropout=lora_dropout,
+                init_lora_weights=init_lora_weights,
+                use_rslora=use_rslora,
+                use_dora=use_dora,
+                **kwargs,
+            )
+        else:
+            raise ValueError(f"out_proj must be an instance of nn.Linear for {self.__class__.__name__}.")
+
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, r, lora_alpha, lora_dropout, init_lora_weights, use_rslora)
+
+    @property
+    def embed_dim(self) -> int:
+        return self.get_base_layer().embed_dim
+
+    @property
+    def kdim(self) -> Optional[int]:
+        return self.get_base_layer().kdim
+
+    @property
+    def vdim(self) -> Optional[int]:
+        return self.get_base_layer().vdim
+
+    @property
+    def _qkv_same_embed_dim(self) -> bool:
+        return self.get_base_layer()._qkv_same_embed_dim
+
+    @property
+    def num_heads(self) -> int:
+        return self.get_base_layer().num_heads
+
+    @property
+    def dropout(self) -> float:
+        return self.get_base_layer().dropout
+
+    @property
+    def batch_first(self) -> bool:
+        return self.get_base_layer().batch_first
+
+    @property
+    def head_dim(self) -> int:
+        return self.get_base_layer().head_dim
+
+    @property
+    def in_proj_weight(self) -> nn.Parameter:
+        return self.get_base_layer().in_proj_weight
+
+    @property
+    def in_proj_bias(self) -> nn.Parameter:
+        return self.get_base_layer().in_proj_bias
+
+    @property
+    def out_proj(self) -> nn.Module:
+        return self.get_base_layer().out_proj.get_base_layer()
+
+    @property
+    def bias_k(self) -> Optional[nn.Parameter]:
+        return self.get_base_layer().bias_k
+
+    @property
+    def bias_v(self) -> Optional[nn.Parameter]:
+        return self.get_base_layer().bias_v
+
+    def merge_masks(self, *args, **kwargs) -> tuple[Optional[torch.Tensor], Optional[int]]:
+        return self.get_base_layer().merge_masks(*args, **kwargs)
+
+    @property
+    def add_zero_attn(self) -> bool:
+        return self.get_base_layer().add_zero_attn
+
+    def update_layer(self, *args, **kwargs) -> None:
+        super().update_layer(*args, **kwargs)
+        # Note: LoRA is applied to both in_proj and out_proj. There is currently no way to only specify one of them.
+        self.base_layer.out_proj.update_layer(*args, **kwargs)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        # Implementation follows this:
+        # https://github.com/Baijiong-Lin/LoRA-Torch/blob/4bfed6820b64fcf47064c30f30606a190a4f0d2e/loratorch/layers.py#L73-L79
+        # Notably, instead of mutating the weight, we delete the original weight and replace it by the merged weight
+        # TODO: work with separate weights
+        for active_adapter in adapter_names:
+            if active_adapter in self.lora_A.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # TODO: work with separate weights
+                    # merging in_proj (nn.Parameter)
+                    orig_weights_in = base_layer.in_proj_weight.data.detach().clone()
+                    orig_weights_in += self.get_delta_weight(active_adapter)
+                    if not torch.isfinite(orig_weights_in).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    # merging out_proj (subclass of nn.Linear)
+                    orig_weights_out = base_layer.out_proj.weight.data.detach().clone()
+                    orig_weights_out += base_layer.out_proj.get_delta_weight(active_adapter)
+                    if not torch.isfinite(orig_weights_out).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    # unregister parameter implicitly and overwrite using merged weights; gradients are computed after
+                    # forward and, thus, after unmerging (see forward()), therefore this is safe to do.
+                    del base_layer.in_proj_weight
+                    base_layer.in_proj_weight = orig_weights_in
+
+                    del base_layer.out_proj.get_base_layer().weight
+                    base_layer.out_proj.get_base_layer().weight = orig_weights_out
+                    base_layer.out_proj.merge(adapter_names=[active_adapter])
+                else:
+                    # merging in_proj (nn.Parameter)
+                    # TODO: work with separate weights
+                    weight_merged = base_layer.in_proj_weight.data.detach() + self.get_delta_weight(active_adapter)
+
+                    # unregister parameter implicitly and overwrite using merged weights; gradients are computed after
+                    # forward and, thus, after unmerging (see forward()), therefore this is safe to do.
+                    del base_layer.in_proj_weight
+                    base_layer.in_proj_weight = weight_merged
+
+                    # merging out_proj (subclass of nn.Linear)
+                    weight_merged = base_layer.out_proj.weight.data.detach() + base_layer.out_proj.get_delta_weight(
+                        active_adapter
+                    )
+                    del base_layer.out_proj.get_base_layer().weight
+                    base_layer.out_proj.get_base_layer().weight = weight_merged
+                    base_layer.out_proj.merge(adapter_names=[active_adapter])
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+
+        # TODO work with separate weights
+        base_layer = self.get_base_layer()
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.lora_A.keys():
+                # Ensure that requires_grad=False for the base weights after unmerging. This may not matter since
+                # requires_grad was False when the optimizer was initialized, but still let's try to be correct here.
+
+                # in_proj
+                old_weight = base_layer.in_proj_weight.data - self.get_delta_weight(active_adapter)
+                del base_layer.in_proj_weight
+                base_layer.register_parameter("in_proj_weight", nn.Parameter(old_weight, requires_grad=False))
+
+                # out_proj
+                old_weight = base_layer.out_proj.base_layer.weight.data - base_layer.out_proj.get_delta_weight(
+                    active_adapter
+                )
+                del base_layer.out_proj.base_layer.weight
+                base_layer.out_proj.base_layer.register_parameter(
+                    "weight", nn.Parameter(old_weight, requires_grad=False)
+                )
+
+        self.get_base_layer().out_proj.unmerge()
+
+    def unload_and_optionally_merge_module(
+        self, merge: bool, safe_merge: bool, adapter_names: Optional[list[str]]
+    ) -> nn.MultiheadAttention:
+        """
+        Merging and unloading of the MultiheadAttention module
+
+        This requires an extra step for MultiheadAttention, which is why there is this special method instead of
+        relying on the normal merge_and_unload code path.
+        """
+        if merge:
+            self.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+        base_layer = self.get_base_layer()
+
+        # extra steps: re-register weights, take care of out_proj layer
+        # in_proj
+        weight = base_layer.in_proj_weight
+        del base_layer.in_proj_weight
+        base_layer.register_parameter("in_proj_weight", nn.Parameter(weight.data, requires_grad=weight.requires_grad))
+
+        # out_proj
+        out_proj_layer = base_layer.out_proj.get_base_layer()
+        weight = out_proj_layer.weight
+        del out_proj_layer.weight
+        out_proj_layer.register_parameter("weight", nn.Parameter(weight.data, requires_grad=weight.requires_grad))
+
+        base_layer.out_proj = out_proj_layer
+        return base_layer
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.lora_B[adapter].weight.device
+        dtype = self.lora_B[adapter].weight.dtype
+
+        # In case users wants to merge the adapter weights that are in
+        # float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # float16 because the `@` and matmul operation in general is not supported in torch + cpu + fp16.
+        cast_to_fp32 = device.type == "cpu" and dtype == torch.float16
+
+        weight_A = self.lora_A[adapter].weight
+        weight_B = self.lora_B[adapter].weight
+
+        if cast_to_fp32:
+            weight_A = weight_A.float()
+            weight_B = weight_B.float()
+
+        output_tensor = (weight_B @ weight_A) * self.scaling[adapter]
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            self.lora_A[adapter].weight.data = weight_A.to(dtype)
+            self.lora_B[adapter].weight.data = weight_B.to(dtype)
+
+        return output_tensor
+
+    def _check_forward_args(self, x, *args, **kwargs):
+        if "adapter_names" in kwargs:
+            raise TypeError(f"lora.{self.__class__.__name__} does not support mixed adapter batches.")
+        super()._check_forward_args(x, *args, **kwargs)
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+        self._check_forward_args(x, *args, **kwargs)
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            out_proj = self.get_base_layer().out_proj
+            if out_proj.active_adapters != self.active_adapters:
+                # We have a case that in_proj and out_proj have diverging merged adapters. We cannot
+                # really deal with this correctly, thus it's better to raise than possibly create a hard to debug mess
+                cls_name = self.get_base_layer().__class__.__name__
+                raise ValueError(
+                    f"The out_proj layer of {cls_name} has merged layers but {cls_name} itself doesn't; please ensure "
+                    "that either both or none have merged layers"
+                )
+
+            # Merge all adapters that are active for this module, i.e. the LoRA weights for in_proj and out_proj.
+            # in_proj uses nn.Parameters, therefore, there is no forward method to be used and we have to explicitly
+            # merge for the LoRA weights to have an effect:
+            # https://github.com/pytorch/pytorch/blob/6ebb26d572d5fcdc6ac0d1297bdf8d1eb5d20722/torch/nn/modules/activation.py#L1020
+            # For out_proj, we have an nn.Linear (or rather: NonDynamicallyQuantizableLinear), but its forward method
+            # is not used:
+            # https://github.com/pytorch/pytorch/blob/6ebb26d572d5fcdc6ac0d1297bdf8d1eb5d20722/torch/nn/modules/activation.py#L1267-L1271
+            # Therefore, its LoRA weights also need to be merged to have an effect.
+            active_adapters = [a for a in self.active_adapters if a in self.lora_A]
+            try:
+                self.merge(adapter_names=active_adapters)
+                result = self.base_layer(x, *args, **kwargs)
+            finally:
+                # it's safe to call unmerge(), which unmerges all adapters, because we checked that not self.merged,
+                # i.e. there is was no merged layer before
+                self.unmerge()
+
+        result = (result[0].to(previous_dtype), result[1].to(previous_dtype) if result[1] is not None else result[1])
+        return result
+
+    # The decorator is needed in case low_cpu_mem_usage=True is used, as we don't want the base layer weights to be
+    # moved to meta device. This requires the use of PEFT's implementation of init_empty_weight instead of using the one
+    # from accelerate.
+    @skip_init_on_device
+    def _restore_weights(self):
+        # Restore the weights as registered parameters on the base layer.
+        # This is necessary because the way that weights are merged/unmerged (which is necessary for forward to work
+        # correctly), the Module "forgets" these attributes. Therefore, we need to call register_parameter explicitly.
+        # We cannot call register_parameter for merging/unmerging because that cuts them off from the autograd graph.
+        # Note that this is hacky, since we need to ensure that _restore_weights is called by each method that needs it.
+
+        # in_proj
+        # TODO work with separate weights
+        base_layer = self.get_base_layer()
+        weight = base_layer.in_proj_weight
+        del base_layer.in_proj_weight
+        base_layer.register_parameter("in_proj_weight", nn.Parameter(weight.data, requires_grad=weight.requires_grad))
+
+        # out_proj
+        base_layer = base_layer.out_proj.get_base_layer()
+        weight = base_layer.weight
+        del base_layer.weight
+        base_layer.register_parameter("weight", nn.Parameter(weight.data, requires_grad=weight.requires_grad))
+
+    def state_dict(self, *args, **kwargs):
+        self._restore_weights()
+        return super().state_dict(*args, **kwargs)
+
+    def named_modules(self, *args, **kwargs):
+        # Note: no need to also implement modules(), as modules() calls named_modules() under the hood
+        self._restore_weights()
+        return super().named_modules(*args, **kwargs)
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+
+def dispatch_default(
+    target: torch.nn.Module,
+    adapter_name: str,
+    lora_config: LoraConfig,
+    **kwargs,
+) -> Optional[torch.nn.Module]:
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    if isinstance(target_base_layer, torch.nn.Embedding):
+        embedding_kwargs = kwargs.copy()
+        embedding_kwargs.pop("fan_in_fan_out", None)
+        embedding_kwargs.update(lora_config.loftq_config)
+        new_module = Embedding(target, adapter_name, **embedding_kwargs)
+    elif isinstance(target_base_layer, torch.nn.Conv2d):
+        kwargs.update(lora_config.loftq_config)
+        new_module = Conv2d(target, adapter_name, **kwargs)
+    elif isinstance(target_base_layer, torch.nn.Conv3d):
+        kwargs.update(lora_config.loftq_config)
+        new_module = Conv3d(target, adapter_name, **kwargs)
+    elif isinstance(target_base_layer, nn.Conv1d):
+        kwargs.update(lora_config.loftq_config)
+        new_module = Conv1d(target, adapter_name, **kwargs)
+    elif isinstance(target_base_layer, torch.nn.MultiheadAttention):
+        kwargs.update(lora_config.loftq_config)
+        new_module = MultiheadAttention(target, adapter_name, **kwargs)
+    elif isinstance(target_base_layer, torch.nn.Linear):
+        if kwargs["fan_in_fan_out"]:
+            warnings.warn(
+                "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                "Setting fan_in_fan_out to False."
+            )
+            kwargs["fan_in_fan_out"] = lora_config.fan_in_fan_out = False
+        kwargs.update(lora_config.loftq_config)
+        new_module = Linear(target, adapter_name, **kwargs)
+    elif isinstance(target_base_layer, Conv1D):
+        if not kwargs["fan_in_fan_out"]:
+            warnings.warn(
+                "fan_in_fan_out is set to False but the target module is `Conv1D`. Setting fan_in_fan_out to True."
+            )
+            kwargs["fan_in_fan_out"] = lora_config.fan_in_fan_out = True
+        kwargs.update(lora_config.loftq_config)
+        new_module = Linear(target, adapter_name, is_target_conv_1d_layer=True, **kwargs)
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..afa692981928941cb421333dfc0db10db6b2d6f5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/model.py
@@ -0,0 +1,947 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import math
+import operator
+import warnings
+from contextlib import contextmanager
+from dataclasses import asdict, replace
+from enum import Enum
+from functools import partial, reduce
+from typing import Literal, Optional
+
+import torch
+from torch import nn
+from tqdm import tqdm
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.tuners.tuners_utils import (
+    BaseTuner,
+    BaseTunerLayer,
+    check_target_module_exists,
+    onload_layer,
+    replicate_layers,
+)
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    AuxiliaryTrainingWrapper,
+    ModulesToSaveWrapper,
+    _freeze_adapter,
+    _get_submodules,
+    get_peft_model_state_dict,
+    get_quantization_config,
+)
+from peft.utils.merge_utils import dare_linear, dare_ties, magnitude_prune, task_arithmetic, ties
+from peft.utils.other import get_pattern_key
+
+from .aqlm import dispatch_aqlm
+from .awq import dispatch_awq
+from .config import LoraConfig
+from .eetq import dispatch_eetq
+from .gptq import dispatch_gptq
+from .hqq import dispatch_hqq
+from .layer import Conv2d, LoraLayer, dispatch_default
+from .torchao import dispatch_torchao
+from .tp_layer import dispatch_megatron
+
+
+def _adapter_names_pre_forward_hook(target, args, kwargs, adapter_names):
+    # pre-forward hook to inject the adapter_names argument when using mixed adapter batches inference
+    kwargs["adapter_names"] = adapter_names
+    return args, kwargs
+
+
+class LoraModel(BaseTuner):
+    """
+    Creates Low Rank Adapter (LoRA) model from a pretrained transformers model.
+
+    The method is described in detail in https://arxiv.org/abs/2106.09685.
+
+    Args:
+        model ([`torch.nn.Module`]): The model to be adapted.
+        config ([`LoraConfig`]): The configuration of the Lora model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The Lora model.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForSeq2SeqLM
+        >>> from peft import LoraModel, LoraConfig
+
+        >>> config = LoraConfig(
+        ...     task_type="SEQ_2_SEQ_LM",
+        ...     r=8,
+        ...     lora_alpha=32,
+        ...     target_modules=["q", "v"],
+        ...     lora_dropout=0.01,
+        ... )
+
+        >>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
+        >>> lora_model = LoraModel(model, config, "default")
+        ```
+
+        ```py
+        >>> import torch
+        >>> import transformers
+        >>> from peft import LoraConfig, PeftModel, get_peft_model, prepare_model_for_kbit_training
+
+        >>> rank = ...
+        >>> target_modules = ["q_proj", "k_proj", "v_proj", "out_proj", "fc_in", "fc_out", "wte"]
+        >>> config = LoraConfig(
+        ...     r=4, lora_alpha=16, target_modules=target_modules, lora_dropout=0.1, bias="none", task_type="CAUSAL_LM"
+        ... )
+        >>> quantization_config = transformers.BitsAndBytesConfig(load_in_8bit=True)
+
+        >>> tokenizer = transformers.AutoTokenizer.from_pretrained(
+        ...     "kakaobrain/kogpt",
+        ...     revision="KoGPT6B-ryan1.5b-float16",  # or float32 version: revision=KoGPT6B-ryan1.5b
+        ...     bos_token="[BOS]",
+        ...     eos_token="[EOS]",
+        ...     unk_token="[UNK]",
+        ...     pad_token="[PAD]",
+        ...     mask_token="[MASK]",
+        ... )
+        >>> model = transformers.GPTJForCausalLM.from_pretrained(
+        ...     "kakaobrain/kogpt",
+        ...     revision="KoGPT6B-ryan1.5b-float16",  # or float32 version: revision=KoGPT6B-ryan1.5b
+        ...     pad_token_id=tokenizer.eos_token_id,
+        ...     use_cache=False,
+        ...     device_map={"": rank},
+        ...     torch_dtype=torch.float16,
+        ...     quantization_config=quantization_config,
+        ... )
+        >>> model = prepare_model_for_kbit_training(model)
+        >>> lora_model = get_peft_model(model, config)
+        ```
+
+    **Attributes**:
+        - **model** ([`~transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`LoraConfig`]): The configuration of the Lora model.
+    """
+
+    prefix: str = "lora_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False) -> None:
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def _check_new_adapter_config(self, config: LoraConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(lora_config, key):
+        return check_target_module_exists(lora_config, key)
+
+    def _prepare_model(self, peft_config: LoraConfig, model: nn.Module):
+        r"""
+        A private method to modify the model structure before adapter is applied.
+
+        Args:
+            peft_config (`PeftConfig`):
+                The prepared adapter config.
+            model (`nn.Module`):
+                The model that is going to be adapted.
+        """
+        if peft_config.layer_replication:
+            replicate_layers(model, peft_config.layer_replication)
+
+    def _create_and_replace(
+        self,
+        lora_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+
+        # Regexp matching - Find key which matches current target_name in patterns provided
+        r_key = get_pattern_key(lora_config.rank_pattern.keys(), current_key)
+        alpha_key = get_pattern_key(lora_config.alpha_pattern.keys(), current_key)
+        r = lora_config.rank_pattern.get(r_key, lora_config.r)
+        alpha = lora_config.alpha_pattern.get(alpha_key, lora_config.lora_alpha)
+
+        kwargs = {
+            "r": r,
+            "lora_alpha": alpha,
+            "lora_dropout": lora_config.lora_dropout,
+            "fan_in_fan_out": lora_config.fan_in_fan_out,
+            "init_lora_weights": lora_config.init_lora_weights,
+            "use_rslora": lora_config.use_rslora,
+            "use_dora": lora_config.use_dora,
+            "ephemeral_gpu_offload": lora_config.runtime_config.ephemeral_gpu_offload,
+            "lora_bias": lora_config.lora_bias,
+            "loaded_in_8bit": getattr(self.model, "is_loaded_in_8bit", False),
+            "loaded_in_4bit": getattr(self.model, "is_loaded_in_4bit", False),
+        }
+        # for torchao merging, we need the get_apply_tensor_subclass from the quantization config
+        try:
+            kwargs["get_apply_tensor_subclass"] = operator.attrgetter(
+                "hf_quantizer.quantization_config.get_apply_tensor_subclass"
+            )(self.model)
+        except AttributeError:
+            pass
+
+        quant_methods = ["gptq", "aqlm", "awq"]
+        for quant_method in quant_methods:
+            quantization_config = get_quantization_config(self.model, method=quant_method)
+            if quantization_config is not None:
+                kwargs[f"{quant_method}_quantization_config"] = quantization_config
+
+        # note: AdaLoraLayer is a subclass of LoraLayer, we need to exclude it
+        from peft.tuners.adalora import AdaLoraLayer
+
+        if isinstance(target, LoraLayer) and not isinstance(target, AdaLoraLayer):
+            target.update_layer(
+                adapter_name,
+                r,
+                lora_alpha=alpha,
+                lora_dropout=lora_config.lora_dropout,
+                init_lora_weights=lora_config.init_lora_weights,
+                use_rslora=lora_config.use_rslora,
+                use_dora=lora_config.use_dora,
+                lora_bias=lora_config.lora_bias,
+            )
+        else:
+            device_map = self.model.hf_device_map if hasattr(self.model, "hf_device_map") else None
+            new_module = self._create_new_module(lora_config, adapter_name, target, device_map=device_map, **kwargs)
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if (self.prefix in name) or ("ranknum" in name):
+                if hasattr(child, "qweight"):
+                    weight = child.qweight
+                elif hasattr(child, "W_q"):
+                    weight = child.W_q
+                elif hasattr(child, "weight"):
+                    weight = child.weight
+                elif getattr(child, "in_proj_weight", None) is not None:  # MHA
+                    weight = child.in_proj_weight
+                else:
+                    weight = next(child.parameters())
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "lora_only":
+                for m in model.modules():
+                    if isinstance(m, LoraLayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(lora_config, adapter_name, target, **kwargs):
+        # Collect dispatcher functions to decide what backend to use for the replaced LoRA layer. The order matters,
+        # because the first match is always used. Therefore, the default layers should be checked last.
+        dispatchers = []
+
+        if lora_config._custom_modules:
+            # Experimental custom LoRA module support. Allows users to pass a custom mapping for unsupported layer
+            # types by impelementing their own LoRA layers.
+            def dynamic_dispatch_func(target, adapter_name, lora_config, **kwargs):
+                new_module = None
+
+                if isinstance(target, BaseTunerLayer):
+                    target_base_layer = target.get_base_layer()
+                else:
+                    target_base_layer = target
+
+                for key, custom_cls in lora_config._custom_modules.items():
+                    if isinstance(target_base_layer, key):
+                        new_module = custom_cls(target, adapter_name, **kwargs)
+                        break
+
+                return new_module
+
+            dispatchers.append(dynamic_dispatch_func)
+
+        # avoid eager bnb import
+        if is_bnb_available():
+            from .bnb import dispatch_bnb_8bit
+
+            dispatchers.append(dispatch_bnb_8bit)
+
+        if is_bnb_4bit_available():
+            from .bnb import dispatch_bnb_4bit
+
+            dispatchers.append(dispatch_bnb_4bit)
+
+        dispatchers.extend(
+            [
+                dispatch_eetq,
+                dispatch_aqlm,
+                dispatch_awq,
+                dispatch_gptq,
+                dispatch_hqq,
+                dispatch_torchao,
+                dispatch_megatron,
+                dispatch_default,
+            ]
+        )
+
+        new_module = None
+        for dispatcher in dispatchers:
+            new_module = dispatcher(target, adapter_name, lora_config=lora_config, **kwargs)
+            if new_module is not None:  # first match wins
+                break
+
+        if new_module is None:
+            # no module could be matched
+            raise ValueError(
+                f"Target module {target} is not supported. Currently, only the following modules are supported: "
+                "`torch.nn.Linear`, `torch.nn.Embedding`, `torch.nn.Conv1d`, `torch.nn.Conv2d`, `torch.nn.Conv3d`, "
+                "`transformers.pytorch_utils.Conv1D`, `torch.nn.MultiheadAttention.`."
+            )
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled: bool = True) -> None:
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, AuxiliaryTrainingWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self) -> None:
+        """Enable all adapters.
+
+        Call this if you have previously disabled all adapters and want to re-enable them.
+        """
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self) -> None:
+        """Disable all adapters.
+
+        When disabling all adapters, the model output corresponds to the output of the base model.
+        """
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name: str | list[str]) -> None:
+        """Set the active adapter(s).
+
+        Additionally, this function will set the specified adapters to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str` or `list[str]`): Name of the adapter(s) to be activated.
+        """
+        for module in self.model.modules():
+            if isinstance(module, LoraLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @contextmanager
+    def _enable_peft_forward_hooks(self, *args, **kwargs):
+        # If adapter_names is passed as an argument, we inject it into the forward arguments.
+        adapter_names = kwargs.pop("adapter_names", None)
+        if adapter_names is None:
+            # nothing to do
+            yield
+            return
+
+        if self.training:
+            raise ValueError("Cannot pass `adapter_names` when the model is in training mode.")
+
+        # Check that users only passed actually existing adapters.
+        # Note: We cannot do this on the layer level, as each individual layer may not have each adapter. Still, we want
+        # to check that there is at least one layer with the given name, or else something like typos can easily slip.
+        expected_adapters = set()
+        for layer in self.modules():
+            if isinstance(layer, LoraLayer):
+                expected_adapters |= layer.lora_A.keys()
+                expected_adapters |= layer.lora_embedding_A.keys()
+        unique_adapters = {name for name in adapter_names if name != "__base__"}
+        unexpected_adapters = unique_adapters - expected_adapters
+        if unexpected_adapters:
+            raise ValueError(f"Trying to infer with non-existing adapter(s): {', '.join(sorted(unexpected_adapters))}")
+
+        # deal with beam search
+        num_beams = kwargs.get("num_beams", None)
+        uses_beam_search = isinstance(num_beams, int) and (num_beams > 1)
+        original_adapter_names = adapter_names[:]
+        if uses_beam_search:
+            if not isinstance(adapter_names, (list, tuple)):
+                raise TypeError(f"Got adapter names of type {type(adapter_names)}, expected a list of str.")
+            # When there is beam search, the inputs are repeated n times, thus we repeat each adapter name n times and
+            # then flatten the nested list. For encoder-decoder models, this extended list should not be applied to the
+            # encoder part. Further below, the original argument is thus restored for the encoder.
+            adapter_names = sum(([n] * kwargs["num_beams"] for n in adapter_names), [])
+
+        hook_handles = []
+        for module in self.modules():
+            if isinstance(module, LoraLayer) or isinstance(module, AuxiliaryTrainingWrapper):
+                pre_forward = partial(_adapter_names_pre_forward_hook, adapter_names=adapter_names)
+                handle = module.register_forward_pre_hook(pre_forward, with_kwargs=True)
+                hook_handles.append(handle)
+
+        if uses_beam_search and hasattr(self.model, "get_encoder"):
+            # For encoder-decoder models, even when applying beam search, the encoder part of the model should not use
+            # the extended adapter_names. This is because the encoder still uses the original, non-extended samples.
+            for module in self.model.get_encoder().modules():
+                if isinstance(module, LoraLayer) or isinstance(module, AuxiliaryTrainingWrapper):
+                    # Add another hook to overwrite the kwargs with the original adapter names -- this is easier than
+                    # trying to exclude the encoder.
+                    pre_forward = partial(_adapter_names_pre_forward_hook, adapter_names=original_adapter_names)
+                    handle = module.register_forward_pre_hook(pre_forward, with_kwargs=True)
+                    hook_handles.append(handle)
+
+        yield
+
+        for handle in hook_handles:
+            handle.remove()
+
+    def _check_merge_allowed(self):
+        """Verify that the configuration supports merging.
+
+        Currently gptq quantization and replicated layers do not support merging.
+        """
+        super()._check_merge_allowed()
+        if getattr(self.model, "quantization_method", None) == "gptq":
+            raise ValueError("Cannot merge LORA layers when the model is gptq quantized")
+        if self.peft_config.get("layer_replication"):
+            raise ValueError("Cannot merge LORA layers when base model layers are replicated")
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        if merge:
+            self._check_merge_allowed()
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+            with onload_layer(target):
+                if hasattr(target, "unload_and_optionally_merge_module"):
+                    # if layers have special unloading method, like MultiheadAttention, use that
+                    unloaded_module = target.unload_and_optionally_merge_module(
+                        merge=merge, safe_merge=safe_merge, adapter_names=adapter_names
+                    )
+                    self._replace_module(parent, target_name, unloaded_module, target)
+                elif hasattr(target, "base_layer"):
+                    if merge:
+                        target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                    self._replace_module(parent, target_name, target.get_base_layer(), target)
+
+        return self.model
+
+    def _check_add_weighted_adapter(
+        self, adapters: list[str], combination_type: str, svd_rank: int | None
+    ) -> tuple[str, int, str]:
+        """
+        Helper function to check if the arguments to add_weighted_adapter are valid and compatible with the underlying
+        model.
+        """
+        for adapter in adapters:
+            if adapter not in list(self.peft_config.keys()):
+                raise ValueError(f"Adapter {adapter} does not exist")
+
+        # If more than one of the adapters targets the same module with modules_to_save, raise an error, as these
+        # modules cannot be merged. First, find the ModulesToSaveWrapper instances in the model, then check if they
+        # have modules for the adapters to be merged.
+        modules_to_save_wrappers = [module for module in self.modules() if isinstance(module, ModulesToSaveWrapper)]
+        problematic_wrappers = [
+            wrapper
+            for wrapper in modules_to_save_wrappers
+            if sum(adapter in wrapper.modules_to_save for adapter in adapters) > 1
+        ]
+        if problematic_wrappers:
+            raise ValueError(
+                "Cannot add weighted adapters if they target the same module with modules_to_save, but found "
+                f"{len(problematic_wrappers)} such instance(s)."
+            )
+
+        # if there is only one adapter, we can only use linear merging
+        combination_type = "linear" if len(adapters) == 1 else combination_type
+
+        adapters_ranks = [self.peft_config[adapter].r for adapter in adapters]
+        if combination_type in ("linear", "ties", "dare_ties", "dare_linear", "magnitude_prune"):
+            # all adapters ranks should be same, new rank is just this value
+            if len(set(adapters_ranks)) != 1:
+                raise ValueError(
+                    "All adapters must have the same r value when using combination_type linear, ties, dare_ties or "
+                    "dare_linear."
+                )
+            new_rank = adapters_ranks[0]
+        elif combination_type == "cat":
+            # adapters ranks may be different, new rank is sum of all ranks
+            # be careful, because output adapter rank may be really big if mixing a lot of adapters
+            new_rank = sum(adapters_ranks)
+        elif combination_type.endswith("svd"):
+            # new rank is the max of all ranks of the adapters if not provided
+            new_rank = svd_rank or max(adapters_ranks)
+        else:
+            raise ValueError(f"Invalid combination_type: {combination_type}")
+
+        target_module_types = [type(self.peft_config[adapter].target_modules) for adapter in adapters]
+        if not target_module_types:
+            raise ValueError(f"Found no adapter matching the names in {adapters}")
+        if len(set(target_module_types)) > 1:
+            raise ValueError(
+                "all adapter configs should follow the same target modules type. "
+                "Combining adapters with `target_modules` type being a mix of list/set and string is not supported."
+            )
+
+        if target_module_types[0] is str:
+            new_target_modules = "|".join(f"({self.peft_config[adapter].target_modules})" for adapter in adapters)
+        elif target_module_types[0] is set:
+            new_target_modules = reduce(
+                operator.or_, (self.peft_config[adapter].target_modules for adapter in adapters)
+            )
+        else:
+            raise TypeError(f"Invalid type {target_module_types[0]} found in target_modules")
+
+        return combination_type, new_rank, new_target_modules
+
+    def add_weighted_adapter(
+        self,
+        adapters: list[str],
+        weights: list[float],
+        adapter_name: str,
+        combination_type: str = "svd",
+        svd_rank: int | None = None,
+        svd_clamp: int | None = None,
+        svd_full_matrices: bool = True,
+        svd_driver: str | None = None,
+        density: float | None = None,
+        majority_sign_method: Literal["total", "frequency"] = "total",
+    ) -> None:
+        """
+        This method adds a new adapter by merging the given adapters with the given weights.
+
+        When using the `cat` combination_type you should be aware that rank of the resulting adapter will be equal to
+        the sum of all adapters ranks. So it's possible that the mixed adapter may become too big and result in OOM
+        errors.
+
+        Args:
+            adapters (`list`):
+                List of adapter names to be merged.
+            weights (`list`):
+                List of weights for each adapter.
+            adapter_name (`str`):
+                Name of the new adapter.
+            combination_type (`str`):
+                The merging type can be one of [`svd`, `linear`, `cat`, `ties`, `ties_svd`, `dare_ties`, `dare_linear`,
+                `dare_ties_svd`, `dare_linear_svd`, `magnitude_prune`, `magnitude_prune_svd`]. When using the `cat`
+                combination_type, the rank of the resulting adapter is equal to the sum of all adapters ranks (the
+                mixed adapter may be too big and result in OOM errors).
+            svd_rank (`int`, *optional*):
+                Rank of output adapter for svd. If None provided, will use max rank of merging adapters.
+            svd_clamp (`float`, *optional*):
+                A quantile threshold for clamping SVD decomposition output. If None is provided, do not perform
+                clamping. Defaults to None.
+            svd_full_matrices (`bool`, *optional*):
+                Controls whether to compute the full or reduced SVD, and consequently, the shape of the returned
+                tensors U and Vh. Defaults to True.
+            svd_driver (`str`, *optional*):
+                Name of the cuSOLVER method to be used. This keyword argument only works when merging on CUDA. Can be
+                one of [None, `gesvd`, `gesvdj`, `gesvda`]. For more info please refer to `torch.linalg.svd`
+                documentation. Defaults to None.
+            density (`float`, *optional*):
+                Value between 0 and 1. 0 means all values are pruned and 1 means no values are pruned. Should be used
+                with [`ties`, `ties_svd`, `dare_ties`, `dare_linear`, `dare_ties_svd`, `dare_linear_svd`,
+                `magnintude_prune`, `magnitude_prune_svd`]
+            majority_sign_method (`str`):
+                The method, should be one of ["total", "frequency"], to use to get the magnitude of the sign values.
+                Should be used with [`ties`, `ties_svd`, `dare_ties`, `dare_ties_svd`]
+        """
+
+        if adapter_name in list(self.peft_config.keys()):
+            return
+
+        combination_type, new_rank, new_target_modules = self._check_add_weighted_adapter(
+            adapters=adapters,
+            combination_type=combination_type,
+            svd_rank=svd_rank,
+        )
+
+        self.peft_config[adapter_name] = replace(
+            self.peft_config[adapters[0]],
+            r=new_rank,
+            lora_alpha=new_rank,
+            target_modules=new_target_modules,
+        )
+        self.inject_adapter(self.model, adapter_name)
+
+        # Do we really need that?
+        _freeze_adapter(self.model, adapter_name)
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, LoraLayer):
+                if adapter_name in target.lora_A:
+                    target_lora_A = target.lora_A[adapter_name].weight
+                    target_lora_B = target.lora_B[adapter_name].weight
+                elif adapter_name in target.lora_embedding_A:
+                    target_lora_A = target.lora_embedding_A[adapter_name]
+                    target_lora_B = target.lora_embedding_B[adapter_name]
+                else:
+                    continue
+
+                target_lora_A.data = target_lora_A.data * 0.0
+                target_lora_B.data = target_lora_B.data * 0.0
+                if combination_type == "cat":
+                    loras_A, loras_B = [], []
+                    for adapter, weight in zip(adapters, weights):
+                        if adapter in target.lora_A:
+                            current_adapter_lora_A = target.lora_A[adapter].weight
+                            current_adapter_lora_B = target.lora_B[adapter].weight
+                        elif adapter in target.lora_embedding_A:
+                            current_adapter_lora_A = target.lora_embedding_A[adapter]
+                            current_adapter_lora_B = target.lora_embedding_B[adapter]
+                        else:
+                            continue
+                        loras_A.append(current_adapter_lora_A.data * weight * target.scaling[adapter])
+                        loras_B.append(current_adapter_lora_B.data)
+
+                    if len(loras_A) == 0:
+                        raise ValueError("No matching LoRAs found. Please raise an issue on GitHub.")
+                    loras_A = torch.cat(loras_A, dim=0)
+                    loras_B = torch.cat(loras_B, dim=1)
+                    target_lora_A.data[: loras_A.shape[0], :] = loras_A
+                    target_lora_B.data[:, : loras_B.shape[1]] = loras_B
+                elif combination_type in [
+                    "svd",
+                    "ties_svd",
+                    "dare_linear_svd",
+                    "dare_ties_svd",
+                    "magnitude_prune_svd",
+                ]:
+                    target_lora_A.data, target_lora_B.data = self._svd_generalized_task_arithmetic_weighted_adapter(
+                        combination_type,
+                        adapters,
+                        weights,
+                        new_rank,
+                        target,
+                        target_lora_A,
+                        target_lora_B,
+                        density,
+                        majority_sign_method,
+                        svd_clamp,
+                        full_matrices=svd_full_matrices,
+                        driver=svd_driver,
+                    )
+                elif combination_type in ["linear", "ties", "dare_linear", "dare_ties", "magnitude_prune"]:
+                    target_lora_A.data, target_lora_B.data = self._generalized_task_arithmetic_weighted_adapter(
+                        combination_type, adapters, weights, target, density, majority_sign_method
+                    )
+
+    def _svd_generalized_task_arithmetic_weighted_adapter(
+        self,
+        combination_type,
+        adapters,
+        weights,
+        new_rank,
+        target,
+        target_lora_A,
+        target_lora_B,
+        density,
+        majority_sign_method,
+        clamp=None,
+        full_matrices=True,
+        driver=None,
+    ):
+        valid_adapters = []
+        valid_weights = []
+        is_embedding = any(adapter in target.lora_embedding_A for adapter in adapters)
+        for adapter, weight in zip(adapters, weights):
+            if adapter in target.lora_A or adapter in target.lora_embedding_A:
+                valid_adapters.append(adapter)
+                valid_weights.append(weight * target.scaling[adapter])
+
+        # if no valid adapter, nothing to do
+        if len(valid_adapters) == 0:
+            raise ValueError("No matching LoRAs found. Please raise an issue on Github.")
+        delta_weight = [target.get_delta_weight(adapter) for adapter in valid_adapters]
+        valid_weights = torch.tensor(valid_weights).to(delta_weight[0].device)
+        if combination_type == "svd":
+            delta_weight = task_arithmetic(delta_weight, valid_weights)
+        elif combination_type == "ties_svd":
+            delta_weight = ties(delta_weight, valid_weights, density, majority_sign_method)
+        elif combination_type == "dare_linear_svd":
+            delta_weight = dare_linear(delta_weight, valid_weights, density)
+        elif combination_type == "dare_ties_svd":
+            delta_weight = dare_ties(delta_weight, valid_weights, density, majority_sign_method)
+        elif combination_type == "magnitude_prune_svd":
+            delta_weight = magnitude_prune(delta_weight, valid_weights, density)
+        else:
+            raise ValueError(f"Invalid value passed to combination type: {combination_type}")
+
+        conv2d = isinstance(target, Conv2d)
+        if conv2d:
+            conv2d_1x1 = target.weight.size()[2:4] == (1, 1)
+            if not conv2d_1x1:
+                delta_weight = delta_weight.flatten(start_dim=1)
+            else:
+                delta_weight = delta_weight.squeeze()
+        if (hasattr(target, "fan_in_fan_out") and target.fan_in_fan_out) or is_embedding:
+            delta_weight = delta_weight.T
+
+        # based on https://github.com/kohya-ss/sd-scripts/blob/main/networks/svd_merge_lora.py#L114-L131
+        U, S, Vh = torch.linalg.svd(delta_weight, full_matrices=full_matrices, driver=driver)
+        U = U[:, :new_rank]
+        S = S[:new_rank]
+        U = U @ torch.diag(S)
+        Vh = Vh[:new_rank, :]
+        if clamp is not None:
+            dist = torch.cat([U.flatten(), Vh.flatten()])
+            hi_val = torch.quantile(dist, clamp)
+            low_val = -hi_val
+            U = U.clamp(low_val, hi_val)
+            Vh = Vh.clamp(low_val, hi_val)
+        if conv2d:
+            U = U.reshape(target_lora_B.data.shape)
+            Vh = Vh.reshape(target_lora_A.data.shape)
+        return Vh, U
+
+    def _generalized_task_arithmetic_weighted_adapter(
+        self,
+        combination_type,
+        adapters,
+        weights,
+        target,
+        density,
+        majority_sign_method,
+    ):
+        # account weights for LoRA A and B layers.
+        valid_weights = []
+        lora_A_deltas = []
+        lora_B_deltas = []
+        for adapter, weight in zip(adapters, weights):
+            if adapter in target.lora_A:
+                current_adapter_lora_A = target.lora_A[adapter].weight
+                current_adapter_lora_B = target.lora_B[adapter].weight
+            elif adapter in target.lora_embedding_A:
+                current_adapter_lora_A = target.lora_embedding_A[adapter]
+                current_adapter_lora_B = target.lora_embedding_B[adapter]
+            else:
+                continue
+            valid_weights.append(math.sqrt(weight * target.scaling[adapter]))
+            lora_A_deltas.append(current_adapter_lora_A.data)
+            lora_B_deltas.append(current_adapter_lora_B.data)
+        valid_weights = torch.tensor(valid_weights).to(lora_A_deltas[0].device)
+        lora_deltas = [lora_A_deltas, lora_B_deltas]
+        dtype = lora_A_deltas[0].dtype
+        for i, task_tensors in enumerate(lora_deltas):
+            if combination_type == "linear":
+                lora_deltas[i] = task_arithmetic(task_tensors, valid_weights)
+            elif combination_type == "ties":
+                lora_deltas[i] = ties(task_tensors, valid_weights, density, majority_sign_method)
+            elif combination_type == "dare_linear":
+                lora_deltas[i] = dare_linear(task_tensors, valid_weights, density)
+            elif combination_type == "dare_ties":
+                lora_deltas[i] = dare_ties(task_tensors, valid_weights, density, majority_sign_method)
+            elif combination_type == "magnitude_prune":
+                lora_deltas[i] = magnitude_prune(task_tensors, valid_weights, density)
+            else:
+                raise ValueError("Invalid combination type")
+        lora_deltas = [delta.to(dtype) for delta in lora_deltas]
+        return lora_deltas
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, LoraLayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the LoRa layers into the base model. This is needed if someone wants to use the base model
+        as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import PeftModel
+
+        >>> base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-40b")
+        >>> peft_model_id = "smangrul/falcon-40B-int4-peft-lora-sfttrainer-sample"
+        >>> model = PeftModel.from_pretrained(base_model, peft_model_id)
+        >>> merged_model = model.merge_and_unload()
+        ```
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the lora modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
+
+    def subtract_mutated_init(self, output_state_dict: dict[str, torch.Tensor], adapter_name: str, kwargs=None):
+        """
+        This function can calculate the updates of the PiSSA/CorDA/OLoRA by comparing the parameters of the
+        PiSSA/CorDA/OLoRA adapter in `output_state_dict` with the initial values of PiSSA/CorDA/OLoRA in
+        `adapter_name`, thus converting PiSSA/CorDA/OLoRA to LoRA.
+        """
+        for name, param in self.model.named_parameters():
+            if (
+                param.data.dtype != torch.float32
+                and param.data.dtype != torch.float16
+                and param.data.dtype != torch.bfloat16
+            ) and adapter_name.startswith("pissa"):
+                warnings.warn(
+                    r"Note that Quant(W_res) + AB != Quant(W) + \Delta(AB); "
+                    "the converted LoRA, when combined with W or Quant(W), may introduce a certain gap in the fine-tuned model. "
+                    "Therefore, we recommend directly using the Quant(W_res) in conjunction with the PiSSA adapter. "
+                )
+        mutated_init_state_dict = get_peft_model_state_dict(
+            self,
+            state_dict=kwargs.get("state_dict", None),
+            adapter_name=adapter_name,
+        )
+        tensors_lora = {}
+        for name in output_state_dict.keys():
+            ## W = W^{res} + A_0 \times B_0,
+            ## W + \Delta W = W^{res} + A \times B,
+            ## \Delta W = A \times B - A_0 \times B_0 = [A | A_0] \times [B | -B_0]^T = A'B'.
+            if "lora_A" in name:
+                tensors_lora[name] = torch.cat(
+                    [output_state_dict[name], mutated_init_state_dict[".".join(name.split(".")[1:])]], dim=0
+                )
+            elif "lora_B" in name:
+                tensors_lora[name] = torch.cat(
+                    [output_state_dict[name], -mutated_init_state_dict[".".join(name.split(".")[1:])]], dim=1
+                )
+
+        return tensors_lora
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/torchao.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/torchao.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e7240a053502bd2be450fd87187c756eeb0c17c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/torchao.py
@@ -0,0 +1,156 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from typing import Any, Optional
+
+import torch
+
+# from torch import nn
+from peft.import_utils import is_torchao_available
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+from .config import LoraConfig
+from .layer import Linear
+
+
+class TorchaoLoraLinear(Linear):
+    """LoRA layer implementation for Linear layers using torchao data"""
+
+    def __init__(self, *args, get_apply_tensor_subclass, **kwargs):
+        # this is not strictly necessary, as kwargs are stored either way, but we want to error early if
+        # get_apply_tensor_subclass is missing.
+        if kwargs.get("lora_bias", False):
+            raise ValueError(f"{self.__class__.__name__} does not support lora_bias yet, set it to False")
+
+        super().__init__(*args, **kwargs)
+        self.get_apply_tensor_subclass = get_apply_tensor_subclass
+        self._check_dtype_supported()
+
+    def _check_dtype_supported(self):
+        # TODO: Not required once int4_weight_only is properly supported by torchao
+        base_layer = self.get_base_layer()
+        weight = base_layer.weight
+        # pytest tests/test_gpu_examples.py::PeftTorchaoGPUTests::test_causal_lm_training_single_gpu_torchao_0_int8_weight_only
+        if (
+            # torchao 0.7.0+
+            (hasattr(weight, "tensor_impl") and (weight.tensor_impl.data.dtype != torch.int8))
+            or
+            # torchao < 0.7.0
+            (hasattr(weight, "layout_tensor") and (weight.layout_tensor.data.dtype != torch.int8))
+        ):
+            raise ValueError(f"{type(self).__name__} only supports int8 weights for now.")
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        from torchao import quantize_
+
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        self._check_dtype_supported()
+
+        base_layer = self.get_base_layer()
+        weight = base_layer.weight
+
+        for active_adapter in adapter_names:
+            try:
+                weight = weight.dequantize()
+            except NotImplementedError as exc:
+                msg = (
+                    f"Weights of type {type(weight).__name__} do not support dequantization (yet), which is needed to "
+                    "support merging."
+                )
+                raise NotImplementedError(msg) from exc
+
+            if safe_merge and not torch.isfinite(weight).all():
+                raise ValueError(
+                    f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                )
+
+            weight += self.get_delta_weight(active_adapter)
+            # TODO: once (if) torchao supports directly mutating the data, use that instead.
+            del base_layer.weight
+            base_layer.weight = weight
+            quantize_(base_layer, self.get_apply_tensor_subclass())
+            del weight
+
+            self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        from torchao import quantize_
+
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter not in self.lora_A.keys():
+                continue
+
+            base_layer = self.get_base_layer()
+            weight = base_layer.weight
+            try:
+                weight = weight.dequantize()
+            except NotImplementedError as exc:
+                msg = (
+                    f"Weights of type {type(weight).__name__} do not support dequantization (yet), which is needed to "
+                    "support unmerging."
+                )
+                raise NotImplementedError(msg) from exc
+
+            weight -= self.get_delta_weight(active_adapter)
+            # We go through a dummy module because overriding the weight.data does not work, the tensor retains the old
+            # data. Therefore, we need to go through quantize_, which takes a module as input, and we need to delete and
+            # re-assign the weight.
+            # TODO: once (if) torchao supports directly mutating the data, use that instead.
+            del base_layer.weight
+            base_layer.weight = weight
+            quantize_(base_layer, self.get_apply_tensor_subclass())
+            del weight
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return rep.replace("lora.Linear", f"lora.{self.__class__.__name__}")
+
+
+def dispatch_torchao(
+    target: torch.nn.Module,
+    adapter_name: str,
+    lora_config: LoraConfig,
+    **kwargs: Any,
+) -> Optional[torch.nn.Module]:
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    if not hasattr(target_base_layer, "weight"):
+        return new_module
+
+    if not is_torchao_available():
+        return new_module
+
+    from torchao.dtypes import AffineQuantizedTensor
+    from torchao.quantization import LinearActivationQuantizedTensor
+
+    if isinstance(target_base_layer.weight, (AffineQuantizedTensor, LinearActivationQuantizedTensor)):
+        new_module = TorchaoLoraLinear(target, adapter_name, **kwargs)
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/tp_layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/tp_layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..fabb3881d3c3f455e81ecd181b2bec512596423c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lora/tp_layer.py
@@ -0,0 +1,404 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import importlib
+import math
+import warnings
+from typing import Any, Optional, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.init as init
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+from peft.utils import transpose
+from peft.utils.integrations import gather_params_ctx
+
+from .layer import LoraLayer
+
+
+class LoraParallelLinear(nn.Module, LoraLayer):
+    """
+    When the target layer parallel_linear is RowParallelLinear, in order to keep the input and output shapes
+    consistent, we need to split the lora matrix A into rows, and the lora_B at this time should be a complete linear
+    layer; In the same way, when the target layer is ColumnParallelLinear, we perform column segmentation on lora_B,
+    while lora_A is still a complete linear layer.
+    """
+
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        backend,
+        r: int = 0,
+        lora_alpha: int = 1,
+        lora_dropout: float = 0.0,
+        fan_in_fan_out: bool = False,
+        is_target_conv_1d_layer: bool = False,
+        init_lora_weights: Union[bool, str] = True,
+        use_rslora: bool = False,
+        use_dora: bool = False,
+        lora_bias: bool = False,
+        **kwargs,
+    ):
+        if lora_bias:
+            raise ValueError(f"{self.__class__.__name__} does not support lora_bias yet, set it to False")
+
+        super().__init__()
+        LoraLayer.__init__(self, base_layer=base_layer, **kwargs)
+
+        if use_dora:
+            raise ValueError(f"{self.__class__.__name__} does not support DoRA yet, please set it to False")
+
+        self.backend = backend
+        self.is_parallel_a = isinstance(base_layer, backend.RowParallelLinear)
+        self.fan_in_fan_out = fan_in_fan_out
+        self._active_adapter = adapter_name
+
+        megatron_config = kwargs["megatron_config"]
+        parallel_linear_kwargs = {"megatron_config": megatron_config}
+        init_method = init.xavier_normal_
+        if hasattr(megatron_config, "init_method"):
+            init_method = megatron_config.init_method
+        input_is_parallel = True
+        gather_output = False
+        if isinstance(base_layer, self.backend.RowParallelLinear):
+            input_is_parallel = base_layer.input_is_parallel
+        else:
+            gather_output = base_layer.gather_output
+        self.update_layer(
+            adapter_name,
+            r,
+            lora_alpha=lora_alpha,
+            lora_dropout=lora_dropout,
+            init_lora_weights=init_lora_weights,
+            use_rslora=use_rslora,
+            use_dora=use_dora,
+            init_method=init_method,
+            input_is_parallel=input_is_parallel,
+            gather_output=gather_output,
+            **parallel_linear_kwargs,
+        )
+
+        if is_target_conv_1d_layer:
+            raise ValueError(
+                f"{self.__class__.__name__} does not support target_conv_1d_layer yet, please set it to False"
+            )
+        self.is_target_conv_1d_layer = False
+
+    def update_layer(
+        self,
+        adapter_name,
+        r,
+        lora_alpha,
+        lora_dropout,
+        init_lora_weights,
+        use_rslora,
+        use_dora=False,
+        init_method=init.xavier_normal_,
+        input_is_parallel=True,
+        gather_output=False,
+        **parallel_linear_kwargs,
+    ):
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+        self.r[adapter_name] = r
+        self.lora_alpha[adapter_name] = lora_alpha
+        if lora_dropout > 0.0:
+            lora_dropout_layer = nn.Dropout(p=lora_dropout)
+        else:
+            lora_dropout_layer = nn.Identity()
+
+        self.lora_dropout[adapter_name] = lora_dropout_layer
+
+        megatron_config = parallel_linear_kwargs["megatron_config"]
+        # lora needs to be forced to upgrade to 32-bit precision, otherwise it will overflow
+        megatron_config.params_dtype = torch.float32
+        if self.is_parallel_a:
+            lora_a = self.backend.RowParallelLinear(
+                input_size=self.in_features,
+                output_size=r,
+                bias=False,
+                input_is_parallel=input_is_parallel,
+                skip_bias_add=True,
+                init_method=init_method,
+                config=megatron_config,
+            )
+            lora_b = nn.Linear(in_features=r, out_features=self.out_features, bias=False, dtype=torch.float32)
+        else:
+            lora_a = nn.Linear(in_features=self.in_features, out_features=r, bias=False, dtype=torch.float32)
+            lora_b = self.backend.ColumnParallelLinear(
+                input_size=r,
+                output_size=self.out_features,
+                bias=False,
+                gather_output=gather_output,
+                init_method=init_method,
+                config=megatron_config,
+            )
+        self.lora_A[adapter_name] = lora_a
+        self.lora_B[adapter_name] = lora_b
+        if use_rslora:
+            self.scaling[adapter_name] = lora_alpha / math.sqrt(r)
+        else:
+            self.scaling[adapter_name] = lora_alpha / r
+
+        # for inits that require access to the base weight, use gather_param_ctx so that the weight is gathered when using DeepSpeed
+        if isinstance(init_lora_weights, str) and init_lora_weights.startswith("pissa"):
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.pissa_init(adapter_name, init_lora_weights)
+        elif isinstance(init_lora_weights, str) and init_lora_weights.startswith("corda"):
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.corda_init(adapter_name, init_lora_weights)
+        elif isinstance(init_lora_weights, str) and init_lora_weights.lower() == "olora":
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.olora_init(adapter_name)
+        elif init_lora_weights == "loftq":
+            with gather_params_ctx(self.get_base_layer().weight):
+                self.loftq_init(adapter_name)
+        elif init_lora_weights:
+            self.reset_lora_parameters(adapter_name, init_lora_weights)
+
+        # call this before dora_init
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+
+        if use_dora:
+            self.dora_init(adapter_name)
+            self.use_dora[adapter_name] = True
+        else:
+            self.use_dora[adapter_name] = False
+
+        self.set_adapter(self.active_adapters)
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any):
+        self._check_forward_args(x, *args, **kwargs)
+        adapter_names = kwargs.pop("adapter_names", None)
+        # If weight is used for matrix multiplication here, the final aggregation operation of the original
+        # parallel_linear layer will be missing, so we need to directly call its forward function to obtain the
+        # output of the original parallel_linear layer.
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result, bias = self.base_layer(x, *args, **kwargs)
+        elif adapter_names is not None:
+            raise ValueError(f"{self.__class__.__name__} does not support mixed_batch_forward yet.")
+        elif self.merged:
+            result, bias = self.base_layer(x, *args, **kwargs)
+        else:
+            result, bias = self.base_layer(x, *args, **kwargs)
+            torch_result_dtype = result.dtype
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.lora_A.keys():
+                    continue
+                lora_A = self.lora_A[active_adapter]
+                lora_B = self.lora_B[active_adapter]
+                dropout = self.lora_dropout[active_adapter]
+                scaling = self.scaling[active_adapter]
+                x = self._cast_input_dtype(x, lora_A.weight.dtype)
+
+                if not self.use_dora[active_adapter]:
+                    result = result + lora_B(lora_A(dropout(x))) * scaling
+                else:
+                    if isinstance(dropout, torch.nn.Identity) or not self.training:
+                        base_result = result
+                    else:
+                        x = dropout(x)
+                        base_result = None
+
+                    result = result + self.lora_magnitude_vector[active_adapter](
+                        x,
+                        lora_A=lora_A,
+                        lora_B=lora_B,
+                        scaling=scaling,
+                        base_layer=self.get_base_layer(),
+                        base_result=base_result,
+                    )
+
+            result = result.to(torch_result_dtype)
+        return result, bias
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`list[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.lora_A.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    if not self.use_dora[active_adapter]:
+                        orig_weights = orig_weights + delta_weight
+                    else:
+                        # handle dora
+                        # since delta_weight already includes scaling, set it to 1 here
+                        weight_norm = (
+                            self.lora_magnitude_vector[active_adapter]
+                            .get_weight_norm(orig_weights, transpose(delta_weight, self.fan_in_fan_out), scaling=1)
+                            .detach()
+                        )
+                        # We need to cache weight_norm because it has to be based on the original weights. We
+                        # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                        # different value
+                        self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                        dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                        dora_factor = transpose(dora_factor.view(-1, 1), self.fan_in_fan_out)
+                        orig_weights = dora_factor * (orig_weights + delta_weight)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights
+                else:
+                    delta_weight = self.get_delta_weight(active_adapter)
+                    if not self.use_dora[active_adapter]:
+                        base_layer.weight.data = base_layer.weight.data + delta_weight
+                    else:
+                        # handle dora
+                        # since delta_weight already includes scaling, set it to 1 here
+                        weight_norm = (
+                            self.lora_magnitude_vector[active_adapter]
+                            .get_weight_norm(
+                                base_layer.weight, transpose(delta_weight, self.fan_in_fan_out), scaling=1
+                            )
+                            .detach()
+                        )
+                        # We need to cache weight_norm because it has to be based on the original weights. We
+                        # cannot calculate it on the fly based on the merged weights when unmerging because its a
+                        # different value
+                        self._cache_store(f"{active_adapter}-weight_norm", weight_norm)
+                        dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                        dora_factor = transpose(dora_factor.view(-1, 1), self.fan_in_fan_out)
+                        new_weight = dora_factor * (base_layer.weight.data + delta_weight)
+                        base_layer.weight.data = new_weight
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.lora_A.keys():
+                weight = self.get_base_layer().weight
+                delta_weight = self.get_delta_weight(active_adapter)
+                if not self.use_dora[active_adapter]:
+                    weight.data -= delta_weight
+                else:
+                    weight_norm = self._cache_pop(f"{active_adapter}-weight_norm")
+                    dora_factor = self.lora_magnitude_vector[active_adapter].weight / weight_norm
+                    weight_orig = weight.data / dora_factor.view(-1, 1) - delta_weight
+                    weight.data = weight_orig
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.lora_B[adapter].weight.device
+        dtype = self.lora_B[adapter].weight.dtype
+
+        # In case users wants to merge the adapter weights that are in
+        # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+        cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+        weight_A = self.lora_A[adapter].weight
+        weight_B = self.lora_B[adapter].weight
+
+        if cast_to_fp32:
+            weight_A = weight_A.float()
+            weight_B = weight_B.float()
+
+        output_tensor = transpose(weight_B @ weight_A, self.fan_in_fan_out) * self.scaling[adapter]
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            self.lora_A[adapter].weight.data = weight_A.to(dtype)
+            self.lora_B[adapter].weight.data = weight_B.to(dtype)
+
+        return output_tensor
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "lora." + rep
+
+
+def dispatch_megatron(
+    target: torch.nn.Module,
+    adapter_name: str,
+    lora_config,
+    **kwargs: Any,
+) -> Optional[torch.nn.Module]:
+    new_module = None
+
+    if isinstance(target, BaseTunerLayer):
+        target_base_layer = target.get_base_layer()
+    else:
+        target_base_layer = target
+
+    if lora_config.megatron_config:
+        megatron_core = importlib.import_module(lora_config.megatron_core)
+    else:
+        megatron_core = None
+
+    if megatron_core and isinstance(
+        target_base_layer,
+        (megatron_core.tensor_parallel.ColumnParallelLinear, megatron_core.tensor_parallel.RowParallelLinear),
+    ):
+        megatron_kwargs = kwargs.copy()
+        megatron_config = lora_config.megatron_config
+        if isinstance(megatron_config, dict):
+            transformer_config_class = megatron_core.transformer.transformer_config.TransformerConfig
+            megatron_config = transformer_config_class(**lora_config.megatron_config)
+        megatron_kwargs["megatron_config"] = megatron_config
+        if megatron_kwargs["fan_in_fan_out"]:
+            warnings.warn(
+                "fan_in_fan_out is set to True but the target module is `ColumnParallelLinear` "
+                "or `RowParallelLinear`. "
+                "Setting fan_in_fan_out to False."
+            )
+            megatron_kwargs["fan_in_fan_out"] = lora_config.fan_in_fan_out = False
+        new_module = LoraParallelLinear(
+            base_layer=target, adapter_name=adapter_name, backend=megatron_core.tensor_parallel, **megatron_kwargs
+        )
+
+    return new_module
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lycoris_utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lycoris_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..99d42c1d7d6a25b9f1471b59738ae7bc23e8a14d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/lycoris_utils.py
@@ -0,0 +1,436 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from abc import abstractmethod
+from dataclasses import dataclass, field
+from typing import Any, Optional, Union
+
+import torch
+import torch.nn as nn
+from tqdm import tqdm
+
+from peft.config import PeftConfig
+from peft.utils import (
+    ModulesToSaveWrapper,
+    _get_submodules,
+)
+
+from .tuners_utils import BaseTuner, BaseTunerLayer, check_adapters_to_merge, check_target_module_exists
+
+
+@dataclass
+class LycorisConfig(PeftConfig):
+    r"""
+    A base config for LyCORIS like adapters
+    """
+
+    rank_pattern: Optional[dict] = field(
+        default_factory=dict,
+        metadata={
+            "help": (
+                "The mapping from layer names or regexp expression to ranks which are different from the default rank specified by `r`. "
+                "For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`."
+            )
+        },
+    )
+    alpha_pattern: Optional[dict] = field(
+        default_factory=dict,
+        metadata={
+            "help": (
+                "The mapping from layer names or regexp expression to alphas which are different from the default alpha specified by `alpha`. "
+                "For example, `{'^model.decoder.layers.0.encoder_attn.k_proj': 16}`."
+            )
+        },
+    )
+
+
+class LycorisLayer(BaseTunerLayer):
+    r"""
+    A base layer for LyCORIS like adapters
+    """
+
+    # adapter_layer_names needs to be defined on the child class
+    other_param_names = ("r", "alpha", "scaling", "rank_dropout", "module_dropout")
+
+    def __init__(self, base_layer: nn.Module) -> None:
+        self.base_layer = base_layer
+        self.r = {}
+        self.alpha = {}
+        self.scaling = {}
+        self.rank_dropout = {}
+        self.rank_dropout_scale = {}
+        self.module_dropout = {}
+
+        # Tuner info
+        self._disable_adapters = False
+        self.merged_adapters = []
+
+    @property
+    @abstractmethod
+    def _available_adapters(self) -> set[str]: ...
+
+    def _init_empty_weights(self, cls, *args, **kwargs) -> None:
+        # A helper method that allows to initialize the layer of the given class without spending time to initialize the
+        # model weights. The implementation is inspired by
+        # https://pytorch.org/docs/stable/generated/torch.nn.utils.skip_init.html but this function cannot be used
+        # directly.
+        # Instead of this approach, it would be possible to bypass the __init__ of the class but that runs the risk of
+        # omitting important logic inside that __init__.
+        kwargs = kwargs.copy()
+        final_device = kwargs.pop("device", "cpu")
+        cls.__init__(self, *args, device="meta", **kwargs)
+        self.to_empty(device=final_device)
+
+    @abstractmethod
+    def create_adapter_parameters(self, adapter_name: str, r: int, **kwargs): ...
+
+    # TODO: refactor LoRA to use the same approach
+    @abstractmethod
+    def _get_delta_activations(self, adapter_name: str, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        """Activations added on top of the base layer output (i.e. after the base layer forward pass)"""
+
+    @abstractmethod
+    def get_delta_weight(self, adapter_name: str) -> torch.Tensor: ...
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If `True`, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If `None`, all active adapters will be merged.
+                Defaults to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self._available_adapters:
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    orig_weights = base_layer.weight.data.clone()
+                    orig_weights += self.get_delta_weight(active_adapter)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights
+                else:
+                    base_layer.weight.data += self.get_delta_weight(active_adapter)
+                self.merged_adapters.append(active_adapter)
+
+    @abstractmethod
+    def reset_adapter_parameters(self, adapter_name: str): ...
+
+    def set_scale(self, adapter, scale):
+        if adapter not in self._available_adapters:
+            # Ignore the case where the adapter is not in the layer
+            return
+        self.scaling[adapter] = scale * self.alpha[adapter] / self.r[adapter]
+
+    def scale_layer(self, scale: float) -> None:
+        if scale == 1:
+            return
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self._available_adapters:
+                continue
+
+            self.scaling[active_adapter] *= scale
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self._available_adapters:
+                self.get_base_layer().weight.data -= self.get_delta_weight(active_adapter)
+
+    def unscale_layer(self, scale=None) -> None:
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self._available_adapters:
+                continue
+
+            if scale is None:
+                self.scaling[active_adapter] = self.alpha[active_adapter] / self.r[active_adapter]
+            else:
+                self.scaling[active_adapter] /= scale
+
+    @abstractmethod
+    def update_layer(self, adapter_name: str, r: int, alpha: float, **kwargs): ...
+
+
+class LycorisTuner(BaseTuner):
+    r"""
+    A base tuner for LyCORIS like adapters
+
+    Args:
+        model ([`torch.nn.Module`]): The model to be adapted.
+        config ([`LoraConfig`]): The configuration of the Lora model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    """
+
+    prefix: str
+    layers_mapping: dict[type[torch.nn.Module], type[LycorisLayer]]
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False):
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    @staticmethod
+    def _check_target_module_exists(config, key):
+        return check_target_module_exists(config, key)
+
+    @abstractmethod
+    def _create_and_replace(
+        self,
+        config: LycorisConfig,
+        adapter_name: str,
+        target: Union[LycorisLayer, nn.Module],
+        target_name,
+        parent,
+        current_key,
+    ): ...
+
+    @classmethod
+    def _create_new_module(cls, config: LycorisConfig, adapter_name: str, target: nn.Module, **kwargs) -> LycorisLayer:
+        # Find corresponding subtype of provided target module
+        new_module_cls = None
+        for subtype, target_cls in cls.layers_mapping.items():
+            if (
+                hasattr(target, "base_layer")
+                and isinstance(target.get_base_layer(), subtype)
+                and isinstance(target, BaseTunerLayer)
+            ):
+                # nested tuner layers are allowed
+                new_module_cls = target_cls
+                break
+            elif isinstance(target, subtype):
+                new_module_cls = target_cls
+                break
+
+        # We didn't find corresponding type, so adapter for this layer is not supported
+        if new_module_cls is None:
+            supported_modules = ", ".join(layer.__name__ for layer in cls.layers_mapping.keys())
+            raise ValueError(
+                f"Target module of type {type(target)} not supported, "
+                f"currently only adapters for {supported_modules} are supported"
+            )
+
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Conv2d):
+            new_module = new_module_cls(target, adapter_name=adapter_name, **kwargs)
+        elif isinstance(target_base_layer, torch.nn.Linear):
+            new_module = new_module_cls(target, adapter_name=adapter_name, **kwargs)
+        else:
+            supported_modules = ", ".join(layer.__name__ for layer in cls.layers_mapping.keys())
+            raise ValueError(
+                f"Target module of type {type(target)} not supported, "
+                f"currently only adapters for {supported_modules} are supported"
+            )
+
+        return new_module
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            raise ValueError("Please specify `target_modules` in `peft_config`")
+        return peft_config
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if self.prefix in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def _unload_and_optionally_merge(
+        self,
+        merge: bool = True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        if merge:
+            if getattr(self.model, "quantization_method", None) == "gptq":
+                raise ValueError("Cannot merge LOHA layers when the model is gptq quantized")
+
+        self._unloading_checks(adapter_names)
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                new_module = target.modules_to_save[target.active_adapter]
+                if hasattr(new_module, "base_layer"):
+                    # check if the module is itself a tuner layer
+                    if merge:
+                        new_module.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                    new_module = new_module.get_base_layer()
+                setattr(parent, target_name, new_module)
+
+        return self.model
+
+    def enable_adapter_layers(self) -> None:
+        """Enable all adapters.
+
+        Call this if you have previously disabled all adapters and want to re-enable them.
+        """
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self) -> None:
+        """Disable all adapters.
+
+        When disabling all adapters, the model output corresponds to the output of the base model.
+        """
+        self._set_adapter_layers(enabled=False)
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the adapter layers into the base model. This is needed if someone wants to use the base
+        model as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the lora modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
+
+    def set_adapter(self, adapter_name: str | list[str]) -> None:
+        """Set the active adapter(s).
+
+        Additionally, this function will set the specified adapters to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str` or `list[str]`): Name of the adapter(s) to be activated.
+        """
+        for module in self.model.modules():
+            if isinstance(module, LycorisLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (`str`): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, LycorisLayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/mixed/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/mixed/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..2955d7258ddcf76b47b38fd6fd5ebeb3d1d6110c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/mixed/__init__.py
@@ -0,0 +1,18 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from .model import COMPATIBLE_TUNER_TYPES, MixedModel
+
+
+__all__ = ["COMPATIBLE_TUNER_TYPES", "MixedModel"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/mixed/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/mixed/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..4f83571e2582f89c22a0f3ec7f2cd7aed31a0ca4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/mixed/model.py
@@ -0,0 +1,341 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from typing import Any, Optional, Union
+
+from torch import nn
+from tqdm import tqdm
+
+from peft.tuners import adalora, loha, lokr, lora, oft
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    PeftType,
+    _get_submodules,
+    get_auto_gptq_quant_linear,
+)
+
+
+# Collection of constants used for all tuners
+COMPATIBLE_TUNER_TYPES = (PeftType.LORA, PeftType.LOHA, PeftType.LOKR, PeftType.ADALORA, PeftType.OFT)
+PREFIXES = [lora.LoraModel.prefix, lokr.LoKrModel.prefix, loha.LoHaModel.prefix, oft.OFTModel.prefix]
+Configs = Union[lora.LoraConfig, loha.LoHaConfig, lokr.LoKrConfig, adalora.AdaLoraConfig, oft.OFTConfig]
+Layers = (lora.layer.LoraLayer, loha.layer.LoHaLayer, lokr.layer.LoKrLayer, adalora.layer.AdaLoraLayer, oft.OFTLayer)
+
+
+class MixedModel(BaseTuner):
+    """
+    A class that allows to mix different types of adapters in a single model.
+
+    Note: This class should usually not be initialized directly. Instead, use `get_peft_model` with the argument
+    `mixed=True`.
+
+    Args:
+        model (:obj:`nn.Module`):
+            The model to be tuned.
+        config (:obj:`PeftConfig`):
+            The config of the model to be tuned. The adapter type must be compatible.
+        adapter_name (:obj:`str`):
+            The name of the first adapter.
+    """
+
+    def __init__(self, model: nn.Module, config: Configs, adapter_name: str) -> None:
+        super().__init__(model, config, adapter_name)
+
+    def _check_new_adapter_config(self, config: Configs) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        if not isinstance(config, Configs.__args__):
+            raise ValueError(
+                f"{self.__class__.__name__} only supports {COMPATIBLE_TUNER_TYPES} configs, but got {type(config)}."
+            )
+
+        biases = (getattr(config, "bias", None) for config in self.peft_config)
+        biases = [bias for bias in biases if bias not in (None, "none")]
+        if len(biases) > 1:
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(config: Configs, key: str):
+        return check_target_module_exists(config, key)
+
+    def _create_and_replace(
+        self,
+        config: Configs,
+        *args: Any,
+        **kwargs: Any,
+    ) -> None:
+        if isinstance(config, adalora.AdaLoraConfig):
+            adalora.AdaLoraModel._create_and_replace(self, config, *args, **kwargs)
+        elif isinstance(config, lora.LoraConfig):
+            lora.LoraModel._create_and_replace(self, config, *args, **kwargs)
+        elif isinstance(config, loha.LoHaConfig):
+            loha.LoHaModel._create_and_replace(self, config, *args, **kwargs)
+        elif isinstance(config, lokr.LoKrConfig):
+            lokr.LoKrModel._create_and_replace(self, config, *args, **kwargs)
+        elif isinstance(config, oft.OFTConfig):
+            oft.OFTModel._create_and_replace(self, config, *args, **kwargs)
+        else:
+            raise ValueError(f"Unsupported config type {type(config)}, should be one of {COMPATIBLE_TUNER_TYPES}.")
+
+    def _replace_module(self, parent, child_name, new_module, child) -> None:
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.get_base_layer()
+        elif hasattr(child, "quant_linear_module"):
+            # TODO maybe not necessary to have special treatment?
+            child = child.quant_linear_module
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if any(prefix in name for prefix in PREFIXES):
+                module.to(child.weight.device)
+            if "ranknum" in name:
+                module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if not any(prefix in n for prefix in PREFIXES):
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = getattr(self.peft_config[active_adapter], "bias", "none")
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "lora_only":
+                # TODO: check if this is needed for other supported types
+                for m in model.modules():
+                    if isinstance(m, Layers) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise ValueError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(config, adapter_name, target, **kwargs):
+        gptq_quantization_config = kwargs.get("gptq_quantization_config", None)
+        AutoGPTQQuantLinear = get_auto_gptq_quant_linear(gptq_quantization_config)
+        if (gptq_quantization_config is not None) or (AutoGPTQQuantLinear is not None):
+            raise ValueError(f"GPTQ quantization not supported for {config.peft_type.value} (yet).")
+
+        loaded_in_8bit = kwargs.pop("loaded_in_8bit", False)
+        loaded_in_4bit = kwargs.pop("loaded_in_4bit", False)
+        if loaded_in_8bit or loaded_in_4bit:
+            raise ValueError(f"8bit and 4bit quantization not supported for {config.peft_type.value} (yet).")
+
+        if isinstance(config, adalora.AdaLoraConfig):
+            new_module = adalora.AdaLoraModel._create_new_module(config, adapter_name, target, **kwargs)
+        elif isinstance(config, lora.LoraConfig):
+            new_module = lora.LoraModel._create_new_module(config, adapter_name, target, **kwargs)
+        elif isinstance(config, loha.LoHaConfig):
+            new_module = loha.LoHaModel._create_new_module(config, adapter_name, target, **kwargs)
+        elif isinstance(config, lokr.LoKrConfig):
+            new_module = lokr.LoKrModel._create_new_module(config, adapter_name, target, **kwargs)
+        elif isinstance(config, oft.OFTConfig):
+            new_module = oft.OFTModel._create_new_module(config, adapter_name, target, **kwargs)
+        else:
+            raise ValueError(f"Unknown config type {type(config)}, should be one of {COMPATIBLE_TUNER_TYPES}.")
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self):
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self):
+        for active_adapter in self.active_adapters:
+            val = getattr(self.peft_config[active_adapter], "bias", "none")
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name: Union[str, list[str]]) -> None:
+        for module in self.model.modules():
+            if isinstance(module, Layers):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        if merge:
+            if getattr(self.model, "quantization_method", None) == "gptq":
+                raise ValueError("Cannot merge layers when the model is gptq quantized")
+
+        def merge_recursively(module):
+            # helper function to recursively merge the base_layer of the target
+            path = []
+            layer = module
+            while hasattr(layer, "base_layer"):
+                path.append(layer)
+                layer = layer.base_layer
+            for layer_before, layer_after in zip(path[:-1], path[1:]):
+                layer_after.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                layer_before.base_layer = layer_after.base_layer
+            module.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+
+        key_list = [key for key, _ in self.model.named_modules() if not any(prefix in key for prefix in PREFIXES)]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    merge_recursively(target)
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                new_module = target.modules_to_save[target.active_adapter]
+                if hasattr(new_module, "base_layer"):
+                    # check if the module is itself a tuner layer
+                    if merge:
+                        new_module.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                    new_module = new_module.get_base_layer()
+                setattr(parent, target_name, new_module)
+
+        return self.model
+
+    def add_weighted_adapter(self, *args: Any, **kwargs: Any) -> None:
+        raise NotImplementedError(f"Weighted adapters are not supported for {self.__class__.__name__} (yet).")
+
+    def delete_adapter(self, adapter_name: Union[str, list[str]]) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (Union[str, list[str]]): Name of the adapter(s) to delete.
+        """
+        if isinstance(adapter_name, str):
+            adapter_names = [adapter_name]
+        else:
+            adapter_names = adapter_name
+
+        mismatched = set(adapter_names) - set(self.peft_config.keys())
+        if mismatched:
+            raise ValueError(
+                f"Adapter(s) {sorted(mismatched)} not found, available adapters: {sorted(self.peft_config.keys())}"
+            )
+
+        for adapter_name in adapter_names:
+            del self.peft_config[adapter_name]
+
+            key_list = [key for key, _ in self.model.named_modules() if not any(prefix in key for prefix in PREFIXES)]
+            new_adapter = None
+            for key in key_list:
+                _, target, _ = _get_submodules(self.model, key)
+                if isinstance(target, BaseTunerLayer):
+                    target.delete_adapter(adapter_name)
+                    if new_adapter is None:
+                        new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ) -> nn.Module:
+        r"""
+        This method merges the layers into the base model. This is needed if someone wants to use the base model as a
+        standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> nn.Module:
+        """
+        Gets back the base model by removing all the lora modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
+
+    def generate(self, *args: Any, **kwargs: Any):
+        return self.model.generate(*args, **kwargs)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe692a93378254601753cc9b17218fdd5a92b8de
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/__init__.py
@@ -0,0 +1,25 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import MultitaskPromptTuningConfig, MultitaskPromptTuningInit
+from .model import MultitaskPromptEmbedding
+
+
+__all__ = ["MultitaskPromptEmbedding", "MultitaskPromptTuningConfig", "MultitaskPromptTuningInit"]
+
+register_peft_method(
+    name="multitask_prompt_tuning", config_cls=MultitaskPromptTuningConfig, model_cls=MultitaskPromptEmbedding
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..6cb279573559e4fa33a973aa35e052647a6ab8f9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/config.py
@@ -0,0 +1,62 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import enum
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.tuners.prompt_tuning import PromptTuningConfig
+from peft.utils import PeftType
+
+
+class MultitaskPromptTuningInit(str, enum.Enum):
+    # initialize prompt with text
+    TEXT = "TEXT"
+    # initialize prompt with random matrix
+    RANDOM = "RANDOM"
+    # average the prefix and column matrices obtained during source training
+    AVERAGE_SOURCE_TASKS = "AVERAGE_SOURCE_TASKS"
+    # pick prefix and column matrices for a particular task obtained during source training
+    EXACT_SOURCE_TASK = "EXACT_SOURCE_TASK"
+    # only use the prompt embeddings trained during source training
+    ONLY_SOURCE_SHARED = "ONLY_SOURCE_SHARED"
+
+
+@dataclass
+class MultitaskPromptTuningConfig(PromptTuningConfig):
+    prompt_tuning_init: Union[MultitaskPromptTuningInit, str] = field(
+        default=MultitaskPromptTuningInit.RANDOM,
+        metadata={
+            "help": (
+                "How to initialize the prompt tuning parameters. Can be one of TEXT, RANDOM, AVERAGE_SOURCE_TASKS, "
+                "EXACT_SOURCE_TASK, ONLY_SOURCE_SHARED."
+            ),
+        },
+    )
+    prompt_tuning_init_state_dict_path: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The path of source state dict. This is required when training the downstream target prompt from "
+                "the pretrained source prompt"
+            ),
+        },
+    )
+    prompt_tuning_init_task: Optional[int] = field(default=0, metadata={"help": "source task id for initialization"})
+    num_ranks: Optional[int] = field(default=1, metadata={"help": "ranks"})
+    num_tasks: Optional[int] = field(default=1, metadata={"help": "number of tasks"})
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.MULTITASK_PROMPT_TUNING
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..3350999eaef8f4f53b196a08a5a66e51475df617
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/multitask_prompt_tuning/model.py
@@ -0,0 +1,120 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+
+from peft.tuners.prompt_tuning import PromptEmbedding
+from peft.utils import TaskType
+from peft.utils.save_and_load import torch_load
+
+from .config import MultitaskPromptTuningConfig, MultitaskPromptTuningInit
+
+
+# This code is adapted for the paper: https://arxiv.org/abs/2303.02861 and
+# constitutes the work done at MIT-IBM Watson Research Lab.
+
+
+class MultitaskPromptEmbedding(PromptEmbedding):
+    def __init__(self, config: MultitaskPromptTuningConfig, word_embeddings):
+        super().__init__(config, word_embeddings)
+
+        self.num_tasks = config.num_tasks
+        self.num_ranks = config.num_ranks
+        self.num_virtual_tokens = config.num_virtual_tokens
+
+        self.num_transformer_submodules = config.num_transformer_submodules
+        if self.num_transformer_submodules is None:
+            self.num_transformer_submodules = 2 if config.task_type == TaskType.SEQ_2_SEQ_LM else 1
+
+        self.token_dim = config.token_dim
+
+        total_virtual_tokens = self.num_virtual_tokens * self.num_transformer_submodules
+
+        self.prefix_task_cols = torch.nn.Parameter(
+            torch.normal(
+                mean=0,
+                std=0.02,
+                size=(self.num_tasks, total_virtual_tokens, self.num_ranks),
+            )
+        )
+        self.prefix_task_rows = torch.nn.Parameter(
+            torch.normal(
+                mean=0,
+                std=0.02,
+                size=(self.num_tasks, self.num_ranks, self.token_dim),
+            )
+        )
+
+        if config.prompt_tuning_init in [
+            MultitaskPromptTuningInit.AVERAGE_SOURCE_TASKS,
+            MultitaskPromptTuningInit.EXACT_SOURCE_TASK,
+            MultitaskPromptTuningInit.ONLY_SOURCE_SHARED,
+        ]:
+            if config.prompt_tuning_init_state_dict_path is None:
+                raise ValueError(
+                    f"prompt_tuning_init_state_dict_path needs to be specified with {config.prompt_tuning_init} "
+                    "init method"
+                )
+
+            if config.prompt_tuning_init_state_dict_path.endswith(".safetensors"):
+                from safetensors.torch import load_file
+
+                state_dict: dict = load_file(config.prompt_tuning_init_state_dict_path)
+            else:
+                state_dict: dict = torch_load(
+                    config.prompt_tuning_init_state_dict_path,
+                    map_location=word_embeddings.weight.device,
+                )
+
+        if config.prompt_tuning_init in [
+            MultitaskPromptTuningInit.AVERAGE_SOURCE_TASKS,
+            MultitaskPromptTuningInit.EXACT_SOURCE_TASK,
+        ]:
+            prefix_task_cols_: torch.Tensor = state_dict["prefix_task_cols"]
+            prefix_task_rows_: torch.Tensor = state_dict["prefix_task_rows"]
+
+            if config.prompt_tuning_init == MultitaskPromptTuningInit.AVERAGE_SOURCE_TASKS:
+                prefix_task_cols_ = prefix_task_cols_.mean(0, keepdim=True)
+                prefix_task_rows_ = prefix_task_rows_.mean(0, keepdim=True)
+            elif config.prompt_tuning_init == MultitaskPromptTuningInit.EXACT_SOURCE_TASK:
+                prefix_task_cols_ = prefix_task_cols_[config.prompt_tuning_init_task, ...].unsqueeze(0)
+                prefix_task_rows_ = prefix_task_rows_[config.prompt_tuning_init_task, ...].unsqueeze(0)
+
+            state_dict = {
+                "embedding.weight": state_dict["prompt_embeddings"],
+                "prefix_task_cols": prefix_task_cols_,
+                "prefix_task_rows": prefix_task_rows_,
+            }
+
+            self.load_state_dict(state_dict, strict=True)
+        elif config.prompt_tuning_init == MultitaskPromptTuningInit.ONLY_SOURCE_SHARED:
+            state_dict = {
+                "embedding.weight": state_dict["prompt_embeddings"],
+            }
+
+            self.load_state_dict(state_dict, strict=False)
+
+    def forward(self, indices, task_ids):
+        if task_ids is None:
+            raise ValueError("task_ids cannot be None")
+
+        prompt_embeddings = self.embedding(indices)
+
+        task_cols = torch.index_select(self.prefix_task_cols, 0, task_ids)
+        task_rows = torch.index_select(self.prefix_task_rows, 0, task_ids)
+        task_prompts = torch.matmul(task_cols, task_rows)
+
+        prompt_embeddings *= task_prompts
+
+        return prompt_embeddings
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5df395090faa68e308c705ae3e640375dccb05b8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import OFTConfig
+from .layer import Conv2d, Linear, OFTLayer
+from .model import OFTModel
+
+
+__all__ = ["Conv2d", "Linear", "OFTConfig", "OFTLayer", "OFTModel"]
+
+register_peft_method(name="oft", config_cls=OFTConfig, model_cls=OFTModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..36775f1aac50735bcf651e8ac97d2c4f09a0663f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/config.py
@@ -0,0 +1,184 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Literal, Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class OFTConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`OFTModel`].
+
+    Args:
+        r (`int`): OFT rank, number of OFT blocks per injected layer.
+        oft_block_size (`int`): OFT block size across different layers.
+        module_dropout (`float`):
+            The multiplicative dropout probability, by setting OFT blocks to identity during training, similar to the
+            dropout layer in LoRA.
+        target_modules (`Optional[Union[list[str], str]]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear modules are chosen, excluding
+            the output layer. If this is not specified, modules will be chosen according to the model architecture. If
+            the architecture is not known, an error will be raised -- in this case, you should specify the target
+            modules manually.
+        fan_in_fan_out (`bool`): Set this to True if the layer to replace stores weight like (fan_in, fan_out).
+        bias (`str`): Bias type for OFT. Can be 'none', 'all' or 'oft_only'. If 'all' or 'oft_only', the
+            corresponding biases will be updated during training. Be aware that this means that, even when disabling
+            the adapters, the model will not produce the same output as the base model would have without adaptation.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        init_weights (`bool`):
+            Whether to perform initialization of OFT weights.
+        layers_to_transform (`Union[List[int], int]`):
+            The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
+            that are specified in this list. If a single integer is passed, it will apply the transformations on the
+            layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`. This should target the
+            `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`.
+        modules_to_save (`List[str]`):
+            List of modules apart from adapter layers to be set as trainable and saved in the final checkpoint.
+        coft (`bool`):
+            Whether to use the constrained variant of OFT or not, off by default.
+        eps (`float`):
+            The control strength of COFT. The freedom of rotation. Only has an effect if `coft` is set to True.
+        block_share (`bool`):
+            Whether to share the OFT parameters between blocks or not. This is `False` by default.
+    """
+
+    r: int = field(default=8, metadata={"help": "OFT rank, number of OFT blocks per injected layer."})
+    oft_block_size: int = field(
+        default=0,
+        metadata={
+            "help": "OFT block size across different layers.",
+            "note": "You can only specify either r or oft_block_size, but not both simultaneously, because r x oft_block_size = layer dimension.",
+        },
+    )
+    module_dropout: float = field(
+        default=0.0,
+        metadata={
+            "help": "OFT multiplicative dropout, randomly setting blocks of OFT to be identity matrix, similar to the dropout layer in LoRA."
+        },
+    )
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or regex expression of the module names to replace with OFT."
+            "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$' "
+            "This can also be a wildcard 'all-linear' which matches all linear/Conv1D layers except the output layer."
+        },
+    )
+    fan_in_fan_out: bool = field(
+        default=False,
+        metadata={"help": "Set this to True if the layer to replace stores weight like (fan_in, fan_out)"},
+    )
+    bias: Literal["none", "all", "oft_only"] = field(
+        default="none", metadata={"help": "Bias type for OFT. Can be 'none', 'all' or 'oft_only'"}
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from OFT."},
+    )
+    init_weights: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the OFT layers with their default initialization. Don't change "
+                "this setting, except if you know exactly what you're doing."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index."
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern. "
+            "This should target the `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`."
+        },
+    )
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from OFT layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+    coft: bool = field(
+        default=False,
+        metadata={"help": "Whether to use the constrained variant of OFT or not."},
+    )
+    eps: float = field(
+        default=6e-5,
+        metadata={
+            "help": "The control strength of COFT. The freedom of rotation. Only has an effect if `coft` is set to True."
+        },
+    )
+    block_share: bool = field(
+        default=False,
+        metadata={"help": "Whether to share the OFT parameters between blocks or not."},
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.OFT
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
+        if self.r == 0 and self.oft_block_size == 0:
+            raise ValueError(
+                f"Either `r` or `oft_block_size` must be non-zero. Currently, r = {self.r} and oft_block_size = {self.oft_block_size}."
+            )
+        if not (self.r != 0) ^ (self.oft_block_size != 0):
+            raise ValueError(
+                f"You can only specify either r ({self.r}) or oft_block_size ({self.oft_block_size}), but not both simultaneously, because r x oft_block_size == in_features."
+            )
+
+    @classmethod
+    def check_kwargs(cls, **kwargs):
+        r"""
+        Check if the kwargs are valid for the configuration.
+
+        Args:
+            kwargs (additional keyword arguments, *optional*):
+                Additional keyword arguments passed along to the child class initialization.
+        """
+        if "oft_block_size" not in kwargs:
+            raise ValueError(
+                "OFT has been updated since PEFT 0.14.0. Your trained adapter weights are incompatible "
+                "with the latest version of OFT. Please retrain your adapter weights with newer PEFT versions. "
+                "Alternatively, downgrade PEFT to version 0.13.0 to use the old adapter weights."
+            )
+        return super().check_kwargs(**kwargs)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d58a8c023532e7a59304711c017065a4d757cac
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/layer.py
@@ -0,0 +1,747 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import math
+import warnings
+from typing import Any, Optional, Union
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+
+class MultiplicativeDropoutLayer(nn.Module):
+    """
+    Implements the multiplicative dropout layer for OFT.
+    """
+
+    def __init__(self, p=0.0):
+        """
+        Initializes the multiplicative dropout layer.
+
+        Parameters:
+        p (float): The probability of dropping out a block. Defaults to 0.0.
+        """
+        super().__init__()
+        self.p = p
+
+    def forward(self, x):
+        """
+        Applies multiplicative dropout to the input tensor.
+
+        Parameters:
+        x (Tensor): The input tensor of shape (D, H, H), where `D` represents
+                    the number of OFT blocks, and `H` is the size of the square blocks along the last two dimensions,
+                    the block size in OFT.
+        """
+        if self.training:
+            # Ensure the last two dimensions are the same
+            if x.shape[-1] != x.shape[-2]:
+                raise ValueError("The last two dimensions of input should be the same!")
+
+            D, H, _ = x.shape
+
+            # If block share, skip the multiplicative dropout
+            if D == 1:
+                return x
+
+            num_to_replace = int(self.p * D)
+            num_zeros = D - num_to_replace
+            mask = torch.cat([torch.ones(num_to_replace, device=x.device), torch.zeros(num_zeros, device=x.device)])
+            mask = mask[torch.randperm(D)].view(D, 1, 1)
+            eye_matrix = torch.eye(H, device=x.device).repeat(D, 1, 1)
+            x = (1 - mask) * x + mask * eye_matrix
+        return x
+
+
+class OFTLayer(BaseTunerLayer):
+    """
+    Implements the OFT layer.
+    """
+
+    # All names of layers that may contain adapter weights
+    adapter_layer_names = ("oft_r", "oft_s")
+    # other_param_names is defined on parent class
+    other_param_names = ("r", "oft_block_size", "oft_dropout")
+
+    def __init__(self, base_layer: nn.Module, **kwargs) -> None:
+        """
+        Initializes the OFT layer.
+
+        Note, currently only support linear layer and convolutional layer, with further support for other layers to be
+        added soon.
+
+        Parameters:
+        base_layer: the pretrained model layer
+        """
+        self.base_layer = base_layer
+        # OFT info
+        self.oft_r = nn.ParameterDict({})
+        self.oft_s = nn.ParameterDict({})
+        self.r = {}
+        self.oft_block_size = {}
+        self.oft_dropout = nn.ModuleDict({})
+        self.coft = {}
+        self.eps = {}
+        self.block_share = {}
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+        self.kwargs = kwargs
+
+        base_layer = self.get_base_layer()
+
+        if isinstance(base_layer, nn.Linear):
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, nn.Conv2d):
+            in_features, out_features = base_layer.in_channels, base_layer.out_channels
+        else:
+            raise ValueError(f"Unsupported layer type {type(base_layer)}")
+
+        self.in_features = in_features
+        self.out_features = out_features
+
+    @property
+    def _available_adapters(self) -> set[str]:
+        return {*self.oft_r}
+
+    def set_scale(self, adapter, scale):
+        if adapter not in self.scaling:
+            # Ignore the case where the adapter is not in the layer
+            return
+
+        warnings.warn("Scaling operation for OFT not supported! Automatically set scale to 1.")
+
+    def scale_layer(self, scale: float) -> None:
+        if scale == 1:
+            return
+
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.oft_r.keys():
+                continue
+
+            warnings.warn("Scaling operation for OFT not supported! Automatically set scale to 1.")
+
+    def unscale_layer(self, scale=None) -> None:
+        for active_adapter in self.active_adapters:
+            if active_adapter not in self.oft_r.keys():
+                continue
+
+            warnings.warn("Unscaling operation for OFT not supported! Keeping scale to 1.")
+
+    def update_layer(self, adapter_name, r, oft_block_size, module_dropout, coft, eps, block_share, init_weights):
+        """
+        Update the linear layer with trainable OFT weights. Override for other layer types.
+        """
+        """Internal function to create oft adapter
+
+        Args:
+            adapter_name (`str`): Name for the adapter to add.
+            r (`int`): Rank for the added adapter.
+            oft_block_size (`int`): The block size for added adapter.
+            module_dropout (`float`):
+                The multiplicative dropout probability for disabling adapter blocks during training.
+            coft (`bool`): Whether to use the constrained variant of OFT or not.
+            eps (`float`):
+                The control strength of COFT. The freedom of rotation. Only has an effect if `coft` is set to True.
+            block_share (`bool`): Whether to share the OFT parameters between blocks or not.
+            init_weights (`bool`): Whether to initialize weights.
+        """
+        # Initialize the MultiplicativeDropoutLayer for module_dropout > 0.0.
+        if module_dropout > 0.0:
+            oft_dropout_layer = MultiplicativeDropoutLayer(p=module_dropout)
+        else:
+            oft_dropout_layer = nn.Identity()
+        self.oft_dropout.update(nn.ModuleDict({adapter_name: oft_dropout_layer}))
+
+        if r == 0 and oft_block_size != 0:
+            if self.in_features % oft_block_size != 0 or oft_block_size > self.in_features:
+                old_oft_block_size = oft_block_size
+                oft_block_size = self.adjust_oft_parameters(self.in_features, oft_block_size)
+                warnings.warn(
+                    f"Invalid `oft_block_size` ({old_oft_block_size})! Adjusted `oft_block_size` to ({oft_block_size})."
+                )
+            r = int(self.in_features // oft_block_size)
+        elif r != 0 and oft_block_size == 0:
+            if self.in_features % r != 0 or r > self.in_features:
+                old_r = r
+                r = self.adjust_oft_parameters(self.in_features, r)
+                warnings.warn(f"Invalid `r` ({old_r})! Adjusted `r` to ({r}).")
+            oft_block_size = int(self.in_features // r)
+        else:
+            raise ValueError(
+                "Something went wrong, please report this error: https://github.com/huggingface/peft/issues"
+            )
+
+        self.coft[adapter_name] = coft
+        self.block_share[adapter_name] = block_share
+        self.eps[adapter_name] = eps * math.ceil(self.out_features / r) * math.ceil(self.out_features / r)
+
+        # Create weights with provided shape
+        if block_share:
+            self.oft_r[adapter_name] = nn.Parameter(
+                torch.empty(1, math.ceil(self.in_features / r), math.ceil(self.in_features / r))
+            )
+        else:
+            self.oft_r[adapter_name] = nn.Parameter(
+                torch.empty(r, math.ceil(self.in_features / r), math.ceil(self.in_features / r))
+            )
+        self.oft_s[adapter_name] = nn.Parameter(torch.empty(int(self.out_features), 1))
+
+        # Initialize weights
+        self.reset_oft_parameters(adapter_name, init_weights)
+
+        # set oft r and block size
+        self.r[adapter_name] = r
+        self.oft_block_size[adapter_name] = oft_block_size
+
+        # Move new weights to device
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_oft_parameters(self, adapter_name, init_weights):
+        """
+        Reset the OFT parameters.
+        """
+        if init_weights is False:
+            nn.init.normal_(self.oft_r[adapter_name], mean=0.0, std=0.1)
+            nn.init.normal_(self.oft_s[adapter_name], mean=1.0, std=0.1)
+            return
+
+        if adapter_name in self.oft_r.keys():
+            if init_weights is True:
+                # initialize oft_r to zero
+                nn.init.zeros_(self.oft_r[adapter_name])
+                nn.init.ones_(self.oft_s[adapter_name])
+            else:
+                raise ValueError(f"Unknown initialization {init_weights=}")
+
+    def _cayley_batch(self, data: torch.Tensor) -> torch.Tensor:
+        """
+        Perform the Cayley parametrization on a batch of skew-symmetric matrices.
+
+        Args:
+            data: A batch of skew-symmetric matrices of shape (b, r, c).
+        """
+        b, r, c = data.shape
+        # Ensure the input matrix is skew-symmetric
+        skew_mat = 0.5 * (data - data.transpose(1, 2))
+        id_mat = torch.eye(r, device=data.device).unsqueeze(0).expand(b, r, c)  # noqa: E741
+
+        # Perform the Cayley parametrization
+        Q = torch.linalg.solve(id_mat + skew_mat, id_mat - skew_mat, left=False)
+
+        return Q
+
+    # Copied from https://github.com/Zeju1997/oft/blob/84cebb965df69781e3d9c3c875f5980b421eaf24/oft-control/oft.py#L155
+    def _block_diagonal(self, oft_r: torch.Tensor, rank: int) -> torch.Tensor:
+        if oft_r.shape[0] == 1:
+            # block share
+            blocks = [oft_r[0, ...] for i in range(rank)]
+        else:
+            blocks = [oft_r[i, ...] for i in range(rank)]
+
+        # Use torch.block_diag to create the block diagonal matrix
+        A = torch.block_diag(*blocks)
+
+        return A
+
+    # Copied from https://github.com/Zeju1997/oft/blob/84cebb965df69781e3d9c3c875f5980b421eaf24/oft-control/oft.py#L52
+    def _project_batch(self, oft_r, eps=1e-5):
+        # scaling factor for each of the smaller block matrix
+        eps = eps * 1 / torch.sqrt(torch.tensor(oft_r.shape[0]))
+        I = (  # noqa: E741
+            torch.zeros((oft_r.size(1), oft_r.size(1)), device=oft_r.device, dtype=oft_r.dtype)
+            .unsqueeze(0)
+            .expand_as(oft_r)
+        )
+        diff = oft_r - I
+        norm_diff = torch.norm(oft_r - I, dim=(1, 2), keepdim=True)
+        mask = (norm_diff <= eps).bool()
+        out = torch.where(mask, oft_r, I + eps * (diff / norm_diff))
+        return out
+
+    def adjust_oft_parameters(self, in_features, params):
+        """
+        Adjust the OFT parameters to be divisible by the in_features dimension.
+        """
+        if params < in_features:
+            higher_params = params
+            while higher_params <= in_features and in_features % higher_params != 0:
+                higher_params += 1
+        else:
+            return in_features
+
+        lower_params = params
+        while lower_params > 1 and in_features % lower_params != 0:
+            lower_params -= 1
+
+        if (params - lower_params) <= (higher_params - params):
+            return lower_params
+        else:
+            return higher_params
+
+
+class Linear(nn.Module, OFTLayer):
+    """OFT implemented in Linear layer"""
+
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        r: int = 8,
+        oft_block_size: int = 0,
+        module_dropout: float = 0.0,
+        coft: bool = False,
+        eps: float = 6e-5,
+        block_share: bool = False,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        init_weights: Union[bool, str] = True,
+        is_target_conv_1d_layer: bool = False,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        OFTLayer.__init__(self, base_layer, **kwargs)
+        self.fan_in_fan_out = fan_in_fan_out
+
+        self._active_adapter = adapter_name
+
+        self.update_layer(adapter_name, r, oft_block_size, module_dropout, coft, eps, block_share, init_weights)
+        self.is_target_conv_1d_layer = is_target_conv_1d_layer
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If `True`, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If `None`, all active adapters will be merged.
+                Defaults to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self._available_adapters:
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data
+                    oft_mat, oft_s = self.get_delta_weight(active_adapter)
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = torch.mm(oft_mat, orig_weights)
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = orig_weights * oft_s
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights.contiguous()
+                else:
+                    oft_mat, oft_s = self.get_delta_weight(active_adapter)
+                    orig_weights = base_layer.weight.data
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = torch.mm(oft_mat, orig_weights)
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = orig_weights * oft_s
+
+                    base_layer.weight.data = orig_weights.contiguous()
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.oft_r.keys():
+                oft_mat, oft_s = self.get_delta_weight(active_adapter)
+
+                orig_weights = self.get_base_layer().weight.data
+                orig_weights = torch.transpose(orig_weights, 0, 1)
+                orig_weights = torch.mm(oft_mat.t(), orig_weights)
+                orig_weights = torch.transpose(orig_weights, 0, 1)
+
+                self.get_base_layer().weight.data = orig_weights * (1 / oft_s)
+
+    def get_delta_weight(self, adapter_name) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        oft_r = self.oft_r[adapter_name]
+        oft_s = self.oft_s[adapter_name]
+
+        rank = self.r[adapter_name]
+        coft = self.coft[adapter_name]
+        eps = self.eps[adapter_name]
+
+        if coft:
+            with torch.no_grad():
+                oft_r.copy_(self._project_batch(oft_r, eps=eps))
+
+        orth_rotate = self._cayley_batch(oft_r)
+        weight = self._block_diagonal(orth_rotate, rank)
+
+        return weight, oft_s
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            oft_rotation = torch.eye(self.in_features, device=x.device, dtype=previous_dtype)
+            oft_scale = torch.ones((int(self.out_features), 1), device=x.device, dtype=previous_dtype)
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.oft_r.keys():
+                    continue
+                oft_r = self.oft_r[active_adapter]
+                oft_s = self.oft_s[active_adapter]
+                dropout = self.oft_dropout[active_adapter]
+
+                rank = self.r[active_adapter]
+                coft = self.coft[active_adapter]
+                eps = self.eps[active_adapter]
+
+                if coft:
+                    with torch.no_grad():
+                        oft_r.copy_(self._project_batch(oft_r, eps=eps))
+
+                orth_rotate = self._cayley_batch(oft_r)
+                orth_rotate = dropout(orth_rotate)
+                oft_mat = self._block_diagonal(orth_rotate, rank)
+
+                oft_rotation = oft_mat @ oft_rotation
+                oft_scale = oft_s * oft_scale
+
+            x = x.to(self.get_base_layer().weight.data.dtype)
+
+            orig_weight = self.get_base_layer().weight.data
+            orig_weight = torch.transpose(orig_weight, 0, 1)
+            oft_rotation = oft_rotation.to(previous_dtype)
+            orig_weight = orig_weight.to(previous_dtype)
+            rotated_weight = torch.mm(oft_rotation, orig_weight)
+            rotated_weight = torch.transpose(rotated_weight, 0, 1)
+
+            scaled_rotated_weight = rotated_weight * oft_scale
+
+            scaled_rotated_weight = scaled_rotated_weight.to(previous_dtype)
+            bias = self.get_base_layer().bias.to(previous_dtype) if self.get_base_layer().bias is not None else None
+            result = F.linear(input=x, weight=scaled_rotated_weight, bias=bias)
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "oft." + rep
+
+
+class Conv2d(nn.Module, OFTLayer):
+    """OFT implemented in Conv2d layer"""
+
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        r: int = 8,
+        oft_block_size: int = 0,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        module_dropout: float = 0.0,
+        coft: bool = False,
+        eps: float = 6e-5,
+        block_share: bool = False,
+        init_weights: Union[bool, str] = True,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        OFTLayer.__init__(self, base_layer)
+        self.fan_in_fan_out = fan_in_fan_out
+
+        self._active_adapter = adapter_name
+
+        # Create adapter and set it active
+        self.update_layer(adapter_name, r, oft_block_size, module_dropout, coft, eps, block_share, init_weights)
+
+    def update_layer(self, adapter_name, r, oft_block_size, module_dropout, coft, eps, block_share, init_weights):
+        """
+        Update the conv2d layer with trainable OFT weights.
+        """
+        # Initialize the MultiplicativeDropoutLayer for module_dropout > 0.0.
+        if module_dropout > 0.0:
+            oft_dropout_layer = MultiplicativeDropoutLayer(p=module_dropout)
+        else:
+            oft_dropout_layer = nn.Identity()
+        self.oft_dropout.update(nn.ModuleDict({adapter_name: oft_dropout_layer}))
+
+        # layer information from the base layer
+        base_layer = self.get_base_layer()
+        conv_filter_dim = self.in_features * base_layer.kernel_size[0] * base_layer.kernel_size[0]
+
+        if r == 0 and oft_block_size != 0:
+            if conv_filter_dim % oft_block_size != 0 or oft_block_size > conv_filter_dim:
+                old_oft_block_size = oft_block_size
+                oft_block_size = self.adjust_oft_parameters(conv_filter_dim, oft_block_size)
+                warnings.warn(
+                    f"Invalid `oft_block_size` ({old_oft_block_size})! Adjusted `oft_block_size` to ({oft_block_size})."
+                )
+            r = int(conv_filter_dim // oft_block_size)
+        elif r != 0 and oft_block_size == 0:
+            if conv_filter_dim % r != 0 or r > conv_filter_dim:
+                old_r = r
+                r = self.adjust_oft_parameters(conv_filter_dim, r)
+                warnings.warn(f"Invalid `r` ({old_r})! Adjusted `r` to ({r}).")
+            oft_block_size = int(conv_filter_dim // r)
+        else:
+            raise ValueError(
+                "Something went wrong, please report this error: https://github.com/huggingface/peft/issues"
+            )
+
+        self.coft[adapter_name] = coft
+        self.block_share[adapter_name] = block_share
+        self.eps[adapter_name] = eps * math.ceil(self.out_features / r) * math.ceil(self.out_features / r)
+
+        # Create weights with provided shape
+        if block_share:
+            self.oft_r[adapter_name] = nn.Parameter(
+                torch.empty(1, math.ceil(conv_filter_dim / r), math.ceil(conv_filter_dim / r))
+            )
+        else:
+            self.oft_r[adapter_name] = nn.Parameter(
+                torch.empty(r, math.ceil(conv_filter_dim / r), math.ceil(conv_filter_dim / r))
+            )
+        self.oft_s[adapter_name] = nn.Parameter(torch.empty(int(self.out_features), 1))
+
+        # Initialize weights
+        self.reset_oft_parameters(adapter_name, init_weights)
+
+        # set oft r and block size
+        self.r[adapter_name] = r
+        self.oft_block_size[adapter_name] = oft_block_size
+
+        # Move new weights to device
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.oft_r.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    oft_mat, oft_s = self.get_delta_weight(active_adapter)
+
+                    orig_weights = orig_weights.view(
+                        self.out_features, self.in_features * base_layer.kernel_size[0] * base_layer.kernel_size[0]
+                    )
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = torch.mm(oft_mat, orig_weights)
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = orig_weights * oft_s
+                    orig_weights = orig_weights.view(
+                        self.out_features, self.in_features, base_layer.kernel_size[0], base_layer.kernel_size[0]
+                    )
+
+                    base_layer.weight.data = orig_weights.contiguous()
+                else:
+                    oft_mat, oft_s = self.get_delta_weight(active_adapter)
+
+                    orig_weights = base_layer.weight.data.clone()
+                    orig_weights = orig_weights.view(
+                        self.out_features, self.in_features * base_layer.kernel_size[0] * base_layer.kernel_size[0]
+                    )
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = torch.mm(oft_mat, orig_weights)
+                    orig_weights = torch.transpose(orig_weights, 0, 1)
+                    orig_weights = orig_weights * oft_s
+                    orig_weights = orig_weights.view(
+                        self.out_features, self.in_features, base_layer.kernel_size[0], base_layer.kernel_size[0]
+                    )
+
+                    base_layer.weight.data = orig_weights.contiguous()
+
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        """
+        This method unmerges all merged adapter layers from the base weights.
+        """
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.oft_r.keys():
+                oft_mat, oft_s = self.get_delta_weight(active_adapter)
+
+                orig_weights = self.get_base_layer().weight.data.clone()
+                orig_weights = orig_weights.view(
+                    self.out_features,
+                    self.in_features * self.get_base_layer().kernel_size[0] * self.get_base_layer().kernel_size[0],
+                )
+                orig_weights = torch.transpose(orig_weights, 0, 1)
+                orig_weights = torch.mm(oft_mat.t(), orig_weights)
+                orig_weights = torch.transpose(orig_weights, 0, 1)
+                orig_weights = orig_weights * (1 / oft_s)
+                orig_weights = orig_weights.view(
+                    self.out_features,
+                    self.in_features,
+                    self.get_base_layer().kernel_size[0],
+                    self.get_base_layer().kernel_size[0],
+                )
+
+                self.get_base_layer().weight.data = orig_weights
+
+    def get_delta_weight(self, adapter_name) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        oft_r = self.oft_r[adapter_name]
+        oft_s = self.oft_s[adapter_name]
+
+        rank = self.r[adapter_name]
+        coft = self.coft[adapter_name]
+        eps = self.eps[adapter_name]
+
+        if coft:
+            with torch.no_grad():
+                oft_r.copy_(self._project_batch(oft_r, eps=eps))
+
+        orth_rotate = self._cayley_batch(oft_r)
+        weight = self._block_diagonal(orth_rotate, rank)
+
+        return weight, oft_s
+
+    def forward(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            oft_rotation = torch.eye(
+                self.in_features * self.get_base_layer().kernel_size[0] * self.get_base_layer().kernel_size[0],
+                device=x.device,
+                dtype=previous_dtype,
+            )
+            oft_scale = torch.ones((int(self.out_features), 1), device=x.device, dtype=previous_dtype)
+
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.oft_r.keys():
+                    continue
+                oft_r = self.oft_r[active_adapter]
+                oft_s = self.oft_s[active_adapter]
+                dropout = self.oft_dropout[active_adapter]
+
+                rank = self.r[active_adapter]
+                coft = self.coft[active_adapter]
+                eps = self.eps[active_adapter]
+
+                if coft:
+                    with torch.no_grad():
+                        oft_r.copy_(self._project_batch(oft_r, eps=eps))
+
+                orth_rotate = self._cayley_batch(oft_r)
+                orth_rotate = dropout(orth_rotate)
+                oft_mat = self._block_diagonal(orth_rotate, rank)
+
+                oft_rotation = oft_mat @ oft_rotation
+                oft_scale = oft_s * oft_scale
+
+            x = x.to(self.get_base_layer().weight.data.dtype)
+
+            orig_weights = self.base_layer.weight.data
+            orig_weights = orig_weights.view(
+                self.out_features,
+                self.in_features * self.get_base_layer().kernel_size[0] * self.get_base_layer().kernel_size[0],
+            )
+            orig_weights = torch.transpose(orig_weights, 0, 1)
+            oft_rotation = oft_rotation.to(previous_dtype)
+            orig_weights = orig_weights.to(previous_dtype)
+            rotated_weight = torch.mm(oft_rotation, orig_weights)
+            rotated_weight = torch.transpose(rotated_weight, 0, 1)
+
+            scaled_rotated_weight = rotated_weight * oft_scale
+
+            scaled_rotated_weight = scaled_rotated_weight.view(
+                self.out_features,
+                self.in_features,
+                self.get_base_layer().kernel_size[0],
+                self.get_base_layer().kernel_size[0],
+            )
+            result = F.conv2d(
+                input=x,
+                weight=scaled_rotated_weight,
+                bias=self.get_base_layer().bias,
+                padding=self.get_base_layer().padding[0],
+                stride=self.get_base_layer().stride[0],
+            )
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "oft." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..e44ced3b13b81b0021e480aa386360f924f55c3c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/oft/model.py
@@ -0,0 +1,374 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from dataclasses import asdict
+from enum import Enum
+from typing import List, Optional
+
+import torch
+from torch import nn
+from tqdm import tqdm
+
+from peft.tuners.tuners_utils import (
+    BaseTuner,
+    BaseTunerLayer,
+    check_target_module_exists,
+    onload_layer,
+)
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    _get_submodules,
+)
+
+from .config import OFTConfig
+from .layer import Conv2d, Linear, OFTLayer
+
+
+class OFTModel(BaseTuner):
+    """
+    Creates Orthogonal Finetuning model from a pretrained model. The method is described in
+    https://arxiv.org/abs/2306.07280
+
+    Args:
+        model (`torch.nn.Module`): The model to which the adapter tuner layers will be attached.
+        config ([`OFTConfig`]): The configuration of the OFT model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The OFT model.
+
+    Example:
+        ```py
+        >>> from diffusers import StableDiffusionPipeline
+        >>> from peft import OFTModel, OFTConfig
+
+        >>> config_te = OFTConfig(
+        ...     r=8,
+        ...     target_modules=["k_proj", "q_proj", "v_proj", "out_proj", "fc1", "fc2"],
+        ...     module_dropout=0.0,
+        ...     init_weights=True,
+        ... )
+        >>> config_unet = OFTConfig(
+        ...     r=8,
+        ...     target_modules=[
+        ...         "proj_in",
+        ...         "proj_out",
+        ...         "to_k",
+        ...         "to_q",
+        ...         "to_v",
+        ...         "to_out.0",
+        ...         "ff.net.0.proj",
+        ...         "ff.net.2",
+        ...     ],
+        ...     module_dropout=0.0,
+        ...     init_weights=True,
+        ... )
+
+        >>> model = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+        >>> model.text_encoder = OFTModel(model.text_encoder, config_te, "default")
+        >>> model.unet = OFTModel(model.unet, config_unet, "default")
+        ```
+
+    **Attributes**:
+        - **model** ([`~torch.nn.Module`]) -- The model to be adapted.
+        - **peft_config** ([`OFTConfig`]): The configuration of the OFT model.
+    """
+
+    prefix: str = "oft_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False) -> None:
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def _check_new_adapter_config(self, config: OFTConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(oft_config, key):
+        return check_target_module_exists(oft_config, key)
+
+    def _create_and_replace(
+        self,
+        oft_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+        **optional_kwargs,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+
+        bias = hasattr(target, "bias") and target.bias is not None
+        kwargs = {
+            "r": oft_config.r,
+            "oft_block_size": oft_config.oft_block_size,
+            "module_dropout": oft_config.module_dropout,
+            "coft": oft_config.coft,
+            "eps": oft_config.eps,
+            "block_share": oft_config.block_share,
+            "fan_in_fan_out": oft_config.fan_in_fan_out,
+            "init_weights": oft_config.init_weights,
+        }
+        kwargs["bias"] = bias
+
+        # If it is not a OFTLayer, create a new module, else update it with new adapters
+        if not isinstance(target, OFTLayer):
+            new_module = self._create_new_module(oft_config, adapter_name, target, **kwargs)
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+        else:
+            target.update_layer(
+                adapter_name,
+                r=oft_config.r,
+                oft_block_size=oft_config.oft_block_size,
+                module_dropout=oft_config.module_dropout,
+                coft=oft_config.coft,
+                eps=oft_config.eps,
+                block_share=oft_config.block_share,
+                init_weights=oft_config.init_weights,
+            )
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if self.prefix in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "oft_only":
+                for name, m in model.named_modules():
+                    if isinstance(m, OFTLayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(oft_config, adapter_name, target, **kwargs):
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Linear):
+            if kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                    "Setting fan_in_fan_out to False."
+                )
+                kwargs["fan_in_fan_out"] = oft_config.fan_in_fan_out = False
+            new_module = Linear(target, adapter_name, **kwargs)
+        elif isinstance(target_base_layer, torch.nn.Conv2d):
+            new_module = Conv2d(target, adapter_name, **kwargs)
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. "
+                "Currently, only `torch.nn.Linear` and `torch.nn.Conv2d` are supported."
+            )
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self):
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self):
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name):
+        for module in self.model.modules():
+            if isinstance(module, OFTLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[List[str]] = None,
+    ):
+        if merge:
+            self._check_merge_allowed()
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+            with onload_layer(target):
+                if hasattr(target, "base_layer"):
+                    if merge:
+                        target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                    self._replace_module(parent, target_name, target.get_base_layer(), target)
+                elif isinstance(target, ModulesToSaveWrapper):
+                    # save any additional trainable modules part of `modules_to_save`
+                    new_module = target.modules_to_save[target.active_adapter]
+                    if hasattr(new_module, "base_layer"):
+                        # check if the module is itself a tuner layer
+                        if merge:
+                            new_module.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                        new_module = new_module.get_base_layer()
+                    setattr(parent, target_name, new_module)
+
+        return self.model
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, OFTLayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapters[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[List[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the OFT layers into the base model. This is needed if someone wants to use the base model as
+        a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the oft modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9195c0d75d3d11e752d0477b64edd79599bdaa01
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/__init__.py
@@ -0,0 +1,23 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import PromptEncoderConfig, PromptEncoderReparameterizationType
+from .model import PromptEncoder
+
+
+__all__ = ["PromptEncoder", "PromptEncoderConfig", "PromptEncoderReparameterizationType"]
+
+register_peft_method(name="p_tuning", config_cls=PromptEncoderConfig, model_cls=PromptEncoder)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..a69c13db9c8a0f57a7daa7d312472625251fb6c8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/config.py
@@ -0,0 +1,60 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import enum
+from dataclasses import dataclass, field
+from typing import Union
+
+from peft.config import PromptLearningConfig
+from peft.utils import PeftType
+
+
+class PromptEncoderReparameterizationType(str, enum.Enum):
+    MLP = "MLP"
+    LSTM = "LSTM"
+
+
+@dataclass
+class PromptEncoderConfig(PromptLearningConfig):
+    """
+    This is the configuration class to store the configuration of a [`PromptEncoder`].
+
+    Args:
+        encoder_reparameterization_type (Union[[`PromptEncoderReparameterizationType`], `str`]):
+            The type of reparameterization to use.
+        encoder_hidden_size (`int`): The hidden size of the prompt encoder.
+        encoder_num_layers (`int`): The number of layers of the prompt encoder.
+        encoder_dropout (`float`): The dropout probability of the prompt encoder.
+    """
+
+    encoder_reparameterization_type: Union[str, PromptEncoderReparameterizationType] = field(
+        default=PromptEncoderReparameterizationType.MLP,
+        metadata={"help": "How to reparameterize the prompt encoder"},
+    )
+    encoder_hidden_size: int = field(
+        default=None,
+        metadata={"help": "The hidden size of the prompt encoder"},
+    )
+    encoder_num_layers: int = field(
+        default=2,
+        metadata={"help": "The number of layers of the prompt encoder"},
+    )
+    encoder_dropout: float = field(
+        default=0.0,
+        metadata={"help": "The dropout of the prompt encoder"},
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.P_TUNING
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..ade2b1128158376c134441687803b85d444cfb96
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/p_tuning/model.py
@@ -0,0 +1,130 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Based on https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/nlp/modules/common/prompt_encoder.py
+# with some refactor
+import warnings
+
+import torch
+
+from .config import PromptEncoderConfig, PromptEncoderReparameterizationType
+
+
+class PromptEncoder(torch.nn.Module):
+    """
+    The prompt encoder network that is used to generate the virtual token embeddings for p-tuning.
+
+    Args:
+        config ([`PromptEncoderConfig`]): The configuration of the prompt encoder.
+
+    Example:
+
+    ```py
+    >>> from peft import PromptEncoder, PromptEncoderConfig
+
+    >>> config = PromptEncoderConfig(
+    ...     peft_type="P_TUNING",
+    ...     task_type="SEQ_2_SEQ_LM",
+    ...     num_virtual_tokens=20,
+    ...     token_dim=768,
+    ...     num_transformer_submodules=1,
+    ...     num_attention_heads=12,
+    ...     num_layers=12,
+    ...     encoder_reparameterization_type="MLP",
+    ...     encoder_hidden_size=768,
+    ... )
+
+    >>> prompt_encoder = PromptEncoder(config)
+    ```
+
+    **Attributes**:
+        - **embedding** (`torch.nn.Embedding`) -- The embedding layer of the prompt encoder.
+        - **mlp_head** (`torch.nn.Sequential`) -- The MLP head of the prompt encoder if `inference_mode=False`.
+        - **lstm_head** (`torch.nn.LSTM`) -- The LSTM head of the prompt encoder if `inference_mode=False` and
+        `encoder_reparameterization_type="LSTM"`.
+        - **token_dim** (`int`) -- The hidden embedding dimension of the base transformer model.
+        - **input_size** (`int`) -- The input size of the prompt encoder.
+        - **output_size** (`int`) -- The output size of the prompt encoder.
+        - **hidden_size** (`int`) -- The hidden size of the prompt encoder.
+        - **total_virtual_tokens** (`int`): The total number of virtual tokens of the
+        prompt encoder.
+        - **encoder_type** (Union[[`PromptEncoderReparameterizationType`], `str`]): The encoder type of the prompt
+          encoder.
+
+
+    Input shape: (`batch_size`, `total_virtual_tokens`)
+
+    Output shape: (`batch_size`, `total_virtual_tokens`, `token_dim`)
+    """
+
+    def __init__(self, config):
+        super().__init__()
+        self.token_dim = config.token_dim
+        self.input_size = self.token_dim
+        self.output_size = self.token_dim
+        self.hidden_size = config.encoder_hidden_size
+        self.total_virtual_tokens = config.num_virtual_tokens * config.num_transformer_submodules
+        self.encoder_type = config.encoder_reparameterization_type
+
+        # embedding
+        self.embedding = torch.nn.Embedding(self.total_virtual_tokens, self.token_dim)
+        if not config.inference_mode:
+            if self.encoder_type == PromptEncoderReparameterizationType.LSTM:
+                lstm_dropout = config.encoder_dropout
+                num_layers = config.encoder_num_layers
+                # LSTM
+                self.lstm_head = torch.nn.LSTM(
+                    input_size=self.input_size,
+                    hidden_size=self.hidden_size,
+                    num_layers=num_layers,
+                    dropout=lstm_dropout,
+                    bidirectional=True,
+                    batch_first=True,
+                )
+
+                self.mlp_head = torch.nn.Sequential(
+                    torch.nn.Linear(self.hidden_size * 2, self.hidden_size * 2),
+                    torch.nn.ReLU(),
+                    torch.nn.Linear(self.hidden_size * 2, self.output_size),
+                )
+
+            elif self.encoder_type == PromptEncoderReparameterizationType.MLP:
+                encoder_num_layers_default = PromptEncoderConfig.encoder_num_layers
+                if config.encoder_num_layers != encoder_num_layers_default:
+                    warnings.warn(
+                        f"for {self.encoder_type.value}, the argument `encoder_num_layers` is ignored. "
+                        f"Exactly {encoder_num_layers_default} MLP layers are used."
+                    )
+                layers = [
+                    torch.nn.Linear(self.input_size, self.hidden_size),
+                    torch.nn.ReLU(),
+                    torch.nn.Linear(self.hidden_size, self.hidden_size),
+                    torch.nn.ReLU(),
+                    torch.nn.Linear(self.hidden_size, self.output_size),
+                ]
+                self.mlp_head = torch.nn.Sequential(*layers)
+
+            else:
+                raise ValueError("Prompt encoder type not recognized. Please use one of MLP (recommended) or LSTM.")
+
+    def forward(self, indices):
+        input_embeds = self.embedding(indices)
+        if self.encoder_type == PromptEncoderReparameterizationType.LSTM:
+            output_embeds = self.mlp_head(self.lstm_head(input_embeds)[0])
+        elif self.encoder_type == PromptEncoderReparameterizationType.MLP:
+            output_embeds = self.mlp_head(input_embeds)
+        else:
+            raise ValueError("Prompt encoder type not recognized. Please use one of MLP (recommended) or LSTM.")
+
+        return output_embeds
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..1c18933eba3fa44106ba9fa89ba34ecd12a2bed4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import PolyConfig
+from .layer import Linear, PolyLayer
+from .model import PolyModel
+
+
+__all__ = ["Linear", "PolyConfig", "PolyLayer", "PolyModel"]
+
+register_peft_method(name="poly", config_cls=PolyConfig, model_cls=PolyModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..040c1647a005fa59bc2046640dacdd4783aa11fe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/config.py
@@ -0,0 +1,103 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Literal, Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class PolyConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`PolyModel`].
+        - [Polytropon (Poly)](https://arxiv.org/abs/2202.13914)
+        - [Multi-Head Routing (MHR)](https://arxiv.org/abs/2211.03831)
+
+    Args:
+        r (`int`): Attention dimension of each Lora in Poly.
+        target_modules (`Union[List[str],str]`): The names of the modules to apply Poly to.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        modules_to_save (`List[str]`): List of modules apart from Poly layers to be set as trainable
+            and saved in the final checkpoint.
+        init_weights (bool): Whether to perform initialization of Poly weights.
+        poly_type (`Literal["poly"]`): The variant of the Poly module to use. Currently, only "poly"
+            is supported.
+        n_tasks (`int`): The number of tasks in a multitasking scenario.
+        n_skills (`int`): The number of skills (LoRA) in each Poly layer.
+        n_splits (`int`): The number of splits within each LoRA of a Poly layer. A value greater
+            than 1 indicates the use of Multi-Head Routing (MHR).
+    """
+
+    r: int = field(default=8, metadata={"help": "Lora attention dimension"})
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "List of module names or regex expression of the module names to replace with Poly."
+            "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$' "
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from Poly."},
+    )
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": "List of modules apart from Poly layers to be set as trainable and saved in the final checkpoint. "
+            "For example, in Sequence Classification or Token Classification tasks, "
+            "the final layer `classifier/score` are randomly initialized and as such need to be trainable and saved."
+        },
+    )
+    init_weights: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the Poly layers with their default initialization. Don't change "
+                "this setting, except if you know exactly what you're doing."
+            ),
+        },
+    )
+    poly_type: Literal["poly"] = field(
+        default="poly",
+        metadata={"help": 'Type of Poly modules to be used. Currently only "poly" is supported.'},
+    )
+    n_tasks: int = field(
+        default=1,
+        metadata={"help": "Number of tasks in multitasking scenario."},
+    )
+    n_skills: int = field(
+        default=4,
+        metadata={"help": "Number of skills (LoRA) in each Poly layer."},
+    )
+    n_splits: int = field(
+        default=1,
+        metadata={"help": "Number of splits within each LoRA of a Poly layer."},
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.POLY
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..5169d9ba72904898afdec7e032650c9fabbeec82
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/layer.py
@@ -0,0 +1,165 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import math
+from typing import Any
+
+import torch
+import torch.nn as nn
+
+from peft.tuners.tuners_utils import BaseTunerLayer
+
+from .config import PolyConfig
+from .router import get_router
+
+
+class PolyLayer(BaseTunerLayer):
+    # All names of layers that may contain (trainable) adapter weights
+    adapter_layer_names = ("poly_lora_A", "poly_lora_B", "poly_router")
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("r", "n_tasks", "n_skills", "n_splits")
+
+    def __init__(self, base_layer: nn.Module, **kwargs):
+        self.base_layer = base_layer
+        self.r = {}
+        self.n_tasks = {}
+        self.n_skills = {}
+        self.n_splits = {}
+        self.poly_type = {}
+        self.poly_router = nn.ModuleDict()
+        self.poly_lora_A = nn.ParameterDict()
+        self.poly_lora_B = nn.ParameterDict()
+        self.kwargs = kwargs
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        else:
+            raise ValueError(f"Unsupported layer type {type(base_layer)}")
+
+        self.in_features = in_features
+        self.out_features = out_features
+
+    def update_layer(self, adapter_name, poly_config):
+        if poly_config.r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {poly_config.r}")
+
+        self.r[adapter_name] = poly_config.r
+        self.n_tasks[adapter_name] = poly_config.n_tasks
+        self.n_skills[adapter_name] = poly_config.n_skills
+        self.n_splits[adapter_name] = poly_config.n_splits
+        self.poly_type[adapter_name] = poly_config.poly_type
+
+        self.poly_lora_A[adapter_name] = nn.Parameter(
+            torch.empty(
+                poly_config.n_splits,
+                poly_config.n_skills,
+                self.in_features // poly_config.n_splits,
+                poly_config.r,
+            )
+        )
+        self.poly_lora_B[adapter_name] = nn.Parameter(
+            torch.empty(
+                poly_config.n_splits,
+                poly_config.n_skills,
+                poly_config.r,
+                self.out_features // poly_config.n_splits,
+            )
+        )
+        self.poly_router[adapter_name] = get_router(poly_config)
+
+        self.reset_poly_parameters(adapter_name, init_weights=poly_config.init_weights)
+
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_poly_parameters(self, adapter_name, init_weights):
+        if adapter_name in self.poly_lora_A.keys():
+            # initialize A the same way as the default for nn.Linear
+            # https://github.com/microsoft/mttl/blob/ce4ca51dbca73be656feb9b3e5233633e3c5dec7/mttl/models/poly.py#L269
+            n_splits, n_skills, d, r = self.poly_lora_A[adapter_name].shape
+            for skill in range(n_skills):
+                for split in range(n_splits):
+                    param = torch.empty((r, d))
+                    torch.nn.init.kaiming_uniform_(param, a=math.sqrt(5))
+                    self.poly_lora_A[adapter_name].data[split, skill, :, :] = param.T
+
+            if init_weights:
+                # initialize B to zero
+                torch.nn.init.zeros_(self.poly_lora_B[adapter_name])
+            else:
+                # initialize B the same way as the default for nn.Linear
+                n_splits, n_skills, r, d = self.poly_lora_B[adapter_name].shape
+                for skill in range(n_skills):
+                    for split in range(n_splits):
+                        param = torch.empty((d, r))
+                        torch.nn.init.kaiming_uniform_(param, a=math.sqrt(5))
+                        self.poly_lora_B[adapter_name].data[split, skill, :, :] = param.T
+
+            # initialized router
+            self.poly_router[adapter_name].reset()
+
+
+class Linear(nn.Module, PolyLayer):
+    # Lora implemented in a dense layer
+    def __init__(
+        self,
+        base_layer,
+        adapter_name: str,
+        poly_config: PolyConfig,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+        PolyLayer.__init__(self, base_layer, **kwargs)
+
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, poly_config)
+
+    def forward(self, x: torch.Tensor, *args: Any, task_ids: torch.Tensor = None, **kwargs: Any) -> torch.Tensor:
+        previous_dtype = x.dtype
+        if self.disable_adapters:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.poly_lora_A.keys():
+                    continue
+
+                r = self.r[active_adapter]
+                poly_router = self.poly_router[active_adapter]
+                poly_lora_A = self.poly_lora_A[active_adapter]
+                poly_lora_B = self.poly_lora_B[active_adapter]
+
+                # Combine the output of LoRAs
+                # https://github.com/microsoft/mttl/blob/ce4ca51dbca73be656feb9b3e5233633e3c5dec7/mttl/models/poly.py#L293
+                mixing_weights = poly_router(task_ids=task_ids, input_ids=x)
+                bs, n_splits, n_skills = mixing_weights.size()
+
+                # A is    n_splits, n_skills, D // n_splits, rank
+                # we want bs,       n_splits, D // n_splits, rank
+                A = torch.einsum("bqs,qsdr->bqdr", (mixing_weights, poly_lora_A))
+                B = torch.einsum("bqs,qsrd->bqrd", (mixing_weights, poly_lora_B))
+
+                A = A.reshape(bs, self.in_features, r)
+                B = B.transpose(1, 2).reshape(bs, r, self.out_features)
+
+                x = x.to(A.dtype)
+                result += x.bmm(A).bmm(B) / r
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "poly." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..30313cdabbc2aaac9621ccd418fa7720db5b8ce9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/model.py
@@ -0,0 +1,189 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from contextlib import contextmanager
+from dataclasses import asdict
+from enum import Enum
+from typing import Any
+
+import torch
+from torch import nn
+
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+)
+
+from .config import PolyConfig
+from .layer import Linear, PolyLayer
+
+
+class PolyModel(BaseTuner):
+    prefix: str = "poly_"
+
+    def __init__(self, model, config, adapter_name) -> None:
+        super().__init__(model, config, adapter_name)
+
+    @staticmethod
+    def _check_target_module_exists(poly_config, key):
+        return check_target_module_exists(poly_config, key)
+
+    def _create_and_replace(
+        self,
+        poly_config: PolyConfig,
+        adapter_name: str,
+        target: nn.Module,
+        target_name: str,
+        parent: nn.Module,
+        **optional_kwargs: Any,
+    ):
+        if isinstance(target, PolyLayer):
+            target.update_layer(adapter_name, poly_config)
+        else:
+            new_module = self._create_new_module(
+                poly_config,
+                adapter_name,
+                target,
+            )
+            if adapter_name not in self.active_adapters:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if (self.prefix in name) or ("ranknum" in name):
+                weight = child.qweight if hasattr(child, "qweight") else child.weight
+                module.to(weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+    @staticmethod
+    def _create_new_module(poly_config, adapter_name, target, **kwargs):
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Linear):
+            return Linear(target, adapter_name, poly_config, **kwargs)
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. Currently, only the following modules are supported: "
+                "`torch.nn.Linear`."
+            )
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (PolyLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self):
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self):
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name):
+        for module in self.model.modules():
+            if isinstance(module, PolyLayer):
+                module.set_adapter(adapter_name)
+
+    def _prepare_adapter_config(self, peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _register_pre_hooks(self, task_ids):
+        """Helper method to register pre hooks."""
+        if task_ids is None:
+            return []
+
+        def pre_hook(_, args, kwargs):
+            kwargs["task_ids"] = task_ids
+            return args, kwargs
+
+        handles = []
+
+        for module in self.model.modules():
+            if isinstance(module, Linear):
+                handle = module.register_forward_pre_hook(pre_hook, with_kwargs=True)
+                handles.append(handle)
+
+        return handles
+
+    @contextmanager
+    def _manage_pre_hooks(self, task_ids):
+        """Context manager to handle the lifecycle of pre hooks."""
+        handles = self._register_pre_hooks(task_ids)
+        try:
+            yield
+        finally:
+            for handle in handles:
+                handle.remove()
+
+    def forward(self, *args, task_ids=None, **kwargs):
+        with self._manage_pre_hooks(task_ids):
+            return self.model(*args, **kwargs)
+
+    def generate(self, *args, task_ids=None, **kwargs):
+        with self._manage_pre_hooks(task_ids):
+            return self.model.generate(*args, **kwargs)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/router.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/router.py
new file mode 100644
index 0000000000000000000000000000000000000000..3dda3e75e35b6a9fbd5a2412815a0f05421f2ef4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/poly/router.py
@@ -0,0 +1,81 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from abc import ABC, abstractmethod
+
+import torch
+from torch import nn
+from torch.distributions.relaxed_bernoulli import RelaxedBernoulli
+
+from .config import PolyConfig
+
+
+EPS = 1e-12
+
+
+def get_router(poly_config: PolyConfig) -> nn.Module:
+    if poly_config.poly_type == "poly":
+        return PolyRouter(poly_config)
+    else:
+        raise ValueError(
+            f"Unsupported poly_type: {poly_config.poly_type}. "
+            "Currently, only the following types are supported: "
+            "`poly`."
+        )
+
+
+class Router(nn.Module, ABC):
+    @abstractmethod
+    def reset(self): ...
+
+    @abstractmethod
+    def forward(self, task_ids: torch.Tensor, input_ids: torch.Tensor): ...
+
+
+class PolyRouter(Router):
+    # It's a simplified implementation of
+    # https://github.com/microsoft/mttl/blob/ce4ca51dbca73be656feb9b3e5233633e3c5dec7/mttl/models/poly.py#L138
+    def __init__(self, poly_config: PolyConfig):
+        super().__init__()
+
+        self.poly_type = poly_config.poly_type
+        self.n_tasks = poly_config.n_tasks
+        self.n_skills = poly_config.n_skills
+        self.n_splits = poly_config.n_splits
+
+        self.module_logits = nn.Parameter(torch.empty((self.n_tasks, self.n_splits * self.n_skills)))
+
+    def reset(self):
+        torch.nn.init.uniform_(self.module_logits, -1e-3, 1e-3)
+
+    def forward(self, task_ids: torch.Tensor, input_ids: torch.Tensor):
+        if task_ids is None:
+            raise ValueError("task_ids should not be None.")
+        if task_ids.max().item() >= self.n_tasks:
+            raise ValueError(f"Only {self.n_tasks} tasks available. Found task id = {task_ids.max().item()}")
+
+        # move task id to input's device
+        task_ids = task_ids.to(self.module_logits.device)
+
+        module_logits = self.module_logits[task_ids]
+        module_logits = module_logits.view(-1, self.n_splits, self.n_skills)
+
+        if self.training:
+            module_logits = RelaxedBernoulli(temperature=1.0, logits=module_logits).rsample()
+        else:
+            module_logits = torch.sigmoid(module_logits)
+
+        module_weights = module_logits / (module_logits.sum(dim=-1, keepdim=True) + EPS)
+
+        return module_weights
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..939f74d3f689f400dfdcb0139f4a2cf04cce52fc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/__init__.py
@@ -0,0 +1,23 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import PrefixTuningConfig
+from .model import PrefixEncoder
+
+
+__all__ = ["PrefixEncoder", "PrefixTuningConfig"]
+
+register_peft_method(name="prefix_tuning", config_cls=PrefixTuningConfig, model_cls=PrefixEncoder)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..6eed77167a6e0b928e59e7e07fbf842c2d7a2d83
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/config.py
@@ -0,0 +1,42 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from dataclasses import dataclass, field
+
+from peft.config import PromptLearningConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class PrefixTuningConfig(PromptLearningConfig):
+    """
+    This is the configuration class to store the configuration of a [`PrefixEncoder`].
+
+    Args:
+        encoder_hidden_size (`int`): The hidden size of the prompt encoder.
+        prefix_projection (`bool`): Whether to project the prefix embeddings.
+    """
+
+    encoder_hidden_size: int = field(
+        default=None,
+        metadata={"help": "The hidden size of the encoder"},
+    )
+    prefix_projection: bool = field(
+        default=False,
+        metadata={"help": "Whether to project the prefix tokens"},
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.PREFIX_TUNING
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..ffd51892a3cc074406791f6bc7d1b088d25148e3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prefix_tuning/model.py
@@ -0,0 +1,80 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Based on https://github.com/THUDM/P-tuning-v2/blob/main/model/prefix_encoder.py
+# with some refactor
+import torch
+
+
+class PrefixEncoder(torch.nn.Module):
+    r"""
+    The `torch.nn` model to encode the prefix.
+
+    Args:
+        config ([`PrefixTuningConfig`]): The configuration of the prefix encoder.
+
+    Example:
+
+    ```py
+    >>> from peft import PrefixEncoder, PrefixTuningConfig
+
+    >>> config = PrefixTuningConfig(
+    ...     peft_type="PREFIX_TUNING",
+    ...     task_type="SEQ_2_SEQ_LM",
+    ...     num_virtual_tokens=20,
+    ...     token_dim=768,
+    ...     num_transformer_submodules=1,
+    ...     num_attention_heads=12,
+    ...     num_layers=12,
+    ...     encoder_hidden_size=768,
+    ... )
+    >>> prefix_encoder = PrefixEncoder(config)
+    ```
+
+    **Attributes**:
+        - **embedding** (`torch.nn.Embedding`) -- The embedding layer of the prefix encoder.
+        - **transform** (`torch.nn.Sequential`) -- The two-layer MLP to transform the prefix embeddings if
+          `prefix_projection` is `True`.
+        - **prefix_projection** (`bool`) -- Whether to project the prefix embeddings.
+
+    Input shape: (`batch_size`, `num_virtual_tokens`)
+
+    Output shape: (`batch_size`, `num_virtual_tokens`, `2*layers*hidden`)
+    """
+
+    def __init__(self, config):
+        super().__init__()
+        self.prefix_projection = config.prefix_projection
+        token_dim = config.token_dim
+        num_layers = config.num_layers
+        encoder_hidden_size = config.encoder_hidden_size
+        num_virtual_tokens = config.num_virtual_tokens
+        if self.prefix_projection and not config.inference_mode:
+            # Use a two-layer MLP to encode the prefix
+            self.embedding = torch.nn.Embedding(num_virtual_tokens, token_dim)
+            self.transform = torch.nn.Sequential(
+                torch.nn.Linear(token_dim, encoder_hidden_size),
+                torch.nn.Tanh(),
+                torch.nn.Linear(encoder_hidden_size, num_layers * 2 * token_dim),
+            )
+        else:
+            self.embedding = torch.nn.Embedding(num_virtual_tokens, num_layers * 2 * token_dim)
+
+    def forward(self, prefix: torch.Tensor):
+        if self.prefix_projection:
+            prefix_tokens = self.embedding(prefix)
+            past_key_values = self.transform(prefix_tokens)
+        else:
+            past_key_values = self.embedding(prefix)
+        return past_key_values
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..c99ca6a26fea22e3d829c16eec378e82633e1b7b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/__init__.py
@@ -0,0 +1,23 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import PromptTuningConfig, PromptTuningInit
+from .model import PromptEmbedding
+
+
+__all__ = ["PromptEmbedding", "PromptTuningConfig", "PromptTuningInit"]
+
+register_peft_method(name="prompt_tuning", config_cls=PromptTuningConfig, model_cls=PromptEmbedding)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee8ceb8d89ca09f44c5dd9b38f2c69a9d26705b9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/config.py
@@ -0,0 +1,87 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import enum
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PromptLearningConfig
+from peft.utils import PeftType
+
+
+class PromptTuningInit(str, enum.Enum):
+    TEXT = "TEXT"
+    RANDOM = "RANDOM"
+
+
+@dataclass
+class PromptTuningConfig(PromptLearningConfig):
+    """
+    This is the configuration class to store the configuration of a [`PromptEmbedding`].
+
+    Args:
+        prompt_tuning_init (Union[[`PromptTuningInit`], `str`]): The initialization of the prompt embedding.
+        prompt_tuning_init_text (`str`, *optional*):
+            The text to initialize the prompt embedding. Only used if `prompt_tuning_init` is `TEXT`.
+        tokenizer_name_or_path (`str`, *optional*):
+            The name or path of the tokenizer. Only used if `prompt_tuning_init` is `TEXT`.
+        tokenizer_kwargs (`dict`, *optional*):
+            The keyword arguments to pass to `AutoTokenizer.from_pretrained`. Only used if `prompt_tuning_init` is
+            `TEXT`.
+    """
+
+    prompt_tuning_init: Union[PromptTuningInit, str] = field(
+        default=PromptTuningInit.RANDOM,
+        metadata={"help": "How to initialize the prompt tuning parameters"},
+    )
+    prompt_tuning_init_text: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": "The text to use for prompt tuning initialization. Only used if prompt_tuning_init is `TEXT`"
+        },
+    )
+    tokenizer_name_or_path: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": "The tokenizer to use for prompt tuning initialization. Only used if prompt_tuning_init is `TEXT`"
+        },
+    )
+
+    tokenizer_kwargs: Optional[dict] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The keyword arguments to pass to `AutoTokenizer.from_pretrained`. Only used if prompt_tuning_init is "
+                "`TEXT`"
+            ),
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.PROMPT_TUNING
+        if (self.prompt_tuning_init == PromptTuningInit.TEXT) and not self.tokenizer_name_or_path:
+            raise ValueError(
+                f"When prompt_tuning_init='{PromptTuningInit.TEXT.value}', "
+                f"tokenizer_name_or_path can't be {self.tokenizer_name_or_path}."
+            )
+        if (self.prompt_tuning_init == PromptTuningInit.TEXT) and self.prompt_tuning_init_text is None:
+            raise ValueError(
+                f"When prompt_tuning_init='{PromptTuningInit.TEXT.value}', "
+                f"prompt_tuning_init_text can't be {self.prompt_tuning_init_text}."
+            )
+        if self.tokenizer_kwargs and (self.prompt_tuning_init != PromptTuningInit.TEXT):
+            raise ValueError(
+                f"tokenizer_kwargs only valid when using prompt_tuning_init='{PromptTuningInit.TEXT.value}'."
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..ce9b6bc409e0b26f846ea159464bdb953f8b0c4e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/prompt_tuning/model.py
@@ -0,0 +1,91 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import math
+
+import torch
+
+from peft.utils.integrations import gather_params_ctx
+
+from .config import PromptTuningInit
+
+
+class PromptEmbedding(torch.nn.Module):
+    """
+    The model to encode virtual tokens into prompt embeddings.
+
+    Args:
+        config ([`PromptTuningConfig`]): The configuration of the prompt embedding.
+        word_embeddings (`torch.nn.Module`): The word embeddings of the base transformer model.
+
+    **Attributes**:
+        - **embedding** (`torch.nn.Embedding`) -- The embedding layer of the prompt embedding.
+
+    Example:
+
+    ```py
+    >>> from peft import PromptEmbedding, PromptTuningConfig
+
+    >>> config = PromptTuningConfig(
+    ...     peft_type="PROMPT_TUNING",
+    ...     task_type="SEQ_2_SEQ_LM",
+    ...     num_virtual_tokens=20,
+    ...     token_dim=768,
+    ...     num_transformer_submodules=1,
+    ...     num_attention_heads=12,
+    ...     num_layers=12,
+    ...     prompt_tuning_init="TEXT",
+    ...     prompt_tuning_init_text="Predict if sentiment of this review is positive, negative or neutral",
+    ...     tokenizer_name_or_path="t5-base",
+    ... )
+
+    >>> # t5_model.shared is the word embeddings of the base model
+    >>> prompt_embedding = PromptEmbedding(config, t5_model.shared)
+    ```
+
+    Input Shape: (`batch_size`, `total_virtual_tokens`)
+
+    Output Shape: (`batch_size`, `total_virtual_tokens`, `token_dim`)
+    """
+
+    def __init__(self, config, word_embeddings):
+        super().__init__()
+
+        total_virtual_tokens = config.num_virtual_tokens * config.num_transformer_submodules
+        self.embedding = torch.nn.Embedding(total_virtual_tokens, config.token_dim)
+        if config.prompt_tuning_init == PromptTuningInit.TEXT and not config.inference_mode:
+            from transformers import AutoTokenizer
+
+            tokenizer_kwargs = config.tokenizer_kwargs or {}
+            tokenizer = AutoTokenizer.from_pretrained(config.tokenizer_name_or_path, **tokenizer_kwargs)
+            init_text = config.prompt_tuning_init_text
+            init_token_ids = tokenizer(init_text)["input_ids"]
+            # Trim or iterate until num_text_tokens matches total_virtual_tokens
+            num_text_tokens = len(init_token_ids)
+            if num_text_tokens > total_virtual_tokens:
+                init_token_ids = init_token_ids[:total_virtual_tokens]
+            elif num_text_tokens < total_virtual_tokens:
+                num_reps = math.ceil(total_virtual_tokens / num_text_tokens)
+                init_token_ids = init_token_ids * num_reps
+            init_token_ids = init_token_ids[:total_virtual_tokens]
+            init_token_ids = torch.LongTensor(init_token_ids).to(word_embeddings.weight.device)
+            with gather_params_ctx(word_embeddings.parameters()):
+                word_embedding_weights = word_embeddings(init_token_ids).detach().clone()
+            word_embedding_weights = word_embedding_weights.to(torch.float32)
+            self.embedding.weight = torch.nn.Parameter(word_embedding_weights)
+
+    def forward(self, indices):
+        # Just get embeddings
+        prompt_embeddings = self.embedding(indices)
+        return prompt_embeddings
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..4aa7bf8e5fc4705cb7b190cee0de53ac8db89573
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/__init__.py
@@ -0,0 +1,33 @@
+# Copyright 2025-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import TrainableTokensConfig
+from .layer import TrainableTokensLayer
+from .model import TrainableTokensModel
+
+
+__all__ = [
+    "TrainableTokensConfig",
+    "TrainableTokensLayer",
+    "TrainableTokensModel",
+]
+
+register_peft_method(
+    name="trainable_tokens",
+    config_cls=TrainableTokensConfig,
+    model_cls=TrainableTokensModel,
+    is_mixed_compatible=False,
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..c4a93880db5345de93b98978e7fb02ef43cf14fa
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/config.py
@@ -0,0 +1,88 @@
+# Copyright 2025-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class TrainableTokensConfig(PeftConfig):
+    """
+    Configuration for the `TrainableTokens` method.
+
+    Allows for training new tokens (and re-training existing ones) without training the full embedding matrix. By
+    marking a few select tokens (identified by their indices) trainable and leaving the rest untouched, this method can
+    be used to add new tokens or changing the embedding of existing tokens while saving on memory. Both storage as well
+    as working memory usage are reduced in contrast to training the embedding matrix fully.
+
+    Note that training with FSDP/DeepSpeed might not yet be fully supported.
+
+    Args:
+        token_indices (`list[int]`):
+            List of integers, signifying the indices of the tokens you want to be trainable. To find the index of a
+            token with a tokenizer, you can tokenize the string and look at the returned `input_ids`. The closer the
+            amount of indices is to the total amount of tokens, the less efficient this method gets.
+        target_modules (`Optional[Union[list[str], str]]`):
+            List of module names or regex expression of the module names to replace with our `TrainableTokensLayer`. If
+            not defined, it will attempt to get the model's input embedding layer if the model has a
+            `get_input_embeddings` method (transformer models usually do), if that fails the default is 'embed_tokens'.
+            Other example targets are `embedding`, `encoder.embeddings` or `decoder.embeddings`.
+        init_weights (`bool`):
+            By default the new token weights are initialized to be the same as the respective token embeddings. This
+            makes TrainableTokens a no-op when not trained. If set to `False` the weights will be random values. Do not
+            change this setting unless you know exactly what you're doing.
+    """
+
+    token_indices: list[int] = field(
+        default_factory=list,
+        metadata={
+            "help": (
+                "List of integers, signifying the indices of the tokens you want to be trainable. "
+                "To find the index of a token with a tokenizer, you can tokenize the string and "
+                "look at the returned `input_ids`. The closer the amount of indices is to the total amount of "
+                "tokens, the less efficient this method gets."
+            )
+        },
+    )
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of module names or regex expression of the module names to replace with our "
+                "`TrainableTokensLayer`. If not defined, it will default to the model's input embedding layer if "
+                "the model has a `get_input_embeddings` method (transformer models usually do), if that fails the "
+                "default is 'embed_tokens'. Other example targets could be `embedding`, `encoder.embeddings` or "
+                "`decoder.embeddings`."
+            ),
+        },
+    )
+
+    init_weights: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "By default the new token weights are initialized to be the same as the respective token embeddings. "
+                "This makes TrainableTokens a no-op when not trained. If set to `False` the weights will be random "
+                "values. Do not change this setting unless you know exactly what you're doing. "
+            )
+        },
+    )
+
+    def __post_init__(self):
+        self.peft_type = PeftType.TRAINABLE_TOKENS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..73d7d49d554dd7d0655b7ac7efc20aa3b28c0f72
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/layer.py
@@ -0,0 +1,208 @@
+# Copyright 2025-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import warnings
+from typing import Optional
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from peft.tuners._buffer_dict import BufferDict
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+
+
+class TrainableTokensLayer(nn.Module, BaseTunerLayer):
+    # All names of layers that may contain (trainable) adapter weights
+    adapter_layer_names = ("trainable_tokens_delta",)
+
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names = ("token_indices", "trainable_tokens_original")
+
+    def __init__(
+        self,
+        base_layer: nn.Module,
+        adapter_name: str,
+        token_indices: list[int],
+        tied_adapter: Optional[TrainableTokensLayer] = None,
+        **kwargs,
+    ) -> None:
+        super().__init__()
+
+        self.base_layer = base_layer
+        self._active_adapter = adapter_name
+        self.kwargs = kwargs
+
+        # wrap the tied adapter in a list so that it is excluded from .(named_)modules() and, therefore,
+        # not included in the state dict since it would be a copy of the tied adapter anyway.
+        self._tied_adapter = [tied_adapter] if tied_adapter else []
+
+        # we store the updated weights of particular tokens and their originals. we assume
+        # that the count of new tokens is far smaller than the number of total tokens.
+        #
+        # In case we have weight tying with another token adapter, we'll have no actual
+        # references on our own but use everything from the tied adapter.
+        if not self.tied_adapter:
+            self.trainable_tokens_delta = nn.ParameterDict({})
+            self.trainable_tokens_original = BufferDict({})
+            self.token_indices = {}
+        else:
+            self.trainable_tokens_delta = self.tied_adapter.trainable_tokens_delta
+            self.trainable_tokens_original = self.tied_adapter.trainable_tokens_original
+            self.token_indices = self.tied_adapter.token_indices
+
+        # Mark the weight as unmerged
+        self.merged_adapters = []
+
+    @property
+    def tied_adapter(self):
+        if self._tied_adapter:
+            return self._tied_adapter[0]
+        return None
+
+    def update_layer(self, adapter_name, **kwargs):
+        if kwargs.get("tied_adapter", None):
+            # as a tied adapter, we're just following whatever the adpater we're tied to does, we don't update anything.
+            return
+
+        self.token_indices[adapter_name] = kwargs["token_indices"]
+        init_weights = kwargs.get("init_weights", True)
+
+        # we initialize the delta embedding weights from the base embedding matrix and replace values instead of
+        # adding/subtracting deltas. we do it this way and use `embedding.weight.index_copy()` to write the updated
+        # values during `forward()` to avoid that the user resizing the embedding matrix, effectively filling the new
+        # token space with random values, training the model with TrainableTokensLayer, initializing the model anew -
+        # thus re-initializing the new embeddings again with new random variables. If we would add/subtract deltas
+        # onto the new values, we would get undefined behavior. By replacing the specific token values we always
+        # get defined behavior.
+        #
+        if init_weights:
+            values = self.get_base_layer().weight[self.token_indices[adapter_name]]
+        else:
+            values = torch.rand_like(self.get_base_layer().weight[self.token_indices[adapter_name]])
+
+        self.trainable_tokens_delta[adapter_name] = nn.Parameter(values.clone(), requires_grad=True)
+        self.trainable_tokens_original[adapter_name] = values.clone()
+
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+
+    def _check_overlapping_tokens(self, adapter_names):
+        """Raises an error if the token indices of the given adapter names are overlapping.
+        This is currently not supported and can lead to undefined behavior of the model if no specific merging between
+        the overlapping indices' values is applied.
+        """
+        if len(adapter_names) <= 1:
+            return
+
+        indices = set()
+
+        # we take already merged adapters into account as well since they can be overriden by new adapters as well.
+        for adapter_name in set(adapter_names + self.merged_adapters):
+            index_set = set(self.token_indices[adapter_name])
+            if len(indices.intersection(index_set)):
+                raise ValueError(
+                    f"Token indices of adapter {adapter_name} are already defined and would result in "
+                    "undefined merging behavior. Only disjunct token indices are currently supported."
+                )
+            indices.update(index_set)
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        self._check_overlapping_tokens(adapter_names)
+
+        merged = self.base_layer.weight.data
+
+        for adapter_name in adapter_names:
+            index = torch.tensor(self.token_indices[adapter_name]).to(merged.device)
+            deltas = self.trainable_tokens_delta[adapter_name].to(merged)
+            merged = merged.index_copy(dim=0, index=index, source=deltas)
+
+            if safe_merge and not torch.isfinite(merged).all():
+                raise ValueError(f"NaNs detected in the merged weights. The adapter {adapter_name} seems to be broken")
+
+        self.base_layer.weight.data = merged
+        self.merged_adapters.extend(adapter_names)
+
+    def unmerge(self) -> None:
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+
+        while len(self.merged_adapters) > 0:
+            adapter_name = self.merged_adapters.pop()
+
+            index = torch.tensor(self.token_indices[adapter_name]).to(self.base_layer.weight.device)
+            originals = self.trainable_tokens_original[adapter_name].to(self.base_layer.weight)
+            self.base_layer.weight.data.index_copy_(dim=0, index=index, source=originals)
+
+    def get_merged_weights(self, active_adapters):
+        W = self.base_layer.weight
+
+        for adapter_name in active_adapters:
+            index = torch.tensor(self.token_indices[adapter_name]).to(W.device)
+            deltas = self.trainable_tokens_delta[adapter_name].to(W)
+            W = W.index_copy(dim=0, index=index, source=deltas)
+
+        return W
+
+    def forward_adapters(self, x: torch.Tensor, active_adapters, *args, **kwargs) -> torch.Tensor:
+        if self.disable_adapters or not active_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            self._check_overlapping_tokens(active_adapters)
+
+            W = self.get_merged_weights(active_adapters)
+
+            # Normally it should be very clear that we're wrapping Embedding layers but there are cases, such as
+            # tying weights with an LM head where the layer we wrap is a Linear layer. Therefore we must choose
+            # accordingly.
+            #
+            # TODO: the isinstance checks, especially the one for nn.Linear, may not hold for quantized layers;
+            # TODO: we may need to find a better way to detect quantized layers.
+            if isinstance(self.base_layer, torch.nn.Embedding):
+                result = F.embedding(
+                    input=x,
+                    weight=W,
+                    padding_idx=self.base_layer.padding_idx,
+                    max_norm=self.base_layer.max_norm,
+                    norm_type=self.base_layer.norm_type,
+                    scale_grad_by_freq=self.base_layer.scale_grad_by_freq,
+                    sparse=self.base_layer.sparse,
+                )
+            elif isinstance(self.base_layer, torch.nn.Linear):
+                # Probably a tied adapter that wraps an LM head.
+                result = F.linear(
+                    input=x,
+                    weight=W,
+                )
+            else:
+                raise ValueError(
+                    "TrainableTokensLayer wraps an unknown layer type, maybe you are targeting the wrong layer?"
+                )
+
+        return result
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        return self.forward_adapters(x, self.active_adapters, *args, **kwargs)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6b797ebaf9f9aa7555d10983985b18b18535e57
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/trainable_tokens/model.py
@@ -0,0 +1,280 @@
+# Copyright 2025-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import warnings
+from typing import Optional
+
+import torch
+import torch.nn as nn
+from tqdm import tqdm
+
+from peft.config import PeftConfig
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists, onload_layer
+from peft.utils import AuxiliaryTrainingWrapper, _get_input_embeddings_name, _get_submodules
+
+from .layer import TrainableTokensLayer
+
+
+class TrainableTokensModel(BaseTuner):
+    prefix: str = "trainable_tokens_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False):
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            return getattr(self.model, name)
+
+    def _prepare_adapter_config(self, peft_config, model_config):
+        # target_modules can be none which prompts us to infer the embedding layer name ourselves.
+        if peft_config.target_modules is None:
+            peft_config.target_modules = _get_input_embeddings_name(self.model, "embed_tokens")
+
+        return peft_config
+
+    def inject_adapter(
+        self, model: nn.Module, adapter_name: str, autocast_adapter_dtype: bool = True, low_cpu_mem_usage: bool = False
+    ) -> None:
+        super().inject_adapter(
+            model=model,
+            adapter_name=adapter_name,
+            autocast_adapter_dtype=autocast_adapter_dtype,
+            low_cpu_mem_usage=low_cpu_mem_usage,
+        )
+
+        model_config = self.get_model_config(self)
+
+        # In case of weight-tying we need to adapt the tied weights as well and use tie the embedding adapter.
+        #
+        # The TrainableTokensLayer supports being tied to another TrainableTokensLayer meaning that the layer will
+        # not do any changes on its own but solely rely on the weights from the tied adapter. We will search for the
+        # tied weights and put tied TrainableTokensLayer adapters on them, all tied to the adapter of the embedding
+        # matrix.
+        if (
+            model_config.get("tie_word_embeddings", False)
+            # some models may be misconfigured to have weight tying enabled but don't define tied weights keys
+            and self.model._tied_weights_keys is not None
+            and isinstance(self.model.get_input_embeddings(), TrainableTokensLayer)
+        ):
+            module_keys = [".".join(n.split(".")[:-1]) for n in self.model._tied_weights_keys]
+            # disable removing of duplicates since we're essentially only dealing with duplicates (i.e. tied weights)
+            for name, module in self.model.named_modules(remove_duplicate=False):
+                matched_keys = [target_key for target_key in module_keys if name.endswith(target_key)]
+                if matched_keys:
+                    parent, target, target_name = _get_submodules(model, name)
+
+                    peft_config = self.peft_config[adapter_name].to_dict()
+                    peft_config["tied_adapter"] = self.model.get_input_embeddings()
+
+                    self._create_and_replace_dict(
+                        peft_config,
+                        adapter_name,
+                        target,
+                        target_name,
+                        parent,
+                        matched_keys[0],
+                    )
+
+    def _get_tied_target_modules(self, *args, **kwargs):
+        # Normally this method would return the layers that target tied layers.
+        #
+        # We override this method since we explicitly support tied weights tied to the embedding layer.
+        # Therefore, we don't need the warning issued by returning the modules here.
+        return []
+
+    def _create_and_replace_dict(
+        self,
+        peft_config: dict,
+        adapter_name: str,
+        target: nn.Module,
+        target_name: str,
+        parent: nn.Module,
+        current_key: str,
+    ) -> None:
+        """
+        The same as `_create_and_replace` but takes a dictionary instead of a peft config so that we can add keys that
+        are not present in the config, such as `tied_adapter`.
+        """
+        kwargs = peft_config
+
+        if isinstance(target, TrainableTokensLayer):
+            target.update_layer(adapter_name, **kwargs)
+        else:
+            new_module = self._create_new_module(peft_config, adapter_name, target, **kwargs)
+            self._replace_module(parent, target_name, new_module, target)
+
+    def _create_and_replace(
+        self,
+        peft_config: PeftConfig,
+        adapter_name: str,
+        target: nn.Module,
+        target_name: str,
+        parent: nn.Module,
+        current_key: str,
+    ) -> None:
+        """
+        A private method to create and replace the target module with the adapter module.
+        """
+        kwargs = peft_config.to_dict()
+        self._create_and_replace_dict(kwargs, adapter_name, target, target_name, parent, current_key)
+
+    def _check_target_module_exists(self, peft_config: PeftConfig, key: str) -> bool:
+        return check_target_module_exists(peft_config, key)
+
+    @staticmethod
+    def _create_new_module(peft_config, adapter_name, target, **kwargs):
+        new_module = TrainableTokensLayer(target, adapter_name, **kwargs)
+        new_module.update_layer(
+            adapter_name,
+            init_weights=kwargs["init_weights"],
+            token_indices=kwargs["token_indices"],
+            tied_adapter=kwargs.get("tied_adapter", None),
+        )
+
+        return new_module
+
+    def _replace_module(self, parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if self.prefix in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+    def _set_adapter_layers(self, enabled: bool = True) -> None:
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, AuxiliaryTrainingWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self) -> None:
+        """Enable all adapters.
+
+        Call this if you have previously disabled all adapters and want to re-enable them.
+        """
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self) -> None:
+        """Disable all adapters.
+
+        When disabling all adapters, the model output corresponds to the output of the base model.
+        """
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name: str | list[str]) -> None:
+        """Set the active adapter(s).
+
+        Additionally, this function will set the specified adapters to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str` or `list[str]`): Name of the adapter(s) to be activated.
+        """
+        for module in self.model.modules():
+            if isinstance(module, TrainableTokensLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    def unload(self) -> torch.nn.Module:
+        """
+        Gets back the base model by removing all the trainable tokens modules without merging.
+        """
+        return self._unload_and_optionally_merge(merge=False)
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the trained tokens into the targeted embedding layer(s) of the base model. This is needed if
+        someone wants to use the base model as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+            with onload_layer(target):
+                if hasattr(target, "unload_and_optionally_merge_module"):
+                    # if layers have special unloading method, like MultiheadAttention, use that
+                    unloaded_module = target.unload_and_optionally_merge_module(
+                        merge=merge, safe_merge=safe_merge, adapter_names=adapter_names
+                    )
+                    self._replace_module(parent, target_name, unloaded_module, target)
+                elif hasattr(target, "base_layer"):
+                    if merge:
+                        target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+                    self._replace_module(parent, target_name, target.get_base_layer(), target)
+
+        return self.model
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/tuners_utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/tuners_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..770af21319ace813da82daf9086ae5f2f748b788
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/tuners_utils.py
@@ -0,0 +1,1199 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import copy
+import os
+import re
+import textwrap
+import warnings
+from abc import ABC, abstractmethod
+from contextlib import contextmanager, nullcontext
+from typing import Any, Optional, Union
+
+import torch
+from accelerate.hooks import AlignDevicesHook
+from accelerate.utils import named_module_tensors, offload_state_dict
+from torch import nn
+from transformers import PreTrainedModel
+from transformers.pytorch_utils import Conv1D
+
+from peft.utils import INCLUDE_LINEAR_LAYERS_SHORTHAND
+from peft.utils.constants import (
+    DUMMY_MODEL_CONFIG,
+    DUMMY_TARGET_MODULES,
+    EMBEDDING_LAYER_NAMES,
+    MIN_TARGET_MODULES_FOR_OPTIMIZATION,
+    SEQ_CLS_HEAD_NAMES,
+)
+from peft.utils.integrations import init_empty_weights
+from peft.utils.peft_types import PeftType, TaskType
+
+from ..config import PeftConfig
+from ..utils import ModulesToSaveWrapper, _get_submodules
+from ._buffer_dict import BufferDict
+
+
+@contextmanager
+def onload_layer(layer):
+    r"""
+    A utility for modifying a module containing one or more tuners and a base layer, any of which are offloaded to the
+    CPU or disk. Moves a module's sub-modules to the execution device before some action is performed, after that the
+    base layer state dictionary is re-assigned (if that layer was offloaded to the disk) and finally the parameters are
+    offloaded.
+
+    If the module has no offloaded sub-modules, this function does nothing.
+
+    Args:
+        layer ('torch.nn.Module'):
+            layer with tuners to be merged
+    """
+
+    offloaded_modules = []
+    for name, module in layer.named_modules():
+        if name in ["", "base_layer"]:
+            continue
+        if hasattr(module, "_hf_hook") and isinstance(module._hf_hook, AlignDevicesHook) and module._hf_hook.offload:
+            module._hf_hook.pre_forward(module)
+            offloaded_modules.append(module)
+
+    base_layer_offload = False
+    if hasattr(layer, "base_layer") and (
+        hasattr(layer.base_layer, "_hf_hook")
+        and isinstance(layer.base_layer._hf_hook, AlignDevicesHook)
+        and layer.base_layer._hf_hook.offload
+    ):
+        # check if the base layer is disk-offloaded (must contain a 'dataset' and an offload index)
+        if torch.device("meta") in layer.base_layer._hf_hook.original_devices.values() and hasattr(
+            layer.base_layer._hf_hook.weights_map, "dataset"
+        ):
+            # find the disk-offload index (maps modules to safetensors) from the `dataset` (OffloadedWeightsLoader object)
+            index = layer.base_layer._hf_hook.weights_map.dataset.index
+            module_name = list(dict(layer.base_layer._hf_hook.weights_map.dataset).keys())[0]  # any module will do
+            file_name = index[module_name]["safetensors_file"]
+            base_name_arr = []
+            # get effective dir name
+            for i in os.path.split(file_name):
+                if "--" in i:
+                    base_name_arr.append(i)
+                    break
+                base_name_arr.append(i)
+            base_name = os.path.join(*base_name_arr)
+            safetensors_filename = base_name + "-merged"
+        layer.base_layer._hf_hook.pre_forward(layer.base_layer)
+        base_layer_offload = True
+
+    yield
+
+    for module in offloaded_modules:
+        module._hf_hook.post_forward(module, torch.tensor([]))
+
+    if base_layer_offload:
+        # re-make weights map (must be on cpu to send params to the disk via memmap if disk offload)
+        layer.base_layer._hf_hook.weights_map = {
+            name: param.to("cpu") for name, param in named_module_tensors(layer.base_layer)
+        }
+        # offload weights map to disk if original device is the disk
+        if torch.device("meta") in layer.base_layer._hf_hook.original_devices.values() and hasattr(
+            layer.base_layer._hf_hook.weights_map, "dataset"
+        ):
+            # rewrite directory with merged weights
+            offload_state_dict(safetensors_filename, layer.base_layer._hf_hook.weights_map)
+        layer.base_layer._hf_hook.post_forward(layer.base_layer, torch.tensor([]))
+
+
+class BaseTuner(nn.Module, ABC):
+    r"""
+    A base tuner model that provides the common methods and attributes for all tuners that are injectable into a
+    torch.nn.Module
+
+    For adding a new Tuner class, one needs to overwrite the following methods:
+
+    - **_prepare_adapter_config**:
+        A private method to eventually prepare the adapter config, for example in case the field `target_modules` is
+        missing.
+    - **_create_and_replace**:
+        A private method to create and replace the target module with the adapter module.
+    - **_check_target_module_exists**:
+        A private helper method to check if the passed module's key name matches any of the target modules in the
+        adapter_config.
+
+    The easiest is to check what is done in the `peft.tuners.lora.LoraModel` class.
+
+    Attributes:
+        model (`torch.nn.Module`):
+            The model to which the adapter tuner layers will be attached.
+        forward (`Callable`):
+            The forward method of the model.
+        peft_config (`Union[`PeftConfig`, dict[str, PeftConfig]]`):
+            The adapter configuration object, it should be a dictionary of `str` to `PeftConfig` objects. One can also
+            pass a PeftConfig object and a new adapter will be created with the default name `adapter` or create a new
+            dictionary with a key `adapter_name` and a value of that peft config.
+        config (`dict[str, Any]`):
+            The model configuration object, it should be a dictionary of `str` to `Any` objects.
+        targeted_module_names (`list[str]`):
+            The list of module names that were actually adapted. Can be useful to inspect if you want to quickly
+            double-check that the `config.target_modules` were specified correctly.
+    """
+
+    def __init__(
+        self,
+        model,
+        peft_config: Union[PeftConfig, dict[str, PeftConfig]],
+        adapter_name: str,
+        low_cpu_mem_usage: bool = False,
+    ) -> None:
+        super().__init__()
+
+        self.model = model
+        self.targeted_module_names: list[str] = []
+
+        # For advanced developers, if you want to attach multiple adapters to your
+        # model, just add a `peft_config` dict attribute to your model.
+        if not hasattr(self, "peft_config"):
+            self.peft_config = {adapter_name: peft_config} if isinstance(peft_config, PeftConfig) else peft_config
+        else:
+            warnings.warn(
+                "Already found a `peft_config` attribute in the model. This will lead to having multiple adapters"
+                " in the model. Make sure to know what you are doing!"
+            )
+            if isinstance(peft_config, PeftConfig):
+                self.peft_config[adapter_name] = peft_config
+            else:
+                # user is adding a dict of PeftConfigs
+                self.peft_config.update(peft_config)
+
+        self.active_adapter: str | list[str] = adapter_name
+        self._pre_injection_hook(self.model, self.peft_config[adapter_name], adapter_name)
+        if peft_config != PeftType.XLORA or peft_config[adapter_name] != PeftType.XLORA:
+            self.inject_adapter(self.model, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+        # Copy the peft_config in the injected model.
+        self.model.peft_config = self.peft_config
+
+    @property
+    def active_adapters(self) -> list[str]:
+        if isinstance(self.active_adapter, str):
+            return [self.active_adapter]
+        # is already a list of str
+        return self.active_adapter
+
+    def forward(self, *args: Any, **kwargs: Any):
+        return self.model.forward(*args, **kwargs)
+
+    def _pre_injection_hook(self, model: nn.Module, config: PeftConfig, adapter_name: str) -> None:
+        r"""
+        A hook to be called before the adapter is injected into the model. This method can be overridden by child
+        classes to perform any pre-injection operations.
+
+        Args:
+            model (`nn.Module`):
+                The model to be adapted.
+            config (`PeftConfig`):
+                The adapter config.
+            adapter_name (`str`):
+                The adapter name.
+        """
+        pass
+
+    @abstractmethod
+    def _prepare_adapter_config(self, peft_config: PeftConfig, model_config: dict) -> PeftConfig:
+        r"""
+        A private method to eventually prepare the adapter config. For transformers based models, if
+        `peft_config.target_modules` is None, we can automatically infer the target modules from the
+        `TRANSFORMERS_MODELS_TO_XXX_TARGET_MODULES_MAPPING`. This method can be further refactored in the future to
+        automatically infer it for all tuner models.
+
+        Check out `peft.tuner.lora.LoraModel._prepare_adapter_config` for an example.
+
+        Args:
+            peft_config (`PeftConfig`):
+                The adapter config.
+            model_config (`dict`):
+                The transformers model config, that config should contain the `model_type` key.
+        """
+        ...
+
+    def _prepare_model(self, peft_config: PeftConfig, model: nn.Module):
+        r"""
+        A private method to modify the model structure before adapter is applied.
+
+        See `peft.tuner.lora.LoraModel._prepare_model` for an example.
+
+        Args:
+            peft_config (`PeftConfig`):
+                The prepared adapter config.
+            model (`nn.Module`):
+                The model that is going to be adapted.
+        """
+        pass
+
+    @abstractmethod
+    def _check_target_module_exists(peft_config: PeftConfig, key: str) -> bool:
+        r"""
+        A helper private method to check if the passed module's key name matches any of the target modules in the
+        `peft_config.target_modules` list. If it does, return `True`, else return `False`.
+
+        Args:
+            peft_config (`PeftConfig`):
+                The adapter config.
+            key (`str`):
+                The module's key name.
+        """
+        ...
+
+    @abstractmethod
+    def _create_and_replace(
+        self,
+        peft_config: PeftConfig,
+        adapter_name: str,
+        target: nn.Module,
+        target_name: str,
+        parent: nn.Module,
+        current_key: str,
+    ) -> None:
+        r"""
+        Inplace replacement of the target module with the adapter layer. This method needs to be overridden by all the
+        tuner classes.
+
+        Check `peft.tuners.lora.LoraModel._create_and_replace` for an example.
+
+        Args:
+            peft_config (`PeftConfig`):
+                The adapter config.
+            adapter_name (`str`):
+                The adapter name.
+            target (`nn.Module`):
+                The target module.
+            target_name (`str`):
+                The target module's name.
+            parent (`nn.Module`):
+                The parent module.
+            current_key (`str`):
+                The key of the current target being adapted.
+        """
+        ...
+
+    @abstractmethod
+    def _mark_only_adapters_as_trainable(self, model: nn.Module):
+        r"""
+        A helper method to mark only the adapter layers as trainable (i.e. module.requires_grad = False) This needs to
+        be overridden for all tuner classes to match the correct key names.
+
+        Check `peft.tuners.lora.LoraModel._mark_only_adapters_as_trainable` for an example.
+        """
+        ...
+
+    @abstractmethod
+    def disable_adapter_layers(self) -> None:
+        """
+        Disable all adapters in-place.
+        """
+        ...
+
+    @abstractmethod
+    def enable_adapter_layers(self) -> None:
+        """
+        Enable all adapters in-place
+        """
+        ...
+
+    def _check_new_adapter_config(self, config: PeftConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        pass
+
+    def _cast_adapter_dtype(self, adapter_name: str, autocast_adapter_dtype: bool = True) -> None:
+        """
+        A helper method to cast the adapter weights to the correct dtype.
+
+        Currently, this only upcasts float16 and bfloat16 to float32.
+
+        Args:
+            adapter_name (`str`):
+                The adapter name.
+            autocast_adapter_dtype (`bool`, *optional*):
+                Whether to autocast the adapter dtype. Defaults to `True`.
+
+        """
+        if not autocast_adapter_dtype:
+            return
+
+        dtypes_to_convert_to_fp32 = {torch.float16, torch.bfloat16}
+
+        for module in self.model.modules():
+            if not isinstance(module, BaseTunerLayer):
+                continue
+
+            for submodule in module.modules():
+                if not isinstance(submodule, (nn.ModuleDict, nn.ParameterDict, BufferDict)):
+                    continue
+
+                if adapter_name not in submodule:
+                    continue
+
+                if isinstance(submodule[adapter_name], nn.Parameter):
+                    if submodule[adapter_name].dtype in dtypes_to_convert_to_fp32:
+                        submodule[adapter_name].data = submodule[adapter_name].data.to(torch.float32)
+                    continue
+
+                if isinstance(submodule[adapter_name], torch.Tensor):  # e.g. from a BufferDict
+                    if submodule[adapter_name].dtype in dtypes_to_convert_to_fp32:
+                        submodule[adapter_name] = submodule[adapter_name].to(torch.float32)
+                    continue
+
+                for param in submodule[adapter_name].parameters():
+                    if param.dtype in dtypes_to_convert_to_fp32:
+                        param.data = param.data.to(torch.float32)
+
+    def _check_merge_allowed(self):
+        """Helper method to check whether the adapter can be merged.
+
+        Raise a ValueError if it is not possible to merge the adapter with the given configuration.
+        """
+        example_code = textwrap.dedent(
+            """
+            ```python
+            from transformers import AutoModelForCausalLM
+
+            # Load original tied model
+            model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it", tie_word_embeddings=False)
+
+            # Set the randomly initialized lm_head to the previously tied embeddings
+            model.lm_head.weight.data = model.model.embed_tokens.weight.data.clone()
+
+            # Save the untied model
+            untied_model_dir = "dir/for/untied/model"
+            model.save_pretrained(untied_model_dir)
+            model.config.save_pretrained(untied_model_dir)
+
+            # Now use the original model but in untied format
+            model = AutoModelForCausalLM.from_pretrained(untied_model_dir)
+            ```
+            """
+        )
+        tied_target_modules = self._get_tied_target_modules(self.model)
+        if tied_target_modules:
+            warnings.warn(
+                f"Model with `tie_word_embeddings=True` and the {tied_target_modules=} are part of the adapter. "
+                "This can lead to complications. "
+                "You can opt to merge the adapter after cloning the weights (to untie the embeddings). "
+                "You can untie the embeddings by loading the model with `tie_word_embeddings=False`. For example:"
+                + example_code
+            )
+
+    def inject_adapter(
+        self, model: nn.Module, adapter_name: str, autocast_adapter_dtype: bool = True, low_cpu_mem_usage: bool = False
+    ) -> None:
+        r"""
+        Creates adapter layers and replaces the target modules with the adapter layers. This method is called under the
+        hood by `peft.mapping.get_peft_model` if a non-prompt tuning adapter class is passed.
+
+        The corresponding PEFT config is directly retrieved from the `peft_config` attribute of the BaseTuner class.
+
+        Args:
+            model (`nn.Module`):
+                The model to be tuned.
+            adapter_name (`str`):
+                The adapter name.
+            autocast_adapter_dtype (`bool`, *optional*):
+                Whether to autocast the adapter dtype. Defaults to `True`.
+            low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+                Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+        """
+        peft_config = self.peft_config[adapter_name]
+        excluded_modules = []
+        unmatched_modules = []
+        # Note: If possible, all checks should be performed *at the start of this method*.
+        # This way, we can raise early if something goes wrong, without leaving the model
+        # in a bad (half-initialized) state.
+        self._check_new_adapter_config(peft_config)
+
+        _check_for_modules_to_save = getattr(peft_config, "modules_to_save", None) is not None
+        _has_modules_to_save = False
+
+        model_config = self.get_model_config(model)
+
+        peft_config = self._prepare_adapter_config(peft_config, model_config)
+
+        self._prepare_model(peft_config, model)
+        key_list = [key for key, _ in model.named_modules()]
+
+        uses_dummy_target_modules = getattr(peft_config, "target_modules", None) == DUMMY_TARGET_MODULES
+        if uses_dummy_target_modules:
+            # dummy adapter, we allow not matching any module
+            key_list = []
+
+        # update peft_config.target_modules if required
+        peft_config = _maybe_include_all_linear_layers(peft_config, model)
+
+        # This is an optimization to reduce the number of entries in the target_modules list. The reason is that in some
+        # circumstances, target_modules can contain hundreds of entries. Since each target module is checked against
+        # each module of the net (which can be thousands), this can become quite expensive when many adapters are being
+        # added. Often, the target_modules can be condensed in such a case, which speeds up the process.
+        # A context in which this can happen is when diffusers loads non-PEFT LoRAs. As there is no meta info on
+        # target_modules in that case, they are just inferred by listing all keys from the state_dict, which can be
+        # quite a lot. See: https://github.com/huggingface/diffusers/issues/9297
+        # As there is a small chance for undiscovered bugs, we apply this optimization only if the list of
+        # target_modules is sufficiently big.
+        # We also exclude IA³ from this optimization. This is because IA³ has both target_modules and
+        # feedforward_modules, which are coupled (the latter must be a subset). It would be possible to change the logic
+        # to keep both in sync, but it's not quite trivial and probably not worth the effort. See #2429.
+        if (
+            isinstance(peft_config.target_modules, (list, set))
+            and (len(peft_config.target_modules) >= MIN_TARGET_MODULES_FOR_OPTIMIZATION)
+            and (peft_config.peft_type != PeftType.IA3)
+        ):
+            names_no_target = [
+                name
+                for name in key_list
+                if not any((name == suffix) or name.endswith("." + suffix) for suffix in peft_config.target_modules)
+            ]
+            new_target_modules = _find_minimal_target_modules(peft_config.target_modules, names_no_target)
+            if len(new_target_modules) < len(peft_config.target_modules):
+                peft_config.target_modules = new_target_modules
+
+        for key in key_list:
+            if not key:
+                continue
+            # Check for modules_to_save in case
+            #
+            # Note that this is redundant with PeftModel.set_additional_trainable_models but might be necessary
+            # when calling inject_adapter without a PEFT model. This is outdated as it only focuses on
+            # ModulesToSaveWrapper and ignores other potentially configured AuxiliaryTrainingWrapper instances.
+            #
+            # TODO: determine if there's a good reason for this and refactor to support AuxiliaryTrainingWrapper,
+            # or remove if superfluous.
+            if _check_for_modules_to_save and any(
+                key.endswith(module_to_save) for module_to_save in peft_config.modules_to_save
+            ):
+                # Optionally set the modules to save
+                parent, target, target_name = _get_submodules(model, key)
+
+                if not isinstance(target, ModulesToSaveWrapper):
+                    new_module = ModulesToSaveWrapper(target, adapter_name)
+                    setattr(parent, target_name, new_module)
+                else:
+                    target.update(adapter_name)
+
+                _has_modules_to_save = True
+                continue
+
+            result = self._check_target_module_exists(peft_config, key)
+            if isinstance(result, _ExcludedModule):
+                excluded_modules.append(key)
+            elif not result:
+                unmatched_modules.append(key)
+            else:
+                self.targeted_module_names.append(key)
+                parent, target, target_name = _get_submodules(model, key)
+                ctx = init_empty_weights if low_cpu_mem_usage else nullcontext
+                with ctx():
+                    self._create_and_replace(peft_config, adapter_name, target, target_name, parent, current_key=key)
+
+        if not self.targeted_module_names and not uses_dummy_target_modules:
+            if excluded_modules and not unmatched_modules:
+                # All targeted modules were excluded
+                raise ValueError(
+                    "All modules were excluded. This is likely unintended. "
+                    "Check your `target_modules` and `exclude_modules` configuration."
+                )
+            elif not excluded_modules and unmatched_modules:
+                # None of the targeted modules matched
+                error_msg = (
+                    f"Target modules {peft_config.target_modules} not found in the base model. "
+                    f"Please check the target modules and try again."
+                )
+                if getattr(peft_config, "layers_to_transform", None) is not None:
+                    error_msg += f" Note: You specified 'layers_to_transform': {peft_config.layers_to_transform}."
+                if getattr(peft_config, "layers_pattern", None) is not None:
+                    error_msg += f" You also specified 'layers_pattern': {peft_config.layers_pattern}."
+                raise ValueError(error_msg)
+            else:
+                # Some modules did not match and some matched but were excluded
+                error_msg = (
+                    "No modules were targeted for adaptation. "
+                    "This might be caused by a combination of mismatched target modules and excluded modules. "
+                    "Please check your `target_modules` and `exclude_modules` configuration."
+                )
+                if getattr(peft_config, "layers_to_transform", None) is not None:
+                    error_msg += f" Note: You specified 'layers_to_transform': {peft_config.layers_to_transform}."
+                if getattr(peft_config, "layers_pattern", None) is not None:
+                    error_msg += f" You also specified 'layers_pattern': {peft_config.layers_pattern}."
+                raise ValueError(error_msg)
+
+        elif hasattr(peft_config, "exclude_modules") and peft_config.exclude_modules and not excluded_modules:
+            # exclude_modules was passed but was not used
+            warnings.warn(
+                f"You have passed exclude_modules={peft_config.exclude_modules} but no modules were excluded. "
+                "Please check that exclude_modules was set correctly."
+            )
+
+        tied_target_modules = self._get_tied_target_modules(model=model)
+        if tied_target_modules:
+            warnings.warn(
+                f"Model with `tie_word_embeddings=True` and the {tied_target_modules=} are part of the adapter. "
+                "This can lead to complications, for example when merging the adapter "
+                "or converting your model to formats other than safetensors. "
+                "See for example https://github.com/huggingface/peft/issues/2018."
+            )
+
+        # It's important to set the adapter here (again), because otherwise it can happen that if a 2nd adapter is
+        # added, and it targets different layer(s) than the first adapter (which is active), then those different
+        # layers will be activated, which we don't want.
+        self.set_adapter(self.active_adapters)
+        self._mark_only_adapters_as_trainable(model)
+
+        if self.peft_config[adapter_name].inference_mode:
+            for n, p in model.named_parameters():
+                if adapter_name in n:
+                    p.requires_grad = False
+
+        if _has_modules_to_save:
+            if not hasattr(model, "modules_to_save"):
+                model.modules_to_save = set(peft_config.modules_to_save)
+            else:
+                model.modules_to_save.update(set(peft_config.modules_to_save))
+
+    def merge_adapter(self, adapter_names: Optional[list[str]] = None) -> None:
+        """
+        This method merges the adapter layers into the base model.
+
+        Merging adapters can lead to a speed up of the forward pass. A copy of the adapter weights is still kept in
+        memory, which is required to unmerge the adapters. In order to merge the adapter weights without keeping them
+        in memory, please call `merge_and_unload`.
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If `True`, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`list[str]`, *optional*):
+                The list of adapter names that should be merged. If `None`, all active adapters will be merged.
+                Defaults to `None`.
+        """
+        self._check_merge_allowed()
+        for module in self.model.modules():
+            if isinstance(module, BaseTunerLayer):
+                with onload_layer(module):
+                    module.merge(adapter_names=adapter_names)
+
+    def unmerge_adapter(self):
+        """
+        This method unmerges all merged adapter layers from the base model.
+        """
+        for module in self.model.modules():
+            if isinstance(module, BaseTunerLayer):
+                with onload_layer(module):
+                    module.unmerge()
+
+    def _unloading_checks(self, adapter_names: Optional[list[str]]):
+        adapters_to_consider = adapter_names or self.active_adapters
+        is_modules_to_save_available = any(
+            self.peft_config[adapter].modules_to_save for adapter in adapters_to_consider
+        )
+        if is_modules_to_save_available and len(adapters_to_consider) > 1:
+            raise ValueError("Cannot unload multiple adapters that specify `modules_to_save`.")
+
+    @staticmethod
+    def get_model_config(model: nn.Module) -> dict:
+        """
+        This method gets the config from a model in dictionary form. If model has not attribute config, then this
+        method returns a default config.
+
+        Args:
+            model (`nn.Module`):
+                Model to get the config from.
+            default (`dict|None`, *optional*)::
+                What to return if model does not have a config attribute.
+        """
+        model_config = getattr(model, "config", DUMMY_MODEL_CONFIG)
+        if hasattr(model_config, "to_dict"):
+            model_config = model_config.to_dict()
+        return model_config
+
+    def _get_tied_target_modules(self, model: nn.Module) -> list[str]:
+        tied_target_modules = []
+        model_config = self.get_model_config(model)
+        if model_config.get("tie_word_embeddings"):
+            for target_module in self.targeted_module_names:
+                # This potentially yields false positives since we're just looking at the layer names. So if we use a
+                # model that uses weight-tying of lm_head and embed_tokens, a third, unrelated, layer which is
+                # unfortunately named so that it is in EMBEDDING_LAYER_NAMES will be falsely reported here as well.
+                if target_module.split(".")[-1] in EMBEDDING_LAYER_NAMES:
+                    tied_target_modules.append(target_module)
+        return tied_target_modules
+
+
+class BaseTunerLayer(ABC):
+    r"""
+    A tuner layer mixin that provides the common methods and attributes for all tuners.
+
+    Args:
+        is_pluggable (`bool`, *optional*):
+            Whether the adapter layer can be plugged to any pytorch module
+        active_adapters (Union[List[`str`], `str`], *optional*):
+            The name of the active adapter.
+    """
+
+    # All names of layers that may contain adapter (trainable) weights
+    adapter_layer_names: tuple[str, ...] = ()
+    # All names of other parameters that may contain adapter-related parameters
+    other_param_names: tuple[str, ...] = ()
+
+    # indicates whether all adapters should be disabled
+    _disable_adapters: bool = False
+
+    # the currently active adapter(s)
+    _active_adapter: str | list[str] = "default"
+
+    # List all merged adapters
+    merged_adapters: list[str] = []
+
+    def get_base_layer(self) -> nn.Module:
+        """
+        (Recursively) get the base_layer.
+
+        This is necessary for the case that the tuner layer wraps another tuner layer.
+
+        """
+        base_layer = self
+        while hasattr(base_layer, "base_layer"):
+            base_layer = base_layer.base_layer
+        return base_layer
+
+    @property
+    def weight(self) -> torch.Tensor:
+        # This is required for some transformers code, e.g. for T5, weight is accessed as:
+        #     self.wo.weight
+        # where "wo" is the adapter layer.
+        # https://github.com/huggingface/transformers/blob/78f6ed6c70b29c1560780e3869a7ad4c6b3d2710/src/transformers
+        # /models/t5/modeling_t5.py#L292
+        base_layer = self.get_base_layer()
+        if hasattr(base_layer, "qweight"):
+            # QuantLinear
+            weight = base_layer.qweight
+        else:
+            # Other layers
+            weight = base_layer.weight
+        return weight
+
+    @property
+    def bias(self) -> torch.Tensor:
+        base_layer = self.get_base_layer()
+        return base_layer.bias
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+        raise NotImplementedError
+
+    def unmerge(self) -> None:
+        raise NotImplementedError
+
+    @property
+    def merged(self) -> bool:
+        return bool(self.merged_adapters)
+
+    @property
+    def disable_adapters(self) -> bool:
+        # use a property to ensure that disable_adapters is not set directly, instead use the enable_adapters method
+        return self._disable_adapters
+
+    @property
+    def active_adapter(self) -> str | list[str]:
+        # use a property to ensure that active_adapter is not set directly, instead use the set_adapter method
+        return self._active_adapter
+
+    def _get_available_adapters(self) -> set[str]:
+        """Return all adapter names that can be found on this module."""
+        adapters = set()
+        for layer_name in self.adapter_layer_names:
+            module = getattr(self, layer_name)
+            if not isinstance(module, (nn.ModuleDict, nn.ParameterDict)):
+                continue
+            adapters.update(set(module.keys()))
+        return adapters
+
+    @property
+    def active_adapters(self):
+        if isinstance(self.active_adapter, str):
+            return [self.active_adapter]
+        # is already a list of str
+        return self.active_adapter
+
+    def enable_adapters(self, enabled: bool) -> None:
+        """Toggle the enabling and disabling of adapters
+
+        Takes care of setting the requires_grad flag for the adapter weights.
+
+        Args:
+            enabled (bool): True to enable adapters, False to disable adapters
+        """
+        if enabled:
+            self.set_adapter(self.active_adapters)
+            self._disable_adapters = False
+        else:
+            # disable grads on all adapter layers
+            for layer_name in self.adapter_layer_names:
+                layer = getattr(self, layer_name)
+                layer.requires_grad_(False)
+            self._disable_adapters = True
+
+    def set_adapter(self, adapter_names: str | list[str]) -> None:
+        """Set the active adapter(s).
+
+        Additionally, this function will set the specified adapters to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str` or `List[str]`): Name of the adapter(s) to be activated.
+        """
+        if isinstance(adapter_names, str):
+            adapter_names = [adapter_names]
+
+        # Deactivate grads on the inactive adapter and activate grads on the active adapter
+        for layer_name in self.adapter_layer_names:
+            module_dict = getattr(self, layer_name)
+            for key, layer in module_dict.items():
+                if key in adapter_names:
+                    # Note: It is possible that not a single layer is called with requires_grad_(True) here. This may
+                    # happen if a completely different adapter layer is being activated.
+                    layer.requires_grad_(True)
+                else:
+                    layer.requires_grad_(False)
+
+        self._active_adapter = adapter_names
+
+    def _all_available_adapter_names(self) -> list[str]:
+        """Return a sorted list of all available adapter names"""
+        adapter_names = set()
+        for name in self.adapter_layer_names + self.other_param_names:
+            # we check each possible attribute and if it's a dict or ModuleDict, we assume that the keys are the adapter
+            # names
+            attr = getattr(self, name)
+            if hasattr(attr, "keys"):
+                adapter_names.update(attr.keys())
+        return sorted(adapter_names)
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Delete an adapter from the layer
+
+        This should be called on all adapter layers, or else we will get an inconsistent state.
+
+        This method will also set a new active adapter if the deleted adapter was an active adapter. It is important
+        that the new adapter is chosen in a deterministic way, so that the same adapter is chosen on all layers.
+
+        Args:
+            adapter_name (`str`): The name of the adapter to delete
+
+        """
+        for attr in self.adapter_layer_names + self.other_param_names:
+            if adapter_name in getattr(self, attr):
+                del getattr(self, attr)[adapter_name]
+
+        if adapter_name in self.active_adapters:
+            # choose a new active adapter
+            active_adapters = self.active_adapters[:]
+            active_adapters.remove(adapter_name)
+            if active_adapters:
+                self.set_adapter(active_adapters)
+            else:
+                # no active adapters left, set a new default adapter
+                # here we get the list of all adapters existing adapter names and choose the first one
+                remaining_adapters = self._all_available_adapter_names()
+                if not remaining_adapters:
+                    self.set_adapter([])
+                else:
+                    new_active_adapter = remaining_adapters[0]
+                    warnings.warn(
+                        f"Adapter {adapter_name} was active which is now deleted. Setting active adapter to "
+                        f"{new_active_adapter}."
+                    )
+                    self.set_adapter(remaining_adapters[0])
+
+    def _move_adapter_to_device_of_base_layer(self, adapter_name: str, device: Optional[torch.device] = None) -> None:
+        """
+        Move the adapter of the given name to the device of the base layer.
+        """
+        if device is None:
+            base_layer = self.get_base_layer()
+            if isinstance(base_layer, nn.MultiheadAttention):
+                base_layer = base_layer.out_proj
+            # check weight and qweight (for GPTQ)
+            for weight_name in ("weight", "qweight"):
+                weight = getattr(base_layer, weight_name, None)
+                if weight is not None:
+                    device = weight.device
+                    dtype = weight.dtype
+                    break
+            else:
+                # no break encountered: could not determine the device
+                return
+
+        meta = torch.device("meta")
+
+        # loop through all potential adapter layers and move them to the device of the base layer; be careful to only
+        # move this specific adapter to the device, as the other adapters could be on different devices
+        # see #1639
+        for adapter_layer_name in self.adapter_layer_names + self.other_param_names:
+            adapter_layer = getattr(self, adapter_layer_name, None)
+            if not isinstance(adapter_layer, (nn.ModuleDict, nn.ParameterDict, BufferDict)):
+                continue
+            if adapter_name not in adapter_layer:
+                continue
+            if any(p.device == meta for p in adapter_layer.parameters()):
+                continue
+
+            if weight.dtype.is_floating_point or weight.dtype.is_complex:
+                adapter_layer[adapter_name] = adapter_layer[adapter_name].to(device, dtype=dtype)
+            else:
+                adapter_layer[adapter_name] = adapter_layer[adapter_name].to(device)
+
+
+def _find_minimal_target_modules(
+    target_modules: list[str] | set[str], other_module_names: list[str] | set[str]
+) -> set[str]:
+    """Find the minimal set of target modules that is sufficient to separate them from the other modules.
+
+    Sometimes, a very large list of target_modules could be passed, which can slow down loading of adapters (e.g. when
+    loaded from diffusers). It may be possible to condense this list from hundreds of items to just a handful of
+    suffixes that are sufficient to distinguish the target modules from the other modules.
+
+    Example:
+        ```py
+        >>> from peft.tuners.tuners_utils import _find_minimal_target_modules
+
+        >>> target_modules = [f"model.decoder.layers.{i}.self_attn.q_proj" for i in range(100)]
+        >>> target_modules += [f"model.decoder.layers.{i}.self_attn.v_proj" for i in range(100)]
+        >>> other_module_names = [f"model.encoder.layers.{i}.self_attn.k_proj" for i in range(100)]
+        >>> _find_minimal_target_modules(target_modules, other_module_names)
+        {"q_proj", "v_proj"}
+        ```
+
+    Args:
+        target_modules (`list[str]` | `set[str]`):
+            The list of target modules.
+        other_module_names (`list[str]` | `set[str]`):
+            The list of other module names. They must not overlap with the target modules.
+
+    Returns:
+        `set[str]`:
+            The minimal set of target modules that is sufficient to separate them from the other modules.
+
+    Raises:
+        ValueError:
+            If `target_modules` is not a list or set of strings or if it contains an empty string. Also raises an error
+            if `target_modules` and `other_module_names` contain common elements.
+    """
+    if isinstance(target_modules, str) or not target_modules:
+        raise ValueError("target_modules should be a list or set of strings.")
+
+    target_modules = set(target_modules)
+    if "" in target_modules:
+        raise ValueError("target_modules should not contain an empty string.")
+
+    other_module_names = set(other_module_names)
+    if not target_modules.isdisjoint(other_module_names):
+        msg = (
+            "target_modules and other_module_names contain common elements, this should not happen, please "
+            "open a GitHub issue at https://github.com/huggingface/peft/issues with the code to reproduce this issue"
+        )
+        raise ValueError(msg)
+
+    # it is assumed that module name parts are separated by a "."
+    def generate_suffixes(s):
+        parts = s.split(".")
+        return [".".join(parts[i:]) for i in range(len(parts))][::-1]
+
+    # Create a reverse lookup for other_module_names to quickly check suffix matches
+    other_module_suffixes = {suffix for item in other_module_names for suffix in generate_suffixes(item)}
+
+    # Find all potential suffixes from target_modules
+    target_modules_suffix_map = {item: generate_suffixes(item) for item in target_modules}
+
+    # Initialize a set for required suffixes
+    required_suffixes = set()
+
+    # We sort the target_modules_suffix_map simply to get deterministic behavior, since sets have no order. In theory
+    # the order should not matter but in case there is a bug, it's better for the bug to be deterministic.
+    for item, suffixes in sorted(target_modules_suffix_map.items(), key=lambda tup: tup[1]):
+        # Go through target_modules items, shortest suffixes first
+        for suffix in suffixes:
+            # If the suffix is already in required_suffixes or matches other_module_names, skip it
+            if suffix in required_suffixes or suffix in other_module_suffixes:
+                continue
+            # Check if adding this suffix covers the item
+            if not any(item.endswith("." + req_suffix) for req_suffix in required_suffixes):
+                required_suffixes.add(suffix)
+                break
+
+    if not required_suffixes:
+        return set(target_modules)
+    return required_suffixes
+
+
+class _ExcludedModule:
+    """
+    A private helper method used to represent excluded modules in the check_target_module_exists function.
+    """
+
+    def __bool__(self):
+        return False
+
+
+def check_target_module_exists(config, key: str) -> bool | re.Match[str] | None:
+    """A helper method to check if the passed module's key name matches any of the target modules in the adapter_config.
+
+    Args:
+        config (`LoraConfig` | `LycorisConfig`): A config to match target modules from
+        key (`str`): A key to search any matches in config
+
+    Returns:
+        `bool` | `re.Match[str]` | `None`: True of match object if key matches any target modules from config, False or
+        None if no match found
+    """
+    if hasattr(config, "exclude_modules") and config.exclude_modules:
+        if isinstance(config.exclude_modules, str):
+            if re.fullmatch(config.exclude_modules, key):
+                return _ExcludedModule()
+        elif key in config.exclude_modules:
+            return _ExcludedModule()
+        elif any(key.endswith(f".{exclude_key}") for exclude_key in config.exclude_modules):
+            return _ExcludedModule()
+
+    if isinstance(config.target_modules, str):
+        target_module_found = re.fullmatch(config.target_modules, key)
+    elif key in config.target_modules:
+        # this module is specified directly in target_modules
+        target_module_found = True
+    else:
+        target_module_found = any(key.endswith(f".{target_key}") for target_key in config.target_modules)
+
+        layer_indexes = getattr(config, "layers_to_transform", None)
+        layers_pattern = getattr(config, "layers_pattern", None)
+
+        is_using_layer_indexes = layer_indexes is not None and (
+            len(layer_indexes) != 0 if isinstance(layer_indexes, list) else True
+        )
+        if is_using_layer_indexes and target_module_found:
+            layer_index = None
+            # TODO: It's still unclear how empty layers_pattern (None, [], or "") should behave
+            # For now, empty layers_pattern means any layer pattern is ok
+            if layers_pattern is None or len(layers_pattern) == 0:
+                layer_index = re.match(r".*\.[^.]*\.(\d+)\.", key)
+            else:
+                layers_pattern = [layers_pattern] if isinstance(layers_pattern, str) else layers_pattern
+                for pattern in layers_pattern:
+                    layer_index = re.match(rf".*\.{pattern}\.(\d+)\.", key)
+                    if layer_index is not None:
+                        break
+
+            if layer_index is None:
+                target_module_found = False
+            else:
+                layer_index = int(layer_index.group(1))
+                if isinstance(layer_indexes, int):
+                    target_module_found = layer_index == layer_indexes
+                else:
+                    target_module_found = layer_index in layer_indexes
+
+    return target_module_found
+
+
+def inspect_matched_modules(tuner: BaseTuner, adapter_name: str = "default") -> dict:
+    """
+    A helper function to inspect the set of matched and unmatched modules for a PEFT model and the given adapter.
+    """
+    config = tuner.peft_config[adapter_name]
+    key_list = [key for key, _ in tuner.model.named_modules()]
+    module_dict = {"matched": [], "unmatched": []}
+    for key in key_list:
+        if tuner._check_target_module_exists(config, key):
+            module_dict["matched"].append(key)
+        else:
+            module_dict["unmatched"].append(key)
+    return module_dict
+
+
+def _maybe_include_all_linear_layers(peft_config: PeftConfig, model: nn.Module) -> PeftConfig:
+    """
+    Helper function to update `target_modules` to all linear/Conv1D layers if provided as 'all-linear'. Adapted from
+    the QLoRA repository: https://github.com/artidoro/qlora/blob/main/qlora.py
+    """
+    if not hasattr(peft_config, "target_modules"):
+        return peft_config
+
+    # if `target_modules` is a string, convert to lower case and check if it matches "all-linear"
+    if not (
+        isinstance(peft_config.target_modules, str)
+        and peft_config.target_modules.lower() == INCLUDE_LINEAR_LAYERS_SHORTHAND
+    ):
+        return peft_config
+
+    linear_classes = (torch.nn.Linear, Conv1D)
+    linear_names = ("Linear",)
+    linear_module_names = set()
+    for name, module in model.named_modules():
+        # match with all linear classes.
+        if isinstance(module, linear_classes):
+            linear_module_names.add(name)
+        elif isinstance(module, BaseTunerLayer) and any(n in type(module).__name__ for n in linear_names):
+            # If the model already has adapter layers applied, then the "linear" layer is actually an adapter layer,
+            # e.g. lora.Linear, and not nn.Linear. To target this layer, we don't want to check the layer type, as there
+            # are many possible layer types (one for each PEFT method) and the list would quickly get out of date. Thus
+            # we rely on the name of the layer class, which by convention is something like "Linear", "Linear4bit",
+            # "HqqLoraLinear", ... in PEFT. It's not pretty but should generally work.
+            # See 2390
+            linear_module_names.add(name)
+
+    # Try to remove linear layers that should not be targeted as best as possible. We have to rely on convention as
+    # there are no hard rules to detect these modules.
+    module_names_to_exclude = set()
+    if isinstance(model, PreTrainedModel):
+        output_emb = model.get_output_embeddings()
+        if output_emb is not None:
+            # ignore the last classification head for text generation models
+            last_module_name = [name for name, module in model.named_modules() if module is output_emb][0]
+            module_names_to_exclude.add(last_module_name)
+        elif peft_config.task_type == TaskType.SEQ_CLS:
+            # ignore classifier head for classification models (issue 2027)
+            # there is no fix name for the classifier head, so check the common ones
+            for name in SEQ_CLS_HEAD_NAMES:
+                cls_head = getattr(model, name, None)
+                if cls_head is not None:
+                    last_module_name = [name for name, module in model.named_modules() if module is cls_head][0]
+                    module_names_to_exclude.add(last_module_name)
+                    break
+
+    # we don't want nested LoRA layers, i.e. LoRA being applied to possibly existing lora_A, lora_B, etc.
+    # see 2390
+    for prefix, module in model.named_modules():
+        if isinstance(module, BaseTunerLayer):
+            for suffix, child in module.named_modules():
+                if suffix:
+                    module_names_to_exclude.add(f"{prefix}.{suffix}")
+
+    linear_module_names -= module_names_to_exclude
+    peft_config.target_modules = linear_module_names
+    return peft_config
+
+
+def check_adapters_to_merge(module: BaseTunerLayer, adapter_names: Optional[list[str]] = None) -> list[str]:
+    """
+    Helper function to check which adapters should be merged.
+
+    Only return those adapters that are not already merged. Give a warning if some or all of the adapters are already
+    merged.
+
+    """
+    if adapter_names is None:
+        adapter_names = module.active_adapters
+    if isinstance(adapter_names, str):
+        raise ValueError(f"adapter_names should be a list of strings, got {adapter_names!r}.")
+
+    if module.merged:
+        merged_adapters = set(module.merged_adapters)
+        adapter_names = [name for name in adapter_names if name not in merged_adapters]
+
+        if adapter_names:
+            warnings.warn(
+                f"Already following adapters were merged {','.join(module.merged_adapters)}. "
+                f"You are now additionally merging {','.join(adapter_names)}."
+            )
+        else:
+            warnings.warn("All adapters are already merged, nothing to do.")
+
+    return adapter_names
+
+
+def clone_module(module: nn.Module, share_weights=False):
+    """Clone a module in a pytorch model.
+
+    Clones a module of a model, optionally sharing all the parameters between the original and the clone. Simplifies
+    reusing a module when manipulating the architecture of a model.
+    """
+    clone = copy.deepcopy(module)
+
+    def _share_weights(src: nn.Module, dst: nn.Module):
+        for name, param in src.named_parameters(recurse=False):
+            dst.register_parameter(name, param)
+
+    if share_weights:
+        for name, submodule in module.named_modules():
+            _share_weights(submodule, clone.get_submodule(name))
+
+    return clone
+
+
+def replicate_layers(model: nn.Module, layer_map: list[tuple[int, int]]):
+    """Replicate layers in a transfomer model with weight sharing.
+
+    This function looks for a module list attribute at model[(.model)*].layers and replicates the layers in the module
+    list according to the layer map. For example the map `[[0, 4], [2, 5]]` will take the set of layers `[0, 1, 2, 3,
+    4]` and replace them with a module list containing `[0, 1, 2, 3, 2, 3, 4]`.
+    """
+    while hasattr(model, "model"):
+        model = model.model
+    # Some variants of the bert model nest the main model under the bert attribute.
+    if hasattr(model, "bert"):
+        model = model.bert
+
+    model_type = None
+    layers: nn.ModuleList = None
+    if hasattr(model, "layers"):
+        model_type = "llama"
+        layers = model.layers
+    elif hasattr(model, "encoder") and hasattr(model.encoder, "layer"):
+        model_type = "bert"
+        layers = model.encoder.layer
+    elif hasattr(model, "h"):
+        model_type = "falcon"
+        layers = model.h
+    if not model_type or not isinstance(layers, nn.ModuleList):
+        raise ValueError(
+            "Could not locate the layers attribute in the model. "
+            "Expected Llama, Bert or Falcon compatible architectures."
+        )
+
+    new_layers = []
+    for start, end in layer_map:
+        for i in range(start, end):
+            current_idx = len(new_layers)
+            new_layers.append(clone_module(layers[i], share_weights=True))
+            # This is a hack needed to work around the layer_idx introduced in HF transformers.
+            for submodule in new_layers[-1].modules():
+                if hasattr(submodule, "layer_idx"):
+                    submodule.layer_idx = current_idx
+    layers = nn.ModuleList(new_layers)
+    if model_type == "llama":
+        model.layers = layers
+    elif model_type == "bert":
+        model.encoder.layer = layers
+    elif model_type == "falcon":
+        model.h = layers
+    else:
+        raise ValueError("Unexpected model type, need to handle post-processing of layers.")
+    if hasattr(model.config, "num_hidden_layers"):  # Common to Llama, Bert, Falcon.
+        model.config.num_hidden_layers = len(new_layers)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e71a08461e8b7cb2fb5513a3bf908a4a98c0747
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/__init__.py
@@ -0,0 +1,24 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import VBLoRAConfig
+from .layer import Linear, VBLoRALayer
+from .model import VBLoRAModel
+
+
+__all__ = ["Linear", "VBLoRAConfig", "VBLoRALayer", "VBLoRAModel"]
+
+register_peft_method(name="vblora", config_cls=VBLoRAConfig, model_cls=VBLoRAModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..4b951c60f0d1d04f9f70b1a5c1bcb64a7790fea1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/config.py
@@ -0,0 +1,196 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class VBLoRAConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`VBLoRAConfig`].
+
+    Paper: https://arxiv.org/abs/2405.15179
+
+    Args:
+        r (`int`):
+            The rank of incremental matrices.
+        num_vectors (`int`):
+            Number of vectors in the vector bank. Use higher values when the model size increases.
+        vector_length (`int`):
+            The length of the vectors in the vector bank. The length of the vectors should be divisible by the hidden
+            dimension of the model.
+        topk (`int`):
+            The K value for top-K selection. A larger value of K increases the size of the saved model. In practice,
+            setting K=2 typically provides the best performance and parameter efficiency. For more details, refer to
+            the discussion in the paper.
+        target_modules (`Union[List[str], str]`):
+            The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
+            names will be replaced. When passing a string, a regex match will be performed. When passing a list of
+            strings, either an exact match will be performed or it is checked if the name of the module ends with any
+            of the passed strings. If this is specified as 'all-linear', then all linear/Conv1D modules are chosen,
+            excluding the output layer. If this is not specified, modules will be chosen according to the model
+            architecture. If the architecture is not known, an error will be raised -- in this case, you should specify
+            the target modules manually.
+        exclude_modules (`Optional[Union[List[str], str]]`):
+            The names of the modules to not apply the adapter. When passing a string, a regex match will be performed.
+            When passing a list of strings, either an exact match will be performed or it is checked if the name of the
+            module ends with any of the passed strings.
+        save_only_topk_weights (`bool`):
+            Whether to only save the topk weights. Setting `save_only_topk_weights = True` significantly reduces
+            storage space. However, models saved in this mode can be used for merging or inference only, not for
+            resuming training.
+        vblora_dropout (`float`):
+            The dropout probability for VBLoRA layers.
+        fan_in_fan_out (`bool`):
+            Set this to True if the layer to replace stores weight like (fan_in, fan_out). For example, gpt-2 uses
+            `Conv1D` which stores weights like (fan_in, fan_out) and hence this should be set to `True`.
+        bias (`str`):
+            Bias type for VBLoRA. Can be 'none', 'all' or 'vblora_only'. If 'all' or 'vblora_only', the corresponding
+            biases will be updated during training. Be aware that this means that, even when disabling the adapters,
+            the model will not produce the same output as the base model would have without adaptation.
+        modules_to_save (`List[str]`):
+            List of modules apart from VBLoRA layers to be set as trainable and saved in the final checkpoint.
+        init_vector_bank_bound (`float`):
+            The vector bank is initialized with a uniform distribution between -init_vector_bank_bound and
+            init_vector_bank_bound. Avoid initializing the vector bank with all zeros to prevent zero gradients. A
+            small value, such as 0.02, is typically effective. Initializing with a large value may cause training
+            instability.
+        init_logits_std (`float`):
+            The logits are initialized with a normal distribution with a standard deviation of init_logits_std. Default
+            is 0.1.
+        layers_to_transform (`Union[List[int],int]`):
+            The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
+            that are specified in this list. If a single integer is passed, it will apply the transformations on the
+            layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`. This should target the
+            `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`.
+    """
+
+    r: int = field(default=4, metadata={"help": "The rank of incremental matrices."})
+    num_vectors: int = field(
+        default=256,
+        metadata={"help": "Number of vectors in the vector bank. Use higher values when the model size increases."},
+    )
+    vector_length: int = field(
+        default=256,
+        metadata={
+            "help": "The length of the vectors in the vector bank. The length of the vectors should be divisible by "
+            "the hidden dimension of the model."
+        },
+    )
+    topk: int = field(
+        default=2,
+        metadata={
+            "help": "The K value for top-K selection. A larger value of K increases the size of the saved model. "
+            "In practice, setting K=2 typically provides the best performance and parameter efficiency. "
+            "For more details, refer to the discussion in the paper."
+        },
+    )
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of module names or regex expression of the module names to replace with LoRA."
+                "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$'."
+                "This can also be a wildcard 'all-linear' which matches all linear/Conv1D layers except the output layer."
+                "If not specified, modules will be chosen according to the model architecture, If the architecture is "
+                "not known, an error will be raised -- in this case, you should specify the target modules manually."
+            )
+        },
+    )
+    exclude_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={"help": "List of module names or regex expression of the module names to exclude from VBLoRA."},
+    )
+    save_only_topk_weights: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "Whether to only save the topk weights. Setting `save_only_topk_weights = True` significantly reduces "
+                "storage space. However, models saved in this mode can be used for merging or inference only, not for "
+                "resuming training."
+            )
+        },
+    )
+    vblora_dropout: float = field(default=0.0, metadata={"help": "VBLoRA dropout"})
+    fan_in_fan_out: bool = field(
+        default=False,
+        metadata={"help": "Set this to True if the layer to replace stores weight like (fan_in, fan_out)"},
+    )
+    bias: str = field(default="none", metadata={"help": "Bias type for VBLoRA. Can be 'none', 'all' or 'vblora_only'"})
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of modules apart from VBLoRA layers to be set as trainable and saved in the final checkpoint. For"
+                " example, in Sequence Classification or Token Classification tasks, the final layer"
+                " `classifier/score` are randomly initialized and as such need to be trainable and saved."
+            )
+        },
+    )
+    init_vector_bank_bound: float = field(
+        default=0.02,
+        metadata={
+            "help": (
+                "The vector bank is initialized with a uniform distribution between -init_vector_bank_bound and"
+                " init_vector_bank_bound. Avoid initializing the vector bank with all zeros to prevent zero gradients."
+                " A small value, such as 0.02, is typically effective. Initializing with a large value may cause"
+                " training instability."
+            ),
+        },
+    )
+    init_logits_std: float = field(
+        default=0.1,
+        metadata={
+            "help": (
+                "The logits are initialized with a normal distribution with a standard deviation of init_logits_std. "
+                "Default value 0.1 typically works well."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers indexes that are specified inside this list. If a single integer is passed, PEFT will transform only the layer at this index. "
+            "This only works when target_modules is a list of str. This should target the `nn.ModuleList` of the "
+            "model, which is often called `'layers'` or `'h'`."
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer pattern is not in the common layers pattern."
+            "This only works when target_modules is a list of str."
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.VBLORA
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        self.exclude_modules = (
+            set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
+        )
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..1db8035dd980c775c6dafa1fc23d361da4c234f7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/layer.py
@@ -0,0 +1,249 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from typing import List, Optional, Tuple
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+from peft.utils.other import transpose
+
+
+class VBLoRALayer(BaseTunerLayer):
+    # List all names of layers that may contain adapter weights
+    adapter_layer_names = ("vblora_logits_A", "vblora_logits_B", "vblora_vector_bank")
+
+    def __init__(self, base_layer: nn.Module, **kwargs):
+        self.base_layer = base_layer
+        self.r = {}
+        self.topk = {}
+        self.vblora_dropout = nn.ModuleDict({})
+
+        # For storing vector scale
+        self.vblora_logits_A = nn.ParameterDict({})
+        self.vblora_logits_B = nn.ParameterDict({})
+
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, Conv1D):
+            in_features, out_features = (
+                base_layer.weight.ds_shape if hasattr(base_layer.weight, "ds_shape") else base_layer.weight.shape
+            )
+
+        self.in_features = in_features
+        self.out_features = out_features
+        self.kwargs = kwargs
+
+    @property
+    def merged(self) -> bool:
+        return bool(self.merged_adapters)
+
+    def update_layer(
+        self,
+        adapter_name: str,
+        vblora_vector_bank,
+        r: int,
+        topk: int,
+        num_vectors: int,
+        vector_length: float,
+        vblora_dropout: float = 0.0,
+        init_logits_std: float = 0.01,
+    ):
+        if r <= 0:
+            raise ValueError(f"`r` {r} should be a positive integer value")
+        if topk <= 0:
+            raise ValueError(f"`topk` {topk} should be a positive integer value")
+
+        if self.in_features % vector_length != 0:
+            raise ValueError(f"`in_features` {self.in_features} must be divisible by `vector_length` {vector_length}")
+        if self.out_features % vector_length != 0:
+            raise ValueError(
+                f"`out_features` {self.out_features} must be divisible by `vector_length` {vector_length}"
+            )
+
+        self.r[adapter_name] = r
+        self.topk[adapter_name] = topk
+        if vblora_dropout > 0.0:
+            vblora_dropout_layer = nn.Dropout(p=vblora_dropout)
+        else:
+            vblora_dropout_layer = nn.Identity()
+        self.vblora_dropout.update(nn.ModuleDict({adapter_name: vblora_dropout_layer}))
+        self.vblora_logits_A[adapter_name] = nn.Parameter(
+            torch.zeros(r, self.in_features // vector_length, num_vectors), requires_grad=True
+        )
+        self.vblora_logits_B[adapter_name] = nn.Parameter(
+            torch.zeros(self.out_features // vector_length, r, num_vectors), requires_grad=True
+        )
+        self.vblora_vector_bank = vblora_vector_bank
+        self.reset_vblora_logits(adapter_name, init_logits_std)
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_vblora_logits(self, adapter_name, init_logits_std):
+        if adapter_name in self.vblora_logits_A.keys():
+            with torch.no_grad():
+                nn.init.normal_(self.vblora_logits_A[adapter_name], 0, init_logits_std)
+                nn.init.normal_(self.vblora_logits_B[adapter_name], 0, init_logits_std)
+
+
+class Linear(nn.Linear, VBLoRALayer):
+    # VBLoRA implemented in a dense layer
+    def __init__(
+        self,
+        base_layer,
+        vblora_vector_bank,
+        adapter_name: str,
+        r: int,
+        num_vectors: int,
+        vector_length: int,
+        topk: int = 2,
+        vblora_dropout: float = 0.0,
+        init_logits_std: float = 0.01,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        is_target_conv_1d_layer: bool = False,
+        **kwargs,
+    ) -> None:
+        # this gets the init from nn.Linear's super perspective, i.e. nn.Module.__init__, which should always be called
+        super(nn.Linear, self).__init__()
+        VBLoRALayer.__init__(self, base_layer, **kwargs)
+        self.fan_in_fan_out = fan_in_fan_out
+        self._active_adapter = adapter_name
+        self.update_layer(
+            adapter_name, vblora_vector_bank, r, topk, num_vectors, vector_length, vblora_dropout, init_logits_std
+        )
+        self.is_target_conv_1d_layer = is_target_conv_1d_layer
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.vblora_logits_A.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+                    orig_weights += self.get_delta_weight(active_adapter)
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+                    base_layer.weight.data = orig_weights
+                else:
+                    base_layer.weight.data += self.get_delta_weight(active_adapter)
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.vblora_logits_A.keys():
+                self.get_base_layer().weight.data -= self.get_delta_weight(active_adapter)
+
+    def _get_low_rank_matrix(self, logits: torch.tensor, vblora_vector_bank, topk) -> torch.Tensor:
+        top_k_logits, indices = logits.topk(topk, dim=-1)
+        topk_weights = F.softmax(top_k_logits, dim=-1)
+        return (topk_weights.unsqueeze(-1) * vblora_vector_bank[indices]).sum(-2)
+
+    def _get_lora_matrices(self, adapter, cast_to_fp32=False) -> Tuple[torch.Tensor, torch.Tensor]:
+        vblora_logits_A = self.vblora_logits_A[adapter]
+        vblora_logits_B = self.vblora_logits_B[adapter]
+
+        # Check for infinity values when training. If found, training was likely resumed from a `save_only_topk_weights` model.
+        if self.training and vblora_logits_A[0, 0].isinf().any():
+            raise RuntimeError(
+                "Found infinity values in VB-LoRA logits. Ensure training was not resumed from a `save_only_topk_weights` model."
+            )
+
+        vblora_vector_bank = self.vblora_vector_bank[adapter].to(vblora_logits_A.device)
+        topk = self.topk[adapter]
+        # In case users wants to merge the adapter weights that are in
+        # float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # float16 because the `@` and matmul operation in general is not supported in torch + cpu + fp16.
+        if cast_to_fp32:
+            vblora_logits_A = vblora_logits_A.float()
+            vblora_logits_B = vblora_logits_B.float()
+            vblora_vector_bank = vblora_vector_bank.float()
+
+        # A: (rank, in_tile, vector_length) -> (rank, in_tile x vector_length)
+        A = self._get_low_rank_matrix(vblora_logits_A, vblora_vector_bank, topk).reshape(vblora_logits_A.shape[0], -1)
+        # B: (out_tile, rank, vector_length) -> (out_tile, vector_length, rank) -> (out_tile x vector_length, rank)
+        B = (
+            self._get_low_rank_matrix(vblora_logits_B, vblora_vector_bank, topk)
+            .transpose(1, 2)
+            .reshape(-1, vblora_logits_B.shape[1])
+        )
+        return A, B
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        device = self.vblora_logits_A[adapter].device
+        dtype = self.vblora_logits_A[adapter].dtype
+        cast_to_fp32 = device.type == "cpu" and dtype == torch.float16
+        A, B = self._get_lora_matrices(adapter, cast_to_fp32)
+        output_tensor = transpose(B @ A, self.fan_in_fan_out)
+        return output_tensor
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        previous_dtype = x.dtype
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.vblora_logits_A.keys():
+                    continue
+                A, B = self._get_lora_matrices(active_adapter)
+                x = x.to(self.vblora_vector_bank[active_adapter].dtype)
+                dropout = self.vblora_dropout[active_adapter]
+                result = result + F.linear(F.linear(dropout(x), A), B)
+        result = result.to(previous_dtype)
+        return result
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f409e3d5d3983f5ac6be782c6d0cf269dfe887e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vblora/model.py
@@ -0,0 +1,449 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from dataclasses import asdict
+from enum import Enum
+from typing import Optional
+
+import torch
+import torch.nn as nn
+from tqdm import tqdm
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING, ModulesToSaveWrapper, _get_submodules
+
+from .config import VBLoRAConfig
+from .layer import Linear, VBLoRALayer
+
+
+class VBLoRAModel(BaseTuner):
+    """
+    Creates VBLoRA model from a pretrained transformers model.
+
+    The method is described in detail in https://arxiv.org/abs/2405.15179.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): The model to be adapted.
+        config ([`VBLoRAConfig`]): The configuration of the VBLoRA model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The VBLoRA model.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import VBLoRAConfig, get_peft_model
+
+        >>> base_model = AutoModelForCausalLM.from_pretrained("facebook/opt-125m")
+        >>> config = VBLoRAConfig(
+        ...     task_type="SEQ_CLS",
+        ...     r=4,
+        ...     target_modules=["fc1", "fc2", "k_proj", "out_proj", "q_proj", "v_proj"],
+        ...     num_vectors=60,
+        ...     vector_length=256,
+        ...     save_only_topk_weights=True,
+        ... )
+        >>> model = get_peft_model(base_model, config)
+        ```
+
+    **Attributes**:
+        - **model** ([`~transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`VBLoRAConfig`]): The configuration of the VBLoRAConfig model.
+    """
+
+    prefix: str = "vblora_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False) -> None:
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def _init_vblora_vector_bank(self, config: VBLoRAConfig, adapter_name: str) -> None:
+        vblora_vector_bank = torch.zeros(config.num_vectors, config.vector_length)
+        torch.nn.init.uniform_(vblora_vector_bank, -config.init_vector_bank_bound, config.init_vector_bank_bound)
+        self.vblora_vector_bank[adapter_name] = vblora_vector_bank
+
+    def _pre_injection_hook(self, model: nn.Module, config: VBLoRAConfig, adapter_name: str) -> None:
+        self.vblora_vector_bank = nn.ParameterDict({})
+
+    def _check_new_adapter_config(self, config: VBLoRAConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # the below todo is copied from LoRA
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+    @staticmethod
+    def _check_target_module_exists(vblora_config, key):
+        return check_target_module_exists(vblora_config, key)
+
+    def _create_and_replace(
+        self,
+        vblora_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+
+        bias = hasattr(target, "bias") and target.bias is not None
+        kwargs = {
+            "fan_in_fan_out": vblora_config.fan_in_fan_out,
+            "bias": bias,
+        }
+        self._init_vblora_vector_bank(vblora_config, adapter_name)
+        # TODO: add quantization support
+
+        if isinstance(target, Linear):
+            target.update_layer(
+                adapter_name=adapter_name,
+                vblora_vector_bank=self.vblora_vector_bank,
+                r=vblora_config.r,
+                topk=vblora_config.topk,
+                num_vectors=vblora_config.num_vectors,
+                vector_length=vblora_config.vector_length,
+                vblora_dropout=vblora_config.vblora_dropout,
+                init_logits_std=vblora_config.init_logits_std,
+            )
+        else:
+            new_module = self._create_new_module(
+                vblora_config=vblora_config,
+                vblora_vector_bank=self.vblora_vector_bank,
+                adapter_name=adapter_name,
+                target=target,
+                **kwargs,
+            )
+            if adapter_name not in self.active_adapter:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+
+    @staticmethod
+    def _replace_module(parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if "vblora_" in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "vblora_only":
+                for m in model.modules():
+                    if isinstance(m, VBLoRALayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(vblora_config, vblora_vector_bank, adapter_name, target, **kwargs):
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if isinstance(target_base_layer, torch.nn.Linear):
+            if kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                    "Setting fan_in_fan_out to False."
+                )
+                kwargs["fan_in_fan_out"] = vblora_config.fan_in_fan_out = False
+        elif isinstance(target_base_layer, Conv1D):
+            kwargs["is_target_conv_1d_layer"] = True
+            if not kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to False but the target module is `Conv1D`. Setting fan_in_fan_out to True."
+                )
+                kwargs["fan_in_fan_out"] = vblora_config.fan_in_fan_out = True
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. Currently, only the following modules are supported: "
+                "`torch.nn.Linear`, `transformers.pytorch_utils.Conv1D`."
+            )
+        new_module = Linear(
+            base_layer=target,
+            vblora_vector_bank=vblora_vector_bank,
+            adapter_name=adapter_name,
+            r=vblora_config.r,
+            num_vectors=vblora_config.num_vectors,
+            vector_length=vblora_config.vector_length,
+            topk=vblora_config.topk,
+            vblora_dropout=vblora_config.vblora_dropout,
+            init_logits_std=vblora_config.init_logits_std,
+            **kwargs,
+        )
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled: bool = True) -> None:
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self) -> None:
+        """Enable all adapters.
+
+        Call this if you have previously disabled all adapters and want to re-enable them.
+        """
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self) -> None:
+        """Disable all adapters.
+
+        When disabling all adapters, the model output corresponds to the output of the base model.
+        """
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name: str | list[str]) -> None:
+        """Set the active adapter(s).
+
+        Additionally, this function will set the specified adapters to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_name (`str` or `list[str]`): Name of the adapter(s) to be activated.
+        """
+        for module in self.model.modules():
+            if isinstance(module, VBLoRALayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                setattr(parent, target_name, target.modules_to_save[target.active_adapter])
+
+        return self.model
+
+    def delete_adapter(self, adapter_name: str) -> None:
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        key_list = [key for key, _ in self.model.named_modules() if self.prefix not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, VBLoRALayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapter[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ) -> torch.nn.Module:
+        r"""
+        This method merges the VBLoRA layers into the base model. This is needed if someone wants to use the base model
+        as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`list[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import PeftModel
+
+        >>> base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-40b")
+        >>> peft_model_id = "smangrul/falcon-40B-int4-peft-lora-sfttrainer-sample"
+        >>> model = PeftModel.from_pretrained(base_model, peft_model_id)
+        >>> merged_model = model.merge_and_unload()
+        ```
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self):
+        """
+        Gets back the base model by removing all the VBLoRA modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
+
+    def get_nb_savable_parameters(self, adapter="default") -> tuple[int, int]:
+        r"""
+        Returns the number of savable VB-LoRA parameters and other savable parameters.
+        """
+        logits_params = 0
+        vector_bank_params = 0
+        other_params = 0
+        for name, param in self.named_parameters():
+            if "vblora_logits" in name:
+                logits_params += param.numel()
+            elif "vblora_vector_bank" in name:
+                vector_bank_params += param.numel()
+            elif param.requires_grad:
+                other_params += param.numel()
+        if self.peft_config[adapter].save_only_topk_weights:
+            num_vectors = self.peft_config[adapter].num_vectors
+            factor = 1  # factor to count float32-equivalent parameters
+            if num_vectors < 2**8:
+                factor = 0.25
+            elif num_vectors < 2**15:
+                factor = 0.5
+            elif num_vectors < 2**31:
+                factor = 1
+            else:
+                factor = 2
+            topk_weight_params = (
+                logits_params / self.peft_config[adapter].num_vectors * (self.peft_config[adapter].topk - 1)
+            )
+            topk_indices_params = (
+                logits_params / self.peft_config[adapter].num_vectors * self.peft_config[adapter].topk * factor
+            )
+            vblora_params = int(vector_bank_params + topk_weight_params + topk_indices_params)
+        else:
+            vblora_params = vector_bank_params + logits_params
+        return vblora_params, other_params
+
+    def print_savable_parameters(self) -> None:
+        r"""
+        Prints the number of savable VB-LoRA parameters and total savable parameters.
+        """
+        vblora_params, other_params = self.get_nb_savable_parameters()
+        print(
+            f"VB-LoRA params to-be-saved (float32-equivalent): {vblora_params:,d} "
+            f"|| total params to-be-saved: {(vblora_params + other_params):,d}"
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..25c4a96619524bfdcd41a8f7df331533ba370782
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/__init__.py
@@ -0,0 +1,40 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.utils import register_peft_method
+
+from .config import VeraConfig
+from .layer import Linear, VeraLayer
+from .model import VeraModel
+
+
+__all__ = ["Linear", "VeraConfig", "VeraLayer", "VeraModel"]
+
+
+register_peft_method(name="vera", config_cls=VeraConfig, model_cls=VeraModel, prefix="vera_lambda_")
+
+
+def __getattr__(name):
+    if (name == "Linear8bitLt") and is_bnb_available():
+        from .bnb import Linear8bitLt
+
+        return Linear8bitLt
+
+    if (name == "Linear4bit") and is_bnb_4bit_available():
+        from .bnb import Linear4bit
+
+        return Linear4bit
+
+    raise AttributeError(f"module {__name__} has no attribute {name}")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/bnb.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/bnb.py
new file mode 100644
index 0000000000000000000000000000000000000000..71d20e4b1163ab9cc93b7b33c2aa022ddd3eb11f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/bnb.py
@@ -0,0 +1,411 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from typing import Optional
+
+import bitsandbytes as bnb
+import torch
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.tuners.tuners_utils import check_adapters_to_merge
+from peft.utils.integrations import dequantize_bnb_weight
+from peft.utils.other import transpose
+
+from .layer import VeraLayer
+
+
+if is_bnb_available():
+
+    class Linear8bitLt(torch.nn.Module, VeraLayer):
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            vera_A,
+            vera_B,
+            r: int = 0,
+            vera_dropout: float = 0.0,
+            fan_in_fan_out: bool = False,
+            init_weights: bool = True,
+            d_initial: float = 0.1,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            VeraLayer.__init__(self, base_layer)
+            self.fan_in_fan_out = fan_in_fan_out
+
+            self._active_adapter = adapter_name
+            self.update_layer(
+                adapter_name,
+                vera_A,
+                vera_B,
+                r,
+                vera_dropout=vera_dropout,
+                init_weights=init_weights,
+                d_initial=d_initial,
+            )
+
+        def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+            if self.merged:
+                warnings.warn(
+                    f"Already following adapters were merged {','.join(self.merged_adapters)}. "
+                    f"You are now additionally merging {','.join(self.active_adapters)}."
+                )
+
+            adapter_names = check_adapters_to_merge(self, adapter_names)
+            if not adapter_names:
+                return
+
+            for active_adapter in adapter_names:
+                if active_adapter not in self.vera_lambda_d.keys():
+                    continue
+
+                warnings.warn(
+                    "Merge vera module to 8-bit linear may get different generations due to rounding errors."
+                )
+                vera_data = self.get_delta_weight(active_adapter)
+
+                weight = self.get_base_layer().weight
+                state = self.get_base_layer().state
+                if state.SCB is None:
+                    state.SCB = weight.SCB
+
+                output = dequantize_bnb_weight(weight, state)
+                w_data = output.to(vera_data.dtype).to(vera_data.device) + vera_data
+
+                if safe_merge and not torch.isfinite(w_data).all():
+                    raise ValueError(
+                        f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                    )
+
+                self.get_base_layer().weight = bnb.nn.Int8Params(
+                    w_data.to("cpu"), requires_grad=False, has_fp16_weights=weight.has_fp16_weights
+                ).to(weight.device)
+                state.reset_grads()
+                self.merged_adapters.append(active_adapter)
+
+        def unmerge(self) -> None:
+            if not self.merged:
+                warnings.warn("Already unmerged. Nothing to do")
+                return
+
+            while len(self.merged_adapters) > 0:
+                active_adapter = self.merged_adapters.pop()
+                if active_adapter not in self.vera_lambda_d.keys():
+                    continue
+                warnings.warn(
+                    "Unmerge vera module to 8-bit linear may get different generations due to rounding errors."
+                )
+                vera_data = self.get_delta_weight(active_adapter)
+
+                weight = self.get_base_layer().weight
+                state = self.get_base_layer().state
+                if state.SCB is None:
+                    state.SCB = weight.SCB
+                output = dequantize_bnb_weight(weight, state=state)
+
+                w_data = output.to(vera_data.dtype).to(vera_data.device) - vera_data
+
+                self.get_base_layer().weight = bnb.nn.Int8Params(
+                    w_data.to("cpu"), requires_grad=False, has_fp16_weights=weight.has_fp16_weights
+                ).to(weight.device)
+                state.reset_grads()
+
+        def get_delta_weight(self, adapter) -> torch.Tensor:
+            """
+            Compute the delta weight for the given adapter.
+
+            Args:
+                adapter (str): The name of the adapter for which the delta weight should be computed.
+
+            Returns:
+                torch.Tensor: The computed delta weight for the VeRA adapter.
+
+            Note:
+                This method implements the VeRA-specific weight update. Unlike LoRA, VeRA uses shared projection
+                matrices (vera_A and vera_B) across all layers, along with per-layer trainable parameters (lambda_d and
+                lambda_b).
+            """
+            # Retrieve shared projection matrices
+            vera_A = self.vera_A[adapter]
+            vera_B = self.vera_B[adapter]
+
+            # Retrieve per-layer trainable parameters
+            device = vera_B.device
+            dtype = vera_B.dtype
+
+            # In case users wants to merge the adapter weights that are in
+            # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+            # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+            cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+            lambda_d = self.vera_lambda_d[adapter]
+            lambda_b = self.vera_lambda_b[adapter]
+
+            if cast_to_fp32:
+                vera_A = vera_A.float()
+                vera_B = vera_B.float()
+                lambda_d = lambda_d.float()
+                lambda_b = lambda_b.float()
+
+            sliced_A = vera_A[:, : self.in_features].to(lambda_d.device)
+            sliced_B = vera_B[: self.out_features, :].to(lambda_d.device)
+            lambda_b = lambda_b.unsqueeze(-1)
+            lambda_d = lambda_d.unsqueeze(-1)
+
+            # VeRA-specific computation:
+            # 1. Apply lambda_d to the input projection (vera_A)
+            # 2. Apply lambda_b to the output projection (vera_B)
+            # 3. Compute the outer product of the scaled projections
+            output_tensor = transpose((lambda_b * sliced_B) @ (lambda_d * sliced_A), self.fan_in_fan_out)
+
+            if cast_to_fp32:
+                output_tensor = output_tensor.to(dtype=dtype)
+
+            return output_tensor
+
+        def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+            """
+            Perform the forward pass using the VeRA adapter.
+
+            Args:
+                x (torch.Tensor): Input tensor.
+
+            Returns:
+                torch.Tensor: Output tensor after applying the VeRA adaptation.
+
+            Note:
+                This method implements the VeRA-specific forward pass. It applies the shared projections (vera_A and
+                vera_B) along with the per-layer trainable parameters (lambda_d and lambda_b) to compute the adapter
+                output.
+            """
+            if self.disable_adapters:
+                if self.merged:
+                    self.unmerge()
+                result = self.base_layer(x, *args, **kwargs)
+            elif self.merged:
+                result = self.base_layer(x, *args, **kwargs)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+                for active_adapter in self.active_adapters:
+                    if active_adapter not in self.vera_lambda_d.keys():
+                        continue
+
+                    lambda_d = self.vera_lambda_d[active_adapter]
+                    lambda_b = self.vera_lambda_b[active_adapter]
+
+                    vera_A = self.vera_A[active_adapter]
+                    vera_B = self.vera_B[active_adapter]
+
+                    dropout = self.vera_dropout[active_adapter]
+
+                    requires_conversion = not torch.is_autocast_enabled()
+                    if requires_conversion:
+                        expected_dtype = result.dtype
+                        compute_dtype = lambda_d.dtype
+                        if x.dtype != compute_dtype:
+                            x = x.to(compute_dtype)
+
+                    sliced_A = vera_A[:, : self.in_features].to(x.device)
+                    sliced_B = vera_B[: self.out_features, :].to(x.device)
+
+                    x_temp = dropout(x.to(lambda_d.dtype))
+
+                    adapter_output = lambda_b * torch.nn.functional.linear(
+                        lambda_d * torch.nn.functional.linear(x_temp, sliced_A), sliced_B
+                    )
+
+                    if requires_conversion:
+                        adapter_output = adapter_output.to(expected_dtype)
+
+                    result = result + adapter_output
+
+            # Ensure the output tensor has the same dtype as the input tensor
+            return result.to(x.dtype)
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "vera." + rep
+
+
+if is_bnb_4bit_available():
+
+    class Linear4bit(torch.nn.Module, VeraLayer):
+        def __init__(
+            self,
+            base_layer: torch.nn.Module,
+            adapter_name: str,
+            vera_A,
+            vera_B,
+            r: int = 0,
+            vera_dropout: float = 0.0,
+            fan_in_fan_out: bool = False,
+            init_weights: bool = True,
+            d_initial: float = 0.1,
+            **kwargs,
+        ) -> None:
+            super().__init__()
+            VeraLayer.__init__(self, base_layer)
+            self.fan_in_fan_out = fan_in_fan_out
+
+            self._active_adapter = adapter_name
+            self.update_layer(
+                adapter_name,
+                vera_A,
+                vera_B,
+                r,
+                vera_dropout=vera_dropout,
+                init_weights=init_weights,
+                d_initial=d_initial,
+            )
+
+        def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
+            if self.merged:
+                warnings.warn(
+                    f"Already following adapters were merged {','.join(self.merged_adapters)}. "
+                    f"You are now additionally merging {','.join(self.active_adapters)}."
+                )
+
+            adapter_names = check_adapters_to_merge(self, adapter_names)
+            if not adapter_names:
+                return
+
+            for active_adapter in adapter_names:
+                if active_adapter not in self.vera_lambda_d.keys():
+                    continue
+
+                warnings.warn(
+                    "Merge vera module to 4-bit linear may get different generations due to rounding errors."
+                )
+                vera_data = self.get_delta_weight(active_adapter)
+
+                weight = self.get_base_layer().weight
+                kwargs = weight.__dict__
+                # torch.compile can introduce attributes preceded by '_', remove them
+                kwargs = {k: v for k, v in kwargs.items() if not k.startswith("_")}
+                w_data = bnb.functional.dequantize_4bit(weight.data, weight.quant_state) + vera_data
+
+                if safe_merge and not torch.isfinite(w_data).all():
+                    raise ValueError(
+                        f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                    )
+
+                self.get_base_layer().weight = bnb.nn.Params4bit(w_data.to("cpu"), requires_grad=False, **kwargs).to(
+                    weight.device
+                )
+                self.merged_adapters.append(active_adapter)
+
+        def unmerge(self) -> None:
+            if not self.merged:
+                warnings.warn("Already unmerged. Nothing to do")
+                return
+
+            while len(self.merged_adapters) > 0:
+                active_adapter = self.merged_adapters.pop()
+                if active_adapter not in self.vera_lambda_d.keys():
+                    continue
+                warnings.warn(
+                    "Unmerge vera module to 4-bit linear may get different generations due to rounding errors."
+                )
+                vera_data = self.get_delta_weight(active_adapter)
+
+                weight = self.get_base_layer().weight
+                kwargs = weight.__dict__
+                w_data = bnb.functional.dequantize_4bit(weight.data, weight.quant_state) - vera_data
+
+                self.get_base_layer().weight = bnb.nn.Params4bit(w_data.to("cpu"), requires_grad=False, **kwargs).to(
+                    weight.device
+                )
+
+        def get_delta_weight(self, adapter) -> torch.Tensor:
+            vera_A = self.vera_A[adapter]
+            vera_B = self.vera_B[adapter]
+
+            device = vera_B.device
+            dtype = vera_B.dtype
+
+            cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+            lambda_d = self.vera_lambda_d[adapter]
+            lambda_b = self.vera_lambda_b[adapter]
+
+            if cast_to_fp32:
+                vera_A = vera_A.float()
+                vera_B = vera_B.float()
+                lambda_d = lambda_d.float()
+                lambda_b = lambda_b.float()
+
+            sliced_A = vera_A[:, : self.in_features].to(lambda_d.device)
+            sliced_B = vera_B[: self.out_features, :].to(lambda_d.device)
+            lambda_b = lambda_b.unsqueeze(-1)
+            lambda_d = lambda_d.unsqueeze(-1)
+
+            output_tensor = transpose((lambda_b * sliced_B) @ (lambda_d * sliced_A), self.fan_in_fan_out)
+
+            if cast_to_fp32:
+                output_tensor = output_tensor.to(dtype=dtype)
+
+            return output_tensor
+
+        def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+            if self.disable_adapters:
+                if self.merged:
+                    self.unmerge()
+                result = self.base_layer(x, *args, **kwargs)
+            elif self.merged:
+                result = self.base_layer(x, *args, **kwargs)
+            else:
+                result = self.base_layer(x, *args, **kwargs)
+                result = result.clone()
+                for active_adapter in self.active_adapters:
+                    if active_adapter not in self.vera_lambda_d.keys():
+                        continue
+
+                    lambda_d = self.vera_lambda_d[active_adapter]
+                    lambda_b = self.vera_lambda_b[active_adapter]
+
+                    vera_A = self.vera_A[active_adapter]
+                    vera_B = self.vera_B[active_adapter]
+
+                    dropout = self.vera_dropout[active_adapter]
+
+                    requires_conversion = not torch.is_autocast_enabled()
+                    if requires_conversion:
+                        expected_dtype = result.dtype
+                        compute_dtype = lambda_d.dtype
+                        if x.dtype != compute_dtype:
+                            x = x.to(compute_dtype)
+
+                    sliced_A = vera_A[:, : self.in_features].to(x.device)
+                    sliced_B = vera_B[: self.out_features, :].to(x.device)
+
+                    x_temp = dropout(x.to(lambda_d.dtype))
+
+                    adapter_output = lambda_b * torch.nn.functional.linear(
+                        lambda_d * torch.nn.functional.linear(x_temp, sliced_A), sliced_B
+                    )
+
+                    if requires_conversion:
+                        adapter_output = adapter_output.to(expected_dtype)
+
+                    result = result + adapter_output
+
+            # Ensure the output tensor has the same dtype as the input tensor
+            return result.to(x.dtype)
+
+        def __repr__(self) -> str:
+            rep = super().__repr__()
+            return "vera." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..5a8eaa4cdc27505bf3b3d6b9404f61eaa76f9494
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/config.py
@@ -0,0 +1,162 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from dataclasses import dataclass, field
+from typing import Optional, Union
+
+from peft.config import PeftConfig
+from peft.utils import PeftType
+
+
+@dataclass
+class VeraConfig(PeftConfig):
+    """
+    This is the configuration class to store the configuration of a [`VeraModel`].
+
+    Paper: https://arxiv.org/abs/2310.11454.
+
+    Args:
+        r (`int`, *optional*, defaults to `256`):
+            VeRA parameter dimension ("rank"). Choose higher values than LoRA ranks here, since VeRA uses far fewer
+            parameters than LoRA (see Table 1).
+        target_modules (`Union[List[str], str]`):
+            The names of the modules to apply Vera to. Only linear layers are supported.
+        projection_prng_key (`int`):
+            Vera PRNG init key. Used for initialising vera_A and vera_B for new models or when loading a checkpoint
+            that did not include these projections. Defaults to `0`.
+        save_projection (`bool`):
+            Whether to save the vera_A / vera_B projections in the state dict alongside per layer lambda_b / lambda_d
+            weights. This will increase the size of the checkpoint, but guarantee that we can reload the checkpoint on
+            all system configurations. Defaults to `True`.
+        vera_dropout (`float`):
+            The dropout probability for Vera layers.
+        d_initial (`float`, *optional*, defaults to `0.1`):
+            Initial init value for `vera_lambda_d` vector used when initializing the VeRA parameters. Small values
+            (<=0.1) are recommended (see Table 6c in the paper).
+        fan_in_fan_out (`bool`):
+            Set this to True if the layer to replace stores weight like (fan_in, fan_out). For example, gpt-2 uses
+            `Conv1D` which stores weights like (fan_in, fan_out) and hence this should be set to `True`.
+        bias (`str`):
+            Bias type for Vera. Can be 'none', 'all' or 'vera_only'. If 'all' or 'vera_only', the corresponding biases
+            will be updated during training. Be aware that this means that, even when disabling the adapters, the model
+            will not produce the same output as the base model would have without adaptation.
+        modules_to_save (`List[str]`):
+            List of modules apart from Vera layers to be set as trainable and saved in the final checkpoint.
+        init_weights (`bool`):
+            Whether to initialize the weights of the Vera layers with their default initialization. Don't change this
+            setting, except if you know exactly what you're doing.
+        layers_to_transform (`Union[List[int],int]`):
+            The layer indexes to transform, if this argument is specified, it will apply the Vera transformations on
+            the layer indexes that are specified in this list. If a single integer is passed, it will apply the Vera
+            transformations on the layer at this index.
+        layers_pattern (`Optional[Union[List[str], str]]`):
+            The layer pattern name, used only if `layers_to_transform` is different from `None`. This should target the
+            `nn.ModuleList` of the model, which is often called `'layers'` or `'h'`.
+    """
+
+    r: int = field(default=256, metadata={"help": "Vera attention dimension"})
+
+    target_modules: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of module names or regex expression of the module names to replace with Vera."
+                "For example, ['q', 'v'] or '.*decoder.*(SelfAttention|EncDecAttention).*(q|v)$'. "
+                "Only linear layers are supported."
+            )
+        },
+    )
+    projection_prng_key: int = field(
+        default=0,
+        metadata={
+            "help": (
+                "Vera PRNG init key. Used for initialising vera_A and vera_B for new models or when loading a "
+                "checkpoint that did not include these projections."
+            )
+        },
+    )
+    save_projection: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to save the vera_A / vera_B projections in the state dict alongside per layer lambda_b / "
+                "lambda_d weights. This will increase the size of the checkpoint, but guarantee that we can reload "
+                "the checkpoint on all system configurations."
+            )
+        },
+    )
+    vera_dropout: float = field(default=0.0, metadata={"help": "Vera dropout"})
+    d_initial: float = field(default=0.1, metadata={"help": "Initial init value for d vector."})
+    fan_in_fan_out: bool = field(
+        default=False,
+        metadata={"help": "Set this to True if the layer to replace stores weight like (fan_in, fan_out)"},
+    )
+    bias: str = field(default="none", metadata={"help": "Bias type for Vera. Can be 'none', 'all' or 'vera_only'"})
+    modules_to_save: Optional[list[str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "List of modules apart from Vera layers to be set as trainable and saved in the final checkpoint. For"
+                " example, in Sequence Classification or Token Classification tasks, the final layer"
+                " `classifier/score` are randomly initialized and as such need to be trainable and saved."
+            )
+        },
+    )
+    init_weights: bool = field(
+        default=True,
+        metadata={
+            "help": (
+                "Whether to initialize the weights of the Vera layers with their default initialization. Don't change "
+                "this setting, except if you know exactly what you're doing."
+            ),
+        },
+    )
+    layers_to_transform: Optional[Union[list[int], int]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The layer indexes to transform, is this argument is specified, PEFT will transform only the layers"
+                " indexes that are specified inside this list. If a single integer is passed, PEFT will transform only"
+                " the layer at this index."
+            )
+        },
+    )
+    layers_pattern: Optional[Union[list[str], str]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "The layer pattern name, used only if `layers_to_transform` is different to None and if the layer "
+                "pattern is not in the common layers pattern. This should target the `nn.ModuleList` of the "
+                "model, which is often called `'layers'` or `'h'`."
+            )
+        },
+    )
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.VERA
+        self.target_modules = (
+            set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
+        )
+        # check for layers_to_transform and layers_pattern
+        if self.layers_pattern and not self.layers_to_transform:
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
+        if not self.save_projection:
+            warnings.warn(
+                "Specified to not save vera_A and vera_B within the state dictionary, instead they will be restored "
+                "using the PRNG key store in `config.projection_prng_key`. Consider setting `config.save_projection` "
+                "to `True` to guarantee restoring the checkpoint correctly on all system configurations."
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..25789e8f59cdf70de58a280b620cd6d2bd356c75
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/layer.py
@@ -0,0 +1,294 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from typing import List, Optional
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from transformers.pytorch_utils import Conv1D
+
+from peft.tuners.tuners_utils import BaseTunerLayer, check_adapters_to_merge
+from peft.utils.other import transpose
+
+from .._buffer_dict import BufferDict
+
+
+class VeraLayer(BaseTunerLayer):
+    # List all names of layers that may contain adapter weights
+    adapter_layer_names = ("vera_lambda_b", "vera_lambda_d")
+    other_param_names = ("vera_A", "vera_B")
+
+    def __init__(self, base_layer: nn.Module, **kwargs):
+        self.base_layer = base_layer
+        self.r = {}
+        self.vera_dropout = nn.ModuleDict({})
+
+        # For storing vector scale
+        self.vera_lambda_b = nn.ParameterDict({})
+        self.vera_lambda_d = nn.ParameterDict({})
+
+        # Stores a reference to the vera_A/B BufferDict.
+        # Set to `None` otherwise to avoid computation with random weights
+        self.vera_A: Optional[BufferDict] = None
+        self.vera_B: Optional[BufferDict] = None
+
+        # Mark the weight as unmerged
+        self._disable_adapters = False
+        self.merged_adapters = []
+
+        base_layer = self.get_base_layer()
+        if isinstance(base_layer, nn.Linear):
+            in_features, out_features = base_layer.in_features, base_layer.out_features
+        elif isinstance(base_layer, Conv1D):
+            in_features, out_features = (
+                base_layer.weight.ds_shape if hasattr(base_layer.weight, "ds_shape") else base_layer.weight.shape
+            )
+
+        self.in_features = in_features
+        self.out_features = out_features
+        self.kwargs = kwargs
+
+    @property
+    def merged(self) -> bool:
+        return bool(self.merged_adapters)
+
+    def update_layer(
+        self,
+        adapter_name,
+        vera_A: BufferDict,
+        vera_B: BufferDict,
+        r,
+        vera_dropout,
+        init_weights,
+        d_initial: float = 0.1,
+    ):
+        if r <= 0:
+            raise ValueError(f"`r` should be a positive integer value but the value passed is {r}")
+        self.r[adapter_name] = r
+        if vera_dropout > 0.0:
+            vera_dropout_layer = nn.Dropout(p=vera_dropout)
+        else:
+            vera_dropout_layer = nn.Identity()
+
+        self.vera_dropout.update(nn.ModuleDict({adapter_name: vera_dropout_layer}))
+        # Actual trainable parameters
+        self.vera_lambda_b[adapter_name] = nn.Parameter(torch.ones(self.out_features), requires_grad=True)
+        self.vera_lambda_d[adapter_name] = nn.Parameter(torch.randn(r), requires_grad=True)
+
+        # non trainable references to vera_A/B buffers
+        self.vera_A = vera_A
+        self.vera_B = vera_B
+        if adapter_name not in vera_A:
+            # This means that this is not the first VeRA adapter. We have to add an entry in the dict for this adapter.
+            if len(self.vera_A) < 1:
+                raise ValueError(
+                    "The `vera_A` and `vera_B` buffers are empty. This should not happen. Please report this issue."
+                )
+            # we can take any of the existing adapter's parameters, as they should all be identical
+            vera_A_param = list(self.vera_A.values())[0]
+            vera_B_param = list(self.vera_B.values())[0]
+
+            error_tmpl = (
+                "{} has a size of {} but {} or greater is required; this probably happened because an additional VeRA "
+                "adapter was added after the first one with incompatible shapes."
+            )
+            # check input size
+            if vera_A_param.shape[1] < self.in_features:
+                raise ValueError(error_tmpl.format("vera_A", vera_A_param.shape[1], self.in_features))
+            # check output size
+            if vera_B_param.shape[0] < self.out_features:
+                raise ValueError(error_tmpl.format("vera_B", vera_B_param.shape[0], self.out_features))
+            # check r
+            error_tmpl = (
+                "{} has a size of {} but {} or greater is required; this probably happened because an additional VeRA "
+                "adapter with a lower rank was added after the first one; loading the adapters "
+                "in reverse order may solve this."
+            )
+            if vera_A_param.shape[0] < self.r[adapter_name]:
+                raise ValueError(error_tmpl.format("vera_A", vera_A_param.shape[0], self.r[adapter_name]))
+            if vera_B_param.shape[1] < self.r[adapter_name]:
+                raise ValueError(error_tmpl.format("vera_B", vera_B_param.shape[1], self.r[adapter_name]))
+
+            self.vera_A[adapter_name] = vera_A_param
+            self.vera_B[adapter_name] = vera_B_param
+
+        if init_weights:
+            self.reset_vera_parameters(adapter_name, d_initial=d_initial)
+
+        self._move_adapter_to_device_of_base_layer(adapter_name)
+        self.set_adapter(self.active_adapters)
+
+    def reset_vera_parameters(self, adapter_name, d_initial: float = 0.1):
+        if adapter_name in self.vera_lambda_d.keys():
+            with torch.no_grad():
+                nn.init.zeros_(self.vera_lambda_d[adapter_name]).fill_(d_initial)
+                nn.init.zeros_(self.vera_lambda_b[adapter_name])
+
+
+class Linear(nn.Linear, VeraLayer):
+    # Vera implemented in a dense layer
+    def __init__(
+        self,
+        base_layer,
+        vera_A: BufferDict,
+        vera_B: BufferDict,
+        adapter_name: str,
+        r: int = 0,
+        vera_dropout: float = 0.0,
+        fan_in_fan_out: bool = False,  # Set this to True if the layer to replace stores weight like (fan_in, fan_out)
+        is_target_conv_1d_layer: bool = False,
+        init_weights: bool = True,
+        d_initial: float = 0.1,
+        **kwargs,
+    ) -> None:
+        # this gets the init from nn.Linear's super perspective, i.e. nn.Module.__init__, which should always be called
+        super(nn.Linear, self).__init__()
+        VeraLayer.__init__(self, base_layer, **kwargs)
+        self.fan_in_fan_out = fan_in_fan_out
+
+        self._active_adapter = adapter_name
+        self.update_layer(adapter_name, vera_A, vera_B, r, vera_dropout, init_weights, d_initial=d_initial)
+        self.is_target_conv_1d_layer = is_target_conv_1d_layer
+
+    def merge(self, safe_merge: bool = False, adapter_names: Optional[List[str]] = None) -> None:
+        """
+        Merge the active adapter weights into the base weights
+
+        Args:
+            safe_merge (`bool`, *optional*):
+                If True, the merge operation will be performed in a copy of the original weights and check for NaNs
+                before merging the weights. This is useful if you want to check if the merge operation will produce
+                NaNs. Defaults to `False`.
+            adapter_names (`List[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+        """
+        adapter_names = check_adapters_to_merge(self, adapter_names)
+        if not adapter_names:
+            # no adapter to merge
+            return
+
+        for active_adapter in adapter_names:
+            if active_adapter in self.vera_lambda_d.keys():
+                base_layer = self.get_base_layer()
+                if safe_merge:
+                    # Note that safe_merge will be slower than the normal merge
+                    # because of the copy operation.
+                    orig_weights = base_layer.weight.data.clone()
+
+                    orig_weights += self.get_delta_weight(active_adapter)
+
+                    if not torch.isfinite(orig_weights).all():
+                        raise ValueError(
+                            f"NaNs detected in the merged weights. The adapter {active_adapter} seems to be broken"
+                        )
+
+                    base_layer.weight.data = orig_weights
+                else:
+                    base_layer.weight.data += self.get_delta_weight(active_adapter)
+                self.merged_adapters.append(active_adapter)
+
+    def unmerge(self) -> None:
+        if not self.merged:
+            warnings.warn("Already unmerged. Nothing to do.")
+            return
+
+        while len(self.merged_adapters) > 0:
+            active_adapter = self.merged_adapters.pop()
+            if active_adapter in self.vera_lambda_d.keys():
+                self.get_base_layer().weight.data -= self.get_delta_weight(active_adapter)
+
+    def get_delta_weight(self, adapter) -> torch.Tensor:
+        """
+        Compute the delta weight for the given adapter.
+
+        Args:
+            adapter (str):
+                The name of the adapter for which the delta weight should be computed.
+        """
+        vera_A = self.vera_A[adapter]
+        vera_B = self.vera_B[adapter]
+
+        device = vera_B.device
+        dtype = vera_B.dtype
+
+        # In case users wants to merge the adapter weights that are in
+        # (b)float16 while being on CPU, we need to cast the weights to float32, perform the merge and then cast back to
+        # (b)float16 because some CPUs have slow bf16/fp16 matmuls.
+        cast_to_fp32 = device.type == "cpu" and (dtype == torch.float16 or dtype == torch.bfloat16)
+
+        lambda_d = self.vera_lambda_d[adapter]
+        lambda_b = self.vera_lambda_b[adapter]
+
+        if cast_to_fp32:
+            vera_A = vera_A.float()
+            vera_B = vera_B.float()
+            lambda_d = lambda_d.float()
+            lambda_b = lambda_b.float()
+
+        sliced_A = vera_A[:, : self.in_features].to(lambda_d.device)
+        sliced_B = vera_B[: self.out_features, :].to(lambda_d.device)
+        lambda_b = lambda_b.unsqueeze(-1)
+        lambda_d = lambda_d.unsqueeze(-1)
+        output_tensor = transpose((lambda_b * sliced_B) @ (lambda_d * sliced_A), self.fan_in_fan_out)
+
+        if cast_to_fp32:
+            output_tensor = output_tensor.to(dtype=dtype)
+
+            # cast back the weights
+            # TODO: why?
+            self.vera_lambda_d[adapter].data = lambda_d.to(dtype)
+            self.vera_lambda_b[adapter].data = lambda_b.to(dtype)
+
+        return output_tensor
+
+    def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
+        previous_dtype = x.dtype
+
+        if self.disable_adapters:
+            if self.merged:
+                self.unmerge()
+            result = self.base_layer(x, *args, **kwargs)
+        elif self.merged:
+            result = self.base_layer(x, *args, **kwargs)
+        else:
+            result = self.base_layer(x, *args, **kwargs)
+            for active_adapter in self.active_adapters:
+                if active_adapter not in self.vera_lambda_d.keys():
+                    continue
+
+                lambda_d = self.vera_lambda_d[active_adapter]
+                lambda_b = self.vera_lambda_b[active_adapter]
+
+                vera_A = self.vera_A[active_adapter]
+                vera_B = self.vera_B[active_adapter]
+
+                # As adapted layers may have different shapes and VeRA contains a single shared pair of A and B matrices,
+                # we initialize these matrices with the largest required size for each dimension.
+                # During the forward pass, required submatrices are sliced out from the shared vera_A and vera_B.
+                sliced_A = vera_A[:, : self.in_features].to(x.device)
+                sliced_B = vera_B[: self.out_features, :].to(x.device)
+
+                dropout = self.vera_dropout[active_adapter]
+                x = x.to(lambda_d.dtype)
+                result = result + lambda_b * F.linear(lambda_d * F.linear(dropout(x), sliced_A), sliced_B)
+
+        result = result.to(previous_dtype)
+        return result
+
+    def __repr__(self) -> str:
+        rep = super().__repr__()
+        return "vera." + rep
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..ddf1dc57d61f19a90014f4cb85ee738cb44fa84b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/vera/model.py
@@ -0,0 +1,507 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import math
+import warnings
+from dataclasses import asdict
+from enum import Enum
+from typing import Optional, Union
+
+import torch
+import torch.nn as nn
+from torch.nn.init import _calculate_correct_fan
+from tqdm import tqdm
+from transformers.pytorch_utils import Conv1D
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available
+from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
+from peft.utils import (
+    TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING,
+    ModulesToSaveWrapper,
+    _get_submodules,
+)
+
+from .._buffer_dict import BufferDict
+from ..tuners_utils import _maybe_include_all_linear_layers
+from .config import VeraConfig
+from .layer import Linear, VeraLayer
+
+
+def _kaiming_init(
+    tensor_or_shape: Union[torch.Tensor, tuple[int, ...]],
+    generator: torch.Generator,
+) -> torch.Tensor:
+    """
+    Kaiming Uniform Initialisation adapted to accept a `torch.Generator` object for PRNG.
+
+    Args:
+        tensor_or_shape (`Union[torch.Tensor, tuple[int, ...]]`):
+            Tensor to initialise, or shape of new tensor to create and then initialise.
+        generator: (`torch.Generator`):
+            Generator object that manages the state of the PRNG algorithm in use.
+
+    Returns:
+        `torch.Tensor`: The initialised tensor.
+    """
+    if isinstance(tensor_or_shape, tuple):
+        tensor = torch.empty(tensor_or_shape)
+    else:
+        tensor = tensor_or_shape
+    fan = _calculate_correct_fan(tensor, "fan_in")
+    gain = math.sqrt(2)
+    std = gain / math.sqrt(fan)
+    bound = math.sqrt(3.0) * std
+
+    with torch.no_grad():
+        return tensor.uniform_(-bound, bound, generator=generator)
+
+
+class VeraModel(BaseTuner):
+    """
+    Creates Vector-based Random Matrix Adaptation (Vera) model from a pretrained transformers model.
+
+    Args:
+        model ([`~transformers.PreTrainedModel`]): The model to be adapted.
+        config ([`VeraConfig`]): The configuration of the Vera model.
+        adapter_name (`str`): The name of the adapter, defaults to `"default"`.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            Create empty adapter weights on meta device. Useful to speed up the loading process.
+
+    Returns:
+        `torch.nn.Module`: The Vera model.
+
+    Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import VeraConfig, get_peft_model
+
+        >>> base_model = AutoModelForCausalLM.from_pretrained("facebook/opt-125m")
+        >>> config = VeraConfig(r=128)
+        >>> model = get_peft_model(base_model, config)
+        ```
+
+    **Attributes**:
+        - **model** ([`~transformers.PreTrainedModel`]) -- The model to be adapted.
+        - **peft_config** ([`VeraConfig`]): The configuration of the Vera model.
+    """
+
+    prefix: str = "vera_lambda_"
+
+    def __init__(self, model, config, adapter_name, low_cpu_mem_usage: bool = False) -> None:
+        super().__init__(model, config, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage)
+
+    def _find_dim(self, config) -> tuple[int, int]:
+        """
+        Finds the largest input and output dimensions across linear layers that have been wrapped with VeRA.
+
+        This will be used for determining the size of the shared vera_A and vera_B matrices.
+        """
+        model_config = self.get_model_config(self.model)
+
+        peft_config = self._prepare_adapter_config(config, model_config)
+        peft_config = _maybe_include_all_linear_layers(peft_config, self.model)
+
+        largest_shape = None
+        for key, module in self.model.named_modules():
+            if not self._check_target_module_exists(peft_config, key):
+                continue
+
+            if isinstance(module, nn.Linear):
+                module_shape = module.out_features, module.in_features
+            elif isinstance(module, Conv1D):
+                module_shape = module.weight.ds_shape if hasattr(module.weight, "ds_shape") else module.weight.shape
+                module_shape = module_shape[::-1]
+            else:
+                continue
+
+            if largest_shape is None:
+                largest_shape = module_shape
+                continue
+
+            if module_shape != largest_shape:
+                largest_shape = tuple(max(a, b) for a, b in zip(largest_shape, module_shape))
+
+        if largest_shape is None:
+            msg = "No layers types compatible with VeRA were found. Please check `peft_config.target_modules`."
+            raise ValueError(msg)
+
+        return largest_shape
+
+    def _init_vera_A_vera_B(self, config: VeraConfig, adapter_name: str) -> None:
+        linear_out_dim, linear_in_dim = self._find_dim(config)
+
+        # use of persistent to exclude vera_A and vera_B from the state dict if we choose not to save them.
+        self.vera_A = BufferDict({}, persistent=config.save_projection)
+        self.vera_B = BufferDict({}, persistent=config.save_projection)
+
+        # deterministic init of vera_A and vera_B if we know the key
+        generator = torch.Generator(device="cpu").manual_seed(config.projection_prng_key)
+        vera_A = _kaiming_init((config.r, linear_in_dim), generator=generator)
+        vera_B = _kaiming_init((linear_out_dim, config.r), generator=generator)
+
+        self.vera_A[adapter_name] = vera_A
+        self.vera_B[adapter_name] = vera_B
+
+    def _pre_injection_hook(self, model: nn.Module, config: VeraConfig, adapter_name: str) -> None:
+        self._init_vera_A_vera_B(config, adapter_name)
+
+    def _check_new_adapter_config(self, config: VeraConfig) -> None:
+        """
+        A helper method to check the config when a new adapter is being added.
+
+        Raise a ValueError if there is something wrong with the config or if it conflicts with existing adapters.
+
+        """
+        # the below todo is copied from LoRA
+        # TODO: there should be a check if any of the existing adapters actually has bias != "none", or else the check
+        # does not fully correspond to the error message.
+        if (len(self.peft_config) > 1) and (config.bias != "none"):
+            raise ValueError(
+                f"{self.__class__.__name__} supports only 1 adapter with bias. When using multiple adapters, "
+                "set bias to 'none' for all adapters."
+            )
+
+        for existing_config in self.peft_config.values():
+            if existing_config is config:
+                # skip the current config
+                continue
+
+            if existing_config.projection_prng_key != config.projection_prng_key:
+                raise ValueError(
+                    f"Vera PRNG initialisation key must be the same for all adapters. Got {config.projection_prng_key=} but "
+                    f"previous config had {existing_config.projection_prng_key}."
+                )
+
+        save_project_unique_values = sorted({config.save_projection for config in self.peft_config.values()})
+        if len(save_project_unique_values) > 1:
+            raise ValueError(
+                "VeRA projection weights must be saved for all adapters or none, but got multiple different values: "
+                f"{save_project_unique_values}"
+            )
+
+    @staticmethod
+    def _check_target_module_exists(vera_config, key):
+        return check_target_module_exists(vera_config, key)
+
+    def _create_and_replace(
+        self,
+        vera_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+        **optional_kwargs,
+    ):
+        if current_key is None:
+            raise ValueError("Current Key shouldn't be `None`")
+
+        r = vera_config.r
+        bias = hasattr(target, "bias") and target.bias is not None
+        kwargs = {
+            "r": r,
+            "vera_dropout": vera_config.vera_dropout,
+            "fan_in_fan_out": vera_config.fan_in_fan_out,
+            "init_weights": vera_config.init_weights,
+            "loaded_in_8bit": getattr(self.model, "is_loaded_in_8bit", False),
+            "loaded_in_4bit": getattr(self.model, "is_loaded_in_4bit", False),
+        }
+        kwargs["bias"] = bias
+
+        if isinstance(target, Linear):
+            target.update_layer(
+                adapter_name,
+                self.vera_A,
+                self.vera_B,
+                r,
+                vera_config.vera_dropout,
+                vera_config.init_weights,
+                d_initial=vera_config.d_initial,
+            )
+        else:
+            new_module = self._create_new_module(vera_config, self.vera_A, self.vera_B, adapter_name, target, **kwargs)
+            if adapter_name not in self.active_adapter:
+                # adding an additional adapter: it is not automatically trainable
+                new_module.requires_grad_(False)
+            self._replace_module(parent, target_name, new_module, target)
+
+    @staticmethod
+    def _replace_module(parent, child_name, new_module, child):
+        setattr(parent, child_name, new_module)
+        # It's not necessary to set requires_grad here, as that is handled by
+        # _mark_only_adapters_as_trainable
+
+        # child layer wraps the original module, unpack it
+        if hasattr(child, "base_layer"):
+            child = child.base_layer
+
+        if not hasattr(new_module, "base_layer"):
+            new_module.weight = child.weight
+            if hasattr(child, "bias"):
+                new_module.bias = child.bias
+
+        if getattr(child, "state", None) is not None:
+            if hasattr(new_module, "base_layer"):
+                new_module.base_layer.state = child.state
+            else:
+                new_module.state = child.state
+            new_module.to(child.weight.device)
+
+        meta = torch.device("meta")
+        # dispatch to correct device
+        for name, module in new_module.named_modules():
+            if "vera_" in name:
+                if not any(p.device == meta for p in module.parameters()):
+                    module.to(child.weight.device)
+
+    def _mark_only_adapters_as_trainable(self, model: nn.Module) -> None:
+        for n, p in model.named_parameters():
+            if self.prefix not in n:
+                p.requires_grad = False
+
+        for active_adapter in self.active_adapters:
+            bias = self.peft_config[active_adapter].bias
+            if bias == "none":
+                continue
+
+            if bias == "all":
+                for n, p in model.named_parameters():
+                    if "bias" in n:
+                        p.requires_grad = True
+            elif bias == "vera_only":
+                for m in model.modules():
+                    if isinstance(m, VeraLayer) and hasattr(m, "bias") and m.bias is not None:
+                        m.bias.requires_grad = True
+            else:
+                raise NotImplementedError(f"Requested bias: {bias}, is not implemented.")
+
+    @staticmethod
+    def _create_new_module(vera_config, vera_A, vera_B, adapter_name, target, **kwargs):
+        # avoid eager bnb import
+        if is_bnb_available():
+            import bitsandbytes as bnb
+
+            from .bnb import Linear8bitLt
+
+        if is_bnb_4bit_available():
+            from .bnb import Linear4bit
+
+        bias = kwargs.pop("bias", False)
+        loaded_in_8bit = kwargs.get("loaded_in_8bit", False)
+        loaded_in_4bit = kwargs.get("loaded_in_4bit", False)
+
+        if isinstance(target, BaseTunerLayer):
+            target_base_layer = target.get_base_layer()
+        else:
+            target_base_layer = target
+
+        if loaded_in_8bit and isinstance(target_base_layer, bnb.nn.Linear8bitLt):
+            eightbit_kwargs = kwargs.copy()
+            eightbit_kwargs.update(
+                {
+                    "has_fp16_weights": target_base_layer.state.has_fp16_weights,
+                    "threshold": target_base_layer.state.threshold,
+                    "index": target_base_layer.index,
+                }
+            )
+            return Linear8bitLt(target, adapter_name, vera_A, vera_B, **eightbit_kwargs)
+        elif loaded_in_4bit and isinstance(target_base_layer, bnb.nn.Linear4bit):
+            fourbit_kwargs = kwargs.copy()
+            fourbit_kwargs.update(
+                {
+                    "compute_dtype": target_base_layer.compute_dtype,
+                    "compress_statistics": target_base_layer.weight.compress_statistics,
+                    "quant_type": target_base_layer.weight.quant_type,
+                }
+            )
+            return Linear4bit(target, adapter_name, vera_A, vera_B, **fourbit_kwargs)
+        elif isinstance(target_base_layer, torch.nn.Linear):
+            if kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to True but the target module is `torch.nn.Linear`. "
+                    "Setting fan_in_fan_out to False."
+                )
+                kwargs["fan_in_fan_out"] = vera_config.fan_in_fan_out = False
+        elif isinstance(target_base_layer, Conv1D):
+            kwargs["is_target_conv_1d_layer"] = True
+            if not kwargs["fan_in_fan_out"]:
+                warnings.warn(
+                    "fan_in_fan_out is set to False but the target module is `Conv1D`. Setting fan_in_fan_out to True."
+                )
+                kwargs["fan_in_fan_out"] = vera_config.fan_in_fan_out = True
+        else:
+            raise ValueError(
+                f"Target module {target} is not supported. Currently, only the following modules are supported: "
+                "`torch.nn.Linear`, `transformers.pytorch_utils.Conv1D`."
+            )
+        new_module = Linear(
+            target,
+            vera_A,
+            vera_B,
+            adapter_name,
+            bias=bias,
+            d_initial=vera_config.d_initial,
+            **kwargs,
+        )
+
+        return new_module
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.model, name)
+
+    def get_peft_config_as_dict(self, inference: bool = False):
+        config_dict = {}
+        for key, value in self.peft_config.items():
+            config = {k: v.value if isinstance(v, Enum) else v for k, v in asdict(value).items()}
+            if inference:
+                config["inference_mode"] = True
+        config_dict[key] = config
+        return config
+
+    def _set_adapter_layers(self, enabled=True):
+        for module in self.model.modules():
+            if isinstance(module, (BaseTunerLayer, ModulesToSaveWrapper)):
+                module.enable_adapters(enabled)
+
+    def enable_adapter_layers(self):
+        self._set_adapter_layers(enabled=True)
+
+    def disable_adapter_layers(self):
+        for active_adapter in self.active_adapters:
+            val = self.peft_config[active_adapter].bias
+            if val != "none":
+                msg = (
+                    f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
+                    "output as the the base model would without adaption."
+                )
+                warnings.warn(msg)
+        self._set_adapter_layers(enabled=False)
+
+    def set_adapter(self, adapter_name):
+        for module in self.model.modules():
+            if isinstance(module, VeraLayer):
+                if module.merged:
+                    warnings.warn("Adapter cannot be set when the model is merged. Unmerging the model first.")
+                    module.unmerge()
+                module.set_adapter(adapter_name)
+        self.active_adapter = adapter_name
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, model_config):
+        if peft_config.target_modules is None:
+            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING:
+                raise ValueError("Please specify `target_modules` in `peft_config`")
+            peft_config.target_modules = set(
+                TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            )
+        return peft_config
+
+    def _unload_and_optionally_merge(
+        self,
+        merge=True,
+        progressbar: bool = False,
+        safe_merge: bool = False,
+        adapter_names: Optional[list[str]] = None,
+    ):
+        # we cannot use self.prefix as we want to include non-trainable vera parameters
+        key_list = [key for key, _ in self.model.named_modules() if "vera" not in key]
+        desc = "Unloading " + ("and merging " if merge else "") + "model"
+        for key in tqdm(key_list, disable=not progressbar, desc=desc):
+            try:
+                parent, target, target_name = _get_submodules(self.model, key)
+            except AttributeError:
+                continue
+
+            if hasattr(target, "base_layer"):
+                if merge:
+                    target.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+
+                self._replace_module(parent, target_name, target.get_base_layer(), target)
+            elif isinstance(target, ModulesToSaveWrapper):
+                # save any additional trainable modules part of `modules_to_save`
+                setattr(parent, target_name, target.modules_to_save[target.active_adapter])
+
+        return self.model
+
+    def delete_adapter(self, adapter_name: str):
+        """
+        Deletes an existing adapter.
+
+        Args:
+            adapter_name (str): Name of the adapter to be deleted.
+        """
+        if adapter_name not in list(self.peft_config.keys()):
+            raise ValueError(f"Adapter {adapter_name} does not exist")
+        del self.peft_config[adapter_name]
+
+        # we cannot use self.prefix as we want to include non-trainable vera parameters
+        key_list = [key for key, _ in self.model.named_modules() if "vera" not in key]
+        new_adapter = None
+        for key in key_list:
+            _, target, _ = _get_submodules(self.model, key)
+            if isinstance(target, VeraLayer):
+                target.delete_adapter(adapter_name)
+                if new_adapter is None:
+                    new_adapter = target.active_adapter[:]
+
+        self.active_adapter = new_adapter or []
+
+    def merge_and_unload(
+        self, progressbar: bool = False, safe_merge: bool = False, adapter_names: Optional[list[str]] = None
+    ):
+        r"""
+        This method merges the Vera layers into the base model. This is needed if someone wants to use the base model
+        as a standalone model.
+
+        Args:
+            progressbar (`bool`):
+                whether to show a progressbar indicating the unload and merge process
+            safe_merge (`bool`):
+                whether to activate the safe merging check to check if there is any potential Nan in the adapter
+                weights
+            adapter_names (`list[str]`, *optional*):
+                The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
+                to `None`.
+
+        Example:
+
+        ```py
+        >>> from transformers import AutoModelForCausalLM
+        >>> from peft import PeftModel
+
+        >>> base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-40b")
+        >>> peft_model_id = "smangrul/falcon-40B-int4-peft-lora-sfttrainer-sample"
+        >>> model = PeftModel.from_pretrained(base_model, peft_model_id)
+        >>> merged_model = model.merge_and_unload()
+        ```
+        """
+        return self._unload_and_optionally_merge(
+            progressbar=progressbar, safe_merge=safe_merge, adapter_names=adapter_names
+        )
+
+    def unload(self):
+        """
+        Gets back the base model by removing all the Vera modules without merging. This gives back the original base
+        model.
+        """
+        return self._unload_and_optionally_merge(merge=False)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..6eae1f779b81e883f1dd64e3a4fca859391836c5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/__init__.py
@@ -0,0 +1,23 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from peft.utils import register_peft_method
+
+from .config import XLoraConfig
+from .model import XLoraModel
+
+
+__all__ = ["XLoraConfig", "XLoraModel"]
+
+register_peft_method(name="xlora", config_cls=XLoraConfig, model_cls=XLoraModel)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/classifier.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/classifier.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ccf9edf9db3178ba9dc4dd3e07989251a676cb8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/classifier.py
@@ -0,0 +1,195 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import builtins
+from typing import Optional, Union
+
+import torch
+import torch.nn as nn
+
+from .config import XLoraConfig
+
+
+Number = Union[builtins.int, builtins.float, builtins.bool]
+
+
+class TemperatureScaledSoftmax(nn.Module):
+    def __init__(self, temperature=1.0):
+        super().__init__()
+        self.temperature = temperature
+        self.softmax = nn.Softmax(dim=-1)
+
+    def forward(self, logits):
+        # Scale logits by the temperature
+        scaled_logits = logits / self.temperature
+        # Apply softmax to the scaled logits
+        return self.softmax(scaled_logits)
+
+
+class XLoraClassifier(nn.Module):
+    """
+    A classifier to select LoRA layers for XLora.
+    """
+
+    def __init__(
+        self,
+        model: nn.Module,  # PeftModel
+        config: XLoraConfig,
+        n_classes: int,
+        n_layers: int,
+        device: torch.device,
+    ):
+        """
+        Construct an X-LoRA classifier from a model, config and some metadata. Note that n_layers is the number of LoRA
+        adapter layers, not the number of model layers.
+        """
+        super().__init__()
+
+        self.n_classes = n_classes
+        self.n_layers = n_layers
+        self.config = config
+        self.log_scalings = []
+        self.softmax = TemperatureScaledSoftmax(temperature=self.config.softmax_temperature)
+        self.override_scaling_pass_value: Number = config.scaling_pass_value
+
+        self.scalings_logging = False
+
+        self.dtype = next(model.parameters()).dtype
+        add_dropout = config.xlora_dropout_p > 0.0
+
+        layers = []
+        if self.config.xlora_depth == 1:
+            if config.layerwise_scalings:  # bias=False if we have just one layer
+                last = nn.Linear(config.hidden_size, n_classes * n_layers, bias=True).to(device).to(self.dtype)
+            else:
+                last = nn.Linear(config.hidden_size, n_classes, bias=True).to(device).to(self.dtype)
+        else:
+            if self.config.xlora_depth <= 0:
+                raise ValueError("X-LoRA depth must be strictly positive.")
+
+            layers.append(nn.Linear(config.hidden_size, config.xlora_size, bias=True).to(device).to(self.dtype))
+
+            layers.append(nn.ReLU())
+            if add_dropout:
+                layers.append(nn.Dropout(p=config.xlora_dropout_p))
+
+            for _ in range(config.xlora_depth - 2):
+                layers.append(nn.Linear(config.xlora_size, config.xlora_size, bias=True).to(device).to(self.dtype))
+
+                layers.append(nn.ReLU())
+                if add_dropout:
+                    layers.append(nn.Dropout(p=config.xlora_dropout_p))
+
+            if config.layerwise_scalings:
+                last = nn.Linear(config.xlora_size, n_classes * n_layers, bias=True).to(device).to(self.dtype)
+            else:
+                last = nn.Linear(config.xlora_size, n_classes, bias=True).to(device).to(self.dtype)
+        self.layers = nn.Sequential(*layers, last)
+
+    def make_dummy_scalings(
+        self,
+        input_ids: Optional[torch.LongTensor] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        *args,
+        **kwargs,
+    ) -> torch.Tensor:
+        """
+        Make some dummy scalings for the scalings pass (the one to get the logits for the X-LoRA classifier). These are
+        of shape (batch_size, seq_len, n_layers, n_classes) and filled with the override scalings pass value. Note that
+        n_layers is the number of LoRA adapter layers, not the number of model layers.
+        """
+        if input_ids is not None:
+            batch_size = input_ids.shape[0]
+            device = input_ids.device
+            seq_len = input_ids.shape[1]
+        else:
+            batch_size = inputs_embeds.shape[0]
+            device = inputs_embeds.device
+            seq_len = inputs_embeds.shape[1]
+
+        return torch.full(  # type: ignore
+            (batch_size, seq_len, self.n_layers, self.n_classes),
+            self.override_scaling_pass_value,
+        ).to(device=device, dtype=self.dtype)
+
+    def forward(
+        self,
+        result,
+        input_ids: Optional[torch.LongTensor] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        *args,
+        **kwargs,
+    ) -> torch.Tensor:
+        """
+        Using the hidden states of the model, predict `n_classes` LoRA alpha values. Returns the scalings.
+        """
+        if input_ids is not None:
+            batch_size = input_ids.shape[0]
+            seq_len = input_ids.shape[1]
+        else:
+            batch_size = inputs_embeds.shape[0]
+            seq_len = inputs_embeds.shape[1]
+
+        hidden_states = result.hidden_states  # type: ignore
+
+        hidden_state = hidden_states[-1]  # Get the last hidden state
+
+        ### Classifier run
+        # hidden_state=[batch_size, seq_len, hidden_size]
+        logits = self.layers.forward(hidden_state)
+
+        ### Repeat to make layerwise scalings
+        ### If layerwise_scalings=False, then the classifier only outputs logits which are not layer-wise.
+        ### So, we expand them to the correct shape.
+        if not self.config.layerwise_scalings:
+            logits = logits.unsqueeze(2)
+            logits = logits.expand(-1, -1, self.n_layers, -1)
+
+        ### Classifier run
+
+        scalings = logits.reshape(batch_size, seq_len, self.n_layers, self.n_classes)
+        # scalings = [batch_size, seq_len, n_layers, n_classes]
+
+        if self.config.enable_softmax:
+            scalings = self.softmax(scalings)
+
+        if self.scalings_logging:
+            self.log_scalings.append(scalings)
+
+        return scalings
+
+    def _get_bucketed_scalings(self) -> dict[int, tuple[list[int], list[torch.Tensor]]]:
+        """
+        Returns bucketed scalings, bucketed by seq_len. Each value consists of the positions (the first) and the
+        associated tensors. The positions are paired with the associated tensors and give the position in the scaling
+        log. Each scaling is a tensor of shape (batch_size, seq_len, n_layers, n_classes)).
+        """
+        seqlens_map: dict[int, tuple[list[int], list[torch.Tensor]]] = {}
+        for i, scaling in enumerate(self.log_scalings):
+            seq_len = scaling.shape[1]
+            if seq_len not in seqlens_map:
+                seqlens_map[seq_len] = ([i], [scaling])
+            else:
+                seqlens_map[seq_len][0].append(i)
+                seqlens_map[seq_len][1].append(scaling)
+
+        return seqlens_map
+
+    def _set_override_scaling_pass_value(self, value: Union[Number, None]):
+        if value is None:
+            self.override_scaling_pass_value = 1 / self.n_classes
+        else:
+            self.override_scaling_pass_value = value
+        self.config.scaling_pass_value = self.override_scaling_pass_value
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/config.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..9cdb0f6e49f367c640ef4abf14e29b3b60f22fa6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/config.py
@@ -0,0 +1,102 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import warnings
+from dataclasses import dataclass
+from typing import Optional
+
+from peft.config import PeftConfig
+from peft.utils.peft_types import PeftType
+
+
+@dataclass
+class XLoraConfig(PeftConfig):
+    r"""
+    This is the configuration class to store the configuration of a `XLoraModel`. When the config is reloaded, the
+    paths of the `adapters` field is disregarded in favor of the saved adapters. As such, only the keys matter during
+    loading.
+
+    Args:
+        hidden_size (`int`):
+            Hidden size of the base model.
+        adapters (`dict`):
+            Mapping of adapter names to the LoRA adapter id, as per PeftModel.load_adapter. *They will be automatically
+            loaded*, to use as LoRA experts. When using from_pretrained, pass the new adapters dict as a keyword
+            argument.
+        enable_softmax (`bool`, *optional*, defaults to `True`):
+            Enable softmax application for the X-LoRA classifier.
+        enable_softmax_topk (`bool`, *optional*, defaults to `False`):
+            Enable softmax application for the top-k LoRA adapters. Mutually exclusive to `enable_softmax` and must
+            only be set if `top_k_lora` is.
+        softmax_temperature (`float`, *optional*, defaults to 1.0):
+            Softmax temperature, lower yields sharper predictions
+        layerwise_scalings (`bool`, *optional*, defaults to `False`):
+            If True, generate scalings for each LoRA adapter (each layer). If this is False, then scalings will be
+            broadcasted, the same, to each layer.
+        top_k_lora (`int`, *optional*, defaults to None):
+            Sparsely select the top_k LoRA experts instead of the default dense method.
+        xlora_depth (`int`, *optional*, defaults to 1):
+            Depth of the X-LoRA classifier.
+        xlora_size (`int`, *optional*, defaults to 2048):
+            Hidden size of the X-LoRA classifier, irrelevant if `xlora_depth=1`.
+        xlora_dropout_p (`float`, *optional*, defaults to 0.2):
+            Dropout probability of the X-LoRA classifier, irrelevant if `xlora_depth=1`.
+        use_trainable_adapters (`bool`, *optional*, defaults to False):
+            Make the adapters trainable.
+        scaling_pass_value (`float`, *optional*, defaults to 0):
+            Scaling pass value.
+        global_scaling_weight (`float`, *optional*, defaults to 1):
+            Weight to multiply output of each LoRA adapter by.
+    """
+
+    hidden_size: int = None  # type: ignore
+    adapters: dict[str, str] = None  # type: ignore
+    enable_softmax: bool = True
+    enable_softmax_topk: bool = False
+    layerwise_scalings: bool = False
+    xlora_depth: int = 1
+    xlora_size: int = 2048
+    xlora_dropout_p: float = 0.2
+    use_trainable_adapters: bool = False
+    softmax_temperature: float = 1.0
+    top_k_lora: Optional[int] = None
+    scaling_pass_value: float = 0.0
+    global_scaling_weight: float = 1.0
+
+    def __post_init__(self):
+        super().__post_init__()
+        self.peft_type = PeftType.XLORA
+
+        if self.hidden_size is None:
+            warnings.warn(
+                "No value was provided for `hidden_size`. This will be set to 4096 by default, please ensure that this is correct."
+            )
+            self.hidden_size = 4096
+        if self.adapters is None:
+            warnings.warn(
+                "No value was provided for for `adapters`. This will be set to empty, please ensure that this is correct."
+            )
+            self.adapters = {}
+
+        if self.enable_softmax_topk and self.top_k_lora is None:
+            warnings.warn("`enable_softmax_topk` enabled `top_k_lora` is not set")
+
+        if self.enable_softmax_topk and self.enable_softmax:
+            warnings.warn(
+                "`enable_softmax_topk` and `enable_softmax` are both enabled. This will result in worse performance."
+            )
+
+        if self.top_k_lora is not None and self.top_k_lora < 1:
+            warnings.warn("`top_k_lora` value must be at least 1.")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/layer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..a5035456d4646446dde06eb60088319b2c533fc3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/layer.py
@@ -0,0 +1,223 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+from typing import Any, Callable, Optional
+
+import torch
+import torch.nn as nn
+from torch import Tensor
+
+from peft.tuners import lora
+
+from .config import XLoraConfig
+
+
+class XLoraLayer:
+    """
+    A XLoraLayer wraps any LoraLayer and performs the XLora operation on the LoRA adaptors specified. Its primary API
+    is the forward method, which uses the scalings to execute the XLora algorithm.
+    """
+
+    def __init__(
+        self,
+        model: nn.Module,  # XLoraModel
+        target: lora.LoraLayer,
+        target_forward: Callable[..., Any],
+        layer_number: int,
+        config: XLoraConfig,
+    ) -> None:
+        self.model = model
+        self.target_forward = target_forward
+        self.target = target
+        self.layer_number = layer_number
+        self.config = config
+
+    """
+    Apply the scalings for the adapter.
+    """
+
+    @staticmethod
+    def apply_scalings_to_x(x: torch.Tensor, scalings_layer: torch.Tensor, adapter: int) -> torch.Tensor:
+        # scalings_layer = [batch_size, seq_len, n_classes]
+        scalings = scalings_layer[:, :, adapter].unsqueeze(-1)
+        # scalings_layer = [batch_size, seq_len, 1]
+        return x * scalings
+
+    """
+    Get the scalings for this layer, potentially applying topk and topk+softmax. This is called before
+    `apply_scalings_to_x`
+    """
+
+    def get_maybe_topk_scalings(self, scalings) -> torch.Tensor:
+        # xlora_scalings = [batch_size, seq_len, n_classes]
+        xlora_scalings: Tensor = scalings[:, :, self.layer_number, :]  # type: ignore
+
+        if self.config.top_k_lora is not None:
+            _, topk_indices = torch.topk(xlora_scalings, k=self.config.top_k_lora, dim=-1)
+
+            # Mask the topk to True, the rest to False
+            mask = torch.zeros_like(xlora_scalings, dtype=torch.bool)
+            mask.scatter_(-1, topk_indices, True)
+
+            xlora_scalings = xlora_scalings * mask.to(xlora_scalings.dtype)
+
+        if self.config.enable_softmax_topk:
+            nonzero_mask = xlora_scalings != 0
+            softmax_res_nonzero = torch.softmax(xlora_scalings[nonzero_mask], dim=-1)
+            xlora_scalings[nonzero_mask] = softmax_res_nonzero
+
+        return xlora_scalings
+
+
+class XLoraLinearLayer(XLoraLayer):
+    def __init__(
+        self,
+        model: nn.Module,
+        target: lora.Linear,
+        target_forward: Callable[..., Any],
+        layer_number: int,
+        config: XLoraConfig,
+    ) -> None:
+        super().__init__(model, target, target_forward, layer_number, config)
+
+    def forward(self, x: Tensor, *args: Any, scalings: Optional[Tensor] = None, **kwargs: Any) -> Tensor:
+        """
+        This method is designed to be a drop-in-replacement for the LoRA layers' .forward method. To use it, a bound
+        method must be created (bound to an instance of the XLoraLayer class).
+        """
+
+        previous_dtype = x.dtype
+        if scalings is not None:
+            xlora_scalings = self.get_maybe_topk_scalings(scalings)
+
+        result = self.target.base_layer(x, *args, **kwargs)
+
+        # Ignore if disabled. We want to make sure this is always run.
+        if not self.target.merged:
+            for adapter_n, active_adapter in enumerate(self.target.active_adapters):
+                # TODO: implement X-LoRA with Lora+Dora layers
+                if self.target.use_dora[active_adapter]:
+                    raise ValueError("X-LoRA currently does not support LoRA layers with DoRA")
+                if active_adapter not in self.target.lora_A.keys():
+                    continue
+                lora_A = self.target.lora_A[active_adapter]
+                lora_B = self.target.lora_B[active_adapter]
+                dropout = self.target.lora_dropout[active_adapter]
+                scaling = self.target.scaling[active_adapter]
+                x = x.to(lora_A.weight.dtype)  # type: ignore
+                if scalings is not None:
+                    x_mod = self.apply_scalings_to_x(x, xlora_scalings, adapter_n)
+                    scaling_weight = self.config.global_scaling_weight
+                else:
+                    x_mod = x
+                    scaling_weight = 1
+                result += lora_B(lora_A(dropout(x_mod))) * scaling * scaling_weight
+
+        result = result.to(previous_dtype)
+        return result
+
+
+class XLoraEmbeddingLayer(XLoraLayer):
+    def __init__(
+        self,
+        model: nn.Module,
+        target: lora.Embedding,
+        target_forward: Callable[..., Any],
+        layer_number: int,
+        config: XLoraConfig,
+    ) -> None:
+        super().__init__(model, target, target_forward, layer_number, config)
+
+    def forward(self, x: Tensor, *args: Any, scalings: Optional[Tensor] = None, **kwargs: Any) -> Tensor:
+        """
+        This method is designed to be a drop-in-replacement for the LoRA layers' .forward method. To use it, a bound
+        method must be created (bound to an instance of the XLoraLayer class).
+        """
+
+        if scalings is not None:
+            xlora_scalings = self.get_maybe_topk_scalings(scalings)
+
+        result = self.target.base_layer(x, *args, **kwargs)
+
+        # Ignore if disabled. We want to make sure this is always run.
+        if not self.target.merged:
+            for adapter_n, active_adapter in enumerate(self.target.active_adapters):
+                # TODO: implement X-LoRA with Lora+Dora layers
+                if self.target.use_dora.get(active_adapter, False):
+                    raise ValueError("X-LoRA currently does not support LoRA layers with DoRA")
+                if active_adapter not in self.target.lora_embedding_A:
+                    continue
+                embedding_A = self.target.lora_embedding_A[active_adapter].T
+                embedding_B = self.target.lora_embedding_B[active_adapter].T
+                scaling = self.target.scaling[active_adapter]
+                after_A = self.target._embed(x, embedding_A)  # type: ignore
+                if scalings is not None:
+                    after_A_mod = self.apply_scalings_to_x(after_A, xlora_scalings, adapter_n)
+                    scaling_weight = self.config.global_scaling_weight
+                else:
+                    after_A_mod = after_A
+                    scaling_weight = 1
+                result += (after_A_mod @ embedding_B) * scaling * scaling_weight
+
+        return result
+
+
+class XLoraConv2dLayer(XLoraLayer):
+    def __init__(
+        self,
+        model: nn.Module,
+        target: lora.Conv2d,
+        target_forward: Callable[..., Any],
+        layer_number: int,
+        config: XLoraConfig,
+    ) -> None:
+        super().__init__(model, target, target_forward, layer_number, config)
+
+    def forward(self, x: Tensor, *args: Any, scalings: Optional[Tensor] = None, **kwargs: Any) -> Tensor:
+        """
+        This method is designed to be a drop-in-replacement for the LoRA layers' .forward method. To use it, a bound
+        method must be created (bound to an instance of the XLoraLayer class).
+        """
+
+        previous_dtype = x.dtype
+
+        if scalings is not None:
+            xlora_scalings = self.get_maybe_topk_scalings(scalings)
+
+        result = self.target.base_layer(x, *args, **kwargs)
+
+        # Ignore if disabled. We want to make sure this is always run.
+        if not self.target.merged:
+            for adapter_n, active_adapter in enumerate(self.target.active_adapters):
+                # TODO: implement X-LoRA with Lora+Dora layers
+                if self.target.use_dora[active_adapter]:
+                    raise ValueError("X-LoRA currently does not support LoRA layers with DoRA")
+                if active_adapter not in self.target.lora_A.keys():
+                    continue
+                lora_A = self.target.lora_A[active_adapter]
+                lora_B = self.target.lora_B[active_adapter]
+                dropout = self.target.lora_dropout[active_adapter]
+                scaling = self.target.scaling[active_adapter]
+                x = x.to(lora_A.weight.dtype)  # type: ignore
+                if scalings is not None:
+                    x_mod = self.apply_scalings_to_x(x, xlora_scalings, adapter_n)
+                    scaling_weight = self.config.global_scaling_weight
+                else:
+                    x_mod = x
+                    scaling_weight = 1
+                result += lora_B(lora_A(dropout(x_mod))) * scaling * scaling_weight
+
+        result = result.to(previous_dtype)
+        return result
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/model.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..c1aae7c9a561ad74696fbf124bdab200068eb408
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/tuners/xlora/model.py
@@ -0,0 +1,520 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import copy
+from contextlib import contextmanager
+from functools import partial
+from typing import Optional, Union
+
+import torch
+import torch.nn as nn
+
+from peft.tuners.lora.layer import LoraLayer
+from peft.tuners.lora.model import LoraModel
+from peft.tuners.tuners_utils import BaseTuner
+from peft.utils.constants import DUMMY_TARGET_MODULES
+from peft.utils.save_and_load import set_peft_model_state_dict
+
+from .. import lora
+from .classifier import XLoraClassifier
+from .config import XLoraConfig
+from .layer import XLoraConv2dLayer, XLoraEmbeddingLayer, XLoraLinearLayer
+
+
+def convert_layers_to_xlora(
+    base: nn.Module,  # PeftModel
+    xloramodel: nn.Module,  # XLoraModel
+    config: XLoraConfig,
+) -> tuple[int, torch.device | None]:
+    """
+    Returns the number of swapped layers.
+    """
+    total_swapped = 0
+    all_layers = []
+
+    device = None
+    for module in base.modules():
+        # Check the exact type because classes like OPTLearnedPositionalEmbedding inherit from nn.Embedding
+        if isinstance(module, lora.Linear):
+            device = module.lora_A[next(iter(module.lora_A))].weight.device
+            new_layer = XLoraLinearLayer(
+                model=xloramodel,
+                target=module,
+                target_forward=module.forward,
+                layer_number=total_swapped,
+                config=config,
+            )
+            all_layers.append(new_layer)
+            module.forward = new_layer.forward  # type: ignore[method-assign]
+            total_swapped += 1
+        elif isinstance(module, lora.Embedding):
+            device = module.lora_embedding_A[next(iter(module.lora_embedding_A))].device
+            new_layer = XLoraEmbeddingLayer(
+                model=xloramodel,
+                target=module,
+                target_forward=module.forward,
+                layer_number=total_swapped,
+                config=config,
+            )
+            all_layers.append(new_layer)
+            module.forward = new_layer.forward  # type: ignore[method-assign]
+            total_swapped += 1
+        elif isinstance(module, lora.Conv2d):
+            device = module.lora_A[next(iter(module.lora_A))].weight.device
+            new_layer = XLoraConv2dLayer(
+                model=xloramodel,
+                target=module,
+                target_forward=module.forward,
+                layer_number=total_swapped,
+                config=config,
+            )
+            all_layers.append(new_layer)
+            module.forward = new_layer.forward  # type: ignore[method-assign]
+            total_swapped += 1
+
+    return (total_swapped, device)
+
+
+def _load_adapter_into_lora_model(
+    lora_model: LoraModel,
+    adapter_name: str,
+    model_id: str,
+    torch_device: Optional[str] = None,
+    ephemeral_gpu_offload: bool = False,
+    autocast_adapter_dtype: bool = True,
+    subfolder: Optional[str] = None,
+    **kwargs,
+):
+    """
+    This method emulates the behavior of `PeftModel.from_pretrained`. Updates to `PeftModel.from_pretrained` may need
+    to be reflected here.
+
+    All params pertain to the adapter (adapter name, model id, `i` is the adapter number in 0 indexing).
+    """
+    from peft.peft_model import PeftModel
+    from peft.tuners.lora.config import LoraConfig
+    from peft.utils.other import infer_device
+    from peft.utils.save_and_load import load_peft_weights
+
+    hf_hub_download_kwargs, kwargs = PeftModel._split_kwargs(kwargs)
+    if torch_device is None:
+        torch_device = infer_device()
+
+    if adapter_name not in lora_model.peft_config:
+        # load the config
+        lora_peft_config = LoraConfig.from_pretrained(
+            model_id,
+            ephemeral_gpu_offload=ephemeral_gpu_offload,
+            subfolder=subfolder,
+            **hf_hub_download_kwargs,
+        )
+        lora_peft_config.inference_mode = False
+        lora_model.peft_config[adapter_name] = lora_peft_config
+        lora_model.inject_adapter(lora_model.model, adapter_name)
+
+    adapter_weights = load_peft_weights(model_id, device=torch_device, subfolder=subfolder, **hf_hub_download_kwargs)
+    new_adapter_weights = {}
+    # Rework the keys to contain the adapter numbers
+    for old_key in adapter_weights.keys():
+        key: str = old_key
+        # Remove all the prefixes until we have model.<...>
+        while not (key.startswith("model.") and not key.startswith("model.model.")):
+            key = key[key.find(".") + 1 :]
+        # We always want model.model
+        key = "model." + key
+        new_adapter_weights[key] = adapter_weights[old_key]
+
+    # load the weights into the model
+    ignore_mismatched_sizes = kwargs.get("ignore_mismatched_sizes", False)
+    load_result = set_peft_model_state_dict(
+        lora_model,
+        new_adapter_weights,
+        adapter_name=adapter_name,
+        ignore_mismatched_sizes=ignore_mismatched_sizes,
+    )
+    if len(load_result.unexpected_keys) > 0:
+        raise ValueError(
+            f"Got unexpected keys! Please raise an issue and tag @EricLBuehler.\n\nunexpected_keys={load_result.unexpected_keys}"
+        )
+
+    if hasattr(lora_model, "_cast_adapter_dtype"):
+        lora_model._cast_adapter_dtype(adapter_name=adapter_name, autocast_adapter_dtype=autocast_adapter_dtype)
+
+
+class XLoraModel(BaseTuner):
+    """
+    Creates an X-LoRA (Mixture of LoRA experts), model from a pretrained transformers model. Currently, this X-LoRA
+    implementation only works with models with a transformer architecture.
+
+    The method is described in detail in https://arxiv.org/abs/2402.07148.
+
+    Args:
+        model ([`torch.nn.Module`]): The model to be adapted.
+        config ([`XLoraConfig`]): The configuration of the Lora model.
+        adapter_name (`str`): The name of the adapter, does not affect the LoRA adapter names.
+
+    Returns:
+        `torch.nn.Module`: The X-LoRA model.
+
+    Example:
+        ```py
+        >>> from transformers import AutoModelForCausalLM, AutoConfig, BitsAndBytesConfig
+        >>> from peft import LoraConfig, PeftModel, get_peft_model, prepare_model_for_kbit_training
+
+        >>> model_config = AutoConfig.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
+        >>> config = XLoraConfig(
+        ...     task_type="CAUSAL_LM",
+        ...     hidden_size=model_config.hidden_size,
+        ...     xlora_depth=4,
+        ...     adapters={
+        ...         "adapter_1": "./path/to/the/checkpoint/",
+        ...         "adapter_2": "./path/to/the/checkpoint/",
+        ...         "adapter_n": "./path/to/the/checkpoint/",
+        ...     },
+        ... )
+        >>> int8_config = BitsAndBytesConfig(load_in_8bit=True)
+        >>> model = AutoModelForCausalLM.from_pretrained(
+        ...     "mistralai/Mistral-7B-Instruct-v0.1",
+        ...     trust_remote_code=True,
+        ...     attn_implementation="flash_attention_2",
+        ...     device_map="cuda:0",
+        ...     torch_dtype=torch.bfloat16,
+        ...     quantization_config=int8_config,
+        ... )
+        >>> model = prepare_model_for_kbit_training(4)
+        >>> xlora_model = get_peft_model(model, config)
+        ```
+    """
+
+    def __init__(
+        self,
+        model: nn.Module,
+        config: Union[dict[str, XLoraConfig], XLoraConfig],
+        adapter_name: str,
+        torch_device: Optional[str] = None,
+        ephemeral_gpu_offload: bool = False,
+        autocast_adapter_dtype: bool = True,
+        **kwargs,
+    ) -> None:
+        """
+        Create a new X-LoRA model
+
+        Args:
+            model (`nn.Module`):
+                Base model to apply X-LoRA to.
+            config: ([`XLoraConfig`]):
+                X-LoRA configuration object.
+            adapter_name: (`str`):
+                Adapter name for the X-LoRA adapter.
+            torch_device (`str`, *optional*, defaults to None):
+                (For loading the LoRA adapters) The device to load the adapter on. If `None`, the device will be
+                inferred.
+            ephemeral_gpu_offload (`bool`, *optional*, defaults to `False`):
+                (For loading the LoRA adapters) Whether to use ephemeral GPU offloading for partially loaded modules.
+                Defaults to `False`.
+            autocast_adapter_dtype (`bool`, *optional*, defaults to `True`):
+                (For loading the LoRA adapters) Whether to autocast the adapter dtype. Defaults to `True`. Right now,
+                this will only cast adapter weights using float16 and bfloat16 to float32, as this is typically
+                required for stable training, and only affect select PEFT tuners.
+            kwargs: (`optional`):
+                (For loading the LoRA adapters) Additional arguments to modify the way the adapter is loaded, e.g. the
+                token for Hugging Face Hub.
+        """
+
+        nn.Module.__init__(self)
+
+        if isinstance(config, dict):
+            conf = config[adapter_name]
+        else:
+            conf = config
+
+        # Create an empty LoraModel
+        base_lora_config = copy.copy(conf)
+        base_lora_config.target_modules = DUMMY_TARGET_MODULES
+        # Imitate a LoraConfig, fields might need to be updated if LoraConfig is updated
+        base_lora_config.layer_replication = None
+        base_lora_config.bias = "none"
+        lora_model = LoraModel(model, base_lora_config, adapter_name)
+
+        self.xlora_config = conf
+        self.lora_model = lora_model
+
+        peft_config = conf
+
+        if hasattr(model.config, "use_cache") and model.config.use_cache:
+            raise ValueError("`use_cache` must be False")
+
+        adapters_items = peft_config.adapters.items()
+        if hasattr(self.xlora_config, "_subfolders"):
+            adapters_items = zip(peft_config.adapters.items(), self.xlora_config._subfolders)
+        else:
+            adapters_items = peft_config.adapters.items()
+
+        if hasattr(self.xlora_config, "_subfolders"):
+            for i, (_adapter_name, model_id), subfolder in enumerate(adapters_items):
+                _load_adapter_into_lora_model(
+                    lora_model=self.lora_model,
+                    adapter_name=str(i),
+                    model_id=model_id,
+                    torch_device=torch_device,
+                    ephemeral_gpu_offload=ephemeral_gpu_offload,
+                    autocast_adapter_dtype=autocast_adapter_dtype,
+                    subfolder=subfolder,
+                    **kwargs,
+                )
+        else:
+            for i, (_adapter_name, model_id) in enumerate(adapters_items):
+                _load_adapter_into_lora_model(
+                    lora_model=self.lora_model,
+                    adapter_name=str(i),
+                    model_id=model_id,
+                    torch_device=torch_device,
+                    ephemeral_gpu_offload=ephemeral_gpu_offload,
+                    autocast_adapter_dtype=autocast_adapter_dtype,
+                    subfolder=None,
+                    **kwargs,
+                )
+
+        self.lora_model.set_adapter(list(peft_config.adapters.keys()))
+
+        self._maybe_freeze_all_adapters()
+
+        total_swapped, device = convert_layers_to_xlora(
+            model,
+            self,
+            peft_config,
+        )
+
+        n_classes = len(peft_config.adapters)
+        xlora_classifier = XLoraClassifier(model, peft_config, n_classes, total_swapped, device)
+
+        # Setup the model internal state
+        self.internal_xlora_classifier = xlora_classifier
+        self.internal_xlora_scalings = None  # type: ignore
+        # Controlled by enable_adapter_layers or disable_adapter_layers
+        self.disabled = False
+
+    def _maybe_freeze_all_adapters(self):
+        self.eval()
+        if not self.xlora_config.use_trainable_adapters:
+            for name, param in self.named_parameters():
+                if "lora_" in name:
+                    param.requires_grad = False
+
+    def generate(self, *args, **kwargs):
+        kwargs["use_cache"] = False
+        res = self.lora_model.generate(*args, **kwargs)  # type: ignore
+        #  This is necessary because we use PeftModel.disable_adapter() which reenables the adapters
+        self._maybe_freeze_all_adapters()
+        return res
+
+    @contextmanager
+    def _enable_peft_forward_hooks(self, *generate_args, **generate_kwargs):
+        def scalings_injection_hook(target, args, kwargs, scalings):
+            # pre-forward hook to inject the adapter_names argument when using mixed adapter batches inference
+            kwargs["scalings"] = scalings
+            return args, kwargs
+
+        handles_to_remove = None
+
+        def pre_forward(module, *args, **kwargs):
+            nonlocal handles_to_remove
+
+            # =========================== Forward pass with "dummy" scalings ==================
+
+            args_real = args[0]
+            kwargs_real = args[1]
+            kwargs_real.update(kwargs)
+
+            dummy_scalings = self.internal_xlora_classifier.make_dummy_scalings(*args_real, **kwargs_real)
+
+            hook_handles = []
+            for module in self.modules():
+                if isinstance(module, LoraLayer):
+                    pre_forward = partial(scalings_injection_hook, scalings=dummy_scalings)
+                    handle = module.register_forward_pre_hook(pre_forward, with_kwargs=True)
+                    hook_handles.append(handle)
+
+            with torch.no_grad():
+                self.lora_model.disable_adapter_layers()
+
+                try:
+                    scaling_pass_kwargs = kwargs_real.copy()
+                    scaling_pass_kwargs["output_hidden_states"] = True
+                    scaling_pass_kwargs["return_dict"] = True
+                    try:
+                        base_output = self.lora_model.model.forward(*args_real, **scaling_pass_kwargs)
+                    finally:
+                        # Clean everything up
+                        for handle in hook_handles:
+                            handle.remove()
+                finally:
+                    self.lora_model.enable_adapter_layers()
+
+            xlora_scalings = self.internal_xlora_classifier(result=base_output, *args_real, **kwargs_real)
+
+            # =========================== Real forward pass with calculated scalings ==================
+
+            hook_handles = []
+            for module in self.modules():
+                if isinstance(module, LoraLayer):
+                    pre_forward = partial(scalings_injection_hook, scalings=xlora_scalings)
+                    handle = module.register_forward_pre_hook(pre_forward, with_kwargs=True)
+                    hook_handles.append(handle)
+
+            handles_to_remove = hook_handles
+
+        if not self.disabled:
+            forward_handle = self.lora_model.model.register_forward_pre_hook(pre_forward, with_kwargs=True)
+
+        # Run the forward pass: first the scaling pass in the hook, and then with the base model
+        yield
+
+        if not self.disabled:
+            # TODO(EricLBuehler): If we get a forward exception, we may have multiple forward hooks.
+            for handle in handles_to_remove:
+                handle.remove()
+            forward_handle.remove()
+
+    def __getattr__(self, name: str):
+        """Forward missing attributes to the wrapped module."""
+        try:
+            return super().__getattr__(name)  # defer to nn.Module's logic
+        except AttributeError:
+            if name == "lora_model":  # see #1892: prevent infinite recursion if class is not initialized
+                raise
+            return getattr(self.lora_model, name)
+
+    @staticmethod
+    def _prepare_adapter_config(peft_config, _model_config):
+        # Handle X-LoRA case
+        return peft_config
+
+    """
+    Does nothing. X-LoRA needs adapters to be frozen.
+    """
+
+    def _mark_only_adapters_as_trainable(self) -> None: ...
+
+    """
+    This enables the X-LoRA adapter.
+    """
+
+    def enable_adapter_layers(self) -> None:
+        self.disabled = False
+
+    """
+    This diasables the X-LoRA adapter.
+    """
+
+    def disable_adapter_layers(self) -> None:
+        self.disabled = True
+
+    def _create_and_replace(
+        self,
+        lora_config,
+        adapter_name,
+        target,
+        target_name,
+        parent,
+        current_key,
+    ):
+        # Does nothing because XLoraModel has no target modules
+        pass
+
+    @staticmethod
+    def _check_target_module_exists(lora_config, key):
+        # Does nothing because XLoraModel has no target modules
+        return False
+
+    def forward(self, *args, **kwargs):
+        return self.lora_model.model(*args, **kwargs)
+
+    def set_topk_lora(self, value: Optional[int]):
+        """
+        Sparsely select the specified top_k LoRA experts instead of the default dense method. Set to None to use dense.
+        This is reflected in the config.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        classifier.config.top_k_lora = value
+
+    def set_global_scaling_weight(self, weight: float):
+        """
+        Set the global LoRA weight, a scalar to multiply the output of each LoRA adapter by. This is by default 1. This
+        is reflected in the config.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        classifier.config.global_scaling_weight = weight
+
+    def set_scaling_pass_value(self, value: float | None):
+        """
+        Set the scaling pass value, the value to set the scalings to during the scaling pass. If the value is None, the
+        scaling pass value will be 1/n where n is the number of adapters.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        classifier._set_override_scaling_pass_value(value)
+
+    def get_global_scaling_weight(self) -> float:
+        """
+        Get the global LoRA weight.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        return classifier.config.global_scaling_weight
+
+    def get_latest_scalings(self) -> Optional[torch.Tensor]:
+        """
+        Returns the latest scalings prediction, or None if no scalings have been predicted. The tensor is of shape
+        (batch_size, seq_len, n_layers, n_classes).
+        """
+        return self.internal_xlora_scalings
+
+    def get_scalings_log(self) -> list[torch.Tensor]:
+        """
+        Returns a shallow (only copying the list itself not the tensors) copy of the list containing the scalings log.
+        Editing the list does not change the underlying log. The tensors are of shape (batch_size, seq_len, n_layers,
+        n_classes). The seq_len dim may vary with input dimension.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        return classifier.log_scalings.copy()
+
+    def enable_scalings_logging(self):
+        """
+        Enable scalings logging.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        classifier.scalings_logging = True
+
+    def disable_scalings_logging(self):
+        """
+        Disable scalings logging, without clearing the log.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        classifier.scalings_logging = False
+
+    def clear_scalings_log(self):
+        """
+        Clear the scalings log.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        classifier.log_scalings.clear()
+
+    def get_bucketed_scalings_log(self) -> dict[int, tuple[list[int], list[torch.Tensor]]]:
+        """
+        Returns bucketed scalings, bucketed by seq_len. Each value consists of the positions (the first) and the
+        associated tensors. The positions are paired with the associated tensors and give the position in the scaling
+        log.
+        """
+        classifier: XLoraClassifier = self.internal_xlora_classifier  # type: ignore
+        return classifier._get_bucketed_scalings()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..97474caad6264291f378be081670d847e087cc84
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/__init__.py
@@ -0,0 +1,98 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from .integrations import map_cache_to_layer_device_map
+from .loftq_utils import replace_lora_weights_loftq
+from .other import (
+    CONFIG_NAME,
+    INCLUDE_LINEAR_LAYERS_SHORTHAND,
+    SAFETENSORS_WEIGHTS_NAME,
+    TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING,
+    TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING,
+    WEIGHTS_NAME,
+    AuxiliaryTrainingWrapper,
+    ModulesToSaveWrapper,
+    _freeze_adapter,
+    _get_batch_size,
+    _get_input_embeddings_name,
+    _get_submodules,
+    _is_valid_match,
+    _prepare_prompt_learning_config,
+    _set_adapter,
+    _set_trainable,
+    bloom_model_postprocess_past_key_value,
+    cast_mixed_precision_params,
+    get_auto_gptq_quant_linear,
+    get_gptqmodel_quant_linear,
+    get_quantization_config,
+    id_tensor_storage,
+    infer_device,
+    prepare_model_for_kbit_training,
+    shift_tokens_right,
+    transpose,
+)
+from .peft_types import PeftType, TaskType, register_peft_method
+from .save_and_load import get_peft_model_state_dict, load_peft_weights, set_peft_model_state_dict
+
+
+__all__ = [
+    "CONFIG_NAME",
+    "INCLUDE_LINEAR_LAYERS_SHORTHAND",
+    "SAFETENSORS_WEIGHTS_NAME",
+    "TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING",
+    "TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING",
+    "WEIGHTS_NAME",
+    "AuxiliaryTrainingWrapper",
+    "ModulesToSaveWrapper",
+    "PeftType",
+    "TaskType",
+    "_freeze_adapter",
+    "_get_batch_size",
+    "_get_input_embeddings_name",
+    "_get_submodules",
+    "_is_valid_match",
+    "_prepare_prompt_learning_config",
+    "_set_adapter",
+    "_set_trainable",
+    "bloom_model_postprocess_past_key_value",
+    "cast_mixed_precision_params",
+    "get_auto_gptq_quant_linear",
+    "get_gptqmodel_quant_linear",
+    "get_peft_model_state_dict",
+    "get_quantization_config",
+    "id_tensor_storage",
+    "infer_device",
+    "load_peft_weights",
+    "map_cache_to_layer_device_map",
+    "prepare_model_for_kbit_training",
+    "register_peft_method",
+    "replace_lora_weights_loftq",
+    "set_peft_model_state_dict",
+    "shift_tokens_right",
+    "transpose",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/constants.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/constants.py
new file mode 100644
index 0000000000000000000000000000000000000000..e7c305926ad628825562ff46ed3b8d64745a1326
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/constants.py
@@ -0,0 +1,301 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+from transformers import BloomPreTrainedModel
+
+
+# needed for prefix-tuning of bloom model
+def bloom_model_postprocess_past_key_value(past_key_values):
+    past_key_values = torch.cat(past_key_values)
+    total_layers, batch_size, num_attention_heads, num_virtual_tokens, head_dim = past_key_values.shape
+    keys = past_key_values[: total_layers // 2]
+    keys = keys.transpose(2, 3).reshape(
+        total_layers // 2, batch_size * num_attention_heads, head_dim, num_virtual_tokens
+    )
+    values = past_key_values[total_layers // 2 :]
+    values = values.reshape(total_layers // 2, batch_size * num_attention_heads, num_virtual_tokens, head_dim)
+
+    return tuple(zip(keys, values))
+
+
+# needed for prefix-tuning of StarCoder models
+def starcoder_model_postprocess_past_key_value(past_key_values):
+    result = []
+    for k in past_key_values:
+        k = k[:, :, 0]
+        k = k.permute([1, 2, 0, 3])
+        k = k.reshape(*k.shape[:-2], -1)
+        result.append(k)
+    return tuple(result)
+
+
+TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING = {
+    "gpt_bigcode": starcoder_model_postprocess_past_key_value,
+}
+
+if hasattr(BloomPreTrainedModel, "_convert_to_standard_cache"):
+    # special handling for bloom architecture was fixed in:
+    # https://github.com/huggingface/transformers/pull/31445
+    # the _convert_to_standard_cache method is removed in the PR and thus serves as an indicator
+    TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING["bloom"] = bloom_model_postprocess_past_key_value
+
+TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING = {
+    "llama": ["input_layernorm", "post_attention_layernorm", "norm"],
+    "bloom": ["input_layernorm", "post_attention_layernorm", "ln_f"],
+    "llava": [
+        "multi_modal_projector",
+        "input_layernorm",
+        "post_attention_layernorm",
+        "norm",
+        "embed_tokens",
+        "lm_head",
+    ],
+    "t5": ["layer_norm", "final_layer_norm"],
+    "mt5": ["layer_norm", "final_layer_norm"],
+    "bart": ["self_attn_layer_norm", "encoder_attn_layer_norm", "final_layer_norm"],
+    "gpt2": ["ln_1", "ln_2", "ln_f"],
+    "blip-2": ["layernorm", "LayerNorm", "final_layer_norm", "self_attn_layer_norm"],
+    "gptj": ["ln_1", "ln_f"],
+    "falcon": ["input_layernorm", "post_attention_layernorm", "ln_f"],
+    "mistral": ["input_layernorm", "post_attention_layernorm", "norm"],
+    "phi": ["input_layernorm", "final_layernorm"],
+    "gemma": ["input_layernorm", "post_attention_layernorm", "norm"],
+    "gemma2": [
+        "input_layernorm",
+        "post_attention_layernorm",
+        "pre_feedforward_layernorm",
+        "post_feedforward_layernorm",
+        "norm",
+    ],
+    "qwen2": ["post_attention_layernorm"],
+}
+
+TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING = {
+    "t5": ["q", "v"],
+    "mt5": ["q", "v"],
+    "bart": ["q_proj", "v_proj"],
+    "gpt2": ["c_attn"],
+    "bloom": ["query_key_value"],
+    "blip-2": ["q", "v", "q_proj", "v_proj"],
+    "opt": ["q_proj", "v_proj"],
+    "gptj": ["q_proj", "v_proj"],
+    "gpt_neox": ["query_key_value"],
+    "gpt_neo": ["q_proj", "v_proj"],
+    "bert": ["query", "value"],
+    "roberta": ["query", "value"],
+    "xlm-roberta": ["query", "value"],
+    "electra": ["query", "value"],
+    "deberta-v2": ["query_proj", "value_proj"],
+    "deberta": ["in_proj"],
+    "layoutlm": ["query", "value"],
+    "llama": ["q_proj", "v_proj"],
+    "chatglm": ["query_key_value"],
+    "gpt_bigcode": ["c_attn"],
+    "mpt": ["Wqkv"],
+    "RefinedWebModel": ["query_key_value"],
+    "RefinedWeb": ["query_key_value"],
+    "falcon": ["query_key_value"],
+    "btlm": ["c_proj", "c_attn"],
+    "codegen": ["qkv_proj"],
+    "mistral": ["q_proj", "v_proj"],
+    "mixtral": ["q_proj", "v_proj"],
+    "stablelm": ["q_proj", "v_proj"],
+    "phi": ["q_proj", "v_proj", "fc1", "fc2"],
+    "gemma": ["q_proj", "v_proj"],
+    "gemma2": ["q_proj", "v_proj"],
+    "qwen2": ["q_proj", "v_proj"],
+}
+
+TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING = {
+    "t5": ["k", "v", "wo"],
+    "mt5": ["k", "v", "wi_1"],
+    "gpt2": ["c_attn", "mlp.c_proj"],
+    "bloom": ["query_key_value", "mlp.dense_4h_to_h"],
+    "roberta": ["key", "value", "output.dense"],
+    "opt": ["q_proj", "k_proj", "fc2"],
+    "gptj": ["q_proj", "v_proj", "fc_out"],
+    "gpt_neox": ["query_key_value", "dense_4h_to_h"],
+    "gpt_neo": ["q_proj", "v_proj", "c_proj"],
+    "bart": ["q_proj", "v_proj", "fc2"],
+    "gpt_bigcode": ["c_attn", "mlp.c_proj"],
+    "llama": ["k_proj", "v_proj", "down_proj"],
+    "mistral": ["k_proj", "v_proj", "down_proj"],
+    "mixtral": ["k_proj", "v_proj", "w2"],
+    "bert": ["key", "value", "output.dense"],
+    "deberta-v2": ["key_proj", "value_proj", "output.dense"],
+    "deberta": ["in_proj", "output.dense"],
+    "RefinedWebModel": ["query_key_value", "dense_4h_to_h"],
+    "RefinedWeb": ["query_key_value", "dense_4h_to_h"],
+    "falcon": ["query_key_value", "dense_4h_to_h"],
+    "phi": ["q_proj", "v_proj", "fc2"],
+    "gemma": ["q_proj", "v_proj", "down_proj"],
+    "gemma2": ["q_proj", "v_proj", "down_proj"],
+    "qwen2": ["q_proj", "v_proj", "down_proj"],
+}
+
+TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING = {
+    "t5": ["wo"],
+    "mt5": [],
+    "gpt2": ["mlp.c_proj"],
+    "bloom": ["mlp.dense_4h_to_h"],
+    "roberta": ["output.dense"],
+    "opt": ["fc2"],
+    "gptj": ["fc_out"],
+    "gpt_neox": ["dense_4h_to_h"],
+    "gpt_neo": ["c_proj"],
+    "bart": ["fc2"],
+    "gpt_bigcode": ["mlp.c_proj"],
+    "llama": ["down_proj"],
+    "mistral": ["down_proj"],
+    "mixtral": ["w2"],
+    "bert": ["output.dense"],
+    "deberta-v2": ["output.dense"],
+    "deberta": ["output.dense"],
+    "RefinedWeb": ["dense_4h_to_h"],
+    "RefinedWebModel": ["dense_4h_to_h"],
+    "falcon": ["dense_4h_to_h"],
+    "phi": ["fc2"],
+    "gemma": ["down_proj"],
+    "gemma2": ["down_proj"],
+    "qwen2": ["down_proj"],
+}
+
+TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING = {
+    "t5": ["q", "k", "v", "o", "wi", "wo"],
+    "mt5": ["q", "k", "v", "o", "wi_0", "wi_1", "wo"],
+    "bart": ["q_proj", "k_proj", "v_proj", "out_proj", "fc1", "fc2"],
+    "gpt2": ["c_attn"],
+    "bloom": ["query_key_value"],
+    "opt": ["q_proj", "k_proj", "v_proj", "out_proj", "fc1", "fc2"],
+    "gptj": ["q_proj", "v_proj"],
+    "gpt_neox": ["query_key_value"],
+    "gpt_neo": ["q_proj", "v_proj"],
+    "llama": ["q_proj", "v_proj"],
+    "bert": ["query", "value"],
+    "roberta": ["query", "key", "value", "dense"],
+    # "xlm-roberta": ["query", "value"],
+    # "electra": ["query", "value"],
+    "deberta-v2": ["query_proj", "key_proj", "value_proj", "dense"],
+    "gpt_bigcode": ["c_attn"],
+    "deberta": ["in_proj"],
+    # "layoutlm": ["query", "value"],
+    "qwen2": ["q_proj", "v_proj"],
+}
+
+TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING = {
+    "t5": ["q", "v"],
+    "mt5": ["q", "v"],
+    "bart": ["q_proj", "v_proj"],
+    "gpt2": ["c_attn"],
+    "bloom": ["query_key_value"],
+    "blip-2": ["q", "v", "q_proj", "v_proj"],
+    "opt": ["q_proj", "v_proj"],
+    "gptj": ["q_proj", "v_proj"],
+    "gpt_neox": ["query_key_value"],
+    "gpt_neo": ["q_proj", "v_proj"],
+    "bert": ["query", "value"],
+    "roberta": ["query", "value"],
+    "xlm-roberta": ["query", "value"],
+    "electra": ["query", "value"],
+    "deberta-v2": ["query_proj", "value_proj"],
+    "deberta": ["in_proj"],
+    "layoutlm": ["query", "value"],
+    "llama": ["q_proj", "v_proj"],
+    "chatglm": ["query_key_value"],
+    "gpt_bigcode": ["c_attn"],
+    "mpt": ["Wqkv"],
+    "RefinedWebModel": ["query_key_value"],
+    "RefinedWeb": ["query_key_value"],
+    "falcon": ["query_key_value"],
+    "btlm": ["c_proj", "c_attn"],
+    "codegen": ["qkv_proj"],
+    "mistral": ["q_proj", "v_proj"],
+    "mixtral": ["q_proj", "v_proj"],
+    "stablelm": ["q_proj", "v_proj"],
+    "phi": ["q_proj", "v_proj"],
+    "gemma": ["q_proj", "v_proj"],
+    "gemma2": ["q_proj", "v_proj"],
+    "qwen2": ["q_proj", "v_proj"],
+}
+
+TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING = {
+    "t5": ["q", "v"],
+    "mt5": ["q", "v"],
+    "bart": ["q_proj", "v_proj"],
+    "gpt2": ["mlp.c_proj"],
+    "bloom": ["query_key_value"],
+    "blip-2": ["q", "v", "q_proj", "v_proj"],
+    "opt": ["q_proj", "v_proj"],
+    "gptj": ["q_proj", "v_proj"],
+    "gpt_neox": ["query_key_value"],
+    "gpt_neo": ["q_proj", "v_proj"],
+    "bert": ["query", "value"],
+    "roberta": ["query", "value"],
+    "xlm-roberta": ["query", "value"],
+    "electra": ["query", "value"],
+    "deberta-v2": ["query_proj", "value_proj"],
+    "deberta": ["in_proj"],
+    "layoutlm": ["query", "value"],
+    "llama": ["q_proj", "v_proj"],
+    "chatglm": ["query_key_value"],
+    "gpt_bigcode": ["mlp.c_proj"],
+    "mpt": ["Wqkv"],
+    "RefinedWebModel": ["query_key_value"],
+    "RefinedWeb": ["query_key_value"],
+    "falcon": ["query_key_value"],
+    "codegen": ["qkv_proj"],
+    "mistral": ["q_proj", "v_proj"],
+    "mixtral": ["q_proj", "v_proj"],
+    "stablelm": ["q_proj", "v_proj"],
+    "phi": ["q_proj", "v_proj", "fc1", "fc2"],
+    "gemma": ["q_proj", "v_proj"],
+    "gemma2": ["q_proj", "v_proj"],
+    "qwen2": ["q_proj", "v_proj"],
+}
+
+TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING = {
+    "t5": ["q", "k", "v", "o", "wi", "wo"],
+    "mt5": ["q", "k", "v", "o", "wi_0", "wi_1", "wo"],
+    "bart": ["q_proj", "k_proj", "v_proj", "out_proj", "fc1", "fc2"],
+    "gpt2": ["c_attn"],
+    "bloom": ["query_key_value"],
+    "opt": ["q_proj", "k_proj", "v_proj", "out_proj", "fc1", "fc2"],
+    "gptj": ["q_proj", "v_proj"],
+    "gpt_neox": ["query_key_value"],
+    "gpt_neo": ["q_proj", "v_proj"],
+    "llama": ["q_proj", "v_proj"],
+    "bert": ["query", "value"],
+    "roberta": ["query", "value"],
+    "deberta-v2": ["query_proj", "key_proj", "value_proj", "dense"],
+    "gpt_bigcode": ["c_attn"],
+    "deberta": ["in_proj"],
+    "qwen2": ["q_proj", "v_proj"],
+}
+
+WEIGHTS_NAME = "adapter_model.bin"
+SAFETENSORS_WEIGHTS_NAME = "adapter_model.safetensors"
+CONFIG_NAME = "adapter_config.json"
+EMBEDDING_LAYER_NAMES = ["embed_tokens", "lm_head"]
+SEQ_CLS_HEAD_NAMES = ["score", "classifier"]
+INCLUDE_LINEAR_LAYERS_SHORTHAND = "all-linear"
+TOKENIZER_CONFIG_NAME = "tokenizer_config.json"
+DUMMY_TARGET_MODULES = "dummy-target-modules"
+DUMMY_MODEL_CONFIG = {"model_type": "custom"}
+
+# If users specify more than this number of target modules, we apply an optimization to try to reduce the target modules
+# to a minimal set of suffixes, which makes loading faster. We only apply this when exceeding a certain size since
+# otherwise there is no point in optimizing and there is a small chance of bugs in the optimization algorithm, so no
+# point in taking unnecessary risks. See #2045 for more context.
+MIN_TARGET_MODULES_FOR_OPTIMIZATION = 20
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/hotswap.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/hotswap.py
new file mode 100644
index 0000000000000000000000000000000000000000..f05ecbd00ff1e44048d121a4399e36b300d7f3f7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/hotswap.py
@@ -0,0 +1,632 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import math
+import warnings
+from operator import attrgetter
+from typing import Literal, Optional
+
+import torch
+
+from peft.config import PeftConfig
+from peft.mapping import PEFT_TYPE_TO_CONFIG_MAPPING, PEFT_TYPE_TO_PREFIX_MAPPING
+from peft.tuners.lora import Conv2d, Linear, LoraConfig, LoraLayer
+
+from .other import get_pattern_key, infer_device
+from .peft_types import PeftType
+from .save_and_load import _insert_adapter_name_into_state_dict, load_peft_weights
+
+
+# so far only LoRA is supported
+CONFIG_KEYS_TO_CHECK = {PeftType.LORA: ["use_rslora", "lora_dropout", "alpha_pattern", "use_dora"]}
+
+
+def _update_scaling(lora_module, adapter_name, scaling=None):
+    """
+    Update the value of the scalings of the LoRA module.
+
+    Takes into consideration that scalings can be tensors from prepare_model_for_compiled_hotswap.
+    """
+    if lora_module.scaling[adapter_name] == scaling:
+        return
+
+    if isinstance(lora_module.scaling[adapter_name], torch.Tensor):
+        lora_module.scaling[adapter_name].fill_(scaling)
+    elif isinstance(lora_module.scaling[adapter_name], (float, int)):
+        lora_module.scaling[adapter_name] = scaling
+    else:
+        raise ValueError(
+            "Something went wrong when trying to set the new scale value, expected to find the old value to be of type "
+            f"float or torch.Tensor, got {type(lora_module.scaling[adapter_name])} instead."
+        )
+
+
+def _convert_scalings_to_tensor(model) -> bool:
+    """
+    Convert the LoRA scaling values into torch.tensors to prevent recompilation if they change.
+
+    Returns:
+        bool:
+            Returns `True` if an appropriate adapter was found, else `False`.
+    """
+    found_adapter = False
+    for module in model.modules():
+        if not isinstance(module, LoraLayer):
+            continue
+
+        found_adapter = True
+        scaling = module.scaling
+        for key, val in scaling.items():
+            if isinstance(val, float):
+                # no need to deal with dtype as scalars are coerced
+                scaling[key] = torch.tensor(val, device=module.weight.device)
+            elif not isinstance(val, torch.Tensor):
+                raise ValueError(
+                    "Something went wrong while trying to convert the scalings, expected to find values of type float "
+                    f"but found {type(val)} instead."
+                )
+    return found_adapter
+
+
+def _get_padded_linear(lora_module: torch.nn.Module, target_rank: int, is_lora_A: bool) -> torch.nn.Linear:
+    """
+    Get a new Linear layer for LoRA with padded weights according to the target rank.
+
+    Args:
+        lora_module (nn.Module):
+            The LoRA sub-module (e.g. module.lora_A[adapter_name]).
+        target_rank (int):
+            The desired rank to pad to.
+        is_lora_A (bool):
+            True if this is the LoRA A matrix, False if LoRA B.
+
+    Returns:
+        nn.Linear:
+            A newly created and padded Linear layer. If the rank already fit, the original layer is returned.
+    """
+    weight = lora_module.weight
+    # For LoRA A, the "rank dimension" is weight.size(0) (out_features).
+    # For LoRA B, it is weight.size(1) (in_features).
+    original_rank = weight.size(0) if is_lora_A else weight.size(1)
+
+    # If no padding needed
+    if original_rank == target_rank:
+        return lora_module
+
+    if original_rank > target_rank:
+        raise ValueError(
+            f"Trying to pad the adapter to the target rank {target_rank}, but the original rank is larger "
+            f"({original_rank}). This is not possible."
+        )
+
+    out_features, in_features = weight.shape
+
+    # lora_A and lora_B are always nn.Linear
+    if is_lora_A:
+        # LoRA A affects out_features
+        padded = torch.zeros(target_rank, in_features, device=weight.device, dtype=weight.dtype)
+        padded[:original_rank, :] = weight
+        new_layer = torch.nn.Linear(in_features, target_rank, bias=lora_module.bias is not None)
+    else:
+        # LoRA B affects in_features
+        padded = torch.zeros(out_features, target_rank, device=weight.device, dtype=weight.dtype)
+        padded[:, :original_rank] = weight
+        new_layer = torch.nn.Linear(target_rank, out_features, bias=lora_module.bias is not None)
+
+    # Sanity check
+    if new_layer.weight.shape != padded.shape:
+        raise ValueError(
+            "Something went wrong when trying to pad the LoRA Linear weights, the new shape should be "
+            f"{padded.shape} but {new_layer.weight.shape} was found. Please open an issue on PEFT "
+            "(https://github.com/huggingface/peft/issues) and report this error."
+        )
+    if (lora_module.bias is not None) and (new_layer.bias.shape != lora_module.bias.shape):
+        raise ValueError(
+            "Something went wrong when trying to pad the LoRA Linear bias, the new shape should be "
+            f"{lora_module.bias.shape} but {new_layer.bias.shape} was found. Please open an issue on PEFT "
+            "(https://github.com/huggingface/peft/issues) and report this error."
+        )
+
+    new_layer.weight.data = padded
+    # Copy bias if present
+    if lora_module.bias is not None:
+        new_layer.bias.data = lora_module.bias.data
+
+    return new_layer
+
+
+def _get_padded_conv2d(lora_module: torch.nn.Module, target_rank: int, is_lora_A: bool) -> torch.nn.Conv2d:
+    """
+    Get a new Conv2d layer for LoRA with padded weights according to the target rank.
+
+    Args:
+        lora_module (nn.Module):
+            The LoRA sub-module (e.g. module.lora_A[adapter_name]).
+        target_rank (int):
+            The desired rank to pad to.
+        is_lora_A (bool):
+            True if this is the LoRA A matrix, False if LoRA B.
+
+    Returns:
+        nn.Conv2d:
+            A newly created and padded Conv2d layer. If the rank already fit, the original layer is returned.
+    """
+    weight = lora_module.weight
+    # For Conv2d: [out_channels, in_channels, kernel_height, kernel_width]
+    out_channels, in_channels, kh, kw = weight.shape
+    original_rank = out_channels if is_lora_A else in_channels
+
+    if original_rank == target_rank:
+        return lora_module
+
+    if original_rank > target_rank:
+        raise ValueError(
+            f"Trying to pad the adapter to the target rank {target_rank}, but the original rank is larger "
+            f"({original_rank}). This is not possible."
+        )
+
+    # lora_A and lora_B are always nn.Conv2d
+    if is_lora_A:
+        # LoRA A affects out_channels
+        padded = torch.zeros(target_rank, in_channels, kh, kw, device=weight.device, dtype=weight.dtype)
+        padded[:out_channels, :, :, :] = weight
+        new_layer = torch.nn.Conv2d(
+            in_channels,
+            target_rank,
+            kernel_size=lora_module.kernel_size,
+            stride=lora_module.stride,
+            padding=lora_module.padding,
+            bias=lora_module.bias is not None,
+            groups=lora_module.groups,
+        )
+    else:
+        # LoRA B affects in_channels
+        padded = torch.zeros(out_channels, target_rank, kh, kw, device=weight.device, dtype=weight.dtype)
+        padded[:, :in_channels, :, :] = weight
+        new_layer = torch.nn.Conv2d(
+            target_rank,
+            out_channels,
+            kernel_size=lora_module.kernel_size,
+            stride=lora_module.stride,
+            padding=lora_module.padding,
+            bias=lora_module.bias is not None,
+            groups=lora_module.groups,
+        )
+
+    # Sanity check
+    if new_layer.weight.shape != padded.shape:
+        raise ValueError(
+            "Something went wrong when trying to pad the LoRA  weights, the new shape should be "
+            f"{padded.shape} but {new_layer.weight.shape} was found. Please open an issue on PEFT "
+            "(https://github.com/huggingface/peft/issues) and report this error."
+        )
+    if (lora_module.bias is not None) and (new_layer.bias.shape != lora_module.bias.shape):
+        raise ValueError(
+            "Something went wrong when trying to pad the LoRA Conv2d bias, the new shape should be "
+            f"{lora_module.bias.shape} but {new_layer.bias.shape} was found. Please open an issue on PEFT "
+            "(https://github.com/huggingface/peft/issues) and report this error."
+        )
+
+    new_layer.weight.data = padded
+    # Copy bias if present
+    if lora_module.bias is not None:
+        new_layer.bias.data = lora_module.bias.data
+
+    return new_layer
+
+
+def _pad_lora_weights(model: torch.nn.Module, target_rank: int) -> bool:
+    """
+    Pad LoRA weights in a model to a target rank while preserving the original behavior.
+
+    Args:
+      model (nn.Module): The model containing LoRA modules (with lora_A and lora_B).
+      target_rank (int): The target rank to pad to.
+
+    Returns:
+        bool:
+            Returns `True` if an appropriate adapter was found, else `False`.
+    """
+    found_adapter = False
+
+    for module in model.modules():
+        # Decide which pad function to call based on module type
+        if isinstance(module, Linear):
+            pad_fn = _get_padded_linear
+        elif isinstance(module, Conv2d):
+            pad_fn = _get_padded_conv2d
+        else:
+            # Skip any other module types
+            continue
+
+        # Pad LoRA A
+        for adapter_name, lora_A_module in module.lora_A.items():
+            new_layer = pad_fn(lora_A_module, target_rank=target_rank, is_lora_A=True)
+            module.lora_A[adapter_name] = new_layer
+
+        # Pad LoRA B
+        for adapter_name, lora_B_module in module.lora_B.items():
+            new_layer = pad_fn(lora_B_module, target_rank=target_rank, is_lora_A=False)
+            module.lora_B[adapter_name] = new_layer
+
+        found_adapter = True
+    return found_adapter
+
+
+def prepare_model_for_compiled_hotswap(
+    model: torch.nn.Module,
+    *,
+    target_rank: Optional[int] = None,
+    config: Optional[LoraConfig | dict[str, LoraConfig]] = None,
+    check_compiled: Literal["error", "warn", "ignore"] = "error",
+) -> None:
+    """
+    Helper function that prepares the model so that it can later be compiled and then used with hot-swapping.
+
+    It is necessary to call this function on the model for hot-swapping to work if both of these are true:
+
+    - the different LoRA adapters have different ranks and/or different alpha values (i.e. scalings)
+    - you plan to torch.compile the model and want to avoid re-compilation
+
+    It is important to call this function *after* the first LoRA adapter has been loaded (i.e. the one that will be
+    swapped out) but *before* the model is compiled.
+
+    Even with this function, hot-swapping LoRA adapters that target different layers is still not supported.
+
+    Note: This function modifies the model in-place. If you want to restore the model to its initial state, you will
+    have to reload it.
+
+    Args:
+        model (`nn.Module`):
+            The model with the loaded adapter, before compilation.
+        target_rank (`int`, *optional*):
+            The target rank to pad the LoRA weights to. Should be the maximum rank among all LoRA adapters that will be
+            hot-swapped. If not specified, the target ranks will not be changed.
+        config (`LoraConfig` or `dict[str, LoraConfig]`, *optional*):
+            Optionally pass the `LoraConfig`s of the LoRA adapters. If passed, the rank in the configs will be updated
+            to `target_rank`.
+        check_compiled (`str`, *optional*, defaults to `"error"`):
+            How to handle the case when the model is already compiled, which should generally be avoided. The options
+            are:
+              - "error" (default): raise an error
+              - "warn": issue a warning
+              - "ignore": do nothing
+
+    Raises:
+        ValueError
+            If the model is already compiled or if no adpater layer was found, raise an error.
+
+    Example:
+
+        ```py
+        base_model = ...
+        model = PeftModel.from_pretrained(base_model, path_adapter_0)
+        # Prepare the model to allow hotswapping even if ranks/scalings of 2nd adapter differ.
+        # You can skip this step if all ranks and scalings are identical.
+        prepare_model_for_compiled_hotswap(model, target_rank=highest_lora_rank)
+        model = torch.compile(model)
+        # do inference with adapter 0
+        # replace the "default" lora adapter with the new one
+        hotswap_adapter(model, path_adapter_1, adapter_name="default", torch_device=device)
+        # do inference with adapter 1
+        ```
+
+    """
+    is_compiled = hasattr(model, "_orig_mod") or getattr(model, "_compiled_call_impl", False)
+    if is_compiled:
+        if check_compiled == "error":
+            raise ValueError("Call prepare_model_for_compiled_hotswap *before* compiling the model")
+        elif check_compiled == "warn":
+            warnings.warn(
+                "prepare_model_for_compiled_hotswap was called with a model that is already compiled. This will likely "
+                "result in re-compilation, hurting performance. Call the function before compiling the model."
+            )
+        elif check_compiled != "ignore":
+            raise ValueError(
+                f"check_compiles should be one of 'error', 'warn', or 'ignore', got '{check_compiled}' instead."
+            )
+
+    conversion_found_adapter = _convert_scalings_to_tensor(model)
+    if target_rank is not None:
+        padding_found_adapter = _pad_lora_weights(model, target_rank=target_rank)
+    else:
+        padding_found_adapter = False
+
+    if not (conversion_found_adapter or padding_found_adapter):
+        raise ValueError(
+            "No adapter layers found on the model, make sure call `prepare_model_for_compiled_hotswap` after loading "
+            "the first adapter and before loading the second adapter."
+        )
+
+    if not config:
+        return
+    if target_rank is None:
+        return
+
+    if not isinstance(config, dict):
+        # config can be either a PeftConfig, or a dict of PeftConfigs like PeftModel.peft_config
+        config = {"dummy": config}
+
+    for lora_config in config.values():
+        lora_config.r = target_rank
+        if lora_config.rank_pattern:
+            for key in lora_config.rank_pattern:
+                lora_config.rank_pattern[key] = target_rank
+
+
+def hotswap_adapter_from_state_dict(
+    model: torch.nn.Module,
+    state_dict: dict[str, torch.Tensor],
+    adapter_name: str,
+    config: LoraConfig,
+    parameter_prefix: str = "lora_",
+):
+    """
+    Swap out the adapter weights from the model with the weights from state_dict.
+
+    As of now, only LoRA is supported.
+
+    This is a low-level function that assumes that the adapters have been checked for compatibility and that the
+    state_dict has been correctly mapped to work with PEFT. For a high level function that performs this work for you,
+    use `hotswap_adapter` instead.
+
+    Args:
+        model (`nn.Module`):
+            The model with the loaded adapter.
+        state_dict (`dict[str, torch.Tensor]`):
+            The state dict of the new adapter, which needs to be compatible (targeting same modules etc.).
+        adapter_name (`str`):
+            The name of the adapter that should be hot-swapped, e.g. `"default"`. The name will remain the same after
+            swapping.
+        config (`LoraConfig`):
+            The config of the LoRA adapter. This is used to determine the scaling and rank of the adapter.
+        parameter_prefix (`str`, *optional*, defaults to `"lora_"`)
+            The prefix used to identify the adapter's keys in the state dict. For LoRA, this would be `"lora_"` (the
+            default).
+
+    Raises:
+        RuntimeError
+            If the old and the new adapter are not compatible, a RuntimeError is raised.
+
+    """
+    # Ensure that all the keys of the new adapter correspond exactly to the keys of the old adapter, otherwise
+    # hot-swapping is not possible
+
+    # _orig_mod is for torch.compile(model) and _compiled_call_impl is for model.compile() (not wrapped)
+    is_compiled = hasattr(model, "_orig_mod")
+    is_compiled_inplace = bool(getattr(model, "_compiled_call_impl", None))
+    # TODO: there is probably a more precise way to identify the adapter keys
+    missing_keys = {k for k in model.state_dict() if (parameter_prefix in k) and (adapter_name in k)}
+    unexpected_keys = []
+
+    # first: dry run, not swapping anything
+    for key, new_val in state_dict.items():
+        try:
+            old_val = attrgetter(key)(model)
+        except AttributeError:
+            unexpected_keys.append(key)
+            continue
+
+        if is_compiled:
+            missing_keys.remove("_orig_mod." + key)
+        else:
+            missing_keys.remove(key)
+
+    # Right now, we don't deal with unexpected keys, i.e. if the adapter being swapped in targeting new layers. We could
+    # probably add LoRA to these layers ad hoc, but that would not work with compiled models.
+    if unexpected_keys:
+        msg = f"Hot swapping the adapter did not succeed, unexpected keys found: {', '.join(unexpected_keys)}."
+        raise RuntimeError(msg)
+
+    # If the adapter that is being swapped in is missing some keys, this is fine. We just need to ensure that those LoRA
+    # weights from the previous adapter are set to 0 so that they don't influence the output. We don't need to worry
+    # about ranks are alphas.
+    for key in missing_keys:
+        # in case it's a compiled model
+        key = key.removeprefix("_orig_mod.")
+        # get LoRA parent module name by removing the 'lora_*..weight' part
+        module_name = ".".join(key.split(".")[:-3])
+        module = model.get_submodule(module_name)
+        old_val = attrgetter(key)(model)
+        old_val.data.fill_(0.0)
+
+    # actual swapping
+    for key, new_val in state_dict.items():
+        # get LoRA parent module name by removing the 'lora_*..weight' part
+        module_name = ".".join(key.split(".")[:-3])
+        module = model.get_submodule(module_name)
+
+        # swap alpha/scaling
+        r_key = get_pattern_key(config.rank_pattern.keys(), key)
+        alpha_key = get_pattern_key(config.alpha_pattern.keys(), key)
+        rank = config.rank_pattern.get(r_key, config.r)
+        alpha = config.alpha_pattern.get(alpha_key, config.lora_alpha)
+        if config.use_rslora:
+            scaling = alpha / math.sqrt(rank)
+        else:
+            scaling = alpha / rank
+        _update_scaling(module, adapter_name=adapter_name, scaling=scaling)
+
+        # swap actual weights
+        # no need to account for potential _orig_mod in key here, as torch handles that
+        old_val = attrgetter(key)(model)
+        new_val = new_val.to(old_val.data.device)
+
+        # We try to detect if the model is compiled but it does not always work, e.g. if hotswapping is called from
+        # within the model itself. In this case, swap_tensors raises RuntimeError and should continue without
+        # swap_tensors.
+        if not is_compiled and not is_compiled_inplace:
+            try:
+                torch.utils.swap_tensors(old_val, new_val)
+                continue
+            except RuntimeError:
+                is_compiled = True
+
+        # Compiled models don't work with swap_tensors because there are weakrefs for the tensor. It is unclear if
+        # this workaround could not cause trouble but the tests indicate that it works.
+        if old_val.shape == new_val.shape:
+            # either
+            # - adapters had the same rank
+            # - adapters were padded with prepare_model_for_compiled_hotswap and 2nd adapter was larger
+            old_val.data = new_val.data
+        else:
+            # if 2nd adapter was smaller, ensure to fill up to adapter dimension and set the rest to zeros
+            if old_val.dim() not in (2, 4):
+                raise NotImplementedError(
+                    f"Trying to hotswap an adapter whose weight has {old_val.dim()} dimensions, but only Conv2d and "
+                    "Linear are supported"
+                )
+
+            # Linear or Conv2d: the check for dim 0 or 1 works for both of these layer types
+            if old_val.shape[0] > new_val.shape[0]:
+                old_val.data.fill_(0)
+                old_val.data[: new_val.shape[0]] = new_val.data
+            elif old_val.shape[1] > new_val.shape[1]:
+                old_val.data.fill_(0)
+                old_val.data[:, : new_val.shape[1]] = new_val.data
+            else:
+                raise ValueError(
+                    f"Incompatible shapes found for LoRA weights {key}: {old_val.shape} vs {new_val.shape}. Please "
+                    "ensure that all ranks are padded to the largest rank among all LoRA adapters by using "
+                    "peft.utils.hotswap.prepare_model_for_compiled_hotswap."
+                )
+
+
+def check_hotswap_configs_compatible(config0: PeftConfig, config1: PeftConfig) -> None:
+    """
+    Check if two configs are compatible for hot-swapping.
+
+    Only LoRA parameters are checked for now.
+
+    To hot-swap two adapters, their configs must be compatible. Otherwise, the results could be false. E.g. if they use
+    different alpha values, after hot-swapping, the alphas from the first adapter would still be used with the weights
+    from the 2nd adapter, which would result in incorrect behavior. There is probably a way to swap these values as
+    well, but that's not implemented yet, and we need to be careful not to trigger re-compilation if the model is
+    compiled (so no modification of the dict).
+
+    """
+
+    if config0.peft_type != config1.peft_type:
+        msg = f"Incompatible PEFT types found: {config0.peft_type.value} and {config1.peft_type.value}"
+        raise ValueError(msg)
+
+    if config0.peft_type not in CONFIG_KEYS_TO_CHECK:
+        msg = (
+            f"Hotswapping only supports {', '.join(CONFIG_KEYS_TO_CHECK.keys())} but "
+            f"{config0.peft_type.value} was passed."
+        )
+        raise ValueError(msg)
+    config_keys_to_check = CONFIG_KEYS_TO_CHECK[config0.peft_type]
+
+    # TODO: This is a very rough check only for LoRA at the moment. Also, there might be some options that don't
+    # necessarily require an error.
+    config0 = config0.to_dict()
+    config1 = config1.to_dict()
+    sentinel = object()
+    for key in config_keys_to_check:
+        val0 = config0.get(key, sentinel)
+        val1 = config1.get(key, sentinel)
+        if val0 != val1:
+            raise ValueError(f"Configs are incompatible: for {key}, {val0} != {val1}")
+
+
+def hotswap_adapter(model, model_name_or_path, adapter_name, torch_device=None, **kwargs):
+    """Substitute old adapter data with new adapter data, keeping the rest the same.
+
+    As of now, only LoRA is supported.
+
+    This function is useful when you want to replace the loaded adapter with a new adapter. The adapter name will
+    remain the same, but the weights and other parameters will be swapped out.
+
+    If the adapters are incomptabile, e.g. targeting different layers or having different alpha values, an error will
+    be raised.
+
+    Example:
+
+    ```py
+    >>> import torch
+    >>> from transformers import AutoModelForCausalLM
+    >>> from peft import PeftModel
+    >>> from peft.utils.hotswap import hotswap_adapter
+
+    >>> model_id = ...
+    >>> inputs = ...
+    >>> device = ...
+    >>> model = AutoModelForCausalLM.from_pretrained(model_id).to(device)
+
+    >>> # load lora 0
+    >>> model = PeftModel.from_pretrained(model, "path-adapter-0")
+    >>> model = torch.compile(model)  # optionally compile the model
+    >>> with torch.inference_mode():
+    ...     output_adapter_0 = model(inputs)
+
+    >>> # replace the "default" lora adapter with the new one
+    >>> hotswap_adapter(model, "path-adapter-1", adapter_name="default", torch_device=device)
+    >>> with torch.inference_mode():
+    ...     output_adapter_1 = model(inputs).logits
+    ```
+
+    Args:
+        model ([`~PeftModel`]):
+            The PEFT model with the loaded adapter.
+        model_name_or_path (`str`):
+            The name or path of the model to load the new adapter from.
+        adapter_name (`str`):
+            The name of the adapter to swap, e.g. `"default"`. The name will stay the same after swapping.
+        torch_device: (`str`, *optional*, defaults to None):
+            The device to load the new adapter onto.
+        **kwargs (`optional`):
+            Additional keyword arguments used for loading the config and weights.
+
+    """
+    if torch_device is None:
+        torch_device = infer_device()
+
+    ############################
+    # LOAD CONFIG AND VALIDATE #
+    ############################
+
+    config_cls = PEFT_TYPE_TO_CONFIG_MAPPING[
+        PeftConfig._get_peft_type(
+            model_name_or_path,
+            subfolder=kwargs.get("subfolder", None),
+            revision=kwargs.get("revision", None),
+            cache_dir=kwargs.get("cache_dir", None),
+            use_auth_token=kwargs.get("use_auth_token", None),
+            token=kwargs.get("token", None),
+        )
+    ]
+    config = config_cls.from_pretrained(model_name_or_path, **kwargs)
+    # config keys that could affect the model output besides what is determined by the state_dict
+    check_hotswap_configs_compatible(model.active_peft_config, config)
+
+    state_dict = load_peft_weights(model_name_or_path, device=torch_device, **kwargs)
+
+    ###########################
+    # LOAD & REMAP STATE_DICT #
+    ###########################
+
+    parameter_prefix = PEFT_TYPE_TO_PREFIX_MAPPING[config.peft_type]
+    peft_model_state_dict = _insert_adapter_name_into_state_dict(
+        state_dict, adapter_name=adapter_name, parameter_prefix=parameter_prefix
+    )
+
+    hotswap_adapter_from_state_dict(
+        model=model,
+        state_dict=peft_model_state_dict,
+        adapter_name=adapter_name,
+        parameter_prefix=parameter_prefix,
+        config=config,
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/incremental_pca.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/incremental_pca.py
new file mode 100644
index 0000000000000000000000000000000000000000..e703f11262c2b7defe8c0c448a1eb05f100ccff2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/incremental_pca.py
@@ -0,0 +1,338 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Optional, Tuple
+
+import torch
+
+
+class IncrementalPCA:
+    """
+    An implementation of Incremental Principal Components Analysis (IPCA) that leverages PyTorch for GPU acceleration.
+    Adapted from https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/decomposition/_incremental_pca.py
+
+    This class provides methods to fit the model on data incrementally in batches, and to transform new data based on
+    the principal components learned during the fitting process.
+
+    Args:
+        n_components (int, optional): Number of components to keep. If `None`, it's set to the minimum of the
+            number of samples and features. Defaults to None.
+        copy (bool): If False, input data will be overwritten. Defaults to True.
+        batch_size (int, optional): The number of samples to use for each batch. Only needed if self.fit is called.
+            If `None`, it's inferred from the data and set to `5 * n_features`. Defaults to None.
+        svd_driver (str, optional): name of the cuSOLVER method to be used for torch.linalg.svd. This keyword
+            argument only works on CUDA inputs. Available options are: None, gesvd, gesvdj, and gesvda. Defaults to
+            None.
+        lowrank (bool, optional): Whether to use torch.svd_lowrank instead of torch.linalg.svd which can be faster.
+            Defaults to False.
+        lowrank_q (int, optional): For an adequate approximation of n_components, this parameter defaults to
+            n_components * 2.
+        lowrank_niter (int, optional): Number of subspace iterations to conduct for torch.svd_lowrank.
+            Defaults to 4.
+        lowrank_seed (int, optional): Seed for making results of torch.svd_lowrank reproducible.
+    """
+
+    def __init__(
+        self,
+        n_components: Optional[int] = None,
+        copy: Optional[bool] = True,
+        batch_size: Optional[int] = None,
+        svd_driver: Optional[str] = None,
+        lowrank: bool = False,
+        lowrank_q: Optional[int] = None,
+        lowrank_niter: int = 4,
+        lowrank_seed: Optional[int] = None,
+    ):
+        self.n_components = n_components
+        self.copy = copy
+        self.batch_size = batch_size
+        self.svd_driver = svd_driver
+        self.lowrank = lowrank
+        self.lowrank_q = lowrank_q
+        self.lowrank_niter = lowrank_niter
+        self.lowrank_seed = lowrank_seed
+
+        self.n_features_ = None
+
+        if self.lowrank:
+            self._validate_lowrank_params()
+
+    def _validate_lowrank_params(self):
+        if self.lowrank_q is None:
+            if self.n_components is None:
+                raise ValueError("n_components must be specified when using lowrank mode with lowrank_q=None.")
+            self.lowrank_q = self.n_components * 2
+        elif self.lowrank_q < self.n_components:
+            raise ValueError("lowrank_q must be greater than or equal to n_components.")
+
+    def _svd_fn_full(self, X):
+        return torch.linalg.svd(X, full_matrices=False, driver=self.svd_driver)
+
+    def _svd_fn_lowrank(self, X):
+        seed_enabled = self.lowrank_seed is not None
+        with torch.random.fork_rng(enabled=seed_enabled):
+            if seed_enabled:
+                torch.manual_seed(self.lowrank_seed)
+            U, S, V = torch.svd_lowrank(X, q=self.lowrank_q, niter=self.lowrank_niter)
+            return U, S, V.mH
+
+    def _validate_data(self, X) -> torch.Tensor:
+        """
+        Validates and converts the input data `X` to the appropriate tensor format.
+
+        Args:
+            X (torch.Tensor): Input data.
+
+        Returns:
+            torch.Tensor: Converted to appropriate format.
+        """
+        valid_dtypes = [torch.float32, torch.float64]
+
+        if not isinstance(X, torch.Tensor):
+            X = torch.tensor(X, dtype=torch.float32)
+        elif self.copy:
+            X = X.clone()
+
+        n_samples, n_features = X.shape
+        if self.n_components is None:
+            pass
+        elif self.n_components > n_features:
+            raise ValueError(
+                f"n_components={self.n_components} invalid for n_features={n_features}, "
+                "need more rows than columns for IncrementalPCA processing."
+            )
+        elif self.n_components > n_samples:
+            raise ValueError(
+                f"n_components={self.n_components} must be less or equal to the batch number of samples {n_samples}"
+            )
+
+        if X.dtype not in valid_dtypes:
+            X = X.to(torch.float32)
+
+        return X
+
+    @staticmethod
+    def _incremental_mean_and_var(
+        X, last_mean, last_variance, last_sample_count
+    ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+        """
+        Computes the incremental mean and variance for the data `X`.
+
+        Args:
+            X (torch.Tensor): The batch input data tensor with shape (n_samples, n_features).
+            last_mean (torch.Tensor): The previous mean tensor with shape (n_features,).
+            last_variance (torch.Tensor): The previous variance tensor with shape (n_features,).
+            last_sample_count (torch.Tensor): The count tensor of samples processed before the current batch.
+
+        Returns:
+            Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: Updated mean, variance tensors, and total sample count.
+        """
+        if X.shape[0] == 0:
+            return last_mean, last_variance, last_sample_count
+
+        if last_sample_count > 0:
+            if last_mean is None:
+                raise ValueError("last_mean should not be None if last_sample_count > 0.")
+            if last_variance is None:
+                raise ValueError("last_variance should not be None if last_sample_count > 0.")
+
+        new_sample_count = torch.tensor([X.shape[0]], device=X.device)
+        updated_sample_count = last_sample_count + new_sample_count
+
+        if last_mean is None:
+            last_sum = torch.zeros(X.shape[1], dtype=torch.float64, device=X.device)
+        else:
+            last_sum = last_mean * last_sample_count
+
+        new_sum = X.sum(dim=0, dtype=torch.float64)
+
+        updated_mean = (last_sum + new_sum) / updated_sample_count
+
+        T = new_sum / new_sample_count
+        temp = X - T
+        correction = temp.sum(dim=0, dtype=torch.float64).square()
+        temp.square_()
+        new_unnormalized_variance = temp.sum(dim=0, dtype=torch.float64)
+        new_unnormalized_variance -= correction / new_sample_count
+        if last_variance is None:
+            updated_variance = new_unnormalized_variance / updated_sample_count
+        else:
+            last_unnormalized_variance = last_variance * last_sample_count
+            last_over_new_count = last_sample_count.double() / new_sample_count
+            updated_unnormalized_variance = (
+                last_unnormalized_variance
+                + new_unnormalized_variance
+                + last_over_new_count / updated_sample_count * (last_sum / last_over_new_count - new_sum).square()
+            )
+            updated_variance = updated_unnormalized_variance / updated_sample_count
+
+        return updated_mean, updated_variance, updated_sample_count
+
+    @staticmethod
+    def _svd_flip(u, v, u_based_decision=True) -> Tuple[torch.Tensor, torch.Tensor]:
+        """
+        Adjusts the signs of the singular vectors from the SVD decomposition for deterministic output.
+
+        This method ensures that the output remains consistent across different runs.
+
+        Args:
+            u (torch.Tensor): Left singular vectors tensor.
+            v (torch.Tensor): Right singular vectors tensor.
+            u_based_decision (bool, optional): If True, uses the left singular vectors to determine the sign flipping.
+                Defaults to True.
+
+        Returns:
+            Tuple[torch.Tensor, torch.Tensor]: Adjusted left and right singular vectors tensors.
+        """
+        if u_based_decision:
+            max_abs_cols = torch.argmax(torch.abs(u), dim=0)
+            signs = torch.sign(u[max_abs_cols, range(u.shape[1])])
+        else:
+            max_abs_rows = torch.argmax(torch.abs(v), dim=1)
+            signs = torch.sign(v[range(v.shape[0]), max_abs_rows])
+        u *= signs[: u.shape[1]].view(1, -1)
+        v *= signs.view(-1, 1)
+        return u, v
+
+    def fit(self, X, check_input=True):
+        """
+        Fits the model with data `X` using minibatches of size `batch_size`.
+
+        Args:
+            X (torch.Tensor): The input data tensor with shape (n_samples, n_features).
+            check_input (bool, optional): If True, validates the input. Defaults to True.
+
+        Returns:
+            IncrementalPCA: The fitted IPCA model.
+        """
+        if check_input:
+            X = self._validate_data(X)
+        n_samples, n_features = X.shape
+        if self.batch_size is None:
+            self.batch_size = 5 * n_features
+
+        for batch in self.gen_batches(n_samples, self.batch_size, min_batch_size=self.n_components or 0):
+            self.partial_fit(X[batch], check_input=False)
+
+        return self
+
+    def partial_fit(self, X, check_input=True):
+        """
+        Incrementally fits the model with batch data `X`.
+
+        Args:
+            X (torch.Tensor): The batch input data tensor with shape (n_samples, n_features).
+            check_input (bool, optional): If True, validates the input. Defaults to True.
+
+        Returns:
+            IncrementalPCA: The updated IPCA model after processing the batch.
+        """
+        first_pass = not hasattr(self, "components_")
+
+        if check_input:
+            X = self._validate_data(X)
+        n_samples, n_features = X.shape
+
+        # Initialize attributes to avoid errors during the first call to partial_fit
+        if first_pass:
+            self.mean_ = None  # Will be initialized properly in _incremental_mean_and_var based on data dimensions
+            self.var_ = None  # Will be initialized properly in _incremental_mean_and_var based on data dimensions
+            self.n_samples_seen_ = torch.tensor([0], device=X.device)
+            self.n_features_ = n_features
+            if not self.n_components:
+                self.n_components = min(n_samples, n_features)
+
+        if n_features != self.n_features_:
+            raise ValueError(
+                "Number of features of the new batch does not match the number of features of the first batch."
+            )
+
+        col_mean, col_var, n_total_samples = self._incremental_mean_and_var(
+            X, self.mean_, self.var_, self.n_samples_seen_
+        )
+
+        if first_pass:
+            X -= col_mean
+        else:
+            col_batch_mean = torch.mean(X, dim=0)
+            X -= col_batch_mean
+            mean_correction_factor = torch.sqrt((self.n_samples_seen_.double() / n_total_samples) * n_samples)
+            mean_correction = mean_correction_factor * (self.mean_ - col_batch_mean)
+            X = torch.vstack(
+                (
+                    self.singular_values_.view((-1, 1)) * self.components_,
+                    X,
+                    mean_correction,
+                )
+            )
+
+        if self.lowrank:
+            U, S, Vt = self._svd_fn_lowrank(X)
+        else:
+            U, S, Vt = self._svd_fn_full(X)
+        U, Vt = self._svd_flip(U, Vt, u_based_decision=False)
+        explained_variance = S**2 / (n_total_samples - 1)
+        explained_variance_ratio = S**2 / torch.sum(col_var * n_total_samples)
+
+        self.n_samples_seen_ = n_total_samples
+        self.components_ = Vt[: self.n_components]
+        self.singular_values_ = S[: self.n_components]
+        self.mean_ = col_mean
+        self.var_ = col_var
+        self.explained_variance_ = explained_variance[: self.n_components]
+        self.explained_variance_ratio_ = explained_variance_ratio[: self.n_components]
+        if self.n_components not in (n_samples, n_features):
+            self.noise_variance_ = explained_variance[self.n_components :].mean()
+        else:
+            self.noise_variance_ = torch.tensor(0.0, device=X.device)
+        return self
+
+    def transform(self, X) -> torch.Tensor:
+        """
+        Applies dimensionality reduction to `X`.
+
+        The input data `X` is projected on the first principal components previously extracted from a training set.
+
+        Args:
+            X (torch.Tensor): New data tensor with shape (n_samples, n_features) to be transformed.
+
+        Returns:
+            torch.Tensor: Transformed data tensor with shape (n_samples, n_components).
+        """
+        X = X - self.mean_
+        return torch.mm(X.double(), self.components_.T).to(X.dtype)
+
+    @staticmethod
+    def gen_batches(n: int, batch_size: int, min_batch_size: int = 0):
+        """Generator to create slices containing `batch_size` elements from 0 to `n`.
+
+        The last slice may contain less than `batch_size` elements, when `batch_size` does not divide `n`.
+
+        Args:
+            n (int): Size of the sequence.
+            batch_size (int): Number of elements in each batch.
+            min_batch_size (int, optional): Minimum number of elements in each batch. Defaults to 0.
+
+        Yields:
+            slice: A slice of `batch_size` elements.
+        """
+        start = 0
+        for _ in range(int(n // batch_size)):
+            end = start + batch_size
+            if end + min_batch_size > n:
+                continue
+            yield slice(start, end)
+            start = end
+        if start < n:
+            yield slice(start, n)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/integrations.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/integrations.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d472870df2e85f6a4c22078a7194d5a060807d2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/integrations.py
@@ -0,0 +1,285 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import functools
+from contextlib import contextmanager
+from typing import Literal
+
+import packaging.version
+import torch
+import transformers
+from torch import nn
+
+from peft.import_utils import is_xpu_available
+
+
+@contextmanager
+def gather_params_ctx(param, modifier_rank: int = 0, fwd_module: torch.nn.Module = None):
+    """Call DeepSpeed GatheredParameters context manager if DeepSpeed is enabled, otherwise do nothing."""
+    if packaging.version.parse(transformers.__version__) >= packaging.version.parse("4.33.0"):
+        from transformers.integrations import is_deepspeed_zero3_enabled
+    else:
+        from transformers.deepspeed import is_deepspeed_zero3_enabled
+
+    if not is_deepspeed_zero3_enabled():
+        yield
+        return
+
+    import deepspeed
+
+    with deepspeed.zero.GatheredParameters(param, modifier_rank=modifier_rank, fwd_module=fwd_module):
+        yield
+    return
+
+
+def dequantize_module_weight(module: torch.nn.Module) -> torch.nn.Parameter:
+    """
+    Helper function to dequantize a quantized weight.
+
+    This function should be extended if more quantization schemes are added to the library.
+
+    If the weight is not quantized, it will be returned as is.
+    """
+    if hasattr(module, "W_q"):  # For handling HQQ quantized weight
+        weight = module.dequantize()
+        return weight
+    elif type(module.weight).__module__.startswith("torchao."):
+        # check for torchao without requiring any torchao imports
+        weight = module.weight.dequantize()
+        return weight
+
+    weight = module.weight
+    if not isinstance(weight, torch.nn.Parameter):
+        if isinstance(weight, torch.Tensor):
+            # this is an FSDP-specific edge case
+            return weight  # type: ignore
+        raise TypeError(f"Input weight should be of type nn.Parameter, got {type(weight)} instead")
+
+    cls_name = weight.__class__.__name__
+    if cls_name not in ("Params4bit", "Int8Params"):
+        return weight
+
+    quant_state = getattr(module, "state", None)
+    device = weight.device
+    is_cpu = device.type == torch.device("cpu").type
+    weight = dequantize_bnb_weight(weight, state=quant_state)  # no-op if not bnb
+    if is_cpu:
+        # dequantize_bnb_weight for 8bit moves the device in-place, thus we need to move it back to CPU if necessary
+        module.weight = module.weight.to(device)
+    return weight
+
+
+def dequantize_bnb_weight(weight: torch.nn.Parameter, state=None):
+    """Helper function to dequantize 4bit or 8bit bnb weights.
+
+    Since dequantization is not supported on CPU, the weight will be temporarily moved to CUDA if necessary.
+    """
+    import bitsandbytes as bnb
+
+    # BNB requires CUDA weights
+    device = weight.device
+    is_cpu = device.type == torch.device("cpu").type
+    if is_cpu:
+        if torch.cuda.is_available():
+            weight = weight.to(torch.device("cuda"))
+        elif is_xpu_available():
+            weight = weight.to(torch.device("xpu"))
+
+    cls_name = weight.__class__.__name__
+    if cls_name == "Params4bit":
+        dequantized = bnb.functional.dequantize_4bit(weight.data, weight.quant_state)
+        if is_cpu:
+            dequantized = dequantized.to(device)
+        return dequantized
+
+    if state.SCB is None:
+        state.SCB = weight.SCB
+
+    if hasattr(bnb.functional, "int8_vectorwise_dequant"):
+        # Use bitsandbytes API if available (requires v0.45.0+)
+        dequantized = bnb.functional.int8_vectorwise_dequant(weight.data, state.SCB)
+    else:
+        # Multiply by (scale/127) to dequantize.
+        dequantized = weight.data * state.SCB.view(-1, 1) * 7.874015718698502e-3
+
+    if is_cpu:
+        dequantized = dequantized.to(device)
+    return dequantized
+
+
+def get_bnb_param_type(param: torch.nn.Parameter) -> Literal[False, "4bit", "8bit"]:
+    """Returns '4bit' or '8bit' if bitsandbytes parameter, else False"""
+    if param.__class__.__name__ == "Params4bit":
+        return "4bit"
+    if param.__class__.__name__ == "Int8Params":
+        return "8bit"
+    return False
+
+
+# adapted from:
+# https://github.com/huggingface/transformers/blob/eab6c491d439e83d5e31c660df6f7e36592eb0a2/src/transformers/generation/utils.py#L1617-L1643
+def get_layer_device_map(model):
+    """
+    Derive the device map for the layers of the model.
+    """
+    main_device = [d for d in model.hf_device_map.values() if d not in ["cpu", "disk"]][0]
+
+    execution_device_map = {
+        name: main_device if device in ["cpu", "disk"] else device for name, device in model.hf_device_map.items()
+    }
+
+    if execution_device_map is None:
+        return None
+
+    if len(execution_device_map) == 1 and "" in execution_device_map:
+        return {idx: execution_device_map[""] for idx in range(model.config.num_hidden_layers)}
+
+    layer_device_map = {}
+    for layer in execution_device_map:
+        for idx in range(model.config.num_hidden_layers):
+            if f".{idx}." in f"{layer}.":
+                layer_device_map[idx] = execution_device_map[layer]
+                break
+    for idx in range(model.config.num_hidden_layers):
+        if idx not in layer_device_map:
+            raise RuntimeError(f"layer {idx} has not been mapped to a device.")
+    return layer_device_map
+
+
+# adapted from:
+# https://github.com/huggingface/transformers/blob/eab6c491d439e83d5e31c660df6f7e36592eb0a2/src/transformers/cache_utils.py#L1159-L1179
+def map_cache_to_layer_device_map(model, cache) -> None:
+    """
+    Ensure that the key and value cache of the model are on the same device as their corresponding layers.
+    """
+    if not (isinstance(cache, transformers.Cache) and hasattr(model, "hf_device_map")):
+        return
+
+    if isinstance(cache, transformers.EncoderDecoderCache):
+        map_cache_to_layer_device_map(model, cache.self_attention_cache)
+        return
+
+    layer_device_map = get_layer_device_map(model)
+    for idx in range(model.config.num_hidden_layers):
+        layer_device = layer_device_map[idx]
+        cache.key_cache[idx] = cache.key_cache[idx].to(layer_device)
+        cache.value_cache[idx] = cache.value_cache[idx].to(layer_device)
+
+
+##################################
+# START: ADAPTED FROM ACCELERATE #
+##################################
+#
+# Modified to support explicitly skipping layer initialization for faster switching between layer states
+# (necessary for supporting `nn.MultiHeadAttention` adapters)
+
+
+@contextmanager
+def init_empty_weights(include_buffers: bool = None):
+    # adapted from accelerate.big_modeling.py
+    with _init_on_device(torch.device("meta"), include_buffers=include_buffers) as f:
+        yield f
+
+
+@contextmanager
+def _init_on_device(device: torch.device, include_buffers: bool = None):
+    # adapted from accelerate.big_modeling.py
+    old_register_parameter = nn.Module.register_parameter
+    if include_buffers:
+        old_register_buffer = nn.Module.register_buffer
+
+    def register_empty_parameter(module, name, param):
+        # This works because torch first initializes the parameters with torch.empty, thus not assigning any new memory.
+        # Then the parameter is moved to meta device before reset_parameters() is called, which then operates on the
+        # meta device, making any subsequent calls to initialization methods no-ops.
+        old_register_parameter(module, name, param)
+        if (param is not None) and (getattr(_init_on_device, "_skip", False) is not True):
+            param_cls = type(module._parameters[name])
+            kwargs = module._parameters[name].__dict__
+            kwargs["requires_grad"] = param.requires_grad
+            module._parameters[name] = param_cls(module._parameters[name].to(device), **kwargs)
+
+    def register_empty_buffer(module, name, buffer, persistent=True):
+        old_register_buffer(module, name, buffer, persistent=persistent)
+        if buffer is not None:
+            module._buffers[name] = module._buffers[name].to(device)
+
+    # Patch tensor creation
+    if include_buffers:
+        tensor_constructors_to_patch = {
+            torch_function_name: getattr(torch, torch_function_name)
+            for torch_function_name in ["empty", "zeros", "ones", "full"]
+        }
+    else:
+        tensor_constructors_to_patch = {}
+
+    def patch_tensor_constructor(fn):
+        def wrapper(*args, **kwargs):
+            kwargs["device"] = device
+            return fn(*args, **kwargs)
+
+        return wrapper
+
+    try:
+        nn.Module.register_parameter = register_empty_parameter
+        if include_buffers:
+            nn.Module.register_buffer = register_empty_buffer
+        for torch_function_name in tensor_constructors_to_patch.keys():
+            setattr(torch, torch_function_name, patch_tensor_constructor(getattr(torch, torch_function_name)))
+        yield
+    finally:
+        nn.Module.register_parameter = old_register_parameter
+        if include_buffers:
+            nn.Module.register_buffer = old_register_buffer
+        for torch_function_name, old_torch_function in tensor_constructors_to_patch.items():
+            setattr(torch, torch_function_name, old_torch_function)
+
+
+@contextmanager
+def _skip_init_on_device():
+    # context manager to skip the _init_on_device context manager
+    old_val = getattr(_init_on_device, "_skip", False)
+    try:
+        _init_on_device._skip = True
+        yield
+    finally:
+        _init_on_device._skip = old_val
+
+
+def skip_init_on_device(func):
+    """
+    Ignore the init_on_device context manager when calling the decorated function.
+
+    This is a narrow use decorator that allows us to avoid initializing on meta device even when we're inside the
+    init_empty_weights context.
+
+    """
+
+    # The need for this functionality arose when working on MultiheadAttention, where we have to call _restore_weights
+    # repeatedly as parametes are overwritten and need to be re-registered. When using low_cpu_mem_usage=True, as
+    # register_parameter is patched inside of the init_empty_weights context, this would result in those parameters
+    # suddenly being moved to meta device. Using this decorator allows us to avoid this.
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        with _skip_init_on_device():
+            return func(*args, **kwargs)
+
+    return wrapper
+
+
+#######
+# END #
+#######
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/loftq_utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/loftq_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..1019326e1e85d31b37f9973a7dffaaedf75c90aa
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/loftq_utils.py
@@ -0,0 +1,409 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Reference code: https://github.com/yxli2123/LoftQ/blob/main/utils.py
+# Reference paper: https://arxiv.org/abs/2310.08659
+
+from __future__ import annotations
+
+import logging
+import os
+from typing import Callable, Optional, Union
+
+import torch
+from accelerate.utils.memory import clear_device_cache
+from huggingface_hub import snapshot_download
+from huggingface_hub.errors import HFValidationError, LocalEntryNotFoundError
+from safetensors import SafetensorError, safe_open
+from transformers.utils import cached_file
+from transformers.utils.hub import get_checkpoint_shard_files
+
+from peft.import_utils import is_bnb_4bit_available, is_bnb_available, is_xpu_available
+
+
+class NFQuantizer:
+    def __init__(self, num_bits=2, device="cuda", method="normal", block_size=64, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.num_bits = num_bits
+        self.device = device
+        self.method = method
+        self.block_size = block_size
+        if self.method == "normal":
+            self.norm_lookup_table = self.create_normal_map(num_bits=self.num_bits)
+            self.norm_lookup_table = self.norm_lookup_table.to(device)
+        elif self.method == "uniform":
+            self.norm_lookup_table = self.create_uniform_map(num_bits=self.num_bits)
+            self.norm_lookup_table = self.norm_lookup_table.to(device)
+        else:
+            raise NotImplementedError("Other quantization methods not supported yet.")
+
+    @staticmethod
+    def create_uniform_map(symmetric=False, num_bits=4):
+        if symmetric:
+            # print("symmetric uniform quantization")
+            negative = torch.linspace(-1, 0, 2 ** (num_bits - 1))
+            positive = torch.linspace(0, 1, 2 ** (num_bits - 1))
+            table = torch.cat([negative, positive[1:]])
+        else:
+            # print("asymmetric uniform quantization")
+            table = torch.linspace(-1, 1, 2**num_bits)
+        return table
+
+    @staticmethod
+    def create_normal_map(offset=0.9677083, symmetric=False, num_bits=2):
+        try:
+            from scipy.stats import norm
+        except ImportError:
+            raise ImportError("The required package 'scipy' is not installed. Please install it to continue.")
+
+        variations = 2**num_bits
+        if symmetric:
+            v = norm.ppf(torch.linspace(1 - offset, offset, variations + 1)).tolist()
+            values = []
+            for index in range(len(v) - 1):
+                values.append(0.5 * v[index] + 0.5 * v[index + 1])
+            v = values
+        else:
+            # one more positive value, this is an asymmetric type
+            v1 = norm.ppf(torch.linspace(offset, 0.5, variations // 2 + 1)[:-1]).tolist()
+            v2 = [0]
+            v3 = (-norm.ppf(torch.linspace(offset, 0.5, variations // 2)[:-1])).tolist()
+            v = v1 + v2 + v3
+
+        values = torch.Tensor(v)
+        values = values.sort().values
+        values /= values.max()
+        return values
+
+    def quantize_tensor(self, weight):
+        max_abs = torch.abs(weight).max()
+        weight_normed = weight / max_abs
+
+        weight_normed_expanded = weight_normed.unsqueeze(-1)
+
+        # Reshape L to have the same number of dimensions as X_expanded
+        L_reshaped = torch.tensor(self.norm_lookup_table).reshape(1, -1)
+
+        # Calculate the absolute difference between X_expanded and L_reshaped
+        abs_diff = torch.abs(weight_normed_expanded - L_reshaped)
+
+        # Find the index of the minimum absolute difference for each element
+        qweight = torch.argmin(abs_diff, dim=-1)
+        return qweight, max_abs
+
+    def dequantize_tensor(self, qweight, max_abs):
+        qweight_flatten = qweight.flatten()
+
+        weight_normed = self.norm_lookup_table[qweight_flatten]
+        weight = weight_normed * max_abs
+
+        weight = weight.reshape(qweight.shape)
+
+        return weight
+
+    def quantize_block(self, weight):
+        if len(weight.shape) != 2:
+            raise ValueError(f"Only support 2D matrix, but your input has {len(weight.shape)} dimensions.")
+        if weight.shape[0] * weight.shape[1] % self.block_size != 0:
+            raise ValueError(
+                f"Weight with shape ({weight.shape[0]} x {weight.shape[1]}) "
+                f"is not dividable by block size {self.block_size}."
+            )
+
+        M, N = weight.shape
+        device = weight.device
+
+        # Quantization
+        weight_flatten = weight.flatten()  # (M*N, )
+        weight_block = weight_flatten.reshape(-1, self.block_size)  # (L, B), L = M * N / B
+        if self.method == "normal":
+            weight_max = weight_block.abs().max(dim=-1)[0]  # (L, 1)
+        elif self.method == "uniform":
+            weight_max = weight_block.mean(dim=-1) + 2.5 * weight_block.std(dim=-1)
+        else:
+            raise NotImplementedError("Method not supported yet.")
+        weight_max = weight_max.unsqueeze(-1)
+        weight_divabs = weight_block / weight_max  # (L, B)
+        weight_divabs = weight_divabs.unsqueeze(-1)  # (L, B, 1)
+        L_reshaped = self.norm_lookup_table.reshape(1, -1)  # (1, 2**K)
+
+        abs_diff = torch.abs(weight_divabs - L_reshaped)  # (L, B, 2**K)
+        qweight = torch.argmin(abs_diff, dim=-1)  # (L, B)
+
+        # Pack multiple k-bit into uint8
+        qweight = qweight.reshape(-1, 8 // self.num_bits)
+        qweight_pack = torch.zeros((M * N // 8 * self.num_bits, 1), dtype=torch.uint8, device=device)
+
+        # data format example:
+        # [1, 0, 3, 2] or [01, 00, 11, 10]  -> [10110001], LIFO
+        for i in range(8 // self.num_bits):
+            qweight[:, i] = qweight[:, i] << i * self.num_bits
+            qweight_pack[:, 0] |= qweight[:, i]
+
+        return qweight_pack, weight_max, weight.shape
+
+    def dequantize_block(self, qweight, weight_max, weight_shape):
+        # unpack weight
+        device = qweight.device
+        weight = torch.zeros((qweight.shape[0], 8 // self.num_bits), dtype=torch.float32, device=device)
+        for i in range(8 // self.num_bits):
+            lookup_table_idx = qweight.to(torch.long) % 2**self.num_bits  # get the most right 2 bits
+            lookup_table_idx = lookup_table_idx.to(torch.long)
+            weight[:, i] = self.norm_lookup_table[lookup_table_idx].squeeze()
+            qweight = qweight >> self.num_bits  # right shift 2 bits of the original data
+
+        weight_block = weight.reshape(-1, self.block_size)
+        weight = weight_block * weight_max
+        weight = weight.reshape(weight_shape)
+
+        return weight
+
+
+def _low_rank_decomposition(weight, reduced_rank=32):
+    """
+    :param weight: The matrix to decompose, of shape (H, W) :param reduced_rank: the final rank :return:
+    """
+    matrix_dimension = len(weight.size())
+    if matrix_dimension != 2:
+        raise ValueError(f"Only support 2D matrix, but your input has {matrix_dimension} dimensions.")
+
+    # Use SVD to decompose a matrix, default full_matrices is False to save parameters
+    U, S, Vh = torch.linalg.svd(weight, full_matrices=False)
+
+    L = U @ (torch.sqrt(torch.diag(S)[:, 0:reduced_rank]))
+    R = torch.sqrt(torch.diag(S)[0:reduced_rank, :]) @ Vh
+
+    return {"L": L, "R": R, "U": U, "S": S, "Vh": Vh, "reduced_rank": reduced_rank}
+
+
+@torch.no_grad()
+def loftq_init(weight: Union[torch.Tensor, torch.nn.Parameter], num_bits: int, reduced_rank: int, num_iter=1):
+    if is_bnb_available():
+        import bitsandbytes as bnb
+    else:
+        raise ValueError("bitsandbytes is not available, please install it to use LoftQ.")
+
+    if num_bits not in [2, 4, 8]:
+        raise ValueError("Only support 2, 4, 8 bits quantization")
+    if num_iter <= 0:
+        raise ValueError("Number of iterations must be greater than 0")
+
+    out_feature, in_feature = weight.size()
+    device = weight.device
+    dtype = weight.dtype
+    logging.info(
+        f"Weight: ({out_feature}, {in_feature}) | Rank: {reduced_rank} | Num Iter: {num_iter} | Num Bits: {num_bits}"
+    )
+    if not is_bnb_4bit_available() or num_bits in [2, 8]:
+        quantizer = NFQuantizer(num_bits=num_bits, device=device, method="normal", block_size=64)
+        compute_device = device
+    else:
+        compute_device = "xpu" if is_xpu_available() else "cuda"
+
+    weight = weight.to(device=compute_device, dtype=torch.float32)
+    res = weight.clone()
+    for i in range(num_iter):
+        clear_device_cache()
+        # Quantization
+        if num_bits == 4 and is_bnb_4bit_available():
+            qweight = bnb.nn.Params4bit(
+                res.to("cpu"), requires_grad=False, compress_statistics=False, quant_type="nf4"
+            ).to(compute_device)
+            dequantized_weight = bnb.functional.dequantize_4bit(qweight.data, qweight.quant_state)
+        else:
+            quantized_weight, max_abs, shape = quantizer.quantize_block(res)
+            dequantized_weight = quantizer.dequantize_block(quantized_weight, max_abs, shape)
+
+        res = weight - dequantized_weight
+
+        # Decompose the residual by SVD
+        output = _low_rank_decomposition(res, reduced_rank=reduced_rank)
+        L, R, reduced_rank = output["L"], output["R"], output["reduced_rank"]
+        res = weight - torch.mm(L, R)
+
+    lora_A, lora_B = R, L
+
+    return dequantized_weight.to(device=device, dtype=dtype), lora_A, lora_B
+
+
+@torch.no_grad()
+def _loftq_init_new(qweight, weight, num_bits: int, reduced_rank: int):
+    import bitsandbytes as bnb
+
+    if num_bits != 4:
+        raise ValueError("Only 4 bit quantization supported at the moment.")
+    if not is_bnb_4bit_available():
+        raise ValueError("bitsandbytes 4bit quantization is not available.")
+
+    compute_device = "xpu" if is_xpu_available() else "cuda"
+    dequantized_weight = bnb.functional.dequantize_4bit(qweight.data, qweight.quant_state)
+
+    weight = weight.to(device=compute_device, dtype=torch.float32)
+    residual = weight - dequantized_weight
+    clear_device_cache()
+    # Decompose the residualidual by SVD
+    output = _low_rank_decomposition(residual, reduced_rank=reduced_rank)
+    L, R, reduced_rank = output["L"], output["R"], output["reduced_rank"]
+    return R, L
+
+
+class _SafetensorLoader:
+    """
+    Simple utility class that loads tensors with safetensors from a single file or sharded files.
+
+    Takes care of file name normalization etc.
+
+    """
+
+    def __init__(self, peft_model, model_path):
+        if model_path is None:
+            try:
+                model_path = snapshot_download(peft_model.base_model.config._name_or_path, local_files_only=True)
+            except (AttributeError, HFValidationError) as exc:
+                raise ValueError(
+                    "The provided model does not appear to be a transformers model or is a local model. In this case, "
+                    "you must pass the model_path argument that points to the safetensors file."
+                ) from exc
+            except LocalEntryNotFoundError as exc:
+                raise ValueError(
+                    "The model.safetensors file must be present on disk, but it could not be found."
+                ) from exc
+
+        suffix = "model.safetensors"
+        if not model_path.endswith(suffix):
+            model_path = os.path.join(model_path, suffix)
+
+        self.model_path = model_path
+        self.base_model_prefix = getattr(peft_model.get_base_model(), "base_model_prefix", None)
+        self.prefix = "base_model.model."
+        self.is_sharded = False
+        self.weight_map = None
+
+        if not os.path.exists(model_path):
+            # check if the file is sharded
+            par_dir = model_path.rpartition(os.path.sep)[0]
+            try:
+                resolved_archive_file, sharded_metadata = get_checkpoint_shard_files(
+                    par_dir, cached_file(par_dir, "model.safetensors.index.json")
+                )
+            except OSError as exc:
+                raise FileNotFoundError(
+                    f"Could not find file for {model_path}, ensure that there is a (sharded) safetensors file of the model."
+                ) from exc
+
+            self.is_sharded = True
+            # maps from 'model-X-of-Y.safetensors' to full file path
+            file_map = {k.rpartition(os.path.sep)[-1]: k for k in resolved_archive_file}
+            self.weight_map = {k: file_map[v] for k, v in sharded_metadata["weight_map"].items()}
+
+    def get_tensor(self, name):
+        if not self.is_sharded:
+            file_path = self.model_path
+        else:
+            file_path = self.weight_map[name]
+
+        with safe_open(file_path, framework="pt", device="cpu") as f:
+            try:
+                tensor = f.get_tensor(name)
+            except SafetensorError as exc:
+                # no matching key found, we probably need to remove the base model prefix
+                if self.base_model_prefix:
+                    # remove 1 extra character for "."
+                    name = name[len(self.base_model_prefix) + 1 :]
+                    tensor = f.get_tensor(name)
+                else:
+                    raise exc
+        return tensor
+
+
+@torch.no_grad()
+def replace_lora_weights_loftq(
+    peft_model,
+    model_path: Optional[str] = None,
+    adapter_name: str = "default",
+    callback: Optional[Callable[[torch.nn.Module, str], bool]] = None,
+):
+    """
+    Replace the LoRA weights of a model quantized with bitsandbytes, using the LoftQ technique.
+
+    The replacement is done on the fly by loading in the non-quantized weights from a locally stored safetensors model
+    file and initializing the LoRA weights such that the quantization error between the original and quantized weights
+    is minimized.
+
+    As lazy loading is not possible with pickle, normal PyTorch checkpoint files cannot be supported.
+
+    Depending on the model size, calling this function may take some time to finish.
+
+    Args:
+        peft_model (`PeftModel`):
+            The model to replace the weights of. Must be a quantized PEFT model with LoRA layers.
+        model_path (`Optional[str]`):
+            The path to the model safetensors file. If the model is a Hugging Face model, this will be inferred from
+            the model's config. Otherwise, it must be provided.
+        adapter_name (`str`):
+            The name of the adapter to replace the weights of. The default adapter name is "default".
+        callback (`Optional[Callable[[PeftModel, str], bool]]`):
+            A callback function that will be called after each module is replaced. The callback function should take
+            the model and the name of the current module as input and return a boolean indicating whether the
+            replacement should be kept. If the callback returns False, the replacement will be rolled back. This can be
+            very useful to confirm that the LoftQ initialization actually decreases the quantization error of the
+            model. As an example, this callback could generate logits for given input and compare it with the logits
+            from the original, non-quanitzed model with the same input, and only return `True` if there is an
+            improvement. As this is a greedy optimization, it's possible that calling this function multiple times
+            yields incremental improvements.
+    """
+    if not is_bnb_4bit_available():
+        raise ValueError("bitsandbytes must be installed and the model must be quantized in 4bits.")
+
+    from peft.tuners.lora import Linear4bit
+
+    # model_path = _check_model_path_loftq(model_path, peft_model)
+    prefix = "base_model.model."
+    any_match = False
+    safetensor_loader = _SafetensorLoader(peft_model, model_path)
+
+    # if too slow, consider adding tqdm as an option
+    for name, module in peft_model.named_modules():
+        if not isinstance(module, Linear4bit):
+            continue
+
+        if not name.startswith(prefix):
+            raise TypeError("The passed model does not appear to be a valid PeftModel")
+
+        any_match = True
+        name = name[len(prefix) :]
+        tensor = safetensor_loader.get_tensor(name + ".weight")
+
+        reduced_rank = module.r[adapter_name]
+        lora_A, lora_B = _loftq_init_new(module.weight, tensor, num_bits=4, reduced_rank=reduced_rank)
+        if not callback:
+            module.lora_A[adapter_name].weight.data = lora_A
+            module.lora_B[adapter_name].weight.data = lora_B
+            continue
+
+        lora_A_before = module.lora_A[adapter_name].weight.data
+        lora_B_before = module.lora_B[adapter_name].weight.data
+
+        module.lora_A[adapter_name].weight.data = lora_A
+        module.lora_B[adapter_name].weight.data = lora_B
+        should_replace = callback(peft_model, name)
+        if not should_replace:
+            # roll back
+            module.lora_A[adapter_name].weight.data = lora_A_before
+            module.lora_B[adapter_name].weight.data = lora_B_before
+
+        del lora_A_before, lora_B_before
+
+    if not any_match:
+        raise ValueError("No bnb LoRA module found on the model")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/merge_utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/merge_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..900cb878e2d785e5e800caa58642f0532f4d574b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/merge_utils.py
@@ -0,0 +1,268 @@
+# Copyright 2024-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import warnings
+from typing import List, Literal
+
+import torch
+
+
+def reshape_weight_task_tensors(task_tensors, weights):
+    """
+    Reshapes `weights` to match the shape of `task_tensors` by unsqeezing in the remaining dimenions.
+
+    Args:
+        task_tensors (`torch.Tensor`): The tensors that will be used to reshape `weights`.
+        weights (`torch.Tensor`): The tensor to be reshaped.
+
+    Returns:
+        `torch.Tensor`: The reshaped tensor.
+    """
+    new_shape = weights.shape + (1,) * (task_tensors.dim() - weights.dim())
+    weights = weights.view(new_shape)
+    return weights
+
+
+def magnitude_based_pruning(tensor: torch.Tensor, density: float) -> torch.Tensor:
+    """
+    Prune the smallest values of the task tensors and retain the top-k values based on the specified fraction
+    `density`.
+
+    Args:
+        tensor (`torch.Tensor`):The tensor to prune.
+        density (`float`):The fraction of values to preserve. Should be in [0,1].
+
+    Returns:
+        `torch.Tensor`: The tensor with the pruned weights.
+    """
+    mask = torch.zeros_like(tensor).reshape(-1)
+    k = int(density * tensor.numel())
+    top_k = torch.topk(tensor.abs().reshape(-1), k=k, largest=True)
+    mask[top_k[1]] = 1
+    return tensor * mask.reshape(tensor.shape)
+
+
+def random_pruning(tensor: torch.Tensor, density: float, rescale: bool) -> torch.Tensor:
+    """
+    Prune random values based on the specified fraction `density`.
+
+    Args:
+        tensor (`torch.Tensor`):The tensor to prune.
+        density (`float`):The fraction of values to preserve. Should be in [0,1].
+        rescale (`bool`):Whether to rescale the result to preserve the expected value of the original tensor.
+
+    Returns:
+        `torch.Tensor`: The pruned tensor.
+    """
+    mask = torch.bernoulli(torch.full_like(input=tensor, fill_value=density))
+    pruned_tensor = tensor * mask
+    if rescale:
+        torch.div(input=pruned_tensor, other=density)
+    return pruned_tensor
+
+
+def prune(
+    tensor: torch.Tensor, density: float, method: Literal["magnitude", "random"], rescale: bool = False
+) -> torch.Tensor:
+    """
+    Prune the values of task tensors based on the `method`.
+
+    Args:
+        tensor (`torch.Tensor`):The tensor to prune.
+        density (`float`):The fraction of values to preserve. Should be in [0,1].
+        method (`str`):The method to use to prune. Should be one of ["magnitude", "random"].
+        rescale (`bool`):Whether to rescale the result to preserve the expected value of the original tensor.
+
+    Returns:
+        `torch.Tensor`: The pruned tensor.
+    """
+    if density >= 1:
+        warnings.warn(f"The density {density} is greater than or equal to 1, no pruning will be performed.")
+        return tensor
+    elif density < 0:
+        raise ValueError(f"Density should be >= 0, got {density}")
+    if method == "magnitude":
+        return magnitude_based_pruning(tensor, density)
+    elif method == "random":
+        return random_pruning(tensor, density, rescale=rescale)
+    else:
+        raise ValueError(f"Unknown method {method}")
+
+
+def calculate_majority_sign_mask(
+    tensor: torch.Tensor, method: Literal["total", "frequency"] = "total"
+) -> torch.Tensor:
+    """
+    Get the mask of the majority sign across the task tensors. Task tensors are stacked on dimension 0.
+
+    Args:
+        tensor (`torch.Tensor`):The tensor to get the mask from.
+        method (`str`):The method to use to get the mask. Should be one of ["total", "frequency"].
+
+    Returns:
+        `torch.Tensor`: The majority sign mask.
+    """
+
+    sign = tensor.sign()
+    if method == "total":
+        sign_magnitude = tensor.sum(dim=0)
+    elif method == "frequency":
+        sign_magnitude = sign.sum(dim=0)
+    else:
+        raise RuntimeError(f'Unimplemented mask method "{method}"')
+    majority_sign = torch.where(sign_magnitude >= 0, 1, -1)
+    return sign == majority_sign
+
+
+def disjoint_merge(task_tensors: torch.Tensor, majority_sign_mask: torch.Tensor) -> torch.Tensor:
+    """
+    Merge the task tensors using disjoint merge.
+
+    Args:
+        task_tensors (`torch.Tensor`):The task tensors to merge.
+        majority_sign_mask (`torch.Tensor`):The mask of the majority sign across the task tensors.
+
+    Returns:
+        `torch.Tensor`: The merged tensor.
+    """
+    mixed_task_tensors = (task_tensors * majority_sign_mask).sum(dim=0)
+    num_params_preserved = majority_sign_mask.sum(dim=0)
+    return mixed_task_tensors / torch.clamp(num_params_preserved, min=1.0)
+
+
+def task_arithmetic(task_tensors: List[torch.Tensor], weights: torch.Tensor) -> torch.Tensor:
+    """
+    Merge the task tensors using `task arithmetic`.
+
+    Args:
+        task_tensors(`List[torch.Tensor]`):The task tensors to merge.
+        weights (`torch.Tensor`):The weights of the task tensors.
+
+    Returns:
+        `torch.Tensor`: The merged tensor.
+    """
+    task_tensors = torch.stack(task_tensors, dim=0)
+    # weighted task tensors
+    weights = reshape_weight_task_tensors(task_tensors, weights)
+    weighted_task_tensors = task_tensors * weights
+    mixed_task_tensors = weighted_task_tensors.sum(dim=0)
+    return mixed_task_tensors
+
+
+def magnitude_prune(task_tensors: List[torch.Tensor], weights: torch.Tensor, density: float) -> torch.Tensor:
+    """
+    Merge the task tensors using `task arithmetic`.
+
+    Args:
+        task_tensors(`List[torch.Tensor]`):The task tensors to merge.
+        weights (`torch.Tensor`):The weights of the task tensors.
+        density (`float`): The fraction of values to preserve. Should be in [0,1].
+
+    Returns:
+        `torch.Tensor`: The merged tensor.
+    """
+    # sparsify
+    task_tensors = [prune(tensor, density, method="magnitude") for tensor in task_tensors]
+    task_tensors = torch.stack(task_tensors, dim=0)
+    # weighted task tensors
+    weights = reshape_weight_task_tensors(task_tensors, weights)
+    weighted_task_tensors = task_tensors * weights
+    mixed_task_tensors = weighted_task_tensors.sum(dim=0)
+    return mixed_task_tensors
+
+
+def ties(
+    task_tensors: List[torch.Tensor],
+    weights: torch.Tensor,
+    density: float,
+    majority_sign_method: Literal["total", "frequency"] = "total",
+) -> torch.Tensor:
+    """
+    Merge the task tensors using `ties`.
+
+    Args:
+        task_tensors(`List[torch.Tensor]`):The task tensors to merge.
+        weights (`torch.Tensor`):The weights of the task tensors.
+        density (`float`):The fraction of values to preserve. Should be in [0,1].
+        majority_sign_method (`str`):
+            The method to use to get the majority sign mask. Should be one of ["total", "frequency"].
+
+    Returns:
+        `torch.Tensor`: The merged tensor.
+    """
+    # sparsify
+    task_tensors = [prune(tensor, density, method="magnitude") for tensor in task_tensors]
+    task_tensors = torch.stack(task_tensors, dim=0)
+    # Elect Sign
+    majority_sign_mask = calculate_majority_sign_mask(task_tensors, method=majority_sign_method)
+    # weighted task tensors
+    weights = reshape_weight_task_tensors(task_tensors, weights)
+    weighted_task_tensors = task_tensors * weights
+    # Disjoint Merge
+    mixed_task_tensors = disjoint_merge(weighted_task_tensors, majority_sign_mask)
+    return mixed_task_tensors
+
+
+def dare_linear(task_tensors: List[torch.Tensor], weights: torch.Tensor, density: float) -> torch.Tensor:
+    """
+    Merge the task tensors using `dare linear`.
+
+    Args:
+        task_tensors(`List[torch.Tensor]`):The task tensors to merge.
+        weights (`torch.Tensor`):The weights of the task tensors.
+        density (`float`):The fraction of values to preserve. Should be in [0,1].
+
+    Returns:
+        `torch.Tensor`: The merged tensor.
+    """
+    # sparsify
+    task_tensors = [prune(tensor, density, method="random", rescale=True) for tensor in task_tensors]
+    task_tensors = torch.stack(task_tensors, dim=0)
+    # weighted task tensors
+    weights = reshape_weight_task_tensors(task_tensors, weights)
+    weighted_task_tensors = task_tensors * weights
+    mixed_task_tensors = weighted_task_tensors.sum(dim=0)
+    return mixed_task_tensors
+
+
+def dare_ties(
+    task_tensors: List[torch.Tensor],
+    weights: torch.Tensor,
+    density: float,
+    majority_sign_method: Literal["total", "frequency"] = "total",
+) -> torch.Tensor:
+    """
+    Merge the task tensors using `dare ties`.
+
+    Args:
+        task_tensors(`List[torch.Tensor]`):The task tensors to merge.
+        weights (`torch.Tensor`):The weights of the task tensors.
+        density (`float`):The fraction of values to preserve. Should be in [0,1].
+        majority_sign_method (`str`):
+            The method to use to get the majority sign mask. Should be one of ["total", "frequency"].
+
+    Returns:
+        `torch.Tensor`: The merged tensor.
+    """
+    # sparsify
+    task_tensors = [prune(tensor, density, method="random", rescale=True) for tensor in task_tensors]
+    task_tensors = torch.stack(task_tensors, dim=0)
+    # Elect Sign
+    majority_sign_mask = calculate_majority_sign_mask(task_tensors, method=majority_sign_method)
+    # weighted task tensors
+    weights = reshape_weight_task_tensors(task_tensors, weights)
+    weighted_task_tensors = task_tensors * weights
+    # Disjoint Merge
+    mixed_task_tensors = disjoint_merge(weighted_task_tensors, majority_sign_mask)
+    return mixed_task_tensors
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/other.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/other.py
new file mode 100644
index 0000000000000000000000000000000000000000..155e0adc4a8a5aebe2f3babbbb8b0a7f945f1557
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/other.py
@@ -0,0 +1,1126 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import copy
+import inspect
+import os
+import re
+import warnings
+from contextlib import nullcontext
+from typing import Any, Optional, Sequence, Union
+
+import accelerate
+import torch
+from accelerate.hooks import add_hook_to_module, remove_hook_from_module
+from accelerate.utils import is_npu_available, is_xpu_available
+from huggingface_hub import file_exists
+from huggingface_hub.errors import EntryNotFoundError, HFValidationError
+from packaging import version
+from safetensors.torch import storage_ptr, storage_size
+
+from ..import_utils import is_auto_gptq_available, is_gptqmodel_available, is_torch_tpu_available
+from .constants import (
+    CONFIG_NAME,
+    EMBEDDING_LAYER_NAMES,
+    INCLUDE_LINEAR_LAYERS_SHORTHAND,
+    SAFETENSORS_WEIGHTS_NAME,
+    TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING,
+    TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING,
+    TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING,
+    WEIGHTS_NAME,
+    bloom_model_postprocess_past_key_value,
+    starcoder_model_postprocess_past_key_value,
+)
+
+
+mlu_available = False
+if version.parse(accelerate.__version__) >= version.parse("0.29.0"):
+    from accelerate.utils import is_mlu_available
+
+    mlu_available = is_mlu_available()
+
+
+__all__ = [
+    "CONFIG_NAME",
+    "EMBEDDING_LAYER_NAMES",
+    "INCLUDE_LINEAR_LAYERS_SHORTHAND",
+    "SAFETENSORS_WEIGHTS_NAME",
+    "TRANSFORMERS_MODELS_TO_ADALORA_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_FOURIERFT_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_IA3_FEEDFORWARD_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_LNTUNING_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_PREFIX_TUNING_POSTPROCESS_MAPPING",
+    "TRANSFORMERS_MODELS_TO_VBLORA_TARGET_MODULES_MAPPING",
+    "TRANSFORMERS_MODELS_TO_VERA_TARGET_MODULES_MAPPING",
+    "WEIGHTS_NAME",
+    "bloom_model_postprocess_past_key_value",
+    "starcoder_model_postprocess_past_key_value",
+]
+
+
+# Get current device name based on available devices
+def infer_device() -> str:
+    if torch.cuda.is_available():
+        return "cuda"
+    elif hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
+        return "mps"
+    elif mlu_available:
+        return "mlu"
+    elif is_xpu_available():
+        return "xpu"
+    elif is_npu_available():
+        return "npu"
+    return "cpu"
+
+
+def prepare_model_for_kbit_training(model, use_gradient_checkpointing=True, gradient_checkpointing_kwargs=None):
+    r"""
+    Note this method only works for `transformers` models.
+
+    This method wraps the entire protocol for preparing a model before running a training. This includes:
+        1- Cast the layernorm in fp32 2- making output embedding layer require grads 3- Add the upcasting of the lm
+        head to fp32 4- Freezing the base model layers to ensure they are not updated during training
+
+
+    Args:
+        model (`transformers.PreTrainedModel`):
+            The loaded model from `transformers`
+        use_gradient_checkpointing (`bool`, *optional*, defaults to `True`):
+            If True, use gradient checkpointing to save memory at the expense of slower backward pass.
+        gradient_checkpointing_kwargs (`dict`, *optional*, defaults to `None`):
+            Keyword arguments to pass to the gradient checkpointing function, please refer to the documentation of
+            `torch.utils.checkpoint.checkpoint` for more details about the arguments that you can pass to that method.
+            Note this is only available in the latest transformers versions (> 4.34.1).
+    """
+    loaded_in_kbit = getattr(model, "is_loaded_in_8bit", False) or getattr(model, "is_loaded_in_4bit", False)
+    is_gptq_quantized = getattr(model, "quantization_method", None) == "gptq"
+    is_aqlm_quantized = getattr(model, "quantization_method", None) == "aqlm"
+    is_eetq_quantized = getattr(model, "quantization_method", None) == "eetq"
+    is_torchao_quantized = getattr(model, "quantization_method", None) == "torchao"
+    is_hqq_quantized = getattr(model, "quantization_method", None) == "hqq" or getattr(model, "hqq_quantized", False)
+
+    if gradient_checkpointing_kwargs is None:
+        gradient_checkpointing_kwargs = {}
+
+    for name, param in model.named_parameters():
+        # freeze base model's layers
+        param.requires_grad = False
+
+    if (
+        not is_gptq_quantized
+        and not is_aqlm_quantized
+        and not is_eetq_quantized
+        and not is_hqq_quantized
+        and not is_torchao_quantized
+    ):
+        # cast all non INT8 parameters to fp32
+        for param in model.parameters():
+            if (
+                (param.dtype == torch.float16) or (param.dtype == torch.bfloat16)
+            ) and param.__class__.__name__ != "Params4bit":
+                param.data = param.data.to(torch.float32)
+
+    if (
+        loaded_in_kbit
+        or is_gptq_quantized
+        or is_aqlm_quantized
+        or is_eetq_quantized
+        or is_hqq_quantized
+        or is_torchao_quantized
+    ) and use_gradient_checkpointing:
+        # When having `use_reentrant=False` + gradient_checkpointing, there is no need for this hack
+        if "use_reentrant" not in gradient_checkpointing_kwargs or gradient_checkpointing_kwargs["use_reentrant"]:
+            # For backward compatibility
+            if hasattr(model, "enable_input_require_grads"):
+                model.enable_input_require_grads()
+            else:
+
+                def make_inputs_require_grad(module, input, output):
+                    output.requires_grad_(True)
+
+                model.get_input_embeddings().register_forward_hook(make_inputs_require_grad)
+
+        # To support older transformers versions, check if the model supports gradient_checkpointing_kwargs
+        _supports_gc_kwargs = "gradient_checkpointing_kwargs" in list(
+            inspect.signature(model.gradient_checkpointing_enable).parameters
+        )
+
+        if not _supports_gc_kwargs and len(gradient_checkpointing_kwargs) > 0:
+            warnings.warn(
+                "gradient_checkpointing_kwargs is not supported in this version of transformers. The passed kwargs will be ignored."
+                " if you want to use that feature, please upgrade to the latest version of transformers.",
+                FutureWarning,
+            )
+
+        gc_enable_kwargs = (
+            {} if not _supports_gc_kwargs else {"gradient_checkpointing_kwargs": gradient_checkpointing_kwargs}
+        )
+
+        # enable gradient checkpointing for memory efficiency
+        model.gradient_checkpointing_enable(**gc_enable_kwargs)
+    return model
+
+
+# copied from transformers.models.bart.modeling_bart
+def shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):
+    """
+    Shift input ids one token to the right.
+
+    Args:
+        input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`): input ids
+        pad_token_id (`int`): The id of the `padding` token.
+        decoder_start_token_id (`int`): The id of the `start` token.
+    """
+    shifted_input_ids = input_ids.new_zeros(input_ids.shape)
+    shifted_input_ids[:, 1:] = input_ids[:, :-1].clone()
+    shifted_input_ids[:, 0] = decoder_start_token_id
+
+    if pad_token_id is None:
+        raise ValueError("self.model.config.pad_token_id has to be defined.")
+    # replace possible -100 values in labels by `pad_token_id`
+    shifted_input_ids.masked_fill_(shifted_input_ids == -100, pad_token_id)
+
+    return shifted_input_ids
+
+
+class AuxiliaryTrainingWrapper(torch.nn.Module):
+    """Wrap a specific module so that it can be trained and saved in a way that is tangential to how
+    PEFT normally works, e.g. fully training a classification layer instead of using an adapter.
+
+    """
+
+    def __init__(self, module_to_save, adapter_name, **kwargs):
+        """Extra kwargs will be passed to `self.init_modules` and `self.update`."""
+        super().__init__()
+        self.original_module = module_to_save
+        self._active_adapter = [adapter_name]
+        self._disable_adapters = False
+        self._adapters = set()
+
+        self.init_modules(adapter_name, **kwargs)
+
+        self.update(adapter_name, **kwargs)
+        self.check_module()
+
+    def init_modules(self, adapter_name, **kwargs):
+        """A place to initialize PyTorch modules in `__init__` before the call to `self.update()`."""
+        raise NotImplementedError
+
+    def _error_message_name(self):
+        """Returns a user friendly identifier for error messages, e.g. for type compatibility error messages from
+        `check_module()` so that the user can backtrack where the error comes from. A generic "training wrapper" is
+        less helpful than "modules_to_save", for example.
+        """
+        return "training wrapper"
+
+    def check_module(self):
+        """Perform some sanity checks on the module to ensure that it works"""
+        # Try to anticipate some modules that users could try to target that would not work.
+        # Note: It's not possible to check hasattr(module, "forward"), since that returns True for ModuleDict and
+        # ModuleList, even though their forward methods cannot be called
+        forbidden_classes = (torch.nn.ModuleDict, torch.nn.ModuleList, torch.nn.ParameterDict, torch.nn.ParameterList)
+        if isinstance(self.original_module, forbidden_classes):
+            cls_name = self.original_module.__class__
+            raise TypeError(f"{self._error_message_name()} cannot be applied to modules of type {cls_name}")
+
+        # local import to avoid circular import
+        from peft.tuners.tuners_utils import BaseTunerLayer
+
+        if isinstance(self.original_module, BaseTunerLayer):
+            # e.g. applying a training wrapper to a lora layer makes no sense
+            cls_name = self.original_module.__class__
+            raise TypeError(f"{self._error_message_name()} cannot be applied to modules of type {cls_name}")
+
+    @property
+    def disable_adapters(self) -> bool:
+        # use a property to ensure that disable_adapters is not set directly, instead use the enable_adapters method
+        return self._disable_adapters
+
+    @property
+    def active_adapter(self) -> Union[list[str], str]:
+        # use a property to ensure that active_adapter is not set directly, instead use the set_adapter method
+        return self._active_adapter
+
+    @property
+    def active_adapters(self) -> list[str]:
+        if isinstance(self._active_adapter, str):
+            return [self._active_adapter]
+        return self._active_adapter
+
+    def _hasattr_wrapped(self, name, modules):
+        """Infrastructure to enable the implementing class to delegate attributes to other modules.
+        Returns True if the implementing class knows how to handle attribute `name`.
+
+        Gets passed `modules` which is PyTorch's internal list of assigned modules from `nn.Module`.
+        """
+        return False
+
+    def _getattr_wrapped(self, name, modules):
+        """If `_hasattr_wrapped` returns True for `name`, then this function should return the corresponding
+        value associated with `name`.
+        """
+        return None
+
+    def __getattr__(self, name: str):
+        # Note: This whole method may seem overly complex at first but PyTorch messes with __getattr__ in a way that
+        # requires very careful handling to avoid infinite recursion.
+        try:
+            return super().__getattr__(name)
+        except AttributeError:
+            pass
+
+        if "_modules" not in self.__dict__:
+            raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
+
+        # Could not find the attribute the PyTorch way. So let's check if it's an attribute on the
+        # original_module or the module further down (e.g., `modules_to_save[active_adapter]`).
+        modules = self.__dict__["_modules"]
+        if self.disable_adapters:
+            return getattr(self.original_module, name)
+        elif self._hasattr_wrapped(name, modules):
+            return self._getattr_wrapped(name, modules)
+
+        # For some reason, there is no module corresponding to the active adapter; this should normally not be
+        # reached and exists as a failsafe (otherwise, a KeyError would be raised)
+        raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
+
+    def update(self, adapter_name, **kwargs):
+        """Called when this instance should be part of an adapter's training.
+        Adds the given adapter to the list of adapters that this instance is training along with.
+
+        Additional kwargs are expected to be the same kwargs that are also passed for initializing this class.
+        """
+        if adapter_name not in self._adapters:
+            self._adapters.add(adapter_name)
+
+    def _create_new_hook(self, old_hook):
+        r"""
+        Creates a new hook based on the old hook. Use it only if you know what you are doing !
+        """
+        old_hook_cls = getattr(accelerate.hooks, old_hook.__class__.__name__)
+        old_hook_attr = old_hook.__dict__
+        filtered_old_hook_attr = {}
+        old_hook_init_signature = inspect.signature(old_hook_cls.__init__)
+        for k in old_hook_attr.keys():
+            if k in old_hook_init_signature.parameters:
+                filtered_old_hook_attr[k] = old_hook_attr[k]
+        new_hook = old_hook_cls(**filtered_old_hook_attr)
+        return new_hook
+
+    def _check_forward_args(self, x, *args, **kwargs):
+        """Check if the arguments are compatible with the configs and state of the model"""
+        adapter_names = kwargs.get("adapter_names", None)
+        if adapter_names is None:
+            return
+
+        if len(x) != len(adapter_names):
+            msg = (
+                "Length of `adapter_names` should be the same as the number of inputs, but got "
+                f"{len(adapter_names)} and {len(x)} respectively."
+            )
+            raise ValueError(msg)
+
+    def _forward_wrapped(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        raise NotImplementedError
+
+    def _forward_wrapped_mixed_batch(
+        self, x: torch.Tensor, active_adapter: str, *args: Any, **kwargs: Any
+    ) -> torch.Tensor:
+        raise NotImplementedError
+
+    def _forward_disabled(self, x: torch.Tensor, *args: Any, **kwargs: Any) -> torch.Tensor:
+        """The forward call when all 'adapters' are disabled. For example this could entail
+        restoring (unmerging) a base model and returning its forward return values.
+        """
+        raise NotImplementedError
+
+    def _mixed_batch_forward(
+        self, input: torch.Tensor, *args: Any, adapter_names: list[str], **kwargs: Any
+    ) -> torch.Tensor:
+        # This is a special method that handles the case when users pass the argument `adapter_names`. This is an
+        # extra argument that allows mixing different adapters in the same batch at inference time.
+
+        SUPPORTED_MODULES = (torch.nn.Linear, torch.nn.Embedding, torch.nn.Conv1d, torch.nn.Conv2d, torch.nn.Conv3d)
+
+        module_names = ", ".join([module.__name__ for module in SUPPORTED_MODULES])
+
+        if not isinstance(self.original_module, SUPPORTED_MODULES):
+            raise TypeError(f"Mixed batching is only supported for the following modules: {module_names}.")
+
+        unique_adapters = set(adapter_names)
+        sub_batch_indices_list = []
+
+        for adapter in unique_adapters:
+            sub_batch_indices_list.append([index for index, item in enumerate(adapter_names) if item == adapter])
+
+        results = [0 for _ in range(len(input))]
+
+        for i, active_adapter in enumerate(unique_adapters):
+            sub_batch = input[sub_batch_indices_list[i]]
+
+            if active_adapter == "__base__":
+                output = self.original_module(sub_batch, *args, **kwargs)
+            else:
+                output = self._forward_wrapped_mixed_batch(sub_batch, active_adapter, *args, **kwargs)
+
+            for index, j in enumerate(sub_batch_indices_list[i]):
+                results[j] = output[index]
+
+        return torch.stack(results)
+
+    def forward(self, x: torch.Tensor, *args, **kwargs):
+        self._check_forward_args(x, *args, **kwargs)
+        adapter_names = kwargs.pop("adapter_names", None)
+
+        if self.disable_adapters or any(adapter not in self._adapters for adapter in self.active_adapters):
+            return self._forward_wrapped_disabled(x, *args, **kwargs)
+
+        if adapter_names is None:
+            return self._forward_wrapped(x, *args, **kwargs)
+        return self._mixed_batch_forward(x, *args, adapter_names=adapter_names, **kwargs)
+
+    def enable_adapters(self, enabled: bool):
+        """Toggle the enabling and disabling of adapters
+
+        Args:
+            enabled (bool): True to enable adapters, False to disable adapters
+        """
+        if enabled:
+            self._disable_adapters = False
+        else:
+            self._disable_adapters = True
+
+    def set_adapter(self, adapter_names: Union[str, list[str]]):
+        """Set the active adapter
+
+        Args:
+            adapter_name (str): The name of the adapter to set as active
+        """
+        if isinstance(adapter_names, str):
+            self._active_adapter = adapter_names
+        else:
+            self._active_adapter = []
+            for adapter_name in adapter_names:
+                if adapter_name not in self._adapters:
+                    raise ValueError(f"Adapter {adapter_name} not found in {self._adapters}")
+
+                self._active_adapter.append(adapter_name)
+
+    def adapter_state_dict(self, adapter_name):
+        """Return the state dict of this module for a given adapter."""
+        raise NotImplementedError
+
+    def adapter_state_dict_load_map(self, adapter_name):
+        """Return a mapping from the key present in disk-loaded state dict
+        and how it should be represented in the loaded model's state dict.
+
+        The default should be a 1:1 mapping but it is important to define a mapping as it also serves as the
+        ground-truth for which keys are supposed to be loaded from a saved state dict.
+        """
+        raise NotImplementedError
+
+    def unload_and_optionally_merge_module(
+        self, merge: bool, safe_merge: bool, adapter_names: Optional[list[str]]
+    ) -> torch.nn.Module:
+        """Handles unloading when called from PEFT models. Returns the wrapped module
+        and handles merging onto the wrapped module if requested.
+        """
+        raise NotImplementedError
+
+
+class ModulesToSaveWrapper(AuxiliaryTrainingWrapper):
+    """Wraps a module that is supposed to be trained (i.e. `requires_grad_(True)`) and saved after training."""
+
+    def __init__(self, module_to_save, adapter_name):
+        super().__init__(module_to_save, adapter_name)
+
+    def init_modules(self, adapter_name):
+        # we treat each adapter separately, so we have multiple adapters, same (copied) module for each
+        self.modules_to_save = torch.nn.ModuleDict({})
+
+    def _error_message_name(self):
+        return "modules_to_save"
+
+    def _forward_wrapped(self, x, *args, **kwargs):
+        return self.modules_to_save[self.active_adapters[0]](x, *args, **kwargs)
+
+    def _forward_wrapped_mixed_batch(self, x, active_adapter, *args, **kwargs):
+        return self.modules_to_save[active_adapter](x, *args, **kwargs)
+
+    def _forward_wrapped_disabled(self, x, *args, **kwargs):
+        return self.original_module(x, *args, **kwargs)
+
+    def _hasattr_wrapped(self, name, modules):
+        return self.active_adapters[0] in modules["modules_to_save"]
+
+    def _getattr_wrapped(self, name, modules):
+        return getattr(modules["modules_to_save"][self.active_adapters[0]], name)
+
+    def update(self, adapter_name, **kwargs):
+        super().update(adapter_name)
+
+        context_manager = nullcontext()
+        for _, param in self.original_module.named_parameters():
+            num_params = param.numel()
+            # if using DS Zero 3 and the weights are initialized empty
+            if num_params == 0 and hasattr(param, "ds_numel"):
+                import deepspeed
+
+                context_manager = deepspeed.zero.GatheredParameters(self.original_module.parameters(), modifier_rank=0)
+                break
+
+        if adapter_name not in self.modules_to_save:
+            with context_manager:
+                self.modules_to_save[adapter_name] = copy.deepcopy(self.original_module)
+
+        if hasattr(self.modules_to_save[adapter_name], "_hf_hook"):
+            old_hook = self.modules_to_save[adapter_name]._hf_hook
+            new_hook = self._create_new_hook(old_hook)
+            remove_hook_from_module(self.modules_to_save[adapter_name])
+            add_hook_to_module(self.modules_to_save[adapter_name], new_hook)
+
+        self.original_module.requires_grad_(False)
+
+        # note that there currently cannot be more than one active adapter for the same layer with modules to save
+        # since there would be no clear way to decide which adapter's weights are the correct ones. therefore we
+        # assume that there is only one active adapter. this precondition is enforced by _set_adapter.
+        if adapter_name == self.active_adapter:
+            self.modules_to_save[adapter_name].requires_grad_(True)
+
+    def enable_adapters(self, enabled: bool):
+        """Takes care of setting the required_grad flag on the wrapped module.
+        If adapters are enabled, gradients for the module are required as well.
+        """
+        super().enable_adapters(enabled)
+
+        if enabled:
+            self.original_module.requires_grad_(False)
+            self.modules_to_save[self.active_adapter].requires_grad_(True)
+        else:
+            self.original_module.requires_grad_(True)
+            self.modules_to_save.requires_grad_(False)
+
+    def set_adapter(self, adapter_names: Union[str, list[str]]):
+        """Set the active adapter
+
+        Additionally, this function will set the specified adapter to trainable (i.e., requires_grad=True). If this is
+        not desired, use the following code.
+
+        ```py
+        >>> for name, param in model_peft.named_parameters():
+        ...     if ...:  # some check on name (ex. if 'lora' in name)
+        ...         param.requires_grad = False
+        ```
+
+        Args:
+            adapter_names (list[str], str): The name of the adapter to set as active
+        """
+        if isinstance(adapter_names, str):
+            adapter_names = [adapter_names]
+
+        if len(adapter_names) > 1:
+            raise ValueError(f"Attempted to set multiple ({adapter_names}) adapters at once for modules_to_save.")
+
+        adapter_name = adapter_names[0]
+
+        if adapter_name not in self._adapters:
+            raise ValueError(f"Adapter {adapter_name} not found in {self._adapters}")
+
+        self.modules_to_save[self.active_adapters[0]].requires_grad_(False)
+        self.modules_to_save[adapter_name].requires_grad_(True)
+        self._active_adapter = adapter_name
+
+    def adapter_state_dict_load_map(self, adapter_name):
+        # Maps the module keys as they are in the saved state dict to the in-memory state dict.
+        # Must contain all keys that are supposed to be loaded.
+        if adapter_name not in self._adapters:
+            # In caes of multiple adapters, each bringing their own modules to save, each
+            # ModulesToSaveWrapper will be queried but not every wrapper is obliged to serve the same adapters.
+            return {}
+        return {k: f"modules_to_save.{adapter_name}.{k}" for k in self.modules_to_save[adapter_name].state_dict()}
+
+    def adapter_state_dict(self, adapter_name, state_dict):
+        if adapter_name not in self._adapters:
+            # In caes of multiple adapters, each bringing their own modules to save, each
+            # ModulesToSaveWrapper will be queried but not every wrapper is obliged to serve the same adapters.
+            return {}
+
+        return {
+            k: state_dict[f"modules_to_save.{adapter_name}.{k}"]
+            for k in self.modules_to_save[adapter_name].state_dict()
+        }
+
+    def unload_and_optionally_merge_module(
+        self, merge: bool, safe_merge: bool, adapter_names: Optional[list[str]]
+    ) -> torch.nn.Module:
+        """Unloading in case of `ModulesToSave` means to simply return the wrapped module.
+
+        However, if the wrapped module is itself a tuner, we'll call merge on it before.
+        """
+        new_module = self.modules_to_save[self.active_adapter]
+
+        # TODO: not sure if this is still a sensible thing to do. We would basically have to
+        # do the same checks as `_unload_and_optionally_merge` to support MHA, for example.
+        if hasattr(new_module, "base_layer"):
+            # check if the module is itself a tuner layer
+            if merge:
+                new_module.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+            new_module = new_module.get_base_layer()
+
+        return new_module
+
+
+class TrainableTokensWrapper(AuxiliaryTrainingWrapper):
+    """Wraps a module (typically an embedding layer) that is supposed to be re-trained selectively (i.e.
+    solely updating a few columns) using the `TrainableTokensLayer` PEFT method.
+
+    Supports weight-tying to another adapter when passed a `tied_adapter` which is expected to be a
+    `TrainableTokensLayer`.
+    """
+
+    def __init__(
+        self,
+        module_to_save: torch.nn.Module,
+        adapter_name: str,
+        token_indices: list[int],
+        tied_adapter=None,
+    ) -> None:
+        super().__init__(module_to_save, adapter_name, token_indices=token_indices, tied_adapter=tied_adapter)
+
+        # unset the original_module attribute since we're using a property to remove this from the state dict.
+        self.original_module = None
+
+    @property
+    def original_module(self):
+        # use a property instead of an attribute to exclude this pointer from the state dict
+        # to make sure that it will not be saved.
+        return self.token_adapter.base_layer
+
+    def init_modules(self, adapter_name, token_indices, tied_adapter):
+        # use a local import to avoid potential circular imports
+        from peft.tuners.trainable_tokens import TrainableTokensLayer
+
+        # since super().__init__() calls update before we have a chance to initialise the adapter we would
+        # need here, we do the initialization here.
+        self.token_adapter = TrainableTokensLayer(self.original_module, adapter_name, token_indices, tied_adapter)
+
+    def _error_message_name(self):
+        return "trainable_token_indices"
+
+    def _hasattr_wrapped(self, name, modules):
+        return name == "weight"
+
+    def _getattr_wrapped(self, name, modules):
+        # some models query self.wte.weight.dtype, some may query the weights directly. for the first case it is not
+        # necessary to do anything special but we don't know if is going to be `.dtype`. so we need to get the merged
+        # weights from the adapter.
+        if name == "weight":
+            return modules["token_adapter"].get_merged_weights(self.token_adapter.active_adapters)
+
+        raise RuntimeError(
+            f"This code should've never been reached, probably a bad check in `_hasattr_wrapped` for {name}. "
+            "Please file an issue under https://github.com/huggingface/peft/issues."
+        )
+
+    def _forward_wrapped(self, x, *args, **kwargs):
+        return self.token_adapter(x)
+
+    def _forward_wrapped_mixed_batch(self, x, active_adapter, *args, **kwargs):
+        return self.token_adapter.forward_adapters(x, [active_adapter])
+
+    def _forward_wrapped_disabled(self, x, *args, **kwargs):
+        # we already disabled the adapter so we can safely forward call to the adapter
+        # since it will know best what to do when being disabled.
+        return self.token_adapter(x, *args, **kwargs)
+
+    def update(self, active_adapter, **kwargs):
+        # TODO this does not support deepspeed/fsdp since it is missing a context manager
+        # see ModulesToSaveWrapper implementation
+        if active_adapter not in self._adapters:
+            self.token_adapter.update_layer(active_adapter, **kwargs)
+
+        super().update(active_adapter)
+
+    def adapter_state_dict_load_map(self, adapter_name):
+        if self.token_adapter.tied_adapter:
+            return {}
+        return {"token_adapter.trainable_tokens_delta": f"token_adapter.trainable_tokens_delta.{adapter_name}"}
+
+    def adapter_state_dict(self, adapter_name, state_dict):
+        if self.token_adapter.tied_adapter:
+            # storing of weight-tied layers is not up to us and will be handled by
+            # transformers. we're just here to keep those layers in sync during training.
+            # therefore we return an empty state dict.
+            return {}
+
+        return {
+            f"token_adapter.{k}": state_dict[f"token_adapter.{k}.{adapter_name}"] for k in ["trainable_tokens_delta"]
+        }
+
+    def enable_adapters(self, enabled: bool):
+        """Enables/disables the underlying `TrainableTokens` adapter.
+        Also handles the internal adapter disable flag.
+        """
+        super().enable_adapters(enabled)
+
+        self.token_adapter.enable_adapters(enabled)
+
+    def set_adapter(self, adapter_names: Union[str, list[str]]):
+        super().set_adapter(adapter_names)
+        self.token_adapter.set_adapter(adapter_names)
+
+    def unload_and_optionally_merge_module(
+        self, merge: bool, safe_merge: bool, adapter_names: Optional[list[str]]
+    ) -> torch.nn.Module:
+        """Unloading for `TrainableTokensWrapper` means to return the wrapped module, e.g. the embedding layer and,
+        if requested, merging the `TrainableTokens` adapter onto the wrapped module.
+        """
+        if merge:
+            self.token_adapter.merge(safe_merge=safe_merge, adapter_names=adapter_names)
+        return self.token_adapter.get_base_layer()
+
+
+def _get_input_embeddings_name(model, default=None):
+    if not hasattr(model, "get_input_embeddings"):
+        return default
+
+    input_embeddings = model.get_input_embeddings()
+    for name, module in model.named_modules():
+        if module is input_embeddings:
+            return name
+
+    return default
+
+
+def _get_submodules(model, key):
+    parent = model.get_submodule(".".join(key.split(".")[:-1]))
+    target_name = key.split(".")[-1]
+    target = model.get_submodule(key)
+    return parent, target, target_name
+
+
+def _freeze_adapter(model, adapter_name):
+    for n, p in model.named_parameters():
+        if adapter_name in n:
+            p.requires_grad = False
+
+
+def _set_trainable(
+    model,
+    adapter_name,
+    module_names,
+    strict_module_check=False,
+    wrapper_cls: Optional[AuxiliaryTrainingWrapper] = None,
+    **wrapper_kwargs,
+):
+    """Wraps modules that are supposed to be re-trained either normally, i.e. marking them to require gradients and
+    saving them alongside other modules, or with certain methods that go alongside PEFT methods, such as retraining
+    specific token indices using selective read/write.
+
+    Note that you need to validate beforehand if there are layers targeted by multiple wrappers, e.g. if the
+    'embedding' layer is configured for both `ModulesToSaveWrapper` and `TrainableTokensWrapper` there would be
+    conflicts down the line.
+
+    The default is to wrap the module in a `ModulesToSaveWrapper` wrapper.
+
+    If `strict_module_check` is set, this method raises an ValueError, similar to BaseTuner.inject_adapter when none of
+    the requested modules in `module_names` is not found in the model.
+    """
+    if wrapper_cls is None:
+        wrapper_cls = ModulesToSaveWrapper
+
+    if module_names is None:
+        return
+
+    trainable_modules = []
+    found_modules = set()
+    # disable removal of duplicates to support targeting tied weights
+    key_list = [key for key, _ in model.named_modules(remove_duplicate=False)]
+
+    for key in key_list:
+        target_module_found = any(key.endswith(target_key) for target_key in module_names)
+        if target_module_found:
+            parent, target, target_name = _get_submodules(model, key)
+            if isinstance(target, wrapper_cls):
+                target.update(adapter_name, **wrapper_kwargs)
+                target.set_adapter(target.active_adapter)
+            else:
+                new_module = wrapper_cls(target, adapter_name, **wrapper_kwargs)
+                new_module.set_adapter(adapter_name)
+                setattr(parent, target_name, new_module)
+                trainable_modules.append(new_module)
+            found_modules.add(target_name)
+
+    not_found = set(module_names).difference(found_modules)
+    if strict_module_check and not found_modules:
+        raise ValueError(
+            f"Target modules {not_found} not found in the base model. Please check the target modules and try again."
+        )
+
+    return trainable_modules
+
+
+def _set_adapter(model, adapter_name):
+    def check_adapter_name(adapter_name):
+        if isinstance(adapter_name, str):
+            return adapter_name
+
+        # adapter_name is a list of str
+        if len(adapter_name) > 1:
+            raise ValueError("Only one adapter can be set at a time for modules_to_save")
+        elif len(adapter_name) == 0:
+            raise ValueError("Please specify at least one adapter to set")
+        adapter_name = adapter_name[0]
+        return adapter_name
+
+    for module in model.modules():
+        if isinstance(module, AuxiliaryTrainingWrapper):
+            # only check the adapter_name if we actually encounter a AuxiliaryTrainingWrapper, otherwise we don't care
+            adapter_name = check_adapter_name(adapter_name)
+
+            # if the adapter is found in this module, set it as the active adapter, else disable the adapters of this
+            # module
+            if adapter_name in module._adapters:
+                module.enable_adapters(True)
+                module.set_adapter(adapter_name)
+            else:
+                module.enable_adapters(False)
+
+
+def _prepare_prompt_learning_config(peft_config, model_config):
+    if peft_config.num_layers is None:
+        if "num_hidden_layers" in model_config:
+            num_layers = model_config["num_hidden_layers"]
+        elif "num_layers" in model_config:
+            num_layers = model_config["num_layers"]
+        elif "n_layer" in model_config:
+            num_layers = model_config["n_layer"]
+        else:
+            raise ValueError("Please specify `num_layers` in `peft_config`")
+        peft_config.num_layers = num_layers
+
+    if peft_config.token_dim is None:
+        if "hidden_size" in model_config:
+            token_dim = model_config["hidden_size"]
+        elif "n_embd" in model_config:
+            token_dim = model_config["n_embd"]
+        elif "d_model" in model_config:
+            token_dim = model_config["d_model"]
+        else:
+            raise ValueError("Please specify `token_dim` in `peft_config`")
+        peft_config.token_dim = token_dim
+
+    if peft_config.num_attention_heads is None:
+        if "num_attention_heads" in model_config:
+            num_attention_heads = model_config["num_attention_heads"]
+        elif "n_head" in model_config:
+            num_attention_heads = model_config["n_head"]
+        elif "num_heads" in model_config:
+            num_attention_heads = model_config["num_heads"]
+        elif "encoder_attention_heads" in model_config:
+            num_attention_heads = model_config["encoder_attention_heads"]
+        else:
+            raise ValueError("Please specify `num_attention_heads` in `peft_config`")
+        peft_config.num_attention_heads = num_attention_heads
+
+    # For grouped-query attention, see #1901.
+    if peft_config.peft_type == "PREFIX_TUNING" and "num_key_value_heads" in model_config:
+        num_key_value_heads = model_config["num_key_value_heads"]
+        peft_config.token_dim = peft_config.token_dim // peft_config.num_attention_heads * num_key_value_heads
+        peft_config.num_attention_heads = num_key_value_heads
+
+    if getattr(peft_config, "encoder_hidden_size", None) is None:
+        setattr(peft_config, "encoder_hidden_size", peft_config.token_dim)
+
+    return peft_config
+
+
+def fsdp_auto_wrap_policy(model):
+    import functools
+    import os
+
+    from accelerate import FullyShardedDataParallelPlugin
+
+    if hasattr(FullyShardedDataParallelPlugin, "get_module_class_from_name"):
+        get_module_class_from_name = FullyShardedDataParallelPlugin.get_module_class_from_name
+    else:
+        from accelerate.utils.dataclasses import get_module_class_from_name
+    from torch.distributed.fsdp.wrap import _or_policy, lambda_auto_wrap_policy, transformer_auto_wrap_policy
+
+    from ..tuners import PrefixEncoder, PromptEmbedding, PromptEncoder
+
+    default_transformer_cls_names_to_wrap = (
+        ",".join(model._no_split_modules) if getattr(model, "_no_split_modules", None) is not None else ""
+    )
+    transformer_cls_names_to_wrap = os.environ.get(
+        "FSDP_TRANSFORMER_CLS_TO_WRAP", default_transformer_cls_names_to_wrap
+    ).split(",")
+    transformer_cls_to_wrap = {PrefixEncoder, PromptEncoder, PromptEmbedding}
+    for layer_class in transformer_cls_names_to_wrap:
+        if len(layer_class) == 0:
+            continue
+        transformer_cls = get_module_class_from_name(model, layer_class)
+        if transformer_cls is None:
+            raise Exception("Could not find the transformer layer class to wrap in the model.")
+        else:
+            transformer_cls_to_wrap.add(transformer_cls)
+
+    def lambda_policy_fn(module):
+        if (
+            len(list(module.named_children())) == 0
+            and getattr(module, "weight", None) is not None
+            and module.weight.requires_grad
+        ):
+            return True
+        return False
+
+    lambda_policy = functools.partial(lambda_auto_wrap_policy, lambda_fn=lambda_policy_fn)
+    transformer_wrap_policy = functools.partial(
+        transformer_auto_wrap_policy,
+        transformer_layer_cls=transformer_cls_to_wrap,
+    )
+
+    auto_wrap_policy = functools.partial(_or_policy, policies=[lambda_policy, transformer_wrap_policy])
+    return auto_wrap_policy
+
+
+def transpose(weight, fan_in_fan_out):
+    if not fan_in_fan_out:
+        return weight
+
+    if isinstance(weight, torch.nn.Parameter):
+        return torch.nn.Parameter(weight.T)
+    return weight.T
+
+
+def _is_valid_match(key: str, target_key: str):
+    """
+    Helper function to match module names target_key and key. Makes sure that either the key is exactly the target_key
+    or the target_key is a submodule of key
+    """
+    if key.endswith(target_key):
+        if len(key) > len(target_key):
+            return key.endswith("." + target_key)  # must be a sub module
+        return True
+    return False
+
+
+def _get_batch_size(input_ids: Optional[torch.Tensor], inputs_embeds: Optional[torch.Tensor]) -> int:
+    """Get the batch size based on either input_ids or input_embeds
+
+    Raises an ValueError if both are None.
+
+    """
+    if (input_ids is None) and (inputs_embeds is None):
+        raise ValueError("You have to provide either input_ids or inputs_embeds")
+
+    if input_ids is not None:
+        batch_size = input_ids.shape[0]
+    else:
+        batch_size = inputs_embeds.shape[0]
+    return batch_size
+
+
+def get_quantization_config(model: torch.nn.Module, method: str):
+    """
+    Get the quantization config of the related quantization method
+    """
+    if (
+        hasattr(model, "config")
+        and hasattr(model.config, "quantization_config")
+        and (getattr(model, "quantization_method", None) == method)
+    ):
+        return model.config.quantization_config
+    return None
+
+
+def get_auto_gptq_quant_linear(gptq_quantization_config):
+    """
+    Get the right AutoGPTQQuantLinear class based on the quantization config file
+    """
+    if gptq_quantization_config is None:
+        return None
+
+    if is_auto_gptq_available():
+        from auto_gptq.utils.import_utils import dynamically_import_QuantLinear
+    else:
+        return None
+
+    desc_act = gptq_quantization_config.desc_act
+    group_size = gptq_quantization_config.group_size
+    bits = gptq_quantization_config.bits
+    if hasattr(gptq_quantization_config, "use_exllama"):
+        use_exllama = gptq_quantization_config.use_exllama
+    else:
+        use_exllama = not gptq_quantization_config.disable_exllama
+    if hasattr(gptq_quantization_config, "exllama_config"):
+        exllama_version = gptq_quantization_config.exllama_config["version"]
+    else:
+        exllama_version = 1
+
+    QuantLinear = dynamically_import_QuantLinear(
+        use_triton=False,
+        desc_act=desc_act,
+        group_size=group_size,
+        bits=bits,
+        disable_exllama=not (use_exllama and exllama_version == 1),
+        disable_exllamav2=not (use_exllama and exllama_version == 2),
+    )
+
+    return QuantLinear
+
+
+def get_gptqmodel_quant_linear(gptq_quantization_config, device_map=None):
+    """
+    Get the right GPTQQuantLinear class based on the quantization config file
+    """
+    if gptq_quantization_config is None:
+        return None
+
+    if not is_gptqmodel_available():
+        return None
+
+    from gptqmodel.utils.importer import hf_select_quant_linear
+
+    desc_act = gptq_quantization_config.desc_act
+    group_size = gptq_quantization_config.group_size
+    bits = gptq_quantization_config.bits
+    checkpoint_format = (
+        gptq_quantization_config.checkpoint_format
+        if hasattr(gptq_quantization_config, "checkpoint_format")
+        else "gptq"
+    )
+    sym = gptq_quantization_config.sym
+    meta = gptq_quantization_config.meta if hasattr(gptq_quantization_config, "meta") else None
+
+    QuantLinear = hf_select_quant_linear(
+        bits=bits,
+        group_size=group_size,
+        desc_act=desc_act,
+        sym=sym,
+        device_map=device_map,
+        checkpoint_format=checkpoint_format,
+        meta=meta,
+        backend="auto_trainable",
+    )
+
+    return QuantLinear
+
+
+def id_tensor_storage(tensor: torch.Tensor) -> tuple[torch.device, int, int]:
+    """
+    Unique identifier to a tensor storage. Multiple different tensors can share the same underlying storage. For
+    example, "meta" tensors all share the same storage, and thus their identifier will all be equal. This identifier is
+    guaranteed to be unique and constant for this tensor's storage during its lifetime. Two tensor storages with
+    non-overlapping lifetimes may have the same id.
+
+    This method is the exact same copy of
+    https://github.com/huggingface/transformers/blob/main/src/transformers/pytorch_utils.py#L282C1-L300C58 but we added
+    it here manually to avoid import issue with old versions of transformers.
+    """
+    if tensor.device.type == "xla" and is_torch_tpu_available():
+        # NOTE: xla tensors dont have storage
+        # use some other unique id to distinguish.
+        # this is a XLA tensor, it must be created using torch_xla's
+        # device. So the following import is safe:
+        import torch_xla
+
+        unique_id = torch_xla._XLAC._xla_get_tensor_id(tensor)
+    else:
+        unique_id = storage_ptr(tensor)
+
+    return tensor.device, unique_id, storage_size(tensor)
+
+
+def cast_mixed_precision_params(model, dtype):
+    """
+    Cast all non-trainable parameters of the model to the given `dtype`. The `dtype` can be `torch.float16` or
+    `torch.bfloat16` as per the mixed-precision training you are performing. The trainable parameters are cast to full
+    precision. This is meant to reduce the GPU memory usage when using PEFT methods by using half-precision dtype for
+    non-trainable parameters. Having the trainable parameters in full-precision preserves training stability when using
+    automatic mixed-precision training.
+
+    Args:
+        model (`torch.nn.Module`):
+            The model to cast the non-trainable parameters of.
+        dtype (`torch.dtype`):
+            The dtype to cast the non-trainable parameters to. The `dtype` can be `torch.float16` or
+    `torch.bfloat16` as per the mixed-precision training you are performing.
+    """
+    for p in model.parameters():
+        if not p.requires_grad:
+            p.data = p.to(dtype)
+        else:
+            p.data = p.to(torch.float32)
+
+
+def str_to_bool(value: str) -> int:
+    """
+    Converts a string representation of truth to `True` (1) or `False` (0).
+
+    True values are `y`, `yes`, `t`, `true`, `on`, and `1`; False value are `n`, `no`, `f`, `false`, `off`, and `0`;
+    """
+    # same as function as in accelerate.utils, which replaces the deprecated distutils.util.strtobool
+    value = value.lower()
+    if value in ("y", "yes", "t", "true", "on", "1"):
+        return 1
+    elif value in ("n", "no", "f", "false", "off", "0"):
+        return 0
+    else:
+        raise ValueError(f"invalid truth value {value}")
+
+
+def check_file_exists_on_hf_hub(repo_id: str, filename: str, **kwargs) -> Optional[bool]:
+    """Check if a file exists on HF Hub, if check was not successful returns None instead of erroring.
+
+    Respect offline mode if set.
+
+    """
+    exists: Optional[bool] = None
+    if str_to_bool(os.environ.get("HF_HUB_OFFLINE", "0")):
+        # user set offline mode, cannot check
+        return exists
+
+    try:
+        exists = file_exists(repo_id, filename, **kwargs)
+    except (HFValidationError, EntryNotFoundError):
+        # error, exists stays None
+        pass
+    except Exception as e:
+        warnings.warn(
+            f"Unable to fetch remote file due to the following error {e} - silently ignoring the lookup"
+            f" for the file {filename} in {repo_id}."
+        )
+
+    return exists
+
+
+def get_pattern_key(pattern_keys: Sequence[str], key_to_match: str) -> str:
+    """Match a substring of key_to_match in pattern keys"""
+    for key in pattern_keys:
+        match = re.match(rf"(.*\.)?({key})$", key_to_match)
+        if not match:
+            continue
+        return key
+
+    return key_to_match
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/peft_types.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/peft_types.py
new file mode 100644
index 0000000000000000000000000000000000000000..a205bd4550cad185bd464490ecbac87ecddd654a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/peft_types.py
@@ -0,0 +1,165 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import enum
+from typing import Optional
+
+
+class PeftType(str, enum.Enum):
+    """
+    Enum class for the different types of adapters in PEFT.
+
+    Supported PEFT types:
+    - PROMPT_TUNING
+    - MULTITASK_PROMPT_TUNING
+    - P_TUNING
+    - PREFIX_TUNING
+    - LORA
+    - ADALORA
+    - BOFT
+    - ADAPTION_PROMPT
+    - IA3
+    - LOHA
+    - LOKR
+    - OFT
+    - XLORA
+    - POLY
+    - LN_TUNING
+    - VERA
+    - FOURIERFT
+    - HRA
+    - BONE
+    """
+
+    PROMPT_TUNING = "PROMPT_TUNING"
+    MULTITASK_PROMPT_TUNING = "MULTITASK_PROMPT_TUNING"
+    P_TUNING = "P_TUNING"
+    PREFIX_TUNING = "PREFIX_TUNING"
+    LORA = "LORA"
+    ADALORA = "ADALORA"
+    BOFT = "BOFT"
+    ADAPTION_PROMPT = "ADAPTION_PROMPT"
+    IA3 = "IA3"
+    LOHA = "LOHA"
+    LOKR = "LOKR"
+    OFT = "OFT"
+    POLY = "POLY"
+    LN_TUNING = "LN_TUNING"
+    VERA = "VERA"
+    FOURIERFT = "FOURIERFT"
+    XLORA = "XLORA"
+    HRA = "HRA"
+    VBLORA = "VBLORA"
+    CPT = "CPT"
+    BONE = "BONE"
+    TRAINABLE_TOKENS = "TRAINABLE_TOKENS"
+
+
+class TaskType(str, enum.Enum):
+    """
+    Enum class for the different types of tasks supported by PEFT.
+
+    Overview of the supported task types:
+    - SEQ_CLS: Text classification.
+    - SEQ_2_SEQ_LM: Sequence-to-sequence language modeling.
+    - CAUSAL_LM: Causal language modeling.
+    - TOKEN_CLS: Token classification.
+    - QUESTION_ANS: Question answering.
+    - FEATURE_EXTRACTION: Feature extraction. Provides the hidden states which can be used as embeddings or features
+      for downstream tasks.
+    """
+
+    SEQ_CLS = "SEQ_CLS"
+    SEQ_2_SEQ_LM = "SEQ_2_SEQ_LM"
+    CAUSAL_LM = "CAUSAL_LM"
+    TOKEN_CLS = "TOKEN_CLS"
+    QUESTION_ANS = "QUESTION_ANS"
+    FEATURE_EXTRACTION = "FEATURE_EXTRACTION"
+
+
+def register_peft_method(
+    *, name: str, config_cls, model_cls, prefix: Optional[str] = None, is_mixed_compatible=False
+) -> None:
+    """
+    Function to register a finetuning method like LoRA to be available in PEFT.
+
+    This method takes care of registering the PEFT method's configuration class, the model class, and optionally the
+    prefix.
+
+    Args:
+        name (str):
+            The name of the PEFT method. It must be unique.
+        config_cls:
+            The configuration class of the PEFT method.
+        model_cls:
+            The model class of the PEFT method.
+        prefix (Optional[str], optional):
+            The prefix of the PEFT method. It should be unique. If not provided, the name of the PEFT method is used as
+            the prefix.
+        is_mixed_compatible (bool, optional):
+            Whether the PEFT method is compatible with `PeftMixedModel`. If you're not sure, leave it as False
+            (default).
+
+    Example:
+
+        ```py
+        # inside of peft/tuners/my_peft_method/__init__.py
+        from peft.utils import register_peft_method
+
+        register_peft_method(name="my_peft_method", config_cls=MyConfig, model_cls=MyModel)
+        ```
+    """
+    from peft.mapping import (
+        PEFT_TYPE_TO_CONFIG_MAPPING,
+        PEFT_TYPE_TO_MIXED_MODEL_MAPPING,
+        PEFT_TYPE_TO_PREFIX_MAPPING,
+        PEFT_TYPE_TO_TUNER_MAPPING,
+    )
+
+    if name.endswith("_"):
+        raise ValueError(f"Please pass the name of the PEFT method without '_' suffix, got {name}.")
+
+    if not name.islower():
+        raise ValueError(f"The name of the PEFT method should be in lower case letters, got {name}.")
+
+    if name.upper() not in list(PeftType):
+        raise ValueError(f"Unknown PEFT type {name.upper()}, please add an entry to peft.utils.peft_types.PeftType.")
+
+    peft_type = getattr(PeftType, name.upper())
+
+    # model_cls can be None for prompt learning methods, which don't have dedicated model classes
+    if prefix is None:
+        prefix = name + "_"
+
+    if (
+        (peft_type in PEFT_TYPE_TO_CONFIG_MAPPING)
+        or (peft_type in PEFT_TYPE_TO_TUNER_MAPPING)
+        or (peft_type in PEFT_TYPE_TO_MIXED_MODEL_MAPPING)
+    ):
+        raise KeyError(f"There is already PEFT method called '{name}', please choose a unique name.")
+
+    if prefix in PEFT_TYPE_TO_PREFIX_MAPPING:
+        raise KeyError(f"There is already a prefix called '{prefix}', please choose a unique prefix.")
+
+    model_cls_prefix = getattr(model_cls, "prefix", None)
+    if (model_cls_prefix is not None) and (model_cls_prefix != prefix):
+        raise ValueError(
+            f"Inconsistent prefixes found: '{prefix}' and '{model_cls_prefix}' (they should be the same)."
+        )
+
+    PEFT_TYPE_TO_PREFIX_MAPPING[peft_type] = prefix
+    PEFT_TYPE_TO_CONFIG_MAPPING[peft_type] = config_cls
+    PEFT_TYPE_TO_TUNER_MAPPING[peft_type] = model_cls
+    if is_mixed_compatible:
+        PEFT_TYPE_TO_MIXED_MODEL_MAPPING[peft_type] = model_cls
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/save_and_load.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/save_and_load.py
new file mode 100644
index 0000000000000000000000000000000000000000..f950b91069974fffb89fead1fc6382e145f9b116
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/peft/utils/save_and_load.py
@@ -0,0 +1,571 @@
+# Copyright 2023-present the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import os
+import warnings
+from typing import Optional
+
+import huggingface_hub
+import torch
+from huggingface_hub import file_exists, hf_hub_download
+from huggingface_hub.errors import EntryNotFoundError, LocalEntryNotFoundError
+from safetensors.torch import load_file as safe_load_file
+
+from peft.mapping import PEFT_TYPE_TO_PREFIX_MAPPING
+
+from .other import (
+    EMBEDDING_LAYER_NAMES,
+    SAFETENSORS_WEIGHTS_NAME,
+    WEIGHTS_NAME,
+    AuxiliaryTrainingWrapper,
+    check_file_exists_on_hf_hub,
+    infer_device,
+)
+from .peft_types import PeftType
+
+
+def has_valid_embedding_base_layer(layer):
+    """Check if the layer has an embedding base layer"""
+    return hasattr(layer, "base_layer") and isinstance(layer.base_layer, (torch.nn.Linear, torch.nn.Embedding))
+
+
+def get_embedding_layer_name(model, layer, is_embedding_in_target_modules):
+    """Get the name of the embedding module for a given layer."""
+    for name, module in model.named_modules():
+        if (not is_embedding_in_target_modules and module == layer) or module == getattr(layer, "base_layer", None):
+            return name
+    return None
+
+
+def get_peft_model_state_dict(
+    model, state_dict=None, adapter_name="default", unwrap_compiled=False, save_embedding_layers="auto"
+):
+    """
+    Get the state dict of the Peft model.
+
+    Args:
+        model ([`PeftModel`]): The Peft model. When using torch.nn.DistributedDataParallel, DeepSpeed or FSDP,
+            the model should be the underlying model/unwrapped model (i.e. model.module).
+        state_dict (`dict`, *optional*, defaults to `None`):
+            The state dict of the model. If not provided, the state dict of the passed model will be used.
+        adapter_name (`str`, *optional*, defaults to `"default"`):
+            The name of the adapter whose state dict should be returned.
+        unwrap_compiled (`bool`, *optional*, defaults to `False`):
+            Whether to unwrap the model if torch.compile was used.
+        save_embedding_layers (`Union[bool, str]`, , *optional*, defaults to `auto`):
+            If `True`, save the embedding layers in addition to adapter weights. If `auto`, checks the common embedding
+            layers `peft.utils.other.EMBEDDING_LAYER_NAMES` in config's `target_modules` when available. Based on it
+            sets the boolean flag. This only works for 🤗 transformers models.
+    """
+    if unwrap_compiled:
+        model = getattr(model, "_orig_mod", model)
+
+    config = model.peft_config[adapter_name]
+    if state_dict is None:
+        state_dict = model.state_dict()
+
+    # TUNER SPECIFIC CODE
+    if config.peft_type in (PeftType.LORA, PeftType.ADALORA):
+        # to_return = lora_state_dict(model, bias=model.peft_config.bias)
+        # adapted from `https://github.com/microsoft/LoRA/blob/main/loralib/utils.py`
+        # to be used directly with the state dict which is necessary when using DeepSpeed or FSDP
+        bias = config.bias
+        if bias == "none":
+            to_return = {k: state_dict[k] for k in state_dict if "lora_" in k}
+        elif bias == "all":
+            to_return = {k: state_dict[k] for k in state_dict if "lora_" in k or "bias" in k}
+        elif bias == "lora_only":
+            to_return = {}
+            for k in state_dict:
+                if "lora_" in k:
+                    to_return[k] = state_dict[k]
+                    bias_name = k.split("lora_")[0] + "bias"
+                    if bias_name in state_dict:
+                        to_return[bias_name] = state_dict[bias_name]
+        else:
+            raise NotImplementedError
+        to_return = {k: v for k, v in to_return.items() if (("lora_" in k and adapter_name in k) or ("bias" in k))}
+        if config.peft_type == PeftType.ADALORA:
+            rank_pattern = config.rank_pattern
+            if rank_pattern is not None:
+                rank_pattern = {k.replace(f".{adapter_name}", ""): v for k, v in rank_pattern.items()}
+                config.rank_pattern = rank_pattern
+                to_return = model.resize_state_dict_by_rank_pattern(rank_pattern, to_return, adapter_name)
+
+        if config.use_dora:
+            # Here we take care of a refactor of DoRA which changed lora_magnitude_vector from a ParameterDict to a
+            # ModuleDict with a DoraLayer instance. The old parameter is now the "weight" attribute of that layer. Since
+            # we want the state_dict format not to change, we remove the "weight" part.
+            new_dora_suffix = f"lora_magnitude_vector.{adapter_name}.weight"
+
+            def renamed_dora_weights(k):
+                if k.endswith(new_dora_suffix):
+                    k = k[:-7]  # remove ".weight"
+                return k
+
+            to_return = {renamed_dora_weights(k): v for k, v in to_return.items()}
+
+    elif config.peft_type == PeftType.BOFT:
+        bias = config.bias
+        if bias == "none":
+            to_return = {k: state_dict[k] for k in state_dict if "boft_" in k}
+        elif bias == "all":
+            to_return = {k: state_dict[k] for k in state_dict if "boft_" in k or "bias" in k}
+        elif bias == "boft_only":
+            to_return = {}
+            for k in state_dict:
+                if "boft_" in k:
+                    to_return[k] = state_dict[k]
+                    bias_name = k.split("boft_")[0] + "bias"
+                    if bias_name in state_dict:
+                        to_return[bias_name] = state_dict[bias_name]
+        else:
+            raise NotImplementedError
+
+    elif config.peft_type == PeftType.ADAPTION_PROMPT:
+        to_return = {k: state_dict[k] for k in state_dict if k.split(".")[-1].startswith("adaption_")}
+
+    elif config.is_prompt_learning:
+        to_return = {}
+        if config.peft_type == PeftType.MULTITASK_PROMPT_TUNING:
+            to_return["prefix_task_cols"] = model.prompt_encoder[adapter_name].prefix_task_cols
+            to_return["prefix_task_rows"] = model.prompt_encoder[adapter_name].prefix_task_rows
+            prompt_embeddings = model.prompt_encoder[adapter_name].embedding.weight
+        else:
+            if config.inference_mode:
+                prompt_embeddings = model.prompt_encoder[adapter_name].embedding.weight
+            else:
+                prompt_embeddings = model.get_prompt_embedding_to_save(adapter_name)
+        to_return["prompt_embeddings"] = prompt_embeddings
+
+    elif config.peft_type == PeftType.VERA:
+        vera_prefix = PEFT_TYPE_TO_PREFIX_MAPPING[config.peft_type]
+        to_return = {k: state_dict[k] for k in state_dict if vera_prefix in k}
+        if config.save_projection:
+            # TODO: adding vera_A and vera_B to `self.get_base_layer` would
+            # make name to match here difficult to predict.
+            if f"base_model.vera_A.{adapter_name}" not in state_dict:
+                raise ValueError(
+                    "Model was initialised to not save vera_A and vera_B but config now specifies to save projection!"
+                    " Set `config.save_projection` to `False`."
+                )
+            to_return["base_model.vera_A." + adapter_name] = state_dict["base_model.vera_A." + adapter_name]
+            to_return["base_model.vera_B." + adapter_name] = state_dict["base_model.vera_B." + adapter_name]
+    elif config.peft_type == PeftType.XLORA:
+        to_return = {k: state_dict[k] for k in state_dict if "internal_xlora_classifier" in k}
+    elif config.peft_type == PeftType.VBLORA:
+        to_return = {}
+        # choose the most efficient dtype for indices
+        if config.num_vectors < 2**8:
+            indices_dtype = torch.uint8
+        elif config.num_vectors < 2**15:
+            indices_dtype = torch.int16
+        elif config.num_vectors < 2**31:
+            indices_dtype = torch.int32
+        else:
+            indices_dtype = torch.int64
+        if config.save_only_topk_weights:
+            # in save_only_topk_weights mode, we save topk_indices and topk_weights for parameter efficiency
+            for k in state_dict:
+                if "vblora_logits" in k:
+                    logits, indices = state_dict[k].topk(config.topk)
+                    to_return.update({k + "_topk_indices": indices.to(dtype=indices_dtype)})
+                    to_return.update({k + "_topk_weights": torch.softmax(logits, dim=-1)[:, :, :-1].contiguous()})
+        else:
+            to_return = {k: state_dict[k] for k in state_dict if "vblora_logits" in k}
+        to_return["base_model.vblora_vector_bank." + adapter_name] = state_dict[
+            "base_model.vblora_vector_bank." + adapter_name
+        ]
+    elif config.peft_type in list(PeftType):
+        prefix = PEFT_TYPE_TO_PREFIX_MAPPING[config.peft_type]
+        to_return = {k: state_dict[k] for k in state_dict if prefix in k}
+    else:
+        raise ValueError(f"Unknown PEFT type passed: {config.peft_type}")
+
+    # ADDITIONAL TRAINING MODULES / MODULES_TO_SAVE
+    for name, module in model.named_modules():
+        if isinstance(module, AuxiliaryTrainingWrapper):
+            # Compute the module-relative state dict to make it easier for the adapter to fetch the appropriate
+            # keys that the module thinks need to be saved. We cannot rely on `.state_dict()` internally of the
+            # module since accelerators like DeepSpeed require special handling which is done for the model
+            # state dict from above but most likely not in the module itself. See #2450.
+            module_state_dict = {
+                k.removeprefix(f"{name}."): v for k, v in state_dict.items() if k.startswith(f"{name}.")
+            }
+            to_return.update(
+                {f"{name}.{k}": v for k, v in module.adapter_state_dict(adapter_name, module_state_dict).items()}
+            )
+
+    # DEAL WITH EMBEDDINGS
+    # check the common embedding layers in `target_modules` to reset `save_embedding_layers` if necessary
+    is_embedding_in_target_modules = False
+    if (
+        save_embedding_layers == "auto"
+        and hasattr(config, "target_modules")
+        and any(k in config.target_modules for k in EMBEDDING_LAYER_NAMES)
+        and config.peft_type != PeftType.TRAINABLE_TOKENS
+    ):
+        warnings.warn("Setting `save_embedding_layers` to `True` as embedding layers found in `target_modules`.")
+        save_embedding_layers = is_embedding_in_target_modules = True
+    elif save_embedding_layers == "auto":
+        vocab_size = getattr(getattr(model, "config", None), "vocab_size", None)
+        model_id = getattr(config, "base_model_name_or_path", None)
+
+        # For some models e.g. diffusers the text config file is stored in a subfolder
+        # we need to make sure we can download that config.
+        has_base_config = False
+
+        # ensure that this check is not performed in HF offline mode, see #1452
+        if model_id is not None:
+            local_config_exists = os.path.exists(os.path.join(model_id, "config.json"))
+            exists = local_config_exists or check_file_exists_on_hf_hub(model_id, "config.json")
+            if exists is None:
+                # check failed, could not determine if it exists or not
+                warnings.warn(
+                    f"Could not find a config file in {model_id} - will assume that the vocabulary was not modified."
+                )
+                has_base_config = False
+            else:
+                has_base_config = exists
+
+        # check if the vocab size of the base model is different from the vocab size of the finetuned model
+        if (
+            vocab_size
+            and model_id
+            and has_base_config
+            and (vocab_size != model.config.__class__.from_pretrained(model_id).vocab_size)
+        ):
+            warnings.warn(
+                "Setting `save_embedding_layers` to `True` as the embedding layer has been resized during finetuning."
+            )
+            save_embedding_layers = True
+        else:
+            save_embedding_layers = False
+
+    if save_embedding_layers and hasattr(model, "get_input_embeddings"):
+        for layer in [model.get_input_embeddings(), model.get_output_embeddings()]:
+            if not is_embedding_in_target_modules or has_valid_embedding_base_layer(layer):
+                # support from version >= 0.6.2
+                embedding_module_name = get_embedding_layer_name(model, layer, is_embedding_in_target_modules)
+                if embedding_module_name:
+                    to_return.update({k: v for k, v in state_dict.items() if embedding_module_name in k})
+    elif save_embedding_layers:
+        warnings.warn("Could not identify embedding layer(s) because the model is not a 🤗 transformers model.")
+
+    # REMOVE ADAPTER NAME
+    to_return = {k.replace(f".{adapter_name}", ""): v for k, v in to_return.items()}
+    return to_return
+
+
+def _find_mismatched_keys(
+    model: torch.nn.Module, peft_model_state_dict: dict[str, torch.Tensor], ignore_mismatched_sizes: bool = False
+) -> tuple[dict[str, torch.Tensor], list[tuple[str, tuple[int, ...], tuple[int, ...]]]]:
+    if not ignore_mismatched_sizes:
+        return peft_model_state_dict, []
+
+    mismatched = []
+    state_dict = model.state_dict()
+    for key, tensor in peft_model_state_dict.items():
+        if key not in state_dict:
+            continue
+
+        # see https://github.com/huggingface/transformers/blob/09f9f566de83eef1f13ee83b5a1bbeebde5c80c1/src/transformers/modeling_utils.py#L3858-L3864
+        if (state_dict[key].shape[-1] == 1) and (state_dict[key].numel() * 2 == tensor.numel()):
+            # This skips size mismatches for 4-bit weights. Two 4-bit values share an 8-bit container, causing size
+            # differences. Without matching with module type or paramter type it seems like a practical way to detect
+            # valid 4bit weights.
+            continue
+
+        if state_dict[key].shape != tensor.shape:
+            mismatched.append((key, tensor.shape, state_dict[key].shape))
+
+    for key, _, _ in mismatched:
+        del peft_model_state_dict[key]
+
+    return peft_model_state_dict, mismatched
+
+
+def _insert_adapter_name_into_state_dict(
+    state_dict: dict[str, torch.Tensor], adapter_name: str, parameter_prefix: str
+) -> dict[str, torch.Tensor]:
+    """Utility function to remap the state_dict keys to fit the PEFT model by inserting the adapter name."""
+    peft_model_state_dict = {}
+    for key, val in state_dict.items():
+        if parameter_prefix in key:
+            suffix = key.split(parameter_prefix)[1]
+            if "." in suffix:
+                suffix_to_replace = ".".join(suffix.split(".")[1:])
+                key = key.replace(suffix_to_replace, f"{adapter_name}.{suffix_to_replace}")
+            else:
+                key = f"{key}.{adapter_name}"
+            peft_model_state_dict[key] = val
+        else:
+            peft_model_state_dict[key] = val
+    return peft_model_state_dict
+
+
+def set_peft_model_state_dict(
+    model,
+    peft_model_state_dict,
+    adapter_name="default",
+    ignore_mismatched_sizes: bool = False,
+    low_cpu_mem_usage: bool = False,
+):
+    """
+    Set the state dict of the Peft model.
+
+    Args:
+        model ([`PeftModel`]):
+            The Peft model.
+        peft_model_state_dict (`dict`):
+            The state dict of the Peft model.
+        adapter_name (`str`, *optional*, defaults to `"default"`):
+            The name of the adapter whose state dict should be set.
+        ignore_mismatched_sizes (`bool`, *optional*, defaults to `False`):
+            Whether to ignore mismatched in the state dict.
+        low_cpu_mem_usage (`bool`, `optional`, defaults to `False`):
+            This argument must be `True` if the `model` was loaded with adapter weights on the meta device, e.g. after
+            calling `inject_adapter_in_model` with `low_cpu_mem_usage=True`. Otherwise, leave it as `False`.
+
+    """
+    config = model.peft_config[adapter_name]
+    state_dict = peft_model_state_dict
+
+    # handle auxiliary training wrappers such as ModulesToSaveWrapper and TrainableTokensWrapper by getting each of
+    # them and translating saved state dict key (which does not include the adapter name) to loaded state dict key
+    # (which includes the adapter name).
+    for name, module in model.named_modules():
+        if isinstance(module, AuxiliaryTrainingWrapper):
+            # Not every module has a 1:1 mapping. ModulesToSaveWrapper, for example, removes the
+            # `modules_to_save.{adapter_name}.` prefix. This prefix must be restored when loading the model from the
+            # saved state dict which is why we fetch a load key map from the wrapper.
+            key_map = module.adapter_state_dict_load_map(adapter_name)
+            for k in key_map:
+                lookup_key = f"{name}.{k}"
+                store_key = f"{name}.{key_map[k]}"
+
+                state_dict[store_key] = peft_model_state_dict[lookup_key]
+
+                # delete the old key from the previous `state_dict = peft_model_state_dict` statement.
+                del state_dict[lookup_key]
+
+    if config.is_prompt_learning or config.peft_type == PeftType.ADAPTION_PROMPT:
+        peft_model_state_dict = state_dict
+    elif config.peft_type == PeftType.XLORA:
+        peft_model_state_dict = state_dict
+    elif config.peft_type in PEFT_TYPE_TO_PREFIX_MAPPING:
+        peft_model_state_dict = {}
+        parameter_prefix = PEFT_TYPE_TO_PREFIX_MAPPING[config.peft_type]
+        if config.peft_type == PeftType.VBLORA and config.save_only_topk_weights:
+            num_vectors, _ = model.vblora_vector_bank[adapter_name].shape
+            state_dict_keys = list(state_dict.keys())
+            for k in state_dict_keys:
+                # in save_only_topk_weights mode, only topk_indices and topk_weights are saved
+                # note that topk_indices and topk_weights serve as an efficient representation of the logits
+                # so we need to recover the logits from the topk_indices and topk_weights
+                if "_topk_indices" in k:
+                    v = state_dict[k].to(torch.long)
+                    original_key = k.replace("_topk_indices", "")
+                    # find the corresponding topk_weights from the state_dict
+                    topk_weights = state_dict[k.replace("_topk_indices", "_topk_weights")]
+                    # as we only save the first k-1 topk_weights, here we recover the last one
+                    topk_weights = torch.cat([topk_weights, 1 - topk_weights.sum(-1, keepdim=True)], dim=-1)
+                    # convert the weights to logits
+                    topk_logits = torch.log(topk_weights)
+                    matrix = (
+                        torch.zeros([*(topk_logits.shape[:-1]), num_vectors])
+                        .fill_(float("-inf"))
+                        .to(topk_logits.device)
+                        .scatter(-1, v, topk_logits)
+                    )
+                    # add logits to the state_dict
+                    state_dict[original_key] = matrix
+                    # delete the topk_indices and topk_weights from the state_dict
+                    del state_dict[k]
+                    del state_dict[k.replace("_topk_indices", "_topk_weights")]
+
+        peft_model_state_dict = _insert_adapter_name_into_state_dict(
+            state_dict, adapter_name=adapter_name, parameter_prefix=parameter_prefix
+        )
+
+        if config.peft_type == PeftType.ADALORA:
+            rank_pattern = config.rank_pattern
+            if rank_pattern is not None:
+                model.resize_modules_by_rank_pattern(rank_pattern, adapter_name)
+        elif config.peft_type == PeftType.VERA:
+            if config.save_projection and "base_model.vera_A" not in peft_model_state_dict:
+                raise ValueError(
+                    "Specified to load vera_A and vera_B from state dictionary however they were not present!"
+                )
+            elif not config.save_projection and "base_model.vera_A" in peft_model_state_dict:
+                warnings.warn(
+                    "Specified to not load vera_A and vera_B from state dictionary however they are present in state"
+                    " dictionary! Consider using them to ensure checkpoint loading is correct on all platforms using"
+                    " `peft_config.save_projection = True`"
+                )
+            elif not config.save_projection:  # and no vera_A in state dictionary
+                warnings.warn(
+                    "Specified to not load vera_A and vera_B from state dictionary. This means we will be relying on"
+                    " PRNG initialisation to restore these projections using `config.projection_prng_key`, which may"
+                    " not be accurate on all system configurations."
+                )
+        elif config.peft_type == PeftType.LORA:
+            # Here we take care of a refactor of DoRA which changed lora_magnitude_vector from a ParameterDict to a
+            # ModuleDict with a DoraLayer instance. The old parameter is now the "weight" attribute of that layer.
+            old_dora_suffix = f"lora_magnitude_vector.{adapter_name}"
+
+            def renamed_dora_weights(k):
+                if k.endswith(old_dora_suffix):
+                    k = k + ".weight"
+                return k
+
+            peft_model_state_dict = {renamed_dora_weights(k): v for k, v in peft_model_state_dict.items()}
+    else:
+        raise NotImplementedError
+
+    peft_model_state_dict, mismatched_keys = _find_mismatched_keys(
+        model, peft_model_state_dict, ignore_mismatched_sizes=ignore_mismatched_sizes
+    )
+    if low_cpu_mem_usage:
+        load_result = model.load_state_dict(peft_model_state_dict, strict=False, assign=True)
+        # ensure that the correct device is set
+        for module in model.modules():
+            if hasattr(module, "_move_adapter_to_device_of_base_layer"):
+                module._move_adapter_to_device_of_base_layer(adapter_name)
+    else:
+        load_result = model.load_state_dict(peft_model_state_dict, strict=False)
+
+    if config.is_prompt_learning:
+        model.prompt_encoder[adapter_name].embedding.load_state_dict(
+            {"weight": peft_model_state_dict["prompt_embeddings"]}, strict=True
+        )
+
+    if config.peft_type == PeftType.MULTITASK_PROMPT_TUNING:
+        model.prompt_encoder[adapter_name].load_state_dict(peft_model_state_dict, strict=False)
+
+    if mismatched_keys:
+        # see https://github.com/huggingface/transformers/blob/09f9f566de83eef1f13ee83b5a1bbeebde5c80c1/src/transformers/modeling_utils.py#L4039
+        mismatched_warning = "\n".join(
+            [
+                f"- {key}: found shape {shape1} in the checkpoint and {shape2} in the model instantiated"
+                for key, shape1, shape2 in mismatched_keys
+            ]
+        )
+        msg = (
+            f"Some weights of {model.__class__.__name__} were not initialized from the model checkpoint "
+            f"and are being ignored because you passed `ignore_mismatched_sizes=True`: {mismatched_warning}."
+        )
+        warnings.warn(msg)
+    return load_result
+
+
+# TODO: remove this function, use vanilla torch.load as soon as torch < 2.6.0 is no longer supported
+def torch_load(*args, weights_only=True, **kwargs):
+    """Call torch.load and handle weights_only.
+
+    Defaults to weights_only=True to anticipate upcoming switch on the PyTorch side.
+
+    """
+    return torch.load(*args, weights_only=weights_only, **kwargs)
+
+
+def load_peft_weights(model_id: str, device: Optional[str] = None, **hf_hub_download_kwargs) -> dict:
+    r"""
+    A helper method to load the PEFT weights from the HuggingFace Hub or locally
+
+    Args:
+        model_id (`str`):
+            The local path to the adapter weights or the name of the adapter to load from the HuggingFace Hub.
+        device (`str`):
+            The device to load the weights onto.
+        hf_hub_download_kwargs (`dict`):
+            Additional arguments to pass to the `hf_hub_download` method when loading from the HuggingFace Hub.
+    """
+    path = (
+        os.path.join(model_id, hf_hub_download_kwargs["subfolder"])
+        if hf_hub_download_kwargs.get("subfolder", None) is not None
+        else model_id
+    )
+
+    if device is None:
+        device = infer_device()
+
+    def get_hub_filename(use_safetensors=True):
+        weights_name = SAFETENSORS_WEIGHTS_NAME if use_safetensors else WEIGHTS_NAME
+        return (
+            os.path.join(hf_hub_download_kwargs["subfolder"], weights_name)
+            if hf_hub_download_kwargs.get("subfolder", None) is not None
+            else weights_name
+        )
+
+    if os.path.exists(os.path.join(path, SAFETENSORS_WEIGHTS_NAME)):
+        filename = os.path.join(path, SAFETENSORS_WEIGHTS_NAME)
+        use_safetensors = True
+    elif os.path.exists(os.path.join(path, WEIGHTS_NAME)):
+        filename = os.path.join(path, WEIGHTS_NAME)
+        use_safetensors = False
+    elif huggingface_hub.constants.HF_HUB_OFFLINE:
+        # if in offline mode, check if we can find the adapter file locally
+        hub_filename = get_hub_filename(use_safetensors=True)
+        hf_hub_download_kwargs.pop("local_files_only", None)
+        try:
+            filename = hf_hub_download(model_id, hub_filename, local_files_only=True, **hf_hub_download_kwargs)
+            use_safetensors = True
+        except LocalEntryNotFoundError:
+            # Could not find safetensors, try pickle. If this also fails, it's fine to let the error be raised here, as
+            # it means that the user tried to load a non-cached model in offline mode.
+            hub_filename = get_hub_filename(use_safetensors=False)
+            filename = hf_hub_download(model_id, hub_filename, local_files_only=True, **hf_hub_download_kwargs)
+            use_safetensors = False
+    else:
+        token = hf_hub_download_kwargs.get("token", None)
+        if token is None:
+            token = hf_hub_download_kwargs.get("use_auth_token", None)
+
+        hub_filename = get_hub_filename(use_safetensors=True)
+        has_remote_safetensors_file = file_exists(
+            repo_id=model_id,
+            filename=hub_filename,
+            revision=hf_hub_download_kwargs.get("revision", None),
+            repo_type=hf_hub_download_kwargs.get("repo_type", None),
+            token=token,
+        )
+        use_safetensors = has_remote_safetensors_file
+
+        if has_remote_safetensors_file:
+            # Priority 1: load safetensors weights
+            filename = hf_hub_download(
+                model_id,
+                SAFETENSORS_WEIGHTS_NAME,
+                **hf_hub_download_kwargs,
+            )
+        else:
+            try:
+                filename = hf_hub_download(model_id, WEIGHTS_NAME, **hf_hub_download_kwargs)
+            except EntryNotFoundError:
+                raise ValueError(
+                    f"Can't find weights for {model_id} in {model_id} or in the Hugging Face Hub. "
+                    f"Please check that the file {WEIGHTS_NAME} or {SAFETENSORS_WEIGHTS_NAME} is present at {model_id}."
+                )
+
+    if use_safetensors:
+        if hasattr(torch.backends, "mps") and (device == torch.device("mps")):
+            adapters_weights = safe_load_file(filename, device="cpu")
+        else:
+            adapters_weights = safe_load_file(filename, device=device)
+    else:
+        adapters_weights = torch_load(filename, map_location=torch.device(device))
+
+    return adapters_weights
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/INSTALLER b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/METADATA b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..c147a6463bc3a423623f2c4cc616b82e4cd32a1b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/METADATA
@@ -0,0 +1,175 @@
+Metadata-Version: 2.4
+Name: pillow
+Version: 12.1.0
+Summary: Python Imaging Library (fork)
+Author-email: "Jeffrey A. Clark" 
+License-Expression: MIT-CMU
+Project-URL: Changelog, https://github.com/python-pillow/Pillow/releases
+Project-URL: Documentation, https://pillow.readthedocs.io
+Project-URL: Funding, https://tidelift.com/subscription/pkg/pypi-pillow?utm_source=pypi-pillow&utm_medium=pypi
+Project-URL: Homepage, https://python-pillow.github.io
+Project-URL: Mastodon, https://fosstodon.org/@pillow
+Project-URL: Release notes, https://pillow.readthedocs.io/en/stable/releasenotes/index.html
+Project-URL: Source, https://github.com/python-pillow/Pillow
+Keywords: Imaging
+Classifier: Development Status :: 6 - Mature
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Topic :: Multimedia :: Graphics
+Classifier: Topic :: Multimedia :: Graphics :: Capture :: Digital Camera
+Classifier: Topic :: Multimedia :: Graphics :: Capture :: Screen Capture
+Classifier: Topic :: Multimedia :: Graphics :: Graphics Conversion
+Classifier: Topic :: Multimedia :: Graphics :: Viewers
+Classifier: Typing :: Typed
+Requires-Python: >=3.10
+Description-Content-Type: text/markdown
+License-File: LICENSE
+Provides-Extra: docs
+Requires-Dist: furo; extra == "docs"
+Requires-Dist: olefile; extra == "docs"
+Requires-Dist: sphinx>=8.2; extra == "docs"
+Requires-Dist: sphinx-autobuild; extra == "docs"
+Requires-Dist: sphinx-copybutton; extra == "docs"
+Requires-Dist: sphinx-inline-tabs; extra == "docs"
+Requires-Dist: sphinxext-opengraph; extra == "docs"
+Provides-Extra: fpx
+Requires-Dist: olefile; extra == "fpx"
+Provides-Extra: mic
+Requires-Dist: olefile; extra == "mic"
+Provides-Extra: test-arrow
+Requires-Dist: arro3-compute; extra == "test-arrow"
+Requires-Dist: arro3-core; extra == "test-arrow"
+Requires-Dist: nanoarrow; extra == "test-arrow"
+Requires-Dist: pyarrow; extra == "test-arrow"
+Provides-Extra: tests
+Requires-Dist: check-manifest; extra == "tests"
+Requires-Dist: coverage>=7.4.2; extra == "tests"
+Requires-Dist: defusedxml; extra == "tests"
+Requires-Dist: markdown2; extra == "tests"
+Requires-Dist: olefile; extra == "tests"
+Requires-Dist: packaging; extra == "tests"
+Requires-Dist: pyroma>=5; extra == "tests"
+Requires-Dist: pytest; extra == "tests"
+Requires-Dist: pytest-cov; extra == "tests"
+Requires-Dist: pytest-timeout; extra == "tests"
+Requires-Dist: pytest-xdist; extra == "tests"
+Requires-Dist: trove-classifiers>=2024.10.12; extra == "tests"
+Provides-Extra: xmp
+Requires-Dist: defusedxml; extra == "xmp"
+Dynamic: license-file
+
+

+    Pillow logo
+

+
+# Pillow
+
+## Python Imaging Library (Fork)
+
+Pillow is the friendly PIL fork by [Jeffrey A. Clark and
+contributors](https://github.com/python-pillow/Pillow/graphs/contributors).
+PIL is the Python Imaging Library by Fredrik Lundh and contributors.
+As of 2019, Pillow development is
+[supported by Tidelift](https://tidelift.com/subscription/pkg/pypi-pillow?utm_source=pypi-pillow&utm_medium=readme&utm_campaign=enterprise).
+
+
+    
+        
+        
+    
+    
+        
+        
+    
+    
+        
+        
+    
+    
+        
+        
+    
+
docs
+            Documentation Status
+        
tests
+            GitHub Actions build status (Lint)
+            GitHub Actions build status (Test Linux and macOS)
+            GitHub Actions build status (Test Windows)
+            GitHub Actions build status (Test MinGW)
+            GitHub Actions build status (Test Docker)
+            GitHub Actions build status (Wheels)
+            Code coverage
+            Fuzzing Status
+        
package
+            Zenodo
+            Tidelift
+            Newest PyPI version
+            Number of PyPI downloads
+            OpenSSF Best Practices
+        
social
+            Join the chat at https://gitter.im/python-pillow/Pillow
+            Follow on https://fosstodon.org/@pillow
+        

+
+## Overview
+
+The Python Imaging Library adds image processing capabilities to your Python interpreter.
+
+This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities.
+
+The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.
+
+## More information
+
+- [Documentation](https://pillow.readthedocs.io/)
+  - [Installation](https://pillow.readthedocs.io/en/latest/installation/basic-installation.html)
+  - [Handbook](https://pillow.readthedocs.io/en/latest/handbook/index.html)
+- [Contribute](https://github.com/python-pillow/Pillow/blob/main/.github/CONTRIBUTING.md)
+  - [Issues](https://github.com/python-pillow/Pillow/issues)
+  - [Pull requests](https://github.com/python-pillow/Pillow/pulls)
+- [Release notes](https://pillow.readthedocs.io/en/stable/releasenotes/index.html)
+- [Changelog](https://github.com/python-pillow/Pillow/releases)
+  - [Pre-fork](https://github.com/python-pillow/Pillow/blob/main/CHANGES.rst#pre-fork)
+
+## Report a vulnerability
+
+To report a security vulnerability, please follow the procedure described in the [Tidelift security policy](https://tidelift.com/docs/security).
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/RECORD b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..fdbaebf3e6da3d120bddf334a2fe815a9cb647db
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/RECORD
@@ -0,0 +1,238 @@
+PIL/AvifImagePlugin.py,sha256=sHaYxONtVEDZ24y8Ad7qRlixD4iIPC2ipH1W79-uPbE,9030
+PIL/BdfFontFile.py,sha256=PhlZfIRmEfmorbhZZeSM5eebGo1Ei7fL-lR9XlfTZZA,3285
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+PIL/BmpImagePlugin.py,sha256=64PB3YE8kEL8QrAuUMlWoEaByYJUTYV6OQA254Uj4Lc,19925
+PIL/BufrStubImagePlugin.py,sha256=gMbELNwEghE_IM2Ov1NT4jy-96CTpEvyuj_mXmckL-c,1765
+PIL/ContainerIO.py,sha256=wkBqL2GDAb5fh3wrtfTGUfqioJipCl-lg2GxbjQrTZw,4604
+PIL/CurImagePlugin.py,sha256=-WEsgwQbA9rQzXB0HG0LK1V_qbuwHosPZ0T2IjfN8r0,1791
+PIL/DcxImagePlugin.py,sha256=OlCv6yDI0LLZNbuUI7s69FI1DuArPyGxo3YCzQ1n8Hg,2180
+PIL/DdsImagePlugin.py,sha256=JRhDGFhKXvolAiD_X4_nYQ3DARogu2hmE2AhZuGc02Q,18931
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+PIL/ExifTags.py,sha256=zW6kVikCosiyoCo7J7R62evD3hoxjKPchnVh8po7CZc,9931
+PIL/FitsImagePlugin.py,sha256=-oDJnAH113CK5qPvwz9lL81fkV1gla_tNfqLcq8zKgo,4644
+PIL/FliImagePlugin.py,sha256=4zxH8IXBX9DGi6dJRM6Y5NMdbA1d99x696mcGZHxHzI,4929
+PIL/FontFile.py,sha256=St7MxO5Q-oakCLWn3ZrgrtaT3wSsmAarxm8AU-G8Moc,3577
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diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/licenses/LICENSE b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/licenses/LICENSE
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+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pillow-12.1.0.dist-info/licenses/LICENSE
@@ -0,0 +1,1523 @@
+The Python Imaging Library (PIL) is
+
+    Copyright © 1997-2011 by Secret Labs AB
+    Copyright © 1995-2011 by Fredrik Lundh and contributors
+
+Pillow is the friendly PIL fork. It is
+
+    Copyright © 2010 by Jeffrey A. Clark and contributors
+
+Like PIL, Pillow is licensed under the open source MIT-CMU License:
+
+By obtaining, using, and/or copying this software and/or its associated
+documentation, you agree that you have read, understood, and will comply
+with the following terms and conditions:
+
+Permission to use, copy, modify and distribute this software and its
+documentation for any purpose and without fee is hereby granted,
+provided that the above copyright notice appears in all copies, and that
+both that copyright notice and this permission notice appear in supporting
+documentation, and that the name of Secret Labs AB or the author not be
+used in advertising or publicity pertaining to distribution of the software
+without specific, written prior permission.
+
+SECRET LABS AB AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS
+SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS.
+IN NO EVENT SHALL SECRET LABS AB OR THE AUTHOR BE LIABLE FOR ANY SPECIAL,
+INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
+LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE
+OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
+PERFORMANCE OF THIS SOFTWARE.
+
+
+----
+
+AOM
+
+Copyright (c) 2016, Alliance for Open Media. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions
+are met:
+
+1. Redistributions of source code must retain the above copyright
+   notice, this list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright
+   notice, this list of conditions and the following disclaimer in
+   the documentation and/or other materials provided with the
+   distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+
+
+----
+
+BROTLI
+
+Copyright (c) 2009, 2010, 2013-2016 by the Brotli Authors.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
+
+
+----
+
+BZIP2
+
+
+--------------------------------------------------------------------------
+
+This program, "bzip2", the associated library "libbzip2", and all
+documentation, are copyright (C) 1996-2019 Julian R Seward.  All
+rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions
+are met:
+
+1. Redistributions of source code must retain the above copyright
+   notice, this list of conditions and the following disclaimer.
+
+2. The origin of this software must not be misrepresented; you must
+   not claim that you wrote the original software.  If you use this
+   software in a product, an acknowledgment in the product
+   documentation would be appreciated but is not required.
+
+3. Altered source versions must be plainly marked as such, and must
+   not be misrepresented as being the original software.
+
+4. The name of the author may not be used to endorse or promote
+   products derived from this software without specific prior written
+   permission.
+
+THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS
+OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ARE DISCLAIMED.  IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY
+DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
+GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+Julian Seward, jseward@acm.org
+bzip2/libbzip2 version 1.0.8 of 13 July 2019
+
+--------------------------------------------------------------------------
+
+
+----
+
+DAV1D
+
+Copyright © 2018-2019, VideoLAN and dav1d authors
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+----
+
+FREETYPE2
+
+The FreeType  2 font  engine is  copyrighted work  and cannot  be used
+legally without  a software  license.  In order  to make  this project
+usable to  a vast majority of  developers, we distribute it  under two
+mutually exclusive open-source licenses.
+
+This means that *you* must choose  *one* of the two licenses described
+below, then obey all its terms and conditions when using FreeType 2 in
+any of your projects or products.
+
+  - The FreeType License,  found in the file  `docs/FTL.TXT`, which is
+    similar to the  original BSD license *with*  an advertising clause
+    that forces  you to explicitly  cite the FreeType project  in your
+    product's  documentation.  All  details are  in the  license file.
+    This license is suited to products which don't use the GNU General
+    Public License.
+
+    Note that  this license  is compatible to  the GNU  General Public
+    License version 3, but not version 2.
+
+  - The   GNU   General   Public   License   version   2,   found   in
+    `docs/GPLv2.TXT`  (any  later  version  can  be  used  also),  for
+    programs  which  already  use  the  GPL.  Note  that  the  FTL  is
+    incompatible with GPLv2 due to its advertisement clause.
+
+The contributed  BDF and PCF  drivers come  with a license  similar to
+that  of the  X Window  System.   It is  compatible to  the above  two
+licenses (see files `src/bdf/README`  and `src/pcf/README`).  The same
+holds   for   the   source    code   files   `src/base/fthash.c`   and
+`include/freetype/internal/fthash.h`; they were part of the BDF driver
+in earlier FreeType versions.
+
+The gzip  module uses the  zlib license (see  `src/gzip/zlib.h`) which
+too is compatible to the above two licenses.
+
+The files `src/autofit/ft-hb.c` and `src/autofit/ft-hb.h` contain code
+taken almost  verbatim from the  HarfBuzz file `hb-ft.cc`,  which uses
+the 'Old MIT' license, compatible to the above two licenses.
+
+The  MD5 checksum  support  (only used  for  debugging in  development
+builds) is in the public domain.
+
+--------------------------------------------------------------------------
+
+                    The FreeType Project LICENSE
+                    ----------------------------
+
+                            2006-Jan-27
+
+                    Copyright 1996-2002, 2006 by
+          David Turner, Robert Wilhelm, and Werner Lemberg
+
+
+
+Introduction
+============
+
+  The FreeType  Project is distributed in  several archive packages;
+  some of them may contain, in addition to the FreeType font engine,
+  various tools and  contributions which rely on, or  relate to, the
+  FreeType Project.
+
+  This  license applies  to all  files found  in such  packages, and
+  which do not  fall under their own explicit  license.  The license
+  affects  thus  the  FreeType   font  engine,  the  test  programs,
+  documentation and makefiles, at the very least.
+
+  This  license   was  inspired  by  the  BSD,   Artistic,  and  IJG
+  (Independent JPEG  Group) licenses, which  all encourage inclusion
+  and  use of  free  software in  commercial  and freeware  products
+  alike.  As a consequence, its main points are that:
+
+    o We don't promise that this software works. However, we will be
+      interested in any kind of bug reports. (`as is' distribution)
+
+    o You can  use this software for whatever you  want, in parts or
+      full form, without having to pay us. (`royalty-free' usage)
+
+    o You may not pretend that  you wrote this software.  If you use
+      it, or  only parts of it,  in a program,  you must acknowledge
+      somewhere  in  your  documentation  that  you  have  used  the
+      FreeType code. (`credits')
+
+  We  specifically  permit  and  encourage  the  inclusion  of  this
+  software, with  or without modifications,  in commercial products.
+  We  disclaim  all warranties  covering  The  FreeType Project  and
+  assume no liability related to The FreeType Project.
+
+
+  Finally,  many  people  asked  us  for  a  preferred  form  for  a
+  credit/disclaimer to use in compliance with this license.  We thus
+  encourage you to use the following text:
+
+   """
+    Portions of this software are copyright ©  The FreeType
+    Project (www.freetype.org).  All rights reserved.
+   """
+
+  Please replace  with the value from the FreeType version you
+  actually use.
+
+
+Legal Terms
+===========
+
+0. Definitions
+--------------
+
+  Throughout this license,  the terms `package', `FreeType Project',
+  and  `FreeType  archive' refer  to  the  set  of files  originally
+  distributed  by the  authors  (David Turner,  Robert Wilhelm,  and
+  Werner Lemberg) as the `FreeType Project', be they named as alpha,
+  beta or final release.
+
+  `You' refers to  the licensee, or person using  the project, where
+  `using' is a generic term including compiling the project's source
+  code as  well as linking it  to form a  `program' or `executable'.
+  This  program is  referred to  as  `a program  using the  FreeType
+  engine'.
+
+  This  license applies  to all  files distributed  in  the original
+  FreeType  Project,   including  all  source   code,  binaries  and
+  documentation,  unless  otherwise  stated   in  the  file  in  its
+  original, unmodified form as  distributed in the original archive.
+  If you are  unsure whether or not a particular  file is covered by
+  this license, you must contact us to verify this.
+
+  The FreeType  Project is copyright (C) 1996-2000  by David Turner,
+  Robert Wilhelm, and Werner Lemberg.  All rights reserved except as
+  specified below.
+
+1. No Warranty
+--------------
+
+  THE FREETYPE PROJECT  IS PROVIDED `AS IS' WITHOUT  WARRANTY OF ANY
+  KIND, EITHER  EXPRESS OR IMPLIED,  INCLUDING, BUT NOT  LIMITED TO,
+  WARRANTIES  OF  MERCHANTABILITY   AND  FITNESS  FOR  A  PARTICULAR
+  PURPOSE.  IN NO EVENT WILL ANY OF THE AUTHORS OR COPYRIGHT HOLDERS
+  BE LIABLE  FOR ANY DAMAGES CAUSED  BY THE USE OR  THE INABILITY TO
+  USE, OF THE FREETYPE PROJECT.
+
+2. Redistribution
+-----------------
+
+  This  license  grants  a  worldwide, royalty-free,  perpetual  and
+  irrevocable right  and license to use,  execute, perform, compile,
+  display,  copy,   create  derivative  works   of,  distribute  and
+  sublicense the  FreeType Project (in  both source and  object code
+  forms)  and  derivative works  thereof  for  any  purpose; and  to
+  authorize others  to exercise  some or all  of the  rights granted
+  herein, subject to the following conditions:
+
+    o Redistribution of  source code  must retain this  license file
+      (`FTL.TXT') unaltered; any  additions, deletions or changes to
+      the original  files must be clearly  indicated in accompanying
+      documentation.   The  copyright   notices  of  the  unaltered,
+      original  files must  be  preserved in  all  copies of  source
+      files.
+
+    o Redistribution in binary form must provide a  disclaimer  that
+      states  that  the software is based in part of the work of the
+      FreeType Team,  in  the  distribution  documentation.  We also
+      encourage you to put an URL to the FreeType web page  in  your
+      documentation, though this isn't mandatory.
+
+  These conditions  apply to any  software derived from or  based on
+  the FreeType Project,  not just the unmodified files.   If you use
+  our work, you  must acknowledge us.  However, no  fee need be paid
+  to us.
+
+3. Advertising
+--------------
+
+  Neither the  FreeType authors and  contributors nor you  shall use
+  the name of the  other for commercial, advertising, or promotional
+  purposes without specific prior written permission.
+
+  We suggest,  but do not require, that  you use one or  more of the
+  following phrases to refer  to this software in your documentation
+  or advertising  materials: `FreeType Project',  `FreeType Engine',
+  `FreeType library', or `FreeType Distribution'.
+
+  As  you have  not signed  this license,  you are  not  required to
+  accept  it.   However,  as  the FreeType  Project  is  copyrighted
+  material, only  this license, or  another one contracted  with the
+  authors, grants you  the right to use, distribute,  and modify it.
+  Therefore,  by  using,  distributing,  or modifying  the  FreeType
+  Project, you indicate that you understand and accept all the terms
+  of this license.
+
+4. Contacts
+-----------
+
+  There are two mailing lists related to FreeType:
+
+    o freetype@nongnu.org
+
+      Discusses general use and applications of FreeType, as well as
+      future and  wanted additions to the  library and distribution.
+      If  you are looking  for support,  start in  this list  if you
+      haven't found anything to help you in the documentation.
+
+    o freetype-devel@nongnu.org
+
+      Discusses bugs,  as well  as engine internals,  design issues,
+      specific licenses, porting, etc.
+
+  Our home page can be found at
+
+    https://www.freetype.org
+
+
+--- end of FTL.TXT ---
+
+The following license details are part of `src/bdf/README`:
+
+```
+License
+*******
+
+Copyright (C) 2001-2002 by Francesco Zappa Nardelli
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be
+included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+*** Portions of the driver (that is, bdflib.c and bdf.h):
+
+Copyright 2000 Computing Research Labs, New Mexico State University
+Copyright 2001-2002, 2011 Francesco Zappa Nardelli
+
+Permission is hereby granted, free of charge, to any person obtaining a
+copy of this software and associated documentation files (the "Software"),
+to deal in the Software without restriction, including without limitation
+the rights to use, copy, modify, merge, publish, distribute, sublicense,
+and/or sell copies of the Software, and to permit persons to whom the
+Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL
+THE COMPUTING RESEARCH LAB OR NEW MEXICO STATE UNIVERSITY BE LIABLE FOR ANY
+CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT
+OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR
+THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+
+Credits
+*******
+
+This driver is based on excellent Mark Leisher's bdf library.  If you
+find something good in this driver you should probably thank him, not
+me.
+```
+
+The following license details are part of `src/pcf/README`:
+
+```
+License
+*******
+
+Copyright (C) 2000 by Francesco Zappa Nardelli
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be
+included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+
+Credits
+*******
+
+Keith Packard wrote the pcf driver found in XFree86.  His work is at
+the same time the specification and the sample implementation of the
+PCF format.  Undoubtedly, this driver is inspired from his work.
+```
+
+
+----
+
+HARFBUZZ
+
+HarfBuzz is licensed under the so-called "Old MIT" license.  Details follow.
+For parts of HarfBuzz that are licensed under different licenses see individual
+files names COPYING in subdirectories where applicable.
+
+Copyright © 2010-2022  Google, Inc.
+Copyright © 2015-2020  Ebrahim Byagowi
+Copyright © 2019,2020  Facebook, Inc.
+Copyright © 2012,2015  Mozilla Foundation
+Copyright © 2011  Codethink Limited
+Copyright © 2008,2010  Nokia Corporation and/or its subsidiary(-ies)
+Copyright © 2009  Keith Stribley
+Copyright © 2011  Martin Hosken and SIL International
+Copyright © 2007  Chris Wilson
+Copyright © 2005,2006,2020,2021,2022,2023  Behdad Esfahbod
+Copyright © 2004,2007,2008,2009,2010,2013,2021,2022,2023  Red Hat, Inc.
+Copyright © 1998-2005  David Turner and Werner Lemberg
+Copyright © 2016  Igalia S.L.
+Copyright © 2022  Matthias Clasen
+Copyright © 2018,2021  Khaled Hosny
+Copyright © 2018,2019,2020  Adobe, Inc
+Copyright © 2013-2015  Alexei Podtelezhnikov
+
+For full copyright notices consult the individual files in the package.
+
+
+Permission is hereby granted, without written agreement and without
+license or royalty fees, to use, copy, modify, and distribute this
+software and its documentation for any purpose, provided that the
+above copyright notice and the following two paragraphs appear in
+all copies of this software.
+
+IN NO EVENT SHALL THE COPYRIGHT HOLDER BE LIABLE TO ANY PARTY FOR
+DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES
+ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN
+IF THE COPYRIGHT HOLDER HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
+DAMAGE.
+
+THE COPYRIGHT HOLDER SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING,
+BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
+FITNESS FOR A PARTICULAR PURPOSE.  THE SOFTWARE PROVIDED HEREUNDER IS
+ON AN "AS IS" BASIS, AND THE COPYRIGHT HOLDER HAS NO OBLIGATION TO
+PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+
+----
+
+LCMS2
+
+Little CMS
+Copyright (c) 1998-2020 Marti Maria Saguer
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+
+----
+
+LIBAVIF
+
+Copyright 2019 Joe Drago. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+this list of conditions and the following disclaimer in the documentation
+and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+------------------------------------------------------------------------------
+
+Files: src/obu.c
+
+Copyright © 2018-2019, VideoLAN and dav1d authors
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+------------------------------------------------------------------------------
+
+Files: third_party/iccjpeg/*
+
+In plain English:
+
+1. We don't promise that this software works.  (But if you find any bugs,
+   please let us know!)
+2. You can use this software for whatever you want.  You don't have to pay us.
+3. You may not pretend that you wrote this software.  If you use it in a
+   program, you must acknowledge somewhere in your documentation that
+   you've used the IJG code.
+
+In legalese:
+
+The authors make NO WARRANTY or representation, either express or implied,
+with respect to this software, its quality, accuracy, merchantability, or
+fitness for a particular purpose.  This software is provided "AS IS", and you,
+its user, assume the entire risk as to its quality and accuracy.
+
+This software is copyright (C) 1991-2013, Thomas G. Lane, Guido Vollbeding.
+All Rights Reserved except as specified below.
+
+Permission is hereby granted to use, copy, modify, and distribute this
+software (or portions thereof) for any purpose, without fee, subject to these
+conditions:
+(1) If any part of the source code for this software is distributed, then this
+README file must be included, with this copyright and no-warranty notice
+unaltered; and any additions, deletions, or changes to the original files
+must be clearly indicated in accompanying documentation.
+(2) If only executable code is distributed, then the accompanying
+documentation must state that "this software is based in part on the work of
+the Independent JPEG Group".
+(3) Permission for use of this software is granted only if the user accepts
+full responsibility for any undesirable consequences; the authors accept
+NO LIABILITY for damages of any kind.
+
+These conditions apply to any software derived from or based on the IJG code,
+not just to the unmodified library.  If you use our work, you ought to
+acknowledge us.
+
+Permission is NOT granted for the use of any IJG author's name or company name
+in advertising or publicity relating to this software or products derived from
+it.  This software may be referred to only as "the Independent JPEG Group's
+software".
+
+We specifically permit and encourage the use of this software as the basis of
+commercial products, provided that all warranty or liability claims are
+assumed by the product vendor.
+
+
+The Unix configuration script "configure" was produced with GNU Autoconf.
+It is copyright by the Free Software Foundation but is freely distributable.
+The same holds for its supporting scripts (config.guess, config.sub,
+ltmain.sh).  Another support script, install-sh, is copyright by X Consortium
+but is also freely distributable.
+
+The IJG distribution formerly included code to read and write GIF files.
+To avoid entanglement with the Unisys LZW patent, GIF reading support has
+been removed altogether, and the GIF writer has been simplified to produce
+"uncompressed GIFs".  This technique does not use the LZW algorithm; the
+resulting GIF files are larger than usual, but are readable by all standard
+GIF decoders.
+
+We are required to state that
+    "The Graphics Interchange Format(c) is the Copyright property of
+    CompuServe Incorporated.  GIF(sm) is a Service Mark property of
+    CompuServe Incorporated."
+
+------------------------------------------------------------------------------
+
+Files: contrib/gdk-pixbuf/*
+
+Copyright 2020 Emmanuel Gil Peyrot. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+this list of conditions and the following disclaimer in the documentation
+and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+------------------------------------------------------------------------------
+
+Files: android_jni/gradlew*
+
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
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+   Copyright [yyyy] [name of copyright owner]
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+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
+
+------------------------------------------------------------------------------
+
+Files: third_party/libyuv/*
+
+Copyright 2011 The LibYuv Project Authors. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+  * Redistributions of source code must retain the above copyright
+    notice, this list of conditions and the following disclaimer.
+
+  * Redistributions in binary form must reproduce the above copyright
+    notice, this list of conditions and the following disclaimer in
+    the documentation and/or other materials provided with the
+    distribution.
+
+  * Neither the name of Google nor the names of its contributors may
+    be used to endorse or promote products derived from this software
+    without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+----
+
+LIBJPEG
+
+1. We don't promise that this software works.  (But if you find any bugs,
+   please let us know!)
+2. You can use this software for whatever you want.  You don't have to pay us.
+3. You may not pretend that you wrote this software.  If you use it in a
+   program, you must acknowledge somewhere in your documentation that
+   you've used the IJG code.
+
+In legalese:
+
+The authors make NO WARRANTY or representation, either express or implied,
+with respect to this software, its quality, accuracy, merchantability, or
+fitness for a particular purpose.  This software is provided "AS IS", and you,
+its user, assume the entire risk as to its quality and accuracy.
+
+This software is copyright (C) 1991-2020, Thomas G. Lane, Guido Vollbeding.
+All Rights Reserved except as specified below.
+
+Permission is hereby granted to use, copy, modify, and distribute this
+software (or portions thereof) for any purpose, without fee, subject to these
+conditions:
+(1) If any part of the source code for this software is distributed, then this
+README file must be included, with this copyright and no-warranty notice
+unaltered; and any additions, deletions, or changes to the original files
+must be clearly indicated in accompanying documentation.
+(2) If only executable code is distributed, then the accompanying
+documentation must state that "this software is based in part on the work of
+the Independent JPEG Group".
+(3) Permission for use of this software is granted only if the user accepts
+full responsibility for any undesirable consequences; the authors accept
+NO LIABILITY for damages of any kind.
+
+These conditions apply to any software derived from or based on the IJG code,
+not just to the unmodified library.  If you use our work, you ought to
+acknowledge us.
+
+Permission is NOT granted for the use of any IJG author's name or company name
+in advertising or publicity relating to this software or products derived from
+it.  This software may be referred to only as "the Independent JPEG Group's
+software".
+
+We specifically permit and encourage the use of this software as the basis of
+commercial products, provided that all warranty or liability claims are
+assumed by the product vendor.
+
+
+----
+
+LIBLZMA
+
+XZ Utils Licensing
+==================
+
+    Different licenses apply to different files in this package. Here
+    is a rough summary of which licenses apply to which parts of this
+    package (but check the individual files to be sure!):
+
+      - liblzma is in the public domain.
+
+      - xz, xzdec, and lzmadec command line tools are in the public
+        domain unless GNU getopt_long had to be compiled and linked
+        in from the lib directory. The getopt_long code is under
+        GNU LGPLv2.1+.
+
+      - The scripts to grep, diff, and view compressed files have been
+        adapted from gzip. These scripts and their documentation are
+        under GNU GPLv2+.
+
+      - All the documentation in the doc directory and most of the
+        XZ Utils specific documentation files in other directories
+        are in the public domain.
+
+      - Translated messages are in the public domain.
+
+      - The build system contains public domain files, and files that
+        are under GNU GPLv2+ or GNU GPLv3+. None of these files end up
+        in the binaries being built.
+
+      - Test files and test code in the tests directory, and debugging
+        utilities in the debug directory are in the public domain.
+
+      - The extra directory may contain public domain files, and files
+        that are under various free software licenses.
+
+    You can do whatever you want with the files that have been put into
+    the public domain. If you find public domain legally problematic,
+    take the previous sentence as a license grant. If you still find
+    the lack of copyright legally problematic, you have too many
+    lawyers.
+
+    As usual, this software is provided "as is", without any warranty.
+
+    If you copy significant amounts of public domain code from XZ Utils
+    into your project, acknowledging this somewhere in your software is
+    polite (especially if it is proprietary, non-free software), but
+    naturally it is not legally required. Here is an example of a good
+    notice to put into "about box" or into documentation:
+
+        This software includes code from XZ Utils .
+
+    The following license texts are included in the following files:
+      - COPYING.LGPLv2.1: GNU Lesser General Public License version 2.1
+      - COPYING.GPLv2: GNU General Public License version 2
+      - COPYING.GPLv3: GNU General Public License version 3
+
+    Note that the toolchain (compiler, linker etc.) may add some code
+    pieces that are copyrighted. Thus, it is possible that e.g. liblzma
+    binary wouldn't actually be in the public domain in its entirety
+    even though it contains no copyrighted code from the XZ Utils source
+    package.
+
+    If you have questions, don't hesitate to ask the author(s) for more
+    information.
+
+
+----
+
+LIBPNG
+
+COPYRIGHT NOTICE, DISCLAIMER, and LICENSE
+=========================================
+
+PNG Reference Library License version 2
+---------------------------------------
+
+ * Copyright (c) 1995-2022 The PNG Reference Library Authors.
+ * Copyright (c) 2018-2022 Cosmin Truta.
+ * Copyright (c) 2000-2002, 2004, 2006-2018 Glenn Randers-Pehrson.
+ * Copyright (c) 1996-1997 Andreas Dilger.
+ * Copyright (c) 1995-1996 Guy Eric Schalnat, Group 42, Inc.
+
+The software is supplied "as is", without warranty of any kind,
+express or implied, including, without limitation, the warranties
+of merchantability, fitness for a particular purpose, title, and
+non-infringement.  In no event shall the Copyright owners, or
+anyone distributing the software, be liable for any damages or
+other liability, whether in contract, tort or otherwise, arising
+from, out of, or in connection with the software, or the use or
+other dealings in the software, even if advised of the possibility
+of such damage.
+
+Permission is hereby granted to use, copy, modify, and distribute
+this software, or portions hereof, for any purpose, without fee,
+subject to the following restrictions:
+
+ 1. The origin of this software must not be misrepresented; you
+    must not claim that you wrote the original software.  If you
+    use this software in a product, an acknowledgment in the product
+    documentation would be appreciated, but is not required.
+
+ 2. Altered source versions must be plainly marked as such, and must
+    not be misrepresented as being the original software.
+
+ 3. This Copyright notice may not be removed or altered from any
+    source or altered source distribution.
+
+
+PNG Reference Library License version 1 (for libpng 0.5 through 1.6.35)
+-----------------------------------------------------------------------
+
+libpng versions 1.0.7, July 1, 2000, through 1.6.35, July 15, 2018 are
+Copyright (c) 2000-2002, 2004, 2006-2018 Glenn Randers-Pehrson, are
+derived from libpng-1.0.6, and are distributed according to the same
+disclaimer and license as libpng-1.0.6 with the following individuals
+added to the list of Contributing Authors:
+
+    Simon-Pierre Cadieux
+    Eric S. Raymond
+    Mans Rullgard
+    Cosmin Truta
+    Gilles Vollant
+    James Yu
+    Mandar Sahastrabuddhe
+    Google Inc.
+    Vadim Barkov
+
+and with the following additions to the disclaimer:
+
+    There is no warranty against interference with your enjoyment of
+    the library or against infringement.  There is no warranty that our
+    efforts or the library will fulfill any of your particular purposes
+    or needs.  This library is provided with all faults, and the entire
+    risk of satisfactory quality, performance, accuracy, and effort is
+    with the user.
+
+Some files in the "contrib" directory and some configure-generated
+files that are distributed with libpng have other copyright owners, and
+are released under other open source licenses.
+
+libpng versions 0.97, January 1998, through 1.0.6, March 20, 2000, are
+Copyright (c) 1998-2000 Glenn Randers-Pehrson, are derived from
+libpng-0.96, and are distributed according to the same disclaimer and
+license as libpng-0.96, with the following individuals added to the
+list of Contributing Authors:
+
+    Tom Lane
+    Glenn Randers-Pehrson
+    Willem van Schaik
+
+libpng versions 0.89, June 1996, through 0.96, May 1997, are
+Copyright (c) 1996-1997 Andreas Dilger, are derived from libpng-0.88,
+and are distributed according to the same disclaimer and license as
+libpng-0.88, with the following individuals added to the list of
+Contributing Authors:
+
+    John Bowler
+    Kevin Bracey
+    Sam Bushell
+    Magnus Holmgren
+    Greg Roelofs
+    Tom Tanner
+
+Some files in the "scripts" directory have other copyright owners,
+but are released under this license.
+
+libpng versions 0.5, May 1995, through 0.88, January 1996, are
+Copyright (c) 1995-1996 Guy Eric Schalnat, Group 42, Inc.
+
+For the purposes of this copyright and license, "Contributing Authors"
+is defined as the following set of individuals:
+
+    Andreas Dilger
+    Dave Martindale
+    Guy Eric Schalnat
+    Paul Schmidt
+    Tim Wegner
+
+The PNG Reference Library is supplied "AS IS".  The Contributing
+Authors and Group 42, Inc. disclaim all warranties, expressed or
+implied, including, without limitation, the warranties of
+merchantability and of fitness for any purpose.  The Contributing
+Authors and Group 42, Inc. assume no liability for direct, indirect,
+incidental, special, exemplary, or consequential damages, which may
+result from the use of the PNG Reference Library, even if advised of
+the possibility of such damage.
+
+Permission is hereby granted to use, copy, modify, and distribute this
+source code, or portions hereof, for any purpose, without fee, subject
+to the following restrictions:
+
+ 1. The origin of this source code must not be misrepresented.
+
+ 2. Altered versions must be plainly marked as such and must not
+    be misrepresented as being the original source.
+
+ 3. This Copyright notice may not be removed or altered from any
+    source or altered source distribution.
+
+The Contributing Authors and Group 42, Inc. specifically permit,
+without fee, and encourage the use of this source code as a component
+to supporting the PNG file format in commercial products.  If you use
+this source code in a product, acknowledgment is not required but would
+be appreciated.
+
+
+----
+
+LIBTIFF
+
+Copyright (c) 1988-1997 Sam Leffler
+Copyright (c) 1991-1997 Silicon Graphics, Inc.
+
+Permission to use, copy, modify, distribute, and sell this software and
+its documentation for any purpose is hereby granted without fee, provided
+that (i) the above copyright notices and this permission notice appear in
+all copies of the software and related documentation, and (ii) the names of
+Sam Leffler and Silicon Graphics may not be used in any advertising or
+publicity relating to the software without the specific, prior written
+permission of Sam Leffler and Silicon Graphics.
+
+THE SOFTWARE IS PROVIDED "AS-IS" AND WITHOUT WARRANTY OF ANY KIND,
+EXPRESS, IMPLIED OR OTHERWISE, INCLUDING WITHOUT LIMITATION, ANY
+WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
+
+IN NO EVENT SHALL SAM LEFFLER OR SILICON GRAPHICS BE LIABLE FOR
+ANY SPECIAL, INCIDENTAL, INDIRECT OR CONSEQUENTIAL DAMAGES OF ANY KIND,
+OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+WHETHER OR NOT ADVISED OF THE POSSIBILITY OF DAMAGE, AND ON ANY THEORY OF
+LIABILITY, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+OF THIS SOFTWARE.
+
+
+----
+
+LIBWEBP
+
+Copyright (c) 2010, Google Inc. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+  * Redistributions of source code must retain the above copyright
+    notice, this list of conditions and the following disclaimer.
+
+  * Redistributions in binary form must reproduce the above copyright
+    notice, this list of conditions and the following disclaimer in
+    the documentation and/or other materials provided with the
+    distribution.
+
+  * Neither the name of Google nor the names of its contributors may
+    be used to endorse or promote products derived from this software
+    without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+----
+
+LIBYUV
+
+Copyright 2011 The LibYuv Project Authors. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+  * Redistributions of source code must retain the above copyright
+    notice, this list of conditions and the following disclaimer.
+
+  * Redistributions in binary form must reproduce the above copyright
+    notice, this list of conditions and the following disclaimer in
+    the documentation and/or other materials provided with the
+    distribution.
+
+  * Neither the name of Google nor the names of its contributors may
+    be used to endorse or promote products derived from this software
+    without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+----
+
+OPENJPEG
+
+*
+ * The copyright in this software is being made available under the 2-clauses
+ * BSD License, included below. This software may be subject to other third
+ * party and contributor rights, including patent rights, and no such rights
+ * are granted under this license.
+ *
+ * Copyright (c) 2002-2014, Universite catholique de Louvain (UCL), Belgium
+ * Copyright (c) 2002-2014, Professor Benoit Macq
+ * Copyright (c) 2003-2014, Antonin Descampe
+ * Copyright (c) 2003-2009, Francois-Olivier Devaux
+ * Copyright (c) 2005, Herve Drolon, FreeImage Team
+ * Copyright (c) 2002-2003, Yannick Verschueren
+ * Copyright (c) 2001-2003, David Janssens
+ * Copyright (c) 2011-2012, Centre National d'Etudes Spatiales (CNES), France
+ * Copyright (c) 2012, CS Systemes d'Information, France
+ *
+ * All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions
+ * are met:
+ * 1. Redistributions of source code must retain the above copyright
+ *    notice, this list of conditions and the following disclaimer.
+ * 2. Redistributions in binary form must reproduce the above copyright
+ *    notice, this list of conditions and the following disclaimer in the
+ *    documentation and/or other materials provided with the distribution.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS `AS IS'
+ * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ * ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+ * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+ * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+ * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+ * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ * POSSIBILITY OF SUCH DAMAGE.
+ */
+
+
+----
+
+RAQM
+
+The MIT License (MIT)
+
+Copyright © 2015 Information Technology Authority (ITA) 
+Copyright © 2016 Khaled Hosny 
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
+
+----
+
+XAU
+
+Copyright 1988, 1993, 1994, 1998  The Open Group
+
+Permission to use, copy, modify, distribute, and sell this software and its
+documentation for any purpose is hereby granted without fee, provided that
+the above copyright notice appear in all copies and that both that
+copyright notice and this permission notice appear in supporting
+documentation.
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+OPEN GROUP BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN
+AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+Except as contained in this notice, the name of The Open Group shall not be
+used in advertising or otherwise to promote the sale, use or other dealings
+in this Software without prior written authorization from The Open Group.
+
+
+----
+
+XCB
+
+Copyright (C) 2001-2006 Bart Massey, Jamey Sharp, and Josh Triplett.
+All Rights Reserved.
+
+Permission is hereby granted, free of charge, to any person
+obtaining a copy of this software and associated
+documentation files (the "Software"), to deal in the
+Software without restriction, including without limitation
+the rights to use, copy, modify, merge, publish, distribute,
+sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
+
+The above copyright notice and this permission notice shall
+be included in all copies or substantial portions of the
+Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY
+KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
+WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
+PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS
+BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+OTHER DEALINGS IN THE SOFTWARE.
+
+Except as contained in this notice, the names of the authors
+or their institutions shall not be used in advertising or
+otherwise to promote the sale, use or other dealings in this
+Software without prior written authorization from the
+authors.
+
+
+----
+
+XDMCP
+
+Copyright 1989, 1998  The Open Group
+
+Permission to use, copy, modify, distribute, and sell this software and its
+documentation for any purpose is hereby granted without fee, provided that
+the above copyright notice appear in all copies and that both that
+copyright notice and this permission notice appear in supporting
+documentation.
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+OPEN GROUP BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN
+AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+Except as contained in this notice, the name of The Open Group shall not be
+used in advertising or otherwise to promote the sale, use or other dealings
+in this Software without prior written authorization from The Open Group.
+
+Author:  Keith Packard, MIT X Consortium
+
+
+----
+
+ZLIB
+
+ (C) 1995-2017 Jean-loup Gailly and Mark Adler
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the authors be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  Jean-loup Gailly        Mark Adler
+  jloup@gzip.org          madler@alumni.caltech.edu
+
+If you use the zlib library in a product, we would appreciate *not* receiving
+lengthy legal documents to sign.  The sources are provided for free but without
+warranty of any kind.  The library has been entirely written by Jean-loup
+Gailly and Mark Adler; it does not include third-party code.
+
+If you redistribute modified sources, we would appreciate that you include in
+the file ChangeLog history information documenting your changes.  Please read
+the FAQ for more information on the distribution of modified source versions.
+
+
+----
+
+ZSTD
+
+BSD License
+
+For Zstandard software
+
+Copyright (c) Meta Platforms, Inc. and affiliates. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without modification,
+are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+ * Neither the name Facebook, nor Meta, nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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+Copyright (c) 2008-present The pip developers (see AUTHORS.txt file)
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be
+included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
+LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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+Name: pip
+Version: 23.0.1
+Summary: The PyPA recommended tool for installing Python packages.
+Home-page: https://pip.pypa.io/
+Author: The pip developers
+Author-email: distutils-sig@python.org
+License: MIT
+Project-URL: Documentation, https://pip.pypa.io
+Project-URL: Source, https://github.com/pypa/pip
+Project-URL: Changelog, https://pip.pypa.io/en/stable/news/
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Topic :: Software Development :: Build Tools
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
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+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Requires-Python: >=3.7
+License-File: LICENSE.txt
+
+pip - The Python Package Installer
+==================================
+
+.. image:: https://img.shields.io/pypi/v/pip.svg
+   :target: https://pypi.org/project/pip/
+
+.. image:: https://readthedocs.org/projects/pip/badge/?version=latest
+   :target: https://pip.pypa.io/en/latest
+
+pip is the `package installer`_ for Python. You can use pip to install packages from the `Python Package Index`_ and other indexes.
+
+Please take a look at our documentation for how to install and use pip:
+
+* `Installation`_
+* `Usage`_
+
+We release updates regularly, with a new version every 3 months. Find more details in our documentation:
+
+* `Release notes`_
+* `Release process`_
+
+In pip 20.3, we've `made a big improvement to the heart of pip`_; `learn more`_. We want your input, so `sign up for our user experience research studies`_ to help us do it right.
+
+**Note**: pip 21.0, in January 2021, removed Python 2 support, per pip's `Python 2 support policy`_. Please migrate to Python 3.
+
+If you find bugs, need help, or want to talk to the developers, please use our mailing lists or chat rooms:
+
+* `Issue tracking`_
+* `Discourse channel`_
+* `User IRC`_
+
+If you want to get involved head over to GitHub to get the source code, look at our development documentation and feel free to jump on the developer mailing lists and chat rooms:
+
+* `GitHub page`_
+* `Development documentation`_
+* `Development IRC`_
+
+Code of Conduct
+---------------
+
+Everyone interacting in the pip project's codebases, issue trackers, chat
+rooms, and mailing lists is expected to follow the `PSF Code of Conduct`_.
+
+.. _package installer: https://packaging.python.org/guides/tool-recommendations/
+.. _Python Package Index: https://pypi.org
+.. _Installation: https://pip.pypa.io/en/stable/installation/
+.. _Usage: https://pip.pypa.io/en/stable/
+.. _Release notes: https://pip.pypa.io/en/stable/news.html
+.. _Release process: https://pip.pypa.io/en/latest/development/release-process/
+.. _GitHub page: https://github.com/pypa/pip
+.. _Development documentation: https://pip.pypa.io/en/latest/development
+.. _made a big improvement to the heart of pip: https://pyfound.blogspot.com/2020/11/pip-20-3-new-resolver.html
+.. _learn more: https://pip.pypa.io/en/latest/user_guide/#changes-to-the-pip-dependency-resolver-in-20-3-2020
+.. _sign up for our user experience research studies: https://pyfound.blogspot.com/2020/03/new-pip-resolver-to-roll-out-this-year.html
+.. _Python 2 support policy: https://pip.pypa.io/en/latest/development/release-process/#python-2-support
+.. _Issue tracking: https://github.com/pypa/pip/issues
+.. _Discourse channel: https://discuss.python.org/c/packaging
+.. _User IRC: https://kiwiirc.com/nextclient/#ircs://irc.libera.chat:+6697/pypa
+.. _Development IRC: https://kiwiirc.com/nextclient/#ircs://irc.libera.chat:+6697/pypa-dev
+.. _PSF Code of Conduct: https://github.com/pypa/.github/blob/main/CODE_OF_CONDUCT.md
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diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/REQUESTED b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/REQUESTED
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/WHEEL b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/WHEEL
new file mode 100644
index 0000000000000000000000000000000000000000..57e3d840d59a650ac5bccbad5baeec47d155f0ad
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/WHEEL
@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.38.4)
+Root-Is-Purelib: true
+Tag: py3-none-any
+
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/entry_points.txt b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/entry_points.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ab909c9b34e885f9cdf17705e34d07242e514c94
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/entry_points.txt
@@ -0,0 +1,4 @@
+[console_scripts]
+pip = pip._internal.cli.main:main
+pip3 = pip._internal.cli.main:main
+pip3.9 = pip._internal.cli.main:main
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/top_level.txt b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip-23.0.1.dist-info/top_level.txt
@@ -0,0 +1 @@
+pip
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..42f6c455c6eac114945bcda6912d8d5ae41017d6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__init__.py
@@ -0,0 +1,13 @@
+from typing import List, Optional
+
+__version__ = "23.0.1"
+
+
+def main(args: Optional[List[str]] = None) -> int:
+    """This is an internal API only meant for use by pip's own console scripts.
+
+    For additional details, see https://github.com/pypa/pip/issues/7498.
+    """
+    from pip._internal.utils.entrypoints import _wrapper
+
+    return _wrapper(args)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__main__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe34a7b7772cef55f5b5cb3455a2850489620ca7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__main__.py
@@ -0,0 +1,31 @@
+import os
+import sys
+import warnings
+
+# Remove '' and current working directory from the first entry
+# of sys.path, if present to avoid using current directory
+# in pip commands check, freeze, install, list and show,
+# when invoked as python -m pip 
+if sys.path[0] in ("", os.getcwd()):
+    sys.path.pop(0)
+
+# If we are running from a wheel, add the wheel to sys.path
+# This allows the usage python pip-*.whl/pip install pip-*.whl
+if __package__ == "":
+    # __file__ is pip-*.whl/pip/__main__.py
+    # first dirname call strips of '/__main__.py', second strips off '/pip'
+    # Resulting path is the name of the wheel itself
+    # Add that to sys.path so we can import pip
+    path = os.path.dirname(os.path.dirname(__file__))
+    sys.path.insert(0, path)
+
+if __name__ == "__main__":
+    # Work around the error reported in #9540, pending a proper fix.
+    # Note: It is essential the warning filter is set *before* importing
+    #       pip, as the deprecation happens at import time, not runtime.
+    warnings.filterwarnings(
+        "ignore", category=DeprecationWarning, module=".*packaging\\.version"
+    )
+    from pip._internal.cli.main import main as _main
+
+    sys.exit(_main())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__pip-runner__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__pip-runner__.py
new file mode 100644
index 0000000000000000000000000000000000000000..49a148a097e9cc06c165571e0bffaf7cae17dc5b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/__pip-runner__.py
@@ -0,0 +1,50 @@
+"""Execute exactly this copy of pip, within a different environment.
+
+This file is named as it is, to ensure that this module can't be imported via
+an import statement.
+"""
+
+# /!\ This version compatibility check section must be Python 2 compatible. /!\
+
+import sys
+
+# Copied from setup.py
+PYTHON_REQUIRES = (3, 7)
+
+
+def version_str(version):  # type: ignore
+    return ".".join(str(v) for v in version)
+
+
+if sys.version_info[:2] < PYTHON_REQUIRES:
+    raise SystemExit(
+        "This version of pip does not support python {} (requires >={}).".format(
+            version_str(sys.version_info[:2]), version_str(PYTHON_REQUIRES)
+        )
+    )
+
+# From here on, we can use Python 3 features, but the syntax must remain
+# Python 2 compatible.
+
+import runpy  # noqa: E402
+from importlib.machinery import PathFinder  # noqa: E402
+from os.path import dirname  # noqa: E402
+
+PIP_SOURCES_ROOT = dirname(dirname(__file__))
+
+
+class PipImportRedirectingFinder:
+    @classmethod
+    def find_spec(self, fullname, path=None, target=None):  # type: ignore
+        if fullname != "pip":
+            return None
+
+        spec = PathFinder.find_spec(fullname, [PIP_SOURCES_ROOT], target)
+        assert spec, (PIP_SOURCES_ROOT, fullname)
+        return spec
+
+
+sys.meta_path.insert(0, PipImportRedirectingFinder())
+
+assert __name__ == "__main__", "Cannot run __pip-runner__.py as a non-main module"
+runpy.run_module("pip", run_name="__main__", alter_sys=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..6afb5c627ce3db6e61cbf46276f7ddd42552eb28
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/__init__.py
@@ -0,0 +1,19 @@
+from typing import List, Optional
+
+import pip._internal.utils.inject_securetransport  # noqa
+from pip._internal.utils import _log
+
+# init_logging() must be called before any call to logging.getLogger()
+# which happens at import of most modules.
+_log.init_logging()
+
+
+def main(args: (Optional[List[str]]) = None) -> int:
+    """This is preserved for old console scripts that may still be referencing
+    it.
+
+    For additional details, see https://github.com/pypa/pip/issues/7498.
+    """
+    from pip._internal.utils.entrypoints import _wrapper
+
+    return _wrapper(args)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/build_env.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/build_env.py
new file mode 100644
index 0000000000000000000000000000000000000000..4f704a3547da02f913d6cfdbd4e0ed77c81caabe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/build_env.py
@@ -0,0 +1,311 @@
+"""Build Environment used for isolation during sdist building
+"""
+
+import logging
+import os
+import pathlib
+import site
+import sys
+import textwrap
+from collections import OrderedDict
+from types import TracebackType
+from typing import TYPE_CHECKING, Iterable, List, Optional, Set, Tuple, Type, Union
+
+from pip._vendor.certifi import where
+from pip._vendor.packaging.requirements import Requirement
+from pip._vendor.packaging.version import Version
+
+from pip import __file__ as pip_location
+from pip._internal.cli.spinners import open_spinner
+from pip._internal.locations import get_platlib, get_purelib, get_scheme
+from pip._internal.metadata import get_default_environment, get_environment
+from pip._internal.utils.subprocess import call_subprocess
+from pip._internal.utils.temp_dir import TempDirectory, tempdir_kinds
+
+if TYPE_CHECKING:
+    from pip._internal.index.package_finder import PackageFinder
+
+logger = logging.getLogger(__name__)
+
+
+def _dedup(a: str, b: str) -> Union[Tuple[str], Tuple[str, str]]:
+    return (a, b) if a != b else (a,)
+
+
+class _Prefix:
+    def __init__(self, path: str) -> None:
+        self.path = path
+        self.setup = False
+        scheme = get_scheme("", prefix=path)
+        self.bin_dir = scheme.scripts
+        self.lib_dirs = _dedup(scheme.purelib, scheme.platlib)
+
+
+def get_runnable_pip() -> str:
+    """Get a file to pass to a Python executable, to run the currently-running pip.
+
+    This is used to run a pip subprocess, for installing requirements into the build
+    environment.
+    """
+    source = pathlib.Path(pip_location).resolve().parent
+
+    if not source.is_dir():
+        # This would happen if someone is using pip from inside a zip file. In that
+        # case, we can use that directly.
+        return str(source)
+
+    return os.fsdecode(source / "__pip-runner__.py")
+
+
+def _get_system_sitepackages() -> Set[str]:
+    """Get system site packages
+
+    Usually from site.getsitepackages,
+    but fallback on `get_purelib()/get_platlib()` if unavailable
+    (e.g. in a virtualenv created by virtualenv<20)
+
+    Returns normalized set of strings.
+    """
+    if hasattr(site, "getsitepackages"):
+        system_sites = site.getsitepackages()
+    else:
+        # virtualenv < 20 overwrites site.py without getsitepackages
+        # fallback on get_purelib/get_platlib.
+        # this is known to miss things, but shouldn't in the cases
+        # where getsitepackages() has been removed (inside a virtualenv)
+        system_sites = [get_purelib(), get_platlib()]
+    return {os.path.normcase(path) for path in system_sites}
+
+
+class BuildEnvironment:
+    """Creates and manages an isolated environment to install build deps"""
+
+    def __init__(self) -> None:
+        temp_dir = TempDirectory(kind=tempdir_kinds.BUILD_ENV, globally_managed=True)
+
+        self._prefixes = OrderedDict(
+            (name, _Prefix(os.path.join(temp_dir.path, name)))
+            for name in ("normal", "overlay")
+        )
+
+        self._bin_dirs: List[str] = []
+        self._lib_dirs: List[str] = []
+        for prefix in reversed(list(self._prefixes.values())):
+            self._bin_dirs.append(prefix.bin_dir)
+            self._lib_dirs.extend(prefix.lib_dirs)
+
+        # Customize site to:
+        # - ensure .pth files are honored
+        # - prevent access to system site packages
+        system_sites = _get_system_sitepackages()
+
+        self._site_dir = os.path.join(temp_dir.path, "site")
+        if not os.path.exists(self._site_dir):
+            os.mkdir(self._site_dir)
+        with open(
+            os.path.join(self._site_dir, "sitecustomize.py"), "w", encoding="utf-8"
+        ) as fp:
+            fp.write(
+                textwrap.dedent(
+                    """
+                import os, site, sys
+
+                # First, drop system-sites related paths.
+                original_sys_path = sys.path[:]
+                known_paths = set()
+                for path in {system_sites!r}:
+                    site.addsitedir(path, known_paths=known_paths)
+                system_paths = set(
+                    os.path.normcase(path)
+                    for path in sys.path[len(original_sys_path):]
+                )
+                original_sys_path = [
+                    path for path in original_sys_path
+                    if os.path.normcase(path) not in system_paths
+                ]
+                sys.path = original_sys_path
+
+                # Second, add lib directories.
+                # ensuring .pth file are processed.
+                for path in {lib_dirs!r}:
+                    assert not path in sys.path
+                    site.addsitedir(path)
+                """
+                ).format(system_sites=system_sites, lib_dirs=self._lib_dirs)
+            )
+
+    def __enter__(self) -> None:
+        self._save_env = {
+            name: os.environ.get(name, None)
+            for name in ("PATH", "PYTHONNOUSERSITE", "PYTHONPATH")
+        }
+
+        path = self._bin_dirs[:]
+        old_path = self._save_env["PATH"]
+        if old_path:
+            path.extend(old_path.split(os.pathsep))
+
+        pythonpath = [self._site_dir]
+
+        os.environ.update(
+            {
+                "PATH": os.pathsep.join(path),
+                "PYTHONNOUSERSITE": "1",
+                "PYTHONPATH": os.pathsep.join(pythonpath),
+            }
+        )
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> None:
+        for varname, old_value in self._save_env.items():
+            if old_value is None:
+                os.environ.pop(varname, None)
+            else:
+                os.environ[varname] = old_value
+
+    def check_requirements(
+        self, reqs: Iterable[str]
+    ) -> Tuple[Set[Tuple[str, str]], Set[str]]:
+        """Return 2 sets:
+        - conflicting requirements: set of (installed, wanted) reqs tuples
+        - missing requirements: set of reqs
+        """
+        missing = set()
+        conflicting = set()
+        if reqs:
+            env = (
+                get_environment(self._lib_dirs)
+                if hasattr(self, "_lib_dirs")
+                else get_default_environment()
+            )
+            for req_str in reqs:
+                req = Requirement(req_str)
+                # We're explicitly evaluating with an empty extra value, since build
+                # environments are not provided any mechanism to select specific extras.
+                if req.marker is not None and not req.marker.evaluate({"extra": ""}):
+                    continue
+                dist = env.get_distribution(req.name)
+                if not dist:
+                    missing.add(req_str)
+                    continue
+                if isinstance(dist.version, Version):
+                    installed_req_str = f"{req.name}=={dist.version}"
+                else:
+                    installed_req_str = f"{req.name}==={dist.version}"
+                if not req.specifier.contains(dist.version, prereleases=True):
+                    conflicting.add((installed_req_str, req_str))
+                # FIXME: Consider direct URL?
+        return conflicting, missing
+
+    def install_requirements(
+        self,
+        finder: "PackageFinder",
+        requirements: Iterable[str],
+        prefix_as_string: str,
+        *,
+        kind: str,
+    ) -> None:
+        prefix = self._prefixes[prefix_as_string]
+        assert not prefix.setup
+        prefix.setup = True
+        if not requirements:
+            return
+        self._install_requirements(
+            get_runnable_pip(),
+            finder,
+            requirements,
+            prefix,
+            kind=kind,
+        )
+
+    @staticmethod
+    def _install_requirements(
+        pip_runnable: str,
+        finder: "PackageFinder",
+        requirements: Iterable[str],
+        prefix: _Prefix,
+        *,
+        kind: str,
+    ) -> None:
+        args: List[str] = [
+            sys.executable,
+            pip_runnable,
+            "install",
+            "--ignore-installed",
+            "--no-user",
+            "--prefix",
+            prefix.path,
+            "--no-warn-script-location",
+        ]
+        if logger.getEffectiveLevel() <= logging.DEBUG:
+            args.append("-v")
+        for format_control in ("no_binary", "only_binary"):
+            formats = getattr(finder.format_control, format_control)
+            args.extend(
+                (
+                    "--" + format_control.replace("_", "-"),
+                    ",".join(sorted(formats or {":none:"})),
+                )
+            )
+
+        index_urls = finder.index_urls
+        if index_urls:
+            args.extend(["-i", index_urls[0]])
+            for extra_index in index_urls[1:]:
+                args.extend(["--extra-index-url", extra_index])
+        else:
+            args.append("--no-index")
+        for link in finder.find_links:
+            args.extend(["--find-links", link])
+
+        for host in finder.trusted_hosts:
+            args.extend(["--trusted-host", host])
+        if finder.allow_all_prereleases:
+            args.append("--pre")
+        if finder.prefer_binary:
+            args.append("--prefer-binary")
+        args.append("--")
+        args.extend(requirements)
+        extra_environ = {"_PIP_STANDALONE_CERT": where()}
+        with open_spinner(f"Installing {kind}") as spinner:
+            call_subprocess(
+                args,
+                command_desc=f"pip subprocess to install {kind}",
+                spinner=spinner,
+                extra_environ=extra_environ,
+            )
+
+
+class NoOpBuildEnvironment(BuildEnvironment):
+    """A no-op drop-in replacement for BuildEnvironment"""
+
+    def __init__(self) -> None:
+        pass
+
+    def __enter__(self) -> None:
+        pass
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> None:
+        pass
+
+    def cleanup(self) -> None:
+        pass
+
+    def install_requirements(
+        self,
+        finder: "PackageFinder",
+        requirements: Iterable[str],
+        prefix_as_string: str,
+        *,
+        kind: str,
+    ) -> None:
+        raise NotImplementedError()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cache.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..c53b7f023a1ec6d40fb4784c30acf7d4c411a8c3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cache.py
@@ -0,0 +1,293 @@
+"""Cache Management
+"""
+
+import hashlib
+import json
+import logging
+import os
+from pathlib import Path
+from typing import Any, Dict, List, Optional, Set
+
+from pip._vendor.packaging.tags import Tag, interpreter_name, interpreter_version
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.exceptions import InvalidWheelFilename
+from pip._internal.models.direct_url import DirectUrl
+from pip._internal.models.format_control import FormatControl
+from pip._internal.models.link import Link
+from pip._internal.models.wheel import Wheel
+from pip._internal.utils.temp_dir import TempDirectory, tempdir_kinds
+from pip._internal.utils.urls import path_to_url
+
+logger = logging.getLogger(__name__)
+
+ORIGIN_JSON_NAME = "origin.json"
+
+
+def _hash_dict(d: Dict[str, str]) -> str:
+    """Return a stable sha224 of a dictionary."""
+    s = json.dumps(d, sort_keys=True, separators=(",", ":"), ensure_ascii=True)
+    return hashlib.sha224(s.encode("ascii")).hexdigest()
+
+
+class Cache:
+    """An abstract class - provides cache directories for data from links
+
+
+    :param cache_dir: The root of the cache.
+    :param format_control: An object of FormatControl class to limit
+        binaries being read from the cache.
+    :param allowed_formats: which formats of files the cache should store.
+        ('binary' and 'source' are the only allowed values)
+    """
+
+    def __init__(
+        self, cache_dir: str, format_control: FormatControl, allowed_formats: Set[str]
+    ) -> None:
+        super().__init__()
+        assert not cache_dir or os.path.isabs(cache_dir)
+        self.cache_dir = cache_dir or None
+        self.format_control = format_control
+        self.allowed_formats = allowed_formats
+
+        _valid_formats = {"source", "binary"}
+        assert self.allowed_formats.union(_valid_formats) == _valid_formats
+
+    def _get_cache_path_parts(self, link: Link) -> List[str]:
+        """Get parts of part that must be os.path.joined with cache_dir"""
+
+        # We want to generate an url to use as our cache key, we don't want to
+        # just re-use the URL because it might have other items in the fragment
+        # and we don't care about those.
+        key_parts = {"url": link.url_without_fragment}
+        if link.hash_name is not None and link.hash is not None:
+            key_parts[link.hash_name] = link.hash
+        if link.subdirectory_fragment:
+            key_parts["subdirectory"] = link.subdirectory_fragment
+
+        # Include interpreter name, major and minor version in cache key
+        # to cope with ill-behaved sdists that build a different wheel
+        # depending on the python version their setup.py is being run on,
+        # and don't encode the difference in compatibility tags.
+        # https://github.com/pypa/pip/issues/7296
+        key_parts["interpreter_name"] = interpreter_name()
+        key_parts["interpreter_version"] = interpreter_version()
+
+        # Encode our key url with sha224, we'll use this because it has similar
+        # security properties to sha256, but with a shorter total output (and
+        # thus less secure). However the differences don't make a lot of
+        # difference for our use case here.
+        hashed = _hash_dict(key_parts)
+
+        # We want to nest the directories some to prevent having a ton of top
+        # level directories where we might run out of sub directories on some
+        # FS.
+        parts = [hashed[:2], hashed[2:4], hashed[4:6], hashed[6:]]
+
+        return parts
+
+    def _get_candidates(self, link: Link, canonical_package_name: str) -> List[Any]:
+        can_not_cache = not self.cache_dir or not canonical_package_name or not link
+        if can_not_cache:
+            return []
+
+        formats = self.format_control.get_allowed_formats(canonical_package_name)
+        if not self.allowed_formats.intersection(formats):
+            return []
+
+        candidates = []
+        path = self.get_path_for_link(link)
+        if os.path.isdir(path):
+            for candidate in os.listdir(path):
+                candidates.append((candidate, path))
+        return candidates
+
+    def get_path_for_link(self, link: Link) -> str:
+        """Return a directory to store cached items in for link."""
+        raise NotImplementedError()
+
+    def get(
+        self,
+        link: Link,
+        package_name: Optional[str],
+        supported_tags: List[Tag],
+    ) -> Link:
+        """Returns a link to a cached item if it exists, otherwise returns the
+        passed link.
+        """
+        raise NotImplementedError()
+
+
+class SimpleWheelCache(Cache):
+    """A cache of wheels for future installs."""
+
+    def __init__(self, cache_dir: str, format_control: FormatControl) -> None:
+        super().__init__(cache_dir, format_control, {"binary"})
+
+    def get_path_for_link(self, link: Link) -> str:
+        """Return a directory to store cached wheels for link
+
+        Because there are M wheels for any one sdist, we provide a directory
+        to cache them in, and then consult that directory when looking up
+        cache hits.
+
+        We only insert things into the cache if they have plausible version
+        numbers, so that we don't contaminate the cache with things that were
+        not unique. E.g. ./package might have dozens of installs done for it
+        and build a version of 0.0...and if we built and cached a wheel, we'd
+        end up using the same wheel even if the source has been edited.
+
+        :param link: The link of the sdist for which this will cache wheels.
+        """
+        parts = self._get_cache_path_parts(link)
+        assert self.cache_dir
+        # Store wheels within the root cache_dir
+        return os.path.join(self.cache_dir, "wheels", *parts)
+
+    def get(
+        self,
+        link: Link,
+        package_name: Optional[str],
+        supported_tags: List[Tag],
+    ) -> Link:
+        candidates = []
+
+        if not package_name:
+            return link
+
+        canonical_package_name = canonicalize_name(package_name)
+        for wheel_name, wheel_dir in self._get_candidates(link, canonical_package_name):
+            try:
+                wheel = Wheel(wheel_name)
+            except InvalidWheelFilename:
+                continue
+            if canonicalize_name(wheel.name) != canonical_package_name:
+                logger.debug(
+                    "Ignoring cached wheel %s for %s as it "
+                    "does not match the expected distribution name %s.",
+                    wheel_name,
+                    link,
+                    package_name,
+                )
+                continue
+            if not wheel.supported(supported_tags):
+                # Built for a different python/arch/etc
+                continue
+            candidates.append(
+                (
+                    wheel.support_index_min(supported_tags),
+                    wheel_name,
+                    wheel_dir,
+                )
+            )
+
+        if not candidates:
+            return link
+
+        _, wheel_name, wheel_dir = min(candidates)
+        return Link(path_to_url(os.path.join(wheel_dir, wheel_name)))
+
+
+class EphemWheelCache(SimpleWheelCache):
+    """A SimpleWheelCache that creates it's own temporary cache directory"""
+
+    def __init__(self, format_control: FormatControl) -> None:
+        self._temp_dir = TempDirectory(
+            kind=tempdir_kinds.EPHEM_WHEEL_CACHE,
+            globally_managed=True,
+        )
+
+        super().__init__(self._temp_dir.path, format_control)
+
+
+class CacheEntry:
+    def __init__(
+        self,
+        link: Link,
+        persistent: bool,
+    ):
+        self.link = link
+        self.persistent = persistent
+        self.origin: Optional[DirectUrl] = None
+        origin_direct_url_path = Path(self.link.file_path).parent / ORIGIN_JSON_NAME
+        if origin_direct_url_path.exists():
+            self.origin = DirectUrl.from_json(origin_direct_url_path.read_text())
+
+
+class WheelCache(Cache):
+    """Wraps EphemWheelCache and SimpleWheelCache into a single Cache
+
+    This Cache allows for gracefully degradation, using the ephem wheel cache
+    when a certain link is not found in the simple wheel cache first.
+    """
+
+    def __init__(
+        self, cache_dir: str, format_control: Optional[FormatControl] = None
+    ) -> None:
+        if format_control is None:
+            format_control = FormatControl()
+        super().__init__(cache_dir, format_control, {"binary"})
+        self._wheel_cache = SimpleWheelCache(cache_dir, format_control)
+        self._ephem_cache = EphemWheelCache(format_control)
+
+    def get_path_for_link(self, link: Link) -> str:
+        return self._wheel_cache.get_path_for_link(link)
+
+    def get_ephem_path_for_link(self, link: Link) -> str:
+        return self._ephem_cache.get_path_for_link(link)
+
+    def get(
+        self,
+        link: Link,
+        package_name: Optional[str],
+        supported_tags: List[Tag],
+    ) -> Link:
+        cache_entry = self.get_cache_entry(link, package_name, supported_tags)
+        if cache_entry is None:
+            return link
+        return cache_entry.link
+
+    def get_cache_entry(
+        self,
+        link: Link,
+        package_name: Optional[str],
+        supported_tags: List[Tag],
+    ) -> Optional[CacheEntry]:
+        """Returns a CacheEntry with a link to a cached item if it exists or
+        None. The cache entry indicates if the item was found in the persistent
+        or ephemeral cache.
+        """
+        retval = self._wheel_cache.get(
+            link=link,
+            package_name=package_name,
+            supported_tags=supported_tags,
+        )
+        if retval is not link:
+            return CacheEntry(retval, persistent=True)
+
+        retval = self._ephem_cache.get(
+            link=link,
+            package_name=package_name,
+            supported_tags=supported_tags,
+        )
+        if retval is not link:
+            return CacheEntry(retval, persistent=False)
+
+        return None
+
+    @staticmethod
+    def record_download_origin(cache_dir: str, download_info: DirectUrl) -> None:
+        origin_path = Path(cache_dir) / ORIGIN_JSON_NAME
+        if origin_path.is_file():
+            origin = DirectUrl.from_json(origin_path.read_text())
+            # TODO: use DirectUrl.equivalent when https://github.com/pypa/pip/pull/10564
+            # is merged.
+            if origin.url != download_info.url:
+                logger.warning(
+                    "Origin URL %s in cache entry %s does not match download URL %s. "
+                    "This is likely a pip bug or a cache corruption issue.",
+                    origin.url,
+                    cache_dir,
+                    download_info.url,
+                )
+        origin_path.write_text(download_info.to_json(), encoding="utf-8")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e589bb917e23823e25f9fff7e0849c4d6d4a62bc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/__init__.py
@@ -0,0 +1,4 @@
+"""Subpackage containing all of pip's command line interface related code
+"""
+
+# This file intentionally does not import submodules
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/autocompletion.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/autocompletion.py
new file mode 100644
index 0000000000000000000000000000000000000000..226fe84dc0d0c4eb78f9b3c603df20cef0fdfda4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/autocompletion.py
@@ -0,0 +1,171 @@
+"""Logic that powers autocompletion installed by ``pip completion``.
+"""
+
+import optparse
+import os
+import sys
+from itertools import chain
+from typing import Any, Iterable, List, Optional
+
+from pip._internal.cli.main_parser import create_main_parser
+from pip._internal.commands import commands_dict, create_command
+from pip._internal.metadata import get_default_environment
+
+
+def autocomplete() -> None:
+    """Entry Point for completion of main and subcommand options."""
+    # Don't complete if user hasn't sourced bash_completion file.
+    if "PIP_AUTO_COMPLETE" not in os.environ:
+        return
+    cwords = os.environ["COMP_WORDS"].split()[1:]
+    cword = int(os.environ["COMP_CWORD"])
+    try:
+        current = cwords[cword - 1]
+    except IndexError:
+        current = ""
+
+    parser = create_main_parser()
+    subcommands = list(commands_dict)
+    options = []
+
+    # subcommand
+    subcommand_name: Optional[str] = None
+    for word in cwords:
+        if word in subcommands:
+            subcommand_name = word
+            break
+    # subcommand options
+    if subcommand_name is not None:
+        # special case: 'help' subcommand has no options
+        if subcommand_name == "help":
+            sys.exit(1)
+        # special case: list locally installed dists for show and uninstall
+        should_list_installed = not current.startswith("-") and subcommand_name in [
+            "show",
+            "uninstall",
+        ]
+        if should_list_installed:
+            env = get_default_environment()
+            lc = current.lower()
+            installed = [
+                dist.canonical_name
+                for dist in env.iter_installed_distributions(local_only=True)
+                if dist.canonical_name.startswith(lc)
+                and dist.canonical_name not in cwords[1:]
+            ]
+            # if there are no dists installed, fall back to option completion
+            if installed:
+                for dist in installed:
+                    print(dist)
+                sys.exit(1)
+
+        should_list_installables = (
+            not current.startswith("-") and subcommand_name == "install"
+        )
+        if should_list_installables:
+            for path in auto_complete_paths(current, "path"):
+                print(path)
+            sys.exit(1)
+
+        subcommand = create_command(subcommand_name)
+
+        for opt in subcommand.parser.option_list_all:
+            if opt.help != optparse.SUPPRESS_HELP:
+                for opt_str in opt._long_opts + opt._short_opts:
+                    options.append((opt_str, opt.nargs))
+
+        # filter out previously specified options from available options
+        prev_opts = [x.split("=")[0] for x in cwords[1 : cword - 1]]
+        options = [(x, v) for (x, v) in options if x not in prev_opts]
+        # filter options by current input
+        options = [(k, v) for k, v in options if k.startswith(current)]
+        # get completion type given cwords and available subcommand options
+        completion_type = get_path_completion_type(
+            cwords,
+            cword,
+            subcommand.parser.option_list_all,
+        )
+        # get completion files and directories if ``completion_type`` is
+        # ````, ```` or ````
+        if completion_type:
+            paths = auto_complete_paths(current, completion_type)
+            options = [(path, 0) for path in paths]
+        for option in options:
+            opt_label = option[0]
+            # append '=' to options which require args
+            if option[1] and option[0][:2] == "--":
+                opt_label += "="
+            print(opt_label)
+    else:
+        # show main parser options only when necessary
+
+        opts = [i.option_list for i in parser.option_groups]
+        opts.append(parser.option_list)
+        flattened_opts = chain.from_iterable(opts)
+        if current.startswith("-"):
+            for opt in flattened_opts:
+                if opt.help != optparse.SUPPRESS_HELP:
+                    subcommands += opt._long_opts + opt._short_opts
+        else:
+            # get completion type given cwords and all available options
+            completion_type = get_path_completion_type(cwords, cword, flattened_opts)
+            if completion_type:
+                subcommands = list(auto_complete_paths(current, completion_type))
+
+        print(" ".join([x for x in subcommands if x.startswith(current)]))
+    sys.exit(1)
+
+
+def get_path_completion_type(
+    cwords: List[str], cword: int, opts: Iterable[Any]
+) -> Optional[str]:
+    """Get the type of path completion (``file``, ``dir``, ``path`` or None)
+
+    :param cwords: same as the environmental variable ``COMP_WORDS``
+    :param cword: same as the environmental variable ``COMP_CWORD``
+    :param opts: The available options to check
+    :return: path completion type (``file``, ``dir``, ``path`` or None)
+    """
+    if cword < 2 or not cwords[cword - 2].startswith("-"):
+        return None
+    for opt in opts:
+        if opt.help == optparse.SUPPRESS_HELP:
+            continue
+        for o in str(opt).split("/"):
+            if cwords[cword - 2].split("=")[0] == o:
+                if not opt.metavar or any(
+                    x in ("path", "file", "dir") for x in opt.metavar.split("/")
+                ):
+                    return opt.metavar
+    return None
+
+
+def auto_complete_paths(current: str, completion_type: str) -> Iterable[str]:
+    """If ``completion_type`` is ``file`` or ``path``, list all regular files
+    and directories starting with ``current``; otherwise only list directories
+    starting with ``current``.
+
+    :param current: The word to be completed
+    :param completion_type: path completion type(``file``, ``path`` or ``dir``)
+    :return: A generator of regular files and/or directories
+    """
+    directory, filename = os.path.split(current)
+    current_path = os.path.abspath(directory)
+    # Don't complete paths if they can't be accessed
+    if not os.access(current_path, os.R_OK):
+        return
+    filename = os.path.normcase(filename)
+    # list all files that start with ``filename``
+    file_list = (
+        x for x in os.listdir(current_path) if os.path.normcase(x).startswith(filename)
+    )
+    for f in file_list:
+        opt = os.path.join(current_path, f)
+        comp_file = os.path.normcase(os.path.join(directory, f))
+        # complete regular files when there is not ```` after option
+        # complete directories when there is ````, ```` or
+        # ````after option
+        if completion_type != "dir" and os.path.isfile(opt):
+            yield comp_file
+        elif os.path.isdir(opt):
+            yield os.path.join(comp_file, "")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/base_command.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/base_command.py
new file mode 100644
index 0000000000000000000000000000000000000000..5bd7e67e649d256292fb12b8be6dc9ff88c111ac
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/base_command.py
@@ -0,0 +1,216 @@
+"""Base Command class, and related routines"""
+
+import functools
+import logging
+import logging.config
+import optparse
+import os
+import sys
+import traceback
+from optparse import Values
+from typing import Any, Callable, List, Optional, Tuple
+
+from pip._vendor.rich import traceback as rich_traceback
+
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.command_context import CommandContextMixIn
+from pip._internal.cli.parser import ConfigOptionParser, UpdatingDefaultsHelpFormatter
+from pip._internal.cli.status_codes import (
+    ERROR,
+    PREVIOUS_BUILD_DIR_ERROR,
+    UNKNOWN_ERROR,
+    VIRTUALENV_NOT_FOUND,
+)
+from pip._internal.exceptions import (
+    BadCommand,
+    CommandError,
+    DiagnosticPipError,
+    InstallationError,
+    NetworkConnectionError,
+    PreviousBuildDirError,
+    UninstallationError,
+)
+from pip._internal.utils.filesystem import check_path_owner
+from pip._internal.utils.logging import BrokenStdoutLoggingError, setup_logging
+from pip._internal.utils.misc import get_prog, normalize_path
+from pip._internal.utils.temp_dir import TempDirectoryTypeRegistry as TempDirRegistry
+from pip._internal.utils.temp_dir import global_tempdir_manager, tempdir_registry
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+__all__ = ["Command"]
+
+logger = logging.getLogger(__name__)
+
+
+class Command(CommandContextMixIn):
+    usage: str = ""
+    ignore_require_venv: bool = False
+
+    def __init__(self, name: str, summary: str, isolated: bool = False) -> None:
+        super().__init__()
+
+        self.name = name
+        self.summary = summary
+        self.parser = ConfigOptionParser(
+            usage=self.usage,
+            prog=f"{get_prog()} {name}",
+            formatter=UpdatingDefaultsHelpFormatter(),
+            add_help_option=False,
+            name=name,
+            description=self.__doc__,
+            isolated=isolated,
+        )
+
+        self.tempdir_registry: Optional[TempDirRegistry] = None
+
+        # Commands should add options to this option group
+        optgroup_name = f"{self.name.capitalize()} Options"
+        self.cmd_opts = optparse.OptionGroup(self.parser, optgroup_name)
+
+        # Add the general options
+        gen_opts = cmdoptions.make_option_group(
+            cmdoptions.general_group,
+            self.parser,
+        )
+        self.parser.add_option_group(gen_opts)
+
+        self.add_options()
+
+    def add_options(self) -> None:
+        pass
+
+    def handle_pip_version_check(self, options: Values) -> None:
+        """
+        This is a no-op so that commands by default do not do the pip version
+        check.
+        """
+        # Make sure we do the pip version check if the index_group options
+        # are present.
+        assert not hasattr(options, "no_index")
+
+    def run(self, options: Values, args: List[str]) -> int:
+        raise NotImplementedError
+
+    def parse_args(self, args: List[str]) -> Tuple[Values, List[str]]:
+        # factored out for testability
+        return self.parser.parse_args(args)
+
+    def main(self, args: List[str]) -> int:
+        try:
+            with self.main_context():
+                return self._main(args)
+        finally:
+            logging.shutdown()
+
+    def _main(self, args: List[str]) -> int:
+        # We must initialize this before the tempdir manager, otherwise the
+        # configuration would not be accessible by the time we clean up the
+        # tempdir manager.
+        self.tempdir_registry = self.enter_context(tempdir_registry())
+        # Intentionally set as early as possible so globally-managed temporary
+        # directories are available to the rest of the code.
+        self.enter_context(global_tempdir_manager())
+
+        options, args = self.parse_args(args)
+
+        # Set verbosity so that it can be used elsewhere.
+        self.verbosity = options.verbose - options.quiet
+
+        level_number = setup_logging(
+            verbosity=self.verbosity,
+            no_color=options.no_color,
+            user_log_file=options.log,
+        )
+
+        # TODO: Try to get these passing down from the command?
+        #       without resorting to os.environ to hold these.
+        #       This also affects isolated builds and it should.
+
+        if options.no_input:
+            os.environ["PIP_NO_INPUT"] = "1"
+
+        if options.exists_action:
+            os.environ["PIP_EXISTS_ACTION"] = " ".join(options.exists_action)
+
+        if options.require_venv and not self.ignore_require_venv:
+            # If a venv is required check if it can really be found
+            if not running_under_virtualenv():
+                logger.critical("Could not find an activated virtualenv (required).")
+                sys.exit(VIRTUALENV_NOT_FOUND)
+
+        if options.cache_dir:
+            options.cache_dir = normalize_path(options.cache_dir)
+            if not check_path_owner(options.cache_dir):
+                logger.warning(
+                    "The directory '%s' or its parent directory is not owned "
+                    "or is not writable by the current user. The cache "
+                    "has been disabled. Check the permissions and owner of "
+                    "that directory. If executing pip with sudo, you should "
+                    "use sudo's -H flag.",
+                    options.cache_dir,
+                )
+                options.cache_dir = None
+
+        def intercepts_unhandled_exc(
+            run_func: Callable[..., int]
+        ) -> Callable[..., int]:
+            @functools.wraps(run_func)
+            def exc_logging_wrapper(*args: Any) -> int:
+                try:
+                    status = run_func(*args)
+                    assert isinstance(status, int)
+                    return status
+                except DiagnosticPipError as exc:
+                    logger.error("[present-rich] %s", exc)
+                    logger.debug("Exception information:", exc_info=True)
+
+                    return ERROR
+                except PreviousBuildDirError as exc:
+                    logger.critical(str(exc))
+                    logger.debug("Exception information:", exc_info=True)
+
+                    return PREVIOUS_BUILD_DIR_ERROR
+                except (
+                    InstallationError,
+                    UninstallationError,
+                    BadCommand,
+                    NetworkConnectionError,
+                ) as exc:
+                    logger.critical(str(exc))
+                    logger.debug("Exception information:", exc_info=True)
+
+                    return ERROR
+                except CommandError as exc:
+                    logger.critical("%s", exc)
+                    logger.debug("Exception information:", exc_info=True)
+
+                    return ERROR
+                except BrokenStdoutLoggingError:
+                    # Bypass our logger and write any remaining messages to
+                    # stderr because stdout no longer works.
+                    print("ERROR: Pipe to stdout was broken", file=sys.stderr)
+                    if level_number <= logging.DEBUG:
+                        traceback.print_exc(file=sys.stderr)
+
+                    return ERROR
+                except KeyboardInterrupt:
+                    logger.critical("Operation cancelled by user")
+                    logger.debug("Exception information:", exc_info=True)
+
+                    return ERROR
+                except BaseException:
+                    logger.critical("Exception:", exc_info=True)
+
+                    return UNKNOWN_ERROR
+
+            return exc_logging_wrapper
+
+        try:
+            if not options.debug_mode:
+                run = intercepts_unhandled_exc(self.run)
+            else:
+                run = self.run
+                rich_traceback.install(show_locals=True)
+            return run(options, args)
+        finally:
+            self.handle_pip_version_check(options)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/cmdoptions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/cmdoptions.py
new file mode 100644
index 0000000000000000000000000000000000000000..1f804097e862db899e8d57e0ac1885f12a055b0d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/cmdoptions.py
@@ -0,0 +1,1055 @@
+"""
+shared options and groups
+
+The principle here is to define options once, but *not* instantiate them
+globally. One reason being that options with action='append' can carry state
+between parses. pip parses general options twice internally, and shouldn't
+pass on state. To be consistent, all options will follow this design.
+"""
+
+# The following comment should be removed at some point in the future.
+# mypy: strict-optional=False
+
+import importlib.util
+import logging
+import os
+import textwrap
+from functools import partial
+from optparse import SUPPRESS_HELP, Option, OptionGroup, OptionParser, Values
+from textwrap import dedent
+from typing import Any, Callable, Dict, Optional, Tuple
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.cli.parser import ConfigOptionParser
+from pip._internal.exceptions import CommandError
+from pip._internal.locations import USER_CACHE_DIR, get_src_prefix
+from pip._internal.models.format_control import FormatControl
+from pip._internal.models.index import PyPI
+from pip._internal.models.target_python import TargetPython
+from pip._internal.utils.hashes import STRONG_HASHES
+from pip._internal.utils.misc import strtobool
+
+logger = logging.getLogger(__name__)
+
+
+def raise_option_error(parser: OptionParser, option: Option, msg: str) -> None:
+    """
+    Raise an option parsing error using parser.error().
+
+    Args:
+      parser: an OptionParser instance.
+      option: an Option instance.
+      msg: the error text.
+    """
+    msg = f"{option} error: {msg}"
+    msg = textwrap.fill(" ".join(msg.split()))
+    parser.error(msg)
+
+
+def make_option_group(group: Dict[str, Any], parser: ConfigOptionParser) -> OptionGroup:
+    """
+    Return an OptionGroup object
+    group  -- assumed to be dict with 'name' and 'options' keys
+    parser -- an optparse Parser
+    """
+    option_group = OptionGroup(parser, group["name"])
+    for option in group["options"]:
+        option_group.add_option(option())
+    return option_group
+
+
+def check_dist_restriction(options: Values, check_target: bool = False) -> None:
+    """Function for determining if custom platform options are allowed.
+
+    :param options: The OptionParser options.
+    :param check_target: Whether or not to check if --target is being used.
+    """
+    dist_restriction_set = any(
+        [
+            options.python_version,
+            options.platforms,
+            options.abis,
+            options.implementation,
+        ]
+    )
+
+    binary_only = FormatControl(set(), {":all:"})
+    sdist_dependencies_allowed = (
+        options.format_control != binary_only and not options.ignore_dependencies
+    )
+
+    # Installations or downloads using dist restrictions must not combine
+    # source distributions and dist-specific wheels, as they are not
+    # guaranteed to be locally compatible.
+    if dist_restriction_set and sdist_dependencies_allowed:
+        raise CommandError(
+            "When restricting platform and interpreter constraints using "
+            "--python-version, --platform, --abi, or --implementation, "
+            "either --no-deps must be set, or --only-binary=:all: must be "
+            "set and --no-binary must not be set (or must be set to "
+            ":none:)."
+        )
+
+    if check_target:
+        if dist_restriction_set and not options.target_dir:
+            raise CommandError(
+                "Can not use any platform or abi specific options unless "
+                "installing via '--target'"
+            )
+
+
+def _path_option_check(option: Option, opt: str, value: str) -> str:
+    return os.path.expanduser(value)
+
+
+def _package_name_option_check(option: Option, opt: str, value: str) -> str:
+    return canonicalize_name(value)
+
+
+class PipOption(Option):
+    TYPES = Option.TYPES + ("path", "package_name")
+    TYPE_CHECKER = Option.TYPE_CHECKER.copy()
+    TYPE_CHECKER["package_name"] = _package_name_option_check
+    TYPE_CHECKER["path"] = _path_option_check
+
+
+###########
+# options #
+###########
+
+help_: Callable[..., Option] = partial(
+    Option,
+    "-h",
+    "--help",
+    dest="help",
+    action="help",
+    help="Show help.",
+)
+
+debug_mode: Callable[..., Option] = partial(
+    Option,
+    "--debug",
+    dest="debug_mode",
+    action="store_true",
+    default=False,
+    help=(
+        "Let unhandled exceptions propagate outside the main subroutine, "
+        "instead of logging them to stderr."
+    ),
+)
+
+isolated_mode: Callable[..., Option] = partial(
+    Option,
+    "--isolated",
+    dest="isolated_mode",
+    action="store_true",
+    default=False,
+    help=(
+        "Run pip in an isolated mode, ignoring environment variables and user "
+        "configuration."
+    ),
+)
+
+require_virtualenv: Callable[..., Option] = partial(
+    Option,
+    "--require-virtualenv",
+    "--require-venv",
+    dest="require_venv",
+    action="store_true",
+    default=False,
+    help=(
+        "Allow pip to only run in a virtual environment; "
+        "exit with an error otherwise."
+    ),
+)
+
+override_externally_managed: Callable[..., Option] = partial(
+    Option,
+    "--break-system-packages",
+    dest="override_externally_managed",
+    action="store_true",
+    help="Allow pip to modify an EXTERNALLY-MANAGED Python installation",
+)
+
+python: Callable[..., Option] = partial(
+    Option,
+    "--python",
+    dest="python",
+    help="Run pip with the specified Python interpreter.",
+)
+
+verbose: Callable[..., Option] = partial(
+    Option,
+    "-v",
+    "--verbose",
+    dest="verbose",
+    action="count",
+    default=0,
+    help="Give more output. Option is additive, and can be used up to 3 times.",
+)
+
+no_color: Callable[..., Option] = partial(
+    Option,
+    "--no-color",
+    dest="no_color",
+    action="store_true",
+    default=False,
+    help="Suppress colored output.",
+)
+
+version: Callable[..., Option] = partial(
+    Option,
+    "-V",
+    "--version",
+    dest="version",
+    action="store_true",
+    help="Show version and exit.",
+)
+
+quiet: Callable[..., Option] = partial(
+    Option,
+    "-q",
+    "--quiet",
+    dest="quiet",
+    action="count",
+    default=0,
+    help=(
+        "Give less output. Option is additive, and can be used up to 3"
+        " times (corresponding to WARNING, ERROR, and CRITICAL logging"
+        " levels)."
+    ),
+)
+
+progress_bar: Callable[..., Option] = partial(
+    Option,
+    "--progress-bar",
+    dest="progress_bar",
+    type="choice",
+    choices=["on", "off"],
+    default="on",
+    help="Specify whether the progress bar should be used [on, off] (default: on)",
+)
+
+log: Callable[..., Option] = partial(
+    PipOption,
+    "--log",
+    "--log-file",
+    "--local-log",
+    dest="log",
+    metavar="path",
+    type="path",
+    help="Path to a verbose appending log.",
+)
+
+no_input: Callable[..., Option] = partial(
+    Option,
+    # Don't ask for input
+    "--no-input",
+    dest="no_input",
+    action="store_true",
+    default=False,
+    help="Disable prompting for input.",
+)
+
+proxy: Callable[..., Option] = partial(
+    Option,
+    "--proxy",
+    dest="proxy",
+    type="str",
+    default="",
+    help="Specify a proxy in the form scheme://[user:passwd@]proxy.server:port.",
+)
+
+retries: Callable[..., Option] = partial(
+    Option,
+    "--retries",
+    dest="retries",
+    type="int",
+    default=5,
+    help="Maximum number of retries each connection should attempt "
+    "(default %default times).",
+)
+
+timeout: Callable[..., Option] = partial(
+    Option,
+    "--timeout",
+    "--default-timeout",
+    metavar="sec",
+    dest="timeout",
+    type="float",
+    default=15,
+    help="Set the socket timeout (default %default seconds).",
+)
+
+
+def exists_action() -> Option:
+    return Option(
+        # Option when path already exist
+        "--exists-action",
+        dest="exists_action",
+        type="choice",
+        choices=["s", "i", "w", "b", "a"],
+        default=[],
+        action="append",
+        metavar="action",
+        help="Default action when a path already exists: "
+        "(s)witch, (i)gnore, (w)ipe, (b)ackup, (a)bort.",
+    )
+
+
+cert: Callable[..., Option] = partial(
+    PipOption,
+    "--cert",
+    dest="cert",
+    type="path",
+    metavar="path",
+    help=(
+        "Path to PEM-encoded CA certificate bundle. "
+        "If provided, overrides the default. "
+        "See 'SSL Certificate Verification' in pip documentation "
+        "for more information."
+    ),
+)
+
+client_cert: Callable[..., Option] = partial(
+    PipOption,
+    "--client-cert",
+    dest="client_cert",
+    type="path",
+    default=None,
+    metavar="path",
+    help="Path to SSL client certificate, a single file containing the "
+    "private key and the certificate in PEM format.",
+)
+
+index_url: Callable[..., Option] = partial(
+    Option,
+    "-i",
+    "--index-url",
+    "--pypi-url",
+    dest="index_url",
+    metavar="URL",
+    default=PyPI.simple_url,
+    help="Base URL of the Python Package Index (default %default). "
+    "This should point to a repository compliant with PEP 503 "
+    "(the simple repository API) or a local directory laid out "
+    "in the same format.",
+)
+
+
+def extra_index_url() -> Option:
+    return Option(
+        "--extra-index-url",
+        dest="extra_index_urls",
+        metavar="URL",
+        action="append",
+        default=[],
+        help="Extra URLs of package indexes to use in addition to "
+        "--index-url. Should follow the same rules as "
+        "--index-url.",
+    )
+
+
+no_index: Callable[..., Option] = partial(
+    Option,
+    "--no-index",
+    dest="no_index",
+    action="store_true",
+    default=False,
+    help="Ignore package index (only looking at --find-links URLs instead).",
+)
+
+
+def find_links() -> Option:
+    return Option(
+        "-f",
+        "--find-links",
+        dest="find_links",
+        action="append",
+        default=[],
+        metavar="url",
+        help="If a URL or path to an html file, then parse for links to "
+        "archives such as sdist (.tar.gz) or wheel (.whl) files. "
+        "If a local path or file:// URL that's a directory, "
+        "then look for archives in the directory listing. "
+        "Links to VCS project URLs are not supported.",
+    )
+
+
+def trusted_host() -> Option:
+    return Option(
+        "--trusted-host",
+        dest="trusted_hosts",
+        action="append",
+        metavar="HOSTNAME",
+        default=[],
+        help="Mark this host or host:port pair as trusted, even though it "
+        "does not have valid or any HTTPS.",
+    )
+
+
+def constraints() -> Option:
+    return Option(
+        "-c",
+        "--constraint",
+        dest="constraints",
+        action="append",
+        default=[],
+        metavar="file",
+        help="Constrain versions using the given constraints file. "
+        "This option can be used multiple times.",
+    )
+
+
+def requirements() -> Option:
+    return Option(
+        "-r",
+        "--requirement",
+        dest="requirements",
+        action="append",
+        default=[],
+        metavar="file",
+        help="Install from the given requirements file. "
+        "This option can be used multiple times.",
+    )
+
+
+def editable() -> Option:
+    return Option(
+        "-e",
+        "--editable",
+        dest="editables",
+        action="append",
+        default=[],
+        metavar="path/url",
+        help=(
+            "Install a project in editable mode (i.e. setuptools "
+            '"develop mode") from a local project path or a VCS url.'
+        ),
+    )
+
+
+def _handle_src(option: Option, opt_str: str, value: str, parser: OptionParser) -> None:
+    value = os.path.abspath(value)
+    setattr(parser.values, option.dest, value)
+
+
+src: Callable[..., Option] = partial(
+    PipOption,
+    "--src",
+    "--source",
+    "--source-dir",
+    "--source-directory",
+    dest="src_dir",
+    type="path",
+    metavar="dir",
+    default=get_src_prefix(),
+    action="callback",
+    callback=_handle_src,
+    help="Directory to check out editable projects into. "
+    'The default in a virtualenv is "/src". '
+    'The default for global installs is "/src".',
+)
+
+
+def _get_format_control(values: Values, option: Option) -> Any:
+    """Get a format_control object."""
+    return getattr(values, option.dest)
+
+
+def _handle_no_binary(
+    option: Option, opt_str: str, value: str, parser: OptionParser
+) -> None:
+    existing = _get_format_control(parser.values, option)
+    FormatControl.handle_mutual_excludes(
+        value,
+        existing.no_binary,
+        existing.only_binary,
+    )
+
+
+def _handle_only_binary(
+    option: Option, opt_str: str, value: str, parser: OptionParser
+) -> None:
+    existing = _get_format_control(parser.values, option)
+    FormatControl.handle_mutual_excludes(
+        value,
+        existing.only_binary,
+        existing.no_binary,
+    )
+
+
+def no_binary() -> Option:
+    format_control = FormatControl(set(), set())
+    return Option(
+        "--no-binary",
+        dest="format_control",
+        action="callback",
+        callback=_handle_no_binary,
+        type="str",
+        default=format_control,
+        help="Do not use binary packages. Can be supplied multiple times, and "
+        'each time adds to the existing value. Accepts either ":all:" to '
+        'disable all binary packages, ":none:" to empty the set (notice '
+        "the colons), or one or more package names with commas between "
+        "them (no colons). Note that some packages are tricky to compile "
+        "and may fail to install when this option is used on them.",
+    )
+
+
+def only_binary() -> Option:
+    format_control = FormatControl(set(), set())
+    return Option(
+        "--only-binary",
+        dest="format_control",
+        action="callback",
+        callback=_handle_only_binary,
+        type="str",
+        default=format_control,
+        help="Do not use source packages. Can be supplied multiple times, and "
+        'each time adds to the existing value. Accepts either ":all:" to '
+        'disable all source packages, ":none:" to empty the set, or one '
+        "or more package names with commas between them. Packages "
+        "without binary distributions will fail to install when this "
+        "option is used on them.",
+    )
+
+
+platforms: Callable[..., Option] = partial(
+    Option,
+    "--platform",
+    dest="platforms",
+    metavar="platform",
+    action="append",
+    default=None,
+    help=(
+        "Only use wheels compatible with . Defaults to the "
+        "platform of the running system. Use this option multiple times to "
+        "specify multiple platforms supported by the target interpreter."
+    ),
+)
+
+
+# This was made a separate function for unit-testing purposes.
+def _convert_python_version(value: str) -> Tuple[Tuple[int, ...], Optional[str]]:
+    """
+    Convert a version string like "3", "37", or "3.7.3" into a tuple of ints.
+
+    :return: A 2-tuple (version_info, error_msg), where `error_msg` is
+        non-None if and only if there was a parsing error.
+    """
+    if not value:
+        # The empty string is the same as not providing a value.
+        return (None, None)
+
+    parts = value.split(".")
+    if len(parts) > 3:
+        return ((), "at most three version parts are allowed")
+
+    if len(parts) == 1:
+        # Then we are in the case of "3" or "37".
+        value = parts[0]
+        if len(value) > 1:
+            parts = [value[0], value[1:]]
+
+    try:
+        version_info = tuple(int(part) for part in parts)
+    except ValueError:
+        return ((), "each version part must be an integer")
+
+    return (version_info, None)
+
+
+def _handle_python_version(
+    option: Option, opt_str: str, value: str, parser: OptionParser
+) -> None:
+    """
+    Handle a provided --python-version value.
+    """
+    version_info, error_msg = _convert_python_version(value)
+    if error_msg is not None:
+        msg = "invalid --python-version value: {!r}: {}".format(
+            value,
+            error_msg,
+        )
+        raise_option_error(parser, option=option, msg=msg)
+
+    parser.values.python_version = version_info
+
+
+python_version: Callable[..., Option] = partial(
+    Option,
+    "--python-version",
+    dest="python_version",
+    metavar="python_version",
+    action="callback",
+    callback=_handle_python_version,
+    type="str",
+    default=None,
+    help=dedent(
+        """\
+    The Python interpreter version to use for wheel and "Requires-Python"
+    compatibility checks. Defaults to a version derived from the running
+    interpreter. The version can be specified using up to three dot-separated
+    integers (e.g. "3" for 3.0.0, "3.7" for 3.7.0, or "3.7.3"). A major-minor
+    version can also be given as a string without dots (e.g. "37" for 3.7.0).
+    """
+    ),
+)
+
+
+implementation: Callable[..., Option] = partial(
+    Option,
+    "--implementation",
+    dest="implementation",
+    metavar="implementation",
+    default=None,
+    help=(
+        "Only use wheels compatible with Python "
+        "implementation , e.g. 'pp', 'jy', 'cp', "
+        " or 'ip'. If not specified, then the current "
+        "interpreter implementation is used.  Use 'py' to force "
+        "implementation-agnostic wheels."
+    ),
+)
+
+
+abis: Callable[..., Option] = partial(
+    Option,
+    "--abi",
+    dest="abis",
+    metavar="abi",
+    action="append",
+    default=None,
+    help=(
+        "Only use wheels compatible with Python abi , e.g. 'pypy_41'. "
+        "If not specified, then the current interpreter abi tag is used. "
+        "Use this option multiple times to specify multiple abis supported "
+        "by the target interpreter. Generally you will need to specify "
+        "--implementation, --platform, and --python-version when using this "
+        "option."
+    ),
+)
+
+
+def add_target_python_options(cmd_opts: OptionGroup) -> None:
+    cmd_opts.add_option(platforms())
+    cmd_opts.add_option(python_version())
+    cmd_opts.add_option(implementation())
+    cmd_opts.add_option(abis())
+
+
+def make_target_python(options: Values) -> TargetPython:
+    target_python = TargetPython(
+        platforms=options.platforms,
+        py_version_info=options.python_version,
+        abis=options.abis,
+        implementation=options.implementation,
+    )
+
+    return target_python
+
+
+def prefer_binary() -> Option:
+    return Option(
+        "--prefer-binary",
+        dest="prefer_binary",
+        action="store_true",
+        default=False,
+        help="Prefer older binary packages over newer source packages.",
+    )
+
+
+cache_dir: Callable[..., Option] = partial(
+    PipOption,
+    "--cache-dir",
+    dest="cache_dir",
+    default=USER_CACHE_DIR,
+    metavar="dir",
+    type="path",
+    help="Store the cache data in .",
+)
+
+
+def _handle_no_cache_dir(
+    option: Option, opt: str, value: str, parser: OptionParser
+) -> None:
+    """
+    Process a value provided for the --no-cache-dir option.
+
+    This is an optparse.Option callback for the --no-cache-dir option.
+    """
+    # The value argument will be None if --no-cache-dir is passed via the
+    # command-line, since the option doesn't accept arguments.  However,
+    # the value can be non-None if the option is triggered e.g. by an
+    # environment variable, like PIP_NO_CACHE_DIR=true.
+    if value is not None:
+        # Then parse the string value to get argument error-checking.
+        try:
+            strtobool(value)
+        except ValueError as exc:
+            raise_option_error(parser, option=option, msg=str(exc))
+
+    # Originally, setting PIP_NO_CACHE_DIR to a value that strtobool()
+    # converted to 0 (like "false" or "no") caused cache_dir to be disabled
+    # rather than enabled (logic would say the latter).  Thus, we disable
+    # the cache directory not just on values that parse to True, but (for
+    # backwards compatibility reasons) also on values that parse to False.
+    # In other words, always set it to False if the option is provided in
+    # some (valid) form.
+    parser.values.cache_dir = False
+
+
+no_cache: Callable[..., Option] = partial(
+    Option,
+    "--no-cache-dir",
+    dest="cache_dir",
+    action="callback",
+    callback=_handle_no_cache_dir,
+    help="Disable the cache.",
+)
+
+no_deps: Callable[..., Option] = partial(
+    Option,
+    "--no-deps",
+    "--no-dependencies",
+    dest="ignore_dependencies",
+    action="store_true",
+    default=False,
+    help="Don't install package dependencies.",
+)
+
+ignore_requires_python: Callable[..., Option] = partial(
+    Option,
+    "--ignore-requires-python",
+    dest="ignore_requires_python",
+    action="store_true",
+    help="Ignore the Requires-Python information.",
+)
+
+no_build_isolation: Callable[..., Option] = partial(
+    Option,
+    "--no-build-isolation",
+    dest="build_isolation",
+    action="store_false",
+    default=True,
+    help="Disable isolation when building a modern source distribution. "
+    "Build dependencies specified by PEP 518 must be already installed "
+    "if this option is used.",
+)
+
+check_build_deps: Callable[..., Option] = partial(
+    Option,
+    "--check-build-dependencies",
+    dest="check_build_deps",
+    action="store_true",
+    default=False,
+    help="Check the build dependencies when PEP517 is used.",
+)
+
+
+def _handle_no_use_pep517(
+    option: Option, opt: str, value: str, parser: OptionParser
+) -> None:
+    """
+    Process a value provided for the --no-use-pep517 option.
+
+    This is an optparse.Option callback for the no_use_pep517 option.
+    """
+    # Since --no-use-pep517 doesn't accept arguments, the value argument
+    # will be None if --no-use-pep517 is passed via the command-line.
+    # However, the value can be non-None if the option is triggered e.g.
+    # by an environment variable, for example "PIP_NO_USE_PEP517=true".
+    if value is not None:
+        msg = """A value was passed for --no-use-pep517,
+        probably using either the PIP_NO_USE_PEP517 environment variable
+        or the "no-use-pep517" config file option. Use an appropriate value
+        of the PIP_USE_PEP517 environment variable or the "use-pep517"
+        config file option instead.
+        """
+        raise_option_error(parser, option=option, msg=msg)
+
+    # If user doesn't wish to use pep517, we check if setuptools is installed
+    # and raise error if it is not.
+    if not importlib.util.find_spec("setuptools"):
+        msg = "It is not possible to use --no-use-pep517 without setuptools installed."
+        raise_option_error(parser, option=option, msg=msg)
+
+    # Otherwise, --no-use-pep517 was passed via the command-line.
+    parser.values.use_pep517 = False
+
+
+use_pep517: Any = partial(
+    Option,
+    "--use-pep517",
+    dest="use_pep517",
+    action="store_true",
+    default=None,
+    help="Use PEP 517 for building source distributions "
+    "(use --no-use-pep517 to force legacy behaviour).",
+)
+
+no_use_pep517: Any = partial(
+    Option,
+    "--no-use-pep517",
+    dest="use_pep517",
+    action="callback",
+    callback=_handle_no_use_pep517,
+    default=None,
+    help=SUPPRESS_HELP,
+)
+
+
+def _handle_config_settings(
+    option: Option, opt_str: str, value: str, parser: OptionParser
+) -> None:
+    key, sep, val = value.partition("=")
+    if sep != "=":
+        parser.error(f"Arguments to {opt_str} must be of the form KEY=VAL")  # noqa
+    dest = getattr(parser.values, option.dest)
+    if dest is None:
+        dest = {}
+        setattr(parser.values, option.dest, dest)
+    dest[key] = val
+
+
+config_settings: Callable[..., Option] = partial(
+    Option,
+    "--config-settings",
+    dest="config_settings",
+    type=str,
+    action="callback",
+    callback=_handle_config_settings,
+    metavar="settings",
+    help="Configuration settings to be passed to the PEP 517 build backend. "
+    "Settings take the form KEY=VALUE. Use multiple --config-settings options "
+    "to pass multiple keys to the backend.",
+)
+
+install_options: Callable[..., Option] = partial(
+    Option,
+    "--install-option",
+    dest="install_options",
+    action="append",
+    metavar="options",
+    help="This option is deprecated. Using this option with location-changing "
+    "options may cause unexpected behavior. "
+    "Use pip-level options like --user, --prefix, --root, and --target.",
+)
+
+build_options: Callable[..., Option] = partial(
+    Option,
+    "--build-option",
+    dest="build_options",
+    metavar="options",
+    action="append",
+    help="Extra arguments to be supplied to 'setup.py bdist_wheel'.",
+)
+
+global_options: Callable[..., Option] = partial(
+    Option,
+    "--global-option",
+    dest="global_options",
+    action="append",
+    metavar="options",
+    help="Extra global options to be supplied to the setup.py "
+    "call before the install or bdist_wheel command.",
+)
+
+no_clean: Callable[..., Option] = partial(
+    Option,
+    "--no-clean",
+    action="store_true",
+    default=False,
+    help="Don't clean up build directories.",
+)
+
+pre: Callable[..., Option] = partial(
+    Option,
+    "--pre",
+    action="store_true",
+    default=False,
+    help="Include pre-release and development versions. By default, "
+    "pip only finds stable versions.",
+)
+
+disable_pip_version_check: Callable[..., Option] = partial(
+    Option,
+    "--disable-pip-version-check",
+    dest="disable_pip_version_check",
+    action="store_true",
+    default=False,
+    help="Don't periodically check PyPI to determine whether a new version "
+    "of pip is available for download. Implied with --no-index.",
+)
+
+root_user_action: Callable[..., Option] = partial(
+    Option,
+    "--root-user-action",
+    dest="root_user_action",
+    default="warn",
+    choices=["warn", "ignore"],
+    help="Action if pip is run as a root user. By default, a warning message is shown.",
+)
+
+
+def _handle_merge_hash(
+    option: Option, opt_str: str, value: str, parser: OptionParser
+) -> None:
+    """Given a value spelled "algo:digest", append the digest to a list
+    pointed to in a dict by the algo name."""
+    if not parser.values.hashes:
+        parser.values.hashes = {}
+    try:
+        algo, digest = value.split(":", 1)
+    except ValueError:
+        parser.error(
+            "Arguments to {} must be a hash name "  # noqa
+            "followed by a value, like --hash=sha256:"
+            "abcde...".format(opt_str)
+        )
+    if algo not in STRONG_HASHES:
+        parser.error(
+            "Allowed hash algorithms for {} are {}.".format(  # noqa
+                opt_str, ", ".join(STRONG_HASHES)
+            )
+        )
+    parser.values.hashes.setdefault(algo, []).append(digest)
+
+
+hash: Callable[..., Option] = partial(
+    Option,
+    "--hash",
+    # Hash values eventually end up in InstallRequirement.hashes due to
+    # __dict__ copying in process_line().
+    dest="hashes",
+    action="callback",
+    callback=_handle_merge_hash,
+    type="string",
+    help="Verify that the package's archive matches this "
+    "hash before installing. Example: --hash=sha256:abcdef...",
+)
+
+
+require_hashes: Callable[..., Option] = partial(
+    Option,
+    "--require-hashes",
+    dest="require_hashes",
+    action="store_true",
+    default=False,
+    help="Require a hash to check each requirement against, for "
+    "repeatable installs. This option is implied when any package in a "
+    "requirements file has a --hash option.",
+)
+
+
+list_path: Callable[..., Option] = partial(
+    PipOption,
+    "--path",
+    dest="path",
+    type="path",
+    action="append",
+    help="Restrict to the specified installation path for listing "
+    "packages (can be used multiple times).",
+)
+
+
+def check_list_path_option(options: Values) -> None:
+    if options.path and (options.user or options.local):
+        raise CommandError("Cannot combine '--path' with '--user' or '--local'")
+
+
+list_exclude: Callable[..., Option] = partial(
+    PipOption,
+    "--exclude",
+    dest="excludes",
+    action="append",
+    metavar="package",
+    type="package_name",
+    help="Exclude specified package from the output",
+)
+
+
+no_python_version_warning: Callable[..., Option] = partial(
+    Option,
+    "--no-python-version-warning",
+    dest="no_python_version_warning",
+    action="store_true",
+    default=False,
+    help="Silence deprecation warnings for upcoming unsupported Pythons.",
+)
+
+
+use_new_feature: Callable[..., Option] = partial(
+    Option,
+    "--use-feature",
+    dest="features_enabled",
+    metavar="feature",
+    action="append",
+    default=[],
+    choices=[
+        "fast-deps",
+        "truststore",
+        "no-binary-enable-wheel-cache",
+    ],
+    help="Enable new functionality, that may be backward incompatible.",
+)
+
+use_deprecated_feature: Callable[..., Option] = partial(
+    Option,
+    "--use-deprecated",
+    dest="deprecated_features_enabled",
+    metavar="feature",
+    action="append",
+    default=[],
+    choices=[
+        "legacy-resolver",
+    ],
+    help=("Enable deprecated functionality, that will be removed in the future."),
+)
+
+
+##########
+# groups #
+##########
+
+general_group: Dict[str, Any] = {
+    "name": "General Options",
+    "options": [
+        help_,
+        debug_mode,
+        isolated_mode,
+        require_virtualenv,
+        python,
+        verbose,
+        version,
+        quiet,
+        log,
+        no_input,
+        proxy,
+        retries,
+        timeout,
+        exists_action,
+        trusted_host,
+        cert,
+        client_cert,
+        cache_dir,
+        no_cache,
+        disable_pip_version_check,
+        no_color,
+        no_python_version_warning,
+        use_new_feature,
+        use_deprecated_feature,
+    ],
+}
+
+index_group: Dict[str, Any] = {
+    "name": "Package Index Options",
+    "options": [
+        index_url,
+        extra_index_url,
+        no_index,
+        find_links,
+    ],
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/command_context.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/command_context.py
new file mode 100644
index 0000000000000000000000000000000000000000..139995ac3f109a82664e4913f7ebc32ecf7617e1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/command_context.py
@@ -0,0 +1,27 @@
+from contextlib import ExitStack, contextmanager
+from typing import ContextManager, Generator, TypeVar
+
+_T = TypeVar("_T", covariant=True)
+
+
+class CommandContextMixIn:
+    def __init__(self) -> None:
+        super().__init__()
+        self._in_main_context = False
+        self._main_context = ExitStack()
+
+    @contextmanager
+    def main_context(self) -> Generator[None, None, None]:
+        assert not self._in_main_context
+
+        self._in_main_context = True
+        try:
+            with self._main_context:
+                yield
+        finally:
+            self._in_main_context = False
+
+    def enter_context(self, context_provider: ContextManager[_T]) -> _T:
+        assert self._in_main_context
+
+        return self._main_context.enter_context(context_provider)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/main.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/main.py
new file mode 100644
index 0000000000000000000000000000000000000000..0e31221543adcd5cbec489985bbf473dcf7503f6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/main.py
@@ -0,0 +1,70 @@
+"""Primary application entrypoint.
+"""
+import locale
+import logging
+import os
+import sys
+from typing import List, Optional
+
+from pip._internal.cli.autocompletion import autocomplete
+from pip._internal.cli.main_parser import parse_command
+from pip._internal.commands import create_command
+from pip._internal.exceptions import PipError
+from pip._internal.utils import deprecation
+
+logger = logging.getLogger(__name__)
+
+
+# Do not import and use main() directly! Using it directly is actively
+# discouraged by pip's maintainers. The name, location and behavior of
+# this function is subject to change, so calling it directly is not
+# portable across different pip versions.
+
+# In addition, running pip in-process is unsupported and unsafe. This is
+# elaborated in detail at
+# https://pip.pypa.io/en/stable/user_guide/#using-pip-from-your-program.
+# That document also provides suggestions that should work for nearly
+# all users that are considering importing and using main() directly.
+
+# However, we know that certain users will still want to invoke pip
+# in-process. If you understand and accept the implications of using pip
+# in an unsupported manner, the best approach is to use runpy to avoid
+# depending on the exact location of this entry point.
+
+# The following example shows how to use runpy to invoke pip in that
+# case:
+#
+#     sys.argv = ["pip", your, args, here]
+#     runpy.run_module("pip", run_name="__main__")
+#
+# Note that this will exit the process after running, unlike a direct
+# call to main. As it is not safe to do any processing after calling
+# main, this should not be an issue in practice.
+
+
+def main(args: Optional[List[str]] = None) -> int:
+    if args is None:
+        args = sys.argv[1:]
+
+    # Configure our deprecation warnings to be sent through loggers
+    deprecation.install_warning_logger()
+
+    autocomplete()
+
+    try:
+        cmd_name, cmd_args = parse_command(args)
+    except PipError as exc:
+        sys.stderr.write(f"ERROR: {exc}")
+        sys.stderr.write(os.linesep)
+        sys.exit(1)
+
+    # Needed for locale.getpreferredencoding(False) to work
+    # in pip._internal.utils.encoding.auto_decode
+    try:
+        locale.setlocale(locale.LC_ALL, "")
+    except locale.Error as e:
+        # setlocale can apparently crash if locale are uninitialized
+        logger.debug("Ignoring error %s when setting locale", e)
+    command = create_command(cmd_name, isolated=("--isolated" in cmd_args))
+
+    return command.main(cmd_args)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/main_parser.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/main_parser.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ade356b9c2f3e375bf598635627870f248c0cc3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/main_parser.py
@@ -0,0 +1,134 @@
+"""A single place for constructing and exposing the main parser
+"""
+
+import os
+import subprocess
+import sys
+from typing import List, Optional, Tuple
+
+from pip._internal.build_env import get_runnable_pip
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.parser import ConfigOptionParser, UpdatingDefaultsHelpFormatter
+from pip._internal.commands import commands_dict, get_similar_commands
+from pip._internal.exceptions import CommandError
+from pip._internal.utils.misc import get_pip_version, get_prog
+
+__all__ = ["create_main_parser", "parse_command"]
+
+
+def create_main_parser() -> ConfigOptionParser:
+    """Creates and returns the main parser for pip's CLI"""
+
+    parser = ConfigOptionParser(
+        usage="\n%prog  [options]",
+        add_help_option=False,
+        formatter=UpdatingDefaultsHelpFormatter(),
+        name="global",
+        prog=get_prog(),
+    )
+    parser.disable_interspersed_args()
+
+    parser.version = get_pip_version()
+
+    # add the general options
+    gen_opts = cmdoptions.make_option_group(cmdoptions.general_group, parser)
+    parser.add_option_group(gen_opts)
+
+    # so the help formatter knows
+    parser.main = True  # type: ignore
+
+    # create command listing for description
+    description = [""] + [
+        f"{name:27} {command_info.summary}"
+        for name, command_info in commands_dict.items()
+    ]
+    parser.description = "\n".join(description)
+
+    return parser
+
+
+def identify_python_interpreter(python: str) -> Optional[str]:
+    # If the named file exists, use it.
+    # If it's a directory, assume it's a virtual environment and
+    # look for the environment's Python executable.
+    if os.path.exists(python):
+        if os.path.isdir(python):
+            # bin/python for Unix, Scripts/python.exe for Windows
+            # Try both in case of odd cases like cygwin.
+            for exe in ("bin/python", "Scripts/python.exe"):
+                py = os.path.join(python, exe)
+                if os.path.exists(py):
+                    return py
+        else:
+            return python
+
+    # Could not find the interpreter specified
+    return None
+
+
+def parse_command(args: List[str]) -> Tuple[str, List[str]]:
+    parser = create_main_parser()
+
+    # Note: parser calls disable_interspersed_args(), so the result of this
+    # call is to split the initial args into the general options before the
+    # subcommand and everything else.
+    # For example:
+    #  args: ['--timeout=5', 'install', '--user', 'INITools']
+    #  general_options: ['--timeout==5']
+    #  args_else: ['install', '--user', 'INITools']
+    general_options, args_else = parser.parse_args(args)
+
+    # --python
+    if general_options.python and "_PIP_RUNNING_IN_SUBPROCESS" not in os.environ:
+        # Re-invoke pip using the specified Python interpreter
+        interpreter = identify_python_interpreter(general_options.python)
+        if interpreter is None:
+            raise CommandError(
+                f"Could not locate Python interpreter {general_options.python}"
+            )
+
+        pip_cmd = [
+            interpreter,
+            get_runnable_pip(),
+        ]
+        pip_cmd.extend(args)
+
+        # Set a flag so the child doesn't re-invoke itself, causing
+        # an infinite loop.
+        os.environ["_PIP_RUNNING_IN_SUBPROCESS"] = "1"
+        returncode = 0
+        try:
+            proc = subprocess.run(pip_cmd)
+            returncode = proc.returncode
+        except (subprocess.SubprocessError, OSError) as exc:
+            raise CommandError(f"Failed to run pip under {interpreter}: {exc}")
+        sys.exit(returncode)
+
+    # --version
+    if general_options.version:
+        sys.stdout.write(parser.version)
+        sys.stdout.write(os.linesep)
+        sys.exit()
+
+    # pip || pip help -> print_help()
+    if not args_else or (args_else[0] == "help" and len(args_else) == 1):
+        parser.print_help()
+        sys.exit()
+
+    # the subcommand name
+    cmd_name = args_else[0]
+
+    if cmd_name not in commands_dict:
+        guess = get_similar_commands(cmd_name)
+
+        msg = [f'unknown command "{cmd_name}"']
+        if guess:
+            msg.append(f'maybe you meant "{guess}"')
+
+        raise CommandError(" - ".join(msg))
+
+    # all the args without the subcommand
+    cmd_args = args[:]
+    cmd_args.remove(cmd_name)
+
+    return cmd_name, cmd_args
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/parser.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/parser.py
new file mode 100644
index 0000000000000000000000000000000000000000..c762cf2781d460288674314959c727e860aad067
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/parser.py
@@ -0,0 +1,294 @@
+"""Base option parser setup"""
+
+import logging
+import optparse
+import shutil
+import sys
+import textwrap
+from contextlib import suppress
+from typing import Any, Dict, Generator, List, Tuple
+
+from pip._internal.cli.status_codes import UNKNOWN_ERROR
+from pip._internal.configuration import Configuration, ConfigurationError
+from pip._internal.utils.misc import redact_auth_from_url, strtobool
+
+logger = logging.getLogger(__name__)
+
+
+class PrettyHelpFormatter(optparse.IndentedHelpFormatter):
+    """A prettier/less verbose help formatter for optparse."""
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        # help position must be aligned with __init__.parseopts.description
+        kwargs["max_help_position"] = 30
+        kwargs["indent_increment"] = 1
+        kwargs["width"] = shutil.get_terminal_size()[0] - 2
+        super().__init__(*args, **kwargs)
+
+    def format_option_strings(self, option: optparse.Option) -> str:
+        return self._format_option_strings(option)
+
+    def _format_option_strings(
+        self, option: optparse.Option, mvarfmt: str = " <{}>", optsep: str = ", "
+    ) -> str:
+        """
+        Return a comma-separated list of option strings and metavars.
+
+        :param option:  tuple of (short opt, long opt), e.g: ('-f', '--format')
+        :param mvarfmt: metavar format string
+        :param optsep:  separator
+        """
+        opts = []
+
+        if option._short_opts:
+            opts.append(option._short_opts[0])
+        if option._long_opts:
+            opts.append(option._long_opts[0])
+        if len(opts) > 1:
+            opts.insert(1, optsep)
+
+        if option.takes_value():
+            assert option.dest is not None
+            metavar = option.metavar or option.dest.lower()
+            opts.append(mvarfmt.format(metavar.lower()))
+
+        return "".join(opts)
+
+    def format_heading(self, heading: str) -> str:
+        if heading == "Options":
+            return ""
+        return heading + ":\n"
+
+    def format_usage(self, usage: str) -> str:
+        """
+        Ensure there is only one newline between usage and the first heading
+        if there is no description.
+        """
+        msg = "\nUsage: {}\n".format(self.indent_lines(textwrap.dedent(usage), "  "))
+        return msg
+
+    def format_description(self, description: str) -> str:
+        # leave full control over description to us
+        if description:
+            if hasattr(self.parser, "main"):
+                label = "Commands"
+            else:
+                label = "Description"
+            # some doc strings have initial newlines, some don't
+            description = description.lstrip("\n")
+            # some doc strings have final newlines and spaces, some don't
+            description = description.rstrip()
+            # dedent, then reindent
+            description = self.indent_lines(textwrap.dedent(description), "  ")
+            description = f"{label}:\n{description}\n"
+            return description
+        else:
+            return ""
+
+    def format_epilog(self, epilog: str) -> str:
+        # leave full control over epilog to us
+        if epilog:
+            return epilog
+        else:
+            return ""
+
+    def indent_lines(self, text: str, indent: str) -> str:
+        new_lines = [indent + line for line in text.split("\n")]
+        return "\n".join(new_lines)
+
+
+class UpdatingDefaultsHelpFormatter(PrettyHelpFormatter):
+    """Custom help formatter for use in ConfigOptionParser.
+
+    This is updates the defaults before expanding them, allowing
+    them to show up correctly in the help listing.
+
+    Also redact auth from url type options
+    """
+
+    def expand_default(self, option: optparse.Option) -> str:
+        default_values = None
+        if self.parser is not None:
+            assert isinstance(self.parser, ConfigOptionParser)
+            self.parser._update_defaults(self.parser.defaults)
+            assert option.dest is not None
+            default_values = self.parser.defaults.get(option.dest)
+        help_text = super().expand_default(option)
+
+        if default_values and option.metavar == "URL":
+            if isinstance(default_values, str):
+                default_values = [default_values]
+
+            # If its not a list, we should abort and just return the help text
+            if not isinstance(default_values, list):
+                default_values = []
+
+            for val in default_values:
+                help_text = help_text.replace(val, redact_auth_from_url(val))
+
+        return help_text
+
+
+class CustomOptionParser(optparse.OptionParser):
+    def insert_option_group(
+        self, idx: int, *args: Any, **kwargs: Any
+    ) -> optparse.OptionGroup:
+        """Insert an OptionGroup at a given position."""
+        group = self.add_option_group(*args, **kwargs)
+
+        self.option_groups.pop()
+        self.option_groups.insert(idx, group)
+
+        return group
+
+    @property
+    def option_list_all(self) -> List[optparse.Option]:
+        """Get a list of all options, including those in option groups."""
+        res = self.option_list[:]
+        for i in self.option_groups:
+            res.extend(i.option_list)
+
+        return res
+
+
+class ConfigOptionParser(CustomOptionParser):
+    """Custom option parser which updates its defaults by checking the
+    configuration files and environmental variables"""
+
+    def __init__(
+        self,
+        *args: Any,
+        name: str,
+        isolated: bool = False,
+        **kwargs: Any,
+    ) -> None:
+        self.name = name
+        self.config = Configuration(isolated)
+
+        assert self.name
+        super().__init__(*args, **kwargs)
+
+    def check_default(self, option: optparse.Option, key: str, val: Any) -> Any:
+        try:
+            return option.check_value(key, val)
+        except optparse.OptionValueError as exc:
+            print(f"An error occurred during configuration: {exc}")
+            sys.exit(3)
+
+    def _get_ordered_configuration_items(
+        self,
+    ) -> Generator[Tuple[str, Any], None, None]:
+        # Configuration gives keys in an unordered manner. Order them.
+        override_order = ["global", self.name, ":env:"]
+
+        # Pool the options into different groups
+        section_items: Dict[str, List[Tuple[str, Any]]] = {
+            name: [] for name in override_order
+        }
+        for section_key, val in self.config.items():
+            # ignore empty values
+            if not val:
+                logger.debug(
+                    "Ignoring configuration key '%s' as it's value is empty.",
+                    section_key,
+                )
+                continue
+
+            section, key = section_key.split(".", 1)
+            if section in override_order:
+                section_items[section].append((key, val))
+
+        # Yield each group in their override order
+        for section in override_order:
+            for key, val in section_items[section]:
+                yield key, val
+
+    def _update_defaults(self, defaults: Dict[str, Any]) -> Dict[str, Any]:
+        """Updates the given defaults with values from the config files and
+        the environ. Does a little special handling for certain types of
+        options (lists)."""
+
+        # Accumulate complex default state.
+        self.values = optparse.Values(self.defaults)
+        late_eval = set()
+        # Then set the options with those values
+        for key, val in self._get_ordered_configuration_items():
+            # '--' because configuration supports only long names
+            option = self.get_option("--" + key)
+
+            # Ignore options not present in this parser. E.g. non-globals put
+            # in [global] by users that want them to apply to all applicable
+            # commands.
+            if option is None:
+                continue
+
+            assert option.dest is not None
+
+            if option.action in ("store_true", "store_false"):
+                try:
+                    val = strtobool(val)
+                except ValueError:
+                    self.error(
+                        "{} is not a valid value for {} option, "  # noqa
+                        "please specify a boolean value like yes/no, "
+                        "true/false or 1/0 instead.".format(val, key)
+                    )
+            elif option.action == "count":
+                with suppress(ValueError):
+                    val = strtobool(val)
+                with suppress(ValueError):
+                    val = int(val)
+                if not isinstance(val, int) or val < 0:
+                    self.error(
+                        "{} is not a valid value for {} option, "  # noqa
+                        "please instead specify either a non-negative integer "
+                        "or a boolean value like yes/no or false/true "
+                        "which is equivalent to 1/0.".format(val, key)
+                    )
+            elif option.action == "append":
+                val = val.split()
+                val = [self.check_default(option, key, v) for v in val]
+            elif option.action == "callback":
+                assert option.callback is not None
+                late_eval.add(option.dest)
+                opt_str = option.get_opt_string()
+                val = option.convert_value(opt_str, val)
+                # From take_action
+                args = option.callback_args or ()
+                kwargs = option.callback_kwargs or {}
+                option.callback(option, opt_str, val, self, *args, **kwargs)
+            else:
+                val = self.check_default(option, key, val)
+
+            defaults[option.dest] = val
+
+        for key in late_eval:
+            defaults[key] = getattr(self.values, key)
+        self.values = None
+        return defaults
+
+    def get_default_values(self) -> optparse.Values:
+        """Overriding to make updating the defaults after instantiation of
+        the option parser possible, _update_defaults() does the dirty work."""
+        if not self.process_default_values:
+            # Old, pre-Optik 1.5 behaviour.
+            return optparse.Values(self.defaults)
+
+        # Load the configuration, or error out in case of an error
+        try:
+            self.config.load()
+        except ConfigurationError as err:
+            self.exit(UNKNOWN_ERROR, str(err))
+
+        defaults = self._update_defaults(self.defaults.copy())  # ours
+        for option in self._get_all_options():
+            assert option.dest is not None
+            default = defaults.get(option.dest)
+            if isinstance(default, str):
+                opt_str = option.get_opt_string()
+                defaults[option.dest] = option.check_value(opt_str, default)
+        return optparse.Values(defaults)
+
+    def error(self, msg: str) -> None:
+        self.print_usage(sys.stderr)
+        self.exit(UNKNOWN_ERROR, f"{msg}\n")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/progress_bars.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/progress_bars.py
new file mode 100644
index 0000000000000000000000000000000000000000..0ad14031ca50c2c348dc0daa8fe7b38af532c0f5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/progress_bars.py
@@ -0,0 +1,68 @@
+import functools
+from typing import Callable, Generator, Iterable, Iterator, Optional, Tuple
+
+from pip._vendor.rich.progress import (
+    BarColumn,
+    DownloadColumn,
+    FileSizeColumn,
+    Progress,
+    ProgressColumn,
+    SpinnerColumn,
+    TextColumn,
+    TimeElapsedColumn,
+    TimeRemainingColumn,
+    TransferSpeedColumn,
+)
+
+from pip._internal.utils.logging import get_indentation
+
+DownloadProgressRenderer = Callable[[Iterable[bytes]], Iterator[bytes]]
+
+
+def _rich_progress_bar(
+    iterable: Iterable[bytes],
+    *,
+    bar_type: str,
+    size: int,
+) -> Generator[bytes, None, None]:
+    assert bar_type == "on", "This should only be used in the default mode."
+
+    if not size:
+        total = float("inf")
+        columns: Tuple[ProgressColumn, ...] = (
+            TextColumn("[progress.description]{task.description}"),
+            SpinnerColumn("line", speed=1.5),
+            FileSizeColumn(),
+            TransferSpeedColumn(),
+            TimeElapsedColumn(),
+        )
+    else:
+        total = size
+        columns = (
+            TextColumn("[progress.description]{task.description}"),
+            BarColumn(),
+            DownloadColumn(),
+            TransferSpeedColumn(),
+            TextColumn("eta"),
+            TimeRemainingColumn(),
+        )
+
+    progress = Progress(*columns, refresh_per_second=30)
+    task_id = progress.add_task(" " * (get_indentation() + 2), total=total)
+    with progress:
+        for chunk in iterable:
+            yield chunk
+            progress.update(task_id, advance=len(chunk))
+
+
+def get_download_progress_renderer(
+    *, bar_type: str, size: Optional[int] = None
+) -> DownloadProgressRenderer:
+    """Get an object that can be used to render the download progress.
+
+    Returns a callable, that takes an iterable to "wrap".
+    """
+    if bar_type == "on":
+        return functools.partial(_rich_progress_bar, bar_type=bar_type, size=size)
+    else:
+        return iter  # no-op, when passed an iterator
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/req_command.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/req_command.py
new file mode 100644
index 0000000000000000000000000000000000000000..1044809f04082fe8ba43e57946638870e494dd40
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/req_command.py
@@ -0,0 +1,502 @@
+"""Contains the Command base classes that depend on PipSession.
+
+The classes in this module are in a separate module so the commands not
+needing download / PackageFinder capability don't unnecessarily import the
+PackageFinder machinery and all its vendored dependencies, etc.
+"""
+
+import logging
+import os
+import sys
+from functools import partial
+from optparse import Values
+from typing import TYPE_CHECKING, Any, List, Optional, Tuple
+
+from pip._internal.cache import WheelCache
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.command_context import CommandContextMixIn
+from pip._internal.exceptions import CommandError, PreviousBuildDirError
+from pip._internal.index.collector import LinkCollector
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.models.selection_prefs import SelectionPreferences
+from pip._internal.models.target_python import TargetPython
+from pip._internal.network.session import PipSession
+from pip._internal.operations.build.build_tracker import BuildTracker
+from pip._internal.operations.prepare import RequirementPreparer
+from pip._internal.req.constructors import (
+    install_req_from_editable,
+    install_req_from_line,
+    install_req_from_parsed_requirement,
+    install_req_from_req_string,
+)
+from pip._internal.req.req_file import parse_requirements
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.resolution.base import BaseResolver
+from pip._internal.self_outdated_check import pip_self_version_check
+from pip._internal.utils.temp_dir import (
+    TempDirectory,
+    TempDirectoryTypeRegistry,
+    tempdir_kinds,
+)
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+if TYPE_CHECKING:
+    from ssl import SSLContext
+
+logger = logging.getLogger(__name__)
+
+
+def _create_truststore_ssl_context() -> Optional["SSLContext"]:
+    if sys.version_info < (3, 10):
+        raise CommandError("The truststore feature is only available for Python 3.10+")
+
+    try:
+        import ssl
+    except ImportError:
+        logger.warning("Disabling truststore since ssl support is missing")
+        return None
+
+    try:
+        import truststore
+    except ImportError:
+        raise CommandError(
+            "To use the truststore feature, 'truststore' must be installed into "
+            "pip's current environment."
+        )
+
+    return truststore.SSLContext(ssl.PROTOCOL_TLS_CLIENT)
+
+
+class SessionCommandMixin(CommandContextMixIn):
+
+    """
+    A class mixin for command classes needing _build_session().
+    """
+
+    def __init__(self) -> None:
+        super().__init__()
+        self._session: Optional[PipSession] = None
+
+    @classmethod
+    def _get_index_urls(cls, options: Values) -> Optional[List[str]]:
+        """Return a list of index urls from user-provided options."""
+        index_urls = []
+        if not getattr(options, "no_index", False):
+            url = getattr(options, "index_url", None)
+            if url:
+                index_urls.append(url)
+        urls = getattr(options, "extra_index_urls", None)
+        if urls:
+            index_urls.extend(urls)
+        # Return None rather than an empty list
+        return index_urls or None
+
+    def get_default_session(self, options: Values) -> PipSession:
+        """Get a default-managed session."""
+        if self._session is None:
+            self._session = self.enter_context(self._build_session(options))
+            # there's no type annotation on requests.Session, so it's
+            # automatically ContextManager[Any] and self._session becomes Any,
+            # then https://github.com/python/mypy/issues/7696 kicks in
+            assert self._session is not None
+        return self._session
+
+    def _build_session(
+        self,
+        options: Values,
+        retries: Optional[int] = None,
+        timeout: Optional[int] = None,
+        fallback_to_certifi: bool = False,
+    ) -> PipSession:
+        cache_dir = options.cache_dir
+        assert not cache_dir or os.path.isabs(cache_dir)
+
+        if "truststore" in options.features_enabled:
+            try:
+                ssl_context = _create_truststore_ssl_context()
+            except Exception:
+                if not fallback_to_certifi:
+                    raise
+                ssl_context = None
+        else:
+            ssl_context = None
+
+        session = PipSession(
+            cache=os.path.join(cache_dir, "http") if cache_dir else None,
+            retries=retries if retries is not None else options.retries,
+            trusted_hosts=options.trusted_hosts,
+            index_urls=self._get_index_urls(options),
+            ssl_context=ssl_context,
+        )
+
+        # Handle custom ca-bundles from the user
+        if options.cert:
+            session.verify = options.cert
+
+        # Handle SSL client certificate
+        if options.client_cert:
+            session.cert = options.client_cert
+
+        # Handle timeouts
+        if options.timeout or timeout:
+            session.timeout = timeout if timeout is not None else options.timeout
+
+        # Handle configured proxies
+        if options.proxy:
+            session.proxies = {
+                "http": options.proxy,
+                "https": options.proxy,
+            }
+
+        # Determine if we can prompt the user for authentication or not
+        session.auth.prompting = not options.no_input
+
+        return session
+
+
+class IndexGroupCommand(Command, SessionCommandMixin):
+
+    """
+    Abstract base class for commands with the index_group options.
+
+    This also corresponds to the commands that permit the pip version check.
+    """
+
+    def handle_pip_version_check(self, options: Values) -> None:
+        """
+        Do the pip version check if not disabled.
+
+        This overrides the default behavior of not doing the check.
+        """
+        # Make sure the index_group options are present.
+        assert hasattr(options, "no_index")
+
+        if options.disable_pip_version_check or options.no_index:
+            return
+
+        # Otherwise, check if we're using the latest version of pip available.
+        session = self._build_session(
+            options,
+            retries=0,
+            timeout=min(5, options.timeout),
+            # This is set to ensure the function does not fail when truststore is
+            # specified in use-feature but cannot be loaded. This usually raises a
+            # CommandError and shows a nice user-facing error, but this function is not
+            # called in that try-except block.
+            fallback_to_certifi=True,
+        )
+        with session:
+            pip_self_version_check(session, options)
+
+
+KEEPABLE_TEMPDIR_TYPES = [
+    tempdir_kinds.BUILD_ENV,
+    tempdir_kinds.EPHEM_WHEEL_CACHE,
+    tempdir_kinds.REQ_BUILD,
+]
+
+
+def warn_if_run_as_root() -> None:
+    """Output a warning for sudo users on Unix.
+
+    In a virtual environment, sudo pip still writes to virtualenv.
+    On Windows, users may run pip as Administrator without issues.
+    This warning only applies to Unix root users outside of virtualenv.
+    """
+    if running_under_virtualenv():
+        return
+    if not hasattr(os, "getuid"):
+        return
+    # On Windows, there are no "system managed" Python packages. Installing as
+    # Administrator via pip is the correct way of updating system environments.
+    #
+    # We choose sys.platform over utils.compat.WINDOWS here to enable Mypy platform
+    # checks: https://mypy.readthedocs.io/en/stable/common_issues.html
+    if sys.platform == "win32" or sys.platform == "cygwin":
+        return
+
+    if os.getuid() != 0:
+        return
+
+    logger.warning(
+        "Running pip as the 'root' user can result in broken permissions and "
+        "conflicting behaviour with the system package manager. "
+        "It is recommended to use a virtual environment instead: "
+        "https://pip.pypa.io/warnings/venv"
+    )
+
+
+def with_cleanup(func: Any) -> Any:
+    """Decorator for common logic related to managing temporary
+    directories.
+    """
+
+    def configure_tempdir_registry(registry: TempDirectoryTypeRegistry) -> None:
+        for t in KEEPABLE_TEMPDIR_TYPES:
+            registry.set_delete(t, False)
+
+    def wrapper(
+        self: RequirementCommand, options: Values, args: List[Any]
+    ) -> Optional[int]:
+        assert self.tempdir_registry is not None
+        if options.no_clean:
+            configure_tempdir_registry(self.tempdir_registry)
+
+        try:
+            return func(self, options, args)
+        except PreviousBuildDirError:
+            # This kind of conflict can occur when the user passes an explicit
+            # build directory with a pre-existing folder. In that case we do
+            # not want to accidentally remove it.
+            configure_tempdir_registry(self.tempdir_registry)
+            raise
+
+    return wrapper
+
+
+class RequirementCommand(IndexGroupCommand):
+    def __init__(self, *args: Any, **kw: Any) -> None:
+        super().__init__(*args, **kw)
+
+        self.cmd_opts.add_option(cmdoptions.no_clean())
+
+    @staticmethod
+    def determine_resolver_variant(options: Values) -> str:
+        """Determines which resolver should be used, based on the given options."""
+        if "legacy-resolver" in options.deprecated_features_enabled:
+            return "legacy"
+
+        return "2020-resolver"
+
+    @classmethod
+    def make_requirement_preparer(
+        cls,
+        temp_build_dir: TempDirectory,
+        options: Values,
+        build_tracker: BuildTracker,
+        session: PipSession,
+        finder: PackageFinder,
+        use_user_site: bool,
+        download_dir: Optional[str] = None,
+        verbosity: int = 0,
+    ) -> RequirementPreparer:
+        """
+        Create a RequirementPreparer instance for the given parameters.
+        """
+        temp_build_dir_path = temp_build_dir.path
+        assert temp_build_dir_path is not None
+
+        resolver_variant = cls.determine_resolver_variant(options)
+        if resolver_variant == "2020-resolver":
+            lazy_wheel = "fast-deps" in options.features_enabled
+            if lazy_wheel:
+                logger.warning(
+                    "pip is using lazily downloaded wheels using HTTP "
+                    "range requests to obtain dependency information. "
+                    "This experimental feature is enabled through "
+                    "--use-feature=fast-deps and it is not ready for "
+                    "production."
+                )
+        else:
+            lazy_wheel = False
+            if "fast-deps" in options.features_enabled:
+                logger.warning(
+                    "fast-deps has no effect when used with the legacy resolver."
+                )
+
+        return RequirementPreparer(
+            build_dir=temp_build_dir_path,
+            src_dir=options.src_dir,
+            download_dir=download_dir,
+            build_isolation=options.build_isolation,
+            check_build_deps=options.check_build_deps,
+            build_tracker=build_tracker,
+            session=session,
+            progress_bar=options.progress_bar,
+            finder=finder,
+            require_hashes=options.require_hashes,
+            use_user_site=use_user_site,
+            lazy_wheel=lazy_wheel,
+            verbosity=verbosity,
+        )
+
+    @classmethod
+    def make_resolver(
+        cls,
+        preparer: RequirementPreparer,
+        finder: PackageFinder,
+        options: Values,
+        wheel_cache: Optional[WheelCache] = None,
+        use_user_site: bool = False,
+        ignore_installed: bool = True,
+        ignore_requires_python: bool = False,
+        force_reinstall: bool = False,
+        upgrade_strategy: str = "to-satisfy-only",
+        use_pep517: Optional[bool] = None,
+        py_version_info: Optional[Tuple[int, ...]] = None,
+    ) -> BaseResolver:
+        """
+        Create a Resolver instance for the given parameters.
+        """
+        make_install_req = partial(
+            install_req_from_req_string,
+            isolated=options.isolated_mode,
+            use_pep517=use_pep517,
+            config_settings=getattr(options, "config_settings", None),
+        )
+        resolver_variant = cls.determine_resolver_variant(options)
+        # The long import name and duplicated invocation is needed to convince
+        # Mypy into correctly typechecking. Otherwise it would complain the
+        # "Resolver" class being redefined.
+        if resolver_variant == "2020-resolver":
+            import pip._internal.resolution.resolvelib.resolver
+
+            return pip._internal.resolution.resolvelib.resolver.Resolver(
+                preparer=preparer,
+                finder=finder,
+                wheel_cache=wheel_cache,
+                make_install_req=make_install_req,
+                use_user_site=use_user_site,
+                ignore_dependencies=options.ignore_dependencies,
+                ignore_installed=ignore_installed,
+                ignore_requires_python=ignore_requires_python,
+                force_reinstall=force_reinstall,
+                upgrade_strategy=upgrade_strategy,
+                py_version_info=py_version_info,
+            )
+        import pip._internal.resolution.legacy.resolver
+
+        return pip._internal.resolution.legacy.resolver.Resolver(
+            preparer=preparer,
+            finder=finder,
+            wheel_cache=wheel_cache,
+            make_install_req=make_install_req,
+            use_user_site=use_user_site,
+            ignore_dependencies=options.ignore_dependencies,
+            ignore_installed=ignore_installed,
+            ignore_requires_python=ignore_requires_python,
+            force_reinstall=force_reinstall,
+            upgrade_strategy=upgrade_strategy,
+            py_version_info=py_version_info,
+        )
+
+    def get_requirements(
+        self,
+        args: List[str],
+        options: Values,
+        finder: PackageFinder,
+        session: PipSession,
+    ) -> List[InstallRequirement]:
+        """
+        Parse command-line arguments into the corresponding requirements.
+        """
+        requirements: List[InstallRequirement] = []
+        for filename in options.constraints:
+            for parsed_req in parse_requirements(
+                filename,
+                constraint=True,
+                finder=finder,
+                options=options,
+                session=session,
+            ):
+                req_to_add = install_req_from_parsed_requirement(
+                    parsed_req,
+                    isolated=options.isolated_mode,
+                    user_supplied=False,
+                )
+                requirements.append(req_to_add)
+
+        for req in args:
+            req_to_add = install_req_from_line(
+                req,
+                None,
+                isolated=options.isolated_mode,
+                use_pep517=options.use_pep517,
+                user_supplied=True,
+                config_settings=getattr(options, "config_settings", None),
+            )
+            requirements.append(req_to_add)
+
+        for req in options.editables:
+            req_to_add = install_req_from_editable(
+                req,
+                user_supplied=True,
+                isolated=options.isolated_mode,
+                use_pep517=options.use_pep517,
+                config_settings=getattr(options, "config_settings", None),
+            )
+            requirements.append(req_to_add)
+
+        # NOTE: options.require_hashes may be set if --require-hashes is True
+        for filename in options.requirements:
+            for parsed_req in parse_requirements(
+                filename, finder=finder, options=options, session=session
+            ):
+                req_to_add = install_req_from_parsed_requirement(
+                    parsed_req,
+                    isolated=options.isolated_mode,
+                    use_pep517=options.use_pep517,
+                    user_supplied=True,
+                )
+                requirements.append(req_to_add)
+
+        # If any requirement has hash options, enable hash checking.
+        if any(req.has_hash_options for req in requirements):
+            options.require_hashes = True
+
+        if not (args or options.editables or options.requirements):
+            opts = {"name": self.name}
+            if options.find_links:
+                raise CommandError(
+                    "You must give at least one requirement to {name} "
+                    '(maybe you meant "pip {name} {links}"?)'.format(
+                        **dict(opts, links=" ".join(options.find_links))
+                    )
+                )
+            else:
+                raise CommandError(
+                    "You must give at least one requirement to {name} "
+                    '(see "pip help {name}")'.format(**opts)
+                )
+
+        return requirements
+
+    @staticmethod
+    def trace_basic_info(finder: PackageFinder) -> None:
+        """
+        Trace basic information about the provided objects.
+        """
+        # Display where finder is looking for packages
+        search_scope = finder.search_scope
+        locations = search_scope.get_formatted_locations()
+        if locations:
+            logger.info(locations)
+
+    def _build_package_finder(
+        self,
+        options: Values,
+        session: PipSession,
+        target_python: Optional[TargetPython] = None,
+        ignore_requires_python: Optional[bool] = None,
+    ) -> PackageFinder:
+        """
+        Create a package finder appropriate to this requirement command.
+
+        :param ignore_requires_python: Whether to ignore incompatible
+            "Requires-Python" values in links. Defaults to False.
+        """
+        link_collector = LinkCollector.create(session, options=options)
+        selection_prefs = SelectionPreferences(
+            allow_yanked=True,
+            format_control=options.format_control,
+            allow_all_prereleases=options.pre,
+            prefer_binary=options.prefer_binary,
+            ignore_requires_python=ignore_requires_python,
+        )
+
+        return PackageFinder.create(
+            link_collector=link_collector,
+            selection_prefs=selection_prefs,
+            target_python=target_python,
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/spinners.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/spinners.py
new file mode 100644
index 0000000000000000000000000000000000000000..cf2b976f377c2656afb3d84add8d30b0fc280c03
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/spinners.py
@@ -0,0 +1,159 @@
+import contextlib
+import itertools
+import logging
+import sys
+import time
+from typing import IO, Generator, Optional
+
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.logging import get_indentation
+
+logger = logging.getLogger(__name__)
+
+
+class SpinnerInterface:
+    def spin(self) -> None:
+        raise NotImplementedError()
+
+    def finish(self, final_status: str) -> None:
+        raise NotImplementedError()
+
+
+class InteractiveSpinner(SpinnerInterface):
+    def __init__(
+        self,
+        message: str,
+        file: Optional[IO[str]] = None,
+        spin_chars: str = "-\\|/",
+        # Empirically, 8 updates/second looks nice
+        min_update_interval_seconds: float = 0.125,
+    ):
+        self._message = message
+        if file is None:
+            file = sys.stdout
+        self._file = file
+        self._rate_limiter = RateLimiter(min_update_interval_seconds)
+        self._finished = False
+
+        self._spin_cycle = itertools.cycle(spin_chars)
+
+        self._file.write(" " * get_indentation() + self._message + " ... ")
+        self._width = 0
+
+    def _write(self, status: str) -> None:
+        assert not self._finished
+        # Erase what we wrote before by backspacing to the beginning, writing
+        # spaces to overwrite the old text, and then backspacing again
+        backup = "\b" * self._width
+        self._file.write(backup + " " * self._width + backup)
+        # Now we have a blank slate to add our status
+        self._file.write(status)
+        self._width = len(status)
+        self._file.flush()
+        self._rate_limiter.reset()
+
+    def spin(self) -> None:
+        if self._finished:
+            return
+        if not self._rate_limiter.ready():
+            return
+        self._write(next(self._spin_cycle))
+
+    def finish(self, final_status: str) -> None:
+        if self._finished:
+            return
+        self._write(final_status)
+        self._file.write("\n")
+        self._file.flush()
+        self._finished = True
+
+
+# Used for dumb terminals, non-interactive installs (no tty), etc.
+# We still print updates occasionally (once every 60 seconds by default) to
+# act as a keep-alive for systems like Travis-CI that take lack-of-output as
+# an indication that a task has frozen.
+class NonInteractiveSpinner(SpinnerInterface):
+    def __init__(self, message: str, min_update_interval_seconds: float = 60.0) -> None:
+        self._message = message
+        self._finished = False
+        self._rate_limiter = RateLimiter(min_update_interval_seconds)
+        self._update("started")
+
+    def _update(self, status: str) -> None:
+        assert not self._finished
+        self._rate_limiter.reset()
+        logger.info("%s: %s", self._message, status)
+
+    def spin(self) -> None:
+        if self._finished:
+            return
+        if not self._rate_limiter.ready():
+            return
+        self._update("still running...")
+
+    def finish(self, final_status: str) -> None:
+        if self._finished:
+            return
+        self._update(f"finished with status '{final_status}'")
+        self._finished = True
+
+
+class RateLimiter:
+    def __init__(self, min_update_interval_seconds: float) -> None:
+        self._min_update_interval_seconds = min_update_interval_seconds
+        self._last_update: float = 0
+
+    def ready(self) -> bool:
+        now = time.time()
+        delta = now - self._last_update
+        return delta >= self._min_update_interval_seconds
+
+    def reset(self) -> None:
+        self._last_update = time.time()
+
+
+@contextlib.contextmanager
+def open_spinner(message: str) -> Generator[SpinnerInterface, None, None]:
+    # Interactive spinner goes directly to sys.stdout rather than being routed
+    # through the logging system, but it acts like it has level INFO,
+    # i.e. it's only displayed if we're at level INFO or better.
+    # Non-interactive spinner goes through the logging system, so it is always
+    # in sync with logging configuration.
+    if sys.stdout.isatty() and logger.getEffectiveLevel() <= logging.INFO:
+        spinner: SpinnerInterface = InteractiveSpinner(message)
+    else:
+        spinner = NonInteractiveSpinner(message)
+    try:
+        with hidden_cursor(sys.stdout):
+            yield spinner
+    except KeyboardInterrupt:
+        spinner.finish("canceled")
+        raise
+    except Exception:
+        spinner.finish("error")
+        raise
+    else:
+        spinner.finish("done")
+
+
+HIDE_CURSOR = "\x1b[?25l"
+SHOW_CURSOR = "\x1b[?25h"
+
+
+@contextlib.contextmanager
+def hidden_cursor(file: IO[str]) -> Generator[None, None, None]:
+    # The Windows terminal does not support the hide/show cursor ANSI codes,
+    # even via colorama. So don't even try.
+    if WINDOWS:
+        yield
+    # We don't want to clutter the output with control characters if we're
+    # writing to a file, or if the user is running with --quiet.
+    # See https://github.com/pypa/pip/issues/3418
+    elif not file.isatty() or logger.getEffectiveLevel() > logging.INFO:
+        yield
+    else:
+        file.write(HIDE_CURSOR)
+        try:
+            yield
+        finally:
+            file.write(SHOW_CURSOR)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/status_codes.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/status_codes.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e29502cddfa9a9887a93399ab4193fb75dfe605
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/cli/status_codes.py
@@ -0,0 +1,6 @@
+SUCCESS = 0
+ERROR = 1
+UNKNOWN_ERROR = 2
+VIRTUALENV_NOT_FOUND = 3
+PREVIOUS_BUILD_DIR_ERROR = 4
+NO_MATCHES_FOUND = 23
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..858a41014169b8f0eb1b905fa3bb69c753a1bda5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/__init__.py
@@ -0,0 +1,132 @@
+"""
+Package containing all pip commands
+"""
+
+import importlib
+from collections import namedtuple
+from typing import Any, Dict, Optional
+
+from pip._internal.cli.base_command import Command
+
+CommandInfo = namedtuple("CommandInfo", "module_path, class_name, summary")
+
+# This dictionary does a bunch of heavy lifting for help output:
+# - Enables avoiding additional (costly) imports for presenting `--help`.
+# - The ordering matters for help display.
+#
+# Even though the module path starts with the same "pip._internal.commands"
+# prefix, the full path makes testing easier (specifically when modifying
+# `commands_dict` in test setup / teardown).
+commands_dict: Dict[str, CommandInfo] = {
+    "install": CommandInfo(
+        "pip._internal.commands.install",
+        "InstallCommand",
+        "Install packages.",
+    ),
+    "download": CommandInfo(
+        "pip._internal.commands.download",
+        "DownloadCommand",
+        "Download packages.",
+    ),
+    "uninstall": CommandInfo(
+        "pip._internal.commands.uninstall",
+        "UninstallCommand",
+        "Uninstall packages.",
+    ),
+    "freeze": CommandInfo(
+        "pip._internal.commands.freeze",
+        "FreezeCommand",
+        "Output installed packages in requirements format.",
+    ),
+    "inspect": CommandInfo(
+        "pip._internal.commands.inspect",
+        "InspectCommand",
+        "Inspect the python environment.",
+    ),
+    "list": CommandInfo(
+        "pip._internal.commands.list",
+        "ListCommand",
+        "List installed packages.",
+    ),
+    "show": CommandInfo(
+        "pip._internal.commands.show",
+        "ShowCommand",
+        "Show information about installed packages.",
+    ),
+    "check": CommandInfo(
+        "pip._internal.commands.check",
+        "CheckCommand",
+        "Verify installed packages have compatible dependencies.",
+    ),
+    "config": CommandInfo(
+        "pip._internal.commands.configuration",
+        "ConfigurationCommand",
+        "Manage local and global configuration.",
+    ),
+    "search": CommandInfo(
+        "pip._internal.commands.search",
+        "SearchCommand",
+        "Search PyPI for packages.",
+    ),
+    "cache": CommandInfo(
+        "pip._internal.commands.cache",
+        "CacheCommand",
+        "Inspect and manage pip's wheel cache.",
+    ),
+    "index": CommandInfo(
+        "pip._internal.commands.index",
+        "IndexCommand",
+        "Inspect information available from package indexes.",
+    ),
+    "wheel": CommandInfo(
+        "pip._internal.commands.wheel",
+        "WheelCommand",
+        "Build wheels from your requirements.",
+    ),
+    "hash": CommandInfo(
+        "pip._internal.commands.hash",
+        "HashCommand",
+        "Compute hashes of package archives.",
+    ),
+    "completion": CommandInfo(
+        "pip._internal.commands.completion",
+        "CompletionCommand",
+        "A helper command used for command completion.",
+    ),
+    "debug": CommandInfo(
+        "pip._internal.commands.debug",
+        "DebugCommand",
+        "Show information useful for debugging.",
+    ),
+    "help": CommandInfo(
+        "pip._internal.commands.help",
+        "HelpCommand",
+        "Show help for commands.",
+    ),
+}
+
+
+def create_command(name: str, **kwargs: Any) -> Command:
+    """
+    Create an instance of the Command class with the given name.
+    """
+    module_path, class_name, summary = commands_dict[name]
+    module = importlib.import_module(module_path)
+    command_class = getattr(module, class_name)
+    command = command_class(name=name, summary=summary, **kwargs)
+
+    return command
+
+
+def get_similar_commands(name: str) -> Optional[str]:
+    """Command name auto-correct."""
+    from difflib import get_close_matches
+
+    name = name.lower()
+
+    close_commands = get_close_matches(name, commands_dict.keys())
+
+    if close_commands:
+        return close_commands[0]
+    else:
+        return None
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/cache.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..c5f03302d6b03989e900cb6786946ffd01968798
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/cache.py
@@ -0,0 +1,223 @@
+import os
+import textwrap
+from optparse import Values
+from typing import Any, List
+
+import pip._internal.utils.filesystem as filesystem
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import ERROR, SUCCESS
+from pip._internal.exceptions import CommandError, PipError
+from pip._internal.utils.logging import getLogger
+
+logger = getLogger(__name__)
+
+
+class CacheCommand(Command):
+    """
+    Inspect and manage pip's wheel cache.
+
+    Subcommands:
+
+    - dir: Show the cache directory.
+    - info: Show information about the cache.
+    - list: List filenames of packages stored in the cache.
+    - remove: Remove one or more package from the cache.
+    - purge: Remove all items from the cache.
+
+    ```` can be a glob expression or a package name.
+    """
+
+    ignore_require_venv = True
+    usage = """
+        %prog dir
+        %prog info
+        %prog list [] [--format=[human, abspath]]
+        %prog remove 
+        %prog purge
+    """
+
+    def add_options(self) -> None:
+
+        self.cmd_opts.add_option(
+            "--format",
+            action="store",
+            dest="list_format",
+            default="human",
+            choices=("human", "abspath"),
+            help="Select the output format among: human (default) or abspath",
+        )
+
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        handlers = {
+            "dir": self.get_cache_dir,
+            "info": self.get_cache_info,
+            "list": self.list_cache_items,
+            "remove": self.remove_cache_items,
+            "purge": self.purge_cache,
+        }
+
+        if not options.cache_dir:
+            logger.error("pip cache commands can not function since cache is disabled.")
+            return ERROR
+
+        # Determine action
+        if not args or args[0] not in handlers:
+            logger.error(
+                "Need an action (%s) to perform.",
+                ", ".join(sorted(handlers)),
+            )
+            return ERROR
+
+        action = args[0]
+
+        # Error handling happens here, not in the action-handlers.
+        try:
+            handlers[action](options, args[1:])
+        except PipError as e:
+            logger.error(e.args[0])
+            return ERROR
+
+        return SUCCESS
+
+    def get_cache_dir(self, options: Values, args: List[Any]) -> None:
+        if args:
+            raise CommandError("Too many arguments")
+
+        logger.info(options.cache_dir)
+
+    def get_cache_info(self, options: Values, args: List[Any]) -> None:
+        if args:
+            raise CommandError("Too many arguments")
+
+        num_http_files = len(self._find_http_files(options))
+        num_packages = len(self._find_wheels(options, "*"))
+
+        http_cache_location = self._cache_dir(options, "http")
+        wheels_cache_location = self._cache_dir(options, "wheels")
+        http_cache_size = filesystem.format_directory_size(http_cache_location)
+        wheels_cache_size = filesystem.format_directory_size(wheels_cache_location)
+
+        message = (
+            textwrap.dedent(
+                """
+                    Package index page cache location: {http_cache_location}
+                    Package index page cache size: {http_cache_size}
+                    Number of HTTP files: {num_http_files}
+                    Locally built wheels location: {wheels_cache_location}
+                    Locally built wheels size: {wheels_cache_size}
+                    Number of locally built wheels: {package_count}
+                """
+            )
+            .format(
+                http_cache_location=http_cache_location,
+                http_cache_size=http_cache_size,
+                num_http_files=num_http_files,
+                wheels_cache_location=wheels_cache_location,
+                package_count=num_packages,
+                wheels_cache_size=wheels_cache_size,
+            )
+            .strip()
+        )
+
+        logger.info(message)
+
+    def list_cache_items(self, options: Values, args: List[Any]) -> None:
+        if len(args) > 1:
+            raise CommandError("Too many arguments")
+
+        if args:
+            pattern = args[0]
+        else:
+            pattern = "*"
+
+        files = self._find_wheels(options, pattern)
+        if options.list_format == "human":
+            self.format_for_human(files)
+        else:
+            self.format_for_abspath(files)
+
+    def format_for_human(self, files: List[str]) -> None:
+        if not files:
+            logger.info("No locally built wheels cached.")
+            return
+
+        results = []
+        for filename in files:
+            wheel = os.path.basename(filename)
+            size = filesystem.format_file_size(filename)
+            results.append(f" - {wheel} ({size})")
+        logger.info("Cache contents:\n")
+        logger.info("\n".join(sorted(results)))
+
+    def format_for_abspath(self, files: List[str]) -> None:
+        if not files:
+            return
+
+        results = []
+        for filename in files:
+            results.append(filename)
+
+        logger.info("\n".join(sorted(results)))
+
+    def remove_cache_items(self, options: Values, args: List[Any]) -> None:
+        if len(args) > 1:
+            raise CommandError("Too many arguments")
+
+        if not args:
+            raise CommandError("Please provide a pattern")
+
+        files = self._find_wheels(options, args[0])
+
+        no_matching_msg = "No matching packages"
+        if args[0] == "*":
+            # Only fetch http files if no specific pattern given
+            files += self._find_http_files(options)
+        else:
+            # Add the pattern to the log message
+            no_matching_msg += ' for pattern "{}"'.format(args[0])
+
+        if not files:
+            logger.warning(no_matching_msg)
+
+        for filename in files:
+            os.unlink(filename)
+            logger.verbose("Removed %s", filename)
+        logger.info("Files removed: %s", len(files))
+
+    def purge_cache(self, options: Values, args: List[Any]) -> None:
+        if args:
+            raise CommandError("Too many arguments")
+
+        return self.remove_cache_items(options, ["*"])
+
+    def _cache_dir(self, options: Values, subdir: str) -> str:
+        return os.path.join(options.cache_dir, subdir)
+
+    def _find_http_files(self, options: Values) -> List[str]:
+        http_dir = self._cache_dir(options, "http")
+        return filesystem.find_files(http_dir, "*")
+
+    def _find_wheels(self, options: Values, pattern: str) -> List[str]:
+        wheel_dir = self._cache_dir(options, "wheels")
+
+        # The wheel filename format, as specified in PEP 427, is:
+        #     {distribution}-{version}(-{build})?-{python}-{abi}-{platform}.whl
+        #
+        # Additionally, non-alphanumeric values in the distribution are
+        # normalized to underscores (_), meaning hyphens can never occur
+        # before `-{version}`.
+        #
+        # Given that information:
+        # - If the pattern we're given contains a hyphen (-), the user is
+        #   providing at least the version. Thus, we can just append `*.whl`
+        #   to match the rest of it.
+        # - If the pattern we're given doesn't contain a hyphen (-), the
+        #   user is only providing the name. Thus, we append `-*.whl` to
+        #   match the hyphen before the version, followed by anything else.
+        #
+        # PEP 427: https://www.python.org/dev/peps/pep-0427/
+        pattern = pattern + ("*.whl" if "-" in pattern else "-*.whl")
+
+        return filesystem.find_files(wheel_dir, pattern)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/check.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/check.py
new file mode 100644
index 0000000000000000000000000000000000000000..3864220b2b4a2fd3803bdff0ab9e4c3941c1f313
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/check.py
@@ -0,0 +1,53 @@
+import logging
+from optparse import Values
+from typing import List
+
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import ERROR, SUCCESS
+from pip._internal.operations.check import (
+    check_package_set,
+    create_package_set_from_installed,
+)
+from pip._internal.utils.misc import write_output
+
+logger = logging.getLogger(__name__)
+
+
+class CheckCommand(Command):
+    """Verify installed packages have compatible dependencies."""
+
+    usage = """
+      %prog [options]"""
+
+    def run(self, options: Values, args: List[str]) -> int:
+
+        package_set, parsing_probs = create_package_set_from_installed()
+        missing, conflicting = check_package_set(package_set)
+
+        for project_name in missing:
+            version = package_set[project_name].version
+            for dependency in missing[project_name]:
+                write_output(
+                    "%s %s requires %s, which is not installed.",
+                    project_name,
+                    version,
+                    dependency[0],
+                )
+
+        for project_name in conflicting:
+            version = package_set[project_name].version
+            for dep_name, dep_version, req in conflicting[project_name]:
+                write_output(
+                    "%s %s has requirement %s, but you have %s %s.",
+                    project_name,
+                    version,
+                    req,
+                    dep_name,
+                    dep_version,
+                )
+
+        if missing or conflicting or parsing_probs:
+            return ERROR
+        else:
+            write_output("No broken requirements found.")
+            return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/completion.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/completion.py
new file mode 100644
index 0000000000000000000000000000000000000000..deaa30899e64cd9fd4382d1054371679d8e713d5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/completion.py
@@ -0,0 +1,126 @@
+import sys
+import textwrap
+from optparse import Values
+from typing import List
+
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.utils.misc import get_prog
+
+BASE_COMPLETION = """
+# pip {shell} completion start{script}# pip {shell} completion end
+"""
+
+COMPLETION_SCRIPTS = {
+    "bash": """
+        _pip_completion()
+        {{
+            COMPREPLY=( $( COMP_WORDS="${{COMP_WORDS[*]}}" \\
+                           COMP_CWORD=$COMP_CWORD \\
+                           PIP_AUTO_COMPLETE=1 $1 2>/dev/null ) )
+        }}
+        complete -o default -F _pip_completion {prog}
+    """,
+    "zsh": """
+        function _pip_completion {{
+          local words cword
+          read -Ac words
+          read -cn cword
+          reply=( $( COMP_WORDS="$words[*]" \\
+                     COMP_CWORD=$(( cword-1 )) \\
+                     PIP_AUTO_COMPLETE=1 $words[1] 2>/dev/null ))
+        }}
+        compctl -K _pip_completion {prog}
+    """,
+    "fish": """
+        function __fish_complete_pip
+            set -lx COMP_WORDS (commandline -o) ""
+            set -lx COMP_CWORD ( \\
+                math (contains -i -- (commandline -t) $COMP_WORDS)-1 \\
+            )
+            set -lx PIP_AUTO_COMPLETE 1
+            string split \\  -- (eval $COMP_WORDS[1])
+        end
+        complete -fa "(__fish_complete_pip)" -c {prog}
+    """,
+    "powershell": """
+        if ((Test-Path Function:\\TabExpansion) -and -not `
+            (Test-Path Function:\\_pip_completeBackup)) {{
+            Rename-Item Function:\\TabExpansion _pip_completeBackup
+        }}
+        function TabExpansion($line, $lastWord) {{
+            $lastBlock = [regex]::Split($line, '[|;]')[-1].TrimStart()
+            if ($lastBlock.StartsWith("{prog} ")) {{
+                $Env:COMP_WORDS=$lastBlock
+                $Env:COMP_CWORD=$lastBlock.Split().Length - 1
+                $Env:PIP_AUTO_COMPLETE=1
+                (& {prog}).Split()
+                Remove-Item Env:COMP_WORDS
+                Remove-Item Env:COMP_CWORD
+                Remove-Item Env:PIP_AUTO_COMPLETE
+            }}
+            elseif (Test-Path Function:\\_pip_completeBackup) {{
+                # Fall back on existing tab expansion
+                _pip_completeBackup $line $lastWord
+            }}
+        }}
+    """,
+}
+
+
+class CompletionCommand(Command):
+    """A helper command to be used for command completion."""
+
+    ignore_require_venv = True
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "--bash",
+            "-b",
+            action="store_const",
+            const="bash",
+            dest="shell",
+            help="Emit completion code for bash",
+        )
+        self.cmd_opts.add_option(
+            "--zsh",
+            "-z",
+            action="store_const",
+            const="zsh",
+            dest="shell",
+            help="Emit completion code for zsh",
+        )
+        self.cmd_opts.add_option(
+            "--fish",
+            "-f",
+            action="store_const",
+            const="fish",
+            dest="shell",
+            help="Emit completion code for fish",
+        )
+        self.cmd_opts.add_option(
+            "--powershell",
+            "-p",
+            action="store_const",
+            const="powershell",
+            dest="shell",
+            help="Emit completion code for powershell",
+        )
+
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        """Prints the completion code of the given shell"""
+        shells = COMPLETION_SCRIPTS.keys()
+        shell_options = ["--" + shell for shell in sorted(shells)]
+        if options.shell in shells:
+            script = textwrap.dedent(
+                COMPLETION_SCRIPTS.get(options.shell, "").format(prog=get_prog())
+            )
+            print(BASE_COMPLETION.format(script=script, shell=options.shell))
+            return SUCCESS
+        else:
+            sys.stderr.write(
+                "ERROR: You must pass {}\n".format(" or ".join(shell_options))
+            )
+            return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/configuration.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/configuration.py
new file mode 100644
index 0000000000000000000000000000000000000000..84b134e490b081d661daf69f98e0b9b1fdddd36f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/configuration.py
@@ -0,0 +1,282 @@
+import logging
+import os
+import subprocess
+from optparse import Values
+from typing import Any, List, Optional
+
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import ERROR, SUCCESS
+from pip._internal.configuration import (
+    Configuration,
+    Kind,
+    get_configuration_files,
+    kinds,
+)
+from pip._internal.exceptions import PipError
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.misc import get_prog, write_output
+
+logger = logging.getLogger(__name__)
+
+
+class ConfigurationCommand(Command):
+    """
+    Manage local and global configuration.
+
+    Subcommands:
+
+    - list: List the active configuration (or from the file specified)
+    - edit: Edit the configuration file in an editor
+    - get: Get the value associated with command.option
+    - set: Set the command.option=value
+    - unset: Unset the value associated with command.option
+    - debug: List the configuration files and values defined under them
+
+    Configuration keys should be dot separated command and option name,
+    with the special prefix "global" affecting any command. For example,
+    "pip config set global.index-url https://example.org/" would configure
+    the index url for all commands, but "pip config set download.timeout 10"
+    would configure a 10 second timeout only for "pip download" commands.
+
+    If none of --user, --global and --site are passed, a virtual
+    environment configuration file is used if one is active and the file
+    exists. Otherwise, all modifications happen to the user file by
+    default.
+    """
+
+    ignore_require_venv = True
+    usage = """
+        %prog [] list
+        %prog [] [--editor ] edit
+
+        %prog [] get command.option
+        %prog [] set command.option value
+        %prog [] unset command.option
+        %prog [] debug
+    """
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "--editor",
+            dest="editor",
+            action="store",
+            default=None,
+            help=(
+                "Editor to use to edit the file. Uses VISUAL or EDITOR "
+                "environment variables if not provided."
+            ),
+        )
+
+        self.cmd_opts.add_option(
+            "--global",
+            dest="global_file",
+            action="store_true",
+            default=False,
+            help="Use the system-wide configuration file only",
+        )
+
+        self.cmd_opts.add_option(
+            "--user",
+            dest="user_file",
+            action="store_true",
+            default=False,
+            help="Use the user configuration file only",
+        )
+
+        self.cmd_opts.add_option(
+            "--site",
+            dest="site_file",
+            action="store_true",
+            default=False,
+            help="Use the current environment configuration file only",
+        )
+
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        handlers = {
+            "list": self.list_values,
+            "edit": self.open_in_editor,
+            "get": self.get_name,
+            "set": self.set_name_value,
+            "unset": self.unset_name,
+            "debug": self.list_config_values,
+        }
+
+        # Determine action
+        if not args or args[0] not in handlers:
+            logger.error(
+                "Need an action (%s) to perform.",
+                ", ".join(sorted(handlers)),
+            )
+            return ERROR
+
+        action = args[0]
+
+        # Determine which configuration files are to be loaded
+        #    Depends on whether the command is modifying.
+        try:
+            load_only = self._determine_file(
+                options, need_value=(action in ["get", "set", "unset", "edit"])
+            )
+        except PipError as e:
+            logger.error(e.args[0])
+            return ERROR
+
+        # Load a new configuration
+        self.configuration = Configuration(
+            isolated=options.isolated_mode, load_only=load_only
+        )
+        self.configuration.load()
+
+        # Error handling happens here, not in the action-handlers.
+        try:
+            handlers[action](options, args[1:])
+        except PipError as e:
+            logger.error(e.args[0])
+            return ERROR
+
+        return SUCCESS
+
+    def _determine_file(self, options: Values, need_value: bool) -> Optional[Kind]:
+        file_options = [
+            key
+            for key, value in (
+                (kinds.USER, options.user_file),
+                (kinds.GLOBAL, options.global_file),
+                (kinds.SITE, options.site_file),
+            )
+            if value
+        ]
+
+        if not file_options:
+            if not need_value:
+                return None
+            # Default to user, unless there's a site file.
+            elif any(
+                os.path.exists(site_config_file)
+                for site_config_file in get_configuration_files()[kinds.SITE]
+            ):
+                return kinds.SITE
+            else:
+                return kinds.USER
+        elif len(file_options) == 1:
+            return file_options[0]
+
+        raise PipError(
+            "Need exactly one file to operate upon "
+            "(--user, --site, --global) to perform."
+        )
+
+    def list_values(self, options: Values, args: List[str]) -> None:
+        self._get_n_args(args, "list", n=0)
+
+        for key, value in sorted(self.configuration.items()):
+            write_output("%s=%r", key, value)
+
+    def get_name(self, options: Values, args: List[str]) -> None:
+        key = self._get_n_args(args, "get [name]", n=1)
+        value = self.configuration.get_value(key)
+
+        write_output("%s", value)
+
+    def set_name_value(self, options: Values, args: List[str]) -> None:
+        key, value = self._get_n_args(args, "set [name] [value]", n=2)
+        self.configuration.set_value(key, value)
+
+        self._save_configuration()
+
+    def unset_name(self, options: Values, args: List[str]) -> None:
+        key = self._get_n_args(args, "unset [name]", n=1)
+        self.configuration.unset_value(key)
+
+        self._save_configuration()
+
+    def list_config_values(self, options: Values, args: List[str]) -> None:
+        """List config key-value pairs across different config files"""
+        self._get_n_args(args, "debug", n=0)
+
+        self.print_env_var_values()
+        # Iterate over config files and print if they exist, and the
+        # key-value pairs present in them if they do
+        for variant, files in sorted(self.configuration.iter_config_files()):
+            write_output("%s:", variant)
+            for fname in files:
+                with indent_log():
+                    file_exists = os.path.exists(fname)
+                    write_output("%s, exists: %r", fname, file_exists)
+                    if file_exists:
+                        self.print_config_file_values(variant)
+
+    def print_config_file_values(self, variant: Kind) -> None:
+        """Get key-value pairs from the file of a variant"""
+        for name, value in self.configuration.get_values_in_config(variant).items():
+            with indent_log():
+                write_output("%s: %s", name, value)
+
+    def print_env_var_values(self) -> None:
+        """Get key-values pairs present as environment variables"""
+        write_output("%s:", "env_var")
+        with indent_log():
+            for key, value in sorted(self.configuration.get_environ_vars()):
+                env_var = f"PIP_{key.upper()}"
+                write_output("%s=%r", env_var, value)
+
+    def open_in_editor(self, options: Values, args: List[str]) -> None:
+        editor = self._determine_editor(options)
+
+        fname = self.configuration.get_file_to_edit()
+        if fname is None:
+            raise PipError("Could not determine appropriate file.")
+        elif '"' in fname:
+            # This shouldn't happen, unless we see a username like that.
+            # If that happens, we'd appreciate a pull request fixing this.
+            raise PipError(
+                f'Can not open an editor for a file name containing "\n{fname}'
+            )
+
+        try:
+            subprocess.check_call(f'{editor} "{fname}"', shell=True)
+        except FileNotFoundError as e:
+            if not e.filename:
+                e.filename = editor
+            raise
+        except subprocess.CalledProcessError as e:
+            raise PipError(
+                "Editor Subprocess exited with exit code {}".format(e.returncode)
+            )
+
+    def _get_n_args(self, args: List[str], example: str, n: int) -> Any:
+        """Helper to make sure the command got the right number of arguments"""
+        if len(args) != n:
+            msg = (
+                "Got unexpected number of arguments, expected {}. "
+                '(example: "{} config {}")'
+            ).format(n, get_prog(), example)
+            raise PipError(msg)
+
+        if n == 1:
+            return args[0]
+        else:
+            return args
+
+    def _save_configuration(self) -> None:
+        # We successfully ran a modifying command. Need to save the
+        # configuration.
+        try:
+            self.configuration.save()
+        except Exception:
+            logger.exception(
+                "Unable to save configuration. Please report this as a bug."
+            )
+            raise PipError("Internal Error.")
+
+    def _determine_editor(self, options: Values) -> str:
+        if options.editor is not None:
+            return options.editor
+        elif "VISUAL" in os.environ:
+            return os.environ["VISUAL"]
+        elif "EDITOR" in os.environ:
+            return os.environ["EDITOR"]
+        else:
+            raise PipError("Could not determine editor to use.")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/debug.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/debug.py
new file mode 100644
index 0000000000000000000000000000000000000000..2a3e7d298f393ed8532e4f11913635efc94cb329
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/debug.py
@@ -0,0 +1,199 @@
+import importlib.resources
+import locale
+import logging
+import os
+import sys
+from optparse import Values
+from types import ModuleType
+from typing import Any, Dict, List, Optional
+
+import pip._vendor
+from pip._vendor.certifi import where
+from pip._vendor.packaging.version import parse as parse_version
+
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.cmdoptions import make_target_python
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.configuration import Configuration
+from pip._internal.metadata import get_environment
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.misc import get_pip_version
+
+logger = logging.getLogger(__name__)
+
+
+def show_value(name: str, value: Any) -> None:
+    logger.info("%s: %s", name, value)
+
+
+def show_sys_implementation() -> None:
+    logger.info("sys.implementation:")
+    implementation_name = sys.implementation.name
+    with indent_log():
+        show_value("name", implementation_name)
+
+
+def create_vendor_txt_map() -> Dict[str, str]:
+    with importlib.resources.open_text("pip._vendor", "vendor.txt") as f:
+        # Purge non version specifying lines.
+        # Also, remove any space prefix or suffixes (including comments).
+        lines = [
+            line.strip().split(" ", 1)[0] for line in f.readlines() if "==" in line
+        ]
+
+    # Transform into "module" -> version dict.
+    return dict(line.split("==", 1) for line in lines)
+
+
+def get_module_from_module_name(module_name: str) -> ModuleType:
+    # Module name can be uppercase in vendor.txt for some reason...
+    module_name = module_name.lower().replace("-", "_")
+    # PATCH: setuptools is actually only pkg_resources.
+    if module_name == "setuptools":
+        module_name = "pkg_resources"
+
+    __import__(f"pip._vendor.{module_name}", globals(), locals(), level=0)
+    return getattr(pip._vendor, module_name)
+
+
+def get_vendor_version_from_module(module_name: str) -> Optional[str]:
+    module = get_module_from_module_name(module_name)
+    version = getattr(module, "__version__", None)
+
+    if not version:
+        # Try to find version in debundled module info.
+        assert module.__file__ is not None
+        env = get_environment([os.path.dirname(module.__file__)])
+        dist = env.get_distribution(module_name)
+        if dist:
+            version = str(dist.version)
+
+    return version
+
+
+def show_actual_vendor_versions(vendor_txt_versions: Dict[str, str]) -> None:
+    """Log the actual version and print extra info if there is
+    a conflict or if the actual version could not be imported.
+    """
+    for module_name, expected_version in vendor_txt_versions.items():
+        extra_message = ""
+        actual_version = get_vendor_version_from_module(module_name)
+        if not actual_version:
+            extra_message = (
+                " (Unable to locate actual module version, using"
+                " vendor.txt specified version)"
+            )
+            actual_version = expected_version
+        elif parse_version(actual_version) != parse_version(expected_version):
+            extra_message = (
+                " (CONFLICT: vendor.txt suggests version should"
+                " be {})".format(expected_version)
+            )
+        logger.info("%s==%s%s", module_name, actual_version, extra_message)
+
+
+def show_vendor_versions() -> None:
+    logger.info("vendored library versions:")
+
+    vendor_txt_versions = create_vendor_txt_map()
+    with indent_log():
+        show_actual_vendor_versions(vendor_txt_versions)
+
+
+def show_tags(options: Values) -> None:
+    tag_limit = 10
+
+    target_python = make_target_python(options)
+    tags = target_python.get_tags()
+
+    # Display the target options that were explicitly provided.
+    formatted_target = target_python.format_given()
+    suffix = ""
+    if formatted_target:
+        suffix = f" (target: {formatted_target})"
+
+    msg = "Compatible tags: {}{}".format(len(tags), suffix)
+    logger.info(msg)
+
+    if options.verbose < 1 and len(tags) > tag_limit:
+        tags_limited = True
+        tags = tags[:tag_limit]
+    else:
+        tags_limited = False
+
+    with indent_log():
+        for tag in tags:
+            logger.info(str(tag))
+
+        if tags_limited:
+            msg = (
+                "...\n[First {tag_limit} tags shown. Pass --verbose to show all.]"
+            ).format(tag_limit=tag_limit)
+            logger.info(msg)
+
+
+def ca_bundle_info(config: Configuration) -> str:
+    levels = set()
+    for key, _ in config.items():
+        levels.add(key.split(".")[0])
+
+    if not levels:
+        return "Not specified"
+
+    levels_that_override_global = ["install", "wheel", "download"]
+    global_overriding_level = [
+        level for level in levels if level in levels_that_override_global
+    ]
+    if not global_overriding_level:
+        return "global"
+
+    if "global" in levels:
+        levels.remove("global")
+    return ", ".join(levels)
+
+
+class DebugCommand(Command):
+    """
+    Display debug information.
+    """
+
+    usage = """
+      %prog """
+    ignore_require_venv = True
+
+    def add_options(self) -> None:
+        cmdoptions.add_target_python_options(self.cmd_opts)
+        self.parser.insert_option_group(0, self.cmd_opts)
+        self.parser.config.load()
+
+    def run(self, options: Values, args: List[str]) -> int:
+        logger.warning(
+            "This command is only meant for debugging. "
+            "Do not use this with automation for parsing and getting these "
+            "details, since the output and options of this command may "
+            "change without notice."
+        )
+        show_value("pip version", get_pip_version())
+        show_value("sys.version", sys.version)
+        show_value("sys.executable", sys.executable)
+        show_value("sys.getdefaultencoding", sys.getdefaultencoding())
+        show_value("sys.getfilesystemencoding", sys.getfilesystemencoding())
+        show_value(
+            "locale.getpreferredencoding",
+            locale.getpreferredencoding(),
+        )
+        show_value("sys.platform", sys.platform)
+        show_sys_implementation()
+
+        show_value("'cert' config value", ca_bundle_info(self.parser.config))
+        show_value("REQUESTS_CA_BUNDLE", os.environ.get("REQUESTS_CA_BUNDLE"))
+        show_value("CURL_CA_BUNDLE", os.environ.get("CURL_CA_BUNDLE"))
+        show_value("pip._vendor.certifi.where()", where())
+        show_value("pip._vendor.DEBUNDLED", pip._vendor.DEBUNDLED)
+
+        show_vendor_versions()
+
+        show_tags(options)
+
+        return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/download.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/download.py
new file mode 100644
index 0000000000000000000000000000000000000000..4132e0898831bc18faa313f103f55e7d5a1ea2b7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/download.py
@@ -0,0 +1,149 @@
+import logging
+import os
+from optparse import Values
+from typing import List
+
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.cmdoptions import make_target_python
+from pip._internal.cli.req_command import RequirementCommand, with_cleanup
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.operations.build.build_tracker import get_build_tracker
+from pip._internal.req.req_install import (
+    LegacySetupPyOptionsCheckMode,
+    check_legacy_setup_py_options,
+)
+from pip._internal.utils.misc import ensure_dir, normalize_path, write_output
+from pip._internal.utils.temp_dir import TempDirectory
+
+logger = logging.getLogger(__name__)
+
+
+class DownloadCommand(RequirementCommand):
+    """
+    Download packages from:
+
+    - PyPI (and other indexes) using requirement specifiers.
+    - VCS project urls.
+    - Local project directories.
+    - Local or remote source archives.
+
+    pip also supports downloading from "requirements files", which provide
+    an easy way to specify a whole environment to be downloaded.
+    """
+
+    usage = """
+      %prog [options]  [package-index-options] ...
+      %prog [options] -r  [package-index-options] ...
+      %prog [options]  ...
+      %prog [options]  ...
+      %prog [options]  ..."""
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(cmdoptions.constraints())
+        self.cmd_opts.add_option(cmdoptions.requirements())
+        self.cmd_opts.add_option(cmdoptions.no_deps())
+        self.cmd_opts.add_option(cmdoptions.global_options())
+        self.cmd_opts.add_option(cmdoptions.no_binary())
+        self.cmd_opts.add_option(cmdoptions.only_binary())
+        self.cmd_opts.add_option(cmdoptions.prefer_binary())
+        self.cmd_opts.add_option(cmdoptions.src())
+        self.cmd_opts.add_option(cmdoptions.pre())
+        self.cmd_opts.add_option(cmdoptions.require_hashes())
+        self.cmd_opts.add_option(cmdoptions.progress_bar())
+        self.cmd_opts.add_option(cmdoptions.no_build_isolation())
+        self.cmd_opts.add_option(cmdoptions.use_pep517())
+        self.cmd_opts.add_option(cmdoptions.no_use_pep517())
+        self.cmd_opts.add_option(cmdoptions.check_build_deps())
+        self.cmd_opts.add_option(cmdoptions.ignore_requires_python())
+
+        self.cmd_opts.add_option(
+            "-d",
+            "--dest",
+            "--destination-dir",
+            "--destination-directory",
+            dest="download_dir",
+            metavar="dir",
+            default=os.curdir,
+            help="Download packages into .",
+        )
+
+        cmdoptions.add_target_python_options(self.cmd_opts)
+
+        index_opts = cmdoptions.make_option_group(
+            cmdoptions.index_group,
+            self.parser,
+        )
+
+        self.parser.insert_option_group(0, index_opts)
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    @with_cleanup
+    def run(self, options: Values, args: List[str]) -> int:
+
+        options.ignore_installed = True
+        # editable doesn't really make sense for `pip download`, but the bowels
+        # of the RequirementSet code require that property.
+        options.editables = []
+
+        cmdoptions.check_dist_restriction(options)
+
+        options.download_dir = normalize_path(options.download_dir)
+        ensure_dir(options.download_dir)
+
+        session = self.get_default_session(options)
+
+        target_python = make_target_python(options)
+        finder = self._build_package_finder(
+            options=options,
+            session=session,
+            target_python=target_python,
+            ignore_requires_python=options.ignore_requires_python,
+        )
+
+        build_tracker = self.enter_context(get_build_tracker())
+
+        directory = TempDirectory(
+            delete=not options.no_clean,
+            kind="download",
+            globally_managed=True,
+        )
+
+        reqs = self.get_requirements(args, options, finder, session)
+        check_legacy_setup_py_options(
+            options, reqs, LegacySetupPyOptionsCheckMode.DOWNLOAD
+        )
+
+        preparer = self.make_requirement_preparer(
+            temp_build_dir=directory,
+            options=options,
+            build_tracker=build_tracker,
+            session=session,
+            finder=finder,
+            download_dir=options.download_dir,
+            use_user_site=False,
+            verbosity=self.verbosity,
+        )
+
+        resolver = self.make_resolver(
+            preparer=preparer,
+            finder=finder,
+            options=options,
+            ignore_requires_python=options.ignore_requires_python,
+            use_pep517=options.use_pep517,
+            py_version_info=options.python_version,
+        )
+
+        self.trace_basic_info(finder)
+
+        requirement_set = resolver.resolve(reqs, check_supported_wheels=True)
+
+        downloaded: List[str] = []
+        for req in requirement_set.requirements.values():
+            if req.satisfied_by is None:
+                assert req.name is not None
+                preparer.save_linked_requirement(req)
+                downloaded.append(req.name)
+        if downloaded:
+            write_output("Successfully downloaded %s", " ".join(downloaded))
+
+        return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/freeze.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/freeze.py
new file mode 100644
index 0000000000000000000000000000000000000000..5fa6d39b2c7c74635f9570c1e1665d03a45024b2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/freeze.py
@@ -0,0 +1,97 @@
+import sys
+from optparse import Values
+from typing import List
+
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.operations.freeze import freeze
+from pip._internal.utils.compat import stdlib_pkgs
+
+DEV_PKGS = {"pip", "setuptools", "distribute", "wheel"}
+
+
+class FreezeCommand(Command):
+    """
+    Output installed packages in requirements format.
+
+    packages are listed in a case-insensitive sorted order.
+    """
+
+    usage = """
+      %prog [options]"""
+    log_streams = ("ext://sys.stderr", "ext://sys.stderr")
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "-r",
+            "--requirement",
+            dest="requirements",
+            action="append",
+            default=[],
+            metavar="file",
+            help=(
+                "Use the order in the given requirements file and its "
+                "comments when generating output. This option can be "
+                "used multiple times."
+            ),
+        )
+        self.cmd_opts.add_option(
+            "-l",
+            "--local",
+            dest="local",
+            action="store_true",
+            default=False,
+            help=(
+                "If in a virtualenv that has global access, do not output "
+                "globally-installed packages."
+            ),
+        )
+        self.cmd_opts.add_option(
+            "--user",
+            dest="user",
+            action="store_true",
+            default=False,
+            help="Only output packages installed in user-site.",
+        )
+        self.cmd_opts.add_option(cmdoptions.list_path())
+        self.cmd_opts.add_option(
+            "--all",
+            dest="freeze_all",
+            action="store_true",
+            help=(
+                "Do not skip these packages in the output:"
+                " {}".format(", ".join(DEV_PKGS))
+            ),
+        )
+        self.cmd_opts.add_option(
+            "--exclude-editable",
+            dest="exclude_editable",
+            action="store_true",
+            help="Exclude editable package from output.",
+        )
+        self.cmd_opts.add_option(cmdoptions.list_exclude())
+
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        skip = set(stdlib_pkgs)
+        if not options.freeze_all:
+            skip.update(DEV_PKGS)
+
+        if options.excludes:
+            skip.update(options.excludes)
+
+        cmdoptions.check_list_path_option(options)
+
+        for line in freeze(
+            requirement=options.requirements,
+            local_only=options.local,
+            user_only=options.user,
+            paths=options.path,
+            isolated=options.isolated_mode,
+            skip=skip,
+            exclude_editable=options.exclude_editable,
+        ):
+            sys.stdout.write(line + "\n")
+        return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/hash.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/hash.py
new file mode 100644
index 0000000000000000000000000000000000000000..042dac813e74b8187c3754cb9a937c7f7183e331
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/hash.py
@@ -0,0 +1,59 @@
+import hashlib
+import logging
+import sys
+from optparse import Values
+from typing import List
+
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import ERROR, SUCCESS
+from pip._internal.utils.hashes import FAVORITE_HASH, STRONG_HASHES
+from pip._internal.utils.misc import read_chunks, write_output
+
+logger = logging.getLogger(__name__)
+
+
+class HashCommand(Command):
+    """
+    Compute a hash of a local package archive.
+
+    These can be used with --hash in a requirements file to do repeatable
+    installs.
+    """
+
+    usage = "%prog [options]  ..."
+    ignore_require_venv = True
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "-a",
+            "--algorithm",
+            dest="algorithm",
+            choices=STRONG_HASHES,
+            action="store",
+            default=FAVORITE_HASH,
+            help="The hash algorithm to use: one of {}".format(
+                ", ".join(STRONG_HASHES)
+            ),
+        )
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        if not args:
+            self.parser.print_usage(sys.stderr)
+            return ERROR
+
+        algorithm = options.algorithm
+        for path in args:
+            write_output(
+                "%s:\n--hash=%s:%s", path, algorithm, _hash_of_file(path, algorithm)
+            )
+        return SUCCESS
+
+
+def _hash_of_file(path: str, algorithm: str) -> str:
+    """Return the hash digest of a file."""
+    with open(path, "rb") as archive:
+        hash = hashlib.new(algorithm)
+        for chunk in read_chunks(archive):
+            hash.update(chunk)
+    return hash.hexdigest()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/help.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/help.py
new file mode 100644
index 0000000000000000000000000000000000000000..62066318b74dcc5c32bcd24b9493fb34d1ce52d7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/help.py
@@ -0,0 +1,41 @@
+from optparse import Values
+from typing import List
+
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.exceptions import CommandError
+
+
+class HelpCommand(Command):
+    """Show help for commands"""
+
+    usage = """
+      %prog """
+    ignore_require_venv = True
+
+    def run(self, options: Values, args: List[str]) -> int:
+        from pip._internal.commands import (
+            commands_dict,
+            create_command,
+            get_similar_commands,
+        )
+
+        try:
+            # 'pip help' with no args is handled by pip.__init__.parseopt()
+            cmd_name = args[0]  # the command we need help for
+        except IndexError:
+            return SUCCESS
+
+        if cmd_name not in commands_dict:
+            guess = get_similar_commands(cmd_name)
+
+            msg = [f'unknown command "{cmd_name}"']
+            if guess:
+                msg.append(f'maybe you meant "{guess}"')
+
+            raise CommandError(" - ".join(msg))
+
+        command = create_command(cmd_name)
+        command.parser.print_help()
+
+        return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/index.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/index.py
new file mode 100644
index 0000000000000000000000000000000000000000..7267effed2413ba315d0a1af8490ec677c227662
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/index.py
@@ -0,0 +1,139 @@
+import logging
+from optparse import Values
+from typing import Any, Iterable, List, Optional, Union
+
+from pip._vendor.packaging.version import LegacyVersion, Version
+
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.req_command import IndexGroupCommand
+from pip._internal.cli.status_codes import ERROR, SUCCESS
+from pip._internal.commands.search import print_dist_installation_info
+from pip._internal.exceptions import CommandError, DistributionNotFound, PipError
+from pip._internal.index.collector import LinkCollector
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.models.selection_prefs import SelectionPreferences
+from pip._internal.models.target_python import TargetPython
+from pip._internal.network.session import PipSession
+from pip._internal.utils.misc import write_output
+
+logger = logging.getLogger(__name__)
+
+
+class IndexCommand(IndexGroupCommand):
+    """
+    Inspect information available from package indexes.
+    """
+
+    ignore_require_venv = True
+    usage = """
+        %prog versions 
+    """
+
+    def add_options(self) -> None:
+        cmdoptions.add_target_python_options(self.cmd_opts)
+
+        self.cmd_opts.add_option(cmdoptions.ignore_requires_python())
+        self.cmd_opts.add_option(cmdoptions.pre())
+        self.cmd_opts.add_option(cmdoptions.no_binary())
+        self.cmd_opts.add_option(cmdoptions.only_binary())
+
+        index_opts = cmdoptions.make_option_group(
+            cmdoptions.index_group,
+            self.parser,
+        )
+
+        self.parser.insert_option_group(0, index_opts)
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        handlers = {
+            "versions": self.get_available_package_versions,
+        }
+
+        logger.warning(
+            "pip index is currently an experimental command. "
+            "It may be removed/changed in a future release "
+            "without prior warning."
+        )
+
+        # Determine action
+        if not args or args[0] not in handlers:
+            logger.error(
+                "Need an action (%s) to perform.",
+                ", ".join(sorted(handlers)),
+            )
+            return ERROR
+
+        action = args[0]
+
+        # Error handling happens here, not in the action-handlers.
+        try:
+            handlers[action](options, args[1:])
+        except PipError as e:
+            logger.error(e.args[0])
+            return ERROR
+
+        return SUCCESS
+
+    def _build_package_finder(
+        self,
+        options: Values,
+        session: PipSession,
+        target_python: Optional[TargetPython] = None,
+        ignore_requires_python: Optional[bool] = None,
+    ) -> PackageFinder:
+        """
+        Create a package finder appropriate to the index command.
+        """
+        link_collector = LinkCollector.create(session, options=options)
+
+        # Pass allow_yanked=False to ignore yanked versions.
+        selection_prefs = SelectionPreferences(
+            allow_yanked=False,
+            allow_all_prereleases=options.pre,
+            ignore_requires_python=ignore_requires_python,
+        )
+
+        return PackageFinder.create(
+            link_collector=link_collector,
+            selection_prefs=selection_prefs,
+            target_python=target_python,
+        )
+
+    def get_available_package_versions(self, options: Values, args: List[Any]) -> None:
+        if len(args) != 1:
+            raise CommandError("You need to specify exactly one argument")
+
+        target_python = cmdoptions.make_target_python(options)
+        query = args[0]
+
+        with self._build_session(options) as session:
+            finder = self._build_package_finder(
+                options=options,
+                session=session,
+                target_python=target_python,
+                ignore_requires_python=options.ignore_requires_python,
+            )
+
+            versions: Iterable[Union[LegacyVersion, Version]] = (
+                candidate.version for candidate in finder.find_all_candidates(query)
+            )
+
+            if not options.pre:
+                # Remove prereleases
+                versions = (
+                    version for version in versions if not version.is_prerelease
+                )
+            versions = set(versions)
+
+            if not versions:
+                raise DistributionNotFound(
+                    "No matching distribution found for {}".format(query)
+                )
+
+            formatted_versions = [str(ver) for ver in sorted(versions, reverse=True)]
+            latest = formatted_versions[0]
+
+        write_output("{} ({})".format(query, latest))
+        write_output("Available versions: {}".format(", ".join(formatted_versions)))
+        print_dist_installation_info(query, latest)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/inspect.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/inspect.py
new file mode 100644
index 0000000000000000000000000000000000000000..27c8fa3d5b6999c77dad7aece312a5d6cf12ab48
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/inspect.py
@@ -0,0 +1,92 @@
+import logging
+from optparse import Values
+from typing import Any, Dict, List
+
+from pip._vendor.packaging.markers import default_environment
+from pip._vendor.rich import print_json
+
+from pip import __version__
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.req_command import Command
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.metadata import BaseDistribution, get_environment
+from pip._internal.utils.compat import stdlib_pkgs
+from pip._internal.utils.urls import path_to_url
+
+logger = logging.getLogger(__name__)
+
+
+class InspectCommand(Command):
+    """
+    Inspect the content of a Python environment and produce a report in JSON format.
+    """
+
+    ignore_require_venv = True
+    usage = """
+      %prog [options]"""
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "--local",
+            action="store_true",
+            default=False,
+            help=(
+                "If in a virtualenv that has global access, do not list "
+                "globally-installed packages."
+            ),
+        )
+        self.cmd_opts.add_option(
+            "--user",
+            dest="user",
+            action="store_true",
+            default=False,
+            help="Only output packages installed in user-site.",
+        )
+        self.cmd_opts.add_option(cmdoptions.list_path())
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        cmdoptions.check_list_path_option(options)
+        dists = get_environment(options.path).iter_installed_distributions(
+            local_only=options.local,
+            user_only=options.user,
+            skip=set(stdlib_pkgs),
+        )
+        output = {
+            "version": "1",
+            "pip_version": __version__,
+            "installed": [self._dist_to_dict(dist) for dist in dists],
+            "environment": default_environment(),
+            # TODO tags? scheme?
+        }
+        print_json(data=output)
+        return SUCCESS
+
+    def _dist_to_dict(self, dist: BaseDistribution) -> Dict[str, Any]:
+        res: Dict[str, Any] = {
+            "metadata": dist.metadata_dict,
+            "metadata_location": dist.info_location,
+        }
+        # direct_url. Note that we don't have download_info (as in the installation
+        # report) since it is not recorded in installed metadata.
+        direct_url = dist.direct_url
+        if direct_url is not None:
+            res["direct_url"] = direct_url.to_dict()
+        else:
+            # Emulate direct_url for legacy editable installs.
+            editable_project_location = dist.editable_project_location
+            if editable_project_location is not None:
+                res["direct_url"] = {
+                    "url": path_to_url(editable_project_location),
+                    "dir_info": {
+                        "editable": True,
+                    },
+                }
+        # installer
+        installer = dist.installer
+        if dist.installer:
+            res["installer"] = installer
+        # requested
+        if dist.installed_with_dist_info:
+            res["requested"] = dist.requested
+        return res
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/install.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/install.py
new file mode 100644
index 0000000000000000000000000000000000000000..b20aeddf83590bb1dae96dfe84ae498017575ca8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/install.py
@@ -0,0 +1,873 @@
+import errno
+import json
+import operator
+import os
+import shutil
+import site
+from optparse import SUPPRESS_HELP, Values
+from typing import Iterable, List, Optional
+
+from pip._vendor.packaging.utils import canonicalize_name
+from pip._vendor.rich import print_json
+
+from pip._internal.cache import WheelCache
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.cmdoptions import make_target_python
+from pip._internal.cli.req_command import (
+    RequirementCommand,
+    warn_if_run_as_root,
+    with_cleanup,
+)
+from pip._internal.cli.status_codes import ERROR, SUCCESS
+from pip._internal.exceptions import CommandError, InstallationError
+from pip._internal.locations import get_scheme
+from pip._internal.metadata import get_environment
+from pip._internal.models.format_control import FormatControl
+from pip._internal.models.installation_report import InstallationReport
+from pip._internal.operations.build.build_tracker import get_build_tracker
+from pip._internal.operations.check import ConflictDetails, check_install_conflicts
+from pip._internal.req import install_given_reqs
+from pip._internal.req.req_install import (
+    InstallRequirement,
+    LegacySetupPyOptionsCheckMode,
+    check_legacy_setup_py_options,
+)
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.deprecation import (
+    LegacyInstallReasonFailedBdistWheel,
+    deprecated,
+)
+from pip._internal.utils.distutils_args import parse_distutils_args
+from pip._internal.utils.filesystem import test_writable_dir
+from pip._internal.utils.logging import getLogger
+from pip._internal.utils.misc import (
+    check_externally_managed,
+    ensure_dir,
+    get_pip_version,
+    protect_pip_from_modification_on_windows,
+    write_output,
+)
+from pip._internal.utils.temp_dir import TempDirectory
+from pip._internal.utils.virtualenv import (
+    running_under_virtualenv,
+    virtualenv_no_global,
+)
+from pip._internal.wheel_builder import (
+    BdistWheelAllowedPredicate,
+    build,
+    should_build_for_install_command,
+)
+
+logger = getLogger(__name__)
+
+
+def get_check_bdist_wheel_allowed(
+    format_control: FormatControl,
+) -> BdistWheelAllowedPredicate:
+    def check_binary_allowed(req: InstallRequirement) -> bool:
+        canonical_name = canonicalize_name(req.name or "")
+        allowed_formats = format_control.get_allowed_formats(canonical_name)
+        return "binary" in allowed_formats
+
+    return check_binary_allowed
+
+
+class InstallCommand(RequirementCommand):
+    """
+    Install packages from:
+
+    - PyPI (and other indexes) using requirement specifiers.
+    - VCS project urls.
+    - Local project directories.
+    - Local or remote source archives.
+
+    pip also supports installing from "requirements files", which provide
+    an easy way to specify a whole environment to be installed.
+    """
+
+    usage = """
+      %prog [options]  [package-index-options] ...
+      %prog [options] -r  [package-index-options] ...
+      %prog [options] [-e]  ...
+      %prog [options] [-e]  ...
+      %prog [options]  ..."""
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(cmdoptions.requirements())
+        self.cmd_opts.add_option(cmdoptions.constraints())
+        self.cmd_opts.add_option(cmdoptions.no_deps())
+        self.cmd_opts.add_option(cmdoptions.pre())
+
+        self.cmd_opts.add_option(cmdoptions.editable())
+        self.cmd_opts.add_option(
+            "--dry-run",
+            action="store_true",
+            dest="dry_run",
+            default=False,
+            help=(
+                "Don't actually install anything, just print what would be. "
+                "Can be used in combination with --ignore-installed "
+                "to 'resolve' the requirements."
+            ),
+        )
+        self.cmd_opts.add_option(
+            "-t",
+            "--target",
+            dest="target_dir",
+            metavar="dir",
+            default=None,
+            help=(
+                "Install packages into . "
+                "By default this will not replace existing files/folders in "
+                ". Use --upgrade to replace existing packages in  "
+                "with new versions."
+            ),
+        )
+        cmdoptions.add_target_python_options(self.cmd_opts)
+
+        self.cmd_opts.add_option(
+            "--user",
+            dest="use_user_site",
+            action="store_true",
+            help=(
+                "Install to the Python user install directory for your "
+                "platform. Typically ~/.local/, or %APPDATA%\\Python on "
+                "Windows. (See the Python documentation for site.USER_BASE "
+                "for full details.)"
+            ),
+        )
+        self.cmd_opts.add_option(
+            "--no-user",
+            dest="use_user_site",
+            action="store_false",
+            help=SUPPRESS_HELP,
+        )
+        self.cmd_opts.add_option(
+            "--root",
+            dest="root_path",
+            metavar="dir",
+            default=None,
+            help="Install everything relative to this alternate root directory.",
+        )
+        self.cmd_opts.add_option(
+            "--prefix",
+            dest="prefix_path",
+            metavar="dir",
+            default=None,
+            help=(
+                "Installation prefix where lib, bin and other top-level "
+                "folders are placed"
+            ),
+        )
+
+        self.cmd_opts.add_option(cmdoptions.src())
+
+        self.cmd_opts.add_option(
+            "-U",
+            "--upgrade",
+            dest="upgrade",
+            action="store_true",
+            help=(
+                "Upgrade all specified packages to the newest available "
+                "version. The handling of dependencies depends on the "
+                "upgrade-strategy used."
+            ),
+        )
+
+        self.cmd_opts.add_option(
+            "--upgrade-strategy",
+            dest="upgrade_strategy",
+            default="only-if-needed",
+            choices=["only-if-needed", "eager"],
+            help=(
+                "Determines how dependency upgrading should be handled "
+                "[default: %default]. "
+                '"eager" - dependencies are upgraded regardless of '
+                "whether the currently installed version satisfies the "
+                "requirements of the upgraded package(s). "
+                '"only-if-needed" -  are upgraded only when they do not '
+                "satisfy the requirements of the upgraded package(s)."
+            ),
+        )
+
+        self.cmd_opts.add_option(
+            "--force-reinstall",
+            dest="force_reinstall",
+            action="store_true",
+            help="Reinstall all packages even if they are already up-to-date.",
+        )
+
+        self.cmd_opts.add_option(
+            "-I",
+            "--ignore-installed",
+            dest="ignore_installed",
+            action="store_true",
+            help=(
+                "Ignore the installed packages, overwriting them. "
+                "This can break your system if the existing package "
+                "is of a different version or was installed "
+                "with a different package manager!"
+            ),
+        )
+
+        self.cmd_opts.add_option(cmdoptions.ignore_requires_python())
+        self.cmd_opts.add_option(cmdoptions.no_build_isolation())
+        self.cmd_opts.add_option(cmdoptions.use_pep517())
+        self.cmd_opts.add_option(cmdoptions.no_use_pep517())
+        self.cmd_opts.add_option(cmdoptions.check_build_deps())
+        self.cmd_opts.add_option(cmdoptions.override_externally_managed())
+
+        self.cmd_opts.add_option(cmdoptions.config_settings())
+        self.cmd_opts.add_option(cmdoptions.install_options())
+        self.cmd_opts.add_option(cmdoptions.global_options())
+
+        self.cmd_opts.add_option(
+            "--compile",
+            action="store_true",
+            dest="compile",
+            default=True,
+            help="Compile Python source files to bytecode",
+        )
+
+        self.cmd_opts.add_option(
+            "--no-compile",
+            action="store_false",
+            dest="compile",
+            help="Do not compile Python source files to bytecode",
+        )
+
+        self.cmd_opts.add_option(
+            "--no-warn-script-location",
+            action="store_false",
+            dest="warn_script_location",
+            default=True,
+            help="Do not warn when installing scripts outside PATH",
+        )
+        self.cmd_opts.add_option(
+            "--no-warn-conflicts",
+            action="store_false",
+            dest="warn_about_conflicts",
+            default=True,
+            help="Do not warn about broken dependencies",
+        )
+        self.cmd_opts.add_option(cmdoptions.no_binary())
+        self.cmd_opts.add_option(cmdoptions.only_binary())
+        self.cmd_opts.add_option(cmdoptions.prefer_binary())
+        self.cmd_opts.add_option(cmdoptions.require_hashes())
+        self.cmd_opts.add_option(cmdoptions.progress_bar())
+        self.cmd_opts.add_option(cmdoptions.root_user_action())
+
+        index_opts = cmdoptions.make_option_group(
+            cmdoptions.index_group,
+            self.parser,
+        )
+
+        self.parser.insert_option_group(0, index_opts)
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+        self.cmd_opts.add_option(
+            "--report",
+            dest="json_report_file",
+            metavar="file",
+            default=None,
+            help=(
+                "Generate a JSON file describing what pip did to install "
+                "the provided requirements. "
+                "Can be used in combination with --dry-run and --ignore-installed "
+                "to 'resolve' the requirements. "
+                "When - is used as file name it writes to stdout. "
+                "When writing to stdout, please combine with the --quiet option "
+                "to avoid mixing pip logging output with JSON output."
+            ),
+        )
+
+    @with_cleanup
+    def run(self, options: Values, args: List[str]) -> int:
+        if options.use_user_site and options.target_dir is not None:
+            raise CommandError("Can not combine '--user' and '--target'")
+
+        # Check whether the environment we're installing into is externally
+        # managed, as specified in PEP 668. Specifying --root, --target, or
+        # --prefix disables the check, since there's no reliable way to locate
+        # the EXTERNALLY-MANAGED file for those cases. An exception is also
+        # made specifically for "--dry-run --report" for convenience.
+        installing_into_current_environment = (
+            not (options.dry_run and options.json_report_file)
+            and options.root_path is None
+            and options.target_dir is None
+            and options.prefix_path is None
+        )
+        if (
+            installing_into_current_environment
+            and not options.override_externally_managed
+        ):
+            check_externally_managed()
+
+        upgrade_strategy = "to-satisfy-only"
+        if options.upgrade:
+            upgrade_strategy = options.upgrade_strategy
+
+        cmdoptions.check_dist_restriction(options, check_target=True)
+
+        install_options = options.install_options or []
+
+        logger.verbose("Using %s", get_pip_version())
+        options.use_user_site = decide_user_install(
+            options.use_user_site,
+            prefix_path=options.prefix_path,
+            target_dir=options.target_dir,
+            root_path=options.root_path,
+            isolated_mode=options.isolated_mode,
+        )
+
+        target_temp_dir: Optional[TempDirectory] = None
+        target_temp_dir_path: Optional[str] = None
+        if options.target_dir:
+            options.ignore_installed = True
+            options.target_dir = os.path.abspath(options.target_dir)
+            if (
+                # fmt: off
+                os.path.exists(options.target_dir) and
+                not os.path.isdir(options.target_dir)
+                # fmt: on
+            ):
+                raise CommandError(
+                    "Target path exists but is not a directory, will not continue."
+                )
+
+            # Create a target directory for using with the target option
+            target_temp_dir = TempDirectory(kind="target")
+            target_temp_dir_path = target_temp_dir.path
+            self.enter_context(target_temp_dir)
+
+        global_options = options.global_options or []
+
+        session = self.get_default_session(options)
+
+        target_python = make_target_python(options)
+        finder = self._build_package_finder(
+            options=options,
+            session=session,
+            target_python=target_python,
+            ignore_requires_python=options.ignore_requires_python,
+        )
+        build_tracker = self.enter_context(get_build_tracker())
+
+        directory = TempDirectory(
+            delete=not options.no_clean,
+            kind="install",
+            globally_managed=True,
+        )
+
+        try:
+            reqs = self.get_requirements(args, options, finder, session)
+            check_legacy_setup_py_options(
+                options, reqs, LegacySetupPyOptionsCheckMode.INSTALL
+            )
+
+            if "no-binary-enable-wheel-cache" in options.features_enabled:
+                # TODO: remove format_control from WheelCache when the deprecation cycle
+                # is over
+                wheel_cache = WheelCache(options.cache_dir)
+            else:
+                if options.format_control.no_binary:
+                    deprecated(
+                        reason=(
+                            "--no-binary currently disables reading from "
+                            "the cache of locally built wheels. In the future "
+                            "--no-binary will not influence the wheel cache."
+                        ),
+                        replacement="to use the --no-cache-dir option",
+                        feature_flag="no-binary-enable-wheel-cache",
+                        issue=11453,
+                        gone_in="23.1",
+                    )
+                wheel_cache = WheelCache(options.cache_dir, options.format_control)
+
+            # Only when installing is it permitted to use PEP 660.
+            # In other circumstances (pip wheel, pip download) we generate
+            # regular (i.e. non editable) metadata and wheels.
+            for req in reqs:
+                req.permit_editable_wheels = True
+
+            reject_location_related_install_options(reqs, options.install_options)
+
+            preparer = self.make_requirement_preparer(
+                temp_build_dir=directory,
+                options=options,
+                build_tracker=build_tracker,
+                session=session,
+                finder=finder,
+                use_user_site=options.use_user_site,
+                verbosity=self.verbosity,
+            )
+            resolver = self.make_resolver(
+                preparer=preparer,
+                finder=finder,
+                options=options,
+                wheel_cache=wheel_cache,
+                use_user_site=options.use_user_site,
+                ignore_installed=options.ignore_installed,
+                ignore_requires_python=options.ignore_requires_python,
+                force_reinstall=options.force_reinstall,
+                upgrade_strategy=upgrade_strategy,
+                use_pep517=options.use_pep517,
+            )
+
+            self.trace_basic_info(finder)
+
+            requirement_set = resolver.resolve(
+                reqs, check_supported_wheels=not options.target_dir
+            )
+
+            if options.json_report_file:
+                report = InstallationReport(requirement_set.requirements_to_install)
+                if options.json_report_file == "-":
+                    print_json(data=report.to_dict())
+                else:
+                    with open(options.json_report_file, "w", encoding="utf-8") as f:
+                        json.dump(report.to_dict(), f, indent=2, ensure_ascii=False)
+
+            if options.dry_run:
+                would_install_items = sorted(
+                    (r.metadata["name"], r.metadata["version"])
+                    for r in requirement_set.requirements_to_install
+                )
+                if would_install_items:
+                    write_output(
+                        "Would install %s",
+                        " ".join("-".join(item) for item in would_install_items),
+                    )
+                return SUCCESS
+
+            try:
+                pip_req = requirement_set.get_requirement("pip")
+            except KeyError:
+                modifying_pip = False
+            else:
+                # If we're not replacing an already installed pip,
+                # we're not modifying it.
+                modifying_pip = pip_req.satisfied_by is None
+            protect_pip_from_modification_on_windows(modifying_pip=modifying_pip)
+
+            check_bdist_wheel_allowed = get_check_bdist_wheel_allowed(
+                finder.format_control
+            )
+
+            reqs_to_build = [
+                r
+                for r in requirement_set.requirements.values()
+                if should_build_for_install_command(r, check_bdist_wheel_allowed)
+            ]
+
+            _, build_failures = build(
+                reqs_to_build,
+                wheel_cache=wheel_cache,
+                verify=True,
+                build_options=[],
+                global_options=global_options,
+            )
+
+            # If we're using PEP 517, we cannot do a legacy setup.py install
+            # so we fail here.
+            pep517_build_failure_names: List[str] = [
+                r.name for r in build_failures if r.use_pep517  # type: ignore
+            ]
+            if pep517_build_failure_names:
+                raise InstallationError(
+                    "Could not build wheels for {}, which is required to "
+                    "install pyproject.toml-based projects".format(
+                        ", ".join(pep517_build_failure_names)
+                    )
+                )
+
+            # For now, we just warn about failures building legacy
+            # requirements, as we'll fall through to a setup.py install for
+            # those.
+            for r in build_failures:
+                if not r.use_pep517:
+                    r.legacy_install_reason = LegacyInstallReasonFailedBdistWheel
+
+            to_install = resolver.get_installation_order(requirement_set)
+
+            # Check for conflicts in the package set we're installing.
+            conflicts: Optional[ConflictDetails] = None
+            should_warn_about_conflicts = (
+                not options.ignore_dependencies and options.warn_about_conflicts
+            )
+            if should_warn_about_conflicts:
+                conflicts = self._determine_conflicts(to_install)
+
+            # Don't warn about script install locations if
+            # --target or --prefix has been specified
+            warn_script_location = options.warn_script_location
+            if options.target_dir or options.prefix_path:
+                warn_script_location = False
+
+            installed = install_given_reqs(
+                to_install,
+                install_options,
+                global_options,
+                root=options.root_path,
+                home=target_temp_dir_path,
+                prefix=options.prefix_path,
+                warn_script_location=warn_script_location,
+                use_user_site=options.use_user_site,
+                pycompile=options.compile,
+            )
+
+            lib_locations = get_lib_location_guesses(
+                user=options.use_user_site,
+                home=target_temp_dir_path,
+                root=options.root_path,
+                prefix=options.prefix_path,
+                isolated=options.isolated_mode,
+            )
+            env = get_environment(lib_locations)
+
+            installed.sort(key=operator.attrgetter("name"))
+            items = []
+            for result in installed:
+                item = result.name
+                try:
+                    installed_dist = env.get_distribution(item)
+                    if installed_dist is not None:
+                        item = f"{item}-{installed_dist.version}"
+                except Exception:
+                    pass
+                items.append(item)
+
+            if conflicts is not None:
+                self._warn_about_conflicts(
+                    conflicts,
+                    resolver_variant=self.determine_resolver_variant(options),
+                )
+
+            installed_desc = " ".join(items)
+            if installed_desc:
+                write_output(
+                    "Successfully installed %s",
+                    installed_desc,
+                )
+        except OSError as error:
+            show_traceback = self.verbosity >= 1
+
+            message = create_os_error_message(
+                error,
+                show_traceback,
+                options.use_user_site,
+            )
+            logger.error(message, exc_info=show_traceback)  # noqa
+
+            return ERROR
+
+        if options.target_dir:
+            assert target_temp_dir
+            self._handle_target_dir(
+                options.target_dir, target_temp_dir, options.upgrade
+            )
+        if options.root_user_action == "warn":
+            warn_if_run_as_root()
+        return SUCCESS
+
+    def _handle_target_dir(
+        self, target_dir: str, target_temp_dir: TempDirectory, upgrade: bool
+    ) -> None:
+        ensure_dir(target_dir)
+
+        # Checking both purelib and platlib directories for installed
+        # packages to be moved to target directory
+        lib_dir_list = []
+
+        # Checking both purelib and platlib directories for installed
+        # packages to be moved to target directory
+        scheme = get_scheme("", home=target_temp_dir.path)
+        purelib_dir = scheme.purelib
+        platlib_dir = scheme.platlib
+        data_dir = scheme.data
+
+        if os.path.exists(purelib_dir):
+            lib_dir_list.append(purelib_dir)
+        if os.path.exists(platlib_dir) and platlib_dir != purelib_dir:
+            lib_dir_list.append(platlib_dir)
+        if os.path.exists(data_dir):
+            lib_dir_list.append(data_dir)
+
+        for lib_dir in lib_dir_list:
+            for item in os.listdir(lib_dir):
+                if lib_dir == data_dir:
+                    ddir = os.path.join(data_dir, item)
+                    if any(s.startswith(ddir) for s in lib_dir_list[:-1]):
+                        continue
+                target_item_dir = os.path.join(target_dir, item)
+                if os.path.exists(target_item_dir):
+                    if not upgrade:
+                        logger.warning(
+                            "Target directory %s already exists. Specify "
+                            "--upgrade to force replacement.",
+                            target_item_dir,
+                        )
+                        continue
+                    if os.path.islink(target_item_dir):
+                        logger.warning(
+                            "Target directory %s already exists and is "
+                            "a link. pip will not automatically replace "
+                            "links, please remove if replacement is "
+                            "desired.",
+                            target_item_dir,
+                        )
+                        continue
+                    if os.path.isdir(target_item_dir):
+                        shutil.rmtree(target_item_dir)
+                    else:
+                        os.remove(target_item_dir)
+
+                shutil.move(os.path.join(lib_dir, item), target_item_dir)
+
+    def _determine_conflicts(
+        self, to_install: List[InstallRequirement]
+    ) -> Optional[ConflictDetails]:
+        try:
+            return check_install_conflicts(to_install)
+        except Exception:
+            logger.exception(
+                "Error while checking for conflicts. Please file an issue on "
+                "pip's issue tracker: https://github.com/pypa/pip/issues/new"
+            )
+            return None
+
+    def _warn_about_conflicts(
+        self, conflict_details: ConflictDetails, resolver_variant: str
+    ) -> None:
+        package_set, (missing, conflicting) = conflict_details
+        if not missing and not conflicting:
+            return
+
+        parts: List[str] = []
+        if resolver_variant == "legacy":
+            parts.append(
+                "pip's legacy dependency resolver does not consider dependency "
+                "conflicts when selecting packages. This behaviour is the "
+                "source of the following dependency conflicts."
+            )
+        else:
+            assert resolver_variant == "2020-resolver"
+            parts.append(
+                "pip's dependency resolver does not currently take into account "
+                "all the packages that are installed. This behaviour is the "
+                "source of the following dependency conflicts."
+            )
+
+        # NOTE: There is some duplication here, with commands/check.py
+        for project_name in missing:
+            version = package_set[project_name][0]
+            for dependency in missing[project_name]:
+                message = (
+                    "{name} {version} requires {requirement}, "
+                    "which is not installed."
+                ).format(
+                    name=project_name,
+                    version=version,
+                    requirement=dependency[1],
+                )
+                parts.append(message)
+
+        for project_name in conflicting:
+            version = package_set[project_name][0]
+            for dep_name, dep_version, req in conflicting[project_name]:
+                message = (
+                    "{name} {version} requires {requirement}, but {you} have "
+                    "{dep_name} {dep_version} which is incompatible."
+                ).format(
+                    name=project_name,
+                    version=version,
+                    requirement=req,
+                    dep_name=dep_name,
+                    dep_version=dep_version,
+                    you=("you" if resolver_variant == "2020-resolver" else "you'll"),
+                )
+                parts.append(message)
+
+        logger.critical("\n".join(parts))
+
+
+def get_lib_location_guesses(
+    user: bool = False,
+    home: Optional[str] = None,
+    root: Optional[str] = None,
+    isolated: bool = False,
+    prefix: Optional[str] = None,
+) -> List[str]:
+    scheme = get_scheme(
+        "",
+        user=user,
+        home=home,
+        root=root,
+        isolated=isolated,
+        prefix=prefix,
+    )
+    return [scheme.purelib, scheme.platlib]
+
+
+def site_packages_writable(root: Optional[str], isolated: bool) -> bool:
+    return all(
+        test_writable_dir(d)
+        for d in set(get_lib_location_guesses(root=root, isolated=isolated))
+    )
+
+
+def decide_user_install(
+    use_user_site: Optional[bool],
+    prefix_path: Optional[str] = None,
+    target_dir: Optional[str] = None,
+    root_path: Optional[str] = None,
+    isolated_mode: bool = False,
+) -> bool:
+    """Determine whether to do a user install based on the input options.
+
+    If use_user_site is False, no additional checks are done.
+    If use_user_site is True, it is checked for compatibility with other
+    options.
+    If use_user_site is None, the default behaviour depends on the environment,
+    which is provided by the other arguments.
+    """
+    # In some cases (config from tox), use_user_site can be set to an integer
+    # rather than a bool, which 'use_user_site is False' wouldn't catch.
+    if (use_user_site is not None) and (not use_user_site):
+        logger.debug("Non-user install by explicit request")
+        return False
+
+    if use_user_site:
+        if prefix_path:
+            raise CommandError(
+                "Can not combine '--user' and '--prefix' as they imply "
+                "different installation locations"
+            )
+        if virtualenv_no_global():
+            raise InstallationError(
+                "Can not perform a '--user' install. User site-packages "
+                "are not visible in this virtualenv."
+            )
+        logger.debug("User install by explicit request")
+        return True
+
+    # If we are here, user installs have not been explicitly requested/avoided
+    assert use_user_site is None
+
+    # user install incompatible with --prefix/--target
+    if prefix_path or target_dir:
+        logger.debug("Non-user install due to --prefix or --target option")
+        return False
+
+    # If user installs are not enabled, choose a non-user install
+    if not site.ENABLE_USER_SITE:
+        logger.debug("Non-user install because user site-packages disabled")
+        return False
+
+    # If we have permission for a non-user install, do that,
+    # otherwise do a user install.
+    if site_packages_writable(root=root_path, isolated=isolated_mode):
+        logger.debug("Non-user install because site-packages writeable")
+        return False
+
+    logger.info(
+        "Defaulting to user installation because normal site-packages "
+        "is not writeable"
+    )
+    return True
+
+
+def reject_location_related_install_options(
+    requirements: List[InstallRequirement], options: Optional[List[str]]
+) -> None:
+    """If any location-changing --install-option arguments were passed for
+    requirements or on the command-line, then show a deprecation warning.
+    """
+
+    def format_options(option_names: Iterable[str]) -> List[str]:
+        return ["--{}".format(name.replace("_", "-")) for name in option_names]
+
+    offenders = []
+
+    for requirement in requirements:
+        install_options = requirement.install_options
+        location_options = parse_distutils_args(install_options)
+        if location_options:
+            offenders.append(
+                "{!r} from {}".format(
+                    format_options(location_options.keys()), requirement
+                )
+            )
+
+    if options:
+        location_options = parse_distutils_args(options)
+        if location_options:
+            offenders.append(
+                "{!r} from command line".format(format_options(location_options.keys()))
+            )
+
+    if not offenders:
+        return
+
+    raise CommandError(
+        "Location-changing options found in --install-option: {}."
+        " This is unsupported, use pip-level options like --user,"
+        " --prefix, --root, and --target instead.".format("; ".join(offenders))
+    )
+
+
+def create_os_error_message(
+    error: OSError, show_traceback: bool, using_user_site: bool
+) -> str:
+    """Format an error message for an OSError
+
+    It may occur anytime during the execution of the install command.
+    """
+    parts = []
+
+    # Mention the error if we are not going to show a traceback
+    parts.append("Could not install packages due to an OSError")
+    if not show_traceback:
+        parts.append(": ")
+        parts.append(str(error))
+    else:
+        parts.append(".")
+
+    # Spilt the error indication from a helper message (if any)
+    parts[-1] += "\n"
+
+    # Suggest useful actions to the user:
+    #  (1) using user site-packages or (2) verifying the permissions
+    if error.errno == errno.EACCES:
+        user_option_part = "Consider using the `--user` option"
+        permissions_part = "Check the permissions"
+
+        if not running_under_virtualenv() and not using_user_site:
+            parts.extend(
+                [
+                    user_option_part,
+                    " or ",
+                    permissions_part.lower(),
+                ]
+            )
+        else:
+            parts.append(permissions_part)
+        parts.append(".\n")
+
+    # Suggest the user to enable Long Paths if path length is
+    # more than 260
+    if (
+        WINDOWS
+        and error.errno == errno.ENOENT
+        and error.filename
+        and len(error.filename) > 260
+    ):
+        parts.append(
+            "HINT: This error might have occurred since "
+            "this system does not have Windows Long Path "
+            "support enabled. You can find information on "
+            "how to enable this at "
+            "https://pip.pypa.io/warnings/enable-long-paths\n"
+        )
+
+    return "".join(parts).strip() + "\n"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/list.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/list.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e1426dbb6c6762a673db2691ecd7ac124d46ec8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/list.py
@@ -0,0 +1,365 @@
+import json
+import logging
+from optparse import Values
+from typing import TYPE_CHECKING, Generator, List, Optional, Sequence, Tuple, cast
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.req_command import IndexGroupCommand
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.exceptions import CommandError
+from pip._internal.index.collector import LinkCollector
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import BaseDistribution, get_environment
+from pip._internal.models.selection_prefs import SelectionPreferences
+from pip._internal.network.session import PipSession
+from pip._internal.utils.compat import stdlib_pkgs
+from pip._internal.utils.misc import tabulate, write_output
+
+if TYPE_CHECKING:
+    from pip._internal.metadata.base import DistributionVersion
+
+    class _DistWithLatestInfo(BaseDistribution):
+        """Give the distribution object a couple of extra fields.
+
+        These will be populated during ``get_outdated()``. This is dirty but
+        makes the rest of the code much cleaner.
+        """
+
+        latest_version: DistributionVersion
+        latest_filetype: str
+
+    _ProcessedDists = Sequence[_DistWithLatestInfo]
+
+
+logger = logging.getLogger(__name__)
+
+
+class ListCommand(IndexGroupCommand):
+    """
+    List installed packages, including editables.
+
+    Packages are listed in a case-insensitive sorted order.
+    """
+
+    ignore_require_venv = True
+    usage = """
+      %prog [options]"""
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "-o",
+            "--outdated",
+            action="store_true",
+            default=False,
+            help="List outdated packages",
+        )
+        self.cmd_opts.add_option(
+            "-u",
+            "--uptodate",
+            action="store_true",
+            default=False,
+            help="List uptodate packages",
+        )
+        self.cmd_opts.add_option(
+            "-e",
+            "--editable",
+            action="store_true",
+            default=False,
+            help="List editable projects.",
+        )
+        self.cmd_opts.add_option(
+            "-l",
+            "--local",
+            action="store_true",
+            default=False,
+            help=(
+                "If in a virtualenv that has global access, do not list "
+                "globally-installed packages."
+            ),
+        )
+        self.cmd_opts.add_option(
+            "--user",
+            dest="user",
+            action="store_true",
+            default=False,
+            help="Only output packages installed in user-site.",
+        )
+        self.cmd_opts.add_option(cmdoptions.list_path())
+        self.cmd_opts.add_option(
+            "--pre",
+            action="store_true",
+            default=False,
+            help=(
+                "Include pre-release and development versions. By default, "
+                "pip only finds stable versions."
+            ),
+        )
+
+        self.cmd_opts.add_option(
+            "--format",
+            action="store",
+            dest="list_format",
+            default="columns",
+            choices=("columns", "freeze", "json"),
+            help="Select the output format among: columns (default), freeze, or json",
+        )
+
+        self.cmd_opts.add_option(
+            "--not-required",
+            action="store_true",
+            dest="not_required",
+            help="List packages that are not dependencies of installed packages.",
+        )
+
+        self.cmd_opts.add_option(
+            "--exclude-editable",
+            action="store_false",
+            dest="include_editable",
+            help="Exclude editable package from output.",
+        )
+        self.cmd_opts.add_option(
+            "--include-editable",
+            action="store_true",
+            dest="include_editable",
+            help="Include editable package from output.",
+            default=True,
+        )
+        self.cmd_opts.add_option(cmdoptions.list_exclude())
+        index_opts = cmdoptions.make_option_group(cmdoptions.index_group, self.parser)
+
+        self.parser.insert_option_group(0, index_opts)
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def _build_package_finder(
+        self, options: Values, session: PipSession
+    ) -> PackageFinder:
+        """
+        Create a package finder appropriate to this list command.
+        """
+        link_collector = LinkCollector.create(session, options=options)
+
+        # Pass allow_yanked=False to ignore yanked versions.
+        selection_prefs = SelectionPreferences(
+            allow_yanked=False,
+            allow_all_prereleases=options.pre,
+        )
+
+        return PackageFinder.create(
+            link_collector=link_collector,
+            selection_prefs=selection_prefs,
+        )
+
+    def run(self, options: Values, args: List[str]) -> int:
+        if options.outdated and options.uptodate:
+            raise CommandError("Options --outdated and --uptodate cannot be combined.")
+
+        if options.outdated and options.list_format == "freeze":
+            raise CommandError(
+                "List format 'freeze' can not be used with the --outdated option."
+            )
+
+        cmdoptions.check_list_path_option(options)
+
+        skip = set(stdlib_pkgs)
+        if options.excludes:
+            skip.update(canonicalize_name(n) for n in options.excludes)
+
+        packages: "_ProcessedDists" = [
+            cast("_DistWithLatestInfo", d)
+            for d in get_environment(options.path).iter_installed_distributions(
+                local_only=options.local,
+                user_only=options.user,
+                editables_only=options.editable,
+                include_editables=options.include_editable,
+                skip=skip,
+            )
+        ]
+
+        # get_not_required must be called firstly in order to find and
+        # filter out all dependencies correctly. Otherwise a package
+        # can't be identified as requirement because some parent packages
+        # could be filtered out before.
+        if options.not_required:
+            packages = self.get_not_required(packages, options)
+
+        if options.outdated:
+            packages = self.get_outdated(packages, options)
+        elif options.uptodate:
+            packages = self.get_uptodate(packages, options)
+
+        self.output_package_listing(packages, options)
+        return SUCCESS
+
+    def get_outdated(
+        self, packages: "_ProcessedDists", options: Values
+    ) -> "_ProcessedDists":
+        return [
+            dist
+            for dist in self.iter_packages_latest_infos(packages, options)
+            if dist.latest_version > dist.version
+        ]
+
+    def get_uptodate(
+        self, packages: "_ProcessedDists", options: Values
+    ) -> "_ProcessedDists":
+        return [
+            dist
+            for dist in self.iter_packages_latest_infos(packages, options)
+            if dist.latest_version == dist.version
+        ]
+
+    def get_not_required(
+        self, packages: "_ProcessedDists", options: Values
+    ) -> "_ProcessedDists":
+        dep_keys = {
+            canonicalize_name(dep.name)
+            for dist in packages
+            for dep in (dist.iter_dependencies() or ())
+        }
+
+        # Create a set to remove duplicate packages, and cast it to a list
+        # to keep the return type consistent with get_outdated and
+        # get_uptodate
+        return list({pkg for pkg in packages if pkg.canonical_name not in dep_keys})
+
+    def iter_packages_latest_infos(
+        self, packages: "_ProcessedDists", options: Values
+    ) -> Generator["_DistWithLatestInfo", None, None]:
+        with self._build_session(options) as session:
+            finder = self._build_package_finder(options, session)
+
+            def latest_info(
+                dist: "_DistWithLatestInfo",
+            ) -> Optional["_DistWithLatestInfo"]:
+                all_candidates = finder.find_all_candidates(dist.canonical_name)
+                if not options.pre:
+                    # Remove prereleases
+                    all_candidates = [
+                        candidate
+                        for candidate in all_candidates
+                        if not candidate.version.is_prerelease
+                    ]
+
+                evaluator = finder.make_candidate_evaluator(
+                    project_name=dist.canonical_name,
+                )
+                best_candidate = evaluator.sort_best_candidate(all_candidates)
+                if best_candidate is None:
+                    return None
+
+                remote_version = best_candidate.version
+                if best_candidate.link.is_wheel:
+                    typ = "wheel"
+                else:
+                    typ = "sdist"
+                dist.latest_version = remote_version
+                dist.latest_filetype = typ
+                return dist
+
+            for dist in map(latest_info, packages):
+                if dist is not None:
+                    yield dist
+
+    def output_package_listing(
+        self, packages: "_ProcessedDists", options: Values
+    ) -> None:
+        packages = sorted(
+            packages,
+            key=lambda dist: dist.canonical_name,
+        )
+        if options.list_format == "columns" and packages:
+            data, header = format_for_columns(packages, options)
+            self.output_package_listing_columns(data, header)
+        elif options.list_format == "freeze":
+            for dist in packages:
+                if options.verbose >= 1:
+                    write_output(
+                        "%s==%s (%s)", dist.raw_name, dist.version, dist.location
+                    )
+                else:
+                    write_output("%s==%s", dist.raw_name, dist.version)
+        elif options.list_format == "json":
+            write_output(format_for_json(packages, options))
+
+    def output_package_listing_columns(
+        self, data: List[List[str]], header: List[str]
+    ) -> None:
+        # insert the header first: we need to know the size of column names
+        if len(data) > 0:
+            data.insert(0, header)
+
+        pkg_strings, sizes = tabulate(data)
+
+        # Create and add a separator.
+        if len(data) > 0:
+            pkg_strings.insert(1, " ".join(map(lambda x: "-" * x, sizes)))
+
+        for val in pkg_strings:
+            write_output(val)
+
+
+def format_for_columns(
+    pkgs: "_ProcessedDists", options: Values
+) -> Tuple[List[List[str]], List[str]]:
+    """
+    Convert the package data into something usable
+    by output_package_listing_columns.
+    """
+    header = ["Package", "Version"]
+
+    running_outdated = options.outdated
+    if running_outdated:
+        header.extend(["Latest", "Type"])
+
+    has_editables = any(x.editable for x in pkgs)
+    if has_editables:
+        header.append("Editable project location")
+
+    if options.verbose >= 1:
+        header.append("Location")
+    if options.verbose >= 1:
+        header.append("Installer")
+
+    data = []
+    for proj in pkgs:
+        # if we're working on the 'outdated' list, separate out the
+        # latest_version and type
+        row = [proj.raw_name, str(proj.version)]
+
+        if running_outdated:
+            row.append(str(proj.latest_version))
+            row.append(proj.latest_filetype)
+
+        if has_editables:
+            row.append(proj.editable_project_location or "")
+
+        if options.verbose >= 1:
+            row.append(proj.location or "")
+        if options.verbose >= 1:
+            row.append(proj.installer)
+
+        data.append(row)
+
+    return data, header
+
+
+def format_for_json(packages: "_ProcessedDists", options: Values) -> str:
+    data = []
+    for dist in packages:
+        info = {
+            "name": dist.raw_name,
+            "version": str(dist.version),
+        }
+        if options.verbose >= 1:
+            info["location"] = dist.location or ""
+            info["installer"] = dist.installer
+        if options.outdated:
+            info["latest_version"] = str(dist.latest_version)
+            info["latest_filetype"] = dist.latest_filetype
+        editable_project_location = dist.editable_project_location
+        if editable_project_location:
+            info["editable_project_location"] = editable_project_location
+        data.append(info)
+    return json.dumps(data)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/search.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/search.py
new file mode 100644
index 0000000000000000000000000000000000000000..03ed925b246dd551ec2ef45095ed6cad00fd2745
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/search.py
@@ -0,0 +1,174 @@
+import logging
+import shutil
+import sys
+import textwrap
+import xmlrpc.client
+from collections import OrderedDict
+from optparse import Values
+from typing import TYPE_CHECKING, Dict, List, Optional
+
+from pip._vendor.packaging.version import parse as parse_version
+
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.req_command import SessionCommandMixin
+from pip._internal.cli.status_codes import NO_MATCHES_FOUND, SUCCESS
+from pip._internal.exceptions import CommandError
+from pip._internal.metadata import get_default_environment
+from pip._internal.models.index import PyPI
+from pip._internal.network.xmlrpc import PipXmlrpcTransport
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.misc import write_output
+
+if TYPE_CHECKING:
+    from typing import TypedDict
+
+    class TransformedHit(TypedDict):
+        name: str
+        summary: str
+        versions: List[str]
+
+
+logger = logging.getLogger(__name__)
+
+
+class SearchCommand(Command, SessionCommandMixin):
+    """Search for PyPI packages whose name or summary contains ."""
+
+    usage = """
+      %prog [options] """
+    ignore_require_venv = True
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "-i",
+            "--index",
+            dest="index",
+            metavar="URL",
+            default=PyPI.pypi_url,
+            help="Base URL of Python Package Index (default %default)",
+        )
+
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        if not args:
+            raise CommandError("Missing required argument (search query).")
+        query = args
+        pypi_hits = self.search(query, options)
+        hits = transform_hits(pypi_hits)
+
+        terminal_width = None
+        if sys.stdout.isatty():
+            terminal_width = shutil.get_terminal_size()[0]
+
+        print_results(hits, terminal_width=terminal_width)
+        if pypi_hits:
+            return SUCCESS
+        return NO_MATCHES_FOUND
+
+    def search(self, query: List[str], options: Values) -> List[Dict[str, str]]:
+        index_url = options.index
+
+        session = self.get_default_session(options)
+
+        transport = PipXmlrpcTransport(index_url, session)
+        pypi = xmlrpc.client.ServerProxy(index_url, transport)
+        try:
+            hits = pypi.search({"name": query, "summary": query}, "or")
+        except xmlrpc.client.Fault as fault:
+            message = "XMLRPC request failed [code: {code}]\n{string}".format(
+                code=fault.faultCode,
+                string=fault.faultString,
+            )
+            raise CommandError(message)
+        assert isinstance(hits, list)
+        return hits
+
+
+def transform_hits(hits: List[Dict[str, str]]) -> List["TransformedHit"]:
+    """
+    The list from pypi is really a list of versions. We want a list of
+    packages with the list of versions stored inline. This converts the
+    list from pypi into one we can use.
+    """
+    packages: Dict[str, "TransformedHit"] = OrderedDict()
+    for hit in hits:
+        name = hit["name"]
+        summary = hit["summary"]
+        version = hit["version"]
+
+        if name not in packages.keys():
+            packages[name] = {
+                "name": name,
+                "summary": summary,
+                "versions": [version],
+            }
+        else:
+            packages[name]["versions"].append(version)
+
+            # if this is the highest version, replace summary and score
+            if version == highest_version(packages[name]["versions"]):
+                packages[name]["summary"] = summary
+
+    return list(packages.values())
+
+
+def print_dist_installation_info(name: str, latest: str) -> None:
+    env = get_default_environment()
+    dist = env.get_distribution(name)
+    if dist is not None:
+        with indent_log():
+            if dist.version == latest:
+                write_output("INSTALLED: %s (latest)", dist.version)
+            else:
+                write_output("INSTALLED: %s", dist.version)
+                if parse_version(latest).pre:
+                    write_output(
+                        "LATEST:    %s (pre-release; install"
+                        " with `pip install --pre`)",
+                        latest,
+                    )
+                else:
+                    write_output("LATEST:    %s", latest)
+
+
+def print_results(
+    hits: List["TransformedHit"],
+    name_column_width: Optional[int] = None,
+    terminal_width: Optional[int] = None,
+) -> None:
+    if not hits:
+        return
+    if name_column_width is None:
+        name_column_width = (
+            max(
+                [
+                    len(hit["name"]) + len(highest_version(hit.get("versions", ["-"])))
+                    for hit in hits
+                ]
+            )
+            + 4
+        )
+
+    for hit in hits:
+        name = hit["name"]
+        summary = hit["summary"] or ""
+        latest = highest_version(hit.get("versions", ["-"]))
+        if terminal_width is not None:
+            target_width = terminal_width - name_column_width - 5
+            if target_width > 10:
+                # wrap and indent summary to fit terminal
+                summary_lines = textwrap.wrap(summary, target_width)
+                summary = ("\n" + " " * (name_column_width + 3)).join(summary_lines)
+
+        name_latest = f"{name} ({latest})"
+        line = f"{name_latest:{name_column_width}} - {summary}"
+        try:
+            write_output(line)
+            print_dist_installation_info(name, latest)
+        except UnicodeEncodeError:
+            pass
+
+
+def highest_version(versions: List[str]) -> str:
+    return max(versions, key=parse_version)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/show.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/show.py
new file mode 100644
index 0000000000000000000000000000000000000000..3f10701f6b28c72b62c9904fec37b96bdd199dcc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/show.py
@@ -0,0 +1,189 @@
+import logging
+from optparse import Values
+from typing import Generator, Iterable, Iterator, List, NamedTuple, Optional
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.status_codes import ERROR, SUCCESS
+from pip._internal.metadata import BaseDistribution, get_default_environment
+from pip._internal.utils.misc import write_output
+
+logger = logging.getLogger(__name__)
+
+
+class ShowCommand(Command):
+    """
+    Show information about one or more installed packages.
+
+    The output is in RFC-compliant mail header format.
+    """
+
+    usage = """
+      %prog [options]  ..."""
+    ignore_require_venv = True
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "-f",
+            "--files",
+            dest="files",
+            action="store_true",
+            default=False,
+            help="Show the full list of installed files for each package.",
+        )
+
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        if not args:
+            logger.warning("ERROR: Please provide a package name or names.")
+            return ERROR
+        query = args
+
+        results = search_packages_info(query)
+        if not print_results(
+            results, list_files=options.files, verbose=options.verbose
+        ):
+            return ERROR
+        return SUCCESS
+
+
+class _PackageInfo(NamedTuple):
+    name: str
+    version: str
+    location: str
+    editable_project_location: Optional[str]
+    requires: List[str]
+    required_by: List[str]
+    installer: str
+    metadata_version: str
+    classifiers: List[str]
+    summary: str
+    homepage: str
+    project_urls: List[str]
+    author: str
+    author_email: str
+    license: str
+    entry_points: List[str]
+    files: Optional[List[str]]
+
+
+def search_packages_info(query: List[str]) -> Generator[_PackageInfo, None, None]:
+    """
+    Gather details from installed distributions. Print distribution name,
+    version, location, and installed files. Installed files requires a
+    pip generated 'installed-files.txt' in the distributions '.egg-info'
+    directory.
+    """
+    env = get_default_environment()
+
+    installed = {dist.canonical_name: dist for dist in env.iter_all_distributions()}
+    query_names = [canonicalize_name(name) for name in query]
+    missing = sorted(
+        [name for name, pkg in zip(query, query_names) if pkg not in installed]
+    )
+    if missing:
+        logger.warning("Package(s) not found: %s", ", ".join(missing))
+
+    def _get_requiring_packages(current_dist: BaseDistribution) -> Iterator[str]:
+        return (
+            dist.metadata["Name"] or "UNKNOWN"
+            for dist in installed.values()
+            if current_dist.canonical_name
+            in {canonicalize_name(d.name) for d in dist.iter_dependencies()}
+        )
+
+    for query_name in query_names:
+        try:
+            dist = installed[query_name]
+        except KeyError:
+            continue
+
+        requires = sorted((req.name for req in dist.iter_dependencies()), key=str.lower)
+        required_by = sorted(_get_requiring_packages(dist), key=str.lower)
+
+        try:
+            entry_points_text = dist.read_text("entry_points.txt")
+            entry_points = entry_points_text.splitlines(keepends=False)
+        except FileNotFoundError:
+            entry_points = []
+
+        files_iter = dist.iter_declared_entries()
+        if files_iter is None:
+            files: Optional[List[str]] = None
+        else:
+            files = sorted(files_iter)
+
+        metadata = dist.metadata
+
+        yield _PackageInfo(
+            name=dist.raw_name,
+            version=str(dist.version),
+            location=dist.location or "",
+            editable_project_location=dist.editable_project_location,
+            requires=requires,
+            required_by=required_by,
+            installer=dist.installer,
+            metadata_version=dist.metadata_version or "",
+            classifiers=metadata.get_all("Classifier", []),
+            summary=metadata.get("Summary", ""),
+            homepage=metadata.get("Home-page", ""),
+            project_urls=metadata.get_all("Project-URL", []),
+            author=metadata.get("Author", ""),
+            author_email=metadata.get("Author-email", ""),
+            license=metadata.get("License", ""),
+            entry_points=entry_points,
+            files=files,
+        )
+
+
+def print_results(
+    distributions: Iterable[_PackageInfo],
+    list_files: bool,
+    verbose: bool,
+) -> bool:
+    """
+    Print the information from installed distributions found.
+    """
+    results_printed = False
+    for i, dist in enumerate(distributions):
+        results_printed = True
+        if i > 0:
+            write_output("---")
+
+        write_output("Name: %s", dist.name)
+        write_output("Version: %s", dist.version)
+        write_output("Summary: %s", dist.summary)
+        write_output("Home-page: %s", dist.homepage)
+        write_output("Author: %s", dist.author)
+        write_output("Author-email: %s", dist.author_email)
+        write_output("License: %s", dist.license)
+        write_output("Location: %s", dist.location)
+        if dist.editable_project_location is not None:
+            write_output(
+                "Editable project location: %s", dist.editable_project_location
+            )
+        write_output("Requires: %s", ", ".join(dist.requires))
+        write_output("Required-by: %s", ", ".join(dist.required_by))
+
+        if verbose:
+            write_output("Metadata-Version: %s", dist.metadata_version)
+            write_output("Installer: %s", dist.installer)
+            write_output("Classifiers:")
+            for classifier in dist.classifiers:
+                write_output("  %s", classifier)
+            write_output("Entry-points:")
+            for entry in dist.entry_points:
+                write_output("  %s", entry.strip())
+            write_output("Project-URLs:")
+            for project_url in dist.project_urls:
+                write_output("  %s", project_url)
+        if list_files:
+            write_output("Files:")
+            if dist.files is None:
+                write_output("Cannot locate RECORD or installed-files.txt")
+            else:
+                for line in dist.files:
+                    write_output("  %s", line.strip())
+    return results_printed
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/uninstall.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/uninstall.py
new file mode 100644
index 0000000000000000000000000000000000000000..f198fc313ff57929d95d36216e3e6ecec3877673
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/uninstall.py
@@ -0,0 +1,113 @@
+import logging
+from optparse import Values
+from typing import List
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.base_command import Command
+from pip._internal.cli.req_command import SessionCommandMixin, warn_if_run_as_root
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.exceptions import InstallationError
+from pip._internal.req import parse_requirements
+from pip._internal.req.constructors import (
+    install_req_from_line,
+    install_req_from_parsed_requirement,
+)
+from pip._internal.utils.misc import (
+    check_externally_managed,
+    protect_pip_from_modification_on_windows,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class UninstallCommand(Command, SessionCommandMixin):
+    """
+    Uninstall packages.
+
+    pip is able to uninstall most installed packages. Known exceptions are:
+
+    - Pure distutils packages installed with ``python setup.py install``, which
+      leave behind no metadata to determine what files were installed.
+    - Script wrappers installed by ``python setup.py develop``.
+    """
+
+    usage = """
+      %prog [options]  ...
+      %prog [options] -r  ..."""
+
+    def add_options(self) -> None:
+        self.cmd_opts.add_option(
+            "-r",
+            "--requirement",
+            dest="requirements",
+            action="append",
+            default=[],
+            metavar="file",
+            help=(
+                "Uninstall all the packages listed in the given requirements "
+                "file.  This option can be used multiple times."
+            ),
+        )
+        self.cmd_opts.add_option(
+            "-y",
+            "--yes",
+            dest="yes",
+            action="store_true",
+            help="Don't ask for confirmation of uninstall deletions.",
+        )
+        self.cmd_opts.add_option(cmdoptions.root_user_action())
+        self.cmd_opts.add_option(cmdoptions.override_externally_managed())
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    def run(self, options: Values, args: List[str]) -> int:
+        session = self.get_default_session(options)
+
+        reqs_to_uninstall = {}
+        for name in args:
+            req = install_req_from_line(
+                name,
+                isolated=options.isolated_mode,
+            )
+            if req.name:
+                reqs_to_uninstall[canonicalize_name(req.name)] = req
+            else:
+                logger.warning(
+                    "Invalid requirement: %r ignored -"
+                    " the uninstall command expects named"
+                    " requirements.",
+                    name,
+                )
+        for filename in options.requirements:
+            for parsed_req in parse_requirements(
+                filename, options=options, session=session
+            ):
+                req = install_req_from_parsed_requirement(
+                    parsed_req, isolated=options.isolated_mode
+                )
+                if req.name:
+                    reqs_to_uninstall[canonicalize_name(req.name)] = req
+        if not reqs_to_uninstall:
+            raise InstallationError(
+                f"You must give at least one requirement to {self.name} (see "
+                f'"pip help {self.name}")'
+            )
+
+        if not options.override_externally_managed:
+            check_externally_managed()
+
+        protect_pip_from_modification_on_windows(
+            modifying_pip="pip" in reqs_to_uninstall
+        )
+
+        for req in reqs_to_uninstall.values():
+            uninstall_pathset = req.uninstall(
+                auto_confirm=options.yes,
+                verbose=self.verbosity > 0,
+            )
+            if uninstall_pathset:
+                uninstall_pathset.commit()
+        if options.root_user_action == "warn":
+            warn_if_run_as_root()
+        return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..1afbd562c65832b985e0e5f350876cd723aa3b72
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/commands/wheel.py
@@ -0,0 +1,203 @@
+import logging
+import os
+import shutil
+from optparse import Values
+from typing import List
+
+from pip._internal.cache import WheelCache
+from pip._internal.cli import cmdoptions
+from pip._internal.cli.req_command import RequirementCommand, with_cleanup
+from pip._internal.cli.status_codes import SUCCESS
+from pip._internal.exceptions import CommandError
+from pip._internal.operations.build.build_tracker import get_build_tracker
+from pip._internal.req.req_install import (
+    InstallRequirement,
+    LegacySetupPyOptionsCheckMode,
+    check_legacy_setup_py_options,
+)
+from pip._internal.utils.deprecation import deprecated
+from pip._internal.utils.misc import ensure_dir, normalize_path
+from pip._internal.utils.temp_dir import TempDirectory
+from pip._internal.wheel_builder import build, should_build_for_wheel_command
+
+logger = logging.getLogger(__name__)
+
+
+class WheelCommand(RequirementCommand):
+    """
+    Build Wheel archives for your requirements and dependencies.
+
+    Wheel is a built-package format, and offers the advantage of not
+    recompiling your software during every install. For more details, see the
+    wheel docs: https://wheel.readthedocs.io/en/latest/
+
+    'pip wheel' uses the build system interface as described here:
+    https://pip.pypa.io/en/stable/reference/build-system/
+
+    """
+
+    usage = """
+      %prog [options]  ...
+      %prog [options] -r  ...
+      %prog [options] [-e]  ...
+      %prog [options] [-e]  ...
+      %prog [options]  ..."""
+
+    def add_options(self) -> None:
+
+        self.cmd_opts.add_option(
+            "-w",
+            "--wheel-dir",
+            dest="wheel_dir",
+            metavar="dir",
+            default=os.curdir,
+            help=(
+                "Build wheels into , where the default is the "
+                "current working directory."
+            ),
+        )
+        self.cmd_opts.add_option(cmdoptions.no_binary())
+        self.cmd_opts.add_option(cmdoptions.only_binary())
+        self.cmd_opts.add_option(cmdoptions.prefer_binary())
+        self.cmd_opts.add_option(cmdoptions.no_build_isolation())
+        self.cmd_opts.add_option(cmdoptions.use_pep517())
+        self.cmd_opts.add_option(cmdoptions.no_use_pep517())
+        self.cmd_opts.add_option(cmdoptions.check_build_deps())
+        self.cmd_opts.add_option(cmdoptions.constraints())
+        self.cmd_opts.add_option(cmdoptions.editable())
+        self.cmd_opts.add_option(cmdoptions.requirements())
+        self.cmd_opts.add_option(cmdoptions.src())
+        self.cmd_opts.add_option(cmdoptions.ignore_requires_python())
+        self.cmd_opts.add_option(cmdoptions.no_deps())
+        self.cmd_opts.add_option(cmdoptions.progress_bar())
+
+        self.cmd_opts.add_option(
+            "--no-verify",
+            dest="no_verify",
+            action="store_true",
+            default=False,
+            help="Don't verify if built wheel is valid.",
+        )
+
+        self.cmd_opts.add_option(cmdoptions.config_settings())
+        self.cmd_opts.add_option(cmdoptions.build_options())
+        self.cmd_opts.add_option(cmdoptions.global_options())
+
+        self.cmd_opts.add_option(
+            "--pre",
+            action="store_true",
+            default=False,
+            help=(
+                "Include pre-release and development versions. By default, "
+                "pip only finds stable versions."
+            ),
+        )
+
+        self.cmd_opts.add_option(cmdoptions.require_hashes())
+
+        index_opts = cmdoptions.make_option_group(
+            cmdoptions.index_group,
+            self.parser,
+        )
+
+        self.parser.insert_option_group(0, index_opts)
+        self.parser.insert_option_group(0, self.cmd_opts)
+
+    @with_cleanup
+    def run(self, options: Values, args: List[str]) -> int:
+        session = self.get_default_session(options)
+
+        finder = self._build_package_finder(options, session)
+        wheel_cache = WheelCache(options.cache_dir, options.format_control)
+
+        options.wheel_dir = normalize_path(options.wheel_dir)
+        ensure_dir(options.wheel_dir)
+
+        build_tracker = self.enter_context(get_build_tracker())
+
+        directory = TempDirectory(
+            delete=not options.no_clean,
+            kind="wheel",
+            globally_managed=True,
+        )
+
+        reqs = self.get_requirements(args, options, finder, session)
+        check_legacy_setup_py_options(
+            options, reqs, LegacySetupPyOptionsCheckMode.WHEEL
+        )
+
+        if "no-binary-enable-wheel-cache" in options.features_enabled:
+            # TODO: remove format_control from WheelCache when the deprecation cycle
+            # is over
+            wheel_cache = WheelCache(options.cache_dir)
+        else:
+            if options.format_control.no_binary:
+                deprecated(
+                    reason=(
+                        "--no-binary currently disables reading from "
+                        "the cache of locally built wheels. In the future "
+                        "--no-binary will not influence the wheel cache."
+                    ),
+                    replacement="to use the --no-cache-dir option",
+                    feature_flag="no-binary-enable-wheel-cache",
+                    issue=11453,
+                    gone_in="23.1",
+                )
+            wheel_cache = WheelCache(options.cache_dir, options.format_control)
+
+        preparer = self.make_requirement_preparer(
+            temp_build_dir=directory,
+            options=options,
+            build_tracker=build_tracker,
+            session=session,
+            finder=finder,
+            download_dir=options.wheel_dir,
+            use_user_site=False,
+            verbosity=self.verbosity,
+        )
+
+        resolver = self.make_resolver(
+            preparer=preparer,
+            finder=finder,
+            options=options,
+            wheel_cache=wheel_cache,
+            ignore_requires_python=options.ignore_requires_python,
+            use_pep517=options.use_pep517,
+        )
+
+        self.trace_basic_info(finder)
+
+        requirement_set = resolver.resolve(reqs, check_supported_wheels=True)
+
+        reqs_to_build: List[InstallRequirement] = []
+        for req in requirement_set.requirements.values():
+            if req.is_wheel:
+                preparer.save_linked_requirement(req)
+            elif should_build_for_wheel_command(req):
+                reqs_to_build.append(req)
+
+        # build wheels
+        build_successes, build_failures = build(
+            reqs_to_build,
+            wheel_cache=wheel_cache,
+            verify=(not options.no_verify),
+            build_options=options.build_options or [],
+            global_options=options.global_options or [],
+        )
+        for req in build_successes:
+            assert req.link and req.link.is_wheel
+            assert req.local_file_path
+            # copy from cache to target directory
+            try:
+                shutil.copy(req.local_file_path, options.wheel_dir)
+            except OSError as e:
+                logger.warning(
+                    "Building wheel for %s failed: %s",
+                    req.name,
+                    e,
+                )
+                build_failures.append(req)
+        if len(build_failures) != 0:
+            raise CommandError("Failed to build one or more wheels")
+
+        return SUCCESS
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/configuration.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/configuration.py
new file mode 100644
index 0000000000000000000000000000000000000000..8fd46c9b8e0dbab8716c33d349f55a494613ba8f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/configuration.py
@@ -0,0 +1,374 @@
+"""Configuration management setup
+
+Some terminology:
+- name
+  As written in config files.
+- value
+  Value associated with a name
+- key
+  Name combined with it's section (section.name)
+- variant
+  A single word describing where the configuration key-value pair came from
+"""
+
+import configparser
+import locale
+import os
+import sys
+from typing import Any, Dict, Iterable, List, NewType, Optional, Tuple
+
+from pip._internal.exceptions import (
+    ConfigurationError,
+    ConfigurationFileCouldNotBeLoaded,
+)
+from pip._internal.utils import appdirs
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.logging import getLogger
+from pip._internal.utils.misc import ensure_dir, enum
+
+RawConfigParser = configparser.RawConfigParser  # Shorthand
+Kind = NewType("Kind", str)
+
+CONFIG_BASENAME = "pip.ini" if WINDOWS else "pip.conf"
+ENV_NAMES_IGNORED = "version", "help"
+
+# The kinds of configurations there are.
+kinds = enum(
+    USER="user",  # User Specific
+    GLOBAL="global",  # System Wide
+    SITE="site",  # [Virtual] Environment Specific
+    ENV="env",  # from PIP_CONFIG_FILE
+    ENV_VAR="env-var",  # from Environment Variables
+)
+OVERRIDE_ORDER = kinds.GLOBAL, kinds.USER, kinds.SITE, kinds.ENV, kinds.ENV_VAR
+VALID_LOAD_ONLY = kinds.USER, kinds.GLOBAL, kinds.SITE
+
+logger = getLogger(__name__)
+
+
+# NOTE: Maybe use the optionx attribute to normalize keynames.
+def _normalize_name(name: str) -> str:
+    """Make a name consistent regardless of source (environment or file)"""
+    name = name.lower().replace("_", "-")
+    if name.startswith("--"):
+        name = name[2:]  # only prefer long opts
+    return name
+
+
+def _disassemble_key(name: str) -> List[str]:
+    if "." not in name:
+        error_message = (
+            "Key does not contain dot separated section and key. "
+            "Perhaps you wanted to use 'global.{}' instead?"
+        ).format(name)
+        raise ConfigurationError(error_message)
+    return name.split(".", 1)
+
+
+def get_configuration_files() -> Dict[Kind, List[str]]:
+    global_config_files = [
+        os.path.join(path, CONFIG_BASENAME) for path in appdirs.site_config_dirs("pip")
+    ]
+
+    site_config_file = os.path.join(sys.prefix, CONFIG_BASENAME)
+    legacy_config_file = os.path.join(
+        os.path.expanduser("~"),
+        "pip" if WINDOWS else ".pip",
+        CONFIG_BASENAME,
+    )
+    new_config_file = os.path.join(appdirs.user_config_dir("pip"), CONFIG_BASENAME)
+    return {
+        kinds.GLOBAL: global_config_files,
+        kinds.SITE: [site_config_file],
+        kinds.USER: [legacy_config_file, new_config_file],
+    }
+
+
+class Configuration:
+    """Handles management of configuration.
+
+    Provides an interface to accessing and managing configuration files.
+
+    This class converts provides an API that takes "section.key-name" style
+    keys and stores the value associated with it as "key-name" under the
+    section "section".
+
+    This allows for a clean interface wherein the both the section and the
+    key-name are preserved in an easy to manage form in the configuration files
+    and the data stored is also nice.
+    """
+
+    def __init__(self, isolated: bool, load_only: Optional[Kind] = None) -> None:
+        super().__init__()
+
+        if load_only is not None and load_only not in VALID_LOAD_ONLY:
+            raise ConfigurationError(
+                "Got invalid value for load_only - should be one of {}".format(
+                    ", ".join(map(repr, VALID_LOAD_ONLY))
+                )
+            )
+        self.isolated = isolated
+        self.load_only = load_only
+
+        # Because we keep track of where we got the data from
+        self._parsers: Dict[Kind, List[Tuple[str, RawConfigParser]]] = {
+            variant: [] for variant in OVERRIDE_ORDER
+        }
+        self._config: Dict[Kind, Dict[str, Any]] = {
+            variant: {} for variant in OVERRIDE_ORDER
+        }
+        self._modified_parsers: List[Tuple[str, RawConfigParser]] = []
+
+    def load(self) -> None:
+        """Loads configuration from configuration files and environment"""
+        self._load_config_files()
+        if not self.isolated:
+            self._load_environment_vars()
+
+    def get_file_to_edit(self) -> Optional[str]:
+        """Returns the file with highest priority in configuration"""
+        assert self.load_only is not None, "Need to be specified a file to be editing"
+
+        try:
+            return self._get_parser_to_modify()[0]
+        except IndexError:
+            return None
+
+    def items(self) -> Iterable[Tuple[str, Any]]:
+        """Returns key-value pairs like dict.items() representing the loaded
+        configuration
+        """
+        return self._dictionary.items()
+
+    def get_value(self, key: str) -> Any:
+        """Get a value from the configuration."""
+        orig_key = key
+        key = _normalize_name(key)
+        try:
+            return self._dictionary[key]
+        except KeyError:
+            # disassembling triggers a more useful error message than simply
+            # "No such key" in the case that the key isn't in the form command.option
+            _disassemble_key(key)
+            raise ConfigurationError(f"No such key - {orig_key}")
+
+    def set_value(self, key: str, value: Any) -> None:
+        """Modify a value in the configuration."""
+        key = _normalize_name(key)
+        self._ensure_have_load_only()
+
+        assert self.load_only
+        fname, parser = self._get_parser_to_modify()
+
+        if parser is not None:
+            section, name = _disassemble_key(key)
+
+            # Modify the parser and the configuration
+            if not parser.has_section(section):
+                parser.add_section(section)
+            parser.set(section, name, value)
+
+        self._config[self.load_only][key] = value
+        self._mark_as_modified(fname, parser)
+
+    def unset_value(self, key: str) -> None:
+        """Unset a value in the configuration."""
+        orig_key = key
+        key = _normalize_name(key)
+        self._ensure_have_load_only()
+
+        assert self.load_only
+        if key not in self._config[self.load_only]:
+            raise ConfigurationError(f"No such key - {orig_key}")
+
+        fname, parser = self._get_parser_to_modify()
+
+        if parser is not None:
+            section, name = _disassemble_key(key)
+            if not (
+                parser.has_section(section) and parser.remove_option(section, name)
+            ):
+                # The option was not removed.
+                raise ConfigurationError(
+                    "Fatal Internal error [id=1]. Please report as a bug."
+                )
+
+            # The section may be empty after the option was removed.
+            if not parser.items(section):
+                parser.remove_section(section)
+            self._mark_as_modified(fname, parser)
+
+        del self._config[self.load_only][key]
+
+    def save(self) -> None:
+        """Save the current in-memory state."""
+        self._ensure_have_load_only()
+
+        for fname, parser in self._modified_parsers:
+            logger.info("Writing to %s", fname)
+
+            # Ensure directory exists.
+            ensure_dir(os.path.dirname(fname))
+
+            with open(fname, "w") as f:
+                parser.write(f)
+
+    #
+    # Private routines
+    #
+
+    def _ensure_have_load_only(self) -> None:
+        if self.load_only is None:
+            raise ConfigurationError("Needed a specific file to be modifying.")
+        logger.debug("Will be working with %s variant only", self.load_only)
+
+    @property
+    def _dictionary(self) -> Dict[str, Any]:
+        """A dictionary representing the loaded configuration."""
+        # NOTE: Dictionaries are not populated if not loaded. So, conditionals
+        #       are not needed here.
+        retval = {}
+
+        for variant in OVERRIDE_ORDER:
+            retval.update(self._config[variant])
+
+        return retval
+
+    def _load_config_files(self) -> None:
+        """Loads configuration from configuration files"""
+        config_files = dict(self.iter_config_files())
+        if config_files[kinds.ENV][0:1] == [os.devnull]:
+            logger.debug(
+                "Skipping loading configuration files due to "
+                "environment's PIP_CONFIG_FILE being os.devnull"
+            )
+            return
+
+        for variant, files in config_files.items():
+            for fname in files:
+                # If there's specific variant set in `load_only`, load only
+                # that variant, not the others.
+                if self.load_only is not None and variant != self.load_only:
+                    logger.debug("Skipping file '%s' (variant: %s)", fname, variant)
+                    continue
+
+                parser = self._load_file(variant, fname)
+
+                # Keeping track of the parsers used
+                self._parsers[variant].append((fname, parser))
+
+    def _load_file(self, variant: Kind, fname: str) -> RawConfigParser:
+        logger.verbose("For variant '%s', will try loading '%s'", variant, fname)
+        parser = self._construct_parser(fname)
+
+        for section in parser.sections():
+            items = parser.items(section)
+            self._config[variant].update(self._normalized_keys(section, items))
+
+        return parser
+
+    def _construct_parser(self, fname: str) -> RawConfigParser:
+        parser = configparser.RawConfigParser()
+        # If there is no such file, don't bother reading it but create the
+        # parser anyway, to hold the data.
+        # Doing this is useful when modifying and saving files, where we don't
+        # need to construct a parser.
+        if os.path.exists(fname):
+            locale_encoding = locale.getpreferredencoding(False)
+            try:
+                parser.read(fname, encoding=locale_encoding)
+            except UnicodeDecodeError:
+                # See https://github.com/pypa/pip/issues/4963
+                raise ConfigurationFileCouldNotBeLoaded(
+                    reason=f"contains invalid {locale_encoding} characters",
+                    fname=fname,
+                )
+            except configparser.Error as error:
+                # See https://github.com/pypa/pip/issues/4893
+                raise ConfigurationFileCouldNotBeLoaded(error=error)
+        return parser
+
+    def _load_environment_vars(self) -> None:
+        """Loads configuration from environment variables"""
+        self._config[kinds.ENV_VAR].update(
+            self._normalized_keys(":env:", self.get_environ_vars())
+        )
+
+    def _normalized_keys(
+        self, section: str, items: Iterable[Tuple[str, Any]]
+    ) -> Dict[str, Any]:
+        """Normalizes items to construct a dictionary with normalized keys.
+
+        This routine is where the names become keys and are made the same
+        regardless of source - configuration files or environment.
+        """
+        normalized = {}
+        for name, val in items:
+            key = section + "." + _normalize_name(name)
+            normalized[key] = val
+        return normalized
+
+    def get_environ_vars(self) -> Iterable[Tuple[str, str]]:
+        """Returns a generator with all environmental vars with prefix PIP_"""
+        for key, val in os.environ.items():
+            if key.startswith("PIP_"):
+                name = key[4:].lower()
+                if name not in ENV_NAMES_IGNORED:
+                    yield name, val
+
+    # XXX: This is patched in the tests.
+    def iter_config_files(self) -> Iterable[Tuple[Kind, List[str]]]:
+        """Yields variant and configuration files associated with it.
+
+        This should be treated like items of a dictionary.
+        """
+        # SMELL: Move the conditions out of this function
+
+        # environment variables have the lowest priority
+        config_file = os.environ.get("PIP_CONFIG_FILE", None)
+        if config_file is not None:
+            yield kinds.ENV, [config_file]
+        else:
+            yield kinds.ENV, []
+
+        config_files = get_configuration_files()
+
+        # at the base we have any global configuration
+        yield kinds.GLOBAL, config_files[kinds.GLOBAL]
+
+        # per-user configuration next
+        should_load_user_config = not self.isolated and not (
+            config_file and os.path.exists(config_file)
+        )
+        if should_load_user_config:
+            # The legacy config file is overridden by the new config file
+            yield kinds.USER, config_files[kinds.USER]
+
+        # finally virtualenv configuration first trumping others
+        yield kinds.SITE, config_files[kinds.SITE]
+
+    def get_values_in_config(self, variant: Kind) -> Dict[str, Any]:
+        """Get values present in a config file"""
+        return self._config[variant]
+
+    def _get_parser_to_modify(self) -> Tuple[str, RawConfigParser]:
+        # Determine which parser to modify
+        assert self.load_only
+        parsers = self._parsers[self.load_only]
+        if not parsers:
+            # This should not happen if everything works correctly.
+            raise ConfigurationError(
+                "Fatal Internal error [id=2]. Please report as a bug."
+            )
+
+        # Use the highest priority parser.
+        return parsers[-1]
+
+    # XXX: This is patched in the tests.
+    def _mark_as_modified(self, fname: str, parser: RawConfigParser) -> None:
+        file_parser_tuple = (fname, parser)
+        if file_parser_tuple not in self._modified_parsers:
+            self._modified_parsers.append(file_parser_tuple)
+
+    def __repr__(self) -> str:
+        return f"{self.__class__.__name__}({self._dictionary!r})"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9a89a838b9a5cb264e9ae9d269fbedca6e2d6333
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/__init__.py
@@ -0,0 +1,21 @@
+from pip._internal.distributions.base import AbstractDistribution
+from pip._internal.distributions.sdist import SourceDistribution
+from pip._internal.distributions.wheel import WheelDistribution
+from pip._internal.req.req_install import InstallRequirement
+
+
+def make_distribution_for_install_requirement(
+    install_req: InstallRequirement,
+) -> AbstractDistribution:
+    """Returns a Distribution for the given InstallRequirement"""
+    # Editable requirements will always be source distributions. They use the
+    # legacy logic until we create a modern standard for them.
+    if install_req.editable:
+        return SourceDistribution(install_req)
+
+    # If it's a wheel, it's a WheelDistribution
+    if install_req.is_wheel:
+        return WheelDistribution(install_req)
+
+    # Otherwise, a SourceDistribution
+    return SourceDistribution(install_req)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/base.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..75ce2dc9057a20a957abe2fbd4ef094dc4196684
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/base.py
@@ -0,0 +1,39 @@
+import abc
+
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata.base import BaseDistribution
+from pip._internal.req import InstallRequirement
+
+
+class AbstractDistribution(metaclass=abc.ABCMeta):
+    """A base class for handling installable artifacts.
+
+    The requirements for anything installable are as follows:
+
+     - we must be able to determine the requirement name
+       (or we can't correctly handle the non-upgrade case).
+
+     - for packages with setup requirements, we must also be able
+       to determine their requirements without installing additional
+       packages (for the same reason as run-time dependencies)
+
+     - we must be able to create a Distribution object exposing the
+       above metadata.
+    """
+
+    def __init__(self, req: InstallRequirement) -> None:
+        super().__init__()
+        self.req = req
+
+    @abc.abstractmethod
+    def get_metadata_distribution(self) -> BaseDistribution:
+        raise NotImplementedError()
+
+    @abc.abstractmethod
+    def prepare_distribution_metadata(
+        self,
+        finder: PackageFinder,
+        build_isolation: bool,
+        check_build_deps: bool,
+    ) -> None:
+        raise NotImplementedError()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/installed.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/installed.py
new file mode 100644
index 0000000000000000000000000000000000000000..edb38aa1a6c54dcb73e2f74b6bdfff337841d99f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/installed.py
@@ -0,0 +1,23 @@
+from pip._internal.distributions.base import AbstractDistribution
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import BaseDistribution
+
+
+class InstalledDistribution(AbstractDistribution):
+    """Represents an installed package.
+
+    This does not need any preparation as the required information has already
+    been computed.
+    """
+
+    def get_metadata_distribution(self) -> BaseDistribution:
+        assert self.req.satisfied_by is not None, "not actually installed"
+        return self.req.satisfied_by
+
+    def prepare_distribution_metadata(
+        self,
+        finder: PackageFinder,
+        build_isolation: bool,
+        check_build_deps: bool,
+    ) -> None:
+        pass
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/sdist.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/sdist.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c25647930c6557d10e8a3ee92b68cfe3a07f7d7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/sdist.py
@@ -0,0 +1,150 @@
+import logging
+from typing import Iterable, Set, Tuple
+
+from pip._internal.build_env import BuildEnvironment
+from pip._internal.distributions.base import AbstractDistribution
+from pip._internal.exceptions import InstallationError
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import BaseDistribution
+from pip._internal.utils.subprocess import runner_with_spinner_message
+
+logger = logging.getLogger(__name__)
+
+
+class SourceDistribution(AbstractDistribution):
+    """Represents a source distribution.
+
+    The preparation step for these needs metadata for the packages to be
+    generated, either using PEP 517 or using the legacy `setup.py egg_info`.
+    """
+
+    def get_metadata_distribution(self) -> BaseDistribution:
+        return self.req.get_dist()
+
+    def prepare_distribution_metadata(
+        self,
+        finder: PackageFinder,
+        build_isolation: bool,
+        check_build_deps: bool,
+    ) -> None:
+        # Load pyproject.toml, to determine whether PEP 517 is to be used
+        self.req.load_pyproject_toml()
+
+        # Set up the build isolation, if this requirement should be isolated
+        should_isolate = self.req.use_pep517 and build_isolation
+        if should_isolate:
+            # Setup an isolated environment and install the build backend static
+            # requirements in it.
+            self._prepare_build_backend(finder)
+            # Check that if the requirement is editable, it either supports PEP 660 or
+            # has a setup.py or a setup.cfg. This cannot be done earlier because we need
+            # to setup the build backend to verify it supports build_editable, nor can
+            # it be done later, because we want to avoid installing build requirements
+            # needlessly. Doing it here also works around setuptools generating
+            # UNKNOWN.egg-info when running get_requires_for_build_wheel on a directory
+            # without setup.py nor setup.cfg.
+            self.req.isolated_editable_sanity_check()
+            # Install the dynamic build requirements.
+            self._install_build_reqs(finder)
+        # Check if the current environment provides build dependencies
+        should_check_deps = self.req.use_pep517 and check_build_deps
+        if should_check_deps:
+            pyproject_requires = self.req.pyproject_requires
+            assert pyproject_requires is not None
+            conflicting, missing = self.req.build_env.check_requirements(
+                pyproject_requires
+            )
+            if conflicting:
+                self._raise_conflicts("the backend dependencies", conflicting)
+            if missing:
+                self._raise_missing_reqs(missing)
+        self.req.prepare_metadata()
+
+    def _prepare_build_backend(self, finder: PackageFinder) -> None:
+        # Isolate in a BuildEnvironment and install the build-time
+        # requirements.
+        pyproject_requires = self.req.pyproject_requires
+        assert pyproject_requires is not None
+
+        self.req.build_env = BuildEnvironment()
+        self.req.build_env.install_requirements(
+            finder, pyproject_requires, "overlay", kind="build dependencies"
+        )
+        conflicting, missing = self.req.build_env.check_requirements(
+            self.req.requirements_to_check
+        )
+        if conflicting:
+            self._raise_conflicts("PEP 517/518 supported requirements", conflicting)
+        if missing:
+            logger.warning(
+                "Missing build requirements in pyproject.toml for %s.",
+                self.req,
+            )
+            logger.warning(
+                "The project does not specify a build backend, and "
+                "pip cannot fall back to setuptools without %s.",
+                " and ".join(map(repr, sorted(missing))),
+            )
+
+    def _get_build_requires_wheel(self) -> Iterable[str]:
+        with self.req.build_env:
+            runner = runner_with_spinner_message("Getting requirements to build wheel")
+            backend = self.req.pep517_backend
+            assert backend is not None
+            with backend.subprocess_runner(runner):
+                return backend.get_requires_for_build_wheel()
+
+    def _get_build_requires_editable(self) -> Iterable[str]:
+        with self.req.build_env:
+            runner = runner_with_spinner_message(
+                "Getting requirements to build editable"
+            )
+            backend = self.req.pep517_backend
+            assert backend is not None
+            with backend.subprocess_runner(runner):
+                return backend.get_requires_for_build_editable()
+
+    def _install_build_reqs(self, finder: PackageFinder) -> None:
+        # Install any extra build dependencies that the backend requests.
+        # This must be done in a second pass, as the pyproject.toml
+        # dependencies must be installed before we can call the backend.
+        if (
+            self.req.editable
+            and self.req.permit_editable_wheels
+            and self.req.supports_pyproject_editable()
+        ):
+            build_reqs = self._get_build_requires_editable()
+        else:
+            build_reqs = self._get_build_requires_wheel()
+        conflicting, missing = self.req.build_env.check_requirements(build_reqs)
+        if conflicting:
+            self._raise_conflicts("the backend dependencies", conflicting)
+        self.req.build_env.install_requirements(
+            finder, missing, "normal", kind="backend dependencies"
+        )
+
+    def _raise_conflicts(
+        self, conflicting_with: str, conflicting_reqs: Set[Tuple[str, str]]
+    ) -> None:
+        format_string = (
+            "Some build dependencies for {requirement} "
+            "conflict with {conflicting_with}: {description}."
+        )
+        error_message = format_string.format(
+            requirement=self.req,
+            conflicting_with=conflicting_with,
+            description=", ".join(
+                f"{installed} is incompatible with {wanted}"
+                for installed, wanted in sorted(conflicting_reqs)
+            ),
+        )
+        raise InstallationError(error_message)
+
+    def _raise_missing_reqs(self, missing: Set[str]) -> None:
+        format_string = (
+            "Some build dependencies for {requirement} are missing: {missing}."
+        )
+        error_message = format_string.format(
+            requirement=self.req, missing=", ".join(map(repr, sorted(missing)))
+        )
+        raise InstallationError(error_message)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..03aac775b53f2dd3153a9f44829e7987258950aa
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/distributions/wheel.py
@@ -0,0 +1,34 @@
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.distributions.base import AbstractDistribution
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import (
+    BaseDistribution,
+    FilesystemWheel,
+    get_wheel_distribution,
+)
+
+
+class WheelDistribution(AbstractDistribution):
+    """Represents a wheel distribution.
+
+    This does not need any preparation as wheels can be directly unpacked.
+    """
+
+    def get_metadata_distribution(self) -> BaseDistribution:
+        """Loads the metadata from the wheel file into memory and returns a
+        Distribution that uses it, not relying on the wheel file or
+        requirement.
+        """
+        assert self.req.local_file_path, "Set as part of preparation during download"
+        assert self.req.name, "Wheels are never unnamed"
+        wheel = FilesystemWheel(self.req.local_file_path)
+        return get_wheel_distribution(wheel, canonicalize_name(self.req.name))
+
+    def prepare_distribution_metadata(
+        self,
+        finder: PackageFinder,
+        build_isolation: bool,
+        check_build_deps: bool,
+    ) -> None:
+        pass
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/exceptions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/exceptions.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4527295da38d974938c194ee3b66bb4d7fb7024
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/exceptions.py
@@ -0,0 +1,747 @@
+"""Exceptions used throughout package.
+
+This module MUST NOT try to import from anything within `pip._internal` to
+operate. This is expected to be importable from any/all files within the
+subpackage and, thus, should not depend on them.
+"""
+
+import configparser
+import contextlib
+import locale
+import logging
+import pathlib
+import re
+import sys
+from itertools import chain, groupby, repeat
+from typing import TYPE_CHECKING, Dict, Iterator, List, Optional, Union
+
+from pip._vendor.requests.models import Request, Response
+from pip._vendor.rich.console import Console, ConsoleOptions, RenderResult
+from pip._vendor.rich.markup import escape
+from pip._vendor.rich.text import Text
+
+if TYPE_CHECKING:
+    from hashlib import _Hash
+    from typing import Literal
+
+    from pip._internal.metadata import BaseDistribution
+    from pip._internal.req.req_install import InstallRequirement
+
+logger = logging.getLogger(__name__)
+
+
+#
+# Scaffolding
+#
+def _is_kebab_case(s: str) -> bool:
+    return re.match(r"^[a-z]+(-[a-z]+)*$", s) is not None
+
+
+def _prefix_with_indent(
+    s: Union[Text, str],
+    console: Console,
+    *,
+    prefix: str,
+    indent: str,
+) -> Text:
+    if isinstance(s, Text):
+        text = s
+    else:
+        text = console.render_str(s)
+
+    return console.render_str(prefix, overflow="ignore") + console.render_str(
+        f"\n{indent}", overflow="ignore"
+    ).join(text.split(allow_blank=True))
+
+
+class PipError(Exception):
+    """The base pip error."""
+
+
+class DiagnosticPipError(PipError):
+    """An error, that presents diagnostic information to the user.
+
+    This contains a bunch of logic, to enable pretty presentation of our error
+    messages. Each error gets a unique reference. Each error can also include
+    additional context, a hint and/or a note -- which are presented with the
+    main error message in a consistent style.
+
+    This is adapted from the error output styling in `sphinx-theme-builder`.
+    """
+
+    reference: str
+
+    def __init__(
+        self,
+        *,
+        kind: 'Literal["error", "warning"]' = "error",
+        reference: Optional[str] = None,
+        message: Union[str, Text],
+        context: Optional[Union[str, Text]],
+        hint_stmt: Optional[Union[str, Text]],
+        note_stmt: Optional[Union[str, Text]] = None,
+        link: Optional[str] = None,
+    ) -> None:
+        # Ensure a proper reference is provided.
+        if reference is None:
+            assert hasattr(self, "reference"), "error reference not provided!"
+            reference = self.reference
+        assert _is_kebab_case(reference), "error reference must be kebab-case!"
+
+        self.kind = kind
+        self.reference = reference
+
+        self.message = message
+        self.context = context
+
+        self.note_stmt = note_stmt
+        self.hint_stmt = hint_stmt
+
+        self.link = link
+
+        super().__init__(f"<{self.__class__.__name__}: {self.reference}>")
+
+    def __repr__(self) -> str:
+        return (
+            f"<{self.__class__.__name__}("
+            f"reference={self.reference!r}, "
+            f"message={self.message!r}, "
+            f"context={self.context!r}, "
+            f"note_stmt={self.note_stmt!r}, "
+            f"hint_stmt={self.hint_stmt!r}"
+            ")>"
+        )
+
+    def __rich_console__(
+        self,
+        console: Console,
+        options: ConsoleOptions,
+    ) -> RenderResult:
+        colour = "red" if self.kind == "error" else "yellow"
+
+        yield f"[{colour} bold]{self.kind}[/]: [bold]{self.reference}[/]"
+        yield ""
+
+        if not options.ascii_only:
+            # Present the main message, with relevant context indented.
+            if self.context is not None:
+                yield _prefix_with_indent(
+                    self.message,
+                    console,
+                    prefix=f"[{colour}]×[/] ",
+                    indent=f"[{colour}]│[/] ",
+                )
+                yield _prefix_with_indent(
+                    self.context,
+                    console,
+                    prefix=f"[{colour}]╰─>[/] ",
+                    indent=f"[{colour}]   [/] ",
+                )
+            else:
+                yield _prefix_with_indent(
+                    self.message,
+                    console,
+                    prefix="[red]×[/] ",
+                    indent="  ",
+                )
+        else:
+            yield self.message
+            if self.context is not None:
+                yield ""
+                yield self.context
+
+        if self.note_stmt is not None or self.hint_stmt is not None:
+            yield ""
+
+        if self.note_stmt is not None:
+            yield _prefix_with_indent(
+                self.note_stmt,
+                console,
+                prefix="[magenta bold]note[/]: ",
+                indent="      ",
+            )
+        if self.hint_stmt is not None:
+            yield _prefix_with_indent(
+                self.hint_stmt,
+                console,
+                prefix="[cyan bold]hint[/]: ",
+                indent="      ",
+            )
+
+        if self.link is not None:
+            yield ""
+            yield f"Link: {self.link}"
+
+
+#
+# Actual Errors
+#
+class ConfigurationError(PipError):
+    """General exception in configuration"""
+
+
+class InstallationError(PipError):
+    """General exception during installation"""
+
+
+class UninstallationError(PipError):
+    """General exception during uninstallation"""
+
+
+class MissingPyProjectBuildRequires(DiagnosticPipError):
+    """Raised when pyproject.toml has `build-system`, but no `build-system.requires`."""
+
+    reference = "missing-pyproject-build-system-requires"
+
+    def __init__(self, *, package: str) -> None:
+        super().__init__(
+            message=f"Can not process {escape(package)}",
+            context=Text(
+                "This package has an invalid pyproject.toml file.\n"
+                "The [build-system] table is missing the mandatory `requires` key."
+            ),
+            note_stmt="This is an issue with the package mentioned above, not pip.",
+            hint_stmt=Text("See PEP 518 for the detailed specification."),
+        )
+
+
+class InvalidPyProjectBuildRequires(DiagnosticPipError):
+    """Raised when pyproject.toml an invalid `build-system.requires`."""
+
+    reference = "invalid-pyproject-build-system-requires"
+
+    def __init__(self, *, package: str, reason: str) -> None:
+        super().__init__(
+            message=f"Can not process {escape(package)}",
+            context=Text(
+                "This package has an invalid `build-system.requires` key in "
+                f"pyproject.toml.\n{reason}"
+            ),
+            note_stmt="This is an issue with the package mentioned above, not pip.",
+            hint_stmt=Text("See PEP 518 for the detailed specification."),
+        )
+
+
+class NoneMetadataError(PipError):
+    """Raised when accessing a Distribution's "METADATA" or "PKG-INFO".
+
+    This signifies an inconsistency, when the Distribution claims to have
+    the metadata file (if not, raise ``FileNotFoundError`` instead), but is
+    not actually able to produce its content. This may be due to permission
+    errors.
+    """
+
+    def __init__(
+        self,
+        dist: "BaseDistribution",
+        metadata_name: str,
+    ) -> None:
+        """
+        :param dist: A Distribution object.
+        :param metadata_name: The name of the metadata being accessed
+            (can be "METADATA" or "PKG-INFO").
+        """
+        self.dist = dist
+        self.metadata_name = metadata_name
+
+    def __str__(self) -> str:
+        # Use `dist` in the error message because its stringification
+        # includes more information, like the version and location.
+        return "None {} metadata found for distribution: {}".format(
+            self.metadata_name,
+            self.dist,
+        )
+
+
+class UserInstallationInvalid(InstallationError):
+    """A --user install is requested on an environment without user site."""
+
+    def __str__(self) -> str:
+        return "User base directory is not specified"
+
+
+class InvalidSchemeCombination(InstallationError):
+    def __str__(self) -> str:
+        before = ", ".join(str(a) for a in self.args[:-1])
+        return f"Cannot set {before} and {self.args[-1]} together"
+
+
+class DistributionNotFound(InstallationError):
+    """Raised when a distribution cannot be found to satisfy a requirement"""
+
+
+class RequirementsFileParseError(InstallationError):
+    """Raised when a general error occurs parsing a requirements file line."""
+
+
+class BestVersionAlreadyInstalled(PipError):
+    """Raised when the most up-to-date version of a package is already
+    installed."""
+
+
+class BadCommand(PipError):
+    """Raised when virtualenv or a command is not found"""
+
+
+class CommandError(PipError):
+    """Raised when there is an error in command-line arguments"""
+
+
+class PreviousBuildDirError(PipError):
+    """Raised when there's a previous conflicting build directory"""
+
+
+class NetworkConnectionError(PipError):
+    """HTTP connection error"""
+
+    def __init__(
+        self,
+        error_msg: str,
+        response: Optional[Response] = None,
+        request: Optional[Request] = None,
+    ) -> None:
+        """
+        Initialize NetworkConnectionError with  `request` and `response`
+        objects.
+        """
+        self.response = response
+        self.request = request
+        self.error_msg = error_msg
+        if (
+            self.response is not None
+            and not self.request
+            and hasattr(response, "request")
+        ):
+            self.request = self.response.request
+        super().__init__(error_msg, response, request)
+
+    def __str__(self) -> str:
+        return str(self.error_msg)
+
+
+class InvalidWheelFilename(InstallationError):
+    """Invalid wheel filename."""
+
+
+class UnsupportedWheel(InstallationError):
+    """Unsupported wheel."""
+
+
+class InvalidWheel(InstallationError):
+    """Invalid (e.g. corrupt) wheel."""
+
+    def __init__(self, location: str, name: str):
+        self.location = location
+        self.name = name
+
+    def __str__(self) -> str:
+        return f"Wheel '{self.name}' located at {self.location} is invalid."
+
+
+class MetadataInconsistent(InstallationError):
+    """Built metadata contains inconsistent information.
+
+    This is raised when the metadata contains values (e.g. name and version)
+    that do not match the information previously obtained from sdist filename,
+    user-supplied ``#egg=`` value, or an install requirement name.
+    """
+
+    def __init__(
+        self, ireq: "InstallRequirement", field: str, f_val: str, m_val: str
+    ) -> None:
+        self.ireq = ireq
+        self.field = field
+        self.f_val = f_val
+        self.m_val = m_val
+
+    def __str__(self) -> str:
+        return (
+            f"Requested {self.ireq} has inconsistent {self.field}: "
+            f"expected {self.f_val!r}, but metadata has {self.m_val!r}"
+        )
+
+
+class LegacyInstallFailure(DiagnosticPipError):
+    """Error occurred while executing `setup.py install`"""
+
+    reference = "legacy-install-failure"
+
+    def __init__(self, package_details: str) -> None:
+        super().__init__(
+            message="Encountered error while trying to install package.",
+            context=package_details,
+            hint_stmt="See above for output from the failure.",
+            note_stmt="This is an issue with the package mentioned above, not pip.",
+        )
+
+
+class InstallationSubprocessError(DiagnosticPipError, InstallationError):
+    """A subprocess call failed."""
+
+    reference = "subprocess-exited-with-error"
+
+    def __init__(
+        self,
+        *,
+        command_description: str,
+        exit_code: int,
+        output_lines: Optional[List[str]],
+    ) -> None:
+        if output_lines is None:
+            output_prompt = Text("See above for output.")
+        else:
+            output_prompt = (
+                Text.from_markup(f"[red][{len(output_lines)} lines of output][/]\n")
+                + Text("".join(output_lines))
+                + Text.from_markup(R"[red]\[end of output][/]")
+            )
+
+        super().__init__(
+            message=(
+                f"[green]{escape(command_description)}[/] did not run successfully.\n"
+                f"exit code: {exit_code}"
+            ),
+            context=output_prompt,
+            hint_stmt=None,
+            note_stmt=(
+                "This error originates from a subprocess, and is likely not a "
+                "problem with pip."
+            ),
+        )
+
+        self.command_description = command_description
+        self.exit_code = exit_code
+
+    def __str__(self) -> str:
+        return f"{self.command_description} exited with {self.exit_code}"
+
+
+class MetadataGenerationFailed(InstallationSubprocessError, InstallationError):
+    reference = "metadata-generation-failed"
+
+    def __init__(
+        self,
+        *,
+        package_details: str,
+    ) -> None:
+        super(InstallationSubprocessError, self).__init__(
+            message="Encountered error while generating package metadata.",
+            context=escape(package_details),
+            hint_stmt="See above for details.",
+            note_stmt="This is an issue with the package mentioned above, not pip.",
+        )
+
+    def __str__(self) -> str:
+        return "metadata generation failed"
+
+
+class HashErrors(InstallationError):
+    """Multiple HashError instances rolled into one for reporting"""
+
+    def __init__(self) -> None:
+        self.errors: List["HashError"] = []
+
+    def append(self, error: "HashError") -> None:
+        self.errors.append(error)
+
+    def __str__(self) -> str:
+        lines = []
+        self.errors.sort(key=lambda e: e.order)
+        for cls, errors_of_cls in groupby(self.errors, lambda e: e.__class__):
+            lines.append(cls.head)
+            lines.extend(e.body() for e in errors_of_cls)
+        if lines:
+            return "\n".join(lines)
+        return ""
+
+    def __bool__(self) -> bool:
+        return bool(self.errors)
+
+
+class HashError(InstallationError):
+    """
+    A failure to verify a package against known-good hashes
+
+    :cvar order: An int sorting hash exception classes by difficulty of
+        recovery (lower being harder), so the user doesn't bother fretting
+        about unpinned packages when he has deeper issues, like VCS
+        dependencies, to deal with. Also keeps error reports in a
+        deterministic order.
+    :cvar head: A section heading for display above potentially many
+        exceptions of this kind
+    :ivar req: The InstallRequirement that triggered this error. This is
+        pasted on after the exception is instantiated, because it's not
+        typically available earlier.
+
+    """
+
+    req: Optional["InstallRequirement"] = None
+    head = ""
+    order: int = -1
+
+    def body(self) -> str:
+        """Return a summary of me for display under the heading.
+
+        This default implementation simply prints a description of the
+        triggering requirement.
+
+        :param req: The InstallRequirement that provoked this error, with
+            its link already populated by the resolver's _populate_link().
+
+        """
+        return f"    {self._requirement_name()}"
+
+    def __str__(self) -> str:
+        return f"{self.head}\n{self.body()}"
+
+    def _requirement_name(self) -> str:
+        """Return a description of the requirement that triggered me.
+
+        This default implementation returns long description of the req, with
+        line numbers
+
+        """
+        return str(self.req) if self.req else "unknown package"
+
+
+class VcsHashUnsupported(HashError):
+    """A hash was provided for a version-control-system-based requirement, but
+    we don't have a method for hashing those."""
+
+    order = 0
+    head = (
+        "Can't verify hashes for these requirements because we don't "
+        "have a way to hash version control repositories:"
+    )
+
+
+class DirectoryUrlHashUnsupported(HashError):
+    """A hash was provided for a version-control-system-based requirement, but
+    we don't have a method for hashing those."""
+
+    order = 1
+    head = (
+        "Can't verify hashes for these file:// requirements because they "
+        "point to directories:"
+    )
+
+
+class HashMissing(HashError):
+    """A hash was needed for a requirement but is absent."""
+
+    order = 2
+    head = (
+        "Hashes are required in --require-hashes mode, but they are "
+        "missing from some requirements. Here is a list of those "
+        "requirements along with the hashes their downloaded archives "
+        "actually had. Add lines like these to your requirements files to "
+        "prevent tampering. (If you did not enable --require-hashes "
+        "manually, note that it turns on automatically when any package "
+        "has a hash.)"
+    )
+
+    def __init__(self, gotten_hash: str) -> None:
+        """
+        :param gotten_hash: The hash of the (possibly malicious) archive we
+            just downloaded
+        """
+        self.gotten_hash = gotten_hash
+
+    def body(self) -> str:
+        # Dodge circular import.
+        from pip._internal.utils.hashes import FAVORITE_HASH
+
+        package = None
+        if self.req:
+            # In the case of URL-based requirements, display the original URL
+            # seen in the requirements file rather than the package name,
+            # so the output can be directly copied into the requirements file.
+            package = (
+                self.req.original_link
+                if self.req.original_link
+                # In case someone feeds something downright stupid
+                # to InstallRequirement's constructor.
+                else getattr(self.req, "req", None)
+            )
+        return "    {} --hash={}:{}".format(
+            package or "unknown package", FAVORITE_HASH, self.gotten_hash
+        )
+
+
+class HashUnpinned(HashError):
+    """A requirement had a hash specified but was not pinned to a specific
+    version."""
+
+    order = 3
+    head = (
+        "In --require-hashes mode, all requirements must have their "
+        "versions pinned with ==. These do not:"
+    )
+
+
+class HashMismatch(HashError):
+    """
+    Distribution file hash values don't match.
+
+    :ivar package_name: The name of the package that triggered the hash
+        mismatch. Feel free to write to this after the exception is raise to
+        improve its error message.
+
+    """
+
+    order = 4
+    head = (
+        "THESE PACKAGES DO NOT MATCH THE HASHES FROM THE REQUIREMENTS "
+        "FILE. If you have updated the package versions, please update "
+        "the hashes. Otherwise, examine the package contents carefully; "
+        "someone may have tampered with them."
+    )
+
+    def __init__(self, allowed: Dict[str, List[str]], gots: Dict[str, "_Hash"]) -> None:
+        """
+        :param allowed: A dict of algorithm names pointing to lists of allowed
+            hex digests
+        :param gots: A dict of algorithm names pointing to hashes we
+            actually got from the files under suspicion
+        """
+        self.allowed = allowed
+        self.gots = gots
+
+    def body(self) -> str:
+        return "    {}:\n{}".format(self._requirement_name(), self._hash_comparison())
+
+    def _hash_comparison(self) -> str:
+        """
+        Return a comparison of actual and expected hash values.
+
+        Example::
+
+               Expected sha256 abcdeabcdeabcdeabcdeabcdeabcdeabcdeabcdeabcde
+                            or 123451234512345123451234512345123451234512345
+                    Got        bcdefbcdefbcdefbcdefbcdefbcdefbcdefbcdefbcdef
+
+        """
+
+        def hash_then_or(hash_name: str) -> "chain[str]":
+            # For now, all the decent hashes have 6-char names, so we can get
+            # away with hard-coding space literals.
+            return chain([hash_name], repeat("    or"))
+
+        lines: List[str] = []
+        for hash_name, expecteds in self.allowed.items():
+            prefix = hash_then_or(hash_name)
+            lines.extend(
+                ("        Expected {} {}".format(next(prefix), e)) for e in expecteds
+            )
+            lines.append(
+                "             Got        {}\n".format(self.gots[hash_name].hexdigest())
+            )
+        return "\n".join(lines)
+
+
+class UnsupportedPythonVersion(InstallationError):
+    """Unsupported python version according to Requires-Python package
+    metadata."""
+
+
+class ConfigurationFileCouldNotBeLoaded(ConfigurationError):
+    """When there are errors while loading a configuration file"""
+
+    def __init__(
+        self,
+        reason: str = "could not be loaded",
+        fname: Optional[str] = None,
+        error: Optional[configparser.Error] = None,
+    ) -> None:
+        super().__init__(error)
+        self.reason = reason
+        self.fname = fname
+        self.error = error
+
+    def __str__(self) -> str:
+        if self.fname is not None:
+            message_part = f" in {self.fname}."
+        else:
+            assert self.error is not None
+            message_part = f".\n{self.error}\n"
+        return f"Configuration file {self.reason}{message_part}"
+
+
+_DEFAULT_EXTERNALLY_MANAGED_ERROR = f"""\
+The Python environment under {sys.prefix} is managed externally, and may not be
+manipulated by the user. Please use specific tooling from the distributor of
+the Python installation to interact with this environment instead.
+"""
+
+
+class ExternallyManagedEnvironment(DiagnosticPipError):
+    """The current environment is externally managed.
+
+    This is raised when the current environment is externally managed, as
+    defined by `PEP 668`_. The ``EXTERNALLY-MANAGED`` configuration is checked
+    and displayed when the error is bubbled up to the user.
+
+    :param error: The error message read from ``EXTERNALLY-MANAGED``.
+    """
+
+    reference = "externally-managed-environment"
+
+    def __init__(self, error: Optional[str]) -> None:
+        if error is None:
+            context = Text(_DEFAULT_EXTERNALLY_MANAGED_ERROR)
+        else:
+            context = Text(error)
+        super().__init__(
+            message="This environment is externally managed",
+            context=context,
+            note_stmt=(
+                "If you believe this is a mistake, please contact your "
+                "Python installation or OS distribution provider. "
+                "You can override this, at the risk of breaking your Python "
+                "installation or OS, by passing --break-system-packages."
+            ),
+            hint_stmt=Text("See PEP 668 for the detailed specification."),
+        )
+
+    @staticmethod
+    def _iter_externally_managed_error_keys() -> Iterator[str]:
+        # LC_MESSAGES is in POSIX, but not the C standard. The most common
+        # platform that does not implement this category is Windows, where
+        # using other categories for console message localization is equally
+        # unreliable, so we fall back to the locale-less vendor message. This
+        # can always be re-evaluated when a vendor proposes a new alternative.
+        try:
+            category = locale.LC_MESSAGES
+        except AttributeError:
+            lang: Optional[str] = None
+        else:
+            lang, _ = locale.getlocale(category)
+        if lang is not None:
+            yield f"Error-{lang}"
+            for sep in ("-", "_"):
+                before, found, _ = lang.partition(sep)
+                if not found:
+                    continue
+                yield f"Error-{before}"
+        yield "Error"
+
+    @classmethod
+    def from_config(
+        cls,
+        config: Union[pathlib.Path, str],
+    ) -> "ExternallyManagedEnvironment":
+        parser = configparser.ConfigParser(interpolation=None)
+        try:
+            parser.read(config, encoding="utf-8")
+            section = parser["externally-managed"]
+            for key in cls._iter_externally_managed_error_keys():
+                with contextlib.suppress(KeyError):
+                    return cls(section[key])
+        except KeyError:
+            pass
+        except (OSError, UnicodeDecodeError, configparser.ParsingError):
+            from pip._internal.utils._log import VERBOSE
+
+            exc_info = logger.isEnabledFor(VERBOSE)
+            logger.warning("Failed to read %s", config, exc_info=exc_info)
+        return cls(None)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..7a17b7b3b6ad49157ee41f3da304fec3d32342d3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/__init__.py
@@ -0,0 +1,2 @@
+"""Index interaction code
+"""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/collector.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/collector.py
new file mode 100644
index 0000000000000000000000000000000000000000..b3e293ea3a508dc54674349e845f9794118f548b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/collector.py
@@ -0,0 +1,505 @@
+"""
+The main purpose of this module is to expose LinkCollector.collect_sources().
+"""
+
+import collections
+import email.message
+import functools
+import itertools
+import json
+import logging
+import os
+import urllib.parse
+import urllib.request
+from html.parser import HTMLParser
+from optparse import Values
+from typing import (
+    TYPE_CHECKING,
+    Callable,
+    Dict,
+    Iterable,
+    List,
+    MutableMapping,
+    NamedTuple,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+)
+
+from pip._vendor import requests
+from pip._vendor.requests import Response
+from pip._vendor.requests.exceptions import RetryError, SSLError
+
+from pip._internal.exceptions import NetworkConnectionError
+from pip._internal.models.link import Link
+from pip._internal.models.search_scope import SearchScope
+from pip._internal.network.session import PipSession
+from pip._internal.network.utils import raise_for_status
+from pip._internal.utils.filetypes import is_archive_file
+from pip._internal.utils.misc import redact_auth_from_url
+from pip._internal.vcs import vcs
+
+from .sources import CandidatesFromPage, LinkSource, build_source
+
+if TYPE_CHECKING:
+    from typing import Protocol
+else:
+    Protocol = object
+
+logger = logging.getLogger(__name__)
+
+ResponseHeaders = MutableMapping[str, str]
+
+
+def _match_vcs_scheme(url: str) -> Optional[str]:
+    """Look for VCS schemes in the URL.
+
+    Returns the matched VCS scheme, or None if there's no match.
+    """
+    for scheme in vcs.schemes:
+        if url.lower().startswith(scheme) and url[len(scheme)] in "+:":
+            return scheme
+    return None
+
+
+class _NotAPIContent(Exception):
+    def __init__(self, content_type: str, request_desc: str) -> None:
+        super().__init__(content_type, request_desc)
+        self.content_type = content_type
+        self.request_desc = request_desc
+
+
+def _ensure_api_header(response: Response) -> None:
+    """
+    Check the Content-Type header to ensure the response contains a Simple
+    API Response.
+
+    Raises `_NotAPIContent` if the content type is not a valid content-type.
+    """
+    content_type = response.headers.get("Content-Type", "Unknown")
+
+    content_type_l = content_type.lower()
+    if content_type_l.startswith(
+        (
+            "text/html",
+            "application/vnd.pypi.simple.v1+html",
+            "application/vnd.pypi.simple.v1+json",
+        )
+    ):
+        return
+
+    raise _NotAPIContent(content_type, response.request.method)
+
+
+class _NotHTTP(Exception):
+    pass
+
+
+def _ensure_api_response(url: str, session: PipSession) -> None:
+    """
+    Send a HEAD request to the URL, and ensure the response contains a simple
+    API Response.
+
+    Raises `_NotHTTP` if the URL is not available for a HEAD request, or
+    `_NotAPIContent` if the content type is not a valid content type.
+    """
+    scheme, netloc, path, query, fragment = urllib.parse.urlsplit(url)
+    if scheme not in {"http", "https"}:
+        raise _NotHTTP()
+
+    resp = session.head(url, allow_redirects=True)
+    raise_for_status(resp)
+
+    _ensure_api_header(resp)
+
+
+def _get_simple_response(url: str, session: PipSession) -> Response:
+    """Access an Simple API response with GET, and return the response.
+
+    This consists of three parts:
+
+    1. If the URL looks suspiciously like an archive, send a HEAD first to
+       check the Content-Type is HTML or Simple API, to avoid downloading a
+       large file. Raise `_NotHTTP` if the content type cannot be determined, or
+       `_NotAPIContent` if it is not HTML or a Simple API.
+    2. Actually perform the request. Raise HTTP exceptions on network failures.
+    3. Check the Content-Type header to make sure we got a Simple API response,
+       and raise `_NotAPIContent` otherwise.
+    """
+    if is_archive_file(Link(url).filename):
+        _ensure_api_response(url, session=session)
+
+    logger.debug("Getting page %s", redact_auth_from_url(url))
+
+    resp = session.get(
+        url,
+        headers={
+            "Accept": ", ".join(
+                [
+                    "application/vnd.pypi.simple.v1+json",
+                    "application/vnd.pypi.simple.v1+html; q=0.1",
+                    "text/html; q=0.01",
+                ]
+            ),
+            # We don't want to blindly returned cached data for
+            # /simple/, because authors generally expecting that
+            # twine upload && pip install will function, but if
+            # they've done a pip install in the last ~10 minutes
+            # it won't. Thus by setting this to zero we will not
+            # blindly use any cached data, however the benefit of
+            # using max-age=0 instead of no-cache, is that we will
+            # still support conditional requests, so we will still
+            # minimize traffic sent in cases where the page hasn't
+            # changed at all, we will just always incur the round
+            # trip for the conditional GET now instead of only
+            # once per 10 minutes.
+            # For more information, please see pypa/pip#5670.
+            "Cache-Control": "max-age=0",
+        },
+    )
+    raise_for_status(resp)
+
+    # The check for archives above only works if the url ends with
+    # something that looks like an archive. However that is not a
+    # requirement of an url. Unless we issue a HEAD request on every
+    # url we cannot know ahead of time for sure if something is a
+    # Simple API response or not. However we can check after we've
+    # downloaded it.
+    _ensure_api_header(resp)
+
+    logger.debug(
+        "Fetched page %s as %s",
+        redact_auth_from_url(url),
+        resp.headers.get("Content-Type", "Unknown"),
+    )
+
+    return resp
+
+
+def _get_encoding_from_headers(headers: ResponseHeaders) -> Optional[str]:
+    """Determine if we have any encoding information in our headers."""
+    if headers and "Content-Type" in headers:
+        m = email.message.Message()
+        m["content-type"] = headers["Content-Type"]
+        charset = m.get_param("charset")
+        if charset:
+            return str(charset)
+    return None
+
+
+class CacheablePageContent:
+    def __init__(self, page: "IndexContent") -> None:
+        assert page.cache_link_parsing
+        self.page = page
+
+    def __eq__(self, other: object) -> bool:
+        return isinstance(other, type(self)) and self.page.url == other.page.url
+
+    def __hash__(self) -> int:
+        return hash(self.page.url)
+
+
+class ParseLinks(Protocol):
+    def __call__(self, page: "IndexContent") -> Iterable[Link]:
+        ...
+
+
+def with_cached_index_content(fn: ParseLinks) -> ParseLinks:
+    """
+    Given a function that parses an Iterable[Link] from an IndexContent, cache the
+    function's result (keyed by CacheablePageContent), unless the IndexContent
+    `page` has `page.cache_link_parsing == False`.
+    """
+
+    @functools.lru_cache(maxsize=None)
+    def wrapper(cacheable_page: CacheablePageContent) -> List[Link]:
+        return list(fn(cacheable_page.page))
+
+    @functools.wraps(fn)
+    def wrapper_wrapper(page: "IndexContent") -> List[Link]:
+        if page.cache_link_parsing:
+            return wrapper(CacheablePageContent(page))
+        return list(fn(page))
+
+    return wrapper_wrapper
+
+
+@with_cached_index_content
+def parse_links(page: "IndexContent") -> Iterable[Link]:
+    """
+    Parse a Simple API's Index Content, and yield its anchor elements as Link objects.
+    """
+
+    content_type_l = page.content_type.lower()
+    if content_type_l.startswith("application/vnd.pypi.simple.v1+json"):
+        data = json.loads(page.content)
+        for file in data.get("files", []):
+            link = Link.from_json(file, page.url)
+            if link is None:
+                continue
+            yield link
+        return
+
+    parser = HTMLLinkParser(page.url)
+    encoding = page.encoding or "utf-8"
+    parser.feed(page.content.decode(encoding))
+
+    url = page.url
+    base_url = parser.base_url or url
+    for anchor in parser.anchors:
+        link = Link.from_element(anchor, page_url=url, base_url=base_url)
+        if link is None:
+            continue
+        yield link
+
+
+class IndexContent:
+    """Represents one response (or page), along with its URL"""
+
+    def __init__(
+        self,
+        content: bytes,
+        content_type: str,
+        encoding: Optional[str],
+        url: str,
+        cache_link_parsing: bool = True,
+    ) -> None:
+        """
+        :param encoding: the encoding to decode the given content.
+        :param url: the URL from which the HTML was downloaded.
+        :param cache_link_parsing: whether links parsed from this page's url
+                                   should be cached. PyPI index urls should
+                                   have this set to False, for example.
+        """
+        self.content = content
+        self.content_type = content_type
+        self.encoding = encoding
+        self.url = url
+        self.cache_link_parsing = cache_link_parsing
+
+    def __str__(self) -> str:
+        return redact_auth_from_url(self.url)
+
+
+class HTMLLinkParser(HTMLParser):
+    """
+    HTMLParser that keeps the first base HREF and a list of all anchor
+    elements' attributes.
+    """
+
+    def __init__(self, url: str) -> None:
+        super().__init__(convert_charrefs=True)
+
+        self.url: str = url
+        self.base_url: Optional[str] = None
+        self.anchors: List[Dict[str, Optional[str]]] = []
+
+    def handle_starttag(self, tag: str, attrs: List[Tuple[str, Optional[str]]]) -> None:
+        if tag == "base" and self.base_url is None:
+            href = self.get_href(attrs)
+            if href is not None:
+                self.base_url = href
+        elif tag == "a":
+            self.anchors.append(dict(attrs))
+
+    def get_href(self, attrs: List[Tuple[str, Optional[str]]]) -> Optional[str]:
+        for name, value in attrs:
+            if name == "href":
+                return value
+        return None
+
+
+def _handle_get_simple_fail(
+    link: Link,
+    reason: Union[str, Exception],
+    meth: Optional[Callable[..., None]] = None,
+) -> None:
+    if meth is None:
+        meth = logger.debug
+    meth("Could not fetch URL %s: %s - skipping", link, reason)
+
+
+def _make_index_content(
+    response: Response, cache_link_parsing: bool = True
+) -> IndexContent:
+    encoding = _get_encoding_from_headers(response.headers)
+    return IndexContent(
+        response.content,
+        response.headers["Content-Type"],
+        encoding=encoding,
+        url=response.url,
+        cache_link_parsing=cache_link_parsing,
+    )
+
+
+def _get_index_content(link: Link, *, session: PipSession) -> Optional["IndexContent"]:
+    url = link.url.split("#", 1)[0]
+
+    # Check for VCS schemes that do not support lookup as web pages.
+    vcs_scheme = _match_vcs_scheme(url)
+    if vcs_scheme:
+        logger.warning(
+            "Cannot look at %s URL %s because it does not support lookup as web pages.",
+            vcs_scheme,
+            link,
+        )
+        return None
+
+    # Tack index.html onto file:// URLs that point to directories
+    scheme, _, path, _, _, _ = urllib.parse.urlparse(url)
+    if scheme == "file" and os.path.isdir(urllib.request.url2pathname(path)):
+        # add trailing slash if not present so urljoin doesn't trim
+        # final segment
+        if not url.endswith("/"):
+            url += "/"
+        # TODO: In the future, it would be nice if pip supported PEP 691
+        #       style responses in the file:// URLs, however there's no
+        #       standard file extension for application/vnd.pypi.simple.v1+json
+        #       so we'll need to come up with something on our own.
+        url = urllib.parse.urljoin(url, "index.html")
+        logger.debug(" file: URL is directory, getting %s", url)
+
+    try:
+        resp = _get_simple_response(url, session=session)
+    except _NotHTTP:
+        logger.warning(
+            "Skipping page %s because it looks like an archive, and cannot "
+            "be checked by a HTTP HEAD request.",
+            link,
+        )
+    except _NotAPIContent as exc:
+        logger.warning(
+            "Skipping page %s because the %s request got Content-Type: %s. "
+            "The only supported Content-Types are application/vnd.pypi.simple.v1+json, "
+            "application/vnd.pypi.simple.v1+html, and text/html",
+            link,
+            exc.request_desc,
+            exc.content_type,
+        )
+    except NetworkConnectionError as exc:
+        _handle_get_simple_fail(link, exc)
+    except RetryError as exc:
+        _handle_get_simple_fail(link, exc)
+    except SSLError as exc:
+        reason = "There was a problem confirming the ssl certificate: "
+        reason += str(exc)
+        _handle_get_simple_fail(link, reason, meth=logger.info)
+    except requests.ConnectionError as exc:
+        _handle_get_simple_fail(link, f"connection error: {exc}")
+    except requests.Timeout:
+        _handle_get_simple_fail(link, "timed out")
+    else:
+        return _make_index_content(resp, cache_link_parsing=link.cache_link_parsing)
+    return None
+
+
+class CollectedSources(NamedTuple):
+    find_links: Sequence[Optional[LinkSource]]
+    index_urls: Sequence[Optional[LinkSource]]
+
+
+class LinkCollector:
+
+    """
+    Responsible for collecting Link objects from all configured locations,
+    making network requests as needed.
+
+    The class's main method is its collect_sources() method.
+    """
+
+    def __init__(
+        self,
+        session: PipSession,
+        search_scope: SearchScope,
+    ) -> None:
+        self.search_scope = search_scope
+        self.session = session
+
+    @classmethod
+    def create(
+        cls,
+        session: PipSession,
+        options: Values,
+        suppress_no_index: bool = False,
+    ) -> "LinkCollector":
+        """
+        :param session: The Session to use to make requests.
+        :param suppress_no_index: Whether to ignore the --no-index option
+            when constructing the SearchScope object.
+        """
+        index_urls = [options.index_url] + options.extra_index_urls
+        if options.no_index and not suppress_no_index:
+            logger.debug(
+                "Ignoring indexes: %s",
+                ",".join(redact_auth_from_url(url) for url in index_urls),
+            )
+            index_urls = []
+
+        # Make sure find_links is a list before passing to create().
+        find_links = options.find_links or []
+
+        search_scope = SearchScope.create(
+            find_links=find_links,
+            index_urls=index_urls,
+            no_index=options.no_index,
+        )
+        link_collector = LinkCollector(
+            session=session,
+            search_scope=search_scope,
+        )
+        return link_collector
+
+    @property
+    def find_links(self) -> List[str]:
+        return self.search_scope.find_links
+
+    def fetch_response(self, location: Link) -> Optional[IndexContent]:
+        """
+        Fetch an HTML page containing package links.
+        """
+        return _get_index_content(location, session=self.session)
+
+    def collect_sources(
+        self,
+        project_name: str,
+        candidates_from_page: CandidatesFromPage,
+    ) -> CollectedSources:
+        # The OrderedDict calls deduplicate sources by URL.
+        index_url_sources = collections.OrderedDict(
+            build_source(
+                loc,
+                candidates_from_page=candidates_from_page,
+                page_validator=self.session.is_secure_origin,
+                expand_dir=False,
+                cache_link_parsing=False,
+            )
+            for loc in self.search_scope.get_index_urls_locations(project_name)
+        ).values()
+        find_links_sources = collections.OrderedDict(
+            build_source(
+                loc,
+                candidates_from_page=candidates_from_page,
+                page_validator=self.session.is_secure_origin,
+                expand_dir=True,
+                cache_link_parsing=True,
+            )
+            for loc in self.find_links
+        ).values()
+
+        if logger.isEnabledFor(logging.DEBUG):
+            lines = [
+                f"* {s.link}"
+                for s in itertools.chain(find_links_sources, index_url_sources)
+                if s is not None and s.link is not None
+            ]
+            lines = [
+                f"{len(lines)} location(s) to search "
+                f"for versions of {project_name}:"
+            ] + lines
+            logger.debug("\n".join(lines))
+
+        return CollectedSources(
+            find_links=list(find_links_sources),
+            index_urls=list(index_url_sources),
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/package_finder.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/package_finder.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6f8d57e854b77f60c04f59a7f3ff74476a5f5d6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/package_finder.py
@@ -0,0 +1,1029 @@
+"""Routines related to PyPI, indexes"""
+
+import enum
+import functools
+import itertools
+import logging
+import re
+from typing import TYPE_CHECKING, FrozenSet, Iterable, List, Optional, Set, Tuple, Union
+
+from pip._vendor.packaging import specifiers
+from pip._vendor.packaging.tags import Tag
+from pip._vendor.packaging.utils import canonicalize_name
+from pip._vendor.packaging.version import _BaseVersion
+from pip._vendor.packaging.version import parse as parse_version
+
+from pip._internal.exceptions import (
+    BestVersionAlreadyInstalled,
+    DistributionNotFound,
+    InvalidWheelFilename,
+    UnsupportedWheel,
+)
+from pip._internal.index.collector import LinkCollector, parse_links
+from pip._internal.models.candidate import InstallationCandidate
+from pip._internal.models.format_control import FormatControl
+from pip._internal.models.link import Link
+from pip._internal.models.search_scope import SearchScope
+from pip._internal.models.selection_prefs import SelectionPreferences
+from pip._internal.models.target_python import TargetPython
+from pip._internal.models.wheel import Wheel
+from pip._internal.req import InstallRequirement
+from pip._internal.utils._log import getLogger
+from pip._internal.utils.filetypes import WHEEL_EXTENSION
+from pip._internal.utils.hashes import Hashes
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.misc import build_netloc
+from pip._internal.utils.packaging import check_requires_python
+from pip._internal.utils.unpacking import SUPPORTED_EXTENSIONS
+
+if TYPE_CHECKING:
+    from pip._vendor.typing_extensions import TypeGuard
+
+__all__ = ["FormatControl", "BestCandidateResult", "PackageFinder"]
+
+
+logger = getLogger(__name__)
+
+BuildTag = Union[Tuple[()], Tuple[int, str]]
+CandidateSortingKey = Tuple[int, int, int, _BaseVersion, Optional[int], BuildTag]
+
+
+def _check_link_requires_python(
+    link: Link,
+    version_info: Tuple[int, int, int],
+    ignore_requires_python: bool = False,
+) -> bool:
+    """
+    Return whether the given Python version is compatible with a link's
+    "Requires-Python" value.
+
+    :param version_info: A 3-tuple of ints representing the Python
+        major-minor-micro version to check.
+    :param ignore_requires_python: Whether to ignore the "Requires-Python"
+        value if the given Python version isn't compatible.
+    """
+    try:
+        is_compatible = check_requires_python(
+            link.requires_python,
+            version_info=version_info,
+        )
+    except specifiers.InvalidSpecifier:
+        logger.debug(
+            "Ignoring invalid Requires-Python (%r) for link: %s",
+            link.requires_python,
+            link,
+        )
+    else:
+        if not is_compatible:
+            version = ".".join(map(str, version_info))
+            if not ignore_requires_python:
+                logger.verbose(
+                    "Link requires a different Python (%s not in: %r): %s",
+                    version,
+                    link.requires_python,
+                    link,
+                )
+                return False
+
+            logger.debug(
+                "Ignoring failed Requires-Python check (%s not in: %r) for link: %s",
+                version,
+                link.requires_python,
+                link,
+            )
+
+    return True
+
+
+class LinkType(enum.Enum):
+    candidate = enum.auto()
+    different_project = enum.auto()
+    yanked = enum.auto()
+    format_unsupported = enum.auto()
+    format_invalid = enum.auto()
+    platform_mismatch = enum.auto()
+    requires_python_mismatch = enum.auto()
+
+
+class LinkEvaluator:
+
+    """
+    Responsible for evaluating links for a particular project.
+    """
+
+    _py_version_re = re.compile(r"-py([123]\.?[0-9]?)$")
+
+    # Don't include an allow_yanked default value to make sure each call
+    # site considers whether yanked releases are allowed. This also causes
+    # that decision to be made explicit in the calling code, which helps
+    # people when reading the code.
+    def __init__(
+        self,
+        project_name: str,
+        canonical_name: str,
+        formats: FrozenSet[str],
+        target_python: TargetPython,
+        allow_yanked: bool,
+        ignore_requires_python: Optional[bool] = None,
+    ) -> None:
+        """
+        :param project_name: The user supplied package name.
+        :param canonical_name: The canonical package name.
+        :param formats: The formats allowed for this package. Should be a set
+            with 'binary' or 'source' or both in it.
+        :param target_python: The target Python interpreter to use when
+            evaluating link compatibility. This is used, for example, to
+            check wheel compatibility, as well as when checking the Python
+            version, e.g. the Python version embedded in a link filename
+            (or egg fragment) and against an HTML link's optional PEP 503
+            "data-requires-python" attribute.
+        :param allow_yanked: Whether files marked as yanked (in the sense
+            of PEP 592) are permitted to be candidates for install.
+        :param ignore_requires_python: Whether to ignore incompatible
+            PEP 503 "data-requires-python" values in HTML links. Defaults
+            to False.
+        """
+        if ignore_requires_python is None:
+            ignore_requires_python = False
+
+        self._allow_yanked = allow_yanked
+        self._canonical_name = canonical_name
+        self._ignore_requires_python = ignore_requires_python
+        self._formats = formats
+        self._target_python = target_python
+
+        self.project_name = project_name
+
+    def evaluate_link(self, link: Link) -> Tuple[LinkType, str]:
+        """
+        Determine whether a link is a candidate for installation.
+
+        :return: A tuple (result, detail), where *result* is an enum
+            representing whether the evaluation found a candidate, or the reason
+            why one is not found. If a candidate is found, *detail* will be the
+            candidate's version string; if one is not found, it contains the
+            reason the link fails to qualify.
+        """
+        version = None
+        if link.is_yanked and not self._allow_yanked:
+            reason = link.yanked_reason or ""
+            return (LinkType.yanked, f"yanked for reason: {reason}")
+
+        if link.egg_fragment:
+            egg_info = link.egg_fragment
+            ext = link.ext
+        else:
+            egg_info, ext = link.splitext()
+            if not ext:
+                return (LinkType.format_unsupported, "not a file")
+            if ext not in SUPPORTED_EXTENSIONS:
+                return (
+                    LinkType.format_unsupported,
+                    f"unsupported archive format: {ext}",
+                )
+            if "binary" not in self._formats and ext == WHEEL_EXTENSION:
+                reason = f"No binaries permitted for {self.project_name}"
+                return (LinkType.format_unsupported, reason)
+            if "macosx10" in link.path and ext == ".zip":
+                return (LinkType.format_unsupported, "macosx10 one")
+            if ext == WHEEL_EXTENSION:
+                try:
+                    wheel = Wheel(link.filename)
+                except InvalidWheelFilename:
+                    return (
+                        LinkType.format_invalid,
+                        "invalid wheel filename",
+                    )
+                if canonicalize_name(wheel.name) != self._canonical_name:
+                    reason = f"wrong project name (not {self.project_name})"
+                    return (LinkType.different_project, reason)
+
+                supported_tags = self._target_python.get_tags()
+                if not wheel.supported(supported_tags):
+                    # Include the wheel's tags in the reason string to
+                    # simplify troubleshooting compatibility issues.
+                    file_tags = ", ".join(wheel.get_formatted_file_tags())
+                    reason = (
+                        f"none of the wheel's tags ({file_tags}) are compatible "
+                        f"(run pip debug --verbose to show compatible tags)"
+                    )
+                    return (LinkType.platform_mismatch, reason)
+
+                version = wheel.version
+
+        # This should be up by the self.ok_binary check, but see issue 2700.
+        if "source" not in self._formats and ext != WHEEL_EXTENSION:
+            reason = f"No sources permitted for {self.project_name}"
+            return (LinkType.format_unsupported, reason)
+
+        if not version:
+            version = _extract_version_from_fragment(
+                egg_info,
+                self._canonical_name,
+            )
+        if not version:
+            reason = f"Missing project version for {self.project_name}"
+            return (LinkType.format_invalid, reason)
+
+        match = self._py_version_re.search(version)
+        if match:
+            version = version[: match.start()]
+            py_version = match.group(1)
+            if py_version != self._target_python.py_version:
+                return (
+                    LinkType.platform_mismatch,
+                    "Python version is incorrect",
+                )
+
+        supports_python = _check_link_requires_python(
+            link,
+            version_info=self._target_python.py_version_info,
+            ignore_requires_python=self._ignore_requires_python,
+        )
+        if not supports_python:
+            reason = f"{version} Requires-Python {link.requires_python}"
+            return (LinkType.requires_python_mismatch, reason)
+
+        logger.debug("Found link %s, version: %s", link, version)
+
+        return (LinkType.candidate, version)
+
+
+def filter_unallowed_hashes(
+    candidates: List[InstallationCandidate],
+    hashes: Optional[Hashes],
+    project_name: str,
+) -> List[InstallationCandidate]:
+    """
+    Filter out candidates whose hashes aren't allowed, and return a new
+    list of candidates.
+
+    If at least one candidate has an allowed hash, then all candidates with
+    either an allowed hash or no hash specified are returned.  Otherwise,
+    the given candidates are returned.
+
+    Including the candidates with no hash specified when there is a match
+    allows a warning to be logged if there is a more preferred candidate
+    with no hash specified.  Returning all candidates in the case of no
+    matches lets pip report the hash of the candidate that would otherwise
+    have been installed (e.g. permitting the user to more easily update
+    their requirements file with the desired hash).
+    """
+    if not hashes:
+        logger.debug(
+            "Given no hashes to check %s links for project %r: "
+            "discarding no candidates",
+            len(candidates),
+            project_name,
+        )
+        # Make sure we're not returning back the given value.
+        return list(candidates)
+
+    matches_or_no_digest = []
+    # Collect the non-matches for logging purposes.
+    non_matches = []
+    match_count = 0
+    for candidate in candidates:
+        link = candidate.link
+        if not link.has_hash:
+            pass
+        elif link.is_hash_allowed(hashes=hashes):
+            match_count += 1
+        else:
+            non_matches.append(candidate)
+            continue
+
+        matches_or_no_digest.append(candidate)
+
+    if match_count:
+        filtered = matches_or_no_digest
+    else:
+        # Make sure we're not returning back the given value.
+        filtered = list(candidates)
+
+    if len(filtered) == len(candidates):
+        discard_message = "discarding no candidates"
+    else:
+        discard_message = "discarding {} non-matches:\n  {}".format(
+            len(non_matches),
+            "\n  ".join(str(candidate.link) for candidate in non_matches),
+        )
+
+    logger.debug(
+        "Checked %s links for project %r against %s hashes "
+        "(%s matches, %s no digest): %s",
+        len(candidates),
+        project_name,
+        hashes.digest_count,
+        match_count,
+        len(matches_or_no_digest) - match_count,
+        discard_message,
+    )
+
+    return filtered
+
+
+class CandidatePreferences:
+
+    """
+    Encapsulates some of the preferences for filtering and sorting
+    InstallationCandidate objects.
+    """
+
+    def __init__(
+        self,
+        prefer_binary: bool = False,
+        allow_all_prereleases: bool = False,
+    ) -> None:
+        """
+        :param allow_all_prereleases: Whether to allow all pre-releases.
+        """
+        self.allow_all_prereleases = allow_all_prereleases
+        self.prefer_binary = prefer_binary
+
+
+class BestCandidateResult:
+    """A collection of candidates, returned by `PackageFinder.find_best_candidate`.
+
+    This class is only intended to be instantiated by CandidateEvaluator's
+    `compute_best_candidate()` method.
+    """
+
+    def __init__(
+        self,
+        candidates: List[InstallationCandidate],
+        applicable_candidates: List[InstallationCandidate],
+        best_candidate: Optional[InstallationCandidate],
+    ) -> None:
+        """
+        :param candidates: A sequence of all available candidates found.
+        :param applicable_candidates: The applicable candidates.
+        :param best_candidate: The most preferred candidate found, or None
+            if no applicable candidates were found.
+        """
+        assert set(applicable_candidates) <= set(candidates)
+
+        if best_candidate is None:
+            assert not applicable_candidates
+        else:
+            assert best_candidate in applicable_candidates
+
+        self._applicable_candidates = applicable_candidates
+        self._candidates = candidates
+
+        self.best_candidate = best_candidate
+
+    def iter_all(self) -> Iterable[InstallationCandidate]:
+        """Iterate through all candidates."""
+        return iter(self._candidates)
+
+    def iter_applicable(self) -> Iterable[InstallationCandidate]:
+        """Iterate through the applicable candidates."""
+        return iter(self._applicable_candidates)
+
+
+class CandidateEvaluator:
+
+    """
+    Responsible for filtering and sorting candidates for installation based
+    on what tags are valid.
+    """
+
+    @classmethod
+    def create(
+        cls,
+        project_name: str,
+        target_python: Optional[TargetPython] = None,
+        prefer_binary: bool = False,
+        allow_all_prereleases: bool = False,
+        specifier: Optional[specifiers.BaseSpecifier] = None,
+        hashes: Optional[Hashes] = None,
+    ) -> "CandidateEvaluator":
+        """Create a CandidateEvaluator object.
+
+        :param target_python: The target Python interpreter to use when
+            checking compatibility. If None (the default), a TargetPython
+            object will be constructed from the running Python.
+        :param specifier: An optional object implementing `filter`
+            (e.g. `packaging.specifiers.SpecifierSet`) to filter applicable
+            versions.
+        :param hashes: An optional collection of allowed hashes.
+        """
+        if target_python is None:
+            target_python = TargetPython()
+        if specifier is None:
+            specifier = specifiers.SpecifierSet()
+
+        supported_tags = target_python.get_tags()
+
+        return cls(
+            project_name=project_name,
+            supported_tags=supported_tags,
+            specifier=specifier,
+            prefer_binary=prefer_binary,
+            allow_all_prereleases=allow_all_prereleases,
+            hashes=hashes,
+        )
+
+    def __init__(
+        self,
+        project_name: str,
+        supported_tags: List[Tag],
+        specifier: specifiers.BaseSpecifier,
+        prefer_binary: bool = False,
+        allow_all_prereleases: bool = False,
+        hashes: Optional[Hashes] = None,
+    ) -> None:
+        """
+        :param supported_tags: The PEP 425 tags supported by the target
+            Python in order of preference (most preferred first).
+        """
+        self._allow_all_prereleases = allow_all_prereleases
+        self._hashes = hashes
+        self._prefer_binary = prefer_binary
+        self._project_name = project_name
+        self._specifier = specifier
+        self._supported_tags = supported_tags
+        # Since the index of the tag in the _supported_tags list is used
+        # as a priority, precompute a map from tag to index/priority to be
+        # used in wheel.find_most_preferred_tag.
+        self._wheel_tag_preferences = {
+            tag: idx for idx, tag in enumerate(supported_tags)
+        }
+
+    def get_applicable_candidates(
+        self,
+        candidates: List[InstallationCandidate],
+    ) -> List[InstallationCandidate]:
+        """
+        Return the applicable candidates from a list of candidates.
+        """
+        # Using None infers from the specifier instead.
+        allow_prereleases = self._allow_all_prereleases or None
+        specifier = self._specifier
+        versions = {
+            str(v)
+            for v in specifier.filter(
+                # We turn the version object into a str here because otherwise
+                # when we're debundled but setuptools isn't, Python will see
+                # packaging.version.Version and
+                # pkg_resources._vendor.packaging.version.Version as different
+                # types. This way we'll use a str as a common data interchange
+                # format. If we stop using the pkg_resources provided specifier
+                # and start using our own, we can drop the cast to str().
+                (str(c.version) for c in candidates),
+                prereleases=allow_prereleases,
+            )
+        }
+
+        # Again, converting version to str to deal with debundling.
+        applicable_candidates = [c for c in candidates if str(c.version) in versions]
+
+        filtered_applicable_candidates = filter_unallowed_hashes(
+            candidates=applicable_candidates,
+            hashes=self._hashes,
+            project_name=self._project_name,
+        )
+
+        return sorted(filtered_applicable_candidates, key=self._sort_key)
+
+    def _sort_key(self, candidate: InstallationCandidate) -> CandidateSortingKey:
+        """
+        Function to pass as the `key` argument to a call to sorted() to sort
+        InstallationCandidates by preference.
+
+        Returns a tuple such that tuples sorting as greater using Python's
+        default comparison operator are more preferred.
+
+        The preference is as follows:
+
+        First and foremost, candidates with allowed (matching) hashes are
+        always preferred over candidates without matching hashes. This is
+        because e.g. if the only candidate with an allowed hash is yanked,
+        we still want to use that candidate.
+
+        Second, excepting hash considerations, candidates that have been
+        yanked (in the sense of PEP 592) are always less preferred than
+        candidates that haven't been yanked. Then:
+
+        If not finding wheels, they are sorted by version only.
+        If finding wheels, then the sort order is by version, then:
+          1. existing installs
+          2. wheels ordered via Wheel.support_index_min(self._supported_tags)
+          3. source archives
+        If prefer_binary was set, then all wheels are sorted above sources.
+
+        Note: it was considered to embed this logic into the Link
+              comparison operators, but then different sdist links
+              with the same version, would have to be considered equal
+        """
+        valid_tags = self._supported_tags
+        support_num = len(valid_tags)
+        build_tag: BuildTag = ()
+        binary_preference = 0
+        link = candidate.link
+        if link.is_wheel:
+            # can raise InvalidWheelFilename
+            wheel = Wheel(link.filename)
+            try:
+                pri = -(
+                    wheel.find_most_preferred_tag(
+                        valid_tags, self._wheel_tag_preferences
+                    )
+                )
+            except ValueError:
+                raise UnsupportedWheel(
+                    "{} is not a supported wheel for this platform. It "
+                    "can't be sorted.".format(wheel.filename)
+                )
+            if self._prefer_binary:
+                binary_preference = 1
+            if wheel.build_tag is not None:
+                match = re.match(r"^(\d+)(.*)$", wheel.build_tag)
+                assert match is not None, "guaranteed by filename validation"
+                build_tag_groups = match.groups()
+                build_tag = (int(build_tag_groups[0]), build_tag_groups[1])
+        else:  # sdist
+            pri = -(support_num)
+        has_allowed_hash = int(link.is_hash_allowed(self._hashes))
+        yank_value = -1 * int(link.is_yanked)  # -1 for yanked.
+        return (
+            has_allowed_hash,
+            yank_value,
+            binary_preference,
+            candidate.version,
+            pri,
+            build_tag,
+        )
+
+    def sort_best_candidate(
+        self,
+        candidates: List[InstallationCandidate],
+    ) -> Optional[InstallationCandidate]:
+        """
+        Return the best candidate per the instance's sort order, or None if
+        no candidate is acceptable.
+        """
+        if not candidates:
+            return None
+        best_candidate = max(candidates, key=self._sort_key)
+        return best_candidate
+
+    def compute_best_candidate(
+        self,
+        candidates: List[InstallationCandidate],
+    ) -> BestCandidateResult:
+        """
+        Compute and return a `BestCandidateResult` instance.
+        """
+        applicable_candidates = self.get_applicable_candidates(candidates)
+
+        best_candidate = self.sort_best_candidate(applicable_candidates)
+
+        return BestCandidateResult(
+            candidates,
+            applicable_candidates=applicable_candidates,
+            best_candidate=best_candidate,
+        )
+
+
+class PackageFinder:
+    """This finds packages.
+
+    This is meant to match easy_install's technique for looking for
+    packages, by reading pages and looking for appropriate links.
+    """
+
+    def __init__(
+        self,
+        link_collector: LinkCollector,
+        target_python: TargetPython,
+        allow_yanked: bool,
+        format_control: Optional[FormatControl] = None,
+        candidate_prefs: Optional[CandidatePreferences] = None,
+        ignore_requires_python: Optional[bool] = None,
+    ) -> None:
+        """
+        This constructor is primarily meant to be used by the create() class
+        method and from tests.
+
+        :param format_control: A FormatControl object, used to control
+            the selection of source packages / binary packages when consulting
+            the index and links.
+        :param candidate_prefs: Options to use when creating a
+            CandidateEvaluator object.
+        """
+        if candidate_prefs is None:
+            candidate_prefs = CandidatePreferences()
+
+        format_control = format_control or FormatControl(set(), set())
+
+        self._allow_yanked = allow_yanked
+        self._candidate_prefs = candidate_prefs
+        self._ignore_requires_python = ignore_requires_python
+        self._link_collector = link_collector
+        self._target_python = target_python
+
+        self.format_control = format_control
+
+        # These are boring links that have already been logged somehow.
+        self._logged_links: Set[Tuple[Link, LinkType, str]] = set()
+
+    # Don't include an allow_yanked default value to make sure each call
+    # site considers whether yanked releases are allowed. This also causes
+    # that decision to be made explicit in the calling code, which helps
+    # people when reading the code.
+    @classmethod
+    def create(
+        cls,
+        link_collector: LinkCollector,
+        selection_prefs: SelectionPreferences,
+        target_python: Optional[TargetPython] = None,
+    ) -> "PackageFinder":
+        """Create a PackageFinder.
+
+        :param selection_prefs: The candidate selection preferences, as a
+            SelectionPreferences object.
+        :param target_python: The target Python interpreter to use when
+            checking compatibility. If None (the default), a TargetPython
+            object will be constructed from the running Python.
+        """
+        if target_python is None:
+            target_python = TargetPython()
+
+        candidate_prefs = CandidatePreferences(
+            prefer_binary=selection_prefs.prefer_binary,
+            allow_all_prereleases=selection_prefs.allow_all_prereleases,
+        )
+
+        return cls(
+            candidate_prefs=candidate_prefs,
+            link_collector=link_collector,
+            target_python=target_python,
+            allow_yanked=selection_prefs.allow_yanked,
+            format_control=selection_prefs.format_control,
+            ignore_requires_python=selection_prefs.ignore_requires_python,
+        )
+
+    @property
+    def target_python(self) -> TargetPython:
+        return self._target_python
+
+    @property
+    def search_scope(self) -> SearchScope:
+        return self._link_collector.search_scope
+
+    @search_scope.setter
+    def search_scope(self, search_scope: SearchScope) -> None:
+        self._link_collector.search_scope = search_scope
+
+    @property
+    def find_links(self) -> List[str]:
+        return self._link_collector.find_links
+
+    @property
+    def index_urls(self) -> List[str]:
+        return self.search_scope.index_urls
+
+    @property
+    def trusted_hosts(self) -> Iterable[str]:
+        for host_port in self._link_collector.session.pip_trusted_origins:
+            yield build_netloc(*host_port)
+
+    @property
+    def allow_all_prereleases(self) -> bool:
+        return self._candidate_prefs.allow_all_prereleases
+
+    def set_allow_all_prereleases(self) -> None:
+        self._candidate_prefs.allow_all_prereleases = True
+
+    @property
+    def prefer_binary(self) -> bool:
+        return self._candidate_prefs.prefer_binary
+
+    def set_prefer_binary(self) -> None:
+        self._candidate_prefs.prefer_binary = True
+
+    def requires_python_skipped_reasons(self) -> List[str]:
+        reasons = {
+            detail
+            for _, result, detail in self._logged_links
+            if result == LinkType.requires_python_mismatch
+        }
+        return sorted(reasons)
+
+    def make_link_evaluator(self, project_name: str) -> LinkEvaluator:
+        canonical_name = canonicalize_name(project_name)
+        formats = self.format_control.get_allowed_formats(canonical_name)
+
+        return LinkEvaluator(
+            project_name=project_name,
+            canonical_name=canonical_name,
+            formats=formats,
+            target_python=self._target_python,
+            allow_yanked=self._allow_yanked,
+            ignore_requires_python=self._ignore_requires_python,
+        )
+
+    def _sort_links(self, links: Iterable[Link]) -> List[Link]:
+        """
+        Returns elements of links in order, non-egg links first, egg links
+        second, while eliminating duplicates
+        """
+        eggs, no_eggs = [], []
+        seen: Set[Link] = set()
+        for link in links:
+            if link not in seen:
+                seen.add(link)
+                if link.egg_fragment:
+                    eggs.append(link)
+                else:
+                    no_eggs.append(link)
+        return no_eggs + eggs
+
+    def _log_skipped_link(self, link: Link, result: LinkType, detail: str) -> None:
+        entry = (link, result, detail)
+        if entry not in self._logged_links:
+            # Put the link at the end so the reason is more visible and because
+            # the link string is usually very long.
+            logger.debug("Skipping link: %s: %s", detail, link)
+            self._logged_links.add(entry)
+
+    def get_install_candidate(
+        self, link_evaluator: LinkEvaluator, link: Link
+    ) -> Optional[InstallationCandidate]:
+        """
+        If the link is a candidate for install, convert it to an
+        InstallationCandidate and return it. Otherwise, return None.
+        """
+        result, detail = link_evaluator.evaluate_link(link)
+        if result != LinkType.candidate:
+            self._log_skipped_link(link, result, detail)
+            return None
+
+        return InstallationCandidate(
+            name=link_evaluator.project_name,
+            link=link,
+            version=detail,
+        )
+
+    def evaluate_links(
+        self, link_evaluator: LinkEvaluator, links: Iterable[Link]
+    ) -> List[InstallationCandidate]:
+        """
+        Convert links that are candidates to InstallationCandidate objects.
+        """
+        candidates = []
+        for link in self._sort_links(links):
+            candidate = self.get_install_candidate(link_evaluator, link)
+            if candidate is not None:
+                candidates.append(candidate)
+
+        return candidates
+
+    def process_project_url(
+        self, project_url: Link, link_evaluator: LinkEvaluator
+    ) -> List[InstallationCandidate]:
+        logger.debug(
+            "Fetching project page and analyzing links: %s",
+            project_url,
+        )
+        index_response = self._link_collector.fetch_response(project_url)
+        if index_response is None:
+            return []
+
+        page_links = list(parse_links(index_response))
+
+        with indent_log():
+            package_links = self.evaluate_links(
+                link_evaluator,
+                links=page_links,
+            )
+
+        return package_links
+
+    @functools.lru_cache(maxsize=None)
+    def find_all_candidates(self, project_name: str) -> List[InstallationCandidate]:
+        """Find all available InstallationCandidate for project_name
+
+        This checks index_urls and find_links.
+        All versions found are returned as an InstallationCandidate list.
+
+        See LinkEvaluator.evaluate_link() for details on which files
+        are accepted.
+        """
+        link_evaluator = self.make_link_evaluator(project_name)
+
+        collected_sources = self._link_collector.collect_sources(
+            project_name=project_name,
+            candidates_from_page=functools.partial(
+                self.process_project_url,
+                link_evaluator=link_evaluator,
+            ),
+        )
+
+        page_candidates_it = itertools.chain.from_iterable(
+            source.page_candidates()
+            for sources in collected_sources
+            for source in sources
+            if source is not None
+        )
+        page_candidates = list(page_candidates_it)
+
+        file_links_it = itertools.chain.from_iterable(
+            source.file_links()
+            for sources in collected_sources
+            for source in sources
+            if source is not None
+        )
+        file_candidates = self.evaluate_links(
+            link_evaluator,
+            sorted(file_links_it, reverse=True),
+        )
+
+        if logger.isEnabledFor(logging.DEBUG) and file_candidates:
+            paths = []
+            for candidate in file_candidates:
+                assert candidate.link.url  # we need to have a URL
+                try:
+                    paths.append(candidate.link.file_path)
+                except Exception:
+                    paths.append(candidate.link.url)  # it's not a local file
+
+            logger.debug("Local files found: %s", ", ".join(paths))
+
+        # This is an intentional priority ordering
+        return file_candidates + page_candidates
+
+    def make_candidate_evaluator(
+        self,
+        project_name: str,
+        specifier: Optional[specifiers.BaseSpecifier] = None,
+        hashes: Optional[Hashes] = None,
+    ) -> CandidateEvaluator:
+        """Create a CandidateEvaluator object to use."""
+        candidate_prefs = self._candidate_prefs
+        return CandidateEvaluator.create(
+            project_name=project_name,
+            target_python=self._target_python,
+            prefer_binary=candidate_prefs.prefer_binary,
+            allow_all_prereleases=candidate_prefs.allow_all_prereleases,
+            specifier=specifier,
+            hashes=hashes,
+        )
+
+    @functools.lru_cache(maxsize=None)
+    def find_best_candidate(
+        self,
+        project_name: str,
+        specifier: Optional[specifiers.BaseSpecifier] = None,
+        hashes: Optional[Hashes] = None,
+    ) -> BestCandidateResult:
+        """Find matches for the given project and specifier.
+
+        :param specifier: An optional object implementing `filter`
+            (e.g. `packaging.specifiers.SpecifierSet`) to filter applicable
+            versions.
+
+        :return: A `BestCandidateResult` instance.
+        """
+        candidates = self.find_all_candidates(project_name)
+        candidate_evaluator = self.make_candidate_evaluator(
+            project_name=project_name,
+            specifier=specifier,
+            hashes=hashes,
+        )
+        return candidate_evaluator.compute_best_candidate(candidates)
+
+    def find_requirement(
+        self, req: InstallRequirement, upgrade: bool
+    ) -> Optional[InstallationCandidate]:
+        """Try to find a Link matching req
+
+        Expects req, an InstallRequirement and upgrade, a boolean
+        Returns a InstallationCandidate if found,
+        Raises DistributionNotFound or BestVersionAlreadyInstalled otherwise
+        """
+        hashes = req.hashes(trust_internet=False)
+        best_candidate_result = self.find_best_candidate(
+            req.name,
+            specifier=req.specifier,
+            hashes=hashes,
+        )
+        best_candidate = best_candidate_result.best_candidate
+
+        installed_version: Optional[_BaseVersion] = None
+        if req.satisfied_by is not None:
+            installed_version = req.satisfied_by.version
+
+        def _format_versions(cand_iter: Iterable[InstallationCandidate]) -> str:
+            # This repeated parse_version and str() conversion is needed to
+            # handle different vendoring sources from pip and pkg_resources.
+            # If we stop using the pkg_resources provided specifier and start
+            # using our own, we can drop the cast to str().
+            return (
+                ", ".join(
+                    sorted(
+                        {str(c.version) for c in cand_iter},
+                        key=parse_version,
+                    )
+                )
+                or "none"
+            )
+
+        if installed_version is None and best_candidate is None:
+            logger.critical(
+                "Could not find a version that satisfies the requirement %s "
+                "(from versions: %s)",
+                req,
+                _format_versions(best_candidate_result.iter_all()),
+            )
+
+            raise DistributionNotFound(
+                "No matching distribution found for {}".format(req)
+            )
+
+        def _should_install_candidate(
+            candidate: Optional[InstallationCandidate],
+        ) -> "TypeGuard[InstallationCandidate]":
+            if installed_version is None:
+                return True
+            if best_candidate is None:
+                return False
+            return best_candidate.version > installed_version
+
+        if not upgrade and installed_version is not None:
+            if _should_install_candidate(best_candidate):
+                logger.debug(
+                    "Existing installed version (%s) satisfies requirement "
+                    "(most up-to-date version is %s)",
+                    installed_version,
+                    best_candidate.version,
+                )
+            else:
+                logger.debug(
+                    "Existing installed version (%s) is most up-to-date and "
+                    "satisfies requirement",
+                    installed_version,
+                )
+            return None
+
+        if _should_install_candidate(best_candidate):
+            logger.debug(
+                "Using version %s (newest of versions: %s)",
+                best_candidate.version,
+                _format_versions(best_candidate_result.iter_applicable()),
+            )
+            return best_candidate
+
+        # We have an existing version, and its the best version
+        logger.debug(
+            "Installed version (%s) is most up-to-date (past versions: %s)",
+            installed_version,
+            _format_versions(best_candidate_result.iter_applicable()),
+        )
+        raise BestVersionAlreadyInstalled
+
+
+def _find_name_version_sep(fragment: str, canonical_name: str) -> int:
+    """Find the separator's index based on the package's canonical name.
+
+    :param fragment: A + filename "fragment" (stem) or
+        egg fragment.
+    :param canonical_name: The package's canonical name.
+
+    This function is needed since the canonicalized name does not necessarily
+    have the same length as the egg info's name part. An example::
+
+    >>> fragment = 'foo__bar-1.0'
+    >>> canonical_name = 'foo-bar'
+    >>> _find_name_version_sep(fragment, canonical_name)
+    8
+    """
+    # Project name and version must be separated by one single dash. Find all
+    # occurrences of dashes; if the string in front of it matches the canonical
+    # name, this is the one separating the name and version parts.
+    for i, c in enumerate(fragment):
+        if c != "-":
+            continue
+        if canonicalize_name(fragment[:i]) == canonical_name:
+            return i
+    raise ValueError(f"{fragment} does not match {canonical_name}")
+
+
+def _extract_version_from_fragment(fragment: str, canonical_name: str) -> Optional[str]:
+    """Parse the version string from a + filename
+    "fragment" (stem) or egg fragment.
+
+    :param fragment: The string to parse. E.g. foo-2.1
+    :param canonical_name: The canonicalized name of the package this
+        belongs to.
+    """
+    try:
+        version_start = _find_name_version_sep(fragment, canonical_name) + 1
+    except ValueError:
+        return None
+    version = fragment[version_start:]
+    if not version:
+        return None
+    return version
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/sources.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/sources.py
new file mode 100644
index 0000000000000000000000000000000000000000..eec3f12f7e394a9eba2ebc43cf754a0040cdebf3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/index/sources.py
@@ -0,0 +1,224 @@
+import logging
+import mimetypes
+import os
+import pathlib
+from typing import Callable, Iterable, Optional, Tuple
+
+from pip._internal.models.candidate import InstallationCandidate
+from pip._internal.models.link import Link
+from pip._internal.utils.urls import path_to_url, url_to_path
+from pip._internal.vcs import is_url
+
+logger = logging.getLogger(__name__)
+
+FoundCandidates = Iterable[InstallationCandidate]
+FoundLinks = Iterable[Link]
+CandidatesFromPage = Callable[[Link], Iterable[InstallationCandidate]]
+PageValidator = Callable[[Link], bool]
+
+
+class LinkSource:
+    @property
+    def link(self) -> Optional[Link]:
+        """Returns the underlying link, if there's one."""
+        raise NotImplementedError()
+
+    def page_candidates(self) -> FoundCandidates:
+        """Candidates found by parsing an archive listing HTML file."""
+        raise NotImplementedError()
+
+    def file_links(self) -> FoundLinks:
+        """Links found by specifying archives directly."""
+        raise NotImplementedError()
+
+
+def _is_html_file(file_url: str) -> bool:
+    return mimetypes.guess_type(file_url, strict=False)[0] == "text/html"
+
+
+class _FlatDirectorySource(LinkSource):
+    """Link source specified by ``--find-links=``.
+
+    This looks the content of the directory, and returns:
+
+    * ``page_candidates``: Links listed on each HTML file in the directory.
+    * ``file_candidates``: Archives in the directory.
+    """
+
+    def __init__(
+        self,
+        candidates_from_page: CandidatesFromPage,
+        path: str,
+    ) -> None:
+        self._candidates_from_page = candidates_from_page
+        self._path = pathlib.Path(os.path.realpath(path))
+
+    @property
+    def link(self) -> Optional[Link]:
+        return None
+
+    def page_candidates(self) -> FoundCandidates:
+        for path in self._path.iterdir():
+            url = path_to_url(str(path))
+            if not _is_html_file(url):
+                continue
+            yield from self._candidates_from_page(Link(url))
+
+    def file_links(self) -> FoundLinks:
+        for path in self._path.iterdir():
+            url = path_to_url(str(path))
+            if _is_html_file(url):
+                continue
+            yield Link(url)
+
+
+class _LocalFileSource(LinkSource):
+    """``--find-links=`` or ``--[extra-]index-url=``.
+
+    If a URL is supplied, it must be a ``file:`` URL. If a path is supplied to
+    the option, it is converted to a URL first. This returns:
+
+    * ``page_candidates``: Links listed on an HTML file.
+    * ``file_candidates``: The non-HTML file.
+    """
+
+    def __init__(
+        self,
+        candidates_from_page: CandidatesFromPage,
+        link: Link,
+    ) -> None:
+        self._candidates_from_page = candidates_from_page
+        self._link = link
+
+    @property
+    def link(self) -> Optional[Link]:
+        return self._link
+
+    def page_candidates(self) -> FoundCandidates:
+        if not _is_html_file(self._link.url):
+            return
+        yield from self._candidates_from_page(self._link)
+
+    def file_links(self) -> FoundLinks:
+        if _is_html_file(self._link.url):
+            return
+        yield self._link
+
+
+class _RemoteFileSource(LinkSource):
+    """``--find-links=`` or ``--[extra-]index-url=``.
+
+    This returns:
+
+    * ``page_candidates``: Links listed on an HTML file.
+    * ``file_candidates``: The non-HTML file.
+    """
+
+    def __init__(
+        self,
+        candidates_from_page: CandidatesFromPage,
+        page_validator: PageValidator,
+        link: Link,
+    ) -> None:
+        self._candidates_from_page = candidates_from_page
+        self._page_validator = page_validator
+        self._link = link
+
+    @property
+    def link(self) -> Optional[Link]:
+        return self._link
+
+    def page_candidates(self) -> FoundCandidates:
+        if not self._page_validator(self._link):
+            return
+        yield from self._candidates_from_page(self._link)
+
+    def file_links(self) -> FoundLinks:
+        yield self._link
+
+
+class _IndexDirectorySource(LinkSource):
+    """``--[extra-]index-url=``.
+
+    This is treated like a remote URL; ``candidates_from_page`` contains logic
+    for this by appending ``index.html`` to the link.
+    """
+
+    def __init__(
+        self,
+        candidates_from_page: CandidatesFromPage,
+        link: Link,
+    ) -> None:
+        self._candidates_from_page = candidates_from_page
+        self._link = link
+
+    @property
+    def link(self) -> Optional[Link]:
+        return self._link
+
+    def page_candidates(self) -> FoundCandidates:
+        yield from self._candidates_from_page(self._link)
+
+    def file_links(self) -> FoundLinks:
+        return ()
+
+
+def build_source(
+    location: str,
+    *,
+    candidates_from_page: CandidatesFromPage,
+    page_validator: PageValidator,
+    expand_dir: bool,
+    cache_link_parsing: bool,
+) -> Tuple[Optional[str], Optional[LinkSource]]:
+
+    path: Optional[str] = None
+    url: Optional[str] = None
+    if os.path.exists(location):  # Is a local path.
+        url = path_to_url(location)
+        path = location
+    elif location.startswith("file:"):  # A file: URL.
+        url = location
+        path = url_to_path(location)
+    elif is_url(location):
+        url = location
+
+    if url is None:
+        msg = (
+            "Location '%s' is ignored: "
+            "it is either a non-existing path or lacks a specific scheme."
+        )
+        logger.warning(msg, location)
+        return (None, None)
+
+    if path is None:
+        source: LinkSource = _RemoteFileSource(
+            candidates_from_page=candidates_from_page,
+            page_validator=page_validator,
+            link=Link(url, cache_link_parsing=cache_link_parsing),
+        )
+        return (url, source)
+
+    if os.path.isdir(path):
+        if expand_dir:
+            source = _FlatDirectorySource(
+                candidates_from_page=candidates_from_page,
+                path=path,
+            )
+        else:
+            source = _IndexDirectorySource(
+                candidates_from_page=candidates_from_page,
+                link=Link(url, cache_link_parsing=cache_link_parsing),
+            )
+        return (url, source)
+    elif os.path.isfile(path):
+        source = _LocalFileSource(
+            candidates_from_page=candidates_from_page,
+            link=Link(url, cache_link_parsing=cache_link_parsing),
+        )
+        return (url, source)
+    logger.warning(
+        "Location '%s' is ignored: it is neither a file nor a directory.",
+        location,
+    )
+    return (url, None)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d54bc63eba364bda3f869a0f3b1863b872f9682a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/__init__.py
@@ -0,0 +1,467 @@
+import functools
+import logging
+import os
+import pathlib
+import sys
+import sysconfig
+from typing import Any, Dict, Generator, Optional, Tuple
+
+from pip._internal.models.scheme import SCHEME_KEYS, Scheme
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.deprecation import deprecated
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+from . import _sysconfig
+from .base import (
+    USER_CACHE_DIR,
+    get_major_minor_version,
+    get_src_prefix,
+    is_osx_framework,
+    site_packages,
+    user_site,
+)
+
+__all__ = [
+    "USER_CACHE_DIR",
+    "get_bin_prefix",
+    "get_bin_user",
+    "get_major_minor_version",
+    "get_platlib",
+    "get_purelib",
+    "get_scheme",
+    "get_src_prefix",
+    "site_packages",
+    "user_site",
+]
+
+
+logger = logging.getLogger(__name__)
+
+
+_PLATLIBDIR: str = getattr(sys, "platlibdir", "lib")
+
+_USE_SYSCONFIG_DEFAULT = sys.version_info >= (3, 10)
+
+
+def _should_use_sysconfig() -> bool:
+    """This function determines the value of _USE_SYSCONFIG.
+
+    By default, pip uses sysconfig on Python 3.10+.
+    But Python distributors can override this decision by setting:
+        sysconfig._PIP_USE_SYSCONFIG = True / False
+    Rationale in https://github.com/pypa/pip/issues/10647
+
+    This is a function for testability, but should be constant during any one
+    run.
+    """
+    return bool(getattr(sysconfig, "_PIP_USE_SYSCONFIG", _USE_SYSCONFIG_DEFAULT))
+
+
+_USE_SYSCONFIG = _should_use_sysconfig()
+
+if not _USE_SYSCONFIG:
+    # Import distutils lazily to avoid deprecation warnings,
+    # but import it soon enough that it is in memory and available during
+    # a pip reinstall.
+    from . import _distutils
+
+# Be noisy about incompatibilities if this platforms "should" be using
+# sysconfig, but is explicitly opting out and using distutils instead.
+if _USE_SYSCONFIG_DEFAULT and not _USE_SYSCONFIG:
+    _MISMATCH_LEVEL = logging.WARNING
+else:
+    _MISMATCH_LEVEL = logging.DEBUG
+
+
+def _looks_like_bpo_44860() -> bool:
+    """The resolution to bpo-44860 will change this incorrect platlib.
+
+    See .
+    """
+    from distutils.command.install import INSTALL_SCHEMES
+
+    try:
+        unix_user_platlib = INSTALL_SCHEMES["unix_user"]["platlib"]
+    except KeyError:
+        return False
+    return unix_user_platlib == "$usersite"
+
+
+def _looks_like_red_hat_patched_platlib_purelib(scheme: Dict[str, str]) -> bool:
+    platlib = scheme["platlib"]
+    if "/$platlibdir/" in platlib:
+        platlib = platlib.replace("/$platlibdir/", f"/{_PLATLIBDIR}/")
+    if "/lib64/" not in platlib:
+        return False
+    unpatched = platlib.replace("/lib64/", "/lib/")
+    return unpatched.replace("$platbase/", "$base/") == scheme["purelib"]
+
+
+@functools.lru_cache(maxsize=None)
+def _looks_like_red_hat_lib() -> bool:
+    """Red Hat patches platlib in unix_prefix and unix_home, but not purelib.
+
+    This is the only way I can see to tell a Red Hat-patched Python.
+    """
+    from distutils.command.install import INSTALL_SCHEMES
+
+    return all(
+        k in INSTALL_SCHEMES
+        and _looks_like_red_hat_patched_platlib_purelib(INSTALL_SCHEMES[k])
+        for k in ("unix_prefix", "unix_home")
+    )
+
+
+@functools.lru_cache(maxsize=None)
+def _looks_like_debian_scheme() -> bool:
+    """Debian adds two additional schemes."""
+    from distutils.command.install import INSTALL_SCHEMES
+
+    return "deb_system" in INSTALL_SCHEMES and "unix_local" in INSTALL_SCHEMES
+
+
+@functools.lru_cache(maxsize=None)
+def _looks_like_red_hat_scheme() -> bool:
+    """Red Hat patches ``sys.prefix`` and ``sys.exec_prefix``.
+
+    Red Hat's ``00251-change-user-install-location.patch`` changes the install
+    command's ``prefix`` and ``exec_prefix`` to append ``"/local"``. This is
+    (fortunately?) done quite unconditionally, so we create a default command
+    object without any configuration to detect this.
+    """
+    from distutils.command.install import install
+    from distutils.dist import Distribution
+
+    cmd: Any = install(Distribution())
+    cmd.finalize_options()
+    return (
+        cmd.exec_prefix == f"{os.path.normpath(sys.exec_prefix)}/local"
+        and cmd.prefix == f"{os.path.normpath(sys.prefix)}/local"
+    )
+
+
+@functools.lru_cache(maxsize=None)
+def _looks_like_slackware_scheme() -> bool:
+    """Slackware patches sysconfig but fails to patch distutils and site.
+
+    Slackware changes sysconfig's user scheme to use ``"lib64"`` for the lib
+    path, but does not do the same to the site module.
+    """
+    if user_site is None:  # User-site not available.
+        return False
+    try:
+        paths = sysconfig.get_paths(scheme="posix_user", expand=False)
+    except KeyError:  # User-site not available.
+        return False
+    return "/lib64/" in paths["purelib"] and "/lib64/" not in user_site
+
+
+@functools.lru_cache(maxsize=None)
+def _looks_like_msys2_mingw_scheme() -> bool:
+    """MSYS2 patches distutils and sysconfig to use a UNIX-like scheme.
+
+    However, MSYS2 incorrectly patches sysconfig ``nt`` scheme. The fix is
+    likely going to be included in their 3.10 release, so we ignore the warning.
+    See msys2/MINGW-packages#9319.
+
+    MSYS2 MINGW's patch uses lowercase ``"lib"`` instead of the usual uppercase,
+    and is missing the final ``"site-packages"``.
+    """
+    paths = sysconfig.get_paths("nt", expand=False)
+    return all(
+        "Lib" not in p and "lib" in p and not p.endswith("site-packages")
+        for p in (paths[key] for key in ("platlib", "purelib"))
+    )
+
+
+def _fix_abiflags(parts: Tuple[str]) -> Generator[str, None, None]:
+    ldversion = sysconfig.get_config_var("LDVERSION")
+    abiflags = getattr(sys, "abiflags", None)
+
+    # LDVERSION does not end with sys.abiflags. Just return the path unchanged.
+    if not ldversion or not abiflags or not ldversion.endswith(abiflags):
+        yield from parts
+        return
+
+    # Strip sys.abiflags from LDVERSION-based path components.
+    for part in parts:
+        if part.endswith(ldversion):
+            part = part[: (0 - len(abiflags))]
+        yield part
+
+
+@functools.lru_cache(maxsize=None)
+def _warn_mismatched(old: pathlib.Path, new: pathlib.Path, *, key: str) -> None:
+    issue_url = "https://github.com/pypa/pip/issues/10151"
+    message = (
+        "Value for %s does not match. Please report this to <%s>"
+        "\ndistutils: %s"
+        "\nsysconfig: %s"
+    )
+    logger.log(_MISMATCH_LEVEL, message, key, issue_url, old, new)
+
+
+def _warn_if_mismatch(old: pathlib.Path, new: pathlib.Path, *, key: str) -> bool:
+    if old == new:
+        return False
+    _warn_mismatched(old, new, key=key)
+    return True
+
+
+@functools.lru_cache(maxsize=None)
+def _log_context(
+    *,
+    user: bool = False,
+    home: Optional[str] = None,
+    root: Optional[str] = None,
+    prefix: Optional[str] = None,
+) -> None:
+    parts = [
+        "Additional context:",
+        "user = %r",
+        "home = %r",
+        "root = %r",
+        "prefix = %r",
+    ]
+
+    logger.log(_MISMATCH_LEVEL, "\n".join(parts), user, home, root, prefix)
+
+
+def get_scheme(
+    dist_name: str,
+    user: bool = False,
+    home: Optional[str] = None,
+    root: Optional[str] = None,
+    isolated: bool = False,
+    prefix: Optional[str] = None,
+) -> Scheme:
+    new = _sysconfig.get_scheme(
+        dist_name,
+        user=user,
+        home=home,
+        root=root,
+        isolated=isolated,
+        prefix=prefix,
+    )
+    if _USE_SYSCONFIG:
+        return new
+
+    old = _distutils.get_scheme(
+        dist_name,
+        user=user,
+        home=home,
+        root=root,
+        isolated=isolated,
+        prefix=prefix,
+    )
+
+    warning_contexts = []
+    for k in SCHEME_KEYS:
+        old_v = pathlib.Path(getattr(old, k))
+        new_v = pathlib.Path(getattr(new, k))
+
+        if old_v == new_v:
+            continue
+
+        # distutils incorrectly put PyPy packages under ``site-packages/python``
+        # in the ``posix_home`` scheme, but PyPy devs said they expect the
+        # directory name to be ``pypy`` instead. So we treat this as a bug fix
+        # and not warn about it. See bpo-43307 and python/cpython#24628.
+        skip_pypy_special_case = (
+            sys.implementation.name == "pypy"
+            and home is not None
+            and k in ("platlib", "purelib")
+            and old_v.parent == new_v.parent
+            and old_v.name.startswith("python")
+            and new_v.name.startswith("pypy")
+        )
+        if skip_pypy_special_case:
+            continue
+
+        # sysconfig's ``osx_framework_user`` does not include ``pythonX.Y`` in
+        # the ``include`` value, but distutils's ``headers`` does. We'll let
+        # CPython decide whether this is a bug or feature. See bpo-43948.
+        skip_osx_framework_user_special_case = (
+            user
+            and is_osx_framework()
+            and k == "headers"
+            and old_v.parent.parent == new_v.parent
+            and old_v.parent.name.startswith("python")
+        )
+        if skip_osx_framework_user_special_case:
+            continue
+
+        # On Red Hat and derived Linux distributions, distutils is patched to
+        # use "lib64" instead of "lib" for platlib.
+        if k == "platlib" and _looks_like_red_hat_lib():
+            continue
+
+        # On Python 3.9+, sysconfig's posix_user scheme sets platlib against
+        # sys.platlibdir, but distutils's unix_user incorrectly coninutes
+        # using the same $usersite for both platlib and purelib. This creates a
+        # mismatch when sys.platlibdir is not "lib".
+        skip_bpo_44860 = (
+            user
+            and k == "platlib"
+            and not WINDOWS
+            and sys.version_info >= (3, 9)
+            and _PLATLIBDIR != "lib"
+            and _looks_like_bpo_44860()
+        )
+        if skip_bpo_44860:
+            continue
+
+        # Slackware incorrectly patches posix_user to use lib64 instead of lib,
+        # but not usersite to match the location.
+        skip_slackware_user_scheme = (
+            user
+            and k in ("platlib", "purelib")
+            and not WINDOWS
+            and _looks_like_slackware_scheme()
+        )
+        if skip_slackware_user_scheme:
+            continue
+
+        # Both Debian and Red Hat patch Python to place the system site under
+        # /usr/local instead of /usr. Debian also places lib in dist-packages
+        # instead of site-packages, but the /usr/local check should cover it.
+        skip_linux_system_special_case = (
+            not (user or home or prefix or running_under_virtualenv())
+            and old_v.parts[1:3] == ("usr", "local")
+            and len(new_v.parts) > 1
+            and new_v.parts[1] == "usr"
+            and (len(new_v.parts) < 3 or new_v.parts[2] != "local")
+            and (_looks_like_red_hat_scheme() or _looks_like_debian_scheme())
+        )
+        if skip_linux_system_special_case:
+            continue
+
+        # On Python 3.7 and earlier, sysconfig does not include sys.abiflags in
+        # the "pythonX.Y" part of the path, but distutils does.
+        skip_sysconfig_abiflag_bug = (
+            sys.version_info < (3, 8)
+            and not WINDOWS
+            and k in ("headers", "platlib", "purelib")
+            and tuple(_fix_abiflags(old_v.parts)) == new_v.parts
+        )
+        if skip_sysconfig_abiflag_bug:
+            continue
+
+        # MSYS2 MINGW's sysconfig patch does not include the "site-packages"
+        # part of the path. This is incorrect and will be fixed in MSYS.
+        skip_msys2_mingw_bug = (
+            WINDOWS and k in ("platlib", "purelib") and _looks_like_msys2_mingw_scheme()
+        )
+        if skip_msys2_mingw_bug:
+            continue
+
+        # CPython's POSIX install script invokes pip (via ensurepip) against the
+        # interpreter located in the source tree, not the install site. This
+        # triggers special logic in sysconfig that's not present in distutils.
+        # https://github.com/python/cpython/blob/8c21941ddaf/Lib/sysconfig.py#L178-L194
+        skip_cpython_build = (
+            sysconfig.is_python_build(check_home=True)
+            and not WINDOWS
+            and k in ("headers", "include", "platinclude")
+        )
+        if skip_cpython_build:
+            continue
+
+        warning_contexts.append((old_v, new_v, f"scheme.{k}"))
+
+    if not warning_contexts:
+        return old
+
+    # Check if this path mismatch is caused by distutils config files. Those
+    # files will no longer work once we switch to sysconfig, so this raises a
+    # deprecation message for them.
+    default_old = _distutils.distutils_scheme(
+        dist_name,
+        user,
+        home,
+        root,
+        isolated,
+        prefix,
+        ignore_config_files=True,
+    )
+    if any(default_old[k] != getattr(old, k) for k in SCHEME_KEYS):
+        deprecated(
+            reason=(
+                "Configuring installation scheme with distutils config files "
+                "is deprecated and will no longer work in the near future. If you "
+                "are using a Homebrew or Linuxbrew Python, please see discussion "
+                "at https://github.com/Homebrew/homebrew-core/issues/76621"
+            ),
+            replacement=None,
+            gone_in=None,
+        )
+        return old
+
+    # Post warnings about this mismatch so user can report them back.
+    for old_v, new_v, key in warning_contexts:
+        _warn_mismatched(old_v, new_v, key=key)
+    _log_context(user=user, home=home, root=root, prefix=prefix)
+
+    return old
+
+
+def get_bin_prefix() -> str:
+    new = _sysconfig.get_bin_prefix()
+    if _USE_SYSCONFIG:
+        return new
+
+    old = _distutils.get_bin_prefix()
+    if _warn_if_mismatch(pathlib.Path(old), pathlib.Path(new), key="bin_prefix"):
+        _log_context()
+    return old
+
+
+def get_bin_user() -> str:
+    return _sysconfig.get_scheme("", user=True).scripts
+
+
+def _looks_like_deb_system_dist_packages(value: str) -> bool:
+    """Check if the value is Debian's APT-controlled dist-packages.
+
+    Debian's ``distutils.sysconfig.get_python_lib()`` implementation returns the
+    default package path controlled by APT, but does not patch ``sysconfig`` to
+    do the same. This is similar to the bug worked around in ``get_scheme()``,
+    but here the default is ``deb_system`` instead of ``unix_local``. Ultimately
+    we can't do anything about this Debian bug, and this detection allows us to
+    skip the warning when needed.
+    """
+    if not _looks_like_debian_scheme():
+        return False
+    if value == "/usr/lib/python3/dist-packages":
+        return True
+    return False
+
+
+def get_purelib() -> str:
+    """Return the default pure-Python lib location."""
+    new = _sysconfig.get_purelib()
+    if _USE_SYSCONFIG:
+        return new
+
+    old = _distutils.get_purelib()
+    if _looks_like_deb_system_dist_packages(old):
+        return old
+    if _warn_if_mismatch(pathlib.Path(old), pathlib.Path(new), key="purelib"):
+        _log_context()
+    return old
+
+
+def get_platlib() -> str:
+    """Return the default platform-shared lib location."""
+    new = _sysconfig.get_platlib()
+    if _USE_SYSCONFIG:
+        return new
+
+    from . import _distutils
+
+    old = _distutils.get_platlib()
+    if _looks_like_deb_system_dist_packages(old):
+        return old
+    if _warn_if_mismatch(pathlib.Path(old), pathlib.Path(new), key="platlib"):
+        _log_context()
+    return old
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/_distutils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/_distutils.py
new file mode 100644
index 0000000000000000000000000000000000000000..92bd93179c5cd3cb377c8b9f1e9d22d13fd7d003
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/_distutils.py
@@ -0,0 +1,173 @@
+"""Locations where we look for configs, install stuff, etc"""
+
+# The following comment should be removed at some point in the future.
+# mypy: strict-optional=False
+
+# If pip's going to use distutils, it should not be using the copy that setuptools
+# might have injected into the environment. This is done by removing the injected
+# shim, if it's injected.
+#
+# See https://github.com/pypa/pip/issues/8761 for the original discussion and
+# rationale for why this is done within pip.
+try:
+    __import__("_distutils_hack").remove_shim()
+except (ImportError, AttributeError):
+    pass
+
+import logging
+import os
+import sys
+from distutils.cmd import Command as DistutilsCommand
+from distutils.command.install import SCHEME_KEYS
+from distutils.command.install import install as distutils_install_command
+from distutils.sysconfig import get_python_lib
+from typing import Dict, List, Optional, Union, cast
+
+from pip._internal.models.scheme import Scheme
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+from .base import get_major_minor_version
+
+logger = logging.getLogger(__name__)
+
+
+def distutils_scheme(
+    dist_name: str,
+    user: bool = False,
+    home: Optional[str] = None,
+    root: Optional[str] = None,
+    isolated: bool = False,
+    prefix: Optional[str] = None,
+    *,
+    ignore_config_files: bool = False,
+) -> Dict[str, str]:
+    """
+    Return a distutils install scheme
+    """
+    from distutils.dist import Distribution
+
+    dist_args: Dict[str, Union[str, List[str]]] = {"name": dist_name}
+    if isolated:
+        dist_args["script_args"] = ["--no-user-cfg"]
+
+    d = Distribution(dist_args)
+    if not ignore_config_files:
+        try:
+            d.parse_config_files()
+        except UnicodeDecodeError:
+            # Typeshed does not include find_config_files() for some reason.
+            paths = d.find_config_files()  # type: ignore
+            logger.warning(
+                "Ignore distutils configs in %s due to encoding errors.",
+                ", ".join(os.path.basename(p) for p in paths),
+            )
+    obj: Optional[DistutilsCommand] = None
+    obj = d.get_command_obj("install", create=True)
+    assert obj is not None
+    i = cast(distutils_install_command, obj)
+    # NOTE: setting user or home has the side-effect of creating the home dir
+    # or user base for installations during finalize_options()
+    # ideally, we'd prefer a scheme class that has no side-effects.
+    assert not (user and prefix), f"user={user} prefix={prefix}"
+    assert not (home and prefix), f"home={home} prefix={prefix}"
+    i.user = user or i.user
+    if user or home:
+        i.prefix = ""
+    i.prefix = prefix or i.prefix
+    i.home = home or i.home
+    i.root = root or i.root
+    i.finalize_options()
+
+    scheme = {}
+    for key in SCHEME_KEYS:
+        scheme[key] = getattr(i, "install_" + key)
+
+    # install_lib specified in setup.cfg should install *everything*
+    # into there (i.e. it takes precedence over both purelib and
+    # platlib).  Note, i.install_lib is *always* set after
+    # finalize_options(); we only want to override here if the user
+    # has explicitly requested it hence going back to the config
+    if "install_lib" in d.get_option_dict("install"):
+        scheme.update(dict(purelib=i.install_lib, platlib=i.install_lib))
+
+    if running_under_virtualenv():
+        if home:
+            prefix = home
+        elif user:
+            prefix = i.install_userbase
+        else:
+            prefix = i.prefix
+        scheme["headers"] = os.path.join(
+            prefix,
+            "include",
+            "site",
+            f"python{get_major_minor_version()}",
+            dist_name,
+        )
+
+        if root is not None:
+            path_no_drive = os.path.splitdrive(os.path.abspath(scheme["headers"]))[1]
+            scheme["headers"] = os.path.join(root, path_no_drive[1:])
+
+    return scheme
+
+
+def get_scheme(
+    dist_name: str,
+    user: bool = False,
+    home: Optional[str] = None,
+    root: Optional[str] = None,
+    isolated: bool = False,
+    prefix: Optional[str] = None,
+) -> Scheme:
+    """
+    Get the "scheme" corresponding to the input parameters. The distutils
+    documentation provides the context for the available schemes:
+    https://docs.python.org/3/install/index.html#alternate-installation
+
+    :param dist_name: the name of the package to retrieve the scheme for, used
+        in the headers scheme path
+    :param user: indicates to use the "user" scheme
+    :param home: indicates to use the "home" scheme and provides the base
+        directory for the same
+    :param root: root under which other directories are re-based
+    :param isolated: equivalent to --no-user-cfg, i.e. do not consider
+        ~/.pydistutils.cfg (posix) or ~/pydistutils.cfg (non-posix) for
+        scheme paths
+    :param prefix: indicates to use the "prefix" scheme and provides the
+        base directory for the same
+    """
+    scheme = distutils_scheme(dist_name, user, home, root, isolated, prefix)
+    return Scheme(
+        platlib=scheme["platlib"],
+        purelib=scheme["purelib"],
+        headers=scheme["headers"],
+        scripts=scheme["scripts"],
+        data=scheme["data"],
+    )
+
+
+def get_bin_prefix() -> str:
+    # XXX: In old virtualenv versions, sys.prefix can contain '..' components,
+    # so we need to call normpath to eliminate them.
+    prefix = os.path.normpath(sys.prefix)
+    if WINDOWS:
+        bin_py = os.path.join(prefix, "Scripts")
+        # buildout uses 'bin' on Windows too?
+        if not os.path.exists(bin_py):
+            bin_py = os.path.join(prefix, "bin")
+        return bin_py
+    # Forcing to use /usr/local/bin for standard macOS framework installs
+    # Also log to ~/Library/Logs/ for use with the Console.app log viewer
+    if sys.platform[:6] == "darwin" and prefix[:16] == "/System/Library/":
+        return "/usr/local/bin"
+    return os.path.join(prefix, "bin")
+
+
+def get_purelib() -> str:
+    return get_python_lib(plat_specific=False)
+
+
+def get_platlib() -> str:
+    return get_python_lib(plat_specific=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/_sysconfig.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/_sysconfig.py
new file mode 100644
index 0000000000000000000000000000000000000000..97aef1f1ac237e6ef97b1a1d026818d7b8ab9be9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/_sysconfig.py
@@ -0,0 +1,213 @@
+import logging
+import os
+import sys
+import sysconfig
+import typing
+
+from pip._internal.exceptions import InvalidSchemeCombination, UserInstallationInvalid
+from pip._internal.models.scheme import SCHEME_KEYS, Scheme
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+from .base import change_root, get_major_minor_version, is_osx_framework
+
+logger = logging.getLogger(__name__)
+
+
+# Notes on _infer_* functions.
+# Unfortunately ``get_default_scheme()`` didn't exist before 3.10, so there's no
+# way to ask things like "what is the '_prefix' scheme on this platform". These
+# functions try to answer that with some heuristics while accounting for ad-hoc
+# platforms not covered by CPython's default sysconfig implementation. If the
+# ad-hoc implementation does not fully implement sysconfig, we'll fall back to
+# a POSIX scheme.
+
+_AVAILABLE_SCHEMES = set(sysconfig.get_scheme_names())
+
+_PREFERRED_SCHEME_API = getattr(sysconfig, "get_preferred_scheme", None)
+
+
+def _should_use_osx_framework_prefix() -> bool:
+    """Check for Apple's ``osx_framework_library`` scheme.
+
+    Python distributed by Apple's Command Line Tools has this special scheme
+    that's used when:
+
+    * This is a framework build.
+    * We are installing into the system prefix.
+
+    This does not account for ``pip install --prefix`` (also means we're not
+    installing to the system prefix), which should use ``posix_prefix``, but
+    logic here means ``_infer_prefix()`` outputs ``osx_framework_library``. But
+    since ``prefix`` is not available for ``sysconfig.get_default_scheme()``,
+    which is the stdlib replacement for ``_infer_prefix()``, presumably Apple
+    wouldn't be able to magically switch between ``osx_framework_library`` and
+    ``posix_prefix``. ``_infer_prefix()`` returning ``osx_framework_library``
+    means its behavior is consistent whether we use the stdlib implementation
+    or our own, and we deal with this special case in ``get_scheme()`` instead.
+    """
+    return (
+        "osx_framework_library" in _AVAILABLE_SCHEMES
+        and not running_under_virtualenv()
+        and is_osx_framework()
+    )
+
+
+def _infer_prefix() -> str:
+    """Try to find a prefix scheme for the current platform.
+
+    This tries:
+
+    * A special ``osx_framework_library`` for Python distributed by Apple's
+      Command Line Tools, when not running in a virtual environment.
+    * Implementation + OS, used by PyPy on Windows (``pypy_nt``).
+    * Implementation without OS, used by PyPy on POSIX (``pypy``).
+    * OS + "prefix", used by CPython on POSIX (``posix_prefix``).
+    * Just the OS name, used by CPython on Windows (``nt``).
+
+    If none of the above works, fall back to ``posix_prefix``.
+    """
+    if _PREFERRED_SCHEME_API:
+        return _PREFERRED_SCHEME_API("prefix")
+    if _should_use_osx_framework_prefix():
+        return "osx_framework_library"
+    implementation_suffixed = f"{sys.implementation.name}_{os.name}"
+    if implementation_suffixed in _AVAILABLE_SCHEMES:
+        return implementation_suffixed
+    if sys.implementation.name in _AVAILABLE_SCHEMES:
+        return sys.implementation.name
+    suffixed = f"{os.name}_prefix"
+    if suffixed in _AVAILABLE_SCHEMES:
+        return suffixed
+    if os.name in _AVAILABLE_SCHEMES:  # On Windows, prefx is just called "nt".
+        return os.name
+    return "posix_prefix"
+
+
+def _infer_user() -> str:
+    """Try to find a user scheme for the current platform."""
+    if _PREFERRED_SCHEME_API:
+        return _PREFERRED_SCHEME_API("user")
+    if is_osx_framework() and not running_under_virtualenv():
+        suffixed = "osx_framework_user"
+    else:
+        suffixed = f"{os.name}_user"
+    if suffixed in _AVAILABLE_SCHEMES:
+        return suffixed
+    if "posix_user" not in _AVAILABLE_SCHEMES:  # User scheme unavailable.
+        raise UserInstallationInvalid()
+    return "posix_user"
+
+
+def _infer_home() -> str:
+    """Try to find a home for the current platform."""
+    if _PREFERRED_SCHEME_API:
+        return _PREFERRED_SCHEME_API("home")
+    suffixed = f"{os.name}_home"
+    if suffixed in _AVAILABLE_SCHEMES:
+        return suffixed
+    return "posix_home"
+
+
+# Update these keys if the user sets a custom home.
+_HOME_KEYS = [
+    "installed_base",
+    "base",
+    "installed_platbase",
+    "platbase",
+    "prefix",
+    "exec_prefix",
+]
+if sysconfig.get_config_var("userbase") is not None:
+    _HOME_KEYS.append("userbase")
+
+
+def get_scheme(
+    dist_name: str,
+    user: bool = False,
+    home: typing.Optional[str] = None,
+    root: typing.Optional[str] = None,
+    isolated: bool = False,
+    prefix: typing.Optional[str] = None,
+) -> Scheme:
+    """
+    Get the "scheme" corresponding to the input parameters.
+
+    :param dist_name: the name of the package to retrieve the scheme for, used
+        in the headers scheme path
+    :param user: indicates to use the "user" scheme
+    :param home: indicates to use the "home" scheme
+    :param root: root under which other directories are re-based
+    :param isolated: ignored, but kept for distutils compatibility (where
+        this controls whether the user-site pydistutils.cfg is honored)
+    :param prefix: indicates to use the "prefix" scheme and provides the
+        base directory for the same
+    """
+    if user and prefix:
+        raise InvalidSchemeCombination("--user", "--prefix")
+    if home and prefix:
+        raise InvalidSchemeCombination("--home", "--prefix")
+
+    if home is not None:
+        scheme_name = _infer_home()
+    elif user:
+        scheme_name = _infer_user()
+    else:
+        scheme_name = _infer_prefix()
+
+    # Special case: When installing into a custom prefix, use posix_prefix
+    # instead of osx_framework_library. See _should_use_osx_framework_prefix()
+    # docstring for details.
+    if prefix is not None and scheme_name == "osx_framework_library":
+        scheme_name = "posix_prefix"
+
+    if home is not None:
+        variables = {k: home for k in _HOME_KEYS}
+    elif prefix is not None:
+        variables = {k: prefix for k in _HOME_KEYS}
+    else:
+        variables = {}
+
+    paths = sysconfig.get_paths(scheme=scheme_name, vars=variables)
+
+    # Logic here is very arbitrary, we're doing it for compatibility, don't ask.
+    # 1. Pip historically uses a special header path in virtual environments.
+    # 2. If the distribution name is not known, distutils uses 'UNKNOWN'. We
+    #    only do the same when not running in a virtual environment because
+    #    pip's historical header path logic (see point 1) did not do this.
+    if running_under_virtualenv():
+        if user:
+            base = variables.get("userbase", sys.prefix)
+        else:
+            base = variables.get("base", sys.prefix)
+        python_xy = f"python{get_major_minor_version()}"
+        paths["include"] = os.path.join(base, "include", "site", python_xy)
+    elif not dist_name:
+        dist_name = "UNKNOWN"
+
+    scheme = Scheme(
+        platlib=paths["platlib"],
+        purelib=paths["purelib"],
+        headers=os.path.join(paths["include"], dist_name),
+        scripts=paths["scripts"],
+        data=paths["data"],
+    )
+    if root is not None:
+        for key in SCHEME_KEYS:
+            value = change_root(root, getattr(scheme, key))
+            setattr(scheme, key, value)
+    return scheme
+
+
+def get_bin_prefix() -> str:
+    # Forcing to use /usr/local/bin for standard macOS framework installs.
+    if sys.platform[:6] == "darwin" and sys.prefix[:16] == "/System/Library/":
+        return "/usr/local/bin"
+    return sysconfig.get_paths()["scripts"]
+
+
+def get_purelib() -> str:
+    return sysconfig.get_paths()["purelib"]
+
+
+def get_platlib() -> str:
+    return sysconfig.get_paths()["platlib"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/base.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..3f9f896e632e929a63e9724ab80ecdfc9761b795
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/locations/base.py
@@ -0,0 +1,81 @@
+import functools
+import os
+import site
+import sys
+import sysconfig
+import typing
+
+from pip._internal.exceptions import InstallationError
+from pip._internal.utils import appdirs
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+# Application Directories
+USER_CACHE_DIR = appdirs.user_cache_dir("pip")
+
+# FIXME doesn't account for venv linked to global site-packages
+site_packages: str = sysconfig.get_path("purelib")
+
+
+def get_major_minor_version() -> str:
+    """
+    Return the major-minor version of the current Python as a string, e.g.
+    "3.7" or "3.10".
+    """
+    return "{}.{}".format(*sys.version_info)
+
+
+def change_root(new_root: str, pathname: str) -> str:
+    """Return 'pathname' with 'new_root' prepended.
+
+    If 'pathname' is relative, this is equivalent to os.path.join(new_root, pathname).
+    Otherwise, it requires making 'pathname' relative and then joining the
+    two, which is tricky on DOS/Windows and Mac OS.
+
+    This is borrowed from Python's standard library's distutils module.
+    """
+    if os.name == "posix":
+        if not os.path.isabs(pathname):
+            return os.path.join(new_root, pathname)
+        else:
+            return os.path.join(new_root, pathname[1:])
+
+    elif os.name == "nt":
+        (drive, path) = os.path.splitdrive(pathname)
+        if path[0] == "\\":
+            path = path[1:]
+        return os.path.join(new_root, path)
+
+    else:
+        raise InstallationError(
+            f"Unknown platform: {os.name}\n"
+            "Can not change root path prefix on unknown platform."
+        )
+
+
+def get_src_prefix() -> str:
+    if running_under_virtualenv():
+        src_prefix = os.path.join(sys.prefix, "src")
+    else:
+        # FIXME: keep src in cwd for now (it is not a temporary folder)
+        try:
+            src_prefix = os.path.join(os.getcwd(), "src")
+        except OSError:
+            # In case the current working directory has been renamed or deleted
+            sys.exit("The folder you are executing pip from can no longer be found.")
+
+    # under macOS + virtualenv sys.prefix is not properly resolved
+    # it is something like /path/to/python/bin/..
+    return os.path.abspath(src_prefix)
+
+
+try:
+    # Use getusersitepackages if this is present, as it ensures that the
+    # value is initialised properly.
+    user_site: typing.Optional[str] = site.getusersitepackages()
+except AttributeError:
+    user_site = site.USER_SITE
+
+
+@functools.lru_cache(maxsize=None)
+def is_osx_framework() -> bool:
+    return bool(sysconfig.get_config_var("PYTHONFRAMEWORK"))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/main.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/main.py
new file mode 100644
index 0000000000000000000000000000000000000000..33c6d24cd85b55a9fb1b1e6ab784f471e2b135f0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/main.py
@@ -0,0 +1,12 @@
+from typing import List, Optional
+
+
+def main(args: Optional[List[str]] = None) -> int:
+    """This is preserved for old console scripts that may still be referencing
+    it.
+
+    For additional details, see https://github.com/pypa/pip/issues/7498.
+    """
+    from pip._internal.utils.entrypoints import _wrapper
+
+    return _wrapper(args)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f73ca7105ff0bf11d74dd16ffb0653059466f70
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/__init__.py
@@ -0,0 +1,127 @@
+import contextlib
+import functools
+import os
+import sys
+from typing import TYPE_CHECKING, List, Optional, Type, cast
+
+from pip._internal.utils.misc import strtobool
+
+from .base import BaseDistribution, BaseEnvironment, FilesystemWheel, MemoryWheel, Wheel
+
+if TYPE_CHECKING:
+    from typing import Protocol
+else:
+    Protocol = object
+
+__all__ = [
+    "BaseDistribution",
+    "BaseEnvironment",
+    "FilesystemWheel",
+    "MemoryWheel",
+    "Wheel",
+    "get_default_environment",
+    "get_environment",
+    "get_wheel_distribution",
+    "select_backend",
+]
+
+
+def _should_use_importlib_metadata() -> bool:
+    """Whether to use the ``importlib.metadata`` or ``pkg_resources`` backend.
+
+    By default, pip uses ``importlib.metadata`` on Python 3.11+, and
+    ``pkg_resourcess`` otherwise. This can be overridden by a couple of ways:
+
+    * If environment variable ``_PIP_USE_IMPORTLIB_METADATA`` is set, it
+      dictates whether ``importlib.metadata`` is used, regardless of Python
+      version.
+    * On Python 3.11+, Python distributors can patch ``importlib.metadata``
+      to add a global constant ``_PIP_USE_IMPORTLIB_METADATA = False``. This
+      makes pip use ``pkg_resources`` (unless the user set the aforementioned
+      environment variable to *True*).
+    """
+    with contextlib.suppress(KeyError, ValueError):
+        return bool(strtobool(os.environ["_PIP_USE_IMPORTLIB_METADATA"]))
+    if sys.version_info < (3, 11):
+        return False
+    import importlib.metadata
+
+    return bool(getattr(importlib.metadata, "_PIP_USE_IMPORTLIB_METADATA", True))
+
+
+class Backend(Protocol):
+    Distribution: Type[BaseDistribution]
+    Environment: Type[BaseEnvironment]
+
+
+@functools.lru_cache(maxsize=None)
+def select_backend() -> Backend:
+    if _should_use_importlib_metadata():
+        from . import importlib
+
+        return cast(Backend, importlib)
+    from . import pkg_resources
+
+    return cast(Backend, pkg_resources)
+
+
+def get_default_environment() -> BaseEnvironment:
+    """Get the default representation for the current environment.
+
+    This returns an Environment instance from the chosen backend. The default
+    Environment instance should be built from ``sys.path`` and may use caching
+    to share instance state accorss calls.
+    """
+    return select_backend().Environment.default()
+
+
+def get_environment(paths: Optional[List[str]]) -> BaseEnvironment:
+    """Get a representation of the environment specified by ``paths``.
+
+    This returns an Environment instance from the chosen backend based on the
+    given import paths. The backend must build a fresh instance representing
+    the state of installed distributions when this function is called.
+    """
+    return select_backend().Environment.from_paths(paths)
+
+
+def get_directory_distribution(directory: str) -> BaseDistribution:
+    """Get the distribution metadata representation in the specified directory.
+
+    This returns a Distribution instance from the chosen backend based on
+    the given on-disk ``.dist-info`` directory.
+    """
+    return select_backend().Distribution.from_directory(directory)
+
+
+def get_wheel_distribution(wheel: Wheel, canonical_name: str) -> BaseDistribution:
+    """Get the representation of the specified wheel's distribution metadata.
+
+    This returns a Distribution instance from the chosen backend based on
+    the given wheel's ``.dist-info`` directory.
+
+    :param canonical_name: Normalized project name of the given wheel.
+    """
+    return select_backend().Distribution.from_wheel(wheel, canonical_name)
+
+
+def get_metadata_distribution(
+    metadata_contents: bytes,
+    filename: str,
+    canonical_name: str,
+) -> BaseDistribution:
+    """Get the dist representation of the specified METADATA file contents.
+
+    This returns a Distribution instance from the chosen backend sourced from the data
+    in `metadata_contents`.
+
+    :param metadata_contents: Contents of a METADATA file within a dist, or one served
+                              via PEP 658.
+    :param filename: Filename for the dist this metadata represents.
+    :param canonical_name: Normalized project name of the given dist.
+    """
+    return select_backend().Distribution.from_metadata_file_contents(
+        metadata_contents,
+        filename,
+        canonical_name,
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/_json.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/_json.py
new file mode 100644
index 0000000000000000000000000000000000000000..336b52f1efddbcaeb6716583fc2f043699e278fa
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/_json.py
@@ -0,0 +1,84 @@
+# Extracted from https://github.com/pfmoore/pkg_metadata
+
+from email.header import Header, decode_header, make_header
+from email.message import Message
+from typing import Any, Dict, List, Union
+
+METADATA_FIELDS = [
+    # Name, Multiple-Use
+    ("Metadata-Version", False),
+    ("Name", False),
+    ("Version", False),
+    ("Dynamic", True),
+    ("Platform", True),
+    ("Supported-Platform", True),
+    ("Summary", False),
+    ("Description", False),
+    ("Description-Content-Type", False),
+    ("Keywords", False),
+    ("Home-page", False),
+    ("Download-URL", False),
+    ("Author", False),
+    ("Author-email", False),
+    ("Maintainer", False),
+    ("Maintainer-email", False),
+    ("License", False),
+    ("Classifier", True),
+    ("Requires-Dist", True),
+    ("Requires-Python", False),
+    ("Requires-External", True),
+    ("Project-URL", True),
+    ("Provides-Extra", True),
+    ("Provides-Dist", True),
+    ("Obsoletes-Dist", True),
+]
+
+
+def json_name(field: str) -> str:
+    return field.lower().replace("-", "_")
+
+
+def msg_to_json(msg: Message) -> Dict[str, Any]:
+    """Convert a Message object into a JSON-compatible dictionary."""
+
+    def sanitise_header(h: Union[Header, str]) -> str:
+        if isinstance(h, Header):
+            chunks = []
+            for bytes, encoding in decode_header(h):
+                if encoding == "unknown-8bit":
+                    try:
+                        # See if UTF-8 works
+                        bytes.decode("utf-8")
+                        encoding = "utf-8"
+                    except UnicodeDecodeError:
+                        # If not, latin1 at least won't fail
+                        encoding = "latin1"
+                chunks.append((bytes, encoding))
+            return str(make_header(chunks))
+        return str(h)
+
+    result = {}
+    for field, multi in METADATA_FIELDS:
+        if field not in msg:
+            continue
+        key = json_name(field)
+        if multi:
+            value: Union[str, List[str]] = [
+                sanitise_header(v) for v in msg.get_all(field)
+            ]
+        else:
+            value = sanitise_header(msg.get(field))
+            if key == "keywords":
+                # Accept both comma-separated and space-separated
+                # forms, for better compatibility with old data.
+                if "," in value:
+                    value = [v.strip() for v in value.split(",")]
+                else:
+                    value = value.split()
+        result[key] = value
+
+    payload = msg.get_payload()
+    if payload:
+        result["description"] = payload
+
+    return result
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/base.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..cafb79fb3dcf43744393e2964056fe32c350bbc1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/base.py
@@ -0,0 +1,688 @@
+import csv
+import email.message
+import functools
+import json
+import logging
+import pathlib
+import re
+import zipfile
+from typing import (
+    IO,
+    TYPE_CHECKING,
+    Any,
+    Collection,
+    Container,
+    Dict,
+    Iterable,
+    Iterator,
+    List,
+    NamedTuple,
+    Optional,
+    Tuple,
+    Union,
+)
+
+from pip._vendor.packaging.requirements import Requirement
+from pip._vendor.packaging.specifiers import InvalidSpecifier, SpecifierSet
+from pip._vendor.packaging.utils import NormalizedName
+from pip._vendor.packaging.version import LegacyVersion, Version
+
+from pip._internal.exceptions import NoneMetadataError
+from pip._internal.locations import site_packages, user_site
+from pip._internal.models.direct_url import (
+    DIRECT_URL_METADATA_NAME,
+    DirectUrl,
+    DirectUrlValidationError,
+)
+from pip._internal.utils.compat import stdlib_pkgs  # TODO: Move definition here.
+from pip._internal.utils.egg_link import egg_link_path_from_sys_path
+from pip._internal.utils.misc import is_local, normalize_path
+from pip._internal.utils.packaging import safe_extra
+from pip._internal.utils.urls import url_to_path
+
+from ._json import msg_to_json
+
+if TYPE_CHECKING:
+    from typing import Protocol
+else:
+    Protocol = object
+
+DistributionVersion = Union[LegacyVersion, Version]
+
+InfoPath = Union[str, pathlib.PurePath]
+
+logger = logging.getLogger(__name__)
+
+
+class BaseEntryPoint(Protocol):
+    @property
+    def name(self) -> str:
+        raise NotImplementedError()
+
+    @property
+    def value(self) -> str:
+        raise NotImplementedError()
+
+    @property
+    def group(self) -> str:
+        raise NotImplementedError()
+
+
+def _convert_installed_files_path(
+    entry: Tuple[str, ...],
+    info: Tuple[str, ...],
+) -> str:
+    """Convert a legacy installed-files.txt path into modern RECORD path.
+
+    The legacy format stores paths relative to the info directory, while the
+    modern format stores paths relative to the package root, e.g. the
+    site-packages directory.
+
+    :param entry: Path parts of the installed-files.txt entry.
+    :param info: Path parts of the egg-info directory relative to package root.
+    :returns: The converted entry.
+
+    For best compatibility with symlinks, this does not use ``abspath()`` or
+    ``Path.resolve()``, but tries to work with path parts:
+
+    1. While ``entry`` starts with ``..``, remove the equal amounts of parts
+       from ``info``; if ``info`` is empty, start appending ``..`` instead.
+    2. Join the two directly.
+    """
+    while entry and entry[0] == "..":
+        if not info or info[-1] == "..":
+            info += ("..",)
+        else:
+            info = info[:-1]
+        entry = entry[1:]
+    return str(pathlib.Path(*info, *entry))
+
+
+class RequiresEntry(NamedTuple):
+    requirement: str
+    extra: str
+    marker: str
+
+
+class BaseDistribution(Protocol):
+    @classmethod
+    def from_directory(cls, directory: str) -> "BaseDistribution":
+        """Load the distribution from a metadata directory.
+
+        :param directory: Path to a metadata directory, e.g. ``.dist-info``.
+        """
+        raise NotImplementedError()
+
+    @classmethod
+    def from_metadata_file_contents(
+        cls,
+        metadata_contents: bytes,
+        filename: str,
+        project_name: str,
+    ) -> "BaseDistribution":
+        """Load the distribution from the contents of a METADATA file.
+
+        This is used to implement PEP 658 by generating a "shallow" dist object that can
+        be used for resolution without downloading or building the actual dist yet.
+
+        :param metadata_contents: The contents of a METADATA file.
+        :param filename: File name for the dist with this metadata.
+        :param project_name: Name of the project this dist represents.
+        """
+        raise NotImplementedError()
+
+    @classmethod
+    def from_wheel(cls, wheel: "Wheel", name: str) -> "BaseDistribution":
+        """Load the distribution from a given wheel.
+
+        :param wheel: A concrete wheel definition.
+        :param name: File name of the wheel.
+
+        :raises InvalidWheel: Whenever loading of the wheel causes a
+            :py:exc:`zipfile.BadZipFile` exception to be thrown.
+        :raises UnsupportedWheel: If the wheel is a valid zip, but malformed
+            internally.
+        """
+        raise NotImplementedError()
+
+    def __repr__(self) -> str:
+        return f"{self.raw_name} {self.version} ({self.location})"
+
+    def __str__(self) -> str:
+        return f"{self.raw_name} {self.version}"
+
+    @property
+    def location(self) -> Optional[str]:
+        """Where the distribution is loaded from.
+
+        A string value is not necessarily a filesystem path, since distributions
+        can be loaded from other sources, e.g. arbitrary zip archives. ``None``
+        means the distribution is created in-memory.
+
+        Do not canonicalize this value with e.g. ``pathlib.Path.resolve()``. If
+        this is a symbolic link, we want to preserve the relative path between
+        it and files in the distribution.
+        """
+        raise NotImplementedError()
+
+    @property
+    def editable_project_location(self) -> Optional[str]:
+        """The project location for editable distributions.
+
+        This is the directory where pyproject.toml or setup.py is located.
+        None if the distribution is not installed in editable mode.
+        """
+        # TODO: this property is relatively costly to compute, memoize it ?
+        direct_url = self.direct_url
+        if direct_url:
+            if direct_url.is_local_editable():
+                return url_to_path(direct_url.url)
+        else:
+            # Search for an .egg-link file by walking sys.path, as it was
+            # done before by dist_is_editable().
+            egg_link_path = egg_link_path_from_sys_path(self.raw_name)
+            if egg_link_path:
+                # TODO: get project location from second line of egg_link file
+                #       (https://github.com/pypa/pip/issues/10243)
+                return self.location
+        return None
+
+    @property
+    def installed_location(self) -> Optional[str]:
+        """The distribution's "installed" location.
+
+        This should generally be a ``site-packages`` directory. This is
+        usually ``dist.location``, except for legacy develop-installed packages,
+        where ``dist.location`` is the source code location, and this is where
+        the ``.egg-link`` file is.
+
+        The returned location is normalized (in particular, with symlinks removed).
+        """
+        raise NotImplementedError()
+
+    @property
+    def info_location(self) -> Optional[str]:
+        """Location of the .[egg|dist]-info directory or file.
+
+        Similarly to ``location``, a string value is not necessarily a
+        filesystem path. ``None`` means the distribution is created in-memory.
+
+        For a modern .dist-info installation on disk, this should be something
+        like ``{location}/{raw_name}-{version}.dist-info``.
+
+        Do not canonicalize this value with e.g. ``pathlib.Path.resolve()``. If
+        this is a symbolic link, we want to preserve the relative path between
+        it and other files in the distribution.
+        """
+        raise NotImplementedError()
+
+    @property
+    def installed_by_distutils(self) -> bool:
+        """Whether this distribution is installed with legacy distutils format.
+
+        A distribution installed with "raw" distutils not patched by setuptools
+        uses one single file at ``info_location`` to store metadata. We need to
+        treat this specially on uninstallation.
+        """
+        info_location = self.info_location
+        if not info_location:
+            return False
+        return pathlib.Path(info_location).is_file()
+
+    @property
+    def installed_as_egg(self) -> bool:
+        """Whether this distribution is installed as an egg.
+
+        This usually indicates the distribution was installed by (older versions
+        of) easy_install.
+        """
+        location = self.location
+        if not location:
+            return False
+        return location.endswith(".egg")
+
+    @property
+    def installed_with_setuptools_egg_info(self) -> bool:
+        """Whether this distribution is installed with the ``.egg-info`` format.
+
+        This usually indicates the distribution was installed with setuptools
+        with an old pip version or with ``single-version-externally-managed``.
+
+        Note that this ensure the metadata store is a directory. distutils can
+        also installs an ``.egg-info``, but as a file, not a directory. This
+        property is *False* for that case. Also see ``installed_by_distutils``.
+        """
+        info_location = self.info_location
+        if not info_location:
+            return False
+        if not info_location.endswith(".egg-info"):
+            return False
+        return pathlib.Path(info_location).is_dir()
+
+    @property
+    def installed_with_dist_info(self) -> bool:
+        """Whether this distribution is installed with the "modern format".
+
+        This indicates a "modern" installation, e.g. storing metadata in the
+        ``.dist-info`` directory. This applies to installations made by
+        setuptools (but through pip, not directly), or anything using the
+        standardized build backend interface (PEP 517).
+        """
+        info_location = self.info_location
+        if not info_location:
+            return False
+        if not info_location.endswith(".dist-info"):
+            return False
+        return pathlib.Path(info_location).is_dir()
+
+    @property
+    def canonical_name(self) -> NormalizedName:
+        raise NotImplementedError()
+
+    @property
+    def version(self) -> DistributionVersion:
+        raise NotImplementedError()
+
+    @property
+    def setuptools_filename(self) -> str:
+        """Convert a project name to its setuptools-compatible filename.
+
+        This is a copy of ``pkg_resources.to_filename()`` for compatibility.
+        """
+        return self.raw_name.replace("-", "_")
+
+    @property
+    def direct_url(self) -> Optional[DirectUrl]:
+        """Obtain a DirectUrl from this distribution.
+
+        Returns None if the distribution has no `direct_url.json` metadata,
+        or if `direct_url.json` is invalid.
+        """
+        try:
+            content = self.read_text(DIRECT_URL_METADATA_NAME)
+        except FileNotFoundError:
+            return None
+        try:
+            return DirectUrl.from_json(content)
+        except (
+            UnicodeDecodeError,
+            json.JSONDecodeError,
+            DirectUrlValidationError,
+        ) as e:
+            logger.warning(
+                "Error parsing %s for %s: %s",
+                DIRECT_URL_METADATA_NAME,
+                self.canonical_name,
+                e,
+            )
+            return None
+
+    @property
+    def installer(self) -> str:
+        try:
+            installer_text = self.read_text("INSTALLER")
+        except (OSError, ValueError, NoneMetadataError):
+            return ""  # Fail silently if the installer file cannot be read.
+        for line in installer_text.splitlines():
+            cleaned_line = line.strip()
+            if cleaned_line:
+                return cleaned_line
+        return ""
+
+    @property
+    def requested(self) -> bool:
+        return self.is_file("REQUESTED")
+
+    @property
+    def editable(self) -> bool:
+        return bool(self.editable_project_location)
+
+    @property
+    def local(self) -> bool:
+        """If distribution is installed in the current virtual environment.
+
+        Always True if we're not in a virtualenv.
+        """
+        if self.installed_location is None:
+            return False
+        return is_local(self.installed_location)
+
+    @property
+    def in_usersite(self) -> bool:
+        if self.installed_location is None or user_site is None:
+            return False
+        return self.installed_location.startswith(normalize_path(user_site))
+
+    @property
+    def in_site_packages(self) -> bool:
+        if self.installed_location is None or site_packages is None:
+            return False
+        return self.installed_location.startswith(normalize_path(site_packages))
+
+    def is_file(self, path: InfoPath) -> bool:
+        """Check whether an entry in the info directory is a file."""
+        raise NotImplementedError()
+
+    def iter_distutils_script_names(self) -> Iterator[str]:
+        """Find distutils 'scripts' entries metadata.
+
+        If 'scripts' is supplied in ``setup.py``, distutils records those in the
+        installed distribution's ``scripts`` directory, a file for each script.
+        """
+        raise NotImplementedError()
+
+    def read_text(self, path: InfoPath) -> str:
+        """Read a file in the info directory.
+
+        :raise FileNotFoundError: If ``path`` does not exist in the directory.
+        :raise NoneMetadataError: If ``path`` exists in the info directory, but
+            cannot be read.
+        """
+        raise NotImplementedError()
+
+    def iter_entry_points(self) -> Iterable[BaseEntryPoint]:
+        raise NotImplementedError()
+
+    def _metadata_impl(self) -> email.message.Message:
+        raise NotImplementedError()
+
+    @functools.lru_cache(maxsize=1)
+    def _metadata_cached(self) -> email.message.Message:
+        # When we drop python 3.7 support, move this to the metadata property and use
+        # functools.cached_property instead of lru_cache.
+        metadata = self._metadata_impl()
+        self._add_egg_info_requires(metadata)
+        return metadata
+
+    @property
+    def metadata(self) -> email.message.Message:
+        """Metadata of distribution parsed from e.g. METADATA or PKG-INFO.
+
+        This should return an empty message if the metadata file is unavailable.
+
+        :raises NoneMetadataError: If the metadata file is available, but does
+            not contain valid metadata.
+        """
+        return self._metadata_cached()
+
+    @property
+    def metadata_dict(self) -> Dict[str, Any]:
+        """PEP 566 compliant JSON-serializable representation of METADATA or PKG-INFO.
+
+        This should return an empty dict if the metadata file is unavailable.
+
+        :raises NoneMetadataError: If the metadata file is available, but does
+            not contain valid metadata.
+        """
+        return msg_to_json(self.metadata)
+
+    @property
+    def metadata_version(self) -> Optional[str]:
+        """Value of "Metadata-Version:" in distribution metadata, if available."""
+        return self.metadata.get("Metadata-Version")
+
+    @property
+    def raw_name(self) -> str:
+        """Value of "Name:" in distribution metadata."""
+        # The metadata should NEVER be missing the Name: key, but if it somehow
+        # does, fall back to the known canonical name.
+        return self.metadata.get("Name", self.canonical_name)
+
+    @property
+    def requires_python(self) -> SpecifierSet:
+        """Value of "Requires-Python:" in distribution metadata.
+
+        If the key does not exist or contains an invalid value, an empty
+        SpecifierSet should be returned.
+        """
+        value = self.metadata.get("Requires-Python")
+        if value is None:
+            return SpecifierSet()
+        try:
+            # Convert to str to satisfy the type checker; this can be a Header object.
+            spec = SpecifierSet(str(value))
+        except InvalidSpecifier as e:
+            message = "Package %r has an invalid Requires-Python: %s"
+            logger.warning(message, self.raw_name, e)
+            return SpecifierSet()
+        return spec
+
+    def iter_dependencies(self, extras: Collection[str] = ()) -> Iterable[Requirement]:
+        """Dependencies of this distribution.
+
+        For modern .dist-info distributions, this is the collection of
+        "Requires-Dist:" entries in distribution metadata.
+        """
+        raise NotImplementedError()
+
+    def iter_provided_extras(self) -> Iterable[str]:
+        """Extras provided by this distribution.
+
+        For modern .dist-info distributions, this is the collection of
+        "Provides-Extra:" entries in distribution metadata.
+        """
+        raise NotImplementedError()
+
+    def _iter_declared_entries_from_record(self) -> Optional[Iterator[str]]:
+        try:
+            text = self.read_text("RECORD")
+        except FileNotFoundError:
+            return None
+        # This extra Path-str cast normalizes entries.
+        return (str(pathlib.Path(row[0])) for row in csv.reader(text.splitlines()))
+
+    def _iter_declared_entries_from_legacy(self) -> Optional[Iterator[str]]:
+        try:
+            text = self.read_text("installed-files.txt")
+        except FileNotFoundError:
+            return None
+        paths = (p for p in text.splitlines(keepends=False) if p)
+        root = self.location
+        info = self.info_location
+        if root is None or info is None:
+            return paths
+        try:
+            info_rel = pathlib.Path(info).relative_to(root)
+        except ValueError:  # info is not relative to root.
+            return paths
+        if not info_rel.parts:  # info *is* root.
+            return paths
+        return (
+            _convert_installed_files_path(pathlib.Path(p).parts, info_rel.parts)
+            for p in paths
+        )
+
+    def iter_declared_entries(self) -> Optional[Iterator[str]]:
+        """Iterate through file entries declared in this distribution.
+
+        For modern .dist-info distributions, this is the files listed in the
+        ``RECORD`` metadata file. For legacy setuptools distributions, this
+        comes from ``installed-files.txt``, with entries normalized to be
+        compatible with the format used by ``RECORD``.
+
+        :return: An iterator for listed entries, or None if the distribution
+            contains neither ``RECORD`` nor ``installed-files.txt``.
+        """
+        return (
+            self._iter_declared_entries_from_record()
+            or self._iter_declared_entries_from_legacy()
+        )
+
+    def _iter_requires_txt_entries(self) -> Iterator[RequiresEntry]:
+        """Parse a ``requires.txt`` in an egg-info directory.
+
+        This is an INI-ish format where an egg-info stores dependencies. A
+        section name describes extra other environment markers, while each entry
+        is an arbitrary string (not a key-value pair) representing a dependency
+        as a requirement string (no markers).
+
+        There is a construct in ``importlib.metadata`` called ``Sectioned`` that
+        does mostly the same, but the format is currently considered private.
+        """
+        try:
+            content = self.read_text("requires.txt")
+        except FileNotFoundError:
+            return
+        extra = marker = ""  # Section-less entries don't have markers.
+        for line in content.splitlines():
+            line = line.strip()
+            if not line or line.startswith("#"):  # Comment; ignored.
+                continue
+            if line.startswith("[") and line.endswith("]"):  # A section header.
+                extra, _, marker = line.strip("[]").partition(":")
+                continue
+            yield RequiresEntry(requirement=line, extra=extra, marker=marker)
+
+    def _iter_egg_info_extras(self) -> Iterable[str]:
+        """Get extras from the egg-info directory."""
+        known_extras = {""}
+        for entry in self._iter_requires_txt_entries():
+            if entry.extra in known_extras:
+                continue
+            known_extras.add(entry.extra)
+            yield entry.extra
+
+    def _iter_egg_info_dependencies(self) -> Iterable[str]:
+        """Get distribution dependencies from the egg-info directory.
+
+        To ease parsing, this converts a legacy dependency entry into a PEP 508
+        requirement string. Like ``_iter_requires_txt_entries()``, there is code
+        in ``importlib.metadata`` that does mostly the same, but not do exactly
+        what we need.
+
+        Namely, ``importlib.metadata`` does not normalize the extra name before
+        putting it into the requirement string, which causes marker comparison
+        to fail because the dist-info format do normalize. This is consistent in
+        all currently available PEP 517 backends, although not standardized.
+        """
+        for entry in self._iter_requires_txt_entries():
+            if entry.extra and entry.marker:
+                marker = f'({entry.marker}) and extra == "{safe_extra(entry.extra)}"'
+            elif entry.extra:
+                marker = f'extra == "{safe_extra(entry.extra)}"'
+            elif entry.marker:
+                marker = entry.marker
+            else:
+                marker = ""
+            if marker:
+                yield f"{entry.requirement} ; {marker}"
+            else:
+                yield entry.requirement
+
+    def _add_egg_info_requires(self, metadata: email.message.Message) -> None:
+        """Add egg-info requires.txt information to the metadata."""
+        if not metadata.get_all("Requires-Dist"):
+            for dep in self._iter_egg_info_dependencies():
+                metadata["Requires-Dist"] = dep
+        if not metadata.get_all("Provides-Extra"):
+            for extra in self._iter_egg_info_extras():
+                metadata["Provides-Extra"] = extra
+
+
+class BaseEnvironment:
+    """An environment containing distributions to introspect."""
+
+    @classmethod
+    def default(cls) -> "BaseEnvironment":
+        raise NotImplementedError()
+
+    @classmethod
+    def from_paths(cls, paths: Optional[List[str]]) -> "BaseEnvironment":
+        raise NotImplementedError()
+
+    def get_distribution(self, name: str) -> Optional["BaseDistribution"]:
+        """Given a requirement name, return the installed distributions.
+
+        The name may not be normalized. The implementation must canonicalize
+        it for lookup.
+        """
+        raise NotImplementedError()
+
+    def _iter_distributions(self) -> Iterator["BaseDistribution"]:
+        """Iterate through installed distributions.
+
+        This function should be implemented by subclass, but never called
+        directly. Use the public ``iter_distribution()`` instead, which
+        implements additional logic to make sure the distributions are valid.
+        """
+        raise NotImplementedError()
+
+    def iter_all_distributions(self) -> Iterator[BaseDistribution]:
+        """Iterate through all installed distributions without any filtering."""
+        for dist in self._iter_distributions():
+            # Make sure the distribution actually comes from a valid Python
+            # packaging distribution. Pip's AdjacentTempDirectory leaves folders
+            # e.g. ``~atplotlib.dist-info`` if cleanup was interrupted. The
+            # valid project name pattern is taken from PEP 508.
+            project_name_valid = re.match(
+                r"^([A-Z0-9]|[A-Z0-9][A-Z0-9._-]*[A-Z0-9])$",
+                dist.canonical_name,
+                flags=re.IGNORECASE,
+            )
+            if not project_name_valid:
+                logger.warning(
+                    "Ignoring invalid distribution %s (%s)",
+                    dist.canonical_name,
+                    dist.location,
+                )
+                continue
+            yield dist
+
+    def iter_installed_distributions(
+        self,
+        local_only: bool = True,
+        skip: Container[str] = stdlib_pkgs,
+        include_editables: bool = True,
+        editables_only: bool = False,
+        user_only: bool = False,
+    ) -> Iterator[BaseDistribution]:
+        """Return a list of installed distributions.
+
+        This is based on ``iter_all_distributions()`` with additional filtering
+        options. Note that ``iter_installed_distributions()`` without arguments
+        is *not* equal to ``iter_all_distributions()``, since some of the
+        configurations exclude packages by default.
+
+        :param local_only: If True (default), only return installations
+        local to the current virtualenv, if in a virtualenv.
+        :param skip: An iterable of canonicalized project names to ignore;
+            defaults to ``stdlib_pkgs``.
+        :param include_editables: If False, don't report editables.
+        :param editables_only: If True, only report editables.
+        :param user_only: If True, only report installations in the user
+        site directory.
+        """
+        it = self.iter_all_distributions()
+        if local_only:
+            it = (d for d in it if d.local)
+        if not include_editables:
+            it = (d for d in it if not d.editable)
+        if editables_only:
+            it = (d for d in it if d.editable)
+        if user_only:
+            it = (d for d in it if d.in_usersite)
+        return (d for d in it if d.canonical_name not in skip)
+
+
+class Wheel(Protocol):
+    location: str
+
+    def as_zipfile(self) -> zipfile.ZipFile:
+        raise NotImplementedError()
+
+
+class FilesystemWheel(Wheel):
+    def __init__(self, location: str) -> None:
+        self.location = location
+
+    def as_zipfile(self) -> zipfile.ZipFile:
+        return zipfile.ZipFile(self.location, allowZip64=True)
+
+
+class MemoryWheel(Wheel):
+    def __init__(self, location: str, stream: IO[bytes]) -> None:
+        self.location = location
+        self.stream = stream
+
+    def as_zipfile(self) -> zipfile.ZipFile:
+        return zipfile.ZipFile(self.stream, allowZip64=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e7af9fe521bd529dd2c1878b0a6e9ea7c57752d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/__init__.py
@@ -0,0 +1,4 @@
+from ._dists import Distribution
+from ._envs import Environment
+
+__all__ = ["Distribution", "Environment"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..593bff23edecd3c517c96e119ee777bd4ee1d9d0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_compat.py
@@ -0,0 +1,55 @@
+import importlib.metadata
+from typing import Any, Optional, Protocol, cast
+
+
+class BadMetadata(ValueError):
+    def __init__(self, dist: importlib.metadata.Distribution, *, reason: str) -> None:
+        self.dist = dist
+        self.reason = reason
+
+    def __str__(self) -> str:
+        return f"Bad metadata in {self.dist} ({self.reason})"
+
+
+class BasePath(Protocol):
+    """A protocol that various path objects conform.
+
+    This exists because importlib.metadata uses both ``pathlib.Path`` and
+    ``zipfile.Path``, and we need a common base for type hints (Union does not
+    work well since ``zipfile.Path`` is too new for our linter setup).
+
+    This does not mean to be exhaustive, but only contains things that present
+    in both classes *that we need*.
+    """
+
+    @property
+    def name(self) -> str:
+        raise NotImplementedError()
+
+    @property
+    def parent(self) -> "BasePath":
+        raise NotImplementedError()
+
+
+def get_info_location(d: importlib.metadata.Distribution) -> Optional[BasePath]:
+    """Find the path to the distribution's metadata directory.
+
+    HACK: This relies on importlib.metadata's private ``_path`` attribute. Not
+    all distributions exist on disk, so importlib.metadata is correct to not
+    expose the attribute as public. But pip's code base is old and not as clean,
+    so we do this to avoid having to rewrite too many things. Hopefully we can
+    eliminate this some day.
+    """
+    return getattr(d, "_path", None)
+
+
+def get_dist_name(dist: importlib.metadata.Distribution) -> str:
+    """Get the distribution's project name.
+
+    The ``name`` attribute is only available in Python 3.10 or later. We are
+    targeting exactly that, but Mypy does not know this.
+    """
+    name = cast(Any, dist).name
+    if not isinstance(name, str):
+        raise BadMetadata(dist, reason="invalid metadata entry 'name'")
+    return name
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_dists.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_dists.py
new file mode 100644
index 0000000000000000000000000000000000000000..65c043c87eff27e9405316fdbc0c695f2b347441
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_dists.py
@@ -0,0 +1,224 @@
+import email.message
+import importlib.metadata
+import os
+import pathlib
+import zipfile
+from typing import (
+    Collection,
+    Dict,
+    Iterable,
+    Iterator,
+    Mapping,
+    Optional,
+    Sequence,
+    cast,
+)
+
+from pip._vendor.packaging.requirements import Requirement
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+from pip._vendor.packaging.version import parse as parse_version
+
+from pip._internal.exceptions import InvalidWheel, UnsupportedWheel
+from pip._internal.metadata.base import (
+    BaseDistribution,
+    BaseEntryPoint,
+    DistributionVersion,
+    InfoPath,
+    Wheel,
+)
+from pip._internal.utils.misc import normalize_path
+from pip._internal.utils.packaging import safe_extra
+from pip._internal.utils.temp_dir import TempDirectory
+from pip._internal.utils.wheel import parse_wheel, read_wheel_metadata_file
+
+from ._compat import BasePath, get_dist_name
+
+
+class WheelDistribution(importlib.metadata.Distribution):
+    """An ``importlib.metadata.Distribution`` read from a wheel.
+
+    Although ``importlib.metadata.PathDistribution`` accepts ``zipfile.Path``,
+    its implementation is too "lazy" for pip's needs (we can't keep the ZipFile
+    handle open for the entire lifetime of the distribution object).
+
+    This implementation eagerly reads the entire metadata directory into the
+    memory instead, and operates from that.
+    """
+
+    def __init__(
+        self,
+        files: Mapping[pathlib.PurePosixPath, bytes],
+        info_location: pathlib.PurePosixPath,
+    ) -> None:
+        self._files = files
+        self.info_location = info_location
+
+    @classmethod
+    def from_zipfile(
+        cls,
+        zf: zipfile.ZipFile,
+        name: str,
+        location: str,
+    ) -> "WheelDistribution":
+        info_dir, _ = parse_wheel(zf, name)
+        paths = (
+            (name, pathlib.PurePosixPath(name.split("/", 1)[-1]))
+            for name in zf.namelist()
+            if name.startswith(f"{info_dir}/")
+        )
+        files = {
+            relpath: read_wheel_metadata_file(zf, fullpath)
+            for fullpath, relpath in paths
+        }
+        info_location = pathlib.PurePosixPath(location, info_dir)
+        return cls(files, info_location)
+
+    def iterdir(self, path: InfoPath) -> Iterator[pathlib.PurePosixPath]:
+        # Only allow iterating through the metadata directory.
+        if pathlib.PurePosixPath(str(path)) in self._files:
+            return iter(self._files)
+        raise FileNotFoundError(path)
+
+    def read_text(self, filename: str) -> Optional[str]:
+        try:
+            data = self._files[pathlib.PurePosixPath(filename)]
+        except KeyError:
+            return None
+        try:
+            text = data.decode("utf-8")
+        except UnicodeDecodeError as e:
+            wheel = self.info_location.parent
+            error = f"Error decoding metadata for {wheel}: {e} in {filename} file"
+            raise UnsupportedWheel(error)
+        return text
+
+
+class Distribution(BaseDistribution):
+    def __init__(
+        self,
+        dist: importlib.metadata.Distribution,
+        info_location: Optional[BasePath],
+        installed_location: Optional[BasePath],
+    ) -> None:
+        self._dist = dist
+        self._info_location = info_location
+        self._installed_location = installed_location
+
+    @classmethod
+    def from_directory(cls, directory: str) -> BaseDistribution:
+        info_location = pathlib.Path(directory)
+        dist = importlib.metadata.Distribution.at(info_location)
+        return cls(dist, info_location, info_location.parent)
+
+    @classmethod
+    def from_metadata_file_contents(
+        cls,
+        metadata_contents: bytes,
+        filename: str,
+        project_name: str,
+    ) -> BaseDistribution:
+        # Generate temp dir to contain the metadata file, and write the file contents.
+        temp_dir = pathlib.Path(
+            TempDirectory(kind="metadata", globally_managed=True).path
+        )
+        metadata_path = temp_dir / "METADATA"
+        metadata_path.write_bytes(metadata_contents)
+        # Construct dist pointing to the newly created directory.
+        dist = importlib.metadata.Distribution.at(metadata_path.parent)
+        return cls(dist, metadata_path.parent, None)
+
+    @classmethod
+    def from_wheel(cls, wheel: Wheel, name: str) -> BaseDistribution:
+        try:
+            with wheel.as_zipfile() as zf:
+                dist = WheelDistribution.from_zipfile(zf, name, wheel.location)
+        except zipfile.BadZipFile as e:
+            raise InvalidWheel(wheel.location, name) from e
+        except UnsupportedWheel as e:
+            raise UnsupportedWheel(f"{name} has an invalid wheel, {e}")
+        return cls(dist, dist.info_location, pathlib.PurePosixPath(wheel.location))
+
+    @property
+    def location(self) -> Optional[str]:
+        if self._info_location is None:
+            return None
+        return str(self._info_location.parent)
+
+    @property
+    def info_location(self) -> Optional[str]:
+        if self._info_location is None:
+            return None
+        return str(self._info_location)
+
+    @property
+    def installed_location(self) -> Optional[str]:
+        if self._installed_location is None:
+            return None
+        return normalize_path(str(self._installed_location))
+
+    def _get_dist_name_from_location(self) -> Optional[str]:
+        """Try to get the name from the metadata directory name.
+
+        This is much faster than reading metadata.
+        """
+        if self._info_location is None:
+            return None
+        stem, suffix = os.path.splitext(self._info_location.name)
+        if suffix not in (".dist-info", ".egg-info"):
+            return None
+        return stem.split("-", 1)[0]
+
+    @property
+    def canonical_name(self) -> NormalizedName:
+        name = self._get_dist_name_from_location() or get_dist_name(self._dist)
+        return canonicalize_name(name)
+
+    @property
+    def version(self) -> DistributionVersion:
+        return parse_version(self._dist.version)
+
+    def is_file(self, path: InfoPath) -> bool:
+        return self._dist.read_text(str(path)) is not None
+
+    def iter_distutils_script_names(self) -> Iterator[str]:
+        # A distutils installation is always "flat" (not in e.g. egg form), so
+        # if this distribution's info location is NOT a pathlib.Path (but e.g.
+        # zipfile.Path), it can never contain any distutils scripts.
+        if not isinstance(self._info_location, pathlib.Path):
+            return
+        for child in self._info_location.joinpath("scripts").iterdir():
+            yield child.name
+
+    def read_text(self, path: InfoPath) -> str:
+        content = self._dist.read_text(str(path))
+        if content is None:
+            raise FileNotFoundError(path)
+        return content
+
+    def iter_entry_points(self) -> Iterable[BaseEntryPoint]:
+        # importlib.metadata's EntryPoint structure sasitfies BaseEntryPoint.
+        return self._dist.entry_points
+
+    def _metadata_impl(self) -> email.message.Message:
+        # From Python 3.10+, importlib.metadata declares PackageMetadata as the
+        # return type. This protocol is unfortunately a disaster now and misses
+        # a ton of fields that we need, including get() and get_payload(). We
+        # rely on the implementation that the object is actually a Message now,
+        # until upstream can improve the protocol. (python/cpython#94952)
+        return cast(email.message.Message, self._dist.metadata)
+
+    def iter_provided_extras(self) -> Iterable[str]:
+        return (
+            safe_extra(extra) for extra in self.metadata.get_all("Provides-Extra", [])
+        )
+
+    def iter_dependencies(self, extras: Collection[str] = ()) -> Iterable[Requirement]:
+        contexts: Sequence[Dict[str, str]] = [{"extra": safe_extra(e)} for e in extras]
+        for req_string in self.metadata.get_all("Requires-Dist", []):
+            req = Requirement(req_string)
+            if not req.marker:
+                yield req
+            elif not extras and req.marker.evaluate({"extra": ""}):
+                yield req
+            elif any(req.marker.evaluate(context) for context in contexts):
+                yield req
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_envs.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_envs.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbec59e2c6d3238afd29b4d46626a1550f849e2b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/importlib/_envs.py
@@ -0,0 +1,188 @@
+import functools
+import importlib.metadata
+import logging
+import os
+import pathlib
+import sys
+import zipfile
+import zipimport
+from typing import Iterator, List, Optional, Sequence, Set, Tuple
+
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+
+from pip._internal.metadata.base import BaseDistribution, BaseEnvironment
+from pip._internal.models.wheel import Wheel
+from pip._internal.utils.deprecation import deprecated
+from pip._internal.utils.filetypes import WHEEL_EXTENSION
+
+from ._compat import BadMetadata, BasePath, get_dist_name, get_info_location
+from ._dists import Distribution
+
+logger = logging.getLogger(__name__)
+
+
+def _looks_like_wheel(location: str) -> bool:
+    if not location.endswith(WHEEL_EXTENSION):
+        return False
+    if not os.path.isfile(location):
+        return False
+    if not Wheel.wheel_file_re.match(os.path.basename(location)):
+        return False
+    return zipfile.is_zipfile(location)
+
+
+class _DistributionFinder:
+    """Finder to locate distributions.
+
+    The main purpose of this class is to memoize found distributions' names, so
+    only one distribution is returned for each package name. At lot of pip code
+    assumes this (because it is setuptools's behavior), and not doing the same
+    can potentially cause a distribution in lower precedence path to override a
+    higher precedence one if the caller is not careful.
+
+    Eventually we probably want to make it possible to see lower precedence
+    installations as well. It's useful feature, after all.
+    """
+
+    FoundResult = Tuple[importlib.metadata.Distribution, Optional[BasePath]]
+
+    def __init__(self) -> None:
+        self._found_names: Set[NormalizedName] = set()
+
+    def _find_impl(self, location: str) -> Iterator[FoundResult]:
+        """Find distributions in a location."""
+        # Skip looking inside a wheel. Since a package inside a wheel is not
+        # always valid (due to .data directories etc.), its .dist-info entry
+        # should not be considered an installed distribution.
+        if _looks_like_wheel(location):
+            return
+        # To know exactly where we find a distribution, we have to feed in the
+        # paths one by one, instead of dumping the list to importlib.metadata.
+        for dist in importlib.metadata.distributions(path=[location]):
+            info_location = get_info_location(dist)
+            try:
+                raw_name = get_dist_name(dist)
+            except BadMetadata as e:
+                logger.warning("Skipping %s due to %s", info_location, e.reason)
+                continue
+            normalized_name = canonicalize_name(raw_name)
+            if normalized_name in self._found_names:
+                continue
+            self._found_names.add(normalized_name)
+            yield dist, info_location
+
+    def find(self, location: str) -> Iterator[BaseDistribution]:
+        """Find distributions in a location.
+
+        The path can be either a directory, or a ZIP archive.
+        """
+        for dist, info_location in self._find_impl(location):
+            if info_location is None:
+                installed_location: Optional[BasePath] = None
+            else:
+                installed_location = info_location.parent
+            yield Distribution(dist, info_location, installed_location)
+
+    def find_linked(self, location: str) -> Iterator[BaseDistribution]:
+        """Read location in egg-link files and return distributions in there.
+
+        The path should be a directory; otherwise this returns nothing. This
+        follows how setuptools does this for compatibility. The first non-empty
+        line in the egg-link is read as a path (resolved against the egg-link's
+        containing directory if relative). Distributions found at that linked
+        location are returned.
+        """
+        path = pathlib.Path(location)
+        if not path.is_dir():
+            return
+        for child in path.iterdir():
+            if child.suffix != ".egg-link":
+                continue
+            with child.open() as f:
+                lines = (line.strip() for line in f)
+                target_rel = next((line for line in lines if line), "")
+            if not target_rel:
+                continue
+            target_location = str(path.joinpath(target_rel))
+            for dist, info_location in self._find_impl(target_location):
+                yield Distribution(dist, info_location, path)
+
+    def _find_eggs_in_dir(self, location: str) -> Iterator[BaseDistribution]:
+        from pip._vendor.pkg_resources import find_distributions
+
+        from pip._internal.metadata import pkg_resources as legacy
+
+        with os.scandir(location) as it:
+            for entry in it:
+                if not entry.name.endswith(".egg"):
+                    continue
+                for dist in find_distributions(entry.path):
+                    yield legacy.Distribution(dist)
+
+    def _find_eggs_in_zip(self, location: str) -> Iterator[BaseDistribution]:
+        from pip._vendor.pkg_resources import find_eggs_in_zip
+
+        from pip._internal.metadata import pkg_resources as legacy
+
+        try:
+            importer = zipimport.zipimporter(location)
+        except zipimport.ZipImportError:
+            return
+        for dist in find_eggs_in_zip(importer, location):
+            yield legacy.Distribution(dist)
+
+    def find_eggs(self, location: str) -> Iterator[BaseDistribution]:
+        """Find eggs in a location.
+
+        This actually uses the old *pkg_resources* backend. We likely want to
+        deprecate this so we can eventually remove the *pkg_resources*
+        dependency entirely. Before that, this should first emit a deprecation
+        warning for some versions when using the fallback since importing
+        *pkg_resources* is slow for those who don't need it.
+        """
+        if os.path.isdir(location):
+            yield from self._find_eggs_in_dir(location)
+        if zipfile.is_zipfile(location):
+            yield from self._find_eggs_in_zip(location)
+
+
+@functools.lru_cache(maxsize=None)  # Warn a distribution exactly once.
+def _emit_egg_deprecation(location: Optional[str]) -> None:
+    deprecated(
+        reason=f"Loading egg at {location} is deprecated.",
+        replacement="to use pip for package installation.",
+        gone_in=None,
+    )
+
+
+class Environment(BaseEnvironment):
+    def __init__(self, paths: Sequence[str]) -> None:
+        self._paths = paths
+
+    @classmethod
+    def default(cls) -> BaseEnvironment:
+        return cls(sys.path)
+
+    @classmethod
+    def from_paths(cls, paths: Optional[List[str]]) -> BaseEnvironment:
+        if paths is None:
+            return cls(sys.path)
+        return cls(paths)
+
+    def _iter_distributions(self) -> Iterator[BaseDistribution]:
+        finder = _DistributionFinder()
+        for location in self._paths:
+            yield from finder.find(location)
+            for dist in finder.find_eggs(location):
+                # _emit_egg_deprecation(dist.location)  # TODO: Enable this.
+                yield dist
+            # This must go last because that's how pkg_resources tie-breaks.
+            yield from finder.find_linked(location)
+
+    def get_distribution(self, name: str) -> Optional[BaseDistribution]:
+        matches = (
+            distribution
+            for distribution in self.iter_all_distributions()
+            if distribution.canonical_name == canonicalize_name(name)
+        )
+        return next(matches, None)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/pkg_resources.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/pkg_resources.py
new file mode 100644
index 0000000000000000000000000000000000000000..f330ef12a2c5ea0a4adbecbeea389741479d5eb4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/metadata/pkg_resources.py
@@ -0,0 +1,270 @@
+import email.message
+import email.parser
+import logging
+import os
+import zipfile
+from typing import Collection, Iterable, Iterator, List, Mapping, NamedTuple, Optional
+
+from pip._vendor import pkg_resources
+from pip._vendor.packaging.requirements import Requirement
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+from pip._vendor.packaging.version import parse as parse_version
+
+from pip._internal.exceptions import InvalidWheel, NoneMetadataError, UnsupportedWheel
+from pip._internal.utils.egg_link import egg_link_path_from_location
+from pip._internal.utils.misc import display_path, normalize_path
+from pip._internal.utils.wheel import parse_wheel, read_wheel_metadata_file
+
+from .base import (
+    BaseDistribution,
+    BaseEntryPoint,
+    BaseEnvironment,
+    DistributionVersion,
+    InfoPath,
+    Wheel,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class EntryPoint(NamedTuple):
+    name: str
+    value: str
+    group: str
+
+
+class InMemoryMetadata:
+    """IMetadataProvider that reads metadata files from a dictionary.
+
+    This also maps metadata decoding exceptions to our internal exception type.
+    """
+
+    def __init__(self, metadata: Mapping[str, bytes], wheel_name: str) -> None:
+        self._metadata = metadata
+        self._wheel_name = wheel_name
+
+    def has_metadata(self, name: str) -> bool:
+        return name in self._metadata
+
+    def get_metadata(self, name: str) -> str:
+        try:
+            return self._metadata[name].decode()
+        except UnicodeDecodeError as e:
+            # Augment the default error with the origin of the file.
+            raise UnsupportedWheel(
+                f"Error decoding metadata for {self._wheel_name}: {e} in {name} file"
+            )
+
+    def get_metadata_lines(self, name: str) -> Iterable[str]:
+        return pkg_resources.yield_lines(self.get_metadata(name))
+
+    def metadata_isdir(self, name: str) -> bool:
+        return False
+
+    def metadata_listdir(self, name: str) -> List[str]:
+        return []
+
+    def run_script(self, script_name: str, namespace: str) -> None:
+        pass
+
+
+class Distribution(BaseDistribution):
+    def __init__(self, dist: pkg_resources.Distribution) -> None:
+        self._dist = dist
+
+    @classmethod
+    def from_directory(cls, directory: str) -> BaseDistribution:
+        dist_dir = directory.rstrip(os.sep)
+
+        # Build a PathMetadata object, from path to metadata. :wink:
+        base_dir, dist_dir_name = os.path.split(dist_dir)
+        metadata = pkg_resources.PathMetadata(base_dir, dist_dir)
+
+        # Determine the correct Distribution object type.
+        if dist_dir.endswith(".egg-info"):
+            dist_cls = pkg_resources.Distribution
+            dist_name = os.path.splitext(dist_dir_name)[0]
+        else:
+            assert dist_dir.endswith(".dist-info")
+            dist_cls = pkg_resources.DistInfoDistribution
+            dist_name = os.path.splitext(dist_dir_name)[0].split("-")[0]
+
+        dist = dist_cls(base_dir, project_name=dist_name, metadata=metadata)
+        return cls(dist)
+
+    @classmethod
+    def from_metadata_file_contents(
+        cls,
+        metadata_contents: bytes,
+        filename: str,
+        project_name: str,
+    ) -> BaseDistribution:
+        metadata_dict = {
+            "METADATA": metadata_contents,
+        }
+        dist = pkg_resources.DistInfoDistribution(
+            location=filename,
+            metadata=InMemoryMetadata(metadata_dict, filename),
+            project_name=project_name,
+        )
+        return cls(dist)
+
+    @classmethod
+    def from_wheel(cls, wheel: Wheel, name: str) -> BaseDistribution:
+        try:
+            with wheel.as_zipfile() as zf:
+                info_dir, _ = parse_wheel(zf, name)
+                metadata_dict = {
+                    path.split("/", 1)[-1]: read_wheel_metadata_file(zf, path)
+                    for path in zf.namelist()
+                    if path.startswith(f"{info_dir}/")
+                }
+        except zipfile.BadZipFile as e:
+            raise InvalidWheel(wheel.location, name) from e
+        except UnsupportedWheel as e:
+            raise UnsupportedWheel(f"{name} has an invalid wheel, {e}")
+        dist = pkg_resources.DistInfoDistribution(
+            location=wheel.location,
+            metadata=InMemoryMetadata(metadata_dict, wheel.location),
+            project_name=name,
+        )
+        return cls(dist)
+
+    @property
+    def location(self) -> Optional[str]:
+        return self._dist.location
+
+    @property
+    def installed_location(self) -> Optional[str]:
+        egg_link = egg_link_path_from_location(self.raw_name)
+        if egg_link:
+            location = egg_link
+        elif self.location:
+            location = self.location
+        else:
+            return None
+        return normalize_path(location)
+
+    @property
+    def info_location(self) -> Optional[str]:
+        return self._dist.egg_info
+
+    @property
+    def installed_by_distutils(self) -> bool:
+        # A distutils-installed distribution is provided by FileMetadata. This
+        # provider has a "path" attribute not present anywhere else. Not the
+        # best introspection logic, but pip has been doing this for a long time.
+        try:
+            return bool(self._dist._provider.path)
+        except AttributeError:
+            return False
+
+    @property
+    def canonical_name(self) -> NormalizedName:
+        return canonicalize_name(self._dist.project_name)
+
+    @property
+    def version(self) -> DistributionVersion:
+        return parse_version(self._dist.version)
+
+    def is_file(self, path: InfoPath) -> bool:
+        return self._dist.has_metadata(str(path))
+
+    def iter_distutils_script_names(self) -> Iterator[str]:
+        yield from self._dist.metadata_listdir("scripts")
+
+    def read_text(self, path: InfoPath) -> str:
+        name = str(path)
+        if not self._dist.has_metadata(name):
+            raise FileNotFoundError(name)
+        content = self._dist.get_metadata(name)
+        if content is None:
+            raise NoneMetadataError(self, name)
+        return content
+
+    def iter_entry_points(self) -> Iterable[BaseEntryPoint]:
+        for group, entries in self._dist.get_entry_map().items():
+            for name, entry_point in entries.items():
+                name, _, value = str(entry_point).partition("=")
+                yield EntryPoint(name=name.strip(), value=value.strip(), group=group)
+
+    def _metadata_impl(self) -> email.message.Message:
+        """
+        :raises NoneMetadataError: if the distribution reports `has_metadata()`
+            True but `get_metadata()` returns None.
+        """
+        if isinstance(self._dist, pkg_resources.DistInfoDistribution):
+            metadata_name = "METADATA"
+        else:
+            metadata_name = "PKG-INFO"
+        try:
+            metadata = self.read_text(metadata_name)
+        except FileNotFoundError:
+            if self.location:
+                displaying_path = display_path(self.location)
+            else:
+                displaying_path = repr(self.location)
+            logger.warning("No metadata found in %s", displaying_path)
+            metadata = ""
+        feed_parser = email.parser.FeedParser()
+        feed_parser.feed(metadata)
+        return feed_parser.close()
+
+    def iter_dependencies(self, extras: Collection[str] = ()) -> Iterable[Requirement]:
+        if extras:  # pkg_resources raises on invalid extras, so we sanitize.
+            extras = frozenset(extras).intersection(self._dist.extras)
+        return self._dist.requires(extras)
+
+    def iter_provided_extras(self) -> Iterable[str]:
+        return self._dist.extras
+
+
+class Environment(BaseEnvironment):
+    def __init__(self, ws: pkg_resources.WorkingSet) -> None:
+        self._ws = ws
+
+    @classmethod
+    def default(cls) -> BaseEnvironment:
+        return cls(pkg_resources.working_set)
+
+    @classmethod
+    def from_paths(cls, paths: Optional[List[str]]) -> BaseEnvironment:
+        return cls(pkg_resources.WorkingSet(paths))
+
+    def _iter_distributions(self) -> Iterator[BaseDistribution]:
+        for dist in self._ws:
+            yield Distribution(dist)
+
+    def _search_distribution(self, name: str) -> Optional[BaseDistribution]:
+        """Find a distribution matching the ``name`` in the environment.
+
+        This searches from *all* distributions available in the environment, to
+        match the behavior of ``pkg_resources.get_distribution()``.
+        """
+        canonical_name = canonicalize_name(name)
+        for dist in self.iter_all_distributions():
+            if dist.canonical_name == canonical_name:
+                return dist
+        return None
+
+    def get_distribution(self, name: str) -> Optional[BaseDistribution]:
+        # Search the distribution by looking through the working set.
+        dist = self._search_distribution(name)
+        if dist:
+            return dist
+
+        # If distribution could not be found, call working_set.require to
+        # update the working set, and try to find the distribution again.
+        # This might happen for e.g. when you install a package twice, once
+        # using setup.py develop and again using setup.py install. Now when
+        # running pip uninstall twice, the package gets removed from the
+        # working set in the first uninstall, so we have to populate the
+        # working set again so that pip knows about it and the packages gets
+        # picked up and is successfully uninstalled the second time too.
+        try:
+            # We didn't pass in any version specifiers, so this can never
+            # raise pkg_resources.VersionConflict.
+            self._ws.require(name)
+        except pkg_resources.DistributionNotFound:
+            return None
+        return self._search_distribution(name)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..7855226e4b500142deef8fb247cd33a9a991d122
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/__init__.py
@@ -0,0 +1,2 @@
+"""A package that contains models that represent entities.
+"""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/candidate.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/candidate.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4963aec6388c27c3beb064f0a730af200380aee
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/candidate.py
@@ -0,0 +1,34 @@
+from pip._vendor.packaging.version import parse as parse_version
+
+from pip._internal.models.link import Link
+from pip._internal.utils.models import KeyBasedCompareMixin
+
+
+class InstallationCandidate(KeyBasedCompareMixin):
+    """Represents a potential "candidate" for installation."""
+
+    __slots__ = ["name", "version", "link"]
+
+    def __init__(self, name: str, version: str, link: Link) -> None:
+        self.name = name
+        self.version = parse_version(version)
+        self.link = link
+
+        super().__init__(
+            key=(self.name, self.version, self.link),
+            defining_class=InstallationCandidate,
+        )
+
+    def __repr__(self) -> str:
+        return "".format(
+            self.name,
+            self.version,
+            self.link,
+        )
+
+    def __str__(self) -> str:
+        return "{!r} candidate (version {} at {})".format(
+            self.name,
+            self.version,
+            self.link,
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/direct_url.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/direct_url.py
new file mode 100644
index 0000000000000000000000000000000000000000..c3de70a749c3dc35b339c299961d0c3f6439cf2b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/direct_url.py
@@ -0,0 +1,228 @@
+""" PEP 610 """
+import json
+import re
+import urllib.parse
+from typing import Any, Dict, Iterable, Optional, Type, TypeVar, Union
+
+__all__ = [
+    "DirectUrl",
+    "DirectUrlValidationError",
+    "DirInfo",
+    "ArchiveInfo",
+    "VcsInfo",
+]
+
+T = TypeVar("T")
+
+DIRECT_URL_METADATA_NAME = "direct_url.json"
+ENV_VAR_RE = re.compile(r"^\$\{[A-Za-z0-9-_]+\}(:\$\{[A-Za-z0-9-_]+\})?$")
+
+
+class DirectUrlValidationError(Exception):
+    pass
+
+
+def _get(
+    d: Dict[str, Any], expected_type: Type[T], key: str, default: Optional[T] = None
+) -> Optional[T]:
+    """Get value from dictionary and verify expected type."""
+    if key not in d:
+        return default
+    value = d[key]
+    if not isinstance(value, expected_type):
+        raise DirectUrlValidationError(
+            "{!r} has unexpected type for {} (expected {})".format(
+                value, key, expected_type
+            )
+        )
+    return value
+
+
+def _get_required(
+    d: Dict[str, Any], expected_type: Type[T], key: str, default: Optional[T] = None
+) -> T:
+    value = _get(d, expected_type, key, default)
+    if value is None:
+        raise DirectUrlValidationError(f"{key} must have a value")
+    return value
+
+
+def _exactly_one_of(infos: Iterable[Optional["InfoType"]]) -> "InfoType":
+    infos = [info for info in infos if info is not None]
+    if not infos:
+        raise DirectUrlValidationError(
+            "missing one of archive_info, dir_info, vcs_info"
+        )
+    if len(infos) > 1:
+        raise DirectUrlValidationError(
+            "more than one of archive_info, dir_info, vcs_info"
+        )
+    assert infos[0] is not None
+    return infos[0]
+
+
+def _filter_none(**kwargs: Any) -> Dict[str, Any]:
+    """Make dict excluding None values."""
+    return {k: v for k, v in kwargs.items() if v is not None}
+
+
+class VcsInfo:
+    name = "vcs_info"
+
+    def __init__(
+        self,
+        vcs: str,
+        commit_id: str,
+        requested_revision: Optional[str] = None,
+    ) -> None:
+        self.vcs = vcs
+        self.requested_revision = requested_revision
+        self.commit_id = commit_id
+
+    @classmethod
+    def _from_dict(cls, d: Optional[Dict[str, Any]]) -> Optional["VcsInfo"]:
+        if d is None:
+            return None
+        return cls(
+            vcs=_get_required(d, str, "vcs"),
+            commit_id=_get_required(d, str, "commit_id"),
+            requested_revision=_get(d, str, "requested_revision"),
+        )
+
+    def _to_dict(self) -> Dict[str, Any]:
+        return _filter_none(
+            vcs=self.vcs,
+            requested_revision=self.requested_revision,
+            commit_id=self.commit_id,
+        )
+
+
+class ArchiveInfo:
+    name = "archive_info"
+
+    def __init__(
+        self,
+        hash: Optional[str] = None,
+        hashes: Optional[Dict[str, str]] = None,
+    ) -> None:
+        if hash is not None:
+            # Auto-populate the hashes key to upgrade to the new format automatically.
+            # We don't back-populate the legacy hash key.
+            try:
+                hash_name, hash_value = hash.split("=", 1)
+            except ValueError:
+                raise DirectUrlValidationError(
+                    f"invalid archive_info.hash format: {hash!r}"
+                )
+            if hashes is None:
+                hashes = {hash_name: hash_value}
+            elif hash_name not in hash:
+                hashes = hashes.copy()
+                hashes[hash_name] = hash_value
+        self.hash = hash
+        self.hashes = hashes
+
+    @classmethod
+    def _from_dict(cls, d: Optional[Dict[str, Any]]) -> Optional["ArchiveInfo"]:
+        if d is None:
+            return None
+        return cls(hash=_get(d, str, "hash"), hashes=_get(d, dict, "hashes"))
+
+    def _to_dict(self) -> Dict[str, Any]:
+        return _filter_none(hash=self.hash, hashes=self.hashes)
+
+
+class DirInfo:
+    name = "dir_info"
+
+    def __init__(
+        self,
+        editable: bool = False,
+    ) -> None:
+        self.editable = editable
+
+    @classmethod
+    def _from_dict(cls, d: Optional[Dict[str, Any]]) -> Optional["DirInfo"]:
+        if d is None:
+            return None
+        return cls(editable=_get_required(d, bool, "editable", default=False))
+
+    def _to_dict(self) -> Dict[str, Any]:
+        return _filter_none(editable=self.editable or None)
+
+
+InfoType = Union[ArchiveInfo, DirInfo, VcsInfo]
+
+
+class DirectUrl:
+    def __init__(
+        self,
+        url: str,
+        info: InfoType,
+        subdirectory: Optional[str] = None,
+    ) -> None:
+        self.url = url
+        self.info = info
+        self.subdirectory = subdirectory
+
+    def _remove_auth_from_netloc(self, netloc: str) -> str:
+        if "@" not in netloc:
+            return netloc
+        user_pass, netloc_no_user_pass = netloc.split("@", 1)
+        if (
+            isinstance(self.info, VcsInfo)
+            and self.info.vcs == "git"
+            and user_pass == "git"
+        ):
+            return netloc
+        if ENV_VAR_RE.match(user_pass):
+            return netloc
+        return netloc_no_user_pass
+
+    @property
+    def redacted_url(self) -> str:
+        """url with user:password part removed unless it is formed with
+        environment variables as specified in PEP 610, or it is ``git``
+        in the case of a git URL.
+        """
+        purl = urllib.parse.urlsplit(self.url)
+        netloc = self._remove_auth_from_netloc(purl.netloc)
+        surl = urllib.parse.urlunsplit(
+            (purl.scheme, netloc, purl.path, purl.query, purl.fragment)
+        )
+        return surl
+
+    def validate(self) -> None:
+        self.from_dict(self.to_dict())
+
+    @classmethod
+    def from_dict(cls, d: Dict[str, Any]) -> "DirectUrl":
+        return DirectUrl(
+            url=_get_required(d, str, "url"),
+            subdirectory=_get(d, str, "subdirectory"),
+            info=_exactly_one_of(
+                [
+                    ArchiveInfo._from_dict(_get(d, dict, "archive_info")),
+                    DirInfo._from_dict(_get(d, dict, "dir_info")),
+                    VcsInfo._from_dict(_get(d, dict, "vcs_info")),
+                ]
+            ),
+        )
+
+    def to_dict(self) -> Dict[str, Any]:
+        res = _filter_none(
+            url=self.redacted_url,
+            subdirectory=self.subdirectory,
+        )
+        res[self.info.name] = self.info._to_dict()
+        return res
+
+    @classmethod
+    def from_json(cls, s: str) -> "DirectUrl":
+        return cls.from_dict(json.loads(s))
+
+    def to_json(self) -> str:
+        return json.dumps(self.to_dict(), sort_keys=True)
+
+    def is_local_editable(self) -> bool:
+        return isinstance(self.info, DirInfo) and self.info.editable
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/format_control.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/format_control.py
new file mode 100644
index 0000000000000000000000000000000000000000..db3995eac9f9ec2450e0e2d4a18e666c0b178681
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/format_control.py
@@ -0,0 +1,80 @@
+from typing import FrozenSet, Optional, Set
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.exceptions import CommandError
+
+
+class FormatControl:
+    """Helper for managing formats from which a package can be installed."""
+
+    __slots__ = ["no_binary", "only_binary"]
+
+    def __init__(
+        self,
+        no_binary: Optional[Set[str]] = None,
+        only_binary: Optional[Set[str]] = None,
+    ) -> None:
+        if no_binary is None:
+            no_binary = set()
+        if only_binary is None:
+            only_binary = set()
+
+        self.no_binary = no_binary
+        self.only_binary = only_binary
+
+    def __eq__(self, other: object) -> bool:
+        if not isinstance(other, self.__class__):
+            return NotImplemented
+
+        if self.__slots__ != other.__slots__:
+            return False
+
+        return all(getattr(self, k) == getattr(other, k) for k in self.__slots__)
+
+    def __repr__(self) -> str:
+        return "{}({}, {})".format(
+            self.__class__.__name__, self.no_binary, self.only_binary
+        )
+
+    @staticmethod
+    def handle_mutual_excludes(value: str, target: Set[str], other: Set[str]) -> None:
+        if value.startswith("-"):
+            raise CommandError(
+                "--no-binary / --only-binary option requires 1 argument."
+            )
+        new = value.split(",")
+        while ":all:" in new:
+            other.clear()
+            target.clear()
+            target.add(":all:")
+            del new[: new.index(":all:") + 1]
+            # Without a none, we want to discard everything as :all: covers it
+            if ":none:" not in new:
+                return
+        for name in new:
+            if name == ":none:":
+                target.clear()
+                continue
+            name = canonicalize_name(name)
+            other.discard(name)
+            target.add(name)
+
+    def get_allowed_formats(self, canonical_name: str) -> FrozenSet[str]:
+        result = {"binary", "source"}
+        if canonical_name in self.only_binary:
+            result.discard("source")
+        elif canonical_name in self.no_binary:
+            result.discard("binary")
+        elif ":all:" in self.only_binary:
+            result.discard("source")
+        elif ":all:" in self.no_binary:
+            result.discard("binary")
+        return frozenset(result)
+
+    def disallow_binaries(self) -> None:
+        self.handle_mutual_excludes(
+            ":all:",
+            self.no_binary,
+            self.only_binary,
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/index.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/index.py
new file mode 100644
index 0000000000000000000000000000000000000000..b94c32511f0cda2363bfc4f29c9c8bfcc7101f9b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/index.py
@@ -0,0 +1,28 @@
+import urllib.parse
+
+
+class PackageIndex:
+    """Represents a Package Index and provides easier access to endpoints"""
+
+    __slots__ = ["url", "netloc", "simple_url", "pypi_url", "file_storage_domain"]
+
+    def __init__(self, url: str, file_storage_domain: str) -> None:
+        super().__init__()
+        self.url = url
+        self.netloc = urllib.parse.urlsplit(url).netloc
+        self.simple_url = self._url_for_path("simple")
+        self.pypi_url = self._url_for_path("pypi")
+
+        # This is part of a temporary hack used to block installs of PyPI
+        # packages which depend on external urls only necessary until PyPI can
+        # block such packages themselves
+        self.file_storage_domain = file_storage_domain
+
+    def _url_for_path(self, path: str) -> str:
+        return urllib.parse.urljoin(self.url, path)
+
+
+PyPI = PackageIndex("https://pypi.org/", file_storage_domain="files.pythonhosted.org")
+TestPyPI = PackageIndex(
+    "https://test.pypi.org/", file_storage_domain="test-files.pythonhosted.org"
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/installation_report.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/installation_report.py
new file mode 100644
index 0000000000000000000000000000000000000000..b54afb109b47538793ea97c776cd8829e64684ce
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/installation_report.py
@@ -0,0 +1,53 @@
+from typing import Any, Dict, Sequence
+
+from pip._vendor.packaging.markers import default_environment
+
+from pip import __version__
+from pip._internal.req.req_install import InstallRequirement
+
+
+class InstallationReport:
+    def __init__(self, install_requirements: Sequence[InstallRequirement]):
+        self._install_requirements = install_requirements
+
+    @classmethod
+    def _install_req_to_dict(cls, ireq: InstallRequirement) -> Dict[str, Any]:
+        assert ireq.download_info, f"No download_info for {ireq}"
+        res = {
+            # PEP 610 json for the download URL. download_info.archive_info.hash may
+            # be absent when the requirement was installed from the wheel cache
+            # and the cache entry was populated by an older pip version that did not
+            # record origin.json.
+            "download_info": ireq.download_info.to_dict(),
+            # is_direct is true if the requirement was a direct URL reference (which
+            # includes editable requirements), and false if the requirement was
+            # downloaded from a PEP 503 index or --find-links.
+            "is_direct": bool(ireq.original_link),
+            # requested is true if the requirement was specified by the user (aka
+            # top level requirement), and false if it was installed as a dependency of a
+            # requirement. https://peps.python.org/pep-0376/#requested
+            "requested": ireq.user_supplied,
+            # PEP 566 json encoding for metadata
+            # https://www.python.org/dev/peps/pep-0566/#json-compatible-metadata
+            "metadata": ireq.get_dist().metadata_dict,
+        }
+        if ireq.user_supplied and ireq.extras:
+            # For top level requirements, the list of requested extras, if any.
+            res["requested_extras"] = list(sorted(ireq.extras))
+        return res
+
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "version": "1",
+            "pip_version": __version__,
+            "install": [
+                self._install_req_to_dict(ireq) for ireq in self._install_requirements
+            ],
+            # https://peps.python.org/pep-0508/#environment-markers
+            # TODO: currently, the resolver uses the default environment to evaluate
+            # environment markers, so that is what we report here. In the future, it
+            # should also take into account options such as --python-version or
+            # --platform, perhaps under the form of an environment_override field?
+            # https://github.com/pypa/pip/issues/11198
+            "environment": default_environment(),
+        }
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/link.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/link.py
new file mode 100644
index 0000000000000000000000000000000000000000..a1e4d5a08dffd7e939ae36ab837fb26d20189fbc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/link.py
@@ -0,0 +1,524 @@
+import functools
+import itertools
+import logging
+import os
+import posixpath
+import re
+import urllib.parse
+from dataclasses import dataclass
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Dict,
+    List,
+    Mapping,
+    NamedTuple,
+    Optional,
+    Tuple,
+    Union,
+)
+
+from pip._internal.utils.deprecation import deprecated
+from pip._internal.utils.filetypes import WHEEL_EXTENSION
+from pip._internal.utils.hashes import Hashes
+from pip._internal.utils.misc import (
+    pairwise,
+    redact_auth_from_url,
+    split_auth_from_netloc,
+    splitext,
+)
+from pip._internal.utils.models import KeyBasedCompareMixin
+from pip._internal.utils.urls import path_to_url, url_to_path
+
+if TYPE_CHECKING:
+    from pip._internal.index.collector import IndexContent
+
+logger = logging.getLogger(__name__)
+
+
+# Order matters, earlier hashes have a precedence over later hashes for what
+# we will pick to use.
+_SUPPORTED_HASHES = ("sha512", "sha384", "sha256", "sha224", "sha1", "md5")
+
+
+@dataclass(frozen=True)
+class LinkHash:
+    """Links to content may have embedded hash values. This class parses those.
+
+    `name` must be any member of `_SUPPORTED_HASHES`.
+
+    This class can be converted to and from `ArchiveInfo`. While ArchiveInfo intends to
+    be JSON-serializable to conform to PEP 610, this class contains the logic for
+    parsing a hash name and value for correctness, and then checking whether that hash
+    conforms to a schema with `.is_hash_allowed()`."""
+
+    name: str
+    value: str
+
+    _hash_re = re.compile(
+        # NB: we do not validate that the second group (.*) is a valid hex
+        # digest. Instead, we simply keep that string in this class, and then check it
+        # against Hashes when hash-checking is needed. This is easier to debug than
+        # proactively discarding an invalid hex digest, as we handle incorrect hashes
+        # and malformed hashes in the same place.
+        r"({choices})=(.*)".format(
+            choices="|".join(re.escape(hash_name) for hash_name in _SUPPORTED_HASHES)
+        ),
+    )
+
+    def __post_init__(self) -> None:
+        assert self._hash_re.match(f"{self.name}={self.value}")
+
+    @classmethod
+    @functools.lru_cache(maxsize=None)
+    def split_hash_name_and_value(cls, url: str) -> Optional["LinkHash"]:
+        """Search a string for a checksum algorithm name and encoded output value."""
+        match = cls._hash_re.search(url)
+        if match is None:
+            return None
+        name, value = match.groups()
+        return cls(name=name, value=value)
+
+    def as_dict(self) -> Dict[str, str]:
+        return {self.name: self.value}
+
+    def as_hashes(self) -> Hashes:
+        """Return a Hashes instance which checks only for the current hash."""
+        return Hashes({self.name: [self.value]})
+
+    def is_hash_allowed(self, hashes: Optional[Hashes]) -> bool:
+        """
+        Return True if the current hash is allowed by `hashes`.
+        """
+        if hashes is None:
+            return False
+        return hashes.is_hash_allowed(self.name, hex_digest=self.value)
+
+
+def _clean_url_path_part(part: str) -> str:
+    """
+    Clean a "part" of a URL path (i.e. after splitting on "@" characters).
+    """
+    # We unquote prior to quoting to make sure nothing is double quoted.
+    return urllib.parse.quote(urllib.parse.unquote(part))
+
+
+def _clean_file_url_path(part: str) -> str:
+    """
+    Clean the first part of a URL path that corresponds to a local
+    filesystem path (i.e. the first part after splitting on "@" characters).
+    """
+    # We unquote prior to quoting to make sure nothing is double quoted.
+    # Also, on Windows the path part might contain a drive letter which
+    # should not be quoted. On Linux where drive letters do not
+    # exist, the colon should be quoted. We rely on urllib.request
+    # to do the right thing here.
+    return urllib.request.pathname2url(urllib.request.url2pathname(part))
+
+
+# percent-encoded:                   /
+_reserved_chars_re = re.compile("(@|%2F)", re.IGNORECASE)
+
+
+def _clean_url_path(path: str, is_local_path: bool) -> str:
+    """
+    Clean the path portion of a URL.
+    """
+    if is_local_path:
+        clean_func = _clean_file_url_path
+    else:
+        clean_func = _clean_url_path_part
+
+    # Split on the reserved characters prior to cleaning so that
+    # revision strings in VCS URLs are properly preserved.
+    parts = _reserved_chars_re.split(path)
+
+    cleaned_parts = []
+    for to_clean, reserved in pairwise(itertools.chain(parts, [""])):
+        cleaned_parts.append(clean_func(to_clean))
+        # Normalize %xx escapes (e.g. %2f -> %2F)
+        cleaned_parts.append(reserved.upper())
+
+    return "".join(cleaned_parts)
+
+
+def _ensure_quoted_url(url: str) -> str:
+    """
+    Make sure a link is fully quoted.
+    For example, if ' ' occurs in the URL, it will be replaced with "%20",
+    and without double-quoting other characters.
+    """
+    # Split the URL into parts according to the general structure
+    # `scheme://netloc/path;parameters?query#fragment`.
+    result = urllib.parse.urlparse(url)
+    # If the netloc is empty, then the URL refers to a local filesystem path.
+    is_local_path = not result.netloc
+    path = _clean_url_path(result.path, is_local_path=is_local_path)
+    return urllib.parse.urlunparse(result._replace(path=path))
+
+
+class Link(KeyBasedCompareMixin):
+    """Represents a parsed link from a Package Index's simple URL"""
+
+    __slots__ = [
+        "_parsed_url",
+        "_url",
+        "_hashes",
+        "comes_from",
+        "requires_python",
+        "yanked_reason",
+        "dist_info_metadata",
+        "cache_link_parsing",
+        "egg_fragment",
+    ]
+
+    def __init__(
+        self,
+        url: str,
+        comes_from: Optional[Union[str, "IndexContent"]] = None,
+        requires_python: Optional[str] = None,
+        yanked_reason: Optional[str] = None,
+        dist_info_metadata: Optional[str] = None,
+        cache_link_parsing: bool = True,
+        hashes: Optional[Mapping[str, str]] = None,
+    ) -> None:
+        """
+        :param url: url of the resource pointed to (href of the link)
+        :param comes_from: instance of IndexContent where the link was found,
+            or string.
+        :param requires_python: String containing the `Requires-Python`
+            metadata field, specified in PEP 345. This may be specified by
+            a data-requires-python attribute in the HTML link tag, as
+            described in PEP 503.
+        :param yanked_reason: the reason the file has been yanked, if the
+            file has been yanked, or None if the file hasn't been yanked.
+            This is the value of the "data-yanked" attribute, if present, in
+            a simple repository HTML link. If the file has been yanked but
+            no reason was provided, this should be the empty string. See
+            PEP 592 for more information and the specification.
+        :param dist_info_metadata: the metadata attached to the file, or None if no such
+            metadata is provided. This is the value of the "data-dist-info-metadata"
+            attribute, if present, in a simple repository HTML link. This may be parsed
+            into its own `Link` by `self.metadata_link()`. See PEP 658 for more
+            information and the specification.
+        :param cache_link_parsing: A flag that is used elsewhere to determine
+            whether resources retrieved from this link should be cached. PyPI
+            URLs should generally have this set to False, for example.
+        :param hashes: A mapping of hash names to digests to allow us to
+            determine the validity of a download.
+        """
+
+        # url can be a UNC windows share
+        if url.startswith("\\\\"):
+            url = path_to_url(url)
+
+        self._parsed_url = urllib.parse.urlsplit(url)
+        # Store the url as a private attribute to prevent accidentally
+        # trying to set a new value.
+        self._url = url
+
+        link_hash = LinkHash.split_hash_name_and_value(url)
+        hashes_from_link = {} if link_hash is None else link_hash.as_dict()
+        if hashes is None:
+            self._hashes = hashes_from_link
+        else:
+            self._hashes = {**hashes, **hashes_from_link}
+
+        self.comes_from = comes_from
+        self.requires_python = requires_python if requires_python else None
+        self.yanked_reason = yanked_reason
+        self.dist_info_metadata = dist_info_metadata
+
+        super().__init__(key=url, defining_class=Link)
+
+        self.cache_link_parsing = cache_link_parsing
+        self.egg_fragment = self._egg_fragment()
+
+    @classmethod
+    def from_json(
+        cls,
+        file_data: Dict[str, Any],
+        page_url: str,
+    ) -> Optional["Link"]:
+        """
+        Convert an pypi json document from a simple repository page into a Link.
+        """
+        file_url = file_data.get("url")
+        if file_url is None:
+            return None
+
+        url = _ensure_quoted_url(urllib.parse.urljoin(page_url, file_url))
+        pyrequire = file_data.get("requires-python")
+        yanked_reason = file_data.get("yanked")
+        dist_info_metadata = file_data.get("dist-info-metadata")
+        hashes = file_data.get("hashes", {})
+
+        # The Link.yanked_reason expects an empty string instead of a boolean.
+        if yanked_reason and not isinstance(yanked_reason, str):
+            yanked_reason = ""
+        # The Link.yanked_reason expects None instead of False.
+        elif not yanked_reason:
+            yanked_reason = None
+
+        return cls(
+            url,
+            comes_from=page_url,
+            requires_python=pyrequire,
+            yanked_reason=yanked_reason,
+            hashes=hashes,
+            dist_info_metadata=dist_info_metadata,
+        )
+
+    @classmethod
+    def from_element(
+        cls,
+        anchor_attribs: Dict[str, Optional[str]],
+        page_url: str,
+        base_url: str,
+    ) -> Optional["Link"]:
+        """
+        Convert an anchor element's attributes in a simple repository page to a Link.
+        """
+        href = anchor_attribs.get("href")
+        if not href:
+            return None
+
+        url = _ensure_quoted_url(urllib.parse.urljoin(base_url, href))
+        pyrequire = anchor_attribs.get("data-requires-python")
+        yanked_reason = anchor_attribs.get("data-yanked")
+        dist_info_metadata = anchor_attribs.get("data-dist-info-metadata")
+
+        return cls(
+            url,
+            comes_from=page_url,
+            requires_python=pyrequire,
+            yanked_reason=yanked_reason,
+            dist_info_metadata=dist_info_metadata,
+        )
+
+    def __str__(self) -> str:
+        if self.requires_python:
+            rp = f" (requires-python:{self.requires_python})"
+        else:
+            rp = ""
+        if self.comes_from:
+            return "{} (from {}){}".format(
+                redact_auth_from_url(self._url), self.comes_from, rp
+            )
+        else:
+            return redact_auth_from_url(str(self._url))
+
+    def __repr__(self) -> str:
+        return f""
+
+    @property
+    def url(self) -> str:
+        return self._url
+
+    @property
+    def filename(self) -> str:
+        path = self.path.rstrip("/")
+        name = posixpath.basename(path)
+        if not name:
+            # Make sure we don't leak auth information if the netloc
+            # includes a username and password.
+            netloc, user_pass = split_auth_from_netloc(self.netloc)
+            return netloc
+
+        name = urllib.parse.unquote(name)
+        assert name, f"URL {self._url!r} produced no filename"
+        return name
+
+    @property
+    def file_path(self) -> str:
+        return url_to_path(self.url)
+
+    @property
+    def scheme(self) -> str:
+        return self._parsed_url.scheme
+
+    @property
+    def netloc(self) -> str:
+        """
+        This can contain auth information.
+        """
+        return self._parsed_url.netloc
+
+    @property
+    def path(self) -> str:
+        return urllib.parse.unquote(self._parsed_url.path)
+
+    def splitext(self) -> Tuple[str, str]:
+        return splitext(posixpath.basename(self.path.rstrip("/")))
+
+    @property
+    def ext(self) -> str:
+        return self.splitext()[1]
+
+    @property
+    def url_without_fragment(self) -> str:
+        scheme, netloc, path, query, fragment = self._parsed_url
+        return urllib.parse.urlunsplit((scheme, netloc, path, query, ""))
+
+    _egg_fragment_re = re.compile(r"[#&]egg=([^&]*)")
+
+    # Per PEP 508.
+    _project_name_re = re.compile(
+        r"^([A-Z0-9]|[A-Z0-9][A-Z0-9._-]*[A-Z0-9])$", re.IGNORECASE
+    )
+
+    def _egg_fragment(self) -> Optional[str]:
+        match = self._egg_fragment_re.search(self._url)
+        if not match:
+            return None
+
+        # An egg fragment looks like a PEP 508 project name, along with
+        # an optional extras specifier. Anything else is invalid.
+        project_name = match.group(1)
+        if not self._project_name_re.match(project_name):
+            deprecated(
+                reason=f"{self} contains an egg fragment with a non-PEP 508 name",
+                replacement="to use the req @ url syntax, and remove the egg fragment",
+                gone_in="25.0",
+                issue=11617,
+            )
+
+        return project_name
+
+    _subdirectory_fragment_re = re.compile(r"[#&]subdirectory=([^&]*)")
+
+    @property
+    def subdirectory_fragment(self) -> Optional[str]:
+        match = self._subdirectory_fragment_re.search(self._url)
+        if not match:
+            return None
+        return match.group(1)
+
+    def metadata_link(self) -> Optional["Link"]:
+        """Implementation of PEP 658 parsing."""
+        # Note that Link.from_element() parsing the "data-dist-info-metadata" attribute
+        # from an HTML anchor tag is typically how the Link.dist_info_metadata attribute
+        # gets set.
+        if self.dist_info_metadata is None:
+            return None
+        metadata_url = f"{self.url_without_fragment}.metadata"
+        # If data-dist-info-metadata="true" is set, then the metadata file exists,
+        # but there is no information about its checksum or anything else.
+        if self.dist_info_metadata != "true":
+            link_hash = LinkHash.split_hash_name_and_value(self.dist_info_metadata)
+        else:
+            link_hash = None
+        if link_hash is None:
+            return Link(metadata_url)
+        return Link(metadata_url, hashes=link_hash.as_dict())
+
+    def as_hashes(self) -> Hashes:
+        return Hashes({k: [v] for k, v in self._hashes.items()})
+
+    @property
+    def hash(self) -> Optional[str]:
+        return next(iter(self._hashes.values()), None)
+
+    @property
+    def hash_name(self) -> Optional[str]:
+        return next(iter(self._hashes), None)
+
+    @property
+    def show_url(self) -> str:
+        return posixpath.basename(self._url.split("#", 1)[0].split("?", 1)[0])
+
+    @property
+    def is_file(self) -> bool:
+        return self.scheme == "file"
+
+    def is_existing_dir(self) -> bool:
+        return self.is_file and os.path.isdir(self.file_path)
+
+    @property
+    def is_wheel(self) -> bool:
+        return self.ext == WHEEL_EXTENSION
+
+    @property
+    def is_vcs(self) -> bool:
+        from pip._internal.vcs import vcs
+
+        return self.scheme in vcs.all_schemes
+
+    @property
+    def is_yanked(self) -> bool:
+        return self.yanked_reason is not None
+
+    @property
+    def has_hash(self) -> bool:
+        return bool(self._hashes)
+
+    def is_hash_allowed(self, hashes: Optional[Hashes]) -> bool:
+        """
+        Return True if the link has a hash and it is allowed by `hashes`.
+        """
+        if hashes is None:
+            return False
+        return any(hashes.is_hash_allowed(k, v) for k, v in self._hashes.items())
+
+
+class _CleanResult(NamedTuple):
+    """Convert link for equivalency check.
+
+    This is used in the resolver to check whether two URL-specified requirements
+    likely point to the same distribution and can be considered equivalent. This
+    equivalency logic avoids comparing URLs literally, which can be too strict
+    (e.g. "a=1&b=2" vs "b=2&a=1") and produce conflicts unexpecting to users.
+
+    Currently this does three things:
+
+    1. Drop the basic auth part. This is technically wrong since a server can
+       serve different content based on auth, but if it does that, it is even
+       impossible to guarantee two URLs without auth are equivalent, since
+       the user can input different auth information when prompted. So the
+       practical solution is to assume the auth doesn't affect the response.
+    2. Parse the query to avoid the ordering issue. Note that ordering under the
+       same key in the query are NOT cleaned; i.e. "a=1&a=2" and "a=2&a=1" are
+       still considered different.
+    3. Explicitly drop most of the fragment part, except ``subdirectory=`` and
+       hash values, since it should have no impact the downloaded content. Note
+       that this drops the "egg=" part historically used to denote the requested
+       project (and extras), which is wrong in the strictest sense, but too many
+       people are supplying it inconsistently to cause superfluous resolution
+       conflicts, so we choose to also ignore them.
+    """
+
+    parsed: urllib.parse.SplitResult
+    query: Dict[str, List[str]]
+    subdirectory: str
+    hashes: Dict[str, str]
+
+
+def _clean_link(link: Link) -> _CleanResult:
+    parsed = link._parsed_url
+    netloc = parsed.netloc.rsplit("@", 1)[-1]
+    # According to RFC 8089, an empty host in file: means localhost.
+    if parsed.scheme == "file" and not netloc:
+        netloc = "localhost"
+    fragment = urllib.parse.parse_qs(parsed.fragment)
+    if "egg" in fragment:
+        logger.debug("Ignoring egg= fragment in %s", link)
+    try:
+        # If there are multiple subdirectory values, use the first one.
+        # This matches the behavior of Link.subdirectory_fragment.
+        subdirectory = fragment["subdirectory"][0]
+    except (IndexError, KeyError):
+        subdirectory = ""
+    # If there are multiple hash values under the same algorithm, use the
+    # first one. This matches the behavior of Link.hash_value.
+    hashes = {k: fragment[k][0] for k in _SUPPORTED_HASHES if k in fragment}
+    return _CleanResult(
+        parsed=parsed._replace(netloc=netloc, query="", fragment=""),
+        query=urllib.parse.parse_qs(parsed.query),
+        subdirectory=subdirectory,
+        hashes=hashes,
+    )
+
+
+@functools.lru_cache(maxsize=None)
+def links_equivalent(link1: Link, link2: Link) -> bool:
+    return _clean_link(link1) == _clean_link(link2)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/scheme.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/scheme.py
new file mode 100644
index 0000000000000000000000000000000000000000..f51190ac60354d90eb2aef4b04c484f8517275c2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/scheme.py
@@ -0,0 +1,31 @@
+"""
+For types associated with installation schemes.
+
+For a general overview of available schemes and their context, see
+https://docs.python.org/3/install/index.html#alternate-installation.
+"""
+
+
+SCHEME_KEYS = ["platlib", "purelib", "headers", "scripts", "data"]
+
+
+class Scheme:
+    """A Scheme holds paths which are used as the base directories for
+    artifacts associated with a Python package.
+    """
+
+    __slots__ = SCHEME_KEYS
+
+    def __init__(
+        self,
+        platlib: str,
+        purelib: str,
+        headers: str,
+        scripts: str,
+        data: str,
+    ) -> None:
+        self.platlib = platlib
+        self.purelib = purelib
+        self.headers = headers
+        self.scripts = scripts
+        self.data = data
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/search_scope.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/search_scope.py
new file mode 100644
index 0000000000000000000000000000000000000000..a64af73899de1a292ebadebb3cf4ad9bae27d6fc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/search_scope.py
@@ -0,0 +1,133 @@
+import itertools
+import logging
+import os
+import posixpath
+import urllib.parse
+from typing import List
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.models.index import PyPI
+from pip._internal.utils.compat import has_tls
+from pip._internal.utils.misc import normalize_path, redact_auth_from_url
+
+logger = logging.getLogger(__name__)
+
+
+class SearchScope:
+
+    """
+    Encapsulates the locations that pip is configured to search.
+    """
+
+    __slots__ = ["find_links", "index_urls", "no_index"]
+
+    @classmethod
+    def create(
+        cls,
+        find_links: List[str],
+        index_urls: List[str],
+        no_index: bool,
+    ) -> "SearchScope":
+        """
+        Create a SearchScope object after normalizing the `find_links`.
+        """
+        # Build find_links. If an argument starts with ~, it may be
+        # a local file relative to a home directory. So try normalizing
+        # it and if it exists, use the normalized version.
+        # This is deliberately conservative - it might be fine just to
+        # blindly normalize anything starting with a ~...
+        built_find_links: List[str] = []
+        for link in find_links:
+            if link.startswith("~"):
+                new_link = normalize_path(link)
+                if os.path.exists(new_link):
+                    link = new_link
+            built_find_links.append(link)
+
+        # If we don't have TLS enabled, then WARN if anyplace we're looking
+        # relies on TLS.
+        if not has_tls():
+            for link in itertools.chain(index_urls, built_find_links):
+                parsed = urllib.parse.urlparse(link)
+                if parsed.scheme == "https":
+                    logger.warning(
+                        "pip is configured with locations that require "
+                        "TLS/SSL, however the ssl module in Python is not "
+                        "available."
+                    )
+                    break
+
+        return cls(
+            find_links=built_find_links,
+            index_urls=index_urls,
+            no_index=no_index,
+        )
+
+    def __init__(
+        self,
+        find_links: List[str],
+        index_urls: List[str],
+        no_index: bool,
+    ) -> None:
+        self.find_links = find_links
+        self.index_urls = index_urls
+        self.no_index = no_index
+
+    def get_formatted_locations(self) -> str:
+        lines = []
+        redacted_index_urls = []
+        if self.index_urls and self.index_urls != [PyPI.simple_url]:
+            for url in self.index_urls:
+
+                redacted_index_url = redact_auth_from_url(url)
+
+                # Parse the URL
+                purl = urllib.parse.urlsplit(redacted_index_url)
+
+                # URL is generally invalid if scheme and netloc is missing
+                # there are issues with Python and URL parsing, so this test
+                # is a bit crude. See bpo-20271, bpo-23505. Python doesn't
+                # always parse invalid URLs correctly - it should raise
+                # exceptions for malformed URLs
+                if not purl.scheme and not purl.netloc:
+                    logger.warning(
+                        'The index url "%s" seems invalid, please provide a scheme.',
+                        redacted_index_url,
+                    )
+
+                redacted_index_urls.append(redacted_index_url)
+
+            lines.append(
+                "Looking in indexes: {}".format(", ".join(redacted_index_urls))
+            )
+
+        if self.find_links:
+            lines.append(
+                "Looking in links: {}".format(
+                    ", ".join(redact_auth_from_url(url) for url in self.find_links)
+                )
+            )
+        return "\n".join(lines)
+
+    def get_index_urls_locations(self, project_name: str) -> List[str]:
+        """Returns the locations found via self.index_urls
+
+        Checks the url_name on the main (first in the list) index and
+        use this url_name to produce all locations
+        """
+
+        def mkurl_pypi_url(url: str) -> str:
+            loc = posixpath.join(
+                url, urllib.parse.quote(canonicalize_name(project_name))
+            )
+            # For maximum compatibility with easy_install, ensure the path
+            # ends in a trailing slash.  Although this isn't in the spec
+            # (and PyPI can handle it without the slash) some other index
+            # implementations might break if they relied on easy_install's
+            # behavior.
+            if not loc.endswith("/"):
+                loc = loc + "/"
+            return loc
+
+        return [mkurl_pypi_url(url) for url in self.index_urls]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/selection_prefs.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/selection_prefs.py
new file mode 100644
index 0000000000000000000000000000000000000000..977bc4caa75c1e76156fa97e2841a01332f6fa47
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/selection_prefs.py
@@ -0,0 +1,51 @@
+from typing import Optional
+
+from pip._internal.models.format_control import FormatControl
+
+
+class SelectionPreferences:
+    """
+    Encapsulates the candidate selection preferences for downloading
+    and installing files.
+    """
+
+    __slots__ = [
+        "allow_yanked",
+        "allow_all_prereleases",
+        "format_control",
+        "prefer_binary",
+        "ignore_requires_python",
+    ]
+
+    # Don't include an allow_yanked default value to make sure each call
+    # site considers whether yanked releases are allowed. This also causes
+    # that decision to be made explicit in the calling code, which helps
+    # people when reading the code.
+    def __init__(
+        self,
+        allow_yanked: bool,
+        allow_all_prereleases: bool = False,
+        format_control: Optional[FormatControl] = None,
+        prefer_binary: bool = False,
+        ignore_requires_python: Optional[bool] = None,
+    ) -> None:
+        """Create a SelectionPreferences object.
+
+        :param allow_yanked: Whether files marked as yanked (in the sense
+            of PEP 592) are permitted to be candidates for install.
+        :param format_control: A FormatControl object or None. Used to control
+            the selection of source packages / binary packages when consulting
+            the index and links.
+        :param prefer_binary: Whether to prefer an old, but valid, binary
+            dist over a new source dist.
+        :param ignore_requires_python: Whether to ignore incompatible
+            "Requires-Python" values in links. Defaults to False.
+        """
+        if ignore_requires_python is None:
+            ignore_requires_python = False
+
+        self.allow_yanked = allow_yanked
+        self.allow_all_prereleases = allow_all_prereleases
+        self.format_control = format_control
+        self.prefer_binary = prefer_binary
+        self.ignore_requires_python = ignore_requires_python
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/target_python.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/target_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..744bd7ef58b4870406fcef8cb3b3667548a0ccea
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/target_python.py
@@ -0,0 +1,110 @@
+import sys
+from typing import List, Optional, Tuple
+
+from pip._vendor.packaging.tags import Tag
+
+from pip._internal.utils.compatibility_tags import get_supported, version_info_to_nodot
+from pip._internal.utils.misc import normalize_version_info
+
+
+class TargetPython:
+
+    """
+    Encapsulates the properties of a Python interpreter one is targeting
+    for a package install, download, etc.
+    """
+
+    __slots__ = [
+        "_given_py_version_info",
+        "abis",
+        "implementation",
+        "platforms",
+        "py_version",
+        "py_version_info",
+        "_valid_tags",
+    ]
+
+    def __init__(
+        self,
+        platforms: Optional[List[str]] = None,
+        py_version_info: Optional[Tuple[int, ...]] = None,
+        abis: Optional[List[str]] = None,
+        implementation: Optional[str] = None,
+    ) -> None:
+        """
+        :param platforms: A list of strings or None. If None, searches for
+            packages that are supported by the current system. Otherwise, will
+            find packages that can be built on the platforms passed in. These
+            packages will only be downloaded for distribution: they will
+            not be built locally.
+        :param py_version_info: An optional tuple of ints representing the
+            Python version information to use (e.g. `sys.version_info[:3]`).
+            This can have length 1, 2, or 3 when provided.
+        :param abis: A list of strings or None. This is passed to
+            compatibility_tags.py's get_supported() function as is.
+        :param implementation: A string or None. This is passed to
+            compatibility_tags.py's get_supported() function as is.
+        """
+        # Store the given py_version_info for when we call get_supported().
+        self._given_py_version_info = py_version_info
+
+        if py_version_info is None:
+            py_version_info = sys.version_info[:3]
+        else:
+            py_version_info = normalize_version_info(py_version_info)
+
+        py_version = ".".join(map(str, py_version_info[:2]))
+
+        self.abis = abis
+        self.implementation = implementation
+        self.platforms = platforms
+        self.py_version = py_version
+        self.py_version_info = py_version_info
+
+        # This is used to cache the return value of get_tags().
+        self._valid_tags: Optional[List[Tag]] = None
+
+    def format_given(self) -> str:
+        """
+        Format the given, non-None attributes for display.
+        """
+        display_version = None
+        if self._given_py_version_info is not None:
+            display_version = ".".join(
+                str(part) for part in self._given_py_version_info
+            )
+
+        key_values = [
+            ("platforms", self.platforms),
+            ("version_info", display_version),
+            ("abis", self.abis),
+            ("implementation", self.implementation),
+        ]
+        return " ".join(
+            f"{key}={value!r}" for key, value in key_values if value is not None
+        )
+
+    def get_tags(self) -> List[Tag]:
+        """
+        Return the supported PEP 425 tags to check wheel candidates against.
+
+        The tags are returned in order of preference (most preferred first).
+        """
+        if self._valid_tags is None:
+            # Pass versions=None if no py_version_info was given since
+            # versions=None uses special default logic.
+            py_version_info = self._given_py_version_info
+            if py_version_info is None:
+                version = None
+            else:
+                version = version_info_to_nodot(py_version_info)
+
+            tags = get_supported(
+                version=version,
+                platforms=self.platforms,
+                abis=self.abis,
+                impl=self.implementation,
+            )
+            self._valid_tags = tags
+
+        return self._valid_tags
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..a5dc12bdd63163c86f87ce4b5430cdb16d73769d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/models/wheel.py
@@ -0,0 +1,92 @@
+"""Represents a wheel file and provides access to the various parts of the
+name that have meaning.
+"""
+import re
+from typing import Dict, Iterable, List
+
+from pip._vendor.packaging.tags import Tag
+
+from pip._internal.exceptions import InvalidWheelFilename
+
+
+class Wheel:
+    """A wheel file"""
+
+    wheel_file_re = re.compile(
+        r"""^(?P(?P[^\s-]+?)-(?P[^\s-]*?))
+        ((-(?P\d[^-]*?))?-(?P[^\s-]+?)-(?P[^\s-]+?)-(?P[^\s-]+?)
+        \.whl|\.dist-info)$""",
+        re.VERBOSE,
+    )
+
+    def __init__(self, filename: str) -> None:
+        """
+        :raises InvalidWheelFilename: when the filename is invalid for a wheel
+        """
+        wheel_info = self.wheel_file_re.match(filename)
+        if not wheel_info:
+            raise InvalidWheelFilename(f"{filename} is not a valid wheel filename.")
+        self.filename = filename
+        self.name = wheel_info.group("name").replace("_", "-")
+        # we'll assume "_" means "-" due to wheel naming scheme
+        # (https://github.com/pypa/pip/issues/1150)
+        self.version = wheel_info.group("ver").replace("_", "-")
+        self.build_tag = wheel_info.group("build")
+        self.pyversions = wheel_info.group("pyver").split(".")
+        self.abis = wheel_info.group("abi").split(".")
+        self.plats = wheel_info.group("plat").split(".")
+
+        # All the tag combinations from this file
+        self.file_tags = {
+            Tag(x, y, z) for x in self.pyversions for y in self.abis for z in self.plats
+        }
+
+    def get_formatted_file_tags(self) -> List[str]:
+        """Return the wheel's tags as a sorted list of strings."""
+        return sorted(str(tag) for tag in self.file_tags)
+
+    def support_index_min(self, tags: List[Tag]) -> int:
+        """Return the lowest index that one of the wheel's file_tag combinations
+        achieves in the given list of supported tags.
+
+        For example, if there are 8 supported tags and one of the file tags
+        is first in the list, then return 0.
+
+        :param tags: the PEP 425 tags to check the wheel against, in order
+            with most preferred first.
+
+        :raises ValueError: If none of the wheel's file tags match one of
+            the supported tags.
+        """
+        try:
+            return next(i for i, t in enumerate(tags) if t in self.file_tags)
+        except StopIteration:
+            raise ValueError()
+
+    def find_most_preferred_tag(
+        self, tags: List[Tag], tag_to_priority: Dict[Tag, int]
+    ) -> int:
+        """Return the priority of the most preferred tag that one of the wheel's file
+        tag combinations achieves in the given list of supported tags using the given
+        tag_to_priority mapping, where lower priorities are more-preferred.
+
+        This is used in place of support_index_min in some cases in order to avoid
+        an expensive linear scan of a large list of tags.
+
+        :param tags: the PEP 425 tags to check the wheel against.
+        :param tag_to_priority: a mapping from tag to priority of that tag, where
+            lower is more preferred.
+
+        :raises ValueError: If none of the wheel's file tags match one of
+            the supported tags.
+        """
+        return min(
+            tag_to_priority[tag] for tag in self.file_tags if tag in tag_to_priority
+        )
+
+    def supported(self, tags: Iterable[Tag]) -> bool:
+        """Return whether the wheel is compatible with one of the given tags.
+
+        :param tags: the PEP 425 tags to check the wheel against.
+        """
+        return not self.file_tags.isdisjoint(tags)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..b51bde91b2e5b4e557ed9b70fc113843cc3d49ae
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/__init__.py
@@ -0,0 +1,2 @@
+"""Contains purely network-related utilities.
+"""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/auth.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/auth.py
new file mode 100644
index 0000000000000000000000000000000000000000..c16213268261544c04b31baa951da1917af4753b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/auth.py
@@ -0,0 +1,446 @@
+"""Network Authentication Helpers
+
+Contains interface (MultiDomainBasicAuth) and associated glue code for
+providing credentials in the context of network requests.
+"""
+
+import os
+import shutil
+import subprocess
+import urllib.parse
+from abc import ABC, abstractmethod
+from typing import Any, Dict, List, NamedTuple, Optional, Tuple
+
+from pip._vendor.requests.auth import AuthBase, HTTPBasicAuth
+from pip._vendor.requests.models import Request, Response
+from pip._vendor.requests.utils import get_netrc_auth
+
+from pip._internal.utils.logging import getLogger
+from pip._internal.utils.misc import (
+    ask,
+    ask_input,
+    ask_password,
+    remove_auth_from_url,
+    split_auth_netloc_from_url,
+)
+from pip._internal.vcs.versioncontrol import AuthInfo
+
+logger = getLogger(__name__)
+
+KEYRING_DISABLED = False
+
+
+class Credentials(NamedTuple):
+    url: str
+    username: str
+    password: str
+
+
+class KeyRingBaseProvider(ABC):
+    """Keyring base provider interface"""
+
+    @abstractmethod
+    def get_auth_info(self, url: str, username: Optional[str]) -> Optional[AuthInfo]:
+        ...
+
+    @abstractmethod
+    def save_auth_info(self, url: str, username: str, password: str) -> None:
+        ...
+
+
+class KeyRingNullProvider(KeyRingBaseProvider):
+    """Keyring null provider"""
+
+    def get_auth_info(self, url: str, username: Optional[str]) -> Optional[AuthInfo]:
+        return None
+
+    def save_auth_info(self, url: str, username: str, password: str) -> None:
+        return None
+
+
+class KeyRingPythonProvider(KeyRingBaseProvider):
+    """Keyring interface which uses locally imported `keyring`"""
+
+    def __init__(self) -> None:
+        import keyring
+
+        self.keyring = keyring
+
+    def get_auth_info(self, url: str, username: Optional[str]) -> Optional[AuthInfo]:
+        # Support keyring's get_credential interface which supports getting
+        # credentials without a username. This is only available for
+        # keyring>=15.2.0.
+        if hasattr(self.keyring, "get_credential"):
+            logger.debug("Getting credentials from keyring for %s", url)
+            cred = self.keyring.get_credential(url, username)
+            if cred is not None:
+                return cred.username, cred.password
+            return None
+
+        if username is not None:
+            logger.debug("Getting password from keyring for %s", url)
+            password = self.keyring.get_password(url, username)
+            if password:
+                return username, password
+        return None
+
+    def save_auth_info(self, url: str, username: str, password: str) -> None:
+        self.keyring.set_password(url, username, password)
+
+
+class KeyRingCliProvider(KeyRingBaseProvider):
+    """Provider which uses `keyring` cli
+
+    Instead of calling the keyring package installed alongside pip
+    we call keyring on the command line which will enable pip to
+    use which ever installation of keyring is available first in
+    PATH.
+    """
+
+    def __init__(self, cmd: str) -> None:
+        self.keyring = cmd
+
+    def get_auth_info(self, url: str, username: Optional[str]) -> Optional[AuthInfo]:
+        # This is the default implementation of keyring.get_credential
+        # https://github.com/jaraco/keyring/blob/97689324abcf01bd1793d49063e7ca01e03d7d07/keyring/backend.py#L134-L139
+        if username is not None:
+            password = self._get_password(url, username)
+            if password is not None:
+                return username, password
+        return None
+
+    def save_auth_info(self, url: str, username: str, password: str) -> None:
+        return self._set_password(url, username, password)
+
+    def _get_password(self, service_name: str, username: str) -> Optional[str]:
+        """Mirror the implementation of keyring.get_password using cli"""
+        if self.keyring is None:
+            return None
+
+        cmd = [self.keyring, "get", service_name, username]
+        env = os.environ.copy()
+        env["PYTHONIOENCODING"] = "utf-8"
+        res = subprocess.run(
+            cmd,
+            stdin=subprocess.DEVNULL,
+            capture_output=True,
+            env=env,
+        )
+        if res.returncode:
+            return None
+        return res.stdout.decode("utf-8").strip(os.linesep)
+
+    def _set_password(self, service_name: str, username: str, password: str) -> None:
+        """Mirror the implementation of keyring.set_password using cli"""
+        if self.keyring is None:
+            return None
+
+        cmd = [self.keyring, "set", service_name, username]
+        input_ = (password + os.linesep).encode("utf-8")
+        env = os.environ.copy()
+        env["PYTHONIOENCODING"] = "utf-8"
+        res = subprocess.run(cmd, input=input_, env=env)
+        res.check_returncode()
+        return None
+
+
+def get_keyring_provider() -> KeyRingBaseProvider:
+    # keyring has previously failed and been disabled
+    if not KEYRING_DISABLED:
+        # Default to trying to use Python provider
+        try:
+            return KeyRingPythonProvider()
+        except ImportError:
+            pass
+        except Exception as exc:
+            # In the event of an unexpected exception
+            # we should warn the user
+            logger.warning(
+                "Installed copy of keyring fails with exception %s, "
+                "trying to find a keyring executable as a fallback",
+                str(exc),
+            )
+
+        # Fallback to Cli Provider if `keyring` isn't installed
+        cli = shutil.which("keyring")
+        if cli:
+            return KeyRingCliProvider(cli)
+
+    return KeyRingNullProvider()
+
+
+def get_keyring_auth(url: Optional[str], username: Optional[str]) -> Optional[AuthInfo]:
+    """Return the tuple auth for a given url from keyring."""
+    # Do nothing if no url was provided
+    if not url:
+        return None
+
+    keyring = get_keyring_provider()
+    try:
+        return keyring.get_auth_info(url, username)
+    except Exception as exc:
+        logger.warning(
+            "Keyring is skipped due to an exception: %s",
+            str(exc),
+        )
+        global KEYRING_DISABLED
+        KEYRING_DISABLED = True
+        return None
+
+
+class MultiDomainBasicAuth(AuthBase):
+    def __init__(
+        self, prompting: bool = True, index_urls: Optional[List[str]] = None
+    ) -> None:
+        self.prompting = prompting
+        self.index_urls = index_urls
+        self.passwords: Dict[str, AuthInfo] = {}
+        # When the user is prompted to enter credentials and keyring is
+        # available, we will offer to save them. If the user accepts,
+        # this value is set to the credentials they entered. After the
+        # request authenticates, the caller should call
+        # ``save_credentials`` to save these.
+        self._credentials_to_save: Optional[Credentials] = None
+
+    def _get_index_url(self, url: str) -> Optional[str]:
+        """Return the original index URL matching the requested URL.
+
+        Cached or dynamically generated credentials may work against
+        the original index URL rather than just the netloc.
+
+        The provided url should have had its username and password
+        removed already. If the original index url had credentials then
+        they will be included in the return value.
+
+        Returns None if no matching index was found, or if --no-index
+        was specified by the user.
+        """
+        if not url or not self.index_urls:
+            return None
+
+        for u in self.index_urls:
+            prefix = remove_auth_from_url(u).rstrip("/") + "/"
+            if url.startswith(prefix):
+                return u
+        return None
+
+    def _get_new_credentials(
+        self,
+        original_url: str,
+        allow_netrc: bool = True,
+        allow_keyring: bool = False,
+    ) -> AuthInfo:
+        """Find and return credentials for the specified URL."""
+        # Split the credentials and netloc from the url.
+        url, netloc, url_user_password = split_auth_netloc_from_url(
+            original_url,
+        )
+
+        # Start with the credentials embedded in the url
+        username, password = url_user_password
+        if username is not None and password is not None:
+            logger.debug("Found credentials in url for %s", netloc)
+            return url_user_password
+
+        # Find a matching index url for this request
+        index_url = self._get_index_url(url)
+        if index_url:
+            # Split the credentials from the url.
+            index_info = split_auth_netloc_from_url(index_url)
+            if index_info:
+                index_url, _, index_url_user_password = index_info
+                logger.debug("Found index url %s", index_url)
+
+        # If an index URL was found, try its embedded credentials
+        if index_url and index_url_user_password[0] is not None:
+            username, password = index_url_user_password
+            if username is not None and password is not None:
+                logger.debug("Found credentials in index url for %s", netloc)
+                return index_url_user_password
+
+        # Get creds from netrc if we still don't have them
+        if allow_netrc:
+            netrc_auth = get_netrc_auth(original_url)
+            if netrc_auth:
+                logger.debug("Found credentials in netrc for %s", netloc)
+                return netrc_auth
+
+        # If we don't have a password and keyring is available, use it.
+        if allow_keyring:
+            # The index url is more specific than the netloc, so try it first
+            # fmt: off
+            kr_auth = (
+                get_keyring_auth(index_url, username) or
+                get_keyring_auth(netloc, username)
+            )
+            # fmt: on
+            if kr_auth:
+                logger.debug("Found credentials in keyring for %s", netloc)
+                return kr_auth
+
+        return username, password
+
+    def _get_url_and_credentials(
+        self, original_url: str
+    ) -> Tuple[str, Optional[str], Optional[str]]:
+        """Return the credentials to use for the provided URL.
+
+        If allowed, netrc and keyring may be used to obtain the
+        correct credentials.
+
+        Returns (url_without_credentials, username, password). Note
+        that even if the original URL contains credentials, this
+        function may return a different username and password.
+        """
+        url, netloc, _ = split_auth_netloc_from_url(original_url)
+
+        # Try to get credentials from original url
+        username, password = self._get_new_credentials(original_url)
+
+        # If credentials not found, use any stored credentials for this netloc.
+        # Do this if either the username or the password is missing.
+        # This accounts for the situation in which the user has specified
+        # the username in the index url, but the password comes from keyring.
+        if (username is None or password is None) and netloc in self.passwords:
+            un, pw = self.passwords[netloc]
+            # It is possible that the cached credentials are for a different username,
+            # in which case the cache should be ignored.
+            if username is None or username == un:
+                username, password = un, pw
+
+        if username is not None or password is not None:
+            # Convert the username and password if they're None, so that
+            # this netloc will show up as "cached" in the conditional above.
+            # Further, HTTPBasicAuth doesn't accept None, so it makes sense to
+            # cache the value that is going to be used.
+            username = username or ""
+            password = password or ""
+
+            # Store any acquired credentials.
+            self.passwords[netloc] = (username, password)
+
+        assert (
+            # Credentials were found
+            (username is not None and password is not None)
+            # Credentials were not found
+            or (username is None and password is None)
+        ), f"Could not load credentials from url: {original_url}"
+
+        return url, username, password
+
+    def __call__(self, req: Request) -> Request:
+        # Get credentials for this request
+        url, username, password = self._get_url_and_credentials(req.url)
+
+        # Set the url of the request to the url without any credentials
+        req.url = url
+
+        if username is not None and password is not None:
+            # Send the basic auth with this request
+            req = HTTPBasicAuth(username, password)(req)
+
+        # Attach a hook to handle 401 responses
+        req.register_hook("response", self.handle_401)
+
+        return req
+
+    # Factored out to allow for easy patching in tests
+    def _prompt_for_password(
+        self, netloc: str
+    ) -> Tuple[Optional[str], Optional[str], bool]:
+        username = ask_input(f"User for {netloc}: ")
+        if not username:
+            return None, None, False
+        auth = get_keyring_auth(netloc, username)
+        if auth and auth[0] is not None and auth[1] is not None:
+            return auth[0], auth[1], False
+        password = ask_password("Password: ")
+        return username, password, True
+
+    # Factored out to allow for easy patching in tests
+    def _should_save_password_to_keyring(self) -> bool:
+        if get_keyring_provider() is None:
+            return False
+        return ask("Save credentials to keyring [y/N]: ", ["y", "n"]) == "y"
+
+    def handle_401(self, resp: Response, **kwargs: Any) -> Response:
+        # We only care about 401 responses, anything else we want to just
+        #   pass through the actual response
+        if resp.status_code != 401:
+            return resp
+
+        # We are not able to prompt the user so simply return the response
+        if not self.prompting:
+            return resp
+
+        parsed = urllib.parse.urlparse(resp.url)
+
+        # Query the keyring for credentials:
+        username, password = self._get_new_credentials(
+            resp.url,
+            allow_netrc=False,
+            allow_keyring=True,
+        )
+
+        # Prompt the user for a new username and password
+        save = False
+        if not username and not password:
+            username, password, save = self._prompt_for_password(parsed.netloc)
+
+        # Store the new username and password to use for future requests
+        self._credentials_to_save = None
+        if username is not None and password is not None:
+            self.passwords[parsed.netloc] = (username, password)
+
+            # Prompt to save the password to keyring
+            if save and self._should_save_password_to_keyring():
+                self._credentials_to_save = Credentials(
+                    url=parsed.netloc,
+                    username=username,
+                    password=password,
+                )
+
+        # Consume content and release the original connection to allow our new
+        #   request to reuse the same one.
+        resp.content
+        resp.raw.release_conn()
+
+        # Add our new username and password to the request
+        req = HTTPBasicAuth(username or "", password or "")(resp.request)
+        req.register_hook("response", self.warn_on_401)
+
+        # On successful request, save the credentials that were used to
+        # keyring. (Note that if the user responded "no" above, this member
+        # is not set and nothing will be saved.)
+        if self._credentials_to_save:
+            req.register_hook("response", self.save_credentials)
+
+        # Send our new request
+        new_resp = resp.connection.send(req, **kwargs)
+        new_resp.history.append(resp)
+
+        return new_resp
+
+    def warn_on_401(self, resp: Response, **kwargs: Any) -> None:
+        """Response callback to warn about incorrect credentials."""
+        if resp.status_code == 401:
+            logger.warning(
+                "401 Error, Credentials not correct for %s",
+                resp.request.url,
+            )
+
+    def save_credentials(self, resp: Response, **kwargs: Any) -> None:
+        """Response callback to save credentials on success."""
+        keyring = get_keyring_provider()
+        assert not isinstance(
+            keyring, KeyRingNullProvider
+        ), "should never reach here without keyring"
+
+        creds = self._credentials_to_save
+        self._credentials_to_save = None
+        if creds and resp.status_code < 400:
+            try:
+                logger.info("Saving credentials to keyring")
+                keyring.save_auth_info(creds.url, creds.username, creds.password)
+            except Exception:
+                logger.exception("Failed to save credentials")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/cache.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..a81a23985198d2eaa3c25ad1f77924f0fcdb037b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/cache.py
@@ -0,0 +1,69 @@
+"""HTTP cache implementation.
+"""
+
+import os
+from contextlib import contextmanager
+from typing import Generator, Optional
+
+from pip._vendor.cachecontrol.cache import BaseCache
+from pip._vendor.cachecontrol.caches import FileCache
+from pip._vendor.requests.models import Response
+
+from pip._internal.utils.filesystem import adjacent_tmp_file, replace
+from pip._internal.utils.misc import ensure_dir
+
+
+def is_from_cache(response: Response) -> bool:
+    return getattr(response, "from_cache", False)
+
+
+@contextmanager
+def suppressed_cache_errors() -> Generator[None, None, None]:
+    """If we can't access the cache then we can just skip caching and process
+    requests as if caching wasn't enabled.
+    """
+    try:
+        yield
+    except OSError:
+        pass
+
+
+class SafeFileCache(BaseCache):
+    """
+    A file based cache which is safe to use even when the target directory may
+    not be accessible or writable.
+    """
+
+    def __init__(self, directory: str) -> None:
+        assert directory is not None, "Cache directory must not be None."
+        super().__init__()
+        self.directory = directory
+
+    def _get_cache_path(self, name: str) -> str:
+        # From cachecontrol.caches.file_cache.FileCache._fn, brought into our
+        # class for backwards-compatibility and to avoid using a non-public
+        # method.
+        hashed = FileCache.encode(name)
+        parts = list(hashed[:5]) + [hashed]
+        return os.path.join(self.directory, *parts)
+
+    def get(self, key: str) -> Optional[bytes]:
+        path = self._get_cache_path(key)
+        with suppressed_cache_errors():
+            with open(path, "rb") as f:
+                return f.read()
+
+    def set(self, key: str, value: bytes, expires: Optional[int] = None) -> None:
+        path = self._get_cache_path(key)
+        with suppressed_cache_errors():
+            ensure_dir(os.path.dirname(path))
+
+            with adjacent_tmp_file(path) as f:
+                f.write(value)
+
+            replace(f.name, path)
+
+    def delete(self, key: str) -> None:
+        path = self._get_cache_path(key)
+        with suppressed_cache_errors():
+            os.remove(path)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/download.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/download.py
new file mode 100644
index 0000000000000000000000000000000000000000..79b82a570e5be5ce4f8e4dcc4906da8c18f08ef6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/download.py
@@ -0,0 +1,186 @@
+"""Download files with progress indicators.
+"""
+import email.message
+import logging
+import mimetypes
+import os
+from typing import Iterable, Optional, Tuple
+
+from pip._vendor.requests.models import CONTENT_CHUNK_SIZE, Response
+
+from pip._internal.cli.progress_bars import get_download_progress_renderer
+from pip._internal.exceptions import NetworkConnectionError
+from pip._internal.models.index import PyPI
+from pip._internal.models.link import Link
+from pip._internal.network.cache import is_from_cache
+from pip._internal.network.session import PipSession
+from pip._internal.network.utils import HEADERS, raise_for_status, response_chunks
+from pip._internal.utils.misc import format_size, redact_auth_from_url, splitext
+
+logger = logging.getLogger(__name__)
+
+
+def _get_http_response_size(resp: Response) -> Optional[int]:
+    try:
+        return int(resp.headers["content-length"])
+    except (ValueError, KeyError, TypeError):
+        return None
+
+
+def _prepare_download(
+    resp: Response,
+    link: Link,
+    progress_bar: str,
+) -> Iterable[bytes]:
+    total_length = _get_http_response_size(resp)
+
+    if link.netloc == PyPI.file_storage_domain:
+        url = link.show_url
+    else:
+        url = link.url_without_fragment
+
+    logged_url = redact_auth_from_url(url)
+
+    if total_length:
+        logged_url = "{} ({})".format(logged_url, format_size(total_length))
+
+    if is_from_cache(resp):
+        logger.info("Using cached %s", logged_url)
+    else:
+        logger.info("Downloading %s", logged_url)
+
+    if logger.getEffectiveLevel() > logging.INFO:
+        show_progress = False
+    elif is_from_cache(resp):
+        show_progress = False
+    elif not total_length:
+        show_progress = True
+    elif total_length > (40 * 1000):
+        show_progress = True
+    else:
+        show_progress = False
+
+    chunks = response_chunks(resp, CONTENT_CHUNK_SIZE)
+
+    if not show_progress:
+        return chunks
+
+    renderer = get_download_progress_renderer(bar_type=progress_bar, size=total_length)
+    return renderer(chunks)
+
+
+def sanitize_content_filename(filename: str) -> str:
+    """
+    Sanitize the "filename" value from a Content-Disposition header.
+    """
+    return os.path.basename(filename)
+
+
+def parse_content_disposition(content_disposition: str, default_filename: str) -> str:
+    """
+    Parse the "filename" value from a Content-Disposition header, and
+    return the default filename if the result is empty.
+    """
+    m = email.message.Message()
+    m["content-type"] = content_disposition
+    filename = m.get_param("filename")
+    if filename:
+        # We need to sanitize the filename to prevent directory traversal
+        # in case the filename contains ".." path parts.
+        filename = sanitize_content_filename(str(filename))
+    return filename or default_filename
+
+
+def _get_http_response_filename(resp: Response, link: Link) -> str:
+    """Get an ideal filename from the given HTTP response, falling back to
+    the link filename if not provided.
+    """
+    filename = link.filename  # fallback
+    # Have a look at the Content-Disposition header for a better guess
+    content_disposition = resp.headers.get("content-disposition")
+    if content_disposition:
+        filename = parse_content_disposition(content_disposition, filename)
+    ext: Optional[str] = splitext(filename)[1]
+    if not ext:
+        ext = mimetypes.guess_extension(resp.headers.get("content-type", ""))
+        if ext:
+            filename += ext
+    if not ext and link.url != resp.url:
+        ext = os.path.splitext(resp.url)[1]
+        if ext:
+            filename += ext
+    return filename
+
+
+def _http_get_download(session: PipSession, link: Link) -> Response:
+    target_url = link.url.split("#", 1)[0]
+    resp = session.get(target_url, headers=HEADERS, stream=True)
+    raise_for_status(resp)
+    return resp
+
+
+class Downloader:
+    def __init__(
+        self,
+        session: PipSession,
+        progress_bar: str,
+    ) -> None:
+        self._session = session
+        self._progress_bar = progress_bar
+
+    def __call__(self, link: Link, location: str) -> Tuple[str, str]:
+        """Download the file given by link into location."""
+        try:
+            resp = _http_get_download(self._session, link)
+        except NetworkConnectionError as e:
+            assert e.response is not None
+            logger.critical(
+                "HTTP error %s while getting %s", e.response.status_code, link
+            )
+            raise
+
+        filename = _get_http_response_filename(resp, link)
+        filepath = os.path.join(location, filename)
+
+        chunks = _prepare_download(resp, link, self._progress_bar)
+        with open(filepath, "wb") as content_file:
+            for chunk in chunks:
+                content_file.write(chunk)
+        content_type = resp.headers.get("Content-Type", "")
+        return filepath, content_type
+
+
+class BatchDownloader:
+    def __init__(
+        self,
+        session: PipSession,
+        progress_bar: str,
+    ) -> None:
+        self._session = session
+        self._progress_bar = progress_bar
+
+    def __call__(
+        self, links: Iterable[Link], location: str
+    ) -> Iterable[Tuple[Link, Tuple[str, str]]]:
+        """Download the files given by links into location."""
+        for link in links:
+            try:
+                resp = _http_get_download(self._session, link)
+            except NetworkConnectionError as e:
+                assert e.response is not None
+                logger.critical(
+                    "HTTP error %s while getting %s",
+                    e.response.status_code,
+                    link,
+                )
+                raise
+
+            filename = _get_http_response_filename(resp, link)
+            filepath = os.path.join(location, filename)
+
+            chunks = _prepare_download(resp, link, self._progress_bar)
+            with open(filepath, "wb") as content_file:
+                for chunk in chunks:
+                    content_file.write(chunk)
+            content_type = resp.headers.get("Content-Type", "")
+            yield link, (filepath, content_type)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/lazy_wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/lazy_wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..854a6fa1fdc818061f47d55faa5c78b7b26eac45
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/lazy_wheel.py
@@ -0,0 +1,210 @@
+"""Lazy ZIP over HTTP"""
+
+__all__ = ["HTTPRangeRequestUnsupported", "dist_from_wheel_url"]
+
+from bisect import bisect_left, bisect_right
+from contextlib import contextmanager
+from tempfile import NamedTemporaryFile
+from typing import Any, Dict, Generator, List, Optional, Tuple
+from zipfile import BadZipfile, ZipFile
+
+from pip._vendor.packaging.utils import canonicalize_name
+from pip._vendor.requests.models import CONTENT_CHUNK_SIZE, Response
+
+from pip._internal.metadata import BaseDistribution, MemoryWheel, get_wheel_distribution
+from pip._internal.network.session import PipSession
+from pip._internal.network.utils import HEADERS, raise_for_status, response_chunks
+
+
+class HTTPRangeRequestUnsupported(Exception):
+    pass
+
+
+def dist_from_wheel_url(name: str, url: str, session: PipSession) -> BaseDistribution:
+    """Return a distribution object from the given wheel URL.
+
+    This uses HTTP range requests to only fetch the portion of the wheel
+    containing metadata, just enough for the object to be constructed.
+    If such requests are not supported, HTTPRangeRequestUnsupported
+    is raised.
+    """
+    with LazyZipOverHTTP(url, session) as zf:
+        # For read-only ZIP files, ZipFile only needs methods read,
+        # seek, seekable and tell, not the whole IO protocol.
+        wheel = MemoryWheel(zf.name, zf)  # type: ignore
+        # After context manager exit, wheel.name
+        # is an invalid file by intention.
+        return get_wheel_distribution(wheel, canonicalize_name(name))
+
+
+class LazyZipOverHTTP:
+    """File-like object mapped to a ZIP file over HTTP.
+
+    This uses HTTP range requests to lazily fetch the file's content,
+    which is supposed to be fed to ZipFile.  If such requests are not
+    supported by the server, raise HTTPRangeRequestUnsupported
+    during initialization.
+    """
+
+    def __init__(
+        self, url: str, session: PipSession, chunk_size: int = CONTENT_CHUNK_SIZE
+    ) -> None:
+        head = session.head(url, headers=HEADERS)
+        raise_for_status(head)
+        assert head.status_code == 200
+        self._session, self._url, self._chunk_size = session, url, chunk_size
+        self._length = int(head.headers["Content-Length"])
+        self._file = NamedTemporaryFile()
+        self.truncate(self._length)
+        self._left: List[int] = []
+        self._right: List[int] = []
+        if "bytes" not in head.headers.get("Accept-Ranges", "none"):
+            raise HTTPRangeRequestUnsupported("range request is not supported")
+        self._check_zip()
+
+    @property
+    def mode(self) -> str:
+        """Opening mode, which is always rb."""
+        return "rb"
+
+    @property
+    def name(self) -> str:
+        """Path to the underlying file."""
+        return self._file.name
+
+    def seekable(self) -> bool:
+        """Return whether random access is supported, which is True."""
+        return True
+
+    def close(self) -> None:
+        """Close the file."""
+        self._file.close()
+
+    @property
+    def closed(self) -> bool:
+        """Whether the file is closed."""
+        return self._file.closed
+
+    def read(self, size: int = -1) -> bytes:
+        """Read up to size bytes from the object and return them.
+
+        As a convenience, if size is unspecified or -1,
+        all bytes until EOF are returned.  Fewer than
+        size bytes may be returned if EOF is reached.
+        """
+        download_size = max(size, self._chunk_size)
+        start, length = self.tell(), self._length
+        stop = length if size < 0 else min(start + download_size, length)
+        start = max(0, stop - download_size)
+        self._download(start, stop - 1)
+        return self._file.read(size)
+
+    def readable(self) -> bool:
+        """Return whether the file is readable, which is True."""
+        return True
+
+    def seek(self, offset: int, whence: int = 0) -> int:
+        """Change stream position and return the new absolute position.
+
+        Seek to offset relative position indicated by whence:
+        * 0: Start of stream (the default).  pos should be >= 0;
+        * 1: Current position - pos may be negative;
+        * 2: End of stream - pos usually negative.
+        """
+        return self._file.seek(offset, whence)
+
+    def tell(self) -> int:
+        """Return the current position."""
+        return self._file.tell()
+
+    def truncate(self, size: Optional[int] = None) -> int:
+        """Resize the stream to the given size in bytes.
+
+        If size is unspecified resize to the current position.
+        The current stream position isn't changed.
+
+        Return the new file size.
+        """
+        return self._file.truncate(size)
+
+    def writable(self) -> bool:
+        """Return False."""
+        return False
+
+    def __enter__(self) -> "LazyZipOverHTTP":
+        self._file.__enter__()
+        return self
+
+    def __exit__(self, *exc: Any) -> None:
+        self._file.__exit__(*exc)
+
+    @contextmanager
+    def _stay(self) -> Generator[None, None, None]:
+        """Return a context manager keeping the position.
+
+        At the end of the block, seek back to original position.
+        """
+        pos = self.tell()
+        try:
+            yield
+        finally:
+            self.seek(pos)
+
+    def _check_zip(self) -> None:
+        """Check and download until the file is a valid ZIP."""
+        end = self._length - 1
+        for start in reversed(range(0, end, self._chunk_size)):
+            self._download(start, end)
+            with self._stay():
+                try:
+                    # For read-only ZIP files, ZipFile only needs
+                    # methods read, seek, seekable and tell.
+                    ZipFile(self)  # type: ignore
+                except BadZipfile:
+                    pass
+                else:
+                    break
+
+    def _stream_response(
+        self, start: int, end: int, base_headers: Dict[str, str] = HEADERS
+    ) -> Response:
+        """Return HTTP response to a range request from start to end."""
+        headers = base_headers.copy()
+        headers["Range"] = f"bytes={start}-{end}"
+        # TODO: Get range requests to be correctly cached
+        headers["Cache-Control"] = "no-cache"
+        return self._session.get(self._url, headers=headers, stream=True)
+
+    def _merge(
+        self, start: int, end: int, left: int, right: int
+    ) -> Generator[Tuple[int, int], None, None]:
+        """Return a generator of intervals to be fetched.
+
+        Args:
+            start (int): Start of needed interval
+            end (int): End of needed interval
+            left (int): Index of first overlapping downloaded data
+            right (int): Index after last overlapping downloaded data
+        """
+        lslice, rslice = self._left[left:right], self._right[left:right]
+        i = start = min([start] + lslice[:1])
+        end = max([end] + rslice[-1:])
+        for j, k in zip(lslice, rslice):
+            if j > i:
+                yield i, j - 1
+            i = k + 1
+        if i <= end:
+            yield i, end
+        self._left[left:right], self._right[left:right] = [start], [end]
+
+    def _download(self, start: int, end: int) -> None:
+        """Download bytes from start to end inclusively."""
+        with self._stay():
+            left = bisect_left(self._right, start)
+            right = bisect_right(self._left, end)
+            for start, end in self._merge(start, end, left, right):
+                response = self._stream_response(start, end)
+                response.raise_for_status()
+                self.seek(start)
+                for chunk in response_chunks(response, self._chunk_size):
+                    self._file.write(chunk)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/session.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/session.py
new file mode 100644
index 0000000000000000000000000000000000000000..e512ac784649b9dd8845e24e4d17f9e13f6591b0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/session.py
@@ -0,0 +1,518 @@
+"""PipSession and supporting code, containing all pip-specific
+network request configuration and behavior.
+"""
+
+import email.utils
+import io
+import ipaddress
+import json
+import logging
+import mimetypes
+import os
+import platform
+import shutil
+import subprocess
+import sys
+import urllib.parse
+import warnings
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Dict,
+    Generator,
+    List,
+    Mapping,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+)
+
+from pip._vendor import requests, urllib3
+from pip._vendor.cachecontrol import CacheControlAdapter as _BaseCacheControlAdapter
+from pip._vendor.requests.adapters import DEFAULT_POOLBLOCK, BaseAdapter
+from pip._vendor.requests.adapters import HTTPAdapter as _BaseHTTPAdapter
+from pip._vendor.requests.models import PreparedRequest, Response
+from pip._vendor.requests.structures import CaseInsensitiveDict
+from pip._vendor.urllib3.connectionpool import ConnectionPool
+from pip._vendor.urllib3.exceptions import InsecureRequestWarning
+
+from pip import __version__
+from pip._internal.metadata import get_default_environment
+from pip._internal.models.link import Link
+from pip._internal.network.auth import MultiDomainBasicAuth
+from pip._internal.network.cache import SafeFileCache
+
+# Import ssl from compat so the initial import occurs in only one place.
+from pip._internal.utils.compat import has_tls
+from pip._internal.utils.glibc import libc_ver
+from pip._internal.utils.misc import build_url_from_netloc, parse_netloc
+from pip._internal.utils.urls import url_to_path
+
+if TYPE_CHECKING:
+    from ssl import SSLContext
+
+    from pip._vendor.urllib3.poolmanager import PoolManager
+
+
+logger = logging.getLogger(__name__)
+
+SecureOrigin = Tuple[str, str, Optional[Union[int, str]]]
+
+
+# Ignore warning raised when using --trusted-host.
+warnings.filterwarnings("ignore", category=InsecureRequestWarning)
+
+
+SECURE_ORIGINS: List[SecureOrigin] = [
+    # protocol, hostname, port
+    # Taken from Chrome's list of secure origins (See: http://bit.ly/1qrySKC)
+    ("https", "*", "*"),
+    ("*", "localhost", "*"),
+    ("*", "127.0.0.0/8", "*"),
+    ("*", "::1/128", "*"),
+    ("file", "*", None),
+    # ssh is always secure.
+    ("ssh", "*", "*"),
+]
+
+
+# These are environment variables present when running under various
+# CI systems.  For each variable, some CI systems that use the variable
+# are indicated.  The collection was chosen so that for each of a number
+# of popular systems, at least one of the environment variables is used.
+# This list is used to provide some indication of and lower bound for
+# CI traffic to PyPI.  Thus, it is okay if the list is not comprehensive.
+# For more background, see: https://github.com/pypa/pip/issues/5499
+CI_ENVIRONMENT_VARIABLES = (
+    # Azure Pipelines
+    "BUILD_BUILDID",
+    # Jenkins
+    "BUILD_ID",
+    # AppVeyor, CircleCI, Codeship, Gitlab CI, Shippable, Travis CI
+    "CI",
+    # Explicit environment variable.
+    "PIP_IS_CI",
+)
+
+
+def looks_like_ci() -> bool:
+    """
+    Return whether it looks like pip is running under CI.
+    """
+    # We don't use the method of checking for a tty (e.g. using isatty())
+    # because some CI systems mimic a tty (e.g. Travis CI).  Thus that
+    # method doesn't provide definitive information in either direction.
+    return any(name in os.environ for name in CI_ENVIRONMENT_VARIABLES)
+
+
+def user_agent() -> str:
+    """
+    Return a string representing the user agent.
+    """
+    data: Dict[str, Any] = {
+        "installer": {"name": "pip", "version": __version__},
+        "python": platform.python_version(),
+        "implementation": {
+            "name": platform.python_implementation(),
+        },
+    }
+
+    if data["implementation"]["name"] == "CPython":
+        data["implementation"]["version"] = platform.python_version()
+    elif data["implementation"]["name"] == "PyPy":
+        pypy_version_info = sys.pypy_version_info  # type: ignore
+        if pypy_version_info.releaselevel == "final":
+            pypy_version_info = pypy_version_info[:3]
+        data["implementation"]["version"] = ".".join(
+            [str(x) for x in pypy_version_info]
+        )
+    elif data["implementation"]["name"] == "Jython":
+        # Complete Guess
+        data["implementation"]["version"] = platform.python_version()
+    elif data["implementation"]["name"] == "IronPython":
+        # Complete Guess
+        data["implementation"]["version"] = platform.python_version()
+
+    if sys.platform.startswith("linux"):
+        from pip._vendor import distro
+
+        linux_distribution = distro.name(), distro.version(), distro.codename()
+        distro_infos: Dict[str, Any] = dict(
+            filter(
+                lambda x: x[1],
+                zip(["name", "version", "id"], linux_distribution),
+            )
+        )
+        libc = dict(
+            filter(
+                lambda x: x[1],
+                zip(["lib", "version"], libc_ver()),
+            )
+        )
+        if libc:
+            distro_infos["libc"] = libc
+        if distro_infos:
+            data["distro"] = distro_infos
+
+    if sys.platform.startswith("darwin") and platform.mac_ver()[0]:
+        data["distro"] = {"name": "macOS", "version": platform.mac_ver()[0]}
+
+    if platform.system():
+        data.setdefault("system", {})["name"] = platform.system()
+
+    if platform.release():
+        data.setdefault("system", {})["release"] = platform.release()
+
+    if platform.machine():
+        data["cpu"] = platform.machine()
+
+    if has_tls():
+        import _ssl as ssl
+
+        data["openssl_version"] = ssl.OPENSSL_VERSION
+
+    setuptools_dist = get_default_environment().get_distribution("setuptools")
+    if setuptools_dist is not None:
+        data["setuptools_version"] = str(setuptools_dist.version)
+
+    if shutil.which("rustc") is not None:
+        # If for any reason `rustc --version` fails, silently ignore it
+        try:
+            rustc_output = subprocess.check_output(
+                ["rustc", "--version"], stderr=subprocess.STDOUT, timeout=0.5
+            )
+        except Exception:
+            pass
+        else:
+            if rustc_output.startswith(b"rustc "):
+                # The format of `rustc --version` is:
+                # `b'rustc 1.52.1 (9bc8c42bb 2021-05-09)\n'`
+                # We extract just the middle (1.52.1) part
+                data["rustc_version"] = rustc_output.split(b" ")[1].decode()
+
+    # Use None rather than False so as not to give the impression that
+    # pip knows it is not being run under CI.  Rather, it is a null or
+    # inconclusive result.  Also, we include some value rather than no
+    # value to make it easier to know that the check has been run.
+    data["ci"] = True if looks_like_ci() else None
+
+    user_data = os.environ.get("PIP_USER_AGENT_USER_DATA")
+    if user_data is not None:
+        data["user_data"] = user_data
+
+    return "{data[installer][name]}/{data[installer][version]} {json}".format(
+        data=data,
+        json=json.dumps(data, separators=(",", ":"), sort_keys=True),
+    )
+
+
+class LocalFSAdapter(BaseAdapter):
+    def send(
+        self,
+        request: PreparedRequest,
+        stream: bool = False,
+        timeout: Optional[Union[float, Tuple[float, float]]] = None,
+        verify: Union[bool, str] = True,
+        cert: Optional[Union[str, Tuple[str, str]]] = None,
+        proxies: Optional[Mapping[str, str]] = None,
+    ) -> Response:
+        pathname = url_to_path(request.url)
+
+        resp = Response()
+        resp.status_code = 200
+        resp.url = request.url
+
+        try:
+            stats = os.stat(pathname)
+        except OSError as exc:
+            # format the exception raised as a io.BytesIO object,
+            # to return a better error message:
+            resp.status_code = 404
+            resp.reason = type(exc).__name__
+            resp.raw = io.BytesIO(f"{resp.reason}: {exc}".encode("utf8"))
+        else:
+            modified = email.utils.formatdate(stats.st_mtime, usegmt=True)
+            content_type = mimetypes.guess_type(pathname)[0] or "text/plain"
+            resp.headers = CaseInsensitiveDict(
+                {
+                    "Content-Type": content_type,
+                    "Content-Length": stats.st_size,
+                    "Last-Modified": modified,
+                }
+            )
+
+            resp.raw = open(pathname, "rb")
+            resp.close = resp.raw.close
+
+        return resp
+
+    def close(self) -> None:
+        pass
+
+
+class _SSLContextAdapterMixin:
+    """Mixin to add the ``ssl_context`` constructor argument to HTTP adapters.
+
+    The additional argument is forwarded directly to the pool manager. This allows us
+    to dynamically decide what SSL store to use at runtime, which is used to implement
+    the optional ``truststore`` backend.
+    """
+
+    def __init__(
+        self,
+        *,
+        ssl_context: Optional["SSLContext"] = None,
+        **kwargs: Any,
+    ) -> None:
+        self._ssl_context = ssl_context
+        super().__init__(**kwargs)
+
+    def init_poolmanager(
+        self,
+        connections: int,
+        maxsize: int,
+        block: bool = DEFAULT_POOLBLOCK,
+        **pool_kwargs: Any,
+    ) -> "PoolManager":
+        if self._ssl_context is not None:
+            pool_kwargs.setdefault("ssl_context", self._ssl_context)
+        return super().init_poolmanager(  # type: ignore[misc]
+            connections=connections,
+            maxsize=maxsize,
+            block=block,
+            **pool_kwargs,
+        )
+
+
+class HTTPAdapter(_SSLContextAdapterMixin, _BaseHTTPAdapter):
+    pass
+
+
+class CacheControlAdapter(_SSLContextAdapterMixin, _BaseCacheControlAdapter):
+    pass
+
+
+class InsecureHTTPAdapter(HTTPAdapter):
+    def cert_verify(
+        self,
+        conn: ConnectionPool,
+        url: str,
+        verify: Union[bool, str],
+        cert: Optional[Union[str, Tuple[str, str]]],
+    ) -> None:
+        super().cert_verify(conn=conn, url=url, verify=False, cert=cert)
+
+
+class InsecureCacheControlAdapter(CacheControlAdapter):
+    def cert_verify(
+        self,
+        conn: ConnectionPool,
+        url: str,
+        verify: Union[bool, str],
+        cert: Optional[Union[str, Tuple[str, str]]],
+    ) -> None:
+        super().cert_verify(conn=conn, url=url, verify=False, cert=cert)
+
+
+class PipSession(requests.Session):
+
+    timeout: Optional[int] = None
+
+    def __init__(
+        self,
+        *args: Any,
+        retries: int = 0,
+        cache: Optional[str] = None,
+        trusted_hosts: Sequence[str] = (),
+        index_urls: Optional[List[str]] = None,
+        ssl_context: Optional["SSLContext"] = None,
+        **kwargs: Any,
+    ) -> None:
+        """
+        :param trusted_hosts: Domains not to emit warnings for when not using
+            HTTPS.
+        """
+        super().__init__(*args, **kwargs)
+
+        # Namespace the attribute with "pip_" just in case to prevent
+        # possible conflicts with the base class.
+        self.pip_trusted_origins: List[Tuple[str, Optional[int]]] = []
+
+        # Attach our User Agent to the request
+        self.headers["User-Agent"] = user_agent()
+
+        # Attach our Authentication handler to the session
+        self.auth = MultiDomainBasicAuth(index_urls=index_urls)
+
+        # Create our urllib3.Retry instance which will allow us to customize
+        # how we handle retries.
+        retries = urllib3.Retry(
+            # Set the total number of retries that a particular request can
+            # have.
+            total=retries,
+            # A 503 error from PyPI typically means that the Fastly -> Origin
+            # connection got interrupted in some way. A 503 error in general
+            # is typically considered a transient error so we'll go ahead and
+            # retry it.
+            # A 500 may indicate transient error in Amazon S3
+            # A 520 or 527 - may indicate transient error in CloudFlare
+            status_forcelist=[500, 503, 520, 527],
+            # Add a small amount of back off between failed requests in
+            # order to prevent hammering the service.
+            backoff_factor=0.25,
+        )  # type: ignore
+
+        # Our Insecure HTTPAdapter disables HTTPS validation. It does not
+        # support caching so we'll use it for all http:// URLs.
+        # If caching is disabled, we will also use it for
+        # https:// hosts that we've marked as ignoring
+        # TLS errors for (trusted-hosts).
+        insecure_adapter = InsecureHTTPAdapter(max_retries=retries)
+
+        # We want to _only_ cache responses on securely fetched origins or when
+        # the host is specified as trusted. We do this because
+        # we can't validate the response of an insecurely/untrusted fetched
+        # origin, and we don't want someone to be able to poison the cache and
+        # require manual eviction from the cache to fix it.
+        if cache:
+            secure_adapter = CacheControlAdapter(
+                cache=SafeFileCache(cache),
+                max_retries=retries,
+                ssl_context=ssl_context,
+            )
+            self._trusted_host_adapter = InsecureCacheControlAdapter(
+                cache=SafeFileCache(cache),
+                max_retries=retries,
+            )
+        else:
+            secure_adapter = HTTPAdapter(max_retries=retries, ssl_context=ssl_context)
+            self._trusted_host_adapter = insecure_adapter
+
+        self.mount("https://", secure_adapter)
+        self.mount("http://", insecure_adapter)
+
+        # Enable file:// urls
+        self.mount("file://", LocalFSAdapter())
+
+        for host in trusted_hosts:
+            self.add_trusted_host(host, suppress_logging=True)
+
+    def update_index_urls(self, new_index_urls: List[str]) -> None:
+        """
+        :param new_index_urls: New index urls to update the authentication
+            handler with.
+        """
+        self.auth.index_urls = new_index_urls
+
+    def add_trusted_host(
+        self, host: str, source: Optional[str] = None, suppress_logging: bool = False
+    ) -> None:
+        """
+        :param host: It is okay to provide a host that has previously been
+            added.
+        :param source: An optional source string, for logging where the host
+            string came from.
+        """
+        if not suppress_logging:
+            msg = f"adding trusted host: {host!r}"
+            if source is not None:
+                msg += f" (from {source})"
+            logger.info(msg)
+
+        host_port = parse_netloc(host)
+        if host_port not in self.pip_trusted_origins:
+            self.pip_trusted_origins.append(host_port)
+
+        self.mount(
+            build_url_from_netloc(host, scheme="http") + "/", self._trusted_host_adapter
+        )
+        self.mount(build_url_from_netloc(host) + "/", self._trusted_host_adapter)
+        if not host_port[1]:
+            self.mount(
+                build_url_from_netloc(host, scheme="http") + ":",
+                self._trusted_host_adapter,
+            )
+            # Mount wildcard ports for the same host.
+            self.mount(build_url_from_netloc(host) + ":", self._trusted_host_adapter)
+
+    def iter_secure_origins(self) -> Generator[SecureOrigin, None, None]:
+        yield from SECURE_ORIGINS
+        for host, port in self.pip_trusted_origins:
+            yield ("*", host, "*" if port is None else port)
+
+    def is_secure_origin(self, location: Link) -> bool:
+        # Determine if this url used a secure transport mechanism
+        parsed = urllib.parse.urlparse(str(location))
+        origin_protocol, origin_host, origin_port = (
+            parsed.scheme,
+            parsed.hostname,
+            parsed.port,
+        )
+
+        # The protocol to use to see if the protocol matches.
+        # Don't count the repository type as part of the protocol: in
+        # cases such as "git+ssh", only use "ssh". (I.e., Only verify against
+        # the last scheme.)
+        origin_protocol = origin_protocol.rsplit("+", 1)[-1]
+
+        # Determine if our origin is a secure origin by looking through our
+        # hardcoded list of secure origins, as well as any additional ones
+        # configured on this PackageFinder instance.
+        for secure_origin in self.iter_secure_origins():
+            secure_protocol, secure_host, secure_port = secure_origin
+            if origin_protocol != secure_protocol and secure_protocol != "*":
+                continue
+
+            try:
+                addr = ipaddress.ip_address(origin_host or "")
+                network = ipaddress.ip_network(secure_host)
+            except ValueError:
+                # We don't have both a valid address or a valid network, so
+                # we'll check this origin against hostnames.
+                if (
+                    origin_host
+                    and origin_host.lower() != secure_host.lower()
+                    and secure_host != "*"
+                ):
+                    continue
+            else:
+                # We have a valid address and network, so see if the address
+                # is contained within the network.
+                if addr not in network:
+                    continue
+
+            # Check to see if the port matches.
+            if (
+                origin_port != secure_port
+                and secure_port != "*"
+                and secure_port is not None
+            ):
+                continue
+
+            # If we've gotten here, then this origin matches the current
+            # secure origin and we should return True
+            return True
+
+        # If we've gotten to this point, then the origin isn't secure and we
+        # will not accept it as a valid location to search. We will however
+        # log a warning that we are ignoring it.
+        logger.warning(
+            "The repository located at %s is not a trusted or secure host and "
+            "is being ignored. If this repository is available via HTTPS we "
+            "recommend you use HTTPS instead, otherwise you may silence "
+            "this warning and allow it anyway with '--trusted-host %s'.",
+            origin_host,
+            origin_host,
+        )
+
+        return False
+
+    def request(self, method: str, url: str, *args: Any, **kwargs: Any) -> Response:
+        # Allow setting a default timeout on a session
+        kwargs.setdefault("timeout", self.timeout)
+        # Allow setting a default proxies on a session
+        kwargs.setdefault("proxies", self.proxies)
+
+        # Dispatch the actual request
+        return super().request(method, url, *args, **kwargs)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..134848ae526e54e2b18738f83088c4a17efcce96
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/utils.py
@@ -0,0 +1,96 @@
+from typing import Dict, Generator
+
+from pip._vendor.requests.models import CONTENT_CHUNK_SIZE, Response
+
+from pip._internal.exceptions import NetworkConnectionError
+
+# The following comments and HTTP headers were originally added by
+# Donald Stufft in git commit 22c562429a61bb77172039e480873fb239dd8c03.
+#
+# We use Accept-Encoding: identity here because requests defaults to
+# accepting compressed responses. This breaks in a variety of ways
+# depending on how the server is configured.
+# - Some servers will notice that the file isn't a compressible file
+#   and will leave the file alone and with an empty Content-Encoding
+# - Some servers will notice that the file is already compressed and
+#   will leave the file alone, adding a Content-Encoding: gzip header
+# - Some servers won't notice anything at all and will take a file
+#   that's already been compressed and compress it again, and set
+#   the Content-Encoding: gzip header
+# By setting this to request only the identity encoding we're hoping
+# to eliminate the third case.  Hopefully there does not exist a server
+# which when given a file will notice it is already compressed and that
+# you're not asking for a compressed file and will then decompress it
+# before sending because if that's the case I don't think it'll ever be
+# possible to make this work.
+HEADERS: Dict[str, str] = {"Accept-Encoding": "identity"}
+
+
+def raise_for_status(resp: Response) -> None:
+    http_error_msg = ""
+    if isinstance(resp.reason, bytes):
+        # We attempt to decode utf-8 first because some servers
+        # choose to localize their reason strings. If the string
+        # isn't utf-8, we fall back to iso-8859-1 for all other
+        # encodings.
+        try:
+            reason = resp.reason.decode("utf-8")
+        except UnicodeDecodeError:
+            reason = resp.reason.decode("iso-8859-1")
+    else:
+        reason = resp.reason
+
+    if 400 <= resp.status_code < 500:
+        http_error_msg = (
+            f"{resp.status_code} Client Error: {reason} for url: {resp.url}"
+        )
+
+    elif 500 <= resp.status_code < 600:
+        http_error_msg = (
+            f"{resp.status_code} Server Error: {reason} for url: {resp.url}"
+        )
+
+    if http_error_msg:
+        raise NetworkConnectionError(http_error_msg, response=resp)
+
+
+def response_chunks(
+    response: Response, chunk_size: int = CONTENT_CHUNK_SIZE
+) -> Generator[bytes, None, None]:
+    """Given a requests Response, provide the data chunks."""
+    try:
+        # Special case for urllib3.
+        for chunk in response.raw.stream(
+            chunk_size,
+            # We use decode_content=False here because we don't
+            # want urllib3 to mess with the raw bytes we get
+            # from the server. If we decompress inside of
+            # urllib3 then we cannot verify the checksum
+            # because the checksum will be of the compressed
+            # file. This breakage will only occur if the
+            # server adds a Content-Encoding header, which
+            # depends on how the server was configured:
+            # - Some servers will notice that the file isn't a
+            #   compressible file and will leave the file alone
+            #   and with an empty Content-Encoding
+            # - Some servers will notice that the file is
+            #   already compressed and will leave the file
+            #   alone and will add a Content-Encoding: gzip
+            #   header
+            # - Some servers won't notice anything at all and
+            #   will take a file that's already been compressed
+            #   and compress it again and set the
+            #   Content-Encoding: gzip header
+            #
+            # By setting this not to decode automatically we
+            # hope to eliminate problems with the second case.
+            decode_content=False,
+        ):
+            yield chunk
+    except AttributeError:
+        # Standard file-like object.
+        while True:
+            chunk = response.raw.read(chunk_size)
+            if not chunk:
+                break
+            yield chunk
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/xmlrpc.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/xmlrpc.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a7d55d0e50cb8b892caa021695522e5ddd54a17
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/network/xmlrpc.py
@@ -0,0 +1,60 @@
+"""xmlrpclib.Transport implementation
+"""
+
+import logging
+import urllib.parse
+import xmlrpc.client
+from typing import TYPE_CHECKING, Tuple
+
+from pip._internal.exceptions import NetworkConnectionError
+from pip._internal.network.session import PipSession
+from pip._internal.network.utils import raise_for_status
+
+if TYPE_CHECKING:
+    from xmlrpc.client import _HostType, _Marshallable
+
+logger = logging.getLogger(__name__)
+
+
+class PipXmlrpcTransport(xmlrpc.client.Transport):
+    """Provide a `xmlrpclib.Transport` implementation via a `PipSession`
+    object.
+    """
+
+    def __init__(
+        self, index_url: str, session: PipSession, use_datetime: bool = False
+    ) -> None:
+        super().__init__(use_datetime)
+        index_parts = urllib.parse.urlparse(index_url)
+        self._scheme = index_parts.scheme
+        self._session = session
+
+    def request(
+        self,
+        host: "_HostType",
+        handler: str,
+        request_body: bytes,
+        verbose: bool = False,
+    ) -> Tuple["_Marshallable", ...]:
+        assert isinstance(host, str)
+        parts = (self._scheme, host, handler, None, None, None)
+        url = urllib.parse.urlunparse(parts)
+        try:
+            headers = {"Content-Type": "text/xml"}
+            response = self._session.post(
+                url,
+                data=request_body,
+                headers=headers,
+                stream=True,
+            )
+            raise_for_status(response)
+            self.verbose = verbose
+            return self.parse_response(response.raw)
+        except NetworkConnectionError as exc:
+            assert exc.response
+            logger.critical(
+                "HTTP error %s while getting %s",
+                exc.response.status_code,
+                url,
+            )
+            raise
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/build_tracker.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/build_tracker.py
new file mode 100644
index 0000000000000000000000000000000000000000..6621549b8449130d2d01ebac0a3649d8b70c4f91
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/build_tracker.py
@@ -0,0 +1,124 @@
+import contextlib
+import hashlib
+import logging
+import os
+from types import TracebackType
+from typing import Dict, Generator, Optional, Set, Type, Union
+
+from pip._internal.models.link import Link
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.utils.temp_dir import TempDirectory
+
+logger = logging.getLogger(__name__)
+
+
+@contextlib.contextmanager
+def update_env_context_manager(**changes: str) -> Generator[None, None, None]:
+    target = os.environ
+
+    # Save values from the target and change them.
+    non_existent_marker = object()
+    saved_values: Dict[str, Union[object, str]] = {}
+    for name, new_value in changes.items():
+        try:
+            saved_values[name] = target[name]
+        except KeyError:
+            saved_values[name] = non_existent_marker
+        target[name] = new_value
+
+    try:
+        yield
+    finally:
+        # Restore original values in the target.
+        for name, original_value in saved_values.items():
+            if original_value is non_existent_marker:
+                del target[name]
+            else:
+                assert isinstance(original_value, str)  # for mypy
+                target[name] = original_value
+
+
+@contextlib.contextmanager
+def get_build_tracker() -> Generator["BuildTracker", None, None]:
+    root = os.environ.get("PIP_BUILD_TRACKER")
+    with contextlib.ExitStack() as ctx:
+        if root is None:
+            root = ctx.enter_context(TempDirectory(kind="build-tracker")).path
+            ctx.enter_context(update_env_context_manager(PIP_BUILD_TRACKER=root))
+            logger.debug("Initialized build tracking at %s", root)
+
+        with BuildTracker(root) as tracker:
+            yield tracker
+
+
+class BuildTracker:
+    def __init__(self, root: str) -> None:
+        self._root = root
+        self._entries: Set[InstallRequirement] = set()
+        logger.debug("Created build tracker: %s", self._root)
+
+    def __enter__(self) -> "BuildTracker":
+        logger.debug("Entered build tracker: %s", self._root)
+        return self
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> None:
+        self.cleanup()
+
+    def _entry_path(self, link: Link) -> str:
+        hashed = hashlib.sha224(link.url_without_fragment.encode()).hexdigest()
+        return os.path.join(self._root, hashed)
+
+    def add(self, req: InstallRequirement) -> None:
+        """Add an InstallRequirement to build tracking."""
+
+        assert req.link
+        # Get the file to write information about this requirement.
+        entry_path = self._entry_path(req.link)
+
+        # Try reading from the file. If it exists and can be read from, a build
+        # is already in progress, so a LookupError is raised.
+        try:
+            with open(entry_path) as fp:
+                contents = fp.read()
+        except FileNotFoundError:
+            pass
+        else:
+            message = "{} is already being built: {}".format(req.link, contents)
+            raise LookupError(message)
+
+        # If we're here, req should really not be building already.
+        assert req not in self._entries
+
+        # Start tracking this requirement.
+        with open(entry_path, "w", encoding="utf-8") as fp:
+            fp.write(str(req))
+        self._entries.add(req)
+
+        logger.debug("Added %s to build tracker %r", req, self._root)
+
+    def remove(self, req: InstallRequirement) -> None:
+        """Remove an InstallRequirement from build tracking."""
+
+        assert req.link
+        # Delete the created file and the corresponding entries.
+        os.unlink(self._entry_path(req.link))
+        self._entries.remove(req)
+
+        logger.debug("Removed %s from build tracker %r", req, self._root)
+
+    def cleanup(self) -> None:
+        for req in set(self._entries):
+            self.remove(req)
+
+        logger.debug("Removed build tracker: %r", self._root)
+
+    @contextlib.contextmanager
+    def track(self, req: InstallRequirement) -> Generator[None, None, None]:
+        self.add(req)
+        yield
+        self.remove(req)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata.py
new file mode 100644
index 0000000000000000000000000000000000000000..c66ac354deb035405fe0e4040dac539d28570257
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata.py
@@ -0,0 +1,39 @@
+"""Metadata generation logic for source distributions.
+"""
+
+import os
+
+from pip._vendor.pyproject_hooks import BuildBackendHookCaller
+
+from pip._internal.build_env import BuildEnvironment
+from pip._internal.exceptions import (
+    InstallationSubprocessError,
+    MetadataGenerationFailed,
+)
+from pip._internal.utils.subprocess import runner_with_spinner_message
+from pip._internal.utils.temp_dir import TempDirectory
+
+
+def generate_metadata(
+    build_env: BuildEnvironment, backend: BuildBackendHookCaller, details: str
+) -> str:
+    """Generate metadata using mechanisms described in PEP 517.
+
+    Returns the generated metadata directory.
+    """
+    metadata_tmpdir = TempDirectory(kind="modern-metadata", globally_managed=True)
+
+    metadata_dir = metadata_tmpdir.path
+
+    with build_env:
+        # Note that BuildBackendHookCaller implements a fallback for
+        # prepare_metadata_for_build_wheel, so we don't have to
+        # consider the possibility that this hook doesn't exist.
+        runner = runner_with_spinner_message("Preparing metadata (pyproject.toml)")
+        with backend.subprocess_runner(runner):
+            try:
+                distinfo_dir = backend.prepare_metadata_for_build_wheel(metadata_dir)
+            except InstallationSubprocessError as error:
+                raise MetadataGenerationFailed(package_details=details) from error
+
+    return os.path.join(metadata_dir, distinfo_dir)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata_editable.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata_editable.py
new file mode 100644
index 0000000000000000000000000000000000000000..27c69f0d1eaf3e223d599e91f969d52a821426fe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata_editable.py
@@ -0,0 +1,41 @@
+"""Metadata generation logic for source distributions.
+"""
+
+import os
+
+from pip._vendor.pyproject_hooks import BuildBackendHookCaller
+
+from pip._internal.build_env import BuildEnvironment
+from pip._internal.exceptions import (
+    InstallationSubprocessError,
+    MetadataGenerationFailed,
+)
+from pip._internal.utils.subprocess import runner_with_spinner_message
+from pip._internal.utils.temp_dir import TempDirectory
+
+
+def generate_editable_metadata(
+    build_env: BuildEnvironment, backend: BuildBackendHookCaller, details: str
+) -> str:
+    """Generate metadata using mechanisms described in PEP 660.
+
+    Returns the generated metadata directory.
+    """
+    metadata_tmpdir = TempDirectory(kind="modern-metadata", globally_managed=True)
+
+    metadata_dir = metadata_tmpdir.path
+
+    with build_env:
+        # Note that BuildBackendHookCaller implements a fallback for
+        # prepare_metadata_for_build_wheel/editable, so we don't have to
+        # consider the possibility that this hook doesn't exist.
+        runner = runner_with_spinner_message(
+            "Preparing editable metadata (pyproject.toml)"
+        )
+        with backend.subprocess_runner(runner):
+            try:
+                distinfo_dir = backend.prepare_metadata_for_build_editable(metadata_dir)
+            except InstallationSubprocessError as error:
+                raise MetadataGenerationFailed(package_details=details) from error
+
+    return os.path.join(metadata_dir, distinfo_dir)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata_legacy.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata_legacy.py
new file mode 100644
index 0000000000000000000000000000000000000000..e60988d643e007801f79e8718354e7d00c7acf18
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/metadata_legacy.py
@@ -0,0 +1,74 @@
+"""Metadata generation logic for legacy source distributions.
+"""
+
+import logging
+import os
+
+from pip._internal.build_env import BuildEnvironment
+from pip._internal.cli.spinners import open_spinner
+from pip._internal.exceptions import (
+    InstallationError,
+    InstallationSubprocessError,
+    MetadataGenerationFailed,
+)
+from pip._internal.utils.setuptools_build import make_setuptools_egg_info_args
+from pip._internal.utils.subprocess import call_subprocess
+from pip._internal.utils.temp_dir import TempDirectory
+
+logger = logging.getLogger(__name__)
+
+
+def _find_egg_info(directory: str) -> str:
+    """Find an .egg-info subdirectory in `directory`."""
+    filenames = [f for f in os.listdir(directory) if f.endswith(".egg-info")]
+
+    if not filenames:
+        raise InstallationError(f"No .egg-info directory found in {directory}")
+
+    if len(filenames) > 1:
+        raise InstallationError(
+            "More than one .egg-info directory found in {}".format(directory)
+        )
+
+    return os.path.join(directory, filenames[0])
+
+
+def generate_metadata(
+    build_env: BuildEnvironment,
+    setup_py_path: str,
+    source_dir: str,
+    isolated: bool,
+    details: str,
+) -> str:
+    """Generate metadata using setup.py-based defacto mechanisms.
+
+    Returns the generated metadata directory.
+    """
+    logger.debug(
+        "Running setup.py (path:%s) egg_info for package %s",
+        setup_py_path,
+        details,
+    )
+
+    egg_info_dir = TempDirectory(kind="pip-egg-info", globally_managed=True).path
+
+    args = make_setuptools_egg_info_args(
+        setup_py_path,
+        egg_info_dir=egg_info_dir,
+        no_user_config=isolated,
+    )
+
+    with build_env:
+        with open_spinner("Preparing metadata (setup.py)") as spinner:
+            try:
+                call_subprocess(
+                    args,
+                    cwd=source_dir,
+                    command_desc="python setup.py egg_info",
+                    spinner=spinner,
+                )
+            except InstallationSubprocessError as error:
+                raise MetadataGenerationFailed(package_details=details) from error
+
+    # Return the .egg-info directory.
+    return _find_egg_info(egg_info_dir)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..064811ad11bb07b2b7bc8e30ec6c03f21997d6b2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel.py
@@ -0,0 +1,37 @@
+import logging
+import os
+from typing import Optional
+
+from pip._vendor.pyproject_hooks import BuildBackendHookCaller
+
+from pip._internal.utils.subprocess import runner_with_spinner_message
+
+logger = logging.getLogger(__name__)
+
+
+def build_wheel_pep517(
+    name: str,
+    backend: BuildBackendHookCaller,
+    metadata_directory: str,
+    tempd: str,
+) -> Optional[str]:
+    """Build one InstallRequirement using the PEP 517 build process.
+
+    Returns path to wheel if successfully built. Otherwise, returns None.
+    """
+    assert metadata_directory is not None
+    try:
+        logger.debug("Destination directory: %s", tempd)
+
+        runner = runner_with_spinner_message(
+            f"Building wheel for {name} (pyproject.toml)"
+        )
+        with backend.subprocess_runner(runner):
+            wheel_name = backend.build_wheel(
+                tempd,
+                metadata_directory=metadata_directory,
+            )
+    except Exception:
+        logger.error("Failed building wheel for %s", name)
+        return None
+    return os.path.join(tempd, wheel_name)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel_editable.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel_editable.py
new file mode 100644
index 0000000000000000000000000000000000000000..719d69dd801b78b360c6c2234080eee638b8de82
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel_editable.py
@@ -0,0 +1,46 @@
+import logging
+import os
+from typing import Optional
+
+from pip._vendor.pyproject_hooks import BuildBackendHookCaller, HookMissing
+
+from pip._internal.utils.subprocess import runner_with_spinner_message
+
+logger = logging.getLogger(__name__)
+
+
+def build_wheel_editable(
+    name: str,
+    backend: BuildBackendHookCaller,
+    metadata_directory: str,
+    tempd: str,
+) -> Optional[str]:
+    """Build one InstallRequirement using the PEP 660 build process.
+
+    Returns path to wheel if successfully built. Otherwise, returns None.
+    """
+    assert metadata_directory is not None
+    try:
+        logger.debug("Destination directory: %s", tempd)
+
+        runner = runner_with_spinner_message(
+            f"Building editable for {name} (pyproject.toml)"
+        )
+        with backend.subprocess_runner(runner):
+            try:
+                wheel_name = backend.build_editable(
+                    tempd,
+                    metadata_directory=metadata_directory,
+                )
+            except HookMissing as e:
+                logger.error(
+                    "Cannot build editable %s because the build "
+                    "backend does not have the %s hook",
+                    name,
+                    e,
+                )
+                return None
+    except Exception:
+        logger.error("Failed building editable for %s", name)
+        return None
+    return os.path.join(tempd, wheel_name)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel_legacy.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel_legacy.py
new file mode 100644
index 0000000000000000000000000000000000000000..c5f0492ccbe9c727c835c12c84a1d8340366fa1e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/build/wheel_legacy.py
@@ -0,0 +1,102 @@
+import logging
+import os.path
+from typing import List, Optional
+
+from pip._internal.cli.spinners import open_spinner
+from pip._internal.utils.setuptools_build import make_setuptools_bdist_wheel_args
+from pip._internal.utils.subprocess import call_subprocess, format_command_args
+
+logger = logging.getLogger(__name__)
+
+
+def format_command_result(
+    command_args: List[str],
+    command_output: str,
+) -> str:
+    """Format command information for logging."""
+    command_desc = format_command_args(command_args)
+    text = f"Command arguments: {command_desc}\n"
+
+    if not command_output:
+        text += "Command output: None"
+    elif logger.getEffectiveLevel() > logging.DEBUG:
+        text += "Command output: [use --verbose to show]"
+    else:
+        if not command_output.endswith("\n"):
+            command_output += "\n"
+        text += f"Command output:\n{command_output}"
+
+    return text
+
+
+def get_legacy_build_wheel_path(
+    names: List[str],
+    temp_dir: str,
+    name: str,
+    command_args: List[str],
+    command_output: str,
+) -> Optional[str]:
+    """Return the path to the wheel in the temporary build directory."""
+    # Sort for determinism.
+    names = sorted(names)
+    if not names:
+        msg = ("Legacy build of wheel for {!r} created no files.\n").format(name)
+        msg += format_command_result(command_args, command_output)
+        logger.warning(msg)
+        return None
+
+    if len(names) > 1:
+        msg = (
+            "Legacy build of wheel for {!r} created more than one file.\n"
+            "Filenames (choosing first): {}\n"
+        ).format(name, names)
+        msg += format_command_result(command_args, command_output)
+        logger.warning(msg)
+
+    return os.path.join(temp_dir, names[0])
+
+
+def build_wheel_legacy(
+    name: str,
+    setup_py_path: str,
+    source_dir: str,
+    global_options: List[str],
+    build_options: List[str],
+    tempd: str,
+) -> Optional[str]:
+    """Build one unpacked package using the "legacy" build process.
+
+    Returns path to wheel if successfully built. Otherwise, returns None.
+    """
+    wheel_args = make_setuptools_bdist_wheel_args(
+        setup_py_path,
+        global_options=global_options,
+        build_options=build_options,
+        destination_dir=tempd,
+    )
+
+    spin_message = f"Building wheel for {name} (setup.py)"
+    with open_spinner(spin_message) as spinner:
+        logger.debug("Destination directory: %s", tempd)
+
+        try:
+            output = call_subprocess(
+                wheel_args,
+                command_desc="python setup.py bdist_wheel",
+                cwd=source_dir,
+                spinner=spinner,
+            )
+        except Exception:
+            spinner.finish("error")
+            logger.error("Failed building wheel for %s", name)
+            return None
+
+        names = os.listdir(tempd)
+        wheel_path = get_legacy_build_wheel_path(
+            names=names,
+            temp_dir=tempd,
+            name=name,
+            command_args=wheel_args,
+            command_output=output,
+        )
+        return wheel_path
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/check.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/check.py
new file mode 100644
index 0000000000000000000000000000000000000000..e3bce69b204f80ccc706050a1fa5f10362fbc76f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/check.py
@@ -0,0 +1,149 @@
+"""Validation of dependencies of packages
+"""
+
+import logging
+from typing import Callable, Dict, List, NamedTuple, Optional, Set, Tuple
+
+from pip._vendor.packaging.requirements import Requirement
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+
+from pip._internal.distributions import make_distribution_for_install_requirement
+from pip._internal.metadata import get_default_environment
+from pip._internal.metadata.base import DistributionVersion
+from pip._internal.req.req_install import InstallRequirement
+
+logger = logging.getLogger(__name__)
+
+
+class PackageDetails(NamedTuple):
+    version: DistributionVersion
+    dependencies: List[Requirement]
+
+
+# Shorthands
+PackageSet = Dict[NormalizedName, PackageDetails]
+Missing = Tuple[NormalizedName, Requirement]
+Conflicting = Tuple[NormalizedName, DistributionVersion, Requirement]
+
+MissingDict = Dict[NormalizedName, List[Missing]]
+ConflictingDict = Dict[NormalizedName, List[Conflicting]]
+CheckResult = Tuple[MissingDict, ConflictingDict]
+ConflictDetails = Tuple[PackageSet, CheckResult]
+
+
+def create_package_set_from_installed() -> Tuple[PackageSet, bool]:
+    """Converts a list of distributions into a PackageSet."""
+    package_set = {}
+    problems = False
+    env = get_default_environment()
+    for dist in env.iter_installed_distributions(local_only=False, skip=()):
+        name = dist.canonical_name
+        try:
+            dependencies = list(dist.iter_dependencies())
+            package_set[name] = PackageDetails(dist.version, dependencies)
+        except (OSError, ValueError) as e:
+            # Don't crash on unreadable or broken metadata.
+            logger.warning("Error parsing requirements for %s: %s", name, e)
+            problems = True
+    return package_set, problems
+
+
+def check_package_set(
+    package_set: PackageSet, should_ignore: Optional[Callable[[str], bool]] = None
+) -> CheckResult:
+    """Check if a package set is consistent
+
+    If should_ignore is passed, it should be a callable that takes a
+    package name and returns a boolean.
+    """
+
+    missing = {}
+    conflicting = {}
+
+    for package_name, package_detail in package_set.items():
+        # Info about dependencies of package_name
+        missing_deps: Set[Missing] = set()
+        conflicting_deps: Set[Conflicting] = set()
+
+        if should_ignore and should_ignore(package_name):
+            continue
+
+        for req in package_detail.dependencies:
+            name = canonicalize_name(req.name)
+
+            # Check if it's missing
+            if name not in package_set:
+                missed = True
+                if req.marker is not None:
+                    missed = req.marker.evaluate({"extra": ""})
+                if missed:
+                    missing_deps.add((name, req))
+                continue
+
+            # Check if there's a conflict
+            version = package_set[name].version
+            if not req.specifier.contains(version, prereleases=True):
+                conflicting_deps.add((name, version, req))
+
+        if missing_deps:
+            missing[package_name] = sorted(missing_deps, key=str)
+        if conflicting_deps:
+            conflicting[package_name] = sorted(conflicting_deps, key=str)
+
+    return missing, conflicting
+
+
+def check_install_conflicts(to_install: List[InstallRequirement]) -> ConflictDetails:
+    """For checking if the dependency graph would be consistent after \
+    installing given requirements
+    """
+    # Start from the current state
+    package_set, _ = create_package_set_from_installed()
+    # Install packages
+    would_be_installed = _simulate_installation_of(to_install, package_set)
+
+    # Only warn about directly-dependent packages; create a whitelist of them
+    whitelist = _create_whitelist(would_be_installed, package_set)
+
+    return (
+        package_set,
+        check_package_set(
+            package_set, should_ignore=lambda name: name not in whitelist
+        ),
+    )
+
+
+def _simulate_installation_of(
+    to_install: List[InstallRequirement], package_set: PackageSet
+) -> Set[NormalizedName]:
+    """Computes the version of packages after installing to_install."""
+    # Keep track of packages that were installed
+    installed = set()
+
+    # Modify it as installing requirement_set would (assuming no errors)
+    for inst_req in to_install:
+        abstract_dist = make_distribution_for_install_requirement(inst_req)
+        dist = abstract_dist.get_metadata_distribution()
+        name = dist.canonical_name
+        package_set[name] = PackageDetails(dist.version, list(dist.iter_dependencies()))
+
+        installed.add(name)
+
+    return installed
+
+
+def _create_whitelist(
+    would_be_installed: Set[NormalizedName], package_set: PackageSet
+) -> Set[NormalizedName]:
+    packages_affected = set(would_be_installed)
+
+    for package_name in package_set:
+        if package_name in packages_affected:
+            continue
+
+        for req in package_set[package_name].dependencies:
+            if canonicalize_name(req.name) in packages_affected:
+                packages_affected.add(package_name)
+                break
+
+    return packages_affected
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/freeze.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/freeze.py
new file mode 100644
index 0000000000000000000000000000000000000000..930d4c6005ea87c498711bd8facfc4981bfed3fe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/freeze.py
@@ -0,0 +1,254 @@
+import collections
+import logging
+import os
+from typing import Container, Dict, Generator, Iterable, List, NamedTuple, Optional, Set
+
+from pip._vendor.packaging.utils import canonicalize_name
+from pip._vendor.packaging.version import Version
+
+from pip._internal.exceptions import BadCommand, InstallationError
+from pip._internal.metadata import BaseDistribution, get_environment
+from pip._internal.req.constructors import (
+    install_req_from_editable,
+    install_req_from_line,
+)
+from pip._internal.req.req_file import COMMENT_RE
+from pip._internal.utils.direct_url_helpers import direct_url_as_pep440_direct_reference
+
+logger = logging.getLogger(__name__)
+
+
+class _EditableInfo(NamedTuple):
+    requirement: str
+    comments: List[str]
+
+
+def freeze(
+    requirement: Optional[List[str]] = None,
+    local_only: bool = False,
+    user_only: bool = False,
+    paths: Optional[List[str]] = None,
+    isolated: bool = False,
+    exclude_editable: bool = False,
+    skip: Container[str] = (),
+) -> Generator[str, None, None]:
+    installations: Dict[str, FrozenRequirement] = {}
+
+    dists = get_environment(paths).iter_installed_distributions(
+        local_only=local_only,
+        skip=(),
+        user_only=user_only,
+    )
+    for dist in dists:
+        req = FrozenRequirement.from_dist(dist)
+        if exclude_editable and req.editable:
+            continue
+        installations[req.canonical_name] = req
+
+    if requirement:
+        # the options that don't get turned into an InstallRequirement
+        # should only be emitted once, even if the same option is in multiple
+        # requirements files, so we need to keep track of what has been emitted
+        # so that we don't emit it again if it's seen again
+        emitted_options: Set[str] = set()
+        # keep track of which files a requirement is in so that we can
+        # give an accurate warning if a requirement appears multiple times.
+        req_files: Dict[str, List[str]] = collections.defaultdict(list)
+        for req_file_path in requirement:
+            with open(req_file_path) as req_file:
+                for line in req_file:
+                    if (
+                        not line.strip()
+                        or line.strip().startswith("#")
+                        or line.startswith(
+                            (
+                                "-r",
+                                "--requirement",
+                                "-f",
+                                "--find-links",
+                                "-i",
+                                "--index-url",
+                                "--pre",
+                                "--trusted-host",
+                                "--process-dependency-links",
+                                "--extra-index-url",
+                                "--use-feature",
+                            )
+                        )
+                    ):
+                        line = line.rstrip()
+                        if line not in emitted_options:
+                            emitted_options.add(line)
+                            yield line
+                        continue
+
+                    if line.startswith("-e") or line.startswith("--editable"):
+                        if line.startswith("-e"):
+                            line = line[2:].strip()
+                        else:
+                            line = line[len("--editable") :].strip().lstrip("=")
+                        line_req = install_req_from_editable(
+                            line,
+                            isolated=isolated,
+                        )
+                    else:
+                        line_req = install_req_from_line(
+                            COMMENT_RE.sub("", line).strip(),
+                            isolated=isolated,
+                        )
+
+                    if not line_req.name:
+                        logger.info(
+                            "Skipping line in requirement file [%s] because "
+                            "it's not clear what it would install: %s",
+                            req_file_path,
+                            line.strip(),
+                        )
+                        logger.info(
+                            "  (add #egg=PackageName to the URL to avoid"
+                            " this warning)"
+                        )
+                    else:
+                        line_req_canonical_name = canonicalize_name(line_req.name)
+                        if line_req_canonical_name not in installations:
+                            # either it's not installed, or it is installed
+                            # but has been processed already
+                            if not req_files[line_req.name]:
+                                logger.warning(
+                                    "Requirement file [%s] contains %s, but "
+                                    "package %r is not installed",
+                                    req_file_path,
+                                    COMMENT_RE.sub("", line).strip(),
+                                    line_req.name,
+                                )
+                            else:
+                                req_files[line_req.name].append(req_file_path)
+                        else:
+                            yield str(installations[line_req_canonical_name]).rstrip()
+                            del installations[line_req_canonical_name]
+                            req_files[line_req.name].append(req_file_path)
+
+        # Warn about requirements that were included multiple times (in a
+        # single requirements file or in different requirements files).
+        for name, files in req_files.items():
+            if len(files) > 1:
+                logger.warning(
+                    "Requirement %s included multiple times [%s]",
+                    name,
+                    ", ".join(sorted(set(files))),
+                )
+
+        yield ("## The following requirements were added by pip freeze:")
+    for installation in sorted(installations.values(), key=lambda x: x.name.lower()):
+        if installation.canonical_name not in skip:
+            yield str(installation).rstrip()
+
+
+def _format_as_name_version(dist: BaseDistribution) -> str:
+    if isinstance(dist.version, Version):
+        return f"{dist.raw_name}=={dist.version}"
+    return f"{dist.raw_name}==={dist.version}"
+
+
+def _get_editable_info(dist: BaseDistribution) -> _EditableInfo:
+    """
+    Compute and return values (req, comments) for use in
+    FrozenRequirement.from_dist().
+    """
+    editable_project_location = dist.editable_project_location
+    assert editable_project_location
+    location = os.path.normcase(os.path.abspath(editable_project_location))
+
+    from pip._internal.vcs import RemoteNotFoundError, RemoteNotValidError, vcs
+
+    vcs_backend = vcs.get_backend_for_dir(location)
+
+    if vcs_backend is None:
+        display = _format_as_name_version(dist)
+        logger.debug(
+            'No VCS found for editable requirement "%s" in: %r',
+            display,
+            location,
+        )
+        return _EditableInfo(
+            requirement=location,
+            comments=[f"# Editable install with no version control ({display})"],
+        )
+
+    vcs_name = type(vcs_backend).__name__
+
+    try:
+        req = vcs_backend.get_src_requirement(location, dist.raw_name)
+    except RemoteNotFoundError:
+        display = _format_as_name_version(dist)
+        return _EditableInfo(
+            requirement=location,
+            comments=[f"# Editable {vcs_name} install with no remote ({display})"],
+        )
+    except RemoteNotValidError as ex:
+        display = _format_as_name_version(dist)
+        return _EditableInfo(
+            requirement=location,
+            comments=[
+                f"# Editable {vcs_name} install ({display}) with either a deleted "
+                f"local remote or invalid URI:",
+                f"# '{ex.url}'",
+            ],
+        )
+    except BadCommand:
+        logger.warning(
+            "cannot determine version of editable source in %s "
+            "(%s command not found in path)",
+            location,
+            vcs_backend.name,
+        )
+        return _EditableInfo(requirement=location, comments=[])
+    except InstallationError as exc:
+        logger.warning("Error when trying to get requirement for VCS system %s", exc)
+    else:
+        return _EditableInfo(requirement=req, comments=[])
+
+    logger.warning("Could not determine repository location of %s", location)
+
+    return _EditableInfo(
+        requirement=location,
+        comments=["## !! Could not determine repository location"],
+    )
+
+
+class FrozenRequirement:
+    def __init__(
+        self,
+        name: str,
+        req: str,
+        editable: bool,
+        comments: Iterable[str] = (),
+    ) -> None:
+        self.name = name
+        self.canonical_name = canonicalize_name(name)
+        self.req = req
+        self.editable = editable
+        self.comments = comments
+
+    @classmethod
+    def from_dist(cls, dist: BaseDistribution) -> "FrozenRequirement":
+        editable = dist.editable
+        if editable:
+            req, comments = _get_editable_info(dist)
+        else:
+            comments = []
+            direct_url = dist.direct_url
+            if direct_url:
+                # if PEP 610 metadata is present, use it
+                req = direct_url_as_pep440_direct_reference(direct_url, dist.raw_name)
+            else:
+                # name==version requirement
+                req = _format_as_name_version(dist)
+
+        return cls(dist.raw_name, req, editable, comments=comments)
+
+    def __str__(self) -> str:
+        req = self.req
+        if self.editable:
+            req = f"-e {req}"
+        return "\n".join(list(self.comments) + [str(req)]) + "\n"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..24d6a5dd31fe33b03f90ed0f9ee465253686900c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/__init__.py
@@ -0,0 +1,2 @@
+"""For modules related to installing packages.
+"""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/editable_legacy.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/editable_legacy.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb548cdca75a924bf090f2be29779e2be1951a2c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/editable_legacy.py
@@ -0,0 +1,47 @@
+"""Legacy editable installation process, i.e. `setup.py develop`.
+"""
+import logging
+from typing import List, Optional, Sequence
+
+from pip._internal.build_env import BuildEnvironment
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.setuptools_build import make_setuptools_develop_args
+from pip._internal.utils.subprocess import call_subprocess
+
+logger = logging.getLogger(__name__)
+
+
+def install_editable(
+    install_options: List[str],
+    global_options: Sequence[str],
+    prefix: Optional[str],
+    home: Optional[str],
+    use_user_site: bool,
+    name: str,
+    setup_py_path: str,
+    isolated: bool,
+    build_env: BuildEnvironment,
+    unpacked_source_directory: str,
+) -> None:
+    """Install a package in editable mode. Most arguments are pass-through
+    to setuptools.
+    """
+    logger.info("Running setup.py develop for %s", name)
+
+    args = make_setuptools_develop_args(
+        setup_py_path,
+        global_options=global_options,
+        install_options=install_options,
+        no_user_config=isolated,
+        prefix=prefix,
+        home=home,
+        use_user_site=use_user_site,
+    )
+
+    with indent_log():
+        with build_env:
+            call_subprocess(
+                args,
+                command_desc="python setup.py develop",
+                cwd=unpacked_source_directory,
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/legacy.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/legacy.py
new file mode 100644
index 0000000000000000000000000000000000000000..290967dd6d57adef52a4999e92aafceac5760cd7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/legacy.py
@@ -0,0 +1,120 @@
+"""Legacy installation process, i.e. `setup.py install`.
+"""
+
+import logging
+import os
+from typing import List, Optional, Sequence
+
+from pip._internal.build_env import BuildEnvironment
+from pip._internal.exceptions import InstallationError, LegacyInstallFailure
+from pip._internal.locations.base import change_root
+from pip._internal.models.scheme import Scheme
+from pip._internal.utils.misc import ensure_dir
+from pip._internal.utils.setuptools_build import make_setuptools_install_args
+from pip._internal.utils.subprocess import runner_with_spinner_message
+from pip._internal.utils.temp_dir import TempDirectory
+
+logger = logging.getLogger(__name__)
+
+
+def write_installed_files_from_setuptools_record(
+    record_lines: List[str],
+    root: Optional[str],
+    req_description: str,
+) -> None:
+    def prepend_root(path: str) -> str:
+        if root is None or not os.path.isabs(path):
+            return path
+        else:
+            return change_root(root, path)
+
+    for line in record_lines:
+        directory = os.path.dirname(line)
+        if directory.endswith(".egg-info"):
+            egg_info_dir = prepend_root(directory)
+            break
+    else:
+        message = (
+            "{} did not indicate that it installed an "
+            ".egg-info directory. Only setup.py projects "
+            "generating .egg-info directories are supported."
+        ).format(req_description)
+        raise InstallationError(message)
+
+    new_lines = []
+    for line in record_lines:
+        filename = line.strip()
+        if os.path.isdir(filename):
+            filename += os.path.sep
+        new_lines.append(os.path.relpath(prepend_root(filename), egg_info_dir))
+    new_lines.sort()
+    ensure_dir(egg_info_dir)
+    inst_files_path = os.path.join(egg_info_dir, "installed-files.txt")
+    with open(inst_files_path, "w") as f:
+        f.write("\n".join(new_lines) + "\n")
+
+
+def install(
+    install_options: List[str],
+    global_options: Sequence[str],
+    root: Optional[str],
+    home: Optional[str],
+    prefix: Optional[str],
+    use_user_site: bool,
+    pycompile: bool,
+    scheme: Scheme,
+    setup_py_path: str,
+    isolated: bool,
+    req_name: str,
+    build_env: BuildEnvironment,
+    unpacked_source_directory: str,
+    req_description: str,
+) -> bool:
+
+    header_dir = scheme.headers
+
+    with TempDirectory(kind="record") as temp_dir:
+        try:
+            record_filename = os.path.join(temp_dir.path, "install-record.txt")
+            install_args = make_setuptools_install_args(
+                setup_py_path,
+                global_options=global_options,
+                install_options=install_options,
+                record_filename=record_filename,
+                root=root,
+                prefix=prefix,
+                header_dir=header_dir,
+                home=home,
+                use_user_site=use_user_site,
+                no_user_config=isolated,
+                pycompile=pycompile,
+            )
+
+            runner = runner_with_spinner_message(
+                f"Running setup.py install for {req_name}"
+            )
+            with build_env:
+                runner(
+                    cmd=install_args,
+                    cwd=unpacked_source_directory,
+                )
+
+            if not os.path.exists(record_filename):
+                logger.debug("Record file %s not found", record_filename)
+                # Signal to the caller that we didn't install the new package
+                return False
+
+        except Exception as e:
+            # Signal to the caller that we didn't install the new package
+            raise LegacyInstallFailure(package_details=req_name) from e
+
+        # At this point, we have successfully installed the requirement.
+
+        # We intentionally do not use any encoding to read the file because
+        # setuptools writes the file using distutils.file_util.write_file,
+        # which does not specify an encoding.
+        with open(record_filename) as f:
+            record_lines = f.read().splitlines()
+
+    write_installed_files_from_setuptools_record(record_lines, root, req_description)
+    return True
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..c79941398a2c1d502e60cd0dd0703d8c0530a30f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/install/wheel.py
@@ -0,0 +1,738 @@
+"""Support for installing and building the "wheel" binary package format.
+"""
+
+import collections
+import compileall
+import contextlib
+import csv
+import importlib
+import logging
+import os.path
+import re
+import shutil
+import sys
+import warnings
+from base64 import urlsafe_b64encode
+from email.message import Message
+from itertools import chain, filterfalse, starmap
+from typing import (
+    IO,
+    TYPE_CHECKING,
+    Any,
+    BinaryIO,
+    Callable,
+    Dict,
+    Generator,
+    Iterable,
+    Iterator,
+    List,
+    NewType,
+    Optional,
+    Sequence,
+    Set,
+    Tuple,
+    Union,
+    cast,
+)
+from zipfile import ZipFile, ZipInfo
+
+from pip._vendor.distlib.scripts import ScriptMaker
+from pip._vendor.distlib.util import get_export_entry
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.exceptions import InstallationError
+from pip._internal.locations import get_major_minor_version
+from pip._internal.metadata import (
+    BaseDistribution,
+    FilesystemWheel,
+    get_wheel_distribution,
+)
+from pip._internal.models.direct_url import DIRECT_URL_METADATA_NAME, DirectUrl
+from pip._internal.models.scheme import SCHEME_KEYS, Scheme
+from pip._internal.utils.filesystem import adjacent_tmp_file, replace
+from pip._internal.utils.misc import captured_stdout, ensure_dir, hash_file, partition
+from pip._internal.utils.unpacking import (
+    current_umask,
+    is_within_directory,
+    set_extracted_file_to_default_mode_plus_executable,
+    zip_item_is_executable,
+)
+from pip._internal.utils.wheel import parse_wheel
+
+if TYPE_CHECKING:
+    from typing import Protocol
+
+    class File(Protocol):
+        src_record_path: "RecordPath"
+        dest_path: str
+        changed: bool
+
+        def save(self) -> None:
+            pass
+
+
+logger = logging.getLogger(__name__)
+
+RecordPath = NewType("RecordPath", str)
+InstalledCSVRow = Tuple[RecordPath, str, Union[int, str]]
+
+
+def rehash(path: str, blocksize: int = 1 << 20) -> Tuple[str, str]:
+    """Return (encoded_digest, length) for path using hashlib.sha256()"""
+    h, length = hash_file(path, blocksize)
+    digest = "sha256=" + urlsafe_b64encode(h.digest()).decode("latin1").rstrip("=")
+    return (digest, str(length))
+
+
+def csv_io_kwargs(mode: str) -> Dict[str, Any]:
+    """Return keyword arguments to properly open a CSV file
+    in the given mode.
+    """
+    return {"mode": mode, "newline": "", "encoding": "utf-8"}
+
+
+def fix_script(path: str) -> bool:
+    """Replace #!python with #!/path/to/python
+    Return True if file was changed.
+    """
+    # XXX RECORD hashes will need to be updated
+    assert os.path.isfile(path)
+
+    with open(path, "rb") as script:
+        firstline = script.readline()
+        if not firstline.startswith(b"#!python"):
+            return False
+        exename = sys.executable.encode(sys.getfilesystemencoding())
+        firstline = b"#!" + exename + os.linesep.encode("ascii")
+        rest = script.read()
+    with open(path, "wb") as script:
+        script.write(firstline)
+        script.write(rest)
+    return True
+
+
+def wheel_root_is_purelib(metadata: Message) -> bool:
+    return metadata.get("Root-Is-Purelib", "").lower() == "true"
+
+
+def get_entrypoints(dist: BaseDistribution) -> Tuple[Dict[str, str], Dict[str, str]]:
+    console_scripts = {}
+    gui_scripts = {}
+    for entry_point in dist.iter_entry_points():
+        if entry_point.group == "console_scripts":
+            console_scripts[entry_point.name] = entry_point.value
+        elif entry_point.group == "gui_scripts":
+            gui_scripts[entry_point.name] = entry_point.value
+    return console_scripts, gui_scripts
+
+
+def message_about_scripts_not_on_PATH(scripts: Sequence[str]) -> Optional[str]:
+    """Determine if any scripts are not on PATH and format a warning.
+    Returns a warning message if one or more scripts are not on PATH,
+    otherwise None.
+    """
+    if not scripts:
+        return None
+
+    # Group scripts by the path they were installed in
+    grouped_by_dir: Dict[str, Set[str]] = collections.defaultdict(set)
+    for destfile in scripts:
+        parent_dir = os.path.dirname(destfile)
+        script_name = os.path.basename(destfile)
+        grouped_by_dir[parent_dir].add(script_name)
+
+    # We don't want to warn for directories that are on PATH.
+    not_warn_dirs = [
+        os.path.normcase(i).rstrip(os.sep)
+        for i in os.environ.get("PATH", "").split(os.pathsep)
+    ]
+    # If an executable sits with sys.executable, we don't warn for it.
+    #     This covers the case of venv invocations without activating the venv.
+    not_warn_dirs.append(os.path.normcase(os.path.dirname(sys.executable)))
+    warn_for: Dict[str, Set[str]] = {
+        parent_dir: scripts
+        for parent_dir, scripts in grouped_by_dir.items()
+        if os.path.normcase(parent_dir) not in not_warn_dirs
+    }
+    if not warn_for:
+        return None
+
+    # Format a message
+    msg_lines = []
+    for parent_dir, dir_scripts in warn_for.items():
+        sorted_scripts: List[str] = sorted(dir_scripts)
+        if len(sorted_scripts) == 1:
+            start_text = "script {} is".format(sorted_scripts[0])
+        else:
+            start_text = "scripts {} are".format(
+                ", ".join(sorted_scripts[:-1]) + " and " + sorted_scripts[-1]
+            )
+
+        msg_lines.append(
+            "The {} installed in '{}' which is not on PATH.".format(
+                start_text, parent_dir
+            )
+        )
+
+    last_line_fmt = (
+        "Consider adding {} to PATH or, if you prefer "
+        "to suppress this warning, use --no-warn-script-location."
+    )
+    if len(msg_lines) == 1:
+        msg_lines.append(last_line_fmt.format("this directory"))
+    else:
+        msg_lines.append(last_line_fmt.format("these directories"))
+
+    # Add a note if any directory starts with ~
+    warn_for_tilde = any(
+        i[0] == "~" for i in os.environ.get("PATH", "").split(os.pathsep) if i
+    )
+    if warn_for_tilde:
+        tilde_warning_msg = (
+            "NOTE: The current PATH contains path(s) starting with `~`, "
+            "which may not be expanded by all applications."
+        )
+        msg_lines.append(tilde_warning_msg)
+
+    # Returns the formatted multiline message
+    return "\n".join(msg_lines)
+
+
+def _normalized_outrows(
+    outrows: Iterable[InstalledCSVRow],
+) -> List[Tuple[str, str, str]]:
+    """Normalize the given rows of a RECORD file.
+
+    Items in each row are converted into str. Rows are then sorted to make
+    the value more predictable for tests.
+
+    Each row is a 3-tuple (path, hash, size) and corresponds to a record of
+    a RECORD file (see PEP 376 and PEP 427 for details).  For the rows
+    passed to this function, the size can be an integer as an int or string,
+    or the empty string.
+    """
+    # Normally, there should only be one row per path, in which case the
+    # second and third elements don't come into play when sorting.
+    # However, in cases in the wild where a path might happen to occur twice,
+    # we don't want the sort operation to trigger an error (but still want
+    # determinism).  Since the third element can be an int or string, we
+    # coerce each element to a string to avoid a TypeError in this case.
+    # For additional background, see--
+    # https://github.com/pypa/pip/issues/5868
+    return sorted(
+        (record_path, hash_, str(size)) for record_path, hash_, size in outrows
+    )
+
+
+def _record_to_fs_path(record_path: RecordPath, lib_dir: str) -> str:
+    return os.path.join(lib_dir, record_path)
+
+
+def _fs_to_record_path(path: str, lib_dir: str) -> RecordPath:
+    # On Windows, do not handle relative paths if they belong to different
+    # logical disks
+    if os.path.splitdrive(path)[0].lower() == os.path.splitdrive(lib_dir)[0].lower():
+        path = os.path.relpath(path, lib_dir)
+
+    path = path.replace(os.path.sep, "/")
+    return cast("RecordPath", path)
+
+
+def get_csv_rows_for_installed(
+    old_csv_rows: List[List[str]],
+    installed: Dict[RecordPath, RecordPath],
+    changed: Set[RecordPath],
+    generated: List[str],
+    lib_dir: str,
+) -> List[InstalledCSVRow]:
+    """
+    :param installed: A map from archive RECORD path to installation RECORD
+        path.
+    """
+    installed_rows: List[InstalledCSVRow] = []
+    for row in old_csv_rows:
+        if len(row) > 3:
+            logger.warning("RECORD line has more than three elements: %s", row)
+        old_record_path = cast("RecordPath", row[0])
+        new_record_path = installed.pop(old_record_path, old_record_path)
+        if new_record_path in changed:
+            digest, length = rehash(_record_to_fs_path(new_record_path, lib_dir))
+        else:
+            digest = row[1] if len(row) > 1 else ""
+            length = row[2] if len(row) > 2 else ""
+        installed_rows.append((new_record_path, digest, length))
+    for f in generated:
+        path = _fs_to_record_path(f, lib_dir)
+        digest, length = rehash(f)
+        installed_rows.append((path, digest, length))
+    for installed_record_path in installed.values():
+        installed_rows.append((installed_record_path, "", ""))
+    return installed_rows
+
+
+def get_console_script_specs(console: Dict[str, str]) -> List[str]:
+    """
+    Given the mapping from entrypoint name to callable, return the relevant
+    console script specs.
+    """
+    # Don't mutate caller's version
+    console = console.copy()
+
+    scripts_to_generate = []
+
+    # Special case pip and setuptools to generate versioned wrappers
+    #
+    # The issue is that some projects (specifically, pip and setuptools) use
+    # code in setup.py to create "versioned" entry points - pip2.7 on Python
+    # 2.7, pip3.3 on Python 3.3, etc. But these entry points are baked into
+    # the wheel metadata at build time, and so if the wheel is installed with
+    # a *different* version of Python the entry points will be wrong. The
+    # correct fix for this is to enhance the metadata to be able to describe
+    # such versioned entry points, but that won't happen till Metadata 2.0 is
+    # available.
+    # In the meantime, projects using versioned entry points will either have
+    # incorrect versioned entry points, or they will not be able to distribute
+    # "universal" wheels (i.e., they will need a wheel per Python version).
+    #
+    # Because setuptools and pip are bundled with _ensurepip and virtualenv,
+    # we need to use universal wheels. So, as a stopgap until Metadata 2.0, we
+    # override the versioned entry points in the wheel and generate the
+    # correct ones. This code is purely a short-term measure until Metadata 2.0
+    # is available.
+    #
+    # To add the level of hack in this section of code, in order to support
+    # ensurepip this code will look for an ``ENSUREPIP_OPTIONS`` environment
+    # variable which will control which version scripts get installed.
+    #
+    # ENSUREPIP_OPTIONS=altinstall
+    #   - Only pipX.Y and easy_install-X.Y will be generated and installed
+    # ENSUREPIP_OPTIONS=install
+    #   - pipX.Y, pipX, easy_install-X.Y will be generated and installed. Note
+    #     that this option is technically if ENSUREPIP_OPTIONS is set and is
+    #     not altinstall
+    # DEFAULT
+    #   - The default behavior is to install pip, pipX, pipX.Y, easy_install
+    #     and easy_install-X.Y.
+    pip_script = console.pop("pip", None)
+    if pip_script:
+        if "ENSUREPIP_OPTIONS" not in os.environ:
+            scripts_to_generate.append("pip = " + pip_script)
+
+        if os.environ.get("ENSUREPIP_OPTIONS", "") != "altinstall":
+            scripts_to_generate.append(
+                "pip{} = {}".format(sys.version_info[0], pip_script)
+            )
+
+        scripts_to_generate.append(f"pip{get_major_minor_version()} = {pip_script}")
+        # Delete any other versioned pip entry points
+        pip_ep = [k for k in console if re.match(r"pip(\d+(\.\d+)?)?$", k)]
+        for k in pip_ep:
+            del console[k]
+    easy_install_script = console.pop("easy_install", None)
+    if easy_install_script:
+        if "ENSUREPIP_OPTIONS" not in os.environ:
+            scripts_to_generate.append("easy_install = " + easy_install_script)
+
+        scripts_to_generate.append(
+            "easy_install-{} = {}".format(
+                get_major_minor_version(), easy_install_script
+            )
+        )
+        # Delete any other versioned easy_install entry points
+        easy_install_ep = [
+            k for k in console if re.match(r"easy_install(-\d+\.\d+)?$", k)
+        ]
+        for k in easy_install_ep:
+            del console[k]
+
+    # Generate the console entry points specified in the wheel
+    scripts_to_generate.extend(starmap("{} = {}".format, console.items()))
+
+    return scripts_to_generate
+
+
+class ZipBackedFile:
+    def __init__(
+        self, src_record_path: RecordPath, dest_path: str, zip_file: ZipFile
+    ) -> None:
+        self.src_record_path = src_record_path
+        self.dest_path = dest_path
+        self._zip_file = zip_file
+        self.changed = False
+
+    def _getinfo(self) -> ZipInfo:
+        return self._zip_file.getinfo(self.src_record_path)
+
+    def save(self) -> None:
+        # directory creation is lazy and after file filtering
+        # to ensure we don't install empty dirs; empty dirs can't be
+        # uninstalled.
+        parent_dir = os.path.dirname(self.dest_path)
+        ensure_dir(parent_dir)
+
+        # When we open the output file below, any existing file is truncated
+        # before we start writing the new contents. This is fine in most
+        # cases, but can cause a segfault if pip has loaded a shared
+        # object (e.g. from pyopenssl through its vendored urllib3)
+        # Since the shared object is mmap'd an attempt to call a
+        # symbol in it will then cause a segfault. Unlinking the file
+        # allows writing of new contents while allowing the process to
+        # continue to use the old copy.
+        if os.path.exists(self.dest_path):
+            os.unlink(self.dest_path)
+
+        zipinfo = self._getinfo()
+
+        with self._zip_file.open(zipinfo) as f:
+            with open(self.dest_path, "wb") as dest:
+                shutil.copyfileobj(f, dest)
+
+        if zip_item_is_executable(zipinfo):
+            set_extracted_file_to_default_mode_plus_executable(self.dest_path)
+
+
+class ScriptFile:
+    def __init__(self, file: "File") -> None:
+        self._file = file
+        self.src_record_path = self._file.src_record_path
+        self.dest_path = self._file.dest_path
+        self.changed = False
+
+    def save(self) -> None:
+        self._file.save()
+        self.changed = fix_script(self.dest_path)
+
+
+class MissingCallableSuffix(InstallationError):
+    def __init__(self, entry_point: str) -> None:
+        super().__init__(
+            "Invalid script entry point: {} - A callable "
+            "suffix is required. Cf https://packaging.python.org/"
+            "specifications/entry-points/#use-for-scripts for more "
+            "information.".format(entry_point)
+        )
+
+
+def _raise_for_invalid_entrypoint(specification: str) -> None:
+    entry = get_export_entry(specification)
+    if entry is not None and entry.suffix is None:
+        raise MissingCallableSuffix(str(entry))
+
+
+class PipScriptMaker(ScriptMaker):
+    def make(
+        self, specification: str, options: Optional[Dict[str, Any]] = None
+    ) -> List[str]:
+        _raise_for_invalid_entrypoint(specification)
+        return super().make(specification, options)
+
+
+def _install_wheel(
+    name: str,
+    wheel_zip: ZipFile,
+    wheel_path: str,
+    scheme: Scheme,
+    pycompile: bool = True,
+    warn_script_location: bool = True,
+    direct_url: Optional[DirectUrl] = None,
+    requested: bool = False,
+) -> None:
+    """Install a wheel.
+
+    :param name: Name of the project to install
+    :param wheel_zip: open ZipFile for wheel being installed
+    :param scheme: Distutils scheme dictating the install directories
+    :param req_description: String used in place of the requirement, for
+        logging
+    :param pycompile: Whether to byte-compile installed Python files
+    :param warn_script_location: Whether to check that scripts are installed
+        into a directory on PATH
+    :raises UnsupportedWheel:
+        * when the directory holds an unpacked wheel with incompatible
+          Wheel-Version
+        * when the .dist-info dir does not match the wheel
+    """
+    info_dir, metadata = parse_wheel(wheel_zip, name)
+
+    if wheel_root_is_purelib(metadata):
+        lib_dir = scheme.purelib
+    else:
+        lib_dir = scheme.platlib
+
+    # Record details of the files moved
+    #   installed = files copied from the wheel to the destination
+    #   changed = files changed while installing (scripts #! line typically)
+    #   generated = files newly generated during the install (script wrappers)
+    installed: Dict[RecordPath, RecordPath] = {}
+    changed: Set[RecordPath] = set()
+    generated: List[str] = []
+
+    def record_installed(
+        srcfile: RecordPath, destfile: str, modified: bool = False
+    ) -> None:
+        """Map archive RECORD paths to installation RECORD paths."""
+        newpath = _fs_to_record_path(destfile, lib_dir)
+        installed[srcfile] = newpath
+        if modified:
+            changed.add(newpath)
+
+    def is_dir_path(path: RecordPath) -> bool:
+        return path.endswith("/")
+
+    def assert_no_path_traversal(dest_dir_path: str, target_path: str) -> None:
+        if not is_within_directory(dest_dir_path, target_path):
+            message = (
+                "The wheel {!r} has a file {!r} trying to install"
+                " outside the target directory {!r}"
+            )
+            raise InstallationError(
+                message.format(wheel_path, target_path, dest_dir_path)
+            )
+
+    def root_scheme_file_maker(
+        zip_file: ZipFile, dest: str
+    ) -> Callable[[RecordPath], "File"]:
+        def make_root_scheme_file(record_path: RecordPath) -> "File":
+            normed_path = os.path.normpath(record_path)
+            dest_path = os.path.join(dest, normed_path)
+            assert_no_path_traversal(dest, dest_path)
+            return ZipBackedFile(record_path, dest_path, zip_file)
+
+        return make_root_scheme_file
+
+    def data_scheme_file_maker(
+        zip_file: ZipFile, scheme: Scheme
+    ) -> Callable[[RecordPath], "File"]:
+        scheme_paths = {key: getattr(scheme, key) for key in SCHEME_KEYS}
+
+        def make_data_scheme_file(record_path: RecordPath) -> "File":
+            normed_path = os.path.normpath(record_path)
+            try:
+                _, scheme_key, dest_subpath = normed_path.split(os.path.sep, 2)
+            except ValueError:
+                message = (
+                    "Unexpected file in {}: {!r}. .data directory contents"
+                    " should be named like: '/'."
+                ).format(wheel_path, record_path)
+                raise InstallationError(message)
+
+            try:
+                scheme_path = scheme_paths[scheme_key]
+            except KeyError:
+                valid_scheme_keys = ", ".join(sorted(scheme_paths))
+                message = (
+                    "Unknown scheme key used in {}: {} (for file {!r}). .data"
+                    " directory contents should be in subdirectories named"
+                    " with a valid scheme key ({})"
+                ).format(wheel_path, scheme_key, record_path, valid_scheme_keys)
+                raise InstallationError(message)
+
+            dest_path = os.path.join(scheme_path, dest_subpath)
+            assert_no_path_traversal(scheme_path, dest_path)
+            return ZipBackedFile(record_path, dest_path, zip_file)
+
+        return make_data_scheme_file
+
+    def is_data_scheme_path(path: RecordPath) -> bool:
+        return path.split("/", 1)[0].endswith(".data")
+
+    paths = cast(List[RecordPath], wheel_zip.namelist())
+    file_paths = filterfalse(is_dir_path, paths)
+    root_scheme_paths, data_scheme_paths = partition(is_data_scheme_path, file_paths)
+
+    make_root_scheme_file = root_scheme_file_maker(wheel_zip, lib_dir)
+    files: Iterator[File] = map(make_root_scheme_file, root_scheme_paths)
+
+    def is_script_scheme_path(path: RecordPath) -> bool:
+        parts = path.split("/", 2)
+        return len(parts) > 2 and parts[0].endswith(".data") and parts[1] == "scripts"
+
+    other_scheme_paths, script_scheme_paths = partition(
+        is_script_scheme_path, data_scheme_paths
+    )
+
+    make_data_scheme_file = data_scheme_file_maker(wheel_zip, scheme)
+    other_scheme_files = map(make_data_scheme_file, other_scheme_paths)
+    files = chain(files, other_scheme_files)
+
+    # Get the defined entry points
+    distribution = get_wheel_distribution(
+        FilesystemWheel(wheel_path),
+        canonicalize_name(name),
+    )
+    console, gui = get_entrypoints(distribution)
+
+    def is_entrypoint_wrapper(file: "File") -> bool:
+        # EP, EP.exe and EP-script.py are scripts generated for
+        # entry point EP by setuptools
+        path = file.dest_path
+        name = os.path.basename(path)
+        if name.lower().endswith(".exe"):
+            matchname = name[:-4]
+        elif name.lower().endswith("-script.py"):
+            matchname = name[:-10]
+        elif name.lower().endswith(".pya"):
+            matchname = name[:-4]
+        else:
+            matchname = name
+        # Ignore setuptools-generated scripts
+        return matchname in console or matchname in gui
+
+    script_scheme_files: Iterator[File] = map(
+        make_data_scheme_file, script_scheme_paths
+    )
+    script_scheme_files = filterfalse(is_entrypoint_wrapper, script_scheme_files)
+    script_scheme_files = map(ScriptFile, script_scheme_files)
+    files = chain(files, script_scheme_files)
+
+    for file in files:
+        file.save()
+        record_installed(file.src_record_path, file.dest_path, file.changed)
+
+    def pyc_source_file_paths() -> Generator[str, None, None]:
+        # We de-duplicate installation paths, since there can be overlap (e.g.
+        # file in .data maps to same location as file in wheel root).
+        # Sorting installation paths makes it easier to reproduce and debug
+        # issues related to permissions on existing files.
+        for installed_path in sorted(set(installed.values())):
+            full_installed_path = os.path.join(lib_dir, installed_path)
+            if not os.path.isfile(full_installed_path):
+                continue
+            if not full_installed_path.endswith(".py"):
+                continue
+            yield full_installed_path
+
+    def pyc_output_path(path: str) -> str:
+        """Return the path the pyc file would have been written to."""
+        return importlib.util.cache_from_source(path)
+
+    # Compile all of the pyc files for the installed files
+    if pycompile:
+        with captured_stdout() as stdout:
+            with warnings.catch_warnings():
+                warnings.filterwarnings("ignore")
+                for path in pyc_source_file_paths():
+                    success = compileall.compile_file(path, force=True, quiet=True)
+                    if success:
+                        pyc_path = pyc_output_path(path)
+                        assert os.path.exists(pyc_path)
+                        pyc_record_path = cast(
+                            "RecordPath", pyc_path.replace(os.path.sep, "/")
+                        )
+                        record_installed(pyc_record_path, pyc_path)
+        logger.debug(stdout.getvalue())
+
+    maker = PipScriptMaker(None, scheme.scripts)
+
+    # Ensure old scripts are overwritten.
+    # See https://github.com/pypa/pip/issues/1800
+    maker.clobber = True
+
+    # Ensure we don't generate any variants for scripts because this is almost
+    # never what somebody wants.
+    # See https://bitbucket.org/pypa/distlib/issue/35/
+    maker.variants = {""}
+
+    # This is required because otherwise distlib creates scripts that are not
+    # executable.
+    # See https://bitbucket.org/pypa/distlib/issue/32/
+    maker.set_mode = True
+
+    # Generate the console and GUI entry points specified in the wheel
+    scripts_to_generate = get_console_script_specs(console)
+
+    gui_scripts_to_generate = list(starmap("{} = {}".format, gui.items()))
+
+    generated_console_scripts = maker.make_multiple(scripts_to_generate)
+    generated.extend(generated_console_scripts)
+
+    generated.extend(maker.make_multiple(gui_scripts_to_generate, {"gui": True}))
+
+    if warn_script_location:
+        msg = message_about_scripts_not_on_PATH(generated_console_scripts)
+        if msg is not None:
+            logger.warning(msg)
+
+    generated_file_mode = 0o666 & ~current_umask()
+
+    @contextlib.contextmanager
+    def _generate_file(path: str, **kwargs: Any) -> Generator[BinaryIO, None, None]:
+        with adjacent_tmp_file(path, **kwargs) as f:
+            yield f
+        os.chmod(f.name, generated_file_mode)
+        replace(f.name, path)
+
+    dest_info_dir = os.path.join(lib_dir, info_dir)
+
+    # Record pip as the installer
+    installer_path = os.path.join(dest_info_dir, "INSTALLER")
+    with _generate_file(installer_path) as installer_file:
+        installer_file.write(b"pip\n")
+    generated.append(installer_path)
+
+    # Record the PEP 610 direct URL reference
+    if direct_url is not None:
+        direct_url_path = os.path.join(dest_info_dir, DIRECT_URL_METADATA_NAME)
+        with _generate_file(direct_url_path) as direct_url_file:
+            direct_url_file.write(direct_url.to_json().encode("utf-8"))
+        generated.append(direct_url_path)
+
+    # Record the REQUESTED file
+    if requested:
+        requested_path = os.path.join(dest_info_dir, "REQUESTED")
+        with open(requested_path, "wb"):
+            pass
+        generated.append(requested_path)
+
+    record_text = distribution.read_text("RECORD")
+    record_rows = list(csv.reader(record_text.splitlines()))
+
+    rows = get_csv_rows_for_installed(
+        record_rows,
+        installed=installed,
+        changed=changed,
+        generated=generated,
+        lib_dir=lib_dir,
+    )
+
+    # Record details of all files installed
+    record_path = os.path.join(dest_info_dir, "RECORD")
+
+    with _generate_file(record_path, **csv_io_kwargs("w")) as record_file:
+        # Explicitly cast to typing.IO[str] as a workaround for the mypy error:
+        # "writer" has incompatible type "BinaryIO"; expected "_Writer"
+        writer = csv.writer(cast("IO[str]", record_file))
+        writer.writerows(_normalized_outrows(rows))
+
+
+@contextlib.contextmanager
+def req_error_context(req_description: str) -> Generator[None, None, None]:
+    try:
+        yield
+    except InstallationError as e:
+        message = "For req: {}. {}".format(req_description, e.args[0])
+        raise InstallationError(message) from e
+
+
+def install_wheel(
+    name: str,
+    wheel_path: str,
+    scheme: Scheme,
+    req_description: str,
+    pycompile: bool = True,
+    warn_script_location: bool = True,
+    direct_url: Optional[DirectUrl] = None,
+    requested: bool = False,
+) -> None:
+    with ZipFile(wheel_path, allowZip64=True) as z:
+        with req_error_context(req_description):
+            _install_wheel(
+                name=name,
+                wheel_zip=z,
+                wheel_path=wheel_path,
+                scheme=scheme,
+                pycompile=pycompile,
+                warn_script_location=warn_script_location,
+                direct_url=direct_url,
+                requested=requested,
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/prepare.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/prepare.py
new file mode 100644
index 0000000000000000000000000000000000000000..4bf414cb0052e351b6976b500123633bcacff15a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/operations/prepare.py
@@ -0,0 +1,667 @@
+"""Prepares a distribution for installation
+"""
+
+# The following comment should be removed at some point in the future.
+# mypy: strict-optional=False
+
+import logging
+import mimetypes
+import os
+import shutil
+from typing import Dict, Iterable, List, Optional
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.distributions import make_distribution_for_install_requirement
+from pip._internal.distributions.installed import InstalledDistribution
+from pip._internal.exceptions import (
+    DirectoryUrlHashUnsupported,
+    HashMismatch,
+    HashUnpinned,
+    InstallationError,
+    MetadataInconsistent,
+    NetworkConnectionError,
+    PreviousBuildDirError,
+    VcsHashUnsupported,
+)
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import BaseDistribution, get_metadata_distribution
+from pip._internal.models.direct_url import ArchiveInfo
+from pip._internal.models.link import Link
+from pip._internal.models.wheel import Wheel
+from pip._internal.network.download import BatchDownloader, Downloader
+from pip._internal.network.lazy_wheel import (
+    HTTPRangeRequestUnsupported,
+    dist_from_wheel_url,
+)
+from pip._internal.network.session import PipSession
+from pip._internal.operations.build.build_tracker import BuildTracker
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.utils.direct_url_helpers import (
+    direct_url_for_editable,
+    direct_url_from_link,
+)
+from pip._internal.utils.hashes import Hashes, MissingHashes
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.misc import (
+    display_path,
+    hash_file,
+    hide_url,
+    is_installable_dir,
+)
+from pip._internal.utils.temp_dir import TempDirectory
+from pip._internal.utils.unpacking import unpack_file
+from pip._internal.vcs import vcs
+
+logger = logging.getLogger(__name__)
+
+
+def _get_prepared_distribution(
+    req: InstallRequirement,
+    build_tracker: BuildTracker,
+    finder: PackageFinder,
+    build_isolation: bool,
+    check_build_deps: bool,
+) -> BaseDistribution:
+    """Prepare a distribution for installation."""
+    abstract_dist = make_distribution_for_install_requirement(req)
+    with build_tracker.track(req):
+        abstract_dist.prepare_distribution_metadata(
+            finder, build_isolation, check_build_deps
+        )
+    return abstract_dist.get_metadata_distribution()
+
+
+def unpack_vcs_link(link: Link, location: str, verbosity: int) -> None:
+    vcs_backend = vcs.get_backend_for_scheme(link.scheme)
+    assert vcs_backend is not None
+    vcs_backend.unpack(location, url=hide_url(link.url), verbosity=verbosity)
+
+
+class File:
+    def __init__(self, path: str, content_type: Optional[str]) -> None:
+        self.path = path
+        if content_type is None:
+            self.content_type = mimetypes.guess_type(path)[0]
+        else:
+            self.content_type = content_type
+
+
+def get_http_url(
+    link: Link,
+    download: Downloader,
+    download_dir: Optional[str] = None,
+    hashes: Optional[Hashes] = None,
+) -> File:
+    temp_dir = TempDirectory(kind="unpack", globally_managed=True)
+    # If a download dir is specified, is the file already downloaded there?
+    already_downloaded_path = None
+    if download_dir:
+        already_downloaded_path = _check_download_dir(link, download_dir, hashes)
+
+    if already_downloaded_path:
+        from_path = already_downloaded_path
+        content_type = None
+    else:
+        # let's download to a tmp dir
+        from_path, content_type = download(link, temp_dir.path)
+        if hashes:
+            hashes.check_against_path(from_path)
+
+    return File(from_path, content_type)
+
+
+def get_file_url(
+    link: Link, download_dir: Optional[str] = None, hashes: Optional[Hashes] = None
+) -> File:
+    """Get file and optionally check its hash."""
+    # If a download dir is specified, is the file already there and valid?
+    already_downloaded_path = None
+    if download_dir:
+        already_downloaded_path = _check_download_dir(link, download_dir, hashes)
+
+    if already_downloaded_path:
+        from_path = already_downloaded_path
+    else:
+        from_path = link.file_path
+
+    # If --require-hashes is off, `hashes` is either empty, the
+    # link's embedded hash, or MissingHashes; it is required to
+    # match. If --require-hashes is on, we are satisfied by any
+    # hash in `hashes` matching: a URL-based or an option-based
+    # one; no internet-sourced hash will be in `hashes`.
+    if hashes:
+        hashes.check_against_path(from_path)
+    return File(from_path, None)
+
+
+def unpack_url(
+    link: Link,
+    location: str,
+    download: Downloader,
+    verbosity: int,
+    download_dir: Optional[str] = None,
+    hashes: Optional[Hashes] = None,
+) -> Optional[File]:
+    """Unpack link into location, downloading if required.
+
+    :param hashes: A Hashes object, one of whose embedded hashes must match,
+        or HashMismatch will be raised. If the Hashes is empty, no matches are
+        required, and unhashable types of requirements (like VCS ones, which
+        would ordinarily raise HashUnsupported) are allowed.
+    """
+    # non-editable vcs urls
+    if link.is_vcs:
+        unpack_vcs_link(link, location, verbosity=verbosity)
+        return None
+
+    assert not link.is_existing_dir()
+
+    # file urls
+    if link.is_file:
+        file = get_file_url(link, download_dir, hashes=hashes)
+
+    # http urls
+    else:
+        file = get_http_url(
+            link,
+            download,
+            download_dir,
+            hashes=hashes,
+        )
+
+    # unpack the archive to the build dir location. even when only downloading
+    # archives, they have to be unpacked to parse dependencies, except wheels
+    if not link.is_wheel:
+        unpack_file(file.path, location, file.content_type)
+
+    return file
+
+
+def _check_download_dir(
+    link: Link, download_dir: str, hashes: Optional[Hashes]
+) -> Optional[str]:
+    """Check download_dir for previously downloaded file with correct hash
+    If a correct file is found return its path else None
+    """
+    download_path = os.path.join(download_dir, link.filename)
+
+    if not os.path.exists(download_path):
+        return None
+
+    # If already downloaded, does its hash match?
+    logger.info("File was already downloaded %s", download_path)
+    if hashes:
+        try:
+            hashes.check_against_path(download_path)
+        except HashMismatch:
+            logger.warning(
+                "Previously-downloaded file %s has bad hash. Re-downloading.",
+                download_path,
+            )
+            os.unlink(download_path)
+            return None
+    return download_path
+
+
+class RequirementPreparer:
+    """Prepares a Requirement"""
+
+    def __init__(
+        self,
+        build_dir: str,
+        download_dir: Optional[str],
+        src_dir: str,
+        build_isolation: bool,
+        check_build_deps: bool,
+        build_tracker: BuildTracker,
+        session: PipSession,
+        progress_bar: str,
+        finder: PackageFinder,
+        require_hashes: bool,
+        use_user_site: bool,
+        lazy_wheel: bool,
+        verbosity: int,
+    ) -> None:
+        super().__init__()
+
+        self.src_dir = src_dir
+        self.build_dir = build_dir
+        self.build_tracker = build_tracker
+        self._session = session
+        self._download = Downloader(session, progress_bar)
+        self._batch_download = BatchDownloader(session, progress_bar)
+        self.finder = finder
+
+        # Where still-packed archives should be written to. If None, they are
+        # not saved, and are deleted immediately after unpacking.
+        self.download_dir = download_dir
+
+        # Is build isolation allowed?
+        self.build_isolation = build_isolation
+
+        # Should check build dependencies?
+        self.check_build_deps = check_build_deps
+
+        # Should hash-checking be required?
+        self.require_hashes = require_hashes
+
+        # Should install in user site-packages?
+        self.use_user_site = use_user_site
+
+        # Should wheels be downloaded lazily?
+        self.use_lazy_wheel = lazy_wheel
+
+        # How verbose should underlying tooling be?
+        self.verbosity = verbosity
+
+        # Memoized downloaded files, as mapping of url: path.
+        self._downloaded: Dict[str, str] = {}
+
+        # Previous "header" printed for a link-based InstallRequirement
+        self._previous_requirement_header = ("", "")
+
+    def _log_preparing_link(self, req: InstallRequirement) -> None:
+        """Provide context for the requirement being prepared."""
+        if req.link.is_file and not req.original_link_is_in_wheel_cache:
+            message = "Processing %s"
+            information = str(display_path(req.link.file_path))
+        else:
+            message = "Collecting %s"
+            information = str(req.req or req)
+
+        if (message, information) != self._previous_requirement_header:
+            self._previous_requirement_header = (message, information)
+            logger.info(message, information)
+
+        if req.original_link_is_in_wheel_cache:
+            with indent_log():
+                logger.info("Using cached %s", req.link.filename)
+
+    def _ensure_link_req_src_dir(
+        self, req: InstallRequirement, parallel_builds: bool
+    ) -> None:
+        """Ensure source_dir of a linked InstallRequirement."""
+        # Since source_dir is only set for editable requirements.
+        if req.link.is_wheel:
+            # We don't need to unpack wheels, so no need for a source
+            # directory.
+            return
+        assert req.source_dir is None
+        if req.link.is_existing_dir():
+            # build local directories in-tree
+            req.source_dir = req.link.file_path
+            return
+
+        # We always delete unpacked sdists after pip runs.
+        req.ensure_has_source_dir(
+            self.build_dir,
+            autodelete=True,
+            parallel_builds=parallel_builds,
+        )
+
+        # If a checkout exists, it's unwise to keep going.  version
+        # inconsistencies are logged later, but do not fail the
+        # installation.
+        # FIXME: this won't upgrade when there's an existing
+        # package unpacked in `req.source_dir`
+        # TODO: this check is now probably dead code
+        if is_installable_dir(req.source_dir):
+            raise PreviousBuildDirError(
+                "pip can't proceed with requirements '{}' due to a"
+                "pre-existing build directory ({}). This is likely "
+                "due to a previous installation that failed . pip is "
+                "being responsible and not assuming it can delete this. "
+                "Please delete it and try again.".format(req, req.source_dir)
+            )
+
+    def _get_linked_req_hashes(self, req: InstallRequirement) -> Hashes:
+        # By the time this is called, the requirement's link should have
+        # been checked so we can tell what kind of requirements req is
+        # and raise some more informative errors than otherwise.
+        # (For example, we can raise VcsHashUnsupported for a VCS URL
+        # rather than HashMissing.)
+        if not self.require_hashes:
+            return req.hashes(trust_internet=True)
+
+        # We could check these first 2 conditions inside unpack_url
+        # and save repetition of conditions, but then we would
+        # report less-useful error messages for unhashable
+        # requirements, complaining that there's no hash provided.
+        if req.link.is_vcs:
+            raise VcsHashUnsupported()
+        if req.link.is_existing_dir():
+            raise DirectoryUrlHashUnsupported()
+
+        # Unpinned packages are asking for trouble when a new version
+        # is uploaded.  This isn't a security check, but it saves users
+        # a surprising hash mismatch in the future.
+        # file:/// URLs aren't pinnable, so don't complain about them
+        # not being pinned.
+        if req.original_link is None and not req.is_pinned:
+            raise HashUnpinned()
+
+        # If known-good hashes are missing for this requirement,
+        # shim it with a facade object that will provoke hash
+        # computation and then raise a HashMissing exception
+        # showing the user what the hash should be.
+        return req.hashes(trust_internet=False) or MissingHashes()
+
+    def _fetch_metadata_only(
+        self,
+        req: InstallRequirement,
+    ) -> Optional[BaseDistribution]:
+        if self.require_hashes:
+            logger.debug(
+                "Metadata-only fetching is not used as hash checking is required",
+            )
+            return None
+        # Try PEP 658 metadata first, then fall back to lazy wheel if unavailable.
+        return self._fetch_metadata_using_link_data_attr(
+            req
+        ) or self._fetch_metadata_using_lazy_wheel(req.link)
+
+    def _fetch_metadata_using_link_data_attr(
+        self,
+        req: InstallRequirement,
+    ) -> Optional[BaseDistribution]:
+        """Fetch metadata from the data-dist-info-metadata attribute, if possible."""
+        # (1) Get the link to the metadata file, if provided by the backend.
+        metadata_link = req.link.metadata_link()
+        if metadata_link is None:
+            return None
+        assert req.req is not None
+        logger.info(
+            "Obtaining dependency information for %s from %s",
+            req.req,
+            metadata_link,
+        )
+        # (2) Download the contents of the METADATA file, separate from the dist itself.
+        metadata_file = get_http_url(
+            metadata_link,
+            self._download,
+            hashes=metadata_link.as_hashes(),
+        )
+        with open(metadata_file.path, "rb") as f:
+            metadata_contents = f.read()
+        # (3) Generate a dist just from those file contents.
+        metadata_dist = get_metadata_distribution(
+            metadata_contents,
+            req.link.filename,
+            req.req.name,
+        )
+        # (4) Ensure the Name: field from the METADATA file matches the name from the
+        #     install requirement.
+        #
+        #     NB: raw_name will fall back to the name from the install requirement if
+        #     the Name: field is not present, but it's noted in the raw_name docstring
+        #     that that should NEVER happen anyway.
+        if metadata_dist.raw_name != req.req.name:
+            raise MetadataInconsistent(
+                req, "Name", req.req.name, metadata_dist.raw_name
+            )
+        return metadata_dist
+
+    def _fetch_metadata_using_lazy_wheel(
+        self,
+        link: Link,
+    ) -> Optional[BaseDistribution]:
+        """Fetch metadata using lazy wheel, if possible."""
+        # --use-feature=fast-deps must be provided.
+        if not self.use_lazy_wheel:
+            return None
+        if link.is_file or not link.is_wheel:
+            logger.debug(
+                "Lazy wheel is not used as %r does not point to a remote wheel",
+                link,
+            )
+            return None
+
+        wheel = Wheel(link.filename)
+        name = canonicalize_name(wheel.name)
+        logger.info(
+            "Obtaining dependency information from %s %s",
+            name,
+            wheel.version,
+        )
+        url = link.url.split("#", 1)[0]
+        try:
+            return dist_from_wheel_url(name, url, self._session)
+        except HTTPRangeRequestUnsupported:
+            logger.debug("%s does not support range requests", url)
+            return None
+
+    def _complete_partial_requirements(
+        self,
+        partially_downloaded_reqs: Iterable[InstallRequirement],
+        parallel_builds: bool = False,
+    ) -> None:
+        """Download any requirements which were only fetched by metadata."""
+        # Download to a temporary directory. These will be copied over as
+        # needed for downstream 'download', 'wheel', and 'install' commands.
+        temp_dir = TempDirectory(kind="unpack", globally_managed=True).path
+
+        # Map each link to the requirement that owns it. This allows us to set
+        # `req.local_file_path` on the appropriate requirement after passing
+        # all the links at once into BatchDownloader.
+        links_to_fully_download: Dict[Link, InstallRequirement] = {}
+        for req in partially_downloaded_reqs:
+            assert req.link
+            links_to_fully_download[req.link] = req
+
+        batch_download = self._batch_download(
+            links_to_fully_download.keys(),
+            temp_dir,
+        )
+        for link, (filepath, _) in batch_download:
+            logger.debug("Downloading link %s to %s", link, filepath)
+            req = links_to_fully_download[link]
+            req.local_file_path = filepath
+
+        # This step is necessary to ensure all lazy wheels are processed
+        # successfully by the 'download', 'wheel', and 'install' commands.
+        for req in partially_downloaded_reqs:
+            self._prepare_linked_requirement(req, parallel_builds)
+
+    def prepare_linked_requirement(
+        self, req: InstallRequirement, parallel_builds: bool = False
+    ) -> BaseDistribution:
+        """Prepare a requirement to be obtained from req.link."""
+        assert req.link
+        self._log_preparing_link(req)
+        with indent_log():
+            # Check if the relevant file is already available
+            # in the download directory
+            file_path = None
+            if self.download_dir is not None and req.link.is_wheel:
+                hashes = self._get_linked_req_hashes(req)
+                file_path = _check_download_dir(req.link, self.download_dir, hashes)
+
+            if file_path is not None:
+                # The file is already available, so mark it as downloaded
+                self._downloaded[req.link.url] = file_path
+            else:
+                # The file is not available, attempt to fetch only metadata
+                metadata_dist = self._fetch_metadata_only(req)
+                if metadata_dist is not None:
+                    req.needs_more_preparation = True
+                    return metadata_dist
+
+            # None of the optimizations worked, fully prepare the requirement
+            return self._prepare_linked_requirement(req, parallel_builds)
+
+    def prepare_linked_requirements_more(
+        self, reqs: Iterable[InstallRequirement], parallel_builds: bool = False
+    ) -> None:
+        """Prepare linked requirements more, if needed."""
+        reqs = [req for req in reqs if req.needs_more_preparation]
+        for req in reqs:
+            # Determine if any of these requirements were already downloaded.
+            if self.download_dir is not None and req.link.is_wheel:
+                hashes = self._get_linked_req_hashes(req)
+                file_path = _check_download_dir(req.link, self.download_dir, hashes)
+                if file_path is not None:
+                    self._downloaded[req.link.url] = file_path
+                    req.needs_more_preparation = False
+
+        # Prepare requirements we found were already downloaded for some
+        # reason. The other downloads will be completed separately.
+        partially_downloaded_reqs: List[InstallRequirement] = []
+        for req in reqs:
+            if req.needs_more_preparation:
+                partially_downloaded_reqs.append(req)
+            else:
+                self._prepare_linked_requirement(req, parallel_builds)
+
+        # TODO: separate this part out from RequirementPreparer when the v1
+        # resolver can be removed!
+        self._complete_partial_requirements(
+            partially_downloaded_reqs,
+            parallel_builds=parallel_builds,
+        )
+
+    def _prepare_linked_requirement(
+        self, req: InstallRequirement, parallel_builds: bool
+    ) -> BaseDistribution:
+        assert req.link
+        link = req.link
+
+        self._ensure_link_req_src_dir(req, parallel_builds)
+        hashes = self._get_linked_req_hashes(req)
+
+        if link.is_existing_dir():
+            local_file = None
+        elif link.url not in self._downloaded:
+            try:
+                local_file = unpack_url(
+                    link,
+                    req.source_dir,
+                    self._download,
+                    self.verbosity,
+                    self.download_dir,
+                    hashes,
+                )
+            except NetworkConnectionError as exc:
+                raise InstallationError(
+                    "Could not install requirement {} because of HTTP "
+                    "error {} for URL {}".format(req, exc, link)
+                )
+        else:
+            file_path = self._downloaded[link.url]
+            if hashes:
+                hashes.check_against_path(file_path)
+            local_file = File(file_path, content_type=None)
+
+        # If download_info is set, we got it from the wheel cache.
+        if req.download_info is None:
+            # Editables don't go through this function (see
+            # prepare_editable_requirement).
+            assert not req.editable
+            req.download_info = direct_url_from_link(link, req.source_dir)
+            # Make sure we have a hash in download_info. If we got it as part of the
+            # URL, it will have been verified and we can rely on it. Otherwise we
+            # compute it from the downloaded file.
+            if (
+                isinstance(req.download_info.info, ArchiveInfo)
+                and not req.download_info.info.hash
+                and local_file
+            ):
+                hash = hash_file(local_file.path)[0].hexdigest()
+                req.download_info.info.hash = f"sha256={hash}"
+
+        # For use in later processing,
+        # preserve the file path on the requirement.
+        if local_file:
+            req.local_file_path = local_file.path
+
+        dist = _get_prepared_distribution(
+            req,
+            self.build_tracker,
+            self.finder,
+            self.build_isolation,
+            self.check_build_deps,
+        )
+        return dist
+
+    def save_linked_requirement(self, req: InstallRequirement) -> None:
+        assert self.download_dir is not None
+        assert req.link is not None
+        link = req.link
+        if link.is_vcs or (link.is_existing_dir() and req.editable):
+            # Make a .zip of the source_dir we already created.
+            req.archive(self.download_dir)
+            return
+
+        if link.is_existing_dir():
+            logger.debug(
+                "Not copying link to destination directory "
+                "since it is a directory: %s",
+                link,
+            )
+            return
+        if req.local_file_path is None:
+            # No distribution was downloaded for this requirement.
+            return
+
+        download_location = os.path.join(self.download_dir, link.filename)
+        if not os.path.exists(download_location):
+            shutil.copy(req.local_file_path, download_location)
+            download_path = display_path(download_location)
+            logger.info("Saved %s", download_path)
+
+    def prepare_editable_requirement(
+        self,
+        req: InstallRequirement,
+    ) -> BaseDistribution:
+        """Prepare an editable requirement."""
+        assert req.editable, "cannot prepare a non-editable req as editable"
+
+        logger.info("Obtaining %s", req)
+
+        with indent_log():
+            if self.require_hashes:
+                raise InstallationError(
+                    "The editable requirement {} cannot be installed when "
+                    "requiring hashes, because there is no single file to "
+                    "hash.".format(req)
+                )
+            req.ensure_has_source_dir(self.src_dir)
+            req.update_editable()
+            assert req.source_dir
+            req.download_info = direct_url_for_editable(req.unpacked_source_directory)
+
+            dist = _get_prepared_distribution(
+                req,
+                self.build_tracker,
+                self.finder,
+                self.build_isolation,
+                self.check_build_deps,
+            )
+
+            req.check_if_exists(self.use_user_site)
+
+        return dist
+
+    def prepare_installed_requirement(
+        self,
+        req: InstallRequirement,
+        skip_reason: str,
+    ) -> BaseDistribution:
+        """Prepare an already-installed requirement."""
+        assert req.satisfied_by, "req should have been satisfied but isn't"
+        assert skip_reason is not None, (
+            "did not get skip reason skipped but req.satisfied_by "
+            "is set to {}".format(req.satisfied_by)
+        )
+        logger.info(
+            "Requirement %s: %s (%s)", skip_reason, req, req.satisfied_by.version
+        )
+        with indent_log():
+            if self.require_hashes:
+                logger.debug(
+                    "Since it is already installed, we are trusting this "
+                    "package without checking its hash. To ensure a "
+                    "completely repeatable environment, install into an "
+                    "empty virtualenv."
+                )
+            return InstalledDistribution(req).get_metadata_distribution()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/pyproject.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/pyproject.py
new file mode 100644
index 0000000000000000000000000000000000000000..1de9f0fde5da150769d9d467eab24874d8543505
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/pyproject.py
@@ -0,0 +1,174 @@
+import importlib.util
+import os
+from collections import namedtuple
+from typing import Any, List, Optional
+
+from pip._vendor import tomli
+from pip._vendor.packaging.requirements import InvalidRequirement, Requirement
+
+from pip._internal.exceptions import (
+    InstallationError,
+    InvalidPyProjectBuildRequires,
+    MissingPyProjectBuildRequires,
+)
+
+
+def _is_list_of_str(obj: Any) -> bool:
+    return isinstance(obj, list) and all(isinstance(item, str) for item in obj)
+
+
+def make_pyproject_path(unpacked_source_directory: str) -> str:
+    return os.path.join(unpacked_source_directory, "pyproject.toml")
+
+
+BuildSystemDetails = namedtuple(
+    "BuildSystemDetails", ["requires", "backend", "check", "backend_path"]
+)
+
+
+def load_pyproject_toml(
+    use_pep517: Optional[bool], pyproject_toml: str, setup_py: str, req_name: str
+) -> Optional[BuildSystemDetails]:
+    """Load the pyproject.toml file.
+
+    Parameters:
+        use_pep517 - Has the user requested PEP 517 processing? None
+                     means the user hasn't explicitly specified.
+        pyproject_toml - Location of the project's pyproject.toml file
+        setup_py - Location of the project's setup.py file
+        req_name - The name of the requirement we're processing (for
+                   error reporting)
+
+    Returns:
+        None if we should use the legacy code path, otherwise a tuple
+        (
+            requirements from pyproject.toml,
+            name of PEP 517 backend,
+            requirements we should check are installed after setting
+                up the build environment
+            directory paths to import the backend from (backend-path),
+                relative to the project root.
+        )
+    """
+    has_pyproject = os.path.isfile(pyproject_toml)
+    has_setup = os.path.isfile(setup_py)
+
+    if not has_pyproject and not has_setup:
+        raise InstallationError(
+            f"{req_name} does not appear to be a Python project: "
+            f"neither 'setup.py' nor 'pyproject.toml' found."
+        )
+
+    if has_pyproject:
+        with open(pyproject_toml, encoding="utf-8") as f:
+            pp_toml = tomli.loads(f.read())
+        build_system = pp_toml.get("build-system")
+    else:
+        build_system = None
+
+    # The following cases must use PEP 517
+    # We check for use_pep517 being non-None and falsey because that means
+    # the user explicitly requested --no-use-pep517.  The value 0 as
+    # opposed to False can occur when the value is provided via an
+    # environment variable or config file option (due to the quirk of
+    # strtobool() returning an integer in pip's configuration code).
+    if has_pyproject and not has_setup:
+        if use_pep517 is not None and not use_pep517:
+            raise InstallationError(
+                "Disabling PEP 517 processing is invalid: "
+                "project does not have a setup.py"
+            )
+        use_pep517 = True
+    elif build_system and "build-backend" in build_system:
+        if use_pep517 is not None and not use_pep517:
+            raise InstallationError(
+                "Disabling PEP 517 processing is invalid: "
+                "project specifies a build backend of {} "
+                "in pyproject.toml".format(build_system["build-backend"])
+            )
+        use_pep517 = True
+
+    # If we haven't worked out whether to use PEP 517 yet,
+    # and the user hasn't explicitly stated a preference,
+    # we do so if the project has a pyproject.toml file
+    # or if we cannot import setuptools.
+
+    # We fallback to PEP 517 when without setuptools,
+    # so setuptools can be installed as a default build backend.
+    # For more info see:
+    # https://discuss.python.org/t/pip-without-setuptools-could-the-experience-be-improved/11810/9
+    elif use_pep517 is None:
+        use_pep517 = has_pyproject or not importlib.util.find_spec("setuptools")
+
+    # At this point, we know whether we're going to use PEP 517.
+    assert use_pep517 is not None
+
+    # If we're using the legacy code path, there is nothing further
+    # for us to do here.
+    if not use_pep517:
+        return None
+
+    if build_system is None:
+        # Either the user has a pyproject.toml with no build-system
+        # section, or the user has no pyproject.toml, but has opted in
+        # explicitly via --use-pep517.
+        # In the absence of any explicit backend specification, we
+        # assume the setuptools backend that most closely emulates the
+        # traditional direct setup.py execution, and require wheel and
+        # a version of setuptools that supports that backend.
+
+        build_system = {
+            "requires": ["setuptools>=40.8.0", "wheel"],
+            "build-backend": "setuptools.build_meta:__legacy__",
+        }
+
+    # If we're using PEP 517, we have build system information (either
+    # from pyproject.toml, or defaulted by the code above).
+    # Note that at this point, we do not know if the user has actually
+    # specified a backend, though.
+    assert build_system is not None
+
+    # Ensure that the build-system section in pyproject.toml conforms
+    # to PEP 518.
+
+    # Specifying the build-system table but not the requires key is invalid
+    if "requires" not in build_system:
+        raise MissingPyProjectBuildRequires(package=req_name)
+
+    # Error out if requires is not a list of strings
+    requires = build_system["requires"]
+    if not _is_list_of_str(requires):
+        raise InvalidPyProjectBuildRequires(
+            package=req_name,
+            reason="It is not a list of strings.",
+        )
+
+    # Each requirement must be valid as per PEP 508
+    for requirement in requires:
+        try:
+            Requirement(requirement)
+        except InvalidRequirement as error:
+            raise InvalidPyProjectBuildRequires(
+                package=req_name,
+                reason=f"It contains an invalid requirement: {requirement!r}",
+            ) from error
+
+    backend = build_system.get("build-backend")
+    backend_path = build_system.get("backend-path", [])
+    check: List[str] = []
+    if backend is None:
+        # If the user didn't specify a backend, we assume they want to use
+        # the setuptools backend. But we can't be sure they have included
+        # a version of setuptools which supplies the backend. So we
+        # make a note to check that this requirement is present once
+        # we have set up the environment.
+        # This is quite a lot of work to check for a very specific case. But
+        # the problem is, that case is potentially quite common - projects that
+        # adopted PEP 518 early for the ability to specify requirements to
+        # execute setup.py, but never considered needing to mention the build
+        # tools themselves. The original PEP 518 code had a similar check (but
+        # implemented in a different way).
+        backend = "setuptools.build_meta:__legacy__"
+        check = ["setuptools>=40.8.0"]
+
+    return BuildSystemDetails(requires, backend, check, backend_path)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8d56359666869463527be82a7de2e7a04eec165b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/__init__.py
@@ -0,0 +1,94 @@
+import collections
+import logging
+from typing import Generator, List, Optional, Sequence, Tuple
+
+from pip._internal.utils.logging import indent_log
+
+from .req_file import parse_requirements
+from .req_install import InstallRequirement
+from .req_set import RequirementSet
+
+__all__ = [
+    "RequirementSet",
+    "InstallRequirement",
+    "parse_requirements",
+    "install_given_reqs",
+]
+
+logger = logging.getLogger(__name__)
+
+
+class InstallationResult:
+    def __init__(self, name: str) -> None:
+        self.name = name
+
+    def __repr__(self) -> str:
+        return f"InstallationResult(name={self.name!r})"
+
+
+def _validate_requirements(
+    requirements: List[InstallRequirement],
+) -> Generator[Tuple[str, InstallRequirement], None, None]:
+    for req in requirements:
+        assert req.name, f"invalid to-be-installed requirement: {req}"
+        yield req.name, req
+
+
+def install_given_reqs(
+    requirements: List[InstallRequirement],
+    install_options: List[str],
+    global_options: Sequence[str],
+    root: Optional[str],
+    home: Optional[str],
+    prefix: Optional[str],
+    warn_script_location: bool,
+    use_user_site: bool,
+    pycompile: bool,
+) -> List[InstallationResult]:
+    """
+    Install everything in the given list.
+
+    (to be called after having downloaded and unpacked the packages)
+    """
+    to_install = collections.OrderedDict(_validate_requirements(requirements))
+
+    if to_install:
+        logger.info(
+            "Installing collected packages: %s",
+            ", ".join(to_install.keys()),
+        )
+
+    installed = []
+
+    with indent_log():
+        for req_name, requirement in to_install.items():
+            if requirement.should_reinstall:
+                logger.info("Attempting uninstall: %s", req_name)
+                with indent_log():
+                    uninstalled_pathset = requirement.uninstall(auto_confirm=True)
+            else:
+                uninstalled_pathset = None
+
+            try:
+                requirement.install(
+                    install_options,
+                    global_options,
+                    root=root,
+                    home=home,
+                    prefix=prefix,
+                    warn_script_location=warn_script_location,
+                    use_user_site=use_user_site,
+                    pycompile=pycompile,
+                )
+            except Exception:
+                # if install did not succeed, rollback previous uninstall
+                if uninstalled_pathset and not requirement.install_succeeded:
+                    uninstalled_pathset.rollback()
+                raise
+            else:
+                if uninstalled_pathset and requirement.install_succeeded:
+                    uninstalled_pathset.commit()
+
+            installed.append(InstallationResult(req_name))
+
+    return installed
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/constructors.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/constructors.py
new file mode 100644
index 0000000000000000000000000000000000000000..dea7c3b0116267a62f2b79af8be2e19d72eb2d96
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/constructors.py
@@ -0,0 +1,501 @@
+"""Backing implementation for InstallRequirement's various constructors
+
+The idea here is that these formed a major chunk of InstallRequirement's size
+so, moving them and support code dedicated to them outside of that class
+helps creates for better understandability for the rest of the code.
+
+These are meant to be used elsewhere within pip to create instances of
+InstallRequirement.
+"""
+
+import logging
+import os
+import re
+from typing import Any, Dict, Optional, Set, Tuple, Union
+
+from pip._vendor.packaging.markers import Marker
+from pip._vendor.packaging.requirements import InvalidRequirement, Requirement
+from pip._vendor.packaging.specifiers import Specifier
+
+from pip._internal.exceptions import InstallationError
+from pip._internal.models.index import PyPI, TestPyPI
+from pip._internal.models.link import Link
+from pip._internal.models.wheel import Wheel
+from pip._internal.req.req_file import ParsedRequirement
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.utils.filetypes import is_archive_file
+from pip._internal.utils.misc import is_installable_dir
+from pip._internal.utils.packaging import get_requirement
+from pip._internal.utils.urls import path_to_url
+from pip._internal.vcs import is_url, vcs
+
+__all__ = [
+    "install_req_from_editable",
+    "install_req_from_line",
+    "parse_editable",
+]
+
+logger = logging.getLogger(__name__)
+operators = Specifier._operators.keys()
+
+
+def _strip_extras(path: str) -> Tuple[str, Optional[str]]:
+    m = re.match(r"^(.+)(\[[^\]]+\])$", path)
+    extras = None
+    if m:
+        path_no_extras = m.group(1)
+        extras = m.group(2)
+    else:
+        path_no_extras = path
+
+    return path_no_extras, extras
+
+
+def convert_extras(extras: Optional[str]) -> Set[str]:
+    if not extras:
+        return set()
+    return get_requirement("placeholder" + extras.lower()).extras
+
+
+def parse_editable(editable_req: str) -> Tuple[Optional[str], str, Set[str]]:
+    """Parses an editable requirement into:
+        - a requirement name
+        - an URL
+        - extras
+        - editable options
+    Accepted requirements:
+        svn+http://blahblah@rev#egg=Foobar[baz]&subdirectory=version_subdir
+        .[some_extra]
+    """
+
+    url = editable_req
+
+    # If a file path is specified with extras, strip off the extras.
+    url_no_extras, extras = _strip_extras(url)
+
+    if os.path.isdir(url_no_extras):
+        # Treating it as code that has already been checked out
+        url_no_extras = path_to_url(url_no_extras)
+
+    if url_no_extras.lower().startswith("file:"):
+        package_name = Link(url_no_extras).egg_fragment
+        if extras:
+            return (
+                package_name,
+                url_no_extras,
+                get_requirement("placeholder" + extras.lower()).extras,
+            )
+        else:
+            return package_name, url_no_extras, set()
+
+    for version_control in vcs:
+        if url.lower().startswith(f"{version_control}:"):
+            url = f"{version_control}+{url}"
+            break
+
+    link = Link(url)
+
+    if not link.is_vcs:
+        backends = ", ".join(vcs.all_schemes)
+        raise InstallationError(
+            f"{editable_req} is not a valid editable requirement. "
+            f"It should either be a path to a local project or a VCS URL "
+            f"(beginning with {backends})."
+        )
+
+    package_name = link.egg_fragment
+    if not package_name:
+        raise InstallationError(
+            "Could not detect requirement name for '{}', please specify one "
+            "with #egg=your_package_name".format(editable_req)
+        )
+    return package_name, url, set()
+
+
+def check_first_requirement_in_file(filename: str) -> None:
+    """Check if file is parsable as a requirements file.
+
+    This is heavily based on ``pkg_resources.parse_requirements``, but
+    simplified to just check the first meaningful line.
+
+    :raises InvalidRequirement: If the first meaningful line cannot be parsed
+        as an requirement.
+    """
+    with open(filename, encoding="utf-8", errors="ignore") as f:
+        # Create a steppable iterator, so we can handle \-continuations.
+        lines = (
+            line
+            for line in (line.strip() for line in f)
+            if line and not line.startswith("#")  # Skip blank lines/comments.
+        )
+
+        for line in lines:
+            # Drop comments -- a hash without a space may be in a URL.
+            if " #" in line:
+                line = line[: line.find(" #")]
+            # If there is a line continuation, drop it, and append the next line.
+            if line.endswith("\\"):
+                line = line[:-2].strip() + next(lines, "")
+            Requirement(line)
+            return
+
+
+def deduce_helpful_msg(req: str) -> str:
+    """Returns helpful msg in case requirements file does not exist,
+    or cannot be parsed.
+
+    :params req: Requirements file path
+    """
+    if not os.path.exists(req):
+        return f" File '{req}' does not exist."
+    msg = " The path does exist. "
+    # Try to parse and check if it is a requirements file.
+    try:
+        check_first_requirement_in_file(req)
+    except InvalidRequirement:
+        logger.debug("Cannot parse '%s' as requirements file", req)
+    else:
+        msg += (
+            f"The argument you provided "
+            f"({req}) appears to be a"
+            f" requirements file. If that is the"
+            f" case, use the '-r' flag to install"
+            f" the packages specified within it."
+        )
+    return msg
+
+
+class RequirementParts:
+    def __init__(
+        self,
+        requirement: Optional[Requirement],
+        link: Optional[Link],
+        markers: Optional[Marker],
+        extras: Set[str],
+    ):
+        self.requirement = requirement
+        self.link = link
+        self.markers = markers
+        self.extras = extras
+
+
+def parse_req_from_editable(editable_req: str) -> RequirementParts:
+    name, url, extras_override = parse_editable(editable_req)
+
+    if name is not None:
+        try:
+            req: Optional[Requirement] = Requirement(name)
+        except InvalidRequirement:
+            raise InstallationError(f"Invalid requirement: '{name}'")
+    else:
+        req = None
+
+    link = Link(url)
+
+    return RequirementParts(req, link, None, extras_override)
+
+
+# ---- The actual constructors follow ----
+
+
+def install_req_from_editable(
+    editable_req: str,
+    comes_from: Optional[Union[InstallRequirement, str]] = None,
+    use_pep517: Optional[bool] = None,
+    isolated: bool = False,
+    options: Optional[Dict[str, Any]] = None,
+    constraint: bool = False,
+    user_supplied: bool = False,
+    permit_editable_wheels: bool = False,
+    config_settings: Optional[Dict[str, str]] = None,
+) -> InstallRequirement:
+
+    parts = parse_req_from_editable(editable_req)
+
+    return InstallRequirement(
+        parts.requirement,
+        comes_from=comes_from,
+        user_supplied=user_supplied,
+        editable=True,
+        permit_editable_wheels=permit_editable_wheels,
+        link=parts.link,
+        constraint=constraint,
+        use_pep517=use_pep517,
+        isolated=isolated,
+        install_options=options.get("install_options", []) if options else [],
+        global_options=options.get("global_options", []) if options else [],
+        hash_options=options.get("hashes", {}) if options else {},
+        config_settings=config_settings,
+        extras=parts.extras,
+    )
+
+
+def _looks_like_path(name: str) -> bool:
+    """Checks whether the string "looks like" a path on the filesystem.
+
+    This does not check whether the target actually exists, only judge from the
+    appearance.
+
+    Returns true if any of the following conditions is true:
+    * a path separator is found (either os.path.sep or os.path.altsep);
+    * a dot is found (which represents the current directory).
+    """
+    if os.path.sep in name:
+        return True
+    if os.path.altsep is not None and os.path.altsep in name:
+        return True
+    if name.startswith("."):
+        return True
+    return False
+
+
+def _get_url_from_path(path: str, name: str) -> Optional[str]:
+    """
+    First, it checks whether a provided path is an installable directory. If it
+    is, returns the path.
+
+    If false, check if the path is an archive file (such as a .whl).
+    The function checks if the path is a file. If false, if the path has
+    an @, it will treat it as a PEP 440 URL requirement and return the path.
+    """
+    if _looks_like_path(name) and os.path.isdir(path):
+        if is_installable_dir(path):
+            return path_to_url(path)
+        # TODO: The is_installable_dir test here might not be necessary
+        #       now that it is done in load_pyproject_toml too.
+        raise InstallationError(
+            f"Directory {name!r} is not installable. Neither 'setup.py' "
+            "nor 'pyproject.toml' found."
+        )
+    if not is_archive_file(path):
+        return None
+    if os.path.isfile(path):
+        return path_to_url(path)
+    urlreq_parts = name.split("@", 1)
+    if len(urlreq_parts) >= 2 and not _looks_like_path(urlreq_parts[0]):
+        # If the path contains '@' and the part before it does not look
+        # like a path, try to treat it as a PEP 440 URL req instead.
+        return None
+    logger.warning(
+        "Requirement %r looks like a filename, but the file does not exist",
+        name,
+    )
+    return path_to_url(path)
+
+
+def parse_req_from_line(name: str, line_source: Optional[str]) -> RequirementParts:
+    if is_url(name):
+        marker_sep = "; "
+    else:
+        marker_sep = ";"
+    if marker_sep in name:
+        name, markers_as_string = name.split(marker_sep, 1)
+        markers_as_string = markers_as_string.strip()
+        if not markers_as_string:
+            markers = None
+        else:
+            markers = Marker(markers_as_string)
+    else:
+        markers = None
+    name = name.strip()
+    req_as_string = None
+    path = os.path.normpath(os.path.abspath(name))
+    link = None
+    extras_as_string = None
+
+    if is_url(name):
+        link = Link(name)
+    else:
+        p, extras_as_string = _strip_extras(path)
+        url = _get_url_from_path(p, name)
+        if url is not None:
+            link = Link(url)
+
+    # it's a local file, dir, or url
+    if link:
+        # Handle relative file URLs
+        if link.scheme == "file" and re.search(r"\.\./", link.url):
+            link = Link(path_to_url(os.path.normpath(os.path.abspath(link.path))))
+        # wheel file
+        if link.is_wheel:
+            wheel = Wheel(link.filename)  # can raise InvalidWheelFilename
+            req_as_string = f"{wheel.name}=={wheel.version}"
+        else:
+            # set the req to the egg fragment.  when it's not there, this
+            # will become an 'unnamed' requirement
+            req_as_string = link.egg_fragment
+
+    # a requirement specifier
+    else:
+        req_as_string = name
+
+    extras = convert_extras(extras_as_string)
+
+    def with_source(text: str) -> str:
+        if not line_source:
+            return text
+        return f"{text} (from {line_source})"
+
+    def _parse_req_string(req_as_string: str) -> Requirement:
+        try:
+            req = get_requirement(req_as_string)
+        except InvalidRequirement:
+            if os.path.sep in req_as_string:
+                add_msg = "It looks like a path."
+                add_msg += deduce_helpful_msg(req_as_string)
+            elif "=" in req_as_string and not any(
+                op in req_as_string for op in operators
+            ):
+                add_msg = "= is not a valid operator. Did you mean == ?"
+            else:
+                add_msg = ""
+            msg = with_source(f"Invalid requirement: {req_as_string!r}")
+            if add_msg:
+                msg += f"\nHint: {add_msg}"
+            raise InstallationError(msg)
+        else:
+            # Deprecate extras after specifiers: "name>=1.0[extras]"
+            # This currently works by accident because _strip_extras() parses
+            # any extras in the end of the string and those are saved in
+            # RequirementParts
+            for spec in req.specifier:
+                spec_str = str(spec)
+                if spec_str.endswith("]"):
+                    msg = f"Extras after version '{spec_str}'."
+                    raise InstallationError(msg)
+        return req
+
+    if req_as_string is not None:
+        req: Optional[Requirement] = _parse_req_string(req_as_string)
+    else:
+        req = None
+
+    return RequirementParts(req, link, markers, extras)
+
+
+def install_req_from_line(
+    name: str,
+    comes_from: Optional[Union[str, InstallRequirement]] = None,
+    use_pep517: Optional[bool] = None,
+    isolated: bool = False,
+    options: Optional[Dict[str, Any]] = None,
+    constraint: bool = False,
+    line_source: Optional[str] = None,
+    user_supplied: bool = False,
+    config_settings: Optional[Dict[str, str]] = None,
+) -> InstallRequirement:
+    """Creates an InstallRequirement from a name, which might be a
+    requirement, directory containing 'setup.py', filename, or URL.
+
+    :param line_source: An optional string describing where the line is from,
+        for logging purposes in case of an error.
+    """
+    parts = parse_req_from_line(name, line_source)
+
+    return InstallRequirement(
+        parts.requirement,
+        comes_from,
+        link=parts.link,
+        markers=parts.markers,
+        use_pep517=use_pep517,
+        isolated=isolated,
+        install_options=options.get("install_options", []) if options else [],
+        global_options=options.get("global_options", []) if options else [],
+        hash_options=options.get("hashes", {}) if options else {},
+        config_settings=config_settings,
+        constraint=constraint,
+        extras=parts.extras,
+        user_supplied=user_supplied,
+    )
+
+
+def install_req_from_req_string(
+    req_string: str,
+    comes_from: Optional[InstallRequirement] = None,
+    isolated: bool = False,
+    use_pep517: Optional[bool] = None,
+    user_supplied: bool = False,
+    config_settings: Optional[Dict[str, str]] = None,
+) -> InstallRequirement:
+    try:
+        req = get_requirement(req_string)
+    except InvalidRequirement:
+        raise InstallationError(f"Invalid requirement: '{req_string}'")
+
+    domains_not_allowed = [
+        PyPI.file_storage_domain,
+        TestPyPI.file_storage_domain,
+    ]
+    if (
+        req.url
+        and comes_from
+        and comes_from.link
+        and comes_from.link.netloc in domains_not_allowed
+    ):
+        # Explicitly disallow pypi packages that depend on external urls
+        raise InstallationError(
+            "Packages installed from PyPI cannot depend on packages "
+            "which are not also hosted on PyPI.\n"
+            "{} depends on {} ".format(comes_from.name, req)
+        )
+
+    return InstallRequirement(
+        req,
+        comes_from,
+        isolated=isolated,
+        use_pep517=use_pep517,
+        user_supplied=user_supplied,
+        config_settings=config_settings,
+    )
+
+
+def install_req_from_parsed_requirement(
+    parsed_req: ParsedRequirement,
+    isolated: bool = False,
+    use_pep517: Optional[bool] = None,
+    user_supplied: bool = False,
+    config_settings: Optional[Dict[str, str]] = None,
+) -> InstallRequirement:
+    if parsed_req.is_editable:
+        req = install_req_from_editable(
+            parsed_req.requirement,
+            comes_from=parsed_req.comes_from,
+            use_pep517=use_pep517,
+            constraint=parsed_req.constraint,
+            isolated=isolated,
+            user_supplied=user_supplied,
+            config_settings=config_settings,
+        )
+
+    else:
+        req = install_req_from_line(
+            parsed_req.requirement,
+            comes_from=parsed_req.comes_from,
+            use_pep517=use_pep517,
+            isolated=isolated,
+            options=parsed_req.options,
+            constraint=parsed_req.constraint,
+            line_source=parsed_req.line_source,
+            user_supplied=user_supplied,
+            config_settings=config_settings,
+        )
+    return req
+
+
+def install_req_from_link_and_ireq(
+    link: Link, ireq: InstallRequirement
+) -> InstallRequirement:
+    return InstallRequirement(
+        req=ireq.req,
+        comes_from=ireq.comes_from,
+        editable=ireq.editable,
+        link=link,
+        markers=ireq.markers,
+        use_pep517=ireq.use_pep517,
+        isolated=ireq.isolated,
+        install_options=ireq.install_options,
+        global_options=ireq.global_options,
+        hash_options=ireq.hash_options,
+        config_settings=ireq.config_settings,
+        user_supplied=ireq.user_supplied,
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_file.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_file.py
new file mode 100644
index 0000000000000000000000000000000000000000..11ec699acc561cda2ed0392b9e5973464f4b196c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_file.py
@@ -0,0 +1,544 @@
+"""
+Requirements file parsing
+"""
+
+import optparse
+import os
+import re
+import shlex
+import urllib.parse
+from optparse import Values
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    Dict,
+    Generator,
+    Iterable,
+    List,
+    Optional,
+    Tuple,
+)
+
+from pip._internal.cli import cmdoptions
+from pip._internal.exceptions import InstallationError, RequirementsFileParseError
+from pip._internal.models.search_scope import SearchScope
+from pip._internal.network.session import PipSession
+from pip._internal.network.utils import raise_for_status
+from pip._internal.utils.encoding import auto_decode
+from pip._internal.utils.urls import get_url_scheme
+
+if TYPE_CHECKING:
+    # NoReturn introduced in 3.6.2; imported only for type checking to maintain
+    # pip compatibility with older patch versions of Python 3.6
+    from typing import NoReturn
+
+    from pip._internal.index.package_finder import PackageFinder
+
+__all__ = ["parse_requirements"]
+
+ReqFileLines = Iterable[Tuple[int, str]]
+
+LineParser = Callable[[str], Tuple[str, Values]]
+
+SCHEME_RE = re.compile(r"^(http|https|file):", re.I)
+COMMENT_RE = re.compile(r"(^|\s+)#.*$")
+
+# Matches environment variable-style values in '${MY_VARIABLE_1}' with the
+# variable name consisting of only uppercase letters, digits or the '_'
+# (underscore). This follows the POSIX standard defined in IEEE Std 1003.1,
+# 2013 Edition.
+ENV_VAR_RE = re.compile(r"(?P\$\{(?P[A-Z0-9_]+)\})")
+
+SUPPORTED_OPTIONS: List[Callable[..., optparse.Option]] = [
+    cmdoptions.index_url,
+    cmdoptions.extra_index_url,
+    cmdoptions.no_index,
+    cmdoptions.constraints,
+    cmdoptions.requirements,
+    cmdoptions.editable,
+    cmdoptions.find_links,
+    cmdoptions.no_binary,
+    cmdoptions.only_binary,
+    cmdoptions.prefer_binary,
+    cmdoptions.require_hashes,
+    cmdoptions.pre,
+    cmdoptions.trusted_host,
+    cmdoptions.use_new_feature,
+]
+
+# options to be passed to requirements
+SUPPORTED_OPTIONS_REQ: List[Callable[..., optparse.Option]] = [
+    cmdoptions.install_options,
+    cmdoptions.global_options,
+    cmdoptions.hash,
+]
+
+# the 'dest' string values
+SUPPORTED_OPTIONS_REQ_DEST = [str(o().dest) for o in SUPPORTED_OPTIONS_REQ]
+
+
+class ParsedRequirement:
+    def __init__(
+        self,
+        requirement: str,
+        is_editable: bool,
+        comes_from: str,
+        constraint: bool,
+        options: Optional[Dict[str, Any]] = None,
+        line_source: Optional[str] = None,
+    ) -> None:
+        self.requirement = requirement
+        self.is_editable = is_editable
+        self.comes_from = comes_from
+        self.options = options
+        self.constraint = constraint
+        self.line_source = line_source
+
+
+class ParsedLine:
+    def __init__(
+        self,
+        filename: str,
+        lineno: int,
+        args: str,
+        opts: Values,
+        constraint: bool,
+    ) -> None:
+        self.filename = filename
+        self.lineno = lineno
+        self.opts = opts
+        self.constraint = constraint
+
+        if args:
+            self.is_requirement = True
+            self.is_editable = False
+            self.requirement = args
+        elif opts.editables:
+            self.is_requirement = True
+            self.is_editable = True
+            # We don't support multiple -e on one line
+            self.requirement = opts.editables[0]
+        else:
+            self.is_requirement = False
+
+
+def parse_requirements(
+    filename: str,
+    session: PipSession,
+    finder: Optional["PackageFinder"] = None,
+    options: Optional[optparse.Values] = None,
+    constraint: bool = False,
+) -> Generator[ParsedRequirement, None, None]:
+    """Parse a requirements file and yield ParsedRequirement instances.
+
+    :param filename:    Path or url of requirements file.
+    :param session:     PipSession instance.
+    :param finder:      Instance of pip.index.PackageFinder.
+    :param options:     cli options.
+    :param constraint:  If true, parsing a constraint file rather than
+        requirements file.
+    """
+    line_parser = get_line_parser(finder)
+    parser = RequirementsFileParser(session, line_parser)
+
+    for parsed_line in parser.parse(filename, constraint):
+        parsed_req = handle_line(
+            parsed_line, options=options, finder=finder, session=session
+        )
+        if parsed_req is not None:
+            yield parsed_req
+
+
+def preprocess(content: str) -> ReqFileLines:
+    """Split, filter, and join lines, and return a line iterator
+
+    :param content: the content of the requirements file
+    """
+    lines_enum: ReqFileLines = enumerate(content.splitlines(), start=1)
+    lines_enum = join_lines(lines_enum)
+    lines_enum = ignore_comments(lines_enum)
+    lines_enum = expand_env_variables(lines_enum)
+    return lines_enum
+
+
+def handle_requirement_line(
+    line: ParsedLine,
+    options: Optional[optparse.Values] = None,
+) -> ParsedRequirement:
+
+    # preserve for the nested code path
+    line_comes_from = "{} {} (line {})".format(
+        "-c" if line.constraint else "-r",
+        line.filename,
+        line.lineno,
+    )
+
+    assert line.is_requirement
+
+    if line.is_editable:
+        # For editable requirements, we don't support per-requirement
+        # options, so just return the parsed requirement.
+        return ParsedRequirement(
+            requirement=line.requirement,
+            is_editable=line.is_editable,
+            comes_from=line_comes_from,
+            constraint=line.constraint,
+        )
+    else:
+        # get the options that apply to requirements
+        req_options = {}
+        for dest in SUPPORTED_OPTIONS_REQ_DEST:
+            if dest in line.opts.__dict__ and line.opts.__dict__[dest]:
+                req_options[dest] = line.opts.__dict__[dest]
+
+        line_source = f"line {line.lineno} of {line.filename}"
+        return ParsedRequirement(
+            requirement=line.requirement,
+            is_editable=line.is_editable,
+            comes_from=line_comes_from,
+            constraint=line.constraint,
+            options=req_options,
+            line_source=line_source,
+        )
+
+
+def handle_option_line(
+    opts: Values,
+    filename: str,
+    lineno: int,
+    finder: Optional["PackageFinder"] = None,
+    options: Optional[optparse.Values] = None,
+    session: Optional[PipSession] = None,
+) -> None:
+
+    if options:
+        # percolate options upward
+        if opts.require_hashes:
+            options.require_hashes = opts.require_hashes
+        if opts.features_enabled:
+            options.features_enabled.extend(
+                f for f in opts.features_enabled if f not in options.features_enabled
+            )
+
+    # set finder options
+    if finder:
+        find_links = finder.find_links
+        index_urls = finder.index_urls
+        no_index = finder.search_scope.no_index
+        if opts.no_index is True:
+            no_index = True
+            index_urls = []
+        if opts.index_url and not no_index:
+            index_urls = [opts.index_url]
+        if opts.extra_index_urls and not no_index:
+            index_urls.extend(opts.extra_index_urls)
+        if opts.find_links:
+            # FIXME: it would be nice to keep track of the source
+            # of the find_links: support a find-links local path
+            # relative to a requirements file.
+            value = opts.find_links[0]
+            req_dir = os.path.dirname(os.path.abspath(filename))
+            relative_to_reqs_file = os.path.join(req_dir, value)
+            if os.path.exists(relative_to_reqs_file):
+                value = relative_to_reqs_file
+            find_links.append(value)
+
+        if session:
+            # We need to update the auth urls in session
+            session.update_index_urls(index_urls)
+
+        search_scope = SearchScope(
+            find_links=find_links,
+            index_urls=index_urls,
+            no_index=no_index,
+        )
+        finder.search_scope = search_scope
+
+        if opts.pre:
+            finder.set_allow_all_prereleases()
+
+        if opts.prefer_binary:
+            finder.set_prefer_binary()
+
+        if session:
+            for host in opts.trusted_hosts or []:
+                source = f"line {lineno} of {filename}"
+                session.add_trusted_host(host, source=source)
+
+
+def handle_line(
+    line: ParsedLine,
+    options: Optional[optparse.Values] = None,
+    finder: Optional["PackageFinder"] = None,
+    session: Optional[PipSession] = None,
+) -> Optional[ParsedRequirement]:
+    """Handle a single parsed requirements line; This can result in
+    creating/yielding requirements, or updating the finder.
+
+    :param line:        The parsed line to be processed.
+    :param options:     CLI options.
+    :param finder:      The finder - updated by non-requirement lines.
+    :param session:     The session - updated by non-requirement lines.
+
+    Returns a ParsedRequirement object if the line is a requirement line,
+    otherwise returns None.
+
+    For lines that contain requirements, the only options that have an effect
+    are from SUPPORTED_OPTIONS_REQ, and they are scoped to the
+    requirement. Other options from SUPPORTED_OPTIONS may be present, but are
+    ignored.
+
+    For lines that do not contain requirements, the only options that have an
+    effect are from SUPPORTED_OPTIONS. Options from SUPPORTED_OPTIONS_REQ may
+    be present, but are ignored. These lines may contain multiple options
+    (although our docs imply only one is supported), and all our parsed and
+    affect the finder.
+    """
+
+    if line.is_requirement:
+        parsed_req = handle_requirement_line(line, options)
+        return parsed_req
+    else:
+        handle_option_line(
+            line.opts,
+            line.filename,
+            line.lineno,
+            finder,
+            options,
+            session,
+        )
+        return None
+
+
+class RequirementsFileParser:
+    def __init__(
+        self,
+        session: PipSession,
+        line_parser: LineParser,
+    ) -> None:
+        self._session = session
+        self._line_parser = line_parser
+
+    def parse(
+        self, filename: str, constraint: bool
+    ) -> Generator[ParsedLine, None, None]:
+        """Parse a given file, yielding parsed lines."""
+        yield from self._parse_and_recurse(filename, constraint)
+
+    def _parse_and_recurse(
+        self, filename: str, constraint: bool
+    ) -> Generator[ParsedLine, None, None]:
+        for line in self._parse_file(filename, constraint):
+            if not line.is_requirement and (
+                line.opts.requirements or line.opts.constraints
+            ):
+                # parse a nested requirements file
+                if line.opts.requirements:
+                    req_path = line.opts.requirements[0]
+                    nested_constraint = False
+                else:
+                    req_path = line.opts.constraints[0]
+                    nested_constraint = True
+
+                # original file is over http
+                if SCHEME_RE.search(filename):
+                    # do a url join so relative paths work
+                    req_path = urllib.parse.urljoin(filename, req_path)
+                # original file and nested file are paths
+                elif not SCHEME_RE.search(req_path):
+                    # do a join so relative paths work
+                    req_path = os.path.join(
+                        os.path.dirname(filename),
+                        req_path,
+                    )
+
+                yield from self._parse_and_recurse(req_path, nested_constraint)
+            else:
+                yield line
+
+    def _parse_file(
+        self, filename: str, constraint: bool
+    ) -> Generator[ParsedLine, None, None]:
+        _, content = get_file_content(filename, self._session)
+
+        lines_enum = preprocess(content)
+
+        for line_number, line in lines_enum:
+            try:
+                args_str, opts = self._line_parser(line)
+            except OptionParsingError as e:
+                # add offending line
+                msg = f"Invalid requirement: {line}\n{e.msg}"
+                raise RequirementsFileParseError(msg)
+
+            yield ParsedLine(
+                filename,
+                line_number,
+                args_str,
+                opts,
+                constraint,
+            )
+
+
+def get_line_parser(finder: Optional["PackageFinder"]) -> LineParser:
+    def parse_line(line: str) -> Tuple[str, Values]:
+        # Build new parser for each line since it accumulates appendable
+        # options.
+        parser = build_parser()
+        defaults = parser.get_default_values()
+        defaults.index_url = None
+        if finder:
+            defaults.format_control = finder.format_control
+
+        args_str, options_str = break_args_options(line)
+
+        try:
+            options = shlex.split(options_str)
+        except ValueError as e:
+            raise OptionParsingError(f"Could not split options: {options_str}") from e
+
+        opts, _ = parser.parse_args(options, defaults)
+
+        return args_str, opts
+
+    return parse_line
+
+
+def break_args_options(line: str) -> Tuple[str, str]:
+    """Break up the line into an args and options string.  We only want to shlex
+    (and then optparse) the options, not the args.  args can contain markers
+    which are corrupted by shlex.
+    """
+    tokens = line.split(" ")
+    args = []
+    options = tokens[:]
+    for token in tokens:
+        if token.startswith("-") or token.startswith("--"):
+            break
+        else:
+            args.append(token)
+            options.pop(0)
+    return " ".join(args), " ".join(options)
+
+
+class OptionParsingError(Exception):
+    def __init__(self, msg: str) -> None:
+        self.msg = msg
+
+
+def build_parser() -> optparse.OptionParser:
+    """
+    Return a parser for parsing requirement lines
+    """
+    parser = optparse.OptionParser(add_help_option=False)
+
+    option_factories = SUPPORTED_OPTIONS + SUPPORTED_OPTIONS_REQ
+    for option_factory in option_factories:
+        option = option_factory()
+        parser.add_option(option)
+
+    # By default optparse sys.exits on parsing errors. We want to wrap
+    # that in our own exception.
+    def parser_exit(self: Any, msg: str) -> "NoReturn":
+        raise OptionParsingError(msg)
+
+    # NOTE: mypy disallows assigning to a method
+    #       https://github.com/python/mypy/issues/2427
+    parser.exit = parser_exit  # type: ignore
+
+    return parser
+
+
+def join_lines(lines_enum: ReqFileLines) -> ReqFileLines:
+    """Joins a line ending in '\' with the previous line (except when following
+    comments).  The joined line takes on the index of the first line.
+    """
+    primary_line_number = None
+    new_line: List[str] = []
+    for line_number, line in lines_enum:
+        if not line.endswith("\\") or COMMENT_RE.match(line):
+            if COMMENT_RE.match(line):
+                # this ensures comments are always matched later
+                line = " " + line
+            if new_line:
+                new_line.append(line)
+                assert primary_line_number is not None
+                yield primary_line_number, "".join(new_line)
+                new_line = []
+            else:
+                yield line_number, line
+        else:
+            if not new_line:
+                primary_line_number = line_number
+            new_line.append(line.strip("\\"))
+
+    # last line contains \
+    if new_line:
+        assert primary_line_number is not None
+        yield primary_line_number, "".join(new_line)
+
+    # TODO: handle space after '\'.
+
+
+def ignore_comments(lines_enum: ReqFileLines) -> ReqFileLines:
+    """
+    Strips comments and filter empty lines.
+    """
+    for line_number, line in lines_enum:
+        line = COMMENT_RE.sub("", line)
+        line = line.strip()
+        if line:
+            yield line_number, line
+
+
+def expand_env_variables(lines_enum: ReqFileLines) -> ReqFileLines:
+    """Replace all environment variables that can be retrieved via `os.getenv`.
+
+    The only allowed format for environment variables defined in the
+    requirement file is `${MY_VARIABLE_1}` to ensure two things:
+
+    1. Strings that contain a `$` aren't accidentally (partially) expanded.
+    2. Ensure consistency across platforms for requirement files.
+
+    These points are the result of a discussion on the `github pull
+    request #3514 `_.
+
+    Valid characters in variable names follow the `POSIX standard
+    `_ and are limited
+    to uppercase letter, digits and the `_` (underscore).
+    """
+    for line_number, line in lines_enum:
+        for env_var, var_name in ENV_VAR_RE.findall(line):
+            value = os.getenv(var_name)
+            if not value:
+                continue
+
+            line = line.replace(env_var, value)
+
+        yield line_number, line
+
+
+def get_file_content(url: str, session: PipSession) -> Tuple[str, str]:
+    """Gets the content of a file; it may be a filename, file: URL, or
+    http: URL.  Returns (location, content).  Content is unicode.
+    Respects # -*- coding: declarations on the retrieved files.
+
+    :param url:         File path or url.
+    :param session:     PipSession instance.
+    """
+    scheme = get_url_scheme(url)
+
+    # Pip has special support for file:// URLs (LocalFSAdapter).
+    if scheme in ["http", "https", "file"]:
+        resp = session.get(url)
+        raise_for_status(resp)
+        return resp.url, resp.text
+
+    # Assume this is a bare path.
+    try:
+        with open(url, "rb") as f:
+            content = auto_decode(f.read())
+    except OSError as exc:
+        raise InstallationError(f"Could not open requirements file: {exc}")
+    return url, content
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_install.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_install.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb38ec09da4f5d4ec24ee168fc6dba1e3aa8267a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_install.py
@@ -0,0 +1,946 @@
+# The following comment should be removed at some point in the future.
+# mypy: strict-optional=False
+
+import functools
+import logging
+import os
+import shutil
+import sys
+import uuid
+import zipfile
+from enum import Enum
+from optparse import Values
+from typing import Any, Collection, Dict, Iterable, List, Optional, Sequence, Union
+
+from pip._vendor.packaging.markers import Marker
+from pip._vendor.packaging.requirements import Requirement
+from pip._vendor.packaging.specifiers import SpecifierSet
+from pip._vendor.packaging.utils import canonicalize_name
+from pip._vendor.packaging.version import Version
+from pip._vendor.packaging.version import parse as parse_version
+from pip._vendor.pyproject_hooks import BuildBackendHookCaller
+
+from pip._internal.build_env import BuildEnvironment, NoOpBuildEnvironment
+from pip._internal.exceptions import InstallationError, LegacyInstallFailure
+from pip._internal.locations import get_scheme
+from pip._internal.metadata import (
+    BaseDistribution,
+    get_default_environment,
+    get_directory_distribution,
+    get_wheel_distribution,
+)
+from pip._internal.metadata.base import FilesystemWheel
+from pip._internal.models.direct_url import DirectUrl
+from pip._internal.models.link import Link
+from pip._internal.operations.build.metadata import generate_metadata
+from pip._internal.operations.build.metadata_editable import generate_editable_metadata
+from pip._internal.operations.build.metadata_legacy import (
+    generate_metadata as generate_metadata_legacy,
+)
+from pip._internal.operations.install.editable_legacy import (
+    install_editable as install_editable_legacy,
+)
+from pip._internal.operations.install.legacy import install as install_legacy
+from pip._internal.operations.install.wheel import install_wheel
+from pip._internal.pyproject import load_pyproject_toml, make_pyproject_path
+from pip._internal.req.req_uninstall import UninstallPathSet
+from pip._internal.utils.deprecation import LegacyInstallReason, deprecated
+from pip._internal.utils.direct_url_helpers import (
+    direct_url_for_editable,
+    direct_url_from_link,
+)
+from pip._internal.utils.hashes import Hashes
+from pip._internal.utils.misc import (
+    ConfiguredBuildBackendHookCaller,
+    ask_path_exists,
+    backup_dir,
+    display_path,
+    hide_url,
+    redact_auth_from_url,
+)
+from pip._internal.utils.packaging import safe_extra
+from pip._internal.utils.subprocess import runner_with_spinner_message
+from pip._internal.utils.temp_dir import TempDirectory, tempdir_kinds
+from pip._internal.utils.virtualenv import running_under_virtualenv
+from pip._internal.vcs import vcs
+
+logger = logging.getLogger(__name__)
+
+
+class InstallRequirement:
+    """
+    Represents something that may be installed later on, may have information
+    about where to fetch the relevant requirement and also contains logic for
+    installing the said requirement.
+    """
+
+    def __init__(
+        self,
+        req: Optional[Requirement],
+        comes_from: Optional[Union[str, "InstallRequirement"]],
+        editable: bool = False,
+        link: Optional[Link] = None,
+        markers: Optional[Marker] = None,
+        use_pep517: Optional[bool] = None,
+        isolated: bool = False,
+        install_options: Optional[List[str]] = None,
+        global_options: Optional[List[str]] = None,
+        hash_options: Optional[Dict[str, List[str]]] = None,
+        config_settings: Optional[Dict[str, str]] = None,
+        constraint: bool = False,
+        extras: Collection[str] = (),
+        user_supplied: bool = False,
+        permit_editable_wheels: bool = False,
+    ) -> None:
+        assert req is None or isinstance(req, Requirement), req
+        self.req = req
+        self.comes_from = comes_from
+        self.constraint = constraint
+        self.editable = editable
+        self.permit_editable_wheels = permit_editable_wheels
+        self.legacy_install_reason: Optional[LegacyInstallReason] = None
+
+        # source_dir is the local directory where the linked requirement is
+        # located, or unpacked. In case unpacking is needed, creating and
+        # populating source_dir is done by the RequirementPreparer. Note this
+        # is not necessarily the directory where pyproject.toml or setup.py is
+        # located - that one is obtained via unpacked_source_directory.
+        self.source_dir: Optional[str] = None
+        if self.editable:
+            assert link
+            if link.is_file:
+                self.source_dir = os.path.normpath(os.path.abspath(link.file_path))
+
+        if link is None and req and req.url:
+            # PEP 508 URL requirement
+            link = Link(req.url)
+        self.link = self.original_link = link
+        self.original_link_is_in_wheel_cache = False
+
+        # Information about the location of the artifact that was downloaded . This
+        # property is guaranteed to be set in resolver results.
+        self.download_info: Optional[DirectUrl] = None
+
+        # Path to any downloaded or already-existing package.
+        self.local_file_path: Optional[str] = None
+        if self.link and self.link.is_file:
+            self.local_file_path = self.link.file_path
+
+        if extras:
+            self.extras = extras
+        elif req:
+            self.extras = {safe_extra(extra) for extra in req.extras}
+        else:
+            self.extras = set()
+        if markers is None and req:
+            markers = req.marker
+        self.markers = markers
+
+        # This holds the Distribution object if this requirement is already installed.
+        self.satisfied_by: Optional[BaseDistribution] = None
+        # Whether the installation process should try to uninstall an existing
+        # distribution before installing this requirement.
+        self.should_reinstall = False
+        # Temporary build location
+        self._temp_build_dir: Optional[TempDirectory] = None
+        # Set to True after successful installation
+        self.install_succeeded: Optional[bool] = None
+        # Supplied options
+        self.install_options = install_options if install_options else []
+        self.global_options = global_options if global_options else []
+        self.hash_options = hash_options if hash_options else {}
+        self.config_settings = config_settings
+        # Set to True after successful preparation of this requirement
+        self.prepared = False
+        # User supplied requirement are explicitly requested for installation
+        # by the user via CLI arguments or requirements files, as opposed to,
+        # e.g. dependencies, extras or constraints.
+        self.user_supplied = user_supplied
+
+        self.isolated = isolated
+        self.build_env: BuildEnvironment = NoOpBuildEnvironment()
+
+        # For PEP 517, the directory where we request the project metadata
+        # gets stored. We need this to pass to build_wheel, so the backend
+        # can ensure that the wheel matches the metadata (see the PEP for
+        # details).
+        self.metadata_directory: Optional[str] = None
+
+        # The static build requirements (from pyproject.toml)
+        self.pyproject_requires: Optional[List[str]] = None
+
+        # Build requirements that we will check are available
+        self.requirements_to_check: List[str] = []
+
+        # The PEP 517 backend we should use to build the project
+        self.pep517_backend: Optional[BuildBackendHookCaller] = None
+
+        # Are we using PEP 517 for this requirement?
+        # After pyproject.toml has been loaded, the only valid values are True
+        # and False. Before loading, None is valid (meaning "use the default").
+        # Setting an explicit value before loading pyproject.toml is supported,
+        # but after loading this flag should be treated as read only.
+        self.use_pep517 = use_pep517
+
+        # This requirement needs more preparation before it can be built
+        self.needs_more_preparation = False
+
+    def __str__(self) -> str:
+        if self.req:
+            s = str(self.req)
+            if self.link:
+                s += " from {}".format(redact_auth_from_url(self.link.url))
+        elif self.link:
+            s = redact_auth_from_url(self.link.url)
+        else:
+            s = ""
+        if self.satisfied_by is not None:
+            if self.satisfied_by.location is not None:
+                location = display_path(self.satisfied_by.location)
+            else:
+                location = ""
+            s += f" in {location}"
+        if self.comes_from:
+            if isinstance(self.comes_from, str):
+                comes_from: Optional[str] = self.comes_from
+            else:
+                comes_from = self.comes_from.from_path()
+            if comes_from:
+                s += f" (from {comes_from})"
+        return s
+
+    def __repr__(self) -> str:
+        return "<{} object: {} editable={!r}>".format(
+            self.__class__.__name__, str(self), self.editable
+        )
+
+    def format_debug(self) -> str:
+        """An un-tested helper for getting state, for debugging."""
+        attributes = vars(self)
+        names = sorted(attributes)
+
+        state = ("{}={!r}".format(attr, attributes[attr]) for attr in sorted(names))
+        return "<{name} object: {{{state}}}>".format(
+            name=self.__class__.__name__,
+            state=", ".join(state),
+        )
+
+    # Things that are valid for all kinds of requirements?
+    @property
+    def name(self) -> Optional[str]:
+        if self.req is None:
+            return None
+        return self.req.name
+
+    @functools.lru_cache()  # use cached_property in python 3.8+
+    def supports_pyproject_editable(self) -> bool:
+        if not self.use_pep517:
+            return False
+        assert self.pep517_backend
+        with self.build_env:
+            runner = runner_with_spinner_message(
+                "Checking if build backend supports build_editable"
+            )
+            with self.pep517_backend.subprocess_runner(runner):
+                return "build_editable" in self.pep517_backend._supported_features()
+
+    @property
+    def specifier(self) -> SpecifierSet:
+        return self.req.specifier
+
+    @property
+    def is_pinned(self) -> bool:
+        """Return whether I am pinned to an exact version.
+
+        For example, some-package==1.2 is pinned; some-package>1.2 is not.
+        """
+        specifiers = self.specifier
+        return len(specifiers) == 1 and next(iter(specifiers)).operator in {"==", "==="}
+
+    def match_markers(self, extras_requested: Optional[Iterable[str]] = None) -> bool:
+        if not extras_requested:
+            # Provide an extra to safely evaluate the markers
+            # without matching any extra
+            extras_requested = ("",)
+        if self.markers is not None:
+            return any(
+                self.markers.evaluate({"extra": extra}) for extra in extras_requested
+            )
+        else:
+            return True
+
+    @property
+    def has_hash_options(self) -> bool:
+        """Return whether any known-good hashes are specified as options.
+
+        These activate --require-hashes mode; hashes specified as part of a
+        URL do not.
+
+        """
+        return bool(self.hash_options)
+
+    def hashes(self, trust_internet: bool = True) -> Hashes:
+        """Return a hash-comparer that considers my option- and URL-based
+        hashes to be known-good.
+
+        Hashes in URLs--ones embedded in the requirements file, not ones
+        downloaded from an index server--are almost peers with ones from
+        flags. They satisfy --require-hashes (whether it was implicitly or
+        explicitly activated) but do not activate it. md5 and sha224 are not
+        allowed in flags, which should nudge people toward good algos. We
+        always OR all hashes together, even ones from URLs.
+
+        :param trust_internet: Whether to trust URL-based (#md5=...) hashes
+            downloaded from the internet, as by populate_link()
+
+        """
+        good_hashes = self.hash_options.copy()
+        link = self.link if trust_internet else self.original_link
+        if link and link.hash:
+            good_hashes.setdefault(link.hash_name, []).append(link.hash)
+        return Hashes(good_hashes)
+
+    def from_path(self) -> Optional[str]:
+        """Format a nice indicator to show where this "comes from" """
+        if self.req is None:
+            return None
+        s = str(self.req)
+        if self.comes_from:
+            if isinstance(self.comes_from, str):
+                comes_from = self.comes_from
+            else:
+                comes_from = self.comes_from.from_path()
+            if comes_from:
+                s += "->" + comes_from
+        return s
+
+    def ensure_build_location(
+        self, build_dir: str, autodelete: bool, parallel_builds: bool
+    ) -> str:
+        assert build_dir is not None
+        if self._temp_build_dir is not None:
+            assert self._temp_build_dir.path
+            return self._temp_build_dir.path
+        if self.req is None:
+            # Some systems have /tmp as a symlink which confuses custom
+            # builds (such as numpy). Thus, we ensure that the real path
+            # is returned.
+            self._temp_build_dir = TempDirectory(
+                kind=tempdir_kinds.REQ_BUILD, globally_managed=True
+            )
+
+            return self._temp_build_dir.path
+
+        # This is the only remaining place where we manually determine the path
+        # for the temporary directory. It is only needed for editables where
+        # it is the value of the --src option.
+
+        # When parallel builds are enabled, add a UUID to the build directory
+        # name so multiple builds do not interfere with each other.
+        dir_name: str = canonicalize_name(self.name)
+        if parallel_builds:
+            dir_name = f"{dir_name}_{uuid.uuid4().hex}"
+
+        # FIXME: Is there a better place to create the build_dir? (hg and bzr
+        # need this)
+        if not os.path.exists(build_dir):
+            logger.debug("Creating directory %s", build_dir)
+            os.makedirs(build_dir)
+        actual_build_dir = os.path.join(build_dir, dir_name)
+        # `None` indicates that we respect the globally-configured deletion
+        # settings, which is what we actually want when auto-deleting.
+        delete_arg = None if autodelete else False
+        return TempDirectory(
+            path=actual_build_dir,
+            delete=delete_arg,
+            kind=tempdir_kinds.REQ_BUILD,
+            globally_managed=True,
+        ).path
+
+    def _set_requirement(self) -> None:
+        """Set requirement after generating metadata."""
+        assert self.req is None
+        assert self.metadata is not None
+        assert self.source_dir is not None
+
+        # Construct a Requirement object from the generated metadata
+        if isinstance(parse_version(self.metadata["Version"]), Version):
+            op = "=="
+        else:
+            op = "==="
+
+        self.req = Requirement(
+            "".join(
+                [
+                    self.metadata["Name"],
+                    op,
+                    self.metadata["Version"],
+                ]
+            )
+        )
+
+    def warn_on_mismatching_name(self) -> None:
+        metadata_name = canonicalize_name(self.metadata["Name"])
+        if canonicalize_name(self.req.name) == metadata_name:
+            # Everything is fine.
+            return
+
+        # If we're here, there's a mismatch. Log a warning about it.
+        logger.warning(
+            "Generating metadata for package %s "
+            "produced metadata for project name %s. Fix your "
+            "#egg=%s fragments.",
+            self.name,
+            metadata_name,
+            self.name,
+        )
+        self.req = Requirement(metadata_name)
+
+    def check_if_exists(self, use_user_site: bool) -> None:
+        """Find an installed distribution that satisfies or conflicts
+        with this requirement, and set self.satisfied_by or
+        self.should_reinstall appropriately.
+        """
+        if self.req is None:
+            return
+        existing_dist = get_default_environment().get_distribution(self.req.name)
+        if not existing_dist:
+            return
+
+        version_compatible = self.req.specifier.contains(
+            existing_dist.version,
+            prereleases=True,
+        )
+        if not version_compatible:
+            self.satisfied_by = None
+            if use_user_site:
+                if existing_dist.in_usersite:
+                    self.should_reinstall = True
+                elif running_under_virtualenv() and existing_dist.in_site_packages:
+                    raise InstallationError(
+                        f"Will not install to the user site because it will "
+                        f"lack sys.path precedence to {existing_dist.raw_name} "
+                        f"in {existing_dist.location}"
+                    )
+            else:
+                self.should_reinstall = True
+        else:
+            if self.editable:
+                self.should_reinstall = True
+                # when installing editables, nothing pre-existing should ever
+                # satisfy
+                self.satisfied_by = None
+            else:
+                self.satisfied_by = existing_dist
+
+    # Things valid for wheels
+    @property
+    def is_wheel(self) -> bool:
+        if not self.link:
+            return False
+        return self.link.is_wheel
+
+    # Things valid for sdists
+    @property
+    def unpacked_source_directory(self) -> str:
+        return os.path.join(
+            self.source_dir, self.link and self.link.subdirectory_fragment or ""
+        )
+
+    @property
+    def setup_py_path(self) -> str:
+        assert self.source_dir, f"No source dir for {self}"
+        setup_py = os.path.join(self.unpacked_source_directory, "setup.py")
+
+        return setup_py
+
+    @property
+    def setup_cfg_path(self) -> str:
+        assert self.source_dir, f"No source dir for {self}"
+        setup_cfg = os.path.join(self.unpacked_source_directory, "setup.cfg")
+
+        return setup_cfg
+
+    @property
+    def pyproject_toml_path(self) -> str:
+        assert self.source_dir, f"No source dir for {self}"
+        return make_pyproject_path(self.unpacked_source_directory)
+
+    def load_pyproject_toml(self) -> None:
+        """Load the pyproject.toml file.
+
+        After calling this routine, all of the attributes related to PEP 517
+        processing for this requirement have been set. In particular, the
+        use_pep517 attribute can be used to determine whether we should
+        follow the PEP 517 or legacy (setup.py) code path.
+        """
+        pyproject_toml_data = load_pyproject_toml(
+            self.use_pep517, self.pyproject_toml_path, self.setup_py_path, str(self)
+        )
+
+        if pyproject_toml_data is None:
+            self.use_pep517 = False
+            return
+
+        self.use_pep517 = True
+        requires, backend, check, backend_path = pyproject_toml_data
+        self.requirements_to_check = check
+        self.pyproject_requires = requires
+        self.pep517_backend = ConfiguredBuildBackendHookCaller(
+            self,
+            self.unpacked_source_directory,
+            backend,
+            backend_path=backend_path,
+        )
+
+    def isolated_editable_sanity_check(self) -> None:
+        """Check that an editable requirement if valid for use with PEP 517/518.
+
+        This verifies that an editable that has a pyproject.toml either supports PEP 660
+        or as a setup.py or a setup.cfg
+        """
+        if (
+            self.editable
+            and self.use_pep517
+            and not self.supports_pyproject_editable()
+            and not os.path.isfile(self.setup_py_path)
+            and not os.path.isfile(self.setup_cfg_path)
+        ):
+            raise InstallationError(
+                f"Project {self} has a 'pyproject.toml' and its build "
+                f"backend is missing the 'build_editable' hook. Since it does not "
+                f"have a 'setup.py' nor a 'setup.cfg', "
+                f"it cannot be installed in editable mode. "
+                f"Consider using a build backend that supports PEP 660."
+            )
+
+    def prepare_metadata(self) -> None:
+        """Ensure that project metadata is available.
+
+        Under PEP 517 and PEP 660, call the backend hook to prepare the metadata.
+        Under legacy processing, call setup.py egg-info.
+        """
+        assert self.source_dir
+        details = self.name or f"from {self.link}"
+
+        if self.use_pep517:
+            assert self.pep517_backend is not None
+            if (
+                self.editable
+                and self.permit_editable_wheels
+                and self.supports_pyproject_editable()
+            ):
+                self.metadata_directory = generate_editable_metadata(
+                    build_env=self.build_env,
+                    backend=self.pep517_backend,
+                    details=details,
+                )
+            else:
+                self.metadata_directory = generate_metadata(
+                    build_env=self.build_env,
+                    backend=self.pep517_backend,
+                    details=details,
+                )
+        else:
+            self.metadata_directory = generate_metadata_legacy(
+                build_env=self.build_env,
+                setup_py_path=self.setup_py_path,
+                source_dir=self.unpacked_source_directory,
+                isolated=self.isolated,
+                details=details,
+            )
+
+        # Act on the newly generated metadata, based on the name and version.
+        if not self.name:
+            self._set_requirement()
+        else:
+            self.warn_on_mismatching_name()
+
+        self.assert_source_matches_version()
+
+    @property
+    def metadata(self) -> Any:
+        if not hasattr(self, "_metadata"):
+            self._metadata = self.get_dist().metadata
+
+        return self._metadata
+
+    def get_dist(self) -> BaseDistribution:
+        if self.metadata_directory:
+            return get_directory_distribution(self.metadata_directory)
+        elif self.local_file_path and self.is_wheel:
+            return get_wheel_distribution(
+                FilesystemWheel(self.local_file_path), canonicalize_name(self.name)
+            )
+        raise AssertionError(
+            f"InstallRequirement {self} has no metadata directory and no wheel: "
+            f"can't make a distribution."
+        )
+
+    def assert_source_matches_version(self) -> None:
+        assert self.source_dir
+        version = self.metadata["version"]
+        if self.req.specifier and version not in self.req.specifier:
+            logger.warning(
+                "Requested %s, but installing version %s",
+                self,
+                version,
+            )
+        else:
+            logger.debug(
+                "Source in %s has version %s, which satisfies requirement %s",
+                display_path(self.source_dir),
+                version,
+                self,
+            )
+
+    # For both source distributions and editables
+    def ensure_has_source_dir(
+        self,
+        parent_dir: str,
+        autodelete: bool = False,
+        parallel_builds: bool = False,
+    ) -> None:
+        """Ensure that a source_dir is set.
+
+        This will create a temporary build dir if the name of the requirement
+        isn't known yet.
+
+        :param parent_dir: The ideal pip parent_dir for the source_dir.
+            Generally src_dir for editables and build_dir for sdists.
+        :return: self.source_dir
+        """
+        if self.source_dir is None:
+            self.source_dir = self.ensure_build_location(
+                parent_dir,
+                autodelete=autodelete,
+                parallel_builds=parallel_builds,
+            )
+
+    # For editable installations
+    def update_editable(self) -> None:
+        if not self.link:
+            logger.debug(
+                "Cannot update repository at %s; repository location is unknown",
+                self.source_dir,
+            )
+            return
+        assert self.editable
+        assert self.source_dir
+        if self.link.scheme == "file":
+            # Static paths don't get updated
+            return
+        vcs_backend = vcs.get_backend_for_scheme(self.link.scheme)
+        # Editable requirements are validated in Requirement constructors.
+        # So here, if it's neither a path nor a valid VCS URL, it's a bug.
+        assert vcs_backend, f"Unsupported VCS URL {self.link.url}"
+        hidden_url = hide_url(self.link.url)
+        vcs_backend.obtain(self.source_dir, url=hidden_url, verbosity=0)
+
+    # Top-level Actions
+    def uninstall(
+        self, auto_confirm: bool = False, verbose: bool = False
+    ) -> Optional[UninstallPathSet]:
+        """
+        Uninstall the distribution currently satisfying this requirement.
+
+        Prompts before removing or modifying files unless
+        ``auto_confirm`` is True.
+
+        Refuses to delete or modify files outside of ``sys.prefix`` -
+        thus uninstallation within a virtual environment can only
+        modify that virtual environment, even if the virtualenv is
+        linked to global site-packages.
+
+        """
+        assert self.req
+        dist = get_default_environment().get_distribution(self.req.name)
+        if not dist:
+            logger.warning("Skipping %s as it is not installed.", self.name)
+            return None
+        logger.info("Found existing installation: %s", dist)
+
+        uninstalled_pathset = UninstallPathSet.from_dist(dist)
+        uninstalled_pathset.remove(auto_confirm, verbose)
+        return uninstalled_pathset
+
+    def _get_archive_name(self, path: str, parentdir: str, rootdir: str) -> str:
+        def _clean_zip_name(name: str, prefix: str) -> str:
+            assert name.startswith(
+                prefix + os.path.sep
+            ), f"name {name!r} doesn't start with prefix {prefix!r}"
+            name = name[len(prefix) + 1 :]
+            name = name.replace(os.path.sep, "/")
+            return name
+
+        path = os.path.join(parentdir, path)
+        name = _clean_zip_name(path, rootdir)
+        return self.name + "/" + name
+
+    def archive(self, build_dir: Optional[str]) -> None:
+        """Saves archive to provided build_dir.
+
+        Used for saving downloaded VCS requirements as part of `pip download`.
+        """
+        assert self.source_dir
+        if build_dir is None:
+            return
+
+        create_archive = True
+        archive_name = "{}-{}.zip".format(self.name, self.metadata["version"])
+        archive_path = os.path.join(build_dir, archive_name)
+
+        if os.path.exists(archive_path):
+            response = ask_path_exists(
+                "The file {} exists. (i)gnore, (w)ipe, "
+                "(b)ackup, (a)bort ".format(display_path(archive_path)),
+                ("i", "w", "b", "a"),
+            )
+            if response == "i":
+                create_archive = False
+            elif response == "w":
+                logger.warning("Deleting %s", display_path(archive_path))
+                os.remove(archive_path)
+            elif response == "b":
+                dest_file = backup_dir(archive_path)
+                logger.warning(
+                    "Backing up %s to %s",
+                    display_path(archive_path),
+                    display_path(dest_file),
+                )
+                shutil.move(archive_path, dest_file)
+            elif response == "a":
+                sys.exit(-1)
+
+        if not create_archive:
+            return
+
+        zip_output = zipfile.ZipFile(
+            archive_path,
+            "w",
+            zipfile.ZIP_DEFLATED,
+            allowZip64=True,
+        )
+        with zip_output:
+            dir = os.path.normcase(os.path.abspath(self.unpacked_source_directory))
+            for dirpath, dirnames, filenames in os.walk(dir):
+                for dirname in dirnames:
+                    dir_arcname = self._get_archive_name(
+                        dirname,
+                        parentdir=dirpath,
+                        rootdir=dir,
+                    )
+                    zipdir = zipfile.ZipInfo(dir_arcname + "/")
+                    zipdir.external_attr = 0x1ED << 16  # 0o755
+                    zip_output.writestr(zipdir, "")
+                for filename in filenames:
+                    file_arcname = self._get_archive_name(
+                        filename,
+                        parentdir=dirpath,
+                        rootdir=dir,
+                    )
+                    filename = os.path.join(dirpath, filename)
+                    zip_output.write(filename, file_arcname)
+
+        logger.info("Saved %s", display_path(archive_path))
+
+    def install(
+        self,
+        install_options: List[str],
+        global_options: Optional[Sequence[str]] = None,
+        root: Optional[str] = None,
+        home: Optional[str] = None,
+        prefix: Optional[str] = None,
+        warn_script_location: bool = True,
+        use_user_site: bool = False,
+        pycompile: bool = True,
+    ) -> None:
+        scheme = get_scheme(
+            self.name,
+            user=use_user_site,
+            home=home,
+            root=root,
+            isolated=self.isolated,
+            prefix=prefix,
+        )
+
+        global_options = global_options if global_options is not None else []
+        if self.editable and not self.is_wheel:
+            install_editable_legacy(
+                install_options,
+                global_options,
+                prefix=prefix,
+                home=home,
+                use_user_site=use_user_site,
+                name=self.name,
+                setup_py_path=self.setup_py_path,
+                isolated=self.isolated,
+                build_env=self.build_env,
+                unpacked_source_directory=self.unpacked_source_directory,
+            )
+            self.install_succeeded = True
+            return
+
+        if self.is_wheel:
+            assert self.local_file_path
+            direct_url = None
+            # TODO this can be refactored to direct_url = self.download_info
+            if self.editable:
+                direct_url = direct_url_for_editable(self.unpacked_source_directory)
+            elif self.original_link:
+                direct_url = direct_url_from_link(
+                    self.original_link,
+                    self.source_dir,
+                    self.original_link_is_in_wheel_cache,
+                )
+            install_wheel(
+                self.name,
+                self.local_file_path,
+                scheme=scheme,
+                req_description=str(self.req),
+                pycompile=pycompile,
+                warn_script_location=warn_script_location,
+                direct_url=direct_url,
+                requested=self.user_supplied,
+            )
+            self.install_succeeded = True
+            return
+
+        # TODO: Why don't we do this for editable installs?
+
+        # Extend the list of global and install options passed on to
+        # the setup.py call with the ones from the requirements file.
+        # Options specified in requirements file override those
+        # specified on the command line, since the last option given
+        # to setup.py is the one that is used.
+        global_options = list(global_options) + self.global_options
+        install_options = list(install_options) + self.install_options
+
+        try:
+            if (
+                self.legacy_install_reason is not None
+                and self.legacy_install_reason.emit_before_install
+            ):
+                self.legacy_install_reason.emit_deprecation(self.name)
+            success = install_legacy(
+                install_options=install_options,
+                global_options=global_options,
+                root=root,
+                home=home,
+                prefix=prefix,
+                use_user_site=use_user_site,
+                pycompile=pycompile,
+                scheme=scheme,
+                setup_py_path=self.setup_py_path,
+                isolated=self.isolated,
+                req_name=self.name,
+                build_env=self.build_env,
+                unpacked_source_directory=self.unpacked_source_directory,
+                req_description=str(self.req),
+            )
+        except LegacyInstallFailure as exc:
+            self.install_succeeded = False
+            raise exc
+        except Exception:
+            self.install_succeeded = True
+            raise
+
+        self.install_succeeded = success
+
+        if (
+            success
+            and self.legacy_install_reason is not None
+            and self.legacy_install_reason.emit_after_success
+        ):
+            self.legacy_install_reason.emit_deprecation(self.name)
+
+
+def check_invalid_constraint_type(req: InstallRequirement) -> str:
+
+    # Check for unsupported forms
+    problem = ""
+    if not req.name:
+        problem = "Unnamed requirements are not allowed as constraints"
+    elif req.editable:
+        problem = "Editable requirements are not allowed as constraints"
+    elif req.extras:
+        problem = "Constraints cannot have extras"
+
+    if problem:
+        deprecated(
+            reason=(
+                "Constraints are only allowed to take the form of a package "
+                "name and a version specifier. Other forms were originally "
+                "permitted as an accident of the implementation, but were "
+                "undocumented. The new implementation of the resolver no "
+                "longer supports these forms."
+            ),
+            replacement="replacing the constraint with a requirement",
+            # No plan yet for when the new resolver becomes default
+            gone_in=None,
+            issue=8210,
+        )
+
+    return problem
+
+
+def _has_option(options: Values, reqs: List[InstallRequirement], option: str) -> bool:
+    if getattr(options, option, None):
+        return True
+    for req in reqs:
+        if getattr(req, option, None):
+            return True
+    return False
+
+
+def _install_option_ignored(
+    install_options: List[str], reqs: List[InstallRequirement]
+) -> bool:
+    for req in reqs:
+        if (install_options or req.install_options) and not req.use_pep517:
+            return False
+    return True
+
+
+class LegacySetupPyOptionsCheckMode(Enum):
+    INSTALL = 1
+    WHEEL = 2
+    DOWNLOAD = 3
+
+
+def check_legacy_setup_py_options(
+    options: Values,
+    reqs: List[InstallRequirement],
+    mode: LegacySetupPyOptionsCheckMode,
+) -> None:
+    has_install_options = _has_option(options, reqs, "install_options")
+    has_build_options = _has_option(options, reqs, "build_options")
+    has_global_options = _has_option(options, reqs, "global_options")
+    legacy_setup_py_options_present = (
+        has_install_options or has_build_options or has_global_options
+    )
+    if not legacy_setup_py_options_present:
+        return
+
+    options.format_control.disallow_binaries()
+    logger.warning(
+        "Implying --no-binary=:all: due to the presence of "
+        "--build-option / --global-option / --install-option. "
+        "Consider using --config-settings for more flexibility.",
+    )
+    if mode == LegacySetupPyOptionsCheckMode.INSTALL and has_install_options:
+        if _install_option_ignored(options.install_options, reqs):
+            logger.warning(
+                "Ignoring --install-option when building using PEP 517",
+            )
+        else:
+            deprecated(
+                reason=(
+                    "--install-option is deprecated because "
+                    "it forces pip to use the 'setup.py install' "
+                    "command which is itself deprecated."
+                ),
+                issue=11358,
+                replacement="to use --config-settings",
+                gone_in="23.1",
+            )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_set.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_set.py
new file mode 100644
index 0000000000000000000000000000000000000000..ec7a6e07a25acfa978030c65ae7c1d8609163249
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_set.py
@@ -0,0 +1,82 @@
+import logging
+from collections import OrderedDict
+from typing import Dict, List
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.req.req_install import InstallRequirement
+
+logger = logging.getLogger(__name__)
+
+
+class RequirementSet:
+    def __init__(self, check_supported_wheels: bool = True) -> None:
+        """Create a RequirementSet."""
+
+        self.requirements: Dict[str, InstallRequirement] = OrderedDict()
+        self.check_supported_wheels = check_supported_wheels
+
+        self.unnamed_requirements: List[InstallRequirement] = []
+
+    def __str__(self) -> str:
+        requirements = sorted(
+            (req for req in self.requirements.values() if not req.comes_from),
+            key=lambda req: canonicalize_name(req.name or ""),
+        )
+        return " ".join(str(req.req) for req in requirements)
+
+    def __repr__(self) -> str:
+        requirements = sorted(
+            self.requirements.values(),
+            key=lambda req: canonicalize_name(req.name or ""),
+        )
+
+        format_string = "<{classname} object; {count} requirement(s): {reqs}>"
+        return format_string.format(
+            classname=self.__class__.__name__,
+            count=len(requirements),
+            reqs=", ".join(str(req.req) for req in requirements),
+        )
+
+    def add_unnamed_requirement(self, install_req: InstallRequirement) -> None:
+        assert not install_req.name
+        self.unnamed_requirements.append(install_req)
+
+    def add_named_requirement(self, install_req: InstallRequirement) -> None:
+        assert install_req.name
+
+        project_name = canonicalize_name(install_req.name)
+        self.requirements[project_name] = install_req
+
+    def has_requirement(self, name: str) -> bool:
+        project_name = canonicalize_name(name)
+
+        return (
+            project_name in self.requirements
+            and not self.requirements[project_name].constraint
+        )
+
+    def get_requirement(self, name: str) -> InstallRequirement:
+        project_name = canonicalize_name(name)
+
+        if project_name in self.requirements:
+            return self.requirements[project_name]
+
+        raise KeyError(f"No project with the name {name!r}")
+
+    @property
+    def all_requirements(self) -> List[InstallRequirement]:
+        return self.unnamed_requirements + list(self.requirements.values())
+
+    @property
+    def requirements_to_install(self) -> List[InstallRequirement]:
+        """Return the list of requirements that need to be installed.
+
+        TODO remove this property together with the legacy resolver, since the new
+             resolver only returns requirements that need to be installed.
+        """
+        return [
+            install_req
+            for install_req in self.all_requirements
+            if not install_req.constraint and not install_req.satisfied_by
+        ]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_uninstall.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_uninstall.py
new file mode 100644
index 0000000000000000000000000000000000000000..15b67385c86218b6716ddac9d2fb4c8fcf1020e5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/req/req_uninstall.py
@@ -0,0 +1,640 @@
+import functools
+import os
+import sys
+import sysconfig
+from importlib.util import cache_from_source
+from typing import Any, Callable, Dict, Generator, Iterable, List, Optional, Set, Tuple
+
+from pip._internal.exceptions import UninstallationError
+from pip._internal.locations import get_bin_prefix, get_bin_user
+from pip._internal.metadata import BaseDistribution
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.egg_link import egg_link_path_from_location
+from pip._internal.utils.logging import getLogger, indent_log
+from pip._internal.utils.misc import ask, is_local, normalize_path, renames, rmtree
+from pip._internal.utils.temp_dir import AdjacentTempDirectory, TempDirectory
+
+logger = getLogger(__name__)
+
+
+def _script_names(
+    bin_dir: str, script_name: str, is_gui: bool
+) -> Generator[str, None, None]:
+    """Create the fully qualified name of the files created by
+    {console,gui}_scripts for the given ``dist``.
+    Returns the list of file names
+    """
+    exe_name = os.path.join(bin_dir, script_name)
+    yield exe_name
+    if not WINDOWS:
+        return
+    yield f"{exe_name}.exe"
+    yield f"{exe_name}.exe.manifest"
+    if is_gui:
+        yield f"{exe_name}-script.pyw"
+    else:
+        yield f"{exe_name}-script.py"
+
+
+def _unique(
+    fn: Callable[..., Generator[Any, None, None]]
+) -> Callable[..., Generator[Any, None, None]]:
+    @functools.wraps(fn)
+    def unique(*args: Any, **kw: Any) -> Generator[Any, None, None]:
+        seen: Set[Any] = set()
+        for item in fn(*args, **kw):
+            if item not in seen:
+                seen.add(item)
+                yield item
+
+    return unique
+
+
+@_unique
+def uninstallation_paths(dist: BaseDistribution) -> Generator[str, None, None]:
+    """
+    Yield all the uninstallation paths for dist based on RECORD-without-.py[co]
+
+    Yield paths to all the files in RECORD. For each .py file in RECORD, add
+    the .pyc and .pyo in the same directory.
+
+    UninstallPathSet.add() takes care of the __pycache__ .py[co].
+
+    If RECORD is not found, raises UninstallationError,
+    with possible information from the INSTALLER file.
+
+    https://packaging.python.org/specifications/recording-installed-packages/
+    """
+    location = dist.location
+    assert location is not None, "not installed"
+
+    entries = dist.iter_declared_entries()
+    if entries is None:
+        msg = "Cannot uninstall {dist}, RECORD file not found.".format(dist=dist)
+        installer = dist.installer
+        if not installer or installer == "pip":
+            dep = "{}=={}".format(dist.raw_name, dist.version)
+            msg += (
+                " You might be able to recover from this via: "
+                "'pip install --force-reinstall --no-deps {}'.".format(dep)
+            )
+        else:
+            msg += " Hint: The package was installed by {}.".format(installer)
+        raise UninstallationError(msg)
+
+    for entry in entries:
+        path = os.path.join(location, entry)
+        yield path
+        if path.endswith(".py"):
+            dn, fn = os.path.split(path)
+            base = fn[:-3]
+            path = os.path.join(dn, base + ".pyc")
+            yield path
+            path = os.path.join(dn, base + ".pyo")
+            yield path
+
+
+def compact(paths: Iterable[str]) -> Set[str]:
+    """Compact a path set to contain the minimal number of paths
+    necessary to contain all paths in the set. If /a/path/ and
+    /a/path/to/a/file.txt are both in the set, leave only the
+    shorter path."""
+
+    sep = os.path.sep
+    short_paths: Set[str] = set()
+    for path in sorted(paths, key=len):
+        should_skip = any(
+            path.startswith(shortpath.rstrip("*"))
+            and path[len(shortpath.rstrip("*").rstrip(sep))] == sep
+            for shortpath in short_paths
+        )
+        if not should_skip:
+            short_paths.add(path)
+    return short_paths
+
+
+def compress_for_rename(paths: Iterable[str]) -> Set[str]:
+    """Returns a set containing the paths that need to be renamed.
+
+    This set may include directories when the original sequence of paths
+    included every file on disk.
+    """
+    case_map = {os.path.normcase(p): p for p in paths}
+    remaining = set(case_map)
+    unchecked = sorted({os.path.split(p)[0] for p in case_map.values()}, key=len)
+    wildcards: Set[str] = set()
+
+    def norm_join(*a: str) -> str:
+        return os.path.normcase(os.path.join(*a))
+
+    for root in unchecked:
+        if any(os.path.normcase(root).startswith(w) for w in wildcards):
+            # This directory has already been handled.
+            continue
+
+        all_files: Set[str] = set()
+        all_subdirs: Set[str] = set()
+        for dirname, subdirs, files in os.walk(root):
+            all_subdirs.update(norm_join(root, dirname, d) for d in subdirs)
+            all_files.update(norm_join(root, dirname, f) for f in files)
+        # If all the files we found are in our remaining set of files to
+        # remove, then remove them from the latter set and add a wildcard
+        # for the directory.
+        if not (all_files - remaining):
+            remaining.difference_update(all_files)
+            wildcards.add(root + os.sep)
+
+    return set(map(case_map.__getitem__, remaining)) | wildcards
+
+
+def compress_for_output_listing(paths: Iterable[str]) -> Tuple[Set[str], Set[str]]:
+    """Returns a tuple of 2 sets of which paths to display to user
+
+    The first set contains paths that would be deleted. Files of a package
+    are not added and the top-level directory of the package has a '*' added
+    at the end - to signify that all it's contents are removed.
+
+    The second set contains files that would have been skipped in the above
+    folders.
+    """
+
+    will_remove = set(paths)
+    will_skip = set()
+
+    # Determine folders and files
+    folders = set()
+    files = set()
+    for path in will_remove:
+        if path.endswith(".pyc"):
+            continue
+        if path.endswith("__init__.py") or ".dist-info" in path:
+            folders.add(os.path.dirname(path))
+        files.add(path)
+
+    # probably this one https://github.com/python/mypy/issues/390
+    _normcased_files = set(map(os.path.normcase, files))  # type: ignore
+
+    folders = compact(folders)
+
+    # This walks the tree using os.walk to not miss extra folders
+    # that might get added.
+    for folder in folders:
+        for dirpath, _, dirfiles in os.walk(folder):
+            for fname in dirfiles:
+                if fname.endswith(".pyc"):
+                    continue
+
+                file_ = os.path.join(dirpath, fname)
+                if (
+                    os.path.isfile(file_)
+                    and os.path.normcase(file_) not in _normcased_files
+                ):
+                    # We are skipping this file. Add it to the set.
+                    will_skip.add(file_)
+
+    will_remove = files | {os.path.join(folder, "*") for folder in folders}
+
+    return will_remove, will_skip
+
+
+class StashedUninstallPathSet:
+    """A set of file rename operations to stash files while
+    tentatively uninstalling them."""
+
+    def __init__(self) -> None:
+        # Mapping from source file root to [Adjacent]TempDirectory
+        # for files under that directory.
+        self._save_dirs: Dict[str, TempDirectory] = {}
+        # (old path, new path) tuples for each move that may need
+        # to be undone.
+        self._moves: List[Tuple[str, str]] = []
+
+    def _get_directory_stash(self, path: str) -> str:
+        """Stashes a directory.
+
+        Directories are stashed adjacent to their original location if
+        possible, or else moved/copied into the user's temp dir."""
+
+        try:
+            save_dir: TempDirectory = AdjacentTempDirectory(path)
+        except OSError:
+            save_dir = TempDirectory(kind="uninstall")
+        self._save_dirs[os.path.normcase(path)] = save_dir
+
+        return save_dir.path
+
+    def _get_file_stash(self, path: str) -> str:
+        """Stashes a file.
+
+        If no root has been provided, one will be created for the directory
+        in the user's temp directory."""
+        path = os.path.normcase(path)
+        head, old_head = os.path.dirname(path), None
+        save_dir = None
+
+        while head != old_head:
+            try:
+                save_dir = self._save_dirs[head]
+                break
+            except KeyError:
+                pass
+            head, old_head = os.path.dirname(head), head
+        else:
+            # Did not find any suitable root
+            head = os.path.dirname(path)
+            save_dir = TempDirectory(kind="uninstall")
+            self._save_dirs[head] = save_dir
+
+        relpath = os.path.relpath(path, head)
+        if relpath and relpath != os.path.curdir:
+            return os.path.join(save_dir.path, relpath)
+        return save_dir.path
+
+    def stash(self, path: str) -> str:
+        """Stashes the directory or file and returns its new location.
+        Handle symlinks as files to avoid modifying the symlink targets.
+        """
+        path_is_dir = os.path.isdir(path) and not os.path.islink(path)
+        if path_is_dir:
+            new_path = self._get_directory_stash(path)
+        else:
+            new_path = self._get_file_stash(path)
+
+        self._moves.append((path, new_path))
+        if path_is_dir and os.path.isdir(new_path):
+            # If we're moving a directory, we need to
+            # remove the destination first or else it will be
+            # moved to inside the existing directory.
+            # We just created new_path ourselves, so it will
+            # be removable.
+            os.rmdir(new_path)
+        renames(path, new_path)
+        return new_path
+
+    def commit(self) -> None:
+        """Commits the uninstall by removing stashed files."""
+        for _, save_dir in self._save_dirs.items():
+            save_dir.cleanup()
+        self._moves = []
+        self._save_dirs = {}
+
+    def rollback(self) -> None:
+        """Undoes the uninstall by moving stashed files back."""
+        for p in self._moves:
+            logger.info("Moving to %s\n from %s", *p)
+
+        for new_path, path in self._moves:
+            try:
+                logger.debug("Replacing %s from %s", new_path, path)
+                if os.path.isfile(new_path) or os.path.islink(new_path):
+                    os.unlink(new_path)
+                elif os.path.isdir(new_path):
+                    rmtree(new_path)
+                renames(path, new_path)
+            except OSError as ex:
+                logger.error("Failed to restore %s", new_path)
+                logger.debug("Exception: %s", ex)
+
+        self.commit()
+
+    @property
+    def can_rollback(self) -> bool:
+        return bool(self._moves)
+
+
+class UninstallPathSet:
+    """A set of file paths to be removed in the uninstallation of a
+    requirement."""
+
+    def __init__(self, dist: BaseDistribution) -> None:
+        self._paths: Set[str] = set()
+        self._refuse: Set[str] = set()
+        self._pth: Dict[str, UninstallPthEntries] = {}
+        self._dist = dist
+        self._moved_paths = StashedUninstallPathSet()
+
+    def _permitted(self, path: str) -> bool:
+        """
+        Return True if the given path is one we are permitted to
+        remove/modify, False otherwise.
+
+        """
+        return is_local(path)
+
+    def add(self, path: str) -> None:
+        head, tail = os.path.split(path)
+
+        # we normalize the head to resolve parent directory symlinks, but not
+        # the tail, since we only want to uninstall symlinks, not their targets
+        path = os.path.join(normalize_path(head), os.path.normcase(tail))
+
+        if not os.path.exists(path):
+            return
+        if self._permitted(path):
+            self._paths.add(path)
+        else:
+            self._refuse.add(path)
+
+        # __pycache__ files can show up after 'installed-files.txt' is created,
+        # due to imports
+        if os.path.splitext(path)[1] == ".py":
+            self.add(cache_from_source(path))
+
+    def add_pth(self, pth_file: str, entry: str) -> None:
+        pth_file = normalize_path(pth_file)
+        if self._permitted(pth_file):
+            if pth_file not in self._pth:
+                self._pth[pth_file] = UninstallPthEntries(pth_file)
+            self._pth[pth_file].add(entry)
+        else:
+            self._refuse.add(pth_file)
+
+    def remove(self, auto_confirm: bool = False, verbose: bool = False) -> None:
+        """Remove paths in ``self._paths`` with confirmation (unless
+        ``auto_confirm`` is True)."""
+
+        if not self._paths:
+            logger.info(
+                "Can't uninstall '%s'. No files were found to uninstall.",
+                self._dist.raw_name,
+            )
+            return
+
+        dist_name_version = f"{self._dist.raw_name}-{self._dist.version}"
+        logger.info("Uninstalling %s:", dist_name_version)
+
+        with indent_log():
+            if auto_confirm or self._allowed_to_proceed(verbose):
+                moved = self._moved_paths
+
+                for_rename = compress_for_rename(self._paths)
+
+                for path in sorted(compact(for_rename)):
+                    moved.stash(path)
+                    logger.verbose("Removing file or directory %s", path)
+
+                for pth in self._pth.values():
+                    pth.remove()
+
+                logger.info("Successfully uninstalled %s", dist_name_version)
+
+    def _allowed_to_proceed(self, verbose: bool) -> bool:
+        """Display which files would be deleted and prompt for confirmation"""
+
+        def _display(msg: str, paths: Iterable[str]) -> None:
+            if not paths:
+                return
+
+            logger.info(msg)
+            with indent_log():
+                for path in sorted(compact(paths)):
+                    logger.info(path)
+
+        if not verbose:
+            will_remove, will_skip = compress_for_output_listing(self._paths)
+        else:
+            # In verbose mode, display all the files that are going to be
+            # deleted.
+            will_remove = set(self._paths)
+            will_skip = set()
+
+        _display("Would remove:", will_remove)
+        _display("Would not remove (might be manually added):", will_skip)
+        _display("Would not remove (outside of prefix):", self._refuse)
+        if verbose:
+            _display("Will actually move:", compress_for_rename(self._paths))
+
+        return ask("Proceed (Y/n)? ", ("y", "n", "")) != "n"
+
+    def rollback(self) -> None:
+        """Rollback the changes previously made by remove()."""
+        if not self._moved_paths.can_rollback:
+            logger.error(
+                "Can't roll back %s; was not uninstalled",
+                self._dist.raw_name,
+            )
+            return
+        logger.info("Rolling back uninstall of %s", self._dist.raw_name)
+        self._moved_paths.rollback()
+        for pth in self._pth.values():
+            pth.rollback()
+
+    def commit(self) -> None:
+        """Remove temporary save dir: rollback will no longer be possible."""
+        self._moved_paths.commit()
+
+    @classmethod
+    def from_dist(cls, dist: BaseDistribution) -> "UninstallPathSet":
+        dist_location = dist.location
+        info_location = dist.info_location
+        if dist_location is None:
+            logger.info(
+                "Not uninstalling %s since it is not installed",
+                dist.canonical_name,
+            )
+            return cls(dist)
+
+        normalized_dist_location = normalize_path(dist_location)
+        if not dist.local:
+            logger.info(
+                "Not uninstalling %s at %s, outside environment %s",
+                dist.canonical_name,
+                normalized_dist_location,
+                sys.prefix,
+            )
+            return cls(dist)
+
+        if normalized_dist_location in {
+            p
+            for p in {sysconfig.get_path("stdlib"), sysconfig.get_path("platstdlib")}
+            if p
+        }:
+            logger.info(
+                "Not uninstalling %s at %s, as it is in the standard library.",
+                dist.canonical_name,
+                normalized_dist_location,
+            )
+            return cls(dist)
+
+        paths_to_remove = cls(dist)
+        develop_egg_link = egg_link_path_from_location(dist.raw_name)
+
+        # Distribution is installed with metadata in a "flat" .egg-info
+        # directory. This means it is not a modern .dist-info installation, an
+        # egg, or legacy editable.
+        setuptools_flat_installation = (
+            dist.installed_with_setuptools_egg_info
+            and info_location is not None
+            and os.path.exists(info_location)
+            # If dist is editable and the location points to a ``.egg-info``,
+            # we are in fact in the legacy editable case.
+            and not info_location.endswith(f"{dist.setuptools_filename}.egg-info")
+        )
+
+        # Uninstall cases order do matter as in the case of 2 installs of the
+        # same package, pip needs to uninstall the currently detected version
+        if setuptools_flat_installation:
+            if info_location is not None:
+                paths_to_remove.add(info_location)
+            installed_files = dist.iter_declared_entries()
+            if installed_files is not None:
+                for installed_file in installed_files:
+                    paths_to_remove.add(os.path.join(dist_location, installed_file))
+            # FIXME: need a test for this elif block
+            # occurs with --single-version-externally-managed/--record outside
+            # of pip
+            elif dist.is_file("top_level.txt"):
+                try:
+                    namespace_packages = dist.read_text("namespace_packages.txt")
+                except FileNotFoundError:
+                    namespaces = []
+                else:
+                    namespaces = namespace_packages.splitlines(keepends=False)
+                for top_level_pkg in [
+                    p
+                    for p in dist.read_text("top_level.txt").splitlines()
+                    if p and p not in namespaces
+                ]:
+                    path = os.path.join(dist_location, top_level_pkg)
+                    paths_to_remove.add(path)
+                    paths_to_remove.add(f"{path}.py")
+                    paths_to_remove.add(f"{path}.pyc")
+                    paths_to_remove.add(f"{path}.pyo")
+
+        elif dist.installed_by_distutils:
+            raise UninstallationError(
+                "Cannot uninstall {!r}. It is a distutils installed project "
+                "and thus we cannot accurately determine which files belong "
+                "to it which would lead to only a partial uninstall.".format(
+                    dist.raw_name,
+                )
+            )
+
+        elif dist.installed_as_egg:
+            # package installed by easy_install
+            # We cannot match on dist.egg_name because it can slightly vary
+            # i.e. setuptools-0.6c11-py2.6.egg vs setuptools-0.6rc11-py2.6.egg
+            paths_to_remove.add(dist_location)
+            easy_install_egg = os.path.split(dist_location)[1]
+            easy_install_pth = os.path.join(
+                os.path.dirname(dist_location),
+                "easy-install.pth",
+            )
+            paths_to_remove.add_pth(easy_install_pth, "./" + easy_install_egg)
+
+        elif dist.installed_with_dist_info:
+            for path in uninstallation_paths(dist):
+                paths_to_remove.add(path)
+
+        elif develop_egg_link:
+            # PEP 660 modern editable is handled in the ``.dist-info`` case
+            # above, so this only covers the setuptools-style editable.
+            with open(develop_egg_link) as fh:
+                link_pointer = os.path.normcase(fh.readline().strip())
+                normalized_link_pointer = normalize_path(link_pointer)
+            assert os.path.samefile(
+                normalized_link_pointer, normalized_dist_location
+            ), (
+                f"Egg-link {link_pointer} does not match installed location of "
+                f"{dist.raw_name} (at {dist_location})"
+            )
+            paths_to_remove.add(develop_egg_link)
+            easy_install_pth = os.path.join(
+                os.path.dirname(develop_egg_link), "easy-install.pth"
+            )
+            paths_to_remove.add_pth(easy_install_pth, dist_location)
+
+        else:
+            logger.debug(
+                "Not sure how to uninstall: %s - Check: %s",
+                dist,
+                dist_location,
+            )
+
+        if dist.in_usersite:
+            bin_dir = get_bin_user()
+        else:
+            bin_dir = get_bin_prefix()
+
+        # find distutils scripts= scripts
+        try:
+            for script in dist.iter_distutils_script_names():
+                paths_to_remove.add(os.path.join(bin_dir, script))
+                if WINDOWS:
+                    paths_to_remove.add(os.path.join(bin_dir, f"{script}.bat"))
+        except (FileNotFoundError, NotADirectoryError):
+            pass
+
+        # find console_scripts and gui_scripts
+        def iter_scripts_to_remove(
+            dist: BaseDistribution,
+            bin_dir: str,
+        ) -> Generator[str, None, None]:
+            for entry_point in dist.iter_entry_points():
+                if entry_point.group == "console_scripts":
+                    yield from _script_names(bin_dir, entry_point.name, False)
+                elif entry_point.group == "gui_scripts":
+                    yield from _script_names(bin_dir, entry_point.name, True)
+
+        for s in iter_scripts_to_remove(dist, bin_dir):
+            paths_to_remove.add(s)
+
+        return paths_to_remove
+
+
+class UninstallPthEntries:
+    def __init__(self, pth_file: str) -> None:
+        self.file = pth_file
+        self.entries: Set[str] = set()
+        self._saved_lines: Optional[List[bytes]] = None
+
+    def add(self, entry: str) -> None:
+        entry = os.path.normcase(entry)
+        # On Windows, os.path.normcase converts the entry to use
+        # backslashes.  This is correct for entries that describe absolute
+        # paths outside of site-packages, but all the others use forward
+        # slashes.
+        # os.path.splitdrive is used instead of os.path.isabs because isabs
+        # treats non-absolute paths with drive letter markings like c:foo\bar
+        # as absolute paths. It also does not recognize UNC paths if they don't
+        # have more than "\\sever\share". Valid examples: "\\server\share\" or
+        # "\\server\share\folder".
+        if WINDOWS and not os.path.splitdrive(entry)[0]:
+            entry = entry.replace("\\", "/")
+        self.entries.add(entry)
+
+    def remove(self) -> None:
+        logger.verbose("Removing pth entries from %s:", self.file)
+
+        # If the file doesn't exist, log a warning and return
+        if not os.path.isfile(self.file):
+            logger.warning("Cannot remove entries from nonexistent file %s", self.file)
+            return
+        with open(self.file, "rb") as fh:
+            # windows uses '\r\n' with py3k, but uses '\n' with py2.x
+            lines = fh.readlines()
+            self._saved_lines = lines
+        if any(b"\r\n" in line for line in lines):
+            endline = "\r\n"
+        else:
+            endline = "\n"
+        # handle missing trailing newline
+        if lines and not lines[-1].endswith(endline.encode("utf-8")):
+            lines[-1] = lines[-1] + endline.encode("utf-8")
+        for entry in self.entries:
+            try:
+                logger.verbose("Removing entry: %s", entry)
+                lines.remove((entry + endline).encode("utf-8"))
+            except ValueError:
+                pass
+        with open(self.file, "wb") as fh:
+            fh.writelines(lines)
+
+    def rollback(self) -> bool:
+        if self._saved_lines is None:
+            logger.error("Cannot roll back changes to %s, none were made", self.file)
+            return False
+        logger.debug("Rolling %s back to previous state", self.file)
+        with open(self.file, "wb") as fh:
+            fh.writelines(self._saved_lines)
+        return True
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/base.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..42dade18c1ec2b825f756dad4aaa89f2d9e6ce21
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/base.py
@@ -0,0 +1,20 @@
+from typing import Callable, List, Optional
+
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.req.req_set import RequirementSet
+
+InstallRequirementProvider = Callable[
+    [str, Optional[InstallRequirement]], InstallRequirement
+]
+
+
+class BaseResolver:
+    def resolve(
+        self, root_reqs: List[InstallRequirement], check_supported_wheels: bool
+    ) -> RequirementSet:
+        raise NotImplementedError()
+
+    def get_installation_order(
+        self, req_set: RequirementSet
+    ) -> List[InstallRequirement]:
+        raise NotImplementedError()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/legacy/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/legacy/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/legacy/resolver.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/legacy/resolver.py
new file mode 100644
index 0000000000000000000000000000000000000000..fb49d41695fec744a674da8bc11b646264c768b7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/legacy/resolver.py
@@ -0,0 +1,600 @@
+"""Dependency Resolution
+
+The dependency resolution in pip is performed as follows:
+
+for top-level requirements:
+    a. only one spec allowed per project, regardless of conflicts or not.
+       otherwise a "double requirement" exception is raised
+    b. they override sub-dependency requirements.
+for sub-dependencies
+    a. "first found, wins" (where the order is breadth first)
+"""
+
+# The following comment should be removed at some point in the future.
+# mypy: strict-optional=False
+
+import logging
+import sys
+from collections import defaultdict
+from itertools import chain
+from typing import DefaultDict, Iterable, List, Optional, Set, Tuple
+
+from pip._vendor.packaging import specifiers
+from pip._vendor.packaging.requirements import Requirement
+
+from pip._internal.cache import WheelCache
+from pip._internal.exceptions import (
+    BestVersionAlreadyInstalled,
+    DistributionNotFound,
+    HashError,
+    HashErrors,
+    InstallationError,
+    NoneMetadataError,
+    UnsupportedPythonVersion,
+)
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import BaseDistribution
+from pip._internal.models.link import Link
+from pip._internal.models.wheel import Wheel
+from pip._internal.operations.prepare import RequirementPreparer
+from pip._internal.req.req_install import (
+    InstallRequirement,
+    check_invalid_constraint_type,
+)
+from pip._internal.req.req_set import RequirementSet
+from pip._internal.resolution.base import BaseResolver, InstallRequirementProvider
+from pip._internal.utils import compatibility_tags
+from pip._internal.utils.compatibility_tags import get_supported
+from pip._internal.utils.direct_url_helpers import direct_url_from_link
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.misc import normalize_version_info
+from pip._internal.utils.packaging import check_requires_python
+
+logger = logging.getLogger(__name__)
+
+DiscoveredDependencies = DefaultDict[str, List[InstallRequirement]]
+
+
+def _check_dist_requires_python(
+    dist: BaseDistribution,
+    version_info: Tuple[int, int, int],
+    ignore_requires_python: bool = False,
+) -> None:
+    """
+    Check whether the given Python version is compatible with a distribution's
+    "Requires-Python" value.
+
+    :param version_info: A 3-tuple of ints representing the Python
+        major-minor-micro version to check.
+    :param ignore_requires_python: Whether to ignore the "Requires-Python"
+        value if the given Python version isn't compatible.
+
+    :raises UnsupportedPythonVersion: When the given Python version isn't
+        compatible.
+    """
+    # This idiosyncratically converts the SpecifierSet to str and let
+    # check_requires_python then parse it again into SpecifierSet. But this
+    # is the legacy resolver so I'm just not going to bother refactoring.
+    try:
+        requires_python = str(dist.requires_python)
+    except FileNotFoundError as e:
+        raise NoneMetadataError(dist, str(e))
+    try:
+        is_compatible = check_requires_python(
+            requires_python,
+            version_info=version_info,
+        )
+    except specifiers.InvalidSpecifier as exc:
+        logger.warning(
+            "Package %r has an invalid Requires-Python: %s", dist.raw_name, exc
+        )
+        return
+
+    if is_compatible:
+        return
+
+    version = ".".join(map(str, version_info))
+    if ignore_requires_python:
+        logger.debug(
+            "Ignoring failed Requires-Python check for package %r: %s not in %r",
+            dist.raw_name,
+            version,
+            requires_python,
+        )
+        return
+
+    raise UnsupportedPythonVersion(
+        "Package {!r} requires a different Python: {} not in {!r}".format(
+            dist.raw_name, version, requires_python
+        )
+    )
+
+
+class Resolver(BaseResolver):
+    """Resolves which packages need to be installed/uninstalled to perform \
+    the requested operation without breaking the requirements of any package.
+    """
+
+    _allowed_strategies = {"eager", "only-if-needed", "to-satisfy-only"}
+
+    def __init__(
+        self,
+        preparer: RequirementPreparer,
+        finder: PackageFinder,
+        wheel_cache: Optional[WheelCache],
+        make_install_req: InstallRequirementProvider,
+        use_user_site: bool,
+        ignore_dependencies: bool,
+        ignore_installed: bool,
+        ignore_requires_python: bool,
+        force_reinstall: bool,
+        upgrade_strategy: str,
+        py_version_info: Optional[Tuple[int, ...]] = None,
+    ) -> None:
+        super().__init__()
+        assert upgrade_strategy in self._allowed_strategies
+
+        if py_version_info is None:
+            py_version_info = sys.version_info[:3]
+        else:
+            py_version_info = normalize_version_info(py_version_info)
+
+        self._py_version_info = py_version_info
+
+        self.preparer = preparer
+        self.finder = finder
+        self.wheel_cache = wheel_cache
+
+        self.upgrade_strategy = upgrade_strategy
+        self.force_reinstall = force_reinstall
+        self.ignore_dependencies = ignore_dependencies
+        self.ignore_installed = ignore_installed
+        self.ignore_requires_python = ignore_requires_python
+        self.use_user_site = use_user_site
+        self._make_install_req = make_install_req
+
+        self._discovered_dependencies: DiscoveredDependencies = defaultdict(list)
+
+    def resolve(
+        self, root_reqs: List[InstallRequirement], check_supported_wheels: bool
+    ) -> RequirementSet:
+        """Resolve what operations need to be done
+
+        As a side-effect of this method, the packages (and their dependencies)
+        are downloaded, unpacked and prepared for installation. This
+        preparation is done by ``pip.operations.prepare``.
+
+        Once PyPI has static dependency metadata available, it would be
+        possible to move the preparation to become a step separated from
+        dependency resolution.
+        """
+        requirement_set = RequirementSet(check_supported_wheels=check_supported_wheels)
+        for req in root_reqs:
+            if req.constraint:
+                check_invalid_constraint_type(req)
+            self._add_requirement_to_set(requirement_set, req)
+
+        # Actually prepare the files, and collect any exceptions. Most hash
+        # exceptions cannot be checked ahead of time, because
+        # _populate_link() needs to be called before we can make decisions
+        # based on link type.
+        discovered_reqs: List[InstallRequirement] = []
+        hash_errors = HashErrors()
+        for req in chain(requirement_set.all_requirements, discovered_reqs):
+            try:
+                discovered_reqs.extend(self._resolve_one(requirement_set, req))
+            except HashError as exc:
+                exc.req = req
+                hash_errors.append(exc)
+
+        if hash_errors:
+            raise hash_errors
+
+        return requirement_set
+
+    def _add_requirement_to_set(
+        self,
+        requirement_set: RequirementSet,
+        install_req: InstallRequirement,
+        parent_req_name: Optional[str] = None,
+        extras_requested: Optional[Iterable[str]] = None,
+    ) -> Tuple[List[InstallRequirement], Optional[InstallRequirement]]:
+        """Add install_req as a requirement to install.
+
+        :param parent_req_name: The name of the requirement that needed this
+            added. The name is used because when multiple unnamed requirements
+            resolve to the same name, we could otherwise end up with dependency
+            links that point outside the Requirements set. parent_req must
+            already be added. Note that None implies that this is a user
+            supplied requirement, vs an inferred one.
+        :param extras_requested: an iterable of extras used to evaluate the
+            environment markers.
+        :return: Additional requirements to scan. That is either [] if
+            the requirement is not applicable, or [install_req] if the
+            requirement is applicable and has just been added.
+        """
+        # If the markers do not match, ignore this requirement.
+        if not install_req.match_markers(extras_requested):
+            logger.info(
+                "Ignoring %s: markers '%s' don't match your environment",
+                install_req.name,
+                install_req.markers,
+            )
+            return [], None
+
+        # If the wheel is not supported, raise an error.
+        # Should check this after filtering out based on environment markers to
+        # allow specifying different wheels based on the environment/OS, in a
+        # single requirements file.
+        if install_req.link and install_req.link.is_wheel:
+            wheel = Wheel(install_req.link.filename)
+            tags = compatibility_tags.get_supported()
+            if requirement_set.check_supported_wheels and not wheel.supported(tags):
+                raise InstallationError(
+                    "{} is not a supported wheel on this platform.".format(
+                        wheel.filename
+                    )
+                )
+
+        # This next bit is really a sanity check.
+        assert (
+            not install_req.user_supplied or parent_req_name is None
+        ), "a user supplied req shouldn't have a parent"
+
+        # Unnamed requirements are scanned again and the requirement won't be
+        # added as a dependency until after scanning.
+        if not install_req.name:
+            requirement_set.add_unnamed_requirement(install_req)
+            return [install_req], None
+
+        try:
+            existing_req: Optional[
+                InstallRequirement
+            ] = requirement_set.get_requirement(install_req.name)
+        except KeyError:
+            existing_req = None
+
+        has_conflicting_requirement = (
+            parent_req_name is None
+            and existing_req
+            and not existing_req.constraint
+            and existing_req.extras == install_req.extras
+            and existing_req.req
+            and install_req.req
+            and existing_req.req.specifier != install_req.req.specifier
+        )
+        if has_conflicting_requirement:
+            raise InstallationError(
+                "Double requirement given: {} (already in {}, name={!r})".format(
+                    install_req, existing_req, install_req.name
+                )
+            )
+
+        # When no existing requirement exists, add the requirement as a
+        # dependency and it will be scanned again after.
+        if not existing_req:
+            requirement_set.add_named_requirement(install_req)
+            # We'd want to rescan this requirement later
+            return [install_req], install_req
+
+        # Assume there's no need to scan, and that we've already
+        # encountered this for scanning.
+        if install_req.constraint or not existing_req.constraint:
+            return [], existing_req
+
+        does_not_satisfy_constraint = install_req.link and not (
+            existing_req.link and install_req.link.path == existing_req.link.path
+        )
+        if does_not_satisfy_constraint:
+            raise InstallationError(
+                "Could not satisfy constraints for '{}': "
+                "installation from path or url cannot be "
+                "constrained to a version".format(install_req.name)
+            )
+        # If we're now installing a constraint, mark the existing
+        # object for real installation.
+        existing_req.constraint = False
+        # If we're now installing a user supplied requirement,
+        # mark the existing object as such.
+        if install_req.user_supplied:
+            existing_req.user_supplied = True
+        existing_req.extras = tuple(
+            sorted(set(existing_req.extras) | set(install_req.extras))
+        )
+        logger.debug(
+            "Setting %s extras to: %s",
+            existing_req,
+            existing_req.extras,
+        )
+        # Return the existing requirement for addition to the parent and
+        # scanning again.
+        return [existing_req], existing_req
+
+    def _is_upgrade_allowed(self, req: InstallRequirement) -> bool:
+        if self.upgrade_strategy == "to-satisfy-only":
+            return False
+        elif self.upgrade_strategy == "eager":
+            return True
+        else:
+            assert self.upgrade_strategy == "only-if-needed"
+            return req.user_supplied or req.constraint
+
+    def _set_req_to_reinstall(self, req: InstallRequirement) -> None:
+        """
+        Set a requirement to be installed.
+        """
+        # Don't uninstall the conflict if doing a user install and the
+        # conflict is not a user install.
+        if not self.use_user_site or req.satisfied_by.in_usersite:
+            req.should_reinstall = True
+        req.satisfied_by = None
+
+    def _check_skip_installed(
+        self, req_to_install: InstallRequirement
+    ) -> Optional[str]:
+        """Check if req_to_install should be skipped.
+
+        This will check if the req is installed, and whether we should upgrade
+        or reinstall it, taking into account all the relevant user options.
+
+        After calling this req_to_install will only have satisfied_by set to
+        None if the req_to_install is to be upgraded/reinstalled etc. Any
+        other value will be a dist recording the current thing installed that
+        satisfies the requirement.
+
+        Note that for vcs urls and the like we can't assess skipping in this
+        routine - we simply identify that we need to pull the thing down,
+        then later on it is pulled down and introspected to assess upgrade/
+        reinstalls etc.
+
+        :return: A text reason for why it was skipped, or None.
+        """
+        if self.ignore_installed:
+            return None
+
+        req_to_install.check_if_exists(self.use_user_site)
+        if not req_to_install.satisfied_by:
+            return None
+
+        if self.force_reinstall:
+            self._set_req_to_reinstall(req_to_install)
+            return None
+
+        if not self._is_upgrade_allowed(req_to_install):
+            if self.upgrade_strategy == "only-if-needed":
+                return "already satisfied, skipping upgrade"
+            return "already satisfied"
+
+        # Check for the possibility of an upgrade.  For link-based
+        # requirements we have to pull the tree down and inspect to assess
+        # the version #, so it's handled way down.
+        if not req_to_install.link:
+            try:
+                self.finder.find_requirement(req_to_install, upgrade=True)
+            except BestVersionAlreadyInstalled:
+                # Then the best version is installed.
+                return "already up-to-date"
+            except DistributionNotFound:
+                # No distribution found, so we squash the error.  It will
+                # be raised later when we re-try later to do the install.
+                # Why don't we just raise here?
+                pass
+
+        self._set_req_to_reinstall(req_to_install)
+        return None
+
+    def _find_requirement_link(self, req: InstallRequirement) -> Optional[Link]:
+        upgrade = self._is_upgrade_allowed(req)
+        best_candidate = self.finder.find_requirement(req, upgrade)
+        if not best_candidate:
+            return None
+
+        # Log a warning per PEP 592 if necessary before returning.
+        link = best_candidate.link
+        if link.is_yanked:
+            reason = link.yanked_reason or ""
+            msg = (
+                # Mark this as a unicode string to prevent
+                # "UnicodeEncodeError: 'ascii' codec can't encode character"
+                # in Python 2 when the reason contains non-ascii characters.
+                "The candidate selected for download or install is a "
+                "yanked version: {candidate}\n"
+                "Reason for being yanked: {reason}"
+            ).format(candidate=best_candidate, reason=reason)
+            logger.warning(msg)
+
+        return link
+
+    def _populate_link(self, req: InstallRequirement) -> None:
+        """Ensure that if a link can be found for this, that it is found.
+
+        Note that req.link may still be None - if the requirement is already
+        installed and not needed to be upgraded based on the return value of
+        _is_upgrade_allowed().
+
+        If preparer.require_hashes is True, don't use the wheel cache, because
+        cached wheels, always built locally, have different hashes than the
+        files downloaded from the index server and thus throw false hash
+        mismatches. Furthermore, cached wheels at present have undeterministic
+        contents due to file modification times.
+        """
+        if req.link is None:
+            req.link = self._find_requirement_link(req)
+
+        if self.wheel_cache is None or self.preparer.require_hashes:
+            return
+        cache_entry = self.wheel_cache.get_cache_entry(
+            link=req.link,
+            package_name=req.name,
+            supported_tags=get_supported(),
+        )
+        if cache_entry is not None:
+            logger.debug("Using cached wheel link: %s", cache_entry.link)
+            if req.link is req.original_link and cache_entry.persistent:
+                req.original_link_is_in_wheel_cache = True
+            if cache_entry.origin is not None:
+                req.download_info = cache_entry.origin
+            else:
+                # Legacy cache entry that does not have origin.json.
+                # download_info may miss the archive_info.hash field.
+                req.download_info = direct_url_from_link(
+                    req.link, link_is_in_wheel_cache=cache_entry.persistent
+                )
+            req.link = cache_entry.link
+
+    def _get_dist_for(self, req: InstallRequirement) -> BaseDistribution:
+        """Takes a InstallRequirement and returns a single AbstractDist \
+        representing a prepared variant of the same.
+        """
+        if req.editable:
+            return self.preparer.prepare_editable_requirement(req)
+
+        # satisfied_by is only evaluated by calling _check_skip_installed,
+        # so it must be None here.
+        assert req.satisfied_by is None
+        skip_reason = self._check_skip_installed(req)
+
+        if req.satisfied_by:
+            return self.preparer.prepare_installed_requirement(req, skip_reason)
+
+        # We eagerly populate the link, since that's our "legacy" behavior.
+        self._populate_link(req)
+        dist = self.preparer.prepare_linked_requirement(req)
+
+        # NOTE
+        # The following portion is for determining if a certain package is
+        # going to be re-installed/upgraded or not and reporting to the user.
+        # This should probably get cleaned up in a future refactor.
+
+        # req.req is only avail after unpack for URL
+        # pkgs repeat check_if_exists to uninstall-on-upgrade
+        # (#14)
+        if not self.ignore_installed:
+            req.check_if_exists(self.use_user_site)
+
+        if req.satisfied_by:
+            should_modify = (
+                self.upgrade_strategy != "to-satisfy-only"
+                or self.force_reinstall
+                or self.ignore_installed
+                or req.link.scheme == "file"
+            )
+            if should_modify:
+                self._set_req_to_reinstall(req)
+            else:
+                logger.info(
+                    "Requirement already satisfied (use --upgrade to upgrade): %s",
+                    req,
+                )
+        return dist
+
+    def _resolve_one(
+        self,
+        requirement_set: RequirementSet,
+        req_to_install: InstallRequirement,
+    ) -> List[InstallRequirement]:
+        """Prepare a single requirements file.
+
+        :return: A list of additional InstallRequirements to also install.
+        """
+        # Tell user what we are doing for this requirement:
+        # obtain (editable), skipping, processing (local url), collecting
+        # (remote url or package name)
+        if req_to_install.constraint or req_to_install.prepared:
+            return []
+
+        req_to_install.prepared = True
+
+        # Parse and return dependencies
+        dist = self._get_dist_for(req_to_install)
+        # This will raise UnsupportedPythonVersion if the given Python
+        # version isn't compatible with the distribution's Requires-Python.
+        _check_dist_requires_python(
+            dist,
+            version_info=self._py_version_info,
+            ignore_requires_python=self.ignore_requires_python,
+        )
+
+        more_reqs: List[InstallRequirement] = []
+
+        def add_req(subreq: Requirement, extras_requested: Iterable[str]) -> None:
+            # This idiosyncratically converts the Requirement to str and let
+            # make_install_req then parse it again into Requirement. But this is
+            # the legacy resolver so I'm just not going to bother refactoring.
+            sub_install_req = self._make_install_req(str(subreq), req_to_install)
+            parent_req_name = req_to_install.name
+            to_scan_again, add_to_parent = self._add_requirement_to_set(
+                requirement_set,
+                sub_install_req,
+                parent_req_name=parent_req_name,
+                extras_requested=extras_requested,
+            )
+            if parent_req_name and add_to_parent:
+                self._discovered_dependencies[parent_req_name].append(add_to_parent)
+            more_reqs.extend(to_scan_again)
+
+        with indent_log():
+            # We add req_to_install before its dependencies, so that we
+            # can refer to it when adding dependencies.
+            if not requirement_set.has_requirement(req_to_install.name):
+                # 'unnamed' requirements will get added here
+                # 'unnamed' requirements can only come from being directly
+                # provided by the user.
+                assert req_to_install.user_supplied
+                self._add_requirement_to_set(
+                    requirement_set, req_to_install, parent_req_name=None
+                )
+
+            if not self.ignore_dependencies:
+                if req_to_install.extras:
+                    logger.debug(
+                        "Installing extra requirements: %r",
+                        ",".join(req_to_install.extras),
+                    )
+                missing_requested = sorted(
+                    set(req_to_install.extras) - set(dist.iter_provided_extras())
+                )
+                for missing in missing_requested:
+                    logger.warning(
+                        "%s %s does not provide the extra '%s'",
+                        dist.raw_name,
+                        dist.version,
+                        missing,
+                    )
+
+                available_requested = sorted(
+                    set(dist.iter_provided_extras()) & set(req_to_install.extras)
+                )
+                for subreq in dist.iter_dependencies(available_requested):
+                    add_req(subreq, extras_requested=available_requested)
+
+        return more_reqs
+
+    def get_installation_order(
+        self, req_set: RequirementSet
+    ) -> List[InstallRequirement]:
+        """Create the installation order.
+
+        The installation order is topological - requirements are installed
+        before the requiring thing. We break cycles at an arbitrary point,
+        and make no other guarantees.
+        """
+        # The current implementation, which we may change at any point
+        # installs the user specified things in the order given, except when
+        # dependencies must come earlier to achieve topological order.
+        order = []
+        ordered_reqs: Set[InstallRequirement] = set()
+
+        def schedule(req: InstallRequirement) -> None:
+            if req.satisfied_by or req in ordered_reqs:
+                return
+            if req.constraint:
+                return
+            ordered_reqs.add(req)
+            for dep in self._discovered_dependencies[req.name]:
+                schedule(dep)
+            order.append(req)
+
+        for install_req in req_set.requirements.values():
+            schedule(install_req)
+        return order
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/base.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..b206692a0a976d8336e3f5896eadf4765a33fb2c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/base.py
@@ -0,0 +1,141 @@
+from typing import FrozenSet, Iterable, Optional, Tuple, Union
+
+from pip._vendor.packaging.specifiers import SpecifierSet
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+from pip._vendor.packaging.version import LegacyVersion, Version
+
+from pip._internal.models.link import Link, links_equivalent
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.utils.hashes import Hashes
+
+CandidateLookup = Tuple[Optional["Candidate"], Optional[InstallRequirement]]
+CandidateVersion = Union[LegacyVersion, Version]
+
+
+def format_name(project: str, extras: FrozenSet[str]) -> str:
+    if not extras:
+        return project
+    canonical_extras = sorted(canonicalize_name(e) for e in extras)
+    return "{}[{}]".format(project, ",".join(canonical_extras))
+
+
+class Constraint:
+    def __init__(
+        self, specifier: SpecifierSet, hashes: Hashes, links: FrozenSet[Link]
+    ) -> None:
+        self.specifier = specifier
+        self.hashes = hashes
+        self.links = links
+
+    @classmethod
+    def empty(cls) -> "Constraint":
+        return Constraint(SpecifierSet(), Hashes(), frozenset())
+
+    @classmethod
+    def from_ireq(cls, ireq: InstallRequirement) -> "Constraint":
+        links = frozenset([ireq.link]) if ireq.link else frozenset()
+        return Constraint(ireq.specifier, ireq.hashes(trust_internet=False), links)
+
+    def __bool__(self) -> bool:
+        return bool(self.specifier) or bool(self.hashes) or bool(self.links)
+
+    def __and__(self, other: InstallRequirement) -> "Constraint":
+        if not isinstance(other, InstallRequirement):
+            return NotImplemented
+        specifier = self.specifier & other.specifier
+        hashes = self.hashes & other.hashes(trust_internet=False)
+        links = self.links
+        if other.link:
+            links = links.union([other.link])
+        return Constraint(specifier, hashes, links)
+
+    def is_satisfied_by(self, candidate: "Candidate") -> bool:
+        # Reject if there are any mismatched URL constraints on this package.
+        if self.links and not all(_match_link(link, candidate) for link in self.links):
+            return False
+        # We can safely always allow prereleases here since PackageFinder
+        # already implements the prerelease logic, and would have filtered out
+        # prerelease candidates if the user does not expect them.
+        return self.specifier.contains(candidate.version, prereleases=True)
+
+
+class Requirement:
+    @property
+    def project_name(self) -> NormalizedName:
+        """The "project name" of a requirement.
+
+        This is different from ``name`` if this requirement contains extras,
+        in which case ``name`` would contain the ``[...]`` part, while this
+        refers to the name of the project.
+        """
+        raise NotImplementedError("Subclass should override")
+
+    @property
+    def name(self) -> str:
+        """The name identifying this requirement in the resolver.
+
+        This is different from ``project_name`` if this requirement contains
+        extras, where ``project_name`` would not contain the ``[...]`` part.
+        """
+        raise NotImplementedError("Subclass should override")
+
+    def is_satisfied_by(self, candidate: "Candidate") -> bool:
+        return False
+
+    def get_candidate_lookup(self) -> CandidateLookup:
+        raise NotImplementedError("Subclass should override")
+
+    def format_for_error(self) -> str:
+        raise NotImplementedError("Subclass should override")
+
+
+def _match_link(link: Link, candidate: "Candidate") -> bool:
+    if candidate.source_link:
+        return links_equivalent(link, candidate.source_link)
+    return False
+
+
+class Candidate:
+    @property
+    def project_name(self) -> NormalizedName:
+        """The "project name" of the candidate.
+
+        This is different from ``name`` if this candidate contains extras,
+        in which case ``name`` would contain the ``[...]`` part, while this
+        refers to the name of the project.
+        """
+        raise NotImplementedError("Override in subclass")
+
+    @property
+    def name(self) -> str:
+        """The name identifying this candidate in the resolver.
+
+        This is different from ``project_name`` if this candidate contains
+        extras, where ``project_name`` would not contain the ``[...]`` part.
+        """
+        raise NotImplementedError("Override in subclass")
+
+    @property
+    def version(self) -> CandidateVersion:
+        raise NotImplementedError("Override in subclass")
+
+    @property
+    def is_installed(self) -> bool:
+        raise NotImplementedError("Override in subclass")
+
+    @property
+    def is_editable(self) -> bool:
+        raise NotImplementedError("Override in subclass")
+
+    @property
+    def source_link(self) -> Optional[Link]:
+        raise NotImplementedError("Override in subclass")
+
+    def iter_dependencies(self, with_requires: bool) -> Iterable[Optional[Requirement]]:
+        raise NotImplementedError("Override in subclass")
+
+    def get_install_requirement(self) -> Optional[InstallRequirement]:
+        raise NotImplementedError("Override in subclass")
+
+    def format_for_error(self) -> str:
+        raise NotImplementedError("Subclass should override")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/candidates.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/candidates.py
new file mode 100644
index 0000000000000000000000000000000000000000..f5bc343b91be9cd7038a64cda0df08a37f932e61
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/candidates.py
@@ -0,0 +1,556 @@
+import logging
+import sys
+from typing import TYPE_CHECKING, Any, FrozenSet, Iterable, Optional, Tuple, Union, cast
+
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+from pip._vendor.packaging.version import Version
+
+from pip._internal.exceptions import (
+    HashError,
+    InstallationSubprocessError,
+    MetadataInconsistent,
+)
+from pip._internal.metadata import BaseDistribution
+from pip._internal.models.link import Link, links_equivalent
+from pip._internal.models.wheel import Wheel
+from pip._internal.req.constructors import (
+    install_req_from_editable,
+    install_req_from_line,
+)
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.utils.direct_url_helpers import direct_url_from_link
+from pip._internal.utils.misc import normalize_version_info
+
+from .base import Candidate, CandidateVersion, Requirement, format_name
+
+if TYPE_CHECKING:
+    from .factory import Factory
+
+logger = logging.getLogger(__name__)
+
+BaseCandidate = Union[
+    "AlreadyInstalledCandidate",
+    "EditableCandidate",
+    "LinkCandidate",
+]
+
+# Avoid conflicting with the PyPI package "Python".
+REQUIRES_PYTHON_IDENTIFIER = cast(NormalizedName, "")
+
+
+def as_base_candidate(candidate: Candidate) -> Optional[BaseCandidate]:
+    """The runtime version of BaseCandidate."""
+    base_candidate_classes = (
+        AlreadyInstalledCandidate,
+        EditableCandidate,
+        LinkCandidate,
+    )
+    if isinstance(candidate, base_candidate_classes):
+        return candidate
+    return None
+
+
+def make_install_req_from_link(
+    link: Link, template: InstallRequirement
+) -> InstallRequirement:
+    assert not template.editable, "template is editable"
+    if template.req:
+        line = str(template.req)
+    else:
+        line = link.url
+    ireq = install_req_from_line(
+        line,
+        user_supplied=template.user_supplied,
+        comes_from=template.comes_from,
+        use_pep517=template.use_pep517,
+        isolated=template.isolated,
+        constraint=template.constraint,
+        options=dict(
+            install_options=template.install_options,
+            global_options=template.global_options,
+            hashes=template.hash_options,
+        ),
+        config_settings=template.config_settings,
+    )
+    ireq.original_link = template.original_link
+    ireq.link = link
+    return ireq
+
+
+def make_install_req_from_editable(
+    link: Link, template: InstallRequirement
+) -> InstallRequirement:
+    assert template.editable, "template not editable"
+    return install_req_from_editable(
+        link.url,
+        user_supplied=template.user_supplied,
+        comes_from=template.comes_from,
+        use_pep517=template.use_pep517,
+        isolated=template.isolated,
+        constraint=template.constraint,
+        permit_editable_wheels=template.permit_editable_wheels,
+        options=dict(
+            install_options=template.install_options,
+            global_options=template.global_options,
+            hashes=template.hash_options,
+        ),
+        config_settings=template.config_settings,
+    )
+
+
+def _make_install_req_from_dist(
+    dist: BaseDistribution, template: InstallRequirement
+) -> InstallRequirement:
+    if template.req:
+        line = str(template.req)
+    elif template.link:
+        line = f"{dist.canonical_name} @ {template.link.url}"
+    else:
+        line = f"{dist.canonical_name}=={dist.version}"
+    ireq = install_req_from_line(
+        line,
+        user_supplied=template.user_supplied,
+        comes_from=template.comes_from,
+        use_pep517=template.use_pep517,
+        isolated=template.isolated,
+        constraint=template.constraint,
+        options=dict(
+            install_options=template.install_options,
+            global_options=template.global_options,
+            hashes=template.hash_options,
+        ),
+        config_settings=template.config_settings,
+    )
+    ireq.satisfied_by = dist
+    return ireq
+
+
+class _InstallRequirementBackedCandidate(Candidate):
+    """A candidate backed by an ``InstallRequirement``.
+
+    This represents a package request with the target not being already
+    in the environment, and needs to be fetched and installed. The backing
+    ``InstallRequirement`` is responsible for most of the leg work; this
+    class exposes appropriate information to the resolver.
+
+    :param link: The link passed to the ``InstallRequirement``. The backing
+        ``InstallRequirement`` will use this link to fetch the distribution.
+    :param source_link: The link this candidate "originates" from. This is
+        different from ``link`` when the link is found in the wheel cache.
+        ``link`` would point to the wheel cache, while this points to the
+        found remote link (e.g. from pypi.org).
+    """
+
+    dist: BaseDistribution
+    is_installed = False
+
+    def __init__(
+        self,
+        link: Link,
+        source_link: Link,
+        ireq: InstallRequirement,
+        factory: "Factory",
+        name: Optional[NormalizedName] = None,
+        version: Optional[CandidateVersion] = None,
+    ) -> None:
+        self._link = link
+        self._source_link = source_link
+        self._factory = factory
+        self._ireq = ireq
+        self._name = name
+        self._version = version
+        self.dist = self._prepare()
+
+    def __str__(self) -> str:
+        return f"{self.name} {self.version}"
+
+    def __repr__(self) -> str:
+        return "{class_name}({link!r})".format(
+            class_name=self.__class__.__name__,
+            link=str(self._link),
+        )
+
+    def __hash__(self) -> int:
+        return hash((self.__class__, self._link))
+
+    def __eq__(self, other: Any) -> bool:
+        if isinstance(other, self.__class__):
+            return links_equivalent(self._link, other._link)
+        return False
+
+    @property
+    def source_link(self) -> Optional[Link]:
+        return self._source_link
+
+    @property
+    def project_name(self) -> NormalizedName:
+        """The normalised name of the project the candidate refers to"""
+        if self._name is None:
+            self._name = self.dist.canonical_name
+        return self._name
+
+    @property
+    def name(self) -> str:
+        return self.project_name
+
+    @property
+    def version(self) -> CandidateVersion:
+        if self._version is None:
+            self._version = self.dist.version
+        return self._version
+
+    def format_for_error(self) -> str:
+        return "{} {} (from {})".format(
+            self.name,
+            self.version,
+            self._link.file_path if self._link.is_file else self._link,
+        )
+
+    def _prepare_distribution(self) -> BaseDistribution:
+        raise NotImplementedError("Override in subclass")
+
+    def _check_metadata_consistency(self, dist: BaseDistribution) -> None:
+        """Check for consistency of project name and version of dist."""
+        if self._name is not None and self._name != dist.canonical_name:
+            raise MetadataInconsistent(
+                self._ireq,
+                "name",
+                self._name,
+                dist.canonical_name,
+            )
+        if self._version is not None and self._version != dist.version:
+            raise MetadataInconsistent(
+                self._ireq,
+                "version",
+                str(self._version),
+                str(dist.version),
+            )
+
+    def _prepare(self) -> BaseDistribution:
+        try:
+            dist = self._prepare_distribution()
+        except HashError as e:
+            # Provide HashError the underlying ireq that caused it. This
+            # provides context for the resulting error message to show the
+            # offending line to the user.
+            e.req = self._ireq
+            raise
+        except InstallationSubprocessError as exc:
+            # The output has been presented already, so don't duplicate it.
+            exc.context = "See above for output."
+            raise
+
+        self._check_metadata_consistency(dist)
+        return dist
+
+    def iter_dependencies(self, with_requires: bool) -> Iterable[Optional[Requirement]]:
+        requires = self.dist.iter_dependencies() if with_requires else ()
+        for r in requires:
+            yield self._factory.make_requirement_from_spec(str(r), self._ireq)
+        yield self._factory.make_requires_python_requirement(self.dist.requires_python)
+
+    def get_install_requirement(self) -> Optional[InstallRequirement]:
+        return self._ireq
+
+
+class LinkCandidate(_InstallRequirementBackedCandidate):
+    is_editable = False
+
+    def __init__(
+        self,
+        link: Link,
+        template: InstallRequirement,
+        factory: "Factory",
+        name: Optional[NormalizedName] = None,
+        version: Optional[CandidateVersion] = None,
+    ) -> None:
+        source_link = link
+        cache_entry = factory.get_wheel_cache_entry(link, name)
+        if cache_entry is not None:
+            logger.debug("Using cached wheel link: %s", cache_entry.link)
+            link = cache_entry.link
+        ireq = make_install_req_from_link(link, template)
+        assert ireq.link == link
+        if ireq.link.is_wheel and not ireq.link.is_file:
+            wheel = Wheel(ireq.link.filename)
+            wheel_name = canonicalize_name(wheel.name)
+            assert name == wheel_name, f"{name!r} != {wheel_name!r} for wheel"
+            # Version may not be present for PEP 508 direct URLs
+            if version is not None:
+                wheel_version = Version(wheel.version)
+                assert version == wheel_version, "{!r} != {!r} for wheel {}".format(
+                    version, wheel_version, name
+                )
+
+        if cache_entry is not None:
+            if cache_entry.persistent and template.link is template.original_link:
+                ireq.original_link_is_in_wheel_cache = True
+            if cache_entry.origin is not None:
+                ireq.download_info = cache_entry.origin
+            else:
+                # Legacy cache entry that does not have origin.json.
+                # download_info may miss the archive_info.hash field.
+                ireq.download_info = direct_url_from_link(
+                    source_link, link_is_in_wheel_cache=cache_entry.persistent
+                )
+
+        super().__init__(
+            link=link,
+            source_link=source_link,
+            ireq=ireq,
+            factory=factory,
+            name=name,
+            version=version,
+        )
+
+    def _prepare_distribution(self) -> BaseDistribution:
+        preparer = self._factory.preparer
+        return preparer.prepare_linked_requirement(self._ireq, parallel_builds=True)
+
+
+class EditableCandidate(_InstallRequirementBackedCandidate):
+    is_editable = True
+
+    def __init__(
+        self,
+        link: Link,
+        template: InstallRequirement,
+        factory: "Factory",
+        name: Optional[NormalizedName] = None,
+        version: Optional[CandidateVersion] = None,
+    ) -> None:
+        super().__init__(
+            link=link,
+            source_link=link,
+            ireq=make_install_req_from_editable(link, template),
+            factory=factory,
+            name=name,
+            version=version,
+        )
+
+    def _prepare_distribution(self) -> BaseDistribution:
+        return self._factory.preparer.prepare_editable_requirement(self._ireq)
+
+
+class AlreadyInstalledCandidate(Candidate):
+    is_installed = True
+    source_link = None
+
+    def __init__(
+        self,
+        dist: BaseDistribution,
+        template: InstallRequirement,
+        factory: "Factory",
+    ) -> None:
+        self.dist = dist
+        self._ireq = _make_install_req_from_dist(dist, template)
+        self._factory = factory
+
+        # This is just logging some messages, so we can do it eagerly.
+        # The returned dist would be exactly the same as self.dist because we
+        # set satisfied_by in _make_install_req_from_dist.
+        # TODO: Supply reason based on force_reinstall and upgrade_strategy.
+        skip_reason = "already satisfied"
+        factory.preparer.prepare_installed_requirement(self._ireq, skip_reason)
+
+    def __str__(self) -> str:
+        return str(self.dist)
+
+    def __repr__(self) -> str:
+        return "{class_name}({distribution!r})".format(
+            class_name=self.__class__.__name__,
+            distribution=self.dist,
+        )
+
+    def __hash__(self) -> int:
+        return hash((self.__class__, self.name, self.version))
+
+    def __eq__(self, other: Any) -> bool:
+        if isinstance(other, self.__class__):
+            return self.name == other.name and self.version == other.version
+        return False
+
+    @property
+    def project_name(self) -> NormalizedName:
+        return self.dist.canonical_name
+
+    @property
+    def name(self) -> str:
+        return self.project_name
+
+    @property
+    def version(self) -> CandidateVersion:
+        return self.dist.version
+
+    @property
+    def is_editable(self) -> bool:
+        return self.dist.editable
+
+    def format_for_error(self) -> str:
+        return f"{self.name} {self.version} (Installed)"
+
+    def iter_dependencies(self, with_requires: bool) -> Iterable[Optional[Requirement]]:
+        if not with_requires:
+            return
+        for r in self.dist.iter_dependencies():
+            yield self._factory.make_requirement_from_spec(str(r), self._ireq)
+
+    def get_install_requirement(self) -> Optional[InstallRequirement]:
+        return None
+
+
+class ExtrasCandidate(Candidate):
+    """A candidate that has 'extras', indicating additional dependencies.
+
+    Requirements can be for a project with dependencies, something like
+    foo[extra].  The extras don't affect the project/version being installed
+    directly, but indicate that we need additional dependencies. We model that
+    by having an artificial ExtrasCandidate that wraps the "base" candidate.
+
+    The ExtrasCandidate differs from the base in the following ways:
+
+    1. It has a unique name, of the form foo[extra]. This causes the resolver
+       to treat it as a separate node in the dependency graph.
+    2. When we're getting the candidate's dependencies,
+       a) We specify that we want the extra dependencies as well.
+       b) We add a dependency on the base candidate.
+          See below for why this is needed.
+    3. We return None for the underlying InstallRequirement, as the base
+       candidate will provide it, and we don't want to end up with duplicates.
+
+    The dependency on the base candidate is needed so that the resolver can't
+    decide that it should recommend foo[extra1] version 1.0 and foo[extra2]
+    version 2.0. Having those candidates depend on foo=1.0 and foo=2.0
+    respectively forces the resolver to recognise that this is a conflict.
+    """
+
+    def __init__(
+        self,
+        base: BaseCandidate,
+        extras: FrozenSet[str],
+    ) -> None:
+        self.base = base
+        self.extras = extras
+
+    def __str__(self) -> str:
+        name, rest = str(self.base).split(" ", 1)
+        return "{}[{}] {}".format(name, ",".join(self.extras), rest)
+
+    def __repr__(self) -> str:
+        return "{class_name}(base={base!r}, extras={extras!r})".format(
+            class_name=self.__class__.__name__,
+            base=self.base,
+            extras=self.extras,
+        )
+
+    def __hash__(self) -> int:
+        return hash((self.base, self.extras))
+
+    def __eq__(self, other: Any) -> bool:
+        if isinstance(other, self.__class__):
+            return self.base == other.base and self.extras == other.extras
+        return False
+
+    @property
+    def project_name(self) -> NormalizedName:
+        return self.base.project_name
+
+    @property
+    def name(self) -> str:
+        """The normalised name of the project the candidate refers to"""
+        return format_name(self.base.project_name, self.extras)
+
+    @property
+    def version(self) -> CandidateVersion:
+        return self.base.version
+
+    def format_for_error(self) -> str:
+        return "{} [{}]".format(
+            self.base.format_for_error(), ", ".join(sorted(self.extras))
+        )
+
+    @property
+    def is_installed(self) -> bool:
+        return self.base.is_installed
+
+    @property
+    def is_editable(self) -> bool:
+        return self.base.is_editable
+
+    @property
+    def source_link(self) -> Optional[Link]:
+        return self.base.source_link
+
+    def iter_dependencies(self, with_requires: bool) -> Iterable[Optional[Requirement]]:
+        factory = self.base._factory
+
+        # Add a dependency on the exact base
+        # (See note 2b in the class docstring)
+        yield factory.make_requirement_from_candidate(self.base)
+        if not with_requires:
+            return
+
+        # The user may have specified extras that the candidate doesn't
+        # support. We ignore any unsupported extras here.
+        valid_extras = self.extras.intersection(self.base.dist.iter_provided_extras())
+        invalid_extras = self.extras.difference(self.base.dist.iter_provided_extras())
+        for extra in sorted(invalid_extras):
+            logger.warning(
+                "%s %s does not provide the extra '%s'",
+                self.base.name,
+                self.version,
+                extra,
+            )
+
+        for r in self.base.dist.iter_dependencies(valid_extras):
+            requirement = factory.make_requirement_from_spec(
+                str(r), self.base._ireq, valid_extras
+            )
+            if requirement:
+                yield requirement
+
+    def get_install_requirement(self) -> Optional[InstallRequirement]:
+        # We don't return anything here, because we always
+        # depend on the base candidate, and we'll get the
+        # install requirement from that.
+        return None
+
+
+class RequiresPythonCandidate(Candidate):
+    is_installed = False
+    source_link = None
+
+    def __init__(self, py_version_info: Optional[Tuple[int, ...]]) -> None:
+        if py_version_info is not None:
+            version_info = normalize_version_info(py_version_info)
+        else:
+            version_info = sys.version_info[:3]
+        self._version = Version(".".join(str(c) for c in version_info))
+
+    # We don't need to implement __eq__() and __ne__() since there is always
+    # only one RequiresPythonCandidate in a resolution, i.e. the host Python.
+    # The built-in object.__eq__() and object.__ne__() do exactly what we want.
+
+    def __str__(self) -> str:
+        return f"Python {self._version}"
+
+    @property
+    def project_name(self) -> NormalizedName:
+        return REQUIRES_PYTHON_IDENTIFIER
+
+    @property
+    def name(self) -> str:
+        return REQUIRES_PYTHON_IDENTIFIER
+
+    @property
+    def version(self) -> CandidateVersion:
+        return self._version
+
+    def format_for_error(self) -> str:
+        return f"Python {self.version}"
+
+    def iter_dependencies(self, with_requires: bool) -> Iterable[Optional[Requirement]]:
+        return ()
+
+    def get_install_requirement(self) -> Optional[InstallRequirement]:
+        return None
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/factory.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/factory.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4c24b52a1bf4fd055f4a130e80f4401fe06ea6b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/factory.py
@@ -0,0 +1,731 @@
+import contextlib
+import functools
+import logging
+from typing import (
+    TYPE_CHECKING,
+    Dict,
+    FrozenSet,
+    Iterable,
+    Iterator,
+    List,
+    Mapping,
+    NamedTuple,
+    Optional,
+    Sequence,
+    Set,
+    Tuple,
+    TypeVar,
+    cast,
+)
+
+from pip._vendor.packaging.requirements import InvalidRequirement
+from pip._vendor.packaging.specifiers import SpecifierSet
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+from pip._vendor.resolvelib import ResolutionImpossible
+
+from pip._internal.cache import CacheEntry, WheelCache
+from pip._internal.exceptions import (
+    DistributionNotFound,
+    InstallationError,
+    MetadataInconsistent,
+    UnsupportedPythonVersion,
+    UnsupportedWheel,
+)
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import BaseDistribution, get_default_environment
+from pip._internal.models.link import Link
+from pip._internal.models.wheel import Wheel
+from pip._internal.operations.prepare import RequirementPreparer
+from pip._internal.req.constructors import install_req_from_link_and_ireq
+from pip._internal.req.req_install import (
+    InstallRequirement,
+    check_invalid_constraint_type,
+)
+from pip._internal.resolution.base import InstallRequirementProvider
+from pip._internal.utils.compatibility_tags import get_supported
+from pip._internal.utils.hashes import Hashes
+from pip._internal.utils.packaging import get_requirement
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+from .base import Candidate, CandidateVersion, Constraint, Requirement
+from .candidates import (
+    AlreadyInstalledCandidate,
+    BaseCandidate,
+    EditableCandidate,
+    ExtrasCandidate,
+    LinkCandidate,
+    RequiresPythonCandidate,
+    as_base_candidate,
+)
+from .found_candidates import FoundCandidates, IndexCandidateInfo
+from .requirements import (
+    ExplicitRequirement,
+    RequiresPythonRequirement,
+    SpecifierRequirement,
+    UnsatisfiableRequirement,
+)
+
+if TYPE_CHECKING:
+    from typing import Protocol
+
+    class ConflictCause(Protocol):
+        requirement: RequiresPythonRequirement
+        parent: Candidate
+
+
+logger = logging.getLogger(__name__)
+
+C = TypeVar("C")
+Cache = Dict[Link, C]
+
+
+class CollectedRootRequirements(NamedTuple):
+    requirements: List[Requirement]
+    constraints: Dict[str, Constraint]
+    user_requested: Dict[str, int]
+
+
+class Factory:
+    def __init__(
+        self,
+        finder: PackageFinder,
+        preparer: RequirementPreparer,
+        make_install_req: InstallRequirementProvider,
+        wheel_cache: Optional[WheelCache],
+        use_user_site: bool,
+        force_reinstall: bool,
+        ignore_installed: bool,
+        ignore_requires_python: bool,
+        py_version_info: Optional[Tuple[int, ...]] = None,
+    ) -> None:
+        self._finder = finder
+        self.preparer = preparer
+        self._wheel_cache = wheel_cache
+        self._python_candidate = RequiresPythonCandidate(py_version_info)
+        self._make_install_req_from_spec = make_install_req
+        self._use_user_site = use_user_site
+        self._force_reinstall = force_reinstall
+        self._ignore_requires_python = ignore_requires_python
+
+        self._build_failures: Cache[InstallationError] = {}
+        self._link_candidate_cache: Cache[LinkCandidate] = {}
+        self._editable_candidate_cache: Cache[EditableCandidate] = {}
+        self._installed_candidate_cache: Dict[str, AlreadyInstalledCandidate] = {}
+        self._extras_candidate_cache: Dict[
+            Tuple[int, FrozenSet[str]], ExtrasCandidate
+        ] = {}
+
+        if not ignore_installed:
+            env = get_default_environment()
+            self._installed_dists = {
+                dist.canonical_name: dist
+                for dist in env.iter_installed_distributions(local_only=False)
+            }
+        else:
+            self._installed_dists = {}
+
+    @property
+    def force_reinstall(self) -> bool:
+        return self._force_reinstall
+
+    def _fail_if_link_is_unsupported_wheel(self, link: Link) -> None:
+        if not link.is_wheel:
+            return
+        wheel = Wheel(link.filename)
+        if wheel.supported(self._finder.target_python.get_tags()):
+            return
+        msg = f"{link.filename} is not a supported wheel on this platform."
+        raise UnsupportedWheel(msg)
+
+    def _make_extras_candidate(
+        self, base: BaseCandidate, extras: FrozenSet[str]
+    ) -> ExtrasCandidate:
+        cache_key = (id(base), extras)
+        try:
+            candidate = self._extras_candidate_cache[cache_key]
+        except KeyError:
+            candidate = ExtrasCandidate(base, extras)
+            self._extras_candidate_cache[cache_key] = candidate
+        return candidate
+
+    def _make_candidate_from_dist(
+        self,
+        dist: BaseDistribution,
+        extras: FrozenSet[str],
+        template: InstallRequirement,
+    ) -> Candidate:
+        try:
+            base = self._installed_candidate_cache[dist.canonical_name]
+        except KeyError:
+            base = AlreadyInstalledCandidate(dist, template, factory=self)
+            self._installed_candidate_cache[dist.canonical_name] = base
+        if not extras:
+            return base
+        return self._make_extras_candidate(base, extras)
+
+    def _make_candidate_from_link(
+        self,
+        link: Link,
+        extras: FrozenSet[str],
+        template: InstallRequirement,
+        name: Optional[NormalizedName],
+        version: Optional[CandidateVersion],
+    ) -> Optional[Candidate]:
+        # TODO: Check already installed candidate, and use it if the link and
+        # editable flag match.
+
+        if link in self._build_failures:
+            # We already tried this candidate before, and it does not build.
+            # Don't bother trying again.
+            return None
+
+        if template.editable:
+            if link not in self._editable_candidate_cache:
+                try:
+                    self._editable_candidate_cache[link] = EditableCandidate(
+                        link,
+                        template,
+                        factory=self,
+                        name=name,
+                        version=version,
+                    )
+                except MetadataInconsistent as e:
+                    logger.info(
+                        "Discarding [blue underline]%s[/]: [yellow]%s[reset]",
+                        link,
+                        e,
+                        extra={"markup": True},
+                    )
+                    self._build_failures[link] = e
+                    return None
+
+            base: BaseCandidate = self._editable_candidate_cache[link]
+        else:
+            if link not in self._link_candidate_cache:
+                try:
+                    self._link_candidate_cache[link] = LinkCandidate(
+                        link,
+                        template,
+                        factory=self,
+                        name=name,
+                        version=version,
+                    )
+                except MetadataInconsistent as e:
+                    logger.info(
+                        "Discarding [blue underline]%s[/]: [yellow]%s[reset]",
+                        link,
+                        e,
+                        extra={"markup": True},
+                    )
+                    self._build_failures[link] = e
+                    return None
+            base = self._link_candidate_cache[link]
+
+        if not extras:
+            return base
+        return self._make_extras_candidate(base, extras)
+
+    def _iter_found_candidates(
+        self,
+        ireqs: Sequence[InstallRequirement],
+        specifier: SpecifierSet,
+        hashes: Hashes,
+        prefers_installed: bool,
+        incompatible_ids: Set[int],
+    ) -> Iterable[Candidate]:
+        if not ireqs:
+            return ()
+
+        # The InstallRequirement implementation requires us to give it a
+        # "template". Here we just choose the first requirement to represent
+        # all of them.
+        # Hopefully the Project model can correct this mismatch in the future.
+        template = ireqs[0]
+        assert template.req, "Candidates found on index must be PEP 508"
+        name = canonicalize_name(template.req.name)
+
+        extras: FrozenSet[str] = frozenset()
+        for ireq in ireqs:
+            assert ireq.req, "Candidates found on index must be PEP 508"
+            specifier &= ireq.req.specifier
+            hashes &= ireq.hashes(trust_internet=False)
+            extras |= frozenset(ireq.extras)
+
+        def _get_installed_candidate() -> Optional[Candidate]:
+            """Get the candidate for the currently-installed version."""
+            # If --force-reinstall is set, we want the version from the index
+            # instead, so we "pretend" there is nothing installed.
+            if self._force_reinstall:
+                return None
+            try:
+                installed_dist = self._installed_dists[name]
+            except KeyError:
+                return None
+            # Don't use the installed distribution if its version does not fit
+            # the current dependency graph.
+            if not specifier.contains(installed_dist.version, prereleases=True):
+                return None
+            candidate = self._make_candidate_from_dist(
+                dist=installed_dist,
+                extras=extras,
+                template=template,
+            )
+            # The candidate is a known incompatibility. Don't use it.
+            if id(candidate) in incompatible_ids:
+                return None
+            return candidate
+
+        def iter_index_candidate_infos() -> Iterator[IndexCandidateInfo]:
+            result = self._finder.find_best_candidate(
+                project_name=name,
+                specifier=specifier,
+                hashes=hashes,
+            )
+            icans = list(result.iter_applicable())
+
+            # PEP 592: Yanked releases are ignored unless the specifier
+            # explicitly pins a version (via '==' or '===') that can be
+            # solely satisfied by a yanked release.
+            all_yanked = all(ican.link.is_yanked for ican in icans)
+
+            def is_pinned(specifier: SpecifierSet) -> bool:
+                for sp in specifier:
+                    if sp.operator == "===":
+                        return True
+                    if sp.operator != "==":
+                        continue
+                    if sp.version.endswith(".*"):
+                        continue
+                    return True
+                return False
+
+            pinned = is_pinned(specifier)
+
+            # PackageFinder returns earlier versions first, so we reverse.
+            for ican in reversed(icans):
+                if not (all_yanked and pinned) and ican.link.is_yanked:
+                    continue
+                func = functools.partial(
+                    self._make_candidate_from_link,
+                    link=ican.link,
+                    extras=extras,
+                    template=template,
+                    name=name,
+                    version=ican.version,
+                )
+                yield ican.version, func
+
+        return FoundCandidates(
+            iter_index_candidate_infos,
+            _get_installed_candidate(),
+            prefers_installed,
+            incompatible_ids,
+        )
+
+    def _iter_explicit_candidates_from_base(
+        self,
+        base_requirements: Iterable[Requirement],
+        extras: FrozenSet[str],
+    ) -> Iterator[Candidate]:
+        """Produce explicit candidates from the base given an extra-ed package.
+
+        :param base_requirements: Requirements known to the resolver. The
+            requirements are guaranteed to not have extras.
+        :param extras: The extras to inject into the explicit requirements'
+            candidates.
+        """
+        for req in base_requirements:
+            lookup_cand, _ = req.get_candidate_lookup()
+            if lookup_cand is None:  # Not explicit.
+                continue
+            # We've stripped extras from the identifier, and should always
+            # get a BaseCandidate here, unless there's a bug elsewhere.
+            base_cand = as_base_candidate(lookup_cand)
+            assert base_cand is not None, "no extras here"
+            yield self._make_extras_candidate(base_cand, extras)
+
+    def _iter_candidates_from_constraints(
+        self,
+        identifier: str,
+        constraint: Constraint,
+        template: InstallRequirement,
+    ) -> Iterator[Candidate]:
+        """Produce explicit candidates from constraints.
+
+        This creates "fake" InstallRequirement objects that are basically clones
+        of what "should" be the template, but with original_link set to link.
+        """
+        for link in constraint.links:
+            self._fail_if_link_is_unsupported_wheel(link)
+            candidate = self._make_candidate_from_link(
+                link,
+                extras=frozenset(),
+                template=install_req_from_link_and_ireq(link, template),
+                name=canonicalize_name(identifier),
+                version=None,
+            )
+            if candidate:
+                yield candidate
+
+    def find_candidates(
+        self,
+        identifier: str,
+        requirements: Mapping[str, Iterable[Requirement]],
+        incompatibilities: Mapping[str, Iterator[Candidate]],
+        constraint: Constraint,
+        prefers_installed: bool,
+    ) -> Iterable[Candidate]:
+        # Collect basic lookup information from the requirements.
+        explicit_candidates: Set[Candidate] = set()
+        ireqs: List[InstallRequirement] = []
+        for req in requirements[identifier]:
+            cand, ireq = req.get_candidate_lookup()
+            if cand is not None:
+                explicit_candidates.add(cand)
+            if ireq is not None:
+                ireqs.append(ireq)
+
+        # If the current identifier contains extras, add explicit candidates
+        # from entries from extra-less identifier.
+        with contextlib.suppress(InvalidRequirement):
+            parsed_requirement = get_requirement(identifier)
+            explicit_candidates.update(
+                self._iter_explicit_candidates_from_base(
+                    requirements.get(parsed_requirement.name, ()),
+                    frozenset(parsed_requirement.extras),
+                ),
+            )
+
+        # Add explicit candidates from constraints. We only do this if there are
+        # known ireqs, which represent requirements not already explicit. If
+        # there are no ireqs, we're constraining already-explicit requirements,
+        # which is handled later when we return the explicit candidates.
+        if ireqs:
+            try:
+                explicit_candidates.update(
+                    self._iter_candidates_from_constraints(
+                        identifier,
+                        constraint,
+                        template=ireqs[0],
+                    ),
+                )
+            except UnsupportedWheel:
+                # If we're constrained to install a wheel incompatible with the
+                # target architecture, no candidates will ever be valid.
+                return ()
+
+        # Since we cache all the candidates, incompatibility identification
+        # can be made quicker by comparing only the id() values.
+        incompat_ids = {id(c) for c in incompatibilities.get(identifier, ())}
+
+        # If none of the requirements want an explicit candidate, we can ask
+        # the finder for candidates.
+        if not explicit_candidates:
+            return self._iter_found_candidates(
+                ireqs,
+                constraint.specifier,
+                constraint.hashes,
+                prefers_installed,
+                incompat_ids,
+            )
+
+        return (
+            c
+            for c in explicit_candidates
+            if id(c) not in incompat_ids
+            and constraint.is_satisfied_by(c)
+            and all(req.is_satisfied_by(c) for req in requirements[identifier])
+        )
+
+    def _make_requirement_from_install_req(
+        self, ireq: InstallRequirement, requested_extras: Iterable[str]
+    ) -> Optional[Requirement]:
+        if not ireq.match_markers(requested_extras):
+            logger.info(
+                "Ignoring %s: markers '%s' don't match your environment",
+                ireq.name,
+                ireq.markers,
+            )
+            return None
+        if not ireq.link:
+            return SpecifierRequirement(ireq)
+        self._fail_if_link_is_unsupported_wheel(ireq.link)
+        cand = self._make_candidate_from_link(
+            ireq.link,
+            extras=frozenset(ireq.extras),
+            template=ireq,
+            name=canonicalize_name(ireq.name) if ireq.name else None,
+            version=None,
+        )
+        if cand is None:
+            # There's no way we can satisfy a URL requirement if the underlying
+            # candidate fails to build. An unnamed URL must be user-supplied, so
+            # we fail eagerly. If the URL is named, an unsatisfiable requirement
+            # can make the resolver do the right thing, either backtrack (and
+            # maybe find some other requirement that's buildable) or raise a
+            # ResolutionImpossible eventually.
+            if not ireq.name:
+                raise self._build_failures[ireq.link]
+            return UnsatisfiableRequirement(canonicalize_name(ireq.name))
+        return self.make_requirement_from_candidate(cand)
+
+    def collect_root_requirements(
+        self, root_ireqs: List[InstallRequirement]
+    ) -> CollectedRootRequirements:
+        collected = CollectedRootRequirements([], {}, {})
+        for i, ireq in enumerate(root_ireqs):
+            if ireq.constraint:
+                # Ensure we only accept valid constraints
+                problem = check_invalid_constraint_type(ireq)
+                if problem:
+                    raise InstallationError(problem)
+                if not ireq.match_markers():
+                    continue
+                assert ireq.name, "Constraint must be named"
+                name = canonicalize_name(ireq.name)
+                if name in collected.constraints:
+                    collected.constraints[name] &= ireq
+                else:
+                    collected.constraints[name] = Constraint.from_ireq(ireq)
+            else:
+                req = self._make_requirement_from_install_req(
+                    ireq,
+                    requested_extras=(),
+                )
+                if req is None:
+                    continue
+                if ireq.user_supplied and req.name not in collected.user_requested:
+                    collected.user_requested[req.name] = i
+                collected.requirements.append(req)
+        return collected
+
+    def make_requirement_from_candidate(
+        self, candidate: Candidate
+    ) -> ExplicitRequirement:
+        return ExplicitRequirement(candidate)
+
+    def make_requirement_from_spec(
+        self,
+        specifier: str,
+        comes_from: Optional[InstallRequirement],
+        requested_extras: Iterable[str] = (),
+    ) -> Optional[Requirement]:
+        ireq = self._make_install_req_from_spec(specifier, comes_from)
+        return self._make_requirement_from_install_req(ireq, requested_extras)
+
+    def make_requires_python_requirement(
+        self,
+        specifier: SpecifierSet,
+    ) -> Optional[Requirement]:
+        if self._ignore_requires_python:
+            return None
+        # Don't bother creating a dependency for an empty Requires-Python.
+        if not str(specifier):
+            return None
+        return RequiresPythonRequirement(specifier, self._python_candidate)
+
+    def get_wheel_cache_entry(
+        self, link: Link, name: Optional[str]
+    ) -> Optional[CacheEntry]:
+        """Look up the link in the wheel cache.
+
+        If ``preparer.require_hashes`` is True, don't use the wheel cache,
+        because cached wheels, always built locally, have different hashes
+        than the files downloaded from the index server and thus throw false
+        hash mismatches. Furthermore, cached wheels at present have
+        nondeterministic contents due to file modification times.
+        """
+        if self._wheel_cache is None or self.preparer.require_hashes:
+            return None
+        return self._wheel_cache.get_cache_entry(
+            link=link,
+            package_name=name,
+            supported_tags=get_supported(),
+        )
+
+    def get_dist_to_uninstall(self, candidate: Candidate) -> Optional[BaseDistribution]:
+        # TODO: Are there more cases this needs to return True? Editable?
+        dist = self._installed_dists.get(candidate.project_name)
+        if dist is None:  # Not installed, no uninstallation required.
+            return None
+
+        # We're installing into global site. The current installation must
+        # be uninstalled, no matter it's in global or user site, because the
+        # user site installation has precedence over global.
+        if not self._use_user_site:
+            return dist
+
+        # We're installing into user site. Remove the user site installation.
+        if dist.in_usersite:
+            return dist
+
+        # We're installing into user site, but the installed incompatible
+        # package is in global site. We can't uninstall that, and would let
+        # the new user installation to "shadow" it. But shadowing won't work
+        # in virtual environments, so we error out.
+        if running_under_virtualenv() and dist.in_site_packages:
+            message = (
+                f"Will not install to the user site because it will lack "
+                f"sys.path precedence to {dist.raw_name} in {dist.location}"
+            )
+            raise InstallationError(message)
+        return None
+
+    def _report_requires_python_error(
+        self, causes: Sequence["ConflictCause"]
+    ) -> UnsupportedPythonVersion:
+        assert causes, "Requires-Python error reported with no cause"
+
+        version = self._python_candidate.version
+
+        if len(causes) == 1:
+            specifier = str(causes[0].requirement.specifier)
+            message = (
+                f"Package {causes[0].parent.name!r} requires a different "
+                f"Python: {version} not in {specifier!r}"
+            )
+            return UnsupportedPythonVersion(message)
+
+        message = f"Packages require a different Python. {version} not in:"
+        for cause in causes:
+            package = cause.parent.format_for_error()
+            specifier = str(cause.requirement.specifier)
+            message += f"\n{specifier!r} (required by {package})"
+        return UnsupportedPythonVersion(message)
+
+    def _report_single_requirement_conflict(
+        self, req: Requirement, parent: Optional[Candidate]
+    ) -> DistributionNotFound:
+        if parent is None:
+            req_disp = str(req)
+        else:
+            req_disp = f"{req} (from {parent.name})"
+
+        cands = self._finder.find_all_candidates(req.project_name)
+        skipped_by_requires_python = self._finder.requires_python_skipped_reasons()
+        versions = [str(v) for v in sorted({c.version for c in cands})]
+
+        if skipped_by_requires_python:
+            logger.critical(
+                "Ignored the following versions that require a different python "
+                "version: %s",
+                "; ".join(skipped_by_requires_python) or "none",
+            )
+        logger.critical(
+            "Could not find a version that satisfies the requirement %s "
+            "(from versions: %s)",
+            req_disp,
+            ", ".join(versions) or "none",
+        )
+        if str(req) == "requirements.txt":
+            logger.info(
+                "HINT: You are attempting to install a package literally "
+                'named "requirements.txt" (which cannot exist). Consider '
+                "using the '-r' flag to install the packages listed in "
+                "requirements.txt"
+            )
+
+        return DistributionNotFound(f"No matching distribution found for {req}")
+
+    def get_installation_error(
+        self,
+        e: "ResolutionImpossible[Requirement, Candidate]",
+        constraints: Dict[str, Constraint],
+    ) -> InstallationError:
+
+        assert e.causes, "Installation error reported with no cause"
+
+        # If one of the things we can't solve is "we need Python X.Y",
+        # that is what we report.
+        requires_python_causes = [
+            cause
+            for cause in e.causes
+            if isinstance(cause.requirement, RequiresPythonRequirement)
+            and not cause.requirement.is_satisfied_by(self._python_candidate)
+        ]
+        if requires_python_causes:
+            # The comprehension above makes sure all Requirement instances are
+            # RequiresPythonRequirement, so let's cast for convenience.
+            return self._report_requires_python_error(
+                cast("Sequence[ConflictCause]", requires_python_causes),
+            )
+
+        # Otherwise, we have a set of causes which can't all be satisfied
+        # at once.
+
+        # The simplest case is when we have *one* cause that can't be
+        # satisfied. We just report that case.
+        if len(e.causes) == 1:
+            req, parent = e.causes[0]
+            if req.name not in constraints:
+                return self._report_single_requirement_conflict(req, parent)
+
+        # OK, we now have a list of requirements that can't all be
+        # satisfied at once.
+
+        # A couple of formatting helpers
+        def text_join(parts: List[str]) -> str:
+            if len(parts) == 1:
+                return parts[0]
+
+            return ", ".join(parts[:-1]) + " and " + parts[-1]
+
+        def describe_trigger(parent: Candidate) -> str:
+            ireq = parent.get_install_requirement()
+            if not ireq or not ireq.comes_from:
+                return f"{parent.name}=={parent.version}"
+            if isinstance(ireq.comes_from, InstallRequirement):
+                return str(ireq.comes_from.name)
+            return str(ireq.comes_from)
+
+        triggers = set()
+        for req, parent in e.causes:
+            if parent is None:
+                # This is a root requirement, so we can report it directly
+                trigger = req.format_for_error()
+            else:
+                trigger = describe_trigger(parent)
+            triggers.add(trigger)
+
+        if triggers:
+            info = text_join(sorted(triggers))
+        else:
+            info = "the requested packages"
+
+        msg = (
+            "Cannot install {} because these package versions "
+            "have conflicting dependencies.".format(info)
+        )
+        logger.critical(msg)
+        msg = "\nThe conflict is caused by:"
+
+        relevant_constraints = set()
+        for req, parent in e.causes:
+            if req.name in constraints:
+                relevant_constraints.add(req.name)
+            msg = msg + "\n    "
+            if parent:
+                msg = msg + f"{parent.name} {parent.version} depends on "
+            else:
+                msg = msg + "The user requested "
+            msg = msg + req.format_for_error()
+        for key in relevant_constraints:
+            spec = constraints[key].specifier
+            msg += f"\n    The user requested (constraint) {key}{spec}"
+
+        msg = (
+            msg
+            + "\n\n"
+            + "To fix this you could try to:\n"
+            + "1. loosen the range of package versions you've specified\n"
+            + "2. remove package versions to allow pip attempt to solve "
+            + "the dependency conflict\n"
+        )
+
+        logger.info(msg)
+
+        return DistributionNotFound(
+            "ResolutionImpossible: for help visit "
+            "https://pip.pypa.io/en/latest/topics/dependency-resolution/"
+            "#dealing-with-dependency-conflicts"
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/found_candidates.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/found_candidates.py
new file mode 100644
index 0000000000000000000000000000000000000000..8663097b447cdd80c52e2b2abde33a4736ddb9c2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/found_candidates.py
@@ -0,0 +1,155 @@
+"""Utilities to lazily create and visit candidates found.
+
+Creating and visiting a candidate is a *very* costly operation. It involves
+fetching, extracting, potentially building modules from source, and verifying
+distribution metadata. It is therefore crucial for performance to keep
+everything here lazy all the way down, so we only touch candidates that we
+absolutely need, and not "download the world" when we only need one version of
+something.
+"""
+
+import functools
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any, Callable, Iterator, Optional, Set, Tuple
+
+from pip._vendor.packaging.version import _BaseVersion
+
+from .base import Candidate
+
+IndexCandidateInfo = Tuple[_BaseVersion, Callable[[], Optional[Candidate]]]
+
+if TYPE_CHECKING:
+    SequenceCandidate = Sequence[Candidate]
+else:
+    # For compatibility: Python before 3.9 does not support using [] on the
+    # Sequence class.
+    #
+    # >>> from collections.abc import Sequence
+    # >>> Sequence[str]
+    # Traceback (most recent call last):
+    #   File "", line 1, in 
+    # TypeError: 'ABCMeta' object is not subscriptable
+    #
+    # TODO: Remove this block after dropping Python 3.8 support.
+    SequenceCandidate = Sequence
+
+
+def _iter_built(infos: Iterator[IndexCandidateInfo]) -> Iterator[Candidate]:
+    """Iterator for ``FoundCandidates``.
+
+    This iterator is used when the package is not already installed. Candidates
+    from index come later in their normal ordering.
+    """
+    versions_found: Set[_BaseVersion] = set()
+    for version, func in infos:
+        if version in versions_found:
+            continue
+        candidate = func()
+        if candidate is None:
+            continue
+        yield candidate
+        versions_found.add(version)
+
+
+def _iter_built_with_prepended(
+    installed: Candidate, infos: Iterator[IndexCandidateInfo]
+) -> Iterator[Candidate]:
+    """Iterator for ``FoundCandidates``.
+
+    This iterator is used when the resolver prefers the already-installed
+    candidate and NOT to upgrade. The installed candidate is therefore
+    always yielded first, and candidates from index come later in their
+    normal ordering, except skipped when the version is already installed.
+    """
+    yield installed
+    versions_found: Set[_BaseVersion] = {installed.version}
+    for version, func in infos:
+        if version in versions_found:
+            continue
+        candidate = func()
+        if candidate is None:
+            continue
+        yield candidate
+        versions_found.add(version)
+
+
+def _iter_built_with_inserted(
+    installed: Candidate, infos: Iterator[IndexCandidateInfo]
+) -> Iterator[Candidate]:
+    """Iterator for ``FoundCandidates``.
+
+    This iterator is used when the resolver prefers to upgrade an
+    already-installed package. Candidates from index are returned in their
+    normal ordering, except replaced when the version is already installed.
+
+    The implementation iterates through and yields other candidates, inserting
+    the installed candidate exactly once before we start yielding older or
+    equivalent candidates, or after all other candidates if they are all newer.
+    """
+    versions_found: Set[_BaseVersion] = set()
+    for version, func in infos:
+        if version in versions_found:
+            continue
+        # If the installed candidate is better, yield it first.
+        if installed.version >= version:
+            yield installed
+            versions_found.add(installed.version)
+        candidate = func()
+        if candidate is None:
+            continue
+        yield candidate
+        versions_found.add(version)
+
+    # If the installed candidate is older than all other candidates.
+    if installed.version not in versions_found:
+        yield installed
+
+
+class FoundCandidates(SequenceCandidate):
+    """A lazy sequence to provide candidates to the resolver.
+
+    The intended usage is to return this from `find_matches()` so the resolver
+    can iterate through the sequence multiple times, but only access the index
+    page when remote packages are actually needed. This improve performances
+    when suitable candidates are already installed on disk.
+    """
+
+    def __init__(
+        self,
+        get_infos: Callable[[], Iterator[IndexCandidateInfo]],
+        installed: Optional[Candidate],
+        prefers_installed: bool,
+        incompatible_ids: Set[int],
+    ):
+        self._get_infos = get_infos
+        self._installed = installed
+        self._prefers_installed = prefers_installed
+        self._incompatible_ids = incompatible_ids
+
+    def __getitem__(self, index: Any) -> Any:
+        # Implemented to satisfy the ABC check. This is not needed by the
+        # resolver, and should not be used by the provider either (for
+        # performance reasons).
+        raise NotImplementedError("don't do this")
+
+    def __iter__(self) -> Iterator[Candidate]:
+        infos = self._get_infos()
+        if not self._installed:
+            iterator = _iter_built(infos)
+        elif self._prefers_installed:
+            iterator = _iter_built_with_prepended(self._installed, infos)
+        else:
+            iterator = _iter_built_with_inserted(self._installed, infos)
+        return (c for c in iterator if id(c) not in self._incompatible_ids)
+
+    def __len__(self) -> int:
+        # Implemented to satisfy the ABC check. This is not needed by the
+        # resolver, and should not be used by the provider either (for
+        # performance reasons).
+        raise NotImplementedError("don't do this")
+
+    @functools.lru_cache(maxsize=1)
+    def __bool__(self) -> bool:
+        if self._prefers_installed and self._installed:
+            return True
+        return any(self)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/provider.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/provider.py
new file mode 100644
index 0000000000000000000000000000000000000000..6300dfc57f051e461776b82591471c7dc7fc486d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/provider.py
@@ -0,0 +1,248 @@
+import collections
+import math
+from typing import (
+    TYPE_CHECKING,
+    Dict,
+    Iterable,
+    Iterator,
+    Mapping,
+    Sequence,
+    TypeVar,
+    Union,
+)
+
+from pip._vendor.resolvelib.providers import AbstractProvider
+
+from .base import Candidate, Constraint, Requirement
+from .candidates import REQUIRES_PYTHON_IDENTIFIER
+from .factory import Factory
+
+if TYPE_CHECKING:
+    from pip._vendor.resolvelib.providers import Preference
+    from pip._vendor.resolvelib.resolvers import RequirementInformation
+
+    PreferenceInformation = RequirementInformation[Requirement, Candidate]
+
+    _ProviderBase = AbstractProvider[Requirement, Candidate, str]
+else:
+    _ProviderBase = AbstractProvider
+
+# Notes on the relationship between the provider, the factory, and the
+# candidate and requirement classes.
+#
+# The provider is a direct implementation of the resolvelib class. Its role
+# is to deliver the API that resolvelib expects.
+#
+# Rather than work with completely abstract "requirement" and "candidate"
+# concepts as resolvelib does, pip has concrete classes implementing these two
+# ideas. The API of Requirement and Candidate objects are defined in the base
+# classes, but essentially map fairly directly to the equivalent provider
+# methods. In particular, `find_matches` and `is_satisfied_by` are
+# requirement methods, and `get_dependencies` is a candidate method.
+#
+# The factory is the interface to pip's internal mechanisms. It is stateless,
+# and is created by the resolver and held as a property of the provider. It is
+# responsible for creating Requirement and Candidate objects, and provides
+# services to those objects (access to pip's finder and preparer).
+
+
+D = TypeVar("D")
+V = TypeVar("V")
+
+
+def _get_with_identifier(
+    mapping: Mapping[str, V],
+    identifier: str,
+    default: D,
+) -> Union[D, V]:
+    """Get item from a package name lookup mapping with a resolver identifier.
+
+    This extra logic is needed when the target mapping is keyed by package
+    name, which cannot be directly looked up with an identifier (which may
+    contain requested extras). Additional logic is added to also look up a value
+    by "cleaning up" the extras from the identifier.
+    """
+    if identifier in mapping:
+        return mapping[identifier]
+    # HACK: Theoretically we should check whether this identifier is a valid
+    # "NAME[EXTRAS]" format, and parse out the name part with packaging or
+    # some regular expression. But since pip's resolver only spits out three
+    # kinds of identifiers: normalized PEP 503 names, normalized names plus
+    # extras, and Requires-Python, we can cheat a bit here.
+    name, open_bracket, _ = identifier.partition("[")
+    if open_bracket and name in mapping:
+        return mapping[name]
+    return default
+
+
+class PipProvider(_ProviderBase):
+    """Pip's provider implementation for resolvelib.
+
+    :params constraints: A mapping of constraints specified by the user. Keys
+        are canonicalized project names.
+    :params ignore_dependencies: Whether the user specified ``--no-deps``.
+    :params upgrade_strategy: The user-specified upgrade strategy.
+    :params user_requested: A set of canonicalized package names that the user
+        supplied for pip to install/upgrade.
+    """
+
+    def __init__(
+        self,
+        factory: Factory,
+        constraints: Dict[str, Constraint],
+        ignore_dependencies: bool,
+        upgrade_strategy: str,
+        user_requested: Dict[str, int],
+    ) -> None:
+        self._factory = factory
+        self._constraints = constraints
+        self._ignore_dependencies = ignore_dependencies
+        self._upgrade_strategy = upgrade_strategy
+        self._user_requested = user_requested
+        self._known_depths: Dict[str, float] = collections.defaultdict(lambda: math.inf)
+
+    def identify(self, requirement_or_candidate: Union[Requirement, Candidate]) -> str:
+        return requirement_or_candidate.name
+
+    def get_preference(  # type: ignore
+        self,
+        identifier: str,
+        resolutions: Mapping[str, Candidate],
+        candidates: Mapping[str, Iterator[Candidate]],
+        information: Mapping[str, Iterable["PreferenceInformation"]],
+        backtrack_causes: Sequence["PreferenceInformation"],
+    ) -> "Preference":
+        """Produce a sort key for given requirement based on preference.
+
+        The lower the return value is, the more preferred this group of
+        arguments is.
+
+        Currently pip considers the following in order:
+
+        * Prefer if any of the known requirements is "direct", e.g. points to an
+          explicit URL.
+        * If equal, prefer if any requirement is "pinned", i.e. contains
+          operator ``===`` or ``==``.
+        * If equal, calculate an approximate "depth" and resolve requirements
+          closer to the user-specified requirements first.
+        * Order user-specified requirements by the order they are specified.
+        * If equal, prefers "non-free" requirements, i.e. contains at least one
+          operator, such as ``>=`` or ``<``.
+        * If equal, order alphabetically for consistency (helps debuggability).
+        """
+        lookups = (r.get_candidate_lookup() for r, _ in information[identifier])
+        candidate, ireqs = zip(*lookups)
+        operators = [
+            specifier.operator
+            for specifier_set in (ireq.specifier for ireq in ireqs if ireq)
+            for specifier in specifier_set
+        ]
+
+        direct = candidate is not None
+        pinned = any(op[:2] == "==" for op in operators)
+        unfree = bool(operators)
+
+        try:
+            requested_order: Union[int, float] = self._user_requested[identifier]
+        except KeyError:
+            requested_order = math.inf
+            parent_depths = (
+                self._known_depths[parent.name] if parent is not None else 0.0
+                for _, parent in information[identifier]
+            )
+            inferred_depth = min(d for d in parent_depths) + 1.0
+        else:
+            inferred_depth = 1.0
+        self._known_depths[identifier] = inferred_depth
+
+        requested_order = self._user_requested.get(identifier, math.inf)
+
+        # Requires-Python has only one candidate and the check is basically
+        # free, so we always do it first to avoid needless work if it fails.
+        requires_python = identifier == REQUIRES_PYTHON_IDENTIFIER
+
+        # HACK: Setuptools have a very long and solid backward compatibility
+        # track record, and extremely few projects would request a narrow,
+        # non-recent version range of it since that would break a lot things.
+        # (Most projects specify it only to request for an installer feature,
+        # which does not work, but that's another topic.) Intentionally
+        # delaying Setuptools helps reduce branches the resolver has to check.
+        # This serves as a temporary fix for issues like "apache-airflow[all]"
+        # while we work on "proper" branch pruning techniques.
+        delay_this = identifier == "setuptools"
+
+        # Prefer the causes of backtracking on the assumption that the problem
+        # resolving the dependency tree is related to the failures that caused
+        # the backtracking
+        backtrack_cause = self.is_backtrack_cause(identifier, backtrack_causes)
+
+        return (
+            not requires_python,
+            delay_this,
+            not direct,
+            not pinned,
+            not backtrack_cause,
+            inferred_depth,
+            requested_order,
+            not unfree,
+            identifier,
+        )
+
+    def find_matches(
+        self,
+        identifier: str,
+        requirements: Mapping[str, Iterator[Requirement]],
+        incompatibilities: Mapping[str, Iterator[Candidate]],
+    ) -> Iterable[Candidate]:
+        def _eligible_for_upgrade(identifier: str) -> bool:
+            """Are upgrades allowed for this project?
+
+            This checks the upgrade strategy, and whether the project was one
+            that the user specified in the command line, in order to decide
+            whether we should upgrade if there's a newer version available.
+
+            (Note that we don't need access to the `--upgrade` flag, because
+            an upgrade strategy of "to-satisfy-only" means that `--upgrade`
+            was not specified).
+            """
+            if self._upgrade_strategy == "eager":
+                return True
+            elif self._upgrade_strategy == "only-if-needed":
+                user_order = _get_with_identifier(
+                    self._user_requested,
+                    identifier,
+                    default=None,
+                )
+                return user_order is not None
+            return False
+
+        constraint = _get_with_identifier(
+            self._constraints,
+            identifier,
+            default=Constraint.empty(),
+        )
+        return self._factory.find_candidates(
+            identifier=identifier,
+            requirements=requirements,
+            constraint=constraint,
+            prefers_installed=(not _eligible_for_upgrade(identifier)),
+            incompatibilities=incompatibilities,
+        )
+
+    def is_satisfied_by(self, requirement: Requirement, candidate: Candidate) -> bool:
+        return requirement.is_satisfied_by(candidate)
+
+    def get_dependencies(self, candidate: Candidate) -> Sequence[Requirement]:
+        with_requires = not self._ignore_dependencies
+        return [r for r in candidate.iter_dependencies(with_requires) if r is not None]
+
+    @staticmethod
+    def is_backtrack_cause(
+        identifier: str, backtrack_causes: Sequence["PreferenceInformation"]
+    ) -> bool:
+        for backtrack_cause in backtrack_causes:
+            if identifier == backtrack_cause.requirement.name:
+                return True
+            if backtrack_cause.parent and identifier == backtrack_cause.parent.name:
+                return True
+        return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/reporter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/reporter.py
new file mode 100644
index 0000000000000000000000000000000000000000..6ced5329b814e0fd3c397bb11dc69a82b06eb1f4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/reporter.py
@@ -0,0 +1,68 @@
+from collections import defaultdict
+from logging import getLogger
+from typing import Any, DefaultDict
+
+from pip._vendor.resolvelib.reporters import BaseReporter
+
+from .base import Candidate, Requirement
+
+logger = getLogger(__name__)
+
+
+class PipReporter(BaseReporter):
+    def __init__(self) -> None:
+        self.backtracks_by_package: DefaultDict[str, int] = defaultdict(int)
+
+        self._messages_at_backtrack = {
+            1: (
+                "pip is looking at multiple versions of {package_name} to "
+                "determine which version is compatible with other "
+                "requirements. This could take a while."
+            ),
+            8: (
+                "pip is looking at multiple versions of {package_name} to "
+                "determine which version is compatible with other "
+                "requirements. This could take a while."
+            ),
+            13: (
+                "This is taking longer than usual. You might need to provide "
+                "the dependency resolver with stricter constraints to reduce "
+                "runtime. See https://pip.pypa.io/warnings/backtracking for "
+                "guidance. If you want to abort this run, press Ctrl + C."
+            ),
+        }
+
+    def backtracking(self, candidate: Candidate) -> None:
+        self.backtracks_by_package[candidate.name] += 1
+
+        count = self.backtracks_by_package[candidate.name]
+        if count not in self._messages_at_backtrack:
+            return
+
+        message = self._messages_at_backtrack[count]
+        logger.info("INFO: %s", message.format(package_name=candidate.name))
+
+
+class PipDebuggingReporter(BaseReporter):
+    """A reporter that does an info log for every event it sees."""
+
+    def starting(self) -> None:
+        logger.info("Reporter.starting()")
+
+    def starting_round(self, index: int) -> None:
+        logger.info("Reporter.starting_round(%r)", index)
+
+    def ending_round(self, index: int, state: Any) -> None:
+        logger.info("Reporter.ending_round(%r, state)", index)
+
+    def ending(self, state: Any) -> None:
+        logger.info("Reporter.ending(%r)", state)
+
+    def adding_requirement(self, requirement: Requirement, parent: Candidate) -> None:
+        logger.info("Reporter.adding_requirement(%r, %r)", requirement, parent)
+
+    def backtracking(self, candidate: Candidate) -> None:
+        logger.info("Reporter.backtracking(%r)", candidate)
+
+    def pinning(self, candidate: Candidate) -> None:
+        logger.info("Reporter.pinning(%r)", candidate)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/requirements.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/requirements.py
new file mode 100644
index 0000000000000000000000000000000000000000..f561f1f1e270666ccd74c9d61f78c9c24f5c4c99
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/requirements.py
@@ -0,0 +1,166 @@
+from pip._vendor.packaging.specifiers import SpecifierSet
+from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
+
+from pip._internal.req.req_install import InstallRequirement
+
+from .base import Candidate, CandidateLookup, Requirement, format_name
+
+
+class ExplicitRequirement(Requirement):
+    def __init__(self, candidate: Candidate) -> None:
+        self.candidate = candidate
+
+    def __str__(self) -> str:
+        return str(self.candidate)
+
+    def __repr__(self) -> str:
+        return "{class_name}({candidate!r})".format(
+            class_name=self.__class__.__name__,
+            candidate=self.candidate,
+        )
+
+    @property
+    def project_name(self) -> NormalizedName:
+        # No need to canonicalize - the candidate did this
+        return self.candidate.project_name
+
+    @property
+    def name(self) -> str:
+        # No need to canonicalize - the candidate did this
+        return self.candidate.name
+
+    def format_for_error(self) -> str:
+        return self.candidate.format_for_error()
+
+    def get_candidate_lookup(self) -> CandidateLookup:
+        return self.candidate, None
+
+    def is_satisfied_by(self, candidate: Candidate) -> bool:
+        return candidate == self.candidate
+
+
+class SpecifierRequirement(Requirement):
+    def __init__(self, ireq: InstallRequirement) -> None:
+        assert ireq.link is None, "This is a link, not a specifier"
+        self._ireq = ireq
+        self._extras = frozenset(ireq.extras)
+
+    def __str__(self) -> str:
+        return str(self._ireq.req)
+
+    def __repr__(self) -> str:
+        return "{class_name}({requirement!r})".format(
+            class_name=self.__class__.__name__,
+            requirement=str(self._ireq.req),
+        )
+
+    @property
+    def project_name(self) -> NormalizedName:
+        assert self._ireq.req, "Specifier-backed ireq is always PEP 508"
+        return canonicalize_name(self._ireq.req.name)
+
+    @property
+    def name(self) -> str:
+        return format_name(self.project_name, self._extras)
+
+    def format_for_error(self) -> str:
+
+        # Convert comma-separated specifiers into "A, B, ..., F and G"
+        # This makes the specifier a bit more "human readable", without
+        # risking a change in meaning. (Hopefully! Not all edge cases have
+        # been checked)
+        parts = [s.strip() for s in str(self).split(",")]
+        if len(parts) == 0:
+            return ""
+        elif len(parts) == 1:
+            return parts[0]
+
+        return ", ".join(parts[:-1]) + " and " + parts[-1]
+
+    def get_candidate_lookup(self) -> CandidateLookup:
+        return None, self._ireq
+
+    def is_satisfied_by(self, candidate: Candidate) -> bool:
+        assert candidate.name == self.name, (
+            f"Internal issue: Candidate is not for this requirement "
+            f"{candidate.name} vs {self.name}"
+        )
+        # We can safely always allow prereleases here since PackageFinder
+        # already implements the prerelease logic, and would have filtered out
+        # prerelease candidates if the user does not expect them.
+        assert self._ireq.req, "Specifier-backed ireq is always PEP 508"
+        spec = self._ireq.req.specifier
+        return spec.contains(candidate.version, prereleases=True)
+
+
+class RequiresPythonRequirement(Requirement):
+    """A requirement representing Requires-Python metadata."""
+
+    def __init__(self, specifier: SpecifierSet, match: Candidate) -> None:
+        self.specifier = specifier
+        self._candidate = match
+
+    def __str__(self) -> str:
+        return f"Python {self.specifier}"
+
+    def __repr__(self) -> str:
+        return "{class_name}({specifier!r})".format(
+            class_name=self.__class__.__name__,
+            specifier=str(self.specifier),
+        )
+
+    @property
+    def project_name(self) -> NormalizedName:
+        return self._candidate.project_name
+
+    @property
+    def name(self) -> str:
+        return self._candidate.name
+
+    def format_for_error(self) -> str:
+        return str(self)
+
+    def get_candidate_lookup(self) -> CandidateLookup:
+        if self.specifier.contains(self._candidate.version, prereleases=True):
+            return self._candidate, None
+        return None, None
+
+    def is_satisfied_by(self, candidate: Candidate) -> bool:
+        assert candidate.name == self._candidate.name, "Not Python candidate"
+        # We can safely always allow prereleases here since PackageFinder
+        # already implements the prerelease logic, and would have filtered out
+        # prerelease candidates if the user does not expect them.
+        return self.specifier.contains(candidate.version, prereleases=True)
+
+
+class UnsatisfiableRequirement(Requirement):
+    """A requirement that cannot be satisfied."""
+
+    def __init__(self, name: NormalizedName) -> None:
+        self._name = name
+
+    def __str__(self) -> str:
+        return f"{self._name} (unavailable)"
+
+    def __repr__(self) -> str:
+        return "{class_name}({name!r})".format(
+            class_name=self.__class__.__name__,
+            name=str(self._name),
+        )
+
+    @property
+    def project_name(self) -> NormalizedName:
+        return self._name
+
+    @property
+    def name(self) -> str:
+        return self._name
+
+    def format_for_error(self) -> str:
+        return str(self)
+
+    def get_candidate_lookup(self) -> CandidateLookup:
+        return None, None
+
+    def is_satisfied_by(self, candidate: Candidate) -> bool:
+        return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/resolver.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/resolver.py
new file mode 100644
index 0000000000000000000000000000000000000000..a605d6c254f519ec221b18f104a62b758241a99b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/resolution/resolvelib/resolver.py
@@ -0,0 +1,296 @@
+import functools
+import logging
+import os
+from typing import TYPE_CHECKING, Dict, List, Optional, Set, Tuple, cast
+
+from pip._vendor.packaging.utils import canonicalize_name
+from pip._vendor.resolvelib import BaseReporter, ResolutionImpossible
+from pip._vendor.resolvelib import Resolver as RLResolver
+from pip._vendor.resolvelib.structs import DirectedGraph
+
+from pip._internal.cache import WheelCache
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.operations.prepare import RequirementPreparer
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.req.req_set import RequirementSet
+from pip._internal.resolution.base import BaseResolver, InstallRequirementProvider
+from pip._internal.resolution.resolvelib.provider import PipProvider
+from pip._internal.resolution.resolvelib.reporter import (
+    PipDebuggingReporter,
+    PipReporter,
+)
+
+from .base import Candidate, Requirement
+from .factory import Factory
+
+if TYPE_CHECKING:
+    from pip._vendor.resolvelib.resolvers import Result as RLResult
+
+    Result = RLResult[Requirement, Candidate, str]
+
+
+logger = logging.getLogger(__name__)
+
+
+class Resolver(BaseResolver):
+    _allowed_strategies = {"eager", "only-if-needed", "to-satisfy-only"}
+
+    def __init__(
+        self,
+        preparer: RequirementPreparer,
+        finder: PackageFinder,
+        wheel_cache: Optional[WheelCache],
+        make_install_req: InstallRequirementProvider,
+        use_user_site: bool,
+        ignore_dependencies: bool,
+        ignore_installed: bool,
+        ignore_requires_python: bool,
+        force_reinstall: bool,
+        upgrade_strategy: str,
+        py_version_info: Optional[Tuple[int, ...]] = None,
+    ):
+        super().__init__()
+        assert upgrade_strategy in self._allowed_strategies
+
+        self.factory = Factory(
+            finder=finder,
+            preparer=preparer,
+            make_install_req=make_install_req,
+            wheel_cache=wheel_cache,
+            use_user_site=use_user_site,
+            force_reinstall=force_reinstall,
+            ignore_installed=ignore_installed,
+            ignore_requires_python=ignore_requires_python,
+            py_version_info=py_version_info,
+        )
+        self.ignore_dependencies = ignore_dependencies
+        self.upgrade_strategy = upgrade_strategy
+        self._result: Optional[Result] = None
+
+    def resolve(
+        self, root_reqs: List[InstallRequirement], check_supported_wheels: bool
+    ) -> RequirementSet:
+        collected = self.factory.collect_root_requirements(root_reqs)
+        provider = PipProvider(
+            factory=self.factory,
+            constraints=collected.constraints,
+            ignore_dependencies=self.ignore_dependencies,
+            upgrade_strategy=self.upgrade_strategy,
+            user_requested=collected.user_requested,
+        )
+        if "PIP_RESOLVER_DEBUG" in os.environ:
+            reporter: BaseReporter = PipDebuggingReporter()
+        else:
+            reporter = PipReporter()
+        resolver: RLResolver[Requirement, Candidate, str] = RLResolver(
+            provider,
+            reporter,
+        )
+
+        try:
+            try_to_avoid_resolution_too_deep = 2000000
+            result = self._result = resolver.resolve(
+                collected.requirements, max_rounds=try_to_avoid_resolution_too_deep
+            )
+
+        except ResolutionImpossible as e:
+            error = self.factory.get_installation_error(
+                cast("ResolutionImpossible[Requirement, Candidate]", e),
+                collected.constraints,
+            )
+            raise error from e
+
+        req_set = RequirementSet(check_supported_wheels=check_supported_wheels)
+        for candidate in result.mapping.values():
+            ireq = candidate.get_install_requirement()
+            if ireq is None:
+                continue
+
+            # Check if there is already an installation under the same name,
+            # and set a flag for later stages to uninstall it, if needed.
+            installed_dist = self.factory.get_dist_to_uninstall(candidate)
+            if installed_dist is None:
+                # There is no existing installation -- nothing to uninstall.
+                ireq.should_reinstall = False
+            elif self.factory.force_reinstall:
+                # The --force-reinstall flag is set -- reinstall.
+                ireq.should_reinstall = True
+            elif installed_dist.version != candidate.version:
+                # The installation is different in version -- reinstall.
+                ireq.should_reinstall = True
+            elif candidate.is_editable or installed_dist.editable:
+                # The incoming distribution is editable, or different in
+                # editable-ness to installation -- reinstall.
+                ireq.should_reinstall = True
+            elif candidate.source_link and candidate.source_link.is_file:
+                # The incoming distribution is under file://
+                if candidate.source_link.is_wheel:
+                    # is a local wheel -- do nothing.
+                    logger.info(
+                        "%s is already installed with the same version as the "
+                        "provided wheel. Use --force-reinstall to force an "
+                        "installation of the wheel.",
+                        ireq.name,
+                    )
+                    continue
+
+                # is a local sdist or path -- reinstall
+                ireq.should_reinstall = True
+            else:
+                continue
+
+            link = candidate.source_link
+            if link and link.is_yanked:
+                # The reason can contain non-ASCII characters, Unicode
+                # is required for Python 2.
+                msg = (
+                    "The candidate selected for download or install is a "
+                    "yanked version: {name!r} candidate (version {version} "
+                    "at {link})\nReason for being yanked: {reason}"
+                ).format(
+                    name=candidate.name,
+                    version=candidate.version,
+                    link=link,
+                    reason=link.yanked_reason or "",
+                )
+                logger.warning(msg)
+
+            req_set.add_named_requirement(ireq)
+
+        reqs = req_set.all_requirements
+        self.factory.preparer.prepare_linked_requirements_more(reqs)
+        return req_set
+
+    def get_installation_order(
+        self, req_set: RequirementSet
+    ) -> List[InstallRequirement]:
+        """Get order for installation of requirements in RequirementSet.
+
+        The returned list contains a requirement before another that depends on
+        it. This helps ensure that the environment is kept consistent as they
+        get installed one-by-one.
+
+        The current implementation creates a topological ordering of the
+        dependency graph, giving more weight to packages with less
+        or no dependencies, while breaking any cycles in the graph at
+        arbitrary points. We make no guarantees about where the cycle
+        would be broken, other than it *would* be broken.
+        """
+        assert self._result is not None, "must call resolve() first"
+
+        if not req_set.requirements:
+            # Nothing is left to install, so we do not need an order.
+            return []
+
+        graph = self._result.graph
+        weights = get_topological_weights(graph, set(req_set.requirements.keys()))
+
+        sorted_items = sorted(
+            req_set.requirements.items(),
+            key=functools.partial(_req_set_item_sorter, weights=weights),
+            reverse=True,
+        )
+        return [ireq for _, ireq in sorted_items]
+
+
+def get_topological_weights(
+    graph: "DirectedGraph[Optional[str]]", requirement_keys: Set[str]
+) -> Dict[Optional[str], int]:
+    """Assign weights to each node based on how "deep" they are.
+
+    This implementation may change at any point in the future without prior
+    notice.
+
+    We first simplify the dependency graph by pruning any leaves and giving them
+    the highest weight: a package without any dependencies should be installed
+    first. This is done again and again in the same way, giving ever less weight
+    to the newly found leaves. The loop stops when no leaves are left: all
+    remaining packages have at least one dependency left in the graph.
+
+    Then we continue with the remaining graph, by taking the length for the
+    longest path to any node from root, ignoring any paths that contain a single
+    node twice (i.e. cycles). This is done through a depth-first search through
+    the graph, while keeping track of the path to the node.
+
+    Cycles in the graph result would result in node being revisited while also
+    being on its own path. In this case, take no action. This helps ensure we
+    don't get stuck in a cycle.
+
+    When assigning weight, the longer path (i.e. larger length) is preferred.
+
+    We are only interested in the weights of packages that are in the
+    requirement_keys.
+    """
+    path: Set[Optional[str]] = set()
+    weights: Dict[Optional[str], int] = {}
+
+    def visit(node: Optional[str]) -> None:
+        if node in path:
+            # We hit a cycle, so we'll break it here.
+            return
+
+        # Time to visit the children!
+        path.add(node)
+        for child in graph.iter_children(node):
+            visit(child)
+        path.remove(node)
+
+        if node not in requirement_keys:
+            return
+
+        last_known_parent_count = weights.get(node, 0)
+        weights[node] = max(last_known_parent_count, len(path))
+
+    # Simplify the graph, pruning leaves that have no dependencies.
+    # This is needed for large graphs (say over 200 packages) because the
+    # `visit` function is exponentially slower then, taking minutes.
+    # See https://github.com/pypa/pip/issues/10557
+    # We will loop until we explicitly break the loop.
+    while True:
+        leaves = set()
+        for key in graph:
+            if key is None:
+                continue
+            for _child in graph.iter_children(key):
+                # This means we have at least one child
+                break
+            else:
+                # No child.
+                leaves.add(key)
+        if not leaves:
+            # We are done simplifying.
+            break
+        # Calculate the weight for the leaves.
+        weight = len(graph) - 1
+        for leaf in leaves:
+            if leaf not in requirement_keys:
+                continue
+            weights[leaf] = weight
+        # Remove the leaves from the graph, making it simpler.
+        for leaf in leaves:
+            graph.remove(leaf)
+
+    # Visit the remaining graph.
+    # `None` is guaranteed to be the root node by resolvelib.
+    visit(None)
+
+    # Sanity check: all requirement keys should be in the weights,
+    # and no other keys should be in the weights.
+    difference = set(weights.keys()).difference(requirement_keys)
+    assert not difference, difference
+
+    return weights
+
+
+def _req_set_item_sorter(
+    item: Tuple[str, InstallRequirement],
+    weights: Dict[Optional[str], int],
+) -> Tuple[int, str]:
+    """Key function used to sort install requirements for installation.
+
+    Based on the "weight" mapping calculated in ``get_installation_order()``.
+    The canonical package name is returned as the second member as a tie-
+    breaker to ensure the result is predictable, which is useful in tests.
+    """
+    name = canonicalize_name(item[0])
+    return weights[name], name
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/self_outdated_check.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/self_outdated_check.py
new file mode 100644
index 0000000000000000000000000000000000000000..41cc42c5677ddf0709d9eeb894eb8dbe4fd16f91
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/self_outdated_check.py
@@ -0,0 +1,242 @@
+import datetime
+import functools
+import hashlib
+import json
+import logging
+import optparse
+import os.path
+import sys
+from dataclasses import dataclass
+from typing import Any, Callable, Dict, Optional
+
+from pip._vendor.packaging.version import parse as parse_version
+from pip._vendor.rich.console import Group
+from pip._vendor.rich.markup import escape
+from pip._vendor.rich.text import Text
+
+from pip._internal.index.collector import LinkCollector
+from pip._internal.index.package_finder import PackageFinder
+from pip._internal.metadata import get_default_environment
+from pip._internal.metadata.base import DistributionVersion
+from pip._internal.models.selection_prefs import SelectionPreferences
+from pip._internal.network.session import PipSession
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.entrypoints import (
+    get_best_invocation_for_this_pip,
+    get_best_invocation_for_this_python,
+)
+from pip._internal.utils.filesystem import adjacent_tmp_file, check_path_owner, replace
+from pip._internal.utils.misc import ensure_dir
+
+_DATE_FMT = "%Y-%m-%dT%H:%M:%SZ"
+
+
+logger = logging.getLogger(__name__)
+
+
+def _get_statefile_name(key: str) -> str:
+    key_bytes = key.encode()
+    name = hashlib.sha224(key_bytes).hexdigest()
+    return name
+
+
+class SelfCheckState:
+    def __init__(self, cache_dir: str) -> None:
+        self._state: Dict[str, Any] = {}
+        self._statefile_path = None
+
+        # Try to load the existing state
+        if cache_dir:
+            self._statefile_path = os.path.join(
+                cache_dir, "selfcheck", _get_statefile_name(self.key)
+            )
+            try:
+                with open(self._statefile_path, encoding="utf-8") as statefile:
+                    self._state = json.load(statefile)
+            except (OSError, ValueError, KeyError):
+                # Explicitly suppressing exceptions, since we don't want to
+                # error out if the cache file is invalid.
+                pass
+
+    @property
+    def key(self) -> str:
+        return sys.prefix
+
+    def get(self, current_time: datetime.datetime) -> Optional[str]:
+        """Check if we have a not-outdated version loaded already."""
+        if not self._state:
+            return None
+
+        if "last_check" not in self._state:
+            return None
+
+        if "pypi_version" not in self._state:
+            return None
+
+        seven_days_in_seconds = 7 * 24 * 60 * 60
+
+        # Determine if we need to refresh the state
+        last_check = datetime.datetime.strptime(self._state["last_check"], _DATE_FMT)
+        seconds_since_last_check = (current_time - last_check).total_seconds()
+        if seconds_since_last_check > seven_days_in_seconds:
+            return None
+
+        return self._state["pypi_version"]
+
+    def set(self, pypi_version: str, current_time: datetime.datetime) -> None:
+        # If we do not have a path to cache in, don't bother saving.
+        if not self._statefile_path:
+            return
+
+        # Check to make sure that we own the directory
+        if not check_path_owner(os.path.dirname(self._statefile_path)):
+            return
+
+        # Now that we've ensured the directory is owned by this user, we'll go
+        # ahead and make sure that all our directories are created.
+        ensure_dir(os.path.dirname(self._statefile_path))
+
+        state = {
+            # Include the key so it's easy to tell which pip wrote the
+            # file.
+            "key": self.key,
+            "last_check": current_time.strftime(_DATE_FMT),
+            "pypi_version": pypi_version,
+        }
+
+        text = json.dumps(state, sort_keys=True, separators=(",", ":"))
+
+        with adjacent_tmp_file(self._statefile_path) as f:
+            f.write(text.encode())
+
+        try:
+            # Since we have a prefix-specific state file, we can just
+            # overwrite whatever is there, no need to check.
+            replace(f.name, self._statefile_path)
+        except OSError:
+            # Best effort.
+            pass
+
+
+@dataclass
+class UpgradePrompt:
+    old: str
+    new: str
+
+    def __rich__(self) -> Group:
+        if WINDOWS:
+            pip_cmd = f"{get_best_invocation_for_this_python()} -m pip"
+        else:
+            pip_cmd = get_best_invocation_for_this_pip()
+
+        notice = "[bold][[reset][blue]notice[reset][bold]][reset]"
+        return Group(
+            Text(),
+            Text.from_markup(
+                f"{notice} A new release of pip is available: "
+                f"[red]{self.old}[reset] -> [green]{self.new}[reset]"
+            ),
+            Text.from_markup(
+                f"{notice} To update, run: "
+                f"[green]{escape(pip_cmd)} install --upgrade pip"
+            ),
+        )
+
+
+def was_installed_by_pip(pkg: str) -> bool:
+    """Checks whether pkg was installed by pip
+
+    This is used not to display the upgrade message when pip is in fact
+    installed by system package manager, such as dnf on Fedora.
+    """
+    dist = get_default_environment().get_distribution(pkg)
+    return dist is not None and "pip" == dist.installer
+
+
+def _get_current_remote_pip_version(
+    session: PipSession, options: optparse.Values
+) -> Optional[str]:
+    # Lets use PackageFinder to see what the latest pip version is
+    link_collector = LinkCollector.create(
+        session,
+        options=options,
+        suppress_no_index=True,
+    )
+
+    # Pass allow_yanked=False so we don't suggest upgrading to a
+    # yanked version.
+    selection_prefs = SelectionPreferences(
+        allow_yanked=False,
+        allow_all_prereleases=False,  # Explicitly set to False
+    )
+
+    finder = PackageFinder.create(
+        link_collector=link_collector,
+        selection_prefs=selection_prefs,
+    )
+    best_candidate = finder.find_best_candidate("pip").best_candidate
+    if best_candidate is None:
+        return None
+
+    return str(best_candidate.version)
+
+
+def _self_version_check_logic(
+    *,
+    state: SelfCheckState,
+    current_time: datetime.datetime,
+    local_version: DistributionVersion,
+    get_remote_version: Callable[[], Optional[str]],
+) -> Optional[UpgradePrompt]:
+    remote_version_str = state.get(current_time)
+    if remote_version_str is None:
+        remote_version_str = get_remote_version()
+        if remote_version_str is None:
+            logger.debug("No remote pip version found")
+            return None
+        state.set(remote_version_str, current_time)
+
+    remote_version = parse_version(remote_version_str)
+    logger.debug("Remote version of pip: %s", remote_version)
+    logger.debug("Local version of pip:  %s", local_version)
+
+    pip_installed_by_pip = was_installed_by_pip("pip")
+    logger.debug("Was pip installed by pip? %s", pip_installed_by_pip)
+    if not pip_installed_by_pip:
+        return None  # Only suggest upgrade if pip is installed by pip.
+
+    local_version_is_older = (
+        local_version < remote_version
+        and local_version.base_version != remote_version.base_version
+    )
+    if local_version_is_older:
+        return UpgradePrompt(old=str(local_version), new=remote_version_str)
+
+    return None
+
+
+def pip_self_version_check(session: PipSession, options: optparse.Values) -> None:
+    """Check for an update for pip.
+
+    Limit the frequency of checks to once per week. State is stored either in
+    the active virtualenv or in the user's USER_CACHE_DIR keyed off the prefix
+    of the pip script path.
+    """
+    installed_dist = get_default_environment().get_distribution("pip")
+    if not installed_dist:
+        return
+
+    try:
+        upgrade_prompt = _self_version_check_logic(
+            state=SelfCheckState(cache_dir=options.cache_dir),
+            current_time=datetime.datetime.utcnow(),
+            local_version=installed_dist.version,
+            get_remote_version=functools.partial(
+                _get_current_remote_pip_version, session, options
+            ),
+        )
+        if upgrade_prompt is not None:
+            logger.warning("[present-rich] %s", upgrade_prompt)
+    except Exception:
+        logger.warning("There was an error checking the latest version of pip.")
+        logger.debug("See below for error", exc_info=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/_log.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/_log.py
new file mode 100644
index 0000000000000000000000000000000000000000..92c4c6a193873ce09629f6cfaa2dabc4f14ecb03
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/_log.py
@@ -0,0 +1,38 @@
+"""Customize logging
+
+Defines custom logger class for the `logger.verbose(...)` method.
+
+init_logging() must be called before any other modules that call logging.getLogger.
+"""
+
+import logging
+from typing import Any, cast
+
+# custom log level for `--verbose` output
+# between DEBUG and INFO
+VERBOSE = 15
+
+
+class VerboseLogger(logging.Logger):
+    """Custom Logger, defining a verbose log-level
+
+    VERBOSE is between INFO and DEBUG.
+    """
+
+    def verbose(self, msg: str, *args: Any, **kwargs: Any) -> None:
+        return self.log(VERBOSE, msg, *args, **kwargs)
+
+
+def getLogger(name: str) -> VerboseLogger:
+    """logging.getLogger, but ensures our VerboseLogger class is returned"""
+    return cast(VerboseLogger, logging.getLogger(name))
+
+
+def init_logging() -> None:
+    """Register our VerboseLogger and VERBOSE log level.
+
+    Should be called before any calls to getLogger(),
+    i.e. in pip._internal.__init__
+    """
+    logging.setLoggerClass(VerboseLogger)
+    logging.addLevelName(VERBOSE, "VERBOSE")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/appdirs.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/appdirs.py
new file mode 100644
index 0000000000000000000000000000000000000000..16933bf8afedcbe3e9d4fcc04e5f7246228c56fc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/appdirs.py
@@ -0,0 +1,52 @@
+"""
+This code wraps the vendored appdirs module to so the return values are
+compatible for the current pip code base.
+
+The intention is to rewrite current usages gradually, keeping the tests pass,
+and eventually drop this after all usages are changed.
+"""
+
+import os
+import sys
+from typing import List
+
+from pip._vendor import platformdirs as _appdirs
+
+
+def user_cache_dir(appname: str) -> str:
+    return _appdirs.user_cache_dir(appname, appauthor=False)
+
+
+def _macos_user_config_dir(appname: str, roaming: bool = True) -> str:
+    # Use ~/Application Support/pip, if the directory exists.
+    path = _appdirs.user_data_dir(appname, appauthor=False, roaming=roaming)
+    if os.path.isdir(path):
+        return path
+
+    # Use a Linux-like ~/.config/pip, by default.
+    linux_like_path = "~/.config/"
+    if appname:
+        linux_like_path = os.path.join(linux_like_path, appname)
+
+    return os.path.expanduser(linux_like_path)
+
+
+def user_config_dir(appname: str, roaming: bool = True) -> str:
+    if sys.platform == "darwin":
+        return _macos_user_config_dir(appname, roaming)
+
+    return _appdirs.user_config_dir(appname, appauthor=False, roaming=roaming)
+
+
+# for the discussion regarding site_config_dir locations
+# see 
+def site_config_dirs(appname: str) -> List[str]:
+    if sys.platform == "darwin":
+        return [_appdirs.site_data_dir(appname, appauthor=False, multipath=True)]
+
+    dirval = _appdirs.site_config_dir(appname, appauthor=False, multipath=True)
+    if sys.platform == "win32":
+        return [dirval]
+
+    # Unix-y system. Look in /etc as well.
+    return dirval.split(os.pathsep) + ["/etc"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..3f4d300cef077e698989245562375a9444d983fa
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/compat.py
@@ -0,0 +1,63 @@
+"""Stuff that differs in different Python versions and platform
+distributions."""
+
+import logging
+import os
+import sys
+
+__all__ = ["get_path_uid", "stdlib_pkgs", "WINDOWS"]
+
+
+logger = logging.getLogger(__name__)
+
+
+def has_tls() -> bool:
+    try:
+        import _ssl  # noqa: F401  # ignore unused
+
+        return True
+    except ImportError:
+        pass
+
+    from pip._vendor.urllib3.util import IS_PYOPENSSL
+
+    return IS_PYOPENSSL
+
+
+def get_path_uid(path: str) -> int:
+    """
+    Return path's uid.
+
+    Does not follow symlinks:
+        https://github.com/pypa/pip/pull/935#discussion_r5307003
+
+    Placed this function in compat due to differences on AIX and
+    Jython, that should eventually go away.
+
+    :raises OSError: When path is a symlink or can't be read.
+    """
+    if hasattr(os, "O_NOFOLLOW"):
+        fd = os.open(path, os.O_RDONLY | os.O_NOFOLLOW)
+        file_uid = os.fstat(fd).st_uid
+        os.close(fd)
+    else:  # AIX and Jython
+        # WARNING: time of check vulnerability, but best we can do w/o NOFOLLOW
+        if not os.path.islink(path):
+            # older versions of Jython don't have `os.fstat`
+            file_uid = os.stat(path).st_uid
+        else:
+            # raise OSError for parity with os.O_NOFOLLOW above
+            raise OSError(f"{path} is a symlink; Will not return uid for symlinks")
+    return file_uid
+
+
+# packages in the stdlib that may have installation metadata, but should not be
+# considered 'installed'.  this theoretically could be determined based on
+# dist.location (py27:`sysconfig.get_paths()['stdlib']`,
+# py26:sysconfig.get_config_vars('LIBDEST')), but fear platform variation may
+# make this ineffective, so hard-coding
+stdlib_pkgs = {"python", "wsgiref", "argparse"}
+
+
+# windows detection, covers cpython and ironpython
+WINDOWS = sys.platform.startswith("win") or (sys.platform == "cli" and os.name == "nt")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/compatibility_tags.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/compatibility_tags.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6ed9a78e552806cb23d8ac48ada6d41db5b4de5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/compatibility_tags.py
@@ -0,0 +1,165 @@
+"""Generate and work with PEP 425 Compatibility Tags.
+"""
+
+import re
+from typing import List, Optional, Tuple
+
+from pip._vendor.packaging.tags import (
+    PythonVersion,
+    Tag,
+    compatible_tags,
+    cpython_tags,
+    generic_tags,
+    interpreter_name,
+    interpreter_version,
+    mac_platforms,
+)
+
+_osx_arch_pat = re.compile(r"(.+)_(\d+)_(\d+)_(.+)")
+
+
+def version_info_to_nodot(version_info: Tuple[int, ...]) -> str:
+    # Only use up to the first two numbers.
+    return "".join(map(str, version_info[:2]))
+
+
+def _mac_platforms(arch: str) -> List[str]:
+    match = _osx_arch_pat.match(arch)
+    if match:
+        name, major, minor, actual_arch = match.groups()
+        mac_version = (int(major), int(minor))
+        arches = [
+            # Since we have always only checked that the platform starts
+            # with "macosx", for backwards-compatibility we extract the
+            # actual prefix provided by the user in case they provided
+            # something like "macosxcustom_". It may be good to remove
+            # this as undocumented or deprecate it in the future.
+            "{}_{}".format(name, arch[len("macosx_") :])
+            for arch in mac_platforms(mac_version, actual_arch)
+        ]
+    else:
+        # arch pattern didn't match (?!)
+        arches = [arch]
+    return arches
+
+
+def _custom_manylinux_platforms(arch: str) -> List[str]:
+    arches = [arch]
+    arch_prefix, arch_sep, arch_suffix = arch.partition("_")
+    if arch_prefix == "manylinux2014":
+        # manylinux1/manylinux2010 wheels run on most manylinux2014 systems
+        # with the exception of wheels depending on ncurses. PEP 599 states
+        # manylinux1/manylinux2010 wheels should be considered
+        # manylinux2014 wheels:
+        # https://www.python.org/dev/peps/pep-0599/#backwards-compatibility-with-manylinux2010-wheels
+        if arch_suffix in {"i686", "x86_64"}:
+            arches.append("manylinux2010" + arch_sep + arch_suffix)
+            arches.append("manylinux1" + arch_sep + arch_suffix)
+    elif arch_prefix == "manylinux2010":
+        # manylinux1 wheels run on most manylinux2010 systems with the
+        # exception of wheels depending on ncurses. PEP 571 states
+        # manylinux1 wheels should be considered manylinux2010 wheels:
+        # https://www.python.org/dev/peps/pep-0571/#backwards-compatibility-with-manylinux1-wheels
+        arches.append("manylinux1" + arch_sep + arch_suffix)
+    return arches
+
+
+def _get_custom_platforms(arch: str) -> List[str]:
+    arch_prefix, arch_sep, arch_suffix = arch.partition("_")
+    if arch.startswith("macosx"):
+        arches = _mac_platforms(arch)
+    elif arch_prefix in ["manylinux2014", "manylinux2010"]:
+        arches = _custom_manylinux_platforms(arch)
+    else:
+        arches = [arch]
+    return arches
+
+
+def _expand_allowed_platforms(platforms: Optional[List[str]]) -> Optional[List[str]]:
+    if not platforms:
+        return None
+
+    seen = set()
+    result = []
+
+    for p in platforms:
+        if p in seen:
+            continue
+        additions = [c for c in _get_custom_platforms(p) if c not in seen]
+        seen.update(additions)
+        result.extend(additions)
+
+    return result
+
+
+def _get_python_version(version: str) -> PythonVersion:
+    if len(version) > 1:
+        return int(version[0]), int(version[1:])
+    else:
+        return (int(version[0]),)
+
+
+def _get_custom_interpreter(
+    implementation: Optional[str] = None, version: Optional[str] = None
+) -> str:
+    if implementation is None:
+        implementation = interpreter_name()
+    if version is None:
+        version = interpreter_version()
+    return f"{implementation}{version}"
+
+
+def get_supported(
+    version: Optional[str] = None,
+    platforms: Optional[List[str]] = None,
+    impl: Optional[str] = None,
+    abis: Optional[List[str]] = None,
+) -> List[Tag]:
+    """Return a list of supported tags for each version specified in
+    `versions`.
+
+    :param version: a string version, of the form "33" or "32",
+        or None. The version will be assumed to support our ABI.
+    :param platform: specify a list of platforms you want valid
+        tags for, or None. If None, use the local system platform.
+    :param impl: specify the exact implementation you want valid
+        tags for, or None. If None, use the local interpreter impl.
+    :param abis: specify a list of abis you want valid
+        tags for, or None. If None, use the local interpreter abi.
+    """
+    supported: List[Tag] = []
+
+    python_version: Optional[PythonVersion] = None
+    if version is not None:
+        python_version = _get_python_version(version)
+
+    interpreter = _get_custom_interpreter(impl, version)
+
+    platforms = _expand_allowed_platforms(platforms)
+
+    is_cpython = (impl or interpreter_name()) == "cp"
+    if is_cpython:
+        supported.extend(
+            cpython_tags(
+                python_version=python_version,
+                abis=abis,
+                platforms=platforms,
+            )
+        )
+    else:
+        supported.extend(
+            generic_tags(
+                interpreter=interpreter,
+                abis=abis,
+                platforms=platforms,
+            )
+        )
+    supported.extend(
+        compatible_tags(
+            python_version=python_version,
+            interpreter=interpreter,
+            platforms=platforms,
+        )
+    )
+
+    return supported
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/datetime.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/datetime.py
new file mode 100644
index 0000000000000000000000000000000000000000..8668b3b0ec1deec2aeb7ff6bd94265d6705e05bf
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/datetime.py
@@ -0,0 +1,11 @@
+"""For when pip wants to check the date or time.
+"""
+
+import datetime
+
+
+def today_is_later_than(year: int, month: int, day: int) -> bool:
+    today = datetime.date.today()
+    given = datetime.date(year, month, day)
+
+    return today > given
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/deprecation.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/deprecation.py
new file mode 100644
index 0000000000000000000000000000000000000000..18e9be9f36ec47fcacd153de4e3ed0cf945ddeba
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/deprecation.py
@@ -0,0 +1,188 @@
+"""
+A module that implements tooling to enable easy warnings about deprecations.
+"""
+
+import logging
+import warnings
+from typing import Any, Optional, TextIO, Type, Union
+
+from pip._vendor.packaging.version import parse
+
+from pip import __version__ as current_version  # NOTE: tests patch this name.
+
+DEPRECATION_MSG_PREFIX = "DEPRECATION: "
+
+
+class PipDeprecationWarning(Warning):
+    pass
+
+
+_original_showwarning: Any = None
+
+
+# Warnings <-> Logging Integration
+def _showwarning(
+    message: Union[Warning, str],
+    category: Type[Warning],
+    filename: str,
+    lineno: int,
+    file: Optional[TextIO] = None,
+    line: Optional[str] = None,
+) -> None:
+    if file is not None:
+        if _original_showwarning is not None:
+            _original_showwarning(message, category, filename, lineno, file, line)
+    elif issubclass(category, PipDeprecationWarning):
+        # We use a specially named logger which will handle all of the
+        # deprecation messages for pip.
+        logger = logging.getLogger("pip._internal.deprecations")
+        logger.warning(message)
+    else:
+        _original_showwarning(message, category, filename, lineno, file, line)
+
+
+def install_warning_logger() -> None:
+    # Enable our Deprecation Warnings
+    warnings.simplefilter("default", PipDeprecationWarning, append=True)
+
+    global _original_showwarning
+
+    if _original_showwarning is None:
+        _original_showwarning = warnings.showwarning
+        warnings.showwarning = _showwarning
+
+
+def deprecated(
+    *,
+    reason: str,
+    replacement: Optional[str],
+    gone_in: Optional[str],
+    feature_flag: Optional[str] = None,
+    issue: Optional[int] = None,
+) -> None:
+    """Helper to deprecate existing functionality.
+
+    reason:
+        Textual reason shown to the user about why this functionality has
+        been deprecated. Should be a complete sentence.
+    replacement:
+        Textual suggestion shown to the user about what alternative
+        functionality they can use.
+    gone_in:
+        The version of pip does this functionality should get removed in.
+        Raises an error if pip's current version is greater than or equal to
+        this.
+    feature_flag:
+        Command-line flag of the form --use-feature={feature_flag} for testing
+        upcoming functionality.
+    issue:
+        Issue number on the tracker that would serve as a useful place for
+        users to find related discussion and provide feedback.
+    """
+
+    # Determine whether or not the feature is already gone in this version.
+    is_gone = gone_in is not None and parse(current_version) >= parse(gone_in)
+
+    message_parts = [
+        (reason, f"{DEPRECATION_MSG_PREFIX}{{}}"),
+        (
+            gone_in,
+            "pip {} will enforce this behaviour change."
+            if not is_gone
+            else "Since pip {}, this is no longer supported.",
+        ),
+        (
+            replacement,
+            "A possible replacement is {}.",
+        ),
+        (
+            feature_flag,
+            "You can use the flag --use-feature={} to test the upcoming behaviour."
+            if not is_gone
+            else None,
+        ),
+        (
+            issue,
+            "Discussion can be found at https://github.com/pypa/pip/issues/{}",
+        ),
+    ]
+
+    message = " ".join(
+        format_str.format(value)
+        for value, format_str in message_parts
+        if format_str is not None and value is not None
+    )
+
+    # Raise as an error if this behaviour is deprecated.
+    if is_gone:
+        raise PipDeprecationWarning(message)
+
+    warnings.warn(message, category=PipDeprecationWarning, stacklevel=2)
+
+
+class LegacyInstallReason:
+    def __init__(
+        self,
+        reason: str,
+        replacement: Optional[str] = None,
+        gone_in: Optional[str] = None,
+        feature_flag: Optional[str] = None,
+        issue: Optional[int] = None,
+        emit_after_success: bool = False,
+        emit_before_install: bool = False,
+    ):
+        self._reason = reason
+        self._replacement = replacement
+        self._gone_in = gone_in
+        self._feature_flag = feature_flag
+        self._issue = issue
+        self.emit_after_success = emit_after_success
+        self.emit_before_install = emit_before_install
+
+    def emit_deprecation(self, name: str) -> None:
+        deprecated(
+            reason=self._reason.format(name=name),
+            replacement=self._replacement,
+            gone_in=self._gone_in,
+            feature_flag=self._feature_flag,
+            issue=self._issue,
+        )
+
+
+LegacyInstallReasonFailedBdistWheel = LegacyInstallReason(
+    reason=(
+        "{name} was installed using the legacy 'setup.py install' "
+        "method, because a wheel could not be built for it."
+    ),
+    replacement="to fix the wheel build issue reported above",
+    gone_in="23.1",
+    issue=8368,
+    emit_after_success=True,
+)
+
+
+LegacyInstallReasonMissingWheelPackage = LegacyInstallReason(
+    reason=(
+        "{name} is being installed using the legacy "
+        "'setup.py install' method, because it does not have a "
+        "'pyproject.toml' and the 'wheel' package "
+        "is not installed."
+    ),
+    replacement="to enable the '--use-pep517' option",
+    gone_in="23.1",
+    issue=8559,
+    emit_before_install=True,
+)
+
+LegacyInstallReasonNoBinaryForcesSetuptoolsInstall = LegacyInstallReason(
+    reason=(
+        "{name} is being installed using the legacy "
+        "'setup.py install' method, because the '--no-binary' option was enabled "
+        "for it and this currently disables local wheel building for projects that "
+        "don't have a 'pyproject.toml' file."
+    ),
+    replacement="to enable the '--use-pep517' option",
+    gone_in="23.1",
+    issue=11451,
+    emit_before_install=True,
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/direct_url_helpers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/direct_url_helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..0e8e5e1608b911e789a3d346ebe48aa7cc54b79e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/direct_url_helpers.py
@@ -0,0 +1,87 @@
+from typing import Optional
+
+from pip._internal.models.direct_url import ArchiveInfo, DirectUrl, DirInfo, VcsInfo
+from pip._internal.models.link import Link
+from pip._internal.utils.urls import path_to_url
+from pip._internal.vcs import vcs
+
+
+def direct_url_as_pep440_direct_reference(direct_url: DirectUrl, name: str) -> str:
+    """Convert a DirectUrl to a pip requirement string."""
+    direct_url.validate()  # if invalid, this is a pip bug
+    requirement = name + " @ "
+    fragments = []
+    if isinstance(direct_url.info, VcsInfo):
+        requirement += "{}+{}@{}".format(
+            direct_url.info.vcs, direct_url.url, direct_url.info.commit_id
+        )
+    elif isinstance(direct_url.info, ArchiveInfo):
+        requirement += direct_url.url
+        if direct_url.info.hash:
+            fragments.append(direct_url.info.hash)
+    else:
+        assert isinstance(direct_url.info, DirInfo)
+        requirement += direct_url.url
+    if direct_url.subdirectory:
+        fragments.append("subdirectory=" + direct_url.subdirectory)
+    if fragments:
+        requirement += "#" + "&".join(fragments)
+    return requirement
+
+
+def direct_url_for_editable(source_dir: str) -> DirectUrl:
+    return DirectUrl(
+        url=path_to_url(source_dir),
+        info=DirInfo(editable=True),
+    )
+
+
+def direct_url_from_link(
+    link: Link, source_dir: Optional[str] = None, link_is_in_wheel_cache: bool = False
+) -> DirectUrl:
+    if link.is_vcs:
+        vcs_backend = vcs.get_backend_for_scheme(link.scheme)
+        assert vcs_backend
+        url, requested_revision, _ = vcs_backend.get_url_rev_and_auth(
+            link.url_without_fragment
+        )
+        # For VCS links, we need to find out and add commit_id.
+        if link_is_in_wheel_cache:
+            # If the requested VCS link corresponds to a cached
+            # wheel, it means the requested revision was an
+            # immutable commit hash, otherwise it would not have
+            # been cached. In that case we don't have a source_dir
+            # with the VCS checkout.
+            assert requested_revision
+            commit_id = requested_revision
+        else:
+            # If the wheel was not in cache, it means we have
+            # had to checkout from VCS to build and we have a source_dir
+            # which we can inspect to find out the commit id.
+            assert source_dir
+            commit_id = vcs_backend.get_revision(source_dir)
+        return DirectUrl(
+            url=url,
+            info=VcsInfo(
+                vcs=vcs_backend.name,
+                commit_id=commit_id,
+                requested_revision=requested_revision,
+            ),
+            subdirectory=link.subdirectory_fragment,
+        )
+    elif link.is_existing_dir():
+        return DirectUrl(
+            url=link.url_without_fragment,
+            info=DirInfo(),
+            subdirectory=link.subdirectory_fragment,
+        )
+    else:
+        hash = None
+        hash_name = link.hash_name
+        if hash_name:
+            hash = f"{hash_name}={link.hash}"
+        return DirectUrl(
+            url=link.url_without_fragment,
+            info=ArchiveInfo(hash=hash),
+            subdirectory=link.subdirectory_fragment,
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/distutils_args.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/distutils_args.py
new file mode 100644
index 0000000000000000000000000000000000000000..2fd1862073f55d5551fc2c1bc1e9eaaed0c0e877
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/distutils_args.py
@@ -0,0 +1,43 @@
+from getopt import GetoptError, getopt
+from typing import Dict, List
+
+_options = [
+    "exec-prefix=",
+    "home=",
+    "install-base=",
+    "install-data=",
+    "install-headers=",
+    "install-lib=",
+    "install-platlib=",
+    "install-purelib=",
+    "install-scripts=",
+    "prefix=",
+    "root=",
+    "user",
+]
+
+
+def parse_distutils_args(args: List[str]) -> Dict[str, str]:
+    """Parse provided arguments, returning an object that has the matched arguments.
+
+    Any unknown arguments are ignored.
+    """
+    result = {}
+    for arg in args:
+        try:
+            parsed_opt, _ = getopt(args=[arg], shortopts="", longopts=_options)
+        except GetoptError:
+            # We don't care about any other options, which here may be
+            # considered unrecognized since our option list is not
+            # exhaustive.
+            continue
+
+        if not parsed_opt:
+            continue
+
+        option = parsed_opt[0]
+        name_from_parsed = option[0][2:].replace("-", "_")
+        value_from_parsed = option[1] or "true"
+        result[name_from_parsed] = value_from_parsed
+
+    return result
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/egg_link.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/egg_link.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb57ed1519f82adb79a3d2377e1f286df9d8ef6b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/egg_link.py
@@ -0,0 +1,72 @@
+import os
+import re
+import sys
+from typing import List, Optional
+
+from pip._internal.locations import site_packages, user_site
+from pip._internal.utils.virtualenv import (
+    running_under_virtualenv,
+    virtualenv_no_global,
+)
+
+__all__ = [
+    "egg_link_path_from_sys_path",
+    "egg_link_path_from_location",
+]
+
+
+def _egg_link_name(raw_name: str) -> str:
+    """
+    Convert a Name metadata value to a .egg-link name, by applying
+    the same substitution as pkg_resources's safe_name function.
+    Note: we cannot use canonicalize_name because it has a different logic.
+    """
+    return re.sub("[^A-Za-z0-9.]+", "-", raw_name) + ".egg-link"
+
+
+def egg_link_path_from_sys_path(raw_name: str) -> Optional[str]:
+    """
+    Look for a .egg-link file for project name, by walking sys.path.
+    """
+    egg_link_name = _egg_link_name(raw_name)
+    for path_item in sys.path:
+        egg_link = os.path.join(path_item, egg_link_name)
+        if os.path.isfile(egg_link):
+            return egg_link
+    return None
+
+
+def egg_link_path_from_location(raw_name: str) -> Optional[str]:
+    """
+    Return the path for the .egg-link file if it exists, otherwise, None.
+
+    There's 3 scenarios:
+    1) not in a virtualenv
+       try to find in site.USER_SITE, then site_packages
+    2) in a no-global virtualenv
+       try to find in site_packages
+    3) in a yes-global virtualenv
+       try to find in site_packages, then site.USER_SITE
+       (don't look in global location)
+
+    For #1 and #3, there could be odd cases, where there's an egg-link in 2
+    locations.
+
+    This method will just return the first one found.
+    """
+    sites: List[str] = []
+    if running_under_virtualenv():
+        sites.append(site_packages)
+        if not virtualenv_no_global() and user_site:
+            sites.append(user_site)
+    else:
+        if user_site:
+            sites.append(user_site)
+        sites.append(site_packages)
+
+    egg_link_name = _egg_link_name(raw_name)
+    for site in sites:
+        egglink = os.path.join(site, egg_link_name)
+        if os.path.isfile(egglink):
+            return egglink
+    return None
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/encoding.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/encoding.py
new file mode 100644
index 0000000000000000000000000000000000000000..008f06a79bf598b149bdccb73e572d13331a1631
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/encoding.py
@@ -0,0 +1,36 @@
+import codecs
+import locale
+import re
+import sys
+from typing import List, Tuple
+
+BOMS: List[Tuple[bytes, str]] = [
+    (codecs.BOM_UTF8, "utf-8"),
+    (codecs.BOM_UTF16, "utf-16"),
+    (codecs.BOM_UTF16_BE, "utf-16-be"),
+    (codecs.BOM_UTF16_LE, "utf-16-le"),
+    (codecs.BOM_UTF32, "utf-32"),
+    (codecs.BOM_UTF32_BE, "utf-32-be"),
+    (codecs.BOM_UTF32_LE, "utf-32-le"),
+]
+
+ENCODING_RE = re.compile(rb"coding[:=]\s*([-\w.]+)")
+
+
+def auto_decode(data: bytes) -> str:
+    """Check a bytes string for a BOM to correctly detect the encoding
+
+    Fallback to locale.getpreferredencoding(False) like open() on Python3"""
+    for bom, encoding in BOMS:
+        if data.startswith(bom):
+            return data[len(bom) :].decode(encoding)
+    # Lets check the first two lines as in PEP263
+    for line in data.split(b"\n")[:2]:
+        if line[0:1] == b"#" and ENCODING_RE.search(line):
+            result = ENCODING_RE.search(line)
+            assert result is not None
+            encoding = result.groups()[0].decode("ascii")
+            return data.decode(encoding)
+    return data.decode(
+        locale.getpreferredencoding(False) or sys.getdefaultencoding(),
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/entrypoints.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/entrypoints.py
new file mode 100644
index 0000000000000000000000000000000000000000..150136938548af6aa5ae1f716b330d0eb2d3e013
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/entrypoints.py
@@ -0,0 +1,84 @@
+import itertools
+import os
+import shutil
+import sys
+from typing import List, Optional
+
+from pip._internal.cli.main import main
+from pip._internal.utils.compat import WINDOWS
+
+_EXECUTABLE_NAMES = [
+    "pip",
+    f"pip{sys.version_info.major}",
+    f"pip{sys.version_info.major}.{sys.version_info.minor}",
+]
+if WINDOWS:
+    _allowed_extensions = {"", ".exe"}
+    _EXECUTABLE_NAMES = [
+        "".join(parts)
+        for parts in itertools.product(_EXECUTABLE_NAMES, _allowed_extensions)
+    ]
+
+
+def _wrapper(args: Optional[List[str]] = None) -> int:
+    """Central wrapper for all old entrypoints.
+
+    Historically pip has had several entrypoints defined. Because of issues
+    arising from PATH, sys.path, multiple Pythons, their interactions, and most
+    of them having a pip installed, users suffer every time an entrypoint gets
+    moved.
+
+    To alleviate this pain, and provide a mechanism for warning users and
+    directing them to an appropriate place for help, we now define all of
+    our old entrypoints as wrappers for the current one.
+    """
+    sys.stderr.write(
+        "WARNING: pip is being invoked by an old script wrapper. This will "
+        "fail in a future version of pip.\n"
+        "Please see https://github.com/pypa/pip/issues/5599 for advice on "
+        "fixing the underlying issue.\n"
+        "To avoid this problem you can invoke Python with '-m pip' instead of "
+        "running pip directly.\n"
+    )
+    return main(args)
+
+
+def get_best_invocation_for_this_pip() -> str:
+    """Try to figure out the best way to invoke pip in the current environment."""
+    binary_directory = "Scripts" if WINDOWS else "bin"
+    binary_prefix = os.path.join(sys.prefix, binary_directory)
+
+    # Try to use pip[X[.Y]] names, if those executables for this environment are
+    # the first on PATH with that name.
+    path_parts = os.path.normcase(os.environ.get("PATH", "")).split(os.pathsep)
+    exe_are_in_PATH = os.path.normcase(binary_prefix) in path_parts
+    if exe_are_in_PATH:
+        for exe_name in _EXECUTABLE_NAMES:
+            found_executable = shutil.which(exe_name)
+            binary_executable = os.path.join(binary_prefix, exe_name)
+            if (
+                found_executable
+                and os.path.exists(binary_executable)
+                and os.path.samefile(
+                    found_executable,
+                    binary_executable,
+                )
+            ):
+                return exe_name
+
+    # Use the `-m` invocation, if there's no "nice" invocation.
+    return f"{get_best_invocation_for_this_python()} -m pip"
+
+
+def get_best_invocation_for_this_python() -> str:
+    """Try to figure out the best way to invoke the current Python."""
+    exe = sys.executable
+    exe_name = os.path.basename(exe)
+
+    # Try to use the basename, if it's the first executable.
+    found_executable = shutil.which(exe_name)
+    if found_executable and os.path.samefile(found_executable, exe):
+        return exe_name
+
+    # Use the full executable name, because we couldn't find something simpler.
+    return exe
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/filesystem.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/filesystem.py
new file mode 100644
index 0000000000000000000000000000000000000000..83c2df75b963e5866b63aaf0f4446a8ca61aebce
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/filesystem.py
@@ -0,0 +1,153 @@
+import fnmatch
+import os
+import os.path
+import random
+import sys
+from contextlib import contextmanager
+from tempfile import NamedTemporaryFile
+from typing import Any, BinaryIO, Generator, List, Union, cast
+
+from pip._vendor.tenacity import retry, stop_after_delay, wait_fixed
+
+from pip._internal.utils.compat import get_path_uid
+from pip._internal.utils.misc import format_size
+
+
+def check_path_owner(path: str) -> bool:
+    # If we don't have a way to check the effective uid of this process, then
+    # we'll just assume that we own the directory.
+    if sys.platform == "win32" or not hasattr(os, "geteuid"):
+        return True
+
+    assert os.path.isabs(path)
+
+    previous = None
+    while path != previous:
+        if os.path.lexists(path):
+            # Check if path is writable by current user.
+            if os.geteuid() == 0:
+                # Special handling for root user in order to handle properly
+                # cases where users use sudo without -H flag.
+                try:
+                    path_uid = get_path_uid(path)
+                except OSError:
+                    return False
+                return path_uid == 0
+            else:
+                return os.access(path, os.W_OK)
+        else:
+            previous, path = path, os.path.dirname(path)
+    return False  # assume we don't own the path
+
+
+@contextmanager
+def adjacent_tmp_file(path: str, **kwargs: Any) -> Generator[BinaryIO, None, None]:
+    """Return a file-like object pointing to a tmp file next to path.
+
+    The file is created securely and is ensured to be written to disk
+    after the context reaches its end.
+
+    kwargs will be passed to tempfile.NamedTemporaryFile to control
+    the way the temporary file will be opened.
+    """
+    with NamedTemporaryFile(
+        delete=False,
+        dir=os.path.dirname(path),
+        prefix=os.path.basename(path),
+        suffix=".tmp",
+        **kwargs,
+    ) as f:
+        result = cast(BinaryIO, f)
+        try:
+            yield result
+        finally:
+            result.flush()
+            os.fsync(result.fileno())
+
+
+# Tenacity raises RetryError by default, explicitly raise the original exception
+_replace_retry = retry(reraise=True, stop=stop_after_delay(1), wait=wait_fixed(0.25))
+
+replace = _replace_retry(os.replace)
+
+
+# test_writable_dir and _test_writable_dir_win are copied from Flit,
+# with the author's agreement to also place them under pip's license.
+def test_writable_dir(path: str) -> bool:
+    """Check if a directory is writable.
+
+    Uses os.access() on POSIX, tries creating files on Windows.
+    """
+    # If the directory doesn't exist, find the closest parent that does.
+    while not os.path.isdir(path):
+        parent = os.path.dirname(path)
+        if parent == path:
+            break  # Should never get here, but infinite loops are bad
+        path = parent
+
+    if os.name == "posix":
+        return os.access(path, os.W_OK)
+
+    return _test_writable_dir_win(path)
+
+
+def _test_writable_dir_win(path: str) -> bool:
+    # os.access doesn't work on Windows: http://bugs.python.org/issue2528
+    # and we can't use tempfile: http://bugs.python.org/issue22107
+    basename = "accesstest_deleteme_fishfingers_custard_"
+    alphabet = "abcdefghijklmnopqrstuvwxyz0123456789"
+    for _ in range(10):
+        name = basename + "".join(random.choice(alphabet) for _ in range(6))
+        file = os.path.join(path, name)
+        try:
+            fd = os.open(file, os.O_RDWR | os.O_CREAT | os.O_EXCL)
+        except FileExistsError:
+            pass
+        except PermissionError:
+            # This could be because there's a directory with the same name.
+            # But it's highly unlikely there's a directory called that,
+            # so we'll assume it's because the parent dir is not writable.
+            # This could as well be because the parent dir is not readable,
+            # due to non-privileged user access.
+            return False
+        else:
+            os.close(fd)
+            os.unlink(file)
+            return True
+
+    # This should never be reached
+    raise OSError("Unexpected condition testing for writable directory")
+
+
+def find_files(path: str, pattern: str) -> List[str]:
+    """Returns a list of absolute paths of files beneath path, recursively,
+    with filenames which match the UNIX-style shell glob pattern."""
+    result: List[str] = []
+    for root, _, files in os.walk(path):
+        matches = fnmatch.filter(files, pattern)
+        result.extend(os.path.join(root, f) for f in matches)
+    return result
+
+
+def file_size(path: str) -> Union[int, float]:
+    # If it's a symlink, return 0.
+    if os.path.islink(path):
+        return 0
+    return os.path.getsize(path)
+
+
+def format_file_size(path: str) -> str:
+    return format_size(file_size(path))
+
+
+def directory_size(path: str) -> Union[int, float]:
+    size = 0.0
+    for root, _dirs, files in os.walk(path):
+        for filename in files:
+            file_path = os.path.join(root, filename)
+            size += file_size(file_path)
+    return size
+
+
+def format_directory_size(path: str) -> str:
+    return format_size(directory_size(path))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/filetypes.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/filetypes.py
new file mode 100644
index 0000000000000000000000000000000000000000..5948570178f3e6e79d1ff574241d09d4d8ed78de
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/filetypes.py
@@ -0,0 +1,27 @@
+"""Filetype information.
+"""
+
+from typing import Tuple
+
+from pip._internal.utils.misc import splitext
+
+WHEEL_EXTENSION = ".whl"
+BZ2_EXTENSIONS: Tuple[str, ...] = (".tar.bz2", ".tbz")
+XZ_EXTENSIONS: Tuple[str, ...] = (
+    ".tar.xz",
+    ".txz",
+    ".tlz",
+    ".tar.lz",
+    ".tar.lzma",
+)
+ZIP_EXTENSIONS: Tuple[str, ...] = (".zip", WHEEL_EXTENSION)
+TAR_EXTENSIONS: Tuple[str, ...] = (".tar.gz", ".tgz", ".tar")
+ARCHIVE_EXTENSIONS = ZIP_EXTENSIONS + BZ2_EXTENSIONS + TAR_EXTENSIONS + XZ_EXTENSIONS
+
+
+def is_archive_file(name: str) -> bool:
+    """Return True if `name` is a considered as an archive file."""
+    ext = splitext(name)[1].lower()
+    if ext in ARCHIVE_EXTENSIONS:
+        return True
+    return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/glibc.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/glibc.py
new file mode 100644
index 0000000000000000000000000000000000000000..7bd3c20681d865cb4fa42617cf939b5512c7663f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/glibc.py
@@ -0,0 +1,88 @@
+# The following comment should be removed at some point in the future.
+# mypy: strict-optional=False
+
+import os
+import sys
+from typing import Optional, Tuple
+
+
+def glibc_version_string() -> Optional[str]:
+    "Returns glibc version string, or None if not using glibc."
+    return glibc_version_string_confstr() or glibc_version_string_ctypes()
+
+
+def glibc_version_string_confstr() -> Optional[str]:
+    "Primary implementation of glibc_version_string using os.confstr."
+    # os.confstr is quite a bit faster than ctypes.DLL. It's also less likely
+    # to be broken or missing. This strategy is used in the standard library
+    # platform module:
+    # https://github.com/python/cpython/blob/fcf1d003bf4f0100c9d0921ff3d70e1127ca1b71/Lib/platform.py#L175-L183
+    if sys.platform == "win32":
+        return None
+    try:
+        # os.confstr("CS_GNU_LIBC_VERSION") returns a string like "glibc 2.17":
+        _, version = os.confstr("CS_GNU_LIBC_VERSION").split()
+    except (AttributeError, OSError, ValueError):
+        # os.confstr() or CS_GNU_LIBC_VERSION not available (or a bad value)...
+        return None
+    return version
+
+
+def glibc_version_string_ctypes() -> Optional[str]:
+    "Fallback implementation of glibc_version_string using ctypes."
+
+    try:
+        import ctypes
+    except ImportError:
+        return None
+
+    # ctypes.CDLL(None) internally calls dlopen(NULL), and as the dlopen
+    # manpage says, "If filename is NULL, then the returned handle is for the
+    # main program". This way we can let the linker do the work to figure out
+    # which libc our process is actually using.
+    process_namespace = ctypes.CDLL(None)
+    try:
+        gnu_get_libc_version = process_namespace.gnu_get_libc_version
+    except AttributeError:
+        # Symbol doesn't exist -> therefore, we are not linked to
+        # glibc.
+        return None
+
+    # Call gnu_get_libc_version, which returns a string like "2.5"
+    gnu_get_libc_version.restype = ctypes.c_char_p
+    version_str = gnu_get_libc_version()
+    # py2 / py3 compatibility:
+    if not isinstance(version_str, str):
+        version_str = version_str.decode("ascii")
+
+    return version_str
+
+
+# platform.libc_ver regularly returns completely nonsensical glibc
+# versions. E.g. on my computer, platform says:
+#
+#   ~$ python2.7 -c 'import platform; print(platform.libc_ver())'
+#   ('glibc', '2.7')
+#   ~$ python3.5 -c 'import platform; print(platform.libc_ver())'
+#   ('glibc', '2.9')
+#
+# But the truth is:
+#
+#   ~$ ldd --version
+#   ldd (Debian GLIBC 2.22-11) 2.22
+#
+# This is unfortunate, because it means that the linehaul data on libc
+# versions that was generated by pip 8.1.2 and earlier is useless and
+# misleading. Solution: instead of using platform, use our code that actually
+# works.
+def libc_ver() -> Tuple[str, str]:
+    """Try to determine the glibc version
+
+    Returns a tuple of strings (lib, version) which default to empty strings
+    in case the lookup fails.
+    """
+    glibc_version = glibc_version_string()
+    if glibc_version is None:
+        return ("", "")
+    else:
+        return ("glibc", glibc_version)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/hashes.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/hashes.py
new file mode 100644
index 0000000000000000000000000000000000000000..76727306a4c2b9fa47f1c3ed97c4941b2619cabe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/hashes.py
@@ -0,0 +1,144 @@
+import hashlib
+from typing import TYPE_CHECKING, BinaryIO, Dict, Iterable, List, Optional
+
+from pip._internal.exceptions import HashMismatch, HashMissing, InstallationError
+from pip._internal.utils.misc import read_chunks
+
+if TYPE_CHECKING:
+    from hashlib import _Hash
+
+    # NoReturn introduced in 3.6.2; imported only for type checking to maintain
+    # pip compatibility with older patch versions of Python 3.6
+    from typing import NoReturn
+
+
+# The recommended hash algo of the moment. Change this whenever the state of
+# the art changes; it won't hurt backward compatibility.
+FAVORITE_HASH = "sha256"
+
+
+# Names of hashlib algorithms allowed by the --hash option and ``pip hash``
+# Currently, those are the ones at least as collision-resistant as sha256.
+STRONG_HASHES = ["sha256", "sha384", "sha512"]
+
+
+class Hashes:
+    """A wrapper that builds multiple hashes at once and checks them against
+    known-good values
+
+    """
+
+    def __init__(self, hashes: Optional[Dict[str, List[str]]] = None) -> None:
+        """
+        :param hashes: A dict of algorithm names pointing to lists of allowed
+            hex digests
+        """
+        allowed = {}
+        if hashes is not None:
+            for alg, keys in hashes.items():
+                # Make sure values are always sorted (to ease equality checks)
+                allowed[alg] = sorted(keys)
+        self._allowed = allowed
+
+    def __and__(self, other: "Hashes") -> "Hashes":
+        if not isinstance(other, Hashes):
+            return NotImplemented
+
+        # If either of the Hashes object is entirely empty (i.e. no hash
+        # specified at all), all hashes from the other object are allowed.
+        if not other:
+            return self
+        if not self:
+            return other
+
+        # Otherwise only hashes that present in both objects are allowed.
+        new = {}
+        for alg, values in other._allowed.items():
+            if alg not in self._allowed:
+                continue
+            new[alg] = [v for v in values if v in self._allowed[alg]]
+        return Hashes(new)
+
+    @property
+    def digest_count(self) -> int:
+        return sum(len(digests) for digests in self._allowed.values())
+
+    def is_hash_allowed(self, hash_name: str, hex_digest: str) -> bool:
+        """Return whether the given hex digest is allowed."""
+        return hex_digest in self._allowed.get(hash_name, [])
+
+    def check_against_chunks(self, chunks: Iterable[bytes]) -> None:
+        """Check good hashes against ones built from iterable of chunks of
+        data.
+
+        Raise HashMismatch if none match.
+
+        """
+        gots = {}
+        for hash_name in self._allowed.keys():
+            try:
+                gots[hash_name] = hashlib.new(hash_name)
+            except (ValueError, TypeError):
+                raise InstallationError(f"Unknown hash name: {hash_name}")
+
+        for chunk in chunks:
+            for hash in gots.values():
+                hash.update(chunk)
+
+        for hash_name, got in gots.items():
+            if got.hexdigest() in self._allowed[hash_name]:
+                return
+        self._raise(gots)
+
+    def _raise(self, gots: Dict[str, "_Hash"]) -> "NoReturn":
+        raise HashMismatch(self._allowed, gots)
+
+    def check_against_file(self, file: BinaryIO) -> None:
+        """Check good hashes against a file-like object
+
+        Raise HashMismatch if none match.
+
+        """
+        return self.check_against_chunks(read_chunks(file))
+
+    def check_against_path(self, path: str) -> None:
+        with open(path, "rb") as file:
+            return self.check_against_file(file)
+
+    def __bool__(self) -> bool:
+        """Return whether I know any known-good hashes."""
+        return bool(self._allowed)
+
+    def __eq__(self, other: object) -> bool:
+        if not isinstance(other, Hashes):
+            return NotImplemented
+        return self._allowed == other._allowed
+
+    def __hash__(self) -> int:
+        return hash(
+            ",".join(
+                sorted(
+                    ":".join((alg, digest))
+                    for alg, digest_list in self._allowed.items()
+                    for digest in digest_list
+                )
+            )
+        )
+
+
+class MissingHashes(Hashes):
+    """A workalike for Hashes used when we're missing a hash for a requirement
+
+    It computes the actual hash of the requirement and raises a HashMissing
+    exception showing it to the user.
+
+    """
+
+    def __init__(self) -> None:
+        """Don't offer the ``hashes`` kwarg."""
+        # Pass our favorite hash in to generate a "gotten hash". With the
+        # empty list, it will never match, so an error will always raise.
+        super().__init__(hashes={FAVORITE_HASH: []})
+
+    def _raise(self, gots: Dict[str, "_Hash"]) -> "NoReturn":
+        raise HashMissing(gots[FAVORITE_HASH].hexdigest())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/inject_securetransport.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/inject_securetransport.py
new file mode 100644
index 0000000000000000000000000000000000000000..276aa79bb81356cdca73af0a5851b448707784a4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/inject_securetransport.py
@@ -0,0 +1,35 @@
+"""A helper module that injects SecureTransport, on import.
+
+The import should be done as early as possible, to ensure all requests and
+sessions (or whatever) are created after injecting SecureTransport.
+
+Note that we only do the injection on macOS, when the linked OpenSSL is too
+old to handle TLSv1.2.
+"""
+
+import sys
+
+
+def inject_securetransport() -> None:
+    # Only relevant on macOS
+    if sys.platform != "darwin":
+        return
+
+    try:
+        import ssl
+    except ImportError:
+        return
+
+    # Checks for OpenSSL 1.0.1
+    if ssl.OPENSSL_VERSION_NUMBER >= 0x1000100F:
+        return
+
+    try:
+        from pip._vendor.urllib3.contrib import securetransport
+    except (ImportError, OSError):
+        return
+
+    securetransport.inject_into_urllib3()
+
+
+inject_securetransport()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/logging.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/logging.py
new file mode 100644
index 0000000000000000000000000000000000000000..c10e1f4ced6bcc799799b62666695998e095bbaf
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/logging.py
@@ -0,0 +1,348 @@
+import contextlib
+import errno
+import logging
+import logging.handlers
+import os
+import sys
+import threading
+from dataclasses import dataclass
+from io import TextIOWrapper
+from logging import Filter
+from typing import Any, ClassVar, Generator, List, Optional, TextIO, Type
+
+from pip._vendor.rich.console import (
+    Console,
+    ConsoleOptions,
+    ConsoleRenderable,
+    RenderableType,
+    RenderResult,
+    RichCast,
+)
+from pip._vendor.rich.highlighter import NullHighlighter
+from pip._vendor.rich.logging import RichHandler
+from pip._vendor.rich.segment import Segment
+from pip._vendor.rich.style import Style
+
+from pip._internal.utils._log import VERBOSE, getLogger
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.deprecation import DEPRECATION_MSG_PREFIX
+from pip._internal.utils.misc import ensure_dir
+
+_log_state = threading.local()
+subprocess_logger = getLogger("pip.subprocessor")
+
+
+class BrokenStdoutLoggingError(Exception):
+    """
+    Raised if BrokenPipeError occurs for the stdout stream while logging.
+    """
+
+
+def _is_broken_pipe_error(exc_class: Type[BaseException], exc: BaseException) -> bool:
+    if exc_class is BrokenPipeError:
+        return True
+
+    # On Windows, a broken pipe can show up as EINVAL rather than EPIPE:
+    # https://bugs.python.org/issue19612
+    # https://bugs.python.org/issue30418
+    if not WINDOWS:
+        return False
+
+    return isinstance(exc, OSError) and exc.errno in (errno.EINVAL, errno.EPIPE)
+
+
+@contextlib.contextmanager
+def indent_log(num: int = 2) -> Generator[None, None, None]:
+    """
+    A context manager which will cause the log output to be indented for any
+    log messages emitted inside it.
+    """
+    # For thread-safety
+    _log_state.indentation = get_indentation()
+    _log_state.indentation += num
+    try:
+        yield
+    finally:
+        _log_state.indentation -= num
+
+
+def get_indentation() -> int:
+    return getattr(_log_state, "indentation", 0)
+
+
+class IndentingFormatter(logging.Formatter):
+    default_time_format = "%Y-%m-%dT%H:%M:%S"
+
+    def __init__(
+        self,
+        *args: Any,
+        add_timestamp: bool = False,
+        **kwargs: Any,
+    ) -> None:
+        """
+        A logging.Formatter that obeys the indent_log() context manager.
+
+        :param add_timestamp: A bool indicating output lines should be prefixed
+            with their record's timestamp.
+        """
+        self.add_timestamp = add_timestamp
+        super().__init__(*args, **kwargs)
+
+    def get_message_start(self, formatted: str, levelno: int) -> str:
+        """
+        Return the start of the formatted log message (not counting the
+        prefix to add to each line).
+        """
+        if levelno < logging.WARNING:
+            return ""
+        if formatted.startswith(DEPRECATION_MSG_PREFIX):
+            # Then the message already has a prefix.  We don't want it to
+            # look like "WARNING: DEPRECATION: ...."
+            return ""
+        if levelno < logging.ERROR:
+            return "WARNING: "
+
+        return "ERROR: "
+
+    def format(self, record: logging.LogRecord) -> str:
+        """
+        Calls the standard formatter, but will indent all of the log message
+        lines by our current indentation level.
+        """
+        formatted = super().format(record)
+        message_start = self.get_message_start(formatted, record.levelno)
+        formatted = message_start + formatted
+
+        prefix = ""
+        if self.add_timestamp:
+            prefix = f"{self.formatTime(record)} "
+        prefix += " " * get_indentation()
+        formatted = "".join([prefix + line for line in formatted.splitlines(True)])
+        return formatted
+
+
+@dataclass
+class IndentedRenderable:
+    renderable: RenderableType
+    indent: int
+
+    def __rich_console__(
+        self, console: Console, options: ConsoleOptions
+    ) -> RenderResult:
+        segments = console.render(self.renderable, options)
+        lines = Segment.split_lines(segments)
+        for line in lines:
+            yield Segment(" " * self.indent)
+            yield from line
+            yield Segment("\n")
+
+
+class RichPipStreamHandler(RichHandler):
+    KEYWORDS: ClassVar[Optional[List[str]]] = []
+
+    def __init__(self, stream: Optional[TextIO], no_color: bool) -> None:
+        super().__init__(
+            console=Console(file=stream, no_color=no_color, soft_wrap=True),
+            show_time=False,
+            show_level=False,
+            show_path=False,
+            highlighter=NullHighlighter(),
+        )
+
+    # Our custom override on Rich's logger, to make things work as we need them to.
+    def emit(self, record: logging.LogRecord) -> None:
+        style: Optional[Style] = None
+
+        # If we are given a diagnostic error to present, present it with indentation.
+        assert isinstance(record.args, tuple)
+        if record.msg == "[present-rich] %s" and len(record.args) == 1:
+            rich_renderable = record.args[0]
+            assert isinstance(
+                rich_renderable, (ConsoleRenderable, RichCast, str)
+            ), f"{rich_renderable} is not rich-console-renderable"
+
+            renderable: RenderableType = IndentedRenderable(
+                rich_renderable, indent=get_indentation()
+            )
+        else:
+            message = self.format(record)
+            renderable = self.render_message(record, message)
+            if record.levelno is not None:
+                if record.levelno >= logging.ERROR:
+                    style = Style(color="red")
+                elif record.levelno >= logging.WARNING:
+                    style = Style(color="yellow")
+
+        try:
+            self.console.print(renderable, overflow="ignore", crop=False, style=style)
+        except Exception:
+            self.handleError(record)
+
+    def handleError(self, record: logging.LogRecord) -> None:
+        """Called when logging is unable to log some output."""
+
+        exc_class, exc = sys.exc_info()[:2]
+        # If a broken pipe occurred while calling write() or flush() on the
+        # stdout stream in logging's Handler.emit(), then raise our special
+        # exception so we can handle it in main() instead of logging the
+        # broken pipe error and continuing.
+        if (
+            exc_class
+            and exc
+            and self.console.file is sys.stdout
+            and _is_broken_pipe_error(exc_class, exc)
+        ):
+            raise BrokenStdoutLoggingError()
+
+        return super().handleError(record)
+
+
+class BetterRotatingFileHandler(logging.handlers.RotatingFileHandler):
+    def _open(self) -> TextIOWrapper:
+        ensure_dir(os.path.dirname(self.baseFilename))
+        return super()._open()
+
+
+class MaxLevelFilter(Filter):
+    def __init__(self, level: int) -> None:
+        self.level = level
+
+    def filter(self, record: logging.LogRecord) -> bool:
+        return record.levelno < self.level
+
+
+class ExcludeLoggerFilter(Filter):
+
+    """
+    A logging Filter that excludes records from a logger (or its children).
+    """
+
+    def filter(self, record: logging.LogRecord) -> bool:
+        # The base Filter class allows only records from a logger (or its
+        # children).
+        return not super().filter(record)
+
+
+def setup_logging(verbosity: int, no_color: bool, user_log_file: Optional[str]) -> int:
+    """Configures and sets up all of the logging
+
+    Returns the requested logging level, as its integer value.
+    """
+
+    # Determine the level to be logging at.
+    if verbosity >= 2:
+        level_number = logging.DEBUG
+    elif verbosity == 1:
+        level_number = VERBOSE
+    elif verbosity == -1:
+        level_number = logging.WARNING
+    elif verbosity == -2:
+        level_number = logging.ERROR
+    elif verbosity <= -3:
+        level_number = logging.CRITICAL
+    else:
+        level_number = logging.INFO
+
+    level = logging.getLevelName(level_number)
+
+    # The "root" logger should match the "console" level *unless* we also need
+    # to log to a user log file.
+    include_user_log = user_log_file is not None
+    if include_user_log:
+        additional_log_file = user_log_file
+        root_level = "DEBUG"
+    else:
+        additional_log_file = "/dev/null"
+        root_level = level
+
+    # Disable any logging besides WARNING unless we have DEBUG level logging
+    # enabled for vendored libraries.
+    vendored_log_level = "WARNING" if level in ["INFO", "ERROR"] else "DEBUG"
+
+    # Shorthands for clarity
+    log_streams = {
+        "stdout": "ext://sys.stdout",
+        "stderr": "ext://sys.stderr",
+    }
+    handler_classes = {
+        "stream": "pip._internal.utils.logging.RichPipStreamHandler",
+        "file": "pip._internal.utils.logging.BetterRotatingFileHandler",
+    }
+    handlers = ["console", "console_errors", "console_subprocess"] + (
+        ["user_log"] if include_user_log else []
+    )
+
+    logging.config.dictConfig(
+        {
+            "version": 1,
+            "disable_existing_loggers": False,
+            "filters": {
+                "exclude_warnings": {
+                    "()": "pip._internal.utils.logging.MaxLevelFilter",
+                    "level": logging.WARNING,
+                },
+                "restrict_to_subprocess": {
+                    "()": "logging.Filter",
+                    "name": subprocess_logger.name,
+                },
+                "exclude_subprocess": {
+                    "()": "pip._internal.utils.logging.ExcludeLoggerFilter",
+                    "name": subprocess_logger.name,
+                },
+            },
+            "formatters": {
+                "indent": {
+                    "()": IndentingFormatter,
+                    "format": "%(message)s",
+                },
+                "indent_with_timestamp": {
+                    "()": IndentingFormatter,
+                    "format": "%(message)s",
+                    "add_timestamp": True,
+                },
+            },
+            "handlers": {
+                "console": {
+                    "level": level,
+                    "class": handler_classes["stream"],
+                    "no_color": no_color,
+                    "stream": log_streams["stdout"],
+                    "filters": ["exclude_subprocess", "exclude_warnings"],
+                    "formatter": "indent",
+                },
+                "console_errors": {
+                    "level": "WARNING",
+                    "class": handler_classes["stream"],
+                    "no_color": no_color,
+                    "stream": log_streams["stderr"],
+                    "filters": ["exclude_subprocess"],
+                    "formatter": "indent",
+                },
+                # A handler responsible for logging to the console messages
+                # from the "subprocessor" logger.
+                "console_subprocess": {
+                    "level": level,
+                    "class": handler_classes["stream"],
+                    "stream": log_streams["stderr"],
+                    "no_color": no_color,
+                    "filters": ["restrict_to_subprocess"],
+                    "formatter": "indent",
+                },
+                "user_log": {
+                    "level": "DEBUG",
+                    "class": handler_classes["file"],
+                    "filename": additional_log_file,
+                    "encoding": "utf-8",
+                    "delay": True,
+                    "formatter": "indent_with_timestamp",
+                },
+            },
+            "root": {
+                "level": root_level,
+                "handlers": handlers,
+            },
+            "loggers": {"pip._vendor": {"level": vendored_log_level}},
+        }
+    )
+
+    return level_number
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/misc.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/misc.py
new file mode 100644
index 0000000000000000000000000000000000000000..baa1ba7eac27ca1d7cd6df23600d578385d5290e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/misc.py
@@ -0,0 +1,739 @@
+# The following comment should be removed at some point in the future.
+# mypy: strict-optional=False
+
+import contextlib
+import errno
+import getpass
+import hashlib
+import io
+import logging
+import os
+import posixpath
+import shutil
+import stat
+import sys
+import sysconfig
+import urllib.parse
+from io import StringIO
+from itertools import filterfalse, tee, zip_longest
+from types import TracebackType
+from typing import (
+    Any,
+    BinaryIO,
+    Callable,
+    ContextManager,
+    Dict,
+    Generator,
+    Iterable,
+    Iterator,
+    List,
+    Optional,
+    TextIO,
+    Tuple,
+    Type,
+    TypeVar,
+    cast,
+)
+
+from pip._vendor.pyproject_hooks import BuildBackendHookCaller
+from pip._vendor.tenacity import retry, stop_after_delay, wait_fixed
+
+from pip import __version__
+from pip._internal.exceptions import CommandError, ExternallyManagedEnvironment
+from pip._internal.locations import get_major_minor_version
+from pip._internal.utils.compat import WINDOWS
+from pip._internal.utils.virtualenv import running_under_virtualenv
+
+__all__ = [
+    "rmtree",
+    "display_path",
+    "backup_dir",
+    "ask",
+    "splitext",
+    "format_size",
+    "is_installable_dir",
+    "normalize_path",
+    "renames",
+    "get_prog",
+    "captured_stdout",
+    "ensure_dir",
+    "remove_auth_from_url",
+    "check_externally_managed",
+    "ConfiguredBuildBackendHookCaller",
+]
+
+logger = logging.getLogger(__name__)
+
+T = TypeVar("T")
+ExcInfo = Tuple[Type[BaseException], BaseException, TracebackType]
+VersionInfo = Tuple[int, int, int]
+NetlocTuple = Tuple[str, Tuple[Optional[str], Optional[str]]]
+
+
+def get_pip_version() -> str:
+    pip_pkg_dir = os.path.join(os.path.dirname(__file__), "..", "..")
+    pip_pkg_dir = os.path.abspath(pip_pkg_dir)
+
+    return "pip {} from {} (python {})".format(
+        __version__,
+        pip_pkg_dir,
+        get_major_minor_version(),
+    )
+
+
+def normalize_version_info(py_version_info: Tuple[int, ...]) -> Tuple[int, int, int]:
+    """
+    Convert a tuple of ints representing a Python version to one of length
+    three.
+
+    :param py_version_info: a tuple of ints representing a Python version,
+        or None to specify no version. The tuple can have any length.
+
+    :return: a tuple of length three if `py_version_info` is non-None.
+        Otherwise, return `py_version_info` unchanged (i.e. None).
+    """
+    if len(py_version_info) < 3:
+        py_version_info += (3 - len(py_version_info)) * (0,)
+    elif len(py_version_info) > 3:
+        py_version_info = py_version_info[:3]
+
+    return cast("VersionInfo", py_version_info)
+
+
+def ensure_dir(path: str) -> None:
+    """os.path.makedirs without EEXIST."""
+    try:
+        os.makedirs(path)
+    except OSError as e:
+        # Windows can raise spurious ENOTEMPTY errors. See #6426.
+        if e.errno != errno.EEXIST and e.errno != errno.ENOTEMPTY:
+            raise
+
+
+def get_prog() -> str:
+    try:
+        prog = os.path.basename(sys.argv[0])
+        if prog in ("__main__.py", "-c"):
+            return f"{sys.executable} -m pip"
+        else:
+            return prog
+    except (AttributeError, TypeError, IndexError):
+        pass
+    return "pip"
+
+
+# Retry every half second for up to 3 seconds
+# Tenacity raises RetryError by default, explicitly raise the original exception
+@retry(reraise=True, stop=stop_after_delay(3), wait=wait_fixed(0.5))
+def rmtree(dir: str, ignore_errors: bool = False) -> None:
+    shutil.rmtree(dir, ignore_errors=ignore_errors, onerror=rmtree_errorhandler)
+
+
+def rmtree_errorhandler(func: Callable[..., Any], path: str, exc_info: ExcInfo) -> None:
+    """On Windows, the files in .svn are read-only, so when rmtree() tries to
+    remove them, an exception is thrown.  We catch that here, remove the
+    read-only attribute, and hopefully continue without problems."""
+    try:
+        has_attr_readonly = not (os.stat(path).st_mode & stat.S_IWRITE)
+    except OSError:
+        # it's equivalent to os.path.exists
+        return
+
+    if has_attr_readonly:
+        # convert to read/write
+        os.chmod(path, stat.S_IWRITE)
+        # use the original function to repeat the operation
+        func(path)
+        return
+    else:
+        raise
+
+
+def display_path(path: str) -> str:
+    """Gives the display value for a given path, making it relative to cwd
+    if possible."""
+    path = os.path.normcase(os.path.abspath(path))
+    if path.startswith(os.getcwd() + os.path.sep):
+        path = "." + path[len(os.getcwd()) :]
+    return path
+
+
+def backup_dir(dir: str, ext: str = ".bak") -> str:
+    """Figure out the name of a directory to back up the given dir to
+    (adding .bak, .bak2, etc)"""
+    n = 1
+    extension = ext
+    while os.path.exists(dir + extension):
+        n += 1
+        extension = ext + str(n)
+    return dir + extension
+
+
+def ask_path_exists(message: str, options: Iterable[str]) -> str:
+    for action in os.environ.get("PIP_EXISTS_ACTION", "").split():
+        if action in options:
+            return action
+    return ask(message, options)
+
+
+def _check_no_input(message: str) -> None:
+    """Raise an error if no input is allowed."""
+    if os.environ.get("PIP_NO_INPUT"):
+        raise Exception(
+            f"No input was expected ($PIP_NO_INPUT set); question: {message}"
+        )
+
+
+def ask(message: str, options: Iterable[str]) -> str:
+    """Ask the message interactively, with the given possible responses"""
+    while 1:
+        _check_no_input(message)
+        response = input(message)
+        response = response.strip().lower()
+        if response not in options:
+            print(
+                "Your response ({!r}) was not one of the expected responses: "
+                "{}".format(response, ", ".join(options))
+            )
+        else:
+            return response
+
+
+def ask_input(message: str) -> str:
+    """Ask for input interactively."""
+    _check_no_input(message)
+    return input(message)
+
+
+def ask_password(message: str) -> str:
+    """Ask for a password interactively."""
+    _check_no_input(message)
+    return getpass.getpass(message)
+
+
+def strtobool(val: str) -> int:
+    """Convert a string representation of truth to true (1) or false (0).
+
+    True values are 'y', 'yes', 't', 'true', 'on', and '1'; false values
+    are 'n', 'no', 'f', 'false', 'off', and '0'.  Raises ValueError if
+    'val' is anything else.
+    """
+    val = val.lower()
+    if val in ("y", "yes", "t", "true", "on", "1"):
+        return 1
+    elif val in ("n", "no", "f", "false", "off", "0"):
+        return 0
+    else:
+        raise ValueError(f"invalid truth value {val!r}")
+
+
+def format_size(bytes: float) -> str:
+    if bytes > 1000 * 1000:
+        return "{:.1f} MB".format(bytes / 1000.0 / 1000)
+    elif bytes > 10 * 1000:
+        return "{} kB".format(int(bytes / 1000))
+    elif bytes > 1000:
+        return "{:.1f} kB".format(bytes / 1000.0)
+    else:
+        return "{} bytes".format(int(bytes))
+
+
+def tabulate(rows: Iterable[Iterable[Any]]) -> Tuple[List[str], List[int]]:
+    """Return a list of formatted rows and a list of column sizes.
+
+    For example::
+
+    >>> tabulate([['foobar', 2000], [0xdeadbeef]])
+    (['foobar     2000', '3735928559'], [10, 4])
+    """
+    rows = [tuple(map(str, row)) for row in rows]
+    sizes = [max(map(len, col)) for col in zip_longest(*rows, fillvalue="")]
+    table = [" ".join(map(str.ljust, row, sizes)).rstrip() for row in rows]
+    return table, sizes
+
+
+def is_installable_dir(path: str) -> bool:
+    """Is path is a directory containing pyproject.toml or setup.py?
+
+    If pyproject.toml exists, this is a PEP 517 project. Otherwise we look for
+    a legacy setuptools layout by identifying setup.py. We don't check for the
+    setup.cfg because using it without setup.py is only available for PEP 517
+    projects, which are already covered by the pyproject.toml check.
+    """
+    if not os.path.isdir(path):
+        return False
+    if os.path.isfile(os.path.join(path, "pyproject.toml")):
+        return True
+    if os.path.isfile(os.path.join(path, "setup.py")):
+        return True
+    return False
+
+
+def read_chunks(
+    file: BinaryIO, size: int = io.DEFAULT_BUFFER_SIZE
+) -> Generator[bytes, None, None]:
+    """Yield pieces of data from a file-like object until EOF."""
+    while True:
+        chunk = file.read(size)
+        if not chunk:
+            break
+        yield chunk
+
+
+def normalize_path(path: str, resolve_symlinks: bool = True) -> str:
+    """
+    Convert a path to its canonical, case-normalized, absolute version.
+
+    """
+    path = os.path.expanduser(path)
+    if resolve_symlinks:
+        path = os.path.realpath(path)
+    else:
+        path = os.path.abspath(path)
+    return os.path.normcase(path)
+
+
+def splitext(path: str) -> Tuple[str, str]:
+    """Like os.path.splitext, but take off .tar too"""
+    base, ext = posixpath.splitext(path)
+    if base.lower().endswith(".tar"):
+        ext = base[-4:] + ext
+        base = base[:-4]
+    return base, ext
+
+
+def renames(old: str, new: str) -> None:
+    """Like os.renames(), but handles renaming across devices."""
+    # Implementation borrowed from os.renames().
+    head, tail = os.path.split(new)
+    if head and tail and not os.path.exists(head):
+        os.makedirs(head)
+
+    shutil.move(old, new)
+
+    head, tail = os.path.split(old)
+    if head and tail:
+        try:
+            os.removedirs(head)
+        except OSError:
+            pass
+
+
+def is_local(path: str) -> bool:
+    """
+    Return True if path is within sys.prefix, if we're running in a virtualenv.
+
+    If we're not in a virtualenv, all paths are considered "local."
+
+    Caution: this function assumes the head of path has been normalized
+    with normalize_path.
+    """
+    if not running_under_virtualenv():
+        return True
+    return path.startswith(normalize_path(sys.prefix))
+
+
+def write_output(msg: Any, *args: Any) -> None:
+    logger.info(msg, *args)
+
+
+class StreamWrapper(StringIO):
+    orig_stream: TextIO = None
+
+    @classmethod
+    def from_stream(cls, orig_stream: TextIO) -> "StreamWrapper":
+        cls.orig_stream = orig_stream
+        return cls()
+
+    # compileall.compile_dir() needs stdout.encoding to print to stdout
+    # https://github.com/python/mypy/issues/4125
+    @property
+    def encoding(self):  # type: ignore
+        return self.orig_stream.encoding
+
+
+@contextlib.contextmanager
+def captured_output(stream_name: str) -> Generator[StreamWrapper, None, None]:
+    """Return a context manager used by captured_stdout/stdin/stderr
+    that temporarily replaces the sys stream *stream_name* with a StringIO.
+
+    Taken from Lib/support/__init__.py in the CPython repo.
+    """
+    orig_stdout = getattr(sys, stream_name)
+    setattr(sys, stream_name, StreamWrapper.from_stream(orig_stdout))
+    try:
+        yield getattr(sys, stream_name)
+    finally:
+        setattr(sys, stream_name, orig_stdout)
+
+
+def captured_stdout() -> ContextManager[StreamWrapper]:
+    """Capture the output of sys.stdout:
+
+       with captured_stdout() as stdout:
+           print('hello')
+       self.assertEqual(stdout.getvalue(), 'hello\n')
+
+    Taken from Lib/support/__init__.py in the CPython repo.
+    """
+    return captured_output("stdout")
+
+
+def captured_stderr() -> ContextManager[StreamWrapper]:
+    """
+    See captured_stdout().
+    """
+    return captured_output("stderr")
+
+
+# Simulates an enum
+def enum(*sequential: Any, **named: Any) -> Type[Any]:
+    enums = dict(zip(sequential, range(len(sequential))), **named)
+    reverse = {value: key for key, value in enums.items()}
+    enums["reverse_mapping"] = reverse
+    return type("Enum", (), enums)
+
+
+def build_netloc(host: str, port: Optional[int]) -> str:
+    """
+    Build a netloc from a host-port pair
+    """
+    if port is None:
+        return host
+    if ":" in host:
+        # Only wrap host with square brackets when it is IPv6
+        host = f"[{host}]"
+    return f"{host}:{port}"
+
+
+def build_url_from_netloc(netloc: str, scheme: str = "https") -> str:
+    """
+    Build a full URL from a netloc.
+    """
+    if netloc.count(":") >= 2 and "@" not in netloc and "[" not in netloc:
+        # It must be a bare IPv6 address, so wrap it with brackets.
+        netloc = f"[{netloc}]"
+    return f"{scheme}://{netloc}"
+
+
+def parse_netloc(netloc: str) -> Tuple[str, Optional[int]]:
+    """
+    Return the host-port pair from a netloc.
+    """
+    url = build_url_from_netloc(netloc)
+    parsed = urllib.parse.urlparse(url)
+    return parsed.hostname, parsed.port
+
+
+def split_auth_from_netloc(netloc: str) -> NetlocTuple:
+    """
+    Parse out and remove the auth information from a netloc.
+
+    Returns: (netloc, (username, password)).
+    """
+    if "@" not in netloc:
+        return netloc, (None, None)
+
+    # Split from the right because that's how urllib.parse.urlsplit()
+    # behaves if more than one @ is present (which can be checked using
+    # the password attribute of urlsplit()'s return value).
+    auth, netloc = netloc.rsplit("@", 1)
+    pw: Optional[str] = None
+    if ":" in auth:
+        # Split from the left because that's how urllib.parse.urlsplit()
+        # behaves if more than one : is present (which again can be checked
+        # using the password attribute of the return value)
+        user, pw = auth.split(":", 1)
+    else:
+        user, pw = auth, None
+
+    user = urllib.parse.unquote(user)
+    if pw is not None:
+        pw = urllib.parse.unquote(pw)
+
+    return netloc, (user, pw)
+
+
+def redact_netloc(netloc: str) -> str:
+    """
+    Replace the sensitive data in a netloc with "****", if it exists.
+
+    For example:
+        - "user:pass@example.com" returns "user:****@example.com"
+        - "accesstoken@example.com" returns "****@example.com"
+    """
+    netloc, (user, password) = split_auth_from_netloc(netloc)
+    if user is None:
+        return netloc
+    if password is None:
+        user = "****"
+        password = ""
+    else:
+        user = urllib.parse.quote(user)
+        password = ":****"
+    return "{user}{password}@{netloc}".format(
+        user=user, password=password, netloc=netloc
+    )
+
+
+def _transform_url(
+    url: str, transform_netloc: Callable[[str], Tuple[Any, ...]]
+) -> Tuple[str, NetlocTuple]:
+    """Transform and replace netloc in a url.
+
+    transform_netloc is a function taking the netloc and returning a
+    tuple. The first element of this tuple is the new netloc. The
+    entire tuple is returned.
+
+    Returns a tuple containing the transformed url as item 0 and the
+    original tuple returned by transform_netloc as item 1.
+    """
+    purl = urllib.parse.urlsplit(url)
+    netloc_tuple = transform_netloc(purl.netloc)
+    # stripped url
+    url_pieces = (purl.scheme, netloc_tuple[0], purl.path, purl.query, purl.fragment)
+    surl = urllib.parse.urlunsplit(url_pieces)
+    return surl, cast("NetlocTuple", netloc_tuple)
+
+
+def _get_netloc(netloc: str) -> NetlocTuple:
+    return split_auth_from_netloc(netloc)
+
+
+def _redact_netloc(netloc: str) -> Tuple[str]:
+    return (redact_netloc(netloc),)
+
+
+def split_auth_netloc_from_url(url: str) -> Tuple[str, str, Tuple[str, str]]:
+    """
+    Parse a url into separate netloc, auth, and url with no auth.
+
+    Returns: (url_without_auth, netloc, (username, password))
+    """
+    url_without_auth, (netloc, auth) = _transform_url(url, _get_netloc)
+    return url_without_auth, netloc, auth
+
+
+def remove_auth_from_url(url: str) -> str:
+    """Return a copy of url with 'username:password@' removed."""
+    # username/pass params are passed to subversion through flags
+    # and are not recognized in the url.
+    return _transform_url(url, _get_netloc)[0]
+
+
+def redact_auth_from_url(url: str) -> str:
+    """Replace the password in a given url with ****."""
+    return _transform_url(url, _redact_netloc)[0]
+
+
+class HiddenText:
+    def __init__(self, secret: str, redacted: str) -> None:
+        self.secret = secret
+        self.redacted = redacted
+
+    def __repr__(self) -> str:
+        return "".format(str(self))
+
+    def __str__(self) -> str:
+        return self.redacted
+
+    # This is useful for testing.
+    def __eq__(self, other: Any) -> bool:
+        if type(self) != type(other):
+            return False
+
+        # The string being used for redaction doesn't also have to match,
+        # just the raw, original string.
+        return self.secret == other.secret
+
+
+def hide_value(value: str) -> HiddenText:
+    return HiddenText(value, redacted="****")
+
+
+def hide_url(url: str) -> HiddenText:
+    redacted = redact_auth_from_url(url)
+    return HiddenText(url, redacted=redacted)
+
+
+def protect_pip_from_modification_on_windows(modifying_pip: bool) -> None:
+    """Protection of pip.exe from modification on Windows
+
+    On Windows, any operation modifying pip should be run as:
+        python -m pip ...
+    """
+    pip_names = [
+        "pip",
+        f"pip{sys.version_info.major}",
+        f"pip{sys.version_info.major}.{sys.version_info.minor}",
+    ]
+
+    # See https://github.com/pypa/pip/issues/1299 for more discussion
+    should_show_use_python_msg = (
+        modifying_pip and WINDOWS and os.path.basename(sys.argv[0]) in pip_names
+    )
+
+    if should_show_use_python_msg:
+        new_command = [sys.executable, "-m", "pip"] + sys.argv[1:]
+        raise CommandError(
+            "To modify pip, please run the following command:\n{}".format(
+                " ".join(new_command)
+            )
+        )
+
+
+def check_externally_managed() -> None:
+    """Check whether the current environment is externally managed.
+
+    If the ``EXTERNALLY-MANAGED`` config file is found, the current environment
+    is considered externally managed, and an ExternallyManagedEnvironment is
+    raised.
+    """
+    if running_under_virtualenv():
+        return
+    marker = os.path.join(sysconfig.get_path("stdlib"), "EXTERNALLY-MANAGED")
+    if not os.path.isfile(marker):
+        return
+    raise ExternallyManagedEnvironment.from_config(marker)
+
+
+def is_console_interactive() -> bool:
+    """Is this console interactive?"""
+    return sys.stdin is not None and sys.stdin.isatty()
+
+
+def hash_file(path: str, blocksize: int = 1 << 20) -> Tuple[Any, int]:
+    """Return (hash, length) for path using hashlib.sha256()"""
+
+    h = hashlib.sha256()
+    length = 0
+    with open(path, "rb") as f:
+        for block in read_chunks(f, size=blocksize):
+            length += len(block)
+            h.update(block)
+    return h, length
+
+
+def is_wheel_installed() -> bool:
+    """
+    Return whether the wheel package is installed.
+    """
+    try:
+        import wheel  # noqa: F401
+    except ImportError:
+        return False
+
+    return True
+
+
+def pairwise(iterable: Iterable[Any]) -> Iterator[Tuple[Any, Any]]:
+    """
+    Return paired elements.
+
+    For example:
+        s -> (s0, s1), (s2, s3), (s4, s5), ...
+    """
+    iterable = iter(iterable)
+    return zip_longest(iterable, iterable)
+
+
+def partition(
+    pred: Callable[[T], bool],
+    iterable: Iterable[T],
+) -> Tuple[Iterable[T], Iterable[T]]:
+    """
+    Use a predicate to partition entries into false entries and true entries,
+    like
+
+        partition(is_odd, range(10)) --> 0 2 4 6 8   and  1 3 5 7 9
+    """
+    t1, t2 = tee(iterable)
+    return filterfalse(pred, t1), filter(pred, t2)
+
+
+class ConfiguredBuildBackendHookCaller(BuildBackendHookCaller):
+    def __init__(
+        self,
+        config_holder: Any,
+        source_dir: str,
+        build_backend: str,
+        backend_path: Optional[str] = None,
+        runner: Optional[Callable[..., None]] = None,
+        python_executable: Optional[str] = None,
+    ):
+        super().__init__(
+            source_dir, build_backend, backend_path, runner, python_executable
+        )
+        self.config_holder = config_holder
+
+    def build_wheel(
+        self,
+        wheel_directory: str,
+        config_settings: Optional[Dict[str, str]] = None,
+        metadata_directory: Optional[str] = None,
+    ) -> str:
+        cs = self.config_holder.config_settings
+        return super().build_wheel(
+            wheel_directory, config_settings=cs, metadata_directory=metadata_directory
+        )
+
+    def build_sdist(
+        self, sdist_directory: str, config_settings: Optional[Dict[str, str]] = None
+    ) -> str:
+        cs = self.config_holder.config_settings
+        return super().build_sdist(sdist_directory, config_settings=cs)
+
+    def build_editable(
+        self,
+        wheel_directory: str,
+        config_settings: Optional[Dict[str, str]] = None,
+        metadata_directory: Optional[str] = None,
+    ) -> str:
+        cs = self.config_holder.config_settings
+        return super().build_editable(
+            wheel_directory, config_settings=cs, metadata_directory=metadata_directory
+        )
+
+    def get_requires_for_build_wheel(
+        self, config_settings: Optional[Dict[str, str]] = None
+    ) -> List[str]:
+        cs = self.config_holder.config_settings
+        return super().get_requires_for_build_wheel(config_settings=cs)
+
+    def get_requires_for_build_sdist(
+        self, config_settings: Optional[Dict[str, str]] = None
+    ) -> List[str]:
+        cs = self.config_holder.config_settings
+        return super().get_requires_for_build_sdist(config_settings=cs)
+
+    def get_requires_for_build_editable(
+        self, config_settings: Optional[Dict[str, str]] = None
+    ) -> List[str]:
+        cs = self.config_holder.config_settings
+        return super().get_requires_for_build_editable(config_settings=cs)
+
+    def prepare_metadata_for_build_wheel(
+        self,
+        metadata_directory: str,
+        config_settings: Optional[Dict[str, str]] = None,
+        _allow_fallback: bool = True,
+    ) -> str:
+        cs = self.config_holder.config_settings
+        return super().prepare_metadata_for_build_wheel(
+            metadata_directory=metadata_directory,
+            config_settings=cs,
+            _allow_fallback=_allow_fallback,
+        )
+
+    def prepare_metadata_for_build_editable(
+        self,
+        metadata_directory: str,
+        config_settings: Optional[Dict[str, str]] = None,
+        _allow_fallback: bool = True,
+    ) -> str:
+        cs = self.config_holder.config_settings
+        return super().prepare_metadata_for_build_editable(
+            metadata_directory=metadata_directory,
+            config_settings=cs,
+            _allow_fallback=_allow_fallback,
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/models.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/models.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6bb21a8b26680b38c3af8278ed139b6628356c5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/models.py
@@ -0,0 +1,39 @@
+"""Utilities for defining models
+"""
+
+import operator
+from typing import Any, Callable, Type
+
+
+class KeyBasedCompareMixin:
+    """Provides comparison capabilities that is based on a key"""
+
+    __slots__ = ["_compare_key", "_defining_class"]
+
+    def __init__(self, key: Any, defining_class: Type["KeyBasedCompareMixin"]) -> None:
+        self._compare_key = key
+        self._defining_class = defining_class
+
+    def __hash__(self) -> int:
+        return hash(self._compare_key)
+
+    def __lt__(self, other: Any) -> bool:
+        return self._compare(other, operator.__lt__)
+
+    def __le__(self, other: Any) -> bool:
+        return self._compare(other, operator.__le__)
+
+    def __gt__(self, other: Any) -> bool:
+        return self._compare(other, operator.__gt__)
+
+    def __ge__(self, other: Any) -> bool:
+        return self._compare(other, operator.__ge__)
+
+    def __eq__(self, other: Any) -> bool:
+        return self._compare(other, operator.__eq__)
+
+    def _compare(self, other: Any, method: Callable[[Any, Any], bool]) -> bool:
+        if not isinstance(other, self._defining_class):
+            return NotImplemented
+
+        return method(self._compare_key, other._compare_key)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/packaging.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/packaging.py
new file mode 100644
index 0000000000000000000000000000000000000000..b9f6af4d17410ce7e1d573c41a1f04dd18ae275e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/packaging.py
@@ -0,0 +1,57 @@
+import functools
+import logging
+import re
+from typing import NewType, Optional, Tuple, cast
+
+from pip._vendor.packaging import specifiers, version
+from pip._vendor.packaging.requirements import Requirement
+
+NormalizedExtra = NewType("NormalizedExtra", str)
+
+logger = logging.getLogger(__name__)
+
+
+def check_requires_python(
+    requires_python: Optional[str], version_info: Tuple[int, ...]
+) -> bool:
+    """
+    Check if the given Python version matches a "Requires-Python" specifier.
+
+    :param version_info: A 3-tuple of ints representing a Python
+        major-minor-micro version to check (e.g. `sys.version_info[:3]`).
+
+    :return: `True` if the given Python version satisfies the requirement.
+        Otherwise, return `False`.
+
+    :raises InvalidSpecifier: If `requires_python` has an invalid format.
+    """
+    if requires_python is None:
+        # The package provides no information
+        return True
+    requires_python_specifier = specifiers.SpecifierSet(requires_python)
+
+    python_version = version.parse(".".join(map(str, version_info)))
+    return python_version in requires_python_specifier
+
+
+@functools.lru_cache(maxsize=512)
+def get_requirement(req_string: str) -> Requirement:
+    """Construct a packaging.Requirement object with caching"""
+    # Parsing requirement strings is expensive, and is also expected to happen
+    # with a low diversity of different arguments (at least relative the number
+    # constructed). This method adds a cache to requirement object creation to
+    # minimize repeated parsing of the same string to construct equivalent
+    # Requirement objects.
+    return Requirement(req_string)
+
+
+def safe_extra(extra: str) -> NormalizedExtra:
+    """Convert an arbitrary string to a standard 'extra' name
+
+    Any runs of non-alphanumeric characters are replaced with a single '_',
+    and the result is always lowercased.
+
+    This function is duplicated from ``pkg_resources``. Note that this is not
+    the same to either ``canonicalize_name`` or ``_egg_link_name``.
+    """
+    return cast(NormalizedExtra, re.sub("[^A-Za-z0-9.-]+", "_", extra).lower())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/setuptools_build.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/setuptools_build.py
new file mode 100644
index 0000000000000000000000000000000000000000..01ef4a4ca59b5f592c7b89bec136d6b8af785ba2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/setuptools_build.py
@@ -0,0 +1,195 @@
+import sys
+import textwrap
+from typing import List, Optional, Sequence
+
+# Shim to wrap setup.py invocation with setuptools
+# Note that __file__ is handled via two {!r} *and* %r, to ensure that paths on
+# Windows are correctly handled (it should be "C:\\Users" not "C:\Users").
+_SETUPTOOLS_SHIM = textwrap.dedent(
+    """
+    exec(compile('''
+    # This is  -- a caller that pip uses to run setup.py
+    #
+    # - It imports setuptools before invoking setup.py, to enable projects that directly
+    #   import from `distutils.core` to work with newer packaging standards.
+    # - It provides a clear error message when setuptools is not installed.
+    # - It sets `sys.argv[0]` to the underlying `setup.py`, when invoking `setup.py` so
+    #   setuptools doesn't think the script is `-c`. This avoids the following warning:
+    #     manifest_maker: standard file '-c' not found".
+    # - It generates a shim setup.py, for handling setup.cfg-only projects.
+    import os, sys, tokenize
+
+    try:
+        import setuptools
+    except ImportError as error:
+        print(
+            "ERROR: Can not execute `setup.py` since setuptools is not available in "
+            "the build environment.",
+            file=sys.stderr,
+        )
+        sys.exit(1)
+
+    __file__ = %r
+    sys.argv[0] = __file__
+
+    if os.path.exists(__file__):
+        filename = __file__
+        with tokenize.open(__file__) as f:
+            setup_py_code = f.read()
+    else:
+        filename = ""
+        setup_py_code = "from setuptools import setup; setup()"
+
+    exec(compile(setup_py_code, filename, "exec"))
+    ''' % ({!r},), "", "exec"))
+    """
+).rstrip()
+
+
+def make_setuptools_shim_args(
+    setup_py_path: str,
+    global_options: Optional[Sequence[str]] = None,
+    no_user_config: bool = False,
+    unbuffered_output: bool = False,
+) -> List[str]:
+    """
+    Get setuptools command arguments with shim wrapped setup file invocation.
+
+    :param setup_py_path: The path to setup.py to be wrapped.
+    :param global_options: Additional global options.
+    :param no_user_config: If True, disables personal user configuration.
+    :param unbuffered_output: If True, adds the unbuffered switch to the
+     argument list.
+    """
+    args = [sys.executable]
+    if unbuffered_output:
+        args += ["-u"]
+    args += ["-c", _SETUPTOOLS_SHIM.format(setup_py_path)]
+    if global_options:
+        args += global_options
+    if no_user_config:
+        args += ["--no-user-cfg"]
+    return args
+
+
+def make_setuptools_bdist_wheel_args(
+    setup_py_path: str,
+    global_options: Sequence[str],
+    build_options: Sequence[str],
+    destination_dir: str,
+) -> List[str]:
+    # NOTE: Eventually, we'd want to also -S to the flags here, when we're
+    # isolating. Currently, it breaks Python in virtualenvs, because it
+    # relies on site.py to find parts of the standard library outside the
+    # virtualenv.
+    args = make_setuptools_shim_args(
+        setup_py_path, global_options=global_options, unbuffered_output=True
+    )
+    args += ["bdist_wheel", "-d", destination_dir]
+    args += build_options
+    return args
+
+
+def make_setuptools_clean_args(
+    setup_py_path: str,
+    global_options: Sequence[str],
+) -> List[str]:
+    args = make_setuptools_shim_args(
+        setup_py_path, global_options=global_options, unbuffered_output=True
+    )
+    args += ["clean", "--all"]
+    return args
+
+
+def make_setuptools_develop_args(
+    setup_py_path: str,
+    global_options: Sequence[str],
+    install_options: Sequence[str],
+    no_user_config: bool,
+    prefix: Optional[str],
+    home: Optional[str],
+    use_user_site: bool,
+) -> List[str]:
+    assert not (use_user_site and prefix)
+
+    args = make_setuptools_shim_args(
+        setup_py_path,
+        global_options=global_options,
+        no_user_config=no_user_config,
+    )
+
+    args += ["develop", "--no-deps"]
+
+    args += install_options
+
+    if prefix:
+        args += ["--prefix", prefix]
+    if home is not None:
+        args += ["--install-dir", home]
+
+    if use_user_site:
+        args += ["--user", "--prefix="]
+
+    return args
+
+
+def make_setuptools_egg_info_args(
+    setup_py_path: str,
+    egg_info_dir: Optional[str],
+    no_user_config: bool,
+) -> List[str]:
+    args = make_setuptools_shim_args(setup_py_path, no_user_config=no_user_config)
+
+    args += ["egg_info"]
+
+    if egg_info_dir:
+        args += ["--egg-base", egg_info_dir]
+
+    return args
+
+
+def make_setuptools_install_args(
+    setup_py_path: str,
+    global_options: Sequence[str],
+    install_options: Sequence[str],
+    record_filename: str,
+    root: Optional[str],
+    prefix: Optional[str],
+    header_dir: Optional[str],
+    home: Optional[str],
+    use_user_site: bool,
+    no_user_config: bool,
+    pycompile: bool,
+) -> List[str]:
+    assert not (use_user_site and prefix)
+    assert not (use_user_site and root)
+
+    args = make_setuptools_shim_args(
+        setup_py_path,
+        global_options=global_options,
+        no_user_config=no_user_config,
+        unbuffered_output=True,
+    )
+    args += ["install", "--record", record_filename]
+    args += ["--single-version-externally-managed"]
+
+    if root is not None:
+        args += ["--root", root]
+    if prefix is not None:
+        args += ["--prefix", prefix]
+    if home is not None:
+        args += ["--home", home]
+    if use_user_site:
+        args += ["--user", "--prefix="]
+
+    if pycompile:
+        args += ["--compile"]
+    else:
+        args += ["--no-compile"]
+
+    if header_dir:
+        args += ["--install-headers", header_dir]
+
+    args += install_options
+
+    return args
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/subprocess.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/subprocess.py
new file mode 100644
index 0000000000000000000000000000000000000000..1e8ff50edfb8059799b334325e65eea9bb9b1ab3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/subprocess.py
@@ -0,0 +1,260 @@
+import logging
+import os
+import shlex
+import subprocess
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    Iterable,
+    List,
+    Mapping,
+    Optional,
+    Union,
+)
+
+from pip._vendor.rich.markup import escape
+
+from pip._internal.cli.spinners import SpinnerInterface, open_spinner
+from pip._internal.exceptions import InstallationSubprocessError
+from pip._internal.utils.logging import VERBOSE, subprocess_logger
+from pip._internal.utils.misc import HiddenText
+
+if TYPE_CHECKING:
+    # Literal was introduced in Python 3.8.
+    #
+    # TODO: Remove `if TYPE_CHECKING` when dropping support for Python 3.7.
+    from typing import Literal
+
+CommandArgs = List[Union[str, HiddenText]]
+
+
+def make_command(*args: Union[str, HiddenText, CommandArgs]) -> CommandArgs:
+    """
+    Create a CommandArgs object.
+    """
+    command_args: CommandArgs = []
+    for arg in args:
+        # Check for list instead of CommandArgs since CommandArgs is
+        # only known during type-checking.
+        if isinstance(arg, list):
+            command_args.extend(arg)
+        else:
+            # Otherwise, arg is str or HiddenText.
+            command_args.append(arg)
+
+    return command_args
+
+
+def format_command_args(args: Union[List[str], CommandArgs]) -> str:
+    """
+    Format command arguments for display.
+    """
+    # For HiddenText arguments, display the redacted form by calling str().
+    # Also, we don't apply str() to arguments that aren't HiddenText since
+    # this can trigger a UnicodeDecodeError in Python 2 if the argument
+    # has type unicode and includes a non-ascii character.  (The type
+    # checker doesn't ensure the annotations are correct in all cases.)
+    return " ".join(
+        shlex.quote(str(arg)) if isinstance(arg, HiddenText) else shlex.quote(arg)
+        for arg in args
+    )
+
+
+def reveal_command_args(args: Union[List[str], CommandArgs]) -> List[str]:
+    """
+    Return the arguments in their raw, unredacted form.
+    """
+    return [arg.secret if isinstance(arg, HiddenText) else arg for arg in args]
+
+
+def call_subprocess(
+    cmd: Union[List[str], CommandArgs],
+    show_stdout: bool = False,
+    cwd: Optional[str] = None,
+    on_returncode: 'Literal["raise", "warn", "ignore"]' = "raise",
+    extra_ok_returncodes: Optional[Iterable[int]] = None,
+    extra_environ: Optional[Mapping[str, Any]] = None,
+    unset_environ: Optional[Iterable[str]] = None,
+    spinner: Optional[SpinnerInterface] = None,
+    log_failed_cmd: Optional[bool] = True,
+    stdout_only: Optional[bool] = False,
+    *,
+    command_desc: str,
+) -> str:
+    """
+    Args:
+      show_stdout: if true, use INFO to log the subprocess's stderr and
+        stdout streams.  Otherwise, use DEBUG.  Defaults to False.
+      extra_ok_returncodes: an iterable of integer return codes that are
+        acceptable, in addition to 0. Defaults to None, which means [].
+      unset_environ: an iterable of environment variable names to unset
+        prior to calling subprocess.Popen().
+      log_failed_cmd: if false, failed commands are not logged, only raised.
+      stdout_only: if true, return only stdout, else return both. When true,
+        logging of both stdout and stderr occurs when the subprocess has
+        terminated, else logging occurs as subprocess output is produced.
+    """
+    if extra_ok_returncodes is None:
+        extra_ok_returncodes = []
+    if unset_environ is None:
+        unset_environ = []
+    # Most places in pip use show_stdout=False. What this means is--
+    #
+    # - We connect the child's output (combined stderr and stdout) to a
+    #   single pipe, which we read.
+    # - We log this output to stderr at DEBUG level as it is received.
+    # - If DEBUG logging isn't enabled (e.g. if --verbose logging wasn't
+    #   requested), then we show a spinner so the user can still see the
+    #   subprocess is in progress.
+    # - If the subprocess exits with an error, we log the output to stderr
+    #   at ERROR level if it hasn't already been displayed to the console
+    #   (e.g. if --verbose logging wasn't enabled).  This way we don't log
+    #   the output to the console twice.
+    #
+    # If show_stdout=True, then the above is still done, but with DEBUG
+    # replaced by INFO.
+    if show_stdout:
+        # Then log the subprocess output at INFO level.
+        log_subprocess: Callable[..., None] = subprocess_logger.info
+        used_level = logging.INFO
+    else:
+        # Then log the subprocess output using VERBOSE.  This also ensures
+        # it will be logged to the log file (aka user_log), if enabled.
+        log_subprocess = subprocess_logger.verbose
+        used_level = VERBOSE
+
+    # Whether the subprocess will be visible in the console.
+    showing_subprocess = subprocess_logger.getEffectiveLevel() <= used_level
+
+    # Only use the spinner if we're not showing the subprocess output
+    # and we have a spinner.
+    use_spinner = not showing_subprocess and spinner is not None
+
+    log_subprocess("Running command %s", command_desc)
+    env = os.environ.copy()
+    if extra_environ:
+        env.update(extra_environ)
+    for name in unset_environ:
+        env.pop(name, None)
+    try:
+        proc = subprocess.Popen(
+            # Convert HiddenText objects to the underlying str.
+            reveal_command_args(cmd),
+            stdin=subprocess.PIPE,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.STDOUT if not stdout_only else subprocess.PIPE,
+            cwd=cwd,
+            env=env,
+            errors="backslashreplace",
+        )
+    except Exception as exc:
+        if log_failed_cmd:
+            subprocess_logger.critical(
+                "Error %s while executing command %s",
+                exc,
+                command_desc,
+            )
+        raise
+    all_output = []
+    if not stdout_only:
+        assert proc.stdout
+        assert proc.stdin
+        proc.stdin.close()
+        # In this mode, stdout and stderr are in the same pipe.
+        while True:
+            line: str = proc.stdout.readline()
+            if not line:
+                break
+            line = line.rstrip()
+            all_output.append(line + "\n")
+
+            # Show the line immediately.
+            log_subprocess(line)
+            # Update the spinner.
+            if use_spinner:
+                assert spinner
+                spinner.spin()
+        try:
+            proc.wait()
+        finally:
+            if proc.stdout:
+                proc.stdout.close()
+        output = "".join(all_output)
+    else:
+        # In this mode, stdout and stderr are in different pipes.
+        # We must use communicate() which is the only safe way to read both.
+        out, err = proc.communicate()
+        # log line by line to preserve pip log indenting
+        for out_line in out.splitlines():
+            log_subprocess(out_line)
+        all_output.append(out)
+        for err_line in err.splitlines():
+            log_subprocess(err_line)
+        all_output.append(err)
+        output = out
+
+    proc_had_error = proc.returncode and proc.returncode not in extra_ok_returncodes
+    if use_spinner:
+        assert spinner
+        if proc_had_error:
+            spinner.finish("error")
+        else:
+            spinner.finish("done")
+    if proc_had_error:
+        if on_returncode == "raise":
+            error = InstallationSubprocessError(
+                command_description=command_desc,
+                exit_code=proc.returncode,
+                output_lines=all_output if not showing_subprocess else None,
+            )
+            if log_failed_cmd:
+                subprocess_logger.error("[present-rich] %s", error)
+                subprocess_logger.verbose(
+                    "[bold magenta]full command[/]: [blue]%s[/]",
+                    escape(format_command_args(cmd)),
+                    extra={"markup": True},
+                )
+                subprocess_logger.verbose(
+                    "[bold magenta]cwd[/]: %s",
+                    escape(cwd or "[inherit]"),
+                    extra={"markup": True},
+                )
+
+            raise error
+        elif on_returncode == "warn":
+            subprocess_logger.warning(
+                'Command "%s" had error code %s in %s',
+                command_desc,
+                proc.returncode,
+                cwd,
+            )
+        elif on_returncode == "ignore":
+            pass
+        else:
+            raise ValueError(f"Invalid value: on_returncode={on_returncode!r}")
+    return output
+
+
+def runner_with_spinner_message(message: str) -> Callable[..., None]:
+    """Provide a subprocess_runner that shows a spinner message.
+
+    Intended for use with for BuildBackendHookCaller. Thus, the runner has
+    an API that matches what's expected by BuildBackendHookCaller.subprocess_runner.
+    """
+
+    def runner(
+        cmd: List[str],
+        cwd: Optional[str] = None,
+        extra_environ: Optional[Mapping[str, Any]] = None,
+    ) -> None:
+        with open_spinner(message) as spinner:
+            call_subprocess(
+                cmd,
+                command_desc=message,
+                cwd=cwd,
+                extra_environ=extra_environ,
+                spinner=spinner,
+            )
+
+    return runner
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/temp_dir.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/temp_dir.py
new file mode 100644
index 0000000000000000000000000000000000000000..8ee8a1cb18017880cd0bebd66bc2cec5702118c6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/temp_dir.py
@@ -0,0 +1,246 @@
+import errno
+import itertools
+import logging
+import os.path
+import tempfile
+from contextlib import ExitStack, contextmanager
+from typing import Any, Dict, Generator, Optional, TypeVar, Union
+
+from pip._internal.utils.misc import enum, rmtree
+
+logger = logging.getLogger(__name__)
+
+_T = TypeVar("_T", bound="TempDirectory")
+
+
+# Kinds of temporary directories. Only needed for ones that are
+# globally-managed.
+tempdir_kinds = enum(
+    BUILD_ENV="build-env",
+    EPHEM_WHEEL_CACHE="ephem-wheel-cache",
+    REQ_BUILD="req-build",
+)
+
+
+_tempdir_manager: Optional[ExitStack] = None
+
+
+@contextmanager
+def global_tempdir_manager() -> Generator[None, None, None]:
+    global _tempdir_manager
+    with ExitStack() as stack:
+        old_tempdir_manager, _tempdir_manager = _tempdir_manager, stack
+        try:
+            yield
+        finally:
+            _tempdir_manager = old_tempdir_manager
+
+
+class TempDirectoryTypeRegistry:
+    """Manages temp directory behavior"""
+
+    def __init__(self) -> None:
+        self._should_delete: Dict[str, bool] = {}
+
+    def set_delete(self, kind: str, value: bool) -> None:
+        """Indicate whether a TempDirectory of the given kind should be
+        auto-deleted.
+        """
+        self._should_delete[kind] = value
+
+    def get_delete(self, kind: str) -> bool:
+        """Get configured auto-delete flag for a given TempDirectory type,
+        default True.
+        """
+        return self._should_delete.get(kind, True)
+
+
+_tempdir_registry: Optional[TempDirectoryTypeRegistry] = None
+
+
+@contextmanager
+def tempdir_registry() -> Generator[TempDirectoryTypeRegistry, None, None]:
+    """Provides a scoped global tempdir registry that can be used to dictate
+    whether directories should be deleted.
+    """
+    global _tempdir_registry
+    old_tempdir_registry = _tempdir_registry
+    _tempdir_registry = TempDirectoryTypeRegistry()
+    try:
+        yield _tempdir_registry
+    finally:
+        _tempdir_registry = old_tempdir_registry
+
+
+class _Default:
+    pass
+
+
+_default = _Default()
+
+
+class TempDirectory:
+    """Helper class that owns and cleans up a temporary directory.
+
+    This class can be used as a context manager or as an OO representation of a
+    temporary directory.
+
+    Attributes:
+        path
+            Location to the created temporary directory
+        delete
+            Whether the directory should be deleted when exiting
+            (when used as a contextmanager)
+
+    Methods:
+        cleanup()
+            Deletes the temporary directory
+
+    When used as a context manager, if the delete attribute is True, on
+    exiting the context the temporary directory is deleted.
+    """
+
+    def __init__(
+        self,
+        path: Optional[str] = None,
+        delete: Union[bool, None, _Default] = _default,
+        kind: str = "temp",
+        globally_managed: bool = False,
+    ):
+        super().__init__()
+
+        if delete is _default:
+            if path is not None:
+                # If we were given an explicit directory, resolve delete option
+                # now.
+                delete = False
+            else:
+                # Otherwise, we wait until cleanup and see what
+                # tempdir_registry says.
+                delete = None
+
+        # The only time we specify path is in for editables where it
+        # is the value of the --src option.
+        if path is None:
+            path = self._create(kind)
+
+        self._path = path
+        self._deleted = False
+        self.delete = delete
+        self.kind = kind
+
+        if globally_managed:
+            assert _tempdir_manager is not None
+            _tempdir_manager.enter_context(self)
+
+    @property
+    def path(self) -> str:
+        assert not self._deleted, f"Attempted to access deleted path: {self._path}"
+        return self._path
+
+    def __repr__(self) -> str:
+        return f"<{self.__class__.__name__} {self.path!r}>"
+
+    def __enter__(self: _T) -> _T:
+        return self
+
+    def __exit__(self, exc: Any, value: Any, tb: Any) -> None:
+        if self.delete is not None:
+            delete = self.delete
+        elif _tempdir_registry:
+            delete = _tempdir_registry.get_delete(self.kind)
+        else:
+            delete = True
+
+        if delete:
+            self.cleanup()
+
+    def _create(self, kind: str) -> str:
+        """Create a temporary directory and store its path in self.path"""
+        # We realpath here because some systems have their default tmpdir
+        # symlinked to another directory.  This tends to confuse build
+        # scripts, so we canonicalize the path by traversing potential
+        # symlinks here.
+        path = os.path.realpath(tempfile.mkdtemp(prefix=f"pip-{kind}-"))
+        logger.debug("Created temporary directory: %s", path)
+        return path
+
+    def cleanup(self) -> None:
+        """Remove the temporary directory created and reset state"""
+        self._deleted = True
+        if not os.path.exists(self._path):
+            return
+        rmtree(self._path)
+
+
+class AdjacentTempDirectory(TempDirectory):
+    """Helper class that creates a temporary directory adjacent to a real one.
+
+    Attributes:
+        original
+            The original directory to create a temp directory for.
+        path
+            After calling create() or entering, contains the full
+            path to the temporary directory.
+        delete
+            Whether the directory should be deleted when exiting
+            (when used as a contextmanager)
+
+    """
+
+    # The characters that may be used to name the temp directory
+    # We always prepend a ~ and then rotate through these until
+    # a usable name is found.
+    # pkg_resources raises a different error for .dist-info folder
+    # with leading '-' and invalid metadata
+    LEADING_CHARS = "-~.=%0123456789"
+
+    def __init__(self, original: str, delete: Optional[bool] = None) -> None:
+        self.original = original.rstrip("/\\")
+        super().__init__(delete=delete)
+
+    @classmethod
+    def _generate_names(cls, name: str) -> Generator[str, None, None]:
+        """Generates a series of temporary names.
+
+        The algorithm replaces the leading characters in the name
+        with ones that are valid filesystem characters, but are not
+        valid package names (for both Python and pip definitions of
+        package).
+        """
+        for i in range(1, len(name)):
+            for candidate in itertools.combinations_with_replacement(
+                cls.LEADING_CHARS, i - 1
+            ):
+                new_name = "~" + "".join(candidate) + name[i:]
+                if new_name != name:
+                    yield new_name
+
+        # If we make it this far, we will have to make a longer name
+        for i in range(len(cls.LEADING_CHARS)):
+            for candidate in itertools.combinations_with_replacement(
+                cls.LEADING_CHARS, i
+            ):
+                new_name = "~" + "".join(candidate) + name
+                if new_name != name:
+                    yield new_name
+
+    def _create(self, kind: str) -> str:
+        root, name = os.path.split(self.original)
+        for candidate in self._generate_names(name):
+            path = os.path.join(root, candidate)
+            try:
+                os.mkdir(path)
+            except OSError as ex:
+                # Continue if the name exists already
+                if ex.errno != errno.EEXIST:
+                    raise
+            else:
+                path = os.path.realpath(path)
+                break
+        else:
+            # Final fallback on the default behavior.
+            path = os.path.realpath(tempfile.mkdtemp(prefix=f"pip-{kind}-"))
+
+        logger.debug("Created temporary directory: %s", path)
+        return path
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/unpacking.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/unpacking.py
new file mode 100644
index 0000000000000000000000000000000000000000..78b5c13ced3d0a429b6d292e2b0b985d50909942
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/unpacking.py
@@ -0,0 +1,257 @@
+"""Utilities related archives.
+"""
+
+import logging
+import os
+import shutil
+import stat
+import tarfile
+import zipfile
+from typing import Iterable, List, Optional
+from zipfile import ZipInfo
+
+from pip._internal.exceptions import InstallationError
+from pip._internal.utils.filetypes import (
+    BZ2_EXTENSIONS,
+    TAR_EXTENSIONS,
+    XZ_EXTENSIONS,
+    ZIP_EXTENSIONS,
+)
+from pip._internal.utils.misc import ensure_dir
+
+logger = logging.getLogger(__name__)
+
+
+SUPPORTED_EXTENSIONS = ZIP_EXTENSIONS + TAR_EXTENSIONS
+
+try:
+    import bz2  # noqa
+
+    SUPPORTED_EXTENSIONS += BZ2_EXTENSIONS
+except ImportError:
+    logger.debug("bz2 module is not available")
+
+try:
+    # Only for Python 3.3+
+    import lzma  # noqa
+
+    SUPPORTED_EXTENSIONS += XZ_EXTENSIONS
+except ImportError:
+    logger.debug("lzma module is not available")
+
+
+def current_umask() -> int:
+    """Get the current umask which involves having to set it temporarily."""
+    mask = os.umask(0)
+    os.umask(mask)
+    return mask
+
+
+def split_leading_dir(path: str) -> List[str]:
+    path = path.lstrip("/").lstrip("\\")
+    if "/" in path and (
+        ("\\" in path and path.find("/") < path.find("\\")) or "\\" not in path
+    ):
+        return path.split("/", 1)
+    elif "\\" in path:
+        return path.split("\\", 1)
+    else:
+        return [path, ""]
+
+
+def has_leading_dir(paths: Iterable[str]) -> bool:
+    """Returns true if all the paths have the same leading path name
+    (i.e., everything is in one subdirectory in an archive)"""
+    common_prefix = None
+    for path in paths:
+        prefix, rest = split_leading_dir(path)
+        if not prefix:
+            return False
+        elif common_prefix is None:
+            common_prefix = prefix
+        elif prefix != common_prefix:
+            return False
+    return True
+
+
+def is_within_directory(directory: str, target: str) -> bool:
+    """
+    Return true if the absolute path of target is within the directory
+    """
+    abs_directory = os.path.abspath(directory)
+    abs_target = os.path.abspath(target)
+
+    prefix = os.path.commonprefix([abs_directory, abs_target])
+    return prefix == abs_directory
+
+
+def set_extracted_file_to_default_mode_plus_executable(path: str) -> None:
+    """
+    Make file present at path have execute for user/group/world
+    (chmod +x) is no-op on windows per python docs
+    """
+    os.chmod(path, (0o777 & ~current_umask() | 0o111))
+
+
+def zip_item_is_executable(info: ZipInfo) -> bool:
+    mode = info.external_attr >> 16
+    # if mode and regular file and any execute permissions for
+    # user/group/world?
+    return bool(mode and stat.S_ISREG(mode) and mode & 0o111)
+
+
+def unzip_file(filename: str, location: str, flatten: bool = True) -> None:
+    """
+    Unzip the file (with path `filename`) to the destination `location`.  All
+    files are written based on system defaults and umask (i.e. permissions are
+    not preserved), except that regular file members with any execute
+    permissions (user, group, or world) have "chmod +x" applied after being
+    written. Note that for windows, any execute changes using os.chmod are
+    no-ops per the python docs.
+    """
+    ensure_dir(location)
+    zipfp = open(filename, "rb")
+    try:
+        zip = zipfile.ZipFile(zipfp, allowZip64=True)
+        leading = has_leading_dir(zip.namelist()) and flatten
+        for info in zip.infolist():
+            name = info.filename
+            fn = name
+            if leading:
+                fn = split_leading_dir(name)[1]
+            fn = os.path.join(location, fn)
+            dir = os.path.dirname(fn)
+            if not is_within_directory(location, fn):
+                message = (
+                    "The zip file ({}) has a file ({}) trying to install "
+                    "outside target directory ({})"
+                )
+                raise InstallationError(message.format(filename, fn, location))
+            if fn.endswith("/") or fn.endswith("\\"):
+                # A directory
+                ensure_dir(fn)
+            else:
+                ensure_dir(dir)
+                # Don't use read() to avoid allocating an arbitrarily large
+                # chunk of memory for the file's content
+                fp = zip.open(name)
+                try:
+                    with open(fn, "wb") as destfp:
+                        shutil.copyfileobj(fp, destfp)
+                finally:
+                    fp.close()
+                    if zip_item_is_executable(info):
+                        set_extracted_file_to_default_mode_plus_executable(fn)
+    finally:
+        zipfp.close()
+
+
+def untar_file(filename: str, location: str) -> None:
+    """
+    Untar the file (with path `filename`) to the destination `location`.
+    All files are written based on system defaults and umask (i.e. permissions
+    are not preserved), except that regular file members with any execute
+    permissions (user, group, or world) have "chmod +x" applied after being
+    written.  Note that for windows, any execute changes using os.chmod are
+    no-ops per the python docs.
+    """
+    ensure_dir(location)
+    if filename.lower().endswith(".gz") or filename.lower().endswith(".tgz"):
+        mode = "r:gz"
+    elif filename.lower().endswith(BZ2_EXTENSIONS):
+        mode = "r:bz2"
+    elif filename.lower().endswith(XZ_EXTENSIONS):
+        mode = "r:xz"
+    elif filename.lower().endswith(".tar"):
+        mode = "r"
+    else:
+        logger.warning(
+            "Cannot determine compression type for file %s",
+            filename,
+        )
+        mode = "r:*"
+    tar = tarfile.open(filename, mode, encoding="utf-8")
+    try:
+        leading = has_leading_dir([member.name for member in tar.getmembers()])
+        for member in tar.getmembers():
+            fn = member.name
+            if leading:
+                fn = split_leading_dir(fn)[1]
+            path = os.path.join(location, fn)
+            if not is_within_directory(location, path):
+                message = (
+                    "The tar file ({}) has a file ({}) trying to install "
+                    "outside target directory ({})"
+                )
+                raise InstallationError(message.format(filename, path, location))
+            if member.isdir():
+                ensure_dir(path)
+            elif member.issym():
+                try:
+                    tar._extract_member(member, path)
+                except Exception as exc:
+                    # Some corrupt tar files seem to produce this
+                    # (specifically bad symlinks)
+                    logger.warning(
+                        "In the tar file %s the member %s is invalid: %s",
+                        filename,
+                        member.name,
+                        exc,
+                    )
+                    continue
+            else:
+                try:
+                    fp = tar.extractfile(member)
+                except (KeyError, AttributeError) as exc:
+                    # Some corrupt tar files seem to produce this
+                    # (specifically bad symlinks)
+                    logger.warning(
+                        "In the tar file %s the member %s is invalid: %s",
+                        filename,
+                        member.name,
+                        exc,
+                    )
+                    continue
+                ensure_dir(os.path.dirname(path))
+                assert fp is not None
+                with open(path, "wb") as destfp:
+                    shutil.copyfileobj(fp, destfp)
+                fp.close()
+                # Update the timestamp (useful for cython compiled files)
+                tar.utime(member, path)
+                # member have any execute permissions for user/group/world?
+                if member.mode & 0o111:
+                    set_extracted_file_to_default_mode_plus_executable(path)
+    finally:
+        tar.close()
+
+
+def unpack_file(
+    filename: str,
+    location: str,
+    content_type: Optional[str] = None,
+) -> None:
+    filename = os.path.realpath(filename)
+    if (
+        content_type == "application/zip"
+        or filename.lower().endswith(ZIP_EXTENSIONS)
+        or zipfile.is_zipfile(filename)
+    ):
+        unzip_file(filename, location, flatten=not filename.endswith(".whl"))
+    elif (
+        content_type == "application/x-gzip"
+        or tarfile.is_tarfile(filename)
+        or filename.lower().endswith(TAR_EXTENSIONS + BZ2_EXTENSIONS + XZ_EXTENSIONS)
+    ):
+        untar_file(filename, location)
+    else:
+        # FIXME: handle?
+        # FIXME: magic signatures?
+        logger.critical(
+            "Cannot unpack file %s (downloaded from %s, content-type: %s); "
+            "cannot detect archive format",
+            filename,
+            location,
+            content_type,
+        )
+        raise InstallationError(f"Cannot determine archive format of {location}")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/urls.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/urls.py
new file mode 100644
index 0000000000000000000000000000000000000000..6ba2e04f350792e2c0021cf7ba7f40b25dc6cd51
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/urls.py
@@ -0,0 +1,62 @@
+import os
+import string
+import urllib.parse
+import urllib.request
+from typing import Optional
+
+from .compat import WINDOWS
+
+
+def get_url_scheme(url: str) -> Optional[str]:
+    if ":" not in url:
+        return None
+    return url.split(":", 1)[0].lower()
+
+
+def path_to_url(path: str) -> str:
+    """
+    Convert a path to a file: URL.  The path will be made absolute and have
+    quoted path parts.
+    """
+    path = os.path.normpath(os.path.abspath(path))
+    url = urllib.parse.urljoin("file:", urllib.request.pathname2url(path))
+    return url
+
+
+def url_to_path(url: str) -> str:
+    """
+    Convert a file: URL to a path.
+    """
+    assert url.startswith(
+        "file:"
+    ), f"You can only turn file: urls into filenames (not {url!r})"
+
+    _, netloc, path, _, _ = urllib.parse.urlsplit(url)
+
+    if not netloc or netloc == "localhost":
+        # According to RFC 8089, same as empty authority.
+        netloc = ""
+    elif WINDOWS:
+        # If we have a UNC path, prepend UNC share notation.
+        netloc = "\\\\" + netloc
+    else:
+        raise ValueError(
+            f"non-local file URIs are not supported on this platform: {url!r}"
+        )
+
+    path = urllib.request.url2pathname(netloc + path)
+
+    # On Windows, urlsplit parses the path as something like "/C:/Users/foo".
+    # This creates issues for path-related functions like io.open(), so we try
+    # to detect and strip the leading slash.
+    if (
+        WINDOWS
+        and not netloc  # Not UNC.
+        and len(path) >= 3
+        and path[0] == "/"  # Leading slash to strip.
+        and path[1] in string.ascii_letters  # Drive letter.
+        and path[2:4] in (":", ":/")  # Colon + end of string, or colon + absolute path.
+    ):
+        path = path[1:]
+
+    return path
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/virtualenv.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/virtualenv.py
new file mode 100644
index 0000000000000000000000000000000000000000..882e36f5c1de19a8200000c216cf80119b37c96d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/virtualenv.py
@@ -0,0 +1,104 @@
+import logging
+import os
+import re
+import site
+import sys
+from typing import List, Optional
+
+logger = logging.getLogger(__name__)
+_INCLUDE_SYSTEM_SITE_PACKAGES_REGEX = re.compile(
+    r"include-system-site-packages\s*=\s*(?Ptrue|false)"
+)
+
+
+def _running_under_venv() -> bool:
+    """Checks if sys.base_prefix and sys.prefix match.
+
+    This handles PEP 405 compliant virtual environments.
+    """
+    return sys.prefix != getattr(sys, "base_prefix", sys.prefix)
+
+
+def _running_under_legacy_virtualenv() -> bool:
+    """Checks if sys.real_prefix is set.
+
+    This handles virtual environments created with pypa's virtualenv.
+    """
+    # pypa/virtualenv case
+    return hasattr(sys, "real_prefix")
+
+
+def running_under_virtualenv() -> bool:
+    """True if we're running inside a virtual environment, False otherwise."""
+    return _running_under_venv() or _running_under_legacy_virtualenv()
+
+
+def _get_pyvenv_cfg_lines() -> Optional[List[str]]:
+    """Reads {sys.prefix}/pyvenv.cfg and returns its contents as list of lines
+
+    Returns None, if it could not read/access the file.
+    """
+    pyvenv_cfg_file = os.path.join(sys.prefix, "pyvenv.cfg")
+    try:
+        # Although PEP 405 does not specify, the built-in venv module always
+        # writes with UTF-8. (pypa/pip#8717)
+        with open(pyvenv_cfg_file, encoding="utf-8") as f:
+            return f.read().splitlines()  # avoids trailing newlines
+    except OSError:
+        return None
+
+
+def _no_global_under_venv() -> bool:
+    """Check `{sys.prefix}/pyvenv.cfg` for system site-packages inclusion
+
+    PEP 405 specifies that when system site-packages are not supposed to be
+    visible from a virtual environment, `pyvenv.cfg` must contain the following
+    line:
+
+        include-system-site-packages = false
+
+    Additionally, log a warning if accessing the file fails.
+    """
+    cfg_lines = _get_pyvenv_cfg_lines()
+    if cfg_lines is None:
+        # We're not in a "sane" venv, so assume there is no system
+        # site-packages access (since that's PEP 405's default state).
+        logger.warning(
+            "Could not access 'pyvenv.cfg' despite a virtual environment "
+            "being active. Assuming global site-packages is not accessible "
+            "in this environment."
+        )
+        return True
+
+    for line in cfg_lines:
+        match = _INCLUDE_SYSTEM_SITE_PACKAGES_REGEX.match(line)
+        if match is not None and match.group("value") == "false":
+            return True
+    return False
+
+
+def _no_global_under_legacy_virtualenv() -> bool:
+    """Check if "no-global-site-packages.txt" exists beside site.py
+
+    This mirrors logic in pypa/virtualenv for determining whether system
+    site-packages are visible in the virtual environment.
+    """
+    site_mod_dir = os.path.dirname(os.path.abspath(site.__file__))
+    no_global_site_packages_file = os.path.join(
+        site_mod_dir,
+        "no-global-site-packages.txt",
+    )
+    return os.path.exists(no_global_site_packages_file)
+
+
+def virtualenv_no_global() -> bool:
+    """Returns a boolean, whether running in venv with no system site-packages."""
+    # PEP 405 compliance needs to be checked first since virtualenv >=20 would
+    # return True for both checks, but is only able to use the PEP 405 config.
+    if _running_under_venv():
+        return _no_global_under_venv()
+
+    if _running_under_legacy_virtualenv():
+        return _no_global_under_legacy_virtualenv()
+
+    return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..e5e3f34ed81453ce759c6ade8b2def733e9063e2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/utils/wheel.py
@@ -0,0 +1,136 @@
+"""Support functions for working with wheel files.
+"""
+
+import logging
+from email.message import Message
+from email.parser import Parser
+from typing import Tuple
+from zipfile import BadZipFile, ZipFile
+
+from pip._vendor.packaging.utils import canonicalize_name
+
+from pip._internal.exceptions import UnsupportedWheel
+
+VERSION_COMPATIBLE = (1, 0)
+
+
+logger = logging.getLogger(__name__)
+
+
+def parse_wheel(wheel_zip: ZipFile, name: str) -> Tuple[str, Message]:
+    """Extract information from the provided wheel, ensuring it meets basic
+    standards.
+
+    Returns the name of the .dist-info directory and the parsed WHEEL metadata.
+    """
+    try:
+        info_dir = wheel_dist_info_dir(wheel_zip, name)
+        metadata = wheel_metadata(wheel_zip, info_dir)
+        version = wheel_version(metadata)
+    except UnsupportedWheel as e:
+        raise UnsupportedWheel("{} has an invalid wheel, {}".format(name, str(e)))
+
+    check_compatibility(version, name)
+
+    return info_dir, metadata
+
+
+def wheel_dist_info_dir(source: ZipFile, name: str) -> str:
+    """Returns the name of the contained .dist-info directory.
+
+    Raises AssertionError or UnsupportedWheel if not found, >1 found, or
+    it doesn't match the provided name.
+    """
+    # Zip file path separators must be /
+    subdirs = {p.split("/", 1)[0] for p in source.namelist()}
+
+    info_dirs = [s for s in subdirs if s.endswith(".dist-info")]
+
+    if not info_dirs:
+        raise UnsupportedWheel(".dist-info directory not found")
+
+    if len(info_dirs) > 1:
+        raise UnsupportedWheel(
+            "multiple .dist-info directories found: {}".format(", ".join(info_dirs))
+        )
+
+    info_dir = info_dirs[0]
+
+    info_dir_name = canonicalize_name(info_dir)
+    canonical_name = canonicalize_name(name)
+    if not info_dir_name.startswith(canonical_name):
+        raise UnsupportedWheel(
+            ".dist-info directory {!r} does not start with {!r}".format(
+                info_dir, canonical_name
+            )
+        )
+
+    return info_dir
+
+
+def read_wheel_metadata_file(source: ZipFile, path: str) -> bytes:
+    try:
+        return source.read(path)
+        # BadZipFile for general corruption, KeyError for missing entry,
+        # and RuntimeError for password-protected files
+    except (BadZipFile, KeyError, RuntimeError) as e:
+        raise UnsupportedWheel(f"could not read {path!r} file: {e!r}")
+
+
+def wheel_metadata(source: ZipFile, dist_info_dir: str) -> Message:
+    """Return the WHEEL metadata of an extracted wheel, if possible.
+    Otherwise, raise UnsupportedWheel.
+    """
+    path = f"{dist_info_dir}/WHEEL"
+    # Zip file path separators must be /
+    wheel_contents = read_wheel_metadata_file(source, path)
+
+    try:
+        wheel_text = wheel_contents.decode()
+    except UnicodeDecodeError as e:
+        raise UnsupportedWheel(f"error decoding {path!r}: {e!r}")
+
+    # FeedParser (used by Parser) does not raise any exceptions. The returned
+    # message may have .defects populated, but for backwards-compatibility we
+    # currently ignore them.
+    return Parser().parsestr(wheel_text)
+
+
+def wheel_version(wheel_data: Message) -> Tuple[int, ...]:
+    """Given WHEEL metadata, return the parsed Wheel-Version.
+    Otherwise, raise UnsupportedWheel.
+    """
+    version_text = wheel_data["Wheel-Version"]
+    if version_text is None:
+        raise UnsupportedWheel("WHEEL is missing Wheel-Version")
+
+    version = version_text.strip()
+
+    try:
+        return tuple(map(int, version.split(".")))
+    except ValueError:
+        raise UnsupportedWheel(f"invalid Wheel-Version: {version!r}")
+
+
+def check_compatibility(version: Tuple[int, ...], name: str) -> None:
+    """Raises errors or warns if called with an incompatible Wheel-Version.
+
+    pip should refuse to install a Wheel-Version that's a major series
+    ahead of what it's compatible with (e.g 2.0 > 1.1); and warn when
+    installing a version only minor version ahead (e.g 1.2 > 1.1).
+
+    version: a 2-tuple representing a Wheel-Version (Major, Minor)
+    name: name of wheel or package to raise exception about
+
+    :raises UnsupportedWheel: when an incompatible Wheel-Version is given
+    """
+    if version[0] > VERSION_COMPATIBLE[0]:
+        raise UnsupportedWheel(
+            "{}'s Wheel-Version ({}) is not compatible with this version "
+            "of pip".format(name, ".".join(map(str, version)))
+        )
+    elif version > VERSION_COMPATIBLE:
+        logger.warning(
+            "Installing from a newer Wheel-Version (%s)",
+            ".".join(map(str, version)),
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6beddbe6d24d2949dc89ed07abfebd59d8b63b9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/__init__.py
@@ -0,0 +1,15 @@
+# Expose a limited set of classes and functions so callers outside of
+# the vcs package don't need to import deeper than `pip._internal.vcs`.
+# (The test directory may still need to import from a vcs sub-package.)
+# Import all vcs modules to register each VCS in the VcsSupport object.
+import pip._internal.vcs.bazaar
+import pip._internal.vcs.git
+import pip._internal.vcs.mercurial
+import pip._internal.vcs.subversion  # noqa: F401
+from pip._internal.vcs.versioncontrol import (  # noqa: F401
+    RemoteNotFoundError,
+    RemoteNotValidError,
+    is_url,
+    make_vcs_requirement_url,
+    vcs,
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/bazaar.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/bazaar.py
new file mode 100644
index 0000000000000000000000000000000000000000..20a17ed09272a09a5b3c0bfbd0e6c43f78db4c1e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/bazaar.py
@@ -0,0 +1,112 @@
+import logging
+from typing import List, Optional, Tuple
+
+from pip._internal.utils.misc import HiddenText, display_path
+from pip._internal.utils.subprocess import make_command
+from pip._internal.utils.urls import path_to_url
+from pip._internal.vcs.versioncontrol import (
+    AuthInfo,
+    RemoteNotFoundError,
+    RevOptions,
+    VersionControl,
+    vcs,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class Bazaar(VersionControl):
+    name = "bzr"
+    dirname = ".bzr"
+    repo_name = "branch"
+    schemes = (
+        "bzr+http",
+        "bzr+https",
+        "bzr+ssh",
+        "bzr+sftp",
+        "bzr+ftp",
+        "bzr+lp",
+        "bzr+file",
+    )
+
+    @staticmethod
+    def get_base_rev_args(rev: str) -> List[str]:
+        return ["-r", rev]
+
+    def fetch_new(
+        self, dest: str, url: HiddenText, rev_options: RevOptions, verbosity: int
+    ) -> None:
+        rev_display = rev_options.to_display()
+        logger.info(
+            "Checking out %s%s to %s",
+            url,
+            rev_display,
+            display_path(dest),
+        )
+        if verbosity <= 0:
+            flag = "--quiet"
+        elif verbosity == 1:
+            flag = ""
+        else:
+            flag = f"-{'v'*verbosity}"
+        cmd_args = make_command(
+            "checkout", "--lightweight", flag, rev_options.to_args(), url, dest
+        )
+        self.run_command(cmd_args)
+
+    def switch(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        self.run_command(make_command("switch", url), cwd=dest)
+
+    def update(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        output = self.run_command(
+            make_command("info"), show_stdout=False, stdout_only=True, cwd=dest
+        )
+        if output.startswith("Standalone "):
+            # Older versions of pip used to create standalone branches.
+            # Convert the standalone branch to a checkout by calling "bzr bind".
+            cmd_args = make_command("bind", "-q", url)
+            self.run_command(cmd_args, cwd=dest)
+
+        cmd_args = make_command("update", "-q", rev_options.to_args())
+        self.run_command(cmd_args, cwd=dest)
+
+    @classmethod
+    def get_url_rev_and_auth(cls, url: str) -> Tuple[str, Optional[str], AuthInfo]:
+        # hotfix the URL scheme after removing bzr+ from bzr+ssh:// re-add it
+        url, rev, user_pass = super().get_url_rev_and_auth(url)
+        if url.startswith("ssh://"):
+            url = "bzr+" + url
+        return url, rev, user_pass
+
+    @classmethod
+    def get_remote_url(cls, location: str) -> str:
+        urls = cls.run_command(
+            ["info"], show_stdout=False, stdout_only=True, cwd=location
+        )
+        for line in urls.splitlines():
+            line = line.strip()
+            for x in ("checkout of branch: ", "parent branch: "):
+                if line.startswith(x):
+                    repo = line.split(x)[1]
+                    if cls._is_local_repository(repo):
+                        return path_to_url(repo)
+                    return repo
+        raise RemoteNotFoundError
+
+    @classmethod
+    def get_revision(cls, location: str) -> str:
+        revision = cls.run_command(
+            ["revno"],
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        )
+        return revision.splitlines()[-1]
+
+    @classmethod
+    def is_commit_id_equal(cls, dest: str, name: Optional[str]) -> bool:
+        """Always assume the versions don't match"""
+        return False
+
+
+vcs.register(Bazaar)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/git.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/git.py
new file mode 100644
index 0000000000000000000000000000000000000000..8d1d499376744954308bdf96f80e5b5a39a24195
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/git.py
@@ -0,0 +1,526 @@
+import logging
+import os.path
+import pathlib
+import re
+import urllib.parse
+import urllib.request
+from typing import List, Optional, Tuple
+
+from pip._internal.exceptions import BadCommand, InstallationError
+from pip._internal.utils.misc import HiddenText, display_path, hide_url
+from pip._internal.utils.subprocess import make_command
+from pip._internal.vcs.versioncontrol import (
+    AuthInfo,
+    RemoteNotFoundError,
+    RemoteNotValidError,
+    RevOptions,
+    VersionControl,
+    find_path_to_project_root_from_repo_root,
+    vcs,
+)
+
+urlsplit = urllib.parse.urlsplit
+urlunsplit = urllib.parse.urlunsplit
+
+
+logger = logging.getLogger(__name__)
+
+
+GIT_VERSION_REGEX = re.compile(
+    r"^git version "  # Prefix.
+    r"(\d+)"  # Major.
+    r"\.(\d+)"  # Dot, minor.
+    r"(?:\.(\d+))?"  # Optional dot, patch.
+    r".*$"  # Suffix, including any pre- and post-release segments we don't care about.
+)
+
+HASH_REGEX = re.compile("^[a-fA-F0-9]{40}$")
+
+# SCP (Secure copy protocol) shorthand. e.g. 'git@example.com:foo/bar.git'
+SCP_REGEX = re.compile(
+    r"""^
+    # Optional user, e.g. 'git@'
+    (\w+@)?
+    # Server, e.g. 'github.com'.
+    ([^/:]+):
+    # The server-side path. e.g. 'user/project.git'. Must start with an
+    # alphanumeric character so as not to be confusable with a Windows paths
+    # like 'C:/foo/bar' or 'C:\foo\bar'.
+    (\w[^:]*)
+    $""",
+    re.VERBOSE,
+)
+
+
+def looks_like_hash(sha: str) -> bool:
+    return bool(HASH_REGEX.match(sha))
+
+
+class Git(VersionControl):
+    name = "git"
+    dirname = ".git"
+    repo_name = "clone"
+    schemes = (
+        "git+http",
+        "git+https",
+        "git+ssh",
+        "git+git",
+        "git+file",
+    )
+    # Prevent the user's environment variables from interfering with pip:
+    # https://github.com/pypa/pip/issues/1130
+    unset_environ = ("GIT_DIR", "GIT_WORK_TREE")
+    default_arg_rev = "HEAD"
+
+    @staticmethod
+    def get_base_rev_args(rev: str) -> List[str]:
+        return [rev]
+
+    def is_immutable_rev_checkout(self, url: str, dest: str) -> bool:
+        _, rev_options = self.get_url_rev_options(hide_url(url))
+        if not rev_options.rev:
+            return False
+        if not self.is_commit_id_equal(dest, rev_options.rev):
+            # the current commit is different from rev,
+            # which means rev was something else than a commit hash
+            return False
+        # return False in the rare case rev is both a commit hash
+        # and a tag or a branch; we don't want to cache in that case
+        # because that branch/tag could point to something else in the future
+        is_tag_or_branch = bool(self.get_revision_sha(dest, rev_options.rev)[0])
+        return not is_tag_or_branch
+
+    def get_git_version(self) -> Tuple[int, ...]:
+        version = self.run_command(
+            ["version"],
+            command_desc="git version",
+            show_stdout=False,
+            stdout_only=True,
+        )
+        match = GIT_VERSION_REGEX.match(version)
+        if not match:
+            logger.warning("Can't parse git version: %s", version)
+            return ()
+        return tuple(int(c) for c in match.groups())
+
+    @classmethod
+    def get_current_branch(cls, location: str) -> Optional[str]:
+        """
+        Return the current branch, or None if HEAD isn't at a branch
+        (e.g. detached HEAD).
+        """
+        # git-symbolic-ref exits with empty stdout if "HEAD" is a detached
+        # HEAD rather than a symbolic ref.  In addition, the -q causes the
+        # command to exit with status code 1 instead of 128 in this case
+        # and to suppress the message to stderr.
+        args = ["symbolic-ref", "-q", "HEAD"]
+        output = cls.run_command(
+            args,
+            extra_ok_returncodes=(1,),
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        )
+        ref = output.strip()
+
+        if ref.startswith("refs/heads/"):
+            return ref[len("refs/heads/") :]
+
+        return None
+
+    @classmethod
+    def get_revision_sha(cls, dest: str, rev: str) -> Tuple[Optional[str], bool]:
+        """
+        Return (sha_or_none, is_branch), where sha_or_none is a commit hash
+        if the revision names a remote branch or tag, otherwise None.
+
+        Args:
+          dest: the repository directory.
+          rev: the revision name.
+        """
+        # Pass rev to pre-filter the list.
+        output = cls.run_command(
+            ["show-ref", rev],
+            cwd=dest,
+            show_stdout=False,
+            stdout_only=True,
+            on_returncode="ignore",
+        )
+        refs = {}
+        # NOTE: We do not use splitlines here since that would split on other
+        #       unicode separators, which can be maliciously used to install a
+        #       different revision.
+        for line in output.strip().split("\n"):
+            line = line.rstrip("\r")
+            if not line:
+                continue
+            try:
+                ref_sha, ref_name = line.split(" ", maxsplit=2)
+            except ValueError:
+                # Include the offending line to simplify troubleshooting if
+                # this error ever occurs.
+                raise ValueError(f"unexpected show-ref line: {line!r}")
+
+            refs[ref_name] = ref_sha
+
+        branch_ref = f"refs/remotes/origin/{rev}"
+        tag_ref = f"refs/tags/{rev}"
+
+        sha = refs.get(branch_ref)
+        if sha is not None:
+            return (sha, True)
+
+        sha = refs.get(tag_ref)
+
+        return (sha, False)
+
+    @classmethod
+    def _should_fetch(cls, dest: str, rev: str) -> bool:
+        """
+        Return true if rev is a ref or is a commit that we don't have locally.
+
+        Branches and tags are not considered in this method because they are
+        assumed to be always available locally (which is a normal outcome of
+        ``git clone`` and ``git fetch --tags``).
+        """
+        if rev.startswith("refs/"):
+            # Always fetch remote refs.
+            return True
+
+        if not looks_like_hash(rev):
+            # Git fetch would fail with abbreviated commits.
+            return False
+
+        if cls.has_commit(dest, rev):
+            # Don't fetch if we have the commit locally.
+            return False
+
+        return True
+
+    @classmethod
+    def resolve_revision(
+        cls, dest: str, url: HiddenText, rev_options: RevOptions
+    ) -> RevOptions:
+        """
+        Resolve a revision to a new RevOptions object with the SHA1 of the
+        branch, tag, or ref if found.
+
+        Args:
+          rev_options: a RevOptions object.
+        """
+        rev = rev_options.arg_rev
+        # The arg_rev property's implementation for Git ensures that the
+        # rev return value is always non-None.
+        assert rev is not None
+
+        sha, is_branch = cls.get_revision_sha(dest, rev)
+
+        if sha is not None:
+            rev_options = rev_options.make_new(sha)
+            rev_options.branch_name = rev if is_branch else None
+
+            return rev_options
+
+        # Do not show a warning for the common case of something that has
+        # the form of a Git commit hash.
+        if not looks_like_hash(rev):
+            logger.warning(
+                "Did not find branch or tag '%s', assuming revision or ref.",
+                rev,
+            )
+
+        if not cls._should_fetch(dest, rev):
+            return rev_options
+
+        # fetch the requested revision
+        cls.run_command(
+            make_command("fetch", "-q", url, rev_options.to_args()),
+            cwd=dest,
+        )
+        # Change the revision to the SHA of the ref we fetched
+        sha = cls.get_revision(dest, rev="FETCH_HEAD")
+        rev_options = rev_options.make_new(sha)
+
+        return rev_options
+
+    @classmethod
+    def is_commit_id_equal(cls, dest: str, name: Optional[str]) -> bool:
+        """
+        Return whether the current commit hash equals the given name.
+
+        Args:
+          dest: the repository directory.
+          name: a string name.
+        """
+        if not name:
+            # Then avoid an unnecessary subprocess call.
+            return False
+
+        return cls.get_revision(dest) == name
+
+    def fetch_new(
+        self, dest: str, url: HiddenText, rev_options: RevOptions, verbosity: int
+    ) -> None:
+        rev_display = rev_options.to_display()
+        logger.info("Cloning %s%s to %s", url, rev_display, display_path(dest))
+        if verbosity <= 0:
+            flags: Tuple[str, ...] = ("--quiet",)
+        elif verbosity == 1:
+            flags = ()
+        else:
+            flags = ("--verbose", "--progress")
+        if self.get_git_version() >= (2, 17):
+            # Git added support for partial clone in 2.17
+            # https://git-scm.com/docs/partial-clone
+            # Speeds up cloning by functioning without a complete copy of repository
+            self.run_command(
+                make_command(
+                    "clone",
+                    "--filter=blob:none",
+                    *flags,
+                    url,
+                    dest,
+                )
+            )
+        else:
+            self.run_command(make_command("clone", *flags, url, dest))
+
+        if rev_options.rev:
+            # Then a specific revision was requested.
+            rev_options = self.resolve_revision(dest, url, rev_options)
+            branch_name = getattr(rev_options, "branch_name", None)
+            logger.debug("Rev options %s, branch_name %s", rev_options, branch_name)
+            if branch_name is None:
+                # Only do a checkout if the current commit id doesn't match
+                # the requested revision.
+                if not self.is_commit_id_equal(dest, rev_options.rev):
+                    cmd_args = make_command(
+                        "checkout",
+                        "-q",
+                        rev_options.to_args(),
+                    )
+                    self.run_command(cmd_args, cwd=dest)
+            elif self.get_current_branch(dest) != branch_name:
+                # Then a specific branch was requested, and that branch
+                # is not yet checked out.
+                track_branch = f"origin/{branch_name}"
+                cmd_args = [
+                    "checkout",
+                    "-b",
+                    branch_name,
+                    "--track",
+                    track_branch,
+                ]
+                self.run_command(cmd_args, cwd=dest)
+        else:
+            sha = self.get_revision(dest)
+            rev_options = rev_options.make_new(sha)
+
+        logger.info("Resolved %s to commit %s", url, rev_options.rev)
+
+        #: repo may contain submodules
+        self.update_submodules(dest)
+
+    def switch(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        self.run_command(
+            make_command("config", "remote.origin.url", url),
+            cwd=dest,
+        )
+        cmd_args = make_command("checkout", "-q", rev_options.to_args())
+        self.run_command(cmd_args, cwd=dest)
+
+        self.update_submodules(dest)
+
+    def update(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        # First fetch changes from the default remote
+        if self.get_git_version() >= (1, 9):
+            # fetch tags in addition to everything else
+            self.run_command(["fetch", "-q", "--tags"], cwd=dest)
+        else:
+            self.run_command(["fetch", "-q"], cwd=dest)
+        # Then reset to wanted revision (maybe even origin/master)
+        rev_options = self.resolve_revision(dest, url, rev_options)
+        cmd_args = make_command("reset", "--hard", "-q", rev_options.to_args())
+        self.run_command(cmd_args, cwd=dest)
+        #: update submodules
+        self.update_submodules(dest)
+
+    @classmethod
+    def get_remote_url(cls, location: str) -> str:
+        """
+        Return URL of the first remote encountered.
+
+        Raises RemoteNotFoundError if the repository does not have a remote
+        url configured.
+        """
+        # We need to pass 1 for extra_ok_returncodes since the command
+        # exits with return code 1 if there are no matching lines.
+        stdout = cls.run_command(
+            ["config", "--get-regexp", r"remote\..*\.url"],
+            extra_ok_returncodes=(1,),
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        )
+        remotes = stdout.splitlines()
+        try:
+            found_remote = remotes[0]
+        except IndexError:
+            raise RemoteNotFoundError
+
+        for remote in remotes:
+            if remote.startswith("remote.origin.url "):
+                found_remote = remote
+                break
+        url = found_remote.split(" ")[1]
+        return cls._git_remote_to_pip_url(url.strip())
+
+    @staticmethod
+    def _git_remote_to_pip_url(url: str) -> str:
+        """
+        Convert a remote url from what git uses to what pip accepts.
+
+        There are 3 legal forms **url** may take:
+
+            1. A fully qualified url: ssh://git@example.com/foo/bar.git
+            2. A local project.git folder: /path/to/bare/repository.git
+            3. SCP shorthand for form 1: git@example.com:foo/bar.git
+
+        Form 1 is output as-is. Form 2 must be converted to URI and form 3 must
+        be converted to form 1.
+
+        See the corresponding test test_git_remote_url_to_pip() for examples of
+        sample inputs/outputs.
+        """
+        if re.match(r"\w+://", url):
+            # This is already valid. Pass it though as-is.
+            return url
+        if os.path.exists(url):
+            # A local bare remote (git clone --mirror).
+            # Needs a file:// prefix.
+            return pathlib.PurePath(url).as_uri()
+        scp_match = SCP_REGEX.match(url)
+        if scp_match:
+            # Add an ssh:// prefix and replace the ':' with a '/'.
+            return scp_match.expand(r"ssh://\1\2/\3")
+        # Otherwise, bail out.
+        raise RemoteNotValidError(url)
+
+    @classmethod
+    def has_commit(cls, location: str, rev: str) -> bool:
+        """
+        Check if rev is a commit that is available in the local repository.
+        """
+        try:
+            cls.run_command(
+                ["rev-parse", "-q", "--verify", "sha^" + rev],
+                cwd=location,
+                log_failed_cmd=False,
+            )
+        except InstallationError:
+            return False
+        else:
+            return True
+
+    @classmethod
+    def get_revision(cls, location: str, rev: Optional[str] = None) -> str:
+        if rev is None:
+            rev = "HEAD"
+        current_rev = cls.run_command(
+            ["rev-parse", rev],
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        )
+        return current_rev.strip()
+
+    @classmethod
+    def get_subdirectory(cls, location: str) -> Optional[str]:
+        """
+        Return the path to Python project root, relative to the repo root.
+        Return None if the project root is in the repo root.
+        """
+        # find the repo root
+        git_dir = cls.run_command(
+            ["rev-parse", "--git-dir"],
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        ).strip()
+        if not os.path.isabs(git_dir):
+            git_dir = os.path.join(location, git_dir)
+        repo_root = os.path.abspath(os.path.join(git_dir, ".."))
+        return find_path_to_project_root_from_repo_root(location, repo_root)
+
+    @classmethod
+    def get_url_rev_and_auth(cls, url: str) -> Tuple[str, Optional[str], AuthInfo]:
+        """
+        Prefixes stub URLs like 'user@hostname:user/repo.git' with 'ssh://'.
+        That's required because although they use SSH they sometimes don't
+        work with a ssh:// scheme (e.g. GitHub). But we need a scheme for
+        parsing. Hence we remove it again afterwards and return it as a stub.
+        """
+        # Works around an apparent Git bug
+        # (see https://article.gmane.org/gmane.comp.version-control.git/146500)
+        scheme, netloc, path, query, fragment = urlsplit(url)
+        if scheme.endswith("file"):
+            initial_slashes = path[: -len(path.lstrip("/"))]
+            newpath = initial_slashes + urllib.request.url2pathname(path).replace(
+                "\\", "/"
+            ).lstrip("/")
+            after_plus = scheme.find("+") + 1
+            url = scheme[:after_plus] + urlunsplit(
+                (scheme[after_plus:], netloc, newpath, query, fragment),
+            )
+
+        if "://" not in url:
+            assert "file:" not in url
+            url = url.replace("git+", "git+ssh://")
+            url, rev, user_pass = super().get_url_rev_and_auth(url)
+            url = url.replace("ssh://", "")
+        else:
+            url, rev, user_pass = super().get_url_rev_and_auth(url)
+
+        return url, rev, user_pass
+
+    @classmethod
+    def update_submodules(cls, location: str) -> None:
+        if not os.path.exists(os.path.join(location, ".gitmodules")):
+            return
+        cls.run_command(
+            ["submodule", "update", "--init", "--recursive", "-q"],
+            cwd=location,
+        )
+
+    @classmethod
+    def get_repository_root(cls, location: str) -> Optional[str]:
+        loc = super().get_repository_root(location)
+        if loc:
+            return loc
+        try:
+            r = cls.run_command(
+                ["rev-parse", "--show-toplevel"],
+                cwd=location,
+                show_stdout=False,
+                stdout_only=True,
+                on_returncode="raise",
+                log_failed_cmd=False,
+            )
+        except BadCommand:
+            logger.debug(
+                "could not determine if %s is under git control "
+                "because git is not available",
+                location,
+            )
+            return None
+        except InstallationError:
+            return None
+        return os.path.normpath(r.rstrip("\r\n"))
+
+    @staticmethod
+    def should_add_vcs_url_prefix(repo_url: str) -> bool:
+        """In either https or ssh form, requirements must be prefixed with git+."""
+        return True
+
+
+vcs.register(Git)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/mercurial.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/mercurial.py
new file mode 100644
index 0000000000000000000000000000000000000000..2a005e0aff2df95f01aff4706b48af5da0c81db1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/mercurial.py
@@ -0,0 +1,163 @@
+import configparser
+import logging
+import os
+from typing import List, Optional, Tuple
+
+from pip._internal.exceptions import BadCommand, InstallationError
+from pip._internal.utils.misc import HiddenText, display_path
+from pip._internal.utils.subprocess import make_command
+from pip._internal.utils.urls import path_to_url
+from pip._internal.vcs.versioncontrol import (
+    RevOptions,
+    VersionControl,
+    find_path_to_project_root_from_repo_root,
+    vcs,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class Mercurial(VersionControl):
+    name = "hg"
+    dirname = ".hg"
+    repo_name = "clone"
+    schemes = (
+        "hg+file",
+        "hg+http",
+        "hg+https",
+        "hg+ssh",
+        "hg+static-http",
+    )
+
+    @staticmethod
+    def get_base_rev_args(rev: str) -> List[str]:
+        return [rev]
+
+    def fetch_new(
+        self, dest: str, url: HiddenText, rev_options: RevOptions, verbosity: int
+    ) -> None:
+        rev_display = rev_options.to_display()
+        logger.info(
+            "Cloning hg %s%s to %s",
+            url,
+            rev_display,
+            display_path(dest),
+        )
+        if verbosity <= 0:
+            flags: Tuple[str, ...] = ("--quiet",)
+        elif verbosity == 1:
+            flags = ()
+        elif verbosity == 2:
+            flags = ("--verbose",)
+        else:
+            flags = ("--verbose", "--debug")
+        self.run_command(make_command("clone", "--noupdate", *flags, url, dest))
+        self.run_command(
+            make_command("update", *flags, rev_options.to_args()),
+            cwd=dest,
+        )
+
+    def switch(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        repo_config = os.path.join(dest, self.dirname, "hgrc")
+        config = configparser.RawConfigParser()
+        try:
+            config.read(repo_config)
+            config.set("paths", "default", url.secret)
+            with open(repo_config, "w") as config_file:
+                config.write(config_file)
+        except (OSError, configparser.NoSectionError) as exc:
+            logger.warning("Could not switch Mercurial repository to %s: %s", url, exc)
+        else:
+            cmd_args = make_command("update", "-q", rev_options.to_args())
+            self.run_command(cmd_args, cwd=dest)
+
+    def update(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        self.run_command(["pull", "-q"], cwd=dest)
+        cmd_args = make_command("update", "-q", rev_options.to_args())
+        self.run_command(cmd_args, cwd=dest)
+
+    @classmethod
+    def get_remote_url(cls, location: str) -> str:
+        url = cls.run_command(
+            ["showconfig", "paths.default"],
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        ).strip()
+        if cls._is_local_repository(url):
+            url = path_to_url(url)
+        return url.strip()
+
+    @classmethod
+    def get_revision(cls, location: str) -> str:
+        """
+        Return the repository-local changeset revision number, as an integer.
+        """
+        current_revision = cls.run_command(
+            ["parents", "--template={rev}"],
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        ).strip()
+        return current_revision
+
+    @classmethod
+    def get_requirement_revision(cls, location: str) -> str:
+        """
+        Return the changeset identification hash, as a 40-character
+        hexadecimal string
+        """
+        current_rev_hash = cls.run_command(
+            ["parents", "--template={node}"],
+            show_stdout=False,
+            stdout_only=True,
+            cwd=location,
+        ).strip()
+        return current_rev_hash
+
+    @classmethod
+    def is_commit_id_equal(cls, dest: str, name: Optional[str]) -> bool:
+        """Always assume the versions don't match"""
+        return False
+
+    @classmethod
+    def get_subdirectory(cls, location: str) -> Optional[str]:
+        """
+        Return the path to Python project root, relative to the repo root.
+        Return None if the project root is in the repo root.
+        """
+        # find the repo root
+        repo_root = cls.run_command(
+            ["root"], show_stdout=False, stdout_only=True, cwd=location
+        ).strip()
+        if not os.path.isabs(repo_root):
+            repo_root = os.path.abspath(os.path.join(location, repo_root))
+        return find_path_to_project_root_from_repo_root(location, repo_root)
+
+    @classmethod
+    def get_repository_root(cls, location: str) -> Optional[str]:
+        loc = super().get_repository_root(location)
+        if loc:
+            return loc
+        try:
+            r = cls.run_command(
+                ["root"],
+                cwd=location,
+                show_stdout=False,
+                stdout_only=True,
+                on_returncode="raise",
+                log_failed_cmd=False,
+            )
+        except BadCommand:
+            logger.debug(
+                "could not determine if %s is under hg control "
+                "because hg is not available",
+                location,
+            )
+            return None
+        except InstallationError:
+            return None
+        return os.path.normpath(r.rstrip("\r\n"))
+
+
+vcs.register(Mercurial)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/subversion.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/subversion.py
new file mode 100644
index 0000000000000000000000000000000000000000..16d93a67b7b6feed66f2cc432f6250ca3ad34914
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/subversion.py
@@ -0,0 +1,324 @@
+import logging
+import os
+import re
+from typing import List, Optional, Tuple
+
+from pip._internal.utils.misc import (
+    HiddenText,
+    display_path,
+    is_console_interactive,
+    is_installable_dir,
+    split_auth_from_netloc,
+)
+from pip._internal.utils.subprocess import CommandArgs, make_command
+from pip._internal.vcs.versioncontrol import (
+    AuthInfo,
+    RemoteNotFoundError,
+    RevOptions,
+    VersionControl,
+    vcs,
+)
+
+logger = logging.getLogger(__name__)
+
+_svn_xml_url_re = re.compile('url="([^"]+)"')
+_svn_rev_re = re.compile(r'committed-rev="(\d+)"')
+_svn_info_xml_rev_re = re.compile(r'\s*revision="(\d+)"')
+_svn_info_xml_url_re = re.compile(r"(.*)")
+
+
+class Subversion(VersionControl):
+    name = "svn"
+    dirname = ".svn"
+    repo_name = "checkout"
+    schemes = ("svn+ssh", "svn+http", "svn+https", "svn+svn", "svn+file")
+
+    @classmethod
+    def should_add_vcs_url_prefix(cls, remote_url: str) -> bool:
+        return True
+
+    @staticmethod
+    def get_base_rev_args(rev: str) -> List[str]:
+        return ["-r", rev]
+
+    @classmethod
+    def get_revision(cls, location: str) -> str:
+        """
+        Return the maximum revision for all files under a given location
+        """
+        # Note: taken from setuptools.command.egg_info
+        revision = 0
+
+        for base, dirs, _ in os.walk(location):
+            if cls.dirname not in dirs:
+                dirs[:] = []
+                continue  # no sense walking uncontrolled subdirs
+            dirs.remove(cls.dirname)
+            entries_fn = os.path.join(base, cls.dirname, "entries")
+            if not os.path.exists(entries_fn):
+                # FIXME: should we warn?
+                continue
+
+            dirurl, localrev = cls._get_svn_url_rev(base)
+
+            if base == location:
+                assert dirurl is not None
+                base = dirurl + "/"  # save the root url
+            elif not dirurl or not dirurl.startswith(base):
+                dirs[:] = []
+                continue  # not part of the same svn tree, skip it
+            revision = max(revision, localrev)
+        return str(revision)
+
+    @classmethod
+    def get_netloc_and_auth(
+        cls, netloc: str, scheme: str
+    ) -> Tuple[str, Tuple[Optional[str], Optional[str]]]:
+        """
+        This override allows the auth information to be passed to svn via the
+        --username and --password options instead of via the URL.
+        """
+        if scheme == "ssh":
+            # The --username and --password options can't be used for
+            # svn+ssh URLs, so keep the auth information in the URL.
+            return super().get_netloc_and_auth(netloc, scheme)
+
+        return split_auth_from_netloc(netloc)
+
+    @classmethod
+    def get_url_rev_and_auth(cls, url: str) -> Tuple[str, Optional[str], AuthInfo]:
+        # hotfix the URL scheme after removing svn+ from svn+ssh:// re-add it
+        url, rev, user_pass = super().get_url_rev_and_auth(url)
+        if url.startswith("ssh://"):
+            url = "svn+" + url
+        return url, rev, user_pass
+
+    @staticmethod
+    def make_rev_args(
+        username: Optional[str], password: Optional[HiddenText]
+    ) -> CommandArgs:
+        extra_args: CommandArgs = []
+        if username:
+            extra_args += ["--username", username]
+        if password:
+            extra_args += ["--password", password]
+
+        return extra_args
+
+    @classmethod
+    def get_remote_url(cls, location: str) -> str:
+        # In cases where the source is in a subdirectory, we have to look up in
+        # the location until we find a valid project root.
+        orig_location = location
+        while not is_installable_dir(location):
+            last_location = location
+            location = os.path.dirname(location)
+            if location == last_location:
+                # We've traversed up to the root of the filesystem without
+                # finding a Python project.
+                logger.warning(
+                    "Could not find Python project for directory %s (tried all "
+                    "parent directories)",
+                    orig_location,
+                )
+                raise RemoteNotFoundError
+
+        url, _rev = cls._get_svn_url_rev(location)
+        if url is None:
+            raise RemoteNotFoundError
+
+        return url
+
+    @classmethod
+    def _get_svn_url_rev(cls, location: str) -> Tuple[Optional[str], int]:
+        from pip._internal.exceptions import InstallationError
+
+        entries_path = os.path.join(location, cls.dirname, "entries")
+        if os.path.exists(entries_path):
+            with open(entries_path) as f:
+                data = f.read()
+        else:  # subversion >= 1.7 does not have the 'entries' file
+            data = ""
+
+        url = None
+        if data.startswith("8") or data.startswith("9") or data.startswith("10"):
+            entries = list(map(str.splitlines, data.split("\n\x0c\n")))
+            del entries[0][0]  # get rid of the '8'
+            url = entries[0][3]
+            revs = [int(d[9]) for d in entries if len(d) > 9 and d[9]] + [0]
+        elif data.startswith("= 1.7
+                # Note that using get_remote_call_options is not necessary here
+                # because `svn info` is being run against a local directory.
+                # We don't need to worry about making sure interactive mode
+                # is being used to prompt for passwords, because passwords
+                # are only potentially needed for remote server requests.
+                xml = cls.run_command(
+                    ["info", "--xml", location],
+                    show_stdout=False,
+                    stdout_only=True,
+                )
+                match = _svn_info_xml_url_re.search(xml)
+                assert match is not None
+                url = match.group(1)
+                revs = [int(m.group(1)) for m in _svn_info_xml_rev_re.finditer(xml)]
+            except InstallationError:
+                url, revs = None, []
+
+        if revs:
+            rev = max(revs)
+        else:
+            rev = 0
+
+        return url, rev
+
+    @classmethod
+    def is_commit_id_equal(cls, dest: str, name: Optional[str]) -> bool:
+        """Always assume the versions don't match"""
+        return False
+
+    def __init__(self, use_interactive: Optional[bool] = None) -> None:
+        if use_interactive is None:
+            use_interactive = is_console_interactive()
+        self.use_interactive = use_interactive
+
+        # This member is used to cache the fetched version of the current
+        # ``svn`` client.
+        # Special value definitions:
+        #   None: Not evaluated yet.
+        #   Empty tuple: Could not parse version.
+        self._vcs_version: Optional[Tuple[int, ...]] = None
+
+        super().__init__()
+
+    def call_vcs_version(self) -> Tuple[int, ...]:
+        """Query the version of the currently installed Subversion client.
+
+        :return: A tuple containing the parts of the version information or
+            ``()`` if the version returned from ``svn`` could not be parsed.
+        :raises: BadCommand: If ``svn`` is not installed.
+        """
+        # Example versions:
+        #   svn, version 1.10.3 (r1842928)
+        #      compiled Feb 25 2019, 14:20:39 on x86_64-apple-darwin17.0.0
+        #   svn, version 1.7.14 (r1542130)
+        #      compiled Mar 28 2018, 08:49:13 on x86_64-pc-linux-gnu
+        #   svn, version 1.12.0-SlikSvn (SlikSvn/1.12.0)
+        #      compiled May 28 2019, 13:44:56 on x86_64-microsoft-windows6.2
+        version_prefix = "svn, version "
+        version = self.run_command(["--version"], show_stdout=False, stdout_only=True)
+        if not version.startswith(version_prefix):
+            return ()
+
+        version = version[len(version_prefix) :].split()[0]
+        version_list = version.partition("-")[0].split(".")
+        try:
+            parsed_version = tuple(map(int, version_list))
+        except ValueError:
+            return ()
+
+        return parsed_version
+
+    def get_vcs_version(self) -> Tuple[int, ...]:
+        """Return the version of the currently installed Subversion client.
+
+        If the version of the Subversion client has already been queried,
+        a cached value will be used.
+
+        :return: A tuple containing the parts of the version information or
+            ``()`` if the version returned from ``svn`` could not be parsed.
+        :raises: BadCommand: If ``svn`` is not installed.
+        """
+        if self._vcs_version is not None:
+            # Use cached version, if available.
+            # If parsing the version failed previously (empty tuple),
+            # do not attempt to parse it again.
+            return self._vcs_version
+
+        vcs_version = self.call_vcs_version()
+        self._vcs_version = vcs_version
+        return vcs_version
+
+    def get_remote_call_options(self) -> CommandArgs:
+        """Return options to be used on calls to Subversion that contact the server.
+
+        These options are applicable for the following ``svn`` subcommands used
+        in this class.
+
+            - checkout
+            - switch
+            - update
+
+        :return: A list of command line arguments to pass to ``svn``.
+        """
+        if not self.use_interactive:
+            # --non-interactive switch is available since Subversion 0.14.4.
+            # Subversion < 1.8 runs in interactive mode by default.
+            return ["--non-interactive"]
+
+        svn_version = self.get_vcs_version()
+        # By default, Subversion >= 1.8 runs in non-interactive mode if
+        # stdin is not a TTY. Since that is how pip invokes SVN, in
+        # call_subprocess(), pip must pass --force-interactive to ensure
+        # the user can be prompted for a password, if required.
+        #   SVN added the --force-interactive option in SVN 1.8. Since
+        # e.g. RHEL/CentOS 7, which is supported until 2024, ships with
+        # SVN 1.7, pip should continue to support SVN 1.7. Therefore, pip
+        # can't safely add the option if the SVN version is < 1.8 (or unknown).
+        if svn_version >= (1, 8):
+            return ["--force-interactive"]
+
+        return []
+
+    def fetch_new(
+        self, dest: str, url: HiddenText, rev_options: RevOptions, verbosity: int
+    ) -> None:
+        rev_display = rev_options.to_display()
+        logger.info(
+            "Checking out %s%s to %s",
+            url,
+            rev_display,
+            display_path(dest),
+        )
+        if verbosity <= 0:
+            flag = "--quiet"
+        else:
+            flag = ""
+        cmd_args = make_command(
+            "checkout",
+            flag,
+            self.get_remote_call_options(),
+            rev_options.to_args(),
+            url,
+            dest,
+        )
+        self.run_command(cmd_args)
+
+    def switch(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        cmd_args = make_command(
+            "switch",
+            self.get_remote_call_options(),
+            rev_options.to_args(),
+            url,
+            dest,
+        )
+        self.run_command(cmd_args)
+
+    def update(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        cmd_args = make_command(
+            "update",
+            self.get_remote_call_options(),
+            rev_options.to_args(),
+            dest,
+        )
+        self.run_command(cmd_args)
+
+
+vcs.register(Subversion)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/versioncontrol.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/versioncontrol.py
new file mode 100644
index 0000000000000000000000000000000000000000..02bbf68e7ad3ce14f191af24260312e817e12df7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/vcs/versioncontrol.py
@@ -0,0 +1,705 @@
+"""Handles all VCS (version control) support"""
+
+import logging
+import os
+import shutil
+import sys
+import urllib.parse
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Dict,
+    Iterable,
+    Iterator,
+    List,
+    Mapping,
+    Optional,
+    Tuple,
+    Type,
+    Union,
+)
+
+from pip._internal.cli.spinners import SpinnerInterface
+from pip._internal.exceptions import BadCommand, InstallationError
+from pip._internal.utils.misc import (
+    HiddenText,
+    ask_path_exists,
+    backup_dir,
+    display_path,
+    hide_url,
+    hide_value,
+    is_installable_dir,
+    rmtree,
+)
+from pip._internal.utils.subprocess import (
+    CommandArgs,
+    call_subprocess,
+    format_command_args,
+    make_command,
+)
+from pip._internal.utils.urls import get_url_scheme
+
+if TYPE_CHECKING:
+    # Literal was introduced in Python 3.8.
+    #
+    # TODO: Remove `if TYPE_CHECKING` when dropping support for Python 3.7.
+    from typing import Literal
+
+
+__all__ = ["vcs"]
+
+
+logger = logging.getLogger(__name__)
+
+AuthInfo = Tuple[Optional[str], Optional[str]]
+
+
+def is_url(name: str) -> bool:
+    """
+    Return true if the name looks like a URL.
+    """
+    scheme = get_url_scheme(name)
+    if scheme is None:
+        return False
+    return scheme in ["http", "https", "file", "ftp"] + vcs.all_schemes
+
+
+def make_vcs_requirement_url(
+    repo_url: str, rev: str, project_name: str, subdir: Optional[str] = None
+) -> str:
+    """
+    Return the URL for a VCS requirement.
+
+    Args:
+      repo_url: the remote VCS url, with any needed VCS prefix (e.g. "git+").
+      project_name: the (unescaped) project name.
+    """
+    egg_project_name = project_name.replace("-", "_")
+    req = f"{repo_url}@{rev}#egg={egg_project_name}"
+    if subdir:
+        req += f"&subdirectory={subdir}"
+
+    return req
+
+
+def find_path_to_project_root_from_repo_root(
+    location: str, repo_root: str
+) -> Optional[str]:
+    """
+    Find the the Python project's root by searching up the filesystem from
+    `location`. Return the path to project root relative to `repo_root`.
+    Return None if the project root is `repo_root`, or cannot be found.
+    """
+    # find project root.
+    orig_location = location
+    while not is_installable_dir(location):
+        last_location = location
+        location = os.path.dirname(location)
+        if location == last_location:
+            # We've traversed up to the root of the filesystem without
+            # finding a Python project.
+            logger.warning(
+                "Could not find a Python project for directory %s (tried all "
+                "parent directories)",
+                orig_location,
+            )
+            return None
+
+    if os.path.samefile(repo_root, location):
+        return None
+
+    return os.path.relpath(location, repo_root)
+
+
+class RemoteNotFoundError(Exception):
+    pass
+
+
+class RemoteNotValidError(Exception):
+    def __init__(self, url: str):
+        super().__init__(url)
+        self.url = url
+
+
+class RevOptions:
+
+    """
+    Encapsulates a VCS-specific revision to install, along with any VCS
+    install options.
+
+    Instances of this class should be treated as if immutable.
+    """
+
+    def __init__(
+        self,
+        vc_class: Type["VersionControl"],
+        rev: Optional[str] = None,
+        extra_args: Optional[CommandArgs] = None,
+    ) -> None:
+        """
+        Args:
+          vc_class: a VersionControl subclass.
+          rev: the name of the revision to install.
+          extra_args: a list of extra options.
+        """
+        if extra_args is None:
+            extra_args = []
+
+        self.extra_args = extra_args
+        self.rev = rev
+        self.vc_class = vc_class
+        self.branch_name: Optional[str] = None
+
+    def __repr__(self) -> str:
+        return f""
+
+    @property
+    def arg_rev(self) -> Optional[str]:
+        if self.rev is None:
+            return self.vc_class.default_arg_rev
+
+        return self.rev
+
+    def to_args(self) -> CommandArgs:
+        """
+        Return the VCS-specific command arguments.
+        """
+        args: CommandArgs = []
+        rev = self.arg_rev
+        if rev is not None:
+            args += self.vc_class.get_base_rev_args(rev)
+        args += self.extra_args
+
+        return args
+
+    def to_display(self) -> str:
+        if not self.rev:
+            return ""
+
+        return f" (to revision {self.rev})"
+
+    def make_new(self, rev: str) -> "RevOptions":
+        """
+        Make a copy of the current instance, but with a new rev.
+
+        Args:
+          rev: the name of the revision for the new object.
+        """
+        return self.vc_class.make_rev_options(rev, extra_args=self.extra_args)
+
+
+class VcsSupport:
+    _registry: Dict[str, "VersionControl"] = {}
+    schemes = ["ssh", "git", "hg", "bzr", "sftp", "svn"]
+
+    def __init__(self) -> None:
+        # Register more schemes with urlparse for various version control
+        # systems
+        urllib.parse.uses_netloc.extend(self.schemes)
+        super().__init__()
+
+    def __iter__(self) -> Iterator[str]:
+        return self._registry.__iter__()
+
+    @property
+    def backends(self) -> List["VersionControl"]:
+        return list(self._registry.values())
+
+    @property
+    def dirnames(self) -> List[str]:
+        return [backend.dirname for backend in self.backends]
+
+    @property
+    def all_schemes(self) -> List[str]:
+        schemes: List[str] = []
+        for backend in self.backends:
+            schemes.extend(backend.schemes)
+        return schemes
+
+    def register(self, cls: Type["VersionControl"]) -> None:
+        if not hasattr(cls, "name"):
+            logger.warning("Cannot register VCS %s", cls.__name__)
+            return
+        if cls.name not in self._registry:
+            self._registry[cls.name] = cls()
+            logger.debug("Registered VCS backend: %s", cls.name)
+
+    def unregister(self, name: str) -> None:
+        if name in self._registry:
+            del self._registry[name]
+
+    def get_backend_for_dir(self, location: str) -> Optional["VersionControl"]:
+        """
+        Return a VersionControl object if a repository of that type is found
+        at the given directory.
+        """
+        vcs_backends = {}
+        for vcs_backend in self._registry.values():
+            repo_path = vcs_backend.get_repository_root(location)
+            if not repo_path:
+                continue
+            logger.debug("Determine that %s uses VCS: %s", location, vcs_backend.name)
+            vcs_backends[repo_path] = vcs_backend
+
+        if not vcs_backends:
+            return None
+
+        # Choose the VCS in the inner-most directory. Since all repository
+        # roots found here would be either `location` or one of its
+        # parents, the longest path should have the most path components,
+        # i.e. the backend representing the inner-most repository.
+        inner_most_repo_path = max(vcs_backends, key=len)
+        return vcs_backends[inner_most_repo_path]
+
+    def get_backend_for_scheme(self, scheme: str) -> Optional["VersionControl"]:
+        """
+        Return a VersionControl object or None.
+        """
+        for vcs_backend in self._registry.values():
+            if scheme in vcs_backend.schemes:
+                return vcs_backend
+        return None
+
+    def get_backend(self, name: str) -> Optional["VersionControl"]:
+        """
+        Return a VersionControl object or None.
+        """
+        name = name.lower()
+        return self._registry.get(name)
+
+
+vcs = VcsSupport()
+
+
+class VersionControl:
+    name = ""
+    dirname = ""
+    repo_name = ""
+    # List of supported schemes for this Version Control
+    schemes: Tuple[str, ...] = ()
+    # Iterable of environment variable names to pass to call_subprocess().
+    unset_environ: Tuple[str, ...] = ()
+    default_arg_rev: Optional[str] = None
+
+    @classmethod
+    def should_add_vcs_url_prefix(cls, remote_url: str) -> bool:
+        """
+        Return whether the vcs prefix (e.g. "git+") should be added to a
+        repository's remote url when used in a requirement.
+        """
+        return not remote_url.lower().startswith(f"{cls.name}:")
+
+    @classmethod
+    def get_subdirectory(cls, location: str) -> Optional[str]:
+        """
+        Return the path to Python project root, relative to the repo root.
+        Return None if the project root is in the repo root.
+        """
+        return None
+
+    @classmethod
+    def get_requirement_revision(cls, repo_dir: str) -> str:
+        """
+        Return the revision string that should be used in a requirement.
+        """
+        return cls.get_revision(repo_dir)
+
+    @classmethod
+    def get_src_requirement(cls, repo_dir: str, project_name: str) -> str:
+        """
+        Return the requirement string to use to redownload the files
+        currently at the given repository directory.
+
+        Args:
+          project_name: the (unescaped) project name.
+
+        The return value has a form similar to the following:
+
+            {repository_url}@{revision}#egg={project_name}
+        """
+        repo_url = cls.get_remote_url(repo_dir)
+
+        if cls.should_add_vcs_url_prefix(repo_url):
+            repo_url = f"{cls.name}+{repo_url}"
+
+        revision = cls.get_requirement_revision(repo_dir)
+        subdir = cls.get_subdirectory(repo_dir)
+        req = make_vcs_requirement_url(repo_url, revision, project_name, subdir=subdir)
+
+        return req
+
+    @staticmethod
+    def get_base_rev_args(rev: str) -> List[str]:
+        """
+        Return the base revision arguments for a vcs command.
+
+        Args:
+          rev: the name of a revision to install.  Cannot be None.
+        """
+        raise NotImplementedError
+
+    def is_immutable_rev_checkout(self, url: str, dest: str) -> bool:
+        """
+        Return true if the commit hash checked out at dest matches
+        the revision in url.
+
+        Always return False, if the VCS does not support immutable commit
+        hashes.
+
+        This method does not check if there are local uncommitted changes
+        in dest after checkout, as pip currently has no use case for that.
+        """
+        return False
+
+    @classmethod
+    def make_rev_options(
+        cls, rev: Optional[str] = None, extra_args: Optional[CommandArgs] = None
+    ) -> RevOptions:
+        """
+        Return a RevOptions object.
+
+        Args:
+          rev: the name of a revision to install.
+          extra_args: a list of extra options.
+        """
+        return RevOptions(cls, rev, extra_args=extra_args)
+
+    @classmethod
+    def _is_local_repository(cls, repo: str) -> bool:
+        """
+        posix absolute paths start with os.path.sep,
+        win32 ones start with drive (like c:\\folder)
+        """
+        drive, tail = os.path.splitdrive(repo)
+        return repo.startswith(os.path.sep) or bool(drive)
+
+    @classmethod
+    def get_netloc_and_auth(
+        cls, netloc: str, scheme: str
+    ) -> Tuple[str, Tuple[Optional[str], Optional[str]]]:
+        """
+        Parse the repository URL's netloc, and return the new netloc to use
+        along with auth information.
+
+        Args:
+          netloc: the original repository URL netloc.
+          scheme: the repository URL's scheme without the vcs prefix.
+
+        This is mainly for the Subversion class to override, so that auth
+        information can be provided via the --username and --password options
+        instead of through the URL.  For other subclasses like Git without
+        such an option, auth information must stay in the URL.
+
+        Returns: (netloc, (username, password)).
+        """
+        return netloc, (None, None)
+
+    @classmethod
+    def get_url_rev_and_auth(cls, url: str) -> Tuple[str, Optional[str], AuthInfo]:
+        """
+        Parse the repository URL to use, and return the URL, revision,
+        and auth info to use.
+
+        Returns: (url, rev, (username, password)).
+        """
+        scheme, netloc, path, query, frag = urllib.parse.urlsplit(url)
+        if "+" not in scheme:
+            raise ValueError(
+                "Sorry, {!r} is a malformed VCS url. "
+                "The format is +://, "
+                "e.g. svn+http://myrepo/svn/MyApp#egg=MyApp".format(url)
+            )
+        # Remove the vcs prefix.
+        scheme = scheme.split("+", 1)[1]
+        netloc, user_pass = cls.get_netloc_and_auth(netloc, scheme)
+        rev = None
+        if "@" in path:
+            path, rev = path.rsplit("@", 1)
+            if not rev:
+                raise InstallationError(
+                    "The URL {!r} has an empty revision (after @) "
+                    "which is not supported. Include a revision after @ "
+                    "or remove @ from the URL.".format(url)
+                )
+        url = urllib.parse.urlunsplit((scheme, netloc, path, query, ""))
+        return url, rev, user_pass
+
+    @staticmethod
+    def make_rev_args(
+        username: Optional[str], password: Optional[HiddenText]
+    ) -> CommandArgs:
+        """
+        Return the RevOptions "extra arguments" to use in obtain().
+        """
+        return []
+
+    def get_url_rev_options(self, url: HiddenText) -> Tuple[HiddenText, RevOptions]:
+        """
+        Return the URL and RevOptions object to use in obtain(),
+        as a tuple (url, rev_options).
+        """
+        secret_url, rev, user_pass = self.get_url_rev_and_auth(url.secret)
+        username, secret_password = user_pass
+        password: Optional[HiddenText] = None
+        if secret_password is not None:
+            password = hide_value(secret_password)
+        extra_args = self.make_rev_args(username, password)
+        rev_options = self.make_rev_options(rev, extra_args=extra_args)
+
+        return hide_url(secret_url), rev_options
+
+    @staticmethod
+    def normalize_url(url: str) -> str:
+        """
+        Normalize a URL for comparison by unquoting it and removing any
+        trailing slash.
+        """
+        return urllib.parse.unquote(url).rstrip("/")
+
+    @classmethod
+    def compare_urls(cls, url1: str, url2: str) -> bool:
+        """
+        Compare two repo URLs for identity, ignoring incidental differences.
+        """
+        return cls.normalize_url(url1) == cls.normalize_url(url2)
+
+    def fetch_new(
+        self, dest: str, url: HiddenText, rev_options: RevOptions, verbosity: int
+    ) -> None:
+        """
+        Fetch a revision from a repository, in the case that this is the
+        first fetch from the repository.
+
+        Args:
+          dest: the directory to fetch the repository to.
+          rev_options: a RevOptions object.
+          verbosity: verbosity level.
+        """
+        raise NotImplementedError
+
+    def switch(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        """
+        Switch the repo at ``dest`` to point to ``URL``.
+
+        Args:
+          rev_options: a RevOptions object.
+        """
+        raise NotImplementedError
+
+    def update(self, dest: str, url: HiddenText, rev_options: RevOptions) -> None:
+        """
+        Update an already-existing repo to the given ``rev_options``.
+
+        Args:
+          rev_options: a RevOptions object.
+        """
+        raise NotImplementedError
+
+    @classmethod
+    def is_commit_id_equal(cls, dest: str, name: Optional[str]) -> bool:
+        """
+        Return whether the id of the current commit equals the given name.
+
+        Args:
+          dest: the repository directory.
+          name: a string name.
+        """
+        raise NotImplementedError
+
+    def obtain(self, dest: str, url: HiddenText, verbosity: int) -> None:
+        """
+        Install or update in editable mode the package represented by this
+        VersionControl object.
+
+        :param dest: the repository directory in which to install or update.
+        :param url: the repository URL starting with a vcs prefix.
+        :param verbosity: verbosity level.
+        """
+        url, rev_options = self.get_url_rev_options(url)
+
+        if not os.path.exists(dest):
+            self.fetch_new(dest, url, rev_options, verbosity=verbosity)
+            return
+
+        rev_display = rev_options.to_display()
+        if self.is_repository_directory(dest):
+            existing_url = self.get_remote_url(dest)
+            if self.compare_urls(existing_url, url.secret):
+                logger.debug(
+                    "%s in %s exists, and has correct URL (%s)",
+                    self.repo_name.title(),
+                    display_path(dest),
+                    url,
+                )
+                if not self.is_commit_id_equal(dest, rev_options.rev):
+                    logger.info(
+                        "Updating %s %s%s",
+                        display_path(dest),
+                        self.repo_name,
+                        rev_display,
+                    )
+                    self.update(dest, url, rev_options)
+                else:
+                    logger.info("Skipping because already up-to-date.")
+                return
+
+            logger.warning(
+                "%s %s in %s exists with URL %s",
+                self.name,
+                self.repo_name,
+                display_path(dest),
+                existing_url,
+            )
+            prompt = ("(s)witch, (i)gnore, (w)ipe, (b)ackup ", ("s", "i", "w", "b"))
+        else:
+            logger.warning(
+                "Directory %s already exists, and is not a %s %s.",
+                dest,
+                self.name,
+                self.repo_name,
+            )
+            # https://github.com/python/mypy/issues/1174
+            prompt = ("(i)gnore, (w)ipe, (b)ackup ", ("i", "w", "b"))  # type: ignore
+
+        logger.warning(
+            "The plan is to install the %s repository %s",
+            self.name,
+            url,
+        )
+        response = ask_path_exists("What to do?  {}".format(prompt[0]), prompt[1])
+
+        if response == "a":
+            sys.exit(-1)
+
+        if response == "w":
+            logger.warning("Deleting %s", display_path(dest))
+            rmtree(dest)
+            self.fetch_new(dest, url, rev_options, verbosity=verbosity)
+            return
+
+        if response == "b":
+            dest_dir = backup_dir(dest)
+            logger.warning("Backing up %s to %s", display_path(dest), dest_dir)
+            shutil.move(dest, dest_dir)
+            self.fetch_new(dest, url, rev_options, verbosity=verbosity)
+            return
+
+        # Do nothing if the response is "i".
+        if response == "s":
+            logger.info(
+                "Switching %s %s to %s%s",
+                self.repo_name,
+                display_path(dest),
+                url,
+                rev_display,
+            )
+            self.switch(dest, url, rev_options)
+
+    def unpack(self, location: str, url: HiddenText, verbosity: int) -> None:
+        """
+        Clean up current location and download the url repository
+        (and vcs infos) into location
+
+        :param url: the repository URL starting with a vcs prefix.
+        :param verbosity: verbosity level.
+        """
+        if os.path.exists(location):
+            rmtree(location)
+        self.obtain(location, url=url, verbosity=verbosity)
+
+    @classmethod
+    def get_remote_url(cls, location: str) -> str:
+        """
+        Return the url used at location
+
+        Raises RemoteNotFoundError if the repository does not have a remote
+        url configured.
+        """
+        raise NotImplementedError
+
+    @classmethod
+    def get_revision(cls, location: str) -> str:
+        """
+        Return the current commit id of the files at the given location.
+        """
+        raise NotImplementedError
+
+    @classmethod
+    def run_command(
+        cls,
+        cmd: Union[List[str], CommandArgs],
+        show_stdout: bool = True,
+        cwd: Optional[str] = None,
+        on_returncode: 'Literal["raise", "warn", "ignore"]' = "raise",
+        extra_ok_returncodes: Optional[Iterable[int]] = None,
+        command_desc: Optional[str] = None,
+        extra_environ: Optional[Mapping[str, Any]] = None,
+        spinner: Optional[SpinnerInterface] = None,
+        log_failed_cmd: bool = True,
+        stdout_only: bool = False,
+    ) -> str:
+        """
+        Run a VCS subcommand
+        This is simply a wrapper around call_subprocess that adds the VCS
+        command name, and checks that the VCS is available
+        """
+        cmd = make_command(cls.name, *cmd)
+        if command_desc is None:
+            command_desc = format_command_args(cmd)
+        try:
+            return call_subprocess(
+                cmd,
+                show_stdout,
+                cwd,
+                on_returncode=on_returncode,
+                extra_ok_returncodes=extra_ok_returncodes,
+                command_desc=command_desc,
+                extra_environ=extra_environ,
+                unset_environ=cls.unset_environ,
+                spinner=spinner,
+                log_failed_cmd=log_failed_cmd,
+                stdout_only=stdout_only,
+            )
+        except FileNotFoundError:
+            # errno.ENOENT = no such file or directory
+            # In other words, the VCS executable isn't available
+            raise BadCommand(
+                f"Cannot find command {cls.name!r} - do you have "
+                f"{cls.name!r} installed and in your PATH?"
+            )
+        except PermissionError:
+            # errno.EACCES = Permission denied
+            # This error occurs, for instance, when the command is installed
+            # only for another user. So, the current user don't have
+            # permission to call the other user command.
+            raise BadCommand(
+                f"No permission to execute {cls.name!r} - install it "
+                f"locally, globally (ask admin), or check your PATH. "
+                f"See possible solutions at "
+                f"https://pip.pypa.io/en/latest/reference/pip_freeze/"
+                f"#fixing-permission-denied."
+            )
+
+    @classmethod
+    def is_repository_directory(cls, path: str) -> bool:
+        """
+        Return whether a directory path is a repository directory.
+        """
+        logger.debug("Checking in %s for %s (%s)...", path, cls.dirname, cls.name)
+        return os.path.exists(os.path.join(path, cls.dirname))
+
+    @classmethod
+    def get_repository_root(cls, location: str) -> Optional[str]:
+        """
+        Return the "root" (top-level) directory controlled by the vcs,
+        or `None` if the directory is not in any.
+
+        It is meant to be overridden to implement smarter detection
+        mechanisms for specific vcs.
+
+        This can do more than is_repository_directory() alone. For
+        example, the Git override checks that Git is actually available.
+        """
+        if cls.is_repository_directory(location):
+            return location
+        return None
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/wheel_builder.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/wheel_builder.py
new file mode 100644
index 0000000000000000000000000000000000000000..15b30af58e49da798befbe7afe1bb80d1b784cd0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_internal/wheel_builder.py
@@ -0,0 +1,382 @@
+"""Orchestrator for building wheels from InstallRequirements.
+"""
+
+import logging
+import os.path
+import re
+import shutil
+from typing import Callable, Iterable, List, Optional, Tuple
+
+from pip._vendor.packaging.utils import canonicalize_name, canonicalize_version
+from pip._vendor.packaging.version import InvalidVersion, Version
+
+from pip._internal.cache import WheelCache
+from pip._internal.exceptions import InvalidWheelFilename, UnsupportedWheel
+from pip._internal.metadata import FilesystemWheel, get_wheel_distribution
+from pip._internal.models.link import Link
+from pip._internal.models.wheel import Wheel
+from pip._internal.operations.build.wheel import build_wheel_pep517
+from pip._internal.operations.build.wheel_editable import build_wheel_editable
+from pip._internal.operations.build.wheel_legacy import build_wheel_legacy
+from pip._internal.req.req_install import InstallRequirement
+from pip._internal.utils.deprecation import (
+    LegacyInstallReasonMissingWheelPackage,
+    LegacyInstallReasonNoBinaryForcesSetuptoolsInstall,
+)
+from pip._internal.utils.logging import indent_log
+from pip._internal.utils.misc import ensure_dir, hash_file, is_wheel_installed
+from pip._internal.utils.setuptools_build import make_setuptools_clean_args
+from pip._internal.utils.subprocess import call_subprocess
+from pip._internal.utils.temp_dir import TempDirectory
+from pip._internal.utils.urls import path_to_url
+from pip._internal.vcs import vcs
+
+logger = logging.getLogger(__name__)
+
+_egg_info_re = re.compile(r"([a-z0-9_.]+)-([a-z0-9_.!+-]+)", re.IGNORECASE)
+
+BdistWheelAllowedPredicate = Callable[[InstallRequirement], bool]
+BuildResult = Tuple[List[InstallRequirement], List[InstallRequirement]]
+
+
+def _contains_egg_info(s: str) -> bool:
+    """Determine whether the string looks like an egg_info.
+
+    :param s: The string to parse. E.g. foo-2.1
+    """
+    return bool(_egg_info_re.search(s))
+
+
+def _should_build(
+    req: InstallRequirement,
+    need_wheel: bool,
+    check_bdist_wheel: Optional[BdistWheelAllowedPredicate] = None,
+) -> bool:
+    """Return whether an InstallRequirement should be built into a wheel."""
+    if req.constraint:
+        # never build requirements that are merely constraints
+        return False
+    if req.is_wheel:
+        if need_wheel:
+            logger.info(
+                "Skipping %s, due to already being wheel.",
+                req.name,
+            )
+        return False
+
+    if need_wheel:
+        # i.e. pip wheel, not pip install
+        return True
+
+    # From this point, this concerns the pip install command only
+    # (need_wheel=False).
+
+    if not req.source_dir:
+        return False
+
+    if req.editable:
+        # we only build PEP 660 editable requirements
+        return req.supports_pyproject_editable()
+
+    if req.use_pep517:
+        return True
+
+    assert check_bdist_wheel is not None
+    if not check_bdist_wheel(req):
+        # /!\ When we change this to unconditionally return True, we must also remove
+        # support for `--install-option`. Indeed, `--install-option` implies
+        # `--no-binary` so we can return False here and run `setup.py install`.
+        # `--global-option` and `--build-option` can remain until we drop support for
+        # building with `setup.py bdist_wheel`.
+        req.legacy_install_reason = LegacyInstallReasonNoBinaryForcesSetuptoolsInstall
+        return False
+
+    if not is_wheel_installed():
+        # we don't build legacy requirements if wheel is not installed
+        req.legacy_install_reason = LegacyInstallReasonMissingWheelPackage
+        return False
+
+    return True
+
+
+def should_build_for_wheel_command(
+    req: InstallRequirement,
+) -> bool:
+    return _should_build(req, need_wheel=True)
+
+
+def should_build_for_install_command(
+    req: InstallRequirement,
+    check_bdist_wheel_allowed: BdistWheelAllowedPredicate,
+) -> bool:
+    return _should_build(
+        req, need_wheel=False, check_bdist_wheel=check_bdist_wheel_allowed
+    )
+
+
+def _should_cache(
+    req: InstallRequirement,
+) -> Optional[bool]:
+    """
+    Return whether a built InstallRequirement can be stored in the persistent
+    wheel cache, assuming the wheel cache is available, and _should_build()
+    has determined a wheel needs to be built.
+    """
+    if req.editable or not req.source_dir:
+        # never cache editable requirements
+        return False
+
+    if req.link and req.link.is_vcs:
+        # VCS checkout. Do not cache
+        # unless it points to an immutable commit hash.
+        assert not req.editable
+        assert req.source_dir
+        vcs_backend = vcs.get_backend_for_scheme(req.link.scheme)
+        assert vcs_backend
+        if vcs_backend.is_immutable_rev_checkout(req.link.url, req.source_dir):
+            return True
+        return False
+
+    assert req.link
+    base, ext = req.link.splitext()
+    if _contains_egg_info(base):
+        return True
+
+    # Otherwise, do not cache.
+    return False
+
+
+def _get_cache_dir(
+    req: InstallRequirement,
+    wheel_cache: WheelCache,
+) -> str:
+    """Return the persistent or temporary cache directory where the built
+    wheel need to be stored.
+    """
+    cache_available = bool(wheel_cache.cache_dir)
+    assert req.link
+    if cache_available and _should_cache(req):
+        cache_dir = wheel_cache.get_path_for_link(req.link)
+    else:
+        cache_dir = wheel_cache.get_ephem_path_for_link(req.link)
+    return cache_dir
+
+
+def _verify_one(req: InstallRequirement, wheel_path: str) -> None:
+    canonical_name = canonicalize_name(req.name or "")
+    w = Wheel(os.path.basename(wheel_path))
+    if canonicalize_name(w.name) != canonical_name:
+        raise InvalidWheelFilename(
+            "Wheel has unexpected file name: expected {!r}, "
+            "got {!r}".format(canonical_name, w.name),
+        )
+    dist = get_wheel_distribution(FilesystemWheel(wheel_path), canonical_name)
+    dist_verstr = str(dist.version)
+    if canonicalize_version(dist_verstr) != canonicalize_version(w.version):
+        raise InvalidWheelFilename(
+            "Wheel has unexpected file name: expected {!r}, "
+            "got {!r}".format(dist_verstr, w.version),
+        )
+    metadata_version_value = dist.metadata_version
+    if metadata_version_value is None:
+        raise UnsupportedWheel("Missing Metadata-Version")
+    try:
+        metadata_version = Version(metadata_version_value)
+    except InvalidVersion:
+        msg = f"Invalid Metadata-Version: {metadata_version_value}"
+        raise UnsupportedWheel(msg)
+    if metadata_version >= Version("1.2") and not isinstance(dist.version, Version):
+        raise UnsupportedWheel(
+            "Metadata 1.2 mandates PEP 440 version, "
+            "but {!r} is not".format(dist_verstr)
+        )
+
+
+def _build_one(
+    req: InstallRequirement,
+    output_dir: str,
+    verify: bool,
+    build_options: List[str],
+    global_options: List[str],
+    editable: bool,
+) -> Optional[str]:
+    """Build one wheel.
+
+    :return: The filename of the built wheel, or None if the build failed.
+    """
+    artifact = "editable" if editable else "wheel"
+    try:
+        ensure_dir(output_dir)
+    except OSError as e:
+        logger.warning(
+            "Building %s for %s failed: %s",
+            artifact,
+            req.name,
+            e,
+        )
+        return None
+
+    # Install build deps into temporary directory (PEP 518)
+    with req.build_env:
+        wheel_path = _build_one_inside_env(
+            req, output_dir, build_options, global_options, editable
+        )
+    if wheel_path and verify:
+        try:
+            _verify_one(req, wheel_path)
+        except (InvalidWheelFilename, UnsupportedWheel) as e:
+            logger.warning("Built %s for %s is invalid: %s", artifact, req.name, e)
+            return None
+    return wheel_path
+
+
+def _build_one_inside_env(
+    req: InstallRequirement,
+    output_dir: str,
+    build_options: List[str],
+    global_options: List[str],
+    editable: bool,
+) -> Optional[str]:
+    with TempDirectory(kind="wheel") as temp_dir:
+        assert req.name
+        if req.use_pep517:
+            assert req.metadata_directory
+            assert req.pep517_backend
+            if global_options:
+                logger.warning(
+                    "Ignoring --global-option when building %s using PEP 517", req.name
+                )
+            if build_options:
+                logger.warning(
+                    "Ignoring --build-option when building %s using PEP 517", req.name
+                )
+            if editable:
+                wheel_path = build_wheel_editable(
+                    name=req.name,
+                    backend=req.pep517_backend,
+                    metadata_directory=req.metadata_directory,
+                    tempd=temp_dir.path,
+                )
+            else:
+                wheel_path = build_wheel_pep517(
+                    name=req.name,
+                    backend=req.pep517_backend,
+                    metadata_directory=req.metadata_directory,
+                    tempd=temp_dir.path,
+                )
+        else:
+            wheel_path = build_wheel_legacy(
+                name=req.name,
+                setup_py_path=req.setup_py_path,
+                source_dir=req.unpacked_source_directory,
+                global_options=global_options,
+                build_options=build_options,
+                tempd=temp_dir.path,
+            )
+
+        if wheel_path is not None:
+            wheel_name = os.path.basename(wheel_path)
+            dest_path = os.path.join(output_dir, wheel_name)
+            try:
+                wheel_hash, length = hash_file(wheel_path)
+                shutil.move(wheel_path, dest_path)
+                logger.info(
+                    "Created wheel for %s: filename=%s size=%d sha256=%s",
+                    req.name,
+                    wheel_name,
+                    length,
+                    wheel_hash.hexdigest(),
+                )
+                logger.info("Stored in directory: %s", output_dir)
+                return dest_path
+            except Exception as e:
+                logger.warning(
+                    "Building wheel for %s failed: %s",
+                    req.name,
+                    e,
+                )
+        # Ignore return, we can't do anything else useful.
+        if not req.use_pep517:
+            _clean_one_legacy(req, global_options)
+        return None
+
+
+def _clean_one_legacy(req: InstallRequirement, global_options: List[str]) -> bool:
+    clean_args = make_setuptools_clean_args(
+        req.setup_py_path,
+        global_options=global_options,
+    )
+
+    logger.info("Running setup.py clean for %s", req.name)
+    try:
+        call_subprocess(
+            clean_args, command_desc="python setup.py clean", cwd=req.source_dir
+        )
+        return True
+    except Exception:
+        logger.error("Failed cleaning build dir for %s", req.name)
+        return False
+
+
+def build(
+    requirements: Iterable[InstallRequirement],
+    wheel_cache: WheelCache,
+    verify: bool,
+    build_options: List[str],
+    global_options: List[str],
+) -> BuildResult:
+    """Build wheels.
+
+    :return: The list of InstallRequirement that succeeded to build and
+        the list of InstallRequirement that failed to build.
+    """
+    if not requirements:
+        return [], []
+
+    # Build the wheels.
+    logger.info(
+        "Building wheels for collected packages: %s",
+        ", ".join(req.name for req in requirements),  # type: ignore
+    )
+
+    with indent_log():
+        build_successes, build_failures = [], []
+        for req in requirements:
+            assert req.name
+            cache_dir = _get_cache_dir(req, wheel_cache)
+            wheel_file = _build_one(
+                req,
+                cache_dir,
+                verify,
+                build_options,
+                global_options,
+                req.editable and req.permit_editable_wheels,
+            )
+            if wheel_file:
+                # Record the download origin in the cache
+                if req.download_info is not None:
+                    # download_info is guaranteed to be set because when we build an
+                    # InstallRequirement it has been through the preparer before, but
+                    # let's be cautious.
+                    wheel_cache.record_download_origin(cache_dir, req.download_info)
+                # Update the link for this.
+                req.link = Link(path_to_url(wheel_file))
+                req.local_file_path = req.link.file_path
+                assert req.link.is_wheel
+                build_successes.append(req)
+            else:
+                build_failures.append(req)
+
+    # notify success/failure
+    if build_successes:
+        logger.info(
+            "Successfully built %s",
+            " ".join([req.name for req in build_successes]),  # type: ignore
+        )
+    if build_failures:
+        logger.info(
+            "Failed to build %s",
+            " ".join([req.name for req in build_failures]),  # type: ignore
+        )
+    # Return a list of requirements that failed to build
+    return build_successes, build_failures
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..b22f7abb93b9d7aeee50829b35746aaa3f9f5feb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/__init__.py
@@ -0,0 +1,120 @@
+"""
+pip._vendor is for vendoring dependencies of pip to prevent needing pip to
+depend on something external.
+
+Files inside of pip._vendor should be considered immutable and should only be
+updated to versions from upstream.
+"""
+from __future__ import absolute_import
+
+import glob
+import os.path
+import sys
+
+# Downstream redistributors which have debundled our dependencies should also
+# patch this value to be true. This will trigger the additional patching
+# to cause things like "six" to be available as pip.
+DEBUNDLED = False
+
+# By default, look in this directory for a bunch of .whl files which we will
+# add to the beginning of sys.path before attempting to import anything. This
+# is done to support downstream re-distributors like Debian and Fedora who
+# wish to create their own Wheels for our dependencies to aid in debundling.
+WHEEL_DIR = os.path.abspath(os.path.dirname(__file__))
+
+
+# Define a small helper function to alias our vendored modules to the real ones
+# if the vendored ones do not exist. This idea of this was taken from
+# https://github.com/kennethreitz/requests/pull/2567.
+def vendored(modulename):
+    vendored_name = "{0}.{1}".format(__name__, modulename)
+
+    try:
+        __import__(modulename, globals(), locals(), level=0)
+    except ImportError:
+        # We can just silently allow import failures to pass here. If we
+        # got to this point it means that ``import pip._vendor.whatever``
+        # failed and so did ``import whatever``. Since we're importing this
+        # upfront in an attempt to alias imports, not erroring here will
+        # just mean we get a regular import error whenever pip *actually*
+        # tries to import one of these modules to use it, which actually
+        # gives us a better error message than we would have otherwise
+        # gotten.
+        pass
+    else:
+        sys.modules[vendored_name] = sys.modules[modulename]
+        base, head = vendored_name.rsplit(".", 1)
+        setattr(sys.modules[base], head, sys.modules[modulename])
+
+
+# If we're operating in a debundled setup, then we want to go ahead and trigger
+# the aliasing of our vendored libraries as well as looking for wheels to add
+# to our sys.path. This will cause all of this code to be a no-op typically
+# however downstream redistributors can enable it in a consistent way across
+# all platforms.
+if DEBUNDLED:
+    # Actually look inside of WHEEL_DIR to find .whl files and add them to the
+    # front of our sys.path.
+    sys.path[:] = glob.glob(os.path.join(WHEEL_DIR, "*.whl")) + sys.path
+
+    # Actually alias all of our vendored dependencies.
+    vendored("cachecontrol")
+    vendored("certifi")
+    vendored("colorama")
+    vendored("distlib")
+    vendored("distro")
+    vendored("six")
+    vendored("six.moves")
+    vendored("six.moves.urllib")
+    vendored("six.moves.urllib.parse")
+    vendored("packaging")
+    vendored("packaging.version")
+    vendored("packaging.specifiers")
+    vendored("pep517")
+    vendored("pkg_resources")
+    vendored("platformdirs")
+    vendored("progress")
+    vendored("requests")
+    vendored("requests.exceptions")
+    vendored("requests.packages")
+    vendored("requests.packages.urllib3")
+    vendored("requests.packages.urllib3._collections")
+    vendored("requests.packages.urllib3.connection")
+    vendored("requests.packages.urllib3.connectionpool")
+    vendored("requests.packages.urllib3.contrib")
+    vendored("requests.packages.urllib3.contrib.ntlmpool")
+    vendored("requests.packages.urllib3.contrib.pyopenssl")
+    vendored("requests.packages.urllib3.exceptions")
+    vendored("requests.packages.urllib3.fields")
+    vendored("requests.packages.urllib3.filepost")
+    vendored("requests.packages.urllib3.packages")
+    vendored("requests.packages.urllib3.packages.ordered_dict")
+    vendored("requests.packages.urllib3.packages.six")
+    vendored("requests.packages.urllib3.packages.ssl_match_hostname")
+    vendored("requests.packages.urllib3.packages.ssl_match_hostname."
+             "_implementation")
+    vendored("requests.packages.urllib3.poolmanager")
+    vendored("requests.packages.urllib3.request")
+    vendored("requests.packages.urllib3.response")
+    vendored("requests.packages.urllib3.util")
+    vendored("requests.packages.urllib3.util.connection")
+    vendored("requests.packages.urllib3.util.request")
+    vendored("requests.packages.urllib3.util.response")
+    vendored("requests.packages.urllib3.util.retry")
+    vendored("requests.packages.urllib3.util.ssl_")
+    vendored("requests.packages.urllib3.util.timeout")
+    vendored("requests.packages.urllib3.util.url")
+    vendored("resolvelib")
+    vendored("rich")
+    vendored("rich.console")
+    vendored("rich.highlighter")
+    vendored("rich.logging")
+    vendored("rich.markup")
+    vendored("rich.progress")
+    vendored("rich.segment")
+    vendored("rich.style")
+    vendored("rich.text")
+    vendored("rich.traceback")
+    vendored("tenacity")
+    vendored("tomli")
+    vendored("urllib3")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..f631ae6df4747b808cac7c03b38e3e1d48bea00b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/__init__.py
@@ -0,0 +1,18 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""CacheControl import Interface.
+
+Make it easy to import from cachecontrol without long namespaces.
+"""
+__author__ = "Eric Larson"
+__email__ = "eric@ionrock.org"
+__version__ = "0.12.11"
+
+from .wrapper import CacheControl
+from .adapter import CacheControlAdapter
+from .controller import CacheController
+
+import logging
+logging.getLogger(__name__).addHandler(logging.NullHandler())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/_cmd.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/_cmd.py
new file mode 100644
index 0000000000000000000000000000000000000000..4266b5ee92a24b5e0ef65689a1b94a98bb4a9b56
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/_cmd.py
@@ -0,0 +1,61 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import logging
+
+from pip._vendor import requests
+
+from pip._vendor.cachecontrol.adapter import CacheControlAdapter
+from pip._vendor.cachecontrol.cache import DictCache
+from pip._vendor.cachecontrol.controller import logger
+
+from argparse import ArgumentParser
+
+
+def setup_logging():
+    logger.setLevel(logging.DEBUG)
+    handler = logging.StreamHandler()
+    logger.addHandler(handler)
+
+
+def get_session():
+    adapter = CacheControlAdapter(
+        DictCache(), cache_etags=True, serializer=None, heuristic=None
+    )
+    sess = requests.Session()
+    sess.mount("http://", adapter)
+    sess.mount("https://", adapter)
+
+    sess.cache_controller = adapter.controller
+    return sess
+
+
+def get_args():
+    parser = ArgumentParser()
+    parser.add_argument("url", help="The URL to try and cache")
+    return parser.parse_args()
+
+
+def main(args=None):
+    args = get_args()
+    sess = get_session()
+
+    # Make a request to get a response
+    resp = sess.get(args.url)
+
+    # Turn on logging
+    setup_logging()
+
+    # try setting the cache
+    sess.cache_controller.cache_response(resp.request, resp.raw)
+
+    # Now try to get it
+    if sess.cache_controller.cached_request(resp.request):
+        print("Cached!")
+    else:
+        print("Not cached :(")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/adapter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/adapter.py
new file mode 100644
index 0000000000000000000000000000000000000000..94c75e1a05b47922945c5233e90e9f936b108b66
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/adapter.py
@@ -0,0 +1,137 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import types
+import functools
+import zlib
+
+from pip._vendor.requests.adapters import HTTPAdapter
+
+from .controller import CacheController, PERMANENT_REDIRECT_STATUSES
+from .cache import DictCache
+from .filewrapper import CallbackFileWrapper
+
+
+class CacheControlAdapter(HTTPAdapter):
+    invalidating_methods = {"PUT", "PATCH", "DELETE"}
+
+    def __init__(
+        self,
+        cache=None,
+        cache_etags=True,
+        controller_class=None,
+        serializer=None,
+        heuristic=None,
+        cacheable_methods=None,
+        *args,
+        **kw
+    ):
+        super(CacheControlAdapter, self).__init__(*args, **kw)
+        self.cache = DictCache() if cache is None else cache
+        self.heuristic = heuristic
+        self.cacheable_methods = cacheable_methods or ("GET",)
+
+        controller_factory = controller_class or CacheController
+        self.controller = controller_factory(
+            self.cache, cache_etags=cache_etags, serializer=serializer
+        )
+
+    def send(self, request, cacheable_methods=None, **kw):
+        """
+        Send a request. Use the request information to see if it
+        exists in the cache and cache the response if we need to and can.
+        """
+        cacheable = cacheable_methods or self.cacheable_methods
+        if request.method in cacheable:
+            try:
+                cached_response = self.controller.cached_request(request)
+            except zlib.error:
+                cached_response = None
+            if cached_response:
+                return self.build_response(request, cached_response, from_cache=True)
+
+            # check for etags and add headers if appropriate
+            request.headers.update(self.controller.conditional_headers(request))
+
+        resp = super(CacheControlAdapter, self).send(request, **kw)
+
+        return resp
+
+    def build_response(
+        self, request, response, from_cache=False, cacheable_methods=None
+    ):
+        """
+        Build a response by making a request or using the cache.
+
+        This will end up calling send and returning a potentially
+        cached response
+        """
+        cacheable = cacheable_methods or self.cacheable_methods
+        if not from_cache and request.method in cacheable:
+            # Check for any heuristics that might update headers
+            # before trying to cache.
+            if self.heuristic:
+                response = self.heuristic.apply(response)
+
+            # apply any expiration heuristics
+            if response.status == 304:
+                # We must have sent an ETag request. This could mean
+                # that we've been expired already or that we simply
+                # have an etag. In either case, we want to try and
+                # update the cache if that is the case.
+                cached_response = self.controller.update_cached_response(
+                    request, response
+                )
+
+                if cached_response is not response:
+                    from_cache = True
+
+                # We are done with the server response, read a
+                # possible response body (compliant servers will
+                # not return one, but we cannot be 100% sure) and
+                # release the connection back to the pool.
+                response.read(decode_content=False)
+                response.release_conn()
+
+                response = cached_response
+
+            # We always cache the 301 responses
+            elif int(response.status) in PERMANENT_REDIRECT_STATUSES:
+                self.controller.cache_response(request, response)
+            else:
+                # Wrap the response file with a wrapper that will cache the
+                #   response when the stream has been consumed.
+                response._fp = CallbackFileWrapper(
+                    response._fp,
+                    functools.partial(
+                        self.controller.cache_response, request, response
+                    ),
+                )
+                if response.chunked:
+                    super_update_chunk_length = response._update_chunk_length
+
+                    def _update_chunk_length(self):
+                        super_update_chunk_length()
+                        if self.chunk_left == 0:
+                            self._fp._close()
+
+                    response._update_chunk_length = types.MethodType(
+                        _update_chunk_length, response
+                    )
+
+        resp = super(CacheControlAdapter, self).build_response(request, response)
+
+        # See if we should invalidate the cache.
+        if request.method in self.invalidating_methods and resp.ok:
+            cache_url = self.controller.cache_url(request.url)
+            self.cache.delete(cache_url)
+
+        # Give the request a from_cache attr to let people use it
+        resp.from_cache = from_cache
+
+        return resp
+
+    def close(self):
+        self.cache.close()
+        super(CacheControlAdapter, self).close()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/cache.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..2a965f595ff0756002e2a2c79da551fa8c8fff25
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/cache.py
@@ -0,0 +1,65 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""
+The cache object API for implementing caches. The default is a thread
+safe in-memory dictionary.
+"""
+from threading import Lock
+
+
+class BaseCache(object):
+
+    def get(self, key):
+        raise NotImplementedError()
+
+    def set(self, key, value, expires=None):
+        raise NotImplementedError()
+
+    def delete(self, key):
+        raise NotImplementedError()
+
+    def close(self):
+        pass
+
+
+class DictCache(BaseCache):
+
+    def __init__(self, init_dict=None):
+        self.lock = Lock()
+        self.data = init_dict or {}
+
+    def get(self, key):
+        return self.data.get(key, None)
+
+    def set(self, key, value, expires=None):
+        with self.lock:
+            self.data.update({key: value})
+
+    def delete(self, key):
+        with self.lock:
+            if key in self.data:
+                self.data.pop(key)
+
+
+class SeparateBodyBaseCache(BaseCache):
+    """
+    In this variant, the body is not stored mixed in with the metadata, but is
+    passed in (as a bytes-like object) in a separate call to ``set_body()``.
+
+    That is, the expected interaction pattern is::
+
+        cache.set(key, serialized_metadata)
+        cache.set_body(key)
+
+    Similarly, the body should be loaded separately via ``get_body()``.
+    """
+    def set_body(self, key, body):
+        raise NotImplementedError()
+
+    def get_body(self, key):
+        """
+        Return the body as file-like object.
+        """
+        raise NotImplementedError()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..37827291fb5a76d7ef9a7a3a695710b2074ca09a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/__init__.py
@@ -0,0 +1,9 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from .file_cache import FileCache, SeparateBodyFileCache
+from .redis_cache import RedisCache
+
+
+__all__ = ["FileCache", "SeparateBodyFileCache", "RedisCache"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/file_cache.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/file_cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..f1ddb2ebdf9eb702718fd31e09ff92b592da519f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/file_cache.py
@@ -0,0 +1,188 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import hashlib
+import os
+from textwrap import dedent
+
+from ..cache import BaseCache, SeparateBodyBaseCache
+from ..controller import CacheController
+
+try:
+    FileNotFoundError
+except NameError:
+    # py2.X
+    FileNotFoundError = (IOError, OSError)
+
+
+def _secure_open_write(filename, fmode):
+    # We only want to write to this file, so open it in write only mode
+    flags = os.O_WRONLY
+
+    # os.O_CREAT | os.O_EXCL will fail if the file already exists, so we only
+    #  will open *new* files.
+    # We specify this because we want to ensure that the mode we pass is the
+    # mode of the file.
+    flags |= os.O_CREAT | os.O_EXCL
+
+    # Do not follow symlinks to prevent someone from making a symlink that
+    # we follow and insecurely open a cache file.
+    if hasattr(os, "O_NOFOLLOW"):
+        flags |= os.O_NOFOLLOW
+
+    # On Windows we'll mark this file as binary
+    if hasattr(os, "O_BINARY"):
+        flags |= os.O_BINARY
+
+    # Before we open our file, we want to delete any existing file that is
+    # there
+    try:
+        os.remove(filename)
+    except (IOError, OSError):
+        # The file must not exist already, so we can just skip ahead to opening
+        pass
+
+    # Open our file, the use of os.O_CREAT | os.O_EXCL will ensure that if a
+    # race condition happens between the os.remove and this line, that an
+    # error will be raised. Because we utilize a lockfile this should only
+    # happen if someone is attempting to attack us.
+    fd = os.open(filename, flags, fmode)
+    try:
+        return os.fdopen(fd, "wb")
+
+    except:
+        # An error occurred wrapping our FD in a file object
+        os.close(fd)
+        raise
+
+
+class _FileCacheMixin:
+    """Shared implementation for both FileCache variants."""
+
+    def __init__(
+        self,
+        directory,
+        forever=False,
+        filemode=0o0600,
+        dirmode=0o0700,
+        use_dir_lock=None,
+        lock_class=None,
+    ):
+
+        if use_dir_lock is not None and lock_class is not None:
+            raise ValueError("Cannot use use_dir_lock and lock_class together")
+
+        try:
+            from lockfile import LockFile
+            from lockfile.mkdirlockfile import MkdirLockFile
+        except ImportError:
+            notice = dedent(
+                """
+            NOTE: In order to use the FileCache you must have
+            lockfile installed. You can install it via pip:
+              pip install lockfile
+            """
+            )
+            raise ImportError(notice)
+
+        else:
+            if use_dir_lock:
+                lock_class = MkdirLockFile
+
+            elif lock_class is None:
+                lock_class = LockFile
+
+        self.directory = directory
+        self.forever = forever
+        self.filemode = filemode
+        self.dirmode = dirmode
+        self.lock_class = lock_class
+
+    @staticmethod
+    def encode(x):
+        return hashlib.sha224(x.encode()).hexdigest()
+
+    def _fn(self, name):
+        # NOTE: This method should not change as some may depend on it.
+        #       See: https://github.com/ionrock/cachecontrol/issues/63
+        hashed = self.encode(name)
+        parts = list(hashed[:5]) + [hashed]
+        return os.path.join(self.directory, *parts)
+
+    def get(self, key):
+        name = self._fn(key)
+        try:
+            with open(name, "rb") as fh:
+                return fh.read()
+
+        except FileNotFoundError:
+            return None
+
+    def set(self, key, value, expires=None):
+        name = self._fn(key)
+        self._write(name, value)
+
+    def _write(self, path, data: bytes):
+        """
+        Safely write the data to the given path.
+        """
+        # Make sure the directory exists
+        try:
+            os.makedirs(os.path.dirname(path), self.dirmode)
+        except (IOError, OSError):
+            pass
+
+        with self.lock_class(path) as lock:
+            # Write our actual file
+            with _secure_open_write(lock.path, self.filemode) as fh:
+                fh.write(data)
+
+    def _delete(self, key, suffix):
+        name = self._fn(key) + suffix
+        if not self.forever:
+            try:
+                os.remove(name)
+            except FileNotFoundError:
+                pass
+
+
+class FileCache(_FileCacheMixin, BaseCache):
+    """
+    Traditional FileCache: body is stored in memory, so not suitable for large
+    downloads.
+    """
+
+    def delete(self, key):
+        self._delete(key, "")
+
+
+class SeparateBodyFileCache(_FileCacheMixin, SeparateBodyBaseCache):
+    """
+    Memory-efficient FileCache: body is stored in a separate file, reducing
+    peak memory usage.
+    """
+
+    def get_body(self, key):
+        name = self._fn(key) + ".body"
+        try:
+            return open(name, "rb")
+        except FileNotFoundError:
+            return None
+
+    def set_body(self, key, body):
+        name = self._fn(key) + ".body"
+        self._write(name, body)
+
+    def delete(self, key):
+        self._delete(key, "")
+        self._delete(key, ".body")
+
+
+def url_to_file_path(url, filecache):
+    """Return the file cache path based on the URL.
+
+    This does not ensure the file exists!
+    """
+    key = CacheController.cache_url(url)
+    return filecache._fn(key)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/redis_cache.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/redis_cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..2cba4b0708032d62b4c1278f99e5db87ed8d90fe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/caches/redis_cache.py
@@ -0,0 +1,39 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import division
+
+from datetime import datetime
+from pip._vendor.cachecontrol.cache import BaseCache
+
+
+class RedisCache(BaseCache):
+
+    def __init__(self, conn):
+        self.conn = conn
+
+    def get(self, key):
+        return self.conn.get(key)
+
+    def set(self, key, value, expires=None):
+        if not expires:
+            self.conn.set(key, value)
+        elif isinstance(expires, datetime):
+            expires = expires - datetime.utcnow()
+            self.conn.setex(key, int(expires.total_seconds()), value)
+        else:
+            self.conn.setex(key, expires, value)
+
+    def delete(self, key):
+        self.conn.delete(key)
+
+    def clear(self):
+        """Helper for clearing all the keys in a database. Use with
+        caution!"""
+        for key in self.conn.keys():
+            self.conn.delete(key)
+
+    def close(self):
+        """Redis uses connection pooling, no need to close the connection."""
+        pass
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..ccec9379dba2b03015ce123dd04a042f32431235
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/compat.py
@@ -0,0 +1,32 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+try:
+    from urllib.parse import urljoin
+except ImportError:
+    from urlparse import urljoin
+
+
+try:
+    import cPickle as pickle
+except ImportError:
+    import pickle
+
+# Handle the case where the requests module has been patched to not have
+# urllib3 bundled as part of its source.
+try:
+    from pip._vendor.requests.packages.urllib3.response import HTTPResponse
+except ImportError:
+    from pip._vendor.urllib3.response import HTTPResponse
+
+try:
+    from pip._vendor.requests.packages.urllib3.util import is_fp_closed
+except ImportError:
+    from pip._vendor.urllib3.util import is_fp_closed
+
+# Replicate some six behaviour
+try:
+    text_type = unicode
+except NameError:
+    text_type = str
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/controller.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/controller.py
new file mode 100644
index 0000000000000000000000000000000000000000..7f23529f1155cd3bbfde335ccdb7fc483b9d2d19
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/controller.py
@@ -0,0 +1,439 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""
+The httplib2 algorithms ported for use with requests.
+"""
+import logging
+import re
+import calendar
+import time
+from email.utils import parsedate_tz
+
+from pip._vendor.requests.structures import CaseInsensitiveDict
+
+from .cache import DictCache, SeparateBodyBaseCache
+from .serialize import Serializer
+
+
+logger = logging.getLogger(__name__)
+
+URI = re.compile(r"^(([^:/?#]+):)?(//([^/?#]*))?([^?#]*)(\?([^#]*))?(#(.*))?")
+
+PERMANENT_REDIRECT_STATUSES = (301, 308)
+
+
+def parse_uri(uri):
+    """Parses a URI using the regex given in Appendix B of RFC 3986.
+
+    (scheme, authority, path, query, fragment) = parse_uri(uri)
+    """
+    groups = URI.match(uri).groups()
+    return (groups[1], groups[3], groups[4], groups[6], groups[8])
+
+
+class CacheController(object):
+    """An interface to see if request should cached or not."""
+
+    def __init__(
+        self, cache=None, cache_etags=True, serializer=None, status_codes=None
+    ):
+        self.cache = DictCache() if cache is None else cache
+        self.cache_etags = cache_etags
+        self.serializer = serializer or Serializer()
+        self.cacheable_status_codes = status_codes or (200, 203, 300, 301, 308)
+
+    @classmethod
+    def _urlnorm(cls, uri):
+        """Normalize the URL to create a safe key for the cache"""
+        (scheme, authority, path, query, fragment) = parse_uri(uri)
+        if not scheme or not authority:
+            raise Exception("Only absolute URIs are allowed. uri = %s" % uri)
+
+        scheme = scheme.lower()
+        authority = authority.lower()
+
+        if not path:
+            path = "/"
+
+        # Could do syntax based normalization of the URI before
+        # computing the digest. See Section 6.2.2 of Std 66.
+        request_uri = query and "?".join([path, query]) or path
+        defrag_uri = scheme + "://" + authority + request_uri
+
+        return defrag_uri
+
+    @classmethod
+    def cache_url(cls, uri):
+        return cls._urlnorm(uri)
+
+    def parse_cache_control(self, headers):
+        known_directives = {
+            # https://tools.ietf.org/html/rfc7234#section-5.2
+            "max-age": (int, True),
+            "max-stale": (int, False),
+            "min-fresh": (int, True),
+            "no-cache": (None, False),
+            "no-store": (None, False),
+            "no-transform": (None, False),
+            "only-if-cached": (None, False),
+            "must-revalidate": (None, False),
+            "public": (None, False),
+            "private": (None, False),
+            "proxy-revalidate": (None, False),
+            "s-maxage": (int, True),
+        }
+
+        cc_headers = headers.get("cache-control", headers.get("Cache-Control", ""))
+
+        retval = {}
+
+        for cc_directive in cc_headers.split(","):
+            if not cc_directive.strip():
+                continue
+
+            parts = cc_directive.split("=", 1)
+            directive = parts[0].strip()
+
+            try:
+                typ, required = known_directives[directive]
+            except KeyError:
+                logger.debug("Ignoring unknown cache-control directive: %s", directive)
+                continue
+
+            if not typ or not required:
+                retval[directive] = None
+            if typ:
+                try:
+                    retval[directive] = typ(parts[1].strip())
+                except IndexError:
+                    if required:
+                        logger.debug(
+                            "Missing value for cache-control " "directive: %s",
+                            directive,
+                        )
+                except ValueError:
+                    logger.debug(
+                        "Invalid value for cache-control directive " "%s, must be %s",
+                        directive,
+                        typ.__name__,
+                    )
+
+        return retval
+
+    def cached_request(self, request):
+        """
+        Return a cached response if it exists in the cache, otherwise
+        return False.
+        """
+        cache_url = self.cache_url(request.url)
+        logger.debug('Looking up "%s" in the cache', cache_url)
+        cc = self.parse_cache_control(request.headers)
+
+        # Bail out if the request insists on fresh data
+        if "no-cache" in cc:
+            logger.debug('Request header has "no-cache", cache bypassed')
+            return False
+
+        if "max-age" in cc and cc["max-age"] == 0:
+            logger.debug('Request header has "max_age" as 0, cache bypassed')
+            return False
+
+        # Request allows serving from the cache, let's see if we find something
+        cache_data = self.cache.get(cache_url)
+        if cache_data is None:
+            logger.debug("No cache entry available")
+            return False
+
+        if isinstance(self.cache, SeparateBodyBaseCache):
+            body_file = self.cache.get_body(cache_url)
+        else:
+            body_file = None
+
+        # Check whether it can be deserialized
+        resp = self.serializer.loads(request, cache_data, body_file)
+        if not resp:
+            logger.warning("Cache entry deserialization failed, entry ignored")
+            return False
+
+        # If we have a cached permanent redirect, return it immediately. We
+        # don't need to test our response for other headers b/c it is
+        # intrinsically "cacheable" as it is Permanent.
+        #
+        # See:
+        #   https://tools.ietf.org/html/rfc7231#section-6.4.2
+        #
+        # Client can try to refresh the value by repeating the request
+        # with cache busting headers as usual (ie no-cache).
+        if int(resp.status) in PERMANENT_REDIRECT_STATUSES:
+            msg = (
+                "Returning cached permanent redirect response "
+                "(ignoring date and etag information)"
+            )
+            logger.debug(msg)
+            return resp
+
+        headers = CaseInsensitiveDict(resp.headers)
+        if not headers or "date" not in headers:
+            if "etag" not in headers:
+                # Without date or etag, the cached response can never be used
+                # and should be deleted.
+                logger.debug("Purging cached response: no date or etag")
+                self.cache.delete(cache_url)
+            logger.debug("Ignoring cached response: no date")
+            return False
+
+        now = time.time()
+        date = calendar.timegm(parsedate_tz(headers["date"]))
+        current_age = max(0, now - date)
+        logger.debug("Current age based on date: %i", current_age)
+
+        # TODO: There is an assumption that the result will be a
+        #       urllib3 response object. This may not be best since we
+        #       could probably avoid instantiating or constructing the
+        #       response until we know we need it.
+        resp_cc = self.parse_cache_control(headers)
+
+        # determine freshness
+        freshness_lifetime = 0
+
+        # Check the max-age pragma in the cache control header
+        if "max-age" in resp_cc:
+            freshness_lifetime = resp_cc["max-age"]
+            logger.debug("Freshness lifetime from max-age: %i", freshness_lifetime)
+
+        # If there isn't a max-age, check for an expires header
+        elif "expires" in headers:
+            expires = parsedate_tz(headers["expires"])
+            if expires is not None:
+                expire_time = calendar.timegm(expires) - date
+                freshness_lifetime = max(0, expire_time)
+                logger.debug("Freshness lifetime from expires: %i", freshness_lifetime)
+
+        # Determine if we are setting freshness limit in the
+        # request. Note, this overrides what was in the response.
+        if "max-age" in cc:
+            freshness_lifetime = cc["max-age"]
+            logger.debug(
+                "Freshness lifetime from request max-age: %i", freshness_lifetime
+            )
+
+        if "min-fresh" in cc:
+            min_fresh = cc["min-fresh"]
+            # adjust our current age by our min fresh
+            current_age += min_fresh
+            logger.debug("Adjusted current age from min-fresh: %i", current_age)
+
+        # Return entry if it is fresh enough
+        if freshness_lifetime > current_age:
+            logger.debug('The response is "fresh", returning cached response')
+            logger.debug("%i > %i", freshness_lifetime, current_age)
+            return resp
+
+        # we're not fresh. If we don't have an Etag, clear it out
+        if "etag" not in headers:
+            logger.debug('The cached response is "stale" with no etag, purging')
+            self.cache.delete(cache_url)
+
+        # return the original handler
+        return False
+
+    def conditional_headers(self, request):
+        cache_url = self.cache_url(request.url)
+        resp = self.serializer.loads(request, self.cache.get(cache_url))
+        new_headers = {}
+
+        if resp:
+            headers = CaseInsensitiveDict(resp.headers)
+
+            if "etag" in headers:
+                new_headers["If-None-Match"] = headers["ETag"]
+
+            if "last-modified" in headers:
+                new_headers["If-Modified-Since"] = headers["Last-Modified"]
+
+        return new_headers
+
+    def _cache_set(self, cache_url, request, response, body=None, expires_time=None):
+        """
+        Store the data in the cache.
+        """
+        if isinstance(self.cache, SeparateBodyBaseCache):
+            # We pass in the body separately; just put a placeholder empty
+            # string in the metadata.
+            self.cache.set(
+                cache_url,
+                self.serializer.dumps(request, response, b""),
+                expires=expires_time,
+            )
+            self.cache.set_body(cache_url, body)
+        else:
+            self.cache.set(
+                cache_url,
+                self.serializer.dumps(request, response, body),
+                expires=expires_time,
+            )
+
+    def cache_response(self, request, response, body=None, status_codes=None):
+        """
+        Algorithm for caching requests.
+
+        This assumes a requests Response object.
+        """
+        # From httplib2: Don't cache 206's since we aren't going to
+        #                handle byte range requests
+        cacheable_status_codes = status_codes or self.cacheable_status_codes
+        if response.status not in cacheable_status_codes:
+            logger.debug(
+                "Status code %s not in %s", response.status, cacheable_status_codes
+            )
+            return
+
+        response_headers = CaseInsensitiveDict(response.headers)
+
+        if "date" in response_headers:
+            date = calendar.timegm(parsedate_tz(response_headers["date"]))
+        else:
+            date = 0
+
+        # If we've been given a body, our response has a Content-Length, that
+        # Content-Length is valid then we can check to see if the body we've
+        # been given matches the expected size, and if it doesn't we'll just
+        # skip trying to cache it.
+        if (
+            body is not None
+            and "content-length" in response_headers
+            and response_headers["content-length"].isdigit()
+            and int(response_headers["content-length"]) != len(body)
+        ):
+            return
+
+        cc_req = self.parse_cache_control(request.headers)
+        cc = self.parse_cache_control(response_headers)
+
+        cache_url = self.cache_url(request.url)
+        logger.debug('Updating cache with response from "%s"', cache_url)
+
+        # Delete it from the cache if we happen to have it stored there
+        no_store = False
+        if "no-store" in cc:
+            no_store = True
+            logger.debug('Response header has "no-store"')
+        if "no-store" in cc_req:
+            no_store = True
+            logger.debug('Request header has "no-store"')
+        if no_store and self.cache.get(cache_url):
+            logger.debug('Purging existing cache entry to honor "no-store"')
+            self.cache.delete(cache_url)
+        if no_store:
+            return
+
+        # https://tools.ietf.org/html/rfc7234#section-4.1:
+        # A Vary header field-value of "*" always fails to match.
+        # Storing such a response leads to a deserialization warning
+        # during cache lookup and is not allowed to ever be served,
+        # so storing it can be avoided.
+        if "*" in response_headers.get("vary", ""):
+            logger.debug('Response header has "Vary: *"')
+            return
+
+        # If we've been given an etag, then keep the response
+        if self.cache_etags and "etag" in response_headers:
+            expires_time = 0
+            if response_headers.get("expires"):
+                expires = parsedate_tz(response_headers["expires"])
+                if expires is not None:
+                    expires_time = calendar.timegm(expires) - date
+
+            expires_time = max(expires_time, 14 * 86400)
+
+            logger.debug("etag object cached for {0} seconds".format(expires_time))
+            logger.debug("Caching due to etag")
+            self._cache_set(cache_url, request, response, body, expires_time)
+
+        # Add to the cache any permanent redirects. We do this before looking
+        # that the Date headers.
+        elif int(response.status) in PERMANENT_REDIRECT_STATUSES:
+            logger.debug("Caching permanent redirect")
+            self._cache_set(cache_url, request, response, b"")
+
+        # Add to the cache if the response headers demand it. If there
+        # is no date header then we can't do anything about expiring
+        # the cache.
+        elif "date" in response_headers:
+            date = calendar.timegm(parsedate_tz(response_headers["date"]))
+            # cache when there is a max-age > 0
+            if "max-age" in cc and cc["max-age"] > 0:
+                logger.debug("Caching b/c date exists and max-age > 0")
+                expires_time = cc["max-age"]
+                self._cache_set(
+                    cache_url,
+                    request,
+                    response,
+                    body,
+                    expires_time,
+                )
+
+            # If the request can expire, it means we should cache it
+            # in the meantime.
+            elif "expires" in response_headers:
+                if response_headers["expires"]:
+                    expires = parsedate_tz(response_headers["expires"])
+                    if expires is not None:
+                        expires_time = calendar.timegm(expires) - date
+                    else:
+                        expires_time = None
+
+                    logger.debug(
+                        "Caching b/c of expires header. expires in {0} seconds".format(
+                            expires_time
+                        )
+                    )
+                    self._cache_set(
+                        cache_url,
+                        request,
+                        response,
+                        body,
+                        expires_time,
+                    )
+
+    def update_cached_response(self, request, response):
+        """On a 304 we will get a new set of headers that we want to
+        update our cached value with, assuming we have one.
+
+        This should only ever be called when we've sent an ETag and
+        gotten a 304 as the response.
+        """
+        cache_url = self.cache_url(request.url)
+
+        cached_response = self.serializer.loads(request, self.cache.get(cache_url))
+
+        if not cached_response:
+            # we didn't have a cached response
+            return response
+
+        # Lets update our headers with the headers from the new request:
+        # http://tools.ietf.org/html/draft-ietf-httpbis-p4-conditional-26#section-4.1
+        #
+        # The server isn't supposed to send headers that would make
+        # the cached body invalid. But... just in case, we'll be sure
+        # to strip out ones we know that might be problmatic due to
+        # typical assumptions.
+        excluded_headers = ["content-length"]
+
+        cached_response.headers.update(
+            dict(
+                (k, v)
+                for k, v in response.headers.items()
+                if k.lower() not in excluded_headers
+            )
+        )
+
+        # we want a 200 b/c we have content via the cache
+        cached_response.status = 200
+
+        # update our cache
+        self._cache_set(cache_url, request, cached_response)
+
+        return cached_response
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/filewrapper.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/filewrapper.py
new file mode 100644
index 0000000000000000000000000000000000000000..f5ed5f6f6ec0eae90a9f48753622b2b5ee5d4a4f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/filewrapper.py
@@ -0,0 +1,111 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from tempfile import NamedTemporaryFile
+import mmap
+
+
+class CallbackFileWrapper(object):
+    """
+    Small wrapper around a fp object which will tee everything read into a
+    buffer, and when that file is closed it will execute a callback with the
+    contents of that buffer.
+
+    All attributes are proxied to the underlying file object.
+
+    This class uses members with a double underscore (__) leading prefix so as
+    not to accidentally shadow an attribute.
+
+    The data is stored in a temporary file until it is all available.  As long
+    as the temporary files directory is disk-based (sometimes it's a
+    memory-backed-``tmpfs`` on Linux), data will be unloaded to disk if memory
+    pressure is high.  For small files the disk usually won't be used at all,
+    it'll all be in the filesystem memory cache, so there should be no
+    performance impact.
+    """
+
+    def __init__(self, fp, callback):
+        self.__buf = NamedTemporaryFile("rb+", delete=True)
+        self.__fp = fp
+        self.__callback = callback
+
+    def __getattr__(self, name):
+        # The vaguaries of garbage collection means that self.__fp is
+        # not always set.  By using __getattribute__ and the private
+        # name[0] allows looking up the attribute value and raising an
+        # AttributeError when it doesn't exist. This stop thigns from
+        # infinitely recursing calls to getattr in the case where
+        # self.__fp hasn't been set.
+        #
+        # [0] https://docs.python.org/2/reference/expressions.html#atom-identifiers
+        fp = self.__getattribute__("_CallbackFileWrapper__fp")
+        return getattr(fp, name)
+
+    def __is_fp_closed(self):
+        try:
+            return self.__fp.fp is None
+
+        except AttributeError:
+            pass
+
+        try:
+            return self.__fp.closed
+
+        except AttributeError:
+            pass
+
+        # We just don't cache it then.
+        # TODO: Add some logging here...
+        return False
+
+    def _close(self):
+        if self.__callback:
+            if self.__buf.tell() == 0:
+                # Empty file:
+                result = b""
+            else:
+                # Return the data without actually loading it into memory,
+                # relying on Python's buffer API and mmap(). mmap() just gives
+                # a view directly into the filesystem's memory cache, so it
+                # doesn't result in duplicate memory use.
+                self.__buf.seek(0, 0)
+                result = memoryview(
+                    mmap.mmap(self.__buf.fileno(), 0, access=mmap.ACCESS_READ)
+                )
+            self.__callback(result)
+
+        # We assign this to None here, because otherwise we can get into
+        # really tricky problems where the CPython interpreter dead locks
+        # because the callback is holding a reference to something which
+        # has a __del__ method. Setting this to None breaks the cycle
+        # and allows the garbage collector to do it's thing normally.
+        self.__callback = None
+
+        # Closing the temporary file releases memory and frees disk space.
+        # Important when caching big files.
+        self.__buf.close()
+
+    def read(self, amt=None):
+        data = self.__fp.read(amt)
+        if data:
+            # We may be dealing with b'', a sign that things are over:
+            # it's passed e.g. after we've already closed self.__buf.
+            self.__buf.write(data)
+        if self.__is_fp_closed():
+            self._close()
+
+        return data
+
+    def _safe_read(self, amt):
+        data = self.__fp._safe_read(amt)
+        if amt == 2 and data == b"\r\n":
+            # urllib executes this read to toss the CRLF at the end
+            # of the chunk.
+            return data
+
+        self.__buf.write(data)
+        if self.__is_fp_closed():
+            self._close()
+
+        return data
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/heuristics.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/heuristics.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebe4a96f589474f6f441858de2bb961c5e473c6d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/heuristics.py
@@ -0,0 +1,139 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import calendar
+import time
+
+from email.utils import formatdate, parsedate, parsedate_tz
+
+from datetime import datetime, timedelta
+
+TIME_FMT = "%a, %d %b %Y %H:%M:%S GMT"
+
+
+def expire_after(delta, date=None):
+    date = date or datetime.utcnow()
+    return date + delta
+
+
+def datetime_to_header(dt):
+    return formatdate(calendar.timegm(dt.timetuple()))
+
+
+class BaseHeuristic(object):
+
+    def warning(self, response):
+        """
+        Return a valid 1xx warning header value describing the cache
+        adjustments.
+
+        The response is provided too allow warnings like 113
+        http://tools.ietf.org/html/rfc7234#section-5.5.4 where we need
+        to explicitly say response is over 24 hours old.
+        """
+        return '110 - "Response is Stale"'
+
+    def update_headers(self, response):
+        """Update the response headers with any new headers.
+
+        NOTE: This SHOULD always include some Warning header to
+              signify that the response was cached by the client, not
+              by way of the provided headers.
+        """
+        return {}
+
+    def apply(self, response):
+        updated_headers = self.update_headers(response)
+
+        if updated_headers:
+            response.headers.update(updated_headers)
+            warning_header_value = self.warning(response)
+            if warning_header_value is not None:
+                response.headers.update({"Warning": warning_header_value})
+
+        return response
+
+
+class OneDayCache(BaseHeuristic):
+    """
+    Cache the response by providing an expires 1 day in the
+    future.
+    """
+
+    def update_headers(self, response):
+        headers = {}
+
+        if "expires" not in response.headers:
+            date = parsedate(response.headers["date"])
+            expires = expire_after(timedelta(days=1), date=datetime(*date[:6]))
+            headers["expires"] = datetime_to_header(expires)
+            headers["cache-control"] = "public"
+        return headers
+
+
+class ExpiresAfter(BaseHeuristic):
+    """
+    Cache **all** requests for a defined time period.
+    """
+
+    def __init__(self, **kw):
+        self.delta = timedelta(**kw)
+
+    def update_headers(self, response):
+        expires = expire_after(self.delta)
+        return {"expires": datetime_to_header(expires), "cache-control": "public"}
+
+    def warning(self, response):
+        tmpl = "110 - Automatically cached for %s. Response might be stale"
+        return tmpl % self.delta
+
+
+class LastModified(BaseHeuristic):
+    """
+    If there is no Expires header already, fall back on Last-Modified
+    using the heuristic from
+    http://tools.ietf.org/html/rfc7234#section-4.2.2
+    to calculate a reasonable value.
+
+    Firefox also does something like this per
+    https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching_FAQ
+    http://lxr.mozilla.org/mozilla-release/source/netwerk/protocol/http/nsHttpResponseHead.cpp#397
+    Unlike mozilla we limit this to 24-hr.
+    """
+    cacheable_by_default_statuses = {
+        200, 203, 204, 206, 300, 301, 404, 405, 410, 414, 501
+    }
+
+    def update_headers(self, resp):
+        headers = resp.headers
+
+        if "expires" in headers:
+            return {}
+
+        if "cache-control" in headers and headers["cache-control"] != "public":
+            return {}
+
+        if resp.status not in self.cacheable_by_default_statuses:
+            return {}
+
+        if "date" not in headers or "last-modified" not in headers:
+            return {}
+
+        date = calendar.timegm(parsedate_tz(headers["date"]))
+        last_modified = parsedate(headers["last-modified"])
+        if date is None or last_modified is None:
+            return {}
+
+        now = time.time()
+        current_age = max(0, now - date)
+        delta = date - calendar.timegm(last_modified)
+        freshness_lifetime = max(0, min(delta / 10, 24 * 3600))
+        if freshness_lifetime <= current_age:
+            return {}
+
+        expires = date + freshness_lifetime
+        return {"expires": time.strftime(TIME_FMT, time.gmtime(expires))}
+
+    def warning(self, resp):
+        return None
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/serialize.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/serialize.py
new file mode 100644
index 0000000000000000000000000000000000000000..7fe1a3e33a3adbfd9ad1126a22d7175154ebc200
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/serialize.py
@@ -0,0 +1,190 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import base64
+import io
+import json
+import zlib
+
+from pip._vendor import msgpack
+from pip._vendor.requests.structures import CaseInsensitiveDict
+
+from .compat import HTTPResponse, pickle, text_type
+
+
+def _b64_decode_bytes(b):
+    return base64.b64decode(b.encode("ascii"))
+
+
+def _b64_decode_str(s):
+    return _b64_decode_bytes(s).decode("utf8")
+
+
+_default_body_read = object()
+
+
+class Serializer(object):
+    def dumps(self, request, response, body=None):
+        response_headers = CaseInsensitiveDict(response.headers)
+
+        if body is None:
+            # When a body isn't passed in, we'll read the response. We
+            # also update the response with a new file handler to be
+            # sure it acts as though it was never read.
+            body = response.read(decode_content=False)
+            response._fp = io.BytesIO(body)
+
+        # NOTE: This is all a bit weird, but it's really important that on
+        #       Python 2.x these objects are unicode and not str, even when
+        #       they contain only ascii. The problem here is that msgpack
+        #       understands the difference between unicode and bytes and we
+        #       have it set to differentiate between them, however Python 2
+        #       doesn't know the difference. Forcing these to unicode will be
+        #       enough to have msgpack know the difference.
+        data = {
+            u"response": {
+                u"body": body,  # Empty bytestring if body is stored separately
+                u"headers": dict(
+                    (text_type(k), text_type(v)) for k, v in response.headers.items()
+                ),
+                u"status": response.status,
+                u"version": response.version,
+                u"reason": text_type(response.reason),
+                u"strict": response.strict,
+                u"decode_content": response.decode_content,
+            }
+        }
+
+        # Construct our vary headers
+        data[u"vary"] = {}
+        if u"vary" in response_headers:
+            varied_headers = response_headers[u"vary"].split(",")
+            for header in varied_headers:
+                header = text_type(header).strip()
+                header_value = request.headers.get(header, None)
+                if header_value is not None:
+                    header_value = text_type(header_value)
+                data[u"vary"][header] = header_value
+
+        return b",".join([b"cc=4", msgpack.dumps(data, use_bin_type=True)])
+
+    def loads(self, request, data, body_file=None):
+        # Short circuit if we've been given an empty set of data
+        if not data:
+            return
+
+        # Determine what version of the serializer the data was serialized
+        # with
+        try:
+            ver, data = data.split(b",", 1)
+        except ValueError:
+            ver = b"cc=0"
+
+        # Make sure that our "ver" is actually a version and isn't a false
+        # positive from a , being in the data stream.
+        if ver[:3] != b"cc=":
+            data = ver + data
+            ver = b"cc=0"
+
+        # Get the version number out of the cc=N
+        ver = ver.split(b"=", 1)[-1].decode("ascii")
+
+        # Dispatch to the actual load method for the given version
+        try:
+            return getattr(self, "_loads_v{}".format(ver))(request, data, body_file)
+
+        except AttributeError:
+            # This is a version we don't have a loads function for, so we'll
+            # just treat it as a miss and return None
+            return
+
+    def prepare_response(self, request, cached, body_file=None):
+        """Verify our vary headers match and construct a real urllib3
+        HTTPResponse object.
+        """
+        # Special case the '*' Vary value as it means we cannot actually
+        # determine if the cached response is suitable for this request.
+        # This case is also handled in the controller code when creating
+        # a cache entry, but is left here for backwards compatibility.
+        if "*" in cached.get("vary", {}):
+            return
+
+        # Ensure that the Vary headers for the cached response match our
+        # request
+        for header, value in cached.get("vary", {}).items():
+            if request.headers.get(header, None) != value:
+                return
+
+        body_raw = cached["response"].pop("body")
+
+        headers = CaseInsensitiveDict(data=cached["response"]["headers"])
+        if headers.get("transfer-encoding", "") == "chunked":
+            headers.pop("transfer-encoding")
+
+        cached["response"]["headers"] = headers
+
+        try:
+            if body_file is None:
+                body = io.BytesIO(body_raw)
+            else:
+                body = body_file
+        except TypeError:
+            # This can happen if cachecontrol serialized to v1 format (pickle)
+            # using Python 2. A Python 2 str(byte string) will be unpickled as
+            # a Python 3 str (unicode string), which will cause the above to
+            # fail with:
+            #
+            #     TypeError: 'str' does not support the buffer interface
+            body = io.BytesIO(body_raw.encode("utf8"))
+
+        return HTTPResponse(body=body, preload_content=False, **cached["response"])
+
+    def _loads_v0(self, request, data, body_file=None):
+        # The original legacy cache data. This doesn't contain enough
+        # information to construct everything we need, so we'll treat this as
+        # a miss.
+        return
+
+    def _loads_v1(self, request, data, body_file=None):
+        try:
+            cached = pickle.loads(data)
+        except ValueError:
+            return
+
+        return self.prepare_response(request, cached, body_file)
+
+    def _loads_v2(self, request, data, body_file=None):
+        assert body_file is None
+        try:
+            cached = json.loads(zlib.decompress(data).decode("utf8"))
+        except (ValueError, zlib.error):
+            return
+
+        # We need to decode the items that we've base64 encoded
+        cached["response"]["body"] = _b64_decode_bytes(cached["response"]["body"])
+        cached["response"]["headers"] = dict(
+            (_b64_decode_str(k), _b64_decode_str(v))
+            for k, v in cached["response"]["headers"].items()
+        )
+        cached["response"]["reason"] = _b64_decode_str(cached["response"]["reason"])
+        cached["vary"] = dict(
+            (_b64_decode_str(k), _b64_decode_str(v) if v is not None else v)
+            for k, v in cached["vary"].items()
+        )
+
+        return self.prepare_response(request, cached, body_file)
+
+    def _loads_v3(self, request, data, body_file):
+        # Due to Python 2 encoding issues, it's impossible to know for sure
+        # exactly how to load v3 entries, thus we'll treat these as a miss so
+        # that they get rewritten out as v4 entries.
+        return
+
+    def _loads_v4(self, request, data, body_file=None):
+        try:
+            cached = msgpack.loads(data, raw=False)
+        except ValueError:
+            return
+
+        return self.prepare_response(request, cached, body_file)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/wrapper.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/wrapper.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6ee7f2039801c9792dfe6e473843fb0a4bc4a5b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/cachecontrol/wrapper.py
@@ -0,0 +1,33 @@
+# SPDX-FileCopyrightText: 2015 Eric Larson
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from .adapter import CacheControlAdapter
+from .cache import DictCache
+
+
+def CacheControl(
+    sess,
+    cache=None,
+    cache_etags=True,
+    serializer=None,
+    heuristic=None,
+    controller_class=None,
+    adapter_class=None,
+    cacheable_methods=None,
+):
+
+    cache = DictCache() if cache is None else cache
+    adapter_class = adapter_class or CacheControlAdapter
+    adapter = adapter_class(
+        cache,
+        cache_etags=cache_etags,
+        serializer=serializer,
+        heuristic=heuristic,
+        controller_class=controller_class,
+        cacheable_methods=cacheable_methods,
+    )
+    sess.mount("http://", adapter)
+    sess.mount("https://", adapter)
+
+    return sess
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a3546f12555c2c8d186489c5220e8d2e25f0b0a9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/__init__.py
@@ -0,0 +1,4 @@
+from .core import contents, where
+
+__all__ = ["contents", "where"]
+__version__ = "2022.12.07"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/__main__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..00376349e69ad8b9dbf401cddc34055951e4b02e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/__main__.py
@@ -0,0 +1,12 @@
+import argparse
+
+from pip._vendor.certifi import contents, where
+
+parser = argparse.ArgumentParser()
+parser.add_argument("-c", "--contents", action="store_true")
+args = parser.parse_args()
+
+if args.contents:
+    print(contents())
+else:
+    print(where())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/cacert.pem b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/cacert.pem
new file mode 100644
index 0000000000000000000000000000000000000000..df9e4e3c75560ac0381a036a20771674e8099e91
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/cacert.pem
@@ -0,0 +1,4527 @@
+
+# Issuer: CN=GlobalSign Root CA O=GlobalSign nv-sa OU=Root CA
+# Subject: CN=GlobalSign Root CA O=GlobalSign nv-sa OU=Root CA
+# Label: "GlobalSign Root CA"
+# Serial: 4835703278459707669005204
+# MD5 Fingerprint: 3e:45:52:15:09:51:92:e1:b7:5d:37:9f:b1:87:29:8a
+# SHA1 Fingerprint: b1:bc:96:8b:d4:f4:9d:62:2a:a8:9a:81:f2:15:01:52:a4:1d:82:9c
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Entrust.net Certification Authority (2048) O=Entrust.net OU=www.entrust.net/CPS_2048 incorp. by ref. (limits liab.)/(c) 1999 Entrust.net Limited
+# Subject: CN=Entrust.net Certification Authority (2048) O=Entrust.net OU=www.entrust.net/CPS_2048 incorp. by ref. (limits liab.)/(c) 1999 Entrust.net Limited
+# Label: "Entrust.net Premium 2048 Secure Server CA"
+# Serial: 946069240
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Baltimore CyberTrust Root O=Baltimore OU=CyberTrust
+# Subject: CN=Baltimore CyberTrust Root O=Baltimore OU=CyberTrust
+# Label: "Baltimore CyberTrust Root"
+# Serial: 33554617
+# MD5 Fingerprint: ac:b6:94:a5:9c:17:e0:d7:91:52:9b:b1:97:06:a6:e4
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Entrust Root Certification Authority O=Entrust, Inc. OU=www.entrust.net/CPS is incorporated by reference/(c) 2006 Entrust, Inc.
+# Subject: CN=Entrust Root Certification Authority O=Entrust, Inc. OU=www.entrust.net/CPS is incorporated by reference/(c) 2006 Entrust, Inc.
+# Label: "Entrust Root Certification Authority"
+# Serial: 1164660820
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=AAA Certificate Services O=Comodo CA Limited
+# Subject: CN=AAA Certificate Services O=Comodo CA Limited
+# Label: "Comodo AAA Services root"
+# Serial: 1
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=QuoVadis Root CA 2 O=QuoVadis Limited
+# Subject: CN=QuoVadis Root CA 2 O=QuoVadis Limited
+# Label: "QuoVadis Root CA 2"
+# Serial: 1289
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+-----BEGIN CERTIFICATE-----
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+# Label: "QuoVadis Root CA 3"
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+# Issuer: O=SECOM Trust.net OU=Security Communication RootCA1
+# Subject: O=SECOM Trust.net OU=Security Communication RootCA1
+# Label: "Security Communication Root CA"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=XRamp Global Certification Authority O=XRamp Security Services Inc OU=www.xrampsecurity.com
+# Subject: CN=XRamp Global Certification Authority O=XRamp Security Services Inc OU=www.xrampsecurity.com
+# Label: "XRamp Global CA Root"
+# Serial: 107108908803651509692980124233745014957
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: O=The Go Daddy Group, Inc. OU=Go Daddy Class 2 Certification Authority
+# Subject: O=The Go Daddy Group, Inc. OU=Go Daddy Class 2 Certification Authority
+# Label: "Go Daddy Class 2 CA"
+# Serial: 0
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: O=Starfield Technologies, Inc. OU=Starfield Class 2 Certification Authority
+# Subject: O=Starfield Technologies, Inc. OU=Starfield Class 2 Certification Authority
+# Label: "Starfield Class 2 CA"
+# Serial: 0
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert Assured ID Root CA O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert Assured ID Root CA O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert Assured ID Root CA"
+# Serial: 17154717934120587862167794914071425081
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert Global Root CA O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert Global Root CA O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert Global Root CA"
+# Serial: 10944719598952040374951832963794454346
+# MD5 Fingerprint: 79:e4:a9:84:0d:7d:3a:96:d7:c0:4f:e2:43:4c:89:2e
+# SHA1 Fingerprint: a8:98:5d:3a:65:e5:e5:c4:b2:d7:d6:6d:40:c6:dd:2f:b1:9c:54:36
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert High Assurance EV Root CA O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert High Assurance EV Root CA O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert High Assurance EV Root CA"
+# Serial: 3553400076410547919724730734378100087
+# MD5 Fingerprint: d4:74:de:57:5c:39:b2:d3:9c:85:83:c5:c0:65:49:8a
+# SHA1 Fingerprint: 5f:b7:ee:06:33:e2:59:db:ad:0c:4c:9a:e6:d3:8f:1a:61:c7:dc:25
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SwissSign Gold CA - G2 O=SwissSign AG
+# Subject: CN=SwissSign Gold CA - G2 O=SwissSign AG
+# Label: "SwissSign Gold CA - G2"
+# Serial: 13492815561806991280
+# MD5 Fingerprint: 24:77:d9:a8:91:d1:3b:fa:88:2d:c2:ff:f8:cd:33:93
+# SHA1 Fingerprint: d8:c5:38:8a:b7:30:1b:1b:6e:d4:7a:e6:45:25:3a:6f:9f:1a:27:61
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SwissSign Silver CA - G2 O=SwissSign AG
+# Subject: CN=SwissSign Silver CA - G2 O=SwissSign AG
+# Label: "SwissSign Silver CA - G2"
+# Serial: 5700383053117599563
+# MD5 Fingerprint: e0:06:a1:c9:7d:cf:c9:fc:0d:c0:56:75:96:d8:62:13
+# SHA1 Fingerprint: 9b:aa:e5:9f:56:ee:21:cb:43:5a:be:25:93:df:a7:f0:40:d1:1d:cb
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SecureTrust CA O=SecureTrust Corporation
+# Subject: CN=SecureTrust CA O=SecureTrust Corporation
+# Label: "SecureTrust CA"
+# Serial: 17199774589125277788362757014266862032
+# MD5 Fingerprint: dc:32:c3:a7:6d:25:57:c7:68:09:9d:ea:2d:a9:a2:d1
+# SHA1 Fingerprint: 87:82:c6:c3:04:35:3b:cf:d2:96:92:d2:59:3e:7d:44:d9:34:ff:11
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=Secure Global CA O=SecureTrust Corporation
+# Subject: CN=Secure Global CA O=SecureTrust Corporation
+# Label: "Secure Global CA"
+# Serial: 9751836167731051554232119481456978597
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=COMODO Certification Authority O=COMODO CA Limited
+# Subject: CN=COMODO Certification Authority O=COMODO CA Limited
+# Label: "COMODO Certification Authority"
+# Serial: 104350513648249232941998508985834464573
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=COMODO ECC Certification Authority O=COMODO CA Limited
+# Subject: CN=COMODO ECC Certification Authority O=COMODO CA Limited
+# Label: "COMODO ECC Certification Authority"
+# Serial: 41578283867086692638256921589707938090
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Certigna O=Dhimyotis
+# Subject: CN=Certigna O=Dhimyotis
+# Label: "Certigna"
+# Serial: 18364802974209362175
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: O=Chunghwa Telecom Co., Ltd. OU=ePKI Root Certification Authority
+# Subject: O=Chunghwa Telecom Co., Ltd. OU=ePKI Root Certification Authority
+# Label: "ePKI Root Certification Authority"
+# Serial: 28956088682735189655030529057352760477
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: O=certSIGN OU=certSIGN ROOT CA
+# Subject: O=certSIGN OU=certSIGN ROOT CA
+# Label: "certSIGN ROOT CA"
+# Serial: 35210227249154
+# MD5 Fingerprint: 18:98:c0:d6:e9:3a:fc:f9:b0:f5:0c:f7:4b:01:44:17
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny O=NetLock Kft. OU=Tan\xfas\xedtv\xe1nykiad\xf3k (Certification Services)
+# Subject: CN=NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny O=NetLock Kft. OU=Tan\xfas\xedtv\xe1nykiad\xf3k (Certification Services)
+# Label: "NetLock Arany (Class Gold) F\u0151tan\xfas\xedtv\xe1ny"
+# Serial: 80544274841616
+# MD5 Fingerprint: c5:a1:b7:ff:73:dd:d6:d7:34:32:18:df:fc:3c:ad:88
+# SHA1 Fingerprint: 06:08:3f:59:3f:15:a1:04:a0:69:a4:6b:a9:03:d0:06:b7:97:09:91
+# SHA256 Fingerprint: 6c:61:da:c3:a2:de:f0:31:50:6b:e0:36:d2:a6:fe:40:19:94:fb:d1:3d:f9:c8:d4:66:59:92:74:c4:46:ec:98
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Hongkong Post Root CA 1 O=Hongkong Post
+# Subject: CN=Hongkong Post Root CA 1 O=Hongkong Post
+# Label: "Hongkong Post Root CA 1"
+# Serial: 1000
+# MD5 Fingerprint: a8:0d:6f:39:78:b9:43:6d:77:42:6d:98:5a:cc:23:ca
+# SHA1 Fingerprint: d6:da:a8:20:8d:09:d2:15:4d:24:b5:2f:cb:34:6e:b2:58:b2:8a:58
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SecureSign RootCA11 O=Japan Certification Services, Inc.
+# Subject: CN=SecureSign RootCA11 O=Japan Certification Services, Inc.
+# Label: "SecureSign RootCA11"
+# Serial: 1
+# MD5 Fingerprint: b7:52:74:e2:92:b4:80:93:f2:75:e4:cc:d7:f2:ea:26
+# SHA1 Fingerprint: 3b:c4:9f:48:f8:f3:73:a0:9c:1e:bd:f8:5b:b1:c3:65:c7:d8:11:b3
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Microsec e-Szigno Root CA 2009 O=Microsec Ltd.
+# Subject: CN=Microsec e-Szigno Root CA 2009 O=Microsec Ltd.
+# Label: "Microsec e-Szigno Root CA 2009"
+# Serial: 14014712776195784473
+# MD5 Fingerprint: f8:49:f4:03:bc:44:2d:83:be:48:69:7d:29:64:fc:b1
+# SHA1 Fingerprint: 89:df:74:fe:5c:f4:0f:4a:80:f9:e3:37:7d:54:da:91:e1:01:31:8e
+# SHA256 Fingerprint: 3c:5f:81:fe:a5:fa:b8:2c:64:bf:a2:ea:ec:af:cd:e8:e0:77:fc:86:20:a7:ca:e5:37:16:3d:f3:6e:db:f3:78
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R3
+# Subject: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R3
+# Label: "GlobalSign Root CA - R3"
+# Serial: 4835703278459759426209954
+# MD5 Fingerprint: c5:df:b8:49:ca:05:13:55:ee:2d:ba:1a:c3:3e:b0:28
+# SHA1 Fingerprint: d6:9b:56:11:48:f0:1c:77:c5:45:78:c1:09:26:df:5b:85:69:76:ad
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Autoridad de Certificacion Firmaprofesional CIF A62634068
+# Subject: CN=Autoridad de Certificacion Firmaprofesional CIF A62634068
+# Label: "Autoridad de Certificacion Firmaprofesional CIF A62634068"
+# Serial: 6047274297262753887
+# MD5 Fingerprint: 73:3a:74:7a:ec:bb:a3:96:a6:c2:e4:e2:c8:9b:c0:c3
+# SHA1 Fingerprint: ae:c5:fb:3f:c8:e1:bf:c4:e5:4f:03:07:5a:9a:e8:00:b7:f7:b6:fa
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+-----BEGIN CERTIFICATE-----
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+# Label: "Go Daddy Root Certificate Authority - G2"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Starfield Root Certificate Authority - G2 O=Starfield Technologies, Inc.
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+# Label: "Starfield Root Certificate Authority - G2"
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+-----BEGIN CERTIFICATE-----
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+# Label: "Starfield Services Root Certificate Authority - G2"
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+-----BEGIN CERTIFICATE-----
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+-----BEGIN CERTIFICATE-----
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+# Label: "AffirmTrust Networking"
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+-----BEGIN CERTIFICATE-----
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+# Label: "AffirmTrust Premium"
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+# Issuer: CN=AffirmTrust Premium ECC O=AffirmTrust
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+# Label: "AffirmTrust Premium ECC"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Certum Trusted Network CA O=Unizeto Technologies S.A. OU=Certum Certification Authority
+# Subject: CN=Certum Trusted Network CA O=Unizeto Technologies S.A. OU=Certum Certification Authority
+# Label: "Certum Trusted Network CA"
+# Serial: 279744
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=TWCA Root Certification Authority O=TAIWAN-CA OU=Root CA
+# Subject: CN=TWCA Root Certification Authority O=TAIWAN-CA OU=Root CA
+# Label: "TWCA Root Certification Authority"
+# Serial: 1
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+-----BEGIN CERTIFICATE-----
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+# Issuer: O=SECOM Trust Systems CO.,LTD. OU=Security Communication RootCA2
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+# Label: "Security Communication RootCA2"
+# Serial: 0
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+-----BEGIN CERTIFICATE-----
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+# Subject: CN=Actalis Authentication Root CA O=Actalis S.p.A./03358520967
+# Label: "Actalis Authentication Root CA"
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=Buypass Class 2 Root CA O=Buypass AS-983163327
+# Subject: CN=Buypass Class 2 Root CA O=Buypass AS-983163327
+# Label: "Buypass Class 2 Root CA"
+# Serial: 2
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Buypass Class 3 Root CA O=Buypass AS-983163327
+# Subject: CN=Buypass Class 3 Root CA O=Buypass AS-983163327
+# Label: "Buypass Class 3 Root CA"
+# Serial: 2
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=T-TeleSec GlobalRoot Class 3 O=T-Systems Enterprise Services GmbH OU=T-Systems Trust Center
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+# Label: "T-TeleSec GlobalRoot Class 3"
+# Serial: 1
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=D-TRUST Root Class 3 CA 2 2009 O=D-Trust GmbH
+# Subject: CN=D-TRUST Root Class 3 CA 2 2009 O=D-Trust GmbH
+# Label: "D-TRUST Root Class 3 CA 2 2009"
+# Serial: 623603
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=D-TRUST Root Class 3 CA 2 EV 2009 O=D-Trust GmbH
+# Subject: CN=D-TRUST Root Class 3 CA 2 EV 2009 O=D-Trust GmbH
+# Label: "D-TRUST Root Class 3 CA 2 EV 2009"
+# Serial: 623604
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=CA Disig Root R2 O=Disig a.s.
+# Subject: CN=CA Disig Root R2 O=Disig a.s.
+# Label: "CA Disig Root R2"
+# Serial: 10572350602393338211
+# MD5 Fingerprint: 26:01:fb:d8:27:a7:17:9a:45:54:38:1a:43:01:3b:03
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=ACCVRAIZ1 O=ACCV OU=PKIACCV
+# Subject: CN=ACCVRAIZ1 O=ACCV OU=PKIACCV
+# Label: "ACCVRAIZ1"
+# Serial: 6828503384748696800
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=TWCA Global Root CA O=TAIWAN-CA OU=Root CA
+# Subject: CN=TWCA Global Root CA O=TAIWAN-CA OU=Root CA
+# Label: "TWCA Global Root CA"
+# Serial: 3262
+# MD5 Fingerprint: f9:03:7e:cf:e6:9e:3c:73:7a:2a:90:07:69:ff:2b:96
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=TeliaSonera Root CA v1 O=TeliaSonera
+# Subject: CN=TeliaSonera Root CA v1 O=TeliaSonera
+# Label: "TeliaSonera Root CA v1"
+# Serial: 199041966741090107964904287217786801558
+# MD5 Fingerprint: 37:41:49:1b:18:56:9a:26:f5:ad:c2:66:fb:40:a5:4c
+# SHA1 Fingerprint: 43:13:bb:96:f1:d5:86:9b:c1:4e:6a:92:f6:cf:f6:34:69:87:82:37
+# SHA256 Fingerprint: dd:69:36:fe:21:f8:f0:77:c1:23:a1:a5:21:c1:22:24:f7:22:55:b7:3e:03:a7:26:06:93:e8:a2:4b:0f:a3:89
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=E-Tugra Certification Authority O=E-Tu\u011fra EBG Bili\u015fim Teknolojileri ve Hizmetleri A.\u015e. OU=E-Tugra Sertifikasyon Merkezi
+# Subject: CN=E-Tugra Certification Authority O=E-Tu\u011fra EBG Bili\u015fim Teknolojileri ve Hizmetleri A.\u015e. OU=E-Tugra Sertifikasyon Merkezi
+# Label: "E-Tugra Certification Authority"
+# Serial: 7667447206703254355
+# MD5 Fingerprint: b8:a1:03:63:b0:bd:21:71:70:8a:6f:13:3a:bb:79:49
+# SHA1 Fingerprint: 51:c6:e7:08:49:06:6e:f3:92:d4:5c:a0:0d:6d:a3:62:8f:c3:52:39
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=T-TeleSec GlobalRoot Class 2 O=T-Systems Enterprise Services GmbH OU=T-Systems Trust Center
+# Subject: CN=T-TeleSec GlobalRoot Class 2 O=T-Systems Enterprise Services GmbH OU=T-Systems Trust Center
+# Label: "T-TeleSec GlobalRoot Class 2"
+# Serial: 1
+# MD5 Fingerprint: 2b:9b:9e:e4:7b:6c:1f:00:72:1a:cc:c1:77:79:df:6a
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Atos TrustedRoot 2011 O=Atos
+# Subject: CN=Atos TrustedRoot 2011 O=Atos
+# Label: "Atos TrustedRoot 2011"
+# Serial: 6643877497813316402
+# MD5 Fingerprint: ae:b9:c4:32:4b:ac:7f:5d:66:cc:77:94:bb:2a:77:56
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=QuoVadis Root CA 1 G3 O=QuoVadis Limited
+# Subject: CN=QuoVadis Root CA 1 G3 O=QuoVadis Limited
+# Label: "QuoVadis Root CA 1 G3"
+# Serial: 687049649626669250736271037606554624078720034195
+# MD5 Fingerprint: a4:bc:5b:3f:fe:37:9a:fa:64:f0:e2:fa:05:3d:0b:ab
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=QuoVadis Root CA 2 G3 O=QuoVadis Limited
+# Subject: CN=QuoVadis Root CA 2 G3 O=QuoVadis Limited
+# Label: "QuoVadis Root CA 2 G3"
+# Serial: 390156079458959257446133169266079962026824725800
+# MD5 Fingerprint: af:0c:86:6e:bf:40:2d:7f:0b:3e:12:50:ba:12:3d:06
+# SHA1 Fingerprint: 09:3c:61:f3:8b:8b:dc:7d:55:df:75:38:02:05:00:e1:25:f5:c8:36
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=QuoVadis Root CA 3 G3 O=QuoVadis Limited
+# Subject: CN=QuoVadis Root CA 3 G3 O=QuoVadis Limited
+# Label: "QuoVadis Root CA 3 G3"
+# Serial: 268090761170461462463995952157327242137089239581
+# MD5 Fingerprint: df:7d:b9:ad:54:6f:68:a1:df:89:57:03:97:43:b0:d7
+# SHA1 Fingerprint: 48:12:bd:92:3c:a8:c4:39:06:e7:30:6d:27:96:e6:a4:cf:22:2e:7d
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert Assured ID Root G2 O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert Assured ID Root G2 O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert Assured ID Root G2"
+# Serial: 15385348160840213938643033620894905419
+# MD5 Fingerprint: 92:38:b9:f8:63:24:82:65:2c:57:33:e6:fe:81:8f:9d
+# SHA1 Fingerprint: a1:4b:48:d9:43:ee:0a:0e:40:90:4f:3c:e0:a4:c0:91:93:51:5d:3f
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert Assured ID Root G3 O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert Assured ID Root G3 O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert Assured ID Root G3"
+# Serial: 15459312981008553731928384953135426796
+# MD5 Fingerprint: 7c:7f:65:31:0c:81:df:8d:ba:3e:99:e2:5c:ad:6e:fb
+# SHA1 Fingerprint: f5:17:a2:4f:9a:48:c6:c9:f8:a2:00:26:9f:dc:0f:48:2c:ab:30:89
+# SHA256 Fingerprint: 7e:37:cb:8b:4c:47:09:0c:ab:36:55:1b:a6:f4:5d:b8:40:68:0f:ba:16:6a:95:2d:b1:00:71:7f:43:05:3f:c2
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert Global Root G2 O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert Global Root G2 O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert Global Root G2"
+# Serial: 4293743540046975378534879503202253541
+# MD5 Fingerprint: e4:a6:8a:c8:54:ac:52:42:46:0a:fd:72:48:1b:2a:44
+# SHA1 Fingerprint: df:3c:24:f9:bf:d6:66:76:1b:26:80:73:fe:06:d1:cc:8d:4f:82:a4
+# SHA256 Fingerprint: cb:3c:cb:b7:60:31:e5:e0:13:8f:8d:d3:9a:23:f9:de:47:ff:c3:5e:43:c1:14:4c:ea:27:d4:6a:5a:b1:cb:5f
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert Global Root G3 O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert Global Root G3 O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert Global Root G3"
+# Serial: 7089244469030293291760083333884364146
+# MD5 Fingerprint: f5:5d:a4:50:a5:fb:28:7e:1e:0f:0d:cc:96:57:56:ca
+# SHA1 Fingerprint: 7e:04:de:89:6a:3e:66:6d:00:e6:87:d3:3f:fa:d9:3b:e8:3d:34:9e
+# SHA256 Fingerprint: 31:ad:66:48:f8:10:41:38:c7:38:f3:9e:a4:32:01:33:39:3e:3a:18:cc:02:29:6e:f9:7c:2a:c9:ef:67:31:d0
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert Trusted Root G4 O=DigiCert Inc OU=www.digicert.com
+# Subject: CN=DigiCert Trusted Root G4 O=DigiCert Inc OU=www.digicert.com
+# Label: "DigiCert Trusted Root G4"
+# Serial: 7451500558977370777930084869016614236
+# MD5 Fingerprint: 78:f2:fc:aa:60:1f:2f:b4:eb:c9:37:ba:53:2e:75:49
+# SHA1 Fingerprint: dd:fb:16:cd:49:31:c9:73:a2:03:7d:3f:c8:3a:4d:7d:77:5d:05:e4
+# SHA256 Fingerprint: 55:2f:7b:dc:f1:a7:af:9e:6c:e6:72:01:7f:4f:12:ab:f7:72:40:c7:8e:76:1a:c2:03:d1:d9:d2:0a:c8:99:88
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=COMODO RSA Certification Authority O=COMODO CA Limited
+# Subject: CN=COMODO RSA Certification Authority O=COMODO CA Limited
+# Label: "COMODO RSA Certification Authority"
+# Serial: 101909084537582093308941363524873193117
+# MD5 Fingerprint: 1b:31:b0:71:40:36:cc:14:36:91:ad:c4:3e:fd:ec:18
+# SHA1 Fingerprint: af:e5:d2:44:a8:d1:19:42:30:ff:47:9f:e2:f8:97:bb:cd:7a:8c:b4
+# SHA256 Fingerprint: 52:f0:e1:c4:e5:8e:c6:29:29:1b:60:31:7f:07:46:71:b8:5d:7e:a8:0d:5b:07:27:34:63:53:4b:32:b4:02:34
+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=USERTrust RSA Certification Authority O=The USERTRUST Network
+# Subject: CN=USERTrust RSA Certification Authority O=The USERTRUST Network
+# Label: "USERTrust RSA Certification Authority"
+# Serial: 2645093764781058787591871645665788717
+# MD5 Fingerprint: 1b:fe:69:d1:91:b7:19:33:a3:72:a8:0f:e1:55:e5:b5
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=USERTrust ECC Certification Authority O=The USERTRUST Network
+# Subject: CN=USERTrust ECC Certification Authority O=The USERTRUST Network
+# Label: "USERTrust ECC Certification Authority"
+# Serial: 123013823720199481456569720443997572134
+# MD5 Fingerprint: fa:68:bc:d9:b5:7f:ad:fd:c9:1d:06:83:28:cc:24:c1
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign ECC Root CA - R5
+# Subject: CN=GlobalSign O=GlobalSign OU=GlobalSign ECC Root CA - R5
+# Label: "GlobalSign ECC Root CA - R5"
+# Serial: 32785792099990507226680698011560947931244
+# MD5 Fingerprint: 9f:ad:3b:1c:02:1e:8a:ba:17:74:38:81:0c:a2:bc:08
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=IdenTrust Commercial Root CA 1 O=IdenTrust
+# Subject: CN=IdenTrust Commercial Root CA 1 O=IdenTrust
+# Label: "IdenTrust Commercial Root CA 1"
+# Serial: 13298821034946342390520003877796839426
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=IdenTrust Public Sector Root CA 1 O=IdenTrust
+# Subject: CN=IdenTrust Public Sector Root CA 1 O=IdenTrust
+# Label: "IdenTrust Public Sector Root CA 1"
+# Serial: 13298821034946342390521976156843933698
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Entrust Root Certification Authority - G2 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2009 Entrust, Inc. - for authorized use only
+# Subject: CN=Entrust Root Certification Authority - G2 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2009 Entrust, Inc. - for authorized use only
+# Label: "Entrust Root Certification Authority - G2"
+# Serial: 1246989352
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Entrust Root Certification Authority - EC1 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2012 Entrust, Inc. - for authorized use only
+# Subject: CN=Entrust Root Certification Authority - EC1 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2012 Entrust, Inc. - for authorized use only
+# Label: "Entrust Root Certification Authority - EC1"
+# Serial: 51543124481930649114116133369
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=CFCA EV ROOT O=China Financial Certification Authority
+# Subject: CN=CFCA EV ROOT O=China Financial Certification Authority
+# Label: "CFCA EV ROOT"
+# Serial: 407555286
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=OISTE WISeKey Global Root GB CA O=WISeKey OU=OISTE Foundation Endorsed
+# Subject: CN=OISTE WISeKey Global Root GB CA O=WISeKey OU=OISTE Foundation Endorsed
+# Label: "OISTE WISeKey Global Root GB CA"
+# Serial: 157768595616588414422159278966750757568
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=SZAFIR ROOT CA2 O=Krajowa Izba Rozliczeniowa S.A.
+# Subject: CN=SZAFIR ROOT CA2 O=Krajowa Izba Rozliczeniowa S.A.
+# Label: "SZAFIR ROOT CA2"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Certum Trusted Network CA 2 O=Unizeto Technologies S.A. OU=Certum Certification Authority
+# Subject: CN=Certum Trusted Network CA 2 O=Unizeto Technologies S.A. OU=Certum Certification Authority
+# Label: "Certum Trusted Network CA 2"
+# Serial: 44979900017204383099463764357512596969
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+-----BEGIN CERTIFICATE-----
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Amazon Root CA 2 O=Amazon
+# Subject: CN=Amazon Root CA 2 O=Amazon
+# Label: "Amazon Root CA 2"
+# Serial: 143266982885963551818349160658925006970653239
+# MD5 Fingerprint: c8:e5:8d:ce:a8:42:e2:7a:c0:2a:5c:7c:9e:26:bf:66
+# SHA1 Fingerprint: 5a:8c:ef:45:d7:a6:98:59:76:7a:8c:8b:44:96:b5:78:cf:47:4b:1a
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Amazon Root CA 3 O=Amazon
+# Subject: CN=Amazon Root CA 3 O=Amazon
+# Label: "Amazon Root CA 3"
+# Serial: 143266986699090766294700635381230934788665930
+# MD5 Fingerprint: a0:d4:ef:0b:f7:b5:d8:49:95:2a:ec:f5:c4:fc:81:87
+# SHA1 Fingerprint: 0d:44:dd:8c:3c:8c:1a:1a:58:75:64:81:e9:0f:2e:2a:ff:b3:d2:6e
+# SHA256 Fingerprint: 18:ce:6c:fe:7b:f1:4e:60:b2:e3:47:b8:df:e8:68:cb:31:d0:2e:bb:3a:da:27:15:69:f5:03:43:b4:6d:b3:a4
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Amazon Root CA 4 O=Amazon
+# Subject: CN=Amazon Root CA 4 O=Amazon
+# Label: "Amazon Root CA 4"
+# Serial: 143266989758080763974105200630763877849284878
+# MD5 Fingerprint: 89:bc:27:d5:eb:17:8d:06:6a:69:d5:fd:89:47:b4:cd
+# SHA1 Fingerprint: f6:10:84:07:d6:f8:bb:67:98:0c:c2:e2:44:c2:eb:ae:1c:ef:63:be
+# SHA256 Fingerprint: e3:5d:28:41:9e:d0:20:25:cf:a6:90:38:cd:62:39:62:45:8d:a5:c6:95:fb:de:a3:c2:2b:0b:fb:25:89:70:92
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1 O=Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK OU=Kamu Sertifikasyon Merkezi - Kamu SM
+# Subject: CN=TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1 O=Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK OU=Kamu Sertifikasyon Merkezi - Kamu SM
+# Label: "TUBITAK Kamu SM SSL Kok Sertifikasi - Surum 1"
+# Serial: 1
+# MD5 Fingerprint: dc:00:81:dc:69:2f:3e:2f:b0:3b:f6:3d:5a:91:8e:49
+# SHA1 Fingerprint: 31:43:64:9b:ec:ce:27:ec:ed:3a:3f:0b:8f:0d:e4:e8:91:dd:ee:ca
+# SHA256 Fingerprint: 46:ed:c3:68:90:46:d5:3a:45:3f:b3:10:4a:b8:0d:ca:ec:65:8b:26:60:ea:16:29:dd:7e:86:79:90:64:87:16
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=GDCA TrustAUTH R5 ROOT O=GUANG DONG CERTIFICATE AUTHORITY CO.,LTD.
+# Subject: CN=GDCA TrustAUTH R5 ROOT O=GUANG DONG CERTIFICATE AUTHORITY CO.,LTD.
+# Label: "GDCA TrustAUTH R5 ROOT"
+# Serial: 9009899650740120186
+# MD5 Fingerprint: 63:cc:d9:3d:34:35:5c:6f:53:a3:e2:08:70:48:1f:b4
+# SHA1 Fingerprint: 0f:36:38:5b:81:1a:25:c3:9b:31:4e:83:ca:e9:34:66:70:cc:74:b4
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SSL.com Root Certification Authority RSA O=SSL Corporation
+# Subject: CN=SSL.com Root Certification Authority RSA O=SSL Corporation
+# Label: "SSL.com Root Certification Authority RSA"
+# Serial: 8875640296558310041
+# MD5 Fingerprint: 86:69:12:c0:70:f1:ec:ac:ac:c2:d5:bc:a5:5b:a1:29
+# SHA1 Fingerprint: b7:ab:33:08:d1:ea:44:77:ba:14:80:12:5a:6f:bd:a9:36:49:0c:bb
+# SHA256 Fingerprint: 85:66:6a:56:2e:e0:be:5c:e9:25:c1:d8:89:0a:6f:76:a8:7e:c1:6d:4d:7d:5f:29:ea:74:19:cf:20:12:3b:69
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SSL.com Root Certification Authority ECC O=SSL Corporation
+# Subject: CN=SSL.com Root Certification Authority ECC O=SSL Corporation
+# Label: "SSL.com Root Certification Authority ECC"
+# Serial: 8495723813297216424
+# MD5 Fingerprint: 2e:da:e4:39:7f:9c:8f:37:d1:70:9f:26:17:51:3a:8e
+# SHA1 Fingerprint: c3:19:7c:39:24:e6:54:af:1b:c4:ab:20:95:7a:e2:c3:0e:13:02:6a
+# SHA256 Fingerprint: 34:17:bb:06:cc:60:07:da:1b:96:1c:92:0b:8a:b4:ce:3f:ad:82:0e:4a:a3:0b:9a:cb:c4:a7:4e:bd:ce:bc:65
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SSL.com EV Root Certification Authority RSA R2 O=SSL Corporation
+# Subject: CN=SSL.com EV Root Certification Authority RSA R2 O=SSL Corporation
+# Label: "SSL.com EV Root Certification Authority RSA R2"
+# Serial: 6248227494352943350
+# MD5 Fingerprint: e1:1e:31:58:1a:ae:54:53:02:f6:17:6a:11:7b:4d:95
+# SHA1 Fingerprint: 74:3a:f0:52:9b:d0:32:a0:f4:4a:83:cd:d4:ba:a9:7b:7c:2e:c4:9a
+# SHA256 Fingerprint: 2e:7b:f1:6c:c2:24:85:a7:bb:e2:aa:86:96:75:07:61:b0:ae:39:be:3b:2f:e9:d0:cc:6d:4e:f7:34:91:42:5c
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=SSL.com EV Root Certification Authority ECC O=SSL Corporation
+# Subject: CN=SSL.com EV Root Certification Authority ECC O=SSL Corporation
+# Label: "SSL.com EV Root Certification Authority ECC"
+# Serial: 3182246526754555285
+# MD5 Fingerprint: 59:53:22:65:83:42:01:54:c0:ce:42:b9:5a:7c:f2:90
+# SHA1 Fingerprint: 4c:dd:51:a3:d1:f5:20:32:14:b0:c6:c5:32:23:03:91:c7:46:42:6d
+# SHA256 Fingerprint: 22:a2:c1:f7:bd:ed:70:4c:c1:e7:01:b5:f4:08:c3:10:88:0f:e9:56:b5:de:2a:4a:44:f9:9c:87:3a:25:a7:c8
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R6
+# Subject: CN=GlobalSign O=GlobalSign OU=GlobalSign Root CA - R6
+# Label: "GlobalSign Root CA - R6"
+# Serial: 1417766617973444989252670301619537
+# MD5 Fingerprint: 4f:dd:07:e4:d4:22:64:39:1e:0c:37:42:ea:d1:c6:ae
+# SHA1 Fingerprint: 80:94:64:0e:b5:a7:a1:ca:11:9c:1f:dd:d5:9f:81:02:63:a7:fb:d1
+# SHA256 Fingerprint: 2c:ab:ea:fe:37:d0:6c:a2:2a:ba:73:91:c0:03:3d:25:98:29:52:c4:53:64:73:49:76:3a:3a:b5:ad:6c:cf:69
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=OISTE WISeKey Global Root GC CA O=WISeKey OU=OISTE Foundation Endorsed
+# Subject: CN=OISTE WISeKey Global Root GC CA O=WISeKey OU=OISTE Foundation Endorsed
+# Label: "OISTE WISeKey Global Root GC CA"
+# Serial: 44084345621038548146064804565436152554
+# MD5 Fingerprint: a9:d6:b9:2d:2f:93:64:f8:a5:69:ca:91:e9:68:07:23
+# SHA1 Fingerprint: e0:11:84:5e:34:de:be:88:81:b9:9c:f6:16:26:d1:96:1f:c3:b9:31
+# SHA256 Fingerprint: 85:60:f9:1c:36:24:da:ba:95:70:b5:fe:a0:db:e3:6f:f1:1a:83:23:be:94:86:85:4f:b3:f3:4a:55:71:19:8d
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=UCA Global G2 Root O=UniTrust
+# Subject: CN=UCA Global G2 Root O=UniTrust
+# Label: "UCA Global G2 Root"
+# Serial: 124779693093741543919145257850076631279
+# MD5 Fingerprint: 80:fe:f0:c4:4a:f0:5c:62:32:9f:1c:ba:78:a9:50:f8
+# SHA1 Fingerprint: 28:f9:78:16:19:7a:ff:18:25:18:aa:44:fe:c1:a0:ce:5c:b6:4c:8a
+# SHA256 Fingerprint: 9b:ea:11:c9:76:fe:01:47:64:c1:be:56:a6:f9:14:b5:a5:60:31:7a:bd:99:88:39:33:82:e5:16:1a:a0:49:3c
+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=UCA Extended Validation Root O=UniTrust
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+# Label: "UCA Extended Validation Root"
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+# Issuer: CN=Certigna Root CA O=Dhimyotis OU=0002 48146308100036
+# Subject: CN=Certigna Root CA O=Dhimyotis OU=0002 48146308100036
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=emSign Root CA - G1 O=eMudhra Technologies Limited OU=emSign PKI
+# Subject: CN=emSign Root CA - G1 O=eMudhra Technologies Limited OU=emSign PKI
+# Label: "emSign Root CA - G1"
+# Serial: 235931866688319308814040
+# MD5 Fingerprint: 9c:42:84:57:dd:cb:0b:a7:2e:95:ad:b6:f3:da:bc:ac
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=emSign ECC Root CA - G3 O=eMudhra Technologies Limited OU=emSign PKI
+# Subject: CN=emSign ECC Root CA - G3 O=eMudhra Technologies Limited OU=emSign PKI
+# Label: "emSign ECC Root CA - G3"
+# Serial: 287880440101571086945156
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=emSign Root CA - C1 O=eMudhra Inc OU=emSign PKI
+# Subject: CN=emSign Root CA - C1 O=eMudhra Inc OU=emSign PKI
+# Label: "emSign Root CA - C1"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=emSign ECC Root CA - C3 O=eMudhra Inc OU=emSign PKI
+# Subject: CN=emSign ECC Root CA - C3 O=eMudhra Inc OU=emSign PKI
+# Label: "emSign ECC Root CA - C3"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Hongkong Post Root CA 3 O=Hongkong Post
+# Subject: CN=Hongkong Post Root CA 3 O=Hongkong Post
+# Label: "Hongkong Post Root CA 3"
+# Serial: 46170865288971385588281144162979347873371282084
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Entrust Root Certification Authority - G4 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2015 Entrust, Inc. - for authorized use only
+# Subject: CN=Entrust Root Certification Authority - G4 O=Entrust, Inc. OU=See www.entrust.net/legal-terms/(c) 2015 Entrust, Inc. - for authorized use only
+# Label: "Entrust Root Certification Authority - G4"
+# Serial: 289383649854506086828220374796556676440
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=Microsoft ECC Root Certificate Authority 2017 O=Microsoft Corporation
+# Subject: CN=Microsoft ECC Root Certificate Authority 2017 O=Microsoft Corporation
+# Label: "Microsoft ECC Root Certificate Authority 2017"
+# Serial: 136839042543790627607696632466672567020
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Microsoft RSA Root Certificate Authority 2017 O=Microsoft Corporation
+# Subject: CN=Microsoft RSA Root Certificate Authority 2017 O=Microsoft Corporation
+# Label: "Microsoft RSA Root Certificate Authority 2017"
+# Serial: 40975477897264996090493496164228220339
+# MD5 Fingerprint: 10:ff:00:ff:cf:c9:f8:c7:7a:c0:ee:35:8e:c9:0f:47
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=e-Szigno Root CA 2017 O=Microsec Ltd.
+# Subject: CN=e-Szigno Root CA 2017 O=Microsec Ltd.
+# Label: "e-Szigno Root CA 2017"
+# Serial: 411379200276854331539784714
+# MD5 Fingerprint: de:1f:f6:9e:84:ae:a7:b4:21:ce:1e:58:7d:d1:84:98
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
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+# Issuer: O=CERTSIGN SA OU=certSIGN ROOT CA G2
+# Subject: O=CERTSIGN SA OU=certSIGN ROOT CA G2
+# Label: "certSIGN Root CA G2"
+# Serial: 313609486401300475190
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Trustwave Global Certification Authority O=Trustwave Holdings, Inc.
+# Subject: CN=Trustwave Global Certification Authority O=Trustwave Holdings, Inc.
+# Label: "Trustwave Global Certification Authority"
+# Serial: 1846098327275375458322922162
+# MD5 Fingerprint: f8:1c:18:2d:2f:ba:5f:6d:a1:6c:bc:c7:ab:91:c7:0e
+# SHA1 Fingerprint: 2f:8f:36:4f:e1:58:97:44:21:59:87:a5:2a:9a:d0:69:95:26:7f:b5
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Trustwave Global ECC P256 Certification Authority O=Trustwave Holdings, Inc.
+# Subject: CN=Trustwave Global ECC P256 Certification Authority O=Trustwave Holdings, Inc.
+# Label: "Trustwave Global ECC P256 Certification Authority"
+# Serial: 4151900041497450638097112925
+# MD5 Fingerprint: 5b:44:e3:8d:5d:36:86:26:e8:0d:05:d2:59:a7:83:54
+# SHA1 Fingerprint: b4:90:82:dd:45:0c:be:8b:5b:b1:66:d3:e2:a4:08:26:cd:ed:42:cf
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=Trustwave Global ECC P384 Certification Authority O=Trustwave Holdings, Inc.
+# Subject: CN=Trustwave Global ECC P384 Certification Authority O=Trustwave Holdings, Inc.
+# Label: "Trustwave Global ECC P384 Certification Authority"
+# Serial: 2704997926503831671788816187
+# MD5 Fingerprint: ea:cf:60:c4:3b:b9:15:29:40:a1:97:ed:78:27:93:d6
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=NAVER Global Root Certification Authority O=NAVER BUSINESS PLATFORM Corp.
+# Subject: CN=NAVER Global Root Certification Authority O=NAVER BUSINESS PLATFORM Corp.
+# Label: "NAVER Global Root Certification Authority"
+# Serial: 9013692873798656336226253319739695165984492813
+# MD5 Fingerprint: c8:7e:41:f6:25:3b:f5:09:b3:17:e8:46:3d:bf:d0:9b
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=AC RAIZ FNMT-RCM SERVIDORES SEGUROS O=FNMT-RCM OU=Ceres
+# Subject: CN=AC RAIZ FNMT-RCM SERVIDORES SEGUROS O=FNMT-RCM OU=Ceres
+# Label: "AC RAIZ FNMT-RCM SERVIDORES SEGUROS"
+# Serial: 131542671362353147877283741781055151509
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=GlobalSign Root R46 O=GlobalSign nv-sa
+# Subject: CN=GlobalSign Root R46 O=GlobalSign nv-sa
+# Label: "GlobalSign Root R46"
+# Serial: 1552617688466950547958867513931858518042577
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=GlobalSign Root E46 O=GlobalSign nv-sa
+# Subject: CN=GlobalSign Root E46 O=GlobalSign nv-sa
+# Label: "GlobalSign Root E46"
+# Serial: 1552617690338932563915843282459653771421763
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=GLOBALTRUST 2020 O=e-commerce monitoring GmbH
+# Subject: CN=GLOBALTRUST 2020 O=e-commerce monitoring GmbH
+# Label: "GLOBALTRUST 2020"
+# Serial: 109160994242082918454945253
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=ANF Secure Server Root CA O=ANF Autoridad de Certificacion OU=ANF CA Raiz
+# Subject: CN=ANF Secure Server Root CA O=ANF Autoridad de Certificacion OU=ANF CA Raiz
+# Label: "ANF Secure Server Root CA"
+# Serial: 996390341000653745
+# MD5 Fingerprint: 26:a6:44:5a:d9:af:4e:2f:b2:1d:b6:65:b0:4e:e8:96
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Certum EC-384 CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
+# Subject: CN=Certum EC-384 CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
+# Label: "Certum EC-384 CA"
+# Serial: 160250656287871593594747141429395092468
+# MD5 Fingerprint: b6:65:b3:96:60:97:12:a1:ec:4e:e1:3d:a3:c6:c9:f1
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Certum Trusted Root CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
+# Subject: CN=Certum Trusted Root CA O=Asseco Data Systems S.A. OU=Certum Certification Authority
+# Label: "Certum Trusted Root CA"
+# Serial: 40870380103424195783807378461123655149
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=TunTrust Root CA O=Agence Nationale de Certification Electronique
+# Subject: CN=TunTrust Root CA O=Agence Nationale de Certification Electronique
+# Label: "TunTrust Root CA"
+# Serial: 108534058042236574382096126452369648152337120275
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=HARICA TLS RSA Root CA 2021 O=Hellenic Academic and Research Institutions CA
+# Subject: CN=HARICA TLS RSA Root CA 2021 O=Hellenic Academic and Research Institutions CA
+# Label: "HARICA TLS RSA Root CA 2021"
+# Serial: 76817823531813593706434026085292783742
+# MD5 Fingerprint: 65:47:9b:58:86:dd:2c:f0:fc:a2:84:1f:1e:96:c4:91
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=HARICA TLS ECC Root CA 2021 O=Hellenic Academic and Research Institutions CA
+# Subject: CN=HARICA TLS ECC Root CA 2021 O=Hellenic Academic and Research Institutions CA
+# Label: "HARICA TLS ECC Root CA 2021"
+# Serial: 137515985548005187474074462014555733966
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Autoridad de Certificacion Firmaprofesional CIF A62634068
+# Subject: CN=Autoridad de Certificacion Firmaprofesional CIF A62634068
+# Label: "Autoridad de Certificacion Firmaprofesional CIF A62634068"
+# Serial: 1977337328857672817
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+-----BEGIN CERTIFICATE-----
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+# Subject: CN=vTrus ECC Root CA O=iTrusChina Co.,Ltd.
+# Label: "vTrus ECC Root CA"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=vTrus Root CA O=iTrusChina Co.,Ltd.
+# Subject: CN=vTrus Root CA O=iTrusChina Co.,Ltd.
+# Label: "vTrus Root CA"
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+# Issuer: CN=ISRG Root X2 O=Internet Security Research Group
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+# Label: "ISRG Root X2"
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=HiPKI Root CA - G1 O=Chunghwa Telecom Co., Ltd.
+# Subject: CN=HiPKI Root CA - G1 O=Chunghwa Telecom Co., Ltd.
+# Label: "HiPKI Root CA - G1"
+# Serial: 60966262342023497858655262305426234976
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=GlobalSign O=GlobalSign OU=GlobalSign ECC Root CA - R4
+# Subject: CN=GlobalSign O=GlobalSign OU=GlobalSign ECC Root CA - R4
+# Label: "GlobalSign ECC Root CA - R4"
+# Serial: 159662223612894884239637590694
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+-----BEGIN CERTIFICATE-----
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+
+# Issuer: CN=GTS Root R1 O=Google Trust Services LLC
+# Subject: CN=GTS Root R1 O=Google Trust Services LLC
+# Label: "GTS Root R1"
+# Serial: 159662320309726417404178440727
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=GTS Root R2 O=Google Trust Services LLC
+# Subject: CN=GTS Root R2 O=Google Trust Services LLC
+# Label: "GTS Root R2"
+# Serial: 159662449406622349769042896298
+# MD5 Fingerprint: 1e:39:c0:53:e6:1e:29:82:0b:ca:52:55:36:5d:57:dc
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=GTS Root R3 O=Google Trust Services LLC
+# Subject: CN=GTS Root R3 O=Google Trust Services LLC
+# Label: "GTS Root R3"
+# Serial: 159662495401136852707857743206
+# MD5 Fingerprint: 3e:e7:9d:58:02:94:46:51:94:e5:e0:22:4a:8b:e7:73
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=GTS Root R4 O=Google Trust Services LLC
+# Subject: CN=GTS Root R4 O=Google Trust Services LLC
+# Label: "GTS Root R4"
+# Serial: 159662532700760215368942768210
+# MD5 Fingerprint: 43:96:83:77:19:4d:76:b3:9d:65:52:e4:1d:22:a5:e8
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+-----BEGIN CERTIFICATE-----
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+# Issuer: CN=Telia Root CA v2 O=Telia Finland Oyj
+# Subject: CN=Telia Root CA v2 O=Telia Finland Oyj
+# Label: "Telia Root CA v2"
+# Serial: 7288924052977061235122729490515358
+# MD5 Fingerprint: 0e:8f:ac:aa:82:df:85:b1:f4:dc:10:1c:fc:99:d9:48
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=D-TRUST BR Root CA 1 2020 O=D-Trust GmbH
+# Subject: CN=D-TRUST BR Root CA 1 2020 O=D-Trust GmbH
+# Label: "D-TRUST BR Root CA 1 2020"
+# Serial: 165870826978392376648679885835942448534
+# MD5 Fingerprint: b5:aa:4b:d5:ed:f7:e3:55:2e:8f:72:0a:f3:75:b8:ed
+# SHA1 Fingerprint: 1f:5b:98:f0:e3:b5:f7:74:3c:ed:e6:b0:36:7d:32:cd:f4:09:41:67
+# SHA256 Fingerprint: e5:9a:aa:81:60:09:c2:2b:ff:5b:25:ba:d3:7d:f3:06:f0:49:79:7c:1f:81:d8:5a:b0:89:e6:57:bd:8f:00:44
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=D-TRUST EV Root CA 1 2020 O=D-Trust GmbH
+# Subject: CN=D-TRUST EV Root CA 1 2020 O=D-Trust GmbH
+# Label: "D-TRUST EV Root CA 1 2020"
+# Serial: 126288379621884218666039612629459926992
+# MD5 Fingerprint: 8c:2d:9d:70:9f:48:99:11:06:11:fb:e9:cb:30:c0:6e
+# SHA1 Fingerprint: 61:db:8c:21:59:69:03:90:d8:7c:9c:12:86:54:cf:9d:3d:f4:dd:07
+# SHA256 Fingerprint: 08:17:0d:1a:a3:64:53:90:1a:2f:95:92:45:e3:47:db:0c:8d:37:ab:aa:bc:56:b8:1a:a1:00:dc:95:89:70:db
+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert TLS ECC P384 Root G5 O=DigiCert, Inc.
+# Subject: CN=DigiCert TLS ECC P384 Root G5 O=DigiCert, Inc.
+# Label: "DigiCert TLS ECC P384 Root G5"
+# Serial: 13129116028163249804115411775095713523
+# MD5 Fingerprint: d3:71:04:6a:43:1c:db:a6:59:e1:a8:a3:aa:c5:71:ed
+# SHA1 Fingerprint: 17:f3:de:5e:9f:0f:19:e9:8e:f6:1f:32:26:6e:20:c4:07:ae:30:ee
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=DigiCert TLS RSA4096 Root G5 O=DigiCert, Inc.
+# Subject: CN=DigiCert TLS RSA4096 Root G5 O=DigiCert, Inc.
+# Label: "DigiCert TLS RSA4096 Root G5"
+# Serial: 11930366277458970227240571539258396554
+# MD5 Fingerprint: ac:fe:f7:34:96:a9:f2:b3:b4:12:4b:e4:27:41:6f:e1
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Certainly Root R1 O=Certainly
+# Subject: CN=Certainly Root R1 O=Certainly
+# Label: "Certainly Root R1"
+# Serial: 188833316161142517227353805653483829216
+# MD5 Fingerprint: 07:70:d4:3e:82:87:a0:fa:33:36:13:f4:fa:33:e7:12
+# SHA1 Fingerprint: a0:50:ee:0f:28:71:f4:27:b2:12:6d:6f:50:96:25:ba:cc:86:42:af
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Certainly Root E1 O=Certainly
+# Subject: CN=Certainly Root E1 O=Certainly
+# Label: "Certainly Root E1"
+# Serial: 8168531406727139161245376702891150584
+# MD5 Fingerprint: 0a:9e:ca:cd:3e:52:50:c6:36:f3:4b:a3:ed:a7:53:e9
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=E-Tugra Global Root CA RSA v3 O=E-Tugra EBG A.S. OU=E-Tugra Trust Center
+# Subject: CN=E-Tugra Global Root CA RSA v3 O=E-Tugra EBG A.S. OU=E-Tugra Trust Center
+# Label: "E-Tugra Global Root CA RSA v3"
+# Serial: 75951268308633135324246244059508261641472512052
+# MD5 Fingerprint: 22:be:10:f6:c2:f8:03:88:73:5f:33:29:47:28:47:a4
+# SHA1 Fingerprint: e9:a8:5d:22:14:52:1c:5b:aa:0a:b4:be:24:6a:23:8a:c9:ba:e2:a9
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=E-Tugra Global Root CA ECC v3 O=E-Tugra EBG A.S. OU=E-Tugra Trust Center
+# Subject: CN=E-Tugra Global Root CA ECC v3 O=E-Tugra EBG A.S. OU=E-Tugra Trust Center
+# Label: "E-Tugra Global Root CA ECC v3"
+# Serial: 218504919822255052842371958738296604628416471745
+# MD5 Fingerprint: 46:bc:81:bb:f1:b5:1e:f7:4b:96:bc:14:e2:e7:27:64
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+-----BEGIN CERTIFICATE-----
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+-----END CERTIFICATE-----
+
+# Issuer: CN=Security Communication RootCA3 O=SECOM Trust Systems CO.,LTD.
+# Subject: CN=Security Communication RootCA3 O=SECOM Trust Systems CO.,LTD.
+# Label: "Security Communication RootCA3"
+# Serial: 16247922307909811815
+# MD5 Fingerprint: 1c:9a:16:ff:9e:5c:e0:4d:8a:14:01:f4:35:5d:29:26
+# SHA1 Fingerprint: c3:03:c8:22:74:92:e5:61:a2:9c:5f:79:91:2b:1e:44:13:91:30:3a
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+-----BEGIN CERTIFICATE-----
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+TdJ0MN1kURXbg4NR16/9M51NZg==
+-----END CERTIFICATE-----
+
+# Issuer: CN=Security Communication ECC RootCA1 O=SECOM Trust Systems CO.,LTD.
+# Subject: CN=Security Communication ECC RootCA1 O=SECOM Trust Systems CO.,LTD.
+# Label: "Security Communication ECC RootCA1"
+# Serial: 15446673492073852651
+# MD5 Fingerprint: 7e:43:b0:92:68:ec:05:43:4c:98:ab:5d:35:2e:7e:86
+# SHA1 Fingerprint: b8:0e:26:a9:bf:d2:b2:3b:c0:ef:46:c9:ba:c7:bb:f6:1d:0d:41:41
+# SHA256 Fingerprint: e7:4f:bd:a5:5b:d5:64:c4:73:a3:6b:44:1a:a7:99:c8:a6:8e:07:74:40:e8:28:8b:9f:a1:e5:0e:4b:ba:ca:11
+-----BEGIN CERTIFICATE-----
+MIICODCCAb6gAwIBAgIJANZdm7N4gS7rMAoGCCqGSM49BAMDMGExCzAJBgNVBAYT
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+-----END CERTIFICATE-----
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/core.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/core.py
new file mode 100644
index 0000000000000000000000000000000000000000..c3e546604c85678dd72db35893c46ffe2d79c052
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/certifi/core.py
@@ -0,0 +1,108 @@
+"""
+certifi.py
+~~~~~~~~~~
+
+This module returns the installation location of cacert.pem or its contents.
+"""
+import sys
+
+
+if sys.version_info >= (3, 11):
+
+    from importlib.resources import as_file, files
+
+    _CACERT_CTX = None
+    _CACERT_PATH = None
+
+    def where() -> str:
+        # This is slightly terrible, but we want to delay extracting the file
+        # in cases where we're inside of a zipimport situation until someone
+        # actually calls where(), but we don't want to re-extract the file
+        # on every call of where(), so we'll do it once then store it in a
+        # global variable.
+        global _CACERT_CTX
+        global _CACERT_PATH
+        if _CACERT_PATH is None:
+            # This is slightly janky, the importlib.resources API wants you to
+            # manage the cleanup of this file, so it doesn't actually return a
+            # path, it returns a context manager that will give you the path
+            # when you enter it and will do any cleanup when you leave it. In
+            # the common case of not needing a temporary file, it will just
+            # return the file system location and the __exit__() is a no-op.
+            #
+            # We also have to hold onto the actual context manager, because
+            # it will do the cleanup whenever it gets garbage collected, so
+            # we will also store that at the global level as well.
+            _CACERT_CTX = as_file(files("pip._vendor.certifi").joinpath("cacert.pem"))
+            _CACERT_PATH = str(_CACERT_CTX.__enter__())
+
+        return _CACERT_PATH
+
+    def contents() -> str:
+        return files("pip._vendor.certifi").joinpath("cacert.pem").read_text(encoding="ascii")
+
+elif sys.version_info >= (3, 7):
+
+    from importlib.resources import path as get_path, read_text
+
+    _CACERT_CTX = None
+    _CACERT_PATH = None
+
+    def where() -> str:
+        # This is slightly terrible, but we want to delay extracting the
+        # file in cases where we're inside of a zipimport situation until
+        # someone actually calls where(), but we don't want to re-extract
+        # the file on every call of where(), so we'll do it once then store
+        # it in a global variable.
+        global _CACERT_CTX
+        global _CACERT_PATH
+        if _CACERT_PATH is None:
+            # This is slightly janky, the importlib.resources API wants you
+            # to manage the cleanup of this file, so it doesn't actually
+            # return a path, it returns a context manager that will give
+            # you the path when you enter it and will do any cleanup when
+            # you leave it. In the common case of not needing a temporary
+            # file, it will just return the file system location and the
+            # __exit__() is a no-op.
+            #
+            # We also have to hold onto the actual context manager, because
+            # it will do the cleanup whenever it gets garbage collected, so
+            # we will also store that at the global level as well.
+            _CACERT_CTX = get_path("pip._vendor.certifi", "cacert.pem")
+            _CACERT_PATH = str(_CACERT_CTX.__enter__())
+
+        return _CACERT_PATH
+
+    def contents() -> str:
+        return read_text("pip._vendor.certifi", "cacert.pem", encoding="ascii")
+
+else:
+    import os
+    import types
+    from typing import Union
+
+    Package = Union[types.ModuleType, str]
+    Resource = Union[str, "os.PathLike"]
+
+    # This fallback will work for Python versions prior to 3.7 that lack the
+    # importlib.resources module but relies on the existing `where` function
+    # so won't address issues with environments like PyOxidizer that don't set
+    # __file__ on modules.
+    def read_text(
+        package: Package,
+        resource: Resource,
+        encoding: str = 'utf-8',
+        errors: str = 'strict'
+    ) -> str:
+        with open(where(), encoding=encoding) as data:
+            return data.read()
+
+    # If we don't have importlib.resources, then we will just do the old logic
+    # of assuming we're on the filesystem and munge the path directly.
+    def where() -> str:
+        f = os.path.dirname(__file__)
+
+        return os.path.join(f, "cacert.pem")
+
+    def contents() -> str:
+        return read_text("pip._vendor.certifi", "cacert.pem", encoding="ascii")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe581623d89d67a49eb43f3c3e88f3f450257707
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/__init__.py
@@ -0,0 +1,115 @@
+######################## BEGIN LICENSE BLOCK ########################
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Union
+
+from .charsetgroupprober import CharSetGroupProber
+from .charsetprober import CharSetProber
+from .enums import InputState
+from .resultdict import ResultDict
+from .universaldetector import UniversalDetector
+from .version import VERSION, __version__
+
+__all__ = ["UniversalDetector", "detect", "detect_all", "__version__", "VERSION"]
+
+
+def detect(
+    byte_str: Union[bytes, bytearray], should_rename_legacy: bool = False
+) -> ResultDict:
+    """
+    Detect the encoding of the given byte string.
+
+    :param byte_str:     The byte sequence to examine.
+    :type byte_str:      ``bytes`` or ``bytearray``
+    :param should_rename_legacy:  Should we rename legacy encodings
+                                  to their more modern equivalents?
+    :type should_rename_legacy:   ``bool``
+    """
+    if not isinstance(byte_str, bytearray):
+        if not isinstance(byte_str, bytes):
+            raise TypeError(
+                f"Expected object of type bytes or bytearray, got: {type(byte_str)}"
+            )
+        byte_str = bytearray(byte_str)
+    detector = UniversalDetector(should_rename_legacy=should_rename_legacy)
+    detector.feed(byte_str)
+    return detector.close()
+
+
+def detect_all(
+    byte_str: Union[bytes, bytearray],
+    ignore_threshold: bool = False,
+    should_rename_legacy: bool = False,
+) -> List[ResultDict]:
+    """
+    Detect all the possible encodings of the given byte string.
+
+    :param byte_str:          The byte sequence to examine.
+    :type byte_str:           ``bytes`` or ``bytearray``
+    :param ignore_threshold:  Include encodings that are below
+                              ``UniversalDetector.MINIMUM_THRESHOLD``
+                              in results.
+    :type ignore_threshold:   ``bool``
+    :param should_rename_legacy:  Should we rename legacy encodings
+                                  to their more modern equivalents?
+    :type should_rename_legacy:   ``bool``
+    """
+    if not isinstance(byte_str, bytearray):
+        if not isinstance(byte_str, bytes):
+            raise TypeError(
+                f"Expected object of type bytes or bytearray, got: {type(byte_str)}"
+            )
+        byte_str = bytearray(byte_str)
+
+    detector = UniversalDetector(should_rename_legacy=should_rename_legacy)
+    detector.feed(byte_str)
+    detector.close()
+
+    if detector.input_state == InputState.HIGH_BYTE:
+        results: List[ResultDict] = []
+        probers: List[CharSetProber] = []
+        for prober in detector.charset_probers:
+            if isinstance(prober, CharSetGroupProber):
+                probers.extend(p for p in prober.probers)
+            else:
+                probers.append(prober)
+        for prober in probers:
+            if ignore_threshold or prober.get_confidence() > detector.MINIMUM_THRESHOLD:
+                charset_name = prober.charset_name or ""
+                lower_charset_name = charset_name.lower()
+                # Use Windows encoding name instead of ISO-8859 if we saw any
+                # extra Windows-specific bytes
+                if lower_charset_name.startswith("iso-8859") and detector.has_win_bytes:
+                    charset_name = detector.ISO_WIN_MAP.get(
+                        lower_charset_name, charset_name
+                    )
+                # Rename legacy encodings with superset encodings if asked
+                if should_rename_legacy:
+                    charset_name = detector.LEGACY_MAP.get(
+                        charset_name.lower(), charset_name
+                    )
+                results.append(
+                    {
+                        "encoding": charset_name,
+                        "confidence": prober.get_confidence(),
+                        "language": prober.language,
+                    }
+                )
+        if len(results) > 0:
+            return sorted(results, key=lambda result: -result["confidence"])
+
+    return [detector.result]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/big5freq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/big5freq.py
new file mode 100644
index 0000000000000000000000000000000000000000..87d9f972edde20d1f8e391b8010703242a8de977
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/big5freq.py
@@ -0,0 +1,386 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# Big5 frequency table
+# by Taiwan's Mandarin Promotion Council
+# 
+#
+# 128  --> 0.42261
+# 256  --> 0.57851
+# 512  --> 0.74851
+# 1024 --> 0.89384
+# 2048 --> 0.97583
+#
+# Ideal Distribution Ratio = 0.74851/(1-0.74851) =2.98
+# Random Distribution Ration = 512/(5401-512)=0.105
+#
+# Typical Distribution Ratio about 25% of Ideal one, still much higher than RDR
+
+BIG5_TYPICAL_DISTRIBUTION_RATIO = 0.75
+
+# Char to FreqOrder table
+BIG5_TABLE_SIZE = 5376
+# fmt: off
+BIG5_CHAR_TO_FREQ_ORDER = (
+   1,1801,1506, 255,1431, 198,   9,  82,   6,5008, 177, 202,3681,1256,2821, 110, #   16
+3814,  33,3274, 261,  76,  44,2114,  16,2946,2187,1176, 659,3971,  26,3451,2653, #   32
+1198,3972,3350,4202, 410,2215, 302, 590, 361,1964,   8, 204,  58,4510,5009,1932, #   48
+  63,5010,5011, 317,1614,  75, 222, 159,4203,2417,1480,5012,3555,3091, 224,2822, #   64
+3682,   3,  10,3973,1471,  29,2787,1135,2866,1940, 873, 130,3275,1123, 312,5013, #   80
+4511,2052, 507, 252, 682,5014, 142,1915, 124, 206,2947,  34,3556,3204,  64, 604, #   96
+5015,2501,1977,1978, 155,1991, 645, 641,1606,5016,3452, 337,  72, 406,5017,  80, #  112
+ 630, 238,3205,1509, 263, 939,1092,2654, 756,1440,1094,3453, 449,  69,2987, 591, #  128
+ 179,2096, 471, 115,2035,1844,  60,  50,2988, 134, 806,1869, 734,2036,3454, 180, #  144
+ 995,1607, 156, 537,2907, 688,5018, 319,1305, 779,2145, 514,2379, 298,4512, 359, #  160
+2502,  90,2716,1338, 663,  11, 906,1099,2553,  20,2441, 182, 532,1716,5019, 732, #  176
+1376,4204,1311,1420,3206,  25,2317,1056, 113, 399, 382,1950, 242,3455,2474, 529, #  192
+3276, 475,1447,3683,5020, 117,  21, 656, 810,1297,2300,2334,3557,5021, 126,4205, #  208
+ 706, 456, 150, 613,4513,  71,1118,2037,4206, 145,3092,  85, 835, 486,2115,1246, #  224
+1426, 428, 727,1285,1015, 800, 106, 623, 303,1281,5022,2128,2359, 347,3815, 221, #  240
+3558,3135,5023,1956,1153,4207,  83, 296,1199,3093, 192, 624,  93,5024, 822,1898, #  256
+2823,3136, 795,2065, 991,1554,1542,1592,  27,  43,2867, 859, 139,1456, 860,4514, #  272
+ 437, 712,3974, 164,2397,3137, 695, 211,3037,2097, 195,3975,1608,3559,3560,3684, #  288
+3976, 234, 811,2989,2098,3977,2233,1441,3561,1615,2380, 668,2077,1638, 305, 228, #  304
+1664,4515, 467, 415,5025, 262,2099,1593, 239, 108, 300, 200,1033, 512,1247,2078, #  320
+5026,5027,2176,3207,3685,2682, 593, 845,1062,3277,  88,1723,2038,3978,1951, 212, #  336
+ 266, 152, 149, 468,1899,4208,4516,  77, 187,5028,3038,  37,   5,2990,5029,3979, #  352
+5030,5031,  39,2524,4517,2908,3208,2079,  55, 148,  74,4518, 545, 483,1474,1029, #  368
+1665, 217,1870,1531,3138,1104,2655,4209,  24, 172,3562, 900,3980,3563,3564,4519, #  384
+  32,1408,2824,1312, 329, 487,2360,2251,2717, 784,2683,   4,3039,3351,1427,1789, #  400
+ 188, 109, 499,5032,3686,1717,1790, 888,1217,3040,4520,5033,3565,5034,3352,1520, #  416
+3687,3981, 196,1034, 775,5035,5036, 929,1816, 249, 439,  38,5037,1063,5038, 794, #  432
+3982,1435,2301,  46, 178,3278,2066,5039,2381,5040, 214,1709,4521, 804,  35, 707, #  448
+ 324,3688,1601,2554, 140, 459,4210,5041,5042,1365, 839, 272, 978,2262,2580,3456, #  464
+2129,1363,3689,1423, 697, 100,3094,  48,  70,1231, 495,3139,2196,5043,1294,5044, #  480
+2080, 462, 586,1042,3279, 853, 256, 988, 185,2382,3457,1698, 434,1084,5045,3458, #  496
+ 314,2625,2788,4522,2335,2336, 569,2285, 637,1817,2525, 757,1162,1879,1616,3459, #  512
+ 287,1577,2116, 768,4523,1671,2868,3566,2526,1321,3816, 909,2418,5046,4211, 933, #  528
+3817,4212,2053,2361,1222,4524, 765,2419,1322, 786,4525,5047,1920,1462,1677,2909, #  544
+1699,5048,4526,1424,2442,3140,3690,2600,3353,1775,1941,3460,3983,4213, 309,1369, #  560
+1130,2825, 364,2234,1653,1299,3984,3567,3985,3986,2656, 525,1085,3041, 902,2001, #  576
+1475, 964,4527, 421,1845,1415,1057,2286, 940,1364,3141, 376,4528,4529,1381,   7, #  592
+2527, 983,2383, 336,1710,2684,1846, 321,3461, 559,1131,3042,2752,1809,1132,1313, #  608
+ 265,1481,1858,5049, 352,1203,2826,3280, 167,1089, 420,2827, 776, 792,1724,3568, #  624
+4214,2443,3281,5050,4215,5051, 446, 229, 333,2753, 901,3818,1200,1557,4530,2657, #  640
+1921, 395,2754,2685,3819,4216,1836, 125, 916,3209,2626,4531,5052,5053,3820,5054, #  656
+5055,5056,4532,3142,3691,1133,2555,1757,3462,1510,2318,1409,3569,5057,2146, 438, #  672
+2601,2910,2384,3354,1068, 958,3043, 461, 311,2869,2686,4217,1916,3210,4218,1979, #  688
+ 383, 750,2755,2627,4219, 274, 539, 385,1278,1442,5058,1154,1965, 384, 561, 210, #  704
+  98,1295,2556,3570,5059,1711,2420,1482,3463,3987,2911,1257, 129,5060,3821, 642, #  720
+ 523,2789,2790,2658,5061, 141,2235,1333,  68, 176, 441, 876, 907,4220, 603,2602, #  736
+ 710, 171,3464, 404, 549,  18,3143,2398,1410,3692,1666,5062,3571,4533,2912,4534, #  752
+5063,2991, 368,5064, 146, 366,  99, 871,3693,1543, 748, 807,1586,1185,  22,2263, #  768
+ 379,3822,3211,5065,3212, 505,1942,2628,1992,1382,2319,5066, 380,2362, 218, 702, #  784
+1818,1248,3465,3044,3572,3355,3282,5067,2992,3694, 930,3283,3823,5068,  59,5069, #  800
+ 585, 601,4221, 497,3466,1112,1314,4535,1802,5070,1223,1472,2177,5071, 749,1837, #  816
+ 690,1900,3824,1773,3988,1476, 429,1043,1791,2236,2117, 917,4222, 447,1086,1629, #  832
+5072, 556,5073,5074,2021,1654, 844,1090, 105, 550, 966,1758,2828,1008,1783, 686, #  848
+1095,5075,2287, 793,1602,5076,3573,2603,4536,4223,2948,2302,4537,3825, 980,2503, #  864
+ 544, 353, 527,4538, 908,2687,2913,5077, 381,2629,1943,1348,5078,1341,1252, 560, #  880
+3095,5079,3467,2870,5080,2054, 973, 886,2081, 143,4539,5081,5082, 157,3989, 496, #  896
+4224,  57, 840, 540,2039,4540,4541,3468,2118,1445, 970,2264,1748,1966,2082,4225, #  912
+3144,1234,1776,3284,2829,3695, 773,1206,2130,1066,2040,1326,3990,1738,1725,4226, #  928
+ 279,3145,  51,1544,2604, 423,1578,2131,2067, 173,4542,1880,5083,5084,1583, 264, #  944
+ 610,3696,4543,2444, 280, 154,5085,5086,5087,1739, 338,1282,3096, 693,2871,1411, #  960
+1074,3826,2445,5088,4544,5089,5090,1240, 952,2399,5091,2914,1538,2688, 685,1483, #  976
+4227,2475,1436, 953,4228,2055,4545, 671,2400,  79,4229,2446,3285, 608, 567,2689, #  992
+3469,4230,4231,1691, 393,1261,1792,2401,5092,4546,5093,5094,5095,5096,1383,1672, # 1008
+3827,3213,1464, 522,1119, 661,1150, 216, 675,4547,3991,1432,3574, 609,4548,2690, # 1024
+2402,5097,5098,5099,4232,3045,   0,5100,2476, 315, 231,2447, 301,3356,4549,2385, # 1040
+5101, 233,4233,3697,1819,4550,4551,5102,  96,1777,1315,2083,5103, 257,5104,1810, # 1056
+3698,2718,1139,1820,4234,2022,1124,2164,2791,1778,2659,5105,3097, 363,1655,3214, # 1072
+5106,2993,5107,5108,5109,3992,1567,3993, 718, 103,3215, 849,1443, 341,3357,2949, # 1088
+1484,5110,1712, 127,  67, 339,4235,2403, 679,1412, 821,5111,5112, 834, 738, 351, # 1104
+2994,2147, 846, 235,1497,1881, 418,1993,3828,2719, 186,1100,2148,2756,3575,1545, # 1120
+1355,2950,2872,1377, 583,3994,4236,2581,2995,5113,1298,3699,1078,2557,3700,2363, # 1136
+  78,3829,3830, 267,1289,2100,2002,1594,4237, 348, 369,1274,2197,2178,1838,4552, # 1152
+1821,2830,3701,2757,2288,2003,4553,2951,2758, 144,3358, 882,4554,3995,2759,3470, # 1168
+4555,2915,5114,4238,1726, 320,5115,3996,3046, 788,2996,5116,2831,1774,1327,2873, # 1184
+3997,2832,5117,1306,4556,2004,1700,3831,3576,2364,2660, 787,2023, 506, 824,3702, # 1200
+ 534, 323,4557,1044,3359,2024,1901, 946,3471,5118,1779,1500,1678,5119,1882,4558, # 1216
+ 165, 243,4559,3703,2528, 123, 683,4239, 764,4560,  36,3998,1793, 589,2916, 816, # 1232
+ 626,1667,3047,2237,1639,1555,1622,3832,3999,5120,4000,2874,1370,1228,1933, 891, # 1248
+2084,2917, 304,4240,5121, 292,2997,2720,3577, 691,2101,4241,1115,4561, 118, 662, # 1264
+5122, 611,1156, 854,2386,1316,2875,   2, 386, 515,2918,5123,5124,3286, 868,2238, # 1280
+1486, 855,2661, 785,2216,3048,5125,1040,3216,3578,5126,3146, 448,5127,1525,5128, # 1296
+2165,4562,5129,3833,5130,4242,2833,3579,3147, 503, 818,4001,3148,1568, 814, 676, # 1312
+1444, 306,1749,5131,3834,1416,1030, 197,1428, 805,2834,1501,4563,5132,5133,5134, # 1328
+1994,5135,4564,5136,5137,2198,  13,2792,3704,2998,3149,1229,1917,5138,3835,2132, # 1344
+5139,4243,4565,2404,3580,5140,2217,1511,1727,1120,5141,5142, 646,3836,2448, 307, # 1360
+5143,5144,1595,3217,5145,5146,5147,3705,1113,1356,4002,1465,2529,2530,5148, 519, # 1376
+5149, 128,2133,  92,2289,1980,5150,4003,1512, 342,3150,2199,5151,2793,2218,1981, # 1392
+3360,4244, 290,1656,1317, 789, 827,2365,5152,3837,4566, 562, 581,4004,5153, 401, # 1408
+4567,2252,  94,4568,5154,1399,2794,5155,1463,2025,4569,3218,1944,5156, 828,1105, # 1424
+4245,1262,1394,5157,4246, 605,4570,5158,1784,2876,5159,2835, 819,2102, 578,2200, # 1440
+2952,5160,1502, 436,3287,4247,3288,2836,4005,2919,3472,3473,5161,2721,2320,5162, # 1456
+5163,2337,2068,  23,4571, 193, 826,3838,2103, 699,1630,4248,3098, 390,1794,1064, # 1472
+3581,5164,1579,3099,3100,1400,5165,4249,1839,1640,2877,5166,4572,4573, 137,4250, # 1488
+ 598,3101,1967, 780, 104, 974,2953,5167, 278, 899, 253, 402, 572, 504, 493,1339, # 1504
+5168,4006,1275,4574,2582,2558,5169,3706,3049,3102,2253, 565,1334,2722, 863,  41, # 1520
+5170,5171,4575,5172,1657,2338,  19, 463,2760,4251, 606,5173,2999,3289,1087,2085, # 1536
+1323,2662,3000,5174,1631,1623,1750,4252,2691,5175,2878, 791,2723,2663,2339, 232, # 1552
+2421,5176,3001,1498,5177,2664,2630, 755,1366,3707,3290,3151,2026,1609, 119,1918, # 1568
+3474, 862,1026,4253,5178,4007,3839,4576,4008,4577,2265,1952,2477,5179,1125, 817, # 1584
+4254,4255,4009,1513,1766,2041,1487,4256,3050,3291,2837,3840,3152,5180,5181,1507, # 1600
+5182,2692, 733,  40,1632,1106,2879, 345,4257, 841,2531, 230,4578,3002,1847,3292, # 1616
+3475,5183,1263, 986,3476,5184, 735, 879, 254,1137, 857, 622,1300,1180,1388,1562, # 1632
+4010,4011,2954, 967,2761,2665,1349, 592,2134,1692,3361,3003,1995,4258,1679,4012, # 1648
+1902,2188,5185, 739,3708,2724,1296,1290,5186,4259,2201,2202,1922,1563,2605,2559, # 1664
+1871,2762,3004,5187, 435,5188, 343,1108, 596,  17,1751,4579,2239,3477,3709,5189, # 1680
+4580, 294,3582,2955,1693, 477, 979, 281,2042,3583, 643,2043,3710,2631,2795,2266, # 1696
+1031,2340,2135,2303,3584,4581, 367,1249,2560,5190,3585,5191,4582,1283,3362,2005, # 1712
+ 240,1762,3363,4583,4584, 836,1069,3153, 474,5192,2149,2532, 268,3586,5193,3219, # 1728
+1521,1284,5194,1658,1546,4260,5195,3587,3588,5196,4261,3364,2693,1685,4262, 961, # 1744
+1673,2632, 190,2006,2203,3841,4585,4586,5197, 570,2504,3711,1490,5198,4587,2633, # 1760
+3293,1957,4588, 584,1514, 396,1045,1945,5199,4589,1968,2449,5200,5201,4590,4013, # 1776
+ 619,5202,3154,3294, 215,2007,2796,2561,3220,4591,3221,4592, 763,4263,3842,4593, # 1792
+5203,5204,1958,1767,2956,3365,3712,1174, 452,1477,4594,3366,3155,5205,2838,1253, # 1808
+2387,2189,1091,2290,4264, 492,5206, 638,1169,1825,2136,1752,4014, 648, 926,1021, # 1824
+1324,4595, 520,4596, 997, 847,1007, 892,4597,3843,2267,1872,3713,2405,1785,4598, # 1840
+1953,2957,3103,3222,1728,4265,2044,3714,4599,2008,1701,3156,1551,  30,2268,4266, # 1856
+5207,2027,4600,3589,5208, 501,5209,4267, 594,3478,2166,1822,3590,3479,3591,3223, # 1872
+ 829,2839,4268,5210,1680,3157,1225,4269,5211,3295,4601,4270,3158,2341,5212,4602, # 1888
+4271,5213,4015,4016,5214,1848,2388,2606,3367,5215,4603, 374,4017, 652,4272,4273, # 1904
+ 375,1140, 798,5216,5217,5218,2366,4604,2269, 546,1659, 138,3051,2450,4605,5219, # 1920
+2254, 612,1849, 910, 796,3844,1740,1371, 825,3845,3846,5220,2920,2562,5221, 692, # 1936
+ 444,3052,2634, 801,4606,4274,5222,1491, 244,1053,3053,4275,4276, 340,5223,4018, # 1952
+1041,3005, 293,1168,  87,1357,5224,1539, 959,5225,2240, 721, 694,4277,3847, 219, # 1968
+1478, 644,1417,3368,2666,1413,1401,1335,1389,4019,5226,5227,3006,2367,3159,1826, # 1984
+ 730,1515, 184,2840,  66,4607,5228,1660,2958, 246,3369, 378,1457, 226,3480, 975, # 2000
+4020,2959,1264,3592, 674, 696,5229, 163,5230,1141,2422,2167, 713,3593,3370,4608, # 2016
+4021,5231,5232,1186,  15,5233,1079,1070,5234,1522,3224,3594, 276,1050,2725, 758, # 2032
+1126, 653,2960,3296,5235,2342, 889,3595,4022,3104,3007, 903,1250,4609,4023,3481, # 2048
+3596,1342,1681,1718, 766,3297, 286,  89,2961,3715,5236,1713,5237,2607,3371,3008, # 2064
+5238,2962,2219,3225,2880,5239,4610,2505,2533, 181, 387,1075,4024, 731,2190,3372, # 2080
+5240,3298, 310, 313,3482,2304, 770,4278,  54,3054, 189,4611,3105,3848,4025,5241, # 2096
+1230,1617,1850, 355,3597,4279,4612,3373, 111,4280,3716,1350,3160,3483,3055,4281, # 2112
+2150,3299,3598,5242,2797,4026,4027,3009, 722,2009,5243,1071, 247,1207,2343,2478, # 2128
+1378,4613,2010, 864,1437,1214,4614, 373,3849,1142,2220, 667,4615, 442,2763,2563, # 2144
+3850,4028,1969,4282,3300,1840, 837, 170,1107, 934,1336,1883,5244,5245,2119,4283, # 2160
+2841, 743,1569,5246,4616,4284, 582,2389,1418,3484,5247,1803,5248, 357,1395,1729, # 2176
+3717,3301,2423,1564,2241,5249,3106,3851,1633,4617,1114,2086,4285,1532,5250, 482, # 2192
+2451,4618,5251,5252,1492, 833,1466,5253,2726,3599,1641,2842,5254,1526,1272,3718, # 2208
+4286,1686,1795, 416,2564,1903,1954,1804,5255,3852,2798,3853,1159,2321,5256,2881, # 2224
+4619,1610,1584,3056,2424,2764, 443,3302,1163,3161,5257,5258,4029,5259,4287,2506, # 2240
+3057,4620,4030,3162,2104,1647,3600,2011,1873,4288,5260,4289, 431,3485,5261, 250, # 2256
+  97,  81,4290,5262,1648,1851,1558, 160, 848,5263, 866, 740,1694,5264,2204,2843, # 2272
+3226,4291,4621,3719,1687, 950,2479, 426, 469,3227,3720,3721,4031,5265,5266,1188, # 2288
+ 424,1996, 861,3601,4292,3854,2205,2694, 168,1235,3602,4293,5267,2087,1674,4622, # 2304
+3374,3303, 220,2565,1009,5268,3855, 670,3010, 332,1208, 717,5269,5270,3603,2452, # 2320
+4032,3375,5271, 513,5272,1209,2882,3376,3163,4623,1080,5273,5274,5275,5276,2534, # 2336
+3722,3604, 815,1587,4033,4034,5277,3605,3486,3856,1254,4624,1328,3058,1390,4035, # 2352
+1741,4036,3857,4037,5278, 236,3858,2453,3304,5279,5280,3723,3859,1273,3860,4625, # 2368
+5281, 308,5282,4626, 245,4627,1852,2480,1307,2583, 430, 715,2137,2454,5283, 270, # 2384
+ 199,2883,4038,5284,3606,2727,1753, 761,1754, 725,1661,1841,4628,3487,3724,5285, # 2400
+5286, 587,  14,3305, 227,2608, 326, 480,2270, 943,2765,3607, 291, 650,1884,5287, # 2416
+1702,1226, 102,1547,  62,3488, 904,4629,3489,1164,4294,5288,5289,1224,1548,2766, # 2432
+ 391, 498,1493,5290,1386,1419,5291,2056,1177,4630, 813, 880,1081,2368, 566,1145, # 2448
+4631,2291,1001,1035,2566,2609,2242, 394,1286,5292,5293,2069,5294,  86,1494,1730, # 2464
+4039, 491,1588, 745, 897,2963, 843,3377,4040,2767,2884,3306,1768, 998,2221,2070, # 2480
+ 397,1827,1195,1970,3725,3011,3378, 284,5295,3861,2507,2138,2120,1904,5296,4041, # 2496
+2151,4042,4295,1036,3490,1905, 114,2567,4296, 209,1527,5297,5298,2964,2844,2635, # 2512
+2390,2728,3164, 812,2568,5299,3307,5300,1559, 737,1885,3726,1210, 885,  28,2695, # 2528
+3608,3862,5301,4297,1004,1780,4632,5302, 346,1982,2222,2696,4633,3863,1742, 797, # 2544
+1642,4043,1934,1072,1384,2152, 896,4044,3308,3727,3228,2885,3609,5303,2569,1959, # 2560
+4634,2455,1786,5304,5305,5306,4045,4298,1005,1308,3728,4299,2729,4635,4636,1528, # 2576
+2610, 161,1178,4300,1983, 987,4637,1101,4301, 631,4046,1157,3229,2425,1343,1241, # 2592
+1016,2243,2570, 372, 877,2344,2508,1160, 555,1935, 911,4047,5307, 466,1170, 169, # 2608
+1051,2921,2697,3729,2481,3012,1182,2012,2571,1251,2636,5308, 992,2345,3491,1540, # 2624
+2730,1201,2071,2406,1997,2482,5309,4638, 528,1923,2191,1503,1874,1570,2369,3379, # 2640
+3309,5310, 557,1073,5311,1828,3492,2088,2271,3165,3059,3107, 767,3108,2799,4639, # 2656
+1006,4302,4640,2346,1267,2179,3730,3230, 778,4048,3231,2731,1597,2667,5312,4641, # 2672
+5313,3493,5314,5315,5316,3310,2698,1433,3311, 131,  95,1504,4049, 723,4303,3166, # 2688
+1842,3610,2768,2192,4050,2028,2105,3731,5317,3013,4051,1218,5318,3380,3232,4052, # 2704
+4304,2584, 248,1634,3864, 912,5319,2845,3732,3060,3865, 654,  53,5320,3014,5321, # 2720
+1688,4642, 777,3494,1032,4053,1425,5322, 191, 820,2121,2846, 971,4643, 931,3233, # 2736
+ 135, 664, 783,3866,1998, 772,2922,1936,4054,3867,4644,2923,3234, 282,2732, 640, # 2752
+1372,3495,1127, 922, 325,3381,5323,5324, 711,2045,5325,5326,4055,2223,2800,1937, # 2768
+4056,3382,2224,2255,3868,2305,5327,4645,3869,1258,3312,4057,3235,2139,2965,4058, # 2784
+4059,5328,2225, 258,3236,4646, 101,1227,5329,3313,1755,5330,1391,3314,5331,2924, # 2800
+2057, 893,5332,5333,5334,1402,4305,2347,5335,5336,3237,3611,5337,5338, 878,1325, # 2816
+1781,2801,4647, 259,1385,2585, 744,1183,2272,4648,5339,4060,2509,5340, 684,1024, # 2832
+4306,5341, 472,3612,3496,1165,3315,4061,4062, 322,2153, 881, 455,1695,1152,1340, # 2848
+ 660, 554,2154,4649,1058,4650,4307, 830,1065,3383,4063,4651,1924,5342,1703,1919, # 2864
+5343, 932,2273, 122,5344,4652, 947, 677,5345,3870,2637, 297,1906,1925,2274,4653, # 2880
+2322,3316,5346,5347,4308,5348,4309,  84,4310, 112, 989,5349, 547,1059,4064, 701, # 2896
+3613,1019,5350,4311,5351,3497, 942, 639, 457,2306,2456, 993,2966, 407, 851, 494, # 2912
+4654,3384, 927,5352,1237,5353,2426,3385, 573,4312, 680, 921,2925,1279,1875, 285, # 2928
+ 790,1448,1984, 719,2168,5354,5355,4655,4065,4066,1649,5356,1541, 563,5357,1077, # 2944
+5358,3386,3061,3498, 511,3015,4067,4068,3733,4069,1268,2572,3387,3238,4656,4657, # 2960
+5359, 535,1048,1276,1189,2926,2029,3167,1438,1373,2847,2967,1134,2013,5360,4313, # 2976
+1238,2586,3109,1259,5361, 700,5362,2968,3168,3734,4314,5363,4315,1146,1876,1907, # 2992
+4658,2611,4070, 781,2427, 132,1589, 203, 147, 273,2802,2407, 898,1787,2155,4071, # 3008
+4072,5364,3871,2803,5365,5366,4659,4660,5367,3239,5368,1635,3872, 965,5369,1805, # 3024
+2699,1516,3614,1121,1082,1329,3317,4073,1449,3873,  65,1128,2848,2927,2769,1590, # 3040
+3874,5370,5371,  12,2668,  45, 976,2587,3169,4661, 517,2535,1013,1037,3240,5372, # 3056
+3875,2849,5373,3876,5374,3499,5375,2612, 614,1999,2323,3877,3110,2733,2638,5376, # 3072
+2588,4316, 599,1269,5377,1811,3735,5378,2700,3111, 759,1060, 489,1806,3388,3318, # 3088
+1358,5379,5380,2391,1387,1215,2639,2256, 490,5381,5382,4317,1759,2392,2348,5383, # 3104
+4662,3878,1908,4074,2640,1807,3241,4663,3500,3319,2770,2349, 874,5384,5385,3501, # 3120
+3736,1859,  91,2928,3737,3062,3879,4664,5386,3170,4075,2669,5387,3502,1202,1403, # 3136
+3880,2969,2536,1517,2510,4665,3503,2511,5388,4666,5389,2701,1886,1495,1731,4076, # 3152
+2370,4667,5390,2030,5391,5392,4077,2702,1216, 237,2589,4318,2324,4078,3881,4668, # 3168
+4669,2703,3615,3504, 445,4670,5393,5394,5395,5396,2771,  61,4079,3738,1823,4080, # 3184
+5397, 687,2046, 935, 925, 405,2670, 703,1096,1860,2734,4671,4081,1877,1367,2704, # 3200
+3389, 918,2106,1782,2483, 334,3320,1611,1093,4672, 564,3171,3505,3739,3390, 945, # 3216
+2641,2058,4673,5398,1926, 872,4319,5399,3506,2705,3112, 349,4320,3740,4082,4674, # 3232
+3882,4321,3741,2156,4083,4675,4676,4322,4677,2408,2047, 782,4084, 400, 251,4323, # 3248
+1624,5400,5401, 277,3742, 299,1265, 476,1191,3883,2122,4324,4325,1109, 205,5402, # 3264
+2590,1000,2157,3616,1861,5403,5404,5405,4678,5406,4679,2573, 107,2484,2158,4085, # 3280
+3507,3172,5407,1533, 541,1301, 158, 753,4326,2886,3617,5408,1696, 370,1088,4327, # 3296
+4680,3618, 579, 327, 440, 162,2244, 269,1938,1374,3508, 968,3063,  56,1396,3113, # 3312
+2107,3321,3391,5409,1927,2159,4681,3016,5410,3619,5411,5412,3743,4682,2485,5413, # 3328
+2804,5414,1650,4683,5415,2613,5416,5417,4086,2671,3392,1149,3393,4087,3884,4088, # 3344
+5418,1076,  49,5419, 951,3242,3322,3323, 450,2850, 920,5420,1812,2805,2371,4328, # 3360
+1909,1138,2372,3885,3509,5421,3243,4684,1910,1147,1518,2428,4685,3886,5422,4686, # 3376
+2393,2614, 260,1796,3244,5423,5424,3887,3324, 708,5425,3620,1704,5426,3621,1351, # 3392
+1618,3394,3017,1887, 944,4329,3395,4330,3064,3396,4331,5427,3744, 422, 413,1714, # 3408
+3325, 500,2059,2350,4332,2486,5428,1344,1911, 954,5429,1668,5430,5431,4089,2409, # 3424
+4333,3622,3888,4334,5432,2307,1318,2512,3114, 133,3115,2887,4687, 629,  31,2851, # 3440
+2706,3889,4688, 850, 949,4689,4090,2970,1732,2089,4335,1496,1853,5433,4091, 620, # 3456
+3245, 981,1242,3745,3397,1619,3746,1643,3326,2140,2457,1971,1719,3510,2169,5434, # 3472
+3246,5435,5436,3398,1829,5437,1277,4690,1565,2048,5438,1636,3623,3116,5439, 869, # 3488
+2852, 655,3890,3891,3117,4092,3018,3892,1310,3624,4691,5440,5441,5442,1733, 558, # 3504
+4692,3747, 335,1549,3065,1756,4336,3748,1946,3511,1830,1291,1192, 470,2735,2108, # 3520
+2806, 913,1054,4093,5443,1027,5444,3066,4094,4693, 982,2672,3399,3173,3512,3247, # 3536
+3248,1947,2807,5445, 571,4694,5446,1831,5447,3625,2591,1523,2429,5448,2090, 984, # 3552
+4695,3749,1960,5449,3750, 852, 923,2808,3513,3751, 969,1519, 999,2049,2325,1705, # 3568
+5450,3118, 615,1662, 151, 597,4095,2410,2326,1049, 275,4696,3752,4337, 568,3753, # 3584
+3626,2487,4338,3754,5451,2430,2275, 409,3249,5452,1566,2888,3514,1002, 769,2853, # 3600
+ 194,2091,3174,3755,2226,3327,4339, 628,1505,5453,5454,1763,2180,3019,4096, 521, # 3616
+1161,2592,1788,2206,2411,4697,4097,1625,4340,4341, 412,  42,3119, 464,5455,2642, # 3632
+4698,3400,1760,1571,2889,3515,2537,1219,2207,3893,2643,2141,2373,4699,4700,3328, # 3648
+1651,3401,3627,5456,5457,3628,2488,3516,5458,3756,5459,5460,2276,2092, 460,5461, # 3664
+4701,5462,3020, 962, 588,3629, 289,3250,2644,1116,  52,5463,3067,1797,5464,5465, # 3680
+5466,1467,5467,1598,1143,3757,4342,1985,1734,1067,4702,1280,3402, 465,4703,1572, # 3696
+ 510,5468,1928,2245,1813,1644,3630,5469,4704,3758,5470,5471,2673,1573,1534,5472, # 3712
+5473, 536,1808,1761,3517,3894,3175,2645,5474,5475,5476,4705,3518,2929,1912,2809, # 3728
+5477,3329,1122, 377,3251,5478, 360,5479,5480,4343,1529, 551,5481,2060,3759,1769, # 3744
+2431,5482,2930,4344,3330,3120,2327,2109,2031,4706,1404, 136,1468,1479, 672,1171, # 3760
+3252,2308, 271,3176,5483,2772,5484,2050, 678,2736, 865,1948,4707,5485,2014,4098, # 3776
+2971,5486,2737,2227,1397,3068,3760,4708,4709,1735,2931,3403,3631,5487,3895, 509, # 3792
+2854,2458,2890,3896,5488,5489,3177,3178,4710,4345,2538,4711,2309,1166,1010, 552, # 3808
+ 681,1888,5490,5491,2972,2973,4099,1287,1596,1862,3179, 358, 453, 736, 175, 478, # 3824
+1117, 905,1167,1097,5492,1854,1530,5493,1706,5494,2181,3519,2292,3761,3520,3632, # 3840
+4346,2093,4347,5495,3404,1193,2489,4348,1458,2193,2208,1863,1889,1421,3331,2932, # 3856
+3069,2182,3521, 595,2123,5496,4100,5497,5498,4349,1707,2646, 223,3762,1359, 751, # 3872
+3121, 183,3522,5499,2810,3021, 419,2374, 633, 704,3897,2394, 241,5500,5501,5502, # 3888
+ 838,3022,3763,2277,2773,2459,3898,1939,2051,4101,1309,3122,2246,1181,5503,1136, # 3904
+2209,3899,2375,1446,4350,2310,4712,5504,5505,4351,1055,2615, 484,3764,5506,4102, # 3920
+ 625,4352,2278,3405,1499,4353,4103,5507,4104,4354,3253,2279,2280,3523,5508,5509, # 3936
+2774, 808,2616,3765,3406,4105,4355,3123,2539, 526,3407,3900,4356, 955,5510,1620, # 3952
+4357,2647,2432,5511,1429,3766,1669,1832, 994, 928,5512,3633,1260,5513,5514,5515, # 3968
+1949,2293, 741,2933,1626,4358,2738,2460, 867,1184, 362,3408,1392,5516,5517,4106, # 3984
+4359,1770,1736,3254,2934,4713,4714,1929,2707,1459,1158,5518,3070,3409,2891,1292, # 4000
+1930,2513,2855,3767,1986,1187,2072,2015,2617,4360,5519,2574,2514,2170,3768,2490, # 4016
+3332,5520,3769,4715,5521,5522, 666,1003,3023,1022,3634,4361,5523,4716,1814,2257, # 4032
+ 574,3901,1603, 295,1535, 705,3902,4362, 283, 858, 417,5524,5525,3255,4717,4718, # 4048
+3071,1220,1890,1046,2281,2461,4107,1393,1599, 689,2575, 388,4363,5526,2491, 802, # 4064
+5527,2811,3903,2061,1405,2258,5528,4719,3904,2110,1052,1345,3256,1585,5529, 809, # 4080
+5530,5531,5532, 575,2739,3524, 956,1552,1469,1144,2328,5533,2329,1560,2462,3635, # 4096
+3257,4108, 616,2210,4364,3180,2183,2294,5534,1833,5535,3525,4720,5536,1319,3770, # 4112
+3771,1211,3636,1023,3258,1293,2812,5537,5538,5539,3905, 607,2311,3906, 762,2892, # 4128
+1439,4365,1360,4721,1485,3072,5540,4722,1038,4366,1450,2062,2648,4367,1379,4723, # 4144
+2593,5541,5542,4368,1352,1414,2330,2935,1172,5543,5544,3907,3908,4724,1798,1451, # 4160
+5545,5546,5547,5548,2936,4109,4110,2492,2351, 411,4111,4112,3637,3333,3124,4725, # 4176
+1561,2674,1452,4113,1375,5549,5550,  47,2974, 316,5551,1406,1591,2937,3181,5552, # 4192
+1025,2142,3125,3182, 354,2740, 884,2228,4369,2412, 508,3772, 726,3638, 996,2433, # 4208
+3639, 729,5553, 392,2194,1453,4114,4726,3773,5554,5555,2463,3640,2618,1675,2813, # 4224
+ 919,2352,2975,2353,1270,4727,4115,  73,5556,5557, 647,5558,3259,2856,2259,1550, # 4240
+1346,3024,5559,1332, 883,3526,5560,5561,5562,5563,3334,2775,5564,1212, 831,1347, # 4256
+4370,4728,2331,3909,1864,3073, 720,3910,4729,4730,3911,5565,4371,5566,5567,4731, # 4272
+5568,5569,1799,4732,3774,2619,4733,3641,1645,2376,4734,5570,2938, 669,2211,2675, # 4288
+2434,5571,2893,5572,5573,1028,3260,5574,4372,2413,5575,2260,1353,5576,5577,4735, # 4304
+3183, 518,5578,4116,5579,4373,1961,5580,2143,4374,5581,5582,3025,2354,2355,3912, # 4320
+ 516,1834,1454,4117,2708,4375,4736,2229,2620,1972,1129,3642,5583,2776,5584,2976, # 4336
+1422, 577,1470,3026,1524,3410,5585,5586, 432,4376,3074,3527,5587,2594,1455,2515, # 4352
+2230,1973,1175,5588,1020,2741,4118,3528,4737,5589,2742,5590,1743,1361,3075,3529, # 4368
+2649,4119,4377,4738,2295, 895, 924,4378,2171, 331,2247,3076, 166,1627,3077,1098, # 4384
+5591,1232,2894,2231,3411,4739, 657, 403,1196,2377, 542,3775,3412,1600,4379,3530, # 4400
+5592,4740,2777,3261, 576, 530,1362,4741,4742,2540,2676,3776,4120,5593, 842,3913, # 4416
+5594,2814,2032,1014,4121, 213,2709,3413, 665, 621,4380,5595,3777,2939,2435,5596, # 4432
+2436,3335,3643,3414,4743,4381,2541,4382,4744,3644,1682,4383,3531,1380,5597, 724, # 4448
+2282, 600,1670,5598,1337,1233,4745,3126,2248,5599,1621,4746,5600, 651,4384,5601, # 4464
+1612,4385,2621,5602,2857,5603,2743,2312,3078,5604, 716,2464,3079, 174,1255,2710, # 4480
+4122,3645, 548,1320,1398, 728,4123,1574,5605,1891,1197,3080,4124,5606,3081,3082, # 4496
+3778,3646,3779, 747,5607, 635,4386,4747,5608,5609,5610,4387,5611,5612,4748,5613, # 4512
+3415,4749,2437, 451,5614,3780,2542,2073,4388,2744,4389,4125,5615,1764,4750,5616, # 4528
+4390, 350,4751,2283,2395,2493,5617,4391,4126,2249,1434,4127, 488,4752, 458,4392, # 4544
+4128,3781, 771,1330,2396,3914,2576,3184,2160,2414,1553,2677,3185,4393,5618,2494, # 4560
+2895,2622,1720,2711,4394,3416,4753,5619,2543,4395,5620,3262,4396,2778,5621,2016, # 4576
+2745,5622,1155,1017,3782,3915,5623,3336,2313, 201,1865,4397,1430,5624,4129,5625, # 4592
+5626,5627,5628,5629,4398,1604,5630, 414,1866, 371,2595,4754,4755,3532,2017,3127, # 4608
+4756,1708, 960,4399, 887, 389,2172,1536,1663,1721,5631,2232,4130,2356,2940,1580, # 4624
+5632,5633,1744,4757,2544,4758,4759,5634,4760,5635,2074,5636,4761,3647,3417,2896, # 4640
+4400,5637,4401,2650,3418,2815, 673,2712,2465, 709,3533,4131,3648,4402,5638,1148, # 4656
+ 502, 634,5639,5640,1204,4762,3649,1575,4763,2623,3783,5641,3784,3128, 948,3263, # 4672
+ 121,1745,3916,1110,5642,4403,3083,2516,3027,4132,3785,1151,1771,3917,1488,4133, # 4688
+1987,5643,2438,3534,5644,5645,2094,5646,4404,3918,1213,1407,2816, 531,2746,2545, # 4704
+3264,1011,1537,4764,2779,4405,3129,1061,5647,3786,3787,1867,2897,5648,2018, 120, # 4720
+4406,4407,2063,3650,3265,2314,3919,2678,3419,1955,4765,4134,5649,3535,1047,2713, # 4736
+1266,5650,1368,4766,2858, 649,3420,3920,2546,2747,1102,2859,2679,5651,5652,2000, # 4752
+5653,1111,3651,2977,5654,2495,3921,3652,2817,1855,3421,3788,5655,5656,3422,2415, # 4768
+2898,3337,3266,3653,5657,2577,5658,3654,2818,4135,1460, 856,5659,3655,5660,2899, # 4784
+2978,5661,2900,3922,5662,4408, 632,2517, 875,3923,1697,3924,2296,5663,5664,4767, # 4800
+3028,1239, 580,4768,4409,5665, 914, 936,2075,1190,4136,1039,2124,5666,5667,5668, # 4816
+5669,3423,1473,5670,1354,4410,3925,4769,2173,3084,4137, 915,3338,4411,4412,3339, # 4832
+1605,1835,5671,2748, 398,3656,4413,3926,4138, 328,1913,2860,4139,3927,1331,4414, # 4848
+3029, 937,4415,5672,3657,4140,4141,3424,2161,4770,3425, 524, 742, 538,3085,1012, # 4864
+5673,5674,3928,2466,5675, 658,1103, 225,3929,5676,5677,4771,5678,4772,5679,3267, # 4880
+1243,5680,4142, 963,2250,4773,5681,2714,3658,3186,5682,5683,2596,2332,5684,4774, # 4896
+5685,5686,5687,3536, 957,3426,2547,2033,1931,2941,2467, 870,2019,3659,1746,2780, # 4912
+2781,2439,2468,5688,3930,5689,3789,3130,3790,3537,3427,3791,5690,1179,3086,5691, # 4928
+3187,2378,4416,3792,2548,3188,3131,2749,4143,5692,3428,1556,2549,2297, 977,2901, # 4944
+2034,4144,1205,3429,5693,1765,3430,3189,2125,1271, 714,1689,4775,3538,5694,2333, # 4960
+3931, 533,4417,3660,2184, 617,5695,2469,3340,3539,2315,5696,5697,3190,5698,5699, # 4976
+3932,1988, 618, 427,2651,3540,3431,5700,5701,1244,1690,5702,2819,4418,4776,5703, # 4992
+3541,4777,5704,2284,1576, 473,3661,4419,3432, 972,5705,3662,5706,3087,5707,5708, # 5008
+4778,4779,5709,3793,4145,4146,5710, 153,4780, 356,5711,1892,2902,4420,2144, 408, # 5024
+ 803,2357,5712,3933,5713,4421,1646,2578,2518,4781,4782,3934,5714,3935,4422,5715, # 5040
+2416,3433, 752,5716,5717,1962,3341,2979,5718, 746,3030,2470,4783,4423,3794, 698, # 5056
+4784,1893,4424,3663,2550,4785,3664,3936,5719,3191,3434,5720,1824,1302,4147,2715, # 5072
+3937,1974,4425,5721,4426,3192, 823,1303,1288,1236,2861,3542,4148,3435, 774,3938, # 5088
+5722,1581,4786,1304,2862,3939,4787,5723,2440,2162,1083,3268,4427,4149,4428, 344, # 5104
+1173, 288,2316, 454,1683,5724,5725,1461,4788,4150,2597,5726,5727,4789, 985, 894, # 5120
+5728,3436,3193,5729,1914,2942,3795,1989,5730,2111,1975,5731,4151,5732,2579,1194, # 5136
+ 425,5733,4790,3194,1245,3796,4429,5734,5735,2863,5736, 636,4791,1856,3940, 760, # 5152
+1800,5737,4430,2212,1508,4792,4152,1894,1684,2298,5738,5739,4793,4431,4432,2213, # 5168
+ 479,5740,5741, 832,5742,4153,2496,5743,2980,2497,3797, 990,3132, 627,1815,2652, # 5184
+4433,1582,4434,2126,2112,3543,4794,5744, 799,4435,3195,5745,4795,2113,1737,3031, # 5200
+1018, 543, 754,4436,3342,1676,4796,4797,4154,4798,1489,5746,3544,5747,2624,2903, # 5216
+4155,5748,5749,2981,5750,5751,5752,5753,3196,4799,4800,2185,1722,5754,3269,3270, # 5232
+1843,3665,1715, 481, 365,1976,1857,5755,5756,1963,2498,4801,5757,2127,3666,3271, # 5248
+ 433,1895,2064,2076,5758, 602,2750,5759,5760,5761,5762,5763,3032,1628,3437,5764, # 5264
+3197,4802,4156,2904,4803,2519,5765,2551,2782,5766,5767,5768,3343,4804,2905,5769, # 5280
+4805,5770,2864,4806,4807,1221,2982,4157,2520,5771,5772,5773,1868,1990,5774,5775, # 5296
+5776,1896,5777,5778,4808,1897,4158, 318,5779,2095,4159,4437,5780,5781, 485,5782, # 5312
+ 938,3941, 553,2680, 116,5783,3942,3667,5784,3545,2681,2783,3438,3344,2820,5785, # 5328
+3668,2943,4160,1747,2944,2983,5786,5787, 207,5788,4809,5789,4810,2521,5790,3033, # 5344
+ 890,3669,3943,5791,1878,3798,3439,5792,2186,2358,3440,1652,5793,5794,5795, 941, # 5360
+2299, 208,3546,4161,2020, 330,4438,3944,2906,2499,3799,4439,4811,5796,5797,5798, # 5376
+)
+# fmt: on
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/big5prober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/big5prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..ef09c60e327a0122e32f95f2f10a826a033c573c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/big5prober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import Big5DistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import BIG5_SM_MODEL
+
+
+class Big5Prober(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(BIG5_SM_MODEL)
+        self.distribution_analyzer = Big5DistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "Big5"
+
+    @property
+    def language(self) -> str:
+        return "Chinese"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/chardistribution.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/chardistribution.py
new file mode 100644
index 0000000000000000000000000000000000000000..176cb996408e6681a88722783919efc0e9dafb29
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/chardistribution.py
@@ -0,0 +1,261 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Tuple, Union
+
+from .big5freq import (
+    BIG5_CHAR_TO_FREQ_ORDER,
+    BIG5_TABLE_SIZE,
+    BIG5_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .euckrfreq import (
+    EUCKR_CHAR_TO_FREQ_ORDER,
+    EUCKR_TABLE_SIZE,
+    EUCKR_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .euctwfreq import (
+    EUCTW_CHAR_TO_FREQ_ORDER,
+    EUCTW_TABLE_SIZE,
+    EUCTW_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .gb2312freq import (
+    GB2312_CHAR_TO_FREQ_ORDER,
+    GB2312_TABLE_SIZE,
+    GB2312_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .jisfreq import (
+    JIS_CHAR_TO_FREQ_ORDER,
+    JIS_TABLE_SIZE,
+    JIS_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .johabfreq import JOHAB_TO_EUCKR_ORDER_TABLE
+
+
+class CharDistributionAnalysis:
+    ENOUGH_DATA_THRESHOLD = 1024
+    SURE_YES = 0.99
+    SURE_NO = 0.01
+    MINIMUM_DATA_THRESHOLD = 3
+
+    def __init__(self) -> None:
+        # Mapping table to get frequency order from char order (get from
+        # GetOrder())
+        self._char_to_freq_order: Tuple[int, ...] = tuple()
+        self._table_size = 0  # Size of above table
+        # This is a constant value which varies from language to language,
+        # used in calculating confidence.  See
+        # http://www.mozilla.org/projects/intl/UniversalCharsetDetection.html
+        # for further detail.
+        self.typical_distribution_ratio = 0.0
+        self._done = False
+        self._total_chars = 0
+        self._freq_chars = 0
+        self.reset()
+
+    def reset(self) -> None:
+        """reset analyser, clear any state"""
+        # If this flag is set to True, detection is done and conclusion has
+        # been made
+        self._done = False
+        self._total_chars = 0  # Total characters encountered
+        # The number of characters whose frequency order is less than 512
+        self._freq_chars = 0
+
+    def feed(self, char: Union[bytes, bytearray], char_len: int) -> None:
+        """feed a character with known length"""
+        if char_len == 2:
+            # we only care about 2-bytes character in our distribution analysis
+            order = self.get_order(char)
+        else:
+            order = -1
+        if order >= 0:
+            self._total_chars += 1
+            # order is valid
+            if order < self._table_size:
+                if 512 > self._char_to_freq_order[order]:
+                    self._freq_chars += 1
+
+    def get_confidence(self) -> float:
+        """return confidence based on existing data"""
+        # if we didn't receive any character in our consideration range,
+        # return negative answer
+        if self._total_chars <= 0 or self._freq_chars <= self.MINIMUM_DATA_THRESHOLD:
+            return self.SURE_NO
+
+        if self._total_chars != self._freq_chars:
+            r = self._freq_chars / (
+                (self._total_chars - self._freq_chars) * self.typical_distribution_ratio
+            )
+            if r < self.SURE_YES:
+                return r
+
+        # normalize confidence (we don't want to be 100% sure)
+        return self.SURE_YES
+
+    def got_enough_data(self) -> bool:
+        # It is not necessary to receive all data to draw conclusion.
+        # For charset detection, certain amount of data is enough
+        return self._total_chars > self.ENOUGH_DATA_THRESHOLD
+
+    def get_order(self, _: Union[bytes, bytearray]) -> int:
+        # We do not handle characters based on the original encoding string,
+        # but convert this encoding string to a number, here called order.
+        # This allows multiple encodings of a language to share one frequency
+        # table.
+        return -1
+
+
+class EUCTWDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = EUCTW_CHAR_TO_FREQ_ORDER
+        self._table_size = EUCTW_TABLE_SIZE
+        self.typical_distribution_ratio = EUCTW_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for euc-TW encoding, we are interested
+        #   first  byte range: 0xc4 -- 0xfe
+        #   second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char = byte_str[0]
+        if first_char >= 0xC4:
+            return 94 * (first_char - 0xC4) + byte_str[1] - 0xA1
+        return -1
+
+
+class EUCKRDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = EUCKR_CHAR_TO_FREQ_ORDER
+        self._table_size = EUCKR_TABLE_SIZE
+        self.typical_distribution_ratio = EUCKR_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for euc-KR encoding, we are interested
+        #   first  byte range: 0xb0 -- 0xfe
+        #   second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char = byte_str[0]
+        if first_char >= 0xB0:
+            return 94 * (first_char - 0xB0) + byte_str[1] - 0xA1
+        return -1
+
+
+class JOHABDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = EUCKR_CHAR_TO_FREQ_ORDER
+        self._table_size = EUCKR_TABLE_SIZE
+        self.typical_distribution_ratio = EUCKR_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        first_char = byte_str[0]
+        if 0x88 <= first_char < 0xD4:
+            code = first_char * 256 + byte_str[1]
+            return JOHAB_TO_EUCKR_ORDER_TABLE.get(code, -1)
+        return -1
+
+
+class GB2312DistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = GB2312_CHAR_TO_FREQ_ORDER
+        self._table_size = GB2312_TABLE_SIZE
+        self.typical_distribution_ratio = GB2312_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for GB2312 encoding, we are interested
+        #  first  byte range: 0xb0 -- 0xfe
+        #  second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char, second_char = byte_str[0], byte_str[1]
+        if (first_char >= 0xB0) and (second_char >= 0xA1):
+            return 94 * (first_char - 0xB0) + second_char - 0xA1
+        return -1
+
+
+class Big5DistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = BIG5_CHAR_TO_FREQ_ORDER
+        self._table_size = BIG5_TABLE_SIZE
+        self.typical_distribution_ratio = BIG5_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for big5 encoding, we are interested
+        #   first  byte range: 0xa4 -- 0xfe
+        #   second byte range: 0x40 -- 0x7e , 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char, second_char = byte_str[0], byte_str[1]
+        if first_char >= 0xA4:
+            if second_char >= 0xA1:
+                return 157 * (first_char - 0xA4) + second_char - 0xA1 + 63
+            return 157 * (first_char - 0xA4) + second_char - 0x40
+        return -1
+
+
+class SJISDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = JIS_CHAR_TO_FREQ_ORDER
+        self._table_size = JIS_TABLE_SIZE
+        self.typical_distribution_ratio = JIS_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for sjis encoding, we are interested
+        #   first  byte range: 0x81 -- 0x9f , 0xe0 -- 0xfe
+        #   second byte range: 0x40 -- 0x7e,  0x81 -- oxfe
+        # no validation needed here. State machine has done that
+        first_char, second_char = byte_str[0], byte_str[1]
+        if 0x81 <= first_char <= 0x9F:
+            order = 188 * (first_char - 0x81)
+        elif 0xE0 <= first_char <= 0xEF:
+            order = 188 * (first_char - 0xE0 + 31)
+        else:
+            return -1
+        order = order + second_char - 0x40
+        if second_char > 0x7F:
+            order = -1
+        return order
+
+
+class EUCJPDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = JIS_CHAR_TO_FREQ_ORDER
+        self._table_size = JIS_TABLE_SIZE
+        self.typical_distribution_ratio = JIS_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for euc-JP encoding, we are interested
+        #   first  byte range: 0xa0 -- 0xfe
+        #   second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        char = byte_str[0]
+        if char >= 0xA0:
+            return 94 * (char - 0xA1) + byte_str[1] - 0xA1
+        return -1
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/charsetgroupprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/charsetgroupprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..6def56b4a75f67000ed8181ae2d2c40eefb645fb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/charsetgroupprober.py
@@ -0,0 +1,106 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import LanguageFilter, ProbingState
+
+
+class CharSetGroupProber(CharSetProber):
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self._active_num = 0
+        self.probers: List[CharSetProber] = []
+        self._best_guess_prober: Optional[CharSetProber] = None
+
+    def reset(self) -> None:
+        super().reset()
+        self._active_num = 0
+        for prober in self.probers:
+            prober.reset()
+            prober.active = True
+            self._active_num += 1
+        self._best_guess_prober = None
+
+    @property
+    def charset_name(self) -> Optional[str]:
+        if not self._best_guess_prober:
+            self.get_confidence()
+            if not self._best_guess_prober:
+                return None
+        return self._best_guess_prober.charset_name
+
+    @property
+    def language(self) -> Optional[str]:
+        if not self._best_guess_prober:
+            self.get_confidence()
+            if not self._best_guess_prober:
+                return None
+        return self._best_guess_prober.language
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for prober in self.probers:
+            if not prober.active:
+                continue
+            state = prober.feed(byte_str)
+            if not state:
+                continue
+            if state == ProbingState.FOUND_IT:
+                self._best_guess_prober = prober
+                self._state = ProbingState.FOUND_IT
+                return self.state
+            if state == ProbingState.NOT_ME:
+                prober.active = False
+                self._active_num -= 1
+                if self._active_num <= 0:
+                    self._state = ProbingState.NOT_ME
+                    return self.state
+        return self.state
+
+    def get_confidence(self) -> float:
+        state = self.state
+        if state == ProbingState.FOUND_IT:
+            return 0.99
+        if state == ProbingState.NOT_ME:
+            return 0.01
+        best_conf = 0.0
+        self._best_guess_prober = None
+        for prober in self.probers:
+            if not prober.active:
+                self.logger.debug("%s not active", prober.charset_name)
+                continue
+            conf = prober.get_confidence()
+            self.logger.debug(
+                "%s %s confidence = %s", prober.charset_name, prober.language, conf
+            )
+            if best_conf < conf:
+                best_conf = conf
+                self._best_guess_prober = prober
+        if not self._best_guess_prober:
+            return 0.0
+        return best_conf
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/charsetprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/charsetprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..a103ca11356606402c03b320a4fcdb8635051623
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/charsetprober.py
@@ -0,0 +1,147 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+import logging
+import re
+from typing import Optional, Union
+
+from .enums import LanguageFilter, ProbingState
+
+INTERNATIONAL_WORDS_PATTERN = re.compile(
+    b"[a-zA-Z]*[\x80-\xFF]+[a-zA-Z]*[^a-zA-Z\x80-\xFF]?"
+)
+
+
+class CharSetProber:
+
+    SHORTCUT_THRESHOLD = 0.95
+
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        self._state = ProbingState.DETECTING
+        self.active = True
+        self.lang_filter = lang_filter
+        self.logger = logging.getLogger(__name__)
+
+    def reset(self) -> None:
+        self._state = ProbingState.DETECTING
+
+    @property
+    def charset_name(self) -> Optional[str]:
+        return None
+
+    @property
+    def language(self) -> Optional[str]:
+        raise NotImplementedError
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        raise NotImplementedError
+
+    @property
+    def state(self) -> ProbingState:
+        return self._state
+
+    def get_confidence(self) -> float:
+        return 0.0
+
+    @staticmethod
+    def filter_high_byte_only(buf: Union[bytes, bytearray]) -> bytes:
+        buf = re.sub(b"([\x00-\x7F])+", b" ", buf)
+        return buf
+
+    @staticmethod
+    def filter_international_words(buf: Union[bytes, bytearray]) -> bytearray:
+        """
+        We define three types of bytes:
+        alphabet: english alphabets [a-zA-Z]
+        international: international characters [\x80-\xFF]
+        marker: everything else [^a-zA-Z\x80-\xFF]
+        The input buffer can be thought to contain a series of words delimited
+        by markers. This function works to filter all words that contain at
+        least one international character. All contiguous sequences of markers
+        are replaced by a single space ascii character.
+        This filter applies to all scripts which do not use English characters.
+        """
+        filtered = bytearray()
+
+        # This regex expression filters out only words that have at-least one
+        # international character. The word may include one marker character at
+        # the end.
+        words = INTERNATIONAL_WORDS_PATTERN.findall(buf)
+
+        for word in words:
+            filtered.extend(word[:-1])
+
+            # If the last character in the word is a marker, replace it with a
+            # space as markers shouldn't affect our analysis (they are used
+            # similarly across all languages and may thus have similar
+            # frequencies).
+            last_char = word[-1:]
+            if not last_char.isalpha() and last_char < b"\x80":
+                last_char = b" "
+            filtered.extend(last_char)
+
+        return filtered
+
+    @staticmethod
+    def remove_xml_tags(buf: Union[bytes, bytearray]) -> bytes:
+        """
+        Returns a copy of ``buf`` that retains only the sequences of English
+        alphabet and high byte characters that are not between <> characters.
+        This filter can be applied to all scripts which contain both English
+        characters and extended ASCII characters, but is currently only used by
+        ``Latin1Prober``.
+        """
+        filtered = bytearray()
+        in_tag = False
+        prev = 0
+        buf = memoryview(buf).cast("c")
+
+        for curr, buf_char in enumerate(buf):
+            # Check if we're coming out of or entering an XML tag
+
+            # https://github.com/python/typeshed/issues/8182
+            if buf_char == b">":  # type: ignore[comparison-overlap]
+                prev = curr + 1
+                in_tag = False
+            # https://github.com/python/typeshed/issues/8182
+            elif buf_char == b"<":  # type: ignore[comparison-overlap]
+                if curr > prev and not in_tag:
+                    # Keep everything after last non-extended-ASCII,
+                    # non-alphabetic character
+                    filtered.extend(buf[prev:curr])
+                    # Output a space to delimit stretch we kept
+                    filtered.extend(b" ")
+                in_tag = True
+
+        # If we're not in a tag...
+        if not in_tag:
+            # Keep everything after last non-extended-ASCII, non-alphabetic
+            # character
+            filtered.extend(buf[prev:])
+
+        return filtered
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cli/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cli/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cli/chardetect.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cli/chardetect.py
new file mode 100644
index 0000000000000000000000000000000000000000..43f6e144f677a113b5362dcbdfb75db4f41c2b2f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cli/chardetect.py
@@ -0,0 +1,112 @@
+"""
+Script which takes one or more file paths and reports on their detected
+encodings
+
+Example::
+
+    % chardetect somefile someotherfile
+    somefile: windows-1252 with confidence 0.5
+    someotherfile: ascii with confidence 1.0
+
+If no paths are provided, it takes its input from stdin.
+
+"""
+
+
+import argparse
+import sys
+from typing import Iterable, List, Optional
+
+from .. import __version__
+from ..universaldetector import UniversalDetector
+
+
+def description_of(
+    lines: Iterable[bytes],
+    name: str = "stdin",
+    minimal: bool = False,
+    should_rename_legacy: bool = False,
+) -> Optional[str]:
+    """
+    Return a string describing the probable encoding of a file or
+    list of strings.
+
+    :param lines: The lines to get the encoding of.
+    :type lines: Iterable of bytes
+    :param name: Name of file or collection of lines
+    :type name: str
+    :param should_rename_legacy:  Should we rename legacy encodings to
+                                  their more modern equivalents?
+    :type should_rename_legacy:   ``bool``
+    """
+    u = UniversalDetector(should_rename_legacy=should_rename_legacy)
+    for line in lines:
+        line = bytearray(line)
+        u.feed(line)
+        # shortcut out of the loop to save reading further - particularly useful if we read a BOM.
+        if u.done:
+            break
+    u.close()
+    result = u.result
+    if minimal:
+        return result["encoding"]
+    if result["encoding"]:
+        return f'{name}: {result["encoding"]} with confidence {result["confidence"]}'
+    return f"{name}: no result"
+
+
+def main(argv: Optional[List[str]] = None) -> None:
+    """
+    Handles command line arguments and gets things started.
+
+    :param argv: List of arguments, as if specified on the command-line.
+                 If None, ``sys.argv[1:]`` is used instead.
+    :type argv: list of str
+    """
+    # Get command line arguments
+    parser = argparse.ArgumentParser(
+        description=(
+            "Takes one or more file paths and reports their detected encodings"
+        )
+    )
+    parser.add_argument(
+        "input",
+        help="File whose encoding we would like to determine. (default: stdin)",
+        type=argparse.FileType("rb"),
+        nargs="*",
+        default=[sys.stdin.buffer],
+    )
+    parser.add_argument(
+        "--minimal",
+        help="Print only the encoding to standard output",
+        action="store_true",
+    )
+    parser.add_argument(
+        "-l",
+        "--legacy",
+        help="Rename legacy encodings to more modern ones.",
+        action="store_true",
+    )
+    parser.add_argument(
+        "--version", action="version", version=f"%(prog)s {__version__}"
+    )
+    args = parser.parse_args(argv)
+
+    for f in args.input:
+        if f.isatty():
+            print(
+                "You are running chardetect interactively. Press "
+                "CTRL-D twice at the start of a blank line to signal the "
+                "end of your input. If you want help, run chardetect "
+                "--help\n",
+                file=sys.stderr,
+            )
+        print(
+            description_of(
+                f, f.name, minimal=args.minimal, should_rename_legacy=args.legacy
+            )
+        )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/codingstatemachine.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/codingstatemachine.py
new file mode 100644
index 0000000000000000000000000000000000000000..8ed4a8773b8404c2705aa8728e5fd692362ba168
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/codingstatemachine.py
@@ -0,0 +1,90 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+import logging
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+
+class CodingStateMachine:
+    """
+    A state machine to verify a byte sequence for a particular encoding. For
+    each byte the detector receives, it will feed that byte to every active
+    state machine available, one byte at a time. The state machine changes its
+    state based on its previous state and the byte it receives. There are 3
+    states in a state machine that are of interest to an auto-detector:
+
+    START state: This is the state to start with, or a legal byte sequence
+                 (i.e. a valid code point) for character has been identified.
+
+    ME state:  This indicates that the state machine identified a byte sequence
+               that is specific to the charset it is designed for and that
+               there is no other possible encoding which can contain this byte
+               sequence. This will to lead to an immediate positive answer for
+               the detector.
+
+    ERROR state: This indicates the state machine identified an illegal byte
+                 sequence for that encoding. This will lead to an immediate
+                 negative answer for this encoding. Detector will exclude this
+                 encoding from consideration from here on.
+    """
+
+    def __init__(self, sm: CodingStateMachineDict) -> None:
+        self._model = sm
+        self._curr_byte_pos = 0
+        self._curr_char_len = 0
+        self._curr_state = MachineState.START
+        self.active = True
+        self.logger = logging.getLogger(__name__)
+        self.reset()
+
+    def reset(self) -> None:
+        self._curr_state = MachineState.START
+
+    def next_state(self, c: int) -> int:
+        # for each byte we get its class
+        # if it is first byte, we also get byte length
+        byte_class = self._model["class_table"][c]
+        if self._curr_state == MachineState.START:
+            self._curr_byte_pos = 0
+            self._curr_char_len = self._model["char_len_table"][byte_class]
+        # from byte's class and state_table, we get its next state
+        curr_state = self._curr_state * self._model["class_factor"] + byte_class
+        self._curr_state = self._model["state_table"][curr_state]
+        self._curr_byte_pos += 1
+        return self._curr_state
+
+    def get_current_charlen(self) -> int:
+        return self._curr_char_len
+
+    def get_coding_state_machine(self) -> str:
+        return self._model["name"]
+
+    @property
+    def language(self) -> str:
+        return self._model["language"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/codingstatemachinedict.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/codingstatemachinedict.py
new file mode 100644
index 0000000000000000000000000000000000000000..7a3c4c7e3fe16e91225a87cbc58b8bbd798f9cc1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/codingstatemachinedict.py
@@ -0,0 +1,19 @@
+from typing import TYPE_CHECKING, Tuple
+
+if TYPE_CHECKING:
+    # TypedDict was introduced in Python 3.8.
+    #
+    # TODO: Remove the else block and TYPE_CHECKING check when dropping support
+    # for Python 3.7.
+    from typing import TypedDict
+
+    class CodingStateMachineDict(TypedDict, total=False):
+        class_table: Tuple[int, ...]
+        class_factor: int
+        state_table: Tuple[int, ...]
+        char_len_table: Tuple[int, ...]
+        name: str
+        language: str  # Optional key
+
+else:
+    CodingStateMachineDict = dict
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cp949prober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cp949prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..fa7307ed8985ad7e318660da0066440f890d1624
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/cp949prober.py
@@ -0,0 +1,49 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import EUCKRDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import CP949_SM_MODEL
+
+
+class CP949Prober(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(CP949_SM_MODEL)
+        # NOTE: CP949 is a superset of EUC-KR, so the distribution should be
+        #       not different.
+        self.distribution_analyzer = EUCKRDistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "CP949"
+
+    @property
+    def language(self) -> str:
+        return "Korean"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/enums.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/enums.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e3e198233698f2b007489dd299cecb87d971067
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/enums.py
@@ -0,0 +1,85 @@
+"""
+All of the Enums that are used throughout the chardet package.
+
+:author: Dan Blanchard (dan.blanchard@gmail.com)
+"""
+
+from enum import Enum, Flag
+
+
+class InputState:
+    """
+    This enum represents the different states a universal detector can be in.
+    """
+
+    PURE_ASCII = 0
+    ESC_ASCII = 1
+    HIGH_BYTE = 2
+
+
+class LanguageFilter(Flag):
+    """
+    This enum represents the different language filters we can apply to a
+    ``UniversalDetector``.
+    """
+
+    NONE = 0x00
+    CHINESE_SIMPLIFIED = 0x01
+    CHINESE_TRADITIONAL = 0x02
+    JAPANESE = 0x04
+    KOREAN = 0x08
+    NON_CJK = 0x10
+    ALL = 0x1F
+    CHINESE = CHINESE_SIMPLIFIED | CHINESE_TRADITIONAL
+    CJK = CHINESE | JAPANESE | KOREAN
+
+
+class ProbingState(Enum):
+    """
+    This enum represents the different states a prober can be in.
+    """
+
+    DETECTING = 0
+    FOUND_IT = 1
+    NOT_ME = 2
+
+
+class MachineState:
+    """
+    This enum represents the different states a state machine can be in.
+    """
+
+    START = 0
+    ERROR = 1
+    ITS_ME = 2
+
+
+class SequenceLikelihood:
+    """
+    This enum represents the likelihood of a character following the previous one.
+    """
+
+    NEGATIVE = 0
+    UNLIKELY = 1
+    LIKELY = 2
+    POSITIVE = 3
+
+    @classmethod
+    def get_num_categories(cls) -> int:
+        """:returns: The number of likelihood categories in the enum."""
+        return 4
+
+
+class CharacterCategory:
+    """
+    This enum represents the different categories language models for
+    ``SingleByteCharsetProber`` put characters into.
+
+    Anything less than CONTROL is considered a letter.
+    """
+
+    UNDEFINED = 255
+    LINE_BREAK = 254
+    SYMBOL = 253
+    DIGIT = 252
+    CONTROL = 251
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/escprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/escprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..fd713830d36cabc6a0fb4ab4e8cf426a84decdc6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/escprober.py
@@ -0,0 +1,102 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import LanguageFilter, MachineState, ProbingState
+from .escsm import (
+    HZ_SM_MODEL,
+    ISO2022CN_SM_MODEL,
+    ISO2022JP_SM_MODEL,
+    ISO2022KR_SM_MODEL,
+)
+
+
+class EscCharSetProber(CharSetProber):
+    """
+    This CharSetProber uses a "code scheme" approach for detecting encodings,
+    whereby easily recognizable escape or shift sequences are relied on to
+    identify these encodings.
+    """
+
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self.coding_sm = []
+        if self.lang_filter & LanguageFilter.CHINESE_SIMPLIFIED:
+            self.coding_sm.append(CodingStateMachine(HZ_SM_MODEL))
+            self.coding_sm.append(CodingStateMachine(ISO2022CN_SM_MODEL))
+        if self.lang_filter & LanguageFilter.JAPANESE:
+            self.coding_sm.append(CodingStateMachine(ISO2022JP_SM_MODEL))
+        if self.lang_filter & LanguageFilter.KOREAN:
+            self.coding_sm.append(CodingStateMachine(ISO2022KR_SM_MODEL))
+        self.active_sm_count = 0
+        self._detected_charset: Optional[str] = None
+        self._detected_language: Optional[str] = None
+        self._state = ProbingState.DETECTING
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        for coding_sm in self.coding_sm:
+            coding_sm.active = True
+            coding_sm.reset()
+        self.active_sm_count = len(self.coding_sm)
+        self._detected_charset = None
+        self._detected_language = None
+
+    @property
+    def charset_name(self) -> Optional[str]:
+        return self._detected_charset
+
+    @property
+    def language(self) -> Optional[str]:
+        return self._detected_language
+
+    def get_confidence(self) -> float:
+        return 0.99 if self._detected_charset else 0.00
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for c in byte_str:
+            for coding_sm in self.coding_sm:
+                if not coding_sm.active:
+                    continue
+                coding_state = coding_sm.next_state(c)
+                if coding_state == MachineState.ERROR:
+                    coding_sm.active = False
+                    self.active_sm_count -= 1
+                    if self.active_sm_count <= 0:
+                        self._state = ProbingState.NOT_ME
+                        return self.state
+                elif coding_state == MachineState.ITS_ME:
+                    self._state = ProbingState.FOUND_IT
+                    self._detected_charset = coding_sm.get_coding_state_machine()
+                    self._detected_language = coding_sm.language
+                    return self.state
+
+        return self.state
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/escsm.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/escsm.py
new file mode 100644
index 0000000000000000000000000000000000000000..11d4adf771f3f90bb5f1cc11043599b48e955c22
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/escsm.py
@@ -0,0 +1,261 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License,  or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not,  write to the Free Software
+# Foundation,  Inc.,  51 Franklin St,  Fifth Floor,  Boston,  MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+# fmt: off
+HZ_CLS = (
+    1, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 0, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 4, 0, 5, 2, 0,  # 78 - 7f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 80 - 87
+    1, 1, 1, 1, 1, 1, 1, 1,  # 88 - 8f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 90 - 97
+    1, 1, 1, 1, 1, 1, 1, 1,  # 98 - 9f
+    1, 1, 1, 1, 1, 1, 1, 1,  # a0 - a7
+    1, 1, 1, 1, 1, 1, 1, 1,  # a8 - af
+    1, 1, 1, 1, 1, 1, 1, 1,  # b0 - b7
+    1, 1, 1, 1, 1, 1, 1, 1,  # b8 - bf
+    1, 1, 1, 1, 1, 1, 1, 1,  # c0 - c7
+    1, 1, 1, 1, 1, 1, 1, 1,  # c8 - cf
+    1, 1, 1, 1, 1, 1, 1, 1,  # d0 - d7
+    1, 1, 1, 1, 1, 1, 1, 1,  # d8 - df
+    1, 1, 1, 1, 1, 1, 1, 1,  # e0 - e7
+    1, 1, 1, 1, 1, 1, 1, 1,  # e8 - ef
+    1, 1, 1, 1, 1, 1, 1, 1,  # f0 - f7
+    1, 1, 1, 1, 1, 1, 1, 1,  # f8 - ff
+)
+
+HZ_ST = (
+MachineState.START, MachineState.ERROR,      3, MachineState.START, MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, # 00-07
+MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 08-0f
+MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.START, MachineState.START,      4, MachineState.ERROR, # 10-17
+     5, MachineState.ERROR,      6, MachineState.ERROR,      5,      5,      4, MachineState.ERROR, # 18-1f
+     4, MachineState.ERROR,      4,      4,      4, MachineState.ERROR,      4, MachineState.ERROR, # 20-27
+     4, MachineState.ITS_ME, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 28-2f
+)
+# fmt: on
+
+HZ_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0)
+
+HZ_SM_MODEL: CodingStateMachineDict = {
+    "class_table": HZ_CLS,
+    "class_factor": 6,
+    "state_table": HZ_ST,
+    "char_len_table": HZ_CHAR_LEN_TABLE,
+    "name": "HZ-GB-2312",
+    "language": "Chinese",
+}
+
+# fmt: off
+ISO2022CN_CLS = (
+    2, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 3, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 4, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 80 - 87
+    2, 2, 2, 2, 2, 2, 2, 2,  # 88 - 8f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 90 - 97
+    2, 2, 2, 2, 2, 2, 2, 2,  # 98 - 9f
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 2,  # f8 - ff
+)
+
+ISO2022CN_ST = (
+    MachineState.START,      3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 00-07
+    MachineState.START, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 08-0f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 10-17
+    MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      4, MachineState.ERROR, # 18-1f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 20-27
+        5,      6, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 28-2f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 30-37
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.START, # 38-3f
+)
+# fmt: on
+
+ISO2022CN_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0, 0, 0, 0)
+
+ISO2022CN_SM_MODEL: CodingStateMachineDict = {
+    "class_table": ISO2022CN_CLS,
+    "class_factor": 9,
+    "state_table": ISO2022CN_ST,
+    "char_len_table": ISO2022CN_CHAR_LEN_TABLE,
+    "name": "ISO-2022-CN",
+    "language": "Chinese",
+}
+
+# fmt: off
+ISO2022JP_CLS = (
+    2, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 2, 2,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 7, 0, 0, 0,  # 20 - 27
+    3, 0, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    6, 0, 4, 0, 8, 0, 0, 0,  # 40 - 47
+    0, 9, 5, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 80 - 87
+    2, 2, 2, 2, 2, 2, 2, 2,  # 88 - 8f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 90 - 97
+    2, 2, 2, 2, 2, 2, 2, 2,  # 98 - 9f
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 2,  # f8 - ff
+)
+
+ISO2022JP_ST = (
+    MachineState.START,      3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 00-07
+    MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 08-0f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 10-17
+    MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, # 18-1f
+    MachineState.ERROR,      5, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      4, MachineState.ERROR, MachineState.ERROR, # 20-27
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      6, MachineState.ITS_ME, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, # 28-2f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, # 30-37
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 38-3f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.START, MachineState.START, # 40-47
+)
+# fmt: on
+
+ISO2022JP_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
+
+ISO2022JP_SM_MODEL: CodingStateMachineDict = {
+    "class_table": ISO2022JP_CLS,
+    "class_factor": 10,
+    "state_table": ISO2022JP_ST,
+    "char_len_table": ISO2022JP_CHAR_LEN_TABLE,
+    "name": "ISO-2022-JP",
+    "language": "Japanese",
+}
+
+# fmt: off
+ISO2022KR_CLS = (
+    2, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 3, 0, 0, 0,  # 20 - 27
+    0, 4, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 5, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 80 - 87
+    2, 2, 2, 2, 2, 2, 2, 2,  # 88 - 8f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 90 - 97
+    2, 2, 2, 2, 2, 2, 2, 2,  # 98 - 9f
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 2,  # f8 - ff
+)
+
+ISO2022KR_ST = (
+    MachineState.START,      3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, # 00-07
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 08-0f
+    MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      4, MachineState.ERROR, MachineState.ERROR, # 10-17
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      5, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 18-1f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 20-27
+)
+# fmt: on
+
+ISO2022KR_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0)
+
+ISO2022KR_SM_MODEL: CodingStateMachineDict = {
+    "class_table": ISO2022KR_CLS,
+    "class_factor": 6,
+    "state_table": ISO2022KR_ST,
+    "char_len_table": ISO2022KR_CHAR_LEN_TABLE,
+    "name": "ISO-2022-KR",
+    "language": "Korean",
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/eucjpprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/eucjpprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..39487f4098d7c2068b67d7d3dd85b61848974a23
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/eucjpprober.py
@@ -0,0 +1,102 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Union
+
+from .chardistribution import EUCJPDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .enums import MachineState, ProbingState
+from .jpcntx import EUCJPContextAnalysis
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import EUCJP_SM_MODEL
+
+
+class EUCJPProber(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(EUCJP_SM_MODEL)
+        self.distribution_analyzer = EUCJPDistributionAnalysis()
+        self.context_analyzer = EUCJPContextAnalysis()
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        self.context_analyzer.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "EUC-JP"
+
+    @property
+    def language(self) -> str:
+        return "Japanese"
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        assert self.coding_sm is not None
+        assert self.distribution_analyzer is not None
+
+        for i, byte in enumerate(byte_str):
+            # PY3K: byte_str is a byte array, so byte is an int, not a byte
+            coding_state = self.coding_sm.next_state(byte)
+            if coding_state == MachineState.ERROR:
+                self.logger.debug(
+                    "%s %s prober hit error at byte %s",
+                    self.charset_name,
+                    self.language,
+                    i,
+                )
+                self._state = ProbingState.NOT_ME
+                break
+            if coding_state == MachineState.ITS_ME:
+                self._state = ProbingState.FOUND_IT
+                break
+            if coding_state == MachineState.START:
+                char_len = self.coding_sm.get_current_charlen()
+                if i == 0:
+                    self._last_char[1] = byte
+                    self.context_analyzer.feed(self._last_char, char_len)
+                    self.distribution_analyzer.feed(self._last_char, char_len)
+                else:
+                    self.context_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+                    self.distribution_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+
+        self._last_char[0] = byte_str[-1]
+
+        if self.state == ProbingState.DETECTING:
+            if self.context_analyzer.got_enough_data() and (
+                self.get_confidence() > self.SHORTCUT_THRESHOLD
+            ):
+                self._state = ProbingState.FOUND_IT
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        assert self.distribution_analyzer is not None
+
+        context_conf = self.context_analyzer.get_confidence()
+        distrib_conf = self.distribution_analyzer.get_confidence()
+        return max(context_conf, distrib_conf)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euckrfreq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euckrfreq.py
new file mode 100644
index 0000000000000000000000000000000000000000..7dc3b10387d1c3d2da8b4e27e917ee2a85086e0c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euckrfreq.py
@@ -0,0 +1,196 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# Sampling from about 20M text materials include literature and computer technology
+
+# 128  --> 0.79
+# 256  --> 0.92
+# 512  --> 0.986
+# 1024 --> 0.99944
+# 2048 --> 0.99999
+#
+# Idea Distribution Ratio = 0.98653 / (1-0.98653) = 73.24
+# Random Distribution Ration = 512 / (2350-512) = 0.279.
+#
+# Typical Distribution Ratio
+
+EUCKR_TYPICAL_DISTRIBUTION_RATIO = 6.0
+
+EUCKR_TABLE_SIZE = 2352
+
+# Char to FreqOrder table ,
+# fmt: off
+EUCKR_CHAR_TO_FREQ_ORDER = (
+  13, 130, 120,1396, 481,1719,1720, 328, 609, 212,1721, 707, 400, 299,1722,  87,
+1397,1723, 104, 536,1117,1203,1724,1267, 685,1268, 508,1725,1726,1727,1728,1398,
+1399,1729,1730,1731, 141, 621, 326,1057, 368,1732, 267, 488,  20,1733,1269,1734,
+ 945,1400,1735,  47, 904,1270,1736,1737, 773, 248,1738, 409, 313, 786, 429,1739,
+ 116, 987, 813,1401, 683,  75,1204, 145,1740,1741,1742,1743,  16, 847, 667, 622,
+ 708,1744,1745,1746, 966, 787, 304, 129,1747,  60, 820, 123, 676,1748,1749,1750,
+1751, 617,1752, 626,1753,1754,1755,1756, 653,1757,1758,1759,1760,1761,1762, 856,
+ 344,1763,1764,1765,1766,  89, 401, 418, 806, 905, 848,1767,1768,1769, 946,1205,
+ 709,1770,1118,1771, 241,1772,1773,1774,1271,1775, 569,1776, 999,1777,1778,1779,
+1780, 337, 751,1058,  28, 628, 254,1781, 177, 906, 270, 349, 891,1079,1782,  19,
+1783, 379,1784, 315,1785, 629, 754,1402, 559,1786, 636, 203,1206,1787, 710, 567,
+1788, 935, 814,1789,1790,1207, 766, 528,1791,1792,1208,1793,1794,1795,1796,1797,
+1403,1798,1799, 533,1059,1404,1405,1156,1406, 936, 884,1080,1800, 351,1801,1802,
+1803,1804,1805, 801,1806,1807,1808,1119,1809,1157, 714, 474,1407,1810, 298, 899,
+ 885,1811,1120, 802,1158,1812, 892,1813,1814,1408, 659,1815,1816,1121,1817,1818,
+1819,1820,1821,1822, 319,1823, 594, 545,1824, 815, 937,1209,1825,1826, 573,1409,
+1022,1827,1210,1828,1829,1830,1831,1832,1833, 556, 722, 807,1122,1060,1834, 697,
+1835, 900, 557, 715,1836,1410, 540,1411, 752,1159, 294, 597,1211, 976, 803, 770,
+1412,1837,1838,  39, 794,1413, 358,1839, 371, 925,1840, 453, 661, 788, 531, 723,
+ 544,1023,1081, 869,  91,1841, 392, 430, 790, 602,1414, 677,1082, 457,1415,1416,
+1842,1843, 475, 327,1024,1417, 795, 121,1844, 733, 403,1418,1845,1846,1847, 300,
+ 119, 711,1212, 627,1848,1272, 207,1849,1850, 796,1213, 382,1851, 519,1852,1083,
+ 893,1853,1854,1855, 367, 809, 487, 671,1856, 663,1857,1858, 956, 471, 306, 857,
+1859,1860,1160,1084,1861,1862,1863,1864,1865,1061,1866,1867,1868,1869,1870,1871,
+ 282,  96, 574,1872, 502,1085,1873,1214,1874, 907,1875,1876, 827, 977,1419,1420,
+1421, 268,1877,1422,1878,1879,1880, 308,1881,   2, 537,1882,1883,1215,1884,1885,
+ 127, 791,1886,1273,1423,1887,  34, 336, 404, 643,1888, 571, 654, 894, 840,1889,
+   0, 886,1274, 122, 575, 260, 908, 938,1890,1275, 410, 316,1891,1892, 100,1893,
+1894,1123,  48,1161,1124,1025,1895, 633, 901,1276,1896,1897, 115, 816,1898, 317,
+1899, 694,1900, 909, 734,1424, 572, 866,1425, 691,  85, 524,1010, 543, 394, 841,
+1901,1902,1903,1026,1904,1905,1906,1907,1908,1909,  30, 451, 651, 988, 310,1910,
+1911,1426, 810,1216,  93,1912,1913,1277,1217,1914, 858, 759,  45,  58, 181, 610,
+ 269,1915,1916, 131,1062, 551, 443,1000, 821,1427, 957, 895,1086,1917,1918, 375,
+1919, 359,1920, 687,1921, 822,1922, 293,1923,1924,  40, 662, 118, 692,  29, 939,
+ 887, 640, 482, 174,1925,  69,1162, 728,1428, 910,1926,1278,1218,1279, 386, 870,
+ 217, 854,1163, 823,1927,1928,1929,1930, 834,1931,  78,1932, 859,1933,1063,1934,
+1935,1936,1937, 438,1164, 208, 595,1938,1939,1940,1941,1219,1125,1942, 280, 888,
+1429,1430,1220,1431,1943,1944,1945,1946,1947,1280, 150, 510,1432,1948,1949,1950,
+1951,1952,1953,1954,1011,1087,1955,1433,1043,1956, 881,1957, 614, 958,1064,1065,
+1221,1958, 638,1001, 860, 967, 896,1434, 989, 492, 553,1281,1165,1959,1282,1002,
+1283,1222,1960,1961,1962,1963,  36, 383, 228, 753, 247, 454,1964, 876, 678,1965,
+1966,1284, 126, 464, 490, 835, 136, 672, 529, 940,1088,1435, 473,1967,1968, 467,
+  50, 390, 227, 587, 279, 378, 598, 792, 968, 240, 151, 160, 849, 882,1126,1285,
+ 639,1044, 133, 140, 288, 360, 811, 563,1027, 561, 142, 523,1969,1970,1971,   7,
+ 103, 296, 439, 407, 506, 634, 990,1972,1973,1974,1975, 645,1976,1977,1978,1979,
+1980,1981, 236,1982,1436,1983,1984,1089, 192, 828, 618, 518,1166, 333,1127,1985,
+ 818,1223,1986,1987,1988,1989,1990,1991,1992,1993, 342,1128,1286, 746, 842,1994,
+1995, 560, 223,1287,  98,   8, 189, 650, 978,1288,1996,1437,1997,  17, 345, 250,
+ 423, 277, 234, 512, 226,  97, 289,  42, 167,1998, 201,1999,2000, 843, 836, 824,
+ 532, 338, 783,1090, 182, 576, 436,1438,1439, 527, 500,2001, 947, 889,2002,2003,
+2004,2005, 262, 600, 314, 447,2006, 547,2007, 693, 738,1129,2008,  71,1440, 745,
+ 619, 688,2009, 829,2010,2011, 147,2012,  33, 948,2013,2014,  74, 224,2015,  61,
+ 191, 918, 399, 637,2016,1028,1130, 257, 902,2017,2018,2019,2020,2021,2022,2023,
+2024,2025,2026, 837,2027,2028,2029,2030, 179, 874, 591,  52, 724, 246,2031,2032,
+2033,2034,1167, 969,2035,1289, 630, 605, 911,1091,1168,2036,2037,2038,1441, 912,
+2039, 623,2040,2041, 253,1169,1290,2042,1442, 146, 620, 611, 577, 433,2043,1224,
+ 719,1170, 959, 440, 437, 534,  84, 388, 480,1131, 159, 220, 198, 679,2044,1012,
+ 819,1066,1443, 113,1225, 194, 318,1003,1029,2045,2046,2047,2048,1067,2049,2050,
+2051,2052,2053,  59, 913, 112,2054, 632,2055, 455, 144, 739,1291,2056, 273, 681,
+ 499,2057, 448,2058,2059, 760,2060,2061, 970, 384, 169, 245,1132,2062,2063, 414,
+1444,2064,2065,  41, 235,2066, 157, 252, 877, 568, 919, 789, 580,2067, 725,2068,
+2069,1292,2070,2071,1445,2072,1446,2073,2074,  55, 588,  66,1447, 271,1092,2075,
+1226,2076, 960,1013, 372,2077,2078,2079,2080,2081,1293,2082,2083,2084,2085, 850,
+2086,2087,2088,2089,2090, 186,2091,1068, 180,2092,2093,2094, 109,1227, 522, 606,
+2095, 867,1448,1093, 991,1171, 926, 353,1133,2096, 581,2097,2098,2099,1294,1449,
+1450,2100, 596,1172,1014,1228,2101,1451,1295,1173,1229,2102,2103,1296,1134,1452,
+ 949,1135,2104,2105,1094,1453,1454,1455,2106,1095,2107,2108,2109,2110,2111,2112,
+2113,2114,2115,2116,2117, 804,2118,2119,1230,1231, 805,1456, 405,1136,2120,2121,
+2122,2123,2124, 720, 701,1297, 992,1457, 927,1004,2125,2126,2127,2128,2129,2130,
+  22, 417,2131, 303,2132, 385,2133, 971, 520, 513,2134,1174,  73,1096, 231, 274,
+ 962,1458, 673,2135,1459,2136, 152,1137,2137,2138,2139,2140,1005,1138,1460,1139,
+2141,2142,2143,2144,  11, 374, 844,2145, 154,1232,  46,1461,2146, 838, 830, 721,
+1233, 106,2147,  90, 428, 462, 578, 566,1175, 352,2148,2149, 538,1234, 124,1298,
+2150,1462, 761, 565,2151, 686,2152, 649,2153,  72, 173,2154, 460, 415,2155,1463,
+2156,1235, 305,2157,2158,2159,2160,2161,2162, 579,2163,2164,2165,2166,2167, 747,
+2168,2169,2170,2171,1464, 669,2172,2173,2174,2175,2176,1465,2177,  23, 530, 285,
+2178, 335, 729,2179, 397,2180,2181,2182,1030,2183,2184, 698,2185,2186, 325,2187,
+2188, 369,2189, 799,1097,1015, 348,2190,1069, 680,2191, 851,1466,2192,2193,  10,
+2194, 613, 424,2195, 979, 108, 449, 589,  27, 172,  81,1031,  80, 774, 281, 350,
+1032, 525, 301, 582,1176,2196, 674,1045,2197,2198,1467, 730, 762,2199,2200,2201,
+2202,1468,2203, 993,2204,2205, 266,1070, 963,1140,2206,2207,2208, 664,1098, 972,
+2209,2210,2211,1177,1469,1470, 871,2212,2213,2214,2215,2216,1471,2217,2218,2219,
+2220,2221,2222,2223,2224,2225,2226,2227,1472,1236,2228,2229,2230,2231,2232,2233,
+2234,2235,1299,2236,2237, 200,2238, 477, 373,2239,2240, 731, 825, 777,2241,2242,
+2243, 521, 486, 548,2244,2245,2246,1473,1300,  53, 549, 137, 875,  76, 158,2247,
+1301,1474, 469, 396,1016, 278, 712,2248, 321, 442, 503, 767, 744, 941,1237,1178,
+1475,2249,  82, 178,1141,1179, 973,2250,1302,2251, 297,2252,2253, 570,2254,2255,
+2256,  18, 450, 206,2257, 290, 292,1142,2258, 511, 162,  99, 346, 164, 735,2259,
+1476,1477,   4, 554, 343, 798,1099,2260,1100,2261,  43, 171,1303, 139, 215,2262,
+2263, 717, 775,2264,1033, 322, 216,2265, 831,2266, 149,2267,1304,2268,2269, 702,
+1238, 135, 845, 347, 309,2270, 484,2271, 878, 655, 238,1006,1478,2272,  67,2273,
+ 295,2274,2275, 461,2276, 478, 942, 412,2277,1034,2278,2279,2280, 265,2281, 541,
+2282,2283,2284,2285,2286,  70, 852,1071,2287,2288,2289,2290,  21,  56, 509, 117,
+ 432,2291,2292, 331, 980, 552,1101, 148, 284, 105, 393,1180,1239, 755,2293, 187,
+2294,1046,1479,2295, 340,2296,  63,1047, 230,2297,2298,1305, 763,1306, 101, 800,
+ 808, 494,2299,2300,2301, 903,2302,  37,1072,  14,   5,2303,  79, 675,2304, 312,
+2305,2306,2307,2308,2309,1480,   6,1307,2310,2311,2312,   1, 470,  35,  24, 229,
+2313, 695, 210,  86, 778,  15, 784, 592, 779,  32,  77, 855, 964,2314, 259,2315,
+ 501, 380,2316,2317,  83, 981, 153, 689,1308,1481,1482,1483,2318,2319, 716,1484,
+2320,2321,2322,2323,2324,2325,1485,2326,2327, 128,  57,  68, 261,1048, 211, 170,
+1240,  31,2328,  51, 435, 742,2329,2330,2331, 635,2332, 264, 456,2333,2334,2335,
+ 425,2336,1486, 143, 507, 263, 943,2337, 363, 920,1487, 256,1488,1102, 243, 601,
+1489,2338,2339,2340,2341,2342,2343,2344, 861,2345,2346,2347,2348,2349,2350, 395,
+2351,1490,1491,  62, 535, 166, 225,2352,2353, 668, 419,1241, 138, 604, 928,2354,
+1181,2355,1492,1493,2356,2357,2358,1143,2359, 696,2360, 387, 307,1309, 682, 476,
+2361,2362, 332,  12, 222, 156,2363, 232,2364, 641, 276, 656, 517,1494,1495,1035,
+ 416, 736,1496,2365,1017, 586,2366,2367,2368,1497,2369, 242,2370,2371,2372,1498,
+2373, 965, 713,2374,2375,2376,2377, 740, 982,1499, 944,1500,1007,2378,2379,1310,
+1501,2380,2381,2382, 785, 329,2383,2384,1502,2385,2386,2387, 932,2388,1503,2389,
+2390,2391,2392,1242,2393,2394,2395,2396,2397, 994, 950,2398,2399,2400,2401,1504,
+1311,2402,2403,2404,2405,1049, 749,2406,2407, 853, 718,1144,1312,2408,1182,1505,
+2409,2410, 255, 516, 479, 564, 550, 214,1506,1507,1313, 413, 239, 444, 339,1145,
+1036,1508,1509,1314,1037,1510,1315,2411,1511,2412,2413,2414, 176, 703, 497, 624,
+ 593, 921, 302,2415, 341, 165,1103,1512,2416,1513,2417,2418,2419, 376,2420, 700,
+2421,2422,2423, 258, 768,1316,2424,1183,2425, 995, 608,2426,2427,2428,2429, 221,
+2430,2431,2432,2433,2434,2435,2436,2437, 195, 323, 726, 188, 897, 983,1317, 377,
+ 644,1050, 879,2438, 452,2439,2440,2441,2442,2443,2444, 914,2445,2446,2447,2448,
+ 915, 489,2449,1514,1184,2450,2451, 515,  64, 427, 495,2452, 583,2453, 483, 485,
+1038, 562, 213,1515, 748, 666,2454,2455,2456,2457, 334,2458, 780, 996,1008, 705,
+1243,2459,2460,2461,2462,2463, 114,2464, 493,1146, 366, 163,1516, 961,1104,2465,
+ 291,2466,1318,1105,2467,1517, 365,2468, 355, 951,1244,2469,1319,2470, 631,2471,
+2472, 218,1320, 364, 320, 756,1518,1519,1321,1520,1322,2473,2474,2475,2476, 997,
+2477,2478,2479,2480, 665,1185,2481, 916,1521,2482,2483,2484, 584, 684,2485,2486,
+ 797,2487,1051,1186,2488,2489,2490,1522,2491,2492, 370,2493,1039,1187,  65,2494,
+ 434, 205, 463,1188,2495, 125, 812, 391, 402, 826, 699, 286, 398, 155, 781, 771,
+ 585,2496, 590, 505,1073,2497, 599, 244, 219, 917,1018, 952, 646,1523,2498,1323,
+2499,2500,  49, 984, 354, 741,2501, 625,2502,1324,2503,1019, 190, 357, 757, 491,
+  95, 782, 868,2504,2505,2506,2507,2508,2509, 134,1524,1074, 422,1525, 898,2510,
+ 161,2511,2512,2513,2514, 769,2515,1526,2516,2517, 411,1325,2518, 472,1527,2519,
+2520,2521,2522,2523,2524, 985,2525,2526,2527,2528,2529,2530, 764,2531,1245,2532,
+2533,  25, 204, 311,2534, 496,2535,1052,2536,2537,2538,2539,2540,2541,2542, 199,
+ 704, 504, 468, 758, 657,1528, 196,  44, 839,1246, 272, 750,2543, 765, 862,2544,
+2545,1326,2546, 132, 615, 933,2547, 732,2548,2549,2550,1189,1529,2551, 283,1247,
+1053, 607, 929,2552,2553,2554, 930, 183, 872, 616,1040,1147,2555,1148,1020, 441,
+ 249,1075,2556,2557,2558, 466, 743,2559,2560,2561,  92, 514, 426, 420, 526,2562,
+2563,2564,2565,2566,2567,2568, 185,2569,2570,2571,2572, 776,1530, 658,2573, 362,
+2574, 361, 922,1076, 793,2575,2576,2577,2578,2579,2580,1531, 251,2581,2582,2583,
+2584,1532,  54, 612, 237,1327,2585,2586, 275, 408, 647, 111,2587,1533,1106, 465,
+   3, 458,   9,  38,2588, 107, 110, 890, 209,  26, 737, 498,2589,1534,2590, 431,
+ 202,  88,1535, 356, 287,1107, 660,1149,2591, 381,1536, 986,1150, 445,1248,1151,
+ 974,2592,2593, 846,2594, 446, 953, 184,1249,1250, 727,2595, 923, 193, 883,2596,
+2597,2598, 102, 324, 539, 817,2599, 421,1041,2600, 832,2601,  94, 175, 197, 406,
+2602, 459,2603,2604,2605,2606,2607, 330, 555,2608,2609,2610, 706,1108, 389,2611,
+2612,2613,2614, 233,2615, 833, 558, 931, 954,1251,2616,2617,1537, 546,2618,2619,
+1009,2620,2621,2622,1538, 690,1328,2623, 955,2624,1539,2625,2626, 772,2627,2628,
+2629,2630,2631, 924, 648, 863, 603,2632,2633, 934,1540, 864, 865,2634, 642,1042,
+ 670,1190,2635,2636,2637,2638, 168,2639, 652, 873, 542,1054,1541,2640,2641,2642,  # 512, 256
+)
+# fmt: on
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euckrprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euckrprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..1fc5de0462cd9a09472cece4087cafe699da4fa7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euckrprober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import EUCKRDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import EUCKR_SM_MODEL
+
+
+class EUCKRProber(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(EUCKR_SM_MODEL)
+        self.distribution_analyzer = EUCKRDistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "EUC-KR"
+
+    @property
+    def language(self) -> str:
+        return "Korean"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euctwfreq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euctwfreq.py
new file mode 100644
index 0000000000000000000000000000000000000000..4900ccc160a1dbf4de3a01c234735c21dd4417d6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euctwfreq.py
@@ -0,0 +1,388 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# EUCTW frequency table
+# Converted from big5 work
+# by Taiwan's Mandarin Promotion Council
+# 
+
+# 128  --> 0.42261
+# 256  --> 0.57851
+# 512  --> 0.74851
+# 1024 --> 0.89384
+# 2048 --> 0.97583
+#
+# Idea Distribution Ratio = 0.74851/(1-0.74851) =2.98
+# Random Distribution Ration = 512/(5401-512)=0.105
+#
+# Typical Distribution Ratio about 25% of Ideal one, still much higher than RDR
+
+EUCTW_TYPICAL_DISTRIBUTION_RATIO = 0.75
+
+# Char to FreqOrder table
+EUCTW_TABLE_SIZE = 5376
+
+# fmt: off
+EUCTW_CHAR_TO_FREQ_ORDER = (
+    1, 1800, 1506, 255, 1431, 198, 9, 82, 6, 7310, 177, 202, 3615, 1256, 2808, 110,  # 2742
+    3735, 33, 3241, 261, 76, 44, 2113, 16, 2931, 2184, 1176, 659, 3868, 26, 3404, 2643,  # 2758
+    1198, 3869, 3313, 4060, 410, 2211, 302, 590, 361, 1963, 8, 204, 58, 4296, 7311, 1931,  # 2774
+    63, 7312, 7313, 317, 1614, 75, 222, 159, 4061, 2412, 1480, 7314, 3500, 3068, 224, 2809,  # 2790
+    3616, 3, 10, 3870, 1471, 29, 2774, 1135, 2852, 1939, 873, 130, 3242, 1123, 312, 7315,  # 2806
+    4297, 2051, 507, 252, 682, 7316, 142, 1914, 124, 206, 2932, 34, 3501, 3173, 64, 604,  # 2822
+    7317, 2494, 1976, 1977, 155, 1990, 645, 641, 1606, 7318, 3405, 337, 72, 406, 7319, 80,  # 2838
+    630, 238, 3174, 1509, 263, 939, 1092, 2644, 756, 1440, 1094, 3406, 449, 69, 2969, 591,  # 2854
+    179, 2095, 471, 115, 2034, 1843, 60, 50, 2970, 134, 806, 1868, 734, 2035, 3407, 180,  # 2870
+    995, 1607, 156, 537, 2893, 688, 7320, 319, 1305, 779, 2144, 514, 2374, 298, 4298, 359,  # 2886
+    2495, 90, 2707, 1338, 663, 11, 906, 1099, 2545, 20, 2436, 182, 532, 1716, 7321, 732,  # 2902
+    1376, 4062, 1311, 1420, 3175, 25, 2312, 1056, 113, 399, 382, 1949, 242, 3408, 2467, 529,  # 2918
+    3243, 475, 1447, 3617, 7322, 117, 21, 656, 810, 1297, 2295, 2329, 3502, 7323, 126, 4063,  # 2934
+    706, 456, 150, 613, 4299, 71, 1118, 2036, 4064, 145, 3069, 85, 835, 486, 2114, 1246,  # 2950
+    1426, 428, 727, 1285, 1015, 800, 106, 623, 303, 1281, 7324, 2127, 2354, 347, 3736, 221,  # 2966
+    3503, 3110, 7325, 1955, 1153, 4065, 83, 296, 1199, 3070, 192, 624, 93, 7326, 822, 1897,  # 2982
+    2810, 3111, 795, 2064, 991, 1554, 1542, 1592, 27, 43, 2853, 859, 139, 1456, 860, 4300,  # 2998
+    437, 712, 3871, 164, 2392, 3112, 695, 211, 3017, 2096, 195, 3872, 1608, 3504, 3505, 3618,  # 3014
+    3873, 234, 811, 2971, 2097, 3874, 2229, 1441, 3506, 1615, 2375, 668, 2076, 1638, 305, 228,  # 3030
+    1664, 4301, 467, 415, 7327, 262, 2098, 1593, 239, 108, 300, 200, 1033, 512, 1247, 2077,  # 3046
+    7328, 7329, 2173, 3176, 3619, 2673, 593, 845, 1062, 3244, 88, 1723, 2037, 3875, 1950, 212,  # 3062
+    266, 152, 149, 468, 1898, 4066, 4302, 77, 187, 7330, 3018, 37, 5, 2972, 7331, 3876,  # 3078
+    7332, 7333, 39, 2517, 4303, 2894, 3177, 2078, 55, 148, 74, 4304, 545, 483, 1474, 1029,  # 3094
+    1665, 217, 1869, 1531, 3113, 1104, 2645, 4067, 24, 172, 3507, 900, 3877, 3508, 3509, 4305,  # 3110
+    32, 1408, 2811, 1312, 329, 487, 2355, 2247, 2708, 784, 2674, 4, 3019, 3314, 1427, 1788,  # 3126
+    188, 109, 499, 7334, 3620, 1717, 1789, 888, 1217, 3020, 4306, 7335, 3510, 7336, 3315, 1520,  # 3142
+    3621, 3878, 196, 1034, 775, 7337, 7338, 929, 1815, 249, 439, 38, 7339, 1063, 7340, 794,  # 3158
+    3879, 1435, 2296, 46, 178, 3245, 2065, 7341, 2376, 7342, 214, 1709, 4307, 804, 35, 707,  # 3174
+    324, 3622, 1601, 2546, 140, 459, 4068, 7343, 7344, 1365, 839, 272, 978, 2257, 2572, 3409,  # 3190
+    2128, 1363, 3623, 1423, 697, 100, 3071, 48, 70, 1231, 495, 3114, 2193, 7345, 1294, 7346,  # 3206
+    2079, 462, 586, 1042, 3246, 853, 256, 988, 185, 2377, 3410, 1698, 434, 1084, 7347, 3411,  # 3222
+    314, 2615, 2775, 4308, 2330, 2331, 569, 2280, 637, 1816, 2518, 757, 1162, 1878, 1616, 3412,  # 3238
+    287, 1577, 2115, 768, 4309, 1671, 2854, 3511, 2519, 1321, 3737, 909, 2413, 7348, 4069, 933,  # 3254
+    3738, 7349, 2052, 2356, 1222, 4310, 765, 2414, 1322, 786, 4311, 7350, 1919, 1462, 1677, 2895,  # 3270
+    1699, 7351, 4312, 1424, 2437, 3115, 3624, 2590, 3316, 1774, 1940, 3413, 3880, 4070, 309, 1369,  # 3286
+    1130, 2812, 364, 2230, 1653, 1299, 3881, 3512, 3882, 3883, 2646, 525, 1085, 3021, 902, 2000,  # 3302
+    1475, 964, 4313, 421, 1844, 1415, 1057, 2281, 940, 1364, 3116, 376, 4314, 4315, 1381, 7,  # 3318
+    2520, 983, 2378, 336, 1710, 2675, 1845, 321, 3414, 559, 1131, 3022, 2742, 1808, 1132, 1313,  # 3334
+    265, 1481, 1857, 7352, 352, 1203, 2813, 3247, 167, 1089, 420, 2814, 776, 792, 1724, 3513,  # 3350
+    4071, 2438, 3248, 7353, 4072, 7354, 446, 229, 333, 2743, 901, 3739, 1200, 1557, 4316, 2647,  # 3366
+    1920, 395, 2744, 2676, 3740, 4073, 1835, 125, 916, 3178, 2616, 4317, 7355, 7356, 3741, 7357,  # 3382
+    7358, 7359, 4318, 3117, 3625, 1133, 2547, 1757, 3415, 1510, 2313, 1409, 3514, 7360, 2145, 438,  # 3398
+    2591, 2896, 2379, 3317, 1068, 958, 3023, 461, 311, 2855, 2677, 4074, 1915, 3179, 4075, 1978,  # 3414
+    383, 750, 2745, 2617, 4076, 274, 539, 385, 1278, 1442, 7361, 1154, 1964, 384, 561, 210,  # 3430
+    98, 1295, 2548, 3515, 7362, 1711, 2415, 1482, 3416, 3884, 2897, 1257, 129, 7363, 3742, 642,  # 3446
+    523, 2776, 2777, 2648, 7364, 141, 2231, 1333, 68, 176, 441, 876, 907, 4077, 603, 2592,  # 3462
+    710, 171, 3417, 404, 549, 18, 3118, 2393, 1410, 3626, 1666, 7365, 3516, 4319, 2898, 4320,  # 3478
+    7366, 2973, 368, 7367, 146, 366, 99, 871, 3627, 1543, 748, 807, 1586, 1185, 22, 2258,  # 3494
+    379, 3743, 3180, 7368, 3181, 505, 1941, 2618, 1991, 1382, 2314, 7369, 380, 2357, 218, 702,  # 3510
+    1817, 1248, 3418, 3024, 3517, 3318, 3249, 7370, 2974, 3628, 930, 3250, 3744, 7371, 59, 7372,  # 3526
+    585, 601, 4078, 497, 3419, 1112, 1314, 4321, 1801, 7373, 1223, 1472, 2174, 7374, 749, 1836,  # 3542
+    690, 1899, 3745, 1772, 3885, 1476, 429, 1043, 1790, 2232, 2116, 917, 4079, 447, 1086, 1629,  # 3558
+    7375, 556, 7376, 7377, 2020, 1654, 844, 1090, 105, 550, 966, 1758, 2815, 1008, 1782, 686,  # 3574
+    1095, 7378, 2282, 793, 1602, 7379, 3518, 2593, 4322, 4080, 2933, 2297, 4323, 3746, 980, 2496,  # 3590
+    544, 353, 527, 4324, 908, 2678, 2899, 7380, 381, 2619, 1942, 1348, 7381, 1341, 1252, 560,  # 3606
+    3072, 7382, 3420, 2856, 7383, 2053, 973, 886, 2080, 143, 4325, 7384, 7385, 157, 3886, 496,  # 3622
+    4081, 57, 840, 540, 2038, 4326, 4327, 3421, 2117, 1445, 970, 2259, 1748, 1965, 2081, 4082,  # 3638
+    3119, 1234, 1775, 3251, 2816, 3629, 773, 1206, 2129, 1066, 2039, 1326, 3887, 1738, 1725, 4083,  # 3654
+    279, 3120, 51, 1544, 2594, 423, 1578, 2130, 2066, 173, 4328, 1879, 7386, 7387, 1583, 264,  # 3670
+    610, 3630, 4329, 2439, 280, 154, 7388, 7389, 7390, 1739, 338, 1282, 3073, 693, 2857, 1411,  # 3686
+    1074, 3747, 2440, 7391, 4330, 7392, 7393, 1240, 952, 2394, 7394, 2900, 1538, 2679, 685, 1483,  # 3702
+    4084, 2468, 1436, 953, 4085, 2054, 4331, 671, 2395, 79, 4086, 2441, 3252, 608, 567, 2680,  # 3718
+    3422, 4087, 4088, 1691, 393, 1261, 1791, 2396, 7395, 4332, 7396, 7397, 7398, 7399, 1383, 1672,  # 3734
+    3748, 3182, 1464, 522, 1119, 661, 1150, 216, 675, 4333, 3888, 1432, 3519, 609, 4334, 2681,  # 3750
+    2397, 7400, 7401, 7402, 4089, 3025, 0, 7403, 2469, 315, 231, 2442, 301, 3319, 4335, 2380,  # 3766
+    7404, 233, 4090, 3631, 1818, 4336, 4337, 7405, 96, 1776, 1315, 2082, 7406, 257, 7407, 1809,  # 3782
+    3632, 2709, 1139, 1819, 4091, 2021, 1124, 2163, 2778, 1777, 2649, 7408, 3074, 363, 1655, 3183,  # 3798
+    7409, 2975, 7410, 7411, 7412, 3889, 1567, 3890, 718, 103, 3184, 849, 1443, 341, 3320, 2934,  # 3814
+    1484, 7413, 1712, 127, 67, 339, 4092, 2398, 679, 1412, 821, 7414, 7415, 834, 738, 351,  # 3830
+    2976, 2146, 846, 235, 1497, 1880, 418, 1992, 3749, 2710, 186, 1100, 2147, 2746, 3520, 1545,  # 3846
+    1355, 2935, 2858, 1377, 583, 3891, 4093, 2573, 2977, 7416, 1298, 3633, 1078, 2549, 3634, 2358,  # 3862
+    78, 3750, 3751, 267, 1289, 2099, 2001, 1594, 4094, 348, 369, 1274, 2194, 2175, 1837, 4338,  # 3878
+    1820, 2817, 3635, 2747, 2283, 2002, 4339, 2936, 2748, 144, 3321, 882, 4340, 3892, 2749, 3423,  # 3894
+    4341, 2901, 7417, 4095, 1726, 320, 7418, 3893, 3026, 788, 2978, 7419, 2818, 1773, 1327, 2859,  # 3910
+    3894, 2819, 7420, 1306, 4342, 2003, 1700, 3752, 3521, 2359, 2650, 787, 2022, 506, 824, 3636,  # 3926
+    534, 323, 4343, 1044, 3322, 2023, 1900, 946, 3424, 7421, 1778, 1500, 1678, 7422, 1881, 4344,  # 3942
+    165, 243, 4345, 3637, 2521, 123, 683, 4096, 764, 4346, 36, 3895, 1792, 589, 2902, 816,  # 3958
+    626, 1667, 3027, 2233, 1639, 1555, 1622, 3753, 3896, 7423, 3897, 2860, 1370, 1228, 1932, 891,  # 3974
+    2083, 2903, 304, 4097, 7424, 292, 2979, 2711, 3522, 691, 2100, 4098, 1115, 4347, 118, 662,  # 3990
+    7425, 611, 1156, 854, 2381, 1316, 2861, 2, 386, 515, 2904, 7426, 7427, 3253, 868, 2234,  # 4006
+    1486, 855, 2651, 785, 2212, 3028, 7428, 1040, 3185, 3523, 7429, 3121, 448, 7430, 1525, 7431,  # 4022
+    2164, 4348, 7432, 3754, 7433, 4099, 2820, 3524, 3122, 503, 818, 3898, 3123, 1568, 814, 676,  # 4038
+    1444, 306, 1749, 7434, 3755, 1416, 1030, 197, 1428, 805, 2821, 1501, 4349, 7435, 7436, 7437,  # 4054
+    1993, 7438, 4350, 7439, 7440, 2195, 13, 2779, 3638, 2980, 3124, 1229, 1916, 7441, 3756, 2131,  # 4070
+    7442, 4100, 4351, 2399, 3525, 7443, 2213, 1511, 1727, 1120, 7444, 7445, 646, 3757, 2443, 307,  # 4086
+    7446, 7447, 1595, 3186, 7448, 7449, 7450, 3639, 1113, 1356, 3899, 1465, 2522, 2523, 7451, 519,  # 4102
+    7452, 128, 2132, 92, 2284, 1979, 7453, 3900, 1512, 342, 3125, 2196, 7454, 2780, 2214, 1980,  # 4118
+    3323, 7455, 290, 1656, 1317, 789, 827, 2360, 7456, 3758, 4352, 562, 581, 3901, 7457, 401,  # 4134
+    4353, 2248, 94, 4354, 1399, 2781, 7458, 1463, 2024, 4355, 3187, 1943, 7459, 828, 1105, 4101,  # 4150
+    1262, 1394, 7460, 4102, 605, 4356, 7461, 1783, 2862, 7462, 2822, 819, 2101, 578, 2197, 2937,  # 4166
+    7463, 1502, 436, 3254, 4103, 3255, 2823, 3902, 2905, 3425, 3426, 7464, 2712, 2315, 7465, 7466,  # 4182
+    2332, 2067, 23, 4357, 193, 826, 3759, 2102, 699, 1630, 4104, 3075, 390, 1793, 1064, 3526,  # 4198
+    7467, 1579, 3076, 3077, 1400, 7468, 4105, 1838, 1640, 2863, 7469, 4358, 4359, 137, 4106, 598,  # 4214
+    3078, 1966, 780, 104, 974, 2938, 7470, 278, 899, 253, 402, 572, 504, 493, 1339, 7471,  # 4230
+    3903, 1275, 4360, 2574, 2550, 7472, 3640, 3029, 3079, 2249, 565, 1334, 2713, 863, 41, 7473,  # 4246
+    7474, 4361, 7475, 1657, 2333, 19, 463, 2750, 4107, 606, 7476, 2981, 3256, 1087, 2084, 1323,  # 4262
+    2652, 2982, 7477, 1631, 1623, 1750, 4108, 2682, 7478, 2864, 791, 2714, 2653, 2334, 232, 2416,  # 4278
+    7479, 2983, 1498, 7480, 2654, 2620, 755, 1366, 3641, 3257, 3126, 2025, 1609, 119, 1917, 3427,  # 4294
+    862, 1026, 4109, 7481, 3904, 3760, 4362, 3905, 4363, 2260, 1951, 2470, 7482, 1125, 817, 4110,  # 4310
+    4111, 3906, 1513, 1766, 2040, 1487, 4112, 3030, 3258, 2824, 3761, 3127, 7483, 7484, 1507, 7485,  # 4326
+    2683, 733, 40, 1632, 1106, 2865, 345, 4113, 841, 2524, 230, 4364, 2984, 1846, 3259, 3428,  # 4342
+    7486, 1263, 986, 3429, 7487, 735, 879, 254, 1137, 857, 622, 1300, 1180, 1388, 1562, 3907,  # 4358
+    3908, 2939, 967, 2751, 2655, 1349, 592, 2133, 1692, 3324, 2985, 1994, 4114, 1679, 3909, 1901,  # 4374
+    2185, 7488, 739, 3642, 2715, 1296, 1290, 7489, 4115, 2198, 2199, 1921, 1563, 2595, 2551, 1870,  # 4390
+    2752, 2986, 7490, 435, 7491, 343, 1108, 596, 17, 1751, 4365, 2235, 3430, 3643, 7492, 4366,  # 4406
+    294, 3527, 2940, 1693, 477, 979, 281, 2041, 3528, 643, 2042, 3644, 2621, 2782, 2261, 1031,  # 4422
+    2335, 2134, 2298, 3529, 4367, 367, 1249, 2552, 7493, 3530, 7494, 4368, 1283, 3325, 2004, 240,  # 4438
+    1762, 3326, 4369, 4370, 836, 1069, 3128, 474, 7495, 2148, 2525, 268, 3531, 7496, 3188, 1521,  # 4454
+    1284, 7497, 1658, 1546, 4116, 7498, 3532, 3533, 7499, 4117, 3327, 2684, 1685, 4118, 961, 1673,  # 4470
+    2622, 190, 2005, 2200, 3762, 4371, 4372, 7500, 570, 2497, 3645, 1490, 7501, 4373, 2623, 3260,  # 4486
+    1956, 4374, 584, 1514, 396, 1045, 1944, 7502, 4375, 1967, 2444, 7503, 7504, 4376, 3910, 619,  # 4502
+    7505, 3129, 3261, 215, 2006, 2783, 2553, 3189, 4377, 3190, 4378, 763, 4119, 3763, 4379, 7506,  # 4518
+    7507, 1957, 1767, 2941, 3328, 3646, 1174, 452, 1477, 4380, 3329, 3130, 7508, 2825, 1253, 2382,  # 4534
+    2186, 1091, 2285, 4120, 492, 7509, 638, 1169, 1824, 2135, 1752, 3911, 648, 926, 1021, 1324,  # 4550
+    4381, 520, 4382, 997, 847, 1007, 892, 4383, 3764, 2262, 1871, 3647, 7510, 2400, 1784, 4384,  # 4566
+    1952, 2942, 3080, 3191, 1728, 4121, 2043, 3648, 4385, 2007, 1701, 3131, 1551, 30, 2263, 4122,  # 4582
+    7511, 2026, 4386, 3534, 7512, 501, 7513, 4123, 594, 3431, 2165, 1821, 3535, 3432, 3536, 3192,  # 4598
+    829, 2826, 4124, 7514, 1680, 3132, 1225, 4125, 7515, 3262, 4387, 4126, 3133, 2336, 7516, 4388,  # 4614
+    4127, 7517, 3912, 3913, 7518, 1847, 2383, 2596, 3330, 7519, 4389, 374, 3914, 652, 4128, 4129,  # 4630
+    375, 1140, 798, 7520, 7521, 7522, 2361, 4390, 2264, 546, 1659, 138, 3031, 2445, 4391, 7523,  # 4646
+    2250, 612, 1848, 910, 796, 3765, 1740, 1371, 825, 3766, 3767, 7524, 2906, 2554, 7525, 692,  # 4662
+    444, 3032, 2624, 801, 4392, 4130, 7526, 1491, 244, 1053, 3033, 4131, 4132, 340, 7527, 3915,  # 4678
+    1041, 2987, 293, 1168, 87, 1357, 7528, 1539, 959, 7529, 2236, 721, 694, 4133, 3768, 219,  # 4694
+    1478, 644, 1417, 3331, 2656, 1413, 1401, 1335, 1389, 3916, 7530, 7531, 2988, 2362, 3134, 1825,  # 4710
+    730, 1515, 184, 2827, 66, 4393, 7532, 1660, 2943, 246, 3332, 378, 1457, 226, 3433, 975,  # 4726
+    3917, 2944, 1264, 3537, 674, 696, 7533, 163, 7534, 1141, 2417, 2166, 713, 3538, 3333, 4394,  # 4742
+    3918, 7535, 7536, 1186, 15, 7537, 1079, 1070, 7538, 1522, 3193, 3539, 276, 1050, 2716, 758,  # 4758
+    1126, 653, 2945, 3263, 7539, 2337, 889, 3540, 3919, 3081, 2989, 903, 1250, 4395, 3920, 3434,  # 4774
+    3541, 1342, 1681, 1718, 766, 3264, 286, 89, 2946, 3649, 7540, 1713, 7541, 2597, 3334, 2990,  # 4790
+    7542, 2947, 2215, 3194, 2866, 7543, 4396, 2498, 2526, 181, 387, 1075, 3921, 731, 2187, 3335,  # 4806
+    7544, 3265, 310, 313, 3435, 2299, 770, 4134, 54, 3034, 189, 4397, 3082, 3769, 3922, 7545,  # 4822
+    1230, 1617, 1849, 355, 3542, 4135, 4398, 3336, 111, 4136, 3650, 1350, 3135, 3436, 3035, 4137,  # 4838
+    2149, 3266, 3543, 7546, 2784, 3923, 3924, 2991, 722, 2008, 7547, 1071, 247, 1207, 2338, 2471,  # 4854
+    1378, 4399, 2009, 864, 1437, 1214, 4400, 373, 3770, 1142, 2216, 667, 4401, 442, 2753, 2555,  # 4870
+    3771, 3925, 1968, 4138, 3267, 1839, 837, 170, 1107, 934, 1336, 1882, 7548, 7549, 2118, 4139,  # 4886
+    2828, 743, 1569, 7550, 4402, 4140, 582, 2384, 1418, 3437, 7551, 1802, 7552, 357, 1395, 1729,  # 4902
+    3651, 3268, 2418, 1564, 2237, 7553, 3083, 3772, 1633, 4403, 1114, 2085, 4141, 1532, 7554, 482,  # 4918
+    2446, 4404, 7555, 7556, 1492, 833, 1466, 7557, 2717, 3544, 1641, 2829, 7558, 1526, 1272, 3652,  # 4934
+    4142, 1686, 1794, 416, 2556, 1902, 1953, 1803, 7559, 3773, 2785, 3774, 1159, 2316, 7560, 2867,  # 4950
+    4405, 1610, 1584, 3036, 2419, 2754, 443, 3269, 1163, 3136, 7561, 7562, 3926, 7563, 4143, 2499,  # 4966
+    3037, 4406, 3927, 3137, 2103, 1647, 3545, 2010, 1872, 4144, 7564, 4145, 431, 3438, 7565, 250,  # 4982
+    97, 81, 4146, 7566, 1648, 1850, 1558, 160, 848, 7567, 866, 740, 1694, 7568, 2201, 2830,  # 4998
+    3195, 4147, 4407, 3653, 1687, 950, 2472, 426, 469, 3196, 3654, 3655, 3928, 7569, 7570, 1188,  # 5014
+    424, 1995, 861, 3546, 4148, 3775, 2202, 2685, 168, 1235, 3547, 4149, 7571, 2086, 1674, 4408,  # 5030
+    3337, 3270, 220, 2557, 1009, 7572, 3776, 670, 2992, 332, 1208, 717, 7573, 7574, 3548, 2447,  # 5046
+    3929, 3338, 7575, 513, 7576, 1209, 2868, 3339, 3138, 4409, 1080, 7577, 7578, 7579, 7580, 2527,  # 5062
+    3656, 3549, 815, 1587, 3930, 3931, 7581, 3550, 3439, 3777, 1254, 4410, 1328, 3038, 1390, 3932,  # 5078
+    1741, 3933, 3778, 3934, 7582, 236, 3779, 2448, 3271, 7583, 7584, 3657, 3780, 1273, 3781, 4411,  # 5094
+    7585, 308, 7586, 4412, 245, 4413, 1851, 2473, 1307, 2575, 430, 715, 2136, 2449, 7587, 270,  # 5110
+    199, 2869, 3935, 7588, 3551, 2718, 1753, 761, 1754, 725, 1661, 1840, 4414, 3440, 3658, 7589,  # 5126
+    7590, 587, 14, 3272, 227, 2598, 326, 480, 2265, 943, 2755, 3552, 291, 650, 1883, 7591,  # 5142
+    1702, 1226, 102, 1547, 62, 3441, 904, 4415, 3442, 1164, 4150, 7592, 7593, 1224, 1548, 2756,  # 5158
+    391, 498, 1493, 7594, 1386, 1419, 7595, 2055, 1177, 4416, 813, 880, 1081, 2363, 566, 1145,  # 5174
+    4417, 2286, 1001, 1035, 2558, 2599, 2238, 394, 1286, 7596, 7597, 2068, 7598, 86, 1494, 1730,  # 5190
+    3936, 491, 1588, 745, 897, 2948, 843, 3340, 3937, 2757, 2870, 3273, 1768, 998, 2217, 2069,  # 5206
+    397, 1826, 1195, 1969, 3659, 2993, 3341, 284, 7599, 3782, 2500, 2137, 2119, 1903, 7600, 3938,  # 5222
+    2150, 3939, 4151, 1036, 3443, 1904, 114, 2559, 4152, 209, 1527, 7601, 7602, 2949, 2831, 2625,  # 5238
+    2385, 2719, 3139, 812, 2560, 7603, 3274, 7604, 1559, 737, 1884, 3660, 1210, 885, 28, 2686,  # 5254
+    3553, 3783, 7605, 4153, 1004, 1779, 4418, 7606, 346, 1981, 2218, 2687, 4419, 3784, 1742, 797,  # 5270
+    1642, 3940, 1933, 1072, 1384, 2151, 896, 3941, 3275, 3661, 3197, 2871, 3554, 7607, 2561, 1958,  # 5286
+    4420, 2450, 1785, 7608, 7609, 7610, 3942, 4154, 1005, 1308, 3662, 4155, 2720, 4421, 4422, 1528,  # 5302
+    2600, 161, 1178, 4156, 1982, 987, 4423, 1101, 4157, 631, 3943, 1157, 3198, 2420, 1343, 1241,  # 5318
+    1016, 2239, 2562, 372, 877, 2339, 2501, 1160, 555, 1934, 911, 3944, 7611, 466, 1170, 169,  # 5334
+    1051, 2907, 2688, 3663, 2474, 2994, 1182, 2011, 2563, 1251, 2626, 7612, 992, 2340, 3444, 1540,  # 5350
+    2721, 1201, 2070, 2401, 1996, 2475, 7613, 4424, 528, 1922, 2188, 1503, 1873, 1570, 2364, 3342,  # 5366
+    3276, 7614, 557, 1073, 7615, 1827, 3445, 2087, 2266, 3140, 3039, 3084, 767, 3085, 2786, 4425,  # 5382
+    1006, 4158, 4426, 2341, 1267, 2176, 3664, 3199, 778, 3945, 3200, 2722, 1597, 2657, 7616, 4427,  # 5398
+    7617, 3446, 7618, 7619, 7620, 3277, 2689, 1433, 3278, 131, 95, 1504, 3946, 723, 4159, 3141,  # 5414
+    1841, 3555, 2758, 2189, 3947, 2027, 2104, 3665, 7621, 2995, 3948, 1218, 7622, 3343, 3201, 3949,  # 5430
+    4160, 2576, 248, 1634, 3785, 912, 7623, 2832, 3666, 3040, 3786, 654, 53, 7624, 2996, 7625,  # 5446
+    1688, 4428, 777, 3447, 1032, 3950, 1425, 7626, 191, 820, 2120, 2833, 971, 4429, 931, 3202,  # 5462
+    135, 664, 783, 3787, 1997, 772, 2908, 1935, 3951, 3788, 4430, 2909, 3203, 282, 2723, 640,  # 5478
+    1372, 3448, 1127, 922, 325, 3344, 7627, 7628, 711, 2044, 7629, 7630, 3952, 2219, 2787, 1936,  # 5494
+    3953, 3345, 2220, 2251, 3789, 2300, 7631, 4431, 3790, 1258, 3279, 3954, 3204, 2138, 2950, 3955,  # 5510
+    3956, 7632, 2221, 258, 3205, 4432, 101, 1227, 7633, 3280, 1755, 7634, 1391, 3281, 7635, 2910,  # 5526
+    2056, 893, 7636, 7637, 7638, 1402, 4161, 2342, 7639, 7640, 3206, 3556, 7641, 7642, 878, 1325,  # 5542
+    1780, 2788, 4433, 259, 1385, 2577, 744, 1183, 2267, 4434, 7643, 3957, 2502, 7644, 684, 1024,  # 5558
+    4162, 7645, 472, 3557, 3449, 1165, 3282, 3958, 3959, 322, 2152, 881, 455, 1695, 1152, 1340,  # 5574
+    660, 554, 2153, 4435, 1058, 4436, 4163, 830, 1065, 3346, 3960, 4437, 1923, 7646, 1703, 1918,  # 5590
+    7647, 932, 2268, 122, 7648, 4438, 947, 677, 7649, 3791, 2627, 297, 1905, 1924, 2269, 4439,  # 5606
+    2317, 3283, 7650, 7651, 4164, 7652, 4165, 84, 4166, 112, 989, 7653, 547, 1059, 3961, 701,  # 5622
+    3558, 1019, 7654, 4167, 7655, 3450, 942, 639, 457, 2301, 2451, 993, 2951, 407, 851, 494,  # 5638
+    4440, 3347, 927, 7656, 1237, 7657, 2421, 3348, 573, 4168, 680, 921, 2911, 1279, 1874, 285,  # 5654
+    790, 1448, 1983, 719, 2167, 7658, 7659, 4441, 3962, 3963, 1649, 7660, 1541, 563, 7661, 1077,  # 5670
+    7662, 3349, 3041, 3451, 511, 2997, 3964, 3965, 3667, 3966, 1268, 2564, 3350, 3207, 4442, 4443,  # 5686
+    7663, 535, 1048, 1276, 1189, 2912, 2028, 3142, 1438, 1373, 2834, 2952, 1134, 2012, 7664, 4169,  # 5702
+    1238, 2578, 3086, 1259, 7665, 700, 7666, 2953, 3143, 3668, 4170, 7667, 4171, 1146, 1875, 1906,  # 5718
+    4444, 2601, 3967, 781, 2422, 132, 1589, 203, 147, 273, 2789, 2402, 898, 1786, 2154, 3968,  # 5734
+    3969, 7668, 3792, 2790, 7669, 7670, 4445, 4446, 7671, 3208, 7672, 1635, 3793, 965, 7673, 1804,  # 5750
+    2690, 1516, 3559, 1121, 1082, 1329, 3284, 3970, 1449, 3794, 65, 1128, 2835, 2913, 2759, 1590,  # 5766
+    3795, 7674, 7675, 12, 2658, 45, 976, 2579, 3144, 4447, 517, 2528, 1013, 1037, 3209, 7676,  # 5782
+    3796, 2836, 7677, 3797, 7678, 3452, 7679, 2602, 614, 1998, 2318, 3798, 3087, 2724, 2628, 7680,  # 5798
+    2580, 4172, 599, 1269, 7681, 1810, 3669, 7682, 2691, 3088, 759, 1060, 489, 1805, 3351, 3285,  # 5814
+    1358, 7683, 7684, 2386, 1387, 1215, 2629, 2252, 490, 7685, 7686, 4173, 1759, 2387, 2343, 7687,  # 5830
+    4448, 3799, 1907, 3971, 2630, 1806, 3210, 4449, 3453, 3286, 2760, 2344, 874, 7688, 7689, 3454,  # 5846
+    3670, 1858, 91, 2914, 3671, 3042, 3800, 4450, 7690, 3145, 3972, 2659, 7691, 3455, 1202, 1403,  # 5862
+    3801, 2954, 2529, 1517, 2503, 4451, 3456, 2504, 7692, 4452, 7693, 2692, 1885, 1495, 1731, 3973,  # 5878
+    2365, 4453, 7694, 2029, 7695, 7696, 3974, 2693, 1216, 237, 2581, 4174, 2319, 3975, 3802, 4454,  # 5894
+    4455, 2694, 3560, 3457, 445, 4456, 7697, 7698, 7699, 7700, 2761, 61, 3976, 3672, 1822, 3977,  # 5910
+    7701, 687, 2045, 935, 925, 405, 2660, 703, 1096, 1859, 2725, 4457, 3978, 1876, 1367, 2695,  # 5926
+    3352, 918, 2105, 1781, 2476, 334, 3287, 1611, 1093, 4458, 564, 3146, 3458, 3673, 3353, 945,  # 5942
+    2631, 2057, 4459, 7702, 1925, 872, 4175, 7703, 3459, 2696, 3089, 349, 4176, 3674, 3979, 4460,  # 5958
+    3803, 4177, 3675, 2155, 3980, 4461, 4462, 4178, 4463, 2403, 2046, 782, 3981, 400, 251, 4179,  # 5974
+    1624, 7704, 7705, 277, 3676, 299, 1265, 476, 1191, 3804, 2121, 4180, 4181, 1109, 205, 7706,  # 5990
+    2582, 1000, 2156, 3561, 1860, 7707, 7708, 7709, 4464, 7710, 4465, 2565, 107, 2477, 2157, 3982,  # 6006
+    3460, 3147, 7711, 1533, 541, 1301, 158, 753, 4182, 2872, 3562, 7712, 1696, 370, 1088, 4183,  # 6022
+    4466, 3563, 579, 327, 440, 162, 2240, 269, 1937, 1374, 3461, 968, 3043, 56, 1396, 3090,  # 6038
+    2106, 3288, 3354, 7713, 1926, 2158, 4467, 2998, 7714, 3564, 7715, 7716, 3677, 4468, 2478, 7717,  # 6054
+    2791, 7718, 1650, 4469, 7719, 2603, 7720, 7721, 3983, 2661, 3355, 1149, 3356, 3984, 3805, 3985,  # 6070
+    7722, 1076, 49, 7723, 951, 3211, 3289, 3290, 450, 2837, 920, 7724, 1811, 2792, 2366, 4184,  # 6086
+    1908, 1138, 2367, 3806, 3462, 7725, 3212, 4470, 1909, 1147, 1518, 2423, 4471, 3807, 7726, 4472,  # 6102
+    2388, 2604, 260, 1795, 3213, 7727, 7728, 3808, 3291, 708, 7729, 3565, 1704, 7730, 3566, 1351,  # 6118
+    1618, 3357, 2999, 1886, 944, 4185, 3358, 4186, 3044, 3359, 4187, 7731, 3678, 422, 413, 1714,  # 6134
+    3292, 500, 2058, 2345, 4188, 2479, 7732, 1344, 1910, 954, 7733, 1668, 7734, 7735, 3986, 2404,  # 6150
+    4189, 3567, 3809, 4190, 7736, 2302, 1318, 2505, 3091, 133, 3092, 2873, 4473, 629, 31, 2838,  # 6166
+    2697, 3810, 4474, 850, 949, 4475, 3987, 2955, 1732, 2088, 4191, 1496, 1852, 7737, 3988, 620,  # 6182
+    3214, 981, 1242, 3679, 3360, 1619, 3680, 1643, 3293, 2139, 2452, 1970, 1719, 3463, 2168, 7738,  # 6198
+    3215, 7739, 7740, 3361, 1828, 7741, 1277, 4476, 1565, 2047, 7742, 1636, 3568, 3093, 7743, 869,  # 6214
+    2839, 655, 3811, 3812, 3094, 3989, 3000, 3813, 1310, 3569, 4477, 7744, 7745, 7746, 1733, 558,  # 6230
+    4478, 3681, 335, 1549, 3045, 1756, 4192, 3682, 1945, 3464, 1829, 1291, 1192, 470, 2726, 2107,  # 6246
+    2793, 913, 1054, 3990, 7747, 1027, 7748, 3046, 3991, 4479, 982, 2662, 3362, 3148, 3465, 3216,  # 6262
+    3217, 1946, 2794, 7749, 571, 4480, 7750, 1830, 7751, 3570, 2583, 1523, 2424, 7752, 2089, 984,  # 6278
+    4481, 3683, 1959, 7753, 3684, 852, 923, 2795, 3466, 3685, 969, 1519, 999, 2048, 2320, 1705,  # 6294
+    7754, 3095, 615, 1662, 151, 597, 3992, 2405, 2321, 1049, 275, 4482, 3686, 4193, 568, 3687,  # 6310
+    3571, 2480, 4194, 3688, 7755, 2425, 2270, 409, 3218, 7756, 1566, 2874, 3467, 1002, 769, 2840,  # 6326
+    194, 2090, 3149, 3689, 2222, 3294, 4195, 628, 1505, 7757, 7758, 1763, 2177, 3001, 3993, 521,  # 6342
+    1161, 2584, 1787, 2203, 2406, 4483, 3994, 1625, 4196, 4197, 412, 42, 3096, 464, 7759, 2632,  # 6358
+    4484, 3363, 1760, 1571, 2875, 3468, 2530, 1219, 2204, 3814, 2633, 2140, 2368, 4485, 4486, 3295,  # 6374
+    1651, 3364, 3572, 7760, 7761, 3573, 2481, 3469, 7762, 3690, 7763, 7764, 2271, 2091, 460, 7765,  # 6390
+    4487, 7766, 3002, 962, 588, 3574, 289, 3219, 2634, 1116, 52, 7767, 3047, 1796, 7768, 7769,  # 6406
+    7770, 1467, 7771, 1598, 1143, 3691, 4198, 1984, 1734, 1067, 4488, 1280, 3365, 465, 4489, 1572,  # 6422
+    510, 7772, 1927, 2241, 1812, 1644, 3575, 7773, 4490, 3692, 7774, 7775, 2663, 1573, 1534, 7776,  # 6438
+    7777, 4199, 536, 1807, 1761, 3470, 3815, 3150, 2635, 7778, 7779, 7780, 4491, 3471, 2915, 1911,  # 6454
+    2796, 7781, 3296, 1122, 377, 3220, 7782, 360, 7783, 7784, 4200, 1529, 551, 7785, 2059, 3693,  # 6470
+    1769, 2426, 7786, 2916, 4201, 3297, 3097, 2322, 2108, 2030, 4492, 1404, 136, 1468, 1479, 672,  # 6486
+    1171, 3221, 2303, 271, 3151, 7787, 2762, 7788, 2049, 678, 2727, 865, 1947, 4493, 7789, 2013,  # 6502
+    3995, 2956, 7790, 2728, 2223, 1397, 3048, 3694, 4494, 4495, 1735, 2917, 3366, 3576, 7791, 3816,  # 6518
+    509, 2841, 2453, 2876, 3817, 7792, 7793, 3152, 3153, 4496, 4202, 2531, 4497, 2304, 1166, 1010,  # 6534
+    552, 681, 1887, 7794, 7795, 2957, 2958, 3996, 1287, 1596, 1861, 3154, 358, 453, 736, 175,  # 6550
+    478, 1117, 905, 1167, 1097, 7796, 1853, 1530, 7797, 1706, 7798, 2178, 3472, 2287, 3695, 3473,  # 6566
+    3577, 4203, 2092, 4204, 7799, 3367, 1193, 2482, 4205, 1458, 2190, 2205, 1862, 1888, 1421, 3298,  # 6582
+    2918, 3049, 2179, 3474, 595, 2122, 7800, 3997, 7801, 7802, 4206, 1707, 2636, 223, 3696, 1359,  # 6598
+    751, 3098, 183, 3475, 7803, 2797, 3003, 419, 2369, 633, 704, 3818, 2389, 241, 7804, 7805,  # 6614
+    7806, 838, 3004, 3697, 2272, 2763, 2454, 3819, 1938, 2050, 3998, 1309, 3099, 2242, 1181, 7807,  # 6630
+    1136, 2206, 3820, 2370, 1446, 4207, 2305, 4498, 7808, 7809, 4208, 1055, 2605, 484, 3698, 7810,  # 6646
+    3999, 625, 4209, 2273, 3368, 1499, 4210, 4000, 7811, 4001, 4211, 3222, 2274, 2275, 3476, 7812,  # 6662
+    7813, 2764, 808, 2606, 3699, 3369, 4002, 4212, 3100, 2532, 526, 3370, 3821, 4213, 955, 7814,  # 6678
+    1620, 4214, 2637, 2427, 7815, 1429, 3700, 1669, 1831, 994, 928, 7816, 3578, 1260, 7817, 7818,  # 6694
+    7819, 1948, 2288, 741, 2919, 1626, 4215, 2729, 2455, 867, 1184, 362, 3371, 1392, 7820, 7821,  # 6710
+    4003, 4216, 1770, 1736, 3223, 2920, 4499, 4500, 1928, 2698, 1459, 1158, 7822, 3050, 3372, 2877,  # 6726
+    1292, 1929, 2506, 2842, 3701, 1985, 1187, 2071, 2014, 2607, 4217, 7823, 2566, 2507, 2169, 3702,  # 6742
+    2483, 3299, 7824, 3703, 4501, 7825, 7826, 666, 1003, 3005, 1022, 3579, 4218, 7827, 4502, 1813,  # 6758
+    2253, 574, 3822, 1603, 295, 1535, 705, 3823, 4219, 283, 858, 417, 7828, 7829, 3224, 4503,  # 6774
+    4504, 3051, 1220, 1889, 1046, 2276, 2456, 4004, 1393, 1599, 689, 2567, 388, 4220, 7830, 2484,  # 6790
+    802, 7831, 2798, 3824, 2060, 1405, 2254, 7832, 4505, 3825, 2109, 1052, 1345, 3225, 1585, 7833,  # 6806
+    809, 7834, 7835, 7836, 575, 2730, 3477, 956, 1552, 1469, 1144, 2323, 7837, 2324, 1560, 2457,  # 6822
+    3580, 3226, 4005, 616, 2207, 3155, 2180, 2289, 7838, 1832, 7839, 3478, 4506, 7840, 1319, 3704,  # 6838
+    3705, 1211, 3581, 1023, 3227, 1293, 2799, 7841, 7842, 7843, 3826, 607, 2306, 3827, 762, 2878,  # 6854
+    1439, 4221, 1360, 7844, 1485, 3052, 7845, 4507, 1038, 4222, 1450, 2061, 2638, 4223, 1379, 4508,  # 6870
+    2585, 7846, 7847, 4224, 1352, 1414, 2325, 2921, 1172, 7848, 7849, 3828, 3829, 7850, 1797, 1451,  # 6886
+    7851, 7852, 7853, 7854, 2922, 4006, 4007, 2485, 2346, 411, 4008, 4009, 3582, 3300, 3101, 4509,  # 6902
+    1561, 2664, 1452, 4010, 1375, 7855, 7856, 47, 2959, 316, 7857, 1406, 1591, 2923, 3156, 7858,  # 6918
+    1025, 2141, 3102, 3157, 354, 2731, 884, 2224, 4225, 2407, 508, 3706, 726, 3583, 996, 2428,  # 6934
+    3584, 729, 7859, 392, 2191, 1453, 4011, 4510, 3707, 7860, 7861, 2458, 3585, 2608, 1675, 2800,  # 6950
+    919, 2347, 2960, 2348, 1270, 4511, 4012, 73, 7862, 7863, 647, 7864, 3228, 2843, 2255, 1550,  # 6966
+    1346, 3006, 7865, 1332, 883, 3479, 7866, 7867, 7868, 7869, 3301, 2765, 7870, 1212, 831, 1347,  # 6982
+    4226, 4512, 2326, 3830, 1863, 3053, 720, 3831, 4513, 4514, 3832, 7871, 4227, 7872, 7873, 4515,  # 6998
+    7874, 7875, 1798, 4516, 3708, 2609, 4517, 3586, 1645, 2371, 7876, 7877, 2924, 669, 2208, 2665,  # 7014
+    2429, 7878, 2879, 7879, 7880, 1028, 3229, 7881, 4228, 2408, 7882, 2256, 1353, 7883, 7884, 4518,  # 7030
+    3158, 518, 7885, 4013, 7886, 4229, 1960, 7887, 2142, 4230, 7888, 7889, 3007, 2349, 2350, 3833,  # 7046
+    516, 1833, 1454, 4014, 2699, 4231, 4519, 2225, 2610, 1971, 1129, 3587, 7890, 2766, 7891, 2961,  # 7062
+    1422, 577, 1470, 3008, 1524, 3373, 7892, 7893, 432, 4232, 3054, 3480, 7894, 2586, 1455, 2508,  # 7078
+    2226, 1972, 1175, 7895, 1020, 2732, 4015, 3481, 4520, 7896, 2733, 7897, 1743, 1361, 3055, 3482,  # 7094
+    2639, 4016, 4233, 4521, 2290, 895, 924, 4234, 2170, 331, 2243, 3056, 166, 1627, 3057, 1098,  # 7110
+    7898, 1232, 2880, 2227, 3374, 4522, 657, 403, 1196, 2372, 542, 3709, 3375, 1600, 4235, 3483,  # 7126
+    7899, 4523, 2767, 3230, 576, 530, 1362, 7900, 4524, 2533, 2666, 3710, 4017, 7901, 842, 3834,  # 7142
+    7902, 2801, 2031, 1014, 4018, 213, 2700, 3376, 665, 621, 4236, 7903, 3711, 2925, 2430, 7904,  # 7158
+    2431, 3302, 3588, 3377, 7905, 4237, 2534, 4238, 4525, 3589, 1682, 4239, 3484, 1380, 7906, 724,  # 7174
+    2277, 600, 1670, 7907, 1337, 1233, 4526, 3103, 2244, 7908, 1621, 4527, 7909, 651, 4240, 7910,  # 7190
+    1612, 4241, 2611, 7911, 2844, 7912, 2734, 2307, 3058, 7913, 716, 2459, 3059, 174, 1255, 2701,  # 7206
+    4019, 3590, 548, 1320, 1398, 728, 4020, 1574, 7914, 1890, 1197, 3060, 4021, 7915, 3061, 3062,  # 7222
+    3712, 3591, 3713, 747, 7916, 635, 4242, 4528, 7917, 7918, 7919, 4243, 7920, 7921, 4529, 7922,  # 7238
+    3378, 4530, 2432, 451, 7923, 3714, 2535, 2072, 4244, 2735, 4245, 4022, 7924, 1764, 4531, 7925,  # 7254
+    4246, 350, 7926, 2278, 2390, 2486, 7927, 4247, 4023, 2245, 1434, 4024, 488, 4532, 458, 4248,  # 7270
+    4025, 3715, 771, 1330, 2391, 3835, 2568, 3159, 2159, 2409, 1553, 2667, 3160, 4249, 7928, 2487,  # 7286
+    2881, 2612, 1720, 2702, 4250, 3379, 4533, 7929, 2536, 4251, 7930, 3231, 4252, 2768, 7931, 2015,  # 7302
+    2736, 7932, 1155, 1017, 3716, 3836, 7933, 3303, 2308, 201, 1864, 4253, 1430, 7934, 4026, 7935,  # 7318
+    7936, 7937, 7938, 7939, 4254, 1604, 7940, 414, 1865, 371, 2587, 4534, 4535, 3485, 2016, 3104,  # 7334
+    4536, 1708, 960, 4255, 887, 389, 2171, 1536, 1663, 1721, 7941, 2228, 4027, 2351, 2926, 1580,  # 7350
+    7942, 7943, 7944, 1744, 7945, 2537, 4537, 4538, 7946, 4539, 7947, 2073, 7948, 7949, 3592, 3380,  # 7366
+    2882, 4256, 7950, 4257, 2640, 3381, 2802, 673, 2703, 2460, 709, 3486, 4028, 3593, 4258, 7951,  # 7382
+    1148, 502, 634, 7952, 7953, 1204, 4540, 3594, 1575, 4541, 2613, 3717, 7954, 3718, 3105, 948,  # 7398
+    3232, 121, 1745, 3837, 1110, 7955, 4259, 3063, 2509, 3009, 4029, 3719, 1151, 1771, 3838, 1488,  # 7414
+    4030, 1986, 7956, 2433, 3487, 7957, 7958, 2093, 7959, 4260, 3839, 1213, 1407, 2803, 531, 2737,  # 7430
+    2538, 3233, 1011, 1537, 7960, 2769, 4261, 3106, 1061, 7961, 3720, 3721, 1866, 2883, 7962, 2017,  # 7446
+    120, 4262, 4263, 2062, 3595, 3234, 2309, 3840, 2668, 3382, 1954, 4542, 7963, 7964, 3488, 1047,  # 7462
+    2704, 1266, 7965, 1368, 4543, 2845, 649, 3383, 3841, 2539, 2738, 1102, 2846, 2669, 7966, 7967,  # 7478
+    1999, 7968, 1111, 3596, 2962, 7969, 2488, 3842, 3597, 2804, 1854, 3384, 3722, 7970, 7971, 3385,  # 7494
+    2410, 2884, 3304, 3235, 3598, 7972, 2569, 7973, 3599, 2805, 4031, 1460, 856, 7974, 3600, 7975,  # 7510
+    2885, 2963, 7976, 2886, 3843, 7977, 4264, 632, 2510, 875, 3844, 1697, 3845, 2291, 7978, 7979,  # 7526
+    4544, 3010, 1239, 580, 4545, 4265, 7980, 914, 936, 2074, 1190, 4032, 1039, 2123, 7981, 7982,  # 7542
+    7983, 3386, 1473, 7984, 1354, 4266, 3846, 7985, 2172, 3064, 4033, 915, 3305, 4267, 4268, 3306,  # 7558
+    1605, 1834, 7986, 2739, 398, 3601, 4269, 3847, 4034, 328, 1912, 2847, 4035, 3848, 1331, 4270,  # 7574
+    3011, 937, 4271, 7987, 3602, 4036, 4037, 3387, 2160, 4546, 3388, 524, 742, 538, 3065, 1012,  # 7590
+    7988, 7989, 3849, 2461, 7990, 658, 1103, 225, 3850, 7991, 7992, 4547, 7993, 4548, 7994, 3236,  # 7606
+    1243, 7995, 4038, 963, 2246, 4549, 7996, 2705, 3603, 3161, 7997, 7998, 2588, 2327, 7999, 4550,  # 7622
+    8000, 8001, 8002, 3489, 3307, 957, 3389, 2540, 2032, 1930, 2927, 2462, 870, 2018, 3604, 1746,  # 7638
+    2770, 2771, 2434, 2463, 8003, 3851, 8004, 3723, 3107, 3724, 3490, 3390, 3725, 8005, 1179, 3066,  # 7654
+    8006, 3162, 2373, 4272, 3726, 2541, 3163, 3108, 2740, 4039, 8007, 3391, 1556, 2542, 2292, 977,  # 7670
+    2887, 2033, 4040, 1205, 3392, 8008, 1765, 3393, 3164, 2124, 1271, 1689, 714, 4551, 3491, 8009,  # 7686
+    2328, 3852, 533, 4273, 3605, 2181, 617, 8010, 2464, 3308, 3492, 2310, 8011, 8012, 3165, 8013,  # 7702
+    8014, 3853, 1987, 618, 427, 2641, 3493, 3394, 8015, 8016, 1244, 1690, 8017, 2806, 4274, 4552,  # 7718
+    8018, 3494, 8019, 8020, 2279, 1576, 473, 3606, 4275, 3395, 972, 8021, 3607, 8022, 3067, 8023,  # 7734
+    8024, 4553, 4554, 8025, 3727, 4041, 4042, 8026, 153, 4555, 356, 8027, 1891, 2888, 4276, 2143,  # 7750
+    408, 803, 2352, 8028, 3854, 8029, 4277, 1646, 2570, 2511, 4556, 4557, 3855, 8030, 3856, 4278,  # 7766
+    8031, 2411, 3396, 752, 8032, 8033, 1961, 2964, 8034, 746, 3012, 2465, 8035, 4279, 3728, 698,  # 7782
+    4558, 1892, 4280, 3608, 2543, 4559, 3609, 3857, 8036, 3166, 3397, 8037, 1823, 1302, 4043, 2706,  # 7798
+    3858, 1973, 4281, 8038, 4282, 3167, 823, 1303, 1288, 1236, 2848, 3495, 4044, 3398, 774, 3859,  # 7814
+    8039, 1581, 4560, 1304, 2849, 3860, 4561, 8040, 2435, 2161, 1083, 3237, 4283, 4045, 4284, 344,  # 7830
+    1173, 288, 2311, 454, 1683, 8041, 8042, 1461, 4562, 4046, 2589, 8043, 8044, 4563, 985, 894,  # 7846
+    8045, 3399, 3168, 8046, 1913, 2928, 3729, 1988, 8047, 2110, 1974, 8048, 4047, 8049, 2571, 1194,  # 7862
+    425, 8050, 4564, 3169, 1245, 3730, 4285, 8051, 8052, 2850, 8053, 636, 4565, 1855, 3861, 760,  # 7878
+    1799, 8054, 4286, 2209, 1508, 4566, 4048, 1893, 1684, 2293, 8055, 8056, 8057, 4287, 4288, 2210,  # 7894
+    479, 8058, 8059, 832, 8060, 4049, 2489, 8061, 2965, 2490, 3731, 990, 3109, 627, 1814, 2642,  # 7910
+    4289, 1582, 4290, 2125, 2111, 3496, 4567, 8062, 799, 4291, 3170, 8063, 4568, 2112, 1737, 3013,  # 7926
+    1018, 543, 754, 4292, 3309, 1676, 4569, 4570, 4050, 8064, 1489, 8065, 3497, 8066, 2614, 2889,  # 7942
+    4051, 8067, 8068, 2966, 8069, 8070, 8071, 8072, 3171, 4571, 4572, 2182, 1722, 8073, 3238, 3239,  # 7958
+    1842, 3610, 1715, 481, 365, 1975, 1856, 8074, 8075, 1962, 2491, 4573, 8076, 2126, 3611, 3240,  # 7974
+    433, 1894, 2063, 2075, 8077, 602, 2741, 8078, 8079, 8080, 8081, 8082, 3014, 1628, 3400, 8083,  # 7990
+    3172, 4574, 4052, 2890, 4575, 2512, 8084, 2544, 2772, 8085, 8086, 8087, 3310, 4576, 2891, 8088,  # 8006
+    4577, 8089, 2851, 4578, 4579, 1221, 2967, 4053, 2513, 8090, 8091, 8092, 1867, 1989, 8093, 8094,  # 8022
+    8095, 1895, 8096, 8097, 4580, 1896, 4054, 318, 8098, 2094, 4055, 4293, 8099, 8100, 485, 8101,  # 8038
+    938, 3862, 553, 2670, 116, 8102, 3863, 3612, 8103, 3498, 2671, 2773, 3401, 3311, 2807, 8104,  # 8054
+    3613, 2929, 4056, 1747, 2930, 2968, 8105, 8106, 207, 8107, 8108, 2672, 4581, 2514, 8109, 3015,  # 8070
+    890, 3614, 3864, 8110, 1877, 3732, 3402, 8111, 2183, 2353, 3403, 1652, 8112, 8113, 8114, 941,  # 8086
+    2294, 208, 3499, 4057, 2019, 330, 4294, 3865, 2892, 2492, 3733, 4295, 8115, 8116, 8117, 8118,  # 8102
+)
+# fmt: on
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euctwprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euctwprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..a37ab18995822ad6b3372d56366becdccf9a4c26
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/euctwprober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import EUCTWDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import EUCTW_SM_MODEL
+
+
+class EUCTWProber(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(EUCTW_SM_MODEL)
+        self.distribution_analyzer = EUCTWDistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "EUC-TW"
+
+    @property
+    def language(self) -> str:
+        return "Taiwan"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/gb2312freq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/gb2312freq.py
new file mode 100644
index 0000000000000000000000000000000000000000..b32bfc74213d93d434f1f3a47cb5d7d0bf4863d3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/gb2312freq.py
@@ -0,0 +1,284 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# GB2312 most frequently used character table
+#
+# Char to FreqOrder table , from hz6763
+
+# 512  --> 0.79  -- 0.79
+# 1024 --> 0.92  -- 0.13
+# 2048 --> 0.98  -- 0.06
+# 6768 --> 1.00  -- 0.02
+#
+# Ideal Distribution Ratio = 0.79135/(1-0.79135) = 3.79
+# Random Distribution Ration = 512 / (3755 - 512) = 0.157
+#
+# Typical Distribution Ratio about 25% of Ideal one, still much higher that RDR
+
+GB2312_TYPICAL_DISTRIBUTION_RATIO = 0.9
+
+GB2312_TABLE_SIZE = 3760
+
+# fmt: off
+GB2312_CHAR_TO_FREQ_ORDER = (
+1671, 749,1443,2364,3924,3807,2330,3921,1704,3463,2691,1511,1515, 572,3191,2205,
+2361, 224,2558, 479,1711, 963,3162, 440,4060,1905,2966,2947,3580,2647,3961,3842,
+2204, 869,4207, 970,2678,5626,2944,2956,1479,4048, 514,3595, 588,1346,2820,3409,
+ 249,4088,1746,1873,2047,1774, 581,1813, 358,1174,3590,1014,1561,4844,2245, 670,
+1636,3112, 889,1286, 953, 556,2327,3060,1290,3141, 613, 185,3477,1367, 850,3820,
+1715,2428,2642,2303,2732,3041,2562,2648,3566,3946,1349, 388,3098,2091,1360,3585,
+ 152,1687,1539, 738,1559,  59,1232,2925,2267,1388,1249,1741,1679,2960, 151,1566,
+1125,1352,4271, 924,4296, 385,3166,4459, 310,1245,2850,  70,3285,2729,3534,3575,
+2398,3298,3466,1960,2265, 217,3647, 864,1909,2084,4401,2773,1010,3269,5152, 853,
+3051,3121,1244,4251,1895, 364,1499,1540,2313,1180,3655,2268, 562, 715,2417,3061,
+ 544, 336,3768,2380,1752,4075, 950, 280,2425,4382, 183,2759,3272, 333,4297,2155,
+1688,2356,1444,1039,4540, 736,1177,3349,2443,2368,2144,2225, 565, 196,1482,3406,
+ 927,1335,4147, 692, 878,1311,1653,3911,3622,1378,4200,1840,2969,3149,2126,1816,
+2534,1546,2393,2760, 737,2494,  13, 447, 245,2747,  38,2765,2129,2589,1079, 606,
+ 360, 471,3755,2890, 404, 848, 699,1785,1236, 370,2221,1023,3746,2074,2026,2023,
+2388,1581,2119, 812,1141,3091,2536,1519, 804,2053, 406,1596,1090, 784, 548,4414,
+1806,2264,2936,1100, 343,4114,5096, 622,3358, 743,3668,1510,1626,5020,3567,2513,
+3195,4115,5627,2489,2991,  24,2065,2697,1087,2719,  48,1634, 315,  68, 985,2052,
+ 198,2239,1347,1107,1439, 597,2366,2172, 871,3307, 919,2487,2790,1867, 236,2570,
+1413,3794, 906,3365,3381,1701,1982,1818,1524,2924,1205, 616,2586,2072,2004, 575,
+ 253,3099,  32,1365,1182, 197,1714,2454,1201, 554,3388,3224,2748, 756,2587, 250,
+2567,1507,1517,3529,1922,2761,2337,3416,1961,1677,2452,2238,3153, 615, 911,1506,
+1474,2495,1265,1906,2749,3756,3280,2161, 898,2714,1759,3450,2243,2444, 563,  26,
+3286,2266,3769,3344,2707,3677, 611,1402, 531,1028,2871,4548,1375, 261,2948, 835,
+1190,4134, 353, 840,2684,1900,3082,1435,2109,1207,1674, 329,1872,2781,4055,2686,
+2104, 608,3318,2423,2957,2768,1108,3739,3512,3271,3985,2203,1771,3520,1418,2054,
+1681,1153, 225,1627,2929, 162,2050,2511,3687,1954, 124,1859,2431,1684,3032,2894,
+ 585,4805,3969,2869,2704,2088,2032,2095,3656,2635,4362,2209, 256, 518,2042,2105,
+3777,3657, 643,2298,1148,1779, 190, 989,3544, 414,  11,2135,2063,2979,1471, 403,
+3678, 126, 770,1563, 671,2499,3216,2877, 600,1179, 307,2805,4937,1268,1297,2694,
+ 252,4032,1448,1494,1331,1394, 127,2256, 222,1647,1035,1481,3056,1915,1048, 873,
+3651, 210,  33,1608,2516, 200,1520, 415, 102,   0,3389,1287, 817,  91,3299,2940,
+ 836,1814, 549,2197,1396,1669,2987,3582,2297,2848,4528,1070, 687,  20,1819, 121,
+1552,1364,1461,1968,2617,3540,2824,2083, 177, 948,4938,2291, 110,4549,2066, 648,
+3359,1755,2110,2114,4642,4845,1693,3937,3308,1257,1869,2123, 208,1804,3159,2992,
+2531,2549,3361,2418,1350,2347,2800,2568,1291,2036,2680,  72, 842,1990, 212,1233,
+1154,1586,  75,2027,3410,4900,1823,1337,2710,2676, 728,2810,1522,3026,4995, 157,
+ 755,1050,4022, 710, 785,1936,2194,2085,1406,2777,2400, 150,1250,4049,1206, 807,
+1910, 534, 529,3309,1721,1660, 274,  39,2827, 661,2670,1578, 925,3248,3815,1094,
+4278,4901,4252,  41,1150,3747,2572,2227,4501,3658,4902,3813,3357,3617,2884,2258,
+ 887, 538,4187,3199,1294,2439,3042,2329,2343,2497,1255, 107, 543,1527, 521,3478,
+3568, 194,5062,  15, 961,3870,1241,1192,2664,  66,5215,3260,2111,1295,1127,2152,
+3805,4135, 901,1164,1976, 398,1278, 530,1460, 748, 904,1054,1966,1426,  53,2909,
+ 509, 523,2279,1534, 536,1019, 239,1685, 460,2353, 673,1065,2401,3600,4298,2272,
+1272,2363, 284,1753,3679,4064,1695,  81, 815,2677,2757,2731,1386, 859, 500,4221,
+2190,2566, 757,1006,2519,2068,1166,1455, 337,2654,3203,1863,1682,1914,3025,1252,
+1409,1366, 847, 714,2834,2038,3209, 964,2970,1901, 885,2553,1078,1756,3049, 301,
+1572,3326, 688,2130,1996,2429,1805,1648,2930,3421,2750,3652,3088, 262,1158,1254,
+ 389,1641,1812, 526,1719, 923,2073,1073,1902, 468, 489,4625,1140, 857,2375,3070,
+3319,2863, 380, 116,1328,2693,1161,2244, 273,1212,1884,2769,3011,1775,1142, 461,
+3066,1200,2147,2212, 790, 702,2695,4222,1601,1058, 434,2338,5153,3640,  67,2360,
+4099,2502, 618,3472,1329, 416,1132, 830,2782,1807,2653,3211,3510,1662, 192,2124,
+ 296,3979,1739,1611,3684,  23, 118, 324, 446,1239,1225, 293,2520,3814,3795,2535,
+3116,  17,1074, 467,2692,2201, 387,2922,  45,1326,3055,1645,3659,2817, 958, 243,
+1903,2320,1339,2825,1784,3289, 356, 576, 865,2315,2381,3377,3916,1088,3122,1713,
+1655, 935, 628,4689,1034,1327, 441, 800, 720, 894,1979,2183,1528,5289,2702,1071,
+4046,3572,2399,1571,3281,  79, 761,1103, 327, 134, 758,1899,1371,1615, 879, 442,
+ 215,2605,2579, 173,2048,2485,1057,2975,3317,1097,2253,3801,4263,1403,1650,2946,
+ 814,4968,3487,1548,2644,1567,1285,   2, 295,2636,  97, 946,3576, 832, 141,4257,
+3273, 760,3821,3521,3156,2607, 949,1024,1733,1516,1803,1920,2125,2283,2665,3180,
+1501,2064,3560,2171,1592, 803,3518,1416, 732,3897,4258,1363,1362,2458, 119,1427,
+ 602,1525,2608,1605,1639,3175, 694,3064,  10, 465,  76,2000,4846,4208, 444,3781,
+1619,3353,2206,1273,3796, 740,2483, 320,1723,2377,3660,2619,1359,1137,1762,1724,
+2345,2842,1850,1862, 912, 821,1866, 612,2625,1735,2573,3369,1093, 844,  89, 937,
+ 930,1424,3564,2413,2972,1004,3046,3019,2011, 711,3171,1452,4178, 428, 801,1943,
+ 432, 445,2811, 206,4136,1472, 730, 349,  73, 397,2802,2547, 998,1637,1167, 789,
+ 396,3217, 154,1218, 716,1120,1780,2819,4826,1931,3334,3762,2139,1215,2627, 552,
+3664,3628,3232,1405,2383,3111,1356,2652,3577,3320,3101,1703, 640,1045,1370,1246,
+4996, 371,1575,2436,1621,2210, 984,4033,1734,2638,  16,4529, 663,2755,3255,1451,
+3917,2257,1253,1955,2234,1263,2951, 214,1229, 617, 485, 359,1831,1969, 473,2310,
+ 750,2058, 165,  80,2864,2419, 361,4344,2416,2479,1134, 796,3726,1266,2943, 860,
+2715, 938, 390,2734,1313,1384, 248, 202, 877,1064,2854, 522,3907, 279,1602, 297,
+2357, 395,3740, 137,2075, 944,4089,2584,1267,3802,  62,1533,2285, 178, 176, 780,
+2440, 201,3707, 590, 478,1560,4354,2117,1075,  30,  74,4643,4004,1635,1441,2745,
+ 776,2596, 238,1077,1692,1912,2844, 605, 499,1742,3947, 241,3053, 980,1749, 936,
+2640,4511,2582, 515,1543,2162,5322,2892,2993, 890,2148,1924, 665,1827,3581,1032,
+ 968,3163, 339,1044,1896, 270, 583,1791,1720,4367,1194,3488,3669,  43,2523,1657,
+ 163,2167, 290,1209,1622,3378, 550, 634,2508,2510, 695,2634,2384,2512,1476,1414,
+ 220,1469,2341,2138,2852,3183,2900,4939,2865,3502,1211,3680, 854,3227,1299,2976,
+3172, 186,2998,1459, 443,1067,3251,1495, 321,1932,3054, 909, 753,1410,1828, 436,
+2441,1119,1587,3164,2186,1258, 227, 231,1425,1890,3200,3942, 247, 959, 725,5254,
+2741, 577,2158,2079, 929, 120, 174, 838,2813, 591,1115, 417,2024,  40,3240,1536,
+1037, 291,4151,2354, 632,1298,2406,2500,3535,1825,1846,3451, 205,1171, 345,4238,
+  18,1163, 811, 685,2208,1217, 425,1312,1508,1175,4308,2552,1033, 587,1381,3059,
+2984,3482, 340,1316,4023,3972, 792,3176, 519, 777,4690, 918, 933,4130,2981,3741,
+  90,3360,2911,2200,5184,4550, 609,3079,2030, 272,3379,2736, 363,3881,1130,1447,
+ 286, 779, 357,1169,3350,3137,1630,1220,2687,2391, 747,1277,3688,2618,2682,2601,
+1156,3196,5290,4034,3102,1689,3596,3128, 874, 219,2783, 798, 508,1843,2461, 269,
+1658,1776,1392,1913,2983,3287,2866,2159,2372, 829,4076,  46,4253,2873,1889,1894,
+ 915,1834,1631,2181,2318, 298, 664,2818,3555,2735, 954,3228,3117, 527,3511,2173,
+ 681,2712,3033,2247,2346,3467,1652, 155,2164,3382, 113,1994, 450, 899, 494, 994,
+1237,2958,1875,2336,1926,3727, 545,1577,1550, 633,3473, 204,1305,3072,2410,1956,
+2471, 707,2134, 841,2195,2196,2663,3843,1026,4940, 990,3252,4997, 368,1092, 437,
+3212,3258,1933,1829, 675,2977,2893, 412, 943,3723,4644,3294,3283,2230,2373,5154,
+2389,2241,2661,2323,1404,2524, 593, 787, 677,3008,1275,2059, 438,2709,2609,2240,
+2269,2246,1446,  36,1568,1373,3892,1574,2301,1456,3962, 693,2276,5216,2035,1143,
+2720,1919,1797,1811,2763,4137,2597,1830,1699,1488,1198,2090, 424,1694, 312,3634,
+3390,4179,3335,2252,1214, 561,1059,3243,2295,2561, 975,5155,2321,2751,3772, 472,
+1537,3282,3398,1047,2077,2348,2878,1323,3340,3076, 690,2906,  51, 369, 170,3541,
+1060,2187,2688,3670,2541,1083,1683, 928,3918, 459, 109,4427, 599,3744,4286, 143,
+2101,2730,2490,  82,1588,3036,2121, 281,1860, 477,4035,1238,2812,3020,2716,3312,
+1530,2188,2055,1317, 843, 636,1808,1173,3495, 649, 181,1002, 147,3641,1159,2414,
+3750,2289,2795, 813,3123,2610,1136,4368,   5,3391,4541,2174, 420, 429,1728, 754,
+1228,2115,2219, 347,2223,2733, 735,1518,3003,2355,3134,1764,3948,3329,1888,2424,
+1001,1234,1972,3321,3363,1672,1021,1450,1584, 226, 765, 655,2526,3404,3244,2302,
+3665, 731, 594,2184, 319,1576, 621, 658,2656,4299,2099,3864,1279,2071,2598,2739,
+ 795,3086,3699,3908,1707,2352,2402,1382,3136,2475,1465,4847,3496,3865,1085,3004,
+2591,1084, 213,2287,1963,3565,2250, 822, 793,4574,3187,1772,1789,3050, 595,1484,
+1959,2770,1080,2650, 456, 422,2996, 940,3322,4328,4345,3092,2742, 965,2784, 739,
+4124, 952,1358,2498,2949,2565, 332,2698,2378, 660,2260,2473,4194,3856,2919, 535,
+1260,2651,1208,1428,1300,1949,1303,2942, 433,2455,2450,1251,1946, 614,1269, 641,
+1306,1810,2737,3078,2912, 564,2365,1419,1415,1497,4460,2367,2185,1379,3005,1307,
+3218,2175,1897,3063, 682,1157,4040,4005,1712,1160,1941,1399, 394, 402,2952,1573,
+1151,2986,2404, 862, 299,2033,1489,3006, 346, 171,2886,3401,1726,2932, 168,2533,
+  47,2507,1030,3735,1145,3370,1395,1318,1579,3609,4560,2857,4116,1457,2529,1965,
+ 504,1036,2690,2988,2405, 745,5871, 849,2397,2056,3081, 863,2359,3857,2096,  99,
+1397,1769,2300,4428,1643,3455,1978,1757,3718,1440,  35,4879,3742,1296,4228,2280,
+ 160,5063,1599,2013, 166, 520,3479,1646,3345,3012, 490,1937,1545,1264,2182,2505,
+1096,1188,1369,1436,2421,1667,2792,2460,1270,2122, 727,3167,2143, 806,1706,1012,
+1800,3037, 960,2218,1882, 805, 139,2456,1139,1521, 851,1052,3093,3089, 342,2039,
+ 744,5097,1468,1502,1585,2087, 223, 939, 326,2140,2577, 892,2481,1623,4077, 982,
+3708, 135,2131,  87,2503,3114,2326,1106, 876,1616, 547,2997,2831,2093,3441,4530,
+4314,   9,3256,4229,4148, 659,1462,1986,1710,2046,2913,2231,4090,4880,5255,3392,
+3274,1368,3689,4645,1477, 705,3384,3635,1068,1529,2941,1458,3782,1509, 100,1656,
+2548, 718,2339, 408,1590,2780,3548,1838,4117,3719,1345,3530, 717,3442,2778,3220,
+2898,1892,4590,3614,3371,2043,1998,1224,3483, 891, 635, 584,2559,3355, 733,1766,
+1729,1172,3789,1891,2307, 781,2982,2271,1957,1580,5773,2633,2005,4195,3097,1535,
+3213,1189,1934,5693,3262, 586,3118,1324,1598, 517,1564,2217,1868,1893,4445,3728,
+2703,3139,1526,1787,1992,3882,2875,1549,1199,1056,2224,1904,2711,5098,4287, 338,
+1993,3129,3489,2689,1809,2815,1997, 957,1855,3898,2550,3275,3057,1105,1319, 627,
+1505,1911,1883,3526, 698,3629,3456,1833,1431, 746,  77,1261,2017,2296,1977,1885,
+ 125,1334,1600, 525,1798,1109,2222,1470,1945, 559,2236,1186,3443,2476,1929,1411,
+2411,3135,1777,3372,2621,1841,1613,3229, 668,1430,1839,2643,2916, 195,1989,2671,
+2358,1387, 629,3205,2293,5256,4439, 123,1310, 888,1879,4300,3021,3605,1003,1162,
+3192,2910,2010, 140,2395,2859,  55,1082,2012,2901, 662, 419,2081,1438, 680,2774,
+4654,3912,1620,1731,1625,5035,4065,2328, 512,1344, 802,5443,2163,2311,2537, 524,
+3399,  98,1155,2103,1918,2606,3925,2816,1393,2465,1504,3773,2177,3963,1478,4346,
+ 180,1113,4655,3461,2028,1698, 833,2696,1235,1322,1594,4408,3623,3013,3225,2040,
+3022, 541,2881, 607,3632,2029,1665,1219, 639,1385,1686,1099,2803,3231,1938,3188,
+2858, 427, 676,2772,1168,2025, 454,3253,2486,3556, 230,1950, 580, 791,1991,1280,
+1086,1974,2034, 630, 257,3338,2788,4903,1017,  86,4790, 966,2789,1995,1696,1131,
+ 259,3095,4188,1308, 179,1463,5257, 289,4107,1248,  42,3413,1725,2288, 896,1947,
+ 774,4474,4254, 604,3430,4264, 392,2514,2588, 452, 237,1408,3018, 988,4531,1970,
+3034,3310, 540,2370,1562,1288,2990, 502,4765,1147,   4,1853,2708, 207, 294,2814,
+4078,2902,2509, 684,  34,3105,3532,2551, 644, 709,2801,2344, 573,1727,3573,3557,
+2021,1081,3100,4315,2100,3681, 199,2263,1837,2385, 146,3484,1195,2776,3949, 997,
+1939,3973,1008,1091,1202,1962,1847,1149,4209,5444,1076, 493, 117,5400,2521, 972,
+1490,2934,1796,4542,2374,1512,2933,2657, 413,2888,1135,2762,2314,2156,1355,2369,
+ 766,2007,2527,2170,3124,2491,2593,2632,4757,2437, 234,3125,3591,1898,1750,1376,
+1942,3468,3138, 570,2127,2145,3276,4131, 962, 132,1445,4196,  19, 941,3624,3480,
+3366,1973,1374,4461,3431,2629, 283,2415,2275, 808,2887,3620,2112,2563,1353,3610,
+ 955,1089,3103,1053,  96,  88,4097, 823,3808,1583, 399, 292,4091,3313, 421,1128,
+ 642,4006, 903,2539,1877,2082, 596,  29,4066,1790, 722,2157, 130, 995,1569, 769,
+1485, 464, 513,2213, 288,1923,1101,2453,4316, 133, 486,2445,  50, 625, 487,2207,
+  57, 423, 481,2962, 159,3729,1558, 491, 303, 482, 501, 240,2837, 112,3648,2392,
+1783, 362,   8,3433,3422, 610,2793,3277,1390,1284,1654,  21,3823, 734, 367, 623,
+ 193, 287, 374,1009,1483, 816, 476, 313,2255,2340,1262,2150,2899,1146,2581, 782,
+2116,1659,2018,1880, 255,3586,3314,1110,2867,2137,2564, 986,2767,5185,2006, 650,
+ 158, 926, 762, 881,3157,2717,2362,3587, 306,3690,3245,1542,3077,2427,1691,2478,
+2118,2985,3490,2438, 539,2305, 983, 129,1754, 355,4201,2386, 827,2923, 104,1773,
+2838,2771, 411,2905,3919, 376, 767, 122,1114, 828,2422,1817,3506, 266,3460,1007,
+1609,4998, 945,2612,4429,2274, 726,1247,1964,2914,2199,2070,4002,4108, 657,3323,
+1422, 579, 455,2764,4737,1222,2895,1670, 824,1223,1487,2525, 558, 861,3080, 598,
+2659,2515,1967, 752,2583,2376,2214,4180, 977, 704,2464,4999,2622,4109,1210,2961,
+ 819,1541, 142,2284,  44, 418, 457,1126,3730,4347,4626,1644,1876,3671,1864, 302,
+1063,5694, 624, 723,1984,3745,1314,1676,2488,1610,1449,3558,3569,2166,2098, 409,
+1011,2325,3704,2306, 818,1732,1383,1824,1844,3757, 999,2705,3497,1216,1423,2683,
+2426,2954,2501,2726,2229,1475,2554,5064,1971,1794,1666,2014,1343, 783, 724, 191,
+2434,1354,2220,5065,1763,2752,2472,4152, 131, 175,2885,3434,  92,1466,4920,2616,
+3871,3872,3866, 128,1551,1632, 669,1854,3682,4691,4125,1230, 188,2973,3290,1302,
+1213, 560,3266, 917, 763,3909,3249,1760, 868,1958, 764,1782,2097, 145,2277,3774,
+4462,  64,1491,3062, 971,2132,3606,2442, 221,1226,1617, 218, 323,1185,3207,3147,
+ 571, 619,1473,1005,1744,2281, 449,1887,2396,3685, 275, 375,3816,1743,3844,3731,
+ 845,1983,2350,4210,1377, 773, 967,3499,3052,3743,2725,4007,1697,1022,3943,1464,
+3264,2855,2722,1952,1029,2839,2467,  84,4383,2215, 820,1391,2015,2448,3672, 377,
+1948,2168, 797,2545,3536,2578,2645,  94,2874,1678, 405,1259,3071, 771, 546,1315,
+ 470,1243,3083, 895,2468, 981, 969,2037, 846,4181, 653,1276,2928,  14,2594, 557,
+3007,2474, 156, 902,1338,1740,2574, 537,2518, 973,2282,2216,2433,1928, 138,2903,
+1293,2631,1612, 646,3457, 839,2935, 111, 496,2191,2847, 589,3186, 149,3994,2060,
+4031,2641,4067,3145,1870,  37,3597,2136,1025,2051,3009,3383,3549,1121,1016,3261,
+1301, 251,2446,2599,2153, 872,3246, 637, 334,3705, 831, 884, 921,3065,3140,4092,
+2198,1944, 246,2964, 108,2045,1152,1921,2308,1031, 203,3173,4170,1907,3890, 810,
+1401,2003,1690, 506, 647,1242,2828,1761,1649,3208,2249,1589,3709,2931,5156,1708,
+ 498, 666,2613, 834,3817,1231, 184,2851,1124, 883,3197,2261,3710,1765,1553,2658,
+1178,2639,2351,  93,1193, 942,2538,2141,4402, 235,1821, 870,1591,2192,1709,1871,
+3341,1618,4126,2595,2334, 603, 651,  69, 701, 268,2662,3411,2555,1380,1606, 503,
+ 448, 254,2371,2646, 574,1187,2309,1770, 322,2235,1292,1801, 305, 566,1133, 229,
+2067,2057, 706, 167, 483,2002,2672,3295,1820,3561,3067, 316, 378,2746,3452,1112,
+ 136,1981, 507,1651,2917,1117, 285,4591, 182,2580,3522,1304, 335,3303,1835,2504,
+1795,1792,2248, 674,1018,2106,2449,1857,2292,2845, 976,3047,1781,2600,2727,1389,
+1281,  52,3152, 153, 265,3950, 672,3485,3951,4463, 430,1183, 365, 278,2169,  27,
+1407,1336,2304, 209,1340,1730,2202,1852,2403,2883, 979,1737,1062, 631,2829,2542,
+3876,2592, 825,2086,2226,3048,3625, 352,1417,3724, 542, 991, 431,1351,3938,1861,
+2294, 826,1361,2927,3142,3503,1738, 463,2462,2723, 582,1916,1595,2808, 400,3845,
+3891,2868,3621,2254,  58,2492,1123, 910,2160,2614,1372,1603,1196,1072,3385,1700,
+3267,1980, 696, 480,2430, 920, 799,1570,2920,1951,2041,4047,2540,1321,4223,2469,
+3562,2228,1271,2602, 401,2833,3351,2575,5157, 907,2312,1256, 410, 263,3507,1582,
+ 996, 678,1849,2316,1480, 908,3545,2237, 703,2322, 667,1826,2849,1531,2604,2999,
+2407,3146,2151,2630,1786,3711, 469,3542, 497,3899,2409, 858, 837,4446,3393,1274,
+ 786, 620,1845,2001,3311, 484, 308,3367,1204,1815,3691,2332,1532,2557,1842,2020,
+2724,1927,2333,4440, 567,  22,1673,2728,4475,1987,1858,1144,1597, 101,1832,3601,
+  12, 974,3783,4391, 951,1412,   1,3720, 453,4608,4041, 528,1041,1027,3230,2628,
+1129, 875,1051,3291,1203,2262,1069,2860,2799,2149,2615,3278, 144,1758,3040,  31,
+ 475,1680, 366,2685,3184, 311,1642,4008,2466,5036,1593,1493,2809, 216,1420,1668,
+ 233, 304,2128,3284, 232,1429,1768,1040,2008,3407,2740,2967,2543, 242,2133, 778,
+1565,2022,2620, 505,2189,2756,1098,2273, 372,1614, 708, 553,2846,2094,2278, 169,
+3626,2835,4161, 228,2674,3165, 809,1454,1309, 466,1705,1095, 900,3423, 880,2667,
+3751,5258,2317,3109,2571,4317,2766,1503,1342, 866,4447,1118,  63,2076, 314,1881,
+1348,1061, 172, 978,3515,1747, 532, 511,3970,   6, 601, 905,2699,3300,1751, 276,
+1467,3725,2668,  65,4239,2544,2779,2556,1604, 578,2451,1802, 992,2331,2624,1320,
+3446, 713,1513,1013, 103,2786,2447,1661, 886,1702, 916, 654,3574,2031,1556, 751,
+2178,2821,2179,1498,1538,2176, 271, 914,2251,2080,1325, 638,1953,2937,3877,2432,
+2754,  95,3265,1716, 260,1227,4083, 775, 106,1357,3254, 426,1607, 555,2480, 772,
+1985, 244,2546, 474, 495,1046,2611,1851,2061,  71,2089,1675,2590, 742,3758,2843,
+3222,1433, 267,2180,2576,2826,2233,2092,3913,2435, 956,1745,3075, 856,2113,1116,
+ 451,   3,1988,2896,1398, 993,2463,1878,2049,1341,2718,2721,2870,2108, 712,2904,
+4363,2753,2324, 277,2872,2349,2649, 384, 987, 435, 691,3000, 922, 164,3939, 652,
+1500,1184,4153,2482,3373,2165,4848,2335,3775,3508,3154,2806,2830,1554,2102,1664,
+2530,1434,2408, 893,1547,2623,3447,2832,2242,2532,3169,2856,3223,2078,  49,3770,
+3469, 462, 318, 656,2259,3250,3069, 679,1629,2758, 344,1138,1104,3120,1836,1283,
+3115,2154,1437,4448, 934, 759,1999, 794,2862,1038, 533,2560,1722,2342, 855,2626,
+1197,1663,4476,3127,  85,4240,2528,  25,1111,1181,3673, 407,3470,4561,2679,2713,
+ 768,1925,2841,3986,1544,1165, 932, 373,1240,2146,1930,2673, 721,4766, 354,4333,
+ 391,2963, 187,  61,3364,1442,1102, 330,1940,1767, 341,3809,4118, 393,2496,2062,
+2211, 105, 331, 300, 439, 913,1332, 626, 379,3304,1557, 328, 689,3952, 309,1555,
+ 931, 317,2517,3027, 325, 569, 686,2107,3084,  60,1042,1333,2794, 264,3177,4014,
+1628, 258,3712,   7,4464,1176,1043,1778, 683, 114,1975,  78,1492, 383,1886, 510,
+ 386, 645,5291,2891,2069,3305,4138,3867,2939,2603,2493,1935,1066,1848,3588,1015,
+1282,1289,4609, 697,1453,3044,2666,3611,1856,2412,  54, 719,1330, 568,3778,2459,
+1748, 788, 492, 551,1191,1000, 488,3394,3763, 282,1799, 348,2016,1523,3155,2390,
+1049, 382,2019,1788,1170, 729,2968,3523, 897,3926,2785,2938,3292, 350,2319,3238,
+1718,1717,2655,3453,3143,4465, 161,2889,2980,2009,1421,  56,1908,1640,2387,2232,
+1917,1874,2477,4921, 148,  83,3438, 592,4245,2882,1822,1055, 741, 115,1496,1624,
+ 381,1638,4592,1020, 516,3214, 458, 947,4575,1432, 211,1514,2926,1865,2142, 189,
+ 852,1221,1400,1486, 882,2299,4036, 351,  28,1122, 700,6479,6480,6481,6482,6483,  #last 512
+)
+# fmt: on
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/gb2312prober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/gb2312prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..d423e7311e2fbd9a014de808c107e96ad11c66e5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/gb2312prober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import GB2312DistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import GB2312_SM_MODEL
+
+
+class GB2312Prober(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(GB2312_SM_MODEL)
+        self.distribution_analyzer = GB2312DistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "GB2312"
+
+    @property
+    def language(self) -> str:
+        return "Chinese"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/hebrewprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/hebrewprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..785d0057bcc0ea74a4b8d65ab7a0de78474bf892
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/hebrewprober.py
@@ -0,0 +1,316 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+#          Shy Shalom
+# Portions created by the Initial Developer are Copyright (C) 2005
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+from .sbcharsetprober import SingleByteCharSetProber
+
+# This prober doesn't actually recognize a language or a charset.
+# It is a helper prober for the use of the Hebrew model probers
+
+### General ideas of the Hebrew charset recognition ###
+#
+# Four main charsets exist in Hebrew:
+# "ISO-8859-8" - Visual Hebrew
+# "windows-1255" - Logical Hebrew
+# "ISO-8859-8-I" - Logical Hebrew
+# "x-mac-hebrew" - ?? Logical Hebrew ??
+#
+# Both "ISO" charsets use a completely identical set of code points, whereas
+# "windows-1255" and "x-mac-hebrew" are two different proper supersets of
+# these code points. windows-1255 defines additional characters in the range
+# 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific
+# diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6.
+# x-mac-hebrew defines similar additional code points but with a different
+# mapping.
+#
+# As far as an average Hebrew text with no diacritics is concerned, all four
+# charsets are identical with respect to code points. Meaning that for the
+# main Hebrew alphabet, all four map the same values to all 27 Hebrew letters
+# (including final letters).
+#
+# The dominant difference between these charsets is their directionality.
+# "Visual" directionality means that the text is ordered as if the renderer is
+# not aware of a BIDI rendering algorithm. The renderer sees the text and
+# draws it from left to right. The text itself when ordered naturally is read
+# backwards. A buffer of Visual Hebrew generally looks like so:
+# "[last word of first line spelled backwards] [whole line ordered backwards
+# and spelled backwards] [first word of first line spelled backwards]
+# [end of line] [last word of second line] ... etc' "
+# adding punctuation marks, numbers and English text to visual text is
+# naturally also "visual" and from left to right.
+#
+# "Logical" directionality means the text is ordered "naturally" according to
+# the order it is read. It is the responsibility of the renderer to display
+# the text from right to left. A BIDI algorithm is used to place general
+# punctuation marks, numbers and English text in the text.
+#
+# Texts in x-mac-hebrew are almost impossible to find on the Internet. From
+# what little evidence I could find, it seems that its general directionality
+# is Logical.
+#
+# To sum up all of the above, the Hebrew probing mechanism knows about two
+# charsets:
+# Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are
+#    backwards while line order is natural. For charset recognition purposes
+#    the line order is unimportant (In fact, for this implementation, even
+#    word order is unimportant).
+# Logical Hebrew - "windows-1255" - normal, naturally ordered text.
+#
+# "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be
+#    specifically identified.
+# "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew
+#    that contain special punctuation marks or diacritics is displayed with
+#    some unconverted characters showing as question marks. This problem might
+#    be corrected using another model prober for x-mac-hebrew. Due to the fact
+#    that x-mac-hebrew texts are so rare, writing another model prober isn't
+#    worth the effort and performance hit.
+#
+#### The Prober ####
+#
+# The prober is divided between two SBCharSetProbers and a HebrewProber,
+# all of which are managed, created, fed data, inquired and deleted by the
+# SBCSGroupProber. The two SBCharSetProbers identify that the text is in
+# fact some kind of Hebrew, Logical or Visual. The final decision about which
+# one is it is made by the HebrewProber by combining final-letter scores
+# with the scores of the two SBCharSetProbers to produce a final answer.
+#
+# The SBCSGroupProber is responsible for stripping the original text of HTML
+# tags, English characters, numbers, low-ASCII punctuation characters, spaces
+# and new lines. It reduces any sequence of such characters to a single space.
+# The buffer fed to each prober in the SBCS group prober is pure text in
+# high-ASCII.
+# The two SBCharSetProbers (model probers) share the same language model:
+# Win1255Model.
+# The first SBCharSetProber uses the model normally as any other
+# SBCharSetProber does, to recognize windows-1255, upon which this model was
+# built. The second SBCharSetProber is told to make the pair-of-letter
+# lookup in the language model backwards. This in practice exactly simulates
+# a visual Hebrew model using the windows-1255 logical Hebrew model.
+#
+# The HebrewProber is not using any language model. All it does is look for
+# final-letter evidence suggesting the text is either logical Hebrew or visual
+# Hebrew. Disjointed from the model probers, the results of the HebrewProber
+# alone are meaningless. HebrewProber always returns 0.00 as confidence
+# since it never identifies a charset by itself. Instead, the pointer to the
+# HebrewProber is passed to the model probers as a helper "Name Prober".
+# When the Group prober receives a positive identification from any prober,
+# it asks for the name of the charset identified. If the prober queried is a
+# Hebrew model prober, the model prober forwards the call to the
+# HebrewProber to make the final decision. In the HebrewProber, the
+# decision is made according to the final-letters scores maintained and Both
+# model probers scores. The answer is returned in the form of the name of the
+# charset identified, either "windows-1255" or "ISO-8859-8".
+
+
+class HebrewProber(CharSetProber):
+    SPACE = 0x20
+    # windows-1255 / ISO-8859-8 code points of interest
+    FINAL_KAF = 0xEA
+    NORMAL_KAF = 0xEB
+    FINAL_MEM = 0xED
+    NORMAL_MEM = 0xEE
+    FINAL_NUN = 0xEF
+    NORMAL_NUN = 0xF0
+    FINAL_PE = 0xF3
+    NORMAL_PE = 0xF4
+    FINAL_TSADI = 0xF5
+    NORMAL_TSADI = 0xF6
+
+    # Minimum Visual vs Logical final letter score difference.
+    # If the difference is below this, don't rely solely on the final letter score
+    # distance.
+    MIN_FINAL_CHAR_DISTANCE = 5
+
+    # Minimum Visual vs Logical model score difference.
+    # If the difference is below this, don't rely at all on the model score
+    # distance.
+    MIN_MODEL_DISTANCE = 0.01
+
+    VISUAL_HEBREW_NAME = "ISO-8859-8"
+    LOGICAL_HEBREW_NAME = "windows-1255"
+
+    def __init__(self) -> None:
+        super().__init__()
+        self._final_char_logical_score = 0
+        self._final_char_visual_score = 0
+        self._prev = self.SPACE
+        self._before_prev = self.SPACE
+        self._logical_prober: Optional[SingleByteCharSetProber] = None
+        self._visual_prober: Optional[SingleByteCharSetProber] = None
+        self.reset()
+
+    def reset(self) -> None:
+        self._final_char_logical_score = 0
+        self._final_char_visual_score = 0
+        # The two last characters seen in the previous buffer,
+        # mPrev and mBeforePrev are initialized to space in order to simulate
+        # a word delimiter at the beginning of the data
+        self._prev = self.SPACE
+        self._before_prev = self.SPACE
+        # These probers are owned by the group prober.
+
+    def set_model_probers(
+        self,
+        logical_prober: SingleByteCharSetProber,
+        visual_prober: SingleByteCharSetProber,
+    ) -> None:
+        self._logical_prober = logical_prober
+        self._visual_prober = visual_prober
+
+    def is_final(self, c: int) -> bool:
+        return c in [
+            self.FINAL_KAF,
+            self.FINAL_MEM,
+            self.FINAL_NUN,
+            self.FINAL_PE,
+            self.FINAL_TSADI,
+        ]
+
+    def is_non_final(self, c: int) -> bool:
+        # The normal Tsadi is not a good Non-Final letter due to words like
+        # 'lechotet' (to chat) containing an apostrophe after the tsadi. This
+        # apostrophe is converted to a space in FilterWithoutEnglishLetters
+        # causing the Non-Final tsadi to appear at an end of a word even
+        # though this is not the case in the original text.
+        # The letters Pe and Kaf rarely display a related behavior of not being
+        # a good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak'
+        # for example legally end with a Non-Final Pe or Kaf. However, the
+        # benefit of these letters as Non-Final letters outweighs the damage
+        # since these words are quite rare.
+        return c in [self.NORMAL_KAF, self.NORMAL_MEM, self.NORMAL_NUN, self.NORMAL_PE]
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        # Final letter analysis for logical-visual decision.
+        # Look for evidence that the received buffer is either logical Hebrew
+        # or visual Hebrew.
+        # The following cases are checked:
+        # 1) A word longer than 1 letter, ending with a final letter. This is
+        #    an indication that the text is laid out "naturally" since the
+        #    final letter really appears at the end. +1 for logical score.
+        # 2) A word longer than 1 letter, ending with a Non-Final letter. In
+        #    normal Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi,
+        #    should not end with the Non-Final form of that letter. Exceptions
+        #    to this rule are mentioned above in isNonFinal(). This is an
+        #    indication that the text is laid out backwards. +1 for visual
+        #    score
+        # 3) A word longer than 1 letter, starting with a final letter. Final
+        #    letters should not appear at the beginning of a word. This is an
+        #    indication that the text is laid out backwards. +1 for visual
+        #    score.
+        #
+        # The visual score and logical score are accumulated throughout the
+        # text and are finally checked against each other in GetCharSetName().
+        # No checking for final letters in the middle of words is done since
+        # that case is not an indication for either Logical or Visual text.
+        #
+        # We automatically filter out all 7-bit characters (replace them with
+        # spaces) so the word boundary detection works properly. [MAP]
+
+        if self.state == ProbingState.NOT_ME:
+            # Both model probers say it's not them. No reason to continue.
+            return ProbingState.NOT_ME
+
+        byte_str = self.filter_high_byte_only(byte_str)
+
+        for cur in byte_str:
+            if cur == self.SPACE:
+                # We stand on a space - a word just ended
+                if self._before_prev != self.SPACE:
+                    # next-to-last char was not a space so self._prev is not a
+                    # 1 letter word
+                    if self.is_final(self._prev):
+                        # case (1) [-2:not space][-1:final letter][cur:space]
+                        self._final_char_logical_score += 1
+                    elif self.is_non_final(self._prev):
+                        # case (2) [-2:not space][-1:Non-Final letter][
+                        #  cur:space]
+                        self._final_char_visual_score += 1
+            else:
+                # Not standing on a space
+                if (
+                    (self._before_prev == self.SPACE)
+                    and (self.is_final(self._prev))
+                    and (cur != self.SPACE)
+                ):
+                    # case (3) [-2:space][-1:final letter][cur:not space]
+                    self._final_char_visual_score += 1
+            self._before_prev = self._prev
+            self._prev = cur
+
+        # Forever detecting, till the end or until both model probers return
+        # ProbingState.NOT_ME (handled above)
+        return ProbingState.DETECTING
+
+    @property
+    def charset_name(self) -> str:
+        assert self._logical_prober is not None
+        assert self._visual_prober is not None
+
+        # Make the decision: is it Logical or Visual?
+        # If the final letter score distance is dominant enough, rely on it.
+        finalsub = self._final_char_logical_score - self._final_char_visual_score
+        if finalsub >= self.MIN_FINAL_CHAR_DISTANCE:
+            return self.LOGICAL_HEBREW_NAME
+        if finalsub <= -self.MIN_FINAL_CHAR_DISTANCE:
+            return self.VISUAL_HEBREW_NAME
+
+        # It's not dominant enough, try to rely on the model scores instead.
+        modelsub = (
+            self._logical_prober.get_confidence() - self._visual_prober.get_confidence()
+        )
+        if modelsub > self.MIN_MODEL_DISTANCE:
+            return self.LOGICAL_HEBREW_NAME
+        if modelsub < -self.MIN_MODEL_DISTANCE:
+            return self.VISUAL_HEBREW_NAME
+
+        # Still no good, back to final letter distance, maybe it'll save the
+        # day.
+        if finalsub < 0.0:
+            return self.VISUAL_HEBREW_NAME
+
+        # (finalsub > 0 - Logical) or (don't know what to do) default to
+        # Logical.
+        return self.LOGICAL_HEBREW_NAME
+
+    @property
+    def language(self) -> str:
+        return "Hebrew"
+
+    @property
+    def state(self) -> ProbingState:
+        assert self._logical_prober is not None
+        assert self._visual_prober is not None
+
+        # Remain active as long as any of the model probers are active.
+        if (self._logical_prober.state == ProbingState.NOT_ME) and (
+            self._visual_prober.state == ProbingState.NOT_ME
+        ):
+            return ProbingState.NOT_ME
+        return ProbingState.DETECTING
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/jisfreq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/jisfreq.py
new file mode 100644
index 0000000000000000000000000000000000000000..3293576e012a1c931b5e89ebc065c67b65941084
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/jisfreq.py
@@ -0,0 +1,325 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# Sampling from about 20M text materials include literature and computer technology
+#
+# Japanese frequency table, applied to both S-JIS and EUC-JP
+# They are sorted in order.
+
+# 128  --> 0.77094
+# 256  --> 0.85710
+# 512  --> 0.92635
+# 1024 --> 0.97130
+# 2048 --> 0.99431
+#
+# Ideal Distribution Ratio = 0.92635 / (1-0.92635) = 12.58
+# Random Distribution Ration = 512 / (2965+62+83+86-512) = 0.191
+#
+# Typical Distribution Ratio, 25% of IDR
+
+JIS_TYPICAL_DISTRIBUTION_RATIO = 3.0
+
+# Char to FreqOrder table ,
+JIS_TABLE_SIZE = 4368
+
+# fmt: off
+JIS_CHAR_TO_FREQ_ORDER = (
+  40,   1,   6, 182, 152, 180, 295,2127, 285, 381,3295,4304,3068,4606,3165,3510, #   16
+3511,1822,2785,4607,1193,2226,5070,4608, 171,2996,1247,  18, 179,5071, 856,1661, #   32
+1262,5072, 619, 127,3431,3512,3230,1899,1700, 232, 228,1294,1298, 284, 283,2041, #   48
+2042,1061,1062,  48,  49,  44,  45, 433, 434,1040,1041, 996, 787,2997,1255,4305, #   64
+2108,4609,1684,1648,5073,5074,5075,5076,5077,5078,3687,5079,4610,5080,3927,3928, #   80
+5081,3296,3432, 290,2285,1471,2187,5082,2580,2825,1303,2140,1739,1445,2691,3375, #   96
+1691,3297,4306,4307,4611, 452,3376,1182,2713,3688,3069,4308,5083,5084,5085,5086, #  112
+5087,5088,5089,5090,5091,5092,5093,5094,5095,5096,5097,5098,5099,5100,5101,5102, #  128
+5103,5104,5105,5106,5107,5108,5109,5110,5111,5112,4097,5113,5114,5115,5116,5117, #  144
+5118,5119,5120,5121,5122,5123,5124,5125,5126,5127,5128,5129,5130,5131,5132,5133, #  160
+5134,5135,5136,5137,5138,5139,5140,5141,5142,5143,5144,5145,5146,5147,5148,5149, #  176
+5150,5151,5152,4612,5153,5154,5155,5156,5157,5158,5159,5160,5161,5162,5163,5164, #  192
+5165,5166,5167,5168,5169,5170,5171,5172,5173,5174,5175,1472, 598, 618, 820,1205, #  208
+1309,1412,1858,1307,1692,5176,5177,5178,5179,5180,5181,5182,1142,1452,1234,1172, #  224
+1875,2043,2149,1793,1382,2973, 925,2404,1067,1241, 960,1377,2935,1491, 919,1217, #  240
+1865,2030,1406,1499,2749,4098,5183,5184,5185,5186,5187,5188,2561,4099,3117,1804, #  256
+2049,3689,4309,3513,1663,5189,3166,3118,3298,1587,1561,3433,5190,3119,1625,2998, #  272
+3299,4613,1766,3690,2786,4614,5191,5192,5193,5194,2161,  26,3377,   2,3929,  20, #  288
+3691,  47,4100,  50,  17,  16,  35, 268,  27, 243,  42, 155,  24, 154,  29, 184, #  304
+   4,  91,  14,  92,  53, 396,  33, 289,   9,  37,  64, 620,  21,  39, 321,   5, #  320
+  12,  11,  52,  13,   3, 208, 138,   0,   7,  60, 526, 141, 151,1069, 181, 275, #  336
+1591,  83, 132,1475, 126, 331, 829,  15,  69, 160,  59,  22, 157,  55,1079, 312, #  352
+ 109,  38,  23,  25,  10,  19,  79,5195,  61, 382,1124,   8,  30,5196,5197,5198, #  368
+5199,5200,5201,5202,5203,5204,5205,5206,  89,  62,  74,  34,2416, 112, 139, 196, #  384
+ 271, 149,  84, 607, 131, 765,  46,  88, 153, 683,  76, 874, 101, 258,  57,  80, #  400
+  32, 364, 121,1508, 169,1547,  68, 235, 145,2999,  41, 360,3027,  70,  63,  31, #  416
+  43, 259, 262,1383,  99, 533, 194,  66,  93, 846, 217, 192,  56, 106,  58, 565, #  432
+ 280, 272, 311, 256, 146,  82, 308,  71, 100, 128, 214, 655, 110, 261, 104,1140, #  448
+  54,  51,  36,  87,  67,3070, 185,2618,2936,2020,  28,1066,2390,2059,5207,5208, #  464
+5209,5210,5211,5212,5213,5214,5215,5216,4615,5217,5218,5219,5220,5221,5222,5223, #  480
+5224,5225,5226,5227,5228,5229,5230,5231,5232,5233,5234,5235,5236,3514,5237,5238, #  496
+5239,5240,5241,5242,5243,5244,2297,2031,4616,4310,3692,5245,3071,5246,3598,5247, #  512
+4617,3231,3515,5248,4101,4311,4618,3808,4312,4102,5249,4103,4104,3599,5250,5251, #  528
+5252,5253,5254,5255,5256,5257,5258,5259,5260,5261,5262,5263,5264,5265,5266,5267, #  544
+5268,5269,5270,5271,5272,5273,5274,5275,5276,5277,5278,5279,5280,5281,5282,5283, #  560
+5284,5285,5286,5287,5288,5289,5290,5291,5292,5293,5294,5295,5296,5297,5298,5299, #  576
+5300,5301,5302,5303,5304,5305,5306,5307,5308,5309,5310,5311,5312,5313,5314,5315, #  592
+5316,5317,5318,5319,5320,5321,5322,5323,5324,5325,5326,5327,5328,5329,5330,5331, #  608
+5332,5333,5334,5335,5336,5337,5338,5339,5340,5341,5342,5343,5344,5345,5346,5347, #  624
+5348,5349,5350,5351,5352,5353,5354,5355,5356,5357,5358,5359,5360,5361,5362,5363, #  640
+5364,5365,5366,5367,5368,5369,5370,5371,5372,5373,5374,5375,5376,5377,5378,5379, #  656
+5380,5381, 363, 642,2787,2878,2788,2789,2316,3232,2317,3434,2011, 165,1942,3930, #  672
+3931,3932,3933,5382,4619,5383,4620,5384,5385,5386,5387,5388,5389,5390,5391,5392, #  688
+5393,5394,5395,5396,5397,5398,5399,5400,5401,5402,5403,5404,5405,5406,5407,5408, #  704
+5409,5410,5411,5412,5413,5414,5415,5416,5417,5418,5419,5420,5421,5422,5423,5424, #  720
+5425,5426,5427,5428,5429,5430,5431,5432,5433,5434,5435,5436,5437,5438,5439,5440, #  736
+5441,5442,5443,5444,5445,5446,5447,5448,5449,5450,5451,5452,5453,5454,5455,5456, #  752
+5457,5458,5459,5460,5461,5462,5463,5464,5465,5466,5467,5468,5469,5470,5471,5472, #  768
+5473,5474,5475,5476,5477,5478,5479,5480,5481,5482,5483,5484,5485,5486,5487,5488, #  784
+5489,5490,5491,5492,5493,5494,5495,5496,5497,5498,5499,5500,5501,5502,5503,5504, #  800
+5505,5506,5507,5508,5509,5510,5511,5512,5513,5514,5515,5516,5517,5518,5519,5520, #  816
+5521,5522,5523,5524,5525,5526,5527,5528,5529,5530,5531,5532,5533,5534,5535,5536, #  832
+5537,5538,5539,5540,5541,5542,5543,5544,5545,5546,5547,5548,5549,5550,5551,5552, #  848
+5553,5554,5555,5556,5557,5558,5559,5560,5561,5562,5563,5564,5565,5566,5567,5568, #  864
+5569,5570,5571,5572,5573,5574,5575,5576,5577,5578,5579,5580,5581,5582,5583,5584, #  880
+5585,5586,5587,5588,5589,5590,5591,5592,5593,5594,5595,5596,5597,5598,5599,5600, #  896
+5601,5602,5603,5604,5605,5606,5607,5608,5609,5610,5611,5612,5613,5614,5615,5616, #  912
+5617,5618,5619,5620,5621,5622,5623,5624,5625,5626,5627,5628,5629,5630,5631,5632, #  928
+5633,5634,5635,5636,5637,5638,5639,5640,5641,5642,5643,5644,5645,5646,5647,5648, #  944
+5649,5650,5651,5652,5653,5654,5655,5656,5657,5658,5659,5660,5661,5662,5663,5664, #  960
+5665,5666,5667,5668,5669,5670,5671,5672,5673,5674,5675,5676,5677,5678,5679,5680, #  976
+5681,5682,5683,5684,5685,5686,5687,5688,5689,5690,5691,5692,5693,5694,5695,5696, #  992
+5697,5698,5699,5700,5701,5702,5703,5704,5705,5706,5707,5708,5709,5710,5711,5712, # 1008
+5713,5714,5715,5716,5717,5718,5719,5720,5721,5722,5723,5724,5725,5726,5727,5728, # 1024
+5729,5730,5731,5732,5733,5734,5735,5736,5737,5738,5739,5740,5741,5742,5743,5744, # 1040
+5745,5746,5747,5748,5749,5750,5751,5752,5753,5754,5755,5756,5757,5758,5759,5760, # 1056
+5761,5762,5763,5764,5765,5766,5767,5768,5769,5770,5771,5772,5773,5774,5775,5776, # 1072
+5777,5778,5779,5780,5781,5782,5783,5784,5785,5786,5787,5788,5789,5790,5791,5792, # 1088
+5793,5794,5795,5796,5797,5798,5799,5800,5801,5802,5803,5804,5805,5806,5807,5808, # 1104
+5809,5810,5811,5812,5813,5814,5815,5816,5817,5818,5819,5820,5821,5822,5823,5824, # 1120
+5825,5826,5827,5828,5829,5830,5831,5832,5833,5834,5835,5836,5837,5838,5839,5840, # 1136
+5841,5842,5843,5844,5845,5846,5847,5848,5849,5850,5851,5852,5853,5854,5855,5856, # 1152
+5857,5858,5859,5860,5861,5862,5863,5864,5865,5866,5867,5868,5869,5870,5871,5872, # 1168
+5873,5874,5875,5876,5877,5878,5879,5880,5881,5882,5883,5884,5885,5886,5887,5888, # 1184
+5889,5890,5891,5892,5893,5894,5895,5896,5897,5898,5899,5900,5901,5902,5903,5904, # 1200
+5905,5906,5907,5908,5909,5910,5911,5912,5913,5914,5915,5916,5917,5918,5919,5920, # 1216
+5921,5922,5923,5924,5925,5926,5927,5928,5929,5930,5931,5932,5933,5934,5935,5936, # 1232
+5937,5938,5939,5940,5941,5942,5943,5944,5945,5946,5947,5948,5949,5950,5951,5952, # 1248
+5953,5954,5955,5956,5957,5958,5959,5960,5961,5962,5963,5964,5965,5966,5967,5968, # 1264
+5969,5970,5971,5972,5973,5974,5975,5976,5977,5978,5979,5980,5981,5982,5983,5984, # 1280
+5985,5986,5987,5988,5989,5990,5991,5992,5993,5994,5995,5996,5997,5998,5999,6000, # 1296
+6001,6002,6003,6004,6005,6006,6007,6008,6009,6010,6011,6012,6013,6014,6015,6016, # 1312
+6017,6018,6019,6020,6021,6022,6023,6024,6025,6026,6027,6028,6029,6030,6031,6032, # 1328
+6033,6034,6035,6036,6037,6038,6039,6040,6041,6042,6043,6044,6045,6046,6047,6048, # 1344
+6049,6050,6051,6052,6053,6054,6055,6056,6057,6058,6059,6060,6061,6062,6063,6064, # 1360
+6065,6066,6067,6068,6069,6070,6071,6072,6073,6074,6075,6076,6077,6078,6079,6080, # 1376
+6081,6082,6083,6084,6085,6086,6087,6088,6089,6090,6091,6092,6093,6094,6095,6096, # 1392
+6097,6098,6099,6100,6101,6102,6103,6104,6105,6106,6107,6108,6109,6110,6111,6112, # 1408
+6113,6114,2044,2060,4621, 997,1235, 473,1186,4622, 920,3378,6115,6116, 379,1108, # 1424
+4313,2657,2735,3934,6117,3809, 636,3233, 573,1026,3693,3435,2974,3300,2298,4105, # 1440
+ 854,2937,2463, 393,2581,2417, 539, 752,1280,2750,2480, 140,1161, 440, 708,1569, # 1456
+ 665,2497,1746,1291,1523,3000, 164,1603, 847,1331, 537,1997, 486, 508,1693,2418, # 1472
+1970,2227, 878,1220, 299,1030, 969, 652,2751, 624,1137,3301,2619,  65,3302,2045, # 1488
+1761,1859,3120,1930,3694,3516, 663,1767, 852, 835,3695, 269, 767,2826,2339,1305, # 1504
+ 896,1150, 770,1616,6118, 506,1502,2075,1012,2519, 775,2520,2975,2340,2938,4314, # 1520
+3028,2086,1224,1943,2286,6119,3072,4315,2240,1273,1987,3935,1557, 175, 597, 985, # 1536
+3517,2419,2521,1416,3029, 585, 938,1931,1007,1052,1932,1685,6120,3379,4316,4623, # 1552
+ 804, 599,3121,1333,2128,2539,1159,1554,2032,3810, 687,2033,2904, 952, 675,1467, # 1568
+3436,6121,2241,1096,1786,2440,1543,1924, 980,1813,2228, 781,2692,1879, 728,1918, # 1584
+3696,4624, 548,1950,4625,1809,1088,1356,3303,2522,1944, 502, 972, 373, 513,2827, # 1600
+ 586,2377,2391,1003,1976,1631,6122,2464,1084, 648,1776,4626,2141, 324, 962,2012, # 1616
+2177,2076,1384, 742,2178,1448,1173,1810, 222, 102, 301, 445, 125,2420, 662,2498, # 1632
+ 277, 200,1476,1165,1068, 224,2562,1378,1446, 450,1880, 659, 791, 582,4627,2939, # 1648
+3936,1516,1274, 555,2099,3697,1020,1389,1526,3380,1762,1723,1787,2229, 412,2114, # 1664
+1900,2392,3518, 512,2597, 427,1925,2341,3122,1653,1686,2465,2499, 697, 330, 273, # 1680
+ 380,2162, 951, 832, 780, 991,1301,3073, 965,2270,3519, 668,2523,2636,1286, 535, # 1696
+1407, 518, 671, 957,2658,2378, 267, 611,2197,3030,6123, 248,2299, 967,1799,2356, # 1712
+ 850,1418,3437,1876,1256,1480,2828,1718,6124,6125,1755,1664,2405,6126,4628,2879, # 1728
+2829, 499,2179, 676,4629, 557,2329,2214,2090, 325,3234, 464, 811,3001, 992,2342, # 1744
+2481,1232,1469, 303,2242, 466,1070,2163, 603,1777,2091,4630,2752,4631,2714, 322, # 1760
+2659,1964,1768, 481,2188,1463,2330,2857,3600,2092,3031,2421,4632,2318,2070,1849, # 1776
+2598,4633,1302,2254,1668,1701,2422,3811,2905,3032,3123,2046,4106,1763,1694,4634, # 1792
+1604, 943,1724,1454, 917, 868,2215,1169,2940, 552,1145,1800,1228,1823,1955, 316, # 1808
+1080,2510, 361,1807,2830,4107,2660,3381,1346,1423,1134,4108,6127, 541,1263,1229, # 1824
+1148,2540, 545, 465,1833,2880,3438,1901,3074,2482, 816,3937, 713,1788,2500, 122, # 1840
+1575, 195,1451,2501,1111,6128, 859, 374,1225,2243,2483,4317, 390,1033,3439,3075, # 1856
+2524,1687, 266, 793,1440,2599, 946, 779, 802, 507, 897,1081, 528,2189,1292, 711, # 1872
+1866,1725,1167,1640, 753, 398,2661,1053, 246, 348,4318, 137,1024,3440,1600,2077, # 1888
+2129, 825,4319, 698, 238, 521, 187,2300,1157,2423,1641,1605,1464,1610,1097,2541, # 1904
+1260,1436, 759,2255,1814,2150, 705,3235, 409,2563,3304, 561,3033,2005,2564, 726, # 1920
+1956,2343,3698,4109, 949,3812,3813,3520,1669, 653,1379,2525, 881,2198, 632,2256, # 1936
+1027, 778,1074, 733,1957, 514,1481,2466, 554,2180, 702,3938,1606,1017,1398,6129, # 1952
+1380,3521, 921, 993,1313, 594, 449,1489,1617,1166, 768,1426,1360, 495,1794,3601, # 1968
+1177,3602,1170,4320,2344, 476, 425,3167,4635,3168,1424, 401,2662,1171,3382,1998, # 1984
+1089,4110, 477,3169, 474,6130,1909, 596,2831,1842, 494, 693,1051,1028,1207,3076, # 2000
+ 606,2115, 727,2790,1473,1115, 743,3522, 630, 805,1532,4321,2021, 366,1057, 838, # 2016
+ 684,1114,2142,4322,2050,1492,1892,1808,2271,3814,2424,1971,1447,1373,3305,1090, # 2032
+1536,3939,3523,3306,1455,2199, 336, 369,2331,1035, 584,2393, 902, 718,2600,6131, # 2048
+2753, 463,2151,1149,1611,2467, 715,1308,3124,1268, 343,1413,3236,1517,1347,2663, # 2064
+2093,3940,2022,1131,1553,2100,2941,1427,3441,2942,1323,2484,6132,1980, 872,2368, # 2080
+2441,2943, 320,2369,2116,1082, 679,1933,3941,2791,3815, 625,1143,2023, 422,2200, # 2096
+3816,6133, 730,1695, 356,2257,1626,2301,2858,2637,1627,1778, 937, 883,2906,2693, # 2112
+3002,1769,1086, 400,1063,1325,3307,2792,4111,3077, 456,2345,1046, 747,6134,1524, # 2128
+ 884,1094,3383,1474,2164,1059, 974,1688,2181,2258,1047, 345,1665,1187, 358, 875, # 2144
+3170, 305, 660,3524,2190,1334,1135,3171,1540,1649,2542,1527, 927, 968,2793, 885, # 2160
+1972,1850, 482, 500,2638,1218,1109,1085,2543,1654,2034, 876,  78,2287,1482,1277, # 2176
+ 861,1675,1083,1779, 724,2754, 454, 397,1132,1612,2332, 893, 672,1237, 257,2259, # 2192
+2370, 135,3384, 337,2244, 547, 352, 340, 709,2485,1400, 788,1138,2511, 540, 772, # 2208
+1682,2260,2272,2544,2013,1843,1902,4636,1999,1562,2288,4637,2201,1403,1533, 407, # 2224
+ 576,3308,1254,2071, 978,3385, 170, 136,1201,3125,2664,3172,2394, 213, 912, 873, # 2240
+3603,1713,2202, 699,3604,3699, 813,3442, 493, 531,1054, 468,2907,1483, 304, 281, # 2256
+4112,1726,1252,2094, 339,2319,2130,2639, 756,1563,2944, 748, 571,2976,1588,2425, # 2272
+2715,1851,1460,2426,1528,1392,1973,3237, 288,3309, 685,3386, 296, 892,2716,2216, # 2288
+1570,2245, 722,1747,2217, 905,3238,1103,6135,1893,1441,1965, 251,1805,2371,3700, # 2304
+2601,1919,1078,  75,2182,1509,1592,1270,2640,4638,2152,6136,3310,3817, 524, 706, # 2320
+1075, 292,3818,1756,2602, 317,  98,3173,3605,3525,1844,2218,3819,2502, 814, 567, # 2336
+ 385,2908,1534,6137, 534,1642,3239, 797,6138,1670,1529, 953,4323, 188,1071, 538, # 2352
+ 178, 729,3240,2109,1226,1374,2000,2357,2977, 731,2468,1116,2014,2051,6139,1261, # 2368
+1593, 803,2859,2736,3443, 556, 682, 823,1541,6140,1369,2289,1706,2794, 845, 462, # 2384
+2603,2665,1361, 387, 162,2358,1740, 739,1770,1720,1304,1401,3241,1049, 627,1571, # 2400
+2427,3526,1877,3942,1852,1500, 431,1910,1503, 677, 297,2795, 286,1433,1038,1198, # 2416
+2290,1133,1596,4113,4639,2469,1510,1484,3943,6141,2442, 108, 712,4640,2372, 866, # 2432
+3701,2755,3242,1348, 834,1945,1408,3527,2395,3243,1811, 824, 994,1179,2110,1548, # 2448
+1453, 790,3003, 690,4324,4325,2832,2909,3820,1860,3821, 225,1748, 310, 346,1780, # 2464
+2470, 821,1993,2717,2796, 828, 877,3528,2860,2471,1702,2165,2910,2486,1789, 453, # 2480
+ 359,2291,1676,  73,1164,1461,1127,3311, 421, 604, 314,1037, 589, 116,2487, 737, # 2496
+ 837,1180, 111, 244, 735,6142,2261,1861,1362, 986, 523, 418, 581,2666,3822, 103, # 2512
+ 855, 503,1414,1867,2488,1091, 657,1597, 979, 605,1316,4641,1021,2443,2078,2001, # 2528
+1209,  96, 587,2166,1032, 260,1072,2153, 173,  94, 226,3244, 819,2006,4642,4114, # 2544
+2203, 231,1744, 782,  97,2667, 786,3387, 887, 391, 442,2219,4326,1425,6143,2694, # 2560
+ 633,1544,1202, 483,2015, 592,2052,1958,2472,1655, 419, 129,4327,3444,3312,1714, # 2576
+1257,3078,4328,1518,1098, 865,1310,1019,1885,1512,1734, 469,2444, 148, 773, 436, # 2592
+1815,1868,1128,1055,4329,1245,2756,3445,2154,1934,1039,4643, 579,1238, 932,2320, # 2608
+ 353, 205, 801, 115,2428, 944,2321,1881, 399,2565,1211, 678, 766,3944, 335,2101, # 2624
+1459,1781,1402,3945,2737,2131,1010, 844, 981,1326,1013, 550,1816,1545,2620,1335, # 2640
+1008, 371,2881, 936,1419,1613,3529,1456,1395,2273,1834,2604,1317,2738,2503, 416, # 2656
+1643,4330, 806,1126, 229, 591,3946,1314,1981,1576,1837,1666, 347,1790, 977,3313, # 2672
+ 764,2861,1853, 688,2429,1920,1462,  77, 595, 415,2002,3034, 798,1192,4115,6144, # 2688
+2978,4331,3035,2695,2582,2072,2566, 430,2430,1727, 842,1396,3947,3702, 613, 377, # 2704
+ 278, 236,1417,3388,3314,3174, 757,1869, 107,3530,6145,1194, 623,2262, 207,1253, # 2720
+2167,3446,3948, 492,1117,1935, 536,1838,2757,1246,4332, 696,2095,2406,1393,1572, # 2736
+3175,1782, 583, 190, 253,1390,2230, 830,3126,3389, 934,3245,1703,1749,2979,1870, # 2752
+2545,1656,2204, 869,2346,4116,3176,1817, 496,1764,4644, 942,1504, 404,1903,1122, # 2768
+1580,3606,2945,1022, 515, 372,1735, 955,2431,3036,6146,2797,1110,2302,2798, 617, # 2784
+6147, 441, 762,1771,3447,3607,3608,1904, 840,3037,  86, 939,1385, 572,1370,2445, # 2800
+1336, 114,3703, 898, 294, 203,3315, 703,1583,2274, 429, 961,4333,1854,1951,3390, # 2816
+2373,3704,4334,1318,1381, 966,1911,2322,1006,1155, 309, 989, 458,2718,1795,1372, # 2832
+1203, 252,1689,1363,3177, 517,1936, 168,1490, 562, 193,3823,1042,4117,1835, 551, # 2848
+ 470,4645, 395, 489,3448,1871,1465,2583,2641, 417,1493, 279,1295, 511,1236,1119, # 2864
+  72,1231,1982,1812,3004, 871,1564, 984,3449,1667,2696,2096,4646,2347,2833,1673, # 2880
+3609, 695,3246,2668, 807,1183,4647, 890, 388,2333,1801,1457,2911,1765,1477,1031, # 2896
+3316,3317,1278,3391,2799,2292,2526, 163,3450,4335,2669,1404,1802,6148,2323,2407, # 2912
+1584,1728,1494,1824,1269, 298, 909,3318,1034,1632, 375, 776,1683,2061, 291, 210, # 2928
+1123, 809,1249,1002,2642,3038, 206,1011,2132, 144, 975, 882,1565, 342, 667, 754, # 2944
+1442,2143,1299,2303,2062, 447, 626,2205,1221,2739,2912,1144,1214,2206,2584, 760, # 2960
+1715, 614, 950,1281,2670,2621, 810, 577,1287,2546,4648, 242,2168, 250,2643, 691, # 2976
+ 123,2644, 647, 313,1029, 689,1357,2946,1650, 216, 771,1339,1306, 808,2063, 549, # 2992
+ 913,1371,2913,2914,6149,1466,1092,1174,1196,1311,2605,2396,1783,1796,3079, 406, # 3008
+2671,2117,3949,4649, 487,1825,2220,6150,2915, 448,2348,1073,6151,2397,1707, 130, # 3024
+ 900,1598, 329, 176,1959,2527,1620,6152,2275,4336,3319,1983,2191,3705,3610,2155, # 3040
+3706,1912,1513,1614,6153,1988, 646, 392,2304,1589,3320,3039,1826,1239,1352,1340, # 3056
+2916, 505,2567,1709,1437,2408,2547, 906,6154,2672, 384,1458,1594,1100,1329, 710, # 3072
+ 423,3531,2064,2231,2622,1989,2673,1087,1882, 333, 841,3005,1296,2882,2379, 580, # 3088
+1937,1827,1293,2585, 601, 574, 249,1772,4118,2079,1120, 645, 901,1176,1690, 795, # 3104
+2207, 478,1434, 516,1190,1530, 761,2080, 930,1264, 355, 435,1552, 644,1791, 987, # 3120
+ 220,1364,1163,1121,1538, 306,2169,1327,1222, 546,2645, 218, 241, 610,1704,3321, # 3136
+1984,1839,1966,2528, 451,6155,2586,3707,2568, 907,3178, 254,2947, 186,1845,4650, # 3152
+ 745, 432,1757, 428,1633, 888,2246,2221,2489,3611,2118,1258,1265, 956,3127,1784, # 3168
+4337,2490, 319, 510, 119, 457,3612, 274,2035,2007,4651,1409,3128, 970,2758, 590, # 3184
+2800, 661,2247,4652,2008,3950,1420,1549,3080,3322,3951,1651,1375,2111, 485,2491, # 3200
+1429,1156,6156,2548,2183,1495, 831,1840,2529,2446, 501,1657, 307,1894,3247,1341, # 3216
+ 666, 899,2156,1539,2549,1559, 886, 349,2208,3081,2305,1736,3824,2170,2759,1014, # 3232
+1913,1386, 542,1397,2948, 490, 368, 716, 362, 159, 282,2569,1129,1658,1288,1750, # 3248
+2674, 276, 649,2016, 751,1496, 658,1818,1284,1862,2209,2087,2512,3451, 622,2834, # 3264
+ 376, 117,1060,2053,1208,1721,1101,1443, 247,1250,3179,1792,3952,2760,2398,3953, # 3280
+6157,2144,3708, 446,2432,1151,2570,3452,2447,2761,2835,1210,2448,3082, 424,2222, # 3296
+1251,2449,2119,2836, 504,1581,4338, 602, 817, 857,3825,2349,2306, 357,3826,1470, # 3312
+1883,2883, 255, 958, 929,2917,3248, 302,4653,1050,1271,1751,2307,1952,1430,2697, # 3328
+2719,2359, 354,3180, 777, 158,2036,4339,1659,4340,4654,2308,2949,2248,1146,2232, # 3344
+3532,2720,1696,2623,3827,6158,3129,1550,2698,1485,1297,1428, 637, 931,2721,2145, # 3360
+ 914,2550,2587,  81,2450, 612, 827,2646,1242,4655,1118,2884, 472,1855,3181,3533, # 3376
+3534, 569,1353,2699,1244,1758,2588,4119,2009,2762,2171,3709,1312,1531,6159,1152, # 3392
+1938, 134,1830, 471,3710,2276,1112,1535,3323,3453,3535, 982,1337,2950, 488, 826, # 3408
+ 674,1058,1628,4120,2017, 522,2399, 211, 568,1367,3454, 350, 293,1872,1139,3249, # 3424
+1399,1946,3006,1300,2360,3324, 588, 736,6160,2606, 744, 669,3536,3828,6161,1358, # 3440
+ 199, 723, 848, 933, 851,1939,1505,1514,1338,1618,1831,4656,1634,3613, 443,2740, # 3456
+3829, 717,1947, 491,1914,6162,2551,1542,4121,1025,6163,1099,1223, 198,3040,2722, # 3472
+ 370, 410,1905,2589, 998,1248,3182,2380, 519,1449,4122,1710, 947, 928,1153,4341, # 3488
+2277, 344,2624,1511, 615, 105, 161,1212,1076,1960,3130,2054,1926,1175,1906,2473, # 3504
+ 414,1873,2801,6164,2309, 315,1319,3325, 318,2018,2146,2157, 963, 631, 223,4342, # 3520
+4343,2675, 479,3711,1197,2625,3712,2676,2361,6165,4344,4123,6166,2451,3183,1886, # 3536
+2184,1674,1330,1711,1635,1506, 799, 219,3250,3083,3954,1677,3713,3326,2081,3614, # 3552
+1652,2073,4657,1147,3041,1752, 643,1961, 147,1974,3955,6167,1716,2037, 918,3007, # 3568
+1994, 120,1537, 118, 609,3184,4345, 740,3455,1219, 332,1615,3830,6168,1621,2980, # 3584
+1582, 783, 212, 553,2350,3714,1349,2433,2082,4124, 889,6169,2310,1275,1410, 973, # 3600
+ 166,1320,3456,1797,1215,3185,2885,1846,2590,2763,4658, 629, 822,3008, 763, 940, # 3616
+1990,2862, 439,2409,1566,1240,1622, 926,1282,1907,2764, 654,2210,1607, 327,1130, # 3632
+3956,1678,1623,6170,2434,2192, 686, 608,3831,3715, 903,3957,3042,6171,2741,1522, # 3648
+1915,1105,1555,2552,1359, 323,3251,4346,3457, 738,1354,2553,2311,2334,1828,2003, # 3664
+3832,1753,2351,1227,6172,1887,4125,1478,6173,2410,1874,1712,1847, 520,1204,2607, # 3680
+ 264,4659, 836,2677,2102, 600,4660,3833,2278,3084,6174,4347,3615,1342, 640, 532, # 3696
+ 543,2608,1888,2400,2591,1009,4348,1497, 341,1737,3616,2723,1394, 529,3252,1321, # 3712
+ 983,4661,1515,2120, 971,2592, 924, 287,1662,3186,4349,2700,4350,1519, 908,1948, # 3728
+2452, 156, 796,1629,1486,2223,2055, 694,4126,1259,1036,3392,1213,2249,2742,1889, # 3744
+1230,3958,1015, 910, 408, 559,3617,4662, 746, 725, 935,4663,3959,3009,1289, 563, # 3760
+ 867,4664,3960,1567,2981,2038,2626, 988,2263,2381,4351, 143,2374, 704,1895,6175, # 3776
+1188,3716,2088, 673,3085,2362,4352, 484,1608,1921,2765,2918, 215, 904,3618,3537, # 3792
+ 894, 509, 976,3043,2701,3961,4353,2837,2982, 498,6176,6177,1102,3538,1332,3393, # 3808
+1487,1636,1637, 233, 245,3962, 383, 650, 995,3044, 460,1520,1206,2352, 749,3327, # 3824
+ 530, 700, 389,1438,1560,1773,3963,2264, 719,2951,2724,3834, 870,1832,1644,1000, # 3840
+ 839,2474,3717, 197,1630,3394, 365,2886,3964,1285,2133, 734, 922, 818,1106, 732, # 3856
+ 480,2083,1774,3458, 923,2279,1350, 221,3086,  85,2233,2234,3835,1585,3010,2147, # 3872
+1387,1705,2382,1619,2475, 133, 239,2802,1991,1016,2084,2383, 411,2838,1113, 651, # 3888
+1985,1160,3328, 990,1863,3087,1048,1276,2647, 265,2627,1599,3253,2056, 150, 638, # 3904
+2019, 656, 853, 326,1479, 680,1439,4354,1001,1759, 413,3459,3395,2492,1431, 459, # 3920
+4355,1125,3329,2265,1953,1450,2065,2863, 849, 351,2678,3131,3254,3255,1104,1577, # 3936
+ 227,1351,1645,2453,2193,1421,2887, 812,2121, 634,  95,2435, 201,2312,4665,1646, # 3952
+1671,2743,1601,2554,2702,2648,2280,1315,1366,2089,3132,1573,3718,3965,1729,1189, # 3968
+ 328,2679,1077,1940,1136, 558,1283, 964,1195, 621,2074,1199,1743,3460,3619,1896, # 3984
+1916,1890,3836,2952,1154,2112,1064, 862, 378,3011,2066,2113,2803,1568,2839,6178, # 4000
+3088,2919,1941,1660,2004,1992,2194, 142, 707,1590,1708,1624,1922,1023,1836,1233, # 4016
+1004,2313, 789, 741,3620,6179,1609,2411,1200,4127,3719,3720,4666,2057,3721, 593, # 4032
+2840, 367,2920,1878,6180,3461,1521, 628,1168, 692,2211,2649, 300, 720,2067,2571, # 4048
+2953,3396, 959,2504,3966,3539,3462,1977, 701,6181, 954,1043, 800, 681, 183,3722, # 4064
+1803,1730,3540,4128,2103, 815,2314, 174, 467, 230,2454,1093,2134, 755,3541,3397, # 4080
+1141,1162,6182,1738,2039, 270,3256,2513,1005,1647,2185,3837, 858,1679,1897,1719, # 4096
+2954,2324,1806, 402, 670, 167,4129,1498,2158,2104, 750,6183, 915, 189,1680,1551, # 4112
+ 455,4356,1501,2455, 405,1095,2955, 338,1586,1266,1819, 570, 641,1324, 237,1556, # 4128
+2650,1388,3723,6184,1368,2384,1343,1978,3089,2436, 879,3724, 792,1191, 758,3012, # 4144
+1411,2135,1322,4357, 240,4667,1848,3725,1574,6185, 420,3045,1546,1391, 714,4358, # 4160
+1967, 941,1864, 863, 664, 426, 560,1731,2680,1785,2864,1949,2363, 403,3330,1415, # 4176
+1279,2136,1697,2335, 204, 721,2097,3838,  90,6186,2085,2505, 191,3967, 124,2148, # 4192
+1376,1798,1178,1107,1898,1405, 860,4359,1243,1272,2375,2983,1558,2456,1638, 113, # 4208
+3621, 578,1923,2609, 880, 386,4130, 784,2186,2266,1422,2956,2172,1722, 497, 263, # 4224
+2514,1267,2412,2610, 177,2703,3542, 774,1927,1344, 616,1432,1595,1018, 172,4360, # 4240
+2325, 911,4361, 438,1468,3622, 794,3968,2024,2173,1681,1829,2957, 945, 895,3090, # 4256
+ 575,2212,2476, 475,2401,2681, 785,2744,1745,2293,2555,1975,3133,2865, 394,4668, # 4272
+3839, 635,4131, 639, 202,1507,2195,2766,1345,1435,2572,3726,1908,1184,1181,2457, # 4288
+3727,3134,4362, 843,2611, 437, 916,4669, 234, 769,1884,3046,3047,3623, 833,6187, # 4304
+1639,2250,2402,1355,1185,2010,2047, 999, 525,1732,1290,1488,2612, 948,1578,3728, # 4320
+2413,2477,1216,2725,2159, 334,3840,1328,3624,2921,1525,4132, 564,1056, 891,4363, # 4336
+1444,1698,2385,2251,3729,1365,2281,2235,1717,6188, 864,3841,2515, 444, 527,2767, # 4352
+2922,3625, 544, 461,6189, 566, 209,2437,3398,2098,1065,2068,3331,3626,3257,2137, # 4368  #last 512
+)
+# fmt: on
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/johabfreq.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/johabfreq.py
new file mode 100644
index 0000000000000000000000000000000000000000..c12969990d73388f61a6ab98fb4ee8f0f5cbc44f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/johabfreq.py
@@ -0,0 +1,2382 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# The frequency data itself is the same as euc-kr.
+# This is just a mapping table to euc-kr.
+
+JOHAB_TO_EUCKR_ORDER_TABLE = {
+    0x8861: 0,
+    0x8862: 1,
+    0x8865: 2,
+    0x8868: 3,
+    0x8869: 4,
+    0x886A: 5,
+    0x886B: 6,
+    0x8871: 7,
+    0x8873: 8,
+    0x8874: 9,
+    0x8875: 10,
+    0x8876: 11,
+    0x8877: 12,
+    0x8878: 13,
+    0x8879: 14,
+    0x887B: 15,
+    0x887C: 16,
+    0x887D: 17,
+    0x8881: 18,
+    0x8882: 19,
+    0x8885: 20,
+    0x8889: 21,
+    0x8891: 22,
+    0x8893: 23,
+    0x8895: 24,
+    0x8896: 25,
+    0x8897: 26,
+    0x88A1: 27,
+    0x88A2: 28,
+    0x88A5: 29,
+    0x88A9: 30,
+    0x88B5: 31,
+    0x88B7: 32,
+    0x88C1: 33,
+    0x88C5: 34,
+    0x88C9: 35,
+    0x88E1: 36,
+    0x88E2: 37,
+    0x88E5: 38,
+    0x88E8: 39,
+    0x88E9: 40,
+    0x88EB: 41,
+    0x88F1: 42,
+    0x88F3: 43,
+    0x88F5: 44,
+    0x88F6: 45,
+    0x88F7: 46,
+    0x88F8: 47,
+    0x88FB: 48,
+    0x88FC: 49,
+    0x88FD: 50,
+    0x8941: 51,
+    0x8945: 52,
+    0x8949: 53,
+    0x8951: 54,
+    0x8953: 55,
+    0x8955: 56,
+    0x8956: 57,
+    0x8957: 58,
+    0x8961: 59,
+    0x8962: 60,
+    0x8963: 61,
+    0x8965: 62,
+    0x8968: 63,
+    0x8969: 64,
+    0x8971: 65,
+    0x8973: 66,
+    0x8975: 67,
+    0x8976: 68,
+    0x8977: 69,
+    0x897B: 70,
+    0x8981: 71,
+    0x8985: 72,
+    0x8989: 73,
+    0x8993: 74,
+    0x8995: 75,
+    0x89A1: 76,
+    0x89A2: 77,
+    0x89A5: 78,
+    0x89A8: 79,
+    0x89A9: 80,
+    0x89AB: 81,
+    0x89AD: 82,
+    0x89B0: 83,
+    0x89B1: 84,
+    0x89B3: 85,
+    0x89B5: 86,
+    0x89B7: 87,
+    0x89B8: 88,
+    0x89C1: 89,
+    0x89C2: 90,
+    0x89C5: 91,
+    0x89C9: 92,
+    0x89CB: 93,
+    0x89D1: 94,
+    0x89D3: 95,
+    0x89D5: 96,
+    0x89D7: 97,
+    0x89E1: 98,
+    0x89E5: 99,
+    0x89E9: 100,
+    0x89F3: 101,
+    0x89F6: 102,
+    0x89F7: 103,
+    0x8A41: 104,
+    0x8A42: 105,
+    0x8A45: 106,
+    0x8A49: 107,
+    0x8A51: 108,
+    0x8A53: 109,
+    0x8A55: 110,
+    0x8A57: 111,
+    0x8A61: 112,
+    0x8A65: 113,
+    0x8A69: 114,
+    0x8A73: 115,
+    0x8A75: 116,
+    0x8A81: 117,
+    0x8A82: 118,
+    0x8A85: 119,
+    0x8A88: 120,
+    0x8A89: 121,
+    0x8A8A: 122,
+    0x8A8B: 123,
+    0x8A90: 124,
+    0x8A91: 125,
+    0x8A93: 126,
+    0x8A95: 127,
+    0x8A97: 128,
+    0x8A98: 129,
+    0x8AA1: 130,
+    0x8AA2: 131,
+    0x8AA5: 132,
+    0x8AA9: 133,
+    0x8AB6: 134,
+    0x8AB7: 135,
+    0x8AC1: 136,
+    0x8AD5: 137,
+    0x8AE1: 138,
+    0x8AE2: 139,
+    0x8AE5: 140,
+    0x8AE9: 141,
+    0x8AF1: 142,
+    0x8AF3: 143,
+    0x8AF5: 144,
+    0x8B41: 145,
+    0x8B45: 146,
+    0x8B49: 147,
+    0x8B61: 148,
+    0x8B62: 149,
+    0x8B65: 150,
+    0x8B68: 151,
+    0x8B69: 152,
+    0x8B6A: 153,
+    0x8B71: 154,
+    0x8B73: 155,
+    0x8B75: 156,
+    0x8B77: 157,
+    0x8B81: 158,
+    0x8BA1: 159,
+    0x8BA2: 160,
+    0x8BA5: 161,
+    0x8BA8: 162,
+    0x8BA9: 163,
+    0x8BAB: 164,
+    0x8BB1: 165,
+    0x8BB3: 166,
+    0x8BB5: 167,
+    0x8BB7: 168,
+    0x8BB8: 169,
+    0x8BBC: 170,
+    0x8C61: 171,
+    0x8C62: 172,
+    0x8C63: 173,
+    0x8C65: 174,
+    0x8C69: 175,
+    0x8C6B: 176,
+    0x8C71: 177,
+    0x8C73: 178,
+    0x8C75: 179,
+    0x8C76: 180,
+    0x8C77: 181,
+    0x8C7B: 182,
+    0x8C81: 183,
+    0x8C82: 184,
+    0x8C85: 185,
+    0x8C89: 186,
+    0x8C91: 187,
+    0x8C93: 188,
+    0x8C95: 189,
+    0x8C96: 190,
+    0x8C97: 191,
+    0x8CA1: 192,
+    0x8CA2: 193,
+    0x8CA9: 194,
+    0x8CE1: 195,
+    0x8CE2: 196,
+    0x8CE3: 197,
+    0x8CE5: 198,
+    0x8CE9: 199,
+    0x8CF1: 200,
+    0x8CF3: 201,
+    0x8CF5: 202,
+    0x8CF6: 203,
+    0x8CF7: 204,
+    0x8D41: 205,
+    0x8D42: 206,
+    0x8D45: 207,
+    0x8D51: 208,
+    0x8D55: 209,
+    0x8D57: 210,
+    0x8D61: 211,
+    0x8D65: 212,
+    0x8D69: 213,
+    0x8D75: 214,
+    0x8D76: 215,
+    0x8D7B: 216,
+    0x8D81: 217,
+    0x8DA1: 218,
+    0x8DA2: 219,
+    0x8DA5: 220,
+    0x8DA7: 221,
+    0x8DA9: 222,
+    0x8DB1: 223,
+    0x8DB3: 224,
+    0x8DB5: 225,
+    0x8DB7: 226,
+    0x8DB8: 227,
+    0x8DB9: 228,
+    0x8DC1: 229,
+    0x8DC2: 230,
+    0x8DC9: 231,
+    0x8DD6: 232,
+    0x8DD7: 233,
+    0x8DE1: 234,
+    0x8DE2: 235,
+    0x8DF7: 236,
+    0x8E41: 237,
+    0x8E45: 238,
+    0x8E49: 239,
+    0x8E51: 240,
+    0x8E53: 241,
+    0x8E57: 242,
+    0x8E61: 243,
+    0x8E81: 244,
+    0x8E82: 245,
+    0x8E85: 246,
+    0x8E89: 247,
+    0x8E90: 248,
+    0x8E91: 249,
+    0x8E93: 250,
+    0x8E95: 251,
+    0x8E97: 252,
+    0x8E98: 253,
+    0x8EA1: 254,
+    0x8EA9: 255,
+    0x8EB6: 256,
+    0x8EB7: 257,
+    0x8EC1: 258,
+    0x8EC2: 259,
+    0x8EC5: 260,
+    0x8EC9: 261,
+    0x8ED1: 262,
+    0x8ED3: 263,
+    0x8ED6: 264,
+    0x8EE1: 265,
+    0x8EE5: 266,
+    0x8EE9: 267,
+    0x8EF1: 268,
+    0x8EF3: 269,
+    0x8F41: 270,
+    0x8F61: 271,
+    0x8F62: 272,
+    0x8F65: 273,
+    0x8F67: 274,
+    0x8F69: 275,
+    0x8F6B: 276,
+    0x8F70: 277,
+    0x8F71: 278,
+    0x8F73: 279,
+    0x8F75: 280,
+    0x8F77: 281,
+    0x8F7B: 282,
+    0x8FA1: 283,
+    0x8FA2: 284,
+    0x8FA5: 285,
+    0x8FA9: 286,
+    0x8FB1: 287,
+    0x8FB3: 288,
+    0x8FB5: 289,
+    0x8FB7: 290,
+    0x9061: 291,
+    0x9062: 292,
+    0x9063: 293,
+    0x9065: 294,
+    0x9068: 295,
+    0x9069: 296,
+    0x906A: 297,
+    0x906B: 298,
+    0x9071: 299,
+    0x9073: 300,
+    0x9075: 301,
+    0x9076: 302,
+    0x9077: 303,
+    0x9078: 304,
+    0x9079: 305,
+    0x907B: 306,
+    0x907D: 307,
+    0x9081: 308,
+    0x9082: 309,
+    0x9085: 310,
+    0x9089: 311,
+    0x9091: 312,
+    0x9093: 313,
+    0x9095: 314,
+    0x9096: 315,
+    0x9097: 316,
+    0x90A1: 317,
+    0x90A2: 318,
+    0x90A5: 319,
+    0x90A9: 320,
+    0x90B1: 321,
+    0x90B7: 322,
+    0x90E1: 323,
+    0x90E2: 324,
+    0x90E4: 325,
+    0x90E5: 326,
+    0x90E9: 327,
+    0x90EB: 328,
+    0x90EC: 329,
+    0x90F1: 330,
+    0x90F3: 331,
+    0x90F5: 332,
+    0x90F6: 333,
+    0x90F7: 334,
+    0x90FD: 335,
+    0x9141: 336,
+    0x9142: 337,
+    0x9145: 338,
+    0x9149: 339,
+    0x9151: 340,
+    0x9153: 341,
+    0x9155: 342,
+    0x9156: 343,
+    0x9157: 344,
+    0x9161: 345,
+    0x9162: 346,
+    0x9165: 347,
+    0x9169: 348,
+    0x9171: 349,
+    0x9173: 350,
+    0x9176: 351,
+    0x9177: 352,
+    0x917A: 353,
+    0x9181: 354,
+    0x9185: 355,
+    0x91A1: 356,
+    0x91A2: 357,
+    0x91A5: 358,
+    0x91A9: 359,
+    0x91AB: 360,
+    0x91B1: 361,
+    0x91B3: 362,
+    0x91B5: 363,
+    0x91B7: 364,
+    0x91BC: 365,
+    0x91BD: 366,
+    0x91C1: 367,
+    0x91C5: 368,
+    0x91C9: 369,
+    0x91D6: 370,
+    0x9241: 371,
+    0x9245: 372,
+    0x9249: 373,
+    0x9251: 374,
+    0x9253: 375,
+    0x9255: 376,
+    0x9261: 377,
+    0x9262: 378,
+    0x9265: 379,
+    0x9269: 380,
+    0x9273: 381,
+    0x9275: 382,
+    0x9277: 383,
+    0x9281: 384,
+    0x9282: 385,
+    0x9285: 386,
+    0x9288: 387,
+    0x9289: 388,
+    0x9291: 389,
+    0x9293: 390,
+    0x9295: 391,
+    0x9297: 392,
+    0x92A1: 393,
+    0x92B6: 394,
+    0x92C1: 395,
+    0x92E1: 396,
+    0x92E5: 397,
+    0x92E9: 398,
+    0x92F1: 399,
+    0x92F3: 400,
+    0x9341: 401,
+    0x9342: 402,
+    0x9349: 403,
+    0x9351: 404,
+    0x9353: 405,
+    0x9357: 406,
+    0x9361: 407,
+    0x9362: 408,
+    0x9365: 409,
+    0x9369: 410,
+    0x936A: 411,
+    0x936B: 412,
+    0x9371: 413,
+    0x9373: 414,
+    0x9375: 415,
+    0x9377: 416,
+    0x9378: 417,
+    0x937C: 418,
+    0x9381: 419,
+    0x9385: 420,
+    0x9389: 421,
+    0x93A1: 422,
+    0x93A2: 423,
+    0x93A5: 424,
+    0x93A9: 425,
+    0x93AB: 426,
+    0x93B1: 427,
+    0x93B3: 428,
+    0x93B5: 429,
+    0x93B7: 430,
+    0x93BC: 431,
+    0x9461: 432,
+    0x9462: 433,
+    0x9463: 434,
+    0x9465: 435,
+    0x9468: 436,
+    0x9469: 437,
+    0x946A: 438,
+    0x946B: 439,
+    0x946C: 440,
+    0x9470: 441,
+    0x9471: 442,
+    0x9473: 443,
+    0x9475: 444,
+    0x9476: 445,
+    0x9477: 446,
+    0x9478: 447,
+    0x9479: 448,
+    0x947D: 449,
+    0x9481: 450,
+    0x9482: 451,
+    0x9485: 452,
+    0x9489: 453,
+    0x9491: 454,
+    0x9493: 455,
+    0x9495: 456,
+    0x9496: 457,
+    0x9497: 458,
+    0x94A1: 459,
+    0x94E1: 460,
+    0x94E2: 461,
+    0x94E3: 462,
+    0x94E5: 463,
+    0x94E8: 464,
+    0x94E9: 465,
+    0x94EB: 466,
+    0x94EC: 467,
+    0x94F1: 468,
+    0x94F3: 469,
+    0x94F5: 470,
+    0x94F7: 471,
+    0x94F9: 472,
+    0x94FC: 473,
+    0x9541: 474,
+    0x9542: 475,
+    0x9545: 476,
+    0x9549: 477,
+    0x9551: 478,
+    0x9553: 479,
+    0x9555: 480,
+    0x9556: 481,
+    0x9557: 482,
+    0x9561: 483,
+    0x9565: 484,
+    0x9569: 485,
+    0x9576: 486,
+    0x9577: 487,
+    0x9581: 488,
+    0x9585: 489,
+    0x95A1: 490,
+    0x95A2: 491,
+    0x95A5: 492,
+    0x95A8: 493,
+    0x95A9: 494,
+    0x95AB: 495,
+    0x95AD: 496,
+    0x95B1: 497,
+    0x95B3: 498,
+    0x95B5: 499,
+    0x95B7: 500,
+    0x95B9: 501,
+    0x95BB: 502,
+    0x95C1: 503,
+    0x95C5: 504,
+    0x95C9: 505,
+    0x95E1: 506,
+    0x95F6: 507,
+    0x9641: 508,
+    0x9645: 509,
+    0x9649: 510,
+    0x9651: 511,
+    0x9653: 512,
+    0x9655: 513,
+    0x9661: 514,
+    0x9681: 515,
+    0x9682: 516,
+    0x9685: 517,
+    0x9689: 518,
+    0x9691: 519,
+    0x9693: 520,
+    0x9695: 521,
+    0x9697: 522,
+    0x96A1: 523,
+    0x96B6: 524,
+    0x96C1: 525,
+    0x96D7: 526,
+    0x96E1: 527,
+    0x96E5: 528,
+    0x96E9: 529,
+    0x96F3: 530,
+    0x96F5: 531,
+    0x96F7: 532,
+    0x9741: 533,
+    0x9745: 534,
+    0x9749: 535,
+    0x9751: 536,
+    0x9757: 537,
+    0x9761: 538,
+    0x9762: 539,
+    0x9765: 540,
+    0x9768: 541,
+    0x9769: 542,
+    0x976B: 543,
+    0x9771: 544,
+    0x9773: 545,
+    0x9775: 546,
+    0x9777: 547,
+    0x9781: 548,
+    0x97A1: 549,
+    0x97A2: 550,
+    0x97A5: 551,
+    0x97A8: 552,
+    0x97A9: 553,
+    0x97B1: 554,
+    0x97B3: 555,
+    0x97B5: 556,
+    0x97B6: 557,
+    0x97B7: 558,
+    0x97B8: 559,
+    0x9861: 560,
+    0x9862: 561,
+    0x9865: 562,
+    0x9869: 563,
+    0x9871: 564,
+    0x9873: 565,
+    0x9875: 566,
+    0x9876: 567,
+    0x9877: 568,
+    0x987D: 569,
+    0x9881: 570,
+    0x9882: 571,
+    0x9885: 572,
+    0x9889: 573,
+    0x9891: 574,
+    0x9893: 575,
+    0x9895: 576,
+    0x9896: 577,
+    0x9897: 578,
+    0x98E1: 579,
+    0x98E2: 580,
+    0x98E5: 581,
+    0x98E9: 582,
+    0x98EB: 583,
+    0x98EC: 584,
+    0x98F1: 585,
+    0x98F3: 586,
+    0x98F5: 587,
+    0x98F6: 588,
+    0x98F7: 589,
+    0x98FD: 590,
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+    0xC5C5: 1947,
+    0xC5C9: 1948,
+    0xC5D1: 1949,
+    0xC5D7: 1950,
+    0xC5E1: 1951,
+    0xC5F7: 1952,
+    0xC641: 1953,
+    0xC649: 1954,
+    0xC661: 1955,
+    0xC681: 1956,
+    0xC682: 1957,
+    0xC685: 1958,
+    0xC689: 1959,
+    0xC691: 1960,
+    0xC693: 1961,
+    0xC695: 1962,
+    0xC697: 1963,
+    0xC6A1: 1964,
+    0xC6A5: 1965,
+    0xC6A9: 1966,
+    0xC6B7: 1967,
+    0xC6C1: 1968,
+    0xC6D7: 1969,
+    0xC6E1: 1970,
+    0xC6E2: 1971,
+    0xC6E5: 1972,
+    0xC6E9: 1973,
+    0xC6F1: 1974,
+    0xC6F3: 1975,
+    0xC6F5: 1976,
+    0xC6F7: 1977,
+    0xC741: 1978,
+    0xC745: 1979,
+    0xC749: 1980,
+    0xC751: 1981,
+    0xC761: 1982,
+    0xC762: 1983,
+    0xC765: 1984,
+    0xC769: 1985,
+    0xC771: 1986,
+    0xC773: 1987,
+    0xC777: 1988,
+    0xC7A1: 1989,
+    0xC7A2: 1990,
+    0xC7A5: 1991,
+    0xC7A9: 1992,
+    0xC7B1: 1993,
+    0xC7B3: 1994,
+    0xC7B5: 1995,
+    0xC7B7: 1996,
+    0xC861: 1997,
+    0xC862: 1998,
+    0xC865: 1999,
+    0xC869: 2000,
+    0xC86A: 2001,
+    0xC871: 2002,
+    0xC873: 2003,
+    0xC875: 2004,
+    0xC876: 2005,
+    0xC877: 2006,
+    0xC881: 2007,
+    0xC882: 2008,
+    0xC885: 2009,
+    0xC889: 2010,
+    0xC891: 2011,
+    0xC893: 2012,
+    0xC895: 2013,
+    0xC896: 2014,
+    0xC897: 2015,
+    0xC8A1: 2016,
+    0xC8B7: 2017,
+    0xC8E1: 2018,
+    0xC8E2: 2019,
+    0xC8E5: 2020,
+    0xC8E9: 2021,
+    0xC8EB: 2022,
+    0xC8F1: 2023,
+    0xC8F3: 2024,
+    0xC8F5: 2025,
+    0xC8F6: 2026,
+    0xC8F7: 2027,
+    0xC941: 2028,
+    0xC942: 2029,
+    0xC945: 2030,
+    0xC949: 2031,
+    0xC951: 2032,
+    0xC953: 2033,
+    0xC955: 2034,
+    0xC957: 2035,
+    0xC961: 2036,
+    0xC965: 2037,
+    0xC976: 2038,
+    0xC981: 2039,
+    0xC985: 2040,
+    0xC9A1: 2041,
+    0xC9A2: 2042,
+    0xC9A5: 2043,
+    0xC9A9: 2044,
+    0xC9B1: 2045,
+    0xC9B3: 2046,
+    0xC9B5: 2047,
+    0xC9B7: 2048,
+    0xC9BC: 2049,
+    0xC9C1: 2050,
+    0xC9C5: 2051,
+    0xC9E1: 2052,
+    0xCA41: 2053,
+    0xCA45: 2054,
+    0xCA55: 2055,
+    0xCA57: 2056,
+    0xCA61: 2057,
+    0xCA81: 2058,
+    0xCA82: 2059,
+    0xCA85: 2060,
+    0xCA89: 2061,
+    0xCA91: 2062,
+    0xCA93: 2063,
+    0xCA95: 2064,
+    0xCA97: 2065,
+    0xCAA1: 2066,
+    0xCAB6: 2067,
+    0xCAC1: 2068,
+    0xCAE1: 2069,
+    0xCAE2: 2070,
+    0xCAE5: 2071,
+    0xCAE9: 2072,
+    0xCAF1: 2073,
+    0xCAF3: 2074,
+    0xCAF7: 2075,
+    0xCB41: 2076,
+    0xCB45: 2077,
+    0xCB49: 2078,
+    0xCB51: 2079,
+    0xCB57: 2080,
+    0xCB61: 2081,
+    0xCB62: 2082,
+    0xCB65: 2083,
+    0xCB68: 2084,
+    0xCB69: 2085,
+    0xCB6B: 2086,
+    0xCB71: 2087,
+    0xCB73: 2088,
+    0xCB75: 2089,
+    0xCB81: 2090,
+    0xCB85: 2091,
+    0xCB89: 2092,
+    0xCB91: 2093,
+    0xCB93: 2094,
+    0xCBA1: 2095,
+    0xCBA2: 2096,
+    0xCBA5: 2097,
+    0xCBA9: 2098,
+    0xCBB1: 2099,
+    0xCBB3: 2100,
+    0xCBB5: 2101,
+    0xCBB7: 2102,
+    0xCC61: 2103,
+    0xCC62: 2104,
+    0xCC63: 2105,
+    0xCC65: 2106,
+    0xCC69: 2107,
+    0xCC6B: 2108,
+    0xCC71: 2109,
+    0xCC73: 2110,
+    0xCC75: 2111,
+    0xCC76: 2112,
+    0xCC77: 2113,
+    0xCC7B: 2114,
+    0xCC81: 2115,
+    0xCC82: 2116,
+    0xCC85: 2117,
+    0xCC89: 2118,
+    0xCC91: 2119,
+    0xCC93: 2120,
+    0xCC95: 2121,
+    0xCC96: 2122,
+    0xCC97: 2123,
+    0xCCA1: 2124,
+    0xCCA2: 2125,
+    0xCCE1: 2126,
+    0xCCE2: 2127,
+    0xCCE5: 2128,
+    0xCCE9: 2129,
+    0xCCF1: 2130,
+    0xCCF3: 2131,
+    0xCCF5: 2132,
+    0xCCF6: 2133,
+    0xCCF7: 2134,
+    0xCD41: 2135,
+    0xCD42: 2136,
+    0xCD45: 2137,
+    0xCD49: 2138,
+    0xCD51: 2139,
+    0xCD53: 2140,
+    0xCD55: 2141,
+    0xCD57: 2142,
+    0xCD61: 2143,
+    0xCD65: 2144,
+    0xCD69: 2145,
+    0xCD71: 2146,
+    0xCD73: 2147,
+    0xCD76: 2148,
+    0xCD77: 2149,
+    0xCD81: 2150,
+    0xCD89: 2151,
+    0xCD93: 2152,
+    0xCD95: 2153,
+    0xCDA1: 2154,
+    0xCDA2: 2155,
+    0xCDA5: 2156,
+    0xCDA9: 2157,
+    0xCDB1: 2158,
+    0xCDB3: 2159,
+    0xCDB5: 2160,
+    0xCDB7: 2161,
+    0xCDC1: 2162,
+    0xCDD7: 2163,
+    0xCE41: 2164,
+    0xCE45: 2165,
+    0xCE61: 2166,
+    0xCE65: 2167,
+    0xCE69: 2168,
+    0xCE73: 2169,
+    0xCE75: 2170,
+    0xCE81: 2171,
+    0xCE82: 2172,
+    0xCE85: 2173,
+    0xCE88: 2174,
+    0xCE89: 2175,
+    0xCE8B: 2176,
+    0xCE91: 2177,
+    0xCE93: 2178,
+    0xCE95: 2179,
+    0xCE97: 2180,
+    0xCEA1: 2181,
+    0xCEB7: 2182,
+    0xCEE1: 2183,
+    0xCEE5: 2184,
+    0xCEE9: 2185,
+    0xCEF1: 2186,
+    0xCEF5: 2187,
+    0xCF41: 2188,
+    0xCF45: 2189,
+    0xCF49: 2190,
+    0xCF51: 2191,
+    0xCF55: 2192,
+    0xCF57: 2193,
+    0xCF61: 2194,
+    0xCF65: 2195,
+    0xCF69: 2196,
+    0xCF71: 2197,
+    0xCF73: 2198,
+    0xCF75: 2199,
+    0xCFA1: 2200,
+    0xCFA2: 2201,
+    0xCFA5: 2202,
+    0xCFA9: 2203,
+    0xCFB1: 2204,
+    0xCFB3: 2205,
+    0xCFB5: 2206,
+    0xCFB7: 2207,
+    0xD061: 2208,
+    0xD062: 2209,
+    0xD065: 2210,
+    0xD069: 2211,
+    0xD06E: 2212,
+    0xD071: 2213,
+    0xD073: 2214,
+    0xD075: 2215,
+    0xD077: 2216,
+    0xD081: 2217,
+    0xD082: 2218,
+    0xD085: 2219,
+    0xD089: 2220,
+    0xD091: 2221,
+    0xD093: 2222,
+    0xD095: 2223,
+    0xD096: 2224,
+    0xD097: 2225,
+    0xD0A1: 2226,
+    0xD0B7: 2227,
+    0xD0E1: 2228,
+    0xD0E2: 2229,
+    0xD0E5: 2230,
+    0xD0E9: 2231,
+    0xD0EB: 2232,
+    0xD0F1: 2233,
+    0xD0F3: 2234,
+    0xD0F5: 2235,
+    0xD0F7: 2236,
+    0xD141: 2237,
+    0xD142: 2238,
+    0xD145: 2239,
+    0xD149: 2240,
+    0xD151: 2241,
+    0xD153: 2242,
+    0xD155: 2243,
+    0xD157: 2244,
+    0xD161: 2245,
+    0xD162: 2246,
+    0xD165: 2247,
+    0xD169: 2248,
+    0xD171: 2249,
+    0xD173: 2250,
+    0xD175: 2251,
+    0xD176: 2252,
+    0xD177: 2253,
+    0xD181: 2254,
+    0xD185: 2255,
+    0xD189: 2256,
+    0xD193: 2257,
+    0xD1A1: 2258,
+    0xD1A2: 2259,
+    0xD1A5: 2260,
+    0xD1A9: 2261,
+    0xD1AE: 2262,
+    0xD1B1: 2263,
+    0xD1B3: 2264,
+    0xD1B5: 2265,
+    0xD1B7: 2266,
+    0xD1BB: 2267,
+    0xD1C1: 2268,
+    0xD1C2: 2269,
+    0xD1C5: 2270,
+    0xD1C9: 2271,
+    0xD1D5: 2272,
+    0xD1D7: 2273,
+    0xD1E1: 2274,
+    0xD1E2: 2275,
+    0xD1E5: 2276,
+    0xD1F5: 2277,
+    0xD1F7: 2278,
+    0xD241: 2279,
+    0xD242: 2280,
+    0xD245: 2281,
+    0xD249: 2282,
+    0xD253: 2283,
+    0xD255: 2284,
+    0xD257: 2285,
+    0xD261: 2286,
+    0xD265: 2287,
+    0xD269: 2288,
+    0xD273: 2289,
+    0xD275: 2290,
+    0xD281: 2291,
+    0xD282: 2292,
+    0xD285: 2293,
+    0xD289: 2294,
+    0xD28E: 2295,
+    0xD291: 2296,
+    0xD295: 2297,
+    0xD297: 2298,
+    0xD2A1: 2299,
+    0xD2A5: 2300,
+    0xD2A9: 2301,
+    0xD2B1: 2302,
+    0xD2B7: 2303,
+    0xD2C1: 2304,
+    0xD2C2: 2305,
+    0xD2C5: 2306,
+    0xD2C9: 2307,
+    0xD2D7: 2308,
+    0xD2E1: 2309,
+    0xD2E2: 2310,
+    0xD2E5: 2311,
+    0xD2E9: 2312,
+    0xD2F1: 2313,
+    0xD2F3: 2314,
+    0xD2F5: 2315,
+    0xD2F7: 2316,
+    0xD341: 2317,
+    0xD342: 2318,
+    0xD345: 2319,
+    0xD349: 2320,
+    0xD351: 2321,
+    0xD355: 2322,
+    0xD357: 2323,
+    0xD361: 2324,
+    0xD362: 2325,
+    0xD365: 2326,
+    0xD367: 2327,
+    0xD368: 2328,
+    0xD369: 2329,
+    0xD36A: 2330,
+    0xD371: 2331,
+    0xD373: 2332,
+    0xD375: 2333,
+    0xD377: 2334,
+    0xD37B: 2335,
+    0xD381: 2336,
+    0xD385: 2337,
+    0xD389: 2338,
+    0xD391: 2339,
+    0xD393: 2340,
+    0xD397: 2341,
+    0xD3A1: 2342,
+    0xD3A2: 2343,
+    0xD3A5: 2344,
+    0xD3A9: 2345,
+    0xD3B1: 2346,
+    0xD3B3: 2347,
+    0xD3B5: 2348,
+    0xD3B7: 2349,
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/johabprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/johabprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..d7364ba61eca930aa1c868abe3b322cceb995a6b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/johabprober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import JOHABDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import JOHAB_SM_MODEL
+
+
+class JOHABProber(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(JOHAB_SM_MODEL)
+        self.distribution_analyzer = JOHABDistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "Johab"
+
+    @property
+    def language(self) -> str:
+        return "Korean"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/jpcntx.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/jpcntx.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f53bdda09e92da38e31cac1a6d415f4670137f7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/jpcntx.py
@@ -0,0 +1,238 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Tuple, Union
+
+# This is hiragana 2-char sequence table, the number in each cell represents its frequency category
+# fmt: off
+jp2_char_context = (
+    (0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1),
+    (2, 4, 0, 4, 0, 3, 0, 4, 0, 3, 4, 4, 4, 2, 4, 3, 3, 4, 3, 2, 3, 3, 4, 2, 3, 3, 3, 2, 4, 1, 4, 3, 3, 1, 5, 4, 3, 4, 3, 4, 3, 5, 3, 0, 3, 5, 4, 2, 0, 3, 1, 0, 3, 3, 0, 3, 3, 0, 1, 1, 0, 4, 3, 0, 3, 3, 0, 4, 0, 2, 0, 3, 5, 5, 5, 5, 4, 0, 4, 1, 0, 3, 4),
+    (0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2),
+    (0, 4, 0, 5, 0, 5, 0, 4, 0, 4, 5, 4, 4, 3, 5, 3, 5, 1, 5, 3, 4, 3, 4, 4, 3, 4, 3, 3, 4, 3, 5, 4, 4, 3, 5, 5, 3, 5, 5, 5, 3, 5, 5, 3, 4, 5, 5, 3, 1, 3, 2, 0, 3, 4, 0, 4, 2, 0, 4, 2, 1, 5, 3, 2, 3, 5, 0, 4, 0, 2, 0, 5, 4, 4, 5, 4, 5, 0, 4, 0, 0, 4, 4),
+    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+    (0, 3, 0, 4, 0, 3, 0, 3, 0, 4, 5, 4, 3, 3, 3, 3, 4, 3, 5, 4, 4, 3, 5, 4, 4, 3, 4, 3, 4, 4, 4, 4, 5, 3, 4, 4, 3, 4, 5, 5, 4, 5, 5, 1, 4, 5, 4, 3, 0, 3, 3, 1, 3, 3, 0, 4, 4, 0, 3, 3, 1, 5, 3, 3, 3, 5, 0, 4, 0, 3, 0, 4, 4, 3, 4, 3, 3, 0, 4, 1, 1, 3, 4),
+    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+    (0, 4, 0, 3, 0, 3, 0, 4, 0, 3, 4, 4, 3, 2, 2, 1, 2, 1, 3, 1, 3, 3, 3, 3, 3, 4, 3, 1, 3, 3, 5, 3, 3, 0, 4, 3, 0, 5, 4, 3, 3, 5, 4, 4, 3, 4, 4, 5, 0, 1, 2, 0, 1, 2, 0, 2, 2, 0, 1, 0, 0, 5, 2, 2, 1, 4, 0, 3, 0, 1, 0, 4, 4, 3, 5, 4, 3, 0, 2, 1, 0, 4, 3),
+    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+    (0, 3, 0, 5, 0, 4, 0, 2, 1, 4, 4, 2, 4, 1, 4, 2, 4, 2, 4, 3, 3, 3, 4, 3, 3, 3, 3, 1, 4, 2, 3, 3, 3, 1, 4, 4, 1, 1, 1, 4, 3, 3, 2, 0, 2, 4, 3, 2, 0, 3, 3, 0, 3, 1, 1, 0, 0, 0, 3, 3, 0, 4, 2, 2, 3, 4, 0, 4, 0, 3, 0, 4, 4, 5, 3, 4, 4, 0, 3, 0, 0, 1, 4),
+    (1, 4, 0, 4, 0, 4, 0, 4, 0, 3, 5, 4, 4, 3, 4, 3, 5, 4, 3, 3, 4, 3, 5, 4, 4, 4, 4, 3, 4, 2, 4, 3, 3, 1, 5, 4, 3, 2, 4, 5, 4, 5, 5, 4, 4, 5, 4, 4, 0, 3, 2, 2, 3, 3, 0, 4, 3, 1, 3, 2, 1, 4, 3, 3, 4, 5, 0, 3, 0, 2, 0, 4, 5, 5, 4, 5, 4, 0, 4, 0, 0, 5, 4),
+    (0, 5, 0, 5, 0, 4, 0, 3, 0, 4, 4, 3, 4, 3, 3, 3, 4, 0, 4, 4, 4, 3, 4, 3, 4, 3, 3, 1, 4, 2, 4, 3, 4, 0, 5, 4, 1, 4, 5, 4, 4, 5, 3, 2, 4, 3, 4, 3, 2, 4, 1, 3, 3, 3, 2, 3, 2, 0, 4, 3, 3, 4, 3, 3, 3, 4, 0, 4, 0, 3, 0, 4, 5, 4, 4, 4, 3, 0, 4, 1, 0, 1, 3),
+    (0, 3, 1, 4, 0, 3, 0, 2, 0, 3, 4, 4, 3, 1, 4, 2, 3, 3, 4, 3, 4, 3, 4, 3, 4, 4, 3, 2, 3, 1, 5, 4, 4, 1, 4, 4, 3, 5, 4, 4, 3, 5, 5, 4, 3, 4, 4, 3, 1, 2, 3, 1, 2, 2, 0, 3, 2, 0, 3, 1, 0, 5, 3, 3, 3, 4, 3, 3, 3, 3, 4, 4, 4, 4, 5, 4, 2, 0, 3, 3, 2, 4, 3),
+    (0, 2, 0, 3, 0, 1, 0, 1, 0, 0, 3, 2, 0, 0, 2, 0, 1, 0, 2, 1, 3, 3, 3, 1, 2, 3, 1, 0, 1, 0, 4, 2, 1, 1, 3, 3, 0, 4, 3, 3, 1, 4, 3, 3, 0, 3, 3, 2, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 4, 1, 0, 2, 3, 2, 2, 2, 1, 3, 3, 3, 4, 4, 3, 2, 0, 3, 1, 0, 3, 3),
+    (0, 4, 0, 4, 0, 3, 0, 3, 0, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 3, 4, 2, 4, 3, 4, 3, 3, 2, 4, 3, 4, 5, 4, 1, 4, 5, 3, 5, 4, 5, 3, 5, 4, 0, 3, 5, 5, 3, 1, 3, 3, 2, 2, 3, 0, 3, 4, 1, 3, 3, 2, 4, 3, 3, 3, 4, 0, 4, 0, 3, 0, 4, 5, 4, 4, 5, 3, 0, 4, 1, 0, 3, 4),
+    (0, 2, 0, 3, 0, 3, 0, 0, 0, 2, 2, 2, 1, 0, 1, 0, 0, 0, 3, 0, 3, 0, 3, 0, 1, 3, 1, 0, 3, 1, 3, 3, 3, 1, 3, 3, 3, 0, 1, 3, 1, 3, 4, 0, 0, 3, 1, 1, 0, 3, 2, 0, 0, 0, 0, 1, 3, 0, 1, 0, 0, 3, 3, 2, 0, 3, 0, 0, 0, 0, 0, 3, 4, 3, 4, 3, 3, 0, 3, 0, 0, 2, 3),
+    (2, 3, 0, 3, 0, 2, 0, 1, 0, 3, 3, 4, 3, 1, 3, 1, 1, 1, 3, 1, 4, 3, 4, 3, 3, 3, 0, 0, 3, 1, 5, 4, 3, 1, 4, 3, 2, 5, 5, 4, 4, 4, 4, 3, 3, 4, 4, 4, 0, 2, 1, 1, 3, 2, 0, 1, 2, 0, 0, 1, 0, 4, 1, 3, 3, 3, 0, 3, 0, 1, 0, 4, 4, 4, 5, 5, 3, 0, 2, 0, 0, 4, 4),
+    (0, 2, 0, 1, 0, 3, 1, 3, 0, 2, 3, 3, 3, 0, 3, 1, 0, 0, 3, 0, 3, 2, 3, 1, 3, 2, 1, 1, 0, 0, 4, 2, 1, 0, 2, 3, 1, 4, 3, 2, 0, 4, 4, 3, 1, 3, 1, 3, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 4, 1, 1, 1, 2, 0, 3, 0, 0, 0, 3, 4, 2, 4, 3, 2, 0, 1, 0, 0, 3, 3),
+    (0, 1, 0, 4, 0, 5, 0, 4, 0, 2, 4, 4, 2, 3, 3, 2, 3, 3, 5, 3, 3, 3, 4, 3, 4, 2, 3, 0, 4, 3, 3, 3, 4, 1, 4, 3, 2, 1, 5, 5, 3, 4, 5, 1, 3, 5, 4, 2, 0, 3, 3, 0, 1, 3, 0, 4, 2, 0, 1, 3, 1, 4, 3, 3, 3, 3, 0, 3, 0, 1, 0, 3, 4, 4, 4, 5, 5, 0, 3, 0, 1, 4, 5),
+    (0, 2, 0, 3, 0, 3, 0, 0, 0, 2, 3, 1, 3, 0, 4, 0, 1, 1, 3, 0, 3, 4, 3, 2, 3, 1, 0, 3, 3, 2, 3, 1, 3, 0, 2, 3, 0, 2, 1, 4, 1, 2, 2, 0, 0, 3, 3, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 2, 2, 0, 3, 2, 1, 3, 3, 0, 2, 0, 2, 0, 0, 3, 3, 1, 2, 4, 0, 3, 0, 2, 2, 3),
+    (2, 4, 0, 5, 0, 4, 0, 4, 0, 2, 4, 4, 4, 3, 4, 3, 3, 3, 1, 2, 4, 3, 4, 3, 4, 4, 5, 0, 3, 3, 3, 3, 2, 0, 4, 3, 1, 4, 3, 4, 1, 4, 4, 3, 3, 4, 4, 3, 1, 2, 3, 0, 4, 2, 0, 4, 1, 0, 3, 3, 0, 4, 3, 3, 3, 4, 0, 4, 0, 2, 0, 3, 5, 3, 4, 5, 2, 0, 3, 0, 0, 4, 5),
+    (0, 3, 0, 4, 0, 1, 0, 1, 0, 1, 3, 2, 2, 1, 3, 0, 3, 0, 2, 0, 2, 0, 3, 0, 2, 0, 0, 0, 1, 0, 1, 1, 0, 0, 3, 1, 0, 0, 0, 4, 0, 3, 1, 0, 2, 1, 3, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 2, 2, 3, 1, 0, 3, 0, 0, 0, 1, 4, 4, 4, 3, 0, 0, 4, 0, 0, 1, 4),
+    (1, 4, 1, 5, 0, 3, 0, 3, 0, 4, 5, 4, 4, 3, 5, 3, 3, 4, 4, 3, 4, 1, 3, 3, 3, 3, 2, 1, 4, 1, 5, 4, 3, 1, 4, 4, 3, 5, 4, 4, 3, 5, 4, 3, 3, 4, 4, 4, 0, 3, 3, 1, 2, 3, 0, 3, 1, 0, 3, 3, 0, 5, 4, 4, 4, 4, 4, 4, 3, 3, 5, 4, 4, 3, 3, 5, 4, 0, 3, 2, 0, 4, 4),
+    (0, 2, 0, 3, 0, 1, 0, 0, 0, 1, 3, 3, 3, 2, 4, 1, 3, 0, 3, 1, 3, 0, 2, 2, 1, 1, 0, 0, 2, 0, 4, 3, 1, 0, 4, 3, 0, 4, 4, 4, 1, 4, 3, 1, 1, 3, 3, 1, 0, 2, 0, 0, 1, 3, 0, 0, 0, 0, 2, 0, 0, 4, 3, 2, 4, 3, 5, 4, 3, 3, 3, 4, 3, 3, 4, 3, 3, 0, 2, 1, 0, 3, 3),
+    (0, 2, 0, 4, 0, 3, 0, 2, 0, 2, 5, 5, 3, 4, 4, 4, 4, 1, 4, 3, 3, 0, 4, 3, 4, 3, 1, 3, 3, 2, 4, 3, 0, 3, 4, 3, 0, 3, 4, 4, 2, 4, 4, 0, 4, 5, 3, 3, 2, 2, 1, 1, 1, 2, 0, 1, 5, 0, 3, 3, 2, 4, 3, 3, 3, 4, 0, 3, 0, 2, 0, 4, 4, 3, 5, 5, 0, 0, 3, 0, 2, 3, 3),
+    (0, 3, 0, 4, 0, 3, 0, 1, 0, 3, 4, 3, 3, 1, 3, 3, 3, 0, 3, 1, 3, 0, 4, 3, 3, 1, 1, 0, 3, 0, 3, 3, 0, 0, 4, 4, 0, 1, 5, 4, 3, 3, 5, 0, 3, 3, 4, 3, 0, 2, 0, 1, 1, 1, 0, 1, 3, 0, 1, 2, 1, 3, 3, 2, 3, 3, 0, 3, 0, 1, 0, 1, 3, 3, 4, 4, 1, 0, 1, 2, 2, 1, 3),
+    (0, 1, 0, 4, 0, 4, 0, 3, 0, 1, 3, 3, 3, 2, 3, 1, 1, 0, 3, 0, 3, 3, 4, 3, 2, 4, 2, 0, 1, 0, 4, 3, 2, 0, 4, 3, 0, 5, 3, 3, 2, 4, 4, 4, 3, 3, 3, 4, 0, 1, 3, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 4, 2, 3, 3, 3, 0, 3, 0, 0, 0, 4, 4, 4, 5, 3, 2, 0, 3, 3, 0, 3, 5),
+    (0, 2, 0, 3, 0, 0, 0, 3, 0, 1, 3, 0, 2, 0, 0, 0, 1, 0, 3, 1, 1, 3, 3, 0, 0, 3, 0, 0, 3, 0, 2, 3, 1, 0, 3, 1, 0, 3, 3, 2, 0, 4, 2, 2, 0, 2, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 2, 0, 1, 0, 1, 0, 0, 0, 1, 3, 1, 2, 0, 0, 0, 1, 0, 0, 1, 4),
+    (0, 3, 0, 3, 0, 5, 0, 1, 0, 2, 4, 3, 1, 3, 3, 2, 1, 1, 5, 2, 1, 0, 5, 1, 2, 0, 0, 0, 3, 3, 2, 2, 3, 2, 4, 3, 0, 0, 3, 3, 1, 3, 3, 0, 2, 5, 3, 4, 0, 3, 3, 0, 1, 2, 0, 2, 2, 0, 3, 2, 0, 2, 2, 3, 3, 3, 0, 2, 0, 1, 0, 3, 4, 4, 2, 5, 4, 0, 3, 0, 0, 3, 5),
+    (0, 3, 0, 3, 0, 3, 0, 1, 0, 3, 3, 3, 3, 0, 3, 0, 2, 0, 2, 1, 1, 0, 2, 0, 1, 0, 0, 0, 2, 1, 0, 0, 1, 0, 3, 2, 0, 0, 3, 3, 1, 2, 3, 1, 0, 3, 3, 0, 0, 1, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 2, 3, 1, 2, 3, 0, 3, 0, 1, 0, 3, 2, 1, 0, 4, 3, 0, 1, 1, 0, 3, 3),
+    (0, 4, 0, 5, 0, 3, 0, 3, 0, 4, 5, 5, 4, 3, 5, 3, 4, 3, 5, 3, 3, 2, 5, 3, 4, 4, 4, 3, 4, 3, 4, 5, 5, 3, 4, 4, 3, 4, 4, 5, 4, 4, 4, 3, 4, 5, 5, 4, 2, 3, 4, 2, 3, 4, 0, 3, 3, 1, 4, 3, 2, 4, 3, 3, 5, 5, 0, 3, 0, 3, 0, 5, 5, 5, 5, 4, 4, 0, 4, 0, 1, 4, 4),
+    (0, 4, 0, 4, 0, 3, 0, 3, 0, 3, 5, 4, 4, 2, 3, 2, 5, 1, 3, 2, 5, 1, 4, 2, 3, 2, 3, 3, 4, 3, 3, 3, 3, 2, 5, 4, 1, 3, 3, 5, 3, 4, 4, 0, 4, 4, 3, 1, 1, 3, 1, 0, 2, 3, 0, 2, 3, 0, 3, 0, 0, 4, 3, 1, 3, 4, 0, 3, 0, 2, 0, 4, 4, 4, 3, 4, 5, 0, 4, 0, 0, 3, 4),
+    (0, 3, 0, 3, 0, 3, 1, 2, 0, 3, 4, 4, 3, 3, 3, 0, 2, 2, 4, 3, 3, 1, 3, 3, 3, 1, 1, 0, 3, 1, 4, 3, 2, 3, 4, 4, 2, 4, 4, 4, 3, 4, 4, 3, 2, 4, 4, 3, 1, 3, 3, 1, 3, 3, 0, 4, 1, 0, 2, 2, 1, 4, 3, 2, 3, 3, 5, 4, 3, 3, 5, 4, 4, 3, 3, 0, 4, 0, 3, 2, 2, 4, 4),
+    (0, 2, 0, 1, 0, 0, 0, 0, 0, 1, 2, 1, 3, 0, 0, 0, 0, 0, 2, 0, 1, 2, 1, 0, 0, 1, 0, 0, 0, 0, 3, 0, 0, 1, 0, 1, 1, 3, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 2, 2, 0, 3, 4, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1),
+    (0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 4, 0, 4, 1, 4, 0, 3, 0, 4, 0, 3, 0, 4, 0, 3, 0, 3, 0, 4, 1, 5, 1, 4, 0, 0, 3, 0, 5, 0, 5, 2, 0, 1, 0, 0, 0, 2, 1, 4, 0, 1, 3, 0, 0, 3, 0, 0, 3, 1, 1, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0),
+    (1, 4, 0, 5, 0, 3, 0, 2, 0, 3, 5, 4, 4, 3, 4, 3, 5, 3, 4, 3, 3, 0, 4, 3, 3, 3, 3, 3, 3, 2, 4, 4, 3, 1, 3, 4, 4, 5, 4, 4, 3, 4, 4, 1, 3, 5, 4, 3, 3, 3, 1, 2, 2, 3, 3, 1, 3, 1, 3, 3, 3, 5, 3, 3, 4, 5, 0, 3, 0, 3, 0, 3, 4, 3, 4, 4, 3, 0, 3, 0, 2, 4, 3),
+    (0, 1, 0, 4, 0, 0, 0, 0, 0, 1, 4, 0, 4, 1, 4, 2, 4, 0, 3, 0, 1, 0, 1, 0, 0, 0, 0, 0, 2, 0, 3, 1, 1, 1, 0, 3, 0, 0, 0, 1, 2, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 3, 0, 0, 0, 0, 3, 2, 0, 2, 2, 0, 1, 0, 0, 0, 2, 3, 2, 3, 3, 0, 0, 0, 0, 2, 1, 0),
+    (0, 5, 1, 5, 0, 3, 0, 3, 0, 5, 4, 4, 5, 1, 5, 3, 3, 0, 4, 3, 4, 3, 5, 3, 4, 3, 3, 2, 4, 3, 4, 3, 3, 0, 3, 3, 1, 4, 4, 3, 4, 4, 4, 3, 4, 5, 5, 3, 2, 3, 1, 1, 3, 3, 1, 3, 1, 1, 3, 3, 2, 4, 5, 3, 3, 5, 0, 4, 0, 3, 0, 4, 4, 3, 5, 3, 3, 0, 3, 4, 0, 4, 3),
+    (0, 5, 0, 5, 0, 3, 0, 2, 0, 4, 4, 3, 5, 2, 4, 3, 3, 3, 4, 4, 4, 3, 5, 3, 5, 3, 3, 1, 4, 0, 4, 3, 3, 0, 3, 3, 0, 4, 4, 4, 4, 5, 4, 3, 3, 5, 5, 3, 2, 3, 1, 2, 3, 2, 0, 1, 0, 0, 3, 2, 2, 4, 4, 3, 1, 5, 0, 4, 0, 3, 0, 4, 3, 1, 3, 2, 1, 0, 3, 3, 0, 3, 3),
+    (0, 4, 0, 5, 0, 5, 0, 4, 0, 4, 5, 5, 5, 3, 4, 3, 3, 2, 5, 4, 4, 3, 5, 3, 5, 3, 4, 0, 4, 3, 4, 4, 3, 2, 4, 4, 3, 4, 5, 4, 4, 5, 5, 0, 3, 5, 5, 4, 1, 3, 3, 2, 3, 3, 1, 3, 1, 0, 4, 3, 1, 4, 4, 3, 4, 5, 0, 4, 0, 2, 0, 4, 3, 4, 4, 3, 3, 0, 4, 0, 0, 5, 5),
+    (0, 4, 0, 4, 0, 5, 0, 1, 1, 3, 3, 4, 4, 3, 4, 1, 3, 0, 5, 1, 3, 0, 3, 1, 3, 1, 1, 0, 3, 0, 3, 3, 4, 0, 4, 3, 0, 4, 4, 4, 3, 4, 4, 0, 3, 5, 4, 1, 0, 3, 0, 0, 2, 3, 0, 3, 1, 0, 3, 1, 0, 3, 2, 1, 3, 5, 0, 3, 0, 1, 0, 3, 2, 3, 3, 4, 4, 0, 2, 2, 0, 4, 4),
+    (2, 4, 0, 5, 0, 4, 0, 3, 0, 4, 5, 5, 4, 3, 5, 3, 5, 3, 5, 3, 5, 2, 5, 3, 4, 3, 3, 4, 3, 4, 5, 3, 2, 1, 5, 4, 3, 2, 3, 4, 5, 3, 4, 1, 2, 5, 4, 3, 0, 3, 3, 0, 3, 2, 0, 2, 3, 0, 4, 1, 0, 3, 4, 3, 3, 5, 0, 3, 0, 1, 0, 4, 5, 5, 5, 4, 3, 0, 4, 2, 0, 3, 5),
+    (0, 5, 0, 4, 0, 4, 0, 2, 0, 5, 4, 3, 4, 3, 4, 3, 3, 3, 4, 3, 4, 2, 5, 3, 5, 3, 4, 1, 4, 3, 4, 4, 4, 0, 3, 5, 0, 4, 4, 4, 4, 5, 3, 1, 3, 4, 5, 3, 3, 3, 3, 3, 3, 3, 0, 2, 2, 0, 3, 3, 2, 4, 3, 3, 3, 5, 3, 4, 1, 3, 3, 5, 3, 2, 0, 0, 0, 0, 4, 3, 1, 3, 3),
+    (0, 1, 0, 3, 0, 3, 0, 1, 0, 1, 3, 3, 3, 2, 3, 3, 3, 0, 3, 0, 0, 0, 3, 1, 3, 0, 0, 0, 2, 2, 2, 3, 0, 0, 3, 2, 0, 1, 2, 4, 1, 3, 3, 0, 0, 3, 3, 3, 0, 1, 0, 0, 2, 1, 0, 0, 3, 0, 3, 1, 0, 3, 0, 0, 1, 3, 0, 2, 0, 1, 0, 3, 3, 1, 3, 3, 0, 0, 1, 1, 0, 3, 3),
+    (0, 2, 0, 3, 0, 2, 1, 4, 0, 2, 2, 3, 1, 1, 3, 1, 1, 0, 2, 0, 3, 1, 2, 3, 1, 3, 0, 0, 1, 0, 4, 3, 2, 3, 3, 3, 1, 4, 2, 3, 3, 3, 3, 1, 0, 3, 1, 4, 0, 1, 1, 0, 1, 2, 0, 1, 1, 0, 1, 1, 0, 3, 1, 3, 2, 2, 0, 1, 0, 0, 0, 2, 3, 3, 3, 1, 0, 0, 0, 0, 0, 2, 3),
+    (0, 5, 0, 4, 0, 5, 0, 2, 0, 4, 5, 5, 3, 3, 4, 3, 3, 1, 5, 4, 4, 2, 4, 4, 4, 3, 4, 2, 4, 3, 5, 5, 4, 3, 3, 4, 3, 3, 5, 5, 4, 5, 5, 1, 3, 4, 5, 3, 1, 4, 3, 1, 3, 3, 0, 3, 3, 1, 4, 3, 1, 4, 5, 3, 3, 5, 0, 4, 0, 3, 0, 5, 3, 3, 1, 4, 3, 0, 4, 0, 1, 5, 3),
+    (0, 5, 0, 5, 0, 4, 0, 2, 0, 4, 4, 3, 4, 3, 3, 3, 3, 3, 5, 4, 4, 4, 4, 4, 4, 5, 3, 3, 5, 2, 4, 4, 4, 3, 4, 4, 3, 3, 4, 4, 5, 5, 3, 3, 4, 3, 4, 3, 3, 4, 3, 3, 3, 3, 1, 2, 2, 1, 4, 3, 3, 5, 4, 4, 3, 4, 0, 4, 0, 3, 0, 4, 4, 4, 4, 4, 1, 0, 4, 2, 0, 2, 4),
+    (0, 4, 0, 4, 0, 3, 0, 1, 0, 3, 5, 2, 3, 0, 3, 0, 2, 1, 4, 2, 3, 3, 4, 1, 4, 3, 3, 2, 4, 1, 3, 3, 3, 0, 3, 3, 0, 0, 3, 3, 3, 5, 3, 3, 3, 3, 3, 2, 0, 2, 0, 0, 2, 0, 0, 2, 0, 0, 1, 0, 0, 3, 1, 2, 2, 3, 0, 3, 0, 2, 0, 4, 4, 3, 3, 4, 1, 0, 3, 0, 0, 2, 4),
+    (0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 2, 0, 0, 0, 0, 0, 1, 0, 2, 0, 1, 0, 0, 0, 0, 0, 3, 1, 3, 0, 3, 2, 0, 0, 0, 1, 0, 3, 2, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 2, 0, 0, 0, 0, 0, 0, 2),
+    (0, 2, 1, 3, 0, 2, 0, 2, 0, 3, 3, 3, 3, 1, 3, 1, 3, 3, 3, 3, 3, 3, 4, 2, 2, 1, 2, 1, 4, 0, 4, 3, 1, 3, 3, 3, 2, 4, 3, 5, 4, 3, 3, 3, 3, 3, 3, 3, 0, 1, 3, 0, 2, 0, 0, 1, 0, 0, 1, 0, 0, 4, 2, 0, 2, 3, 0, 3, 3, 0, 3, 3, 4, 2, 3, 1, 4, 0, 1, 2, 0, 2, 3),
+    (0, 3, 0, 3, 0, 1, 0, 3, 0, 2, 3, 3, 3, 0, 3, 1, 2, 0, 3, 3, 2, 3, 3, 2, 3, 2, 3, 1, 3, 0, 4, 3, 2, 0, 3, 3, 1, 4, 3, 3, 2, 3, 4, 3, 1, 3, 3, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 4, 1, 1, 0, 3, 0, 3, 1, 0, 2, 3, 3, 3, 3, 3, 1, 0, 0, 2, 0, 3, 3),
+    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 2, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 3, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 2, 0, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3),
+    (0, 2, 0, 3, 1, 3, 0, 3, 0, 2, 3, 3, 3, 1, 3, 1, 3, 1, 3, 1, 3, 3, 3, 1, 3, 0, 2, 3, 1, 1, 4, 3, 3, 2, 3, 3, 1, 2, 2, 4, 1, 3, 3, 0, 1, 4, 2, 3, 0, 1, 3, 0, 3, 0, 0, 1, 3, 0, 2, 0, 0, 3, 3, 2, 1, 3, 0, 3, 0, 2, 0, 3, 4, 4, 4, 3, 1, 0, 3, 0, 0, 3, 3),
+    (0, 2, 0, 1, 0, 2, 0, 0, 0, 1, 3, 2, 2, 1, 3, 0, 1, 1, 3, 0, 3, 2, 3, 1, 2, 0, 2, 0, 1, 1, 3, 3, 3, 0, 3, 3, 1, 1, 2, 3, 2, 3, 3, 1, 2, 3, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 0, 1, 0, 0, 2, 1, 2, 1, 3, 0, 3, 0, 0, 0, 3, 4, 4, 4, 3, 2, 0, 2, 0, 0, 2, 4),
+    (0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 3, 1, 0, 0, 0, 0, 0, 0, 0, 3),
+    (0, 3, 0, 3, 0, 2, 0, 3, 0, 3, 3, 3, 2, 3, 2, 2, 2, 0, 3, 1, 3, 3, 3, 2, 3, 3, 0, 0, 3, 0, 3, 2, 2, 0, 2, 3, 1, 4, 3, 4, 3, 3, 2, 3, 1, 5, 4, 4, 0, 3, 1, 2, 1, 3, 0, 3, 1, 1, 2, 0, 2, 3, 1, 3, 1, 3, 0, 3, 0, 1, 0, 3, 3, 4, 4, 2, 1, 0, 2, 1, 0, 2, 4),
+    (0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 4, 2, 5, 1, 4, 0, 2, 0, 2, 1, 3, 1, 4, 0, 2, 1, 0, 0, 2, 1, 4, 1, 1, 0, 3, 3, 0, 5, 1, 3, 2, 3, 3, 1, 0, 3, 2, 3, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 4, 0, 1, 0, 3, 0, 2, 0, 1, 0, 3, 3, 3, 4, 3, 3, 0, 0, 0, 0, 2, 3),
+    (0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 1, 0, 0, 0, 0, 0, 3),
+    (0, 1, 0, 3, 0, 4, 0, 3, 0, 2, 4, 3, 1, 0, 3, 2, 2, 1, 3, 1, 2, 2, 3, 1, 1, 1, 2, 1, 3, 0, 1, 2, 0, 1, 3, 2, 1, 3, 0, 5, 5, 1, 0, 0, 1, 3, 2, 1, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 3, 4, 0, 1, 1, 1, 3, 2, 0, 2, 0, 1, 0, 2, 3, 3, 1, 2, 3, 0, 1, 0, 1, 0, 4),
+    (0, 0, 0, 1, 0, 3, 0, 3, 0, 2, 2, 1, 0, 0, 4, 0, 3, 0, 3, 1, 3, 0, 3, 0, 3, 0, 1, 0, 3, 0, 3, 1, 3, 0, 3, 3, 0, 0, 1, 2, 1, 1, 1, 0, 1, 2, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 1, 2, 0, 0, 2, 0, 0, 0, 0, 2, 3, 3, 3, 3, 0, 0, 0, 0, 1, 4),
+    (0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 3, 1, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 0, 2, 0, 2, 3, 0, 0, 2, 2, 3, 1, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 2, 0, 0, 0, 0, 2, 3),
+    (2, 4, 0, 5, 0, 5, 0, 4, 0, 3, 4, 3, 3, 3, 4, 3, 3, 3, 4, 3, 4, 4, 5, 4, 5, 5, 5, 2, 3, 0, 5, 5, 4, 1, 5, 4, 3, 1, 5, 4, 3, 4, 4, 3, 3, 4, 3, 3, 0, 3, 2, 0, 2, 3, 0, 3, 0, 0, 3, 3, 0, 5, 3, 2, 3, 3, 0, 3, 0, 3, 0, 3, 4, 5, 4, 5, 3, 0, 4, 3, 0, 3, 4),
+    (0, 3, 0, 3, 0, 3, 0, 3, 0, 3, 3, 4, 3, 2, 3, 2, 3, 0, 4, 3, 3, 3, 3, 3, 3, 3, 3, 0, 3, 2, 4, 3, 3, 1, 3, 4, 3, 4, 4, 4, 3, 4, 4, 3, 2, 4, 4, 1, 0, 2, 0, 0, 1, 1, 0, 2, 0, 0, 3, 1, 0, 5, 3, 2, 1, 3, 0, 3, 0, 1, 2, 4, 3, 2, 4, 3, 3, 0, 3, 2, 0, 4, 4),
+    (0, 3, 0, 3, 0, 1, 0, 0, 0, 1, 4, 3, 3, 2, 3, 1, 3, 1, 4, 2, 3, 2, 4, 2, 3, 4, 3, 0, 2, 2, 3, 3, 3, 0, 3, 3, 3, 0, 3, 4, 1, 3, 3, 0, 3, 4, 3, 3, 0, 1, 1, 0, 1, 0, 0, 0, 4, 0, 3, 0, 0, 3, 1, 2, 1, 3, 0, 4, 0, 1, 0, 4, 3, 3, 4, 3, 3, 0, 2, 0, 0, 3, 3),
+    (0, 3, 0, 4, 0, 1, 0, 3, 0, 3, 4, 3, 3, 0, 3, 3, 3, 1, 3, 1, 3, 3, 4, 3, 3, 3, 0, 0, 3, 1, 5, 3, 3, 1, 3, 3, 2, 5, 4, 3, 3, 4, 5, 3, 2, 5, 3, 4, 0, 1, 0, 0, 0, 0, 0, 2, 0, 0, 1, 1, 0, 4, 2, 2, 1, 3, 0, 3, 0, 2, 0, 4, 4, 3, 5, 3, 2, 0, 1, 1, 0, 3, 4),
+    (0, 5, 0, 4, 0, 5, 0, 2, 0, 4, 4, 3, 3, 2, 3, 3, 3, 1, 4, 3, 4, 1, 5, 3, 4, 3, 4, 0, 4, 2, 4, 3, 4, 1, 5, 4, 0, 4, 4, 4, 4, 5, 4, 1, 3, 5, 4, 2, 1, 4, 1, 1, 3, 2, 0, 3, 1, 0, 3, 2, 1, 4, 3, 3, 3, 4, 0, 4, 0, 3, 0, 4, 4, 4, 3, 3, 3, 0, 4, 2, 0, 3, 4),
+    (1, 4, 0, 4, 0, 3, 0, 1, 0, 3, 3, 3, 1, 1, 3, 3, 2, 2, 3, 3, 1, 0, 3, 2, 2, 1, 2, 0, 3, 1, 2, 1, 2, 0, 3, 2, 0, 2, 2, 3, 3, 4, 3, 0, 3, 3, 1, 2, 0, 1, 1, 3, 1, 2, 0, 0, 3, 0, 1, 1, 0, 3, 2, 2, 3, 3, 0, 3, 0, 0, 0, 2, 3, 3, 4, 3, 3, 0, 1, 0, 0, 1, 4),
+    (0, 4, 0, 4, 0, 4, 0, 0, 0, 3, 4, 4, 3, 1, 4, 2, 3, 2, 3, 3, 3, 1, 4, 3, 4, 0, 3, 0, 4, 2, 3, 3, 2, 2, 5, 4, 2, 1, 3, 4, 3, 4, 3, 1, 3, 3, 4, 2, 0, 2, 1, 0, 3, 3, 0, 0, 2, 0, 3, 1, 0, 4, 4, 3, 4, 3, 0, 4, 0, 1, 0, 2, 4, 4, 4, 4, 4, 0, 3, 2, 0, 3, 3),
+    (0, 0, 0, 1, 0, 4, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 2, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 2),
+    (0, 2, 0, 3, 0, 4, 0, 4, 0, 1, 3, 3, 3, 0, 4, 0, 2, 1, 2, 1, 1, 1, 2, 0, 3, 1, 1, 0, 1, 0, 3, 1, 0, 0, 3, 3, 2, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 2, 0, 2, 2, 0, 3, 1, 0, 0, 1, 0, 1, 1, 0, 1, 2, 0, 3, 0, 0, 0, 0, 1, 0, 0, 3, 3, 4, 3, 1, 0, 1, 0, 3, 0, 2),
+    (0, 0, 0, 3, 0, 5, 0, 0, 0, 0, 1, 0, 2, 0, 3, 1, 0, 1, 3, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 2, 3, 0, 1, 4, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 3, 0, 0, 0, 0, 0, 3),
+    (0, 2, 0, 5, 0, 5, 0, 1, 0, 2, 4, 3, 3, 2, 5, 1, 3, 2, 3, 3, 3, 0, 4, 1, 2, 0, 3, 0, 4, 0, 2, 2, 1, 1, 5, 3, 0, 0, 1, 4, 2, 3, 2, 0, 3, 3, 3, 2, 0, 2, 4, 1, 1, 2, 0, 1, 1, 0, 3, 1, 0, 1, 3, 1, 2, 3, 0, 2, 0, 0, 0, 1, 3, 5, 4, 4, 4, 0, 3, 0, 0, 1, 3),
+    (0, 4, 0, 5, 0, 4, 0, 4, 0, 4, 5, 4, 3, 3, 4, 3, 3, 3, 4, 3, 4, 4, 5, 3, 4, 5, 4, 2, 4, 2, 3, 4, 3, 1, 4, 4, 1, 3, 5, 4, 4, 5, 5, 4, 4, 5, 5, 5, 2, 3, 3, 1, 4, 3, 1, 3, 3, 0, 3, 3, 1, 4, 3, 4, 4, 4, 0, 3, 0, 4, 0, 3, 3, 4, 4, 5, 0, 0, 4, 3, 0, 4, 5),
+    (0, 4, 0, 4, 0, 3, 0, 3, 0, 3, 4, 4, 4, 3, 3, 2, 4, 3, 4, 3, 4, 3, 5, 3, 4, 3, 2, 1, 4, 2, 4, 4, 3, 1, 3, 4, 2, 4, 5, 5, 3, 4, 5, 4, 1, 5, 4, 3, 0, 3, 2, 2, 3, 2, 1, 3, 1, 0, 3, 3, 3, 5, 3, 3, 3, 5, 4, 4, 2, 3, 3, 4, 3, 3, 3, 2, 1, 0, 3, 2, 1, 4, 3),
+    (0, 4, 0, 5, 0, 4, 0, 3, 0, 3, 5, 5, 3, 2, 4, 3, 4, 0, 5, 4, 4, 1, 4, 4, 4, 3, 3, 3, 4, 3, 5, 5, 2, 3, 3, 4, 1, 2, 5, 5, 3, 5, 5, 2, 3, 5, 5, 4, 0, 3, 2, 0, 3, 3, 1, 1, 5, 1, 4, 1, 0, 4, 3, 2, 3, 5, 0, 4, 0, 3, 0, 5, 4, 3, 4, 3, 0, 0, 4, 1, 0, 4, 4),
+    (1, 3, 0, 4, 0, 2, 0, 2, 0, 2, 5, 5, 3, 3, 3, 3, 3, 0, 4, 2, 3, 4, 4, 4, 3, 4, 0, 0, 3, 4, 5, 4, 3, 3, 3, 3, 2, 5, 5, 4, 5, 5, 5, 4, 3, 5, 5, 5, 1, 3, 1, 0, 1, 0, 0, 3, 2, 0, 4, 2, 0, 5, 2, 3, 2, 4, 1, 3, 0, 3, 0, 4, 5, 4, 5, 4, 3, 0, 4, 2, 0, 5, 4),
+    (0, 3, 0, 4, 0, 5, 0, 3, 0, 3, 4, 4, 3, 2, 3, 2, 3, 3, 3, 3, 3, 2, 4, 3, 3, 2, 2, 0, 3, 3, 3, 3, 3, 1, 3, 3, 3, 0, 4, 4, 3, 4, 4, 1, 1, 4, 4, 2, 0, 3, 1, 0, 1, 1, 0, 4, 1, 0, 2, 3, 1, 3, 3, 1, 3, 4, 0, 3, 0, 1, 0, 3, 1, 3, 0, 0, 1, 0, 2, 0, 0, 4, 4),
+    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+    (0, 3, 0, 3, 0, 2, 0, 3, 0, 1, 5, 4, 3, 3, 3, 1, 4, 2, 1, 2, 3, 4, 4, 2, 4, 4, 5, 0, 3, 1, 4, 3, 4, 0, 4, 3, 3, 3, 2, 3, 2, 5, 3, 4, 3, 2, 2, 3, 0, 0, 3, 0, 2, 1, 0, 1, 2, 0, 0, 0, 0, 2, 1, 1, 3, 1, 0, 2, 0, 4, 0, 3, 4, 4, 4, 5, 2, 0, 2, 0, 0, 1, 3),
+    (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 4, 2, 1, 1, 0, 1, 0, 3, 2, 0, 0, 3, 1, 1, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 0, 0, 0, 2, 0, 0, 0, 1, 4, 0, 4, 2, 1, 0, 0, 0, 0, 0, 1),
+    (0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 3, 1, 0, 0, 0, 2, 0, 2, 1, 0, 0, 1, 2, 1, 0, 1, 1, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 1, 0, 0, 0, 0, 0, 1, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2),
+    (0, 4, 0, 4, 0, 4, 0, 3, 0, 4, 4, 3, 4, 2, 4, 3, 2, 0, 4, 4, 4, 3, 5, 3, 5, 3, 3, 2, 4, 2, 4, 3, 4, 3, 1, 4, 0, 2, 3, 4, 4, 4, 3, 3, 3, 4, 4, 4, 3, 4, 1, 3, 4, 3, 2, 1, 2, 1, 3, 3, 3, 4, 4, 3, 3, 5, 0, 4, 0, 3, 0, 4, 3, 3, 3, 2, 1, 0, 3, 0, 0, 3, 3),
+    (0, 4, 0, 3, 0, 3, 0, 3, 0, 3, 5, 5, 3, 3, 3, 3, 4, 3, 4, 3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 4, 3, 5, 3, 3, 1, 3, 2, 4, 5, 5, 5, 5, 4, 3, 4, 5, 5, 3, 2, 2, 3, 3, 3, 3, 2, 3, 3, 1, 2, 3, 2, 4, 3, 3, 3, 4, 0, 4, 0, 2, 0, 4, 3, 2, 2, 1, 2, 0, 3, 0, 0, 4, 1),
+)
+# fmt: on
+
+
+class JapaneseContextAnalysis:
+    NUM_OF_CATEGORY = 6
+    DONT_KNOW = -1
+    ENOUGH_REL_THRESHOLD = 100
+    MAX_REL_THRESHOLD = 1000
+    MINIMUM_DATA_THRESHOLD = 4
+
+    def __init__(self) -> None:
+        self._total_rel = 0
+        self._rel_sample: List[int] = []
+        self._need_to_skip_char_num = 0
+        self._last_char_order = -1
+        self._done = False
+        self.reset()
+
+    def reset(self) -> None:
+        self._total_rel = 0  # total sequence received
+        # category counters, each integer counts sequence in its category
+        self._rel_sample = [0] * self.NUM_OF_CATEGORY
+        # if last byte in current buffer is not the last byte of a character,
+        # we need to know how many bytes to skip in next buffer
+        self._need_to_skip_char_num = 0
+        self._last_char_order = -1  # The order of previous char
+        # If this flag is set to True, detection is done and conclusion has
+        # been made
+        self._done = False
+
+    def feed(self, byte_str: Union[bytes, bytearray], num_bytes: int) -> None:
+        if self._done:
+            return
+
+        # The buffer we got is byte oriented, and a character may span in more than one
+        # buffers. In case the last one or two byte in last buffer is not
+        # complete, we record how many byte needed to complete that character
+        # and skip these bytes here.  We can choose to record those bytes as
+        # well and analyse the character once it is complete, but since a
+        # character will not make much difference, by simply skipping
+        # this character will simply our logic and improve performance.
+        i = self._need_to_skip_char_num
+        while i < num_bytes:
+            order, char_len = self.get_order(byte_str[i : i + 2])
+            i += char_len
+            if i > num_bytes:
+                self._need_to_skip_char_num = i - num_bytes
+                self._last_char_order = -1
+            else:
+                if (order != -1) and (self._last_char_order != -1):
+                    self._total_rel += 1
+                    if self._total_rel > self.MAX_REL_THRESHOLD:
+                        self._done = True
+                        break
+                    self._rel_sample[
+                        jp2_char_context[self._last_char_order][order]
+                    ] += 1
+                self._last_char_order = order
+
+    def got_enough_data(self) -> bool:
+        return self._total_rel > self.ENOUGH_REL_THRESHOLD
+
+    def get_confidence(self) -> float:
+        # This is just one way to calculate confidence. It works well for me.
+        if self._total_rel > self.MINIMUM_DATA_THRESHOLD:
+            return (self._total_rel - self._rel_sample[0]) / self._total_rel
+        return self.DONT_KNOW
+
+    def get_order(self, _: Union[bytes, bytearray]) -> Tuple[int, int]:
+        return -1, 1
+
+
+class SJISContextAnalysis(JapaneseContextAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._charset_name = "SHIFT_JIS"
+
+    @property
+    def charset_name(self) -> str:
+        return self._charset_name
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> Tuple[int, int]:
+        if not byte_str:
+            return -1, 1
+        # find out current char's byte length
+        first_char = byte_str[0]
+        if (0x81 <= first_char <= 0x9F) or (0xE0 <= first_char <= 0xFC):
+            char_len = 2
+            if (first_char == 0x87) or (0xFA <= first_char <= 0xFC):
+                self._charset_name = "CP932"
+        else:
+            char_len = 1
+
+        # return its order if it is hiragana
+        if len(byte_str) > 1:
+            second_char = byte_str[1]
+            if (first_char == 202) and (0x9F <= second_char <= 0xF1):
+                return second_char - 0x9F, char_len
+
+        return -1, char_len
+
+
+class EUCJPContextAnalysis(JapaneseContextAnalysis):
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> Tuple[int, int]:
+        if not byte_str:
+            return -1, 1
+        # find out current char's byte length
+        first_char = byte_str[0]
+        if (first_char == 0x8E) or (0xA1 <= first_char <= 0xFE):
+            char_len = 2
+        elif first_char == 0x8F:
+            char_len = 3
+        else:
+            char_len = 1
+
+        # return its order if it is hiragana
+        if len(byte_str) > 1:
+            second_char = byte_str[1]
+            if (first_char == 0xA4) and (0xA1 <= second_char <= 0xF3):
+                return second_char - 0xA1, char_len
+
+        return -1, char_len
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langbulgarianmodel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langbulgarianmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..994668219dd4def6404e0afd3f538b29a0e50f8b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langbulgarianmodel.py
@@ -0,0 +1,4649 @@
+from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+BULGARIAN_LANG_MODEL = {
+    63: {  # 'e'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 1,  # 'б'
+        9: 1,  # 'в'
+        20: 1,  # 'г'
+        11: 1,  # 'д'
+        3: 1,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 0,  # 'и'
+        26: 1,  # 'й'
+        12: 1,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 1,  # 'о'
+        13: 1,  # 'п'
+        7: 1,  # 'р'
+        8: 1,  # 'с'
+        5: 1,  # 'т'
+        19: 0,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    45: {  # '\xad'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 0,  # 'Л'
+        38: 1,  # 'М'
+        36: 0,  # 'Н'
+        41: 1,  # 'О'
+        30: 1,  # 'П'
+        39: 1,  # 'Р'
+        28: 1,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 0,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 0,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 0,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    31: {  # 'А'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 1,  # 'А'
+        32: 1,  # 'Б'
+        35: 2,  # 'В'
+        43: 1,  # 'Г'
+        37: 2,  # 'Д'
+        44: 2,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 2,  # 'З'
+        40: 1,  # 'И'
+        59: 1,  # 'Й'
+        33: 1,  # 'К'
+        46: 2,  # 'Л'
+        38: 1,  # 'М'
+        36: 2,  # 'Н'
+        41: 1,  # 'О'
+        30: 2,  # 'П'
+        39: 2,  # 'Р'
+        28: 2,  # 'С'
+        34: 2,  # 'Т'
+        51: 1,  # 'У'
+        48: 2,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 2,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 1,  # 'а'
+        18: 2,  # 'б'
+        9: 2,  # 'в'
+        20: 2,  # 'г'
+        11: 2,  # 'д'
+        3: 1,  # 'е'
+        23: 1,  # 'ж'
+        15: 2,  # 'з'
+        2: 0,  # 'и'
+        26: 2,  # 'й'
+        12: 2,  # 'к'
+        10: 3,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 0,  # 'о'
+        13: 2,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 2,  # 'т'
+        19: 1,  # 'у'
+        29: 2,  # 'ф'
+        25: 1,  # 'х'
+        22: 1,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    32: {  # 'Б'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 2,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 2,  # 'Д'
+        44: 1,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 2,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 2,  # 'Н'
+        41: 2,  # 'О'
+        30: 1,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 2,  # 'Т'
+        51: 1,  # 'У'
+        48: 2,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 1,  # 'Щ'
+        61: 2,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 2,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 2,  # 'р'
+        8: 1,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 2,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    35: {  # 'В'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 2,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 1,  # 'П'
+        39: 2,  # 'Р'
+        28: 2,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 2,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 2,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 2,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 2,  # 'н'
+        4: 2,  # 'о'
+        13: 1,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 2,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 2,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    43: {  # 'Г'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 2,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 0,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 0,  # 'П'
+        39: 1,  # 'Р'
+        28: 1,  # 'С'
+        34: 0,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 1,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 1,  # 'б'
+        9: 1,  # 'в'
+        20: 0,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 2,  # 'о'
+        13: 0,  # 'п'
+        7: 2,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 1,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    37: {  # 'Д'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 2,  # 'В'
+        43: 1,  # 'Г'
+        37: 2,  # 'Д'
+        44: 2,  # 'Е'
+        55: 2,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 2,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 2,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 3,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 2,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 2,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    44: {  # 'Е'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 1,  # 'Б'
+        35: 2,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 1,  # 'З'
+        40: 1,  # 'И'
+        59: 1,  # 'Й'
+        33: 2,  # 'К'
+        46: 2,  # 'Л'
+        38: 1,  # 'М'
+        36: 2,  # 'Н'
+        41: 2,  # 'О'
+        30: 1,  # 'П'
+        39: 2,  # 'Р'
+        28: 2,  # 'С'
+        34: 2,  # 'Т'
+        51: 1,  # 'У'
+        48: 2,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 2,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 1,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 0,  # 'а'
+        18: 1,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 2,  # 'д'
+        3: 0,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 0,  # 'и'
+        26: 1,  # 'й'
+        12: 2,  # 'к'
+        10: 2,  # 'л'
+        14: 2,  # 'м'
+        6: 2,  # 'н'
+        4: 0,  # 'о'
+        13: 1,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 1,  # 'т'
+        19: 1,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    55: {  # 'Ж'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 0,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 1,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 1,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 2,  # 'о'
+        13: 1,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    47: {  # 'З'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 2,  # 'Н'
+        41: 1,  # 'О'
+        30: 1,  # 'П'
+        39: 1,  # 'Р'
+        28: 1,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 0,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 2,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 1,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 1,  # 'о'
+        13: 0,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    40: {  # 'И'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 1,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 2,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 2,  # 'З'
+        40: 1,  # 'И'
+        59: 1,  # 'Й'
+        33: 2,  # 'К'
+        46: 2,  # 'Л'
+        38: 2,  # 'М'
+        36: 2,  # 'Н'
+        41: 1,  # 'О'
+        30: 1,  # 'П'
+        39: 2,  # 'Р'
+        28: 2,  # 'С'
+        34: 2,  # 'Т'
+        51: 0,  # 'У'
+        48: 1,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 1,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 2,  # 'Я'
+        1: 1,  # 'а'
+        18: 1,  # 'б'
+        9: 3,  # 'в'
+        20: 2,  # 'г'
+        11: 1,  # 'д'
+        3: 1,  # 'е'
+        23: 0,  # 'ж'
+        15: 3,  # 'з'
+        2: 0,  # 'и'
+        26: 1,  # 'й'
+        12: 1,  # 'к'
+        10: 2,  # 'л'
+        14: 2,  # 'м'
+        6: 2,  # 'н'
+        4: 0,  # 'о'
+        13: 1,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 2,  # 'т'
+        19: 0,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 1,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    59: {  # 'Й'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 1,  # 'С'
+        34: 1,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 0,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 1,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 0,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 2,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    33: {  # 'К'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 0,  # 'М'
+        36: 2,  # 'Н'
+        41: 2,  # 'О'
+        30: 2,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 1,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 2,  # 'е'
+        23: 1,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 2,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 3,  # 'р'
+        8: 1,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    46: {  # 'Л'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 2,  # 'Г'
+        37: 1,  # 'Д'
+        44: 2,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 0,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 1,  # 'П'
+        39: 0,  # 'Р'
+        28: 1,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 0,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 1,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 2,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    38: {  # 'М'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 2,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 1,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 2,  # 'л'
+        14: 0,  # 'м'
+        6: 2,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    36: {  # 'Н'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 2,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 2,  # 'Д'
+        44: 2,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 1,  # 'Й'
+        33: 2,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 1,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 2,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 1,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 0,  # 'с'
+        5: 1,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 2,  # 'ю'
+        16: 2,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    41: {  # 'О'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 1,  # 'Б'
+        35: 2,  # 'В'
+        43: 1,  # 'Г'
+        37: 2,  # 'Д'
+        44: 1,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 1,  # 'З'
+        40: 1,  # 'И'
+        59: 1,  # 'Й'
+        33: 2,  # 'К'
+        46: 2,  # 'Л'
+        38: 2,  # 'М'
+        36: 2,  # 'Н'
+        41: 2,  # 'О'
+        30: 1,  # 'П'
+        39: 2,  # 'Р'
+        28: 2,  # 'С'
+        34: 2,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 1,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 1,  # 'а'
+        18: 2,  # 'б'
+        9: 2,  # 'в'
+        20: 2,  # 'г'
+        11: 1,  # 'д'
+        3: 1,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 0,  # 'и'
+        26: 1,  # 'й'
+        12: 2,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 0,  # 'о'
+        13: 2,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 3,  # 'т'
+        19: 1,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 1,  # 'ц'
+        21: 2,  # 'ч'
+        27: 0,  # 'ш'
+        24: 2,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    30: {  # 'П'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 2,  # 'П'
+        39: 2,  # 'Р'
+        28: 2,  # 'С'
+        34: 1,  # 'Т'
+        51: 2,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 2,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 3,  # 'л'
+        14: 0,  # 'м'
+        6: 1,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 3,  # 'р'
+        8: 1,  # 'с'
+        5: 1,  # 'т'
+        19: 2,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    39: {  # 'Р'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 2,  # 'Г'
+        37: 2,  # 'Д'
+        44: 2,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 0,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 2,  # 'П'
+        39: 1,  # 'Р'
+        28: 1,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 1,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 1,  # 'с'
+        5: 0,  # 'т'
+        19: 3,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    28: {  # 'С'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 3,  # 'А'
+        32: 2,  # 'Б'
+        35: 2,  # 'В'
+        43: 1,  # 'Г'
+        37: 2,  # 'Д'
+        44: 2,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 1,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 2,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 2,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 2,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 1,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 2,  # 'к'
+        10: 3,  # 'л'
+        14: 2,  # 'м'
+        6: 1,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 2,  # 'р'
+        8: 0,  # 'с'
+        5: 3,  # 'т'
+        19: 2,  # 'у'
+        29: 2,  # 'ф'
+        25: 1,  # 'х'
+        22: 1,  # 'ц'
+        21: 1,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    34: {  # 'Т'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 2,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 2,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 2,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 2,  # 'О'
+        30: 1,  # 'П'
+        39: 2,  # 'Р'
+        28: 2,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 1,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 1,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 1,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 1,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 3,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 2,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    51: {  # 'У'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 1,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 2,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 1,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 0,  # 'О'
+        30: 1,  # 'П'
+        39: 1,  # 'Р'
+        28: 1,  # 'С'
+        34: 2,  # 'Т'
+        51: 0,  # 'У'
+        48: 1,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 1,  # 'а'
+        18: 1,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 1,  # 'д'
+        3: 2,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 2,  # 'и'
+        26: 1,  # 'й'
+        12: 2,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 2,  # 'н'
+        4: 2,  # 'о'
+        13: 1,  # 'п'
+        7: 1,  # 'р'
+        8: 2,  # 'с'
+        5: 1,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 2,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    48: {  # 'Ф'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 0,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 2,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 1,  # 'Т'
+        51: 1,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 2,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 2,  # 'о'
+        13: 0,  # 'п'
+        7: 2,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    49: {  # 'Х'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 0,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 1,  # 'П'
+        39: 1,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 1,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 0,  # 'н'
+        4: 2,  # 'о'
+        13: 0,  # 'п'
+        7: 2,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    53: {  # 'Ц'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 0,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 2,  # 'И'
+        59: 0,  # 'Й'
+        33: 2,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 1,  # 'Р'
+        28: 2,  # 'С'
+        34: 0,  # 'Т'
+        51: 1,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 2,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 1,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 1,  # 'о'
+        13: 0,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    50: {  # 'Ч'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 2,  # 'А'
+        32: 1,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 0,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 1,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 1,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 2,  # 'о'
+        13: 0,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    54: {  # 'Ш'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 1,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 1,  # 'Н'
+        41: 1,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 1,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 2,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 2,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 2,  # 'о'
+        13: 1,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    57: {  # 'Щ'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 1,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 1,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 1,  # 'о'
+        13: 0,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 1,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    61: {  # 'Ъ'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 1,  # 'Д'
+        44: 0,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 1,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 2,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 0,  # 'О'
+        30: 1,  # 'П'
+        39: 2,  # 'Р'
+        28: 1,  # 'С'
+        34: 1,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 1,  # 'Х'
+        53: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        54: 1,  # 'Ш'
+        57: 1,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 0,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 0,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 1,  # 'л'
+        14: 0,  # 'м'
+        6: 1,  # 'н'
+        4: 0,  # 'о'
+        13: 0,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    60: {  # 'Ю'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 1,  # 'Б'
+        35: 0,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 0,  # 'Е'
+        55: 1,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 0,  # 'М'
+        36: 1,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 1,  # 'Р'
+        28: 1,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 1,  # 'б'
+        9: 1,  # 'в'
+        20: 2,  # 'г'
+        11: 1,  # 'д'
+        3: 0,  # 'е'
+        23: 2,  # 'ж'
+        15: 1,  # 'з'
+        2: 1,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 0,  # 'о'
+        13: 1,  # 'п'
+        7: 1,  # 'р'
+        8: 1,  # 'с'
+        5: 1,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    56: {  # 'Я'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 1,  # 'Б'
+        35: 1,  # 'В'
+        43: 1,  # 'Г'
+        37: 1,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 1,  # 'Л'
+        38: 1,  # 'М'
+        36: 1,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 1,  # 'С'
+        34: 2,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 1,  # 'б'
+        9: 1,  # 'в'
+        20: 1,  # 'г'
+        11: 1,  # 'д'
+        3: 0,  # 'е'
+        23: 0,  # 'ж'
+        15: 1,  # 'з'
+        2: 1,  # 'и'
+        26: 1,  # 'й'
+        12: 1,  # 'к'
+        10: 1,  # 'л'
+        14: 2,  # 'м'
+        6: 2,  # 'н'
+        4: 0,  # 'о'
+        13: 2,  # 'п'
+        7: 1,  # 'р'
+        8: 1,  # 'с'
+        5: 1,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    1: {  # 'а'
+        63: 1,  # 'e'
+        45: 1,  # '\xad'
+        31: 1,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 1,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 1,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 3,  # 'ж'
+        15: 3,  # 'з'
+        2: 3,  # 'и'
+        26: 3,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 2,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 3,  # 'ф'
+        25: 3,  # 'х'
+        22: 3,  # 'ц'
+        21: 3,  # 'ч'
+        27: 3,  # 'ш'
+        24: 3,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    18: {  # 'б'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 3,  # 'в'
+        20: 1,  # 'г'
+        11: 2,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 3,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 1,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 0,  # 'т'
+        19: 3,  # 'у'
+        29: 0,  # 'ф'
+        25: 2,  # 'х'
+        22: 1,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 3,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    9: {  # 'в'
+        63: 1,  # 'e'
+        45: 1,  # '\xad'
+        31: 0,  # 'А'
+        32: 1,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 0,  # 'в'
+        20: 2,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 3,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 2,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 3,  # 'ч'
+        27: 2,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    20: {  # 'г'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 2,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 3,  # 'л'
+        14: 1,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 1,  # 'п'
+        7: 3,  # 'р'
+        8: 2,  # 'с'
+        5: 2,  # 'т'
+        19: 3,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    11: {  # 'д'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 2,  # 'б'
+        9: 3,  # 'в'
+        20: 2,  # 'г'
+        11: 2,  # 'д'
+        3: 3,  # 'е'
+        23: 3,  # 'ж'
+        15: 2,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 1,  # 'т'
+        19: 3,  # 'у'
+        29: 1,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    3: {  # 'е'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 2,  # 'е'
+        23: 3,  # 'ж'
+        15: 3,  # 'з'
+        2: 2,  # 'и'
+        26: 3,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 2,  # 'у'
+        29: 3,  # 'ф'
+        25: 3,  # 'х'
+        22: 3,  # 'ц'
+        21: 3,  # 'ч'
+        27: 3,  # 'ш'
+        24: 3,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    23: {  # 'ж'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 2,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 3,  # 'н'
+        4: 2,  # 'о'
+        13: 1,  # 'п'
+        7: 1,  # 'р'
+        8: 1,  # 'с'
+        5: 1,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 1,  # 'ц'
+        21: 1,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    15: {  # 'з'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 1,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 2,  # 'ш'
+        24: 1,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 2,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    2: {  # 'и'
+        63: 1,  # 'e'
+        45: 1,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 1,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 1,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 1,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 1,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 3,  # 'ж'
+        15: 3,  # 'з'
+        2: 3,  # 'и'
+        26: 3,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 2,  # 'у'
+        29: 3,  # 'ф'
+        25: 3,  # 'х'
+        22: 3,  # 'ц'
+        21: 3,  # 'ч'
+        27: 3,  # 'ш'
+        24: 3,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    26: {  # 'й'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 1,  # 'а'
+        18: 2,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 2,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 2,  # 'з'
+        2: 1,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 2,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 2,  # 'о'
+        13: 1,  # 'п'
+        7: 2,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 1,  # 'у'
+        29: 2,  # 'ф'
+        25: 1,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    12: {  # 'к'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 1,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 1,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 3,  # 'в'
+        20: 2,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 2,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 3,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 1,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 3,  # 'ц'
+        21: 2,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    10: {  # 'л'
+        63: 1,  # 'e'
+        45: 1,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 1,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 2,  # 'д'
+        3: 3,  # 'е'
+        23: 3,  # 'ж'
+        15: 2,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 1,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 2,  # 'п'
+        7: 2,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 2,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 2,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 2,  # 'ь'
+        42: 3,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    14: {  # 'м'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 1,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 1,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 2,  # 'к'
+        10: 3,  # 'л'
+        14: 1,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 1,  # 'т'
+        19: 3,  # 'у'
+        29: 2,  # 'ф'
+        25: 1,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 2,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    6: {  # 'н'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 1,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 2,  # 'б'
+        9: 2,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 2,  # 'ж'
+        15: 2,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 1,  # 'п'
+        7: 2,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 3,  # 'ф'
+        25: 2,  # 'х'
+        22: 3,  # 'ц'
+        21: 3,  # 'ч'
+        27: 2,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 2,  # 'ь'
+        42: 2,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    4: {  # 'о'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 2,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 3,  # 'ж'
+        15: 3,  # 'з'
+        2: 3,  # 'и'
+        26: 3,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 2,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 2,  # 'у'
+        29: 3,  # 'ф'
+        25: 3,  # 'х'
+        22: 3,  # 'ц'
+        21: 3,  # 'ч'
+        27: 3,  # 'ш'
+        24: 3,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    13: {  # 'п'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 1,  # 'й'
+        12: 2,  # 'к'
+        10: 3,  # 'л'
+        14: 1,  # 'м'
+        6: 2,  # 'н'
+        4: 3,  # 'о'
+        13: 1,  # 'п'
+        7: 3,  # 'р'
+        8: 2,  # 'с'
+        5: 2,  # 'т'
+        19: 3,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 2,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    7: {  # 'р'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 3,  # 'е'
+        23: 3,  # 'ж'
+        15: 2,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 2,  # 'п'
+        7: 1,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 2,  # 'ф'
+        25: 3,  # 'х'
+        22: 3,  # 'ц'
+        21: 2,  # 'ч'
+        27: 3,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 2,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    8: {  # 'с'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 2,  # 'б'
+        9: 3,  # 'в'
+        20: 2,  # 'г'
+        11: 2,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 1,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 2,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 2,  # 'ш'
+        24: 0,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 2,  # 'ь'
+        42: 2,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    5: {  # 'т'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 2,  # 'г'
+        11: 2,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 2,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 3,  # 'у'
+        29: 1,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 2,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 3,  # 'ъ'
+        52: 2,  # 'ь'
+        42: 2,  # 'ю'
+        16: 3,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    19: {  # 'у'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 2,  # 'е'
+        23: 3,  # 'ж'
+        15: 3,  # 'з'
+        2: 2,  # 'и'
+        26: 2,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 2,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 1,  # 'у'
+        29: 2,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 3,  # 'ч'
+        27: 3,  # 'ш'
+        24: 2,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    29: {  # 'ф'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 1,  # 'в'
+        20: 1,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 2,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 2,  # 'т'
+        19: 2,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 2,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    25: {  # 'х'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 3,  # 'в'
+        20: 0,  # 'г'
+        11: 1,  # 'д'
+        3: 2,  # 'е'
+        23: 0,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 2,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 1,  # 'п'
+        7: 3,  # 'р'
+        8: 1,  # 'с'
+        5: 2,  # 'т'
+        19: 3,  # 'у'
+        29: 0,  # 'ф'
+        25: 1,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    22: {  # 'ц'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 2,  # 'в'
+        20: 1,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 1,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 2,  # 'к'
+        10: 1,  # 'л'
+        14: 1,  # 'м'
+        6: 1,  # 'н'
+        4: 2,  # 'о'
+        13: 1,  # 'п'
+        7: 1,  # 'р'
+        8: 1,  # 'с'
+        5: 1,  # 'т'
+        19: 2,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 1,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 0,  # 'ю'
+        16: 2,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    21: {  # 'ч'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 1,  # 'б'
+        9: 3,  # 'в'
+        20: 1,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 1,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 2,  # 'л'
+        14: 2,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 2,  # 'р'
+        8: 0,  # 'с'
+        5: 2,  # 'т'
+        19: 3,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 1,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    27: {  # 'ш'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 2,  # 'в'
+        20: 0,  # 'г'
+        11: 1,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 3,  # 'к'
+        10: 2,  # 'л'
+        14: 1,  # 'м'
+        6: 3,  # 'н'
+        4: 2,  # 'о'
+        13: 2,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 1,  # 'т'
+        19: 2,  # 'у'
+        29: 1,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 1,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 2,  # 'ъ'
+        52: 1,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    24: {  # 'щ'
+        63: 1,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 3,  # 'а'
+        18: 0,  # 'б'
+        9: 1,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 3,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 3,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 2,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 1,  # 'р'
+        8: 0,  # 'с'
+        5: 2,  # 'т'
+        19: 3,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 1,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 2,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    17: {  # 'ъ'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 1,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 3,  # 'г'
+        11: 3,  # 'д'
+        3: 2,  # 'е'
+        23: 3,  # 'ж'
+        15: 3,  # 'з'
+        2: 1,  # 'и'
+        26: 2,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 3,  # 'о'
+        13: 3,  # 'п'
+        7: 3,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 1,  # 'у'
+        29: 1,  # 'ф'
+        25: 2,  # 'х'
+        22: 2,  # 'ц'
+        21: 3,  # 'ч'
+        27: 2,  # 'ш'
+        24: 3,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 2,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    52: {  # 'ь'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 1,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 0,  # 'и'
+        26: 0,  # 'й'
+        12: 1,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 1,  # 'н'
+        4: 3,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 0,  # 'с'
+        5: 1,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 1,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 1,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    42: {  # 'ю'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 1,  # 'а'
+        18: 2,  # 'б'
+        9: 1,  # 'в'
+        20: 2,  # 'г'
+        11: 2,  # 'д'
+        3: 1,  # 'е'
+        23: 2,  # 'ж'
+        15: 2,  # 'з'
+        2: 1,  # 'и'
+        26: 1,  # 'й'
+        12: 2,  # 'к'
+        10: 2,  # 'л'
+        14: 2,  # 'м'
+        6: 2,  # 'н'
+        4: 1,  # 'о'
+        13: 1,  # 'п'
+        7: 2,  # 'р'
+        8: 2,  # 'с'
+        5: 2,  # 'т'
+        19: 1,  # 'у'
+        29: 1,  # 'ф'
+        25: 1,  # 'х'
+        22: 2,  # 'ц'
+        21: 3,  # 'ч'
+        27: 1,  # 'ш'
+        24: 1,  # 'щ'
+        17: 1,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    16: {  # 'я'
+        63: 0,  # 'e'
+        45: 1,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 3,  # 'б'
+        9: 3,  # 'в'
+        20: 2,  # 'г'
+        11: 3,  # 'д'
+        3: 2,  # 'е'
+        23: 1,  # 'ж'
+        15: 2,  # 'з'
+        2: 1,  # 'и'
+        26: 2,  # 'й'
+        12: 3,  # 'к'
+        10: 3,  # 'л'
+        14: 3,  # 'м'
+        6: 3,  # 'н'
+        4: 1,  # 'о'
+        13: 2,  # 'п'
+        7: 2,  # 'р'
+        8: 3,  # 'с'
+        5: 3,  # 'т'
+        19: 1,  # 'у'
+        29: 1,  # 'ф'
+        25: 3,  # 'х'
+        22: 2,  # 'ц'
+        21: 1,  # 'ч'
+        27: 1,  # 'ш'
+        24: 2,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 1,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    58: {  # 'є'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 0,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 0,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 0,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+    62: {  # '№'
+        63: 0,  # 'e'
+        45: 0,  # '\xad'
+        31: 0,  # 'А'
+        32: 0,  # 'Б'
+        35: 0,  # 'В'
+        43: 0,  # 'Г'
+        37: 0,  # 'Д'
+        44: 0,  # 'Е'
+        55: 0,  # 'Ж'
+        47: 0,  # 'З'
+        40: 0,  # 'И'
+        59: 0,  # 'Й'
+        33: 0,  # 'К'
+        46: 0,  # 'Л'
+        38: 0,  # 'М'
+        36: 0,  # 'Н'
+        41: 0,  # 'О'
+        30: 0,  # 'П'
+        39: 0,  # 'Р'
+        28: 0,  # 'С'
+        34: 0,  # 'Т'
+        51: 0,  # 'У'
+        48: 0,  # 'Ф'
+        49: 0,  # 'Х'
+        53: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        54: 0,  # 'Ш'
+        57: 0,  # 'Щ'
+        61: 0,  # 'Ъ'
+        60: 0,  # 'Ю'
+        56: 0,  # 'Я'
+        1: 0,  # 'а'
+        18: 0,  # 'б'
+        9: 0,  # 'в'
+        20: 0,  # 'г'
+        11: 0,  # 'д'
+        3: 0,  # 'е'
+        23: 0,  # 'ж'
+        15: 0,  # 'з'
+        2: 0,  # 'и'
+        26: 0,  # 'й'
+        12: 0,  # 'к'
+        10: 0,  # 'л'
+        14: 0,  # 'м'
+        6: 0,  # 'н'
+        4: 0,  # 'о'
+        13: 0,  # 'п'
+        7: 0,  # 'р'
+        8: 0,  # 'с'
+        5: 0,  # 'т'
+        19: 0,  # 'у'
+        29: 0,  # 'ф'
+        25: 0,  # 'х'
+        22: 0,  # 'ц'
+        21: 0,  # 'ч'
+        27: 0,  # 'ш'
+        24: 0,  # 'щ'
+        17: 0,  # 'ъ'
+        52: 0,  # 'ь'
+        42: 0,  # 'ю'
+        16: 0,  # 'я'
+        58: 0,  # 'є'
+        62: 0,  # '№'
+    },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+ISO_8859_5_BULGARIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 77,  # 'A'
+    66: 90,  # 'B'
+    67: 99,  # 'C'
+    68: 100,  # 'D'
+    69: 72,  # 'E'
+    70: 109,  # 'F'
+    71: 107,  # 'G'
+    72: 101,  # 'H'
+    73: 79,  # 'I'
+    74: 185,  # 'J'
+    75: 81,  # 'K'
+    76: 102,  # 'L'
+    77: 76,  # 'M'
+    78: 94,  # 'N'
+    79: 82,  # 'O'
+    80: 110,  # 'P'
+    81: 186,  # 'Q'
+    82: 108,  # 'R'
+    83: 91,  # 'S'
+    84: 74,  # 'T'
+    85: 119,  # 'U'
+    86: 84,  # 'V'
+    87: 96,  # 'W'
+    88: 111,  # 'X'
+    89: 187,  # 'Y'
+    90: 115,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 65,  # 'a'
+    98: 69,  # 'b'
+    99: 70,  # 'c'
+    100: 66,  # 'd'
+    101: 63,  # 'e'
+    102: 68,  # 'f'
+    103: 112,  # 'g'
+    104: 103,  # 'h'
+    105: 92,  # 'i'
+    106: 194,  # 'j'
+    107: 104,  # 'k'
+    108: 95,  # 'l'
+    109: 86,  # 'm'
+    110: 87,  # 'n'
+    111: 71,  # 'o'
+    112: 116,  # 'p'
+    113: 195,  # 'q'
+    114: 85,  # 'r'
+    115: 93,  # 's'
+    116: 97,  # 't'
+    117: 113,  # 'u'
+    118: 196,  # 'v'
+    119: 197,  # 'w'
+    120: 198,  # 'x'
+    121: 199,  # 'y'
+    122: 200,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 194,  # '\x80'
+    129: 195,  # '\x81'
+    130: 196,  # '\x82'
+    131: 197,  # '\x83'
+    132: 198,  # '\x84'
+    133: 199,  # '\x85'
+    134: 200,  # '\x86'
+    135: 201,  # '\x87'
+    136: 202,  # '\x88'
+    137: 203,  # '\x89'
+    138: 204,  # '\x8a'
+    139: 205,  # '\x8b'
+    140: 206,  # '\x8c'
+    141: 207,  # '\x8d'
+    142: 208,  # '\x8e'
+    143: 209,  # '\x8f'
+    144: 210,  # '\x90'
+    145: 211,  # '\x91'
+    146: 212,  # '\x92'
+    147: 213,  # '\x93'
+    148: 214,  # '\x94'
+    149: 215,  # '\x95'
+    150: 216,  # '\x96'
+    151: 217,  # '\x97'
+    152: 218,  # '\x98'
+    153: 219,  # '\x99'
+    154: 220,  # '\x9a'
+    155: 221,  # '\x9b'
+    156: 222,  # '\x9c'
+    157: 223,  # '\x9d'
+    158: 224,  # '\x9e'
+    159: 225,  # '\x9f'
+    160: 81,  # '\xa0'
+    161: 226,  # 'Ё'
+    162: 227,  # 'Ђ'
+    163: 228,  # 'Ѓ'
+    164: 229,  # 'Є'
+    165: 230,  # 'Ѕ'
+    166: 105,  # 'І'
+    167: 231,  # 'Ї'
+    168: 232,  # 'Ј'
+    169: 233,  # 'Љ'
+    170: 234,  # 'Њ'
+    171: 235,  # 'Ћ'
+    172: 236,  # 'Ќ'
+    173: 45,  # '\xad'
+    174: 237,  # 'Ў'
+    175: 238,  # 'Џ'
+    176: 31,  # 'А'
+    177: 32,  # 'Б'
+    178: 35,  # 'В'
+    179: 43,  # 'Г'
+    180: 37,  # 'Д'
+    181: 44,  # 'Е'
+    182: 55,  # 'Ж'
+    183: 47,  # 'З'
+    184: 40,  # 'И'
+    185: 59,  # 'Й'
+    186: 33,  # 'К'
+    187: 46,  # 'Л'
+    188: 38,  # 'М'
+    189: 36,  # 'Н'
+    190: 41,  # 'О'
+    191: 30,  # 'П'
+    192: 39,  # 'Р'
+    193: 28,  # 'С'
+    194: 34,  # 'Т'
+    195: 51,  # 'У'
+    196: 48,  # 'Ф'
+    197: 49,  # 'Х'
+    198: 53,  # 'Ц'
+    199: 50,  # 'Ч'
+    200: 54,  # 'Ш'
+    201: 57,  # 'Щ'
+    202: 61,  # 'Ъ'
+    203: 239,  # 'Ы'
+    204: 67,  # 'Ь'
+    205: 240,  # 'Э'
+    206: 60,  # 'Ю'
+    207: 56,  # 'Я'
+    208: 1,  # 'а'
+    209: 18,  # 'б'
+    210: 9,  # 'в'
+    211: 20,  # 'г'
+    212: 11,  # 'д'
+    213: 3,  # 'е'
+    214: 23,  # 'ж'
+    215: 15,  # 'з'
+    216: 2,  # 'и'
+    217: 26,  # 'й'
+    218: 12,  # 'к'
+    219: 10,  # 'л'
+    220: 14,  # 'м'
+    221: 6,  # 'н'
+    222: 4,  # 'о'
+    223: 13,  # 'п'
+    224: 7,  # 'р'
+    225: 8,  # 'с'
+    226: 5,  # 'т'
+    227: 19,  # 'у'
+    228: 29,  # 'ф'
+    229: 25,  # 'х'
+    230: 22,  # 'ц'
+    231: 21,  # 'ч'
+    232: 27,  # 'ш'
+    233: 24,  # 'щ'
+    234: 17,  # 'ъ'
+    235: 75,  # 'ы'
+    236: 52,  # 'ь'
+    237: 241,  # 'э'
+    238: 42,  # 'ю'
+    239: 16,  # 'я'
+    240: 62,  # '№'
+    241: 242,  # 'ё'
+    242: 243,  # 'ђ'
+    243: 244,  # 'ѓ'
+    244: 58,  # 'є'
+    245: 245,  # 'ѕ'
+    246: 98,  # 'і'
+    247: 246,  # 'ї'
+    248: 247,  # 'ј'
+    249: 248,  # 'љ'
+    250: 249,  # 'њ'
+    251: 250,  # 'ћ'
+    252: 251,  # 'ќ'
+    253: 91,  # '§'
+    254: 252,  # 'ў'
+    255: 253,  # 'џ'
+}
+
+ISO_8859_5_BULGARIAN_MODEL = SingleByteCharSetModel(
+    charset_name="ISO-8859-5",
+    language="Bulgarian",
+    char_to_order_map=ISO_8859_5_BULGARIAN_CHAR_TO_ORDER,
+    language_model=BULGARIAN_LANG_MODEL,
+    typical_positive_ratio=0.969392,
+    keep_ascii_letters=False,
+    alphabet="АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЬЮЯабвгдежзийклмнопрстуфхцчшщъьюя",
+)
+
+WINDOWS_1251_BULGARIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 77,  # 'A'
+    66: 90,  # 'B'
+    67: 99,  # 'C'
+    68: 100,  # 'D'
+    69: 72,  # 'E'
+    70: 109,  # 'F'
+    71: 107,  # 'G'
+    72: 101,  # 'H'
+    73: 79,  # 'I'
+    74: 185,  # 'J'
+    75: 81,  # 'K'
+    76: 102,  # 'L'
+    77: 76,  # 'M'
+    78: 94,  # 'N'
+    79: 82,  # 'O'
+    80: 110,  # 'P'
+    81: 186,  # 'Q'
+    82: 108,  # 'R'
+    83: 91,  # 'S'
+    84: 74,  # 'T'
+    85: 119,  # 'U'
+    86: 84,  # 'V'
+    87: 96,  # 'W'
+    88: 111,  # 'X'
+    89: 187,  # 'Y'
+    90: 115,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 65,  # 'a'
+    98: 69,  # 'b'
+    99: 70,  # 'c'
+    100: 66,  # 'd'
+    101: 63,  # 'e'
+    102: 68,  # 'f'
+    103: 112,  # 'g'
+    104: 103,  # 'h'
+    105: 92,  # 'i'
+    106: 194,  # 'j'
+    107: 104,  # 'k'
+    108: 95,  # 'l'
+    109: 86,  # 'm'
+    110: 87,  # 'n'
+    111: 71,  # 'o'
+    112: 116,  # 'p'
+    113: 195,  # 'q'
+    114: 85,  # 'r'
+    115: 93,  # 's'
+    116: 97,  # 't'
+    117: 113,  # 'u'
+    118: 196,  # 'v'
+    119: 197,  # 'w'
+    120: 198,  # 'x'
+    121: 199,  # 'y'
+    122: 200,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 206,  # 'Ђ'
+    129: 207,  # 'Ѓ'
+    130: 208,  # '‚'
+    131: 209,  # 'ѓ'
+    132: 210,  # '„'
+    133: 211,  # '…'
+    134: 212,  # '†'
+    135: 213,  # '‡'
+    136: 120,  # '€'
+    137: 214,  # '‰'
+    138: 215,  # 'Љ'
+    139: 216,  # '‹'
+    140: 217,  # 'Њ'
+    141: 218,  # 'Ќ'
+    142: 219,  # 'Ћ'
+    143: 220,  # 'Џ'
+    144: 221,  # 'ђ'
+    145: 78,  # '‘'
+    146: 64,  # '’'
+    147: 83,  # '“'
+    148: 121,  # '”'
+    149: 98,  # '•'
+    150: 117,  # '–'
+    151: 105,  # '—'
+    152: 222,  # None
+    153: 223,  # '™'
+    154: 224,  # 'љ'
+    155: 225,  # '›'
+    156: 226,  # 'њ'
+    157: 227,  # 'ќ'
+    158: 228,  # 'ћ'
+    159: 229,  # 'џ'
+    160: 88,  # '\xa0'
+    161: 230,  # 'Ў'
+    162: 231,  # 'ў'
+    163: 232,  # 'Ј'
+    164: 233,  # '¤'
+    165: 122,  # 'Ґ'
+    166: 89,  # '¦'
+    167: 106,  # '§'
+    168: 234,  # 'Ё'
+    169: 235,  # '©'
+    170: 236,  # 'Є'
+    171: 237,  # '«'
+    172: 238,  # '¬'
+    173: 45,  # '\xad'
+    174: 239,  # '®'
+    175: 240,  # 'Ї'
+    176: 73,  # '°'
+    177: 80,  # '±'
+    178: 118,  # 'І'
+    179: 114,  # 'і'
+    180: 241,  # 'ґ'
+    181: 242,  # 'µ'
+    182: 243,  # '¶'
+    183: 244,  # '·'
+    184: 245,  # 'ё'
+    185: 62,  # '№'
+    186: 58,  # 'є'
+    187: 246,  # '»'
+    188: 247,  # 'ј'
+    189: 248,  # 'Ѕ'
+    190: 249,  # 'ѕ'
+    191: 250,  # 'ї'
+    192: 31,  # 'А'
+    193: 32,  # 'Б'
+    194: 35,  # 'В'
+    195: 43,  # 'Г'
+    196: 37,  # 'Д'
+    197: 44,  # 'Е'
+    198: 55,  # 'Ж'
+    199: 47,  # 'З'
+    200: 40,  # 'И'
+    201: 59,  # 'Й'
+    202: 33,  # 'К'
+    203: 46,  # 'Л'
+    204: 38,  # 'М'
+    205: 36,  # 'Н'
+    206: 41,  # 'О'
+    207: 30,  # 'П'
+    208: 39,  # 'Р'
+    209: 28,  # 'С'
+    210: 34,  # 'Т'
+    211: 51,  # 'У'
+    212: 48,  # 'Ф'
+    213: 49,  # 'Х'
+    214: 53,  # 'Ц'
+    215: 50,  # 'Ч'
+    216: 54,  # 'Ш'
+    217: 57,  # 'Щ'
+    218: 61,  # 'Ъ'
+    219: 251,  # 'Ы'
+    220: 67,  # 'Ь'
+    221: 252,  # 'Э'
+    222: 60,  # 'Ю'
+    223: 56,  # 'Я'
+    224: 1,  # 'а'
+    225: 18,  # 'б'
+    226: 9,  # 'в'
+    227: 20,  # 'г'
+    228: 11,  # 'д'
+    229: 3,  # 'е'
+    230: 23,  # 'ж'
+    231: 15,  # 'з'
+    232: 2,  # 'и'
+    233: 26,  # 'й'
+    234: 12,  # 'к'
+    235: 10,  # 'л'
+    236: 14,  # 'м'
+    237: 6,  # 'н'
+    238: 4,  # 'о'
+    239: 13,  # 'п'
+    240: 7,  # 'р'
+    241: 8,  # 'с'
+    242: 5,  # 'т'
+    243: 19,  # 'у'
+    244: 29,  # 'ф'
+    245: 25,  # 'х'
+    246: 22,  # 'ц'
+    247: 21,  # 'ч'
+    248: 27,  # 'ш'
+    249: 24,  # 'щ'
+    250: 17,  # 'ъ'
+    251: 75,  # 'ы'
+    252: 52,  # 'ь'
+    253: 253,  # 'э'
+    254: 42,  # 'ю'
+    255: 16,  # 'я'
+}
+
+WINDOWS_1251_BULGARIAN_MODEL = SingleByteCharSetModel(
+    charset_name="windows-1251",
+    language="Bulgarian",
+    char_to_order_map=WINDOWS_1251_BULGARIAN_CHAR_TO_ORDER,
+    language_model=BULGARIAN_LANG_MODEL,
+    typical_positive_ratio=0.969392,
+    keep_ascii_letters=False,
+    alphabet="АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЬЮЯабвгдежзийклмнопрстуфхцчшщъьюя",
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langgreekmodel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langgreekmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..cfb8639e5602578cb562ee7197d207dbb539cb74
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langgreekmodel.py
@@ -0,0 +1,4397 @@
+from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+GREEK_LANG_MODEL = {
+    60: {  # 'e'
+        60: 2,  # 'e'
+        55: 1,  # 'o'
+        58: 2,  # 't'
+        36: 1,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 1,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    55: {  # 'o'
+        60: 0,  # 'e'
+        55: 2,  # 'o'
+        58: 2,  # 't'
+        36: 1,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 1,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 1,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    58: {  # 't'
+        60: 2,  # 'e'
+        55: 1,  # 'o'
+        58: 1,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 1,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    36: {  # '·'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    61: {  # 'Ά'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 1,  # 'γ'
+        21: 2,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 1,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    46: {  # 'Έ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 2,  # 'β'
+        20: 2,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 2,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 2,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 1,  # 'σ'
+        2: 2,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 3,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    54: {  # 'Ό'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 2,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 2,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 2,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 2,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    31: {  # 'Α'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 2,  # 'Β'
+        43: 2,  # 'Γ'
+        41: 1,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 2,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 2,  # 'Κ'
+        53: 2,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 1,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 2,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 2,  # 'Υ'
+        56: 2,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 2,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 1,  # 'θ'
+        5: 0,  # 'ι'
+        11: 2,  # 'κ'
+        16: 3,  # 'λ'
+        10: 2,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 2,  # 'ς'
+        7: 2,  # 'σ'
+        2: 0,  # 'τ'
+        12: 3,  # 'υ'
+        28: 2,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    51: {  # 'Β'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 1,  # 'Ε'
+        40: 1,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 1,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 1,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 2,  # 'ή'
+        15: 0,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    43: {  # 'Γ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 1,  # 'Α'
+        51: 0,  # 'Β'
+        43: 2,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 1,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 1,  # 'Κ'
+        53: 1,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 1,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 2,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 1,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 2,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    41: {  # 'Δ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 2,  # 'ή'
+        15: 2,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 1,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    34: {  # 'Ε'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 2,  # 'Γ'
+        41: 2,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 2,  # 'Κ'
+        53: 2,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 1,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 2,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 2,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 2,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 3,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 3,  # 'γ'
+        21: 2,  # 'δ'
+        3: 1,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 1,  # 'θ'
+        5: 2,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 2,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 3,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 2,  # 'σ'
+        2: 2,  # 'τ'
+        12: 2,  # 'υ'
+        28: 2,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 1,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    40: {  # 'Η'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 1,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 2,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 2,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 2,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 1,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 1,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 1,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    52: {  # 'Θ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 1,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 1,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 2,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    47: {  # 'Ι'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 1,  # 'Β'
+        43: 1,  # 'Γ'
+        41: 2,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 2,  # 'Κ'
+        53: 2,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 2,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 2,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 1,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 2,  # 'σ'
+        2: 1,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 1,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    44: {  # 'Κ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 1,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 1,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 1,  # 'Τ'
+        45: 2,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 1,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 2,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    53: {  # 'Λ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 2,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 2,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 0,  # 'ή'
+        15: 2,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 1,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 2,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    38: {  # 'Μ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 2,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 2,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 2,  # 'ή'
+        15: 2,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 3,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 2,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    49: {  # 'Ν'
+        60: 2,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 2,  # 'έ'
+        22: 0,  # 'ή'
+        15: 2,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 1,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 1,  # 'ω'
+        19: 2,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    59: {  # 'Ξ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 1,  # 'Ε'
+        40: 1,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 1,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 2,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    39: {  # 'Ο'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 1,  # 'Β'
+        43: 2,  # 'Γ'
+        41: 2,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 1,  # 'Η'
+        52: 2,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 2,  # 'Κ'
+        53: 2,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 2,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 2,  # 'Υ'
+        56: 2,  # 'Φ'
+        50: 2,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 2,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 2,  # 'κ'
+        16: 2,  # 'λ'
+        10: 2,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 2,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 2,  # 'τ'
+        12: 2,  # 'υ'
+        28: 1,  # 'φ'
+        23: 1,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    35: {  # 'Π'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 2,  # 'Λ'
+        38: 1,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 1,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 1,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 1,  # 'έ'
+        22: 1,  # 'ή'
+        15: 2,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 2,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 2,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    48: {  # 'Ρ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 1,  # 'Γ'
+        41: 1,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 1,  # 'Τ'
+        45: 1,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 1,  # 'Χ'
+        57: 1,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 2,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 1,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 3,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 0,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    37: {  # 'Σ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 1,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 2,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 2,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 2,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 2,  # 'ή'
+        15: 2,  # 'ί'
+        1: 2,  # 'α'
+        29: 2,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 2,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 2,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 0,  # 'φ'
+        23: 2,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 0,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    33: {  # 'Τ'
+        60: 0,  # 'e'
+        55: 1,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 2,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 2,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 1,  # 'Τ'
+        45: 1,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 2,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 0,  # 'ή'
+        15: 2,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 2,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 2,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 2,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    45: {  # 'Υ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 2,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 1,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 2,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 1,  # 'Λ'
+        38: 2,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 2,  # 'Π'
+        48: 1,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 1,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 3,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    56: {  # 'Φ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 1,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 1,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 2,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 2,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 1,  # 'ύ'
+        27: 1,  # 'ώ'
+    },
+    50: {  # 'Χ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 1,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 2,  # 'Ε'
+        40: 2,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 2,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 1,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 1,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 1,  # 'Χ'
+        57: 1,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 2,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 2,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    57: {  # 'Ω'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 1,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 1,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 2,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 2,  # 'Ρ'
+        37: 2,  # 'Σ'
+        33: 2,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 2,  # 'ρ'
+        14: 2,  # 'ς'
+        7: 2,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 1,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    17: {  # 'ά'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 3,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 3,  # 'ε'
+        32: 3,  # 'ζ'
+        13: 0,  # 'η'
+        25: 3,  # 'θ'
+        5: 2,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 3,  # 'φ'
+        23: 3,  # 'χ'
+        42: 3,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    18: {  # 'έ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 3,  # 'α'
+        29: 2,  # 'β'
+        20: 3,  # 'γ'
+        21: 2,  # 'δ'
+        3: 3,  # 'ε'
+        32: 2,  # 'ζ'
+        13: 0,  # 'η'
+        25: 3,  # 'θ'
+        5: 0,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 3,  # 'φ'
+        23: 3,  # 'χ'
+        42: 3,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    22: {  # 'ή'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 1,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 3,  # 'θ'
+        5: 0,  # 'ι'
+        11: 3,  # 'κ'
+        16: 2,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    15: {  # 'ί'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 3,  # 'α'
+        29: 2,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 3,  # 'ε'
+        32: 3,  # 'ζ'
+        13: 3,  # 'η'
+        25: 3,  # 'θ'
+        5: 0,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 1,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    1: {  # 'α'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 2,  # 'έ'
+        22: 0,  # 'ή'
+        15: 3,  # 'ί'
+        1: 0,  # 'α'
+        29: 3,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 2,  # 'ε'
+        32: 3,  # 'ζ'
+        13: 1,  # 'η'
+        25: 3,  # 'θ'
+        5: 3,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 3,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 2,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    29: {  # 'β'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 2,  # 'έ'
+        22: 3,  # 'ή'
+        15: 2,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 2,  # 'γ'
+        21: 2,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 3,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 2,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    20: {  # 'γ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 3,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 3,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    21: {  # 'δ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 3,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    3: {  # 'ε'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 3,  # 'ί'
+        1: 2,  # 'α'
+        29: 3,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 2,  # 'ε'
+        32: 2,  # 'ζ'
+        13: 0,  # 'η'
+        25: 3,  # 'θ'
+        5: 3,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 3,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 2,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    32: {  # 'ζ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 2,  # 'ή'
+        15: 2,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 1,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 2,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    13: {  # 'η'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 3,  # 'γ'
+        21: 2,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 3,  # 'θ'
+        5: 0,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 2,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    25: {  # 'θ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 2,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 1,  # 'λ'
+        10: 3,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 3,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    5: {  # 'ι'
+        60: 0,  # 'e'
+        55: 1,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 1,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 0,  # 'ί'
+        1: 3,  # 'α'
+        29: 3,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 3,  # 'ε'
+        32: 2,  # 'ζ'
+        13: 3,  # 'η'
+        25: 3,  # 'θ'
+        5: 0,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    11: {  # 'κ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 3,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 2,  # 'θ'
+        5: 3,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 2,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 2,  # 'φ'
+        23: 2,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    16: {  # 'λ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 1,  # 'β'
+        20: 2,  # 'γ'
+        21: 1,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 2,  # 'θ'
+        5: 3,  # 'ι'
+        11: 2,  # 'κ'
+        16: 3,  # 'λ'
+        10: 2,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 2,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    10: {  # 'μ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 1,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 3,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 2,  # 'υ'
+        28: 3,  # 'φ'
+        23: 0,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    6: {  # 'ν'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 3,  # 'δ'
+        3: 3,  # 'ε'
+        32: 2,  # 'ζ'
+        13: 3,  # 'η'
+        25: 3,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 1,  # 'λ'
+        10: 0,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    30: {  # 'ξ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 2,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 3,  # 'τ'
+        12: 2,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 2,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 1,  # 'ώ'
+    },
+    4: {  # 'ο'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 2,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 2,  # 'α'
+        29: 3,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 3,  # 'θ'
+        5: 3,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 3,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 1,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    9: {  # 'π'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 3,  # 'λ'
+        10: 0,  # 'μ'
+        6: 2,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 2,  # 'ς'
+        7: 0,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 0,  # 'φ'
+        23: 2,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    8: {  # 'ρ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 2,  # 'β'
+        20: 3,  # 'γ'
+        21: 2,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 3,  # 'θ'
+        5: 3,  # 'ι'
+        11: 3,  # 'κ'
+        16: 1,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 2,  # 'π'
+        8: 2,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 2,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 3,  # 'φ'
+        23: 3,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    14: {  # 'ς'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 2,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 0,  # 'θ'
+        5: 0,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 0,  # 'τ'
+        12: 0,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    7: {  # 'σ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 3,  # 'β'
+        20: 0,  # 'γ'
+        21: 2,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 3,  # 'θ'
+        5: 3,  # 'ι'
+        11: 3,  # 'κ'
+        16: 2,  # 'λ'
+        10: 3,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 3,  # 'φ'
+        23: 3,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    2: {  # 'τ'
+        60: 0,  # 'e'
+        55: 2,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 2,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 3,  # 'ι'
+        11: 2,  # 'κ'
+        16: 2,  # 'λ'
+        10: 3,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 2,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    12: {  # 'υ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 3,  # 'ή'
+        15: 2,  # 'ί'
+        1: 3,  # 'α'
+        29: 2,  # 'β'
+        20: 3,  # 'γ'
+        21: 2,  # 'δ'
+        3: 2,  # 'ε'
+        32: 2,  # 'ζ'
+        13: 2,  # 'η'
+        25: 3,  # 'θ'
+        5: 2,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 3,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 2,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    28: {  # 'φ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 3,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 2,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 0,  # 'μ'
+        6: 1,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 1,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 2,  # 'ύ'
+        27: 2,  # 'ώ'
+    },
+    23: {  # 'χ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 3,  # 'ά'
+        18: 2,  # 'έ'
+        22: 3,  # 'ή'
+        15: 3,  # 'ί'
+        1: 3,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 2,  # 'θ'
+        5: 3,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 2,  # 'μ'
+        6: 3,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 0,  # 'π'
+        8: 3,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 3,  # 'τ'
+        12: 3,  # 'υ'
+        28: 0,  # 'φ'
+        23: 2,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 3,  # 'ω'
+        19: 3,  # 'ό'
+        26: 3,  # 'ύ'
+        27: 3,  # 'ώ'
+    },
+    42: {  # 'ψ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 2,  # 'ά'
+        18: 2,  # 'έ'
+        22: 1,  # 'ή'
+        15: 2,  # 'ί'
+        1: 2,  # 'α'
+        29: 0,  # 'β'
+        20: 0,  # 'γ'
+        21: 0,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 3,  # 'η'
+        25: 0,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 0,  # 'λ'
+        10: 0,  # 'μ'
+        6: 0,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 0,  # 'π'
+        8: 0,  # 'ρ'
+        14: 0,  # 'ς'
+        7: 0,  # 'σ'
+        2: 2,  # 'τ'
+        12: 1,  # 'υ'
+        28: 0,  # 'φ'
+        23: 0,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    24: {  # 'ω'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 1,  # 'ά'
+        18: 0,  # 'έ'
+        22: 2,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 2,  # 'β'
+        20: 3,  # 'γ'
+        21: 2,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 0,  # 'η'
+        25: 3,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 0,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 2,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    19: {  # 'ό'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 3,  # 'β'
+        20: 3,  # 'γ'
+        21: 3,  # 'δ'
+        3: 1,  # 'ε'
+        32: 2,  # 'ζ'
+        13: 2,  # 'η'
+        25: 2,  # 'θ'
+        5: 2,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 1,  # 'ξ'
+        4: 2,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 3,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    26: {  # 'ύ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 2,  # 'α'
+        29: 2,  # 'β'
+        20: 2,  # 'γ'
+        21: 1,  # 'δ'
+        3: 3,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 2,  # 'η'
+        25: 3,  # 'θ'
+        5: 0,  # 'ι'
+        11: 3,  # 'κ'
+        16: 3,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 2,  # 'ξ'
+        4: 3,  # 'ο'
+        9: 3,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 2,  # 'φ'
+        23: 2,  # 'χ'
+        42: 2,  # 'ψ'
+        24: 2,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+    27: {  # 'ώ'
+        60: 0,  # 'e'
+        55: 0,  # 'o'
+        58: 0,  # 't'
+        36: 0,  # '·'
+        61: 0,  # 'Ά'
+        46: 0,  # 'Έ'
+        54: 0,  # 'Ό'
+        31: 0,  # 'Α'
+        51: 0,  # 'Β'
+        43: 0,  # 'Γ'
+        41: 0,  # 'Δ'
+        34: 0,  # 'Ε'
+        40: 0,  # 'Η'
+        52: 0,  # 'Θ'
+        47: 0,  # 'Ι'
+        44: 0,  # 'Κ'
+        53: 0,  # 'Λ'
+        38: 0,  # 'Μ'
+        49: 0,  # 'Ν'
+        59: 0,  # 'Ξ'
+        39: 0,  # 'Ο'
+        35: 0,  # 'Π'
+        48: 0,  # 'Ρ'
+        37: 0,  # 'Σ'
+        33: 0,  # 'Τ'
+        45: 0,  # 'Υ'
+        56: 0,  # 'Φ'
+        50: 0,  # 'Χ'
+        57: 0,  # 'Ω'
+        17: 0,  # 'ά'
+        18: 0,  # 'έ'
+        22: 0,  # 'ή'
+        15: 0,  # 'ί'
+        1: 0,  # 'α'
+        29: 1,  # 'β'
+        20: 0,  # 'γ'
+        21: 3,  # 'δ'
+        3: 0,  # 'ε'
+        32: 0,  # 'ζ'
+        13: 1,  # 'η'
+        25: 2,  # 'θ'
+        5: 2,  # 'ι'
+        11: 0,  # 'κ'
+        16: 2,  # 'λ'
+        10: 3,  # 'μ'
+        6: 3,  # 'ν'
+        30: 1,  # 'ξ'
+        4: 0,  # 'ο'
+        9: 2,  # 'π'
+        8: 3,  # 'ρ'
+        14: 3,  # 'ς'
+        7: 3,  # 'σ'
+        2: 3,  # 'τ'
+        12: 0,  # 'υ'
+        28: 1,  # 'φ'
+        23: 1,  # 'χ'
+        42: 0,  # 'ψ'
+        24: 0,  # 'ω'
+        19: 0,  # 'ό'
+        26: 0,  # 'ύ'
+        27: 0,  # 'ώ'
+    },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+WINDOWS_1253_GREEK_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 82,  # 'A'
+    66: 100,  # 'B'
+    67: 104,  # 'C'
+    68: 94,  # 'D'
+    69: 98,  # 'E'
+    70: 101,  # 'F'
+    71: 116,  # 'G'
+    72: 102,  # 'H'
+    73: 111,  # 'I'
+    74: 187,  # 'J'
+    75: 117,  # 'K'
+    76: 92,  # 'L'
+    77: 88,  # 'M'
+    78: 113,  # 'N'
+    79: 85,  # 'O'
+    80: 79,  # 'P'
+    81: 118,  # 'Q'
+    82: 105,  # 'R'
+    83: 83,  # 'S'
+    84: 67,  # 'T'
+    85: 114,  # 'U'
+    86: 119,  # 'V'
+    87: 95,  # 'W'
+    88: 99,  # 'X'
+    89: 109,  # 'Y'
+    90: 188,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 72,  # 'a'
+    98: 70,  # 'b'
+    99: 80,  # 'c'
+    100: 81,  # 'd'
+    101: 60,  # 'e'
+    102: 96,  # 'f'
+    103: 93,  # 'g'
+    104: 89,  # 'h'
+    105: 68,  # 'i'
+    106: 120,  # 'j'
+    107: 97,  # 'k'
+    108: 77,  # 'l'
+    109: 86,  # 'm'
+    110: 69,  # 'n'
+    111: 55,  # 'o'
+    112: 78,  # 'p'
+    113: 115,  # 'q'
+    114: 65,  # 'r'
+    115: 66,  # 's'
+    116: 58,  # 't'
+    117: 76,  # 'u'
+    118: 106,  # 'v'
+    119: 103,  # 'w'
+    120: 87,  # 'x'
+    121: 107,  # 'y'
+    122: 112,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 255,  # '€'
+    129: 255,  # None
+    130: 255,  # '‚'
+    131: 255,  # 'ƒ'
+    132: 255,  # '„'
+    133: 255,  # '…'
+    134: 255,  # '†'
+    135: 255,  # '‡'
+    136: 255,  # None
+    137: 255,  # '‰'
+    138: 255,  # None
+    139: 255,  # '‹'
+    140: 255,  # None
+    141: 255,  # None
+    142: 255,  # None
+    143: 255,  # None
+    144: 255,  # None
+    145: 255,  # '‘'
+    146: 255,  # '’'
+    147: 255,  # '“'
+    148: 255,  # '”'
+    149: 255,  # '•'
+    150: 255,  # '–'
+    151: 255,  # '—'
+    152: 255,  # None
+    153: 255,  # '™'
+    154: 255,  # None
+    155: 255,  # '›'
+    156: 255,  # None
+    157: 255,  # None
+    158: 255,  # None
+    159: 255,  # None
+    160: 253,  # '\xa0'
+    161: 233,  # '΅'
+    162: 61,  # 'Ά'
+    163: 253,  # '£'
+    164: 253,  # '¤'
+    165: 253,  # '¥'
+    166: 253,  # '¦'
+    167: 253,  # '§'
+    168: 253,  # '¨'
+    169: 253,  # '©'
+    170: 253,  # None
+    171: 253,  # '«'
+    172: 253,  # '¬'
+    173: 74,  # '\xad'
+    174: 253,  # '®'
+    175: 253,  # '―'
+    176: 253,  # '°'
+    177: 253,  # '±'
+    178: 253,  # '²'
+    179: 253,  # '³'
+    180: 247,  # '΄'
+    181: 253,  # 'µ'
+    182: 253,  # '¶'
+    183: 36,  # '·'
+    184: 46,  # 'Έ'
+    185: 71,  # 'Ή'
+    186: 73,  # 'Ί'
+    187: 253,  # '»'
+    188: 54,  # 'Ό'
+    189: 253,  # '½'
+    190: 108,  # 'Ύ'
+    191: 123,  # 'Ώ'
+    192: 110,  # 'ΐ'
+    193: 31,  # 'Α'
+    194: 51,  # 'Β'
+    195: 43,  # 'Γ'
+    196: 41,  # 'Δ'
+    197: 34,  # 'Ε'
+    198: 91,  # 'Ζ'
+    199: 40,  # 'Η'
+    200: 52,  # 'Θ'
+    201: 47,  # 'Ι'
+    202: 44,  # 'Κ'
+    203: 53,  # 'Λ'
+    204: 38,  # 'Μ'
+    205: 49,  # 'Ν'
+    206: 59,  # 'Ξ'
+    207: 39,  # 'Ο'
+    208: 35,  # 'Π'
+    209: 48,  # 'Ρ'
+    210: 250,  # None
+    211: 37,  # 'Σ'
+    212: 33,  # 'Τ'
+    213: 45,  # 'Υ'
+    214: 56,  # 'Φ'
+    215: 50,  # 'Χ'
+    216: 84,  # 'Ψ'
+    217: 57,  # 'Ω'
+    218: 120,  # 'Ϊ'
+    219: 121,  # 'Ϋ'
+    220: 17,  # 'ά'
+    221: 18,  # 'έ'
+    222: 22,  # 'ή'
+    223: 15,  # 'ί'
+    224: 124,  # 'ΰ'
+    225: 1,  # 'α'
+    226: 29,  # 'β'
+    227: 20,  # 'γ'
+    228: 21,  # 'δ'
+    229: 3,  # 'ε'
+    230: 32,  # 'ζ'
+    231: 13,  # 'η'
+    232: 25,  # 'θ'
+    233: 5,  # 'ι'
+    234: 11,  # 'κ'
+    235: 16,  # 'λ'
+    236: 10,  # 'μ'
+    237: 6,  # 'ν'
+    238: 30,  # 'ξ'
+    239: 4,  # 'ο'
+    240: 9,  # 'π'
+    241: 8,  # 'ρ'
+    242: 14,  # 'ς'
+    243: 7,  # 'σ'
+    244: 2,  # 'τ'
+    245: 12,  # 'υ'
+    246: 28,  # 'φ'
+    247: 23,  # 'χ'
+    248: 42,  # 'ψ'
+    249: 24,  # 'ω'
+    250: 64,  # 'ϊ'
+    251: 75,  # 'ϋ'
+    252: 19,  # 'ό'
+    253: 26,  # 'ύ'
+    254: 27,  # 'ώ'
+    255: 253,  # None
+}
+
+WINDOWS_1253_GREEK_MODEL = SingleByteCharSetModel(
+    charset_name="windows-1253",
+    language="Greek",
+    char_to_order_map=WINDOWS_1253_GREEK_CHAR_TO_ORDER,
+    language_model=GREEK_LANG_MODEL,
+    typical_positive_ratio=0.982851,
+    keep_ascii_letters=False,
+    alphabet="ΆΈΉΊΌΎΏΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩάέήίαβγδεζηθικλμνξοπρςστυφχψωόύώ",
+)
+
+ISO_8859_7_GREEK_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 82,  # 'A'
+    66: 100,  # 'B'
+    67: 104,  # 'C'
+    68: 94,  # 'D'
+    69: 98,  # 'E'
+    70: 101,  # 'F'
+    71: 116,  # 'G'
+    72: 102,  # 'H'
+    73: 111,  # 'I'
+    74: 187,  # 'J'
+    75: 117,  # 'K'
+    76: 92,  # 'L'
+    77: 88,  # 'M'
+    78: 113,  # 'N'
+    79: 85,  # 'O'
+    80: 79,  # 'P'
+    81: 118,  # 'Q'
+    82: 105,  # 'R'
+    83: 83,  # 'S'
+    84: 67,  # 'T'
+    85: 114,  # 'U'
+    86: 119,  # 'V'
+    87: 95,  # 'W'
+    88: 99,  # 'X'
+    89: 109,  # 'Y'
+    90: 188,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 72,  # 'a'
+    98: 70,  # 'b'
+    99: 80,  # 'c'
+    100: 81,  # 'd'
+    101: 60,  # 'e'
+    102: 96,  # 'f'
+    103: 93,  # 'g'
+    104: 89,  # 'h'
+    105: 68,  # 'i'
+    106: 120,  # 'j'
+    107: 97,  # 'k'
+    108: 77,  # 'l'
+    109: 86,  # 'm'
+    110: 69,  # 'n'
+    111: 55,  # 'o'
+    112: 78,  # 'p'
+    113: 115,  # 'q'
+    114: 65,  # 'r'
+    115: 66,  # 's'
+    116: 58,  # 't'
+    117: 76,  # 'u'
+    118: 106,  # 'v'
+    119: 103,  # 'w'
+    120: 87,  # 'x'
+    121: 107,  # 'y'
+    122: 112,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 255,  # '\x80'
+    129: 255,  # '\x81'
+    130: 255,  # '\x82'
+    131: 255,  # '\x83'
+    132: 255,  # '\x84'
+    133: 255,  # '\x85'
+    134: 255,  # '\x86'
+    135: 255,  # '\x87'
+    136: 255,  # '\x88'
+    137: 255,  # '\x89'
+    138: 255,  # '\x8a'
+    139: 255,  # '\x8b'
+    140: 255,  # '\x8c'
+    141: 255,  # '\x8d'
+    142: 255,  # '\x8e'
+    143: 255,  # '\x8f'
+    144: 255,  # '\x90'
+    145: 255,  # '\x91'
+    146: 255,  # '\x92'
+    147: 255,  # '\x93'
+    148: 255,  # '\x94'
+    149: 255,  # '\x95'
+    150: 255,  # '\x96'
+    151: 255,  # '\x97'
+    152: 255,  # '\x98'
+    153: 255,  # '\x99'
+    154: 255,  # '\x9a'
+    155: 255,  # '\x9b'
+    156: 255,  # '\x9c'
+    157: 255,  # '\x9d'
+    158: 255,  # '\x9e'
+    159: 255,  # '\x9f'
+    160: 253,  # '\xa0'
+    161: 233,  # '‘'
+    162: 90,  # '’'
+    163: 253,  # '£'
+    164: 253,  # '€'
+    165: 253,  # '₯'
+    166: 253,  # '¦'
+    167: 253,  # '§'
+    168: 253,  # '¨'
+    169: 253,  # '©'
+    170: 253,  # 'ͺ'
+    171: 253,  # '«'
+    172: 253,  # '¬'
+    173: 74,  # '\xad'
+    174: 253,  # None
+    175: 253,  # '―'
+    176: 253,  # '°'
+    177: 253,  # '±'
+    178: 253,  # '²'
+    179: 253,  # '³'
+    180: 247,  # '΄'
+    181: 248,  # '΅'
+    182: 61,  # 'Ά'
+    183: 36,  # '·'
+    184: 46,  # 'Έ'
+    185: 71,  # 'Ή'
+    186: 73,  # 'Ί'
+    187: 253,  # '»'
+    188: 54,  # 'Ό'
+    189: 253,  # '½'
+    190: 108,  # 'Ύ'
+    191: 123,  # 'Ώ'
+    192: 110,  # 'ΐ'
+    193: 31,  # 'Α'
+    194: 51,  # 'Β'
+    195: 43,  # 'Γ'
+    196: 41,  # 'Δ'
+    197: 34,  # 'Ε'
+    198: 91,  # 'Ζ'
+    199: 40,  # 'Η'
+    200: 52,  # 'Θ'
+    201: 47,  # 'Ι'
+    202: 44,  # 'Κ'
+    203: 53,  # 'Λ'
+    204: 38,  # 'Μ'
+    205: 49,  # 'Ν'
+    206: 59,  # 'Ξ'
+    207: 39,  # 'Ο'
+    208: 35,  # 'Π'
+    209: 48,  # 'Ρ'
+    210: 250,  # None
+    211: 37,  # 'Σ'
+    212: 33,  # 'Τ'
+    213: 45,  # 'Υ'
+    214: 56,  # 'Φ'
+    215: 50,  # 'Χ'
+    216: 84,  # 'Ψ'
+    217: 57,  # 'Ω'
+    218: 120,  # 'Ϊ'
+    219: 121,  # 'Ϋ'
+    220: 17,  # 'ά'
+    221: 18,  # 'έ'
+    222: 22,  # 'ή'
+    223: 15,  # 'ί'
+    224: 124,  # 'ΰ'
+    225: 1,  # 'α'
+    226: 29,  # 'β'
+    227: 20,  # 'γ'
+    228: 21,  # 'δ'
+    229: 3,  # 'ε'
+    230: 32,  # 'ζ'
+    231: 13,  # 'η'
+    232: 25,  # 'θ'
+    233: 5,  # 'ι'
+    234: 11,  # 'κ'
+    235: 16,  # 'λ'
+    236: 10,  # 'μ'
+    237: 6,  # 'ν'
+    238: 30,  # 'ξ'
+    239: 4,  # 'ο'
+    240: 9,  # 'π'
+    241: 8,  # 'ρ'
+    242: 14,  # 'ς'
+    243: 7,  # 'σ'
+    244: 2,  # 'τ'
+    245: 12,  # 'υ'
+    246: 28,  # 'φ'
+    247: 23,  # 'χ'
+    248: 42,  # 'ψ'
+    249: 24,  # 'ω'
+    250: 64,  # 'ϊ'
+    251: 75,  # 'ϋ'
+    252: 19,  # 'ό'
+    253: 26,  # 'ύ'
+    254: 27,  # 'ώ'
+    255: 253,  # None
+}
+
+ISO_8859_7_GREEK_MODEL = SingleByteCharSetModel(
+    charset_name="ISO-8859-7",
+    language="Greek",
+    char_to_order_map=ISO_8859_7_GREEK_CHAR_TO_ORDER,
+    language_model=GREEK_LANG_MODEL,
+    typical_positive_ratio=0.982851,
+    keep_ascii_letters=False,
+    alphabet="ΆΈΉΊΌΎΏΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩάέήίαβγδεζηθικλμνξοπρςστυφχψωόύώ",
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langhebrewmodel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langhebrewmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..56d2975877f092ac62ad403803f6456858affcba
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langhebrewmodel.py
@@ -0,0 +1,4380 @@
+from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+HEBREW_LANG_MODEL = {
+    50: {  # 'a'
+        50: 0,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 2,  # 'l'
+        54: 2,  # 'n'
+        49: 0,  # 'o'
+        51: 2,  # 'r'
+        43: 1,  # 's'
+        44: 2,  # 't'
+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
+        2: 0,  # 'ו'
+        24: 0,  # 'ז'
+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 1,  # 'ק'
+        7: 0,  # 'ר'
+        10: 1,  # 'ש'
+        5: 0,  # 'ת'
+        32: 0,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    60: {  # 'c'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 0,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 1,  # 'l'
+        54: 0,  # 'n'
+        49: 1,  # 'o'
+        51: 1,  # 'r'
+        43: 1,  # 's'
+        44: 2,  # 't'
+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
+        2: 0,  # 'ו'
+        24: 0,  # 'ז'
+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 1,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 0,  # 'ר'
+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    61: {  # 'd'
+        50: 1,  # 'a'
+        60: 0,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 1,  # 'l'
+        54: 1,  # 'n'
+        49: 2,  # 'o'
+        51: 1,  # 'r'
+        43: 1,  # 's'
+        44: 0,  # 't'
+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
+        2: 0,  # 'ו'
+        24: 0,  # 'ז'
+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 0,  # 'ר'
+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
+        32: 1,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    42: {  # 'e'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 2,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 2,  # 'l'
+        54: 2,  # 'n'
+        49: 1,  # 'o'
+        51: 2,  # 'r'
+        43: 2,  # 's'
+        44: 2,  # 't'
+        63: 1,  # 'u'
+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 0,  # 'ו'
+        24: 0,  # 'ז'
+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 0,  # 'ר'
+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
+        32: 1,  # '–'
+        52: 2,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    53: {  # 'i'
+        50: 1,  # 'a'
+        60: 2,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
+        53: 0,  # 'i'
+        56: 1,  # 'l'
+        54: 2,  # 'n'
+        49: 2,  # 'o'
+        51: 1,  # 'r'
+        43: 2,  # 's'
+        44: 2,  # 't'
+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 0,  # 'ו'
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+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 0,  # 'ר'
+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
+        32: 0,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    56: {  # 'l'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 2,  # 'e'
+        53: 2,  # 'i'
+        56: 2,  # 'l'
+        54: 1,  # 'n'
+        49: 1,  # 'o'
+        51: 0,  # 'r'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 0,  # 'ו'
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+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 0,  # 'ר'
+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
+        32: 0,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    54: {  # 'n'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 1,  # 'l'
+        54: 1,  # 'n'
+        49: 1,  # 'o'
+        51: 0,  # 'r'
+        43: 1,  # 's'
+        44: 2,  # 't'
+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
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+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
+        2: 0,  # 'ו'
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+        14: 0,  # 'ח'
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+        1: 0,  # 'י'
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+        15: 0,  # 'כ'
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+        6: 0,  # 'מ'
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+        12: 0,  # 'נ'
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+        13: 0,  # 'ע'
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+        18: 0,  # 'פ'
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+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
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+        5: 0,  # 'ת'
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+        52: 2,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    49: {  # 'o'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
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+        56: 1,  # 'l'
+        54: 2,  # 'n'
+        49: 1,  # 'o'
+        51: 2,  # 'r'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
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+        33: 0,  # 'ִ'
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+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 0,  # 'ו'
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+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
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+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 0,  # 'ר'
+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
+        32: 0,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    51: {  # 'r'
+        50: 2,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 2,  # 'e'
+        53: 1,  # 'i'
+        56: 1,  # 'l'
+        54: 1,  # 'n'
+        49: 2,  # 'o'
+        51: 1,  # 'r'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
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+        28: 0,  # 'ּ'
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+        9: 0,  # 'א'
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+        16: 0,  # 'ד'
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+        1: 0,  # 'י'
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+        12: 0,  # 'נ'
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+        13: 0,  # 'ע'
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+        18: 0,  # 'פ'
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+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
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+        5: 0,  # 'ת'
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+        52: 2,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    43: {  # 's'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
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+        42: 2,  # 'e'
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+        54: 1,  # 'n'
+        49: 1,  # 'o'
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+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
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+        33: 0,  # 'ִ'
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+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
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+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
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+        14: 0,  # 'ח'
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+        1: 0,  # 'י'
+        25: 0,  # 'ך'
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+        12: 0,  # 'נ'
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+        13: 0,  # 'ע'
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+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
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+        10: 0,  # 'ש'
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+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 2,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    44: {  # 't'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
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+        42: 2,  # 'e'
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+        56: 1,  # 'l'
+        54: 0,  # 'n'
+        49: 1,  # 'o'
+        51: 1,  # 'r'
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+        44: 1,  # 't'
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+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
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+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
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+        14: 0,  # 'ח'
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+        1: 0,  # 'י'
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+        18: 0,  # 'פ'
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+        17: 0,  # 'ק'
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+        52: 2,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    63: {  # 'u'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
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+        54: 1,  # 'n'
+        49: 0,  # 'o'
+        51: 1,  # 'r'
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+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
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+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
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+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
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+        12: 0,  # 'נ'
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+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    34: {  # '\xa0'
+        50: 1,  # 'a'
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+        34: 2,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
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+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
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+        46: 0,  # '”'
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+        40: 0,  # '…'
+    },
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+        46: 0,  # '”'
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+        40: 0,  # '…'
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+        40: 0,  # '…'
+    },
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+        39: 0,  # '½'
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+        20: 1,  # 'ג'
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+        1: 1,  # 'י'
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+        58: 0,  # '†'
+        40: 0,  # '…'
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+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
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+        39: 0,  # '½'
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+        58: 0,  # '†'
+        40: 0,  # '…'
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+        40: 0,  # '…'
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+        9: 2,  # 'א'
+        8: 2,  # 'ב'
+        20: 2,  # 'ג'
+        16: 2,  # 'ד'
+        3: 2,  # 'ה'
+        2: 1,  # 'ו'
+        24: 2,  # 'ז'
+        14: 2,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
+        25: 1,  # 'ך'
+        15: 2,  # 'כ'
+        4: 2,  # 'ל'
+        11: 2,  # 'ם'
+        6: 2,  # 'מ'
+        23: 2,  # 'ן'
+        12: 2,  # 'נ'
+        19: 2,  # 'ס'
+        13: 2,  # 'ע'
+        26: 2,  # 'ף'
+        18: 2,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 2,  # 'ק'
+        7: 2,  # 'ר'
+        10: 2,  # 'ש'
+        5: 2,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    29: {  # 'ָ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 1,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 1,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 2,  # 'ב'
+        20: 2,  # 'ג'
+        16: 2,  # 'ד'
+        3: 3,  # 'ה'
+        2: 2,  # 'ו'
+        24: 2,  # 'ז'
+        14: 2,  # 'ח'
+        22: 1,  # 'ט'
+        1: 2,  # 'י'
+        25: 2,  # 'ך'
+        15: 2,  # 'כ'
+        4: 2,  # 'ל'
+        11: 2,  # 'ם'
+        6: 2,  # 'מ'
+        23: 2,  # 'ן'
+        12: 2,  # 'נ'
+        19: 1,  # 'ס'
+        13: 2,  # 'ע'
+        26: 1,  # 'ף'
+        18: 2,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 2,  # 'ק'
+        7: 2,  # 'ר'
+        10: 2,  # 'ש'
+        5: 2,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    35: {  # 'ֹ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 2,  # 'ב'
+        20: 1,  # 'ג'
+        16: 2,  # 'ד'
+        3: 2,  # 'ה'
+        2: 1,  # 'ו'
+        24: 1,  # 'ז'
+        14: 1,  # 'ח'
+        22: 1,  # 'ט'
+        1: 1,  # 'י'
+        25: 1,  # 'ך'
+        15: 2,  # 'כ'
+        4: 2,  # 'ל'
+        11: 2,  # 'ם'
+        6: 2,  # 'מ'
+        23: 2,  # 'ן'
+        12: 2,  # 'נ'
+        19: 2,  # 'ס'
+        13: 2,  # 'ע'
+        26: 1,  # 'ף'
+        18: 2,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 2,  # 'ק'
+        7: 2,  # 'ר'
+        10: 2,  # 'ש'
+        5: 2,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    62: {  # 'ֻ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
+        8: 1,  # 'ב'
+        20: 1,  # 'ג'
+        16: 1,  # 'ד'
+        3: 1,  # 'ה'
+        2: 1,  # 'ו'
+        24: 1,  # 'ז'
+        14: 1,  # 'ח'
+        22: 0,  # 'ט'
+        1: 1,  # 'י'
+        25: 0,  # 'ך'
+        15: 1,  # 'כ'
+        4: 2,  # 'ל'
+        11: 1,  # 'ם'
+        6: 1,  # 'מ'
+        23: 1,  # 'ן'
+        12: 1,  # 'נ'
+        19: 1,  # 'ס'
+        13: 1,  # 'ע'
+        26: 0,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 1,  # 'צ'
+        17: 1,  # 'ק'
+        7: 1,  # 'ר'
+        10: 1,  # 'ש'
+        5: 1,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    28: {  # 'ּ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 3,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 1,  # 'ֲ'
+        33: 3,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 3,  # 'ַ'
+        29: 3,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 2,  # 'ׁ'
+        45: 1,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 2,  # 'ב'
+        20: 1,  # 'ג'
+        16: 2,  # 'ד'
+        3: 1,  # 'ה'
+        2: 2,  # 'ו'
+        24: 1,  # 'ז'
+        14: 1,  # 'ח'
+        22: 1,  # 'ט'
+        1: 2,  # 'י'
+        25: 2,  # 'ך'
+        15: 2,  # 'כ'
+        4: 2,  # 'ל'
+        11: 1,  # 'ם'
+        6: 2,  # 'מ'
+        23: 1,  # 'ן'
+        12: 2,  # 'נ'
+        19: 1,  # 'ס'
+        13: 2,  # 'ע'
+        26: 1,  # 'ף'
+        18: 1,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 1,  # 'צ'
+        17: 1,  # 'ק'
+        7: 2,  # 'ר'
+        10: 2,  # 'ש'
+        5: 2,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    38: {  # 'ׁ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
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+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
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+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 2,  # 'ו'
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+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 1,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
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+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
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+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 1,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
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+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
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+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    45: {  # 'ׂ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
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+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 1,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 1,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 0,  # 'ב'
+        20: 1,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
+        2: 2,  # 'ו'
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+        14: 1,  # 'ח'
+        22: 0,  # 'ט'
+        1: 1,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
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+        11: 1,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 1,  # 'נ'
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+        13: 1,  # 'ע'
+        26: 0,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 1,  # 'ר'
+        10: 0,  # 'ש'
+        5: 1,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    9: {  # 'א'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 1,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 2,  # 'ֱ'
+        41: 2,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 3,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 2,  # 'ע'
+        26: 3,  # 'ף'
+        18: 3,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    8: {  # 'ב'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 1,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
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+        33: 2,  # 'ִ'
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+        36: 2,  # 'ֶ'
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+        62: 1,  # 'ֻ'
+        28: 3,  # 'ּ'
+        38: 0,  # 'ׁ'
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+        9: 3,  # 'א'
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+        3: 3,  # 'ה'
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+        1: 3,  # 'י'
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+        6: 3,  # 'מ'
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+        13: 3,  # 'ע'
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+        18: 3,  # 'פ'
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+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
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+        5: 3,  # 'ת'
+        32: 1,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    20: {  # 'ג'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
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+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 2,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 1,  # 'ִ'
+        37: 1,  # 'ֵ'
+        36: 1,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 3,  # 'ב'
+        20: 2,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
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+        14: 2,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
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+        15: 1,  # 'כ'
+        4: 3,  # 'ל'
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+        6: 3,  # 'מ'
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+        12: 3,  # 'נ'
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+        18: 2,  # 'פ'
+        27: 1,  # 'ץ'
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+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    16: {  # 'ד'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
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+        54: 0,  # 'n'
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+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 1,  # 'ז'
+        14: 2,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
+        25: 2,  # 'ך'
+        15: 2,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 2,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    3: {  # 'ה'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 1,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 1,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 1,  # 'ְ'
+        59: 1,  # 'ֱ'
+        41: 2,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 3,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 1,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 0,  # 'ף'
+        18: 3,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 1,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    2: {  # 'ו'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 1,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 1,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 1,  # 'ֵ'
+        36: 1,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 3,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 3,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 3,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 3,  # 'ף'
+        18: 3,  # 'פ'
+        27: 3,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 1,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    24: {  # 'ז'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 1,  # 'ֲ'
+        33: 1,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 2,  # 'ב'
+        20: 2,  # 'ג'
+        16: 2,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 2,  # 'ז'
+        14: 2,  # 'ח'
+        22: 1,  # 'ט'
+        1: 3,  # 'י'
+        25: 1,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 2,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 2,  # 'נ'
+        19: 1,  # 'ס'
+        13: 2,  # 'ע'
+        26: 1,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 1,  # 'ש'
+        5: 2,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    14: {  # 'ח'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
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+        49: 0,  # 'o'
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+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 1,  # 'ֱ'
+        41: 2,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 3,  # 'ב'
+        20: 2,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 2,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
+        25: 1,  # 'ך'
+        15: 2,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 1,  # 'ע'
+        26: 2,  # 'ף'
+        18: 2,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
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+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    22: {  # 'ט'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
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+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 1,  # 'ֵ'
+        36: 1,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 1,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 1,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 1,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 2,  # 'ז'
+        14: 3,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
+        25: 1,  # 'ך'
+        15: 2,  # 'כ'
+        4: 3,  # 'ל'
+        11: 2,  # 'ם'
+        6: 2,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 2,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 2,  # 'ק'
+        7: 3,  # 'ר'
+        10: 2,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    1: {  # 'י'
+        50: 0,  # 'a'
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+        61: 0,  # 'd'
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+        51: 0,  # 'r'
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+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 1,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 1,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
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+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 3,  # 'ך'
+        15: 3,  # 'כ'
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+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
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+        13: 3,  # 'ע'
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+        18: 3,  # 'פ'
+        27: 3,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
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+        32: 1,  # '–'
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+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    25: {  # 'ך'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
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+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 1,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
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+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
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+        14: 1,  # 'ח'
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+        1: 0,  # 'י'
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+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
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+        10: 1,  # 'ש'
+        5: 0,  # 'ת'
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+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    15: {  # 'כ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
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+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
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+        28: 3,  # 'ּ'
+        38: 0,  # 'ׁ'
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+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 2,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
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+        14: 3,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
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+        6: 3,  # 'מ'
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+        12: 3,  # 'נ'
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+        13: 2,  # 'ע'
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+        18: 3,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 2,  # 'ק'
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+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    4: {  # 'ל'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 3,  # 'ְ'
+        59: 0,  # 'ֱ'
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+        33: 2,  # 'ִ'
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+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 3,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 1,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    11: {  # 'ם'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 1,  # 'ב'
+        20: 1,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
+        2: 1,  # 'ו'
+        24: 1,  # 'ז'
+        14: 1,  # 'ח'
+        22: 0,  # 'ט'
+        1: 1,  # 'י'
+        25: 0,  # 'ך'
+        15: 1,  # 'כ'
+        4: 1,  # 'ל'
+        11: 1,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 1,  # 'נ'
+        19: 0,  # 'ס'
+        13: 1,  # 'ע'
+        26: 0,  # 'ף'
+        18: 1,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 1,  # 'צ'
+        17: 1,  # 'ק'
+        7: 1,  # 'ר'
+        10: 1,  # 'ש'
+        5: 1,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    6: {  # 'מ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 2,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 0,  # 'ף'
+        18: 3,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    23: {  # 'ן'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 1,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 1,  # 'ב'
+        20: 1,  # 'ג'
+        16: 1,  # 'ד'
+        3: 1,  # 'ה'
+        2: 1,  # 'ו'
+        24: 0,  # 'ז'
+        14: 1,  # 'ח'
+        22: 1,  # 'ט'
+        1: 1,  # 'י'
+        25: 0,  # 'ך'
+        15: 1,  # 'כ'
+        4: 1,  # 'ל'
+        11: 1,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 1,  # 'נ'
+        19: 1,  # 'ס'
+        13: 1,  # 'ע'
+        26: 1,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 1,  # 'ק'
+        7: 1,  # 'ר'
+        10: 1,  # 'ש'
+        5: 1,  # 'ת'
+        32: 1,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    12: {  # 'נ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 2,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    19: {  # 'ס'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 1,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 1,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 2,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 1,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 2,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 2,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 2,  # 'ס'
+        13: 3,  # 'ע'
+        26: 3,  # 'ף'
+        18: 3,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 1,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    13: {  # 'ע'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 1,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 1,  # 'ְ'
+        59: 1,  # 'ֱ'
+        41: 2,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 2,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 1,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 2,  # 'ך'
+        15: 2,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 2,  # 'ע'
+        26: 1,  # 'ף'
+        18: 2,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    26: {  # 'ף'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 1,  # 'ו'
+        24: 0,  # 'ז'
+        14: 1,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 1,  # 'כ'
+        4: 1,  # 'ל'
+        11: 0,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 1,  # 'ס'
+        13: 0,  # 'ע'
+        26: 1,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 1,  # 'ק'
+        7: 1,  # 'ר'
+        10: 1,  # 'ש'
+        5: 0,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    18: {  # 'פ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 1,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 1,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 2,  # 'ב'
+        20: 3,  # 'ג'
+        16: 2,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 2,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 2,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 2,  # 'ם'
+        6: 2,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 2,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    27: {  # 'ץ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 0,  # 'ו'
+        24: 0,  # 'ז'
+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 1,  # 'ל'
+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 1,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 1,  # 'ר'
+        10: 0,  # 'ש'
+        5: 1,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    21: {  # 'צ'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 1,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 2,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 1,  # 'ז'
+        14: 3,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
+        25: 1,  # 'ך'
+        15: 1,  # 'כ'
+        4: 3,  # 'ל'
+        11: 2,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 1,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 0,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    17: {  # 'ק'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 1,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 1,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 2,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 2,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 1,  # 'ך'
+        15: 1,  # 'כ'
+        4: 3,  # 'ל'
+        11: 2,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 2,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 2,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    7: {  # 'ר'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 2,  # '´'
+        48: 1,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 1,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 2,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 3,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 3,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 3,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 3,  # 'ץ'
+        21: 3,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    10: {  # 'ש'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
+        43: 0,  # 's'
+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 1,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 1,  # 'ִ'
+        37: 1,  # 'ֵ'
+        36: 1,  # 'ֶ'
+        31: 1,  # 'ַ'
+        29: 1,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 3,  # 'ׁ'
+        45: 2,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 3,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 2,  # 'ז'
+        14: 3,  # 'ח'
+        22: 3,  # 'ט'
+        1: 3,  # 'י'
+        25: 3,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 2,  # 'ן'
+        12: 3,  # 'נ'
+        19: 2,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 1,  # '…'
+    },
+    5: {  # 'ת'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        44: 0,  # 't'
+        63: 0,  # 'u'
+        34: 1,  # '\xa0'
+        55: 0,  # '´'
+        48: 1,  # '¼'
+        39: 1,  # '½'
+        57: 0,  # '¾'
+        30: 2,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 2,  # 'ִ'
+        37: 2,  # 'ֵ'
+        36: 2,  # 'ֶ'
+        31: 2,  # 'ַ'
+        29: 2,  # 'ָ'
+        35: 1,  # 'ֹ'
+        62: 1,  # 'ֻ'
+        28: 2,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 3,  # 'א'
+        8: 3,  # 'ב'
+        20: 3,  # 'ג'
+        16: 2,  # 'ד'
+        3: 3,  # 'ה'
+        2: 3,  # 'ו'
+        24: 2,  # 'ז'
+        14: 3,  # 'ח'
+        22: 2,  # 'ט'
+        1: 3,  # 'י'
+        25: 2,  # 'ך'
+        15: 3,  # 'כ'
+        4: 3,  # 'ל'
+        11: 3,  # 'ם'
+        6: 3,  # 'מ'
+        23: 3,  # 'ן'
+        12: 3,  # 'נ'
+        19: 2,  # 'ס'
+        13: 3,  # 'ע'
+        26: 2,  # 'ף'
+        18: 3,  # 'פ'
+        27: 1,  # 'ץ'
+        21: 2,  # 'צ'
+        17: 3,  # 'ק'
+        7: 3,  # 'ר'
+        10: 3,  # 'ש'
+        5: 3,  # 'ת'
+        32: 1,  # '–'
+        52: 1,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+    32: {  # '–'
+        50: 0,  # 'a'
+        60: 0,  # 'c'
+        61: 0,  # 'd'
+        42: 0,  # 'e'
+        53: 0,  # 'i'
+        56: 0,  # 'l'
+        54: 1,  # 'n'
+        49: 0,  # 'o'
+        51: 0,  # 'r'
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+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 1,  # 'ב'
+        20: 1,  # 'ג'
+        16: 1,  # 'ד'
+        3: 1,  # 'ה'
+        2: 1,  # 'ו'
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+        14: 1,  # 'ח'
+        22: 0,  # 'ט'
+        1: 1,  # 'י'
+        25: 0,  # 'ך'
+        15: 1,  # 'כ'
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+        11: 0,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 1,  # 'ס'
+        13: 1,  # 'ע'
+        26: 0,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 1,  # 'צ'
+        17: 0,  # 'ק'
+        7: 1,  # 'ר'
+        10: 1,  # 'ש'
+        5: 1,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    52: {  # '’'
+        50: 1,  # 'a'
+        60: 0,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 1,  # 'l'
+        54: 0,  # 'n'
+        49: 0,  # 'o'
+        51: 1,  # 'r'
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+        44: 2,  # 't'
+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
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+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 0,  # 'א'
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+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 1,  # 'ו'
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+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
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+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
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+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
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+        10: 0,  # 'ש'
+        5: 1,  # 'ת'
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+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    47: {  # '“'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 1,  # 'l'
+        54: 1,  # 'n'
+        49: 1,  # 'o'
+        51: 1,  # 'r'
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+        63: 1,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
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+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
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+        9: 2,  # 'א'
+        8: 1,  # 'ב'
+        20: 1,  # 'ג'
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+        1: 1,  # 'י'
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+        18: 1,  # 'פ'
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+        21: 1,  # 'צ'
+        17: 1,  # 'ק'
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+        5: 1,  # 'ת'
+        32: 0,  # '–'
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+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    46: {  # '”'
+        50: 0,  # 'a'
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+        61: 0,  # 'd'
+        42: 0,  # 'e'
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+        34: 0,  # '\xa0'
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+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
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+        33: 0,  # 'ִ'
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+        28: 0,  # 'ּ'
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+        9: 1,  # 'א'
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+        20: 1,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
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+        14: 0,  # 'ח'
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+        1: 1,  # 'י'
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+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 1,  # 'צ'
+        17: 0,  # 'ק'
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+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 0,  # '†'
+        40: 0,  # '…'
+    },
+    58: {  # '†'
+        50: 0,  # 'a'
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+        54: 0,  # 'n'
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+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
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+        30: 0,  # 'ְ'
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+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
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+        9: 0,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 0,  # 'ה'
+        2: 0,  # 'ו'
+        24: 0,  # 'ז'
+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 0,  # 'י'
+        25: 0,  # 'ך'
+        15: 0,  # 'כ'
+        4: 0,  # 'ל'
+        11: 0,  # 'ם'
+        6: 0,  # 'מ'
+        23: 0,  # 'ן'
+        12: 0,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 0,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 0,  # 'ר'
+        10: 0,  # 'ש'
+        5: 0,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 0,  # '”'
+        58: 2,  # '†'
+        40: 0,  # '…'
+    },
+    40: {  # '…'
+        50: 1,  # 'a'
+        60: 1,  # 'c'
+        61: 1,  # 'd'
+        42: 1,  # 'e'
+        53: 1,  # 'i'
+        56: 0,  # 'l'
+        54: 1,  # 'n'
+        49: 0,  # 'o'
+        51: 1,  # 'r'
+        43: 1,  # 's'
+        44: 1,  # 't'
+        63: 0,  # 'u'
+        34: 0,  # '\xa0'
+        55: 0,  # '´'
+        48: 0,  # '¼'
+        39: 0,  # '½'
+        57: 0,  # '¾'
+        30: 0,  # 'ְ'
+        59: 0,  # 'ֱ'
+        41: 0,  # 'ֲ'
+        33: 0,  # 'ִ'
+        37: 0,  # 'ֵ'
+        36: 0,  # 'ֶ'
+        31: 0,  # 'ַ'
+        29: 0,  # 'ָ'
+        35: 0,  # 'ֹ'
+        62: 0,  # 'ֻ'
+        28: 0,  # 'ּ'
+        38: 0,  # 'ׁ'
+        45: 0,  # 'ׂ'
+        9: 1,  # 'א'
+        8: 0,  # 'ב'
+        20: 0,  # 'ג'
+        16: 0,  # 'ד'
+        3: 1,  # 'ה'
+        2: 1,  # 'ו'
+        24: 1,  # 'ז'
+        14: 0,  # 'ח'
+        22: 0,  # 'ט'
+        1: 1,  # 'י'
+        25: 0,  # 'ך'
+        15: 1,  # 'כ'
+        4: 1,  # 'ל'
+        11: 0,  # 'ם'
+        6: 1,  # 'מ'
+        23: 0,  # 'ן'
+        12: 1,  # 'נ'
+        19: 0,  # 'ס'
+        13: 0,  # 'ע'
+        26: 0,  # 'ף'
+        18: 1,  # 'פ'
+        27: 0,  # 'ץ'
+        21: 0,  # 'צ'
+        17: 0,  # 'ק'
+        7: 1,  # 'ר'
+        10: 1,  # 'ש'
+        5: 1,  # 'ת'
+        32: 0,  # '–'
+        52: 0,  # '’'
+        47: 0,  # '“'
+        46: 1,  # '”'
+        58: 0,  # '†'
+        40: 2,  # '…'
+    },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+WINDOWS_1255_HEBREW_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 69,  # 'A'
+    66: 91,  # 'B'
+    67: 79,  # 'C'
+    68: 80,  # 'D'
+    69: 92,  # 'E'
+    70: 89,  # 'F'
+    71: 97,  # 'G'
+    72: 90,  # 'H'
+    73: 68,  # 'I'
+    74: 111,  # 'J'
+    75: 112,  # 'K'
+    76: 82,  # 'L'
+    77: 73,  # 'M'
+    78: 95,  # 'N'
+    79: 85,  # 'O'
+    80: 78,  # 'P'
+    81: 121,  # 'Q'
+    82: 86,  # 'R'
+    83: 71,  # 'S'
+    84: 67,  # 'T'
+    85: 102,  # 'U'
+    86: 107,  # 'V'
+    87: 84,  # 'W'
+    88: 114,  # 'X'
+    89: 103,  # 'Y'
+    90: 115,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 50,  # 'a'
+    98: 74,  # 'b'
+    99: 60,  # 'c'
+    100: 61,  # 'd'
+    101: 42,  # 'e'
+    102: 76,  # 'f'
+    103: 70,  # 'g'
+    104: 64,  # 'h'
+    105: 53,  # 'i'
+    106: 105,  # 'j'
+    107: 93,  # 'k'
+    108: 56,  # 'l'
+    109: 65,  # 'm'
+    110: 54,  # 'n'
+    111: 49,  # 'o'
+    112: 66,  # 'p'
+    113: 110,  # 'q'
+    114: 51,  # 'r'
+    115: 43,  # 's'
+    116: 44,  # 't'
+    117: 63,  # 'u'
+    118: 81,  # 'v'
+    119: 77,  # 'w'
+    120: 98,  # 'x'
+    121: 75,  # 'y'
+    122: 108,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 124,  # '€'
+    129: 202,  # None
+    130: 203,  # '‚'
+    131: 204,  # 'ƒ'
+    132: 205,  # '„'
+    133: 40,  # '…'
+    134: 58,  # '†'
+    135: 206,  # '‡'
+    136: 207,  # 'ˆ'
+    137: 208,  # '‰'
+    138: 209,  # None
+    139: 210,  # '‹'
+    140: 211,  # None
+    141: 212,  # None
+    142: 213,  # None
+    143: 214,  # None
+    144: 215,  # None
+    145: 83,  # '‘'
+    146: 52,  # '’'
+    147: 47,  # '“'
+    148: 46,  # '”'
+    149: 72,  # '•'
+    150: 32,  # '–'
+    151: 94,  # '—'
+    152: 216,  # '˜'
+    153: 113,  # '™'
+    154: 217,  # None
+    155: 109,  # '›'
+    156: 218,  # None
+    157: 219,  # None
+    158: 220,  # None
+    159: 221,  # None
+    160: 34,  # '\xa0'
+    161: 116,  # '¡'
+    162: 222,  # '¢'
+    163: 118,  # '£'
+    164: 100,  # '₪'
+    165: 223,  # '¥'
+    166: 224,  # '¦'
+    167: 117,  # '§'
+    168: 119,  # '¨'
+    169: 104,  # '©'
+    170: 125,  # '×'
+    171: 225,  # '«'
+    172: 226,  # '¬'
+    173: 87,  # '\xad'
+    174: 99,  # '®'
+    175: 227,  # '¯'
+    176: 106,  # '°'
+    177: 122,  # '±'
+    178: 123,  # '²'
+    179: 228,  # '³'
+    180: 55,  # '´'
+    181: 229,  # 'µ'
+    182: 230,  # '¶'
+    183: 101,  # '·'
+    184: 231,  # '¸'
+    185: 232,  # '¹'
+    186: 120,  # '÷'
+    187: 233,  # '»'
+    188: 48,  # '¼'
+    189: 39,  # '½'
+    190: 57,  # '¾'
+    191: 234,  # '¿'
+    192: 30,  # 'ְ'
+    193: 59,  # 'ֱ'
+    194: 41,  # 'ֲ'
+    195: 88,  # 'ֳ'
+    196: 33,  # 'ִ'
+    197: 37,  # 'ֵ'
+    198: 36,  # 'ֶ'
+    199: 31,  # 'ַ'
+    200: 29,  # 'ָ'
+    201: 35,  # 'ֹ'
+    202: 235,  # None
+    203: 62,  # 'ֻ'
+    204: 28,  # 'ּ'
+    205: 236,  # 'ֽ'
+    206: 126,  # '־'
+    207: 237,  # 'ֿ'
+    208: 238,  # '׀'
+    209: 38,  # 'ׁ'
+    210: 45,  # 'ׂ'
+    211: 239,  # '׃'
+    212: 240,  # 'װ'
+    213: 241,  # 'ױ'
+    214: 242,  # 'ײ'
+    215: 243,  # '׳'
+    216: 127,  # '״'
+    217: 244,  # None
+    218: 245,  # None
+    219: 246,  # None
+    220: 247,  # None
+    221: 248,  # None
+    222: 249,  # None
+    223: 250,  # None
+    224: 9,  # 'א'
+    225: 8,  # 'ב'
+    226: 20,  # 'ג'
+    227: 16,  # 'ד'
+    228: 3,  # 'ה'
+    229: 2,  # 'ו'
+    230: 24,  # 'ז'
+    231: 14,  # 'ח'
+    232: 22,  # 'ט'
+    233: 1,  # 'י'
+    234: 25,  # 'ך'
+    235: 15,  # 'כ'
+    236: 4,  # 'ל'
+    237: 11,  # 'ם'
+    238: 6,  # 'מ'
+    239: 23,  # 'ן'
+    240: 12,  # 'נ'
+    241: 19,  # 'ס'
+    242: 13,  # 'ע'
+    243: 26,  # 'ף'
+    244: 18,  # 'פ'
+    245: 27,  # 'ץ'
+    246: 21,  # 'צ'
+    247: 17,  # 'ק'
+    248: 7,  # 'ר'
+    249: 10,  # 'ש'
+    250: 5,  # 'ת'
+    251: 251,  # None
+    252: 252,  # None
+    253: 128,  # '\u200e'
+    254: 96,  # '\u200f'
+    255: 253,  # None
+}
+
+WINDOWS_1255_HEBREW_MODEL = SingleByteCharSetModel(
+    charset_name="windows-1255",
+    language="Hebrew",
+    char_to_order_map=WINDOWS_1255_HEBREW_CHAR_TO_ORDER,
+    language_model=HEBREW_LANG_MODEL,
+    typical_positive_ratio=0.984004,
+    keep_ascii_letters=False,
+    alphabet="אבגדהוזחטיךכלםמןנסעףפץצקרשתװױײ",
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langhungarianmodel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langhungarianmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..09a0d326b983b59b58f84b00e55fbe6909a23793
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langhungarianmodel.py
@@ -0,0 +1,4649 @@
+from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+HUNGARIAN_LANG_MODEL = {
+    28: {  # 'A'
+        28: 0,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 2,  # 'D'
+        32: 1,  # 'E'
+        50: 1,  # 'F'
+        49: 2,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 2,  # 'K'
+        41: 2,  # 'L'
+        34: 1,  # 'M'
+        35: 2,  # 'N'
+        47: 1,  # 'O'
+        46: 2,  # 'P'
+        43: 2,  # 'R'
+        33: 2,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 2,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 2,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 1,  # 'i'
+        22: 1,  # 'j'
+        7: 2,  # 'k'
+        6: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 2,  # 'n'
+        8: 0,  # 'o'
+        23: 2,  # 'p'
+        10: 2,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 1,  # 'u'
+        19: 1,  # 'v'
+        62: 1,  # 'x'
+        16: 0,  # 'y'
+        11: 3,  # 'z'
+        51: 1,  # 'Á'
+        44: 0,  # 'É'
+        61: 1,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    40: {  # 'B'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 0,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 3,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 2,  # 'i'
+        22: 1,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 3,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    54: {  # 'C'
+        28: 1,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 1,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 0,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 2,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 0,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 1,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 1,  # 'h'
+        9: 1,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 3,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 1,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    45: {  # 'D'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 0,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 0,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 3,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 1,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 1,  # 'o'
+        23: 0,  # 'p'
+        10: 2,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 2,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 1,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    32: {  # 'E'
+        28: 1,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 1,  # 'E'
+        50: 1,  # 'F'
+        49: 2,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 2,  # 'K'
+        41: 2,  # 'L'
+        34: 2,  # 'M'
+        35: 2,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 2,  # 'R'
+        33: 2,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 1,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 2,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 3,  # 'g'
+        20: 1,  # 'h'
+        9: 1,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 2,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 2,  # 's'
+        3: 1,  # 't'
+        21: 2,  # 'u'
+        19: 1,  # 'v'
+        62: 1,  # 'x'
+        16: 0,  # 'y'
+        11: 3,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 0,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 1,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    50: {  # 'F'
+        28: 1,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 1,  # 'E'
+        50: 1,  # 'F'
+        49: 0,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 0,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 0,  # 'V'
+        55: 1,  # 'Y'
+        52: 0,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 1,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 2,  # 'i'
+        22: 1,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 2,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 0,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 2,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    49: {  # 'G'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 2,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 1,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 2,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 2,  # 'y'
+        11: 0,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 0,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    38: {  # 'H'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 0,  # 'D'
+        32: 1,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 1,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 1,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 1,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 0,  # 'V'
+        55: 1,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 2,  # 'i'
+        22: 1,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 0,  # 'n'
+        8: 3,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 2,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 2,  # 'Á'
+        44: 2,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 1,  # 'é'
+        30: 2,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    39: {  # 'I'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 1,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 2,  # 'K'
+        41: 2,  # 'L'
+        34: 1,  # 'M'
+        35: 2,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 2,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 2,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 2,  # 'd'
+        1: 0,  # 'e'
+        27: 1,  # 'f'
+        12: 2,  # 'g'
+        20: 1,  # 'h'
+        9: 0,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 1,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 2,  # 's'
+        3: 2,  # 't'
+        21: 0,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 0,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    53: {  # 'J'
+        28: 2,  # 'A'
+        40: 0,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 1,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 1,  # 'o'
+        23: 0,  # 'p'
+        10: 0,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 2,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 0,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 1,  # 'é'
+        30: 0,  # 'í'
+        25: 2,  # 'ó'
+        24: 2,  # 'ö'
+        31: 1,  # 'ú'
+        29: 0,  # 'ü'
+        42: 1,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    36: {  # 'K'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 0,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 0,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 1,  # 'f'
+        12: 0,  # 'g'
+        20: 1,  # 'h'
+        9: 3,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 2,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 2,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 2,  # 'ö'
+        31: 1,  # 'ú'
+        29: 2,  # 'ü'
+        42: 1,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    41: {  # 'L'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 2,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 3,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 2,  # 'i'
+        22: 1,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 0,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 2,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 2,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 0,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    34: {  # 'M'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 0,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 3,  # 'a'
+        18: 0,  # 'b'
+        26: 1,  # 'c'
+        17: 0,  # 'd'
+        1: 3,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 3,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 3,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 2,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 2,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    35: {  # 'N'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 2,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 2,  # 'Y'
+        52: 1,  # 'Z'
+        2: 3,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 3,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 2,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 0,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 2,  # 'y'
+        11: 0,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 1,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 1,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    47: {  # 'O'
+        28: 1,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 1,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 2,  # 'K'
+        41: 2,  # 'L'
+        34: 2,  # 'M'
+        35: 2,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 2,  # 'R'
+        33: 2,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 1,  # 'i'
+        22: 1,  # 'j'
+        7: 2,  # 'k'
+        6: 2,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 1,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 1,  # 's'
+        3: 2,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 1,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 0,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    46: {  # 'P'
+        28: 1,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 1,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 0,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 2,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 1,  # 'f'
+        12: 0,  # 'g'
+        20: 1,  # 'h'
+        9: 2,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 2,  # 'r'
+        5: 1,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 2,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 3,  # 'á'
+        15: 2,  # 'é'
+        30: 0,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 0,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    43: {  # 'R'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 2,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 1,  # 'h'
+        9: 2,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 0,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 2,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 2,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 2,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    33: {  # 'S'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 2,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 3,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 1,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 1,  # 'h'
+        9: 2,  # 'i'
+        22: 0,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 1,  # 'p'
+        10: 0,  # 'r'
+        5: 0,  # 's'
+        3: 1,  # 't'
+        21: 1,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 3,  # 'z'
+        51: 2,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    37: {  # 'T'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 1,  # 'P'
+        43: 2,  # 'R'
+        33: 1,  # 'S'
+        37: 2,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 2,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 1,  # 'h'
+        9: 2,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 0,  # 't'
+        21: 2,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 1,  # 'z'
+        51: 2,  # 'Á'
+        44: 2,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 2,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    57: {  # 'U'
+        28: 1,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 1,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 2,  # 'S'
+        37: 1,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 1,  # 'e'
+        27: 0,  # 'f'
+        12: 2,  # 'g'
+        20: 0,  # 'h'
+        9: 0,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 1,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    48: {  # 'V'
+        28: 2,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 0,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 2,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 2,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 2,  # 'o'
+        23: 0,  # 'p'
+        10: 0,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 2,  # 'Á'
+        44: 2,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 2,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 0,  # 'ó'
+        24: 1,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    55: {  # 'Y'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 1,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 2,  # 'Z'
+        2: 1,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 1,  # 'd'
+        1: 1,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 0,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 0,  # 'n'
+        8: 1,  # 'o'
+        23: 1,  # 'p'
+        10: 0,  # 'r'
+        5: 0,  # 's'
+        3: 0,  # 't'
+        21: 0,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 1,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    52: {  # 'Z'
+        28: 2,  # 'A'
+        40: 1,  # 'B'
+        54: 0,  # 'C'
+        45: 1,  # 'D'
+        32: 2,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 2,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 2,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 2,  # 'S'
+        37: 1,  # 'T'
+        57: 1,  # 'U'
+        48: 1,  # 'V'
+        55: 1,  # 'Y'
+        52: 1,  # 'Z'
+        2: 1,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 1,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 1,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
+        8: 1,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 2,  # 's'
+        3: 0,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 2,  # 'Á'
+        44: 1,  # 'É'
+        61: 1,  # 'Í'
+        58: 1,  # 'Ó'
+        59: 1,  # 'Ö'
+        60: 1,  # 'Ú'
+        63: 1,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    2: {  # 'a'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 3,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 2,  # 'e'
+        27: 2,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 3,  # 'i'
+        22: 3,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 2,  # 'o'
+        23: 3,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 1,  # 'x'
+        16: 2,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    18: {  # 'b'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 3,  # 'i'
+        22: 2,  # 'j'
+        7: 2,  # 'k'
+        6: 2,  # 'l'
+        13: 1,  # 'm'
+        4: 2,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 3,  # 'r'
+        5: 2,  # 's'
+        3: 1,  # 't'
+        21: 3,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 3,  # 'ó'
+        24: 2,  # 'ö'
+        31: 2,  # 'ú'
+        29: 2,  # 'ü'
+        42: 2,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    26: {  # 'c'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 1,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 1,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 2,  # 'a'
+        18: 1,  # 'b'
+        26: 2,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 3,  # 'h'
+        9: 3,  # 'i'
+        22: 1,  # 'j'
+        7: 2,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 3,  # 's'
+        3: 2,  # 't'
+        21: 2,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 2,  # 'á'
+        15: 2,  # 'é'
+        30: 2,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    17: {  # 'd'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 2,  # 'b'
+        26: 1,  # 'c'
+        17: 2,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 3,  # 'j'
+        7: 2,  # 'k'
+        6: 1,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 2,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 3,  # 'í'
+        25: 3,  # 'ó'
+        24: 3,  # 'ö'
+        31: 2,  # 'ú'
+        29: 2,  # 'ü'
+        42: 2,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    1: {  # 'e'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 2,  # 'a'
+        18: 3,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 2,  # 'e'
+        27: 3,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 3,  # 'i'
+        22: 3,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 2,  # 'o'
+        23: 3,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 2,  # 'u'
+        19: 3,  # 'v'
+        62: 2,  # 'x'
+        16: 2,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    27: {  # 'f'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 2,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 3,  # 'i'
+        22: 2,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 3,  # 'o'
+        23: 0,  # 'p'
+        10: 3,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 2,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 0,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 3,  # 'ö'
+        31: 1,  # 'ú'
+        29: 2,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    12: {  # 'g'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 2,  # 'c'
+        17: 2,  # 'd'
+        1: 3,  # 'e'
+        27: 2,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 3,  # 'i'
+        22: 3,  # 'j'
+        7: 2,  # 'k'
+        6: 3,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 3,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 3,  # 'ó'
+        24: 2,  # 'ö'
+        31: 2,  # 'ú'
+        29: 2,  # 'ü'
+        42: 2,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    20: {  # 'h'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 0,  # 'd'
+        1: 3,  # 'e'
+        27: 0,  # 'f'
+        12: 1,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 3,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 2,  # 's'
+        3: 1,  # 't'
+        21: 3,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 2,  # 'y'
+        11: 0,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 3,  # 'í'
+        25: 2,  # 'ó'
+        24: 2,  # 'ö'
+        31: 2,  # 'ú'
+        29: 1,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    9: {  # 'i'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 3,  # 'e'
+        27: 3,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 2,  # 'i'
+        22: 2,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 2,  # 'o'
+        23: 2,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 1,  # 'x'
+        16: 1,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 3,  # 'ó'
+        24: 1,  # 'ö'
+        31: 2,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    22: {  # 'j'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 2,  # 'b'
+        26: 1,  # 'c'
+        17: 3,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 2,  # 'h'
+        9: 1,  # 'i'
+        22: 2,  # 'j'
+        7: 2,  # 'k'
+        6: 2,  # 'l'
+        13: 1,  # 'm'
+        4: 2,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 2,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 1,  # 'í'
+        25: 3,  # 'ó'
+        24: 3,  # 'ö'
+        31: 3,  # 'ú'
+        29: 2,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    7: {  # 'k'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 2,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 2,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 1,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 2,  # 'v'
+        62: 0,  # 'x'
+        16: 2,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 3,  # 'í'
+        25: 2,  # 'ó'
+        24: 3,  # 'ö'
+        31: 1,  # 'ú'
+        29: 3,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    6: {  # 'l'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 1,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 1,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 2,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 3,  # 'e'
+        27: 3,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 3,  # 'i'
+        22: 3,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 2,  # 'p'
+        10: 2,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 3,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 3,  # 'í'
+        25: 3,  # 'ó'
+        24: 3,  # 'ö'
+        31: 2,  # 'ú'
+        29: 2,  # 'ü'
+        42: 3,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    13: {  # 'm'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 2,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 2,  # 'j'
+        7: 1,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 2,  # 'n'
+        8: 3,  # 'o'
+        23: 3,  # 'p'
+        10: 2,  # 'r'
+        5: 2,  # 's'
+        3: 2,  # 't'
+        21: 3,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 2,  # 'ó'
+        24: 2,  # 'ö'
+        31: 2,  # 'ú'
+        29: 2,  # 'ü'
+        42: 1,  # 'ő'
+        56: 2,  # 'ű'
+    },
+    4: {  # 'n'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 3,  # 'e'
+        27: 2,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 3,  # 'i'
+        22: 2,  # 'j'
+        7: 3,  # 'k'
+        6: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 2,  # 'p'
+        10: 2,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 2,  # 'v'
+        62: 1,  # 'x'
+        16: 3,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 2,  # 'ó'
+        24: 3,  # 'ö'
+        31: 2,  # 'ú'
+        29: 3,  # 'ü'
+        42: 2,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    8: {  # 'o'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 1,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 2,  # 'a'
+        18: 3,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 2,  # 'e'
+        27: 2,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 2,  # 'i'
+        22: 2,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 1,  # 'o'
+        23: 3,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 2,  # 'u'
+        19: 3,  # 'v'
+        62: 1,  # 'x'
+        16: 1,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    23: {  # 'p'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 1,  # 'b'
+        26: 2,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 2,  # 'j'
+        7: 2,  # 'k'
+        6: 3,  # 'l'
+        13: 1,  # 'm'
+        4: 2,  # 'n'
+        8: 3,  # 'o'
+        23: 3,  # 'p'
+        10: 3,  # 'r'
+        5: 2,  # 's'
+        3: 2,  # 't'
+        21: 3,  # 'u'
+        19: 2,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 2,  # 'ó'
+        24: 2,  # 'ö'
+        31: 1,  # 'ú'
+        29: 2,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    10: {  # 'r'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 3,  # 'e'
+        27: 2,  # 'f'
+        12: 3,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 3,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 2,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 1,  # 'x'
+        16: 2,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 3,  # 'ó'
+        24: 3,  # 'ö'
+        31: 3,  # 'ú'
+        29: 3,  # 'ü'
+        42: 2,  # 'ő'
+        56: 2,  # 'ű'
+    },
+    5: {  # 's'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 2,  # 'c'
+        17: 2,  # 'd'
+        1: 3,  # 'e'
+        27: 2,  # 'f'
+        12: 2,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 1,  # 'j'
+        7: 3,  # 'k'
+        6: 2,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 2,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 2,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 3,  # 'í'
+        25: 3,  # 'ó'
+        24: 3,  # 'ö'
+        31: 3,  # 'ú'
+        29: 3,  # 'ü'
+        42: 2,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    3: {  # 't'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 3,  # 'b'
+        26: 2,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 2,  # 'f'
+        12: 1,  # 'g'
+        20: 3,  # 'h'
+        9: 3,  # 'i'
+        22: 3,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 3,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 3,  # 'ó'
+        24: 3,  # 'ö'
+        31: 3,  # 'ú'
+        29: 3,  # 'ü'
+        42: 3,  # 'ő'
+        56: 2,  # 'ű'
+    },
+    21: {  # 'u'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 2,  # 'b'
+        26: 2,  # 'c'
+        17: 3,  # 'd'
+        1: 2,  # 'e'
+        27: 1,  # 'f'
+        12: 3,  # 'g'
+        20: 2,  # 'h'
+        9: 2,  # 'i'
+        22: 2,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 1,  # 'o'
+        23: 2,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 1,  # 'u'
+        19: 3,  # 'v'
+        62: 1,  # 'x'
+        16: 1,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 2,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 0,  # 'ö'
+        31: 1,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    19: {  # 'v'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 2,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 3,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 1,  # 'r'
+        5: 2,  # 's'
+        3: 2,  # 't'
+        21: 2,  # 'u'
+        19: 2,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 2,  # 'ó'
+        24: 2,  # 'ö'
+        31: 1,  # 'ú'
+        29: 2,  # 'ü'
+        42: 1,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    62: {  # 'x'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 0,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 1,  # 'i'
+        22: 0,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 1,  # 'o'
+        23: 1,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 1,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 1,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    16: {  # 'y'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 2,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 3,  # 'e'
+        27: 2,  # 'f'
+        12: 2,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 2,  # 'j'
+        7: 2,  # 'k'
+        6: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 2,  # 'p'
+        10: 2,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 2,  # 'í'
+        25: 2,  # 'ó'
+        24: 3,  # 'ö'
+        31: 2,  # 'ú'
+        29: 2,  # 'ü'
+        42: 1,  # 'ő'
+        56: 2,  # 'ű'
+    },
+    11: {  # 'z'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 3,  # 'a'
+        18: 2,  # 'b'
+        26: 1,  # 'c'
+        17: 3,  # 'd'
+        1: 3,  # 'e'
+        27: 1,  # 'f'
+        12: 2,  # 'g'
+        20: 2,  # 'h'
+        9: 3,  # 'i'
+        22: 1,  # 'j'
+        7: 3,  # 'k'
+        6: 2,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 3,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 3,  # 'u'
+        19: 2,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 3,  # 'á'
+        15: 3,  # 'é'
+        30: 3,  # 'í'
+        25: 3,  # 'ó'
+        24: 3,  # 'ö'
+        31: 2,  # 'ú'
+        29: 3,  # 'ü'
+        42: 2,  # 'ő'
+        56: 1,  # 'ű'
+    },
+    51: {  # 'Á'
+        28: 0,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 0,  # 'E'
+        50: 1,  # 'F'
+        49: 2,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 2,  # 'L'
+        34: 1,  # 'M'
+        35: 2,  # 'N'
+        47: 0,  # 'O'
+        46: 1,  # 'P'
+        43: 2,  # 'R'
+        33: 2,  # 'S'
+        37: 1,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 0,  # 'e'
+        27: 0,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 0,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 0,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 1,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    44: {  # 'É'
+        28: 0,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 1,  # 'E'
+        50: 0,  # 'F'
+        49: 2,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 2,  # 'L'
+        34: 1,  # 'M'
+        35: 2,  # 'N'
+        47: 0,  # 'O'
+        46: 1,  # 'P'
+        43: 2,  # 'R'
+        33: 2,  # 'S'
+        37: 2,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 0,  # 'e'
+        27: 0,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 0,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 2,  # 'l'
+        13: 1,  # 'm'
+        4: 2,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 3,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 0,  # 'Á'
+        44: 1,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    61: {  # 'Í'
+        28: 0,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 0,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 1,  # 'J'
+        36: 0,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 0,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 0,  # 'e'
+        27: 0,  # 'f'
+        12: 2,  # 'g'
+        20: 0,  # 'h'
+        9: 0,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 0,  # 'n'
+        8: 0,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 0,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    58: {  # 'Ó'
+        28: 1,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 0,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 1,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 2,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 0,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 0,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 2,  # 'h'
+        9: 0,  # 'i'
+        22: 0,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 0,  # 't'
+        21: 0,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 1,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    59: {  # 'Ö'
+        28: 0,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 0,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 0,  # 'O'
+        46: 1,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 0,  # 'b'
+        26: 1,  # 'c'
+        17: 1,  # 'd'
+        1: 0,  # 'e'
+        27: 0,  # 'f'
+        12: 0,  # 'g'
+        20: 0,  # 'h'
+        9: 0,  # 'i'
+        22: 0,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        8: 0,  # 'o'
+        23: 0,  # 'p'
+        10: 2,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    60: {  # 'Ú'
+        28: 0,  # 'A'
+        40: 1,  # 'B'
+        54: 1,  # 'C'
+        45: 1,  # 'D'
+        32: 0,  # 'E'
+        50: 1,  # 'F'
+        49: 1,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 0,  # 'b'
+        26: 0,  # 'c'
+        17: 0,  # 'd'
+        1: 0,  # 'e'
+        27: 0,  # 'f'
+        12: 2,  # 'g'
+        20: 0,  # 'h'
+        9: 0,  # 'i'
+        22: 2,  # 'j'
+        7: 0,  # 'k'
+        6: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
+        8: 0,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 0,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 0,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    63: {  # 'Ü'
+        28: 0,  # 'A'
+        40: 1,  # 'B'
+        54: 0,  # 'C'
+        45: 1,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 1,  # 'G'
+        38: 1,  # 'H'
+        39: 0,  # 'I'
+        53: 1,  # 'J'
+        36: 1,  # 'K'
+        41: 1,  # 'L'
+        34: 1,  # 'M'
+        35: 1,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 1,  # 'R'
+        33: 1,  # 'S'
+        37: 1,  # 'T'
+        57: 0,  # 'U'
+        48: 1,  # 'V'
+        55: 0,  # 'Y'
+        52: 1,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 0,  # 'c'
+        17: 1,  # 'd'
+        1: 0,  # 'e'
+        27: 0,  # 'f'
+        12: 1,  # 'g'
+        20: 0,  # 'h'
+        9: 0,  # 'i'
+        22: 0,  # 'j'
+        7: 0,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
+        8: 0,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 1,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    14: {  # 'á'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 3,  # 'b'
+        26: 3,  # 'c'
+        17: 3,  # 'd'
+        1: 1,  # 'e'
+        27: 2,  # 'f'
+        12: 3,  # 'g'
+        20: 2,  # 'h'
+        9: 2,  # 'i'
+        22: 3,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 1,  # 'o'
+        23: 2,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 2,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 1,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 2,  # 'é'
+        30: 1,  # 'í'
+        25: 0,  # 'ó'
+        24: 1,  # 'ö'
+        31: 0,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    15: {  # 'é'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 3,  # 'b'
+        26: 2,  # 'c'
+        17: 3,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 3,  # 'g'
+        20: 3,  # 'h'
+        9: 2,  # 'i'
+        22: 2,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 1,  # 'o'
+        23: 3,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 0,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    30: {  # 'í'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 0,  # 'a'
+        18: 1,  # 'b'
+        26: 2,  # 'c'
+        17: 1,  # 'd'
+        1: 0,  # 'e'
+        27: 1,  # 'f'
+        12: 3,  # 'g'
+        20: 0,  # 'h'
+        9: 0,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 3,  # 'r'
+        5: 2,  # 's'
+        3: 3,  # 't'
+        21: 0,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    25: {  # 'ó'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 2,  # 'a'
+        18: 3,  # 'b'
+        26: 2,  # 'c'
+        17: 3,  # 'd'
+        1: 1,  # 'e'
+        27: 2,  # 'f'
+        12: 2,  # 'g'
+        20: 2,  # 'h'
+        9: 2,  # 'i'
+        22: 2,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        8: 1,  # 'o'
+        23: 2,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 1,  # 'u'
+        19: 2,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 0,  # 'ó'
+        24: 1,  # 'ö'
+        31: 1,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    24: {  # 'ö'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 0,  # 'a'
+        18: 3,  # 'b'
+        26: 1,  # 'c'
+        17: 2,  # 'd'
+        1: 0,  # 'e'
+        27: 1,  # 'f'
+        12: 2,  # 'g'
+        20: 1,  # 'h'
+        9: 0,  # 'i'
+        22: 1,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        8: 0,  # 'o'
+        23: 2,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 3,  # 't'
+        21: 0,  # 'u'
+        19: 3,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 3,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    31: {  # 'ú'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 1,  # 'b'
+        26: 2,  # 'c'
+        17: 1,  # 'd'
+        1: 1,  # 'e'
+        27: 2,  # 'f'
+        12: 3,  # 'g'
+        20: 1,  # 'h'
+        9: 1,  # 'i'
+        22: 3,  # 'j'
+        7: 1,  # 'k'
+        6: 3,  # 'l'
+        13: 1,  # 'm'
+        4: 2,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 3,  # 'r'
+        5: 3,  # 's'
+        3: 2,  # 't'
+        21: 1,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 1,  # 'á'
+        15: 1,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    29: {  # 'ü'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 1,  # 'b'
+        26: 1,  # 'c'
+        17: 2,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 3,  # 'g'
+        20: 2,  # 'h'
+        9: 1,  # 'i'
+        22: 1,  # 'j'
+        7: 3,  # 'k'
+        6: 3,  # 'l'
+        13: 1,  # 'm'
+        4: 3,  # 'n'
+        8: 0,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 2,  # 's'
+        3: 2,  # 't'
+        21: 0,  # 'u'
+        19: 2,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 1,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    42: {  # 'ő'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 2,  # 'b'
+        26: 1,  # 'c'
+        17: 2,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 1,  # 'i'
+        22: 1,  # 'j'
+        7: 2,  # 'k'
+        6: 3,  # 'l'
+        13: 1,  # 'm'
+        4: 2,  # 'n'
+        8: 1,  # 'o'
+        23: 1,  # 'p'
+        10: 2,  # 'r'
+        5: 2,  # 's'
+        3: 2,  # 't'
+        21: 1,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 1,  # 'é'
+        30: 1,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 1,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+    56: {  # 'ű'
+        28: 0,  # 'A'
+        40: 0,  # 'B'
+        54: 0,  # 'C'
+        45: 0,  # 'D'
+        32: 0,  # 'E'
+        50: 0,  # 'F'
+        49: 0,  # 'G'
+        38: 0,  # 'H'
+        39: 0,  # 'I'
+        53: 0,  # 'J'
+        36: 0,  # 'K'
+        41: 0,  # 'L'
+        34: 0,  # 'M'
+        35: 0,  # 'N'
+        47: 0,  # 'O'
+        46: 0,  # 'P'
+        43: 0,  # 'R'
+        33: 0,  # 'S'
+        37: 0,  # 'T'
+        57: 0,  # 'U'
+        48: 0,  # 'V'
+        55: 0,  # 'Y'
+        52: 0,  # 'Z'
+        2: 1,  # 'a'
+        18: 1,  # 'b'
+        26: 0,  # 'c'
+        17: 1,  # 'd'
+        1: 1,  # 'e'
+        27: 1,  # 'f'
+        12: 1,  # 'g'
+        20: 1,  # 'h'
+        9: 1,  # 'i'
+        22: 1,  # 'j'
+        7: 1,  # 'k'
+        6: 1,  # 'l'
+        13: 0,  # 'm'
+        4: 2,  # 'n'
+        8: 0,  # 'o'
+        23: 0,  # 'p'
+        10: 1,  # 'r'
+        5: 1,  # 's'
+        3: 1,  # 't'
+        21: 0,  # 'u'
+        19: 1,  # 'v'
+        62: 0,  # 'x'
+        16: 0,  # 'y'
+        11: 2,  # 'z'
+        51: 0,  # 'Á'
+        44: 0,  # 'É'
+        61: 0,  # 'Í'
+        58: 0,  # 'Ó'
+        59: 0,  # 'Ö'
+        60: 0,  # 'Ú'
+        63: 0,  # 'Ü'
+        14: 0,  # 'á'
+        15: 0,  # 'é'
+        30: 0,  # 'í'
+        25: 0,  # 'ó'
+        24: 0,  # 'ö'
+        31: 0,  # 'ú'
+        29: 0,  # 'ü'
+        42: 0,  # 'ő'
+        56: 0,  # 'ű'
+    },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+WINDOWS_1250_HUNGARIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 28,  # 'A'
+    66: 40,  # 'B'
+    67: 54,  # 'C'
+    68: 45,  # 'D'
+    69: 32,  # 'E'
+    70: 50,  # 'F'
+    71: 49,  # 'G'
+    72: 38,  # 'H'
+    73: 39,  # 'I'
+    74: 53,  # 'J'
+    75: 36,  # 'K'
+    76: 41,  # 'L'
+    77: 34,  # 'M'
+    78: 35,  # 'N'
+    79: 47,  # 'O'
+    80: 46,  # 'P'
+    81: 72,  # 'Q'
+    82: 43,  # 'R'
+    83: 33,  # 'S'
+    84: 37,  # 'T'
+    85: 57,  # 'U'
+    86: 48,  # 'V'
+    87: 64,  # 'W'
+    88: 68,  # 'X'
+    89: 55,  # 'Y'
+    90: 52,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 2,  # 'a'
+    98: 18,  # 'b'
+    99: 26,  # 'c'
+    100: 17,  # 'd'
+    101: 1,  # 'e'
+    102: 27,  # 'f'
+    103: 12,  # 'g'
+    104: 20,  # 'h'
+    105: 9,  # 'i'
+    106: 22,  # 'j'
+    107: 7,  # 'k'
+    108: 6,  # 'l'
+    109: 13,  # 'm'
+    110: 4,  # 'n'
+    111: 8,  # 'o'
+    112: 23,  # 'p'
+    113: 67,  # 'q'
+    114: 10,  # 'r'
+    115: 5,  # 's'
+    116: 3,  # 't'
+    117: 21,  # 'u'
+    118: 19,  # 'v'
+    119: 65,  # 'w'
+    120: 62,  # 'x'
+    121: 16,  # 'y'
+    122: 11,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 161,  # '€'
+    129: 162,  # None
+    130: 163,  # '‚'
+    131: 164,  # None
+    132: 165,  # '„'
+    133: 166,  # '…'
+    134: 167,  # '†'
+    135: 168,  # '‡'
+    136: 169,  # None
+    137: 170,  # '‰'
+    138: 171,  # 'Š'
+    139: 172,  # '‹'
+    140: 173,  # 'Ś'
+    141: 174,  # 'Ť'
+    142: 175,  # 'Ž'
+    143: 176,  # 'Ź'
+    144: 177,  # None
+    145: 178,  # '‘'
+    146: 179,  # '’'
+    147: 180,  # '“'
+    148: 78,  # '”'
+    149: 181,  # '•'
+    150: 69,  # '–'
+    151: 182,  # '—'
+    152: 183,  # None
+    153: 184,  # '™'
+    154: 185,  # 'š'
+    155: 186,  # '›'
+    156: 187,  # 'ś'
+    157: 188,  # 'ť'
+    158: 189,  # 'ž'
+    159: 190,  # 'ź'
+    160: 191,  # '\xa0'
+    161: 192,  # 'ˇ'
+    162: 193,  # '˘'
+    163: 194,  # 'Ł'
+    164: 195,  # '¤'
+    165: 196,  # 'Ą'
+    166: 197,  # '¦'
+    167: 76,  # '§'
+    168: 198,  # '¨'
+    169: 199,  # '©'
+    170: 200,  # 'Ş'
+    171: 201,  # '«'
+    172: 202,  # '¬'
+    173: 203,  # '\xad'
+    174: 204,  # '®'
+    175: 205,  # 'Ż'
+    176: 81,  # '°'
+    177: 206,  # '±'
+    178: 207,  # '˛'
+    179: 208,  # 'ł'
+    180: 209,  # '´'
+    181: 210,  # 'µ'
+    182: 211,  # '¶'
+    183: 212,  # '·'
+    184: 213,  # '¸'
+    185: 214,  # 'ą'
+    186: 215,  # 'ş'
+    187: 216,  # '»'
+    188: 217,  # 'Ľ'
+    189: 218,  # '˝'
+    190: 219,  # 'ľ'
+    191: 220,  # 'ż'
+    192: 221,  # 'Ŕ'
+    193: 51,  # 'Á'
+    194: 83,  # 'Â'
+    195: 222,  # 'Ă'
+    196: 80,  # 'Ä'
+    197: 223,  # 'Ĺ'
+    198: 224,  # 'Ć'
+    199: 225,  # 'Ç'
+    200: 226,  # 'Č'
+    201: 44,  # 'É'
+    202: 227,  # 'Ę'
+    203: 228,  # 'Ë'
+    204: 229,  # 'Ě'
+    205: 61,  # 'Í'
+    206: 230,  # 'Î'
+    207: 231,  # 'Ď'
+    208: 232,  # 'Đ'
+    209: 233,  # 'Ń'
+    210: 234,  # 'Ň'
+    211: 58,  # 'Ó'
+    212: 235,  # 'Ô'
+    213: 66,  # 'Ő'
+    214: 59,  # 'Ö'
+    215: 236,  # '×'
+    216: 237,  # 'Ř'
+    217: 238,  # 'Ů'
+    218: 60,  # 'Ú'
+    219: 70,  # 'Ű'
+    220: 63,  # 'Ü'
+    221: 239,  # 'Ý'
+    222: 240,  # 'Ţ'
+    223: 241,  # 'ß'
+    224: 84,  # 'ŕ'
+    225: 14,  # 'á'
+    226: 75,  # 'â'
+    227: 242,  # 'ă'
+    228: 71,  # 'ä'
+    229: 82,  # 'ĺ'
+    230: 243,  # 'ć'
+    231: 73,  # 'ç'
+    232: 244,  # 'č'
+    233: 15,  # 'é'
+    234: 85,  # 'ę'
+    235: 79,  # 'ë'
+    236: 86,  # 'ě'
+    237: 30,  # 'í'
+    238: 77,  # 'î'
+    239: 87,  # 'ď'
+    240: 245,  # 'đ'
+    241: 246,  # 'ń'
+    242: 247,  # 'ň'
+    243: 25,  # 'ó'
+    244: 74,  # 'ô'
+    245: 42,  # 'ő'
+    246: 24,  # 'ö'
+    247: 248,  # '÷'
+    248: 249,  # 'ř'
+    249: 250,  # 'ů'
+    250: 31,  # 'ú'
+    251: 56,  # 'ű'
+    252: 29,  # 'ü'
+    253: 251,  # 'ý'
+    254: 252,  # 'ţ'
+    255: 253,  # '˙'
+}
+
+WINDOWS_1250_HUNGARIAN_MODEL = SingleByteCharSetModel(
+    charset_name="windows-1250",
+    language="Hungarian",
+    char_to_order_map=WINDOWS_1250_HUNGARIAN_CHAR_TO_ORDER,
+    language_model=HUNGARIAN_LANG_MODEL,
+    typical_positive_ratio=0.947368,
+    keep_ascii_letters=True,
+    alphabet="ABCDEFGHIJKLMNOPRSTUVZabcdefghijklmnoprstuvzÁÉÍÓÖÚÜáéíóöúüŐőŰű",
+)
+
+ISO_8859_2_HUNGARIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 28,  # 'A'
+    66: 40,  # 'B'
+    67: 54,  # 'C'
+    68: 45,  # 'D'
+    69: 32,  # 'E'
+    70: 50,  # 'F'
+    71: 49,  # 'G'
+    72: 38,  # 'H'
+    73: 39,  # 'I'
+    74: 53,  # 'J'
+    75: 36,  # 'K'
+    76: 41,  # 'L'
+    77: 34,  # 'M'
+    78: 35,  # 'N'
+    79: 47,  # 'O'
+    80: 46,  # 'P'
+    81: 71,  # 'Q'
+    82: 43,  # 'R'
+    83: 33,  # 'S'
+    84: 37,  # 'T'
+    85: 57,  # 'U'
+    86: 48,  # 'V'
+    87: 64,  # 'W'
+    88: 68,  # 'X'
+    89: 55,  # 'Y'
+    90: 52,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 2,  # 'a'
+    98: 18,  # 'b'
+    99: 26,  # 'c'
+    100: 17,  # 'd'
+    101: 1,  # 'e'
+    102: 27,  # 'f'
+    103: 12,  # 'g'
+    104: 20,  # 'h'
+    105: 9,  # 'i'
+    106: 22,  # 'j'
+    107: 7,  # 'k'
+    108: 6,  # 'l'
+    109: 13,  # 'm'
+    110: 4,  # 'n'
+    111: 8,  # 'o'
+    112: 23,  # 'p'
+    113: 67,  # 'q'
+    114: 10,  # 'r'
+    115: 5,  # 's'
+    116: 3,  # 't'
+    117: 21,  # 'u'
+    118: 19,  # 'v'
+    119: 65,  # 'w'
+    120: 62,  # 'x'
+    121: 16,  # 'y'
+    122: 11,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 159,  # '\x80'
+    129: 160,  # '\x81'
+    130: 161,  # '\x82'
+    131: 162,  # '\x83'
+    132: 163,  # '\x84'
+    133: 164,  # '\x85'
+    134: 165,  # '\x86'
+    135: 166,  # '\x87'
+    136: 167,  # '\x88'
+    137: 168,  # '\x89'
+    138: 169,  # '\x8a'
+    139: 170,  # '\x8b'
+    140: 171,  # '\x8c'
+    141: 172,  # '\x8d'
+    142: 173,  # '\x8e'
+    143: 174,  # '\x8f'
+    144: 175,  # '\x90'
+    145: 176,  # '\x91'
+    146: 177,  # '\x92'
+    147: 178,  # '\x93'
+    148: 179,  # '\x94'
+    149: 180,  # '\x95'
+    150: 181,  # '\x96'
+    151: 182,  # '\x97'
+    152: 183,  # '\x98'
+    153: 184,  # '\x99'
+    154: 185,  # '\x9a'
+    155: 186,  # '\x9b'
+    156: 187,  # '\x9c'
+    157: 188,  # '\x9d'
+    158: 189,  # '\x9e'
+    159: 190,  # '\x9f'
+    160: 191,  # '\xa0'
+    161: 192,  # 'Ą'
+    162: 193,  # '˘'
+    163: 194,  # 'Ł'
+    164: 195,  # '¤'
+    165: 196,  # 'Ľ'
+    166: 197,  # 'Ś'
+    167: 75,  # '§'
+    168: 198,  # '¨'
+    169: 199,  # 'Š'
+    170: 200,  # 'Ş'
+    171: 201,  # 'Ť'
+    172: 202,  # 'Ź'
+    173: 203,  # '\xad'
+    174: 204,  # 'Ž'
+    175: 205,  # 'Ż'
+    176: 79,  # '°'
+    177: 206,  # 'ą'
+    178: 207,  # '˛'
+    179: 208,  # 'ł'
+    180: 209,  # '´'
+    181: 210,  # 'ľ'
+    182: 211,  # 'ś'
+    183: 212,  # 'ˇ'
+    184: 213,  # '¸'
+    185: 214,  # 'š'
+    186: 215,  # 'ş'
+    187: 216,  # 'ť'
+    188: 217,  # 'ź'
+    189: 218,  # '˝'
+    190: 219,  # 'ž'
+    191: 220,  # 'ż'
+    192: 221,  # 'Ŕ'
+    193: 51,  # 'Á'
+    194: 81,  # 'Â'
+    195: 222,  # 'Ă'
+    196: 78,  # 'Ä'
+    197: 223,  # 'Ĺ'
+    198: 224,  # 'Ć'
+    199: 225,  # 'Ç'
+    200: 226,  # 'Č'
+    201: 44,  # 'É'
+    202: 227,  # 'Ę'
+    203: 228,  # 'Ë'
+    204: 229,  # 'Ě'
+    205: 61,  # 'Í'
+    206: 230,  # 'Î'
+    207: 231,  # 'Ď'
+    208: 232,  # 'Đ'
+    209: 233,  # 'Ń'
+    210: 234,  # 'Ň'
+    211: 58,  # 'Ó'
+    212: 235,  # 'Ô'
+    213: 66,  # 'Ő'
+    214: 59,  # 'Ö'
+    215: 236,  # '×'
+    216: 237,  # 'Ř'
+    217: 238,  # 'Ů'
+    218: 60,  # 'Ú'
+    219: 69,  # 'Ű'
+    220: 63,  # 'Ü'
+    221: 239,  # 'Ý'
+    222: 240,  # 'Ţ'
+    223: 241,  # 'ß'
+    224: 82,  # 'ŕ'
+    225: 14,  # 'á'
+    226: 74,  # 'â'
+    227: 242,  # 'ă'
+    228: 70,  # 'ä'
+    229: 80,  # 'ĺ'
+    230: 243,  # 'ć'
+    231: 72,  # 'ç'
+    232: 244,  # 'č'
+    233: 15,  # 'é'
+    234: 83,  # 'ę'
+    235: 77,  # 'ë'
+    236: 84,  # 'ě'
+    237: 30,  # 'í'
+    238: 76,  # 'î'
+    239: 85,  # 'ď'
+    240: 245,  # 'đ'
+    241: 246,  # 'ń'
+    242: 247,  # 'ň'
+    243: 25,  # 'ó'
+    244: 73,  # 'ô'
+    245: 42,  # 'ő'
+    246: 24,  # 'ö'
+    247: 248,  # '÷'
+    248: 249,  # 'ř'
+    249: 250,  # 'ů'
+    250: 31,  # 'ú'
+    251: 56,  # 'ű'
+    252: 29,  # 'ü'
+    253: 251,  # 'ý'
+    254: 252,  # 'ţ'
+    255: 253,  # '˙'
+}
+
+ISO_8859_2_HUNGARIAN_MODEL = SingleByteCharSetModel(
+    charset_name="ISO-8859-2",
+    language="Hungarian",
+    char_to_order_map=ISO_8859_2_HUNGARIAN_CHAR_TO_ORDER,
+    language_model=HUNGARIAN_LANG_MODEL,
+    typical_positive_ratio=0.947368,
+    keep_ascii_letters=True,
+    alphabet="ABCDEFGHIJKLMNOPRSTUVZabcdefghijklmnoprstuvzÁÉÍÓÖÚÜáéíóöúüŐőŰű",
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langrussianmodel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langrussianmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..39a5388948ef12b69b65fbfa89a84c6ef4a4bfd6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langrussianmodel.py
@@ -0,0 +1,5725 @@
+from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+RUSSIAN_LANG_MODEL = {
+    37: {  # 'А'
+        37: 0,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 1,  # 'З'
+        42: 1,  # 'И'
+        60: 1,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 2,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 1,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 1,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 1,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 0,  # 'е'
+        24: 1,  # 'ж'
+        20: 1,  # 'з'
+        4: 0,  # 'и'
+        23: 1,  # 'й'
+        11: 2,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 2,  # 'н'
+        1: 0,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 2,  # 'у'
+        39: 2,  # 'ф'
+        26: 2,  # 'х'
+        28: 0,  # 'ц'
+        22: 1,  # 'ч'
+        25: 2,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    44: {  # 'Б'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 1,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 2,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 2,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    33: {  # 'В'
+        37: 2,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 2,  # 'а'
+        21: 1,  # 'б'
+        10: 1,  # 'в'
+        19: 1,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 2,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 2,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 3,  # 'с'
+        6: 2,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 1,  # 'ц'
+        22: 2,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 1,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 0,  # 'ю'
+        16: 1,  # 'я'
+    },
+    46: {  # 'Г'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 1,  # 'в'
+        19: 0,  # 'г'
+        13: 2,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 1,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 1,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    41: {  # 'Д'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 2,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 3,  # 'а'
+        21: 0,  # 'б'
+        10: 2,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 3,  # 'ж'
+        20: 1,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 1,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    48: {  # 'Е'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 1,  # 'З'
+        42: 1,  # 'И'
+        60: 1,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 2,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 2,  # 'Р'
+        32: 2,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 1,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 0,  # 'а'
+        21: 0,  # 'б'
+        10: 2,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 2,  # 'е'
+        24: 1,  # 'ж'
+        20: 1,  # 'з'
+        4: 0,  # 'и'
+        23: 2,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 1,  # 'н'
+        1: 0,  # 'о'
+        15: 1,  # 'п'
+        9: 1,  # 'р'
+        7: 3,  # 'с'
+        6: 0,  # 'т'
+        14: 0,  # 'у'
+        39: 1,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 2,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    56: {  # 'Ж'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 1,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 1,  # 'б'
+        10: 0,  # 'в'
+        19: 1,  # 'г'
+        13: 1,  # 'д'
+        2: 2,  # 'е'
+        24: 1,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 1,  # 'м'
+        5: 0,  # 'н'
+        1: 2,  # 'о'
+        15: 0,  # 'п'
+        9: 1,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 2,  # 'ю'
+        16: 0,  # 'я'
+    },
+    51: {  # 'З'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 2,  # 'в'
+        19: 0,  # 'г'
+        13: 2,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 1,  # 'л'
+        12: 1,  # 'м'
+        5: 2,  # 'н'
+        1: 2,  # 'о'
+        15: 0,  # 'п'
+        9: 1,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 1,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 1,  # 'я'
+    },
+    42: {  # 'И'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 2,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 1,  # 'З'
+        42: 1,  # 'И'
+        60: 1,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 2,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 1,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 1,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 1,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 2,  # 'з'
+        4: 1,  # 'и'
+        23: 0,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 2,  # 'н'
+        1: 1,  # 'о'
+        15: 1,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 1,  # 'у'
+        39: 1,  # 'ф'
+        26: 2,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    60: {  # 'Й'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 1,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 1,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 0,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 2,  # 'о'
+        15: 0,  # 'п'
+        9: 0,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 0,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    36: {  # 'К'
+        37: 2,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 1,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 1,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 2,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 0,  # 'б'
+        10: 1,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 2,  # 'л'
+        12: 0,  # 'м'
+        5: 1,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    49: {  # 'Л'
+        37: 2,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 1,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 0,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 0,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 1,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 1,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 1,  # 'л'
+        12: 0,  # 'м'
+        5: 1,  # 'н'
+        1: 2,  # 'о'
+        15: 0,  # 'п'
+        9: 0,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 2,  # 'ю'
+        16: 1,  # 'я'
+    },
+    38: {  # 'М'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 1,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 1,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 3,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 1,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 1,  # 'л'
+        12: 1,  # 'м'
+        5: 2,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 1,  # 'р'
+        7: 1,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    31: {  # 'Н'
+        37: 2,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 1,  # 'З'
+        42: 2,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 1,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 1,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 3,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 1,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 3,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 2,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    34: {  # 'О'
+        37: 0,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 2,  # 'Д'
+        48: 1,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 1,  # 'З'
+        42: 1,  # 'И'
+        60: 1,  # 'Й'
+        36: 1,  # 'К'
+        49: 2,  # 'Л'
+        38: 1,  # 'М'
+        31: 2,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 2,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 1,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 1,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 1,  # 'а'
+        21: 2,  # 'б'
+        10: 1,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 0,  # 'е'
+        24: 1,  # 'ж'
+        20: 1,  # 'з'
+        4: 0,  # 'и'
+        23: 1,  # 'й'
+        11: 2,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 3,  # 'н'
+        1: 0,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 1,  # 'у'
+        39: 1,  # 'ф'
+        26: 2,  # 'х'
+        28: 1,  # 'ц'
+        22: 2,  # 'ч'
+        25: 2,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    35: {  # 'П'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 1,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 2,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 2,  # 'л'
+        12: 0,  # 'м'
+        5: 1,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 3,  # 'р'
+        7: 1,  # 'с'
+        6: 1,  # 'т'
+        14: 2,  # 'у'
+        39: 1,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 2,  # 'ь'
+        30: 1,  # 'э'
+        27: 0,  # 'ю'
+        16: 2,  # 'я'
+    },
+    45: {  # 'Р'
+        37: 2,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 2,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 0,  # 'З'
+        42: 2,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 2,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 1,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 3,  # 'а'
+        21: 0,  # 'б'
+        10: 1,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 1,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 1,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 2,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 2,  # 'я'
+    },
+    32: {  # 'С'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 2,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 1,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 2,  # 'а'
+        21: 1,  # 'б'
+        10: 2,  # 'в'
+        19: 1,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 1,  # 'ж'
+        20: 1,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 2,  # 'н'
+        1: 2,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 1,  # 'с'
+        6: 3,  # 'т'
+        14: 2,  # 'у'
+        39: 1,  # 'ф'
+        26: 1,  # 'х'
+        28: 1,  # 'ц'
+        22: 1,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 1,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    40: {  # 'Т'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 2,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 1,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 2,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 1,  # 'к'
+        8: 1,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 1,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    52: {  # 'У'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 1,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 1,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 1,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 1,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 1,  # 'г'
+        13: 2,  # 'д'
+        2: 1,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 2,  # 'и'
+        23: 1,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 1,  # 'н'
+        1: 2,  # 'о'
+        15: 1,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 0,  # 'у'
+        39: 1,  # 'ф'
+        26: 1,  # 'х'
+        28: 1,  # 'ц'
+        22: 2,  # 'ч'
+        25: 1,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    53: {  # 'Ф'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 1,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 2,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 2,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 0,  # 'с'
+        6: 1,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    55: {  # 'Х'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 2,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 0,  # 'н'
+        1: 2,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 1,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 1,  # 'ь'
+        30: 1,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    58: {  # 'Ц'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 1,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 1,  # 'а'
+        21: 0,  # 'б'
+        10: 1,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 0,  # 'о'
+        15: 0,  # 'п'
+        9: 0,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 1,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    50: {  # 'Ч'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 1,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 1,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 1,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 1,  # 'о'
+        15: 0,  # 'п'
+        9: 1,  # 'р'
+        7: 0,  # 'с'
+        6: 3,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 1,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    57: {  # 'Ш'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 1,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 0,  # 'б'
+        10: 1,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 1,  # 'и'
+        23: 0,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 1,  # 'н'
+        1: 2,  # 'о'
+        15: 2,  # 'п'
+        9: 1,  # 'р'
+        7: 0,  # 'с'
+        6: 2,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    63: {  # 'Щ'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 1,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 1,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 1,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 1,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 1,  # 'о'
+        15: 0,  # 'п'
+        9: 0,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 1,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    62: {  # 'Ы'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 1,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 1,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 0,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 0,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 0,  # 'о'
+        15: 0,  # 'п'
+        9: 0,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 0,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    61: {  # 'Ь'
+        37: 0,  # 'А'
+        44: 1,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 1,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 0,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 1,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 1,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 1,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 1,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 0,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 0,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 0,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 0,  # 'о'
+        15: 0,  # 'п'
+        9: 0,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 0,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    47: {  # 'Э'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 0,  # 'Г'
+        41: 1,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 1,  # 'Й'
+        36: 1,  # 'К'
+        49: 1,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 1,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 1,  # 'а'
+        21: 1,  # 'б'
+        10: 2,  # 'в'
+        19: 1,  # 'г'
+        13: 2,  # 'д'
+        2: 0,  # 'е'
+        24: 1,  # 'ж'
+        20: 0,  # 'з'
+        4: 0,  # 'и'
+        23: 2,  # 'й'
+        11: 2,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 2,  # 'н'
+        1: 0,  # 'о'
+        15: 1,  # 'п'
+        9: 2,  # 'р'
+        7: 1,  # 'с'
+        6: 3,  # 'т'
+        14: 1,  # 'у'
+        39: 1,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    59: {  # 'Ю'
+        37: 1,  # 'А'
+        44: 1,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 1,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 0,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 1,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 1,  # 'б'
+        10: 0,  # 'в'
+        19: 1,  # 'г'
+        13: 1,  # 'д'
+        2: 0,  # 'е'
+        24: 1,  # 'ж'
+        20: 0,  # 'з'
+        4: 0,  # 'и'
+        23: 0,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 2,  # 'н'
+        1: 0,  # 'о'
+        15: 1,  # 'п'
+        9: 1,  # 'р'
+        7: 1,  # 'с'
+        6: 0,  # 'т'
+        14: 0,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    43: {  # 'Я'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 1,  # 'В'
+        46: 1,  # 'Г'
+        41: 0,  # 'Д'
+        48: 1,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 1,  # 'С'
+        40: 1,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 1,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 1,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 1,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 1,  # 'Ю'
+        43: 1,  # 'Я'
+        3: 0,  # 'а'
+        21: 1,  # 'б'
+        10: 1,  # 'в'
+        19: 1,  # 'г'
+        13: 1,  # 'д'
+        2: 0,  # 'е'
+        24: 0,  # 'ж'
+        20: 1,  # 'з'
+        4: 0,  # 'и'
+        23: 1,  # 'й'
+        11: 1,  # 'к'
+        8: 1,  # 'л'
+        12: 1,  # 'м'
+        5: 2,  # 'н'
+        1: 0,  # 'о'
+        15: 1,  # 'п'
+        9: 1,  # 'р'
+        7: 1,  # 'с'
+        6: 0,  # 'т'
+        14: 0,  # 'у'
+        39: 0,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    3: {  # 'а'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 1,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 3,  # 'б'
+        10: 3,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 3,  # 'з'
+        4: 3,  # 'и'
+        23: 3,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 2,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 3,  # 'х'
+        28: 3,  # 'ц'
+        22: 3,  # 'ч'
+        25: 3,  # 'ш'
+        29: 3,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 2,  # 'э'
+        27: 3,  # 'ю'
+        16: 3,  # 'я'
+    },
+    21: {  # 'б'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 1,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 1,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 1,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 1,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 0,  # 'ф'
+        26: 2,  # 'х'
+        28: 1,  # 'ц'
+        22: 1,  # 'ч'
+        25: 2,  # 'ш'
+        29: 3,  # 'щ'
+        54: 2,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 2,  # 'ь'
+        30: 1,  # 'э'
+        27: 2,  # 'ю'
+        16: 3,  # 'я'
+    },
+    10: {  # 'в'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 2,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 1,  # 'ж'
+        20: 3,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 1,  # 'ф'
+        26: 2,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 3,  # 'ш'
+        29: 2,  # 'щ'
+        54: 2,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 3,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 3,  # 'я'
+    },
+    19: {  # 'г'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 2,  # 'в'
+        19: 1,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 1,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 3,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 1,  # 'ф'
+        26: 1,  # 'х'
+        28: 1,  # 'ц'
+        22: 2,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 1,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    13: {  # 'д'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 3,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 1,  # 'ф'
+        26: 2,  # 'х'
+        28: 3,  # 'ц'
+        22: 2,  # 'ч'
+        25: 2,  # 'ш'
+        29: 1,  # 'щ'
+        54: 2,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 3,  # 'ь'
+        30: 1,  # 'э'
+        27: 2,  # 'ю'
+        16: 3,  # 'я'
+    },
+    2: {  # 'е'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 3,  # 'б'
+        10: 3,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 3,  # 'з'
+        4: 2,  # 'и'
+        23: 3,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 2,  # 'у'
+        39: 2,  # 'ф'
+        26: 3,  # 'х'
+        28: 3,  # 'ц'
+        22: 3,  # 'ч'
+        25: 3,  # 'ш'
+        29: 3,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 2,  # 'ю'
+        16: 3,  # 'я'
+    },
+    24: {  # 'ж'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 1,  # 'в'
+        19: 2,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 1,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 3,  # 'н'
+        1: 2,  # 'о'
+        15: 1,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 1,  # 'т'
+        14: 3,  # 'у'
+        39: 1,  # 'ф'
+        26: 0,  # 'х'
+        28: 1,  # 'ц'
+        22: 2,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 2,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    20: {  # 'з'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 3,  # 'б'
+        10: 3,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 3,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 1,  # 'ц'
+        22: 2,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 2,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 2,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 3,  # 'я'
+    },
+    4: {  # 'и'
+        37: 1,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 3,  # 'б'
+        10: 3,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 3,  # 'з'
+        4: 3,  # 'и'
+        23: 3,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 2,  # 'у'
+        39: 2,  # 'ф'
+        26: 3,  # 'х'
+        28: 3,  # 'ц'
+        22: 3,  # 'ч'
+        25: 3,  # 'ш'
+        29: 3,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 2,  # 'э'
+        27: 3,  # 'ю'
+        16: 3,  # 'я'
+    },
+    23: {  # 'й'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 1,  # 'а'
+        21: 1,  # 'б'
+        10: 1,  # 'в'
+        19: 2,  # 'г'
+        13: 3,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 2,  # 'з'
+        4: 1,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 2,  # 'о'
+        15: 1,  # 'п'
+        9: 2,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 1,  # 'у'
+        39: 2,  # 'ф'
+        26: 1,  # 'х'
+        28: 2,  # 'ц'
+        22: 3,  # 'ч'
+        25: 2,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 2,  # 'я'
+    },
+    11: {  # 'к'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 3,  # 'в'
+        19: 1,  # 'г'
+        13: 1,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 3,  # 'л'
+        12: 1,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 1,  # 'ф'
+        26: 2,  # 'х'
+        28: 2,  # 'ц'
+        22: 1,  # 'ч'
+        25: 2,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 1,  # 'ы'
+        17: 1,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    8: {  # 'л'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 3,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 2,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 1,  # 'р'
+        7: 3,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 2,  # 'х'
+        28: 1,  # 'ц'
+        22: 3,  # 'ч'
+        25: 2,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 3,  # 'ь'
+        30: 1,  # 'э'
+        27: 3,  # 'ю'
+        16: 3,  # 'я'
+    },
+    12: {  # 'м'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 2,  # 'г'
+        13: 1,  # 'д'
+        2: 3,  # 'е'
+        24: 1,  # 'ж'
+        20: 1,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 3,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 2,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 1,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 2,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 3,  # 'я'
+    },
+    5: {  # 'н'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 1,  # 'п'
+        9: 2,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 2,  # 'х'
+        28: 3,  # 'ц'
+        22: 3,  # 'ч'
+        25: 2,  # 'ш'
+        29: 2,  # 'щ'
+        54: 1,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 3,  # 'ь'
+        30: 1,  # 'э'
+        27: 3,  # 'ю'
+        16: 3,  # 'я'
+    },
+    1: {  # 'о'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 3,  # 'б'
+        10: 3,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 3,  # 'з'
+        4: 3,  # 'и'
+        23: 3,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 2,  # 'у'
+        39: 2,  # 'ф'
+        26: 3,  # 'х'
+        28: 2,  # 'ц'
+        22: 3,  # 'ч'
+        25: 3,  # 'ш'
+        29: 3,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 2,  # 'э'
+        27: 3,  # 'ю'
+        16: 3,  # 'я'
+    },
+    15: {  # 'п'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 3,  # 'л'
+        12: 1,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 3,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 1,  # 'ф'
+        26: 0,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 1,  # 'ш'
+        29: 1,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 2,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 3,  # 'я'
+    },
+    9: {  # 'р'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 3,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 2,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 2,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 3,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 3,  # 'ш'
+        29: 2,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 3,  # 'ь'
+        30: 2,  # 'э'
+        27: 2,  # 'ю'
+        16: 3,  # 'я'
+    },
+    7: {  # 'с'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 1,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 3,  # 'в'
+        19: 2,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 3,  # 'х'
+        28: 2,  # 'ц'
+        22: 3,  # 'ч'
+        25: 2,  # 'ш'
+        29: 1,  # 'щ'
+        54: 2,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 3,  # 'ь'
+        30: 2,  # 'э'
+        27: 3,  # 'ю'
+        16: 3,  # 'я'
+    },
+    6: {  # 'т'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 2,  # 'б'
+        10: 3,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 1,  # 'ж'
+        20: 1,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 2,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 2,  # 'ш'
+        29: 2,  # 'щ'
+        54: 2,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 3,  # 'ь'
+        30: 2,  # 'э'
+        27: 2,  # 'ю'
+        16: 3,  # 'я'
+    },
+    14: {  # 'у'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 3,  # 'б'
+        10: 3,  # 'в'
+        19: 3,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 3,  # 'з'
+        4: 2,  # 'и'
+        23: 2,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 2,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 1,  # 'у'
+        39: 2,  # 'ф'
+        26: 3,  # 'х'
+        28: 2,  # 'ц'
+        22: 3,  # 'ч'
+        25: 3,  # 'ш'
+        29: 3,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 2,  # 'э'
+        27: 3,  # 'ю'
+        16: 2,  # 'я'
+    },
+    39: {  # 'ф'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 0,  # 'в'
+        19: 1,  # 'г'
+        13: 0,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 1,  # 'н'
+        1: 3,  # 'о'
+        15: 1,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 2,  # 'у'
+        39: 2,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 1,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 2,  # 'ы'
+        17: 1,  # 'ь'
+        30: 2,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    26: {  # 'х'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 0,  # 'б'
+        10: 3,  # 'в'
+        19: 1,  # 'г'
+        13: 1,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 1,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 1,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 1,  # 'п'
+        9: 3,  # 'р'
+        7: 2,  # 'с'
+        6: 2,  # 'т'
+        14: 2,  # 'у'
+        39: 1,  # 'ф'
+        26: 1,  # 'х'
+        28: 1,  # 'ц'
+        22: 1,  # 'ч'
+        25: 2,  # 'ш'
+        29: 0,  # 'щ'
+        54: 1,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 1,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    28: {  # 'ц'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 2,  # 'в'
+        19: 1,  # 'г'
+        13: 1,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 1,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 2,  # 'к'
+        8: 1,  # 'л'
+        12: 1,  # 'м'
+        5: 1,  # 'н'
+        1: 3,  # 'о'
+        15: 0,  # 'п'
+        9: 1,  # 'р'
+        7: 0,  # 'с'
+        6: 1,  # 'т'
+        14: 3,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 1,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 3,  # 'ы'
+        17: 1,  # 'ь'
+        30: 0,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    22: {  # 'ч'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 1,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 3,  # 'е'
+        24: 1,  # 'ж'
+        20: 0,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 2,  # 'л'
+        12: 1,  # 'м'
+        5: 3,  # 'н'
+        1: 2,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 1,  # 'с'
+        6: 3,  # 'т'
+        14: 3,  # 'у'
+        39: 1,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 1,  # 'ч'
+        25: 2,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 3,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    25: {  # 'ш'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 1,  # 'б'
+        10: 2,  # 'в'
+        19: 1,  # 'г'
+        13: 0,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 2,  # 'м'
+        5: 3,  # 'н'
+        1: 3,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 1,  # 'с'
+        6: 2,  # 'т'
+        14: 3,  # 'у'
+        39: 2,  # 'ф'
+        26: 1,  # 'х'
+        28: 1,  # 'ц'
+        22: 1,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 3,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 0,  # 'я'
+    },
+    29: {  # 'щ'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 3,  # 'а'
+        21: 0,  # 'б'
+        10: 1,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 3,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 3,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 1,  # 'м'
+        5: 2,  # 'н'
+        1: 1,  # 'о'
+        15: 0,  # 'п'
+        9: 2,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 2,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 2,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 0,  # 'я'
+    },
+    54: {  # 'ъ'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 0,  # 'б'
+        10: 0,  # 'в'
+        19: 0,  # 'г'
+        13: 0,  # 'д'
+        2: 2,  # 'е'
+        24: 0,  # 'ж'
+        20: 0,  # 'з'
+        4: 0,  # 'и'
+        23: 0,  # 'й'
+        11: 0,  # 'к'
+        8: 0,  # 'л'
+        12: 0,  # 'м'
+        5: 0,  # 'н'
+        1: 0,  # 'о'
+        15: 0,  # 'п'
+        9: 0,  # 'р'
+        7: 0,  # 'с'
+        6: 0,  # 'т'
+        14: 0,  # 'у'
+        39: 0,  # 'ф'
+        26: 0,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 0,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 1,  # 'ю'
+        16: 2,  # 'я'
+    },
+    18: {  # 'ы'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 3,  # 'б'
+        10: 3,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 2,  # 'и'
+        23: 3,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 1,  # 'о'
+        15: 3,  # 'п'
+        9: 3,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 1,  # 'у'
+        39: 0,  # 'ф'
+        26: 3,  # 'х'
+        28: 2,  # 'ц'
+        22: 3,  # 'ч'
+        25: 3,  # 'ш'
+        29: 2,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 0,  # 'ю'
+        16: 2,  # 'я'
+    },
+    17: {  # 'ь'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 2,  # 'б'
+        10: 2,  # 'в'
+        19: 2,  # 'г'
+        13: 2,  # 'д'
+        2: 3,  # 'е'
+        24: 1,  # 'ж'
+        20: 3,  # 'з'
+        4: 2,  # 'и'
+        23: 0,  # 'й'
+        11: 3,  # 'к'
+        8: 0,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 2,  # 'о'
+        15: 2,  # 'п'
+        9: 1,  # 'р'
+        7: 3,  # 'с'
+        6: 2,  # 'т'
+        14: 0,  # 'у'
+        39: 2,  # 'ф'
+        26: 1,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 3,  # 'ш'
+        29: 2,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 3,  # 'ю'
+        16: 3,  # 'я'
+    },
+    30: {  # 'э'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 1,  # 'М'
+        31: 1,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 1,  # 'Р'
+        32: 1,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 1,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 1,  # 'б'
+        10: 1,  # 'в'
+        19: 1,  # 'г'
+        13: 2,  # 'д'
+        2: 1,  # 'е'
+        24: 0,  # 'ж'
+        20: 1,  # 'з'
+        4: 0,  # 'и'
+        23: 2,  # 'й'
+        11: 2,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 2,  # 'н'
+        1: 0,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 2,  # 'с'
+        6: 3,  # 'т'
+        14: 1,  # 'у'
+        39: 2,  # 'ф'
+        26: 1,  # 'х'
+        28: 0,  # 'ц'
+        22: 0,  # 'ч'
+        25: 1,  # 'ш'
+        29: 0,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 1,  # 'ю'
+        16: 1,  # 'я'
+    },
+    27: {  # 'ю'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 2,  # 'а'
+        21: 3,  # 'б'
+        10: 1,  # 'в'
+        19: 2,  # 'г'
+        13: 3,  # 'д'
+        2: 1,  # 'е'
+        24: 2,  # 'ж'
+        20: 2,  # 'з'
+        4: 1,  # 'и'
+        23: 1,  # 'й'
+        11: 2,  # 'к'
+        8: 2,  # 'л'
+        12: 2,  # 'м'
+        5: 2,  # 'н'
+        1: 1,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 0,  # 'у'
+        39: 1,  # 'ф'
+        26: 2,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 2,  # 'ш'
+        29: 3,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 1,  # 'э'
+        27: 2,  # 'ю'
+        16: 1,  # 'я'
+    },
+    16: {  # 'я'
+        37: 0,  # 'А'
+        44: 0,  # 'Б'
+        33: 0,  # 'В'
+        46: 0,  # 'Г'
+        41: 0,  # 'Д'
+        48: 0,  # 'Е'
+        56: 0,  # 'Ж'
+        51: 0,  # 'З'
+        42: 0,  # 'И'
+        60: 0,  # 'Й'
+        36: 0,  # 'К'
+        49: 0,  # 'Л'
+        38: 0,  # 'М'
+        31: 0,  # 'Н'
+        34: 0,  # 'О'
+        35: 0,  # 'П'
+        45: 0,  # 'Р'
+        32: 0,  # 'С'
+        40: 0,  # 'Т'
+        52: 0,  # 'У'
+        53: 0,  # 'Ф'
+        55: 0,  # 'Х'
+        58: 0,  # 'Ц'
+        50: 0,  # 'Ч'
+        57: 0,  # 'Ш'
+        63: 0,  # 'Щ'
+        62: 0,  # 'Ы'
+        61: 0,  # 'Ь'
+        47: 0,  # 'Э'
+        59: 0,  # 'Ю'
+        43: 0,  # 'Я'
+        3: 0,  # 'а'
+        21: 2,  # 'б'
+        10: 3,  # 'в'
+        19: 2,  # 'г'
+        13: 3,  # 'д'
+        2: 3,  # 'е'
+        24: 3,  # 'ж'
+        20: 3,  # 'з'
+        4: 2,  # 'и'
+        23: 2,  # 'й'
+        11: 3,  # 'к'
+        8: 3,  # 'л'
+        12: 3,  # 'м'
+        5: 3,  # 'н'
+        1: 0,  # 'о'
+        15: 2,  # 'п'
+        9: 2,  # 'р'
+        7: 3,  # 'с'
+        6: 3,  # 'т'
+        14: 1,  # 'у'
+        39: 1,  # 'ф'
+        26: 3,  # 'х'
+        28: 2,  # 'ц'
+        22: 2,  # 'ч'
+        25: 2,  # 'ш'
+        29: 3,  # 'щ'
+        54: 0,  # 'ъ'
+        18: 0,  # 'ы'
+        17: 0,  # 'ь'
+        30: 0,  # 'э'
+        27: 2,  # 'ю'
+        16: 2,  # 'я'
+    },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+IBM866_RUSSIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 142,  # 'A'
+    66: 143,  # 'B'
+    67: 144,  # 'C'
+    68: 145,  # 'D'
+    69: 146,  # 'E'
+    70: 147,  # 'F'
+    71: 148,  # 'G'
+    72: 149,  # 'H'
+    73: 150,  # 'I'
+    74: 151,  # 'J'
+    75: 152,  # 'K'
+    76: 74,  # 'L'
+    77: 153,  # 'M'
+    78: 75,  # 'N'
+    79: 154,  # 'O'
+    80: 155,  # 'P'
+    81: 156,  # 'Q'
+    82: 157,  # 'R'
+    83: 158,  # 'S'
+    84: 159,  # 'T'
+    85: 160,  # 'U'
+    86: 161,  # 'V'
+    87: 162,  # 'W'
+    88: 163,  # 'X'
+    89: 164,  # 'Y'
+    90: 165,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 71,  # 'a'
+    98: 172,  # 'b'
+    99: 66,  # 'c'
+    100: 173,  # 'd'
+    101: 65,  # 'e'
+    102: 174,  # 'f'
+    103: 76,  # 'g'
+    104: 175,  # 'h'
+    105: 64,  # 'i'
+    106: 176,  # 'j'
+    107: 177,  # 'k'
+    108: 77,  # 'l'
+    109: 72,  # 'm'
+    110: 178,  # 'n'
+    111: 69,  # 'o'
+    112: 67,  # 'p'
+    113: 179,  # 'q'
+    114: 78,  # 'r'
+    115: 73,  # 's'
+    116: 180,  # 't'
+    117: 181,  # 'u'
+    118: 79,  # 'v'
+    119: 182,  # 'w'
+    120: 183,  # 'x'
+    121: 184,  # 'y'
+    122: 185,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 37,  # 'А'
+    129: 44,  # 'Б'
+    130: 33,  # 'В'
+    131: 46,  # 'Г'
+    132: 41,  # 'Д'
+    133: 48,  # 'Е'
+    134: 56,  # 'Ж'
+    135: 51,  # 'З'
+    136: 42,  # 'И'
+    137: 60,  # 'Й'
+    138: 36,  # 'К'
+    139: 49,  # 'Л'
+    140: 38,  # 'М'
+    141: 31,  # 'Н'
+    142: 34,  # 'О'
+    143: 35,  # 'П'
+    144: 45,  # 'Р'
+    145: 32,  # 'С'
+    146: 40,  # 'Т'
+    147: 52,  # 'У'
+    148: 53,  # 'Ф'
+    149: 55,  # 'Х'
+    150: 58,  # 'Ц'
+    151: 50,  # 'Ч'
+    152: 57,  # 'Ш'
+    153: 63,  # 'Щ'
+    154: 70,  # 'Ъ'
+    155: 62,  # 'Ы'
+    156: 61,  # 'Ь'
+    157: 47,  # 'Э'
+    158: 59,  # 'Ю'
+    159: 43,  # 'Я'
+    160: 3,  # 'а'
+    161: 21,  # 'б'
+    162: 10,  # 'в'
+    163: 19,  # 'г'
+    164: 13,  # 'д'
+    165: 2,  # 'е'
+    166: 24,  # 'ж'
+    167: 20,  # 'з'
+    168: 4,  # 'и'
+    169: 23,  # 'й'
+    170: 11,  # 'к'
+    171: 8,  # 'л'
+    172: 12,  # 'м'
+    173: 5,  # 'н'
+    174: 1,  # 'о'
+    175: 15,  # 'п'
+    176: 191,  # '░'
+    177: 192,  # '▒'
+    178: 193,  # '▓'
+    179: 194,  # '│'
+    180: 195,  # '┤'
+    181: 196,  # '╡'
+    182: 197,  # '╢'
+    183: 198,  # '╖'
+    184: 199,  # '╕'
+    185: 200,  # '╣'
+    186: 201,  # '║'
+    187: 202,  # '╗'
+    188: 203,  # '╝'
+    189: 204,  # '╜'
+    190: 205,  # '╛'
+    191: 206,  # '┐'
+    192: 207,  # '└'
+    193: 208,  # '┴'
+    194: 209,  # '┬'
+    195: 210,  # '├'
+    196: 211,  # '─'
+    197: 212,  # '┼'
+    198: 213,  # '╞'
+    199: 214,  # '╟'
+    200: 215,  # '╚'
+    201: 216,  # '╔'
+    202: 217,  # '╩'
+    203: 218,  # '╦'
+    204: 219,  # '╠'
+    205: 220,  # '═'
+    206: 221,  # '╬'
+    207: 222,  # '╧'
+    208: 223,  # '╨'
+    209: 224,  # '╤'
+    210: 225,  # '╥'
+    211: 226,  # '╙'
+    212: 227,  # '╘'
+    213: 228,  # '╒'
+    214: 229,  # '╓'
+    215: 230,  # '╫'
+    216: 231,  # '╪'
+    217: 232,  # '┘'
+    218: 233,  # '┌'
+    219: 234,  # '█'
+    220: 235,  # '▄'
+    221: 236,  # '▌'
+    222: 237,  # '▐'
+    223: 238,  # '▀'
+    224: 9,  # 'р'
+    225: 7,  # 'с'
+    226: 6,  # 'т'
+    227: 14,  # 'у'
+    228: 39,  # 'ф'
+    229: 26,  # 'х'
+    230: 28,  # 'ц'
+    231: 22,  # 'ч'
+    232: 25,  # 'ш'
+    233: 29,  # 'щ'
+    234: 54,  # 'ъ'
+    235: 18,  # 'ы'
+    236: 17,  # 'ь'
+    237: 30,  # 'э'
+    238: 27,  # 'ю'
+    239: 16,  # 'я'
+    240: 239,  # 'Ё'
+    241: 68,  # 'ё'
+    242: 240,  # 'Є'
+    243: 241,  # 'є'
+    244: 242,  # 'Ї'
+    245: 243,  # 'ї'
+    246: 244,  # 'Ў'
+    247: 245,  # 'ў'
+    248: 246,  # '°'
+    249: 247,  # '∙'
+    250: 248,  # '·'
+    251: 249,  # '√'
+    252: 250,  # '№'
+    253: 251,  # '¤'
+    254: 252,  # '■'
+    255: 255,  # '\xa0'
+}
+
+IBM866_RUSSIAN_MODEL = SingleByteCharSetModel(
+    charset_name="IBM866",
+    language="Russian",
+    char_to_order_map=IBM866_RUSSIAN_CHAR_TO_ORDER,
+    language_model=RUSSIAN_LANG_MODEL,
+    typical_positive_ratio=0.976601,
+    keep_ascii_letters=False,
+    alphabet="ЁАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюяё",
+)
+
+WINDOWS_1251_RUSSIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 142,  # 'A'
+    66: 143,  # 'B'
+    67: 144,  # 'C'
+    68: 145,  # 'D'
+    69: 146,  # 'E'
+    70: 147,  # 'F'
+    71: 148,  # 'G'
+    72: 149,  # 'H'
+    73: 150,  # 'I'
+    74: 151,  # 'J'
+    75: 152,  # 'K'
+    76: 74,  # 'L'
+    77: 153,  # 'M'
+    78: 75,  # 'N'
+    79: 154,  # 'O'
+    80: 155,  # 'P'
+    81: 156,  # 'Q'
+    82: 157,  # 'R'
+    83: 158,  # 'S'
+    84: 159,  # 'T'
+    85: 160,  # 'U'
+    86: 161,  # 'V'
+    87: 162,  # 'W'
+    88: 163,  # 'X'
+    89: 164,  # 'Y'
+    90: 165,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 71,  # 'a'
+    98: 172,  # 'b'
+    99: 66,  # 'c'
+    100: 173,  # 'd'
+    101: 65,  # 'e'
+    102: 174,  # 'f'
+    103: 76,  # 'g'
+    104: 175,  # 'h'
+    105: 64,  # 'i'
+    106: 176,  # 'j'
+    107: 177,  # 'k'
+    108: 77,  # 'l'
+    109: 72,  # 'm'
+    110: 178,  # 'n'
+    111: 69,  # 'o'
+    112: 67,  # 'p'
+    113: 179,  # 'q'
+    114: 78,  # 'r'
+    115: 73,  # 's'
+    116: 180,  # 't'
+    117: 181,  # 'u'
+    118: 79,  # 'v'
+    119: 182,  # 'w'
+    120: 183,  # 'x'
+    121: 184,  # 'y'
+    122: 185,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 191,  # 'Ђ'
+    129: 192,  # 'Ѓ'
+    130: 193,  # '‚'
+    131: 194,  # 'ѓ'
+    132: 195,  # '„'
+    133: 196,  # '…'
+    134: 197,  # '†'
+    135: 198,  # '‡'
+    136: 199,  # '€'
+    137: 200,  # '‰'
+    138: 201,  # 'Љ'
+    139: 202,  # '‹'
+    140: 203,  # 'Њ'
+    141: 204,  # 'Ќ'
+    142: 205,  # 'Ћ'
+    143: 206,  # 'Џ'
+    144: 207,  # 'ђ'
+    145: 208,  # '‘'
+    146: 209,  # '’'
+    147: 210,  # '“'
+    148: 211,  # '”'
+    149: 212,  # '•'
+    150: 213,  # '–'
+    151: 214,  # '—'
+    152: 215,  # None
+    153: 216,  # '™'
+    154: 217,  # 'љ'
+    155: 218,  # '›'
+    156: 219,  # 'њ'
+    157: 220,  # 'ќ'
+    158: 221,  # 'ћ'
+    159: 222,  # 'џ'
+    160: 223,  # '\xa0'
+    161: 224,  # 'Ў'
+    162: 225,  # 'ў'
+    163: 226,  # 'Ј'
+    164: 227,  # '¤'
+    165: 228,  # 'Ґ'
+    166: 229,  # '¦'
+    167: 230,  # '§'
+    168: 231,  # 'Ё'
+    169: 232,  # '©'
+    170: 233,  # 'Є'
+    171: 234,  # '«'
+    172: 235,  # '¬'
+    173: 236,  # '\xad'
+    174: 237,  # '®'
+    175: 238,  # 'Ї'
+    176: 239,  # '°'
+    177: 240,  # '±'
+    178: 241,  # 'І'
+    179: 242,  # 'і'
+    180: 243,  # 'ґ'
+    181: 244,  # 'µ'
+    182: 245,  # '¶'
+    183: 246,  # '·'
+    184: 68,  # 'ё'
+    185: 247,  # '№'
+    186: 248,  # 'є'
+    187: 249,  # '»'
+    188: 250,  # 'ј'
+    189: 251,  # 'Ѕ'
+    190: 252,  # 'ѕ'
+    191: 253,  # 'ї'
+    192: 37,  # 'А'
+    193: 44,  # 'Б'
+    194: 33,  # 'В'
+    195: 46,  # 'Г'
+    196: 41,  # 'Д'
+    197: 48,  # 'Е'
+    198: 56,  # 'Ж'
+    199: 51,  # 'З'
+    200: 42,  # 'И'
+    201: 60,  # 'Й'
+    202: 36,  # 'К'
+    203: 49,  # 'Л'
+    204: 38,  # 'М'
+    205: 31,  # 'Н'
+    206: 34,  # 'О'
+    207: 35,  # 'П'
+    208: 45,  # 'Р'
+    209: 32,  # 'С'
+    210: 40,  # 'Т'
+    211: 52,  # 'У'
+    212: 53,  # 'Ф'
+    213: 55,  # 'Х'
+    214: 58,  # 'Ц'
+    215: 50,  # 'Ч'
+    216: 57,  # 'Ш'
+    217: 63,  # 'Щ'
+    218: 70,  # 'Ъ'
+    219: 62,  # 'Ы'
+    220: 61,  # 'Ь'
+    221: 47,  # 'Э'
+    222: 59,  # 'Ю'
+    223: 43,  # 'Я'
+    224: 3,  # 'а'
+    225: 21,  # 'б'
+    226: 10,  # 'в'
+    227: 19,  # 'г'
+    228: 13,  # 'д'
+    229: 2,  # 'е'
+    230: 24,  # 'ж'
+    231: 20,  # 'з'
+    232: 4,  # 'и'
+    233: 23,  # 'й'
+    234: 11,  # 'к'
+    235: 8,  # 'л'
+    236: 12,  # 'м'
+    237: 5,  # 'н'
+    238: 1,  # 'о'
+    239: 15,  # 'п'
+    240: 9,  # 'р'
+    241: 7,  # 'с'
+    242: 6,  # 'т'
+    243: 14,  # 'у'
+    244: 39,  # 'ф'
+    245: 26,  # 'х'
+    246: 28,  # 'ц'
+    247: 22,  # 'ч'
+    248: 25,  # 'ш'
+    249: 29,  # 'щ'
+    250: 54,  # 'ъ'
+    251: 18,  # 'ы'
+    252: 17,  # 'ь'
+    253: 30,  # 'э'
+    254: 27,  # 'ю'
+    255: 16,  # 'я'
+}
+
+WINDOWS_1251_RUSSIAN_MODEL = SingleByteCharSetModel(
+    charset_name="windows-1251",
+    language="Russian",
+    char_to_order_map=WINDOWS_1251_RUSSIAN_CHAR_TO_ORDER,
+    language_model=RUSSIAN_LANG_MODEL,
+    typical_positive_ratio=0.976601,
+    keep_ascii_letters=False,
+    alphabet="ЁАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюяё",
+)
+
+IBM855_RUSSIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 142,  # 'A'
+    66: 143,  # 'B'
+    67: 144,  # 'C'
+    68: 145,  # 'D'
+    69: 146,  # 'E'
+    70: 147,  # 'F'
+    71: 148,  # 'G'
+    72: 149,  # 'H'
+    73: 150,  # 'I'
+    74: 151,  # 'J'
+    75: 152,  # 'K'
+    76: 74,  # 'L'
+    77: 153,  # 'M'
+    78: 75,  # 'N'
+    79: 154,  # 'O'
+    80: 155,  # 'P'
+    81: 156,  # 'Q'
+    82: 157,  # 'R'
+    83: 158,  # 'S'
+    84: 159,  # 'T'
+    85: 160,  # 'U'
+    86: 161,  # 'V'
+    87: 162,  # 'W'
+    88: 163,  # 'X'
+    89: 164,  # 'Y'
+    90: 165,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 71,  # 'a'
+    98: 172,  # 'b'
+    99: 66,  # 'c'
+    100: 173,  # 'd'
+    101: 65,  # 'e'
+    102: 174,  # 'f'
+    103: 76,  # 'g'
+    104: 175,  # 'h'
+    105: 64,  # 'i'
+    106: 176,  # 'j'
+    107: 177,  # 'k'
+    108: 77,  # 'l'
+    109: 72,  # 'm'
+    110: 178,  # 'n'
+    111: 69,  # 'o'
+    112: 67,  # 'p'
+    113: 179,  # 'q'
+    114: 78,  # 'r'
+    115: 73,  # 's'
+    116: 180,  # 't'
+    117: 181,  # 'u'
+    118: 79,  # 'v'
+    119: 182,  # 'w'
+    120: 183,  # 'x'
+    121: 184,  # 'y'
+    122: 185,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 191,  # 'ђ'
+    129: 192,  # 'Ђ'
+    130: 193,  # 'ѓ'
+    131: 194,  # 'Ѓ'
+    132: 68,  # 'ё'
+    133: 195,  # 'Ё'
+    134: 196,  # 'є'
+    135: 197,  # 'Є'
+    136: 198,  # 'ѕ'
+    137: 199,  # 'Ѕ'
+    138: 200,  # 'і'
+    139: 201,  # 'І'
+    140: 202,  # 'ї'
+    141: 203,  # 'Ї'
+    142: 204,  # 'ј'
+    143: 205,  # 'Ј'
+    144: 206,  # 'љ'
+    145: 207,  # 'Љ'
+    146: 208,  # 'њ'
+    147: 209,  # 'Њ'
+    148: 210,  # 'ћ'
+    149: 211,  # 'Ћ'
+    150: 212,  # 'ќ'
+    151: 213,  # 'Ќ'
+    152: 214,  # 'ў'
+    153: 215,  # 'Ў'
+    154: 216,  # 'џ'
+    155: 217,  # 'Џ'
+    156: 27,  # 'ю'
+    157: 59,  # 'Ю'
+    158: 54,  # 'ъ'
+    159: 70,  # 'Ъ'
+    160: 3,  # 'а'
+    161: 37,  # 'А'
+    162: 21,  # 'б'
+    163: 44,  # 'Б'
+    164: 28,  # 'ц'
+    165: 58,  # 'Ц'
+    166: 13,  # 'д'
+    167: 41,  # 'Д'
+    168: 2,  # 'е'
+    169: 48,  # 'Е'
+    170: 39,  # 'ф'
+    171: 53,  # 'Ф'
+    172: 19,  # 'г'
+    173: 46,  # 'Г'
+    174: 218,  # '«'
+    175: 219,  # '»'
+    176: 220,  # '░'
+    177: 221,  # '▒'
+    178: 222,  # '▓'
+    179: 223,  # '│'
+    180: 224,  # '┤'
+    181: 26,  # 'х'
+    182: 55,  # 'Х'
+    183: 4,  # 'и'
+    184: 42,  # 'И'
+    185: 225,  # '╣'
+    186: 226,  # '║'
+    187: 227,  # '╗'
+    188: 228,  # '╝'
+    189: 23,  # 'й'
+    190: 60,  # 'Й'
+    191: 229,  # '┐'
+    192: 230,  # '└'
+    193: 231,  # '┴'
+    194: 232,  # '┬'
+    195: 233,  # '├'
+    196: 234,  # '─'
+    197: 235,  # '┼'
+    198: 11,  # 'к'
+    199: 36,  # 'К'
+    200: 236,  # '╚'
+    201: 237,  # '╔'
+    202: 238,  # '╩'
+    203: 239,  # '╦'
+    204: 240,  # '╠'
+    205: 241,  # '═'
+    206: 242,  # '╬'
+    207: 243,  # '¤'
+    208: 8,  # 'л'
+    209: 49,  # 'Л'
+    210: 12,  # 'м'
+    211: 38,  # 'М'
+    212: 5,  # 'н'
+    213: 31,  # 'Н'
+    214: 1,  # 'о'
+    215: 34,  # 'О'
+    216: 15,  # 'п'
+    217: 244,  # '┘'
+    218: 245,  # '┌'
+    219: 246,  # '█'
+    220: 247,  # '▄'
+    221: 35,  # 'П'
+    222: 16,  # 'я'
+    223: 248,  # '▀'
+    224: 43,  # 'Я'
+    225: 9,  # 'р'
+    226: 45,  # 'Р'
+    227: 7,  # 'с'
+    228: 32,  # 'С'
+    229: 6,  # 'т'
+    230: 40,  # 'Т'
+    231: 14,  # 'у'
+    232: 52,  # 'У'
+    233: 24,  # 'ж'
+    234: 56,  # 'Ж'
+    235: 10,  # 'в'
+    236: 33,  # 'В'
+    237: 17,  # 'ь'
+    238: 61,  # 'Ь'
+    239: 249,  # '№'
+    240: 250,  # '\xad'
+    241: 18,  # 'ы'
+    242: 62,  # 'Ы'
+    243: 20,  # 'з'
+    244: 51,  # 'З'
+    245: 25,  # 'ш'
+    246: 57,  # 'Ш'
+    247: 30,  # 'э'
+    248: 47,  # 'Э'
+    249: 29,  # 'щ'
+    250: 63,  # 'Щ'
+    251: 22,  # 'ч'
+    252: 50,  # 'Ч'
+    253: 251,  # '§'
+    254: 252,  # '■'
+    255: 255,  # '\xa0'
+}
+
+IBM855_RUSSIAN_MODEL = SingleByteCharSetModel(
+    charset_name="IBM855",
+    language="Russian",
+    char_to_order_map=IBM855_RUSSIAN_CHAR_TO_ORDER,
+    language_model=RUSSIAN_LANG_MODEL,
+    typical_positive_ratio=0.976601,
+    keep_ascii_letters=False,
+    alphabet="ЁАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюяё",
+)
+
+KOI8_R_RUSSIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 142,  # 'A'
+    66: 143,  # 'B'
+    67: 144,  # 'C'
+    68: 145,  # 'D'
+    69: 146,  # 'E'
+    70: 147,  # 'F'
+    71: 148,  # 'G'
+    72: 149,  # 'H'
+    73: 150,  # 'I'
+    74: 151,  # 'J'
+    75: 152,  # 'K'
+    76: 74,  # 'L'
+    77: 153,  # 'M'
+    78: 75,  # 'N'
+    79: 154,  # 'O'
+    80: 155,  # 'P'
+    81: 156,  # 'Q'
+    82: 157,  # 'R'
+    83: 158,  # 'S'
+    84: 159,  # 'T'
+    85: 160,  # 'U'
+    86: 161,  # 'V'
+    87: 162,  # 'W'
+    88: 163,  # 'X'
+    89: 164,  # 'Y'
+    90: 165,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 71,  # 'a'
+    98: 172,  # 'b'
+    99: 66,  # 'c'
+    100: 173,  # 'd'
+    101: 65,  # 'e'
+    102: 174,  # 'f'
+    103: 76,  # 'g'
+    104: 175,  # 'h'
+    105: 64,  # 'i'
+    106: 176,  # 'j'
+    107: 177,  # 'k'
+    108: 77,  # 'l'
+    109: 72,  # 'm'
+    110: 178,  # 'n'
+    111: 69,  # 'o'
+    112: 67,  # 'p'
+    113: 179,  # 'q'
+    114: 78,  # 'r'
+    115: 73,  # 's'
+    116: 180,  # 't'
+    117: 181,  # 'u'
+    118: 79,  # 'v'
+    119: 182,  # 'w'
+    120: 183,  # 'x'
+    121: 184,  # 'y'
+    122: 185,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 191,  # '─'
+    129: 192,  # '│'
+    130: 193,  # '┌'
+    131: 194,  # '┐'
+    132: 195,  # '└'
+    133: 196,  # '┘'
+    134: 197,  # '├'
+    135: 198,  # '┤'
+    136: 199,  # '┬'
+    137: 200,  # '┴'
+    138: 201,  # '┼'
+    139: 202,  # '▀'
+    140: 203,  # '▄'
+    141: 204,  # '█'
+    142: 205,  # '▌'
+    143: 206,  # '▐'
+    144: 207,  # '░'
+    145: 208,  # '▒'
+    146: 209,  # '▓'
+    147: 210,  # '⌠'
+    148: 211,  # '■'
+    149: 212,  # '∙'
+    150: 213,  # '√'
+    151: 214,  # '≈'
+    152: 215,  # '≤'
+    153: 216,  # '≥'
+    154: 217,  # '\xa0'
+    155: 218,  # '⌡'
+    156: 219,  # '°'
+    157: 220,  # '²'
+    158: 221,  # '·'
+    159: 222,  # '÷'
+    160: 223,  # '═'
+    161: 224,  # '║'
+    162: 225,  # '╒'
+    163: 68,  # 'ё'
+    164: 226,  # '╓'
+    165: 227,  # '╔'
+    166: 228,  # '╕'
+    167: 229,  # '╖'
+    168: 230,  # '╗'
+    169: 231,  # '╘'
+    170: 232,  # '╙'
+    171: 233,  # '╚'
+    172: 234,  # '╛'
+    173: 235,  # '╜'
+    174: 236,  # '╝'
+    175: 237,  # '╞'
+    176: 238,  # '╟'
+    177: 239,  # '╠'
+    178: 240,  # '╡'
+    179: 241,  # 'Ё'
+    180: 242,  # '╢'
+    181: 243,  # '╣'
+    182: 244,  # '╤'
+    183: 245,  # '╥'
+    184: 246,  # '╦'
+    185: 247,  # '╧'
+    186: 248,  # '╨'
+    187: 249,  # '╩'
+    188: 250,  # '╪'
+    189: 251,  # '╫'
+    190: 252,  # '╬'
+    191: 253,  # '©'
+    192: 27,  # 'ю'
+    193: 3,  # 'а'
+    194: 21,  # 'б'
+    195: 28,  # 'ц'
+    196: 13,  # 'д'
+    197: 2,  # 'е'
+    198: 39,  # 'ф'
+    199: 19,  # 'г'
+    200: 26,  # 'х'
+    201: 4,  # 'и'
+    202: 23,  # 'й'
+    203: 11,  # 'к'
+    204: 8,  # 'л'
+    205: 12,  # 'м'
+    206: 5,  # 'н'
+    207: 1,  # 'о'
+    208: 15,  # 'п'
+    209: 16,  # 'я'
+    210: 9,  # 'р'
+    211: 7,  # 'с'
+    212: 6,  # 'т'
+    213: 14,  # 'у'
+    214: 24,  # 'ж'
+    215: 10,  # 'в'
+    216: 17,  # 'ь'
+    217: 18,  # 'ы'
+    218: 20,  # 'з'
+    219: 25,  # 'ш'
+    220: 30,  # 'э'
+    221: 29,  # 'щ'
+    222: 22,  # 'ч'
+    223: 54,  # 'ъ'
+    224: 59,  # 'Ю'
+    225: 37,  # 'А'
+    226: 44,  # 'Б'
+    227: 58,  # 'Ц'
+    228: 41,  # 'Д'
+    229: 48,  # 'Е'
+    230: 53,  # 'Ф'
+    231: 46,  # 'Г'
+    232: 55,  # 'Х'
+    233: 42,  # 'И'
+    234: 60,  # 'Й'
+    235: 36,  # 'К'
+    236: 49,  # 'Л'
+    237: 38,  # 'М'
+    238: 31,  # 'Н'
+    239: 34,  # 'О'
+    240: 35,  # 'П'
+    241: 43,  # 'Я'
+    242: 45,  # 'Р'
+    243: 32,  # 'С'
+    244: 40,  # 'Т'
+    245: 52,  # 'У'
+    246: 56,  # 'Ж'
+    247: 33,  # 'В'
+    248: 61,  # 'Ь'
+    249: 62,  # 'Ы'
+    250: 51,  # 'З'
+    251: 57,  # 'Ш'
+    252: 47,  # 'Э'
+    253: 63,  # 'Щ'
+    254: 50,  # 'Ч'
+    255: 70,  # 'Ъ'
+}
+
+KOI8_R_RUSSIAN_MODEL = SingleByteCharSetModel(
+    charset_name="KOI8-R",
+    language="Russian",
+    char_to_order_map=KOI8_R_RUSSIAN_CHAR_TO_ORDER,
+    language_model=RUSSIAN_LANG_MODEL,
+    typical_positive_ratio=0.976601,
+    keep_ascii_letters=False,
+    alphabet="ЁАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюяё",
+)
+
+MACCYRILLIC_RUSSIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 142,  # 'A'
+    66: 143,  # 'B'
+    67: 144,  # 'C'
+    68: 145,  # 'D'
+    69: 146,  # 'E'
+    70: 147,  # 'F'
+    71: 148,  # 'G'
+    72: 149,  # 'H'
+    73: 150,  # 'I'
+    74: 151,  # 'J'
+    75: 152,  # 'K'
+    76: 74,  # 'L'
+    77: 153,  # 'M'
+    78: 75,  # 'N'
+    79: 154,  # 'O'
+    80: 155,  # 'P'
+    81: 156,  # 'Q'
+    82: 157,  # 'R'
+    83: 158,  # 'S'
+    84: 159,  # 'T'
+    85: 160,  # 'U'
+    86: 161,  # 'V'
+    87: 162,  # 'W'
+    88: 163,  # 'X'
+    89: 164,  # 'Y'
+    90: 165,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 71,  # 'a'
+    98: 172,  # 'b'
+    99: 66,  # 'c'
+    100: 173,  # 'd'
+    101: 65,  # 'e'
+    102: 174,  # 'f'
+    103: 76,  # 'g'
+    104: 175,  # 'h'
+    105: 64,  # 'i'
+    106: 176,  # 'j'
+    107: 177,  # 'k'
+    108: 77,  # 'l'
+    109: 72,  # 'm'
+    110: 178,  # 'n'
+    111: 69,  # 'o'
+    112: 67,  # 'p'
+    113: 179,  # 'q'
+    114: 78,  # 'r'
+    115: 73,  # 's'
+    116: 180,  # 't'
+    117: 181,  # 'u'
+    118: 79,  # 'v'
+    119: 182,  # 'w'
+    120: 183,  # 'x'
+    121: 184,  # 'y'
+    122: 185,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 37,  # 'А'
+    129: 44,  # 'Б'
+    130: 33,  # 'В'
+    131: 46,  # 'Г'
+    132: 41,  # 'Д'
+    133: 48,  # 'Е'
+    134: 56,  # 'Ж'
+    135: 51,  # 'З'
+    136: 42,  # 'И'
+    137: 60,  # 'Й'
+    138: 36,  # 'К'
+    139: 49,  # 'Л'
+    140: 38,  # 'М'
+    141: 31,  # 'Н'
+    142: 34,  # 'О'
+    143: 35,  # 'П'
+    144: 45,  # 'Р'
+    145: 32,  # 'С'
+    146: 40,  # 'Т'
+    147: 52,  # 'У'
+    148: 53,  # 'Ф'
+    149: 55,  # 'Х'
+    150: 58,  # 'Ц'
+    151: 50,  # 'Ч'
+    152: 57,  # 'Ш'
+    153: 63,  # 'Щ'
+    154: 70,  # 'Ъ'
+    155: 62,  # 'Ы'
+    156: 61,  # 'Ь'
+    157: 47,  # 'Э'
+    158: 59,  # 'Ю'
+    159: 43,  # 'Я'
+    160: 191,  # '†'
+    161: 192,  # '°'
+    162: 193,  # 'Ґ'
+    163: 194,  # '£'
+    164: 195,  # '§'
+    165: 196,  # '•'
+    166: 197,  # '¶'
+    167: 198,  # 'І'
+    168: 199,  # '®'
+    169: 200,  # '©'
+    170: 201,  # '™'
+    171: 202,  # 'Ђ'
+    172: 203,  # 'ђ'
+    173: 204,  # '≠'
+    174: 205,  # 'Ѓ'
+    175: 206,  # 'ѓ'
+    176: 207,  # '∞'
+    177: 208,  # '±'
+    178: 209,  # '≤'
+    179: 210,  # '≥'
+    180: 211,  # 'і'
+    181: 212,  # 'µ'
+    182: 213,  # 'ґ'
+    183: 214,  # 'Ј'
+    184: 215,  # 'Є'
+    185: 216,  # 'є'
+    186: 217,  # 'Ї'
+    187: 218,  # 'ї'
+    188: 219,  # 'Љ'
+    189: 220,  # 'љ'
+    190: 221,  # 'Њ'
+    191: 222,  # 'њ'
+    192: 223,  # 'ј'
+    193: 224,  # 'Ѕ'
+    194: 225,  # '¬'
+    195: 226,  # '√'
+    196: 227,  # 'ƒ'
+    197: 228,  # '≈'
+    198: 229,  # '∆'
+    199: 230,  # '«'
+    200: 231,  # '»'
+    201: 232,  # '…'
+    202: 233,  # '\xa0'
+    203: 234,  # 'Ћ'
+    204: 235,  # 'ћ'
+    205: 236,  # 'Ќ'
+    206: 237,  # 'ќ'
+    207: 238,  # 'ѕ'
+    208: 239,  # '–'
+    209: 240,  # '—'
+    210: 241,  # '“'
+    211: 242,  # '”'
+    212: 243,  # '‘'
+    213: 244,  # '’'
+    214: 245,  # '÷'
+    215: 246,  # '„'
+    216: 247,  # 'Ў'
+    217: 248,  # 'ў'
+    218: 249,  # 'Џ'
+    219: 250,  # 'џ'
+    220: 251,  # '№'
+    221: 252,  # 'Ё'
+    222: 68,  # 'ё'
+    223: 16,  # 'я'
+    224: 3,  # 'а'
+    225: 21,  # 'б'
+    226: 10,  # 'в'
+    227: 19,  # 'г'
+    228: 13,  # 'д'
+    229: 2,  # 'е'
+    230: 24,  # 'ж'
+    231: 20,  # 'з'
+    232: 4,  # 'и'
+    233: 23,  # 'й'
+    234: 11,  # 'к'
+    235: 8,  # 'л'
+    236: 12,  # 'м'
+    237: 5,  # 'н'
+    238: 1,  # 'о'
+    239: 15,  # 'п'
+    240: 9,  # 'р'
+    241: 7,  # 'с'
+    242: 6,  # 'т'
+    243: 14,  # 'у'
+    244: 39,  # 'ф'
+    245: 26,  # 'х'
+    246: 28,  # 'ц'
+    247: 22,  # 'ч'
+    248: 25,  # 'ш'
+    249: 29,  # 'щ'
+    250: 54,  # 'ъ'
+    251: 18,  # 'ы'
+    252: 17,  # 'ь'
+    253: 30,  # 'э'
+    254: 27,  # 'ю'
+    255: 255,  # '€'
+}
+
+MACCYRILLIC_RUSSIAN_MODEL = SingleByteCharSetModel(
+    charset_name="MacCyrillic",
+    language="Russian",
+    char_to_order_map=MACCYRILLIC_RUSSIAN_CHAR_TO_ORDER,
+    language_model=RUSSIAN_LANG_MODEL,
+    typical_positive_ratio=0.976601,
+    keep_ascii_letters=False,
+    alphabet="ЁАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюяё",
+)
+
+ISO_8859_5_RUSSIAN_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 142,  # 'A'
+    66: 143,  # 'B'
+    67: 144,  # 'C'
+    68: 145,  # 'D'
+    69: 146,  # 'E'
+    70: 147,  # 'F'
+    71: 148,  # 'G'
+    72: 149,  # 'H'
+    73: 150,  # 'I'
+    74: 151,  # 'J'
+    75: 152,  # 'K'
+    76: 74,  # 'L'
+    77: 153,  # 'M'
+    78: 75,  # 'N'
+    79: 154,  # 'O'
+    80: 155,  # 'P'
+    81: 156,  # 'Q'
+    82: 157,  # 'R'
+    83: 158,  # 'S'
+    84: 159,  # 'T'
+    85: 160,  # 'U'
+    86: 161,  # 'V'
+    87: 162,  # 'W'
+    88: 163,  # 'X'
+    89: 164,  # 'Y'
+    90: 165,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 71,  # 'a'
+    98: 172,  # 'b'
+    99: 66,  # 'c'
+    100: 173,  # 'd'
+    101: 65,  # 'e'
+    102: 174,  # 'f'
+    103: 76,  # 'g'
+    104: 175,  # 'h'
+    105: 64,  # 'i'
+    106: 176,  # 'j'
+    107: 177,  # 'k'
+    108: 77,  # 'l'
+    109: 72,  # 'm'
+    110: 178,  # 'n'
+    111: 69,  # 'o'
+    112: 67,  # 'p'
+    113: 179,  # 'q'
+    114: 78,  # 'r'
+    115: 73,  # 's'
+    116: 180,  # 't'
+    117: 181,  # 'u'
+    118: 79,  # 'v'
+    119: 182,  # 'w'
+    120: 183,  # 'x'
+    121: 184,  # 'y'
+    122: 185,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 191,  # '\x80'
+    129: 192,  # '\x81'
+    130: 193,  # '\x82'
+    131: 194,  # '\x83'
+    132: 195,  # '\x84'
+    133: 196,  # '\x85'
+    134: 197,  # '\x86'
+    135: 198,  # '\x87'
+    136: 199,  # '\x88'
+    137: 200,  # '\x89'
+    138: 201,  # '\x8a'
+    139: 202,  # '\x8b'
+    140: 203,  # '\x8c'
+    141: 204,  # '\x8d'
+    142: 205,  # '\x8e'
+    143: 206,  # '\x8f'
+    144: 207,  # '\x90'
+    145: 208,  # '\x91'
+    146: 209,  # '\x92'
+    147: 210,  # '\x93'
+    148: 211,  # '\x94'
+    149: 212,  # '\x95'
+    150: 213,  # '\x96'
+    151: 214,  # '\x97'
+    152: 215,  # '\x98'
+    153: 216,  # '\x99'
+    154: 217,  # '\x9a'
+    155: 218,  # '\x9b'
+    156: 219,  # '\x9c'
+    157: 220,  # '\x9d'
+    158: 221,  # '\x9e'
+    159: 222,  # '\x9f'
+    160: 223,  # '\xa0'
+    161: 224,  # 'Ё'
+    162: 225,  # 'Ђ'
+    163: 226,  # 'Ѓ'
+    164: 227,  # 'Є'
+    165: 228,  # 'Ѕ'
+    166: 229,  # 'І'
+    167: 230,  # 'Ї'
+    168: 231,  # 'Ј'
+    169: 232,  # 'Љ'
+    170: 233,  # 'Њ'
+    171: 234,  # 'Ћ'
+    172: 235,  # 'Ќ'
+    173: 236,  # '\xad'
+    174: 237,  # 'Ў'
+    175: 238,  # 'Џ'
+    176: 37,  # 'А'
+    177: 44,  # 'Б'
+    178: 33,  # 'В'
+    179: 46,  # 'Г'
+    180: 41,  # 'Д'
+    181: 48,  # 'Е'
+    182: 56,  # 'Ж'
+    183: 51,  # 'З'
+    184: 42,  # 'И'
+    185: 60,  # 'Й'
+    186: 36,  # 'К'
+    187: 49,  # 'Л'
+    188: 38,  # 'М'
+    189: 31,  # 'Н'
+    190: 34,  # 'О'
+    191: 35,  # 'П'
+    192: 45,  # 'Р'
+    193: 32,  # 'С'
+    194: 40,  # 'Т'
+    195: 52,  # 'У'
+    196: 53,  # 'Ф'
+    197: 55,  # 'Х'
+    198: 58,  # 'Ц'
+    199: 50,  # 'Ч'
+    200: 57,  # 'Ш'
+    201: 63,  # 'Щ'
+    202: 70,  # 'Ъ'
+    203: 62,  # 'Ы'
+    204: 61,  # 'Ь'
+    205: 47,  # 'Э'
+    206: 59,  # 'Ю'
+    207: 43,  # 'Я'
+    208: 3,  # 'а'
+    209: 21,  # 'б'
+    210: 10,  # 'в'
+    211: 19,  # 'г'
+    212: 13,  # 'д'
+    213: 2,  # 'е'
+    214: 24,  # 'ж'
+    215: 20,  # 'з'
+    216: 4,  # 'и'
+    217: 23,  # 'й'
+    218: 11,  # 'к'
+    219: 8,  # 'л'
+    220: 12,  # 'м'
+    221: 5,  # 'н'
+    222: 1,  # 'о'
+    223: 15,  # 'п'
+    224: 9,  # 'р'
+    225: 7,  # 'с'
+    226: 6,  # 'т'
+    227: 14,  # 'у'
+    228: 39,  # 'ф'
+    229: 26,  # 'х'
+    230: 28,  # 'ц'
+    231: 22,  # 'ч'
+    232: 25,  # 'ш'
+    233: 29,  # 'щ'
+    234: 54,  # 'ъ'
+    235: 18,  # 'ы'
+    236: 17,  # 'ь'
+    237: 30,  # 'э'
+    238: 27,  # 'ю'
+    239: 16,  # 'я'
+    240: 239,  # '№'
+    241: 68,  # 'ё'
+    242: 240,  # 'ђ'
+    243: 241,  # 'ѓ'
+    244: 242,  # 'є'
+    245: 243,  # 'ѕ'
+    246: 244,  # 'і'
+    247: 245,  # 'ї'
+    248: 246,  # 'ј'
+    249: 247,  # 'љ'
+    250: 248,  # 'њ'
+    251: 249,  # 'ћ'
+    252: 250,  # 'ќ'
+    253: 251,  # '§'
+    254: 252,  # 'ў'
+    255: 255,  # 'џ'
+}
+
+ISO_8859_5_RUSSIAN_MODEL = SingleByteCharSetModel(
+    charset_name="ISO-8859-5",
+    language="Russian",
+    char_to_order_map=ISO_8859_5_RUSSIAN_CHAR_TO_ORDER,
+    language_model=RUSSIAN_LANG_MODEL,
+    typical_positive_ratio=0.976601,
+    keep_ascii_letters=False,
+    alphabet="ЁАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюяё",
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langthaimodel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langthaimodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..489cad930e0029fc2f8e5111df1bad38151a07a9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langthaimodel.py
@@ -0,0 +1,4380 @@
+from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+THAI_LANG_MODEL = {
+    5: {  # 'ก'
+        5: 2,  # 'ก'
+        30: 2,  # 'ข'
+        24: 2,  # 'ค'
+        8: 2,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 3,  # 'ฎ'
+        57: 2,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 2,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 3,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 1,  # 'บ'
+        25: 2,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 1,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 1,  # 'ย'
+        2: 3,  # 'ร'
+        61: 2,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 3,  # 'ว'
+        42: 2,  # 'ศ'
+        46: 3,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 3,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 3,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 2,  # 'ื'
+        32: 2,  # 'ุ'
+        35: 1,  # 'ู'
+        11: 2,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 3,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    30: {  # 'ข'
+        5: 1,  # 'ก'
+        30: 0,  # 'ข'
+        24: 1,  # 'ค'
+        8: 1,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 2,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 2,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 1,  # 'บ'
+        25: 1,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 2,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 1,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 3,  # 'ึ'
+        27: 1,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 1,  # '็'
+        6: 2,  # '่'
+        7: 3,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    24: {  # 'ค'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 2,  # 'ค'
+        8: 2,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 2,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 2,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 0,  # 'บ'
+        25: 1,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 2,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 3,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 2,  # 'า'
+        36: 3,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 1,  # 'เ'
+        28: 0,  # 'แ'
+        41: 3,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 1,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 3,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    8: {  # 'ง'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 3,  # 'ค'
+        8: 2,  # 'ง'
+        26: 2,  # 'จ'
+        52: 1,  # 'ฉ'
+        34: 2,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 1,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 1,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 2,  # 'ว'
+        42: 2,  # 'ศ'
+        46: 1,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 3,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 1,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 1,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 3,  # 'ๆ'
+        37: 0,  # '็'
+        6: 2,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    26: {  # 'จ'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 0,  # 'ค'
+        8: 2,  # 'ง'
+        26: 3,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 1,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 1,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 1,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 1,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 3,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 3,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 3,  # 'ึ'
+        27: 1,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 1,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 2,  # '่'
+        7: 2,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    52: {  # 'ฉ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 3,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 3,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 1,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 1,  # 'ั'
+        1: 1,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    34: {  # 'ช'
+        5: 1,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 1,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 1,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 1,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 2,  # 'ั'
+        1: 3,  # 'า'
+        36: 1,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 1,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 1,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    51: {  # 'ซ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 1,  # 'ั'
+        1: 1,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 3,  # 'ึ'
+        27: 2,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 1,  # 'ู'
+        11: 1,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 1,  # '็'
+        6: 1,  # '่'
+        7: 2,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    47: {  # 'ญ'
+        5: 1,  # 'ก'
+        30: 1,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 3,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 1,  # 'บ'
+        25: 1,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 2,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 2,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 1,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 0,  # '็'
+        6: 2,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    58: {  # 'ฎ'
+        5: 2,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 1,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    57: {  # 'ฏ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    49: {  # 'ฐ'
+        5: 1,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 2,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    53: {  # 'ฑ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 3,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    55: {  # 'ฒ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    43: {  # 'ณ'
+        5: 1,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 3,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 3,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 1,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 3,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 1,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 3,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    20: {  # 'ด'
+        5: 2,  # 'ก'
+        30: 2,  # 'ข'
+        24: 2,  # 'ค'
+        8: 3,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 1,  # 'บ'
+        25: 1,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 3,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 2,  # 'า'
+        36: 2,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 1,  # 'ึ'
+        27: 2,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 2,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 2,  # 'ๆ'
+        37: 2,  # '็'
+        6: 1,  # '่'
+        7: 3,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    19: {  # 'ต'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 1,  # 'ค'
+        8: 0,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 1,  # 'ต'
+        44: 2,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 1,  # 'บ'
+        25: 1,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 2,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 1,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 0,  # 'ห'
+        4: 3,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 2,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 1,  # 'ึ'
+        27: 1,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 1,  # 'เ'
+        28: 1,  # 'แ'
+        41: 1,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 2,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    44: {  # 'ถ'
+        5: 1,  # 'ก'
+        30: 0,  # 'ข'
+        24: 1,  # 'ค'
+        8: 0,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 2,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 2,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 3,  # 'ึ'
+        27: 2,  # 'ื'
+        32: 2,  # 'ุ'
+        35: 3,  # 'ู'
+        11: 1,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 2,  # '่'
+        7: 3,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    14: {  # 'ท'
+        5: 1,  # 'ก'
+        30: 1,  # 'ข'
+        24: 3,  # 'ค'
+        8: 1,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 3,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 3,  # 'ย'
+        2: 3,  # 'ร'
+        61: 1,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 2,  # 'ว'
+        42: 3,  # 'ศ'
+        46: 1,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 3,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 2,  # 'ึ'
+        27: 1,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 1,  # 'ู'
+        11: 0,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 1,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    48: {  # 'ธ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 1,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 2,  # 'า'
+        36: 0,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 2,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 3,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    3: {  # 'น'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 3,  # 'ค'
+        8: 1,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 1,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 2,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 3,  # 'ธ'
+        3: 2,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 2,  # 'ย'
+        2: 2,  # 'ร'
+        61: 1,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 3,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 3,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 3,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 3,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 3,  # 'เ'
+        28: 2,  # 'แ'
+        41: 3,  # 'โ'
+        29: 3,  # 'ใ'
+        33: 3,  # 'ไ'
+        50: 2,  # 'ๆ'
+        37: 1,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    17: {  # 'บ'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 2,  # 'ค'
+        8: 1,  # 'ง'
+        26: 1,  # 'จ'
+        52: 1,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 2,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 0,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 3,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 2,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 2,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 2,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 2,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 1,  # '็'
+        6: 2,  # '่'
+        7: 2,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    25: {  # 'ป'
+        5: 2,  # 'ก'
+        30: 0,  # 'ข'
+        24: 1,  # 'ค'
+        8: 0,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 1,  # 'ฎ'
+        57: 3,  # 'ฏ'
+        49: 1,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 1,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 0,  # 'บ'
+        25: 1,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 1,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 0,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 1,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 1,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 1,  # 'า'
+        36: 0,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 1,  # 'เ'
+        28: 2,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 3,  # '็'
+        6: 1,  # '่'
+        7: 2,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    39: {  # 'ผ'
+        5: 1,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 1,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 2,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 1,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 1,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 3,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 1,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    62: {  # 'ฝ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 1,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 2,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 2,  # '่'
+        7: 1,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    31: {  # 'พ'
+        5: 1,  # 'ก'
+        30: 1,  # 'ข'
+        24: 1,  # 'ค'
+        8: 1,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 1,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 0,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 2,  # 'ย'
+        2: 3,  # 'ร'
+        61: 2,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 1,  # 'ห'
+        4: 2,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 1,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 1,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 1,  # '็'
+        6: 0,  # '่'
+        7: 1,  # '้'
+        38: 3,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    54: {  # 'ฟ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 2,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 2,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 1,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 2,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    45: {  # 'ภ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 1,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    9: {  # 'ม'
+        5: 2,  # 'ก'
+        30: 2,  # 'ข'
+        24: 2,  # 'ค'
+        8: 2,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 1,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 3,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 1,  # 'ย'
+        2: 2,  # 'ร'
+        61: 2,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 2,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 1,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 3,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 3,  # 'ู'
+        11: 2,  # 'เ'
+        28: 2,  # 'แ'
+        41: 2,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 1,  # '็'
+        6: 3,  # '่'
+        7: 2,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    16: {  # 'ย'
+        5: 3,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 3,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 2,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 2,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 1,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 0,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 3,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 1,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 1,  # 'ึ'
+        27: 2,  # 'ื'
+        32: 2,  # 'ุ'
+        35: 3,  # 'ู'
+        11: 2,  # 'เ'
+        28: 1,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 2,  # 'ๆ'
+        37: 1,  # '็'
+        6: 3,  # '่'
+        7: 2,  # '้'
+        38: 3,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    2: {  # 'ร'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 2,  # 'ค'
+        8: 3,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 2,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 3,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 3,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 2,  # 'ต'
+        44: 3,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 2,  # 'น'
+        17: 2,  # 'บ'
+        25: 3,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 1,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 2,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 3,  # 'ว'
+        42: 2,  # 'ศ'
+        46: 2,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 3,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 3,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 2,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 3,  # 'ู'
+        11: 3,  # 'เ'
+        28: 3,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 3,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 3,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    61: {  # 'ฤ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 2,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 2,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    15: {  # 'ล'
+        5: 2,  # 'ก'
+        30: 3,  # 'ข'
+        24: 1,  # 'ค'
+        8: 3,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 3,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 1,  # 'ห'
+        4: 3,  # 'อ'
+        63: 2,  # 'ฯ'
+        22: 3,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 2,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 2,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 2,  # 'ุ'
+        35: 3,  # 'ู'
+        11: 2,  # 'เ'
+        28: 1,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 2,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    12: {  # 'ว'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 1,  # 'ค'
+        8: 3,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 1,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 1,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 1,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 3,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 2,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 2,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    42: {  # 'ศ'
+        5: 1,  # 'ก'
+        30: 0,  # 'ข'
+        24: 1,  # 'ค'
+        8: 0,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 1,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 2,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 2,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 2,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 3,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 2,  # 'ู'
+        11: 0,  # 'เ'
+        28: 1,  # 'แ'
+        41: 0,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    46: {  # 'ษ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 2,  # 'ฎ'
+        57: 1,  # 'ฏ'
+        49: 2,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 3,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 2,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 2,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 1,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    18: {  # 'ส'
+        5: 2,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 2,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 3,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 1,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 2,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 1,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 2,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 3,  # 'ำ'
+        23: 3,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 2,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 3,  # 'ู'
+        11: 2,  # 'เ'
+        28: 0,  # 'แ'
+        41: 1,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 1,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    21: {  # 'ห'
+        5: 3,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 1,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 2,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 3,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 0,  # 'บ'
+        25: 1,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 2,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 0,  # 'ำ'
+        23: 1,  # 'ิ'
+        13: 1,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 1,  # 'ุ'
+        35: 1,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 3,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    4: {  # 'อ'
+        5: 3,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 3,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 1,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 3,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 2,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 2,  # 'ะ'
+        10: 3,  # 'ั'
+        1: 3,  # 'า'
+        36: 2,  # 'ำ'
+        23: 2,  # 'ิ'
+        13: 3,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 3,  # 'ื'
+        32: 3,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 1,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 1,  # '็'
+        6: 2,  # '่'
+        7: 2,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    63: {  # 'ฯ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    22: {  # 'ะ'
+        5: 3,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 1,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 3,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 2,  # 'น'
+        17: 3,  # 'บ'
+        25: 2,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 2,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 3,  # 'ห'
+        4: 2,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    10: {  # 'ั'
+        5: 3,  # 'ก'
+        30: 0,  # 'ข'
+        24: 1,  # 'ค'
+        8: 3,  # 'ง'
+        26: 3,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 3,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 2,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 3,  # 'ฒ'
+        43: 3,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 1,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 3,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 3,  # 'ว'
+        42: 2,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    1: {  # 'า'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 3,  # 'ค'
+        8: 3,  # 'ง'
+        26: 3,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 3,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 2,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 3,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 2,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 2,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 1,  # 'ฝ'
+        31: 3,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 3,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 3,  # 'ว'
+        42: 2,  # 'ศ'
+        46: 3,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 3,  # 'ห'
+        4: 2,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 3,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    36: {  # 'ำ'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 3,  # 'ค'
+        8: 2,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 1,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 1,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 1,  # 'บ'
+        25: 1,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 0,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 3,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    23: {  # 'ิ'
+        5: 3,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 3,  # 'ง'
+        26: 3,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 3,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 2,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 3,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 2,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 3,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 2,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 2,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 3,  # 'ว'
+        42: 3,  # 'ศ'
+        46: 2,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 3,  # 'ห'
+        4: 1,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 1,  # 'แ'
+        41: 1,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 2,  # '้'
+        38: 2,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    13: {  # 'ี'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 2,  # 'ค'
+        8: 0,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 1,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 3,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 2,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 1,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 2,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    40: {  # 'ึ'
+        5: 3,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 3,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    27: {  # 'ื'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 3,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    32: {  # 'ุ'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 3,  # 'ค'
+        8: 3,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 2,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 1,  # 'ฒ'
+        43: 3,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 2,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 1,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 1,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 2,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 1,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 1,  # 'เ'
+        28: 0,  # 'แ'
+        41: 1,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 2,  # '้'
+        38: 1,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    35: {  # 'ู'
+        5: 3,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 2,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 2,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 1,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 2,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 2,  # 'น'
+        17: 0,  # 'บ'
+        25: 3,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 0,  # 'ย'
+        2: 1,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 1,  # 'เ'
+        28: 1,  # 'แ'
+        41: 1,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 3,  # '่'
+        7: 3,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    11: {  # 'เ'
+        5: 3,  # 'ก'
+        30: 3,  # 'ข'
+        24: 3,  # 'ค'
+        8: 2,  # 'ง'
+        26: 3,  # 'จ'
+        52: 3,  # 'ฉ'
+        34: 3,  # 'ช'
+        51: 2,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 1,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 3,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 3,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 1,  # 'ฝ'
+        31: 3,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 3,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 2,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 3,  # 'ว'
+        42: 2,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 3,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    28: {  # 'แ'
+        5: 3,  # 'ก'
+        30: 2,  # 'ข'
+        24: 2,  # 'ค'
+        8: 1,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 3,  # 'ต'
+        44: 2,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 2,  # 'ป'
+        39: 3,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 2,  # 'พ'
+        54: 2,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 2,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 3,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    41: {  # 'โ'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 0,  # 'ง'
+        26: 1,  # 'จ'
+        52: 1,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 2,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 1,  # 'บ'
+        25: 3,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 1,  # 'ภ'
+        9: 1,  # 'ม'
+        16: 2,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 3,  # 'ล'
+        12: 0,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 0,  # 'ห'
+        4: 2,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    29: {  # 'ใ'
+        5: 2,  # 'ก'
+        30: 0,  # 'ข'
+        24: 1,  # 'ค'
+        8: 0,  # 'ง'
+        26: 3,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 3,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 1,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 3,  # 'ส'
+        21: 3,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    33: {  # 'ไ'
+        5: 1,  # 'ก'
+        30: 2,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 3,  # 'ด'
+        19: 1,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 3,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 1,  # 'บ'
+        25: 3,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 2,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 0,  # 'ย'
+        2: 3,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 3,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 2,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    50: {  # 'ๆ'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    37: {  # '็'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 2,  # 'ง'
+        26: 3,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 1,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 2,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 3,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 1,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 2,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 0,  # 'ห'
+        4: 1,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 1,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    6: {  # '่'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 3,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 1,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 1,  # 'ธ'
+        3: 3,  # 'น'
+        17: 1,  # 'บ'
+        25: 2,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 1,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 3,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 2,  # 'ล'
+        12: 3,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 1,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 1,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 3,  # 'า'
+        36: 2,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 3,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 1,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    7: {  # '้'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 2,  # 'ค'
+        8: 3,  # 'ง'
+        26: 2,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 1,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 1,  # 'ด'
+        19: 2,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 2,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 3,  # 'น'
+        17: 2,  # 'บ'
+        25: 2,  # 'ป'
+        39: 2,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 3,  # 'ม'
+        16: 2,  # 'ย'
+        2: 2,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 3,  # 'ว'
+        42: 1,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 2,  # 'ส'
+        21: 2,  # 'ห'
+        4: 3,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 3,  # 'า'
+        36: 2,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 2,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 2,  # 'ใ'
+        33: 2,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    38: {  # '์'
+        5: 2,  # 'ก'
+        30: 1,  # 'ข'
+        24: 1,  # 'ค'
+        8: 0,  # 'ง'
+        26: 1,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 1,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 2,  # 'ด'
+        19: 1,  # 'ต'
+        44: 1,  # 'ถ'
+        14: 1,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 1,  # 'น'
+        17: 1,  # 'บ'
+        25: 1,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 1,  # 'พ'
+        54: 1,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 2,  # 'ม'
+        16: 0,  # 'ย'
+        2: 1,  # 'ร'
+        61: 1,  # 'ฤ'
+        15: 1,  # 'ล'
+        12: 1,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 1,  # 'ส'
+        21: 1,  # 'ห'
+        4: 2,  # 'อ'
+        63: 1,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 2,  # 'เ'
+        28: 2,  # 'แ'
+        41: 1,  # 'โ'
+        29: 1,  # 'ใ'
+        33: 1,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 0,  # '๑'
+        59: 0,  # '๒'
+        60: 0,  # '๕'
+    },
+    56: {  # '๑'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 2,  # '๑'
+        59: 1,  # '๒'
+        60: 1,  # '๕'
+    },
+    59: {  # '๒'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 1,  # '๑'
+        59: 1,  # '๒'
+        60: 3,  # '๕'
+    },
+    60: {  # '๕'
+        5: 0,  # 'ก'
+        30: 0,  # 'ข'
+        24: 0,  # 'ค'
+        8: 0,  # 'ง'
+        26: 0,  # 'จ'
+        52: 0,  # 'ฉ'
+        34: 0,  # 'ช'
+        51: 0,  # 'ซ'
+        47: 0,  # 'ญ'
+        58: 0,  # 'ฎ'
+        57: 0,  # 'ฏ'
+        49: 0,  # 'ฐ'
+        53: 0,  # 'ฑ'
+        55: 0,  # 'ฒ'
+        43: 0,  # 'ณ'
+        20: 0,  # 'ด'
+        19: 0,  # 'ต'
+        44: 0,  # 'ถ'
+        14: 0,  # 'ท'
+        48: 0,  # 'ธ'
+        3: 0,  # 'น'
+        17: 0,  # 'บ'
+        25: 0,  # 'ป'
+        39: 0,  # 'ผ'
+        62: 0,  # 'ฝ'
+        31: 0,  # 'พ'
+        54: 0,  # 'ฟ'
+        45: 0,  # 'ภ'
+        9: 0,  # 'ม'
+        16: 0,  # 'ย'
+        2: 0,  # 'ร'
+        61: 0,  # 'ฤ'
+        15: 0,  # 'ล'
+        12: 0,  # 'ว'
+        42: 0,  # 'ศ'
+        46: 0,  # 'ษ'
+        18: 0,  # 'ส'
+        21: 0,  # 'ห'
+        4: 0,  # 'อ'
+        63: 0,  # 'ฯ'
+        22: 0,  # 'ะ'
+        10: 0,  # 'ั'
+        1: 0,  # 'า'
+        36: 0,  # 'ำ'
+        23: 0,  # 'ิ'
+        13: 0,  # 'ี'
+        40: 0,  # 'ึ'
+        27: 0,  # 'ื'
+        32: 0,  # 'ุ'
+        35: 0,  # 'ู'
+        11: 0,  # 'เ'
+        28: 0,  # 'แ'
+        41: 0,  # 'โ'
+        29: 0,  # 'ใ'
+        33: 0,  # 'ไ'
+        50: 0,  # 'ๆ'
+        37: 0,  # '็'
+        6: 0,  # '่'
+        7: 0,  # '้'
+        38: 0,  # '์'
+        56: 2,  # '๑'
+        59: 1,  # '๒'
+        60: 0,  # '๕'
+    },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+TIS_620_THAI_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 254,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 254,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 253,  # ' '
+    33: 253,  # '!'
+    34: 253,  # '"'
+    35: 253,  # '#'
+    36: 253,  # '$'
+    37: 253,  # '%'
+    38: 253,  # '&'
+    39: 253,  # "'"
+    40: 253,  # '('
+    41: 253,  # ')'
+    42: 253,  # '*'
+    43: 253,  # '+'
+    44: 253,  # ','
+    45: 253,  # '-'
+    46: 253,  # '.'
+    47: 253,  # '/'
+    48: 252,  # '0'
+    49: 252,  # '1'
+    50: 252,  # '2'
+    51: 252,  # '3'
+    52: 252,  # '4'
+    53: 252,  # '5'
+    54: 252,  # '6'
+    55: 252,  # '7'
+    56: 252,  # '8'
+    57: 252,  # '9'
+    58: 253,  # ':'
+    59: 253,  # ';'
+    60: 253,  # '<'
+    61: 253,  # '='
+    62: 253,  # '>'
+    63: 253,  # '?'
+    64: 253,  # '@'
+    65: 182,  # 'A'
+    66: 106,  # 'B'
+    67: 107,  # 'C'
+    68: 100,  # 'D'
+    69: 183,  # 'E'
+    70: 184,  # 'F'
+    71: 185,  # 'G'
+    72: 101,  # 'H'
+    73: 94,  # 'I'
+    74: 186,  # 'J'
+    75: 187,  # 'K'
+    76: 108,  # 'L'
+    77: 109,  # 'M'
+    78: 110,  # 'N'
+    79: 111,  # 'O'
+    80: 188,  # 'P'
+    81: 189,  # 'Q'
+    82: 190,  # 'R'
+    83: 89,  # 'S'
+    84: 95,  # 'T'
+    85: 112,  # 'U'
+    86: 113,  # 'V'
+    87: 191,  # 'W'
+    88: 192,  # 'X'
+    89: 193,  # 'Y'
+    90: 194,  # 'Z'
+    91: 253,  # '['
+    92: 253,  # '\\'
+    93: 253,  # ']'
+    94: 253,  # '^'
+    95: 253,  # '_'
+    96: 253,  # '`'
+    97: 64,  # 'a'
+    98: 72,  # 'b'
+    99: 73,  # 'c'
+    100: 114,  # 'd'
+    101: 74,  # 'e'
+    102: 115,  # 'f'
+    103: 116,  # 'g'
+    104: 102,  # 'h'
+    105: 81,  # 'i'
+    106: 201,  # 'j'
+    107: 117,  # 'k'
+    108: 90,  # 'l'
+    109: 103,  # 'm'
+    110: 78,  # 'n'
+    111: 82,  # 'o'
+    112: 96,  # 'p'
+    113: 202,  # 'q'
+    114: 91,  # 'r'
+    115: 79,  # 's'
+    116: 84,  # 't'
+    117: 104,  # 'u'
+    118: 105,  # 'v'
+    119: 97,  # 'w'
+    120: 98,  # 'x'
+    121: 92,  # 'y'
+    122: 203,  # 'z'
+    123: 253,  # '{'
+    124: 253,  # '|'
+    125: 253,  # '}'
+    126: 253,  # '~'
+    127: 253,  # '\x7f'
+    128: 209,  # '\x80'
+    129: 210,  # '\x81'
+    130: 211,  # '\x82'
+    131: 212,  # '\x83'
+    132: 213,  # '\x84'
+    133: 88,  # '\x85'
+    134: 214,  # '\x86'
+    135: 215,  # '\x87'
+    136: 216,  # '\x88'
+    137: 217,  # '\x89'
+    138: 218,  # '\x8a'
+    139: 219,  # '\x8b'
+    140: 220,  # '\x8c'
+    141: 118,  # '\x8d'
+    142: 221,  # '\x8e'
+    143: 222,  # '\x8f'
+    144: 223,  # '\x90'
+    145: 224,  # '\x91'
+    146: 99,  # '\x92'
+    147: 85,  # '\x93'
+    148: 83,  # '\x94'
+    149: 225,  # '\x95'
+    150: 226,  # '\x96'
+    151: 227,  # '\x97'
+    152: 228,  # '\x98'
+    153: 229,  # '\x99'
+    154: 230,  # '\x9a'
+    155: 231,  # '\x9b'
+    156: 232,  # '\x9c'
+    157: 233,  # '\x9d'
+    158: 234,  # '\x9e'
+    159: 235,  # '\x9f'
+    160: 236,  # None
+    161: 5,  # 'ก'
+    162: 30,  # 'ข'
+    163: 237,  # 'ฃ'
+    164: 24,  # 'ค'
+    165: 238,  # 'ฅ'
+    166: 75,  # 'ฆ'
+    167: 8,  # 'ง'
+    168: 26,  # 'จ'
+    169: 52,  # 'ฉ'
+    170: 34,  # 'ช'
+    171: 51,  # 'ซ'
+    172: 119,  # 'ฌ'
+    173: 47,  # 'ญ'
+    174: 58,  # 'ฎ'
+    175: 57,  # 'ฏ'
+    176: 49,  # 'ฐ'
+    177: 53,  # 'ฑ'
+    178: 55,  # 'ฒ'
+    179: 43,  # 'ณ'
+    180: 20,  # 'ด'
+    181: 19,  # 'ต'
+    182: 44,  # 'ถ'
+    183: 14,  # 'ท'
+    184: 48,  # 'ธ'
+    185: 3,  # 'น'
+    186: 17,  # 'บ'
+    187: 25,  # 'ป'
+    188: 39,  # 'ผ'
+    189: 62,  # 'ฝ'
+    190: 31,  # 'พ'
+    191: 54,  # 'ฟ'
+    192: 45,  # 'ภ'
+    193: 9,  # 'ม'
+    194: 16,  # 'ย'
+    195: 2,  # 'ร'
+    196: 61,  # 'ฤ'
+    197: 15,  # 'ล'
+    198: 239,  # 'ฦ'
+    199: 12,  # 'ว'
+    200: 42,  # 'ศ'
+    201: 46,  # 'ษ'
+    202: 18,  # 'ส'
+    203: 21,  # 'ห'
+    204: 76,  # 'ฬ'
+    205: 4,  # 'อ'
+    206: 66,  # 'ฮ'
+    207: 63,  # 'ฯ'
+    208: 22,  # 'ะ'
+    209: 10,  # 'ั'
+    210: 1,  # 'า'
+    211: 36,  # 'ำ'
+    212: 23,  # 'ิ'
+    213: 13,  # 'ี'
+    214: 40,  # 'ึ'
+    215: 27,  # 'ื'
+    216: 32,  # 'ุ'
+    217: 35,  # 'ู'
+    218: 86,  # 'ฺ'
+    219: 240,  # None
+    220: 241,  # None
+    221: 242,  # None
+    222: 243,  # None
+    223: 244,  # '฿'
+    224: 11,  # 'เ'
+    225: 28,  # 'แ'
+    226: 41,  # 'โ'
+    227: 29,  # 'ใ'
+    228: 33,  # 'ไ'
+    229: 245,  # 'ๅ'
+    230: 50,  # 'ๆ'
+    231: 37,  # '็'
+    232: 6,  # '่'
+    233: 7,  # '้'
+    234: 67,  # '๊'
+    235: 77,  # '๋'
+    236: 38,  # '์'
+    237: 93,  # 'ํ'
+    238: 246,  # '๎'
+    239: 247,  # '๏'
+    240: 68,  # '๐'
+    241: 56,  # '๑'
+    242: 59,  # '๒'
+    243: 65,  # '๓'
+    244: 69,  # '๔'
+    245: 60,  # '๕'
+    246: 70,  # '๖'
+    247: 80,  # '๗'
+    248: 71,  # '๘'
+    249: 87,  # '๙'
+    250: 248,  # '๚'
+    251: 249,  # '๛'
+    252: 250,  # None
+    253: 251,  # None
+    254: 252,  # None
+    255: 253,  # None
+}
+
+TIS_620_THAI_MODEL = SingleByteCharSetModel(
+    charset_name="TIS-620",
+    language="Thai",
+    char_to_order_map=TIS_620_THAI_CHAR_TO_ORDER,
+    language_model=THAI_LANG_MODEL,
+    typical_positive_ratio=0.926386,
+    keep_ascii_letters=False,
+    alphabet="กขฃคฅฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรฤลฦวศษสหฬอฮฯะัาำิีึืฺุู฿เแโใไๅๆ็่้๊๋์ํ๎๏๐๑๒๓๔๕๖๗๘๙๚๛",
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langturkishmodel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langturkishmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..291857c25c83f91a151c1d7760e8e5e09c1ee238
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/langturkishmodel.py
@@ -0,0 +1,4380 @@
+from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+TURKISH_LANG_MODEL = {
+    23: {  # 'A'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 0,  # 'c'
+        12: 2,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 1,  # 'g'
+        25: 1,  # 'h'
+        3: 1,  # 'i'
+        24: 0,  # 'j'
+        10: 2,  # 'k'
+        5: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
+        7: 1,  # 'r'
+        8: 1,  # 's'
+        9: 1,  # 't'
+        14: 1,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 3,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 0,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    37: {  # 'B'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 2,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 2,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 1,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 1,  # 'P'
+        44: 0,  # 'R'
+        35: 1,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 0,  # 'Z'
+        1: 2,  # 'a'
+        21: 0,  # 'b'
+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 0,  # 'j'
+        10: 0,  # 'k'
+        5: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
+        7: 0,  # 'r'
+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 2,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 1,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 1,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 0,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    47: {  # 'C'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 1,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 1,  # 'L'
+        20: 0,  # 'M'
+        46: 1,  # 'N'
+        42: 0,  # 'O'
+        48: 1,  # 'P'
+        44: 1,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 2,  # 'j'
+        10: 1,  # 'k'
+        5: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 2,  # 'n'
+        15: 1,  # 'o'
+        26: 0,  # 'p'
+        7: 2,  # 'r'
+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 3,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 2,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 1,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    39: {  # 'D'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 1,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 1,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 1,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 2,  # 'a'
+        21: 0,  # 'b'
+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 2,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 0,  # 'j'
+        10: 0,  # 'k'
+        5: 1,  # 'l'
+        13: 3,  # 'm'
+        4: 0,  # 'n'
+        15: 1,  # 'o'
+        26: 0,  # 'p'
+        7: 0,  # 'r'
+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 1,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 1,  # 'z'
+        63: 0,  # '·'
+        54: 1,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 1,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    29: {  # 'E'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 1,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 0,  # 'c'
+        12: 2,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 1,  # 'g'
+        25: 0,  # 'h'
+        3: 1,  # 'i'
+        24: 1,  # 'j'
+        10: 0,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
+        7: 0,  # 'r'
+        8: 1,  # 's'
+        9: 1,  # 't'
+        14: 1,  # 'u'
+        32: 1,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 2,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    52: {  # 'F'
+        23: 0,  # 'A'
+        37: 1,  # 'B'
+        47: 1,  # 'C'
+        39: 1,  # 'D'
+        29: 1,  # 'E'
+        52: 2,  # 'F'
+        36: 0,  # 'G'
+        45: 2,  # 'H'
+        53: 1,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 1,  # 'N'
+        42: 1,  # 'O'
+        48: 2,  # 'P'
+        44: 1,  # 'R'
+        35: 1,  # 'S'
+        31: 1,  # 'T'
+        51: 1,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 2,  # 'Y'
+        56: 0,  # 'Z'
+        1: 0,  # 'a'
+        21: 1,  # 'b'
+        28: 1,  # 'c'
+        12: 1,  # 'd'
+        2: 0,  # 'e'
+        18: 1,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 2,  # 'i'
+        24: 1,  # 'j'
+        10: 0,  # 'k'
+        5: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 2,  # 'n'
+        15: 1,  # 'o'
+        26: 0,  # 'p'
+        7: 2,  # 'r'
+        8: 1,  # 's'
+        9: 1,  # 't'
+        14: 1,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 1,  # 'y'
+        22: 1,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 1,  # 'Ö'
+        55: 2,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 2,  # 'ö'
+        17: 0,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 2,  # 'ş'
+    },
+    36: {  # 'G'
+        23: 1,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 1,  # 'F'
+        36: 2,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 2,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 2,  # 'N'
+        42: 1,  # 'O'
+        48: 1,  # 'P'
+        44: 1,  # 'R'
+        35: 1,  # 'S'
+        31: 0,  # 'T'
+        51: 1,  # 'U'
+        38: 2,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 1,  # 'c'
+        12: 0,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 1,  # 'j'
+        10: 1,  # 'k'
+        5: 0,  # 'l'
+        13: 3,  # 'm'
+        4: 2,  # 'n'
+        15: 0,  # 'o'
+        26: 1,  # 'p'
+        7: 0,  # 'r'
+        8: 1,  # 's'
+        9: 1,  # 't'
+        14: 3,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 1,  # 'x'
+        11: 0,  # 'y'
+        22: 2,  # 'z'
+        63: 0,  # '·'
+        54: 1,  # 'Ç'
+        50: 2,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 1,  # 'â'
+        33: 2,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 2,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    45: {  # 'H'
+        23: 0,  # 'A'
+        37: 1,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 2,  # 'F'
+        36: 2,  # 'G'
+        45: 1,  # 'H'
+        53: 1,  # 'I'
+        60: 0,  # 'J'
+        16: 2,  # 'K'
+        49: 1,  # 'L'
+        20: 0,  # 'M'
+        46: 1,  # 'N'
+        42: 1,  # 'O'
+        48: 1,  # 'P'
+        44: 0,  # 'R'
+        35: 2,  # 'S'
+        31: 0,  # 'T'
+        51: 1,  # 'U'
+        38: 2,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 2,  # 'i'
+        24: 0,  # 'j'
+        10: 1,  # 'k'
+        5: 0,  # 'l'
+        13: 2,  # 'm'
+        4: 0,  # 'n'
+        15: 1,  # 'o'
+        26: 1,  # 'p'
+        7: 1,  # 'r'
+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 3,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 2,  # 'z'
+        63: 0,  # '·'
+        54: 1,  # 'Ç'
+        50: 1,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 0,  # 'ü'
+        30: 2,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 0,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    53: {  # 'I'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 1,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 2,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 1,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 2,  # 'a'
+        21: 0,  # 'b'
+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 2,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 0,  # 'j'
+        10: 0,  # 'k'
+        5: 2,  # 'l'
+        13: 2,  # 'm'
+        4: 0,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
+        7: 0,  # 'r'
+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 2,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 2,  # 'z'
+        63: 0,  # '·'
+        54: 1,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 2,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 0,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    60: {  # 'J'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 0,  # 'a'
+        21: 1,  # 'b'
+        28: 0,  # 'c'
+        12: 1,  # 'd'
+        2: 0,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 1,  # 'i'
+        24: 0,  # 'j'
+        10: 0,  # 'k'
+        5: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
+        7: 0,  # 'r'
+        8: 1,  # 's'
+        9: 0,  # 't'
+        14: 0,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 0,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    16: {  # 'K'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 3,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 2,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 2,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 2,  # 'a'
+        21: 3,  # 'b'
+        28: 0,  # 'c'
+        12: 3,  # 'd'
+        2: 1,  # 'e'
+        18: 3,  # 'f'
+        27: 3,  # 'g'
+        25: 3,  # 'h'
+        3: 3,  # 'i'
+        24: 2,  # 'j'
+        10: 3,  # 'k'
+        5: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 1,  # 'p'
+        7: 3,  # 'r'
+        8: 3,  # 's'
+        9: 3,  # 't'
+        14: 0,  # 'u'
+        32: 3,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 2,  # 'y'
+        22: 1,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 2,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    49: {  # 'L'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 2,  # 'E'
+        52: 0,  # 'F'
+        36: 1,  # 'G'
+        45: 1,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 0,  # 'N'
+        42: 2,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 0,  # 'Z'
+        1: 0,  # 'a'
+        21: 3,  # 'b'
+        28: 0,  # 'c'
+        12: 2,  # 'd'
+        2: 0,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 2,  # 'i'
+        24: 0,  # 'j'
+        10: 1,  # 'k'
+        5: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 2,  # 'n'
+        15: 1,  # 'o'
+        26: 1,  # 'p'
+        7: 1,  # 'r'
+        8: 1,  # 's'
+        9: 1,  # 't'
+        14: 0,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 2,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 2,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 1,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    20: {  # 'M'
+        23: 1,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 1,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 2,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 1,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 2,  # 'b'
+        28: 0,  # 'c'
+        12: 3,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 1,  # 'g'
+        25: 1,  # 'h'
+        3: 2,  # 'i'
+        24: 2,  # 'j'
+        10: 2,  # 'k'
+        5: 2,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 1,  # 'p'
+        7: 3,  # 'r'
+        8: 0,  # 's'
+        9: 2,  # 't'
+        14: 3,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 2,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 3,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    46: {  # 'N'
+        23: 0,  # 'A'
+        37: 1,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 1,  # 'F'
+        36: 1,  # 'G'
+        45: 1,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 2,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 1,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 1,  # 'R'
+        35: 1,  # 'S'
+        31: 0,  # 'T'
+        51: 1,  # 'U'
+        38: 2,  # 'V'
+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 1,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 2,  # 'j'
+        10: 1,  # 'k'
+        5: 1,  # 'l'
+        13: 3,  # 'm'
+        4: 2,  # 'n'
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+        41: 1,  # 'İ'
+        6: 2,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 1,  # 'ş'
+    },
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+        6: 1,  # 'ı'
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+        19: 1,  # 'ş'
+    },
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+        6: 0,  # 'ı'
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+        19: 1,  # 'ş'
+    },
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+        6: 2,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 1,  # 'ş'
+    },
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+        6: 3,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 1,  # 'ş'
+    },
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+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
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+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
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+        6: 3,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 1,  # 'ş'
+    },
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+    },
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+        6: 0,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 1,  # 'ş'
+    },
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+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 2,  # 'Z'
+        1: 2,  # 'a'
+        21: 1,  # 'b'
+        28: 0,  # 'c'
+        12: 0,  # 'd'
+        2: 2,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 2,  # 'i'
+        24: 1,  # 'j'
+        10: 0,  # 'k'
+        5: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
+        7: 1,  # 'r'
+        8: 1,  # 's'
+        9: 0,  # 't'
+        14: 2,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 1,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 1,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    1: {  # 'a'
+        23: 3,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 0,  # 'D'
+        29: 3,  # 'E'
+        52: 0,  # 'F'
+        36: 1,  # 'G'
+        45: 1,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 3,  # 'M'
+        46: 1,  # 'N'
+        42: 0,  # 'O'
+        48: 1,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 3,  # 'T'
+        51: 0,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 2,  # 'Z'
+        1: 2,  # 'a'
+        21: 3,  # 'b'
+        28: 0,  # 'c'
+        12: 3,  # 'd'
+        2: 2,  # 'e'
+        18: 3,  # 'f'
+        27: 3,  # 'g'
+        25: 3,  # 'h'
+        3: 3,  # 'i'
+        24: 3,  # 'j'
+        10: 3,  # 'k'
+        5: 0,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        15: 1,  # 'o'
+        26: 3,  # 'p'
+        7: 3,  # 'r'
+        8: 3,  # 's'
+        9: 3,  # 't'
+        14: 3,  # 'u'
+        32: 3,  # 'v'
+        57: 2,  # 'w'
+        58: 0,  # 'x'
+        11: 3,  # 'y'
+        22: 0,  # 'z'
+        63: 1,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 1,  # 'î'
+        34: 1,  # 'ö'
+        17: 3,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    21: {  # 'b'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 1,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 1,  # 'J'
+        16: 2,  # 'K'
+        49: 0,  # 'L'
+        20: 2,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 1,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 2,  # 'b'
+        28: 0,  # 'c'
+        12: 3,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 3,  # 'g'
+        25: 1,  # 'h'
+        3: 3,  # 'i'
+        24: 2,  # 'j'
+        10: 3,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 3,  # 'p'
+        7: 1,  # 'r'
+        8: 2,  # 's'
+        9: 2,  # 't'
+        14: 2,  # 'u'
+        32: 1,  # 'v'
+        57: 0,  # 'w'
+        58: 1,  # 'x'
+        11: 3,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    28: {  # 'c'
+        23: 0,  # 'A'
+        37: 1,  # 'B'
+        47: 1,  # 'C'
+        39: 1,  # 'D'
+        29: 2,  # 'E'
+        52: 0,  # 'F'
+        36: 2,  # 'G'
+        45: 2,  # 'H'
+        53: 1,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 2,  # 'M'
+        46: 1,  # 'N'
+        42: 1,  # 'O'
+        48: 2,  # 'P'
+        44: 1,  # 'R'
+        35: 1,  # 'S'
+        31: 2,  # 'T'
+        51: 2,  # 'U'
+        38: 2,  # 'V'
+        62: 0,  # 'W'
+        43: 3,  # 'Y'
+        56: 0,  # 'Z'
+        1: 1,  # 'a'
+        21: 1,  # 'b'
+        28: 2,  # 'c'
+        12: 2,  # 'd'
+        2: 1,  # 'e'
+        18: 1,  # 'f'
+        27: 2,  # 'g'
+        25: 2,  # 'h'
+        3: 3,  # 'i'
+        24: 1,  # 'j'
+        10: 3,  # 'k'
+        5: 0,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        15: 2,  # 'o'
+        26: 2,  # 'p'
+        7: 3,  # 'r'
+        8: 3,  # 's'
+        9: 3,  # 't'
+        14: 1,  # 'u'
+        32: 0,  # 'v'
+        57: 1,  # 'w'
+        58: 0,  # 'x'
+        11: 2,  # 'y'
+        22: 1,  # 'z'
+        63: 1,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 1,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 1,  # 'î'
+        34: 2,  # 'ö'
+        17: 2,  # 'ü'
+        30: 2,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 2,  # 'ş'
+    },
+    12: {  # 'd'
+        23: 1,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 2,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 3,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 1,  # 'S'
+        31: 1,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 2,  # 'b'
+        28: 1,  # 'c'
+        12: 3,  # 'd'
+        2: 3,  # 'e'
+        18: 1,  # 'f'
+        27: 3,  # 'g'
+        25: 3,  # 'h'
+        3: 2,  # 'i'
+        24: 3,  # 'j'
+        10: 2,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 1,  # 'o'
+        26: 2,  # 'p'
+        7: 3,  # 'r'
+        8: 2,  # 's'
+        9: 2,  # 't'
+        14: 3,  # 'u'
+        32: 1,  # 'v'
+        57: 0,  # 'w'
+        58: 1,  # 'x'
+        11: 3,  # 'y'
+        22: 1,  # 'z'
+        63: 1,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 1,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    2: {  # 'e'
+        23: 2,  # 'A'
+        37: 0,  # 'B'
+        47: 2,  # 'C'
+        39: 0,  # 'D'
+        29: 3,  # 'E'
+        52: 1,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 1,  # 'K'
+        49: 0,  # 'L'
+        20: 3,  # 'M'
+        46: 1,  # 'N'
+        42: 0,  # 'O'
+        48: 1,  # 'P'
+        44: 1,  # 'R'
+        35: 0,  # 'S'
+        31: 3,  # 'T'
+        51: 0,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 3,  # 'b'
+        28: 0,  # 'c'
+        12: 3,  # 'd'
+        2: 2,  # 'e'
+        18: 3,  # 'f'
+        27: 3,  # 'g'
+        25: 3,  # 'h'
+        3: 3,  # 'i'
+        24: 3,  # 'j'
+        10: 3,  # 'k'
+        5: 0,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        15: 1,  # 'o'
+        26: 3,  # 'p'
+        7: 3,  # 'r'
+        8: 3,  # 's'
+        9: 3,  # 't'
+        14: 3,  # 'u'
+        32: 3,  # 'v'
+        57: 2,  # 'w'
+        58: 0,  # 'x'
+        11: 3,  # 'y'
+        22: 1,  # 'z'
+        63: 1,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 3,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    18: {  # 'f'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 2,  # 'K'
+        49: 0,  # 'L'
+        20: 2,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 2,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 1,  # 'b'
+        28: 0,  # 'c'
+        12: 3,  # 'd'
+        2: 3,  # 'e'
+        18: 2,  # 'f'
+        27: 1,  # 'g'
+        25: 1,  # 'h'
+        3: 1,  # 'i'
+        24: 1,  # 'j'
+        10: 1,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 2,  # 'p'
+        7: 1,  # 'r'
+        8: 3,  # 's'
+        9: 3,  # 't'
+        14: 1,  # 'u'
+        32: 2,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 1,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 1,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 1,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    27: {  # 'g'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 1,  # 'S'
+        31: 1,  # 'T'
+        51: 0,  # 'U'
+        38: 2,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 1,  # 'b'
+        28: 0,  # 'c'
+        12: 1,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 2,  # 'g'
+        25: 1,  # 'h'
+        3: 2,  # 'i'
+        24: 3,  # 'j'
+        10: 2,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 2,  # 'n'
+        15: 0,  # 'o'
+        26: 1,  # 'p'
+        7: 2,  # 'r'
+        8: 2,  # 's'
+        9: 3,  # 't'
+        14: 3,  # 'u'
+        32: 1,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 1,  # 'y'
+        22: 0,  # 'z'
+        63: 1,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    25: {  # 'h'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 2,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 0,  # 'c'
+        12: 2,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 1,  # 'g'
+        25: 2,  # 'h'
+        3: 2,  # 'i'
+        24: 3,  # 'j'
+        10: 3,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 1,  # 'o'
+        26: 1,  # 'p'
+        7: 3,  # 'r'
+        8: 3,  # 's'
+        9: 2,  # 't'
+        14: 3,  # 'u'
+        32: 2,  # 'v'
+        57: 1,  # 'w'
+        58: 0,  # 'x'
+        11: 1,  # 'y'
+        22: 0,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    3: {  # 'i'
+        23: 2,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 1,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 3,  # 'M'
+        46: 0,  # 'N'
+        42: 1,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 1,  # 'S'
+        31: 2,  # 'T'
+        51: 0,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 2,  # 'b'
+        28: 0,  # 'c'
+        12: 3,  # 'd'
+        2: 3,  # 'e'
+        18: 2,  # 'f'
+        27: 3,  # 'g'
+        25: 1,  # 'h'
+        3: 3,  # 'i'
+        24: 2,  # 'j'
+        10: 3,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 1,  # 'o'
+        26: 3,  # 'p'
+        7: 3,  # 'r'
+        8: 3,  # 's'
+        9: 3,  # 't'
+        14: 3,  # 'u'
+        32: 2,  # 'v'
+        57: 1,  # 'w'
+        58: 1,  # 'x'
+        11: 3,  # 'y'
+        22: 1,  # 'z'
+        63: 1,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 1,  # 'Ü'
+        59: 0,  # 'â'
+        33: 2,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 3,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    24: {  # 'j'
+        23: 0,  # 'A'
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+        39: 0,  # 'D'
+        29: 0,  # 'E'
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+        56: 1,  # 'Z'
+        1: 3,  # 'a'
+        21: 1,  # 'b'
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+        12: 3,  # 'd'
+        2: 3,  # 'e'
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+        27: 1,  # 'g'
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+        3: 2,  # 'i'
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+        33: 1,  # 'ç'
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+        17: 1,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    10: {  # 'k'
+        23: 0,  # 'A'
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+        3: 3,  # 'i'
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+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    5: {  # 'l'
+        23: 0,  # 'A'
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+        29: 3,  # 'E'
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+        60: 0,  # 'J'
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+        3: 3,  # 'i'
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+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    13: {  # 'm'
+        23: 1,  # 'A'
+        37: 0,  # 'B'
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+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    4: {  # 'n'
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+        45: 1,  # 'H'
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+        41: 0,  # 'İ'
+        6: 1,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    15: {  # 'o'
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+        6: 3,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 2,  # 'ş'
+    },
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+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
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+        19: 0,  # 'ş'
+    },
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+        19: 1,  # 'ş'
+    },
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+        50: 0,  # 'Ö'
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+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 2,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    14: {  # 'u'
+        23: 3,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 3,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 1,  # 'H'
+        53: 0,  # 'I'
+        60: 1,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 3,  # 'M'
+        46: 2,  # 'N'
+        42: 0,  # 'O'
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+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 3,  # 'T'
+        51: 0,  # 'U'
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+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 2,  # 'Z'
+        1: 2,  # 'a'
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+        12: 3,  # 'd'
+        2: 2,  # 'e'
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+        3: 3,  # 'i'
+        24: 2,  # 'j'
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+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
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+        17: 3,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    32: {  # 'v'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
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+        60: 0,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
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+        44: 0,  # 'R'
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+        1: 3,  # 'a'
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+        12: 3,  # 'd'
+        2: 3,  # 'e'
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+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 1,  # 'j'
+        10: 1,  # 'k'
+        5: 3,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 1,  # 'p'
+        7: 1,  # 'r'
+        8: 2,  # 's'
+        9: 3,  # 't'
+        14: 3,  # 'u'
+        32: 1,  # 'v'
+        57: 0,  # 'w'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 2,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 1,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    57: {  # 'w'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
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+        60: 0,  # 'J'
+        16: 0,  # 'K'
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+        20: 0,  # 'M'
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+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 1,  # 'U'
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+        1: 1,  # 'a'
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+        12: 0,  # 'd'
+        2: 2,  # 'e'
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+        27: 0,  # 'g'
+        25: 1,  # 'h'
+        3: 0,  # 'i'
+        24: 0,  # 'j'
+        10: 1,  # 'k'
+        5: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 1,  # 'n'
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+        9: 0,  # 't'
+        14: 1,  # 'u'
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+        57: 2,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 0,  # 'z'
+        63: 1,  # '·'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 1,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 0,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    58: {  # 'x'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 1,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 1,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
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+        42: 0,  # 'O'
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+        44: 0,  # 'R'
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+        2: 1,  # 'e'
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+        3: 2,  # 'i'
+        24: 2,  # 'j'
+        10: 1,  # 'k'
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+        4: 2,  # 'n'
+        15: 0,  # 'o'
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+        9: 1,  # 't'
+        14: 0,  # 'u'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
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+        34: 0,  # 'ö'
+        17: 1,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    11: {  # 'y'
+        23: 1,  # 'A'
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+        47: 0,  # 'C'
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+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 1,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
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+        35: 0,  # 'S'
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+        1: 3,  # 'a'
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+        12: 2,  # 'd'
+        2: 3,  # 'e'
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+        27: 2,  # 'g'
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+        3: 2,  # 'i'
+        24: 1,  # 'j'
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+        4: 3,  # 'n'
+        15: 0,  # 'o'
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+        14: 3,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 1,  # 'x'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 3,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 2,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    22: {  # 'z'
+        23: 2,  # 'A'
+        37: 2,  # 'B'
+        47: 1,  # 'C'
+        39: 2,  # 'D'
+        29: 3,  # 'E'
+        52: 1,  # 'F'
+        36: 2,  # 'G'
+        45: 2,  # 'H'
+        53: 1,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 3,  # 'M'
+        46: 2,  # 'N'
+        42: 2,  # 'O'
+        48: 2,  # 'P'
+        44: 1,  # 'R'
+        35: 1,  # 'S'
+        31: 3,  # 'T'
+        51: 2,  # 'U'
+        38: 2,  # 'V'
+        62: 0,  # 'W'
+        43: 2,  # 'Y'
+        56: 1,  # 'Z'
+        1: 1,  # 'a'
+        21: 2,  # 'b'
+        28: 1,  # 'c'
+        12: 2,  # 'd'
+        2: 2,  # 'e'
+        18: 3,  # 'f'
+        27: 2,  # 'g'
+        25: 2,  # 'h'
+        3: 3,  # 'i'
+        24: 2,  # 'j'
+        10: 3,  # 'k'
+        5: 0,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        15: 2,  # 'o'
+        26: 2,  # 'p'
+        7: 3,  # 'r'
+        8: 3,  # 's'
+        9: 3,  # 't'
+        14: 0,  # 'u'
+        32: 2,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 3,  # 'y'
+        22: 2,  # 'z'
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+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 2,  # 'Ü'
+        59: 1,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 2,  # 'ö'
+        17: 2,  # 'ü'
+        30: 2,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 3,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 2,  # 'ş'
+    },
+    63: {  # '·'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
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+        20: 0,  # 'M'
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+        43: 0,  # 'Y'
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+        1: 0,  # 'a'
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+        12: 0,  # 'd'
+        2: 1,  # 'e'
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+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 0,  # 'j'
+        10: 0,  # 'k'
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+        13: 2,  # 'm'
+        4: 0,  # 'n'
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+        14: 2,  # 'u'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
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+        41: 0,  # 'İ'
+        6: 0,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    54: {  # 'Ç'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 1,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 1,  # 'G'
+        45: 1,  # 'H'
+        53: 1,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 1,  # 'O'
+        48: 1,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 1,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 2,  # 'Y'
+        56: 0,  # 'Z'
+        1: 0,  # 'a'
+        21: 1,  # 'b'
+        28: 0,  # 'c'
+        12: 1,  # 'd'
+        2: 0,  # 'e'
+        18: 0,  # 'f'
+        27: 1,  # 'g'
+        25: 0,  # 'h'
+        3: 3,  # 'i'
+        24: 0,  # 'j'
+        10: 1,  # 'k'
+        5: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 2,  # 'n'
+        15: 1,  # 'o'
+        26: 0,  # 'p'
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+        8: 0,  # 's'
+        9: 1,  # 't'
+        14: 0,  # 'u'
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+        57: 0,  # 'w'
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+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 2,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
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+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    50: {  # 'Ö'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 1,  # 'D'
+        29: 2,  # 'E'
+        52: 0,  # 'F'
+        36: 1,  # 'G'
+        45: 2,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 1,  # 'N'
+        42: 2,  # 'O'
+        48: 2,  # 'P'
+        44: 1,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
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+        38: 1,  # 'V'
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+        1: 0,  # 'a'
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+        12: 2,  # 'd'
+        2: 0,  # 'e'
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+        27: 1,  # 'g'
+        25: 1,  # 'h'
+        3: 2,  # 'i'
+        24: 0,  # 'j'
+        10: 2,  # 'k'
+        5: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 3,  # 'n'
+        15: 2,  # 'o'
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+        14: 0,  # 'u'
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+        57: 0,  # 'w'
+        58: 0,  # 'x'
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+        22: 1,  # 'z'
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+        34: 2,  # 'ö'
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+        30: 1,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    55: {  # 'Ü'
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+        29: 0,  # 'E'
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+        36: 0,  # 'G'
+        45: 0,  # 'H'
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+        60: 0,  # 'J'
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+        46: 0,  # 'N'
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+        38: 1,  # 'V'
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+        43: 0,  # 'Y'
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+        1: 2,  # 'a'
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+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 2,  # 'e'
+        18: 0,  # 'f'
+        27: 1,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 0,  # 'j'
+        10: 0,  # 'k'
+        5: 1,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
+        7: 0,  # 'r'
+        8: 0,  # 's'
+        9: 1,  # 't'
+        14: 2,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 1,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 1,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 0,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 0,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    59: {  # 'â'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 1,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 1,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 2,  # 'a'
+        21: 0,  # 'b'
+        28: 0,  # 'c'
+        12: 0,  # 'd'
+        2: 2,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 0,  # 'j'
+        10: 0,  # 'k'
+        5: 0,  # 'l'
+        13: 2,  # 'm'
+        4: 0,  # 'n'
+        15: 1,  # 'o'
+        26: 0,  # 'p'
+        7: 0,  # 'r'
+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 2,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 1,  # 'z'
+        63: 0,  # '·'
+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 1,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    33: {  # 'ç'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 3,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 2,  # 'T'
+        51: 0,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 0,  # 'Z'
+        1: 0,  # 'a'
+        21: 3,  # 'b'
+        28: 0,  # 'c'
+        12: 2,  # 'd'
+        2: 0,  # 'e'
+        18: 2,  # 'f'
+        27: 1,  # 'g'
+        25: 3,  # 'h'
+        3: 3,  # 'i'
+        24: 0,  # 'j'
+        10: 3,  # 'k'
+        5: 0,  # 'l'
+        13: 0,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 1,  # 'p'
+        7: 3,  # 'r'
+        8: 2,  # 's'
+        9: 3,  # 't'
+        14: 0,  # 'u'
+        32: 2,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 2,  # 'y'
+        22: 0,  # 'z'
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+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 1,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    61: {  # 'î'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 0,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
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+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 0,  # 'T'
+        51: 0,  # 'U'
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+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 1,  # 'Z'
+        1: 2,  # 'a'
+        21: 0,  # 'b'
+        28: 0,  # 'c'
+        12: 0,  # 'd'
+        2: 2,  # 'e'
+        18: 0,  # 'f'
+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 1,  # 'j'
+        10: 0,  # 'k'
+        5: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 1,  # 'n'
+        15: 0,  # 'o'
+        26: 0,  # 'p'
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+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 1,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 1,  # 'z'
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+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 1,  # 'î'
+        34: 0,  # 'ö'
+        17: 0,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 1,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    34: {  # 'ö'
+        23: 0,  # 'A'
+        37: 1,  # 'B'
+        47: 1,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 2,  # 'F'
+        36: 1,  # 'G'
+        45: 1,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 3,  # 'K'
+        49: 1,  # 'L'
+        20: 0,  # 'M'
+        46: 1,  # 'N'
+        42: 1,  # 'O'
+        48: 2,  # 'P'
+        44: 1,  # 'R'
+        35: 1,  # 'S'
+        31: 1,  # 'T'
+        51: 1,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 1,  # 'Z'
+        1: 3,  # 'a'
+        21: 1,  # 'b'
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+        12: 1,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 2,  # 'g'
+        25: 2,  # 'h'
+        3: 1,  # 'i'
+        24: 2,  # 'j'
+        10: 1,  # 'k'
+        5: 2,  # 'l'
+        13: 3,  # 'm'
+        4: 2,  # 'n'
+        15: 2,  # 'o'
+        26: 0,  # 'p'
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+        9: 1,  # 't'
+        14: 3,  # 'u'
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+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 1,  # 'y'
+        22: 2,  # 'z'
+        63: 0,  # '·'
+        54: 1,  # 'Ç'
+        50: 2,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 2,  # 'ç'
+        61: 0,  # 'î'
+        34: 2,  # 'ö'
+        17: 0,  # 'ü'
+        30: 2,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 1,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    17: {  # 'ü'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 0,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 1,  # 'J'
+        16: 1,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 0,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 1,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 0,  # 'Y'
+        56: 1,  # 'Z'
+        1: 3,  # 'a'
+        21: 0,  # 'b'
+        28: 0,  # 'c'
+        12: 1,  # 'd'
+        2: 3,  # 'e'
+        18: 1,  # 'f'
+        27: 2,  # 'g'
+        25: 0,  # 'h'
+        3: 1,  # 'i'
+        24: 1,  # 'j'
+        10: 2,  # 'k'
+        5: 3,  # 'l'
+        13: 2,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 2,  # 'p'
+        7: 2,  # 'r'
+        8: 3,  # 's'
+        9: 2,  # 't'
+        14: 3,  # 'u'
+        32: 1,  # 'v'
+        57: 1,  # 'w'
+        58: 0,  # 'x'
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+        22: 0,  # 'z'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 0,  # 'ö'
+        17: 2,  # 'ü'
+        30: 0,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    30: {  # 'ğ'
+        23: 0,  # 'A'
+        37: 2,  # 'B'
+        47: 1,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 2,  # 'F'
+        36: 1,  # 'G'
+        45: 0,  # 'H'
+        53: 1,  # 'I'
+        60: 0,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 1,  # 'M'
+        46: 2,  # 'N'
+        42: 2,  # 'O'
+        48: 1,  # 'P'
+        44: 1,  # 'R'
+        35: 0,  # 'S'
+        31: 1,  # 'T'
+        51: 0,  # 'U'
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+        1: 3,  # 'a'
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+        12: 0,  # 'd'
+        2: 2,  # 'e'
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+        27: 0,  # 'g'
+        25: 0,  # 'h'
+        3: 0,  # 'i'
+        24: 3,  # 'j'
+        10: 1,  # 'k'
+        5: 2,  # 'l'
+        13: 3,  # 'm'
+        4: 0,  # 'n'
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+        14: 3,  # 'u'
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+        57: 0,  # 'w'
+        58: 0,  # 'x'
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+        22: 2,  # 'z'
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+        54: 2,  # 'Ç'
+        50: 2,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 0,  # 'î'
+        34: 2,  # 'ö'
+        17: 0,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 2,  # 'İ'
+        6: 2,  # 'ı'
+        40: 2,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    41: {  # 'İ'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 1,  # 'D'
+        29: 1,  # 'E'
+        52: 0,  # 'F'
+        36: 2,  # 'G'
+        45: 2,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
+        49: 0,  # 'L'
+        20: 2,  # 'M'
+        46: 1,  # 'N'
+        42: 1,  # 'O'
+        48: 2,  # 'P'
+        44: 0,  # 'R'
+        35: 1,  # 'S'
+        31: 1,  # 'T'
+        51: 1,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 2,  # 'Y'
+        56: 0,  # 'Z'
+        1: 1,  # 'a'
+        21: 2,  # 'b'
+        28: 1,  # 'c'
+        12: 2,  # 'd'
+        2: 1,  # 'e'
+        18: 0,  # 'f'
+        27: 3,  # 'g'
+        25: 2,  # 'h'
+        3: 2,  # 'i'
+        24: 2,  # 'j'
+        10: 2,  # 'k'
+        5: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 3,  # 'n'
+        15: 1,  # 'o'
+        26: 1,  # 'p'
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+        8: 3,  # 's'
+        9: 2,  # 't'
+        14: 0,  # 'u'
+        32: 0,  # 'v'
+        57: 1,  # 'w'
+        58: 0,  # 'x'
+        11: 2,  # 'y'
+        22: 0,  # 'z'
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+        54: 0,  # 'Ç'
+        50: 0,  # 'Ö'
+        55: 1,  # 'Ü'
+        59: 1,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 1,  # 'ö'
+        17: 1,  # 'ü'
+        30: 2,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+    6: {  # 'ı'
+        23: 2,  # 'A'
+        37: 0,  # 'B'
+        47: 0,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 0,  # 'F'
+        36: 1,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 2,  # 'J'
+        16: 3,  # 'K'
+        49: 0,  # 'L'
+        20: 3,  # 'M'
+        46: 1,  # 'N'
+        42: 0,  # 'O'
+        48: 0,  # 'P'
+        44: 0,  # 'R'
+        35: 0,  # 'S'
+        31: 2,  # 'T'
+        51: 0,  # 'U'
+        38: 0,  # 'V'
+        62: 0,  # 'W'
+        43: 2,  # 'Y'
+        56: 1,  # 'Z'
+        1: 3,  # 'a'
+        21: 2,  # 'b'
+        28: 1,  # 'c'
+        12: 3,  # 'd'
+        2: 3,  # 'e'
+        18: 3,  # 'f'
+        27: 3,  # 'g'
+        25: 2,  # 'h'
+        3: 3,  # 'i'
+        24: 3,  # 'j'
+        10: 3,  # 'k'
+        5: 3,  # 'l'
+        13: 3,  # 'm'
+        4: 3,  # 'n'
+        15: 0,  # 'o'
+        26: 3,  # 'p'
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+        9: 3,  # 't'
+        14: 3,  # 'u'
+        32: 3,  # 'v'
+        57: 1,  # 'w'
+        58: 1,  # 'x'
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+        22: 0,  # 'z'
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+        50: 0,  # 'Ö'
+        55: 0,  # 'Ü'
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+        33: 2,  # 'ç'
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+        17: 3,  # 'ü'
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+        41: 0,  # 'İ'
+        6: 3,  # 'ı'
+        40: 0,  # 'Ş'
+        19: 0,  # 'ş'
+    },
+    40: {  # 'Ş'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 1,  # 'D'
+        29: 1,  # 'E'
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+        36: 1,  # 'G'
+        45: 2,  # 'H'
+        53: 1,  # 'I'
+        60: 0,  # 'J'
+        16: 0,  # 'K'
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+        20: 2,  # 'M'
+        46: 1,  # 'N'
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+        48: 2,  # 'P'
+        44: 2,  # 'R'
+        35: 1,  # 'S'
+        31: 1,  # 'T'
+        51: 0,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 2,  # 'Y'
+        56: 1,  # 'Z'
+        1: 0,  # 'a'
+        21: 2,  # 'b'
+        28: 0,  # 'c'
+        12: 2,  # 'd'
+        2: 0,  # 'e'
+        18: 3,  # 'f'
+        27: 0,  # 'g'
+        25: 2,  # 'h'
+        3: 3,  # 'i'
+        24: 2,  # 'j'
+        10: 1,  # 'k'
+        5: 0,  # 'l'
+        13: 1,  # 'm'
+        4: 3,  # 'n'
+        15: 2,  # 'o'
+        26: 0,  # 'p'
+        7: 3,  # 'r'
+        8: 2,  # 's'
+        9: 2,  # 't'
+        14: 1,  # 'u'
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+        57: 0,  # 'w'
+        58: 0,  # 'x'
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+        22: 0,  # 'z'
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+        50: 0,  # 'Ö'
+        55: 1,  # 'Ü'
+        59: 0,  # 'â'
+        33: 0,  # 'ç'
+        61: 0,  # 'î'
+        34: 2,  # 'ö'
+        17: 1,  # 'ü'
+        30: 2,  # 'ğ'
+        41: 0,  # 'İ'
+        6: 2,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 2,  # 'ş'
+    },
+    19: {  # 'ş'
+        23: 0,  # 'A'
+        37: 0,  # 'B'
+        47: 1,  # 'C'
+        39: 0,  # 'D'
+        29: 0,  # 'E'
+        52: 2,  # 'F'
+        36: 1,  # 'G'
+        45: 0,  # 'H'
+        53: 0,  # 'I'
+        60: 0,  # 'J'
+        16: 3,  # 'K'
+        49: 2,  # 'L'
+        20: 0,  # 'M'
+        46: 1,  # 'N'
+        42: 1,  # 'O'
+        48: 1,  # 'P'
+        44: 1,  # 'R'
+        35: 1,  # 'S'
+        31: 0,  # 'T'
+        51: 1,  # 'U'
+        38: 1,  # 'V'
+        62: 0,  # 'W'
+        43: 1,  # 'Y'
+        56: 0,  # 'Z'
+        1: 3,  # 'a'
+        21: 1,  # 'b'
+        28: 2,  # 'c'
+        12: 0,  # 'd'
+        2: 3,  # 'e'
+        18: 0,  # 'f'
+        27: 2,  # 'g'
+        25: 1,  # 'h'
+        3: 1,  # 'i'
+        24: 0,  # 'j'
+        10: 2,  # 'k'
+        5: 2,  # 'l'
+        13: 3,  # 'm'
+        4: 0,  # 'n'
+        15: 0,  # 'o'
+        26: 1,  # 'p'
+        7: 3,  # 'r'
+        8: 0,  # 's'
+        9: 0,  # 't'
+        14: 3,  # 'u'
+        32: 0,  # 'v'
+        57: 0,  # 'w'
+        58: 0,  # 'x'
+        11: 0,  # 'y'
+        22: 2,  # 'z'
+        63: 0,  # '·'
+        54: 1,  # 'Ç'
+        50: 2,  # 'Ö'
+        55: 0,  # 'Ü'
+        59: 0,  # 'â'
+        33: 1,  # 'ç'
+        61: 1,  # 'î'
+        34: 2,  # 'ö'
+        17: 0,  # 'ü'
+        30: 1,  # 'ğ'
+        41: 1,  # 'İ'
+        6: 1,  # 'ı'
+        40: 1,  # 'Ş'
+        19: 1,  # 'ş'
+    },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+ISO_8859_9_TURKISH_CHAR_TO_ORDER = {
+    0: 255,  # '\x00'
+    1: 255,  # '\x01'
+    2: 255,  # '\x02'
+    3: 255,  # '\x03'
+    4: 255,  # '\x04'
+    5: 255,  # '\x05'
+    6: 255,  # '\x06'
+    7: 255,  # '\x07'
+    8: 255,  # '\x08'
+    9: 255,  # '\t'
+    10: 255,  # '\n'
+    11: 255,  # '\x0b'
+    12: 255,  # '\x0c'
+    13: 255,  # '\r'
+    14: 255,  # '\x0e'
+    15: 255,  # '\x0f'
+    16: 255,  # '\x10'
+    17: 255,  # '\x11'
+    18: 255,  # '\x12'
+    19: 255,  # '\x13'
+    20: 255,  # '\x14'
+    21: 255,  # '\x15'
+    22: 255,  # '\x16'
+    23: 255,  # '\x17'
+    24: 255,  # '\x18'
+    25: 255,  # '\x19'
+    26: 255,  # '\x1a'
+    27: 255,  # '\x1b'
+    28: 255,  # '\x1c'
+    29: 255,  # '\x1d'
+    30: 255,  # '\x1e'
+    31: 255,  # '\x1f'
+    32: 255,  # ' '
+    33: 255,  # '!'
+    34: 255,  # '"'
+    35: 255,  # '#'
+    36: 255,  # '$'
+    37: 255,  # '%'
+    38: 255,  # '&'
+    39: 255,  # "'"
+    40: 255,  # '('
+    41: 255,  # ')'
+    42: 255,  # '*'
+    43: 255,  # '+'
+    44: 255,  # ','
+    45: 255,  # '-'
+    46: 255,  # '.'
+    47: 255,  # '/'
+    48: 255,  # '0'
+    49: 255,  # '1'
+    50: 255,  # '2'
+    51: 255,  # '3'
+    52: 255,  # '4'
+    53: 255,  # '5'
+    54: 255,  # '6'
+    55: 255,  # '7'
+    56: 255,  # '8'
+    57: 255,  # '9'
+    58: 255,  # ':'
+    59: 255,  # ';'
+    60: 255,  # '<'
+    61: 255,  # '='
+    62: 255,  # '>'
+    63: 255,  # '?'
+    64: 255,  # '@'
+    65: 23,  # 'A'
+    66: 37,  # 'B'
+    67: 47,  # 'C'
+    68: 39,  # 'D'
+    69: 29,  # 'E'
+    70: 52,  # 'F'
+    71: 36,  # 'G'
+    72: 45,  # 'H'
+    73: 53,  # 'I'
+    74: 60,  # 'J'
+    75: 16,  # 'K'
+    76: 49,  # 'L'
+    77: 20,  # 'M'
+    78: 46,  # 'N'
+    79: 42,  # 'O'
+    80: 48,  # 'P'
+    81: 69,  # 'Q'
+    82: 44,  # 'R'
+    83: 35,  # 'S'
+    84: 31,  # 'T'
+    85: 51,  # 'U'
+    86: 38,  # 'V'
+    87: 62,  # 'W'
+    88: 65,  # 'X'
+    89: 43,  # 'Y'
+    90: 56,  # 'Z'
+    91: 255,  # '['
+    92: 255,  # '\\'
+    93: 255,  # ']'
+    94: 255,  # '^'
+    95: 255,  # '_'
+    96: 255,  # '`'
+    97: 1,  # 'a'
+    98: 21,  # 'b'
+    99: 28,  # 'c'
+    100: 12,  # 'd'
+    101: 2,  # 'e'
+    102: 18,  # 'f'
+    103: 27,  # 'g'
+    104: 25,  # 'h'
+    105: 3,  # 'i'
+    106: 24,  # 'j'
+    107: 10,  # 'k'
+    108: 5,  # 'l'
+    109: 13,  # 'm'
+    110: 4,  # 'n'
+    111: 15,  # 'o'
+    112: 26,  # 'p'
+    113: 64,  # 'q'
+    114: 7,  # 'r'
+    115: 8,  # 's'
+    116: 9,  # 't'
+    117: 14,  # 'u'
+    118: 32,  # 'v'
+    119: 57,  # 'w'
+    120: 58,  # 'x'
+    121: 11,  # 'y'
+    122: 22,  # 'z'
+    123: 255,  # '{'
+    124: 255,  # '|'
+    125: 255,  # '}'
+    126: 255,  # '~'
+    127: 255,  # '\x7f'
+    128: 180,  # '\x80'
+    129: 179,  # '\x81'
+    130: 178,  # '\x82'
+    131: 177,  # '\x83'
+    132: 176,  # '\x84'
+    133: 175,  # '\x85'
+    134: 174,  # '\x86'
+    135: 173,  # '\x87'
+    136: 172,  # '\x88'
+    137: 171,  # '\x89'
+    138: 170,  # '\x8a'
+    139: 169,  # '\x8b'
+    140: 168,  # '\x8c'
+    141: 167,  # '\x8d'
+    142: 166,  # '\x8e'
+    143: 165,  # '\x8f'
+    144: 164,  # '\x90'
+    145: 163,  # '\x91'
+    146: 162,  # '\x92'
+    147: 161,  # '\x93'
+    148: 160,  # '\x94'
+    149: 159,  # '\x95'
+    150: 101,  # '\x96'
+    151: 158,  # '\x97'
+    152: 157,  # '\x98'
+    153: 156,  # '\x99'
+    154: 155,  # '\x9a'
+    155: 154,  # '\x9b'
+    156: 153,  # '\x9c'
+    157: 152,  # '\x9d'
+    158: 151,  # '\x9e'
+    159: 106,  # '\x9f'
+    160: 150,  # '\xa0'
+    161: 149,  # '¡'
+    162: 148,  # '¢'
+    163: 147,  # '£'
+    164: 146,  # '¤'
+    165: 145,  # '¥'
+    166: 144,  # '¦'
+    167: 100,  # '§'
+    168: 143,  # '¨'
+    169: 142,  # '©'
+    170: 141,  # 'ª'
+    171: 140,  # '«'
+    172: 139,  # '¬'
+    173: 138,  # '\xad'
+    174: 137,  # '®'
+    175: 136,  # '¯'
+    176: 94,  # '°'
+    177: 80,  # '±'
+    178: 93,  # '²'
+    179: 135,  # '³'
+    180: 105,  # '´'
+    181: 134,  # 'µ'
+    182: 133,  # '¶'
+    183: 63,  # '·'
+    184: 132,  # '¸'
+    185: 131,  # '¹'
+    186: 130,  # 'º'
+    187: 129,  # '»'
+    188: 128,  # '¼'
+    189: 127,  # '½'
+    190: 126,  # '¾'
+    191: 125,  # '¿'
+    192: 124,  # 'À'
+    193: 104,  # 'Á'
+    194: 73,  # 'Â'
+    195: 99,  # 'Ã'
+    196: 79,  # 'Ä'
+    197: 85,  # 'Å'
+    198: 123,  # 'Æ'
+    199: 54,  # 'Ç'
+    200: 122,  # 'È'
+    201: 98,  # 'É'
+    202: 92,  # 'Ê'
+    203: 121,  # 'Ë'
+    204: 120,  # 'Ì'
+    205: 91,  # 'Í'
+    206: 103,  # 'Î'
+    207: 119,  # 'Ï'
+    208: 68,  # 'Ğ'
+    209: 118,  # 'Ñ'
+    210: 117,  # 'Ò'
+    211: 97,  # 'Ó'
+    212: 116,  # 'Ô'
+    213: 115,  # 'Õ'
+    214: 50,  # 'Ö'
+    215: 90,  # '×'
+    216: 114,  # 'Ø'
+    217: 113,  # 'Ù'
+    218: 112,  # 'Ú'
+    219: 111,  # 'Û'
+    220: 55,  # 'Ü'
+    221: 41,  # 'İ'
+    222: 40,  # 'Ş'
+    223: 86,  # 'ß'
+    224: 89,  # 'à'
+    225: 70,  # 'á'
+    226: 59,  # 'â'
+    227: 78,  # 'ã'
+    228: 71,  # 'ä'
+    229: 82,  # 'å'
+    230: 88,  # 'æ'
+    231: 33,  # 'ç'
+    232: 77,  # 'è'
+    233: 66,  # 'é'
+    234: 84,  # 'ê'
+    235: 83,  # 'ë'
+    236: 110,  # 'ì'
+    237: 75,  # 'í'
+    238: 61,  # 'î'
+    239: 96,  # 'ï'
+    240: 30,  # 'ğ'
+    241: 67,  # 'ñ'
+    242: 109,  # 'ò'
+    243: 74,  # 'ó'
+    244: 87,  # 'ô'
+    245: 102,  # 'õ'
+    246: 34,  # 'ö'
+    247: 95,  # '÷'
+    248: 81,  # 'ø'
+    249: 108,  # 'ù'
+    250: 76,  # 'ú'
+    251: 72,  # 'û'
+    252: 17,  # 'ü'
+    253: 6,  # 'ı'
+    254: 19,  # 'ş'
+    255: 107,  # 'ÿ'
+}
+
+ISO_8859_9_TURKISH_MODEL = SingleByteCharSetModel(
+    charset_name="ISO-8859-9",
+    language="Turkish",
+    char_to_order_map=ISO_8859_9_TURKISH_CHAR_TO_ORDER,
+    language_model=TURKISH_LANG_MODEL,
+    typical_positive_ratio=0.97029,
+    keep_ascii_letters=True,
+    alphabet="ABCDEFGHIJKLMNOPRSTUVYZabcdefghijklmnoprstuvyzÂÇÎÖÛÜâçîöûüĞğİıŞş",
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/latin1prober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/latin1prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..59a01d91b87d4282bede38ade7cc78c0f7552d0e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/latin1prober.py
@@ -0,0 +1,147 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+
+FREQ_CAT_NUM = 4
+
+UDF = 0  # undefined
+OTH = 1  # other
+ASC = 2  # ascii capital letter
+ASS = 3  # ascii small letter
+ACV = 4  # accent capital vowel
+ACO = 5  # accent capital other
+ASV = 6  # accent small vowel
+ASO = 7  # accent small other
+CLASS_NUM = 8  # total classes
+
+# fmt: off
+Latin1_CharToClass = (
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 00 - 07
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 08 - 0F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 10 - 17
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 18 - 1F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 20 - 27
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 28 - 2F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 30 - 37
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 38 - 3F
+    OTH, ASC, ASC, ASC, ASC, ASC, ASC, ASC,   # 40 - 47
+    ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC,   # 48 - 4F
+    ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC,   # 50 - 57
+    ASC, ASC, ASC, OTH, OTH, OTH, OTH, OTH,   # 58 - 5F
+    OTH, ASS, ASS, ASS, ASS, ASS, ASS, ASS,   # 60 - 67
+    ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS,   # 68 - 6F
+    ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS,   # 70 - 77
+    ASS, ASS, ASS, OTH, OTH, OTH, OTH, OTH,   # 78 - 7F
+    OTH, UDF, OTH, ASO, OTH, OTH, OTH, OTH,   # 80 - 87
+    OTH, OTH, ACO, OTH, ACO, UDF, ACO, UDF,   # 88 - 8F
+    UDF, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # 90 - 97
+    OTH, OTH, ASO, OTH, ASO, UDF, ASO, ACO,   # 98 - 9F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # A0 - A7
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # A8 - AF
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # B0 - B7
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,   # B8 - BF
+    ACV, ACV, ACV, ACV, ACV, ACV, ACO, ACO,   # C0 - C7
+    ACV, ACV, ACV, ACV, ACV, ACV, ACV, ACV,   # C8 - CF
+    ACO, ACO, ACV, ACV, ACV, ACV, ACV, OTH,   # D0 - D7
+    ACV, ACV, ACV, ACV, ACV, ACO, ACO, ACO,   # D8 - DF
+    ASV, ASV, ASV, ASV, ASV, ASV, ASO, ASO,   # E0 - E7
+    ASV, ASV, ASV, ASV, ASV, ASV, ASV, ASV,   # E8 - EF
+    ASO, ASO, ASV, ASV, ASV, ASV, ASV, OTH,   # F0 - F7
+    ASV, ASV, ASV, ASV, ASV, ASO, ASO, ASO,   # F8 - FF
+)
+
+# 0 : illegal
+# 1 : very unlikely
+# 2 : normal
+# 3 : very likely
+Latin1ClassModel = (
+# UDF OTH ASC ASS ACV ACO ASV ASO
+    0,  0,  0,  0,  0,  0,  0,  0,  # UDF
+    0,  3,  3,  3,  3,  3,  3,  3,  # OTH
+    0,  3,  3,  3,  3,  3,  3,  3,  # ASC
+    0,  3,  3,  3,  1,  1,  3,  3,  # ASS
+    0,  3,  3,  3,  1,  2,  1,  2,  # ACV
+    0,  3,  3,  3,  3,  3,  3,  3,  # ACO
+    0,  3,  1,  3,  1,  1,  1,  3,  # ASV
+    0,  3,  1,  3,  1,  1,  3,  3,  # ASO
+)
+# fmt: on
+
+
+class Latin1Prober(CharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self._last_char_class = OTH
+        self._freq_counter: List[int] = []
+        self.reset()
+
+    def reset(self) -> None:
+        self._last_char_class = OTH
+        self._freq_counter = [0] * FREQ_CAT_NUM
+        super().reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "ISO-8859-1"
+
+    @property
+    def language(self) -> str:
+        return ""
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        byte_str = self.remove_xml_tags(byte_str)
+        for c in byte_str:
+            char_class = Latin1_CharToClass[c]
+            freq = Latin1ClassModel[(self._last_char_class * CLASS_NUM) + char_class]
+            if freq == 0:
+                self._state = ProbingState.NOT_ME
+                break
+            self._freq_counter[freq] += 1
+            self._last_char_class = char_class
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        if self.state == ProbingState.NOT_ME:
+            return 0.01
+
+        total = sum(self._freq_counter)
+        confidence = (
+            0.0
+            if total < 0.01
+            else (self._freq_counter[3] - self._freq_counter[1] * 20.0) / total
+        )
+        confidence = max(confidence, 0.0)
+        # lower the confidence of latin1 so that other more accurate
+        # detector can take priority.
+        confidence *= 0.73
+        return confidence
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/macromanprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/macromanprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..1425d10ecaa59a9e49b73cea2b8b4747de73f6b5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/macromanprober.py
@@ -0,0 +1,162 @@
+######################## BEGIN LICENSE BLOCK ########################
+# This code was modified from latin1prober.py by Rob Speer .
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Rob Speer - adapt to MacRoman encoding
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+
+FREQ_CAT_NUM = 4
+
+UDF = 0  # undefined
+OTH = 1  # other
+ASC = 2  # ascii capital letter
+ASS = 3  # ascii small letter
+ACV = 4  # accent capital vowel
+ACO = 5  # accent capital other
+ASV = 6  # accent small vowel
+ASO = 7  # accent small other
+ODD = 8  # character that is unlikely to appear
+CLASS_NUM = 9  # total classes
+
+# The change from Latin1 is that we explicitly look for extended characters
+# that are infrequently-occurring symbols, and consider them to always be
+# improbable. This should let MacRoman get out of the way of more likely
+# encodings in most situations.
+
+# fmt: off
+MacRoman_CharToClass = (
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 00 - 07
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 08 - 0F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 10 - 17
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 18 - 1F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 20 - 27
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 28 - 2F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 30 - 37
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 38 - 3F
+    OTH, ASC, ASC, ASC, ASC, ASC, ASC, ASC,  # 40 - 47
+    ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC,  # 48 - 4F
+    ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC,  # 50 - 57
+    ASC, ASC, ASC, OTH, OTH, OTH, OTH, OTH,  # 58 - 5F
+    OTH, ASS, ASS, ASS, ASS, ASS, ASS, ASS,  # 60 - 67
+    ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS,  # 68 - 6F
+    ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS,  # 70 - 77
+    ASS, ASS, ASS, OTH, OTH, OTH, OTH, OTH,  # 78 - 7F
+    ACV, ACV, ACO, ACV, ACO, ACV, ACV, ASV,  # 80 - 87
+    ASV, ASV, ASV, ASV, ASV, ASO, ASV, ASV,  # 88 - 8F
+    ASV, ASV, ASV, ASV, ASV, ASV, ASO, ASV,  # 90 - 97
+    ASV, ASV, ASV, ASV, ASV, ASV, ASV, ASV,  # 98 - 9F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, ASO,  # A0 - A7
+    OTH, OTH, ODD, ODD, OTH, OTH, ACV, ACV,  # A8 - AF
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # B0 - B7
+    OTH, OTH, OTH, OTH, OTH, OTH, ASV, ASV,  # B8 - BF
+    OTH, OTH, ODD, OTH, ODD, OTH, OTH, OTH,  # C0 - C7
+    OTH, OTH, OTH, ACV, ACV, ACV, ACV, ASV,  # C8 - CF
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, ODD,  # D0 - D7
+    ASV, ACV, ODD, OTH, OTH, OTH, OTH, OTH,  # D8 - DF
+    OTH, OTH, OTH, OTH, OTH, ACV, ACV, ACV,  # E0 - E7
+    ACV, ACV, ACV, ACV, ACV, ACV, ACV, ACV,  # E8 - EF
+    ODD, ACV, ACV, ACV, ACV, ASV, ODD, ODD,  # F0 - F7
+    ODD, ODD, ODD, ODD, ODD, ODD, ODD, ODD,  # F8 - FF
+)
+
+# 0 : illegal
+# 1 : very unlikely
+# 2 : normal
+# 3 : very likely
+MacRomanClassModel = (
+# UDF OTH ASC ASS ACV ACO ASV ASO ODD
+    0,  0,  0,  0,  0,  0,  0,  0,  0,  # UDF
+    0,  3,  3,  3,  3,  3,  3,  3,  1,  # OTH
+    0,  3,  3,  3,  3,  3,  3,  3,  1,  # ASC
+    0,  3,  3,  3,  1,  1,  3,  3,  1,  # ASS
+    0,  3,  3,  3,  1,  2,  1,  2,  1,  # ACV
+    0,  3,  3,  3,  3,  3,  3,  3,  1,  # ACO
+    0,  3,  1,  3,  1,  1,  1,  3,  1,  # ASV
+    0,  3,  1,  3,  1,  1,  3,  3,  1,  # ASO
+    0,  1,  1,  1,  1,  1,  1,  1,  1,  # ODD
+)
+# fmt: on
+
+
+class MacRomanProber(CharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self._last_char_class = OTH
+        self._freq_counter: List[int] = []
+        self.reset()
+
+    def reset(self) -> None:
+        self._last_char_class = OTH
+        self._freq_counter = [0] * FREQ_CAT_NUM
+
+        # express the prior that MacRoman is a somewhat rare encoding;
+        # this can be done by starting out in a slightly improbable state
+        # that must be overcome
+        self._freq_counter[2] = 10
+
+        super().reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "MacRoman"
+
+    @property
+    def language(self) -> str:
+        return ""
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        byte_str = self.remove_xml_tags(byte_str)
+        for c in byte_str:
+            char_class = MacRoman_CharToClass[c]
+            freq = MacRomanClassModel[(self._last_char_class * CLASS_NUM) + char_class]
+            if freq == 0:
+                self._state = ProbingState.NOT_ME
+                break
+            self._freq_counter[freq] += 1
+            self._last_char_class = char_class
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        if self.state == ProbingState.NOT_ME:
+            return 0.01
+
+        total = sum(self._freq_counter)
+        confidence = (
+            0.0
+            if total < 0.01
+            else (self._freq_counter[3] - self._freq_counter[1] * 20.0) / total
+        )
+        confidence = max(confidence, 0.0)
+        # lower the confidence of MacRoman so that other more accurate
+        # detector can take priority.
+        confidence *= 0.73
+        return confidence
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcharsetprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcharsetprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..666307e8fe0608c69f2b6578a49794e1e20a139a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcharsetprober.py
@@ -0,0 +1,95 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#   Proofpoint, Inc.
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .chardistribution import CharDistributionAnalysis
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import LanguageFilter, MachineState, ProbingState
+
+
+class MultiByteCharSetProber(CharSetProber):
+    """
+    MultiByteCharSetProber
+    """
+
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self.distribution_analyzer: Optional[CharDistributionAnalysis] = None
+        self.coding_sm: Optional[CodingStateMachine] = None
+        self._last_char = bytearray(b"\0\0")
+
+    def reset(self) -> None:
+        super().reset()
+        if self.coding_sm:
+            self.coding_sm.reset()
+        if self.distribution_analyzer:
+            self.distribution_analyzer.reset()
+        self._last_char = bytearray(b"\0\0")
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        assert self.coding_sm is not None
+        assert self.distribution_analyzer is not None
+
+        for i, byte in enumerate(byte_str):
+            coding_state = self.coding_sm.next_state(byte)
+            if coding_state == MachineState.ERROR:
+                self.logger.debug(
+                    "%s %s prober hit error at byte %s",
+                    self.charset_name,
+                    self.language,
+                    i,
+                )
+                self._state = ProbingState.NOT_ME
+                break
+            if coding_state == MachineState.ITS_ME:
+                self._state = ProbingState.FOUND_IT
+                break
+            if coding_state == MachineState.START:
+                char_len = self.coding_sm.get_current_charlen()
+                if i == 0:
+                    self._last_char[1] = byte
+                    self.distribution_analyzer.feed(self._last_char, char_len)
+                else:
+                    self.distribution_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+
+        self._last_char[0] = byte_str[-1]
+
+        if self.state == ProbingState.DETECTING:
+            if self.distribution_analyzer.got_enough_data() and (
+                self.get_confidence() > self.SHORTCUT_THRESHOLD
+            ):
+                self._state = ProbingState.FOUND_IT
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        assert self.distribution_analyzer is not None
+        return self.distribution_analyzer.get_confidence()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcsgroupprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcsgroupprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..6cb9cc7b3bc751fbb5a54ba06eaaf953bf14ed8d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcsgroupprober.py
@@ -0,0 +1,57 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#   Proofpoint, Inc.
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .big5prober import Big5Prober
+from .charsetgroupprober import CharSetGroupProber
+from .cp949prober import CP949Prober
+from .enums import LanguageFilter
+from .eucjpprober import EUCJPProber
+from .euckrprober import EUCKRProber
+from .euctwprober import EUCTWProber
+from .gb2312prober import GB2312Prober
+from .johabprober import JOHABProber
+from .sjisprober import SJISProber
+from .utf8prober import UTF8Prober
+
+
+class MBCSGroupProber(CharSetGroupProber):
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self.probers = [
+            UTF8Prober(),
+            SJISProber(),
+            EUCJPProber(),
+            GB2312Prober(),
+            EUCKRProber(),
+            CP949Prober(),
+            Big5Prober(),
+            EUCTWProber(),
+            JOHABProber(),
+        ]
+        self.reset()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcssm.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcssm.py
new file mode 100644
index 0000000000000000000000000000000000000000..7bbe97e6665356327814e2b797ffcc5724974a46
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/mbcssm.py
@@ -0,0 +1,661 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+# BIG5
+
+# fmt: off
+BIG5_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07    #allow 0x00 as legal value
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 1,  # 78 - 7f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 80 - 87
+    4, 4, 4, 4, 4, 4, 4, 4,  # 88 - 8f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 90 - 97
+    4, 4, 4, 4, 4, 4, 4, 4,  # 98 - 9f
+    4, 3, 3, 3, 3, 3, 3, 3,  # a0 - a7
+    3, 3, 3, 3, 3, 3, 3, 3,  # a8 - af
+    3, 3, 3, 3, 3, 3, 3, 3,  # b0 - b7
+    3, 3, 3, 3, 3, 3, 3, 3,  # b8 - bf
+    3, 3, 3, 3, 3, 3, 3, 3,  # c0 - c7
+    3, 3, 3, 3, 3, 3, 3, 3,  # c8 - cf
+    3, 3, 3, 3, 3, 3, 3, 3,  # d0 - d7
+    3, 3, 3, 3, 3, 3, 3, 3,  # d8 - df
+    3, 3, 3, 3, 3, 3, 3, 3,  # e0 - e7
+    3, 3, 3, 3, 3, 3, 3, 3,  # e8 - ef
+    3, 3, 3, 3, 3, 3, 3, 3,  # f0 - f7
+    3, 3, 3, 3, 3, 3, 3, 0  # f8 - ff
+)
+
+BIG5_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.START,     3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,#08-0f
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START#10-17
+)
+# fmt: on
+
+BIG5_CHAR_LEN_TABLE = (0, 1, 1, 2, 0)
+
+BIG5_SM_MODEL: CodingStateMachineDict = {
+    "class_table": BIG5_CLS,
+    "class_factor": 5,
+    "state_table": BIG5_ST,
+    "char_len_table": BIG5_CHAR_LEN_TABLE,
+    "name": "Big5",
+}
+
+# CP949
+# fmt: off
+CP949_CLS  = (
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,  # 00 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,  # 10 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 3f
+    1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,  # 40 - 4f
+    4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1, 1,  # 50 - 5f
+    1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,  # 60 - 6f
+    5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1, 1,  # 70 - 7f
+    0, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,  # 80 - 8f
+    6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,  # 90 - 9f
+    6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8,  # a0 - af
+    7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7,  # b0 - bf
+    7, 7, 7, 7, 7, 7, 9, 2, 2, 3, 2, 2, 2, 2, 2, 2,  # c0 - cf
+    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,  # d0 - df
+    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,  # e0 - ef
+    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0,  # f0 - ff
+)
+
+CP949_ST = (
+#cls=    0      1      2      3      4      5      6      7      8      9  # previous state =
+    MachineState.ERROR,MachineState.START,     3,MachineState.ERROR,MachineState.START,MachineState.START,     4,     5,MachineState.ERROR,     6, # MachineState.START
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, # MachineState.ERROR
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME, # MachineState.ITS_ME
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START, # 3
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START, # 4
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START, # 5
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START, # 6
+)
+# fmt: on
+
+CP949_CHAR_LEN_TABLE = (0, 1, 2, 0, 1, 1, 2, 2, 0, 2)
+
+CP949_SM_MODEL: CodingStateMachineDict = {
+    "class_table": CP949_CLS,
+    "class_factor": 10,
+    "state_table": CP949_ST,
+    "char_len_table": CP949_CHAR_LEN_TABLE,
+    "name": "CP949",
+}
+
+# EUC-JP
+# fmt: off
+EUCJP_CLS = (
+    4, 4, 4, 4, 4, 4, 4, 4,  # 00 - 07
+    4, 4, 4, 4, 4, 4, 5, 5,  # 08 - 0f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 10 - 17
+    4, 4, 4, 5, 4, 4, 4, 4,  # 18 - 1f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 20 - 27
+    4, 4, 4, 4, 4, 4, 4, 4,  # 28 - 2f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 30 - 37
+    4, 4, 4, 4, 4, 4, 4, 4,  # 38 - 3f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 40 - 47
+    4, 4, 4, 4, 4, 4, 4, 4,  # 48 - 4f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 50 - 57
+    4, 4, 4, 4, 4, 4, 4, 4,  # 58 - 5f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 60 - 67
+    4, 4, 4, 4, 4, 4, 4, 4,  # 68 - 6f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 70 - 77
+    4, 4, 4, 4, 4, 4, 4, 4,  # 78 - 7f
+    5, 5, 5, 5, 5, 5, 5, 5,  # 80 - 87
+    5, 5, 5, 5, 5, 5, 1, 3,  # 88 - 8f
+    5, 5, 5, 5, 5, 5, 5, 5,  # 90 - 97
+    5, 5, 5, 5, 5, 5, 5, 5,  # 98 - 9f
+    5, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    0, 0, 0, 0, 0, 0, 0, 0,  # e0 - e7
+    0, 0, 0, 0, 0, 0, 0, 0,  # e8 - ef
+    0, 0, 0, 0, 0, 0, 0, 0,  # f0 - f7
+    0, 0, 0, 0, 0, 0, 0, 5  # f8 - ff
+)
+
+EUCJP_ST = (
+          3,     4,     3,     5,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+     MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+     MachineState.ITS_ME,MachineState.ITS_ME,MachineState.START,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#10-17
+     MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     3,MachineState.ERROR,#18-1f
+          3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START#20-27
+)
+# fmt: on
+
+EUCJP_CHAR_LEN_TABLE = (2, 2, 2, 3, 1, 0)
+
+EUCJP_SM_MODEL: CodingStateMachineDict = {
+    "class_table": EUCJP_CLS,
+    "class_factor": 6,
+    "state_table": EUCJP_ST,
+    "char_len_table": EUCJP_CHAR_LEN_TABLE,
+    "name": "EUC-JP",
+}
+
+# EUC-KR
+# fmt: off
+EUCKR_CLS  = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 40 - 47
+    1, 1, 1, 1, 1, 1, 1, 1,  # 48 - 4f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 50 - 57
+    1, 1, 1, 1, 1, 1, 1, 1,  # 58 - 5f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 60 - 67
+    1, 1, 1, 1, 1, 1, 1, 1,  # 68 - 6f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 70 - 77
+    1, 1, 1, 1, 1, 1, 1, 1,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 0, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 3, 3, 3,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 3, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 0   # f8 - ff
+)
+
+EUCKR_ST = (
+    MachineState.ERROR,MachineState.START,     3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START #08-0f
+)
+# fmt: on
+
+EUCKR_CHAR_LEN_TABLE = (0, 1, 2, 0)
+
+EUCKR_SM_MODEL: CodingStateMachineDict = {
+    "class_table": EUCKR_CLS,
+    "class_factor": 4,
+    "state_table": EUCKR_ST,
+    "char_len_table": EUCKR_CHAR_LEN_TABLE,
+    "name": "EUC-KR",
+}
+
+# JOHAB
+# fmt: off
+JOHAB_CLS = (
+    4,4,4,4,4,4,4,4,  # 00 - 07
+    4,4,4,4,4,4,0,0,  # 08 - 0f
+    4,4,4,4,4,4,4,4,  # 10 - 17
+    4,4,4,0,4,4,4,4,  # 18 - 1f
+    4,4,4,4,4,4,4,4,  # 20 - 27
+    4,4,4,4,4,4,4,4,  # 28 - 2f
+    4,3,3,3,3,3,3,3,  # 30 - 37
+    3,3,3,3,3,3,3,3,  # 38 - 3f
+    3,1,1,1,1,1,1,1,  # 40 - 47
+    1,1,1,1,1,1,1,1,  # 48 - 4f
+    1,1,1,1,1,1,1,1,  # 50 - 57
+    1,1,1,1,1,1,1,1,  # 58 - 5f
+    1,1,1,1,1,1,1,1,  # 60 - 67
+    1,1,1,1,1,1,1,1,  # 68 - 6f
+    1,1,1,1,1,1,1,1,  # 70 - 77
+    1,1,1,1,1,1,1,2,  # 78 - 7f
+    6,6,6,6,8,8,8,8,  # 80 - 87
+    8,8,8,8,8,8,8,8,  # 88 - 8f
+    8,7,7,7,7,7,7,7,  # 90 - 97
+    7,7,7,7,7,7,7,7,  # 98 - 9f
+    7,7,7,7,7,7,7,7,  # a0 - a7
+    7,7,7,7,7,7,7,7,  # a8 - af
+    7,7,7,7,7,7,7,7,  # b0 - b7
+    7,7,7,7,7,7,7,7,  # b8 - bf
+    7,7,7,7,7,7,7,7,  # c0 - c7
+    7,7,7,7,7,7,7,7,  # c8 - cf
+    7,7,7,7,5,5,5,5,  # d0 - d7
+    5,9,9,9,9,9,9,5,  # d8 - df
+    9,9,9,9,9,9,9,9,  # e0 - e7
+    9,9,9,9,9,9,9,9,  # e8 - ef
+    9,9,9,9,9,9,9,9,  # f0 - f7
+    9,9,5,5,5,5,5,0   # f8 - ff
+)
+
+JOHAB_ST = (
+# cls = 0                   1                   2                   3                   4                   5                   6                   7                   8                   9
+    MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.ERROR ,MachineState.ERROR ,3                  ,3                  ,4                  ,  # MachineState.START
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,  # MachineState.ITS_ME
+    MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,  # MachineState.ERROR
+    MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.ERROR ,MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,  # 3
+    MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,  # 4
+)
+# fmt: on
+
+JOHAB_CHAR_LEN_TABLE = (0, 1, 1, 1, 1, 0, 0, 2, 2, 2)
+
+JOHAB_SM_MODEL: CodingStateMachineDict = {
+    "class_table": JOHAB_CLS,
+    "class_factor": 10,
+    "state_table": JOHAB_ST,
+    "char_len_table": JOHAB_CHAR_LEN_TABLE,
+    "name": "Johab",
+}
+
+# EUC-TW
+# fmt: off
+EUCTW_CLS = (
+    2, 2, 2, 2, 2, 2, 2, 2,  # 00 - 07
+    2, 2, 2, 2, 2, 2, 0, 0,  # 08 - 0f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 10 - 17
+    2, 2, 2, 0, 2, 2, 2, 2,  # 18 - 1f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 20 - 27
+    2, 2, 2, 2, 2, 2, 2, 2,  # 28 - 2f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 30 - 37
+    2, 2, 2, 2, 2, 2, 2, 2,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 2,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 6, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 3, 4, 4, 4, 4, 4, 4,  # a0 - a7
+    5, 5, 1, 1, 1, 1, 1, 1,  # a8 - af
+    1, 1, 1, 1, 1, 1, 1, 1,  # b0 - b7
+    1, 1, 1, 1, 1, 1, 1, 1,  # b8 - bf
+    1, 1, 3, 1, 3, 3, 3, 3,  # c0 - c7
+    3, 3, 3, 3, 3, 3, 3, 3,  # c8 - cf
+    3, 3, 3, 3, 3, 3, 3, 3,  # d0 - d7
+    3, 3, 3, 3, 3, 3, 3, 3,  # d8 - df
+    3, 3, 3, 3, 3, 3, 3, 3,  # e0 - e7
+    3, 3, 3, 3, 3, 3, 3, 3,  # e8 - ef
+    3, 3, 3, 3, 3, 3, 3, 3,  # f0 - f7
+    3, 3, 3, 3, 3, 3, 3, 0   # f8 - ff
+)
+
+EUCTW_ST = (
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,     3,     3,     3,     4,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.START,MachineState.ERROR,#10-17
+    MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+         5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.START,MachineState.START,#20-27
+    MachineState.START,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START #28-2f
+)
+# fmt: on
+
+EUCTW_CHAR_LEN_TABLE = (0, 0, 1, 2, 2, 2, 3)
+
+EUCTW_SM_MODEL: CodingStateMachineDict = {
+    "class_table": EUCTW_CLS,
+    "class_factor": 7,
+    "state_table": EUCTW_ST,
+    "char_len_table": EUCTW_CHAR_LEN_TABLE,
+    "name": "x-euc-tw",
+}
+
+# GB2312
+# fmt: off
+GB2312_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    3, 3, 3, 3, 3, 3, 3, 3,  # 30 - 37
+    3, 3, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 4,  # 78 - 7f
+    5, 6, 6, 6, 6, 6, 6, 6,  # 80 - 87
+    6, 6, 6, 6, 6, 6, 6, 6,  # 88 - 8f
+    6, 6, 6, 6, 6, 6, 6, 6,  # 90 - 97
+    6, 6, 6, 6, 6, 6, 6, 6,  # 98 - 9f
+    6, 6, 6, 6, 6, 6, 6, 6,  # a0 - a7
+    6, 6, 6, 6, 6, 6, 6, 6,  # a8 - af
+    6, 6, 6, 6, 6, 6, 6, 6,  # b0 - b7
+    6, 6, 6, 6, 6, 6, 6, 6,  # b8 - bf
+    6, 6, 6, 6, 6, 6, 6, 6,  # c0 - c7
+    6, 6, 6, 6, 6, 6, 6, 6,  # c8 - cf
+    6, 6, 6, 6, 6, 6, 6, 6,  # d0 - d7
+    6, 6, 6, 6, 6, 6, 6, 6,  # d8 - df
+    6, 6, 6, 6, 6, 6, 6, 6,  # e0 - e7
+    6, 6, 6, 6, 6, 6, 6, 6,  # e8 - ef
+    6, 6, 6, 6, 6, 6, 6, 6,  # f0 - f7
+    6, 6, 6, 6, 6, 6, 6, 0   # f8 - ff
+)
+
+GB2312_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,     3,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,#10-17
+         4,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+    MachineState.ERROR,MachineState.ERROR,     5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ERROR,#20-27
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START #28-2f
+)
+# fmt: on
+
+# To be accurate, the length of class 6 can be either 2 or 4.
+# But it is not necessary to discriminate between the two since
+# it is used for frequency analysis only, and we are validating
+# each code range there as well. So it is safe to set it to be
+# 2 here.
+GB2312_CHAR_LEN_TABLE = (0, 1, 1, 1, 1, 1, 2)
+
+GB2312_SM_MODEL: CodingStateMachineDict = {
+    "class_table": GB2312_CLS,
+    "class_factor": 7,
+    "state_table": GB2312_ST,
+    "char_len_table": GB2312_CHAR_LEN_TABLE,
+    "name": "GB2312",
+}
+
+# Shift_JIS
+# fmt: off
+SJIS_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 1,  # 78 - 7f
+    3, 3, 3, 3, 3, 2, 2, 3,  # 80 - 87
+    3, 3, 3, 3, 3, 3, 3, 3,  # 88 - 8f
+    3, 3, 3, 3, 3, 3, 3, 3,  # 90 - 97
+    3, 3, 3, 3, 3, 3, 3, 3,  # 98 - 9f
+    #0xa0 is illegal in sjis encoding, but some pages does
+    #contain such byte. We need to be more error forgiven.
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    3, 3, 3, 3, 3, 3, 3, 3,  # e0 - e7
+    3, 3, 3, 3, 3, 4, 4, 4,  # e8 - ef
+    3, 3, 3, 3, 3, 3, 3, 3,  # f0 - f7
+    3, 3, 3, 3, 3, 0, 0, 0,  # f8 - ff
+)
+
+SJIS_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.START,     3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START #10-17
+)
+# fmt: on
+
+SJIS_CHAR_LEN_TABLE = (0, 1, 1, 2, 0, 0)
+
+SJIS_SM_MODEL: CodingStateMachineDict = {
+    "class_table": SJIS_CLS,
+    "class_factor": 6,
+    "state_table": SJIS_ST,
+    "char_len_table": SJIS_CHAR_LEN_TABLE,
+    "name": "Shift_JIS",
+}
+
+# UCS2-BE
+# fmt: off
+UCS2BE_CLS = (
+    0, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 1, 0, 0, 2, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 3, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 3, 3, 3, 3, 3, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 0, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 0, 0, 0, 0, 0, 0, 0,  # a0 - a7
+    0, 0, 0, 0, 0, 0, 0, 0,  # a8 - af
+    0, 0, 0, 0, 0, 0, 0, 0,  # b0 - b7
+    0, 0, 0, 0, 0, 0, 0, 0,  # b8 - bf
+    0, 0, 0, 0, 0, 0, 0, 0,  # c0 - c7
+    0, 0, 0, 0, 0, 0, 0, 0,  # c8 - cf
+    0, 0, 0, 0, 0, 0, 0, 0,  # d0 - d7
+    0, 0, 0, 0, 0, 0, 0, 0,  # d8 - df
+    0, 0, 0, 0, 0, 0, 0, 0,  # e0 - e7
+    0, 0, 0, 0, 0, 0, 0, 0,  # e8 - ef
+    0, 0, 0, 0, 0, 0, 0, 0,  # f0 - f7
+    0, 0, 0, 0, 0, 0, 4, 5   # f8 - ff
+)
+
+UCS2BE_ST  = (
+          5,     7,     7,MachineState.ERROR,     4,     3,MachineState.ERROR,MachineState.ERROR,#00-07
+     MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+     MachineState.ITS_ME,MachineState.ITS_ME,     6,     6,     6,     6,MachineState.ERROR,MachineState.ERROR,#10-17
+          6,     6,     6,     6,     6,MachineState.ITS_ME,     6,     6,#18-1f
+          6,     6,     6,     6,     5,     7,     7,MachineState.ERROR,#20-27
+          5,     8,     6,     6,MachineState.ERROR,     6,     6,     6,#28-2f
+          6,     6,     6,     6,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START #30-37
+)
+# fmt: on
+
+UCS2BE_CHAR_LEN_TABLE = (2, 2, 2, 0, 2, 2)
+
+UCS2BE_SM_MODEL: CodingStateMachineDict = {
+    "class_table": UCS2BE_CLS,
+    "class_factor": 6,
+    "state_table": UCS2BE_ST,
+    "char_len_table": UCS2BE_CHAR_LEN_TABLE,
+    "name": "UTF-16BE",
+}
+
+# UCS2-LE
+# fmt: off
+UCS2LE_CLS = (
+    0, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 1, 0, 0, 2, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 3, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 3, 3, 3, 3, 3, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 0, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 0, 0, 0, 0, 0, 0, 0,  # a0 - a7
+    0, 0, 0, 0, 0, 0, 0, 0,  # a8 - af
+    0, 0, 0, 0, 0, 0, 0, 0,  # b0 - b7
+    0, 0, 0, 0, 0, 0, 0, 0,  # b8 - bf
+    0, 0, 0, 0, 0, 0, 0, 0,  # c0 - c7
+    0, 0, 0, 0, 0, 0, 0, 0,  # c8 - cf
+    0, 0, 0, 0, 0, 0, 0, 0,  # d0 - d7
+    0, 0, 0, 0, 0, 0, 0, 0,  # d8 - df
+    0, 0, 0, 0, 0, 0, 0, 0,  # e0 - e7
+    0, 0, 0, 0, 0, 0, 0, 0,  # e8 - ef
+    0, 0, 0, 0, 0, 0, 0, 0,  # f0 - f7
+    0, 0, 0, 0, 0, 0, 4, 5   # f8 - ff
+)
+
+UCS2LE_ST = (
+          6,     6,     7,     6,     4,     3,MachineState.ERROR,MachineState.ERROR,#00-07
+     MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+     MachineState.ITS_ME,MachineState.ITS_ME,     5,     5,     5,MachineState.ERROR,MachineState.ITS_ME,MachineState.ERROR,#10-17
+          5,     5,     5,MachineState.ERROR,     5,MachineState.ERROR,     6,     6,#18-1f
+          7,     6,     8,     8,     5,     5,     5,MachineState.ERROR,#20-27
+          5,     5,     5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     5,     5,#28-2f
+          5,     5,     5,MachineState.ERROR,     5,MachineState.ERROR,MachineState.START,MachineState.START #30-37
+)
+# fmt: on
+
+UCS2LE_CHAR_LEN_TABLE = (2, 2, 2, 2, 2, 2)
+
+UCS2LE_SM_MODEL: CodingStateMachineDict = {
+    "class_table": UCS2LE_CLS,
+    "class_factor": 6,
+    "state_table": UCS2LE_ST,
+    "char_len_table": UCS2LE_CHAR_LEN_TABLE,
+    "name": "UTF-16LE",
+}
+
+# UTF-8
+# fmt: off
+UTF8_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07  #allow 0x00 as a legal value
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 40 - 47
+    1, 1, 1, 1, 1, 1, 1, 1,  # 48 - 4f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 50 - 57
+    1, 1, 1, 1, 1, 1, 1, 1,  # 58 - 5f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 60 - 67
+    1, 1, 1, 1, 1, 1, 1, 1,  # 68 - 6f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 70 - 77
+    1, 1, 1, 1, 1, 1, 1, 1,  # 78 - 7f
+    2, 2, 2, 2, 3, 3, 3, 3,  # 80 - 87
+    4, 4, 4, 4, 4, 4, 4, 4,  # 88 - 8f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 90 - 97
+    4, 4, 4, 4, 4, 4, 4, 4,  # 98 - 9f
+    5, 5, 5, 5, 5, 5, 5, 5,  # a0 - a7
+    5, 5, 5, 5, 5, 5, 5, 5,  # a8 - af
+    5, 5, 5, 5, 5, 5, 5, 5,  # b0 - b7
+    5, 5, 5, 5, 5, 5, 5, 5,  # b8 - bf
+    0, 0, 6, 6, 6, 6, 6, 6,  # c0 - c7
+    6, 6, 6, 6, 6, 6, 6, 6,  # c8 - cf
+    6, 6, 6, 6, 6, 6, 6, 6,  # d0 - d7
+    6, 6, 6, 6, 6, 6, 6, 6,  # d8 - df
+    7, 8, 8, 8, 8, 8, 8, 8,  # e0 - e7
+    8, 8, 8, 8, 8, 9, 8, 8,  # e8 - ef
+    10, 11, 11, 11, 11, 11, 11, 11,  # f0 - f7
+    12, 13, 13, 13, 14, 15, 0, 0    # f8 - ff
+)
+
+UTF8_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     12,   10,#00-07
+         9,     11,     8,     7,     6,     5,     4,    3,#08-0f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#10-17
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#20-27
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#28-2f
+    MachineState.ERROR,MachineState.ERROR,     5,     5,     5,     5,MachineState.ERROR,MachineState.ERROR,#30-37
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#38-3f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     5,     5,     5,MachineState.ERROR,MachineState.ERROR,#40-47
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#48-4f
+    MachineState.ERROR,MachineState.ERROR,     7,     7,     7,     7,MachineState.ERROR,MachineState.ERROR,#50-57
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#58-5f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     7,     7,MachineState.ERROR,MachineState.ERROR,#60-67
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#68-6f
+    MachineState.ERROR,MachineState.ERROR,     9,     9,     9,     9,MachineState.ERROR,MachineState.ERROR,#70-77
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#78-7f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     9,MachineState.ERROR,MachineState.ERROR,#80-87
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#88-8f
+    MachineState.ERROR,MachineState.ERROR,    12,    12,    12,    12,MachineState.ERROR,MachineState.ERROR,#90-97
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#98-9f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,    12,MachineState.ERROR,MachineState.ERROR,#a0-a7
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#a8-af
+    MachineState.ERROR,MachineState.ERROR,    12,    12,    12,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#b0-b7
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#b8-bf
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,#c0-c7
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR #c8-cf
+)
+# fmt: on
+
+UTF8_CHAR_LEN_TABLE = (0, 1, 0, 0, 0, 0, 2, 3, 3, 3, 4, 4, 5, 5, 6, 6)
+
+UTF8_SM_MODEL: CodingStateMachineDict = {
+    "class_table": UTF8_CLS,
+    "class_factor": 16,
+    "state_table": UTF8_ST,
+    "char_len_table": UTF8_CHAR_LEN_TABLE,
+    "name": "UTF-8",
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/metadata/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/metadata/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/metadata/languages.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/metadata/languages.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb40c5f0c8526208d434d762855d23079dc68b36
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/metadata/languages.py
@@ -0,0 +1,352 @@
+"""
+Metadata about languages used by our model training code for our
+SingleByteCharSetProbers.  Could be used for other things in the future.
+
+This code is based on the language metadata from the uchardet project.
+"""
+
+from string import ascii_letters
+from typing import List, Optional
+
+# TODO: Add Ukrainian (KOI8-U)
+
+
+class Language:
+    """Metadata about a language useful for training models
+
+    :ivar name: The human name for the language, in English.
+    :type name: str
+    :ivar iso_code: 2-letter ISO 639-1 if possible, 3-letter ISO code otherwise,
+                    or use another catalog as a last resort.
+    :type iso_code: str
+    :ivar use_ascii: Whether or not ASCII letters should be included in trained
+                     models.
+    :type use_ascii: bool
+    :ivar charsets: The charsets we want to support and create data for.
+    :type charsets: list of str
+    :ivar alphabet: The characters in the language's alphabet. If `use_ascii` is
+                    `True`, you only need to add those not in the ASCII set.
+    :type alphabet: str
+    :ivar wiki_start_pages: The Wikipedia pages to start from if we're crawling
+                            Wikipedia for training data.
+    :type wiki_start_pages: list of str
+    """
+
+    def __init__(
+        self,
+        name: Optional[str] = None,
+        iso_code: Optional[str] = None,
+        use_ascii: bool = True,
+        charsets: Optional[List[str]] = None,
+        alphabet: Optional[str] = None,
+        wiki_start_pages: Optional[List[str]] = None,
+    ) -> None:
+        super().__init__()
+        self.name = name
+        self.iso_code = iso_code
+        self.use_ascii = use_ascii
+        self.charsets = charsets
+        if self.use_ascii:
+            if alphabet:
+                alphabet += ascii_letters
+            else:
+                alphabet = ascii_letters
+        elif not alphabet:
+            raise ValueError("Must supply alphabet if use_ascii is False")
+        self.alphabet = "".join(sorted(set(alphabet))) if alphabet else None
+        self.wiki_start_pages = wiki_start_pages
+
+    def __repr__(self) -> str:
+        param_str = ", ".join(
+            f"{k}={v!r}" for k, v in self.__dict__.items() if not k.startswith("_")
+        )
+        return f"{self.__class__.__name__}({param_str})"
+
+
+LANGUAGES = {
+    "Arabic": Language(
+        name="Arabic",
+        iso_code="ar",
+        use_ascii=False,
+        # We only support encodings that use isolated
+        # forms, because the current recommendation is
+        # that the rendering system handles presentation
+        # forms. This means we purposefully skip IBM864.
+        charsets=["ISO-8859-6", "WINDOWS-1256", "CP720", "CP864"],
+        alphabet="ءآأؤإئابةتثجحخدذرزسشصضطظعغػؼؽؾؿـفقكلمنهوىيًٌٍَُِّ",
+        wiki_start_pages=["الصفحة_الرئيسية"],
+    ),
+    "Belarusian": Language(
+        name="Belarusian",
+        iso_code="be",
+        use_ascii=False,
+        charsets=["ISO-8859-5", "WINDOWS-1251", "IBM866", "MacCyrillic"],
+        alphabet="АБВГДЕЁЖЗІЙКЛМНОПРСТУЎФХЦЧШЫЬЭЮЯабвгдеёжзійклмнопрстуўфхцчшыьэюяʼ",
+        wiki_start_pages=["Галоўная_старонка"],
+    ),
+    "Bulgarian": Language(
+        name="Bulgarian",
+        iso_code="bg",
+        use_ascii=False,
+        charsets=["ISO-8859-5", "WINDOWS-1251", "IBM855"],
+        alphabet="АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЬЮЯабвгдежзийклмнопрстуфхцчшщъьюя",
+        wiki_start_pages=["Начална_страница"],
+    ),
+    "Czech": Language(
+        name="Czech",
+        iso_code="cz",
+        use_ascii=True,
+        charsets=["ISO-8859-2", "WINDOWS-1250"],
+        alphabet="áčďéěíňóřšťúůýžÁČĎÉĚÍŇÓŘŠŤÚŮÝŽ",
+        wiki_start_pages=["Hlavní_strana"],
+    ),
+    "Danish": Language(
+        name="Danish",
+        iso_code="da",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+        alphabet="æøåÆØÅ",
+        wiki_start_pages=["Forside"],
+    ),
+    "German": Language(
+        name="German",
+        iso_code="de",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+        alphabet="äöüßẞÄÖÜ",
+        wiki_start_pages=["Wikipedia:Hauptseite"],
+    ),
+    "Greek": Language(
+        name="Greek",
+        iso_code="el",
+        use_ascii=False,
+        charsets=["ISO-8859-7", "WINDOWS-1253"],
+        alphabet="αβγδεζηθικλμνξοπρσςτυφχψωάέήίόύώΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΣΤΥΦΧΨΩΆΈΉΊΌΎΏ",
+        wiki_start_pages=["Πύλη:Κύρια"],
+    ),
+    "English": Language(
+        name="English",
+        iso_code="en",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "WINDOWS-1252", "MacRoman"],
+        wiki_start_pages=["Main_Page"],
+    ),
+    "Esperanto": Language(
+        name="Esperanto",
+        iso_code="eo",
+        # Q, W, X, and Y not used at all
+        use_ascii=False,
+        charsets=["ISO-8859-3"],
+        alphabet="abcĉdefgĝhĥijĵklmnoprsŝtuŭvzABCĈDEFGĜHĤIJĴKLMNOPRSŜTUŬVZ",
+        wiki_start_pages=["Vikipedio:Ĉefpaĝo"],
+    ),
+    "Spanish": Language(
+        name="Spanish",
+        iso_code="es",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+        alphabet="ñáéíóúüÑÁÉÍÓÚÜ",
+        wiki_start_pages=["Wikipedia:Portada"],
+    ),
+    "Estonian": Language(
+        name="Estonian",
+        iso_code="et",
+        use_ascii=False,
+        charsets=["ISO-8859-4", "ISO-8859-13", "WINDOWS-1257"],
+        # C, F, Š, Q, W, X, Y, Z, Ž are only for
+        # loanwords
+        alphabet="ABDEGHIJKLMNOPRSTUVÕÄÖÜabdeghijklmnoprstuvõäöü",
+        wiki_start_pages=["Esileht"],
+    ),
+    "Finnish": Language(
+        name="Finnish",
+        iso_code="fi",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+        alphabet="ÅÄÖŠŽåäöšž",
+        wiki_start_pages=["Wikipedia:Etusivu"],
+    ),
+    "French": Language(
+        name="French",
+        iso_code="fr",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+        alphabet="œàâçèéîïùûêŒÀÂÇÈÉÎÏÙÛÊ",
+        wiki_start_pages=["Wikipédia:Accueil_principal", "Bœuf (animal)"],
+    ),
+    "Hebrew": Language(
+        name="Hebrew",
+        iso_code="he",
+        use_ascii=False,
+        charsets=["ISO-8859-8", "WINDOWS-1255"],
+        alphabet="אבגדהוזחטיךכלםמןנסעףפץצקרשתװױײ",
+        wiki_start_pages=["עמוד_ראשי"],
+    ),
+    "Croatian": Language(
+        name="Croatian",
+        iso_code="hr",
+        # Q, W, X, Y are only used for foreign words.
+        use_ascii=False,
+        charsets=["ISO-8859-2", "WINDOWS-1250"],
+        alphabet="abcčćdđefghijklmnoprsštuvzžABCČĆDĐEFGHIJKLMNOPRSŠTUVZŽ",
+        wiki_start_pages=["Glavna_stranica"],
+    ),
+    "Hungarian": Language(
+        name="Hungarian",
+        iso_code="hu",
+        # Q, W, X, Y are only used for foreign words.
+        use_ascii=False,
+        charsets=["ISO-8859-2", "WINDOWS-1250"],
+        alphabet="abcdefghijklmnoprstuvzáéíóöőúüűABCDEFGHIJKLMNOPRSTUVZÁÉÍÓÖŐÚÜŰ",
+        wiki_start_pages=["Kezdőlap"],
+    ),
+    "Italian": Language(
+        name="Italian",
+        iso_code="it",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+        alphabet="ÀÈÉÌÒÓÙàèéìòóù",
+        wiki_start_pages=["Pagina_principale"],
+    ),
+    "Lithuanian": Language(
+        name="Lithuanian",
+        iso_code="lt",
+        use_ascii=False,
+        charsets=["ISO-8859-13", "WINDOWS-1257", "ISO-8859-4"],
+        # Q, W, and X not used at all
+        alphabet="AĄBCČDEĘĖFGHIĮYJKLMNOPRSŠTUŲŪVZŽaąbcčdeęėfghiįyjklmnoprsštuųūvzž",
+        wiki_start_pages=["Pagrindinis_puslapis"],
+    ),
+    "Latvian": Language(
+        name="Latvian",
+        iso_code="lv",
+        use_ascii=False,
+        charsets=["ISO-8859-13", "WINDOWS-1257", "ISO-8859-4"],
+        # Q, W, X, Y are only for loanwords
+        alphabet="AĀBCČDEĒFGĢHIĪJKĶLĻMNŅOPRSŠTUŪVZŽaābcčdeēfgģhiījkķlļmnņoprsštuūvzž",
+        wiki_start_pages=["Sākumlapa"],
+    ),
+    "Macedonian": Language(
+        name="Macedonian",
+        iso_code="mk",
+        use_ascii=False,
+        charsets=["ISO-8859-5", "WINDOWS-1251", "MacCyrillic", "IBM855"],
+        alphabet="АБВГДЃЕЖЗЅИЈКЛЉМНЊОПРСТЌУФХЦЧЏШабвгдѓежзѕијклљмнњопрстќуфхцчџш",
+        wiki_start_pages=["Главна_страница"],
+    ),
+    "Dutch": Language(
+        name="Dutch",
+        iso_code="nl",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "WINDOWS-1252", "MacRoman"],
+        wiki_start_pages=["Hoofdpagina"],
+    ),
+    "Polish": Language(
+        name="Polish",
+        iso_code="pl",
+        # Q and X are only used for foreign words.
+        use_ascii=False,
+        charsets=["ISO-8859-2", "WINDOWS-1250"],
+        alphabet="AĄBCĆDEĘFGHIJKLŁMNŃOÓPRSŚTUWYZŹŻaąbcćdeęfghijklłmnńoóprsśtuwyzźż",
+        wiki_start_pages=["Wikipedia:Strona_główna"],
+    ),
+    "Portuguese": Language(
+        name="Portuguese",
+        iso_code="pt",
+        use_ascii=True,
+        charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+        alphabet="ÁÂÃÀÇÉÊÍÓÔÕÚáâãàçéêíóôõú",
+        wiki_start_pages=["Wikipédia:Página_principal"],
+    ),
+    "Romanian": Language(
+        name="Romanian",
+        iso_code="ro",
+        use_ascii=True,
+        charsets=["ISO-8859-2", "WINDOWS-1250"],
+        alphabet="ăâîșțĂÂÎȘȚ",
+        wiki_start_pages=["Pagina_principală"],
+    ),
+    "Russian": Language(
+        name="Russian",
+        iso_code="ru",
+        use_ascii=False,
+        charsets=[
+            "ISO-8859-5",
+            "WINDOWS-1251",
+            "KOI8-R",
+            "MacCyrillic",
+            "IBM866",
+            "IBM855",
+        ],
+        alphabet="абвгдеёжзийклмнопрстуфхцчшщъыьэюяАБВГДЕЁЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯ",
+        wiki_start_pages=["Заглавная_страница"],
+    ),
+    "Slovak": Language(
+        name="Slovak",
+        iso_code="sk",
+        use_ascii=True,
+        charsets=["ISO-8859-2", "WINDOWS-1250"],
+        alphabet="áäčďéíĺľňóôŕšťúýžÁÄČĎÉÍĹĽŇÓÔŔŠŤÚÝŽ",
+        wiki_start_pages=["Hlavná_stránka"],
+    ),
+    "Slovene": Language(
+        name="Slovene",
+        iso_code="sl",
+        # Q, W, X, Y are only used for foreign words.
+        use_ascii=False,
+        charsets=["ISO-8859-2", "WINDOWS-1250"],
+        alphabet="abcčdefghijklmnoprsštuvzžABCČDEFGHIJKLMNOPRSŠTUVZŽ",
+        wiki_start_pages=["Glavna_stran"],
+    ),
+    # Serbian can be written in both Latin and Cyrillic, but there's no
+    # simple way to get the Latin alphabet pages from Wikipedia through
+    # the API, so for now we just support Cyrillic.
+    "Serbian": Language(
+        name="Serbian",
+        iso_code="sr",
+        alphabet="АБВГДЂЕЖЗИЈКЛЉМНЊОПРСТЋУФХЦЧЏШабвгдђежзијклљмнњопрстћуфхцчџш",
+        charsets=["ISO-8859-5", "WINDOWS-1251", "MacCyrillic", "IBM855"],
+        wiki_start_pages=["Главна_страна"],
+    ),
+    "Thai": Language(
+        name="Thai",
+        iso_code="th",
+        use_ascii=False,
+        charsets=["ISO-8859-11", "TIS-620", "CP874"],
+        alphabet="กขฃคฅฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรฤลฦวศษสหฬอฮฯะัาำิีึืฺุู฿เแโใไๅๆ็่้๊๋์ํ๎๏๐๑๒๓๔๕๖๗๘๙๚๛",
+        wiki_start_pages=["หน้าหลัก"],
+    ),
+    "Turkish": Language(
+        name="Turkish",
+        iso_code="tr",
+        # Q, W, and X are not used by Turkish
+        use_ascii=False,
+        charsets=["ISO-8859-3", "ISO-8859-9", "WINDOWS-1254"],
+        alphabet="abcçdefgğhıijklmnoöprsştuüvyzâîûABCÇDEFGĞHIİJKLMNOÖPRSŞTUÜVYZÂÎÛ",
+        wiki_start_pages=["Ana_Sayfa"],
+    ),
+    "Vietnamese": Language(
+        name="Vietnamese",
+        iso_code="vi",
+        use_ascii=False,
+        # Windows-1258 is the only common 8-bit
+        # Vietnamese encoding supported by Python.
+        # From Wikipedia:
+        # For systems that lack support for Unicode,
+        # dozens of 8-bit Vietnamese code pages are
+        # available.[1] The most common are VISCII
+        # (TCVN 5712:1993), VPS, and Windows-1258.[3]
+        # Where ASCII is required, such as when
+        # ensuring readability in plain text e-mail,
+        # Vietnamese letters are often encoded
+        # according to Vietnamese Quoted-Readable
+        # (VIQR) or VSCII Mnemonic (VSCII-MNEM),[4]
+        # though usage of either variable-width
+        # scheme has declined dramatically following
+        # the adoption of Unicode on the World Wide
+        # Web.
+        charsets=["WINDOWS-1258"],
+        alphabet="aăâbcdđeêghiklmnoôơpqrstuưvxyAĂÂBCDĐEÊGHIKLMNOÔƠPQRSTUƯVXY",
+        wiki_start_pages=["Chữ_Quốc_ngữ"],
+    ),
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/resultdict.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/resultdict.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d36e64c467ca8d9cadc88ab03da71faf1aa8abb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/resultdict.py
@@ -0,0 +1,16 @@
+from typing import TYPE_CHECKING, Optional
+
+if TYPE_CHECKING:
+    # TypedDict was introduced in Python 3.8.
+    #
+    # TODO: Remove the else block and TYPE_CHECKING check when dropping support
+    # for Python 3.7.
+    from typing import TypedDict
+
+    class ResultDict(TypedDict):
+        encoding: Optional[str]
+        confidence: float
+        language: Optional[str]
+
+else:
+    ResultDict = dict
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sbcharsetprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sbcharsetprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..0ffbcdd2c3e21b68566c88a3f05239447489df84
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sbcharsetprober.py
@@ -0,0 +1,162 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Dict, List, NamedTuple, Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import CharacterCategory, ProbingState, SequenceLikelihood
+
+
+class SingleByteCharSetModel(NamedTuple):
+    charset_name: str
+    language: str
+    char_to_order_map: Dict[int, int]
+    language_model: Dict[int, Dict[int, int]]
+    typical_positive_ratio: float
+    keep_ascii_letters: bool
+    alphabet: str
+
+
+class SingleByteCharSetProber(CharSetProber):
+    SAMPLE_SIZE = 64
+    SB_ENOUGH_REL_THRESHOLD = 1024  # 0.25 * SAMPLE_SIZE^2
+    POSITIVE_SHORTCUT_THRESHOLD = 0.95
+    NEGATIVE_SHORTCUT_THRESHOLD = 0.05
+
+    def __init__(
+        self,
+        model: SingleByteCharSetModel,
+        is_reversed: bool = False,
+        name_prober: Optional[CharSetProber] = None,
+    ) -> None:
+        super().__init__()
+        self._model = model
+        # TRUE if we need to reverse every pair in the model lookup
+        self._reversed = is_reversed
+        # Optional auxiliary prober for name decision
+        self._name_prober = name_prober
+        self._last_order = 255
+        self._seq_counters: List[int] = []
+        self._total_seqs = 0
+        self._total_char = 0
+        self._control_char = 0
+        self._freq_char = 0
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        # char order of last character
+        self._last_order = 255
+        self._seq_counters = [0] * SequenceLikelihood.get_num_categories()
+        self._total_seqs = 0
+        self._total_char = 0
+        self._control_char = 0
+        # characters that fall in our sampling range
+        self._freq_char = 0
+
+    @property
+    def charset_name(self) -> Optional[str]:
+        if self._name_prober:
+            return self._name_prober.charset_name
+        return self._model.charset_name
+
+    @property
+    def language(self) -> Optional[str]:
+        if self._name_prober:
+            return self._name_prober.language
+        return self._model.language
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        # TODO: Make filter_international_words keep things in self.alphabet
+        if not self._model.keep_ascii_letters:
+            byte_str = self.filter_international_words(byte_str)
+        else:
+            byte_str = self.remove_xml_tags(byte_str)
+        if not byte_str:
+            return self.state
+        char_to_order_map = self._model.char_to_order_map
+        language_model = self._model.language_model
+        for char in byte_str:
+            order = char_to_order_map.get(char, CharacterCategory.UNDEFINED)
+            # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but
+            #      CharacterCategory.SYMBOL is actually 253, so we use CONTROL
+            #      to make it closer to the original intent. The only difference
+            #      is whether or not we count digits and control characters for
+            #      _total_char purposes.
+            if order < CharacterCategory.CONTROL:
+                self._total_char += 1
+            if order < self.SAMPLE_SIZE:
+                self._freq_char += 1
+                if self._last_order < self.SAMPLE_SIZE:
+                    self._total_seqs += 1
+                    if not self._reversed:
+                        lm_cat = language_model[self._last_order][order]
+                    else:
+                        lm_cat = language_model[order][self._last_order]
+                    self._seq_counters[lm_cat] += 1
+            self._last_order = order
+
+        charset_name = self._model.charset_name
+        if self.state == ProbingState.DETECTING:
+            if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD:
+                confidence = self.get_confidence()
+                if confidence > self.POSITIVE_SHORTCUT_THRESHOLD:
+                    self.logger.debug(
+                        "%s confidence = %s, we have a winner", charset_name, confidence
+                    )
+                    self._state = ProbingState.FOUND_IT
+                elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD:
+                    self.logger.debug(
+                        "%s confidence = %s, below negative shortcut threshold %s",
+                        charset_name,
+                        confidence,
+                        self.NEGATIVE_SHORTCUT_THRESHOLD,
+                    )
+                    self._state = ProbingState.NOT_ME
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        r = 0.01
+        if self._total_seqs > 0:
+            r = (
+                (
+                    self._seq_counters[SequenceLikelihood.POSITIVE]
+                    + 0.25 * self._seq_counters[SequenceLikelihood.LIKELY]
+                )
+                / self._total_seqs
+                / self._model.typical_positive_ratio
+            )
+            # The more control characters (proportionnaly to the size
+            # of the text), the less confident we become in the current
+            # charset.
+            r = r * (self._total_char - self._control_char) / self._total_char
+            r = r * self._freq_char / self._total_char
+            if r >= 1.0:
+                r = 0.99
+        return r
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sbcsgroupprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sbcsgroupprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..890ae8465c5b0ad2a5f99464fe5f5c0be49809f1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sbcsgroupprober.py
@@ -0,0 +1,88 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .charsetgroupprober import CharSetGroupProber
+from .hebrewprober import HebrewProber
+from .langbulgarianmodel import ISO_8859_5_BULGARIAN_MODEL, WINDOWS_1251_BULGARIAN_MODEL
+from .langgreekmodel import ISO_8859_7_GREEK_MODEL, WINDOWS_1253_GREEK_MODEL
+from .langhebrewmodel import WINDOWS_1255_HEBREW_MODEL
+
+# from .langhungarianmodel import (ISO_8859_2_HUNGARIAN_MODEL,
+#                                  WINDOWS_1250_HUNGARIAN_MODEL)
+from .langrussianmodel import (
+    IBM855_RUSSIAN_MODEL,
+    IBM866_RUSSIAN_MODEL,
+    ISO_8859_5_RUSSIAN_MODEL,
+    KOI8_R_RUSSIAN_MODEL,
+    MACCYRILLIC_RUSSIAN_MODEL,
+    WINDOWS_1251_RUSSIAN_MODEL,
+)
+from .langthaimodel import TIS_620_THAI_MODEL
+from .langturkishmodel import ISO_8859_9_TURKISH_MODEL
+from .sbcharsetprober import SingleByteCharSetProber
+
+
+class SBCSGroupProber(CharSetGroupProber):
+    def __init__(self) -> None:
+        super().__init__()
+        hebrew_prober = HebrewProber()
+        logical_hebrew_prober = SingleByteCharSetProber(
+            WINDOWS_1255_HEBREW_MODEL, is_reversed=False, name_prober=hebrew_prober
+        )
+        # TODO: See if using ISO-8859-8 Hebrew model works better here, since
+        #       it's actually the visual one
+        visual_hebrew_prober = SingleByteCharSetProber(
+            WINDOWS_1255_HEBREW_MODEL, is_reversed=True, name_prober=hebrew_prober
+        )
+        hebrew_prober.set_model_probers(logical_hebrew_prober, visual_hebrew_prober)
+        # TODO: ORDER MATTERS HERE. I changed the order vs what was in master
+        #       and several tests failed that did not before. Some thought
+        #       should be put into the ordering, and we should consider making
+        #       order not matter here, because that is very counter-intuitive.
+        self.probers = [
+            SingleByteCharSetProber(WINDOWS_1251_RUSSIAN_MODEL),
+            SingleByteCharSetProber(KOI8_R_RUSSIAN_MODEL),
+            SingleByteCharSetProber(ISO_8859_5_RUSSIAN_MODEL),
+            SingleByteCharSetProber(MACCYRILLIC_RUSSIAN_MODEL),
+            SingleByteCharSetProber(IBM866_RUSSIAN_MODEL),
+            SingleByteCharSetProber(IBM855_RUSSIAN_MODEL),
+            SingleByteCharSetProber(ISO_8859_7_GREEK_MODEL),
+            SingleByteCharSetProber(WINDOWS_1253_GREEK_MODEL),
+            SingleByteCharSetProber(ISO_8859_5_BULGARIAN_MODEL),
+            SingleByteCharSetProber(WINDOWS_1251_BULGARIAN_MODEL),
+            # TODO: Restore Hungarian encodings (iso-8859-2 and windows-1250)
+            #       after we retrain model.
+            # SingleByteCharSetProber(ISO_8859_2_HUNGARIAN_MODEL),
+            # SingleByteCharSetProber(WINDOWS_1250_HUNGARIAN_MODEL),
+            SingleByteCharSetProber(TIS_620_THAI_MODEL),
+            SingleByteCharSetProber(ISO_8859_9_TURKISH_MODEL),
+            hebrew_prober,
+            logical_hebrew_prober,
+            visual_hebrew_prober,
+        ]
+        self.reset()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sjisprober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sjisprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..91df077961b6310b8e1c708b74003d5343bff6a8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/sjisprober.py
@@ -0,0 +1,105 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Union
+
+from .chardistribution import SJISDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .enums import MachineState, ProbingState
+from .jpcntx import SJISContextAnalysis
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import SJIS_SM_MODEL
+
+
+class SJISProber(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(SJIS_SM_MODEL)
+        self.distribution_analyzer = SJISDistributionAnalysis()
+        self.context_analyzer = SJISContextAnalysis()
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        self.context_analyzer.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return self.context_analyzer.charset_name
+
+    @property
+    def language(self) -> str:
+        return "Japanese"
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        assert self.coding_sm is not None
+        assert self.distribution_analyzer is not None
+
+        for i, byte in enumerate(byte_str):
+            coding_state = self.coding_sm.next_state(byte)
+            if coding_state == MachineState.ERROR:
+                self.logger.debug(
+                    "%s %s prober hit error at byte %s",
+                    self.charset_name,
+                    self.language,
+                    i,
+                )
+                self._state = ProbingState.NOT_ME
+                break
+            if coding_state == MachineState.ITS_ME:
+                self._state = ProbingState.FOUND_IT
+                break
+            if coding_state == MachineState.START:
+                char_len = self.coding_sm.get_current_charlen()
+                if i == 0:
+                    self._last_char[1] = byte
+                    self.context_analyzer.feed(
+                        self._last_char[2 - char_len :], char_len
+                    )
+                    self.distribution_analyzer.feed(self._last_char, char_len)
+                else:
+                    self.context_analyzer.feed(
+                        byte_str[i + 1 - char_len : i + 3 - char_len], char_len
+                    )
+                    self.distribution_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+
+        self._last_char[0] = byte_str[-1]
+
+        if self.state == ProbingState.DETECTING:
+            if self.context_analyzer.got_enough_data() and (
+                self.get_confidence() > self.SHORTCUT_THRESHOLD
+            ):
+                self._state = ProbingState.FOUND_IT
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        assert self.distribution_analyzer is not None
+
+        context_conf = self.context_analyzer.get_confidence()
+        distrib_conf = self.distribution_analyzer.get_confidence()
+        return max(context_conf, distrib_conf)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/universaldetector.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/universaldetector.py
new file mode 100644
index 0000000000000000000000000000000000000000..30c441dc28ee327076a850b1d3c88a9a2c8f04f0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/universaldetector.py
@@ -0,0 +1,362 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+"""
+Module containing the UniversalDetector detector class, which is the primary
+class a user of ``chardet`` should use.
+
+:author: Mark Pilgrim (initial port to Python)
+:author: Shy Shalom (original C code)
+:author: Dan Blanchard (major refactoring for 3.0)
+:author: Ian Cordasco
+"""
+
+
+import codecs
+import logging
+import re
+from typing import List, Optional, Union
+
+from .charsetgroupprober import CharSetGroupProber
+from .charsetprober import CharSetProber
+from .enums import InputState, LanguageFilter, ProbingState
+from .escprober import EscCharSetProber
+from .latin1prober import Latin1Prober
+from .macromanprober import MacRomanProber
+from .mbcsgroupprober import MBCSGroupProber
+from .resultdict import ResultDict
+from .sbcsgroupprober import SBCSGroupProber
+from .utf1632prober import UTF1632Prober
+
+
+class UniversalDetector:
+    """
+    The ``UniversalDetector`` class underlies the ``chardet.detect`` function
+    and coordinates all of the different charset probers.
+
+    To get a ``dict`` containing an encoding and its confidence, you can simply
+    run:
+
+    .. code::
+
+            u = UniversalDetector()
+            u.feed(some_bytes)
+            u.close()
+            detected = u.result
+
+    """
+
+    MINIMUM_THRESHOLD = 0.20
+    HIGH_BYTE_DETECTOR = re.compile(b"[\x80-\xFF]")
+    ESC_DETECTOR = re.compile(b"(\033|~{)")
+    WIN_BYTE_DETECTOR = re.compile(b"[\x80-\x9F]")
+    ISO_WIN_MAP = {
+        "iso-8859-1": "Windows-1252",
+        "iso-8859-2": "Windows-1250",
+        "iso-8859-5": "Windows-1251",
+        "iso-8859-6": "Windows-1256",
+        "iso-8859-7": "Windows-1253",
+        "iso-8859-8": "Windows-1255",
+        "iso-8859-9": "Windows-1254",
+        "iso-8859-13": "Windows-1257",
+    }
+    # Based on https://encoding.spec.whatwg.org/#names-and-labels
+    # but altered to match Python names for encodings and remove mappings
+    # that break tests.
+    LEGACY_MAP = {
+        "ascii": "Windows-1252",
+        "iso-8859-1": "Windows-1252",
+        "tis-620": "ISO-8859-11",
+        "iso-8859-9": "Windows-1254",
+        "gb2312": "GB18030",
+        "euc-kr": "CP949",
+        "utf-16le": "UTF-16",
+    }
+
+    def __init__(
+        self,
+        lang_filter: LanguageFilter = LanguageFilter.ALL,
+        should_rename_legacy: bool = False,
+    ) -> None:
+        self._esc_charset_prober: Optional[EscCharSetProber] = None
+        self._utf1632_prober: Optional[UTF1632Prober] = None
+        self._charset_probers: List[CharSetProber] = []
+        self.result: ResultDict = {
+            "encoding": None,
+            "confidence": 0.0,
+            "language": None,
+        }
+        self.done = False
+        self._got_data = False
+        self._input_state = InputState.PURE_ASCII
+        self._last_char = b""
+        self.lang_filter = lang_filter
+        self.logger = logging.getLogger(__name__)
+        self._has_win_bytes = False
+        self.should_rename_legacy = should_rename_legacy
+        self.reset()
+
+    @property
+    def input_state(self) -> int:
+        return self._input_state
+
+    @property
+    def has_win_bytes(self) -> bool:
+        return self._has_win_bytes
+
+    @property
+    def charset_probers(self) -> List[CharSetProber]:
+        return self._charset_probers
+
+    def reset(self) -> None:
+        """
+        Reset the UniversalDetector and all of its probers back to their
+        initial states.  This is called by ``__init__``, so you only need to
+        call this directly in between analyses of different documents.
+        """
+        self.result = {"encoding": None, "confidence": 0.0, "language": None}
+        self.done = False
+        self._got_data = False
+        self._has_win_bytes = False
+        self._input_state = InputState.PURE_ASCII
+        self._last_char = b""
+        if self._esc_charset_prober:
+            self._esc_charset_prober.reset()
+        if self._utf1632_prober:
+            self._utf1632_prober.reset()
+        for prober in self._charset_probers:
+            prober.reset()
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> None:
+        """
+        Takes a chunk of a document and feeds it through all of the relevant
+        charset probers.
+
+        After calling ``feed``, you can check the value of the ``done``
+        attribute to see if you need to continue feeding the
+        ``UniversalDetector`` more data, or if it has made a prediction
+        (in the ``result`` attribute).
+
+        .. note::
+           You should always call ``close`` when you're done feeding in your
+           document if ``done`` is not already ``True``.
+        """
+        if self.done:
+            return
+
+        if not byte_str:
+            return
+
+        if not isinstance(byte_str, bytearray):
+            byte_str = bytearray(byte_str)
+
+        # First check for known BOMs, since these are guaranteed to be correct
+        if not self._got_data:
+            # If the data starts with BOM, we know it is UTF
+            if byte_str.startswith(codecs.BOM_UTF8):
+                # EF BB BF  UTF-8 with BOM
+                self.result = {
+                    "encoding": "UTF-8-SIG",
+                    "confidence": 1.0,
+                    "language": "",
+                }
+            elif byte_str.startswith((codecs.BOM_UTF32_LE, codecs.BOM_UTF32_BE)):
+                # FF FE 00 00  UTF-32, little-endian BOM
+                # 00 00 FE FF  UTF-32, big-endian BOM
+                self.result = {"encoding": "UTF-32", "confidence": 1.0, "language": ""}
+            elif byte_str.startswith(b"\xFE\xFF\x00\x00"):
+                # FE FF 00 00  UCS-4, unusual octet order BOM (3412)
+                self.result = {
+                    # TODO: This encoding is not supported by Python. Should remove?
+                    "encoding": "X-ISO-10646-UCS-4-3412",
+                    "confidence": 1.0,
+                    "language": "",
+                }
+            elif byte_str.startswith(b"\x00\x00\xFF\xFE"):
+                # 00 00 FF FE  UCS-4, unusual octet order BOM (2143)
+                self.result = {
+                    # TODO: This encoding is not supported by Python. Should remove?
+                    "encoding": "X-ISO-10646-UCS-4-2143",
+                    "confidence": 1.0,
+                    "language": "",
+                }
+            elif byte_str.startswith((codecs.BOM_LE, codecs.BOM_BE)):
+                # FF FE  UTF-16, little endian BOM
+                # FE FF  UTF-16, big endian BOM
+                self.result = {"encoding": "UTF-16", "confidence": 1.0, "language": ""}
+
+            self._got_data = True
+            if self.result["encoding"] is not None:
+                self.done = True
+                return
+
+        # If none of those matched and we've only see ASCII so far, check
+        # for high bytes and escape sequences
+        if self._input_state == InputState.PURE_ASCII:
+            if self.HIGH_BYTE_DETECTOR.search(byte_str):
+                self._input_state = InputState.HIGH_BYTE
+            elif (
+                self._input_state == InputState.PURE_ASCII
+                and self.ESC_DETECTOR.search(self._last_char + byte_str)
+            ):
+                self._input_state = InputState.ESC_ASCII
+
+        self._last_char = byte_str[-1:]
+
+        # next we will look to see if it is appears to be either a UTF-16 or
+        # UTF-32 encoding
+        if not self._utf1632_prober:
+            self._utf1632_prober = UTF1632Prober()
+
+        if self._utf1632_prober.state == ProbingState.DETECTING:
+            if self._utf1632_prober.feed(byte_str) == ProbingState.FOUND_IT:
+                self.result = {
+                    "encoding": self._utf1632_prober.charset_name,
+                    "confidence": self._utf1632_prober.get_confidence(),
+                    "language": "",
+                }
+                self.done = True
+                return
+
+        # If we've seen escape sequences, use the EscCharSetProber, which
+        # uses a simple state machine to check for known escape sequences in
+        # HZ and ISO-2022 encodings, since those are the only encodings that
+        # use such sequences.
+        if self._input_state == InputState.ESC_ASCII:
+            if not self._esc_charset_prober:
+                self._esc_charset_prober = EscCharSetProber(self.lang_filter)
+            if self._esc_charset_prober.feed(byte_str) == ProbingState.FOUND_IT:
+                self.result = {
+                    "encoding": self._esc_charset_prober.charset_name,
+                    "confidence": self._esc_charset_prober.get_confidence(),
+                    "language": self._esc_charset_prober.language,
+                }
+                self.done = True
+        # If we've seen high bytes (i.e., those with values greater than 127),
+        # we need to do more complicated checks using all our multi-byte and
+        # single-byte probers that are left.  The single-byte probers
+        # use character bigram distributions to determine the encoding, whereas
+        # the multi-byte probers use a combination of character unigram and
+        # bigram distributions.
+        elif self._input_state == InputState.HIGH_BYTE:
+            if not self._charset_probers:
+                self._charset_probers = [MBCSGroupProber(self.lang_filter)]
+                # If we're checking non-CJK encodings, use single-byte prober
+                if self.lang_filter & LanguageFilter.NON_CJK:
+                    self._charset_probers.append(SBCSGroupProber())
+                self._charset_probers.append(Latin1Prober())
+                self._charset_probers.append(MacRomanProber())
+            for prober in self._charset_probers:
+                if prober.feed(byte_str) == ProbingState.FOUND_IT:
+                    self.result = {
+                        "encoding": prober.charset_name,
+                        "confidence": prober.get_confidence(),
+                        "language": prober.language,
+                    }
+                    self.done = True
+                    break
+            if self.WIN_BYTE_DETECTOR.search(byte_str):
+                self._has_win_bytes = True
+
+    def close(self) -> ResultDict:
+        """
+        Stop analyzing the current document and come up with a final
+        prediction.
+
+        :returns:  The ``result`` attribute, a ``dict`` with the keys
+                   `encoding`, `confidence`, and `language`.
+        """
+        # Don't bother with checks if we're already done
+        if self.done:
+            return self.result
+        self.done = True
+
+        if not self._got_data:
+            self.logger.debug("no data received!")
+
+        # Default to ASCII if it is all we've seen so far
+        elif self._input_state == InputState.PURE_ASCII:
+            self.result = {"encoding": "ascii", "confidence": 1.0, "language": ""}
+
+        # If we have seen non-ASCII, return the best that met MINIMUM_THRESHOLD
+        elif self._input_state == InputState.HIGH_BYTE:
+            prober_confidence = None
+            max_prober_confidence = 0.0
+            max_prober = None
+            for prober in self._charset_probers:
+                if not prober:
+                    continue
+                prober_confidence = prober.get_confidence()
+                if prober_confidence > max_prober_confidence:
+                    max_prober_confidence = prober_confidence
+                    max_prober = prober
+            if max_prober and (max_prober_confidence > self.MINIMUM_THRESHOLD):
+                charset_name = max_prober.charset_name
+                assert charset_name is not None
+                lower_charset_name = charset_name.lower()
+                confidence = max_prober.get_confidence()
+                # Use Windows encoding name instead of ISO-8859 if we saw any
+                # extra Windows-specific bytes
+                if lower_charset_name.startswith("iso-8859"):
+                    if self._has_win_bytes:
+                        charset_name = self.ISO_WIN_MAP.get(
+                            lower_charset_name, charset_name
+                        )
+                # Rename legacy encodings with superset encodings if asked
+                if self.should_rename_legacy:
+                    charset_name = self.LEGACY_MAP.get(
+                        (charset_name or "").lower(), charset_name
+                    )
+                self.result = {
+                    "encoding": charset_name,
+                    "confidence": confidence,
+                    "language": max_prober.language,
+                }
+
+        # Log all prober confidences if none met MINIMUM_THRESHOLD
+        if self.logger.getEffectiveLevel() <= logging.DEBUG:
+            if self.result["encoding"] is None:
+                self.logger.debug("no probers hit minimum threshold")
+                for group_prober in self._charset_probers:
+                    if not group_prober:
+                        continue
+                    if isinstance(group_prober, CharSetGroupProber):
+                        for prober in group_prober.probers:
+                            self.logger.debug(
+                                "%s %s confidence = %s",
+                                prober.charset_name,
+                                prober.language,
+                                prober.get_confidence(),
+                            )
+                    else:
+                        self.logger.debug(
+                            "%s %s confidence = %s",
+                            group_prober.charset_name,
+                            group_prober.language,
+                            group_prober.get_confidence(),
+                        )
+        return self.result
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/utf1632prober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/utf1632prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..6bdec63d6867928bf73a7e513f60cee8f49ca050
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/utf1632prober.py
@@ -0,0 +1,225 @@
+######################## BEGIN LICENSE BLOCK ########################
+#
+# Contributor(s):
+#   Jason Zavaglia
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+from typing import List, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+
+
+class UTF1632Prober(CharSetProber):
+    """
+    This class simply looks for occurrences of zero bytes, and infers
+    whether the file is UTF16 or UTF32 (low-endian or big-endian)
+    For instance, files looking like ( \0 \0 \0 [nonzero] )+
+    have a good probability to be UTF32BE.  Files looking like ( \0 [nonzero] )+
+    may be guessed to be UTF16BE, and inversely for little-endian varieties.
+    """
+
+    # how many logical characters to scan before feeling confident of prediction
+    MIN_CHARS_FOR_DETECTION = 20
+    # a fixed constant ratio of expected zeros or non-zeros in modulo-position.
+    EXPECTED_RATIO = 0.94
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.position = 0
+        self.zeros_at_mod = [0] * 4
+        self.nonzeros_at_mod = [0] * 4
+        self._state = ProbingState.DETECTING
+        self.quad = [0, 0, 0, 0]
+        self.invalid_utf16be = False
+        self.invalid_utf16le = False
+        self.invalid_utf32be = False
+        self.invalid_utf32le = False
+        self.first_half_surrogate_pair_detected_16be = False
+        self.first_half_surrogate_pair_detected_16le = False
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        self.position = 0
+        self.zeros_at_mod = [0] * 4
+        self.nonzeros_at_mod = [0] * 4
+        self._state = ProbingState.DETECTING
+        self.invalid_utf16be = False
+        self.invalid_utf16le = False
+        self.invalid_utf32be = False
+        self.invalid_utf32le = False
+        self.first_half_surrogate_pair_detected_16be = False
+        self.first_half_surrogate_pair_detected_16le = False
+        self.quad = [0, 0, 0, 0]
+
+    @property
+    def charset_name(self) -> str:
+        if self.is_likely_utf32be():
+            return "utf-32be"
+        if self.is_likely_utf32le():
+            return "utf-32le"
+        if self.is_likely_utf16be():
+            return "utf-16be"
+        if self.is_likely_utf16le():
+            return "utf-16le"
+        # default to something valid
+        return "utf-16"
+
+    @property
+    def language(self) -> str:
+        return ""
+
+    def approx_32bit_chars(self) -> float:
+        return max(1.0, self.position / 4.0)
+
+    def approx_16bit_chars(self) -> float:
+        return max(1.0, self.position / 2.0)
+
+    def is_likely_utf32be(self) -> bool:
+        approx_chars = self.approx_32bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            self.zeros_at_mod[0] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[1] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[2] / approx_chars > self.EXPECTED_RATIO
+            and self.nonzeros_at_mod[3] / approx_chars > self.EXPECTED_RATIO
+            and not self.invalid_utf32be
+        )
+
+    def is_likely_utf32le(self) -> bool:
+        approx_chars = self.approx_32bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            self.nonzeros_at_mod[0] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[1] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[2] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[3] / approx_chars > self.EXPECTED_RATIO
+            and not self.invalid_utf32le
+        )
+
+    def is_likely_utf16be(self) -> bool:
+        approx_chars = self.approx_16bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            (self.nonzeros_at_mod[1] + self.nonzeros_at_mod[3]) / approx_chars
+            > self.EXPECTED_RATIO
+            and (self.zeros_at_mod[0] + self.zeros_at_mod[2]) / approx_chars
+            > self.EXPECTED_RATIO
+            and not self.invalid_utf16be
+        )
+
+    def is_likely_utf16le(self) -> bool:
+        approx_chars = self.approx_16bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            (self.nonzeros_at_mod[0] + self.nonzeros_at_mod[2]) / approx_chars
+            > self.EXPECTED_RATIO
+            and (self.zeros_at_mod[1] + self.zeros_at_mod[3]) / approx_chars
+            > self.EXPECTED_RATIO
+            and not self.invalid_utf16le
+        )
+
+    def validate_utf32_characters(self, quad: List[int]) -> None:
+        """
+        Validate if the quad of bytes is valid UTF-32.
+
+        UTF-32 is valid in the range 0x00000000 - 0x0010FFFF
+        excluding 0x0000D800 - 0x0000DFFF
+
+        https://en.wikipedia.org/wiki/UTF-32
+        """
+        if (
+            quad[0] != 0
+            or quad[1] > 0x10
+            or (quad[0] == 0 and quad[1] == 0 and 0xD8 <= quad[2] <= 0xDF)
+        ):
+            self.invalid_utf32be = True
+        if (
+            quad[3] != 0
+            or quad[2] > 0x10
+            or (quad[3] == 0 and quad[2] == 0 and 0xD8 <= quad[1] <= 0xDF)
+        ):
+            self.invalid_utf32le = True
+
+    def validate_utf16_characters(self, pair: List[int]) -> None:
+        """
+        Validate if the pair of bytes is  valid UTF-16.
+
+        UTF-16 is valid in the range 0x0000 - 0xFFFF excluding 0xD800 - 0xFFFF
+        with an exception for surrogate pairs, which must be in the range
+        0xD800-0xDBFF followed by 0xDC00-0xDFFF
+
+        https://en.wikipedia.org/wiki/UTF-16
+        """
+        if not self.first_half_surrogate_pair_detected_16be:
+            if 0xD8 <= pair[0] <= 0xDB:
+                self.first_half_surrogate_pair_detected_16be = True
+            elif 0xDC <= pair[0] <= 0xDF:
+                self.invalid_utf16be = True
+        else:
+            if 0xDC <= pair[0] <= 0xDF:
+                self.first_half_surrogate_pair_detected_16be = False
+            else:
+                self.invalid_utf16be = True
+
+        if not self.first_half_surrogate_pair_detected_16le:
+            if 0xD8 <= pair[1] <= 0xDB:
+                self.first_half_surrogate_pair_detected_16le = True
+            elif 0xDC <= pair[1] <= 0xDF:
+                self.invalid_utf16le = True
+        else:
+            if 0xDC <= pair[1] <= 0xDF:
+                self.first_half_surrogate_pair_detected_16le = False
+            else:
+                self.invalid_utf16le = True
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for c in byte_str:
+            mod4 = self.position % 4
+            self.quad[mod4] = c
+            if mod4 == 3:
+                self.validate_utf32_characters(self.quad)
+                self.validate_utf16_characters(self.quad[0:2])
+                self.validate_utf16_characters(self.quad[2:4])
+            if c == 0:
+                self.zeros_at_mod[mod4] += 1
+            else:
+                self.nonzeros_at_mod[mod4] += 1
+            self.position += 1
+        return self.state
+
+    @property
+    def state(self) -> ProbingState:
+        if self._state in {ProbingState.NOT_ME, ProbingState.FOUND_IT}:
+            # terminal, decided states
+            return self._state
+        if self.get_confidence() > 0.80:
+            self._state = ProbingState.FOUND_IT
+        elif self.position > 4 * 1024:
+            # if we get to 4kb into the file, and we can't conclude it's UTF,
+            # let's give up
+            self._state = ProbingState.NOT_ME
+        return self._state
+
+    def get_confidence(self) -> float:
+        return (
+            0.85
+            if (
+                self.is_likely_utf16le()
+                or self.is_likely_utf16be()
+                or self.is_likely_utf32le()
+                or self.is_likely_utf32be()
+            )
+            else 0.00
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/utf8prober.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/utf8prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..d96354d97c2195320d0acc1717a5876eafbea2af
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/utf8prober.py
@@ -0,0 +1,82 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Union
+
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import MachineState, ProbingState
+from .mbcssm import UTF8_SM_MODEL
+
+
+class UTF8Prober(CharSetProber):
+    ONE_CHAR_PROB = 0.5
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(UTF8_SM_MODEL)
+        self._num_mb_chars = 0
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        self.coding_sm.reset()
+        self._num_mb_chars = 0
+
+    @property
+    def charset_name(self) -> str:
+        return "utf-8"
+
+    @property
+    def language(self) -> str:
+        return ""
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for c in byte_str:
+            coding_state = self.coding_sm.next_state(c)
+            if coding_state == MachineState.ERROR:
+                self._state = ProbingState.NOT_ME
+                break
+            if coding_state == MachineState.ITS_ME:
+                self._state = ProbingState.FOUND_IT
+                break
+            if coding_state == MachineState.START:
+                if self.coding_sm.get_current_charlen() >= 2:
+                    self._num_mb_chars += 1
+
+        if self.state == ProbingState.DETECTING:
+            if self.get_confidence() > self.SHORTCUT_THRESHOLD:
+                self._state = ProbingState.FOUND_IT
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        unlike = 0.99
+        if self._num_mb_chars < 6:
+            unlike *= self.ONE_CHAR_PROB**self._num_mb_chars
+            return 1.0 - unlike
+        return unlike
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/version.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..c5e9d85cd75884b129d4ab8d0453c0e50d0c1f68
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/chardet/version.py
@@ -0,0 +1,9 @@
+"""
+This module exists only to simplify retrieving the version number of chardet
+from within setuptools and from chardet subpackages.
+
+:author: Dan Blanchard (dan.blanchard@gmail.com)
+"""
+
+__version__ = "5.1.0"
+VERSION = __version__.split(".")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..383101cdb38706c305449674044e9288b92b7d75
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/__init__.py
@@ -0,0 +1,7 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+from .initialise import init, deinit, reinit, colorama_text, just_fix_windows_console
+from .ansi import Fore, Back, Style, Cursor
+from .ansitowin32 import AnsiToWin32
+
+__version__ = '0.4.6'
+
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/ansi.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/ansi.py
new file mode 100644
index 0000000000000000000000000000000000000000..11ec695ff79627463a0282d25079527562de9e42
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/ansi.py
@@ -0,0 +1,102 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+'''
+This module generates ANSI character codes to printing colors to terminals.
+See: http://en.wikipedia.org/wiki/ANSI_escape_code
+'''
+
+CSI = '\033['
+OSC = '\033]'
+BEL = '\a'
+
+
+def code_to_chars(code):
+    return CSI + str(code) + 'm'
+
+def set_title(title):
+    return OSC + '2;' + title + BEL
+
+def clear_screen(mode=2):
+    return CSI + str(mode) + 'J'
+
+def clear_line(mode=2):
+    return CSI + str(mode) + 'K'
+
+
+class AnsiCodes(object):
+    def __init__(self):
+        # the subclasses declare class attributes which are numbers.
+        # Upon instantiation we define instance attributes, which are the same
+        # as the class attributes but wrapped with the ANSI escape sequence
+        for name in dir(self):
+            if not name.startswith('_'):
+                value = getattr(self, name)
+                setattr(self, name, code_to_chars(value))
+
+
+class AnsiCursor(object):
+    def UP(self, n=1):
+        return CSI + str(n) + 'A'
+    def DOWN(self, n=1):
+        return CSI + str(n) + 'B'
+    def FORWARD(self, n=1):
+        return CSI + str(n) + 'C'
+    def BACK(self, n=1):
+        return CSI + str(n) + 'D'
+    def POS(self, x=1, y=1):
+        return CSI + str(y) + ';' + str(x) + 'H'
+
+
+class AnsiFore(AnsiCodes):
+    BLACK           = 30
+    RED             = 31
+    GREEN           = 32
+    YELLOW          = 33
+    BLUE            = 34
+    MAGENTA         = 35
+    CYAN            = 36
+    WHITE           = 37
+    RESET           = 39
+
+    # These are fairly well supported, but not part of the standard.
+    LIGHTBLACK_EX   = 90
+    LIGHTRED_EX     = 91
+    LIGHTGREEN_EX   = 92
+    LIGHTYELLOW_EX  = 93
+    LIGHTBLUE_EX    = 94
+    LIGHTMAGENTA_EX = 95
+    LIGHTCYAN_EX    = 96
+    LIGHTWHITE_EX   = 97
+
+
+class AnsiBack(AnsiCodes):
+    BLACK           = 40
+    RED             = 41
+    GREEN           = 42
+    YELLOW          = 43
+    BLUE            = 44
+    MAGENTA         = 45
+    CYAN            = 46
+    WHITE           = 47
+    RESET           = 49
+
+    # These are fairly well supported, but not part of the standard.
+    LIGHTBLACK_EX   = 100
+    LIGHTRED_EX     = 101
+    LIGHTGREEN_EX   = 102
+    LIGHTYELLOW_EX  = 103
+    LIGHTBLUE_EX    = 104
+    LIGHTMAGENTA_EX = 105
+    LIGHTCYAN_EX    = 106
+    LIGHTWHITE_EX   = 107
+
+
+class AnsiStyle(AnsiCodes):
+    BRIGHT    = 1
+    DIM       = 2
+    NORMAL    = 22
+    RESET_ALL = 0
+
+Fore   = AnsiFore()
+Back   = AnsiBack()
+Style  = AnsiStyle()
+Cursor = AnsiCursor()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/ansitowin32.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/ansitowin32.py
new file mode 100644
index 0000000000000000000000000000000000000000..abf209e60c7c4a9b1ae57452e36b383969848c2e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/ansitowin32.py
@@ -0,0 +1,277 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+import re
+import sys
+import os
+
+from .ansi import AnsiFore, AnsiBack, AnsiStyle, Style, BEL
+from .winterm import enable_vt_processing, WinTerm, WinColor, WinStyle
+from .win32 import windll, winapi_test
+
+
+winterm = None
+if windll is not None:
+    winterm = WinTerm()
+
+
+class StreamWrapper(object):
+    '''
+    Wraps a stream (such as stdout), acting as a transparent proxy for all
+    attribute access apart from method 'write()', which is delegated to our
+    Converter instance.
+    '''
+    def __init__(self, wrapped, converter):
+        # double-underscore everything to prevent clashes with names of
+        # attributes on the wrapped stream object.
+        self.__wrapped = wrapped
+        self.__convertor = converter
+
+    def __getattr__(self, name):
+        return getattr(self.__wrapped, name)
+
+    def __enter__(self, *args, **kwargs):
+        # special method lookup bypasses __getattr__/__getattribute__, see
+        # https://stackoverflow.com/questions/12632894/why-doesnt-getattr-work-with-exit
+        # thus, contextlib magic methods are not proxied via __getattr__
+        return self.__wrapped.__enter__(*args, **kwargs)
+
+    def __exit__(self, *args, **kwargs):
+        return self.__wrapped.__exit__(*args, **kwargs)
+
+    def __setstate__(self, state):
+        self.__dict__ = state
+
+    def __getstate__(self):
+        return self.__dict__
+
+    def write(self, text):
+        self.__convertor.write(text)
+
+    def isatty(self):
+        stream = self.__wrapped
+        if 'PYCHARM_HOSTED' in os.environ:
+            if stream is not None and (stream is sys.__stdout__ or stream is sys.__stderr__):
+                return True
+        try:
+            stream_isatty = stream.isatty
+        except AttributeError:
+            return False
+        else:
+            return stream_isatty()
+
+    @property
+    def closed(self):
+        stream = self.__wrapped
+        try:
+            return stream.closed
+        # AttributeError in the case that the stream doesn't support being closed
+        # ValueError for the case that the stream has already been detached when atexit runs
+        except (AttributeError, ValueError):
+            return True
+
+
+class AnsiToWin32(object):
+    '''
+    Implements a 'write()' method which, on Windows, will strip ANSI character
+    sequences from the text, and if outputting to a tty, will convert them into
+    win32 function calls.
+    '''
+    ANSI_CSI_RE = re.compile('\001?\033\\[((?:\\d|;)*)([a-zA-Z])\002?')   # Control Sequence Introducer
+    ANSI_OSC_RE = re.compile('\001?\033\\]([^\a]*)(\a)\002?')             # Operating System Command
+
+    def __init__(self, wrapped, convert=None, strip=None, autoreset=False):
+        # The wrapped stream (normally sys.stdout or sys.stderr)
+        self.wrapped = wrapped
+
+        # should we reset colors to defaults after every .write()
+        self.autoreset = autoreset
+
+        # create the proxy wrapping our output stream
+        self.stream = StreamWrapper(wrapped, self)
+
+        on_windows = os.name == 'nt'
+        # We test if the WinAPI works, because even if we are on Windows
+        # we may be using a terminal that doesn't support the WinAPI
+        # (e.g. Cygwin Terminal). In this case it's up to the terminal
+        # to support the ANSI codes.
+        conversion_supported = on_windows and winapi_test()
+        try:
+            fd = wrapped.fileno()
+        except Exception:
+            fd = -1
+        system_has_native_ansi = not on_windows or enable_vt_processing(fd)
+        have_tty = not self.stream.closed and self.stream.isatty()
+        need_conversion = conversion_supported and not system_has_native_ansi
+
+        # should we strip ANSI sequences from our output?
+        if strip is None:
+            strip = need_conversion or not have_tty
+        self.strip = strip
+
+        # should we should convert ANSI sequences into win32 calls?
+        if convert is None:
+            convert = need_conversion and have_tty
+        self.convert = convert
+
+        # dict of ansi codes to win32 functions and parameters
+        self.win32_calls = self.get_win32_calls()
+
+        # are we wrapping stderr?
+        self.on_stderr = self.wrapped is sys.stderr
+
+    def should_wrap(self):
+        '''
+        True if this class is actually needed. If false, then the output
+        stream will not be affected, nor will win32 calls be issued, so
+        wrapping stdout is not actually required. This will generally be
+        False on non-Windows platforms, unless optional functionality like
+        autoreset has been requested using kwargs to init()
+        '''
+        return self.convert or self.strip or self.autoreset
+
+    def get_win32_calls(self):
+        if self.convert and winterm:
+            return {
+                AnsiStyle.RESET_ALL: (winterm.reset_all, ),
+                AnsiStyle.BRIGHT: (winterm.style, WinStyle.BRIGHT),
+                AnsiStyle.DIM: (winterm.style, WinStyle.NORMAL),
+                AnsiStyle.NORMAL: (winterm.style, WinStyle.NORMAL),
+                AnsiFore.BLACK: (winterm.fore, WinColor.BLACK),
+                AnsiFore.RED: (winterm.fore, WinColor.RED),
+                AnsiFore.GREEN: (winterm.fore, WinColor.GREEN),
+                AnsiFore.YELLOW: (winterm.fore, WinColor.YELLOW),
+                AnsiFore.BLUE: (winterm.fore, WinColor.BLUE),
+                AnsiFore.MAGENTA: (winterm.fore, WinColor.MAGENTA),
+                AnsiFore.CYAN: (winterm.fore, WinColor.CYAN),
+                AnsiFore.WHITE: (winterm.fore, WinColor.GREY),
+                AnsiFore.RESET: (winterm.fore, ),
+                AnsiFore.LIGHTBLACK_EX: (winterm.fore, WinColor.BLACK, True),
+                AnsiFore.LIGHTRED_EX: (winterm.fore, WinColor.RED, True),
+                AnsiFore.LIGHTGREEN_EX: (winterm.fore, WinColor.GREEN, True),
+                AnsiFore.LIGHTYELLOW_EX: (winterm.fore, WinColor.YELLOW, True),
+                AnsiFore.LIGHTBLUE_EX: (winterm.fore, WinColor.BLUE, True),
+                AnsiFore.LIGHTMAGENTA_EX: (winterm.fore, WinColor.MAGENTA, True),
+                AnsiFore.LIGHTCYAN_EX: (winterm.fore, WinColor.CYAN, True),
+                AnsiFore.LIGHTWHITE_EX: (winterm.fore, WinColor.GREY, True),
+                AnsiBack.BLACK: (winterm.back, WinColor.BLACK),
+                AnsiBack.RED: (winterm.back, WinColor.RED),
+                AnsiBack.GREEN: (winterm.back, WinColor.GREEN),
+                AnsiBack.YELLOW: (winterm.back, WinColor.YELLOW),
+                AnsiBack.BLUE: (winterm.back, WinColor.BLUE),
+                AnsiBack.MAGENTA: (winterm.back, WinColor.MAGENTA),
+                AnsiBack.CYAN: (winterm.back, WinColor.CYAN),
+                AnsiBack.WHITE: (winterm.back, WinColor.GREY),
+                AnsiBack.RESET: (winterm.back, ),
+                AnsiBack.LIGHTBLACK_EX: (winterm.back, WinColor.BLACK, True),
+                AnsiBack.LIGHTRED_EX: (winterm.back, WinColor.RED, True),
+                AnsiBack.LIGHTGREEN_EX: (winterm.back, WinColor.GREEN, True),
+                AnsiBack.LIGHTYELLOW_EX: (winterm.back, WinColor.YELLOW, True),
+                AnsiBack.LIGHTBLUE_EX: (winterm.back, WinColor.BLUE, True),
+                AnsiBack.LIGHTMAGENTA_EX: (winterm.back, WinColor.MAGENTA, True),
+                AnsiBack.LIGHTCYAN_EX: (winterm.back, WinColor.CYAN, True),
+                AnsiBack.LIGHTWHITE_EX: (winterm.back, WinColor.GREY, True),
+            }
+        return dict()
+
+    def write(self, text):
+        if self.strip or self.convert:
+            self.write_and_convert(text)
+        else:
+            self.wrapped.write(text)
+            self.wrapped.flush()
+        if self.autoreset:
+            self.reset_all()
+
+
+    def reset_all(self):
+        if self.convert:
+            self.call_win32('m', (0,))
+        elif not self.strip and not self.stream.closed:
+            self.wrapped.write(Style.RESET_ALL)
+
+
+    def write_and_convert(self, text):
+        '''
+        Write the given text to our wrapped stream, stripping any ANSI
+        sequences from the text, and optionally converting them into win32
+        calls.
+        '''
+        cursor = 0
+        text = self.convert_osc(text)
+        for match in self.ANSI_CSI_RE.finditer(text):
+            start, end = match.span()
+            self.write_plain_text(text, cursor, start)
+            self.convert_ansi(*match.groups())
+            cursor = end
+        self.write_plain_text(text, cursor, len(text))
+
+
+    def write_plain_text(self, text, start, end):
+        if start < end:
+            self.wrapped.write(text[start:end])
+            self.wrapped.flush()
+
+
+    def convert_ansi(self, paramstring, command):
+        if self.convert:
+            params = self.extract_params(command, paramstring)
+            self.call_win32(command, params)
+
+
+    def extract_params(self, command, paramstring):
+        if command in 'Hf':
+            params = tuple(int(p) if len(p) != 0 else 1 for p in paramstring.split(';'))
+            while len(params) < 2:
+                # defaults:
+                params = params + (1,)
+        else:
+            params = tuple(int(p) for p in paramstring.split(';') if len(p) != 0)
+            if len(params) == 0:
+                # defaults:
+                if command in 'JKm':
+                    params = (0,)
+                elif command in 'ABCD':
+                    params = (1,)
+
+        return params
+
+
+    def call_win32(self, command, params):
+        if command == 'm':
+            for param in params:
+                if param in self.win32_calls:
+                    func_args = self.win32_calls[param]
+                    func = func_args[0]
+                    args = func_args[1:]
+                    kwargs = dict(on_stderr=self.on_stderr)
+                    func(*args, **kwargs)
+        elif command in 'J':
+            winterm.erase_screen(params[0], on_stderr=self.on_stderr)
+        elif command in 'K':
+            winterm.erase_line(params[0], on_stderr=self.on_stderr)
+        elif command in 'Hf':     # cursor position - absolute
+            winterm.set_cursor_position(params, on_stderr=self.on_stderr)
+        elif command in 'ABCD':   # cursor position - relative
+            n = params[0]
+            # A - up, B - down, C - forward, D - back
+            x, y = {'A': (0, -n), 'B': (0, n), 'C': (n, 0), 'D': (-n, 0)}[command]
+            winterm.cursor_adjust(x, y, on_stderr=self.on_stderr)
+
+
+    def convert_osc(self, text):
+        for match in self.ANSI_OSC_RE.finditer(text):
+            start, end = match.span()
+            text = text[:start] + text[end:]
+            paramstring, command = match.groups()
+            if command == BEL:
+                if paramstring.count(";") == 1:
+                    params = paramstring.split(";")
+                    # 0 - change title and icon (we will only change title)
+                    # 1 - change icon (we don't support this)
+                    # 2 - change title
+                    if params[0] in '02':
+                        winterm.set_title(params[1])
+        return text
+
+
+    def flush(self):
+        self.wrapped.flush()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/initialise.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/initialise.py
new file mode 100644
index 0000000000000000000000000000000000000000..d5fd4b71fed1bb4871717f978f0c470280f099c1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/initialise.py
@@ -0,0 +1,121 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+import atexit
+import contextlib
+import sys
+
+from .ansitowin32 import AnsiToWin32
+
+
+def _wipe_internal_state_for_tests():
+    global orig_stdout, orig_stderr
+    orig_stdout = None
+    orig_stderr = None
+
+    global wrapped_stdout, wrapped_stderr
+    wrapped_stdout = None
+    wrapped_stderr = None
+
+    global atexit_done
+    atexit_done = False
+
+    global fixed_windows_console
+    fixed_windows_console = False
+
+    try:
+        # no-op if it wasn't registered
+        atexit.unregister(reset_all)
+    except AttributeError:
+        # python 2: no atexit.unregister. Oh well, we did our best.
+        pass
+
+
+def reset_all():
+    if AnsiToWin32 is not None:    # Issue #74: objects might become None at exit
+        AnsiToWin32(orig_stdout).reset_all()
+
+
+def init(autoreset=False, convert=None, strip=None, wrap=True):
+
+    if not wrap and any([autoreset, convert, strip]):
+        raise ValueError('wrap=False conflicts with any other arg=True')
+
+    global wrapped_stdout, wrapped_stderr
+    global orig_stdout, orig_stderr
+
+    orig_stdout = sys.stdout
+    orig_stderr = sys.stderr
+
+    if sys.stdout is None:
+        wrapped_stdout = None
+    else:
+        sys.stdout = wrapped_stdout = \
+            wrap_stream(orig_stdout, convert, strip, autoreset, wrap)
+    if sys.stderr is None:
+        wrapped_stderr = None
+    else:
+        sys.stderr = wrapped_stderr = \
+            wrap_stream(orig_stderr, convert, strip, autoreset, wrap)
+
+    global atexit_done
+    if not atexit_done:
+        atexit.register(reset_all)
+        atexit_done = True
+
+
+def deinit():
+    if orig_stdout is not None:
+        sys.stdout = orig_stdout
+    if orig_stderr is not None:
+        sys.stderr = orig_stderr
+
+
+def just_fix_windows_console():
+    global fixed_windows_console
+
+    if sys.platform != "win32":
+        return
+    if fixed_windows_console:
+        return
+    if wrapped_stdout is not None or wrapped_stderr is not None:
+        # Someone already ran init() and it did stuff, so we won't second-guess them
+        return
+
+    # On newer versions of Windows, AnsiToWin32.__init__ will implicitly enable the
+    # native ANSI support in the console as a side-effect. We only need to actually
+    # replace sys.stdout/stderr if we're in the old-style conversion mode.
+    new_stdout = AnsiToWin32(sys.stdout, convert=None, strip=None, autoreset=False)
+    if new_stdout.convert:
+        sys.stdout = new_stdout
+    new_stderr = AnsiToWin32(sys.stderr, convert=None, strip=None, autoreset=False)
+    if new_stderr.convert:
+        sys.stderr = new_stderr
+
+    fixed_windows_console = True
+
+@contextlib.contextmanager
+def colorama_text(*args, **kwargs):
+    init(*args, **kwargs)
+    try:
+        yield
+    finally:
+        deinit()
+
+
+def reinit():
+    if wrapped_stdout is not None:
+        sys.stdout = wrapped_stdout
+    if wrapped_stderr is not None:
+        sys.stderr = wrapped_stderr
+
+
+def wrap_stream(stream, convert, strip, autoreset, wrap):
+    if wrap:
+        wrapper = AnsiToWin32(stream,
+            convert=convert, strip=strip, autoreset=autoreset)
+        if wrapper.should_wrap():
+            stream = wrapper.stream
+    return stream
+
+
+# Use this for initial setup as well, to reduce code duplication
+_wipe_internal_state_for_tests()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8c5661e93a205bf4fb22404d4fc50f902cc31369
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/__init__.py
@@ -0,0 +1 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/ansi_test.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/ansi_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..0a20c80f882066e0e1323b0c7f61e22913c32e35
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/ansi_test.py
@@ -0,0 +1,76 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+import sys
+from unittest import TestCase, main
+
+from ..ansi import Back, Fore, Style
+from ..ansitowin32 import AnsiToWin32
+
+stdout_orig = sys.stdout
+stderr_orig = sys.stderr
+
+
+class AnsiTest(TestCase):
+
+    def setUp(self):
+        # sanity check: stdout should be a file or StringIO object.
+        # It will only be AnsiToWin32 if init() has previously wrapped it
+        self.assertNotEqual(type(sys.stdout), AnsiToWin32)
+        self.assertNotEqual(type(sys.stderr), AnsiToWin32)
+
+    def tearDown(self):
+        sys.stdout = stdout_orig
+        sys.stderr = stderr_orig
+
+
+    def testForeAttributes(self):
+        self.assertEqual(Fore.BLACK, '\033[30m')
+        self.assertEqual(Fore.RED, '\033[31m')
+        self.assertEqual(Fore.GREEN, '\033[32m')
+        self.assertEqual(Fore.YELLOW, '\033[33m')
+        self.assertEqual(Fore.BLUE, '\033[34m')
+        self.assertEqual(Fore.MAGENTA, '\033[35m')
+        self.assertEqual(Fore.CYAN, '\033[36m')
+        self.assertEqual(Fore.WHITE, '\033[37m')
+        self.assertEqual(Fore.RESET, '\033[39m')
+
+        # Check the light, extended versions.
+        self.assertEqual(Fore.LIGHTBLACK_EX, '\033[90m')
+        self.assertEqual(Fore.LIGHTRED_EX, '\033[91m')
+        self.assertEqual(Fore.LIGHTGREEN_EX, '\033[92m')
+        self.assertEqual(Fore.LIGHTYELLOW_EX, '\033[93m')
+        self.assertEqual(Fore.LIGHTBLUE_EX, '\033[94m')
+        self.assertEqual(Fore.LIGHTMAGENTA_EX, '\033[95m')
+        self.assertEqual(Fore.LIGHTCYAN_EX, '\033[96m')
+        self.assertEqual(Fore.LIGHTWHITE_EX, '\033[97m')
+
+
+    def testBackAttributes(self):
+        self.assertEqual(Back.BLACK, '\033[40m')
+        self.assertEqual(Back.RED, '\033[41m')
+        self.assertEqual(Back.GREEN, '\033[42m')
+        self.assertEqual(Back.YELLOW, '\033[43m')
+        self.assertEqual(Back.BLUE, '\033[44m')
+        self.assertEqual(Back.MAGENTA, '\033[45m')
+        self.assertEqual(Back.CYAN, '\033[46m')
+        self.assertEqual(Back.WHITE, '\033[47m')
+        self.assertEqual(Back.RESET, '\033[49m')
+
+        # Check the light, extended versions.
+        self.assertEqual(Back.LIGHTBLACK_EX, '\033[100m')
+        self.assertEqual(Back.LIGHTRED_EX, '\033[101m')
+        self.assertEqual(Back.LIGHTGREEN_EX, '\033[102m')
+        self.assertEqual(Back.LIGHTYELLOW_EX, '\033[103m')
+        self.assertEqual(Back.LIGHTBLUE_EX, '\033[104m')
+        self.assertEqual(Back.LIGHTMAGENTA_EX, '\033[105m')
+        self.assertEqual(Back.LIGHTCYAN_EX, '\033[106m')
+        self.assertEqual(Back.LIGHTWHITE_EX, '\033[107m')
+
+
+    def testStyleAttributes(self):
+        self.assertEqual(Style.DIM, '\033[2m')
+        self.assertEqual(Style.NORMAL, '\033[22m')
+        self.assertEqual(Style.BRIGHT, '\033[1m')
+
+
+if __name__ == '__main__':
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/ansitowin32_test.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/ansitowin32_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..91ca551f97b4576c680711e826a1855fb944c872
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/ansitowin32_test.py
@@ -0,0 +1,294 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+from io import StringIO, TextIOWrapper
+from unittest import TestCase, main
+try:
+    from contextlib import ExitStack
+except ImportError:
+    # python 2
+    from contextlib2 import ExitStack
+
+try:
+    from unittest.mock import MagicMock, Mock, patch
+except ImportError:
+    from mock import MagicMock, Mock, patch
+
+from ..ansitowin32 import AnsiToWin32, StreamWrapper
+from ..win32 import ENABLE_VIRTUAL_TERMINAL_PROCESSING
+from .utils import osname
+
+
+class StreamWrapperTest(TestCase):
+
+    def testIsAProxy(self):
+        mockStream = Mock()
+        wrapper = StreamWrapper(mockStream, None)
+        self.assertTrue( wrapper.random_attr is mockStream.random_attr )
+
+    def testDelegatesWrite(self):
+        mockStream = Mock()
+        mockConverter = Mock()
+        wrapper = StreamWrapper(mockStream, mockConverter)
+        wrapper.write('hello')
+        self.assertTrue(mockConverter.write.call_args, (('hello',), {}))
+
+    def testDelegatesContext(self):
+        mockConverter = Mock()
+        s = StringIO()
+        with StreamWrapper(s, mockConverter) as fp:
+            fp.write(u'hello')
+        self.assertTrue(s.closed)
+
+    def testProxyNoContextManager(self):
+        mockStream = MagicMock()
+        mockStream.__enter__.side_effect = AttributeError()
+        mockConverter = Mock()
+        with self.assertRaises(AttributeError) as excinfo:
+            with StreamWrapper(mockStream, mockConverter) as wrapper:
+                wrapper.write('hello')
+
+    def test_closed_shouldnt_raise_on_closed_stream(self):
+        stream = StringIO()
+        stream.close()
+        wrapper = StreamWrapper(stream, None)
+        self.assertEqual(wrapper.closed, True)
+
+    def test_closed_shouldnt_raise_on_detached_stream(self):
+        stream = TextIOWrapper(StringIO())
+        stream.detach()
+        wrapper = StreamWrapper(stream, None)
+        self.assertEqual(wrapper.closed, True)
+
+class AnsiToWin32Test(TestCase):
+
+    def testInit(self):
+        mockStdout = Mock()
+        auto = Mock()
+        stream = AnsiToWin32(mockStdout, autoreset=auto)
+        self.assertEqual(stream.wrapped, mockStdout)
+        self.assertEqual(stream.autoreset, auto)
+
+    @patch('colorama.ansitowin32.winterm', None)
+    @patch('colorama.ansitowin32.winapi_test', lambda *_: True)
+    def testStripIsTrueOnWindows(self):
+        with osname('nt'):
+            mockStdout = Mock()
+            stream = AnsiToWin32(mockStdout)
+            self.assertTrue(stream.strip)
+
+    def testStripIsFalseOffWindows(self):
+        with osname('posix'):
+            mockStdout = Mock(closed=False)
+            stream = AnsiToWin32(mockStdout)
+            self.assertFalse(stream.strip)
+
+    def testWriteStripsAnsi(self):
+        mockStdout = Mock()
+        stream = AnsiToWin32(mockStdout)
+        stream.wrapped = Mock()
+        stream.write_and_convert = Mock()
+        stream.strip = True
+
+        stream.write('abc')
+
+        self.assertFalse(stream.wrapped.write.called)
+        self.assertEqual(stream.write_and_convert.call_args, (('abc',), {}))
+
+    def testWriteDoesNotStripAnsi(self):
+        mockStdout = Mock()
+        stream = AnsiToWin32(mockStdout)
+        stream.wrapped = Mock()
+        stream.write_and_convert = Mock()
+        stream.strip = False
+        stream.convert = False
+
+        stream.write('abc')
+
+        self.assertFalse(stream.write_and_convert.called)
+        self.assertEqual(stream.wrapped.write.call_args, (('abc',), {}))
+
+    def assert_autoresets(self, convert, autoreset=True):
+        stream = AnsiToWin32(Mock())
+        stream.convert = convert
+        stream.reset_all = Mock()
+        stream.autoreset = autoreset
+        stream.winterm = Mock()
+
+        stream.write('abc')
+
+        self.assertEqual(stream.reset_all.called, autoreset)
+
+    def testWriteAutoresets(self):
+        self.assert_autoresets(convert=True)
+        self.assert_autoresets(convert=False)
+        self.assert_autoresets(convert=True, autoreset=False)
+        self.assert_autoresets(convert=False, autoreset=False)
+
+    def testWriteAndConvertWritesPlainText(self):
+        stream = AnsiToWin32(Mock())
+        stream.write_and_convert( 'abc' )
+        self.assertEqual( stream.wrapped.write.call_args, (('abc',), {}) )
+
+    def testWriteAndConvertStripsAllValidAnsi(self):
+        stream = AnsiToWin32(Mock())
+        stream.call_win32 = Mock()
+        data = [
+            'abc\033[mdef',
+            'abc\033[0mdef',
+            'abc\033[2mdef',
+            'abc\033[02mdef',
+            'abc\033[002mdef',
+            'abc\033[40mdef',
+            'abc\033[040mdef',
+            'abc\033[0;1mdef',
+            'abc\033[40;50mdef',
+            'abc\033[50;30;40mdef',
+            'abc\033[Adef',
+            'abc\033[0Gdef',
+            'abc\033[1;20;128Hdef',
+        ]
+        for datum in data:
+            stream.wrapped.write.reset_mock()
+            stream.write_and_convert( datum )
+            self.assertEqual(
+               [args[0] for args in stream.wrapped.write.call_args_list],
+               [ ('abc',), ('def',) ]
+            )
+
+    def testWriteAndConvertSkipsEmptySnippets(self):
+        stream = AnsiToWin32(Mock())
+        stream.call_win32 = Mock()
+        stream.write_and_convert( '\033[40m\033[41m' )
+        self.assertFalse( stream.wrapped.write.called )
+
+    def testWriteAndConvertCallsWin32WithParamsAndCommand(self):
+        stream = AnsiToWin32(Mock())
+        stream.convert = True
+        stream.call_win32 = Mock()
+        stream.extract_params = Mock(return_value='params')
+        data = {
+            'abc\033[adef':         ('a', 'params'),
+            'abc\033[;;bdef':       ('b', 'params'),
+            'abc\033[0cdef':        ('c', 'params'),
+            'abc\033[;;0;;Gdef':    ('G', 'params'),
+            'abc\033[1;20;128Hdef': ('H', 'params'),
+        }
+        for datum, expected in data.items():
+            stream.call_win32.reset_mock()
+            stream.write_and_convert( datum )
+            self.assertEqual( stream.call_win32.call_args[0], expected )
+
+    def test_reset_all_shouldnt_raise_on_closed_orig_stdout(self):
+        stream = StringIO()
+        converter = AnsiToWin32(stream)
+        stream.close()
+
+        converter.reset_all()
+
+    def test_wrap_shouldnt_raise_on_closed_orig_stdout(self):
+        stream = StringIO()
+        stream.close()
+        with \
+            patch("colorama.ansitowin32.os.name", "nt"), \
+            patch("colorama.ansitowin32.winapi_test", lambda: True):
+                converter = AnsiToWin32(stream)
+        self.assertTrue(converter.strip)
+        self.assertFalse(converter.convert)
+
+    def test_wrap_shouldnt_raise_on_missing_closed_attr(self):
+        with \
+            patch("colorama.ansitowin32.os.name", "nt"), \
+            patch("colorama.ansitowin32.winapi_test", lambda: True):
+                converter = AnsiToWin32(object())
+        self.assertTrue(converter.strip)
+        self.assertFalse(converter.convert)
+
+    def testExtractParams(self):
+        stream = AnsiToWin32(Mock())
+        data = {
+            '':               (0,),
+            ';;':             (0,),
+            '2':              (2,),
+            ';;002;;':        (2,),
+            '0;1':            (0, 1),
+            ';;003;;456;;':   (3, 456),
+            '11;22;33;44;55': (11, 22, 33, 44, 55),
+        }
+        for datum, expected in data.items():
+            self.assertEqual(stream.extract_params('m', datum), expected)
+
+    def testCallWin32UsesLookup(self):
+        listener = Mock()
+        stream = AnsiToWin32(listener)
+        stream.win32_calls = {
+            1: (lambda *_, **__: listener(11),),
+            2: (lambda *_, **__: listener(22),),
+            3: (lambda *_, **__: listener(33),),
+        }
+        stream.call_win32('m', (3, 1, 99, 2))
+        self.assertEqual(
+            [a[0][0] for a in listener.call_args_list],
+            [33, 11, 22] )
+
+    def test_osc_codes(self):
+        mockStdout = Mock()
+        stream = AnsiToWin32(mockStdout, convert=True)
+        with patch('colorama.ansitowin32.winterm') as winterm:
+            data = [
+                '\033]0\x07',                      # missing arguments
+                '\033]0;foo\x08',                  # wrong OSC command
+                '\033]0;colorama_test_title\x07',  # should work
+                '\033]1;colorama_test_title\x07',  # wrong set command
+                '\033]2;colorama_test_title\x07',  # should work
+                '\033]' + ';' * 64 + '\x08',       # see issue #247
+            ]
+            for code in data:
+                stream.write(code)
+            self.assertEqual(winterm.set_title.call_count, 2)
+
+    def test_native_windows_ansi(self):
+        with ExitStack() as stack:
+            def p(a, b):
+                stack.enter_context(patch(a, b, create=True))
+            # Pretend to be on Windows
+            p("colorama.ansitowin32.os.name", "nt")
+            p("colorama.ansitowin32.winapi_test", lambda: True)
+            p("colorama.win32.winapi_test", lambda: True)
+            p("colorama.winterm.win32.windll", "non-None")
+            p("colorama.winterm.get_osfhandle", lambda _: 1234)
+
+            # Pretend that our mock stream has native ANSI support
+            p(
+                "colorama.winterm.win32.GetConsoleMode",
+                lambda _: ENABLE_VIRTUAL_TERMINAL_PROCESSING,
+            )
+            SetConsoleMode = Mock()
+            p("colorama.winterm.win32.SetConsoleMode", SetConsoleMode)
+
+            stdout = Mock()
+            stdout.closed = False
+            stdout.isatty.return_value = True
+            stdout.fileno.return_value = 1
+
+            # Our fake console says it has native vt support, so AnsiToWin32 should
+            # enable that support and do nothing else.
+            stream = AnsiToWin32(stdout)
+            SetConsoleMode.assert_called_with(1234, ENABLE_VIRTUAL_TERMINAL_PROCESSING)
+            self.assertFalse(stream.strip)
+            self.assertFalse(stream.convert)
+            self.assertFalse(stream.should_wrap())
+
+            # Now let's pretend we're on an old Windows console, that doesn't have
+            # native ANSI support.
+            p("colorama.winterm.win32.GetConsoleMode", lambda _: 0)
+            SetConsoleMode = Mock()
+            p("colorama.winterm.win32.SetConsoleMode", SetConsoleMode)
+
+            stream = AnsiToWin32(stdout)
+            SetConsoleMode.assert_called_with(1234, ENABLE_VIRTUAL_TERMINAL_PROCESSING)
+            self.assertTrue(stream.strip)
+            self.assertTrue(stream.convert)
+            self.assertTrue(stream.should_wrap())
+
+
+if __name__ == '__main__':
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/initialise_test.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/initialise_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..89f9b07511c8fee74686d9cc434bf66345a46d6d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/initialise_test.py
@@ -0,0 +1,189 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+import sys
+from unittest import TestCase, main, skipUnless
+
+try:
+    from unittest.mock import patch, Mock
+except ImportError:
+    from mock import patch, Mock
+
+from ..ansitowin32 import StreamWrapper
+from ..initialise import init, just_fix_windows_console, _wipe_internal_state_for_tests
+from .utils import osname, replace_by
+
+orig_stdout = sys.stdout
+orig_stderr = sys.stderr
+
+
+class InitTest(TestCase):
+
+    @skipUnless(sys.stdout.isatty(), "sys.stdout is not a tty")
+    def setUp(self):
+        # sanity check
+        self.assertNotWrapped()
+
+    def tearDown(self):
+        _wipe_internal_state_for_tests()
+        sys.stdout = orig_stdout
+        sys.stderr = orig_stderr
+
+    def assertWrapped(self):
+        self.assertIsNot(sys.stdout, orig_stdout, 'stdout should be wrapped')
+        self.assertIsNot(sys.stderr, orig_stderr, 'stderr should be wrapped')
+        self.assertTrue(isinstance(sys.stdout, StreamWrapper),
+            'bad stdout wrapper')
+        self.assertTrue(isinstance(sys.stderr, StreamWrapper),
+            'bad stderr wrapper')
+
+    def assertNotWrapped(self):
+        self.assertIs(sys.stdout, orig_stdout, 'stdout should not be wrapped')
+        self.assertIs(sys.stderr, orig_stderr, 'stderr should not be wrapped')
+
+    @patch('colorama.initialise.reset_all')
+    @patch('colorama.ansitowin32.winapi_test', lambda *_: True)
+    @patch('colorama.ansitowin32.enable_vt_processing', lambda *_: False)
+    def testInitWrapsOnWindows(self, _):
+        with osname("nt"):
+            init()
+            self.assertWrapped()
+
+    @patch('colorama.initialise.reset_all')
+    @patch('colorama.ansitowin32.winapi_test', lambda *_: False)
+    def testInitDoesntWrapOnEmulatedWindows(self, _):
+        with osname("nt"):
+            init()
+            self.assertNotWrapped()
+
+    def testInitDoesntWrapOnNonWindows(self):
+        with osname("posix"):
+            init()
+            self.assertNotWrapped()
+
+    def testInitDoesntWrapIfNone(self):
+        with replace_by(None):
+            init()
+            # We can't use assertNotWrapped here because replace_by(None)
+            # changes stdout/stderr already.
+            self.assertIsNone(sys.stdout)
+            self.assertIsNone(sys.stderr)
+
+    def testInitAutoresetOnWrapsOnAllPlatforms(self):
+        with osname("posix"):
+            init(autoreset=True)
+            self.assertWrapped()
+
+    def testInitWrapOffDoesntWrapOnWindows(self):
+        with osname("nt"):
+            init(wrap=False)
+            self.assertNotWrapped()
+
+    def testInitWrapOffIncompatibleWithAutoresetOn(self):
+        self.assertRaises(ValueError, lambda: init(autoreset=True, wrap=False))
+
+    @patch('colorama.win32.SetConsoleTextAttribute')
+    @patch('colorama.initialise.AnsiToWin32')
+    def testAutoResetPassedOn(self, mockATW32, _):
+        with osname("nt"):
+            init(autoreset=True)
+            self.assertEqual(len(mockATW32.call_args_list), 2)
+            self.assertEqual(mockATW32.call_args_list[1][1]['autoreset'], True)
+            self.assertEqual(mockATW32.call_args_list[0][1]['autoreset'], True)
+
+    @patch('colorama.initialise.AnsiToWin32')
+    def testAutoResetChangeable(self, mockATW32):
+        with osname("nt"):
+            init()
+
+            init(autoreset=True)
+            self.assertEqual(len(mockATW32.call_args_list), 4)
+            self.assertEqual(mockATW32.call_args_list[2][1]['autoreset'], True)
+            self.assertEqual(mockATW32.call_args_list[3][1]['autoreset'], True)
+
+            init()
+            self.assertEqual(len(mockATW32.call_args_list), 6)
+            self.assertEqual(
+                mockATW32.call_args_list[4][1]['autoreset'], False)
+            self.assertEqual(
+                mockATW32.call_args_list[5][1]['autoreset'], False)
+
+
+    @patch('colorama.initialise.atexit.register')
+    def testAtexitRegisteredOnlyOnce(self, mockRegister):
+        init()
+        self.assertTrue(mockRegister.called)
+        mockRegister.reset_mock()
+        init()
+        self.assertFalse(mockRegister.called)
+
+
+class JustFixWindowsConsoleTest(TestCase):
+    def _reset(self):
+        _wipe_internal_state_for_tests()
+        sys.stdout = orig_stdout
+        sys.stderr = orig_stderr
+
+    def tearDown(self):
+        self._reset()
+
+    @patch("colorama.ansitowin32.winapi_test", lambda: True)
+    def testJustFixWindowsConsole(self):
+        if sys.platform != "win32":
+            # just_fix_windows_console should be a no-op
+            just_fix_windows_console()
+            self.assertIs(sys.stdout, orig_stdout)
+            self.assertIs(sys.stderr, orig_stderr)
+        else:
+            def fake_std():
+                # Emulate stdout=not a tty, stderr=tty
+                # to check that we handle both cases correctly
+                stdout = Mock()
+                stdout.closed = False
+                stdout.isatty.return_value = False
+                stdout.fileno.return_value = 1
+                sys.stdout = stdout
+
+                stderr = Mock()
+                stderr.closed = False
+                stderr.isatty.return_value = True
+                stderr.fileno.return_value = 2
+                sys.stderr = stderr
+
+            for native_ansi in [False, True]:
+                with patch(
+                    'colorama.ansitowin32.enable_vt_processing',
+                    lambda *_: native_ansi
+                ):
+                    self._reset()
+                    fake_std()
+
+                    # Regular single-call test
+                    prev_stdout = sys.stdout
+                    prev_stderr = sys.stderr
+                    just_fix_windows_console()
+                    self.assertIs(sys.stdout, prev_stdout)
+                    if native_ansi:
+                        self.assertIs(sys.stderr, prev_stderr)
+                    else:
+                        self.assertIsNot(sys.stderr, prev_stderr)
+
+                    # second call without resetting is always a no-op
+                    prev_stdout = sys.stdout
+                    prev_stderr = sys.stderr
+                    just_fix_windows_console()
+                    self.assertIs(sys.stdout, prev_stdout)
+                    self.assertIs(sys.stderr, prev_stderr)
+
+                    self._reset()
+                    fake_std()
+
+                    # If init() runs first, just_fix_windows_console should be a no-op
+                    init()
+                    prev_stdout = sys.stdout
+                    prev_stderr = sys.stderr
+                    just_fix_windows_console()
+                    self.assertIs(prev_stdout, sys.stdout)
+                    self.assertIs(prev_stderr, sys.stderr)
+
+
+if __name__ == '__main__':
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/isatty_test.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/isatty_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..0f84e4befe550d4386d24264648abf1323e682ff
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/isatty_test.py
@@ -0,0 +1,57 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+import sys
+from unittest import TestCase, main
+
+from ..ansitowin32 import StreamWrapper, AnsiToWin32
+from .utils import pycharm, replace_by, replace_original_by, StreamTTY, StreamNonTTY
+
+
+def is_a_tty(stream):
+    return StreamWrapper(stream, None).isatty()
+
+class IsattyTest(TestCase):
+
+    def test_TTY(self):
+        tty = StreamTTY()
+        self.assertTrue(is_a_tty(tty))
+        with pycharm():
+            self.assertTrue(is_a_tty(tty))
+
+    def test_nonTTY(self):
+        non_tty = StreamNonTTY()
+        self.assertFalse(is_a_tty(non_tty))
+        with pycharm():
+            self.assertFalse(is_a_tty(non_tty))
+
+    def test_withPycharm(self):
+        with pycharm():
+            self.assertTrue(is_a_tty(sys.stderr))
+            self.assertTrue(is_a_tty(sys.stdout))
+
+    def test_withPycharmTTYOverride(self):
+        tty = StreamTTY()
+        with pycharm(), replace_by(tty):
+            self.assertTrue(is_a_tty(tty))
+
+    def test_withPycharmNonTTYOverride(self):
+        non_tty = StreamNonTTY()
+        with pycharm(), replace_by(non_tty):
+            self.assertFalse(is_a_tty(non_tty))
+
+    def test_withPycharmNoneOverride(self):
+        with pycharm():
+            with replace_by(None), replace_original_by(None):
+                self.assertFalse(is_a_tty(None))
+                self.assertFalse(is_a_tty(StreamNonTTY()))
+                self.assertTrue(is_a_tty(StreamTTY()))
+
+    def test_withPycharmStreamWrapped(self):
+        with pycharm():
+            self.assertTrue(AnsiToWin32(StreamTTY()).stream.isatty())
+            self.assertFalse(AnsiToWin32(StreamNonTTY()).stream.isatty())
+            self.assertTrue(AnsiToWin32(sys.stdout).stream.isatty())
+            self.assertTrue(AnsiToWin32(sys.stderr).stream.isatty())
+
+
+if __name__ == '__main__':
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..472fafb4403efb9673d5cc724dafd9cf764aac5b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/utils.py
@@ -0,0 +1,49 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+from contextlib import contextmanager
+from io import StringIO
+import sys
+import os
+
+
+class StreamTTY(StringIO):
+    def isatty(self):
+        return True
+
+class StreamNonTTY(StringIO):
+    def isatty(self):
+        return False
+
+@contextmanager
+def osname(name):
+    orig = os.name
+    os.name = name
+    yield
+    os.name = orig
+
+@contextmanager
+def replace_by(stream):
+    orig_stdout = sys.stdout
+    orig_stderr = sys.stderr
+    sys.stdout = stream
+    sys.stderr = stream
+    yield
+    sys.stdout = orig_stdout
+    sys.stderr = orig_stderr
+
+@contextmanager
+def replace_original_by(stream):
+    orig_stdout = sys.__stdout__
+    orig_stderr = sys.__stderr__
+    sys.__stdout__ = stream
+    sys.__stderr__ = stream
+    yield
+    sys.__stdout__ = orig_stdout
+    sys.__stderr__ = orig_stderr
+
+@contextmanager
+def pycharm():
+    os.environ["PYCHARM_HOSTED"] = "1"
+    non_tty = StreamNonTTY()
+    with replace_by(non_tty), replace_original_by(non_tty):
+        yield
+    del os.environ["PYCHARM_HOSTED"]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/winterm_test.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/winterm_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..d0955f9e608377940f0d548576964f2fcf3caf48
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/tests/winterm_test.py
@@ -0,0 +1,131 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+import sys
+from unittest import TestCase, main, skipUnless
+
+try:
+    from unittest.mock import Mock, patch
+except ImportError:
+    from mock import Mock, patch
+
+from ..winterm import WinColor, WinStyle, WinTerm
+
+
+class WinTermTest(TestCase):
+
+    @patch('colorama.winterm.win32')
+    def testInit(self, mockWin32):
+        mockAttr = Mock()
+        mockAttr.wAttributes = 7 + 6 * 16 + 8
+        mockWin32.GetConsoleScreenBufferInfo.return_value = mockAttr
+        term = WinTerm()
+        self.assertEqual(term._fore, 7)
+        self.assertEqual(term._back, 6)
+        self.assertEqual(term._style, 8)
+
+    @skipUnless(sys.platform.startswith("win"), "requires Windows")
+    def testGetAttrs(self):
+        term = WinTerm()
+
+        term._fore = 0
+        term._back = 0
+        term._style = 0
+        self.assertEqual(term.get_attrs(), 0)
+
+        term._fore = WinColor.YELLOW
+        self.assertEqual(term.get_attrs(), WinColor.YELLOW)
+
+        term._back = WinColor.MAGENTA
+        self.assertEqual(
+            term.get_attrs(),
+            WinColor.YELLOW + WinColor.MAGENTA * 16)
+
+        term._style = WinStyle.BRIGHT
+        self.assertEqual(
+            term.get_attrs(),
+            WinColor.YELLOW + WinColor.MAGENTA * 16 + WinStyle.BRIGHT)
+
+    @patch('colorama.winterm.win32')
+    def testResetAll(self, mockWin32):
+        mockAttr = Mock()
+        mockAttr.wAttributes = 1 + 2 * 16 + 8
+        mockWin32.GetConsoleScreenBufferInfo.return_value = mockAttr
+        term = WinTerm()
+
+        term.set_console = Mock()
+        term._fore = -1
+        term._back = -1
+        term._style = -1
+
+        term.reset_all()
+
+        self.assertEqual(term._fore, 1)
+        self.assertEqual(term._back, 2)
+        self.assertEqual(term._style, 8)
+        self.assertEqual(term.set_console.called, True)
+
+    @skipUnless(sys.platform.startswith("win"), "requires Windows")
+    def testFore(self):
+        term = WinTerm()
+        term.set_console = Mock()
+        term._fore = 0
+
+        term.fore(5)
+
+        self.assertEqual(term._fore, 5)
+        self.assertEqual(term.set_console.called, True)
+
+    @skipUnless(sys.platform.startswith("win"), "requires Windows")
+    def testBack(self):
+        term = WinTerm()
+        term.set_console = Mock()
+        term._back = 0
+
+        term.back(5)
+
+        self.assertEqual(term._back, 5)
+        self.assertEqual(term.set_console.called, True)
+
+    @skipUnless(sys.platform.startswith("win"), "requires Windows")
+    def testStyle(self):
+        term = WinTerm()
+        term.set_console = Mock()
+        term._style = 0
+
+        term.style(22)
+
+        self.assertEqual(term._style, 22)
+        self.assertEqual(term.set_console.called, True)
+
+    @patch('colorama.winterm.win32')
+    def testSetConsole(self, mockWin32):
+        mockAttr = Mock()
+        mockAttr.wAttributes = 0
+        mockWin32.GetConsoleScreenBufferInfo.return_value = mockAttr
+        term = WinTerm()
+        term.windll = Mock()
+
+        term.set_console()
+
+        self.assertEqual(
+            mockWin32.SetConsoleTextAttribute.call_args,
+            ((mockWin32.STDOUT, term.get_attrs()), {})
+        )
+
+    @patch('colorama.winterm.win32')
+    def testSetConsoleOnStderr(self, mockWin32):
+        mockAttr = Mock()
+        mockAttr.wAttributes = 0
+        mockWin32.GetConsoleScreenBufferInfo.return_value = mockAttr
+        term = WinTerm()
+        term.windll = Mock()
+
+        term.set_console(on_stderr=True)
+
+        self.assertEqual(
+            mockWin32.SetConsoleTextAttribute.call_args,
+            ((mockWin32.STDERR, term.get_attrs()), {})
+        )
+
+
+if __name__ == '__main__':
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/win32.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/win32.py
new file mode 100644
index 0000000000000000000000000000000000000000..841b0e270a381cdfaca544a9be976d7276d83b1e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/win32.py
@@ -0,0 +1,180 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+
+# from winbase.h
+STDOUT = -11
+STDERR = -12
+
+ENABLE_VIRTUAL_TERMINAL_PROCESSING = 0x0004
+
+try:
+    import ctypes
+    from ctypes import LibraryLoader
+    windll = LibraryLoader(ctypes.WinDLL)
+    from ctypes import wintypes
+except (AttributeError, ImportError):
+    windll = None
+    SetConsoleTextAttribute = lambda *_: None
+    winapi_test = lambda *_: None
+else:
+    from ctypes import byref, Structure, c_char, POINTER
+
+    COORD = wintypes._COORD
+
+    class CONSOLE_SCREEN_BUFFER_INFO(Structure):
+        """struct in wincon.h."""
+        _fields_ = [
+            ("dwSize", COORD),
+            ("dwCursorPosition", COORD),
+            ("wAttributes", wintypes.WORD),
+            ("srWindow", wintypes.SMALL_RECT),
+            ("dwMaximumWindowSize", COORD),
+        ]
+        def __str__(self):
+            return '(%d,%d,%d,%d,%d,%d,%d,%d,%d,%d,%d)' % (
+                self.dwSize.Y, self.dwSize.X
+                , self.dwCursorPosition.Y, self.dwCursorPosition.X
+                , self.wAttributes
+                , self.srWindow.Top, self.srWindow.Left, self.srWindow.Bottom, self.srWindow.Right
+                , self.dwMaximumWindowSize.Y, self.dwMaximumWindowSize.X
+            )
+
+    _GetStdHandle = windll.kernel32.GetStdHandle
+    _GetStdHandle.argtypes = [
+        wintypes.DWORD,
+    ]
+    _GetStdHandle.restype = wintypes.HANDLE
+
+    _GetConsoleScreenBufferInfo = windll.kernel32.GetConsoleScreenBufferInfo
+    _GetConsoleScreenBufferInfo.argtypes = [
+        wintypes.HANDLE,
+        POINTER(CONSOLE_SCREEN_BUFFER_INFO),
+    ]
+    _GetConsoleScreenBufferInfo.restype = wintypes.BOOL
+
+    _SetConsoleTextAttribute = windll.kernel32.SetConsoleTextAttribute
+    _SetConsoleTextAttribute.argtypes = [
+        wintypes.HANDLE,
+        wintypes.WORD,
+    ]
+    _SetConsoleTextAttribute.restype = wintypes.BOOL
+
+    _SetConsoleCursorPosition = windll.kernel32.SetConsoleCursorPosition
+    _SetConsoleCursorPosition.argtypes = [
+        wintypes.HANDLE,
+        COORD,
+    ]
+    _SetConsoleCursorPosition.restype = wintypes.BOOL
+
+    _FillConsoleOutputCharacterA = windll.kernel32.FillConsoleOutputCharacterA
+    _FillConsoleOutputCharacterA.argtypes = [
+        wintypes.HANDLE,
+        c_char,
+        wintypes.DWORD,
+        COORD,
+        POINTER(wintypes.DWORD),
+    ]
+    _FillConsoleOutputCharacterA.restype = wintypes.BOOL
+
+    _FillConsoleOutputAttribute = windll.kernel32.FillConsoleOutputAttribute
+    _FillConsoleOutputAttribute.argtypes = [
+        wintypes.HANDLE,
+        wintypes.WORD,
+        wintypes.DWORD,
+        COORD,
+        POINTER(wintypes.DWORD),
+    ]
+    _FillConsoleOutputAttribute.restype = wintypes.BOOL
+
+    _SetConsoleTitleW = windll.kernel32.SetConsoleTitleW
+    _SetConsoleTitleW.argtypes = [
+        wintypes.LPCWSTR
+    ]
+    _SetConsoleTitleW.restype = wintypes.BOOL
+
+    _GetConsoleMode = windll.kernel32.GetConsoleMode
+    _GetConsoleMode.argtypes = [
+        wintypes.HANDLE,
+        POINTER(wintypes.DWORD)
+    ]
+    _GetConsoleMode.restype = wintypes.BOOL
+
+    _SetConsoleMode = windll.kernel32.SetConsoleMode
+    _SetConsoleMode.argtypes = [
+        wintypes.HANDLE,
+        wintypes.DWORD
+    ]
+    _SetConsoleMode.restype = wintypes.BOOL
+
+    def _winapi_test(handle):
+        csbi = CONSOLE_SCREEN_BUFFER_INFO()
+        success = _GetConsoleScreenBufferInfo(
+            handle, byref(csbi))
+        return bool(success)
+
+    def winapi_test():
+        return any(_winapi_test(h) for h in
+                   (_GetStdHandle(STDOUT), _GetStdHandle(STDERR)))
+
+    def GetConsoleScreenBufferInfo(stream_id=STDOUT):
+        handle = _GetStdHandle(stream_id)
+        csbi = CONSOLE_SCREEN_BUFFER_INFO()
+        success = _GetConsoleScreenBufferInfo(
+            handle, byref(csbi))
+        return csbi
+
+    def SetConsoleTextAttribute(stream_id, attrs):
+        handle = _GetStdHandle(stream_id)
+        return _SetConsoleTextAttribute(handle, attrs)
+
+    def SetConsoleCursorPosition(stream_id, position, adjust=True):
+        position = COORD(*position)
+        # If the position is out of range, do nothing.
+        if position.Y <= 0 or position.X <= 0:
+            return
+        # Adjust for Windows' SetConsoleCursorPosition:
+        #    1. being 0-based, while ANSI is 1-based.
+        #    2. expecting (x,y), while ANSI uses (y,x).
+        adjusted_position = COORD(position.Y - 1, position.X - 1)
+        if adjust:
+            # Adjust for viewport's scroll position
+            sr = GetConsoleScreenBufferInfo(STDOUT).srWindow
+            adjusted_position.Y += sr.Top
+            adjusted_position.X += sr.Left
+        # Resume normal processing
+        handle = _GetStdHandle(stream_id)
+        return _SetConsoleCursorPosition(handle, adjusted_position)
+
+    def FillConsoleOutputCharacter(stream_id, char, length, start):
+        handle = _GetStdHandle(stream_id)
+        char = c_char(char.encode())
+        length = wintypes.DWORD(length)
+        num_written = wintypes.DWORD(0)
+        # Note that this is hard-coded for ANSI (vs wide) bytes.
+        success = _FillConsoleOutputCharacterA(
+            handle, char, length, start, byref(num_written))
+        return num_written.value
+
+    def FillConsoleOutputAttribute(stream_id, attr, length, start):
+        ''' FillConsoleOutputAttribute( hConsole, csbi.wAttributes, dwConSize, coordScreen, &cCharsWritten )'''
+        handle = _GetStdHandle(stream_id)
+        attribute = wintypes.WORD(attr)
+        length = wintypes.DWORD(length)
+        num_written = wintypes.DWORD(0)
+        # Note that this is hard-coded for ANSI (vs wide) bytes.
+        return _FillConsoleOutputAttribute(
+            handle, attribute, length, start, byref(num_written))
+
+    def SetConsoleTitle(title):
+        return _SetConsoleTitleW(title)
+
+    def GetConsoleMode(handle):
+        mode = wintypes.DWORD()
+        success = _GetConsoleMode(handle, byref(mode))
+        if not success:
+            raise ctypes.WinError()
+        return mode.value
+
+    def SetConsoleMode(handle, mode):
+        success = _SetConsoleMode(handle, mode)
+        if not success:
+            raise ctypes.WinError()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/winterm.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/winterm.py
new file mode 100644
index 0000000000000000000000000000000000000000..aad867e8c80b826bf6a060116f17fa08a8eb0765
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/colorama/winterm.py
@@ -0,0 +1,195 @@
+# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
+try:
+    from msvcrt import get_osfhandle
+except ImportError:
+    def get_osfhandle(_):
+        raise OSError("This isn't windows!")
+
+
+from . import win32
+
+# from wincon.h
+class WinColor(object):
+    BLACK   = 0
+    BLUE    = 1
+    GREEN   = 2
+    CYAN    = 3
+    RED     = 4
+    MAGENTA = 5
+    YELLOW  = 6
+    GREY    = 7
+
+# from wincon.h
+class WinStyle(object):
+    NORMAL              = 0x00 # dim text, dim background
+    BRIGHT              = 0x08 # bright text, dim background
+    BRIGHT_BACKGROUND   = 0x80 # dim text, bright background
+
+class WinTerm(object):
+
+    def __init__(self):
+        self._default = win32.GetConsoleScreenBufferInfo(win32.STDOUT).wAttributes
+        self.set_attrs(self._default)
+        self._default_fore = self._fore
+        self._default_back = self._back
+        self._default_style = self._style
+        # In order to emulate LIGHT_EX in windows, we borrow the BRIGHT style.
+        # So that LIGHT_EX colors and BRIGHT style do not clobber each other,
+        # we track them separately, since LIGHT_EX is overwritten by Fore/Back
+        # and BRIGHT is overwritten by Style codes.
+        self._light = 0
+
+    def get_attrs(self):
+        return self._fore + self._back * 16 + (self._style | self._light)
+
+    def set_attrs(self, value):
+        self._fore = value & 7
+        self._back = (value >> 4) & 7
+        self._style = value & (WinStyle.BRIGHT | WinStyle.BRIGHT_BACKGROUND)
+
+    def reset_all(self, on_stderr=None):
+        self.set_attrs(self._default)
+        self.set_console(attrs=self._default)
+        self._light = 0
+
+    def fore(self, fore=None, light=False, on_stderr=False):
+        if fore is None:
+            fore = self._default_fore
+        self._fore = fore
+        # Emulate LIGHT_EX with BRIGHT Style
+        if light:
+            self._light |= WinStyle.BRIGHT
+        else:
+            self._light &= ~WinStyle.BRIGHT
+        self.set_console(on_stderr=on_stderr)
+
+    def back(self, back=None, light=False, on_stderr=False):
+        if back is None:
+            back = self._default_back
+        self._back = back
+        # Emulate LIGHT_EX with BRIGHT_BACKGROUND Style
+        if light:
+            self._light |= WinStyle.BRIGHT_BACKGROUND
+        else:
+            self._light &= ~WinStyle.BRIGHT_BACKGROUND
+        self.set_console(on_stderr=on_stderr)
+
+    def style(self, style=None, on_stderr=False):
+        if style is None:
+            style = self._default_style
+        self._style = style
+        self.set_console(on_stderr=on_stderr)
+
+    def set_console(self, attrs=None, on_stderr=False):
+        if attrs is None:
+            attrs = self.get_attrs()
+        handle = win32.STDOUT
+        if on_stderr:
+            handle = win32.STDERR
+        win32.SetConsoleTextAttribute(handle, attrs)
+
+    def get_position(self, handle):
+        position = win32.GetConsoleScreenBufferInfo(handle).dwCursorPosition
+        # Because Windows coordinates are 0-based,
+        # and win32.SetConsoleCursorPosition expects 1-based.
+        position.X += 1
+        position.Y += 1
+        return position
+
+    def set_cursor_position(self, position=None, on_stderr=False):
+        if position is None:
+            # I'm not currently tracking the position, so there is no default.
+            # position = self.get_position()
+            return
+        handle = win32.STDOUT
+        if on_stderr:
+            handle = win32.STDERR
+        win32.SetConsoleCursorPosition(handle, position)
+
+    def cursor_adjust(self, x, y, on_stderr=False):
+        handle = win32.STDOUT
+        if on_stderr:
+            handle = win32.STDERR
+        position = self.get_position(handle)
+        adjusted_position = (position.Y + y, position.X + x)
+        win32.SetConsoleCursorPosition(handle, adjusted_position, adjust=False)
+
+    def erase_screen(self, mode=0, on_stderr=False):
+        # 0 should clear from the cursor to the end of the screen.
+        # 1 should clear from the cursor to the beginning of the screen.
+        # 2 should clear the entire screen, and move cursor to (1,1)
+        handle = win32.STDOUT
+        if on_stderr:
+            handle = win32.STDERR
+        csbi = win32.GetConsoleScreenBufferInfo(handle)
+        # get the number of character cells in the current buffer
+        cells_in_screen = csbi.dwSize.X * csbi.dwSize.Y
+        # get number of character cells before current cursor position
+        cells_before_cursor = csbi.dwSize.X * csbi.dwCursorPosition.Y + csbi.dwCursorPosition.X
+        if mode == 0:
+            from_coord = csbi.dwCursorPosition
+            cells_to_erase = cells_in_screen - cells_before_cursor
+        elif mode == 1:
+            from_coord = win32.COORD(0, 0)
+            cells_to_erase = cells_before_cursor
+        elif mode == 2:
+            from_coord = win32.COORD(0, 0)
+            cells_to_erase = cells_in_screen
+        else:
+            # invalid mode
+            return
+        # fill the entire screen with blanks
+        win32.FillConsoleOutputCharacter(handle, ' ', cells_to_erase, from_coord)
+        # now set the buffer's attributes accordingly
+        win32.FillConsoleOutputAttribute(handle, self.get_attrs(), cells_to_erase, from_coord)
+        if mode == 2:
+            # put the cursor where needed
+            win32.SetConsoleCursorPosition(handle, (1, 1))
+
+    def erase_line(self, mode=0, on_stderr=False):
+        # 0 should clear from the cursor to the end of the line.
+        # 1 should clear from the cursor to the beginning of the line.
+        # 2 should clear the entire line.
+        handle = win32.STDOUT
+        if on_stderr:
+            handle = win32.STDERR
+        csbi = win32.GetConsoleScreenBufferInfo(handle)
+        if mode == 0:
+            from_coord = csbi.dwCursorPosition
+            cells_to_erase = csbi.dwSize.X - csbi.dwCursorPosition.X
+        elif mode == 1:
+            from_coord = win32.COORD(0, csbi.dwCursorPosition.Y)
+            cells_to_erase = csbi.dwCursorPosition.X
+        elif mode == 2:
+            from_coord = win32.COORD(0, csbi.dwCursorPosition.Y)
+            cells_to_erase = csbi.dwSize.X
+        else:
+            # invalid mode
+            return
+        # fill the entire screen with blanks
+        win32.FillConsoleOutputCharacter(handle, ' ', cells_to_erase, from_coord)
+        # now set the buffer's attributes accordingly
+        win32.FillConsoleOutputAttribute(handle, self.get_attrs(), cells_to_erase, from_coord)
+
+    def set_title(self, title):
+        win32.SetConsoleTitle(title)
+
+
+def enable_vt_processing(fd):
+    if win32.windll is None or not win32.winapi_test():
+        return False
+
+    try:
+        handle = get_osfhandle(fd)
+        mode = win32.GetConsoleMode(handle)
+        win32.SetConsoleMode(
+            handle,
+            mode | win32.ENABLE_VIRTUAL_TERMINAL_PROCESSING,
+        )
+
+        mode = win32.GetConsoleMode(handle)
+        if mode & win32.ENABLE_VIRTUAL_TERMINAL_PROCESSING:
+            return True
+    # Can get TypeError in testsuite where 'fd' is a Mock()
+    except (OSError, TypeError):
+        return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..962173c8d0a6906b59f2910c9cae759010534786
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/__init__.py
@@ -0,0 +1,23 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2012-2022 Vinay Sajip.
+# Licensed to the Python Software Foundation under a contributor agreement.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+import logging
+
+__version__ = '0.3.6'
+
+class DistlibException(Exception):
+    pass
+
+try:
+    from logging import NullHandler
+except ImportError: # pragma: no cover
+    class NullHandler(logging.Handler):
+        def handle(self, record): pass
+        def emit(self, record): pass
+        def createLock(self): self.lock = None
+
+logger = logging.getLogger(__name__)
+logger.addHandler(NullHandler())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..1fe3d225acb9bf37acffafc2198dc96c7c7fd313
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/compat.py
@@ -0,0 +1,1116 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2013-2017 Vinay Sajip.
+# Licensed to the Python Software Foundation under a contributor agreement.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+from __future__ import absolute_import
+
+import os
+import re
+import sys
+
+try:
+    import ssl
+except ImportError:  # pragma: no cover
+    ssl = None
+
+if sys.version_info[0] < 3:  # pragma: no cover
+    from StringIO import StringIO
+    string_types = basestring,
+    text_type = unicode
+    from types import FileType as file_type
+    import __builtin__ as builtins
+    import ConfigParser as configparser
+    from urlparse import urlparse, urlunparse, urljoin, urlsplit, urlunsplit
+    from urllib import (urlretrieve, quote as _quote, unquote, url2pathname,
+                        pathname2url, ContentTooShortError, splittype)
+
+    def quote(s):
+        if isinstance(s, unicode):
+            s = s.encode('utf-8')
+        return _quote(s)
+
+    import urllib2
+    from urllib2 import (Request, urlopen, URLError, HTTPError,
+                         HTTPBasicAuthHandler, HTTPPasswordMgr,
+                         HTTPHandler, HTTPRedirectHandler,
+                         build_opener)
+    if ssl:
+        from urllib2 import HTTPSHandler
+    import httplib
+    import xmlrpclib
+    import Queue as queue
+    from HTMLParser import HTMLParser
+    import htmlentitydefs
+    raw_input = raw_input
+    from itertools import ifilter as filter
+    from itertools import ifilterfalse as filterfalse
+
+    # Leaving this around for now, in case it needs resurrecting in some way
+    # _userprog = None
+    # def splituser(host):
+        # """splituser('user[:passwd]@host[:port]') --> 'user[:passwd]', 'host[:port]'."""
+        # global _userprog
+        # if _userprog is None:
+            # import re
+            # _userprog = re.compile('^(.*)@(.*)$')
+
+        # match = _userprog.match(host)
+        # if match: return match.group(1, 2)
+        # return None, host
+
+else:  # pragma: no cover
+    from io import StringIO
+    string_types = str,
+    text_type = str
+    from io import TextIOWrapper as file_type
+    import builtins
+    import configparser
+    import shutil
+    from urllib.parse import (urlparse, urlunparse, urljoin, quote,
+                              unquote, urlsplit, urlunsplit, splittype)
+    from urllib.request import (urlopen, urlretrieve, Request, url2pathname,
+                                pathname2url,
+                                HTTPBasicAuthHandler, HTTPPasswordMgr,
+                                HTTPHandler, HTTPRedirectHandler,
+                                build_opener)
+    if ssl:
+        from urllib.request import HTTPSHandler
+    from urllib.error import HTTPError, URLError, ContentTooShortError
+    import http.client as httplib
+    import urllib.request as urllib2
+    import xmlrpc.client as xmlrpclib
+    import queue
+    from html.parser import HTMLParser
+    import html.entities as htmlentitydefs
+    raw_input = input
+    from itertools import filterfalse
+    filter = filter
+
+
+try:
+    from ssl import match_hostname, CertificateError
+except ImportError: # pragma: no cover
+    class CertificateError(ValueError):
+        pass
+
+
+    def _dnsname_match(dn, hostname, max_wildcards=1):
+        """Matching according to RFC 6125, section 6.4.3
+
+        http://tools.ietf.org/html/rfc6125#section-6.4.3
+        """
+        pats = []
+        if not dn:
+            return False
+
+        parts = dn.split('.')
+        leftmost, remainder = parts[0], parts[1:]
+
+        wildcards = leftmost.count('*')
+        if wildcards > max_wildcards:
+            # Issue #17980: avoid denials of service by refusing more
+            # than one wildcard per fragment.  A survey of established
+            # policy among SSL implementations showed it to be a
+            # reasonable choice.
+            raise CertificateError(
+                "too many wildcards in certificate DNS name: " + repr(dn))
+
+        # speed up common case w/o wildcards
+        if not wildcards:
+            return dn.lower() == hostname.lower()
+
+        # RFC 6125, section 6.4.3, subitem 1.
+        # The client SHOULD NOT attempt to match a presented identifier in which
+        # the wildcard character comprises a label other than the left-most label.
+        if leftmost == '*':
+            # When '*' is a fragment by itself, it matches a non-empty dotless
+            # fragment.
+            pats.append('[^.]+')
+        elif leftmost.startswith('xn--') or hostname.startswith('xn--'):
+            # RFC 6125, section 6.4.3, subitem 3.
+            # The client SHOULD NOT attempt to match a presented identifier
+            # where the wildcard character is embedded within an A-label or
+            # U-label of an internationalized domain name.
+            pats.append(re.escape(leftmost))
+        else:
+            # Otherwise, '*' matches any dotless string, e.g. www*
+            pats.append(re.escape(leftmost).replace(r'\*', '[^.]*'))
+
+        # add the remaining fragments, ignore any wildcards
+        for frag in remainder:
+            pats.append(re.escape(frag))
+
+        pat = re.compile(r'\A' + r'\.'.join(pats) + r'\Z', re.IGNORECASE)
+        return pat.match(hostname)
+
+
+    def match_hostname(cert, hostname):
+        """Verify that *cert* (in decoded format as returned by
+        SSLSocket.getpeercert()) matches the *hostname*.  RFC 2818 and RFC 6125
+        rules are followed, but IP addresses are not accepted for *hostname*.
+
+        CertificateError is raised on failure. On success, the function
+        returns nothing.
+        """
+        if not cert:
+            raise ValueError("empty or no certificate, match_hostname needs a "
+                             "SSL socket or SSL context with either "
+                             "CERT_OPTIONAL or CERT_REQUIRED")
+        dnsnames = []
+        san = cert.get('subjectAltName', ())
+        for key, value in san:
+            if key == 'DNS':
+                if _dnsname_match(value, hostname):
+                    return
+                dnsnames.append(value)
+        if not dnsnames:
+            # The subject is only checked when there is no dNSName entry
+            # in subjectAltName
+            for sub in cert.get('subject', ()):
+                for key, value in sub:
+                    # XXX according to RFC 2818, the most specific Common Name
+                    # must be used.
+                    if key == 'commonName':
+                        if _dnsname_match(value, hostname):
+                            return
+                        dnsnames.append(value)
+        if len(dnsnames) > 1:
+            raise CertificateError("hostname %r "
+                "doesn't match either of %s"
+                % (hostname, ', '.join(map(repr, dnsnames))))
+        elif len(dnsnames) == 1:
+            raise CertificateError("hostname %r "
+                "doesn't match %r"
+                % (hostname, dnsnames[0]))
+        else:
+            raise CertificateError("no appropriate commonName or "
+                "subjectAltName fields were found")
+
+
+try:
+    from types import SimpleNamespace as Container
+except ImportError:  # pragma: no cover
+    class Container(object):
+        """
+        A generic container for when multiple values need to be returned
+        """
+        def __init__(self, **kwargs):
+            self.__dict__.update(kwargs)
+
+
+try:
+    from shutil import which
+except ImportError:  # pragma: no cover
+    # Implementation from Python 3.3
+    def which(cmd, mode=os.F_OK | os.X_OK, path=None):
+        """Given a command, mode, and a PATH string, return the path which
+        conforms to the given mode on the PATH, or None if there is no such
+        file.
+
+        `mode` defaults to os.F_OK | os.X_OK. `path` defaults to the result
+        of os.environ.get("PATH"), or can be overridden with a custom search
+        path.
+
+        """
+        # Check that a given file can be accessed with the correct mode.
+        # Additionally check that `file` is not a directory, as on Windows
+        # directories pass the os.access check.
+        def _access_check(fn, mode):
+            return (os.path.exists(fn) and os.access(fn, mode)
+                    and not os.path.isdir(fn))
+
+        # If we're given a path with a directory part, look it up directly rather
+        # than referring to PATH directories. This includes checking relative to the
+        # current directory, e.g. ./script
+        if os.path.dirname(cmd):
+            if _access_check(cmd, mode):
+                return cmd
+            return None
+
+        if path is None:
+            path = os.environ.get("PATH", os.defpath)
+        if not path:
+            return None
+        path = path.split(os.pathsep)
+
+        if sys.platform == "win32":
+            # The current directory takes precedence on Windows.
+            if not os.curdir in path:
+                path.insert(0, os.curdir)
+
+            # PATHEXT is necessary to check on Windows.
+            pathext = os.environ.get("PATHEXT", "").split(os.pathsep)
+            # See if the given file matches any of the expected path extensions.
+            # This will allow us to short circuit when given "python.exe".
+            # If it does match, only test that one, otherwise we have to try
+            # others.
+            if any(cmd.lower().endswith(ext.lower()) for ext in pathext):
+                files = [cmd]
+            else:
+                files = [cmd + ext for ext in pathext]
+        else:
+            # On other platforms you don't have things like PATHEXT to tell you
+            # what file suffixes are executable, so just pass on cmd as-is.
+            files = [cmd]
+
+        seen = set()
+        for dir in path:
+            normdir = os.path.normcase(dir)
+            if not normdir in seen:
+                seen.add(normdir)
+                for thefile in files:
+                    name = os.path.join(dir, thefile)
+                    if _access_check(name, mode):
+                        return name
+        return None
+
+
+# ZipFile is a context manager in 2.7, but not in 2.6
+
+from zipfile import ZipFile as BaseZipFile
+
+if hasattr(BaseZipFile, '__enter__'):  # pragma: no cover
+    ZipFile = BaseZipFile
+else:  # pragma: no cover
+    from zipfile import ZipExtFile as BaseZipExtFile
+
+    class ZipExtFile(BaseZipExtFile):
+        def __init__(self, base):
+            self.__dict__.update(base.__dict__)
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *exc_info):
+            self.close()
+            # return None, so if an exception occurred, it will propagate
+
+    class ZipFile(BaseZipFile):
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *exc_info):
+            self.close()
+            # return None, so if an exception occurred, it will propagate
+
+        def open(self, *args, **kwargs):
+            base = BaseZipFile.open(self, *args, **kwargs)
+            return ZipExtFile(base)
+
+try:
+    from platform import python_implementation
+except ImportError: # pragma: no cover
+    def python_implementation():
+        """Return a string identifying the Python implementation."""
+        if 'PyPy' in sys.version:
+            return 'PyPy'
+        if os.name == 'java':
+            return 'Jython'
+        if sys.version.startswith('IronPython'):
+            return 'IronPython'
+        return 'CPython'
+
+import shutil
+import sysconfig
+
+try:
+    callable = callable
+except NameError:   # pragma: no cover
+    from collections.abc import Callable
+
+    def callable(obj):
+        return isinstance(obj, Callable)
+
+
+try:
+    fsencode = os.fsencode
+    fsdecode = os.fsdecode
+except AttributeError:  # pragma: no cover
+    # Issue #99: on some systems (e.g. containerised),
+    # sys.getfilesystemencoding() returns None, and we need a real value,
+    # so fall back to utf-8. From the CPython 2.7 docs relating to Unix and
+    # sys.getfilesystemencoding(): the return value is "the user’s preference
+    # according to the result of nl_langinfo(CODESET), or None if the
+    # nl_langinfo(CODESET) failed."
+    _fsencoding = sys.getfilesystemencoding() or 'utf-8'
+    if _fsencoding == 'mbcs':
+        _fserrors = 'strict'
+    else:
+        _fserrors = 'surrogateescape'
+
+    def fsencode(filename):
+        if isinstance(filename, bytes):
+            return filename
+        elif isinstance(filename, text_type):
+            return filename.encode(_fsencoding, _fserrors)
+        else:
+            raise TypeError("expect bytes or str, not %s" %
+                            type(filename).__name__)
+
+    def fsdecode(filename):
+        if isinstance(filename, text_type):
+            return filename
+        elif isinstance(filename, bytes):
+            return filename.decode(_fsencoding, _fserrors)
+        else:
+            raise TypeError("expect bytes or str, not %s" %
+                            type(filename).__name__)
+
+try:
+    from tokenize import detect_encoding
+except ImportError: # pragma: no cover
+    from codecs import BOM_UTF8, lookup
+    import re
+
+    cookie_re = re.compile(r"coding[:=]\s*([-\w.]+)")
+
+    def _get_normal_name(orig_enc):
+        """Imitates get_normal_name in tokenizer.c."""
+        # Only care about the first 12 characters.
+        enc = orig_enc[:12].lower().replace("_", "-")
+        if enc == "utf-8" or enc.startswith("utf-8-"):
+            return "utf-8"
+        if enc in ("latin-1", "iso-8859-1", "iso-latin-1") or \
+           enc.startswith(("latin-1-", "iso-8859-1-", "iso-latin-1-")):
+            return "iso-8859-1"
+        return orig_enc
+
+    def detect_encoding(readline):
+        """
+        The detect_encoding() function is used to detect the encoding that should
+        be used to decode a Python source file.  It requires one argument, readline,
+        in the same way as the tokenize() generator.
+
+        It will call readline a maximum of twice, and return the encoding used
+        (as a string) and a list of any lines (left as bytes) it has read in.
+
+        It detects the encoding from the presence of a utf-8 bom or an encoding
+        cookie as specified in pep-0263.  If both a bom and a cookie are present,
+        but disagree, a SyntaxError will be raised.  If the encoding cookie is an
+        invalid charset, raise a SyntaxError.  Note that if a utf-8 bom is found,
+        'utf-8-sig' is returned.
+
+        If no encoding is specified, then the default of 'utf-8' will be returned.
+        """
+        try:
+            filename = readline.__self__.name
+        except AttributeError:
+            filename = None
+        bom_found = False
+        encoding = None
+        default = 'utf-8'
+        def read_or_stop():
+            try:
+                return readline()
+            except StopIteration:
+                return b''
+
+        def find_cookie(line):
+            try:
+                # Decode as UTF-8. Either the line is an encoding declaration,
+                # in which case it should be pure ASCII, or it must be UTF-8
+                # per default encoding.
+                line_string = line.decode('utf-8')
+            except UnicodeDecodeError:
+                msg = "invalid or missing encoding declaration"
+                if filename is not None:
+                    msg = '{} for {!r}'.format(msg, filename)
+                raise SyntaxError(msg)
+
+            matches = cookie_re.findall(line_string)
+            if not matches:
+                return None
+            encoding = _get_normal_name(matches[0])
+            try:
+                codec = lookup(encoding)
+            except LookupError:
+                # This behaviour mimics the Python interpreter
+                if filename is None:
+                    msg = "unknown encoding: " + encoding
+                else:
+                    msg = "unknown encoding for {!r}: {}".format(filename,
+                            encoding)
+                raise SyntaxError(msg)
+
+            if bom_found:
+                if codec.name != 'utf-8':
+                    # This behaviour mimics the Python interpreter
+                    if filename is None:
+                        msg = 'encoding problem: utf-8'
+                    else:
+                        msg = 'encoding problem for {!r}: utf-8'.format(filename)
+                    raise SyntaxError(msg)
+                encoding += '-sig'
+            return encoding
+
+        first = read_or_stop()
+        if first.startswith(BOM_UTF8):
+            bom_found = True
+            first = first[3:]
+            default = 'utf-8-sig'
+        if not first:
+            return default, []
+
+        encoding = find_cookie(first)
+        if encoding:
+            return encoding, [first]
+
+        second = read_or_stop()
+        if not second:
+            return default, [first]
+
+        encoding = find_cookie(second)
+        if encoding:
+            return encoding, [first, second]
+
+        return default, [first, second]
+
+# For converting & <-> & etc.
+try:
+    from html import escape
+except ImportError:
+    from cgi import escape
+if sys.version_info[:2] < (3, 4):
+    unescape = HTMLParser().unescape
+else:
+    from html import unescape
+
+try:
+    from collections import ChainMap
+except ImportError: # pragma: no cover
+    from collections import MutableMapping
+
+    try:
+        from reprlib import recursive_repr as _recursive_repr
+    except ImportError:
+        def _recursive_repr(fillvalue='...'):
+            '''
+            Decorator to make a repr function return fillvalue for a recursive
+            call
+            '''
+
+            def decorating_function(user_function):
+                repr_running = set()
+
+                def wrapper(self):
+                    key = id(self), get_ident()
+                    if key in repr_running:
+                        return fillvalue
+                    repr_running.add(key)
+                    try:
+                        result = user_function(self)
+                    finally:
+                        repr_running.discard(key)
+                    return result
+
+                # Can't use functools.wraps() here because of bootstrap issues
+                wrapper.__module__ = getattr(user_function, '__module__')
+                wrapper.__doc__ = getattr(user_function, '__doc__')
+                wrapper.__name__ = getattr(user_function, '__name__')
+                wrapper.__annotations__ = getattr(user_function, '__annotations__', {})
+                return wrapper
+
+            return decorating_function
+
+    class ChainMap(MutableMapping):
+        ''' A ChainMap groups multiple dicts (or other mappings) together
+        to create a single, updateable view.
+
+        The underlying mappings are stored in a list.  That list is public and can
+        accessed or updated using the *maps* attribute.  There is no other state.
+
+        Lookups search the underlying mappings successively until a key is found.
+        In contrast, writes, updates, and deletions only operate on the first
+        mapping.
+
+        '''
+
+        def __init__(self, *maps):
+            '''Initialize a ChainMap by setting *maps* to the given mappings.
+            If no mappings are provided, a single empty dictionary is used.
+
+            '''
+            self.maps = list(maps) or [{}]          # always at least one map
+
+        def __missing__(self, key):
+            raise KeyError(key)
+
+        def __getitem__(self, key):
+            for mapping in self.maps:
+                try:
+                    return mapping[key]             # can't use 'key in mapping' with defaultdict
+                except KeyError:
+                    pass
+            return self.__missing__(key)            # support subclasses that define __missing__
+
+        def get(self, key, default=None):
+            return self[key] if key in self else default
+
+        def __len__(self):
+            return len(set().union(*self.maps))     # reuses stored hash values if possible
+
+        def __iter__(self):
+            return iter(set().union(*self.maps))
+
+        def __contains__(self, key):
+            return any(key in m for m in self.maps)
+
+        def __bool__(self):
+            return any(self.maps)
+
+        @_recursive_repr()
+        def __repr__(self):
+            return '{0.__class__.__name__}({1})'.format(
+                self, ', '.join(map(repr, self.maps)))
+
+        @classmethod
+        def fromkeys(cls, iterable, *args):
+            'Create a ChainMap with a single dict created from the iterable.'
+            return cls(dict.fromkeys(iterable, *args))
+
+        def copy(self):
+            'New ChainMap or subclass with a new copy of maps[0] and refs to maps[1:]'
+            return self.__class__(self.maps[0].copy(), *self.maps[1:])
+
+        __copy__ = copy
+
+        def new_child(self):                        # like Django's Context.push()
+            'New ChainMap with a new dict followed by all previous maps.'
+            return self.__class__({}, *self.maps)
+
+        @property
+        def parents(self):                          # like Django's Context.pop()
+            'New ChainMap from maps[1:].'
+            return self.__class__(*self.maps[1:])
+
+        def __setitem__(self, key, value):
+            self.maps[0][key] = value
+
+        def __delitem__(self, key):
+            try:
+                del self.maps[0][key]
+            except KeyError:
+                raise KeyError('Key not found in the first mapping: {!r}'.format(key))
+
+        def popitem(self):
+            'Remove and return an item pair from maps[0]. Raise KeyError is maps[0] is empty.'
+            try:
+                return self.maps[0].popitem()
+            except KeyError:
+                raise KeyError('No keys found in the first mapping.')
+
+        def pop(self, key, *args):
+            'Remove *key* from maps[0] and return its value. Raise KeyError if *key* not in maps[0].'
+            try:
+                return self.maps[0].pop(key, *args)
+            except KeyError:
+                raise KeyError('Key not found in the first mapping: {!r}'.format(key))
+
+        def clear(self):
+            'Clear maps[0], leaving maps[1:] intact.'
+            self.maps[0].clear()
+
+try:
+    from importlib.util import cache_from_source  # Python >= 3.4
+except ImportError:  # pragma: no cover
+    def cache_from_source(path, debug_override=None):
+        assert path.endswith('.py')
+        if debug_override is None:
+            debug_override = __debug__
+        if debug_override:
+            suffix = 'c'
+        else:
+            suffix = 'o'
+        return path + suffix
+
+try:
+    from collections import OrderedDict
+except ImportError: # pragma: no cover
+## {{{ http://code.activestate.com/recipes/576693/ (r9)
+# Backport of OrderedDict() class that runs on Python 2.4, 2.5, 2.6, 2.7 and pypy.
+# Passes Python2.7's test suite and incorporates all the latest updates.
+    try:
+        from thread import get_ident as _get_ident
+    except ImportError:
+        from dummy_thread import get_ident as _get_ident
+
+    try:
+        from _abcoll import KeysView, ValuesView, ItemsView
+    except ImportError:
+        pass
+
+
+    class OrderedDict(dict):
+        'Dictionary that remembers insertion order'
+        # An inherited dict maps keys to values.
+        # The inherited dict provides __getitem__, __len__, __contains__, and get.
+        # The remaining methods are order-aware.
+        # Big-O running times for all methods are the same as for regular dictionaries.
+
+        # The internal self.__map dictionary maps keys to links in a doubly linked list.
+        # The circular doubly linked list starts and ends with a sentinel element.
+        # The sentinel element never gets deleted (this simplifies the algorithm).
+        # Each link is stored as a list of length three:  [PREV, NEXT, KEY].
+
+        def __init__(self, *args, **kwds):
+            '''Initialize an ordered dictionary.  Signature is the same as for
+            regular dictionaries, but keyword arguments are not recommended
+            because their insertion order is arbitrary.
+
+            '''
+            if len(args) > 1:
+                raise TypeError('expected at most 1 arguments, got %d' % len(args))
+            try:
+                self.__root
+            except AttributeError:
+                self.__root = root = []                     # sentinel node
+                root[:] = [root, root, None]
+                self.__map = {}
+            self.__update(*args, **kwds)
+
+        def __setitem__(self, key, value, dict_setitem=dict.__setitem__):
+            'od.__setitem__(i, y) <==> od[i]=y'
+            # Setting a new item creates a new link which goes at the end of the linked
+            # list, and the inherited dictionary is updated with the new key/value pair.
+            if key not in self:
+                root = self.__root
+                last = root[0]
+                last[1] = root[0] = self.__map[key] = [last, root, key]
+            dict_setitem(self, key, value)
+
+        def __delitem__(self, key, dict_delitem=dict.__delitem__):
+            'od.__delitem__(y) <==> del od[y]'
+            # Deleting an existing item uses self.__map to find the link which is
+            # then removed by updating the links in the predecessor and successor nodes.
+            dict_delitem(self, key)
+            link_prev, link_next, key = self.__map.pop(key)
+            link_prev[1] = link_next
+            link_next[0] = link_prev
+
+        def __iter__(self):
+            'od.__iter__() <==> iter(od)'
+            root = self.__root
+            curr = root[1]
+            while curr is not root:
+                yield curr[2]
+                curr = curr[1]
+
+        def __reversed__(self):
+            'od.__reversed__() <==> reversed(od)'
+            root = self.__root
+            curr = root[0]
+            while curr is not root:
+                yield curr[2]
+                curr = curr[0]
+
+        def clear(self):
+            'od.clear() -> None.  Remove all items from od.'
+            try:
+                for node in self.__map.itervalues():
+                    del node[:]
+                root = self.__root
+                root[:] = [root, root, None]
+                self.__map.clear()
+            except AttributeError:
+                pass
+            dict.clear(self)
+
+        def popitem(self, last=True):
+            '''od.popitem() -> (k, v), return and remove a (key, value) pair.
+            Pairs are returned in LIFO order if last is true or FIFO order if false.
+
+            '''
+            if not self:
+                raise KeyError('dictionary is empty')
+            root = self.__root
+            if last:
+                link = root[0]
+                link_prev = link[0]
+                link_prev[1] = root
+                root[0] = link_prev
+            else:
+                link = root[1]
+                link_next = link[1]
+                root[1] = link_next
+                link_next[0] = root
+            key = link[2]
+            del self.__map[key]
+            value = dict.pop(self, key)
+            return key, value
+
+        # -- the following methods do not depend on the internal structure --
+
+        def keys(self):
+            'od.keys() -> list of keys in od'
+            return list(self)
+
+        def values(self):
+            'od.values() -> list of values in od'
+            return [self[key] for key in self]
+
+        def items(self):
+            'od.items() -> list of (key, value) pairs in od'
+            return [(key, self[key]) for key in self]
+
+        def iterkeys(self):
+            'od.iterkeys() -> an iterator over the keys in od'
+            return iter(self)
+
+        def itervalues(self):
+            'od.itervalues -> an iterator over the values in od'
+            for k in self:
+                yield self[k]
+
+        def iteritems(self):
+            'od.iteritems -> an iterator over the (key, value) items in od'
+            for k in self:
+                yield (k, self[k])
+
+        def update(*args, **kwds):
+            '''od.update(E, **F) -> None.  Update od from dict/iterable E and F.
+
+            If E is a dict instance, does:           for k in E: od[k] = E[k]
+            If E has a .keys() method, does:         for k in E.keys(): od[k] = E[k]
+            Or if E is an iterable of items, does:   for k, v in E: od[k] = v
+            In either case, this is followed by:     for k, v in F.items(): od[k] = v
+
+            '''
+            if len(args) > 2:
+                raise TypeError('update() takes at most 2 positional '
+                                'arguments (%d given)' % (len(args),))
+            elif not args:
+                raise TypeError('update() takes at least 1 argument (0 given)')
+            self = args[0]
+            # Make progressively weaker assumptions about "other"
+            other = ()
+            if len(args) == 2:
+                other = args[1]
+            if isinstance(other, dict):
+                for key in other:
+                    self[key] = other[key]
+            elif hasattr(other, 'keys'):
+                for key in other.keys():
+                    self[key] = other[key]
+            else:
+                for key, value in other:
+                    self[key] = value
+            for key, value in kwds.items():
+                self[key] = value
+
+        __update = update  # let subclasses override update without breaking __init__
+
+        __marker = object()
+
+        def pop(self, key, default=__marker):
+            '''od.pop(k[,d]) -> v, remove specified key and return the corresponding value.
+            If key is not found, d is returned if given, otherwise KeyError is raised.
+
+            '''
+            if key in self:
+                result = self[key]
+                del self[key]
+                return result
+            if default is self.__marker:
+                raise KeyError(key)
+            return default
+
+        def setdefault(self, key, default=None):
+            'od.setdefault(k[,d]) -> od.get(k,d), also set od[k]=d if k not in od'
+            if key in self:
+                return self[key]
+            self[key] = default
+            return default
+
+        def __repr__(self, _repr_running=None):
+            'od.__repr__() <==> repr(od)'
+            if not _repr_running: _repr_running = {}
+            call_key = id(self), _get_ident()
+            if call_key in _repr_running:
+                return '...'
+            _repr_running[call_key] = 1
+            try:
+                if not self:
+                    return '%s()' % (self.__class__.__name__,)
+                return '%s(%r)' % (self.__class__.__name__, self.items())
+            finally:
+                del _repr_running[call_key]
+
+        def __reduce__(self):
+            'Return state information for pickling'
+            items = [[k, self[k]] for k in self]
+            inst_dict = vars(self).copy()
+            for k in vars(OrderedDict()):
+                inst_dict.pop(k, None)
+            if inst_dict:
+                return (self.__class__, (items,), inst_dict)
+            return self.__class__, (items,)
+
+        def copy(self):
+            'od.copy() -> a shallow copy of od'
+            return self.__class__(self)
+
+        @classmethod
+        def fromkeys(cls, iterable, value=None):
+            '''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S
+            and values equal to v (which defaults to None).
+
+            '''
+            d = cls()
+            for key in iterable:
+                d[key] = value
+            return d
+
+        def __eq__(self, other):
+            '''od.__eq__(y) <==> od==y.  Comparison to another OD is order-sensitive
+            while comparison to a regular mapping is order-insensitive.
+
+            '''
+            if isinstance(other, OrderedDict):
+                return len(self)==len(other) and self.items() == other.items()
+            return dict.__eq__(self, other)
+
+        def __ne__(self, other):
+            return not self == other
+
+        # -- the following methods are only used in Python 2.7 --
+
+        def viewkeys(self):
+            "od.viewkeys() -> a set-like object providing a view on od's keys"
+            return KeysView(self)
+
+        def viewvalues(self):
+            "od.viewvalues() -> an object providing a view on od's values"
+            return ValuesView(self)
+
+        def viewitems(self):
+            "od.viewitems() -> a set-like object providing a view on od's items"
+            return ItemsView(self)
+
+try:
+    from logging.config import BaseConfigurator, valid_ident
+except ImportError: # pragma: no cover
+    IDENTIFIER = re.compile('^[a-z_][a-z0-9_]*$', re.I)
+
+
+    def valid_ident(s):
+        m = IDENTIFIER.match(s)
+        if not m:
+            raise ValueError('Not a valid Python identifier: %r' % s)
+        return True
+
+
+    # The ConvertingXXX classes are wrappers around standard Python containers,
+    # and they serve to convert any suitable values in the container. The
+    # conversion converts base dicts, lists and tuples to their wrapped
+    # equivalents, whereas strings which match a conversion format are converted
+    # appropriately.
+    #
+    # Each wrapper should have a configurator attribute holding the actual
+    # configurator to use for conversion.
+
+    class ConvertingDict(dict):
+        """A converting dictionary wrapper."""
+
+        def __getitem__(self, key):
+            value = dict.__getitem__(self, key)
+            result = self.configurator.convert(value)
+            #If the converted value is different, save for next time
+            if value is not result:
+                self[key] = result
+                if type(result) in (ConvertingDict, ConvertingList,
+                                    ConvertingTuple):
+                    result.parent = self
+                    result.key = key
+            return result
+
+        def get(self, key, default=None):
+            value = dict.get(self, key, default)
+            result = self.configurator.convert(value)
+            #If the converted value is different, save for next time
+            if value is not result:
+                self[key] = result
+                if type(result) in (ConvertingDict, ConvertingList,
+                                    ConvertingTuple):
+                    result.parent = self
+                    result.key = key
+            return result
+
+    def pop(self, key, default=None):
+        value = dict.pop(self, key, default)
+        result = self.configurator.convert(value)
+        if value is not result:
+            if type(result) in (ConvertingDict, ConvertingList,
+                                ConvertingTuple):
+                result.parent = self
+                result.key = key
+        return result
+
+    class ConvertingList(list):
+        """A converting list wrapper."""
+        def __getitem__(self, key):
+            value = list.__getitem__(self, key)
+            result = self.configurator.convert(value)
+            #If the converted value is different, save for next time
+            if value is not result:
+                self[key] = result
+                if type(result) in (ConvertingDict, ConvertingList,
+                                    ConvertingTuple):
+                    result.parent = self
+                    result.key = key
+            return result
+
+        def pop(self, idx=-1):
+            value = list.pop(self, idx)
+            result = self.configurator.convert(value)
+            if value is not result:
+                if type(result) in (ConvertingDict, ConvertingList,
+                                    ConvertingTuple):
+                    result.parent = self
+            return result
+
+    class ConvertingTuple(tuple):
+        """A converting tuple wrapper."""
+        def __getitem__(self, key):
+            value = tuple.__getitem__(self, key)
+            result = self.configurator.convert(value)
+            if value is not result:
+                if type(result) in (ConvertingDict, ConvertingList,
+                                    ConvertingTuple):
+                    result.parent = self
+                    result.key = key
+            return result
+
+    class BaseConfigurator(object):
+        """
+        The configurator base class which defines some useful defaults.
+        """
+
+        CONVERT_PATTERN = re.compile(r'^(?P[a-z]+)://(?P.*)$')
+
+        WORD_PATTERN = re.compile(r'^\s*(\w+)\s*')
+        DOT_PATTERN = re.compile(r'^\.\s*(\w+)\s*')
+        INDEX_PATTERN = re.compile(r'^\[\s*(\w+)\s*\]\s*')
+        DIGIT_PATTERN = re.compile(r'^\d+$')
+
+        value_converters = {
+            'ext' : 'ext_convert',
+            'cfg' : 'cfg_convert',
+        }
+
+        # We might want to use a different one, e.g. importlib
+        importer = staticmethod(__import__)
+
+        def __init__(self, config):
+            self.config = ConvertingDict(config)
+            self.config.configurator = self
+
+        def resolve(self, s):
+            """
+            Resolve strings to objects using standard import and attribute
+            syntax.
+            """
+            name = s.split('.')
+            used = name.pop(0)
+            try:
+                found = self.importer(used)
+                for frag in name:
+                    used += '.' + frag
+                    try:
+                        found = getattr(found, frag)
+                    except AttributeError:
+                        self.importer(used)
+                        found = getattr(found, frag)
+                return found
+            except ImportError:
+                e, tb = sys.exc_info()[1:]
+                v = ValueError('Cannot resolve %r: %s' % (s, e))
+                v.__cause__, v.__traceback__ = e, tb
+                raise v
+
+        def ext_convert(self, value):
+            """Default converter for the ext:// protocol."""
+            return self.resolve(value)
+
+        def cfg_convert(self, value):
+            """Default converter for the cfg:// protocol."""
+            rest = value
+            m = self.WORD_PATTERN.match(rest)
+            if m is None:
+                raise ValueError("Unable to convert %r" % value)
+            else:
+                rest = rest[m.end():]
+                d = self.config[m.groups()[0]]
+                #print d, rest
+                while rest:
+                    m = self.DOT_PATTERN.match(rest)
+                    if m:
+                        d = d[m.groups()[0]]
+                    else:
+                        m = self.INDEX_PATTERN.match(rest)
+                        if m:
+                            idx = m.groups()[0]
+                            if not self.DIGIT_PATTERN.match(idx):
+                                d = d[idx]
+                            else:
+                                try:
+                                    n = int(idx) # try as number first (most likely)
+                                    d = d[n]
+                                except TypeError:
+                                    d = d[idx]
+                    if m:
+                        rest = rest[m.end():]
+                    else:
+                        raise ValueError('Unable to convert '
+                                         '%r at %r' % (value, rest))
+            #rest should be empty
+            return d
+
+        def convert(self, value):
+            """
+            Convert values to an appropriate type. dicts, lists and tuples are
+            replaced by their converting alternatives. Strings are checked to
+            see if they have a conversion format and are converted if they do.
+            """
+            if not isinstance(value, ConvertingDict) and isinstance(value, dict):
+                value = ConvertingDict(value)
+                value.configurator = self
+            elif not isinstance(value, ConvertingList) and isinstance(value, list):
+                value = ConvertingList(value)
+                value.configurator = self
+            elif not isinstance(value, ConvertingTuple) and\
+                     isinstance(value, tuple):
+                value = ConvertingTuple(value)
+                value.configurator = self
+            elif isinstance(value, string_types):
+                m = self.CONVERT_PATTERN.match(value)
+                if m:
+                    d = m.groupdict()
+                    prefix = d['prefix']
+                    converter = self.value_converters.get(prefix, None)
+                    if converter:
+                        suffix = d['suffix']
+                        converter = getattr(self, converter)
+                        value = converter(suffix)
+            return value
+
+        def configure_custom(self, config):
+            """Configure an object with a user-supplied factory."""
+            c = config.pop('()')
+            if not callable(c):
+                c = self.resolve(c)
+            props = config.pop('.', None)
+            # Check for valid identifiers
+            kwargs = dict([(k, config[k]) for k in config if valid_ident(k)])
+            result = c(**kwargs)
+            if props:
+                for name, value in props.items():
+                    setattr(result, name, value)
+            return result
+
+        def as_tuple(self, value):
+            """Utility function which converts lists to tuples."""
+            if isinstance(value, list):
+                value = tuple(value)
+            return value
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/database.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/database.py
new file mode 100644
index 0000000000000000000000000000000000000000..5db5d7f507c1d150e6b36f236df7ee61c0f65581
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/database.py
@@ -0,0 +1,1350 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2012-2017 The Python Software Foundation.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+"""PEP 376 implementation."""
+
+from __future__ import unicode_literals
+
+import base64
+import codecs
+import contextlib
+import hashlib
+import logging
+import os
+import posixpath
+import sys
+import zipimport
+
+from . import DistlibException, resources
+from .compat import StringIO
+from .version import get_scheme, UnsupportedVersionError
+from .metadata import (Metadata, METADATA_FILENAME, WHEEL_METADATA_FILENAME,
+                       LEGACY_METADATA_FILENAME)
+from .util import (parse_requirement, cached_property, parse_name_and_version,
+                   read_exports, write_exports, CSVReader, CSVWriter)
+
+
+__all__ = ['Distribution', 'BaseInstalledDistribution',
+           'InstalledDistribution', 'EggInfoDistribution',
+           'DistributionPath']
+
+
+logger = logging.getLogger(__name__)
+
+EXPORTS_FILENAME = 'pydist-exports.json'
+COMMANDS_FILENAME = 'pydist-commands.json'
+
+DIST_FILES = ('INSTALLER', METADATA_FILENAME, 'RECORD', 'REQUESTED',
+              'RESOURCES', EXPORTS_FILENAME, 'SHARED')
+
+DISTINFO_EXT = '.dist-info'
+
+
+class _Cache(object):
+    """
+    A simple cache mapping names and .dist-info paths to distributions
+    """
+    def __init__(self):
+        """
+        Initialise an instance. There is normally one for each DistributionPath.
+        """
+        self.name = {}
+        self.path = {}
+        self.generated = False
+
+    def clear(self):
+        """
+        Clear the cache, setting it to its initial state.
+        """
+        self.name.clear()
+        self.path.clear()
+        self.generated = False
+
+    def add(self, dist):
+        """
+        Add a distribution to the cache.
+        :param dist: The distribution to add.
+        """
+        if dist.path not in self.path:
+            self.path[dist.path] = dist
+            self.name.setdefault(dist.key, []).append(dist)
+
+
+class DistributionPath(object):
+    """
+    Represents a set of distributions installed on a path (typically sys.path).
+    """
+    def __init__(self, path=None, include_egg=False):
+        """
+        Create an instance from a path, optionally including legacy (distutils/
+        setuptools/distribute) distributions.
+        :param path: The path to use, as a list of directories. If not specified,
+                     sys.path is used.
+        :param include_egg: If True, this instance will look for and return legacy
+                            distributions as well as those based on PEP 376.
+        """
+        if path is None:
+            path = sys.path
+        self.path = path
+        self._include_dist = True
+        self._include_egg = include_egg
+
+        self._cache = _Cache()
+        self._cache_egg = _Cache()
+        self._cache_enabled = True
+        self._scheme = get_scheme('default')
+
+    def _get_cache_enabled(self):
+        return self._cache_enabled
+
+    def _set_cache_enabled(self, value):
+        self._cache_enabled = value
+
+    cache_enabled = property(_get_cache_enabled, _set_cache_enabled)
+
+    def clear_cache(self):
+        """
+        Clears the internal cache.
+        """
+        self._cache.clear()
+        self._cache_egg.clear()
+
+
+    def _yield_distributions(self):
+        """
+        Yield .dist-info and/or .egg(-info) distributions.
+        """
+        # We need to check if we've seen some resources already, because on
+        # some Linux systems (e.g. some Debian/Ubuntu variants) there are
+        # symlinks which alias other files in the environment.
+        seen = set()
+        for path in self.path:
+            finder = resources.finder_for_path(path)
+            if finder is None:
+                continue
+            r = finder.find('')
+            if not r or not r.is_container:
+                continue
+            rset = sorted(r.resources)
+            for entry in rset:
+                r = finder.find(entry)
+                if not r or r.path in seen:
+                    continue
+                try:
+                    if self._include_dist and entry.endswith(DISTINFO_EXT):
+                        possible_filenames = [METADATA_FILENAME,
+                                              WHEEL_METADATA_FILENAME,
+                                              LEGACY_METADATA_FILENAME]
+                        for metadata_filename in possible_filenames:
+                            metadata_path = posixpath.join(entry, metadata_filename)
+                            pydist = finder.find(metadata_path)
+                            if pydist:
+                                break
+                        else:
+                            continue
+
+                        with contextlib.closing(pydist.as_stream()) as stream:
+                            metadata = Metadata(fileobj=stream, scheme='legacy')
+                        logger.debug('Found %s', r.path)
+                        seen.add(r.path)
+                        yield new_dist_class(r.path, metadata=metadata,
+                                             env=self)
+                    elif self._include_egg and entry.endswith(('.egg-info',
+                                                              '.egg')):
+                        logger.debug('Found %s', r.path)
+                        seen.add(r.path)
+                        yield old_dist_class(r.path, self)
+                except Exception as e:
+                    msg = 'Unable to read distribution at %s, perhaps due to bad metadata: %s'
+                    logger.warning(msg, r.path, e)
+                    import warnings
+                    warnings.warn(msg % (r.path, e), stacklevel=2)
+
+    def _generate_cache(self):
+        """
+        Scan the path for distributions and populate the cache with
+        those that are found.
+        """
+        gen_dist = not self._cache.generated
+        gen_egg = self._include_egg and not self._cache_egg.generated
+        if gen_dist or gen_egg:
+            for dist in self._yield_distributions():
+                if isinstance(dist, InstalledDistribution):
+                    self._cache.add(dist)
+                else:
+                    self._cache_egg.add(dist)
+
+            if gen_dist:
+                self._cache.generated = True
+            if gen_egg:
+                self._cache_egg.generated = True
+
+    @classmethod
+    def distinfo_dirname(cls, name, version):
+        """
+        The *name* and *version* parameters are converted into their
+        filename-escaped form, i.e. any ``'-'`` characters are replaced
+        with ``'_'`` other than the one in ``'dist-info'`` and the one
+        separating the name from the version number.
+
+        :parameter name: is converted to a standard distribution name by replacing
+                         any runs of non- alphanumeric characters with a single
+                         ``'-'``.
+        :type name: string
+        :parameter version: is converted to a standard version string. Spaces
+                            become dots, and all other non-alphanumeric characters
+                            (except dots) become dashes, with runs of multiple
+                            dashes condensed to a single dash.
+        :type version: string
+        :returns: directory name
+        :rtype: string"""
+        name = name.replace('-', '_')
+        return '-'.join([name, version]) + DISTINFO_EXT
+
+    def get_distributions(self):
+        """
+        Provides an iterator that looks for distributions and returns
+        :class:`InstalledDistribution` or
+        :class:`EggInfoDistribution` instances for each one of them.
+
+        :rtype: iterator of :class:`InstalledDistribution` and
+                :class:`EggInfoDistribution` instances
+        """
+        if not self._cache_enabled:
+            for dist in self._yield_distributions():
+                yield dist
+        else:
+            self._generate_cache()
+
+            for dist in self._cache.path.values():
+                yield dist
+
+            if self._include_egg:
+                for dist in self._cache_egg.path.values():
+                    yield dist
+
+    def get_distribution(self, name):
+        """
+        Looks for a named distribution on the path.
+
+        This function only returns the first result found, as no more than one
+        value is expected. If nothing is found, ``None`` is returned.
+
+        :rtype: :class:`InstalledDistribution`, :class:`EggInfoDistribution`
+                or ``None``
+        """
+        result = None
+        name = name.lower()
+        if not self._cache_enabled:
+            for dist in self._yield_distributions():
+                if dist.key == name:
+                    result = dist
+                    break
+        else:
+            self._generate_cache()
+
+            if name in self._cache.name:
+                result = self._cache.name[name][0]
+            elif self._include_egg and name in self._cache_egg.name:
+                result = self._cache_egg.name[name][0]
+        return result
+
+    def provides_distribution(self, name, version=None):
+        """
+        Iterates over all distributions to find which distributions provide *name*.
+        If a *version* is provided, it will be used to filter the results.
+
+        This function only returns the first result found, since no more than
+        one values are expected. If the directory is not found, returns ``None``.
+
+        :parameter version: a version specifier that indicates the version
+                            required, conforming to the format in ``PEP-345``
+
+        :type name: string
+        :type version: string
+        """
+        matcher = None
+        if version is not None:
+            try:
+                matcher = self._scheme.matcher('%s (%s)' % (name, version))
+            except ValueError:
+                raise DistlibException('invalid name or version: %r, %r' %
+                                      (name, version))
+
+        for dist in self.get_distributions():
+            # We hit a problem on Travis where enum34 was installed and doesn't
+            # have a provides attribute ...
+            if not hasattr(dist, 'provides'):
+                logger.debug('No "provides": %s', dist)
+            else:
+                provided = dist.provides
+
+                for p in provided:
+                    p_name, p_ver = parse_name_and_version(p)
+                    if matcher is None:
+                        if p_name == name:
+                            yield dist
+                            break
+                    else:
+                        if p_name == name and matcher.match(p_ver):
+                            yield dist
+                            break
+
+    def get_file_path(self, name, relative_path):
+        """
+        Return the path to a resource file.
+        """
+        dist = self.get_distribution(name)
+        if dist is None:
+            raise LookupError('no distribution named %r found' % name)
+        return dist.get_resource_path(relative_path)
+
+    def get_exported_entries(self, category, name=None):
+        """
+        Return all of the exported entries in a particular category.
+
+        :param category: The category to search for entries.
+        :param name: If specified, only entries with that name are returned.
+        """
+        for dist in self.get_distributions():
+            r = dist.exports
+            if category in r:
+                d = r[category]
+                if name is not None:
+                    if name in d:
+                        yield d[name]
+                else:
+                    for v in d.values():
+                        yield v
+
+
+class Distribution(object):
+    """
+    A base class for distributions, whether installed or from indexes.
+    Either way, it must have some metadata, so that's all that's needed
+    for construction.
+    """
+
+    build_time_dependency = False
+    """
+    Set to True if it's known to be only a build-time dependency (i.e.
+    not needed after installation).
+    """
+
+    requested = False
+    """A boolean that indicates whether the ``REQUESTED`` metadata file is
+    present (in other words, whether the package was installed by user
+    request or it was installed as a dependency)."""
+
+    def __init__(self, metadata):
+        """
+        Initialise an instance.
+        :param metadata: The instance of :class:`Metadata` describing this
+        distribution.
+        """
+        self.metadata = metadata
+        self.name = metadata.name
+        self.key = self.name.lower()    # for case-insensitive comparisons
+        self.version = metadata.version
+        self.locator = None
+        self.digest = None
+        self.extras = None      # additional features requested
+        self.context = None     # environment marker overrides
+        self.download_urls = set()
+        self.digests = {}
+
+    @property
+    def source_url(self):
+        """
+        The source archive download URL for this distribution.
+        """
+        return self.metadata.source_url
+
+    download_url = source_url   # Backward compatibility
+
+    @property
+    def name_and_version(self):
+        """
+        A utility property which displays the name and version in parentheses.
+        """
+        return '%s (%s)' % (self.name, self.version)
+
+    @property
+    def provides(self):
+        """
+        A set of distribution names and versions provided by this distribution.
+        :return: A set of "name (version)" strings.
+        """
+        plist = self.metadata.provides
+        s = '%s (%s)' % (self.name, self.version)
+        if s not in plist:
+            plist.append(s)
+        return plist
+
+    def _get_requirements(self, req_attr):
+        md = self.metadata
+        reqts = getattr(md, req_attr)
+        logger.debug('%s: got requirements %r from metadata: %r', self.name, req_attr,
+                     reqts)
+        return set(md.get_requirements(reqts, extras=self.extras,
+                                       env=self.context))
+
+    @property
+    def run_requires(self):
+        return self._get_requirements('run_requires')
+
+    @property
+    def meta_requires(self):
+        return self._get_requirements('meta_requires')
+
+    @property
+    def build_requires(self):
+        return self._get_requirements('build_requires')
+
+    @property
+    def test_requires(self):
+        return self._get_requirements('test_requires')
+
+    @property
+    def dev_requires(self):
+        return self._get_requirements('dev_requires')
+
+    def matches_requirement(self, req):
+        """
+        Say if this instance matches (fulfills) a requirement.
+        :param req: The requirement to match.
+        :rtype req: str
+        :return: True if it matches, else False.
+        """
+        # Requirement may contain extras - parse to lose those
+        # from what's passed to the matcher
+        r = parse_requirement(req)
+        scheme = get_scheme(self.metadata.scheme)
+        try:
+            matcher = scheme.matcher(r.requirement)
+        except UnsupportedVersionError:
+            # XXX compat-mode if cannot read the version
+            logger.warning('could not read version %r - using name only',
+                           req)
+            name = req.split()[0]
+            matcher = scheme.matcher(name)
+
+        name = matcher.key   # case-insensitive
+
+        result = False
+        for p in self.provides:
+            p_name, p_ver = parse_name_and_version(p)
+            if p_name != name:
+                continue
+            try:
+                result = matcher.match(p_ver)
+                break
+            except UnsupportedVersionError:
+                pass
+        return result
+
+    def __repr__(self):
+        """
+        Return a textual representation of this instance,
+        """
+        if self.source_url:
+            suffix = ' [%s]' % self.source_url
+        else:
+            suffix = ''
+        return '' % (self.name, self.version, suffix)
+
+    def __eq__(self, other):
+        """
+        See if this distribution is the same as another.
+        :param other: The distribution to compare with. To be equal to one
+                      another. distributions must have the same type, name,
+                      version and source_url.
+        :return: True if it is the same, else False.
+        """
+        if type(other) is not type(self):
+            result = False
+        else:
+            result = (self.name == other.name and
+                      self.version == other.version and
+                      self.source_url == other.source_url)
+        return result
+
+    def __hash__(self):
+        """
+        Compute hash in a way which matches the equality test.
+        """
+        return hash(self.name) + hash(self.version) + hash(self.source_url)
+
+
+class BaseInstalledDistribution(Distribution):
+    """
+    This is the base class for installed distributions (whether PEP 376 or
+    legacy).
+    """
+
+    hasher = None
+
+    def __init__(self, metadata, path, env=None):
+        """
+        Initialise an instance.
+        :param metadata: An instance of :class:`Metadata` which describes the
+                         distribution. This will normally have been initialised
+                         from a metadata file in the ``path``.
+        :param path:     The path of the ``.dist-info`` or ``.egg-info``
+                         directory for the distribution.
+        :param env:      This is normally the :class:`DistributionPath`
+                         instance where this distribution was found.
+        """
+        super(BaseInstalledDistribution, self).__init__(metadata)
+        self.path = path
+        self.dist_path = env
+
+    def get_hash(self, data, hasher=None):
+        """
+        Get the hash of some data, using a particular hash algorithm, if
+        specified.
+
+        :param data: The data to be hashed.
+        :type data: bytes
+        :param hasher: The name of a hash implementation, supported by hashlib,
+                       or ``None``. Examples of valid values are ``'sha1'``,
+                       ``'sha224'``, ``'sha384'``, '``sha256'``, ``'md5'`` and
+                       ``'sha512'``. If no hasher is specified, the ``hasher``
+                       attribute of the :class:`InstalledDistribution` instance
+                       is used. If the hasher is determined to be ``None``, MD5
+                       is used as the hashing algorithm.
+        :returns: The hash of the data. If a hasher was explicitly specified,
+                  the returned hash will be prefixed with the specified hasher
+                  followed by '='.
+        :rtype: str
+        """
+        if hasher is None:
+            hasher = self.hasher
+        if hasher is None:
+            hasher = hashlib.md5
+            prefix = ''
+        else:
+            hasher = getattr(hashlib, hasher)
+            prefix = '%s=' % self.hasher
+        digest = hasher(data).digest()
+        digest = base64.urlsafe_b64encode(digest).rstrip(b'=').decode('ascii')
+        return '%s%s' % (prefix, digest)
+
+
+class InstalledDistribution(BaseInstalledDistribution):
+    """
+    Created with the *path* of the ``.dist-info`` directory provided to the
+    constructor. It reads the metadata contained in ``pydist.json`` when it is
+    instantiated., or uses a passed in Metadata instance (useful for when
+    dry-run mode is being used).
+    """
+
+    hasher = 'sha256'
+
+    def __init__(self, path, metadata=None, env=None):
+        self.modules = []
+        self.finder = finder = resources.finder_for_path(path)
+        if finder is None:
+            raise ValueError('finder unavailable for %s' % path)
+        if env and env._cache_enabled and path in env._cache.path:
+            metadata = env._cache.path[path].metadata
+        elif metadata is None:
+            r = finder.find(METADATA_FILENAME)
+            # Temporary - for Wheel 0.23 support
+            if r is None:
+                r = finder.find(WHEEL_METADATA_FILENAME)
+            # Temporary - for legacy support
+            if r is None:
+                r = finder.find(LEGACY_METADATA_FILENAME)
+            if r is None:
+                raise ValueError('no %s found in %s' % (METADATA_FILENAME,
+                                                        path))
+            with contextlib.closing(r.as_stream()) as stream:
+                metadata = Metadata(fileobj=stream, scheme='legacy')
+
+        super(InstalledDistribution, self).__init__(metadata, path, env)
+
+        if env and env._cache_enabled:
+            env._cache.add(self)
+
+        r = finder.find('REQUESTED')
+        self.requested = r is not None
+        p  = os.path.join(path, 'top_level.txt')
+        if os.path.exists(p):
+            with open(p, 'rb') as f:
+                data = f.read().decode('utf-8')
+            self.modules = data.splitlines()
+
+    def __repr__(self):
+        return '' % (
+            self.name, self.version, self.path)
+
+    def __str__(self):
+        return "%s %s" % (self.name, self.version)
+
+    def _get_records(self):
+        """
+        Get the list of installed files for the distribution
+        :return: A list of tuples of path, hash and size. Note that hash and
+                 size might be ``None`` for some entries. The path is exactly
+                 as stored in the file (which is as in PEP 376).
+        """
+        results = []
+        r = self.get_distinfo_resource('RECORD')
+        with contextlib.closing(r.as_stream()) as stream:
+            with CSVReader(stream=stream) as record_reader:
+                # Base location is parent dir of .dist-info dir
+                #base_location = os.path.dirname(self.path)
+                #base_location = os.path.abspath(base_location)
+                for row in record_reader:
+                    missing = [None for i in range(len(row), 3)]
+                    path, checksum, size = row + missing
+                    #if not os.path.isabs(path):
+                    #    path = path.replace('/', os.sep)
+                    #    path = os.path.join(base_location, path)
+                    results.append((path, checksum, size))
+        return results
+
+    @cached_property
+    def exports(self):
+        """
+        Return the information exported by this distribution.
+        :return: A dictionary of exports, mapping an export category to a dict
+                 of :class:`ExportEntry` instances describing the individual
+                 export entries, and keyed by name.
+        """
+        result = {}
+        r = self.get_distinfo_resource(EXPORTS_FILENAME)
+        if r:
+            result = self.read_exports()
+        return result
+
+    def read_exports(self):
+        """
+        Read exports data from a file in .ini format.
+
+        :return: A dictionary of exports, mapping an export category to a list
+                 of :class:`ExportEntry` instances describing the individual
+                 export entries.
+        """
+        result = {}
+        r = self.get_distinfo_resource(EXPORTS_FILENAME)
+        if r:
+            with contextlib.closing(r.as_stream()) as stream:
+                result = read_exports(stream)
+        return result
+
+    def write_exports(self, exports):
+        """
+        Write a dictionary of exports to a file in .ini format.
+        :param exports: A dictionary of exports, mapping an export category to
+                        a list of :class:`ExportEntry` instances describing the
+                        individual export entries.
+        """
+        rf = self.get_distinfo_file(EXPORTS_FILENAME)
+        with open(rf, 'w') as f:
+            write_exports(exports, f)
+
+    def get_resource_path(self, relative_path):
+        """
+        NOTE: This API may change in the future.
+
+        Return the absolute path to a resource file with the given relative
+        path.
+
+        :param relative_path: The path, relative to .dist-info, of the resource
+                              of interest.
+        :return: The absolute path where the resource is to be found.
+        """
+        r = self.get_distinfo_resource('RESOURCES')
+        with contextlib.closing(r.as_stream()) as stream:
+            with CSVReader(stream=stream) as resources_reader:
+                for relative, destination in resources_reader:
+                    if relative == relative_path:
+                        return destination
+        raise KeyError('no resource file with relative path %r '
+                       'is installed' % relative_path)
+
+    def list_installed_files(self):
+        """
+        Iterates over the ``RECORD`` entries and returns a tuple
+        ``(path, hash, size)`` for each line.
+
+        :returns: iterator of (path, hash, size)
+        """
+        for result in self._get_records():
+            yield result
+
+    def write_installed_files(self, paths, prefix, dry_run=False):
+        """
+        Writes the ``RECORD`` file, using the ``paths`` iterable passed in. Any
+        existing ``RECORD`` file is silently overwritten.
+
+        prefix is used to determine when to write absolute paths.
+        """
+        prefix = os.path.join(prefix, '')
+        base = os.path.dirname(self.path)
+        base_under_prefix = base.startswith(prefix)
+        base = os.path.join(base, '')
+        record_path = self.get_distinfo_file('RECORD')
+        logger.info('creating %s', record_path)
+        if dry_run:
+            return None
+        with CSVWriter(record_path) as writer:
+            for path in paths:
+                if os.path.isdir(path) or path.endswith(('.pyc', '.pyo')):
+                    # do not put size and hash, as in PEP-376
+                    hash_value = size = ''
+                else:
+                    size = '%d' % os.path.getsize(path)
+                    with open(path, 'rb') as fp:
+                        hash_value = self.get_hash(fp.read())
+                if path.startswith(base) or (base_under_prefix and
+                                             path.startswith(prefix)):
+                    path = os.path.relpath(path, base)
+                writer.writerow((path, hash_value, size))
+
+            # add the RECORD file itself
+            if record_path.startswith(base):
+                record_path = os.path.relpath(record_path, base)
+            writer.writerow((record_path, '', ''))
+        return record_path
+
+    def check_installed_files(self):
+        """
+        Checks that the hashes and sizes of the files in ``RECORD`` are
+        matched by the files themselves. Returns a (possibly empty) list of
+        mismatches. Each entry in the mismatch list will be a tuple consisting
+        of the path, 'exists', 'size' or 'hash' according to what didn't match
+        (existence is checked first, then size, then hash), the expected
+        value and the actual value.
+        """
+        mismatches = []
+        base = os.path.dirname(self.path)
+        record_path = self.get_distinfo_file('RECORD')
+        for path, hash_value, size in self.list_installed_files():
+            if not os.path.isabs(path):
+                path = os.path.join(base, path)
+            if path == record_path:
+                continue
+            if not os.path.exists(path):
+                mismatches.append((path, 'exists', True, False))
+            elif os.path.isfile(path):
+                actual_size = str(os.path.getsize(path))
+                if size and actual_size != size:
+                    mismatches.append((path, 'size', size, actual_size))
+                elif hash_value:
+                    if '=' in hash_value:
+                        hasher = hash_value.split('=', 1)[0]
+                    else:
+                        hasher = None
+
+                    with open(path, 'rb') as f:
+                        actual_hash = self.get_hash(f.read(), hasher)
+                        if actual_hash != hash_value:
+                            mismatches.append((path, 'hash', hash_value, actual_hash))
+        return mismatches
+
+    @cached_property
+    def shared_locations(self):
+        """
+        A dictionary of shared locations whose keys are in the set 'prefix',
+        'purelib', 'platlib', 'scripts', 'headers', 'data' and 'namespace'.
+        The corresponding value is the absolute path of that category for
+        this distribution, and takes into account any paths selected by the
+        user at installation time (e.g. via command-line arguments). In the
+        case of the 'namespace' key, this would be a list of absolute paths
+        for the roots of namespace packages in this distribution.
+
+        The first time this property is accessed, the relevant information is
+        read from the SHARED file in the .dist-info directory.
+        """
+        result = {}
+        shared_path = os.path.join(self.path, 'SHARED')
+        if os.path.isfile(shared_path):
+            with codecs.open(shared_path, 'r', encoding='utf-8') as f:
+                lines = f.read().splitlines()
+            for line in lines:
+                key, value = line.split('=', 1)
+                if key == 'namespace':
+                    result.setdefault(key, []).append(value)
+                else:
+                    result[key] = value
+        return result
+
+    def write_shared_locations(self, paths, dry_run=False):
+        """
+        Write shared location information to the SHARED file in .dist-info.
+        :param paths: A dictionary as described in the documentation for
+        :meth:`shared_locations`.
+        :param dry_run: If True, the action is logged but no file is actually
+                        written.
+        :return: The path of the file written to.
+        """
+        shared_path = os.path.join(self.path, 'SHARED')
+        logger.info('creating %s', shared_path)
+        if dry_run:
+            return None
+        lines = []
+        for key in ('prefix', 'lib', 'headers', 'scripts', 'data'):
+            path = paths[key]
+            if os.path.isdir(paths[key]):
+                lines.append('%s=%s' % (key,  path))
+        for ns in paths.get('namespace', ()):
+            lines.append('namespace=%s' % ns)
+
+        with codecs.open(shared_path, 'w', encoding='utf-8') as f:
+            f.write('\n'.join(lines))
+        return shared_path
+
+    def get_distinfo_resource(self, path):
+        if path not in DIST_FILES:
+            raise DistlibException('invalid path for a dist-info file: '
+                                   '%r at %r' % (path, self.path))
+        finder = resources.finder_for_path(self.path)
+        if finder is None:
+            raise DistlibException('Unable to get a finder for %s' % self.path)
+        return finder.find(path)
+
+    def get_distinfo_file(self, path):
+        """
+        Returns a path located under the ``.dist-info`` directory. Returns a
+        string representing the path.
+
+        :parameter path: a ``'/'``-separated path relative to the
+                         ``.dist-info`` directory or an absolute path;
+                         If *path* is an absolute path and doesn't start
+                         with the ``.dist-info`` directory path,
+                         a :class:`DistlibException` is raised
+        :type path: str
+        :rtype: str
+        """
+        # Check if it is an absolute path  # XXX use relpath, add tests
+        if path.find(os.sep) >= 0:
+            # it's an absolute path?
+            distinfo_dirname, path = path.split(os.sep)[-2:]
+            if distinfo_dirname != self.path.split(os.sep)[-1]:
+                raise DistlibException(
+                    'dist-info file %r does not belong to the %r %s '
+                    'distribution' % (path, self.name, self.version))
+
+        # The file must be relative
+        if path not in DIST_FILES:
+            raise DistlibException('invalid path for a dist-info file: '
+                                   '%r at %r' % (path, self.path))
+
+        return os.path.join(self.path, path)
+
+    def list_distinfo_files(self):
+        """
+        Iterates over the ``RECORD`` entries and returns paths for each line if
+        the path is pointing to a file located in the ``.dist-info`` directory
+        or one of its subdirectories.
+
+        :returns: iterator of paths
+        """
+        base = os.path.dirname(self.path)
+        for path, checksum, size in self._get_records():
+            # XXX add separator or use real relpath algo
+            if not os.path.isabs(path):
+                path = os.path.join(base, path)
+            if path.startswith(self.path):
+                yield path
+
+    def __eq__(self, other):
+        return (isinstance(other, InstalledDistribution) and
+                self.path == other.path)
+
+    # See http://docs.python.org/reference/datamodel#object.__hash__
+    __hash__ = object.__hash__
+
+
+class EggInfoDistribution(BaseInstalledDistribution):
+    """Created with the *path* of the ``.egg-info`` directory or file provided
+    to the constructor. It reads the metadata contained in the file itself, or
+    if the given path happens to be a directory, the metadata is read from the
+    file ``PKG-INFO`` under that directory."""
+
+    requested = True    # as we have no way of knowing, assume it was
+    shared_locations = {}
+
+    def __init__(self, path, env=None):
+        def set_name_and_version(s, n, v):
+            s.name = n
+            s.key = n.lower()   # for case-insensitive comparisons
+            s.version = v
+
+        self.path = path
+        self.dist_path = env
+        if env and env._cache_enabled and path in env._cache_egg.path:
+            metadata = env._cache_egg.path[path].metadata
+            set_name_and_version(self, metadata.name, metadata.version)
+        else:
+            metadata = self._get_metadata(path)
+
+            # Need to be set before caching
+            set_name_and_version(self, metadata.name, metadata.version)
+
+            if env and env._cache_enabled:
+                env._cache_egg.add(self)
+        super(EggInfoDistribution, self).__init__(metadata, path, env)
+
+    def _get_metadata(self, path):
+        requires = None
+
+        def parse_requires_data(data):
+            """Create a list of dependencies from a requires.txt file.
+
+            *data*: the contents of a setuptools-produced requires.txt file.
+            """
+            reqs = []
+            lines = data.splitlines()
+            for line in lines:
+                line = line.strip()
+                if line.startswith('['):
+                    logger.warning('Unexpected line: quitting requirement scan: %r',
+                                   line)
+                    break
+                r = parse_requirement(line)
+                if not r:
+                    logger.warning('Not recognised as a requirement: %r', line)
+                    continue
+                if r.extras:
+                    logger.warning('extra requirements in requires.txt are '
+                                   'not supported')
+                if not r.constraints:
+                    reqs.append(r.name)
+                else:
+                    cons = ', '.join('%s%s' % c for c in r.constraints)
+                    reqs.append('%s (%s)' % (r.name, cons))
+            return reqs
+
+        def parse_requires_path(req_path):
+            """Create a list of dependencies from a requires.txt file.
+
+            *req_path*: the path to a setuptools-produced requires.txt file.
+            """
+
+            reqs = []
+            try:
+                with codecs.open(req_path, 'r', 'utf-8') as fp:
+                    reqs = parse_requires_data(fp.read())
+            except IOError:
+                pass
+            return reqs
+
+        tl_path = tl_data = None
+        if path.endswith('.egg'):
+            if os.path.isdir(path):
+                p = os.path.join(path, 'EGG-INFO')
+                meta_path = os.path.join(p, 'PKG-INFO')
+                metadata = Metadata(path=meta_path, scheme='legacy')
+                req_path = os.path.join(p, 'requires.txt')
+                tl_path = os.path.join(p, 'top_level.txt')
+                requires = parse_requires_path(req_path)
+            else:
+                # FIXME handle the case where zipfile is not available
+                zipf = zipimport.zipimporter(path)
+                fileobj = StringIO(
+                    zipf.get_data('EGG-INFO/PKG-INFO').decode('utf8'))
+                metadata = Metadata(fileobj=fileobj, scheme='legacy')
+                try:
+                    data = zipf.get_data('EGG-INFO/requires.txt')
+                    tl_data = zipf.get_data('EGG-INFO/top_level.txt').decode('utf-8')
+                    requires = parse_requires_data(data.decode('utf-8'))
+                except IOError:
+                    requires = None
+        elif path.endswith('.egg-info'):
+            if os.path.isdir(path):
+                req_path = os.path.join(path, 'requires.txt')
+                requires = parse_requires_path(req_path)
+                path = os.path.join(path, 'PKG-INFO')
+                tl_path = os.path.join(path, 'top_level.txt')
+            metadata = Metadata(path=path, scheme='legacy')
+        else:
+            raise DistlibException('path must end with .egg-info or .egg, '
+                                   'got %r' % path)
+
+        if requires:
+            metadata.add_requirements(requires)
+        # look for top-level modules in top_level.txt, if present
+        if tl_data is None:
+            if tl_path is not None and os.path.exists(tl_path):
+                with open(tl_path, 'rb') as f:
+                    tl_data = f.read().decode('utf-8')
+        if not tl_data:
+            tl_data = []
+        else:
+            tl_data = tl_data.splitlines()
+        self.modules = tl_data
+        return metadata
+
+    def __repr__(self):
+        return '' % (
+            self.name, self.version, self.path)
+
+    def __str__(self):
+        return "%s %s" % (self.name, self.version)
+
+    def check_installed_files(self):
+        """
+        Checks that the hashes and sizes of the files in ``RECORD`` are
+        matched by the files themselves. Returns a (possibly empty) list of
+        mismatches. Each entry in the mismatch list will be a tuple consisting
+        of the path, 'exists', 'size' or 'hash' according to what didn't match
+        (existence is checked first, then size, then hash), the expected
+        value and the actual value.
+        """
+        mismatches = []
+        record_path = os.path.join(self.path, 'installed-files.txt')
+        if os.path.exists(record_path):
+            for path, _, _ in self.list_installed_files():
+                if path == record_path:
+                    continue
+                if not os.path.exists(path):
+                    mismatches.append((path, 'exists', True, False))
+        return mismatches
+
+    def list_installed_files(self):
+        """
+        Iterates over the ``installed-files.txt`` entries and returns a tuple
+        ``(path, hash, size)`` for each line.
+
+        :returns: a list of (path, hash, size)
+        """
+
+        def _md5(path):
+            f = open(path, 'rb')
+            try:
+                content = f.read()
+            finally:
+                f.close()
+            return hashlib.md5(content).hexdigest()
+
+        def _size(path):
+            return os.stat(path).st_size
+
+        record_path = os.path.join(self.path, 'installed-files.txt')
+        result = []
+        if os.path.exists(record_path):
+            with codecs.open(record_path, 'r', encoding='utf-8') as f:
+                for line in f:
+                    line = line.strip()
+                    p = os.path.normpath(os.path.join(self.path, line))
+                    # "./" is present as a marker between installed files
+                    # and installation metadata files
+                    if not os.path.exists(p):
+                        logger.warning('Non-existent file: %s', p)
+                        if p.endswith(('.pyc', '.pyo')):
+                            continue
+                        #otherwise fall through and fail
+                    if not os.path.isdir(p):
+                        result.append((p, _md5(p), _size(p)))
+            result.append((record_path, None, None))
+        return result
+
+    def list_distinfo_files(self, absolute=False):
+        """
+        Iterates over the ``installed-files.txt`` entries and returns paths for
+        each line if the path is pointing to a file located in the
+        ``.egg-info`` directory or one of its subdirectories.
+
+        :parameter absolute: If *absolute* is ``True``, each returned path is
+                          transformed into a local absolute path. Otherwise the
+                          raw value from ``installed-files.txt`` is returned.
+        :type absolute: boolean
+        :returns: iterator of paths
+        """
+        record_path = os.path.join(self.path, 'installed-files.txt')
+        if os.path.exists(record_path):
+            skip = True
+            with codecs.open(record_path, 'r', encoding='utf-8') as f:
+                for line in f:
+                    line = line.strip()
+                    if line == './':
+                        skip = False
+                        continue
+                    if not skip:
+                        p = os.path.normpath(os.path.join(self.path, line))
+                        if p.startswith(self.path):
+                            if absolute:
+                                yield p
+                            else:
+                                yield line
+
+    def __eq__(self, other):
+        return (isinstance(other, EggInfoDistribution) and
+                self.path == other.path)
+
+    # See http://docs.python.org/reference/datamodel#object.__hash__
+    __hash__ = object.__hash__
+
+new_dist_class = InstalledDistribution
+old_dist_class = EggInfoDistribution
+
+
+class DependencyGraph(object):
+    """
+    Represents a dependency graph between distributions.
+
+    The dependency relationships are stored in an ``adjacency_list`` that maps
+    distributions to a list of ``(other, label)`` tuples where  ``other``
+    is a distribution and the edge is labeled with ``label`` (i.e. the version
+    specifier, if such was provided). Also, for more efficient traversal, for
+    every distribution ``x``, a list of predecessors is kept in
+    ``reverse_list[x]``. An edge from distribution ``a`` to
+    distribution ``b`` means that ``a`` depends on ``b``. If any missing
+    dependencies are found, they are stored in ``missing``, which is a
+    dictionary that maps distributions to a list of requirements that were not
+    provided by any other distributions.
+    """
+
+    def __init__(self):
+        self.adjacency_list = {}
+        self.reverse_list = {}
+        self.missing = {}
+
+    def add_distribution(self, distribution):
+        """Add the *distribution* to the graph.
+
+        :type distribution: :class:`distutils2.database.InstalledDistribution`
+                            or :class:`distutils2.database.EggInfoDistribution`
+        """
+        self.adjacency_list[distribution] = []
+        self.reverse_list[distribution] = []
+        #self.missing[distribution] = []
+
+    def add_edge(self, x, y, label=None):
+        """Add an edge from distribution *x* to distribution *y* with the given
+        *label*.
+
+        :type x: :class:`distutils2.database.InstalledDistribution` or
+                 :class:`distutils2.database.EggInfoDistribution`
+        :type y: :class:`distutils2.database.InstalledDistribution` or
+                 :class:`distutils2.database.EggInfoDistribution`
+        :type label: ``str`` or ``None``
+        """
+        self.adjacency_list[x].append((y, label))
+        # multiple edges are allowed, so be careful
+        if x not in self.reverse_list[y]:
+            self.reverse_list[y].append(x)
+
+    def add_missing(self, distribution, requirement):
+        """
+        Add a missing *requirement* for the given *distribution*.
+
+        :type distribution: :class:`distutils2.database.InstalledDistribution`
+                            or :class:`distutils2.database.EggInfoDistribution`
+        :type requirement: ``str``
+        """
+        logger.debug('%s missing %r', distribution, requirement)
+        self.missing.setdefault(distribution, []).append(requirement)
+
+    def _repr_dist(self, dist):
+        return '%s %s' % (dist.name, dist.version)
+
+    def repr_node(self, dist, level=1):
+        """Prints only a subgraph"""
+        output = [self._repr_dist(dist)]
+        for other, label in self.adjacency_list[dist]:
+            dist = self._repr_dist(other)
+            if label is not None:
+                dist = '%s [%s]' % (dist, label)
+            output.append('    ' * level + str(dist))
+            suboutput = self.repr_node(other, level + 1)
+            subs = suboutput.split('\n')
+            output.extend(subs[1:])
+        return '\n'.join(output)
+
+    def to_dot(self, f, skip_disconnected=True):
+        """Writes a DOT output for the graph to the provided file *f*.
+
+        If *skip_disconnected* is set to ``True``, then all distributions
+        that are not dependent on any other distribution are skipped.
+
+        :type f: has to support ``file``-like operations
+        :type skip_disconnected: ``bool``
+        """
+        disconnected = []
+
+        f.write("digraph dependencies {\n")
+        for dist, adjs in self.adjacency_list.items():
+            if len(adjs) == 0 and not skip_disconnected:
+                disconnected.append(dist)
+            for other, label in adjs:
+                if not label is None:
+                    f.write('"%s" -> "%s" [label="%s"]\n' %
+                            (dist.name, other.name, label))
+                else:
+                    f.write('"%s" -> "%s"\n' % (dist.name, other.name))
+        if not skip_disconnected and len(disconnected) > 0:
+            f.write('subgraph disconnected {\n')
+            f.write('label = "Disconnected"\n')
+            f.write('bgcolor = red\n')
+
+            for dist in disconnected:
+                f.write('"%s"' % dist.name)
+                f.write('\n')
+            f.write('}\n')
+        f.write('}\n')
+
+    def topological_sort(self):
+        """
+        Perform a topological sort of the graph.
+        :return: A tuple, the first element of which is a topologically sorted
+                 list of distributions, and the second element of which is a
+                 list of distributions that cannot be sorted because they have
+                 circular dependencies and so form a cycle.
+        """
+        result = []
+        # Make a shallow copy of the adjacency list
+        alist = {}
+        for k, v in self.adjacency_list.items():
+            alist[k] = v[:]
+        while True:
+            # See what we can remove in this run
+            to_remove = []
+            for k, v in list(alist.items())[:]:
+                if not v:
+                    to_remove.append(k)
+                    del alist[k]
+            if not to_remove:
+                # What's left in alist (if anything) is a cycle.
+                break
+            # Remove from the adjacency list of others
+            for k, v in alist.items():
+                alist[k] = [(d, r) for d, r in v if d not in to_remove]
+            logger.debug('Moving to result: %s',
+                         ['%s (%s)' % (d.name, d.version) for d in to_remove])
+            result.extend(to_remove)
+        return result, list(alist.keys())
+
+    def __repr__(self):
+        """Representation of the graph"""
+        output = []
+        for dist, adjs in self.adjacency_list.items():
+            output.append(self.repr_node(dist))
+        return '\n'.join(output)
+
+
+def make_graph(dists, scheme='default'):
+    """Makes a dependency graph from the given distributions.
+
+    :parameter dists: a list of distributions
+    :type dists: list of :class:`distutils2.database.InstalledDistribution` and
+                 :class:`distutils2.database.EggInfoDistribution` instances
+    :rtype: a :class:`DependencyGraph` instance
+    """
+    scheme = get_scheme(scheme)
+    graph = DependencyGraph()
+    provided = {}  # maps names to lists of (version, dist) tuples
+
+    # first, build the graph and find out what's provided
+    for dist in dists:
+        graph.add_distribution(dist)
+
+        for p in dist.provides:
+            name, version = parse_name_and_version(p)
+            logger.debug('Add to provided: %s, %s, %s', name, version, dist)
+            provided.setdefault(name, []).append((version, dist))
+
+    # now make the edges
+    for dist in dists:
+        requires = (dist.run_requires | dist.meta_requires |
+                    dist.build_requires | dist.dev_requires)
+        for req in requires:
+            try:
+                matcher = scheme.matcher(req)
+            except UnsupportedVersionError:
+                # XXX compat-mode if cannot read the version
+                logger.warning('could not read version %r - using name only',
+                               req)
+                name = req.split()[0]
+                matcher = scheme.matcher(name)
+
+            name = matcher.key   # case-insensitive
+
+            matched = False
+            if name in provided:
+                for version, provider in provided[name]:
+                    try:
+                        match = matcher.match(version)
+                    except UnsupportedVersionError:
+                        match = False
+
+                    if match:
+                        graph.add_edge(dist, provider, req)
+                        matched = True
+                        break
+            if not matched:
+                graph.add_missing(dist, req)
+    return graph
+
+
+def get_dependent_dists(dists, dist):
+    """Recursively generate a list of distributions from *dists* that are
+    dependent on *dist*.
+
+    :param dists: a list of distributions
+    :param dist: a distribution, member of *dists* for which we are interested
+    """
+    if dist not in dists:
+        raise DistlibException('given distribution %r is not a member '
+                               'of the list' % dist.name)
+    graph = make_graph(dists)
+
+    dep = [dist]  # dependent distributions
+    todo = graph.reverse_list[dist]  # list of nodes we should inspect
+
+    while todo:
+        d = todo.pop()
+        dep.append(d)
+        for succ in graph.reverse_list[d]:
+            if succ not in dep:
+                todo.append(succ)
+
+    dep.pop(0)  # remove dist from dep, was there to prevent infinite loops
+    return dep
+
+
+def get_required_dists(dists, dist):
+    """Recursively generate a list of distributions from *dists* that are
+    required by *dist*.
+
+    :param dists: a list of distributions
+    :param dist: a distribution, member of *dists* for which we are interested
+                 in finding the dependencies.
+    """
+    if dist not in dists:
+        raise DistlibException('given distribution %r is not a member '
+                               'of the list' % dist.name)
+    graph = make_graph(dists)
+
+    req = set()  # required distributions
+    todo = graph.adjacency_list[dist]  # list of nodes we should inspect
+    seen = set(t[0] for t in todo) # already added to todo
+
+    while todo:
+        d = todo.pop()[0]
+        req.add(d)
+        pred_list = graph.adjacency_list[d]
+        for pred in pred_list:
+            d = pred[0]
+            if d not in req and d not in seen:
+                seen.add(d)
+                todo.append(pred)
+    return req
+
+
+def make_dist(name, version, **kwargs):
+    """
+    A convenience method for making a dist given just a name and version.
+    """
+    summary = kwargs.pop('summary', 'Placeholder for summary')
+    md = Metadata(**kwargs)
+    md.name = name
+    md.version = version
+    md.summary = summary or 'Placeholder for summary'
+    return Distribution(md)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/index.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/index.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b6d129ed690361770738bec73f44ba7e10a21c5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/index.py
@@ -0,0 +1,508 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2013 Vinay Sajip.
+# Licensed to the Python Software Foundation under a contributor agreement.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+import hashlib
+import logging
+import os
+import shutil
+import subprocess
+import tempfile
+try:
+    from threading import Thread
+except ImportError:  # pragma: no cover
+    from dummy_threading import Thread
+
+from . import DistlibException
+from .compat import (HTTPBasicAuthHandler, Request, HTTPPasswordMgr,
+                     urlparse, build_opener, string_types)
+from .util import zip_dir, ServerProxy
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_INDEX = 'https://pypi.org/pypi'
+DEFAULT_REALM = 'pypi'
+
+class PackageIndex(object):
+    """
+    This class represents a package index compatible with PyPI, the Python
+    Package Index.
+    """
+
+    boundary = b'----------ThIs_Is_tHe_distlib_index_bouNdaRY_$'
+
+    def __init__(self, url=None):
+        """
+        Initialise an instance.
+
+        :param url: The URL of the index. If not specified, the URL for PyPI is
+                    used.
+        """
+        self.url = url or DEFAULT_INDEX
+        self.read_configuration()
+        scheme, netloc, path, params, query, frag = urlparse(self.url)
+        if params or query or frag or scheme not in ('http', 'https'):
+            raise DistlibException('invalid repository: %s' % self.url)
+        self.password_handler = None
+        self.ssl_verifier = None
+        self.gpg = None
+        self.gpg_home = None
+        with open(os.devnull, 'w') as sink:
+            # Use gpg by default rather than gpg2, as gpg2 insists on
+            # prompting for passwords
+            for s in ('gpg', 'gpg2'):
+                try:
+                    rc = subprocess.check_call([s, '--version'], stdout=sink,
+                                               stderr=sink)
+                    if rc == 0:
+                        self.gpg = s
+                        break
+                except OSError:
+                    pass
+
+    def _get_pypirc_command(self):
+        """
+        Get the distutils command for interacting with PyPI configurations.
+        :return: the command.
+        """
+        from .util import _get_pypirc_command as cmd
+        return cmd()
+
+    def read_configuration(self):
+        """
+        Read the PyPI access configuration as supported by distutils. This populates
+        ``username``, ``password``, ``realm`` and ``url`` attributes from the
+        configuration.
+        """
+        from .util import _load_pypirc
+        cfg = _load_pypirc(self)
+        self.username = cfg.get('username')
+        self.password = cfg.get('password')
+        self.realm = cfg.get('realm', 'pypi')
+        self.url = cfg.get('repository', self.url)
+
+    def save_configuration(self):
+        """
+        Save the PyPI access configuration. You must have set ``username`` and
+        ``password`` attributes before calling this method.
+        """
+        self.check_credentials()
+        from .util import _store_pypirc
+        _store_pypirc(self)
+
+    def check_credentials(self):
+        """
+        Check that ``username`` and ``password`` have been set, and raise an
+        exception if not.
+        """
+        if self.username is None or self.password is None:
+            raise DistlibException('username and password must be set')
+        pm = HTTPPasswordMgr()
+        _, netloc, _, _, _, _ = urlparse(self.url)
+        pm.add_password(self.realm, netloc, self.username, self.password)
+        self.password_handler = HTTPBasicAuthHandler(pm)
+
+    def register(self, metadata):  # pragma: no cover
+        """
+        Register a distribution on PyPI, using the provided metadata.
+
+        :param metadata: A :class:`Metadata` instance defining at least a name
+                         and version number for the distribution to be
+                         registered.
+        :return: The HTTP response received from PyPI upon submission of the
+                request.
+        """
+        self.check_credentials()
+        metadata.validate()
+        d = metadata.todict()
+        d[':action'] = 'verify'
+        request = self.encode_request(d.items(), [])
+        response = self.send_request(request)
+        d[':action'] = 'submit'
+        request = self.encode_request(d.items(), [])
+        return self.send_request(request)
+
+    def _reader(self, name, stream, outbuf):
+        """
+        Thread runner for reading lines of from a subprocess into a buffer.
+
+        :param name: The logical name of the stream (used for logging only).
+        :param stream: The stream to read from. This will typically a pipe
+                       connected to the output stream of a subprocess.
+        :param outbuf: The list to append the read lines to.
+        """
+        while True:
+            s = stream.readline()
+            if not s:
+                break
+            s = s.decode('utf-8').rstrip()
+            outbuf.append(s)
+            logger.debug('%s: %s' % (name, s))
+        stream.close()
+
+    def get_sign_command(self, filename, signer, sign_password, keystore=None):  # pragma: no cover
+        """
+        Return a suitable command for signing a file.
+
+        :param filename: The pathname to the file to be signed.
+        :param signer: The identifier of the signer of the file.
+        :param sign_password: The passphrase for the signer's
+                              private key used for signing.
+        :param keystore: The path to a directory which contains the keys
+                         used in verification. If not specified, the
+                         instance's ``gpg_home`` attribute is used instead.
+        :return: The signing command as a list suitable to be
+                 passed to :class:`subprocess.Popen`.
+        """
+        cmd = [self.gpg, '--status-fd', '2', '--no-tty']
+        if keystore is None:
+            keystore = self.gpg_home
+        if keystore:
+            cmd.extend(['--homedir', keystore])
+        if sign_password is not None:
+            cmd.extend(['--batch', '--passphrase-fd', '0'])
+        td = tempfile.mkdtemp()
+        sf = os.path.join(td, os.path.basename(filename) + '.asc')
+        cmd.extend(['--detach-sign', '--armor', '--local-user',
+                    signer, '--output', sf, filename])
+        logger.debug('invoking: %s', ' '.join(cmd))
+        return cmd, sf
+
+    def run_command(self, cmd, input_data=None):
+        """
+        Run a command in a child process , passing it any input data specified.
+
+        :param cmd: The command to run.
+        :param input_data: If specified, this must be a byte string containing
+                           data to be sent to the child process.
+        :return: A tuple consisting of the subprocess' exit code, a list of
+                 lines read from the subprocess' ``stdout``, and a list of
+                 lines read from the subprocess' ``stderr``.
+        """
+        kwargs = {
+            'stdout': subprocess.PIPE,
+            'stderr': subprocess.PIPE,
+        }
+        if input_data is not None:
+            kwargs['stdin'] = subprocess.PIPE
+        stdout = []
+        stderr = []
+        p = subprocess.Popen(cmd, **kwargs)
+        # We don't use communicate() here because we may need to
+        # get clever with interacting with the command
+        t1 = Thread(target=self._reader, args=('stdout', p.stdout, stdout))
+        t1.start()
+        t2 = Thread(target=self._reader, args=('stderr', p.stderr, stderr))
+        t2.start()
+        if input_data is not None:
+            p.stdin.write(input_data)
+            p.stdin.close()
+
+        p.wait()
+        t1.join()
+        t2.join()
+        return p.returncode, stdout, stderr
+
+    def sign_file(self, filename, signer, sign_password, keystore=None):  # pragma: no cover
+        """
+        Sign a file.
+
+        :param filename: The pathname to the file to be signed.
+        :param signer: The identifier of the signer of the file.
+        :param sign_password: The passphrase for the signer's
+                              private key used for signing.
+        :param keystore: The path to a directory which contains the keys
+                         used in signing. If not specified, the instance's
+                         ``gpg_home`` attribute is used instead.
+        :return: The absolute pathname of the file where the signature is
+                 stored.
+        """
+        cmd, sig_file = self.get_sign_command(filename, signer, sign_password,
+                                              keystore)
+        rc, stdout, stderr = self.run_command(cmd,
+                                              sign_password.encode('utf-8'))
+        if rc != 0:
+            raise DistlibException('sign command failed with error '
+                                   'code %s' % rc)
+        return sig_file
+
+    def upload_file(self, metadata, filename, signer=None, sign_password=None,
+                    filetype='sdist', pyversion='source', keystore=None):
+        """
+        Upload a release file to the index.
+
+        :param metadata: A :class:`Metadata` instance defining at least a name
+                         and version number for the file to be uploaded.
+        :param filename: The pathname of the file to be uploaded.
+        :param signer: The identifier of the signer of the file.
+        :param sign_password: The passphrase for the signer's
+                              private key used for signing.
+        :param filetype: The type of the file being uploaded. This is the
+                        distutils command which produced that file, e.g.
+                        ``sdist`` or ``bdist_wheel``.
+        :param pyversion: The version of Python which the release relates
+                          to. For code compatible with any Python, this would
+                          be ``source``, otherwise it would be e.g. ``3.2``.
+        :param keystore: The path to a directory which contains the keys
+                         used in signing. If not specified, the instance's
+                         ``gpg_home`` attribute is used instead.
+        :return: The HTTP response received from PyPI upon submission of the
+                request.
+        """
+        self.check_credentials()
+        if not os.path.exists(filename):
+            raise DistlibException('not found: %s' % filename)
+        metadata.validate()
+        d = metadata.todict()
+        sig_file = None
+        if signer:
+            if not self.gpg:
+                logger.warning('no signing program available - not signed')
+            else:
+                sig_file = self.sign_file(filename, signer, sign_password,
+                                          keystore)
+        with open(filename, 'rb') as f:
+            file_data = f.read()
+        md5_digest = hashlib.md5(file_data).hexdigest()
+        sha256_digest = hashlib.sha256(file_data).hexdigest()
+        d.update({
+            ':action': 'file_upload',
+            'protocol_version': '1',
+            'filetype': filetype,
+            'pyversion': pyversion,
+            'md5_digest': md5_digest,
+            'sha256_digest': sha256_digest,
+        })
+        files = [('content', os.path.basename(filename), file_data)]
+        if sig_file:
+            with open(sig_file, 'rb') as f:
+                sig_data = f.read()
+            files.append(('gpg_signature', os.path.basename(sig_file),
+                         sig_data))
+            shutil.rmtree(os.path.dirname(sig_file))
+        request = self.encode_request(d.items(), files)
+        return self.send_request(request)
+
+    def upload_documentation(self, metadata, doc_dir):  # pragma: no cover
+        """
+        Upload documentation to the index.
+
+        :param metadata: A :class:`Metadata` instance defining at least a name
+                         and version number for the documentation to be
+                         uploaded.
+        :param doc_dir: The pathname of the directory which contains the
+                        documentation. This should be the directory that
+                        contains the ``index.html`` for the documentation.
+        :return: The HTTP response received from PyPI upon submission of the
+                request.
+        """
+        self.check_credentials()
+        if not os.path.isdir(doc_dir):
+            raise DistlibException('not a directory: %r' % doc_dir)
+        fn = os.path.join(doc_dir, 'index.html')
+        if not os.path.exists(fn):
+            raise DistlibException('not found: %r' % fn)
+        metadata.validate()
+        name, version = metadata.name, metadata.version
+        zip_data = zip_dir(doc_dir).getvalue()
+        fields = [(':action', 'doc_upload'),
+                  ('name', name), ('version', version)]
+        files = [('content', name, zip_data)]
+        request = self.encode_request(fields, files)
+        return self.send_request(request)
+
+    def get_verify_command(self, signature_filename, data_filename,
+                           keystore=None):
+        """
+        Return a suitable command for verifying a file.
+
+        :param signature_filename: The pathname to the file containing the
+                                   signature.
+        :param data_filename: The pathname to the file containing the
+                              signed data.
+        :param keystore: The path to a directory which contains the keys
+                         used in verification. If not specified, the
+                         instance's ``gpg_home`` attribute is used instead.
+        :return: The verifying command as a list suitable to be
+                 passed to :class:`subprocess.Popen`.
+        """
+        cmd = [self.gpg, '--status-fd', '2', '--no-tty']
+        if keystore is None:
+            keystore = self.gpg_home
+        if keystore:
+            cmd.extend(['--homedir', keystore])
+        cmd.extend(['--verify', signature_filename, data_filename])
+        logger.debug('invoking: %s', ' '.join(cmd))
+        return cmd
+
+    def verify_signature(self, signature_filename, data_filename,
+                         keystore=None):
+        """
+        Verify a signature for a file.
+
+        :param signature_filename: The pathname to the file containing the
+                                   signature.
+        :param data_filename: The pathname to the file containing the
+                              signed data.
+        :param keystore: The path to a directory which contains the keys
+                         used in verification. If not specified, the
+                         instance's ``gpg_home`` attribute is used instead.
+        :return: True if the signature was verified, else False.
+        """
+        if not self.gpg:
+            raise DistlibException('verification unavailable because gpg '
+                                   'unavailable')
+        cmd = self.get_verify_command(signature_filename, data_filename,
+                                      keystore)
+        rc, stdout, stderr = self.run_command(cmd)
+        if rc not in (0, 1):
+            raise DistlibException('verify command failed with error '
+                             'code %s' % rc)
+        return rc == 0
+
+    def download_file(self, url, destfile, digest=None, reporthook=None):
+        """
+        This is a convenience method for downloading a file from an URL.
+        Normally, this will be a file from the index, though currently
+        no check is made for this (i.e. a file can be downloaded from
+        anywhere).
+
+        The method is just like the :func:`urlretrieve` function in the
+        standard library, except that it allows digest computation to be
+        done during download and checking that the downloaded data
+        matched any expected value.
+
+        :param url: The URL of the file to be downloaded (assumed to be
+                    available via an HTTP GET request).
+        :param destfile: The pathname where the downloaded file is to be
+                         saved.
+        :param digest: If specified, this must be a (hasher, value)
+                       tuple, where hasher is the algorithm used (e.g.
+                       ``'md5'``) and ``value`` is the expected value.
+        :param reporthook: The same as for :func:`urlretrieve` in the
+                           standard library.
+        """
+        if digest is None:
+            digester = None
+            logger.debug('No digest specified')
+        else:
+            if isinstance(digest, (list, tuple)):
+                hasher, digest = digest
+            else:
+                hasher = 'md5'
+            digester = getattr(hashlib, hasher)()
+            logger.debug('Digest specified: %s' % digest)
+        # The following code is equivalent to urlretrieve.
+        # We need to do it this way so that we can compute the
+        # digest of the file as we go.
+        with open(destfile, 'wb') as dfp:
+            # addinfourl is not a context manager on 2.x
+            # so we have to use try/finally
+            sfp = self.send_request(Request(url))
+            try:
+                headers = sfp.info()
+                blocksize = 8192
+                size = -1
+                read = 0
+                blocknum = 0
+                if "content-length" in headers:
+                    size = int(headers["Content-Length"])
+                if reporthook:
+                    reporthook(blocknum, blocksize, size)
+                while True:
+                    block = sfp.read(blocksize)
+                    if not block:
+                        break
+                    read += len(block)
+                    dfp.write(block)
+                    if digester:
+                        digester.update(block)
+                    blocknum += 1
+                    if reporthook:
+                        reporthook(blocknum, blocksize, size)
+            finally:
+                sfp.close()
+
+        # check that we got the whole file, if we can
+        if size >= 0 and read < size:
+            raise DistlibException(
+                'retrieval incomplete: got only %d out of %d bytes'
+                % (read, size))
+        # if we have a digest, it must match.
+        if digester:
+            actual = digester.hexdigest()
+            if digest != actual:
+                raise DistlibException('%s digest mismatch for %s: expected '
+                                       '%s, got %s' % (hasher, destfile,
+                                                       digest, actual))
+            logger.debug('Digest verified: %s', digest)
+
+    def send_request(self, req):
+        """
+        Send a standard library :class:`Request` to PyPI and return its
+        response.
+
+        :param req: The request to send.
+        :return: The HTTP response from PyPI (a standard library HTTPResponse).
+        """
+        handlers = []
+        if self.password_handler:
+            handlers.append(self.password_handler)
+        if self.ssl_verifier:
+            handlers.append(self.ssl_verifier)
+        opener = build_opener(*handlers)
+        return opener.open(req)
+
+    def encode_request(self, fields, files):
+        """
+        Encode fields and files for posting to an HTTP server.
+
+        :param fields: The fields to send as a list of (fieldname, value)
+                       tuples.
+        :param files: The files to send as a list of (fieldname, filename,
+                      file_bytes) tuple.
+        """
+        # Adapted from packaging, which in turn was adapted from
+        # http://code.activestate.com/recipes/146306
+
+        parts = []
+        boundary = self.boundary
+        for k, values in fields:
+            if not isinstance(values, (list, tuple)):
+                values = [values]
+
+            for v in values:
+                parts.extend((
+                    b'--' + boundary,
+                    ('Content-Disposition: form-data; name="%s"' %
+                     k).encode('utf-8'),
+                    b'',
+                    v.encode('utf-8')))
+        for key, filename, value in files:
+            parts.extend((
+                b'--' + boundary,
+                ('Content-Disposition: form-data; name="%s"; filename="%s"' %
+                 (key, filename)).encode('utf-8'),
+                b'',
+                value))
+
+        parts.extend((b'--' + boundary + b'--', b''))
+
+        body = b'\r\n'.join(parts)
+        ct = b'multipart/form-data; boundary=' + boundary
+        headers = {
+            'Content-type': ct,
+            'Content-length': str(len(body))
+        }
+        return Request(self.url, body, headers)
+
+    def search(self, terms, operator=None):  # pragma: no cover
+        if isinstance(terms, string_types):
+            terms = {'name': terms}
+        rpc_proxy = ServerProxy(self.url, timeout=3.0)
+        try:
+            return rpc_proxy.search(terms, operator or 'and')
+        finally:
+            rpc_proxy('close')()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/locators.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/locators.py
new file mode 100644
index 0000000000000000000000000000000000000000..966ebc0e37d6104a8e0e1fefe9dc526f39409ce2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/locators.py
@@ -0,0 +1,1300 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2012-2015 Vinay Sajip.
+# Licensed to the Python Software Foundation under a contributor agreement.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+
+import gzip
+from io import BytesIO
+import json
+import logging
+import os
+import posixpath
+import re
+try:
+    import threading
+except ImportError:  # pragma: no cover
+    import dummy_threading as threading
+import zlib
+
+from . import DistlibException
+from .compat import (urljoin, urlparse, urlunparse, url2pathname, pathname2url,
+                     queue, quote, unescape, build_opener,
+                     HTTPRedirectHandler as BaseRedirectHandler, text_type,
+                     Request, HTTPError, URLError)
+from .database import Distribution, DistributionPath, make_dist
+from .metadata import Metadata, MetadataInvalidError
+from .util import (cached_property, ensure_slash, split_filename, get_project_data,
+                   parse_requirement, parse_name_and_version, ServerProxy,
+                   normalize_name)
+from .version import get_scheme, UnsupportedVersionError
+from .wheel import Wheel, is_compatible
+
+logger = logging.getLogger(__name__)
+
+HASHER_HASH = re.compile(r'^(\w+)=([a-f0-9]+)')
+CHARSET = re.compile(r';\s*charset\s*=\s*(.*)\s*$', re.I)
+HTML_CONTENT_TYPE = re.compile('text/html|application/x(ht)?ml')
+DEFAULT_INDEX = 'https://pypi.org/pypi'
+
+def get_all_distribution_names(url=None):
+    """
+    Return all distribution names known by an index.
+    :param url: The URL of the index.
+    :return: A list of all known distribution names.
+    """
+    if url is None:
+        url = DEFAULT_INDEX
+    client = ServerProxy(url, timeout=3.0)
+    try:
+        return client.list_packages()
+    finally:
+        client('close')()
+
+class RedirectHandler(BaseRedirectHandler):
+    """
+    A class to work around a bug in some Python 3.2.x releases.
+    """
+    # There's a bug in the base version for some 3.2.x
+    # (e.g. 3.2.2 on Ubuntu Oneiric). If a Location header
+    # returns e.g. /abc, it bails because it says the scheme ''
+    # is bogus, when actually it should use the request's
+    # URL for the scheme. See Python issue #13696.
+    def http_error_302(self, req, fp, code, msg, headers):
+        # Some servers (incorrectly) return multiple Location headers
+        # (so probably same goes for URI).  Use first header.
+        newurl = None
+        for key in ('location', 'uri'):
+            if key in headers:
+                newurl = headers[key]
+                break
+        if newurl is None:  # pragma: no cover
+            return
+        urlparts = urlparse(newurl)
+        if urlparts.scheme == '':
+            newurl = urljoin(req.get_full_url(), newurl)
+            if hasattr(headers, 'replace_header'):
+                headers.replace_header(key, newurl)
+            else:
+                headers[key] = newurl
+        return BaseRedirectHandler.http_error_302(self, req, fp, code, msg,
+                                                  headers)
+
+    http_error_301 = http_error_303 = http_error_307 = http_error_302
+
+class Locator(object):
+    """
+    A base class for locators - things that locate distributions.
+    """
+    source_extensions = ('.tar.gz', '.tar.bz2', '.tar', '.zip', '.tgz', '.tbz')
+    binary_extensions = ('.egg', '.exe', '.whl')
+    excluded_extensions = ('.pdf',)
+
+    # A list of tags indicating which wheels you want to match. The default
+    # value of None matches against the tags compatible with the running
+    # Python. If you want to match other values, set wheel_tags on a locator
+    # instance to a list of tuples (pyver, abi, arch) which you want to match.
+    wheel_tags = None
+
+    downloadable_extensions = source_extensions + ('.whl',)
+
+    def __init__(self, scheme='default'):
+        """
+        Initialise an instance.
+        :param scheme: Because locators look for most recent versions, they
+                       need to know the version scheme to use. This specifies
+                       the current PEP-recommended scheme - use ``'legacy'``
+                       if you need to support existing distributions on PyPI.
+        """
+        self._cache = {}
+        self.scheme = scheme
+        # Because of bugs in some of the handlers on some of the platforms,
+        # we use our own opener rather than just using urlopen.
+        self.opener = build_opener(RedirectHandler())
+        # If get_project() is called from locate(), the matcher instance
+        # is set from the requirement passed to locate(). See issue #18 for
+        # why this can be useful to know.
+        self.matcher = None
+        self.errors = queue.Queue()
+
+    def get_errors(self):
+        """
+        Return any errors which have occurred.
+        """
+        result = []
+        while not self.errors.empty():  # pragma: no cover
+            try:
+                e = self.errors.get(False)
+                result.append(e)
+            except self.errors.Empty:
+                continue
+            self.errors.task_done()
+        return result
+
+    def clear_errors(self):
+        """
+        Clear any errors which may have been logged.
+        """
+        # Just get the errors and throw them away
+        self.get_errors()
+
+    def clear_cache(self):
+        self._cache.clear()
+
+    def _get_scheme(self):
+        return self._scheme
+
+    def _set_scheme(self, value):
+        self._scheme = value
+
+    scheme = property(_get_scheme, _set_scheme)
+
+    def _get_project(self, name):
+        """
+        For a given project, get a dictionary mapping available versions to Distribution
+        instances.
+
+        This should be implemented in subclasses.
+
+        If called from a locate() request, self.matcher will be set to a
+        matcher for the requirement to satisfy, otherwise it will be None.
+        """
+        raise NotImplementedError('Please implement in the subclass')
+
+    def get_distribution_names(self):
+        """
+        Return all the distribution names known to this locator.
+        """
+        raise NotImplementedError('Please implement in the subclass')
+
+    def get_project(self, name):
+        """
+        For a given project, get a dictionary mapping available versions to Distribution
+        instances.
+
+        This calls _get_project to do all the work, and just implements a caching layer on top.
+        """
+        if self._cache is None:  # pragma: no cover
+            result = self._get_project(name)
+        elif name in self._cache:
+            result = self._cache[name]
+        else:
+            self.clear_errors()
+            result = self._get_project(name)
+            self._cache[name] = result
+        return result
+
+    def score_url(self, url):
+        """
+        Give an url a score which can be used to choose preferred URLs
+        for a given project release.
+        """
+        t = urlparse(url)
+        basename = posixpath.basename(t.path)
+        compatible = True
+        is_wheel = basename.endswith('.whl')
+        is_downloadable = basename.endswith(self.downloadable_extensions)
+        if is_wheel:
+            compatible = is_compatible(Wheel(basename), self.wheel_tags)
+        return (t.scheme == 'https', 'pypi.org' in t.netloc,
+                is_downloadable, is_wheel, compatible, basename)
+
+    def prefer_url(self, url1, url2):
+        """
+        Choose one of two URLs where both are candidates for distribution
+        archives for the same version of a distribution (for example,
+        .tar.gz vs. zip).
+
+        The current implementation favours https:// URLs over http://, archives
+        from PyPI over those from other locations, wheel compatibility (if a
+        wheel) and then the archive name.
+        """
+        result = url2
+        if url1:
+            s1 = self.score_url(url1)
+            s2 = self.score_url(url2)
+            if s1 > s2:
+                result = url1
+            if result != url2:
+                logger.debug('Not replacing %r with %r', url1, url2)
+            else:
+                logger.debug('Replacing %r with %r', url1, url2)
+        return result
+
+    def split_filename(self, filename, project_name):
+        """
+        Attempt to split a filename in project name, version and Python version.
+        """
+        return split_filename(filename, project_name)
+
+    def convert_url_to_download_info(self, url, project_name):
+        """
+        See if a URL is a candidate for a download URL for a project (the URL
+        has typically been scraped from an HTML page).
+
+        If it is, a dictionary is returned with keys "name", "version",
+        "filename" and "url"; otherwise, None is returned.
+        """
+        def same_project(name1, name2):
+            return normalize_name(name1) == normalize_name(name2)
+
+        result = None
+        scheme, netloc, path, params, query, frag = urlparse(url)
+        if frag.lower().startswith('egg='):  # pragma: no cover
+            logger.debug('%s: version hint in fragment: %r',
+                         project_name, frag)
+        m = HASHER_HASH.match(frag)
+        if m:
+            algo, digest = m.groups()
+        else:
+            algo, digest = None, None
+        origpath = path
+        if path and path[-1] == '/':  # pragma: no cover
+            path = path[:-1]
+        if path.endswith('.whl'):
+            try:
+                wheel = Wheel(path)
+                if not is_compatible(wheel, self.wheel_tags):
+                    logger.debug('Wheel not compatible: %s', path)
+                else:
+                    if project_name is None:
+                        include = True
+                    else:
+                        include = same_project(wheel.name, project_name)
+                    if include:
+                        result = {
+                            'name': wheel.name,
+                            'version': wheel.version,
+                            'filename': wheel.filename,
+                            'url': urlunparse((scheme, netloc, origpath,
+                                               params, query, '')),
+                            'python-version': ', '.join(
+                                ['.'.join(list(v[2:])) for v in wheel.pyver]),
+                        }
+            except Exception as e:  # pragma: no cover
+                logger.warning('invalid path for wheel: %s', path)
+        elif not path.endswith(self.downloadable_extensions):  # pragma: no cover
+            logger.debug('Not downloadable: %s', path)
+        else:  # downloadable extension
+            path = filename = posixpath.basename(path)
+            for ext in self.downloadable_extensions:
+                if path.endswith(ext):
+                    path = path[:-len(ext)]
+                    t = self.split_filename(path, project_name)
+                    if not t:  # pragma: no cover
+                        logger.debug('No match for project/version: %s', path)
+                    else:
+                        name, version, pyver = t
+                        if not project_name or same_project(project_name, name):
+                            result = {
+                                'name': name,
+                                'version': version,
+                                'filename': filename,
+                                'url': urlunparse((scheme, netloc, origpath,
+                                                   params, query, '')),
+                                #'packagetype': 'sdist',
+                            }
+                            if pyver:  # pragma: no cover
+                                result['python-version'] = pyver
+                    break
+        if result and algo:
+            result['%s_digest' % algo] = digest
+        return result
+
+    def _get_digest(self, info):
+        """
+        Get a digest from a dictionary by looking at a "digests" dictionary
+        or keys of the form 'algo_digest'.
+
+        Returns a 2-tuple (algo, digest) if found, else None. Currently
+        looks only for SHA256, then MD5.
+        """
+        result = None
+        if 'digests' in info:
+            digests = info['digests']
+            for algo in ('sha256', 'md5'):
+                if algo in digests:
+                    result = (algo, digests[algo])
+                    break
+        if not result:
+            for algo in ('sha256', 'md5'):
+                key = '%s_digest' % algo
+                if key in info:
+                    result = (algo, info[key])
+                    break
+        return result
+
+    def _update_version_data(self, result, info):
+        """
+        Update a result dictionary (the final result from _get_project) with a
+        dictionary for a specific version, which typically holds information
+        gleaned from a filename or URL for an archive for the distribution.
+        """
+        name = info.pop('name')
+        version = info.pop('version')
+        if version in result:
+            dist = result[version]
+            md = dist.metadata
+        else:
+            dist = make_dist(name, version, scheme=self.scheme)
+            md = dist.metadata
+        dist.digest = digest = self._get_digest(info)
+        url = info['url']
+        result['digests'][url] = digest
+        if md.source_url != info['url']:
+            md.source_url = self.prefer_url(md.source_url, url)
+            result['urls'].setdefault(version, set()).add(url)
+        dist.locator = self
+        result[version] = dist
+
+    def locate(self, requirement, prereleases=False):
+        """
+        Find the most recent distribution which matches the given
+        requirement.
+
+        :param requirement: A requirement of the form 'foo (1.0)' or perhaps
+                            'foo (>= 1.0, < 2.0, != 1.3)'
+        :param prereleases: If ``True``, allow pre-release versions
+                            to be located. Otherwise, pre-release versions
+                            are not returned.
+        :return: A :class:`Distribution` instance, or ``None`` if no such
+                 distribution could be located.
+        """
+        result = None
+        r = parse_requirement(requirement)
+        if r is None:  # pragma: no cover
+            raise DistlibException('Not a valid requirement: %r' % requirement)
+        scheme = get_scheme(self.scheme)
+        self.matcher = matcher = scheme.matcher(r.requirement)
+        logger.debug('matcher: %s (%s)', matcher, type(matcher).__name__)
+        versions = self.get_project(r.name)
+        if len(versions) > 2:   # urls and digests keys are present
+            # sometimes, versions are invalid
+            slist = []
+            vcls = matcher.version_class
+            for k in versions:
+                if k in ('urls', 'digests'):
+                    continue
+                try:
+                    if not matcher.match(k):
+                        pass  # logger.debug('%s did not match %r', matcher, k)
+                    else:
+                        if prereleases or not vcls(k).is_prerelease:
+                            slist.append(k)
+                        # else:
+                            # logger.debug('skipping pre-release '
+                                         # 'version %s of %s', k, matcher.name)
+                except Exception:  # pragma: no cover
+                    logger.warning('error matching %s with %r', matcher, k)
+                    pass # slist.append(k)
+            if len(slist) > 1:
+                slist = sorted(slist, key=scheme.key)
+            if slist:
+                logger.debug('sorted list: %s', slist)
+                version = slist[-1]
+                result = versions[version]
+        if result:
+            if r.extras:
+                result.extras = r.extras
+            result.download_urls = versions.get('urls', {}).get(version, set())
+            d = {}
+            sd = versions.get('digests', {})
+            for url in result.download_urls:
+                if url in sd:  # pragma: no cover
+                    d[url] = sd[url]
+            result.digests = d
+        self.matcher = None
+        return result
+
+
+class PyPIRPCLocator(Locator):
+    """
+    This locator uses XML-RPC to locate distributions. It therefore
+    cannot be used with simple mirrors (that only mirror file content).
+    """
+    def __init__(self, url, **kwargs):
+        """
+        Initialise an instance.
+
+        :param url: The URL to use for XML-RPC.
+        :param kwargs: Passed to the superclass constructor.
+        """
+        super(PyPIRPCLocator, self).__init__(**kwargs)
+        self.base_url = url
+        self.client = ServerProxy(url, timeout=3.0)
+
+    def get_distribution_names(self):
+        """
+        Return all the distribution names known to this locator.
+        """
+        return set(self.client.list_packages())
+
+    def _get_project(self, name):
+        result = {'urls': {}, 'digests': {}}
+        versions = self.client.package_releases(name, True)
+        for v in versions:
+            urls = self.client.release_urls(name, v)
+            data = self.client.release_data(name, v)
+            metadata = Metadata(scheme=self.scheme)
+            metadata.name = data['name']
+            metadata.version = data['version']
+            metadata.license = data.get('license')
+            metadata.keywords = data.get('keywords', [])
+            metadata.summary = data.get('summary')
+            dist = Distribution(metadata)
+            if urls:
+                info = urls[0]
+                metadata.source_url = info['url']
+                dist.digest = self._get_digest(info)
+                dist.locator = self
+                result[v] = dist
+                for info in urls:
+                    url = info['url']
+                    digest = self._get_digest(info)
+                    result['urls'].setdefault(v, set()).add(url)
+                    result['digests'][url] = digest
+        return result
+
+class PyPIJSONLocator(Locator):
+    """
+    This locator uses PyPI's JSON interface. It's very limited in functionality
+    and probably not worth using.
+    """
+    def __init__(self, url, **kwargs):
+        super(PyPIJSONLocator, self).__init__(**kwargs)
+        self.base_url = ensure_slash(url)
+
+    def get_distribution_names(self):
+        """
+        Return all the distribution names known to this locator.
+        """
+        raise NotImplementedError('Not available from this locator')
+
+    def _get_project(self, name):
+        result = {'urls': {}, 'digests': {}}
+        url = urljoin(self.base_url, '%s/json' % quote(name))
+        try:
+            resp = self.opener.open(url)
+            data = resp.read().decode() # for now
+            d = json.loads(data)
+            md = Metadata(scheme=self.scheme)
+            data = d['info']
+            md.name = data['name']
+            md.version = data['version']
+            md.license = data.get('license')
+            md.keywords = data.get('keywords', [])
+            md.summary = data.get('summary')
+            dist = Distribution(md)
+            dist.locator = self
+            urls = d['urls']
+            result[md.version] = dist
+            for info in d['urls']:
+                url = info['url']
+                dist.download_urls.add(url)
+                dist.digests[url] = self._get_digest(info)
+                result['urls'].setdefault(md.version, set()).add(url)
+                result['digests'][url] = self._get_digest(info)
+            # Now get other releases
+            for version, infos in d['releases'].items():
+                if version == md.version:
+                    continue    # already done
+                omd = Metadata(scheme=self.scheme)
+                omd.name = md.name
+                omd.version = version
+                odist = Distribution(omd)
+                odist.locator = self
+                result[version] = odist
+                for info in infos:
+                    url = info['url']
+                    odist.download_urls.add(url)
+                    odist.digests[url] = self._get_digest(info)
+                    result['urls'].setdefault(version, set()).add(url)
+                    result['digests'][url] = self._get_digest(info)
+#            for info in urls:
+#                md.source_url = info['url']
+#                dist.digest = self._get_digest(info)
+#                dist.locator = self
+#                for info in urls:
+#                    url = info['url']
+#                    result['urls'].setdefault(md.version, set()).add(url)
+#                    result['digests'][url] = self._get_digest(info)
+        except Exception as e:
+            self.errors.put(text_type(e))
+            logger.exception('JSON fetch failed: %s', e)
+        return result
+
+
+class Page(object):
+    """
+    This class represents a scraped HTML page.
+    """
+    # The following slightly hairy-looking regex just looks for the contents of
+    # an anchor link, which has an attribute "href" either immediately preceded
+    # or immediately followed by a "rel" attribute. The attribute values can be
+    # declared with double quotes, single quotes or no quotes - which leads to
+    # the length of the expression.
+    _href = re.compile("""
+(rel\\s*=\\s*(?:"(?P[^"]*)"|'(?P[^']*)'|(?P[^>\\s\n]*))\\s+)?
+href\\s*=\\s*(?:"(?P[^"]*)"|'(?P[^']*)'|(?P[^>\\s\n]*))
+(\\s+rel\\s*=\\s*(?:"(?P[^"]*)"|'(?P[^']*)'|(?P[^>\\s\n]*)))?
+""", re.I | re.S | re.X)
+    _base = re.compile(r"""]+)""", re.I | re.S)
+
+    def __init__(self, data, url):
+        """
+        Initialise an instance with the Unicode page contents and the URL they
+        came from.
+        """
+        self.data = data
+        self.base_url = self.url = url
+        m = self._base.search(self.data)
+        if m:
+            self.base_url = m.group(1)
+
+    _clean_re = re.compile(r'[^a-z0-9$&+,/:;=?@.#%_\\|-]', re.I)
+
+    @cached_property
+    def links(self):
+        """
+        Return the URLs of all the links on a page together with information
+        about their "rel" attribute, for determining which ones to treat as
+        downloads and which ones to queue for further scraping.
+        """
+        def clean(url):
+            "Tidy up an URL."
+            scheme, netloc, path, params, query, frag = urlparse(url)
+            return urlunparse((scheme, netloc, quote(path),
+                               params, query, frag))
+
+        result = set()
+        for match in self._href.finditer(self.data):
+            d = match.groupdict('')
+            rel = (d['rel1'] or d['rel2'] or d['rel3'] or
+                   d['rel4'] or d['rel5'] or d['rel6'])
+            url = d['url1'] or d['url2'] or d['url3']
+            url = urljoin(self.base_url, url)
+            url = unescape(url)
+            url = self._clean_re.sub(lambda m: '%%%2x' % ord(m.group(0)), url)
+            result.add((url, rel))
+        # We sort the result, hoping to bring the most recent versions
+        # to the front
+        result = sorted(result, key=lambda t: t[0], reverse=True)
+        return result
+
+
+class SimpleScrapingLocator(Locator):
+    """
+    A locator which scrapes HTML pages to locate downloads for a distribution.
+    This runs multiple threads to do the I/O; performance is at least as good
+    as pip's PackageFinder, which works in an analogous fashion.
+    """
+
+    # These are used to deal with various Content-Encoding schemes.
+    decoders = {
+        'deflate': zlib.decompress,
+        'gzip': lambda b: gzip.GzipFile(fileobj=BytesIO(b)).read(),
+        'none': lambda b: b,
+    }
+
+    def __init__(self, url, timeout=None, num_workers=10, **kwargs):
+        """
+        Initialise an instance.
+        :param url: The root URL to use for scraping.
+        :param timeout: The timeout, in seconds, to be applied to requests.
+                        This defaults to ``None`` (no timeout specified).
+        :param num_workers: The number of worker threads you want to do I/O,
+                            This defaults to 10.
+        :param kwargs: Passed to the superclass.
+        """
+        super(SimpleScrapingLocator, self).__init__(**kwargs)
+        self.base_url = ensure_slash(url)
+        self.timeout = timeout
+        self._page_cache = {}
+        self._seen = set()
+        self._to_fetch = queue.Queue()
+        self._bad_hosts = set()
+        self.skip_externals = False
+        self.num_workers = num_workers
+        self._lock = threading.RLock()
+        # See issue #45: we need to be resilient when the locator is used
+        # in a thread, e.g. with concurrent.futures. We can't use self._lock
+        # as it is for coordinating our internal threads - the ones created
+        # in _prepare_threads.
+        self._gplock = threading.RLock()
+        self.platform_check = False  # See issue #112
+
+    def _prepare_threads(self):
+        """
+        Threads are created only when get_project is called, and terminate
+        before it returns. They are there primarily to parallelise I/O (i.e.
+        fetching web pages).
+        """
+        self._threads = []
+        for i in range(self.num_workers):
+            t = threading.Thread(target=self._fetch)
+            t.daemon = True
+            t.start()
+            self._threads.append(t)
+
+    def _wait_threads(self):
+        """
+        Tell all the threads to terminate (by sending a sentinel value) and
+        wait for them to do so.
+        """
+        # Note that you need two loops, since you can't say which
+        # thread will get each sentinel
+        for t in self._threads:
+            self._to_fetch.put(None)    # sentinel
+        for t in self._threads:
+            t.join()
+        self._threads = []
+
+    def _get_project(self, name):
+        result = {'urls': {}, 'digests': {}}
+        with self._gplock:
+            self.result = result
+            self.project_name = name
+            url = urljoin(self.base_url, '%s/' % quote(name))
+            self._seen.clear()
+            self._page_cache.clear()
+            self._prepare_threads()
+            try:
+                logger.debug('Queueing %s', url)
+                self._to_fetch.put(url)
+                self._to_fetch.join()
+            finally:
+                self._wait_threads()
+            del self.result
+        return result
+
+    platform_dependent = re.compile(r'\b(linux_(i\d86|x86_64|arm\w+)|'
+                                    r'win(32|_amd64)|macosx_?\d+)\b', re.I)
+
+    def _is_platform_dependent(self, url):
+        """
+        Does an URL refer to a platform-specific download?
+        """
+        return self.platform_dependent.search(url)
+
+    def _process_download(self, url):
+        """
+        See if an URL is a suitable download for a project.
+
+        If it is, register information in the result dictionary (for
+        _get_project) about the specific version it's for.
+
+        Note that the return value isn't actually used other than as a boolean
+        value.
+        """
+        if self.platform_check and self._is_platform_dependent(url):
+            info = None
+        else:
+            info = self.convert_url_to_download_info(url, self.project_name)
+        logger.debug('process_download: %s -> %s', url, info)
+        if info:
+            with self._lock:    # needed because self.result is shared
+                self._update_version_data(self.result, info)
+        return info
+
+    def _should_queue(self, link, referrer, rel):
+        """
+        Determine whether a link URL from a referring page and with a
+        particular "rel" attribute should be queued for scraping.
+        """
+        scheme, netloc, path, _, _, _ = urlparse(link)
+        if path.endswith(self.source_extensions + self.binary_extensions +
+                         self.excluded_extensions):
+            result = False
+        elif self.skip_externals and not link.startswith(self.base_url):
+            result = False
+        elif not referrer.startswith(self.base_url):
+            result = False
+        elif rel not in ('homepage', 'download'):
+            result = False
+        elif scheme not in ('http', 'https', 'ftp'):
+            result = False
+        elif self._is_platform_dependent(link):
+            result = False
+        else:
+            host = netloc.split(':', 1)[0]
+            if host.lower() == 'localhost':
+                result = False
+            else:
+                result = True
+        logger.debug('should_queue: %s (%s) from %s -> %s', link, rel,
+                     referrer, result)
+        return result
+
+    def _fetch(self):
+        """
+        Get a URL to fetch from the work queue, get the HTML page, examine its
+        links for download candidates and candidates for further scraping.
+
+        This is a handy method to run in a thread.
+        """
+        while True:
+            url = self._to_fetch.get()
+            try:
+                if url:
+                    page = self.get_page(url)
+                    if page is None:    # e.g. after an error
+                        continue
+                    for link, rel in page.links:
+                        if link not in self._seen:
+                            try:
+                                self._seen.add(link)
+                                if (not self._process_download(link) and
+                                    self._should_queue(link, url, rel)):
+                                    logger.debug('Queueing %s from %s', link, url)
+                                    self._to_fetch.put(link)
+                            except MetadataInvalidError:  # e.g. invalid versions
+                                pass
+            except Exception as e:  # pragma: no cover
+                self.errors.put(text_type(e))
+            finally:
+                # always do this, to avoid hangs :-)
+                self._to_fetch.task_done()
+            if not url:
+                #logger.debug('Sentinel seen, quitting.')
+                break
+
+    def get_page(self, url):
+        """
+        Get the HTML for an URL, possibly from an in-memory cache.
+
+        XXX TODO Note: this cache is never actually cleared. It's assumed that
+        the data won't get stale over the lifetime of a locator instance (not
+        necessarily true for the default_locator).
+        """
+        # http://peak.telecommunity.com/DevCenter/EasyInstall#package-index-api
+        scheme, netloc, path, _, _, _ = urlparse(url)
+        if scheme == 'file' and os.path.isdir(url2pathname(path)):
+            url = urljoin(ensure_slash(url), 'index.html')
+
+        if url in self._page_cache:
+            result = self._page_cache[url]
+            logger.debug('Returning %s from cache: %s', url, result)
+        else:
+            host = netloc.split(':', 1)[0]
+            result = None
+            if host in self._bad_hosts:
+                logger.debug('Skipping %s due to bad host %s', url, host)
+            else:
+                req = Request(url, headers={'Accept-encoding': 'identity'})
+                try:
+                    logger.debug('Fetching %s', url)
+                    resp = self.opener.open(req, timeout=self.timeout)
+                    logger.debug('Fetched %s', url)
+                    headers = resp.info()
+                    content_type = headers.get('Content-Type', '')
+                    if HTML_CONTENT_TYPE.match(content_type):
+                        final_url = resp.geturl()
+                        data = resp.read()
+                        encoding = headers.get('Content-Encoding')
+                        if encoding:
+                            decoder = self.decoders[encoding]   # fail if not found
+                            data = decoder(data)
+                        encoding = 'utf-8'
+                        m = CHARSET.search(content_type)
+                        if m:
+                            encoding = m.group(1)
+                        try:
+                            data = data.decode(encoding)
+                        except UnicodeError:  # pragma: no cover
+                            data = data.decode('latin-1')    # fallback
+                        result = Page(data, final_url)
+                        self._page_cache[final_url] = result
+                except HTTPError as e:
+                    if e.code != 404:
+                        logger.exception('Fetch failed: %s: %s', url, e)
+                except URLError as e:  # pragma: no cover
+                    logger.exception('Fetch failed: %s: %s', url, e)
+                    with self._lock:
+                        self._bad_hosts.add(host)
+                except Exception as e:  # pragma: no cover
+                    logger.exception('Fetch failed: %s: %s', url, e)
+                finally:
+                    self._page_cache[url] = result   # even if None (failure)
+        return result
+
+    _distname_re = re.compile(']*>([^<]+)<')
+
+    def get_distribution_names(self):
+        """
+        Return all the distribution names known to this locator.
+        """
+        result = set()
+        page = self.get_page(self.base_url)
+        if not page:
+            raise DistlibException('Unable to get %s' % self.base_url)
+        for match in self._distname_re.finditer(page.data):
+            result.add(match.group(1))
+        return result
+
+class DirectoryLocator(Locator):
+    """
+    This class locates distributions in a directory tree.
+    """
+
+    def __init__(self, path, **kwargs):
+        """
+        Initialise an instance.
+        :param path: The root of the directory tree to search.
+        :param kwargs: Passed to the superclass constructor,
+                       except for:
+                       * recursive - if True (the default), subdirectories are
+                         recursed into. If False, only the top-level directory
+                         is searched,
+        """
+        self.recursive = kwargs.pop('recursive', True)
+        super(DirectoryLocator, self).__init__(**kwargs)
+        path = os.path.abspath(path)
+        if not os.path.isdir(path):  # pragma: no cover
+            raise DistlibException('Not a directory: %r' % path)
+        self.base_dir = path
+
+    def should_include(self, filename, parent):
+        """
+        Should a filename be considered as a candidate for a distribution
+        archive? As well as the filename, the directory which contains it
+        is provided, though not used by the current implementation.
+        """
+        return filename.endswith(self.downloadable_extensions)
+
+    def _get_project(self, name):
+        result = {'urls': {}, 'digests': {}}
+        for root, dirs, files in os.walk(self.base_dir):
+            for fn in files:
+                if self.should_include(fn, root):
+                    fn = os.path.join(root, fn)
+                    url = urlunparse(('file', '',
+                                      pathname2url(os.path.abspath(fn)),
+                                      '', '', ''))
+                    info = self.convert_url_to_download_info(url, name)
+                    if info:
+                        self._update_version_data(result, info)
+            if not self.recursive:
+                break
+        return result
+
+    def get_distribution_names(self):
+        """
+        Return all the distribution names known to this locator.
+        """
+        result = set()
+        for root, dirs, files in os.walk(self.base_dir):
+            for fn in files:
+                if self.should_include(fn, root):
+                    fn = os.path.join(root, fn)
+                    url = urlunparse(('file', '',
+                                      pathname2url(os.path.abspath(fn)),
+                                      '', '', ''))
+                    info = self.convert_url_to_download_info(url, None)
+                    if info:
+                        result.add(info['name'])
+            if not self.recursive:
+                break
+        return result
+
+class JSONLocator(Locator):
+    """
+    This locator uses special extended metadata (not available on PyPI) and is
+    the basis of performant dependency resolution in distlib. Other locators
+    require archive downloads before dependencies can be determined! As you
+    might imagine, that can be slow.
+    """
+    def get_distribution_names(self):
+        """
+        Return all the distribution names known to this locator.
+        """
+        raise NotImplementedError('Not available from this locator')
+
+    def _get_project(self, name):
+        result = {'urls': {}, 'digests': {}}
+        data = get_project_data(name)
+        if data:
+            for info in data.get('files', []):
+                if info['ptype'] != 'sdist' or info['pyversion'] != 'source':
+                    continue
+                # We don't store summary in project metadata as it makes
+                # the data bigger for no benefit during dependency
+                # resolution
+                dist = make_dist(data['name'], info['version'],
+                                 summary=data.get('summary',
+                                                  'Placeholder for summary'),
+                                 scheme=self.scheme)
+                md = dist.metadata
+                md.source_url = info['url']
+                # TODO SHA256 digest
+                if 'digest' in info and info['digest']:
+                    dist.digest = ('md5', info['digest'])
+                md.dependencies = info.get('requirements', {})
+                dist.exports = info.get('exports', {})
+                result[dist.version] = dist
+                result['urls'].setdefault(dist.version, set()).add(info['url'])
+        return result
+
+class DistPathLocator(Locator):
+    """
+    This locator finds installed distributions in a path. It can be useful for
+    adding to an :class:`AggregatingLocator`.
+    """
+    def __init__(self, distpath, **kwargs):
+        """
+        Initialise an instance.
+
+        :param distpath: A :class:`DistributionPath` instance to search.
+        """
+        super(DistPathLocator, self).__init__(**kwargs)
+        assert isinstance(distpath, DistributionPath)
+        self.distpath = distpath
+
+    def _get_project(self, name):
+        dist = self.distpath.get_distribution(name)
+        if dist is None:
+            result = {'urls': {}, 'digests': {}}
+        else:
+            result = {
+                dist.version: dist,
+                'urls': {dist.version: set([dist.source_url])},
+                'digests': {dist.version: set([None])}
+            }
+        return result
+
+
+class AggregatingLocator(Locator):
+    """
+    This class allows you to chain and/or merge a list of locators.
+    """
+    def __init__(self, *locators, **kwargs):
+        """
+        Initialise an instance.
+
+        :param locators: The list of locators to search.
+        :param kwargs: Passed to the superclass constructor,
+                       except for:
+                       * merge - if False (the default), the first successful
+                         search from any of the locators is returned. If True,
+                         the results from all locators are merged (this can be
+                         slow).
+        """
+        self.merge = kwargs.pop('merge', False)
+        self.locators = locators
+        super(AggregatingLocator, self).__init__(**kwargs)
+
+    def clear_cache(self):
+        super(AggregatingLocator, self).clear_cache()
+        for locator in self.locators:
+            locator.clear_cache()
+
+    def _set_scheme(self, value):
+        self._scheme = value
+        for locator in self.locators:
+            locator.scheme = value
+
+    scheme = property(Locator.scheme.fget, _set_scheme)
+
+    def _get_project(self, name):
+        result = {}
+        for locator in self.locators:
+            d = locator.get_project(name)
+            if d:
+                if self.merge:
+                    files = result.get('urls', {})
+                    digests = result.get('digests', {})
+                    # next line could overwrite result['urls'], result['digests']
+                    result.update(d)
+                    df = result.get('urls')
+                    if files and df:
+                        for k, v in files.items():
+                            if k in df:
+                                df[k] |= v
+                            else:
+                                df[k] = v
+                    dd = result.get('digests')
+                    if digests and dd:
+                        dd.update(digests)
+                else:
+                    # See issue #18. If any dists are found and we're looking
+                    # for specific constraints, we only return something if
+                    # a match is found. For example, if a DirectoryLocator
+                    # returns just foo (1.0) while we're looking for
+                    # foo (>= 2.0), we'll pretend there was nothing there so
+                    # that subsequent locators can be queried. Otherwise we
+                    # would just return foo (1.0) which would then lead to a
+                    # failure to find foo (>= 2.0), because other locators
+                    # weren't searched. Note that this only matters when
+                    # merge=False.
+                    if self.matcher is None:
+                        found = True
+                    else:
+                        found = False
+                        for k in d:
+                            if self.matcher.match(k):
+                                found = True
+                                break
+                    if found:
+                        result = d
+                        break
+        return result
+
+    def get_distribution_names(self):
+        """
+        Return all the distribution names known to this locator.
+        """
+        result = set()
+        for locator in self.locators:
+            try:
+                result |= locator.get_distribution_names()
+            except NotImplementedError:
+                pass
+        return result
+
+
+# We use a legacy scheme simply because most of the dists on PyPI use legacy
+# versions which don't conform to PEP 440.
+default_locator = AggregatingLocator(
+                    # JSONLocator(), # don't use as PEP 426 is withdrawn
+                    SimpleScrapingLocator('https://pypi.org/simple/',
+                                          timeout=3.0),
+                    scheme='legacy')
+
+locate = default_locator.locate
+
+
+class DependencyFinder(object):
+    """
+    Locate dependencies for distributions.
+    """
+
+    def __init__(self, locator=None):
+        """
+        Initialise an instance, using the specified locator
+        to locate distributions.
+        """
+        self.locator = locator or default_locator
+        self.scheme = get_scheme(self.locator.scheme)
+
+    def add_distribution(self, dist):
+        """
+        Add a distribution to the finder. This will update internal information
+        about who provides what.
+        :param dist: The distribution to add.
+        """
+        logger.debug('adding distribution %s', dist)
+        name = dist.key
+        self.dists_by_name[name] = dist
+        self.dists[(name, dist.version)] = dist
+        for p in dist.provides:
+            name, version = parse_name_and_version(p)
+            logger.debug('Add to provided: %s, %s, %s', name, version, dist)
+            self.provided.setdefault(name, set()).add((version, dist))
+
+    def remove_distribution(self, dist):
+        """
+        Remove a distribution from the finder. This will update internal
+        information about who provides what.
+        :param dist: The distribution to remove.
+        """
+        logger.debug('removing distribution %s', dist)
+        name = dist.key
+        del self.dists_by_name[name]
+        del self.dists[(name, dist.version)]
+        for p in dist.provides:
+            name, version = parse_name_and_version(p)
+            logger.debug('Remove from provided: %s, %s, %s', name, version, dist)
+            s = self.provided[name]
+            s.remove((version, dist))
+            if not s:
+                del self.provided[name]
+
+    def get_matcher(self, reqt):
+        """
+        Get a version matcher for a requirement.
+        :param reqt: The requirement
+        :type reqt: str
+        :return: A version matcher (an instance of
+                 :class:`distlib.version.Matcher`).
+        """
+        try:
+            matcher = self.scheme.matcher(reqt)
+        except UnsupportedVersionError:  # pragma: no cover
+            # XXX compat-mode if cannot read the version
+            name = reqt.split()[0]
+            matcher = self.scheme.matcher(name)
+        return matcher
+
+    def find_providers(self, reqt):
+        """
+        Find the distributions which can fulfill a requirement.
+
+        :param reqt: The requirement.
+         :type reqt: str
+        :return: A set of distribution which can fulfill the requirement.
+        """
+        matcher = self.get_matcher(reqt)
+        name = matcher.key   # case-insensitive
+        result = set()
+        provided = self.provided
+        if name in provided:
+            for version, provider in provided[name]:
+                try:
+                    match = matcher.match(version)
+                except UnsupportedVersionError:
+                    match = False
+
+                if match:
+                    result.add(provider)
+                    break
+        return result
+
+    def try_to_replace(self, provider, other, problems):
+        """
+        Attempt to replace one provider with another. This is typically used
+        when resolving dependencies from multiple sources, e.g. A requires
+        (B >= 1.0) while C requires (B >= 1.1).
+
+        For successful replacement, ``provider`` must meet all the requirements
+        which ``other`` fulfills.
+
+        :param provider: The provider we are trying to replace with.
+        :param other: The provider we're trying to replace.
+        :param problems: If False is returned, this will contain what
+                         problems prevented replacement. This is currently
+                         a tuple of the literal string 'cantreplace',
+                         ``provider``, ``other``  and the set of requirements
+                         that ``provider`` couldn't fulfill.
+        :return: True if we can replace ``other`` with ``provider``, else
+                 False.
+        """
+        rlist = self.reqts[other]
+        unmatched = set()
+        for s in rlist:
+            matcher = self.get_matcher(s)
+            if not matcher.match(provider.version):
+                unmatched.add(s)
+        if unmatched:
+            # can't replace other with provider
+            problems.add(('cantreplace', provider, other,
+                          frozenset(unmatched)))
+            result = False
+        else:
+            # can replace other with provider
+            self.remove_distribution(other)
+            del self.reqts[other]
+            for s in rlist:
+                self.reqts.setdefault(provider, set()).add(s)
+            self.add_distribution(provider)
+            result = True
+        return result
+
+    def find(self, requirement, meta_extras=None, prereleases=False):
+        """
+        Find a distribution and all distributions it depends on.
+
+        :param requirement: The requirement specifying the distribution to
+                            find, or a Distribution instance.
+        :param meta_extras: A list of meta extras such as :test:, :build: and
+                            so on.
+        :param prereleases: If ``True``, allow pre-release versions to be
+                            returned - otherwise, don't return prereleases
+                            unless they're all that's available.
+
+        Return a set of :class:`Distribution` instances and a set of
+        problems.
+
+        The distributions returned should be such that they have the
+        :attr:`required` attribute set to ``True`` if they were
+        from the ``requirement`` passed to ``find()``, and they have the
+        :attr:`build_time_dependency` attribute set to ``True`` unless they
+        are post-installation dependencies of the ``requirement``.
+
+        The problems should be a tuple consisting of the string
+        ``'unsatisfied'`` and the requirement which couldn't be satisfied
+        by any distribution known to the locator.
+        """
+
+        self.provided = {}
+        self.dists = {}
+        self.dists_by_name = {}
+        self.reqts = {}
+
+        meta_extras = set(meta_extras or [])
+        if ':*:' in meta_extras:
+            meta_extras.remove(':*:')
+            # :meta: and :run: are implicitly included
+            meta_extras |= set([':test:', ':build:', ':dev:'])
+
+        if isinstance(requirement, Distribution):
+            dist = odist = requirement
+            logger.debug('passed %s as requirement', odist)
+        else:
+            dist = odist = self.locator.locate(requirement,
+                                               prereleases=prereleases)
+            if dist is None:
+                raise DistlibException('Unable to locate %r' % requirement)
+            logger.debug('located %s', odist)
+        dist.requested = True
+        problems = set()
+        todo = set([dist])
+        install_dists = set([odist])
+        while todo:
+            dist = todo.pop()
+            name = dist.key     # case-insensitive
+            if name not in self.dists_by_name:
+                self.add_distribution(dist)
+            else:
+                #import pdb; pdb.set_trace()
+                other = self.dists_by_name[name]
+                if other != dist:
+                    self.try_to_replace(dist, other, problems)
+
+            ireqts = dist.run_requires | dist.meta_requires
+            sreqts = dist.build_requires
+            ereqts = set()
+            if meta_extras and dist in install_dists:
+                for key in ('test', 'build', 'dev'):
+                    e = ':%s:' % key
+                    if e in meta_extras:
+                        ereqts |= getattr(dist, '%s_requires' % key)
+            all_reqts = ireqts | sreqts | ereqts
+            for r in all_reqts:
+                providers = self.find_providers(r)
+                if not providers:
+                    logger.debug('No providers found for %r', r)
+                    provider = self.locator.locate(r, prereleases=prereleases)
+                    # If no provider is found and we didn't consider
+                    # prereleases, consider them now.
+                    if provider is None and not prereleases:
+                        provider = self.locator.locate(r, prereleases=True)
+                    if provider is None:
+                        logger.debug('Cannot satisfy %r', r)
+                        problems.add(('unsatisfied', r))
+                    else:
+                        n, v = provider.key, provider.version
+                        if (n, v) not in self.dists:
+                            todo.add(provider)
+                        providers.add(provider)
+                        if r in ireqts and dist in install_dists:
+                            install_dists.add(provider)
+                            logger.debug('Adding %s to install_dists',
+                                         provider.name_and_version)
+                for p in providers:
+                    name = p.key
+                    if name not in self.dists_by_name:
+                        self.reqts.setdefault(p, set()).add(r)
+                    else:
+                        other = self.dists_by_name[name]
+                        if other != p:
+                            # see if other can be replaced by p
+                            self.try_to_replace(p, other, problems)
+
+        dists = set(self.dists.values())
+        for dist in dists:
+            dist.build_time_dependency = dist not in install_dists
+            if dist.build_time_dependency:
+                logger.debug('%s is a build-time dependency only.',
+                             dist.name_and_version)
+        logger.debug('find done for %s', odist)
+        return dists, problems
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/manifest.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/manifest.py
new file mode 100644
index 0000000000000000000000000000000000000000..ca0fe442d9ca499466df9438df16eca405c5f102
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/manifest.py
@@ -0,0 +1,393 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2012-2013 Python Software Foundation.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+"""
+Class representing the list of files in a distribution.
+
+Equivalent to distutils.filelist, but fixes some problems.
+"""
+import fnmatch
+import logging
+import os
+import re
+import sys
+
+from . import DistlibException
+from .compat import fsdecode
+from .util import convert_path
+
+
+__all__ = ['Manifest']
+
+logger = logging.getLogger(__name__)
+
+# a \ followed by some spaces + EOL
+_COLLAPSE_PATTERN = re.compile('\\\\w*\n', re.M)
+_COMMENTED_LINE = re.compile('#.*?(?=\n)|\n(?=$)', re.M | re.S)
+
+#
+# Due to the different results returned by fnmatch.translate, we need
+# to do slightly different processing for Python 2.7 and 3.2 ... this needed
+# to be brought in for Python 3.6 onwards.
+#
+_PYTHON_VERSION = sys.version_info[:2]
+
+class Manifest(object):
+    """A list of files built by on exploring the filesystem and filtered by
+    applying various patterns to what we find there.
+    """
+
+    def __init__(self, base=None):
+        """
+        Initialise an instance.
+
+        :param base: The base directory to explore under.
+        """
+        self.base = os.path.abspath(os.path.normpath(base or os.getcwd()))
+        self.prefix = self.base + os.sep
+        self.allfiles = None
+        self.files = set()
+
+    #
+    # Public API
+    #
+
+    def findall(self):
+        """Find all files under the base and set ``allfiles`` to the absolute
+        pathnames of files found.
+        """
+        from stat import S_ISREG, S_ISDIR, S_ISLNK
+
+        self.allfiles = allfiles = []
+        root = self.base
+        stack = [root]
+        pop = stack.pop
+        push = stack.append
+
+        while stack:
+            root = pop()
+            names = os.listdir(root)
+
+            for name in names:
+                fullname = os.path.join(root, name)
+
+                # Avoid excess stat calls -- just one will do, thank you!
+                stat = os.stat(fullname)
+                mode = stat.st_mode
+                if S_ISREG(mode):
+                    allfiles.append(fsdecode(fullname))
+                elif S_ISDIR(mode) and not S_ISLNK(mode):
+                    push(fullname)
+
+    def add(self, item):
+        """
+        Add a file to the manifest.
+
+        :param item: The pathname to add. This can be relative to the base.
+        """
+        if not item.startswith(self.prefix):
+            item = os.path.join(self.base, item)
+        self.files.add(os.path.normpath(item))
+
+    def add_many(self, items):
+        """
+        Add a list of files to the manifest.
+
+        :param items: The pathnames to add. These can be relative to the base.
+        """
+        for item in items:
+            self.add(item)
+
+    def sorted(self, wantdirs=False):
+        """
+        Return sorted files in directory order
+        """
+
+        def add_dir(dirs, d):
+            dirs.add(d)
+            logger.debug('add_dir added %s', d)
+            if d != self.base:
+                parent, _ = os.path.split(d)
+                assert parent not in ('', '/')
+                add_dir(dirs, parent)
+
+        result = set(self.files)    # make a copy!
+        if wantdirs:
+            dirs = set()
+            for f in result:
+                add_dir(dirs, os.path.dirname(f))
+            result |= dirs
+        return [os.path.join(*path_tuple) for path_tuple in
+                sorted(os.path.split(path) for path in result)]
+
+    def clear(self):
+        """Clear all collected files."""
+        self.files = set()
+        self.allfiles = []
+
+    def process_directive(self, directive):
+        """
+        Process a directive which either adds some files from ``allfiles`` to
+        ``files``, or removes some files from ``files``.
+
+        :param directive: The directive to process. This should be in a format
+                     compatible with distutils ``MANIFEST.in`` files:
+
+                     http://docs.python.org/distutils/sourcedist.html#commands
+        """
+        # Parse the line: split it up, make sure the right number of words
+        # is there, and return the relevant words.  'action' is always
+        # defined: it's the first word of the line.  Which of the other
+        # three are defined depends on the action; it'll be either
+        # patterns, (dir and patterns), or (dirpattern).
+        action, patterns, thedir, dirpattern = self._parse_directive(directive)
+
+        # OK, now we know that the action is valid and we have the
+        # right number of words on the line for that action -- so we
+        # can proceed with minimal error-checking.
+        if action == 'include':
+            for pattern in patterns:
+                if not self._include_pattern(pattern, anchor=True):
+                    logger.warning('no files found matching %r', pattern)
+
+        elif action == 'exclude':
+            for pattern in patterns:
+                found = self._exclude_pattern(pattern, anchor=True)
+                #if not found:
+                #    logger.warning('no previously-included files '
+                #                   'found matching %r', pattern)
+
+        elif action == 'global-include':
+            for pattern in patterns:
+                if not self._include_pattern(pattern, anchor=False):
+                    logger.warning('no files found matching %r '
+                                   'anywhere in distribution', pattern)
+
+        elif action == 'global-exclude':
+            for pattern in patterns:
+                found = self._exclude_pattern(pattern, anchor=False)
+                #if not found:
+                #    logger.warning('no previously-included files '
+                #                   'matching %r found anywhere in '
+                #                   'distribution', pattern)
+
+        elif action == 'recursive-include':
+            for pattern in patterns:
+                if not self._include_pattern(pattern, prefix=thedir):
+                    logger.warning('no files found matching %r '
+                                   'under directory %r', pattern, thedir)
+
+        elif action == 'recursive-exclude':
+            for pattern in patterns:
+                found = self._exclude_pattern(pattern, prefix=thedir)
+                #if not found:
+                #    logger.warning('no previously-included files '
+                #                   'matching %r found under directory %r',
+                #                   pattern, thedir)
+
+        elif action == 'graft':
+            if not self._include_pattern(None, prefix=dirpattern):
+                logger.warning('no directories found matching %r',
+                               dirpattern)
+
+        elif action == 'prune':
+            if not self._exclude_pattern(None, prefix=dirpattern):
+                logger.warning('no previously-included directories found '
+                               'matching %r', dirpattern)
+        else:   # pragma: no cover
+            # This should never happen, as it should be caught in
+            # _parse_template_line
+            raise DistlibException(
+                'invalid action %r' % action)
+
+    #
+    # Private API
+    #
+
+    def _parse_directive(self, directive):
+        """
+        Validate a directive.
+        :param directive: The directive to validate.
+        :return: A tuple of action, patterns, thedir, dir_patterns
+        """
+        words = directive.split()
+        if len(words) == 1 and words[0] not in ('include', 'exclude',
+                                                'global-include',
+                                                'global-exclude',
+                                                'recursive-include',
+                                                'recursive-exclude',
+                                                'graft', 'prune'):
+            # no action given, let's use the default 'include'
+            words.insert(0, 'include')
+
+        action = words[0]
+        patterns = thedir = dir_pattern = None
+
+        if action in ('include', 'exclude',
+                      'global-include', 'global-exclude'):
+            if len(words) < 2:
+                raise DistlibException(
+                    '%r expects   ...' % action)
+
+            patterns = [convert_path(word) for word in words[1:]]
+
+        elif action in ('recursive-include', 'recursive-exclude'):
+            if len(words) < 3:
+                raise DistlibException(
+                    '%r expects    ...' % action)
+
+            thedir = convert_path(words[1])
+            patterns = [convert_path(word) for word in words[2:]]
+
+        elif action in ('graft', 'prune'):
+            if len(words) != 2:
+                raise DistlibException(
+                    '%r expects a single ' % action)
+
+            dir_pattern = convert_path(words[1])
+
+        else:
+            raise DistlibException('unknown action %r' % action)
+
+        return action, patterns, thedir, dir_pattern
+
+    def _include_pattern(self, pattern, anchor=True, prefix=None,
+                         is_regex=False):
+        """Select strings (presumably filenames) from 'self.files' that
+        match 'pattern', a Unix-style wildcard (glob) pattern.
+
+        Patterns are not quite the same as implemented by the 'fnmatch'
+        module: '*' and '?'  match non-special characters, where "special"
+        is platform-dependent: slash on Unix; colon, slash, and backslash on
+        DOS/Windows; and colon on Mac OS.
+
+        If 'anchor' is true (the default), then the pattern match is more
+        stringent: "*.py" will match "foo.py" but not "foo/bar.py".  If
+        'anchor' is false, both of these will match.
+
+        If 'prefix' is supplied, then only filenames starting with 'prefix'
+        (itself a pattern) and ending with 'pattern', with anything in between
+        them, will match.  'anchor' is ignored in this case.
+
+        If 'is_regex' is true, 'anchor' and 'prefix' are ignored, and
+        'pattern' is assumed to be either a string containing a regex or a
+        regex object -- no translation is done, the regex is just compiled
+        and used as-is.
+
+        Selected strings will be added to self.files.
+
+        Return True if files are found.
+        """
+        # XXX docstring lying about what the special chars are?
+        found = False
+        pattern_re = self._translate_pattern(pattern, anchor, prefix, is_regex)
+
+        # delayed loading of allfiles list
+        if self.allfiles is None:
+            self.findall()
+
+        for name in self.allfiles:
+            if pattern_re.search(name):
+                self.files.add(name)
+                found = True
+        return found
+
+    def _exclude_pattern(self, pattern, anchor=True, prefix=None,
+                         is_regex=False):
+        """Remove strings (presumably filenames) from 'files' that match
+        'pattern'.
+
+        Other parameters are the same as for 'include_pattern()', above.
+        The list 'self.files' is modified in place. Return True if files are
+        found.
+
+        This API is public to allow e.g. exclusion of SCM subdirs, e.g. when
+        packaging source distributions
+        """
+        found = False
+        pattern_re = self._translate_pattern(pattern, anchor, prefix, is_regex)
+        for f in list(self.files):
+            if pattern_re.search(f):
+                self.files.remove(f)
+                found = True
+        return found
+
+    def _translate_pattern(self, pattern, anchor=True, prefix=None,
+                           is_regex=False):
+        """Translate a shell-like wildcard pattern to a compiled regular
+        expression.
+
+        Return the compiled regex.  If 'is_regex' true,
+        then 'pattern' is directly compiled to a regex (if it's a string)
+        or just returned as-is (assumes it's a regex object).
+        """
+        if is_regex:
+            if isinstance(pattern, str):
+                return re.compile(pattern)
+            else:
+                return pattern
+
+        if _PYTHON_VERSION > (3, 2):
+            # ditch start and end characters
+            start, _, end = self._glob_to_re('_').partition('_')
+
+        if pattern:
+            pattern_re = self._glob_to_re(pattern)
+            if _PYTHON_VERSION > (3, 2):
+                assert pattern_re.startswith(start) and pattern_re.endswith(end)
+        else:
+            pattern_re = ''
+
+        base = re.escape(os.path.join(self.base, ''))
+        if prefix is not None:
+            # ditch end of pattern character
+            if _PYTHON_VERSION <= (3, 2):
+                empty_pattern = self._glob_to_re('')
+                prefix_re = self._glob_to_re(prefix)[:-len(empty_pattern)]
+            else:
+                prefix_re = self._glob_to_re(prefix)
+                assert prefix_re.startswith(start) and prefix_re.endswith(end)
+                prefix_re = prefix_re[len(start): len(prefix_re) - len(end)]
+            sep = os.sep
+            if os.sep == '\\':
+                sep = r'\\'
+            if _PYTHON_VERSION <= (3, 2):
+                pattern_re = '^' + base + sep.join((prefix_re,
+                                                    '.*' + pattern_re))
+            else:
+                pattern_re = pattern_re[len(start): len(pattern_re) - len(end)]
+                pattern_re = r'%s%s%s%s.*%s%s' % (start, base, prefix_re, sep,
+                                                  pattern_re, end)
+        else:  # no prefix -- respect anchor flag
+            if anchor:
+                if _PYTHON_VERSION <= (3, 2):
+                    pattern_re = '^' + base + pattern_re
+                else:
+                    pattern_re = r'%s%s%s' % (start, base, pattern_re[len(start):])
+
+        return re.compile(pattern_re)
+
+    def _glob_to_re(self, pattern):
+        """Translate a shell-like glob pattern to a regular expression.
+
+        Return a string containing the regex.  Differs from
+        'fnmatch.translate()' in that '*' does not match "special characters"
+        (which are platform-specific).
+        """
+        pattern_re = fnmatch.translate(pattern)
+
+        # '?' and '*' in the glob pattern become '.' and '.*' in the RE, which
+        # IMHO is wrong -- '?' and '*' aren't supposed to match slash in Unix,
+        # and by extension they shouldn't match such "special characters" under
+        # any OS.  So change all non-escaped dots in the RE to match any
+        # character except the special characters (currently: just os.sep).
+        sep = os.sep
+        if os.sep == '\\':
+            # we're using a regex to manipulate a regex, so we need
+            # to escape the backslash twice
+            sep = r'\\\\'
+        escaped = r'\1[^%s]' % sep
+        pattern_re = re.sub(r'((? y,
+        '!=': lambda x, y: x != y,
+        '<':  lambda x, y: x < y,
+        '<=':  lambda x, y: x == y or x < y,
+        '>':  lambda x, y: x > y,
+        '>=':  lambda x, y: x == y or x > y,
+        'and': lambda x, y: x and y,
+        'or': lambda x, y: x or y,
+        'in': lambda x, y: x in y,
+        'not in': lambda x, y: x not in y,
+    }
+
+    def evaluate(self, expr, context):
+        """
+        Evaluate a marker expression returned by the :func:`parse_requirement`
+        function in the specified context.
+        """
+        if isinstance(expr, string_types):
+            if expr[0] in '\'"':
+                result = expr[1:-1]
+            else:
+                if expr not in context:
+                    raise SyntaxError('unknown variable: %s' % expr)
+                result = context[expr]
+        else:
+            assert isinstance(expr, dict)
+            op = expr['op']
+            if op not in self.operations:
+                raise NotImplementedError('op not implemented: %s' % op)
+            elhs = expr['lhs']
+            erhs = expr['rhs']
+            if _is_literal(expr['lhs']) and _is_literal(expr['rhs']):
+                raise SyntaxError('invalid comparison: %s %s %s' % (elhs, op, erhs))
+
+            lhs = self.evaluate(elhs, context)
+            rhs = self.evaluate(erhs, context)
+            if ((elhs == 'python_version' or erhs == 'python_version') and
+                op in ('<', '<=', '>', '>=', '===', '==', '!=', '~=')):
+                lhs = NV(lhs)
+                rhs = NV(rhs)
+            elif elhs == 'python_version' and op in ('in', 'not in'):
+                lhs = NV(lhs)
+                rhs = _get_versions(rhs)
+            result = self.operations[op](lhs, rhs)
+        return result
+
+_DIGITS = re.compile(r'\d+\.\d+')
+
+def default_context():
+    def format_full_version(info):
+        version = '%s.%s.%s' % (info.major, info.minor, info.micro)
+        kind = info.releaselevel
+        if kind != 'final':
+            version += kind[0] + str(info.serial)
+        return version
+
+    if hasattr(sys, 'implementation'):
+        implementation_version = format_full_version(sys.implementation.version)
+        implementation_name = sys.implementation.name
+    else:
+        implementation_version = '0'
+        implementation_name = ''
+
+    ppv = platform.python_version()
+    m = _DIGITS.match(ppv)
+    pv = m.group(0)
+    result = {
+        'implementation_name': implementation_name,
+        'implementation_version': implementation_version,
+        'os_name': os.name,
+        'platform_machine': platform.machine(),
+        'platform_python_implementation': platform.python_implementation(),
+        'platform_release': platform.release(),
+        'platform_system': platform.system(),
+        'platform_version': platform.version(),
+        'platform_in_venv': str(in_venv()),
+        'python_full_version': ppv,
+        'python_version': pv,
+        'sys_platform': sys.platform,
+    }
+    return result
+
+DEFAULT_CONTEXT = default_context()
+del default_context
+
+evaluator = Evaluator()
+
+def interpret(marker, execution_context=None):
+    """
+    Interpret a marker and return a result depending on environment.
+
+    :param marker: The marker to interpret.
+    :type marker: str
+    :param execution_context: The context used for name lookup.
+    :type execution_context: mapping
+    """
+    try:
+        expr, rest = parse_marker(marker)
+    except Exception as e:
+        raise SyntaxError('Unable to interpret marker syntax: %s: %s' % (marker, e))
+    if rest and rest[0] != '#':
+        raise SyntaxError('unexpected trailing data in marker: %s: %s' % (marker, rest))
+    context = dict(DEFAULT_CONTEXT)
+    if execution_context:
+        context.update(execution_context)
+    return evaluator.evaluate(expr, context)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/metadata.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/metadata.py
new file mode 100644
index 0000000000000000000000000000000000000000..c329e1977fd1ed403bb65529296d5c803a6b289f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/metadata.py
@@ -0,0 +1,1076 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2012 The Python Software Foundation.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+"""Implementation of the Metadata for Python packages PEPs.
+
+Supports all metadata formats (1.0, 1.1, 1.2, 1.3/2.1 and 2.2).
+"""
+from __future__ import unicode_literals
+
+import codecs
+from email import message_from_file
+import json
+import logging
+import re
+
+
+from . import DistlibException, __version__
+from .compat import StringIO, string_types, text_type
+from .markers import interpret
+from .util import extract_by_key, get_extras
+from .version import get_scheme, PEP440_VERSION_RE
+
+logger = logging.getLogger(__name__)
+
+
+class MetadataMissingError(DistlibException):
+    """A required metadata is missing"""
+
+
+class MetadataConflictError(DistlibException):
+    """Attempt to read or write metadata fields that are conflictual."""
+
+
+class MetadataUnrecognizedVersionError(DistlibException):
+    """Unknown metadata version number."""
+
+
+class MetadataInvalidError(DistlibException):
+    """A metadata value is invalid"""
+
+# public API of this module
+__all__ = ['Metadata', 'PKG_INFO_ENCODING', 'PKG_INFO_PREFERRED_VERSION']
+
+# Encoding used for the PKG-INFO files
+PKG_INFO_ENCODING = 'utf-8'
+
+# preferred version. Hopefully will be changed
+# to 1.2 once PEP 345 is supported everywhere
+PKG_INFO_PREFERRED_VERSION = '1.1'
+
+_LINE_PREFIX_1_2 = re.compile('\n       \\|')
+_LINE_PREFIX_PRE_1_2 = re.compile('\n        ')
+_241_FIELDS = ('Metadata-Version', 'Name', 'Version', 'Platform',
+               'Summary', 'Description',
+               'Keywords', 'Home-page', 'Author', 'Author-email',
+               'License')
+
+_314_FIELDS = ('Metadata-Version', 'Name', 'Version', 'Platform',
+               'Supported-Platform', 'Summary', 'Description',
+               'Keywords', 'Home-page', 'Author', 'Author-email',
+               'License', 'Classifier', 'Download-URL', 'Obsoletes',
+               'Provides', 'Requires')
+
+_314_MARKERS = ('Obsoletes', 'Provides', 'Requires', 'Classifier',
+                'Download-URL')
+
+_345_FIELDS = ('Metadata-Version', 'Name', 'Version', 'Platform',
+               'Supported-Platform', 'Summary', 'Description',
+               'Keywords', 'Home-page', 'Author', 'Author-email',
+               'Maintainer', 'Maintainer-email', 'License',
+               'Classifier', 'Download-URL', 'Obsoletes-Dist',
+               'Project-URL', 'Provides-Dist', 'Requires-Dist',
+               'Requires-Python', 'Requires-External')
+
+_345_MARKERS = ('Provides-Dist', 'Requires-Dist', 'Requires-Python',
+                'Obsoletes-Dist', 'Requires-External', 'Maintainer',
+                'Maintainer-email', 'Project-URL')
+
+_426_FIELDS = ('Metadata-Version', 'Name', 'Version', 'Platform',
+               'Supported-Platform', 'Summary', 'Description',
+               'Keywords', 'Home-page', 'Author', 'Author-email',
+               'Maintainer', 'Maintainer-email', 'License',
+               'Classifier', 'Download-URL', 'Obsoletes-Dist',
+               'Project-URL', 'Provides-Dist', 'Requires-Dist',
+               'Requires-Python', 'Requires-External', 'Private-Version',
+               'Obsoleted-By', 'Setup-Requires-Dist', 'Extension',
+               'Provides-Extra')
+
+_426_MARKERS = ('Private-Version', 'Provides-Extra', 'Obsoleted-By',
+                'Setup-Requires-Dist', 'Extension')
+
+# See issue #106: Sometimes 'Requires' and 'Provides' occur wrongly in
+# the metadata. Include them in the tuple literal below to allow them
+# (for now).
+# Ditto for Obsoletes - see issue #140.
+_566_FIELDS = _426_FIELDS + ('Description-Content-Type',
+                             'Requires', 'Provides', 'Obsoletes')
+
+_566_MARKERS = ('Description-Content-Type',)
+
+_643_MARKERS = ('Dynamic', 'License-File')
+
+_643_FIELDS = _566_FIELDS + _643_MARKERS
+
+_ALL_FIELDS = set()
+_ALL_FIELDS.update(_241_FIELDS)
+_ALL_FIELDS.update(_314_FIELDS)
+_ALL_FIELDS.update(_345_FIELDS)
+_ALL_FIELDS.update(_426_FIELDS)
+_ALL_FIELDS.update(_566_FIELDS)
+_ALL_FIELDS.update(_643_FIELDS)
+
+EXTRA_RE = re.compile(r'''extra\s*==\s*("([^"]+)"|'([^']+)')''')
+
+
+def _version2fieldlist(version):
+    if version == '1.0':
+        return _241_FIELDS
+    elif version == '1.1':
+        return _314_FIELDS
+    elif version == '1.2':
+        return _345_FIELDS
+    elif version in ('1.3', '2.1'):
+        # avoid adding field names if already there
+        return _345_FIELDS + tuple(f for f in _566_FIELDS if f not in _345_FIELDS)
+    elif version == '2.0':
+        raise ValueError('Metadata 2.0 is withdrawn and not supported')
+        # return _426_FIELDS
+    elif version == '2.2':
+        return _643_FIELDS
+    raise MetadataUnrecognizedVersionError(version)
+
+
+def _best_version(fields):
+    """Detect the best version depending on the fields used."""
+    def _has_marker(keys, markers):
+        for marker in markers:
+            if marker in keys:
+                return True
+        return False
+
+    keys = []
+    for key, value in fields.items():
+        if value in ([], 'UNKNOWN', None):
+            continue
+        keys.append(key)
+
+    possible_versions = ['1.0', '1.1', '1.2', '1.3', '2.1', '2.2']  # 2.0 removed
+
+    # first let's try to see if a field is not part of one of the version
+    for key in keys:
+        if key not in _241_FIELDS and '1.0' in possible_versions:
+            possible_versions.remove('1.0')
+            logger.debug('Removed 1.0 due to %s', key)
+        if key not in _314_FIELDS and '1.1' in possible_versions:
+            possible_versions.remove('1.1')
+            logger.debug('Removed 1.1 due to %s', key)
+        if key not in _345_FIELDS and '1.2' in possible_versions:
+            possible_versions.remove('1.2')
+            logger.debug('Removed 1.2 due to %s', key)
+        if key not in _566_FIELDS and '1.3' in possible_versions:
+            possible_versions.remove('1.3')
+            logger.debug('Removed 1.3 due to %s', key)
+        if key not in _566_FIELDS and '2.1' in possible_versions:
+            if key != 'Description':  # In 2.1, description allowed after headers
+                possible_versions.remove('2.1')
+                logger.debug('Removed 2.1 due to %s', key)
+        if key not in _643_FIELDS and '2.2' in possible_versions:
+            possible_versions.remove('2.2')
+            logger.debug('Removed 2.2 due to %s', key)
+        # if key not in _426_FIELDS and '2.0' in possible_versions:
+            # possible_versions.remove('2.0')
+            # logger.debug('Removed 2.0 due to %s', key)
+
+    # possible_version contains qualified versions
+    if len(possible_versions) == 1:
+        return possible_versions[0]   # found !
+    elif len(possible_versions) == 0:
+        logger.debug('Out of options - unknown metadata set: %s', fields)
+        raise MetadataConflictError('Unknown metadata set')
+
+    # let's see if one unique marker is found
+    is_1_1 = '1.1' in possible_versions and _has_marker(keys, _314_MARKERS)
+    is_1_2 = '1.2' in possible_versions and _has_marker(keys, _345_MARKERS)
+    is_2_1 = '2.1' in possible_versions and _has_marker(keys, _566_MARKERS)
+    # is_2_0 = '2.0' in possible_versions and _has_marker(keys, _426_MARKERS)
+    is_2_2 = '2.2' in possible_versions and _has_marker(keys, _643_MARKERS)
+    if int(is_1_1) + int(is_1_2) + int(is_2_1) + int(is_2_2) > 1:
+        raise MetadataConflictError('You used incompatible 1.1/1.2/2.1/2.2 fields')
+
+    # we have the choice, 1.0, or 1.2, 2.1 or 2.2
+    #   - 1.0 has a broken Summary field but works with all tools
+    #   - 1.1 is to avoid
+    #   - 1.2 fixes Summary but has little adoption
+    #   - 2.1 adds more features
+    #   - 2.2 is the latest
+    if not is_1_1 and not is_1_2 and not is_2_1 and not is_2_2:
+        # we couldn't find any specific marker
+        if PKG_INFO_PREFERRED_VERSION in possible_versions:
+            return PKG_INFO_PREFERRED_VERSION
+    if is_1_1:
+        return '1.1'
+    if is_1_2:
+        return '1.2'
+    if is_2_1:
+        return '2.1'
+    # if is_2_2:
+        # return '2.2'
+
+    return '2.2'
+
+# This follows the rules about transforming keys as described in
+# https://www.python.org/dev/peps/pep-0566/#id17
+_ATTR2FIELD = {
+    name.lower().replace("-", "_"): name for name in _ALL_FIELDS
+}
+_FIELD2ATTR = {field: attr for attr, field in _ATTR2FIELD.items()}
+
+_PREDICATE_FIELDS = ('Requires-Dist', 'Obsoletes-Dist', 'Provides-Dist')
+_VERSIONS_FIELDS = ('Requires-Python',)
+_VERSION_FIELDS = ('Version',)
+_LISTFIELDS = ('Platform', 'Classifier', 'Obsoletes',
+               'Requires', 'Provides', 'Obsoletes-Dist',
+               'Provides-Dist', 'Requires-Dist', 'Requires-External',
+               'Project-URL', 'Supported-Platform', 'Setup-Requires-Dist',
+               'Provides-Extra', 'Extension', 'License-File')
+_LISTTUPLEFIELDS = ('Project-URL',)
+
+_ELEMENTSFIELD = ('Keywords',)
+
+_UNICODEFIELDS = ('Author', 'Maintainer', 'Summary', 'Description')
+
+_MISSING = object()
+
+_FILESAFE = re.compile('[^A-Za-z0-9.]+')
+
+
+def _get_name_and_version(name, version, for_filename=False):
+    """Return the distribution name with version.
+
+    If for_filename is true, return a filename-escaped form."""
+    if for_filename:
+        # For both name and version any runs of non-alphanumeric or '.'
+        # characters are replaced with a single '-'.  Additionally any
+        # spaces in the version string become '.'
+        name = _FILESAFE.sub('-', name)
+        version = _FILESAFE.sub('-', version.replace(' ', '.'))
+    return '%s-%s' % (name, version)
+
+
+class LegacyMetadata(object):
+    """The legacy metadata of a release.
+
+    Supports versions 1.0, 1.1, 1.2, 2.0 and 1.3/2.1 (auto-detected). You can
+    instantiate the class with one of these arguments (or none):
+    - *path*, the path to a metadata file
+    - *fileobj* give a file-like object with metadata as content
+    - *mapping* is a dict-like object
+    - *scheme* is a version scheme name
+    """
+    # TODO document the mapping API and UNKNOWN default key
+
+    def __init__(self, path=None, fileobj=None, mapping=None,
+                 scheme='default'):
+        if [path, fileobj, mapping].count(None) < 2:
+            raise TypeError('path, fileobj and mapping are exclusive')
+        self._fields = {}
+        self.requires_files = []
+        self._dependencies = None
+        self.scheme = scheme
+        if path is not None:
+            self.read(path)
+        elif fileobj is not None:
+            self.read_file(fileobj)
+        elif mapping is not None:
+            self.update(mapping)
+            self.set_metadata_version()
+
+    def set_metadata_version(self):
+        self._fields['Metadata-Version'] = _best_version(self._fields)
+
+    def _write_field(self, fileobj, name, value):
+        fileobj.write('%s: %s\n' % (name, value))
+
+    def __getitem__(self, name):
+        return self.get(name)
+
+    def __setitem__(self, name, value):
+        return self.set(name, value)
+
+    def __delitem__(self, name):
+        field_name = self._convert_name(name)
+        try:
+            del self._fields[field_name]
+        except KeyError:
+            raise KeyError(name)
+
+    def __contains__(self, name):
+        return (name in self._fields or
+                self._convert_name(name) in self._fields)
+
+    def _convert_name(self, name):
+        if name in _ALL_FIELDS:
+            return name
+        name = name.replace('-', '_').lower()
+        return _ATTR2FIELD.get(name, name)
+
+    def _default_value(self, name):
+        if name in _LISTFIELDS or name in _ELEMENTSFIELD:
+            return []
+        return 'UNKNOWN'
+
+    def _remove_line_prefix(self, value):
+        if self.metadata_version in ('1.0', '1.1'):
+            return _LINE_PREFIX_PRE_1_2.sub('\n', value)
+        else:
+            return _LINE_PREFIX_1_2.sub('\n', value)
+
+    def __getattr__(self, name):
+        if name in _ATTR2FIELD:
+            return self[name]
+        raise AttributeError(name)
+
+    #
+    # Public API
+    #
+
+#    dependencies = property(_get_dependencies, _set_dependencies)
+
+    def get_fullname(self, filesafe=False):
+        """Return the distribution name with version.
+
+        If filesafe is true, return a filename-escaped form."""
+        return _get_name_and_version(self['Name'], self['Version'], filesafe)
+
+    def is_field(self, name):
+        """return True if name is a valid metadata key"""
+        name = self._convert_name(name)
+        return name in _ALL_FIELDS
+
+    def is_multi_field(self, name):
+        name = self._convert_name(name)
+        return name in _LISTFIELDS
+
+    def read(self, filepath):
+        """Read the metadata values from a file path."""
+        fp = codecs.open(filepath, 'r', encoding='utf-8')
+        try:
+            self.read_file(fp)
+        finally:
+            fp.close()
+
+    def read_file(self, fileob):
+        """Read the metadata values from a file object."""
+        msg = message_from_file(fileob)
+        self._fields['Metadata-Version'] = msg['metadata-version']
+
+        # When reading, get all the fields we can
+        for field in _ALL_FIELDS:
+            if field not in msg:
+                continue
+            if field in _LISTFIELDS:
+                # we can have multiple lines
+                values = msg.get_all(field)
+                if field in _LISTTUPLEFIELDS and values is not None:
+                    values = [tuple(value.split(',')) for value in values]
+                self.set(field, values)
+            else:
+                # single line
+                value = msg[field]
+                if value is not None and value != 'UNKNOWN':
+                    self.set(field, value)
+
+        # PEP 566 specifies that the body be used for the description, if
+        # available
+        body = msg.get_payload()
+        self["Description"] = body if body else self["Description"]
+        # logger.debug('Attempting to set metadata for %s', self)
+        # self.set_metadata_version()
+
+    def write(self, filepath, skip_unknown=False):
+        """Write the metadata fields to filepath."""
+        fp = codecs.open(filepath, 'w', encoding='utf-8')
+        try:
+            self.write_file(fp, skip_unknown)
+        finally:
+            fp.close()
+
+    def write_file(self, fileobject, skip_unknown=False):
+        """Write the PKG-INFO format data to a file object."""
+        self.set_metadata_version()
+
+        for field in _version2fieldlist(self['Metadata-Version']):
+            values = self.get(field)
+            if skip_unknown and values in ('UNKNOWN', [], ['UNKNOWN']):
+                continue
+            if field in _ELEMENTSFIELD:
+                self._write_field(fileobject, field, ','.join(values))
+                continue
+            if field not in _LISTFIELDS:
+                if field == 'Description':
+                    if self.metadata_version in ('1.0', '1.1'):
+                        values = values.replace('\n', '\n        ')
+                    else:
+                        values = values.replace('\n', '\n       |')
+                values = [values]
+
+            if field in _LISTTUPLEFIELDS:
+                values = [','.join(value) for value in values]
+
+            for value in values:
+                self._write_field(fileobject, field, value)
+
+    def update(self, other=None, **kwargs):
+        """Set metadata values from the given iterable `other` and kwargs.
+
+        Behavior is like `dict.update`: If `other` has a ``keys`` method,
+        they are looped over and ``self[key]`` is assigned ``other[key]``.
+        Else, ``other`` is an iterable of ``(key, value)`` iterables.
+
+        Keys that don't match a metadata field or that have an empty value are
+        dropped.
+        """
+        def _set(key, value):
+            if key in _ATTR2FIELD and value:
+                self.set(self._convert_name(key), value)
+
+        if not other:
+            # other is None or empty container
+            pass
+        elif hasattr(other, 'keys'):
+            for k in other.keys():
+                _set(k, other[k])
+        else:
+            for k, v in other:
+                _set(k, v)
+
+        if kwargs:
+            for k, v in kwargs.items():
+                _set(k, v)
+
+    def set(self, name, value):
+        """Control then set a metadata field."""
+        name = self._convert_name(name)
+
+        if ((name in _ELEMENTSFIELD or name == 'Platform') and
+            not isinstance(value, (list, tuple))):
+            if isinstance(value, string_types):
+                value = [v.strip() for v in value.split(',')]
+            else:
+                value = []
+        elif (name in _LISTFIELDS and
+              not isinstance(value, (list, tuple))):
+            if isinstance(value, string_types):
+                value = [value]
+            else:
+                value = []
+
+        if logger.isEnabledFor(logging.WARNING):
+            project_name = self['Name']
+
+            scheme = get_scheme(self.scheme)
+            if name in _PREDICATE_FIELDS and value is not None:
+                for v in value:
+                    # check that the values are valid
+                    if not scheme.is_valid_matcher(v.split(';')[0]):
+                        logger.warning(
+                            "'%s': '%s' is not valid (field '%s')",
+                            project_name, v, name)
+            # FIXME this rejects UNKNOWN, is that right?
+            elif name in _VERSIONS_FIELDS and value is not None:
+                if not scheme.is_valid_constraint_list(value):
+                    logger.warning("'%s': '%s' is not a valid version (field '%s')",
+                                   project_name, value, name)
+            elif name in _VERSION_FIELDS and value is not None:
+                if not scheme.is_valid_version(value):
+                    logger.warning("'%s': '%s' is not a valid version (field '%s')",
+                                   project_name, value, name)
+
+        if name in _UNICODEFIELDS:
+            if name == 'Description':
+                value = self._remove_line_prefix(value)
+
+        self._fields[name] = value
+
+    def get(self, name, default=_MISSING):
+        """Get a metadata field."""
+        name = self._convert_name(name)
+        if name not in self._fields:
+            if default is _MISSING:
+                default = self._default_value(name)
+            return default
+        if name in _UNICODEFIELDS:
+            value = self._fields[name]
+            return value
+        elif name in _LISTFIELDS:
+            value = self._fields[name]
+            if value is None:
+                return []
+            res = []
+            for val in value:
+                if name not in _LISTTUPLEFIELDS:
+                    res.append(val)
+                else:
+                    # That's for Project-URL
+                    res.append((val[0], val[1]))
+            return res
+
+        elif name in _ELEMENTSFIELD:
+            value = self._fields[name]
+            if isinstance(value, string_types):
+                return value.split(',')
+        return self._fields[name]
+
+    def check(self, strict=False):
+        """Check if the metadata is compliant. If strict is True then raise if
+        no Name or Version are provided"""
+        self.set_metadata_version()
+
+        # XXX should check the versions (if the file was loaded)
+        missing, warnings = [], []
+
+        for attr in ('Name', 'Version'):  # required by PEP 345
+            if attr not in self:
+                missing.append(attr)
+
+        if strict and missing != []:
+            msg = 'missing required metadata: %s' % ', '.join(missing)
+            raise MetadataMissingError(msg)
+
+        for attr in ('Home-page', 'Author'):
+            if attr not in self:
+                missing.append(attr)
+
+        # checking metadata 1.2 (XXX needs to check 1.1, 1.0)
+        if self['Metadata-Version'] != '1.2':
+            return missing, warnings
+
+        scheme = get_scheme(self.scheme)
+
+        def are_valid_constraints(value):
+            for v in value:
+                if not scheme.is_valid_matcher(v.split(';')[0]):
+                    return False
+            return True
+
+        for fields, controller in ((_PREDICATE_FIELDS, are_valid_constraints),
+                                   (_VERSIONS_FIELDS,
+                                    scheme.is_valid_constraint_list),
+                                   (_VERSION_FIELDS,
+                                    scheme.is_valid_version)):
+            for field in fields:
+                value = self.get(field, None)
+                if value is not None and not controller(value):
+                    warnings.append("Wrong value for '%s': %s" % (field, value))
+
+        return missing, warnings
+
+    def todict(self, skip_missing=False):
+        """Return fields as a dict.
+
+        Field names will be converted to use the underscore-lowercase style
+        instead of hyphen-mixed case (i.e. home_page instead of Home-page).
+        This is as per https://www.python.org/dev/peps/pep-0566/#id17.
+        """
+        self.set_metadata_version()
+
+        fields = _version2fieldlist(self['Metadata-Version'])
+
+        data = {}
+
+        for field_name in fields:
+            if not skip_missing or field_name in self._fields:
+                key = _FIELD2ATTR[field_name]
+                if key != 'project_url':
+                    data[key] = self[field_name]
+                else:
+                    data[key] = [','.join(u) for u in self[field_name]]
+
+        return data
+
+    def add_requirements(self, requirements):
+        if self['Metadata-Version'] == '1.1':
+            # we can't have 1.1 metadata *and* Setuptools requires
+            for field in ('Obsoletes', 'Requires', 'Provides'):
+                if field in self:
+                    del self[field]
+        self['Requires-Dist'] += requirements
+
+    # Mapping API
+    # TODO could add iter* variants
+
+    def keys(self):
+        return list(_version2fieldlist(self['Metadata-Version']))
+
+    def __iter__(self):
+        for key in self.keys():
+            yield key
+
+    def values(self):
+        return [self[key] for key in self.keys()]
+
+    def items(self):
+        return [(key, self[key]) for key in self.keys()]
+
+    def __repr__(self):
+        return '<%s %s %s>' % (self.__class__.__name__, self.name,
+                               self.version)
+
+
+METADATA_FILENAME = 'pydist.json'
+WHEEL_METADATA_FILENAME = 'metadata.json'
+LEGACY_METADATA_FILENAME = 'METADATA'
+
+
+class Metadata(object):
+    """
+    The metadata of a release. This implementation uses 2.1
+    metadata where possible. If not possible, it wraps a LegacyMetadata
+    instance which handles the key-value metadata format.
+    """
+
+    METADATA_VERSION_MATCHER = re.compile(r'^\d+(\.\d+)*$')
+
+    NAME_MATCHER = re.compile('^[0-9A-Z]([0-9A-Z_.-]*[0-9A-Z])?$', re.I)
+
+    FIELDNAME_MATCHER = re.compile('^[A-Z]([0-9A-Z-]*[0-9A-Z])?$', re.I)
+
+    VERSION_MATCHER = PEP440_VERSION_RE
+
+    SUMMARY_MATCHER = re.compile('.{1,2047}')
+
+    METADATA_VERSION = '2.0'
+
+    GENERATOR = 'distlib (%s)' % __version__
+
+    MANDATORY_KEYS = {
+        'name': (),
+        'version': (),
+        'summary': ('legacy',),
+    }
+
+    INDEX_KEYS = ('name version license summary description author '
+                  'author_email keywords platform home_page classifiers '
+                  'download_url')
+
+    DEPENDENCY_KEYS = ('extras run_requires test_requires build_requires '
+                       'dev_requires provides meta_requires obsoleted_by '
+                       'supports_environments')
+
+    SYNTAX_VALIDATORS = {
+        'metadata_version': (METADATA_VERSION_MATCHER, ()),
+        'name': (NAME_MATCHER, ('legacy',)),
+        'version': (VERSION_MATCHER, ('legacy',)),
+        'summary': (SUMMARY_MATCHER, ('legacy',)),
+        'dynamic': (FIELDNAME_MATCHER, ('legacy',)),
+    }
+
+    __slots__ = ('_legacy', '_data', 'scheme')
+
+    def __init__(self, path=None, fileobj=None, mapping=None,
+                 scheme='default'):
+        if [path, fileobj, mapping].count(None) < 2:
+            raise TypeError('path, fileobj and mapping are exclusive')
+        self._legacy = None
+        self._data = None
+        self.scheme = scheme
+        #import pdb; pdb.set_trace()
+        if mapping is not None:
+            try:
+                self._validate_mapping(mapping, scheme)
+                self._data = mapping
+            except MetadataUnrecognizedVersionError:
+                self._legacy = LegacyMetadata(mapping=mapping, scheme=scheme)
+                self.validate()
+        else:
+            data = None
+            if path:
+                with open(path, 'rb') as f:
+                    data = f.read()
+            elif fileobj:
+                data = fileobj.read()
+            if data is None:
+                # Initialised with no args - to be added
+                self._data = {
+                    'metadata_version': self.METADATA_VERSION,
+                    'generator': self.GENERATOR,
+                }
+            else:
+                if not isinstance(data, text_type):
+                    data = data.decode('utf-8')
+                try:
+                    self._data = json.loads(data)
+                    self._validate_mapping(self._data, scheme)
+                except ValueError:
+                    # Note: MetadataUnrecognizedVersionError does not
+                    # inherit from ValueError (it's a DistlibException,
+                    # which should not inherit from ValueError).
+                    # The ValueError comes from the json.load - if that
+                    # succeeds and we get a validation error, we want
+                    # that to propagate
+                    self._legacy = LegacyMetadata(fileobj=StringIO(data),
+                                                  scheme=scheme)
+                    self.validate()
+
+    common_keys = set(('name', 'version', 'license', 'keywords', 'summary'))
+
+    none_list = (None, list)
+    none_dict = (None, dict)
+
+    mapped_keys = {
+        'run_requires': ('Requires-Dist', list),
+        'build_requires': ('Setup-Requires-Dist', list),
+        'dev_requires': none_list,
+        'test_requires': none_list,
+        'meta_requires': none_list,
+        'extras': ('Provides-Extra', list),
+        'modules': none_list,
+        'namespaces': none_list,
+        'exports': none_dict,
+        'commands': none_dict,
+        'classifiers': ('Classifier', list),
+        'source_url': ('Download-URL', None),
+        'metadata_version': ('Metadata-Version', None),
+    }
+
+    del none_list, none_dict
+
+    def __getattribute__(self, key):
+        common = object.__getattribute__(self, 'common_keys')
+        mapped = object.__getattribute__(self, 'mapped_keys')
+        if key in mapped:
+            lk, maker = mapped[key]
+            if self._legacy:
+                if lk is None:
+                    result = None if maker is None else maker()
+                else:
+                    result = self._legacy.get(lk)
+            else:
+                value = None if maker is None else maker()
+                if key not in ('commands', 'exports', 'modules', 'namespaces',
+                               'classifiers'):
+                    result = self._data.get(key, value)
+                else:
+                    # special cases for PEP 459
+                    sentinel = object()
+                    result = sentinel
+                    d = self._data.get('extensions')
+                    if d:
+                        if key == 'commands':
+                            result = d.get('python.commands', value)
+                        elif key == 'classifiers':
+                            d = d.get('python.details')
+                            if d:
+                                result = d.get(key, value)
+                        else:
+                            d = d.get('python.exports')
+                            if not d:
+                                d = self._data.get('python.exports')
+                            if d:
+                                result = d.get(key, value)
+                    if result is sentinel:
+                        result = value
+        elif key not in common:
+            result = object.__getattribute__(self, key)
+        elif self._legacy:
+            result = self._legacy.get(key)
+        else:
+            result = self._data.get(key)
+        return result
+
+    def _validate_value(self, key, value, scheme=None):
+        if key in self.SYNTAX_VALIDATORS:
+            pattern, exclusions = self.SYNTAX_VALIDATORS[key]
+            if (scheme or self.scheme) not in exclusions:
+                m = pattern.match(value)
+                if not m:
+                    raise MetadataInvalidError("'%s' is an invalid value for "
+                                               "the '%s' property" % (value,
+                                                                    key))
+
+    def __setattr__(self, key, value):
+        self._validate_value(key, value)
+        common = object.__getattribute__(self, 'common_keys')
+        mapped = object.__getattribute__(self, 'mapped_keys')
+        if key in mapped:
+            lk, _ = mapped[key]
+            if self._legacy:
+                if lk is None:
+                    raise NotImplementedError
+                self._legacy[lk] = value
+            elif key not in ('commands', 'exports', 'modules', 'namespaces',
+                             'classifiers'):
+                self._data[key] = value
+            else:
+                # special cases for PEP 459
+                d = self._data.setdefault('extensions', {})
+                if key == 'commands':
+                    d['python.commands'] = value
+                elif key == 'classifiers':
+                    d = d.setdefault('python.details', {})
+                    d[key] = value
+                else:
+                    d = d.setdefault('python.exports', {})
+                    d[key] = value
+        elif key not in common:
+            object.__setattr__(self, key, value)
+        else:
+            if key == 'keywords':
+                if isinstance(value, string_types):
+                    value = value.strip()
+                    if value:
+                        value = value.split()
+                    else:
+                        value = []
+            if self._legacy:
+                self._legacy[key] = value
+            else:
+                self._data[key] = value
+
+    @property
+    def name_and_version(self):
+        return _get_name_and_version(self.name, self.version, True)
+
+    @property
+    def provides(self):
+        if self._legacy:
+            result = self._legacy['Provides-Dist']
+        else:
+            result = self._data.setdefault('provides', [])
+        s = '%s (%s)' % (self.name, self.version)
+        if s not in result:
+            result.append(s)
+        return result
+
+    @provides.setter
+    def provides(self, value):
+        if self._legacy:
+            self._legacy['Provides-Dist'] = value
+        else:
+            self._data['provides'] = value
+
+    def get_requirements(self, reqts, extras=None, env=None):
+        """
+        Base method to get dependencies, given a set of extras
+        to satisfy and an optional environment context.
+        :param reqts: A list of sometimes-wanted dependencies,
+                      perhaps dependent on extras and environment.
+        :param extras: A list of optional components being requested.
+        :param env: An optional environment for marker evaluation.
+        """
+        if self._legacy:
+            result = reqts
+        else:
+            result = []
+            extras = get_extras(extras or [], self.extras)
+            for d in reqts:
+                if 'extra' not in d and 'environment' not in d:
+                    # unconditional
+                    include = True
+                else:
+                    if 'extra' not in d:
+                        # Not extra-dependent - only environment-dependent
+                        include = True
+                    else:
+                        include = d.get('extra') in extras
+                    if include:
+                        # Not excluded because of extras, check environment
+                        marker = d.get('environment')
+                        if marker:
+                            include = interpret(marker, env)
+                if include:
+                    result.extend(d['requires'])
+            for key in ('build', 'dev', 'test'):
+                e = ':%s:' % key
+                if e in extras:
+                    extras.remove(e)
+                    # A recursive call, but it should terminate since 'test'
+                    # has been removed from the extras
+                    reqts = self._data.get('%s_requires' % key, [])
+                    result.extend(self.get_requirements(reqts, extras=extras,
+                                                        env=env))
+        return result
+
+    @property
+    def dictionary(self):
+        if self._legacy:
+            return self._from_legacy()
+        return self._data
+
+    @property
+    def dependencies(self):
+        if self._legacy:
+            raise NotImplementedError
+        else:
+            return extract_by_key(self._data, self.DEPENDENCY_KEYS)
+
+    @dependencies.setter
+    def dependencies(self, value):
+        if self._legacy:
+            raise NotImplementedError
+        else:
+            self._data.update(value)
+
+    def _validate_mapping(self, mapping, scheme):
+        if mapping.get('metadata_version') != self.METADATA_VERSION:
+            raise MetadataUnrecognizedVersionError()
+        missing = []
+        for key, exclusions in self.MANDATORY_KEYS.items():
+            if key not in mapping:
+                if scheme not in exclusions:
+                    missing.append(key)
+        if missing:
+            msg = 'Missing metadata items: %s' % ', '.join(missing)
+            raise MetadataMissingError(msg)
+        for k, v in mapping.items():
+            self._validate_value(k, v, scheme)
+
+    def validate(self):
+        if self._legacy:
+            missing, warnings = self._legacy.check(True)
+            if missing or warnings:
+                logger.warning('Metadata: missing: %s, warnings: %s',
+                               missing, warnings)
+        else:
+            self._validate_mapping(self._data, self.scheme)
+
+    def todict(self):
+        if self._legacy:
+            return self._legacy.todict(True)
+        else:
+            result = extract_by_key(self._data, self.INDEX_KEYS)
+            return result
+
+    def _from_legacy(self):
+        assert self._legacy and not self._data
+        result = {
+            'metadata_version': self.METADATA_VERSION,
+            'generator': self.GENERATOR,
+        }
+        lmd = self._legacy.todict(True)     # skip missing ones
+        for k in ('name', 'version', 'license', 'summary', 'description',
+                  'classifier'):
+            if k in lmd:
+                if k == 'classifier':
+                    nk = 'classifiers'
+                else:
+                    nk = k
+                result[nk] = lmd[k]
+        kw = lmd.get('Keywords', [])
+        if kw == ['']:
+            kw = []
+        result['keywords'] = kw
+        keys = (('requires_dist', 'run_requires'),
+                ('setup_requires_dist', 'build_requires'))
+        for ok, nk in keys:
+            if ok in lmd and lmd[ok]:
+                result[nk] = [{'requires': lmd[ok]}]
+        result['provides'] = self.provides
+        author = {}
+        maintainer = {}
+        return result
+
+    LEGACY_MAPPING = {
+        'name': 'Name',
+        'version': 'Version',
+        ('extensions', 'python.details', 'license'): 'License',
+        'summary': 'Summary',
+        'description': 'Description',
+        ('extensions', 'python.project', 'project_urls', 'Home'): 'Home-page',
+        ('extensions', 'python.project', 'contacts', 0, 'name'): 'Author',
+        ('extensions', 'python.project', 'contacts', 0, 'email'): 'Author-email',
+        'source_url': 'Download-URL',
+        ('extensions', 'python.details', 'classifiers'): 'Classifier',
+    }
+
+    def _to_legacy(self):
+        def process_entries(entries):
+            reqts = set()
+            for e in entries:
+                extra = e.get('extra')
+                env = e.get('environment')
+                rlist = e['requires']
+                for r in rlist:
+                    if not env and not extra:
+                        reqts.add(r)
+                    else:
+                        marker = ''
+                        if extra:
+                            marker = 'extra == "%s"' % extra
+                        if env:
+                            if marker:
+                                marker = '(%s) and %s' % (env, marker)
+                            else:
+                                marker = env
+                        reqts.add(';'.join((r, marker)))
+            return reqts
+
+        assert self._data and not self._legacy
+        result = LegacyMetadata()
+        nmd = self._data
+        # import pdb; pdb.set_trace()
+        for nk, ok in self.LEGACY_MAPPING.items():
+            if not isinstance(nk, tuple):
+                if nk in nmd:
+                    result[ok] = nmd[nk]
+            else:
+                d = nmd
+                found = True
+                for k in nk:
+                    try:
+                        d = d[k]
+                    except (KeyError, IndexError):
+                        found = False
+                        break
+                if found:
+                    result[ok] = d
+        r1 = process_entries(self.run_requires + self.meta_requires)
+        r2 = process_entries(self.build_requires + self.dev_requires)
+        if self.extras:
+            result['Provides-Extra'] = sorted(self.extras)
+        result['Requires-Dist'] = sorted(r1)
+        result['Setup-Requires-Dist'] = sorted(r2)
+        # TODO: any other fields wanted
+        return result
+
+    def write(self, path=None, fileobj=None, legacy=False, skip_unknown=True):
+        if [path, fileobj].count(None) != 1:
+            raise ValueError('Exactly one of path and fileobj is needed')
+        self.validate()
+        if legacy:
+            if self._legacy:
+                legacy_md = self._legacy
+            else:
+                legacy_md = self._to_legacy()
+            if path:
+                legacy_md.write(path, skip_unknown=skip_unknown)
+            else:
+                legacy_md.write_file(fileobj, skip_unknown=skip_unknown)
+        else:
+            if self._legacy:
+                d = self._from_legacy()
+            else:
+                d = self._data
+            if fileobj:
+                json.dump(d, fileobj, ensure_ascii=True, indent=2,
+                          sort_keys=True)
+            else:
+                with codecs.open(path, 'w', 'utf-8') as f:
+                    json.dump(d, f, ensure_ascii=True, indent=2,
+                              sort_keys=True)
+
+    def add_requirements(self, requirements):
+        if self._legacy:
+            self._legacy.add_requirements(requirements)
+        else:
+            run_requires = self._data.setdefault('run_requires', [])
+            always = None
+            for entry in run_requires:
+                if 'environment' not in entry and 'extra' not in entry:
+                    always = entry
+                    break
+            if always is None:
+                always = { 'requires': requirements }
+                run_requires.insert(0, always)
+            else:
+                rset = set(always['requires']) | set(requirements)
+                always['requires'] = sorted(rset)
+
+    def __repr__(self):
+        name = self.name or '(no name)'
+        version = self.version or 'no version'
+        return '<%s %s %s (%s)>' % (self.__class__.__name__,
+                                    self.metadata_version, name, version)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/resources.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/resources.py
new file mode 100644
index 0000000000000000000000000000000000000000..fef52aa103ea369c96567b9af2a5a0ba14db5cb9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/resources.py
@@ -0,0 +1,358 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2013-2017 Vinay Sajip.
+# Licensed to the Python Software Foundation under a contributor agreement.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+from __future__ import unicode_literals
+
+import bisect
+import io
+import logging
+import os
+import pkgutil
+import sys
+import types
+import zipimport
+
+from . import DistlibException
+from .util import cached_property, get_cache_base, Cache
+
+logger = logging.getLogger(__name__)
+
+
+cache = None    # created when needed
+
+
+class ResourceCache(Cache):
+    def __init__(self, base=None):
+        if base is None:
+            # Use native string to avoid issues on 2.x: see Python #20140.
+            base = os.path.join(get_cache_base(), str('resource-cache'))
+        super(ResourceCache, self).__init__(base)
+
+    def is_stale(self, resource, path):
+        """
+        Is the cache stale for the given resource?
+
+        :param resource: The :class:`Resource` being cached.
+        :param path: The path of the resource in the cache.
+        :return: True if the cache is stale.
+        """
+        # Cache invalidation is a hard problem :-)
+        return True
+
+    def get(self, resource):
+        """
+        Get a resource into the cache,
+
+        :param resource: A :class:`Resource` instance.
+        :return: The pathname of the resource in the cache.
+        """
+        prefix, path = resource.finder.get_cache_info(resource)
+        if prefix is None:
+            result = path
+        else:
+            result = os.path.join(self.base, self.prefix_to_dir(prefix), path)
+            dirname = os.path.dirname(result)
+            if not os.path.isdir(dirname):
+                os.makedirs(dirname)
+            if not os.path.exists(result):
+                stale = True
+            else:
+                stale = self.is_stale(resource, path)
+            if stale:
+                # write the bytes of the resource to the cache location
+                with open(result, 'wb') as f:
+                    f.write(resource.bytes)
+        return result
+
+
+class ResourceBase(object):
+    def __init__(self, finder, name):
+        self.finder = finder
+        self.name = name
+
+
+class Resource(ResourceBase):
+    """
+    A class representing an in-package resource, such as a data file. This is
+    not normally instantiated by user code, but rather by a
+    :class:`ResourceFinder` which manages the resource.
+    """
+    is_container = False        # Backwards compatibility
+
+    def as_stream(self):
+        """
+        Get the resource as a stream.
+
+        This is not a property to make it obvious that it returns a new stream
+        each time.
+        """
+        return self.finder.get_stream(self)
+
+    @cached_property
+    def file_path(self):
+        global cache
+        if cache is None:
+            cache = ResourceCache()
+        return cache.get(self)
+
+    @cached_property
+    def bytes(self):
+        return self.finder.get_bytes(self)
+
+    @cached_property
+    def size(self):
+        return self.finder.get_size(self)
+
+
+class ResourceContainer(ResourceBase):
+    is_container = True     # Backwards compatibility
+
+    @cached_property
+    def resources(self):
+        return self.finder.get_resources(self)
+
+
+class ResourceFinder(object):
+    """
+    Resource finder for file system resources.
+    """
+
+    if sys.platform.startswith('java'):
+        skipped_extensions = ('.pyc', '.pyo', '.class')
+    else:
+        skipped_extensions = ('.pyc', '.pyo')
+
+    def __init__(self, module):
+        self.module = module
+        self.loader = getattr(module, '__loader__', None)
+        self.base = os.path.dirname(getattr(module, '__file__', ''))
+
+    def _adjust_path(self, path):
+        return os.path.realpath(path)
+
+    def _make_path(self, resource_name):
+        # Issue #50: need to preserve type of path on Python 2.x
+        # like os.path._get_sep
+        if isinstance(resource_name, bytes):    # should only happen on 2.x
+            sep = b'/'
+        else:
+            sep = '/'
+        parts = resource_name.split(sep)
+        parts.insert(0, self.base)
+        result = os.path.join(*parts)
+        return self._adjust_path(result)
+
+    def _find(self, path):
+        return os.path.exists(path)
+
+    def get_cache_info(self, resource):
+        return None, resource.path
+
+    def find(self, resource_name):
+        path = self._make_path(resource_name)
+        if not self._find(path):
+            result = None
+        else:
+            if self._is_directory(path):
+                result = ResourceContainer(self, resource_name)
+            else:
+                result = Resource(self, resource_name)
+            result.path = path
+        return result
+
+    def get_stream(self, resource):
+        return open(resource.path, 'rb')
+
+    def get_bytes(self, resource):
+        with open(resource.path, 'rb') as f:
+            return f.read()
+
+    def get_size(self, resource):
+        return os.path.getsize(resource.path)
+
+    def get_resources(self, resource):
+        def allowed(f):
+            return (f != '__pycache__' and not
+                    f.endswith(self.skipped_extensions))
+        return set([f for f in os.listdir(resource.path) if allowed(f)])
+
+    def is_container(self, resource):
+        return self._is_directory(resource.path)
+
+    _is_directory = staticmethod(os.path.isdir)
+
+    def iterator(self, resource_name):
+        resource = self.find(resource_name)
+        if resource is not None:
+            todo = [resource]
+            while todo:
+                resource = todo.pop(0)
+                yield resource
+                if resource.is_container:
+                    rname = resource.name
+                    for name in resource.resources:
+                        if not rname:
+                            new_name = name
+                        else:
+                            new_name = '/'.join([rname, name])
+                        child = self.find(new_name)
+                        if child.is_container:
+                            todo.append(child)
+                        else:
+                            yield child
+
+
+class ZipResourceFinder(ResourceFinder):
+    """
+    Resource finder for resources in .zip files.
+    """
+    def __init__(self, module):
+        super(ZipResourceFinder, self).__init__(module)
+        archive = self.loader.archive
+        self.prefix_len = 1 + len(archive)
+        # PyPy doesn't have a _files attr on zipimporter, and you can't set one
+        if hasattr(self.loader, '_files'):
+            self._files = self.loader._files
+        else:
+            self._files = zipimport._zip_directory_cache[archive]
+        self.index = sorted(self._files)
+
+    def _adjust_path(self, path):
+        return path
+
+    def _find(self, path):
+        path = path[self.prefix_len:]
+        if path in self._files:
+            result = True
+        else:
+            if path and path[-1] != os.sep:
+                path = path + os.sep
+            i = bisect.bisect(self.index, path)
+            try:
+                result = self.index[i].startswith(path)
+            except IndexError:
+                result = False
+        if not result:
+            logger.debug('_find failed: %r %r', path, self.loader.prefix)
+        else:
+            logger.debug('_find worked: %r %r', path, self.loader.prefix)
+        return result
+
+    def get_cache_info(self, resource):
+        prefix = self.loader.archive
+        path = resource.path[1 + len(prefix):]
+        return prefix, path
+
+    def get_bytes(self, resource):
+        return self.loader.get_data(resource.path)
+
+    def get_stream(self, resource):
+        return io.BytesIO(self.get_bytes(resource))
+
+    def get_size(self, resource):
+        path = resource.path[self.prefix_len:]
+        return self._files[path][3]
+
+    def get_resources(self, resource):
+        path = resource.path[self.prefix_len:]
+        if path and path[-1] != os.sep:
+            path += os.sep
+        plen = len(path)
+        result = set()
+        i = bisect.bisect(self.index, path)
+        while i < len(self.index):
+            if not self.index[i].startswith(path):
+                break
+            s = self.index[i][plen:]
+            result.add(s.split(os.sep, 1)[0])   # only immediate children
+            i += 1
+        return result
+
+    def _is_directory(self, path):
+        path = path[self.prefix_len:]
+        if path and path[-1] != os.sep:
+            path += os.sep
+        i = bisect.bisect(self.index, path)
+        try:
+            result = self.index[i].startswith(path)
+        except IndexError:
+            result = False
+        return result
+
+
+_finder_registry = {
+    type(None): ResourceFinder,
+    zipimport.zipimporter: ZipResourceFinder
+}
+
+try:
+    # In Python 3.6, _frozen_importlib -> _frozen_importlib_external
+    try:
+        import _frozen_importlib_external as _fi
+    except ImportError:
+        import _frozen_importlib as _fi
+    _finder_registry[_fi.SourceFileLoader] = ResourceFinder
+    _finder_registry[_fi.FileFinder] = ResourceFinder
+    # See issue #146
+    _finder_registry[_fi.SourcelessFileLoader] = ResourceFinder
+    del _fi
+except (ImportError, AttributeError):
+    pass
+
+
+def register_finder(loader, finder_maker):
+    _finder_registry[type(loader)] = finder_maker
+
+
+_finder_cache = {}
+
+
+def finder(package):
+    """
+    Return a resource finder for a package.
+    :param package: The name of the package.
+    :return: A :class:`ResourceFinder` instance for the package.
+    """
+    if package in _finder_cache:
+        result = _finder_cache[package]
+    else:
+        if package not in sys.modules:
+            __import__(package)
+        module = sys.modules[package]
+        path = getattr(module, '__path__', None)
+        if path is None:
+            raise DistlibException('You cannot get a finder for a module, '
+                                   'only for a package')
+        loader = getattr(module, '__loader__', None)
+        finder_maker = _finder_registry.get(type(loader))
+        if finder_maker is None:
+            raise DistlibException('Unable to locate finder for %r' % package)
+        result = finder_maker(module)
+        _finder_cache[package] = result
+    return result
+
+
+_dummy_module = types.ModuleType(str('__dummy__'))
+
+
+def finder_for_path(path):
+    """
+    Return a resource finder for a path, which should represent a container.
+
+    :param path: The path.
+    :return: A :class:`ResourceFinder` instance for the path.
+    """
+    result = None
+    # calls any path hooks, gets importer into cache
+    pkgutil.get_importer(path)
+    loader = sys.path_importer_cache.get(path)
+    finder = _finder_registry.get(type(loader))
+    if finder:
+        module = _dummy_module
+        module.__file__ = os.path.join(path, '')
+        module.__loader__ = loader
+        result = finder(module)
+    return result
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/scripts.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/scripts.py
new file mode 100644
index 0000000000000000000000000000000000000000..d2706242b8aac125a66450d5ce8dcd3395336182
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/scripts.py
@@ -0,0 +1,437 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2013-2015 Vinay Sajip.
+# Licensed to the Python Software Foundation under a contributor agreement.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+from io import BytesIO
+import logging
+import os
+import re
+import struct
+import sys
+import time
+from zipfile import ZipInfo
+
+from .compat import sysconfig, detect_encoding, ZipFile
+from .resources import finder
+from .util import (FileOperator, get_export_entry, convert_path,
+                   get_executable, get_platform, in_venv)
+
+logger = logging.getLogger(__name__)
+
+_DEFAULT_MANIFEST = '''
+
+
+ 
+
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+'''.strip()
+
+# check if Python is called on the first line with this expression
+FIRST_LINE_RE = re.compile(b'^#!.*pythonw?[0-9.]*([ \t].*)?$')
+SCRIPT_TEMPLATE = r'''# -*- coding: utf-8 -*-
+import re
+import sys
+from %(module)s import %(import_name)s
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
+    sys.exit(%(func)s())
+'''
+
+
+def enquote_executable(executable):
+    if ' ' in executable:
+        # make sure we quote only the executable in case of env
+        # for example /usr/bin/env "/dir with spaces/bin/jython"
+        # instead of "/usr/bin/env /dir with spaces/bin/jython"
+        # otherwise whole
+        if executable.startswith('/usr/bin/env '):
+            env, _executable = executable.split(' ', 1)
+            if ' ' in _executable and not _executable.startswith('"'):
+                executable = '%s "%s"' % (env, _executable)
+        else:
+            if not executable.startswith('"'):
+                executable = '"%s"' % executable
+    return executable
+
+# Keep the old name around (for now), as there is at least one project using it!
+_enquote_executable = enquote_executable
+
+class ScriptMaker(object):
+    """
+    A class to copy or create scripts from source scripts or callable
+    specifications.
+    """
+    script_template = SCRIPT_TEMPLATE
+
+    executable = None  # for shebangs
+
+    def __init__(self, source_dir, target_dir, add_launchers=True,
+                 dry_run=False, fileop=None):
+        self.source_dir = source_dir
+        self.target_dir = target_dir
+        self.add_launchers = add_launchers
+        self.force = False
+        self.clobber = False
+        # It only makes sense to set mode bits on POSIX.
+        self.set_mode = (os.name == 'posix') or (os.name == 'java' and
+                                                 os._name == 'posix')
+        self.variants = set(('', 'X.Y'))
+        self._fileop = fileop or FileOperator(dry_run)
+
+        self._is_nt = os.name == 'nt' or (
+            os.name == 'java' and os._name == 'nt')
+        self.version_info = sys.version_info
+
+    def _get_alternate_executable(self, executable, options):
+        if options.get('gui', False) and self._is_nt:  # pragma: no cover
+            dn, fn = os.path.split(executable)
+            fn = fn.replace('python', 'pythonw')
+            executable = os.path.join(dn, fn)
+        return executable
+
+    if sys.platform.startswith('java'):  # pragma: no cover
+        def _is_shell(self, executable):
+            """
+            Determine if the specified executable is a script
+            (contains a #! line)
+            """
+            try:
+                with open(executable) as fp:
+                    return fp.read(2) == '#!'
+            except (OSError, IOError):
+                logger.warning('Failed to open %s', executable)
+                return False
+
+        def _fix_jython_executable(self, executable):
+            if self._is_shell(executable):
+                # Workaround for Jython is not needed on Linux systems.
+                import java
+
+                if java.lang.System.getProperty('os.name') == 'Linux':
+                    return executable
+            elif executable.lower().endswith('jython.exe'):
+                # Use wrapper exe for Jython on Windows
+                return executable
+            return '/usr/bin/env %s' % executable
+
+    def _build_shebang(self, executable, post_interp):
+        """
+        Build a shebang line. In the simple case (on Windows, or a shebang line
+        which is not too long or contains spaces) use a simple formulation for
+        the shebang. Otherwise, use /bin/sh as the executable, with a contrived
+        shebang which allows the script to run either under Python or sh, using
+        suitable quoting. Thanks to Harald Nordgren for his input.
+
+        See also: http://www.in-ulm.de/~mascheck/various/shebang/#length
+                  https://hg.mozilla.org/mozilla-central/file/tip/mach
+        """
+        if os.name != 'posix':
+            simple_shebang = True
+        else:
+            # Add 3 for '#!' prefix and newline suffix.
+            shebang_length = len(executable) + len(post_interp) + 3
+            if sys.platform == 'darwin':
+                max_shebang_length = 512
+            else:
+                max_shebang_length = 127
+            simple_shebang = ((b' ' not in executable) and
+                              (shebang_length <= max_shebang_length))
+
+        if simple_shebang:
+            result = b'#!' + executable + post_interp + b'\n'
+        else:
+            result = b'#!/bin/sh\n'
+            result += b"'''exec' " + executable + post_interp + b' "$0" "$@"\n'
+            result += b"' '''"
+        return result
+
+    def _get_shebang(self, encoding, post_interp=b'', options=None):
+        enquote = True
+        if self.executable:
+            executable = self.executable
+            enquote = False     # assume this will be taken care of
+        elif not sysconfig.is_python_build():
+            executable = get_executable()
+        elif in_venv():  # pragma: no cover
+            executable = os.path.join(sysconfig.get_path('scripts'),
+                            'python%s' % sysconfig.get_config_var('EXE'))
+        else:  # pragma: no cover
+            executable = os.path.join(
+                sysconfig.get_config_var('BINDIR'),
+               'python%s%s' % (sysconfig.get_config_var('VERSION'),
+                               sysconfig.get_config_var('EXE')))
+            if not os.path.isfile(executable):
+                # for Python builds from source on Windows, no Python executables with
+                # a version suffix are created, so we use python.exe
+                executable = os.path.join(sysconfig.get_config_var('BINDIR'),
+                                'python%s' % (sysconfig.get_config_var('EXE')))
+        if options:
+            executable = self._get_alternate_executable(executable, options)
+
+        if sys.platform.startswith('java'):  # pragma: no cover
+            executable = self._fix_jython_executable(executable)
+
+        # Normalise case for Windows - COMMENTED OUT
+        # executable = os.path.normcase(executable)
+        # N.B. The normalising operation above has been commented out: See
+        # issue #124. Although paths in Windows are generally case-insensitive,
+        # they aren't always. For example, a path containing a ẞ (which is a
+        # LATIN CAPITAL LETTER SHARP S - U+1E9E) is normcased to ß (which is a
+        # LATIN SMALL LETTER SHARP S' - U+00DF). The two are not considered by
+        # Windows as equivalent in path names.
+
+        # If the user didn't specify an executable, it may be necessary to
+        # cater for executable paths with spaces (not uncommon on Windows)
+        if enquote:
+            executable = enquote_executable(executable)
+        # Issue #51: don't use fsencode, since we later try to
+        # check that the shebang is decodable using utf-8.
+        executable = executable.encode('utf-8')
+        # in case of IronPython, play safe and enable frames support
+        if (sys.platform == 'cli' and '-X:Frames' not in post_interp
+            and '-X:FullFrames' not in post_interp):  # pragma: no cover
+            post_interp += b' -X:Frames'
+        shebang = self._build_shebang(executable, post_interp)
+        # Python parser starts to read a script using UTF-8 until
+        # it gets a #coding:xxx cookie. The shebang has to be the
+        # first line of a file, the #coding:xxx cookie cannot be
+        # written before. So the shebang has to be decodable from
+        # UTF-8.
+        try:
+            shebang.decode('utf-8')
+        except UnicodeDecodeError:  # pragma: no cover
+            raise ValueError(
+                'The shebang (%r) is not decodable from utf-8' % shebang)
+        # If the script is encoded to a custom encoding (use a
+        # #coding:xxx cookie), the shebang has to be decodable from
+        # the script encoding too.
+        if encoding != 'utf-8':
+            try:
+                shebang.decode(encoding)
+            except UnicodeDecodeError:  # pragma: no cover
+                raise ValueError(
+                    'The shebang (%r) is not decodable '
+                    'from the script encoding (%r)' % (shebang, encoding))
+        return shebang
+
+    def _get_script_text(self, entry):
+        return self.script_template % dict(module=entry.prefix,
+                                           import_name=entry.suffix.split('.')[0],
+                                           func=entry.suffix)
+
+    manifest = _DEFAULT_MANIFEST
+
+    def get_manifest(self, exename):
+        base = os.path.basename(exename)
+        return self.manifest % base
+
+    def _write_script(self, names, shebang, script_bytes, filenames, ext):
+        use_launcher = self.add_launchers and self._is_nt
+        linesep = os.linesep.encode('utf-8')
+        if not shebang.endswith(linesep):
+            shebang += linesep
+        if not use_launcher:
+            script_bytes = shebang + script_bytes
+        else:  # pragma: no cover
+            if ext == 'py':
+                launcher = self._get_launcher('t')
+            else:
+                launcher = self._get_launcher('w')
+            stream = BytesIO()
+            with ZipFile(stream, 'w') as zf:
+                source_date_epoch = os.environ.get('SOURCE_DATE_EPOCH')
+                if source_date_epoch:
+                    date_time = time.gmtime(int(source_date_epoch))[:6]
+                    zinfo = ZipInfo(filename='__main__.py', date_time=date_time)
+                    zf.writestr(zinfo, script_bytes)
+                else:
+                    zf.writestr('__main__.py', script_bytes)
+            zip_data = stream.getvalue()
+            script_bytes = launcher + shebang + zip_data
+        for name in names:
+            outname = os.path.join(self.target_dir, name)
+            if use_launcher:  # pragma: no cover
+                n, e = os.path.splitext(outname)
+                if e.startswith('.py'):
+                    outname = n
+                outname = '%s.exe' % outname
+                try:
+                    self._fileop.write_binary_file(outname, script_bytes)
+                except Exception:
+                    # Failed writing an executable - it might be in use.
+                    logger.warning('Failed to write executable - trying to '
+                                   'use .deleteme logic')
+                    dfname = '%s.deleteme' % outname
+                    if os.path.exists(dfname):
+                        os.remove(dfname)       # Not allowed to fail here
+                    os.rename(outname, dfname)  # nor here
+                    self._fileop.write_binary_file(outname, script_bytes)
+                    logger.debug('Able to replace executable using '
+                                 '.deleteme logic')
+                    try:
+                        os.remove(dfname)
+                    except Exception:
+                        pass    # still in use - ignore error
+            else:
+                if self._is_nt and not outname.endswith('.' + ext):  # pragma: no cover
+                    outname = '%s.%s' % (outname, ext)
+                if os.path.exists(outname) and not self.clobber:
+                    logger.warning('Skipping existing file %s', outname)
+                    continue
+                self._fileop.write_binary_file(outname, script_bytes)
+                if self.set_mode:
+                    self._fileop.set_executable_mode([outname])
+            filenames.append(outname)
+
+    variant_separator = '-'
+
+    def get_script_filenames(self, name):
+        result = set()
+        if '' in self.variants:
+            result.add(name)
+        if 'X' in self.variants:
+            result.add('%s%s' % (name, self.version_info[0]))
+        if 'X.Y' in self.variants:
+            result.add('%s%s%s.%s' % (name, self.variant_separator,
+                                      self.version_info[0], self.version_info[1]))
+        return result
+
+    def _make_script(self, entry, filenames, options=None):
+        post_interp = b''
+        if options:
+            args = options.get('interpreter_args', [])
+            if args:
+                args = ' %s' % ' '.join(args)
+                post_interp = args.encode('utf-8')
+        shebang = self._get_shebang('utf-8', post_interp, options=options)
+        script = self._get_script_text(entry).encode('utf-8')
+        scriptnames = self.get_script_filenames(entry.name)
+        if options and options.get('gui', False):
+            ext = 'pyw'
+        else:
+            ext = 'py'
+        self._write_script(scriptnames, shebang, script, filenames, ext)
+
+    def _copy_script(self, script, filenames):
+        adjust = False
+        script = os.path.join(self.source_dir, convert_path(script))
+        outname = os.path.join(self.target_dir, os.path.basename(script))
+        if not self.force and not self._fileop.newer(script, outname):
+            logger.debug('not copying %s (up-to-date)', script)
+            return
+
+        # Always open the file, but ignore failures in dry-run mode --
+        # that way, we'll get accurate feedback if we can read the
+        # script.
+        try:
+            f = open(script, 'rb')
+        except IOError:  # pragma: no cover
+            if not self.dry_run:
+                raise
+            f = None
+        else:
+            first_line = f.readline()
+            if not first_line:  # pragma: no cover
+                logger.warning('%s is an empty file (skipping)', script)
+                return
+
+            match = FIRST_LINE_RE.match(first_line.replace(b'\r\n', b'\n'))
+            if match:
+                adjust = True
+                post_interp = match.group(1) or b''
+
+        if not adjust:
+            if f:
+                f.close()
+            self._fileop.copy_file(script, outname)
+            if self.set_mode:
+                self._fileop.set_executable_mode([outname])
+            filenames.append(outname)
+        else:
+            logger.info('copying and adjusting %s -> %s', script,
+                        self.target_dir)
+            if not self._fileop.dry_run:
+                encoding, lines = detect_encoding(f.readline)
+                f.seek(0)
+                shebang = self._get_shebang(encoding, post_interp)
+                if b'pythonw' in first_line:  # pragma: no cover
+                    ext = 'pyw'
+                else:
+                    ext = 'py'
+                n = os.path.basename(outname)
+                self._write_script([n], shebang, f.read(), filenames, ext)
+            if f:
+                f.close()
+
+    @property
+    def dry_run(self):
+        return self._fileop.dry_run
+
+    @dry_run.setter
+    def dry_run(self, value):
+        self._fileop.dry_run = value
+
+    if os.name == 'nt' or (os.name == 'java' and os._name == 'nt'):  # pragma: no cover
+        # Executable launcher support.
+        # Launchers are from https://bitbucket.org/vinay.sajip/simple_launcher/
+
+        def _get_launcher(self, kind):
+            if struct.calcsize('P') == 8:   # 64-bit
+                bits = '64'
+            else:
+                bits = '32'
+            platform_suffix = '-arm' if get_platform() == 'win-arm64' else ''
+            name = '%s%s%s.exe' % (kind, bits, platform_suffix)
+            # Issue 31: don't hardcode an absolute package name, but
+            # determine it relative to the current package
+            distlib_package = __name__.rsplit('.', 1)[0]
+            resource = finder(distlib_package).find(name)
+            if not resource:
+                msg = ('Unable to find resource %s in package %s' % (name,
+                       distlib_package))
+                raise ValueError(msg)
+            return resource.bytes
+
+    # Public API follows
+
+    def make(self, specification, options=None):
+        """
+        Make a script.
+
+        :param specification: The specification, which is either a valid export
+                              entry specification (to make a script from a
+                              callable) or a filename (to make a script by
+                              copying from a source location).
+        :param options: A dictionary of options controlling script generation.
+        :return: A list of all absolute pathnames written to.
+        """
+        filenames = []
+        entry = get_export_entry(specification)
+        if entry is None:
+            self._copy_script(specification, filenames)
+        else:
+            self._make_script(entry, filenames, options=options)
+        return filenames
+
+    def make_multiple(self, specifications, options=None):
+        """
+        Take a list of specifications and make scripts from them,
+        :param specifications: A list of specifications.
+        :return: A list of all absolute pathnames written to,
+        """
+        filenames = []
+        for specification in specifications:
+            filenames.extend(self.make(specification, options))
+        return filenames
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/t32.exe b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/t32.exe
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diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/t64-arm.exe b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/t64-arm.exe
new file mode 100644
index 0000000000000000000000000000000000000000..4c236ed0ab8253ceee9276ddc3cf5ed9a7ea6a4c
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ebc4c06b7d95e74e315419ee7e88e1d0f71e9e9477538c00a93a9ff8c66a6cfc
+size 182784
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/t64.exe b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/t64.exe
new file mode 100644
index 0000000000000000000000000000000000000000..3fd3d2df6541617229f21bdbb49fbbfc880b7f50
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+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/t64.exe
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:81a618f21cb87db9076134e70388b6e9cb7c2106739011b6a51772d22cae06b7
+size 108032
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/util.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/util.py
new file mode 100644
index 0000000000000000000000000000000000000000..dd01849d997e5ae9dc9809295e29ceb871b14216
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/util.py
@@ -0,0 +1,1932 @@
+#
+# Copyright (C) 2012-2021 The Python Software Foundation.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+import codecs
+from collections import deque
+import contextlib
+import csv
+from glob import iglob as std_iglob
+import io
+import json
+import logging
+import os
+import py_compile
+import re
+import socket
+try:
+    import ssl
+except ImportError:  # pragma: no cover
+    ssl = None
+import subprocess
+import sys
+import tarfile
+import tempfile
+import textwrap
+
+try:
+    import threading
+except ImportError:  # pragma: no cover
+    import dummy_threading as threading
+import time
+
+from . import DistlibException
+from .compat import (string_types, text_type, shutil, raw_input, StringIO,
+                     cache_from_source, urlopen, urljoin, httplib, xmlrpclib,
+                     splittype, HTTPHandler, BaseConfigurator, valid_ident,
+                     Container, configparser, URLError, ZipFile, fsdecode,
+                     unquote, urlparse)
+
+logger = logging.getLogger(__name__)
+
+#
+# Requirement parsing code as per PEP 508
+#
+
+IDENTIFIER = re.compile(r'^([\w\.-]+)\s*')
+VERSION_IDENTIFIER = re.compile(r'^([\w\.*+-]+)\s*')
+COMPARE_OP = re.compile(r'^(<=?|>=?|={2,3}|[~!]=)\s*')
+MARKER_OP = re.compile(r'^((<=?)|(>=?)|={2,3}|[~!]=|in|not\s+in)\s*')
+OR = re.compile(r'^or\b\s*')
+AND = re.compile(r'^and\b\s*')
+NON_SPACE = re.compile(r'(\S+)\s*')
+STRING_CHUNK = re.compile(r'([\s\w\.{}()*+#:;,/?!~`@$%^&=|<>\[\]-]+)')
+
+
+def parse_marker(marker_string):
+    """
+    Parse a marker string and return a dictionary containing a marker expression.
+
+    The dictionary will contain keys "op", "lhs" and "rhs" for non-terminals in
+    the expression grammar, or strings. A string contained in quotes is to be
+    interpreted as a literal string, and a string not contained in quotes is a
+    variable (such as os_name).
+    """
+    def marker_var(remaining):
+        # either identifier, or literal string
+        m = IDENTIFIER.match(remaining)
+        if m:
+            result = m.groups()[0]
+            remaining = remaining[m.end():]
+        elif not remaining:
+            raise SyntaxError('unexpected end of input')
+        else:
+            q = remaining[0]
+            if q not in '\'"':
+                raise SyntaxError('invalid expression: %s' % remaining)
+            oq = '\'"'.replace(q, '')
+            remaining = remaining[1:]
+            parts = [q]
+            while remaining:
+                # either a string chunk, or oq, or q to terminate
+                if remaining[0] == q:
+                    break
+                elif remaining[0] == oq:
+                    parts.append(oq)
+                    remaining = remaining[1:]
+                else:
+                    m = STRING_CHUNK.match(remaining)
+                    if not m:
+                        raise SyntaxError('error in string literal: %s' % remaining)
+                    parts.append(m.groups()[0])
+                    remaining = remaining[m.end():]
+            else:
+                s = ''.join(parts)
+                raise SyntaxError('unterminated string: %s' % s)
+            parts.append(q)
+            result = ''.join(parts)
+            remaining = remaining[1:].lstrip() # skip past closing quote
+        return result, remaining
+
+    def marker_expr(remaining):
+        if remaining and remaining[0] == '(':
+            result, remaining = marker(remaining[1:].lstrip())
+            if remaining[0] != ')':
+                raise SyntaxError('unterminated parenthesis: %s' % remaining)
+            remaining = remaining[1:].lstrip()
+        else:
+            lhs, remaining = marker_var(remaining)
+            while remaining:
+                m = MARKER_OP.match(remaining)
+                if not m:
+                    break
+                op = m.groups()[0]
+                remaining = remaining[m.end():]
+                rhs, remaining = marker_var(remaining)
+                lhs = {'op': op, 'lhs': lhs, 'rhs': rhs}
+            result = lhs
+        return result, remaining
+
+    def marker_and(remaining):
+        lhs, remaining = marker_expr(remaining)
+        while remaining:
+            m = AND.match(remaining)
+            if not m:
+                break
+            remaining = remaining[m.end():]
+            rhs, remaining = marker_expr(remaining)
+            lhs = {'op': 'and', 'lhs': lhs, 'rhs': rhs}
+        return lhs, remaining
+
+    def marker(remaining):
+        lhs, remaining = marker_and(remaining)
+        while remaining:
+            m = OR.match(remaining)
+            if not m:
+                break
+            remaining = remaining[m.end():]
+            rhs, remaining = marker_and(remaining)
+            lhs = {'op': 'or', 'lhs': lhs, 'rhs': rhs}
+        return lhs, remaining
+
+    return marker(marker_string)
+
+
+def parse_requirement(req):
+    """
+    Parse a requirement passed in as a string. Return a Container
+    whose attributes contain the various parts of the requirement.
+    """
+    remaining = req.strip()
+    if not remaining or remaining.startswith('#'):
+        return None
+    m = IDENTIFIER.match(remaining)
+    if not m:
+        raise SyntaxError('name expected: %s' % remaining)
+    distname = m.groups()[0]
+    remaining = remaining[m.end():]
+    extras = mark_expr = versions = uri = None
+    if remaining and remaining[0] == '[':
+        i = remaining.find(']', 1)
+        if i < 0:
+            raise SyntaxError('unterminated extra: %s' % remaining)
+        s = remaining[1:i]
+        remaining = remaining[i + 1:].lstrip()
+        extras = []
+        while s:
+            m = IDENTIFIER.match(s)
+            if not m:
+                raise SyntaxError('malformed extra: %s' % s)
+            extras.append(m.groups()[0])
+            s = s[m.end():]
+            if not s:
+                break
+            if s[0] != ',':
+                raise SyntaxError('comma expected in extras: %s' % s)
+            s = s[1:].lstrip()
+        if not extras:
+            extras = None
+    if remaining:
+        if remaining[0] == '@':
+            # it's a URI
+            remaining = remaining[1:].lstrip()
+            m = NON_SPACE.match(remaining)
+            if not m:
+                raise SyntaxError('invalid URI: %s' % remaining)
+            uri = m.groups()[0]
+            t = urlparse(uri)
+            # there are issues with Python and URL parsing, so this test
+            # is a bit crude. See bpo-20271, bpo-23505. Python doesn't
+            # always parse invalid URLs correctly - it should raise
+            # exceptions for malformed URLs
+            if not (t.scheme and t.netloc):
+                raise SyntaxError('Invalid URL: %s' % uri)
+            remaining = remaining[m.end():].lstrip()
+        else:
+
+            def get_versions(ver_remaining):
+                """
+                Return a list of operator, version tuples if any are
+                specified, else None.
+                """
+                m = COMPARE_OP.match(ver_remaining)
+                versions = None
+                if m:
+                    versions = []
+                    while True:
+                        op = m.groups()[0]
+                        ver_remaining = ver_remaining[m.end():]
+                        m = VERSION_IDENTIFIER.match(ver_remaining)
+                        if not m:
+                            raise SyntaxError('invalid version: %s' % ver_remaining)
+                        v = m.groups()[0]
+                        versions.append((op, v))
+                        ver_remaining = ver_remaining[m.end():]
+                        if not ver_remaining or ver_remaining[0] != ',':
+                            break
+                        ver_remaining = ver_remaining[1:].lstrip()
+                        # Some packages have a trailing comma which would break things
+                        # See issue #148
+                        if not ver_remaining:
+                            break
+                        m = COMPARE_OP.match(ver_remaining)
+                        if not m:
+                            raise SyntaxError('invalid constraint: %s' % ver_remaining)
+                    if not versions:
+                        versions = None
+                return versions, ver_remaining
+
+            if remaining[0] != '(':
+                versions, remaining = get_versions(remaining)
+            else:
+                i = remaining.find(')', 1)
+                if i < 0:
+                    raise SyntaxError('unterminated parenthesis: %s' % remaining)
+                s = remaining[1:i]
+                remaining = remaining[i + 1:].lstrip()
+                # As a special diversion from PEP 508, allow a version number
+                # a.b.c in parentheses as a synonym for ~= a.b.c (because this
+                # is allowed in earlier PEPs)
+                if COMPARE_OP.match(s):
+                    versions, _ = get_versions(s)
+                else:
+                    m = VERSION_IDENTIFIER.match(s)
+                    if not m:
+                        raise SyntaxError('invalid constraint: %s' % s)
+                    v = m.groups()[0]
+                    s = s[m.end():].lstrip()
+                    if s:
+                        raise SyntaxError('invalid constraint: %s' % s)
+                    versions = [('~=', v)]
+
+    if remaining:
+        if remaining[0] != ';':
+            raise SyntaxError('invalid requirement: %s' % remaining)
+        remaining = remaining[1:].lstrip()
+
+        mark_expr, remaining = parse_marker(remaining)
+
+    if remaining and remaining[0] != '#':
+        raise SyntaxError('unexpected trailing data: %s' % remaining)
+
+    if not versions:
+        rs = distname
+    else:
+        rs = '%s %s' % (distname, ', '.join(['%s %s' % con for con in versions]))
+    return Container(name=distname, extras=extras, constraints=versions,
+                     marker=mark_expr, url=uri, requirement=rs)
+
+
+def get_resources_dests(resources_root, rules):
+    """Find destinations for resources files"""
+
+    def get_rel_path(root, path):
+        # normalizes and returns a lstripped-/-separated path
+        root = root.replace(os.path.sep, '/')
+        path = path.replace(os.path.sep, '/')
+        assert path.startswith(root)
+        return path[len(root):].lstrip('/')
+
+    destinations = {}
+    for base, suffix, dest in rules:
+        prefix = os.path.join(resources_root, base)
+        for abs_base in iglob(prefix):
+            abs_glob = os.path.join(abs_base, suffix)
+            for abs_path in iglob(abs_glob):
+                resource_file = get_rel_path(resources_root, abs_path)
+                if dest is None:  # remove the entry if it was here
+                    destinations.pop(resource_file, None)
+                else:
+                    rel_path = get_rel_path(abs_base, abs_path)
+                    rel_dest = dest.replace(os.path.sep, '/').rstrip('/')
+                    destinations[resource_file] = rel_dest + '/' + rel_path
+    return destinations
+
+
+def in_venv():
+    if hasattr(sys, 'real_prefix'):
+        # virtualenv venvs
+        result = True
+    else:
+        # PEP 405 venvs
+        result = sys.prefix != getattr(sys, 'base_prefix', sys.prefix)
+    return result
+
+
+def get_executable():
+# The __PYVENV_LAUNCHER__ dance is apparently no longer needed, as
+# changes to the stub launcher mean that sys.executable always points
+# to the stub on OS X
+#    if sys.platform == 'darwin' and ('__PYVENV_LAUNCHER__'
+#                                     in os.environ):
+#        result =  os.environ['__PYVENV_LAUNCHER__']
+#    else:
+#        result = sys.executable
+#    return result
+    # Avoid normcasing: see issue #143
+    # result = os.path.normcase(sys.executable)
+    result = sys.executable
+    if not isinstance(result, text_type):
+        result = fsdecode(result)
+    return result
+
+
+def proceed(prompt, allowed_chars, error_prompt=None, default=None):
+    p = prompt
+    while True:
+        s = raw_input(p)
+        p = prompt
+        if not s and default:
+            s = default
+        if s:
+            c = s[0].lower()
+            if c in allowed_chars:
+                break
+            if error_prompt:
+                p = '%c: %s\n%s' % (c, error_prompt, prompt)
+    return c
+
+
+def extract_by_key(d, keys):
+    if isinstance(keys, string_types):
+        keys = keys.split()
+    result = {}
+    for key in keys:
+        if key in d:
+            result[key] = d[key]
+    return result
+
+def read_exports(stream):
+    if sys.version_info[0] >= 3:
+        # needs to be a text stream
+        stream = codecs.getreader('utf-8')(stream)
+    # Try to load as JSON, falling back on legacy format
+    data = stream.read()
+    stream = StringIO(data)
+    try:
+        jdata = json.load(stream)
+        result = jdata['extensions']['python.exports']['exports']
+        for group, entries in result.items():
+            for k, v in entries.items():
+                s = '%s = %s' % (k, v)
+                entry = get_export_entry(s)
+                assert entry is not None
+                entries[k] = entry
+        return result
+    except Exception:
+        stream.seek(0, 0)
+
+    def read_stream(cp, stream):
+        if hasattr(cp, 'read_file'):
+            cp.read_file(stream)
+        else:
+            cp.readfp(stream)
+
+    cp = configparser.ConfigParser()
+    try:
+        read_stream(cp, stream)
+    except configparser.MissingSectionHeaderError:
+        stream.close()
+        data = textwrap.dedent(data)
+        stream = StringIO(data)
+        read_stream(cp, stream)
+
+    result = {}
+    for key in cp.sections():
+        result[key] = entries = {}
+        for name, value in cp.items(key):
+            s = '%s = %s' % (name, value)
+            entry = get_export_entry(s)
+            assert entry is not None
+            #entry.dist = self
+            entries[name] = entry
+    return result
+
+
+def write_exports(exports, stream):
+    if sys.version_info[0] >= 3:
+        # needs to be a text stream
+        stream = codecs.getwriter('utf-8')(stream)
+    cp = configparser.ConfigParser()
+    for k, v in exports.items():
+        # TODO check k, v for valid values
+        cp.add_section(k)
+        for entry in v.values():
+            if entry.suffix is None:
+                s = entry.prefix
+            else:
+                s = '%s:%s' % (entry.prefix, entry.suffix)
+            if entry.flags:
+                s = '%s [%s]' % (s, ', '.join(entry.flags))
+            cp.set(k, entry.name, s)
+    cp.write(stream)
+
+
+@contextlib.contextmanager
+def tempdir():
+    td = tempfile.mkdtemp()
+    try:
+        yield td
+    finally:
+        shutil.rmtree(td)
+
+@contextlib.contextmanager
+def chdir(d):
+    cwd = os.getcwd()
+    try:
+        os.chdir(d)
+        yield
+    finally:
+        os.chdir(cwd)
+
+
+@contextlib.contextmanager
+def socket_timeout(seconds=15):
+    cto = socket.getdefaulttimeout()
+    try:
+        socket.setdefaulttimeout(seconds)
+        yield
+    finally:
+        socket.setdefaulttimeout(cto)
+
+
+class cached_property(object):
+    def __init__(self, func):
+        self.func = func
+        #for attr in ('__name__', '__module__', '__doc__'):
+        #    setattr(self, attr, getattr(func, attr, None))
+
+    def __get__(self, obj, cls=None):
+        if obj is None:
+            return self
+        value = self.func(obj)
+        object.__setattr__(obj, self.func.__name__, value)
+        #obj.__dict__[self.func.__name__] = value = self.func(obj)
+        return value
+
+def convert_path(pathname):
+    """Return 'pathname' as a name that will work on the native filesystem.
+
+    The path is split on '/' and put back together again using the current
+    directory separator.  Needed because filenames in the setup script are
+    always supplied in Unix style, and have to be converted to the local
+    convention before we can actually use them in the filesystem.  Raises
+    ValueError on non-Unix-ish systems if 'pathname' either starts or
+    ends with a slash.
+    """
+    if os.sep == '/':
+        return pathname
+    if not pathname:
+        return pathname
+    if pathname[0] == '/':
+        raise ValueError("path '%s' cannot be absolute" % pathname)
+    if pathname[-1] == '/':
+        raise ValueError("path '%s' cannot end with '/'" % pathname)
+
+    paths = pathname.split('/')
+    while os.curdir in paths:
+        paths.remove(os.curdir)
+    if not paths:
+        return os.curdir
+    return os.path.join(*paths)
+
+
+class FileOperator(object):
+    def __init__(self, dry_run=False):
+        self.dry_run = dry_run
+        self.ensured = set()
+        self._init_record()
+
+    def _init_record(self):
+        self.record = False
+        self.files_written = set()
+        self.dirs_created = set()
+
+    def record_as_written(self, path):
+        if self.record:
+            self.files_written.add(path)
+
+    def newer(self, source, target):
+        """Tell if the target is newer than the source.
+
+        Returns true if 'source' exists and is more recently modified than
+        'target', or if 'source' exists and 'target' doesn't.
+
+        Returns false if both exist and 'target' is the same age or younger
+        than 'source'. Raise PackagingFileError if 'source' does not exist.
+
+        Note that this test is not very accurate: files created in the same
+        second will have the same "age".
+        """
+        if not os.path.exists(source):
+            raise DistlibException("file '%r' does not exist" %
+                                   os.path.abspath(source))
+        if not os.path.exists(target):
+            return True
+
+        return os.stat(source).st_mtime > os.stat(target).st_mtime
+
+    def copy_file(self, infile, outfile, check=True):
+        """Copy a file respecting dry-run and force flags.
+        """
+        self.ensure_dir(os.path.dirname(outfile))
+        logger.info('Copying %s to %s', infile, outfile)
+        if not self.dry_run:
+            msg = None
+            if check:
+                if os.path.islink(outfile):
+                    msg = '%s is a symlink' % outfile
+                elif os.path.exists(outfile) and not os.path.isfile(outfile):
+                    msg = '%s is a non-regular file' % outfile
+            if msg:
+                raise ValueError(msg + ' which would be overwritten')
+            shutil.copyfile(infile, outfile)
+        self.record_as_written(outfile)
+
+    def copy_stream(self, instream, outfile, encoding=None):
+        assert not os.path.isdir(outfile)
+        self.ensure_dir(os.path.dirname(outfile))
+        logger.info('Copying stream %s to %s', instream, outfile)
+        if not self.dry_run:
+            if encoding is None:
+                outstream = open(outfile, 'wb')
+            else:
+                outstream = codecs.open(outfile, 'w', encoding=encoding)
+            try:
+                shutil.copyfileobj(instream, outstream)
+            finally:
+                outstream.close()
+        self.record_as_written(outfile)
+
+    def write_binary_file(self, path, data):
+        self.ensure_dir(os.path.dirname(path))
+        if not self.dry_run:
+            if os.path.exists(path):
+                os.remove(path)
+            with open(path, 'wb') as f:
+                f.write(data)
+        self.record_as_written(path)
+
+    def write_text_file(self, path, data, encoding):
+        self.write_binary_file(path, data.encode(encoding))
+
+    def set_mode(self, bits, mask, files):
+        if os.name == 'posix' or (os.name == 'java' and os._name == 'posix'):
+            # Set the executable bits (owner, group, and world) on
+            # all the files specified.
+            for f in files:
+                if self.dry_run:
+                    logger.info("changing mode of %s", f)
+                else:
+                    mode = (os.stat(f).st_mode | bits) & mask
+                    logger.info("changing mode of %s to %o", f, mode)
+                    os.chmod(f, mode)
+
+    set_executable_mode = lambda s, f: s.set_mode(0o555, 0o7777, f)
+
+    def ensure_dir(self, path):
+        path = os.path.abspath(path)
+        if path not in self.ensured and not os.path.exists(path):
+            self.ensured.add(path)
+            d, f = os.path.split(path)
+            self.ensure_dir(d)
+            logger.info('Creating %s' % path)
+            if not self.dry_run:
+                os.mkdir(path)
+            if self.record:
+                self.dirs_created.add(path)
+
+    def byte_compile(self, path, optimize=False, force=False, prefix=None, hashed_invalidation=False):
+        dpath = cache_from_source(path, not optimize)
+        logger.info('Byte-compiling %s to %s', path, dpath)
+        if not self.dry_run:
+            if force or self.newer(path, dpath):
+                if not prefix:
+                    diagpath = None
+                else:
+                    assert path.startswith(prefix)
+                    diagpath = path[len(prefix):]
+            compile_kwargs = {}
+            if hashed_invalidation and hasattr(py_compile, 'PycInvalidationMode'):
+                compile_kwargs['invalidation_mode'] = py_compile.PycInvalidationMode.CHECKED_HASH
+            py_compile.compile(path, dpath, diagpath, True, **compile_kwargs)     # raise error
+        self.record_as_written(dpath)
+        return dpath
+
+    def ensure_removed(self, path):
+        if os.path.exists(path):
+            if os.path.isdir(path) and not os.path.islink(path):
+                logger.debug('Removing directory tree at %s', path)
+                if not self.dry_run:
+                    shutil.rmtree(path)
+                if self.record:
+                    if path in self.dirs_created:
+                        self.dirs_created.remove(path)
+            else:
+                if os.path.islink(path):
+                    s = 'link'
+                else:
+                    s = 'file'
+                logger.debug('Removing %s %s', s, path)
+                if not self.dry_run:
+                    os.remove(path)
+                if self.record:
+                    if path in self.files_written:
+                        self.files_written.remove(path)
+
+    def is_writable(self, path):
+        result = False
+        while not result:
+            if os.path.exists(path):
+                result = os.access(path, os.W_OK)
+                break
+            parent = os.path.dirname(path)
+            if parent == path:
+                break
+            path = parent
+        return result
+
+    def commit(self):
+        """
+        Commit recorded changes, turn off recording, return
+        changes.
+        """
+        assert self.record
+        result = self.files_written, self.dirs_created
+        self._init_record()
+        return result
+
+    def rollback(self):
+        if not self.dry_run:
+            for f in list(self.files_written):
+                if os.path.exists(f):
+                    os.remove(f)
+            # dirs should all be empty now, except perhaps for
+            # __pycache__ subdirs
+            # reverse so that subdirs appear before their parents
+            dirs = sorted(self.dirs_created, reverse=True)
+            for d in dirs:
+                flist = os.listdir(d)
+                if flist:
+                    assert flist == ['__pycache__']
+                    sd = os.path.join(d, flist[0])
+                    os.rmdir(sd)
+                os.rmdir(d)     # should fail if non-empty
+        self._init_record()
+
+def resolve(module_name, dotted_path):
+    if module_name in sys.modules:
+        mod = sys.modules[module_name]
+    else:
+        mod = __import__(module_name)
+    if dotted_path is None:
+        result = mod
+    else:
+        parts = dotted_path.split('.')
+        result = getattr(mod, parts.pop(0))
+        for p in parts:
+            result = getattr(result, p)
+    return result
+
+
+class ExportEntry(object):
+    def __init__(self, name, prefix, suffix, flags):
+        self.name = name
+        self.prefix = prefix
+        self.suffix = suffix
+        self.flags = flags
+
+    @cached_property
+    def value(self):
+        return resolve(self.prefix, self.suffix)
+
+    def __repr__(self):  # pragma: no cover
+        return '' % (self.name, self.prefix,
+                                                self.suffix, self.flags)
+
+    def __eq__(self, other):
+        if not isinstance(other, ExportEntry):
+            result = False
+        else:
+            result = (self.name == other.name and
+                      self.prefix == other.prefix and
+                      self.suffix == other.suffix and
+                      self.flags == other.flags)
+        return result
+
+    __hash__ = object.__hash__
+
+
+ENTRY_RE = re.compile(r'''(?P(\w|[-.+])+)
+                      \s*=\s*(?P(\w+)([:\.]\w+)*)
+                      \s*(\[\s*(?P[\w-]+(=\w+)?(,\s*\w+(=\w+)?)*)\s*\])?
+                      ''', re.VERBOSE)
+
+def get_export_entry(specification):
+    m = ENTRY_RE.search(specification)
+    if not m:
+        result = None
+        if '[' in specification or ']' in specification:
+            raise DistlibException("Invalid specification "
+                                   "'%s'" % specification)
+    else:
+        d = m.groupdict()
+        name = d['name']
+        path = d['callable']
+        colons = path.count(':')
+        if colons == 0:
+            prefix, suffix = path, None
+        else:
+            if colons != 1:
+                raise DistlibException("Invalid specification "
+                                       "'%s'" % specification)
+            prefix, suffix = path.split(':')
+        flags = d['flags']
+        if flags is None:
+            if '[' in specification or ']' in specification:
+                raise DistlibException("Invalid specification "
+                                       "'%s'" % specification)
+            flags = []
+        else:
+            flags = [f.strip() for f in flags.split(',')]
+        result = ExportEntry(name, prefix, suffix, flags)
+    return result
+
+
+def get_cache_base(suffix=None):
+    """
+    Return the default base location for distlib caches. If the directory does
+    not exist, it is created. Use the suffix provided for the base directory,
+    and default to '.distlib' if it isn't provided.
+
+    On Windows, if LOCALAPPDATA is defined in the environment, then it is
+    assumed to be a directory, and will be the parent directory of the result.
+    On POSIX, and on Windows if LOCALAPPDATA is not defined, the user's home
+    directory - using os.expanduser('~') - will be the parent directory of
+    the result.
+
+    The result is just the directory '.distlib' in the parent directory as
+    determined above, or with the name specified with ``suffix``.
+    """
+    if suffix is None:
+        suffix = '.distlib'
+    if os.name == 'nt' and 'LOCALAPPDATA' in os.environ:
+        result = os.path.expandvars('$localappdata')
+    else:
+        # Assume posix, or old Windows
+        result = os.path.expanduser('~')
+    # we use 'isdir' instead of 'exists', because we want to
+    # fail if there's a file with that name
+    if os.path.isdir(result):
+        usable = os.access(result, os.W_OK)
+        if not usable:
+            logger.warning('Directory exists but is not writable: %s', result)
+    else:
+        try:
+            os.makedirs(result)
+            usable = True
+        except OSError:
+            logger.warning('Unable to create %s', result, exc_info=True)
+            usable = False
+    if not usable:
+        result = tempfile.mkdtemp()
+        logger.warning('Default location unusable, using %s', result)
+    return os.path.join(result, suffix)
+
+
+def path_to_cache_dir(path):
+    """
+    Convert an absolute path to a directory name for use in a cache.
+
+    The algorithm used is:
+
+    #. On Windows, any ``':'`` in the drive is replaced with ``'---'``.
+    #. Any occurrence of ``os.sep`` is replaced with ``'--'``.
+    #. ``'.cache'`` is appended.
+    """
+    d, p = os.path.splitdrive(os.path.abspath(path))
+    if d:
+        d = d.replace(':', '---')
+    p = p.replace(os.sep, '--')
+    return d + p + '.cache'
+
+
+def ensure_slash(s):
+    if not s.endswith('/'):
+        return s + '/'
+    return s
+
+
+def parse_credentials(netloc):
+    username = password = None
+    if '@' in netloc:
+        prefix, netloc = netloc.rsplit('@', 1)
+        if ':' not in prefix:
+            username = prefix
+        else:
+            username, password = prefix.split(':', 1)
+    if username:
+        username = unquote(username)
+    if password:
+        password = unquote(password)
+    return username, password, netloc
+
+
+def get_process_umask():
+    result = os.umask(0o22)
+    os.umask(result)
+    return result
+
+def is_string_sequence(seq):
+    result = True
+    i = None
+    for i, s in enumerate(seq):
+        if not isinstance(s, string_types):
+            result = False
+            break
+    assert i is not None
+    return result
+
+PROJECT_NAME_AND_VERSION = re.compile('([a-z0-9_]+([.-][a-z_][a-z0-9_]*)*)-'
+                                      '([a-z0-9_.+-]+)', re.I)
+PYTHON_VERSION = re.compile(r'-py(\d\.?\d?)')
+
+
+def split_filename(filename, project_name=None):
+    """
+    Extract name, version, python version from a filename (no extension)
+
+    Return name, version, pyver or None
+    """
+    result = None
+    pyver = None
+    filename = unquote(filename).replace(' ', '-')
+    m = PYTHON_VERSION.search(filename)
+    if m:
+        pyver = m.group(1)
+        filename = filename[:m.start()]
+    if project_name and len(filename) > len(project_name) + 1:
+        m = re.match(re.escape(project_name) + r'\b', filename)
+        if m:
+            n = m.end()
+            result = filename[:n], filename[n + 1:], pyver
+    if result is None:
+        m = PROJECT_NAME_AND_VERSION.match(filename)
+        if m:
+            result = m.group(1), m.group(3), pyver
+    return result
+
+# Allow spaces in name because of legacy dists like "Twisted Core"
+NAME_VERSION_RE = re.compile(r'(?P[\w .-]+)\s*'
+                             r'\(\s*(?P[^\s)]+)\)$')
+
+def parse_name_and_version(p):
+    """
+    A utility method used to get name and version from a string.
+
+    From e.g. a Provides-Dist value.
+
+    :param p: A value in a form 'foo (1.0)'
+    :return: The name and version as a tuple.
+    """
+    m = NAME_VERSION_RE.match(p)
+    if not m:
+        raise DistlibException('Ill-formed name/version string: \'%s\'' % p)
+    d = m.groupdict()
+    return d['name'].strip().lower(), d['ver']
+
+def get_extras(requested, available):
+    result = set()
+    requested = set(requested or [])
+    available = set(available or [])
+    if '*' in requested:
+        requested.remove('*')
+        result |= available
+    for r in requested:
+        if r == '-':
+            result.add(r)
+        elif r.startswith('-'):
+            unwanted = r[1:]
+            if unwanted not in available:
+                logger.warning('undeclared extra: %s' % unwanted)
+            if unwanted in result:
+                result.remove(unwanted)
+        else:
+            if r not in available:
+                logger.warning('undeclared extra: %s' % r)
+            result.add(r)
+    return result
+#
+# Extended metadata functionality
+#
+
+def _get_external_data(url):
+    result = {}
+    try:
+        # urlopen might fail if it runs into redirections,
+        # because of Python issue #13696. Fixed in locators
+        # using a custom redirect handler.
+        resp = urlopen(url)
+        headers = resp.info()
+        ct = headers.get('Content-Type')
+        if not ct.startswith('application/json'):
+            logger.debug('Unexpected response for JSON request: %s', ct)
+        else:
+            reader = codecs.getreader('utf-8')(resp)
+            #data = reader.read().decode('utf-8')
+            #result = json.loads(data)
+            result = json.load(reader)
+    except Exception as e:
+        logger.exception('Failed to get external data for %s: %s', url, e)
+    return result
+
+_external_data_base_url = 'https://www.red-dove.com/pypi/projects/'
+
+def get_project_data(name):
+    url = '%s/%s/project.json' % (name[0].upper(), name)
+    url = urljoin(_external_data_base_url, url)
+    result = _get_external_data(url)
+    return result
+
+def get_package_data(name, version):
+    url = '%s/%s/package-%s.json' % (name[0].upper(), name, version)
+    url = urljoin(_external_data_base_url, url)
+    return _get_external_data(url)
+
+
+class Cache(object):
+    """
+    A class implementing a cache for resources that need to live in the file system
+    e.g. shared libraries. This class was moved from resources to here because it
+    could be used by other modules, e.g. the wheel module.
+    """
+
+    def __init__(self, base):
+        """
+        Initialise an instance.
+
+        :param base: The base directory where the cache should be located.
+        """
+        # we use 'isdir' instead of 'exists', because we want to
+        # fail if there's a file with that name
+        if not os.path.isdir(base):  # pragma: no cover
+            os.makedirs(base)
+        if (os.stat(base).st_mode & 0o77) != 0:
+            logger.warning('Directory \'%s\' is not private', base)
+        self.base = os.path.abspath(os.path.normpath(base))
+
+    def prefix_to_dir(self, prefix):
+        """
+        Converts a resource prefix to a directory name in the cache.
+        """
+        return path_to_cache_dir(prefix)
+
+    def clear(self):
+        """
+        Clear the cache.
+        """
+        not_removed = []
+        for fn in os.listdir(self.base):
+            fn = os.path.join(self.base, fn)
+            try:
+                if os.path.islink(fn) or os.path.isfile(fn):
+                    os.remove(fn)
+                elif os.path.isdir(fn):
+                    shutil.rmtree(fn)
+            except Exception:
+                not_removed.append(fn)
+        return not_removed
+
+
+class EventMixin(object):
+    """
+    A very simple publish/subscribe system.
+    """
+    def __init__(self):
+        self._subscribers = {}
+
+    def add(self, event, subscriber, append=True):
+        """
+        Add a subscriber for an event.
+
+        :param event: The name of an event.
+        :param subscriber: The subscriber to be added (and called when the
+                           event is published).
+        :param append: Whether to append or prepend the subscriber to an
+                       existing subscriber list for the event.
+        """
+        subs = self._subscribers
+        if event not in subs:
+            subs[event] = deque([subscriber])
+        else:
+            sq = subs[event]
+            if append:
+                sq.append(subscriber)
+            else:
+                sq.appendleft(subscriber)
+
+    def remove(self, event, subscriber):
+        """
+        Remove a subscriber for an event.
+
+        :param event: The name of an event.
+        :param subscriber: The subscriber to be removed.
+        """
+        subs = self._subscribers
+        if event not in subs:
+            raise ValueError('No subscribers: %r' % event)
+        subs[event].remove(subscriber)
+
+    def get_subscribers(self, event):
+        """
+        Return an iterator for the subscribers for an event.
+        :param event: The event to return subscribers for.
+        """
+        return iter(self._subscribers.get(event, ()))
+
+    def publish(self, event, *args, **kwargs):
+        """
+        Publish a event and return a list of values returned by its
+        subscribers.
+
+        :param event: The event to publish.
+        :param args: The positional arguments to pass to the event's
+                     subscribers.
+        :param kwargs: The keyword arguments to pass to the event's
+                       subscribers.
+        """
+        result = []
+        for subscriber in self.get_subscribers(event):
+            try:
+                value = subscriber(event, *args, **kwargs)
+            except Exception:
+                logger.exception('Exception during event publication')
+                value = None
+            result.append(value)
+        logger.debug('publish %s: args = %s, kwargs = %s, result = %s',
+                     event, args, kwargs, result)
+        return result
+
+#
+# Simple sequencing
+#
+class Sequencer(object):
+    def __init__(self):
+        self._preds = {}
+        self._succs = {}
+        self._nodes = set()     # nodes with no preds/succs
+
+    def add_node(self, node):
+        self._nodes.add(node)
+
+    def remove_node(self, node, edges=False):
+        if node in self._nodes:
+            self._nodes.remove(node)
+        if edges:
+            for p in set(self._preds.get(node, ())):
+                self.remove(p, node)
+            for s in set(self._succs.get(node, ())):
+                self.remove(node, s)
+            # Remove empties
+            for k, v in list(self._preds.items()):
+                if not v:
+                    del self._preds[k]
+            for k, v in list(self._succs.items()):
+                if not v:
+                    del self._succs[k]
+
+    def add(self, pred, succ):
+        assert pred != succ
+        self._preds.setdefault(succ, set()).add(pred)
+        self._succs.setdefault(pred, set()).add(succ)
+
+    def remove(self, pred, succ):
+        assert pred != succ
+        try:
+            preds = self._preds[succ]
+            succs = self._succs[pred]
+        except KeyError:  # pragma: no cover
+            raise ValueError('%r not a successor of anything' % succ)
+        try:
+            preds.remove(pred)
+            succs.remove(succ)
+        except KeyError:  # pragma: no cover
+            raise ValueError('%r not a successor of %r' % (succ, pred))
+
+    def is_step(self, step):
+        return (step in self._preds or step in self._succs or
+                step in self._nodes)
+
+    def get_steps(self, final):
+        if not self.is_step(final):
+            raise ValueError('Unknown: %r' % final)
+        result = []
+        todo = []
+        seen = set()
+        todo.append(final)
+        while todo:
+            step = todo.pop(0)
+            if step in seen:
+                # if a step was already seen,
+                # move it to the end (so it will appear earlier
+                # when reversed on return) ... but not for the
+                # final step, as that would be confusing for
+                # users
+                if step != final:
+                    result.remove(step)
+                    result.append(step)
+            else:
+                seen.add(step)
+                result.append(step)
+                preds = self._preds.get(step, ())
+                todo.extend(preds)
+        return reversed(result)
+
+    @property
+    def strong_connections(self):
+        #http://en.wikipedia.org/wiki/Tarjan%27s_strongly_connected_components_algorithm
+        index_counter = [0]
+        stack = []
+        lowlinks = {}
+        index = {}
+        result = []
+
+        graph = self._succs
+
+        def strongconnect(node):
+            # set the depth index for this node to the smallest unused index
+            index[node] = index_counter[0]
+            lowlinks[node] = index_counter[0]
+            index_counter[0] += 1
+            stack.append(node)
+
+            # Consider successors
+            try:
+                successors = graph[node]
+            except Exception:
+                successors = []
+            for successor in successors:
+                if successor not in lowlinks:
+                    # Successor has not yet been visited
+                    strongconnect(successor)
+                    lowlinks[node] = min(lowlinks[node],lowlinks[successor])
+                elif successor in stack:
+                    # the successor is in the stack and hence in the current
+                    # strongly connected component (SCC)
+                    lowlinks[node] = min(lowlinks[node],index[successor])
+
+            # If `node` is a root node, pop the stack and generate an SCC
+            if lowlinks[node] == index[node]:
+                connected_component = []
+
+                while True:
+                    successor = stack.pop()
+                    connected_component.append(successor)
+                    if successor == node: break
+                component = tuple(connected_component)
+                # storing the result
+                result.append(component)
+
+        for node in graph:
+            if node not in lowlinks:
+                strongconnect(node)
+
+        return result
+
+    @property
+    def dot(self):
+        result = ['digraph G {']
+        for succ in self._preds:
+            preds = self._preds[succ]
+            for pred in preds:
+                result.append('  %s -> %s;' % (pred, succ))
+        for node in self._nodes:
+            result.append('  %s;' % node)
+        result.append('}')
+        return '\n'.join(result)
+
+#
+# Unarchiving functionality for zip, tar, tgz, tbz, whl
+#
+
+ARCHIVE_EXTENSIONS = ('.tar.gz', '.tar.bz2', '.tar', '.zip',
+                      '.tgz', '.tbz', '.whl')
+
+def unarchive(archive_filename, dest_dir, format=None, check=True):
+
+    def check_path(path):
+        if not isinstance(path, text_type):
+            path = path.decode('utf-8')
+        p = os.path.abspath(os.path.join(dest_dir, path))
+        if not p.startswith(dest_dir) or p[plen] != os.sep:
+            raise ValueError('path outside destination: %r' % p)
+
+    dest_dir = os.path.abspath(dest_dir)
+    plen = len(dest_dir)
+    archive = None
+    if format is None:
+        if archive_filename.endswith(('.zip', '.whl')):
+            format = 'zip'
+        elif archive_filename.endswith(('.tar.gz', '.tgz')):
+            format = 'tgz'
+            mode = 'r:gz'
+        elif archive_filename.endswith(('.tar.bz2', '.tbz')):
+            format = 'tbz'
+            mode = 'r:bz2'
+        elif archive_filename.endswith('.tar'):
+            format = 'tar'
+            mode = 'r'
+        else:  # pragma: no cover
+            raise ValueError('Unknown format for %r' % archive_filename)
+    try:
+        if format == 'zip':
+            archive = ZipFile(archive_filename, 'r')
+            if check:
+                names = archive.namelist()
+                for name in names:
+                    check_path(name)
+        else:
+            archive = tarfile.open(archive_filename, mode)
+            if check:
+                names = archive.getnames()
+                for name in names:
+                    check_path(name)
+        if format != 'zip' and sys.version_info[0] < 3:
+            # See Python issue 17153. If the dest path contains Unicode,
+            # tarfile extraction fails on Python 2.x if a member path name
+            # contains non-ASCII characters - it leads to an implicit
+            # bytes -> unicode conversion using ASCII to decode.
+            for tarinfo in archive.getmembers():
+                if not isinstance(tarinfo.name, text_type):
+                    tarinfo.name = tarinfo.name.decode('utf-8')
+        archive.extractall(dest_dir)
+
+    finally:
+        if archive:
+            archive.close()
+
+
+def zip_dir(directory):
+    """zip a directory tree into a BytesIO object"""
+    result = io.BytesIO()
+    dlen = len(directory)
+    with ZipFile(result, "w") as zf:
+        for root, dirs, files in os.walk(directory):
+            for name in files:
+                full = os.path.join(root, name)
+                rel = root[dlen:]
+                dest = os.path.join(rel, name)
+                zf.write(full, dest)
+    return result
+
+#
+# Simple progress bar
+#
+
+UNITS = ('', 'K', 'M', 'G','T','P')
+
+
+class Progress(object):
+    unknown = 'UNKNOWN'
+
+    def __init__(self, minval=0, maxval=100):
+        assert maxval is None or maxval >= minval
+        self.min = self.cur = minval
+        self.max = maxval
+        self.started = None
+        self.elapsed = 0
+        self.done = False
+
+    def update(self, curval):
+        assert self.min <= curval
+        assert self.max is None or curval <= self.max
+        self.cur = curval
+        now = time.time()
+        if self.started is None:
+            self.started = now
+        else:
+            self.elapsed = now - self.started
+
+    def increment(self, incr):
+        assert incr >= 0
+        self.update(self.cur + incr)
+
+    def start(self):
+        self.update(self.min)
+        return self
+
+    def stop(self):
+        if self.max is not None:
+            self.update(self.max)
+        self.done = True
+
+    @property
+    def maximum(self):
+        return self.unknown if self.max is None else self.max
+
+    @property
+    def percentage(self):
+        if self.done:
+            result = '100 %'
+        elif self.max is None:
+            result = ' ?? %'
+        else:
+            v = 100.0 * (self.cur - self.min) / (self.max - self.min)
+            result = '%3d %%' % v
+        return result
+
+    def format_duration(self, duration):
+        if (duration <= 0) and self.max is None or self.cur == self.min:
+            result = '??:??:??'
+        #elif duration < 1:
+        #    result = '--:--:--'
+        else:
+            result = time.strftime('%H:%M:%S', time.gmtime(duration))
+        return result
+
+    @property
+    def ETA(self):
+        if self.done:
+            prefix = 'Done'
+            t = self.elapsed
+            #import pdb; pdb.set_trace()
+        else:
+            prefix = 'ETA '
+            if self.max is None:
+                t = -1
+            elif self.elapsed == 0 or (self.cur == self.min):
+                t = 0
+            else:
+                #import pdb; pdb.set_trace()
+                t = float(self.max - self.min)
+                t /= self.cur - self.min
+                t = (t - 1) * self.elapsed
+        return '%s: %s' % (prefix, self.format_duration(t))
+
+    @property
+    def speed(self):
+        if self.elapsed == 0:
+            result = 0.0
+        else:
+            result = (self.cur - self.min) / self.elapsed
+        for unit in UNITS:
+            if result < 1000:
+                break
+            result /= 1000.0
+        return '%d %sB/s' % (result, unit)
+
+#
+# Glob functionality
+#
+
+RICH_GLOB = re.compile(r'\{([^}]*)\}')
+_CHECK_RECURSIVE_GLOB = re.compile(r'[^/\\,{]\*\*|\*\*[^/\\,}]')
+_CHECK_MISMATCH_SET = re.compile(r'^[^{]*\}|\{[^}]*$')
+
+
+def iglob(path_glob):
+    """Extended globbing function that supports ** and {opt1,opt2,opt3}."""
+    if _CHECK_RECURSIVE_GLOB.search(path_glob):
+        msg = """invalid glob %r: recursive glob "**" must be used alone"""
+        raise ValueError(msg % path_glob)
+    if _CHECK_MISMATCH_SET.search(path_glob):
+        msg = """invalid glob %r: mismatching set marker '{' or '}'"""
+        raise ValueError(msg % path_glob)
+    return _iglob(path_glob)
+
+
+def _iglob(path_glob):
+    rich_path_glob = RICH_GLOB.split(path_glob, 1)
+    if len(rich_path_glob) > 1:
+        assert len(rich_path_glob) == 3, rich_path_glob
+        prefix, set, suffix = rich_path_glob
+        for item in set.split(','):
+            for path in _iglob(''.join((prefix, item, suffix))):
+                yield path
+    else:
+        if '**' not in path_glob:
+            for item in std_iglob(path_glob):
+                yield item
+        else:
+            prefix, radical = path_glob.split('**', 1)
+            if prefix == '':
+                prefix = '.'
+            if radical == '':
+                radical = '*'
+            else:
+                # we support both
+                radical = radical.lstrip('/')
+                radical = radical.lstrip('\\')
+            for path, dir, files in os.walk(prefix):
+                path = os.path.normpath(path)
+                for fn in _iglob(os.path.join(path, radical)):
+                    yield fn
+
+if ssl:
+    from .compat import (HTTPSHandler as BaseHTTPSHandler, match_hostname,
+                         CertificateError)
+
+
+#
+# HTTPSConnection which verifies certificates/matches domains
+#
+
+    class HTTPSConnection(httplib.HTTPSConnection):
+        ca_certs = None # set this to the path to the certs file (.pem)
+        check_domain = True # only used if ca_certs is not None
+
+        # noinspection PyPropertyAccess
+        def connect(self):
+            sock = socket.create_connection((self.host, self.port), self.timeout)
+            if getattr(self, '_tunnel_host', False):
+                self.sock = sock
+                self._tunnel()
+
+            context = ssl.SSLContext(ssl.PROTOCOL_SSLv23)
+            if hasattr(ssl, 'OP_NO_SSLv2'):
+                context.options |= ssl.OP_NO_SSLv2
+            if self.cert_file:
+                context.load_cert_chain(self.cert_file, self.key_file)
+            kwargs = {}
+            if self.ca_certs:
+                context.verify_mode = ssl.CERT_REQUIRED
+                context.load_verify_locations(cafile=self.ca_certs)
+                if getattr(ssl, 'HAS_SNI', False):
+                    kwargs['server_hostname'] = self.host
+
+            self.sock = context.wrap_socket(sock, **kwargs)
+            if self.ca_certs and self.check_domain:
+                try:
+                    match_hostname(self.sock.getpeercert(), self.host)
+                    logger.debug('Host verified: %s', self.host)
+                except CertificateError:  # pragma: no cover
+                    self.sock.shutdown(socket.SHUT_RDWR)
+                    self.sock.close()
+                    raise
+
+    class HTTPSHandler(BaseHTTPSHandler):
+        def __init__(self, ca_certs, check_domain=True):
+            BaseHTTPSHandler.__init__(self)
+            self.ca_certs = ca_certs
+            self.check_domain = check_domain
+
+        def _conn_maker(self, *args, **kwargs):
+            """
+            This is called to create a connection instance. Normally you'd
+            pass a connection class to do_open, but it doesn't actually check for
+            a class, and just expects a callable. As long as we behave just as a
+            constructor would have, we should be OK. If it ever changes so that
+            we *must* pass a class, we'll create an UnsafeHTTPSConnection class
+            which just sets check_domain to False in the class definition, and
+            choose which one to pass to do_open.
+            """
+            result = HTTPSConnection(*args, **kwargs)
+            if self.ca_certs:
+                result.ca_certs = self.ca_certs
+                result.check_domain = self.check_domain
+            return result
+
+        def https_open(self, req):
+            try:
+                return self.do_open(self._conn_maker, req)
+            except URLError as e:
+                if 'certificate verify failed' in str(e.reason):
+                    raise CertificateError('Unable to verify server certificate '
+                                           'for %s' % req.host)
+                else:
+                    raise
+
+    #
+    # To prevent against mixing HTTP traffic with HTTPS (examples: A Man-In-The-
+    # Middle proxy using HTTP listens on port 443, or an index mistakenly serves
+    # HTML containing a http://xyz link when it should be https://xyz),
+    # you can use the following handler class, which does not allow HTTP traffic.
+    #
+    # It works by inheriting from HTTPHandler - so build_opener won't add a
+    # handler for HTTP itself.
+    #
+    class HTTPSOnlyHandler(HTTPSHandler, HTTPHandler):
+        def http_open(self, req):
+            raise URLError('Unexpected HTTP request on what should be a secure '
+                           'connection: %s' % req)
+
+#
+# XML-RPC with timeouts
+#
+class Transport(xmlrpclib.Transport):
+    def __init__(self, timeout, use_datetime=0):
+        self.timeout = timeout
+        xmlrpclib.Transport.__init__(self, use_datetime)
+
+    def make_connection(self, host):
+        h, eh, x509 = self.get_host_info(host)
+        if not self._connection or host != self._connection[0]:
+            self._extra_headers = eh
+            self._connection = host, httplib.HTTPConnection(h)
+        return self._connection[1]
+
+if ssl:
+    class SafeTransport(xmlrpclib.SafeTransport):
+        def __init__(self, timeout, use_datetime=0):
+            self.timeout = timeout
+            xmlrpclib.SafeTransport.__init__(self, use_datetime)
+
+        def make_connection(self, host):
+            h, eh, kwargs = self.get_host_info(host)
+            if not kwargs:
+                kwargs = {}
+            kwargs['timeout'] = self.timeout
+            if not self._connection or host != self._connection[0]:
+                self._extra_headers = eh
+                self._connection = host, httplib.HTTPSConnection(h, None,
+                                                                 **kwargs)
+            return self._connection[1]
+
+
+class ServerProxy(xmlrpclib.ServerProxy):
+    def __init__(self, uri, **kwargs):
+        self.timeout = timeout = kwargs.pop('timeout', None)
+        # The above classes only come into play if a timeout
+        # is specified
+        if timeout is not None:
+            # scheme = splittype(uri)  # deprecated as of Python 3.8
+            scheme = urlparse(uri)[0]
+            use_datetime = kwargs.get('use_datetime', 0)
+            if scheme == 'https':
+                tcls = SafeTransport
+            else:
+                tcls = Transport
+            kwargs['transport'] = t = tcls(timeout, use_datetime=use_datetime)
+            self.transport = t
+        xmlrpclib.ServerProxy.__init__(self, uri, **kwargs)
+
+#
+# CSV functionality. This is provided because on 2.x, the csv module can't
+# handle Unicode. However, we need to deal with Unicode in e.g. RECORD files.
+#
+
+def _csv_open(fn, mode, **kwargs):
+    if sys.version_info[0] < 3:
+        mode += 'b'
+    else:
+        kwargs['newline'] = ''
+        # Python 3 determines encoding from locale. Force 'utf-8'
+        # file encoding to match other forced utf-8 encoding
+        kwargs['encoding'] = 'utf-8'
+    return open(fn, mode, **kwargs)
+
+
+class CSVBase(object):
+    defaults = {
+        'delimiter': str(','),      # The strs are used because we need native
+        'quotechar': str('"'),      # str in the csv API (2.x won't take
+        'lineterminator': str('\n') # Unicode)
+    }
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *exc_info):
+        self.stream.close()
+
+
+class CSVReader(CSVBase):
+    def __init__(self, **kwargs):
+        if 'stream' in kwargs:
+            stream = kwargs['stream']
+            if sys.version_info[0] >= 3:
+                # needs to be a text stream
+                stream = codecs.getreader('utf-8')(stream)
+            self.stream = stream
+        else:
+            self.stream = _csv_open(kwargs['path'], 'r')
+        self.reader = csv.reader(self.stream, **self.defaults)
+
+    def __iter__(self):
+        return self
+
+    def next(self):
+        result = next(self.reader)
+        if sys.version_info[0] < 3:
+            for i, item in enumerate(result):
+                if not isinstance(item, text_type):
+                    result[i] = item.decode('utf-8')
+        return result
+
+    __next__ = next
+
+class CSVWriter(CSVBase):
+    def __init__(self, fn, **kwargs):
+        self.stream = _csv_open(fn, 'w')
+        self.writer = csv.writer(self.stream, **self.defaults)
+
+    def writerow(self, row):
+        if sys.version_info[0] < 3:
+            r = []
+            for item in row:
+                if isinstance(item, text_type):
+                    item = item.encode('utf-8')
+                r.append(item)
+            row = r
+        self.writer.writerow(row)
+
+#
+#   Configurator functionality
+#
+
+class Configurator(BaseConfigurator):
+
+    value_converters = dict(BaseConfigurator.value_converters)
+    value_converters['inc'] = 'inc_convert'
+
+    def __init__(self, config, base=None):
+        super(Configurator, self).__init__(config)
+        self.base = base or os.getcwd()
+
+    def configure_custom(self, config):
+        def convert(o):
+            if isinstance(o, (list, tuple)):
+                result = type(o)([convert(i) for i in o])
+            elif isinstance(o, dict):
+                if '()' in o:
+                    result = self.configure_custom(o)
+                else:
+                    result = {}
+                    for k in o:
+                        result[k] = convert(o[k])
+            else:
+                result = self.convert(o)
+            return result
+
+        c = config.pop('()')
+        if not callable(c):
+            c = self.resolve(c)
+        props = config.pop('.', None)
+        # Check for valid identifiers
+        args = config.pop('[]', ())
+        if args:
+            args = tuple([convert(o) for o in args])
+        items = [(k, convert(config[k])) for k in config if valid_ident(k)]
+        kwargs = dict(items)
+        result = c(*args, **kwargs)
+        if props:
+            for n, v in props.items():
+                setattr(result, n, convert(v))
+        return result
+
+    def __getitem__(self, key):
+        result = self.config[key]
+        if isinstance(result, dict) and '()' in result:
+            self.config[key] = result = self.configure_custom(result)
+        return result
+
+    def inc_convert(self, value):
+        """Default converter for the inc:// protocol."""
+        if not os.path.isabs(value):
+            value = os.path.join(self.base, value)
+        with codecs.open(value, 'r', encoding='utf-8') as f:
+            result = json.load(f)
+        return result
+
+
+class SubprocessMixin(object):
+    """
+    Mixin for running subprocesses and capturing their output
+    """
+    def __init__(self, verbose=False, progress=None):
+        self.verbose = verbose
+        self.progress = progress
+
+    def reader(self, stream, context):
+        """
+        Read lines from a subprocess' output stream and either pass to a progress
+        callable (if specified) or write progress information to sys.stderr.
+        """
+        progress = self.progress
+        verbose = self.verbose
+        while True:
+            s = stream.readline()
+            if not s:
+                break
+            if progress is not None:
+                progress(s, context)
+            else:
+                if not verbose:
+                    sys.stderr.write('.')
+                else:
+                    sys.stderr.write(s.decode('utf-8'))
+                sys.stderr.flush()
+        stream.close()
+
+    def run_command(self, cmd, **kwargs):
+        p = subprocess.Popen(cmd, stdout=subprocess.PIPE,
+                             stderr=subprocess.PIPE, **kwargs)
+        t1 = threading.Thread(target=self.reader, args=(p.stdout, 'stdout'))
+        t1.start()
+        t2 = threading.Thread(target=self.reader, args=(p.stderr, 'stderr'))
+        t2.start()
+        p.wait()
+        t1.join()
+        t2.join()
+        if self.progress is not None:
+            self.progress('done.', 'main')
+        elif self.verbose:
+            sys.stderr.write('done.\n')
+        return p
+
+
+def normalize_name(name):
+    """Normalize a python package name a la PEP 503"""
+    # https://www.python.org/dev/peps/pep-0503/#normalized-names
+    return re.sub('[-_.]+', '-', name).lower()
+
+# def _get_pypirc_command():
+    # """
+    # Get the distutils command for interacting with PyPI configurations.
+    # :return: the command.
+    # """
+    # from distutils.core import Distribution
+    # from distutils.config import PyPIRCCommand
+    # d = Distribution()
+    # return PyPIRCCommand(d)
+
+class PyPIRCFile(object):
+
+    DEFAULT_REPOSITORY = 'https://upload.pypi.org/legacy/'
+    DEFAULT_REALM = 'pypi'
+
+    def __init__(self, fn=None, url=None):
+        if fn is None:
+            fn = os.path.join(os.path.expanduser('~'), '.pypirc')
+        self.filename = fn
+        self.url = url
+
+    def read(self):
+        result = {}
+
+        if os.path.exists(self.filename):
+            repository = self.url or self.DEFAULT_REPOSITORY
+
+            config = configparser.RawConfigParser()
+            config.read(self.filename)
+            sections = config.sections()
+            if 'distutils' in sections:
+                # let's get the list of servers
+                index_servers = config.get('distutils', 'index-servers')
+                _servers = [server.strip() for server in
+                            index_servers.split('\n')
+                            if server.strip() != '']
+                if _servers == []:
+                    # nothing set, let's try to get the default pypi
+                    if 'pypi' in sections:
+                        _servers = ['pypi']
+                else:
+                    for server in _servers:
+                        result = {'server': server}
+                        result['username'] = config.get(server, 'username')
+
+                        # optional params
+                        for key, default in (('repository', self.DEFAULT_REPOSITORY),
+                                             ('realm', self.DEFAULT_REALM),
+                                             ('password', None)):
+                            if config.has_option(server, key):
+                                result[key] = config.get(server, key)
+                            else:
+                                result[key] = default
+
+                        # work around people having "repository" for the "pypi"
+                        # section of their config set to the HTTP (rather than
+                        # HTTPS) URL
+                        if (server == 'pypi' and
+                            repository in (self.DEFAULT_REPOSITORY, 'pypi')):
+                            result['repository'] = self.DEFAULT_REPOSITORY
+                        elif (result['server'] != repository and
+                              result['repository'] != repository):
+                            result = {}
+            elif 'server-login' in sections:
+                # old format
+                server = 'server-login'
+                if config.has_option(server, 'repository'):
+                    repository = config.get(server, 'repository')
+                else:
+                    repository = self.DEFAULT_REPOSITORY
+                result = {
+                    'username': config.get(server, 'username'),
+                    'password': config.get(server, 'password'),
+                    'repository': repository,
+                    'server': server,
+                    'realm': self.DEFAULT_REALM
+                }
+        return result
+
+    def update(self, username, password):
+        # import pdb; pdb.set_trace()
+        config = configparser.RawConfigParser()
+        fn = self.filename
+        config.read(fn)
+        if not config.has_section('pypi'):
+            config.add_section('pypi')
+        config.set('pypi', 'username', username)
+        config.set('pypi', 'password', password)
+        with open(fn, 'w') as f:
+            config.write(f)
+
+def _load_pypirc(index):
+    """
+    Read the PyPI access configuration as supported by distutils.
+    """
+    return PyPIRCFile(url=index.url).read()
+
+def _store_pypirc(index):
+    PyPIRCFile().update(index.username, index.password)
+
+#
+# get_platform()/get_host_platform() copied from Python 3.10.a0 source, with some minor
+# tweaks
+#
+
+def get_host_platform():
+    """Return a string that identifies the current platform.  This is used mainly to
+    distinguish platform-specific build directories and platform-specific built
+    distributions.  Typically includes the OS name and version and the
+    architecture (as supplied by 'os.uname()'), although the exact information
+    included depends on the OS; eg. on Linux, the kernel version isn't
+    particularly important.
+
+    Examples of returned values:
+       linux-i586
+       linux-alpha (?)
+       solaris-2.6-sun4u
+
+    Windows will return one of:
+       win-amd64 (64bit Windows on AMD64 (aka x86_64, Intel64, EM64T, etc)
+       win32 (all others - specifically, sys.platform is returned)
+
+    For other non-POSIX platforms, currently just returns 'sys.platform'.
+
+    """
+    if os.name == 'nt':
+        if 'amd64' in sys.version.lower():
+            return 'win-amd64'
+        if '(arm)' in sys.version.lower():
+            return 'win-arm32'
+        if '(arm64)' in sys.version.lower():
+            return 'win-arm64'
+        return sys.platform
+
+    # Set for cross builds explicitly
+    if "_PYTHON_HOST_PLATFORM" in os.environ:
+        return os.environ["_PYTHON_HOST_PLATFORM"]
+
+    if os.name != 'posix' or not hasattr(os, 'uname'):
+        # XXX what about the architecture? NT is Intel or Alpha,
+        # Mac OS is M68k or PPC, etc.
+        return sys.platform
+
+    # Try to distinguish various flavours of Unix
+
+    (osname, host, release, version, machine) = os.uname()
+
+    # Convert the OS name to lowercase, remove '/' characters, and translate
+    # spaces (for "Power Macintosh")
+    osname = osname.lower().replace('/', '')
+    machine = machine.replace(' ', '_').replace('/', '-')
+
+    if osname[:5] == 'linux':
+        # At least on Linux/Intel, 'machine' is the processor --
+        # i386, etc.
+        # XXX what about Alpha, SPARC, etc?
+        return  "%s-%s" % (osname, machine)
+
+    elif osname[:5] == 'sunos':
+        if release[0] >= '5':           # SunOS 5 == Solaris 2
+            osname = 'solaris'
+            release = '%d.%s' % (int(release[0]) - 3, release[2:])
+            # We can't use 'platform.architecture()[0]' because a
+            # bootstrap problem. We use a dict to get an error
+            # if some suspicious happens.
+            bitness = {2147483647:'32bit', 9223372036854775807:'64bit'}
+            machine += '.%s' % bitness[sys.maxsize]
+        # fall through to standard osname-release-machine representation
+    elif osname[:3] == 'aix':
+        from _aix_support import aix_platform
+        return aix_platform()
+    elif osname[:6] == 'cygwin':
+        osname = 'cygwin'
+        rel_re = re.compile (r'[\d.]+', re.ASCII)
+        m = rel_re.match(release)
+        if m:
+            release = m.group()
+    elif osname[:6] == 'darwin':
+        import _osx_support, distutils.sysconfig
+        osname, release, machine = _osx_support.get_platform_osx(
+                                        distutils.sysconfig.get_config_vars(),
+                                        osname, release, machine)
+
+    return '%s-%s-%s' % (osname, release, machine)
+
+
+_TARGET_TO_PLAT = {
+    'x86' : 'win32',
+    'x64' : 'win-amd64',
+    'arm' : 'win-arm32',
+}
+
+
+def get_platform():
+    if os.name != 'nt':
+        return get_host_platform()
+    cross_compilation_target = os.environ.get('VSCMD_ARG_TGT_ARCH')
+    if cross_compilation_target not in _TARGET_TO_PLAT:
+        return get_host_platform()
+    return _TARGET_TO_PLAT[cross_compilation_target]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/version.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..c7c8bb6ff4f8ed84e466a66cac6b953b901626ea
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/version.py
@@ -0,0 +1,739 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2012-2017 The Python Software Foundation.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+"""
+Implementation of a flexible versioning scheme providing support for PEP-440,
+setuptools-compatible and semantic versioning.
+"""
+
+import logging
+import re
+
+from .compat import string_types
+from .util import parse_requirement
+
+__all__ = ['NormalizedVersion', 'NormalizedMatcher',
+           'LegacyVersion', 'LegacyMatcher',
+           'SemanticVersion', 'SemanticMatcher',
+           'UnsupportedVersionError', 'get_scheme']
+
+logger = logging.getLogger(__name__)
+
+
+class UnsupportedVersionError(ValueError):
+    """This is an unsupported version."""
+    pass
+
+
+class Version(object):
+    def __init__(self, s):
+        self._string = s = s.strip()
+        self._parts = parts = self.parse(s)
+        assert isinstance(parts, tuple)
+        assert len(parts) > 0
+
+    def parse(self, s):
+        raise NotImplementedError('please implement in a subclass')
+
+    def _check_compatible(self, other):
+        if type(self) != type(other):
+            raise TypeError('cannot compare %r and %r' % (self, other))
+
+    def __eq__(self, other):
+        self._check_compatible(other)
+        return self._parts == other._parts
+
+    def __ne__(self, other):
+        return not self.__eq__(other)
+
+    def __lt__(self, other):
+        self._check_compatible(other)
+        return self._parts < other._parts
+
+    def __gt__(self, other):
+        return not (self.__lt__(other) or self.__eq__(other))
+
+    def __le__(self, other):
+        return self.__lt__(other) or self.__eq__(other)
+
+    def __ge__(self, other):
+        return self.__gt__(other) or self.__eq__(other)
+
+    # See http://docs.python.org/reference/datamodel#object.__hash__
+    def __hash__(self):
+        return hash(self._parts)
+
+    def __repr__(self):
+        return "%s('%s')" % (self.__class__.__name__, self._string)
+
+    def __str__(self):
+        return self._string
+
+    @property
+    def is_prerelease(self):
+        raise NotImplementedError('Please implement in subclasses.')
+
+
+class Matcher(object):
+    version_class = None
+
+    # value is either a callable or the name of a method
+    _operators = {
+        '<': lambda v, c, p: v < c,
+        '>': lambda v, c, p: v > c,
+        '<=': lambda v, c, p: v == c or v < c,
+        '>=': lambda v, c, p: v == c or v > c,
+        '==': lambda v, c, p: v == c,
+        '===': lambda v, c, p: v == c,
+        # by default, compatible => >=.
+        '~=': lambda v, c, p: v == c or v > c,
+        '!=': lambda v, c, p: v != c,
+    }
+
+    # this is a method only to support alternative implementations
+    # via overriding
+    def parse_requirement(self, s):
+        return parse_requirement(s)
+
+    def __init__(self, s):
+        if self.version_class is None:
+            raise ValueError('Please specify a version class')
+        self._string = s = s.strip()
+        r = self.parse_requirement(s)
+        if not r:
+            raise ValueError('Not valid: %r' % s)
+        self.name = r.name
+        self.key = self.name.lower()    # for case-insensitive comparisons
+        clist = []
+        if r.constraints:
+            # import pdb; pdb.set_trace()
+            for op, s in r.constraints:
+                if s.endswith('.*'):
+                    if op not in ('==', '!='):
+                        raise ValueError('\'.*\' not allowed for '
+                                         '%r constraints' % op)
+                    # Could be a partial version (e.g. for '2.*') which
+                    # won't parse as a version, so keep it as a string
+                    vn, prefix = s[:-2], True
+                    # Just to check that vn is a valid version
+                    self.version_class(vn)
+                else:
+                    # Should parse as a version, so we can create an
+                    # instance for the comparison
+                    vn, prefix = self.version_class(s), False
+                clist.append((op, vn, prefix))
+        self._parts = tuple(clist)
+
+    def match(self, version):
+        """
+        Check if the provided version matches the constraints.
+
+        :param version: The version to match against this instance.
+        :type version: String or :class:`Version` instance.
+        """
+        if isinstance(version, string_types):
+            version = self.version_class(version)
+        for operator, constraint, prefix in self._parts:
+            f = self._operators.get(operator)
+            if isinstance(f, string_types):
+                f = getattr(self, f)
+            if not f:
+                msg = ('%r not implemented '
+                       'for %s' % (operator, self.__class__.__name__))
+                raise NotImplementedError(msg)
+            if not f(version, constraint, prefix):
+                return False
+        return True
+
+    @property
+    def exact_version(self):
+        result = None
+        if len(self._parts) == 1 and self._parts[0][0] in ('==', '==='):
+            result = self._parts[0][1]
+        return result
+
+    def _check_compatible(self, other):
+        if type(self) != type(other) or self.name != other.name:
+            raise TypeError('cannot compare %s and %s' % (self, other))
+
+    def __eq__(self, other):
+        self._check_compatible(other)
+        return self.key == other.key and self._parts == other._parts
+
+    def __ne__(self, other):
+        return not self.__eq__(other)
+
+    # See http://docs.python.org/reference/datamodel#object.__hash__
+    def __hash__(self):
+        return hash(self.key) + hash(self._parts)
+
+    def __repr__(self):
+        return "%s(%r)" % (self.__class__.__name__, self._string)
+
+    def __str__(self):
+        return self._string
+
+
+PEP440_VERSION_RE = re.compile(r'^v?(\d+!)?(\d+(\.\d+)*)((a|b|c|rc)(\d+))?'
+                               r'(\.(post)(\d+))?(\.(dev)(\d+))?'
+                               r'(\+([a-zA-Z\d]+(\.[a-zA-Z\d]+)?))?$')
+
+
+def _pep_440_key(s):
+    s = s.strip()
+    m = PEP440_VERSION_RE.match(s)
+    if not m:
+        raise UnsupportedVersionError('Not a valid version: %s' % s)
+    groups = m.groups()
+    nums = tuple(int(v) for v in groups[1].split('.'))
+    while len(nums) > 1 and nums[-1] == 0:
+        nums = nums[:-1]
+
+    if not groups[0]:
+        epoch = 0
+    else:
+        epoch = int(groups[0][:-1])
+    pre = groups[4:6]
+    post = groups[7:9]
+    dev = groups[10:12]
+    local = groups[13]
+    if pre == (None, None):
+        pre = ()
+    else:
+        pre = pre[0], int(pre[1])
+    if post == (None, None):
+        post = ()
+    else:
+        post = post[0], int(post[1])
+    if dev == (None, None):
+        dev = ()
+    else:
+        dev = dev[0], int(dev[1])
+    if local is None:
+        local = ()
+    else:
+        parts = []
+        for part in local.split('.'):
+            # to ensure that numeric compares as > lexicographic, avoid
+            # comparing them directly, but encode a tuple which ensures
+            # correct sorting
+            if part.isdigit():
+                part = (1, int(part))
+            else:
+                part = (0, part)
+            parts.append(part)
+        local = tuple(parts)
+    if not pre:
+        # either before pre-release, or final release and after
+        if not post and dev:
+            # before pre-release
+            pre = ('a', -1)     # to sort before a0
+        else:
+            pre = ('z',)        # to sort after all pre-releases
+    # now look at the state of post and dev.
+    if not post:
+        post = ('_',)   # sort before 'a'
+    if not dev:
+        dev = ('final',)
+
+    #print('%s -> %s' % (s, m.groups()))
+    return epoch, nums, pre, post, dev, local
+
+
+_normalized_key = _pep_440_key
+
+
+class NormalizedVersion(Version):
+    """A rational version.
+
+    Good:
+        1.2         # equivalent to "1.2.0"
+        1.2.0
+        1.2a1
+        1.2.3a2
+        1.2.3b1
+        1.2.3c1
+        1.2.3.4
+        TODO: fill this out
+
+    Bad:
+        1           # minimum two numbers
+        1.2a        # release level must have a release serial
+        1.2.3b
+    """
+    def parse(self, s):
+        result = _normalized_key(s)
+        # _normalized_key loses trailing zeroes in the release
+        # clause, since that's needed to ensure that X.Y == X.Y.0 == X.Y.0.0
+        # However, PEP 440 prefix matching needs it: for example,
+        # (~= 1.4.5.0) matches differently to (~= 1.4.5.0.0).
+        m = PEP440_VERSION_RE.match(s)      # must succeed
+        groups = m.groups()
+        self._release_clause = tuple(int(v) for v in groups[1].split('.'))
+        return result
+
+    PREREL_TAGS = set(['a', 'b', 'c', 'rc', 'dev'])
+
+    @property
+    def is_prerelease(self):
+        return any(t[0] in self.PREREL_TAGS for t in self._parts if t)
+
+
+def _match_prefix(x, y):
+    x = str(x)
+    y = str(y)
+    if x == y:
+        return True
+    if not x.startswith(y):
+        return False
+    n = len(y)
+    return x[n] == '.'
+
+
+class NormalizedMatcher(Matcher):
+    version_class = NormalizedVersion
+
+    # value is either a callable or the name of a method
+    _operators = {
+        '~=': '_match_compatible',
+        '<': '_match_lt',
+        '>': '_match_gt',
+        '<=': '_match_le',
+        '>=': '_match_ge',
+        '==': '_match_eq',
+        '===': '_match_arbitrary',
+        '!=': '_match_ne',
+    }
+
+    def _adjust_local(self, version, constraint, prefix):
+        if prefix:
+            strip_local = '+' not in constraint and version._parts[-1]
+        else:
+            # both constraint and version are
+            # NormalizedVersion instances.
+            # If constraint does not have a local component,
+            # ensure the version doesn't, either.
+            strip_local = not constraint._parts[-1] and version._parts[-1]
+        if strip_local:
+            s = version._string.split('+', 1)[0]
+            version = self.version_class(s)
+        return version, constraint
+
+    def _match_lt(self, version, constraint, prefix):
+        version, constraint = self._adjust_local(version, constraint, prefix)
+        if version >= constraint:
+            return False
+        release_clause = constraint._release_clause
+        pfx = '.'.join([str(i) for i in release_clause])
+        return not _match_prefix(version, pfx)
+
+    def _match_gt(self, version, constraint, prefix):
+        version, constraint = self._adjust_local(version, constraint, prefix)
+        if version <= constraint:
+            return False
+        release_clause = constraint._release_clause
+        pfx = '.'.join([str(i) for i in release_clause])
+        return not _match_prefix(version, pfx)
+
+    def _match_le(self, version, constraint, prefix):
+        version, constraint = self._adjust_local(version, constraint, prefix)
+        return version <= constraint
+
+    def _match_ge(self, version, constraint, prefix):
+        version, constraint = self._adjust_local(version, constraint, prefix)
+        return version >= constraint
+
+    def _match_eq(self, version, constraint, prefix):
+        version, constraint = self._adjust_local(version, constraint, prefix)
+        if not prefix:
+            result = (version == constraint)
+        else:
+            result = _match_prefix(version, constraint)
+        return result
+
+    def _match_arbitrary(self, version, constraint, prefix):
+        return str(version) == str(constraint)
+
+    def _match_ne(self, version, constraint, prefix):
+        version, constraint = self._adjust_local(version, constraint, prefix)
+        if not prefix:
+            result = (version != constraint)
+        else:
+            result = not _match_prefix(version, constraint)
+        return result
+
+    def _match_compatible(self, version, constraint, prefix):
+        version, constraint = self._adjust_local(version, constraint, prefix)
+        if version == constraint:
+            return True
+        if version < constraint:
+            return False
+#        if not prefix:
+#            return True
+        release_clause = constraint._release_clause
+        if len(release_clause) > 1:
+            release_clause = release_clause[:-1]
+        pfx = '.'.join([str(i) for i in release_clause])
+        return _match_prefix(version, pfx)
+
+_REPLACEMENTS = (
+    (re.compile('[.+-]$'), ''),                     # remove trailing puncts
+    (re.compile(r'^[.](\d)'), r'0.\1'),             # .N -> 0.N at start
+    (re.compile('^[.-]'), ''),                      # remove leading puncts
+    (re.compile(r'^\((.*)\)$'), r'\1'),             # remove parentheses
+    (re.compile(r'^v(ersion)?\s*(\d+)'), r'\2'),    # remove leading v(ersion)
+    (re.compile(r'^r(ev)?\s*(\d+)'), r'\2'),        # remove leading v(ersion)
+    (re.compile('[.]{2,}'), '.'),                   # multiple runs of '.'
+    (re.compile(r'\b(alfa|apha)\b'), 'alpha'),      # misspelt alpha
+    (re.compile(r'\b(pre-alpha|prealpha)\b'),
+                'pre.alpha'),                       # standardise
+    (re.compile(r'\(beta\)$'), 'beta'),             # remove parentheses
+)
+
+_SUFFIX_REPLACEMENTS = (
+    (re.compile('^[:~._+-]+'), ''),                   # remove leading puncts
+    (re.compile('[,*")([\\]]'), ''),                  # remove unwanted chars
+    (re.compile('[~:+_ -]'), '.'),                    # replace illegal chars
+    (re.compile('[.]{2,}'), '.'),                   # multiple runs of '.'
+    (re.compile(r'\.$'), ''),                       # trailing '.'
+)
+
+_NUMERIC_PREFIX = re.compile(r'(\d+(\.\d+)*)')
+
+
+def _suggest_semantic_version(s):
+    """
+    Try to suggest a semantic form for a version for which
+    _suggest_normalized_version couldn't come up with anything.
+    """
+    result = s.strip().lower()
+    for pat, repl in _REPLACEMENTS:
+        result = pat.sub(repl, result)
+    if not result:
+        result = '0.0.0'
+
+    # Now look for numeric prefix, and separate it out from
+    # the rest.
+    #import pdb; pdb.set_trace()
+    m = _NUMERIC_PREFIX.match(result)
+    if not m:
+        prefix = '0.0.0'
+        suffix = result
+    else:
+        prefix = m.groups()[0].split('.')
+        prefix = [int(i) for i in prefix]
+        while len(prefix) < 3:
+            prefix.append(0)
+        if len(prefix) == 3:
+            suffix = result[m.end():]
+        else:
+            suffix = '.'.join([str(i) for i in prefix[3:]]) + result[m.end():]
+            prefix = prefix[:3]
+        prefix = '.'.join([str(i) for i in prefix])
+        suffix = suffix.strip()
+    if suffix:
+        #import pdb; pdb.set_trace()
+        # massage the suffix.
+        for pat, repl in _SUFFIX_REPLACEMENTS:
+            suffix = pat.sub(repl, suffix)
+
+    if not suffix:
+        result = prefix
+    else:
+        sep = '-' if 'dev' in suffix else '+'
+        result = prefix + sep + suffix
+    if not is_semver(result):
+        result = None
+    return result
+
+
+def _suggest_normalized_version(s):
+    """Suggest a normalized version close to the given version string.
+
+    If you have a version string that isn't rational (i.e. NormalizedVersion
+    doesn't like it) then you might be able to get an equivalent (or close)
+    rational version from this function.
+
+    This does a number of simple normalizations to the given string, based
+    on observation of versions currently in use on PyPI. Given a dump of
+    those version during PyCon 2009, 4287 of them:
+    - 2312 (53.93%) match NormalizedVersion without change
+      with the automatic suggestion
+    - 3474 (81.04%) match when using this suggestion method
+
+    @param s {str} An irrational version string.
+    @returns A rational version string, or None, if couldn't determine one.
+    """
+    try:
+        _normalized_key(s)
+        return s   # already rational
+    except UnsupportedVersionError:
+        pass
+
+    rs = s.lower()
+
+    # part of this could use maketrans
+    for orig, repl in (('-alpha', 'a'), ('-beta', 'b'), ('alpha', 'a'),
+                       ('beta', 'b'), ('rc', 'c'), ('-final', ''),
+                       ('-pre', 'c'),
+                       ('-release', ''), ('.release', ''), ('-stable', ''),
+                       ('+', '.'), ('_', '.'), (' ', ''), ('.final', ''),
+                       ('final', '')):
+        rs = rs.replace(orig, repl)
+
+    # if something ends with dev or pre, we add a 0
+    rs = re.sub(r"pre$", r"pre0", rs)
+    rs = re.sub(r"dev$", r"dev0", rs)
+
+    # if we have something like "b-2" or "a.2" at the end of the
+    # version, that is probably beta, alpha, etc
+    # let's remove the dash or dot
+    rs = re.sub(r"([abc]|rc)[\-\.](\d+)$", r"\1\2", rs)
+
+    # 1.0-dev-r371 -> 1.0.dev371
+    # 0.1-dev-r79 -> 0.1.dev79
+    rs = re.sub(r"[\-\.](dev)[\-\.]?r?(\d+)$", r".\1\2", rs)
+
+    # Clean: 2.0.a.3, 2.0.b1, 0.9.0~c1
+    rs = re.sub(r"[.~]?([abc])\.?", r"\1", rs)
+
+    # Clean: v0.3, v1.0
+    if rs.startswith('v'):
+        rs = rs[1:]
+
+    # Clean leading '0's on numbers.
+    #TODO: unintended side-effect on, e.g., "2003.05.09"
+    # PyPI stats: 77 (~2%) better
+    rs = re.sub(r"\b0+(\d+)(?!\d)", r"\1", rs)
+
+    # Clean a/b/c with no version. E.g. "1.0a" -> "1.0a0". Setuptools infers
+    # zero.
+    # PyPI stats: 245 (7.56%) better
+    rs = re.sub(r"(\d+[abc])$", r"\g<1>0", rs)
+
+    # the 'dev-rNNN' tag is a dev tag
+    rs = re.sub(r"\.?(dev-r|dev\.r)\.?(\d+)$", r".dev\2", rs)
+
+    # clean the - when used as a pre delimiter
+    rs = re.sub(r"-(a|b|c)(\d+)$", r"\1\2", rs)
+
+    # a terminal "dev" or "devel" can be changed into ".dev0"
+    rs = re.sub(r"[\.\-](dev|devel)$", r".dev0", rs)
+
+    # a terminal "dev" can be changed into ".dev0"
+    rs = re.sub(r"(?![\.\-])dev$", r".dev0", rs)
+
+    # a terminal "final" or "stable" can be removed
+    rs = re.sub(r"(final|stable)$", "", rs)
+
+    # The 'r' and the '-' tags are post release tags
+    #   0.4a1.r10       ->  0.4a1.post10
+    #   0.9.33-17222    ->  0.9.33.post17222
+    #   0.9.33-r17222   ->  0.9.33.post17222
+    rs = re.sub(r"\.?(r|-|-r)\.?(\d+)$", r".post\2", rs)
+
+    # Clean 'r' instead of 'dev' usage:
+    #   0.9.33+r17222   ->  0.9.33.dev17222
+    #   1.0dev123       ->  1.0.dev123
+    #   1.0.git123      ->  1.0.dev123
+    #   1.0.bzr123      ->  1.0.dev123
+    #   0.1a0dev.123    ->  0.1a0.dev123
+    # PyPI stats:  ~150 (~4%) better
+    rs = re.sub(r"\.?(dev|git|bzr)\.?(\d+)$", r".dev\2", rs)
+
+    # Clean '.pre' (normalized from '-pre' above) instead of 'c' usage:
+    #   0.2.pre1        ->  0.2c1
+    #   0.2-c1         ->  0.2c1
+    #   1.0preview123   ->  1.0c123
+    # PyPI stats: ~21 (0.62%) better
+    rs = re.sub(r"\.?(pre|preview|-c)(\d+)$", r"c\g<2>", rs)
+
+    # Tcl/Tk uses "px" for their post release markers
+    rs = re.sub(r"p(\d+)$", r".post\1", rs)
+
+    try:
+        _normalized_key(rs)
+    except UnsupportedVersionError:
+        rs = None
+    return rs
+
+#
+#   Legacy version processing (distribute-compatible)
+#
+
+_VERSION_PART = re.compile(r'([a-z]+|\d+|[\.-])', re.I)
+_VERSION_REPLACE = {
+    'pre': 'c',
+    'preview': 'c',
+    '-': 'final-',
+    'rc': 'c',
+    'dev': '@',
+    '': None,
+    '.': None,
+}
+
+
+def _legacy_key(s):
+    def get_parts(s):
+        result = []
+        for p in _VERSION_PART.split(s.lower()):
+            p = _VERSION_REPLACE.get(p, p)
+            if p:
+                if '0' <= p[:1] <= '9':
+                    p = p.zfill(8)
+                else:
+                    p = '*' + p
+                result.append(p)
+        result.append('*final')
+        return result
+
+    result = []
+    for p in get_parts(s):
+        if p.startswith('*'):
+            if p < '*final':
+                while result and result[-1] == '*final-':
+                    result.pop()
+            while result and result[-1] == '00000000':
+                result.pop()
+        result.append(p)
+    return tuple(result)
+
+
+class LegacyVersion(Version):
+    def parse(self, s):
+        return _legacy_key(s)
+
+    @property
+    def is_prerelease(self):
+        result = False
+        for x in self._parts:
+            if (isinstance(x, string_types) and x.startswith('*') and
+                x < '*final'):
+                result = True
+                break
+        return result
+
+
+class LegacyMatcher(Matcher):
+    version_class = LegacyVersion
+
+    _operators = dict(Matcher._operators)
+    _operators['~='] = '_match_compatible'
+
+    numeric_re = re.compile(r'^(\d+(\.\d+)*)')
+
+    def _match_compatible(self, version, constraint, prefix):
+        if version < constraint:
+            return False
+        m = self.numeric_re.match(str(constraint))
+        if not m:
+            logger.warning('Cannot compute compatible match for version %s '
+                           ' and constraint %s', version, constraint)
+            return True
+        s = m.groups()[0]
+        if '.' in s:
+            s = s.rsplit('.', 1)[0]
+        return _match_prefix(version, s)
+
+#
+#   Semantic versioning
+#
+
+_SEMVER_RE = re.compile(r'^(\d+)\.(\d+)\.(\d+)'
+                        r'(-[a-z0-9]+(\.[a-z0-9-]+)*)?'
+                        r'(\+[a-z0-9]+(\.[a-z0-9-]+)*)?$', re.I)
+
+
+def is_semver(s):
+    return _SEMVER_RE.match(s)
+
+
+def _semantic_key(s):
+    def make_tuple(s, absent):
+        if s is None:
+            result = (absent,)
+        else:
+            parts = s[1:].split('.')
+            # We can't compare ints and strings on Python 3, so fudge it
+            # by zero-filling numeric values so simulate a numeric comparison
+            result = tuple([p.zfill(8) if p.isdigit() else p for p in parts])
+        return result
+
+    m = is_semver(s)
+    if not m:
+        raise UnsupportedVersionError(s)
+    groups = m.groups()
+    major, minor, patch = [int(i) for i in groups[:3]]
+    # choose the '|' and '*' so that versions sort correctly
+    pre, build = make_tuple(groups[3], '|'), make_tuple(groups[5], '*')
+    return (major, minor, patch), pre, build
+
+
+class SemanticVersion(Version):
+    def parse(self, s):
+        return _semantic_key(s)
+
+    @property
+    def is_prerelease(self):
+        return self._parts[1][0] != '|'
+
+
+class SemanticMatcher(Matcher):
+    version_class = SemanticVersion
+
+
+class VersionScheme(object):
+    def __init__(self, key, matcher, suggester=None):
+        self.key = key
+        self.matcher = matcher
+        self.suggester = suggester
+
+    def is_valid_version(self, s):
+        try:
+            self.matcher.version_class(s)
+            result = True
+        except UnsupportedVersionError:
+            result = False
+        return result
+
+    def is_valid_matcher(self, s):
+        try:
+            self.matcher(s)
+            result = True
+        except UnsupportedVersionError:
+            result = False
+        return result
+
+    def is_valid_constraint_list(self, s):
+        """
+        Used for processing some metadata fields
+        """
+        # See issue #140. Be tolerant of a single trailing comma.
+        if s.endswith(','):
+            s = s[:-1]
+        return self.is_valid_matcher('dummy_name (%s)' % s)
+
+    def suggest(self, s):
+        if self.suggester is None:
+            result = None
+        else:
+            result = self.suggester(s)
+        return result
+
+_SCHEMES = {
+    'normalized': VersionScheme(_normalized_key, NormalizedMatcher,
+                                _suggest_normalized_version),
+    'legacy': VersionScheme(_legacy_key, LegacyMatcher, lambda self, s: s),
+    'semantic': VersionScheme(_semantic_key, SemanticMatcher,
+                              _suggest_semantic_version),
+}
+
+_SCHEMES['default'] = _SCHEMES['normalized']
+
+
+def get_scheme(name):
+    if name not in _SCHEMES:
+        raise ValueError('unknown scheme name: %r' % name)
+    return _SCHEMES[name]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w32.exe b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w32.exe
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diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w64-arm.exe b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w64-arm.exe
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+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w64-arm.exe
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c5dc9884a8f458371550e09bd396e5418bf375820a31b9899f6499bf391c7b2e
+size 168448
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w64.exe b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w64.exe
new file mode 100644
index 0000000000000000000000000000000000000000..daebd1c30353b2d9b016069da83ad5b4c8ee86bd
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+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/w64.exe
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a319ffaba23a017d7b1e18ba726ba6c54c53d6446db55f92af53c279894f8ad
+size 101888
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/wheel.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/wheel.py
new file mode 100644
index 0000000000000000000000000000000000000000..028c2d99b57782ed3bb268ce522ede37c1704d98
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distlib/wheel.py
@@ -0,0 +1,1082 @@
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2013-2020 Vinay Sajip.
+# Licensed to the Python Software Foundation under a contributor agreement.
+# See LICENSE.txt and CONTRIBUTORS.txt.
+#
+from __future__ import unicode_literals
+
+import base64
+import codecs
+import datetime
+from email import message_from_file
+import hashlib
+import json
+import logging
+import os
+import posixpath
+import re
+import shutil
+import sys
+import tempfile
+import zipfile
+
+from . import __version__, DistlibException
+from .compat import sysconfig, ZipFile, fsdecode, text_type, filter
+from .database import InstalledDistribution
+from .metadata import (Metadata, METADATA_FILENAME, WHEEL_METADATA_FILENAME,
+                       LEGACY_METADATA_FILENAME)
+from .util import (FileOperator, convert_path, CSVReader, CSVWriter, Cache,
+                   cached_property, get_cache_base, read_exports, tempdir,
+                   get_platform)
+from .version import NormalizedVersion, UnsupportedVersionError
+
+logger = logging.getLogger(__name__)
+
+cache = None    # created when needed
+
+if hasattr(sys, 'pypy_version_info'):  # pragma: no cover
+    IMP_PREFIX = 'pp'
+elif sys.platform.startswith('java'):  # pragma: no cover
+    IMP_PREFIX = 'jy'
+elif sys.platform == 'cli':  # pragma: no cover
+    IMP_PREFIX = 'ip'
+else:
+    IMP_PREFIX = 'cp'
+
+VER_SUFFIX = sysconfig.get_config_var('py_version_nodot')
+if not VER_SUFFIX:   # pragma: no cover
+    VER_SUFFIX = '%s%s' % sys.version_info[:2]
+PYVER = 'py' + VER_SUFFIX
+IMPVER = IMP_PREFIX + VER_SUFFIX
+
+ARCH = get_platform().replace('-', '_').replace('.', '_')
+
+ABI = sysconfig.get_config_var('SOABI')
+if ABI and ABI.startswith('cpython-'):
+    ABI = ABI.replace('cpython-', 'cp').split('-')[0]
+else:
+    def _derive_abi():
+        parts = ['cp', VER_SUFFIX]
+        if sysconfig.get_config_var('Py_DEBUG'):
+            parts.append('d')
+        if IMP_PREFIX == 'cp':
+            vi = sys.version_info[:2]
+            if vi < (3, 8):
+                wpm = sysconfig.get_config_var('WITH_PYMALLOC')
+                if wpm is None:
+                    wpm = True
+                if wpm:
+                    parts.append('m')
+                if vi < (3, 3):
+                    us = sysconfig.get_config_var('Py_UNICODE_SIZE')
+                    if us == 4 or (us is None and sys.maxunicode == 0x10FFFF):
+                        parts.append('u')
+        return ''.join(parts)
+    ABI = _derive_abi()
+    del _derive_abi
+
+FILENAME_RE = re.compile(r'''
+(?P[^-]+)
+-(?P\d+[^-]*)
+(-(?P\d+[^-]*))?
+-(?P\w+\d+(\.\w+\d+)*)
+-(?P\w+)
+-(?P\w+(\.\w+)*)
+\.whl$
+''', re.IGNORECASE | re.VERBOSE)
+
+NAME_VERSION_RE = re.compile(r'''
+(?P[^-]+)
+-(?P\d+[^-]*)
+(-(?P\d+[^-]*))?$
+''', re.IGNORECASE | re.VERBOSE)
+
+SHEBANG_RE = re.compile(br'\s*#![^\r\n]*')
+SHEBANG_DETAIL_RE = re.compile(br'^(\s*#!("[^"]+"|\S+))\s+(.*)$')
+SHEBANG_PYTHON = b'#!python'
+SHEBANG_PYTHONW = b'#!pythonw'
+
+if os.sep == '/':
+    to_posix = lambda o: o
+else:
+    to_posix = lambda o: o.replace(os.sep, '/')
+
+if sys.version_info[0] < 3:
+    import imp
+else:
+    imp = None
+    import importlib.machinery
+    import importlib.util
+
+def _get_suffixes():
+    if imp:
+        return [s[0] for s in imp.get_suffixes()]
+    else:
+        return importlib.machinery.EXTENSION_SUFFIXES
+
+def _load_dynamic(name, path):
+    # https://docs.python.org/3/library/importlib.html#importing-a-source-file-directly
+    if imp:
+        return imp.load_dynamic(name, path)
+    else:
+        spec = importlib.util.spec_from_file_location(name, path)
+        module = importlib.util.module_from_spec(spec)
+        sys.modules[name] = module
+        spec.loader.exec_module(module)
+        return module
+
+class Mounter(object):
+    def __init__(self):
+        self.impure_wheels = {}
+        self.libs = {}
+
+    def add(self, pathname, extensions):
+        self.impure_wheels[pathname] = extensions
+        self.libs.update(extensions)
+
+    def remove(self, pathname):
+        extensions = self.impure_wheels.pop(pathname)
+        for k, v in extensions:
+            if k in self.libs:
+                del self.libs[k]
+
+    def find_module(self, fullname, path=None):
+        if fullname in self.libs:
+            result = self
+        else:
+            result = None
+        return result
+
+    def load_module(self, fullname):
+        if fullname in sys.modules:
+            result = sys.modules[fullname]
+        else:
+            if fullname not in self.libs:
+                raise ImportError('unable to find extension for %s' % fullname)
+            result = _load_dynamic(fullname, self.libs[fullname])
+            result.__loader__ = self
+            parts = fullname.rsplit('.', 1)
+            if len(parts) > 1:
+                result.__package__ = parts[0]
+        return result
+
+_hook = Mounter()
+
+
+class Wheel(object):
+    """
+    Class to build and install from Wheel files (PEP 427).
+    """
+
+    wheel_version = (1, 1)
+    hash_kind = 'sha256'
+
+    def __init__(self, filename=None, sign=False, verify=False):
+        """
+        Initialise an instance using a (valid) filename.
+        """
+        self.sign = sign
+        self.should_verify = verify
+        self.buildver = ''
+        self.pyver = [PYVER]
+        self.abi = ['none']
+        self.arch = ['any']
+        self.dirname = os.getcwd()
+        if filename is None:
+            self.name = 'dummy'
+            self.version = '0.1'
+            self._filename = self.filename
+        else:
+            m = NAME_VERSION_RE.match(filename)
+            if m:
+                info = m.groupdict('')
+                self.name = info['nm']
+                # Reinstate the local version separator
+                self.version = info['vn'].replace('_', '-')
+                self.buildver = info['bn']
+                self._filename = self.filename
+            else:
+                dirname, filename = os.path.split(filename)
+                m = FILENAME_RE.match(filename)
+                if not m:
+                    raise DistlibException('Invalid name or '
+                                           'filename: %r' % filename)
+                if dirname:
+                    self.dirname = os.path.abspath(dirname)
+                self._filename = filename
+                info = m.groupdict('')
+                self.name = info['nm']
+                self.version = info['vn']
+                self.buildver = info['bn']
+                self.pyver = info['py'].split('.')
+                self.abi = info['bi'].split('.')
+                self.arch = info['ar'].split('.')
+
+    @property
+    def filename(self):
+        """
+        Build and return a filename from the various components.
+        """
+        if self.buildver:
+            buildver = '-' + self.buildver
+        else:
+            buildver = ''
+        pyver = '.'.join(self.pyver)
+        abi = '.'.join(self.abi)
+        arch = '.'.join(self.arch)
+        # replace - with _ as a local version separator
+        version = self.version.replace('-', '_')
+        return '%s-%s%s-%s-%s-%s.whl' % (self.name, version, buildver,
+                                         pyver, abi, arch)
+
+    @property
+    def exists(self):
+        path = os.path.join(self.dirname, self.filename)
+        return os.path.isfile(path)
+
+    @property
+    def tags(self):
+        for pyver in self.pyver:
+            for abi in self.abi:
+                for arch in self.arch:
+                    yield pyver, abi, arch
+
+    @cached_property
+    def metadata(self):
+        pathname = os.path.join(self.dirname, self.filename)
+        name_ver = '%s-%s' % (self.name, self.version)
+        info_dir = '%s.dist-info' % name_ver
+        wrapper = codecs.getreader('utf-8')
+        with ZipFile(pathname, 'r') as zf:
+            wheel_metadata = self.get_wheel_metadata(zf)
+            wv = wheel_metadata['Wheel-Version'].split('.', 1)
+            file_version = tuple([int(i) for i in wv])
+            # if file_version < (1, 1):
+                # fns = [WHEEL_METADATA_FILENAME, METADATA_FILENAME,
+                       # LEGACY_METADATA_FILENAME]
+            # else:
+                # fns = [WHEEL_METADATA_FILENAME, METADATA_FILENAME]
+            fns = [WHEEL_METADATA_FILENAME, LEGACY_METADATA_FILENAME]
+            result = None
+            for fn in fns:
+                try:
+                    metadata_filename = posixpath.join(info_dir, fn)
+                    with zf.open(metadata_filename) as bf:
+                        wf = wrapper(bf)
+                        result = Metadata(fileobj=wf)
+                        if result:
+                            break
+                except KeyError:
+                    pass
+            if not result:
+                raise ValueError('Invalid wheel, because metadata is '
+                                 'missing: looked in %s' % ', '.join(fns))
+        return result
+
+    def get_wheel_metadata(self, zf):
+        name_ver = '%s-%s' % (self.name, self.version)
+        info_dir = '%s.dist-info' % name_ver
+        metadata_filename = posixpath.join(info_dir, 'WHEEL')
+        with zf.open(metadata_filename) as bf:
+            wf = codecs.getreader('utf-8')(bf)
+            message = message_from_file(wf)
+        return dict(message)
+
+    @cached_property
+    def info(self):
+        pathname = os.path.join(self.dirname, self.filename)
+        with ZipFile(pathname, 'r') as zf:
+            result = self.get_wheel_metadata(zf)
+        return result
+
+    def process_shebang(self, data):
+        m = SHEBANG_RE.match(data)
+        if m:
+            end = m.end()
+            shebang, data_after_shebang = data[:end], data[end:]
+            # Preserve any arguments after the interpreter
+            if b'pythonw' in shebang.lower():
+                shebang_python = SHEBANG_PYTHONW
+            else:
+                shebang_python = SHEBANG_PYTHON
+            m = SHEBANG_DETAIL_RE.match(shebang)
+            if m:
+                args = b' ' + m.groups()[-1]
+            else:
+                args = b''
+            shebang = shebang_python + args
+            data = shebang + data_after_shebang
+        else:
+            cr = data.find(b'\r')
+            lf = data.find(b'\n')
+            if cr < 0 or cr > lf:
+                term = b'\n'
+            else:
+                if data[cr:cr + 2] == b'\r\n':
+                    term = b'\r\n'
+                else:
+                    term = b'\r'
+            data = SHEBANG_PYTHON + term + data
+        return data
+
+    def get_hash(self, data, hash_kind=None):
+        if hash_kind is None:
+            hash_kind = self.hash_kind
+        try:
+            hasher = getattr(hashlib, hash_kind)
+        except AttributeError:
+            raise DistlibException('Unsupported hash algorithm: %r' % hash_kind)
+        result = hasher(data).digest()
+        result = base64.urlsafe_b64encode(result).rstrip(b'=').decode('ascii')
+        return hash_kind, result
+
+    def write_record(self, records, record_path, archive_record_path):
+        records = list(records) # make a copy, as mutated
+        records.append((archive_record_path, '', ''))
+        with CSVWriter(record_path) as writer:
+            for row in records:
+                writer.writerow(row)
+
+    def write_records(self, info, libdir, archive_paths):
+        records = []
+        distinfo, info_dir = info
+        hasher = getattr(hashlib, self.hash_kind)
+        for ap, p in archive_paths:
+            with open(p, 'rb') as f:
+                data = f.read()
+            digest = '%s=%s' % self.get_hash(data)
+            size = os.path.getsize(p)
+            records.append((ap, digest, size))
+
+        p = os.path.join(distinfo, 'RECORD')
+        ap = to_posix(os.path.join(info_dir, 'RECORD'))
+        self.write_record(records, p, ap)
+        archive_paths.append((ap, p))
+
+    def build_zip(self, pathname, archive_paths):
+        with ZipFile(pathname, 'w', zipfile.ZIP_DEFLATED) as zf:
+            for ap, p in archive_paths:
+                logger.debug('Wrote %s to %s in wheel', p, ap)
+                zf.write(p, ap)
+
+    def build(self, paths, tags=None, wheel_version=None):
+        """
+        Build a wheel from files in specified paths, and use any specified tags
+        when determining the name of the wheel.
+        """
+        if tags is None:
+            tags = {}
+
+        libkey = list(filter(lambda o: o in paths, ('purelib', 'platlib')))[0]
+        if libkey == 'platlib':
+            is_pure = 'false'
+            default_pyver = [IMPVER]
+            default_abi = [ABI]
+            default_arch = [ARCH]
+        else:
+            is_pure = 'true'
+            default_pyver = [PYVER]
+            default_abi = ['none']
+            default_arch = ['any']
+
+        self.pyver = tags.get('pyver', default_pyver)
+        self.abi = tags.get('abi', default_abi)
+        self.arch = tags.get('arch', default_arch)
+
+        libdir = paths[libkey]
+
+        name_ver = '%s-%s' % (self.name, self.version)
+        data_dir = '%s.data' % name_ver
+        info_dir = '%s.dist-info' % name_ver
+
+        archive_paths = []
+
+        # First, stuff which is not in site-packages
+        for key in ('data', 'headers', 'scripts'):
+            if key not in paths:
+                continue
+            path = paths[key]
+            if os.path.isdir(path):
+                for root, dirs, files in os.walk(path):
+                    for fn in files:
+                        p = fsdecode(os.path.join(root, fn))
+                        rp = os.path.relpath(p, path)
+                        ap = to_posix(os.path.join(data_dir, key, rp))
+                        archive_paths.append((ap, p))
+                        if key == 'scripts' and not p.endswith('.exe'):
+                            with open(p, 'rb') as f:
+                                data = f.read()
+                            data = self.process_shebang(data)
+                            with open(p, 'wb') as f:
+                                f.write(data)
+
+        # Now, stuff which is in site-packages, other than the
+        # distinfo stuff.
+        path = libdir
+        distinfo = None
+        for root, dirs, files in os.walk(path):
+            if root == path:
+                # At the top level only, save distinfo for later
+                # and skip it for now
+                for i, dn in enumerate(dirs):
+                    dn = fsdecode(dn)
+                    if dn.endswith('.dist-info'):
+                        distinfo = os.path.join(root, dn)
+                        del dirs[i]
+                        break
+                assert distinfo, '.dist-info directory expected, not found'
+
+            for fn in files:
+                # comment out next suite to leave .pyc files in
+                if fsdecode(fn).endswith(('.pyc', '.pyo')):
+                    continue
+                p = os.path.join(root, fn)
+                rp = to_posix(os.path.relpath(p, path))
+                archive_paths.append((rp, p))
+
+        # Now distinfo. Assumed to be flat, i.e. os.listdir is enough.
+        files = os.listdir(distinfo)
+        for fn in files:
+            if fn not in ('RECORD', 'INSTALLER', 'SHARED', 'WHEEL'):
+                p = fsdecode(os.path.join(distinfo, fn))
+                ap = to_posix(os.path.join(info_dir, fn))
+                archive_paths.append((ap, p))
+
+        wheel_metadata = [
+            'Wheel-Version: %d.%d' % (wheel_version or self.wheel_version),
+            'Generator: distlib %s' % __version__,
+            'Root-Is-Purelib: %s' % is_pure,
+        ]
+        for pyver, abi, arch in self.tags:
+            wheel_metadata.append('Tag: %s-%s-%s' % (pyver, abi, arch))
+        p = os.path.join(distinfo, 'WHEEL')
+        with open(p, 'w') as f:
+            f.write('\n'.join(wheel_metadata))
+        ap = to_posix(os.path.join(info_dir, 'WHEEL'))
+        archive_paths.append((ap, p))
+
+        # sort the entries by archive path. Not needed by any spec, but it
+        # keeps the archive listing and RECORD tidier than they would otherwise
+        # be. Use the number of path segments to keep directory entries together,
+        # and keep the dist-info stuff at the end.
+        def sorter(t):
+            ap = t[0]
+            n = ap.count('/')
+            if '.dist-info' in ap:
+                n += 10000
+            return (n, ap)
+        archive_paths = sorted(archive_paths, key=sorter)
+
+        # Now, at last, RECORD.
+        # Paths in here are archive paths - nothing else makes sense.
+        self.write_records((distinfo, info_dir), libdir, archive_paths)
+        # Now, ready to build the zip file
+        pathname = os.path.join(self.dirname, self.filename)
+        self.build_zip(pathname, archive_paths)
+        return pathname
+
+    def skip_entry(self, arcname):
+        """
+        Determine whether an archive entry should be skipped when verifying
+        or installing.
+        """
+        # The signature file won't be in RECORD,
+        # and we  don't currently don't do anything with it
+        # We also skip directories, as they won't be in RECORD
+        # either. See:
+        #
+        # https://github.com/pypa/wheel/issues/294
+        # https://github.com/pypa/wheel/issues/287
+        # https://github.com/pypa/wheel/pull/289
+        #
+        return arcname.endswith(('/', '/RECORD.jws'))
+
+    def install(self, paths, maker, **kwargs):
+        """
+        Install a wheel to the specified paths. If kwarg ``warner`` is
+        specified, it should be a callable, which will be called with two
+        tuples indicating the wheel version of this software and the wheel
+        version in the file, if there is a discrepancy in the versions.
+        This can be used to issue any warnings to raise any exceptions.
+        If kwarg ``lib_only`` is True, only the purelib/platlib files are
+        installed, and the headers, scripts, data and dist-info metadata are
+        not written. If kwarg ``bytecode_hashed_invalidation`` is True, written
+        bytecode will try to use file-hash based invalidation (PEP-552) on
+        supported interpreter versions (CPython 2.7+).
+
+        The return value is a :class:`InstalledDistribution` instance unless
+        ``options.lib_only`` is True, in which case the return value is ``None``.
+        """
+
+        dry_run = maker.dry_run
+        warner = kwargs.get('warner')
+        lib_only = kwargs.get('lib_only', False)
+        bc_hashed_invalidation = kwargs.get('bytecode_hashed_invalidation', False)
+
+        pathname = os.path.join(self.dirname, self.filename)
+        name_ver = '%s-%s' % (self.name, self.version)
+        data_dir = '%s.data' % name_ver
+        info_dir = '%s.dist-info' % name_ver
+
+        metadata_name = posixpath.join(info_dir, LEGACY_METADATA_FILENAME)
+        wheel_metadata_name = posixpath.join(info_dir, 'WHEEL')
+        record_name = posixpath.join(info_dir, 'RECORD')
+
+        wrapper = codecs.getreader('utf-8')
+
+        with ZipFile(pathname, 'r') as zf:
+            with zf.open(wheel_metadata_name) as bwf:
+                wf = wrapper(bwf)
+                message = message_from_file(wf)
+            wv = message['Wheel-Version'].split('.', 1)
+            file_version = tuple([int(i) for i in wv])
+            if (file_version != self.wheel_version) and warner:
+                warner(self.wheel_version, file_version)
+
+            if message['Root-Is-Purelib'] == 'true':
+                libdir = paths['purelib']
+            else:
+                libdir = paths['platlib']
+
+            records = {}
+            with zf.open(record_name) as bf:
+                with CSVReader(stream=bf) as reader:
+                    for row in reader:
+                        p = row[0]
+                        records[p] = row
+
+            data_pfx = posixpath.join(data_dir, '')
+            info_pfx = posixpath.join(info_dir, '')
+            script_pfx = posixpath.join(data_dir, 'scripts', '')
+
+            # make a new instance rather than a copy of maker's,
+            # as we mutate it
+            fileop = FileOperator(dry_run=dry_run)
+            fileop.record = True    # so we can rollback if needed
+
+            bc = not sys.dont_write_bytecode    # Double negatives. Lovely!
+
+            outfiles = []   # for RECORD writing
+
+            # for script copying/shebang processing
+            workdir = tempfile.mkdtemp()
+            # set target dir later
+            # we default add_launchers to False, as the
+            # Python Launcher should be used instead
+            maker.source_dir = workdir
+            maker.target_dir = None
+            try:
+                for zinfo in zf.infolist():
+                    arcname = zinfo.filename
+                    if isinstance(arcname, text_type):
+                        u_arcname = arcname
+                    else:
+                        u_arcname = arcname.decode('utf-8')
+                    if self.skip_entry(u_arcname):
+                        continue
+                    row = records[u_arcname]
+                    if row[2] and str(zinfo.file_size) != row[2]:
+                        raise DistlibException('size mismatch for '
+                                               '%s' % u_arcname)
+                    if row[1]:
+                        kind, value = row[1].split('=', 1)
+                        with zf.open(arcname) as bf:
+                            data = bf.read()
+                        _, digest = self.get_hash(data, kind)
+                        if digest != value:
+                            raise DistlibException('digest mismatch for '
+                                                   '%s' % arcname)
+
+                    if lib_only and u_arcname.startswith((info_pfx, data_pfx)):
+                        logger.debug('lib_only: skipping %s', u_arcname)
+                        continue
+                    is_script = (u_arcname.startswith(script_pfx)
+                                 and not u_arcname.endswith('.exe'))
+
+                    if u_arcname.startswith(data_pfx):
+                        _, where, rp = u_arcname.split('/', 2)
+                        outfile = os.path.join(paths[where], convert_path(rp))
+                    else:
+                        # meant for site-packages.
+                        if u_arcname in (wheel_metadata_name, record_name):
+                            continue
+                        outfile = os.path.join(libdir, convert_path(u_arcname))
+                    if not is_script:
+                        with zf.open(arcname) as bf:
+                            fileop.copy_stream(bf, outfile)
+                        # Issue #147: permission bits aren't preserved. Using
+                        # zf.extract(zinfo, libdir) should have worked, but didn't,
+                        # see https://www.thetopsites.net/article/53834422.shtml
+                        # So ... manually preserve permission bits as given in zinfo
+                        if os.name == 'posix':
+                            # just set the normal permission bits
+                            os.chmod(outfile, (zinfo.external_attr >> 16) & 0x1FF)
+                        outfiles.append(outfile)
+                        # Double check the digest of the written file
+                        if not dry_run and row[1]:
+                            with open(outfile, 'rb') as bf:
+                                data = bf.read()
+                                _, newdigest = self.get_hash(data, kind)
+                                if newdigest != digest:
+                                    raise DistlibException('digest mismatch '
+                                                           'on write for '
+                                                           '%s' % outfile)
+                        if bc and outfile.endswith('.py'):
+                            try:
+                                pyc = fileop.byte_compile(outfile,
+                                                          hashed_invalidation=bc_hashed_invalidation)
+                                outfiles.append(pyc)
+                            except Exception:
+                                # Don't give up if byte-compilation fails,
+                                # but log it and perhaps warn the user
+                                logger.warning('Byte-compilation failed',
+                                               exc_info=True)
+                    else:
+                        fn = os.path.basename(convert_path(arcname))
+                        workname = os.path.join(workdir, fn)
+                        with zf.open(arcname) as bf:
+                            fileop.copy_stream(bf, workname)
+
+                        dn, fn = os.path.split(outfile)
+                        maker.target_dir = dn
+                        filenames = maker.make(fn)
+                        fileop.set_executable_mode(filenames)
+                        outfiles.extend(filenames)
+
+                if lib_only:
+                    logger.debug('lib_only: returning None')
+                    dist = None
+                else:
+                    # Generate scripts
+
+                    # Try to get pydist.json so we can see if there are
+                    # any commands to generate. If this fails (e.g. because
+                    # of a legacy wheel), log a warning but don't give up.
+                    commands = None
+                    file_version = self.info['Wheel-Version']
+                    if file_version == '1.0':
+                        # Use legacy info
+                        ep = posixpath.join(info_dir, 'entry_points.txt')
+                        try:
+                            with zf.open(ep) as bwf:
+                                epdata = read_exports(bwf)
+                            commands = {}
+                            for key in ('console', 'gui'):
+                                k = '%s_scripts' % key
+                                if k in epdata:
+                                    commands['wrap_%s' % key] = d = {}
+                                    for v in epdata[k].values():
+                                        s = '%s:%s' % (v.prefix, v.suffix)
+                                        if v.flags:
+                                            s += ' [%s]' % ','.join(v.flags)
+                                        d[v.name] = s
+                        except Exception:
+                            logger.warning('Unable to read legacy script '
+                                           'metadata, so cannot generate '
+                                           'scripts')
+                    else:
+                        try:
+                            with zf.open(metadata_name) as bwf:
+                                wf = wrapper(bwf)
+                                commands = json.load(wf).get('extensions')
+                                if commands:
+                                    commands = commands.get('python.commands')
+                        except Exception:
+                            logger.warning('Unable to read JSON metadata, so '
+                                           'cannot generate scripts')
+                    if commands:
+                        console_scripts = commands.get('wrap_console', {})
+                        gui_scripts = commands.get('wrap_gui', {})
+                        if console_scripts or gui_scripts:
+                            script_dir = paths.get('scripts', '')
+                            if not os.path.isdir(script_dir):
+                                raise ValueError('Valid script path not '
+                                                 'specified')
+                            maker.target_dir = script_dir
+                            for k, v in console_scripts.items():
+                                script = '%s = %s' % (k, v)
+                                filenames = maker.make(script)
+                                fileop.set_executable_mode(filenames)
+
+                            if gui_scripts:
+                                options = {'gui': True }
+                                for k, v in gui_scripts.items():
+                                    script = '%s = %s' % (k, v)
+                                    filenames = maker.make(script, options)
+                                    fileop.set_executable_mode(filenames)
+
+                    p = os.path.join(libdir, info_dir)
+                    dist = InstalledDistribution(p)
+
+                    # Write SHARED
+                    paths = dict(paths)     # don't change passed in dict
+                    del paths['purelib']
+                    del paths['platlib']
+                    paths['lib'] = libdir
+                    p = dist.write_shared_locations(paths, dry_run)
+                    if p:
+                        outfiles.append(p)
+
+                    # Write RECORD
+                    dist.write_installed_files(outfiles, paths['prefix'],
+                                               dry_run)
+                return dist
+            except Exception:  # pragma: no cover
+                logger.exception('installation failed.')
+                fileop.rollback()
+                raise
+            finally:
+                shutil.rmtree(workdir)
+
+    def _get_dylib_cache(self):
+        global cache
+        if cache is None:
+            # Use native string to avoid issues on 2.x: see Python #20140.
+            base = os.path.join(get_cache_base(), str('dylib-cache'),
+                                '%s.%s' % sys.version_info[:2])
+            cache = Cache(base)
+        return cache
+
+    def _get_extensions(self):
+        pathname = os.path.join(self.dirname, self.filename)
+        name_ver = '%s-%s' % (self.name, self.version)
+        info_dir = '%s.dist-info' % name_ver
+        arcname = posixpath.join(info_dir, 'EXTENSIONS')
+        wrapper = codecs.getreader('utf-8')
+        result = []
+        with ZipFile(pathname, 'r') as zf:
+            try:
+                with zf.open(arcname) as bf:
+                    wf = wrapper(bf)
+                    extensions = json.load(wf)
+                    cache = self._get_dylib_cache()
+                    prefix = cache.prefix_to_dir(pathname)
+                    cache_base = os.path.join(cache.base, prefix)
+                    if not os.path.isdir(cache_base):
+                        os.makedirs(cache_base)
+                    for name, relpath in extensions.items():
+                        dest = os.path.join(cache_base, convert_path(relpath))
+                        if not os.path.exists(dest):
+                            extract = True
+                        else:
+                            file_time = os.stat(dest).st_mtime
+                            file_time = datetime.datetime.fromtimestamp(file_time)
+                            info = zf.getinfo(relpath)
+                            wheel_time = datetime.datetime(*info.date_time)
+                            extract = wheel_time > file_time
+                        if extract:
+                            zf.extract(relpath, cache_base)
+                        result.append((name, dest))
+            except KeyError:
+                pass
+        return result
+
+    def is_compatible(self):
+        """
+        Determine if a wheel is compatible with the running system.
+        """
+        return is_compatible(self)
+
+    def is_mountable(self):
+        """
+        Determine if a wheel is asserted as mountable by its metadata.
+        """
+        return True # for now - metadata details TBD
+
+    def mount(self, append=False):
+        pathname = os.path.abspath(os.path.join(self.dirname, self.filename))
+        if not self.is_compatible():
+            msg = 'Wheel %s not compatible with this Python.' % pathname
+            raise DistlibException(msg)
+        if not self.is_mountable():
+            msg = 'Wheel %s is marked as not mountable.' % pathname
+            raise DistlibException(msg)
+        if pathname in sys.path:
+            logger.debug('%s already in path', pathname)
+        else:
+            if append:
+                sys.path.append(pathname)
+            else:
+                sys.path.insert(0, pathname)
+            extensions = self._get_extensions()
+            if extensions:
+                if _hook not in sys.meta_path:
+                    sys.meta_path.append(_hook)
+                _hook.add(pathname, extensions)
+
+    def unmount(self):
+        pathname = os.path.abspath(os.path.join(self.dirname, self.filename))
+        if pathname not in sys.path:
+            logger.debug('%s not in path', pathname)
+        else:
+            sys.path.remove(pathname)
+            if pathname in _hook.impure_wheels:
+                _hook.remove(pathname)
+            if not _hook.impure_wheels:
+                if _hook in sys.meta_path:
+                    sys.meta_path.remove(_hook)
+
+    def verify(self):
+        pathname = os.path.join(self.dirname, self.filename)
+        name_ver = '%s-%s' % (self.name, self.version)
+        data_dir = '%s.data' % name_ver
+        info_dir = '%s.dist-info' % name_ver
+
+        metadata_name = posixpath.join(info_dir, LEGACY_METADATA_FILENAME)
+        wheel_metadata_name = posixpath.join(info_dir, 'WHEEL')
+        record_name = posixpath.join(info_dir, 'RECORD')
+
+        wrapper = codecs.getreader('utf-8')
+
+        with ZipFile(pathname, 'r') as zf:
+            with zf.open(wheel_metadata_name) as bwf:
+                wf = wrapper(bwf)
+                message = message_from_file(wf)
+            wv = message['Wheel-Version'].split('.', 1)
+            file_version = tuple([int(i) for i in wv])
+            # TODO version verification
+
+            records = {}
+            with zf.open(record_name) as bf:
+                with CSVReader(stream=bf) as reader:
+                    for row in reader:
+                        p = row[0]
+                        records[p] = row
+
+            for zinfo in zf.infolist():
+                arcname = zinfo.filename
+                if isinstance(arcname, text_type):
+                    u_arcname = arcname
+                else:
+                    u_arcname = arcname.decode('utf-8')
+                # See issue #115: some wheels have .. in their entries, but
+                # in the filename ... e.g. __main__..py ! So the check is
+                # updated to look for .. in the directory portions
+                p = u_arcname.split('/')
+                if '..' in p:
+                    raise DistlibException('invalid entry in '
+                                           'wheel: %r' % u_arcname)
+
+                if self.skip_entry(u_arcname):
+                    continue
+                row = records[u_arcname]
+                if row[2] and str(zinfo.file_size) != row[2]:
+                    raise DistlibException('size mismatch for '
+                                           '%s' % u_arcname)
+                if row[1]:
+                    kind, value = row[1].split('=', 1)
+                    with zf.open(arcname) as bf:
+                        data = bf.read()
+                    _, digest = self.get_hash(data, kind)
+                    if digest != value:
+                        raise DistlibException('digest mismatch for '
+                                               '%s' % arcname)
+
+    def update(self, modifier, dest_dir=None, **kwargs):
+        """
+        Update the contents of a wheel in a generic way. The modifier should
+        be a callable which expects a dictionary argument: its keys are
+        archive-entry paths, and its values are absolute filesystem paths
+        where the contents the corresponding archive entries can be found. The
+        modifier is free to change the contents of the files pointed to, add
+        new entries and remove entries, before returning. This method will
+        extract the entire contents of the wheel to a temporary location, call
+        the modifier, and then use the passed (and possibly updated)
+        dictionary to write a new wheel. If ``dest_dir`` is specified, the new
+        wheel is written there -- otherwise, the original wheel is overwritten.
+
+        The modifier should return True if it updated the wheel, else False.
+        This method returns the same value the modifier returns.
+        """
+
+        def get_version(path_map, info_dir):
+            version = path = None
+            key = '%s/%s' % (info_dir, LEGACY_METADATA_FILENAME)
+            if key not in path_map:
+                key = '%s/PKG-INFO' % info_dir
+            if key in path_map:
+                path = path_map[key]
+                version = Metadata(path=path).version
+            return version, path
+
+        def update_version(version, path):
+            updated = None
+            try:
+                v = NormalizedVersion(version)
+                i = version.find('-')
+                if i < 0:
+                    updated = '%s+1' % version
+                else:
+                    parts = [int(s) for s in version[i + 1:].split('.')]
+                    parts[-1] += 1
+                    updated = '%s+%s' % (version[:i],
+                                         '.'.join(str(i) for i in parts))
+            except UnsupportedVersionError:
+                logger.debug('Cannot update non-compliant (PEP-440) '
+                             'version %r', version)
+            if updated:
+                md = Metadata(path=path)
+                md.version = updated
+                legacy = path.endswith(LEGACY_METADATA_FILENAME)
+                md.write(path=path, legacy=legacy)
+                logger.debug('Version updated from %r to %r', version,
+                             updated)
+
+        pathname = os.path.join(self.dirname, self.filename)
+        name_ver = '%s-%s' % (self.name, self.version)
+        info_dir = '%s.dist-info' % name_ver
+        record_name = posixpath.join(info_dir, 'RECORD')
+        with tempdir() as workdir:
+            with ZipFile(pathname, 'r') as zf:
+                path_map = {}
+                for zinfo in zf.infolist():
+                    arcname = zinfo.filename
+                    if isinstance(arcname, text_type):
+                        u_arcname = arcname
+                    else:
+                        u_arcname = arcname.decode('utf-8')
+                    if u_arcname == record_name:
+                        continue
+                    if '..' in u_arcname:
+                        raise DistlibException('invalid entry in '
+                                               'wheel: %r' % u_arcname)
+                    zf.extract(zinfo, workdir)
+                    path = os.path.join(workdir, convert_path(u_arcname))
+                    path_map[u_arcname] = path
+
+            # Remember the version.
+            original_version, _ = get_version(path_map, info_dir)
+            # Files extracted. Call the modifier.
+            modified = modifier(path_map, **kwargs)
+            if modified:
+                # Something changed - need to build a new wheel.
+                current_version, path = get_version(path_map, info_dir)
+                if current_version and (current_version == original_version):
+                    # Add or update local version to signify changes.
+                    update_version(current_version, path)
+                # Decide where the new wheel goes.
+                if dest_dir is None:
+                    fd, newpath = tempfile.mkstemp(suffix='.whl',
+                                                   prefix='wheel-update-',
+                                                   dir=workdir)
+                    os.close(fd)
+                else:
+                    if not os.path.isdir(dest_dir):
+                        raise DistlibException('Not a directory: %r' % dest_dir)
+                    newpath = os.path.join(dest_dir, self.filename)
+                archive_paths = list(path_map.items())
+                distinfo = os.path.join(workdir, info_dir)
+                info = distinfo, info_dir
+                self.write_records(info, workdir, archive_paths)
+                self.build_zip(newpath, archive_paths)
+                if dest_dir is None:
+                    shutil.copyfile(newpath, pathname)
+        return modified
+
+def _get_glibc_version():
+    import platform
+    ver = platform.libc_ver()
+    result = []
+    if ver[0] == 'glibc':
+        for s in ver[1].split('.'):
+            result.append(int(s) if s.isdigit() else 0)
+        result = tuple(result)
+    return result
+
+def compatible_tags():
+    """
+    Return (pyver, abi, arch) tuples compatible with this Python.
+    """
+    versions = [VER_SUFFIX]
+    major = VER_SUFFIX[0]
+    for minor in range(sys.version_info[1] - 1, - 1, -1):
+        versions.append(''.join([major, str(minor)]))
+
+    abis = []
+    for suffix in _get_suffixes():
+        if suffix.startswith('.abi'):
+            abis.append(suffix.split('.', 2)[1])
+    abis.sort()
+    if ABI != 'none':
+        abis.insert(0, ABI)
+    abis.append('none')
+    result = []
+
+    arches = [ARCH]
+    if sys.platform == 'darwin':
+        m = re.match(r'(\w+)_(\d+)_(\d+)_(\w+)$', ARCH)
+        if m:
+            name, major, minor, arch = m.groups()
+            minor = int(minor)
+            matches = [arch]
+            if arch in ('i386', 'ppc'):
+                matches.append('fat')
+            if arch in ('i386', 'ppc', 'x86_64'):
+                matches.append('fat3')
+            if arch in ('ppc64', 'x86_64'):
+                matches.append('fat64')
+            if arch in ('i386', 'x86_64'):
+                matches.append('intel')
+            if arch in ('i386', 'x86_64', 'intel', 'ppc', 'ppc64'):
+                matches.append('universal')
+            while minor >= 0:
+                for match in matches:
+                    s = '%s_%s_%s_%s' % (name, major, minor, match)
+                    if s != ARCH:   # already there
+                        arches.append(s)
+                minor -= 1
+
+    # Most specific - our Python version, ABI and arch
+    for abi in abis:
+        for arch in arches:
+            result.append((''.join((IMP_PREFIX, versions[0])), abi, arch))
+            # manylinux
+            if abi != 'none' and sys.platform.startswith('linux'):
+                arch = arch.replace('linux_', '')
+                parts = _get_glibc_version()
+                if len(parts) == 2:
+                    if parts >= (2, 5):
+                        result.append((''.join((IMP_PREFIX, versions[0])), abi,
+                                       'manylinux1_%s' % arch))
+                    if parts >= (2, 12):
+                        result.append((''.join((IMP_PREFIX, versions[0])), abi,
+                                       'manylinux2010_%s' % arch))
+                    if parts >= (2, 17):
+                        result.append((''.join((IMP_PREFIX, versions[0])), abi,
+                                       'manylinux2014_%s' % arch))
+                    result.append((''.join((IMP_PREFIX, versions[0])), abi,
+                                   'manylinux_%s_%s_%s' % (parts[0], parts[1],
+                                                           arch)))
+
+    # where no ABI / arch dependency, but IMP_PREFIX dependency
+    for i, version in enumerate(versions):
+        result.append((''.join((IMP_PREFIX, version)), 'none', 'any'))
+        if i == 0:
+            result.append((''.join((IMP_PREFIX, version[0])), 'none', 'any'))
+
+    # no IMP_PREFIX, ABI or arch dependency
+    for i, version in enumerate(versions):
+        result.append((''.join(('py', version)), 'none', 'any'))
+        if i == 0:
+            result.append((''.join(('py', version[0])), 'none', 'any'))
+
+    return set(result)
+
+
+COMPATIBLE_TAGS = compatible_tags()
+
+del compatible_tags
+
+
+def is_compatible(wheel, tags=None):
+    if not isinstance(wheel, Wheel):
+        wheel = Wheel(wheel)    # assume it's a filename
+    result = False
+    if tags is None:
+        tags = COMPATIBLE_TAGS
+    for ver, abi, arch in tags:
+        if ver in wheel.pyver and abi in wheel.abi and arch in wheel.arch:
+            result = True
+            break
+    return result
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..7686fe85a7cc94188da76bfb1c10ad2a10821256
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/__init__.py
@@ -0,0 +1,54 @@
+from .distro import (
+    NORMALIZED_DISTRO_ID,
+    NORMALIZED_LSB_ID,
+    NORMALIZED_OS_ID,
+    LinuxDistribution,
+    __version__,
+    build_number,
+    codename,
+    distro_release_attr,
+    distro_release_info,
+    id,
+    info,
+    like,
+    linux_distribution,
+    lsb_release_attr,
+    lsb_release_info,
+    major_version,
+    minor_version,
+    name,
+    os_release_attr,
+    os_release_info,
+    uname_attr,
+    uname_info,
+    version,
+    version_parts,
+)
+
+__all__ = [
+    "NORMALIZED_DISTRO_ID",
+    "NORMALIZED_LSB_ID",
+    "NORMALIZED_OS_ID",
+    "LinuxDistribution",
+    "build_number",
+    "codename",
+    "distro_release_attr",
+    "distro_release_info",
+    "id",
+    "info",
+    "like",
+    "linux_distribution",
+    "lsb_release_attr",
+    "lsb_release_info",
+    "major_version",
+    "minor_version",
+    "name",
+    "os_release_attr",
+    "os_release_info",
+    "uname_attr",
+    "uname_info",
+    "version",
+    "version_parts",
+]
+
+__version__ = __version__
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/__main__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..0c01d5b08b6b44379b931d54d7fcf5221fdc9fde
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/__main__.py
@@ -0,0 +1,4 @@
+from .distro import main
+
+if __name__ == "__main__":
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/distro.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/distro.py
new file mode 100644
index 0000000000000000000000000000000000000000..89e1868047225bbcdfe04bdc4bea3281bf91bc20
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/distro/distro.py
@@ -0,0 +1,1399 @@
+#!/usr/bin/env python
+# Copyright 2015,2016,2017 Nir Cohen
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+The ``distro`` package (``distro`` stands for Linux Distribution) provides
+information about the Linux distribution it runs on, such as a reliable
+machine-readable distro ID, or version information.
+
+It is the recommended replacement for Python's original
+:py:func:`platform.linux_distribution` function, but it provides much more
+functionality. An alternative implementation became necessary because Python
+3.5 deprecated this function, and Python 3.8 removed it altogether. Its
+predecessor function :py:func:`platform.dist` was already deprecated since
+Python 2.6 and removed in Python 3.8. Still, there are many cases in which
+access to OS distribution information is needed. See `Python issue 1322
+`_ for more information.
+"""
+
+import argparse
+import json
+import logging
+import os
+import re
+import shlex
+import subprocess
+import sys
+import warnings
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    Iterable,
+    Optional,
+    Sequence,
+    TextIO,
+    Tuple,
+    Type,
+)
+
+try:
+    from typing import TypedDict
+except ImportError:
+    # Python 3.7
+    TypedDict = dict
+
+__version__ = "1.8.0"
+
+
+class VersionDict(TypedDict):
+    major: str
+    minor: str
+    build_number: str
+
+
+class InfoDict(TypedDict):
+    id: str
+    version: str
+    version_parts: VersionDict
+    like: str
+    codename: str
+
+
+_UNIXCONFDIR = os.environ.get("UNIXCONFDIR", "/etc")
+_UNIXUSRLIBDIR = os.environ.get("UNIXUSRLIBDIR", "/usr/lib")
+_OS_RELEASE_BASENAME = "os-release"
+
+#: Translation table for normalizing the "ID" attribute defined in os-release
+#: files, for use by the :func:`distro.id` method.
+#:
+#: * Key: Value as defined in the os-release file, translated to lower case,
+#:   with blanks translated to underscores.
+#:
+#: * Value: Normalized value.
+NORMALIZED_OS_ID = {
+    "ol": "oracle",  # Oracle Linux
+    "opensuse-leap": "opensuse",  # Newer versions of OpenSuSE report as opensuse-leap
+}
+
+#: Translation table for normalizing the "Distributor ID" attribute returned by
+#: the lsb_release command, for use by the :func:`distro.id` method.
+#:
+#: * Key: Value as returned by the lsb_release command, translated to lower
+#:   case, with blanks translated to underscores.
+#:
+#: * Value: Normalized value.
+NORMALIZED_LSB_ID = {
+    "enterpriseenterpriseas": "oracle",  # Oracle Enterprise Linux 4
+    "enterpriseenterpriseserver": "oracle",  # Oracle Linux 5
+    "redhatenterpriseworkstation": "rhel",  # RHEL 6, 7 Workstation
+    "redhatenterpriseserver": "rhel",  # RHEL 6, 7 Server
+    "redhatenterprisecomputenode": "rhel",  # RHEL 6 ComputeNode
+}
+
+#: Translation table for normalizing the distro ID derived from the file name
+#: of distro release files, for use by the :func:`distro.id` method.
+#:
+#: * Key: Value as derived from the file name of a distro release file,
+#:   translated to lower case, with blanks translated to underscores.
+#:
+#: * Value: Normalized value.
+NORMALIZED_DISTRO_ID = {
+    "redhat": "rhel",  # RHEL 6.x, 7.x
+}
+
+# Pattern for content of distro release file (reversed)
+_DISTRO_RELEASE_CONTENT_REVERSED_PATTERN = re.compile(
+    r"(?:[^)]*\)(.*)\()? *(?:STL )?([\d.+\-a-z]*\d) *(?:esaeler *)?(.+)"
+)
+
+# Pattern for base file name of distro release file
+_DISTRO_RELEASE_BASENAME_PATTERN = re.compile(r"(\w+)[-_](release|version)$")
+
+# Base file names to be looked up for if _UNIXCONFDIR is not readable.
+_DISTRO_RELEASE_BASENAMES = [
+    "SuSE-release",
+    "arch-release",
+    "base-release",
+    "centos-release",
+    "fedora-release",
+    "gentoo-release",
+    "mageia-release",
+    "mandrake-release",
+    "mandriva-release",
+    "mandrivalinux-release",
+    "manjaro-release",
+    "oracle-release",
+    "redhat-release",
+    "rocky-release",
+    "sl-release",
+    "slackware-version",
+]
+
+# Base file names to be ignored when searching for distro release file
+_DISTRO_RELEASE_IGNORE_BASENAMES = (
+    "debian_version",
+    "lsb-release",
+    "oem-release",
+    _OS_RELEASE_BASENAME,
+    "system-release",
+    "plesk-release",
+    "iredmail-release",
+)
+
+
+def linux_distribution(full_distribution_name: bool = True) -> Tuple[str, str, str]:
+    """
+    .. deprecated:: 1.6.0
+
+        :func:`distro.linux_distribution()` is deprecated. It should only be
+        used as a compatibility shim with Python's
+        :py:func:`platform.linux_distribution()`. Please use :func:`distro.id`,
+        :func:`distro.version` and :func:`distro.name` instead.
+
+    Return information about the current OS distribution as a tuple
+    ``(id_name, version, codename)`` with items as follows:
+
+    * ``id_name``:  If *full_distribution_name* is false, the result of
+      :func:`distro.id`. Otherwise, the result of :func:`distro.name`.
+
+    * ``version``:  The result of :func:`distro.version`.
+
+    * ``codename``:  The extra item (usually in parentheses) after the
+      os-release version number, or the result of :func:`distro.codename`.
+
+    The interface of this function is compatible with the original
+    :py:func:`platform.linux_distribution` function, supporting a subset of
+    its parameters.
+
+    The data it returns may not exactly be the same, because it uses more data
+    sources than the original function, and that may lead to different data if
+    the OS distribution is not consistent across multiple data sources it
+    provides (there are indeed such distributions ...).
+
+    Another reason for differences is the fact that the :func:`distro.id`
+    method normalizes the distro ID string to a reliable machine-readable value
+    for a number of popular OS distributions.
+    """
+    warnings.warn(
+        "distro.linux_distribution() is deprecated. It should only be used as a "
+        "compatibility shim with Python's platform.linux_distribution(). Please use "
+        "distro.id(), distro.version() and distro.name() instead.",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+    return _distro.linux_distribution(full_distribution_name)
+
+
+def id() -> str:
+    """
+    Return the distro ID of the current distribution, as a
+    machine-readable string.
+
+    For a number of OS distributions, the returned distro ID value is
+    *reliable*, in the sense that it is documented and that it does not change
+    across releases of the distribution.
+
+    This package maintains the following reliable distro ID values:
+
+    ==============  =========================================
+    Distro ID       Distribution
+    ==============  =========================================
+    "ubuntu"        Ubuntu
+    "debian"        Debian
+    "rhel"          RedHat Enterprise Linux
+    "centos"        CentOS
+    "fedora"        Fedora
+    "sles"          SUSE Linux Enterprise Server
+    "opensuse"      openSUSE
+    "amzn"          Amazon Linux
+    "arch"          Arch Linux
+    "buildroot"     Buildroot
+    "cloudlinux"    CloudLinux OS
+    "exherbo"       Exherbo Linux
+    "gentoo"        GenToo Linux
+    "ibm_powerkvm"  IBM PowerKVM
+    "kvmibm"        KVM for IBM z Systems
+    "linuxmint"     Linux Mint
+    "mageia"        Mageia
+    "mandriva"      Mandriva Linux
+    "parallels"     Parallels
+    "pidora"        Pidora
+    "raspbian"      Raspbian
+    "oracle"        Oracle Linux (and Oracle Enterprise Linux)
+    "scientific"    Scientific Linux
+    "slackware"     Slackware
+    "xenserver"     XenServer
+    "openbsd"       OpenBSD
+    "netbsd"        NetBSD
+    "freebsd"       FreeBSD
+    "midnightbsd"   MidnightBSD
+    "rocky"         Rocky Linux
+    "aix"           AIX
+    "guix"          Guix System
+    ==============  =========================================
+
+    If you have a need to get distros for reliable IDs added into this set,
+    or if you find that the :func:`distro.id` function returns a different
+    distro ID for one of the listed distros, please create an issue in the
+    `distro issue tracker`_.
+
+    **Lookup hierarchy and transformations:**
+
+    First, the ID is obtained from the following sources, in the specified
+    order. The first available and non-empty value is used:
+
+    * the value of the "ID" attribute of the os-release file,
+
+    * the value of the "Distributor ID" attribute returned by the lsb_release
+      command,
+
+    * the first part of the file name of the distro release file,
+
+    The so determined ID value then passes the following transformations,
+    before it is returned by this method:
+
+    * it is translated to lower case,
+
+    * blanks (which should not be there anyway) are translated to underscores,
+
+    * a normalization of the ID is performed, based upon
+      `normalization tables`_. The purpose of this normalization is to ensure
+      that the ID is as reliable as possible, even across incompatible changes
+      in the OS distributions. A common reason for an incompatible change is
+      the addition of an os-release file, or the addition of the lsb_release
+      command, with ID values that differ from what was previously determined
+      from the distro release file name.
+    """
+    return _distro.id()
+
+
+def name(pretty: bool = False) -> str:
+    """
+    Return the name of the current OS distribution, as a human-readable
+    string.
+
+    If *pretty* is false, the name is returned without version or codename.
+    (e.g. "CentOS Linux")
+
+    If *pretty* is true, the version and codename are appended.
+    (e.g. "CentOS Linux 7.1.1503 (Core)")
+
+    **Lookup hierarchy:**
+
+    The name is obtained from the following sources, in the specified order.
+    The first available and non-empty value is used:
+
+    * If *pretty* is false:
+
+      - the value of the "NAME" attribute of the os-release file,
+
+      - the value of the "Distributor ID" attribute returned by the lsb_release
+        command,
+
+      - the value of the "" field of the distro release file.
+
+    * If *pretty* is true:
+
+      - the value of the "PRETTY_NAME" attribute of the os-release file,
+
+      - the value of the "Description" attribute returned by the lsb_release
+        command,
+
+      - the value of the "" field of the distro release file, appended
+        with the value of the pretty version ("" and ""
+        fields) of the distro release file, if available.
+    """
+    return _distro.name(pretty)
+
+
+def version(pretty: bool = False, best: bool = False) -> str:
+    """
+    Return the version of the current OS distribution, as a human-readable
+    string.
+
+    If *pretty* is false, the version is returned without codename (e.g.
+    "7.0").
+
+    If *pretty* is true, the codename in parenthesis is appended, if the
+    codename is non-empty (e.g. "7.0 (Maipo)").
+
+    Some distributions provide version numbers with different precisions in
+    the different sources of distribution information. Examining the different
+    sources in a fixed priority order does not always yield the most precise
+    version (e.g. for Debian 8.2, or CentOS 7.1).
+
+    Some other distributions may not provide this kind of information. In these
+    cases, an empty string would be returned. This behavior can be observed
+    with rolling releases distributions (e.g. Arch Linux).
+
+    The *best* parameter can be used to control the approach for the returned
+    version:
+
+    If *best* is false, the first non-empty version number in priority order of
+    the examined sources is returned.
+
+    If *best* is true, the most precise version number out of all examined
+    sources is returned.
+
+    **Lookup hierarchy:**
+
+    In all cases, the version number is obtained from the following sources.
+    If *best* is false, this order represents the priority order:
+
+    * the value of the "VERSION_ID" attribute of the os-release file,
+    * the value of the "Release" attribute returned by the lsb_release
+      command,
+    * the version number parsed from the "" field of the first line
+      of the distro release file,
+    * the version number parsed from the "PRETTY_NAME" attribute of the
+      os-release file, if it follows the format of the distro release files.
+    * the version number parsed from the "Description" attribute returned by
+      the lsb_release command, if it follows the format of the distro release
+      files.
+    """
+    return _distro.version(pretty, best)
+
+
+def version_parts(best: bool = False) -> Tuple[str, str, str]:
+    """
+    Return the version of the current OS distribution as a tuple
+    ``(major, minor, build_number)`` with items as follows:
+
+    * ``major``:  The result of :func:`distro.major_version`.
+
+    * ``minor``:  The result of :func:`distro.minor_version`.
+
+    * ``build_number``:  The result of :func:`distro.build_number`.
+
+    For a description of the *best* parameter, see the :func:`distro.version`
+    method.
+    """
+    return _distro.version_parts(best)
+
+
+def major_version(best: bool = False) -> str:
+    """
+    Return the major version of the current OS distribution, as a string,
+    if provided.
+    Otherwise, the empty string is returned. The major version is the first
+    part of the dot-separated version string.
+
+    For a description of the *best* parameter, see the :func:`distro.version`
+    method.
+    """
+    return _distro.major_version(best)
+
+
+def minor_version(best: bool = False) -> str:
+    """
+    Return the minor version of the current OS distribution, as a string,
+    if provided.
+    Otherwise, the empty string is returned. The minor version is the second
+    part of the dot-separated version string.
+
+    For a description of the *best* parameter, see the :func:`distro.version`
+    method.
+    """
+    return _distro.minor_version(best)
+
+
+def build_number(best: bool = False) -> str:
+    """
+    Return the build number of the current OS distribution, as a string,
+    if provided.
+    Otherwise, the empty string is returned. The build number is the third part
+    of the dot-separated version string.
+
+    For a description of the *best* parameter, see the :func:`distro.version`
+    method.
+    """
+    return _distro.build_number(best)
+
+
+def like() -> str:
+    """
+    Return a space-separated list of distro IDs of distributions that are
+    closely related to the current OS distribution in regards to packaging
+    and programming interfaces, for example distributions the current
+    distribution is a derivative from.
+
+    **Lookup hierarchy:**
+
+    This information item is only provided by the os-release file.
+    For details, see the description of the "ID_LIKE" attribute in the
+    `os-release man page
+    `_.
+    """
+    return _distro.like()
+
+
+def codename() -> str:
+    """
+    Return the codename for the release of the current OS distribution,
+    as a string.
+
+    If the distribution does not have a codename, an empty string is returned.
+
+    Note that the returned codename is not always really a codename. For
+    example, openSUSE returns "x86_64". This function does not handle such
+    cases in any special way and just returns the string it finds, if any.
+
+    **Lookup hierarchy:**
+
+    * the codename within the "VERSION" attribute of the os-release file, if
+      provided,
+
+    * the value of the "Codename" attribute returned by the lsb_release
+      command,
+
+    * the value of the "" field of the distro release file.
+    """
+    return _distro.codename()
+
+
+def info(pretty: bool = False, best: bool = False) -> InfoDict:
+    """
+    Return certain machine-readable information items about the current OS
+    distribution in a dictionary, as shown in the following example:
+
+    .. sourcecode:: python
+
+        {
+            'id': 'rhel',
+            'version': '7.0',
+            'version_parts': {
+                'major': '7',
+                'minor': '0',
+                'build_number': ''
+            },
+            'like': 'fedora',
+            'codename': 'Maipo'
+        }
+
+    The dictionary structure and keys are always the same, regardless of which
+    information items are available in the underlying data sources. The values
+    for the various keys are as follows:
+
+    * ``id``:  The result of :func:`distro.id`.
+
+    * ``version``:  The result of :func:`distro.version`.
+
+    * ``version_parts -> major``:  The result of :func:`distro.major_version`.
+
+    * ``version_parts -> minor``:  The result of :func:`distro.minor_version`.
+
+    * ``version_parts -> build_number``:  The result of
+      :func:`distro.build_number`.
+
+    * ``like``:  The result of :func:`distro.like`.
+
+    * ``codename``:  The result of :func:`distro.codename`.
+
+    For a description of the *pretty* and *best* parameters, see the
+    :func:`distro.version` method.
+    """
+    return _distro.info(pretty, best)
+
+
+def os_release_info() -> Dict[str, str]:
+    """
+    Return a dictionary containing key-value pairs for the information items
+    from the os-release file data source of the current OS distribution.
+
+    See `os-release file`_ for details about these information items.
+    """
+    return _distro.os_release_info()
+
+
+def lsb_release_info() -> Dict[str, str]:
+    """
+    Return a dictionary containing key-value pairs for the information items
+    from the lsb_release command data source of the current OS distribution.
+
+    See `lsb_release command output`_ for details about these information
+    items.
+    """
+    return _distro.lsb_release_info()
+
+
+def distro_release_info() -> Dict[str, str]:
+    """
+    Return a dictionary containing key-value pairs for the information items
+    from the distro release file data source of the current OS distribution.
+
+    See `distro release file`_ for details about these information items.
+    """
+    return _distro.distro_release_info()
+
+
+def uname_info() -> Dict[str, str]:
+    """
+    Return a dictionary containing key-value pairs for the information items
+    from the distro release file data source of the current OS distribution.
+    """
+    return _distro.uname_info()
+
+
+def os_release_attr(attribute: str) -> str:
+    """
+    Return a single named information item from the os-release file data source
+    of the current OS distribution.
+
+    Parameters:
+
+    * ``attribute`` (string): Key of the information item.
+
+    Returns:
+
+    * (string): Value of the information item, if the item exists.
+      The empty string, if the item does not exist.
+
+    See `os-release file`_ for details about these information items.
+    """
+    return _distro.os_release_attr(attribute)
+
+
+def lsb_release_attr(attribute: str) -> str:
+    """
+    Return a single named information item from the lsb_release command output
+    data source of the current OS distribution.
+
+    Parameters:
+
+    * ``attribute`` (string): Key of the information item.
+
+    Returns:
+
+    * (string): Value of the information item, if the item exists.
+      The empty string, if the item does not exist.
+
+    See `lsb_release command output`_ for details about these information
+    items.
+    """
+    return _distro.lsb_release_attr(attribute)
+
+
+def distro_release_attr(attribute: str) -> str:
+    """
+    Return a single named information item from the distro release file
+    data source of the current OS distribution.
+
+    Parameters:
+
+    * ``attribute`` (string): Key of the information item.
+
+    Returns:
+
+    * (string): Value of the information item, if the item exists.
+      The empty string, if the item does not exist.
+
+    See `distro release file`_ for details about these information items.
+    """
+    return _distro.distro_release_attr(attribute)
+
+
+def uname_attr(attribute: str) -> str:
+    """
+    Return a single named information item from the distro release file
+    data source of the current OS distribution.
+
+    Parameters:
+
+    * ``attribute`` (string): Key of the information item.
+
+    Returns:
+
+    * (string): Value of the information item, if the item exists.
+                The empty string, if the item does not exist.
+    """
+    return _distro.uname_attr(attribute)
+
+
+try:
+    from functools import cached_property
+except ImportError:
+    # Python < 3.8
+    class cached_property:  # type: ignore
+        """A version of @property which caches the value.  On access, it calls the
+        underlying function and sets the value in `__dict__` so future accesses
+        will not re-call the property.
+        """
+
+        def __init__(self, f: Callable[[Any], Any]) -> None:
+            self._fname = f.__name__
+            self._f = f
+
+        def __get__(self, obj: Any, owner: Type[Any]) -> Any:
+            assert obj is not None, f"call {self._fname} on an instance"
+            ret = obj.__dict__[self._fname] = self._f(obj)
+            return ret
+
+
+class LinuxDistribution:
+    """
+    Provides information about a OS distribution.
+
+    This package creates a private module-global instance of this class with
+    default initialization arguments, that is used by the
+    `consolidated accessor functions`_ and `single source accessor functions`_.
+    By using default initialization arguments, that module-global instance
+    returns data about the current OS distribution (i.e. the distro this
+    package runs on).
+
+    Normally, it is not necessary to create additional instances of this class.
+    However, in situations where control is needed over the exact data sources
+    that are used, instances of this class can be created with a specific
+    distro release file, or a specific os-release file, or without invoking the
+    lsb_release command.
+    """
+
+    def __init__(
+        self,
+        include_lsb: Optional[bool] = None,
+        os_release_file: str = "",
+        distro_release_file: str = "",
+        include_uname: Optional[bool] = None,
+        root_dir: Optional[str] = None,
+        include_oslevel: Optional[bool] = None,
+    ) -> None:
+        """
+        The initialization method of this class gathers information from the
+        available data sources, and stores that in private instance attributes.
+        Subsequent access to the information items uses these private instance
+        attributes, so that the data sources are read only once.
+
+        Parameters:
+
+        * ``include_lsb`` (bool): Controls whether the
+          `lsb_release command output`_ is included as a data source.
+
+          If the lsb_release command is not available in the program execution
+          path, the data source for the lsb_release command will be empty.
+
+        * ``os_release_file`` (string): The path name of the
+          `os-release file`_ that is to be used as a data source.
+
+          An empty string (the default) will cause the default path name to
+          be used (see `os-release file`_ for details).
+
+          If the specified or defaulted os-release file does not exist, the
+          data source for the os-release file will be empty.
+
+        * ``distro_release_file`` (string): The path name of the
+          `distro release file`_ that is to be used as a data source.
+
+          An empty string (the default) will cause a default search algorithm
+          to be used (see `distro release file`_ for details).
+
+          If the specified distro release file does not exist, or if no default
+          distro release file can be found, the data source for the distro
+          release file will be empty.
+
+        * ``include_uname`` (bool): Controls whether uname command output is
+          included as a data source. If the uname command is not available in
+          the program execution path the data source for the uname command will
+          be empty.
+
+        * ``root_dir`` (string): The absolute path to the root directory to use
+          to find distro-related information files. Note that ``include_*``
+          parameters must not be enabled in combination with ``root_dir``.
+
+        * ``include_oslevel`` (bool): Controls whether (AIX) oslevel command
+          output is included as a data source. If the oslevel command is not
+          available in the program execution path the data source will be
+          empty.
+
+        Public instance attributes:
+
+        * ``os_release_file`` (string): The path name of the
+          `os-release file`_ that is actually used as a data source. The
+          empty string if no distro release file is used as a data source.
+
+        * ``distro_release_file`` (string): The path name of the
+          `distro release file`_ that is actually used as a data source. The
+          empty string if no distro release file is used as a data source.
+
+        * ``include_lsb`` (bool): The result of the ``include_lsb`` parameter.
+          This controls whether the lsb information will be loaded.
+
+        * ``include_uname`` (bool): The result of the ``include_uname``
+          parameter. This controls whether the uname information will
+          be loaded.
+
+        * ``include_oslevel`` (bool): The result of the ``include_oslevel``
+          parameter. This controls whether (AIX) oslevel information will be
+          loaded.
+
+        * ``root_dir`` (string): The result of the ``root_dir`` parameter.
+          The absolute path to the root directory to use to find distro-related
+          information files.
+
+        Raises:
+
+        * :py:exc:`ValueError`: Initialization parameters combination is not
+           supported.
+
+        * :py:exc:`OSError`: Some I/O issue with an os-release file or distro
+          release file.
+
+        * :py:exc:`UnicodeError`: A data source has unexpected characters or
+          uses an unexpected encoding.
+        """
+        self.root_dir = root_dir
+        self.etc_dir = os.path.join(root_dir, "etc") if root_dir else _UNIXCONFDIR
+        self.usr_lib_dir = (
+            os.path.join(root_dir, "usr/lib") if root_dir else _UNIXUSRLIBDIR
+        )
+
+        if os_release_file:
+            self.os_release_file = os_release_file
+        else:
+            etc_dir_os_release_file = os.path.join(self.etc_dir, _OS_RELEASE_BASENAME)
+            usr_lib_os_release_file = os.path.join(
+                self.usr_lib_dir, _OS_RELEASE_BASENAME
+            )
+
+            # NOTE: The idea is to respect order **and** have it set
+            #       at all times for API backwards compatibility.
+            if os.path.isfile(etc_dir_os_release_file) or not os.path.isfile(
+                usr_lib_os_release_file
+            ):
+                self.os_release_file = etc_dir_os_release_file
+            else:
+                self.os_release_file = usr_lib_os_release_file
+
+        self.distro_release_file = distro_release_file or ""  # updated later
+
+        is_root_dir_defined = root_dir is not None
+        if is_root_dir_defined and (include_lsb or include_uname or include_oslevel):
+            raise ValueError(
+                "Including subprocess data sources from specific root_dir is disallowed"
+                " to prevent false information"
+            )
+        self.include_lsb = (
+            include_lsb if include_lsb is not None else not is_root_dir_defined
+        )
+        self.include_uname = (
+            include_uname if include_uname is not None else not is_root_dir_defined
+        )
+        self.include_oslevel = (
+            include_oslevel if include_oslevel is not None else not is_root_dir_defined
+        )
+
+    def __repr__(self) -> str:
+        """Return repr of all info"""
+        return (
+            "LinuxDistribution("
+            "os_release_file={self.os_release_file!r}, "
+            "distro_release_file={self.distro_release_file!r}, "
+            "include_lsb={self.include_lsb!r}, "
+            "include_uname={self.include_uname!r}, "
+            "include_oslevel={self.include_oslevel!r}, "
+            "root_dir={self.root_dir!r}, "
+            "_os_release_info={self._os_release_info!r}, "
+            "_lsb_release_info={self._lsb_release_info!r}, "
+            "_distro_release_info={self._distro_release_info!r}, "
+            "_uname_info={self._uname_info!r}, "
+            "_oslevel_info={self._oslevel_info!r})".format(self=self)
+        )
+
+    def linux_distribution(
+        self, full_distribution_name: bool = True
+    ) -> Tuple[str, str, str]:
+        """
+        Return information about the OS distribution that is compatible
+        with Python's :func:`platform.linux_distribution`, supporting a subset
+        of its parameters.
+
+        For details, see :func:`distro.linux_distribution`.
+        """
+        return (
+            self.name() if full_distribution_name else self.id(),
+            self.version(),
+            self._os_release_info.get("release_codename") or self.codename(),
+        )
+
+    def id(self) -> str:
+        """Return the distro ID of the OS distribution, as a string.
+
+        For details, see :func:`distro.id`.
+        """
+
+        def normalize(distro_id: str, table: Dict[str, str]) -> str:
+            distro_id = distro_id.lower().replace(" ", "_")
+            return table.get(distro_id, distro_id)
+
+        distro_id = self.os_release_attr("id")
+        if distro_id:
+            return normalize(distro_id, NORMALIZED_OS_ID)
+
+        distro_id = self.lsb_release_attr("distributor_id")
+        if distro_id:
+            return normalize(distro_id, NORMALIZED_LSB_ID)
+
+        distro_id = self.distro_release_attr("id")
+        if distro_id:
+            return normalize(distro_id, NORMALIZED_DISTRO_ID)
+
+        distro_id = self.uname_attr("id")
+        if distro_id:
+            return normalize(distro_id, NORMALIZED_DISTRO_ID)
+
+        return ""
+
+    def name(self, pretty: bool = False) -> str:
+        """
+        Return the name of the OS distribution, as a string.
+
+        For details, see :func:`distro.name`.
+        """
+        name = (
+            self.os_release_attr("name")
+            or self.lsb_release_attr("distributor_id")
+            or self.distro_release_attr("name")
+            or self.uname_attr("name")
+        )
+        if pretty:
+            name = self.os_release_attr("pretty_name") or self.lsb_release_attr(
+                "description"
+            )
+            if not name:
+                name = self.distro_release_attr("name") or self.uname_attr("name")
+                version = self.version(pretty=True)
+                if version:
+                    name = f"{name} {version}"
+        return name or ""
+
+    def version(self, pretty: bool = False, best: bool = False) -> str:
+        """
+        Return the version of the OS distribution, as a string.
+
+        For details, see :func:`distro.version`.
+        """
+        versions = [
+            self.os_release_attr("version_id"),
+            self.lsb_release_attr("release"),
+            self.distro_release_attr("version_id"),
+            self._parse_distro_release_content(self.os_release_attr("pretty_name")).get(
+                "version_id", ""
+            ),
+            self._parse_distro_release_content(
+                self.lsb_release_attr("description")
+            ).get("version_id", ""),
+            self.uname_attr("release"),
+        ]
+        if self.uname_attr("id").startswith("aix"):
+            # On AIX platforms, prefer oslevel command output.
+            versions.insert(0, self.oslevel_info())
+        elif self.id() == "debian" or "debian" in self.like().split():
+            # On Debian-like, add debian_version file content to candidates list.
+            versions.append(self._debian_version)
+        version = ""
+        if best:
+            # This algorithm uses the last version in priority order that has
+            # the best precision. If the versions are not in conflict, that
+            # does not matter; otherwise, using the last one instead of the
+            # first one might be considered a surprise.
+            for v in versions:
+                if v.count(".") > version.count(".") or version == "":
+                    version = v
+        else:
+            for v in versions:
+                if v != "":
+                    version = v
+                    break
+        if pretty and version and self.codename():
+            version = f"{version} ({self.codename()})"
+        return version
+
+    def version_parts(self, best: bool = False) -> Tuple[str, str, str]:
+        """
+        Return the version of the OS distribution, as a tuple of version
+        numbers.
+
+        For details, see :func:`distro.version_parts`.
+        """
+        version_str = self.version(best=best)
+        if version_str:
+            version_regex = re.compile(r"(\d+)\.?(\d+)?\.?(\d+)?")
+            matches = version_regex.match(version_str)
+            if matches:
+                major, minor, build_number = matches.groups()
+                return major, minor or "", build_number or ""
+        return "", "", ""
+
+    def major_version(self, best: bool = False) -> str:
+        """
+        Return the major version number of the current distribution.
+
+        For details, see :func:`distro.major_version`.
+        """
+        return self.version_parts(best)[0]
+
+    def minor_version(self, best: bool = False) -> str:
+        """
+        Return the minor version number of the current distribution.
+
+        For details, see :func:`distro.minor_version`.
+        """
+        return self.version_parts(best)[1]
+
+    def build_number(self, best: bool = False) -> str:
+        """
+        Return the build number of the current distribution.
+
+        For details, see :func:`distro.build_number`.
+        """
+        return self.version_parts(best)[2]
+
+    def like(self) -> str:
+        """
+        Return the IDs of distributions that are like the OS distribution.
+
+        For details, see :func:`distro.like`.
+        """
+        return self.os_release_attr("id_like") or ""
+
+    def codename(self) -> str:
+        """
+        Return the codename of the OS distribution.
+
+        For details, see :func:`distro.codename`.
+        """
+        try:
+            # Handle os_release specially since distros might purposefully set
+            # this to empty string to have no codename
+            return self._os_release_info["codename"]
+        except KeyError:
+            return (
+                self.lsb_release_attr("codename")
+                or self.distro_release_attr("codename")
+                or ""
+            )
+
+    def info(self, pretty: bool = False, best: bool = False) -> InfoDict:
+        """
+        Return certain machine-readable information about the OS
+        distribution.
+
+        For details, see :func:`distro.info`.
+        """
+        return dict(
+            id=self.id(),
+            version=self.version(pretty, best),
+            version_parts=dict(
+                major=self.major_version(best),
+                minor=self.minor_version(best),
+                build_number=self.build_number(best),
+            ),
+            like=self.like(),
+            codename=self.codename(),
+        )
+
+    def os_release_info(self) -> Dict[str, str]:
+        """
+        Return a dictionary containing key-value pairs for the information
+        items from the os-release file data source of the OS distribution.
+
+        For details, see :func:`distro.os_release_info`.
+        """
+        return self._os_release_info
+
+    def lsb_release_info(self) -> Dict[str, str]:
+        """
+        Return a dictionary containing key-value pairs for the information
+        items from the lsb_release command data source of the OS
+        distribution.
+
+        For details, see :func:`distro.lsb_release_info`.
+        """
+        return self._lsb_release_info
+
+    def distro_release_info(self) -> Dict[str, str]:
+        """
+        Return a dictionary containing key-value pairs for the information
+        items from the distro release file data source of the OS
+        distribution.
+
+        For details, see :func:`distro.distro_release_info`.
+        """
+        return self._distro_release_info
+
+    def uname_info(self) -> Dict[str, str]:
+        """
+        Return a dictionary containing key-value pairs for the information
+        items from the uname command data source of the OS distribution.
+
+        For details, see :func:`distro.uname_info`.
+        """
+        return self._uname_info
+
+    def oslevel_info(self) -> str:
+        """
+        Return AIX' oslevel command output.
+        """
+        return self._oslevel_info
+
+    def os_release_attr(self, attribute: str) -> str:
+        """
+        Return a single named information item from the os-release file data
+        source of the OS distribution.
+
+        For details, see :func:`distro.os_release_attr`.
+        """
+        return self._os_release_info.get(attribute, "")
+
+    def lsb_release_attr(self, attribute: str) -> str:
+        """
+        Return a single named information item from the lsb_release command
+        output data source of the OS distribution.
+
+        For details, see :func:`distro.lsb_release_attr`.
+        """
+        return self._lsb_release_info.get(attribute, "")
+
+    def distro_release_attr(self, attribute: str) -> str:
+        """
+        Return a single named information item from the distro release file
+        data source of the OS distribution.
+
+        For details, see :func:`distro.distro_release_attr`.
+        """
+        return self._distro_release_info.get(attribute, "")
+
+    def uname_attr(self, attribute: str) -> str:
+        """
+        Return a single named information item from the uname command
+        output data source of the OS distribution.
+
+        For details, see :func:`distro.uname_attr`.
+        """
+        return self._uname_info.get(attribute, "")
+
+    @cached_property
+    def _os_release_info(self) -> Dict[str, str]:
+        """
+        Get the information items from the specified os-release file.
+
+        Returns:
+            A dictionary containing all information items.
+        """
+        if os.path.isfile(self.os_release_file):
+            with open(self.os_release_file, encoding="utf-8") as release_file:
+                return self._parse_os_release_content(release_file)
+        return {}
+
+    @staticmethod
+    def _parse_os_release_content(lines: TextIO) -> Dict[str, str]:
+        """
+        Parse the lines of an os-release file.
+
+        Parameters:
+
+        * lines: Iterable through the lines in the os-release file.
+                 Each line must be a unicode string or a UTF-8 encoded byte
+                 string.
+
+        Returns:
+            A dictionary containing all information items.
+        """
+        props = {}
+        lexer = shlex.shlex(lines, posix=True)
+        lexer.whitespace_split = True
+
+        tokens = list(lexer)
+        for token in tokens:
+            # At this point, all shell-like parsing has been done (i.e.
+            # comments processed, quotes and backslash escape sequences
+            # processed, multi-line values assembled, trailing newlines
+            # stripped, etc.), so the tokens are now either:
+            # * variable assignments: var=value
+            # * commands or their arguments (not allowed in os-release)
+            # Ignore any tokens that are not variable assignments
+            if "=" in token:
+                k, v = token.split("=", 1)
+                props[k.lower()] = v
+
+        if "version" in props:
+            # extract release codename (if any) from version attribute
+            match = re.search(r"\((\D+)\)|,\s*(\D+)", props["version"])
+            if match:
+                release_codename = match.group(1) or match.group(2)
+                props["codename"] = props["release_codename"] = release_codename
+
+        if "version_codename" in props:
+            # os-release added a version_codename field.  Use that in
+            # preference to anything else Note that some distros purposefully
+            # do not have code names.  They should be setting
+            # version_codename=""
+            props["codename"] = props["version_codename"]
+        elif "ubuntu_codename" in props:
+            # Same as above but a non-standard field name used on older Ubuntus
+            props["codename"] = props["ubuntu_codename"]
+
+        return props
+
+    @cached_property
+    def _lsb_release_info(self) -> Dict[str, str]:
+        """
+        Get the information items from the lsb_release command output.
+
+        Returns:
+            A dictionary containing all information items.
+        """
+        if not self.include_lsb:
+            return {}
+        try:
+            cmd = ("lsb_release", "-a")
+            stdout = subprocess.check_output(cmd, stderr=subprocess.DEVNULL)
+        # Command not found or lsb_release returned error
+        except (OSError, subprocess.CalledProcessError):
+            return {}
+        content = self._to_str(stdout).splitlines()
+        return self._parse_lsb_release_content(content)
+
+    @staticmethod
+    def _parse_lsb_release_content(lines: Iterable[str]) -> Dict[str, str]:
+        """
+        Parse the output of the lsb_release command.
+
+        Parameters:
+
+        * lines: Iterable through the lines of the lsb_release output.
+                 Each line must be a unicode string or a UTF-8 encoded byte
+                 string.
+
+        Returns:
+            A dictionary containing all information items.
+        """
+        props = {}
+        for line in lines:
+            kv = line.strip("\n").split(":", 1)
+            if len(kv) != 2:
+                # Ignore lines without colon.
+                continue
+            k, v = kv
+            props.update({k.replace(" ", "_").lower(): v.strip()})
+        return props
+
+    @cached_property
+    def _uname_info(self) -> Dict[str, str]:
+        if not self.include_uname:
+            return {}
+        try:
+            cmd = ("uname", "-rs")
+            stdout = subprocess.check_output(cmd, stderr=subprocess.DEVNULL)
+        except OSError:
+            return {}
+        content = self._to_str(stdout).splitlines()
+        return self._parse_uname_content(content)
+
+    @cached_property
+    def _oslevel_info(self) -> str:
+        if not self.include_oslevel:
+            return ""
+        try:
+            stdout = subprocess.check_output("oslevel", stderr=subprocess.DEVNULL)
+        except (OSError, subprocess.CalledProcessError):
+            return ""
+        return self._to_str(stdout).strip()
+
+    @cached_property
+    def _debian_version(self) -> str:
+        try:
+            with open(
+                os.path.join(self.etc_dir, "debian_version"), encoding="ascii"
+            ) as fp:
+                return fp.readline().rstrip()
+        except FileNotFoundError:
+            return ""
+
+    @staticmethod
+    def _parse_uname_content(lines: Sequence[str]) -> Dict[str, str]:
+        if not lines:
+            return {}
+        props = {}
+        match = re.search(r"^([^\s]+)\s+([\d\.]+)", lines[0].strip())
+        if match:
+            name, version = match.groups()
+
+            # This is to prevent the Linux kernel version from
+            # appearing as the 'best' version on otherwise
+            # identifiable distributions.
+            if name == "Linux":
+                return {}
+            props["id"] = name.lower()
+            props["name"] = name
+            props["release"] = version
+        return props
+
+    @staticmethod
+    def _to_str(bytestring: bytes) -> str:
+        encoding = sys.getfilesystemencoding()
+        return bytestring.decode(encoding)
+
+    @cached_property
+    def _distro_release_info(self) -> Dict[str, str]:
+        """
+        Get the information items from the specified distro release file.
+
+        Returns:
+            A dictionary containing all information items.
+        """
+        if self.distro_release_file:
+            # If it was specified, we use it and parse what we can, even if
+            # its file name or content does not match the expected pattern.
+            distro_info = self._parse_distro_release_file(self.distro_release_file)
+            basename = os.path.basename(self.distro_release_file)
+            # The file name pattern for user-specified distro release files
+            # is somewhat more tolerant (compared to when searching for the
+            # file), because we want to use what was specified as best as
+            # possible.
+            match = _DISTRO_RELEASE_BASENAME_PATTERN.match(basename)
+        else:
+            try:
+                basenames = [
+                    basename
+                    for basename in os.listdir(self.etc_dir)
+                    if basename not in _DISTRO_RELEASE_IGNORE_BASENAMES
+                    and os.path.isfile(os.path.join(self.etc_dir, basename))
+                ]
+                # We sort for repeatability in cases where there are multiple
+                # distro specific files; e.g. CentOS, Oracle, Enterprise all
+                # containing `redhat-release` on top of their own.
+                basenames.sort()
+            except OSError:
+                # This may occur when /etc is not readable but we can't be
+                # sure about the *-release files. Check common entries of
+                # /etc for information. If they turn out to not be there the
+                # error is handled in `_parse_distro_release_file()`.
+                basenames = _DISTRO_RELEASE_BASENAMES
+            for basename in basenames:
+                match = _DISTRO_RELEASE_BASENAME_PATTERN.match(basename)
+                if match is None:
+                    continue
+                filepath = os.path.join(self.etc_dir, basename)
+                distro_info = self._parse_distro_release_file(filepath)
+                # The name is always present if the pattern matches.
+                if "name" not in distro_info:
+                    continue
+                self.distro_release_file = filepath
+                break
+            else:  # the loop didn't "break": no candidate.
+                return {}
+
+        if match is not None:
+            distro_info["id"] = match.group(1)
+
+        # CloudLinux < 7: manually enrich info with proper id.
+        if "cloudlinux" in distro_info.get("name", "").lower():
+            distro_info["id"] = "cloudlinux"
+
+        return distro_info
+
+    def _parse_distro_release_file(self, filepath: str) -> Dict[str, str]:
+        """
+        Parse a distro release file.
+
+        Parameters:
+
+        * filepath: Path name of the distro release file.
+
+        Returns:
+            A dictionary containing all information items.
+        """
+        try:
+            with open(filepath, encoding="utf-8") as fp:
+                # Only parse the first line. For instance, on SLES there
+                # are multiple lines. We don't want them...
+                return self._parse_distro_release_content(fp.readline())
+        except OSError:
+            # Ignore not being able to read a specific, seemingly version
+            # related file.
+            # See https://github.com/python-distro/distro/issues/162
+            return {}
+
+    @staticmethod
+    def _parse_distro_release_content(line: str) -> Dict[str, str]:
+        """
+        Parse a line from a distro release file.
+
+        Parameters:
+        * line: Line from the distro release file. Must be a unicode string
+                or a UTF-8 encoded byte string.
+
+        Returns:
+            A dictionary containing all information items.
+        """
+        matches = _DISTRO_RELEASE_CONTENT_REVERSED_PATTERN.match(line.strip()[::-1])
+        distro_info = {}
+        if matches:
+            # regexp ensures non-None
+            distro_info["name"] = matches.group(3)[::-1]
+            if matches.group(2):
+                distro_info["version_id"] = matches.group(2)[::-1]
+            if matches.group(1):
+                distro_info["codename"] = matches.group(1)[::-1]
+        elif line:
+            distro_info["name"] = line.strip()
+        return distro_info
+
+
+_distro = LinuxDistribution()
+
+
+def main() -> None:
+    logger = logging.getLogger(__name__)
+    logger.setLevel(logging.DEBUG)
+    logger.addHandler(logging.StreamHandler(sys.stdout))
+
+    parser = argparse.ArgumentParser(description="OS distro info tool")
+    parser.add_argument(
+        "--json", "-j", help="Output in machine readable format", action="store_true"
+    )
+
+    parser.add_argument(
+        "--root-dir",
+        "-r",
+        type=str,
+        dest="root_dir",
+        help="Path to the root filesystem directory (defaults to /)",
+    )
+
+    args = parser.parse_args()
+
+    if args.root_dir:
+        dist = LinuxDistribution(
+            include_lsb=False,
+            include_uname=False,
+            include_oslevel=False,
+            root_dir=args.root_dir,
+        )
+    else:
+        dist = _distro
+
+    if args.json:
+        logger.info(json.dumps(dist.info(), indent=4, sort_keys=True))
+    else:
+        logger.info("Name: %s", dist.name(pretty=True))
+        distribution_version = dist.version(pretty=True)
+        logger.info("Version: %s", distribution_version)
+        distribution_codename = dist.codename()
+        logger.info("Codename: %s", distribution_codename)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a40eeafcc914108ca79c5d83d6e81da1b29c6e80
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/__init__.py
@@ -0,0 +1,44 @@
+from .package_data import __version__
+from .core import (
+    IDNABidiError,
+    IDNAError,
+    InvalidCodepoint,
+    InvalidCodepointContext,
+    alabel,
+    check_bidi,
+    check_hyphen_ok,
+    check_initial_combiner,
+    check_label,
+    check_nfc,
+    decode,
+    encode,
+    ulabel,
+    uts46_remap,
+    valid_contextj,
+    valid_contexto,
+    valid_label_length,
+    valid_string_length,
+)
+from .intranges import intranges_contain
+
+__all__ = [
+    "IDNABidiError",
+    "IDNAError",
+    "InvalidCodepoint",
+    "InvalidCodepointContext",
+    "alabel",
+    "check_bidi",
+    "check_hyphen_ok",
+    "check_initial_combiner",
+    "check_label",
+    "check_nfc",
+    "decode",
+    "encode",
+    "intranges_contain",
+    "ulabel",
+    "uts46_remap",
+    "valid_contextj",
+    "valid_contexto",
+    "valid_label_length",
+    "valid_string_length",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/codec.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/codec.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ca9ba62c208527b796b49306f4b8c95eb868a51
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/codec.py
@@ -0,0 +1,112 @@
+from .core import encode, decode, alabel, ulabel, IDNAError
+import codecs
+import re
+from typing import Tuple, Optional
+
+_unicode_dots_re = re.compile('[\u002e\u3002\uff0e\uff61]')
+
+class Codec(codecs.Codec):
+
+    def encode(self, data: str, errors: str = 'strict') -> Tuple[bytes, int]:
+        if errors != 'strict':
+            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
+
+        if not data:
+            return b"", 0
+
+        return encode(data), len(data)
+
+    def decode(self, data: bytes, errors: str = 'strict') -> Tuple[str, int]:
+        if errors != 'strict':
+            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
+
+        if not data:
+            return '', 0
+
+        return decode(data), len(data)
+
+class IncrementalEncoder(codecs.BufferedIncrementalEncoder):
+    def _buffer_encode(self, data: str, errors: str, final: bool) -> Tuple[str, int]:  # type: ignore
+        if errors != 'strict':
+            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
+
+        if not data:
+            return "", 0
+
+        labels = _unicode_dots_re.split(data)
+        trailing_dot = ''
+        if labels:
+            if not labels[-1]:
+                trailing_dot = '.'
+                del labels[-1]
+            elif not final:
+                # Keep potentially unfinished label until the next call
+                del labels[-1]
+                if labels:
+                    trailing_dot = '.'
+
+        result = []
+        size = 0
+        for label in labels:
+            result.append(alabel(label))
+            if size:
+                size += 1
+            size += len(label)
+
+        # Join with U+002E
+        result_str = '.'.join(result) + trailing_dot  # type: ignore
+        size += len(trailing_dot)
+        return result_str, size
+
+class IncrementalDecoder(codecs.BufferedIncrementalDecoder):
+    def _buffer_decode(self, data: str, errors: str, final: bool) -> Tuple[str, int]:  # type: ignore
+        if errors != 'strict':
+            raise IDNAError('Unsupported error handling \"{}\"'.format(errors))
+
+        if not data:
+            return ('', 0)
+
+        labels = _unicode_dots_re.split(data)
+        trailing_dot = ''
+        if labels:
+            if not labels[-1]:
+                trailing_dot = '.'
+                del labels[-1]
+            elif not final:
+                # Keep potentially unfinished label until the next call
+                del labels[-1]
+                if labels:
+                    trailing_dot = '.'
+
+        result = []
+        size = 0
+        for label in labels:
+            result.append(ulabel(label))
+            if size:
+                size += 1
+            size += len(label)
+
+        result_str = '.'.join(result) + trailing_dot
+        size += len(trailing_dot)
+        return (result_str, size)
+
+
+class StreamWriter(Codec, codecs.StreamWriter):
+    pass
+
+
+class StreamReader(Codec, codecs.StreamReader):
+    pass
+
+
+def getregentry() -> codecs.CodecInfo:
+    # Compatibility as a search_function for codecs.register()
+    return codecs.CodecInfo(
+        name='idna',
+        encode=Codec().encode,  # type: ignore
+        decode=Codec().decode,  # type: ignore
+        incrementalencoder=IncrementalEncoder,
+        incrementaldecoder=IncrementalDecoder,
+        streamwriter=StreamWriter,
+        streamreader=StreamReader,
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..786e6bda63699b72d588ba91dd73df017570aee5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/compat.py
@@ -0,0 +1,13 @@
+from .core import *
+from .codec import *
+from typing import Any, Union
+
+def ToASCII(label: str) -> bytes:
+    return encode(label)
+
+def ToUnicode(label: Union[bytes, bytearray]) -> str:
+    return decode(label)
+
+def nameprep(s: Any) -> None:
+    raise NotImplementedError('IDNA 2008 does not utilise nameprep protocol')
+
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/core.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/core.py
new file mode 100644
index 0000000000000000000000000000000000000000..4f3003711020eac05ef5a19ab29ba5670d89f642
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/core.py
@@ -0,0 +1,400 @@
+from . import idnadata
+import bisect
+import unicodedata
+import re
+from typing import Union, Optional
+from .intranges import intranges_contain
+
+_virama_combining_class = 9
+_alabel_prefix = b'xn--'
+_unicode_dots_re = re.compile('[\u002e\u3002\uff0e\uff61]')
+
+class IDNAError(UnicodeError):
+    """ Base exception for all IDNA-encoding related problems """
+    pass
+
+
+class IDNABidiError(IDNAError):
+    """ Exception when bidirectional requirements are not satisfied """
+    pass
+
+
+class InvalidCodepoint(IDNAError):
+    """ Exception when a disallowed or unallocated codepoint is used """
+    pass
+
+
+class InvalidCodepointContext(IDNAError):
+    """ Exception when the codepoint is not valid in the context it is used """
+    pass
+
+
+def _combining_class(cp: int) -> int:
+    v = unicodedata.combining(chr(cp))
+    if v == 0:
+        if not unicodedata.name(chr(cp)):
+            raise ValueError('Unknown character in unicodedata')
+    return v
+
+def _is_script(cp: str, script: str) -> bool:
+    return intranges_contain(ord(cp), idnadata.scripts[script])
+
+def _punycode(s: str) -> bytes:
+    return s.encode('punycode')
+
+def _unot(s: int) -> str:
+    return 'U+{:04X}'.format(s)
+
+
+def valid_label_length(label: Union[bytes, str]) -> bool:
+    if len(label) > 63:
+        return False
+    return True
+
+
+def valid_string_length(label: Union[bytes, str], trailing_dot: bool) -> bool:
+    if len(label) > (254 if trailing_dot else 253):
+        return False
+    return True
+
+
+def check_bidi(label: str, check_ltr: bool = False) -> bool:
+    # Bidi rules should only be applied if string contains RTL characters
+    bidi_label = False
+    for (idx, cp) in enumerate(label, 1):
+        direction = unicodedata.bidirectional(cp)
+        if direction == '':
+            # String likely comes from a newer version of Unicode
+            raise IDNABidiError('Unknown directionality in label {} at position {}'.format(repr(label), idx))
+        if direction in ['R', 'AL', 'AN']:
+            bidi_label = True
+    if not bidi_label and not check_ltr:
+        return True
+
+    # Bidi rule 1
+    direction = unicodedata.bidirectional(label[0])
+    if direction in ['R', 'AL']:
+        rtl = True
+    elif direction == 'L':
+        rtl = False
+    else:
+        raise IDNABidiError('First codepoint in label {} must be directionality L, R or AL'.format(repr(label)))
+
+    valid_ending = False
+    number_type = None  # type: Optional[str]
+    for (idx, cp) in enumerate(label, 1):
+        direction = unicodedata.bidirectional(cp)
+
+        if rtl:
+            # Bidi rule 2
+            if not direction in ['R', 'AL', 'AN', 'EN', 'ES', 'CS', 'ET', 'ON', 'BN', 'NSM']:
+                raise IDNABidiError('Invalid direction for codepoint at position {} in a right-to-left label'.format(idx))
+            # Bidi rule 3
+            if direction in ['R', 'AL', 'EN', 'AN']:
+                valid_ending = True
+            elif direction != 'NSM':
+                valid_ending = False
+            # Bidi rule 4
+            if direction in ['AN', 'EN']:
+                if not number_type:
+                    number_type = direction
+                else:
+                    if number_type != direction:
+                        raise IDNABidiError('Can not mix numeral types in a right-to-left label')
+        else:
+            # Bidi rule 5
+            if not direction in ['L', 'EN', 'ES', 'CS', 'ET', 'ON', 'BN', 'NSM']:
+                raise IDNABidiError('Invalid direction for codepoint at position {} in a left-to-right label'.format(idx))
+            # Bidi rule 6
+            if direction in ['L', 'EN']:
+                valid_ending = True
+            elif direction != 'NSM':
+                valid_ending = False
+
+    if not valid_ending:
+        raise IDNABidiError('Label ends with illegal codepoint directionality')
+
+    return True
+
+
+def check_initial_combiner(label: str) -> bool:
+    if unicodedata.category(label[0])[0] == 'M':
+        raise IDNAError('Label begins with an illegal combining character')
+    return True
+
+
+def check_hyphen_ok(label: str) -> bool:
+    if label[2:4] == '--':
+        raise IDNAError('Label has disallowed hyphens in 3rd and 4th position')
+    if label[0] == '-' or label[-1] == '-':
+        raise IDNAError('Label must not start or end with a hyphen')
+    return True
+
+
+def check_nfc(label: str) -> None:
+    if unicodedata.normalize('NFC', label) != label:
+        raise IDNAError('Label must be in Normalization Form C')
+
+
+def valid_contextj(label: str, pos: int) -> bool:
+    cp_value = ord(label[pos])
+
+    if cp_value == 0x200c:
+
+        if pos > 0:
+            if _combining_class(ord(label[pos - 1])) == _virama_combining_class:
+                return True
+
+        ok = False
+        for i in range(pos-1, -1, -1):
+            joining_type = idnadata.joining_types.get(ord(label[i]))
+            if joining_type == ord('T'):
+                continue
+            if joining_type in [ord('L'), ord('D')]:
+                ok = True
+                break
+
+        if not ok:
+            return False
+
+        ok = False
+        for i in range(pos+1, len(label)):
+            joining_type = idnadata.joining_types.get(ord(label[i]))
+            if joining_type == ord('T'):
+                continue
+            if joining_type in [ord('R'), ord('D')]:
+                ok = True
+                break
+        return ok
+
+    if cp_value == 0x200d:
+
+        if pos > 0:
+            if _combining_class(ord(label[pos - 1])) == _virama_combining_class:
+                return True
+        return False
+
+    else:
+
+        return False
+
+
+def valid_contexto(label: str, pos: int, exception: bool = False) -> bool:
+    cp_value = ord(label[pos])
+
+    if cp_value == 0x00b7:
+        if 0 < pos < len(label)-1:
+            if ord(label[pos - 1]) == 0x006c and ord(label[pos + 1]) == 0x006c:
+                return True
+        return False
+
+    elif cp_value == 0x0375:
+        if pos < len(label)-1 and len(label) > 1:
+            return _is_script(label[pos + 1], 'Greek')
+        return False
+
+    elif cp_value == 0x05f3 or cp_value == 0x05f4:
+        if pos > 0:
+            return _is_script(label[pos - 1], 'Hebrew')
+        return False
+
+    elif cp_value == 0x30fb:
+        for cp in label:
+            if cp == '\u30fb':
+                continue
+            if _is_script(cp, 'Hiragana') or _is_script(cp, 'Katakana') or _is_script(cp, 'Han'):
+                return True
+        return False
+
+    elif 0x660 <= cp_value <= 0x669:
+        for cp in label:
+            if 0x6f0 <= ord(cp) <= 0x06f9:
+                return False
+        return True
+
+    elif 0x6f0 <= cp_value <= 0x6f9:
+        for cp in label:
+            if 0x660 <= ord(cp) <= 0x0669:
+                return False
+        return True
+
+    return False
+
+
+def check_label(label: Union[str, bytes, bytearray]) -> None:
+    if isinstance(label, (bytes, bytearray)):
+        label = label.decode('utf-8')
+    if len(label) == 0:
+        raise IDNAError('Empty Label')
+
+    check_nfc(label)
+    check_hyphen_ok(label)
+    check_initial_combiner(label)
+
+    for (pos, cp) in enumerate(label):
+        cp_value = ord(cp)
+        if intranges_contain(cp_value, idnadata.codepoint_classes['PVALID']):
+            continue
+        elif intranges_contain(cp_value, idnadata.codepoint_classes['CONTEXTJ']):
+            try:
+                if not valid_contextj(label, pos):
+                    raise InvalidCodepointContext('Joiner {} not allowed at position {} in {}'.format(
+                        _unot(cp_value), pos+1, repr(label)))
+            except ValueError:
+                raise IDNAError('Unknown codepoint adjacent to joiner {} at position {} in {}'.format(
+                    _unot(cp_value), pos+1, repr(label)))
+        elif intranges_contain(cp_value, idnadata.codepoint_classes['CONTEXTO']):
+            if not valid_contexto(label, pos):
+                raise InvalidCodepointContext('Codepoint {} not allowed at position {} in {}'.format(_unot(cp_value), pos+1, repr(label)))
+        else:
+            raise InvalidCodepoint('Codepoint {} at position {} of {} not allowed'.format(_unot(cp_value), pos+1, repr(label)))
+
+    check_bidi(label)
+
+
+def alabel(label: str) -> bytes:
+    try:
+        label_bytes = label.encode('ascii')
+        ulabel(label_bytes)
+        if not valid_label_length(label_bytes):
+            raise IDNAError('Label too long')
+        return label_bytes
+    except UnicodeEncodeError:
+        pass
+
+    if not label:
+        raise IDNAError('No Input')
+
+    label = str(label)
+    check_label(label)
+    label_bytes = _punycode(label)
+    label_bytes = _alabel_prefix + label_bytes
+
+    if not valid_label_length(label_bytes):
+        raise IDNAError('Label too long')
+
+    return label_bytes
+
+
+def ulabel(label: Union[str, bytes, bytearray]) -> str:
+    if not isinstance(label, (bytes, bytearray)):
+        try:
+            label_bytes = label.encode('ascii')
+        except UnicodeEncodeError:
+            check_label(label)
+            return label
+    else:
+        label_bytes = label
+
+    label_bytes = label_bytes.lower()
+    if label_bytes.startswith(_alabel_prefix):
+        label_bytes = label_bytes[len(_alabel_prefix):]
+        if not label_bytes:
+            raise IDNAError('Malformed A-label, no Punycode eligible content found')
+        if label_bytes.decode('ascii')[-1] == '-':
+            raise IDNAError('A-label must not end with a hyphen')
+    else:
+        check_label(label_bytes)
+        return label_bytes.decode('ascii')
+
+    try:
+        label = label_bytes.decode('punycode')
+    except UnicodeError:
+        raise IDNAError('Invalid A-label')
+    check_label(label)
+    return label
+
+
+def uts46_remap(domain: str, std3_rules: bool = True, transitional: bool = False) -> str:
+    """Re-map the characters in the string according to UTS46 processing."""
+    from .uts46data import uts46data
+    output = ''
+
+    for pos, char in enumerate(domain):
+        code_point = ord(char)
+        try:
+            uts46row = uts46data[code_point if code_point < 256 else
+                bisect.bisect_left(uts46data, (code_point, 'Z')) - 1]
+            status = uts46row[1]
+            replacement = None  # type: Optional[str]
+            if len(uts46row) == 3:
+                replacement = uts46row[2]  # type: ignore
+            if (status == 'V' or
+                    (status == 'D' and not transitional) or
+                    (status == '3' and not std3_rules and replacement is None)):
+                output += char
+            elif replacement is not None and (status == 'M' or
+                    (status == '3' and not std3_rules) or
+                    (status == 'D' and transitional)):
+                output += replacement
+            elif status != 'I':
+                raise IndexError()
+        except IndexError:
+            raise InvalidCodepoint(
+                'Codepoint {} not allowed at position {} in {}'.format(
+                _unot(code_point), pos + 1, repr(domain)))
+
+    return unicodedata.normalize('NFC', output)
+
+
+def encode(s: Union[str, bytes, bytearray], strict: bool = False, uts46: bool = False, std3_rules: bool = False, transitional: bool = False) -> bytes:
+    if isinstance(s, (bytes, bytearray)):
+        try:
+            s = s.decode('ascii')
+        except UnicodeDecodeError:
+            raise IDNAError('should pass a unicode string to the function rather than a byte string.')
+    if uts46:
+        s = uts46_remap(s, std3_rules, transitional)
+    trailing_dot = False
+    result = []
+    if strict:
+        labels = s.split('.')
+    else:
+        labels = _unicode_dots_re.split(s)
+    if not labels or labels == ['']:
+        raise IDNAError('Empty domain')
+    if labels[-1] == '':
+        del labels[-1]
+        trailing_dot = True
+    for label in labels:
+        s = alabel(label)
+        if s:
+            result.append(s)
+        else:
+            raise IDNAError('Empty label')
+    if trailing_dot:
+        result.append(b'')
+    s = b'.'.join(result)
+    if not valid_string_length(s, trailing_dot):
+        raise IDNAError('Domain too long')
+    return s
+
+
+def decode(s: Union[str, bytes, bytearray], strict: bool = False, uts46: bool = False, std3_rules: bool = False) -> str:
+    try:
+        if isinstance(s, (bytes, bytearray)):
+            s = s.decode('ascii')
+    except UnicodeDecodeError:
+        raise IDNAError('Invalid ASCII in A-label')
+    if uts46:
+        s = uts46_remap(s, std3_rules, False)
+    trailing_dot = False
+    result = []
+    if not strict:
+        labels = _unicode_dots_re.split(s)
+    else:
+        labels = s.split('.')
+    if not labels or labels == ['']:
+        raise IDNAError('Empty domain')
+    if not labels[-1]:
+        del labels[-1]
+        trailing_dot = True
+    for label in labels:
+        s = ulabel(label)
+        if s:
+            result.append(s)
+        else:
+            raise IDNAError('Empty label')
+    if trailing_dot:
+        result.append('')
+    return '.'.join(result)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/idnadata.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/idnadata.py
new file mode 100644
index 0000000000000000000000000000000000000000..67db4625829680298b2a5a9032a379d870a00700
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/idnadata.py
@@ -0,0 +1,2151 @@
+# This file is automatically generated by tools/idna-data
+
+__version__ = '15.0.0'
+scripts = {
+    'Greek': (
+        0x37000000374,
+        0x37500000378,
+        0x37a0000037e,
+        0x37f00000380,
+        0x38400000385,
+        0x38600000387,
+        0x3880000038b,
+        0x38c0000038d,
+        0x38e000003a2,
+        0x3a3000003e2,
+        0x3f000000400,
+        0x1d2600001d2b,
+        0x1d5d00001d62,
+        0x1d6600001d6b,
+        0x1dbf00001dc0,
+        0x1f0000001f16,
+        0x1f1800001f1e,
+        0x1f2000001f46,
+        0x1f4800001f4e,
+        0x1f5000001f58,
+        0x1f5900001f5a,
+        0x1f5b00001f5c,
+        0x1f5d00001f5e,
+        0x1f5f00001f7e,
+        0x1f8000001fb5,
+        0x1fb600001fc5,
+        0x1fc600001fd4,
+        0x1fd600001fdc,
+        0x1fdd00001ff0,
+        0x1ff200001ff5,
+        0x1ff600001fff,
+        0x212600002127,
+        0xab650000ab66,
+        0x101400001018f,
+        0x101a0000101a1,
+        0x1d2000001d246,
+    ),
+    'Han': (
+        0x2e8000002e9a,
+        0x2e9b00002ef4,
+        0x2f0000002fd6,
+        0x300500003006,
+        0x300700003008,
+        0x30210000302a,
+        0x30380000303c,
+        0x340000004dc0,
+        0x4e000000a000,
+        0xf9000000fa6e,
+        0xfa700000fada,
+        0x16fe200016fe4,
+        0x16ff000016ff2,
+        0x200000002a6e0,
+        0x2a7000002b73a,
+        0x2b7400002b81e,
+        0x2b8200002cea2,
+        0x2ceb00002ebe1,
+        0x2f8000002fa1e,
+        0x300000003134b,
+        0x31350000323b0,
+    ),
+    'Hebrew': (
+        0x591000005c8,
+        0x5d0000005eb,
+        0x5ef000005f5,
+        0xfb1d0000fb37,
+        0xfb380000fb3d,
+        0xfb3e0000fb3f,
+        0xfb400000fb42,
+        0xfb430000fb45,
+        0xfb460000fb50,
+    ),
+    'Hiragana': (
+        0x304100003097,
+        0x309d000030a0,
+        0x1b0010001b120,
+        0x1b1320001b133,
+        0x1b1500001b153,
+        0x1f2000001f201,
+    ),
+    'Katakana': (
+        0x30a1000030fb,
+        0x30fd00003100,
+        0x31f000003200,
+        0x32d0000032ff,
+        0x330000003358,
+        0xff660000ff70,
+        0xff710000ff9e,
+        0x1aff00001aff4,
+        0x1aff50001affc,
+        0x1affd0001afff,
+        0x1b0000001b001,
+        0x1b1200001b123,
+        0x1b1550001b156,
+        0x1b1640001b168,
+    ),
+}
+joining_types = {
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+    0x601: 85,
+    0x602: 85,
+    0x603: 85,
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+    0x625: 82,
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+    0x62f: 82,
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+    0x10bad: 68,
+    0x10bae: 68,
+    0x10baf: 85,
+    0x10d00: 76,
+    0x10d01: 68,
+    0x10d02: 68,
+    0x10d03: 68,
+    0x10d04: 68,
+    0x10d05: 68,
+    0x10d06: 68,
+    0x10d07: 68,
+    0x10d08: 68,
+    0x10d09: 68,
+    0x10d0a: 68,
+    0x10d0b: 68,
+    0x10d0c: 68,
+    0x10d0d: 68,
+    0x10d0e: 68,
+    0x10d0f: 68,
+    0x10d10: 68,
+    0x10d11: 68,
+    0x10d12: 68,
+    0x10d13: 68,
+    0x10d14: 68,
+    0x10d15: 68,
+    0x10d16: 68,
+    0x10d17: 68,
+    0x10d18: 68,
+    0x10d19: 68,
+    0x10d1a: 68,
+    0x10d1b: 68,
+    0x10d1c: 68,
+    0x10d1d: 68,
+    0x10d1e: 68,
+    0x10d1f: 68,
+    0x10d20: 68,
+    0x10d21: 68,
+    0x10d22: 82,
+    0x10d23: 68,
+    0x10f30: 68,
+    0x10f31: 68,
+    0x10f32: 68,
+    0x10f33: 82,
+    0x10f34: 68,
+    0x10f35: 68,
+    0x10f36: 68,
+    0x10f37: 68,
+    0x10f38: 68,
+    0x10f39: 68,
+    0x10f3a: 68,
+    0x10f3b: 68,
+    0x10f3c: 68,
+    0x10f3d: 68,
+    0x10f3e: 68,
+    0x10f3f: 68,
+    0x10f40: 68,
+    0x10f41: 68,
+    0x10f42: 68,
+    0x10f43: 68,
+    0x10f44: 68,
+    0x10f45: 85,
+    0x10f51: 68,
+    0x10f52: 68,
+    0x10f53: 68,
+    0x10f54: 82,
+    0x10f70: 68,
+    0x10f71: 68,
+    0x10f72: 68,
+    0x10f73: 68,
+    0x10f74: 82,
+    0x10f75: 82,
+    0x10f76: 68,
+    0x10f77: 68,
+    0x10f78: 68,
+    0x10f79: 68,
+    0x10f7a: 68,
+    0x10f7b: 68,
+    0x10f7c: 68,
+    0x10f7d: 68,
+    0x10f7e: 68,
+    0x10f7f: 68,
+    0x10f80: 68,
+    0x10f81: 68,
+    0x10fb0: 68,
+    0x10fb1: 85,
+    0x10fb2: 68,
+    0x10fb3: 68,
+    0x10fb4: 82,
+    0x10fb5: 82,
+    0x10fb6: 82,
+    0x10fb7: 85,
+    0x10fb8: 68,
+    0x10fb9: 82,
+    0x10fba: 82,
+    0x10fbb: 68,
+    0x10fbc: 68,
+    0x10fbd: 82,
+    0x10fbe: 68,
+    0x10fbf: 68,
+    0x10fc0: 85,
+    0x10fc1: 68,
+    0x10fc2: 82,
+    0x10fc3: 82,
+    0x10fc4: 68,
+    0x10fc5: 85,
+    0x10fc6: 85,
+    0x10fc7: 85,
+    0x10fc8: 85,
+    0x10fc9: 82,
+    0x10fca: 68,
+    0x10fcb: 76,
+    0x110bd: 85,
+    0x110cd: 85,
+    0x1e900: 68,
+    0x1e901: 68,
+    0x1e902: 68,
+    0x1e903: 68,
+    0x1e904: 68,
+    0x1e905: 68,
+    0x1e906: 68,
+    0x1e907: 68,
+    0x1e908: 68,
+    0x1e909: 68,
+    0x1e90a: 68,
+    0x1e90b: 68,
+    0x1e90c: 68,
+    0x1e90d: 68,
+    0x1e90e: 68,
+    0x1e90f: 68,
+    0x1e910: 68,
+    0x1e911: 68,
+    0x1e912: 68,
+    0x1e913: 68,
+    0x1e914: 68,
+    0x1e915: 68,
+    0x1e916: 68,
+    0x1e917: 68,
+    0x1e918: 68,
+    0x1e919: 68,
+    0x1e91a: 68,
+    0x1e91b: 68,
+    0x1e91c: 68,
+    0x1e91d: 68,
+    0x1e91e: 68,
+    0x1e91f: 68,
+    0x1e920: 68,
+    0x1e921: 68,
+    0x1e922: 68,
+    0x1e923: 68,
+    0x1e924: 68,
+    0x1e925: 68,
+    0x1e926: 68,
+    0x1e927: 68,
+    0x1e928: 68,
+    0x1e929: 68,
+    0x1e92a: 68,
+    0x1e92b: 68,
+    0x1e92c: 68,
+    0x1e92d: 68,
+    0x1e92e: 68,
+    0x1e92f: 68,
+    0x1e930: 68,
+    0x1e931: 68,
+    0x1e932: 68,
+    0x1e933: 68,
+    0x1e934: 68,
+    0x1e935: 68,
+    0x1e936: 68,
+    0x1e937: 68,
+    0x1e938: 68,
+    0x1e939: 68,
+    0x1e93a: 68,
+    0x1e93b: 68,
+    0x1e93c: 68,
+    0x1e93d: 68,
+    0x1e93e: 68,
+    0x1e93f: 68,
+    0x1e940: 68,
+    0x1e941: 68,
+    0x1e942: 68,
+    0x1e943: 68,
+    0x1e94b: 84,
+}
+codepoint_classes = {
+    'PVALID': (
+        0x2d0000002e,
+        0x300000003a,
+        0x610000007b,
+        0xdf000000f7,
+        0xf800000100,
+        0x10100000102,
+        0x10300000104,
+        0x10500000106,
+        0x10700000108,
+        0x1090000010a,
+        0x10b0000010c,
+        0x10d0000010e,
+        0x10f00000110,
+        0x11100000112,
+        0x11300000114,
+        0x11500000116,
+        0x11700000118,
+        0x1190000011a,
+        0x11b0000011c,
+        0x11d0000011e,
+        0x11f00000120,
+        0x12100000122,
+        0x12300000124,
+        0x12500000126,
+        0x12700000128,
+        0x1290000012a,
+        0x12b0000012c,
+        0x12d0000012e,
+        0x12f00000130,
+        0x13100000132,
+        0x13500000136,
+        0x13700000139,
+        0x13a0000013b,
+        0x13c0000013d,
+        0x13e0000013f,
+        0x14200000143,
+        0x14400000145,
+        0x14600000147,
+        0x14800000149,
+        0x14b0000014c,
+        0x14d0000014e,
+        0x14f00000150,
+        0x15100000152,
+        0x15300000154,
+        0x15500000156,
+        0x15700000158,
+        0x1590000015a,
+        0x15b0000015c,
+        0x15d0000015e,
+        0x15f00000160,
+        0x16100000162,
+        0x16300000164,
+        0x16500000166,
+        0x16700000168,
+        0x1690000016a,
+        0x16b0000016c,
+        0x16d0000016e,
+        0x16f00000170,
+        0x17100000172,
+        0x17300000174,
+        0x17500000176,
+        0x17700000178,
+        0x17a0000017b,
+        0x17c0000017d,
+        0x17e0000017f,
+        0x18000000181,
+        0x18300000184,
+        0x18500000186,
+        0x18800000189,
+        0x18c0000018e,
+        0x19200000193,
+        0x19500000196,
+        0x1990000019c,
+        0x19e0000019f,
+        0x1a1000001a2,
+        0x1a3000001a4,
+        0x1a5000001a6,
+        0x1a8000001a9,
+        0x1aa000001ac,
+        0x1ad000001ae,
+        0x1b0000001b1,
+        0x1b4000001b5,
+        0x1b6000001b7,
+        0x1b9000001bc,
+        0x1bd000001c4,
+        0x1ce000001cf,
+        0x1d0000001d1,
+        0x1d2000001d3,
+        0x1d4000001d5,
+        0x1d6000001d7,
+        0x1d8000001d9,
+        0x1da000001db,
+        0x1dc000001de,
+        0x1df000001e0,
+        0x1e1000001e2,
+        0x1e3000001e4,
+        0x1e5000001e6,
+        0x1e7000001e8,
+        0x1e9000001ea,
+        0x1eb000001ec,
+        0x1ed000001ee,
+        0x1ef000001f1,
+        0x1f5000001f6,
+        0x1f9000001fa,
+        0x1fb000001fc,
+        0x1fd000001fe,
+        0x1ff00000200,
+        0x20100000202,
+        0x20300000204,
+        0x20500000206,
+        0x20700000208,
+        0x2090000020a,
+        0x20b0000020c,
+        0x20d0000020e,
+        0x20f00000210,
+        0x21100000212,
+        0x21300000214,
+        0x21500000216,
+        0x21700000218,
+        0x2190000021a,
+        0x21b0000021c,
+        0x21d0000021e,
+        0x21f00000220,
+        0x22100000222,
+        0x22300000224,
+        0x22500000226,
+        0x22700000228,
+        0x2290000022a,
+        0x22b0000022c,
+        0x22d0000022e,
+        0x22f00000230,
+        0x23100000232,
+        0x2330000023a,
+        0x23c0000023d,
+        0x23f00000241,
+        0x24200000243,
+        0x24700000248,
+        0x2490000024a,
+        0x24b0000024c,
+        0x24d0000024e,
+        0x24f000002b0,
+        0x2b9000002c2,
+        0x2c6000002d2,
+        0x2ec000002ed,
+        0x2ee000002ef,
+        0x30000000340,
+        0x34200000343,
+        0x3460000034f,
+        0x35000000370,
+        0x37100000372,
+        0x37300000374,
+        0x37700000378,
+        0x37b0000037e,
+        0x39000000391,
+        0x3ac000003cf,
+        0x3d7000003d8,
+        0x3d9000003da,
+        0x3db000003dc,
+        0x3dd000003de,
+        0x3df000003e0,
+        0x3e1000003e2,
+        0x3e3000003e4,
+        0x3e5000003e6,
+        0x3e7000003e8,
+        0x3e9000003ea,
+        0x3eb000003ec,
+        0x3ed000003ee,
+        0x3ef000003f0,
+        0x3f3000003f4,
+        0x3f8000003f9,
+        0x3fb000003fd,
+        0x43000000460,
+        0x46100000462,
+        0x46300000464,
+        0x46500000466,
+        0x46700000468,
+        0x4690000046a,
+        0x46b0000046c,
+        0x46d0000046e,
+        0x46f00000470,
+        0x47100000472,
+        0x47300000474,
+        0x47500000476,
+        0x47700000478,
+        0x4790000047a,
+        0x47b0000047c,
+        0x47d0000047e,
+        0x47f00000480,
+        0x48100000482,
+        0x48300000488,
+        0x48b0000048c,
+        0x48d0000048e,
+        0x48f00000490,
+        0x49100000492,
+        0x49300000494,
+        0x49500000496,
+        0x49700000498,
+        0x4990000049a,
+        0x49b0000049c,
+        0x49d0000049e,
+        0x49f000004a0,
+        0x4a1000004a2,
+        0x4a3000004a4,
+        0x4a5000004a6,
+        0x4a7000004a8,
+        0x4a9000004aa,
+        0x4ab000004ac,
+        0x4ad000004ae,
+        0x4af000004b0,
+        0x4b1000004b2,
+        0x4b3000004b4,
+        0x4b5000004b6,
+        0x4b7000004b8,
+        0x4b9000004ba,
+        0x4bb000004bc,
+        0x4bd000004be,
+        0x4bf000004c0,
+        0x4c2000004c3,
+        0x4c4000004c5,
+        0x4c6000004c7,
+        0x4c8000004c9,
+        0x4ca000004cb,
+        0x4cc000004cd,
+        0x4ce000004d0,
+        0x4d1000004d2,
+        0x4d3000004d4,
+        0x4d5000004d6,
+        0x4d7000004d8,
+        0x4d9000004da,
+        0x4db000004dc,
+        0x4dd000004de,
+        0x4df000004e0,
+        0x4e1000004e2,
+        0x4e3000004e4,
+        0x4e5000004e6,
+        0x4e7000004e8,
+        0x4e9000004ea,
+        0x4eb000004ec,
+        0x4ed000004ee,
+        0x4ef000004f0,
+        0x4f1000004f2,
+        0x4f3000004f4,
+        0x4f5000004f6,
+        0x4f7000004f8,
+        0x4f9000004fa,
+        0x4fb000004fc,
+        0x4fd000004fe,
+        0x4ff00000500,
+        0x50100000502,
+        0x50300000504,
+        0x50500000506,
+        0x50700000508,
+        0x5090000050a,
+        0x50b0000050c,
+        0x50d0000050e,
+        0x50f00000510,
+        0x51100000512,
+        0x51300000514,
+        0x51500000516,
+        0x51700000518,
+        0x5190000051a,
+        0x51b0000051c,
+        0x51d0000051e,
+        0x51f00000520,
+        0x52100000522,
+        0x52300000524,
+        0x52500000526,
+        0x52700000528,
+        0x5290000052a,
+        0x52b0000052c,
+        0x52d0000052e,
+        0x52f00000530,
+        0x5590000055a,
+        0x56000000587,
+        0x58800000589,
+        0x591000005be,
+        0x5bf000005c0,
+        0x5c1000005c3,
+        0x5c4000005c6,
+        0x5c7000005c8,
+        0x5d0000005eb,
+        0x5ef000005f3,
+        0x6100000061b,
+        0x62000000640,
+        0x64100000660,
+        0x66e00000675,
+        0x679000006d4,
+        0x6d5000006dd,
+        0x6df000006e9,
+        0x6ea000006f0,
+        0x6fa00000700,
+        0x7100000074b,
+        0x74d000007b2,
+        0x7c0000007f6,
+        0x7fd000007fe,
+        0x8000000082e,
+        0x8400000085c,
+        0x8600000086b,
+        0x87000000888,
+        0x8890000088f,
+        0x898000008e2,
+        0x8e300000958,
+        0x96000000964,
+        0x96600000970,
+        0x97100000984,
+        0x9850000098d,
+        0x98f00000991,
+        0x993000009a9,
+        0x9aa000009b1,
+        0x9b2000009b3,
+        0x9b6000009ba,
+        0x9bc000009c5,
+        0x9c7000009c9,
+        0x9cb000009cf,
+        0x9d7000009d8,
+        0x9e0000009e4,
+        0x9e6000009f2,
+        0x9fc000009fd,
+        0x9fe000009ff,
+        0xa0100000a04,
+        0xa0500000a0b,
+        0xa0f00000a11,
+        0xa1300000a29,
+        0xa2a00000a31,
+        0xa3200000a33,
+        0xa3500000a36,
+        0xa3800000a3a,
+        0xa3c00000a3d,
+        0xa3e00000a43,
+        0xa4700000a49,
+        0xa4b00000a4e,
+        0xa5100000a52,
+        0xa5c00000a5d,
+        0xa6600000a76,
+        0xa8100000a84,
+        0xa8500000a8e,
+        0xa8f00000a92,
+        0xa9300000aa9,
+        0xaaa00000ab1,
+        0xab200000ab4,
+        0xab500000aba,
+        0xabc00000ac6,
+        0xac700000aca,
+        0xacb00000ace,
+        0xad000000ad1,
+        0xae000000ae4,
+        0xae600000af0,
+        0xaf900000b00,
+        0xb0100000b04,
+        0xb0500000b0d,
+        0xb0f00000b11,
+        0xb1300000b29,
+        0xb2a00000b31,
+        0xb3200000b34,
+        0xb3500000b3a,
+        0xb3c00000b45,
+        0xb4700000b49,
+        0xb4b00000b4e,
+        0xb5500000b58,
+        0xb5f00000b64,
+        0xb6600000b70,
+        0xb7100000b72,
+        0xb8200000b84,
+        0xb8500000b8b,
+        0xb8e00000b91,
+        0xb9200000b96,
+        0xb9900000b9b,
+        0xb9c00000b9d,
+        0xb9e00000ba0,
+        0xba300000ba5,
+        0xba800000bab,
+        0xbae00000bba,
+        0xbbe00000bc3,
+        0xbc600000bc9,
+        0xbca00000bce,
+        0xbd000000bd1,
+        0xbd700000bd8,
+        0xbe600000bf0,
+        0xc0000000c0d,
+        0xc0e00000c11,
+        0xc1200000c29,
+        0xc2a00000c3a,
+        0xc3c00000c45,
+        0xc4600000c49,
+        0xc4a00000c4e,
+        0xc5500000c57,
+        0xc5800000c5b,
+        0xc5d00000c5e,
+        0xc6000000c64,
+        0xc6600000c70,
+        0xc8000000c84,
+        0xc8500000c8d,
+        0xc8e00000c91,
+        0xc9200000ca9,
+        0xcaa00000cb4,
+        0xcb500000cba,
+        0xcbc00000cc5,
+        0xcc600000cc9,
+        0xcca00000cce,
+        0xcd500000cd7,
+        0xcdd00000cdf,
+        0xce000000ce4,
+        0xce600000cf0,
+        0xcf100000cf4,
+        0xd0000000d0d,
+        0xd0e00000d11,
+        0xd1200000d45,
+        0xd4600000d49,
+        0xd4a00000d4f,
+        0xd5400000d58,
+        0xd5f00000d64,
+        0xd6600000d70,
+        0xd7a00000d80,
+        0xd8100000d84,
+        0xd8500000d97,
+        0xd9a00000db2,
+        0xdb300000dbc,
+        0xdbd00000dbe,
+        0xdc000000dc7,
+        0xdca00000dcb,
+        0xdcf00000dd5,
+        0xdd600000dd7,
+        0xdd800000de0,
+        0xde600000df0,
+        0xdf200000df4,
+        0xe0100000e33,
+        0xe3400000e3b,
+        0xe4000000e4f,
+        0xe5000000e5a,
+        0xe8100000e83,
+        0xe8400000e85,
+        0xe8600000e8b,
+        0xe8c00000ea4,
+        0xea500000ea6,
+        0xea700000eb3,
+        0xeb400000ebe,
+        0xec000000ec5,
+        0xec600000ec7,
+        0xec800000ecf,
+        0xed000000eda,
+        0xede00000ee0,
+        0xf0000000f01,
+        0xf0b00000f0c,
+        0xf1800000f1a,
+        0xf2000000f2a,
+        0xf3500000f36,
+        0xf3700000f38,
+        0xf3900000f3a,
+        0xf3e00000f43,
+        0xf4400000f48,
+        0xf4900000f4d,
+        0xf4e00000f52,
+        0xf5300000f57,
+        0xf5800000f5c,
+        0xf5d00000f69,
+        0xf6a00000f6d,
+        0xf7100000f73,
+        0xf7400000f75,
+        0xf7a00000f81,
+        0xf8200000f85,
+        0xf8600000f93,
+        0xf9400000f98,
+        0xf9900000f9d,
+        0xf9e00000fa2,
+        0xfa300000fa7,
+        0xfa800000fac,
+        0xfad00000fb9,
+        0xfba00000fbd,
+        0xfc600000fc7,
+        0x10000000104a,
+        0x10500000109e,
+        0x10d0000010fb,
+        0x10fd00001100,
+        0x120000001249,
+        0x124a0000124e,
+        0x125000001257,
+        0x125800001259,
+        0x125a0000125e,
+        0x126000001289,
+        0x128a0000128e,
+        0x1290000012b1,
+        0x12b2000012b6,
+        0x12b8000012bf,
+        0x12c0000012c1,
+        0x12c2000012c6,
+        0x12c8000012d7,
+        0x12d800001311,
+        0x131200001316,
+        0x13180000135b,
+        0x135d00001360,
+        0x138000001390,
+        0x13a0000013f6,
+        0x14010000166d,
+        0x166f00001680,
+        0x16810000169b,
+        0x16a0000016eb,
+        0x16f1000016f9,
+        0x170000001716,
+        0x171f00001735,
+        0x174000001754,
+        0x17600000176d,
+        0x176e00001771,
+        0x177200001774,
+        0x1780000017b4,
+        0x17b6000017d4,
+        0x17d7000017d8,
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diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/intranges.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/intranges.py
new file mode 100644
index 0000000000000000000000000000000000000000..6a43b0475347cb50d0d65ada1000a82eeca9e882
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/intranges.py
@@ -0,0 +1,54 @@
+"""
+Given a list of integers, made up of (hopefully) a small number of long runs
+of consecutive integers, compute a representation of the form
+((start1, end1), (start2, end2) ...). Then answer the question "was x present
+in the original list?" in time O(log(# runs)).
+"""
+
+import bisect
+from typing import List, Tuple
+
+def intranges_from_list(list_: List[int]) -> Tuple[int, ...]:
+    """Represent a list of integers as a sequence of ranges:
+    ((start_0, end_0), (start_1, end_1), ...), such that the original
+    integers are exactly those x such that start_i <= x < end_i for some i.
+
+    Ranges are encoded as single integers (start << 32 | end), not as tuples.
+    """
+
+    sorted_list = sorted(list_)
+    ranges = []
+    last_write = -1
+    for i in range(len(sorted_list)):
+        if i+1 < len(sorted_list):
+            if sorted_list[i] == sorted_list[i+1]-1:
+                continue
+        current_range = sorted_list[last_write+1:i+1]
+        ranges.append(_encode_range(current_range[0], current_range[-1] + 1))
+        last_write = i
+
+    return tuple(ranges)
+
+def _encode_range(start: int, end: int) -> int:
+    return (start << 32) | end
+
+def _decode_range(r: int) -> Tuple[int, int]:
+    return (r >> 32), (r & ((1 << 32) - 1))
+
+
+def intranges_contain(int_: int, ranges: Tuple[int, ...]) -> bool:
+    """Determine if `int_` falls into one of the ranges in `ranges`."""
+    tuple_ = _encode_range(int_, 0)
+    pos = bisect.bisect_left(ranges, tuple_)
+    # we could be immediately ahead of a tuple (start, end)
+    # with start < int_ <= end
+    if pos > 0:
+        left, right = _decode_range(ranges[pos-1])
+        if left <= int_ < right:
+            return True
+    # or we could be immediately behind a tuple (int_, end)
+    if pos < len(ranges):
+        left, _ = _decode_range(ranges[pos])
+        if left == int_:
+            return True
+    return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/package_data.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/package_data.py
new file mode 100644
index 0000000000000000000000000000000000000000..8501893bd153b7216524084cad23e90aeac0b1f8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/package_data.py
@@ -0,0 +1,2 @@
+__version__ = '3.4'
+
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/uts46data.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/uts46data.py
new file mode 100644
index 0000000000000000000000000000000000000000..186796c17b25c1e766112ef4d9f16bb2dea4b306
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/idna/uts46data.py
@@ -0,0 +1,8600 @@
+# This file is automatically generated by tools/idna-data
+# vim: set fileencoding=utf-8 :
+
+from typing import List, Tuple, Union
+
+
+"""IDNA Mapping Table from UTS46."""
+
+
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+    (0x2F963, 'M', '築'),
+    (0x2F964, 'M', '䈧'),
+    (0x2F965, 'M', '𥲀'),
+    (0x2F966, 'M', '糒'),
+    (0x2F967, 'M', '䊠'),
+    (0x2F968, 'M', '糨'),
+    (0x2F969, 'M', '糣'),
+    (0x2F96A, 'M', '紀'),
+    (0x2F96B, 'M', '𥾆'),
+    (0x2F96C, 'M', '絣'),
+    (0x2F96D, 'M', '䌁'),
+    (0x2F96E, 'M', '緇'),
+    (0x2F96F, 'M', '縂'),
+    (0x2F970, 'M', '繅'),
+    (0x2F971, 'M', '䌴'),
+    ]
+
+def _seg_80() -> List[Union[Tuple[int, str], Tuple[int, str, str]]]:
+    return [
+    (0x2F972, 'M', '𦈨'),
+    (0x2F973, 'M', '𦉇'),
+    (0x2F974, 'M', '䍙'),
+    (0x2F975, 'M', '𦋙'),
+    (0x2F976, 'M', '罺'),
+    (0x2F977, 'M', '𦌾'),
+    (0x2F978, 'M', '羕'),
+    (0x2F979, 'M', '翺'),
+    (0x2F97A, 'M', '者'),
+    (0x2F97B, 'M', '𦓚'),
+    (0x2F97C, 'M', '𦔣'),
+    (0x2F97D, 'M', '聠'),
+    (0x2F97E, 'M', '𦖨'),
+    (0x2F97F, 'M', '聰'),
+    (0x2F980, 'M', '𣍟'),
+    (0x2F981, 'M', '䏕'),
+    (0x2F982, 'M', '育'),
+    (0x2F983, 'M', '脃'),
+    (0x2F984, 'M', '䐋'),
+    (0x2F985, 'M', '脾'),
+    (0x2F986, 'M', '媵'),
+    (0x2F987, 'M', '𦞧'),
+    (0x2F988, 'M', '𦞵'),
+    (0x2F989, 'M', '𣎓'),
+    (0x2F98A, 'M', '𣎜'),
+    (0x2F98B, 'M', '舁'),
+    (0x2F98C, 'M', '舄'),
+    (0x2F98D, 'M', '辞'),
+    (0x2F98E, 'M', '䑫'),
+    (0x2F98F, 'M', '芑'),
+    (0x2F990, 'M', '芋'),
+    (0x2F991, 'M', '芝'),
+    (0x2F992, 'M', '劳'),
+    (0x2F993, 'M', '花'),
+    (0x2F994, 'M', '芳'),
+    (0x2F995, 'M', '芽'),
+    (0x2F996, 'M', '苦'),
+    (0x2F997, 'M', '𦬼'),
+    (0x2F998, 'M', '若'),
+    (0x2F999, 'M', '茝'),
+    (0x2F99A, 'M', '荣'),
+    (0x2F99B, 'M', '莭'),
+    (0x2F99C, 'M', '茣'),
+    (0x2F99D, 'M', '莽'),
+    (0x2F99E, 'M', '菧'),
+    (0x2F99F, 'M', '著'),
+    (0x2F9A0, 'M', '荓'),
+    (0x2F9A1, 'M', '菊'),
+    (0x2F9A2, 'M', '菌'),
+    (0x2F9A3, 'M', '菜'),
+    (0x2F9A4, 'M', '𦰶'),
+    (0x2F9A5, 'M', '𦵫'),
+    (0x2F9A6, 'M', '𦳕'),
+    (0x2F9A7, 'M', '䔫'),
+    (0x2F9A8, 'M', '蓱'),
+    (0x2F9A9, 'M', '蓳'),
+    (0x2F9AA, 'M', '蔖'),
+    (0x2F9AB, 'M', '𧏊'),
+    (0x2F9AC, 'M', '蕤'),
+    (0x2F9AD, 'M', '𦼬'),
+    (0x2F9AE, 'M', '䕝'),
+    (0x2F9AF, 'M', '䕡'),
+    (0x2F9B0, 'M', '𦾱'),
+    (0x2F9B1, 'M', '𧃒'),
+    (0x2F9B2, 'M', '䕫'),
+    (0x2F9B3, 'M', '虐'),
+    (0x2F9B4, 'M', '虜'),
+    (0x2F9B5, 'M', '虧'),
+    (0x2F9B6, 'M', '虩'),
+    (0x2F9B7, 'M', '蚩'),
+    (0x2F9B8, 'M', '蚈'),
+    (0x2F9B9, 'M', '蜎'),
+    (0x2F9BA, 'M', '蛢'),
+    (0x2F9BB, 'M', '蝹'),
+    (0x2F9BC, 'M', '蜨'),
+    (0x2F9BD, 'M', '蝫'),
+    (0x2F9BE, 'M', '螆'),
+    (0x2F9BF, 'X'),
+    (0x2F9C0, 'M', '蟡'),
+    (0x2F9C1, 'M', '蠁'),
+    (0x2F9C2, 'M', '䗹'),
+    (0x2F9C3, 'M', '衠'),
+    (0x2F9C4, 'M', '衣'),
+    (0x2F9C5, 'M', '𧙧'),
+    (0x2F9C6, 'M', '裗'),
+    (0x2F9C7, 'M', '裞'),
+    (0x2F9C8, 'M', '䘵'),
+    (0x2F9C9, 'M', '裺'),
+    (0x2F9CA, 'M', '㒻'),
+    (0x2F9CB, 'M', '𧢮'),
+    (0x2F9CC, 'M', '𧥦'),
+    (0x2F9CD, 'M', '䚾'),
+    (0x2F9CE, 'M', '䛇'),
+    (0x2F9CF, 'M', '誠'),
+    (0x2F9D0, 'M', '諭'),
+    (0x2F9D1, 'M', '變'),
+    (0x2F9D2, 'M', '豕'),
+    (0x2F9D3, 'M', '𧲨'),
+    (0x2F9D4, 'M', '貫'),
+    (0x2F9D5, 'M', '賁'),
+    ]
+
+def _seg_81() -> List[Union[Tuple[int, str], Tuple[int, str, str]]]:
+    return [
+    (0x2F9D6, 'M', '贛'),
+    (0x2F9D7, 'M', '起'),
+    (0x2F9D8, 'M', '𧼯'),
+    (0x2F9D9, 'M', '𠠄'),
+    (0x2F9DA, 'M', '跋'),
+    (0x2F9DB, 'M', '趼'),
+    (0x2F9DC, 'M', '跰'),
+    (0x2F9DD, 'M', '𠣞'),
+    (0x2F9DE, 'M', '軔'),
+    (0x2F9DF, 'M', '輸'),
+    (0x2F9E0, 'M', '𨗒'),
+    (0x2F9E1, 'M', '𨗭'),
+    (0x2F9E2, 'M', '邔'),
+    (0x2F9E3, 'M', '郱'),
+    (0x2F9E4, 'M', '鄑'),
+    (0x2F9E5, 'M', '𨜮'),
+    (0x2F9E6, 'M', '鄛'),
+    (0x2F9E7, 'M', '鈸'),
+    (0x2F9E8, 'M', '鋗'),
+    (0x2F9E9, 'M', '鋘'),
+    (0x2F9EA, 'M', '鉼'),
+    (0x2F9EB, 'M', '鏹'),
+    (0x2F9EC, 'M', '鐕'),
+    (0x2F9ED, 'M', '𨯺'),
+    (0x2F9EE, 'M', '開'),
+    (0x2F9EF, 'M', '䦕'),
+    (0x2F9F0, 'M', '閷'),
+    (0x2F9F1, 'M', '𨵷'),
+    (0x2F9F2, 'M', '䧦'),
+    (0x2F9F3, 'M', '雃'),
+    (0x2F9F4, 'M', '嶲'),
+    (0x2F9F5, 'M', '霣'),
+    (0x2F9F6, 'M', '𩅅'),
+    (0x2F9F7, 'M', '𩈚'),
+    (0x2F9F8, 'M', '䩮'),
+    (0x2F9F9, 'M', '䩶'),
+    (0x2F9FA, 'M', '韠'),
+    (0x2F9FB, 'M', '𩐊'),
+    (0x2F9FC, 'M', '䪲'),
+    (0x2F9FD, 'M', '𩒖'),
+    (0x2F9FE, 'M', '頋'),
+    (0x2FA00, 'M', '頩'),
+    (0x2FA01, 'M', '𩖶'),
+    (0x2FA02, 'M', '飢'),
+    (0x2FA03, 'M', '䬳'),
+    (0x2FA04, 'M', '餩'),
+    (0x2FA05, 'M', '馧'),
+    (0x2FA06, 'M', '駂'),
+    (0x2FA07, 'M', '駾'),
+    (0x2FA08, 'M', '䯎'),
+    (0x2FA09, 'M', '𩬰'),
+    (0x2FA0A, 'M', '鬒'),
+    (0x2FA0B, 'M', '鱀'),
+    (0x2FA0C, 'M', '鳽'),
+    (0x2FA0D, 'M', '䳎'),
+    (0x2FA0E, 'M', '䳭'),
+    (0x2FA0F, 'M', '鵧'),
+    (0x2FA10, 'M', '𪃎'),
+    (0x2FA11, 'M', '䳸'),
+    (0x2FA12, 'M', '𪄅'),
+    (0x2FA13, 'M', '𪈎'),
+    (0x2FA14, 'M', '𪊑'),
+    (0x2FA15, 'M', '麻'),
+    (0x2FA16, 'M', '䵖'),
+    (0x2FA17, 'M', '黹'),
+    (0x2FA18, 'M', '黾'),
+    (0x2FA19, 'M', '鼅'),
+    (0x2FA1A, 'M', '鼏'),
+    (0x2FA1B, 'M', '鼖'),
+    (0x2FA1C, 'M', '鼻'),
+    (0x2FA1D, 'M', '𪘀'),
+    (0x2FA1E, 'X'),
+    (0x30000, 'V'),
+    (0x3134B, 'X'),
+    (0x31350, 'V'),
+    (0x323B0, 'X'),
+    (0xE0100, 'I'),
+    (0xE01F0, 'X'),
+    ]
+
+uts46data = tuple(
+    _seg_0()
+    + _seg_1()
+    + _seg_2()
+    + _seg_3()
+    + _seg_4()
+    + _seg_5()
+    + _seg_6()
+    + _seg_7()
+    + _seg_8()
+    + _seg_9()
+    + _seg_10()
+    + _seg_11()
+    + _seg_12()
+    + _seg_13()
+    + _seg_14()
+    + _seg_15()
+    + _seg_16()
+    + _seg_17()
+    + _seg_18()
+    + _seg_19()
+    + _seg_20()
+    + _seg_21()
+    + _seg_22()
+    + _seg_23()
+    + _seg_24()
+    + _seg_25()
+    + _seg_26()
+    + _seg_27()
+    + _seg_28()
+    + _seg_29()
+    + _seg_30()
+    + _seg_31()
+    + _seg_32()
+    + _seg_33()
+    + _seg_34()
+    + _seg_35()
+    + _seg_36()
+    + _seg_37()
+    + _seg_38()
+    + _seg_39()
+    + _seg_40()
+    + _seg_41()
+    + _seg_42()
+    + _seg_43()
+    + _seg_44()
+    + _seg_45()
+    + _seg_46()
+    + _seg_47()
+    + _seg_48()
+    + _seg_49()
+    + _seg_50()
+    + _seg_51()
+    + _seg_52()
+    + _seg_53()
+    + _seg_54()
+    + _seg_55()
+    + _seg_56()
+    + _seg_57()
+    + _seg_58()
+    + _seg_59()
+    + _seg_60()
+    + _seg_61()
+    + _seg_62()
+    + _seg_63()
+    + _seg_64()
+    + _seg_65()
+    + _seg_66()
+    + _seg_67()
+    + _seg_68()
+    + _seg_69()
+    + _seg_70()
+    + _seg_71()
+    + _seg_72()
+    + _seg_73()
+    + _seg_74()
+    + _seg_75()
+    + _seg_76()
+    + _seg_77()
+    + _seg_78()
+    + _seg_79()
+    + _seg_80()
+    + _seg_81()
+)  # type: Tuple[Union[Tuple[int, str], Tuple[int, str, str]], ...]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5071021898725e4f787daf6c3624ae7f25a018f7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/__init__.py
@@ -0,0 +1,57 @@
+# coding: utf-8
+from .exceptions import *
+from .ext import ExtType, Timestamp
+
+import os
+import sys
+
+
+version = (1, 0, 4)
+__version__ = "1.0.4"
+
+
+if os.environ.get("MSGPACK_PUREPYTHON") or sys.version_info[0] == 2:
+    from .fallback import Packer, unpackb, Unpacker
+else:
+    try:
+        from ._cmsgpack import Packer, unpackb, Unpacker
+    except ImportError:
+        from .fallback import Packer, unpackb, Unpacker
+
+
+def pack(o, stream, **kwargs):
+    """
+    Pack object `o` and write it to `stream`
+
+    See :class:`Packer` for options.
+    """
+    packer = Packer(**kwargs)
+    stream.write(packer.pack(o))
+
+
+def packb(o, **kwargs):
+    """
+    Pack object `o` and return packed bytes
+
+    See :class:`Packer` for options.
+    """
+    return Packer(**kwargs).pack(o)
+
+
+def unpack(stream, **kwargs):
+    """
+    Unpack an object from `stream`.
+
+    Raises `ExtraData` when `stream` contains extra bytes.
+    See :class:`Unpacker` for options.
+    """
+    data = stream.read()
+    return unpackb(data, **kwargs)
+
+
+# alias for compatibility to simplejson/marshal/pickle.
+load = unpack
+loads = unpackb
+
+dump = pack
+dumps = packb
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/exceptions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/exceptions.py
new file mode 100644
index 0000000000000000000000000000000000000000..d6d2615cfdd0b914d064cdf7eecd45761e4bcaf6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/exceptions.py
@@ -0,0 +1,48 @@
+class UnpackException(Exception):
+    """Base class for some exceptions raised while unpacking.
+
+    NOTE: unpack may raise exception other than subclass of
+    UnpackException.  If you want to catch all error, catch
+    Exception instead.
+    """
+
+
+class BufferFull(UnpackException):
+    pass
+
+
+class OutOfData(UnpackException):
+    pass
+
+
+class FormatError(ValueError, UnpackException):
+    """Invalid msgpack format"""
+
+
+class StackError(ValueError, UnpackException):
+    """Too nested"""
+
+
+# Deprecated.  Use ValueError instead
+UnpackValueError = ValueError
+
+
+class ExtraData(UnpackValueError):
+    """ExtraData is raised when there is trailing data.
+
+    This exception is raised while only one-shot (not streaming)
+    unpack.
+    """
+
+    def __init__(self, unpacked, extra):
+        self.unpacked = unpacked
+        self.extra = extra
+
+    def __str__(self):
+        return "unpack(b) received extra data."
+
+
+# Deprecated.  Use Exception instead to catch all exception during packing.
+PackException = Exception
+PackValueError = ValueError
+PackOverflowError = OverflowError
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/ext.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/ext.py
new file mode 100644
index 0000000000000000000000000000000000000000..25544c555648c13762e150ea559d3a69674bdd34
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/ext.py
@@ -0,0 +1,193 @@
+# coding: utf-8
+from collections import namedtuple
+import datetime
+import sys
+import struct
+
+
+PY2 = sys.version_info[0] == 2
+
+if PY2:
+    int_types = (int, long)
+    _utc = None
+else:
+    int_types = int
+    try:
+        _utc = datetime.timezone.utc
+    except AttributeError:
+        _utc = datetime.timezone(datetime.timedelta(0))
+
+
+class ExtType(namedtuple("ExtType", "code data")):
+    """ExtType represents ext type in msgpack."""
+
+    def __new__(cls, code, data):
+        if not isinstance(code, int):
+            raise TypeError("code must be int")
+        if not isinstance(data, bytes):
+            raise TypeError("data must be bytes")
+        if not 0 <= code <= 127:
+            raise ValueError("code must be 0~127")
+        return super(ExtType, cls).__new__(cls, code, data)
+
+
+class Timestamp(object):
+    """Timestamp represents the Timestamp extension type in msgpack.
+
+    When built with Cython, msgpack uses C methods to pack and unpack `Timestamp`. When using pure-Python
+    msgpack, :func:`to_bytes` and :func:`from_bytes` are used to pack and unpack `Timestamp`.
+
+    This class is immutable: Do not override seconds and nanoseconds.
+    """
+
+    __slots__ = ["seconds", "nanoseconds"]
+
+    def __init__(self, seconds, nanoseconds=0):
+        """Initialize a Timestamp object.
+
+        :param int seconds:
+            Number of seconds since the UNIX epoch (00:00:00 UTC Jan 1 1970, minus leap seconds).
+            May be negative.
+
+        :param int nanoseconds:
+            Number of nanoseconds to add to `seconds` to get fractional time.
+            Maximum is 999_999_999.  Default is 0.
+
+        Note: Negative times (before the UNIX epoch) are represented as negative seconds + positive ns.
+        """
+        if not isinstance(seconds, int_types):
+            raise TypeError("seconds must be an interger")
+        if not isinstance(nanoseconds, int_types):
+            raise TypeError("nanoseconds must be an integer")
+        if not (0 <= nanoseconds < 10**9):
+            raise ValueError(
+                "nanoseconds must be a non-negative integer less than 999999999."
+            )
+        self.seconds = seconds
+        self.nanoseconds = nanoseconds
+
+    def __repr__(self):
+        """String representation of Timestamp."""
+        return "Timestamp(seconds={0}, nanoseconds={1})".format(
+            self.seconds, self.nanoseconds
+        )
+
+    def __eq__(self, other):
+        """Check for equality with another Timestamp object"""
+        if type(other) is self.__class__:
+            return (
+                self.seconds == other.seconds and self.nanoseconds == other.nanoseconds
+            )
+        return False
+
+    def __ne__(self, other):
+        """not-equals method (see :func:`__eq__()`)"""
+        return not self.__eq__(other)
+
+    def __hash__(self):
+        return hash((self.seconds, self.nanoseconds))
+
+    @staticmethod
+    def from_bytes(b):
+        """Unpack bytes into a `Timestamp` object.
+
+        Used for pure-Python msgpack unpacking.
+
+        :param b: Payload from msgpack ext message with code -1
+        :type b: bytes
+
+        :returns: Timestamp object unpacked from msgpack ext payload
+        :rtype: Timestamp
+        """
+        if len(b) == 4:
+            seconds = struct.unpack("!L", b)[0]
+            nanoseconds = 0
+        elif len(b) == 8:
+            data64 = struct.unpack("!Q", b)[0]
+            seconds = data64 & 0x00000003FFFFFFFF
+            nanoseconds = data64 >> 34
+        elif len(b) == 12:
+            nanoseconds, seconds = struct.unpack("!Iq", b)
+        else:
+            raise ValueError(
+                "Timestamp type can only be created from 32, 64, or 96-bit byte objects"
+            )
+        return Timestamp(seconds, nanoseconds)
+
+    def to_bytes(self):
+        """Pack this Timestamp object into bytes.
+
+        Used for pure-Python msgpack packing.
+
+        :returns data: Payload for EXT message with code -1 (timestamp type)
+        :rtype: bytes
+        """
+        if (self.seconds >> 34) == 0:  # seconds is non-negative and fits in 34 bits
+            data64 = self.nanoseconds << 34 | self.seconds
+            if data64 & 0xFFFFFFFF00000000 == 0:
+                # nanoseconds is zero and seconds < 2**32, so timestamp 32
+                data = struct.pack("!L", data64)
+            else:
+                # timestamp 64
+                data = struct.pack("!Q", data64)
+        else:
+            # timestamp 96
+            data = struct.pack("!Iq", self.nanoseconds, self.seconds)
+        return data
+
+    @staticmethod
+    def from_unix(unix_sec):
+        """Create a Timestamp from posix timestamp in seconds.
+
+        :param unix_float: Posix timestamp in seconds.
+        :type unix_float: int or float.
+        """
+        seconds = int(unix_sec // 1)
+        nanoseconds = int((unix_sec % 1) * 10**9)
+        return Timestamp(seconds, nanoseconds)
+
+    def to_unix(self):
+        """Get the timestamp as a floating-point value.
+
+        :returns: posix timestamp
+        :rtype: float
+        """
+        return self.seconds + self.nanoseconds / 1e9
+
+    @staticmethod
+    def from_unix_nano(unix_ns):
+        """Create a Timestamp from posix timestamp in nanoseconds.
+
+        :param int unix_ns: Posix timestamp in nanoseconds.
+        :rtype: Timestamp
+        """
+        return Timestamp(*divmod(unix_ns, 10**9))
+
+    def to_unix_nano(self):
+        """Get the timestamp as a unixtime in nanoseconds.
+
+        :returns: posix timestamp in nanoseconds
+        :rtype: int
+        """
+        return self.seconds * 10**9 + self.nanoseconds
+
+    def to_datetime(self):
+        """Get the timestamp as a UTC datetime.
+
+        Python 2 is not supported.
+
+        :rtype: datetime.
+        """
+        return datetime.datetime.fromtimestamp(0, _utc) + datetime.timedelta(
+            seconds=self.to_unix()
+        )
+
+    @staticmethod
+    def from_datetime(dt):
+        """Create a Timestamp from datetime with tzinfo.
+
+        Python 2 is not supported.
+
+        :rtype: Timestamp
+        """
+        return Timestamp.from_unix(dt.timestamp())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/fallback.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/fallback.py
new file mode 100644
index 0000000000000000000000000000000000000000..f560c7b55099976eb29781ed47fdbf92db3c10f8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/msgpack/fallback.py
@@ -0,0 +1,1010 @@
+"""Fallback pure Python implementation of msgpack"""
+from datetime import datetime as _DateTime
+import sys
+import struct
+
+
+PY2 = sys.version_info[0] == 2
+if PY2:
+    int_types = (int, long)
+
+    def dict_iteritems(d):
+        return d.iteritems()
+
+else:
+    int_types = int
+    unicode = str
+    xrange = range
+
+    def dict_iteritems(d):
+        return d.items()
+
+
+if sys.version_info < (3, 5):
+    # Ugly hack...
+    RecursionError = RuntimeError
+
+    def _is_recursionerror(e):
+        return (
+            len(e.args) == 1
+            and isinstance(e.args[0], str)
+            and e.args[0].startswith("maximum recursion depth exceeded")
+        )
+
+else:
+
+    def _is_recursionerror(e):
+        return True
+
+
+if hasattr(sys, "pypy_version_info"):
+    # StringIO is slow on PyPy, StringIO is faster.  However: PyPy's own
+    # StringBuilder is fastest.
+    from __pypy__ import newlist_hint
+
+    try:
+        from __pypy__.builders import BytesBuilder as StringBuilder
+    except ImportError:
+        from __pypy__.builders import StringBuilder
+    USING_STRINGBUILDER = True
+
+    class StringIO(object):
+        def __init__(self, s=b""):
+            if s:
+                self.builder = StringBuilder(len(s))
+                self.builder.append(s)
+            else:
+                self.builder = StringBuilder()
+
+        def write(self, s):
+            if isinstance(s, memoryview):
+                s = s.tobytes()
+            elif isinstance(s, bytearray):
+                s = bytes(s)
+            self.builder.append(s)
+
+        def getvalue(self):
+            return self.builder.build()
+
+else:
+    USING_STRINGBUILDER = False
+    from io import BytesIO as StringIO
+
+    newlist_hint = lambda size: []
+
+
+from .exceptions import BufferFull, OutOfData, ExtraData, FormatError, StackError
+
+from .ext import ExtType, Timestamp
+
+
+EX_SKIP = 0
+EX_CONSTRUCT = 1
+EX_READ_ARRAY_HEADER = 2
+EX_READ_MAP_HEADER = 3
+
+TYPE_IMMEDIATE = 0
+TYPE_ARRAY = 1
+TYPE_MAP = 2
+TYPE_RAW = 3
+TYPE_BIN = 4
+TYPE_EXT = 5
+
+DEFAULT_RECURSE_LIMIT = 511
+
+
+def _check_type_strict(obj, t, type=type, tuple=tuple):
+    if type(t) is tuple:
+        return type(obj) in t
+    else:
+        return type(obj) is t
+
+
+def _get_data_from_buffer(obj):
+    view = memoryview(obj)
+    if view.itemsize != 1:
+        raise ValueError("cannot unpack from multi-byte object")
+    return view
+
+
+def unpackb(packed, **kwargs):
+    """
+    Unpack an object from `packed`.
+
+    Raises ``ExtraData`` when *packed* contains extra bytes.
+    Raises ``ValueError`` when *packed* is incomplete.
+    Raises ``FormatError`` when *packed* is not valid msgpack.
+    Raises ``StackError`` when *packed* contains too nested.
+    Other exceptions can be raised during unpacking.
+
+    See :class:`Unpacker` for options.
+    """
+    unpacker = Unpacker(None, max_buffer_size=len(packed), **kwargs)
+    unpacker.feed(packed)
+    try:
+        ret = unpacker._unpack()
+    except OutOfData:
+        raise ValueError("Unpack failed: incomplete input")
+    except RecursionError as e:
+        if _is_recursionerror(e):
+            raise StackError
+        raise
+    if unpacker._got_extradata():
+        raise ExtraData(ret, unpacker._get_extradata())
+    return ret
+
+
+if sys.version_info < (2, 7, 6):
+
+    def _unpack_from(f, b, o=0):
+        """Explicit type cast for legacy struct.unpack_from"""
+        return struct.unpack_from(f, bytes(b), o)
+
+else:
+    _unpack_from = struct.unpack_from
+
+_NO_FORMAT_USED = ""
+_MSGPACK_HEADERS = {
+    0xC4: (1, _NO_FORMAT_USED, TYPE_BIN),
+    0xC5: (2, ">H", TYPE_BIN),
+    0xC6: (4, ">I", TYPE_BIN),
+    0xC7: (2, "Bb", TYPE_EXT),
+    0xC8: (3, ">Hb", TYPE_EXT),
+    0xC9: (5, ">Ib", TYPE_EXT),
+    0xCA: (4, ">f"),
+    0xCB: (8, ">d"),
+    0xCC: (1, _NO_FORMAT_USED),
+    0xCD: (2, ">H"),
+    0xCE: (4, ">I"),
+    0xCF: (8, ">Q"),
+    0xD0: (1, "b"),
+    0xD1: (2, ">h"),
+    0xD2: (4, ">i"),
+    0xD3: (8, ">q"),
+    0xD4: (1, "b1s", TYPE_EXT),
+    0xD5: (2, "b2s", TYPE_EXT),
+    0xD6: (4, "b4s", TYPE_EXT),
+    0xD7: (8, "b8s", TYPE_EXT),
+    0xD8: (16, "b16s", TYPE_EXT),
+    0xD9: (1, _NO_FORMAT_USED, TYPE_RAW),
+    0xDA: (2, ">H", TYPE_RAW),
+    0xDB: (4, ">I", TYPE_RAW),
+    0xDC: (2, ">H", TYPE_ARRAY),
+    0xDD: (4, ">I", TYPE_ARRAY),
+    0xDE: (2, ">H", TYPE_MAP),
+    0xDF: (4, ">I", TYPE_MAP),
+}
+
+
+class Unpacker(object):
+    """Streaming unpacker.
+
+    Arguments:
+
+    :param file_like:
+        File-like object having `.read(n)` method.
+        If specified, unpacker reads serialized data from it and :meth:`feed()` is not usable.
+
+    :param int read_size:
+        Used as `file_like.read(read_size)`. (default: `min(16*1024, max_buffer_size)`)
+
+    :param bool use_list:
+        If true, unpack msgpack array to Python list.
+        Otherwise, unpack to Python tuple. (default: True)
+
+    :param bool raw:
+        If true, unpack msgpack raw to Python bytes.
+        Otherwise, unpack to Python str by decoding with UTF-8 encoding (default).
+
+    :param int timestamp:
+        Control how timestamp type is unpacked:
+
+            0 - Timestamp
+            1 - float  (Seconds from the EPOCH)
+            2 - int  (Nanoseconds from the EPOCH)
+            3 - datetime.datetime  (UTC).  Python 2 is not supported.
+
+    :param bool strict_map_key:
+        If true (default), only str or bytes are accepted for map (dict) keys.
+
+    :param callable object_hook:
+        When specified, it should be callable.
+        Unpacker calls it with a dict argument after unpacking msgpack map.
+        (See also simplejson)
+
+    :param callable object_pairs_hook:
+        When specified, it should be callable.
+        Unpacker calls it with a list of key-value pairs after unpacking msgpack map.
+        (See also simplejson)
+
+    :param str unicode_errors:
+        The error handler for decoding unicode. (default: 'strict')
+        This option should be used only when you have msgpack data which
+        contains invalid UTF-8 string.
+
+    :param int max_buffer_size:
+        Limits size of data waiting unpacked.  0 means 2**32-1.
+        The default value is 100*1024*1024 (100MiB).
+        Raises `BufferFull` exception when it is insufficient.
+        You should set this parameter when unpacking data from untrusted source.
+
+    :param int max_str_len:
+        Deprecated, use *max_buffer_size* instead.
+        Limits max length of str. (default: max_buffer_size)
+
+    :param int max_bin_len:
+        Deprecated, use *max_buffer_size* instead.
+        Limits max length of bin. (default: max_buffer_size)
+
+    :param int max_array_len:
+        Limits max length of array.
+        (default: max_buffer_size)
+
+    :param int max_map_len:
+        Limits max length of map.
+        (default: max_buffer_size//2)
+
+    :param int max_ext_len:
+        Deprecated, use *max_buffer_size* instead.
+        Limits max size of ext type.  (default: max_buffer_size)
+
+    Example of streaming deserialize from file-like object::
+
+        unpacker = Unpacker(file_like)
+        for o in unpacker:
+            process(o)
+
+    Example of streaming deserialize from socket::
+
+        unpacker = Unpacker()
+        while True:
+            buf = sock.recv(1024**2)
+            if not buf:
+                break
+            unpacker.feed(buf)
+            for o in unpacker:
+                process(o)
+
+    Raises ``ExtraData`` when *packed* contains extra bytes.
+    Raises ``OutOfData`` when *packed* is incomplete.
+    Raises ``FormatError`` when *packed* is not valid msgpack.
+    Raises ``StackError`` when *packed* contains too nested.
+    Other exceptions can be raised during unpacking.
+    """
+
+    def __init__(
+        self,
+        file_like=None,
+        read_size=0,
+        use_list=True,
+        raw=False,
+        timestamp=0,
+        strict_map_key=True,
+        object_hook=None,
+        object_pairs_hook=None,
+        list_hook=None,
+        unicode_errors=None,
+        max_buffer_size=100 * 1024 * 1024,
+        ext_hook=ExtType,
+        max_str_len=-1,
+        max_bin_len=-1,
+        max_array_len=-1,
+        max_map_len=-1,
+        max_ext_len=-1,
+    ):
+        if unicode_errors is None:
+            unicode_errors = "strict"
+
+        if file_like is None:
+            self._feeding = True
+        else:
+            if not callable(file_like.read):
+                raise TypeError("`file_like.read` must be callable")
+            self.file_like = file_like
+            self._feeding = False
+
+        #: array of bytes fed.
+        self._buffer = bytearray()
+        #: Which position we currently reads
+        self._buff_i = 0
+
+        # When Unpacker is used as an iterable, between the calls to next(),
+        # the buffer is not "consumed" completely, for efficiency sake.
+        # Instead, it is done sloppily.  To make sure we raise BufferFull at
+        # the correct moments, we have to keep track of how sloppy we were.
+        # Furthermore, when the buffer is incomplete (that is: in the case
+        # we raise an OutOfData) we need to rollback the buffer to the correct
+        # state, which _buf_checkpoint records.
+        self._buf_checkpoint = 0
+
+        if not max_buffer_size:
+            max_buffer_size = 2**31 - 1
+        if max_str_len == -1:
+            max_str_len = max_buffer_size
+        if max_bin_len == -1:
+            max_bin_len = max_buffer_size
+        if max_array_len == -1:
+            max_array_len = max_buffer_size
+        if max_map_len == -1:
+            max_map_len = max_buffer_size // 2
+        if max_ext_len == -1:
+            max_ext_len = max_buffer_size
+
+        self._max_buffer_size = max_buffer_size
+        if read_size > self._max_buffer_size:
+            raise ValueError("read_size must be smaller than max_buffer_size")
+        self._read_size = read_size or min(self._max_buffer_size, 16 * 1024)
+        self._raw = bool(raw)
+        self._strict_map_key = bool(strict_map_key)
+        self._unicode_errors = unicode_errors
+        self._use_list = use_list
+        if not (0 <= timestamp <= 3):
+            raise ValueError("timestamp must be 0..3")
+        self._timestamp = timestamp
+        self._list_hook = list_hook
+        self._object_hook = object_hook
+        self._object_pairs_hook = object_pairs_hook
+        self._ext_hook = ext_hook
+        self._max_str_len = max_str_len
+        self._max_bin_len = max_bin_len
+        self._max_array_len = max_array_len
+        self._max_map_len = max_map_len
+        self._max_ext_len = max_ext_len
+        self._stream_offset = 0
+
+        if list_hook is not None and not callable(list_hook):
+            raise TypeError("`list_hook` is not callable")
+        if object_hook is not None and not callable(object_hook):
+            raise TypeError("`object_hook` is not callable")
+        if object_pairs_hook is not None and not callable(object_pairs_hook):
+            raise TypeError("`object_pairs_hook` is not callable")
+        if object_hook is not None and object_pairs_hook is not None:
+            raise TypeError(
+                "object_pairs_hook and object_hook are mutually " "exclusive"
+            )
+        if not callable(ext_hook):
+            raise TypeError("`ext_hook` is not callable")
+
+    def feed(self, next_bytes):
+        assert self._feeding
+        view = _get_data_from_buffer(next_bytes)
+        if len(self._buffer) - self._buff_i + len(view) > self._max_buffer_size:
+            raise BufferFull
+
+        # Strip buffer before checkpoint before reading file.
+        if self._buf_checkpoint > 0:
+            del self._buffer[: self._buf_checkpoint]
+            self._buff_i -= self._buf_checkpoint
+            self._buf_checkpoint = 0
+
+        # Use extend here: INPLACE_ADD += doesn't reliably typecast memoryview in jython
+        self._buffer.extend(view)
+
+    def _consume(self):
+        """Gets rid of the used parts of the buffer."""
+        self._stream_offset += self._buff_i - self._buf_checkpoint
+        self._buf_checkpoint = self._buff_i
+
+    def _got_extradata(self):
+        return self._buff_i < len(self._buffer)
+
+    def _get_extradata(self):
+        return self._buffer[self._buff_i :]
+
+    def read_bytes(self, n):
+        ret = self._read(n, raise_outofdata=False)
+        self._consume()
+        return ret
+
+    def _read(self, n, raise_outofdata=True):
+        # (int) -> bytearray
+        self._reserve(n, raise_outofdata=raise_outofdata)
+        i = self._buff_i
+        ret = self._buffer[i : i + n]
+        self._buff_i = i + len(ret)
+        return ret
+
+    def _reserve(self, n, raise_outofdata=True):
+        remain_bytes = len(self._buffer) - self._buff_i - n
+
+        # Fast path: buffer has n bytes already
+        if remain_bytes >= 0:
+            return
+
+        if self._feeding:
+            self._buff_i = self._buf_checkpoint
+            raise OutOfData
+
+        # Strip buffer before checkpoint before reading file.
+        if self._buf_checkpoint > 0:
+            del self._buffer[: self._buf_checkpoint]
+            self._buff_i -= self._buf_checkpoint
+            self._buf_checkpoint = 0
+
+        # Read from file
+        remain_bytes = -remain_bytes
+        if remain_bytes + len(self._buffer) > self._max_buffer_size:
+            raise BufferFull
+        while remain_bytes > 0:
+            to_read_bytes = max(self._read_size, remain_bytes)
+            read_data = self.file_like.read(to_read_bytes)
+            if not read_data:
+                break
+            assert isinstance(read_data, bytes)
+            self._buffer += read_data
+            remain_bytes -= len(read_data)
+
+        if len(self._buffer) < n + self._buff_i and raise_outofdata:
+            self._buff_i = 0  # rollback
+            raise OutOfData
+
+    def _read_header(self):
+        typ = TYPE_IMMEDIATE
+        n = 0
+        obj = None
+        self._reserve(1)
+        b = self._buffer[self._buff_i]
+        self._buff_i += 1
+        if b & 0b10000000 == 0:
+            obj = b
+        elif b & 0b11100000 == 0b11100000:
+            obj = -1 - (b ^ 0xFF)
+        elif b & 0b11100000 == 0b10100000:
+            n = b & 0b00011111
+            typ = TYPE_RAW
+            if n > self._max_str_len:
+                raise ValueError("%s exceeds max_str_len(%s)" % (n, self._max_str_len))
+            obj = self._read(n)
+        elif b & 0b11110000 == 0b10010000:
+            n = b & 0b00001111
+            typ = TYPE_ARRAY
+            if n > self._max_array_len:
+                raise ValueError(
+                    "%s exceeds max_array_len(%s)" % (n, self._max_array_len)
+                )
+        elif b & 0b11110000 == 0b10000000:
+            n = b & 0b00001111
+            typ = TYPE_MAP
+            if n > self._max_map_len:
+                raise ValueError("%s exceeds max_map_len(%s)" % (n, self._max_map_len))
+        elif b == 0xC0:
+            obj = None
+        elif b == 0xC2:
+            obj = False
+        elif b == 0xC3:
+            obj = True
+        elif 0xC4 <= b <= 0xC6:
+            size, fmt, typ = _MSGPACK_HEADERS[b]
+            self._reserve(size)
+            if len(fmt) > 0:
+                n = _unpack_from(fmt, self._buffer, self._buff_i)[0]
+            else:
+                n = self._buffer[self._buff_i]
+            self._buff_i += size
+            if n > self._max_bin_len:
+                raise ValueError("%s exceeds max_bin_len(%s)" % (n, self._max_bin_len))
+            obj = self._read(n)
+        elif 0xC7 <= b <= 0xC9:
+            size, fmt, typ = _MSGPACK_HEADERS[b]
+            self._reserve(size)
+            L, n = _unpack_from(fmt, self._buffer, self._buff_i)
+            self._buff_i += size
+            if L > self._max_ext_len:
+                raise ValueError("%s exceeds max_ext_len(%s)" % (L, self._max_ext_len))
+            obj = self._read(L)
+        elif 0xCA <= b <= 0xD3:
+            size, fmt = _MSGPACK_HEADERS[b]
+            self._reserve(size)
+            if len(fmt) > 0:
+                obj = _unpack_from(fmt, self._buffer, self._buff_i)[0]
+            else:
+                obj = self._buffer[self._buff_i]
+            self._buff_i += size
+        elif 0xD4 <= b <= 0xD8:
+            size, fmt, typ = _MSGPACK_HEADERS[b]
+            if self._max_ext_len < size:
+                raise ValueError(
+                    "%s exceeds max_ext_len(%s)" % (size, self._max_ext_len)
+                )
+            self._reserve(size + 1)
+            n, obj = _unpack_from(fmt, self._buffer, self._buff_i)
+            self._buff_i += size + 1
+        elif 0xD9 <= b <= 0xDB:
+            size, fmt, typ = _MSGPACK_HEADERS[b]
+            self._reserve(size)
+            if len(fmt) > 0:
+                (n,) = _unpack_from(fmt, self._buffer, self._buff_i)
+            else:
+                n = self._buffer[self._buff_i]
+            self._buff_i += size
+            if n > self._max_str_len:
+                raise ValueError("%s exceeds max_str_len(%s)" % (n, self._max_str_len))
+            obj = self._read(n)
+        elif 0xDC <= b <= 0xDD:
+            size, fmt, typ = _MSGPACK_HEADERS[b]
+            self._reserve(size)
+            (n,) = _unpack_from(fmt, self._buffer, self._buff_i)
+            self._buff_i += size
+            if n > self._max_array_len:
+                raise ValueError(
+                    "%s exceeds max_array_len(%s)" % (n, self._max_array_len)
+                )
+        elif 0xDE <= b <= 0xDF:
+            size, fmt, typ = _MSGPACK_HEADERS[b]
+            self._reserve(size)
+            (n,) = _unpack_from(fmt, self._buffer, self._buff_i)
+            self._buff_i += size
+            if n > self._max_map_len:
+                raise ValueError("%s exceeds max_map_len(%s)" % (n, self._max_map_len))
+        else:
+            raise FormatError("Unknown header: 0x%x" % b)
+        return typ, n, obj
+
+    def _unpack(self, execute=EX_CONSTRUCT):
+        typ, n, obj = self._read_header()
+
+        if execute == EX_READ_ARRAY_HEADER:
+            if typ != TYPE_ARRAY:
+                raise ValueError("Expected array")
+            return n
+        if execute == EX_READ_MAP_HEADER:
+            if typ != TYPE_MAP:
+                raise ValueError("Expected map")
+            return n
+        # TODO should we eliminate the recursion?
+        if typ == TYPE_ARRAY:
+            if execute == EX_SKIP:
+                for i in xrange(n):
+                    # TODO check whether we need to call `list_hook`
+                    self._unpack(EX_SKIP)
+                return
+            ret = newlist_hint(n)
+            for i in xrange(n):
+                ret.append(self._unpack(EX_CONSTRUCT))
+            if self._list_hook is not None:
+                ret = self._list_hook(ret)
+            # TODO is the interaction between `list_hook` and `use_list` ok?
+            return ret if self._use_list else tuple(ret)
+        if typ == TYPE_MAP:
+            if execute == EX_SKIP:
+                for i in xrange(n):
+                    # TODO check whether we need to call hooks
+                    self._unpack(EX_SKIP)
+                    self._unpack(EX_SKIP)
+                return
+            if self._object_pairs_hook is not None:
+                ret = self._object_pairs_hook(
+                    (self._unpack(EX_CONSTRUCT), self._unpack(EX_CONSTRUCT))
+                    for _ in xrange(n)
+                )
+            else:
+                ret = {}
+                for _ in xrange(n):
+                    key = self._unpack(EX_CONSTRUCT)
+                    if self._strict_map_key and type(key) not in (unicode, bytes):
+                        raise ValueError(
+                            "%s is not allowed for map key" % str(type(key))
+                        )
+                    if not PY2 and type(key) is str:
+                        key = sys.intern(key)
+                    ret[key] = self._unpack(EX_CONSTRUCT)
+                if self._object_hook is not None:
+                    ret = self._object_hook(ret)
+            return ret
+        if execute == EX_SKIP:
+            return
+        if typ == TYPE_RAW:
+            if self._raw:
+                obj = bytes(obj)
+            else:
+                obj = obj.decode("utf_8", self._unicode_errors)
+            return obj
+        if typ == TYPE_BIN:
+            return bytes(obj)
+        if typ == TYPE_EXT:
+            if n == -1:  # timestamp
+                ts = Timestamp.from_bytes(bytes(obj))
+                if self._timestamp == 1:
+                    return ts.to_unix()
+                elif self._timestamp == 2:
+                    return ts.to_unix_nano()
+                elif self._timestamp == 3:
+                    return ts.to_datetime()
+                else:
+                    return ts
+            else:
+                return self._ext_hook(n, bytes(obj))
+        assert typ == TYPE_IMMEDIATE
+        return obj
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        try:
+            ret = self._unpack(EX_CONSTRUCT)
+            self._consume()
+            return ret
+        except OutOfData:
+            self._consume()
+            raise StopIteration
+        except RecursionError:
+            raise StackError
+
+    next = __next__
+
+    def skip(self):
+        self._unpack(EX_SKIP)
+        self._consume()
+
+    def unpack(self):
+        try:
+            ret = self._unpack(EX_CONSTRUCT)
+        except RecursionError:
+            raise StackError
+        self._consume()
+        return ret
+
+    def read_array_header(self):
+        ret = self._unpack(EX_READ_ARRAY_HEADER)
+        self._consume()
+        return ret
+
+    def read_map_header(self):
+        ret = self._unpack(EX_READ_MAP_HEADER)
+        self._consume()
+        return ret
+
+    def tell(self):
+        return self._stream_offset
+
+
+class Packer(object):
+    """
+    MessagePack Packer
+
+    Usage::
+
+        packer = Packer()
+        astream.write(packer.pack(a))
+        astream.write(packer.pack(b))
+
+    Packer's constructor has some keyword arguments:
+
+    :param callable default:
+        Convert user type to builtin type that Packer supports.
+        See also simplejson's document.
+
+    :param bool use_single_float:
+        Use single precision float type for float. (default: False)
+
+    :param bool autoreset:
+        Reset buffer after each pack and return its content as `bytes`. (default: True).
+        If set this to false, use `bytes()` to get content and `.reset()` to clear buffer.
+
+    :param bool use_bin_type:
+        Use bin type introduced in msgpack spec 2.0 for bytes.
+        It also enables str8 type for unicode. (default: True)
+
+    :param bool strict_types:
+        If set to true, types will be checked to be exact. Derived classes
+        from serializable types will not be serialized and will be
+        treated as unsupported type and forwarded to default.
+        Additionally tuples will not be serialized as lists.
+        This is useful when trying to implement accurate serialization
+        for python types.
+
+    :param bool datetime:
+        If set to true, datetime with tzinfo is packed into Timestamp type.
+        Note that the tzinfo is stripped in the timestamp.
+        You can get UTC datetime with `timestamp=3` option of the Unpacker.
+        (Python 2 is not supported).
+
+    :param str unicode_errors:
+        The error handler for encoding unicode. (default: 'strict')
+        DO NOT USE THIS!!  This option is kept for very specific usage.
+
+    Example of streaming deserialize from file-like object::
+
+        unpacker = Unpacker(file_like)
+        for o in unpacker:
+            process(o)
+
+    Example of streaming deserialize from socket::
+
+        unpacker = Unpacker()
+        while True:
+            buf = sock.recv(1024**2)
+            if not buf:
+                break
+            unpacker.feed(buf)
+            for o in unpacker:
+                process(o)
+
+    Raises ``ExtraData`` when *packed* contains extra bytes.
+    Raises ``OutOfData`` when *packed* is incomplete.
+    Raises ``FormatError`` when *packed* is not valid msgpack.
+    Raises ``StackError`` when *packed* contains too nested.
+    Other exceptions can be raised during unpacking.
+    """
+
+    def __init__(
+        self,
+        default=None,
+        use_single_float=False,
+        autoreset=True,
+        use_bin_type=True,
+        strict_types=False,
+        datetime=False,
+        unicode_errors=None,
+    ):
+        self._strict_types = strict_types
+        self._use_float = use_single_float
+        self._autoreset = autoreset
+        self._use_bin_type = use_bin_type
+        self._buffer = StringIO()
+        if PY2 and datetime:
+            raise ValueError("datetime is not supported in Python 2")
+        self._datetime = bool(datetime)
+        self._unicode_errors = unicode_errors or "strict"
+        if default is not None:
+            if not callable(default):
+                raise TypeError("default must be callable")
+        self._default = default
+
+    def _pack(
+        self,
+        obj,
+        nest_limit=DEFAULT_RECURSE_LIMIT,
+        check=isinstance,
+        check_type_strict=_check_type_strict,
+    ):
+        default_used = False
+        if self._strict_types:
+            check = check_type_strict
+            list_types = list
+        else:
+            list_types = (list, tuple)
+        while True:
+            if nest_limit < 0:
+                raise ValueError("recursion limit exceeded")
+            if obj is None:
+                return self._buffer.write(b"\xc0")
+            if check(obj, bool):
+                if obj:
+                    return self._buffer.write(b"\xc3")
+                return self._buffer.write(b"\xc2")
+            if check(obj, int_types):
+                if 0 <= obj < 0x80:
+                    return self._buffer.write(struct.pack("B", obj))
+                if -0x20 <= obj < 0:
+                    return self._buffer.write(struct.pack("b", obj))
+                if 0x80 <= obj <= 0xFF:
+                    return self._buffer.write(struct.pack("BB", 0xCC, obj))
+                if -0x80 <= obj < 0:
+                    return self._buffer.write(struct.pack(">Bb", 0xD0, obj))
+                if 0xFF < obj <= 0xFFFF:
+                    return self._buffer.write(struct.pack(">BH", 0xCD, obj))
+                if -0x8000 <= obj < -0x80:
+                    return self._buffer.write(struct.pack(">Bh", 0xD1, obj))
+                if 0xFFFF < obj <= 0xFFFFFFFF:
+                    return self._buffer.write(struct.pack(">BI", 0xCE, obj))
+                if -0x80000000 <= obj < -0x8000:
+                    return self._buffer.write(struct.pack(">Bi", 0xD2, obj))
+                if 0xFFFFFFFF < obj <= 0xFFFFFFFFFFFFFFFF:
+                    return self._buffer.write(struct.pack(">BQ", 0xCF, obj))
+                if -0x8000000000000000 <= obj < -0x80000000:
+                    return self._buffer.write(struct.pack(">Bq", 0xD3, obj))
+                if not default_used and self._default is not None:
+                    obj = self._default(obj)
+                    default_used = True
+                    continue
+                raise OverflowError("Integer value out of range")
+            if check(obj, (bytes, bytearray)):
+                n = len(obj)
+                if n >= 2**32:
+                    raise ValueError("%s is too large" % type(obj).__name__)
+                self._pack_bin_header(n)
+                return self._buffer.write(obj)
+            if check(obj, unicode):
+                obj = obj.encode("utf-8", self._unicode_errors)
+                n = len(obj)
+                if n >= 2**32:
+                    raise ValueError("String is too large")
+                self._pack_raw_header(n)
+                return self._buffer.write(obj)
+            if check(obj, memoryview):
+                n = len(obj) * obj.itemsize
+                if n >= 2**32:
+                    raise ValueError("Memoryview is too large")
+                self._pack_bin_header(n)
+                return self._buffer.write(obj)
+            if check(obj, float):
+                if self._use_float:
+                    return self._buffer.write(struct.pack(">Bf", 0xCA, obj))
+                return self._buffer.write(struct.pack(">Bd", 0xCB, obj))
+            if check(obj, (ExtType, Timestamp)):
+                if check(obj, Timestamp):
+                    code = -1
+                    data = obj.to_bytes()
+                else:
+                    code = obj.code
+                    data = obj.data
+                assert isinstance(code, int)
+                assert isinstance(data, bytes)
+                L = len(data)
+                if L == 1:
+                    self._buffer.write(b"\xd4")
+                elif L == 2:
+                    self._buffer.write(b"\xd5")
+                elif L == 4:
+                    self._buffer.write(b"\xd6")
+                elif L == 8:
+                    self._buffer.write(b"\xd7")
+                elif L == 16:
+                    self._buffer.write(b"\xd8")
+                elif L <= 0xFF:
+                    self._buffer.write(struct.pack(">BB", 0xC7, L))
+                elif L <= 0xFFFF:
+                    self._buffer.write(struct.pack(">BH", 0xC8, L))
+                else:
+                    self._buffer.write(struct.pack(">BI", 0xC9, L))
+                self._buffer.write(struct.pack("b", code))
+                self._buffer.write(data)
+                return
+            if check(obj, list_types):
+                n = len(obj)
+                self._pack_array_header(n)
+                for i in xrange(n):
+                    self._pack(obj[i], nest_limit - 1)
+                return
+            if check(obj, dict):
+                return self._pack_map_pairs(
+                    len(obj), dict_iteritems(obj), nest_limit - 1
+                )
+
+            if self._datetime and check(obj, _DateTime) and obj.tzinfo is not None:
+                obj = Timestamp.from_datetime(obj)
+                default_used = 1
+                continue
+
+            if not default_used and self._default is not None:
+                obj = self._default(obj)
+                default_used = 1
+                continue
+
+            if self._datetime and check(obj, _DateTime):
+                raise ValueError("Cannot serialize %r where tzinfo=None" % (obj,))
+
+            raise TypeError("Cannot serialize %r" % (obj,))
+
+    def pack(self, obj):
+        try:
+            self._pack(obj)
+        except:
+            self._buffer = StringIO()  # force reset
+            raise
+        if self._autoreset:
+            ret = self._buffer.getvalue()
+            self._buffer = StringIO()
+            return ret
+
+    def pack_map_pairs(self, pairs):
+        self._pack_map_pairs(len(pairs), pairs)
+        if self._autoreset:
+            ret = self._buffer.getvalue()
+            self._buffer = StringIO()
+            return ret
+
+    def pack_array_header(self, n):
+        if n >= 2**32:
+            raise ValueError
+        self._pack_array_header(n)
+        if self._autoreset:
+            ret = self._buffer.getvalue()
+            self._buffer = StringIO()
+            return ret
+
+    def pack_map_header(self, n):
+        if n >= 2**32:
+            raise ValueError
+        self._pack_map_header(n)
+        if self._autoreset:
+            ret = self._buffer.getvalue()
+            self._buffer = StringIO()
+            return ret
+
+    def pack_ext_type(self, typecode, data):
+        if not isinstance(typecode, int):
+            raise TypeError("typecode must have int type.")
+        if not 0 <= typecode <= 127:
+            raise ValueError("typecode should be 0-127")
+        if not isinstance(data, bytes):
+            raise TypeError("data must have bytes type")
+        L = len(data)
+        if L > 0xFFFFFFFF:
+            raise ValueError("Too large data")
+        if L == 1:
+            self._buffer.write(b"\xd4")
+        elif L == 2:
+            self._buffer.write(b"\xd5")
+        elif L == 4:
+            self._buffer.write(b"\xd6")
+        elif L == 8:
+            self._buffer.write(b"\xd7")
+        elif L == 16:
+            self._buffer.write(b"\xd8")
+        elif L <= 0xFF:
+            self._buffer.write(b"\xc7" + struct.pack("B", L))
+        elif L <= 0xFFFF:
+            self._buffer.write(b"\xc8" + struct.pack(">H", L))
+        else:
+            self._buffer.write(b"\xc9" + struct.pack(">I", L))
+        self._buffer.write(struct.pack("B", typecode))
+        self._buffer.write(data)
+
+    def _pack_array_header(self, n):
+        if n <= 0x0F:
+            return self._buffer.write(struct.pack("B", 0x90 + n))
+        if n <= 0xFFFF:
+            return self._buffer.write(struct.pack(">BH", 0xDC, n))
+        if n <= 0xFFFFFFFF:
+            return self._buffer.write(struct.pack(">BI", 0xDD, n))
+        raise ValueError("Array is too large")
+
+    def _pack_map_header(self, n):
+        if n <= 0x0F:
+            return self._buffer.write(struct.pack("B", 0x80 + n))
+        if n <= 0xFFFF:
+            return self._buffer.write(struct.pack(">BH", 0xDE, n))
+        if n <= 0xFFFFFFFF:
+            return self._buffer.write(struct.pack(">BI", 0xDF, n))
+        raise ValueError("Dict is too large")
+
+    def _pack_map_pairs(self, n, pairs, nest_limit=DEFAULT_RECURSE_LIMIT):
+        self._pack_map_header(n)
+        for (k, v) in pairs:
+            self._pack(k, nest_limit - 1)
+            self._pack(v, nest_limit - 1)
+
+    def _pack_raw_header(self, n):
+        if n <= 0x1F:
+            self._buffer.write(struct.pack("B", 0xA0 + n))
+        elif self._use_bin_type and n <= 0xFF:
+            self._buffer.write(struct.pack(">BB", 0xD9, n))
+        elif n <= 0xFFFF:
+            self._buffer.write(struct.pack(">BH", 0xDA, n))
+        elif n <= 0xFFFFFFFF:
+            self._buffer.write(struct.pack(">BI", 0xDB, n))
+        else:
+            raise ValueError("Raw is too large")
+
+    def _pack_bin_header(self, n):
+        if not self._use_bin_type:
+            return self._pack_raw_header(n)
+        elif n <= 0xFF:
+            return self._buffer.write(struct.pack(">BB", 0xC4, n))
+        elif n <= 0xFFFF:
+            return self._buffer.write(struct.pack(">BH", 0xC5, n))
+        elif n <= 0xFFFFFFFF:
+            return self._buffer.write(struct.pack(">BI", 0xC6, n))
+        else:
+            raise ValueError("Bin is too large")
+
+    def bytes(self):
+        """Return internal buffer contents as bytes object"""
+        return self._buffer.getvalue()
+
+    def reset(self):
+        """Reset internal buffer.
+
+        This method is useful only when autoreset=False.
+        """
+        self._buffer = StringIO()
+
+    def getbuffer(self):
+        """Return view of internal buffer."""
+        if USING_STRINGBUILDER or PY2:
+            return memoryview(self.bytes())
+        else:
+            return self._buffer.getbuffer()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/__about__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/__about__.py
new file mode 100644
index 0000000000000000000000000000000000000000..3551bc2d29846441299cf57b397b02fc164c99b9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/__about__.py
@@ -0,0 +1,26 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+__all__ = [
+    "__title__",
+    "__summary__",
+    "__uri__",
+    "__version__",
+    "__author__",
+    "__email__",
+    "__license__",
+    "__copyright__",
+]
+
+__title__ = "packaging"
+__summary__ = "Core utilities for Python packages"
+__uri__ = "https://github.com/pypa/packaging"
+
+__version__ = "21.3"
+
+__author__ = "Donald Stufft and individual contributors"
+__email__ = "donald@stufft.io"
+
+__license__ = "BSD-2-Clause or Apache-2.0"
+__copyright__ = "2014-2019 %s" % __author__
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..3c50c5dcfeeda2efed282200a5c5cc8c5f7542f7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/__init__.py
@@ -0,0 +1,25 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+from .__about__ import (
+    __author__,
+    __copyright__,
+    __email__,
+    __license__,
+    __summary__,
+    __title__,
+    __uri__,
+    __version__,
+)
+
+__all__ = [
+    "__title__",
+    "__summary__",
+    "__uri__",
+    "__version__",
+    "__author__",
+    "__email__",
+    "__license__",
+    "__copyright__",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_manylinux.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_manylinux.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c379aa6f69ff56c8f19612002c6e3e939ea6012
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_manylinux.py
@@ -0,0 +1,301 @@
+import collections
+import functools
+import os
+import re
+import struct
+import sys
+import warnings
+from typing import IO, Dict, Iterator, NamedTuple, Optional, Tuple
+
+
+# Python does not provide platform information at sufficient granularity to
+# identify the architecture of the running executable in some cases, so we
+# determine it dynamically by reading the information from the running
+# process. This only applies on Linux, which uses the ELF format.
+class _ELFFileHeader:
+    # https://en.wikipedia.org/wiki/Executable_and_Linkable_Format#File_header
+    class _InvalidELFFileHeader(ValueError):
+        """
+        An invalid ELF file header was found.
+        """
+
+    ELF_MAGIC_NUMBER = 0x7F454C46
+    ELFCLASS32 = 1
+    ELFCLASS64 = 2
+    ELFDATA2LSB = 1
+    ELFDATA2MSB = 2
+    EM_386 = 3
+    EM_S390 = 22
+    EM_ARM = 40
+    EM_X86_64 = 62
+    EF_ARM_ABIMASK = 0xFF000000
+    EF_ARM_ABI_VER5 = 0x05000000
+    EF_ARM_ABI_FLOAT_HARD = 0x00000400
+
+    def __init__(self, file: IO[bytes]) -> None:
+        def unpack(fmt: str) -> int:
+            try:
+                data = file.read(struct.calcsize(fmt))
+                result: Tuple[int, ...] = struct.unpack(fmt, data)
+            except struct.error:
+                raise _ELFFileHeader._InvalidELFFileHeader()
+            return result[0]
+
+        self.e_ident_magic = unpack(">I")
+        if self.e_ident_magic != self.ELF_MAGIC_NUMBER:
+            raise _ELFFileHeader._InvalidELFFileHeader()
+        self.e_ident_class = unpack("B")
+        if self.e_ident_class not in {self.ELFCLASS32, self.ELFCLASS64}:
+            raise _ELFFileHeader._InvalidELFFileHeader()
+        self.e_ident_data = unpack("B")
+        if self.e_ident_data not in {self.ELFDATA2LSB, self.ELFDATA2MSB}:
+            raise _ELFFileHeader._InvalidELFFileHeader()
+        self.e_ident_version = unpack("B")
+        self.e_ident_osabi = unpack("B")
+        self.e_ident_abiversion = unpack("B")
+        self.e_ident_pad = file.read(7)
+        format_h = "H"
+        format_i = "I"
+        format_q = "Q"
+        format_p = format_i if self.e_ident_class == self.ELFCLASS32 else format_q
+        self.e_type = unpack(format_h)
+        self.e_machine = unpack(format_h)
+        self.e_version = unpack(format_i)
+        self.e_entry = unpack(format_p)
+        self.e_phoff = unpack(format_p)
+        self.e_shoff = unpack(format_p)
+        self.e_flags = unpack(format_i)
+        self.e_ehsize = unpack(format_h)
+        self.e_phentsize = unpack(format_h)
+        self.e_phnum = unpack(format_h)
+        self.e_shentsize = unpack(format_h)
+        self.e_shnum = unpack(format_h)
+        self.e_shstrndx = unpack(format_h)
+
+
+def _get_elf_header() -> Optional[_ELFFileHeader]:
+    try:
+        with open(sys.executable, "rb") as f:
+            elf_header = _ELFFileHeader(f)
+    except (OSError, TypeError, _ELFFileHeader._InvalidELFFileHeader):
+        return None
+    return elf_header
+
+
+def _is_linux_armhf() -> bool:
+    # hard-float ABI can be detected from the ELF header of the running
+    # process
+    # https://static.docs.arm.com/ihi0044/g/aaelf32.pdf
+    elf_header = _get_elf_header()
+    if elf_header is None:
+        return False
+    result = elf_header.e_ident_class == elf_header.ELFCLASS32
+    result &= elf_header.e_ident_data == elf_header.ELFDATA2LSB
+    result &= elf_header.e_machine == elf_header.EM_ARM
+    result &= (
+        elf_header.e_flags & elf_header.EF_ARM_ABIMASK
+    ) == elf_header.EF_ARM_ABI_VER5
+    result &= (
+        elf_header.e_flags & elf_header.EF_ARM_ABI_FLOAT_HARD
+    ) == elf_header.EF_ARM_ABI_FLOAT_HARD
+    return result
+
+
+def _is_linux_i686() -> bool:
+    elf_header = _get_elf_header()
+    if elf_header is None:
+        return False
+    result = elf_header.e_ident_class == elf_header.ELFCLASS32
+    result &= elf_header.e_ident_data == elf_header.ELFDATA2LSB
+    result &= elf_header.e_machine == elf_header.EM_386
+    return result
+
+
+def _have_compatible_abi(arch: str) -> bool:
+    if arch == "armv7l":
+        return _is_linux_armhf()
+    if arch == "i686":
+        return _is_linux_i686()
+    return arch in {"x86_64", "aarch64", "ppc64", "ppc64le", "s390x"}
+
+
+# If glibc ever changes its major version, we need to know what the last
+# minor version was, so we can build the complete list of all versions.
+# For now, guess what the highest minor version might be, assume it will
+# be 50 for testing. Once this actually happens, update the dictionary
+# with the actual value.
+_LAST_GLIBC_MINOR: Dict[int, int] = collections.defaultdict(lambda: 50)
+
+
+class _GLibCVersion(NamedTuple):
+    major: int
+    minor: int
+
+
+def _glibc_version_string_confstr() -> Optional[str]:
+    """
+    Primary implementation of glibc_version_string using os.confstr.
+    """
+    # os.confstr is quite a bit faster than ctypes.DLL. It's also less likely
+    # to be broken or missing. This strategy is used in the standard library
+    # platform module.
+    # https://github.com/python/cpython/blob/fcf1d003bf4f0100c/Lib/platform.py#L175-L183
+    try:
+        # os.confstr("CS_GNU_LIBC_VERSION") returns a string like "glibc 2.17".
+        version_string = os.confstr("CS_GNU_LIBC_VERSION")
+        assert version_string is not None
+        _, version = version_string.split()
+    except (AssertionError, AttributeError, OSError, ValueError):
+        # os.confstr() or CS_GNU_LIBC_VERSION not available (or a bad value)...
+        return None
+    return version
+
+
+def _glibc_version_string_ctypes() -> Optional[str]:
+    """
+    Fallback implementation of glibc_version_string using ctypes.
+    """
+    try:
+        import ctypes
+    except ImportError:
+        return None
+
+    # ctypes.CDLL(None) internally calls dlopen(NULL), and as the dlopen
+    # manpage says, "If filename is NULL, then the returned handle is for the
+    # main program". This way we can let the linker do the work to figure out
+    # which libc our process is actually using.
+    #
+    # We must also handle the special case where the executable is not a
+    # dynamically linked executable. This can occur when using musl libc,
+    # for example. In this situation, dlopen() will error, leading to an
+    # OSError. Interestingly, at least in the case of musl, there is no
+    # errno set on the OSError. The single string argument used to construct
+    # OSError comes from libc itself and is therefore not portable to
+    # hard code here. In any case, failure to call dlopen() means we
+    # can proceed, so we bail on our attempt.
+    try:
+        process_namespace = ctypes.CDLL(None)
+    except OSError:
+        return None
+
+    try:
+        gnu_get_libc_version = process_namespace.gnu_get_libc_version
+    except AttributeError:
+        # Symbol doesn't exist -> therefore, we are not linked to
+        # glibc.
+        return None
+
+    # Call gnu_get_libc_version, which returns a string like "2.5"
+    gnu_get_libc_version.restype = ctypes.c_char_p
+    version_str: str = gnu_get_libc_version()
+    # py2 / py3 compatibility:
+    if not isinstance(version_str, str):
+        version_str = version_str.decode("ascii")
+
+    return version_str
+
+
+def _glibc_version_string() -> Optional[str]:
+    """Returns glibc version string, or None if not using glibc."""
+    return _glibc_version_string_confstr() or _glibc_version_string_ctypes()
+
+
+def _parse_glibc_version(version_str: str) -> Tuple[int, int]:
+    """Parse glibc version.
+
+    We use a regexp instead of str.split because we want to discard any
+    random junk that might come after the minor version -- this might happen
+    in patched/forked versions of glibc (e.g. Linaro's version of glibc
+    uses version strings like "2.20-2014.11"). See gh-3588.
+    """
+    m = re.match(r"(?P[0-9]+)\.(?P[0-9]+)", version_str)
+    if not m:
+        warnings.warn(
+            "Expected glibc version with 2 components major.minor,"
+            " got: %s" % version_str,
+            RuntimeWarning,
+        )
+        return -1, -1
+    return int(m.group("major")), int(m.group("minor"))
+
+
+@functools.lru_cache()
+def _get_glibc_version() -> Tuple[int, int]:
+    version_str = _glibc_version_string()
+    if version_str is None:
+        return (-1, -1)
+    return _parse_glibc_version(version_str)
+
+
+# From PEP 513, PEP 600
+def _is_compatible(name: str, arch: str, version: _GLibCVersion) -> bool:
+    sys_glibc = _get_glibc_version()
+    if sys_glibc < version:
+        return False
+    # Check for presence of _manylinux module.
+    try:
+        import _manylinux  # noqa
+    except ImportError:
+        return True
+    if hasattr(_manylinux, "manylinux_compatible"):
+        result = _manylinux.manylinux_compatible(version[0], version[1], arch)
+        if result is not None:
+            return bool(result)
+        return True
+    if version == _GLibCVersion(2, 5):
+        if hasattr(_manylinux, "manylinux1_compatible"):
+            return bool(_manylinux.manylinux1_compatible)
+    if version == _GLibCVersion(2, 12):
+        if hasattr(_manylinux, "manylinux2010_compatible"):
+            return bool(_manylinux.manylinux2010_compatible)
+    if version == _GLibCVersion(2, 17):
+        if hasattr(_manylinux, "manylinux2014_compatible"):
+            return bool(_manylinux.manylinux2014_compatible)
+    return True
+
+
+_LEGACY_MANYLINUX_MAP = {
+    # CentOS 7 w/ glibc 2.17 (PEP 599)
+    (2, 17): "manylinux2014",
+    # CentOS 6 w/ glibc 2.12 (PEP 571)
+    (2, 12): "manylinux2010",
+    # CentOS 5 w/ glibc 2.5 (PEP 513)
+    (2, 5): "manylinux1",
+}
+
+
+def platform_tags(linux: str, arch: str) -> Iterator[str]:
+    if not _have_compatible_abi(arch):
+        return
+    # Oldest glibc to be supported regardless of architecture is (2, 17).
+    too_old_glibc2 = _GLibCVersion(2, 16)
+    if arch in {"x86_64", "i686"}:
+        # On x86/i686 also oldest glibc to be supported is (2, 5).
+        too_old_glibc2 = _GLibCVersion(2, 4)
+    current_glibc = _GLibCVersion(*_get_glibc_version())
+    glibc_max_list = [current_glibc]
+    # We can assume compatibility across glibc major versions.
+    # https://sourceware.org/bugzilla/show_bug.cgi?id=24636
+    #
+    # Build a list of maximum glibc versions so that we can
+    # output the canonical list of all glibc from current_glibc
+    # down to too_old_glibc2, including all intermediary versions.
+    for glibc_major in range(current_glibc.major - 1, 1, -1):
+        glibc_minor = _LAST_GLIBC_MINOR[glibc_major]
+        glibc_max_list.append(_GLibCVersion(glibc_major, glibc_minor))
+    for glibc_max in glibc_max_list:
+        if glibc_max.major == too_old_glibc2.major:
+            min_minor = too_old_glibc2.minor
+        else:
+            # For other glibc major versions oldest supported is (x, 0).
+            min_minor = -1
+        for glibc_minor in range(glibc_max.minor, min_minor, -1):
+            glibc_version = _GLibCVersion(glibc_max.major, glibc_minor)
+            tag = "manylinux_{}_{}".format(*glibc_version)
+            if _is_compatible(tag, arch, glibc_version):
+                yield linux.replace("linux", tag)
+            # Handle the legacy manylinux1, manylinux2010, manylinux2014 tags.
+            if glibc_version in _LEGACY_MANYLINUX_MAP:
+                legacy_tag = _LEGACY_MANYLINUX_MAP[glibc_version]
+                if _is_compatible(legacy_tag, arch, glibc_version):
+                    yield linux.replace("linux", legacy_tag)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_musllinux.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_musllinux.py
new file mode 100644
index 0000000000000000000000000000000000000000..8ac3059ba3c246b9a5a6fb8d14936bb07777191e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_musllinux.py
@@ -0,0 +1,136 @@
+"""PEP 656 support.
+
+This module implements logic to detect if the currently running Python is
+linked against musl, and what musl version is used.
+"""
+
+import contextlib
+import functools
+import operator
+import os
+import re
+import struct
+import subprocess
+import sys
+from typing import IO, Iterator, NamedTuple, Optional, Tuple
+
+
+def _read_unpacked(f: IO[bytes], fmt: str) -> Tuple[int, ...]:
+    return struct.unpack(fmt, f.read(struct.calcsize(fmt)))
+
+
+def _parse_ld_musl_from_elf(f: IO[bytes]) -> Optional[str]:
+    """Detect musl libc location by parsing the Python executable.
+
+    Based on: https://gist.github.com/lyssdod/f51579ae8d93c8657a5564aefc2ffbca
+    ELF header: https://refspecs.linuxfoundation.org/elf/gabi4+/ch4.eheader.html
+    """
+    f.seek(0)
+    try:
+        ident = _read_unpacked(f, "16B")
+    except struct.error:
+        return None
+    if ident[:4] != tuple(b"\x7fELF"):  # Invalid magic, not ELF.
+        return None
+    f.seek(struct.calcsize("HHI"), 1)  # Skip file type, machine, and version.
+
+    try:
+        # e_fmt: Format for program header.
+        # p_fmt: Format for section header.
+        # p_idx: Indexes to find p_type, p_offset, and p_filesz.
+        e_fmt, p_fmt, p_idx = {
+            1: ("IIIIHHH", "IIIIIIII", (0, 1, 4)),  # 32-bit.
+            2: ("QQQIHHH", "IIQQQQQQ", (0, 2, 5)),  # 64-bit.
+        }[ident[4]]
+    except KeyError:
+        return None
+    else:
+        p_get = operator.itemgetter(*p_idx)
+
+    # Find the interpreter section and return its content.
+    try:
+        _, e_phoff, _, _, _, e_phentsize, e_phnum = _read_unpacked(f, e_fmt)
+    except struct.error:
+        return None
+    for i in range(e_phnum + 1):
+        f.seek(e_phoff + e_phentsize * i)
+        try:
+            p_type, p_offset, p_filesz = p_get(_read_unpacked(f, p_fmt))
+        except struct.error:
+            return None
+        if p_type != 3:  # Not PT_INTERP.
+            continue
+        f.seek(p_offset)
+        interpreter = os.fsdecode(f.read(p_filesz)).strip("\0")
+        if "musl" not in interpreter:
+            return None
+        return interpreter
+    return None
+
+
+class _MuslVersion(NamedTuple):
+    major: int
+    minor: int
+
+
+def _parse_musl_version(output: str) -> Optional[_MuslVersion]:
+    lines = [n for n in (n.strip() for n in output.splitlines()) if n]
+    if len(lines) < 2 or lines[0][:4] != "musl":
+        return None
+    m = re.match(r"Version (\d+)\.(\d+)", lines[1])
+    if not m:
+        return None
+    return _MuslVersion(major=int(m.group(1)), minor=int(m.group(2)))
+
+
+@functools.lru_cache()
+def _get_musl_version(executable: str) -> Optional[_MuslVersion]:
+    """Detect currently-running musl runtime version.
+
+    This is done by checking the specified executable's dynamic linking
+    information, and invoking the loader to parse its output for a version
+    string. If the loader is musl, the output would be something like::
+
+        musl libc (x86_64)
+        Version 1.2.2
+        Dynamic Program Loader
+    """
+    with contextlib.ExitStack() as stack:
+        try:
+            f = stack.enter_context(open(executable, "rb"))
+        except OSError:
+            return None
+        ld = _parse_ld_musl_from_elf(f)
+    if not ld:
+        return None
+    proc = subprocess.run([ld], stderr=subprocess.PIPE, universal_newlines=True)
+    return _parse_musl_version(proc.stderr)
+
+
+def platform_tags(arch: str) -> Iterator[str]:
+    """Generate musllinux tags compatible to the current platform.
+
+    :param arch: Should be the part of platform tag after the ``linux_``
+        prefix, e.g. ``x86_64``. The ``linux_`` prefix is assumed as a
+        prerequisite for the current platform to be musllinux-compatible.
+
+    :returns: An iterator of compatible musllinux tags.
+    """
+    sys_musl = _get_musl_version(sys.executable)
+    if sys_musl is None:  # Python not dynamically linked against musl.
+        return
+    for minor in range(sys_musl.minor, -1, -1):
+        yield f"musllinux_{sys_musl.major}_{minor}_{arch}"
+
+
+if __name__ == "__main__":  # pragma: no cover
+    import sysconfig
+
+    plat = sysconfig.get_platform()
+    assert plat.startswith("linux-"), "not linux"
+
+    print("plat:", plat)
+    print("musl:", _get_musl_version(sys.executable))
+    print("tags:", end=" ")
+    for t in platform_tags(re.sub(r"[.-]", "_", plat.split("-", 1)[-1])):
+        print(t, end="\n      ")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_structures.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_structures.py
new file mode 100644
index 0000000000000000000000000000000000000000..90a6465f9682c886363eea5327dac64bf623a6ff
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/_structures.py
@@ -0,0 +1,61 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+
+class InfinityType:
+    def __repr__(self) -> str:
+        return "Infinity"
+
+    def __hash__(self) -> int:
+        return hash(repr(self))
+
+    def __lt__(self, other: object) -> bool:
+        return False
+
+    def __le__(self, other: object) -> bool:
+        return False
+
+    def __eq__(self, other: object) -> bool:
+        return isinstance(other, self.__class__)
+
+    def __gt__(self, other: object) -> bool:
+        return True
+
+    def __ge__(self, other: object) -> bool:
+        return True
+
+    def __neg__(self: object) -> "NegativeInfinityType":
+        return NegativeInfinity
+
+
+Infinity = InfinityType()
+
+
+class NegativeInfinityType:
+    def __repr__(self) -> str:
+        return "-Infinity"
+
+    def __hash__(self) -> int:
+        return hash(repr(self))
+
+    def __lt__(self, other: object) -> bool:
+        return True
+
+    def __le__(self, other: object) -> bool:
+        return True
+
+    def __eq__(self, other: object) -> bool:
+        return isinstance(other, self.__class__)
+
+    def __gt__(self, other: object) -> bool:
+        return False
+
+    def __ge__(self, other: object) -> bool:
+        return False
+
+    def __neg__(self: object) -> InfinityType:
+        return Infinity
+
+
+NegativeInfinity = NegativeInfinityType()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/markers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/markers.py
new file mode 100644
index 0000000000000000000000000000000000000000..540e7a4dc79d02a820e291b57c43335d5aa25a41
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/markers.py
@@ -0,0 +1,304 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+import operator
+import os
+import platform
+import sys
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+
+from pip._vendor.pyparsing import (  # noqa: N817
+    Forward,
+    Group,
+    Literal as L,
+    ParseException,
+    ParseResults,
+    QuotedString,
+    ZeroOrMore,
+    stringEnd,
+    stringStart,
+)
+
+from .specifiers import InvalidSpecifier, Specifier
+
+__all__ = [
+    "InvalidMarker",
+    "UndefinedComparison",
+    "UndefinedEnvironmentName",
+    "Marker",
+    "default_environment",
+]
+
+Operator = Callable[[str, str], bool]
+
+
+class InvalidMarker(ValueError):
+    """
+    An invalid marker was found, users should refer to PEP 508.
+    """
+
+
+class UndefinedComparison(ValueError):
+    """
+    An invalid operation was attempted on a value that doesn't support it.
+    """
+
+
+class UndefinedEnvironmentName(ValueError):
+    """
+    A name was attempted to be used that does not exist inside of the
+    environment.
+    """
+
+
+class Node:
+    def __init__(self, value: Any) -> None:
+        self.value = value
+
+    def __str__(self) -> str:
+        return str(self.value)
+
+    def __repr__(self) -> str:
+        return f"<{self.__class__.__name__}('{self}')>"
+
+    def serialize(self) -> str:
+        raise NotImplementedError
+
+
+class Variable(Node):
+    def serialize(self) -> str:
+        return str(self)
+
+
+class Value(Node):
+    def serialize(self) -> str:
+        return f'"{self}"'
+
+
+class Op(Node):
+    def serialize(self) -> str:
+        return str(self)
+
+
+VARIABLE = (
+    L("implementation_version")
+    | L("platform_python_implementation")
+    | L("implementation_name")
+    | L("python_full_version")
+    | L("platform_release")
+    | L("platform_version")
+    | L("platform_machine")
+    | L("platform_system")
+    | L("python_version")
+    | L("sys_platform")
+    | L("os_name")
+    | L("os.name")  # PEP-345
+    | L("sys.platform")  # PEP-345
+    | L("platform.version")  # PEP-345
+    | L("platform.machine")  # PEP-345
+    | L("platform.python_implementation")  # PEP-345
+    | L("python_implementation")  # undocumented setuptools legacy
+    | L("extra")  # PEP-508
+)
+ALIASES = {
+    "os.name": "os_name",
+    "sys.platform": "sys_platform",
+    "platform.version": "platform_version",
+    "platform.machine": "platform_machine",
+    "platform.python_implementation": "platform_python_implementation",
+    "python_implementation": "platform_python_implementation",
+}
+VARIABLE.setParseAction(lambda s, l, t: Variable(ALIASES.get(t[0], t[0])))
+
+VERSION_CMP = (
+    L("===") | L("==") | L(">=") | L("<=") | L("!=") | L("~=") | L(">") | L("<")
+)
+
+MARKER_OP = VERSION_CMP | L("not in") | L("in")
+MARKER_OP.setParseAction(lambda s, l, t: Op(t[0]))
+
+MARKER_VALUE = QuotedString("'") | QuotedString('"')
+MARKER_VALUE.setParseAction(lambda s, l, t: Value(t[0]))
+
+BOOLOP = L("and") | L("or")
+
+MARKER_VAR = VARIABLE | MARKER_VALUE
+
+MARKER_ITEM = Group(MARKER_VAR + MARKER_OP + MARKER_VAR)
+MARKER_ITEM.setParseAction(lambda s, l, t: tuple(t[0]))
+
+LPAREN = L("(").suppress()
+RPAREN = L(")").suppress()
+
+MARKER_EXPR = Forward()
+MARKER_ATOM = MARKER_ITEM | Group(LPAREN + MARKER_EXPR + RPAREN)
+MARKER_EXPR << MARKER_ATOM + ZeroOrMore(BOOLOP + MARKER_EXPR)
+
+MARKER = stringStart + MARKER_EXPR + stringEnd
+
+
+def _coerce_parse_result(results: Union[ParseResults, List[Any]]) -> List[Any]:
+    if isinstance(results, ParseResults):
+        return [_coerce_parse_result(i) for i in results]
+    else:
+        return results
+
+
+def _format_marker(
+    marker: Union[List[str], Tuple[Node, ...], str], first: Optional[bool] = True
+) -> str:
+
+    assert isinstance(marker, (list, tuple, str))
+
+    # Sometimes we have a structure like [[...]] which is a single item list
+    # where the single item is itself it's own list. In that case we want skip
+    # the rest of this function so that we don't get extraneous () on the
+    # outside.
+    if (
+        isinstance(marker, list)
+        and len(marker) == 1
+        and isinstance(marker[0], (list, tuple))
+    ):
+        return _format_marker(marker[0])
+
+    if isinstance(marker, list):
+        inner = (_format_marker(m, first=False) for m in marker)
+        if first:
+            return " ".join(inner)
+        else:
+            return "(" + " ".join(inner) + ")"
+    elif isinstance(marker, tuple):
+        return " ".join([m.serialize() for m in marker])
+    else:
+        return marker
+
+
+_operators: Dict[str, Operator] = {
+    "in": lambda lhs, rhs: lhs in rhs,
+    "not in": lambda lhs, rhs: lhs not in rhs,
+    "<": operator.lt,
+    "<=": operator.le,
+    "==": operator.eq,
+    "!=": operator.ne,
+    ">=": operator.ge,
+    ">": operator.gt,
+}
+
+
+def _eval_op(lhs: str, op: Op, rhs: str) -> bool:
+    try:
+        spec = Specifier("".join([op.serialize(), rhs]))
+    except InvalidSpecifier:
+        pass
+    else:
+        return spec.contains(lhs)
+
+    oper: Optional[Operator] = _operators.get(op.serialize())
+    if oper is None:
+        raise UndefinedComparison(f"Undefined {op!r} on {lhs!r} and {rhs!r}.")
+
+    return oper(lhs, rhs)
+
+
+class Undefined:
+    pass
+
+
+_undefined = Undefined()
+
+
+def _get_env(environment: Dict[str, str], name: str) -> str:
+    value: Union[str, Undefined] = environment.get(name, _undefined)
+
+    if isinstance(value, Undefined):
+        raise UndefinedEnvironmentName(
+            f"{name!r} does not exist in evaluation environment."
+        )
+
+    return value
+
+
+def _evaluate_markers(markers: List[Any], environment: Dict[str, str]) -> bool:
+    groups: List[List[bool]] = [[]]
+
+    for marker in markers:
+        assert isinstance(marker, (list, tuple, str))
+
+        if isinstance(marker, list):
+            groups[-1].append(_evaluate_markers(marker, environment))
+        elif isinstance(marker, tuple):
+            lhs, op, rhs = marker
+
+            if isinstance(lhs, Variable):
+                lhs_value = _get_env(environment, lhs.value)
+                rhs_value = rhs.value
+            else:
+                lhs_value = lhs.value
+                rhs_value = _get_env(environment, rhs.value)
+
+            groups[-1].append(_eval_op(lhs_value, op, rhs_value))
+        else:
+            assert marker in ["and", "or"]
+            if marker == "or":
+                groups.append([])
+
+    return any(all(item) for item in groups)
+
+
+def format_full_version(info: "sys._version_info") -> str:
+    version = "{0.major}.{0.minor}.{0.micro}".format(info)
+    kind = info.releaselevel
+    if kind != "final":
+        version += kind[0] + str(info.serial)
+    return version
+
+
+def default_environment() -> Dict[str, str]:
+    iver = format_full_version(sys.implementation.version)
+    implementation_name = sys.implementation.name
+    return {
+        "implementation_name": implementation_name,
+        "implementation_version": iver,
+        "os_name": os.name,
+        "platform_machine": platform.machine(),
+        "platform_release": platform.release(),
+        "platform_system": platform.system(),
+        "platform_version": platform.version(),
+        "python_full_version": platform.python_version(),
+        "platform_python_implementation": platform.python_implementation(),
+        "python_version": ".".join(platform.python_version_tuple()[:2]),
+        "sys_platform": sys.platform,
+    }
+
+
+class Marker:
+    def __init__(self, marker: str) -> None:
+        try:
+            self._markers = _coerce_parse_result(MARKER.parseString(marker))
+        except ParseException as e:
+            raise InvalidMarker(
+                f"Invalid marker: {marker!r}, parse error at "
+                f"{marker[e.loc : e.loc + 8]!r}"
+            )
+
+    def __str__(self) -> str:
+        return _format_marker(self._markers)
+
+    def __repr__(self) -> str:
+        return f""
+
+    def evaluate(self, environment: Optional[Dict[str, str]] = None) -> bool:
+        """Evaluate a marker.
+
+        Return the boolean from evaluating the given marker against the
+        environment. environment is an optional argument to override all or
+        part of the determined environment.
+
+        The environment is determined from the current Python process.
+        """
+        current_environment = default_environment()
+        if environment is not None:
+            current_environment.update(environment)
+
+        return _evaluate_markers(self._markers, current_environment)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/requirements.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/requirements.py
new file mode 100644
index 0000000000000000000000000000000000000000..1eab7dd66d9bfdefea1a0e159303f1c09fa16d67
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/requirements.py
@@ -0,0 +1,146 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+import re
+import string
+import urllib.parse
+from typing import List, Optional as TOptional, Set
+
+from pip._vendor.pyparsing import (  # noqa
+    Combine,
+    Literal as L,
+    Optional,
+    ParseException,
+    Regex,
+    Word,
+    ZeroOrMore,
+    originalTextFor,
+    stringEnd,
+    stringStart,
+)
+
+from .markers import MARKER_EXPR, Marker
+from .specifiers import LegacySpecifier, Specifier, SpecifierSet
+
+
+class InvalidRequirement(ValueError):
+    """
+    An invalid requirement was found, users should refer to PEP 508.
+    """
+
+
+ALPHANUM = Word(string.ascii_letters + string.digits)
+
+LBRACKET = L("[").suppress()
+RBRACKET = L("]").suppress()
+LPAREN = L("(").suppress()
+RPAREN = L(")").suppress()
+COMMA = L(",").suppress()
+SEMICOLON = L(";").suppress()
+AT = L("@").suppress()
+
+PUNCTUATION = Word("-_.")
+IDENTIFIER_END = ALPHANUM | (ZeroOrMore(PUNCTUATION) + ALPHANUM)
+IDENTIFIER = Combine(ALPHANUM + ZeroOrMore(IDENTIFIER_END))
+
+NAME = IDENTIFIER("name")
+EXTRA = IDENTIFIER
+
+URI = Regex(r"[^ ]+")("url")
+URL = AT + URI
+
+EXTRAS_LIST = EXTRA + ZeroOrMore(COMMA + EXTRA)
+EXTRAS = (LBRACKET + Optional(EXTRAS_LIST) + RBRACKET)("extras")
+
+VERSION_PEP440 = Regex(Specifier._regex_str, re.VERBOSE | re.IGNORECASE)
+VERSION_LEGACY = Regex(LegacySpecifier._regex_str, re.VERBOSE | re.IGNORECASE)
+
+VERSION_ONE = VERSION_PEP440 ^ VERSION_LEGACY
+VERSION_MANY = Combine(
+    VERSION_ONE + ZeroOrMore(COMMA + VERSION_ONE), joinString=",", adjacent=False
+)("_raw_spec")
+_VERSION_SPEC = Optional((LPAREN + VERSION_MANY + RPAREN) | VERSION_MANY)
+_VERSION_SPEC.setParseAction(lambda s, l, t: t._raw_spec or "")
+
+VERSION_SPEC = originalTextFor(_VERSION_SPEC)("specifier")
+VERSION_SPEC.setParseAction(lambda s, l, t: t[1])
+
+MARKER_EXPR = originalTextFor(MARKER_EXPR())("marker")
+MARKER_EXPR.setParseAction(
+    lambda s, l, t: Marker(s[t._original_start : t._original_end])
+)
+MARKER_SEPARATOR = SEMICOLON
+MARKER = MARKER_SEPARATOR + MARKER_EXPR
+
+VERSION_AND_MARKER = VERSION_SPEC + Optional(MARKER)
+URL_AND_MARKER = URL + Optional(MARKER)
+
+NAMED_REQUIREMENT = NAME + Optional(EXTRAS) + (URL_AND_MARKER | VERSION_AND_MARKER)
+
+REQUIREMENT = stringStart + NAMED_REQUIREMENT + stringEnd
+# pyparsing isn't thread safe during initialization, so we do it eagerly, see
+# issue #104
+REQUIREMENT.parseString("x[]")
+
+
+class Requirement:
+    """Parse a requirement.
+
+    Parse a given requirement string into its parts, such as name, specifier,
+    URL, and extras. Raises InvalidRequirement on a badly-formed requirement
+    string.
+    """
+
+    # TODO: Can we test whether something is contained within a requirement?
+    #       If so how do we do that? Do we need to test against the _name_ of
+    #       the thing as well as the version? What about the markers?
+    # TODO: Can we normalize the name and extra name?
+
+    def __init__(self, requirement_string: str) -> None:
+        try:
+            req = REQUIREMENT.parseString(requirement_string)
+        except ParseException as e:
+            raise InvalidRequirement(
+                f'Parse error at "{ requirement_string[e.loc : e.loc + 8]!r}": {e.msg}'
+            )
+
+        self.name: str = req.name
+        if req.url:
+            parsed_url = urllib.parse.urlparse(req.url)
+            if parsed_url.scheme == "file":
+                if urllib.parse.urlunparse(parsed_url) != req.url:
+                    raise InvalidRequirement("Invalid URL given")
+            elif not (parsed_url.scheme and parsed_url.netloc) or (
+                not parsed_url.scheme and not parsed_url.netloc
+            ):
+                raise InvalidRequirement(f"Invalid URL: {req.url}")
+            self.url: TOptional[str] = req.url
+        else:
+            self.url = None
+        self.extras: Set[str] = set(req.extras.asList() if req.extras else [])
+        self.specifier: SpecifierSet = SpecifierSet(req.specifier)
+        self.marker: TOptional[Marker] = req.marker if req.marker else None
+
+    def __str__(self) -> str:
+        parts: List[str] = [self.name]
+
+        if self.extras:
+            formatted_extras = ",".join(sorted(self.extras))
+            parts.append(f"[{formatted_extras}]")
+
+        if self.specifier:
+            parts.append(str(self.specifier))
+
+        if self.url:
+            parts.append(f"@ {self.url}")
+            if self.marker:
+                parts.append(" ")
+
+        if self.marker:
+            parts.append(f"; {self.marker}")
+
+        return "".join(parts)
+
+    def __repr__(self) -> str:
+        return f""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/specifiers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/specifiers.py
new file mode 100644
index 0000000000000000000000000000000000000000..0e218a6f9f75ea2060a8b08d1f1a043fdad68df8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/specifiers.py
@@ -0,0 +1,802 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+import abc
+import functools
+import itertools
+import re
+import warnings
+from typing import (
+    Callable,
+    Dict,
+    Iterable,
+    Iterator,
+    List,
+    Optional,
+    Pattern,
+    Set,
+    Tuple,
+    TypeVar,
+    Union,
+)
+
+from .utils import canonicalize_version
+from .version import LegacyVersion, Version, parse
+
+ParsedVersion = Union[Version, LegacyVersion]
+UnparsedVersion = Union[Version, LegacyVersion, str]
+VersionTypeVar = TypeVar("VersionTypeVar", bound=UnparsedVersion)
+CallableOperator = Callable[[ParsedVersion, str], bool]
+
+
+class InvalidSpecifier(ValueError):
+    """
+    An invalid specifier was found, users should refer to PEP 440.
+    """
+
+
+class BaseSpecifier(metaclass=abc.ABCMeta):
+    @abc.abstractmethod
+    def __str__(self) -> str:
+        """
+        Returns the str representation of this Specifier like object. This
+        should be representative of the Specifier itself.
+        """
+
+    @abc.abstractmethod
+    def __hash__(self) -> int:
+        """
+        Returns a hash value for this Specifier like object.
+        """
+
+    @abc.abstractmethod
+    def __eq__(self, other: object) -> bool:
+        """
+        Returns a boolean representing whether or not the two Specifier like
+        objects are equal.
+        """
+
+    @abc.abstractproperty
+    def prereleases(self) -> Optional[bool]:
+        """
+        Returns whether or not pre-releases as a whole are allowed by this
+        specifier.
+        """
+
+    @prereleases.setter
+    def prereleases(self, value: bool) -> None:
+        """
+        Sets whether or not pre-releases as a whole are allowed by this
+        specifier.
+        """
+
+    @abc.abstractmethod
+    def contains(self, item: str, prereleases: Optional[bool] = None) -> bool:
+        """
+        Determines if the given item is contained within this specifier.
+        """
+
+    @abc.abstractmethod
+    def filter(
+        self, iterable: Iterable[VersionTypeVar], prereleases: Optional[bool] = None
+    ) -> Iterable[VersionTypeVar]:
+        """
+        Takes an iterable of items and filters them so that only items which
+        are contained within this specifier are allowed in it.
+        """
+
+
+class _IndividualSpecifier(BaseSpecifier):
+
+    _operators: Dict[str, str] = {}
+    _regex: Pattern[str]
+
+    def __init__(self, spec: str = "", prereleases: Optional[bool] = None) -> None:
+        match = self._regex.search(spec)
+        if not match:
+            raise InvalidSpecifier(f"Invalid specifier: '{spec}'")
+
+        self._spec: Tuple[str, str] = (
+            match.group("operator").strip(),
+            match.group("version").strip(),
+        )
+
+        # Store whether or not this Specifier should accept prereleases
+        self._prereleases = prereleases
+
+    def __repr__(self) -> str:
+        pre = (
+            f", prereleases={self.prereleases!r}"
+            if self._prereleases is not None
+            else ""
+        )
+
+        return f"<{self.__class__.__name__}({str(self)!r}{pre})>"
+
+    def __str__(self) -> str:
+        return "{}{}".format(*self._spec)
+
+    @property
+    def _canonical_spec(self) -> Tuple[str, str]:
+        return self._spec[0], canonicalize_version(self._spec[1])
+
+    def __hash__(self) -> int:
+        return hash(self._canonical_spec)
+
+    def __eq__(self, other: object) -> bool:
+        if isinstance(other, str):
+            try:
+                other = self.__class__(str(other))
+            except InvalidSpecifier:
+                return NotImplemented
+        elif not isinstance(other, self.__class__):
+            return NotImplemented
+
+        return self._canonical_spec == other._canonical_spec
+
+    def _get_operator(self, op: str) -> CallableOperator:
+        operator_callable: CallableOperator = getattr(
+            self, f"_compare_{self._operators[op]}"
+        )
+        return operator_callable
+
+    def _coerce_version(self, version: UnparsedVersion) -> ParsedVersion:
+        if not isinstance(version, (LegacyVersion, Version)):
+            version = parse(version)
+        return version
+
+    @property
+    def operator(self) -> str:
+        return self._spec[0]
+
+    @property
+    def version(self) -> str:
+        return self._spec[1]
+
+    @property
+    def prereleases(self) -> Optional[bool]:
+        return self._prereleases
+
+    @prereleases.setter
+    def prereleases(self, value: bool) -> None:
+        self._prereleases = value
+
+    def __contains__(self, item: str) -> bool:
+        return self.contains(item)
+
+    def contains(
+        self, item: UnparsedVersion, prereleases: Optional[bool] = None
+    ) -> bool:
+
+        # Determine if prereleases are to be allowed or not.
+        if prereleases is None:
+            prereleases = self.prereleases
+
+        # Normalize item to a Version or LegacyVersion, this allows us to have
+        # a shortcut for ``"2.0" in Specifier(">=2")
+        normalized_item = self._coerce_version(item)
+
+        # Determine if we should be supporting prereleases in this specifier
+        # or not, if we do not support prereleases than we can short circuit
+        # logic if this version is a prereleases.
+        if normalized_item.is_prerelease and not prereleases:
+            return False
+
+        # Actually do the comparison to determine if this item is contained
+        # within this Specifier or not.
+        operator_callable: CallableOperator = self._get_operator(self.operator)
+        return operator_callable(normalized_item, self.version)
+
+    def filter(
+        self, iterable: Iterable[VersionTypeVar], prereleases: Optional[bool] = None
+    ) -> Iterable[VersionTypeVar]:
+
+        yielded = False
+        found_prereleases = []
+
+        kw = {"prereleases": prereleases if prereleases is not None else True}
+
+        # Attempt to iterate over all the values in the iterable and if any of
+        # them match, yield them.
+        for version in iterable:
+            parsed_version = self._coerce_version(version)
+
+            if self.contains(parsed_version, **kw):
+                # If our version is a prerelease, and we were not set to allow
+                # prereleases, then we'll store it for later in case nothing
+                # else matches this specifier.
+                if parsed_version.is_prerelease and not (
+                    prereleases or self.prereleases
+                ):
+                    found_prereleases.append(version)
+                # Either this is not a prerelease, or we should have been
+                # accepting prereleases from the beginning.
+                else:
+                    yielded = True
+                    yield version
+
+        # Now that we've iterated over everything, determine if we've yielded
+        # any values, and if we have not and we have any prereleases stored up
+        # then we will go ahead and yield the prereleases.
+        if not yielded and found_prereleases:
+            for version in found_prereleases:
+                yield version
+
+
+class LegacySpecifier(_IndividualSpecifier):
+
+    _regex_str = r"""
+        (?P(==|!=|<=|>=|<|>))
+        \s*
+        (?P
+            [^,;\s)]* # Since this is a "legacy" specifier, and the version
+                      # string can be just about anything, we match everything
+                      # except for whitespace, a semi-colon for marker support,
+                      # a closing paren since versions can be enclosed in
+                      # them, and a comma since it's a version separator.
+        )
+        """
+
+    _regex = re.compile(r"^\s*" + _regex_str + r"\s*$", re.VERBOSE | re.IGNORECASE)
+
+    _operators = {
+        "==": "equal",
+        "!=": "not_equal",
+        "<=": "less_than_equal",
+        ">=": "greater_than_equal",
+        "<": "less_than",
+        ">": "greater_than",
+    }
+
+    def __init__(self, spec: str = "", prereleases: Optional[bool] = None) -> None:
+        super().__init__(spec, prereleases)
+
+        warnings.warn(
+            "Creating a LegacyVersion has been deprecated and will be "
+            "removed in the next major release",
+            DeprecationWarning,
+        )
+
+    def _coerce_version(self, version: UnparsedVersion) -> LegacyVersion:
+        if not isinstance(version, LegacyVersion):
+            version = LegacyVersion(str(version))
+        return version
+
+    def _compare_equal(self, prospective: LegacyVersion, spec: str) -> bool:
+        return prospective == self._coerce_version(spec)
+
+    def _compare_not_equal(self, prospective: LegacyVersion, spec: str) -> bool:
+        return prospective != self._coerce_version(spec)
+
+    def _compare_less_than_equal(self, prospective: LegacyVersion, spec: str) -> bool:
+        return prospective <= self._coerce_version(spec)
+
+    def _compare_greater_than_equal(
+        self, prospective: LegacyVersion, spec: str
+    ) -> bool:
+        return prospective >= self._coerce_version(spec)
+
+    def _compare_less_than(self, prospective: LegacyVersion, spec: str) -> bool:
+        return prospective < self._coerce_version(spec)
+
+    def _compare_greater_than(self, prospective: LegacyVersion, spec: str) -> bool:
+        return prospective > self._coerce_version(spec)
+
+
+def _require_version_compare(
+    fn: Callable[["Specifier", ParsedVersion, str], bool]
+) -> Callable[["Specifier", ParsedVersion, str], bool]:
+    @functools.wraps(fn)
+    def wrapped(self: "Specifier", prospective: ParsedVersion, spec: str) -> bool:
+        if not isinstance(prospective, Version):
+            return False
+        return fn(self, prospective, spec)
+
+    return wrapped
+
+
+class Specifier(_IndividualSpecifier):
+
+    _regex_str = r"""
+        (?P(~=|==|!=|<=|>=|<|>|===))
+        (?P
+            (?:
+                # The identity operators allow for an escape hatch that will
+                # do an exact string match of the version you wish to install.
+                # This will not be parsed by PEP 440 and we cannot determine
+                # any semantic meaning from it. This operator is discouraged
+                # but included entirely as an escape hatch.
+                (?<====)  # Only match for the identity operator
+                \s*
+                [^\s]*    # We just match everything, except for whitespace
+                          # since we are only testing for strict identity.
+            )
+            |
+            (?:
+                # The (non)equality operators allow for wild card and local
+                # versions to be specified so we have to define these two
+                # operators separately to enable that.
+                (?<===|!=)            # Only match for equals and not equals
+
+                \s*
+                v?
+                (?:[0-9]+!)?          # epoch
+                [0-9]+(?:\.[0-9]+)*   # release
+                (?:                   # pre release
+                    [-_\.]?
+                    (a|b|c|rc|alpha|beta|pre|preview)
+                    [-_\.]?
+                    [0-9]*
+                )?
+                (?:                   # post release
+                    (?:-[0-9]+)|(?:[-_\.]?(post|rev|r)[-_\.]?[0-9]*)
+                )?
+
+                # You cannot use a wild card and a dev or local version
+                # together so group them with a | and make them optional.
+                (?:
+                    (?:[-_\.]?dev[-_\.]?[0-9]*)?         # dev release
+                    (?:\+[a-z0-9]+(?:[-_\.][a-z0-9]+)*)? # local
+                    |
+                    \.\*  # Wild card syntax of .*
+                )?
+            )
+            |
+            (?:
+                # The compatible operator requires at least two digits in the
+                # release segment.
+                (?<=~=)               # Only match for the compatible operator
+
+                \s*
+                v?
+                (?:[0-9]+!)?          # epoch
+                [0-9]+(?:\.[0-9]+)+   # release  (We have a + instead of a *)
+                (?:                   # pre release
+                    [-_\.]?
+                    (a|b|c|rc|alpha|beta|pre|preview)
+                    [-_\.]?
+                    [0-9]*
+                )?
+                (?:                                   # post release
+                    (?:-[0-9]+)|(?:[-_\.]?(post|rev|r)[-_\.]?[0-9]*)
+                )?
+                (?:[-_\.]?dev[-_\.]?[0-9]*)?          # dev release
+            )
+            |
+            (?:
+                # All other operators only allow a sub set of what the
+                # (non)equality operators do. Specifically they do not allow
+                # local versions to be specified nor do they allow the prefix
+                # matching wild cards.
+                (?=": "greater_than_equal",
+        "<": "less_than",
+        ">": "greater_than",
+        "===": "arbitrary",
+    }
+
+    @_require_version_compare
+    def _compare_compatible(self, prospective: ParsedVersion, spec: str) -> bool:
+
+        # Compatible releases have an equivalent combination of >= and ==. That
+        # is that ~=2.2 is equivalent to >=2.2,==2.*. This allows us to
+        # implement this in terms of the other specifiers instead of
+        # implementing it ourselves. The only thing we need to do is construct
+        # the other specifiers.
+
+        # We want everything but the last item in the version, but we want to
+        # ignore suffix segments.
+        prefix = ".".join(
+            list(itertools.takewhile(_is_not_suffix, _version_split(spec)))[:-1]
+        )
+
+        # Add the prefix notation to the end of our string
+        prefix += ".*"
+
+        return self._get_operator(">=")(prospective, spec) and self._get_operator("==")(
+            prospective, prefix
+        )
+
+    @_require_version_compare
+    def _compare_equal(self, prospective: ParsedVersion, spec: str) -> bool:
+
+        # We need special logic to handle prefix matching
+        if spec.endswith(".*"):
+            # In the case of prefix matching we want to ignore local segment.
+            prospective = Version(prospective.public)
+            # Split the spec out by dots, and pretend that there is an implicit
+            # dot in between a release segment and a pre-release segment.
+            split_spec = _version_split(spec[:-2])  # Remove the trailing .*
+
+            # Split the prospective version out by dots, and pretend that there
+            # is an implicit dot in between a release segment and a pre-release
+            # segment.
+            split_prospective = _version_split(str(prospective))
+
+            # Shorten the prospective version to be the same length as the spec
+            # so that we can determine if the specifier is a prefix of the
+            # prospective version or not.
+            shortened_prospective = split_prospective[: len(split_spec)]
+
+            # Pad out our two sides with zeros so that they both equal the same
+            # length.
+            padded_spec, padded_prospective = _pad_version(
+                split_spec, shortened_prospective
+            )
+
+            return padded_prospective == padded_spec
+        else:
+            # Convert our spec string into a Version
+            spec_version = Version(spec)
+
+            # If the specifier does not have a local segment, then we want to
+            # act as if the prospective version also does not have a local
+            # segment.
+            if not spec_version.local:
+                prospective = Version(prospective.public)
+
+            return prospective == spec_version
+
+    @_require_version_compare
+    def _compare_not_equal(self, prospective: ParsedVersion, spec: str) -> bool:
+        return not self._compare_equal(prospective, spec)
+
+    @_require_version_compare
+    def _compare_less_than_equal(self, prospective: ParsedVersion, spec: str) -> bool:
+
+        # NB: Local version identifiers are NOT permitted in the version
+        # specifier, so local version labels can be universally removed from
+        # the prospective version.
+        return Version(prospective.public) <= Version(spec)
+
+    @_require_version_compare
+    def _compare_greater_than_equal(
+        self, prospective: ParsedVersion, spec: str
+    ) -> bool:
+
+        # NB: Local version identifiers are NOT permitted in the version
+        # specifier, so local version labels can be universally removed from
+        # the prospective version.
+        return Version(prospective.public) >= Version(spec)
+
+    @_require_version_compare
+    def _compare_less_than(self, prospective: ParsedVersion, spec_str: str) -> bool:
+
+        # Convert our spec to a Version instance, since we'll want to work with
+        # it as a version.
+        spec = Version(spec_str)
+
+        # Check to see if the prospective version is less than the spec
+        # version. If it's not we can short circuit and just return False now
+        # instead of doing extra unneeded work.
+        if not prospective < spec:
+            return False
+
+        # This special case is here so that, unless the specifier itself
+        # includes is a pre-release version, that we do not accept pre-release
+        # versions for the version mentioned in the specifier (e.g. <3.1 should
+        # not match 3.1.dev0, but should match 3.0.dev0).
+        if not spec.is_prerelease and prospective.is_prerelease:
+            if Version(prospective.base_version) == Version(spec.base_version):
+                return False
+
+        # If we've gotten to here, it means that prospective version is both
+        # less than the spec version *and* it's not a pre-release of the same
+        # version in the spec.
+        return True
+
+    @_require_version_compare
+    def _compare_greater_than(self, prospective: ParsedVersion, spec_str: str) -> bool:
+
+        # Convert our spec to a Version instance, since we'll want to work with
+        # it as a version.
+        spec = Version(spec_str)
+
+        # Check to see if the prospective version is greater than the spec
+        # version. If it's not we can short circuit and just return False now
+        # instead of doing extra unneeded work.
+        if not prospective > spec:
+            return False
+
+        # This special case is here so that, unless the specifier itself
+        # includes is a post-release version, that we do not accept
+        # post-release versions for the version mentioned in the specifier
+        # (e.g. >3.1 should not match 3.0.post0, but should match 3.2.post0).
+        if not spec.is_postrelease and prospective.is_postrelease:
+            if Version(prospective.base_version) == Version(spec.base_version):
+                return False
+
+        # Ensure that we do not allow a local version of the version mentioned
+        # in the specifier, which is technically greater than, to match.
+        if prospective.local is not None:
+            if Version(prospective.base_version) == Version(spec.base_version):
+                return False
+
+        # If we've gotten to here, it means that prospective version is both
+        # greater than the spec version *and* it's not a pre-release of the
+        # same version in the spec.
+        return True
+
+    def _compare_arbitrary(self, prospective: Version, spec: str) -> bool:
+        return str(prospective).lower() == str(spec).lower()
+
+    @property
+    def prereleases(self) -> bool:
+
+        # If there is an explicit prereleases set for this, then we'll just
+        # blindly use that.
+        if self._prereleases is not None:
+            return self._prereleases
+
+        # Look at all of our specifiers and determine if they are inclusive
+        # operators, and if they are if they are including an explicit
+        # prerelease.
+        operator, version = self._spec
+        if operator in ["==", ">=", "<=", "~=", "==="]:
+            # The == specifier can include a trailing .*, if it does we
+            # want to remove before parsing.
+            if operator == "==" and version.endswith(".*"):
+                version = version[:-2]
+
+            # Parse the version, and if it is a pre-release than this
+            # specifier allows pre-releases.
+            if parse(version).is_prerelease:
+                return True
+
+        return False
+
+    @prereleases.setter
+    def prereleases(self, value: bool) -> None:
+        self._prereleases = value
+
+
+_prefix_regex = re.compile(r"^([0-9]+)((?:a|b|c|rc)[0-9]+)$")
+
+
+def _version_split(version: str) -> List[str]:
+    result: List[str] = []
+    for item in version.split("."):
+        match = _prefix_regex.search(item)
+        if match:
+            result.extend(match.groups())
+        else:
+            result.append(item)
+    return result
+
+
+def _is_not_suffix(segment: str) -> bool:
+    return not any(
+        segment.startswith(prefix) for prefix in ("dev", "a", "b", "rc", "post")
+    )
+
+
+def _pad_version(left: List[str], right: List[str]) -> Tuple[List[str], List[str]]:
+    left_split, right_split = [], []
+
+    # Get the release segment of our versions
+    left_split.append(list(itertools.takewhile(lambda x: x.isdigit(), left)))
+    right_split.append(list(itertools.takewhile(lambda x: x.isdigit(), right)))
+
+    # Get the rest of our versions
+    left_split.append(left[len(left_split[0]) :])
+    right_split.append(right[len(right_split[0]) :])
+
+    # Insert our padding
+    left_split.insert(1, ["0"] * max(0, len(right_split[0]) - len(left_split[0])))
+    right_split.insert(1, ["0"] * max(0, len(left_split[0]) - len(right_split[0])))
+
+    return (list(itertools.chain(*left_split)), list(itertools.chain(*right_split)))
+
+
+class SpecifierSet(BaseSpecifier):
+    def __init__(
+        self, specifiers: str = "", prereleases: Optional[bool] = None
+    ) -> None:
+
+        # Split on , to break each individual specifier into it's own item, and
+        # strip each item to remove leading/trailing whitespace.
+        split_specifiers = [s.strip() for s in specifiers.split(",") if s.strip()]
+
+        # Parsed each individual specifier, attempting first to make it a
+        # Specifier and falling back to a LegacySpecifier.
+        parsed: Set[_IndividualSpecifier] = set()
+        for specifier in split_specifiers:
+            try:
+                parsed.add(Specifier(specifier))
+            except InvalidSpecifier:
+                parsed.add(LegacySpecifier(specifier))
+
+        # Turn our parsed specifiers into a frozen set and save them for later.
+        self._specs = frozenset(parsed)
+
+        # Store our prereleases value so we can use it later to determine if
+        # we accept prereleases or not.
+        self._prereleases = prereleases
+
+    def __repr__(self) -> str:
+        pre = (
+            f", prereleases={self.prereleases!r}"
+            if self._prereleases is not None
+            else ""
+        )
+
+        return f""
+
+    def __str__(self) -> str:
+        return ",".join(sorted(str(s) for s in self._specs))
+
+    def __hash__(self) -> int:
+        return hash(self._specs)
+
+    def __and__(self, other: Union["SpecifierSet", str]) -> "SpecifierSet":
+        if isinstance(other, str):
+            other = SpecifierSet(other)
+        elif not isinstance(other, SpecifierSet):
+            return NotImplemented
+
+        specifier = SpecifierSet()
+        specifier._specs = frozenset(self._specs | other._specs)
+
+        if self._prereleases is None and other._prereleases is not None:
+            specifier._prereleases = other._prereleases
+        elif self._prereleases is not None and other._prereleases is None:
+            specifier._prereleases = self._prereleases
+        elif self._prereleases == other._prereleases:
+            specifier._prereleases = self._prereleases
+        else:
+            raise ValueError(
+                "Cannot combine SpecifierSets with True and False prerelease "
+                "overrides."
+            )
+
+        return specifier
+
+    def __eq__(self, other: object) -> bool:
+        if isinstance(other, (str, _IndividualSpecifier)):
+            other = SpecifierSet(str(other))
+        elif not isinstance(other, SpecifierSet):
+            return NotImplemented
+
+        return self._specs == other._specs
+
+    def __len__(self) -> int:
+        return len(self._specs)
+
+    def __iter__(self) -> Iterator[_IndividualSpecifier]:
+        return iter(self._specs)
+
+    @property
+    def prereleases(self) -> Optional[bool]:
+
+        # If we have been given an explicit prerelease modifier, then we'll
+        # pass that through here.
+        if self._prereleases is not None:
+            return self._prereleases
+
+        # If we don't have any specifiers, and we don't have a forced value,
+        # then we'll just return None since we don't know if this should have
+        # pre-releases or not.
+        if not self._specs:
+            return None
+
+        # Otherwise we'll see if any of the given specifiers accept
+        # prereleases, if any of them do we'll return True, otherwise False.
+        return any(s.prereleases for s in self._specs)
+
+    @prereleases.setter
+    def prereleases(self, value: bool) -> None:
+        self._prereleases = value
+
+    def __contains__(self, item: UnparsedVersion) -> bool:
+        return self.contains(item)
+
+    def contains(
+        self, item: UnparsedVersion, prereleases: Optional[bool] = None
+    ) -> bool:
+
+        # Ensure that our item is a Version or LegacyVersion instance.
+        if not isinstance(item, (LegacyVersion, Version)):
+            item = parse(item)
+
+        # Determine if we're forcing a prerelease or not, if we're not forcing
+        # one for this particular filter call, then we'll use whatever the
+        # SpecifierSet thinks for whether or not we should support prereleases.
+        if prereleases is None:
+            prereleases = self.prereleases
+
+        # We can determine if we're going to allow pre-releases by looking to
+        # see if any of the underlying items supports them. If none of them do
+        # and this item is a pre-release then we do not allow it and we can
+        # short circuit that here.
+        # Note: This means that 1.0.dev1 would not be contained in something
+        #       like >=1.0.devabc however it would be in >=1.0.debabc,>0.0.dev0
+        if not prereleases and item.is_prerelease:
+            return False
+
+        # We simply dispatch to the underlying specs here to make sure that the
+        # given version is contained within all of them.
+        # Note: This use of all() here means that an empty set of specifiers
+        #       will always return True, this is an explicit design decision.
+        return all(s.contains(item, prereleases=prereleases) for s in self._specs)
+
+    def filter(
+        self, iterable: Iterable[VersionTypeVar], prereleases: Optional[bool] = None
+    ) -> Iterable[VersionTypeVar]:
+
+        # Determine if we're forcing a prerelease or not, if we're not forcing
+        # one for this particular filter call, then we'll use whatever the
+        # SpecifierSet thinks for whether or not we should support prereleases.
+        if prereleases is None:
+            prereleases = self.prereleases
+
+        # If we have any specifiers, then we want to wrap our iterable in the
+        # filter method for each one, this will act as a logical AND amongst
+        # each specifier.
+        if self._specs:
+            for spec in self._specs:
+                iterable = spec.filter(iterable, prereleases=bool(prereleases))
+            return iterable
+        # If we do not have any specifiers, then we need to have a rough filter
+        # which will filter out any pre-releases, unless there are no final
+        # releases, and which will filter out LegacyVersion in general.
+        else:
+            filtered: List[VersionTypeVar] = []
+            found_prereleases: List[VersionTypeVar] = []
+
+            item: UnparsedVersion
+            parsed_version: Union[Version, LegacyVersion]
+
+            for item in iterable:
+                # Ensure that we some kind of Version class for this item.
+                if not isinstance(item, (LegacyVersion, Version)):
+                    parsed_version = parse(item)
+                else:
+                    parsed_version = item
+
+                # Filter out any item which is parsed as a LegacyVersion
+                if isinstance(parsed_version, LegacyVersion):
+                    continue
+
+                # Store any item which is a pre-release for later unless we've
+                # already found a final version or we are accepting prereleases
+                if parsed_version.is_prerelease and not prereleases:
+                    if not filtered:
+                        found_prereleases.append(item)
+                else:
+                    filtered.append(item)
+
+            # If we've found no items except for pre-releases, then we'll go
+            # ahead and use the pre-releases
+            if not filtered and found_prereleases and prereleases is None:
+                return found_prereleases
+
+            return filtered
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/tags.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/tags.py
new file mode 100644
index 0000000000000000000000000000000000000000..9a3d25a71c75c975291cf987001ecd6882d6417d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/tags.py
@@ -0,0 +1,487 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+import logging
+import platform
+import sys
+import sysconfig
+from importlib.machinery import EXTENSION_SUFFIXES
+from typing import (
+    Dict,
+    FrozenSet,
+    Iterable,
+    Iterator,
+    List,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+    cast,
+)
+
+from . import _manylinux, _musllinux
+
+logger = logging.getLogger(__name__)
+
+PythonVersion = Sequence[int]
+MacVersion = Tuple[int, int]
+
+INTERPRETER_SHORT_NAMES: Dict[str, str] = {
+    "python": "py",  # Generic.
+    "cpython": "cp",
+    "pypy": "pp",
+    "ironpython": "ip",
+    "jython": "jy",
+}
+
+
+_32_BIT_INTERPRETER = sys.maxsize <= 2 ** 32
+
+
+class Tag:
+    """
+    A representation of the tag triple for a wheel.
+
+    Instances are considered immutable and thus are hashable. Equality checking
+    is also supported.
+    """
+
+    __slots__ = ["_interpreter", "_abi", "_platform", "_hash"]
+
+    def __init__(self, interpreter: str, abi: str, platform: str) -> None:
+        self._interpreter = interpreter.lower()
+        self._abi = abi.lower()
+        self._platform = platform.lower()
+        # The __hash__ of every single element in a Set[Tag] will be evaluated each time
+        # that a set calls its `.disjoint()` method, which may be called hundreds of
+        # times when scanning a page of links for packages with tags matching that
+        # Set[Tag]. Pre-computing the value here produces significant speedups for
+        # downstream consumers.
+        self._hash = hash((self._interpreter, self._abi, self._platform))
+
+    @property
+    def interpreter(self) -> str:
+        return self._interpreter
+
+    @property
+    def abi(self) -> str:
+        return self._abi
+
+    @property
+    def platform(self) -> str:
+        return self._platform
+
+    def __eq__(self, other: object) -> bool:
+        if not isinstance(other, Tag):
+            return NotImplemented
+
+        return (
+            (self._hash == other._hash)  # Short-circuit ASAP for perf reasons.
+            and (self._platform == other._platform)
+            and (self._abi == other._abi)
+            and (self._interpreter == other._interpreter)
+        )
+
+    def __hash__(self) -> int:
+        return self._hash
+
+    def __str__(self) -> str:
+        return f"{self._interpreter}-{self._abi}-{self._platform}"
+
+    def __repr__(self) -> str:
+        return f"<{self} @ {id(self)}>"
+
+
+def parse_tag(tag: str) -> FrozenSet[Tag]:
+    """
+    Parses the provided tag (e.g. `py3-none-any`) into a frozenset of Tag instances.
+
+    Returning a set is required due to the possibility that the tag is a
+    compressed tag set.
+    """
+    tags = set()
+    interpreters, abis, platforms = tag.split("-")
+    for interpreter in interpreters.split("."):
+        for abi in abis.split("."):
+            for platform_ in platforms.split("."):
+                tags.add(Tag(interpreter, abi, platform_))
+    return frozenset(tags)
+
+
+def _get_config_var(name: str, warn: bool = False) -> Union[int, str, None]:
+    value = sysconfig.get_config_var(name)
+    if value is None and warn:
+        logger.debug(
+            "Config variable '%s' is unset, Python ABI tag may be incorrect", name
+        )
+    return value
+
+
+def _normalize_string(string: str) -> str:
+    return string.replace(".", "_").replace("-", "_")
+
+
+def _abi3_applies(python_version: PythonVersion) -> bool:
+    """
+    Determine if the Python version supports abi3.
+
+    PEP 384 was first implemented in Python 3.2.
+    """
+    return len(python_version) > 1 and tuple(python_version) >= (3, 2)
+
+
+def _cpython_abis(py_version: PythonVersion, warn: bool = False) -> List[str]:
+    py_version = tuple(py_version)  # To allow for version comparison.
+    abis = []
+    version = _version_nodot(py_version[:2])
+    debug = pymalloc = ucs4 = ""
+    with_debug = _get_config_var("Py_DEBUG", warn)
+    has_refcount = hasattr(sys, "gettotalrefcount")
+    # Windows doesn't set Py_DEBUG, so checking for support of debug-compiled
+    # extension modules is the best option.
+    # https://github.com/pypa/pip/issues/3383#issuecomment-173267692
+    has_ext = "_d.pyd" in EXTENSION_SUFFIXES
+    if with_debug or (with_debug is None and (has_refcount or has_ext)):
+        debug = "d"
+    if py_version < (3, 8):
+        with_pymalloc = _get_config_var("WITH_PYMALLOC", warn)
+        if with_pymalloc or with_pymalloc is None:
+            pymalloc = "m"
+        if py_version < (3, 3):
+            unicode_size = _get_config_var("Py_UNICODE_SIZE", warn)
+            if unicode_size == 4 or (
+                unicode_size is None and sys.maxunicode == 0x10FFFF
+            ):
+                ucs4 = "u"
+    elif debug:
+        # Debug builds can also load "normal" extension modules.
+        # We can also assume no UCS-4 or pymalloc requirement.
+        abis.append(f"cp{version}")
+    abis.insert(
+        0,
+        "cp{version}{debug}{pymalloc}{ucs4}".format(
+            version=version, debug=debug, pymalloc=pymalloc, ucs4=ucs4
+        ),
+    )
+    return abis
+
+
+def cpython_tags(
+    python_version: Optional[PythonVersion] = None,
+    abis: Optional[Iterable[str]] = None,
+    platforms: Optional[Iterable[str]] = None,
+    *,
+    warn: bool = False,
+) -> Iterator[Tag]:
+    """
+    Yields the tags for a CPython interpreter.
+
+    The tags consist of:
+    - cp--
+    - cp-abi3-
+    - cp-none-
+    - cp-abi3-  # Older Python versions down to 3.2.
+
+    If python_version only specifies a major version then user-provided ABIs and
+    the 'none' ABItag will be used.
+
+    If 'abi3' or 'none' are specified in 'abis' then they will be yielded at
+    their normal position and not at the beginning.
+    """
+    if not python_version:
+        python_version = sys.version_info[:2]
+
+    interpreter = f"cp{_version_nodot(python_version[:2])}"
+
+    if abis is None:
+        if len(python_version) > 1:
+            abis = _cpython_abis(python_version, warn)
+        else:
+            abis = []
+    abis = list(abis)
+    # 'abi3' and 'none' are explicitly handled later.
+    for explicit_abi in ("abi3", "none"):
+        try:
+            abis.remove(explicit_abi)
+        except ValueError:
+            pass
+
+    platforms = list(platforms or platform_tags())
+    for abi in abis:
+        for platform_ in platforms:
+            yield Tag(interpreter, abi, platform_)
+    if _abi3_applies(python_version):
+        yield from (Tag(interpreter, "abi3", platform_) for platform_ in platforms)
+    yield from (Tag(interpreter, "none", platform_) for platform_ in platforms)
+
+    if _abi3_applies(python_version):
+        for minor_version in range(python_version[1] - 1, 1, -1):
+            for platform_ in platforms:
+                interpreter = "cp{version}".format(
+                    version=_version_nodot((python_version[0], minor_version))
+                )
+                yield Tag(interpreter, "abi3", platform_)
+
+
+def _generic_abi() -> Iterator[str]:
+    abi = sysconfig.get_config_var("SOABI")
+    if abi:
+        yield _normalize_string(abi)
+
+
+def generic_tags(
+    interpreter: Optional[str] = None,
+    abis: Optional[Iterable[str]] = None,
+    platforms: Optional[Iterable[str]] = None,
+    *,
+    warn: bool = False,
+) -> Iterator[Tag]:
+    """
+    Yields the tags for a generic interpreter.
+
+    The tags consist of:
+    - --
+
+    The "none" ABI will be added if it was not explicitly provided.
+    """
+    if not interpreter:
+        interp_name = interpreter_name()
+        interp_version = interpreter_version(warn=warn)
+        interpreter = "".join([interp_name, interp_version])
+    if abis is None:
+        abis = _generic_abi()
+    platforms = list(platforms or platform_tags())
+    abis = list(abis)
+    if "none" not in abis:
+        abis.append("none")
+    for abi in abis:
+        for platform_ in platforms:
+            yield Tag(interpreter, abi, platform_)
+
+
+def _py_interpreter_range(py_version: PythonVersion) -> Iterator[str]:
+    """
+    Yields Python versions in descending order.
+
+    After the latest version, the major-only version will be yielded, and then
+    all previous versions of that major version.
+    """
+    if len(py_version) > 1:
+        yield f"py{_version_nodot(py_version[:2])}"
+    yield f"py{py_version[0]}"
+    if len(py_version) > 1:
+        for minor in range(py_version[1] - 1, -1, -1):
+            yield f"py{_version_nodot((py_version[0], minor))}"
+
+
+def compatible_tags(
+    python_version: Optional[PythonVersion] = None,
+    interpreter: Optional[str] = None,
+    platforms: Optional[Iterable[str]] = None,
+) -> Iterator[Tag]:
+    """
+    Yields the sequence of tags that are compatible with a specific version of Python.
+
+    The tags consist of:
+    - py*-none-
+    - -none-any  # ... if `interpreter` is provided.
+    - py*-none-any
+    """
+    if not python_version:
+        python_version = sys.version_info[:2]
+    platforms = list(platforms or platform_tags())
+    for version in _py_interpreter_range(python_version):
+        for platform_ in platforms:
+            yield Tag(version, "none", platform_)
+    if interpreter:
+        yield Tag(interpreter, "none", "any")
+    for version in _py_interpreter_range(python_version):
+        yield Tag(version, "none", "any")
+
+
+def _mac_arch(arch: str, is_32bit: bool = _32_BIT_INTERPRETER) -> str:
+    if not is_32bit:
+        return arch
+
+    if arch.startswith("ppc"):
+        return "ppc"
+
+    return "i386"
+
+
+def _mac_binary_formats(version: MacVersion, cpu_arch: str) -> List[str]:
+    formats = [cpu_arch]
+    if cpu_arch == "x86_64":
+        if version < (10, 4):
+            return []
+        formats.extend(["intel", "fat64", "fat32"])
+
+    elif cpu_arch == "i386":
+        if version < (10, 4):
+            return []
+        formats.extend(["intel", "fat32", "fat"])
+
+    elif cpu_arch == "ppc64":
+        # TODO: Need to care about 32-bit PPC for ppc64 through 10.2?
+        if version > (10, 5) or version < (10, 4):
+            return []
+        formats.append("fat64")
+
+    elif cpu_arch == "ppc":
+        if version > (10, 6):
+            return []
+        formats.extend(["fat32", "fat"])
+
+    if cpu_arch in {"arm64", "x86_64"}:
+        formats.append("universal2")
+
+    if cpu_arch in {"x86_64", "i386", "ppc64", "ppc", "intel"}:
+        formats.append("universal")
+
+    return formats
+
+
+def mac_platforms(
+    version: Optional[MacVersion] = None, arch: Optional[str] = None
+) -> Iterator[str]:
+    """
+    Yields the platform tags for a macOS system.
+
+    The `version` parameter is a two-item tuple specifying the macOS version to
+    generate platform tags for. The `arch` parameter is the CPU architecture to
+    generate platform tags for. Both parameters default to the appropriate value
+    for the current system.
+    """
+    version_str, _, cpu_arch = platform.mac_ver()
+    if version is None:
+        version = cast("MacVersion", tuple(map(int, version_str.split(".")[:2])))
+    else:
+        version = version
+    if arch is None:
+        arch = _mac_arch(cpu_arch)
+    else:
+        arch = arch
+
+    if (10, 0) <= version and version < (11, 0):
+        # Prior to Mac OS 11, each yearly release of Mac OS bumped the
+        # "minor" version number.  The major version was always 10.
+        for minor_version in range(version[1], -1, -1):
+            compat_version = 10, minor_version
+            binary_formats = _mac_binary_formats(compat_version, arch)
+            for binary_format in binary_formats:
+                yield "macosx_{major}_{minor}_{binary_format}".format(
+                    major=10, minor=minor_version, binary_format=binary_format
+                )
+
+    if version >= (11, 0):
+        # Starting with Mac OS 11, each yearly release bumps the major version
+        # number.   The minor versions are now the midyear updates.
+        for major_version in range(version[0], 10, -1):
+            compat_version = major_version, 0
+            binary_formats = _mac_binary_formats(compat_version, arch)
+            for binary_format in binary_formats:
+                yield "macosx_{major}_{minor}_{binary_format}".format(
+                    major=major_version, minor=0, binary_format=binary_format
+                )
+
+    if version >= (11, 0):
+        # Mac OS 11 on x86_64 is compatible with binaries from previous releases.
+        # Arm64 support was introduced in 11.0, so no Arm binaries from previous
+        # releases exist.
+        #
+        # However, the "universal2" binary format can have a
+        # macOS version earlier than 11.0 when the x86_64 part of the binary supports
+        # that version of macOS.
+        if arch == "x86_64":
+            for minor_version in range(16, 3, -1):
+                compat_version = 10, minor_version
+                binary_formats = _mac_binary_formats(compat_version, arch)
+                for binary_format in binary_formats:
+                    yield "macosx_{major}_{minor}_{binary_format}".format(
+                        major=compat_version[0],
+                        minor=compat_version[1],
+                        binary_format=binary_format,
+                    )
+        else:
+            for minor_version in range(16, 3, -1):
+                compat_version = 10, minor_version
+                binary_format = "universal2"
+                yield "macosx_{major}_{minor}_{binary_format}".format(
+                    major=compat_version[0],
+                    minor=compat_version[1],
+                    binary_format=binary_format,
+                )
+
+
+def _linux_platforms(is_32bit: bool = _32_BIT_INTERPRETER) -> Iterator[str]:
+    linux = _normalize_string(sysconfig.get_platform())
+    if is_32bit:
+        if linux == "linux_x86_64":
+            linux = "linux_i686"
+        elif linux == "linux_aarch64":
+            linux = "linux_armv7l"
+    _, arch = linux.split("_", 1)
+    yield from _manylinux.platform_tags(linux, arch)
+    yield from _musllinux.platform_tags(arch)
+    yield linux
+
+
+def _generic_platforms() -> Iterator[str]:
+    yield _normalize_string(sysconfig.get_platform())
+
+
+def platform_tags() -> Iterator[str]:
+    """
+    Provides the platform tags for this installation.
+    """
+    if platform.system() == "Darwin":
+        return mac_platforms()
+    elif platform.system() == "Linux":
+        return _linux_platforms()
+    else:
+        return _generic_platforms()
+
+
+def interpreter_name() -> str:
+    """
+    Returns the name of the running interpreter.
+    """
+    name = sys.implementation.name
+    return INTERPRETER_SHORT_NAMES.get(name) or name
+
+
+def interpreter_version(*, warn: bool = False) -> str:
+    """
+    Returns the version of the running interpreter.
+    """
+    version = _get_config_var("py_version_nodot", warn=warn)
+    if version:
+        version = str(version)
+    else:
+        version = _version_nodot(sys.version_info[:2])
+    return version
+
+
+def _version_nodot(version: PythonVersion) -> str:
+    return "".join(map(str, version))
+
+
+def sys_tags(*, warn: bool = False) -> Iterator[Tag]:
+    """
+    Returns the sequence of tag triples for the running interpreter.
+
+    The order of the sequence corresponds to priority order for the
+    interpreter, from most to least important.
+    """
+
+    interp_name = interpreter_name()
+    if interp_name == "cp":
+        yield from cpython_tags(warn=warn)
+    else:
+        yield from generic_tags()
+
+    if interp_name == "pp":
+        yield from compatible_tags(interpreter="pp3")
+    else:
+        yield from compatible_tags()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..bab11b80c60f10a4f3bccb12eb5b17c48a449767
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/utils.py
@@ -0,0 +1,136 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+import re
+from typing import FrozenSet, NewType, Tuple, Union, cast
+
+from .tags import Tag, parse_tag
+from .version import InvalidVersion, Version
+
+BuildTag = Union[Tuple[()], Tuple[int, str]]
+NormalizedName = NewType("NormalizedName", str)
+
+
+class InvalidWheelFilename(ValueError):
+    """
+    An invalid wheel filename was found, users should refer to PEP 427.
+    """
+
+
+class InvalidSdistFilename(ValueError):
+    """
+    An invalid sdist filename was found, users should refer to the packaging user guide.
+    """
+
+
+_canonicalize_regex = re.compile(r"[-_.]+")
+# PEP 427: The build number must start with a digit.
+_build_tag_regex = re.compile(r"(\d+)(.*)")
+
+
+def canonicalize_name(name: str) -> NormalizedName:
+    # This is taken from PEP 503.
+    value = _canonicalize_regex.sub("-", name).lower()
+    return cast(NormalizedName, value)
+
+
+def canonicalize_version(version: Union[Version, str]) -> str:
+    """
+    This is very similar to Version.__str__, but has one subtle difference
+    with the way it handles the release segment.
+    """
+    if isinstance(version, str):
+        try:
+            parsed = Version(version)
+        except InvalidVersion:
+            # Legacy versions cannot be normalized
+            return version
+    else:
+        parsed = version
+
+    parts = []
+
+    # Epoch
+    if parsed.epoch != 0:
+        parts.append(f"{parsed.epoch}!")
+
+    # Release segment
+    # NB: This strips trailing '.0's to normalize
+    parts.append(re.sub(r"(\.0)+$", "", ".".join(str(x) for x in parsed.release)))
+
+    # Pre-release
+    if parsed.pre is not None:
+        parts.append("".join(str(x) for x in parsed.pre))
+
+    # Post-release
+    if parsed.post is not None:
+        parts.append(f".post{parsed.post}")
+
+    # Development release
+    if parsed.dev is not None:
+        parts.append(f".dev{parsed.dev}")
+
+    # Local version segment
+    if parsed.local is not None:
+        parts.append(f"+{parsed.local}")
+
+    return "".join(parts)
+
+
+def parse_wheel_filename(
+    filename: str,
+) -> Tuple[NormalizedName, Version, BuildTag, FrozenSet[Tag]]:
+    if not filename.endswith(".whl"):
+        raise InvalidWheelFilename(
+            f"Invalid wheel filename (extension must be '.whl'): {filename}"
+        )
+
+    filename = filename[:-4]
+    dashes = filename.count("-")
+    if dashes not in (4, 5):
+        raise InvalidWheelFilename(
+            f"Invalid wheel filename (wrong number of parts): {filename}"
+        )
+
+    parts = filename.split("-", dashes - 2)
+    name_part = parts[0]
+    # See PEP 427 for the rules on escaping the project name
+    if "__" in name_part or re.match(r"^[\w\d._]*$", name_part, re.UNICODE) is None:
+        raise InvalidWheelFilename(f"Invalid project name: {filename}")
+    name = canonicalize_name(name_part)
+    version = Version(parts[1])
+    if dashes == 5:
+        build_part = parts[2]
+        build_match = _build_tag_regex.match(build_part)
+        if build_match is None:
+            raise InvalidWheelFilename(
+                f"Invalid build number: {build_part} in '{filename}'"
+            )
+        build = cast(BuildTag, (int(build_match.group(1)), build_match.group(2)))
+    else:
+        build = ()
+    tags = parse_tag(parts[-1])
+    return (name, version, build, tags)
+
+
+def parse_sdist_filename(filename: str) -> Tuple[NormalizedName, Version]:
+    if filename.endswith(".tar.gz"):
+        file_stem = filename[: -len(".tar.gz")]
+    elif filename.endswith(".zip"):
+        file_stem = filename[: -len(".zip")]
+    else:
+        raise InvalidSdistFilename(
+            f"Invalid sdist filename (extension must be '.tar.gz' or '.zip'):"
+            f" {filename}"
+        )
+
+    # We are requiring a PEP 440 version, which cannot contain dashes,
+    # so we split on the last dash.
+    name_part, sep, version_part = file_stem.rpartition("-")
+    if not sep:
+        raise InvalidSdistFilename(f"Invalid sdist filename: {filename}")
+
+    name = canonicalize_name(name_part)
+    version = Version(version_part)
+    return (name, version)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/version.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..de9a09a4ed3b078b37e7490a6686f660ae935aca
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/packaging/version.py
@@ -0,0 +1,504 @@
+# This file is dual licensed under the terms of the Apache License, Version
+# 2.0, and the BSD License. See the LICENSE file in the root of this repository
+# for complete details.
+
+import collections
+import itertools
+import re
+import warnings
+from typing import Callable, Iterator, List, Optional, SupportsInt, Tuple, Union
+
+from ._structures import Infinity, InfinityType, NegativeInfinity, NegativeInfinityType
+
+__all__ = ["parse", "Version", "LegacyVersion", "InvalidVersion", "VERSION_PATTERN"]
+
+InfiniteTypes = Union[InfinityType, NegativeInfinityType]
+PrePostDevType = Union[InfiniteTypes, Tuple[str, int]]
+SubLocalType = Union[InfiniteTypes, int, str]
+LocalType = Union[
+    NegativeInfinityType,
+    Tuple[
+        Union[
+            SubLocalType,
+            Tuple[SubLocalType, str],
+            Tuple[NegativeInfinityType, SubLocalType],
+        ],
+        ...,
+    ],
+]
+CmpKey = Tuple[
+    int, Tuple[int, ...], PrePostDevType, PrePostDevType, PrePostDevType, LocalType
+]
+LegacyCmpKey = Tuple[int, Tuple[str, ...]]
+VersionComparisonMethod = Callable[
+    [Union[CmpKey, LegacyCmpKey], Union[CmpKey, LegacyCmpKey]], bool
+]
+
+_Version = collections.namedtuple(
+    "_Version", ["epoch", "release", "dev", "pre", "post", "local"]
+)
+
+
+def parse(version: str) -> Union["LegacyVersion", "Version"]:
+    """
+    Parse the given version string and return either a :class:`Version` object
+    or a :class:`LegacyVersion` object depending on if the given version is
+    a valid PEP 440 version or a legacy version.
+    """
+    try:
+        return Version(version)
+    except InvalidVersion:
+        return LegacyVersion(version)
+
+
+class InvalidVersion(ValueError):
+    """
+    An invalid version was found, users should refer to PEP 440.
+    """
+
+
+class _BaseVersion:
+    _key: Union[CmpKey, LegacyCmpKey]
+
+    def __hash__(self) -> int:
+        return hash(self._key)
+
+    # Please keep the duplicated `isinstance` check
+    # in the six comparisons hereunder
+    # unless you find a way to avoid adding overhead function calls.
+    def __lt__(self, other: "_BaseVersion") -> bool:
+        if not isinstance(other, _BaseVersion):
+            return NotImplemented
+
+        return self._key < other._key
+
+    def __le__(self, other: "_BaseVersion") -> bool:
+        if not isinstance(other, _BaseVersion):
+            return NotImplemented
+
+        return self._key <= other._key
+
+    def __eq__(self, other: object) -> bool:
+        if not isinstance(other, _BaseVersion):
+            return NotImplemented
+
+        return self._key == other._key
+
+    def __ge__(self, other: "_BaseVersion") -> bool:
+        if not isinstance(other, _BaseVersion):
+            return NotImplemented
+
+        return self._key >= other._key
+
+    def __gt__(self, other: "_BaseVersion") -> bool:
+        if not isinstance(other, _BaseVersion):
+            return NotImplemented
+
+        return self._key > other._key
+
+    def __ne__(self, other: object) -> bool:
+        if not isinstance(other, _BaseVersion):
+            return NotImplemented
+
+        return self._key != other._key
+
+
+class LegacyVersion(_BaseVersion):
+    def __init__(self, version: str) -> None:
+        self._version = str(version)
+        self._key = _legacy_cmpkey(self._version)
+
+        warnings.warn(
+            "Creating a LegacyVersion has been deprecated and will be "
+            "removed in the next major release",
+            DeprecationWarning,
+        )
+
+    def __str__(self) -> str:
+        return self._version
+
+    def __repr__(self) -> str:
+        return f""
+
+    @property
+    def public(self) -> str:
+        return self._version
+
+    @property
+    def base_version(self) -> str:
+        return self._version
+
+    @property
+    def epoch(self) -> int:
+        return -1
+
+    @property
+    def release(self) -> None:
+        return None
+
+    @property
+    def pre(self) -> None:
+        return None
+
+    @property
+    def post(self) -> None:
+        return None
+
+    @property
+    def dev(self) -> None:
+        return None
+
+    @property
+    def local(self) -> None:
+        return None
+
+    @property
+    def is_prerelease(self) -> bool:
+        return False
+
+    @property
+    def is_postrelease(self) -> bool:
+        return False
+
+    @property
+    def is_devrelease(self) -> bool:
+        return False
+
+
+_legacy_version_component_re = re.compile(r"(\d+ | [a-z]+ | \.| -)", re.VERBOSE)
+
+_legacy_version_replacement_map = {
+    "pre": "c",
+    "preview": "c",
+    "-": "final-",
+    "rc": "c",
+    "dev": "@",
+}
+
+
+def _parse_version_parts(s: str) -> Iterator[str]:
+    for part in _legacy_version_component_re.split(s):
+        part = _legacy_version_replacement_map.get(part, part)
+
+        if not part or part == ".":
+            continue
+
+        if part[:1] in "0123456789":
+            # pad for numeric comparison
+            yield part.zfill(8)
+        else:
+            yield "*" + part
+
+    # ensure that alpha/beta/candidate are before final
+    yield "*final"
+
+
+def _legacy_cmpkey(version: str) -> LegacyCmpKey:
+
+    # We hardcode an epoch of -1 here. A PEP 440 version can only have a epoch
+    # greater than or equal to 0. This will effectively put the LegacyVersion,
+    # which uses the defacto standard originally implemented by setuptools,
+    # as before all PEP 440 versions.
+    epoch = -1
+
+    # This scheme is taken from pkg_resources.parse_version setuptools prior to
+    # it's adoption of the packaging library.
+    parts: List[str] = []
+    for part in _parse_version_parts(version.lower()):
+        if part.startswith("*"):
+            # remove "-" before a prerelease tag
+            if part < "*final":
+                while parts and parts[-1] == "*final-":
+                    parts.pop()
+
+            # remove trailing zeros from each series of numeric parts
+            while parts and parts[-1] == "00000000":
+                parts.pop()
+
+        parts.append(part)
+
+    return epoch, tuple(parts)
+
+
+# Deliberately not anchored to the start and end of the string, to make it
+# easier for 3rd party code to reuse
+VERSION_PATTERN = r"""
+    v?
+    (?:
+        (?:(?P[0-9]+)!)?                           # epoch
+        (?P[0-9]+(?:\.[0-9]+)*)                  # release segment
+        (?P
                                          # pre-release
+            [-_\.]?
+            (?P(a|b|c|rc|alpha|beta|pre|preview))
+            [-_\.]?
+            (?P[0-9]+)?
+        )?
+        (?P                                         # post release
+            (?:-(?P[0-9]+))
+            |
+            (?:
+                [-_\.]?
+                (?Ppost|rev|r)
+                [-_\.]?
+                (?P[0-9]+)?
+            )
+        )?
+        (?P                                          # dev release
+            [-_\.]?
+            (?Pdev)
+            [-_\.]?
+            (?P[0-9]+)?
+        )?
+    )
+    (?:\+(?P[a-z0-9]+(?:[-_\.][a-z0-9]+)*))?       # local version
+"""
+
+
+class Version(_BaseVersion):
+
+    _regex = re.compile(r"^\s*" + VERSION_PATTERN + r"\s*$", re.VERBOSE | re.IGNORECASE)
+
+    def __init__(self, version: str) -> None:
+
+        # Validate the version and parse it into pieces
+        match = self._regex.search(version)
+        if not match:
+            raise InvalidVersion(f"Invalid version: '{version}'")
+
+        # Store the parsed out pieces of the version
+        self._version = _Version(
+            epoch=int(match.group("epoch")) if match.group("epoch") else 0,
+            release=tuple(int(i) for i in match.group("release").split(".")),
+            pre=_parse_letter_version(match.group("pre_l"), match.group("pre_n")),
+            post=_parse_letter_version(
+                match.group("post_l"), match.group("post_n1") or match.group("post_n2")
+            ),
+            dev=_parse_letter_version(match.group("dev_l"), match.group("dev_n")),
+            local=_parse_local_version(match.group("local")),
+        )
+
+        # Generate a key which will be used for sorting
+        self._key = _cmpkey(
+            self._version.epoch,
+            self._version.release,
+            self._version.pre,
+            self._version.post,
+            self._version.dev,
+            self._version.local,
+        )
+
+    def __repr__(self) -> str:
+        return f""
+
+    def __str__(self) -> str:
+        parts = []
+
+        # Epoch
+        if self.epoch != 0:
+            parts.append(f"{self.epoch}!")
+
+        # Release segment
+        parts.append(".".join(str(x) for x in self.release))
+
+        # Pre-release
+        if self.pre is not None:
+            parts.append("".join(str(x) for x in self.pre))
+
+        # Post-release
+        if self.post is not None:
+            parts.append(f".post{self.post}")
+
+        # Development release
+        if self.dev is not None:
+            parts.append(f".dev{self.dev}")
+
+        # Local version segment
+        if self.local is not None:
+            parts.append(f"+{self.local}")
+
+        return "".join(parts)
+
+    @property
+    def epoch(self) -> int:
+        _epoch: int = self._version.epoch
+        return _epoch
+
+    @property
+    def release(self) -> Tuple[int, ...]:
+        _release: Tuple[int, ...] = self._version.release
+        return _release
+
+    @property
+    def pre(self) -> Optional[Tuple[str, int]]:
+        _pre: Optional[Tuple[str, int]] = self._version.pre
+        return _pre
+
+    @property
+    def post(self) -> Optional[int]:
+        return self._version.post[1] if self._version.post else None
+
+    @property
+    def dev(self) -> Optional[int]:
+        return self._version.dev[1] if self._version.dev else None
+
+    @property
+    def local(self) -> Optional[str]:
+        if self._version.local:
+            return ".".join(str(x) for x in self._version.local)
+        else:
+            return None
+
+    @property
+    def public(self) -> str:
+        return str(self).split("+", 1)[0]
+
+    @property
+    def base_version(self) -> str:
+        parts = []
+
+        # Epoch
+        if self.epoch != 0:
+            parts.append(f"{self.epoch}!")
+
+        # Release segment
+        parts.append(".".join(str(x) for x in self.release))
+
+        return "".join(parts)
+
+    @property
+    def is_prerelease(self) -> bool:
+        return self.dev is not None or self.pre is not None
+
+    @property
+    def is_postrelease(self) -> bool:
+        return self.post is not None
+
+    @property
+    def is_devrelease(self) -> bool:
+        return self.dev is not None
+
+    @property
+    def major(self) -> int:
+        return self.release[0] if len(self.release) >= 1 else 0
+
+    @property
+    def minor(self) -> int:
+        return self.release[1] if len(self.release) >= 2 else 0
+
+    @property
+    def micro(self) -> int:
+        return self.release[2] if len(self.release) >= 3 else 0
+
+
+def _parse_letter_version(
+    letter: str, number: Union[str, bytes, SupportsInt]
+) -> Optional[Tuple[str, int]]:
+
+    if letter:
+        # We consider there to be an implicit 0 in a pre-release if there is
+        # not a numeral associated with it.
+        if number is None:
+            number = 0
+
+        # We normalize any letters to their lower case form
+        letter = letter.lower()
+
+        # We consider some words to be alternate spellings of other words and
+        # in those cases we want to normalize the spellings to our preferred
+        # spelling.
+        if letter == "alpha":
+            letter = "a"
+        elif letter == "beta":
+            letter = "b"
+        elif letter in ["c", "pre", "preview"]:
+            letter = "rc"
+        elif letter in ["rev", "r"]:
+            letter = "post"
+
+        return letter, int(number)
+    if not letter and number:
+        # We assume if we are given a number, but we are not given a letter
+        # then this is using the implicit post release syntax (e.g. 1.0-1)
+        letter = "post"
+
+        return letter, int(number)
+
+    return None
+
+
+_local_version_separators = re.compile(r"[\._-]")
+
+
+def _parse_local_version(local: str) -> Optional[LocalType]:
+    """
+    Takes a string like abc.1.twelve and turns it into ("abc", 1, "twelve").
+    """
+    if local is not None:
+        return tuple(
+            part.lower() if not part.isdigit() else int(part)
+            for part in _local_version_separators.split(local)
+        )
+    return None
+
+
+def _cmpkey(
+    epoch: int,
+    release: Tuple[int, ...],
+    pre: Optional[Tuple[str, int]],
+    post: Optional[Tuple[str, int]],
+    dev: Optional[Tuple[str, int]],
+    local: Optional[Tuple[SubLocalType]],
+) -> CmpKey:
+
+    # When we compare a release version, we want to compare it with all of the
+    # trailing zeros removed. So we'll use a reverse the list, drop all the now
+    # leading zeros until we come to something non zero, then take the rest
+    # re-reverse it back into the correct order and make it a tuple and use
+    # that for our sorting key.
+    _release = tuple(
+        reversed(list(itertools.dropwhile(lambda x: x == 0, reversed(release))))
+    )
+
+    # We need to "trick" the sorting algorithm to put 1.0.dev0 before 1.0a0.
+    # We'll do this by abusing the pre segment, but we _only_ want to do this
+    # if there is not a pre or a post segment. If we have one of those then
+    # the normal sorting rules will handle this case correctly.
+    if pre is None and post is None and dev is not None:
+        _pre: PrePostDevType = NegativeInfinity
+    # Versions without a pre-release (except as noted above) should sort after
+    # those with one.
+    elif pre is None:
+        _pre = Infinity
+    else:
+        _pre = pre
+
+    # Versions without a post segment should sort before those with one.
+    if post is None:
+        _post: PrePostDevType = NegativeInfinity
+
+    else:
+        _post = post
+
+    # Versions without a development segment should sort after those with one.
+    if dev is None:
+        _dev: PrePostDevType = Infinity
+
+    else:
+        _dev = dev
+
+    if local is None:
+        # Versions without a local segment should sort before those with one.
+        _local: LocalType = NegativeInfinity
+    else:
+        # Versions with a local segment need that segment parsed to implement
+        # the sorting rules in PEP440.
+        # - Alpha numeric segments sort before numeric segments
+        # - Alpha numeric segments sort lexicographically
+        # - Numeric segments sort numerically
+        # - Shorter versions sort before longer versions when the prefixes
+        #   match exactly
+        _local = tuple(
+            (i, "") if isinstance(i, int) else (NegativeInfinity, i) for i in local
+        )
+
+    return epoch, _release, _pre, _post, _dev, _local
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pkg_resources/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pkg_resources/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..4cd562cf94c6d16f6b2b49b38549db9b914a6178
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pkg_resources/__init__.py
@@ -0,0 +1,3296 @@
+# coding: utf-8
+"""
+Package resource API
+--------------------
+
+A resource is a logical file contained within a package, or a logical
+subdirectory thereof.  The package resource API expects resource names
+to have their path parts separated with ``/``, *not* whatever the local
+path separator is.  Do not use os.path operations to manipulate resource
+names being passed into the API.
+
+The package resource API is designed to work with normal filesystem packages,
+.egg files, and unpacked .egg files.  It can also work in a limited way with
+.zip files and with custom PEP 302 loaders that support the ``get_data()``
+method.
+"""
+
+from __future__ import absolute_import
+
+import sys
+import os
+import io
+import time
+import re
+import types
+import zipfile
+import zipimport
+import warnings
+import stat
+import functools
+import pkgutil
+import operator
+import platform
+import collections
+import plistlib
+import email.parser
+import errno
+import tempfile
+import textwrap
+import itertools
+import inspect
+import ntpath
+import posixpath
+from pkgutil import get_importer
+
+try:
+    import _imp
+except ImportError:
+    # Python 3.2 compatibility
+    import imp as _imp
+
+try:
+    FileExistsError
+except NameError:
+    FileExistsError = OSError
+
+from pip._vendor import six
+from pip._vendor.six.moves import urllib, map, filter
+
+# capture these to bypass sandboxing
+from os import utime
+try:
+    from os import mkdir, rename, unlink
+    WRITE_SUPPORT = True
+except ImportError:
+    # no write support, probably under GAE
+    WRITE_SUPPORT = False
+
+from os import open as os_open
+from os.path import isdir, split
+
+try:
+    import importlib.machinery as importlib_machinery
+    # access attribute to force import under delayed import mechanisms.
+    importlib_machinery.__name__
+except ImportError:
+    importlib_machinery = None
+
+from . import py31compat
+from pip._vendor import platformdirs
+from pip._vendor import packaging
+__import__('pip._vendor.packaging.version')
+__import__('pip._vendor.packaging.specifiers')
+__import__('pip._vendor.packaging.requirements')
+__import__('pip._vendor.packaging.markers')
+
+
+__metaclass__ = type
+
+
+if (3, 0) < sys.version_info < (3, 5):
+    raise RuntimeError("Python 3.5 or later is required")
+
+if six.PY2:
+    # Those builtin exceptions are only defined in Python 3
+    PermissionError = None
+    NotADirectoryError = None
+
+# declare some globals that will be defined later to
+# satisfy the linters.
+require = None
+working_set = None
+add_activation_listener = None
+resources_stream = None
+cleanup_resources = None
+resource_dir = None
+resource_stream = None
+set_extraction_path = None
+resource_isdir = None
+resource_string = None
+iter_entry_points = None
+resource_listdir = None
+resource_filename = None
+resource_exists = None
+_distribution_finders = None
+_namespace_handlers = None
+_namespace_packages = None
+
+
+class PEP440Warning(RuntimeWarning):
+    """
+    Used when there is an issue with a version or specifier not complying with
+    PEP 440.
+    """
+
+
+def parse_version(v):
+    try:
+        return packaging.version.Version(v)
+    except packaging.version.InvalidVersion:
+        return packaging.version.LegacyVersion(v)
+
+
+_state_vars = {}
+
+
+def _declare_state(vartype, **kw):
+    globals().update(kw)
+    _state_vars.update(dict.fromkeys(kw, vartype))
+
+
+def __getstate__():
+    state = {}
+    g = globals()
+    for k, v in _state_vars.items():
+        state[k] = g['_sget_' + v](g[k])
+    return state
+
+
+def __setstate__(state):
+    g = globals()
+    for k, v in state.items():
+        g['_sset_' + _state_vars[k]](k, g[k], v)
+    return state
+
+
+def _sget_dict(val):
+    return val.copy()
+
+
+def _sset_dict(key, ob, state):
+    ob.clear()
+    ob.update(state)
+
+
+def _sget_object(val):
+    return val.__getstate__()
+
+
+def _sset_object(key, ob, state):
+    ob.__setstate__(state)
+
+
+_sget_none = _sset_none = lambda *args: None
+
+
+def get_supported_platform():
+    """Return this platform's maximum compatible version.
+
+    distutils.util.get_platform() normally reports the minimum version
+    of Mac OS X that would be required to *use* extensions produced by
+    distutils.  But what we want when checking compatibility is to know the
+    version of Mac OS X that we are *running*.  To allow usage of packages that
+    explicitly require a newer version of Mac OS X, we must also know the
+    current version of the OS.
+
+    If this condition occurs for any other platform with a version in its
+    platform strings, this function should be extended accordingly.
+    """
+    plat = get_build_platform()
+    m = macosVersionString.match(plat)
+    if m is not None and sys.platform == "darwin":
+        try:
+            plat = 'macosx-%s-%s' % ('.'.join(_macosx_vers()[:2]), m.group(3))
+        except ValueError:
+            # not Mac OS X
+            pass
+    return plat
+
+
+__all__ = [
+    # Basic resource access and distribution/entry point discovery
+    'require', 'run_script', 'get_provider', 'get_distribution',
+    'load_entry_point', 'get_entry_map', 'get_entry_info',
+    'iter_entry_points',
+    'resource_string', 'resource_stream', 'resource_filename',
+    'resource_listdir', 'resource_exists', 'resource_isdir',
+
+    # Environmental control
+    'declare_namespace', 'working_set', 'add_activation_listener',
+    'find_distributions', 'set_extraction_path', 'cleanup_resources',
+    'get_default_cache',
+
+    # Primary implementation classes
+    'Environment', 'WorkingSet', 'ResourceManager',
+    'Distribution', 'Requirement', 'EntryPoint',
+
+    # Exceptions
+    'ResolutionError', 'VersionConflict', 'DistributionNotFound',
+    'UnknownExtra', 'ExtractionError',
+
+    # Warnings
+    'PEP440Warning',
+
+    # Parsing functions and string utilities
+    'parse_requirements', 'parse_version', 'safe_name', 'safe_version',
+    'get_platform', 'compatible_platforms', 'yield_lines', 'split_sections',
+    'safe_extra', 'to_filename', 'invalid_marker', 'evaluate_marker',
+
+    # filesystem utilities
+    'ensure_directory', 'normalize_path',
+
+    # Distribution "precedence" constants
+    'EGG_DIST', 'BINARY_DIST', 'SOURCE_DIST', 'CHECKOUT_DIST', 'DEVELOP_DIST',
+
+    # "Provider" interfaces, implementations, and registration/lookup APIs
+    'IMetadataProvider', 'IResourceProvider', 'FileMetadata',
+    'PathMetadata', 'EggMetadata', 'EmptyProvider', 'empty_provider',
+    'NullProvider', 'EggProvider', 'DefaultProvider', 'ZipProvider',
+    'register_finder', 'register_namespace_handler', 'register_loader_type',
+    'fixup_namespace_packages', 'get_importer',
+
+    # Warnings
+    'PkgResourcesDeprecationWarning',
+
+    # Deprecated/backward compatibility only
+    'run_main', 'AvailableDistributions',
+]
+
+
+class ResolutionError(Exception):
+    """Abstract base for dependency resolution errors"""
+
+    def __repr__(self):
+        return self.__class__.__name__ + repr(self.args)
+
+
+class VersionConflict(ResolutionError):
+    """
+    An already-installed version conflicts with the requested version.
+
+    Should be initialized with the installed Distribution and the requested
+    Requirement.
+    """
+
+    _template = "{self.dist} is installed but {self.req} is required"
+
+    @property
+    def dist(self):
+        return self.args[0]
+
+    @property
+    def req(self):
+        return self.args[1]
+
+    def report(self):
+        return self._template.format(**locals())
+
+    def with_context(self, required_by):
+        """
+        If required_by is non-empty, return a version of self that is a
+        ContextualVersionConflict.
+        """
+        if not required_by:
+            return self
+        args = self.args + (required_by,)
+        return ContextualVersionConflict(*args)
+
+
+class ContextualVersionConflict(VersionConflict):
+    """
+    A VersionConflict that accepts a third parameter, the set of the
+    requirements that required the installed Distribution.
+    """
+
+    _template = VersionConflict._template + ' by {self.required_by}'
+
+    @property
+    def required_by(self):
+        return self.args[2]
+
+
+class DistributionNotFound(ResolutionError):
+    """A requested distribution was not found"""
+
+    _template = ("The '{self.req}' distribution was not found "
+                 "and is required by {self.requirers_str}")
+
+    @property
+    def req(self):
+        return self.args[0]
+
+    @property
+    def requirers(self):
+        return self.args[1]
+
+    @property
+    def requirers_str(self):
+        if not self.requirers:
+            return 'the application'
+        return ', '.join(self.requirers)
+
+    def report(self):
+        return self._template.format(**locals())
+
+    def __str__(self):
+        return self.report()
+
+
+class UnknownExtra(ResolutionError):
+    """Distribution doesn't have an "extra feature" of the given name"""
+
+
+_provider_factories = {}
+
+PY_MAJOR = '{}.{}'.format(*sys.version_info)
+EGG_DIST = 3
+BINARY_DIST = 2
+SOURCE_DIST = 1
+CHECKOUT_DIST = 0
+DEVELOP_DIST = -1
+
+
+def register_loader_type(loader_type, provider_factory):
+    """Register `provider_factory` to make providers for `loader_type`
+
+    `loader_type` is the type or class of a PEP 302 ``module.__loader__``,
+    and `provider_factory` is a function that, passed a *module* object,
+    returns an ``IResourceProvider`` for that module.
+    """
+    _provider_factories[loader_type] = provider_factory
+
+
+def get_provider(moduleOrReq):
+    """Return an IResourceProvider for the named module or requirement"""
+    if isinstance(moduleOrReq, Requirement):
+        return working_set.find(moduleOrReq) or require(str(moduleOrReq))[0]
+    try:
+        module = sys.modules[moduleOrReq]
+    except KeyError:
+        __import__(moduleOrReq)
+        module = sys.modules[moduleOrReq]
+    loader = getattr(module, '__loader__', None)
+    return _find_adapter(_provider_factories, loader)(module)
+
+
+def _macosx_vers(_cache=[]):
+    if not _cache:
+        version = platform.mac_ver()[0]
+        # fallback for MacPorts
+        if version == '':
+            plist = '/System/Library/CoreServices/SystemVersion.plist'
+            if os.path.exists(plist):
+                if hasattr(plistlib, 'readPlist'):
+                    plist_content = plistlib.readPlist(plist)
+                    if 'ProductVersion' in plist_content:
+                        version = plist_content['ProductVersion']
+
+        _cache.append(version.split('.'))
+    return _cache[0]
+
+
+def _macosx_arch(machine):
+    return {'PowerPC': 'ppc', 'Power_Macintosh': 'ppc'}.get(machine, machine)
+
+
+def get_build_platform():
+    """Return this platform's string for platform-specific distributions
+
+    XXX Currently this is the same as ``distutils.util.get_platform()``, but it
+    needs some hacks for Linux and Mac OS X.
+    """
+    from sysconfig import get_platform
+
+    plat = get_platform()
+    if sys.platform == "darwin" and not plat.startswith('macosx-'):
+        try:
+            version = _macosx_vers()
+            machine = os.uname()[4].replace(" ", "_")
+            return "macosx-%d.%d-%s" % (
+                int(version[0]), int(version[1]),
+                _macosx_arch(machine),
+            )
+        except ValueError:
+            # if someone is running a non-Mac darwin system, this will fall
+            # through to the default implementation
+            pass
+    return plat
+
+
+macosVersionString = re.compile(r"macosx-(\d+)\.(\d+)-(.*)")
+darwinVersionString = re.compile(r"darwin-(\d+)\.(\d+)\.(\d+)-(.*)")
+# XXX backward compat
+get_platform = get_build_platform
+
+
+def compatible_platforms(provided, required):
+    """Can code for the `provided` platform run on the `required` platform?
+
+    Returns true if either platform is ``None``, or the platforms are equal.
+
+    XXX Needs compatibility checks for Linux and other unixy OSes.
+    """
+    if provided is None or required is None or provided == required:
+        # easy case
+        return True
+
+    # Mac OS X special cases
+    reqMac = macosVersionString.match(required)
+    if reqMac:
+        provMac = macosVersionString.match(provided)
+
+        # is this a Mac package?
+        if not provMac:
+            # this is backwards compatibility for packages built before
+            # setuptools 0.6. All packages built after this point will
+            # use the new macosx designation.
+            provDarwin = darwinVersionString.match(provided)
+            if provDarwin:
+                dversion = int(provDarwin.group(1))
+                macosversion = "%s.%s" % (reqMac.group(1), reqMac.group(2))
+                if dversion == 7 and macosversion >= "10.3" or \
+                        dversion == 8 and macosversion >= "10.4":
+                    return True
+            # egg isn't macosx or legacy darwin
+            return False
+
+        # are they the same major version and machine type?
+        if provMac.group(1) != reqMac.group(1) or \
+                provMac.group(3) != reqMac.group(3):
+            return False
+
+        # is the required OS major update >= the provided one?
+        if int(provMac.group(2)) > int(reqMac.group(2)):
+            return False
+
+        return True
+
+    # XXX Linux and other platforms' special cases should go here
+    return False
+
+
+def run_script(dist_spec, script_name):
+    """Locate distribution `dist_spec` and run its `script_name` script"""
+    ns = sys._getframe(1).f_globals
+    name = ns['__name__']
+    ns.clear()
+    ns['__name__'] = name
+    require(dist_spec)[0].run_script(script_name, ns)
+
+
+# backward compatibility
+run_main = run_script
+
+
+def get_distribution(dist):
+    """Return a current distribution object for a Requirement or string"""
+    if isinstance(dist, six.string_types):
+        dist = Requirement.parse(dist)
+    if isinstance(dist, Requirement):
+        dist = get_provider(dist)
+    if not isinstance(dist, Distribution):
+        raise TypeError("Expected string, Requirement, or Distribution", dist)
+    return dist
+
+
+def load_entry_point(dist, group, name):
+    """Return `name` entry point of `group` for `dist` or raise ImportError"""
+    return get_distribution(dist).load_entry_point(group, name)
+
+
+def get_entry_map(dist, group=None):
+    """Return the entry point map for `group`, or the full entry map"""
+    return get_distribution(dist).get_entry_map(group)
+
+
+def get_entry_info(dist, group, name):
+    """Return the EntryPoint object for `group`+`name`, or ``None``"""
+    return get_distribution(dist).get_entry_info(group, name)
+
+
+class IMetadataProvider:
+    def has_metadata(name):
+        """Does the package's distribution contain the named metadata?"""
+
+    def get_metadata(name):
+        """The named metadata resource as a string"""
+
+    def get_metadata_lines(name):
+        """Yield named metadata resource as list of non-blank non-comment lines
+
+       Leading and trailing whitespace is stripped from each line, and lines
+       with ``#`` as the first non-blank character are omitted."""
+
+    def metadata_isdir(name):
+        """Is the named metadata a directory?  (like ``os.path.isdir()``)"""
+
+    def metadata_listdir(name):
+        """List of metadata names in the directory (like ``os.listdir()``)"""
+
+    def run_script(script_name, namespace):
+        """Execute the named script in the supplied namespace dictionary"""
+
+
+class IResourceProvider(IMetadataProvider):
+    """An object that provides access to package resources"""
+
+    def get_resource_filename(manager, resource_name):
+        """Return a true filesystem path for `resource_name`
+
+        `manager` must be an ``IResourceManager``"""
+
+    def get_resource_stream(manager, resource_name):
+        """Return a readable file-like object for `resource_name`
+
+        `manager` must be an ``IResourceManager``"""
+
+    def get_resource_string(manager, resource_name):
+        """Return a string containing the contents of `resource_name`
+
+        `manager` must be an ``IResourceManager``"""
+
+    def has_resource(resource_name):
+        """Does the package contain the named resource?"""
+
+    def resource_isdir(resource_name):
+        """Is the named resource a directory?  (like ``os.path.isdir()``)"""
+
+    def resource_listdir(resource_name):
+        """List of resource names in the directory (like ``os.listdir()``)"""
+
+
+class WorkingSet:
+    """A collection of active distributions on sys.path (or a similar list)"""
+
+    def __init__(self, entries=None):
+        """Create working set from list of path entries (default=sys.path)"""
+        self.entries = []
+        self.entry_keys = {}
+        self.by_key = {}
+        self.callbacks = []
+
+        if entries is None:
+            entries = sys.path
+
+        for entry in entries:
+            self.add_entry(entry)
+
+    @classmethod
+    def _build_master(cls):
+        """
+        Prepare the master working set.
+        """
+        ws = cls()
+        try:
+            from __main__ import __requires__
+        except ImportError:
+            # The main program does not list any requirements
+            return ws
+
+        # ensure the requirements are met
+        try:
+            ws.require(__requires__)
+        except VersionConflict:
+            return cls._build_from_requirements(__requires__)
+
+        return ws
+
+    @classmethod
+    def _build_from_requirements(cls, req_spec):
+        """
+        Build a working set from a requirement spec. Rewrites sys.path.
+        """
+        # try it without defaults already on sys.path
+        # by starting with an empty path
+        ws = cls([])
+        reqs = parse_requirements(req_spec)
+        dists = ws.resolve(reqs, Environment())
+        for dist in dists:
+            ws.add(dist)
+
+        # add any missing entries from sys.path
+        for entry in sys.path:
+            if entry not in ws.entries:
+                ws.add_entry(entry)
+
+        # then copy back to sys.path
+        sys.path[:] = ws.entries
+        return ws
+
+    def add_entry(self, entry):
+        """Add a path item to ``.entries``, finding any distributions on it
+
+        ``find_distributions(entry, True)`` is used to find distributions
+        corresponding to the path entry, and they are added.  `entry` is
+        always appended to ``.entries``, even if it is already present.
+        (This is because ``sys.path`` can contain the same value more than
+        once, and the ``.entries`` of the ``sys.path`` WorkingSet should always
+        equal ``sys.path``.)
+        """
+        self.entry_keys.setdefault(entry, [])
+        self.entries.append(entry)
+        for dist in find_distributions(entry, True):
+            self.add(dist, entry, False)
+
+    def __contains__(self, dist):
+        """True if `dist` is the active distribution for its project"""
+        return self.by_key.get(dist.key) == dist
+
+    def find(self, req):
+        """Find a distribution matching requirement `req`
+
+        If there is an active distribution for the requested project, this
+        returns it as long as it meets the version requirement specified by
+        `req`.  But, if there is an active distribution for the project and it
+        does *not* meet the `req` requirement, ``VersionConflict`` is raised.
+        If there is no active distribution for the requested project, ``None``
+        is returned.
+        """
+        dist = self.by_key.get(req.key)
+        if dist is not None and dist not in req:
+            # XXX add more info
+            raise VersionConflict(dist, req)
+        return dist
+
+    def iter_entry_points(self, group, name=None):
+        """Yield entry point objects from `group` matching `name`
+
+        If `name` is None, yields all entry points in `group` from all
+        distributions in the working set, otherwise only ones matching
+        both `group` and `name` are yielded (in distribution order).
+        """
+        return (
+            entry
+            for dist in self
+            for entry in dist.get_entry_map(group).values()
+            if name is None or name == entry.name
+        )
+
+    def run_script(self, requires, script_name):
+        """Locate distribution for `requires` and run `script_name` script"""
+        ns = sys._getframe(1).f_globals
+        name = ns['__name__']
+        ns.clear()
+        ns['__name__'] = name
+        self.require(requires)[0].run_script(script_name, ns)
+
+    def __iter__(self):
+        """Yield distributions for non-duplicate projects in the working set
+
+        The yield order is the order in which the items' path entries were
+        added to the working set.
+        """
+        seen = {}
+        for item in self.entries:
+            if item not in self.entry_keys:
+                # workaround a cache issue
+                continue
+
+            for key in self.entry_keys[item]:
+                if key not in seen:
+                    seen[key] = 1
+                    yield self.by_key[key]
+
+    def add(self, dist, entry=None, insert=True, replace=False):
+        """Add `dist` to working set, associated with `entry`
+
+        If `entry` is unspecified, it defaults to the ``.location`` of `dist`.
+        On exit from this routine, `entry` is added to the end of the working
+        set's ``.entries`` (if it wasn't already present).
+
+        `dist` is only added to the working set if it's for a project that
+        doesn't already have a distribution in the set, unless `replace=True`.
+        If it's added, any callbacks registered with the ``subscribe()`` method
+        will be called.
+        """
+        if insert:
+            dist.insert_on(self.entries, entry, replace=replace)
+
+        if entry is None:
+            entry = dist.location
+        keys = self.entry_keys.setdefault(entry, [])
+        keys2 = self.entry_keys.setdefault(dist.location, [])
+        if not replace and dist.key in self.by_key:
+            # ignore hidden distros
+            return
+
+        self.by_key[dist.key] = dist
+        if dist.key not in keys:
+            keys.append(dist.key)
+        if dist.key not in keys2:
+            keys2.append(dist.key)
+        self._added_new(dist)
+
+    def resolve(self, requirements, env=None, installer=None,
+                replace_conflicting=False, extras=None):
+        """List all distributions needed to (recursively) meet `requirements`
+
+        `requirements` must be a sequence of ``Requirement`` objects.  `env`,
+        if supplied, should be an ``Environment`` instance.  If
+        not supplied, it defaults to all distributions available within any
+        entry or distribution in the working set.  `installer`, if supplied,
+        will be invoked with each requirement that cannot be met by an
+        already-installed distribution; it should return a ``Distribution`` or
+        ``None``.
+
+        Unless `replace_conflicting=True`, raises a VersionConflict exception
+        if
+        any requirements are found on the path that have the correct name but
+        the wrong version.  Otherwise, if an `installer` is supplied it will be
+        invoked to obtain the correct version of the requirement and activate
+        it.
+
+        `extras` is a list of the extras to be used with these requirements.
+        This is important because extra requirements may look like `my_req;
+        extra = "my_extra"`, which would otherwise be interpreted as a purely
+        optional requirement.  Instead, we want to be able to assert that these
+        requirements are truly required.
+        """
+
+        # set up the stack
+        requirements = list(requirements)[::-1]
+        # set of processed requirements
+        processed = {}
+        # key -> dist
+        best = {}
+        to_activate = []
+
+        req_extras = _ReqExtras()
+
+        # Mapping of requirement to set of distributions that required it;
+        # useful for reporting info about conflicts.
+        required_by = collections.defaultdict(set)
+
+        while requirements:
+            # process dependencies breadth-first
+            req = requirements.pop(0)
+            if req in processed:
+                # Ignore cyclic or redundant dependencies
+                continue
+
+            if not req_extras.markers_pass(req, extras):
+                continue
+
+            dist = best.get(req.key)
+            if dist is None:
+                # Find the best distribution and add it to the map
+                dist = self.by_key.get(req.key)
+                if dist is None or (dist not in req and replace_conflicting):
+                    ws = self
+                    if env is None:
+                        if dist is None:
+                            env = Environment(self.entries)
+                        else:
+                            # Use an empty environment and workingset to avoid
+                            # any further conflicts with the conflicting
+                            # distribution
+                            env = Environment([])
+                            ws = WorkingSet([])
+                    dist = best[req.key] = env.best_match(
+                        req, ws, installer,
+                        replace_conflicting=replace_conflicting
+                    )
+                    if dist is None:
+                        requirers = required_by.get(req, None)
+                        raise DistributionNotFound(req, requirers)
+                to_activate.append(dist)
+            if dist not in req:
+                # Oops, the "best" so far conflicts with a dependency
+                dependent_req = required_by[req]
+                raise VersionConflict(dist, req).with_context(dependent_req)
+
+            # push the new requirements onto the stack
+            new_requirements = dist.requires(req.extras)[::-1]
+            requirements.extend(new_requirements)
+
+            # Register the new requirements needed by req
+            for new_requirement in new_requirements:
+                required_by[new_requirement].add(req.project_name)
+                req_extras[new_requirement] = req.extras
+
+            processed[req] = True
+
+        # return list of distros to activate
+        return to_activate
+
+    def find_plugins(
+            self, plugin_env, full_env=None, installer=None, fallback=True):
+        """Find all activatable distributions in `plugin_env`
+
+        Example usage::
+
+            distributions, errors = working_set.find_plugins(
+                Environment(plugin_dirlist)
+            )
+            # add plugins+libs to sys.path
+            map(working_set.add, distributions)
+            # display errors
+            print('Could not load', errors)
+
+        The `plugin_env` should be an ``Environment`` instance that contains
+        only distributions that are in the project's "plugin directory" or
+        directories. The `full_env`, if supplied, should be an ``Environment``
+        contains all currently-available distributions.  If `full_env` is not
+        supplied, one is created automatically from the ``WorkingSet`` this
+        method is called on, which will typically mean that every directory on
+        ``sys.path`` will be scanned for distributions.
+
+        `installer` is a standard installer callback as used by the
+        ``resolve()`` method. The `fallback` flag indicates whether we should
+        attempt to resolve older versions of a plugin if the newest version
+        cannot be resolved.
+
+        This method returns a 2-tuple: (`distributions`, `error_info`), where
+        `distributions` is a list of the distributions found in `plugin_env`
+        that were loadable, along with any other distributions that are needed
+        to resolve their dependencies.  `error_info` is a dictionary mapping
+        unloadable plugin distributions to an exception instance describing the
+        error that occurred. Usually this will be a ``DistributionNotFound`` or
+        ``VersionConflict`` instance.
+        """
+
+        plugin_projects = list(plugin_env)
+        # scan project names in alphabetic order
+        plugin_projects.sort()
+
+        error_info = {}
+        distributions = {}
+
+        if full_env is None:
+            env = Environment(self.entries)
+            env += plugin_env
+        else:
+            env = full_env + plugin_env
+
+        shadow_set = self.__class__([])
+        # put all our entries in shadow_set
+        list(map(shadow_set.add, self))
+
+        for project_name in plugin_projects:
+
+            for dist in plugin_env[project_name]:
+
+                req = [dist.as_requirement()]
+
+                try:
+                    resolvees = shadow_set.resolve(req, env, installer)
+
+                except ResolutionError as v:
+                    # save error info
+                    error_info[dist] = v
+                    if fallback:
+                        # try the next older version of project
+                        continue
+                    else:
+                        # give up on this project, keep going
+                        break
+
+                else:
+                    list(map(shadow_set.add, resolvees))
+                    distributions.update(dict.fromkeys(resolvees))
+
+                    # success, no need to try any more versions of this project
+                    break
+
+        distributions = list(distributions)
+        distributions.sort()
+
+        return distributions, error_info
+
+    def require(self, *requirements):
+        """Ensure that distributions matching `requirements` are activated
+
+        `requirements` must be a string or a (possibly-nested) sequence
+        thereof, specifying the distributions and versions required.  The
+        return value is a sequence of the distributions that needed to be
+        activated to fulfill the requirements; all relevant distributions are
+        included, even if they were already activated in this working set.
+        """
+        needed = self.resolve(parse_requirements(requirements))
+
+        for dist in needed:
+            self.add(dist)
+
+        return needed
+
+    def subscribe(self, callback, existing=True):
+        """Invoke `callback` for all distributions
+
+        If `existing=True` (default),
+        call on all existing ones, as well.
+        """
+        if callback in self.callbacks:
+            return
+        self.callbacks.append(callback)
+        if not existing:
+            return
+        for dist in self:
+            callback(dist)
+
+    def _added_new(self, dist):
+        for callback in self.callbacks:
+            callback(dist)
+
+    def __getstate__(self):
+        return (
+            self.entries[:], self.entry_keys.copy(), self.by_key.copy(),
+            self.callbacks[:]
+        )
+
+    def __setstate__(self, e_k_b_c):
+        entries, keys, by_key, callbacks = e_k_b_c
+        self.entries = entries[:]
+        self.entry_keys = keys.copy()
+        self.by_key = by_key.copy()
+        self.callbacks = callbacks[:]
+
+
+class _ReqExtras(dict):
+    """
+    Map each requirement to the extras that demanded it.
+    """
+
+    def markers_pass(self, req, extras=None):
+        """
+        Evaluate markers for req against each extra that
+        demanded it.
+
+        Return False if the req has a marker and fails
+        evaluation. Otherwise, return True.
+        """
+        extra_evals = (
+            req.marker.evaluate({'extra': extra})
+            for extra in self.get(req, ()) + (extras or (None,))
+        )
+        return not req.marker or any(extra_evals)
+
+
+class Environment:
+    """Searchable snapshot of distributions on a search path"""
+
+    def __init__(
+            self, search_path=None, platform=get_supported_platform(),
+            python=PY_MAJOR):
+        """Snapshot distributions available on a search path
+
+        Any distributions found on `search_path` are added to the environment.
+        `search_path` should be a sequence of ``sys.path`` items.  If not
+        supplied, ``sys.path`` is used.
+
+        `platform` is an optional string specifying the name of the platform
+        that platform-specific distributions must be compatible with.  If
+        unspecified, it defaults to the current platform.  `python` is an
+        optional string naming the desired version of Python (e.g. ``'3.6'``);
+        it defaults to the current version.
+
+        You may explicitly set `platform` (and/or `python`) to ``None`` if you
+        wish to map *all* distributions, not just those compatible with the
+        running platform or Python version.
+        """
+        self._distmap = {}
+        self.platform = platform
+        self.python = python
+        self.scan(search_path)
+
+    def can_add(self, dist):
+        """Is distribution `dist` acceptable for this environment?
+
+        The distribution must match the platform and python version
+        requirements specified when this environment was created, or False
+        is returned.
+        """
+        py_compat = (
+            self.python is None
+            or dist.py_version is None
+            or dist.py_version == self.python
+        )
+        return py_compat and compatible_platforms(dist.platform, self.platform)
+
+    def remove(self, dist):
+        """Remove `dist` from the environment"""
+        self._distmap[dist.key].remove(dist)
+
+    def scan(self, search_path=None):
+        """Scan `search_path` for distributions usable in this environment
+
+        Any distributions found are added to the environment.
+        `search_path` should be a sequence of ``sys.path`` items.  If not
+        supplied, ``sys.path`` is used.  Only distributions conforming to
+        the platform/python version defined at initialization are added.
+        """
+        if search_path is None:
+            search_path = sys.path
+
+        for item in search_path:
+            for dist in find_distributions(item):
+                self.add(dist)
+
+    def __getitem__(self, project_name):
+        """Return a newest-to-oldest list of distributions for `project_name`
+
+        Uses case-insensitive `project_name` comparison, assuming all the
+        project's distributions use their project's name converted to all
+        lowercase as their key.
+
+        """
+        distribution_key = project_name.lower()
+        return self._distmap.get(distribution_key, [])
+
+    def add(self, dist):
+        """Add `dist` if we ``can_add()`` it and it has not already been added
+        """
+        if self.can_add(dist) and dist.has_version():
+            dists = self._distmap.setdefault(dist.key, [])
+            if dist not in dists:
+                dists.append(dist)
+                dists.sort(key=operator.attrgetter('hashcmp'), reverse=True)
+
+    def best_match(
+            self, req, working_set, installer=None, replace_conflicting=False):
+        """Find distribution best matching `req` and usable on `working_set`
+
+        This calls the ``find(req)`` method of the `working_set` to see if a
+        suitable distribution is already active.  (This may raise
+        ``VersionConflict`` if an unsuitable version of the project is already
+        active in the specified `working_set`.)  If a suitable distribution
+        isn't active, this method returns the newest distribution in the
+        environment that meets the ``Requirement`` in `req`.  If no suitable
+        distribution is found, and `installer` is supplied, then the result of
+        calling the environment's ``obtain(req, installer)`` method will be
+        returned.
+        """
+        try:
+            dist = working_set.find(req)
+        except VersionConflict:
+            if not replace_conflicting:
+                raise
+            dist = None
+        if dist is not None:
+            return dist
+        for dist in self[req.key]:
+            if dist in req:
+                return dist
+        # try to download/install
+        return self.obtain(req, installer)
+
+    def obtain(self, requirement, installer=None):
+        """Obtain a distribution matching `requirement` (e.g. via download)
+
+        Obtain a distro that matches requirement (e.g. via download).  In the
+        base ``Environment`` class, this routine just returns
+        ``installer(requirement)``, unless `installer` is None, in which case
+        None is returned instead.  This method is a hook that allows subclasses
+        to attempt other ways of obtaining a distribution before falling back
+        to the `installer` argument."""
+        if installer is not None:
+            return installer(requirement)
+
+    def __iter__(self):
+        """Yield the unique project names of the available distributions"""
+        for key in self._distmap.keys():
+            if self[key]:
+                yield key
+
+    def __iadd__(self, other):
+        """In-place addition of a distribution or environment"""
+        if isinstance(other, Distribution):
+            self.add(other)
+        elif isinstance(other, Environment):
+            for project in other:
+                for dist in other[project]:
+                    self.add(dist)
+        else:
+            raise TypeError("Can't add %r to environment" % (other,))
+        return self
+
+    def __add__(self, other):
+        """Add an environment or distribution to an environment"""
+        new = self.__class__([], platform=None, python=None)
+        for env in self, other:
+            new += env
+        return new
+
+
+# XXX backward compatibility
+AvailableDistributions = Environment
+
+
+class ExtractionError(RuntimeError):
+    """An error occurred extracting a resource
+
+    The following attributes are available from instances of this exception:
+
+    manager
+        The resource manager that raised this exception
+
+    cache_path
+        The base directory for resource extraction
+
+    original_error
+        The exception instance that caused extraction to fail
+    """
+
+
+class ResourceManager:
+    """Manage resource extraction and packages"""
+    extraction_path = None
+
+    def __init__(self):
+        self.cached_files = {}
+
+    def resource_exists(self, package_or_requirement, resource_name):
+        """Does the named resource exist?"""
+        return get_provider(package_or_requirement).has_resource(resource_name)
+
+    def resource_isdir(self, package_or_requirement, resource_name):
+        """Is the named resource an existing directory?"""
+        return get_provider(package_or_requirement).resource_isdir(
+            resource_name
+        )
+
+    def resource_filename(self, package_or_requirement, resource_name):
+        """Return a true filesystem path for specified resource"""
+        return get_provider(package_or_requirement).get_resource_filename(
+            self, resource_name
+        )
+
+    def resource_stream(self, package_or_requirement, resource_name):
+        """Return a readable file-like object for specified resource"""
+        return get_provider(package_or_requirement).get_resource_stream(
+            self, resource_name
+        )
+
+    def resource_string(self, package_or_requirement, resource_name):
+        """Return specified resource as a string"""
+        return get_provider(package_or_requirement).get_resource_string(
+            self, resource_name
+        )
+
+    def resource_listdir(self, package_or_requirement, resource_name):
+        """List the contents of the named resource directory"""
+        return get_provider(package_or_requirement).resource_listdir(
+            resource_name
+        )
+
+    def extraction_error(self):
+        """Give an error message for problems extracting file(s)"""
+
+        old_exc = sys.exc_info()[1]
+        cache_path = self.extraction_path or get_default_cache()
+
+        tmpl = textwrap.dedent("""
+            Can't extract file(s) to egg cache
+
+            The following error occurred while trying to extract file(s)
+            to the Python egg cache:
+
+              {old_exc}
+
+            The Python egg cache directory is currently set to:
+
+              {cache_path}
+
+            Perhaps your account does not have write access to this directory?
+            You can change the cache directory by setting the PYTHON_EGG_CACHE
+            environment variable to point to an accessible directory.
+            """).lstrip()
+        err = ExtractionError(tmpl.format(**locals()))
+        err.manager = self
+        err.cache_path = cache_path
+        err.original_error = old_exc
+        raise err
+
+    def get_cache_path(self, archive_name, names=()):
+        """Return absolute location in cache for `archive_name` and `names`
+
+        The parent directory of the resulting path will be created if it does
+        not already exist.  `archive_name` should be the base filename of the
+        enclosing egg (which may not be the name of the enclosing zipfile!),
+        including its ".egg" extension.  `names`, if provided, should be a
+        sequence of path name parts "under" the egg's extraction location.
+
+        This method should only be called by resource providers that need to
+        obtain an extraction location, and only for names they intend to
+        extract, as it tracks the generated names for possible cleanup later.
+        """
+        extract_path = self.extraction_path or get_default_cache()
+        target_path = os.path.join(extract_path, archive_name + '-tmp', *names)
+        try:
+            _bypass_ensure_directory(target_path)
+        except Exception:
+            self.extraction_error()
+
+        self._warn_unsafe_extraction_path(extract_path)
+
+        self.cached_files[target_path] = 1
+        return target_path
+
+    @staticmethod
+    def _warn_unsafe_extraction_path(path):
+        """
+        If the default extraction path is overridden and set to an insecure
+        location, such as /tmp, it opens up an opportunity for an attacker to
+        replace an extracted file with an unauthorized payload. Warn the user
+        if a known insecure location is used.
+
+        See Distribute #375 for more details.
+        """
+        if os.name == 'nt' and not path.startswith(os.environ['windir']):
+            # On Windows, permissions are generally restrictive by default
+            #  and temp directories are not writable by other users, so
+            #  bypass the warning.
+            return
+        mode = os.stat(path).st_mode
+        if mode & stat.S_IWOTH or mode & stat.S_IWGRP:
+            msg = (
+                "%s is writable by group/others and vulnerable to attack "
+                "when "
+                "used with get_resource_filename. Consider a more secure "
+                "location (set with .set_extraction_path or the "
+                "PYTHON_EGG_CACHE environment variable)." % path
+            )
+            warnings.warn(msg, UserWarning)
+
+    def postprocess(self, tempname, filename):
+        """Perform any platform-specific postprocessing of `tempname`
+
+        This is where Mac header rewrites should be done; other platforms don't
+        have anything special they should do.
+
+        Resource providers should call this method ONLY after successfully
+        extracting a compressed resource.  They must NOT call it on resources
+        that are already in the filesystem.
+
+        `tempname` is the current (temporary) name of the file, and `filename`
+        is the name it will be renamed to by the caller after this routine
+        returns.
+        """
+
+        if os.name == 'posix':
+            # Make the resource executable
+            mode = ((os.stat(tempname).st_mode) | 0o555) & 0o7777
+            os.chmod(tempname, mode)
+
+    def set_extraction_path(self, path):
+        """Set the base path where resources will be extracted to, if needed.
+
+        If you do not call this routine before any extractions take place, the
+        path defaults to the return value of ``get_default_cache()``.  (Which
+        is based on the ``PYTHON_EGG_CACHE`` environment variable, with various
+        platform-specific fallbacks.  See that routine's documentation for more
+        details.)
+
+        Resources are extracted to subdirectories of this path based upon
+        information given by the ``IResourceProvider``.  You may set this to a
+        temporary directory, but then you must call ``cleanup_resources()`` to
+        delete the extracted files when done.  There is no guarantee that
+        ``cleanup_resources()`` will be able to remove all extracted files.
+
+        (Note: you may not change the extraction path for a given resource
+        manager once resources have been extracted, unless you first call
+        ``cleanup_resources()``.)
+        """
+        if self.cached_files:
+            raise ValueError(
+                "Can't change extraction path, files already extracted"
+            )
+
+        self.extraction_path = path
+
+    def cleanup_resources(self, force=False):
+        """
+        Delete all extracted resource files and directories, returning a list
+        of the file and directory names that could not be successfully removed.
+        This function does not have any concurrency protection, so it should
+        generally only be called when the extraction path is a temporary
+        directory exclusive to a single process.  This method is not
+        automatically called; you must call it explicitly or register it as an
+        ``atexit`` function if you wish to ensure cleanup of a temporary
+        directory used for extractions.
+        """
+        # XXX
+
+
+def get_default_cache():
+    """
+    Return the ``PYTHON_EGG_CACHE`` environment variable
+    or a platform-relevant user cache dir for an app
+    named "Python-Eggs".
+    """
+    return (
+        os.environ.get('PYTHON_EGG_CACHE')
+        or platformdirs.user_cache_dir(appname='Python-Eggs')
+    )
+
+
+def safe_name(name):
+    """Convert an arbitrary string to a standard distribution name
+
+    Any runs of non-alphanumeric/. characters are replaced with a single '-'.
+    """
+    return re.sub('[^A-Za-z0-9.]+', '-', name)
+
+
+def safe_version(version):
+    """
+    Convert an arbitrary string to a standard version string
+    """
+    try:
+        # normalize the version
+        return str(packaging.version.Version(version))
+    except packaging.version.InvalidVersion:
+        version = version.replace(' ', '.')
+        return re.sub('[^A-Za-z0-9.]+', '-', version)
+
+
+def safe_extra(extra):
+    """Convert an arbitrary string to a standard 'extra' name
+
+    Any runs of non-alphanumeric characters are replaced with a single '_',
+    and the result is always lowercased.
+    """
+    return re.sub('[^A-Za-z0-9.-]+', '_', extra).lower()
+
+
+def to_filename(name):
+    """Convert a project or version name to its filename-escaped form
+
+    Any '-' characters are currently replaced with '_'.
+    """
+    return name.replace('-', '_')
+
+
+def invalid_marker(text):
+    """
+    Validate text as a PEP 508 environment marker; return an exception
+    if invalid or False otherwise.
+    """
+    try:
+        evaluate_marker(text)
+    except SyntaxError as e:
+        e.filename = None
+        e.lineno = None
+        return e
+    return False
+
+
+def evaluate_marker(text, extra=None):
+    """
+    Evaluate a PEP 508 environment marker.
+    Return a boolean indicating the marker result in this environment.
+    Raise SyntaxError if marker is invalid.
+
+    This implementation uses the 'pyparsing' module.
+    """
+    try:
+        marker = packaging.markers.Marker(text)
+        return marker.evaluate()
+    except packaging.markers.InvalidMarker as e:
+        raise SyntaxError(e)
+
+
+class NullProvider:
+    """Try to implement resources and metadata for arbitrary PEP 302 loaders"""
+
+    egg_name = None
+    egg_info = None
+    loader = None
+
+    def __init__(self, module):
+        self.loader = getattr(module, '__loader__', None)
+        self.module_path = os.path.dirname(getattr(module, '__file__', ''))
+
+    def get_resource_filename(self, manager, resource_name):
+        return self._fn(self.module_path, resource_name)
+
+    def get_resource_stream(self, manager, resource_name):
+        return io.BytesIO(self.get_resource_string(manager, resource_name))
+
+    def get_resource_string(self, manager, resource_name):
+        return self._get(self._fn(self.module_path, resource_name))
+
+    def has_resource(self, resource_name):
+        return self._has(self._fn(self.module_path, resource_name))
+
+    def _get_metadata_path(self, name):
+        return self._fn(self.egg_info, name)
+
+    def has_metadata(self, name):
+        if not self.egg_info:
+            return self.egg_info
+
+        path = self._get_metadata_path(name)
+        return self._has(path)
+
+    def get_metadata(self, name):
+        if not self.egg_info:
+            return ""
+        path = self._get_metadata_path(name)
+        value = self._get(path)
+        if six.PY2:
+            return value
+        try:
+            return value.decode('utf-8')
+        except UnicodeDecodeError as exc:
+            # Include the path in the error message to simplify
+            # troubleshooting, and without changing the exception type.
+            exc.reason += ' in {} file at path: {}'.format(name, path)
+            raise
+
+    def get_metadata_lines(self, name):
+        return yield_lines(self.get_metadata(name))
+
+    def resource_isdir(self, resource_name):
+        return self._isdir(self._fn(self.module_path, resource_name))
+
+    def metadata_isdir(self, name):
+        return self.egg_info and self._isdir(self._fn(self.egg_info, name))
+
+    def resource_listdir(self, resource_name):
+        return self._listdir(self._fn(self.module_path, resource_name))
+
+    def metadata_listdir(self, name):
+        if self.egg_info:
+            return self._listdir(self._fn(self.egg_info, name))
+        return []
+
+    def run_script(self, script_name, namespace):
+        script = 'scripts/' + script_name
+        if not self.has_metadata(script):
+            raise ResolutionError(
+                "Script {script!r} not found in metadata at {self.egg_info!r}"
+                .format(**locals()),
+            )
+        script_text = self.get_metadata(script).replace('\r\n', '\n')
+        script_text = script_text.replace('\r', '\n')
+        script_filename = self._fn(self.egg_info, script)
+        namespace['__file__'] = script_filename
+        if os.path.exists(script_filename):
+            source = open(script_filename).read()
+            code = compile(source, script_filename, 'exec')
+            exec(code, namespace, namespace)
+        else:
+            from linecache import cache
+            cache[script_filename] = (
+                len(script_text), 0, script_text.split('\n'), script_filename
+            )
+            script_code = compile(script_text, script_filename, 'exec')
+            exec(script_code, namespace, namespace)
+
+    def _has(self, path):
+        raise NotImplementedError(
+            "Can't perform this operation for unregistered loader type"
+        )
+
+    def _isdir(self, path):
+        raise NotImplementedError(
+            "Can't perform this operation for unregistered loader type"
+        )
+
+    def _listdir(self, path):
+        raise NotImplementedError(
+            "Can't perform this operation for unregistered loader type"
+        )
+
+    def _fn(self, base, resource_name):
+        self._validate_resource_path(resource_name)
+        if resource_name:
+            return os.path.join(base, *resource_name.split('/'))
+        return base
+
+    @staticmethod
+    def _validate_resource_path(path):
+        """
+        Validate the resource paths according to the docs.
+        https://setuptools.readthedocs.io/en/latest/pkg_resources.html#basic-resource-access
+
+        >>> warned = getfixture('recwarn')
+        >>> warnings.simplefilter('always')
+        >>> vrp = NullProvider._validate_resource_path
+        >>> vrp('foo/bar.txt')
+        >>> bool(warned)
+        False
+        >>> vrp('../foo/bar.txt')
+        >>> bool(warned)
+        True
+        >>> warned.clear()
+        >>> vrp('/foo/bar.txt')
+        >>> bool(warned)
+        True
+        >>> vrp('foo/../../bar.txt')
+        >>> bool(warned)
+        True
+        >>> warned.clear()
+        >>> vrp('foo/f../bar.txt')
+        >>> bool(warned)
+        False
+
+        Windows path separators are straight-up disallowed.
+        >>> vrp(r'\\foo/bar.txt')
+        Traceback (most recent call last):
+        ...
+        ValueError: Use of .. or absolute path in a resource path \
+is not allowed.
+
+        >>> vrp(r'C:\\foo/bar.txt')
+        Traceback (most recent call last):
+        ...
+        ValueError: Use of .. or absolute path in a resource path \
+is not allowed.
+
+        Blank values are allowed
+
+        >>> vrp('')
+        >>> bool(warned)
+        False
+
+        Non-string values are not.
+
+        >>> vrp(None)
+        Traceback (most recent call last):
+        ...
+        AttributeError: ...
+        """
+        invalid = (
+            os.path.pardir in path.split(posixpath.sep) or
+            posixpath.isabs(path) or
+            ntpath.isabs(path)
+        )
+        if not invalid:
+            return
+
+        msg = "Use of .. or absolute path in a resource path is not allowed."
+
+        # Aggressively disallow Windows absolute paths
+        if ntpath.isabs(path) and not posixpath.isabs(path):
+            raise ValueError(msg)
+
+        # for compatibility, warn; in future
+        # raise ValueError(msg)
+        warnings.warn(
+            msg[:-1] + " and will raise exceptions in a future release.",
+            DeprecationWarning,
+            stacklevel=4,
+        )
+
+    def _get(self, path):
+        if hasattr(self.loader, 'get_data'):
+            return self.loader.get_data(path)
+        raise NotImplementedError(
+            "Can't perform this operation for loaders without 'get_data()'"
+        )
+
+
+register_loader_type(object, NullProvider)
+
+
+class EggProvider(NullProvider):
+    """Provider based on a virtual filesystem"""
+
+    def __init__(self, module):
+        NullProvider.__init__(self, module)
+        self._setup_prefix()
+
+    def _setup_prefix(self):
+        # we assume here that our metadata may be nested inside a "basket"
+        # of multiple eggs; that's why we use module_path instead of .archive
+        path = self.module_path
+        old = None
+        while path != old:
+            if _is_egg_path(path):
+                self.egg_name = os.path.basename(path)
+                self.egg_info = os.path.join(path, 'EGG-INFO')
+                self.egg_root = path
+                break
+            old = path
+            path, base = os.path.split(path)
+
+
+class DefaultProvider(EggProvider):
+    """Provides access to package resources in the filesystem"""
+
+    def _has(self, path):
+        return os.path.exists(path)
+
+    def _isdir(self, path):
+        return os.path.isdir(path)
+
+    def _listdir(self, path):
+        return os.listdir(path)
+
+    def get_resource_stream(self, manager, resource_name):
+        return open(self._fn(self.module_path, resource_name), 'rb')
+
+    def _get(self, path):
+        with open(path, 'rb') as stream:
+            return stream.read()
+
+    @classmethod
+    def _register(cls):
+        loader_names = 'SourceFileLoader', 'SourcelessFileLoader',
+        for name in loader_names:
+            loader_cls = getattr(importlib_machinery, name, type(None))
+            register_loader_type(loader_cls, cls)
+
+
+DefaultProvider._register()
+
+
+class EmptyProvider(NullProvider):
+    """Provider that returns nothing for all requests"""
+
+    module_path = None
+
+    _isdir = _has = lambda self, path: False
+
+    def _get(self, path):
+        return ''
+
+    def _listdir(self, path):
+        return []
+
+    def __init__(self):
+        pass
+
+
+empty_provider = EmptyProvider()
+
+
+class ZipManifests(dict):
+    """
+    zip manifest builder
+    """
+
+    @classmethod
+    def build(cls, path):
+        """
+        Build a dictionary similar to the zipimport directory
+        caches, except instead of tuples, store ZipInfo objects.
+
+        Use a platform-specific path separator (os.sep) for the path keys
+        for compatibility with pypy on Windows.
+        """
+        with zipfile.ZipFile(path) as zfile:
+            items = (
+                (
+                    name.replace('/', os.sep),
+                    zfile.getinfo(name),
+                )
+                for name in zfile.namelist()
+            )
+            return dict(items)
+
+    load = build
+
+
+class MemoizedZipManifests(ZipManifests):
+    """
+    Memoized zipfile manifests.
+    """
+    manifest_mod = collections.namedtuple('manifest_mod', 'manifest mtime')
+
+    def load(self, path):
+        """
+        Load a manifest at path or return a suitable manifest already loaded.
+        """
+        path = os.path.normpath(path)
+        mtime = os.stat(path).st_mtime
+
+        if path not in self or self[path].mtime != mtime:
+            manifest = self.build(path)
+            self[path] = self.manifest_mod(manifest, mtime)
+
+        return self[path].manifest
+
+
+class ZipProvider(EggProvider):
+    """Resource support for zips and eggs"""
+
+    eagers = None
+    _zip_manifests = MemoizedZipManifests()
+
+    def __init__(self, module):
+        EggProvider.__init__(self, module)
+        self.zip_pre = self.loader.archive + os.sep
+
+    def _zipinfo_name(self, fspath):
+        # Convert a virtual filename (full path to file) into a zipfile subpath
+        # usable with the zipimport directory cache for our target archive
+        fspath = fspath.rstrip(os.sep)
+        if fspath == self.loader.archive:
+            return ''
+        if fspath.startswith(self.zip_pre):
+            return fspath[len(self.zip_pre):]
+        raise AssertionError(
+            "%s is not a subpath of %s" % (fspath, self.zip_pre)
+        )
+
+    def _parts(self, zip_path):
+        # Convert a zipfile subpath into an egg-relative path part list.
+        # pseudo-fs path
+        fspath = self.zip_pre + zip_path
+        if fspath.startswith(self.egg_root + os.sep):
+            return fspath[len(self.egg_root) + 1:].split(os.sep)
+        raise AssertionError(
+            "%s is not a subpath of %s" % (fspath, self.egg_root)
+        )
+
+    @property
+    def zipinfo(self):
+        return self._zip_manifests.load(self.loader.archive)
+
+    def get_resource_filename(self, manager, resource_name):
+        if not self.egg_name:
+            raise NotImplementedError(
+                "resource_filename() only supported for .egg, not .zip"
+            )
+        # no need to lock for extraction, since we use temp names
+        zip_path = self._resource_to_zip(resource_name)
+        eagers = self._get_eager_resources()
+        if '/'.join(self._parts(zip_path)) in eagers:
+            for name in eagers:
+                self._extract_resource(manager, self._eager_to_zip(name))
+        return self._extract_resource(manager, zip_path)
+
+    @staticmethod
+    def _get_date_and_size(zip_stat):
+        size = zip_stat.file_size
+        # ymdhms+wday, yday, dst
+        date_time = zip_stat.date_time + (0, 0, -1)
+        # 1980 offset already done
+        timestamp = time.mktime(date_time)
+        return timestamp, size
+
+    def _extract_resource(self, manager, zip_path):
+
+        if zip_path in self._index():
+            for name in self._index()[zip_path]:
+                last = self._extract_resource(
+                    manager, os.path.join(zip_path, name)
+                )
+            # return the extracted directory name
+            return os.path.dirname(last)
+
+        timestamp, size = self._get_date_and_size(self.zipinfo[zip_path])
+
+        if not WRITE_SUPPORT:
+            raise IOError('"os.rename" and "os.unlink" are not supported '
+                          'on this platform')
+        try:
+
+            real_path = manager.get_cache_path(
+                self.egg_name, self._parts(zip_path)
+            )
+
+            if self._is_current(real_path, zip_path):
+                return real_path
+
+            outf, tmpnam = _mkstemp(
+                ".$extract",
+                dir=os.path.dirname(real_path),
+            )
+            os.write(outf, self.loader.get_data(zip_path))
+            os.close(outf)
+            utime(tmpnam, (timestamp, timestamp))
+            manager.postprocess(tmpnam, real_path)
+
+            try:
+                rename(tmpnam, real_path)
+
+            except os.error:
+                if os.path.isfile(real_path):
+                    if self._is_current(real_path, zip_path):
+                        # the file became current since it was checked above,
+                        #  so proceed.
+                        return real_path
+                    # Windows, del old file and retry
+                    elif os.name == 'nt':
+                        unlink(real_path)
+                        rename(tmpnam, real_path)
+                        return real_path
+                raise
+
+        except os.error:
+            # report a user-friendly error
+            manager.extraction_error()
+
+        return real_path
+
+    def _is_current(self, file_path, zip_path):
+        """
+        Return True if the file_path is current for this zip_path
+        """
+        timestamp, size = self._get_date_and_size(self.zipinfo[zip_path])
+        if not os.path.isfile(file_path):
+            return False
+        stat = os.stat(file_path)
+        if stat.st_size != size or stat.st_mtime != timestamp:
+            return False
+        # check that the contents match
+        zip_contents = self.loader.get_data(zip_path)
+        with open(file_path, 'rb') as f:
+            file_contents = f.read()
+        return zip_contents == file_contents
+
+    def _get_eager_resources(self):
+        if self.eagers is None:
+            eagers = []
+            for name in ('native_libs.txt', 'eager_resources.txt'):
+                if self.has_metadata(name):
+                    eagers.extend(self.get_metadata_lines(name))
+            self.eagers = eagers
+        return self.eagers
+
+    def _index(self):
+        try:
+            return self._dirindex
+        except AttributeError:
+            ind = {}
+            for path in self.zipinfo:
+                parts = path.split(os.sep)
+                while parts:
+                    parent = os.sep.join(parts[:-1])
+                    if parent in ind:
+                        ind[parent].append(parts[-1])
+                        break
+                    else:
+                        ind[parent] = [parts.pop()]
+            self._dirindex = ind
+            return ind
+
+    def _has(self, fspath):
+        zip_path = self._zipinfo_name(fspath)
+        return zip_path in self.zipinfo or zip_path in self._index()
+
+    def _isdir(self, fspath):
+        return self._zipinfo_name(fspath) in self._index()
+
+    def _listdir(self, fspath):
+        return list(self._index().get(self._zipinfo_name(fspath), ()))
+
+    def _eager_to_zip(self, resource_name):
+        return self._zipinfo_name(self._fn(self.egg_root, resource_name))
+
+    def _resource_to_zip(self, resource_name):
+        return self._zipinfo_name(self._fn(self.module_path, resource_name))
+
+
+register_loader_type(zipimport.zipimporter, ZipProvider)
+
+
+class FileMetadata(EmptyProvider):
+    """Metadata handler for standalone PKG-INFO files
+
+    Usage::
+
+        metadata = FileMetadata("/path/to/PKG-INFO")
+
+    This provider rejects all data and metadata requests except for PKG-INFO,
+    which is treated as existing, and will be the contents of the file at
+    the provided location.
+    """
+
+    def __init__(self, path):
+        self.path = path
+
+    def _get_metadata_path(self, name):
+        return self.path
+
+    def has_metadata(self, name):
+        return name == 'PKG-INFO' and os.path.isfile(self.path)
+
+    def get_metadata(self, name):
+        if name != 'PKG-INFO':
+            raise KeyError("No metadata except PKG-INFO is available")
+
+        with io.open(self.path, encoding='utf-8', errors="replace") as f:
+            metadata = f.read()
+        self._warn_on_replacement(metadata)
+        return metadata
+
+    def _warn_on_replacement(self, metadata):
+        # Python 2.7 compat for: replacement_char = '�'
+        replacement_char = b'\xef\xbf\xbd'.decode('utf-8')
+        if replacement_char in metadata:
+            tmpl = "{self.path} could not be properly decoded in UTF-8"
+            msg = tmpl.format(**locals())
+            warnings.warn(msg)
+
+    def get_metadata_lines(self, name):
+        return yield_lines(self.get_metadata(name))
+
+
+class PathMetadata(DefaultProvider):
+    """Metadata provider for egg directories
+
+    Usage::
+
+        # Development eggs:
+
+        egg_info = "/path/to/PackageName.egg-info"
+        base_dir = os.path.dirname(egg_info)
+        metadata = PathMetadata(base_dir, egg_info)
+        dist_name = os.path.splitext(os.path.basename(egg_info))[0]
+        dist = Distribution(basedir, project_name=dist_name, metadata=metadata)
+
+        # Unpacked egg directories:
+
+        egg_path = "/path/to/PackageName-ver-pyver-etc.egg"
+        metadata = PathMetadata(egg_path, os.path.join(egg_path,'EGG-INFO'))
+        dist = Distribution.from_filename(egg_path, metadata=metadata)
+    """
+
+    def __init__(self, path, egg_info):
+        self.module_path = path
+        self.egg_info = egg_info
+
+
+class EggMetadata(ZipProvider):
+    """Metadata provider for .egg files"""
+
+    def __init__(self, importer):
+        """Create a metadata provider from a zipimporter"""
+
+        self.zip_pre = importer.archive + os.sep
+        self.loader = importer
+        if importer.prefix:
+            self.module_path = os.path.join(importer.archive, importer.prefix)
+        else:
+            self.module_path = importer.archive
+        self._setup_prefix()
+
+
+_declare_state('dict', _distribution_finders={})
+
+
+def register_finder(importer_type, distribution_finder):
+    """Register `distribution_finder` to find distributions in sys.path items
+
+    `importer_type` is the type or class of a PEP 302 "Importer" (sys.path item
+    handler), and `distribution_finder` is a callable that, passed a path
+    item and the importer instance, yields ``Distribution`` instances found on
+    that path item.  See ``pkg_resources.find_on_path`` for an example."""
+    _distribution_finders[importer_type] = distribution_finder
+
+
+def find_distributions(path_item, only=False):
+    """Yield distributions accessible via `path_item`"""
+    importer = get_importer(path_item)
+    finder = _find_adapter(_distribution_finders, importer)
+    return finder(importer, path_item, only)
+
+
+def find_eggs_in_zip(importer, path_item, only=False):
+    """
+    Find eggs in zip files; possibly multiple nested eggs.
+    """
+    if importer.archive.endswith('.whl'):
+        # wheels are not supported with this finder
+        # they don't have PKG-INFO metadata, and won't ever contain eggs
+        return
+    metadata = EggMetadata(importer)
+    if metadata.has_metadata('PKG-INFO'):
+        yield Distribution.from_filename(path_item, metadata=metadata)
+    if only:
+        # don't yield nested distros
+        return
+    for subitem in metadata.resource_listdir(''):
+        if _is_egg_path(subitem):
+            subpath = os.path.join(path_item, subitem)
+            dists = find_eggs_in_zip(zipimport.zipimporter(subpath), subpath)
+            for dist in dists:
+                yield dist
+        elif subitem.lower().endswith('.dist-info'):
+            subpath = os.path.join(path_item, subitem)
+            submeta = EggMetadata(zipimport.zipimporter(subpath))
+            submeta.egg_info = subpath
+            yield Distribution.from_location(path_item, subitem, submeta)
+
+
+register_finder(zipimport.zipimporter, find_eggs_in_zip)
+
+
+def find_nothing(importer, path_item, only=False):
+    return ()
+
+
+register_finder(object, find_nothing)
+
+
+def _by_version_descending(names):
+    """
+    Given a list of filenames, return them in descending order
+    by version number.
+
+    >>> names = 'bar', 'foo', 'Python-2.7.10.egg', 'Python-2.7.2.egg'
+    >>> _by_version_descending(names)
+    ['Python-2.7.10.egg', 'Python-2.7.2.egg', 'foo', 'bar']
+    >>> names = 'Setuptools-1.2.3b1.egg', 'Setuptools-1.2.3.egg'
+    >>> _by_version_descending(names)
+    ['Setuptools-1.2.3.egg', 'Setuptools-1.2.3b1.egg']
+    >>> names = 'Setuptools-1.2.3b1.egg', 'Setuptools-1.2.3.post1.egg'
+    >>> _by_version_descending(names)
+    ['Setuptools-1.2.3.post1.egg', 'Setuptools-1.2.3b1.egg']
+    """
+    def _by_version(name):
+        """
+        Parse each component of the filename
+        """
+        name, ext = os.path.splitext(name)
+        parts = itertools.chain(name.split('-'), [ext])
+        return [packaging.version.parse(part) for part in parts]
+
+    return sorted(names, key=_by_version, reverse=True)
+
+
+def find_on_path(importer, path_item, only=False):
+    """Yield distributions accessible on a sys.path directory"""
+    path_item = _normalize_cached(path_item)
+
+    if _is_unpacked_egg(path_item):
+        yield Distribution.from_filename(
+            path_item, metadata=PathMetadata(
+                path_item, os.path.join(path_item, 'EGG-INFO')
+            )
+        )
+        return
+
+    entries = safe_listdir(path_item)
+
+    # for performance, before sorting by version,
+    # screen entries for only those that will yield
+    # distributions
+    filtered = (
+        entry
+        for entry in entries
+        if dist_factory(path_item, entry, only)
+    )
+
+    # scan for .egg and .egg-info in directory
+    path_item_entries = _by_version_descending(filtered)
+    for entry in path_item_entries:
+        fullpath = os.path.join(path_item, entry)
+        factory = dist_factory(path_item, entry, only)
+        for dist in factory(fullpath):
+            yield dist
+
+
+def dist_factory(path_item, entry, only):
+    """
+    Return a dist_factory for a path_item and entry
+    """
+    lower = entry.lower()
+    is_meta = any(map(lower.endswith, ('.egg-info', '.dist-info')))
+    return (
+        distributions_from_metadata
+        if is_meta else
+        find_distributions
+        if not only and _is_egg_path(entry) else
+        resolve_egg_link
+        if not only and lower.endswith('.egg-link') else
+        NoDists()
+    )
+
+
+class NoDists:
+    """
+    >>> bool(NoDists())
+    False
+
+    >>> list(NoDists()('anything'))
+    []
+    """
+    def __bool__(self):
+        return False
+    if six.PY2:
+        __nonzero__ = __bool__
+
+    def __call__(self, fullpath):
+        return iter(())
+
+
+def safe_listdir(path):
+    """
+    Attempt to list contents of path, but suppress some exceptions.
+    """
+    try:
+        return os.listdir(path)
+    except (PermissionError, NotADirectoryError):
+        pass
+    except OSError as e:
+        # Ignore the directory if does not exist, not a directory or
+        # permission denied
+        ignorable = (
+            e.errno in (errno.ENOTDIR, errno.EACCES, errno.ENOENT)
+            # Python 2 on Windows needs to be handled this way :(
+            or getattr(e, "winerror", None) == 267
+        )
+        if not ignorable:
+            raise
+    return ()
+
+
+def distributions_from_metadata(path):
+    root = os.path.dirname(path)
+    if os.path.isdir(path):
+        if len(os.listdir(path)) == 0:
+            # empty metadata dir; skip
+            return
+        metadata = PathMetadata(root, path)
+    else:
+        metadata = FileMetadata(path)
+    entry = os.path.basename(path)
+    yield Distribution.from_location(
+        root, entry, metadata, precedence=DEVELOP_DIST,
+    )
+
+
+def non_empty_lines(path):
+    """
+    Yield non-empty lines from file at path
+    """
+    with open(path) as f:
+        for line in f:
+            line = line.strip()
+            if line:
+                yield line
+
+
+def resolve_egg_link(path):
+    """
+    Given a path to an .egg-link, resolve distributions
+    present in the referenced path.
+    """
+    referenced_paths = non_empty_lines(path)
+    resolved_paths = (
+        os.path.join(os.path.dirname(path), ref)
+        for ref in referenced_paths
+    )
+    dist_groups = map(find_distributions, resolved_paths)
+    return next(dist_groups, ())
+
+
+register_finder(pkgutil.ImpImporter, find_on_path)
+
+if hasattr(importlib_machinery, 'FileFinder'):
+    register_finder(importlib_machinery.FileFinder, find_on_path)
+
+_declare_state('dict', _namespace_handlers={})
+_declare_state('dict', _namespace_packages={})
+
+
+def register_namespace_handler(importer_type, namespace_handler):
+    """Register `namespace_handler` to declare namespace packages
+
+    `importer_type` is the type or class of a PEP 302 "Importer" (sys.path item
+    handler), and `namespace_handler` is a callable like this::
+
+        def namespace_handler(importer, path_entry, moduleName, module):
+            # return a path_entry to use for child packages
+
+    Namespace handlers are only called if the importer object has already
+    agreed that it can handle the relevant path item, and they should only
+    return a subpath if the module __path__ does not already contain an
+    equivalent subpath.  For an example namespace handler, see
+    ``pkg_resources.file_ns_handler``.
+    """
+    _namespace_handlers[importer_type] = namespace_handler
+
+
+def _handle_ns(packageName, path_item):
+    """Ensure that named package includes a subpath of path_item (if needed)"""
+
+    importer = get_importer(path_item)
+    if importer is None:
+        return None
+
+    # capture warnings due to #1111
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        loader = importer.find_module(packageName)
+
+    if loader is None:
+        return None
+    module = sys.modules.get(packageName)
+    if module is None:
+        module = sys.modules[packageName] = types.ModuleType(packageName)
+        module.__path__ = []
+        _set_parent_ns(packageName)
+    elif not hasattr(module, '__path__'):
+        raise TypeError("Not a package:", packageName)
+    handler = _find_adapter(_namespace_handlers, importer)
+    subpath = handler(importer, path_item, packageName, module)
+    if subpath is not None:
+        path = module.__path__
+        path.append(subpath)
+        loader.load_module(packageName)
+        _rebuild_mod_path(path, packageName, module)
+    return subpath
+
+
+def _rebuild_mod_path(orig_path, package_name, module):
+    """
+    Rebuild module.__path__ ensuring that all entries are ordered
+    corresponding to their sys.path order
+    """
+    sys_path = [_normalize_cached(p) for p in sys.path]
+
+    def safe_sys_path_index(entry):
+        """
+        Workaround for #520 and #513.
+        """
+        try:
+            return sys_path.index(entry)
+        except ValueError:
+            return float('inf')
+
+    def position_in_sys_path(path):
+        """
+        Return the ordinal of the path based on its position in sys.path
+        """
+        path_parts = path.split(os.sep)
+        module_parts = package_name.count('.') + 1
+        parts = path_parts[:-module_parts]
+        return safe_sys_path_index(_normalize_cached(os.sep.join(parts)))
+
+    new_path = sorted(orig_path, key=position_in_sys_path)
+    new_path = [_normalize_cached(p) for p in new_path]
+
+    if isinstance(module.__path__, list):
+        module.__path__[:] = new_path
+    else:
+        module.__path__ = new_path
+
+
+def declare_namespace(packageName):
+    """Declare that package 'packageName' is a namespace package"""
+
+    _imp.acquire_lock()
+    try:
+        if packageName in _namespace_packages:
+            return
+
+        path = sys.path
+        parent, _, _ = packageName.rpartition('.')
+
+        if parent:
+            declare_namespace(parent)
+            if parent not in _namespace_packages:
+                __import__(parent)
+            try:
+                path = sys.modules[parent].__path__
+            except AttributeError:
+                raise TypeError("Not a package:", parent)
+
+        # Track what packages are namespaces, so when new path items are added,
+        # they can be updated
+        _namespace_packages.setdefault(parent or None, []).append(packageName)
+        _namespace_packages.setdefault(packageName, [])
+
+        for path_item in path:
+            # Ensure all the parent's path items are reflected in the child,
+            # if they apply
+            _handle_ns(packageName, path_item)
+
+    finally:
+        _imp.release_lock()
+
+
+def fixup_namespace_packages(path_item, parent=None):
+    """Ensure that previously-declared namespace packages include path_item"""
+    _imp.acquire_lock()
+    try:
+        for package in _namespace_packages.get(parent, ()):
+            subpath = _handle_ns(package, path_item)
+            if subpath:
+                fixup_namespace_packages(subpath, package)
+    finally:
+        _imp.release_lock()
+
+
+def file_ns_handler(importer, path_item, packageName, module):
+    """Compute an ns-package subpath for a filesystem or zipfile importer"""
+
+    subpath = os.path.join(path_item, packageName.split('.')[-1])
+    normalized = _normalize_cached(subpath)
+    for item in module.__path__:
+        if _normalize_cached(item) == normalized:
+            break
+    else:
+        # Only return the path if it's not already there
+        return subpath
+
+
+register_namespace_handler(pkgutil.ImpImporter, file_ns_handler)
+register_namespace_handler(zipimport.zipimporter, file_ns_handler)
+
+if hasattr(importlib_machinery, 'FileFinder'):
+    register_namespace_handler(importlib_machinery.FileFinder, file_ns_handler)
+
+
+def null_ns_handler(importer, path_item, packageName, module):
+    return None
+
+
+register_namespace_handler(object, null_ns_handler)
+
+
+def normalize_path(filename):
+    """Normalize a file/dir name for comparison purposes"""
+    return os.path.normcase(os.path.realpath(os.path.normpath(_cygwin_patch(filename))))
+
+
+def _cygwin_patch(filename):  # pragma: nocover
+    """
+    Contrary to POSIX 2008, on Cygwin, getcwd (3) contains
+    symlink components. Using
+    os.path.abspath() works around this limitation. A fix in os.getcwd()
+    would probably better, in Cygwin even more so, except
+    that this seems to be by design...
+    """
+    return os.path.abspath(filename) if sys.platform == 'cygwin' else filename
+
+
+def _normalize_cached(filename, _cache={}):
+    try:
+        return _cache[filename]
+    except KeyError:
+        _cache[filename] = result = normalize_path(filename)
+        return result
+
+
+def _is_egg_path(path):
+    """
+    Determine if given path appears to be an egg.
+    """
+    return path.lower().endswith('.egg')
+
+
+def _is_unpacked_egg(path):
+    """
+    Determine if given path appears to be an unpacked egg.
+    """
+    return (
+        _is_egg_path(path) and
+        os.path.isfile(os.path.join(path, 'EGG-INFO', 'PKG-INFO'))
+    )
+
+
+def _set_parent_ns(packageName):
+    parts = packageName.split('.')
+    name = parts.pop()
+    if parts:
+        parent = '.'.join(parts)
+        setattr(sys.modules[parent], name, sys.modules[packageName])
+
+
+def yield_lines(strs):
+    """Yield non-empty/non-comment lines of a string or sequence"""
+    if isinstance(strs, six.string_types):
+        for s in strs.splitlines():
+            s = s.strip()
+            # skip blank lines/comments
+            if s and not s.startswith('#'):
+                yield s
+    else:
+        for ss in strs:
+            for s in yield_lines(ss):
+                yield s
+
+
+MODULE = re.compile(r"\w+(\.\w+)*$").match
+EGG_NAME = re.compile(
+    r"""
+    (?P[^-]+) (
+        -(?P[^-]+) (
+            -py(?P[^-]+) (
+                -(?P.+)
+            )?
+        )?
+    )?
+    """,
+    re.VERBOSE | re.IGNORECASE,
+).match
+
+
+class EntryPoint:
+    """Object representing an advertised importable object"""
+
+    def __init__(self, name, module_name, attrs=(), extras=(), dist=None):
+        if not MODULE(module_name):
+            raise ValueError("Invalid module name", module_name)
+        self.name = name
+        self.module_name = module_name
+        self.attrs = tuple(attrs)
+        self.extras = tuple(extras)
+        self.dist = dist
+
+    def __str__(self):
+        s = "%s = %s" % (self.name, self.module_name)
+        if self.attrs:
+            s += ':' + '.'.join(self.attrs)
+        if self.extras:
+            s += ' [%s]' % ','.join(self.extras)
+        return s
+
+    def __repr__(self):
+        return "EntryPoint.parse(%r)" % str(self)
+
+    def load(self, require=True, *args, **kwargs):
+        """
+        Require packages for this EntryPoint, then resolve it.
+        """
+        if not require or args or kwargs:
+            warnings.warn(
+                "Parameters to load are deprecated.  Call .resolve and "
+                ".require separately.",
+                PkgResourcesDeprecationWarning,
+                stacklevel=2,
+            )
+        if require:
+            self.require(*args, **kwargs)
+        return self.resolve()
+
+    def resolve(self):
+        """
+        Resolve the entry point from its module and attrs.
+        """
+        module = __import__(self.module_name, fromlist=['__name__'], level=0)
+        try:
+            return functools.reduce(getattr, self.attrs, module)
+        except AttributeError as exc:
+            raise ImportError(str(exc))
+
+    def require(self, env=None, installer=None):
+        if self.extras and not self.dist:
+            raise UnknownExtra("Can't require() without a distribution", self)
+
+        # Get the requirements for this entry point with all its extras and
+        # then resolve them. We have to pass `extras` along when resolving so
+        # that the working set knows what extras we want. Otherwise, for
+        # dist-info distributions, the working set will assume that the
+        # requirements for that extra are purely optional and skip over them.
+        reqs = self.dist.requires(self.extras)
+        items = working_set.resolve(reqs, env, installer, extras=self.extras)
+        list(map(working_set.add, items))
+
+    pattern = re.compile(
+        r'\s*'
+        r'(?P.+?)\s*'
+        r'=\s*'
+        r'(?P[\w.]+)\s*'
+        r'(:\s*(?P[\w.]+))?\s*'
+        r'(?P\[.*\])?\s*$'
+    )
+
+    @classmethod
+    def parse(cls, src, dist=None):
+        """Parse a single entry point from string `src`
+
+        Entry point syntax follows the form::
+
+            name = some.module:some.attr [extra1, extra2]
+
+        The entry name and module name are required, but the ``:attrs`` and
+        ``[extras]`` parts are optional
+        """
+        m = cls.pattern.match(src)
+        if not m:
+            msg = "EntryPoint must be in 'name=module:attrs [extras]' format"
+            raise ValueError(msg, src)
+        res = m.groupdict()
+        extras = cls._parse_extras(res['extras'])
+        attrs = res['attr'].split('.') if res['attr'] else ()
+        return cls(res['name'], res['module'], attrs, extras, dist)
+
+    @classmethod
+    def _parse_extras(cls, extras_spec):
+        if not extras_spec:
+            return ()
+        req = Requirement.parse('x' + extras_spec)
+        if req.specs:
+            raise ValueError()
+        return req.extras
+
+    @classmethod
+    def parse_group(cls, group, lines, dist=None):
+        """Parse an entry point group"""
+        if not MODULE(group):
+            raise ValueError("Invalid group name", group)
+        this = {}
+        for line in yield_lines(lines):
+            ep = cls.parse(line, dist)
+            if ep.name in this:
+                raise ValueError("Duplicate entry point", group, ep.name)
+            this[ep.name] = ep
+        return this
+
+    @classmethod
+    def parse_map(cls, data, dist=None):
+        """Parse a map of entry point groups"""
+        if isinstance(data, dict):
+            data = data.items()
+        else:
+            data = split_sections(data)
+        maps = {}
+        for group, lines in data:
+            if group is None:
+                if not lines:
+                    continue
+                raise ValueError("Entry points must be listed in groups")
+            group = group.strip()
+            if group in maps:
+                raise ValueError("Duplicate group name", group)
+            maps[group] = cls.parse_group(group, lines, dist)
+        return maps
+
+
+def _remove_md5_fragment(location):
+    if not location:
+        return ''
+    parsed = urllib.parse.urlparse(location)
+    if parsed[-1].startswith('md5='):
+        return urllib.parse.urlunparse(parsed[:-1] + ('',))
+    return location
+
+
+def _version_from_file(lines):
+    """
+    Given an iterable of lines from a Metadata file, return
+    the value of the Version field, if present, or None otherwise.
+    """
+    def is_version_line(line):
+        return line.lower().startswith('version:')
+    version_lines = filter(is_version_line, lines)
+    line = next(iter(version_lines), '')
+    _, _, value = line.partition(':')
+    return safe_version(value.strip()) or None
+
+
+class Distribution:
+    """Wrap an actual or potential sys.path entry w/metadata"""
+    PKG_INFO = 'PKG-INFO'
+
+    def __init__(
+            self, location=None, metadata=None, project_name=None,
+            version=None, py_version=PY_MAJOR, platform=None,
+            precedence=EGG_DIST):
+        self.project_name = safe_name(project_name or 'Unknown')
+        if version is not None:
+            self._version = safe_version(version)
+        self.py_version = py_version
+        self.platform = platform
+        self.location = location
+        self.precedence = precedence
+        self._provider = metadata or empty_provider
+
+    @classmethod
+    def from_location(cls, location, basename, metadata=None, **kw):
+        project_name, version, py_version, platform = [None] * 4
+        basename, ext = os.path.splitext(basename)
+        if ext.lower() in _distributionImpl:
+            cls = _distributionImpl[ext.lower()]
+
+            match = EGG_NAME(basename)
+            if match:
+                project_name, version, py_version, platform = match.group(
+                    'name', 'ver', 'pyver', 'plat'
+                )
+        return cls(
+            location, metadata, project_name=project_name, version=version,
+            py_version=py_version, platform=platform, **kw
+        )._reload_version()
+
+    def _reload_version(self):
+        return self
+
+    @property
+    def hashcmp(self):
+        return (
+            self.parsed_version,
+            self.precedence,
+            self.key,
+            _remove_md5_fragment(self.location),
+            self.py_version or '',
+            self.platform or '',
+        )
+
+    def __hash__(self):
+        return hash(self.hashcmp)
+
+    def __lt__(self, other):
+        return self.hashcmp < other.hashcmp
+
+    def __le__(self, other):
+        return self.hashcmp <= other.hashcmp
+
+    def __gt__(self, other):
+        return self.hashcmp > other.hashcmp
+
+    def __ge__(self, other):
+        return self.hashcmp >= other.hashcmp
+
+    def __eq__(self, other):
+        if not isinstance(other, self.__class__):
+            # It's not a Distribution, so they are not equal
+            return False
+        return self.hashcmp == other.hashcmp
+
+    def __ne__(self, other):
+        return not self == other
+
+    # These properties have to be lazy so that we don't have to load any
+    # metadata until/unless it's actually needed.  (i.e., some distributions
+    # may not know their name or version without loading PKG-INFO)
+
+    @property
+    def key(self):
+        try:
+            return self._key
+        except AttributeError:
+            self._key = key = self.project_name.lower()
+            return key
+
+    @property
+    def parsed_version(self):
+        if not hasattr(self, "_parsed_version"):
+            self._parsed_version = parse_version(self.version)
+
+        return self._parsed_version
+
+    def _warn_legacy_version(self):
+        LV = packaging.version.LegacyVersion
+        is_legacy = isinstance(self._parsed_version, LV)
+        if not is_legacy:
+            return
+
+        # While an empty version is technically a legacy version and
+        # is not a valid PEP 440 version, it's also unlikely to
+        # actually come from someone and instead it is more likely that
+        # it comes from setuptools attempting to parse a filename and
+        # including it in the list. So for that we'll gate this warning
+        # on if the version is anything at all or not.
+        if not self.version:
+            return
+
+        tmpl = textwrap.dedent("""
+            '{project_name} ({version})' is being parsed as a legacy,
+            non PEP 440,
+            version. You may find odd behavior and sort order.
+            In particular it will be sorted as less than 0.0. It
+            is recommended to migrate to PEP 440 compatible
+            versions.
+            """).strip().replace('\n', ' ')
+
+        warnings.warn(tmpl.format(**vars(self)), PEP440Warning)
+
+    @property
+    def version(self):
+        try:
+            return self._version
+        except AttributeError:
+            version = self._get_version()
+            if version is None:
+                path = self._get_metadata_path_for_display(self.PKG_INFO)
+                msg = (
+                    "Missing 'Version:' header and/or {} file at path: {}"
+                ).format(self.PKG_INFO, path)
+                raise ValueError(msg, self)
+
+            return version
+
+    @property
+    def _dep_map(self):
+        """
+        A map of extra to its list of (direct) requirements
+        for this distribution, including the null extra.
+        """
+        try:
+            return self.__dep_map
+        except AttributeError:
+            self.__dep_map = self._filter_extras(self._build_dep_map())
+        return self.__dep_map
+
+    @staticmethod
+    def _filter_extras(dm):
+        """
+        Given a mapping of extras to dependencies, strip off
+        environment markers and filter out any dependencies
+        not matching the markers.
+        """
+        for extra in list(filter(None, dm)):
+            new_extra = extra
+            reqs = dm.pop(extra)
+            new_extra, _, marker = extra.partition(':')
+            fails_marker = marker and (
+                invalid_marker(marker)
+                or not evaluate_marker(marker)
+            )
+            if fails_marker:
+                reqs = []
+            new_extra = safe_extra(new_extra) or None
+
+            dm.setdefault(new_extra, []).extend(reqs)
+        return dm
+
+    def _build_dep_map(self):
+        dm = {}
+        for name in 'requires.txt', 'depends.txt':
+            for extra, reqs in split_sections(self._get_metadata(name)):
+                dm.setdefault(extra, []).extend(parse_requirements(reqs))
+        return dm
+
+    def requires(self, extras=()):
+        """List of Requirements needed for this distro if `extras` are used"""
+        dm = self._dep_map
+        deps = []
+        deps.extend(dm.get(None, ()))
+        for ext in extras:
+            try:
+                deps.extend(dm[safe_extra(ext)])
+            except KeyError:
+                raise UnknownExtra(
+                    "%s has no such extra feature %r" % (self, ext)
+                )
+        return deps
+
+    def _get_metadata_path_for_display(self, name):
+        """
+        Return the path to the given metadata file, if available.
+        """
+        try:
+            # We need to access _get_metadata_path() on the provider object
+            # directly rather than through this class's __getattr__()
+            # since _get_metadata_path() is marked private.
+            path = self._provider._get_metadata_path(name)
+
+        # Handle exceptions e.g. in case the distribution's metadata
+        # provider doesn't support _get_metadata_path().
+        except Exception:
+            return '[could not detect]'
+
+        return path
+
+    def _get_metadata(self, name):
+        if self.has_metadata(name):
+            for line in self.get_metadata_lines(name):
+                yield line
+
+    def _get_version(self):
+        lines = self._get_metadata(self.PKG_INFO)
+        version = _version_from_file(lines)
+
+        return version
+
+    def activate(self, path=None, replace=False):
+        """Ensure distribution is importable on `path` (default=sys.path)"""
+        if path is None:
+            path = sys.path
+        self.insert_on(path, replace=replace)
+        if path is sys.path:
+            fixup_namespace_packages(self.location)
+            for pkg in self._get_metadata('namespace_packages.txt'):
+                if pkg in sys.modules:
+                    declare_namespace(pkg)
+
+    def egg_name(self):
+        """Return what this distribution's standard .egg filename should be"""
+        filename = "%s-%s-py%s" % (
+            to_filename(self.project_name), to_filename(self.version),
+            self.py_version or PY_MAJOR
+        )
+
+        if self.platform:
+            filename += '-' + self.platform
+        return filename
+
+    def __repr__(self):
+        if self.location:
+            return "%s (%s)" % (self, self.location)
+        else:
+            return str(self)
+
+    def __str__(self):
+        try:
+            version = getattr(self, 'version', None)
+        except ValueError:
+            version = None
+        version = version or "[unknown version]"
+        return "%s %s" % (self.project_name, version)
+
+    def __getattr__(self, attr):
+        """Delegate all unrecognized public attributes to .metadata provider"""
+        if attr.startswith('_'):
+            raise AttributeError(attr)
+        return getattr(self._provider, attr)
+
+    def __dir__(self):
+        return list(
+            set(super(Distribution, self).__dir__())
+            | set(
+                attr for attr in self._provider.__dir__()
+                if not attr.startswith('_')
+            )
+        )
+
+    if not hasattr(object, '__dir__'):
+        # python 2.7 not supported
+        del __dir__
+
+    @classmethod
+    def from_filename(cls, filename, metadata=None, **kw):
+        return cls.from_location(
+            _normalize_cached(filename), os.path.basename(filename), metadata,
+            **kw
+        )
+
+    def as_requirement(self):
+        """Return a ``Requirement`` that matches this distribution exactly"""
+        if isinstance(self.parsed_version, packaging.version.Version):
+            spec = "%s==%s" % (self.project_name, self.parsed_version)
+        else:
+            spec = "%s===%s" % (self.project_name, self.parsed_version)
+
+        return Requirement.parse(spec)
+
+    def load_entry_point(self, group, name):
+        """Return the `name` entry point of `group` or raise ImportError"""
+        ep = self.get_entry_info(group, name)
+        if ep is None:
+            raise ImportError("Entry point %r not found" % ((group, name),))
+        return ep.load()
+
+    def get_entry_map(self, group=None):
+        """Return the entry point map for `group`, or the full entry map"""
+        try:
+            ep_map = self._ep_map
+        except AttributeError:
+            ep_map = self._ep_map = EntryPoint.parse_map(
+                self._get_metadata('entry_points.txt'), self
+            )
+        if group is not None:
+            return ep_map.get(group, {})
+        return ep_map
+
+    def get_entry_info(self, group, name):
+        """Return the EntryPoint object for `group`+`name`, or ``None``"""
+        return self.get_entry_map(group).get(name)
+
+    def insert_on(self, path, loc=None, replace=False):
+        """Ensure self.location is on path
+
+        If replace=False (default):
+            - If location is already in path anywhere, do nothing.
+            - Else:
+              - If it's an egg and its parent directory is on path,
+                insert just ahead of the parent.
+              - Else: add to the end of path.
+        If replace=True:
+            - If location is already on path anywhere (not eggs)
+              or higher priority than its parent (eggs)
+              do nothing.
+            - Else:
+              - If it's an egg and its parent directory is on path,
+                insert just ahead of the parent,
+                removing any lower-priority entries.
+              - Else: add it to the front of path.
+        """
+
+        loc = loc or self.location
+        if not loc:
+            return
+
+        nloc = _normalize_cached(loc)
+        bdir = os.path.dirname(nloc)
+        npath = [(p and _normalize_cached(p) or p) for p in path]
+
+        for p, item in enumerate(npath):
+            if item == nloc:
+                if replace:
+                    break
+                else:
+                    # don't modify path (even removing duplicates) if
+                    # found and not replace
+                    return
+            elif item == bdir and self.precedence == EGG_DIST:
+                # if it's an .egg, give it precedence over its directory
+                # UNLESS it's already been added to sys.path and replace=False
+                if (not replace) and nloc in npath[p:]:
+                    return
+                if path is sys.path:
+                    self.check_version_conflict()
+                path.insert(p, loc)
+                npath.insert(p, nloc)
+                break
+        else:
+            if path is sys.path:
+                self.check_version_conflict()
+            if replace:
+                path.insert(0, loc)
+            else:
+                path.append(loc)
+            return
+
+        # p is the spot where we found or inserted loc; now remove duplicates
+        while True:
+            try:
+                np = npath.index(nloc, p + 1)
+            except ValueError:
+                break
+            else:
+                del npath[np], path[np]
+                # ha!
+                p = np
+
+        return
+
+    def check_version_conflict(self):
+        if self.key == 'setuptools':
+            # ignore the inevitable setuptools self-conflicts  :(
+            return
+
+        nsp = dict.fromkeys(self._get_metadata('namespace_packages.txt'))
+        loc = normalize_path(self.location)
+        for modname in self._get_metadata('top_level.txt'):
+            if (modname not in sys.modules or modname in nsp
+                    or modname in _namespace_packages):
+                continue
+            if modname in ('pkg_resources', 'setuptools', 'site'):
+                continue
+            fn = getattr(sys.modules[modname], '__file__', None)
+            if fn and (normalize_path(fn).startswith(loc) or
+                       fn.startswith(self.location)):
+                continue
+            issue_warning(
+                "Module %s was already imported from %s, but %s is being added"
+                " to sys.path" % (modname, fn, self.location),
+            )
+
+    def has_version(self):
+        try:
+            self.version
+        except ValueError:
+            issue_warning("Unbuilt egg for " + repr(self))
+            return False
+        return True
+
+    def clone(self, **kw):
+        """Copy this distribution, substituting in any changed keyword args"""
+        names = 'project_name version py_version platform location precedence'
+        for attr in names.split():
+            kw.setdefault(attr, getattr(self, attr, None))
+        kw.setdefault('metadata', self._provider)
+        return self.__class__(**kw)
+
+    @property
+    def extras(self):
+        return [dep for dep in self._dep_map if dep]
+
+
+class EggInfoDistribution(Distribution):
+    def _reload_version(self):
+        """
+        Packages installed by distutils (e.g. numpy or scipy),
+        which uses an old safe_version, and so
+        their version numbers can get mangled when
+        converted to filenames (e.g., 1.11.0.dev0+2329eae to
+        1.11.0.dev0_2329eae). These distributions will not be
+        parsed properly
+        downstream by Distribution and safe_version, so
+        take an extra step and try to get the version number from
+        the metadata file itself instead of the filename.
+        """
+        md_version = self._get_version()
+        if md_version:
+            self._version = md_version
+        return self
+
+
+class DistInfoDistribution(Distribution):
+    """
+    Wrap an actual or potential sys.path entry
+    w/metadata, .dist-info style.
+    """
+    PKG_INFO = 'METADATA'
+    EQEQ = re.compile(r"([\(,])\s*(\d.*?)\s*([,\)])")
+
+    @property
+    def _parsed_pkg_info(self):
+        """Parse and cache metadata"""
+        try:
+            return self._pkg_info
+        except AttributeError:
+            metadata = self.get_metadata(self.PKG_INFO)
+            self._pkg_info = email.parser.Parser().parsestr(metadata)
+            return self._pkg_info
+
+    @property
+    def _dep_map(self):
+        try:
+            return self.__dep_map
+        except AttributeError:
+            self.__dep_map = self._compute_dependencies()
+            return self.__dep_map
+
+    def _compute_dependencies(self):
+        """Recompute this distribution's dependencies."""
+        dm = self.__dep_map = {None: []}
+
+        reqs = []
+        # Including any condition expressions
+        for req in self._parsed_pkg_info.get_all('Requires-Dist') or []:
+            reqs.extend(parse_requirements(req))
+
+        def reqs_for_extra(extra):
+            for req in reqs:
+                if not req.marker or req.marker.evaluate({'extra': extra}):
+                    yield req
+
+        common = frozenset(reqs_for_extra(None))
+        dm[None].extend(common)
+
+        for extra in self._parsed_pkg_info.get_all('Provides-Extra') or []:
+            s_extra = safe_extra(extra.strip())
+            dm[s_extra] = list(frozenset(reqs_for_extra(extra)) - common)
+
+        return dm
+
+
+_distributionImpl = {
+    '.egg': Distribution,
+    '.egg-info': EggInfoDistribution,
+    '.dist-info': DistInfoDistribution,
+}
+
+
+def issue_warning(*args, **kw):
+    level = 1
+    g = globals()
+    try:
+        # find the first stack frame that is *not* code in
+        # the pkg_resources module, to use for the warning
+        while sys._getframe(level).f_globals is g:
+            level += 1
+    except ValueError:
+        pass
+    warnings.warn(stacklevel=level + 1, *args, **kw)
+
+
+class RequirementParseError(ValueError):
+    def __str__(self):
+        return ' '.join(self.args)
+
+
+def parse_requirements(strs):
+    """Yield ``Requirement`` objects for each specification in `strs`
+
+    `strs` must be a string, or a (possibly-nested) iterable thereof.
+    """
+    # create a steppable iterator, so we can handle \-continuations
+    lines = iter(yield_lines(strs))
+
+    for line in lines:
+        # Drop comments -- a hash without a space may be in a URL.
+        if ' #' in line:
+            line = line[:line.find(' #')]
+        # If there is a line continuation, drop it, and append the next line.
+        if line.endswith('\\'):
+            line = line[:-2].strip()
+            try:
+                line += next(lines)
+            except StopIteration:
+                return
+        yield Requirement(line)
+
+
+class Requirement(packaging.requirements.Requirement):
+    def __init__(self, requirement_string):
+        """DO NOT CALL THIS UNDOCUMENTED METHOD; use Requirement.parse()!"""
+        try:
+            super(Requirement, self).__init__(requirement_string)
+        except packaging.requirements.InvalidRequirement as e:
+            raise RequirementParseError(str(e))
+        self.unsafe_name = self.name
+        project_name = safe_name(self.name)
+        self.project_name, self.key = project_name, project_name.lower()
+        self.specs = [
+            (spec.operator, spec.version) for spec in self.specifier]
+        self.extras = tuple(map(safe_extra, self.extras))
+        self.hashCmp = (
+            self.key,
+            self.url,
+            self.specifier,
+            frozenset(self.extras),
+            str(self.marker) if self.marker else None,
+        )
+        self.__hash = hash(self.hashCmp)
+
+    def __eq__(self, other):
+        return (
+            isinstance(other, Requirement) and
+            self.hashCmp == other.hashCmp
+        )
+
+    def __ne__(self, other):
+        return not self == other
+
+    def __contains__(self, item):
+        if isinstance(item, Distribution):
+            if item.key != self.key:
+                return False
+
+            item = item.version
+
+        # Allow prereleases always in order to match the previous behavior of
+        # this method. In the future this should be smarter and follow PEP 440
+        # more accurately.
+        return self.specifier.contains(item, prereleases=True)
+
+    def __hash__(self):
+        return self.__hash
+
+    def __repr__(self):
+        return "Requirement.parse(%r)" % str(self)
+
+    @staticmethod
+    def parse(s):
+        req, = parse_requirements(s)
+        return req
+
+
+def _always_object(classes):
+    """
+    Ensure object appears in the mro even
+    for old-style classes.
+    """
+    if object not in classes:
+        return classes + (object,)
+    return classes
+
+
+def _find_adapter(registry, ob):
+    """Return an adapter factory for `ob` from `registry`"""
+    types = _always_object(inspect.getmro(getattr(ob, '__class__', type(ob))))
+    for t in types:
+        if t in registry:
+            return registry[t]
+
+
+def ensure_directory(path):
+    """Ensure that the parent directory of `path` exists"""
+    dirname = os.path.dirname(path)
+    py31compat.makedirs(dirname, exist_ok=True)
+
+
+def _bypass_ensure_directory(path):
+    """Sandbox-bypassing version of ensure_directory()"""
+    if not WRITE_SUPPORT:
+        raise IOError('"os.mkdir" not supported on this platform.')
+    dirname, filename = split(path)
+    if dirname and filename and not isdir(dirname):
+        _bypass_ensure_directory(dirname)
+        try:
+            mkdir(dirname, 0o755)
+        except FileExistsError:
+            pass
+
+
+def split_sections(s):
+    """Split a string or iterable thereof into (section, content) pairs
+
+    Each ``section`` is a stripped version of the section header ("[section]")
+    and each ``content`` is a list of stripped lines excluding blank lines and
+    comment-only lines.  If there are any such lines before the first section
+    header, they're returned in a first ``section`` of ``None``.
+    """
+    section = None
+    content = []
+    for line in yield_lines(s):
+        if line.startswith("["):
+            if line.endswith("]"):
+                if section or content:
+                    yield section, content
+                section = line[1:-1].strip()
+                content = []
+            else:
+                raise ValueError("Invalid section heading", line)
+        else:
+            content.append(line)
+
+    # wrap up last segment
+    yield section, content
+
+
+def _mkstemp(*args, **kw):
+    old_open = os.open
+    try:
+        # temporarily bypass sandboxing
+        os.open = os_open
+        return tempfile.mkstemp(*args, **kw)
+    finally:
+        # and then put it back
+        os.open = old_open
+
+
+# Silence the PEP440Warning by default, so that end users don't get hit by it
+# randomly just because they use pkg_resources. We want to append the rule
+# because we want earlier uses of filterwarnings to take precedence over this
+# one.
+warnings.filterwarnings("ignore", category=PEP440Warning, append=True)
+
+
+# from jaraco.functools 1.3
+def _call_aside(f, *args, **kwargs):
+    f(*args, **kwargs)
+    return f
+
+
+@_call_aside
+def _initialize(g=globals()):
+    "Set up global resource manager (deliberately not state-saved)"
+    manager = ResourceManager()
+    g['_manager'] = manager
+    g.update(
+        (name, getattr(manager, name))
+        for name in dir(manager)
+        if not name.startswith('_')
+    )
+
+
+@_call_aside
+def _initialize_master_working_set():
+    """
+    Prepare the master working set and make the ``require()``
+    API available.
+
+    This function has explicit effects on the global state
+    of pkg_resources. It is intended to be invoked once at
+    the initialization of this module.
+
+    Invocation by other packages is unsupported and done
+    at their own risk.
+    """
+    working_set = WorkingSet._build_master()
+    _declare_state('object', working_set=working_set)
+
+    require = working_set.require
+    iter_entry_points = working_set.iter_entry_points
+    add_activation_listener = working_set.subscribe
+    run_script = working_set.run_script
+    # backward compatibility
+    run_main = run_script
+    # Activate all distributions already on sys.path with replace=False and
+    # ensure that all distributions added to the working set in the future
+    # (e.g. by calling ``require()``) will get activated as well,
+    # with higher priority (replace=True).
+    tuple(
+        dist.activate(replace=False)
+        for dist in working_set
+    )
+    add_activation_listener(
+        lambda dist: dist.activate(replace=True),
+        existing=False,
+    )
+    working_set.entries = []
+    # match order
+    list(map(working_set.add_entry, sys.path))
+    globals().update(locals())
+
+class PkgResourcesDeprecationWarning(Warning):
+    """
+    Base class for warning about deprecations in ``pkg_resources``
+
+    This class is not derived from ``DeprecationWarning``, and as such is
+    visible by default.
+    """
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pkg_resources/py31compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pkg_resources/py31compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..a2d3007ceb16b0eeb4b1f57361c089558a25daeb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pkg_resources/py31compat.py
@@ -0,0 +1,23 @@
+import os
+import errno
+import sys
+
+from pip._vendor import six
+
+
+def _makedirs_31(path, exist_ok=False):
+    try:
+        os.makedirs(path)
+    except OSError as exc:
+        if not exist_ok or exc.errno != errno.EEXIST:
+            raise
+
+
+# rely on compatibility behavior until mode considerations
+#  and exists_ok considerations are disentangled.
+# See https://github.com/pypa/setuptools/pull/1083#issuecomment-315168663
+needs_makedirs = (
+    six.PY2 or
+    (3, 4) <= sys.version_info < (3, 4, 1)
+)
+makedirs = _makedirs_31 if needs_makedirs else os.makedirs
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..82d907163c75876c73e1b2b932791e9e3880a7f0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/__init__.py
@@ -0,0 +1,342 @@
+"""
+Utilities for determining application-specific dirs. See  for details and
+usage.
+"""
+from __future__ import annotations
+
+import os
+import sys
+from pathlib import Path
+
+if sys.version_info >= (3, 8):  # pragma: no cover (py38+)
+    from typing import Literal
+else:  # pragma: no cover (py38+)
+    from pip._vendor.typing_extensions import Literal
+
+from .api import PlatformDirsABC
+from .version import __version__
+from .version import __version_tuple__ as __version_info__
+
+
+def _set_platform_dir_class() -> type[PlatformDirsABC]:
+    if sys.platform == "win32":
+        from pip._vendor.platformdirs.windows import Windows as Result
+    elif sys.platform == "darwin":
+        from pip._vendor.platformdirs.macos import MacOS as Result
+    else:
+        from pip._vendor.platformdirs.unix import Unix as Result
+
+    if os.getenv("ANDROID_DATA") == "/data" and os.getenv("ANDROID_ROOT") == "/system":
+
+        if os.getenv("SHELL") or os.getenv("PREFIX"):
+            return Result
+
+        from pip._vendor.platformdirs.android import _android_folder
+
+        if _android_folder() is not None:
+            from pip._vendor.platformdirs.android import Android
+
+            return Android  # return to avoid redefinition of result
+
+    return Result
+
+
+PlatformDirs = _set_platform_dir_class()  #: Currently active platform
+AppDirs = PlatformDirs  #: Backwards compatibility with appdirs
+
+
+def user_data_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    roaming: bool = False,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param roaming: See `roaming `.
+    :returns: data directory tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, roaming=roaming).user_data_dir
+
+
+def site_data_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    multipath: bool = False,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param multipath: See `roaming `.
+    :returns: data directory shared by users
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, multipath=multipath).site_data_dir
+
+
+def user_config_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    roaming: bool = False,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param roaming: See `roaming `.
+    :returns: config directory tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, roaming=roaming).user_config_dir
+
+
+def site_config_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    multipath: bool = False,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param multipath: See `roaming `.
+    :returns: config directory shared by the users
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, multipath=multipath).site_config_dir
+
+
+def user_cache_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    opinion: bool = True,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param opinion: See `roaming `.
+    :returns: cache directory tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, opinion=opinion).user_cache_dir
+
+
+def user_state_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    roaming: bool = False,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param roaming: See `roaming `.
+    :returns: state directory tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, roaming=roaming).user_state_dir
+
+
+def user_log_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    opinion: bool = True,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param opinion: See `roaming `.
+    :returns: log directory tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, opinion=opinion).user_log_dir
+
+
+def user_documents_dir() -> str:
+    """
+    :returns: documents directory tied to the user
+    """
+    return PlatformDirs().user_documents_dir
+
+
+def user_runtime_dir(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    opinion: bool = True,
+) -> str:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param opinion: See `opinion `.
+    :returns: runtime directory tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, opinion=opinion).user_runtime_dir
+
+
+def user_data_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    roaming: bool = False,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param roaming: See `roaming `.
+    :returns: data path tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, roaming=roaming).user_data_path
+
+
+def site_data_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    multipath: bool = False,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param multipath: See `multipath `.
+    :returns: data path shared by users
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, multipath=multipath).site_data_path
+
+
+def user_config_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    roaming: bool = False,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param roaming: See `roaming `.
+    :returns: config path tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, roaming=roaming).user_config_path
+
+
+def site_config_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    multipath: bool = False,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param multipath: See `roaming `.
+    :returns: config path shared by the users
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, multipath=multipath).site_config_path
+
+
+def user_cache_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    opinion: bool = True,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param opinion: See `roaming `.
+    :returns: cache path tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, opinion=opinion).user_cache_path
+
+
+def user_state_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    roaming: bool = False,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param roaming: See `roaming `.
+    :returns: state path tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, roaming=roaming).user_state_path
+
+
+def user_log_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    opinion: bool = True,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param opinion: See `roaming `.
+    :returns: log path tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, opinion=opinion).user_log_path
+
+
+def user_documents_path() -> Path:
+    """
+    :returns: documents path tied to the user
+    """
+    return PlatformDirs().user_documents_path
+
+
+def user_runtime_path(
+    appname: str | None = None,
+    appauthor: str | None | Literal[False] = None,
+    version: str | None = None,
+    opinion: bool = True,
+) -> Path:
+    """
+    :param appname: See `appname `.
+    :param appauthor: See `appauthor `.
+    :param version: See `version `.
+    :param opinion: See `opinion `.
+    :returns: runtime path tied to the user
+    """
+    return PlatformDirs(appname=appname, appauthor=appauthor, version=version, opinion=opinion).user_runtime_path
+
+
+__all__ = [
+    "__version__",
+    "__version_info__",
+    "PlatformDirs",
+    "AppDirs",
+    "PlatformDirsABC",
+    "user_data_dir",
+    "user_config_dir",
+    "user_cache_dir",
+    "user_state_dir",
+    "user_log_dir",
+    "user_documents_dir",
+    "user_runtime_dir",
+    "site_data_dir",
+    "site_config_dir",
+    "user_data_path",
+    "user_config_path",
+    "user_cache_path",
+    "user_state_path",
+    "user_log_path",
+    "user_documents_path",
+    "user_runtime_path",
+    "site_data_path",
+    "site_config_path",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/__main__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9c54bfb438d241ad17ce15d1e1346200ddf46b1c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/__main__.py
@@ -0,0 +1,46 @@
+from __future__ import annotations
+
+from pip._vendor.platformdirs import PlatformDirs, __version__
+
+PROPS = (
+    "user_data_dir",
+    "user_config_dir",
+    "user_cache_dir",
+    "user_state_dir",
+    "user_log_dir",
+    "user_documents_dir",
+    "user_runtime_dir",
+    "site_data_dir",
+    "site_config_dir",
+)
+
+
+def main() -> None:
+    app_name = "MyApp"
+    app_author = "MyCompany"
+
+    print(f"-- platformdirs {__version__} --")
+
+    print("-- app dirs (with optional 'version')")
+    dirs = PlatformDirs(app_name, app_author, version="1.0")
+    for prop in PROPS:
+        print(f"{prop}: {getattr(dirs, prop)}")
+
+    print("\n-- app dirs (without optional 'version')")
+    dirs = PlatformDirs(app_name, app_author)
+    for prop in PROPS:
+        print(f"{prop}: {getattr(dirs, prop)}")
+
+    print("\n-- app dirs (without optional 'appauthor')")
+    dirs = PlatformDirs(app_name)
+    for prop in PROPS:
+        print(f"{prop}: {getattr(dirs, prop)}")
+
+    print("\n-- app dirs (with disabled 'appauthor')")
+    dirs = PlatformDirs(app_name, appauthor=False)
+    for prop in PROPS:
+        print(f"{prop}: {getattr(dirs, prop)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/android.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/android.py
new file mode 100644
index 0000000000000000000000000000000000000000..eda80935123cb5db7e18d7fb82fe5f71991d7af8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/android.py
@@ -0,0 +1,120 @@
+from __future__ import annotations
+
+import os
+import re
+import sys
+from functools import lru_cache
+from typing import cast
+
+from .api import PlatformDirsABC
+
+
+class Android(PlatformDirsABC):
+    """
+    Follows the guidance `from here `_. Makes use of the
+    `appname ` and
+    `version `.
+    """
+
+    @property
+    def user_data_dir(self) -> str:
+        """:return: data directory tied to the user, e.g. ``/data/user///files/``"""
+        return self._append_app_name_and_version(cast(str, _android_folder()), "files")
+
+    @property
+    def site_data_dir(self) -> str:
+        """:return: data directory shared by users, same as `user_data_dir`"""
+        return self.user_data_dir
+
+    @property
+    def user_config_dir(self) -> str:
+        """
+        :return: config directory tied to the user, e.g. ``/data/user///shared_prefs/``
+        """
+        return self._append_app_name_and_version(cast(str, _android_folder()), "shared_prefs")
+
+    @property
+    def site_config_dir(self) -> str:
+        """:return: config directory shared by the users, same as `user_config_dir`"""
+        return self.user_config_dir
+
+    @property
+    def user_cache_dir(self) -> str:
+        """:return: cache directory tied to the user, e.g. e.g. ``/data/user///cache/``"""
+        return self._append_app_name_and_version(cast(str, _android_folder()), "cache")
+
+    @property
+    def user_state_dir(self) -> str:
+        """:return: state directory tied to the user, same as `user_data_dir`"""
+        return self.user_data_dir
+
+    @property
+    def user_log_dir(self) -> str:
+        """
+        :return: log directory tied to the user, same as `user_cache_dir` if not opinionated else ``log`` in it,
+          e.g. ``/data/user///cache//log``
+        """
+        path = self.user_cache_dir
+        if self.opinion:
+            path = os.path.join(path, "log")
+        return path
+
+    @property
+    def user_documents_dir(self) -> str:
+        """
+        :return: documents directory tied to the user e.g. ``/storage/emulated/0/Documents``
+        """
+        return _android_documents_folder()
+
+    @property
+    def user_runtime_dir(self) -> str:
+        """
+        :return: runtime directory tied to the user, same as `user_cache_dir` if not opinionated else ``tmp`` in it,
+          e.g. ``/data/user///cache//tmp``
+        """
+        path = self.user_cache_dir
+        if self.opinion:
+            path = os.path.join(path, "tmp")
+        return path
+
+
+@lru_cache(maxsize=1)
+def _android_folder() -> str | None:
+    """:return: base folder for the Android OS or None if cannot be found"""
+    try:
+        # First try to get path to android app via pyjnius
+        from jnius import autoclass
+
+        Context = autoclass("android.content.Context")  # noqa: N806
+        result: str | None = Context.getFilesDir().getParentFile().getAbsolutePath()
+    except Exception:
+        # if fails find an android folder looking path on the sys.path
+        pattern = re.compile(r"/data/(data|user/\d+)/(.+)/files")
+        for path in sys.path:
+            if pattern.match(path):
+                result = path.split("/files")[0]
+                break
+        else:
+            result = None
+    return result
+
+
+@lru_cache(maxsize=1)
+def _android_documents_folder() -> str:
+    """:return: documents folder for the Android OS"""
+    # Get directories with pyjnius
+    try:
+        from jnius import autoclass
+
+        Context = autoclass("android.content.Context")  # noqa: N806
+        Environment = autoclass("android.os.Environment")  # noqa: N806
+        documents_dir: str = Context.getExternalFilesDir(Environment.DIRECTORY_DOCUMENTS).getAbsolutePath()
+    except Exception:
+        documents_dir = "/storage/emulated/0/Documents"
+
+    return documents_dir
+
+
+__all__ = [
+    "Android",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/api.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/api.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f6e2c2c69d25dba4d1038a2d548fbf68017f91b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/api.py
@@ -0,0 +1,156 @@
+from __future__ import annotations
+
+import os
+import sys
+from abc import ABC, abstractmethod
+from pathlib import Path
+
+if sys.version_info >= (3, 8):  # pragma: no branch
+    from typing import Literal  # pragma: no cover
+
+
+class PlatformDirsABC(ABC):
+    """
+    Abstract base class for platform directories.
+    """
+
+    def __init__(
+        self,
+        appname: str | None = None,
+        appauthor: str | None | Literal[False] = None,
+        version: str | None = None,
+        roaming: bool = False,
+        multipath: bool = False,
+        opinion: bool = True,
+    ):
+        """
+        Create a new platform directory.
+
+        :param appname: See `appname`.
+        :param appauthor: See `appauthor`.
+        :param version: See `version`.
+        :param roaming: See `roaming`.
+        :param multipath: See `multipath`.
+        :param opinion: See `opinion`.
+        """
+        self.appname = appname  #: The name of application.
+        self.appauthor = appauthor
+        """
+        The name of the app author or distributing body for this application. Typically, it is the owning company name.
+        Defaults to `appname`. You may pass ``False`` to disable it.
+        """
+        self.version = version
+        """
+        An optional version path element to append to the path. You might want to use this if you want multiple versions
+        of your app to be able to run independently. If used, this would typically be ``.``.
+        """
+        self.roaming = roaming
+        """
+        Whether to use the roaming appdata directory on Windows. That means that for users on a Windows network setup
+        for roaming profiles, this user data will be synced on login (see
+        `here `_).
+        """
+        self.multipath = multipath
+        """
+        An optional parameter only applicable to Unix/Linux which indicates that the entire list of data dirs should be
+        returned. By default, the first item would only be returned.
+        """
+        self.opinion = opinion  #: A flag to indicating to use opinionated values.
+
+    def _append_app_name_and_version(self, *base: str) -> str:
+        params = list(base[1:])
+        if self.appname:
+            params.append(self.appname)
+            if self.version:
+                params.append(self.version)
+        return os.path.join(base[0], *params)
+
+    @property
+    @abstractmethod
+    def user_data_dir(self) -> str:
+        """:return: data directory tied to the user"""
+
+    @property
+    @abstractmethod
+    def site_data_dir(self) -> str:
+        """:return: data directory shared by users"""
+
+    @property
+    @abstractmethod
+    def user_config_dir(self) -> str:
+        """:return: config directory tied to the user"""
+
+    @property
+    @abstractmethod
+    def site_config_dir(self) -> str:
+        """:return: config directory shared by the users"""
+
+    @property
+    @abstractmethod
+    def user_cache_dir(self) -> str:
+        """:return: cache directory tied to the user"""
+
+    @property
+    @abstractmethod
+    def user_state_dir(self) -> str:
+        """:return: state directory tied to the user"""
+
+    @property
+    @abstractmethod
+    def user_log_dir(self) -> str:
+        """:return: log directory tied to the user"""
+
+    @property
+    @abstractmethod
+    def user_documents_dir(self) -> str:
+        """:return: documents directory tied to the user"""
+
+    @property
+    @abstractmethod
+    def user_runtime_dir(self) -> str:
+        """:return: runtime directory tied to the user"""
+
+    @property
+    def user_data_path(self) -> Path:
+        """:return: data path tied to the user"""
+        return Path(self.user_data_dir)
+
+    @property
+    def site_data_path(self) -> Path:
+        """:return: data path shared by users"""
+        return Path(self.site_data_dir)
+
+    @property
+    def user_config_path(self) -> Path:
+        """:return: config path tied to the user"""
+        return Path(self.user_config_dir)
+
+    @property
+    def site_config_path(self) -> Path:
+        """:return: config path shared by the users"""
+        return Path(self.site_config_dir)
+
+    @property
+    def user_cache_path(self) -> Path:
+        """:return: cache path tied to the user"""
+        return Path(self.user_cache_dir)
+
+    @property
+    def user_state_path(self) -> Path:
+        """:return: state path tied to the user"""
+        return Path(self.user_state_dir)
+
+    @property
+    def user_log_path(self) -> Path:
+        """:return: log path tied to the user"""
+        return Path(self.user_log_dir)
+
+    @property
+    def user_documents_path(self) -> Path:
+        """:return: documents path tied to the user"""
+        return Path(self.user_documents_dir)
+
+    @property
+    def user_runtime_path(self) -> Path:
+        """:return: runtime path tied to the user"""
+        return Path(self.user_runtime_dir)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/macos.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/macos.py
new file mode 100644
index 0000000000000000000000000000000000000000..a01337c7764e1e1aba1f3ba378a1c9241f31806d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/macos.py
@@ -0,0 +1,64 @@
+from __future__ import annotations
+
+import os
+
+from .api import PlatformDirsABC
+
+
+class MacOS(PlatformDirsABC):
+    """
+    Platform directories for the macOS operating system. Follows the guidance from `Apple documentation
+    `_.
+    Makes use of the `appname ` and
+    `version `.
+    """
+
+    @property
+    def user_data_dir(self) -> str:
+        """:return: data directory tied to the user, e.g. ``~/Library/Application Support/$appname/$version``"""
+        return self._append_app_name_and_version(os.path.expanduser("~/Library/Application Support/"))
+
+    @property
+    def site_data_dir(self) -> str:
+        """:return: data directory shared by users, e.g. ``/Library/Application Support/$appname/$version``"""
+        return self._append_app_name_and_version("/Library/Application Support")
+
+    @property
+    def user_config_dir(self) -> str:
+        """:return: config directory tied to the user, e.g. ``~/Library/Preferences/$appname/$version``"""
+        return self._append_app_name_and_version(os.path.expanduser("~/Library/Preferences/"))
+
+    @property
+    def site_config_dir(self) -> str:
+        """:return: config directory shared by the users, e.g. ``/Library/Preferences/$appname``"""
+        return self._append_app_name_and_version("/Library/Preferences")
+
+    @property
+    def user_cache_dir(self) -> str:
+        """:return: cache directory tied to the user, e.g. ``~/Library/Caches/$appname/$version``"""
+        return self._append_app_name_and_version(os.path.expanduser("~/Library/Caches"))
+
+    @property
+    def user_state_dir(self) -> str:
+        """:return: state directory tied to the user, same as `user_data_dir`"""
+        return self.user_data_dir
+
+    @property
+    def user_log_dir(self) -> str:
+        """:return: log directory tied to the user, e.g. ``~/Library/Logs/$appname/$version``"""
+        return self._append_app_name_and_version(os.path.expanduser("~/Library/Logs"))
+
+    @property
+    def user_documents_dir(self) -> str:
+        """:return: documents directory tied to the user, e.g. ``~/Documents``"""
+        return os.path.expanduser("~/Documents")
+
+    @property
+    def user_runtime_dir(self) -> str:
+        """:return: runtime directory tied to the user, e.g. ``~/Library/Caches/TemporaryItems/$appname/$version``"""
+        return self._append_app_name_and_version(os.path.expanduser("~/Library/Caches/TemporaryItems"))
+
+
+__all__ = [
+    "MacOS",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/unix.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/unix.py
new file mode 100644
index 0000000000000000000000000000000000000000..9aca5a030545d3ba26fa96fbfd7cae1c31dcdd15
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/unix.py
@@ -0,0 +1,181 @@
+from __future__ import annotations
+
+import os
+import sys
+from configparser import ConfigParser
+from pathlib import Path
+
+from .api import PlatformDirsABC
+
+if sys.platform.startswith("linux"):  # pragma: no branch # no op check, only to please the type checker
+    from os import getuid
+else:
+
+    def getuid() -> int:
+        raise RuntimeError("should only be used on Linux")
+
+
+class Unix(PlatformDirsABC):
+    """
+    On Unix/Linux, we follow the
+    `XDG Basedir Spec `_. The spec allows
+    overriding directories with environment variables. The examples show are the default values, alongside the name of
+    the environment variable that overrides them. Makes use of the
+    `appname `,
+    `version `,
+    `multipath `,
+    `opinion `.
+    """
+
+    @property
+    def user_data_dir(self) -> str:
+        """
+        :return: data directory tied to the user, e.g. ``~/.local/share/$appname/$version`` or
+         ``$XDG_DATA_HOME/$appname/$version``
+        """
+        path = os.environ.get("XDG_DATA_HOME", "")
+        if not path.strip():
+            path = os.path.expanduser("~/.local/share")
+        return self._append_app_name_and_version(path)
+
+    @property
+    def site_data_dir(self) -> str:
+        """
+        :return: data directories shared by users (if `multipath ` is
+         enabled and ``XDG_DATA_DIR`` is set and a multi path the response is also a multi path separated by the OS
+         path separator), e.g. ``/usr/local/share/$appname/$version`` or ``/usr/share/$appname/$version``
+        """
+        # XDG default for $XDG_DATA_DIRS; only first, if multipath is False
+        path = os.environ.get("XDG_DATA_DIRS", "")
+        if not path.strip():
+            path = f"/usr/local/share{os.pathsep}/usr/share"
+        return self._with_multi_path(path)
+
+    def _with_multi_path(self, path: str) -> str:
+        path_list = path.split(os.pathsep)
+        if not self.multipath:
+            path_list = path_list[0:1]
+        path_list = [self._append_app_name_and_version(os.path.expanduser(p)) for p in path_list]
+        return os.pathsep.join(path_list)
+
+    @property
+    def user_config_dir(self) -> str:
+        """
+        :return: config directory tied to the user, e.g. ``~/.config/$appname/$version`` or
+         ``$XDG_CONFIG_HOME/$appname/$version``
+        """
+        path = os.environ.get("XDG_CONFIG_HOME", "")
+        if not path.strip():
+            path = os.path.expanduser("~/.config")
+        return self._append_app_name_and_version(path)
+
+    @property
+    def site_config_dir(self) -> str:
+        """
+        :return: config directories shared by users (if `multipath `
+         is enabled and ``XDG_DATA_DIR`` is set and a multi path the response is also a multi path separated by the OS
+         path separator), e.g. ``/etc/xdg/$appname/$version``
+        """
+        # XDG default for $XDG_CONFIG_DIRS only first, if multipath is False
+        path = os.environ.get("XDG_CONFIG_DIRS", "")
+        if not path.strip():
+            path = "/etc/xdg"
+        return self._with_multi_path(path)
+
+    @property
+    def user_cache_dir(self) -> str:
+        """
+        :return: cache directory tied to the user, e.g. ``~/.cache/$appname/$version`` or
+         ``~/$XDG_CACHE_HOME/$appname/$version``
+        """
+        path = os.environ.get("XDG_CACHE_HOME", "")
+        if not path.strip():
+            path = os.path.expanduser("~/.cache")
+        return self._append_app_name_and_version(path)
+
+    @property
+    def user_state_dir(self) -> str:
+        """
+        :return: state directory tied to the user, e.g. ``~/.local/state/$appname/$version`` or
+         ``$XDG_STATE_HOME/$appname/$version``
+        """
+        path = os.environ.get("XDG_STATE_HOME", "")
+        if not path.strip():
+            path = os.path.expanduser("~/.local/state")
+        return self._append_app_name_and_version(path)
+
+    @property
+    def user_log_dir(self) -> str:
+        """
+        :return: log directory tied to the user, same as `user_state_dir` if not opinionated else ``log`` in it
+        """
+        path = self.user_state_dir
+        if self.opinion:
+            path = os.path.join(path, "log")
+        return path
+
+    @property
+    def user_documents_dir(self) -> str:
+        """
+        :return: documents directory tied to the user, e.g. ``~/Documents``
+        """
+        documents_dir = _get_user_dirs_folder("XDG_DOCUMENTS_DIR")
+        if documents_dir is None:
+            documents_dir = os.environ.get("XDG_DOCUMENTS_DIR", "").strip()
+            if not documents_dir:
+                documents_dir = os.path.expanduser("~/Documents")
+
+        return documents_dir
+
+    @property
+    def user_runtime_dir(self) -> str:
+        """
+        :return: runtime directory tied to the user, e.g. ``/run/user/$(id -u)/$appname/$version`` or
+         ``$XDG_RUNTIME_DIR/$appname/$version``
+        """
+        path = os.environ.get("XDG_RUNTIME_DIR", "")
+        if not path.strip():
+            path = f"/run/user/{getuid()}"
+        return self._append_app_name_and_version(path)
+
+    @property
+    def site_data_path(self) -> Path:
+        """:return: data path shared by users. Only return first item, even if ``multipath`` is set to ``True``"""
+        return self._first_item_as_path_if_multipath(self.site_data_dir)
+
+    @property
+    def site_config_path(self) -> Path:
+        """:return: config path shared by the users. Only return first item, even if ``multipath`` is set to ``True``"""
+        return self._first_item_as_path_if_multipath(self.site_config_dir)
+
+    def _first_item_as_path_if_multipath(self, directory: str) -> Path:
+        if self.multipath:
+            # If multipath is True, the first path is returned.
+            directory = directory.split(os.pathsep)[0]
+        return Path(directory)
+
+
+def _get_user_dirs_folder(key: str) -> str | None:
+    """Return directory from user-dirs.dirs config file. See https://freedesktop.org/wiki/Software/xdg-user-dirs/"""
+    user_dirs_config_path = os.path.join(Unix().user_config_dir, "user-dirs.dirs")
+    if os.path.exists(user_dirs_config_path):
+        parser = ConfigParser()
+
+        with open(user_dirs_config_path) as stream:
+            # Add fake section header, so ConfigParser doesn't complain
+            parser.read_string(f"[top]\n{stream.read()}")
+
+        if key not in parser["top"]:
+            return None
+
+        path = parser["top"][key].strip('"')
+        # Handle relative home paths
+        path = path.replace("$HOME", os.path.expanduser("~"))
+        return path
+
+    return None
+
+
+__all__ = [
+    "Unix",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/version.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f6eb98e8f0ef41d6fab05af6e9c24c5ef8a04b8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/version.py
@@ -0,0 +1,4 @@
+# file generated by setuptools_scm
+# don't change, don't track in version control
+__version__ = version = '2.6.2'
+__version_tuple__ = version_tuple = (2, 6, 2)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/windows.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/windows.py
new file mode 100644
index 0000000000000000000000000000000000000000..d5c27b341403fa03283562373b2a0b05daba075e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/platformdirs/windows.py
@@ -0,0 +1,184 @@
+from __future__ import annotations
+
+import ctypes
+import os
+import sys
+from functools import lru_cache
+from typing import Callable
+
+from .api import PlatformDirsABC
+
+
+class Windows(PlatformDirsABC):
+    """`MSDN on where to store app data files
+    `_.
+    Makes use of the
+    `appname `,
+    `appauthor `,
+    `version `,
+    `roaming `,
+    `opinion `."""
+
+    @property
+    def user_data_dir(self) -> str:
+        """
+        :return: data directory tied to the user, e.g.
+         ``%USERPROFILE%\\AppData\\Local\\$appauthor\\$appname`` (not roaming) or
+         ``%USERPROFILE%\\AppData\\Roaming\\$appauthor\\$appname`` (roaming)
+        """
+        const = "CSIDL_APPDATA" if self.roaming else "CSIDL_LOCAL_APPDATA"
+        path = os.path.normpath(get_win_folder(const))
+        return self._append_parts(path)
+
+    def _append_parts(self, path: str, *, opinion_value: str | None = None) -> str:
+        params = []
+        if self.appname:
+            if self.appauthor is not False:
+                author = self.appauthor or self.appname
+                params.append(author)
+            params.append(self.appname)
+            if opinion_value is not None and self.opinion:
+                params.append(opinion_value)
+            if self.version:
+                params.append(self.version)
+        return os.path.join(path, *params)
+
+    @property
+    def site_data_dir(self) -> str:
+        """:return: data directory shared by users, e.g. ``C:\\ProgramData\\$appauthor\\$appname``"""
+        path = os.path.normpath(get_win_folder("CSIDL_COMMON_APPDATA"))
+        return self._append_parts(path)
+
+    @property
+    def user_config_dir(self) -> str:
+        """:return: config directory tied to the user, same as `user_data_dir`"""
+        return self.user_data_dir
+
+    @property
+    def site_config_dir(self) -> str:
+        """:return: config directory shared by the users, same as `site_data_dir`"""
+        return self.site_data_dir
+
+    @property
+    def user_cache_dir(self) -> str:
+        """
+        :return: cache directory tied to the user (if opinionated with ``Cache`` folder within ``$appname``) e.g.
+         ``%USERPROFILE%\\AppData\\Local\\$appauthor\\$appname\\Cache\\$version``
+        """
+        path = os.path.normpath(get_win_folder("CSIDL_LOCAL_APPDATA"))
+        return self._append_parts(path, opinion_value="Cache")
+
+    @property
+    def user_state_dir(self) -> str:
+        """:return: state directory tied to the user, same as `user_data_dir`"""
+        return self.user_data_dir
+
+    @property
+    def user_log_dir(self) -> str:
+        """
+        :return: log directory tied to the user, same as `user_data_dir` if not opinionated else ``Logs`` in it
+        """
+        path = self.user_data_dir
+        if self.opinion:
+            path = os.path.join(path, "Logs")
+        return path
+
+    @property
+    def user_documents_dir(self) -> str:
+        """
+        :return: documents directory tied to the user e.g. ``%USERPROFILE%\\Documents``
+        """
+        return os.path.normpath(get_win_folder("CSIDL_PERSONAL"))
+
+    @property
+    def user_runtime_dir(self) -> str:
+        """
+        :return: runtime directory tied to the user, e.g.
+         ``%USERPROFILE%\\AppData\\Local\\Temp\\$appauthor\\$appname``
+        """
+        path = os.path.normpath(os.path.join(get_win_folder("CSIDL_LOCAL_APPDATA"), "Temp"))
+        return self._append_parts(path)
+
+
+def get_win_folder_from_env_vars(csidl_name: str) -> str:
+    """Get folder from environment variables."""
+    if csidl_name == "CSIDL_PERSONAL":  # does not have an environment name
+        return os.path.join(os.path.normpath(os.environ["USERPROFILE"]), "Documents")
+
+    env_var_name = {
+        "CSIDL_APPDATA": "APPDATA",
+        "CSIDL_COMMON_APPDATA": "ALLUSERSPROFILE",
+        "CSIDL_LOCAL_APPDATA": "LOCALAPPDATA",
+    }.get(csidl_name)
+    if env_var_name is None:
+        raise ValueError(f"Unknown CSIDL name: {csidl_name}")
+    result = os.environ.get(env_var_name)
+    if result is None:
+        raise ValueError(f"Unset environment variable: {env_var_name}")
+    return result
+
+
+def get_win_folder_from_registry(csidl_name: str) -> str:
+    """Get folder from the registry.
+
+    This is a fallback technique at best. I'm not sure if using the
+    registry for this guarantees us the correct answer for all CSIDL_*
+    names.
+    """
+    shell_folder_name = {
+        "CSIDL_APPDATA": "AppData",
+        "CSIDL_COMMON_APPDATA": "Common AppData",
+        "CSIDL_LOCAL_APPDATA": "Local AppData",
+        "CSIDL_PERSONAL": "Personal",
+    }.get(csidl_name)
+    if shell_folder_name is None:
+        raise ValueError(f"Unknown CSIDL name: {csidl_name}")
+    if sys.platform != "win32":  # only needed for mypy type checker to know that this code runs only on Windows
+        raise NotImplementedError
+    import winreg
+
+    key = winreg.OpenKey(winreg.HKEY_CURRENT_USER, r"Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders")
+    directory, _ = winreg.QueryValueEx(key, shell_folder_name)
+    return str(directory)
+
+
+def get_win_folder_via_ctypes(csidl_name: str) -> str:
+    """Get folder with ctypes."""
+    csidl_const = {
+        "CSIDL_APPDATA": 26,
+        "CSIDL_COMMON_APPDATA": 35,
+        "CSIDL_LOCAL_APPDATA": 28,
+        "CSIDL_PERSONAL": 5,
+    }.get(csidl_name)
+    if csidl_const is None:
+        raise ValueError(f"Unknown CSIDL name: {csidl_name}")
+
+    buf = ctypes.create_unicode_buffer(1024)
+    windll = getattr(ctypes, "windll")  # noqa: B009 # using getattr to avoid false positive with mypy type checker
+    windll.shell32.SHGetFolderPathW(None, csidl_const, None, 0, buf)
+
+    # Downgrade to short path name if it has highbit chars.
+    if any(ord(c) > 255 for c in buf):
+        buf2 = ctypes.create_unicode_buffer(1024)
+        if windll.kernel32.GetShortPathNameW(buf.value, buf2, 1024):
+            buf = buf2
+
+    return buf.value
+
+
+def _pick_get_win_folder() -> Callable[[str], str]:
+    if hasattr(ctypes, "windll"):
+        return get_win_folder_via_ctypes
+    try:
+        import winreg  # noqa: F401
+    except ImportError:
+        return get_win_folder_from_env_vars
+    else:
+        return get_win_folder_from_registry
+
+
+get_win_folder = lru_cache(maxsize=None)(_pick_get_win_folder())
+
+__all__ = [
+    "Windows",
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..7185e5376944e2e7f4947d160ad56fc92fc90aa6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/__init__.py
@@ -0,0 +1,82 @@
+"""
+    Pygments
+    ~~~~~~~~
+
+    Pygments is a syntax highlighting package written in Python.
+
+    It is a generic syntax highlighter for general use in all kinds of software
+    such as forum systems, wikis or other applications that need to prettify
+    source code. Highlights are:
+
+    * a wide range of common languages and markup formats is supported
+    * special attention is paid to details, increasing quality by a fair amount
+    * support for new languages and formats are added easily
+    * a number of output formats, presently HTML, LaTeX, RTF, SVG, all image
+      formats that PIL supports, and ANSI sequences
+    * it is usable as a command-line tool and as a library
+    * ... and it highlights even Brainfuck!
+
+    The `Pygments master branch`_ is installable with ``easy_install Pygments==dev``.
+
+    .. _Pygments master branch:
+       https://github.com/pygments/pygments/archive/master.zip#egg=Pygments-dev
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+from io import StringIO, BytesIO
+
+__version__ = '2.13.0'
+__docformat__ = 'restructuredtext'
+
+__all__ = ['lex', 'format', 'highlight']
+
+
+def lex(code, lexer):
+    """
+    Lex ``code`` with ``lexer`` and return an iterable of tokens.
+    """
+    try:
+        return lexer.get_tokens(code)
+    except TypeError:
+        # Heuristic to catch a common mistake.
+        from pip._vendor.pygments.lexer import RegexLexer
+        if isinstance(lexer, type) and issubclass(lexer, RegexLexer):
+            raise TypeError('lex() argument must be a lexer instance, '
+                            'not a class')
+        raise
+
+
+def format(tokens, formatter, outfile=None):  # pylint: disable=redefined-builtin
+    """
+    Format a tokenlist ``tokens`` with the formatter ``formatter``.
+
+    If ``outfile`` is given and a valid file object (an object
+    with a ``write`` method), the result will be written to it, otherwise
+    it is returned as a string.
+    """
+    try:
+        if not outfile:
+            realoutfile = getattr(formatter, 'encoding', None) and BytesIO() or StringIO()
+            formatter.format(tokens, realoutfile)
+            return realoutfile.getvalue()
+        else:
+            formatter.format(tokens, outfile)
+    except TypeError:
+        # Heuristic to catch a common mistake.
+        from pip._vendor.pygments.formatter import Formatter
+        if isinstance(formatter, type) and issubclass(formatter, Formatter):
+            raise TypeError('format() argument must be a formatter instance, '
+                            'not a class')
+        raise
+
+
+def highlight(code, lexer, formatter, outfile=None):
+    """
+    Lex ``code`` with ``lexer`` and format it with the formatter ``formatter``.
+
+    If ``outfile`` is given and a valid file object (an object
+    with a ``write`` method), the result will be written to it, otherwise
+    it is returned as a string.
+    """
+    return format(lex(code, lexer), formatter, outfile)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/__main__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..90cafd93426f6fb2e8ad57b140b7ae163a67a4a4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/__main__.py
@@ -0,0 +1,17 @@
+"""
+    pygments.__main__
+    ~~~~~~~~~~~~~~~~~
+
+    Main entry point for ``python -m pygments``.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+import sys
+from pip._vendor.pygments.cmdline import main
+
+try:
+    sys.exit(main(sys.argv))
+except KeyboardInterrupt:
+    sys.exit(1)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/cmdline.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/cmdline.py
new file mode 100644
index 0000000000000000000000000000000000000000..de73b06b4cfa3b68a25455148c7e086b32676e95
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/cmdline.py
@@ -0,0 +1,668 @@
+"""
+    pygments.cmdline
+    ~~~~~~~~~~~~~~~~
+
+    Command line interface.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+import os
+import sys
+import shutil
+import argparse
+from textwrap import dedent
+
+from pip._vendor.pygments import __version__, highlight
+from pip._vendor.pygments.util import ClassNotFound, OptionError, docstring_headline, \
+    guess_decode, guess_decode_from_terminal, terminal_encoding, \
+    UnclosingTextIOWrapper
+from pip._vendor.pygments.lexers import get_all_lexers, get_lexer_by_name, guess_lexer, \
+    load_lexer_from_file, get_lexer_for_filename, find_lexer_class_for_filename
+from pip._vendor.pygments.lexers.special import TextLexer
+from pip._vendor.pygments.formatters.latex import LatexEmbeddedLexer, LatexFormatter
+from pip._vendor.pygments.formatters import get_all_formatters, get_formatter_by_name, \
+    load_formatter_from_file, get_formatter_for_filename, find_formatter_class
+from pip._vendor.pygments.formatters.terminal import TerminalFormatter
+from pip._vendor.pygments.formatters.terminal256 import Terminal256Formatter, TerminalTrueColorFormatter
+from pip._vendor.pygments.filters import get_all_filters, find_filter_class
+from pip._vendor.pygments.styles import get_all_styles, get_style_by_name
+
+
+def _parse_options(o_strs):
+    opts = {}
+    if not o_strs:
+        return opts
+    for o_str in o_strs:
+        if not o_str.strip():
+            continue
+        o_args = o_str.split(',')
+        for o_arg in o_args:
+            o_arg = o_arg.strip()
+            try:
+                o_key, o_val = o_arg.split('=', 1)
+                o_key = o_key.strip()
+                o_val = o_val.strip()
+            except ValueError:
+                opts[o_arg] = True
+            else:
+                opts[o_key] = o_val
+    return opts
+
+
+def _parse_filters(f_strs):
+    filters = []
+    if not f_strs:
+        return filters
+    for f_str in f_strs:
+        if ':' in f_str:
+            fname, fopts = f_str.split(':', 1)
+            filters.append((fname, _parse_options([fopts])))
+        else:
+            filters.append((f_str, {}))
+    return filters
+
+
+def _print_help(what, name):
+    try:
+        if what == 'lexer':
+            cls = get_lexer_by_name(name)
+            print("Help on the %s lexer:" % cls.name)
+            print(dedent(cls.__doc__))
+        elif what == 'formatter':
+            cls = find_formatter_class(name)
+            print("Help on the %s formatter:" % cls.name)
+            print(dedent(cls.__doc__))
+        elif what == 'filter':
+            cls = find_filter_class(name)
+            print("Help on the %s filter:" % name)
+            print(dedent(cls.__doc__))
+        return 0
+    except (AttributeError, ValueError):
+        print("%s not found!" % what, file=sys.stderr)
+        return 1
+
+
+def _print_list(what):
+    if what == 'lexer':
+        print()
+        print("Lexers:")
+        print("~~~~~~~")
+
+        info = []
+        for fullname, names, exts, _ in get_all_lexers():
+            tup = (', '.join(names)+':', fullname,
+                   exts and '(filenames ' + ', '.join(exts) + ')' or '')
+            info.append(tup)
+        info.sort()
+        for i in info:
+            print(('* %s\n    %s %s') % i)
+
+    elif what == 'formatter':
+        print()
+        print("Formatters:")
+        print("~~~~~~~~~~~")
+
+        info = []
+        for cls in get_all_formatters():
+            doc = docstring_headline(cls)
+            tup = (', '.join(cls.aliases) + ':', doc, cls.filenames and
+                   '(filenames ' + ', '.join(cls.filenames) + ')' or '')
+            info.append(tup)
+        info.sort()
+        for i in info:
+            print(('* %s\n    %s %s') % i)
+
+    elif what == 'filter':
+        print()
+        print("Filters:")
+        print("~~~~~~~~")
+
+        for name in get_all_filters():
+            cls = find_filter_class(name)
+            print("* " + name + ':')
+            print("    %s" % docstring_headline(cls))
+
+    elif what == 'style':
+        print()
+        print("Styles:")
+        print("~~~~~~~")
+
+        for name in get_all_styles():
+            cls = get_style_by_name(name)
+            print("* " + name + ':')
+            print("    %s" % docstring_headline(cls))
+
+
+def _print_list_as_json(requested_items):
+    import json
+    result = {}
+    if 'lexer' in requested_items:
+        info = {}
+        for fullname, names, filenames, mimetypes in get_all_lexers():
+            info[fullname] = {
+                'aliases': names,
+                'filenames': filenames,
+                'mimetypes': mimetypes
+            }
+        result['lexers'] = info
+
+    if 'formatter' in requested_items:
+        info = {}
+        for cls in get_all_formatters():
+            doc = docstring_headline(cls)
+            info[cls.name] = {
+                'aliases': cls.aliases,
+                'filenames': cls.filenames,
+                'doc': doc
+            }
+        result['formatters'] = info
+
+    if 'filter' in requested_items:
+        info = {}
+        for name in get_all_filters():
+            cls = find_filter_class(name)
+            info[name] = {
+                'doc': docstring_headline(cls)
+            }
+        result['filters'] = info
+
+    if 'style' in requested_items:
+        info = {}
+        for name in get_all_styles():
+            cls = get_style_by_name(name)
+            info[name] = {
+                'doc': docstring_headline(cls)
+            }
+        result['styles'] = info
+
+    json.dump(result, sys.stdout)
+
+def main_inner(parser, argns):
+    if argns.help:
+        parser.print_help()
+        return 0
+
+    if argns.V:
+        print('Pygments version %s, (c) 2006-2022 by Georg Brandl, Matthäus '
+              'Chajdas and contributors.' % __version__)
+        return 0
+
+    def is_only_option(opt):
+        return not any(v for (k, v) in vars(argns).items() if k != opt)
+
+    # handle ``pygmentize -L``
+    if argns.L is not None:
+        arg_set = set()
+        for k, v in vars(argns).items():
+            if v:
+                arg_set.add(k)
+
+        arg_set.discard('L')
+        arg_set.discard('json')
+
+        if arg_set:
+            parser.print_help(sys.stderr)
+            return 2
+
+        # print version
+        if not argns.json:
+            main(['', '-V'])
+        allowed_types = {'lexer', 'formatter', 'filter', 'style'}
+        largs = [arg.rstrip('s') for arg in argns.L]
+        if any(arg not in allowed_types for arg in largs):
+            parser.print_help(sys.stderr)
+            return 0
+        if not largs:
+            largs = allowed_types
+        if not argns.json:
+            for arg in largs:
+                _print_list(arg)
+        else:
+            _print_list_as_json(largs)
+        return 0
+
+    # handle ``pygmentize -H``
+    if argns.H:
+        if not is_only_option('H'):
+            parser.print_help(sys.stderr)
+            return 2
+        what, name = argns.H
+        if what not in ('lexer', 'formatter', 'filter'):
+            parser.print_help(sys.stderr)
+            return 2
+        return _print_help(what, name)
+
+    # parse -O options
+    parsed_opts = _parse_options(argns.O or [])
+
+    # parse -P options
+    for p_opt in argns.P or []:
+        try:
+            name, value = p_opt.split('=', 1)
+        except ValueError:
+            parsed_opts[p_opt] = True
+        else:
+            parsed_opts[name] = value
+
+    # encodings
+    inencoding = parsed_opts.get('inencoding', parsed_opts.get('encoding'))
+    outencoding = parsed_opts.get('outencoding', parsed_opts.get('encoding'))
+
+    # handle ``pygmentize -N``
+    if argns.N:
+        lexer = find_lexer_class_for_filename(argns.N)
+        if lexer is None:
+            lexer = TextLexer
+
+        print(lexer.aliases[0])
+        return 0
+
+    # handle ``pygmentize -C``
+    if argns.C:
+        inp = sys.stdin.buffer.read()
+        try:
+            lexer = guess_lexer(inp, inencoding=inencoding)
+        except ClassNotFound:
+            lexer = TextLexer
+
+        print(lexer.aliases[0])
+        return 0
+
+    # handle ``pygmentize -S``
+    S_opt = argns.S
+    a_opt = argns.a
+    if S_opt is not None:
+        f_opt = argns.f
+        if not f_opt:
+            parser.print_help(sys.stderr)
+            return 2
+        if argns.l or argns.INPUTFILE:
+            parser.print_help(sys.stderr)
+            return 2
+
+        try:
+            parsed_opts['style'] = S_opt
+            fmter = get_formatter_by_name(f_opt, **parsed_opts)
+        except ClassNotFound as err:
+            print(err, file=sys.stderr)
+            return 1
+
+        print(fmter.get_style_defs(a_opt or ''))
+        return 0
+
+    # if no -S is given, -a is not allowed
+    if argns.a is not None:
+        parser.print_help(sys.stderr)
+        return 2
+
+    # parse -F options
+    F_opts = _parse_filters(argns.F or [])
+
+    # -x: allow custom (eXternal) lexers and formatters
+    allow_custom_lexer_formatter = bool(argns.x)
+
+    # select lexer
+    lexer = None
+
+    # given by name?
+    lexername = argns.l
+    if lexername:
+        # custom lexer, located relative to user's cwd
+        if allow_custom_lexer_formatter and '.py' in lexername:
+            try:
+                filename = None
+                name = None
+                if ':' in lexername:
+                    filename, name = lexername.rsplit(':', 1)
+
+                    if '.py' in name:
+                        # This can happen on Windows: If the lexername is
+                        # C:\lexer.py -- return to normal load path in that case
+                        name = None
+
+                if filename and name:
+                    lexer = load_lexer_from_file(filename, name,
+                                                 **parsed_opts)
+                else:
+                    lexer = load_lexer_from_file(lexername, **parsed_opts)
+            except ClassNotFound as err:
+                print('Error:', err, file=sys.stderr)
+                return 1
+        else:
+            try:
+                lexer = get_lexer_by_name(lexername, **parsed_opts)
+            except (OptionError, ClassNotFound) as err:
+                print('Error:', err, file=sys.stderr)
+                return 1
+
+    # read input code
+    code = None
+
+    if argns.INPUTFILE:
+        if argns.s:
+            print('Error: -s option not usable when input file specified',
+                  file=sys.stderr)
+            return 2
+
+        infn = argns.INPUTFILE
+        try:
+            with open(infn, 'rb') as infp:
+                code = infp.read()
+        except Exception as err:
+            print('Error: cannot read infile:', err, file=sys.stderr)
+            return 1
+        if not inencoding:
+            code, inencoding = guess_decode(code)
+
+        # do we have to guess the lexer?
+        if not lexer:
+            try:
+                lexer = get_lexer_for_filename(infn, code, **parsed_opts)
+            except ClassNotFound as err:
+                if argns.g:
+                    try:
+                        lexer = guess_lexer(code, **parsed_opts)
+                    except ClassNotFound:
+                        lexer = TextLexer(**parsed_opts)
+                else:
+                    print('Error:', err, file=sys.stderr)
+                    return 1
+            except OptionError as err:
+                print('Error:', err, file=sys.stderr)
+                return 1
+
+    elif not argns.s:  # treat stdin as full file (-s support is later)
+        # read code from terminal, always in binary mode since we want to
+        # decode ourselves and be tolerant with it
+        code = sys.stdin.buffer.read()  # use .buffer to get a binary stream
+        if not inencoding:
+            code, inencoding = guess_decode_from_terminal(code, sys.stdin)
+            # else the lexer will do the decoding
+        if not lexer:
+            try:
+                lexer = guess_lexer(code, **parsed_opts)
+            except ClassNotFound:
+                lexer = TextLexer(**parsed_opts)
+
+    else:  # -s option needs a lexer with -l
+        if not lexer:
+            print('Error: when using -s a lexer has to be selected with -l',
+                  file=sys.stderr)
+            return 2
+
+    # process filters
+    for fname, fopts in F_opts:
+        try:
+            lexer.add_filter(fname, **fopts)
+        except ClassNotFound as err:
+            print('Error:', err, file=sys.stderr)
+            return 1
+
+    # select formatter
+    outfn = argns.o
+    fmter = argns.f
+    if fmter:
+        # custom formatter, located relative to user's cwd
+        if allow_custom_lexer_formatter and '.py' in fmter:
+            try:
+                filename = None
+                name = None
+                if ':' in fmter:
+                    # Same logic as above for custom lexer
+                    filename, name = fmter.rsplit(':', 1)
+
+                    if '.py' in name:
+                        name = None
+
+                if filename and name:
+                    fmter = load_formatter_from_file(filename, name,
+                                                     **parsed_opts)
+                else:
+                    fmter = load_formatter_from_file(fmter, **parsed_opts)
+            except ClassNotFound as err:
+                print('Error:', err, file=sys.stderr)
+                return 1
+        else:
+            try:
+                fmter = get_formatter_by_name(fmter, **parsed_opts)
+            except (OptionError, ClassNotFound) as err:
+                print('Error:', err, file=sys.stderr)
+                return 1
+
+    if outfn:
+        if not fmter:
+            try:
+                fmter = get_formatter_for_filename(outfn, **parsed_opts)
+            except (OptionError, ClassNotFound) as err:
+                print('Error:', err, file=sys.stderr)
+                return 1
+        try:
+            outfile = open(outfn, 'wb')
+        except Exception as err:
+            print('Error: cannot open outfile:', err, file=sys.stderr)
+            return 1
+    else:
+        if not fmter:
+            if os.environ.get('COLORTERM','') in ('truecolor', '24bit'):
+                fmter = TerminalTrueColorFormatter(**parsed_opts)
+            elif '256' in os.environ.get('TERM', ''):
+                fmter = Terminal256Formatter(**parsed_opts)
+            else:
+                fmter = TerminalFormatter(**parsed_opts)
+        outfile = sys.stdout.buffer
+
+    # determine output encoding if not explicitly selected
+    if not outencoding:
+        if outfn:
+            # output file? use lexer encoding for now (can still be None)
+            fmter.encoding = inencoding
+        else:
+            # else use terminal encoding
+            fmter.encoding = terminal_encoding(sys.stdout)
+
+    # provide coloring under Windows, if possible
+    if not outfn and sys.platform in ('win32', 'cygwin') and \
+       fmter.name in ('Terminal', 'Terminal256'):  # pragma: no cover
+        # unfortunately colorama doesn't support binary streams on Py3
+        outfile = UnclosingTextIOWrapper(outfile, encoding=fmter.encoding)
+        fmter.encoding = None
+        try:
+            import pip._vendor.colorama.initialise as colorama_initialise
+        except ImportError:
+            pass
+        else:
+            outfile = colorama_initialise.wrap_stream(
+                outfile, convert=None, strip=None, autoreset=False, wrap=True)
+
+    # When using the LaTeX formatter and the option `escapeinside` is
+    # specified, we need a special lexer which collects escaped text
+    # before running the chosen language lexer.
+    escapeinside = parsed_opts.get('escapeinside', '')
+    if len(escapeinside) == 2 and isinstance(fmter, LatexFormatter):
+        left = escapeinside[0]
+        right = escapeinside[1]
+        lexer = LatexEmbeddedLexer(left, right, lexer)
+
+    # ... and do it!
+    if not argns.s:
+        # process whole input as per normal...
+        try:
+            highlight(code, lexer, fmter, outfile)
+        finally:
+            if outfn:
+                outfile.close()
+        return 0
+    else:
+        # line by line processing of stdin (eg: for 'tail -f')...
+        try:
+            while 1:
+                line = sys.stdin.buffer.readline()
+                if not line:
+                    break
+                if not inencoding:
+                    line = guess_decode_from_terminal(line, sys.stdin)[0]
+                highlight(line, lexer, fmter, outfile)
+                if hasattr(outfile, 'flush'):
+                    outfile.flush()
+            return 0
+        except KeyboardInterrupt:  # pragma: no cover
+            return 0
+        finally:
+            if outfn:
+                outfile.close()
+
+
+class HelpFormatter(argparse.HelpFormatter):
+    def __init__(self, prog, indent_increment=2, max_help_position=16, width=None):
+        if width is None:
+            try:
+                width = shutil.get_terminal_size().columns - 2
+            except Exception:
+                pass
+        argparse.HelpFormatter.__init__(self, prog, indent_increment,
+                                        max_help_position, width)
+
+
+def main(args=sys.argv):
+    """
+    Main command line entry point.
+    """
+    desc = "Highlight an input file and write the result to an output file."
+    parser = argparse.ArgumentParser(description=desc, add_help=False,
+                                     formatter_class=HelpFormatter)
+
+    operation = parser.add_argument_group('Main operation')
+    lexersel = operation.add_mutually_exclusive_group()
+    lexersel.add_argument(
+        '-l', metavar='LEXER',
+        help='Specify the lexer to use.  (Query names with -L.)  If not '
+        'given and -g is not present, the lexer is guessed from the filename.')
+    lexersel.add_argument(
+        '-g', action='store_true',
+        help='Guess the lexer from the file contents, or pass through '
+        'as plain text if nothing can be guessed.')
+    operation.add_argument(
+        '-F', metavar='FILTER[:options]', action='append',
+        help='Add a filter to the token stream.  (Query names with -L.) '
+        'Filter options are given after a colon if necessary.')
+    operation.add_argument(
+        '-f', metavar='FORMATTER',
+        help='Specify the formatter to use.  (Query names with -L.) '
+        'If not given, the formatter is guessed from the output filename, '
+        'and defaults to the terminal formatter if the output is to the '
+        'terminal or an unknown file extension.')
+    operation.add_argument(
+        '-O', metavar='OPTION=value[,OPTION=value,...]', action='append',
+        help='Give options to the lexer and formatter as a comma-separated '
+        'list of key-value pairs. '
+        'Example: `-O bg=light,python=cool`.')
+    operation.add_argument(
+        '-P', metavar='OPTION=value', action='append',
+        help='Give a single option to the lexer and formatter - with this '
+        'you can pass options whose value contains commas and equal signs. '
+        'Example: `-P "heading=Pygments, the Python highlighter"`.')
+    operation.add_argument(
+        '-o', metavar='OUTPUTFILE',
+        help='Where to write the output.  Defaults to standard output.')
+
+    operation.add_argument(
+        'INPUTFILE', nargs='?',
+        help='Where to read the input.  Defaults to standard input.')
+
+    flags = parser.add_argument_group('Operation flags')
+    flags.add_argument(
+        '-v', action='store_true',
+        help='Print a detailed traceback on unhandled exceptions, which '
+        'is useful for debugging and bug reports.')
+    flags.add_argument(
+        '-s', action='store_true',
+        help='Process lines one at a time until EOF, rather than waiting to '
+        'process the entire file.  This only works for stdin, only for lexers '
+        'with no line-spanning constructs, and is intended for streaming '
+        'input such as you get from `tail -f`. '
+        'Example usage: `tail -f sql.log | pygmentize -s -l sql`.')
+    flags.add_argument(
+        '-x', action='store_true',
+        help='Allow custom lexers and formatters to be loaded from a .py file '
+        'relative to the current working directory. For example, '
+        '`-l ./customlexer.py -x`. By default, this option expects a file '
+        'with a class named CustomLexer or CustomFormatter; you can also '
+        'specify your own class name with a colon (`-l ./lexer.py:MyLexer`). '
+        'Users should be very careful not to use this option with untrusted '
+        'files, because it will import and run them.')
+    flags.add_argument('--json', help='Output as JSON. This can '
+        'be only used in conjunction with -L.',
+        default=False,
+        action='store_true')
+
+    special_modes_group = parser.add_argument_group(
+        'Special modes - do not do any highlighting')
+    special_modes = special_modes_group.add_mutually_exclusive_group()
+    special_modes.add_argument(
+        '-S', metavar='STYLE -f formatter',
+        help='Print style definitions for STYLE for a formatter '
+        'given with -f. The argument given by -a is formatter '
+        'dependent.')
+    special_modes.add_argument(
+        '-L', nargs='*', metavar='WHAT',
+        help='List lexers, formatters, styles or filters -- '
+        'give additional arguments for the thing(s) you want to list '
+        '(e.g. "styles"), or omit them to list everything.')
+    special_modes.add_argument(
+        '-N', metavar='FILENAME',
+        help='Guess and print out a lexer name based solely on the given '
+        'filename. Does not take input or highlight anything. If no specific '
+        'lexer can be determined, "text" is printed.')
+    special_modes.add_argument(
+        '-C', action='store_true',
+        help='Like -N, but print out a lexer name based solely on '
+        'a given content from standard input.')
+    special_modes.add_argument(
+        '-H', action='store', nargs=2, metavar=('NAME', 'TYPE'),
+        help='Print detailed help for the object  of type , '
+        'where  is one of "lexer", "formatter" or "filter".')
+    special_modes.add_argument(
+        '-V', action='store_true',
+        help='Print the package version.')
+    special_modes.add_argument(
+        '-h', '--help', action='store_true',
+        help='Print this help.')
+    special_modes_group.add_argument(
+        '-a', metavar='ARG',
+        help='Formatter-specific additional argument for the -S (print '
+        'style sheet) mode.')
+
+    argns = parser.parse_args(args[1:])
+
+    try:
+        return main_inner(parser, argns)
+    except BrokenPipeError:
+        # someone closed our stdout, e.g. by quitting a pager.
+        return 0
+    except Exception:
+        if argns.v:
+            print(file=sys.stderr)
+            print('*' * 65, file=sys.stderr)
+            print('An unhandled exception occurred while highlighting.',
+                  file=sys.stderr)
+            print('Please report the whole traceback to the issue tracker at',
+                  file=sys.stderr)
+            print('.',
+                  file=sys.stderr)
+            print('*' * 65, file=sys.stderr)
+            print(file=sys.stderr)
+            raise
+        import traceback
+        info = traceback.format_exception(*sys.exc_info())
+        msg = info[-1].strip()
+        if len(info) >= 3:
+            # extract relevant file and position info
+            msg += '\n   (f%s)' % info[-2].split('\n')[0].strip()[1:]
+        print(file=sys.stderr)
+        print('*** Error while highlighting:', file=sys.stderr)
+        print(msg, file=sys.stderr)
+        print('*** If this is a bug you want to report, please rerun with -v.',
+              file=sys.stderr)
+        return 1
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/console.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/console.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ada68e03b3c018e3ddbbf3356a48a1d580aa251
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/console.py
@@ -0,0 +1,70 @@
+"""
+    pygments.console
+    ~~~~~~~~~~~~~~~~
+
+    Format colored console output.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+esc = "\x1b["
+
+codes = {}
+codes[""] = ""
+codes["reset"] = esc + "39;49;00m"
+
+codes["bold"] = esc + "01m"
+codes["faint"] = esc + "02m"
+codes["standout"] = esc + "03m"
+codes["underline"] = esc + "04m"
+codes["blink"] = esc + "05m"
+codes["overline"] = esc + "06m"
+
+dark_colors = ["black", "red", "green", "yellow", "blue",
+               "magenta", "cyan", "gray"]
+light_colors = ["brightblack", "brightred", "brightgreen", "brightyellow", "brightblue",
+                "brightmagenta", "brightcyan", "white"]
+
+x = 30
+for d, l in zip(dark_colors, light_colors):
+    codes[d] = esc + "%im" % x
+    codes[l] = esc + "%im" % (60 + x)
+    x += 1
+
+del d, l, x
+
+codes["white"] = codes["bold"]
+
+
+def reset_color():
+    return codes["reset"]
+
+
+def colorize(color_key, text):
+    return codes[color_key] + text + codes["reset"]
+
+
+def ansiformat(attr, text):
+    """
+    Format ``text`` with a color and/or some attributes::
+
+        color       normal color
+        *color*     bold color
+        _color_     underlined color
+        +color+     blinking color
+    """
+    result = []
+    if attr[:1] == attr[-1:] == '+':
+        result.append(codes['blink'])
+        attr = attr[1:-1]
+    if attr[:1] == attr[-1:] == '*':
+        result.append(codes['bold'])
+        attr = attr[1:-1]
+    if attr[:1] == attr[-1:] == '_':
+        result.append(codes['underline'])
+        attr = attr[1:-1]
+    result.append(codes[attr])
+    result.append(text)
+    result.append(codes['reset'])
+    return ''.join(result)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/filter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/filter.py
new file mode 100644
index 0000000000000000000000000000000000000000..e5c9664938215620d656605ff0a7a5e7636370d2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/filter.py
@@ -0,0 +1,71 @@
+"""
+    pygments.filter
+    ~~~~~~~~~~~~~~~
+
+    Module that implements the default filter.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+
+def apply_filters(stream, filters, lexer=None):
+    """
+    Use this method to apply an iterable of filters to
+    a stream. If lexer is given it's forwarded to the
+    filter, otherwise the filter receives `None`.
+    """
+    def _apply(filter_, stream):
+        yield from filter_.filter(lexer, stream)
+    for filter_ in filters:
+        stream = _apply(filter_, stream)
+    return stream
+
+
+def simplefilter(f):
+    """
+    Decorator that converts a function into a filter::
+
+        @simplefilter
+        def lowercase(self, lexer, stream, options):
+            for ttype, value in stream:
+                yield ttype, value.lower()
+    """
+    return type(f.__name__, (FunctionFilter,), {
+        '__module__': getattr(f, '__module__'),
+        '__doc__': f.__doc__,
+        'function': f,
+    })
+
+
+class Filter:
+    """
+    Default filter. Subclass this class or use the `simplefilter`
+    decorator to create own filters.
+    """
+
+    def __init__(self, **options):
+        self.options = options
+
+    def filter(self, lexer, stream):
+        raise NotImplementedError()
+
+
+class FunctionFilter(Filter):
+    """
+    Abstract class used by `simplefilter` to create simple
+    function filters on the fly. The `simplefilter` decorator
+    automatically creates subclasses of this class for
+    functions passed to it.
+    """
+    function = None
+
+    def __init__(self, **options):
+        if not hasattr(self, 'function'):
+            raise TypeError('%r used without bound function' %
+                            self.__class__.__name__)
+        Filter.__init__(self, **options)
+
+    def filter(self, lexer, stream):
+        # pylint: disable=not-callable
+        yield from self.function(lexer, stream, self.options)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/filters/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/filters/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..c302a6c0c53d7efa8767bd55da2a73535bea0cbf
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/filters/__init__.py
@@ -0,0 +1,940 @@
+"""
+    pygments.filters
+    ~~~~~~~~~~~~~~~~
+
+    Module containing filter lookup functions and default
+    filters.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+import re
+
+from pip._vendor.pygments.token import String, Comment, Keyword, Name, Error, Whitespace, \
+    string_to_tokentype
+from pip._vendor.pygments.filter import Filter
+from pip._vendor.pygments.util import get_list_opt, get_int_opt, get_bool_opt, \
+    get_choice_opt, ClassNotFound, OptionError
+from pip._vendor.pygments.plugin import find_plugin_filters
+
+
+def find_filter_class(filtername):
+    """Lookup a filter by name. Return None if not found."""
+    if filtername in FILTERS:
+        return FILTERS[filtername]
+    for name, cls in find_plugin_filters():
+        if name == filtername:
+            return cls
+    return None
+
+
+def get_filter_by_name(filtername, **options):
+    """Return an instantiated filter.
+
+    Options are passed to the filter initializer if wanted.
+    Raise a ClassNotFound if not found.
+    """
+    cls = find_filter_class(filtername)
+    if cls:
+        return cls(**options)
+    else:
+        raise ClassNotFound('filter %r not found' % filtername)
+
+
+def get_all_filters():
+    """Return a generator of all filter names."""
+    yield from FILTERS
+    for name, _ in find_plugin_filters():
+        yield name
+
+
+def _replace_special(ttype, value, regex, specialttype,
+                     replacefunc=lambda x: x):
+    last = 0
+    for match in regex.finditer(value):
+        start, end = match.start(), match.end()
+        if start != last:
+            yield ttype, value[last:start]
+        yield specialttype, replacefunc(value[start:end])
+        last = end
+    if last != len(value):
+        yield ttype, value[last:]
+
+
+class CodeTagFilter(Filter):
+    """Highlight special code tags in comments and docstrings.
+
+    Options accepted:
+
+    `codetags` : list of strings
+       A list of strings that are flagged as code tags.  The default is to
+       highlight ``XXX``, ``TODO``, ``FIXME``, ``BUG`` and ``NOTE``.
+
+    .. versionchanged:: 2.13
+       Now recognizes ``FIXME`` by default.
+    """
+
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+        tags = get_list_opt(options, 'codetags',
+                            ['XXX', 'TODO', 'FIXME', 'BUG', 'NOTE'])
+        self.tag_re = re.compile(r'\b(%s)\b' % '|'.join([
+            re.escape(tag) for tag in tags if tag
+        ]))
+
+    def filter(self, lexer, stream):
+        regex = self.tag_re
+        for ttype, value in stream:
+            if ttype in String.Doc or \
+               ttype in Comment and \
+               ttype not in Comment.Preproc:
+                yield from _replace_special(ttype, value, regex, Comment.Special)
+            else:
+                yield ttype, value
+
+
+class SymbolFilter(Filter):
+    """Convert mathematical symbols such as \\ in Isabelle
+    or \\longrightarrow in LaTeX into Unicode characters.
+
+    This is mostly useful for HTML or console output when you want to
+    approximate the source rendering you'd see in an IDE.
+
+    Options accepted:
+
+    `lang` : string
+       The symbol language. Must be one of ``'isabelle'`` or
+       ``'latex'``.  The default is ``'isabelle'``.
+    """
+
+    latex_symbols = {
+        '\\alpha'                : '\U000003b1',
+        '\\beta'                 : '\U000003b2',
+        '\\gamma'                : '\U000003b3',
+        '\\delta'                : '\U000003b4',
+        '\\varepsilon'           : '\U000003b5',
+        '\\zeta'                 : '\U000003b6',
+        '\\eta'                  : '\U000003b7',
+        '\\vartheta'             : '\U000003b8',
+        '\\iota'                 : '\U000003b9',
+        '\\kappa'                : '\U000003ba',
+        '\\lambda'               : '\U000003bb',
+        '\\mu'                   : '\U000003bc',
+        '\\nu'                   : '\U000003bd',
+        '\\xi'                   : '\U000003be',
+        '\\pi'                   : '\U000003c0',
+        '\\varrho'               : '\U000003c1',
+        '\\sigma'                : '\U000003c3',
+        '\\tau'                  : '\U000003c4',
+        '\\upsilon'              : '\U000003c5',
+        '\\varphi'               : '\U000003c6',
+        '\\chi'                  : '\U000003c7',
+        '\\psi'                  : '\U000003c8',
+        '\\omega'                : '\U000003c9',
+        '\\Gamma'                : '\U00000393',
+        '\\Delta'                : '\U00000394',
+        '\\Theta'                : '\U00000398',
+        '\\Lambda'               : '\U0000039b',
+        '\\Xi'                   : '\U0000039e',
+        '\\Pi'                   : '\U000003a0',
+        '\\Sigma'                : '\U000003a3',
+        '\\Upsilon'              : '\U000003a5',
+        '\\Phi'                  : '\U000003a6',
+        '\\Psi'                  : '\U000003a8',
+        '\\Omega'                : '\U000003a9',
+        '\\leftarrow'            : '\U00002190',
+        '\\longleftarrow'        : '\U000027f5',
+        '\\rightarrow'           : '\U00002192',
+        '\\longrightarrow'       : '\U000027f6',
+        '\\Leftarrow'            : '\U000021d0',
+        '\\Longleftarrow'        : '\U000027f8',
+        '\\Rightarrow'           : '\U000021d2',
+        '\\Longrightarrow'       : '\U000027f9',
+        '\\leftrightarrow'       : '\U00002194',
+        '\\longleftrightarrow'   : '\U000027f7',
+        '\\Leftrightarrow'       : '\U000021d4',
+        '\\Longleftrightarrow'   : '\U000027fa',
+        '\\mapsto'               : '\U000021a6',
+        '\\longmapsto'           : '\U000027fc',
+        '\\relbar'               : '\U00002500',
+        '\\Relbar'               : '\U00002550',
+        '\\hookleftarrow'        : '\U000021a9',
+        '\\hookrightarrow'       : '\U000021aa',
+        '\\leftharpoondown'      : '\U000021bd',
+        '\\rightharpoondown'     : '\U000021c1',
+        '\\leftharpoonup'        : '\U000021bc',
+        '\\rightharpoonup'       : '\U000021c0',
+        '\\rightleftharpoons'    : '\U000021cc',
+        '\\leadsto'              : '\U0000219d',
+        '\\downharpoonleft'      : '\U000021c3',
+        '\\downharpoonright'     : '\U000021c2',
+        '\\upharpoonleft'        : '\U000021bf',
+        '\\upharpoonright'       : '\U000021be',
+        '\\restriction'          : '\U000021be',
+        '\\uparrow'              : '\U00002191',
+        '\\Uparrow'              : '\U000021d1',
+        '\\downarrow'            : '\U00002193',
+        '\\Downarrow'            : '\U000021d3',
+        '\\updownarrow'          : '\U00002195',
+        '\\Updownarrow'          : '\U000021d5',
+        '\\langle'               : '\U000027e8',
+        '\\rangle'               : '\U000027e9',
+        '\\lceil'                : '\U00002308',
+        '\\rceil'                : '\U00002309',
+        '\\lfloor'               : '\U0000230a',
+        '\\rfloor'               : '\U0000230b',
+        '\\flqq'                 : '\U000000ab',
+        '\\frqq'                 : '\U000000bb',
+        '\\bot'                  : '\U000022a5',
+        '\\top'                  : '\U000022a4',
+        '\\wedge'                : '\U00002227',
+        '\\bigwedge'             : '\U000022c0',
+        '\\vee'                  : '\U00002228',
+        '\\bigvee'               : '\U000022c1',
+        '\\forall'               : '\U00002200',
+        '\\exists'               : '\U00002203',
+        '\\nexists'              : '\U00002204',
+        '\\neg'                  : '\U000000ac',
+        '\\Box'                  : '\U000025a1',
+        '\\Diamond'              : '\U000025c7',
+        '\\vdash'                : '\U000022a2',
+        '\\models'               : '\U000022a8',
+        '\\dashv'                : '\U000022a3',
+        '\\surd'                 : '\U0000221a',
+        '\\le'                   : '\U00002264',
+        '\\ge'                   : '\U00002265',
+        '\\ll'                   : '\U0000226a',
+        '\\gg'                   : '\U0000226b',
+        '\\lesssim'              : '\U00002272',
+        '\\gtrsim'               : '\U00002273',
+        '\\lessapprox'           : '\U00002a85',
+        '\\gtrapprox'            : '\U00002a86',
+        '\\in'                   : '\U00002208',
+        '\\notin'                : '\U00002209',
+        '\\subset'               : '\U00002282',
+        '\\supset'               : '\U00002283',
+        '\\subseteq'             : '\U00002286',
+        '\\supseteq'             : '\U00002287',
+        '\\sqsubset'             : '\U0000228f',
+        '\\sqsupset'             : '\U00002290',
+        '\\sqsubseteq'           : '\U00002291',
+        '\\sqsupseteq'           : '\U00002292',
+        '\\cap'                  : '\U00002229',
+        '\\bigcap'               : '\U000022c2',
+        '\\cup'                  : '\U0000222a',
+        '\\bigcup'               : '\U000022c3',
+        '\\sqcup'                : '\U00002294',
+        '\\bigsqcup'             : '\U00002a06',
+        '\\sqcap'                : '\U00002293',
+        '\\Bigsqcap'             : '\U00002a05',
+        '\\setminus'             : '\U00002216',
+        '\\propto'               : '\U0000221d',
+        '\\uplus'                : '\U0000228e',
+        '\\bigplus'              : '\U00002a04',
+        '\\sim'                  : '\U0000223c',
+        '\\doteq'                : '\U00002250',
+        '\\simeq'                : '\U00002243',
+        '\\approx'               : '\U00002248',
+        '\\asymp'                : '\U0000224d',
+        '\\cong'                 : '\U00002245',
+        '\\equiv'                : '\U00002261',
+        '\\Join'                 : '\U000022c8',
+        '\\bowtie'               : '\U00002a1d',
+        '\\prec'                 : '\U0000227a',
+        '\\succ'                 : '\U0000227b',
+        '\\preceq'               : '\U0000227c',
+        '\\succeq'               : '\U0000227d',
+        '\\parallel'             : '\U00002225',
+        '\\mid'                  : '\U000000a6',
+        '\\pm'                   : '\U000000b1',
+        '\\mp'                   : '\U00002213',
+        '\\times'                : '\U000000d7',
+        '\\div'                  : '\U000000f7',
+        '\\cdot'                 : '\U000022c5',
+        '\\star'                 : '\U000022c6',
+        '\\circ'                 : '\U00002218',
+        '\\dagger'               : '\U00002020',
+        '\\ddagger'              : '\U00002021',
+        '\\lhd'                  : '\U000022b2',
+        '\\rhd'                  : '\U000022b3',
+        '\\unlhd'                : '\U000022b4',
+        '\\unrhd'                : '\U000022b5',
+        '\\triangleleft'         : '\U000025c3',
+        '\\triangleright'        : '\U000025b9',
+        '\\triangle'             : '\U000025b3',
+        '\\triangleq'            : '\U0000225c',
+        '\\oplus'                : '\U00002295',
+        '\\bigoplus'             : '\U00002a01',
+        '\\otimes'               : '\U00002297',
+        '\\bigotimes'            : '\U00002a02',
+        '\\odot'                 : '\U00002299',
+        '\\bigodot'              : '\U00002a00',
+        '\\ominus'               : '\U00002296',
+        '\\oslash'               : '\U00002298',
+        '\\dots'                 : '\U00002026',
+        '\\cdots'                : '\U000022ef',
+        '\\sum'                  : '\U00002211',
+        '\\prod'                 : '\U0000220f',
+        '\\coprod'               : '\U00002210',
+        '\\infty'                : '\U0000221e',
+        '\\int'                  : '\U0000222b',
+        '\\oint'                 : '\U0000222e',
+        '\\clubsuit'             : '\U00002663',
+        '\\diamondsuit'          : '\U00002662',
+        '\\heartsuit'            : '\U00002661',
+        '\\spadesuit'            : '\U00002660',
+        '\\aleph'                : '\U00002135',
+        '\\emptyset'             : '\U00002205',
+        '\\nabla'                : '\U00002207',
+        '\\partial'              : '\U00002202',
+        '\\flat'                 : '\U0000266d',
+        '\\natural'              : '\U0000266e',
+        '\\sharp'                : '\U0000266f',
+        '\\angle'                : '\U00002220',
+        '\\copyright'            : '\U000000a9',
+        '\\textregistered'       : '\U000000ae',
+        '\\textonequarter'       : '\U000000bc',
+        '\\textonehalf'          : '\U000000bd',
+        '\\textthreequarters'    : '\U000000be',
+        '\\textordfeminine'      : '\U000000aa',
+        '\\textordmasculine'     : '\U000000ba',
+        '\\euro'                 : '\U000020ac',
+        '\\pounds'               : '\U000000a3',
+        '\\yen'                  : '\U000000a5',
+        '\\textcent'             : '\U000000a2',
+        '\\textcurrency'         : '\U000000a4',
+        '\\textdegree'           : '\U000000b0',
+    }
+
+    isabelle_symbols = {
+        '\\'                 : '\U0001d7ec',
+        '\\'                  : '\U0001d7ed',
+        '\\'                  : '\U0001d7ee',
+        '\\'                : '\U0001d7ef',
+        '\\'                 : '\U0001d7f0',
+        '\\'                 : '\U0001d7f1',
+        '\\'                  : '\U0001d7f2',
+        '\\'                : '\U0001d7f3',
+        '\\'                : '\U0001d7f4',
+        '\\'                 : '\U0001d7f5',
+        '\\'                    : '\U0001d49c',
+        '\\'                    : '\U0000212c',
+        '\\'                    : '\U0001d49e',
+        '\\'                    : '\U0001d49f',
+        '\\'                    : '\U00002130',
+        '\\'                    : '\U00002131',
+        '\\'                    : '\U0001d4a2',
+        '\\'                    : '\U0000210b',
+        '\\'                    : '\U00002110',
+        '\\'                    : '\U0001d4a5',
+        '\\'                    : '\U0001d4a6',
+        '\\'                    : '\U00002112',
+        '\\'                    : '\U00002133',
+        '\\'                    : '\U0001d4a9',
+        '\\'                    : '\U0001d4aa',
+        '\\
'                    : '\U0001d5c9',
+        '\\'                    : '\U0001d5ca',
+        '\\'                    : '\U0001d5cb',
+        '\\'                    : '\U0001d5cc',
+        '\\'                    : '\U0001d5cd',
+        '\\'                    : '\U0001d5ce',
+        '\\'                    : '\U0001d5cf',
+        '\\'                    : '\U0001d5d0',
+        '\\'                    : '\U0001d5d1',
+        '\\'                    : '\U0001d5d2',
+        '\\'                    : '\U0001d5d3',
+        '\\'                   : '\U0001d504',
+        '\\'                   : '\U0001d505',
+        '\\'                   : '\U0000212d',
+        '\\
'                   : '\U0001d507',
+        '\\'                   : '\U0001d508',
+        '\\'                   : '\U0001d509',
+        '\\'                   : '\U0001d50a',
+        '\\'                   : '\U0000210c',
+        '\\'                   : '\U00002111',
+        '\\'                   : '\U0001d50d',
+        '\\'                   : '\U0001d50e',
+        '\\'                   : '\U0001d50f',
+        '\\'                   : '\U0001d510',
+        '\\'                   : '\U0001d511',
+        '\\'                   : '\U0001d512',
+        '\\'                   : '\U0001d513',
+        '\\'                   : '\U0001d514',
+        '\\'                   : '\U0000211c',
+        '\\'                   : '\U0001d516',
+        '\\'                   : '\U0001d517',
+        '\\'                   : '\U0001d518',
+        '\\'                   : '\U0001d519',
+        '\\'                   : '\U0001d51a',
+        '\\'                   : '\U0001d51b',
+        '\\'                   : '\U0001d51c',
+        '\\'                   : '\U00002128',
+        '\\'                   : '\U0001d51e',
+        '\\'                   : '\U0001d51f',
+        '\\'                   : '\U0001d520',
+        '\\
'                   : '\U0001d521',
+        '\\'                   : '\U0001d522',
+        '\\'                   : '\U0001d523',
+        '\\'                   : '\U0001d524',
+        '\\'                   : '\U0001d525',
+        '\\'                   : '\U0001d526',
+        '\\'                   : '\U0001d527',
+        '\\'                   : '\U0001d528',
+        '\\'                   : '\U0001d529',
+        '\\'                   : '\U0001d52a',
+        '\\'                   : '\U0001d52b',
+        '\\'                   : '\U0001d52c',
+        '\\'                   : '\U0001d52d',
+        '\\'                   : '\U0001d52e',
+        '\\'                   : '\U0001d52f',
+        '\\'                   : '\U0001d530',
+        '\\'                   : '\U0001d531',
+        '\\'                   : '\U0001d532',
+        '\\'                   : '\U0001d533',
+        '\\'                   : '\U0001d534',
+        '\\'                   : '\U0001d535',
+        '\\'                   : '\U0001d536',
+        '\\'                   : '\U0001d537',
+        '\\'                : '\U000003b1',
+        '\\'                 : '\U000003b2',
+        '\\'                : '\U000003b3',
+        '\\'                : '\U000003b4',
+        '\\'              : '\U000003b5',
+        '\\'                 : '\U000003b6',
+        '\\'                  : '\U000003b7',
+        '\\'                : '\U000003b8',
+        '\\'                 : '\U000003b9',
+        '\\'                : '\U000003ba',
+        '\\'               : '\U000003bb',
+        '\\'                   : '\U000003bc',
+        '\\'                   : '\U000003bd',
+        '\\'                   : '\U000003be',
+        '\\'                   : '\U000003c0',
+        '\\'                  : '\U000003c1',
+        '\\'                : '\U000003c3',
+        '\\'                  : '\U000003c4',
+        '\\'              : '\U000003c5',
+        '\\'                  : '\U000003c6',
+        '\\'                  : '\U000003c7',
+        '\\'                  : '\U000003c8',
+        '\\'                : '\U000003c9',
+        '\\'                : '\U00000393',
+        '\\'                : '\U00000394',
+        '\\'                : '\U00000398',
+        '\\'               : '\U0000039b',
+        '\\'                   : '\U0000039e',
+        '\\'                   : '\U000003a0',
+        '\\'                : '\U000003a3',
+        '\\'              : '\U000003a5',
+        '\\'                  : '\U000003a6',
+        '\\'                  : '\U000003a8',
+        '\\'                : '\U000003a9',
+        '\\'                 : '\U0001d539',
+        '\\'              : '\U00002102',
+        '\\'                  : '\U00002115',
+        '\\'                  : '\U0000211a',
+        '\\'                 : '\U0000211d',
+        '\\'                  : '\U00002124',
+        '\\'            : '\U00002190',
+        '\\'        : '\U000027f5',
+        '\\'           : '\U00002192',
+        '\\'       : '\U000027f6',
+        '\\'            : '\U000021d0',
+        '\\'        : '\U000027f8',
+        '\\'           : '\U000021d2',
+        '\\'       : '\U000027f9',
+        '\\'       : '\U00002194',
+        '\\'   : '\U000027f7',
+        '\\'       : '\U000021d4',
+        '\\'   : '\U000027fa',
+        '\\'               : '\U000021a6',
+        '\\'           : '\U000027fc',
+        '\\'             : '\U00002500',
+        '\\'             : '\U00002550',
+        '\\'        : '\U000021a9',
+        '\\'       : '\U000021aa',
+        '\\'      : '\U000021bd',
+        '\\'     : '\U000021c1',
+        '\\'        : '\U000021bc',
+        '\\'       : '\U000021c0',
+        '\\'    : '\U000021cc',
+        '\\'              : '\U0000219d',
+        '\\'      : '\U000021c3',
+        '\\'     : '\U000021c2',
+        '\\'        : '\U000021bf',
+        '\\'       : '\U000021be',
+        '\\'          : '\U000021be',
+        '\\'                : '\U00002237',
+        '\\'                   : '\U00002191',
+        '\\'                   : '\U000021d1',
+        '\\'                 : '\U00002193',
+        '\\'                 : '\U000021d3',
+        '\\'               : '\U00002195',
+        '\\'               : '\U000021d5',
+        '\\'               : '\U000027e8',
+        '\\'               : '\U000027e9',
+        '\\'                : '\U00002308',
+        '\\'                : '\U00002309',
+        '\\'               : '\U0000230a',
+        '\\'               : '\U0000230b',
+        '\\'                : '\U00002987',
+        '\\'                : '\U00002988',
+        '\\'               : '\U000027e6',
+        '\\'               : '\U000027e7',
+        '\\'               : '\U00002983',
+        '\\'               : '\U00002984',
+        '\\'        : '\U000000ab',
+        '\\'       : '\U000000bb',
+        '\\'               : '\U000022a5',
+        '\\'                  : '\U000022a4',
+        '\\'                  : '\U00002227',
+        '\\'                  : '\U000022c0',
+        '\\'                   : '\U00002228',
+        '\\'                   : '\U000022c1',
+        '\\'               : '\U00002200',
+        '\\'               : '\U00002203',
+        '\\'              : '\U00002204',
+        '\\'                  : '\U000000ac',
+        '\\'                  : '\U000025a1',
+        '\\'              : '\U000025c7',
+        '\\'            : '\U000022a2',
+        '\\'            : '\U000022a8',
+        '\\'           : '\U000022a9',
+        '\\'           : '\U000022ab',
+        '\\'            : '\U000022a3',
+        '\\'                 : '\U0000221a',
+        '\\'                   : '\U00002264',
+        '\\'                   : '\U00002265',
+        '\\'                : '\U0000226a',
+        '\\'             : '\U0000226b',
+        '\\'              : '\U00002272',
+        '\\'           : '\U00002273',
+        '\\'           : '\U00002a85',
+        '\\'        : '\U00002a86',
+        '\\'                   : '\U00002208',
+        '\\'                : '\U00002209',
+        '\\'               : '\U00002282',
+        '\\'               : '\U00002283',
+        '\\'             : '\U00002286',
+        '\\'             : '\U00002287',
+        '\\'             : '\U0000228f',
+        '\\'             : '\U00002290',
+        '\\'           : '\U00002291',
+        '\\'           : '\U00002292',
+        '\\'                : '\U00002229',
+        '\\'                : '\U000022c2',
+        '\\'                : '\U0000222a',
+        '\\'                : '\U000022c3',
+        '\\'              : '\U00002294',
+        '\\'              : '\U00002a06',
+        '\\'              : '\U00002293',
+        '\\'              : '\U00002a05',
+        '\\'             : '\U00002216',
+        '\\'               : '\U0000221d',
+        '\\'                : '\U0000228e',
+        '\\'                : '\U00002a04',
+        '\\'                : '\U00002260',
+        '\\'                  : '\U0000223c',
+        '\\'                : '\U00002250',
+        '\\'                : '\U00002243',
+        '\\'               : '\U00002248',
+        '\\'                : '\U0000224d',
+        '\\'                 : '\U00002245',
+        '\\'                : '\U00002323',
+        '\\'                : '\U00002261',
+        '\\'                : '\U00002322',
+        '\\'                 : '\U000022c8',
+        '\\'               : '\U00002a1d',
+        '\\'                 : '\U0000227a',
+        '\\'                 : '\U0000227b',
+        '\\'               : '\U0000227c',
+        '\\'               : '\U0000227d',
+        '\\'             : '\U00002225',
+        '\\'                  : '\U000000a6',
+        '\\'            : '\U000000b1',
+        '\\'            : '\U00002213',
+        '\\'                : '\U000000d7',
+        '\\
'                  : '\U000000f7',
+        '\\'                 : '\U000022c5',
+        '\\'                 : '\U000022c6',
+        '\\'               : '\U00002219',
+        '\\'                 : '\U00002218',
+        '\\'               : '\U00002020',
+        '\\'              : '\U00002021',
+        '\\'                  : '\U000022b2',
+        '\\'                  : '\U000022b3',
+        '\\'                : '\U000022b4',
+        '\\'                : '\U000022b5',
+        '\\'         : '\U000025c3',
+        '\\'        : '\U000025b9',
+        '\\'             : '\U000025b3',
+        '\\'            : '\U0000225c',
+        '\\'                : '\U00002295',
+        '\\'                : '\U00002a01',
+        '\\'               : '\U00002297',
+        '\\'               : '\U00002a02',
+        '\\'                 : '\U00002299',
+        '\\'                 : '\U00002a00',
+        '\\'               : '\U00002296',
+        '\\'               : '\U00002298',
+        '\\'                 : '\U00002026',
+        '\\'                : '\U000022ef',
+        '\\'                  : '\U00002211',
+        '\\'                 : '\U0000220f',
+        '\\'               : '\U00002210',
+        '\\'             : '\U0000221e',
+        '\\'             : '\U0000222b',
+        '\\'            : '\U0000222e',
+        '\\'             : '\U00002663',
+        '\\'          : '\U00002662',
+        '\\'            : '\U00002661',
+        '\\'            : '\U00002660',
+        '\\'                : '\U00002135',
+        '\\'             : '\U00002205',
+        '\\'                : '\U00002207',
+        '\\'              : '\U00002202',
+        '\\'                 : '\U0000266d',
+        '\\'              : '\U0000266e',
+        '\\'                : '\U0000266f',
+        '\\'                : '\U00002220',
+        '\\'            : '\U000000a9',
+        '\\'           : '\U000000ae',
+        '\\'               : '\U000000ad',
+        '\\'              : '\U000000af',
+        '\\'           : '\U000000bc',
+        '\\'              : '\U000000bd',
+        '\\'        : '\U000000be',
+        '\\'          : '\U000000aa',
+        '\\'         : '\U000000ba',
+        '\\
'              : '\U000000a7',
+        '\\'            : '\U000000b6',
+        '\\'           : '\U000000a1',
+        '\\'         : '\U000000bf',
+        '\\'                 : '\U000020ac',
+        '\\'               : '\U000000a3',
+        '\\'                  : '\U000000a5',
+        '\\'                 : '\U000000a2',
+        '\\'             : '\U000000a4',
+        '\\'               : '\U000000b0',
+        '\\'                : '\U00002a3f',
+        '\\'                  : '\U00002127',
+        '\\'              : '\U000025ca',
+        '\\'                   : '\U00002118',
+        '\\'                : '\U00002240',
+        '\\'               : '\U000022c4',
+        '\\'                : '\U000000b4',
+        '\\'                : '\U00000131',
+        '\\'             : '\U000000a8',
+        '\\'              : '\U000000b8',
+        '\\'         : '\U000002dd',
+        '\\'                 : '\U000003f5',
+        '\\'              : '\U000023ce',
+        '\\'                 : '\U00002039',
+        '\\'                : '\U0000203a',
+        '\\'                 : '\U00002302',
+        '\\<^sub>'                 : '\U000021e9',
+        '\\<^sup>'                 : '\U000021e7',
+        '\\<^bold>'                : '\U00002759',
+        '\\<^bsub>'                : '\U000021d8',
+        '\\<^esub>'                : '\U000021d9',
+        '\\<^bsup>'                : '\U000021d7',
+        '\\<^esup>'                : '\U000021d6',
+    }
+
+    lang_map = {'isabelle' : isabelle_symbols, 'latex' : latex_symbols}
+
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+        lang = get_choice_opt(options, 'lang',
+                              ['isabelle', 'latex'], 'isabelle')
+        self.symbols = self.lang_map[lang]
+
+    def filter(self, lexer, stream):
+        for ttype, value in stream:
+            if value in self.symbols:
+                yield ttype, self.symbols[value]
+            else:
+                yield ttype, value
+
+
+class KeywordCaseFilter(Filter):
+    """Convert keywords to lowercase or uppercase or capitalize them, which
+    means first letter uppercase, rest lowercase.
+
+    This can be useful e.g. if you highlight Pascal code and want to adapt the
+    code to your styleguide.
+
+    Options accepted:
+
+    `case` : string
+       The casing to convert keywords to. Must be one of ``'lower'``,
+       ``'upper'`` or ``'capitalize'``.  The default is ``'lower'``.
+    """
+
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+        case = get_choice_opt(options, 'case',
+                              ['lower', 'upper', 'capitalize'], 'lower')
+        self.convert = getattr(str, case)
+
+    def filter(self, lexer, stream):
+        for ttype, value in stream:
+            if ttype in Keyword:
+                yield ttype, self.convert(value)
+            else:
+                yield ttype, value
+
+
+class NameHighlightFilter(Filter):
+    """Highlight a normal Name (and Name.*) token with a different token type.
+
+    Example::
+
+        filter = NameHighlightFilter(
+            names=['foo', 'bar', 'baz'],
+            tokentype=Name.Function,
+        )
+
+    This would highlight the names "foo", "bar" and "baz"
+    as functions. `Name.Function` is the default token type.
+
+    Options accepted:
+
+    `names` : list of strings
+      A list of names that should be given the different token type.
+      There is no default.
+    `tokentype` : TokenType or string
+      A token type or a string containing a token type name that is
+      used for highlighting the strings in `names`.  The default is
+      `Name.Function`.
+    """
+
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+        self.names = set(get_list_opt(options, 'names', []))
+        tokentype = options.get('tokentype')
+        if tokentype:
+            self.tokentype = string_to_tokentype(tokentype)
+        else:
+            self.tokentype = Name.Function
+
+    def filter(self, lexer, stream):
+        for ttype, value in stream:
+            if ttype in Name and value in self.names:
+                yield self.tokentype, value
+            else:
+                yield ttype, value
+
+
+class ErrorToken(Exception):
+    pass
+
+
+class RaiseOnErrorTokenFilter(Filter):
+    """Raise an exception when the lexer generates an error token.
+
+    Options accepted:
+
+    `excclass` : Exception class
+      The exception class to raise.
+      The default is `pygments.filters.ErrorToken`.
+
+    .. versionadded:: 0.8
+    """
+
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+        self.exception = options.get('excclass', ErrorToken)
+        try:
+            # issubclass() will raise TypeError if first argument is not a class
+            if not issubclass(self.exception, Exception):
+                raise TypeError
+        except TypeError:
+            raise OptionError('excclass option is not an exception class')
+
+    def filter(self, lexer, stream):
+        for ttype, value in stream:
+            if ttype is Error:
+                raise self.exception(value)
+            yield ttype, value
+
+
+class VisibleWhitespaceFilter(Filter):
+    """Convert tabs, newlines and/or spaces to visible characters.
+
+    Options accepted:
+
+    `spaces` : string or bool
+      If this is a one-character string, spaces will be replaces by this string.
+      If it is another true value, spaces will be replaced by ``·`` (unicode
+      MIDDLE DOT).  If it is a false value, spaces will not be replaced.  The
+      default is ``False``.
+    `tabs` : string or bool
+      The same as for `spaces`, but the default replacement character is ``»``
+      (unicode RIGHT-POINTING DOUBLE ANGLE QUOTATION MARK).  The default value
+      is ``False``.  Note: this will not work if the `tabsize` option for the
+      lexer is nonzero, as tabs will already have been expanded then.
+    `tabsize` : int
+      If tabs are to be replaced by this filter (see the `tabs` option), this
+      is the total number of characters that a tab should be expanded to.
+      The default is ``8``.
+    `newlines` : string or bool
+      The same as for `spaces`, but the default replacement character is ``¶``
+      (unicode PILCROW SIGN).  The default value is ``False``.
+    `wstokentype` : bool
+      If true, give whitespace the special `Whitespace` token type.  This allows
+      styling the visible whitespace differently (e.g. greyed out), but it can
+      disrupt background colors.  The default is ``True``.
+
+    .. versionadded:: 0.8
+    """
+
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+        for name, default in [('spaces',   '·'),
+                              ('tabs',     '»'),
+                              ('newlines', '¶')]:
+            opt = options.get(name, False)
+            if isinstance(opt, str) and len(opt) == 1:
+                setattr(self, name, opt)
+            else:
+                setattr(self, name, (opt and default or ''))
+        tabsize = get_int_opt(options, 'tabsize', 8)
+        if self.tabs:
+            self.tabs += ' ' * (tabsize - 1)
+        if self.newlines:
+            self.newlines += '\n'
+        self.wstt = get_bool_opt(options, 'wstokentype', True)
+
+    def filter(self, lexer, stream):
+        if self.wstt:
+            spaces = self.spaces or ' '
+            tabs = self.tabs or '\t'
+            newlines = self.newlines or '\n'
+            regex = re.compile(r'\s')
+
+            def replacefunc(wschar):
+                if wschar == ' ':
+                    return spaces
+                elif wschar == '\t':
+                    return tabs
+                elif wschar == '\n':
+                    return newlines
+                return wschar
+
+            for ttype, value in stream:
+                yield from _replace_special(ttype, value, regex, Whitespace,
+                                            replacefunc)
+        else:
+            spaces, tabs, newlines = self.spaces, self.tabs, self.newlines
+            # simpler processing
+            for ttype, value in stream:
+                if spaces:
+                    value = value.replace(' ', spaces)
+                if tabs:
+                    value = value.replace('\t', tabs)
+                if newlines:
+                    value = value.replace('\n', newlines)
+                yield ttype, value
+
+
+class GobbleFilter(Filter):
+    """Gobbles source code lines (eats initial characters).
+
+    This filter drops the first ``n`` characters off every line of code.  This
+    may be useful when the source code fed to the lexer is indented by a fixed
+    amount of space that isn't desired in the output.
+
+    Options accepted:
+
+    `n` : int
+       The number of characters to gobble.
+
+    .. versionadded:: 1.2
+    """
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+        self.n = get_int_opt(options, 'n', 0)
+
+    def gobble(self, value, left):
+        if left < len(value):
+            return value[left:], 0
+        else:
+            return '', left - len(value)
+
+    def filter(self, lexer, stream):
+        n = self.n
+        left = n  # How many characters left to gobble.
+        for ttype, value in stream:
+            # Remove ``left`` tokens from first line, ``n`` from all others.
+            parts = value.split('\n')
+            (parts[0], left) = self.gobble(parts[0], left)
+            for i in range(1, len(parts)):
+                (parts[i], left) = self.gobble(parts[i], n)
+            value = '\n'.join(parts)
+
+            if value != '':
+                yield ttype, value
+
+
+class TokenMergeFilter(Filter):
+    """Merges consecutive tokens with the same token type in the output
+    stream of a lexer.
+
+    .. versionadded:: 1.2
+    """
+    def __init__(self, **options):
+        Filter.__init__(self, **options)
+
+    def filter(self, lexer, stream):
+        current_type = None
+        current_value = None
+        for ttype, value in stream:
+            if ttype is current_type:
+                current_value += value
+            else:
+                if current_type is not None:
+                    yield current_type, current_value
+                current_type = ttype
+                current_value = value
+        if current_type is not None:
+            yield current_type, current_value
+
+
+FILTERS = {
+    'codetagify':     CodeTagFilter,
+    'keywordcase':    KeywordCaseFilter,
+    'highlight':      NameHighlightFilter,
+    'raiseonerror':   RaiseOnErrorTokenFilter,
+    'whitespace':     VisibleWhitespaceFilter,
+    'gobble':         GobbleFilter,
+    'tokenmerge':     TokenMergeFilter,
+    'symbols':        SymbolFilter,
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatter.py
new file mode 100644
index 0000000000000000000000000000000000000000..a2349ef8652c659388ba69477c01989f2e4ce17d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatter.py
@@ -0,0 +1,94 @@
+"""
+    pygments.formatter
+    ~~~~~~~~~~~~~~~~~~
+
+    Base formatter class.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+import codecs
+
+from pip._vendor.pygments.util import get_bool_opt
+from pip._vendor.pygments.styles import get_style_by_name
+
+__all__ = ['Formatter']
+
+
+def _lookup_style(style):
+    if isinstance(style, str):
+        return get_style_by_name(style)
+    return style
+
+
+class Formatter:
+    """
+    Converts a token stream to text.
+
+    Options accepted:
+
+    ``style``
+        The style to use, can be a string or a Style subclass
+        (default: "default"). Not used by e.g. the
+        TerminalFormatter.
+    ``full``
+        Tells the formatter to output a "full" document, i.e.
+        a complete self-contained document. This doesn't have
+        any effect for some formatters (default: false).
+    ``title``
+        If ``full`` is true, the title that should be used to
+        caption the document (default: '').
+    ``encoding``
+        If given, must be an encoding name. This will be used to
+        convert the Unicode token strings to byte strings in the
+        output. If it is "" or None, Unicode strings will be written
+        to the output file, which most file-like objects do not
+        support (default: None).
+    ``outencoding``
+        Overrides ``encoding`` if given.
+    """
+
+    #: Name of the formatter
+    name = None
+
+    #: Shortcuts for the formatter
+    aliases = []
+
+    #: fn match rules
+    filenames = []
+
+    #: If True, this formatter outputs Unicode strings when no encoding
+    #: option is given.
+    unicodeoutput = True
+
+    def __init__(self, **options):
+        self.style = _lookup_style(options.get('style', 'default'))
+        self.full = get_bool_opt(options, 'full', False)
+        self.title = options.get('title', '')
+        self.encoding = options.get('encoding', None) or None
+        if self.encoding in ('guess', 'chardet'):
+            # can happen for e.g. pygmentize -O encoding=guess
+            self.encoding = 'utf-8'
+        self.encoding = options.get('outencoding') or self.encoding
+        self.options = options
+
+    def get_style_defs(self, arg=''):
+        """
+        Return the style definitions for the current style as a string.
+
+        ``arg`` is an additional argument whose meaning depends on the
+        formatter used. Note that ``arg`` can also be a list or tuple
+        for some formatters like the html formatter.
+        """
+        return ''
+
+    def format(self, tokensource, outfile):
+        """
+        Format ``tokensource``, an iterable of ``(tokentype, tokenstring)``
+        tuples and write it into ``outfile``.
+        """
+        if self.encoding:
+            # wrap the outfile in a StreamWriter
+            outfile = codecs.lookup(self.encoding)[3](outfile)
+        return self.format_unencoded(tokensource, outfile)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..43c4c89aacf0c771de138e1f58decf9fb592f62f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/__init__.py
@@ -0,0 +1,143 @@
+"""
+    pygments.formatters
+    ~~~~~~~~~~~~~~~~~~~
+
+    Pygments formatters.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+import re
+import sys
+import types
+from fnmatch import fnmatch
+from os.path import basename
+
+from pip._vendor.pygments.formatters._mapping import FORMATTERS
+from pip._vendor.pygments.plugin import find_plugin_formatters
+from pip._vendor.pygments.util import ClassNotFound
+
+__all__ = ['get_formatter_by_name', 'get_formatter_for_filename',
+           'get_all_formatters', 'load_formatter_from_file'] + list(FORMATTERS)
+
+_formatter_cache = {}  # classes by name
+
+def _load_formatters(module_name):
+    """Load a formatter (and all others in the module too)."""
+    mod = __import__(module_name, None, None, ['__all__'])
+    for formatter_name in mod.__all__:
+        cls = getattr(mod, formatter_name)
+        _formatter_cache[cls.name] = cls
+
+
+def get_all_formatters():
+    """Return a generator for all formatter classes."""
+    # NB: this returns formatter classes, not info like get_all_lexers().
+    for info in FORMATTERS.values():
+        if info[1] not in _formatter_cache:
+            _load_formatters(info[0])
+        yield _formatter_cache[info[1]]
+    for _, formatter in find_plugin_formatters():
+        yield formatter
+
+
+def find_formatter_class(alias):
+    """Lookup a formatter by alias.
+
+    Returns None if not found.
+    """
+    for module_name, name, aliases, _, _ in FORMATTERS.values():
+        if alias in aliases:
+            if name not in _formatter_cache:
+                _load_formatters(module_name)
+            return _formatter_cache[name]
+    for _, cls in find_plugin_formatters():
+        if alias in cls.aliases:
+            return cls
+
+
+def get_formatter_by_name(_alias, **options):
+    """Lookup and instantiate a formatter by alias.
+
+    Raises ClassNotFound if not found.
+    """
+    cls = find_formatter_class(_alias)
+    if cls is None:
+        raise ClassNotFound("no formatter found for name %r" % _alias)
+    return cls(**options)
+
+
+def load_formatter_from_file(filename, formattername="CustomFormatter",
+                             **options):
+    """Load a formatter from a file.
+
+    This method expects a file located relative to the current working
+    directory, which contains a class named CustomFormatter. By default,
+    it expects the Formatter to be named CustomFormatter; you can specify
+    your own class name as the second argument to this function.
+
+    Users should be very careful with the input, because this method
+    is equivalent to running eval on the input file.
+
+    Raises ClassNotFound if there are any problems importing the Formatter.
+
+    .. versionadded:: 2.2
+    """
+    try:
+        # This empty dict will contain the namespace for the exec'd file
+        custom_namespace = {}
+        with open(filename, 'rb') as f:
+            exec(f.read(), custom_namespace)
+        # Retrieve the class `formattername` from that namespace
+        if formattername not in custom_namespace:
+            raise ClassNotFound('no valid %s class found in %s' %
+                                (formattername, filename))
+        formatter_class = custom_namespace[formattername]
+        # And finally instantiate it with the options
+        return formatter_class(**options)
+    except OSError as err:
+        raise ClassNotFound('cannot read %s: %s' % (filename, err))
+    except ClassNotFound:
+        raise
+    except Exception as err:
+        raise ClassNotFound('error when loading custom formatter: %s' % err)
+
+
+def get_formatter_for_filename(fn, **options):
+    """Lookup and instantiate a formatter by filename pattern.
+
+    Raises ClassNotFound if not found.
+    """
+    fn = basename(fn)
+    for modname, name, _, filenames, _ in FORMATTERS.values():
+        for filename in filenames:
+            if fnmatch(fn, filename):
+                if name not in _formatter_cache:
+                    _load_formatters(modname)
+                return _formatter_cache[name](**options)
+    for cls in find_plugin_formatters():
+        for filename in cls.filenames:
+            if fnmatch(fn, filename):
+                return cls(**options)
+    raise ClassNotFound("no formatter found for file name %r" % fn)
+
+
+class _automodule(types.ModuleType):
+    """Automatically import formatters."""
+
+    def __getattr__(self, name):
+        info = FORMATTERS.get(name)
+        if info:
+            _load_formatters(info[0])
+            cls = _formatter_cache[info[1]]
+            setattr(self, name, cls)
+            return cls
+        raise AttributeError(name)
+
+
+oldmod = sys.modules[__name__]
+newmod = _automodule(__name__)
+newmod.__dict__.update(oldmod.__dict__)
+sys.modules[__name__] = newmod
+del newmod.newmod, newmod.oldmod, newmod.sys, newmod.types
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/_mapping.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/_mapping.py
new file mode 100644
index 0000000000000000000000000000000000000000..6e34f9607847cb74f8469823c01776baf8216b59
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/_mapping.py
@@ -0,0 +1,23 @@
+# Automatically generated by scripts/gen_mapfiles.py.
+# DO NOT EDIT BY HAND; run `make mapfiles` instead.
+
+FORMATTERS = {
+    'BBCodeFormatter': ('pygments.formatters.bbcode', 'BBCode', ('bbcode', 'bb'), (), 'Format tokens with BBcodes. These formatting codes are used by many bulletin boards, so you can highlight your sourcecode with pygments before posting it there.'),
+    'BmpImageFormatter': ('pygments.formatters.img', 'img_bmp', ('bmp', 'bitmap'), ('*.bmp',), 'Create a bitmap image from source code. This uses the Python Imaging Library to generate a pixmap from the source code.'),
+    'GifImageFormatter': ('pygments.formatters.img', 'img_gif', ('gif',), ('*.gif',), 'Create a GIF image from source code. This uses the Python Imaging Library to generate a pixmap from the source code.'),
+    'GroffFormatter': ('pygments.formatters.groff', 'groff', ('groff', 'troff', 'roff'), (), 'Format tokens with groff escapes to change their color and font style.'),
+    'HtmlFormatter': ('pygments.formatters.html', 'HTML', ('html',), ('*.html', '*.htm'), "Format tokens as HTML 4 ```` tags within a ``
`` tag, wrapped in a ``
`` tag. The ``
``'s CSS class can be set by the `cssclass` option."),
+    'IRCFormatter': ('pygments.formatters.irc', 'IRC', ('irc', 'IRC'), (), 'Format tokens with IRC color sequences'),
+    'ImageFormatter': ('pygments.formatters.img', 'img', ('img', 'IMG', 'png'), ('*.png',), 'Create a PNG image from source code. This uses the Python Imaging Library to generate a pixmap from the source code.'),
+    'JpgImageFormatter': ('pygments.formatters.img', 'img_jpg', ('jpg', 'jpeg'), ('*.jpg',), 'Create a JPEG image from source code. This uses the Python Imaging Library to generate a pixmap from the source code.'),
+    'LatexFormatter': ('pygments.formatters.latex', 'LaTeX', ('latex', 'tex'), ('*.tex',), 'Format tokens as LaTeX code. This needs the `fancyvrb` and `color` standard packages.'),
+    'NullFormatter': ('pygments.formatters.other', 'Text only', ('text', 'null'), ('*.txt',), 'Output the text unchanged without any formatting.'),
+    'PangoMarkupFormatter': ('pygments.formatters.pangomarkup', 'Pango Markup', ('pango', 'pangomarkup'), (), 'Format tokens as Pango Markup code. It can then be rendered to an SVG.'),
+    'RawTokenFormatter': ('pygments.formatters.other', 'Raw tokens', ('raw', 'tokens'), ('*.raw',), 'Format tokens as a raw representation for storing token streams.'),
+    'RtfFormatter': ('pygments.formatters.rtf', 'RTF', ('rtf',), ('*.rtf',), 'Format tokens as RTF markup. This formatter automatically outputs full RTF documents with color information and other useful stuff. Perfect for Copy and Paste into Microsoft(R) Word(R) documents.'),
+    'SvgFormatter': ('pygments.formatters.svg', 'SVG', ('svg',), ('*.svg',), 'Format tokens as an SVG graphics file.  This formatter is still experimental. Each line of code is a ```` element with explicit ``x`` and ``y`` coordinates containing ```` elements with the individual token styles.'),
+    'Terminal256Formatter': ('pygments.formatters.terminal256', 'Terminal256', ('terminal256', 'console256', '256'), (), 'Format tokens with ANSI color sequences, for output in a 256-color terminal or console.  Like in `TerminalFormatter` color sequences are terminated at newlines, so that paging the output works correctly.'),
+    'TerminalFormatter': ('pygments.formatters.terminal', 'Terminal', ('terminal', 'console'), (), 'Format tokens with ANSI color sequences, for output in a text console. Color sequences are terminated at newlines, so that paging the output works correctly.'),
+    'TerminalTrueColorFormatter': ('pygments.formatters.terminal256', 'TerminalTrueColor', ('terminal16m', 'console16m', '16m'), (), 'Format tokens with ANSI color sequences, for output in a true-color terminal or console.  Like in `TerminalFormatter` color sequences are terminated at newlines, so that paging the output works correctly.'),
+    'TestcaseFormatter': ('pygments.formatters.other', 'Testcase', ('testcase',), (), 'Format tokens as appropriate for a new testcase.'),
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/bbcode.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/bbcode.py
new file mode 100644
index 0000000000000000000000000000000000000000..2be2b4e31292d8364b404f16ef4c654f9d89681a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/bbcode.py
@@ -0,0 +1,108 @@
+"""
+    pygments.formatters.bbcode
+    ~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+    BBcode formatter.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+
+from pip._vendor.pygments.formatter import Formatter
+from pip._vendor.pygments.util import get_bool_opt
+
+__all__ = ['BBCodeFormatter']
+
+
+class BBCodeFormatter(Formatter):
+    """
+    Format tokens with BBcodes. These formatting codes are used by many
+    bulletin boards, so you can highlight your sourcecode with pygments before
+    posting it there.
+
+    This formatter has no support for background colors and borders, as there
+    are no common BBcode tags for that.
+
+    Some board systems (e.g. phpBB) don't support colors in their [code] tag,
+    so you can't use the highlighting together with that tag.
+    Text in a [code] tag usually is shown with a monospace font (which this
+    formatter can do with the ``monofont`` option) and no spaces (which you
+    need for indentation) are removed.
+
+    Additional options accepted:
+
+    `style`
+        The style to use, can be a string or a Style subclass (default:
+        ``'default'``).
+
+    `codetag`
+        If set to true, put the output into ``[code]`` tags (default:
+        ``false``)
+
+    `monofont`
+        If set to true, add a tag to show the code with a monospace font
+        (default: ``false``).
+    """
+    name = 'BBCode'
+    aliases = ['bbcode', 'bb']
+    filenames = []
+
+    def __init__(self, **options):
+        Formatter.__init__(self, **options)
+        self._code = get_bool_opt(options, 'codetag', False)
+        self._mono = get_bool_opt(options, 'monofont', False)
+
+        self.styles = {}
+        self._make_styles()
+
+    def _make_styles(self):
+        for ttype, ndef in self.style:
+            start = end = ''
+            if ndef['color']:
+                start += '[color=#%s]' % ndef['color']
+                end = '[/color]' + end
+            if ndef['bold']:
+                start += '[b]'
+                end = '[/b]' + end
+            if ndef['italic']:
+                start += '[i]'
+                end = '[/i]' + end
+            if ndef['underline']:
+                start += '[u]'
+                end = '[/u]' + end
+            # there are no common BBcodes for background-color and border
+
+            self.styles[ttype] = start, end
+
+    def format_unencoded(self, tokensource, outfile):
+        if self._code:
+            outfile.write('[code]')
+        if self._mono:
+            outfile.write('[font=monospace]')
+
+        lastval = ''
+        lasttype = None
+
+        for ttype, value in tokensource:
+            while ttype not in self.styles:
+                ttype = ttype.parent
+            if ttype == lasttype:
+                lastval += value
+            else:
+                if lastval:
+                    start, end = self.styles[lasttype]
+                    outfile.write(''.join((start, lastval, end)))
+                lastval = value
+                lasttype = ttype
+
+        if lastval:
+            start, end = self.styles[lasttype]
+            outfile.write(''.join((start, lastval, end)))
+
+        if self._mono:
+            outfile.write('[/font]')
+        if self._code:
+            outfile.write('[/code]')
+        if self._code or self._mono:
+            outfile.write('\n')
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/groff.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/groff.py
new file mode 100644
index 0000000000000000000000000000000000000000..f3dcbce9b9fa2904fc361ef09139aeec3568685e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/groff.py
@@ -0,0 +1,170 @@
+"""
+    pygments.formatters.groff
+    ~~~~~~~~~~~~~~~~~~~~~~~~~
+
+    Formatter for groff output.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+import math
+from pip._vendor.pygments.formatter import Formatter
+from pip._vendor.pygments.util import get_bool_opt, get_int_opt
+
+__all__ = ['GroffFormatter']
+
+
+class GroffFormatter(Formatter):
+    """
+    Format tokens with groff escapes to change their color and font style.
+
+    .. versionadded:: 2.11
+
+    Additional options accepted:
+
+    `style`
+        The style to use, can be a string or a Style subclass (default:
+        ``'default'``).
+
+    `monospaced`
+        If set to true, monospace font will be used (default: ``true``).
+
+    `linenos`
+        If set to true, print the line numbers (default: ``false``).
+
+    `wrap`
+        Wrap lines to the specified number of characters. Disabled if set to 0
+        (default: ``0``).
+    """
+
+    name = 'groff'
+    aliases = ['groff','troff','roff']
+    filenames = []
+
+    def __init__(self, **options):
+        Formatter.__init__(self, **options)
+
+        self.monospaced = get_bool_opt(options, 'monospaced', True)
+        self.linenos = get_bool_opt(options, 'linenos', False)
+        self._lineno = 0
+        self.wrap = get_int_opt(options, 'wrap', 0)
+        self._linelen = 0
+
+        self.styles = {}
+        self._make_styles()
+
+
+    def _make_styles(self):
+        regular = '\\f[CR]' if self.monospaced else '\\f[R]'
+        bold = '\\f[CB]' if self.monospaced else '\\f[B]'
+        italic = '\\f[CI]' if self.monospaced else '\\f[I]'
+
+        for ttype, ndef in self.style:
+            start = end = ''
+            if ndef['color']:
+                start += '\\m[%s]' % ndef['color']
+                end = '\\m[]' + end
+            if ndef['bold']:
+                start += bold
+                end = regular + end
+            if ndef['italic']:
+                start += italic
+                end = regular + end
+            if ndef['bgcolor']:
+                start += '\\M[%s]' % ndef['bgcolor']
+                end = '\\M[]' + end
+
+            self.styles[ttype] = start, end
+
+
+    def _define_colors(self, outfile):
+        colors = set()
+        for _, ndef in self.style:
+            if ndef['color'] is not None:
+                colors.add(ndef['color'])
+
+        for color in colors:
+            outfile.write('.defcolor ' + color + ' rgb #' + color + '\n')
+
+
+    def _write_lineno(self, outfile):
+        self._lineno += 1
+        outfile.write("%s% 4d " % (self._lineno != 1 and '\n' or '', self._lineno))
+
+
+    def _wrap_line(self, line):
+        length = len(line.rstrip('\n'))
+        space = '     ' if self.linenos else ''
+        newline = ''
+
+        if length > self.wrap:
+            for i in range(0, math.floor(length / self.wrap)):
+                chunk = line[i*self.wrap:i*self.wrap+self.wrap]
+                newline += (chunk + '\n' + space)
+            remainder = length % self.wrap
+            if remainder > 0:
+                newline += line[-remainder-1:]
+                self._linelen = remainder
+        elif self._linelen + length > self.wrap:
+            newline = ('\n' + space) + line
+            self._linelen = length
+        else:
+            newline = line
+            self._linelen += length
+
+        return newline
+
+
+    def _escape_chars(self, text):
+        text = text.replace('\\', '\\[u005C]'). \
+                    replace('.', '\\[char46]'). \
+                    replace('\'', '\\[u0027]'). \
+                    replace('`', '\\[u0060]'). \
+                    replace('~', '\\[u007E]')
+        copy = text
+
+        for char in copy:
+            if len(char) != len(char.encode()):
+                uni = char.encode('unicode_escape') \
+                    .decode()[1:] \
+                    .replace('x', 'u00') \
+                    .upper()
+                text = text.replace(char, '\\[u' + uni[1:] + ']')
+
+        return text
+
+
+    def format_unencoded(self, tokensource, outfile):
+        self._define_colors(outfile)
+
+        outfile.write('.nf\n\\f[CR]\n')
+
+        if self.linenos:
+            self._write_lineno(outfile)
+
+        for ttype, value in tokensource:
+            while ttype not in self.styles:
+                ttype = ttype.parent
+            start, end = self.styles[ttype]
+
+            for line in value.splitlines(True):
+                if self.wrap > 0:
+                    line = self._wrap_line(line)
+
+                if start and end:
+                    text = self._escape_chars(line.rstrip('\n'))
+                    if text != '':
+                        outfile.write(''.join((start, text, end)))
+                else:
+                    outfile.write(self._escape_chars(line.rstrip('\n')))
+
+                if line.endswith('\n'):
+                    if self.linenos:
+                        self._write_lineno(outfile)
+                        self._linelen = 0
+                    else:
+                        outfile.write('\n')
+                        self._linelen = 0
+
+        outfile.write('\n.fi')
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/html.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/html.py
new file mode 100644
index 0000000000000000000000000000000000000000..d5cda4c4bc33d46e83c0f404efdb51e647202a1d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pygments/formatters/html.py
@@ -0,0 +1,989 @@
+"""
+    pygments.formatters.html
+    ~~~~~~~~~~~~~~~~~~~~~~~~
+
+    Formatter for HTML output.
+
+    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
+    :license: BSD, see LICENSE for details.
+"""
+
+import functools
+import os
+import sys
+import os.path
+from io import StringIO
+
+from pip._vendor.pygments.formatter import Formatter
+from pip._vendor.pygments.token import Token, Text, STANDARD_TYPES
+from pip._vendor.pygments.util import get_bool_opt, get_int_opt, get_list_opt
+
+try:
+    import ctags
+except ImportError:
+    ctags = None
+
+__all__ = ['HtmlFormatter']
+
+
+_escape_html_table = {
+    ord('&'): '&',
+    ord('<'): '<',
+    ord('>'): '>',
+    ord('"'): '"',
+    ord("'"): ''',
+}
+
+
+def escape_html(text, table=_escape_html_table):
+    """Escape &, <, > as well as single and double quotes for HTML."""
+    return text.translate(table)
+
+
+def webify(color):
+    if color.startswith('calc') or color.startswith('var'):
+        return color
+    else:
+        return '#' + color
+
+
+def _get_ttype_class(ttype):
+    fname = STANDARD_TYPES.get(ttype)
+    if fname:
+        return fname
+    aname = ''
+    while fname is None:
+        aname = '-' + ttype[-1] + aname
+        ttype = ttype.parent
+        fname = STANDARD_TYPES.get(ttype)
+    return fname + aname
+
+
+CSSFILE_TEMPLATE = '''\
+/*
+generated by Pygments 
+Copyright 2006-2022 by the Pygments team.
+Licensed under the BSD license, see LICENSE for details.
+*/
+%(styledefs)s
+'''
+
+DOC_HEADER = '''\
+
+
+
+
+  %(title)s
+  
+  
+
+
+
%(title)s

+
+'''
+
+DOC_HEADER_EXTERNALCSS = '''\
+
+
+
+
+  %(title)s
+  
+  
+
+
+
%(title)s

+
+'''
+
+DOC_FOOTER = '''\
+
+
+'''
+
+
+class HtmlFormatter(Formatter):
+    r"""
+    Format tokens as HTML 4 ```` tags within a ``
`` tag, wrapped
+    in a ``
`` tag. The ``
``'s CSS class can be set by the `cssclass`
+    option.
+
+    If the `linenos` option is set to ``"table"``, the ``
`` is
+    additionally wrapped inside a ```` which has one row and two
+    cells: one containing the line numbers and one containing the code.
+    Example:
+
+    .. sourcecode:: html
+
+        

+        

+          
+          
+        

+            
1
+            2

+          		
+            
def foo(bar):
+              pass
+            

+          

+
+    (whitespace added to improve clarity).
+
+    Wrapping can be disabled using the `nowrap` option.
+
+    A list of lines can be specified using the `hl_lines` option to make these
+    lines highlighted (as of Pygments 0.11).
+
+    With the `full` option, a complete HTML 4 document is output, including
+    the style definitions inside a ``
+    {% else %}
+        {{ head | safe }}
+    {% endif %}
+
+
+{{ body | safe }}
+{% for diagram in diagrams %}
+    

+        
{{ diagram.title }}

+        
{{ diagram.text }}

+        

+            {{ diagram.svg }}
+        

+    

+{% endfor %}
+
+
+"""
+
+template = Template(jinja2_template_source)
+
+# Note: ideally this would be a dataclass, but we're supporting Python 3.5+ so we can't do this yet
+NamedDiagram = NamedTuple(
+    "NamedDiagram",
+    [("name", str), ("diagram", typing.Optional[railroad.DiagramItem]), ("index", int)],
+)
+"""
+A simple structure for associating a name with a railroad diagram
+"""
+
+T = TypeVar("T")
+
+
+class EachItem(railroad.Group):
+    """
+    Custom railroad item to compose a:
+    - Group containing a
+      - OneOrMore containing a
+        - Choice of the elements in the Each
+    with the group label indicating that all must be matched
+    """
+
+    all_label = "[ALL]"
+
+    def __init__(self, *items):
+        choice_item = railroad.Choice(len(items) - 1, *items)
+        one_or_more_item = railroad.OneOrMore(item=choice_item)
+        super().__init__(one_or_more_item, label=self.all_label)
+
+
+class AnnotatedItem(railroad.Group):
+    """
+    Simple subclass of Group that creates an annotation label
+    """
+
+    def __init__(self, label: str, item):
+        super().__init__(item=item, label="[{}]".format(label) if label else label)
+
+
+class EditablePartial(Generic[T]):
+    """
+    Acts like a functools.partial, but can be edited. In other words, it represents a type that hasn't yet been
+    constructed.
+    """
+
+    # We need this here because the railroad constructors actually transform the data, so can't be called until the
+    # entire tree is assembled
+
+    def __init__(self, func: Callable[..., T], args: list, kwargs: dict):
+        self.func = func
+        self.args = args
+        self.kwargs = kwargs
+
+    @classmethod
+    def from_call(cls, func: Callable[..., T], *args, **kwargs) -> "EditablePartial[T]":
+        """
+        If you call this function in the same way that you would call the constructor, it will store the arguments
+        as you expect. For example EditablePartial.from_call(Fraction, 1, 3)() == Fraction(1, 3)
+        """
+        return EditablePartial(func=func, args=list(args), kwargs=kwargs)
+
+    @property
+    def name(self):
+        return self.kwargs["name"]
+
+    def __call__(self) -> T:
+        """
+        Evaluate the partial and return the result
+        """
+        args = self.args.copy()
+        kwargs = self.kwargs.copy()
+
+        # This is a helpful hack to allow you to specify varargs parameters (e.g. *args) as keyword args (e.g.
+        # args=['list', 'of', 'things'])
+        arg_spec = inspect.getfullargspec(self.func)
+        if arg_spec.varargs in self.kwargs:
+            args += kwargs.pop(arg_spec.varargs)
+
+        return self.func(*args, **kwargs)
+
+
+def railroad_to_html(diagrams: List[NamedDiagram], **kwargs) -> str:
+    """
+    Given a list of NamedDiagram, produce a single HTML string that visualises those diagrams
+    :params kwargs: kwargs to be passed in to the template
+    """
+    data = []
+    for diagram in diagrams:
+        if diagram.diagram is None:
+            continue
+        io = StringIO()
+        diagram.diagram.writeSvg(io.write)
+        title = diagram.name
+        if diagram.index == 0:
+            title += " (root)"
+        data.append({"title": title, "text": "", "svg": io.getvalue()})
+
+    return template.render(diagrams=data, **kwargs)
+
+
+def resolve_partial(partial: "EditablePartial[T]") -> T:
+    """
+    Recursively resolves a collection of Partials into whatever type they are
+    """
+    if isinstance(partial, EditablePartial):
+        partial.args = resolve_partial(partial.args)
+        partial.kwargs = resolve_partial(partial.kwargs)
+        return partial()
+    elif isinstance(partial, list):
+        return [resolve_partial(x) for x in partial]
+    elif isinstance(partial, dict):
+        return {key: resolve_partial(x) for key, x in partial.items()}
+    else:
+        return partial
+
+
+def to_railroad(
+    element: pyparsing.ParserElement,
+    diagram_kwargs: typing.Optional[dict] = None,
+    vertical: int = 3,
+    show_results_names: bool = False,
+    show_groups: bool = False,
+) -> List[NamedDiagram]:
+    """
+    Convert a pyparsing element tree into a list of diagrams. This is the recommended entrypoint to diagram
+    creation if you want to access the Railroad tree before it is converted to HTML
+    :param element: base element of the parser being diagrammed
+    :param diagram_kwargs: kwargs to pass to the Diagram() constructor
+    :param vertical: (optional) - int - limit at which number of alternatives should be
+       shown vertically instead of horizontally
+    :param show_results_names - bool to indicate whether results name annotations should be
+       included in the diagram
+    :param show_groups - bool to indicate whether groups should be highlighted with an unlabeled
+       surrounding box
+    """
+    # Convert the whole tree underneath the root
+    lookup = ConverterState(diagram_kwargs=diagram_kwargs or {})
+    _to_diagram_element(
+        element,
+        lookup=lookup,
+        parent=None,
+        vertical=vertical,
+        show_results_names=show_results_names,
+        show_groups=show_groups,
+    )
+
+    root_id = id(element)
+    # Convert the root if it hasn't been already
+    if root_id in lookup:
+        if not element.customName:
+            lookup[root_id].name = ""
+        lookup[root_id].mark_for_extraction(root_id, lookup, force=True)
+
+    # Now that we're finished, we can convert from intermediate structures into Railroad elements
+    diags = list(lookup.diagrams.values())
+    if len(diags) > 1:
+        # collapse out duplicate diags with the same name
+        seen = set()
+        deduped_diags = []
+        for d in diags:
+            # don't extract SkipTo elements, they are uninformative as subdiagrams
+            if d.name == "...":
+                continue
+            if d.name is not None and d.name not in seen:
+                seen.add(d.name)
+                deduped_diags.append(d)
+        resolved = [resolve_partial(partial) for partial in deduped_diags]
+    else:
+        # special case - if just one diagram, always display it, even if
+        # it has no name
+        resolved = [resolve_partial(partial) for partial in diags]
+    return sorted(resolved, key=lambda diag: diag.index)
+
+
+def _should_vertical(
+    specification: int, exprs: Iterable[pyparsing.ParserElement]
+) -> bool:
+    """
+    Returns true if we should return a vertical list of elements
+    """
+    if specification is None:
+        return False
+    else:
+        return len(_visible_exprs(exprs)) >= specification
+
+
+class ElementState:
+    """
+    State recorded for an individual pyparsing Element
+    """
+
+    # Note: this should be a dataclass, but we have to support Python 3.5
+    def __init__(
+        self,
+        element: pyparsing.ParserElement,
+        converted: EditablePartial,
+        parent: EditablePartial,
+        number: int,
+        name: str = None,
+        parent_index: typing.Optional[int] = None,
+    ):
+        #: The pyparsing element that this represents
+        self.element: pyparsing.ParserElement = element
+        #: The name of the element
+        self.name: typing.Optional[str] = name
+        #: The output Railroad element in an unconverted state
+        self.converted: EditablePartial = converted
+        #: The parent Railroad element, which we store so that we can extract this if it's duplicated
+        self.parent: EditablePartial = parent
+        #: The order in which we found this element, used for sorting diagrams if this is extracted into a diagram
+        self.number: int = number
+        #: The index of this inside its parent
+        self.parent_index: typing.Optional[int] = parent_index
+        #: If true, we should extract this out into a subdiagram
+        self.extract: bool = False
+        #: If true, all of this element's children have been filled out
+        self.complete: bool = False
+
+    def mark_for_extraction(
+        self, el_id: int, state: "ConverterState", name: str = None, force: bool = False
+    ):
+        """
+        Called when this instance has been seen twice, and thus should eventually be extracted into a sub-diagram
+        :param el_id: id of the element
+        :param state: element/diagram state tracker
+        :param name: name to use for this element's text
+        :param force: If true, force extraction now, regardless of the state of this. Only useful for extracting the
+        root element when we know we're finished
+        """
+        self.extract = True
+
+        # Set the name
+        if not self.name:
+            if name:
+                # Allow forcing a custom name
+                self.name = name
+            elif self.element.customName:
+                self.name = self.element.customName
+            else:
+                self.name = ""
+
+        # Just because this is marked for extraction doesn't mean we can do it yet. We may have to wait for children
+        # to be added
+        # Also, if this is just a string literal etc, don't bother extracting it
+        if force or (self.complete and _worth_extracting(self.element)):
+            state.extract_into_diagram(el_id)
+
+
+class ConverterState:
+    """
+    Stores some state that persists between recursions into the element tree
+    """
+
+    def __init__(self, diagram_kwargs: typing.Optional[dict] = None):
+        #: A dictionary mapping ParserElements to state relating to them
+        self._element_diagram_states: Dict[int, ElementState] = {}
+        #: A dictionary mapping ParserElement IDs to subdiagrams generated from them
+        self.diagrams: Dict[int, EditablePartial[NamedDiagram]] = {}
+        #: The index of the next unnamed element
+        self.unnamed_index: int = 1
+        #: The index of the next element. This is used for sorting
+        self.index: int = 0
+        #: Shared kwargs that are used to customize the construction of diagrams
+        self.diagram_kwargs: dict = diagram_kwargs or {}
+        self.extracted_diagram_names: Set[str] = set()
+
+    def __setitem__(self, key: int, value: ElementState):
+        self._element_diagram_states[key] = value
+
+    def __getitem__(self, key: int) -> ElementState:
+        return self._element_diagram_states[key]
+
+    def __delitem__(self, key: int):
+        del self._element_diagram_states[key]
+
+    def __contains__(self, key: int):
+        return key in self._element_diagram_states
+
+    def generate_unnamed(self) -> int:
+        """
+        Generate a number used in the name of an otherwise unnamed diagram
+        """
+        self.unnamed_index += 1
+        return self.unnamed_index
+
+    def generate_index(self) -> int:
+        """
+        Generate a number used to index a diagram
+        """
+        self.index += 1
+        return self.index
+
+    def extract_into_diagram(self, el_id: int):
+        """
+        Used when we encounter the same token twice in the same tree. When this
+        happens, we replace all instances of that token with a terminal, and
+        create a new subdiagram for the token
+        """
+        position = self[el_id]
+
+        # Replace the original definition of this element with a regular block
+        if position.parent:
+            ret = EditablePartial.from_call(railroad.NonTerminal, text=position.name)
+            if "item" in position.parent.kwargs:
+                position.parent.kwargs["item"] = ret
+            elif "items" in position.parent.kwargs:
+                position.parent.kwargs["items"][position.parent_index] = ret
+
+        # If the element we're extracting is a group, skip to its content but keep the title
+        if position.converted.func == railroad.Group:
+            content = position.converted.kwargs["item"]
+        else:
+            content = position.converted
+
+        self.diagrams[el_id] = EditablePartial.from_call(
+            NamedDiagram,
+            name=position.name,
+            diagram=EditablePartial.from_call(
+                railroad.Diagram, content, **self.diagram_kwargs
+            ),
+            index=position.number,
+        )
+
+        del self[el_id]
+
+
+def _worth_extracting(element: pyparsing.ParserElement) -> bool:
+    """
+    Returns true if this element is worth having its own sub-diagram. Simply, if any of its children
+    themselves have children, then its complex enough to extract
+    """
+    children = element.recurse()
+    return any(child.recurse() for child in children)
+
+
+def _apply_diagram_item_enhancements(fn):
+    """
+    decorator to ensure enhancements to a diagram item (such as results name annotations)
+    get applied on return from _to_diagram_element (we do this since there are several
+    returns in _to_diagram_element)
+    """
+
+    def _inner(
+        element: pyparsing.ParserElement,
+        parent: typing.Optional[EditablePartial],
+        lookup: ConverterState = None,
+        vertical: int = None,
+        index: int = 0,
+        name_hint: str = None,
+        show_results_names: bool = False,
+        show_groups: bool = False,
+    ) -> typing.Optional[EditablePartial]:
+
+        ret = fn(
+            element,
+            parent,
+            lookup,
+            vertical,
+            index,
+            name_hint,
+            show_results_names,
+            show_groups,
+        )
+
+        # apply annotation for results name, if present
+        if show_results_names and ret is not None:
+            element_results_name = element.resultsName
+            if element_results_name:
+                # add "*" to indicate if this is a "list all results" name
+                element_results_name += "" if element.modalResults else "*"
+                ret = EditablePartial.from_call(
+                    railroad.Group, item=ret, label=element_results_name
+                )
+
+        return ret
+
+    return _inner
+
+
+def _visible_exprs(exprs: Iterable[pyparsing.ParserElement]):
+    non_diagramming_exprs = (
+        pyparsing.ParseElementEnhance,
+        pyparsing.PositionToken,
+        pyparsing.And._ErrorStop,
+    )
+    return [
+        e
+        for e in exprs
+        if not (e.customName or e.resultsName or isinstance(e, non_diagramming_exprs))
+    ]
+
+
+@_apply_diagram_item_enhancements
+def _to_diagram_element(
+    element: pyparsing.ParserElement,
+    parent: typing.Optional[EditablePartial],
+    lookup: ConverterState = None,
+    vertical: int = None,
+    index: int = 0,
+    name_hint: str = None,
+    show_results_names: bool = False,
+    show_groups: bool = False,
+) -> typing.Optional[EditablePartial]:
+    """
+    Recursively converts a PyParsing Element to a railroad Element
+    :param lookup: The shared converter state that keeps track of useful things
+    :param index: The index of this element within the parent
+    :param parent: The parent of this element in the output tree
+    :param vertical: Controls at what point we make a list of elements vertical. If this is an integer (the default),
+    it sets the threshold of the number of items before we go vertical. If True, always go vertical, if False, never
+    do so
+    :param name_hint: If provided, this will override the generated name
+    :param show_results_names: bool flag indicating whether to add annotations for results names
+    :returns: The converted version of the input element, but as a Partial that hasn't yet been constructed
+    :param show_groups: bool flag indicating whether to show groups using bounding box
+    """
+    exprs = element.recurse()
+    name = name_hint or element.customName or element.__class__.__name__
+
+    # Python's id() is used to provide a unique identifier for elements
+    el_id = id(element)
+
+    element_results_name = element.resultsName
+
+    # Here we basically bypass processing certain wrapper elements if they contribute nothing to the diagram
+    if not element.customName:
+        if isinstance(
+            element,
+            (
+                # pyparsing.TokenConverter,
+                # pyparsing.Forward,
+                pyparsing.Located,
+            ),
+        ):
+            # However, if this element has a useful custom name, and its child does not, we can pass it on to the child
+            if exprs:
+                if not exprs[0].customName:
+                    propagated_name = name
+                else:
+                    propagated_name = None
+
+                return _to_diagram_element(
+                    element.expr,
+                    parent=parent,
+                    lookup=lookup,
+                    vertical=vertical,
+                    index=index,
+                    name_hint=propagated_name,
+                    show_results_names=show_results_names,
+                    show_groups=show_groups,
+                )
+
+    # If the element isn't worth extracting, we always treat it as the first time we say it
+    if _worth_extracting(element):
+        if el_id in lookup:
+            # If we've seen this element exactly once before, we are only just now finding out that it's a duplicate,
+            # so we have to extract it into a new diagram.
+            looked_up = lookup[el_id]
+            looked_up.mark_for_extraction(el_id, lookup, name=name_hint)
+            ret = EditablePartial.from_call(railroad.NonTerminal, text=looked_up.name)
+            return ret
+
+        elif el_id in lookup.diagrams:
+            # If we have seen the element at least twice before, and have already extracted it into a subdiagram, we
+            # just put in a marker element that refers to the sub-diagram
+            ret = EditablePartial.from_call(
+                railroad.NonTerminal, text=lookup.diagrams[el_id].kwargs["name"]
+            )
+            return ret
+
+    # Recursively convert child elements
+    # Here we find the most relevant Railroad element for matching pyparsing Element
+    # We use ``items=[]`` here to hold the place for where the child elements will go once created
+    if isinstance(element, pyparsing.And):
+        # detect And's created with ``expr*N`` notation - for these use a OneOrMore with a repeat
+        # (all will have the same name, and resultsName)
+        if not exprs:
+            return None
+        if len(set((e.name, e.resultsName) for e in exprs)) == 1:
+            ret = EditablePartial.from_call(
+                railroad.OneOrMore, item="", repeat=str(len(exprs))
+            )
+        elif _should_vertical(vertical, exprs):
+            ret = EditablePartial.from_call(railroad.Stack, items=[])
+        else:
+            ret = EditablePartial.from_call(railroad.Sequence, items=[])
+    elif isinstance(element, (pyparsing.Or, pyparsing.MatchFirst)):
+        if not exprs:
+            return None
+        if _should_vertical(vertical, exprs):
+            ret = EditablePartial.from_call(railroad.Choice, 0, items=[])
+        else:
+            ret = EditablePartial.from_call(railroad.HorizontalChoice, items=[])
+    elif isinstance(element, pyparsing.Each):
+        if not exprs:
+            return None
+        ret = EditablePartial.from_call(EachItem, items=[])
+    elif isinstance(element, pyparsing.NotAny):
+        ret = EditablePartial.from_call(AnnotatedItem, label="NOT", item="")
+    elif isinstance(element, pyparsing.FollowedBy):
+        ret = EditablePartial.from_call(AnnotatedItem, label="LOOKAHEAD", item="")
+    elif isinstance(element, pyparsing.PrecededBy):
+        ret = EditablePartial.from_call(AnnotatedItem, label="LOOKBEHIND", item="")
+    elif isinstance(element, pyparsing.Group):
+        if show_groups:
+            ret = EditablePartial.from_call(AnnotatedItem, label="", item="")
+        else:
+            ret = EditablePartial.from_call(railroad.Group, label="", item="")
+    elif isinstance(element, pyparsing.TokenConverter):
+        ret = EditablePartial.from_call(
+            AnnotatedItem, label=type(element).__name__.lower(), item=""
+        )
+    elif isinstance(element, pyparsing.Opt):
+        ret = EditablePartial.from_call(railroad.Optional, item="")
+    elif isinstance(element, pyparsing.OneOrMore):
+        ret = EditablePartial.from_call(railroad.OneOrMore, item="")
+    elif isinstance(element, pyparsing.ZeroOrMore):
+        ret = EditablePartial.from_call(railroad.ZeroOrMore, item="")
+    elif isinstance(element, pyparsing.Group):
+        ret = EditablePartial.from_call(
+            railroad.Group, item=None, label=element_results_name
+        )
+    elif isinstance(element, pyparsing.Empty) and not element.customName:
+        # Skip unnamed "Empty" elements
+        ret = None
+    elif len(exprs) > 1:
+        ret = EditablePartial.from_call(railroad.Sequence, items=[])
+    elif len(exprs) > 0 and not element_results_name:
+        ret = EditablePartial.from_call(railroad.Group, item="", label=name)
+    else:
+        terminal = EditablePartial.from_call(railroad.Terminal, element.defaultName)
+        ret = terminal
+
+    if ret is None:
+        return
+
+    # Indicate this element's position in the tree so we can extract it if necessary
+    lookup[el_id] = ElementState(
+        element=element,
+        converted=ret,
+        parent=parent,
+        parent_index=index,
+        number=lookup.generate_index(),
+    )
+    if element.customName:
+        lookup[el_id].mark_for_extraction(el_id, lookup, element.customName)
+
+    i = 0
+    for expr in exprs:
+        # Add a placeholder index in case we have to extract the child before we even add it to the parent
+        if "items" in ret.kwargs:
+            ret.kwargs["items"].insert(i, None)
+
+        item = _to_diagram_element(
+            expr,
+            parent=ret,
+            lookup=lookup,
+            vertical=vertical,
+            index=i,
+            show_results_names=show_results_names,
+            show_groups=show_groups,
+        )
+
+        # Some elements don't need to be shown in the diagram
+        if item is not None:
+            if "item" in ret.kwargs:
+                ret.kwargs["item"] = item
+            elif "items" in ret.kwargs:
+                # If we've already extracted the child, don't touch this index, since it's occupied by a nonterminal
+                ret.kwargs["items"][i] = item
+                i += 1
+        elif "items" in ret.kwargs:
+            # If we're supposed to skip this element, remove it from the parent
+            del ret.kwargs["items"][i]
+
+    # If all this items children are none, skip this item
+    if ret and (
+        ("items" in ret.kwargs and len(ret.kwargs["items"]) == 0)
+        or ("item" in ret.kwargs and ret.kwargs["item"] is None)
+    ):
+        ret = EditablePartial.from_call(railroad.Terminal, name)
+
+    # Mark this element as "complete", ie it has all of its children
+    if el_id in lookup:
+        lookup[el_id].complete = True
+
+    if el_id in lookup and lookup[el_id].extract and lookup[el_id].complete:
+        lookup.extract_into_diagram(el_id)
+        if ret is not None:
+            ret = EditablePartial.from_call(
+                railroad.NonTerminal, text=lookup.diagrams[el_id].kwargs["name"]
+            )
+
+    return ret
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/exceptions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/exceptions.py
new file mode 100644
index 0000000000000000000000000000000000000000..a38447bb05bd5d503a32651d6046ff8667785c0c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/exceptions.py
@@ -0,0 +1,267 @@
+# exceptions.py
+
+import re
+import sys
+import typing
+
+from .util import col, line, lineno, _collapse_string_to_ranges
+from .unicode import pyparsing_unicode as ppu
+
+
+class ExceptionWordUnicode(ppu.Latin1, ppu.LatinA, ppu.LatinB, ppu.Greek, ppu.Cyrillic):
+    pass
+
+
+_extract_alphanums = _collapse_string_to_ranges(ExceptionWordUnicode.alphanums)
+_exception_word_extractor = re.compile("([" + _extract_alphanums + "]{1,16})|.")
+
+
+class ParseBaseException(Exception):
+    """base exception class for all parsing runtime exceptions"""
+
+    # Performance tuning: we construct a *lot* of these, so keep this
+    # constructor as small and fast as possible
+    def __init__(
+        self,
+        pstr: str,
+        loc: int = 0,
+        msg: typing.Optional[str] = None,
+        elem=None,
+    ):
+        self.loc = loc
+        if msg is None:
+            self.msg = pstr
+            self.pstr = ""
+        else:
+            self.msg = msg
+            self.pstr = pstr
+        self.parser_element = self.parserElement = elem
+        self.args = (pstr, loc, msg)
+
+    @staticmethod
+    def explain_exception(exc, depth=16):
+        """
+        Method to take an exception and translate the Python internal traceback into a list
+        of the pyparsing expressions that caused the exception to be raised.
+
+        Parameters:
+
+        - exc - exception raised during parsing (need not be a ParseException, in support
+          of Python exceptions that might be raised in a parse action)
+        - depth (default=16) - number of levels back in the stack trace to list expression
+          and function names; if None, the full stack trace names will be listed; if 0, only
+          the failing input line, marker, and exception string will be shown
+
+        Returns a multi-line string listing the ParserElements and/or function names in the
+        exception's stack trace.
+        """
+        import inspect
+        from .core import ParserElement
+
+        if depth is None:
+            depth = sys.getrecursionlimit()
+        ret = []
+        if isinstance(exc, ParseBaseException):
+            ret.append(exc.line)
+            ret.append(" " * (exc.column - 1) + "^")
+        ret.append("{}: {}".format(type(exc).__name__, exc))
+
+        if depth > 0:
+            callers = inspect.getinnerframes(exc.__traceback__, context=depth)
+            seen = set()
+            for i, ff in enumerate(callers[-depth:]):
+                frm = ff[0]
+
+                f_self = frm.f_locals.get("self", None)
+                if isinstance(f_self, ParserElement):
+                    if frm.f_code.co_name not in ("parseImpl", "_parseNoCache"):
+                        continue
+                    if id(f_self) in seen:
+                        continue
+                    seen.add(id(f_self))
+
+                    self_type = type(f_self)
+                    ret.append(
+                        "{}.{} - {}".format(
+                            self_type.__module__, self_type.__name__, f_self
+                        )
+                    )
+
+                elif f_self is not None:
+                    self_type = type(f_self)
+                    ret.append("{}.{}".format(self_type.__module__, self_type.__name__))
+
+                else:
+                    code = frm.f_code
+                    if code.co_name in ("wrapper", ""):
+                        continue
+
+                    ret.append("{}".format(code.co_name))
+
+                depth -= 1
+                if not depth:
+                    break
+
+        return "\n".join(ret)
+
+    @classmethod
+    def _from_exception(cls, pe):
+        """
+        internal factory method to simplify creating one type of ParseException
+        from another - avoids having __init__ signature conflicts among subclasses
+        """
+        return cls(pe.pstr, pe.loc, pe.msg, pe.parserElement)
+
+    @property
+    def line(self) -> str:
+        """
+        Return the line of text where the exception occurred.
+        """
+        return line(self.loc, self.pstr)
+
+    @property
+    def lineno(self) -> int:
+        """
+        Return the 1-based line number of text where the exception occurred.
+        """
+        return lineno(self.loc, self.pstr)
+
+    @property
+    def col(self) -> int:
+        """
+        Return the 1-based column on the line of text where the exception occurred.
+        """
+        return col(self.loc, self.pstr)
+
+    @property
+    def column(self) -> int:
+        """
+        Return the 1-based column on the line of text where the exception occurred.
+        """
+        return col(self.loc, self.pstr)
+
+    def __str__(self) -> str:
+        if self.pstr:
+            if self.loc >= len(self.pstr):
+                foundstr = ", found end of text"
+            else:
+                # pull out next word at error location
+                found_match = _exception_word_extractor.match(self.pstr, self.loc)
+                if found_match is not None:
+                    found = found_match.group(0)
+                else:
+                    found = self.pstr[self.loc : self.loc + 1]
+                foundstr = (", found %r" % found).replace(r"\\", "\\")
+        else:
+            foundstr = ""
+        return "{}{}  (at char {}), (line:{}, col:{})".format(
+            self.msg, foundstr, self.loc, self.lineno, self.column
+        )
+
+    def __repr__(self):
+        return str(self)
+
+    def mark_input_line(self, marker_string: str = None, *, markerString=">!<") -> str:
+        """
+        Extracts the exception line from the input string, and marks
+        the location of the exception with a special symbol.
+        """
+        markerString = marker_string if marker_string is not None else markerString
+        line_str = self.line
+        line_column = self.column - 1
+        if markerString:
+            line_str = "".join(
+                (line_str[:line_column], markerString, line_str[line_column:])
+            )
+        return line_str.strip()
+
+    def explain(self, depth=16) -> str:
+        """
+        Method to translate the Python internal traceback into a list
+        of the pyparsing expressions that caused the exception to be raised.
+
+        Parameters:
+
+        - depth (default=16) - number of levels back in the stack trace to list expression
+          and function names; if None, the full stack trace names will be listed; if 0, only
+          the failing input line, marker, and exception string will be shown
+
+        Returns a multi-line string listing the ParserElements and/or function names in the
+        exception's stack trace.
+
+        Example::
+
+            expr = pp.Word(pp.nums) * 3
+            try:
+                expr.parse_string("123 456 A789")
+            except pp.ParseException as pe:
+                print(pe.explain(depth=0))
+
+        prints::
+
+            123 456 A789
+                    ^
+            ParseException: Expected W:(0-9), found 'A'  (at char 8), (line:1, col:9)
+
+        Note: the diagnostic output will include string representations of the expressions
+        that failed to parse. These representations will be more helpful if you use `set_name` to
+        give identifiable names to your expressions. Otherwise they will use the default string
+        forms, which may be cryptic to read.
+
+        Note: pyparsing's default truncation of exception tracebacks may also truncate the
+        stack of expressions that are displayed in the ``explain`` output. To get the full listing
+        of parser expressions, you may have to set ``ParserElement.verbose_stacktrace = True``
+        """
+        return self.explain_exception(self, depth)
+
+    markInputline = mark_input_line
+
+
+class ParseException(ParseBaseException):
+    """
+    Exception thrown when a parse expression doesn't match the input string
+
+    Example::
+
+        try:
+            Word(nums).set_name("integer").parse_string("ABC")
+        except ParseException as pe:
+            print(pe)
+            print("column: {}".format(pe.column))
+
+    prints::
+
+       Expected integer (at char 0), (line:1, col:1)
+        column: 1
+
+    """
+
+
+class ParseFatalException(ParseBaseException):
+    """
+    User-throwable exception thrown when inconsistent parse content
+    is found; stops all parsing immediately
+    """
+
+
+class ParseSyntaxException(ParseFatalException):
+    """
+    Just like :class:`ParseFatalException`, but thrown internally
+    when an :class:`ErrorStop` ('-' operator) indicates
+    that parsing is to stop immediately because an unbacktrackable
+    syntax error has been found.
+    """
+
+
+class RecursiveGrammarException(Exception):
+    """
+    Exception thrown by :class:`ParserElement.validate` if the
+    grammar could be left-recursive; parser may need to enable
+    left recursion using :class:`ParserElement.enable_left_recursion`
+    """
+
+    def __init__(self, parseElementList):
+        self.parseElementTrace = parseElementList
+
+    def __str__(self) -> str:
+        return "RecursiveGrammarException: {}".format(self.parseElementTrace)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/helpers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..9588b3b780159a2a2d23c7f84a4404ec350e2b65
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/helpers.py
@@ -0,0 +1,1088 @@
+# helpers.py
+import html.entities
+import re
+import typing
+
+from . import __diag__
+from .core import *
+from .util import _bslash, _flatten, _escape_regex_range_chars
+
+
+#
+# global helpers
+#
+def delimited_list(
+    expr: Union[str, ParserElement],
+    delim: Union[str, ParserElement] = ",",
+    combine: bool = False,
+    min: typing.Optional[int] = None,
+    max: typing.Optional[int] = None,
+    *,
+    allow_trailing_delim: bool = False,
+) -> ParserElement:
+    """Helper to define a delimited list of expressions - the delimiter
+    defaults to ','. By default, the list elements and delimiters can
+    have intervening whitespace, and comments, but this can be
+    overridden by passing ``combine=True`` in the constructor. If
+    ``combine`` is set to ``True``, the matching tokens are
+    returned as a single token string, with the delimiters included;
+    otherwise, the matching tokens are returned as a list of tokens,
+    with the delimiters suppressed.
+
+    If ``allow_trailing_delim`` is set to True, then the list may end with
+    a delimiter.
+
+    Example::
+
+        delimited_list(Word(alphas)).parse_string("aa,bb,cc") # -> ['aa', 'bb', 'cc']
+        delimited_list(Word(hexnums), delim=':', combine=True).parse_string("AA:BB:CC:DD:EE") # -> ['AA:BB:CC:DD:EE']
+    """
+    if isinstance(expr, str_type):
+        expr = ParserElement._literalStringClass(expr)
+
+    dlName = "{expr} [{delim} {expr}]...{end}".format(
+        expr=str(expr.copy().streamline()),
+        delim=str(delim),
+        end=" [{}]".format(str(delim)) if allow_trailing_delim else "",
+    )
+
+    if not combine:
+        delim = Suppress(delim)
+
+    if min is not None:
+        if min < 1:
+            raise ValueError("min must be greater than 0")
+        min -= 1
+    if max is not None:
+        if min is not None and max <= min:
+            raise ValueError("max must be greater than, or equal to min")
+        max -= 1
+    delimited_list_expr = expr + (delim + expr)[min, max]
+
+    if allow_trailing_delim:
+        delimited_list_expr += Opt(delim)
+
+    if combine:
+        return Combine(delimited_list_expr).set_name(dlName)
+    else:
+        return delimited_list_expr.set_name(dlName)
+
+
+def counted_array(
+    expr: ParserElement,
+    int_expr: typing.Optional[ParserElement] = None,
+    *,
+    intExpr: typing.Optional[ParserElement] = None,
+) -> ParserElement:
+    """Helper to define a counted list of expressions.
+
+    This helper defines a pattern of the form::
+
+        integer expr expr expr...
+
+    where the leading integer tells how many expr expressions follow.
+    The matched tokens returns the array of expr tokens as a list - the
+    leading count token is suppressed.
+
+    If ``int_expr`` is specified, it should be a pyparsing expression
+    that produces an integer value.
+
+    Example::
+
+        counted_array(Word(alphas)).parse_string('2 ab cd ef')  # -> ['ab', 'cd']
+
+        # in this parser, the leading integer value is given in binary,
+        # '10' indicating that 2 values are in the array
+        binary_constant = Word('01').set_parse_action(lambda t: int(t[0], 2))
+        counted_array(Word(alphas), int_expr=binary_constant).parse_string('10 ab cd ef')  # -> ['ab', 'cd']
+
+        # if other fields must be parsed after the count but before the
+        # list items, give the fields results names and they will
+        # be preserved in the returned ParseResults:
+        count_with_metadata = integer + Word(alphas)("type")
+        typed_array = counted_array(Word(alphanums), int_expr=count_with_metadata)("items")
+        result = typed_array.parse_string("3 bool True True False")
+        print(result.dump())
+
+        # prints
+        # ['True', 'True', 'False']
+        # - items: ['True', 'True', 'False']
+        # - type: 'bool'
+    """
+    intExpr = intExpr or int_expr
+    array_expr = Forward()
+
+    def count_field_parse_action(s, l, t):
+        nonlocal array_expr
+        n = t[0]
+        array_expr <<= (expr * n) if n else Empty()
+        # clear list contents, but keep any named results
+        del t[:]
+
+    if intExpr is None:
+        intExpr = Word(nums).set_parse_action(lambda t: int(t[0]))
+    else:
+        intExpr = intExpr.copy()
+    intExpr.set_name("arrayLen")
+    intExpr.add_parse_action(count_field_parse_action, call_during_try=True)
+    return (intExpr + array_expr).set_name("(len) " + str(expr) + "...")
+
+
+def match_previous_literal(expr: ParserElement) -> ParserElement:
+    """Helper to define an expression that is indirectly defined from
+    the tokens matched in a previous expression, that is, it looks for
+    a 'repeat' of a previous expression.  For example::
+
+        first = Word(nums)
+        second = match_previous_literal(first)
+        match_expr = first + ":" + second
+
+    will match ``"1:1"``, but not ``"1:2"``.  Because this
+    matches a previous literal, will also match the leading
+    ``"1:1"`` in ``"1:10"``. If this is not desired, use
+    :class:`match_previous_expr`. Do *not* use with packrat parsing
+    enabled.
+    """
+    rep = Forward()
+
+    def copy_token_to_repeater(s, l, t):
+        if t:
+            if len(t) == 1:
+                rep << t[0]
+            else:
+                # flatten t tokens
+                tflat = _flatten(t.as_list())
+                rep << And(Literal(tt) for tt in tflat)
+        else:
+            rep << Empty()
+
+    expr.add_parse_action(copy_token_to_repeater, callDuringTry=True)
+    rep.set_name("(prev) " + str(expr))
+    return rep
+
+
+def match_previous_expr(expr: ParserElement) -> ParserElement:
+    """Helper to define an expression that is indirectly defined from
+    the tokens matched in a previous expression, that is, it looks for
+    a 'repeat' of a previous expression.  For example::
+
+        first = Word(nums)
+        second = match_previous_expr(first)
+        match_expr = first + ":" + second
+
+    will match ``"1:1"``, but not ``"1:2"``.  Because this
+    matches by expressions, will *not* match the leading ``"1:1"``
+    in ``"1:10"``; the expressions are evaluated first, and then
+    compared, so ``"1"`` is compared with ``"10"``. Do *not* use
+    with packrat parsing enabled.
+    """
+    rep = Forward()
+    e2 = expr.copy()
+    rep <<= e2
+
+    def copy_token_to_repeater(s, l, t):
+        matchTokens = _flatten(t.as_list())
+
+        def must_match_these_tokens(s, l, t):
+            theseTokens = _flatten(t.as_list())
+            if theseTokens != matchTokens:
+                raise ParseException(
+                    s, l, "Expected {}, found{}".format(matchTokens, theseTokens)
+                )
+
+        rep.set_parse_action(must_match_these_tokens, callDuringTry=True)
+
+    expr.add_parse_action(copy_token_to_repeater, callDuringTry=True)
+    rep.set_name("(prev) " + str(expr))
+    return rep
+
+
+def one_of(
+    strs: Union[typing.Iterable[str], str],
+    caseless: bool = False,
+    use_regex: bool = True,
+    as_keyword: bool = False,
+    *,
+    useRegex: bool = True,
+    asKeyword: bool = False,
+) -> ParserElement:
+    """Helper to quickly define a set of alternative :class:`Literal` s,
+    and makes sure to do longest-first testing when there is a conflict,
+    regardless of the input order, but returns
+    a :class:`MatchFirst` for best performance.
+
+    Parameters:
+
+    - ``strs`` - a string of space-delimited literals, or a collection of
+      string literals
+    - ``caseless`` - treat all literals as caseless - (default= ``False``)
+    - ``use_regex`` - as an optimization, will
+      generate a :class:`Regex` object; otherwise, will generate
+      a :class:`MatchFirst` object (if ``caseless=True`` or ``asKeyword=True``, or if
+      creating a :class:`Regex` raises an exception) - (default= ``True``)
+    - ``as_keyword`` - enforce :class:`Keyword`-style matching on the
+      generated expressions - (default= ``False``)
+    - ``asKeyword`` and ``useRegex`` are retained for pre-PEP8 compatibility,
+      but will be removed in a future release
+
+    Example::
+
+        comp_oper = one_of("< = > <= >= !=")
+        var = Word(alphas)
+        number = Word(nums)
+        term = var | number
+        comparison_expr = term + comp_oper + term
+        print(comparison_expr.search_string("B = 12  AA=23 B<=AA AA>12"))
+
+    prints::
+
+        [['B', '=', '12'], ['AA', '=', '23'], ['B', '<=', 'AA'], ['AA', '>', '12']]
+    """
+    asKeyword = asKeyword or as_keyword
+    useRegex = useRegex and use_regex
+
+    if (
+        isinstance(caseless, str_type)
+        and __diag__.warn_on_multiple_string_args_to_oneof
+    ):
+        warnings.warn(
+            "More than one string argument passed to one_of, pass"
+            " choices as a list or space-delimited string",
+            stacklevel=2,
+        )
+
+    if caseless:
+        isequal = lambda a, b: a.upper() == b.upper()
+        masks = lambda a, b: b.upper().startswith(a.upper())
+        parseElementClass = CaselessKeyword if asKeyword else CaselessLiteral
+    else:
+        isequal = lambda a, b: a == b
+        masks = lambda a, b: b.startswith(a)
+        parseElementClass = Keyword if asKeyword else Literal
+
+    symbols: List[str] = []
+    if isinstance(strs, str_type):
+        symbols = strs.split()
+    elif isinstance(strs, Iterable):
+        symbols = list(strs)
+    else:
+        raise TypeError("Invalid argument to one_of, expected string or iterable")
+    if not symbols:
+        return NoMatch()
+
+    # reorder given symbols to take care to avoid masking longer choices with shorter ones
+    # (but only if the given symbols are not just single characters)
+    if any(len(sym) > 1 for sym in symbols):
+        i = 0
+        while i < len(symbols) - 1:
+            cur = symbols[i]
+            for j, other in enumerate(symbols[i + 1 :]):
+                if isequal(other, cur):
+                    del symbols[i + j + 1]
+                    break
+                elif masks(cur, other):
+                    del symbols[i + j + 1]
+                    symbols.insert(i, other)
+                    break
+            else:
+                i += 1
+
+    if useRegex:
+        re_flags: int = re.IGNORECASE if caseless else 0
+
+        try:
+            if all(len(sym) == 1 for sym in symbols):
+                # symbols are just single characters, create range regex pattern
+                patt = "[{}]".format(
+                    "".join(_escape_regex_range_chars(sym) for sym in symbols)
+                )
+            else:
+                patt = "|".join(re.escape(sym) for sym in symbols)
+
+            # wrap with \b word break markers if defining as keywords
+            if asKeyword:
+                patt = r"\b(?:{})\b".format(patt)
+
+            ret = Regex(patt, flags=re_flags).set_name(" | ".join(symbols))
+
+            if caseless:
+                # add parse action to return symbols as specified, not in random
+                # casing as found in input string
+                symbol_map = {sym.lower(): sym for sym in symbols}
+                ret.add_parse_action(lambda s, l, t: symbol_map[t[0].lower()])
+
+            return ret
+
+        except re.error:
+            warnings.warn(
+                "Exception creating Regex for one_of, building MatchFirst", stacklevel=2
+            )
+
+    # last resort, just use MatchFirst
+    return MatchFirst(parseElementClass(sym) for sym in symbols).set_name(
+        " | ".join(symbols)
+    )
+
+
+def dict_of(key: ParserElement, value: ParserElement) -> ParserElement:
+    """Helper to easily and clearly define a dictionary by specifying
+    the respective patterns for the key and value.  Takes care of
+    defining the :class:`Dict`, :class:`ZeroOrMore`, and
+    :class:`Group` tokens in the proper order.  The key pattern
+    can include delimiting markers or punctuation, as long as they are
+    suppressed, thereby leaving the significant key text.  The value
+    pattern can include named results, so that the :class:`Dict` results
+    can include named token fields.
+
+    Example::
+
+        text = "shape: SQUARE posn: upper left color: light blue texture: burlap"
+        attr_expr = (label + Suppress(':') + OneOrMore(data_word, stop_on=label).set_parse_action(' '.join))
+        print(attr_expr[1, ...].parse_string(text).dump())
+
+        attr_label = label
+        attr_value = Suppress(':') + OneOrMore(data_word, stop_on=label).set_parse_action(' '.join)
+
+        # similar to Dict, but simpler call format
+        result = dict_of(attr_label, attr_value).parse_string(text)
+        print(result.dump())
+        print(result['shape'])
+        print(result.shape)  # object attribute access works too
+        print(result.as_dict())
+
+    prints::
+
+        [['shape', 'SQUARE'], ['posn', 'upper left'], ['color', 'light blue'], ['texture', 'burlap']]
+        - color: 'light blue'
+        - posn: 'upper left'
+        - shape: 'SQUARE'
+        - texture: 'burlap'
+        SQUARE
+        SQUARE
+        {'color': 'light blue', 'shape': 'SQUARE', 'posn': 'upper left', 'texture': 'burlap'}
+    """
+    return Dict(OneOrMore(Group(key + value)))
+
+
+def original_text_for(
+    expr: ParserElement, as_string: bool = True, *, asString: bool = True
+) -> ParserElement:
+    """Helper to return the original, untokenized text for a given
+    expression.  Useful to restore the parsed fields of an HTML start
+    tag into the raw tag text itself, or to revert separate tokens with
+    intervening whitespace back to the original matching input text. By
+    default, returns astring containing the original parsed text.
+
+    If the optional ``as_string`` argument is passed as
+    ``False``, then the return value is
+    a :class:`ParseResults` containing any results names that
+    were originally matched, and a single token containing the original
+    matched text from the input string.  So if the expression passed to
+    :class:`original_text_for` contains expressions with defined
+    results names, you must set ``as_string`` to ``False`` if you
+    want to preserve those results name values.
+
+    The ``asString`` pre-PEP8 argument is retained for compatibility,
+    but will be removed in a future release.
+
+    Example::
+
+        src = "this is test  bold text  normal text "
+        for tag in ("b", "i"):
+            opener, closer = make_html_tags(tag)
+            patt = original_text_for(opener + SkipTo(closer) + closer)
+            print(patt.search_string(src)[0])
+
+    prints::
+
+        [' bold text ']
+        ['text']
+    """
+    asString = asString and as_string
+
+    locMarker = Empty().set_parse_action(lambda s, loc, t: loc)
+    endlocMarker = locMarker.copy()
+    endlocMarker.callPreparse = False
+    matchExpr = locMarker("_original_start") + expr + endlocMarker("_original_end")
+    if asString:
+        extractText = lambda s, l, t: s[t._original_start : t._original_end]
+    else:
+
+        def extractText(s, l, t):
+            t[:] = [s[t.pop("_original_start") : t.pop("_original_end")]]
+
+    matchExpr.set_parse_action(extractText)
+    matchExpr.ignoreExprs = expr.ignoreExprs
+    matchExpr.suppress_warning(Diagnostics.warn_ungrouped_named_tokens_in_collection)
+    return matchExpr
+
+
+def ungroup(expr: ParserElement) -> ParserElement:
+    """Helper to undo pyparsing's default grouping of And expressions,
+    even if all but one are non-empty.
+    """
+    return TokenConverter(expr).add_parse_action(lambda t: t[0])
+
+
+def locatedExpr(expr: ParserElement) -> ParserElement:
+    """
+    (DEPRECATED - future code should use the Located class)
+    Helper to decorate a returned token with its starting and ending
+    locations in the input string.
+
+    This helper adds the following results names:
+
+    - ``locn_start`` - location where matched expression begins
+    - ``locn_end`` - location where matched expression ends
+    - ``value`` - the actual parsed results
+
+    Be careful if the input text contains ```` characters, you
+    may want to call :class:`ParserElement.parseWithTabs`
+
+    Example::
+
+        wd = Word(alphas)
+        for match in locatedExpr(wd).searchString("ljsdf123lksdjjf123lkkjj1222"):
+            print(match)
+
+    prints::
+
+        [[0, 'ljsdf', 5]]
+        [[8, 'lksdjjf', 15]]
+        [[18, 'lkkjj', 23]]
+    """
+    locator = Empty().set_parse_action(lambda ss, ll, tt: ll)
+    return Group(
+        locator("locn_start")
+        + expr("value")
+        + locator.copy().leaveWhitespace()("locn_end")
+    )
+
+
+def nested_expr(
+    opener: Union[str, ParserElement] = "(",
+    closer: Union[str, ParserElement] = ")",
+    content: typing.Optional[ParserElement] = None,
+    ignore_expr: ParserElement = quoted_string(),
+    *,
+    ignoreExpr: ParserElement = quoted_string(),
+) -> ParserElement:
+    """Helper method for defining nested lists enclosed in opening and
+    closing delimiters (``"("`` and ``")"`` are the default).
+
+    Parameters:
+    - ``opener`` - opening character for a nested list
+      (default= ``"("``); can also be a pyparsing expression
+    - ``closer`` - closing character for a nested list
+      (default= ``")"``); can also be a pyparsing expression
+    - ``content`` - expression for items within the nested lists
+      (default= ``None``)
+    - ``ignore_expr`` - expression for ignoring opening and closing delimiters
+      (default= :class:`quoted_string`)
+    - ``ignoreExpr`` - this pre-PEP8 argument is retained for compatibility
+      but will be removed in a future release
+
+    If an expression is not provided for the content argument, the
+    nested expression will capture all whitespace-delimited content
+    between delimiters as a list of separate values.
+
+    Use the ``ignore_expr`` argument to define expressions that may
+    contain opening or closing characters that should not be treated as
+    opening or closing characters for nesting, such as quoted_string or
+    a comment expression.  Specify multiple expressions using an
+    :class:`Or` or :class:`MatchFirst`. The default is
+    :class:`quoted_string`, but if no expressions are to be ignored, then
+    pass ``None`` for this argument.
+
+    Example::
+
+        data_type = one_of("void int short long char float double")
+        decl_data_type = Combine(data_type + Opt(Word('*')))
+        ident = Word(alphas+'_', alphanums+'_')
+        number = pyparsing_common.number
+        arg = Group(decl_data_type + ident)
+        LPAR, RPAR = map(Suppress, "()")
+
+        code_body = nested_expr('{', '}', ignore_expr=(quoted_string | c_style_comment))
+
+        c_function = (decl_data_type("type")
+                      + ident("name")
+                      + LPAR + Opt(delimited_list(arg), [])("args") + RPAR
+                      + code_body("body"))
+        c_function.ignore(c_style_comment)
+
+        source_code = '''
+            int is_odd(int x) {
+                return (x%2);
+            }
+
+            int dec_to_hex(char hchar) {
+                if (hchar >= '0' && hchar <= '9') {
+                    return (ord(hchar)-ord('0'));
+                } else {
+                    return (10+ord(hchar)-ord('A'));
+                }
+            }
+        '''
+        for func in c_function.search_string(source_code):
+            print("%(name)s (%(type)s) args: %(args)s" % func)
+
+
+    prints::
+
+        is_odd (int) args: [['int', 'x']]
+        dec_to_hex (int) args: [['char', 'hchar']]
+    """
+    if ignoreExpr != ignore_expr:
+        ignoreExpr = ignore_expr if ignoreExpr == quoted_string() else ignoreExpr
+    if opener == closer:
+        raise ValueError("opening and closing strings cannot be the same")
+    if content is None:
+        if isinstance(opener, str_type) and isinstance(closer, str_type):
+            if len(opener) == 1 and len(closer) == 1:
+                if ignoreExpr is not None:
+                    content = Combine(
+                        OneOrMore(
+                            ~ignoreExpr
+                            + CharsNotIn(
+                                opener + closer + ParserElement.DEFAULT_WHITE_CHARS,
+                                exact=1,
+                            )
+                        )
+                    ).set_parse_action(lambda t: t[0].strip())
+                else:
+                    content = empty.copy() + CharsNotIn(
+                        opener + closer + ParserElement.DEFAULT_WHITE_CHARS
+                    ).set_parse_action(lambda t: t[0].strip())
+            else:
+                if ignoreExpr is not None:
+                    content = Combine(
+                        OneOrMore(
+                            ~ignoreExpr
+                            + ~Literal(opener)
+                            + ~Literal(closer)
+                            + CharsNotIn(ParserElement.DEFAULT_WHITE_CHARS, exact=1)
+                        )
+                    ).set_parse_action(lambda t: t[0].strip())
+                else:
+                    content = Combine(
+                        OneOrMore(
+                            ~Literal(opener)
+                            + ~Literal(closer)
+                            + CharsNotIn(ParserElement.DEFAULT_WHITE_CHARS, exact=1)
+                        )
+                    ).set_parse_action(lambda t: t[0].strip())
+        else:
+            raise ValueError(
+                "opening and closing arguments must be strings if no content expression is given"
+            )
+    ret = Forward()
+    if ignoreExpr is not None:
+        ret <<= Group(
+            Suppress(opener) + ZeroOrMore(ignoreExpr | ret | content) + Suppress(closer)
+        )
+    else:
+        ret <<= Group(Suppress(opener) + ZeroOrMore(ret | content) + Suppress(closer))
+    ret.set_name("nested %s%s expression" % (opener, closer))
+    return ret
+
+
+def _makeTags(tagStr, xml, suppress_LT=Suppress("<"), suppress_GT=Suppress(">")):
+    """Internal helper to construct opening and closing tag expressions, given a tag name"""
+    if isinstance(tagStr, str_type):
+        resname = tagStr
+        tagStr = Keyword(tagStr, caseless=not xml)
+    else:
+        resname = tagStr.name
+
+    tagAttrName = Word(alphas, alphanums + "_-:")
+    if xml:
+        tagAttrValue = dbl_quoted_string.copy().set_parse_action(remove_quotes)
+        openTag = (
+            suppress_LT
+            + tagStr("tag")
+            + Dict(ZeroOrMore(Group(tagAttrName + Suppress("=") + tagAttrValue)))
+            + Opt("/", default=[False])("empty").set_parse_action(
+                lambda s, l, t: t[0] == "/"
+            )
+            + suppress_GT
+        )
+    else:
+        tagAttrValue = quoted_string.copy().set_parse_action(remove_quotes) | Word(
+            printables, exclude_chars=">"
+        )
+        openTag = (
+            suppress_LT
+            + tagStr("tag")
+            + Dict(
+                ZeroOrMore(
+                    Group(
+                        tagAttrName.set_parse_action(lambda t: t[0].lower())
+                        + Opt(Suppress("=") + tagAttrValue)
+                    )
+                )
+            )
+            + Opt("/", default=[False])("empty").set_parse_action(
+                lambda s, l, t: t[0] == "/"
+            )
+            + suppress_GT
+        )
+    closeTag = Combine(Literal("", adjacent=False)
+
+    openTag.set_name("<%s>" % resname)
+    # add start results name in parse action now that ungrouped names are not reported at two levels
+    openTag.add_parse_action(
+        lambda t: t.__setitem__(
+            "start" + "".join(resname.replace(":", " ").title().split()), t.copy()
+        )
+    )
+    closeTag = closeTag(
+        "end" + "".join(resname.replace(":", " ").title().split())
+    ).set_name("" % resname)
+    openTag.tag = resname
+    closeTag.tag = resname
+    openTag.tag_body = SkipTo(closeTag())
+    return openTag, closeTag
+
+
+def make_html_tags(
+    tag_str: Union[str, ParserElement]
+) -> Tuple[ParserElement, ParserElement]:
+    """Helper to construct opening and closing tag expressions for HTML,
+    given a tag name. Matches tags in either upper or lower case,
+    attributes with namespaces and with quoted or unquoted values.
+
+    Example::
+
+        text = 'More info at the pyparsing wiki page'
+        # make_html_tags returns pyparsing expressions for the opening and
+        # closing tags as a 2-tuple
+        a, a_end = make_html_tags("A")
+        link_expr = a + SkipTo(a_end)("link_text") + a_end
+
+        for link in link_expr.search_string(text):
+            # attributes in the  tag (like "href" shown here) are
+            # also accessible as named results
+            print(link.link_text, '->', link.href)
+
+    prints::
+
+        pyparsing -> https://github.com/pyparsing/pyparsing/wiki
+    """
+    return _makeTags(tag_str, False)
+
+
+def make_xml_tags(
+    tag_str: Union[str, ParserElement]
+) -> Tuple[ParserElement, ParserElement]:
+    """Helper to construct opening and closing tag expressions for XML,
+    given a tag name. Matches tags only in the given upper/lower case.
+
+    Example: similar to :class:`make_html_tags`
+    """
+    return _makeTags(tag_str, True)
+
+
+any_open_tag: ParserElement
+any_close_tag: ParserElement
+any_open_tag, any_close_tag = make_html_tags(
+    Word(alphas, alphanums + "_:").set_name("any tag")
+)
+
+_htmlEntityMap = {k.rstrip(";"): v for k, v in html.entities.html5.items()}
+common_html_entity = Regex("&(?P" + "|".join(_htmlEntityMap) + ");").set_name(
+    "common HTML entity"
+)
+
+
+def replace_html_entity(t):
+    """Helper parser action to replace common HTML entities with their special characters"""
+    return _htmlEntityMap.get(t.entity)
+
+
+class OpAssoc(Enum):
+    LEFT = 1
+    RIGHT = 2
+
+
+InfixNotationOperatorArgType = Union[
+    ParserElement, str, Tuple[Union[ParserElement, str], Union[ParserElement, str]]
+]
+InfixNotationOperatorSpec = Union[
+    Tuple[
+        InfixNotationOperatorArgType,
+        int,
+        OpAssoc,
+        typing.Optional[ParseAction],
+    ],
+    Tuple[
+        InfixNotationOperatorArgType,
+        int,
+        OpAssoc,
+    ],
+]
+
+
+def infix_notation(
+    base_expr: ParserElement,
+    op_list: List[InfixNotationOperatorSpec],
+    lpar: Union[str, ParserElement] = Suppress("("),
+    rpar: Union[str, ParserElement] = Suppress(")"),
+) -> ParserElement:
+    """Helper method for constructing grammars of expressions made up of
+    operators working in a precedence hierarchy.  Operators may be unary
+    or binary, left- or right-associative.  Parse actions can also be
+    attached to operator expressions. The generated parser will also
+    recognize the use of parentheses to override operator precedences
+    (see example below).
+
+    Note: if you define a deep operator list, you may see performance
+    issues when using infix_notation. See
+    :class:`ParserElement.enable_packrat` for a mechanism to potentially
+    improve your parser performance.
+
+    Parameters:
+    - ``base_expr`` - expression representing the most basic operand to
+      be used in the expression
+    - ``op_list`` - list of tuples, one for each operator precedence level
+      in the expression grammar; each tuple is of the form ``(op_expr,
+      num_operands, right_left_assoc, (optional)parse_action)``, where:
+
+      - ``op_expr`` is the pyparsing expression for the operator; may also
+        be a string, which will be converted to a Literal; if ``num_operands``
+        is 3, ``op_expr`` is a tuple of two expressions, for the two
+        operators separating the 3 terms
+      - ``num_operands`` is the number of terms for this operator (must be 1,
+        2, or 3)
+      - ``right_left_assoc`` is the indicator whether the operator is right
+        or left associative, using the pyparsing-defined constants
+        ``OpAssoc.RIGHT`` and ``OpAssoc.LEFT``.
+      - ``parse_action`` is the parse action to be associated with
+        expressions matching this operator expression (the parse action
+        tuple member may be omitted); if the parse action is passed
+        a tuple or list of functions, this is equivalent to calling
+        ``set_parse_action(*fn)``
+        (:class:`ParserElement.set_parse_action`)
+    - ``lpar`` - expression for matching left-parentheses; if passed as a
+      str, then will be parsed as Suppress(lpar). If lpar is passed as
+      an expression (such as ``Literal('(')``), then it will be kept in
+      the parsed results, and grouped with them. (default= ``Suppress('(')``)
+    - ``rpar`` - expression for matching right-parentheses; if passed as a
+      str, then will be parsed as Suppress(rpar). If rpar is passed as
+      an expression (such as ``Literal(')')``), then it will be kept in
+      the parsed results, and grouped with them. (default= ``Suppress(')')``)
+
+    Example::
+
+        # simple example of four-function arithmetic with ints and
+        # variable names
+        integer = pyparsing_common.signed_integer
+        varname = pyparsing_common.identifier
+
+        arith_expr = infix_notation(integer | varname,
+            [
+            ('-', 1, OpAssoc.RIGHT),
+            (one_of('* /'), 2, OpAssoc.LEFT),
+            (one_of('+ -'), 2, OpAssoc.LEFT),
+            ])
+
+        arith_expr.run_tests('''
+            5+3*6
+            (5+3)*6
+            -2--11
+            ''', full_dump=False)
+
+    prints::
+
+        5+3*6
+        [[5, '+', [3, '*', 6]]]
+
+        (5+3)*6
+        [[[5, '+', 3], '*', 6]]
+
+        -2--11
+        [[['-', 2], '-', ['-', 11]]]
+    """
+    # captive version of FollowedBy that does not do parse actions or capture results names
+    class _FB(FollowedBy):
+        def parseImpl(self, instring, loc, doActions=True):
+            self.expr.try_parse(instring, loc)
+            return loc, []
+
+    _FB.__name__ = "FollowedBy>"
+
+    ret = Forward()
+    if isinstance(lpar, str):
+        lpar = Suppress(lpar)
+    if isinstance(rpar, str):
+        rpar = Suppress(rpar)
+
+    # if lpar and rpar are not suppressed, wrap in group
+    if not (isinstance(rpar, Suppress) and isinstance(rpar, Suppress)):
+        lastExpr = base_expr | Group(lpar + ret + rpar)
+    else:
+        lastExpr = base_expr | (lpar + ret + rpar)
+
+    for i, operDef in enumerate(op_list):
+        opExpr, arity, rightLeftAssoc, pa = (operDef + (None,))[:4]
+        if isinstance(opExpr, str_type):
+            opExpr = ParserElement._literalStringClass(opExpr)
+        if arity == 3:
+            if not isinstance(opExpr, (tuple, list)) or len(opExpr) != 2:
+                raise ValueError(
+                    "if numterms=3, opExpr must be a tuple or list of two expressions"
+                )
+            opExpr1, opExpr2 = opExpr
+            term_name = "{}{} term".format(opExpr1, opExpr2)
+        else:
+            term_name = "{} term".format(opExpr)
+
+        if not 1 <= arity <= 3:
+            raise ValueError("operator must be unary (1), binary (2), or ternary (3)")
+
+        if rightLeftAssoc not in (OpAssoc.LEFT, OpAssoc.RIGHT):
+            raise ValueError("operator must indicate right or left associativity")
+
+        thisExpr: Forward = Forward().set_name(term_name)
+        if rightLeftAssoc is OpAssoc.LEFT:
+            if arity == 1:
+                matchExpr = _FB(lastExpr + opExpr) + Group(lastExpr + opExpr[1, ...])
+            elif arity == 2:
+                if opExpr is not None:
+                    matchExpr = _FB(lastExpr + opExpr + lastExpr) + Group(
+                        lastExpr + (opExpr + lastExpr)[1, ...]
+                    )
+                else:
+                    matchExpr = _FB(lastExpr + lastExpr) + Group(lastExpr[2, ...])
+            elif arity == 3:
+                matchExpr = _FB(
+                    lastExpr + opExpr1 + lastExpr + opExpr2 + lastExpr
+                ) + Group(lastExpr + OneOrMore(opExpr1 + lastExpr + opExpr2 + lastExpr))
+        elif rightLeftAssoc is OpAssoc.RIGHT:
+            if arity == 1:
+                # try to avoid LR with this extra test
+                if not isinstance(opExpr, Opt):
+                    opExpr = Opt(opExpr)
+                matchExpr = _FB(opExpr.expr + thisExpr) + Group(opExpr + thisExpr)
+            elif arity == 2:
+                if opExpr is not None:
+                    matchExpr = _FB(lastExpr + opExpr + thisExpr) + Group(
+                        lastExpr + (opExpr + thisExpr)[1, ...]
+                    )
+                else:
+                    matchExpr = _FB(lastExpr + thisExpr) + Group(
+                        lastExpr + thisExpr[1, ...]
+                    )
+            elif arity == 3:
+                matchExpr = _FB(
+                    lastExpr + opExpr1 + thisExpr + opExpr2 + thisExpr
+                ) + Group(lastExpr + opExpr1 + thisExpr + opExpr2 + thisExpr)
+        if pa:
+            if isinstance(pa, (tuple, list)):
+                matchExpr.set_parse_action(*pa)
+            else:
+                matchExpr.set_parse_action(pa)
+        thisExpr <<= (matchExpr | lastExpr).setName(term_name)
+        lastExpr = thisExpr
+    ret <<= lastExpr
+    return ret
+
+
+def indentedBlock(blockStatementExpr, indentStack, indent=True, backup_stacks=[]):
+    """
+    (DEPRECATED - use IndentedBlock class instead)
+    Helper method for defining space-delimited indentation blocks,
+    such as those used to define block statements in Python source code.
+
+    Parameters:
+
+    - ``blockStatementExpr`` - expression defining syntax of statement that
+      is repeated within the indented block
+    - ``indentStack`` - list created by caller to manage indentation stack
+      (multiple ``statementWithIndentedBlock`` expressions within a single
+      grammar should share a common ``indentStack``)
+    - ``indent`` - boolean indicating whether block must be indented beyond
+      the current level; set to ``False`` for block of left-most statements
+      (default= ``True``)
+
+    A valid block must contain at least one ``blockStatement``.
+
+    (Note that indentedBlock uses internal parse actions which make it
+    incompatible with packrat parsing.)
+
+    Example::
+
+        data = '''
+        def A(z):
+          A1
+          B = 100
+          G = A2
+          A2
+          A3
+        B
+        def BB(a,b,c):
+          BB1
+          def BBA():
+            bba1
+            bba2
+            bba3
+        C
+        D
+        def spam(x,y):
+             def eggs(z):
+                 pass
+        '''
+
+
+        indentStack = [1]
+        stmt = Forward()
+
+        identifier = Word(alphas, alphanums)
+        funcDecl = ("def" + identifier + Group("(" + Opt(delimitedList(identifier)) + ")") + ":")
+        func_body = indentedBlock(stmt, indentStack)
+        funcDef = Group(funcDecl + func_body)
+
+        rvalue = Forward()
+        funcCall = Group(identifier + "(" + Opt(delimitedList(rvalue)) + ")")
+        rvalue << (funcCall | identifier | Word(nums))
+        assignment = Group(identifier + "=" + rvalue)
+        stmt << (funcDef | assignment | identifier)
+
+        module_body = stmt[1, ...]
+
+        parseTree = module_body.parseString(data)
+        parseTree.pprint()
+
+    prints::
+
+        [['def',
+          'A',
+          ['(', 'z', ')'],
+          ':',
+          [['A1'], [['B', '=', '100']], [['G', '=', 'A2']], ['A2'], ['A3']]],
+         'B',
+         ['def',
+          'BB',
+          ['(', 'a', 'b', 'c', ')'],
+          ':',
+          [['BB1'], [['def', 'BBA', ['(', ')'], ':', [['bba1'], ['bba2'], ['bba3']]]]]],
+         'C',
+         'D',
+         ['def',
+          'spam',
+          ['(', 'x', 'y', ')'],
+          ':',
+          [[['def', 'eggs', ['(', 'z', ')'], ':', [['pass']]]]]]]
+    """
+    backup_stacks.append(indentStack[:])
+
+    def reset_stack():
+        indentStack[:] = backup_stacks[-1]
+
+    def checkPeerIndent(s, l, t):
+        if l >= len(s):
+            return
+        curCol = col(l, s)
+        if curCol != indentStack[-1]:
+            if curCol > indentStack[-1]:
+                raise ParseException(s, l, "illegal nesting")
+            raise ParseException(s, l, "not a peer entry")
+
+    def checkSubIndent(s, l, t):
+        curCol = col(l, s)
+        if curCol > indentStack[-1]:
+            indentStack.append(curCol)
+        else:
+            raise ParseException(s, l, "not a subentry")
+
+    def checkUnindent(s, l, t):
+        if l >= len(s):
+            return
+        curCol = col(l, s)
+        if not (indentStack and curCol in indentStack):
+            raise ParseException(s, l, "not an unindent")
+        if curCol < indentStack[-1]:
+            indentStack.pop()
+
+    NL = OneOrMore(LineEnd().set_whitespace_chars("\t ").suppress())
+    INDENT = (Empty() + Empty().set_parse_action(checkSubIndent)).set_name("INDENT")
+    PEER = Empty().set_parse_action(checkPeerIndent).set_name("")
+    UNDENT = Empty().set_parse_action(checkUnindent).set_name("UNINDENT")
+    if indent:
+        smExpr = Group(
+            Opt(NL)
+            + INDENT
+            + OneOrMore(PEER + Group(blockStatementExpr) + Opt(NL))
+            + UNDENT
+        )
+    else:
+        smExpr = Group(
+            Opt(NL)
+            + OneOrMore(PEER + Group(blockStatementExpr) + Opt(NL))
+            + Opt(UNDENT)
+        )
+
+    # add a parse action to remove backup_stack from list of backups
+    smExpr.add_parse_action(
+        lambda: backup_stacks.pop(-1) and None if backup_stacks else None
+    )
+    smExpr.set_fail_action(lambda a, b, c, d: reset_stack())
+    blockStatementExpr.ignore(_bslash + LineEnd())
+    return smExpr.set_name("indented block")
+
+
+# it's easy to get these comment structures wrong - they're very common, so may as well make them available
+c_style_comment = Combine(Regex(r"/\*(?:[^*]|\*(?!/))*") + "*/").set_name(
+    "C style comment"
+)
+"Comment of the form ``/* ... */``"
+
+html_comment = Regex(r"").set_name("HTML comment")
+"Comment of the form ````"
+
+rest_of_line = Regex(r".*").leave_whitespace().set_name("rest of line")
+dbl_slash_comment = Regex(r"//(?:\\\n|[^\n])*").set_name("// comment")
+"Comment of the form ``// ... (to end of line)``"
+
+cpp_style_comment = Combine(
+    Regex(r"/\*(?:[^*]|\*(?!/))*") + "*/" | dbl_slash_comment
+).set_name("C++ style comment")
+"Comment of either form :class:`c_style_comment` or :class:`dbl_slash_comment`"
+
+java_style_comment = cpp_style_comment
+"Same as :class:`cpp_style_comment`"
+
+python_style_comment = Regex(r"#.*").set_name("Python style comment")
+"Comment of the form ``# ... (to end of line)``"
+
+
+# build list of built-in expressions, for future reference if a global default value
+# gets updated
+_builtin_exprs: List[ParserElement] = [
+    v for v in vars().values() if isinstance(v, ParserElement)
+]
+
+
+# pre-PEP8 compatible names
+delimitedList = delimited_list
+countedArray = counted_array
+matchPreviousLiteral = match_previous_literal
+matchPreviousExpr = match_previous_expr
+oneOf = one_of
+dictOf = dict_of
+originalTextFor = original_text_for
+nestedExpr = nested_expr
+makeHTMLTags = make_html_tags
+makeXMLTags = make_xml_tags
+anyOpenTag, anyCloseTag = any_open_tag, any_close_tag
+commonHTMLEntity = common_html_entity
+replaceHTMLEntity = replace_html_entity
+opAssoc = OpAssoc
+infixNotation = infix_notation
+cStyleComment = c_style_comment
+htmlComment = html_comment
+restOfLine = rest_of_line
+dblSlashComment = dbl_slash_comment
+cppStyleComment = cpp_style_comment
+javaStyleComment = java_style_comment
+pythonStyleComment = python_style_comment
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/results.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/results.py
new file mode 100644
index 0000000000000000000000000000000000000000..00c9421d3b0362526b8f90dc01e8db73841e0b61
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/results.py
@@ -0,0 +1,760 @@
+# results.py
+from collections.abc import MutableMapping, Mapping, MutableSequence, Iterator
+import pprint
+from weakref import ref as wkref
+from typing import Tuple, Any
+
+str_type: Tuple[type, ...] = (str, bytes)
+_generator_type = type((_ for _ in ()))
+
+
+class _ParseResultsWithOffset:
+    __slots__ = ["tup"]
+
+    def __init__(self, p1, p2):
+        self.tup = (p1, p2)
+
+    def __getitem__(self, i):
+        return self.tup[i]
+
+    def __getstate__(self):
+        return self.tup
+
+    def __setstate__(self, *args):
+        self.tup = args[0]
+
+
+class ParseResults:
+    """Structured parse results, to provide multiple means of access to
+    the parsed data:
+
+    - as a list (``len(results)``)
+    - by list index (``results[0], results[1]``, etc.)
+    - by attribute (``results.`` - see :class:`ParserElement.set_results_name`)
+
+    Example::
+
+        integer = Word(nums)
+        date_str = (integer.set_results_name("year") + '/'
+                    + integer.set_results_name("month") + '/'
+                    + integer.set_results_name("day"))
+        # equivalent form:
+        # date_str = (integer("year") + '/'
+        #             + integer("month") + '/'
+        #             + integer("day"))
+
+        # parse_string returns a ParseResults object
+        result = date_str.parse_string("1999/12/31")
+
+        def test(s, fn=repr):
+            print("{} -> {}".format(s, fn(eval(s))))
+        test("list(result)")
+        test("result[0]")
+        test("result['month']")
+        test("result.day")
+        test("'month' in result")
+        test("'minutes' in result")
+        test("result.dump()", str)
+
+    prints::
+
+        list(result) -> ['1999', '/', '12', '/', '31']
+        result[0] -> '1999'
+        result['month'] -> '12'
+        result.day -> '31'
+        'month' in result -> True
+        'minutes' in result -> False
+        result.dump() -> ['1999', '/', '12', '/', '31']
+        - day: '31'
+        - month: '12'
+        - year: '1999'
+    """
+
+    _null_values: Tuple[Any, ...] = (None, [], "", ())
+
+    __slots__ = [
+        "_name",
+        "_parent",
+        "_all_names",
+        "_modal",
+        "_toklist",
+        "_tokdict",
+        "__weakref__",
+    ]
+
+    class List(list):
+        """
+        Simple wrapper class to distinguish parsed list results that should be preserved
+        as actual Python lists, instead of being converted to :class:`ParseResults`:
+
+            LBRACK, RBRACK = map(pp.Suppress, "[]")
+            element = pp.Forward()
+            item = ppc.integer
+            element_list = LBRACK + pp.delimited_list(element) + RBRACK
+
+            # add parse actions to convert from ParseResults to actual Python collection types
+            def as_python_list(t):
+                return pp.ParseResults.List(t.as_list())
+            element_list.add_parse_action(as_python_list)
+
+            element <<= item | element_list
+
+            element.run_tests('''
+                100
+                [2,3,4]
+                [[2, 1],3,4]
+                [(2, 1),3,4]
+                (2,3,4)
+                ''', post_parse=lambda s, r: (r[0], type(r[0])))
+
+        prints:
+
+            100
+            (100, )
+
+            [2,3,4]
+            ([2, 3, 4], )
+
+            [[2, 1],3,4]
+            ([[2, 1], 3, 4], )
+
+        (Used internally by :class:`Group` when `aslist=True`.)
+        """
+
+        def __new__(cls, contained=None):
+            if contained is None:
+                contained = []
+
+            if not isinstance(contained, list):
+                raise TypeError(
+                    "{} may only be constructed with a list,"
+                    " not {}".format(cls.__name__, type(contained).__name__)
+                )
+
+            return list.__new__(cls)
+
+    def __new__(cls, toklist=None, name=None, **kwargs):
+        if isinstance(toklist, ParseResults):
+            return toklist
+        self = object.__new__(cls)
+        self._name = None
+        self._parent = None
+        self._all_names = set()
+
+        if toklist is None:
+            self._toklist = []
+        elif isinstance(toklist, (list, _generator_type)):
+            self._toklist = (
+                [toklist[:]]
+                if isinstance(toklist, ParseResults.List)
+                else list(toklist)
+            )
+        else:
+            self._toklist = [toklist]
+        self._tokdict = dict()
+        return self
+
+    # Performance tuning: we construct a *lot* of these, so keep this
+    # constructor as small and fast as possible
+    def __init__(
+        self, toklist=None, name=None, asList=True, modal=True, isinstance=isinstance
+    ):
+        self._modal = modal
+        if name is not None and name != "":
+            if isinstance(name, int):
+                name = str(name)
+            if not modal:
+                self._all_names = {name}
+            self._name = name
+            if toklist not in self._null_values:
+                if isinstance(toklist, (str_type, type)):
+                    toklist = [toklist]
+                if asList:
+                    if isinstance(toklist, ParseResults):
+                        self[name] = _ParseResultsWithOffset(
+                            ParseResults(toklist._toklist), 0
+                        )
+                    else:
+                        self[name] = _ParseResultsWithOffset(
+                            ParseResults(toklist[0]), 0
+                        )
+                    self[name]._name = name
+                else:
+                    try:
+                        self[name] = toklist[0]
+                    except (KeyError, TypeError, IndexError):
+                        if toklist is not self:
+                            self[name] = toklist
+                        else:
+                            self._name = name
+
+    def __getitem__(self, i):
+        if isinstance(i, (int, slice)):
+            return self._toklist[i]
+        else:
+            if i not in self._all_names:
+                return self._tokdict[i][-1][0]
+            else:
+                return ParseResults([v[0] for v in self._tokdict[i]])
+
+    def __setitem__(self, k, v, isinstance=isinstance):
+        if isinstance(v, _ParseResultsWithOffset):
+            self._tokdict[k] = self._tokdict.get(k, list()) + [v]
+            sub = v[0]
+        elif isinstance(k, (int, slice)):
+            self._toklist[k] = v
+            sub = v
+        else:
+            self._tokdict[k] = self._tokdict.get(k, list()) + [
+                _ParseResultsWithOffset(v, 0)
+            ]
+            sub = v
+        if isinstance(sub, ParseResults):
+            sub._parent = wkref(self)
+
+    def __delitem__(self, i):
+        if isinstance(i, (int, slice)):
+            mylen = len(self._toklist)
+            del self._toklist[i]
+
+            # convert int to slice
+            if isinstance(i, int):
+                if i < 0:
+                    i += mylen
+                i = slice(i, i + 1)
+            # get removed indices
+            removed = list(range(*i.indices(mylen)))
+            removed.reverse()
+            # fixup indices in token dictionary
+            for name, occurrences in self._tokdict.items():
+                for j in removed:
+                    for k, (value, position) in enumerate(occurrences):
+                        occurrences[k] = _ParseResultsWithOffset(
+                            value, position - (position > j)
+                        )
+        else:
+            del self._tokdict[i]
+
+    def __contains__(self, k) -> bool:
+        return k in self._tokdict
+
+    def __len__(self) -> int:
+        return len(self._toklist)
+
+    def __bool__(self) -> bool:
+        return not not (self._toklist or self._tokdict)
+
+    def __iter__(self) -> Iterator:
+        return iter(self._toklist)
+
+    def __reversed__(self) -> Iterator:
+        return iter(self._toklist[::-1])
+
+    def keys(self):
+        return iter(self._tokdict)
+
+    def values(self):
+        return (self[k] for k in self.keys())
+
+    def items(self):
+        return ((k, self[k]) for k in self.keys())
+
+    def haskeys(self) -> bool:
+        """
+        Since ``keys()`` returns an iterator, this method is helpful in bypassing
+        code that looks for the existence of any defined results names."""
+        return bool(self._tokdict)
+
+    def pop(self, *args, **kwargs):
+        """
+        Removes and returns item at specified index (default= ``last``).
+        Supports both ``list`` and ``dict`` semantics for ``pop()``. If
+        passed no argument or an integer argument, it will use ``list``
+        semantics and pop tokens from the list of parsed tokens. If passed
+        a non-integer argument (most likely a string), it will use ``dict``
+        semantics and pop the corresponding value from any defined results
+        names. A second default return value argument is supported, just as in
+        ``dict.pop()``.
+
+        Example::
+
+            numlist = Word(nums)[...]
+            print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321']
+
+            def remove_first(tokens):
+                tokens.pop(0)
+            numlist.add_parse_action(remove_first)
+            print(numlist.parse_string("0 123 321")) # -> ['123', '321']
+
+            label = Word(alphas)
+            patt = label("LABEL") + Word(nums)[1, ...]
+            print(patt.parse_string("AAB 123 321").dump())
+
+            # Use pop() in a parse action to remove named result (note that corresponding value is not
+            # removed from list form of results)
+            def remove_LABEL(tokens):
+                tokens.pop("LABEL")
+                return tokens
+            patt.add_parse_action(remove_LABEL)
+            print(patt.parse_string("AAB 123 321").dump())
+
+        prints::
+
+            ['AAB', '123', '321']
+            - LABEL: 'AAB'
+
+            ['AAB', '123', '321']
+        """
+        if not args:
+            args = [-1]
+        for k, v in kwargs.items():
+            if k == "default":
+                args = (args[0], v)
+            else:
+                raise TypeError(
+                    "pop() got an unexpected keyword argument {!r}".format(k)
+                )
+        if isinstance(args[0], int) or len(args) == 1 or args[0] in self:
+            index = args[0]
+            ret = self[index]
+            del self[index]
+            return ret
+        else:
+            defaultvalue = args[1]
+            return defaultvalue
+
+    def get(self, key, default_value=None):
+        """
+        Returns named result matching the given key, or if there is no
+        such name, then returns the given ``default_value`` or ``None`` if no
+        ``default_value`` is specified.
+
+        Similar to ``dict.get()``.
+
+        Example::
+
+            integer = Word(nums)
+            date_str = integer("year") + '/' + integer("month") + '/' + integer("day")
+
+            result = date_str.parse_string("1999/12/31")
+            print(result.get("year")) # -> '1999'
+            print(result.get("hour", "not specified")) # -> 'not specified'
+            print(result.get("hour")) # -> None
+        """
+        if key in self:
+            return self[key]
+        else:
+            return default_value
+
+    def insert(self, index, ins_string):
+        """
+        Inserts new element at location index in the list of parsed tokens.
+
+        Similar to ``list.insert()``.
+
+        Example::
+
+            numlist = Word(nums)[...]
+            print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321']
+
+            # use a parse action to insert the parse location in the front of the parsed results
+            def insert_locn(locn, tokens):
+                tokens.insert(0, locn)
+            numlist.add_parse_action(insert_locn)
+            print(numlist.parse_string("0 123 321")) # -> [0, '0', '123', '321']
+        """
+        self._toklist.insert(index, ins_string)
+        # fixup indices in token dictionary
+        for name, occurrences in self._tokdict.items():
+            for k, (value, position) in enumerate(occurrences):
+                occurrences[k] = _ParseResultsWithOffset(
+                    value, position + (position > index)
+                )
+
+    def append(self, item):
+        """
+        Add single element to end of ``ParseResults`` list of elements.
+
+        Example::
+
+            numlist = Word(nums)[...]
+            print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321']
+
+            # use a parse action to compute the sum of the parsed integers, and add it to the end
+            def append_sum(tokens):
+                tokens.append(sum(map(int, tokens)))
+            numlist.add_parse_action(append_sum)
+            print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321', 444]
+        """
+        self._toklist.append(item)
+
+    def extend(self, itemseq):
+        """
+        Add sequence of elements to end of ``ParseResults`` list of elements.
+
+        Example::
+
+            patt = Word(alphas)[1, ...]
+
+            # use a parse action to append the reverse of the matched strings, to make a palindrome
+            def make_palindrome(tokens):
+                tokens.extend(reversed([t[::-1] for t in tokens]))
+                return ''.join(tokens)
+            patt.add_parse_action(make_palindrome)
+            print(patt.parse_string("lskdj sdlkjf lksd")) # -> 'lskdjsdlkjflksddsklfjkldsjdksl'
+        """
+        if isinstance(itemseq, ParseResults):
+            self.__iadd__(itemseq)
+        else:
+            self._toklist.extend(itemseq)
+
+    def clear(self):
+        """
+        Clear all elements and results names.
+        """
+        del self._toklist[:]
+        self._tokdict.clear()
+
+    def __getattr__(self, name):
+        try:
+            return self[name]
+        except KeyError:
+            if name.startswith("__"):
+                raise AttributeError(name)
+            return ""
+
+    def __add__(self, other) -> "ParseResults":
+        ret = self.copy()
+        ret += other
+        return ret
+
+    def __iadd__(self, other) -> "ParseResults":
+        if other._tokdict:
+            offset = len(self._toklist)
+            addoffset = lambda a: offset if a < 0 else a + offset
+            otheritems = other._tokdict.items()
+            otherdictitems = [
+                (k, _ParseResultsWithOffset(v[0], addoffset(v[1])))
+                for k, vlist in otheritems
+                for v in vlist
+            ]
+            for k, v in otherdictitems:
+                self[k] = v
+                if isinstance(v[0], ParseResults):
+                    v[0]._parent = wkref(self)
+
+        self._toklist += other._toklist
+        self._all_names |= other._all_names
+        return self
+
+    def __radd__(self, other) -> "ParseResults":
+        if isinstance(other, int) and other == 0:
+            # useful for merging many ParseResults using sum() builtin
+            return self.copy()
+        else:
+            # this may raise a TypeError - so be it
+            return other + self
+
+    def __repr__(self) -> str:
+        return "{}({!r}, {})".format(type(self).__name__, self._toklist, self.as_dict())
+
+    def __str__(self) -> str:
+        return (
+            "["
+            + ", ".join(
+                [
+                    str(i) if isinstance(i, ParseResults) else repr(i)
+                    for i in self._toklist
+                ]
+            )
+            + "]"
+        )
+
+    def _asStringList(self, sep=""):
+        out = []
+        for item in self._toklist:
+            if out and sep:
+                out.append(sep)
+            if isinstance(item, ParseResults):
+                out += item._asStringList()
+            else:
+                out.append(str(item))
+        return out
+
+    def as_list(self) -> list:
+        """
+        Returns the parse results as a nested list of matching tokens, all converted to strings.
+
+        Example::
+
+            patt = Word(alphas)[1, ...]
+            result = patt.parse_string("sldkj lsdkj sldkj")
+            # even though the result prints in string-like form, it is actually a pyparsing ParseResults
+            print(type(result), result) # ->  ['sldkj', 'lsdkj', 'sldkj']
+
+            # Use as_list() to create an actual list
+            result_list = result.as_list()
+            print(type(result_list), result_list) # ->  ['sldkj', 'lsdkj', 'sldkj']
+        """
+        return [
+            res.as_list() if isinstance(res, ParseResults) else res
+            for res in self._toklist
+        ]
+
+    def as_dict(self) -> dict:
+        """
+        Returns the named parse results as a nested dictionary.
+
+        Example::
+
+            integer = Word(nums)
+            date_str = integer("year") + '/' + integer("month") + '/' + integer("day")
+
+            result = date_str.parse_string('12/31/1999')
+            print(type(result), repr(result)) # ->  (['12', '/', '31', '/', '1999'], {'day': [('1999', 4)], 'year': [('12', 0)], 'month': [('31', 2)]})
+
+            result_dict = result.as_dict()
+            print(type(result_dict), repr(result_dict)) # ->  {'day': '1999', 'year': '12', 'month': '31'}
+
+            # even though a ParseResults supports dict-like access, sometime you just need to have a dict
+            import json
+            print(json.dumps(result)) # -> Exception: TypeError: ... is not JSON serializable
+            print(json.dumps(result.as_dict())) # -> {"month": "31", "day": "1999", "year": "12"}
+        """
+
+        def to_item(obj):
+            if isinstance(obj, ParseResults):
+                return obj.as_dict() if obj.haskeys() else [to_item(v) for v in obj]
+            else:
+                return obj
+
+        return dict((k, to_item(v)) for k, v in self.items())
+
+    def copy(self) -> "ParseResults":
+        """
+        Returns a new copy of a :class:`ParseResults` object.
+        """
+        ret = ParseResults(self._toklist)
+        ret._tokdict = self._tokdict.copy()
+        ret._parent = self._parent
+        ret._all_names |= self._all_names
+        ret._name = self._name
+        return ret
+
+    def get_name(self):
+        r"""
+        Returns the results name for this token expression. Useful when several
+        different expressions might match at a particular location.
+
+        Example::
+
+            integer = Word(nums)
+            ssn_expr = Regex(r"\d\d\d-\d\d-\d\d\d\d")
+            house_number_expr = Suppress('#') + Word(nums, alphanums)
+            user_data = (Group(house_number_expr)("house_number")
+                        | Group(ssn_expr)("ssn")
+                        | Group(integer)("age"))
+            user_info = user_data[1, ...]
+
+            result = user_info.parse_string("22 111-22-3333 #221B")
+            for item in result:
+                print(item.get_name(), ':', item[0])
+
+        prints::
+
+            age : 22
+            ssn : 111-22-3333
+            house_number : 221B
+        """
+        if self._name:
+            return self._name
+        elif self._parent:
+            par = self._parent()
+
+            def find_in_parent(sub):
+                return next(
+                    (
+                        k
+                        for k, vlist in par._tokdict.items()
+                        for v, loc in vlist
+                        if sub is v
+                    ),
+                    None,
+                )
+
+            return find_in_parent(self) if par else None
+        elif (
+            len(self) == 1
+            and len(self._tokdict) == 1
+            and next(iter(self._tokdict.values()))[0][1] in (0, -1)
+        ):
+            return next(iter(self._tokdict.keys()))
+        else:
+            return None
+
+    def dump(self, indent="", full=True, include_list=True, _depth=0) -> str:
+        """
+        Diagnostic method for listing out the contents of
+        a :class:`ParseResults`. Accepts an optional ``indent`` argument so
+        that this string can be embedded in a nested display of other data.
+
+        Example::
+
+            integer = Word(nums)
+            date_str = integer("year") + '/' + integer("month") + '/' + integer("day")
+
+            result = date_str.parse_string('1999/12/31')
+            print(result.dump())
+
+        prints::
+
+            ['1999', '/', '12', '/', '31']
+            - day: '31'
+            - month: '12'
+            - year: '1999'
+        """
+        out = []
+        NL = "\n"
+        out.append(indent + str(self.as_list()) if include_list else "")
+
+        if full:
+            if self.haskeys():
+                items = sorted((str(k), v) for k, v in self.items())
+                for k, v in items:
+                    if out:
+                        out.append(NL)
+                    out.append("{}{}- {}: ".format(indent, ("  " * _depth), k))
+                    if isinstance(v, ParseResults):
+                        if v:
+                            out.append(
+                                v.dump(
+                                    indent=indent,
+                                    full=full,
+                                    include_list=include_list,
+                                    _depth=_depth + 1,
+                                )
+                            )
+                        else:
+                            out.append(str(v))
+                    else:
+                        out.append(repr(v))
+            if any(isinstance(vv, ParseResults) for vv in self):
+                v = self
+                for i, vv in enumerate(v):
+                    if isinstance(vv, ParseResults):
+                        out.append(
+                            "\n{}{}[{}]:\n{}{}{}".format(
+                                indent,
+                                ("  " * (_depth)),
+                                i,
+                                indent,
+                                ("  " * (_depth + 1)),
+                                vv.dump(
+                                    indent=indent,
+                                    full=full,
+                                    include_list=include_list,
+                                    _depth=_depth + 1,
+                                ),
+                            )
+                        )
+                    else:
+                        out.append(
+                            "\n%s%s[%d]:\n%s%s%s"
+                            % (
+                                indent,
+                                ("  " * (_depth)),
+                                i,
+                                indent,
+                                ("  " * (_depth + 1)),
+                                str(vv),
+                            )
+                        )
+
+        return "".join(out)
+
+    def pprint(self, *args, **kwargs):
+        """
+        Pretty-printer for parsed results as a list, using the
+        `pprint `_ module.
+        Accepts additional positional or keyword args as defined for
+        `pprint.pprint `_ .
+
+        Example::
+
+            ident = Word(alphas, alphanums)
+            num = Word(nums)
+            func = Forward()
+            term = ident | num | Group('(' + func + ')')
+            func <<= ident + Group(Optional(delimited_list(term)))
+            result = func.parse_string("fna a,b,(fnb c,d,200),100")
+            result.pprint(width=40)
+
+        prints::
+
+            ['fna',
+             ['a',
+              'b',
+              ['(', 'fnb', ['c', 'd', '200'], ')'],
+              '100']]
+        """
+        pprint.pprint(self.as_list(), *args, **kwargs)
+
+    # add support for pickle protocol
+    def __getstate__(self):
+        return (
+            self._toklist,
+            (
+                self._tokdict.copy(),
+                self._parent is not None and self._parent() or None,
+                self._all_names,
+                self._name,
+            ),
+        )
+
+    def __setstate__(self, state):
+        self._toklist, (self._tokdict, par, inAccumNames, self._name) = state
+        self._all_names = set(inAccumNames)
+        if par is not None:
+            self._parent = wkref(par)
+        else:
+            self._parent = None
+
+    def __getnewargs__(self):
+        return self._toklist, self._name
+
+    def __dir__(self):
+        return dir(type(self)) + list(self.keys())
+
+    @classmethod
+    def from_dict(cls, other, name=None) -> "ParseResults":
+        """
+        Helper classmethod to construct a ``ParseResults`` from a ``dict``, preserving the
+        name-value relations as results names. If an optional ``name`` argument is
+        given, a nested ``ParseResults`` will be returned.
+        """
+
+        def is_iterable(obj):
+            try:
+                iter(obj)
+            except Exception:
+                return False
+            else:
+                return not isinstance(obj, str_type)
+
+        ret = cls([])
+        for k, v in other.items():
+            if isinstance(v, Mapping):
+                ret += cls.from_dict(v, name=k)
+            else:
+                ret += cls([v], name=k, asList=is_iterable(v))
+        if name is not None:
+            ret = cls([ret], name=name)
+        return ret
+
+    asList = as_list
+    asDict = as_dict
+    getName = get_name
+
+
+MutableMapping.register(ParseResults)
+MutableSequence.register(ParseResults)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/testing.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/testing.py
new file mode 100644
index 0000000000000000000000000000000000000000..84a0ef17078c99e5917db41e3dbaf035fe206d7c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/testing.py
@@ -0,0 +1,331 @@
+# testing.py
+
+from contextlib import contextmanager
+import typing
+
+from .core import (
+    ParserElement,
+    ParseException,
+    Keyword,
+    __diag__,
+    __compat__,
+)
+
+
+class pyparsing_test:
+    """
+    namespace class for classes useful in writing unit tests
+    """
+
+    class reset_pyparsing_context:
+        """
+        Context manager to be used when writing unit tests that modify pyparsing config values:
+        - packrat parsing
+        - bounded recursion parsing
+        - default whitespace characters.
+        - default keyword characters
+        - literal string auto-conversion class
+        - __diag__ settings
+
+        Example::
+
+            with reset_pyparsing_context():
+                # test that literals used to construct a grammar are automatically suppressed
+                ParserElement.inlineLiteralsUsing(Suppress)
+
+                term = Word(alphas) | Word(nums)
+                group = Group('(' + term[...] + ')')
+
+                # assert that the '()' characters are not included in the parsed tokens
+                self.assertParseAndCheckList(group, "(abc 123 def)", ['abc', '123', 'def'])
+
+            # after exiting context manager, literals are converted to Literal expressions again
+        """
+
+        def __init__(self):
+            self._save_context = {}
+
+        def save(self):
+            self._save_context["default_whitespace"] = ParserElement.DEFAULT_WHITE_CHARS
+            self._save_context["default_keyword_chars"] = Keyword.DEFAULT_KEYWORD_CHARS
+
+            self._save_context[
+                "literal_string_class"
+            ] = ParserElement._literalStringClass
+
+            self._save_context["verbose_stacktrace"] = ParserElement.verbose_stacktrace
+
+            self._save_context["packrat_enabled"] = ParserElement._packratEnabled
+            if ParserElement._packratEnabled:
+                self._save_context[
+                    "packrat_cache_size"
+                ] = ParserElement.packrat_cache.size
+            else:
+                self._save_context["packrat_cache_size"] = None
+            self._save_context["packrat_parse"] = ParserElement._parse
+            self._save_context[
+                "recursion_enabled"
+            ] = ParserElement._left_recursion_enabled
+
+            self._save_context["__diag__"] = {
+                name: getattr(__diag__, name) for name in __diag__._all_names
+            }
+
+            self._save_context["__compat__"] = {
+                "collect_all_And_tokens": __compat__.collect_all_And_tokens
+            }
+
+            return self
+
+        def restore(self):
+            # reset pyparsing global state
+            if (
+                ParserElement.DEFAULT_WHITE_CHARS
+                != self._save_context["default_whitespace"]
+            ):
+                ParserElement.set_default_whitespace_chars(
+                    self._save_context["default_whitespace"]
+                )
+
+            ParserElement.verbose_stacktrace = self._save_context["verbose_stacktrace"]
+
+            Keyword.DEFAULT_KEYWORD_CHARS = self._save_context["default_keyword_chars"]
+            ParserElement.inlineLiteralsUsing(
+                self._save_context["literal_string_class"]
+            )
+
+            for name, value in self._save_context["__diag__"].items():
+                (__diag__.enable if value else __diag__.disable)(name)
+
+            ParserElement._packratEnabled = False
+            if self._save_context["packrat_enabled"]:
+                ParserElement.enable_packrat(self._save_context["packrat_cache_size"])
+            else:
+                ParserElement._parse = self._save_context["packrat_parse"]
+            ParserElement._left_recursion_enabled = self._save_context[
+                "recursion_enabled"
+            ]
+
+            __compat__.collect_all_And_tokens = self._save_context["__compat__"]
+
+            return self
+
+        def copy(self):
+            ret = type(self)()
+            ret._save_context.update(self._save_context)
+            return ret
+
+        def __enter__(self):
+            return self.save()
+
+        def __exit__(self, *args):
+            self.restore()
+
+    class TestParseResultsAsserts:
+        """
+        A mixin class to add parse results assertion methods to normal unittest.TestCase classes.
+        """
+
+        def assertParseResultsEquals(
+            self, result, expected_list=None, expected_dict=None, msg=None
+        ):
+            """
+            Unit test assertion to compare a :class:`ParseResults` object with an optional ``expected_list``,
+            and compare any defined results names with an optional ``expected_dict``.
+            """
+            if expected_list is not None:
+                self.assertEqual(expected_list, result.as_list(), msg=msg)
+            if expected_dict is not None:
+                self.assertEqual(expected_dict, result.as_dict(), msg=msg)
+
+        def assertParseAndCheckList(
+            self, expr, test_string, expected_list, msg=None, verbose=True
+        ):
+            """
+            Convenience wrapper assert to test a parser element and input string, and assert that
+            the resulting ``ParseResults.asList()`` is equal to the ``expected_list``.
+            """
+            result = expr.parse_string(test_string, parse_all=True)
+            if verbose:
+                print(result.dump())
+            else:
+                print(result.as_list())
+            self.assertParseResultsEquals(result, expected_list=expected_list, msg=msg)
+
+        def assertParseAndCheckDict(
+            self, expr, test_string, expected_dict, msg=None, verbose=True
+        ):
+            """
+            Convenience wrapper assert to test a parser element and input string, and assert that
+            the resulting ``ParseResults.asDict()`` is equal to the ``expected_dict``.
+            """
+            result = expr.parse_string(test_string, parseAll=True)
+            if verbose:
+                print(result.dump())
+            else:
+                print(result.as_list())
+            self.assertParseResultsEquals(result, expected_dict=expected_dict, msg=msg)
+
+        def assertRunTestResults(
+            self, run_tests_report, expected_parse_results=None, msg=None
+        ):
+            """
+            Unit test assertion to evaluate output of ``ParserElement.runTests()``. If a list of
+            list-dict tuples is given as the ``expected_parse_results`` argument, then these are zipped
+            with the report tuples returned by ``runTests`` and evaluated using ``assertParseResultsEquals``.
+            Finally, asserts that the overall ``runTests()`` success value is ``True``.
+
+            :param run_tests_report: tuple(bool, [tuple(str, ParseResults or Exception)]) returned from runTests
+            :param expected_parse_results (optional): [tuple(str, list, dict, Exception)]
+            """
+            run_test_success, run_test_results = run_tests_report
+
+            if expected_parse_results is not None:
+                merged = [
+                    (*rpt, expected)
+                    for rpt, expected in zip(run_test_results, expected_parse_results)
+                ]
+                for test_string, result, expected in merged:
+                    # expected should be a tuple containing a list and/or a dict or an exception,
+                    # and optional failure message string
+                    # an empty tuple will skip any result validation
+                    fail_msg = next(
+                        (exp for exp in expected if isinstance(exp, str)), None
+                    )
+                    expected_exception = next(
+                        (
+                            exp
+                            for exp in expected
+                            if isinstance(exp, type) and issubclass(exp, Exception)
+                        ),
+                        None,
+                    )
+                    if expected_exception is not None:
+                        with self.assertRaises(
+                            expected_exception=expected_exception, msg=fail_msg or msg
+                        ):
+                            if isinstance(result, Exception):
+                                raise result
+                    else:
+                        expected_list = next(
+                            (exp for exp in expected if isinstance(exp, list)), None
+                        )
+                        expected_dict = next(
+                            (exp for exp in expected if isinstance(exp, dict)), None
+                        )
+                        if (expected_list, expected_dict) != (None, None):
+                            self.assertParseResultsEquals(
+                                result,
+                                expected_list=expected_list,
+                                expected_dict=expected_dict,
+                                msg=fail_msg or msg,
+                            )
+                        else:
+                            # warning here maybe?
+                            print("no validation for {!r}".format(test_string))
+
+            # do this last, in case some specific test results can be reported instead
+            self.assertTrue(
+                run_test_success, msg=msg if msg is not None else "failed runTests"
+            )
+
+        @contextmanager
+        def assertRaisesParseException(self, exc_type=ParseException, msg=None):
+            with self.assertRaises(exc_type, msg=msg):
+                yield
+
+    @staticmethod
+    def with_line_numbers(
+        s: str,
+        start_line: typing.Optional[int] = None,
+        end_line: typing.Optional[int] = None,
+        expand_tabs: bool = True,
+        eol_mark: str = "|",
+        mark_spaces: typing.Optional[str] = None,
+        mark_control: typing.Optional[str] = None,
+    ) -> str:
+        """
+        Helpful method for debugging a parser - prints a string with line and column numbers.
+        (Line and column numbers are 1-based.)
+
+        :param s: tuple(bool, str - string to be printed with line and column numbers
+        :param start_line: int - (optional) starting line number in s to print (default=1)
+        :param end_line: int - (optional) ending line number in s to print (default=len(s))
+        :param expand_tabs: bool - (optional) expand tabs to spaces, to match the pyparsing default
+        :param eol_mark: str - (optional) string to mark the end of lines, helps visualize trailing spaces (default="|")
+        :param mark_spaces: str - (optional) special character to display in place of spaces
+        :param mark_control: str - (optional) convert non-printing control characters to a placeholding
+                                 character; valid values:
+                                 - "unicode" - replaces control chars with Unicode symbols, such as "␍" and "␊"
+                                 - any single character string - replace control characters with given string
+                                 - None (default) - string is displayed as-is
+
+        :return: str - input string with leading line numbers and column number headers
+        """
+        if expand_tabs:
+            s = s.expandtabs()
+        if mark_control is not None:
+            if mark_control == "unicode":
+                tbl = str.maketrans(
+                    {c: u for c, u in zip(range(0, 33), range(0x2400, 0x2433))}
+                    | {127: 0x2421}
+                )
+                eol_mark = ""
+            else:
+                tbl = str.maketrans(
+                    {c: mark_control for c in list(range(0, 32)) + [127]}
+                )
+            s = s.translate(tbl)
+        if mark_spaces is not None and mark_spaces != " ":
+            if mark_spaces == "unicode":
+                tbl = str.maketrans({9: 0x2409, 32: 0x2423})
+                s = s.translate(tbl)
+            else:
+                s = s.replace(" ", mark_spaces)
+        if start_line is None:
+            start_line = 1
+        if end_line is None:
+            end_line = len(s)
+        end_line = min(end_line, len(s))
+        start_line = min(max(1, start_line), end_line)
+
+        if mark_control != "unicode":
+            s_lines = s.splitlines()[start_line - 1 : end_line]
+        else:
+            s_lines = [line + "␊" for line in s.split("␊")[start_line - 1 : end_line]]
+        if not s_lines:
+            return ""
+
+        lineno_width = len(str(end_line))
+        max_line_len = max(len(line) for line in s_lines)
+        lead = " " * (lineno_width + 1)
+        if max_line_len >= 99:
+            header0 = (
+                lead
+                + "".join(
+                    "{}{}".format(" " * 99, (i + 1) % 100)
+                    for i in range(max(max_line_len // 100, 1))
+                )
+                + "\n"
+            )
+        else:
+            header0 = ""
+        header1 = (
+            header0
+            + lead
+            + "".join(
+                "         {}".format((i + 1) % 10)
+                for i in range(-(-max_line_len // 10))
+            )
+            + "\n"
+        )
+        header2 = lead + "1234567890" * (-(-max_line_len // 10)) + "\n"
+        return (
+            header1
+            + header2
+            + "\n".join(
+                "{:{}d}:{}{}".format(i, lineno_width, line, eol_mark)
+                for i, line in enumerate(s_lines, start=start_line)
+            )
+            + "\n"
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/unicode.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/unicode.py
new file mode 100644
index 0000000000000000000000000000000000000000..06526203911de55da3c2a8c5ae73f48024c3f018
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/unicode.py
@@ -0,0 +1,352 @@
+# unicode.py
+
+import sys
+from itertools import filterfalse
+from typing import List, Tuple, Union
+
+
+class _lazyclassproperty:
+    def __init__(self, fn):
+        self.fn = fn
+        self.__doc__ = fn.__doc__
+        self.__name__ = fn.__name__
+
+    def __get__(self, obj, cls):
+        if cls is None:
+            cls = type(obj)
+        if not hasattr(cls, "_intern") or any(
+            cls._intern is getattr(superclass, "_intern", [])
+            for superclass in cls.__mro__[1:]
+        ):
+            cls._intern = {}
+        attrname = self.fn.__name__
+        if attrname not in cls._intern:
+            cls._intern[attrname] = self.fn(cls)
+        return cls._intern[attrname]
+
+
+UnicodeRangeList = List[Union[Tuple[int, int], Tuple[int]]]
+
+
+class unicode_set:
+    """
+    A set of Unicode characters, for language-specific strings for
+    ``alphas``, ``nums``, ``alphanums``, and ``printables``.
+    A unicode_set is defined by a list of ranges in the Unicode character
+    set, in a class attribute ``_ranges``. Ranges can be specified using
+    2-tuples or a 1-tuple, such as::
+
+        _ranges = [
+            (0x0020, 0x007e),
+            (0x00a0, 0x00ff),
+            (0x0100,),
+            ]
+
+    Ranges are left- and right-inclusive. A 1-tuple of (x,) is treated as (x, x).
+
+    A unicode set can also be defined using multiple inheritance of other unicode sets::
+
+        class CJK(Chinese, Japanese, Korean):
+            pass
+    """
+
+    _ranges: UnicodeRangeList = []
+
+    @_lazyclassproperty
+    def _chars_for_ranges(cls):
+        ret = []
+        for cc in cls.__mro__:
+            if cc is unicode_set:
+                break
+            for rr in getattr(cc, "_ranges", ()):
+                ret.extend(range(rr[0], rr[-1] + 1))
+        return [chr(c) for c in sorted(set(ret))]
+
+    @_lazyclassproperty
+    def printables(cls):
+        "all non-whitespace characters in this range"
+        return "".join(filterfalse(str.isspace, cls._chars_for_ranges))
+
+    @_lazyclassproperty
+    def alphas(cls):
+        "all alphabetic characters in this range"
+        return "".join(filter(str.isalpha, cls._chars_for_ranges))
+
+    @_lazyclassproperty
+    def nums(cls):
+        "all numeric digit characters in this range"
+        return "".join(filter(str.isdigit, cls._chars_for_ranges))
+
+    @_lazyclassproperty
+    def alphanums(cls):
+        "all alphanumeric characters in this range"
+        return cls.alphas + cls.nums
+
+    @_lazyclassproperty
+    def identchars(cls):
+        "all characters in this range that are valid identifier characters, plus underscore '_'"
+        return "".join(
+            sorted(
+                set(
+                    "".join(filter(str.isidentifier, cls._chars_for_ranges))
+                    + "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzªµº"
+                    + "ÀÁÂÃÄÅÆÇÈÉÊËÌÍÎÏÐÑÒÓÔÕÖØÙÚÛÜÝÞßàáâãäåæçèéêëìíîïðñòóôõöøùúûüýþÿ"
+                    + "_"
+                )
+            )
+        )
+
+    @_lazyclassproperty
+    def identbodychars(cls):
+        """
+        all characters in this range that are valid identifier body characters,
+        plus the digits 0-9
+        """
+        return "".join(
+            sorted(
+                set(
+                    cls.identchars
+                    + "0123456789"
+                    + "".join(
+                        [c for c in cls._chars_for_ranges if ("_" + c).isidentifier()]
+                    )
+                )
+            )
+        )
+
+
+class pyparsing_unicode(unicode_set):
+    """
+    A namespace class for defining common language unicode_sets.
+    """
+
+    # fmt: off
+
+    # define ranges in language character sets
+    _ranges: UnicodeRangeList = [
+        (0x0020, sys.maxunicode),
+    ]
+
+    class BasicMultilingualPlane(unicode_set):
+        "Unicode set for the Basic Multilingual Plane"
+        _ranges: UnicodeRangeList = [
+            (0x0020, 0xFFFF),
+        ]
+
+    class Latin1(unicode_set):
+        "Unicode set for Latin-1 Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0020, 0x007E),
+            (0x00A0, 0x00FF),
+        ]
+
+    class LatinA(unicode_set):
+        "Unicode set for Latin-A Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0100, 0x017F),
+        ]
+
+    class LatinB(unicode_set):
+        "Unicode set for Latin-B Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0180, 0x024F),
+        ]
+
+    class Greek(unicode_set):
+        "Unicode set for Greek Unicode Character Ranges"
+        _ranges: UnicodeRangeList = [
+            (0x0342, 0x0345),
+            (0x0370, 0x0377),
+            (0x037A, 0x037F),
+            (0x0384, 0x038A),
+            (0x038C,),
+            (0x038E, 0x03A1),
+            (0x03A3, 0x03E1),
+            (0x03F0, 0x03FF),
+            (0x1D26, 0x1D2A),
+            (0x1D5E,),
+            (0x1D60,),
+            (0x1D66, 0x1D6A),
+            (0x1F00, 0x1F15),
+            (0x1F18, 0x1F1D),
+            (0x1F20, 0x1F45),
+            (0x1F48, 0x1F4D),
+            (0x1F50, 0x1F57),
+            (0x1F59,),
+            (0x1F5B,),
+            (0x1F5D,),
+            (0x1F5F, 0x1F7D),
+            (0x1F80, 0x1FB4),
+            (0x1FB6, 0x1FC4),
+            (0x1FC6, 0x1FD3),
+            (0x1FD6, 0x1FDB),
+            (0x1FDD, 0x1FEF),
+            (0x1FF2, 0x1FF4),
+            (0x1FF6, 0x1FFE),
+            (0x2129,),
+            (0x2719, 0x271A),
+            (0xAB65,),
+            (0x10140, 0x1018D),
+            (0x101A0,),
+            (0x1D200, 0x1D245),
+            (0x1F7A1, 0x1F7A7),
+        ]
+
+    class Cyrillic(unicode_set):
+        "Unicode set for Cyrillic Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0400, 0x052F),
+            (0x1C80, 0x1C88),
+            (0x1D2B,),
+            (0x1D78,),
+            (0x2DE0, 0x2DFF),
+            (0xA640, 0xA672),
+            (0xA674, 0xA69F),
+            (0xFE2E, 0xFE2F),
+        ]
+
+    class Chinese(unicode_set):
+        "Unicode set for Chinese Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x2E80, 0x2E99),
+            (0x2E9B, 0x2EF3),
+            (0x31C0, 0x31E3),
+            (0x3400, 0x4DB5),
+            (0x4E00, 0x9FEF),
+            (0xA700, 0xA707),
+            (0xF900, 0xFA6D),
+            (0xFA70, 0xFAD9),
+            (0x16FE2, 0x16FE3),
+            (0x1F210, 0x1F212),
+            (0x1F214, 0x1F23B),
+            (0x1F240, 0x1F248),
+            (0x20000, 0x2A6D6),
+            (0x2A700, 0x2B734),
+            (0x2B740, 0x2B81D),
+            (0x2B820, 0x2CEA1),
+            (0x2CEB0, 0x2EBE0),
+            (0x2F800, 0x2FA1D),
+        ]
+
+    class Japanese(unicode_set):
+        "Unicode set for Japanese Unicode Character Range, combining Kanji, Hiragana, and Katakana ranges"
+        _ranges: UnicodeRangeList = []
+
+        class Kanji(unicode_set):
+            "Unicode set for Kanji Unicode Character Range"
+            _ranges: UnicodeRangeList = [
+                (0x4E00, 0x9FBF),
+                (0x3000, 0x303F),
+            ]
+
+        class Hiragana(unicode_set):
+            "Unicode set for Hiragana Unicode Character Range"
+            _ranges: UnicodeRangeList = [
+                (0x3041, 0x3096),
+                (0x3099, 0x30A0),
+                (0x30FC,),
+                (0xFF70,),
+                (0x1B001,),
+                (0x1B150, 0x1B152),
+                (0x1F200,),
+            ]
+
+        class Katakana(unicode_set):
+            "Unicode set for Katakana  Unicode Character Range"
+            _ranges: UnicodeRangeList = [
+                (0x3099, 0x309C),
+                (0x30A0, 0x30FF),
+                (0x31F0, 0x31FF),
+                (0x32D0, 0x32FE),
+                (0xFF65, 0xFF9F),
+                (0x1B000,),
+                (0x1B164, 0x1B167),
+                (0x1F201, 0x1F202),
+                (0x1F213,),
+            ]
+
+    class Hangul(unicode_set):
+        "Unicode set for Hangul (Korean) Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x1100, 0x11FF),
+            (0x302E, 0x302F),
+            (0x3131, 0x318E),
+            (0x3200, 0x321C),
+            (0x3260, 0x327B),
+            (0x327E,),
+            (0xA960, 0xA97C),
+            (0xAC00, 0xD7A3),
+            (0xD7B0, 0xD7C6),
+            (0xD7CB, 0xD7FB),
+            (0xFFA0, 0xFFBE),
+            (0xFFC2, 0xFFC7),
+            (0xFFCA, 0xFFCF),
+            (0xFFD2, 0xFFD7),
+            (0xFFDA, 0xFFDC),
+        ]
+
+    Korean = Hangul
+
+    class CJK(Chinese, Japanese, Hangul):
+        "Unicode set for combined Chinese, Japanese, and Korean (CJK) Unicode Character Range"
+
+    class Thai(unicode_set):
+        "Unicode set for Thai Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0E01, 0x0E3A),
+            (0x0E3F, 0x0E5B)
+        ]
+
+    class Arabic(unicode_set):
+        "Unicode set for Arabic Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0600, 0x061B),
+            (0x061E, 0x06FF),
+            (0x0700, 0x077F),
+        ]
+
+    class Hebrew(unicode_set):
+        "Unicode set for Hebrew Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0591, 0x05C7),
+            (0x05D0, 0x05EA),
+            (0x05EF, 0x05F4),
+            (0xFB1D, 0xFB36),
+            (0xFB38, 0xFB3C),
+            (0xFB3E,),
+            (0xFB40, 0xFB41),
+            (0xFB43, 0xFB44),
+            (0xFB46, 0xFB4F),
+        ]
+
+    class Devanagari(unicode_set):
+        "Unicode set for Devanagari Unicode Character Range"
+        _ranges: UnicodeRangeList = [
+            (0x0900, 0x097F),
+            (0xA8E0, 0xA8FF)
+        ]
+
+    # fmt: on
+
+
+pyparsing_unicode.Japanese._ranges = (
+    pyparsing_unicode.Japanese.Kanji._ranges
+    + pyparsing_unicode.Japanese.Hiragana._ranges
+    + pyparsing_unicode.Japanese.Katakana._ranges
+)
+
+pyparsing_unicode.BMP = pyparsing_unicode.BasicMultilingualPlane
+
+# add language identifiers using language Unicode
+pyparsing_unicode.العربية = pyparsing_unicode.Arabic
+pyparsing_unicode.中文 = pyparsing_unicode.Chinese
+pyparsing_unicode.кириллица = pyparsing_unicode.Cyrillic
+pyparsing_unicode.Ελληνικά = pyparsing_unicode.Greek
+pyparsing_unicode.עִברִית = pyparsing_unicode.Hebrew
+pyparsing_unicode.日本語 = pyparsing_unicode.Japanese
+pyparsing_unicode.Japanese.漢字 = pyparsing_unicode.Japanese.Kanji
+pyparsing_unicode.Japanese.カタカナ = pyparsing_unicode.Japanese.Katakana
+pyparsing_unicode.Japanese.ひらがな = pyparsing_unicode.Japanese.Hiragana
+pyparsing_unicode.한국어 = pyparsing_unicode.Korean
+pyparsing_unicode.ไทย = pyparsing_unicode.Thai
+pyparsing_unicode.देवनागरी = pyparsing_unicode.Devanagari
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/util.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/util.py
new file mode 100644
index 0000000000000000000000000000000000000000..34ce092c6d08d9cdc2704840b7539de7b5ae1dcc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyparsing/util.py
@@ -0,0 +1,235 @@
+# util.py
+import warnings
+import types
+import collections
+import itertools
+from functools import lru_cache
+from typing import List, Union, Iterable
+
+_bslash = chr(92)
+
+
+class __config_flags:
+    """Internal class for defining compatibility and debugging flags"""
+
+    _all_names: List[str] = []
+    _fixed_names: List[str] = []
+    _type_desc = "configuration"
+
+    @classmethod
+    def _set(cls, dname, value):
+        if dname in cls._fixed_names:
+            warnings.warn(
+                "{}.{} {} is {} and cannot be overridden".format(
+                    cls.__name__,
+                    dname,
+                    cls._type_desc,
+                    str(getattr(cls, dname)).upper(),
+                )
+            )
+            return
+        if dname in cls._all_names:
+            setattr(cls, dname, value)
+        else:
+            raise ValueError("no such {} {!r}".format(cls._type_desc, dname))
+
+    enable = classmethod(lambda cls, name: cls._set(name, True))
+    disable = classmethod(lambda cls, name: cls._set(name, False))
+
+
+@lru_cache(maxsize=128)
+def col(loc: int, strg: str) -> int:
+    """
+    Returns current column within a string, counting newlines as line separators.
+    The first column is number 1.
+
+    Note: the default parsing behavior is to expand tabs in the input string
+    before starting the parsing process.  See
+    :class:`ParserElement.parseString` for more
+    information on parsing strings containing ```` s, and suggested
+    methods to maintain a consistent view of the parsed string, the parse
+    location, and line and column positions within the parsed string.
+    """
+    s = strg
+    return 1 if 0 < loc < len(s) and s[loc - 1] == "\n" else loc - s.rfind("\n", 0, loc)
+
+
+@lru_cache(maxsize=128)
+def lineno(loc: int, strg: str) -> int:
+    """Returns current line number within a string, counting newlines as line separators.
+    The first line is number 1.
+
+    Note - the default parsing behavior is to expand tabs in the input string
+    before starting the parsing process.  See :class:`ParserElement.parseString`
+    for more information on parsing strings containing ```` s, and
+    suggested methods to maintain a consistent view of the parsed string, the
+    parse location, and line and column positions within the parsed string.
+    """
+    return strg.count("\n", 0, loc) + 1
+
+
+@lru_cache(maxsize=128)
+def line(loc: int, strg: str) -> str:
+    """
+    Returns the line of text containing loc within a string, counting newlines as line separators.
+    """
+    last_cr = strg.rfind("\n", 0, loc)
+    next_cr = strg.find("\n", loc)
+    return strg[last_cr + 1 : next_cr] if next_cr >= 0 else strg[last_cr + 1 :]
+
+
+class _UnboundedCache:
+    def __init__(self):
+        cache = {}
+        cache_get = cache.get
+        self.not_in_cache = not_in_cache = object()
+
+        def get(_, key):
+            return cache_get(key, not_in_cache)
+
+        def set_(_, key, value):
+            cache[key] = value
+
+        def clear(_):
+            cache.clear()
+
+        self.size = None
+        self.get = types.MethodType(get, self)
+        self.set = types.MethodType(set_, self)
+        self.clear = types.MethodType(clear, self)
+
+
+class _FifoCache:
+    def __init__(self, size):
+        self.not_in_cache = not_in_cache = object()
+        cache = collections.OrderedDict()
+        cache_get = cache.get
+
+        def get(_, key):
+            return cache_get(key, not_in_cache)
+
+        def set_(_, key, value):
+            cache[key] = value
+            while len(cache) > size:
+                cache.popitem(last=False)
+
+        def clear(_):
+            cache.clear()
+
+        self.size = size
+        self.get = types.MethodType(get, self)
+        self.set = types.MethodType(set_, self)
+        self.clear = types.MethodType(clear, self)
+
+
+class LRUMemo:
+    """
+    A memoizing mapping that retains `capacity` deleted items
+
+    The memo tracks retained items by their access order; once `capacity` items
+    are retained, the least recently used item is discarded.
+    """
+
+    def __init__(self, capacity):
+        self._capacity = capacity
+        self._active = {}
+        self._memory = collections.OrderedDict()
+
+    def __getitem__(self, key):
+        try:
+            return self._active[key]
+        except KeyError:
+            self._memory.move_to_end(key)
+            return self._memory[key]
+
+    def __setitem__(self, key, value):
+        self._memory.pop(key, None)
+        self._active[key] = value
+
+    def __delitem__(self, key):
+        try:
+            value = self._active.pop(key)
+        except KeyError:
+            pass
+        else:
+            while len(self._memory) >= self._capacity:
+                self._memory.popitem(last=False)
+            self._memory[key] = value
+
+    def clear(self):
+        self._active.clear()
+        self._memory.clear()
+
+
+class UnboundedMemo(dict):
+    """
+    A memoizing mapping that retains all deleted items
+    """
+
+    def __delitem__(self, key):
+        pass
+
+
+def _escape_regex_range_chars(s: str) -> str:
+    # escape these chars: ^-[]
+    for c in r"\^-[]":
+        s = s.replace(c, _bslash + c)
+    s = s.replace("\n", r"\n")
+    s = s.replace("\t", r"\t")
+    return str(s)
+
+
+def _collapse_string_to_ranges(
+    s: Union[str, Iterable[str]], re_escape: bool = True
+) -> str:
+    def is_consecutive(c):
+        c_int = ord(c)
+        is_consecutive.prev, prev = c_int, is_consecutive.prev
+        if c_int - prev > 1:
+            is_consecutive.value = next(is_consecutive.counter)
+        return is_consecutive.value
+
+    is_consecutive.prev = 0
+    is_consecutive.counter = itertools.count()
+    is_consecutive.value = -1
+
+    def escape_re_range_char(c):
+        return "\\" + c if c in r"\^-][" else c
+
+    def no_escape_re_range_char(c):
+        return c
+
+    if not re_escape:
+        escape_re_range_char = no_escape_re_range_char
+
+    ret = []
+    s = "".join(sorted(set(s)))
+    if len(s) > 3:
+        for _, chars in itertools.groupby(s, key=is_consecutive):
+            first = last = next(chars)
+            last = collections.deque(
+                itertools.chain(iter([last]), chars), maxlen=1
+            ).pop()
+            if first == last:
+                ret.append(escape_re_range_char(first))
+            else:
+                sep = "" if ord(last) == ord(first) + 1 else "-"
+                ret.append(
+                    "{}{}{}".format(
+                        escape_re_range_char(first), sep, escape_re_range_char(last)
+                    )
+                )
+    else:
+        ret = [escape_re_range_char(c) for c in s]
+
+    return "".join(ret)
+
+
+def _flatten(ll: list) -> list:
+    ret = []
+    for i in ll:
+        if isinstance(i, list):
+            ret.extend(_flatten(i))
+        else:
+            ret.append(i)
+    return ret
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ddfcf7f72f31658d75c8128de0732fbbf0e12b15
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/__init__.py
@@ -0,0 +1,23 @@
+"""Wrappers to call pyproject.toml-based build backend hooks.
+"""
+
+from ._impl import (
+    BackendInvalid,
+    BackendUnavailable,
+    BuildBackendHookCaller,
+    HookMissing,
+    UnsupportedOperation,
+    default_subprocess_runner,
+    quiet_subprocess_runner,
+)
+
+__version__ = '1.0.0'
+__all__ = [
+    'BackendUnavailable',
+    'BackendInvalid',
+    'HookMissing',
+    'UnsupportedOperation',
+    'default_subprocess_runner',
+    'quiet_subprocess_runner',
+    'BuildBackendHookCaller',
+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..95e509c0143e14e6371ec3cd1433ffec50c297fc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_compat.py
@@ -0,0 +1,8 @@
+__all__ = ("tomllib",)
+
+import sys
+
+if sys.version_info >= (3, 11):
+    import tomllib
+else:
+    from pip._vendor import tomli as tomllib
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_impl.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..37b0e6531f1544e1ba9b5895c48939fc97441ce7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_impl.py
@@ -0,0 +1,330 @@
+import json
+import os
+import sys
+import tempfile
+from contextlib import contextmanager
+from os.path import abspath
+from os.path import join as pjoin
+from subprocess import STDOUT, check_call, check_output
+
+from ._in_process import _in_proc_script_path
+
+
+def write_json(obj, path, **kwargs):
+    with open(path, 'w', encoding='utf-8') as f:
+        json.dump(obj, f, **kwargs)
+
+
+def read_json(path):
+    with open(path, encoding='utf-8') as f:
+        return json.load(f)
+
+
+class BackendUnavailable(Exception):
+    """Will be raised if the backend cannot be imported in the hook process."""
+    def __init__(self, traceback):
+        self.traceback = traceback
+
+
+class BackendInvalid(Exception):
+    """Will be raised if the backend is invalid."""
+    def __init__(self, backend_name, backend_path, message):
+        super().__init__(message)
+        self.backend_name = backend_name
+        self.backend_path = backend_path
+
+
+class HookMissing(Exception):
+    """Will be raised on missing hooks (if a fallback can't be used)."""
+    def __init__(self, hook_name):
+        super().__init__(hook_name)
+        self.hook_name = hook_name
+
+
+class UnsupportedOperation(Exception):
+    """May be raised by build_sdist if the backend indicates that it can't."""
+    def __init__(self, traceback):
+        self.traceback = traceback
+
+
+def default_subprocess_runner(cmd, cwd=None, extra_environ=None):
+    """The default method of calling the wrapper subprocess.
+
+    This uses :func:`subprocess.check_call` under the hood.
+    """
+    env = os.environ.copy()
+    if extra_environ:
+        env.update(extra_environ)
+
+    check_call(cmd, cwd=cwd, env=env)
+
+
+def quiet_subprocess_runner(cmd, cwd=None, extra_environ=None):
+    """Call the subprocess while suppressing output.
+
+    This uses :func:`subprocess.check_output` under the hood.
+    """
+    env = os.environ.copy()
+    if extra_environ:
+        env.update(extra_environ)
+
+    check_output(cmd, cwd=cwd, env=env, stderr=STDOUT)
+
+
+def norm_and_check(source_tree, requested):
+    """Normalise and check a backend path.
+
+    Ensure that the requested backend path is specified as a relative path,
+    and resolves to a location under the given source tree.
+
+    Return an absolute version of the requested path.
+    """
+    if os.path.isabs(requested):
+        raise ValueError("paths must be relative")
+
+    abs_source = os.path.abspath(source_tree)
+    abs_requested = os.path.normpath(os.path.join(abs_source, requested))
+    # We have to use commonprefix for Python 2.7 compatibility. So we
+    # normalise case to avoid problems because commonprefix is a character
+    # based comparison :-(
+    norm_source = os.path.normcase(abs_source)
+    norm_requested = os.path.normcase(abs_requested)
+    if os.path.commonprefix([norm_source, norm_requested]) != norm_source:
+        raise ValueError("paths must be inside source tree")
+
+    return abs_requested
+
+
+class BuildBackendHookCaller:
+    """A wrapper to call the build backend hooks for a source directory.
+    """
+
+    def __init__(
+            self,
+            source_dir,
+            build_backend,
+            backend_path=None,
+            runner=None,
+            python_executable=None,
+    ):
+        """
+        :param source_dir: The source directory to invoke the build backend for
+        :param build_backend: The build backend spec
+        :param backend_path: Additional path entries for the build backend spec
+        :param runner: The :ref:`subprocess runner ` to use
+        :param python_executable:
+            The Python executable used to invoke the build backend
+        """
+        if runner is None:
+            runner = default_subprocess_runner
+
+        self.source_dir = abspath(source_dir)
+        self.build_backend = build_backend
+        if backend_path:
+            backend_path = [
+                norm_and_check(self.source_dir, p) for p in backend_path
+            ]
+        self.backend_path = backend_path
+        self._subprocess_runner = runner
+        if not python_executable:
+            python_executable = sys.executable
+        self.python_executable = python_executable
+
+    @contextmanager
+    def subprocess_runner(self, runner):
+        """A context manager for temporarily overriding the default
+        :ref:`subprocess runner `.
+
+        .. code-block:: python
+
+            hook_caller = BuildBackendHookCaller(...)
+            with hook_caller.subprocess_runner(quiet_subprocess_runner):
+                ...
+        """
+        prev = self._subprocess_runner
+        self._subprocess_runner = runner
+        try:
+            yield
+        finally:
+            self._subprocess_runner = prev
+
+    def _supported_features(self):
+        """Return the list of optional features supported by the backend."""
+        return self._call_hook('_supported_features', {})
+
+    def get_requires_for_build_wheel(self, config_settings=None):
+        """Get additional dependencies required for building a wheel.
+
+        :returns: A list of :pep:`dependency specifiers <508>`.
+        :rtype: list[str]
+
+        .. admonition:: Fallback
+
+            If the build backend does not defined a hook with this name, an
+            empty list will be returned.
+        """
+        return self._call_hook('get_requires_for_build_wheel', {
+            'config_settings': config_settings
+        })
+
+    def prepare_metadata_for_build_wheel(
+            self, metadata_directory, config_settings=None,
+            _allow_fallback=True):
+        """Prepare a ``*.dist-info`` folder with metadata for this project.
+
+        :returns: Name of the newly created subfolder within
+                  ``metadata_directory``, containing the metadata.
+        :rtype: str
+
+        .. admonition:: Fallback
+
+            If the build backend does not define a hook with this name and
+            ``_allow_fallback`` is truthy, the backend will be asked to build a
+            wheel via the ``build_wheel`` hook and the dist-info extracted from
+            that will be returned.
+        """
+        return self._call_hook('prepare_metadata_for_build_wheel', {
+            'metadata_directory': abspath(metadata_directory),
+            'config_settings': config_settings,
+            '_allow_fallback': _allow_fallback,
+        })
+
+    def build_wheel(
+            self, wheel_directory, config_settings=None,
+            metadata_directory=None):
+        """Build a wheel from this project.
+
+        :returns:
+            The name of the newly created wheel within ``wheel_directory``.
+
+        .. admonition:: Interaction with fallback
+
+            If the ``build_wheel`` hook was called in the fallback for
+            :meth:`prepare_metadata_for_build_wheel`, the build backend would
+            not be invoked. Instead, the previously built wheel will be copied
+            to ``wheel_directory`` and the name of that file will be returned.
+        """
+        if metadata_directory is not None:
+            metadata_directory = abspath(metadata_directory)
+        return self._call_hook('build_wheel', {
+            'wheel_directory': abspath(wheel_directory),
+            'config_settings': config_settings,
+            'metadata_directory': metadata_directory,
+        })
+
+    def get_requires_for_build_editable(self, config_settings=None):
+        """Get additional dependencies required for building an editable wheel.
+
+        :returns: A list of :pep:`dependency specifiers <508>`.
+        :rtype: list[str]
+
+        .. admonition:: Fallback
+
+            If the build backend does not defined a hook with this name, an
+            empty list will be returned.
+        """
+        return self._call_hook('get_requires_for_build_editable', {
+            'config_settings': config_settings
+        })
+
+    def prepare_metadata_for_build_editable(
+            self, metadata_directory, config_settings=None,
+            _allow_fallback=True):
+        """Prepare a ``*.dist-info`` folder with metadata for this project.
+
+        :returns: Name of the newly created subfolder within
+                  ``metadata_directory``, containing the metadata.
+        :rtype: str
+
+        .. admonition:: Fallback
+
+            If the build backend does not define a hook with this name and
+            ``_allow_fallback`` is truthy, the backend will be asked to build a
+            wheel via the ``build_editable`` hook and the dist-info
+            extracted from that will be returned.
+        """
+        return self._call_hook('prepare_metadata_for_build_editable', {
+            'metadata_directory': abspath(metadata_directory),
+            'config_settings': config_settings,
+            '_allow_fallback': _allow_fallback,
+        })
+
+    def build_editable(
+            self, wheel_directory, config_settings=None,
+            metadata_directory=None):
+        """Build an editable wheel from this project.
+
+        :returns:
+            The name of the newly created wheel within ``wheel_directory``.
+
+        .. admonition:: Interaction with fallback
+
+            If the ``build_editable`` hook was called in the fallback for
+            :meth:`prepare_metadata_for_build_editable`, the build backend
+            would not be invoked. Instead, the previously built wheel will be
+            copied to ``wheel_directory`` and the name of that file will be
+            returned.
+        """
+        if metadata_directory is not None:
+            metadata_directory = abspath(metadata_directory)
+        return self._call_hook('build_editable', {
+            'wheel_directory': abspath(wheel_directory),
+            'config_settings': config_settings,
+            'metadata_directory': metadata_directory,
+        })
+
+    def get_requires_for_build_sdist(self, config_settings=None):
+        """Get additional dependencies required for building an sdist.
+
+        :returns: A list of :pep:`dependency specifiers <508>`.
+        :rtype: list[str]
+        """
+        return self._call_hook('get_requires_for_build_sdist', {
+            'config_settings': config_settings
+        })
+
+    def build_sdist(self, sdist_directory, config_settings=None):
+        """Build an sdist from this project.
+
+        :returns:
+            The name of the newly created sdist within ``wheel_directory``.
+        """
+        return self._call_hook('build_sdist', {
+            'sdist_directory': abspath(sdist_directory),
+            'config_settings': config_settings,
+        })
+
+    def _call_hook(self, hook_name, kwargs):
+        extra_environ = {'PEP517_BUILD_BACKEND': self.build_backend}
+
+        if self.backend_path:
+            backend_path = os.pathsep.join(self.backend_path)
+            extra_environ['PEP517_BACKEND_PATH'] = backend_path
+
+        with tempfile.TemporaryDirectory() as td:
+            hook_input = {'kwargs': kwargs}
+            write_json(hook_input, pjoin(td, 'input.json'), indent=2)
+
+            # Run the hook in a subprocess
+            with _in_proc_script_path() as script:
+                python = self.python_executable
+                self._subprocess_runner(
+                    [python, abspath(str(script)), hook_name, td],
+                    cwd=self.source_dir,
+                    extra_environ=extra_environ
+                )
+
+            data = read_json(pjoin(td, 'output.json'))
+            if data.get('unsupported'):
+                raise UnsupportedOperation(data.get('traceback', ''))
+            if data.get('no_backend'):
+                raise BackendUnavailable(data.get('traceback', ''))
+            if data.get('backend_invalid'):
+                raise BackendInvalid(
+                    backend_name=self.build_backend,
+                    backend_path=self.backend_path,
+                    message=data.get('backend_error', '')
+                )
+            if data.get('hook_missing'):
+                raise HookMissing(data.get('missing_hook_name') or hook_name)
+            return data['return_val']
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..917fa065b3c7feccdef5bc666a5109c855217260
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/__init__.py
@@ -0,0 +1,18 @@
+"""This is a subpackage because the directory is on sys.path for _in_process.py
+
+The subpackage should stay as empty as possible to avoid shadowing modules that
+the backend might import.
+"""
+
+import importlib.resources as resources
+
+try:
+    resources.files
+except AttributeError:
+    # Python 3.8 compatibility
+    def _in_proc_script_path():
+        return resources.path(__package__, '_in_process.py')
+else:
+    def _in_proc_script_path():
+        return resources.as_file(
+            resources.files(__package__).joinpath('_in_process.py'))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee511ff20d73bb245fe7ae0c1fc31a41c33e7d29
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py
@@ -0,0 +1,353 @@
+"""This is invoked in a subprocess to call the build backend hooks.
+
+It expects:
+- Command line args: hook_name, control_dir
+- Environment variables:
+      PEP517_BUILD_BACKEND=entry.point:spec
+      PEP517_BACKEND_PATH=paths (separated with os.pathsep)
+- control_dir/input.json:
+  - {"kwargs": {...}}
+
+Results:
+- control_dir/output.json
+  - {"return_val": ...}
+"""
+import json
+import os
+import os.path
+import re
+import shutil
+import sys
+import traceback
+from glob import glob
+from importlib import import_module
+from os.path import join as pjoin
+
+# This file is run as a script, and `import wrappers` is not zip-safe, so we
+# include write_json() and read_json() from wrappers.py.
+
+
+def write_json(obj, path, **kwargs):
+    with open(path, 'w', encoding='utf-8') as f:
+        json.dump(obj, f, **kwargs)
+
+
+def read_json(path):
+    with open(path, encoding='utf-8') as f:
+        return json.load(f)
+
+
+class BackendUnavailable(Exception):
+    """Raised if we cannot import the backend"""
+    def __init__(self, traceback):
+        self.traceback = traceback
+
+
+class BackendInvalid(Exception):
+    """Raised if the backend is invalid"""
+    def __init__(self, message):
+        self.message = message
+
+
+class HookMissing(Exception):
+    """Raised if a hook is missing and we are not executing the fallback"""
+    def __init__(self, hook_name=None):
+        super().__init__(hook_name)
+        self.hook_name = hook_name
+
+
+def contained_in(filename, directory):
+    """Test if a file is located within the given directory."""
+    filename = os.path.normcase(os.path.abspath(filename))
+    directory = os.path.normcase(os.path.abspath(directory))
+    return os.path.commonprefix([filename, directory]) == directory
+
+
+def _build_backend():
+    """Find and load the build backend"""
+    # Add in-tree backend directories to the front of sys.path.
+    backend_path = os.environ.get('PEP517_BACKEND_PATH')
+    if backend_path:
+        extra_pathitems = backend_path.split(os.pathsep)
+        sys.path[:0] = extra_pathitems
+
+    ep = os.environ['PEP517_BUILD_BACKEND']
+    mod_path, _, obj_path = ep.partition(':')
+    try:
+        obj = import_module(mod_path)
+    except ImportError:
+        raise BackendUnavailable(traceback.format_exc())
+
+    if backend_path:
+        if not any(
+            contained_in(obj.__file__, path)
+            for path in extra_pathitems
+        ):
+            raise BackendInvalid("Backend was not loaded from backend-path")
+
+    if obj_path:
+        for path_part in obj_path.split('.'):
+            obj = getattr(obj, path_part)
+    return obj
+
+
+def _supported_features():
+    """Return the list of options features supported by the backend.
+
+    Returns a list of strings.
+    The only possible value is 'build_editable'.
+    """
+    backend = _build_backend()
+    features = []
+    if hasattr(backend, "build_editable"):
+        features.append("build_editable")
+    return features
+
+
+def get_requires_for_build_wheel(config_settings):
+    """Invoke the optional get_requires_for_build_wheel hook
+
+    Returns [] if the hook is not defined.
+    """
+    backend = _build_backend()
+    try:
+        hook = backend.get_requires_for_build_wheel
+    except AttributeError:
+        return []
+    else:
+        return hook(config_settings)
+
+
+def get_requires_for_build_editable(config_settings):
+    """Invoke the optional get_requires_for_build_editable hook
+
+    Returns [] if the hook is not defined.
+    """
+    backend = _build_backend()
+    try:
+        hook = backend.get_requires_for_build_editable
+    except AttributeError:
+        return []
+    else:
+        return hook(config_settings)
+
+
+def prepare_metadata_for_build_wheel(
+        metadata_directory, config_settings, _allow_fallback):
+    """Invoke optional prepare_metadata_for_build_wheel
+
+    Implements a fallback by building a wheel if the hook isn't defined,
+    unless _allow_fallback is False in which case HookMissing is raised.
+    """
+    backend = _build_backend()
+    try:
+        hook = backend.prepare_metadata_for_build_wheel
+    except AttributeError:
+        if not _allow_fallback:
+            raise HookMissing()
+    else:
+        return hook(metadata_directory, config_settings)
+    # fallback to build_wheel outside the try block to avoid exception chaining
+    # which can be confusing to users and is not relevant
+    whl_basename = backend.build_wheel(metadata_directory, config_settings)
+    return _get_wheel_metadata_from_wheel(whl_basename, metadata_directory,
+                                          config_settings)
+
+
+def prepare_metadata_for_build_editable(
+        metadata_directory, config_settings, _allow_fallback):
+    """Invoke optional prepare_metadata_for_build_editable
+
+    Implements a fallback by building an editable wheel if the hook isn't
+    defined, unless _allow_fallback is False in which case HookMissing is
+    raised.
+    """
+    backend = _build_backend()
+    try:
+        hook = backend.prepare_metadata_for_build_editable
+    except AttributeError:
+        if not _allow_fallback:
+            raise HookMissing()
+        try:
+            build_hook = backend.build_editable
+        except AttributeError:
+            raise HookMissing(hook_name='build_editable')
+        else:
+            whl_basename = build_hook(metadata_directory, config_settings)
+            return _get_wheel_metadata_from_wheel(whl_basename,
+                                                  metadata_directory,
+                                                  config_settings)
+    else:
+        return hook(metadata_directory, config_settings)
+
+
+WHEEL_BUILT_MARKER = 'PEP517_ALREADY_BUILT_WHEEL'
+
+
+def _dist_info_files(whl_zip):
+    """Identify the .dist-info folder inside a wheel ZipFile."""
+    res = []
+    for path in whl_zip.namelist():
+        m = re.match(r'[^/\\]+-[^/\\]+\.dist-info/', path)
+        if m:
+            res.append(path)
+    if res:
+        return res
+    raise Exception("No .dist-info folder found in wheel")
+
+
+def _get_wheel_metadata_from_wheel(
+        whl_basename, metadata_directory, config_settings):
+    """Extract the metadata from a wheel.
+
+    Fallback for when the build backend does not
+    define the 'get_wheel_metadata' hook.
+    """
+    from zipfile import ZipFile
+    with open(os.path.join(metadata_directory, WHEEL_BUILT_MARKER), 'wb'):
+        pass  # Touch marker file
+
+    whl_file = os.path.join(metadata_directory, whl_basename)
+    with ZipFile(whl_file) as zipf:
+        dist_info = _dist_info_files(zipf)
+        zipf.extractall(path=metadata_directory, members=dist_info)
+    return dist_info[0].split('/')[0]
+
+
+def _find_already_built_wheel(metadata_directory):
+    """Check for a wheel already built during the get_wheel_metadata hook.
+    """
+    if not metadata_directory:
+        return None
+    metadata_parent = os.path.dirname(metadata_directory)
+    if not os.path.isfile(pjoin(metadata_parent, WHEEL_BUILT_MARKER)):
+        return None
+
+    whl_files = glob(os.path.join(metadata_parent, '*.whl'))
+    if not whl_files:
+        print('Found wheel built marker, but no .whl files')
+        return None
+    if len(whl_files) > 1:
+        print('Found multiple .whl files; unspecified behaviour. '
+              'Will call build_wheel.')
+        return None
+
+    # Exactly one .whl file
+    return whl_files[0]
+
+
+def build_wheel(wheel_directory, config_settings, metadata_directory=None):
+    """Invoke the mandatory build_wheel hook.
+
+    If a wheel was already built in the
+    prepare_metadata_for_build_wheel fallback, this
+    will copy it rather than rebuilding the wheel.
+    """
+    prebuilt_whl = _find_already_built_wheel(metadata_directory)
+    if prebuilt_whl:
+        shutil.copy2(prebuilt_whl, wheel_directory)
+        return os.path.basename(prebuilt_whl)
+
+    return _build_backend().build_wheel(wheel_directory, config_settings,
+                                        metadata_directory)
+
+
+def build_editable(wheel_directory, config_settings, metadata_directory=None):
+    """Invoke the optional build_editable hook.
+
+    If a wheel was already built in the
+    prepare_metadata_for_build_editable fallback, this
+    will copy it rather than rebuilding the wheel.
+    """
+    backend = _build_backend()
+    try:
+        hook = backend.build_editable
+    except AttributeError:
+        raise HookMissing()
+    else:
+        prebuilt_whl = _find_already_built_wheel(metadata_directory)
+        if prebuilt_whl:
+            shutil.copy2(prebuilt_whl, wheel_directory)
+            return os.path.basename(prebuilt_whl)
+
+        return hook(wheel_directory, config_settings, metadata_directory)
+
+
+def get_requires_for_build_sdist(config_settings):
+    """Invoke the optional get_requires_for_build_wheel hook
+
+    Returns [] if the hook is not defined.
+    """
+    backend = _build_backend()
+    try:
+        hook = backend.get_requires_for_build_sdist
+    except AttributeError:
+        return []
+    else:
+        return hook(config_settings)
+
+
+class _DummyException(Exception):
+    """Nothing should ever raise this exception"""
+
+
+class GotUnsupportedOperation(Exception):
+    """For internal use when backend raises UnsupportedOperation"""
+    def __init__(self, traceback):
+        self.traceback = traceback
+
+
+def build_sdist(sdist_directory, config_settings):
+    """Invoke the mandatory build_sdist hook."""
+    backend = _build_backend()
+    try:
+        return backend.build_sdist(sdist_directory, config_settings)
+    except getattr(backend, 'UnsupportedOperation', _DummyException):
+        raise GotUnsupportedOperation(traceback.format_exc())
+
+
+HOOK_NAMES = {
+    'get_requires_for_build_wheel',
+    'prepare_metadata_for_build_wheel',
+    'build_wheel',
+    'get_requires_for_build_editable',
+    'prepare_metadata_for_build_editable',
+    'build_editable',
+    'get_requires_for_build_sdist',
+    'build_sdist',
+    '_supported_features',
+}
+
+
+def main():
+    if len(sys.argv) < 3:
+        sys.exit("Needs args: hook_name, control_dir")
+    hook_name = sys.argv[1]
+    control_dir = sys.argv[2]
+    if hook_name not in HOOK_NAMES:
+        sys.exit("Unknown hook: %s" % hook_name)
+    hook = globals()[hook_name]
+
+    hook_input = read_json(pjoin(control_dir, 'input.json'))
+
+    json_out = {'unsupported': False, 'return_val': None}
+    try:
+        json_out['return_val'] = hook(**hook_input['kwargs'])
+    except BackendUnavailable as e:
+        json_out['no_backend'] = True
+        json_out['traceback'] = e.traceback
+    except BackendInvalid as e:
+        json_out['backend_invalid'] = True
+        json_out['backend_error'] = e.message
+    except GotUnsupportedOperation as e:
+        json_out['unsupported'] = True
+        json_out['traceback'] = e.traceback
+    except HookMissing as e:
+        json_out['hook_missing'] = True
+        json_out['missing_hook_name'] = e.hook_name or hook_name
+
+    write_json(json_out, pjoin(control_dir, 'output.json'), indent=2)
+
+
+if __name__ == '__main__':
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4776248038b04305b116015b9a4edf0fa98c617
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/__init__.py
@@ -0,0 +1,182 @@
+#   __
+#  /__)  _  _     _   _ _/   _
+# / (   (- (/ (/ (- _)  /  _)
+#          /
+
+"""
+Requests HTTP Library
+~~~~~~~~~~~~~~~~~~~~~
+
+Requests is an HTTP library, written in Python, for human beings.
+Basic GET usage:
+
+   >>> import requests
+   >>> r = requests.get('https://www.python.org')
+   >>> r.status_code
+   200
+   >>> b'Python is a programming language' in r.content
+   True
+
+... or POST:
+
+   >>> payload = dict(key1='value1', key2='value2')
+   >>> r = requests.post('https://httpbin.org/post', data=payload)
+   >>> print(r.text)
+   {
+     ...
+     "form": {
+       "key1": "value1",
+       "key2": "value2"
+     },
+     ...
+   }
+
+The other HTTP methods are supported - see `requests.api`. Full documentation
+is at .
+
+:copyright: (c) 2017 by Kenneth Reitz.
+:license: Apache 2.0, see LICENSE for more details.
+"""
+
+import warnings
+
+from pip._vendor import urllib3
+
+from .exceptions import RequestsDependencyWarning
+
+charset_normalizer_version = None
+
+try:
+    from pip._vendor.chardet import __version__ as chardet_version
+except ImportError:
+    chardet_version = None
+
+
+def check_compatibility(urllib3_version, chardet_version, charset_normalizer_version):
+    urllib3_version = urllib3_version.split(".")
+    assert urllib3_version != ["dev"]  # Verify urllib3 isn't installed from git.
+
+    # Sometimes, urllib3 only reports its version as 16.1.
+    if len(urllib3_version) == 2:
+        urllib3_version.append("0")
+
+    # Check urllib3 for compatibility.
+    major, minor, patch = urllib3_version  # noqa: F811
+    major, minor, patch = int(major), int(minor), int(patch)
+    # urllib3 >= 1.21.1, <= 1.26
+    assert major == 1
+    assert minor >= 21
+    assert minor <= 26
+
+    # Check charset_normalizer for compatibility.
+    if chardet_version:
+        major, minor, patch = chardet_version.split(".")[:3]
+        major, minor, patch = int(major), int(minor), int(patch)
+        # chardet_version >= 3.0.2, < 6.0.0
+        assert (3, 0, 2) <= (major, minor, patch) < (6, 0, 0)
+    elif charset_normalizer_version:
+        major, minor, patch = charset_normalizer_version.split(".")[:3]
+        major, minor, patch = int(major), int(minor), int(patch)
+        # charset_normalizer >= 2.0.0 < 4.0.0
+        assert (2, 0, 0) <= (major, minor, patch) < (4, 0, 0)
+    else:
+        raise Exception("You need either charset_normalizer or chardet installed")
+
+
+def _check_cryptography(cryptography_version):
+    # cryptography < 1.3.4
+    try:
+        cryptography_version = list(map(int, cryptography_version.split(".")))
+    except ValueError:
+        return
+
+    if cryptography_version < [1, 3, 4]:
+        warning = "Old version of cryptography ({}) may cause slowdown.".format(
+            cryptography_version
+        )
+        warnings.warn(warning, RequestsDependencyWarning)
+
+
+# Check imported dependencies for compatibility.
+try:
+    check_compatibility(
+        urllib3.__version__, chardet_version, charset_normalizer_version
+    )
+except (AssertionError, ValueError):
+    warnings.warn(
+        "urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported "
+        "version!".format(
+            urllib3.__version__, chardet_version, charset_normalizer_version
+        ),
+        RequestsDependencyWarning,
+    )
+
+# Attempt to enable urllib3's fallback for SNI support
+# if the standard library doesn't support SNI or the
+# 'ssl' library isn't available.
+try:
+    # Note: This logic prevents upgrading cryptography on Windows, if imported
+    #       as part of pip.
+    from pip._internal.utils.compat import WINDOWS
+    if not WINDOWS:
+        raise ImportError("pip internals: don't import cryptography on Windows")
+    try:
+        import ssl
+    except ImportError:
+        ssl = None
+
+    if not getattr(ssl, "HAS_SNI", False):
+        from pip._vendor.urllib3.contrib import pyopenssl
+
+        pyopenssl.inject_into_urllib3()
+
+        # Check cryptography version
+        from cryptography import __version__ as cryptography_version
+
+        _check_cryptography(cryptography_version)
+except ImportError:
+    pass
+
+# urllib3's DependencyWarnings should be silenced.
+from pip._vendor.urllib3.exceptions import DependencyWarning
+
+warnings.simplefilter("ignore", DependencyWarning)
+
+# Set default logging handler to avoid "No handler found" warnings.
+import logging
+from logging import NullHandler
+
+from . import packages, utils
+from .__version__ import (
+    __author__,
+    __author_email__,
+    __build__,
+    __cake__,
+    __copyright__,
+    __description__,
+    __license__,
+    __title__,
+    __url__,
+    __version__,
+)
+from .api import delete, get, head, options, patch, post, put, request
+from .exceptions import (
+    ConnectionError,
+    ConnectTimeout,
+    FileModeWarning,
+    HTTPError,
+    JSONDecodeError,
+    ReadTimeout,
+    RequestException,
+    Timeout,
+    TooManyRedirects,
+    URLRequired,
+)
+from .models import PreparedRequest, Request, Response
+from .sessions import Session, session
+from .status_codes import codes
+
+logging.getLogger(__name__).addHandler(NullHandler())
+
+# FileModeWarnings go off per the default.
+warnings.simplefilter("default", FileModeWarning, append=True)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/__version__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/__version__.py
new file mode 100644
index 0000000000000000000000000000000000000000..69be3dec7418c9bececde7811fd1d5a62f995f03
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/__version__.py
@@ -0,0 +1,14 @@
+# .-. .-. .-. . . .-. .-. .-. .-.
+# |(  |-  |.| | | |-  `-.  |  `-.
+# ' ' `-' `-`.`-' `-' `-'  '  `-'
+
+__title__ = "requests"
+__description__ = "Python HTTP for Humans."
+__url__ = "https://requests.readthedocs.io"
+__version__ = "2.28.2"
+__build__ = 0x022802
+__author__ = "Kenneth Reitz"
+__author_email__ = "me@kennethreitz.org"
+__license__ = "Apache 2.0"
+__copyright__ = "Copyright Kenneth Reitz"
+__cake__ = "\u2728 \U0001f370 \u2728"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/_internal_utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/_internal_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..7dc9bc53360e95abfa99fe1ebd205a3d3ac620e6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/_internal_utils.py
@@ -0,0 +1,48 @@
+"""
+requests._internal_utils
+~~~~~~~~~~~~~~
+
+Provides utility functions that are consumed internally by Requests
+which depend on extremely few external helpers (such as compat)
+"""
+import re
+
+from .compat import builtin_str
+
+_VALID_HEADER_NAME_RE_BYTE = re.compile(rb"^[^:\s][^:\r\n]*$")
+_VALID_HEADER_NAME_RE_STR = re.compile(r"^[^:\s][^:\r\n]*$")
+_VALID_HEADER_VALUE_RE_BYTE = re.compile(rb"^\S[^\r\n]*$|^$")
+_VALID_HEADER_VALUE_RE_STR = re.compile(r"^\S[^\r\n]*$|^$")
+
+HEADER_VALIDATORS = {
+    bytes: (_VALID_HEADER_NAME_RE_BYTE, _VALID_HEADER_VALUE_RE_BYTE),
+    str: (_VALID_HEADER_NAME_RE_STR, _VALID_HEADER_VALUE_RE_STR),
+}
+
+
+def to_native_string(string, encoding="ascii"):
+    """Given a string object, regardless of type, returns a representation of
+    that string in the native string type, encoding and decoding where
+    necessary. This assumes ASCII unless told otherwise.
+    """
+    if isinstance(string, builtin_str):
+        out = string
+    else:
+        out = string.decode(encoding)
+
+    return out
+
+
+def unicode_is_ascii(u_string):
+    """Determine if unicode string only contains ASCII characters.
+
+    :param str u_string: unicode string to check. Must be unicode
+        and not Python 2 `str`.
+    :rtype: bool
+    """
+    assert isinstance(u_string, str)
+    try:
+        u_string.encode("ascii")
+        return True
+    except UnicodeEncodeError:
+        return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/adapters.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/adapters.py
new file mode 100644
index 0000000000000000000000000000000000000000..f68f7d467530845447278f6c0ad104b4beca9531
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/adapters.py
@@ -0,0 +1,584 @@
+"""
+requests.adapters
+~~~~~~~~~~~~~~~~~
+
+This module contains the transport adapters that Requests uses to define
+and maintain connections.
+"""
+
+import os.path
+import socket  # noqa: F401
+
+from pip._vendor.urllib3.exceptions import ClosedPoolError, ConnectTimeoutError
+from pip._vendor.urllib3.exceptions import HTTPError as _HTTPError
+from pip._vendor.urllib3.exceptions import InvalidHeader as _InvalidHeader
+from pip._vendor.urllib3.exceptions import (
+    LocationValueError,
+    MaxRetryError,
+    NewConnectionError,
+    ProtocolError,
+)
+from pip._vendor.urllib3.exceptions import ProxyError as _ProxyError
+from pip._vendor.urllib3.exceptions import ReadTimeoutError, ResponseError
+from pip._vendor.urllib3.exceptions import SSLError as _SSLError
+from pip._vendor.urllib3.poolmanager import PoolManager, proxy_from_url
+from pip._vendor.urllib3.response import HTTPResponse
+from pip._vendor.urllib3.util import Timeout as TimeoutSauce
+from pip._vendor.urllib3.util import parse_url
+from pip._vendor.urllib3.util.retry import Retry
+
+from .auth import _basic_auth_str
+from .compat import basestring, urlparse
+from .cookies import extract_cookies_to_jar
+from .exceptions import (
+    ConnectionError,
+    ConnectTimeout,
+    InvalidHeader,
+    InvalidProxyURL,
+    InvalidSchema,
+    InvalidURL,
+    ProxyError,
+    ReadTimeout,
+    RetryError,
+    SSLError,
+)
+from .models import Response
+from .structures import CaseInsensitiveDict
+from .utils import (
+    DEFAULT_CA_BUNDLE_PATH,
+    extract_zipped_paths,
+    get_auth_from_url,
+    get_encoding_from_headers,
+    prepend_scheme_if_needed,
+    select_proxy,
+    urldefragauth,
+)
+
+try:
+    from pip._vendor.urllib3.contrib.socks import SOCKSProxyManager
+except ImportError:
+
+    def SOCKSProxyManager(*args, **kwargs):
+        raise InvalidSchema("Missing dependencies for SOCKS support.")
+
+
+DEFAULT_POOLBLOCK = False
+DEFAULT_POOLSIZE = 10
+DEFAULT_RETRIES = 0
+DEFAULT_POOL_TIMEOUT = None
+
+
+class BaseAdapter:
+    """The Base Transport Adapter"""
+
+    def __init__(self):
+        super().__init__()
+
+    def send(
+        self, request, stream=False, timeout=None, verify=True, cert=None, proxies=None
+    ):
+        """Sends PreparedRequest object. Returns Response object.
+
+        :param request: The :class:`PreparedRequest ` being sent.
+        :param stream: (optional) Whether to stream the request content.
+        :param timeout: (optional) How long to wait for the server to send
+            data before giving up, as a float, or a :ref:`(connect timeout,
+            read timeout) ` tuple.
+        :type timeout: float or tuple
+        :param verify: (optional) Either a boolean, in which case it controls whether we verify
+            the server's TLS certificate, or a string, in which case it must be a path
+            to a CA bundle to use
+        :param cert: (optional) Any user-provided SSL certificate to be trusted.
+        :param proxies: (optional) The proxies dictionary to apply to the request.
+        """
+        raise NotImplementedError
+
+    def close(self):
+        """Cleans up adapter specific items."""
+        raise NotImplementedError
+
+
+class HTTPAdapter(BaseAdapter):
+    """The built-in HTTP Adapter for urllib3.
+
+    Provides a general-case interface for Requests sessions to contact HTTP and
+    HTTPS urls by implementing the Transport Adapter interface. This class will
+    usually be created by the :class:`Session ` class under the
+    covers.
+
+    :param pool_connections: The number of urllib3 connection pools to cache.
+    :param pool_maxsize: The maximum number of connections to save in the pool.
+    :param max_retries: The maximum number of retries each connection
+        should attempt. Note, this applies only to failed DNS lookups, socket
+        connections and connection timeouts, never to requests where data has
+        made it to the server. By default, Requests does not retry failed
+        connections. If you need granular control over the conditions under
+        which we retry a request, import urllib3's ``Retry`` class and pass
+        that instead.
+    :param pool_block: Whether the connection pool should block for connections.
+
+    Usage::
+
+      >>> import requests
+      >>> s = requests.Session()
+      >>> a = requests.adapters.HTTPAdapter(max_retries=3)
+      >>> s.mount('http://', a)
+    """
+
+    __attrs__ = [
+        "max_retries",
+        "config",
+        "_pool_connections",
+        "_pool_maxsize",
+        "_pool_block",
+    ]
+
+    def __init__(
+        self,
+        pool_connections=DEFAULT_POOLSIZE,
+        pool_maxsize=DEFAULT_POOLSIZE,
+        max_retries=DEFAULT_RETRIES,
+        pool_block=DEFAULT_POOLBLOCK,
+    ):
+        if max_retries == DEFAULT_RETRIES:
+            self.max_retries = Retry(0, read=False)
+        else:
+            self.max_retries = Retry.from_int(max_retries)
+        self.config = {}
+        self.proxy_manager = {}
+
+        super().__init__()
+
+        self._pool_connections = pool_connections
+        self._pool_maxsize = pool_maxsize
+        self._pool_block = pool_block
+
+        self.init_poolmanager(pool_connections, pool_maxsize, block=pool_block)
+
+    def __getstate__(self):
+        return {attr: getattr(self, attr, None) for attr in self.__attrs__}
+
+    def __setstate__(self, state):
+        # Can't handle by adding 'proxy_manager' to self.__attrs__ because
+        # self.poolmanager uses a lambda function, which isn't pickleable.
+        self.proxy_manager = {}
+        self.config = {}
+
+        for attr, value in state.items():
+            setattr(self, attr, value)
+
+        self.init_poolmanager(
+            self._pool_connections, self._pool_maxsize, block=self._pool_block
+        )
+
+    def init_poolmanager(
+        self, connections, maxsize, block=DEFAULT_POOLBLOCK, **pool_kwargs
+    ):
+        """Initializes a urllib3 PoolManager.
+
+        This method should not be called from user code, and is only
+        exposed for use when subclassing the
+        :class:`HTTPAdapter `.
+
+        :param connections: The number of urllib3 connection pools to cache.
+        :param maxsize: The maximum number of connections to save in the pool.
+        :param block: Block when no free connections are available.
+        :param pool_kwargs: Extra keyword arguments used to initialize the Pool Manager.
+        """
+        # save these values for pickling
+        self._pool_connections = connections
+        self._pool_maxsize = maxsize
+        self._pool_block = block
+
+        self.poolmanager = PoolManager(
+            num_pools=connections,
+            maxsize=maxsize,
+            block=block,
+            strict=True,
+            **pool_kwargs,
+        )
+
+    def proxy_manager_for(self, proxy, **proxy_kwargs):
+        """Return urllib3 ProxyManager for the given proxy.
+
+        This method should not be called from user code, and is only
+        exposed for use when subclassing the
+        :class:`HTTPAdapter `.
+
+        :param proxy: The proxy to return a urllib3 ProxyManager for.
+        :param proxy_kwargs: Extra keyword arguments used to configure the Proxy Manager.
+        :returns: ProxyManager
+        :rtype: urllib3.ProxyManager
+        """
+        if proxy in self.proxy_manager:
+            manager = self.proxy_manager[proxy]
+        elif proxy.lower().startswith("socks"):
+            username, password = get_auth_from_url(proxy)
+            manager = self.proxy_manager[proxy] = SOCKSProxyManager(
+                proxy,
+                username=username,
+                password=password,
+                num_pools=self._pool_connections,
+                maxsize=self._pool_maxsize,
+                block=self._pool_block,
+                **proxy_kwargs,
+            )
+        else:
+            proxy_headers = self.proxy_headers(proxy)
+            manager = self.proxy_manager[proxy] = proxy_from_url(
+                proxy,
+                proxy_headers=proxy_headers,
+                num_pools=self._pool_connections,
+                maxsize=self._pool_maxsize,
+                block=self._pool_block,
+                **proxy_kwargs,
+            )
+
+        return manager
+
+    def cert_verify(self, conn, url, verify, cert):
+        """Verify a SSL certificate. This method should not be called from user
+        code, and is only exposed for use when subclassing the
+        :class:`HTTPAdapter `.
+
+        :param conn: The urllib3 connection object associated with the cert.
+        :param url: The requested URL.
+        :param verify: Either a boolean, in which case it controls whether we verify
+            the server's TLS certificate, or a string, in which case it must be a path
+            to a CA bundle to use
+        :param cert: The SSL certificate to verify.
+        """
+        if url.lower().startswith("https") and verify:
+
+            cert_loc = None
+
+            # Allow self-specified cert location.
+            if verify is not True:
+                cert_loc = verify
+
+            if not cert_loc:
+                cert_loc = extract_zipped_paths(DEFAULT_CA_BUNDLE_PATH)
+
+            if not cert_loc or not os.path.exists(cert_loc):
+                raise OSError(
+                    f"Could not find a suitable TLS CA certificate bundle, "
+                    f"invalid path: {cert_loc}"
+                )
+
+            conn.cert_reqs = "CERT_REQUIRED"
+
+            if not os.path.isdir(cert_loc):
+                conn.ca_certs = cert_loc
+            else:
+                conn.ca_cert_dir = cert_loc
+        else:
+            conn.cert_reqs = "CERT_NONE"
+            conn.ca_certs = None
+            conn.ca_cert_dir = None
+
+        if cert:
+            if not isinstance(cert, basestring):
+                conn.cert_file = cert[0]
+                conn.key_file = cert[1]
+            else:
+                conn.cert_file = cert
+                conn.key_file = None
+            if conn.cert_file and not os.path.exists(conn.cert_file):
+                raise OSError(
+                    f"Could not find the TLS certificate file, "
+                    f"invalid path: {conn.cert_file}"
+                )
+            if conn.key_file and not os.path.exists(conn.key_file):
+                raise OSError(
+                    f"Could not find the TLS key file, invalid path: {conn.key_file}"
+                )
+
+    def build_response(self, req, resp):
+        """Builds a :class:`Response ` object from a urllib3
+        response. This should not be called from user code, and is only exposed
+        for use when subclassing the
+        :class:`HTTPAdapter `
+
+        :param req: The :class:`PreparedRequest ` used to generate the response.
+        :param resp: The urllib3 response object.
+        :rtype: requests.Response
+        """
+        response = Response()
+
+        # Fallback to None if there's no status_code, for whatever reason.
+        response.status_code = getattr(resp, "status", None)
+
+        # Make headers case-insensitive.
+        response.headers = CaseInsensitiveDict(getattr(resp, "headers", {}))
+
+        # Set encoding.
+        response.encoding = get_encoding_from_headers(response.headers)
+        response.raw = resp
+        response.reason = response.raw.reason
+
+        if isinstance(req.url, bytes):
+            response.url = req.url.decode("utf-8")
+        else:
+            response.url = req.url
+
+        # Add new cookies from the server.
+        extract_cookies_to_jar(response.cookies, req, resp)
+
+        # Give the Response some context.
+        response.request = req
+        response.connection = self
+
+        return response
+
+    def get_connection(self, url, proxies=None):
+        """Returns a urllib3 connection for the given URL. This should not be
+        called from user code, and is only exposed for use when subclassing the
+        :class:`HTTPAdapter `.
+
+        :param url: The URL to connect to.
+        :param proxies: (optional) A Requests-style dictionary of proxies used on this request.
+        :rtype: urllib3.ConnectionPool
+        """
+        proxy = select_proxy(url, proxies)
+
+        if proxy:
+            proxy = prepend_scheme_if_needed(proxy, "http")
+            proxy_url = parse_url(proxy)
+            if not proxy_url.host:
+                raise InvalidProxyURL(
+                    "Please check proxy URL. It is malformed "
+                    "and could be missing the host."
+                )
+            proxy_manager = self.proxy_manager_for(proxy)
+            conn = proxy_manager.connection_from_url(url)
+        else:
+            # Only scheme should be lower case
+            parsed = urlparse(url)
+            url = parsed.geturl()
+            conn = self.poolmanager.connection_from_url(url)
+
+        return conn
+
+    def close(self):
+        """Disposes of any internal state.
+
+        Currently, this closes the PoolManager and any active ProxyManager,
+        which closes any pooled connections.
+        """
+        self.poolmanager.clear()
+        for proxy in self.proxy_manager.values():
+            proxy.clear()
+
+    def request_url(self, request, proxies):
+        """Obtain the url to use when making the final request.
+
+        If the message is being sent through a HTTP proxy, the full URL has to
+        be used. Otherwise, we should only use the path portion of the URL.
+
+        This should not be called from user code, and is only exposed for use
+        when subclassing the
+        :class:`HTTPAdapter `.
+
+        :param request: The :class:`PreparedRequest ` being sent.
+        :param proxies: A dictionary of schemes or schemes and hosts to proxy URLs.
+        :rtype: str
+        """
+        proxy = select_proxy(request.url, proxies)
+        scheme = urlparse(request.url).scheme
+
+        is_proxied_http_request = proxy and scheme != "https"
+        using_socks_proxy = False
+        if proxy:
+            proxy_scheme = urlparse(proxy).scheme.lower()
+            using_socks_proxy = proxy_scheme.startswith("socks")
+
+        url = request.path_url
+        if is_proxied_http_request and not using_socks_proxy:
+            url = urldefragauth(request.url)
+
+        return url
+
+    def add_headers(self, request, **kwargs):
+        """Add any headers needed by the connection. As of v2.0 this does
+        nothing by default, but is left for overriding by users that subclass
+        the :class:`HTTPAdapter `.
+
+        This should not be called from user code, and is only exposed for use
+        when subclassing the
+        :class:`HTTPAdapter `.
+
+        :param request: The :class:`PreparedRequest ` to add headers to.
+        :param kwargs: The keyword arguments from the call to send().
+        """
+        pass
+
+    def proxy_headers(self, proxy):
+        """Returns a dictionary of the headers to add to any request sent
+        through a proxy. This works with urllib3 magic to ensure that they are
+        correctly sent to the proxy, rather than in a tunnelled request if
+        CONNECT is being used.
+
+        This should not be called from user code, and is only exposed for use
+        when subclassing the
+        :class:`HTTPAdapter `.
+
+        :param proxy: The url of the proxy being used for this request.
+        :rtype: dict
+        """
+        headers = {}
+        username, password = get_auth_from_url(proxy)
+
+        if username:
+            headers["Proxy-Authorization"] = _basic_auth_str(username, password)
+
+        return headers
+
+    def send(
+        self, request, stream=False, timeout=None, verify=True, cert=None, proxies=None
+    ):
+        """Sends PreparedRequest object. Returns Response object.
+
+        :param request: The :class:`PreparedRequest ` being sent.
+        :param stream: (optional) Whether to stream the request content.
+        :param timeout: (optional) How long to wait for the server to send
+            data before giving up, as a float, or a :ref:`(connect timeout,
+            read timeout) ` tuple.
+        :type timeout: float or tuple or urllib3 Timeout object
+        :param verify: (optional) Either a boolean, in which case it controls whether
+            we verify the server's TLS certificate, or a string, in which case it
+            must be a path to a CA bundle to use
+        :param cert: (optional) Any user-provided SSL certificate to be trusted.
+        :param proxies: (optional) The proxies dictionary to apply to the request.
+        :rtype: requests.Response
+        """
+
+        try:
+            conn = self.get_connection(request.url, proxies)
+        except LocationValueError as e:
+            raise InvalidURL(e, request=request)
+
+        self.cert_verify(conn, request.url, verify, cert)
+        url = self.request_url(request, proxies)
+        self.add_headers(
+            request,
+            stream=stream,
+            timeout=timeout,
+            verify=verify,
+            cert=cert,
+            proxies=proxies,
+        )
+
+        chunked = not (request.body is None or "Content-Length" in request.headers)
+
+        if isinstance(timeout, tuple):
+            try:
+                connect, read = timeout
+                timeout = TimeoutSauce(connect=connect, read=read)
+            except ValueError:
+                raise ValueError(
+                    f"Invalid timeout {timeout}. Pass a (connect, read) timeout tuple, "
+                    f"or a single float to set both timeouts to the same value."
+                )
+        elif isinstance(timeout, TimeoutSauce):
+            pass
+        else:
+            timeout = TimeoutSauce(connect=timeout, read=timeout)
+
+        try:
+            if not chunked:
+                resp = conn.urlopen(
+                    method=request.method,
+                    url=url,
+                    body=request.body,
+                    headers=request.headers,
+                    redirect=False,
+                    assert_same_host=False,
+                    preload_content=False,
+                    decode_content=False,
+                    retries=self.max_retries,
+                    timeout=timeout,
+                )
+
+            # Send the request.
+            else:
+                if hasattr(conn, "proxy_pool"):
+                    conn = conn.proxy_pool
+
+                low_conn = conn._get_conn(timeout=DEFAULT_POOL_TIMEOUT)
+
+                try:
+                    skip_host = "Host" in request.headers
+                    low_conn.putrequest(
+                        request.method,
+                        url,
+                        skip_accept_encoding=True,
+                        skip_host=skip_host,
+                    )
+
+                    for header, value in request.headers.items():
+                        low_conn.putheader(header, value)
+
+                    low_conn.endheaders()
+
+                    for i in request.body:
+                        low_conn.send(hex(len(i))[2:].encode("utf-8"))
+                        low_conn.send(b"\r\n")
+                        low_conn.send(i)
+                        low_conn.send(b"\r\n")
+                    low_conn.send(b"0\r\n\r\n")
+
+                    # Receive the response from the server
+                    r = low_conn.getresponse()
+
+                    resp = HTTPResponse.from_httplib(
+                        r,
+                        pool=conn,
+                        connection=low_conn,
+                        preload_content=False,
+                        decode_content=False,
+                    )
+                except Exception:
+                    # If we hit any problems here, clean up the connection.
+                    # Then, raise so that we can handle the actual exception.
+                    low_conn.close()
+                    raise
+
+        except (ProtocolError, OSError) as err:
+            raise ConnectionError(err, request=request)
+
+        except MaxRetryError as e:
+            if isinstance(e.reason, ConnectTimeoutError):
+                # TODO: Remove this in 3.0.0: see #2811
+                if not isinstance(e.reason, NewConnectionError):
+                    raise ConnectTimeout(e, request=request)
+
+            if isinstance(e.reason, ResponseError):
+                raise RetryError(e, request=request)
+
+            if isinstance(e.reason, _ProxyError):
+                raise ProxyError(e, request=request)
+
+            if isinstance(e.reason, _SSLError):
+                # This branch is for urllib3 v1.22 and later.
+                raise SSLError(e, request=request)
+
+            raise ConnectionError(e, request=request)
+
+        except ClosedPoolError as e:
+            raise ConnectionError(e, request=request)
+
+        except _ProxyError as e:
+            raise ProxyError(e)
+
+        except (_SSLError, _HTTPError) as e:
+            if isinstance(e, _SSLError):
+                # This branch is for urllib3 versions earlier than v1.22
+                raise SSLError(e, request=request)
+            elif isinstance(e, ReadTimeoutError):
+                raise ReadTimeout(e, request=request)
+            elif isinstance(e, _InvalidHeader):
+                raise InvalidHeader(e, request=request)
+            else:
+                raise
+
+        return self.build_response(request, resp)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/api.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/api.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f71aaed1afc2f43ae5a58d951896b91e0327abc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/api.py
@@ -0,0 +1,157 @@
+"""
+requests.api
+~~~~~~~~~~~~
+
+This module implements the Requests API.
+
+:copyright: (c) 2012 by Kenneth Reitz.
+:license: Apache2, see LICENSE for more details.
+"""
+
+from . import sessions
+
+
+def request(method, url, **kwargs):
+    """Constructs and sends a :class:`Request `.
+
+    :param method: method for the new :class:`Request` object: ``GET``, ``OPTIONS``, ``HEAD``, ``POST``, ``PUT``, ``PATCH``, or ``DELETE``.
+    :param url: URL for the new :class:`Request` object.
+    :param params: (optional) Dictionary, list of tuples or bytes to send
+        in the query string for the :class:`Request`.
+    :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+        object to send in the body of the :class:`Request`.
+    :param json: (optional) A JSON serializable Python object to send in the body of the :class:`Request`.
+    :param headers: (optional) Dictionary of HTTP Headers to send with the :class:`Request`.
+    :param cookies: (optional) Dict or CookieJar object to send with the :class:`Request`.
+    :param files: (optional) Dictionary of ``'name': file-like-objects`` (or ``{'name': file-tuple}``) for multipart encoding upload.
+        ``file-tuple`` can be a 2-tuple ``('filename', fileobj)``, 3-tuple ``('filename', fileobj, 'content_type')``
+        or a 4-tuple ``('filename', fileobj, 'content_type', custom_headers)``, where ``'content-type'`` is a string
+        defining the content type of the given file and ``custom_headers`` a dict-like object containing additional headers
+        to add for the file.
+    :param auth: (optional) Auth tuple to enable Basic/Digest/Custom HTTP Auth.
+    :param timeout: (optional) How many seconds to wait for the server to send data
+        before giving up, as a float, or a :ref:`(connect timeout, read
+        timeout) ` tuple.
+    :type timeout: float or tuple
+    :param allow_redirects: (optional) Boolean. Enable/disable GET/OPTIONS/POST/PUT/PATCH/DELETE/HEAD redirection. Defaults to ``True``.
+    :type allow_redirects: bool
+    :param proxies: (optional) Dictionary mapping protocol to the URL of the proxy.
+    :param verify: (optional) Either a boolean, in which case it controls whether we verify
+            the server's TLS certificate, or a string, in which case it must be a path
+            to a CA bundle to use. Defaults to ``True``.
+    :param stream: (optional) if ``False``, the response content will be immediately downloaded.
+    :param cert: (optional) if String, path to ssl client cert file (.pem). If Tuple, ('cert', 'key') pair.
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+
+    Usage::
+
+      >>> import requests
+      >>> req = requests.request('GET', 'https://httpbin.org/get')
+      >>> req
+      
+    """
+
+    # By using the 'with' statement we are sure the session is closed, thus we
+    # avoid leaving sockets open which can trigger a ResourceWarning in some
+    # cases, and look like a memory leak in others.
+    with sessions.Session() as session:
+        return session.request(method=method, url=url, **kwargs)
+
+
+def get(url, params=None, **kwargs):
+    r"""Sends a GET request.
+
+    :param url: URL for the new :class:`Request` object.
+    :param params: (optional) Dictionary, list of tuples or bytes to send
+        in the query string for the :class:`Request`.
+    :param \*\*kwargs: Optional arguments that ``request`` takes.
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+    """
+
+    return request("get", url, params=params, **kwargs)
+
+
+def options(url, **kwargs):
+    r"""Sends an OPTIONS request.
+
+    :param url: URL for the new :class:`Request` object.
+    :param \*\*kwargs: Optional arguments that ``request`` takes.
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+    """
+
+    return request("options", url, **kwargs)
+
+
+def head(url, **kwargs):
+    r"""Sends a HEAD request.
+
+    :param url: URL for the new :class:`Request` object.
+    :param \*\*kwargs: Optional arguments that ``request`` takes. If
+        `allow_redirects` is not provided, it will be set to `False` (as
+        opposed to the default :meth:`request` behavior).
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+    """
+
+    kwargs.setdefault("allow_redirects", False)
+    return request("head", url, **kwargs)
+
+
+def post(url, data=None, json=None, **kwargs):
+    r"""Sends a POST request.
+
+    :param url: URL for the new :class:`Request` object.
+    :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+        object to send in the body of the :class:`Request`.
+    :param json: (optional) json data to send in the body of the :class:`Request`.
+    :param \*\*kwargs: Optional arguments that ``request`` takes.
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+    """
+
+    return request("post", url, data=data, json=json, **kwargs)
+
+
+def put(url, data=None, **kwargs):
+    r"""Sends a PUT request.
+
+    :param url: URL for the new :class:`Request` object.
+    :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+        object to send in the body of the :class:`Request`.
+    :param json: (optional) json data to send in the body of the :class:`Request`.
+    :param \*\*kwargs: Optional arguments that ``request`` takes.
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+    """
+
+    return request("put", url, data=data, **kwargs)
+
+
+def patch(url, data=None, **kwargs):
+    r"""Sends a PATCH request.
+
+    :param url: URL for the new :class:`Request` object.
+    :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+        object to send in the body of the :class:`Request`.
+    :param json: (optional) json data to send in the body of the :class:`Request`.
+    :param \*\*kwargs: Optional arguments that ``request`` takes.
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+    """
+
+    return request("patch", url, data=data, **kwargs)
+
+
+def delete(url, **kwargs):
+    r"""Sends a DELETE request.
+
+    :param url: URL for the new :class:`Request` object.
+    :param \*\*kwargs: Optional arguments that ``request`` takes.
+    :return: :class:`Response ` object
+    :rtype: requests.Response
+    """
+
+    return request("delete", url, **kwargs)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/auth.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/auth.py
new file mode 100644
index 0000000000000000000000000000000000000000..9733686ddb36b826ead4f4666d42311397fa6fec
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/auth.py
@@ -0,0 +1,315 @@
+"""
+requests.auth
+~~~~~~~~~~~~~
+
+This module contains the authentication handlers for Requests.
+"""
+
+import hashlib
+import os
+import re
+import threading
+import time
+import warnings
+from base64 import b64encode
+
+from ._internal_utils import to_native_string
+from .compat import basestring, str, urlparse
+from .cookies import extract_cookies_to_jar
+from .utils import parse_dict_header
+
+CONTENT_TYPE_FORM_URLENCODED = "application/x-www-form-urlencoded"
+CONTENT_TYPE_MULTI_PART = "multipart/form-data"
+
+
+def _basic_auth_str(username, password):
+    """Returns a Basic Auth string."""
+
+    # "I want us to put a big-ol' comment on top of it that
+    # says that this behaviour is dumb but we need to preserve
+    # it because people are relying on it."
+    #    - Lukasa
+    #
+    # These are here solely to maintain backwards compatibility
+    # for things like ints. This will be removed in 3.0.0.
+    if not isinstance(username, basestring):
+        warnings.warn(
+            "Non-string usernames will no longer be supported in Requests "
+            "3.0.0. Please convert the object you've passed in ({!r}) to "
+            "a string or bytes object in the near future to avoid "
+            "problems.".format(username),
+            category=DeprecationWarning,
+        )
+        username = str(username)
+
+    if not isinstance(password, basestring):
+        warnings.warn(
+            "Non-string passwords will no longer be supported in Requests "
+            "3.0.0. Please convert the object you've passed in ({!r}) to "
+            "a string or bytes object in the near future to avoid "
+            "problems.".format(type(password)),
+            category=DeprecationWarning,
+        )
+        password = str(password)
+    # -- End Removal --
+
+    if isinstance(username, str):
+        username = username.encode("latin1")
+
+    if isinstance(password, str):
+        password = password.encode("latin1")
+
+    authstr = "Basic " + to_native_string(
+        b64encode(b":".join((username, password))).strip()
+    )
+
+    return authstr
+
+
+class AuthBase:
+    """Base class that all auth implementations derive from"""
+
+    def __call__(self, r):
+        raise NotImplementedError("Auth hooks must be callable.")
+
+
+class HTTPBasicAuth(AuthBase):
+    """Attaches HTTP Basic Authentication to the given Request object."""
+
+    def __init__(self, username, password):
+        self.username = username
+        self.password = password
+
+    def __eq__(self, other):
+        return all(
+            [
+                self.username == getattr(other, "username", None),
+                self.password == getattr(other, "password", None),
+            ]
+        )
+
+    def __ne__(self, other):
+        return not self == other
+
+    def __call__(self, r):
+        r.headers["Authorization"] = _basic_auth_str(self.username, self.password)
+        return r
+
+
+class HTTPProxyAuth(HTTPBasicAuth):
+    """Attaches HTTP Proxy Authentication to a given Request object."""
+
+    def __call__(self, r):
+        r.headers["Proxy-Authorization"] = _basic_auth_str(self.username, self.password)
+        return r
+
+
+class HTTPDigestAuth(AuthBase):
+    """Attaches HTTP Digest Authentication to the given Request object."""
+
+    def __init__(self, username, password):
+        self.username = username
+        self.password = password
+        # Keep state in per-thread local storage
+        self._thread_local = threading.local()
+
+    def init_per_thread_state(self):
+        # Ensure state is initialized just once per-thread
+        if not hasattr(self._thread_local, "init"):
+            self._thread_local.init = True
+            self._thread_local.last_nonce = ""
+            self._thread_local.nonce_count = 0
+            self._thread_local.chal = {}
+            self._thread_local.pos = None
+            self._thread_local.num_401_calls = None
+
+    def build_digest_header(self, method, url):
+        """
+        :rtype: str
+        """
+
+        realm = self._thread_local.chal["realm"]
+        nonce = self._thread_local.chal["nonce"]
+        qop = self._thread_local.chal.get("qop")
+        algorithm = self._thread_local.chal.get("algorithm")
+        opaque = self._thread_local.chal.get("opaque")
+        hash_utf8 = None
+
+        if algorithm is None:
+            _algorithm = "MD5"
+        else:
+            _algorithm = algorithm.upper()
+        # lambdas assume digest modules are imported at the top level
+        if _algorithm == "MD5" or _algorithm == "MD5-SESS":
+
+            def md5_utf8(x):
+                if isinstance(x, str):
+                    x = x.encode("utf-8")
+                return hashlib.md5(x).hexdigest()
+
+            hash_utf8 = md5_utf8
+        elif _algorithm == "SHA":
+
+            def sha_utf8(x):
+                if isinstance(x, str):
+                    x = x.encode("utf-8")
+                return hashlib.sha1(x).hexdigest()
+
+            hash_utf8 = sha_utf8
+        elif _algorithm == "SHA-256":
+
+            def sha256_utf8(x):
+                if isinstance(x, str):
+                    x = x.encode("utf-8")
+                return hashlib.sha256(x).hexdigest()
+
+            hash_utf8 = sha256_utf8
+        elif _algorithm == "SHA-512":
+
+            def sha512_utf8(x):
+                if isinstance(x, str):
+                    x = x.encode("utf-8")
+                return hashlib.sha512(x).hexdigest()
+
+            hash_utf8 = sha512_utf8
+
+        KD = lambda s, d: hash_utf8(f"{s}:{d}")  # noqa:E731
+
+        if hash_utf8 is None:
+            return None
+
+        # XXX not implemented yet
+        entdig = None
+        p_parsed = urlparse(url)
+        #: path is request-uri defined in RFC 2616 which should not be empty
+        path = p_parsed.path or "/"
+        if p_parsed.query:
+            path += f"?{p_parsed.query}"
+
+        A1 = f"{self.username}:{realm}:{self.password}"
+        A2 = f"{method}:{path}"
+
+        HA1 = hash_utf8(A1)
+        HA2 = hash_utf8(A2)
+
+        if nonce == self._thread_local.last_nonce:
+            self._thread_local.nonce_count += 1
+        else:
+            self._thread_local.nonce_count = 1
+        ncvalue = f"{self._thread_local.nonce_count:08x}"
+        s = str(self._thread_local.nonce_count).encode("utf-8")
+        s += nonce.encode("utf-8")
+        s += time.ctime().encode("utf-8")
+        s += os.urandom(8)
+
+        cnonce = hashlib.sha1(s).hexdigest()[:16]
+        if _algorithm == "MD5-SESS":
+            HA1 = hash_utf8(f"{HA1}:{nonce}:{cnonce}")
+
+        if not qop:
+            respdig = KD(HA1, f"{nonce}:{HA2}")
+        elif qop == "auth" or "auth" in qop.split(","):
+            noncebit = f"{nonce}:{ncvalue}:{cnonce}:auth:{HA2}"
+            respdig = KD(HA1, noncebit)
+        else:
+            # XXX handle auth-int.
+            return None
+
+        self._thread_local.last_nonce = nonce
+
+        # XXX should the partial digests be encoded too?
+        base = (
+            f'username="{self.username}", realm="{realm}", nonce="{nonce}", '
+            f'uri="{path}", response="{respdig}"'
+        )
+        if opaque:
+            base += f', opaque="{opaque}"'
+        if algorithm:
+            base += f', algorithm="{algorithm}"'
+        if entdig:
+            base += f', digest="{entdig}"'
+        if qop:
+            base += f', qop="auth", nc={ncvalue}, cnonce="{cnonce}"'
+
+        return f"Digest {base}"
+
+    def handle_redirect(self, r, **kwargs):
+        """Reset num_401_calls counter on redirects."""
+        if r.is_redirect:
+            self._thread_local.num_401_calls = 1
+
+    def handle_401(self, r, **kwargs):
+        """
+        Takes the given response and tries digest-auth, if needed.
+
+        :rtype: requests.Response
+        """
+
+        # If response is not 4xx, do not auth
+        # See https://github.com/psf/requests/issues/3772
+        if not 400 <= r.status_code < 500:
+            self._thread_local.num_401_calls = 1
+            return r
+
+        if self._thread_local.pos is not None:
+            # Rewind the file position indicator of the body to where
+            # it was to resend the request.
+            r.request.body.seek(self._thread_local.pos)
+        s_auth = r.headers.get("www-authenticate", "")
+
+        if "digest" in s_auth.lower() and self._thread_local.num_401_calls < 2:
+
+            self._thread_local.num_401_calls += 1
+            pat = re.compile(r"digest ", flags=re.IGNORECASE)
+            self._thread_local.chal = parse_dict_header(pat.sub("", s_auth, count=1))
+
+            # Consume content and release the original connection
+            # to allow our new request to reuse the same one.
+            r.content
+            r.close()
+            prep = r.request.copy()
+            extract_cookies_to_jar(prep._cookies, r.request, r.raw)
+            prep.prepare_cookies(prep._cookies)
+
+            prep.headers["Authorization"] = self.build_digest_header(
+                prep.method, prep.url
+            )
+            _r = r.connection.send(prep, **kwargs)
+            _r.history.append(r)
+            _r.request = prep
+
+            return _r
+
+        self._thread_local.num_401_calls = 1
+        return r
+
+    def __call__(self, r):
+        # Initialize per-thread state, if needed
+        self.init_per_thread_state()
+        # If we have a saved nonce, skip the 401
+        if self._thread_local.last_nonce:
+            r.headers["Authorization"] = self.build_digest_header(r.method, r.url)
+        try:
+            self._thread_local.pos = r.body.tell()
+        except AttributeError:
+            # In the case of HTTPDigestAuth being reused and the body of
+            # the previous request was a file-like object, pos has the
+            # file position of the previous body. Ensure it's set to
+            # None.
+            self._thread_local.pos = None
+        r.register_hook("response", self.handle_401)
+        r.register_hook("response", self.handle_redirect)
+        self._thread_local.num_401_calls = 1
+
+        return r
+
+    def __eq__(self, other):
+        return all(
+            [
+                self.username == getattr(other, "username", None),
+                self.password == getattr(other, "password", None),
+            ]
+        )
+
+    def __ne__(self, other):
+        return not self == other
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/certs.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/certs.py
new file mode 100644
index 0000000000000000000000000000000000000000..38696a1fb3419dd810004d5aec9654e5224042ed
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/certs.py
@@ -0,0 +1,24 @@
+#!/usr/bin/env python
+
+"""
+requests.certs
+~~~~~~~~~~~~~~
+
+This module returns the preferred default CA certificate bundle. There is
+only one — the one from the certifi package.
+
+If you are packaging Requests, e.g., for a Linux distribution or a managed
+environment, you can change the definition of where() to return a separately
+packaged CA bundle.
+"""
+
+import os
+
+if "_PIP_STANDALONE_CERT" not in os.environ:
+    from pip._vendor.certifi import where
+else:
+    def where():
+        return os.environ["_PIP_STANDALONE_CERT"]
+
+if __name__ == "__main__":
+    print(where())
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/compat.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/compat.py
new file mode 100644
index 0000000000000000000000000000000000000000..9ab2bb48656520a95ec9ac87d090f2e741f0e544
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/compat.py
@@ -0,0 +1,67 @@
+"""
+requests.compat
+~~~~~~~~~~~~~~~
+
+This module previously handled import compatibility issues
+between Python 2 and Python 3. It remains for backwards
+compatibility until the next major version.
+"""
+
+from pip._vendor import chardet
+
+import sys
+
+# -------
+# Pythons
+# -------
+
+# Syntax sugar.
+_ver = sys.version_info
+
+#: Python 2.x?
+is_py2 = _ver[0] == 2
+
+#: Python 3.x?
+is_py3 = _ver[0] == 3
+
+# Note: We've patched out simplejson support in pip because it prevents
+#       upgrading simplejson on Windows.
+import json
+from json import JSONDecodeError
+
+# Keep OrderedDict for backwards compatibility.
+from collections import OrderedDict
+from collections.abc import Callable, Mapping, MutableMapping
+from http import cookiejar as cookielib
+from http.cookies import Morsel
+from io import StringIO
+
+# --------------
+# Legacy Imports
+# --------------
+from urllib.parse import (
+    quote,
+    quote_plus,
+    unquote,
+    unquote_plus,
+    urldefrag,
+    urlencode,
+    urljoin,
+    urlparse,
+    urlsplit,
+    urlunparse,
+)
+from urllib.request import (
+    getproxies,
+    getproxies_environment,
+    parse_http_list,
+    proxy_bypass,
+    proxy_bypass_environment,
+)
+
+builtin_str = str
+str = str
+bytes = bytes
+basestring = (str, bytes)
+numeric_types = (int, float)
+integer_types = (int,)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/cookies.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/cookies.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf54ab237e410603061b8cec8fd195912d3cfb08
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/cookies.py
@@ -0,0 +1,561 @@
+"""
+requests.cookies
+~~~~~~~~~~~~~~~~
+
+Compatibility code to be able to use `cookielib.CookieJar` with requests.
+
+requests.utils imports from here, so be careful with imports.
+"""
+
+import calendar
+import copy
+import time
+
+from ._internal_utils import to_native_string
+from .compat import Morsel, MutableMapping, cookielib, urlparse, urlunparse
+
+try:
+    import threading
+except ImportError:
+    import dummy_threading as threading
+
+
+class MockRequest:
+    """Wraps a `requests.Request` to mimic a `urllib2.Request`.
+
+    The code in `cookielib.CookieJar` expects this interface in order to correctly
+    manage cookie policies, i.e., determine whether a cookie can be set, given the
+    domains of the request and the cookie.
+
+    The original request object is read-only. The client is responsible for collecting
+    the new headers via `get_new_headers()` and interpreting them appropriately. You
+    probably want `get_cookie_header`, defined below.
+    """
+
+    def __init__(self, request):
+        self._r = request
+        self._new_headers = {}
+        self.type = urlparse(self._r.url).scheme
+
+    def get_type(self):
+        return self.type
+
+    def get_host(self):
+        return urlparse(self._r.url).netloc
+
+    def get_origin_req_host(self):
+        return self.get_host()
+
+    def get_full_url(self):
+        # Only return the response's URL if the user hadn't set the Host
+        # header
+        if not self._r.headers.get("Host"):
+            return self._r.url
+        # If they did set it, retrieve it and reconstruct the expected domain
+        host = to_native_string(self._r.headers["Host"], encoding="utf-8")
+        parsed = urlparse(self._r.url)
+        # Reconstruct the URL as we expect it
+        return urlunparse(
+            [
+                parsed.scheme,
+                host,
+                parsed.path,
+                parsed.params,
+                parsed.query,
+                parsed.fragment,
+            ]
+        )
+
+    def is_unverifiable(self):
+        return True
+
+    def has_header(self, name):
+        return name in self._r.headers or name in self._new_headers
+
+    def get_header(self, name, default=None):
+        return self._r.headers.get(name, self._new_headers.get(name, default))
+
+    def add_header(self, key, val):
+        """cookielib has no legitimate use for this method; add it back if you find one."""
+        raise NotImplementedError(
+            "Cookie headers should be added with add_unredirected_header()"
+        )
+
+    def add_unredirected_header(self, name, value):
+        self._new_headers[name] = value
+
+    def get_new_headers(self):
+        return self._new_headers
+
+    @property
+    def unverifiable(self):
+        return self.is_unverifiable()
+
+    @property
+    def origin_req_host(self):
+        return self.get_origin_req_host()
+
+    @property
+    def host(self):
+        return self.get_host()
+
+
+class MockResponse:
+    """Wraps a `httplib.HTTPMessage` to mimic a `urllib.addinfourl`.
+
+    ...what? Basically, expose the parsed HTTP headers from the server response
+    the way `cookielib` expects to see them.
+    """
+
+    def __init__(self, headers):
+        """Make a MockResponse for `cookielib` to read.
+
+        :param headers: a httplib.HTTPMessage or analogous carrying the headers
+        """
+        self._headers = headers
+
+    def info(self):
+        return self._headers
+
+    def getheaders(self, name):
+        self._headers.getheaders(name)
+
+
+def extract_cookies_to_jar(jar, request, response):
+    """Extract the cookies from the response into a CookieJar.
+
+    :param jar: cookielib.CookieJar (not necessarily a RequestsCookieJar)
+    :param request: our own requests.Request object
+    :param response: urllib3.HTTPResponse object
+    """
+    if not (hasattr(response, "_original_response") and response._original_response):
+        return
+    # the _original_response field is the wrapped httplib.HTTPResponse object,
+    req = MockRequest(request)
+    # pull out the HTTPMessage with the headers and put it in the mock:
+    res = MockResponse(response._original_response.msg)
+    jar.extract_cookies(res, req)
+
+
+def get_cookie_header(jar, request):
+    """
+    Produce an appropriate Cookie header string to be sent with `request`, or None.
+
+    :rtype: str
+    """
+    r = MockRequest(request)
+    jar.add_cookie_header(r)
+    return r.get_new_headers().get("Cookie")
+
+
+def remove_cookie_by_name(cookiejar, name, domain=None, path=None):
+    """Unsets a cookie by name, by default over all domains and paths.
+
+    Wraps CookieJar.clear(), is O(n).
+    """
+    clearables = []
+    for cookie in cookiejar:
+        if cookie.name != name:
+            continue
+        if domain is not None and domain != cookie.domain:
+            continue
+        if path is not None and path != cookie.path:
+            continue
+        clearables.append((cookie.domain, cookie.path, cookie.name))
+
+    for domain, path, name in clearables:
+        cookiejar.clear(domain, path, name)
+
+
+class CookieConflictError(RuntimeError):
+    """There are two cookies that meet the criteria specified in the cookie jar.
+    Use .get and .set and include domain and path args in order to be more specific.
+    """
+
+
+class RequestsCookieJar(cookielib.CookieJar, MutableMapping):
+    """Compatibility class; is a cookielib.CookieJar, but exposes a dict
+    interface.
+
+    This is the CookieJar we create by default for requests and sessions that
+    don't specify one, since some clients may expect response.cookies and
+    session.cookies to support dict operations.
+
+    Requests does not use the dict interface internally; it's just for
+    compatibility with external client code. All requests code should work
+    out of the box with externally provided instances of ``CookieJar``, e.g.
+    ``LWPCookieJar`` and ``FileCookieJar``.
+
+    Unlike a regular CookieJar, this class is pickleable.
+
+    .. warning:: dictionary operations that are normally O(1) may be O(n).
+    """
+
+    def get(self, name, default=None, domain=None, path=None):
+        """Dict-like get() that also supports optional domain and path args in
+        order to resolve naming collisions from using one cookie jar over
+        multiple domains.
+
+        .. warning:: operation is O(n), not O(1).
+        """
+        try:
+            return self._find_no_duplicates(name, domain, path)
+        except KeyError:
+            return default
+
+    def set(self, name, value, **kwargs):
+        """Dict-like set() that also supports optional domain and path args in
+        order to resolve naming collisions from using one cookie jar over
+        multiple domains.
+        """
+        # support client code that unsets cookies by assignment of a None value:
+        if value is None:
+            remove_cookie_by_name(
+                self, name, domain=kwargs.get("domain"), path=kwargs.get("path")
+            )
+            return
+
+        if isinstance(value, Morsel):
+            c = morsel_to_cookie(value)
+        else:
+            c = create_cookie(name, value, **kwargs)
+        self.set_cookie(c)
+        return c
+
+    def iterkeys(self):
+        """Dict-like iterkeys() that returns an iterator of names of cookies
+        from the jar.
+
+        .. seealso:: itervalues() and iteritems().
+        """
+        for cookie in iter(self):
+            yield cookie.name
+
+    def keys(self):
+        """Dict-like keys() that returns a list of names of cookies from the
+        jar.
+
+        .. seealso:: values() and items().
+        """
+        return list(self.iterkeys())
+
+    def itervalues(self):
+        """Dict-like itervalues() that returns an iterator of values of cookies
+        from the jar.
+
+        .. seealso:: iterkeys() and iteritems().
+        """
+        for cookie in iter(self):
+            yield cookie.value
+
+    def values(self):
+        """Dict-like values() that returns a list of values of cookies from the
+        jar.
+
+        .. seealso:: keys() and items().
+        """
+        return list(self.itervalues())
+
+    def iteritems(self):
+        """Dict-like iteritems() that returns an iterator of name-value tuples
+        from the jar.
+
+        .. seealso:: iterkeys() and itervalues().
+        """
+        for cookie in iter(self):
+            yield cookie.name, cookie.value
+
+    def items(self):
+        """Dict-like items() that returns a list of name-value tuples from the
+        jar. Allows client-code to call ``dict(RequestsCookieJar)`` and get a
+        vanilla python dict of key value pairs.
+
+        .. seealso:: keys() and values().
+        """
+        return list(self.iteritems())
+
+    def list_domains(self):
+        """Utility method to list all the domains in the jar."""
+        domains = []
+        for cookie in iter(self):
+            if cookie.domain not in domains:
+                domains.append(cookie.domain)
+        return domains
+
+    def list_paths(self):
+        """Utility method to list all the paths in the jar."""
+        paths = []
+        for cookie in iter(self):
+            if cookie.path not in paths:
+                paths.append(cookie.path)
+        return paths
+
+    def multiple_domains(self):
+        """Returns True if there are multiple domains in the jar.
+        Returns False otherwise.
+
+        :rtype: bool
+        """
+        domains = []
+        for cookie in iter(self):
+            if cookie.domain is not None and cookie.domain in domains:
+                return True
+            domains.append(cookie.domain)
+        return False  # there is only one domain in jar
+
+    def get_dict(self, domain=None, path=None):
+        """Takes as an argument an optional domain and path and returns a plain
+        old Python dict of name-value pairs of cookies that meet the
+        requirements.
+
+        :rtype: dict
+        """
+        dictionary = {}
+        for cookie in iter(self):
+            if (domain is None or cookie.domain == domain) and (
+                path is None or cookie.path == path
+            ):
+                dictionary[cookie.name] = cookie.value
+        return dictionary
+
+    def __contains__(self, name):
+        try:
+            return super().__contains__(name)
+        except CookieConflictError:
+            return True
+
+    def __getitem__(self, name):
+        """Dict-like __getitem__() for compatibility with client code. Throws
+        exception if there are more than one cookie with name. In that case,
+        use the more explicit get() method instead.
+
+        .. warning:: operation is O(n), not O(1).
+        """
+        return self._find_no_duplicates(name)
+
+    def __setitem__(self, name, value):
+        """Dict-like __setitem__ for compatibility with client code. Throws
+        exception if there is already a cookie of that name in the jar. In that
+        case, use the more explicit set() method instead.
+        """
+        self.set(name, value)
+
+    def __delitem__(self, name):
+        """Deletes a cookie given a name. Wraps ``cookielib.CookieJar``'s
+        ``remove_cookie_by_name()``.
+        """
+        remove_cookie_by_name(self, name)
+
+    def set_cookie(self, cookie, *args, **kwargs):
+        if (
+            hasattr(cookie.value, "startswith")
+            and cookie.value.startswith('"')
+            and cookie.value.endswith('"')
+        ):
+            cookie.value = cookie.value.replace('\\"', "")
+        return super().set_cookie(cookie, *args, **kwargs)
+
+    def update(self, other):
+        """Updates this jar with cookies from another CookieJar or dict-like"""
+        if isinstance(other, cookielib.CookieJar):
+            for cookie in other:
+                self.set_cookie(copy.copy(cookie))
+        else:
+            super().update(other)
+
+    def _find(self, name, domain=None, path=None):
+        """Requests uses this method internally to get cookie values.
+
+        If there are conflicting cookies, _find arbitrarily chooses one.
+        See _find_no_duplicates if you want an exception thrown if there are
+        conflicting cookies.
+
+        :param name: a string containing name of cookie
+        :param domain: (optional) string containing domain of cookie
+        :param path: (optional) string containing path of cookie
+        :return: cookie.value
+        """
+        for cookie in iter(self):
+            if cookie.name == name:
+                if domain is None or cookie.domain == domain:
+                    if path is None or cookie.path == path:
+                        return cookie.value
+
+        raise KeyError(f"name={name!r}, domain={domain!r}, path={path!r}")
+
+    def _find_no_duplicates(self, name, domain=None, path=None):
+        """Both ``__get_item__`` and ``get`` call this function: it's never
+        used elsewhere in Requests.
+
+        :param name: a string containing name of cookie
+        :param domain: (optional) string containing domain of cookie
+        :param path: (optional) string containing path of cookie
+        :raises KeyError: if cookie is not found
+        :raises CookieConflictError: if there are multiple cookies
+            that match name and optionally domain and path
+        :return: cookie.value
+        """
+        toReturn = None
+        for cookie in iter(self):
+            if cookie.name == name:
+                if domain is None or cookie.domain == domain:
+                    if path is None or cookie.path == path:
+                        if toReturn is not None:
+                            # if there are multiple cookies that meet passed in criteria
+                            raise CookieConflictError(
+                                f"There are multiple cookies with name, {name!r}"
+                            )
+                        # we will eventually return this as long as no cookie conflict
+                        toReturn = cookie.value
+
+        if toReturn:
+            return toReturn
+        raise KeyError(f"name={name!r}, domain={domain!r}, path={path!r}")
+
+    def __getstate__(self):
+        """Unlike a normal CookieJar, this class is pickleable."""
+        state = self.__dict__.copy()
+        # remove the unpickleable RLock object
+        state.pop("_cookies_lock")
+        return state
+
+    def __setstate__(self, state):
+        """Unlike a normal CookieJar, this class is pickleable."""
+        self.__dict__.update(state)
+        if "_cookies_lock" not in self.__dict__:
+            self._cookies_lock = threading.RLock()
+
+    def copy(self):
+        """Return a copy of this RequestsCookieJar."""
+        new_cj = RequestsCookieJar()
+        new_cj.set_policy(self.get_policy())
+        new_cj.update(self)
+        return new_cj
+
+    def get_policy(self):
+        """Return the CookiePolicy instance used."""
+        return self._policy
+
+
+def _copy_cookie_jar(jar):
+    if jar is None:
+        return None
+
+    if hasattr(jar, "copy"):
+        # We're dealing with an instance of RequestsCookieJar
+        return jar.copy()
+    # We're dealing with a generic CookieJar instance
+    new_jar = copy.copy(jar)
+    new_jar.clear()
+    for cookie in jar:
+        new_jar.set_cookie(copy.copy(cookie))
+    return new_jar
+
+
+def create_cookie(name, value, **kwargs):
+    """Make a cookie from underspecified parameters.
+
+    By default, the pair of `name` and `value` will be set for the domain ''
+    and sent on every request (this is sometimes called a "supercookie").
+    """
+    result = {
+        "version": 0,
+        "name": name,
+        "value": value,
+        "port": None,
+        "domain": "",
+        "path": "/",
+        "secure": False,
+        "expires": None,
+        "discard": True,
+        "comment": None,
+        "comment_url": None,
+        "rest": {"HttpOnly": None},
+        "rfc2109": False,
+    }
+
+    badargs = set(kwargs) - set(result)
+    if badargs:
+        raise TypeError(
+            f"create_cookie() got unexpected keyword arguments: {list(badargs)}"
+        )
+
+    result.update(kwargs)
+    result["port_specified"] = bool(result["port"])
+    result["domain_specified"] = bool(result["domain"])
+    result["domain_initial_dot"] = result["domain"].startswith(".")
+    result["path_specified"] = bool(result["path"])
+
+    return cookielib.Cookie(**result)
+
+
+def morsel_to_cookie(morsel):
+    """Convert a Morsel object into a Cookie containing the one k/v pair."""
+
+    expires = None
+    if morsel["max-age"]:
+        try:
+            expires = int(time.time() + int(morsel["max-age"]))
+        except ValueError:
+            raise TypeError(f"max-age: {morsel['max-age']} must be integer")
+    elif morsel["expires"]:
+        time_template = "%a, %d-%b-%Y %H:%M:%S GMT"
+        expires = calendar.timegm(time.strptime(morsel["expires"], time_template))
+    return create_cookie(
+        comment=morsel["comment"],
+        comment_url=bool(morsel["comment"]),
+        discard=False,
+        domain=morsel["domain"],
+        expires=expires,
+        name=morsel.key,
+        path=morsel["path"],
+        port=None,
+        rest={"HttpOnly": morsel["httponly"]},
+        rfc2109=False,
+        secure=bool(morsel["secure"]),
+        value=morsel.value,
+        version=morsel["version"] or 0,
+    )
+
+
+def cookiejar_from_dict(cookie_dict, cookiejar=None, overwrite=True):
+    """Returns a CookieJar from a key/value dictionary.
+
+    :param cookie_dict: Dict of key/values to insert into CookieJar.
+    :param cookiejar: (optional) A cookiejar to add the cookies to.
+    :param overwrite: (optional) If False, will not replace cookies
+        already in the jar with new ones.
+    :rtype: CookieJar
+    """
+    if cookiejar is None:
+        cookiejar = RequestsCookieJar()
+
+    if cookie_dict is not None:
+        names_from_jar = [cookie.name for cookie in cookiejar]
+        for name in cookie_dict:
+            if overwrite or (name not in names_from_jar):
+                cookiejar.set_cookie(create_cookie(name, cookie_dict[name]))
+
+    return cookiejar
+
+
+def merge_cookies(cookiejar, cookies):
+    """Add cookies to cookiejar and returns a merged CookieJar.
+
+    :param cookiejar: CookieJar object to add the cookies to.
+    :param cookies: Dictionary or CookieJar object to be added.
+    :rtype: CookieJar
+    """
+    if not isinstance(cookiejar, cookielib.CookieJar):
+        raise ValueError("You can only merge into CookieJar")
+
+    if isinstance(cookies, dict):
+        cookiejar = cookiejar_from_dict(cookies, cookiejar=cookiejar, overwrite=False)
+    elif isinstance(cookies, cookielib.CookieJar):
+        try:
+            cookiejar.update(cookies)
+        except AttributeError:
+            for cookie_in_jar in cookies:
+                cookiejar.set_cookie(cookie_in_jar)
+
+    return cookiejar
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/exceptions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/exceptions.py
new file mode 100644
index 0000000000000000000000000000000000000000..168d07390dfc366102b8197e4b271e493bd94d11
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/exceptions.py
@@ -0,0 +1,141 @@
+"""
+requests.exceptions
+~~~~~~~~~~~~~~~~~~~
+
+This module contains the set of Requests' exceptions.
+"""
+from pip._vendor.urllib3.exceptions import HTTPError as BaseHTTPError
+
+from .compat import JSONDecodeError as CompatJSONDecodeError
+
+
+class RequestException(IOError):
+    """There was an ambiguous exception that occurred while handling your
+    request.
+    """
+
+    def __init__(self, *args, **kwargs):
+        """Initialize RequestException with `request` and `response` objects."""
+        response = kwargs.pop("response", None)
+        self.response = response
+        self.request = kwargs.pop("request", None)
+        if response is not None and not self.request and hasattr(response, "request"):
+            self.request = self.response.request
+        super().__init__(*args, **kwargs)
+
+
+class InvalidJSONError(RequestException):
+    """A JSON error occurred."""
+
+
+class JSONDecodeError(InvalidJSONError, CompatJSONDecodeError):
+    """Couldn't decode the text into json"""
+
+    def __init__(self, *args, **kwargs):
+        """
+        Construct the JSONDecodeError instance first with all
+        args. Then use it's args to construct the IOError so that
+        the json specific args aren't used as IOError specific args
+        and the error message from JSONDecodeError is preserved.
+        """
+        CompatJSONDecodeError.__init__(self, *args)
+        InvalidJSONError.__init__(self, *self.args, **kwargs)
+
+
+class HTTPError(RequestException):
+    """An HTTP error occurred."""
+
+
+class ConnectionError(RequestException):
+    """A Connection error occurred."""
+
+
+class ProxyError(ConnectionError):
+    """A proxy error occurred."""
+
+
+class SSLError(ConnectionError):
+    """An SSL error occurred."""
+
+
+class Timeout(RequestException):
+    """The request timed out.
+
+    Catching this error will catch both
+    :exc:`~requests.exceptions.ConnectTimeout` and
+    :exc:`~requests.exceptions.ReadTimeout` errors.
+    """
+
+
+class ConnectTimeout(ConnectionError, Timeout):
+    """The request timed out while trying to connect to the remote server.
+
+    Requests that produced this error are safe to retry.
+    """
+
+
+class ReadTimeout(Timeout):
+    """The server did not send any data in the allotted amount of time."""
+
+
+class URLRequired(RequestException):
+    """A valid URL is required to make a request."""
+
+
+class TooManyRedirects(RequestException):
+    """Too many redirects."""
+
+
+class MissingSchema(RequestException, ValueError):
+    """The URL scheme (e.g. http or https) is missing."""
+
+
+class InvalidSchema(RequestException, ValueError):
+    """The URL scheme provided is either invalid or unsupported."""
+
+
+class InvalidURL(RequestException, ValueError):
+    """The URL provided was somehow invalid."""
+
+
+class InvalidHeader(RequestException, ValueError):
+    """The header value provided was somehow invalid."""
+
+
+class InvalidProxyURL(InvalidURL):
+    """The proxy URL provided is invalid."""
+
+
+class ChunkedEncodingError(RequestException):
+    """The server declared chunked encoding but sent an invalid chunk."""
+
+
+class ContentDecodingError(RequestException, BaseHTTPError):
+    """Failed to decode response content."""
+
+
+class StreamConsumedError(RequestException, TypeError):
+    """The content for this response was already consumed."""
+
+
+class RetryError(RequestException):
+    """Custom retries logic failed"""
+
+
+class UnrewindableBodyError(RequestException):
+    """Requests encountered an error when trying to rewind a body."""
+
+
+# Warnings
+
+
+class RequestsWarning(Warning):
+    """Base warning for Requests."""
+
+
+class FileModeWarning(RequestsWarning, DeprecationWarning):
+    """A file was opened in text mode, but Requests determined its binary length."""
+
+
+class RequestsDependencyWarning(RequestsWarning):
+    """An imported dependency doesn't match the expected version range."""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/help.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/help.py
new file mode 100644
index 0000000000000000000000000000000000000000..2d292c2f062cd80cd108aac503eae7b635ceec8d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/help.py
@@ -0,0 +1,131 @@
+"""Module containing bug report helper(s)."""
+
+import json
+import platform
+import ssl
+import sys
+
+from pip._vendor import idna
+from pip._vendor import urllib3
+
+from . import __version__ as requests_version
+
+charset_normalizer = None
+
+try:
+    from pip._vendor import chardet
+except ImportError:
+    chardet = None
+
+try:
+    from pip._vendor.urllib3.contrib import pyopenssl
+except ImportError:
+    pyopenssl = None
+    OpenSSL = None
+    cryptography = None
+else:
+    import cryptography
+    import OpenSSL
+
+
+def _implementation():
+    """Return a dict with the Python implementation and version.
+
+    Provide both the name and the version of the Python implementation
+    currently running. For example, on CPython 3.10.3 it will return
+    {'name': 'CPython', 'version': '3.10.3'}.
+
+    This function works best on CPython and PyPy: in particular, it probably
+    doesn't work for Jython or IronPython. Future investigation should be done
+    to work out the correct shape of the code for those platforms.
+    """
+    implementation = platform.python_implementation()
+
+    if implementation == "CPython":
+        implementation_version = platform.python_version()
+    elif implementation == "PyPy":
+        implementation_version = "{}.{}.{}".format(
+            sys.pypy_version_info.major,
+            sys.pypy_version_info.minor,
+            sys.pypy_version_info.micro,
+        )
+        if sys.pypy_version_info.releaselevel != "final":
+            implementation_version = "".join(
+                [implementation_version, sys.pypy_version_info.releaselevel]
+            )
+    elif implementation == "Jython":
+        implementation_version = platform.python_version()  # Complete Guess
+    elif implementation == "IronPython":
+        implementation_version = platform.python_version()  # Complete Guess
+    else:
+        implementation_version = "Unknown"
+
+    return {"name": implementation, "version": implementation_version}
+
+
+def info():
+    """Generate information for a bug report."""
+    try:
+        platform_info = {
+            "system": platform.system(),
+            "release": platform.release(),
+        }
+    except OSError:
+        platform_info = {
+            "system": "Unknown",
+            "release": "Unknown",
+        }
+
+    implementation_info = _implementation()
+    urllib3_info = {"version": urllib3.__version__}
+    charset_normalizer_info = {"version": None}
+    chardet_info = {"version": None}
+    if charset_normalizer:
+        charset_normalizer_info = {"version": charset_normalizer.__version__}
+    if chardet:
+        chardet_info = {"version": chardet.__version__}
+
+    pyopenssl_info = {
+        "version": None,
+        "openssl_version": "",
+    }
+    if OpenSSL:
+        pyopenssl_info = {
+            "version": OpenSSL.__version__,
+            "openssl_version": f"{OpenSSL.SSL.OPENSSL_VERSION_NUMBER:x}",
+        }
+    cryptography_info = {
+        "version": getattr(cryptography, "__version__", ""),
+    }
+    idna_info = {
+        "version": getattr(idna, "__version__", ""),
+    }
+
+    system_ssl = ssl.OPENSSL_VERSION_NUMBER
+    system_ssl_info = {"version": f"{system_ssl:x}" if system_ssl is not None else ""}
+
+    return {
+        "platform": platform_info,
+        "implementation": implementation_info,
+        "system_ssl": system_ssl_info,
+        "using_pyopenssl": pyopenssl is not None,
+        "using_charset_normalizer": chardet is None,
+        "pyOpenSSL": pyopenssl_info,
+        "urllib3": urllib3_info,
+        "chardet": chardet_info,
+        "charset_normalizer": charset_normalizer_info,
+        "cryptography": cryptography_info,
+        "idna": idna_info,
+        "requests": {
+            "version": requests_version,
+        },
+    }
+
+
+def main():
+    """Pretty-print the bug information as JSON."""
+    print(json.dumps(info(), sort_keys=True, indent=2))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/hooks.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/hooks.py
new file mode 100644
index 0000000000000000000000000000000000000000..d181ba2ec2e55d274897315887b78fbdca757da8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/hooks.py
@@ -0,0 +1,33 @@
+"""
+requests.hooks
+~~~~~~~~~~~~~~
+
+This module provides the capabilities for the Requests hooks system.
+
+Available hooks:
+
+``response``:
+    The response generated from a Request.
+"""
+HOOKS = ["response"]
+
+
+def default_hooks():
+    return {event: [] for event in HOOKS}
+
+
+# TODO: response is the only one
+
+
+def dispatch_hook(key, hooks, hook_data, **kwargs):
+    """Dispatches a hook dictionary on a given piece of data."""
+    hooks = hooks or {}
+    hooks = hooks.get(key)
+    if hooks:
+        if hasattr(hooks, "__call__"):
+            hooks = [hooks]
+        for hook in hooks:
+            _hook_data = hook(hook_data, **kwargs)
+            if _hook_data is not None:
+                hook_data = _hook_data
+    return hook_data
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/models.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/models.py
new file mode 100644
index 0000000000000000000000000000000000000000..76e6f199c0042cec6500f53c062ff9ea1033e79d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/models.py
@@ -0,0 +1,1034 @@
+"""
+requests.models
+~~~~~~~~~~~~~~~
+
+This module contains the primary objects that power Requests.
+"""
+
+import datetime
+
+# Import encoding now, to avoid implicit import later.
+# Implicit import within threads may cause LookupError when standard library is in a ZIP,
+# such as in Embedded Python. See https://github.com/psf/requests/issues/3578.
+import encodings.idna  # noqa: F401
+from io import UnsupportedOperation
+
+from pip._vendor.urllib3.exceptions import (
+    DecodeError,
+    LocationParseError,
+    ProtocolError,
+    ReadTimeoutError,
+    SSLError,
+)
+from pip._vendor.urllib3.fields import RequestField
+from pip._vendor.urllib3.filepost import encode_multipart_formdata
+from pip._vendor.urllib3.util import parse_url
+
+from ._internal_utils import to_native_string, unicode_is_ascii
+from .auth import HTTPBasicAuth
+from .compat import (
+    Callable,
+    JSONDecodeError,
+    Mapping,
+    basestring,
+    builtin_str,
+    chardet,
+    cookielib,
+)
+from .compat import json as complexjson
+from .compat import urlencode, urlsplit, urlunparse
+from .cookies import _copy_cookie_jar, cookiejar_from_dict, get_cookie_header
+from .exceptions import (
+    ChunkedEncodingError,
+    ConnectionError,
+    ContentDecodingError,
+    HTTPError,
+    InvalidJSONError,
+    InvalidURL,
+)
+from .exceptions import JSONDecodeError as RequestsJSONDecodeError
+from .exceptions import MissingSchema
+from .exceptions import SSLError as RequestsSSLError
+from .exceptions import StreamConsumedError
+from .hooks import default_hooks
+from .status_codes import codes
+from .structures import CaseInsensitiveDict
+from .utils import (
+    check_header_validity,
+    get_auth_from_url,
+    guess_filename,
+    guess_json_utf,
+    iter_slices,
+    parse_header_links,
+    requote_uri,
+    stream_decode_response_unicode,
+    super_len,
+    to_key_val_list,
+)
+
+#: The set of HTTP status codes that indicate an automatically
+#: processable redirect.
+REDIRECT_STATI = (
+    codes.moved,  # 301
+    codes.found,  # 302
+    codes.other,  # 303
+    codes.temporary_redirect,  # 307
+    codes.permanent_redirect,  # 308
+)
+
+DEFAULT_REDIRECT_LIMIT = 30
+CONTENT_CHUNK_SIZE = 10 * 1024
+ITER_CHUNK_SIZE = 512
+
+
+class RequestEncodingMixin:
+    @property
+    def path_url(self):
+        """Build the path URL to use."""
+
+        url = []
+
+        p = urlsplit(self.url)
+
+        path = p.path
+        if not path:
+            path = "/"
+
+        url.append(path)
+
+        query = p.query
+        if query:
+            url.append("?")
+            url.append(query)
+
+        return "".join(url)
+
+    @staticmethod
+    def _encode_params(data):
+        """Encode parameters in a piece of data.
+
+        Will successfully encode parameters when passed as a dict or a list of
+        2-tuples. Order is retained if data is a list of 2-tuples but arbitrary
+        if parameters are supplied as a dict.
+        """
+
+        if isinstance(data, (str, bytes)):
+            return data
+        elif hasattr(data, "read"):
+            return data
+        elif hasattr(data, "__iter__"):
+            result = []
+            for k, vs in to_key_val_list(data):
+                if isinstance(vs, basestring) or not hasattr(vs, "__iter__"):
+                    vs = [vs]
+                for v in vs:
+                    if v is not None:
+                        result.append(
+                            (
+                                k.encode("utf-8") if isinstance(k, str) else k,
+                                v.encode("utf-8") if isinstance(v, str) else v,
+                            )
+                        )
+            return urlencode(result, doseq=True)
+        else:
+            return data
+
+    @staticmethod
+    def _encode_files(files, data):
+        """Build the body for a multipart/form-data request.
+
+        Will successfully encode files when passed as a dict or a list of
+        tuples. Order is retained if data is a list of tuples but arbitrary
+        if parameters are supplied as a dict.
+        The tuples may be 2-tuples (filename, fileobj), 3-tuples (filename, fileobj, contentype)
+        or 4-tuples (filename, fileobj, contentype, custom_headers).
+        """
+        if not files:
+            raise ValueError("Files must be provided.")
+        elif isinstance(data, basestring):
+            raise ValueError("Data must not be a string.")
+
+        new_fields = []
+        fields = to_key_val_list(data or {})
+        files = to_key_val_list(files or {})
+
+        for field, val in fields:
+            if isinstance(val, basestring) or not hasattr(val, "__iter__"):
+                val = [val]
+            for v in val:
+                if v is not None:
+                    # Don't call str() on bytestrings: in Py3 it all goes wrong.
+                    if not isinstance(v, bytes):
+                        v = str(v)
+
+                    new_fields.append(
+                        (
+                            field.decode("utf-8")
+                            if isinstance(field, bytes)
+                            else field,
+                            v.encode("utf-8") if isinstance(v, str) else v,
+                        )
+                    )
+
+        for (k, v) in files:
+            # support for explicit filename
+            ft = None
+            fh = None
+            if isinstance(v, (tuple, list)):
+                if len(v) == 2:
+                    fn, fp = v
+                elif len(v) == 3:
+                    fn, fp, ft = v
+                else:
+                    fn, fp, ft, fh = v
+            else:
+                fn = guess_filename(v) or k
+                fp = v
+
+            if isinstance(fp, (str, bytes, bytearray)):
+                fdata = fp
+            elif hasattr(fp, "read"):
+                fdata = fp.read()
+            elif fp is None:
+                continue
+            else:
+                fdata = fp
+
+            rf = RequestField(name=k, data=fdata, filename=fn, headers=fh)
+            rf.make_multipart(content_type=ft)
+            new_fields.append(rf)
+
+        body, content_type = encode_multipart_formdata(new_fields)
+
+        return body, content_type
+
+
+class RequestHooksMixin:
+    def register_hook(self, event, hook):
+        """Properly register a hook."""
+
+        if event not in self.hooks:
+            raise ValueError(f'Unsupported event specified, with event name "{event}"')
+
+        if isinstance(hook, Callable):
+            self.hooks[event].append(hook)
+        elif hasattr(hook, "__iter__"):
+            self.hooks[event].extend(h for h in hook if isinstance(h, Callable))
+
+    def deregister_hook(self, event, hook):
+        """Deregister a previously registered hook.
+        Returns True if the hook existed, False if not.
+        """
+
+        try:
+            self.hooks[event].remove(hook)
+            return True
+        except ValueError:
+            return False
+
+
+class Request(RequestHooksMixin):
+    """A user-created :class:`Request ` object.
+
+    Used to prepare a :class:`PreparedRequest `, which is sent to the server.
+
+    :param method: HTTP method to use.
+    :param url: URL to send.
+    :param headers: dictionary of headers to send.
+    :param files: dictionary of {filename: fileobject} files to multipart upload.
+    :param data: the body to attach to the request. If a dictionary or
+        list of tuples ``[(key, value)]`` is provided, form-encoding will
+        take place.
+    :param json: json for the body to attach to the request (if files or data is not specified).
+    :param params: URL parameters to append to the URL. If a dictionary or
+        list of tuples ``[(key, value)]`` is provided, form-encoding will
+        take place.
+    :param auth: Auth handler or (user, pass) tuple.
+    :param cookies: dictionary or CookieJar of cookies to attach to this request.
+    :param hooks: dictionary of callback hooks, for internal usage.
+
+    Usage::
+
+      >>> import requests
+      >>> req = requests.Request('GET', 'https://httpbin.org/get')
+      >>> req.prepare()
+      
+    """
+
+    def __init__(
+        self,
+        method=None,
+        url=None,
+        headers=None,
+        files=None,
+        data=None,
+        params=None,
+        auth=None,
+        cookies=None,
+        hooks=None,
+        json=None,
+    ):
+
+        # Default empty dicts for dict params.
+        data = [] if data is None else data
+        files = [] if files is None else files
+        headers = {} if headers is None else headers
+        params = {} if params is None else params
+        hooks = {} if hooks is None else hooks
+
+        self.hooks = default_hooks()
+        for (k, v) in list(hooks.items()):
+            self.register_hook(event=k, hook=v)
+
+        self.method = method
+        self.url = url
+        self.headers = headers
+        self.files = files
+        self.data = data
+        self.json = json
+        self.params = params
+        self.auth = auth
+        self.cookies = cookies
+
+    def __repr__(self):
+        return f""
+
+    def prepare(self):
+        """Constructs a :class:`PreparedRequest ` for transmission and returns it."""
+        p = PreparedRequest()
+        p.prepare(
+            method=self.method,
+            url=self.url,
+            headers=self.headers,
+            files=self.files,
+            data=self.data,
+            json=self.json,
+            params=self.params,
+            auth=self.auth,
+            cookies=self.cookies,
+            hooks=self.hooks,
+        )
+        return p
+
+
+class PreparedRequest(RequestEncodingMixin, RequestHooksMixin):
+    """The fully mutable :class:`PreparedRequest ` object,
+    containing the exact bytes that will be sent to the server.
+
+    Instances are generated from a :class:`Request ` object, and
+    should not be instantiated manually; doing so may produce undesirable
+    effects.
+
+    Usage::
+
+      >>> import requests
+      >>> req = requests.Request('GET', 'https://httpbin.org/get')
+      >>> r = req.prepare()
+      >>> r
+      
+
+      >>> s = requests.Session()
+      >>> s.send(r)
+      
+    """
+
+    def __init__(self):
+        #: HTTP verb to send to the server.
+        self.method = None
+        #: HTTP URL to send the request to.
+        self.url = None
+        #: dictionary of HTTP headers.
+        self.headers = None
+        # The `CookieJar` used to create the Cookie header will be stored here
+        # after prepare_cookies is called
+        self._cookies = None
+        #: request body to send to the server.
+        self.body = None
+        #: dictionary of callback hooks, for internal usage.
+        self.hooks = default_hooks()
+        #: integer denoting starting position of a readable file-like body.
+        self._body_position = None
+
+    def prepare(
+        self,
+        method=None,
+        url=None,
+        headers=None,
+        files=None,
+        data=None,
+        params=None,
+        auth=None,
+        cookies=None,
+        hooks=None,
+        json=None,
+    ):
+        """Prepares the entire request with the given parameters."""
+
+        self.prepare_method(method)
+        self.prepare_url(url, params)
+        self.prepare_headers(headers)
+        self.prepare_cookies(cookies)
+        self.prepare_body(data, files, json)
+        self.prepare_auth(auth, url)
+
+        # Note that prepare_auth must be last to enable authentication schemes
+        # such as OAuth to work on a fully prepared request.
+
+        # This MUST go after prepare_auth. Authenticators could add a hook
+        self.prepare_hooks(hooks)
+
+    def __repr__(self):
+        return f""
+
+    def copy(self):
+        p = PreparedRequest()
+        p.method = self.method
+        p.url = self.url
+        p.headers = self.headers.copy() if self.headers is not None else None
+        p._cookies = _copy_cookie_jar(self._cookies)
+        p.body = self.body
+        p.hooks = self.hooks
+        p._body_position = self._body_position
+        return p
+
+    def prepare_method(self, method):
+        """Prepares the given HTTP method."""
+        self.method = method
+        if self.method is not None:
+            self.method = to_native_string(self.method.upper())
+
+    @staticmethod
+    def _get_idna_encoded_host(host):
+        from pip._vendor import idna
+
+        try:
+            host = idna.encode(host, uts46=True).decode("utf-8")
+        except idna.IDNAError:
+            raise UnicodeError
+        return host
+
+    def prepare_url(self, url, params):
+        """Prepares the given HTTP URL."""
+        #: Accept objects that have string representations.
+        #: We're unable to blindly call unicode/str functions
+        #: as this will include the bytestring indicator (b'')
+        #: on python 3.x.
+        #: https://github.com/psf/requests/pull/2238
+        if isinstance(url, bytes):
+            url = url.decode("utf8")
+        else:
+            url = str(url)
+
+        # Remove leading whitespaces from url
+        url = url.lstrip()
+
+        # Don't do any URL preparation for non-HTTP schemes like `mailto`,
+        # `data` etc to work around exceptions from `url_parse`, which
+        # handles RFC 3986 only.
+        if ":" in url and not url.lower().startswith("http"):
+            self.url = url
+            return
+
+        # Support for unicode domain names and paths.
+        try:
+            scheme, auth, host, port, path, query, fragment = parse_url(url)
+        except LocationParseError as e:
+            raise InvalidURL(*e.args)
+
+        if not scheme:
+            raise MissingSchema(
+                f"Invalid URL {url!r}: No scheme supplied. "
+                f"Perhaps you meant https://{url}?"
+            )
+
+        if not host:
+            raise InvalidURL(f"Invalid URL {url!r}: No host supplied")
+
+        # In general, we want to try IDNA encoding the hostname if the string contains
+        # non-ASCII characters. This allows users to automatically get the correct IDNA
+        # behaviour. For strings containing only ASCII characters, we need to also verify
+        # it doesn't start with a wildcard (*), before allowing the unencoded hostname.
+        if not unicode_is_ascii(host):
+            try:
+                host = self._get_idna_encoded_host(host)
+            except UnicodeError:
+                raise InvalidURL("URL has an invalid label.")
+        elif host.startswith(("*", ".")):
+            raise InvalidURL("URL has an invalid label.")
+
+        # Carefully reconstruct the network location
+        netloc = auth or ""
+        if netloc:
+            netloc += "@"
+        netloc += host
+        if port:
+            netloc += f":{port}"
+
+        # Bare domains aren't valid URLs.
+        if not path:
+            path = "/"
+
+        if isinstance(params, (str, bytes)):
+            params = to_native_string(params)
+
+        enc_params = self._encode_params(params)
+        if enc_params:
+            if query:
+                query = f"{query}&{enc_params}"
+            else:
+                query = enc_params
+
+        url = requote_uri(urlunparse([scheme, netloc, path, None, query, fragment]))
+        self.url = url
+
+    def prepare_headers(self, headers):
+        """Prepares the given HTTP headers."""
+
+        self.headers = CaseInsensitiveDict()
+        if headers:
+            for header in headers.items():
+                # Raise exception on invalid header value.
+                check_header_validity(header)
+                name, value = header
+                self.headers[to_native_string(name)] = value
+
+    def prepare_body(self, data, files, json=None):
+        """Prepares the given HTTP body data."""
+
+        # Check if file, fo, generator, iterator.
+        # If not, run through normal process.
+
+        # Nottin' on you.
+        body = None
+        content_type = None
+
+        if not data and json is not None:
+            # urllib3 requires a bytes-like body. Python 2's json.dumps
+            # provides this natively, but Python 3 gives a Unicode string.
+            content_type = "application/json"
+
+            try:
+                body = complexjson.dumps(json, allow_nan=False)
+            except ValueError as ve:
+                raise InvalidJSONError(ve, request=self)
+
+            if not isinstance(body, bytes):
+                body = body.encode("utf-8")
+
+        is_stream = all(
+            [
+                hasattr(data, "__iter__"),
+                not isinstance(data, (basestring, list, tuple, Mapping)),
+            ]
+        )
+
+        if is_stream:
+            try:
+                length = super_len(data)
+            except (TypeError, AttributeError, UnsupportedOperation):
+                length = None
+
+            body = data
+
+            if getattr(body, "tell", None) is not None:
+                # Record the current file position before reading.
+                # This will allow us to rewind a file in the event
+                # of a redirect.
+                try:
+                    self._body_position = body.tell()
+                except OSError:
+                    # This differentiates from None, allowing us to catch
+                    # a failed `tell()` later when trying to rewind the body
+                    self._body_position = object()
+
+            if files:
+                raise NotImplementedError(
+                    "Streamed bodies and files are mutually exclusive."
+                )
+
+            if length:
+                self.headers["Content-Length"] = builtin_str(length)
+            else:
+                self.headers["Transfer-Encoding"] = "chunked"
+        else:
+            # Multi-part file uploads.
+            if files:
+                (body, content_type) = self._encode_files(files, data)
+            else:
+                if data:
+                    body = self._encode_params(data)
+                    if isinstance(data, basestring) or hasattr(data, "read"):
+                        content_type = None
+                    else:
+                        content_type = "application/x-www-form-urlencoded"
+
+            self.prepare_content_length(body)
+
+            # Add content-type if it wasn't explicitly provided.
+            if content_type and ("content-type" not in self.headers):
+                self.headers["Content-Type"] = content_type
+
+        self.body = body
+
+    def prepare_content_length(self, body):
+        """Prepare Content-Length header based on request method and body"""
+        if body is not None:
+            length = super_len(body)
+            if length:
+                # If length exists, set it. Otherwise, we fallback
+                # to Transfer-Encoding: chunked.
+                self.headers["Content-Length"] = builtin_str(length)
+        elif (
+            self.method not in ("GET", "HEAD")
+            and self.headers.get("Content-Length") is None
+        ):
+            # Set Content-Length to 0 for methods that can have a body
+            # but don't provide one. (i.e. not GET or HEAD)
+            self.headers["Content-Length"] = "0"
+
+    def prepare_auth(self, auth, url=""):
+        """Prepares the given HTTP auth data."""
+
+        # If no Auth is explicitly provided, extract it from the URL first.
+        if auth is None:
+            url_auth = get_auth_from_url(self.url)
+            auth = url_auth if any(url_auth) else None
+
+        if auth:
+            if isinstance(auth, tuple) and len(auth) == 2:
+                # special-case basic HTTP auth
+                auth = HTTPBasicAuth(*auth)
+
+            # Allow auth to make its changes.
+            r = auth(self)
+
+            # Update self to reflect the auth changes.
+            self.__dict__.update(r.__dict__)
+
+            # Recompute Content-Length
+            self.prepare_content_length(self.body)
+
+    def prepare_cookies(self, cookies):
+        """Prepares the given HTTP cookie data.
+
+        This function eventually generates a ``Cookie`` header from the
+        given cookies using cookielib. Due to cookielib's design, the header
+        will not be regenerated if it already exists, meaning this function
+        can only be called once for the life of the
+        :class:`PreparedRequest ` object. Any subsequent calls
+        to ``prepare_cookies`` will have no actual effect, unless the "Cookie"
+        header is removed beforehand.
+        """
+        if isinstance(cookies, cookielib.CookieJar):
+            self._cookies = cookies
+        else:
+            self._cookies = cookiejar_from_dict(cookies)
+
+        cookie_header = get_cookie_header(self._cookies, self)
+        if cookie_header is not None:
+            self.headers["Cookie"] = cookie_header
+
+    def prepare_hooks(self, hooks):
+        """Prepares the given hooks."""
+        # hooks can be passed as None to the prepare method and to this
+        # method. To prevent iterating over None, simply use an empty list
+        # if hooks is False-y
+        hooks = hooks or []
+        for event in hooks:
+            self.register_hook(event, hooks[event])
+
+
+class Response:
+    """The :class:`Response ` object, which contains a
+    server's response to an HTTP request.
+    """
+
+    __attrs__ = [
+        "_content",
+        "status_code",
+        "headers",
+        "url",
+        "history",
+        "encoding",
+        "reason",
+        "cookies",
+        "elapsed",
+        "request",
+    ]
+
+    def __init__(self):
+        self._content = False
+        self._content_consumed = False
+        self._next = None
+
+        #: Integer Code of responded HTTP Status, e.g. 404 or 200.
+        self.status_code = None
+
+        #: Case-insensitive Dictionary of Response Headers.
+        #: For example, ``headers['content-encoding']`` will return the
+        #: value of a ``'Content-Encoding'`` response header.
+        self.headers = CaseInsensitiveDict()
+
+        #: File-like object representation of response (for advanced usage).
+        #: Use of ``raw`` requires that ``stream=True`` be set on the request.
+        #: This requirement does not apply for use internally to Requests.
+        self.raw = None
+
+        #: Final URL location of Response.
+        self.url = None
+
+        #: Encoding to decode with when accessing r.text.
+        self.encoding = None
+
+        #: A list of :class:`Response ` objects from
+        #: the history of the Request. Any redirect responses will end
+        #: up here. The list is sorted from the oldest to the most recent request.
+        self.history = []
+
+        #: Textual reason of responded HTTP Status, e.g. "Not Found" or "OK".
+        self.reason = None
+
+        #: A CookieJar of Cookies the server sent back.
+        self.cookies = cookiejar_from_dict({})
+
+        #: The amount of time elapsed between sending the request
+        #: and the arrival of the response (as a timedelta).
+        #: This property specifically measures the time taken between sending
+        #: the first byte of the request and finishing parsing the headers. It
+        #: is therefore unaffected by consuming the response content or the
+        #: value of the ``stream`` keyword argument.
+        self.elapsed = datetime.timedelta(0)
+
+        #: The :class:`PreparedRequest ` object to which this
+        #: is a response.
+        self.request = None
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *args):
+        self.close()
+
+    def __getstate__(self):
+        # Consume everything; accessing the content attribute makes
+        # sure the content has been fully read.
+        if not self._content_consumed:
+            self.content
+
+        return {attr: getattr(self, attr, None) for attr in self.__attrs__}
+
+    def __setstate__(self, state):
+        for name, value in state.items():
+            setattr(self, name, value)
+
+        # pickled objects do not have .raw
+        setattr(self, "_content_consumed", True)
+        setattr(self, "raw", None)
+
+    def __repr__(self):
+        return f""
+
+    def __bool__(self):
+        """Returns True if :attr:`status_code` is less than 400.
+
+        This attribute checks if the status code of the response is between
+        400 and 600 to see if there was a client error or a server error. If
+        the status code, is between 200 and 400, this will return True. This
+        is **not** a check to see if the response code is ``200 OK``.
+        """
+        return self.ok
+
+    def __nonzero__(self):
+        """Returns True if :attr:`status_code` is less than 400.
+
+        This attribute checks if the status code of the response is between
+        400 and 600 to see if there was a client error or a server error. If
+        the status code, is between 200 and 400, this will return True. This
+        is **not** a check to see if the response code is ``200 OK``.
+        """
+        return self.ok
+
+    def __iter__(self):
+        """Allows you to use a response as an iterator."""
+        return self.iter_content(128)
+
+    @property
+    def ok(self):
+        """Returns True if :attr:`status_code` is less than 400, False if not.
+
+        This attribute checks if the status code of the response is between
+        400 and 600 to see if there was a client error or a server error. If
+        the status code is between 200 and 400, this will return True. This
+        is **not** a check to see if the response code is ``200 OK``.
+        """
+        try:
+            self.raise_for_status()
+        except HTTPError:
+            return False
+        return True
+
+    @property
+    def is_redirect(self):
+        """True if this Response is a well-formed HTTP redirect that could have
+        been processed automatically (by :meth:`Session.resolve_redirects`).
+        """
+        return "location" in self.headers and self.status_code in REDIRECT_STATI
+
+    @property
+    def is_permanent_redirect(self):
+        """True if this Response one of the permanent versions of redirect."""
+        return "location" in self.headers and self.status_code in (
+            codes.moved_permanently,
+            codes.permanent_redirect,
+        )
+
+    @property
+    def next(self):
+        """Returns a PreparedRequest for the next request in a redirect chain, if there is one."""
+        return self._next
+
+    @property
+    def apparent_encoding(self):
+        """The apparent encoding, provided by the charset_normalizer or chardet libraries."""
+        return chardet.detect(self.content)["encoding"]
+
+    def iter_content(self, chunk_size=1, decode_unicode=False):
+        """Iterates over the response data.  When stream=True is set on the
+        request, this avoids reading the content at once into memory for
+        large responses.  The chunk size is the number of bytes it should
+        read into memory.  This is not necessarily the length of each item
+        returned as decoding can take place.
+
+        chunk_size must be of type int or None. A value of None will
+        function differently depending on the value of `stream`.
+        stream=True will read data as it arrives in whatever size the
+        chunks are received. If stream=False, data is returned as
+        a single chunk.
+
+        If decode_unicode is True, content will be decoded using the best
+        available encoding based on the response.
+        """
+
+        def generate():
+            # Special case for urllib3.
+            if hasattr(self.raw, "stream"):
+                try:
+                    yield from self.raw.stream(chunk_size, decode_content=True)
+                except ProtocolError as e:
+                    raise ChunkedEncodingError(e)
+                except DecodeError as e:
+                    raise ContentDecodingError(e)
+                except ReadTimeoutError as e:
+                    raise ConnectionError(e)
+                except SSLError as e:
+                    raise RequestsSSLError(e)
+            else:
+                # Standard file-like object.
+                while True:
+                    chunk = self.raw.read(chunk_size)
+                    if not chunk:
+                        break
+                    yield chunk
+
+            self._content_consumed = True
+
+        if self._content_consumed and isinstance(self._content, bool):
+            raise StreamConsumedError()
+        elif chunk_size is not None and not isinstance(chunk_size, int):
+            raise TypeError(
+                f"chunk_size must be an int, it is instead a {type(chunk_size)}."
+            )
+        # simulate reading small chunks of the content
+        reused_chunks = iter_slices(self._content, chunk_size)
+
+        stream_chunks = generate()
+
+        chunks = reused_chunks if self._content_consumed else stream_chunks
+
+        if decode_unicode:
+            chunks = stream_decode_response_unicode(chunks, self)
+
+        return chunks
+
+    def iter_lines(
+        self, chunk_size=ITER_CHUNK_SIZE, decode_unicode=False, delimiter=None
+    ):
+        """Iterates over the response data, one line at a time.  When
+        stream=True is set on the request, this avoids reading the
+        content at once into memory for large responses.
+
+        .. note:: This method is not reentrant safe.
+        """
+
+        pending = None
+
+        for chunk in self.iter_content(
+            chunk_size=chunk_size, decode_unicode=decode_unicode
+        ):
+
+            if pending is not None:
+                chunk = pending + chunk
+
+            if delimiter:
+                lines = chunk.split(delimiter)
+            else:
+                lines = chunk.splitlines()
+
+            if lines and lines[-1] and chunk and lines[-1][-1] == chunk[-1]:
+                pending = lines.pop()
+            else:
+                pending = None
+
+            yield from lines
+
+        if pending is not None:
+            yield pending
+
+    @property
+    def content(self):
+        """Content of the response, in bytes."""
+
+        if self._content is False:
+            # Read the contents.
+            if self._content_consumed:
+                raise RuntimeError("The content for this response was already consumed")
+
+            if self.status_code == 0 or self.raw is None:
+                self._content = None
+            else:
+                self._content = b"".join(self.iter_content(CONTENT_CHUNK_SIZE)) or b""
+
+        self._content_consumed = True
+        # don't need to release the connection; that's been handled by urllib3
+        # since we exhausted the data.
+        return self._content
+
+    @property
+    def text(self):
+        """Content of the response, in unicode.
+
+        If Response.encoding is None, encoding will be guessed using
+        ``charset_normalizer`` or ``chardet``.
+
+        The encoding of the response content is determined based solely on HTTP
+        headers, following RFC 2616 to the letter. If you can take advantage of
+        non-HTTP knowledge to make a better guess at the encoding, you should
+        set ``r.encoding`` appropriately before accessing this property.
+        """
+
+        # Try charset from content-type
+        content = None
+        encoding = self.encoding
+
+        if not self.content:
+            return ""
+
+        # Fallback to auto-detected encoding.
+        if self.encoding is None:
+            encoding = self.apparent_encoding
+
+        # Decode unicode from given encoding.
+        try:
+            content = str(self.content, encoding, errors="replace")
+        except (LookupError, TypeError):
+            # A LookupError is raised if the encoding was not found which could
+            # indicate a misspelling or similar mistake.
+            #
+            # A TypeError can be raised if encoding is None
+            #
+            # So we try blindly encoding.
+            content = str(self.content, errors="replace")
+
+        return content
+
+    def json(self, **kwargs):
+        r"""Returns the json-encoded content of a response, if any.
+
+        :param \*\*kwargs: Optional arguments that ``json.loads`` takes.
+        :raises requests.exceptions.JSONDecodeError: If the response body does not
+            contain valid json.
+        """
+
+        if not self.encoding and self.content and len(self.content) > 3:
+            # No encoding set. JSON RFC 4627 section 3 states we should expect
+            # UTF-8, -16 or -32. Detect which one to use; If the detection or
+            # decoding fails, fall back to `self.text` (using charset_normalizer to make
+            # a best guess).
+            encoding = guess_json_utf(self.content)
+            if encoding is not None:
+                try:
+                    return complexjson.loads(self.content.decode(encoding), **kwargs)
+                except UnicodeDecodeError:
+                    # Wrong UTF codec detected; usually because it's not UTF-8
+                    # but some other 8-bit codec.  This is an RFC violation,
+                    # and the server didn't bother to tell us what codec *was*
+                    # used.
+                    pass
+                except JSONDecodeError as e:
+                    raise RequestsJSONDecodeError(e.msg, e.doc, e.pos)
+
+        try:
+            return complexjson.loads(self.text, **kwargs)
+        except JSONDecodeError as e:
+            # Catch JSON-related errors and raise as requests.JSONDecodeError
+            # This aliases json.JSONDecodeError and simplejson.JSONDecodeError
+            raise RequestsJSONDecodeError(e.msg, e.doc, e.pos)
+
+    @property
+    def links(self):
+        """Returns the parsed header links of the response, if any."""
+
+        header = self.headers.get("link")
+
+        resolved_links = {}
+
+        if header:
+            links = parse_header_links(header)
+
+            for link in links:
+                key = link.get("rel") or link.get("url")
+                resolved_links[key] = link
+
+        return resolved_links
+
+    def raise_for_status(self):
+        """Raises :class:`HTTPError`, if one occurred."""
+
+        http_error_msg = ""
+        if isinstance(self.reason, bytes):
+            # We attempt to decode utf-8 first because some servers
+            # choose to localize their reason strings. If the string
+            # isn't utf-8, we fall back to iso-8859-1 for all other
+            # encodings. (See PR #3538)
+            try:
+                reason = self.reason.decode("utf-8")
+            except UnicodeDecodeError:
+                reason = self.reason.decode("iso-8859-1")
+        else:
+            reason = self.reason
+
+        if 400 <= self.status_code < 500:
+            http_error_msg = (
+                f"{self.status_code} Client Error: {reason} for url: {self.url}"
+            )
+
+        elif 500 <= self.status_code < 600:
+            http_error_msg = (
+                f"{self.status_code} Server Error: {reason} for url: {self.url}"
+            )
+
+        if http_error_msg:
+            raise HTTPError(http_error_msg, response=self)
+
+    def close(self):
+        """Releases the connection back to the pool. Once this method has been
+        called the underlying ``raw`` object must not be accessed again.
+
+        *Note: Should not normally need to be called explicitly.*
+        """
+        if not self._content_consumed:
+            self.raw.close()
+
+        release_conn = getattr(self.raw, "release_conn", None)
+        if release_conn is not None:
+            release_conn()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/packages.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/packages.py
new file mode 100644
index 0000000000000000000000000000000000000000..9582fa730f121634348a79c1a8b0cc2df99c616f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/packages.py
@@ -0,0 +1,16 @@
+import sys
+
+# This code exists for backwards compatibility reasons.
+# I don't like it either. Just look the other way. :)
+
+for package in ('urllib3', 'idna', 'chardet'):
+    vendored_package = "pip._vendor." + package
+    locals()[package] = __import__(vendored_package)
+    # This traversal is apparently necessary such that the identities are
+    # preserved (requests.packages.urllib3.* is urllib3.*)
+    for mod in list(sys.modules):
+        if mod == vendored_package or mod.startswith(vendored_package + '.'):
+            unprefixed_mod = mod[len("pip._vendor."):]
+            sys.modules['pip._vendor.requests.packages.' + unprefixed_mod] = sys.modules[mod]
+
+# Kinda cool, though, right?
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/sessions.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/sessions.py
new file mode 100644
index 0000000000000000000000000000000000000000..6cb3b4dae397930fba60e4c08b25b9444783b6f7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/sessions.py
@@ -0,0 +1,831 @@
+"""
+requests.sessions
+~~~~~~~~~~~~~~~~~
+
+This module provides a Session object to manage and persist settings across
+requests (cookies, auth, proxies).
+"""
+import os
+import sys
+import time
+from collections import OrderedDict
+from datetime import timedelta
+
+from ._internal_utils import to_native_string
+from .adapters import HTTPAdapter
+from .auth import _basic_auth_str
+from .compat import Mapping, cookielib, urljoin, urlparse
+from .cookies import (
+    RequestsCookieJar,
+    cookiejar_from_dict,
+    extract_cookies_to_jar,
+    merge_cookies,
+)
+from .exceptions import (
+    ChunkedEncodingError,
+    ContentDecodingError,
+    InvalidSchema,
+    TooManyRedirects,
+)
+from .hooks import default_hooks, dispatch_hook
+
+# formerly defined here, reexposed here for backward compatibility
+from .models import (  # noqa: F401
+    DEFAULT_REDIRECT_LIMIT,
+    REDIRECT_STATI,
+    PreparedRequest,
+    Request,
+)
+from .status_codes import codes
+from .structures import CaseInsensitiveDict
+from .utils import (  # noqa: F401
+    DEFAULT_PORTS,
+    default_headers,
+    get_auth_from_url,
+    get_environ_proxies,
+    get_netrc_auth,
+    requote_uri,
+    resolve_proxies,
+    rewind_body,
+    should_bypass_proxies,
+    to_key_val_list,
+)
+
+# Preferred clock, based on which one is more accurate on a given system.
+if sys.platform == "win32":
+    preferred_clock = time.perf_counter
+else:
+    preferred_clock = time.time
+
+
+def merge_setting(request_setting, session_setting, dict_class=OrderedDict):
+    """Determines appropriate setting for a given request, taking into account
+    the explicit setting on that request, and the setting in the session. If a
+    setting is a dictionary, they will be merged together using `dict_class`
+    """
+
+    if session_setting is None:
+        return request_setting
+
+    if request_setting is None:
+        return session_setting
+
+    # Bypass if not a dictionary (e.g. verify)
+    if not (
+        isinstance(session_setting, Mapping) and isinstance(request_setting, Mapping)
+    ):
+        return request_setting
+
+    merged_setting = dict_class(to_key_val_list(session_setting))
+    merged_setting.update(to_key_val_list(request_setting))
+
+    # Remove keys that are set to None. Extract keys first to avoid altering
+    # the dictionary during iteration.
+    none_keys = [k for (k, v) in merged_setting.items() if v is None]
+    for key in none_keys:
+        del merged_setting[key]
+
+    return merged_setting
+
+
+def merge_hooks(request_hooks, session_hooks, dict_class=OrderedDict):
+    """Properly merges both requests and session hooks.
+
+    This is necessary because when request_hooks == {'response': []}, the
+    merge breaks Session hooks entirely.
+    """
+    if session_hooks is None or session_hooks.get("response") == []:
+        return request_hooks
+
+    if request_hooks is None or request_hooks.get("response") == []:
+        return session_hooks
+
+    return merge_setting(request_hooks, session_hooks, dict_class)
+
+
+class SessionRedirectMixin:
+    def get_redirect_target(self, resp):
+        """Receives a Response. Returns a redirect URI or ``None``"""
+        # Due to the nature of how requests processes redirects this method will
+        # be called at least once upon the original response and at least twice
+        # on each subsequent redirect response (if any).
+        # If a custom mixin is used to handle this logic, it may be advantageous
+        # to cache the redirect location onto the response object as a private
+        # attribute.
+        if resp.is_redirect:
+            location = resp.headers["location"]
+            # Currently the underlying http module on py3 decode headers
+            # in latin1, but empirical evidence suggests that latin1 is very
+            # rarely used with non-ASCII characters in HTTP headers.
+            # It is more likely to get UTF8 header rather than latin1.
+            # This causes incorrect handling of UTF8 encoded location headers.
+            # To solve this, we re-encode the location in latin1.
+            location = location.encode("latin1")
+            return to_native_string(location, "utf8")
+        return None
+
+    def should_strip_auth(self, old_url, new_url):
+        """Decide whether Authorization header should be removed when redirecting"""
+        old_parsed = urlparse(old_url)
+        new_parsed = urlparse(new_url)
+        if old_parsed.hostname != new_parsed.hostname:
+            return True
+        # Special case: allow http -> https redirect when using the standard
+        # ports. This isn't specified by RFC 7235, but is kept to avoid
+        # breaking backwards compatibility with older versions of requests
+        # that allowed any redirects on the same host.
+        if (
+            old_parsed.scheme == "http"
+            and old_parsed.port in (80, None)
+            and new_parsed.scheme == "https"
+            and new_parsed.port in (443, None)
+        ):
+            return False
+
+        # Handle default port usage corresponding to scheme.
+        changed_port = old_parsed.port != new_parsed.port
+        changed_scheme = old_parsed.scheme != new_parsed.scheme
+        default_port = (DEFAULT_PORTS.get(old_parsed.scheme, None), None)
+        if (
+            not changed_scheme
+            and old_parsed.port in default_port
+            and new_parsed.port in default_port
+        ):
+            return False
+
+        # Standard case: root URI must match
+        return changed_port or changed_scheme
+
+    def resolve_redirects(
+        self,
+        resp,
+        req,
+        stream=False,
+        timeout=None,
+        verify=True,
+        cert=None,
+        proxies=None,
+        yield_requests=False,
+        **adapter_kwargs,
+    ):
+        """Receives a Response. Returns a generator of Responses or Requests."""
+
+        hist = []  # keep track of history
+
+        url = self.get_redirect_target(resp)
+        previous_fragment = urlparse(req.url).fragment
+        while url:
+            prepared_request = req.copy()
+
+            # Update history and keep track of redirects.
+            # resp.history must ignore the original request in this loop
+            hist.append(resp)
+            resp.history = hist[1:]
+
+            try:
+                resp.content  # Consume socket so it can be released
+            except (ChunkedEncodingError, ContentDecodingError, RuntimeError):
+                resp.raw.read(decode_content=False)
+
+            if len(resp.history) >= self.max_redirects:
+                raise TooManyRedirects(
+                    f"Exceeded {self.max_redirects} redirects.", response=resp
+                )
+
+            # Release the connection back into the pool.
+            resp.close()
+
+            # Handle redirection without scheme (see: RFC 1808 Section 4)
+            if url.startswith("//"):
+                parsed_rurl = urlparse(resp.url)
+                url = ":".join([to_native_string(parsed_rurl.scheme), url])
+
+            # Normalize url case and attach previous fragment if needed (RFC 7231 7.1.2)
+            parsed = urlparse(url)
+            if parsed.fragment == "" and previous_fragment:
+                parsed = parsed._replace(fragment=previous_fragment)
+            elif parsed.fragment:
+                previous_fragment = parsed.fragment
+            url = parsed.geturl()
+
+            # Facilitate relative 'location' headers, as allowed by RFC 7231.
+            # (e.g. '/path/to/resource' instead of 'http://domain.tld/path/to/resource')
+            # Compliant with RFC3986, we percent encode the url.
+            if not parsed.netloc:
+                url = urljoin(resp.url, requote_uri(url))
+            else:
+                url = requote_uri(url)
+
+            prepared_request.url = to_native_string(url)
+
+            self.rebuild_method(prepared_request, resp)
+
+            # https://github.com/psf/requests/issues/1084
+            if resp.status_code not in (
+                codes.temporary_redirect,
+                codes.permanent_redirect,
+            ):
+                # https://github.com/psf/requests/issues/3490
+                purged_headers = ("Content-Length", "Content-Type", "Transfer-Encoding")
+                for header in purged_headers:
+                    prepared_request.headers.pop(header, None)
+                prepared_request.body = None
+
+            headers = prepared_request.headers
+            headers.pop("Cookie", None)
+
+            # Extract any cookies sent on the response to the cookiejar
+            # in the new request. Because we've mutated our copied prepared
+            # request, use the old one that we haven't yet touched.
+            extract_cookies_to_jar(prepared_request._cookies, req, resp.raw)
+            merge_cookies(prepared_request._cookies, self.cookies)
+            prepared_request.prepare_cookies(prepared_request._cookies)
+
+            # Rebuild auth and proxy information.
+            proxies = self.rebuild_proxies(prepared_request, proxies)
+            self.rebuild_auth(prepared_request, resp)
+
+            # A failed tell() sets `_body_position` to `object()`. This non-None
+            # value ensures `rewindable` will be True, allowing us to raise an
+            # UnrewindableBodyError, instead of hanging the connection.
+            rewindable = prepared_request._body_position is not None and (
+                "Content-Length" in headers or "Transfer-Encoding" in headers
+            )
+
+            # Attempt to rewind consumed file-like object.
+            if rewindable:
+                rewind_body(prepared_request)
+
+            # Override the original request.
+            req = prepared_request
+
+            if yield_requests:
+                yield req
+            else:
+
+                resp = self.send(
+                    req,
+                    stream=stream,
+                    timeout=timeout,
+                    verify=verify,
+                    cert=cert,
+                    proxies=proxies,
+                    allow_redirects=False,
+                    **adapter_kwargs,
+                )
+
+                extract_cookies_to_jar(self.cookies, prepared_request, resp.raw)
+
+                # extract redirect url, if any, for the next loop
+                url = self.get_redirect_target(resp)
+                yield resp
+
+    def rebuild_auth(self, prepared_request, response):
+        """When being redirected we may want to strip authentication from the
+        request to avoid leaking credentials. This method intelligently removes
+        and reapplies authentication where possible to avoid credential loss.
+        """
+        headers = prepared_request.headers
+        url = prepared_request.url
+
+        if "Authorization" in headers and self.should_strip_auth(
+            response.request.url, url
+        ):
+            # If we get redirected to a new host, we should strip out any
+            # authentication headers.
+            del headers["Authorization"]
+
+        # .netrc might have more auth for us on our new host.
+        new_auth = get_netrc_auth(url) if self.trust_env else None
+        if new_auth is not None:
+            prepared_request.prepare_auth(new_auth)
+
+    def rebuild_proxies(self, prepared_request, proxies):
+        """This method re-evaluates the proxy configuration by considering the
+        environment variables. If we are redirected to a URL covered by
+        NO_PROXY, we strip the proxy configuration. Otherwise, we set missing
+        proxy keys for this URL (in case they were stripped by a previous
+        redirect).
+
+        This method also replaces the Proxy-Authorization header where
+        necessary.
+
+        :rtype: dict
+        """
+        headers = prepared_request.headers
+        scheme = urlparse(prepared_request.url).scheme
+        new_proxies = resolve_proxies(prepared_request, proxies, self.trust_env)
+
+        if "Proxy-Authorization" in headers:
+            del headers["Proxy-Authorization"]
+
+        try:
+            username, password = get_auth_from_url(new_proxies[scheme])
+        except KeyError:
+            username, password = None, None
+
+        if username and password:
+            headers["Proxy-Authorization"] = _basic_auth_str(username, password)
+
+        return new_proxies
+
+    def rebuild_method(self, prepared_request, response):
+        """When being redirected we may want to change the method of the request
+        based on certain specs or browser behavior.
+        """
+        method = prepared_request.method
+
+        # https://tools.ietf.org/html/rfc7231#section-6.4.4
+        if response.status_code == codes.see_other and method != "HEAD":
+            method = "GET"
+
+        # Do what the browsers do, despite standards...
+        # First, turn 302s into GETs.
+        if response.status_code == codes.found and method != "HEAD":
+            method = "GET"
+
+        # Second, if a POST is responded to with a 301, turn it into a GET.
+        # This bizarre behaviour is explained in Issue 1704.
+        if response.status_code == codes.moved and method == "POST":
+            method = "GET"
+
+        prepared_request.method = method
+
+
+class Session(SessionRedirectMixin):
+    """A Requests session.
+
+    Provides cookie persistence, connection-pooling, and configuration.
+
+    Basic Usage::
+
+      >>> import requests
+      >>> s = requests.Session()
+      >>> s.get('https://httpbin.org/get')
+      
+
+    Or as a context manager::
+
+      >>> with requests.Session() as s:
+      ...     s.get('https://httpbin.org/get')
+      
+    """
+
+    __attrs__ = [
+        "headers",
+        "cookies",
+        "auth",
+        "proxies",
+        "hooks",
+        "params",
+        "verify",
+        "cert",
+        "adapters",
+        "stream",
+        "trust_env",
+        "max_redirects",
+    ]
+
+    def __init__(self):
+
+        #: A case-insensitive dictionary of headers to be sent on each
+        #: :class:`Request ` sent from this
+        #: :class:`Session `.
+        self.headers = default_headers()
+
+        #: Default Authentication tuple or object to attach to
+        #: :class:`Request `.
+        self.auth = None
+
+        #: Dictionary mapping protocol or protocol and host to the URL of the proxy
+        #: (e.g. {'http': 'foo.bar:3128', 'http://host.name': 'foo.bar:4012'}) to
+        #: be used on each :class:`Request `.
+        self.proxies = {}
+
+        #: Event-handling hooks.
+        self.hooks = default_hooks()
+
+        #: Dictionary of querystring data to attach to each
+        #: :class:`Request `. The dictionary values may be lists for
+        #: representing multivalued query parameters.
+        self.params = {}
+
+        #: Stream response content default.
+        self.stream = False
+
+        #: SSL Verification default.
+        #: Defaults to `True`, requiring requests to verify the TLS certificate at the
+        #: remote end.
+        #: If verify is set to `False`, requests will accept any TLS certificate
+        #: presented by the server, and will ignore hostname mismatches and/or
+        #: expired certificates, which will make your application vulnerable to
+        #: man-in-the-middle (MitM) attacks.
+        #: Only set this to `False` for testing.
+        self.verify = True
+
+        #: SSL client certificate default, if String, path to ssl client
+        #: cert file (.pem). If Tuple, ('cert', 'key') pair.
+        self.cert = None
+
+        #: Maximum number of redirects allowed. If the request exceeds this
+        #: limit, a :class:`TooManyRedirects` exception is raised.
+        #: This defaults to requests.models.DEFAULT_REDIRECT_LIMIT, which is
+        #: 30.
+        self.max_redirects = DEFAULT_REDIRECT_LIMIT
+
+        #: Trust environment settings for proxy configuration, default
+        #: authentication and similar.
+        self.trust_env = True
+
+        #: A CookieJar containing all currently outstanding cookies set on this
+        #: session. By default it is a
+        #: :class:`RequestsCookieJar `, but
+        #: may be any other ``cookielib.CookieJar`` compatible object.
+        self.cookies = cookiejar_from_dict({})
+
+        # Default connection adapters.
+        self.adapters = OrderedDict()
+        self.mount("https://", HTTPAdapter())
+        self.mount("http://", HTTPAdapter())
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *args):
+        self.close()
+
+    def prepare_request(self, request):
+        """Constructs a :class:`PreparedRequest ` for
+        transmission and returns it. The :class:`PreparedRequest` has settings
+        merged from the :class:`Request ` instance and those of the
+        :class:`Session`.
+
+        :param request: :class:`Request` instance to prepare with this
+            session's settings.
+        :rtype: requests.PreparedRequest
+        """
+        cookies = request.cookies or {}
+
+        # Bootstrap CookieJar.
+        if not isinstance(cookies, cookielib.CookieJar):
+            cookies = cookiejar_from_dict(cookies)
+
+        # Merge with session cookies
+        merged_cookies = merge_cookies(
+            merge_cookies(RequestsCookieJar(), self.cookies), cookies
+        )
+
+        # Set environment's basic authentication if not explicitly set.
+        auth = request.auth
+        if self.trust_env and not auth and not self.auth:
+            auth = get_netrc_auth(request.url)
+
+        p = PreparedRequest()
+        p.prepare(
+            method=request.method.upper(),
+            url=request.url,
+            files=request.files,
+            data=request.data,
+            json=request.json,
+            headers=merge_setting(
+                request.headers, self.headers, dict_class=CaseInsensitiveDict
+            ),
+            params=merge_setting(request.params, self.params),
+            auth=merge_setting(auth, self.auth),
+            cookies=merged_cookies,
+            hooks=merge_hooks(request.hooks, self.hooks),
+        )
+        return p
+
+    def request(
+        self,
+        method,
+        url,
+        params=None,
+        data=None,
+        headers=None,
+        cookies=None,
+        files=None,
+        auth=None,
+        timeout=None,
+        allow_redirects=True,
+        proxies=None,
+        hooks=None,
+        stream=None,
+        verify=None,
+        cert=None,
+        json=None,
+    ):
+        """Constructs a :class:`Request `, prepares it and sends it.
+        Returns :class:`Response ` object.
+
+        :param method: method for the new :class:`Request` object.
+        :param url: URL for the new :class:`Request` object.
+        :param params: (optional) Dictionary or bytes to be sent in the query
+            string for the :class:`Request`.
+        :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+            object to send in the body of the :class:`Request`.
+        :param json: (optional) json to send in the body of the
+            :class:`Request`.
+        :param headers: (optional) Dictionary of HTTP Headers to send with the
+            :class:`Request`.
+        :param cookies: (optional) Dict or CookieJar object to send with the
+            :class:`Request`.
+        :param files: (optional) Dictionary of ``'filename': file-like-objects``
+            for multipart encoding upload.
+        :param auth: (optional) Auth tuple or callable to enable
+            Basic/Digest/Custom HTTP Auth.
+        :param timeout: (optional) How long to wait for the server to send
+            data before giving up, as a float, or a :ref:`(connect timeout,
+            read timeout) ` tuple.
+        :type timeout: float or tuple
+        :param allow_redirects: (optional) Set to True by default.
+        :type allow_redirects: bool
+        :param proxies: (optional) Dictionary mapping protocol or protocol and
+            hostname to the URL of the proxy.
+        :param stream: (optional) whether to immediately download the response
+            content. Defaults to ``False``.
+        :param verify: (optional) Either a boolean, in which case it controls whether we verify
+            the server's TLS certificate, or a string, in which case it must be a path
+            to a CA bundle to use. Defaults to ``True``. When set to
+            ``False``, requests will accept any TLS certificate presented by
+            the server, and will ignore hostname mismatches and/or expired
+            certificates, which will make your application vulnerable to
+            man-in-the-middle (MitM) attacks. Setting verify to ``False``
+            may be useful during local development or testing.
+        :param cert: (optional) if String, path to ssl client cert file (.pem).
+            If Tuple, ('cert', 'key') pair.
+        :rtype: requests.Response
+        """
+        # Create the Request.
+        req = Request(
+            method=method.upper(),
+            url=url,
+            headers=headers,
+            files=files,
+            data=data or {},
+            json=json,
+            params=params or {},
+            auth=auth,
+            cookies=cookies,
+            hooks=hooks,
+        )
+        prep = self.prepare_request(req)
+
+        proxies = proxies or {}
+
+        settings = self.merge_environment_settings(
+            prep.url, proxies, stream, verify, cert
+        )
+
+        # Send the request.
+        send_kwargs = {
+            "timeout": timeout,
+            "allow_redirects": allow_redirects,
+        }
+        send_kwargs.update(settings)
+        resp = self.send(prep, **send_kwargs)
+
+        return resp
+
+    def get(self, url, **kwargs):
+        r"""Sends a GET request. Returns :class:`Response` object.
+
+        :param url: URL for the new :class:`Request` object.
+        :param \*\*kwargs: Optional arguments that ``request`` takes.
+        :rtype: requests.Response
+        """
+
+        kwargs.setdefault("allow_redirects", True)
+        return self.request("GET", url, **kwargs)
+
+    def options(self, url, **kwargs):
+        r"""Sends a OPTIONS request. Returns :class:`Response` object.
+
+        :param url: URL for the new :class:`Request` object.
+        :param \*\*kwargs: Optional arguments that ``request`` takes.
+        :rtype: requests.Response
+        """
+
+        kwargs.setdefault("allow_redirects", True)
+        return self.request("OPTIONS", url, **kwargs)
+
+    def head(self, url, **kwargs):
+        r"""Sends a HEAD request. Returns :class:`Response` object.
+
+        :param url: URL for the new :class:`Request` object.
+        :param \*\*kwargs: Optional arguments that ``request`` takes.
+        :rtype: requests.Response
+        """
+
+        kwargs.setdefault("allow_redirects", False)
+        return self.request("HEAD", url, **kwargs)
+
+    def post(self, url, data=None, json=None, **kwargs):
+        r"""Sends a POST request. Returns :class:`Response` object.
+
+        :param url: URL for the new :class:`Request` object.
+        :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+            object to send in the body of the :class:`Request`.
+        :param json: (optional) json to send in the body of the :class:`Request`.
+        :param \*\*kwargs: Optional arguments that ``request`` takes.
+        :rtype: requests.Response
+        """
+
+        return self.request("POST", url, data=data, json=json, **kwargs)
+
+    def put(self, url, data=None, **kwargs):
+        r"""Sends a PUT request. Returns :class:`Response` object.
+
+        :param url: URL for the new :class:`Request` object.
+        :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+            object to send in the body of the :class:`Request`.
+        :param \*\*kwargs: Optional arguments that ``request`` takes.
+        :rtype: requests.Response
+        """
+
+        return self.request("PUT", url, data=data, **kwargs)
+
+    def patch(self, url, data=None, **kwargs):
+        r"""Sends a PATCH request. Returns :class:`Response` object.
+
+        :param url: URL for the new :class:`Request` object.
+        :param data: (optional) Dictionary, list of tuples, bytes, or file-like
+            object to send in the body of the :class:`Request`.
+        :param \*\*kwargs: Optional arguments that ``request`` takes.
+        :rtype: requests.Response
+        """
+
+        return self.request("PATCH", url, data=data, **kwargs)
+
+    def delete(self, url, **kwargs):
+        r"""Sends a DELETE request. Returns :class:`Response` object.
+
+        :param url: URL for the new :class:`Request` object.
+        :param \*\*kwargs: Optional arguments that ``request`` takes.
+        :rtype: requests.Response
+        """
+
+        return self.request("DELETE", url, **kwargs)
+
+    def send(self, request, **kwargs):
+        """Send a given PreparedRequest.
+
+        :rtype: requests.Response
+        """
+        # Set defaults that the hooks can utilize to ensure they always have
+        # the correct parameters to reproduce the previous request.
+        kwargs.setdefault("stream", self.stream)
+        kwargs.setdefault("verify", self.verify)
+        kwargs.setdefault("cert", self.cert)
+        if "proxies" not in kwargs:
+            kwargs["proxies"] = resolve_proxies(request, self.proxies, self.trust_env)
+
+        # It's possible that users might accidentally send a Request object.
+        # Guard against that specific failure case.
+        if isinstance(request, Request):
+            raise ValueError("You can only send PreparedRequests.")
+
+        # Set up variables needed for resolve_redirects and dispatching of hooks
+        allow_redirects = kwargs.pop("allow_redirects", True)
+        stream = kwargs.get("stream")
+        hooks = request.hooks
+
+        # Get the appropriate adapter to use
+        adapter = self.get_adapter(url=request.url)
+
+        # Start time (approximately) of the request
+        start = preferred_clock()
+
+        # Send the request
+        r = adapter.send(request, **kwargs)
+
+        # Total elapsed time of the request (approximately)
+        elapsed = preferred_clock() - start
+        r.elapsed = timedelta(seconds=elapsed)
+
+        # Response manipulation hooks
+        r = dispatch_hook("response", hooks, r, **kwargs)
+
+        # Persist cookies
+        if r.history:
+
+            # If the hooks create history then we want those cookies too
+            for resp in r.history:
+                extract_cookies_to_jar(self.cookies, resp.request, resp.raw)
+
+        extract_cookies_to_jar(self.cookies, request, r.raw)
+
+        # Resolve redirects if allowed.
+        if allow_redirects:
+            # Redirect resolving generator.
+            gen = self.resolve_redirects(r, request, **kwargs)
+            history = [resp for resp in gen]
+        else:
+            history = []
+
+        # Shuffle things around if there's history.
+        if history:
+            # Insert the first (original) request at the start
+            history.insert(0, r)
+            # Get the last request made
+            r = history.pop()
+            r.history = history
+
+        # If redirects aren't being followed, store the response on the Request for Response.next().
+        if not allow_redirects:
+            try:
+                r._next = next(
+                    self.resolve_redirects(r, request, yield_requests=True, **kwargs)
+                )
+            except StopIteration:
+                pass
+
+        if not stream:
+            r.content
+
+        return r
+
+    def merge_environment_settings(self, url, proxies, stream, verify, cert):
+        """
+        Check the environment and merge it with some settings.
+
+        :rtype: dict
+        """
+        # Gather clues from the surrounding environment.
+        if self.trust_env:
+            # Set environment's proxies.
+            no_proxy = proxies.get("no_proxy") if proxies is not None else None
+            env_proxies = get_environ_proxies(url, no_proxy=no_proxy)
+            for (k, v) in env_proxies.items():
+                proxies.setdefault(k, v)
+
+            # Look for requests environment configuration
+            # and be compatible with cURL.
+            if verify is True or verify is None:
+                verify = (
+                    os.environ.get("REQUESTS_CA_BUNDLE")
+                    or os.environ.get("CURL_CA_BUNDLE")
+                    or verify
+                )
+
+        # Merge all the kwargs.
+        proxies = merge_setting(proxies, self.proxies)
+        stream = merge_setting(stream, self.stream)
+        verify = merge_setting(verify, self.verify)
+        cert = merge_setting(cert, self.cert)
+
+        return {"proxies": proxies, "stream": stream, "verify": verify, "cert": cert}
+
+    def get_adapter(self, url):
+        """
+        Returns the appropriate connection adapter for the given URL.
+
+        :rtype: requests.adapters.BaseAdapter
+        """
+        for (prefix, adapter) in self.adapters.items():
+
+            if url.lower().startswith(prefix.lower()):
+                return adapter
+
+        # Nothing matches :-/
+        raise InvalidSchema(f"No connection adapters were found for {url!r}")
+
+    def close(self):
+        """Closes all adapters and as such the session"""
+        for v in self.adapters.values():
+            v.close()
+
+    def mount(self, prefix, adapter):
+        """Registers a connection adapter to a prefix.
+
+        Adapters are sorted in descending order by prefix length.
+        """
+        self.adapters[prefix] = adapter
+        keys_to_move = [k for k in self.adapters if len(k) < len(prefix)]
+
+        for key in keys_to_move:
+            self.adapters[key] = self.adapters.pop(key)
+
+    def __getstate__(self):
+        state = {attr: getattr(self, attr, None) for attr in self.__attrs__}
+        return state
+
+    def __setstate__(self, state):
+        for attr, value in state.items():
+            setattr(self, attr, value)
+
+
+def session():
+    """
+    Returns a :class:`Session` for context-management.
+
+    .. deprecated:: 1.0.0
+
+        This method has been deprecated since version 1.0.0 and is only kept for
+        backwards compatibility. New code should use :class:`~requests.sessions.Session`
+        to create a session. This may be removed at a future date.
+
+    :rtype: Session
+    """
+    return Session()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/status_codes.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/status_codes.py
new file mode 100644
index 0000000000000000000000000000000000000000..4bd072be9769748a852740d037d5c63021472c9d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/status_codes.py
@@ -0,0 +1,128 @@
+r"""
+The ``codes`` object defines a mapping from common names for HTTP statuses
+to their numerical codes, accessible either as attributes or as dictionary
+items.
+
+Example::
+
+    >>> import requests
+    >>> requests.codes['temporary_redirect']
+    307
+    >>> requests.codes.teapot
+    418
+    >>> requests.codes['\o/']
+    200
+
+Some codes have multiple names, and both upper- and lower-case versions of
+the names are allowed. For example, ``codes.ok``, ``codes.OK``, and
+``codes.okay`` all correspond to the HTTP status code 200.
+"""
+
+from .structures import LookupDict
+
+_codes = {
+    # Informational.
+    100: ("continue",),
+    101: ("switching_protocols",),
+    102: ("processing",),
+    103: ("checkpoint",),
+    122: ("uri_too_long", "request_uri_too_long"),
+    200: ("ok", "okay", "all_ok", "all_okay", "all_good", "\\o/", "✓"),
+    201: ("created",),
+    202: ("accepted",),
+    203: ("non_authoritative_info", "non_authoritative_information"),
+    204: ("no_content",),
+    205: ("reset_content", "reset"),
+    206: ("partial_content", "partial"),
+    207: ("multi_status", "multiple_status", "multi_stati", "multiple_stati"),
+    208: ("already_reported",),
+    226: ("im_used",),
+    # Redirection.
+    300: ("multiple_choices",),
+    301: ("moved_permanently", "moved", "\\o-"),
+    302: ("found",),
+    303: ("see_other", "other"),
+    304: ("not_modified",),
+    305: ("use_proxy",),
+    306: ("switch_proxy",),
+    307: ("temporary_redirect", "temporary_moved", "temporary"),
+    308: (
+        "permanent_redirect",
+        "resume_incomplete",
+        "resume",
+    ),  # "resume" and "resume_incomplete" to be removed in 3.0
+    # Client Error.
+    400: ("bad_request", "bad"),
+    401: ("unauthorized",),
+    402: ("payment_required", "payment"),
+    403: ("forbidden",),
+    404: ("not_found", "-o-"),
+    405: ("method_not_allowed", "not_allowed"),
+    406: ("not_acceptable",),
+    407: ("proxy_authentication_required", "proxy_auth", "proxy_authentication"),
+    408: ("request_timeout", "timeout"),
+    409: ("conflict",),
+    410: ("gone",),
+    411: ("length_required",),
+    412: ("precondition_failed", "precondition"),
+    413: ("request_entity_too_large",),
+    414: ("request_uri_too_large",),
+    415: ("unsupported_media_type", "unsupported_media", "media_type"),
+    416: (
+        "requested_range_not_satisfiable",
+        "requested_range",
+        "range_not_satisfiable",
+    ),
+    417: ("expectation_failed",),
+    418: ("im_a_teapot", "teapot", "i_am_a_teapot"),
+    421: ("misdirected_request",),
+    422: ("unprocessable_entity", "unprocessable"),
+    423: ("locked",),
+    424: ("failed_dependency", "dependency"),
+    425: ("unordered_collection", "unordered"),
+    426: ("upgrade_required", "upgrade"),
+    428: ("precondition_required", "precondition"),
+    429: ("too_many_requests", "too_many"),
+    431: ("header_fields_too_large", "fields_too_large"),
+    444: ("no_response", "none"),
+    449: ("retry_with", "retry"),
+    450: ("blocked_by_windows_parental_controls", "parental_controls"),
+    451: ("unavailable_for_legal_reasons", "legal_reasons"),
+    499: ("client_closed_request",),
+    # Server Error.
+    500: ("internal_server_error", "server_error", "/o\\", "✗"),
+    501: ("not_implemented",),
+    502: ("bad_gateway",),
+    503: ("service_unavailable", "unavailable"),
+    504: ("gateway_timeout",),
+    505: ("http_version_not_supported", "http_version"),
+    506: ("variant_also_negotiates",),
+    507: ("insufficient_storage",),
+    509: ("bandwidth_limit_exceeded", "bandwidth"),
+    510: ("not_extended",),
+    511: ("network_authentication_required", "network_auth", "network_authentication"),
+}
+
+codes = LookupDict(name="status_codes")
+
+
+def _init():
+    for code, titles in _codes.items():
+        for title in titles:
+            setattr(codes, title, code)
+            if not title.startswith(("\\", "/")):
+                setattr(codes, title.upper(), code)
+
+    def doc(code):
+        names = ", ".join(f"``{n}``" for n in _codes[code])
+        return "* %d: %s" % (code, names)
+
+    global __doc__
+    __doc__ = (
+        __doc__ + "\n" + "\n".join(doc(code) for code in sorted(_codes))
+        if __doc__ is not None
+        else None
+    )
+
+
+_init()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/structures.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/structures.py
new file mode 100644
index 0000000000000000000000000000000000000000..188e13e4829591facb23ae0e2eda84b9807cb818
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/structures.py
@@ -0,0 +1,99 @@
+"""
+requests.structures
+~~~~~~~~~~~~~~~~~~~
+
+Data structures that power Requests.
+"""
+
+from collections import OrderedDict
+
+from .compat import Mapping, MutableMapping
+
+
+class CaseInsensitiveDict(MutableMapping):
+    """A case-insensitive ``dict``-like object.
+
+    Implements all methods and operations of
+    ``MutableMapping`` as well as dict's ``copy``. Also
+    provides ``lower_items``.
+
+    All keys are expected to be strings. The structure remembers the
+    case of the last key to be set, and ``iter(instance)``,
+    ``keys()``, ``items()``, ``iterkeys()``, and ``iteritems()``
+    will contain case-sensitive keys. However, querying and contains
+    testing is case insensitive::
+
+        cid = CaseInsensitiveDict()
+        cid['Accept'] = 'application/json'
+        cid['aCCEPT'] == 'application/json'  # True
+        list(cid) == ['Accept']  # True
+
+    For example, ``headers['content-encoding']`` will return the
+    value of a ``'Content-Encoding'`` response header, regardless
+    of how the header name was originally stored.
+
+    If the constructor, ``.update``, or equality comparison
+    operations are given keys that have equal ``.lower()``s, the
+    behavior is undefined.
+    """
+
+    def __init__(self, data=None, **kwargs):
+        self._store = OrderedDict()
+        if data is None:
+            data = {}
+        self.update(data, **kwargs)
+
+    def __setitem__(self, key, value):
+        # Use the lowercased key for lookups, but store the actual
+        # key alongside the value.
+        self._store[key.lower()] = (key, value)
+
+    def __getitem__(self, key):
+        return self._store[key.lower()][1]
+
+    def __delitem__(self, key):
+        del self._store[key.lower()]
+
+    def __iter__(self):
+        return (casedkey for casedkey, mappedvalue in self._store.values())
+
+    def __len__(self):
+        return len(self._store)
+
+    def lower_items(self):
+        """Like iteritems(), but with all lowercase keys."""
+        return ((lowerkey, keyval[1]) for (lowerkey, keyval) in self._store.items())
+
+    def __eq__(self, other):
+        if isinstance(other, Mapping):
+            other = CaseInsensitiveDict(other)
+        else:
+            return NotImplemented
+        # Compare insensitively
+        return dict(self.lower_items()) == dict(other.lower_items())
+
+    # Copy is required
+    def copy(self):
+        return CaseInsensitiveDict(self._store.values())
+
+    def __repr__(self):
+        return str(dict(self.items()))
+
+
+class LookupDict(dict):
+    """Dictionary lookup object."""
+
+    def __init__(self, name=None):
+        self.name = name
+        super().__init__()
+
+    def __repr__(self):
+        return f""
+
+    def __getitem__(self, key):
+        # We allow fall-through here, so values default to None
+
+        return self.__dict__.get(key, None)
+
+    def get(self, key, default=None):
+        return self.__dict__.get(key, default)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/utils.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..33f394d265d5da17dd5b3c2467e2e4e71af1395d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/requests/utils.py
@@ -0,0 +1,1086 @@
+"""
+requests.utils
+~~~~~~~~~~~~~~
+
+This module provides utility functions that are used within Requests
+that are also useful for external consumption.
+"""
+
+import codecs
+import contextlib
+import io
+import os
+import re
+import socket
+import struct
+import sys
+import tempfile
+import warnings
+import zipfile
+from collections import OrderedDict
+
+from pip._vendor.urllib3.util import make_headers, parse_url
+
+from . import certs
+from .__version__ import __version__
+
+# to_native_string is unused here, but imported here for backwards compatibility
+from ._internal_utils import HEADER_VALIDATORS, to_native_string  # noqa: F401
+from .compat import (
+    Mapping,
+    basestring,
+    bytes,
+    getproxies,
+    getproxies_environment,
+    integer_types,
+)
+from .compat import parse_http_list as _parse_list_header
+from .compat import (
+    proxy_bypass,
+    proxy_bypass_environment,
+    quote,
+    str,
+    unquote,
+    urlparse,
+    urlunparse,
+)
+from .cookies import cookiejar_from_dict
+from .exceptions import (
+    FileModeWarning,
+    InvalidHeader,
+    InvalidURL,
+    UnrewindableBodyError,
+)
+from .structures import CaseInsensitiveDict
+
+NETRC_FILES = (".netrc", "_netrc")
+
+DEFAULT_CA_BUNDLE_PATH = certs.where()
+
+DEFAULT_PORTS = {"http": 80, "https": 443}
+
+# Ensure that ', ' is used to preserve previous delimiter behavior.
+DEFAULT_ACCEPT_ENCODING = ", ".join(
+    re.split(r",\s*", make_headers(accept_encoding=True)["accept-encoding"])
+)
+
+
+if sys.platform == "win32":
+    # provide a proxy_bypass version on Windows without DNS lookups
+
+    def proxy_bypass_registry(host):
+        try:
+            import winreg
+        except ImportError:
+            return False
+
+        try:
+            internetSettings = winreg.OpenKey(
+                winreg.HKEY_CURRENT_USER,
+                r"Software\Microsoft\Windows\CurrentVersion\Internet Settings",
+            )
+            # ProxyEnable could be REG_SZ or REG_DWORD, normalizing it
+            proxyEnable = int(winreg.QueryValueEx(internetSettings, "ProxyEnable")[0])
+            # ProxyOverride is almost always a string
+            proxyOverride = winreg.QueryValueEx(internetSettings, "ProxyOverride")[0]
+        except (OSError, ValueError):
+            return False
+        if not proxyEnable or not proxyOverride:
+            return False
+
+        # make a check value list from the registry entry: replace the
+        # '' string by the localhost entry and the corresponding
+        # canonical entry.
+        proxyOverride = proxyOverride.split(";")
+        # now check if we match one of the registry values.
+        for test in proxyOverride:
+            if test == "":
+                if "." not in host:
+                    return True
+            test = test.replace(".", r"\.")  # mask dots
+            test = test.replace("*", r".*")  # change glob sequence
+            test = test.replace("?", r".")  # change glob char
+            if re.match(test, host, re.I):
+                return True
+        return False
+
+    def proxy_bypass(host):  # noqa
+        """Return True, if the host should be bypassed.
+
+        Checks proxy settings gathered from the environment, if specified,
+        or the registry.
+        """
+        if getproxies_environment():
+            return proxy_bypass_environment(host)
+        else:
+            return proxy_bypass_registry(host)
+
+
+def dict_to_sequence(d):
+    """Returns an internal sequence dictionary update."""
+
+    if hasattr(d, "items"):
+        d = d.items()
+
+    return d
+
+
+def super_len(o):
+    total_length = None
+    current_position = 0
+
+    if hasattr(o, "__len__"):
+        total_length = len(o)
+
+    elif hasattr(o, "len"):
+        total_length = o.len
+
+    elif hasattr(o, "fileno"):
+        try:
+            fileno = o.fileno()
+        except (io.UnsupportedOperation, AttributeError):
+            # AttributeError is a surprising exception, seeing as how we've just checked
+            # that `hasattr(o, 'fileno')`.  It happens for objects obtained via
+            # `Tarfile.extractfile()`, per issue 5229.
+            pass
+        else:
+            total_length = os.fstat(fileno).st_size
+
+            # Having used fstat to determine the file length, we need to
+            # confirm that this file was opened up in binary mode.
+            if "b" not in o.mode:
+                warnings.warn(
+                    (
+                        "Requests has determined the content-length for this "
+                        "request using the binary size of the file: however, the "
+                        "file has been opened in text mode (i.e. without the 'b' "
+                        "flag in the mode). This may lead to an incorrect "
+                        "content-length. In Requests 3.0, support will be removed "
+                        "for files in text mode."
+                    ),
+                    FileModeWarning,
+                )
+
+    if hasattr(o, "tell"):
+        try:
+            current_position = o.tell()
+        except OSError:
+            # This can happen in some weird situations, such as when the file
+            # is actually a special file descriptor like stdin. In this
+            # instance, we don't know what the length is, so set it to zero and
+            # let requests chunk it instead.
+            if total_length is not None:
+                current_position = total_length
+        else:
+            if hasattr(o, "seek") and total_length is None:
+                # StringIO and BytesIO have seek but no usable fileno
+                try:
+                    # seek to end of file
+                    o.seek(0, 2)
+                    total_length = o.tell()
+
+                    # seek back to current position to support
+                    # partially read file-like objects
+                    o.seek(current_position or 0)
+                except OSError:
+                    total_length = 0
+
+    if total_length is None:
+        total_length = 0
+
+    return max(0, total_length - current_position)
+
+
+def get_netrc_auth(url, raise_errors=False):
+    """Returns the Requests tuple auth for a given url from netrc."""
+
+    netrc_file = os.environ.get("NETRC")
+    if netrc_file is not None:
+        netrc_locations = (netrc_file,)
+    else:
+        netrc_locations = (f"~/{f}" for f in NETRC_FILES)
+
+    try:
+        from netrc import NetrcParseError, netrc
+
+        netrc_path = None
+
+        for f in netrc_locations:
+            try:
+                loc = os.path.expanduser(f)
+            except KeyError:
+                # os.path.expanduser can fail when $HOME is undefined and
+                # getpwuid fails. See https://bugs.python.org/issue20164 &
+                # https://github.com/psf/requests/issues/1846
+                return
+
+            if os.path.exists(loc):
+                netrc_path = loc
+                break
+
+        # Abort early if there isn't one.
+        if netrc_path is None:
+            return
+
+        ri = urlparse(url)
+
+        # Strip port numbers from netloc. This weird `if...encode`` dance is
+        # used for Python 3.2, which doesn't support unicode literals.
+        splitstr = b":"
+        if isinstance(url, str):
+            splitstr = splitstr.decode("ascii")
+        host = ri.netloc.split(splitstr)[0]
+
+        try:
+            _netrc = netrc(netrc_path).authenticators(host)
+            if _netrc:
+                # Return with login / password
+                login_i = 0 if _netrc[0] else 1
+                return (_netrc[login_i], _netrc[2])
+        except (NetrcParseError, OSError):
+            # If there was a parsing error or a permissions issue reading the file,
+            # we'll just skip netrc auth unless explicitly asked to raise errors.
+            if raise_errors:
+                raise
+
+    # App Engine hackiness.
+    except (ImportError, AttributeError):
+        pass
+
+
+def guess_filename(obj):
+    """Tries to guess the filename of the given object."""
+    name = getattr(obj, "name", None)
+    if name and isinstance(name, basestring) and name[0] != "<" and name[-1] != ">":
+        return os.path.basename(name)
+
+
+def extract_zipped_paths(path):
+    """Replace nonexistent paths that look like they refer to a member of a zip
+    archive with the location of an extracted copy of the target, or else
+    just return the provided path unchanged.
+    """
+    if os.path.exists(path):
+        # this is already a valid path, no need to do anything further
+        return path
+
+    # find the first valid part of the provided path and treat that as a zip archive
+    # assume the rest of the path is the name of a member in the archive
+    archive, member = os.path.split(path)
+    while archive and not os.path.exists(archive):
+        archive, prefix = os.path.split(archive)
+        if not prefix:
+            # If we don't check for an empty prefix after the split (in other words, archive remains unchanged after the split),
+            # we _can_ end up in an infinite loop on a rare corner case affecting a small number of users
+            break
+        member = "/".join([prefix, member])
+
+    if not zipfile.is_zipfile(archive):
+        return path
+
+    zip_file = zipfile.ZipFile(archive)
+    if member not in zip_file.namelist():
+        return path
+
+    # we have a valid zip archive and a valid member of that archive
+    tmp = tempfile.gettempdir()
+    extracted_path = os.path.join(tmp, member.split("/")[-1])
+    if not os.path.exists(extracted_path):
+        # use read + write to avoid the creating nested folders, we only want the file, avoids mkdir racing condition
+        with atomic_open(extracted_path) as file_handler:
+            file_handler.write(zip_file.read(member))
+    return extracted_path
+
+
+@contextlib.contextmanager
+def atomic_open(filename):
+    """Write a file to the disk in an atomic fashion"""
+    tmp_descriptor, tmp_name = tempfile.mkstemp(dir=os.path.dirname(filename))
+    try:
+        with os.fdopen(tmp_descriptor, "wb") as tmp_handler:
+            yield tmp_handler
+        os.replace(tmp_name, filename)
+    except BaseException:
+        os.remove(tmp_name)
+        raise
+
+
+def from_key_val_list(value):
+    """Take an object and test to see if it can be represented as a
+    dictionary. Unless it can not be represented as such, return an
+    OrderedDict, e.g.,
+
+    ::
+
+        >>> from_key_val_list([('key', 'val')])
+        OrderedDict([('key', 'val')])
+        >>> from_key_val_list('string')
+        Traceback (most recent call last):
+        ...
+        ValueError: cannot encode objects that are not 2-tuples
+        >>> from_key_val_list({'key': 'val'})
+        OrderedDict([('key', 'val')])
+
+    :rtype: OrderedDict
+    """
+    if value is None:
+        return None
+
+    if isinstance(value, (str, bytes, bool, int)):
+        raise ValueError("cannot encode objects that are not 2-tuples")
+
+    return OrderedDict(value)
+
+
+def to_key_val_list(value):
+    """Take an object and test to see if it can be represented as a
+    dictionary. If it can be, return a list of tuples, e.g.,
+
+    ::
+
+        >>> to_key_val_list([('key', 'val')])
+        [('key', 'val')]
+        >>> to_key_val_list({'key': 'val'})
+        [('key', 'val')]
+        >>> to_key_val_list('string')
+        Traceback (most recent call last):
+        ...
+        ValueError: cannot encode objects that are not 2-tuples
+
+    :rtype: list
+    """
+    if value is None:
+        return None
+
+    if isinstance(value, (str, bytes, bool, int)):
+        raise ValueError("cannot encode objects that are not 2-tuples")
+
+    if isinstance(value, Mapping):
+        value = value.items()
+
+    return list(value)
+
+
+# From mitsuhiko/werkzeug (used with permission).
+def parse_list_header(value):
+    """Parse lists as described by RFC 2068 Section 2.
+
+    In particular, parse comma-separated lists where the elements of
+    the list may include quoted-strings.  A quoted-string could
+    contain a comma.  A non-quoted string could have quotes in the
+    middle.  Quotes are removed automatically after parsing.
+
+    It basically works like :func:`parse_set_header` just that items
+    may appear multiple times and case sensitivity is preserved.
+
+    The return value is a standard :class:`list`:
+
+    >>> parse_list_header('token, "quoted value"')
+    ['token', 'quoted value']
+
+    To create a header from the :class:`list` again, use the
+    :func:`dump_header` function.
+
+    :param value: a string with a list header.
+    :return: :class:`list`
+    :rtype: list
+    """
+    result = []
+    for item in _parse_list_header(value):
+        if item[:1] == item[-1:] == '"':
+            item = unquote_header_value(item[1:-1])
+        result.append(item)
+    return result
+
+
+# From mitsuhiko/werkzeug (used with permission).
+def parse_dict_header(value):
+    """Parse lists of key, value pairs as described by RFC 2068 Section 2 and
+    convert them into a python dict:
+
+    >>> d = parse_dict_header('foo="is a fish", bar="as well"')
+    >>> type(d) is dict
+    True
+    >>> sorted(d.items())
+    [('bar', 'as well'), ('foo', 'is a fish')]
+
+    If there is no value for a key it will be `None`:
+
+    >>> parse_dict_header('key_without_value')
+    {'key_without_value': None}
+
+    To create a header from the :class:`dict` again, use the
+    :func:`dump_header` function.
+
+    :param value: a string with a dict header.
+    :return: :class:`dict`
+    :rtype: dict
+    """
+    result = {}
+    for item in _parse_list_header(value):
+        if "=" not in item:
+            result[item] = None
+            continue
+        name, value = item.split("=", 1)
+        if value[:1] == value[-1:] == '"':
+            value = unquote_header_value(value[1:-1])
+        result[name] = value
+    return result
+
+
+# From mitsuhiko/werkzeug (used with permission).
+def unquote_header_value(value, is_filename=False):
+    r"""Unquotes a header value.  (Reversal of :func:`quote_header_value`).
+    This does not use the real unquoting but what browsers are actually
+    using for quoting.
+
+    :param value: the header value to unquote.
+    :rtype: str
+    """
+    if value and value[0] == value[-1] == '"':
+        # this is not the real unquoting, but fixing this so that the
+        # RFC is met will result in bugs with internet explorer and
+        # probably some other browsers as well.  IE for example is
+        # uploading files with "C:\foo\bar.txt" as filename
+        value = value[1:-1]
+
+        # if this is a filename and the starting characters look like
+        # a UNC path, then just return the value without quotes.  Using the
+        # replace sequence below on a UNC path has the effect of turning
+        # the leading double slash into a single slash and then
+        # _fix_ie_filename() doesn't work correctly.  See #458.
+        if not is_filename or value[:2] != "\\\\":
+            return value.replace("\\\\", "\\").replace('\\"', '"')
+    return value
+
+
+def dict_from_cookiejar(cj):
+    """Returns a key/value dictionary from a CookieJar.
+
+    :param cj: CookieJar object to extract cookies from.
+    :rtype: dict
+    """
+
+    cookie_dict = {}
+
+    for cookie in cj:
+        cookie_dict[cookie.name] = cookie.value
+
+    return cookie_dict
+
+
+def add_dict_to_cookiejar(cj, cookie_dict):
+    """Returns a CookieJar from a key/value dictionary.
+
+    :param cj: CookieJar to insert cookies into.
+    :param cookie_dict: Dict of key/values to insert into CookieJar.
+    :rtype: CookieJar
+    """
+
+    return cookiejar_from_dict(cookie_dict, cj)
+
+
+def get_encodings_from_content(content):
+    """Returns encodings from given content string.
+
+    :param content: bytestring to extract encodings from.
+    """
+    warnings.warn(
+        (
+            "In requests 3.0, get_encodings_from_content will be removed. For "
+            "more information, please see the discussion on issue #2266. (This"
+            " warning should only appear once.)"
+        ),
+        DeprecationWarning,
+    )
+
+    charset_re = re.compile(r']', flags=re.I)
+    pragma_re = re.compile(r']', flags=re.I)
+    xml_re = re.compile(r'^<\?xml.*?encoding=["\']*(.+?)["\'>]')
+
+    return (
+        charset_re.findall(content)
+        + pragma_re.findall(content)
+        + xml_re.findall(content)
+    )
+
+
+def _parse_content_type_header(header):
+    """Returns content type and parameters from given header
+
+    :param header: string
+    :return: tuple containing content type and dictionary of
+         parameters
+    """
+
+    tokens = header.split(";")
+    content_type, params = tokens[0].strip(), tokens[1:]
+    params_dict = {}
+    items_to_strip = "\"' "
+
+    for param in params:
+        param = param.strip()
+        if param:
+            key, value = param, True
+            index_of_equals = param.find("=")
+            if index_of_equals != -1:
+                key = param[:index_of_equals].strip(items_to_strip)
+                value = param[index_of_equals + 1 :].strip(items_to_strip)
+            params_dict[key.lower()] = value
+    return content_type, params_dict
+
+
+def get_encoding_from_headers(headers):
+    """Returns encodings from given HTTP Header Dict.
+
+    :param headers: dictionary to extract encoding from.
+    :rtype: str
+    """
+
+    content_type = headers.get("content-type")
+
+    if not content_type:
+        return None
+
+    content_type, params = _parse_content_type_header(content_type)
+
+    if "charset" in params:
+        return params["charset"].strip("'\"")
+
+    if "text" in content_type:
+        return "ISO-8859-1"
+
+    if "application/json" in content_type:
+        # Assume UTF-8 based on RFC 4627: https://www.ietf.org/rfc/rfc4627.txt since the charset was unset
+        return "utf-8"
+
+
+def stream_decode_response_unicode(iterator, r):
+    """Stream decodes an iterator."""
+
+    if r.encoding is None:
+        yield from iterator
+        return
+
+    decoder = codecs.getincrementaldecoder(r.encoding)(errors="replace")
+    for chunk in iterator:
+        rv = decoder.decode(chunk)
+        if rv:
+            yield rv
+    rv = decoder.decode(b"", final=True)
+    if rv:
+        yield rv
+
+
+def iter_slices(string, slice_length):
+    """Iterate over slices of a string."""
+    pos = 0
+    if slice_length is None or slice_length <= 0:
+        slice_length = len(string)
+    while pos < len(string):
+        yield string[pos : pos + slice_length]
+        pos += slice_length
+
+
+def get_unicode_from_response(r):
+    """Returns the requested content back in unicode.
+
+    :param r: Response object to get unicode content from.
+
+    Tried:
+
+    1. charset from content-type
+    2. fall back and replace all unicode characters
+
+    :rtype: str
+    """
+    warnings.warn(
+        (
+            "In requests 3.0, get_unicode_from_response will be removed. For "
+            "more information, please see the discussion on issue #2266. (This"
+            " warning should only appear once.)"
+        ),
+        DeprecationWarning,
+    )
+
+    tried_encodings = []
+
+    # Try charset from content-type
+    encoding = get_encoding_from_headers(r.headers)
+
+    if encoding:
+        try:
+            return str(r.content, encoding)
+        except UnicodeError:
+            tried_encodings.append(encoding)
+
+    # Fall back:
+    try:
+        return str(r.content, encoding, errors="replace")
+    except TypeError:
+        return r.content
+
+
+# The unreserved URI characters (RFC 3986)
+UNRESERVED_SET = frozenset(
+    "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz" + "0123456789-._~"
+)
+
+
+def unquote_unreserved(uri):
+    """Un-escape any percent-escape sequences in a URI that are unreserved
+    characters. This leaves all reserved, illegal and non-ASCII bytes encoded.
+
+    :rtype: str
+    """
+    parts = uri.split("%")
+    for i in range(1, len(parts)):
+        h = parts[i][0:2]
+        if len(h) == 2 and h.isalnum():
+            try:
+                c = chr(int(h, 16))
+            except ValueError:
+                raise InvalidURL(f"Invalid percent-escape sequence: '{h}'")
+
+            if c in UNRESERVED_SET:
+                parts[i] = c + parts[i][2:]
+            else:
+                parts[i] = f"%{parts[i]}"
+        else:
+            parts[i] = f"%{parts[i]}"
+    return "".join(parts)
+
+
+def requote_uri(uri):
+    """Re-quote the given URI.
+
+    This function passes the given URI through an unquote/quote cycle to
+    ensure that it is fully and consistently quoted.
+
+    :rtype: str
+    """
+    safe_with_percent = "!#$%&'()*+,/:;=?@[]~"
+    safe_without_percent = "!#$&'()*+,/:;=?@[]~"
+    try:
+        # Unquote only the unreserved characters
+        # Then quote only illegal characters (do not quote reserved,
+        # unreserved, or '%')
+        return quote(unquote_unreserved(uri), safe=safe_with_percent)
+    except InvalidURL:
+        # We couldn't unquote the given URI, so let's try quoting it, but
+        # there may be unquoted '%'s in the URI. We need to make sure they're
+        # properly quoted so they do not cause issues elsewhere.
+        return quote(uri, safe=safe_without_percent)
+
+
+def address_in_network(ip, net):
+    """This function allows you to check if an IP belongs to a network subnet
+
+    Example: returns True if ip = 192.168.1.1 and net = 192.168.1.0/24
+             returns False if ip = 192.168.1.1 and net = 192.168.100.0/24
+
+    :rtype: bool
+    """
+    ipaddr = struct.unpack("=L", socket.inet_aton(ip))[0]
+    netaddr, bits = net.split("/")
+    netmask = struct.unpack("=L", socket.inet_aton(dotted_netmask(int(bits))))[0]
+    network = struct.unpack("=L", socket.inet_aton(netaddr))[0] & netmask
+    return (ipaddr & netmask) == (network & netmask)
+
+
+def dotted_netmask(mask):
+    """Converts mask from /xx format to xxx.xxx.xxx.xxx
+
+    Example: if mask is 24 function returns 255.255.255.0
+
+    :rtype: str
+    """
+    bits = 0xFFFFFFFF ^ (1 << 32 - mask) - 1
+    return socket.inet_ntoa(struct.pack(">I", bits))
+
+
+def is_ipv4_address(string_ip):
+    """
+    :rtype: bool
+    """
+    try:
+        socket.inet_aton(string_ip)
+    except OSError:
+        return False
+    return True
+
+
+def is_valid_cidr(string_network):
+    """
+    Very simple check of the cidr format in no_proxy variable.
+
+    :rtype: bool
+    """
+    if string_network.count("/") == 1:
+        try:
+            mask = int(string_network.split("/")[1])
+        except ValueError:
+            return False
+
+        if mask < 1 or mask > 32:
+            return False
+
+        try:
+            socket.inet_aton(string_network.split("/")[0])
+        except OSError:
+            return False
+    else:
+        return False
+    return True
+
+
+@contextlib.contextmanager
+def set_environ(env_name, value):
+    """Set the environment variable 'env_name' to 'value'
+
+    Save previous value, yield, and then restore the previous value stored in
+    the environment variable 'env_name'.
+
+    If 'value' is None, do nothing"""
+    value_changed = value is not None
+    if value_changed:
+        old_value = os.environ.get(env_name)
+        os.environ[env_name] = value
+    try:
+        yield
+    finally:
+        if value_changed:
+            if old_value is None:
+                del os.environ[env_name]
+            else:
+                os.environ[env_name] = old_value
+
+
+def should_bypass_proxies(url, no_proxy):
+    """
+    Returns whether we should bypass proxies or not.
+
+    :rtype: bool
+    """
+    # Prioritize lowercase environment variables over uppercase
+    # to keep a consistent behaviour with other http projects (curl, wget).
+    def get_proxy(key):
+        return os.environ.get(key) or os.environ.get(key.upper())
+
+    # First check whether no_proxy is defined. If it is, check that the URL
+    # we're getting isn't in the no_proxy list.
+    no_proxy_arg = no_proxy
+    if no_proxy is None:
+        no_proxy = get_proxy("no_proxy")
+    parsed = urlparse(url)
+
+    if parsed.hostname is None:
+        # URLs don't always have hostnames, e.g. file:/// urls.
+        return True
+
+    if no_proxy:
+        # We need to check whether we match here. We need to see if we match
+        # the end of the hostname, both with and without the port.
+        no_proxy = (host for host in no_proxy.replace(" ", "").split(",") if host)
+
+        if is_ipv4_address(parsed.hostname):
+            for proxy_ip in no_proxy:
+                if is_valid_cidr(proxy_ip):
+                    if address_in_network(parsed.hostname, proxy_ip):
+                        return True
+                elif parsed.hostname == proxy_ip:
+                    # If no_proxy ip was defined in plain IP notation instead of cidr notation &
+                    # matches the IP of the index
+                    return True
+        else:
+            host_with_port = parsed.hostname
+            if parsed.port:
+                host_with_port += f":{parsed.port}"
+
+            for host in no_proxy:
+                if parsed.hostname.endswith(host) or host_with_port.endswith(host):
+                    # The URL does match something in no_proxy, so we don't want
+                    # to apply the proxies on this URL.
+                    return True
+
+    with set_environ("no_proxy", no_proxy_arg):
+        # parsed.hostname can be `None` in cases such as a file URI.
+        try:
+            bypass = proxy_bypass(parsed.hostname)
+        except (TypeError, socket.gaierror):
+            bypass = False
+
+    if bypass:
+        return True
+
+    return False
+
+
+def get_environ_proxies(url, no_proxy=None):
+    """
+    Return a dict of environment proxies.
+
+    :rtype: dict
+    """
+    if should_bypass_proxies(url, no_proxy=no_proxy):
+        return {}
+    else:
+        return getproxies()
+
+
+def select_proxy(url, proxies):
+    """Select a proxy for the url, if applicable.
+
+    :param url: The url being for the request
+    :param proxies: A dictionary of schemes or schemes and hosts to proxy URLs
+    """
+    proxies = proxies or {}
+    urlparts = urlparse(url)
+    if urlparts.hostname is None:
+        return proxies.get(urlparts.scheme, proxies.get("all"))
+
+    proxy_keys = [
+        urlparts.scheme + "://" + urlparts.hostname,
+        urlparts.scheme,
+        "all://" + urlparts.hostname,
+        "all",
+    ]
+    proxy = None
+    for proxy_key in proxy_keys:
+        if proxy_key in proxies:
+            proxy = proxies[proxy_key]
+            break
+
+    return proxy
+
+
+def resolve_proxies(request, proxies, trust_env=True):
+    """This method takes proxy information from a request and configuration
+    input to resolve a mapping of target proxies. This will consider settings
+    such a NO_PROXY to strip proxy configurations.
+
+    :param request: Request or PreparedRequest
+    :param proxies: A dictionary of schemes or schemes and hosts to proxy URLs
+    :param trust_env: Boolean declaring whether to trust environment configs
+
+    :rtype: dict
+    """
+    proxies = proxies if proxies is not None else {}
+    url = request.url
+    scheme = urlparse(url).scheme
+    no_proxy = proxies.get("no_proxy")
+    new_proxies = proxies.copy()
+
+    if trust_env and not should_bypass_proxies(url, no_proxy=no_proxy):
+        environ_proxies = get_environ_proxies(url, no_proxy=no_proxy)
+
+        proxy = environ_proxies.get(scheme, environ_proxies.get("all"))
+
+        if proxy:
+            new_proxies.setdefault(scheme, proxy)
+    return new_proxies
+
+
+def default_user_agent(name="python-requests"):
+    """
+    Return a string representing the default user agent.
+
+    :rtype: str
+    """
+    return f"{name}/{__version__}"
+
+
+def default_headers():
+    """
+    :rtype: requests.structures.CaseInsensitiveDict
+    """
+    return CaseInsensitiveDict(
+        {
+            "User-Agent": default_user_agent(),
+            "Accept-Encoding": DEFAULT_ACCEPT_ENCODING,
+            "Accept": "*/*",
+            "Connection": "keep-alive",
+        }
+    )
+
+
+def parse_header_links(value):
+    """Return a list of parsed link headers proxies.
+
+    i.e. Link: ; rel=front; type="image/jpeg",; rel=back;type="image/jpeg"
+
+    :rtype: list
+    """
+
+    links = []
+
+    replace_chars = " '\""
+
+    value = value.strip(replace_chars)
+    if not value:
+        return links
+
+    for val in re.split(", *<", value):
+        try:
+            url, params = val.split(";", 1)
+        except ValueError:
+            url, params = val, ""
+
+        link = {"url": url.strip("<> '\"")}
+
+        for param in params.split(";"):
+            try:
+                key, value = param.split("=")
+            except ValueError:
+                break
+
+            link[key.strip(replace_chars)] = value.strip(replace_chars)
+
+        links.append(link)
+
+    return links
+
+
+# Null bytes; no need to recreate these on each call to guess_json_utf
+_null = "\x00".encode("ascii")  # encoding to ASCII for Python 3
+_null2 = _null * 2
+_null3 = _null * 3
+
+
+def guess_json_utf(data):
+    """
+    :rtype: str
+    """
+    # JSON always starts with two ASCII characters, so detection is as
+    # easy as counting the nulls and from their location and count
+    # determine the encoding. Also detect a BOM, if present.
+    sample = data[:4]
+    if sample in (codecs.BOM_UTF32_LE, codecs.BOM_UTF32_BE):
+        return "utf-32"  # BOM included
+    if sample[:3] == codecs.BOM_UTF8:
+        return "utf-8-sig"  # BOM included, MS style (discouraged)
+    if sample[:2] in (codecs.BOM_UTF16_LE, codecs.BOM_UTF16_BE):
+        return "utf-16"  # BOM included
+    nullcount = sample.count(_null)
+    if nullcount == 0:
+        return "utf-8"
+    if nullcount == 2:
+        if sample[::2] == _null2:  # 1st and 3rd are null
+            return "utf-16-be"
+        if sample[1::2] == _null2:  # 2nd and 4th are null
+            return "utf-16-le"
+        # Did not detect 2 valid UTF-16 ascii-range characters
+    if nullcount == 3:
+        if sample[:3] == _null3:
+            return "utf-32-be"
+        if sample[1:] == _null3:
+            return "utf-32-le"
+        # Did not detect a valid UTF-32 ascii-range character
+    return None
+
+
+def prepend_scheme_if_needed(url, new_scheme):
+    """Given a URL that may or may not have a scheme, prepend the given scheme.
+    Does not replace a present scheme with the one provided as an argument.
+
+    :rtype: str
+    """
+    parsed = parse_url(url)
+    scheme, auth, host, port, path, query, fragment = parsed
+
+    # A defect in urlparse determines that there isn't a netloc present in some
+    # urls. We previously assumed parsing was overly cautious, and swapped the
+    # netloc and path. Due to a lack of tests on the original defect, this is
+    # maintained with parse_url for backwards compatibility.
+    netloc = parsed.netloc
+    if not netloc:
+        netloc, path = path, netloc
+
+    if auth:
+        # parse_url doesn't provide the netloc with auth
+        # so we'll add it ourselves.
+        netloc = "@".join([auth, netloc])
+    if scheme is None:
+        scheme = new_scheme
+    if path is None:
+        path = ""
+
+    return urlunparse((scheme, netloc, path, "", query, fragment))
+
+
+def get_auth_from_url(url):
+    """Given a url with authentication components, extract them into a tuple of
+    username,password.
+
+    :rtype: (str,str)
+    """
+    parsed = urlparse(url)
+
+    try:
+        auth = (unquote(parsed.username), unquote(parsed.password))
+    except (AttributeError, TypeError):
+        auth = ("", "")
+
+    return auth
+
+
+def check_header_validity(header):
+    """Verifies that header parts don't contain leading whitespace
+    reserved characters, or return characters.
+
+    :param header: tuple, in the format (name, value).
+    """
+    name, value = header
+
+    for part in header:
+        if type(part) not in HEADER_VALIDATORS:
+            raise InvalidHeader(
+                f"Header part ({part!r}) from {{{name!r}: {value!r}}} must be "
+                f"of type str or bytes, not {type(part)}"
+            )
+
+    _validate_header_part(name, "name", HEADER_VALIDATORS[type(name)][0])
+    _validate_header_part(value, "value", HEADER_VALIDATORS[type(value)][1])
+
+
+def _validate_header_part(header_part, header_kind, validator):
+    if not validator.match(header_part):
+        raise InvalidHeader(
+            f"Invalid leading whitespace, reserved character(s), or return"
+            f"character(s) in header {header_kind}: {header_part!r}"
+        )
+
+
+def urldefragauth(url):
+    """
+    Given a url remove the fragment and the authentication part.
+
+    :rtype: str
+    """
+    scheme, netloc, path, params, query, fragment = urlparse(url)
+
+    # see func:`prepend_scheme_if_needed`
+    if not netloc:
+        netloc, path = path, netloc
+
+    netloc = netloc.rsplit("@", 1)[-1]
+
+    return urlunparse((scheme, netloc, path, params, query, ""))
+
+
+def rewind_body(prepared_request):
+    """Move file pointer back to its recorded starting position
+    so it can be read again on redirect.
+    """
+    body_seek = getattr(prepared_request.body, "seek", None)
+    if body_seek is not None and isinstance(
+        prepared_request._body_position, integer_types
+    ):
+        try:
+            body_seek(prepared_request._body_position)
+        except OSError:
+            raise UnrewindableBodyError(
+                "An error occurred when rewinding request body for redirect."
+            )
+    else:
+        raise UnrewindableBodyError("Unable to rewind request body for redirect.")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ce05fd3027447fdc64986ecdee950643822e45e6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/__init__.py
@@ -0,0 +1,26 @@
+__all__ = [
+    "__version__",
+    "AbstractProvider",
+    "AbstractResolver",
+    "BaseReporter",
+    "InconsistentCandidate",
+    "Resolver",
+    "RequirementsConflicted",
+    "ResolutionError",
+    "ResolutionImpossible",
+    "ResolutionTooDeep",
+]
+
+__version__ = "0.8.1"
+
+
+from .providers import AbstractProvider, AbstractResolver
+from .reporters import BaseReporter
+from .resolvers import (
+    InconsistentCandidate,
+    RequirementsConflicted,
+    ResolutionError,
+    ResolutionImpossible,
+    ResolutionTooDeep,
+    Resolver,
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/compat/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/compat/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/compat/collections_abc.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/compat/collections_abc.py
new file mode 100644
index 0000000000000000000000000000000000000000..1becc5093c5ab8e196bb9fee415e2381e7158fc3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/compat/collections_abc.py
@@ -0,0 +1,6 @@
+__all__ = ["Mapping", "Sequence"]
+
+try:
+    from collections.abc import Mapping, Sequence
+except ImportError:
+    from collections import Mapping, Sequence
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/providers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/providers.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d0a9c22a4656951910a9fbb70af59a0706cadde
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/providers.py
@@ -0,0 +1,133 @@
+class AbstractProvider(object):
+    """Delegate class to provide requirement interface for the resolver."""
+
+    def identify(self, requirement_or_candidate):
+        """Given a requirement, return an identifier for it.
+
+        This is used to identify a requirement, e.g. whether two requirements
+        should have their specifier parts merged.
+        """
+        raise NotImplementedError
+
+    def get_preference(
+        self,
+        identifier,
+        resolutions,
+        candidates,
+        information,
+        backtrack_causes,
+    ):
+        """Produce a sort key for given requirement based on preference.
+
+        The preference is defined as "I think this requirement should be
+        resolved first". The lower the return value is, the more preferred
+        this group of arguments is.
+
+        :param identifier: An identifier as returned by ``identify()``. This
+            identifies the dependency matches of which should be returned.
+        :param resolutions: Mapping of candidates currently pinned by the
+            resolver. Each key is an identifier, and the value a candidate.
+            The candidate may conflict with requirements from ``information``.
+        :param candidates: Mapping of each dependency's possible candidates.
+            Each value is an iterator of candidates.
+        :param information: Mapping of requirement information of each package.
+            Each value is an iterator of *requirement information*.
+        :param backtrack_causes: Sequence of requirement information that were
+            the requirements that caused the resolver to most recently backtrack.
+
+        A *requirement information* instance is a named tuple with two members:
+
+        * ``requirement`` specifies a requirement contributing to the current
+          list of candidates.
+        * ``parent`` specifies the candidate that provides (dependend on) the
+          requirement, or ``None`` to indicate a root requirement.
+
+        The preference could depend on a various of issues, including (not
+        necessarily in this order):
+
+        * Is this package pinned in the current resolution result?
+        * How relaxed is the requirement? Stricter ones should probably be
+          worked on first? (I don't know, actually.)
+        * How many possibilities are there to satisfy this requirement? Those
+          with few left should likely be worked on first, I guess?
+        * Are there any known conflicts for this requirement? We should
+          probably work on those with the most known conflicts.
+
+        A sortable value should be returned (this will be used as the ``key``
+        parameter of the built-in sorting function). The smaller the value is,
+        the more preferred this requirement is (i.e. the sorting function
+        is called with ``reverse=False``).
+        """
+        raise NotImplementedError
+
+    def find_matches(self, identifier, requirements, incompatibilities):
+        """Find all possible candidates that satisfy given constraints.
+
+        :param identifier: An identifier as returned by ``identify()``. This
+            identifies the dependency matches of which should be returned.
+        :param requirements: A mapping of requirements that all returned
+            candidates must satisfy. Each key is an identifier, and the value
+            an iterator of requirements for that dependency.
+        :param incompatibilities: A mapping of known incompatibilities of
+            each dependency. Each key is an identifier, and the value an
+            iterator of incompatibilities known to the resolver. All
+            incompatibilities *must* be excluded from the return value.
+
+        This should try to get candidates based on the requirements' types.
+        For VCS, local, and archive requirements, the one-and-only match is
+        returned, and for a "named" requirement, the index(es) should be
+        consulted to find concrete candidates for this requirement.
+
+        The return value should produce candidates ordered by preference; the
+        most preferred candidate should come first. The return type may be one
+        of the following:
+
+        * A callable that returns an iterator that yields candidates.
+        * An collection of candidates.
+        * An iterable of candidates. This will be consumed immediately into a
+          list of candidates.
+        """
+        raise NotImplementedError
+
+    def is_satisfied_by(self, requirement, candidate):
+        """Whether the given requirement can be satisfied by a candidate.
+
+        The candidate is guarenteed to have been generated from the
+        requirement.
+
+        A boolean should be returned to indicate whether ``candidate`` is a
+        viable solution to the requirement.
+        """
+        raise NotImplementedError
+
+    def get_dependencies(self, candidate):
+        """Get dependencies of a candidate.
+
+        This should return a collection of requirements that `candidate`
+        specifies as its dependencies.
+        """
+        raise NotImplementedError
+
+
+class AbstractResolver(object):
+    """The thing that performs the actual resolution work."""
+
+    base_exception = Exception
+
+    def __init__(self, provider, reporter):
+        self.provider = provider
+        self.reporter = reporter
+
+    def resolve(self, requirements, **kwargs):
+        """Take a collection of constraints, spit out the resolution result.
+
+        This returns a representation of the final resolution state, with one
+        guarenteed attribute ``mapping`` that contains resolved candidates as
+        values. The keys are their respective identifiers.
+
+        :param requirements: A collection of constraints.
+        :param kwargs: Additional keyword arguments that subclasses may accept.
+
+        :raises: ``self.base_exception`` or its subclass.
+        """
+        raise NotImplementedError
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/reporters.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/reporters.py
new file mode 100644
index 0000000000000000000000000000000000000000..6695480fff4c87608ac2002dfb341f90ed1a5ce4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/reporters.py
@@ -0,0 +1,43 @@
+class BaseReporter(object):
+    """Delegate class to provider progress reporting for the resolver."""
+
+    def starting(self):
+        """Called before the resolution actually starts."""
+
+    def starting_round(self, index):
+        """Called before each round of resolution starts.
+
+        The index is zero-based.
+        """
+
+    def ending_round(self, index, state):
+        """Called before each round of resolution ends.
+
+        This is NOT called if the resolution ends at this round. Use `ending`
+        if you want to report finalization. The index is zero-based.
+        """
+
+    def ending(self, state):
+        """Called before the resolution ends successfully."""
+
+    def adding_requirement(self, requirement, parent):
+        """Called when adding a new requirement into the resolve criteria.
+
+        :param requirement: The additional requirement to be applied to filter
+            the available candidaites.
+        :param parent: The candidate that requires ``requirement`` as a
+            dependency, or None if ``requirement`` is one of the root
+            requirements passed in from ``Resolver.resolve()``.
+        """
+
+    def resolving_conflicts(self, causes):
+        """Called when starting to attempt requirement conflict resolution.
+
+        :param causes: The information on the collision that caused the backtracking.
+        """
+
+    def backtracking(self, candidate):
+        """Called when rejecting a candidate during backtracking."""
+
+    def pinning(self, candidate):
+        """Called when adding a candidate to the potential solution."""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/resolvers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/resolvers.py
new file mode 100644
index 0000000000000000000000000000000000000000..787681b03e9ec2fd4490de10cdc95e58c893c8b5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/resolvers.py
@@ -0,0 +1,482 @@
+import collections
+import operator
+
+from .providers import AbstractResolver
+from .structs import DirectedGraph, IteratorMapping, build_iter_view
+
+RequirementInformation = collections.namedtuple(
+    "RequirementInformation", ["requirement", "parent"]
+)
+
+
+class ResolverException(Exception):
+    """A base class for all exceptions raised by this module.
+
+    Exceptions derived by this class should all be handled in this module. Any
+    bubbling pass the resolver should be treated as a bug.
+    """
+
+
+class RequirementsConflicted(ResolverException):
+    def __init__(self, criterion):
+        super(RequirementsConflicted, self).__init__(criterion)
+        self.criterion = criterion
+
+    def __str__(self):
+        return "Requirements conflict: {}".format(
+            ", ".join(repr(r) for r in self.criterion.iter_requirement()),
+        )
+
+
+class InconsistentCandidate(ResolverException):
+    def __init__(self, candidate, criterion):
+        super(InconsistentCandidate, self).__init__(candidate, criterion)
+        self.candidate = candidate
+        self.criterion = criterion
+
+    def __str__(self):
+        return "Provided candidate {!r} does not satisfy {}".format(
+            self.candidate,
+            ", ".join(repr(r) for r in self.criterion.iter_requirement()),
+        )
+
+
+class Criterion(object):
+    """Representation of possible resolution results of a package.
+
+    This holds three attributes:
+
+    * `information` is a collection of `RequirementInformation` pairs.
+      Each pair is a requirement contributing to this criterion, and the
+      candidate that provides the requirement.
+    * `incompatibilities` is a collection of all known not-to-work candidates
+      to exclude from consideration.
+    * `candidates` is a collection containing all possible candidates deducted
+      from the union of contributing requirements and known incompatibilities.
+      It should never be empty, except when the criterion is an attribute of a
+      raised `RequirementsConflicted` (in which case it is always empty).
+
+    .. note::
+        This class is intended to be externally immutable. **Do not** mutate
+        any of its attribute containers.
+    """
+
+    def __init__(self, candidates, information, incompatibilities):
+        self.candidates = candidates
+        self.information = information
+        self.incompatibilities = incompatibilities
+
+    def __repr__(self):
+        requirements = ", ".join(
+            "({!r}, via={!r})".format(req, parent)
+            for req, parent in self.information
+        )
+        return "Criterion({})".format(requirements)
+
+    def iter_requirement(self):
+        return (i.requirement for i in self.information)
+
+    def iter_parent(self):
+        return (i.parent for i in self.information)
+
+
+class ResolutionError(ResolverException):
+    pass
+
+
+class ResolutionImpossible(ResolutionError):
+    def __init__(self, causes):
+        super(ResolutionImpossible, self).__init__(causes)
+        # causes is a list of RequirementInformation objects
+        self.causes = causes
+
+
+class ResolutionTooDeep(ResolutionError):
+    def __init__(self, round_count):
+        super(ResolutionTooDeep, self).__init__(round_count)
+        self.round_count = round_count
+
+
+# Resolution state in a round.
+State = collections.namedtuple("State", "mapping criteria backtrack_causes")
+
+
+class Resolution(object):
+    """Stateful resolution object.
+
+    This is designed as a one-off object that holds information to kick start
+    the resolution process, and holds the results afterwards.
+    """
+
+    def __init__(self, provider, reporter):
+        self._p = provider
+        self._r = reporter
+        self._states = []
+
+    @property
+    def state(self):
+        try:
+            return self._states[-1]
+        except IndexError:
+            raise AttributeError("state")
+
+    def _push_new_state(self):
+        """Push a new state into history.
+
+        This new state will be used to hold resolution results of the next
+        coming round.
+        """
+        base = self._states[-1]
+        state = State(
+            mapping=base.mapping.copy(),
+            criteria=base.criteria.copy(),
+            backtrack_causes=base.backtrack_causes[:],
+        )
+        self._states.append(state)
+
+    def _add_to_criteria(self, criteria, requirement, parent):
+        self._r.adding_requirement(requirement=requirement, parent=parent)
+
+        identifier = self._p.identify(requirement_or_candidate=requirement)
+        criterion = criteria.get(identifier)
+        if criterion:
+            incompatibilities = list(criterion.incompatibilities)
+        else:
+            incompatibilities = []
+
+        matches = self._p.find_matches(
+            identifier=identifier,
+            requirements=IteratorMapping(
+                criteria,
+                operator.methodcaller("iter_requirement"),
+                {identifier: [requirement]},
+            ),
+            incompatibilities=IteratorMapping(
+                criteria,
+                operator.attrgetter("incompatibilities"),
+                {identifier: incompatibilities},
+            ),
+        )
+
+        if criterion:
+            information = list(criterion.information)
+            information.append(RequirementInformation(requirement, parent))
+        else:
+            information = [RequirementInformation(requirement, parent)]
+
+        criterion = Criterion(
+            candidates=build_iter_view(matches),
+            information=information,
+            incompatibilities=incompatibilities,
+        )
+        if not criterion.candidates:
+            raise RequirementsConflicted(criterion)
+        criteria[identifier] = criterion
+
+    def _get_preference(self, name):
+        return self._p.get_preference(
+            identifier=name,
+            resolutions=self.state.mapping,
+            candidates=IteratorMapping(
+                self.state.criteria,
+                operator.attrgetter("candidates"),
+            ),
+            information=IteratorMapping(
+                self.state.criteria,
+                operator.attrgetter("information"),
+            ),
+            backtrack_causes=self.state.backtrack_causes,
+        )
+
+    def _is_current_pin_satisfying(self, name, criterion):
+        try:
+            current_pin = self.state.mapping[name]
+        except KeyError:
+            return False
+        return all(
+            self._p.is_satisfied_by(requirement=r, candidate=current_pin)
+            for r in criterion.iter_requirement()
+        )
+
+    def _get_updated_criteria(self, candidate):
+        criteria = self.state.criteria.copy()
+        for requirement in self._p.get_dependencies(candidate=candidate):
+            self._add_to_criteria(criteria, requirement, parent=candidate)
+        return criteria
+
+    def _attempt_to_pin_criterion(self, name):
+        criterion = self.state.criteria[name]
+
+        causes = []
+        for candidate in criterion.candidates:
+            try:
+                criteria = self._get_updated_criteria(candidate)
+            except RequirementsConflicted as e:
+                causes.append(e.criterion)
+                continue
+
+            # Check the newly-pinned candidate actually works. This should
+            # always pass under normal circumstances, but in the case of a
+            # faulty provider, we will raise an error to notify the implementer
+            # to fix find_matches() and/or is_satisfied_by().
+            satisfied = all(
+                self._p.is_satisfied_by(requirement=r, candidate=candidate)
+                for r in criterion.iter_requirement()
+            )
+            if not satisfied:
+                raise InconsistentCandidate(candidate, criterion)
+
+            self._r.pinning(candidate=candidate)
+            self.state.criteria.update(criteria)
+
+            # Put newly-pinned candidate at the end. This is essential because
+            # backtracking looks at this mapping to get the last pin.
+            self.state.mapping.pop(name, None)
+            self.state.mapping[name] = candidate
+
+            return []
+
+        # All candidates tried, nothing works. This criterion is a dead
+        # end, signal for backtracking.
+        return causes
+
+    def _backtrack(self):
+        """Perform backtracking.
+
+        When we enter here, the stack is like this::
+
+            [ state Z ]
+            [ state Y ]
+            [ state X ]
+            .... earlier states are irrelevant.
+
+        1. No pins worked for Z, so it does not have a pin.
+        2. We want to reset state Y to unpinned, and pin another candidate.
+        3. State X holds what state Y was before the pin, but does not
+           have the incompatibility information gathered in state Y.
+
+        Each iteration of the loop will:
+
+        1.  Discard Z.
+        2.  Discard Y but remember its incompatibility information gathered
+            previously, and the failure we're dealing with right now.
+        3.  Push a new state Y' based on X, and apply the incompatibility
+            information from Y to Y'.
+        4a. If this causes Y' to conflict, we need to backtrack again. Make Y'
+            the new Z and go back to step 2.
+        4b. If the incompatibilities apply cleanly, end backtracking.
+        """
+        while len(self._states) >= 3:
+            # Remove the state that triggered backtracking.
+            del self._states[-1]
+
+            # Retrieve the last candidate pin and known incompatibilities.
+            broken_state = self._states.pop()
+            name, candidate = broken_state.mapping.popitem()
+            incompatibilities_from_broken = [
+                (k, list(v.incompatibilities))
+                for k, v in broken_state.criteria.items()
+            ]
+
+            # Also mark the newly known incompatibility.
+            incompatibilities_from_broken.append((name, [candidate]))
+
+            self._r.backtracking(candidate=candidate)
+
+            # Create a new state from the last known-to-work one, and apply
+            # the previously gathered incompatibility information.
+            def _patch_criteria():
+                for k, incompatibilities in incompatibilities_from_broken:
+                    if not incompatibilities:
+                        continue
+                    try:
+                        criterion = self.state.criteria[k]
+                    except KeyError:
+                        continue
+                    matches = self._p.find_matches(
+                        identifier=k,
+                        requirements=IteratorMapping(
+                            self.state.criteria,
+                            operator.methodcaller("iter_requirement"),
+                        ),
+                        incompatibilities=IteratorMapping(
+                            self.state.criteria,
+                            operator.attrgetter("incompatibilities"),
+                            {k: incompatibilities},
+                        ),
+                    )
+                    candidates = build_iter_view(matches)
+                    if not candidates:
+                        return False
+                    incompatibilities.extend(criterion.incompatibilities)
+                    self.state.criteria[k] = Criterion(
+                        candidates=candidates,
+                        information=list(criterion.information),
+                        incompatibilities=incompatibilities,
+                    )
+                return True
+
+            self._push_new_state()
+            success = _patch_criteria()
+
+            # It works! Let's work on this new state.
+            if success:
+                return True
+
+            # State does not work after applying known incompatibilities.
+            # Try the still previous state.
+
+        # No way to backtrack anymore.
+        return False
+
+    def resolve(self, requirements, max_rounds):
+        if self._states:
+            raise RuntimeError("already resolved")
+
+        self._r.starting()
+
+        # Initialize the root state.
+        self._states = [
+            State(
+                mapping=collections.OrderedDict(),
+                criteria={},
+                backtrack_causes=[],
+            )
+        ]
+        for r in requirements:
+            try:
+                self._add_to_criteria(self.state.criteria, r, parent=None)
+            except RequirementsConflicted as e:
+                raise ResolutionImpossible(e.criterion.information)
+
+        # The root state is saved as a sentinel so the first ever pin can have
+        # something to backtrack to if it fails. The root state is basically
+        # pinning the virtual "root" package in the graph.
+        self._push_new_state()
+
+        for round_index in range(max_rounds):
+            self._r.starting_round(index=round_index)
+
+            unsatisfied_names = [
+                key
+                for key, criterion in self.state.criteria.items()
+                if not self._is_current_pin_satisfying(key, criterion)
+            ]
+
+            # All criteria are accounted for. Nothing more to pin, we are done!
+            if not unsatisfied_names:
+                self._r.ending(state=self.state)
+                return self.state
+
+            # Choose the most preferred unpinned criterion to try.
+            name = min(unsatisfied_names, key=self._get_preference)
+            failure_causes = self._attempt_to_pin_criterion(name)
+
+            if failure_causes:
+                causes = [i for c in failure_causes for i in c.information]
+                # Backtrack if pinning fails. The backtrack process puts us in
+                # an unpinned state, so we can work on it in the next round.
+                self._r.resolving_conflicts(causes=causes)
+                success = self._backtrack()
+                self.state.backtrack_causes[:] = causes
+
+                # Dead ends everywhere. Give up.
+                if not success:
+                    raise ResolutionImpossible(self.state.backtrack_causes)
+            else:
+                # Pinning was successful. Push a new state to do another pin.
+                self._push_new_state()
+
+            self._r.ending_round(index=round_index, state=self.state)
+
+        raise ResolutionTooDeep(max_rounds)
+
+
+def _has_route_to_root(criteria, key, all_keys, connected):
+    if key in connected:
+        return True
+    if key not in criteria:
+        return False
+    for p in criteria[key].iter_parent():
+        try:
+            pkey = all_keys[id(p)]
+        except KeyError:
+            continue
+        if pkey in connected:
+            connected.add(key)
+            return True
+        if _has_route_to_root(criteria, pkey, all_keys, connected):
+            connected.add(key)
+            return True
+    return False
+
+
+Result = collections.namedtuple("Result", "mapping graph criteria")
+
+
+def _build_result(state):
+    mapping = state.mapping
+    all_keys = {id(v): k for k, v in mapping.items()}
+    all_keys[id(None)] = None
+
+    graph = DirectedGraph()
+    graph.add(None)  # Sentinel as root dependencies' parent.
+
+    connected = {None}
+    for key, criterion in state.criteria.items():
+        if not _has_route_to_root(state.criteria, key, all_keys, connected):
+            continue
+        if key not in graph:
+            graph.add(key)
+        for p in criterion.iter_parent():
+            try:
+                pkey = all_keys[id(p)]
+            except KeyError:
+                continue
+            if pkey not in graph:
+                graph.add(pkey)
+            graph.connect(pkey, key)
+
+    return Result(
+        mapping={k: v for k, v in mapping.items() if k in connected},
+        graph=graph,
+        criteria=state.criteria,
+    )
+
+
+class Resolver(AbstractResolver):
+    """The thing that performs the actual resolution work."""
+
+    base_exception = ResolverException
+
+    def resolve(self, requirements, max_rounds=100):
+        """Take a collection of constraints, spit out the resolution result.
+
+        The return value is a representation to the final resolution result. It
+        is a tuple subclass with three public members:
+
+        * `mapping`: A dict of resolved candidates. Each key is an identifier
+            of a requirement (as returned by the provider's `identify` method),
+            and the value is the resolved candidate.
+        * `graph`: A `DirectedGraph` instance representing the dependency tree.
+            The vertices are keys of `mapping`, and each edge represents *why*
+            a particular package is included. A special vertex `None` is
+            included to represent parents of user-supplied requirements.
+        * `criteria`: A dict of "criteria" that hold detailed information on
+            how edges in the graph are derived. Each key is an identifier of a
+            requirement, and the value is a `Criterion` instance.
+
+        The following exceptions may be raised if a resolution cannot be found:
+
+        * `ResolutionImpossible`: A resolution cannot be found for the given
+            combination of requirements. The `causes` attribute of the
+            exception is a list of (requirement, parent), giving the
+            requirements that could not be satisfied.
+        * `ResolutionTooDeep`: The dependency tree is too deeply nested and
+            the resolver gave up. This is usually caused by a circular
+            dependency, but you can try to resolve this by increasing the
+            `max_rounds` argument.
+        """
+        resolution = Resolution(self.provider, self.reporter)
+        state = resolution.resolve(requirements, max_rounds=max_rounds)
+        return _build_result(state)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/structs.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/structs.py
new file mode 100644
index 0000000000000000000000000000000000000000..93d1568bd4d5d63281b798b09cedbafdfaa158ee
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/resolvelib/structs.py
@@ -0,0 +1,165 @@
+import itertools
+
+from .compat import collections_abc
+
+
+class DirectedGraph(object):
+    """A graph structure with directed edges."""
+
+    def __init__(self):
+        self._vertices = set()
+        self._forwards = {}  #  -> Set[]
+        self._backwards = {}  #  -> Set[]
+
+    def __iter__(self):
+        return iter(self._vertices)
+
+    def __len__(self):
+        return len(self._vertices)
+
+    def __contains__(self, key):
+        return key in self._vertices
+
+    def copy(self):
+        """Return a shallow copy of this graph."""
+        other = DirectedGraph()
+        other._vertices = set(self._vertices)
+        other._forwards = {k: set(v) for k, v in self._forwards.items()}
+        other._backwards = {k: set(v) for k, v in self._backwards.items()}
+        return other
+
+    def add(self, key):
+        """Add a new vertex to the graph."""
+        if key in self._vertices:
+            raise ValueError("vertex exists")
+        self._vertices.add(key)
+        self._forwards[key] = set()
+        self._backwards[key] = set()
+
+    def remove(self, key):
+        """Remove a vertex from the graph, disconnecting all edges from/to it."""
+        self._vertices.remove(key)
+        for f in self._forwards.pop(key):
+            self._backwards[f].remove(key)
+        for t in self._backwards.pop(key):
+            self._forwards[t].remove(key)
+
+    def connected(self, f, t):
+        return f in self._backwards[t] and t in self._forwards[f]
+
+    def connect(self, f, t):
+        """Connect two existing vertices.
+
+        Nothing happens if the vertices are already connected.
+        """
+        if t not in self._vertices:
+            raise KeyError(t)
+        self._forwards[f].add(t)
+        self._backwards[t].add(f)
+
+    def iter_edges(self):
+        for f, children in self._forwards.items():
+            for t in children:
+                yield f, t
+
+    def iter_children(self, key):
+        return iter(self._forwards[key])
+
+    def iter_parents(self, key):
+        return iter(self._backwards[key])
+
+
+class IteratorMapping(collections_abc.Mapping):
+    def __init__(self, mapping, accessor, appends=None):
+        self._mapping = mapping
+        self._accessor = accessor
+        self._appends = appends or {}
+
+    def __repr__(self):
+        return "IteratorMapping({!r}, {!r}, {!r})".format(
+            self._mapping,
+            self._accessor,
+            self._appends,
+        )
+
+    def __bool__(self):
+        return bool(self._mapping or self._appends)
+
+    __nonzero__ = __bool__  # XXX: Python 2.
+
+    def __contains__(self, key):
+        return key in self._mapping or key in self._appends
+
+    def __getitem__(self, k):
+        try:
+            v = self._mapping[k]
+        except KeyError:
+            return iter(self._appends[k])
+        return itertools.chain(self._accessor(v), self._appends.get(k, ()))
+
+    def __iter__(self):
+        more = (k for k in self._appends if k not in self._mapping)
+        return itertools.chain(self._mapping, more)
+
+    def __len__(self):
+        more = sum(1 for k in self._appends if k not in self._mapping)
+        return len(self._mapping) + more
+
+
+class _FactoryIterableView(object):
+    """Wrap an iterator factory returned by `find_matches()`.
+
+    Calling `iter()` on this class would invoke the underlying iterator
+    factory, making it a "collection with ordering" that can be iterated
+    through multiple times, but lacks random access methods presented in
+    built-in Python sequence types.
+    """
+
+    def __init__(self, factory):
+        self._factory = factory
+
+    def __repr__(self):
+        return "{}({})".format(type(self).__name__, list(self._factory()))
+
+    def __bool__(self):
+        try:
+            next(self._factory())
+        except StopIteration:
+            return False
+        return True
+
+    __nonzero__ = __bool__  # XXX: Python 2.
+
+    def __iter__(self):
+        return self._factory()
+
+
+class _SequenceIterableView(object):
+    """Wrap an iterable returned by find_matches().
+
+    This is essentially just a proxy to the underlying sequence that provides
+    the same interface as `_FactoryIterableView`.
+    """
+
+    def __init__(self, sequence):
+        self._sequence = sequence
+
+    def __repr__(self):
+        return "{}({})".format(type(self).__name__, self._sequence)
+
+    def __bool__(self):
+        return bool(self._sequence)
+
+    __nonzero__ = __bool__  # XXX: Python 2.
+
+    def __iter__(self):
+        return iter(self._sequence)
+
+
+def build_iter_view(matches):
+    """Build an iterable view from the value returned by `find_matches()`."""
+    if callable(matches):
+        return _FactoryIterableView(matches)
+    if not isinstance(matches, collections_abc.Sequence):
+        matches = list(matches)
+    return _SequenceIterableView(matches)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/__init__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..73f58d7740813264d20047ffe918c82e1acc84eb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/__init__.py
@@ -0,0 +1,177 @@
+"""Rich text and beautiful formatting in the terminal."""
+
+import os
+from typing import IO, TYPE_CHECKING, Any, Callable, Optional, Union
+
+from ._extension import load_ipython_extension  # noqa: F401
+
+__all__ = ["get_console", "reconfigure", "print", "inspect", "print_json"]
+
+if TYPE_CHECKING:
+    from .console import Console
+
+# Global console used by alternative print
+_console: Optional["Console"] = None
+
+try:
+    _IMPORT_CWD = os.path.abspath(os.getcwd())
+except FileNotFoundError:
+    # Can happen if the cwd has been deleted
+    _IMPORT_CWD = ""
+
+
+def get_console() -> "Console":
+    """Get a global :class:`~rich.console.Console` instance. This function is used when Rich requires a Console,
+    and hasn't been explicitly given one.
+
+    Returns:
+        Console: A console instance.
+    """
+    global _console
+    if _console is None:
+        from .console import Console
+
+        _console = Console()
+
+    return _console
+
+
+def reconfigure(*args: Any, **kwargs: Any) -> None:
+    """Reconfigures the global console by replacing it with another.
+
+    Args:
+        *args (Any): Positional arguments for the replacement :class:`~rich.console.Console`.
+        **kwargs (Any): Keyword arguments for the replacement :class:`~rich.console.Console`.
+    """
+    from pip._vendor.rich.console import Console
+
+    new_console = Console(*args, **kwargs)
+    _console = get_console()
+    _console.__dict__ = new_console.__dict__
+
+
+def print(
+    *objects: Any,
+    sep: str = " ",
+    end: str = "\n",
+    file: Optional[IO[str]] = None,
+    flush: bool = False,
+) -> None:
+    r"""Print object(s) supplied via positional arguments.
+    This function has an identical signature to the built-in print.
+    For more advanced features, see the :class:`~rich.console.Console` class.
+
+    Args:
+        sep (str, optional): Separator between printed objects. Defaults to " ".
+        end (str, optional): Character to write at end of output. Defaults to "\\n".
+        file (IO[str], optional): File to write to, or None for stdout. Defaults to None.
+        flush (bool, optional): Has no effect as Rich always flushes output. Defaults to False.
+
+    """
+    from .console import Console
+
+    write_console = get_console() if file is None else Console(file=file)
+    return write_console.print(*objects, sep=sep, end=end)
+
+
+def print_json(
+    json: Optional[str] = None,
+    *,
+    data: Any = None,
+    indent: Union[None, int, str] = 2,
+    highlight: bool = True,
+    skip_keys: bool = False,
+    ensure_ascii: bool = False,
+    check_circular: bool = True,
+    allow_nan: bool = True,
+    default: Optional[Callable[[Any], Any]] = None,
+    sort_keys: bool = False,
+) -> None:
+    """Pretty prints JSON. Output will be valid JSON.
+
+    Args:
+        json (str): A string containing JSON.
+        data (Any): If json is not supplied, then encode this data.
+        indent (int, optional): Number of spaces to indent. Defaults to 2.
+        highlight (bool, optional): Enable highlighting of output: Defaults to True.
+        skip_keys (bool, optional): Skip keys not of a basic type. Defaults to False.
+        ensure_ascii (bool, optional): Escape all non-ascii characters. Defaults to False.
+        check_circular (bool, optional): Check for circular references. Defaults to True.
+        allow_nan (bool, optional): Allow NaN and Infinity values. Defaults to True.
+        default (Callable, optional): A callable that converts values that can not be encoded
+            in to something that can be JSON encoded. Defaults to None.
+        sort_keys (bool, optional): Sort dictionary keys. Defaults to False.
+    """
+
+    get_console().print_json(
+        json,
+        data=data,
+        indent=indent,
+        highlight=highlight,
+        skip_keys=skip_keys,
+        ensure_ascii=ensure_ascii,
+        check_circular=check_circular,
+        allow_nan=allow_nan,
+        default=default,
+        sort_keys=sort_keys,
+    )
+
+
+def inspect(
+    obj: Any,
+    *,
+    console: Optional["Console"] = None,
+    title: Optional[str] = None,
+    help: bool = False,
+    methods: bool = False,
+    docs: bool = True,
+    private: bool = False,
+    dunder: bool = False,
+    sort: bool = True,
+    all: bool = False,
+    value: bool = True,
+) -> None:
+    """Inspect any Python object.
+
+    * inspect() to see summarized info.
+    * inspect(, methods=True) to see methods.
+    * inspect(, help=True) to see full (non-abbreviated) help.
+    * inspect(, private=True) to see private attributes (single underscore).
+    * inspect(, dunder=True) to see attributes beginning with double underscore.
+    * inspect(, all=True) to see all attributes.
+
+    Args:
+        obj (Any): An object to inspect.
+        title (str, optional): Title to display over inspect result, or None use type. Defaults to None.
+        help (bool, optional): Show full help text rather than just first paragraph. Defaults to False.
+        methods (bool, optional): Enable inspection of callables. Defaults to False.
+        docs (bool, optional): Also render doc strings. Defaults to True.
+        private (bool, optional): Show private attributes (beginning with underscore). Defaults to False.
+        dunder (bool, optional): Show attributes starting with double underscore. Defaults to False.
+        sort (bool, optional): Sort attributes alphabetically. Defaults to True.
+        all (bool, optional): Show all attributes. Defaults to False.
+        value (bool, optional): Pretty print value. Defaults to True.
+    """
+    _console = console or get_console()
+    from pip._vendor.rich._inspect import Inspect
+
+    # Special case for inspect(inspect)
+    is_inspect = obj is inspect
+
+    _inspect = Inspect(
+        obj,
+        title=title,
+        help=is_inspect or help,
+        methods=is_inspect or methods,
+        docs=is_inspect or docs,
+        private=private,
+        dunder=dunder,
+        sort=sort,
+        all=all,
+        value=value,
+    )
+    _console.print(_inspect)
+
+
+if __name__ == "__main__":  # pragma: no cover
+    print("Hello, **World**")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/__main__.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..270629fd8067bfc20ed4a0b39d9897791ffa93ab
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/__main__.py
@@ -0,0 +1,274 @@
+import colorsys
+import io
+from time import process_time
+
+from pip._vendor.rich import box
+from pip._vendor.rich.color import Color
+from pip._vendor.rich.console import Console, ConsoleOptions, Group, RenderableType, RenderResult
+from pip._vendor.rich.markdown import Markdown
+from pip._vendor.rich.measure import Measurement
+from pip._vendor.rich.pretty import Pretty
+from pip._vendor.rich.segment import Segment
+from pip._vendor.rich.style import Style
+from pip._vendor.rich.syntax import Syntax
+from pip._vendor.rich.table import Table
+from pip._vendor.rich.text import Text
+
+
+class ColorBox:
+    def __rich_console__(
+        self, console: Console, options: ConsoleOptions
+    ) -> RenderResult:
+        for y in range(0, 5):
+            for x in range(options.max_width):
+                h = x / options.max_width
+                l = 0.1 + ((y / 5) * 0.7)
+                r1, g1, b1 = colorsys.hls_to_rgb(h, l, 1.0)
+                r2, g2, b2 = colorsys.hls_to_rgb(h, l + 0.7 / 10, 1.0)
+                bgcolor = Color.from_rgb(r1 * 255, g1 * 255, b1 * 255)
+                color = Color.from_rgb(r2 * 255, g2 * 255, b2 * 255)
+                yield Segment("▄", Style(color=color, bgcolor=bgcolor))
+            yield Segment.line()
+
+    def __rich_measure__(
+        self, console: "Console", options: ConsoleOptions
+    ) -> Measurement:
+        return Measurement(1, options.max_width)
+
+
+def make_test_card() -> Table:
+    """Get a renderable that demonstrates a number of features."""
+    table = Table.grid(padding=1, pad_edge=True)
+    table.title = "Rich features"
+    table.add_column("Feature", no_wrap=True, justify="center", style="bold red")
+    table.add_column("Demonstration")
+
+    color_table = Table(
+        box=None,
+        expand=False,
+        show_header=False,
+        show_edge=False,
+        pad_edge=False,
+    )
+    color_table.add_row(
+        (
+            "✓ [bold green]4-bit color[/]\n"
+            "✓ [bold blue]8-bit color[/]\n"
+            "✓ [bold magenta]Truecolor (16.7 million)[/]\n"
+            "✓ [bold yellow]Dumb terminals[/]\n"
+            "✓ [bold cyan]Automatic color conversion"
+        ),
+        ColorBox(),
+    )
+
+    table.add_row("Colors", color_table)
+
+    table.add_row(
+        "Styles",
+        "All ansi styles: [bold]bold[/], [dim]dim[/], [italic]italic[/italic], [underline]underline[/], [strike]strikethrough[/], [reverse]reverse[/], and even [blink]blink[/].",
+    )
+
+    lorem = "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque in metus sed sapien ultricies pretium a at justo. Maecenas luctus velit et auctor maximus."
+    lorem_table = Table.grid(padding=1, collapse_padding=True)
+    lorem_table.pad_edge = False
+    lorem_table.add_row(
+        Text(lorem, justify="left", style="green"),
+        Text(lorem, justify="center", style="yellow"),
+        Text(lorem, justify="right", style="blue"),
+        Text(lorem, justify="full", style="red"),
+    )
+    table.add_row(
+        "Text",
+        Group(
+            Text.from_markup(
+                """Word wrap text. Justify [green]left[/], [yellow]center[/], [blue]right[/] or [red]full[/].\n"""
+            ),
+            lorem_table,
+        ),
+    )
+
+    def comparison(renderable1: RenderableType, renderable2: RenderableType) -> Table:
+        table = Table(show_header=False, pad_edge=False, box=None, expand=True)
+        table.add_column("1", ratio=1)
+        table.add_column("2", ratio=1)
+        table.add_row(renderable1, renderable2)
+        return table
+
+    table.add_row(
+        "Asian\nlanguage\nsupport",
+        ":flag_for_china:  该库支持中文，日文和韩文文本！\n:flag_for_japan:  ライブラリは中国語、日本語、韓国語のテキストをサポートしています\n:flag_for_south_korea:  이 라이브러리는 중국어, 일본어 및 한국어 텍스트를 지원합니다",
+    )
+
+    markup_example = (
+        "[bold magenta]Rich[/] supports a simple [i]bbcode[/i]-like [b]markup[/b] for [yellow]color[/], [underline]style[/], and emoji! "
+        ":+1: :apple: :ant: :bear: :baguette_bread: :bus: "
+    )
+    table.add_row("Markup", markup_example)
+
+    example_table = Table(
+        show_edge=False,
+        show_header=True,
+        expand=False,
+        row_styles=["none", "dim"],
+        box=box.SIMPLE,
+    )
+    example_table.add_column("[green]Date", style="green", no_wrap=True)
+    example_table.add_column("[blue]Title", style="blue")
+    example_table.add_column(
+        "[cyan]Production Budget",
+        style="cyan",
+        justify="right",
+        no_wrap=True,
+    )
+    example_table.add_column(
+        "[magenta]Box Office",
+        style="magenta",
+        justify="right",
+        no_wrap=True,
+    )
+    example_table.add_row(
+        "Dec 20, 2019",
+        "Star Wars: The Rise of Skywalker",
+        "$275,000,000",
+        "$375,126,118",
+    )
+    example_table.add_row(
+        "May 25, 2018",
+        "[b]Solo[/]: A Star Wars Story",
+        "$275,000,000",
+        "$393,151,347",
+    )
+    example_table.add_row(
+        "Dec 15, 2017",
+        "Star Wars Ep. VIII: The Last Jedi",
+        "$262,000,000",
+        "[bold]$1,332,539,889[/bold]",
+    )
+    example_table.add_row(
+        "May 19, 1999",
+        "Star Wars Ep. [b]I[/b]: [i]The phantom Menace",
+        "$115,000,000",
+        "$1,027,044,677",
+    )
+
+    table.add_row("Tables", example_table)
+
+    code = '''\
+def iter_last(values: Iterable[T]) -> Iterable[Tuple[bool, T]]:
+    """Iterate and generate a tuple with a flag for last value."""
+    iter_values = iter(values)
+    try:
+        previous_value = next(iter_values)
+    except StopIteration:
+        return
+    for value in iter_values:
+        yield False, previous_value
+        previous_value = value
+    yield True, previous_value'''
+
+    pretty_data = {
+        "foo": [
+            3.1427,
+            (
+                "Paul Atreides",
+                "Vladimir Harkonnen",
+                "Thufir Hawat",
+            ),
+        ],
+        "atomic": (False, True, None),
+    }
+    table.add_row(
+        "Syntax\nhighlighting\n&\npretty\nprinting",
+        comparison(
+            Syntax(code, "python3", line_numbers=True, indent_guides=True),
+            Pretty(pretty_data, indent_guides=True),
+        ),
+    )
+
+    markdown_example = """\
+# Markdown
+
+Supports much of the *markdown* __syntax__!
+
+- Headers
+- Basic formatting: **bold**, *italic*, `code`
+- Block quotes
+- Lists, and more...
+    """
+    table.add_row(
+        "Markdown", comparison("[cyan]" + markdown_example, Markdown(markdown_example))
+    )
+
+    table.add_row(
+        "+more!",
+        """Progress bars, columns, styled logging handler, tracebacks, etc...""",
+    )
+    return table
+
+
+if __name__ == "__main__":  # pragma: no cover
+
+    console = Console(
+        file=io.StringIO(),
+        force_terminal=True,
+    )
+    test_card = make_test_card()
+
+    # Print once to warm cache
+    start = process_time()
+    console.print(test_card)
+    pre_cache_taken = round((process_time() - start) * 1000.0, 1)
+
+    console.file = io.StringIO()
+
+    start = process_time()
+    console.print(test_card)
+    taken = round((process_time() - start) * 1000.0, 1)
+
+    c = Console(record=True)
+    c.print(test_card)
+
+    print(f"rendered in {pre_cache_taken}ms (cold cache)")
+    print(f"rendered in {taken}ms (warm cache)")
+
+    from pip._vendor.rich.panel import Panel
+
+    console = Console()
+
+    sponsor_message = Table.grid(padding=1)
+    sponsor_message.add_column(style="green", justify="right")
+    sponsor_message.add_column(no_wrap=True)
+
+    sponsor_message.add_row(
+        "Textualize",
+        "[u blue link=https://github.com/textualize]https://github.com/textualize",
+    )
+    sponsor_message.add_row(
+        "Twitter",
+        "[u blue link=https://twitter.com/willmcgugan]https://twitter.com/willmcgugan",
+    )
+
+    intro_message = Text.from_markup(
+        """\
+We hope you enjoy using Rich!
+
+Rich is maintained with [red]:heart:[/] by [link=https://www.textualize.io]Textualize.io[/]
+
+- Will McGugan"""
+    )
+
+    message = Table.grid(padding=2)
+    message.add_column()
+    message.add_column(no_wrap=True)
+    message.add_row(intro_message, sponsor_message)
+
+    console.print(
+        Panel.fit(
+            message,
+            box=box.ROUNDED,
+            padding=(1, 2),
+            title="[b red]Thanks for trying out Rich!",
+            border_style="bright_blue",
+        ),
+        justify="center",
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_cell_widths.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_cell_widths.py
new file mode 100644
index 0000000000000000000000000000000000000000..36286df379e28ea997bea3ee1fd62cadebebbba9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_cell_widths.py
@@ -0,0 +1,451 @@
+# Auto generated by make_terminal_widths.py
+
+CELL_WIDTHS = [
+    (0, 0, 0),
+    (1, 31, -1),
+    (127, 159, -1),
+    (768, 879, 0),
+    (1155, 1161, 0),
+    (1425, 1469, 0),
+    (1471, 1471, 0),
+    (1473, 1474, 0),
+    (1476, 1477, 0),
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+    (1770, 1773, 0),
+    (1809, 1809, 0),
+    (1840, 1866, 0),
+    (1958, 1968, 0),
+    (2027, 2035, 0),
+    (2045, 2045, 0),
+    (2070, 2073, 0),
+    (2075, 2083, 0),
+    (2085, 2087, 0),
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+]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_emoji_codes.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_emoji_codes.py
new file mode 100644
index 0000000000000000000000000000000000000000..1f2877bb2bd520253502b1c05bb811bb0d7ef64c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_emoji_codes.py
@@ -0,0 +1,3610 @@
+EMOJI = {
+    "1st_place_medal": "🥇",
+    "2nd_place_medal": "🥈",
+    "3rd_place_medal": "🥉",
+    "ab_button_(blood_type)": "🆎",
+    "atm_sign": "🏧",
+    "a_button_(blood_type)": "🅰",
+    "afghanistan": "🇦🇫",
+    "albania": "🇦🇱",
+    "algeria": "🇩🇿",
+    "american_samoa": "🇦🇸",
+    "andorra": "🇦🇩",
+    "angola": "🇦🇴",
+    "anguilla": "🇦🇮",
+    "antarctica": "🇦🇶",
+    "antigua_&_barbuda": "🇦🇬",
+    "aquarius": "♒",
+    "argentina": "🇦🇷",
+    "aries": "♈",
+    "armenia": "🇦🇲",
+    "aruba": "🇦🇼",
+    "ascension_island": "🇦🇨",
+    "australia": "🇦🇺",
+    "austria": "🇦🇹",
+    "azerbaijan": "🇦🇿",
+    "back_arrow": "🔙",
+    "b_button_(blood_type)": "🅱",
+    "bahamas": "🇧🇸",
+    "bahrain": "🇧🇭",
+    "bangladesh": "🇧🇩",
+    "barbados": "🇧🇧",
+    "belarus": "🇧🇾",
+    "belgium": "🇧🇪",
+    "belize": "🇧🇿",
+    "benin": "🇧🇯",
+    "bermuda": "🇧🇲",
+    "bhutan": "🇧🇹",
+    "bolivia": "🇧🇴",
+    "bosnia_&_herzegovina": "🇧🇦",
+    "botswana": "🇧🇼",
+    "bouvet_island": "🇧🇻",
+    "brazil": "🇧🇷",
+    "british_indian_ocean_territory": "🇮🇴",
+    "british_virgin_islands": "🇻🇬",
+    "brunei": "🇧🇳",
+    "bulgaria": "🇧🇬",
+    "burkina_faso": "🇧🇫",
+    "burundi": "🇧🇮",
+    "cl_button": "🆑",
+    "cool_button": "🆒",
+    "cambodia": "🇰🇭",
+    "cameroon": "🇨🇲",
+    "canada": "🇨🇦",
+    "canary_islands": "🇮🇨",
+    "cancer": "♋",
+    "cape_verde": "🇨🇻",
+    "capricorn": "♑",
+    "caribbean_netherlands": "🇧🇶",
+    "cayman_islands": "🇰🇾",
+    "central_african_republic": "🇨🇫",
+    "ceuta_&_melilla": "🇪🇦",
+    "chad": "🇹🇩",
+    "chile": "🇨🇱",
+    "china": "🇨🇳",
+    "christmas_island": "🇨🇽",
+    "christmas_tree": "🎄",
+    "clipperton_island": "🇨🇵",
+    "cocos_(keeling)_islands": "🇨🇨",
+    "colombia": "🇨🇴",
+    "comoros": "🇰🇲",
+    "congo_-_brazzaville": "🇨🇬",
+    "congo_-_kinshasa": "🇨🇩",
+    "cook_islands": "🇨🇰",
+    "costa_rica": "🇨🇷",
+    "croatia": "🇭🇷",
+    "cuba": "🇨🇺",
+    "curaçao": "🇨🇼",
+    "cyprus": "🇨🇾",
+    "czechia": "🇨🇿",
+    "côte_d’ivoire": "🇨🇮",
+    "denmark": "🇩🇰",
+    "diego_garcia": "🇩🇬",
+    "djibouti": "🇩🇯",
+    "dominica": "🇩🇲",
+    "dominican_republic": "🇩🇴",
+    "end_arrow": "🔚",
+    "ecuador": "🇪🇨",
+    "egypt": "🇪🇬",
+    "el_salvador": "🇸🇻",
+    "england": "🏴\U000e0067\U000e0062\U000e0065\U000e006e\U000e0067\U000e007f",
+    "equatorial_guinea": "🇬🇶",
+    "eritrea": "🇪🇷",
+    "estonia": "🇪🇪",
+    "ethiopia": "🇪🇹",
+    "european_union": "🇪🇺",
+    "free_button": "🆓",
+    "falkland_islands": "🇫🇰",
+    "faroe_islands": "🇫🇴",
+    "fiji": "🇫🇯",
+    "finland": "🇫🇮",
+    "france": "🇫🇷",
+    "french_guiana": "🇬🇫",
+    "french_polynesia": "🇵🇫",
+    "french_southern_territories": "🇹🇫",
+    "gabon": "🇬🇦",
+    "gambia": "🇬🇲",
+    "gemini": "♊",
+    "georgia": "🇬🇪",
+    "germany": "🇩🇪",
+    "ghana": "🇬🇭",
+    "gibraltar": "🇬🇮",
+    "greece": "🇬🇷",
+    "greenland": "🇬🇱",
+    "grenada": "🇬🇩",
+    "guadeloupe": "🇬🇵",
+    "guam": "🇬🇺",
+    "guatemala": "🇬🇹",
+    "guernsey": "🇬🇬",
+    "guinea": "🇬🇳",
+    "guinea-bissau": "🇬🇼",
+    "guyana": "🇬🇾",
+    "haiti": "🇭🇹",
+    "heard_&_mcdonald_islands": "🇭🇲",
+    "honduras": "🇭🇳",
+    "hong_kong_sar_china": "🇭🇰",
+    "hungary": "🇭🇺",
+    "id_button": "🆔",
+    "iceland": "🇮🇸",
+    "india": "🇮🇳",
+    "indonesia": "🇮🇩",
+    "iran": "🇮🇷",
+    "iraq": "🇮🇶",
+    "ireland": "🇮🇪",
+    "isle_of_man": "🇮🇲",
+    "israel": "🇮🇱",
+    "italy": "🇮🇹",
+    "jamaica": "🇯🇲",
+    "japan": "🗾",
+    "japanese_acceptable_button": "🉑",
+    "japanese_application_button": "🈸",
+    "japanese_bargain_button": "🉐",
+    "japanese_castle": "🏯",
+    "japanese_congratulations_button": "㊗",
+    "japanese_discount_button": "🈹",
+    "japanese_dolls": "🎎",
+    "japanese_free_of_charge_button": "🈚",
+    "japanese_here_button": "🈁",
+    "japanese_monthly_amount_button": "🈷",
+    "japanese_no_vacancy_button": "🈵",
+    "japanese_not_free_of_charge_button": "🈶",
+    "japanese_open_for_business_button": "🈺",
+    "japanese_passing_grade_button": "🈴",
+    "japanese_post_office": "🏣",
+    "japanese_prohibited_button": "🈲",
+    "japanese_reserved_button": "🈯",
+    "japanese_secret_button": "㊙",
+    "japanese_service_charge_button": "🈂",
+    "japanese_symbol_for_beginner": "🔰",
+    "japanese_vacancy_button": "🈳",
+    "jersey": "🇯🇪",
+    "jordan": "🇯🇴",
+    "kazakhstan": "🇰🇿",
+    "kenya": "🇰🇪",
+    "kiribati": "🇰🇮",
+    "kosovo": "🇽🇰",
+    "kuwait": "🇰🇼",
+    "kyrgyzstan": "🇰🇬",
+    "laos": "🇱🇦",
+    "latvia": "🇱🇻",
+    "lebanon": "🇱🇧",
+    "leo": "♌",
+    "lesotho": "🇱🇸",
+    "liberia": "🇱🇷",
+    "libra": "♎",
+    "libya": "🇱🇾",
+    "liechtenstein": "🇱🇮",
+    "lithuania": "🇱🇹",
+    "luxembourg": "🇱🇺",
+    "macau_sar_china": "🇲🇴",
+    "macedonia": "🇲🇰",
+    "madagascar": "🇲🇬",
+    "malawi": "🇲🇼",
+    "malaysia": "🇲🇾",
+    "maldives": "🇲🇻",
+    "mali": "🇲🇱",
+    "malta": "🇲🇹",
+    "marshall_islands": "🇲🇭",
+    "martinique": "🇲🇶",
+    "mauritania": "🇲🇷",
+    "mauritius": "🇲🇺",
+    "mayotte": "🇾🇹",
+    "mexico": "🇲🇽",
+    "micronesia": "🇫🇲",
+    "moldova": "🇲🇩",
+    "monaco": "🇲🇨",
+    "mongolia": "🇲🇳",
+    "montenegro": "🇲🇪",
+    "montserrat": "🇲🇸",
+    "morocco": "🇲🇦",
+    "mozambique": "🇲🇿",
+    "mrs._claus": "🤶",
+    "mrs._claus_dark_skin_tone": "🤶🏿",
+    "mrs._claus_light_skin_tone": "🤶🏻",
+    "mrs._claus_medium-dark_skin_tone": "🤶🏾",
+    "mrs._claus_medium-light_skin_tone": "🤶🏼",
+    "mrs._claus_medium_skin_tone": "🤶🏽",
+    "myanmar_(burma)": "🇲🇲",
+    "new_button": "🆕",
+    "ng_button": "🆖",
+    "namibia": "🇳🇦",
+    "nauru": "🇳🇷",
+    "nepal": "🇳🇵",
+    "netherlands": "🇳🇱",
+    "new_caledonia": "🇳🇨",
+    "new_zealand": "🇳🇿",
+    "nicaragua": "🇳🇮",
+    "niger": "🇳🇪",
+    "nigeria": "🇳🇬",
+    "niue": "🇳🇺",
+    "norfolk_island": "🇳🇫",
+    "north_korea": "🇰🇵",
+    "northern_mariana_islands": "🇲🇵",
+    "norway": "🇳🇴",
+    "ok_button": "🆗",
+    "ok_hand": "👌",
+    "ok_hand_dark_skin_tone": "👌🏿",
+    "ok_hand_light_skin_tone": "👌🏻",
+    "ok_hand_medium-dark_skin_tone": "👌🏾",
+    "ok_hand_medium-light_skin_tone": "👌🏼",
+    "ok_hand_medium_skin_tone": "👌🏽",
+    "on!_arrow": "🔛",
+    "o_button_(blood_type)": "🅾",
+    "oman": "🇴🇲",
+    "ophiuchus": "⛎",
+    "p_button": "🅿",
+    "pakistan": "🇵🇰",
+    "palau": "🇵🇼",
+    "palestinian_territories": "🇵🇸",
+    "panama": "🇵🇦",
+    "papua_new_guinea": "🇵🇬",
+    "paraguay": "🇵🇾",
+    "peru": "🇵🇪",
+    "philippines": "🇵🇭",
+    "pisces": "♓",
+    "pitcairn_islands": "🇵🇳",
+    "poland": "🇵🇱",
+    "portugal": "🇵🇹",
+    "puerto_rico": "🇵🇷",
+    "qatar": "🇶🇦",
+    "romania": "🇷🇴",
+    "russia": "🇷🇺",
+    "rwanda": "🇷🇼",
+    "réunion": "🇷🇪",
+    "soon_arrow": "🔜",
+    "sos_button": "🆘",
+    "sagittarius": "♐",
+    "samoa": "🇼🇸",
+    "san_marino": "🇸🇲",
+    "santa_claus": "🎅",
+    "santa_claus_dark_skin_tone": "🎅🏿",
+    "santa_claus_light_skin_tone": "🎅🏻",
+    "santa_claus_medium-dark_skin_tone": "🎅🏾",
+    "santa_claus_medium-light_skin_tone": "🎅🏼",
+    "santa_claus_medium_skin_tone": "🎅🏽",
+    "saudi_arabia": "🇸🇦",
+    "scorpio": "♏",
+    "scotland": "🏴\U000e0067\U000e0062\U000e0073\U000e0063\U000e0074\U000e007f",
+    "senegal": "🇸🇳",
+    "serbia": "🇷🇸",
+    "seychelles": "🇸🇨",
+    "sierra_leone": "🇸🇱",
+    "singapore": "🇸🇬",
+    "sint_maarten": "🇸🇽",
+    "slovakia": "🇸🇰",
+    "slovenia": "🇸🇮",
+    "solomon_islands": "🇸🇧",
+    "somalia": "🇸🇴",
+    "south_africa": "🇿🇦",
+    "south_georgia_&_south_sandwich_islands": "🇬🇸",
+    "south_korea": "🇰🇷",
+    "south_sudan": "🇸🇸",
+    "spain": "🇪🇸",
+    "sri_lanka": "🇱🇰",
+    "st._barthélemy": "🇧🇱",
+    "st._helena": "🇸🇭",
+    "st._kitts_&_nevis": "🇰🇳",
+    "st._lucia": "🇱🇨",
+    "st._martin": "🇲🇫",
+    "st._pierre_&_miquelon": "🇵🇲",
+    "st._vincent_&_grenadines": "🇻🇨",
+    "statue_of_liberty": "🗽",
+    "sudan": "🇸🇩",
+    "suriname": "🇸🇷",
+    "svalbard_&_jan_mayen": "🇸🇯",
+    "swaziland": "🇸🇿",
+    "sweden": "🇸🇪",
+    "switzerland": "🇨🇭",
+    "syria": "🇸🇾",
+    "são_tomé_&_príncipe": "🇸🇹",
+    "t-rex": "🦖",
+    "top_arrow": "🔝",
+    "taiwan": "🇹🇼",
+    "tajikistan": "🇹🇯",
+    "tanzania": "🇹🇿",
+    "taurus": "♉",
+    "thailand": "🇹🇭",
+    "timor-leste": "🇹🇱",
+    "togo": "🇹🇬",
+    "tokelau": "🇹🇰",
+    "tokyo_tower": "🗼",
+    "tonga": "🇹🇴",
+    "trinidad_&_tobago": "🇹🇹",
+    "tristan_da_cunha": "🇹🇦",
+    "tunisia": "🇹🇳",
+    "turkey": "🦃",
+    "turkmenistan": "🇹🇲",
+    "turks_&_caicos_islands": "🇹🇨",
+    "tuvalu": "🇹🇻",
+    "u.s._outlying_islands": "🇺🇲",
+    "u.s._virgin_islands": "🇻🇮",
+    "up!_button": "🆙",
+    "uganda": "🇺🇬",
+    "ukraine": "🇺🇦",
+    "united_arab_emirates": "🇦🇪",
+    "united_kingdom": "🇬🇧",
+    "united_nations": "🇺🇳",
+    "united_states": "🇺🇸",
+    "uruguay": "🇺🇾",
+    "uzbekistan": "🇺🇿",
+    "vs_button": "🆚",
+    "vanuatu": "🇻🇺",
+    "vatican_city": "🇻🇦",
+    "venezuela": "🇻🇪",
+    "vietnam": "🇻🇳",
+    "virgo": "♍",
+    "wales": "🏴\U000e0067\U000e0062\U000e0077\U000e006c\U000e0073\U000e007f",
+    "wallis_&_futuna": "🇼🇫",
+    "western_sahara": "🇪🇭",
+    "yemen": "🇾🇪",
+    "zambia": "🇿🇲",
+    "zimbabwe": "🇿🇼",
+    "abacus": "🧮",
+    "adhesive_bandage": "🩹",
+    "admission_tickets": "🎟",
+    "adult": "🧑",
+    "adult_dark_skin_tone": "🧑🏿",
+    "adult_light_skin_tone": "🧑🏻",
+    "adult_medium-dark_skin_tone": "🧑🏾",
+    "adult_medium-light_skin_tone": "🧑🏼",
+    "adult_medium_skin_tone": "🧑🏽",
+    "aerial_tramway": "🚡",
+    "airplane": "✈",
+    "airplane_arrival": "🛬",
+    "airplane_departure": "🛫",
+    "alarm_clock": "⏰",
+    "alembic": "⚗",
+    "alien": "👽",
+    "alien_monster": "👾",
+    "ambulance": "🚑",
+    "american_football": "🏈",
+    "amphora": "🏺",
+    "anchor": "⚓",
+    "anger_symbol": "💢",
+    "angry_face": "😠",
+    "angry_face_with_horns": "👿",
+    "anguished_face": "😧",
+    "ant": "🐜",
+    "antenna_bars": "📶",
+    "anxious_face_with_sweat": "😰",
+    "articulated_lorry": "🚛",
+    "artist_palette": "🎨",
+    "astonished_face": "😲",
+    "atom_symbol": "⚛",
+    "auto_rickshaw": "🛺",
+    "automobile": "🚗",
+    "avocado": "🥑",
+    "axe": "🪓",
+    "baby": "👶",
+    "baby_angel": "👼",
+    "baby_angel_dark_skin_tone": "👼🏿",
+    "baby_angel_light_skin_tone": "👼🏻",
+    "baby_angel_medium-dark_skin_tone": "👼🏾",
+    "baby_angel_medium-light_skin_tone": "👼🏼",
+    "baby_angel_medium_skin_tone": "👼🏽",
+    "baby_bottle": "🍼",
+    "baby_chick": "🐤",
+    "baby_dark_skin_tone": "👶🏿",
+    "baby_light_skin_tone": "👶🏻",
+    "baby_medium-dark_skin_tone": "👶🏾",
+    "baby_medium-light_skin_tone": "👶🏼",
+    "baby_medium_skin_tone": "👶🏽",
+    "baby_symbol": "🚼",
+    "backhand_index_pointing_down": "👇",
+    "backhand_index_pointing_down_dark_skin_tone": "👇🏿",
+    "backhand_index_pointing_down_light_skin_tone": "👇🏻",
+    "backhand_index_pointing_down_medium-dark_skin_tone": "👇🏾",
+    "backhand_index_pointing_down_medium-light_skin_tone": "👇🏼",
+    "backhand_index_pointing_down_medium_skin_tone": "👇🏽",
+    "backhand_index_pointing_left": "👈",
+    "backhand_index_pointing_left_dark_skin_tone": "👈🏿",
+    "backhand_index_pointing_left_light_skin_tone": "👈🏻",
+    "backhand_index_pointing_left_medium-dark_skin_tone": "👈🏾",
+    "backhand_index_pointing_left_medium-light_skin_tone": "👈🏼",
+    "backhand_index_pointing_left_medium_skin_tone": "👈🏽",
+    "backhand_index_pointing_right": "👉",
+    "backhand_index_pointing_right_dark_skin_tone": "👉🏿",
+    "backhand_index_pointing_right_light_skin_tone": "👉🏻",
+    "backhand_index_pointing_right_medium-dark_skin_tone": "👉🏾",
+    "backhand_index_pointing_right_medium-light_skin_tone": "👉🏼",
+    "backhand_index_pointing_right_medium_skin_tone": "👉🏽",
+    "backhand_index_pointing_up": "👆",
+    "backhand_index_pointing_up_dark_skin_tone": "👆🏿",
+    "backhand_index_pointing_up_light_skin_tone": "👆🏻",
+    "backhand_index_pointing_up_medium-dark_skin_tone": "👆🏾",
+    "backhand_index_pointing_up_medium-light_skin_tone": "👆🏼",
+    "backhand_index_pointing_up_medium_skin_tone": "👆🏽",
+    "bacon": "🥓",
+    "badger": "🦡",
+    "badminton": "🏸",
+    "bagel": "🥯",
+    "baggage_claim": "🛄",
+    "baguette_bread": "🥖",
+    "balance_scale": "⚖",
+    "bald": "🦲",
+    "bald_man": "👨\u200d🦲",
+    "bald_woman": "👩\u200d🦲",
+    "ballet_shoes": "🩰",
+    "balloon": "🎈",
+    "ballot_box_with_ballot": "🗳",
+    "ballot_box_with_check": "☑",
+    "banana": "🍌",
+    "banjo": "🪕",
+    "bank": "🏦",
+    "bar_chart": "📊",
+    "barber_pole": "💈",
+    "baseball": "⚾",
+    "basket": "🧺",
+    "basketball": "🏀",
+    "bat": "🦇",
+    "bathtub": "🛁",
+    "battery": "🔋",
+    "beach_with_umbrella": "🏖",
+    "beaming_face_with_smiling_eyes": "😁",
+    "bear_face": "🐻",
+    "bearded_person": "🧔",
+    "bearded_person_dark_skin_tone": "🧔🏿",
+    "bearded_person_light_skin_tone": "🧔🏻",
+    "bearded_person_medium-dark_skin_tone": "🧔🏾",
+    "bearded_person_medium-light_skin_tone": "🧔🏼",
+    "bearded_person_medium_skin_tone": "🧔🏽",
+    "beating_heart": "💓",
+    "bed": "🛏",
+    "beer_mug": "🍺",
+    "bell": "🔔",
+    "bell_with_slash": "🔕",
+    "bellhop_bell": "🛎",
+    "bento_box": "🍱",
+    "beverage_box": "🧃",
+    "bicycle": "🚲",
+    "bikini": "👙",
+    "billed_cap": "🧢",
+    "biohazard": "☣",
+    "bird": "🐦",
+    "birthday_cake": "🎂",
+    "black_circle": "⚫",
+    "black_flag": "🏴",
+    "black_heart": "🖤",
+    "black_large_square": "⬛",
+    "black_medium-small_square": "◾",
+    "black_medium_square": "◼",
+    "black_nib": "✒",
+    "black_small_square": "▪",
+    "black_square_button": "🔲",
+    "blond-haired_man": "👱\u200d♂️",
+    "blond-haired_man_dark_skin_tone": "👱🏿\u200d♂️",
+    "blond-haired_man_light_skin_tone": "👱🏻\u200d♂️",
+    "blond-haired_man_medium-dark_skin_tone": "👱🏾\u200d♂️",
+    "blond-haired_man_medium-light_skin_tone": "👱🏼\u200d♂️",
+    "blond-haired_man_medium_skin_tone": "👱🏽\u200d♂️",
+    "blond-haired_person": "👱",
+    "blond-haired_person_dark_skin_tone": "👱🏿",
+    "blond-haired_person_light_skin_tone": "👱🏻",
+    "blond-haired_person_medium-dark_skin_tone": "👱🏾",
+    "blond-haired_person_medium-light_skin_tone": "👱🏼",
+    "blond-haired_person_medium_skin_tone": "👱🏽",
+    "blond-haired_woman": "👱\u200d♀️",
+    "blond-haired_woman_dark_skin_tone": "👱🏿\u200d♀️",
+    "blond-haired_woman_light_skin_tone": "👱🏻\u200d♀️",
+    "blond-haired_woman_medium-dark_skin_tone": "👱🏾\u200d♀️",
+    "blond-haired_woman_medium-light_skin_tone": "👱🏼\u200d♀️",
+    "blond-haired_woman_medium_skin_tone": "👱🏽\u200d♀️",
+    "blossom": "🌼",
+    "blowfish": "🐡",
+    "blue_book": "📘",
+    "blue_circle": "🔵",
+    "blue_heart": "💙",
+    "blue_square": "🟦",
+    "boar": "🐗",
+    "bomb": "💣",
+    "bone": "🦴",
+    "bookmark": "🔖",
+    "bookmark_tabs": "📑",
+    "books": "📚",
+    "bottle_with_popping_cork": "🍾",
+    "bouquet": "💐",
+    "bow_and_arrow": "🏹",
+    "bowl_with_spoon": "🥣",
+    "bowling": "🎳",
+    "boxing_glove": "🥊",
+    "boy": "👦",
+    "boy_dark_skin_tone": "👦🏿",
+    "boy_light_skin_tone": "👦🏻",
+    "boy_medium-dark_skin_tone": "👦🏾",
+    "boy_medium-light_skin_tone": "👦🏼",
+    "boy_medium_skin_tone": "👦🏽",
+    "brain": "🧠",
+    "bread": "🍞",
+    "breast-feeding": "🤱",
+    "breast-feeding_dark_skin_tone": "🤱🏿",
+    "breast-feeding_light_skin_tone": "🤱🏻",
+    "breast-feeding_medium-dark_skin_tone": "🤱🏾",
+    "breast-feeding_medium-light_skin_tone": "🤱🏼",
+    "breast-feeding_medium_skin_tone": "🤱🏽",
+    "brick": "🧱",
+    "bride_with_veil": "👰",
+    "bride_with_veil_dark_skin_tone": "👰🏿",
+    "bride_with_veil_light_skin_tone": "👰🏻",
+    "bride_with_veil_medium-dark_skin_tone": "👰🏾",
+    "bride_with_veil_medium-light_skin_tone": "👰🏼",
+    "bride_with_veil_medium_skin_tone": "👰🏽",
+    "bridge_at_night": "🌉",
+    "briefcase": "💼",
+    "briefs": "🩲",
+    "bright_button": "🔆",
+    "broccoli": "🥦",
+    "broken_heart": "💔",
+    "broom": "🧹",
+    "brown_circle": "🟤",
+    "brown_heart": "🤎",
+    "brown_square": "🟫",
+    "bug": "🐛",
+    "building_construction": "🏗",
+    "bullet_train": "🚅",
+    "burrito": "🌯",
+    "bus": "🚌",
+    "bus_stop": "🚏",
+    "bust_in_silhouette": "👤",
+    "busts_in_silhouette": "👥",
+    "butter": "🧈",
+    "butterfly": "🦋",
+    "cactus": "🌵",
+    "calendar": "📆",
+    "call_me_hand": "🤙",
+    "call_me_hand_dark_skin_tone": "🤙🏿",
+    "call_me_hand_light_skin_tone": "🤙🏻",
+    "call_me_hand_medium-dark_skin_tone": "🤙🏾",
+    "call_me_hand_medium-light_skin_tone": "🤙🏼",
+    "call_me_hand_medium_skin_tone": "🤙🏽",
+    "camel": "🐫",
+    "camera": "📷",
+    "camera_with_flash": "📸",
+    "camping": "🏕",
+    "candle": "🕯",
+    "candy": "🍬",
+    "canned_food": "🥫",
+    "canoe": "🛶",
+    "card_file_box": "🗃",
+    "card_index": "📇",
+    "card_index_dividers": "🗂",
+    "carousel_horse": "🎠",
+    "carp_streamer": "🎏",
+    "carrot": "🥕",
+    "castle": "🏰",
+    "cat": "🐱",
+    "cat_face": "🐱",
+    "cat_face_with_tears_of_joy": "😹",
+    "cat_face_with_wry_smile": "😼",
+    "chains": "⛓",
+    "chair": "🪑",
+    "chart_decreasing": "📉",
+    "chart_increasing": "📈",
+    "chart_increasing_with_yen": "💹",
+    "cheese_wedge": "🧀",
+    "chequered_flag": "🏁",
+    "cherries": "🍒",
+    "cherry_blossom": "🌸",
+    "chess_pawn": "♟",
+    "chestnut": "🌰",
+    "chicken": "🐔",
+    "child": "🧒",
+    "child_dark_skin_tone": "🧒🏿",
+    "child_light_skin_tone": "🧒🏻",
+    "child_medium-dark_skin_tone": "🧒🏾",
+    "child_medium-light_skin_tone": "🧒🏼",
+    "child_medium_skin_tone": "🧒🏽",
+    "children_crossing": "🚸",
+    "chipmunk": "🐿",
+    "chocolate_bar": "🍫",
+    "chopsticks": "🥢",
+    "church": "⛪",
+    "cigarette": "🚬",
+    "cinema": "🎦",
+    "circled_m": "Ⓜ",
+    "circus_tent": "🎪",
+    "cityscape": "🏙",
+    "cityscape_at_dusk": "🌆",
+    "clamp": "🗜",
+    "clapper_board": "🎬",
+    "clapping_hands": "👏",
+    "clapping_hands_dark_skin_tone": "👏🏿",
+    "clapping_hands_light_skin_tone": "👏🏻",
+    "clapping_hands_medium-dark_skin_tone": "👏🏾",
+    "clapping_hands_medium-light_skin_tone": "👏🏼",
+    "clapping_hands_medium_skin_tone": "👏🏽",
+    "classical_building": "🏛",
+    "clinking_beer_mugs": "🍻",
+    "clinking_glasses": "🥂",
+    "clipboard": "📋",
+    "clockwise_vertical_arrows": "🔃",
+    "closed_book": "📕",
+    "closed_mailbox_with_lowered_flag": "📪",
+    "closed_mailbox_with_raised_flag": "📫",
+    "closed_umbrella": "🌂",
+    "cloud": "☁",
+    "cloud_with_lightning": "🌩",
+    "cloud_with_lightning_and_rain": "⛈",
+    "cloud_with_rain": "🌧",
+    "cloud_with_snow": "🌨",
+    "clown_face": "🤡",
+    "club_suit": "♣",
+    "clutch_bag": "👝",
+    "coat": "🧥",
+    "cocktail_glass": "🍸",
+    "coconut": "🥥",
+    "coffin": "⚰",
+    "cold_face": "🥶",
+    "collision": "💥",
+    "comet": "☄",
+    "compass": "🧭",
+    "computer_disk": "💽",
+    "computer_mouse": "🖱",
+    "confetti_ball": "🎊",
+    "confounded_face": "😖",
+    "confused_face": "😕",
+    "construction": "🚧",
+    "construction_worker": "👷",
+    "construction_worker_dark_skin_tone": "👷🏿",
+    "construction_worker_light_skin_tone": "👷🏻",
+    "construction_worker_medium-dark_skin_tone": "👷🏾",
+    "construction_worker_medium-light_skin_tone": "👷🏼",
+    "construction_worker_medium_skin_tone": "👷🏽",
+    "control_knobs": "🎛",
+    "convenience_store": "🏪",
+    "cooked_rice": "🍚",
+    "cookie": "🍪",
+    "cooking": "🍳",
+    "copyright": "©",
+    "couch_and_lamp": "🛋",
+    "counterclockwise_arrows_button": "🔄",
+    "couple_with_heart": "💑",
+    "couple_with_heart_man_man": "👨\u200d❤️\u200d👨",
+    "couple_with_heart_woman_man": "👩\u200d❤️\u200d👨",
+    "couple_with_heart_woman_woman": "👩\u200d❤️\u200d👩",
+    "cow": "🐮",
+    "cow_face": "🐮",
+    "cowboy_hat_face": "🤠",
+    "crab": "🦀",
+    "crayon": "🖍",
+    "credit_card": "💳",
+    "crescent_moon": "🌙",
+    "cricket": "🦗",
+    "cricket_game": "🏏",
+    "crocodile": "🐊",
+    "croissant": "🥐",
+    "cross_mark": "❌",
+    "cross_mark_button": "❎",
+    "crossed_fingers": "🤞",
+    "crossed_fingers_dark_skin_tone": "🤞🏿",
+    "crossed_fingers_light_skin_tone": "🤞🏻",
+    "crossed_fingers_medium-dark_skin_tone": "🤞🏾",
+    "crossed_fingers_medium-light_skin_tone": "🤞🏼",
+    "crossed_fingers_medium_skin_tone": "🤞🏽",
+    "crossed_flags": "🎌",
+    "crossed_swords": "⚔",
+    "crown": "👑",
+    "crying_cat_face": "😿",
+    "crying_face": "😢",
+    "crystal_ball": "🔮",
+    "cucumber": "🥒",
+    "cupcake": "🧁",
+    "cup_with_straw": "🥤",
+    "curling_stone": "🥌",
+    "curly_hair": "🦱",
+    "curly-haired_man": "👨\u200d🦱",
+    "curly-haired_woman": "👩\u200d🦱",
+    "curly_loop": "➰",
+    "currency_exchange": "💱",
+    "curry_rice": "🍛",
+    "custard": "🍮",
+    "customs": "🛃",
+    "cut_of_meat": "🥩",
+    "cyclone": "🌀",
+    "dagger": "🗡",
+    "dango": "🍡",
+    "dashing_away": "💨",
+    "deaf_person": "🧏",
+    "deciduous_tree": "🌳",
+    "deer": "🦌",
+    "delivery_truck": "🚚",
+    "department_store": "🏬",
+    "derelict_house": "🏚",
+    "desert": "🏜",
+    "desert_island": "🏝",
+    "desktop_computer": "🖥",
+    "detective": "🕵",
+    "detective_dark_skin_tone": "🕵🏿",
+    "detective_light_skin_tone": "🕵🏻",
+    "detective_medium-dark_skin_tone": "🕵🏾",
+    "detective_medium-light_skin_tone": "🕵🏼",
+    "detective_medium_skin_tone": "🕵🏽",
+    "diamond_suit": "♦",
+    "diamond_with_a_dot": "💠",
+    "dim_button": "🔅",
+    "direct_hit": "🎯",
+    "disappointed_face": "😞",
+    "diving_mask": "🤿",
+    "diya_lamp": "🪔",
+    "dizzy": "💫",
+    "dizzy_face": "😵",
+    "dna": "🧬",
+    "dog": "🐶",
+    "dog_face": "🐶",
+    "dollar_banknote": "💵",
+    "dolphin": "🐬",
+    "door": "🚪",
+    "dotted_six-pointed_star": "🔯",
+    "double_curly_loop": "➿",
+    "double_exclamation_mark": "‼",
+    "doughnut": "🍩",
+    "dove": "🕊",
+    "down-left_arrow": "↙",
+    "down-right_arrow": "↘",
+    "down_arrow": "⬇",
+    "downcast_face_with_sweat": "😓",
+    "downwards_button": "🔽",
+    "dragon": "🐉",
+    "dragon_face": "🐲",
+    "dress": "👗",
+    "drooling_face": "🤤",
+    "drop_of_blood": "🩸",
+    "droplet": "💧",
+    "drum": "🥁",
+    "duck": "🦆",
+    "dumpling": "🥟",
+    "dvd": "📀",
+    "e-mail": "📧",
+    "eagle": "🦅",
+    "ear": "👂",
+    "ear_dark_skin_tone": "👂🏿",
+    "ear_light_skin_tone": "👂🏻",
+    "ear_medium-dark_skin_tone": "👂🏾",
+    "ear_medium-light_skin_tone": "👂🏼",
+    "ear_medium_skin_tone": "👂🏽",
+    "ear_of_corn": "🌽",
+    "ear_with_hearing_aid": "🦻",
+    "egg": "🍳",
+    "eggplant": "🍆",
+    "eight-pointed_star": "✴",
+    "eight-spoked_asterisk": "✳",
+    "eight-thirty": "🕣",
+    "eight_o’clock": "🕗",
+    "eject_button": "⏏",
+    "electric_plug": "🔌",
+    "elephant": "🐘",
+    "eleven-thirty": "🕦",
+    "eleven_o’clock": "🕚",
+    "elf": "🧝",
+    "elf_dark_skin_tone": "🧝🏿",
+    "elf_light_skin_tone": "🧝🏻",
+    "elf_medium-dark_skin_tone": "🧝🏾",
+    "elf_medium-light_skin_tone": "🧝🏼",
+    "elf_medium_skin_tone": "🧝🏽",
+    "envelope": "✉",
+    "envelope_with_arrow": "📩",
+    "euro_banknote": "💶",
+    "evergreen_tree": "🌲",
+    "ewe": "🐑",
+    "exclamation_mark": "❗",
+    "exclamation_question_mark": "⁉",
+    "exploding_head": "🤯",
+    "expressionless_face": "😑",
+    "eye": "👁",
+    "eye_in_speech_bubble": "👁️\u200d🗨️",
+    "eyes": "👀",
+    "face_blowing_a_kiss": "😘",
+    "face_savoring_food": "😋",
+    "face_screaming_in_fear": "😱",
+    "face_vomiting": "🤮",
+    "face_with_hand_over_mouth": "🤭",
+    "face_with_head-bandage": "🤕",
+    "face_with_medical_mask": "😷",
+    "face_with_monocle": "🧐",
+    "face_with_open_mouth": "😮",
+    "face_with_raised_eyebrow": "🤨",
+    "face_with_rolling_eyes": "🙄",
+    "face_with_steam_from_nose": "😤",
+    "face_with_symbols_on_mouth": "🤬",
+    "face_with_tears_of_joy": "😂",
+    "face_with_thermometer": "🤒",
+    "face_with_tongue": "😛",
+    "face_without_mouth": "😶",
+    "factory": "🏭",
+    "fairy": "🧚",
+    "fairy_dark_skin_tone": "🧚🏿",
+    "fairy_light_skin_tone": "🧚🏻",
+    "fairy_medium-dark_skin_tone": "🧚🏾",
+    "fairy_medium-light_skin_tone": "🧚🏼",
+    "fairy_medium_skin_tone": "🧚🏽",
+    "falafel": "🧆",
+    "fallen_leaf": "🍂",
+    "family": "👪",
+    "family_man_boy": "👨\u200d👦",
+    "family_man_boy_boy": "👨\u200d👦\u200d👦",
+    "family_man_girl": "👨\u200d👧",
+    "family_man_girl_boy": "👨\u200d👧\u200d👦",
+    "family_man_girl_girl": "👨\u200d👧\u200d👧",
+    "family_man_man_boy": "👨\u200d👨\u200d👦",
+    "family_man_man_boy_boy": "👨\u200d👨\u200d👦\u200d👦",
+    "family_man_man_girl": "👨\u200d👨\u200d👧",
+    "family_man_man_girl_boy": "👨\u200d👨\u200d👧\u200d👦",
+    "family_man_man_girl_girl": "👨\u200d👨\u200d👧\u200d👧",
+    "family_man_woman_boy": "👨\u200d👩\u200d👦",
+    "family_man_woman_boy_boy": "👨\u200d👩\u200d👦\u200d👦",
+    "family_man_woman_girl": "👨\u200d👩\u200d👧",
+    "family_man_woman_girl_boy": "👨\u200d👩\u200d👧\u200d👦",
+    "family_man_woman_girl_girl": "👨\u200d👩\u200d👧\u200d👧",
+    "family_woman_boy": "👩\u200d👦",
+    "family_woman_boy_boy": "👩\u200d👦\u200d👦",
+    "family_woman_girl": "👩\u200d👧",
+    "family_woman_girl_boy": "👩\u200d👧\u200d👦",
+    "family_woman_girl_girl": "👩\u200d👧\u200d👧",
+    "family_woman_woman_boy": "👩\u200d👩\u200d👦",
+    "family_woman_woman_boy_boy": "👩\u200d👩\u200d👦\u200d👦",
+    "family_woman_woman_girl": "👩\u200d👩\u200d👧",
+    "family_woman_woman_girl_boy": "👩\u200d👩\u200d👧\u200d👦",
+    "family_woman_woman_girl_girl": "👩\u200d👩\u200d👧\u200d👧",
+    "fast-forward_button": "⏩",
+    "fast_down_button": "⏬",
+    "fast_reverse_button": "⏪",
+    "fast_up_button": "⏫",
+    "fax_machine": "📠",
+    "fearful_face": "😨",
+    "female_sign": "♀",
+    "ferris_wheel": "🎡",
+    "ferry": "⛴",
+    "field_hockey": "🏑",
+    "file_cabinet": "🗄",
+    "file_folder": "📁",
+    "film_frames": "🎞",
+    "film_projector": "📽",
+    "fire": "🔥",
+    "fire_extinguisher": "🧯",
+    "firecracker": "🧨",
+    "fire_engine": "🚒",
+    "fireworks": "🎆",
+    "first_quarter_moon": "🌓",
+    "first_quarter_moon_face": "🌛",
+    "fish": "🐟",
+    "fish_cake_with_swirl": "🍥",
+    "fishing_pole": "🎣",
+    "five-thirty": "🕠",
+    "five_o’clock": "🕔",
+    "flag_in_hole": "⛳",
+    "flamingo": "🦩",
+    "flashlight": "🔦",
+    "flat_shoe": "🥿",
+    "fleur-de-lis": "⚜",
+    "flexed_biceps": "💪",
+    "flexed_biceps_dark_skin_tone": "💪🏿",
+    "flexed_biceps_light_skin_tone": "💪🏻",
+    "flexed_biceps_medium-dark_skin_tone": "💪🏾",
+    "flexed_biceps_medium-light_skin_tone": "💪🏼",
+    "flexed_biceps_medium_skin_tone": "💪🏽",
+    "floppy_disk": "💾",
+    "flower_playing_cards": "🎴",
+    "flushed_face": "😳",
+    "flying_disc": "🥏",
+    "flying_saucer": "🛸",
+    "fog": "🌫",
+    "foggy": "🌁",
+    "folded_hands": "🙏",
+    "folded_hands_dark_skin_tone": "🙏🏿",
+    "folded_hands_light_skin_tone": "🙏🏻",
+    "folded_hands_medium-dark_skin_tone": "🙏🏾",
+    "folded_hands_medium-light_skin_tone": "🙏🏼",
+    "folded_hands_medium_skin_tone": "🙏🏽",
+    "foot": "🦶",
+    "footprints": "👣",
+    "fork_and_knife": "🍴",
+    "fork_and_knife_with_plate": "🍽",
+    "fortune_cookie": "🥠",
+    "fountain": "⛲",
+    "fountain_pen": "🖋",
+    "four-thirty": "🕟",
+    "four_leaf_clover": "🍀",
+    "four_o’clock": "🕓",
+    "fox_face": "🦊",
+    "framed_picture": "🖼",
+    "french_fries": "🍟",
+    "fried_shrimp": "🍤",
+    "frog_face": "🐸",
+    "front-facing_baby_chick": "🐥",
+    "frowning_face": "☹",
+    "frowning_face_with_open_mouth": "😦",
+    "fuel_pump": "⛽",
+    "full_moon": "🌕",
+    "full_moon_face": "🌝",
+    "funeral_urn": "⚱",
+    "game_die": "🎲",
+    "garlic": "🧄",
+    "gear": "⚙",
+    "gem_stone": "💎",
+    "genie": "🧞",
+    "ghost": "👻",
+    "giraffe": "🦒",
+    "girl": "👧",
+    "girl_dark_skin_tone": "👧🏿",
+    "girl_light_skin_tone": "👧🏻",
+    "girl_medium-dark_skin_tone": "👧🏾",
+    "girl_medium-light_skin_tone": "👧🏼",
+    "girl_medium_skin_tone": "👧🏽",
+    "glass_of_milk": "🥛",
+    "glasses": "👓",
+    "globe_showing_americas": "🌎",
+    "globe_showing_asia-australia": "🌏",
+    "globe_showing_europe-africa": "🌍",
+    "globe_with_meridians": "🌐",
+    "gloves": "🧤",
+    "glowing_star": "🌟",
+    "goal_net": "🥅",
+    "goat": "🐐",
+    "goblin": "👺",
+    "goggles": "🥽",
+    "gorilla": "🦍",
+    "graduation_cap": "🎓",
+    "grapes": "🍇",
+    "green_apple": "🍏",
+    "green_book": "📗",
+    "green_circle": "🟢",
+    "green_heart": "💚",
+    "green_salad": "🥗",
+    "green_square": "🟩",
+    "grimacing_face": "😬",
+    "grinning_cat_face": "😺",
+    "grinning_cat_face_with_smiling_eyes": "😸",
+    "grinning_face": "😀",
+    "grinning_face_with_big_eyes": "😃",
+    "grinning_face_with_smiling_eyes": "😄",
+    "grinning_face_with_sweat": "😅",
+    "grinning_squinting_face": "😆",
+    "growing_heart": "💗",
+    "guard": "💂",
+    "guard_dark_skin_tone": "💂🏿",
+    "guard_light_skin_tone": "💂🏻",
+    "guard_medium-dark_skin_tone": "💂🏾",
+    "guard_medium-light_skin_tone": "💂🏼",
+    "guard_medium_skin_tone": "💂🏽",
+    "guide_dog": "🦮",
+    "guitar": "🎸",
+    "hamburger": "🍔",
+    "hammer": "🔨",
+    "hammer_and_pick": "⚒",
+    "hammer_and_wrench": "🛠",
+    "hamster_face": "🐹",
+    "hand_with_fingers_splayed": "🖐",
+    "hand_with_fingers_splayed_dark_skin_tone": "🖐🏿",
+    "hand_with_fingers_splayed_light_skin_tone": "🖐🏻",
+    "hand_with_fingers_splayed_medium-dark_skin_tone": "🖐🏾",
+    "hand_with_fingers_splayed_medium-light_skin_tone": "🖐🏼",
+    "hand_with_fingers_splayed_medium_skin_tone": "🖐🏽",
+    "handbag": "👜",
+    "handshake": "🤝",
+    "hatching_chick": "🐣",
+    "headphone": "🎧",
+    "hear-no-evil_monkey": "🙉",
+    "heart_decoration": "💟",
+    "heart_suit": "♥",
+    "heart_with_arrow": "💘",
+    "heart_with_ribbon": "💝",
+    "heavy_check_mark": "✔",
+    "heavy_division_sign": "➗",
+    "heavy_dollar_sign": "💲",
+    "heavy_heart_exclamation": "❣",
+    "heavy_large_circle": "⭕",
+    "heavy_minus_sign": "➖",
+    "heavy_multiplication_x": "✖",
+    "heavy_plus_sign": "➕",
+    "hedgehog": "🦔",
+    "helicopter": "🚁",
+    "herb": "🌿",
+    "hibiscus": "🌺",
+    "high-heeled_shoe": "👠",
+    "high-speed_train": "🚄",
+    "high_voltage": "⚡",
+    "hiking_boot": "🥾",
+    "hindu_temple": "🛕",
+    "hippopotamus": "🦛",
+    "hole": "🕳",
+    "honey_pot": "🍯",
+    "honeybee": "🐝",
+    "horizontal_traffic_light": "🚥",
+    "horse": "🐴",
+    "horse_face": "🐴",
+    "horse_racing": "🏇",
+    "horse_racing_dark_skin_tone": "🏇🏿",
+    "horse_racing_light_skin_tone": "🏇🏻",
+    "horse_racing_medium-dark_skin_tone": "🏇🏾",
+    "horse_racing_medium-light_skin_tone": "🏇🏼",
+    "horse_racing_medium_skin_tone": "🏇🏽",
+    "hospital": "🏥",
+    "hot_beverage": "☕",
+    "hot_dog": "🌭",
+    "hot_face": "🥵",
+    "hot_pepper": "🌶",
+    "hot_springs": "♨",
+    "hotel": "🏨",
+    "hourglass_done": "⌛",
+    "hourglass_not_done": "⏳",
+    "house": "🏠",
+    "house_with_garden": "🏡",
+    "houses": "🏘",
+    "hugging_face": "🤗",
+    "hundred_points": "💯",
+    "hushed_face": "😯",
+    "ice": "🧊",
+    "ice_cream": "🍨",
+    "ice_hockey": "🏒",
+    "ice_skate": "⛸",
+    "inbox_tray": "📥",
+    "incoming_envelope": "📨",
+    "index_pointing_up": "☝",
+    "index_pointing_up_dark_skin_tone": "☝🏿",
+    "index_pointing_up_light_skin_tone": "☝🏻",
+    "index_pointing_up_medium-dark_skin_tone": "☝🏾",
+    "index_pointing_up_medium-light_skin_tone": "☝🏼",
+    "index_pointing_up_medium_skin_tone": "☝🏽",
+    "infinity": "♾",
+    "information": "ℹ",
+    "input_latin_letters": "🔤",
+    "input_latin_lowercase": "🔡",
+    "input_latin_uppercase": "🔠",
+    "input_numbers": "🔢",
+    "input_symbols": "🔣",
+    "jack-o-lantern": "🎃",
+    "jeans": "👖",
+    "jigsaw": "🧩",
+    "joker": "🃏",
+    "joystick": "🕹",
+    "kaaba": "🕋",
+    "kangaroo": "🦘",
+    "key": "🔑",
+    "keyboard": "⌨",
+    "keycap_#": "#️⃣",
+    "keycap_*": "*️⃣",
+    "keycap_0": "0️⃣",
+    "keycap_1": "1️⃣",
+    "keycap_10": "🔟",
+    "keycap_2": "2️⃣",
+    "keycap_3": "3️⃣",
+    "keycap_4": "4️⃣",
+    "keycap_5": "5️⃣",
+    "keycap_6": "6️⃣",
+    "keycap_7": "7️⃣",
+    "keycap_8": "8️⃣",
+    "keycap_9": "9️⃣",
+    "kick_scooter": "🛴",
+    "kimono": "👘",
+    "kiss": "💋",
+    "kiss_man_man": "👨\u200d❤️\u200d💋\u200d👨",
+    "kiss_mark": "💋",
+    "kiss_woman_man": "👩\u200d❤️\u200d💋\u200d👨",
+    "kiss_woman_woman": "👩\u200d❤️\u200d💋\u200d👩",
+    "kissing_cat_face": "😽",
+    "kissing_face": "😗",
+    "kissing_face_with_closed_eyes": "😚",
+    "kissing_face_with_smiling_eyes": "😙",
+    "kitchen_knife": "🔪",
+    "kite": "🪁",
+    "kiwi_fruit": "🥝",
+    "koala": "🐨",
+    "lab_coat": "🥼",
+    "label": "🏷",
+    "lacrosse": "🥍",
+    "lady_beetle": "🐞",
+    "laptop_computer": "💻",
+    "large_blue_diamond": "🔷",
+    "large_orange_diamond": "🔶",
+    "last_quarter_moon": "🌗",
+    "last_quarter_moon_face": "🌜",
+    "last_track_button": "⏮",
+    "latin_cross": "✝",
+    "leaf_fluttering_in_wind": "🍃",
+    "leafy_green": "🥬",
+    "ledger": "📒",
+    "left-facing_fist": "🤛",
+    "left-facing_fist_dark_skin_tone": "🤛🏿",
+    "left-facing_fist_light_skin_tone": "🤛🏻",
+    "left-facing_fist_medium-dark_skin_tone": "🤛🏾",
+    "left-facing_fist_medium-light_skin_tone": "🤛🏼",
+    "left-facing_fist_medium_skin_tone": "🤛🏽",
+    "left-right_arrow": "↔",
+    "left_arrow": "⬅",
+    "left_arrow_curving_right": "↪",
+    "left_luggage": "🛅",
+    "left_speech_bubble": "🗨",
+    "leg": "🦵",
+    "lemon": "🍋",
+    "leopard": "🐆",
+    "level_slider": "🎚",
+    "light_bulb": "💡",
+    "light_rail": "🚈",
+    "link": "🔗",
+    "linked_paperclips": "🖇",
+    "lion_face": "🦁",
+    "lipstick": "💄",
+    "litter_in_bin_sign": "🚮",
+    "lizard": "🦎",
+    "llama": "🦙",
+    "lobster": "🦞",
+    "locked": "🔒",
+    "locked_with_key": "🔐",
+    "locked_with_pen": "🔏",
+    "locomotive": "🚂",
+    "lollipop": "🍭",
+    "lotion_bottle": "🧴",
+    "loudly_crying_face": "😭",
+    "loudspeaker": "📢",
+    "love-you_gesture": "🤟",
+    "love-you_gesture_dark_skin_tone": "🤟🏿",
+    "love-you_gesture_light_skin_tone": "🤟🏻",
+    "love-you_gesture_medium-dark_skin_tone": "🤟🏾",
+    "love-you_gesture_medium-light_skin_tone": "🤟🏼",
+    "love-you_gesture_medium_skin_tone": "🤟🏽",
+    "love_hotel": "🏩",
+    "love_letter": "💌",
+    "luggage": "🧳",
+    "lying_face": "🤥",
+    "mage": "🧙",
+    "mage_dark_skin_tone": "🧙🏿",
+    "mage_light_skin_tone": "🧙🏻",
+    "mage_medium-dark_skin_tone": "🧙🏾",
+    "mage_medium-light_skin_tone": "🧙🏼",
+    "mage_medium_skin_tone": "🧙🏽",
+    "magnet": "🧲",
+    "magnifying_glass_tilted_left": "🔍",
+    "magnifying_glass_tilted_right": "🔎",
+    "mahjong_red_dragon": "🀄",
+    "male_sign": "♂",
+    "man": "👨",
+    "man_and_woman_holding_hands": "👫",
+    "man_artist": "👨\u200d🎨",
+    "man_artist_dark_skin_tone": "👨🏿\u200d🎨",
+    "man_artist_light_skin_tone": "👨🏻\u200d🎨",
+    "man_artist_medium-dark_skin_tone": "👨🏾\u200d🎨",
+    "man_artist_medium-light_skin_tone": "👨🏼\u200d🎨",
+    "man_artist_medium_skin_tone": "👨🏽\u200d🎨",
+    "man_astronaut": "👨\u200d🚀",
+    "man_astronaut_dark_skin_tone": "👨🏿\u200d🚀",
+    "man_astronaut_light_skin_tone": "👨🏻\u200d🚀",
+    "man_astronaut_medium-dark_skin_tone": "👨🏾\u200d🚀",
+    "man_astronaut_medium-light_skin_tone": "👨🏼\u200d🚀",
+    "man_astronaut_medium_skin_tone": "👨🏽\u200d🚀",
+    "man_biking": "🚴\u200d♂️",
+    "man_biking_dark_skin_tone": "🚴🏿\u200d♂️",
+    "man_biking_light_skin_tone": "🚴🏻\u200d♂️",
+    "man_biking_medium-dark_skin_tone": "🚴🏾\u200d♂️",
+    "man_biking_medium-light_skin_tone": "🚴🏼\u200d♂️",
+    "man_biking_medium_skin_tone": "🚴🏽\u200d♂️",
+    "man_bouncing_ball": "⛹️\u200d♂️",
+    "man_bouncing_ball_dark_skin_tone": "⛹🏿\u200d♂️",
+    "man_bouncing_ball_light_skin_tone": "⛹🏻\u200d♂️",
+    "man_bouncing_ball_medium-dark_skin_tone": "⛹🏾\u200d♂️",
+    "man_bouncing_ball_medium-light_skin_tone": "⛹🏼\u200d♂️",
+    "man_bouncing_ball_medium_skin_tone": "⛹🏽\u200d♂️",
+    "man_bowing": "🙇\u200d♂️",
+    "man_bowing_dark_skin_tone": "🙇🏿\u200d♂️",
+    "man_bowing_light_skin_tone": "🙇🏻\u200d♂️",
+    "man_bowing_medium-dark_skin_tone": "🙇🏾\u200d♂️",
+    "man_bowing_medium-light_skin_tone": "🙇🏼\u200d♂️",
+    "man_bowing_medium_skin_tone": "🙇🏽\u200d♂️",
+    "man_cartwheeling": "🤸\u200d♂️",
+    "man_cartwheeling_dark_skin_tone": "🤸🏿\u200d♂️",
+    "man_cartwheeling_light_skin_tone": "🤸🏻\u200d♂️",
+    "man_cartwheeling_medium-dark_skin_tone": "🤸🏾\u200d♂️",
+    "man_cartwheeling_medium-light_skin_tone": "🤸🏼\u200d♂️",
+    "man_cartwheeling_medium_skin_tone": "🤸🏽\u200d♂️",
+    "man_climbing": "🧗\u200d♂️",
+    "man_climbing_dark_skin_tone": "🧗🏿\u200d♂️",
+    "man_climbing_light_skin_tone": "🧗🏻\u200d♂️",
+    "man_climbing_medium-dark_skin_tone": "🧗🏾\u200d♂️",
+    "man_climbing_medium-light_skin_tone": "🧗🏼\u200d♂️",
+    "man_climbing_medium_skin_tone": "🧗🏽\u200d♂️",
+    "man_construction_worker": "👷\u200d♂️",
+    "man_construction_worker_dark_skin_tone": "👷🏿\u200d♂️",
+    "man_construction_worker_light_skin_tone": "👷🏻\u200d♂️",
+    "man_construction_worker_medium-dark_skin_tone": "👷🏾\u200d♂️",
+    "man_construction_worker_medium-light_skin_tone": "👷🏼\u200d♂️",
+    "man_construction_worker_medium_skin_tone": "👷🏽\u200d♂️",
+    "man_cook": "👨\u200d🍳",
+    "man_cook_dark_skin_tone": "👨🏿\u200d🍳",
+    "man_cook_light_skin_tone": "👨🏻\u200d🍳",
+    "man_cook_medium-dark_skin_tone": "👨🏾\u200d🍳",
+    "man_cook_medium-light_skin_tone": "👨🏼\u200d🍳",
+    "man_cook_medium_skin_tone": "👨🏽\u200d🍳",
+    "man_dancing": "🕺",
+    "man_dancing_dark_skin_tone": "🕺🏿",
+    "man_dancing_light_skin_tone": "🕺🏻",
+    "man_dancing_medium-dark_skin_tone": "🕺🏾",
+    "man_dancing_medium-light_skin_tone": "🕺🏼",
+    "man_dancing_medium_skin_tone": "🕺🏽",
+    "man_dark_skin_tone": "👨🏿",
+    "man_detective": "🕵️\u200d♂️",
+    "man_detective_dark_skin_tone": "🕵🏿\u200d♂️",
+    "man_detective_light_skin_tone": "🕵🏻\u200d♂️",
+    "man_detective_medium-dark_skin_tone": "🕵🏾\u200d♂️",
+    "man_detective_medium-light_skin_tone": "🕵🏼\u200d♂️",
+    "man_detective_medium_skin_tone": "🕵🏽\u200d♂️",
+    "man_elf": "🧝\u200d♂️",
+    "man_elf_dark_skin_tone": "🧝🏿\u200d♂️",
+    "man_elf_light_skin_tone": "🧝🏻\u200d♂️",
+    "man_elf_medium-dark_skin_tone": "🧝🏾\u200d♂️",
+    "man_elf_medium-light_skin_tone": "🧝🏼\u200d♂️",
+    "man_elf_medium_skin_tone": "🧝🏽\u200d♂️",
+    "man_facepalming": "🤦\u200d♂️",
+    "man_facepalming_dark_skin_tone": "🤦🏿\u200d♂️",
+    "man_facepalming_light_skin_tone": "🤦🏻\u200d♂️",
+    "man_facepalming_medium-dark_skin_tone": "🤦🏾\u200d♂️",
+    "man_facepalming_medium-light_skin_tone": "🤦🏼\u200d♂️",
+    "man_facepalming_medium_skin_tone": "🤦🏽\u200d♂️",
+    "man_factory_worker": "👨\u200d🏭",
+    "man_factory_worker_dark_skin_tone": "👨🏿\u200d🏭",
+    "man_factory_worker_light_skin_tone": "👨🏻\u200d🏭",
+    "man_factory_worker_medium-dark_skin_tone": "👨🏾\u200d🏭",
+    "man_factory_worker_medium-light_skin_tone": "👨🏼\u200d🏭",
+    "man_factory_worker_medium_skin_tone": "👨🏽\u200d🏭",
+    "man_fairy": "🧚\u200d♂️",
+    "man_fairy_dark_skin_tone": "🧚🏿\u200d♂️",
+    "man_fairy_light_skin_tone": "🧚🏻\u200d♂️",
+    "man_fairy_medium-dark_skin_tone": "🧚🏾\u200d♂️",
+    "man_fairy_medium-light_skin_tone": "🧚🏼\u200d♂️",
+    "man_fairy_medium_skin_tone": "🧚🏽\u200d♂️",
+    "man_farmer": "👨\u200d🌾",
+    "man_farmer_dark_skin_tone": "👨🏿\u200d🌾",
+    "man_farmer_light_skin_tone": "👨🏻\u200d🌾",
+    "man_farmer_medium-dark_skin_tone": "👨🏾\u200d🌾",
+    "man_farmer_medium-light_skin_tone": "👨🏼\u200d🌾",
+    "man_farmer_medium_skin_tone": "👨🏽\u200d🌾",
+    "man_firefighter": "👨\u200d🚒",
+    "man_firefighter_dark_skin_tone": "👨🏿\u200d🚒",
+    "man_firefighter_light_skin_tone": "👨🏻\u200d🚒",
+    "man_firefighter_medium-dark_skin_tone": "👨🏾\u200d🚒",
+    "man_firefighter_medium-light_skin_tone": "👨🏼\u200d🚒",
+    "man_firefighter_medium_skin_tone": "👨🏽\u200d🚒",
+    "man_frowning": "🙍\u200d♂️",
+    "man_frowning_dark_skin_tone": "🙍🏿\u200d♂️",
+    "man_frowning_light_skin_tone": "🙍🏻\u200d♂️",
+    "man_frowning_medium-dark_skin_tone": "🙍🏾\u200d♂️",
+    "man_frowning_medium-light_skin_tone": "🙍🏼\u200d♂️",
+    "man_frowning_medium_skin_tone": "🙍🏽\u200d♂️",
+    "man_genie": "🧞\u200d♂️",
+    "man_gesturing_no": "🙅\u200d♂️",
+    "man_gesturing_no_dark_skin_tone": "🙅🏿\u200d♂️",
+    "man_gesturing_no_light_skin_tone": "🙅🏻\u200d♂️",
+    "man_gesturing_no_medium-dark_skin_tone": "🙅🏾\u200d♂️",
+    "man_gesturing_no_medium-light_skin_tone": "🙅🏼\u200d♂️",
+    "man_gesturing_no_medium_skin_tone": "🙅🏽\u200d♂️",
+    "man_gesturing_ok": "🙆\u200d♂️",
+    "man_gesturing_ok_dark_skin_tone": "🙆🏿\u200d♂️",
+    "man_gesturing_ok_light_skin_tone": "🙆🏻\u200d♂️",
+    "man_gesturing_ok_medium-dark_skin_tone": "🙆🏾\u200d♂️",
+    "man_gesturing_ok_medium-light_skin_tone": "🙆🏼\u200d♂️",
+    "man_gesturing_ok_medium_skin_tone": "🙆🏽\u200d♂️",
+    "man_getting_haircut": "💇\u200d♂️",
+    "man_getting_haircut_dark_skin_tone": "💇🏿\u200d♂️",
+    "man_getting_haircut_light_skin_tone": "💇🏻\u200d♂️",
+    "man_getting_haircut_medium-dark_skin_tone": "💇🏾\u200d♂️",
+    "man_getting_haircut_medium-light_skin_tone": "💇🏼\u200d♂️",
+    "man_getting_haircut_medium_skin_tone": "💇🏽\u200d♂️",
+    "man_getting_massage": "💆\u200d♂️",
+    "man_getting_massage_dark_skin_tone": "💆🏿\u200d♂️",
+    "man_getting_massage_light_skin_tone": "💆🏻\u200d♂️",
+    "man_getting_massage_medium-dark_skin_tone": "💆🏾\u200d♂️",
+    "man_getting_massage_medium-light_skin_tone": "💆🏼\u200d♂️",
+    "man_getting_massage_medium_skin_tone": "💆🏽\u200d♂️",
+    "man_golfing": "🏌️\u200d♂️",
+    "man_golfing_dark_skin_tone": "🏌🏿\u200d♂️",
+    "man_golfing_light_skin_tone": "🏌🏻\u200d♂️",
+    "man_golfing_medium-dark_skin_tone": "🏌🏾\u200d♂️",
+    "man_golfing_medium-light_skin_tone": "🏌🏼\u200d♂️",
+    "man_golfing_medium_skin_tone": "🏌🏽\u200d♂️",
+    "man_guard": "💂\u200d♂️",
+    "man_guard_dark_skin_tone": "💂🏿\u200d♂️",
+    "man_guard_light_skin_tone": "💂🏻\u200d♂️",
+    "man_guard_medium-dark_skin_tone": "💂🏾\u200d♂️",
+    "man_guard_medium-light_skin_tone": "💂🏼\u200d♂️",
+    "man_guard_medium_skin_tone": "💂🏽\u200d♂️",
+    "man_health_worker": "👨\u200d⚕️",
+    "man_health_worker_dark_skin_tone": "👨🏿\u200d⚕️",
+    "man_health_worker_light_skin_tone": "👨🏻\u200d⚕️",
+    "man_health_worker_medium-dark_skin_tone": "👨🏾\u200d⚕️",
+    "man_health_worker_medium-light_skin_tone": "👨🏼\u200d⚕️",
+    "man_health_worker_medium_skin_tone": "👨🏽\u200d⚕️",
+    "man_in_lotus_position": "🧘\u200d♂️",
+    "man_in_lotus_position_dark_skin_tone": "🧘🏿\u200d♂️",
+    "man_in_lotus_position_light_skin_tone": "🧘🏻\u200d♂️",
+    "man_in_lotus_position_medium-dark_skin_tone": "🧘🏾\u200d♂️",
+    "man_in_lotus_position_medium-light_skin_tone": "🧘🏼\u200d♂️",
+    "man_in_lotus_position_medium_skin_tone": "🧘🏽\u200d♂️",
+    "man_in_manual_wheelchair": "👨\u200d🦽",
+    "man_in_motorized_wheelchair": "👨\u200d🦼",
+    "man_in_steamy_room": "🧖\u200d♂️",
+    "man_in_steamy_room_dark_skin_tone": "🧖🏿\u200d♂️",
+    "man_in_steamy_room_light_skin_tone": "🧖🏻\u200d♂️",
+    "man_in_steamy_room_medium-dark_skin_tone": "🧖🏾\u200d♂️",
+    "man_in_steamy_room_medium-light_skin_tone": "🧖🏼\u200d♂️",
+    "man_in_steamy_room_medium_skin_tone": "🧖🏽\u200d♂️",
+    "man_in_suit_levitating": "🕴",
+    "man_in_suit_levitating_dark_skin_tone": "🕴🏿",
+    "man_in_suit_levitating_light_skin_tone": "🕴🏻",
+    "man_in_suit_levitating_medium-dark_skin_tone": "🕴🏾",
+    "man_in_suit_levitating_medium-light_skin_tone": "🕴🏼",
+    "man_in_suit_levitating_medium_skin_tone": "🕴🏽",
+    "man_in_tuxedo": "🤵",
+    "man_in_tuxedo_dark_skin_tone": "🤵🏿",
+    "man_in_tuxedo_light_skin_tone": "🤵🏻",
+    "man_in_tuxedo_medium-dark_skin_tone": "🤵🏾",
+    "man_in_tuxedo_medium-light_skin_tone": "🤵🏼",
+    "man_in_tuxedo_medium_skin_tone": "🤵🏽",
+    "man_judge": "👨\u200d⚖️",
+    "man_judge_dark_skin_tone": "👨🏿\u200d⚖️",
+    "man_judge_light_skin_tone": "👨🏻\u200d⚖️",
+    "man_judge_medium-dark_skin_tone": "👨🏾\u200d⚖️",
+    "man_judge_medium-light_skin_tone": "👨🏼\u200d⚖️",
+    "man_judge_medium_skin_tone": "👨🏽\u200d⚖️",
+    "man_juggling": "🤹\u200d♂️",
+    "man_juggling_dark_skin_tone": "🤹🏿\u200d♂️",
+    "man_juggling_light_skin_tone": "🤹🏻\u200d♂️",
+    "man_juggling_medium-dark_skin_tone": "🤹🏾\u200d♂️",
+    "man_juggling_medium-light_skin_tone": "🤹🏼\u200d♂️",
+    "man_juggling_medium_skin_tone": "🤹🏽\u200d♂️",
+    "man_lifting_weights": "🏋️\u200d♂️",
+    "man_lifting_weights_dark_skin_tone": "🏋🏿\u200d♂️",
+    "man_lifting_weights_light_skin_tone": "🏋🏻\u200d♂️",
+    "man_lifting_weights_medium-dark_skin_tone": "🏋🏾\u200d♂️",
+    "man_lifting_weights_medium-light_skin_tone": "🏋🏼\u200d♂️",
+    "man_lifting_weights_medium_skin_tone": "🏋🏽\u200d♂️",
+    "man_light_skin_tone": "👨🏻",
+    "man_mage": "🧙\u200d♂️",
+    "man_mage_dark_skin_tone": "🧙🏿\u200d♂️",
+    "man_mage_light_skin_tone": "🧙🏻\u200d♂️",
+    "man_mage_medium-dark_skin_tone": "🧙🏾\u200d♂️",
+    "man_mage_medium-light_skin_tone": "🧙🏼\u200d♂️",
+    "man_mage_medium_skin_tone": "🧙🏽\u200d♂️",
+    "man_mechanic": "👨\u200d🔧",
+    "man_mechanic_dark_skin_tone": "👨🏿\u200d🔧",
+    "man_mechanic_light_skin_tone": "👨🏻\u200d🔧",
+    "man_mechanic_medium-dark_skin_tone": "👨🏾\u200d🔧",
+    "man_mechanic_medium-light_skin_tone": "👨🏼\u200d🔧",
+    "man_mechanic_medium_skin_tone": "👨🏽\u200d🔧",
+    "man_medium-dark_skin_tone": "👨🏾",
+    "man_medium-light_skin_tone": "👨🏼",
+    "man_medium_skin_tone": "👨🏽",
+    "man_mountain_biking": "🚵\u200d♂️",
+    "man_mountain_biking_dark_skin_tone": "🚵🏿\u200d♂️",
+    "man_mountain_biking_light_skin_tone": "🚵🏻\u200d♂️",
+    "man_mountain_biking_medium-dark_skin_tone": "🚵🏾\u200d♂️",
+    "man_mountain_biking_medium-light_skin_tone": "🚵🏼\u200d♂️",
+    "man_mountain_biking_medium_skin_tone": "🚵🏽\u200d♂️",
+    "man_office_worker": "👨\u200d💼",
+    "man_office_worker_dark_skin_tone": "👨🏿\u200d💼",
+    "man_office_worker_light_skin_tone": "👨🏻\u200d💼",
+    "man_office_worker_medium-dark_skin_tone": "👨🏾\u200d💼",
+    "man_office_worker_medium-light_skin_tone": "👨🏼\u200d💼",
+    "man_office_worker_medium_skin_tone": "👨🏽\u200d💼",
+    "man_pilot": "👨\u200d✈️",
+    "man_pilot_dark_skin_tone": "👨🏿\u200d✈️",
+    "man_pilot_light_skin_tone": "👨🏻\u200d✈️",
+    "man_pilot_medium-dark_skin_tone": "👨🏾\u200d✈️",
+    "man_pilot_medium-light_skin_tone": "👨🏼\u200d✈️",
+    "man_pilot_medium_skin_tone": "👨🏽\u200d✈️",
+    "man_playing_handball": "🤾\u200d♂️",
+    "man_playing_handball_dark_skin_tone": "🤾🏿\u200d♂️",
+    "man_playing_handball_light_skin_tone": "🤾🏻\u200d♂️",
+    "man_playing_handball_medium-dark_skin_tone": "🤾🏾\u200d♂️",
+    "man_playing_handball_medium-light_skin_tone": "🤾🏼\u200d♂️",
+    "man_playing_handball_medium_skin_tone": "🤾🏽\u200d♂️",
+    "man_playing_water_polo": "🤽\u200d♂️",
+    "man_playing_water_polo_dark_skin_tone": "🤽🏿\u200d♂️",
+    "man_playing_water_polo_light_skin_tone": "🤽🏻\u200d♂️",
+    "man_playing_water_polo_medium-dark_skin_tone": "🤽🏾\u200d♂️",
+    "man_playing_water_polo_medium-light_skin_tone": "🤽🏼\u200d♂️",
+    "man_playing_water_polo_medium_skin_tone": "🤽🏽\u200d♂️",
+    "man_police_officer": "👮\u200d♂️",
+    "man_police_officer_dark_skin_tone": "👮🏿\u200d♂️",
+    "man_police_officer_light_skin_tone": "👮🏻\u200d♂️",
+    "man_police_officer_medium-dark_skin_tone": "👮🏾\u200d♂️",
+    "man_police_officer_medium-light_skin_tone": "👮🏼\u200d♂️",
+    "man_police_officer_medium_skin_tone": "👮🏽\u200d♂️",
+    "man_pouting": "🙎\u200d♂️",
+    "man_pouting_dark_skin_tone": "🙎🏿\u200d♂️",
+    "man_pouting_light_skin_tone": "🙎🏻\u200d♂️",
+    "man_pouting_medium-dark_skin_tone": "🙎🏾\u200d♂️",
+    "man_pouting_medium-light_skin_tone": "🙎🏼\u200d♂️",
+    "man_pouting_medium_skin_tone": "🙎🏽\u200d♂️",
+    "man_raising_hand": "🙋\u200d♂️",
+    "man_raising_hand_dark_skin_tone": "🙋🏿\u200d♂️",
+    "man_raising_hand_light_skin_tone": "🙋🏻\u200d♂️",
+    "man_raising_hand_medium-dark_skin_tone": "🙋🏾\u200d♂️",
+    "man_raising_hand_medium-light_skin_tone": "🙋🏼\u200d♂️",
+    "man_raising_hand_medium_skin_tone": "🙋🏽\u200d♂️",
+    "man_rowing_boat": "🚣\u200d♂️",
+    "man_rowing_boat_dark_skin_tone": "🚣🏿\u200d♂️",
+    "man_rowing_boat_light_skin_tone": "🚣🏻\u200d♂️",
+    "man_rowing_boat_medium-dark_skin_tone": "🚣🏾\u200d♂️",
+    "man_rowing_boat_medium-light_skin_tone": "🚣🏼\u200d♂️",
+    "man_rowing_boat_medium_skin_tone": "🚣🏽\u200d♂️",
+    "man_running": "🏃\u200d♂️",
+    "man_running_dark_skin_tone": "🏃🏿\u200d♂️",
+    "man_running_light_skin_tone": "🏃🏻\u200d♂️",
+    "man_running_medium-dark_skin_tone": "🏃🏾\u200d♂️",
+    "man_running_medium-light_skin_tone": "🏃🏼\u200d♂️",
+    "man_running_medium_skin_tone": "🏃🏽\u200d♂️",
+    "man_scientist": "👨\u200d🔬",
+    "man_scientist_dark_skin_tone": "👨🏿\u200d🔬",
+    "man_scientist_light_skin_tone": "👨🏻\u200d🔬",
+    "man_scientist_medium-dark_skin_tone": "👨🏾\u200d🔬",
+    "man_scientist_medium-light_skin_tone": "👨🏼\u200d🔬",
+    "man_scientist_medium_skin_tone": "👨🏽\u200d🔬",
+    "man_shrugging": "🤷\u200d♂️",
+    "man_shrugging_dark_skin_tone": "🤷🏿\u200d♂️",
+    "man_shrugging_light_skin_tone": "🤷🏻\u200d♂️",
+    "man_shrugging_medium-dark_skin_tone": "🤷🏾\u200d♂️",
+    "man_shrugging_medium-light_skin_tone": "🤷🏼\u200d♂️",
+    "man_shrugging_medium_skin_tone": "🤷🏽\u200d♂️",
+    "man_singer": "👨\u200d🎤",
+    "man_singer_dark_skin_tone": "👨🏿\u200d🎤",
+    "man_singer_light_skin_tone": "👨🏻\u200d🎤",
+    "man_singer_medium-dark_skin_tone": "👨🏾\u200d🎤",
+    "man_singer_medium-light_skin_tone": "👨🏼\u200d🎤",
+    "man_singer_medium_skin_tone": "👨🏽\u200d🎤",
+    "man_student": "👨\u200d🎓",
+    "man_student_dark_skin_tone": "👨🏿\u200d🎓",
+    "man_student_light_skin_tone": "👨🏻\u200d🎓",
+    "man_student_medium-dark_skin_tone": "👨🏾\u200d🎓",
+    "man_student_medium-light_skin_tone": "👨🏼\u200d🎓",
+    "man_student_medium_skin_tone": "👨🏽\u200d🎓",
+    "man_surfing": "🏄\u200d♂️",
+    "man_surfing_dark_skin_tone": "🏄🏿\u200d♂️",
+    "man_surfing_light_skin_tone": "🏄🏻\u200d♂️",
+    "man_surfing_medium-dark_skin_tone": "🏄🏾\u200d♂️",
+    "man_surfing_medium-light_skin_tone": "🏄🏼\u200d♂️",
+    "man_surfing_medium_skin_tone": "🏄🏽\u200d♂️",
+    "man_swimming": "🏊\u200d♂️",
+    "man_swimming_dark_skin_tone": "🏊🏿\u200d♂️",
+    "man_swimming_light_skin_tone": "🏊🏻\u200d♂️",
+    "man_swimming_medium-dark_skin_tone": "🏊🏾\u200d♂️",
+    "man_swimming_medium-light_skin_tone": "🏊🏼\u200d♂️",
+    "man_swimming_medium_skin_tone": "🏊🏽\u200d♂️",
+    "man_teacher": "👨\u200d🏫",
+    "man_teacher_dark_skin_tone": "👨🏿\u200d🏫",
+    "man_teacher_light_skin_tone": "👨🏻\u200d🏫",
+    "man_teacher_medium-dark_skin_tone": "👨🏾\u200d🏫",
+    "man_teacher_medium-light_skin_tone": "👨🏼\u200d🏫",
+    "man_teacher_medium_skin_tone": "👨🏽\u200d🏫",
+    "man_technologist": "👨\u200d💻",
+    "man_technologist_dark_skin_tone": "👨🏿\u200d💻",
+    "man_technologist_light_skin_tone": "👨🏻\u200d💻",
+    "man_technologist_medium-dark_skin_tone": "👨🏾\u200d💻",
+    "man_technologist_medium-light_skin_tone": "👨🏼\u200d💻",
+    "man_technologist_medium_skin_tone": "👨🏽\u200d💻",
+    "man_tipping_hand": "💁\u200d♂️",
+    "man_tipping_hand_dark_skin_tone": "💁🏿\u200d♂️",
+    "man_tipping_hand_light_skin_tone": "💁🏻\u200d♂️",
+    "man_tipping_hand_medium-dark_skin_tone": "💁🏾\u200d♂️",
+    "man_tipping_hand_medium-light_skin_tone": "💁🏼\u200d♂️",
+    "man_tipping_hand_medium_skin_tone": "💁🏽\u200d♂️",
+    "man_vampire": "🧛\u200d♂️",
+    "man_vampire_dark_skin_tone": "🧛🏿\u200d♂️",
+    "man_vampire_light_skin_tone": "🧛🏻\u200d♂️",
+    "man_vampire_medium-dark_skin_tone": "🧛🏾\u200d♂️",
+    "man_vampire_medium-light_skin_tone": "🧛🏼\u200d♂️",
+    "man_vampire_medium_skin_tone": "🧛🏽\u200d♂️",
+    "man_walking": "🚶\u200d♂️",
+    "man_walking_dark_skin_tone": "🚶🏿\u200d♂️",
+    "man_walking_light_skin_tone": "🚶🏻\u200d♂️",
+    "man_walking_medium-dark_skin_tone": "🚶🏾\u200d♂️",
+    "man_walking_medium-light_skin_tone": "🚶🏼\u200d♂️",
+    "man_walking_medium_skin_tone": "🚶🏽\u200d♂️",
+    "man_wearing_turban": "👳\u200d♂️",
+    "man_wearing_turban_dark_skin_tone": "👳🏿\u200d♂️",
+    "man_wearing_turban_light_skin_tone": "👳🏻\u200d♂️",
+    "man_wearing_turban_medium-dark_skin_tone": "👳🏾\u200d♂️",
+    "man_wearing_turban_medium-light_skin_tone": "👳🏼\u200d♂️",
+    "man_wearing_turban_medium_skin_tone": "👳🏽\u200d♂️",
+    "man_with_probing_cane": "👨\u200d🦯",
+    "man_with_chinese_cap": "👲",
+    "man_with_chinese_cap_dark_skin_tone": "👲🏿",
+    "man_with_chinese_cap_light_skin_tone": "👲🏻",
+    "man_with_chinese_cap_medium-dark_skin_tone": "👲🏾",
+    "man_with_chinese_cap_medium-light_skin_tone": "👲🏼",
+    "man_with_chinese_cap_medium_skin_tone": "👲🏽",
+    "man_zombie": "🧟\u200d♂️",
+    "mango": "🥭",
+    "mantelpiece_clock": "🕰",
+    "manual_wheelchair": "🦽",
+    "man’s_shoe": "👞",
+    "map_of_japan": "🗾",
+    "maple_leaf": "🍁",
+    "martial_arts_uniform": "🥋",
+    "mate": "🧉",
+    "meat_on_bone": "🍖",
+    "mechanical_arm": "🦾",
+    "mechanical_leg": "🦿",
+    "medical_symbol": "⚕",
+    "megaphone": "📣",
+    "melon": "🍈",
+    "memo": "📝",
+    "men_with_bunny_ears": "👯\u200d♂️",
+    "men_wrestling": "🤼\u200d♂️",
+    "menorah": "🕎",
+    "men’s_room": "🚹",
+    "mermaid": "🧜\u200d♀️",
+    "mermaid_dark_skin_tone": "🧜🏿\u200d♀️",
+    "mermaid_light_skin_tone": "🧜🏻\u200d♀️",
+    "mermaid_medium-dark_skin_tone": "🧜🏾\u200d♀️",
+    "mermaid_medium-light_skin_tone": "🧜🏼\u200d♀️",
+    "mermaid_medium_skin_tone": "🧜🏽\u200d♀️",
+    "merman": "🧜\u200d♂️",
+    "merman_dark_skin_tone": "🧜🏿\u200d♂️",
+    "merman_light_skin_tone": "🧜🏻\u200d♂️",
+    "merman_medium-dark_skin_tone": "🧜🏾\u200d♂️",
+    "merman_medium-light_skin_tone": "🧜🏼\u200d♂️",
+    "merman_medium_skin_tone": "🧜🏽\u200d♂️",
+    "merperson": "🧜",
+    "merperson_dark_skin_tone": "🧜🏿",
+    "merperson_light_skin_tone": "🧜🏻",
+    "merperson_medium-dark_skin_tone": "🧜🏾",
+    "merperson_medium-light_skin_tone": "🧜🏼",
+    "merperson_medium_skin_tone": "🧜🏽",
+    "metro": "🚇",
+    "microbe": "🦠",
+    "microphone": "🎤",
+    "microscope": "🔬",
+    "middle_finger": "🖕",
+    "middle_finger_dark_skin_tone": "🖕🏿",
+    "middle_finger_light_skin_tone": "🖕🏻",
+    "middle_finger_medium-dark_skin_tone": "🖕🏾",
+    "middle_finger_medium-light_skin_tone": "🖕🏼",
+    "middle_finger_medium_skin_tone": "🖕🏽",
+    "military_medal": "🎖",
+    "milky_way": "🌌",
+    "minibus": "🚐",
+    "moai": "🗿",
+    "mobile_phone": "📱",
+    "mobile_phone_off": "📴",
+    "mobile_phone_with_arrow": "📲",
+    "money-mouth_face": "🤑",
+    "money_bag": "💰",
+    "money_with_wings": "💸",
+    "monkey": "🐒",
+    "monkey_face": "🐵",
+    "monorail": "🚝",
+    "moon_cake": "🥮",
+    "moon_viewing_ceremony": "🎑",
+    "mosque": "🕌",
+    "mosquito": "🦟",
+    "motor_boat": "🛥",
+    "motor_scooter": "🛵",
+    "motorcycle": "🏍",
+    "motorized_wheelchair": "🦼",
+    "motorway": "🛣",
+    "mount_fuji": "🗻",
+    "mountain": "⛰",
+    "mountain_cableway": "🚠",
+    "mountain_railway": "🚞",
+    "mouse": "🐭",
+    "mouse_face": "🐭",
+    "mouth": "👄",
+    "movie_camera": "🎥",
+    "mushroom": "🍄",
+    "musical_keyboard": "🎹",
+    "musical_note": "🎵",
+    "musical_notes": "🎶",
+    "musical_score": "🎼",
+    "muted_speaker": "🔇",
+    "nail_polish": "💅",
+    "nail_polish_dark_skin_tone": "💅🏿",
+    "nail_polish_light_skin_tone": "💅🏻",
+    "nail_polish_medium-dark_skin_tone": "💅🏾",
+    "nail_polish_medium-light_skin_tone": "💅🏼",
+    "nail_polish_medium_skin_tone": "💅🏽",
+    "name_badge": "📛",
+    "national_park": "🏞",
+    "nauseated_face": "🤢",
+    "nazar_amulet": "🧿",
+    "necktie": "👔",
+    "nerd_face": "🤓",
+    "neutral_face": "😐",
+    "new_moon": "🌑",
+    "new_moon_face": "🌚",
+    "newspaper": "📰",
+    "next_track_button": "⏭",
+    "night_with_stars": "🌃",
+    "nine-thirty": "🕤",
+    "nine_o’clock": "🕘",
+    "no_bicycles": "🚳",
+    "no_entry": "⛔",
+    "no_littering": "🚯",
+    "no_mobile_phones": "📵",
+    "no_one_under_eighteen": "🔞",
+    "no_pedestrians": "🚷",
+    "no_smoking": "🚭",
+    "non-potable_water": "🚱",
+    "nose": "👃",
+    "nose_dark_skin_tone": "👃🏿",
+    "nose_light_skin_tone": "👃🏻",
+    "nose_medium-dark_skin_tone": "👃🏾",
+    "nose_medium-light_skin_tone": "👃🏼",
+    "nose_medium_skin_tone": "👃🏽",
+    "notebook": "📓",
+    "notebook_with_decorative_cover": "📔",
+    "nut_and_bolt": "🔩",
+    "octopus": "🐙",
+    "oden": "🍢",
+    "office_building": "🏢",
+    "ogre": "👹",
+    "oil_drum": "🛢",
+    "old_key": "🗝",
+    "old_man": "👴",
+    "old_man_dark_skin_tone": "👴🏿",
+    "old_man_light_skin_tone": "👴🏻",
+    "old_man_medium-dark_skin_tone": "👴🏾",
+    "old_man_medium-light_skin_tone": "👴🏼",
+    "old_man_medium_skin_tone": "👴🏽",
+    "old_woman": "👵",
+    "old_woman_dark_skin_tone": "👵🏿",
+    "old_woman_light_skin_tone": "👵🏻",
+    "old_woman_medium-dark_skin_tone": "👵🏾",
+    "old_woman_medium-light_skin_tone": "👵🏼",
+    "old_woman_medium_skin_tone": "👵🏽",
+    "older_adult": "🧓",
+    "older_adult_dark_skin_tone": "🧓🏿",
+    "older_adult_light_skin_tone": "🧓🏻",
+    "older_adult_medium-dark_skin_tone": "🧓🏾",
+    "older_adult_medium-light_skin_tone": "🧓🏼",
+    "older_adult_medium_skin_tone": "🧓🏽",
+    "om": "🕉",
+    "oncoming_automobile": "🚘",
+    "oncoming_bus": "🚍",
+    "oncoming_fist": "👊",
+    "oncoming_fist_dark_skin_tone": "👊🏿",
+    "oncoming_fist_light_skin_tone": "👊🏻",
+    "oncoming_fist_medium-dark_skin_tone": "👊🏾",
+    "oncoming_fist_medium-light_skin_tone": "👊🏼",
+    "oncoming_fist_medium_skin_tone": "👊🏽",
+    "oncoming_police_car": "🚔",
+    "oncoming_taxi": "🚖",
+    "one-piece_swimsuit": "🩱",
+    "one-thirty": "🕜",
+    "one_o’clock": "🕐",
+    "onion": "🧅",
+    "open_book": "📖",
+    "open_file_folder": "📂",
+    "open_hands": "👐",
+    "open_hands_dark_skin_tone": "👐🏿",
+    "open_hands_light_skin_tone": "👐🏻",
+    "open_hands_medium-dark_skin_tone": "👐🏾",
+    "open_hands_medium-light_skin_tone": "👐🏼",
+    "open_hands_medium_skin_tone": "👐🏽",
+    "open_mailbox_with_lowered_flag": "📭",
+    "open_mailbox_with_raised_flag": "📬",
+    "optical_disk": "💿",
+    "orange_book": "📙",
+    "orange_circle": "🟠",
+    "orange_heart": "🧡",
+    "orange_square": "🟧",
+    "orangutan": "🦧",
+    "orthodox_cross": "☦",
+    "otter": "🦦",
+    "outbox_tray": "📤",
+    "owl": "🦉",
+    "ox": "🐂",
+    "oyster": "🦪",
+    "package": "📦",
+    "page_facing_up": "📄",
+    "page_with_curl": "📃",
+    "pager": "📟",
+    "paintbrush": "🖌",
+    "palm_tree": "🌴",
+    "palms_up_together": "🤲",
+    "palms_up_together_dark_skin_tone": "🤲🏿",
+    "palms_up_together_light_skin_tone": "🤲🏻",
+    "palms_up_together_medium-dark_skin_tone": "🤲🏾",
+    "palms_up_together_medium-light_skin_tone": "🤲🏼",
+    "palms_up_together_medium_skin_tone": "🤲🏽",
+    "pancakes": "🥞",
+    "panda_face": "🐼",
+    "paperclip": "📎",
+    "parrot": "🦜",
+    "part_alternation_mark": "〽",
+    "party_popper": "🎉",
+    "partying_face": "🥳",
+    "passenger_ship": "🛳",
+    "passport_control": "🛂",
+    "pause_button": "⏸",
+    "paw_prints": "🐾",
+    "peace_symbol": "☮",
+    "peach": "🍑",
+    "peacock": "🦚",
+    "peanuts": "🥜",
+    "pear": "🍐",
+    "pen": "🖊",
+    "pencil": "📝",
+    "penguin": "🐧",
+    "pensive_face": "😔",
+    "people_holding_hands": "🧑\u200d🤝\u200d🧑",
+    "people_with_bunny_ears": "👯",
+    "people_wrestling": "🤼",
+    "performing_arts": "🎭",
+    "persevering_face": "😣",
+    "person_biking": "🚴",
+    "person_biking_dark_skin_tone": "🚴🏿",
+    "person_biking_light_skin_tone": "🚴🏻",
+    "person_biking_medium-dark_skin_tone": "🚴🏾",
+    "person_biking_medium-light_skin_tone": "🚴🏼",
+    "person_biking_medium_skin_tone": "🚴🏽",
+    "person_bouncing_ball": "⛹",
+    "person_bouncing_ball_dark_skin_tone": "⛹🏿",
+    "person_bouncing_ball_light_skin_tone": "⛹🏻",
+    "person_bouncing_ball_medium-dark_skin_tone": "⛹🏾",
+    "person_bouncing_ball_medium-light_skin_tone": "⛹🏼",
+    "person_bouncing_ball_medium_skin_tone": "⛹🏽",
+    "person_bowing": "🙇",
+    "person_bowing_dark_skin_tone": "🙇🏿",
+    "person_bowing_light_skin_tone": "🙇🏻",
+    "person_bowing_medium-dark_skin_tone": "🙇🏾",
+    "person_bowing_medium-light_skin_tone": "🙇🏼",
+    "person_bowing_medium_skin_tone": "🙇🏽",
+    "person_cartwheeling": "🤸",
+    "person_cartwheeling_dark_skin_tone": "🤸🏿",
+    "person_cartwheeling_light_skin_tone": "🤸🏻",
+    "person_cartwheeling_medium-dark_skin_tone": "🤸🏾",
+    "person_cartwheeling_medium-light_skin_tone": "🤸🏼",
+    "person_cartwheeling_medium_skin_tone": "🤸🏽",
+    "person_climbing": "🧗",
+    "person_climbing_dark_skin_tone": "🧗🏿",
+    "person_climbing_light_skin_tone": "🧗🏻",
+    "person_climbing_medium-dark_skin_tone": "🧗🏾",
+    "person_climbing_medium-light_skin_tone": "🧗🏼",
+    "person_climbing_medium_skin_tone": "🧗🏽",
+    "person_facepalming": "🤦",
+    "person_facepalming_dark_skin_tone": "🤦🏿",
+    "person_facepalming_light_skin_tone": "🤦🏻",
+    "person_facepalming_medium-dark_skin_tone": "🤦🏾",
+    "person_facepalming_medium-light_skin_tone": "🤦🏼",
+    "person_facepalming_medium_skin_tone": "🤦🏽",
+    "person_fencing": "🤺",
+    "person_frowning": "🙍",
+    "person_frowning_dark_skin_tone": "🙍🏿",
+    "person_frowning_light_skin_tone": "🙍🏻",
+    "person_frowning_medium-dark_skin_tone": "🙍🏾",
+    "person_frowning_medium-light_skin_tone": "🙍🏼",
+    "person_frowning_medium_skin_tone": "🙍🏽",
+    "person_gesturing_no": "🙅",
+    "person_gesturing_no_dark_skin_tone": "🙅🏿",
+    "person_gesturing_no_light_skin_tone": "🙅🏻",
+    "person_gesturing_no_medium-dark_skin_tone": "🙅🏾",
+    "person_gesturing_no_medium-light_skin_tone": "🙅🏼",
+    "person_gesturing_no_medium_skin_tone": "🙅🏽",
+    "person_gesturing_ok": "🙆",
+    "person_gesturing_ok_dark_skin_tone": "🙆🏿",
+    "person_gesturing_ok_light_skin_tone": "🙆🏻",
+    "person_gesturing_ok_medium-dark_skin_tone": "🙆🏾",
+    "person_gesturing_ok_medium-light_skin_tone": "🙆🏼",
+    "person_gesturing_ok_medium_skin_tone": "🙆🏽",
+    "person_getting_haircut": "💇",
+    "person_getting_haircut_dark_skin_tone": "💇🏿",
+    "person_getting_haircut_light_skin_tone": "💇🏻",
+    "person_getting_haircut_medium-dark_skin_tone": "💇🏾",
+    "person_getting_haircut_medium-light_skin_tone": "💇🏼",
+    "person_getting_haircut_medium_skin_tone": "💇🏽",
+    "person_getting_massage": "💆",
+    "person_getting_massage_dark_skin_tone": "💆🏿",
+    "person_getting_massage_light_skin_tone": "💆🏻",
+    "person_getting_massage_medium-dark_skin_tone": "💆🏾",
+    "person_getting_massage_medium-light_skin_tone": "💆🏼",
+    "person_getting_massage_medium_skin_tone": "💆🏽",
+    "person_golfing": "🏌",
+    "person_golfing_dark_skin_tone": "🏌🏿",
+    "person_golfing_light_skin_tone": "🏌🏻",
+    "person_golfing_medium-dark_skin_tone": "🏌🏾",
+    "person_golfing_medium-light_skin_tone": "🏌🏼",
+    "person_golfing_medium_skin_tone": "🏌🏽",
+    "person_in_bed": "🛌",
+    "person_in_bed_dark_skin_tone": "🛌🏿",
+    "person_in_bed_light_skin_tone": "🛌🏻",
+    "person_in_bed_medium-dark_skin_tone": "🛌🏾",
+    "person_in_bed_medium-light_skin_tone": "🛌🏼",
+    "person_in_bed_medium_skin_tone": "🛌🏽",
+    "person_in_lotus_position": "🧘",
+    "person_in_lotus_position_dark_skin_tone": "🧘🏿",
+    "person_in_lotus_position_light_skin_tone": "🧘🏻",
+    "person_in_lotus_position_medium-dark_skin_tone": "🧘🏾",
+    "person_in_lotus_position_medium-light_skin_tone": "🧘🏼",
+    "person_in_lotus_position_medium_skin_tone": "🧘🏽",
+    "person_in_steamy_room": "🧖",
+    "person_in_steamy_room_dark_skin_tone": "🧖🏿",
+    "person_in_steamy_room_light_skin_tone": "🧖🏻",
+    "person_in_steamy_room_medium-dark_skin_tone": "🧖🏾",
+    "person_in_steamy_room_medium-light_skin_tone": "🧖🏼",
+    "person_in_steamy_room_medium_skin_tone": "🧖🏽",
+    "person_juggling": "🤹",
+    "person_juggling_dark_skin_tone": "🤹🏿",
+    "person_juggling_light_skin_tone": "🤹🏻",
+    "person_juggling_medium-dark_skin_tone": "🤹🏾",
+    "person_juggling_medium-light_skin_tone": "🤹🏼",
+    "person_juggling_medium_skin_tone": "🤹🏽",
+    "person_kneeling": "🧎",
+    "person_lifting_weights": "🏋",
+    "person_lifting_weights_dark_skin_tone": "🏋🏿",
+    "person_lifting_weights_light_skin_tone": "🏋🏻",
+    "person_lifting_weights_medium-dark_skin_tone": "🏋🏾",
+    "person_lifting_weights_medium-light_skin_tone": "🏋🏼",
+    "person_lifting_weights_medium_skin_tone": "🏋🏽",
+    "person_mountain_biking": "🚵",
+    "person_mountain_biking_dark_skin_tone": "🚵🏿",
+    "person_mountain_biking_light_skin_tone": "🚵🏻",
+    "person_mountain_biking_medium-dark_skin_tone": "🚵🏾",
+    "person_mountain_biking_medium-light_skin_tone": "🚵🏼",
+    "person_mountain_biking_medium_skin_tone": "🚵🏽",
+    "person_playing_handball": "🤾",
+    "person_playing_handball_dark_skin_tone": "🤾🏿",
+    "person_playing_handball_light_skin_tone": "🤾🏻",
+    "person_playing_handball_medium-dark_skin_tone": "🤾🏾",
+    "person_playing_handball_medium-light_skin_tone": "🤾🏼",
+    "person_playing_handball_medium_skin_tone": "🤾🏽",
+    "person_playing_water_polo": "🤽",
+    "person_playing_water_polo_dark_skin_tone": "🤽🏿",
+    "person_playing_water_polo_light_skin_tone": "🤽🏻",
+    "person_playing_water_polo_medium-dark_skin_tone": "🤽🏾",
+    "person_playing_water_polo_medium-light_skin_tone": "🤽🏼",
+    "person_playing_water_polo_medium_skin_tone": "🤽🏽",
+    "person_pouting": "🙎",
+    "person_pouting_dark_skin_tone": "🙎🏿",
+    "person_pouting_light_skin_tone": "🙎🏻",
+    "person_pouting_medium-dark_skin_tone": "🙎🏾",
+    "person_pouting_medium-light_skin_tone": "🙎🏼",
+    "person_pouting_medium_skin_tone": "🙎🏽",
+    "person_raising_hand": "🙋",
+    "person_raising_hand_dark_skin_tone": "🙋🏿",
+    "person_raising_hand_light_skin_tone": "🙋🏻",
+    "person_raising_hand_medium-dark_skin_tone": "🙋🏾",
+    "person_raising_hand_medium-light_skin_tone": "🙋🏼",
+    "person_raising_hand_medium_skin_tone": "🙋🏽",
+    "person_rowing_boat": "🚣",
+    "person_rowing_boat_dark_skin_tone": "🚣🏿",
+    "person_rowing_boat_light_skin_tone": "🚣🏻",
+    "person_rowing_boat_medium-dark_skin_tone": "🚣🏾",
+    "person_rowing_boat_medium-light_skin_tone": "🚣🏼",
+    "person_rowing_boat_medium_skin_tone": "🚣🏽",
+    "person_running": "🏃",
+    "person_running_dark_skin_tone": "🏃🏿",
+    "person_running_light_skin_tone": "🏃🏻",
+    "person_running_medium-dark_skin_tone": "🏃🏾",
+    "person_running_medium-light_skin_tone": "🏃🏼",
+    "person_running_medium_skin_tone": "🏃🏽",
+    "person_shrugging": "🤷",
+    "person_shrugging_dark_skin_tone": "🤷🏿",
+    "person_shrugging_light_skin_tone": "🤷🏻",
+    "person_shrugging_medium-dark_skin_tone": "🤷🏾",
+    "person_shrugging_medium-light_skin_tone": "🤷🏼",
+    "person_shrugging_medium_skin_tone": "🤷🏽",
+    "person_standing": "🧍",
+    "person_surfing": "🏄",
+    "person_surfing_dark_skin_tone": "🏄🏿",
+    "person_surfing_light_skin_tone": "🏄🏻",
+    "person_surfing_medium-dark_skin_tone": "🏄🏾",
+    "person_surfing_medium-light_skin_tone": "🏄🏼",
+    "person_surfing_medium_skin_tone": "🏄🏽",
+    "person_swimming": "🏊",
+    "person_swimming_dark_skin_tone": "🏊🏿",
+    "person_swimming_light_skin_tone": "🏊🏻",
+    "person_swimming_medium-dark_skin_tone": "🏊🏾",
+    "person_swimming_medium-light_skin_tone": "🏊🏼",
+    "person_swimming_medium_skin_tone": "🏊🏽",
+    "person_taking_bath": "🛀",
+    "person_taking_bath_dark_skin_tone": "🛀🏿",
+    "person_taking_bath_light_skin_tone": "🛀🏻",
+    "person_taking_bath_medium-dark_skin_tone": "🛀🏾",
+    "person_taking_bath_medium-light_skin_tone": "🛀🏼",
+    "person_taking_bath_medium_skin_tone": "🛀🏽",
+    "person_tipping_hand": "💁",
+    "person_tipping_hand_dark_skin_tone": "💁🏿",
+    "person_tipping_hand_light_skin_tone": "💁🏻",
+    "person_tipping_hand_medium-dark_skin_tone": "💁🏾",
+    "person_tipping_hand_medium-light_skin_tone": "💁🏼",
+    "person_tipping_hand_medium_skin_tone": "💁🏽",
+    "person_walking": "🚶",
+    "person_walking_dark_skin_tone": "🚶🏿",
+    "person_walking_light_skin_tone": "🚶🏻",
+    "person_walking_medium-dark_skin_tone": "🚶🏾",
+    "person_walking_medium-light_skin_tone": "🚶🏼",
+    "person_walking_medium_skin_tone": "🚶🏽",
+    "person_wearing_turban": "👳",
+    "person_wearing_turban_dark_skin_tone": "👳🏿",
+    "person_wearing_turban_light_skin_tone": "👳🏻",
+    "person_wearing_turban_medium-dark_skin_tone": "👳🏾",
+    "person_wearing_turban_medium-light_skin_tone": "👳🏼",
+    "person_wearing_turban_medium_skin_tone": "👳🏽",
+    "petri_dish": "🧫",
+    "pick": "⛏",
+    "pie": "🥧",
+    "pig": "🐷",
+    "pig_face": "🐷",
+    "pig_nose": "🐽",
+    "pile_of_poo": "💩",
+    "pill": "💊",
+    "pinching_hand": "🤏",
+    "pine_decoration": "🎍",
+    "pineapple": "🍍",
+    "ping_pong": "🏓",
+    "pirate_flag": "🏴\u200d☠️",
+    "pistol": "🔫",
+    "pizza": "🍕",
+    "place_of_worship": "🛐",
+    "play_button": "▶",
+    "play_or_pause_button": "⏯",
+    "pleading_face": "🥺",
+    "police_car": "🚓",
+    "police_car_light": "🚨",
+    "police_officer": "👮",
+    "police_officer_dark_skin_tone": "👮🏿",
+    "police_officer_light_skin_tone": "👮🏻",
+    "police_officer_medium-dark_skin_tone": "👮🏾",
+    "police_officer_medium-light_skin_tone": "👮🏼",
+    "police_officer_medium_skin_tone": "👮🏽",
+    "poodle": "🐩",
+    "pool_8_ball": "🎱",
+    "popcorn": "🍿",
+    "post_office": "🏣",
+    "postal_horn": "📯",
+    "postbox": "📮",
+    "pot_of_food": "🍲",
+    "potable_water": "🚰",
+    "potato": "🥔",
+    "poultry_leg": "🍗",
+    "pound_banknote": "💷",
+    "pouting_cat_face": "😾",
+    "pouting_face": "😡",
+    "prayer_beads": "📿",
+    "pregnant_woman": "🤰",
+    "pregnant_woman_dark_skin_tone": "🤰🏿",
+    "pregnant_woman_light_skin_tone": "🤰🏻",
+    "pregnant_woman_medium-dark_skin_tone": "🤰🏾",
+    "pregnant_woman_medium-light_skin_tone": "🤰🏼",
+    "pregnant_woman_medium_skin_tone": "🤰🏽",
+    "pretzel": "🥨",
+    "probing_cane": "🦯",
+    "prince": "🤴",
+    "prince_dark_skin_tone": "🤴🏿",
+    "prince_light_skin_tone": "🤴🏻",
+    "prince_medium-dark_skin_tone": "🤴🏾",
+    "prince_medium-light_skin_tone": "🤴🏼",
+    "prince_medium_skin_tone": "🤴🏽",
+    "princess": "👸",
+    "princess_dark_skin_tone": "👸🏿",
+    "princess_light_skin_tone": "👸🏻",
+    "princess_medium-dark_skin_tone": "👸🏾",
+    "princess_medium-light_skin_tone": "👸🏼",
+    "princess_medium_skin_tone": "👸🏽",
+    "printer": "🖨",
+    "prohibited": "🚫",
+    "purple_circle": "🟣",
+    "purple_heart": "💜",
+    "purple_square": "🟪",
+    "purse": "👛",
+    "pushpin": "📌",
+    "question_mark": "❓",
+    "rabbit": "🐰",
+    "rabbit_face": "🐰",
+    "raccoon": "🦝",
+    "racing_car": "🏎",
+    "radio": "📻",
+    "radio_button": "🔘",
+    "radioactive": "☢",
+    "railway_car": "🚃",
+    "railway_track": "🛤",
+    "rainbow": "🌈",
+    "rainbow_flag": "🏳️\u200d🌈",
+    "raised_back_of_hand": "🤚",
+    "raised_back_of_hand_dark_skin_tone": "🤚🏿",
+    "raised_back_of_hand_light_skin_tone": "🤚🏻",
+    "raised_back_of_hand_medium-dark_skin_tone": "🤚🏾",
+    "raised_back_of_hand_medium-light_skin_tone": "🤚🏼",
+    "raised_back_of_hand_medium_skin_tone": "🤚🏽",
+    "raised_fist": "✊",
+    "raised_fist_dark_skin_tone": "✊🏿",
+    "raised_fist_light_skin_tone": "✊🏻",
+    "raised_fist_medium-dark_skin_tone": "✊🏾",
+    "raised_fist_medium-light_skin_tone": "✊🏼",
+    "raised_fist_medium_skin_tone": "✊🏽",
+    "raised_hand": "✋",
+    "raised_hand_dark_skin_tone": "✋🏿",
+    "raised_hand_light_skin_tone": "✋🏻",
+    "raised_hand_medium-dark_skin_tone": "✋🏾",
+    "raised_hand_medium-light_skin_tone": "✋🏼",
+    "raised_hand_medium_skin_tone": "✋🏽",
+    "raising_hands": "🙌",
+    "raising_hands_dark_skin_tone": "🙌🏿",
+    "raising_hands_light_skin_tone": "🙌🏻",
+    "raising_hands_medium-dark_skin_tone": "🙌🏾",
+    "raising_hands_medium-light_skin_tone": "🙌🏼",
+    "raising_hands_medium_skin_tone": "🙌🏽",
+    "ram": "🐏",
+    "rat": "🐀",
+    "razor": "🪒",
+    "ringed_planet": "🪐",
+    "receipt": "🧾",
+    "record_button": "⏺",
+    "recycling_symbol": "♻",
+    "red_apple": "🍎",
+    "red_circle": "🔴",
+    "red_envelope": "🧧",
+    "red_hair": "🦰",
+    "red-haired_man": "👨\u200d🦰",
+    "red-haired_woman": "👩\u200d🦰",
+    "red_heart": "❤",
+    "red_paper_lantern": "🏮",
+    "red_square": "🟥",
+    "red_triangle_pointed_down": "🔻",
+    "red_triangle_pointed_up": "🔺",
+    "registered": "®",
+    "relieved_face": "😌",
+    "reminder_ribbon": "🎗",
+    "repeat_button": "🔁",
+    "repeat_single_button": "🔂",
+    "rescue_worker’s_helmet": "⛑",
+    "restroom": "🚻",
+    "reverse_button": "◀",
+    "revolving_hearts": "💞",
+    "rhinoceros": "🦏",
+    "ribbon": "🎀",
+    "rice_ball": "🍙",
+    "rice_cracker": "🍘",
+    "right-facing_fist": "🤜",
+    "right-facing_fist_dark_skin_tone": "🤜🏿",
+    "right-facing_fist_light_skin_tone": "🤜🏻",
+    "right-facing_fist_medium-dark_skin_tone": "🤜🏾",
+    "right-facing_fist_medium-light_skin_tone": "🤜🏼",
+    "right-facing_fist_medium_skin_tone": "🤜🏽",
+    "right_anger_bubble": "🗯",
+    "right_arrow": "➡",
+    "right_arrow_curving_down": "⤵",
+    "right_arrow_curving_left": "↩",
+    "right_arrow_curving_up": "⤴",
+    "ring": "💍",
+    "roasted_sweet_potato": "🍠",
+    "robot_face": "🤖",
+    "rocket": "🚀",
+    "roll_of_paper": "🧻",
+    "rolled-up_newspaper": "🗞",
+    "roller_coaster": "🎢",
+    "rolling_on_the_floor_laughing": "🤣",
+    "rooster": "🐓",
+    "rose": "🌹",
+    "rosette": "🏵",
+    "round_pushpin": "📍",
+    "rugby_football": "🏉",
+    "running_shirt": "🎽",
+    "running_shoe": "👟",
+    "sad_but_relieved_face": "😥",
+    "safety_pin": "🧷",
+    "safety_vest": "🦺",
+    "salt": "🧂",
+    "sailboat": "⛵",
+    "sake": "🍶",
+    "sandwich": "🥪",
+    "sari": "🥻",
+    "satellite": "📡",
+    "satellite_antenna": "📡",
+    "sauropod": "🦕",
+    "saxophone": "🎷",
+    "scarf": "🧣",
+    "school": "🏫",
+    "school_backpack": "🎒",
+    "scissors": "✂",
+    "scorpion": "🦂",
+    "scroll": "📜",
+    "seat": "💺",
+    "see-no-evil_monkey": "🙈",
+    "seedling": "🌱",
+    "selfie": "🤳",
+    "selfie_dark_skin_tone": "🤳🏿",
+    "selfie_light_skin_tone": "🤳🏻",
+    "selfie_medium-dark_skin_tone": "🤳🏾",
+    "selfie_medium-light_skin_tone": "🤳🏼",
+    "selfie_medium_skin_tone": "🤳🏽",
+    "service_dog": "🐕\u200d🦺",
+    "seven-thirty": "🕢",
+    "seven_o’clock": "🕖",
+    "shallow_pan_of_food": "🥘",
+    "shamrock": "☘",
+    "shark": "🦈",
+    "shaved_ice": "🍧",
+    "sheaf_of_rice": "🌾",
+    "shield": "🛡",
+    "shinto_shrine": "⛩",
+    "ship": "🚢",
+    "shooting_star": "🌠",
+    "shopping_bags": "🛍",
+    "shopping_cart": "🛒",
+    "shortcake": "🍰",
+    "shorts": "🩳",
+    "shower": "🚿",
+    "shrimp": "🦐",
+    "shuffle_tracks_button": "🔀",
+    "shushing_face": "🤫",
+    "sign_of_the_horns": "🤘",
+    "sign_of_the_horns_dark_skin_tone": "🤘🏿",
+    "sign_of_the_horns_light_skin_tone": "🤘🏻",
+    "sign_of_the_horns_medium-dark_skin_tone": "🤘🏾",
+    "sign_of_the_horns_medium-light_skin_tone": "🤘🏼",
+    "sign_of_the_horns_medium_skin_tone": "🤘🏽",
+    "six-thirty": "🕡",
+    "six_o’clock": "🕕",
+    "skateboard": "🛹",
+    "skier": "⛷",
+    "skis": "🎿",
+    "skull": "💀",
+    "skull_and_crossbones": "☠",
+    "skunk": "🦨",
+    "sled": "🛷",
+    "sleeping_face": "😴",
+    "sleepy_face": "😪",
+    "slightly_frowning_face": "🙁",
+    "slightly_smiling_face": "🙂",
+    "slot_machine": "🎰",
+    "sloth": "🦥",
+    "small_airplane": "🛩",
+    "small_blue_diamond": "🔹",
+    "small_orange_diamond": "🔸",
+    "smiling_cat_face_with_heart-eyes": "😻",
+    "smiling_face": "☺",
+    "smiling_face_with_halo": "😇",
+    "smiling_face_with_3_hearts": "🥰",
+    "smiling_face_with_heart-eyes": "😍",
+    "smiling_face_with_horns": "😈",
+    "smiling_face_with_smiling_eyes": "😊",
+    "smiling_face_with_sunglasses": "😎",
+    "smirking_face": "😏",
+    "snail": "🐌",
+    "snake": "🐍",
+    "sneezing_face": "🤧",
+    "snow-capped_mountain": "🏔",
+    "snowboarder": "🏂",
+    "snowboarder_dark_skin_tone": "🏂🏿",
+    "snowboarder_light_skin_tone": "🏂🏻",
+    "snowboarder_medium-dark_skin_tone": "🏂🏾",
+    "snowboarder_medium-light_skin_tone": "🏂🏼",
+    "snowboarder_medium_skin_tone": "🏂🏽",
+    "snowflake": "❄",
+    "snowman": "☃",
+    "snowman_without_snow": "⛄",
+    "soap": "🧼",
+    "soccer_ball": "⚽",
+    "socks": "🧦",
+    "softball": "🥎",
+    "soft_ice_cream": "🍦",
+    "spade_suit": "♠",
+    "spaghetti": "🍝",
+    "sparkle": "❇",
+    "sparkler": "🎇",
+    "sparkles": "✨",
+    "sparkling_heart": "💖",
+    "speak-no-evil_monkey": "🙊",
+    "speaker_high_volume": "🔊",
+    "speaker_low_volume": "🔈",
+    "speaker_medium_volume": "🔉",
+    "speaking_head": "🗣",
+    "speech_balloon": "💬",
+    "speedboat": "🚤",
+    "spider": "🕷",
+    "spider_web": "🕸",
+    "spiral_calendar": "🗓",
+    "spiral_notepad": "🗒",
+    "spiral_shell": "🐚",
+    "spoon": "🥄",
+    "sponge": "🧽",
+    "sport_utility_vehicle": "🚙",
+    "sports_medal": "🏅",
+    "spouting_whale": "🐳",
+    "squid": "🦑",
+    "squinting_face_with_tongue": "😝",
+    "stadium": "🏟",
+    "star-struck": "🤩",
+    "star_and_crescent": "☪",
+    "star_of_david": "✡",
+    "station": "🚉",
+    "steaming_bowl": "🍜",
+    "stethoscope": "🩺",
+    "stop_button": "⏹",
+    "stop_sign": "🛑",
+    "stopwatch": "⏱",
+    "straight_ruler": "📏",
+    "strawberry": "🍓",
+    "studio_microphone": "🎙",
+    "stuffed_flatbread": "🥙",
+    "sun": "☀",
+    "sun_behind_cloud": "⛅",
+    "sun_behind_large_cloud": "🌥",
+    "sun_behind_rain_cloud": "🌦",
+    "sun_behind_small_cloud": "🌤",
+    "sun_with_face": "🌞",
+    "sunflower": "🌻",
+    "sunglasses": "😎",
+    "sunrise": "🌅",
+    "sunrise_over_mountains": "🌄",
+    "sunset": "🌇",
+    "superhero": "🦸",
+    "supervillain": "🦹",
+    "sushi": "🍣",
+    "suspension_railway": "🚟",
+    "swan": "🦢",
+    "sweat_droplets": "💦",
+    "synagogue": "🕍",
+    "syringe": "💉",
+    "t-shirt": "👕",
+    "taco": "🌮",
+    "takeout_box": "🥡",
+    "tanabata_tree": "🎋",
+    "tangerine": "🍊",
+    "taxi": "🚕",
+    "teacup_without_handle": "🍵",
+    "tear-off_calendar": "📆",
+    "teddy_bear": "🧸",
+    "telephone": "☎",
+    "telephone_receiver": "📞",
+    "telescope": "🔭",
+    "television": "📺",
+    "ten-thirty": "🕥",
+    "ten_o’clock": "🕙",
+    "tennis": "🎾",
+    "tent": "⛺",
+    "test_tube": "🧪",
+    "thermometer": "🌡",
+    "thinking_face": "🤔",
+    "thought_balloon": "💭",
+    "thread": "🧵",
+    "three-thirty": "🕞",
+    "three_o’clock": "🕒",
+    "thumbs_down": "👎",
+    "thumbs_down_dark_skin_tone": "👎🏿",
+    "thumbs_down_light_skin_tone": "👎🏻",
+    "thumbs_down_medium-dark_skin_tone": "👎🏾",
+    "thumbs_down_medium-light_skin_tone": "👎🏼",
+    "thumbs_down_medium_skin_tone": "👎🏽",
+    "thumbs_up": "👍",
+    "thumbs_up_dark_skin_tone": "👍🏿",
+    "thumbs_up_light_skin_tone": "👍🏻",
+    "thumbs_up_medium-dark_skin_tone": "👍🏾",
+    "thumbs_up_medium-light_skin_tone": "👍🏼",
+    "thumbs_up_medium_skin_tone": "👍🏽",
+    "ticket": "🎫",
+    "tiger": "🐯",
+    "tiger_face": "🐯",
+    "timer_clock": "⏲",
+    "tired_face": "😫",
+    "toolbox": "🧰",
+    "toilet": "🚽",
+    "tomato": "🍅",
+    "tongue": "👅",
+    "tooth": "🦷",
+    "top_hat": "🎩",
+    "tornado": "🌪",
+    "trackball": "🖲",
+    "tractor": "🚜",
+    "trade_mark": "™",
+    "train": "🚋",
+    "tram": "🚊",
+    "tram_car": "🚋",
+    "triangular_flag": "🚩",
+    "triangular_ruler": "📐",
+    "trident_emblem": "🔱",
+    "trolleybus": "🚎",
+    "trophy": "🏆",
+    "tropical_drink": "🍹",
+    "tropical_fish": "🐠",
+    "trumpet": "🎺",
+    "tulip": "🌷",
+    "tumbler_glass": "🥃",
+    "turtle": "🐢",
+    "twelve-thirty": "🕧",
+    "twelve_o’clock": "🕛",
+    "two-hump_camel": "🐫",
+    "two-thirty": "🕝",
+    "two_hearts": "💕",
+    "two_men_holding_hands": "👬",
+    "two_o’clock": "🕑",
+    "two_women_holding_hands": "👭",
+    "umbrella": "☂",
+    "umbrella_on_ground": "⛱",
+    "umbrella_with_rain_drops": "☔",
+    "unamused_face": "😒",
+    "unicorn_face": "🦄",
+    "unlocked": "🔓",
+    "up-down_arrow": "↕",
+    "up-left_arrow": "↖",
+    "up-right_arrow": "↗",
+    "up_arrow": "⬆",
+    "upside-down_face": "🙃",
+    "upwards_button": "🔼",
+    "vampire": "🧛",
+    "vampire_dark_skin_tone": "🧛🏿",
+    "vampire_light_skin_tone": "🧛🏻",
+    "vampire_medium-dark_skin_tone": "🧛🏾",
+    "vampire_medium-light_skin_tone": "🧛🏼",
+    "vampire_medium_skin_tone": "🧛🏽",
+    "vertical_traffic_light": "🚦",
+    "vibration_mode": "📳",
+    "victory_hand": "✌",
+    "victory_hand_dark_skin_tone": "✌🏿",
+    "victory_hand_light_skin_tone": "✌🏻",
+    "victory_hand_medium-dark_skin_tone": "✌🏾",
+    "victory_hand_medium-light_skin_tone": "✌🏼",
+    "victory_hand_medium_skin_tone": "✌🏽",
+    "video_camera": "📹",
+    "video_game": "🎮",
+    "videocassette": "📼",
+    "violin": "🎻",
+    "volcano": "🌋",
+    "volleyball": "🏐",
+    "vulcan_salute": "🖖",
+    "vulcan_salute_dark_skin_tone": "🖖🏿",
+    "vulcan_salute_light_skin_tone": "🖖🏻",
+    "vulcan_salute_medium-dark_skin_tone": "🖖🏾",
+    "vulcan_salute_medium-light_skin_tone": "🖖🏼",
+    "vulcan_salute_medium_skin_tone": "🖖🏽",
+    "waffle": "🧇",
+    "waning_crescent_moon": "🌘",
+    "waning_gibbous_moon": "🌖",
+    "warning": "⚠",
+    "wastebasket": "🗑",
+    "watch": "⌚",
+    "water_buffalo": "🐃",
+    "water_closet": "🚾",
+    "water_wave": "🌊",
+    "watermelon": "🍉",
+    "waving_hand": "👋",
+    "waving_hand_dark_skin_tone": "👋🏿",
+    "waving_hand_light_skin_tone": "👋🏻",
+    "waving_hand_medium-dark_skin_tone": "👋🏾",
+    "waving_hand_medium-light_skin_tone": "👋🏼",
+    "waving_hand_medium_skin_tone": "👋🏽",
+    "wavy_dash": "〰",
+    "waxing_crescent_moon": "🌒",
+    "waxing_gibbous_moon": "🌔",
+    "weary_cat_face": "🙀",
+    "weary_face": "😩",
+    "wedding": "💒",
+    "whale": "🐳",
+    "wheel_of_dharma": "☸",
+    "wheelchair_symbol": "♿",
+    "white_circle": "⚪",
+    "white_exclamation_mark": "❕",
+    "white_flag": "🏳",
+    "white_flower": "💮",
+    "white_hair": "🦳",
+    "white-haired_man": "👨\u200d🦳",
+    "white-haired_woman": "👩\u200d🦳",
+    "white_heart": "🤍",
+    "white_heavy_check_mark": "✅",
+    "white_large_square": "⬜",
+    "white_medium-small_square": "◽",
+    "white_medium_square": "◻",
+    "white_medium_star": "⭐",
+    "white_question_mark": "❔",
+    "white_small_square": "▫",
+    "white_square_button": "🔳",
+    "wilted_flower": "🥀",
+    "wind_chime": "🎐",
+    "wind_face": "🌬",
+    "wine_glass": "🍷",
+    "winking_face": "😉",
+    "winking_face_with_tongue": "😜",
+    "wolf_face": "🐺",
+    "woman": "👩",
+    "woman_artist": "👩\u200d🎨",
+    "woman_artist_dark_skin_tone": "👩🏿\u200d🎨",
+    "woman_artist_light_skin_tone": "👩🏻\u200d🎨",
+    "woman_artist_medium-dark_skin_tone": "👩🏾\u200d🎨",
+    "woman_artist_medium-light_skin_tone": "👩🏼\u200d🎨",
+    "woman_artist_medium_skin_tone": "👩🏽\u200d🎨",
+    "woman_astronaut": "👩\u200d🚀",
+    "woman_astronaut_dark_skin_tone": "👩🏿\u200d🚀",
+    "woman_astronaut_light_skin_tone": "👩🏻\u200d🚀",
+    "woman_astronaut_medium-dark_skin_tone": "👩🏾\u200d🚀",
+    "woman_astronaut_medium-light_skin_tone": "👩🏼\u200d🚀",
+    "woman_astronaut_medium_skin_tone": "👩🏽\u200d🚀",
+    "woman_biking": "🚴\u200d♀️",
+    "woman_biking_dark_skin_tone": "🚴🏿\u200d♀️",
+    "woman_biking_light_skin_tone": "🚴🏻\u200d♀️",
+    "woman_biking_medium-dark_skin_tone": "🚴🏾\u200d♀️",
+    "woman_biking_medium-light_skin_tone": "🚴🏼\u200d♀️",
+    "woman_biking_medium_skin_tone": "🚴🏽\u200d♀️",
+    "woman_bouncing_ball": "⛹️\u200d♀️",
+    "woman_bouncing_ball_dark_skin_tone": "⛹🏿\u200d♀️",
+    "woman_bouncing_ball_light_skin_tone": "⛹🏻\u200d♀️",
+    "woman_bouncing_ball_medium-dark_skin_tone": "⛹🏾\u200d♀️",
+    "woman_bouncing_ball_medium-light_skin_tone": "⛹🏼\u200d♀️",
+    "woman_bouncing_ball_medium_skin_tone": "⛹🏽\u200d♀️",
+    "woman_bowing": "🙇\u200d♀️",
+    "woman_bowing_dark_skin_tone": "🙇🏿\u200d♀️",
+    "woman_bowing_light_skin_tone": "🙇🏻\u200d♀️",
+    "woman_bowing_medium-dark_skin_tone": "🙇🏾\u200d♀️",
+    "woman_bowing_medium-light_skin_tone": "🙇🏼\u200d♀️",
+    "woman_bowing_medium_skin_tone": "🙇🏽\u200d♀️",
+    "woman_cartwheeling": "🤸\u200d♀️",
+    "woman_cartwheeling_dark_skin_tone": "🤸🏿\u200d♀️",
+    "woman_cartwheeling_light_skin_tone": "🤸🏻\u200d♀️",
+    "woman_cartwheeling_medium-dark_skin_tone": "🤸🏾\u200d♀️",
+    "woman_cartwheeling_medium-light_skin_tone": "🤸🏼\u200d♀️",
+    "woman_cartwheeling_medium_skin_tone": "🤸🏽\u200d♀️",
+    "woman_climbing": "🧗\u200d♀️",
+    "woman_climbing_dark_skin_tone": "🧗🏿\u200d♀️",
+    "woman_climbing_light_skin_tone": "🧗🏻\u200d♀️",
+    "woman_climbing_medium-dark_skin_tone": "🧗🏾\u200d♀️",
+    "woman_climbing_medium-light_skin_tone": "🧗🏼\u200d♀️",
+    "woman_climbing_medium_skin_tone": "🧗🏽\u200d♀️",
+    "woman_construction_worker": "👷\u200d♀️",
+    "woman_construction_worker_dark_skin_tone": "👷🏿\u200d♀️",
+    "woman_construction_worker_light_skin_tone": "👷🏻\u200d♀️",
+    "woman_construction_worker_medium-dark_skin_tone": "👷🏾\u200d♀️",
+    "woman_construction_worker_medium-light_skin_tone": "👷🏼\u200d♀️",
+    "woman_construction_worker_medium_skin_tone": "👷🏽\u200d♀️",
+    "woman_cook": "👩\u200d🍳",
+    "woman_cook_dark_skin_tone": "👩🏿\u200d🍳",
+    "woman_cook_light_skin_tone": "👩🏻\u200d🍳",
+    "woman_cook_medium-dark_skin_tone": "👩🏾\u200d🍳",
+    "woman_cook_medium-light_skin_tone": "👩🏼\u200d🍳",
+    "woman_cook_medium_skin_tone": "👩🏽\u200d🍳",
+    "woman_dancing": "💃",
+    "woman_dancing_dark_skin_tone": "💃🏿",
+    "woman_dancing_light_skin_tone": "💃🏻",
+    "woman_dancing_medium-dark_skin_tone": "💃🏾",
+    "woman_dancing_medium-light_skin_tone": "💃🏼",
+    "woman_dancing_medium_skin_tone": "💃🏽",
+    "woman_dark_skin_tone": "👩🏿",
+    "woman_detective": "🕵️\u200d♀️",
+    "woman_detective_dark_skin_tone": "🕵🏿\u200d♀️",
+    "woman_detective_light_skin_tone": "🕵🏻\u200d♀️",
+    "woman_detective_medium-dark_skin_tone": "🕵🏾\u200d♀️",
+    "woman_detective_medium-light_skin_tone": "🕵🏼\u200d♀️",
+    "woman_detective_medium_skin_tone": "🕵🏽\u200d♀️",
+    "woman_elf": "🧝\u200d♀️",
+    "woman_elf_dark_skin_tone": "🧝🏿\u200d♀️",
+    "woman_elf_light_skin_tone": "🧝🏻\u200d♀️",
+    "woman_elf_medium-dark_skin_tone": "🧝🏾\u200d♀️",
+    "woman_elf_medium-light_skin_tone": "🧝🏼\u200d♀️",
+    "woman_elf_medium_skin_tone": "🧝🏽\u200d♀️",
+    "woman_facepalming": "🤦\u200d♀️",
+    "woman_facepalming_dark_skin_tone": "🤦🏿\u200d♀️",
+    "woman_facepalming_light_skin_tone": "🤦🏻\u200d♀️",
+    "woman_facepalming_medium-dark_skin_tone": "🤦🏾\u200d♀️",
+    "woman_facepalming_medium-light_skin_tone": "🤦🏼\u200d♀️",
+    "woman_facepalming_medium_skin_tone": "🤦🏽\u200d♀️",
+    "woman_factory_worker": "👩\u200d🏭",
+    "woman_factory_worker_dark_skin_tone": "👩🏿\u200d🏭",
+    "woman_factory_worker_light_skin_tone": "👩🏻\u200d🏭",
+    "woman_factory_worker_medium-dark_skin_tone": "👩🏾\u200d🏭",
+    "woman_factory_worker_medium-light_skin_tone": "👩🏼\u200d🏭",
+    "woman_factory_worker_medium_skin_tone": "👩🏽\u200d🏭",
+    "woman_fairy": "🧚\u200d♀️",
+    "woman_fairy_dark_skin_tone": "🧚🏿\u200d♀️",
+    "woman_fairy_light_skin_tone": "🧚🏻\u200d♀️",
+    "woman_fairy_medium-dark_skin_tone": "🧚🏾\u200d♀️",
+    "woman_fairy_medium-light_skin_tone": "🧚🏼\u200d♀️",
+    "woman_fairy_medium_skin_tone": "🧚🏽\u200d♀️",
+    "woman_farmer": "👩\u200d🌾",
+    "woman_farmer_dark_skin_tone": "👩🏿\u200d🌾",
+    "woman_farmer_light_skin_tone": "👩🏻\u200d🌾",
+    "woman_farmer_medium-dark_skin_tone": "👩🏾\u200d🌾",
+    "woman_farmer_medium-light_skin_tone": "👩🏼\u200d🌾",
+    "woman_farmer_medium_skin_tone": "👩🏽\u200d🌾",
+    "woman_firefighter": "👩\u200d🚒",
+    "woman_firefighter_dark_skin_tone": "👩🏿\u200d🚒",
+    "woman_firefighter_light_skin_tone": "👩🏻\u200d🚒",
+    "woman_firefighter_medium-dark_skin_tone": "👩🏾\u200d🚒",
+    "woman_firefighter_medium-light_skin_tone": "👩🏼\u200d🚒",
+    "woman_firefighter_medium_skin_tone": "👩🏽\u200d🚒",
+    "woman_frowning": "🙍\u200d♀️",
+    "woman_frowning_dark_skin_tone": "🙍🏿\u200d♀️",
+    "woman_frowning_light_skin_tone": "🙍🏻\u200d♀️",
+    "woman_frowning_medium-dark_skin_tone": "🙍🏾\u200d♀️",
+    "woman_frowning_medium-light_skin_tone": "🙍🏼\u200d♀️",
+    "woman_frowning_medium_skin_tone": "🙍🏽\u200d♀️",
+    "woman_genie": "🧞\u200d♀️",
+    "woman_gesturing_no": "🙅\u200d♀️",
+    "woman_gesturing_no_dark_skin_tone": "🙅🏿\u200d♀️",
+    "woman_gesturing_no_light_skin_tone": "🙅🏻\u200d♀️",
+    "woman_gesturing_no_medium-dark_skin_tone": "🙅🏾\u200d♀️",
+    "woman_gesturing_no_medium-light_skin_tone": "🙅🏼\u200d♀️",
+    "woman_gesturing_no_medium_skin_tone": "🙅🏽\u200d♀️",
+    "woman_gesturing_ok": "🙆\u200d♀️",
+    "woman_gesturing_ok_dark_skin_tone": "🙆🏿\u200d♀️",
+    "woman_gesturing_ok_light_skin_tone": "🙆🏻\u200d♀️",
+    "woman_gesturing_ok_medium-dark_skin_tone": "🙆🏾\u200d♀️",
+    "woman_gesturing_ok_medium-light_skin_tone": "🙆🏼\u200d♀️",
+    "woman_gesturing_ok_medium_skin_tone": "🙆🏽\u200d♀️",
+    "woman_getting_haircut": "💇\u200d♀️",
+    "woman_getting_haircut_dark_skin_tone": "💇🏿\u200d♀️",
+    "woman_getting_haircut_light_skin_tone": "💇🏻\u200d♀️",
+    "woman_getting_haircut_medium-dark_skin_tone": "💇🏾\u200d♀️",
+    "woman_getting_haircut_medium-light_skin_tone": "💇🏼\u200d♀️",
+    "woman_getting_haircut_medium_skin_tone": "💇🏽\u200d♀️",
+    "woman_getting_massage": "💆\u200d♀️",
+    "woman_getting_massage_dark_skin_tone": "💆🏿\u200d♀️",
+    "woman_getting_massage_light_skin_tone": "💆🏻\u200d♀️",
+    "woman_getting_massage_medium-dark_skin_tone": "💆🏾\u200d♀️",
+    "woman_getting_massage_medium-light_skin_tone": "💆🏼\u200d♀️",
+    "woman_getting_massage_medium_skin_tone": "💆🏽\u200d♀️",
+    "woman_golfing": "🏌️\u200d♀️",
+    "woman_golfing_dark_skin_tone": "🏌🏿\u200d♀️",
+    "woman_golfing_light_skin_tone": "🏌🏻\u200d♀️",
+    "woman_golfing_medium-dark_skin_tone": "🏌🏾\u200d♀️",
+    "woman_golfing_medium-light_skin_tone": "🏌🏼\u200d♀️",
+    "woman_golfing_medium_skin_tone": "🏌🏽\u200d♀️",
+    "woman_guard": "💂\u200d♀️",
+    "woman_guard_dark_skin_tone": "💂🏿\u200d♀️",
+    "woman_guard_light_skin_tone": "💂🏻\u200d♀️",
+    "woman_guard_medium-dark_skin_tone": "💂🏾\u200d♀️",
+    "woman_guard_medium-light_skin_tone": "💂🏼\u200d♀️",
+    "woman_guard_medium_skin_tone": "💂🏽\u200d♀️",
+    "woman_health_worker": "👩\u200d⚕️",
+    "woman_health_worker_dark_skin_tone": "👩🏿\u200d⚕️",
+    "woman_health_worker_light_skin_tone": "👩🏻\u200d⚕️",
+    "woman_health_worker_medium-dark_skin_tone": "👩🏾\u200d⚕️",
+    "woman_health_worker_medium-light_skin_tone": "👩🏼\u200d⚕️",
+    "woman_health_worker_medium_skin_tone": "👩🏽\u200d⚕️",
+    "woman_in_lotus_position": "🧘\u200d♀️",
+    "woman_in_lotus_position_dark_skin_tone": "🧘🏿\u200d♀️",
+    "woman_in_lotus_position_light_skin_tone": "🧘🏻\u200d♀️",
+    "woman_in_lotus_position_medium-dark_skin_tone": "🧘🏾\u200d♀️",
+    "woman_in_lotus_position_medium-light_skin_tone": "🧘🏼\u200d♀️",
+    "woman_in_lotus_position_medium_skin_tone": "🧘🏽\u200d♀️",
+    "woman_in_manual_wheelchair": "👩\u200d🦽",
+    "woman_in_motorized_wheelchair": "👩\u200d🦼",
+    "woman_in_steamy_room": "🧖\u200d♀️",
+    "woman_in_steamy_room_dark_skin_tone": "🧖🏿\u200d♀️",
+    "woman_in_steamy_room_light_skin_tone": "🧖🏻\u200d♀️",
+    "woman_in_steamy_room_medium-dark_skin_tone": "🧖🏾\u200d♀️",
+    "woman_in_steamy_room_medium-light_skin_tone": "🧖🏼\u200d♀️",
+    "woman_in_steamy_room_medium_skin_tone": "🧖🏽\u200d♀️",
+    "woman_judge": "👩\u200d⚖️",
+    "woman_judge_dark_skin_tone": "👩🏿\u200d⚖️",
+    "woman_judge_light_skin_tone": "👩🏻\u200d⚖️",
+    "woman_judge_medium-dark_skin_tone": "👩🏾\u200d⚖️",
+    "woman_judge_medium-light_skin_tone": "👩🏼\u200d⚖️",
+    "woman_judge_medium_skin_tone": "👩🏽\u200d⚖️",
+    "woman_juggling": "🤹\u200d♀️",
+    "woman_juggling_dark_skin_tone": "🤹🏿\u200d♀️",
+    "woman_juggling_light_skin_tone": "🤹🏻\u200d♀️",
+    "woman_juggling_medium-dark_skin_tone": "🤹🏾\u200d♀️",
+    "woman_juggling_medium-light_skin_tone": "🤹🏼\u200d♀️",
+    "woman_juggling_medium_skin_tone": "🤹🏽\u200d♀️",
+    "woman_lifting_weights": "🏋️\u200d♀️",
+    "woman_lifting_weights_dark_skin_tone": "🏋🏿\u200d♀️",
+    "woman_lifting_weights_light_skin_tone": "🏋🏻\u200d♀️",
+    "woman_lifting_weights_medium-dark_skin_tone": "🏋🏾\u200d♀️",
+    "woman_lifting_weights_medium-light_skin_tone": "🏋🏼\u200d♀️",
+    "woman_lifting_weights_medium_skin_tone": "🏋🏽\u200d♀️",
+    "woman_light_skin_tone": "👩🏻",
+    "woman_mage": "🧙\u200d♀️",
+    "woman_mage_dark_skin_tone": "🧙🏿\u200d♀️",
+    "woman_mage_light_skin_tone": "🧙🏻\u200d♀️",
+    "woman_mage_medium-dark_skin_tone": "🧙🏾\u200d♀️",
+    "woman_mage_medium-light_skin_tone": "🧙🏼\u200d♀️",
+    "woman_mage_medium_skin_tone": "🧙🏽\u200d♀️",
+    "woman_mechanic": "👩\u200d🔧",
+    "woman_mechanic_dark_skin_tone": "👩🏿\u200d🔧",
+    "woman_mechanic_light_skin_tone": "👩🏻\u200d🔧",
+    "woman_mechanic_medium-dark_skin_tone": "👩🏾\u200d🔧",
+    "woman_mechanic_medium-light_skin_tone": "👩🏼\u200d🔧",
+    "woman_mechanic_medium_skin_tone": "👩🏽\u200d🔧",
+    "woman_medium-dark_skin_tone": "👩🏾",
+    "woman_medium-light_skin_tone": "👩🏼",
+    "woman_medium_skin_tone": "👩🏽",
+    "woman_mountain_biking": "🚵\u200d♀️",
+    "woman_mountain_biking_dark_skin_tone": "🚵🏿\u200d♀️",
+    "woman_mountain_biking_light_skin_tone": "🚵🏻\u200d♀️",
+    "woman_mountain_biking_medium-dark_skin_tone": "🚵🏾\u200d♀️",
+    "woman_mountain_biking_medium-light_skin_tone": "🚵🏼\u200d♀️",
+    "woman_mountain_biking_medium_skin_tone": "🚵🏽\u200d♀️",
+    "woman_office_worker": "👩\u200d💼",
+    "woman_office_worker_dark_skin_tone": "👩🏿\u200d💼",
+    "woman_office_worker_light_skin_tone": "👩🏻\u200d💼",
+    "woman_office_worker_medium-dark_skin_tone": "👩🏾\u200d💼",
+    "woman_office_worker_medium-light_skin_tone": "👩🏼\u200d💼",
+    "woman_office_worker_medium_skin_tone": "👩🏽\u200d💼",
+    "woman_pilot": "👩\u200d✈️",
+    "woman_pilot_dark_skin_tone": "👩🏿\u200d✈️",
+    "woman_pilot_light_skin_tone": "👩🏻\u200d✈️",
+    "woman_pilot_medium-dark_skin_tone": "👩🏾\u200d✈️",
+    "woman_pilot_medium-light_skin_tone": "👩🏼\u200d✈️",
+    "woman_pilot_medium_skin_tone": "👩🏽\u200d✈️",
+    "woman_playing_handball": "🤾\u200d♀️",
+    "woman_playing_handball_dark_skin_tone": "🤾🏿\u200d♀️",
+    "woman_playing_handball_light_skin_tone": "🤾🏻\u200d♀️",
+    "woman_playing_handball_medium-dark_skin_tone": "🤾🏾\u200d♀️",
+    "woman_playing_handball_medium-light_skin_tone": "🤾🏼\u200d♀️",
+    "woman_playing_handball_medium_skin_tone": "🤾🏽\u200d♀️",
+    "woman_playing_water_polo": "🤽\u200d♀️",
+    "woman_playing_water_polo_dark_skin_tone": "🤽🏿\u200d♀️",
+    "woman_playing_water_polo_light_skin_tone": "🤽🏻\u200d♀️",
+    "woman_playing_water_polo_medium-dark_skin_tone": "🤽🏾\u200d♀️",
+    "woman_playing_water_polo_medium-light_skin_tone": "🤽🏼\u200d♀️",
+    "woman_playing_water_polo_medium_skin_tone": "🤽🏽\u200d♀️",
+    "woman_police_officer": "👮\u200d♀️",
+    "woman_police_officer_dark_skin_tone": "👮🏿\u200d♀️",
+    "woman_police_officer_light_skin_tone": "👮🏻\u200d♀️",
+    "woman_police_officer_medium-dark_skin_tone": "👮🏾\u200d♀️",
+    "woman_police_officer_medium-light_skin_tone": "👮🏼\u200d♀️",
+    "woman_police_officer_medium_skin_tone": "👮🏽\u200d♀️",
+    "woman_pouting": "🙎\u200d♀️",
+    "woman_pouting_dark_skin_tone": "🙎🏿\u200d♀️",
+    "woman_pouting_light_skin_tone": "🙎🏻\u200d♀️",
+    "woman_pouting_medium-dark_skin_tone": "🙎🏾\u200d♀️",
+    "woman_pouting_medium-light_skin_tone": "🙎🏼\u200d♀️",
+    "woman_pouting_medium_skin_tone": "🙎🏽\u200d♀️",
+    "woman_raising_hand": "🙋\u200d♀️",
+    "woman_raising_hand_dark_skin_tone": "🙋🏿\u200d♀️",
+    "woman_raising_hand_light_skin_tone": "🙋🏻\u200d♀️",
+    "woman_raising_hand_medium-dark_skin_tone": "🙋🏾\u200d♀️",
+    "woman_raising_hand_medium-light_skin_tone": "🙋🏼\u200d♀️",
+    "woman_raising_hand_medium_skin_tone": "🙋🏽\u200d♀️",
+    "woman_rowing_boat": "🚣\u200d♀️",
+    "woman_rowing_boat_dark_skin_tone": "🚣🏿\u200d♀️",
+    "woman_rowing_boat_light_skin_tone": "🚣🏻\u200d♀️",
+    "woman_rowing_boat_medium-dark_skin_tone": "🚣🏾\u200d♀️",
+    "woman_rowing_boat_medium-light_skin_tone": "🚣🏼\u200d♀️",
+    "woman_rowing_boat_medium_skin_tone": "🚣🏽\u200d♀️",
+    "woman_running": "🏃\u200d♀️",
+    "woman_running_dark_skin_tone": "🏃🏿\u200d♀️",
+    "woman_running_light_skin_tone": "🏃🏻\u200d♀️",
+    "woman_running_medium-dark_skin_tone": "🏃🏾\u200d♀️",
+    "woman_running_medium-light_skin_tone": "🏃🏼\u200d♀️",
+    "woman_running_medium_skin_tone": "🏃🏽\u200d♀️",
+    "woman_scientist": "👩\u200d🔬",
+    "woman_scientist_dark_skin_tone": "👩🏿\u200d🔬",
+    "woman_scientist_light_skin_tone": "👩🏻\u200d🔬",
+    "woman_scientist_medium-dark_skin_tone": "👩🏾\u200d🔬",
+    "woman_scientist_medium-light_skin_tone": "👩🏼\u200d🔬",
+    "woman_scientist_medium_skin_tone": "👩🏽\u200d🔬",
+    "woman_shrugging": "🤷\u200d♀️",
+    "woman_shrugging_dark_skin_tone": "🤷🏿\u200d♀️",
+    "woman_shrugging_light_skin_tone": "🤷🏻\u200d♀️",
+    "woman_shrugging_medium-dark_skin_tone": "🤷🏾\u200d♀️",
+    "woman_shrugging_medium-light_skin_tone": "🤷🏼\u200d♀️",
+    "woman_shrugging_medium_skin_tone": "🤷🏽\u200d♀️",
+    "woman_singer": "👩\u200d🎤",
+    "woman_singer_dark_skin_tone": "👩🏿\u200d🎤",
+    "woman_singer_light_skin_tone": "👩🏻\u200d🎤",
+    "woman_singer_medium-dark_skin_tone": "👩🏾\u200d🎤",
+    "woman_singer_medium-light_skin_tone": "👩🏼\u200d🎤",
+    "woman_singer_medium_skin_tone": "👩🏽\u200d🎤",
+    "woman_student": "👩\u200d🎓",
+    "woman_student_dark_skin_tone": "👩🏿\u200d🎓",
+    "woman_student_light_skin_tone": "👩🏻\u200d🎓",
+    "woman_student_medium-dark_skin_tone": "👩🏾\u200d🎓",
+    "woman_student_medium-light_skin_tone": "👩🏼\u200d🎓",
+    "woman_student_medium_skin_tone": "👩🏽\u200d🎓",
+    "woman_surfing": "🏄\u200d♀️",
+    "woman_surfing_dark_skin_tone": "🏄🏿\u200d♀️",
+    "woman_surfing_light_skin_tone": "🏄🏻\u200d♀️",
+    "woman_surfing_medium-dark_skin_tone": "🏄🏾\u200d♀️",
+    "woman_surfing_medium-light_skin_tone": "🏄🏼\u200d♀️",
+    "woman_surfing_medium_skin_tone": "🏄🏽\u200d♀️",
+    "woman_swimming": "🏊\u200d♀️",
+    "woman_swimming_dark_skin_tone": "🏊🏿\u200d♀️",
+    "woman_swimming_light_skin_tone": "🏊🏻\u200d♀️",
+    "woman_swimming_medium-dark_skin_tone": "🏊🏾\u200d♀️",
+    "woman_swimming_medium-light_skin_tone": "🏊🏼\u200d♀️",
+    "woman_swimming_medium_skin_tone": "🏊🏽\u200d♀️",
+    "woman_teacher": "👩\u200d🏫",
+    "woman_teacher_dark_skin_tone": "👩🏿\u200d🏫",
+    "woman_teacher_light_skin_tone": "👩🏻\u200d🏫",
+    "woman_teacher_medium-dark_skin_tone": "👩🏾\u200d🏫",
+    "woman_teacher_medium-light_skin_tone": "👩🏼\u200d🏫",
+    "woman_teacher_medium_skin_tone": "👩🏽\u200d🏫",
+    "woman_technologist": "👩\u200d💻",
+    "woman_technologist_dark_skin_tone": "👩🏿\u200d💻",
+    "woman_technologist_light_skin_tone": "👩🏻\u200d💻",
+    "woman_technologist_medium-dark_skin_tone": "👩🏾\u200d💻",
+    "woman_technologist_medium-light_skin_tone": "👩🏼\u200d💻",
+    "woman_technologist_medium_skin_tone": "👩🏽\u200d💻",
+    "woman_tipping_hand": "💁\u200d♀️",
+    "woman_tipping_hand_dark_skin_tone": "💁🏿\u200d♀️",
+    "woman_tipping_hand_light_skin_tone": "💁🏻\u200d♀️",
+    "woman_tipping_hand_medium-dark_skin_tone": "💁🏾\u200d♀️",
+    "woman_tipping_hand_medium-light_skin_tone": "💁🏼\u200d♀️",
+    "woman_tipping_hand_medium_skin_tone": "💁🏽\u200d♀️",
+    "woman_vampire": "🧛\u200d♀️",
+    "woman_vampire_dark_skin_tone": "🧛🏿\u200d♀️",
+    "woman_vampire_light_skin_tone": "🧛🏻\u200d♀️",
+    "woman_vampire_medium-dark_skin_tone": "🧛🏾\u200d♀️",
+    "woman_vampire_medium-light_skin_tone": "🧛🏼\u200d♀️",
+    "woman_vampire_medium_skin_tone": "🧛🏽\u200d♀️",
+    "woman_walking": "🚶\u200d♀️",
+    "woman_walking_dark_skin_tone": "🚶🏿\u200d♀️",
+    "woman_walking_light_skin_tone": "🚶🏻\u200d♀️",
+    "woman_walking_medium-dark_skin_tone": "🚶🏾\u200d♀️",
+    "woman_walking_medium-light_skin_tone": "🚶🏼\u200d♀️",
+    "woman_walking_medium_skin_tone": "🚶🏽\u200d♀️",
+    "woman_wearing_turban": "👳\u200d♀️",
+    "woman_wearing_turban_dark_skin_tone": "👳🏿\u200d♀️",
+    "woman_wearing_turban_light_skin_tone": "👳🏻\u200d♀️",
+    "woman_wearing_turban_medium-dark_skin_tone": "👳🏾\u200d♀️",
+    "woman_wearing_turban_medium-light_skin_tone": "👳🏼\u200d♀️",
+    "woman_wearing_turban_medium_skin_tone": "👳🏽\u200d♀️",
+    "woman_with_headscarf": "🧕",
+    "woman_with_headscarf_dark_skin_tone": "🧕🏿",
+    "woman_with_headscarf_light_skin_tone": "🧕🏻",
+    "woman_with_headscarf_medium-dark_skin_tone": "🧕🏾",
+    "woman_with_headscarf_medium-light_skin_tone": "🧕🏼",
+    "woman_with_headscarf_medium_skin_tone": "🧕🏽",
+    "woman_with_probing_cane": "👩\u200d🦯",
+    "woman_zombie": "🧟\u200d♀️",
+    "woman’s_boot": "👢",
+    "woman’s_clothes": "👚",
+    "woman’s_hat": "👒",
+    "woman’s_sandal": "👡",
+    "women_with_bunny_ears": "👯\u200d♀️",
+    "women_wrestling": "🤼\u200d♀️",
+    "women’s_room": "🚺",
+    "woozy_face": "🥴",
+    "world_map": "🗺",
+    "worried_face": "😟",
+    "wrapped_gift": "🎁",
+    "wrench": "🔧",
+    "writing_hand": "✍",
+    "writing_hand_dark_skin_tone": "✍🏿",
+    "writing_hand_light_skin_tone": "✍🏻",
+    "writing_hand_medium-dark_skin_tone": "✍🏾",
+    "writing_hand_medium-light_skin_tone": "✍🏼",
+    "writing_hand_medium_skin_tone": "✍🏽",
+    "yarn": "🧶",
+    "yawning_face": "🥱",
+    "yellow_circle": "🟡",
+    "yellow_heart": "💛",
+    "yellow_square": "🟨",
+    "yen_banknote": "💴",
+    "yo-yo": "🪀",
+    "yin_yang": "☯",
+    "zany_face": "🤪",
+    "zebra": "🦓",
+    "zipper-mouth_face": "🤐",
+    "zombie": "🧟",
+    "zzz": "💤",
+    "åland_islands": "🇦🇽",
+    "keycap_asterisk": "*⃣",
+    "keycap_digit_eight": "8⃣",
+    "keycap_digit_five": "5⃣",
+    "keycap_digit_four": "4⃣",
+    "keycap_digit_nine": "9⃣",
+    "keycap_digit_one": "1⃣",
+    "keycap_digit_seven": "7⃣",
+    "keycap_digit_six": "6⃣",
+    "keycap_digit_three": "3⃣",
+    "keycap_digit_two": "2⃣",
+    "keycap_digit_zero": "0⃣",
+    "keycap_number_sign": "#⃣",
+    "light_skin_tone": "🏻",
+    "medium_light_skin_tone": "🏼",
+    "medium_skin_tone": "🏽",
+    "medium_dark_skin_tone": "🏾",
+    "dark_skin_tone": "🏿",
+    "regional_indicator_symbol_letter_a": "🇦",
+    "regional_indicator_symbol_letter_b": "🇧",
+    "regional_indicator_symbol_letter_c": "🇨",
+    "regional_indicator_symbol_letter_d": "🇩",
+    "regional_indicator_symbol_letter_e": "🇪",
+    "regional_indicator_symbol_letter_f": "🇫",
+    "regional_indicator_symbol_letter_g": "🇬",
+    "regional_indicator_symbol_letter_h": "🇭",
+    "regional_indicator_symbol_letter_i": "🇮",
+    "regional_indicator_symbol_letter_j": "🇯",
+    "regional_indicator_symbol_letter_k": "🇰",
+    "regional_indicator_symbol_letter_l": "🇱",
+    "regional_indicator_symbol_letter_m": "🇲",
+    "regional_indicator_symbol_letter_n": "🇳",
+    "regional_indicator_symbol_letter_o": "🇴",
+    "regional_indicator_symbol_letter_p": "🇵",
+    "regional_indicator_symbol_letter_q": "🇶",
+    "regional_indicator_symbol_letter_r": "🇷",
+    "regional_indicator_symbol_letter_s": "🇸",
+    "regional_indicator_symbol_letter_t": "🇹",
+    "regional_indicator_symbol_letter_u": "🇺",
+    "regional_indicator_symbol_letter_v": "🇻",
+    "regional_indicator_symbol_letter_w": "🇼",
+    "regional_indicator_symbol_letter_x": "🇽",
+    "regional_indicator_symbol_letter_y": "🇾",
+    "regional_indicator_symbol_letter_z": "🇿",
+    "airplane_arriving": "🛬",
+    "space_invader": "👾",
+    "football": "🏈",
+    "anger": "💢",
+    "angry": "😠",
+    "anguished": "😧",
+    "signal_strength": "📶",
+    "arrows_counterclockwise": "🔄",
+    "arrow_heading_down": "⤵",
+    "arrow_heading_up": "⤴",
+    "art": "🎨",
+    "astonished": "😲",
+    "athletic_shoe": "👟",
+    "atm": "🏧",
+    "car": "🚗",
+    "red_car": "🚗",
+    "angel": "👼",
+    "back": "🔙",
+    "badminton_racquet_and_shuttlecock": "🏸",
+    "dollar": "💵",
+    "euro": "💶",
+    "pound": "💷",
+    "yen": "💴",
+    "barber": "💈",
+    "bath": "🛀",
+    "bear": "🐻",
+    "heartbeat": "💓",
+    "beer": "🍺",
+    "no_bell": "🔕",
+    "bento": "🍱",
+    "bike": "🚲",
+    "bicyclist": "🚴",
+    "8ball": "🎱",
+    "biohazard_sign": "☣",
+    "birthday": "🎂",
+    "black_circle_for_record": "⏺",
+    "clubs": "♣",
+    "diamonds": "♦",
+    "arrow_double_down": "⏬",
+    "hearts": "♥",
+    "rewind": "⏪",
+    "black_left__pointing_double_triangle_with_vertical_bar": "⏮",
+    "arrow_backward": "◀",
+    "black_medium_small_square": "◾",
+    "question": "❓",
+    "fast_forward": "⏩",
+    "black_right__pointing_double_triangle_with_vertical_bar": "⏭",
+    "arrow_forward": "▶",
+    "black_right__pointing_triangle_with_double_vertical_bar": "⏯",
+    "arrow_right": "➡",
+    "spades": "♠",
+    "black_square_for_stop": "⏹",
+    "sunny": "☀",
+    "phone": "☎",
+    "recycle": "♻",
+    "arrow_double_up": "⏫",
+    "busstop": "🚏",
+    "date": "📅",
+    "flags": "🎏",
+    "cat2": "🐈",
+    "joy_cat": "😹",
+    "smirk_cat": "😼",
+    "chart_with_downwards_trend": "📉",
+    "chart_with_upwards_trend": "📈",
+    "chart": "💹",
+    "mega": "📣",
+    "checkered_flag": "🏁",
+    "accept": "🉑",
+    "ideograph_advantage": "🉐",
+    "congratulations": "㊗",
+    "secret": "㊙",
+    "m": "Ⓜ",
+    "city_sunset": "🌆",
+    "clapper": "🎬",
+    "clap": "👏",
+    "beers": "🍻",
+    "clock830": "🕣",
+    "clock8": "🕗",
+    "clock1130": "🕦",
+    "clock11": "🕚",
+    "clock530": "🕠",
+    "clock5": "🕔",
+    "clock430": "🕟",
+    "clock4": "🕓",
+    "clock930": "🕤",
+    "clock9": "🕘",
+    "clock130": "🕜",
+    "clock1": "🕐",
+    "clock730": "🕢",
+    "clock7": "🕖",
+    "clock630": "🕡",
+    "clock6": "🕕",
+    "clock1030": "🕥",
+    "clock10": "🕙",
+    "clock330": "🕞",
+    "clock3": "🕒",
+    "clock1230": "🕧",
+    "clock12": "🕛",
+    "clock230": "🕝",
+    "clock2": "🕑",
+    "arrows_clockwise": "🔃",
+    "repeat": "🔁",
+    "repeat_one": "🔂",
+    "closed_lock_with_key": "🔐",
+    "mailbox_closed": "📪",
+    "mailbox": "📫",
+    "cloud_with_tornado": "🌪",
+    "cocktail": "🍸",
+    "boom": "💥",
+    "compression": "🗜",
+    "confounded": "😖",
+    "confused": "😕",
+    "rice": "🍚",
+    "cow2": "🐄",
+    "cricket_bat_and_ball": "🏏",
+    "x": "❌",
+    "cry": "😢",
+    "curry": "🍛",
+    "dagger_knife": "🗡",
+    "dancer": "💃",
+    "dark_sunglasses": "🕶",
+    "dash": "💨",
+    "truck": "🚚",
+    "derelict_house_building": "🏚",
+    "diamond_shape_with_a_dot_inside": "💠",
+    "dart": "🎯",
+    "disappointed_relieved": "😥",
+    "disappointed": "😞",
+    "do_not_litter": "🚯",
+    "dog2": "🐕",
+    "flipper": "🐬",
+    "loop": "➿",
+    "bangbang": "‼",
+    "double_vertical_bar": "⏸",
+    "dove_of_peace": "🕊",
+    "small_red_triangle_down": "🔻",
+    "arrow_down_small": "🔽",
+    "arrow_down": "⬇",
+    "dromedary_camel": "🐪",
+    "e__mail": "📧",
+    "corn": "🌽",
+    "ear_of_rice": "🌾",
+    "earth_americas": "🌎",
+    "earth_asia": "🌏",
+    "earth_africa": "🌍",
+    "eight_pointed_black_star": "✴",
+    "eight_spoked_asterisk": "✳",
+    "eject_symbol": "⏏",
+    "bulb": "💡",
+    "emoji_modifier_fitzpatrick_type__1__2": "🏻",
+    "emoji_modifier_fitzpatrick_type__3": "🏼",
+    "emoji_modifier_fitzpatrick_type__4": "🏽",
+    "emoji_modifier_fitzpatrick_type__5": "🏾",
+    "emoji_modifier_fitzpatrick_type__6": "🏿",
+    "end": "🔚",
+    "email": "✉",
+    "european_castle": "🏰",
+    "european_post_office": "🏤",
+    "interrobang": "⁉",
+    "expressionless": "😑",
+    "eyeglasses": "👓",
+    "massage": "💆",
+    "yum": "😋",
+    "scream": "😱",
+    "kissing_heart": "😘",
+    "sweat": "😓",
+    "face_with_head__bandage": "🤕",
+    "triumph": "😤",
+    "mask": "😷",
+    "no_good": "🙅",
+    "ok_woman": "🙆",
+    "open_mouth": "😮",
+    "cold_sweat": "😰",
+    "stuck_out_tongue": "😛",
+    "stuck_out_tongue_closed_eyes": "😝",
+    "stuck_out_tongue_winking_eye": "😜",
+    "joy": "😂",
+    "no_mouth": "😶",
+    "santa": "🎅",
+    "fax": "📠",
+    "fearful": "😨",
+    "field_hockey_stick_and_ball": "🏑",
+    "first_quarter_moon_with_face": "🌛",
+    "fish_cake": "🍥",
+    "fishing_pole_and_fish": "🎣",
+    "facepunch": "👊",
+    "punch": "👊",
+    "flag_for_afghanistan": "🇦🇫",
+    "flag_for_albania": "🇦🇱",
+    "flag_for_algeria": "🇩🇿",
+    "flag_for_american_samoa": "🇦🇸",
+    "flag_for_andorra": "🇦🇩",
+    "flag_for_angola": "🇦🇴",
+    "flag_for_anguilla": "🇦🇮",
+    "flag_for_antarctica": "🇦🇶",
+    "flag_for_antigua_&_barbuda": "🇦🇬",
+    "flag_for_argentina": "🇦🇷",
+    "flag_for_armenia": "🇦🇲",
+    "flag_for_aruba": "🇦🇼",
+    "flag_for_ascension_island": "🇦🇨",
+    "flag_for_australia": "🇦🇺",
+    "flag_for_austria": "🇦🇹",
+    "flag_for_azerbaijan": "🇦🇿",
+    "flag_for_bahamas": "🇧🇸",
+    "flag_for_bahrain": "🇧🇭",
+    "flag_for_bangladesh": "🇧🇩",
+    "flag_for_barbados": "🇧🇧",
+    "flag_for_belarus": "🇧🇾",
+    "flag_for_belgium": "🇧🇪",
+    "flag_for_belize": "🇧🇿",
+    "flag_for_benin": "🇧🇯",
+    "flag_for_bermuda": "🇧🇲",
+    "flag_for_bhutan": "🇧🇹",
+    "flag_for_bolivia": "🇧🇴",
+    "flag_for_bosnia_&_herzegovina": "🇧🇦",
+    "flag_for_botswana": "🇧🇼",
+    "flag_for_bouvet_island": "🇧🇻",
+    "flag_for_brazil": "🇧🇷",
+    "flag_for_british_indian_ocean_territory": "🇮🇴",
+    "flag_for_british_virgin_islands": "🇻🇬",
+    "flag_for_brunei": "🇧🇳",
+    "flag_for_bulgaria": "🇧🇬",
+    "flag_for_burkina_faso": "🇧🇫",
+    "flag_for_burundi": "🇧🇮",
+    "flag_for_cambodia": "🇰🇭",
+    "flag_for_cameroon": "🇨🇲",
+    "flag_for_canada": "🇨🇦",
+    "flag_for_canary_islands": "🇮🇨",
+    "flag_for_cape_verde": "🇨🇻",
+    "flag_for_caribbean_netherlands": "🇧🇶",
+    "flag_for_cayman_islands": "🇰🇾",
+    "flag_for_central_african_republic": "🇨🇫",
+    "flag_for_ceuta_&_melilla": "🇪🇦",
+    "flag_for_chad": "🇹🇩",
+    "flag_for_chile": "🇨🇱",
+    "flag_for_china": "🇨🇳",
+    "flag_for_christmas_island": "🇨🇽",
+    "flag_for_clipperton_island": "🇨🇵",
+    "flag_for_cocos__islands": "🇨🇨",
+    "flag_for_colombia": "🇨🇴",
+    "flag_for_comoros": "🇰🇲",
+    "flag_for_congo____brazzaville": "🇨🇬",
+    "flag_for_congo____kinshasa": "🇨🇩",
+    "flag_for_cook_islands": "🇨🇰",
+    "flag_for_costa_rica": "🇨🇷",
+    "flag_for_croatia": "🇭🇷",
+    "flag_for_cuba": "🇨🇺",
+    "flag_for_curaçao": "🇨🇼",
+    "flag_for_cyprus": "🇨🇾",
+    "flag_for_czech_republic": "🇨🇿",
+    "flag_for_côte_d’ivoire": "🇨🇮",
+    "flag_for_denmark": "🇩🇰",
+    "flag_for_diego_garcia": "🇩🇬",
+    "flag_for_djibouti": "🇩🇯",
+    "flag_for_dominica": "🇩🇲",
+    "flag_for_dominican_republic": "🇩🇴",
+    "flag_for_ecuador": "🇪🇨",
+    "flag_for_egypt": "🇪🇬",
+    "flag_for_el_salvador": "🇸🇻",
+    "flag_for_equatorial_guinea": "🇬🇶",
+    "flag_for_eritrea": "🇪🇷",
+    "flag_for_estonia": "🇪🇪",
+    "flag_for_ethiopia": "🇪🇹",
+    "flag_for_european_union": "🇪🇺",
+    "flag_for_falkland_islands": "🇫🇰",
+    "flag_for_faroe_islands": "🇫🇴",
+    "flag_for_fiji": "🇫🇯",
+    "flag_for_finland": "🇫🇮",
+    "flag_for_france": "🇫🇷",
+    "flag_for_french_guiana": "🇬🇫",
+    "flag_for_french_polynesia": "🇵🇫",
+    "flag_for_french_southern_territories": "🇹🇫",
+    "flag_for_gabon": "🇬🇦",
+    "flag_for_gambia": "🇬🇲",
+    "flag_for_georgia": "🇬🇪",
+    "flag_for_germany": "🇩🇪",
+    "flag_for_ghana": "🇬🇭",
+    "flag_for_gibraltar": "🇬🇮",
+    "flag_for_greece": "🇬🇷",
+    "flag_for_greenland": "🇬🇱",
+    "flag_for_grenada": "🇬🇩",
+    "flag_for_guadeloupe": "🇬🇵",
+    "flag_for_guam": "🇬🇺",
+    "flag_for_guatemala": "🇬🇹",
+    "flag_for_guernsey": "🇬🇬",
+    "flag_for_guinea": "🇬🇳",
+    "flag_for_guinea__bissau": "🇬🇼",
+    "flag_for_guyana": "🇬🇾",
+    "flag_for_haiti": "🇭🇹",
+    "flag_for_heard_&_mcdonald_islands": "🇭🇲",
+    "flag_for_honduras": "🇭🇳",
+    "flag_for_hong_kong": "🇭🇰",
+    "flag_for_hungary": "🇭🇺",
+    "flag_for_iceland": "🇮🇸",
+    "flag_for_india": "🇮🇳",
+    "flag_for_indonesia": "🇮🇩",
+    "flag_for_iran": "🇮🇷",
+    "flag_for_iraq": "🇮🇶",
+    "flag_for_ireland": "🇮🇪",
+    "flag_for_isle_of_man": "🇮🇲",
+    "flag_for_israel": "🇮🇱",
+    "flag_for_italy": "🇮🇹",
+    "flag_for_jamaica": "🇯🇲",
+    "flag_for_japan": "🇯🇵",
+    "flag_for_jersey": "🇯🇪",
+    "flag_for_jordan": "🇯🇴",
+    "flag_for_kazakhstan": "🇰🇿",
+    "flag_for_kenya": "🇰🇪",
+    "flag_for_kiribati": "🇰🇮",
+    "flag_for_kosovo": "🇽🇰",
+    "flag_for_kuwait": "🇰🇼",
+    "flag_for_kyrgyzstan": "🇰🇬",
+    "flag_for_laos": "🇱🇦",
+    "flag_for_latvia": "🇱🇻",
+    "flag_for_lebanon": "🇱🇧",
+    "flag_for_lesotho": "🇱🇸",
+    "flag_for_liberia": "🇱🇷",
+    "flag_for_libya": "🇱🇾",
+    "flag_for_liechtenstein": "🇱🇮",
+    "flag_for_lithuania": "🇱🇹",
+    "flag_for_luxembourg": "🇱🇺",
+    "flag_for_macau": "🇲🇴",
+    "flag_for_macedonia": "🇲🇰",
+    "flag_for_madagascar": "🇲🇬",
+    "flag_for_malawi": "🇲🇼",
+    "flag_for_malaysia": "🇲🇾",
+    "flag_for_maldives": "🇲🇻",
+    "flag_for_mali": "🇲🇱",
+    "flag_for_malta": "🇲🇹",
+    "flag_for_marshall_islands": "🇲🇭",
+    "flag_for_martinique": "🇲🇶",
+    "flag_for_mauritania": "🇲🇷",
+    "flag_for_mauritius": "🇲🇺",
+    "flag_for_mayotte": "🇾🇹",
+    "flag_for_mexico": "🇲🇽",
+    "flag_for_micronesia": "🇫🇲",
+    "flag_for_moldova": "🇲🇩",
+    "flag_for_monaco": "🇲🇨",
+    "flag_for_mongolia": "🇲🇳",
+    "flag_for_montenegro": "🇲🇪",
+    "flag_for_montserrat": "🇲🇸",
+    "flag_for_morocco": "🇲🇦",
+    "flag_for_mozambique": "🇲🇿",
+    "flag_for_myanmar": "🇲🇲",
+    "flag_for_namibia": "🇳🇦",
+    "flag_for_nauru": "🇳🇷",
+    "flag_for_nepal": "🇳🇵",
+    "flag_for_netherlands": "🇳🇱",
+    "flag_for_new_caledonia": "🇳🇨",
+    "flag_for_new_zealand": "🇳🇿",
+    "flag_for_nicaragua": "🇳🇮",
+    "flag_for_niger": "🇳🇪",
+    "flag_for_nigeria": "🇳🇬",
+    "flag_for_niue": "🇳🇺",
+    "flag_for_norfolk_island": "🇳🇫",
+    "flag_for_north_korea": "🇰🇵",
+    "flag_for_northern_mariana_islands": "🇲🇵",
+    "flag_for_norway": "🇳🇴",
+    "flag_for_oman": "🇴🇲",
+    "flag_for_pakistan": "🇵🇰",
+    "flag_for_palau": "🇵🇼",
+    "flag_for_palestinian_territories": "🇵🇸",
+    "flag_for_panama": "🇵🇦",
+    "flag_for_papua_new_guinea": "🇵🇬",
+    "flag_for_paraguay": "🇵🇾",
+    "flag_for_peru": "🇵🇪",
+    "flag_for_philippines": "🇵🇭",
+    "flag_for_pitcairn_islands": "🇵🇳",
+    "flag_for_poland": "🇵🇱",
+    "flag_for_portugal": "🇵🇹",
+    "flag_for_puerto_rico": "🇵🇷",
+    "flag_for_qatar": "🇶🇦",
+    "flag_for_romania": "🇷🇴",
+    "flag_for_russia": "🇷🇺",
+    "flag_for_rwanda": "🇷🇼",
+    "flag_for_réunion": "🇷🇪",
+    "flag_for_samoa": "🇼🇸",
+    "flag_for_san_marino": "🇸🇲",
+    "flag_for_saudi_arabia": "🇸🇦",
+    "flag_for_senegal": "🇸🇳",
+    "flag_for_serbia": "🇷🇸",
+    "flag_for_seychelles": "🇸🇨",
+    "flag_for_sierra_leone": "🇸🇱",
+    "flag_for_singapore": "🇸🇬",
+    "flag_for_sint_maarten": "🇸🇽",
+    "flag_for_slovakia": "🇸🇰",
+    "flag_for_slovenia": "🇸🇮",
+    "flag_for_solomon_islands": "🇸🇧",
+    "flag_for_somalia": "🇸🇴",
+    "flag_for_south_africa": "🇿🇦",
+    "flag_for_south_georgia_&_south_sandwich_islands": "🇬🇸",
+    "flag_for_south_korea": "🇰🇷",
+    "flag_for_south_sudan": "🇸🇸",
+    "flag_for_spain": "🇪🇸",
+    "flag_for_sri_lanka": "🇱🇰",
+    "flag_for_st._barthélemy": "🇧🇱",
+    "flag_for_st._helena": "🇸🇭",
+    "flag_for_st._kitts_&_nevis": "🇰🇳",
+    "flag_for_st._lucia": "🇱🇨",
+    "flag_for_st._martin": "🇲🇫",
+    "flag_for_st._pierre_&_miquelon": "🇵🇲",
+    "flag_for_st._vincent_&_grenadines": "🇻🇨",
+    "flag_for_sudan": "🇸🇩",
+    "flag_for_suriname": "🇸🇷",
+    "flag_for_svalbard_&_jan_mayen": "🇸🇯",
+    "flag_for_swaziland": "🇸🇿",
+    "flag_for_sweden": "🇸🇪",
+    "flag_for_switzerland": "🇨🇭",
+    "flag_for_syria": "🇸🇾",
+    "flag_for_são_tomé_&_príncipe": "🇸🇹",
+    "flag_for_taiwan": "🇹🇼",
+    "flag_for_tajikistan": "🇹🇯",
+    "flag_for_tanzania": "🇹🇿",
+    "flag_for_thailand": "🇹🇭",
+    "flag_for_timor__leste": "🇹🇱",
+    "flag_for_togo": "🇹🇬",
+    "flag_for_tokelau": "🇹🇰",
+    "flag_for_tonga": "🇹🇴",
+    "flag_for_trinidad_&_tobago": "🇹🇹",
+    "flag_for_tristan_da_cunha": "🇹🇦",
+    "flag_for_tunisia": "🇹🇳",
+    "flag_for_turkey": "🇹🇷",
+    "flag_for_turkmenistan": "🇹🇲",
+    "flag_for_turks_&_caicos_islands": "🇹🇨",
+    "flag_for_tuvalu": "🇹🇻",
+    "flag_for_u.s._outlying_islands": "🇺🇲",
+    "flag_for_u.s._virgin_islands": "🇻🇮",
+    "flag_for_uganda": "🇺🇬",
+    "flag_for_ukraine": "🇺🇦",
+    "flag_for_united_arab_emirates": "🇦🇪",
+    "flag_for_united_kingdom": "🇬🇧",
+    "flag_for_united_states": "🇺🇸",
+    "flag_for_uruguay": "🇺🇾",
+    "flag_for_uzbekistan": "🇺🇿",
+    "flag_for_vanuatu": "🇻🇺",
+    "flag_for_vatican_city": "🇻🇦",
+    "flag_for_venezuela": "🇻🇪",
+    "flag_for_vietnam": "🇻🇳",
+    "flag_for_wallis_&_futuna": "🇼🇫",
+    "flag_for_western_sahara": "🇪🇭",
+    "flag_for_yemen": "🇾🇪",
+    "flag_for_zambia": "🇿🇲",
+    "flag_for_zimbabwe": "🇿🇼",
+    "flag_for_åland_islands": "🇦🇽",
+    "golf": "⛳",
+    "fleur__de__lis": "⚜",
+    "muscle": "💪",
+    "flushed": "😳",
+    "frame_with_picture": "🖼",
+    "fries": "🍟",
+    "frog": "🐸",
+    "hatched_chick": "🐥",
+    "frowning": "😦",
+    "fuelpump": "⛽",
+    "full_moon_with_face": "🌝",
+    "gem": "💎",
+    "star2": "🌟",
+    "golfer": "🏌",
+    "mortar_board": "🎓",
+    "grimacing": "😬",
+    "smile_cat": "😸",
+    "grinning": "😀",
+    "grin": "😁",
+    "heartpulse": "💗",
+    "guardsman": "💂",
+    "haircut": "💇",
+    "hamster": "🐹",
+    "raising_hand": "🙋",
+    "headphones": "🎧",
+    "hear_no_evil": "🙉",
+    "cupid": "💘",
+    "gift_heart": "💝",
+    "heart": "❤",
+    "exclamation": "❗",
+    "heavy_exclamation_mark": "❗",
+    "heavy_heart_exclamation_mark_ornament": "❣",
+    "o": "⭕",
+    "helm_symbol": "⎈",
+    "helmet_with_white_cross": "⛑",
+    "high_heel": "👠",
+    "bullettrain_side": "🚄",
+    "bullettrain_front": "🚅",
+    "high_brightness": "🔆",
+    "zap": "⚡",
+    "hocho": "🔪",
+    "knife": "🔪",
+    "bee": "🐝",
+    "traffic_light": "🚥",
+    "racehorse": "🐎",
+    "coffee": "☕",
+    "hotsprings": "♨",
+    "hourglass": "⌛",
+    "hourglass_flowing_sand": "⏳",
+    "house_buildings": "🏘",
+    "100": "💯",
+    "hushed": "😯",
+    "ice_hockey_stick_and_puck": "🏒",
+    "imp": "👿",
+    "information_desk_person": "💁",
+    "information_source": "ℹ",
+    "capital_abcd": "🔠",
+    "abc": "🔤",
+    "abcd": "🔡",
+    "1234": "🔢",
+    "symbols": "🔣",
+    "izakaya_lantern": "🏮",
+    "lantern": "🏮",
+    "jack_o_lantern": "🎃",
+    "dolls": "🎎",
+    "japanese_goblin": "👺",
+    "japanese_ogre": "👹",
+    "beginner": "🔰",
+    "zero": "0️⃣",
+    "one": "1️⃣",
+    "ten": "🔟",
+    "two": "2️⃣",
+    "three": "3️⃣",
+    "four": "4️⃣",
+    "five": "5️⃣",
+    "six": "6️⃣",
+    "seven": "7️⃣",
+    "eight": "8️⃣",
+    "nine": "9️⃣",
+    "couplekiss": "💏",
+    "kissing_cat": "😽",
+    "kissing": "😗",
+    "kissing_closed_eyes": "😚",
+    "kissing_smiling_eyes": "😙",
+    "beetle": "🐞",
+    "large_blue_circle": "🔵",
+    "last_quarter_moon_with_face": "🌜",
+    "leaves": "🍃",
+    "mag": "🔍",
+    "left_right_arrow": "↔",
+    "leftwards_arrow_with_hook": "↩",
+    "arrow_left": "⬅",
+    "lock": "🔒",
+    "lock_with_ink_pen": "🔏",
+    "sob": "😭",
+    "low_brightness": "🔅",
+    "lower_left_ballpoint_pen": "🖊",
+    "lower_left_crayon": "🖍",
+    "lower_left_fountain_pen": "🖋",
+    "lower_left_paintbrush": "🖌",
+    "mahjong": "🀄",
+    "couple": "👫",
+    "man_in_business_suit_levitating": "🕴",
+    "man_with_gua_pi_mao": "👲",
+    "man_with_turban": "👳",
+    "mans_shoe": "👞",
+    "shoe": "👞",
+    "menorah_with_nine_branches": "🕎",
+    "mens": "🚹",
+    "minidisc": "💽",
+    "iphone": "📱",
+    "calling": "📲",
+    "money__mouth_face": "🤑",
+    "moneybag": "💰",
+    "rice_scene": "🎑",
+    "mountain_bicyclist": "🚵",
+    "mouse2": "🐁",
+    "lips": "👄",
+    "moyai": "🗿",
+    "notes": "🎶",
+    "nail_care": "💅",
+    "ab": "🆎",
+    "negative_squared_cross_mark": "❎",
+    "a": "🅰",
+    "b": "🅱",
+    "o2": "🅾",
+    "parking": "🅿",
+    "new_moon_with_face": "🌚",
+    "no_entry_sign": "🚫",
+    "underage": "🔞",
+    "non__potable_water": "🚱",
+    "arrow_upper_right": "↗",
+    "arrow_upper_left": "↖",
+    "office": "🏢",
+    "older_man": "👴",
+    "older_woman": "👵",
+    "om_symbol": "🕉",
+    "on": "🔛",
+    "book": "📖",
+    "unlock": "🔓",
+    "mailbox_with_no_mail": "📭",
+    "mailbox_with_mail": "📬",
+    "cd": "💿",
+    "tada": "🎉",
+    "feet": "🐾",
+    "walking": "🚶",
+    "pencil2": "✏",
+    "pensive": "😔",
+    "persevere": "😣",
+    "bow": "🙇",
+    "raised_hands": "🙌",
+    "person_with_ball": "⛹",
+    "person_with_blond_hair": "👱",
+    "pray": "🙏",
+    "person_with_pouting_face": "🙎",
+    "computer": "💻",
+    "pig2": "🐖",
+    "hankey": "💩",
+    "poop": "💩",
+    "shit": "💩",
+    "bamboo": "🎍",
+    "gun": "🔫",
+    "black_joker": "🃏",
+    "rotating_light": "🚨",
+    "cop": "👮",
+    "stew": "🍲",
+    "pouch": "👝",
+    "pouting_cat": "😾",
+    "rage": "😡",
+    "put_litter_in_its_place": "🚮",
+    "rabbit2": "🐇",
+    "racing_motorcycle": "🏍",
+    "radioactive_sign": "☢",
+    "fist": "✊",
+    "hand": "✋",
+    "raised_hand_with_fingers_splayed": "🖐",
+    "raised_hand_with_part_between_middle_and_ring_fingers": "🖖",
+    "blue_car": "🚙",
+    "apple": "🍎",
+    "relieved": "😌",
+    "reversed_hand_with_middle_finger_extended": "🖕",
+    "mag_right": "🔎",
+    "arrow_right_hook": "↪",
+    "sweet_potato": "🍠",
+    "robot": "🤖",
+    "rolled__up_newspaper": "🗞",
+    "rowboat": "🚣",
+    "runner": "🏃",
+    "running": "🏃",
+    "running_shirt_with_sash": "🎽",
+    "boat": "⛵",
+    "scales": "⚖",
+    "school_satchel": "🎒",
+    "scorpius": "♏",
+    "see_no_evil": "🙈",
+    "sheep": "🐑",
+    "stars": "🌠",
+    "cake": "🍰",
+    "six_pointed_star": "🔯",
+    "ski": "🎿",
+    "sleeping_accommodation": "🛌",
+    "sleeping": "😴",
+    "sleepy": "😪",
+    "sleuth_or_spy": "🕵",
+    "heart_eyes_cat": "😻",
+    "smiley_cat": "😺",
+    "innocent": "😇",
+    "heart_eyes": "😍",
+    "smiling_imp": "😈",
+    "smiley": "😃",
+    "sweat_smile": "😅",
+    "smile": "😄",
+    "laughing": "😆",
+    "satisfied": "😆",
+    "blush": "😊",
+    "smirk": "😏",
+    "smoking": "🚬",
+    "snow_capped_mountain": "🏔",
+    "soccer": "⚽",
+    "icecream": "🍦",
+    "soon": "🔜",
+    "arrow_lower_right": "↘",
+    "arrow_lower_left": "↙",
+    "speak_no_evil": "🙊",
+    "speaker": "🔈",
+    "mute": "🔇",
+    "sound": "🔉",
+    "loud_sound": "🔊",
+    "speaking_head_in_silhouette": "🗣",
+    "spiral_calendar_pad": "🗓",
+    "spiral_note_pad": "🗒",
+    "shell": "🐚",
+    "sweat_drops": "💦",
+    "u5272": "🈹",
+    "u5408": "🈴",
+    "u55b6": "🈺",
+    "u6307": "🈯",
+    "u6708": "🈷",
+    "u6709": "🈶",
+    "u6e80": "🈵",
+    "u7121": "🈚",
+    "u7533": "🈸",
+    "u7981": "🈲",
+    "u7a7a": "🈳",
+    "cl": "🆑",
+    "cool": "🆒",
+    "free": "🆓",
+    "id": "🆔",
+    "koko": "🈁",
+    "sa": "🈂",
+    "new": "🆕",
+    "ng": "🆖",
+    "ok": "🆗",
+    "sos": "🆘",
+    "up": "🆙",
+    "vs": "🆚",
+    "steam_locomotive": "🚂",
+    "ramen": "🍜",
+    "partly_sunny": "⛅",
+    "city_sunrise": "🌇",
+    "surfer": "🏄",
+    "swimmer": "🏊",
+    "shirt": "👕",
+    "tshirt": "👕",
+    "table_tennis_paddle_and_ball": "🏓",
+    "tea": "🍵",
+    "tv": "📺",
+    "three_button_mouse": "🖱",
+    "+1": "👍",
+    "thumbsup": "👍",
+    "__1": "👎",
+    "-1": "👎",
+    "thumbsdown": "👎",
+    "thunder_cloud_and_rain": "⛈",
+    "tiger2": "🐅",
+    "tophat": "🎩",
+    "top": "🔝",
+    "tm": "™",
+    "train2": "🚆",
+    "triangular_flag_on_post": "🚩",
+    "trident": "🔱",
+    "twisted_rightwards_arrows": "🔀",
+    "unamused": "😒",
+    "small_red_triangle": "🔺",
+    "arrow_up_small": "🔼",
+    "arrow_up_down": "↕",
+    "upside__down_face": "🙃",
+    "arrow_up": "⬆",
+    "v": "✌",
+    "vhs": "📼",
+    "wc": "🚾",
+    "ocean": "🌊",
+    "waving_black_flag": "🏴",
+    "wave": "👋",
+    "waving_white_flag": "🏳",
+    "moon": "🌔",
+    "scream_cat": "🙀",
+    "weary": "😩",
+    "weight_lifter": "🏋",
+    "whale2": "🐋",
+    "wheelchair": "♿",
+    "point_down": "👇",
+    "grey_exclamation": "❕",
+    "white_frowning_face": "☹",
+    "white_check_mark": "✅",
+    "point_left": "👈",
+    "white_medium_small_square": "◽",
+    "star": "⭐",
+    "grey_question": "❔",
+    "point_right": "👉",
+    "relaxed": "☺",
+    "white_sun_behind_cloud": "🌥",
+    "white_sun_behind_cloud_with_rain": "🌦",
+    "white_sun_with_small_cloud": "🌤",
+    "point_up_2": "👆",
+    "point_up": "☝",
+    "wind_blowing_face": "🌬",
+    "wink": "😉",
+    "wolf": "🐺",
+    "dancers": "👯",
+    "boot": "👢",
+    "womans_clothes": "👚",
+    "womans_hat": "👒",
+    "sandal": "👡",
+    "womens": "🚺",
+    "worried": "😟",
+    "gift": "🎁",
+    "zipper__mouth_face": "🤐",
+    "regional_indicator_a": "🇦",
+    "regional_indicator_b": "🇧",
+    "regional_indicator_c": "🇨",
+    "regional_indicator_d": "🇩",
+    "regional_indicator_e": "🇪",
+    "regional_indicator_f": "🇫",
+    "regional_indicator_g": "🇬",
+    "regional_indicator_h": "🇭",
+    "regional_indicator_i": "🇮",
+    "regional_indicator_j": "🇯",
+    "regional_indicator_k": "🇰",
+    "regional_indicator_l": "🇱",
+    "regional_indicator_m": "🇲",
+    "regional_indicator_n": "🇳",
+    "regional_indicator_o": "🇴",
+    "regional_indicator_p": "🇵",
+    "regional_indicator_q": "🇶",
+    "regional_indicator_r": "🇷",
+    "regional_indicator_s": "🇸",
+    "regional_indicator_t": "🇹",
+    "regional_indicator_u": "🇺",
+    "regional_indicator_v": "🇻",
+    "regional_indicator_w": "🇼",
+    "regional_indicator_x": "🇽",
+    "regional_indicator_y": "🇾",
+    "regional_indicator_z": "🇿",
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_emoji_replace.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_emoji_replace.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb2cafa18011e7115773055338291c366f173d6f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_emoji_replace.py
@@ -0,0 +1,32 @@
+from typing import Callable, Match, Optional
+import re
+
+from ._emoji_codes import EMOJI
+
+
+_ReStringMatch = Match[str]  # regex match object
+_ReSubCallable = Callable[[_ReStringMatch], str]  # Callable invoked by re.sub
+_EmojiSubMethod = Callable[[_ReSubCallable, str], str]  # Sub method of a compiled re
+
+
+def _emoji_replace(
+    text: str,
+    default_variant: Optional[str] = None,
+    _emoji_sub: _EmojiSubMethod = re.compile(r"(:(\S*?)(?:(?:\-)(emoji|text))?:)").sub,
+) -> str:
+    """Replace emoji code in text."""
+    get_emoji = EMOJI.__getitem__
+    variants = {"text": "\uFE0E", "emoji": "\uFE0F"}
+    get_variant = variants.get
+    default_variant_code = variants.get(default_variant, "") if default_variant else ""
+
+    def do_replace(match: Match[str]) -> str:
+        emoji_code, emoji_name, variant = match.groups()
+        try:
+            return get_emoji(emoji_name.lower()) + get_variant(
+                variant, default_variant_code
+            )
+        except KeyError:
+            return emoji_code
+
+    return _emoji_sub(do_replace, text)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_export_format.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_export_format.py
new file mode 100644
index 0000000000000000000000000000000000000000..b79c13069b9f5a7d7fc1d8c3364d3cd66c80c60f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_export_format.py
@@ -0,0 +1,78 @@
+CONSOLE_HTML_FORMAT = """\
+
+
+
+
+
+
+
+    
+        
{code}

+    
+
+
+"""
+
+CONSOLE_SVG_FORMAT = """\
+
+    
+    
+
+    
+    
+      
+    
+    {lines}
+    
+
+    {chrome}
+    
+    {backgrounds}
+    
+    {matrix}
+    
+    
+
+"""
+
+_SVG_FONT_FAMILY = "Rich Fira Code"
+_SVG_CLASSES_PREFIX = "rich-svg"
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_extension.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_extension.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbd6da9be4956ce8558304ed72ffbe88ccd22ba5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_extension.py
@@ -0,0 +1,10 @@
+from typing import Any
+
+
+def load_ipython_extension(ip: Any) -> None:  # pragma: no cover
+    # prevent circular import
+    from pip._vendor.rich.pretty import install
+    from pip._vendor.rich.traceback import install as tr_install
+
+    install()
+    tr_install()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_inspect.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_inspect.py
new file mode 100644
index 0000000000000000000000000000000000000000..30446ceb3f0235721e435f5fbd53f2e306f078cd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_inspect.py
@@ -0,0 +1,270 @@
+from __future__ import absolute_import
+
+import inspect
+from inspect import cleandoc, getdoc, getfile, isclass, ismodule, signature
+from typing import Any, Collection, Iterable, Optional, Tuple, Type, Union
+
+from .console import Group, RenderableType
+from .control import escape_control_codes
+from .highlighter import ReprHighlighter
+from .jupyter import JupyterMixin
+from .panel import Panel
+from .pretty import Pretty
+from .table import Table
+from .text import Text, TextType
+
+
+def _first_paragraph(doc: str) -> str:
+    """Get the first paragraph from a docstring."""
+    paragraph, _, _ = doc.partition("\n\n")
+    return paragraph
+
+
+class Inspect(JupyterMixin):
+    """A renderable to inspect any Python Object.
+
+    Args:
+        obj (Any): An object to inspect.
+        title (str, optional): Title to display over inspect result, or None use type. Defaults to None.
+        help (bool, optional): Show full help text rather than just first paragraph. Defaults to False.
+        methods (bool, optional): Enable inspection of callables. Defaults to False.
+        docs (bool, optional): Also render doc strings. Defaults to True.
+        private (bool, optional): Show private attributes (beginning with underscore). Defaults to False.
+        dunder (bool, optional): Show attributes starting with double underscore. Defaults to False.
+        sort (bool, optional): Sort attributes alphabetically. Defaults to True.
+        all (bool, optional): Show all attributes. Defaults to False.
+        value (bool, optional): Pretty print value of object. Defaults to True.
+    """
+
+    def __init__(
+        self,
+        obj: Any,
+        *,
+        title: Optional[TextType] = None,
+        help: bool = False,
+        methods: bool = False,
+        docs: bool = True,
+        private: bool = False,
+        dunder: bool = False,
+        sort: bool = True,
+        all: bool = True,
+        value: bool = True,
+    ) -> None:
+        self.highlighter = ReprHighlighter()
+        self.obj = obj
+        self.title = title or self._make_title(obj)
+        if all:
+            methods = private = dunder = True
+        self.help = help
+        self.methods = methods
+        self.docs = docs or help
+        self.private = private or dunder
+        self.dunder = dunder
+        self.sort = sort
+        self.value = value
+
+    def _make_title(self, obj: Any) -> Text:
+        """Make a default title."""
+        title_str = (
+            str(obj)
+            if (isclass(obj) or callable(obj) or ismodule(obj))
+            else str(type(obj))
+        )
+        title_text = self.highlighter(title_str)
+        return title_text
+
+    def __rich__(self) -> Panel:
+        return Panel.fit(
+            Group(*self._render()),
+            title=self.title,
+            border_style="scope.border",
+            padding=(0, 1),
+        )
+
+    def _get_signature(self, name: str, obj: Any) -> Optional[Text]:
+        """Get a signature for a callable."""
+        try:
+            _signature = str(signature(obj)) + ":"
+        except ValueError:
+            _signature = "(...)"
+        except TypeError:
+            return None
+
+        source_filename: Optional[str] = None
+        try:
+            source_filename = getfile(obj)
+        except (OSError, TypeError):
+            # OSError is raised if obj has no source file, e.g. when defined in REPL.
+            pass
+
+        callable_name = Text(name, style="inspect.callable")
+        if source_filename:
+            callable_name.stylize(f"link file://{source_filename}")
+        signature_text = self.highlighter(_signature)
+
+        qualname = name or getattr(obj, "__qualname__", name)
+
+        # If obj is a module, there may be classes (which are callable) to display
+        if inspect.isclass(obj):
+            prefix = "class"
+        elif inspect.iscoroutinefunction(obj):
+            prefix = "async def"
+        else:
+            prefix = "def"
+
+        qual_signature = Text.assemble(
+            (f"{prefix} ", f"inspect.{prefix.replace(' ', '_')}"),
+            (qualname, "inspect.callable"),
+            signature_text,
+        )
+
+        return qual_signature
+
+    def _render(self) -> Iterable[RenderableType]:
+        """Render object."""
+
+        def sort_items(item: Tuple[str, Any]) -> Tuple[bool, str]:
+            key, (_error, value) = item
+            return (callable(value), key.strip("_").lower())
+
+        def safe_getattr(attr_name: str) -> Tuple[Any, Any]:
+            """Get attribute or any exception."""
+            try:
+                return (None, getattr(obj, attr_name))
+            except Exception as error:
+                return (error, None)
+
+        obj = self.obj
+        keys = dir(obj)
+        total_items = len(keys)
+        if not self.dunder:
+            keys = [key for key in keys if not key.startswith("__")]
+        if not self.private:
+            keys = [key for key in keys if not key.startswith("_")]
+        not_shown_count = total_items - len(keys)
+        items = [(key, safe_getattr(key)) for key in keys]
+        if self.sort:
+            items.sort(key=sort_items)
+
+        items_table = Table.grid(padding=(0, 1), expand=False)
+        items_table.add_column(justify="right")
+        add_row = items_table.add_row
+        highlighter = self.highlighter
+
+        if callable(obj):
+            signature = self._get_signature("", obj)
+            if signature is not None:
+                yield signature
+                yield ""
+
+        if self.docs:
+            _doc = self._get_formatted_doc(obj)
+            if _doc is not None:
+                doc_text = Text(_doc, style="inspect.help")
+                doc_text = highlighter(doc_text)
+                yield doc_text
+                yield ""
+
+        if self.value and not (isclass(obj) or callable(obj) or ismodule(obj)):
+            yield Panel(
+                Pretty(obj, indent_guides=True, max_length=10, max_string=60),
+                border_style="inspect.value.border",
+            )
+            yield ""
+
+        for key, (error, value) in items:
+            key_text = Text.assemble(
+                (
+                    key,
+                    "inspect.attr.dunder" if key.startswith("__") else "inspect.attr",
+                ),
+                (" =", "inspect.equals"),
+            )
+            if error is not None:
+                warning = key_text.copy()
+                warning.stylize("inspect.error")
+                add_row(warning, highlighter(repr(error)))
+                continue
+
+            if callable(value):
+                if not self.methods:
+                    continue
+
+                _signature_text = self._get_signature(key, value)
+                if _signature_text is None:
+                    add_row(key_text, Pretty(value, highlighter=highlighter))
+                else:
+                    if self.docs:
+                        docs = self._get_formatted_doc(value)
+                        if docs is not None:
+                            _signature_text.append("\n" if "\n" in docs else " ")
+                            doc = highlighter(docs)
+                            doc.stylize("inspect.doc")
+                            _signature_text.append(doc)
+
+                    add_row(key_text, _signature_text)
+            else:
+                add_row(key_text, Pretty(value, highlighter=highlighter))
+        if items_table.row_count:
+            yield items_table
+        elif not_shown_count:
+            yield Text.from_markup(
+                f"[b cyan]{not_shown_count}[/][i] attribute(s) not shown.[/i] "
+                f"Run [b][magenta]inspect[/]([not b]inspect[/])[/b] for options."
+            )
+
+    def _get_formatted_doc(self, object_: Any) -> Optional[str]:
+        """
+        Extract the docstring of an object, process it and returns it.
+        The processing consists in cleaning up the doctring's indentation,
+        taking only its 1st paragraph if `self.help` is not True,
+        and escape its control codes.
+
+        Args:
+            object_ (Any): the object to get the docstring from.
+
+        Returns:
+            Optional[str]: the processed docstring, or None if no docstring was found.
+        """
+        docs = getdoc(object_)
+        if docs is None:
+            return None
+        docs = cleandoc(docs).strip()
+        if not self.help:
+            docs = _first_paragraph(docs)
+        return escape_control_codes(docs)
+
+
+def get_object_types_mro(obj: Union[object, Type[Any]]) -> Tuple[type, ...]:
+    """Returns the MRO of an object's class, or of the object itself if it's a class."""
+    if not hasattr(obj, "__mro__"):
+        # N.B. we cannot use `if type(obj) is type` here because it doesn't work with
+        # some types of classes, such as the ones that use abc.ABCMeta.
+        obj = type(obj)
+    return getattr(obj, "__mro__", ())
+
+
+def get_object_types_mro_as_strings(obj: object) -> Collection[str]:
+    """
+    Returns the MRO of an object's class as full qualified names, or of the object itself if it's a class.
+
+    Examples:
+        `object_types_mro_as_strings(JSONDecoder)` will return `['json.decoder.JSONDecoder', 'builtins.object']`
+    """
+    return [
+        f'{getattr(type_, "__module__", "")}.{getattr(type_, "__qualname__", "")}'
+        for type_ in get_object_types_mro(obj)
+    ]
+
+
+def is_object_one_of_types(
+    obj: object, fully_qualified_types_names: Collection[str]
+) -> bool:
+    """
+    Returns `True` if the given object's class (or the object itself, if it's a class) has one of the
+    fully qualified names in its MRO.
+    """
+    for type_name in get_object_types_mro_as_strings(obj):
+        if type_name in fully_qualified_types_names:
+            return True
+    return False
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_log_render.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_log_render.py
new file mode 100644
index 0000000000000000000000000000000000000000..fc16c84437a8a34231c44d3f0a331459ddcb0f34
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_log_render.py
@@ -0,0 +1,94 @@
+from datetime import datetime
+from typing import Iterable, List, Optional, TYPE_CHECKING, Union, Callable
+
+
+from .text import Text, TextType
+
+if TYPE_CHECKING:
+    from .console import Console, ConsoleRenderable, RenderableType
+    from .table import Table
+
+FormatTimeCallable = Callable[[datetime], Text]
+
+
+class LogRender:
+    def __init__(
+        self,
+        show_time: bool = True,
+        show_level: bool = False,
+        show_path: bool = True,
+        time_format: Union[str, FormatTimeCallable] = "[%x %X]",
+        omit_repeated_times: bool = True,
+        level_width: Optional[int] = 8,
+    ) -> None:
+        self.show_time = show_time
+        self.show_level = show_level
+        self.show_path = show_path
+        self.time_format = time_format
+        self.omit_repeated_times = omit_repeated_times
+        self.level_width = level_width
+        self._last_time: Optional[Text] = None
+
+    def __call__(
+        self,
+        console: "Console",
+        renderables: Iterable["ConsoleRenderable"],
+        log_time: Optional[datetime] = None,
+        time_format: Optional[Union[str, FormatTimeCallable]] = None,
+        level: TextType = "",
+        path: Optional[str] = None,
+        line_no: Optional[int] = None,
+        link_path: Optional[str] = None,
+    ) -> "Table":
+        from .containers import Renderables
+        from .table import Table
+
+        output = Table.grid(padding=(0, 1))
+        output.expand = True
+        if self.show_time:
+            output.add_column(style="log.time")
+        if self.show_level:
+            output.add_column(style="log.level", width=self.level_width)
+        output.add_column(ratio=1, style="log.message", overflow="fold")
+        if self.show_path and path:
+            output.add_column(style="log.path")
+        row: List["RenderableType"] = []
+        if self.show_time:
+            log_time = log_time or console.get_datetime()
+            time_format = time_format or self.time_format
+            if callable(time_format):
+                log_time_display = time_format(log_time)
+            else:
+                log_time_display = Text(log_time.strftime(time_format))
+            if log_time_display == self._last_time and self.omit_repeated_times:
+                row.append(Text(" " * len(log_time_display)))
+            else:
+                row.append(log_time_display)
+                self._last_time = log_time_display
+        if self.show_level:
+            row.append(level)
+
+        row.append(Renderables(renderables))
+        if self.show_path and path:
+            path_text = Text()
+            path_text.append(
+                path, style=f"link file://{link_path}" if link_path else ""
+            )
+            if line_no:
+                path_text.append(":")
+                path_text.append(
+                    f"{line_no}",
+                    style=f"link file://{link_path}#{line_no}" if link_path else "",
+                )
+            row.append(path_text)
+
+        output.add_row(*row)
+        return output
+
+
+if __name__ == "__main__":  # pragma: no cover
+    from pip._vendor.rich.console import Console
+
+    c = Console()
+    c.print("[on blue]Hello", justify="right")
+    c.log("[on blue]hello", justify="right")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_loop.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_loop.py
new file mode 100644
index 0000000000000000000000000000000000000000..01c6cafbe53f1fcb12f7b382b2b35e2fd2c69933
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_loop.py
@@ -0,0 +1,43 @@
+from typing import Iterable, Tuple, TypeVar
+
+T = TypeVar("T")
+
+
+def loop_first(values: Iterable[T]) -> Iterable[Tuple[bool, T]]:
+    """Iterate and generate a tuple with a flag for first value."""
+    iter_values = iter(values)
+    try:
+        value = next(iter_values)
+    except StopIteration:
+        return
+    yield True, value
+    for value in iter_values:
+        yield False, value
+
+
+def loop_last(values: Iterable[T]) -> Iterable[Tuple[bool, T]]:
+    """Iterate and generate a tuple with a flag for last value."""
+    iter_values = iter(values)
+    try:
+        previous_value = next(iter_values)
+    except StopIteration:
+        return
+    for value in iter_values:
+        yield False, previous_value
+        previous_value = value
+    yield True, previous_value
+
+
+def loop_first_last(values: Iterable[T]) -> Iterable[Tuple[bool, bool, T]]:
+    """Iterate and generate a tuple with a flag for first and last value."""
+    iter_values = iter(values)
+    try:
+        previous_value = next(iter_values)
+    except StopIteration:
+        return
+    first = True
+    for value in iter_values:
+        yield first, False, previous_value
+        first = False
+        previous_value = value
+    yield first, True, previous_value
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_null_file.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_null_file.py
new file mode 100644
index 0000000000000000000000000000000000000000..49038bfcbe5852075d0aad071345e7867de87c4f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_null_file.py
@@ -0,0 +1,83 @@
+from types import TracebackType
+from typing import IO, Iterable, Iterator, List, Optional, Type
+
+
+class NullFile(IO[str]):
+
+    # TODO: "mode", "name" and "closed" are only required for Python 3.6.
+
+    @property
+    def mode(self) -> str:
+        return ""
+
+    @property
+    def name(self) -> str:
+        return "NullFile"
+
+    def closed(self) -> bool:
+        return False
+
+    def close(self) -> None:
+        pass
+
+    def isatty(self) -> bool:
+        return False
+
+    def read(self, __n: int = 1) -> str:
+        return ""
+
+    def readable(self) -> bool:
+        return False
+
+    def readline(self, __limit: int = 1) -> str:
+        return ""
+
+    def readlines(self, __hint: int = 1) -> List[str]:
+        return []
+
+    def seek(self, __offset: int, __whence: int = 1) -> int:
+        return 0
+
+    def seekable(self) -> bool:
+        return False
+
+    def tell(self) -> int:
+        return 0
+
+    def truncate(self, __size: Optional[int] = 1) -> int:
+        return 0
+
+    def writable(self) -> bool:
+        return False
+
+    def writelines(self, __lines: Iterable[str]) -> None:
+        pass
+
+    def __next__(self) -> str:
+        return ""
+
+    def __iter__(self) -> Iterator[str]:
+        return iter([""])
+
+    def __enter__(self) -> IO[str]:
+        pass
+
+    def __exit__(
+        self,
+        __t: Optional[Type[BaseException]],
+        __value: Optional[BaseException],
+        __traceback: Optional[TracebackType],
+    ) -> None:
+        pass
+
+    def write(self, text: str) -> int:
+        return 0
+
+    def flush(self) -> None:
+        pass
+
+    def fileno(self) -> int:
+        return -1
+
+
+NULL_FILE = NullFile()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_palettes.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_palettes.py
new file mode 100644
index 0000000000000000000000000000000000000000..3c748d33e45bfcdc690ceee490cbb50b516cd2b3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_palettes.py
@@ -0,0 +1,309 @@
+from .palette import Palette
+
+
+# Taken from https://en.wikipedia.org/wiki/ANSI_escape_code (Windows 10 column)
+WINDOWS_PALETTE = Palette(
+    [
+        (12, 12, 12),
+        (197, 15, 31),
+        (19, 161, 14),
+        (193, 156, 0),
+        (0, 55, 218),
+        (136, 23, 152),
+        (58, 150, 221),
+        (204, 204, 204),
+        (118, 118, 118),
+        (231, 72, 86),
+        (22, 198, 12),
+        (249, 241, 165),
+        (59, 120, 255),
+        (180, 0, 158),
+        (97, 214, 214),
+        (242, 242, 242),
+    ]
+)
+
+# # The standard ansi colors (including bright variants)
+STANDARD_PALETTE = Palette(
+    [
+        (0, 0, 0),
+        (170, 0, 0),
+        (0, 170, 0),
+        (170, 85, 0),
+        (0, 0, 170),
+        (170, 0, 170),
+        (0, 170, 170),
+        (170, 170, 170),
+        (85, 85, 85),
+        (255, 85, 85),
+        (85, 255, 85),
+        (255, 255, 85),
+        (85, 85, 255),
+        (255, 85, 255),
+        (85, 255, 255),
+        (255, 255, 255),
+    ]
+)
+
+
+# The 256 color palette
+EIGHT_BIT_PALETTE = Palette(
+    [
+        (0, 0, 0),
+        (128, 0, 0),
+        (0, 128, 0),
+        (128, 128, 0),
+        (0, 0, 128),
+        (128, 0, 128),
+        (0, 128, 128),
+        (192, 192, 192),
+        (128, 128, 128),
+        (255, 0, 0),
+        (0, 255, 0),
+        (255, 255, 0),
+        (0, 0, 255),
+        (255, 0, 255),
+        (0, 255, 255),
+        (255, 255, 255),
+        (0, 0, 0),
+        (0, 0, 95),
+        (0, 0, 135),
+        (0, 0, 175),
+        (0, 0, 215),
+        (0, 0, 255),
+        (0, 95, 0),
+        (0, 95, 95),
+        (0, 95, 135),
+        (0, 95, 175),
+        (0, 95, 215),
+        (0, 95, 255),
+        (0, 135, 0),
+        (0, 135, 95),
+        (0, 135, 135),
+        (0, 135, 175),
+        (0, 135, 215),
+        (0, 135, 255),
+        (0, 175, 0),
+        (0, 175, 95),
+        (0, 175, 135),
+        (0, 175, 175),
+        (0, 175, 215),
+        (0, 175, 255),
+        (0, 215, 0),
+        (0, 215, 95),
+        (0, 215, 135),
+        (0, 215, 175),
+        (0, 215, 215),
+        (0, 215, 255),
+        (0, 255, 0),
+        (0, 255, 95),
+        (0, 255, 135),
+        (0, 255, 175),
+        (0, 255, 215),
+        (0, 255, 255),
+        (95, 0, 0),
+        (95, 0, 95),
+        (95, 0, 135),
+        (95, 0, 175),
+        (95, 0, 215),
+        (95, 0, 255),
+        (95, 95, 0),
+        (95, 95, 95),
+        (95, 95, 135),
+        (95, 95, 175),
+        (95, 95, 215),
+        (95, 95, 255),
+        (95, 135, 0),
+        (95, 135, 95),
+        (95, 135, 135),
+        (95, 135, 175),
+        (95, 135, 215),
+        (95, 135, 255),
+        (95, 175, 0),
+        (95, 175, 95),
+        (95, 175, 135),
+        (95, 175, 175),
+        (95, 175, 215),
+        (95, 175, 255),
+        (95, 215, 0),
+        (95, 215, 95),
+        (95, 215, 135),
+        (95, 215, 175),
+        (95, 215, 215),
+        (95, 215, 255),
+        (95, 255, 0),
+        (95, 255, 95),
+        (95, 255, 135),
+        (95, 255, 175),
+        (95, 255, 215),
+        (95, 255, 255),
+        (135, 0, 0),
+        (135, 0, 95),
+        (135, 0, 135),
+        (135, 0, 175),
+        (135, 0, 215),
+        (135, 0, 255),
+        (135, 95, 0),
+        (135, 95, 95),
+        (135, 95, 135),
+        (135, 95, 175),
+        (135, 95, 215),
+        (135, 95, 255),
+        (135, 135, 0),
+        (135, 135, 95),
+        (135, 135, 135),
+        (135, 135, 175),
+        (135, 135, 215),
+        (135, 135, 255),
+        (135, 175, 0),
+        (135, 175, 95),
+        (135, 175, 135),
+        (135, 175, 175),
+        (135, 175, 215),
+        (135, 175, 255),
+        (135, 215, 0),
+        (135, 215, 95),
+        (135, 215, 135),
+        (135, 215, 175),
+        (135, 215, 215),
+        (135, 215, 255),
+        (135, 255, 0),
+        (135, 255, 95),
+        (135, 255, 135),
+        (135, 255, 175),
+        (135, 255, 215),
+        (135, 255, 255),
+        (175, 0, 0),
+        (175, 0, 95),
+        (175, 0, 135),
+        (175, 0, 175),
+        (175, 0, 215),
+        (175, 0, 255),
+        (175, 95, 0),
+        (175, 95, 95),
+        (175, 95, 135),
+        (175, 95, 175),
+        (175, 95, 215),
+        (175, 95, 255),
+        (175, 135, 0),
+        (175, 135, 95),
+        (175, 135, 135),
+        (175, 135, 175),
+        (175, 135, 215),
+        (175, 135, 255),
+        (175, 175, 0),
+        (175, 175, 95),
+        (175, 175, 135),
+        (175, 175, 175),
+        (175, 175, 215),
+        (175, 175, 255),
+        (175, 215, 0),
+        (175, 215, 95),
+        (175, 215, 135),
+        (175, 215, 175),
+        (175, 215, 215),
+        (175, 215, 255),
+        (175, 255, 0),
+        (175, 255, 95),
+        (175, 255, 135),
+        (175, 255, 175),
+        (175, 255, 215),
+        (175, 255, 255),
+        (215, 0, 0),
+        (215, 0, 95),
+        (215, 0, 135),
+        (215, 0, 175),
+        (215, 0, 215),
+        (215, 0, 255),
+        (215, 95, 0),
+        (215, 95, 95),
+        (215, 95, 135),
+        (215, 95, 175),
+        (215, 95, 215),
+        (215, 95, 255),
+        (215, 135, 0),
+        (215, 135, 95),
+        (215, 135, 135),
+        (215, 135, 175),
+        (215, 135, 215),
+        (215, 135, 255),
+        (215, 175, 0),
+        (215, 175, 95),
+        (215, 175, 135),
+        (215, 175, 175),
+        (215, 175, 215),
+        (215, 175, 255),
+        (215, 215, 0),
+        (215, 215, 95),
+        (215, 215, 135),
+        (215, 215, 175),
+        (215, 215, 215),
+        (215, 215, 255),
+        (215, 255, 0),
+        (215, 255, 95),
+        (215, 255, 135),
+        (215, 255, 175),
+        (215, 255, 215),
+        (215, 255, 255),
+        (255, 0, 0),
+        (255, 0, 95),
+        (255, 0, 135),
+        (255, 0, 175),
+        (255, 0, 215),
+        (255, 0, 255),
+        (255, 95, 0),
+        (255, 95, 95),
+        (255, 95, 135),
+        (255, 95, 175),
+        (255, 95, 215),
+        (255, 95, 255),
+        (255, 135, 0),
+        (255, 135, 95),
+        (255, 135, 135),
+        (255, 135, 175),
+        (255, 135, 215),
+        (255, 135, 255),
+        (255, 175, 0),
+        (255, 175, 95),
+        (255, 175, 135),
+        (255, 175, 175),
+        (255, 175, 215),
+        (255, 175, 255),
+        (255, 215, 0),
+        (255, 215, 95),
+        (255, 215, 135),
+        (255, 215, 175),
+        (255, 215, 215),
+        (255, 215, 255),
+        (255, 255, 0),
+        (255, 255, 95),
+        (255, 255, 135),
+        (255, 255, 175),
+        (255, 255, 215),
+        (255, 255, 255),
+        (8, 8, 8),
+        (18, 18, 18),
+        (28, 28, 28),
+        (38, 38, 38),
+        (48, 48, 48),
+        (58, 58, 58),
+        (68, 68, 68),
+        (78, 78, 78),
+        (88, 88, 88),
+        (98, 98, 98),
+        (108, 108, 108),
+        (118, 118, 118),
+        (128, 128, 128),
+        (138, 138, 138),
+        (148, 148, 148),
+        (158, 158, 158),
+        (168, 168, 168),
+        (178, 178, 178),
+        (188, 188, 188),
+        (198, 198, 198),
+        (208, 208, 208),
+        (218, 218, 218),
+        (228, 228, 228),
+        (238, 238, 238),
+    ]
+)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_pick.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_pick.py
new file mode 100644
index 0000000000000000000000000000000000000000..4f6d8b2d79406012c5f8bae9c289ed5bf4d179cc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_pick.py
@@ -0,0 +1,17 @@
+from typing import Optional
+
+
+def pick_bool(*values: Optional[bool]) -> bool:
+    """Pick the first non-none bool or return the last value.
+
+    Args:
+        *values (bool): Any number of boolean or None values.
+
+    Returns:
+        bool: First non-none boolean.
+    """
+    assert values, "1 or more values required"
+    for value in values:
+        if value is not None:
+            return value
+    return bool(value)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_ratio.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_ratio.py
new file mode 100644
index 0000000000000000000000000000000000000000..e8a3a674e0070159b956c29c5092b0f72abc969d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_ratio.py
@@ -0,0 +1,160 @@
+import sys
+from fractions import Fraction
+from math import ceil
+from typing import cast, List, Optional, Sequence
+
+if sys.version_info >= (3, 8):
+    from typing import Protocol
+else:
+    from pip._vendor.typing_extensions import Protocol  # pragma: no cover
+
+
+class Edge(Protocol):
+    """Any object that defines an edge (such as Layout)."""
+
+    size: Optional[int] = None
+    ratio: int = 1
+    minimum_size: int = 1
+
+
+def ratio_resolve(total: int, edges: Sequence[Edge]) -> List[int]:
+    """Divide total space to satisfy size, ratio, and minimum_size, constraints.
+
+    The returned list of integers should add up to total in most cases, unless it is
+    impossible to satisfy all the constraints. For instance, if there are two edges
+    with a minimum size of 20 each and `total` is 30 then the returned list will be
+    greater than total. In practice, this would mean that a Layout object would
+    clip the rows that would overflow the screen height.
+
+    Args:
+        total (int): Total number of characters.
+        edges (List[Edge]): Edges within total space.
+
+    Returns:
+        List[int]: Number of characters for each edge.
+    """
+    # Size of edge or None for yet to be determined
+    sizes = [(edge.size or None) for edge in edges]
+
+    _Fraction = Fraction
+
+    # While any edges haven't been calculated
+    while None in sizes:
+        # Get flexible edges and index to map these back on to sizes list
+        flexible_edges = [
+            (index, edge)
+            for index, (size, edge) in enumerate(zip(sizes, edges))
+            if size is None
+        ]
+        # Remaining space in total
+        remaining = total - sum(size or 0 for size in sizes)
+        if remaining <= 0:
+            # No room for flexible edges
+            return [
+                ((edge.minimum_size or 1) if size is None else size)
+                for size, edge in zip(sizes, edges)
+            ]
+        # Calculate number of characters in a ratio portion
+        portion = _Fraction(
+            remaining, sum((edge.ratio or 1) for _, edge in flexible_edges)
+        )
+
+        # If any edges will be less than their minimum, replace size with the minimum
+        for index, edge in flexible_edges:
+            if portion * edge.ratio <= edge.minimum_size:
+                sizes[index] = edge.minimum_size
+                # New fixed size will invalidate calculations, so we need to repeat the process
+                break
+        else:
+            # Distribute flexible space and compensate for rounding error
+            # Since edge sizes can only be integers we need to add the remainder
+            # to the following line
+            remainder = _Fraction(0)
+            for index, edge in flexible_edges:
+                size, remainder = divmod(portion * edge.ratio + remainder, 1)
+                sizes[index] = size
+            break
+    # Sizes now contains integers only
+    return cast(List[int], sizes)
+
+
+def ratio_reduce(
+    total: int, ratios: List[int], maximums: List[int], values: List[int]
+) -> List[int]:
+    """Divide an integer total in to parts based on ratios.
+
+    Args:
+        total (int): The total to divide.
+        ratios (List[int]): A list of integer ratios.
+        maximums (List[int]): List of maximums values for each slot.
+        values (List[int]): List of values
+
+    Returns:
+        List[int]: A list of integers guaranteed to sum to total.
+    """
+    ratios = [ratio if _max else 0 for ratio, _max in zip(ratios, maximums)]
+    total_ratio = sum(ratios)
+    if not total_ratio:
+        return values[:]
+    total_remaining = total
+    result: List[int] = []
+    append = result.append
+    for ratio, maximum, value in zip(ratios, maximums, values):
+        if ratio and total_ratio > 0:
+            distributed = min(maximum, round(ratio * total_remaining / total_ratio))
+            append(value - distributed)
+            total_remaining -= distributed
+            total_ratio -= ratio
+        else:
+            append(value)
+    return result
+
+
+def ratio_distribute(
+    total: int, ratios: List[int], minimums: Optional[List[int]] = None
+) -> List[int]:
+    """Distribute an integer total in to parts based on ratios.
+
+    Args:
+        total (int): The total to divide.
+        ratios (List[int]): A list of integer ratios.
+        minimums (List[int]): List of minimum values for each slot.
+
+    Returns:
+        List[int]: A list of integers guaranteed to sum to total.
+    """
+    if minimums:
+        ratios = [ratio if _min else 0 for ratio, _min in zip(ratios, minimums)]
+    total_ratio = sum(ratios)
+    assert total_ratio > 0, "Sum of ratios must be > 0"
+
+    total_remaining = total
+    distributed_total: List[int] = []
+    append = distributed_total.append
+    if minimums is None:
+        _minimums = [0] * len(ratios)
+    else:
+        _minimums = minimums
+    for ratio, minimum in zip(ratios, _minimums):
+        if total_ratio > 0:
+            distributed = max(minimum, ceil(ratio * total_remaining / total_ratio))
+        else:
+            distributed = total_remaining
+        append(distributed)
+        total_ratio -= ratio
+        total_remaining -= distributed
+    return distributed_total
+
+
+if __name__ == "__main__":
+    from dataclasses import dataclass
+
+    @dataclass
+    class E:
+
+        size: Optional[int] = None
+        ratio: int = 1
+        minimum_size: int = 1
+
+    resolved = ratio_resolve(110, [E(None, 1, 1), E(None, 1, 1), E(None, 1, 1)])
+    print(sum(resolved))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_spinners.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_spinners.py
new file mode 100644
index 0000000000000000000000000000000000000000..d0bb1fe751677f0ee83fc6bb876ed72443fdcde7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_spinners.py
@@ -0,0 +1,482 @@
+"""
+Spinners are from:
+* cli-spinners:
+    MIT License
+    Copyright (c) Sindre Sorhus  (sindresorhus.com)
+    Permission is hereby granted, free of charge, to any person obtaining a copy
+    of this software and associated documentation files (the "Software"), to deal
+    in the Software without restriction, including without limitation the rights to
+    use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
+    the Software, and to permit persons to whom the Software is furnished to do so,
+    subject to the following conditions:
+    The above copyright notice and this permission notice shall be included
+    in all copies or substantial portions of the Software.
+    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+    INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
+    PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE
+    FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
+    ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+    IN THE SOFTWARE.
+"""
+
+SPINNERS = {
+    "dots": {
+        "interval": 80,
+        "frames": "⠋⠙⠹⠸⠼⠴⠦⠧⠇⠏",
+    },
+    "dots2": {"interval": 80, "frames": "⣾⣽⣻⢿⡿⣟⣯⣷"},
+    "dots3": {
+        "interval": 80,
+        "frames": "⠋⠙⠚⠞⠖⠦⠴⠲⠳⠓",
+    },
+    "dots4": {
+        "interval": 80,
+        "frames": "⠄⠆⠇⠋⠙⠸⠰⠠⠰⠸⠙⠋⠇⠆",
+    },
+    "dots5": {
+        "interval": 80,
+        "frames": "⠋⠙⠚⠒⠂⠂⠒⠲⠴⠦⠖⠒⠐⠐⠒⠓⠋",
+    },
+    "dots6": {
+        "interval": 80,
+        "frames": "⠁⠉⠙⠚⠒⠂⠂⠒⠲⠴⠤⠄⠄⠤⠴⠲⠒⠂⠂⠒⠚⠙⠉⠁",
+    },
+    "dots7": {
+        "interval": 80,
+        "frames": "⠈⠉⠋⠓⠒⠐⠐⠒⠖⠦⠤⠠⠠⠤⠦⠖⠒⠐⠐⠒⠓⠋⠉⠈",
+    },
+    "dots8": {
+        "interval": 80,
+        "frames": "⠁⠁⠉⠙⠚⠒⠂⠂⠒⠲⠴⠤⠄⠄⠤⠠⠠⠤⠦⠖⠒⠐⠐⠒⠓⠋⠉⠈⠈",
+    },
+    "dots9": {"interval": 80, "frames": "⢹⢺⢼⣸⣇⡧⡗⡏"},
+    "dots10": {"interval": 80, "frames": "⢄⢂⢁⡁⡈⡐⡠"},
+    "dots11": {"interval": 100, "frames": "⠁⠂⠄⡀⢀⠠⠐⠈"},
+    "dots12": {
+        "interval": 80,
+        "frames": [
+            "⢀⠀",
+            "⡀⠀",
+            "⠄⠀",
+            "⢂⠀",
+            "⡂⠀",
+            "⠅⠀",
+            "⢃⠀",
+            "⡃⠀",
+            "⠍⠀",
+            "⢋⠀",
+            "⡋⠀",
+            "⠍⠁",
+            "⢋⠁",
+            "⡋⠁",
+            "⠍⠉",
+            "⠋⠉",
+            "⠋⠉",
+            "⠉⠙",
+            "⠉⠙",
+            "⠉⠩",
+            "⠈⢙",
+            "⠈⡙",
+            "⢈⠩",
+            "⡀⢙",
+            "⠄⡙",
+            "⢂⠩",
+            "⡂⢘",
+            "⠅⡘",
+            "⢃⠨",
+            "⡃⢐",
+            "⠍⡐",
+            "⢋⠠",
+            "⡋⢀",
+            "⠍⡁",
+            "⢋⠁",
+            "⡋⠁",
+            "⠍⠉",
+            "⠋⠉",
+            "⠋⠉",
+            "⠉⠙",
+            "⠉⠙",
+            "⠉⠩",
+            "⠈⢙",
+            "⠈⡙",
+            "⠈⠩",
+            "⠀⢙",
+            "⠀⡙",
+            "⠀⠩",
+            "⠀⢘",
+            "⠀⡘",
+            "⠀⠨",
+            "⠀⢐",
+            "⠀⡐",
+            "⠀⠠",
+            "⠀⢀",
+            "⠀⡀",
+        ],
+    },
+    "dots8Bit": {
+        "interval": 80,
+        "frames": "⠀⠁⠂⠃⠄⠅⠆⠇⡀⡁⡂⡃⡄⡅⡆⡇⠈⠉⠊⠋⠌⠍⠎⠏⡈⡉⡊⡋⡌⡍⡎⡏⠐⠑⠒⠓⠔⠕⠖⠗⡐⡑⡒⡓⡔⡕⡖⡗⠘⠙⠚⠛⠜⠝⠞⠟⡘⡙"
+        "⡚⡛⡜⡝⡞⡟⠠⠡⠢⠣⠤⠥⠦⠧⡠⡡⡢⡣⡤⡥⡦⡧⠨⠩⠪⠫⠬⠭⠮⠯⡨⡩⡪⡫⡬⡭⡮⡯⠰⠱⠲⠳⠴⠵⠶⠷⡰⡱⡲⡳⡴⡵⡶⡷⠸⠹⠺⠻"
+        "⠼⠽⠾⠿⡸⡹⡺⡻⡼⡽⡾⡿⢀⢁⢂⢃⢄⢅⢆⢇⣀⣁⣂⣃⣄⣅⣆⣇⢈⢉⢊⢋⢌⢍⢎⢏⣈⣉⣊⣋⣌⣍⣎⣏⢐⢑⢒⢓⢔⢕⢖⢗⣐⣑⣒⣓⣔⣕"
+        "⣖⣗⢘⢙⢚⢛⢜⢝⢞⢟⣘⣙⣚⣛⣜⣝⣞⣟⢠⢡⢢⢣⢤⢥⢦⢧⣠⣡⣢⣣⣤⣥⣦⣧⢨⢩⢪⢫⢬⢭⢮⢯⣨⣩⣪⣫⣬⣭⣮⣯⢰⢱⢲⢳⢴⢵⢶⢷"
+        "⣰⣱⣲⣳⣴⣵⣶⣷⢸⢹⢺⢻⢼⢽⢾⢿⣸⣹⣺⣻⣼⣽⣾⣿",
+    },
+    "line": {"interval": 130, "frames": ["-", "\\", "|", "/"]},
+    "line2": {"interval": 100, "frames": "⠂-–—–-"},
+    "pipe": {"interval": 100, "frames": "┤┘┴└├┌┬┐"},
+    "simpleDots": {"interval": 400, "frames": [".  ", ".. ", "...", "   "]},
+    "simpleDotsScrolling": {
+        "interval": 200,
+        "frames": [".  ", ".. ", "...", " ..", "  .", "   "],
+    },
+    "star": {"interval": 70, "frames": "✶✸✹✺✹✷"},
+    "star2": {"interval": 80, "frames": "+x*"},
+    "flip": {
+        "interval": 70,
+        "frames": "___-``'´-___",
+    },
+    "hamburger": {"interval": 100, "frames": "☱☲☴"},
+    "growVertical": {
+        "interval": 120,
+        "frames": "▁▃▄▅▆▇▆▅▄▃",
+    },
+    "growHorizontal": {
+        "interval": 120,
+        "frames": "▏▎▍▌▋▊▉▊▋▌▍▎",
+    },
+    "balloon": {"interval": 140, "frames": " .oO@* "},
+    "balloon2": {"interval": 120, "frames": ".oO°Oo."},
+    "noise": {"interval": 100, "frames": "▓▒░"},
+    "bounce": {"interval": 120, "frames": "⠁⠂⠄⠂"},
+    "boxBounce": {"interval": 120, "frames": "▖▘▝▗"},
+    "boxBounce2": {"interval": 100, "frames": "▌▀▐▄"},
+    "triangle": {"interval": 50, "frames": "◢◣◤◥"},
+    "arc": {"interval": 100, "frames": "◜◠◝◞◡◟"},
+    "circle": {"interval": 120, "frames": "◡⊙◠"},
+    "squareCorners": {"interval": 180, "frames": "◰◳◲◱"},
+    "circleQuarters": {"interval": 120, "frames": "◴◷◶◵"},
+    "circleHalves": {"interval": 50, "frames": "◐◓◑◒"},
+    "squish": {"interval": 100, "frames": "╫╪"},
+    "toggle": {"interval": 250, "frames": "⊶⊷"},
+    "toggle2": {"interval": 80, "frames": "▫▪"},
+    "toggle3": {"interval": 120, "frames": "□■"},
+    "toggle4": {"interval": 100, "frames": "■□▪▫"},
+    "toggle5": {"interval": 100, "frames": "▮▯"},
+    "toggle6": {"interval": 300, "frames": "ဝ၀"},
+    "toggle7": {"interval": 80, "frames": "⦾⦿"},
+    "toggle8": {"interval": 100, "frames": "◍◌"},
+    "toggle9": {"interval": 100, "frames": "◉◎"},
+    "toggle10": {"interval": 100, "frames": "㊂㊀㊁"},
+    "toggle11": {"interval": 50, "frames": "⧇⧆"},
+    "toggle12": {"interval": 120, "frames": "☗☖"},
+    "toggle13": {"interval": 80, "frames": "=*-"},
+    "arrow": {"interval": 100, "frames": "←↖↑↗→↘↓↙"},
+    "arrow2": {
+        "interval": 80,
+        "frames": ["⬆️ ", "↗️ ", "➡️ ", "↘️ ", "⬇️ ", "↙️ ", "⬅️ ", "↖️ "],
+    },
+    "arrow3": {
+        "interval": 120,
+        "frames": ["▹▹▹▹▹", "▸▹▹▹▹", "▹▸▹▹▹", "▹▹▸▹▹", "▹▹▹▸▹", "▹▹▹▹▸"],
+    },
+    "bouncingBar": {
+        "interval": 80,
+        "frames": [
+            "[    ]",
+            "[=   ]",
+            "[==  ]",
+            "[=== ]",
+            "[ ===]",
+            "[  ==]",
+            "[   =]",
+            "[    ]",
+            "[   =]",
+            "[  ==]",
+            "[ ===]",
+            "[====]",
+            "[=== ]",
+            "[==  ]",
+            "[=   ]",
+        ],
+    },
+    "bouncingBall": {
+        "interval": 80,
+        "frames": [
+            "( ●    )",
+            "(  ●   )",
+            "(   ●  )",
+            "(    ● )",
+            "(     ●)",
+            "(    ● )",
+            "(   ●  )",
+            "(  ●   )",
+            "( ●    )",
+            "(●     )",
+        ],
+    },
+    "smiley": {"interval": 200, "frames": ["😄 ", "😝 "]},
+    "monkey": {"interval": 300, "frames": ["🙈 ", "🙈 ", "🙉 ", "🙊 "]},
+    "hearts": {"interval": 100, "frames": ["💛 ", "💙 ", "💜 ", "💚 ", "❤️ "]},
+    "clock": {
+        "interval": 100,
+        "frames": [
+            "🕛 ",
+            "🕐 ",
+            "🕑 ",
+            "🕒 ",
+            "🕓 ",
+            "🕔 ",
+            "🕕 ",
+            "🕖 ",
+            "🕗 ",
+            "🕘 ",
+            "🕙 ",
+            "🕚 ",
+        ],
+    },
+    "earth": {"interval": 180, "frames": ["🌍 ", "🌎 ", "🌏 "]},
+    "material": {
+        "interval": 17,
+        "frames": [
+            "█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "██▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "███▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "████▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "██████▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "██████▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "███████▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "████████▁▁▁▁▁▁▁▁▁▁▁▁",
+            "█████████▁▁▁▁▁▁▁▁▁▁▁",
+            "█████████▁▁▁▁▁▁▁▁▁▁▁",
+            "██████████▁▁▁▁▁▁▁▁▁▁",
+            "███████████▁▁▁▁▁▁▁▁▁",
+            "█████████████▁▁▁▁▁▁▁",
+            "██████████████▁▁▁▁▁▁",
+            "██████████████▁▁▁▁▁▁",
+            "▁██████████████▁▁▁▁▁",
+            "▁██████████████▁▁▁▁▁",
+            "▁██████████████▁▁▁▁▁",
+            "▁▁██████████████▁▁▁▁",
+            "▁▁▁██████████████▁▁▁",
+            "▁▁▁▁█████████████▁▁▁",
+            "▁▁▁▁██████████████▁▁",
+            "▁▁▁▁██████████████▁▁",
+            "▁▁▁▁▁██████████████▁",
+            "▁▁▁▁▁██████████████▁",
+            "▁▁▁▁▁██████████████▁",
+            "▁▁▁▁▁▁██████████████",
+            "▁▁▁▁▁▁██████████████",
+            "▁▁▁▁▁▁▁█████████████",
+            "▁▁▁▁▁▁▁█████████████",
+            "▁▁▁▁▁▁▁▁████████████",
+            "▁▁▁▁▁▁▁▁████████████",
+            "▁▁▁▁▁▁▁▁▁███████████",
+            "▁▁▁▁▁▁▁▁▁███████████",
+            "▁▁▁▁▁▁▁▁▁▁██████████",
+            "▁▁▁▁▁▁▁▁▁▁██████████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁████████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁███████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁██████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█████",
+            "█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
+            "██▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
+            "██▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
+            "███▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
+            "████▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
+            "█████▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
+            "█████▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
+            "██████▁▁▁▁▁▁▁▁▁▁▁▁▁█",
+            "████████▁▁▁▁▁▁▁▁▁▁▁▁",
+            "█████████▁▁▁▁▁▁▁▁▁▁▁",
+            "█████████▁▁▁▁▁▁▁▁▁▁▁",
+            "█████████▁▁▁▁▁▁▁▁▁▁▁",
+            "█████████▁▁▁▁▁▁▁▁▁▁▁",
+            "███████████▁▁▁▁▁▁▁▁▁",
+            "████████████▁▁▁▁▁▁▁▁",
+            "████████████▁▁▁▁▁▁▁▁",
+            "██████████████▁▁▁▁▁▁",
+            "██████████████▁▁▁▁▁▁",
+            "▁██████████████▁▁▁▁▁",
+            "▁██████████████▁▁▁▁▁",
+            "▁▁▁█████████████▁▁▁▁",
+            "▁▁▁▁▁████████████▁▁▁",
+            "▁▁▁▁▁████████████▁▁▁",
+            "▁▁▁▁▁▁███████████▁▁▁",
+            "▁▁▁▁▁▁▁▁█████████▁▁▁",
+            "▁▁▁▁▁▁▁▁█████████▁▁▁",
+            "▁▁▁▁▁▁▁▁▁█████████▁▁",
+            "▁▁▁▁▁▁▁▁▁█████████▁▁",
+            "▁▁▁▁▁▁▁▁▁▁█████████▁",
+            "▁▁▁▁▁▁▁▁▁▁▁████████▁",
+            "▁▁▁▁▁▁▁▁▁▁▁████████▁",
+            "▁▁▁▁▁▁▁▁▁▁▁▁███████▁",
+            "▁▁▁▁▁▁▁▁▁▁▁▁███████▁",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁███████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁███████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
+        ],
+    },
+    "moon": {
+        "interval": 80,
+        "frames": ["🌑 ", "🌒 ", "🌓 ", "🌔 ", "🌕 ", "🌖 ", "🌗 ", "🌘 "],
+    },
+    "runner": {"interval": 140, "frames": ["🚶 ", "🏃 "]},
+    "pong": {
+        "interval": 80,
+        "frames": [
+            "▐⠂       ▌",
+            "▐⠈       ▌",
+            "▐ ⠂      ▌",
+            "▐ ⠠      ▌",
+            "▐  ⡀     ▌",
+            "▐  ⠠     ▌",
+            "▐   ⠂    ▌",
+            "▐   ⠈    ▌",
+            "▐    ⠂   ▌",
+            "▐    ⠠   ▌",
+            "▐     ⡀  ▌",
+            "▐     ⠠  ▌",
+            "▐      ⠂ ▌",
+            "▐      ⠈ ▌",
+            "▐       ⠂▌",
+            "▐       ⠠▌",
+            "▐       ⡀▌",
+            "▐      ⠠ ▌",
+            "▐      ⠂ ▌",
+            "▐     ⠈  ▌",
+            "▐     ⠂  ▌",
+            "▐    ⠠   ▌",
+            "▐    ⡀   ▌",
+            "▐   ⠠    ▌",
+            "▐   ⠂    ▌",
+            "▐  ⠈     ▌",
+            "▐  ⠂     ▌",
+            "▐ ⠠      ▌",
+            "▐ ⡀      ▌",
+            "▐⠠       ▌",
+        ],
+    },
+    "shark": {
+        "interval": 120,
+        "frames": [
+            "▐|\\____________▌",
+            "▐_|\\___________▌",
+            "▐__|\\__________▌",
+            "▐___|\\_________▌",
+            "▐____|\\________▌",
+            "▐_____|\\_______▌",
+            "▐______|\\______▌",
+            "▐_______|\\_____▌",
+            "▐________|\\____▌",
+            "▐_________|\\___▌",
+            "▐__________|\\__▌",
+            "▐___________|\\_▌",
+            "▐____________|\\▌",
+            "▐____________/|▌",
+            "▐___________/|_▌",
+            "▐__________/|__▌",
+            "▐_________/|___▌",
+            "▐________/|____▌",
+            "▐_______/|_____▌",
+            "▐______/|______▌",
+            "▐_____/|_______▌",
+            "▐____/|________▌",
+            "▐___/|_________▌",
+            "▐__/|__________▌",
+            "▐_/|___________▌",
+            "▐/|____________▌",
+        ],
+    },
+    "dqpb": {"interval": 100, "frames": "dqpb"},
+    "weather": {
+        "interval": 100,
+        "frames": [
+            "☀️ ",
+            "☀️ ",
+            "☀️ ",
+            "🌤 ",
+            "⛅️ ",
+            "🌥 ",
+            "☁️ ",
+            "🌧 ",
+            "🌨 ",
+            "🌧 ",
+            "🌨 ",
+            "🌧 ",
+            "🌨 ",
+            "⛈ ",
+            "🌨 ",
+            "🌧 ",
+            "🌨 ",
+            "☁️ ",
+            "🌥 ",
+            "⛅️ ",
+            "🌤 ",
+            "☀️ ",
+            "☀️ ",
+        ],
+    },
+    "christmas": {"interval": 400, "frames": "🌲🎄"},
+    "grenade": {
+        "interval": 80,
+        "frames": [
+            "،   ",
+            "′   ",
+            " ´ ",
+            " ‾ ",
+            "  ⸌",
+            "  ⸊",
+            "  |",
+            "  ⁎",
+            "  ⁕",
+            " ෴ ",
+            "  ⁓",
+            "   ",
+            "   ",
+            "   ",
+        ],
+    },
+    "point": {"interval": 125, "frames": ["∙∙∙", "●∙∙", "∙●∙", "∙∙●", "∙∙∙"]},
+    "layer": {"interval": 150, "frames": "-=≡"},
+    "betaWave": {
+        "interval": 80,
+        "frames": [
+            "ρββββββ",
+            "βρβββββ",
+            "ββρββββ",
+            "βββρβββ",
+            "ββββρββ",
+            "βββββρβ",
+            "ββββββρ",
+        ],
+    },
+    "aesthetic": {
+        "interval": 80,
+        "frames": [
+            "▰▱▱▱▱▱▱",
+            "▰▰▱▱▱▱▱",
+            "▰▰▰▱▱▱▱",
+            "▰▰▰▰▱▱▱",
+            "▰▰▰▰▰▱▱",
+            "▰▰▰▰▰▰▱",
+            "▰▰▰▰▰▰▰",
+            "▰▱▱▱▱▱▱",
+        ],
+    },
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_stack.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_stack.py
new file mode 100644
index 0000000000000000000000000000000000000000..194564e761ddae165b39ef6598877e2e3820af0a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_stack.py
@@ -0,0 +1,16 @@
+from typing import List, TypeVar
+
+T = TypeVar("T")
+
+
+class Stack(List[T]):
+    """A small shim over builtin list."""
+
+    @property
+    def top(self) -> T:
+        """Get top of stack."""
+        return self[-1]
+
+    def push(self, item: T) -> None:
+        """Push an item on to the stack (append in stack nomenclature)."""
+        self.append(item)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_timer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_timer.py
new file mode 100644
index 0000000000000000000000000000000000000000..a2ca6be03c43054caaa3660998273ebf704345dd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_timer.py
@@ -0,0 +1,19 @@
+"""
+Timer context manager, only used in debug.
+
+"""
+
+from time import time
+
+import contextlib
+from typing import Generator
+
+
+@contextlib.contextmanager
+def timer(subject: str = "time") -> Generator[None, None, None]:
+    """print the elapsed time. (only used in debugging)"""
+    start = time()
+    yield
+    elapsed = time() - start
+    elapsed_ms = elapsed * 1000
+    print(f"{subject} elapsed {elapsed_ms:.1f}ms")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_win32_console.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_win32_console.py
new file mode 100644
index 0000000000000000000000000000000000000000..81b1082905338a74b72b9de432ece50a456687bc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_win32_console.py
@@ -0,0 +1,662 @@
+"""Light wrapper around the Win32 Console API - this module should only be imported on Windows
+
+The API that this module wraps is documented at https://docs.microsoft.com/en-us/windows/console/console-functions
+"""
+import ctypes
+import sys
+from typing import Any
+
+windll: Any = None
+if sys.platform == "win32":
+    windll = ctypes.LibraryLoader(ctypes.WinDLL)
+else:
+    raise ImportError(f"{__name__} can only be imported on Windows")
+
+import time
+from ctypes import Structure, byref, wintypes
+from typing import IO, NamedTuple, Type, cast
+
+from pip._vendor.rich.color import ColorSystem
+from pip._vendor.rich.style import Style
+
+STDOUT = -11
+ENABLE_VIRTUAL_TERMINAL_PROCESSING = 4
+
+COORD = wintypes._COORD
+
+
+class LegacyWindowsError(Exception):
+    pass
+
+
+class WindowsCoordinates(NamedTuple):
+    """Coordinates in the Windows Console API are (y, x), not (x, y).
+    This class is intended to prevent that confusion.
+    Rows and columns are indexed from 0.
+    This class can be used in place of wintypes._COORD in arguments and argtypes.
+    """
+
+    row: int
+    col: int
+
+    @classmethod
+    def from_param(cls, value: "WindowsCoordinates") -> COORD:
+        """Converts a WindowsCoordinates into a wintypes _COORD structure.
+        This classmethod is internally called by ctypes to perform the conversion.
+
+        Args:
+            value (WindowsCoordinates): The input coordinates to convert.
+
+        Returns:
+            wintypes._COORD: The converted coordinates struct.
+        """
+        return COORD(value.col, value.row)
+
+
+class CONSOLE_SCREEN_BUFFER_INFO(Structure):
+    _fields_ = [
+        ("dwSize", COORD),
+        ("dwCursorPosition", COORD),
+        ("wAttributes", wintypes.WORD),
+        ("srWindow", wintypes.SMALL_RECT),
+        ("dwMaximumWindowSize", COORD),
+    ]
+
+
+class CONSOLE_CURSOR_INFO(ctypes.Structure):
+    _fields_ = [("dwSize", wintypes.DWORD), ("bVisible", wintypes.BOOL)]
+
+
+_GetStdHandle = windll.kernel32.GetStdHandle
+_GetStdHandle.argtypes = [
+    wintypes.DWORD,
+]
+_GetStdHandle.restype = wintypes.HANDLE
+
+
+def GetStdHandle(handle: int = STDOUT) -> wintypes.HANDLE:
+    """Retrieves a handle to the specified standard device (standard input, standard output, or standard error).
+
+    Args:
+        handle (int): Integer identifier for the handle. Defaults to -11 (stdout).
+
+    Returns:
+        wintypes.HANDLE: The handle
+    """
+    return cast(wintypes.HANDLE, _GetStdHandle(handle))
+
+
+_GetConsoleMode = windll.kernel32.GetConsoleMode
+_GetConsoleMode.argtypes = [wintypes.HANDLE, wintypes.LPDWORD]
+_GetConsoleMode.restype = wintypes.BOOL
+
+
+def GetConsoleMode(std_handle: wintypes.HANDLE) -> int:
+    """Retrieves the current input mode of a console's input buffer
+    or the current output mode of a console screen buffer.
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+
+    Raises:
+        LegacyWindowsError: If any error occurs while calling the Windows console API.
+
+    Returns:
+        int: Value representing the current console mode as documented at
+            https://docs.microsoft.com/en-us/windows/console/getconsolemode#parameters
+    """
+
+    console_mode = wintypes.DWORD()
+    success = bool(_GetConsoleMode(std_handle, console_mode))
+    if not success:
+        raise LegacyWindowsError("Unable to get legacy Windows Console Mode")
+    return console_mode.value
+
+
+_FillConsoleOutputCharacterW = windll.kernel32.FillConsoleOutputCharacterW
+_FillConsoleOutputCharacterW.argtypes = [
+    wintypes.HANDLE,
+    ctypes.c_char,
+    wintypes.DWORD,
+    cast(Type[COORD], WindowsCoordinates),
+    ctypes.POINTER(wintypes.DWORD),
+]
+_FillConsoleOutputCharacterW.restype = wintypes.BOOL
+
+
+def FillConsoleOutputCharacter(
+    std_handle: wintypes.HANDLE,
+    char: str,
+    length: int,
+    start: WindowsCoordinates,
+) -> int:
+    """Writes a character to the console screen buffer a specified number of times, beginning at the specified coordinates.
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+        char (str): The character to write. Must be a string of length 1.
+        length (int): The number of times to write the character.
+        start (WindowsCoordinates): The coordinates to start writing at.
+
+    Returns:
+        int: The number of characters written.
+    """
+    character = ctypes.c_char(char.encode())
+    num_characters = wintypes.DWORD(length)
+    num_written = wintypes.DWORD(0)
+    _FillConsoleOutputCharacterW(
+        std_handle,
+        character,
+        num_characters,
+        start,
+        byref(num_written),
+    )
+    return num_written.value
+
+
+_FillConsoleOutputAttribute = windll.kernel32.FillConsoleOutputAttribute
+_FillConsoleOutputAttribute.argtypes = [
+    wintypes.HANDLE,
+    wintypes.WORD,
+    wintypes.DWORD,
+    cast(Type[COORD], WindowsCoordinates),
+    ctypes.POINTER(wintypes.DWORD),
+]
+_FillConsoleOutputAttribute.restype = wintypes.BOOL
+
+
+def FillConsoleOutputAttribute(
+    std_handle: wintypes.HANDLE,
+    attributes: int,
+    length: int,
+    start: WindowsCoordinates,
+) -> int:
+    """Sets the character attributes for a specified number of character cells,
+    beginning at the specified coordinates in a screen buffer.
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+        attributes (int): Integer value representing the foreground and background colours of the cells.
+        length (int): The number of cells to set the output attribute of.
+        start (WindowsCoordinates): The coordinates of the first cell whose attributes are to be set.
+
+    Returns:
+        int: The number of cells whose attributes were actually set.
+    """
+    num_cells = wintypes.DWORD(length)
+    style_attrs = wintypes.WORD(attributes)
+    num_written = wintypes.DWORD(0)
+    _FillConsoleOutputAttribute(
+        std_handle, style_attrs, num_cells, start, byref(num_written)
+    )
+    return num_written.value
+
+
+_SetConsoleTextAttribute = windll.kernel32.SetConsoleTextAttribute
+_SetConsoleTextAttribute.argtypes = [
+    wintypes.HANDLE,
+    wintypes.WORD,
+]
+_SetConsoleTextAttribute.restype = wintypes.BOOL
+
+
+def SetConsoleTextAttribute(
+    std_handle: wintypes.HANDLE, attributes: wintypes.WORD
+) -> bool:
+    """Set the colour attributes for all text written after this function is called.
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+        attributes (int): Integer value representing the foreground and background colours.
+
+
+    Returns:
+        bool: True if the attribute was set successfully, otherwise False.
+    """
+    return bool(_SetConsoleTextAttribute(std_handle, attributes))
+
+
+_GetConsoleScreenBufferInfo = windll.kernel32.GetConsoleScreenBufferInfo
+_GetConsoleScreenBufferInfo.argtypes = [
+    wintypes.HANDLE,
+    ctypes.POINTER(CONSOLE_SCREEN_BUFFER_INFO),
+]
+_GetConsoleScreenBufferInfo.restype = wintypes.BOOL
+
+
+def GetConsoleScreenBufferInfo(
+    std_handle: wintypes.HANDLE,
+) -> CONSOLE_SCREEN_BUFFER_INFO:
+    """Retrieves information about the specified console screen buffer.
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+
+    Returns:
+        CONSOLE_SCREEN_BUFFER_INFO: A CONSOLE_SCREEN_BUFFER_INFO ctype struct contain information about
+            screen size, cursor position, colour attributes, and more."""
+    console_screen_buffer_info = CONSOLE_SCREEN_BUFFER_INFO()
+    _GetConsoleScreenBufferInfo(std_handle, byref(console_screen_buffer_info))
+    return console_screen_buffer_info
+
+
+_SetConsoleCursorPosition = windll.kernel32.SetConsoleCursorPosition
+_SetConsoleCursorPosition.argtypes = [
+    wintypes.HANDLE,
+    cast(Type[COORD], WindowsCoordinates),
+]
+_SetConsoleCursorPosition.restype = wintypes.BOOL
+
+
+def SetConsoleCursorPosition(
+    std_handle: wintypes.HANDLE, coords: WindowsCoordinates
+) -> bool:
+    """Set the position of the cursor in the console screen
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+        coords (WindowsCoordinates): The coordinates to move the cursor to.
+
+    Returns:
+        bool: True if the function succeeds, otherwise False.
+    """
+    return bool(_SetConsoleCursorPosition(std_handle, coords))
+
+
+_GetConsoleCursorInfo = windll.kernel32.GetConsoleCursorInfo
+_GetConsoleCursorInfo.argtypes = [
+    wintypes.HANDLE,
+    ctypes.POINTER(CONSOLE_CURSOR_INFO),
+]
+_GetConsoleCursorInfo.restype = wintypes.BOOL
+
+
+def GetConsoleCursorInfo(
+    std_handle: wintypes.HANDLE, cursor_info: CONSOLE_CURSOR_INFO
+) -> bool:
+    """Get the cursor info - used to get cursor visibility and width
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+        cursor_info (CONSOLE_CURSOR_INFO): CONSOLE_CURSOR_INFO ctype struct that receives information
+            about the console's cursor.
+
+    Returns:
+          bool: True if the function succeeds, otherwise False.
+    """
+    return bool(_GetConsoleCursorInfo(std_handle, byref(cursor_info)))
+
+
+_SetConsoleCursorInfo = windll.kernel32.SetConsoleCursorInfo
+_SetConsoleCursorInfo.argtypes = [
+    wintypes.HANDLE,
+    ctypes.POINTER(CONSOLE_CURSOR_INFO),
+]
+_SetConsoleCursorInfo.restype = wintypes.BOOL
+
+
+def SetConsoleCursorInfo(
+    std_handle: wintypes.HANDLE, cursor_info: CONSOLE_CURSOR_INFO
+) -> bool:
+    """Set the cursor info - used for adjusting cursor visibility and width
+
+    Args:
+        std_handle (wintypes.HANDLE): A handle to the console input buffer or the console screen buffer.
+        cursor_info (CONSOLE_CURSOR_INFO): CONSOLE_CURSOR_INFO ctype struct containing the new cursor info.
+
+    Returns:
+          bool: True if the function succeeds, otherwise False.
+    """
+    return bool(_SetConsoleCursorInfo(std_handle, byref(cursor_info)))
+
+
+_SetConsoleTitle = windll.kernel32.SetConsoleTitleW
+_SetConsoleTitle.argtypes = [wintypes.LPCWSTR]
+_SetConsoleTitle.restype = wintypes.BOOL
+
+
+def SetConsoleTitle(title: str) -> bool:
+    """Sets the title of the current console window
+
+    Args:
+        title (str): The new title of the console window.
+
+    Returns:
+        bool: True if the function succeeds, otherwise False.
+    """
+    return bool(_SetConsoleTitle(title))
+
+
+class LegacyWindowsTerm:
+    """This class allows interaction with the legacy Windows Console API. It should only be used in the context
+    of environments where virtual terminal processing is not available. However, if it is used in a Windows environment,
+    the entire API should work.
+
+    Args:
+        file (IO[str]): The file which the Windows Console API HANDLE is retrieved from, defaults to sys.stdout.
+    """
+
+    BRIGHT_BIT = 8
+
+    # Indices are ANSI color numbers, values are the corresponding Windows Console API color numbers
+    ANSI_TO_WINDOWS = [
+        0,  # black                      The Windows colours are defined in wincon.h as follows:
+        4,  # red                         define FOREGROUND_BLUE            0x0001 -- 0000 0001
+        2,  # green                       define FOREGROUND_GREEN           0x0002 -- 0000 0010
+        6,  # yellow                      define FOREGROUND_RED             0x0004 -- 0000 0100
+        1,  # blue                        define FOREGROUND_INTENSITY       0x0008 -- 0000 1000
+        5,  # magenta                     define BACKGROUND_BLUE            0x0010 -- 0001 0000
+        3,  # cyan                        define BACKGROUND_GREEN           0x0020 -- 0010 0000
+        7,  # white                       define BACKGROUND_RED             0x0040 -- 0100 0000
+        8,  # bright black (grey)         define BACKGROUND_INTENSITY       0x0080 -- 1000 0000
+        12,  # bright red
+        10,  # bright green
+        14,  # bright yellow
+        9,  # bright blue
+        13,  # bright magenta
+        11,  # bright cyan
+        15,  # bright white
+    ]
+
+    def __init__(self, file: "IO[str]") -> None:
+        handle = GetStdHandle(STDOUT)
+        self._handle = handle
+        default_text = GetConsoleScreenBufferInfo(handle).wAttributes
+        self._default_text = default_text
+
+        self._default_fore = default_text & 7
+        self._default_back = (default_text >> 4) & 7
+        self._default_attrs = self._default_fore | (self._default_back << 4)
+
+        self._file = file
+        self.write = file.write
+        self.flush = file.flush
+
+    @property
+    def cursor_position(self) -> WindowsCoordinates:
+        """Returns the current position of the cursor (0-based)
+
+        Returns:
+            WindowsCoordinates: The current cursor position.
+        """
+        coord: COORD = GetConsoleScreenBufferInfo(self._handle).dwCursorPosition
+        return WindowsCoordinates(row=cast(int, coord.Y), col=cast(int, coord.X))
+
+    @property
+    def screen_size(self) -> WindowsCoordinates:
+        """Returns the current size of the console screen buffer, in character columns and rows
+
+        Returns:
+            WindowsCoordinates: The width and height of the screen as WindowsCoordinates.
+        """
+        screen_size: COORD = GetConsoleScreenBufferInfo(self._handle).dwSize
+        return WindowsCoordinates(
+            row=cast(int, screen_size.Y), col=cast(int, screen_size.X)
+        )
+
+    def write_text(self, text: str) -> None:
+        """Write text directly to the terminal without any modification of styles
+
+        Args:
+            text (str): The text to write to the console
+        """
+        self.write(text)
+        self.flush()
+
+    def write_styled(self, text: str, style: Style) -> None:
+        """Write styled text to the terminal.
+
+        Args:
+            text (str): The text to write
+            style (Style): The style of the text
+        """
+        color = style.color
+        bgcolor = style.bgcolor
+        if style.reverse:
+            color, bgcolor = bgcolor, color
+
+        if color:
+            fore = color.downgrade(ColorSystem.WINDOWS).number
+            fore = fore if fore is not None else 7  # Default to ANSI 7: White
+            if style.bold:
+                fore = fore | self.BRIGHT_BIT
+            if style.dim:
+                fore = fore & ~self.BRIGHT_BIT
+            fore = self.ANSI_TO_WINDOWS[fore]
+        else:
+            fore = self._default_fore
+
+        if bgcolor:
+            back = bgcolor.downgrade(ColorSystem.WINDOWS).number
+            back = back if back is not None else 0  # Default to ANSI 0: Black
+            back = self.ANSI_TO_WINDOWS[back]
+        else:
+            back = self._default_back
+
+        assert fore is not None
+        assert back is not None
+
+        SetConsoleTextAttribute(
+            self._handle, attributes=ctypes.c_ushort(fore | (back << 4))
+        )
+        self.write_text(text)
+        SetConsoleTextAttribute(self._handle, attributes=self._default_text)
+
+    def move_cursor_to(self, new_position: WindowsCoordinates) -> None:
+        """Set the position of the cursor
+
+        Args:
+            new_position (WindowsCoordinates): The WindowsCoordinates representing the new position of the cursor.
+        """
+        if new_position.col < 0 or new_position.row < 0:
+            return
+        SetConsoleCursorPosition(self._handle, coords=new_position)
+
+    def erase_line(self) -> None:
+        """Erase all content on the line the cursor is currently located at"""
+        screen_size = self.screen_size
+        cursor_position = self.cursor_position
+        cells_to_erase = screen_size.col
+        start_coordinates = WindowsCoordinates(row=cursor_position.row, col=0)
+        FillConsoleOutputCharacter(
+            self._handle, " ", length=cells_to_erase, start=start_coordinates
+        )
+        FillConsoleOutputAttribute(
+            self._handle,
+            self._default_attrs,
+            length=cells_to_erase,
+            start=start_coordinates,
+        )
+
+    def erase_end_of_line(self) -> None:
+        """Erase all content from the cursor position to the end of that line"""
+        cursor_position = self.cursor_position
+        cells_to_erase = self.screen_size.col - cursor_position.col
+        FillConsoleOutputCharacter(
+            self._handle, " ", length=cells_to_erase, start=cursor_position
+        )
+        FillConsoleOutputAttribute(
+            self._handle,
+            self._default_attrs,
+            length=cells_to_erase,
+            start=cursor_position,
+        )
+
+    def erase_start_of_line(self) -> None:
+        """Erase all content from the cursor position to the start of that line"""
+        row, col = self.cursor_position
+        start = WindowsCoordinates(row, 0)
+        FillConsoleOutputCharacter(self._handle, " ", length=col, start=start)
+        FillConsoleOutputAttribute(
+            self._handle, self._default_attrs, length=col, start=start
+        )
+
+    def move_cursor_up(self) -> None:
+        """Move the cursor up a single cell"""
+        cursor_position = self.cursor_position
+        SetConsoleCursorPosition(
+            self._handle,
+            coords=WindowsCoordinates(
+                row=cursor_position.row - 1, col=cursor_position.col
+            ),
+        )
+
+    def move_cursor_down(self) -> None:
+        """Move the cursor down a single cell"""
+        cursor_position = self.cursor_position
+        SetConsoleCursorPosition(
+            self._handle,
+            coords=WindowsCoordinates(
+                row=cursor_position.row + 1,
+                col=cursor_position.col,
+            ),
+        )
+
+    def move_cursor_forward(self) -> None:
+        """Move the cursor forward a single cell. Wrap to the next line if required."""
+        row, col = self.cursor_position
+        if col == self.screen_size.col - 1:
+            row += 1
+            col = 0
+        else:
+            col += 1
+        SetConsoleCursorPosition(
+            self._handle, coords=WindowsCoordinates(row=row, col=col)
+        )
+
+    def move_cursor_to_column(self, column: int) -> None:
+        """Move cursor to the column specified by the zero-based column index, staying on the same row
+
+        Args:
+            column (int): The zero-based column index to move the cursor to.
+        """
+        row, _ = self.cursor_position
+        SetConsoleCursorPosition(self._handle, coords=WindowsCoordinates(row, column))
+
+    def move_cursor_backward(self) -> None:
+        """Move the cursor backward a single cell. Wrap to the previous line if required."""
+        row, col = self.cursor_position
+        if col == 0:
+            row -= 1
+            col = self.screen_size.col - 1
+        else:
+            col -= 1
+        SetConsoleCursorPosition(
+            self._handle, coords=WindowsCoordinates(row=row, col=col)
+        )
+
+    def hide_cursor(self) -> None:
+        """Hide the cursor"""
+        current_cursor_size = self._get_cursor_size()
+        invisible_cursor = CONSOLE_CURSOR_INFO(dwSize=current_cursor_size, bVisible=0)
+        SetConsoleCursorInfo(self._handle, cursor_info=invisible_cursor)
+
+    def show_cursor(self) -> None:
+        """Show the cursor"""
+        current_cursor_size = self._get_cursor_size()
+        visible_cursor = CONSOLE_CURSOR_INFO(dwSize=current_cursor_size, bVisible=1)
+        SetConsoleCursorInfo(self._handle, cursor_info=visible_cursor)
+
+    def set_title(self, title: str) -> None:
+        """Set the title of the terminal window
+
+        Args:
+            title (str): The new title of the console window
+        """
+        assert len(title) < 255, "Console title must be less than 255 characters"
+        SetConsoleTitle(title)
+
+    def _get_cursor_size(self) -> int:
+        """Get the percentage of the character cell that is filled by the cursor"""
+        cursor_info = CONSOLE_CURSOR_INFO()
+        GetConsoleCursorInfo(self._handle, cursor_info=cursor_info)
+        return int(cursor_info.dwSize)
+
+
+if __name__ == "__main__":
+    handle = GetStdHandle()
+
+    from pip._vendor.rich.console import Console
+
+    console = Console()
+
+    term = LegacyWindowsTerm(sys.stdout)
+    term.set_title("Win32 Console Examples")
+
+    style = Style(color="black", bgcolor="red")
+
+    heading = Style.parse("black on green")
+
+    # Check colour output
+    console.rule("Checking colour output")
+    console.print("[on red]on red!")
+    console.print("[blue]blue!")
+    console.print("[yellow]yellow!")
+    console.print("[bold yellow]bold yellow!")
+    console.print("[bright_yellow]bright_yellow!")
+    console.print("[dim bright_yellow]dim bright_yellow!")
+    console.print("[italic cyan]italic cyan!")
+    console.print("[bold white on blue]bold white on blue!")
+    console.print("[reverse bold white on blue]reverse bold white on blue!")
+    console.print("[bold black on cyan]bold black on cyan!")
+    console.print("[black on green]black on green!")
+    console.print("[blue on green]blue on green!")
+    console.print("[white on black]white on black!")
+    console.print("[black on white]black on white!")
+    console.print("[#1BB152 on #DA812D]#1BB152 on #DA812D!")
+
+    # Check cursor movement
+    console.rule("Checking cursor movement")
+    console.print()
+    term.move_cursor_backward()
+    term.move_cursor_backward()
+    term.write_text("went back and wrapped to prev line")
+    time.sleep(1)
+    term.move_cursor_up()
+    term.write_text("we go up")
+    time.sleep(1)
+    term.move_cursor_down()
+    term.write_text("and down")
+    time.sleep(1)
+    term.move_cursor_up()
+    term.move_cursor_backward()
+    term.move_cursor_backward()
+    term.write_text("we went up and back 2")
+    time.sleep(1)
+    term.move_cursor_down()
+    term.move_cursor_backward()
+    term.move_cursor_backward()
+    term.write_text("we went down and back 2")
+    time.sleep(1)
+
+    # Check erasing of lines
+    term.hide_cursor()
+    console.print()
+    console.rule("Checking line erasing")
+    console.print("\n...Deleting to the start of the line...")
+    term.write_text("The red arrow shows the cursor location, and direction of erase")
+    time.sleep(1)
+    term.move_cursor_to_column(16)
+    term.write_styled("<", Style.parse("black on red"))
+    term.move_cursor_backward()
+    time.sleep(1)
+    term.erase_start_of_line()
+    time.sleep(1)
+
+    console.print("\n\n...And to the end of the line...")
+    term.write_text("The red arrow shows the cursor location, and direction of erase")
+    time.sleep(1)
+
+    term.move_cursor_to_column(16)
+    term.write_styled(">", Style.parse("black on red"))
+    time.sleep(1)
+    term.erase_end_of_line()
+    time.sleep(1)
+
+    console.print("\n\n...Now the whole line will be erased...")
+    term.write_styled("I'm going to disappear!", style=Style.parse("black on cyan"))
+    time.sleep(1)
+    term.erase_line()
+
+    term.show_cursor()
+    print("\n")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_windows.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_windows.py
new file mode 100644
index 0000000000000000000000000000000000000000..10fc0d7e9f398dd550a42c6b8c0637684882ee60
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_windows.py
@@ -0,0 +1,72 @@
+import sys
+from dataclasses import dataclass
+
+
+@dataclass
+class WindowsConsoleFeatures:
+    """Windows features available."""
+
+    vt: bool = False
+    """The console supports VT codes."""
+    truecolor: bool = False
+    """The console supports truecolor."""
+
+
+try:
+    import ctypes
+    from ctypes import LibraryLoader
+
+    if sys.platform == "win32":
+        windll = LibraryLoader(ctypes.WinDLL)
+    else:
+        windll = None
+        raise ImportError("Not windows")
+
+    from pip._vendor.rich._win32_console import (
+        ENABLE_VIRTUAL_TERMINAL_PROCESSING,
+        GetConsoleMode,
+        GetStdHandle,
+        LegacyWindowsError,
+    )
+
+except (AttributeError, ImportError, ValueError):
+
+    # Fallback if we can't load the Windows DLL
+    def get_windows_console_features() -> WindowsConsoleFeatures:
+        features = WindowsConsoleFeatures()
+        return features
+
+else:
+
+    def get_windows_console_features() -> WindowsConsoleFeatures:
+        """Get windows console features.
+
+        Returns:
+            WindowsConsoleFeatures: An instance of WindowsConsoleFeatures.
+        """
+        handle = GetStdHandle()
+        try:
+            console_mode = GetConsoleMode(handle)
+            success = True
+        except LegacyWindowsError:
+            console_mode = 0
+            success = False
+        vt = bool(success and console_mode & ENABLE_VIRTUAL_TERMINAL_PROCESSING)
+        truecolor = False
+        if vt:
+            win_version = sys.getwindowsversion()
+            truecolor = win_version.major > 10 or (
+                win_version.major == 10 and win_version.build >= 15063
+            )
+        features = WindowsConsoleFeatures(vt=vt, truecolor=truecolor)
+        return features
+
+
+if __name__ == "__main__":
+    import platform
+
+    features = get_windows_console_features()
+    from pip._vendor.rich import print
+
+    print(f'platform="{platform.system()}"')
+    print(repr(features))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_windows_renderer.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_windows_renderer.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ece05649e7268a75c82de6ced552619ffc093ab
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_windows_renderer.py
@@ -0,0 +1,56 @@
+from typing import Iterable, Sequence, Tuple, cast
+
+from pip._vendor.rich._win32_console import LegacyWindowsTerm, WindowsCoordinates
+from pip._vendor.rich.segment import ControlCode, ControlType, Segment
+
+
+def legacy_windows_render(buffer: Iterable[Segment], term: LegacyWindowsTerm) -> None:
+    """Makes appropriate Windows Console API calls based on the segments in the buffer.
+
+    Args:
+        buffer (Iterable[Segment]): Iterable of Segments to convert to Win32 API calls.
+        term (LegacyWindowsTerm): Used to call the Windows Console API.
+    """
+    for text, style, control in buffer:
+        if not control:
+            if style:
+                term.write_styled(text, style)
+            else:
+                term.write_text(text)
+        else:
+            control_codes: Sequence[ControlCode] = control
+            for control_code in control_codes:
+                control_type = control_code[0]
+                if control_type == ControlType.CURSOR_MOVE_TO:
+                    _, x, y = cast(Tuple[ControlType, int, int], control_code)
+                    term.move_cursor_to(WindowsCoordinates(row=y - 1, col=x - 1))
+                elif control_type == ControlType.CARRIAGE_RETURN:
+                    term.write_text("\r")
+                elif control_type == ControlType.HOME:
+                    term.move_cursor_to(WindowsCoordinates(0, 0))
+                elif control_type == ControlType.CURSOR_UP:
+                    term.move_cursor_up()
+                elif control_type == ControlType.CURSOR_DOWN:
+                    term.move_cursor_down()
+                elif control_type == ControlType.CURSOR_FORWARD:
+                    term.move_cursor_forward()
+                elif control_type == ControlType.CURSOR_BACKWARD:
+                    term.move_cursor_backward()
+                elif control_type == ControlType.CURSOR_MOVE_TO_COLUMN:
+                    _, column = cast(Tuple[ControlType, int], control_code)
+                    term.move_cursor_to_column(column - 1)
+                elif control_type == ControlType.HIDE_CURSOR:
+                    term.hide_cursor()
+                elif control_type == ControlType.SHOW_CURSOR:
+                    term.show_cursor()
+                elif control_type == ControlType.ERASE_IN_LINE:
+                    _, mode = cast(Tuple[ControlType, int], control_code)
+                    if mode == 0:
+                        term.erase_end_of_line()
+                    elif mode == 1:
+                        term.erase_start_of_line()
+                    elif mode == 2:
+                        term.erase_line()
+                elif control_type == ControlType.SET_WINDOW_TITLE:
+                    _, title = cast(Tuple[ControlType, str], control_code)
+                    term.set_title(title)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_wrap.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_wrap.py
new file mode 100644
index 0000000000000000000000000000000000000000..c45f193f74ad7385c84f3b935663198415cfaa4b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/_wrap.py
@@ -0,0 +1,56 @@
+import re
+from typing import Iterable, List, Tuple
+
+from ._loop import loop_last
+from .cells import cell_len, chop_cells
+
+re_word = re.compile(r"\s*\S+\s*")
+
+
+def words(text: str) -> Iterable[Tuple[int, int, str]]:
+    position = 0
+    word_match = re_word.match(text, position)
+    while word_match is not None:
+        start, end = word_match.span()
+        word = word_match.group(0)
+        yield start, end, word
+        word_match = re_word.match(text, end)
+
+
+def divide_line(text: str, width: int, fold: bool = True) -> List[int]:
+    divides: List[int] = []
+    append = divides.append
+    line_position = 0
+    _cell_len = cell_len
+    for start, _end, word in words(text):
+        word_length = _cell_len(word.rstrip())
+        if line_position + word_length > width:
+            if word_length > width:
+                if fold:
+                    chopped_words = chop_cells(word, max_size=width, position=0)
+                    for last, line in loop_last(chopped_words):
+                        if start:
+                            append(start)
+
+                        if last:
+                            line_position = _cell_len(line)
+                        else:
+                            start += len(line)
+                else:
+                    if start:
+                        append(start)
+                    line_position = _cell_len(word)
+            elif line_position and start:
+                append(start)
+                line_position = _cell_len(word)
+        else:
+            line_position += _cell_len(word)
+    return divides
+
+
+if __name__ == "__main__":  # pragma: no cover
+    from .console import Console
+
+    console = Console(width=10)
+    console.print("12345 abcdefghijklmnopqrstuvwyxzABCDEFGHIJKLMNOPQRSTUVWXYZ 12345")
+    print(chop_cells("abcdefghijklmnopqrstuvwxyz", 10, position=2))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/abc.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/abc.py
new file mode 100644
index 0000000000000000000000000000000000000000..e6e498efabfab0dcf31cd7731f8f821cc423bc4f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/abc.py
@@ -0,0 +1,33 @@
+from abc import ABC
+
+
+class RichRenderable(ABC):
+    """An abstract base class for Rich renderables.
+
+    Note that there is no need to extend this class, the intended use is to check if an
+    object supports the Rich renderable protocol. For example::
+
+        if isinstance(my_object, RichRenderable):
+            console.print(my_object)
+
+    """
+
+    @classmethod
+    def __subclasshook__(cls, other: type) -> bool:
+        """Check if this class supports the rich render protocol."""
+        return hasattr(other, "__rich_console__") or hasattr(other, "__rich__")
+
+
+if __name__ == "__main__":  # pragma: no cover
+    from pip._vendor.rich.text import Text
+
+    t = Text()
+    print(isinstance(Text, RichRenderable))
+    print(isinstance(t, RichRenderable))
+
+    class Foo:
+        pass
+
+    f = Foo()
+    print(isinstance(f, RichRenderable))
+    print(isinstance("", RichRenderable))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/align.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/align.py
new file mode 100644
index 0000000000000000000000000000000000000000..d5abb5947325728d0645cb4b7c701bb0b1c06d48
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/align.py
@@ -0,0 +1,311 @@
+import sys
+from itertools import chain
+from typing import TYPE_CHECKING, Iterable, Optional
+
+if sys.version_info >= (3, 8):
+    from typing import Literal
+else:
+    from pip._vendor.typing_extensions import Literal  # pragma: no cover
+
+from .constrain import Constrain
+from .jupyter import JupyterMixin
+from .measure import Measurement
+from .segment import Segment
+from .style import StyleType
+
+if TYPE_CHECKING:
+    from .console import Console, ConsoleOptions, RenderableType, RenderResult
+
+AlignMethod = Literal["left", "center", "right"]
+VerticalAlignMethod = Literal["top", "middle", "bottom"]
+
+
+class Align(JupyterMixin):
+    """Align a renderable by adding spaces if necessary.
+
+    Args:
+        renderable (RenderableType): A console renderable.
+        align (AlignMethod): One of "left", "center", or "right""
+        style (StyleType, optional): An optional style to apply to the background.
+        vertical (Optional[VerticalAlginMethod], optional): Optional vertical align, one of "top", "middle", or "bottom". Defaults to None.
+        pad (bool, optional): Pad the right with spaces. Defaults to True.
+        width (int, optional): Restrict contents to given width, or None to use default width. Defaults to None.
+        height (int, optional): Set height of align renderable, or None to fit to contents. Defaults to None.
+
+    Raises:
+        ValueError: if ``align`` is not one of the expected values.
+    """
+
+    def __init__(
+        self,
+        renderable: "RenderableType",
+        align: AlignMethod = "left",
+        style: Optional[StyleType] = None,
+        *,
+        vertical: Optional[VerticalAlignMethod] = None,
+        pad: bool = True,
+        width: Optional[int] = None,
+        height: Optional[int] = None,
+    ) -> None:
+        if align not in ("left", "center", "right"):
+            raise ValueError(
+                f'invalid value for align, expected "left", "center", or "right" (not {align!r})'
+            )
+        if vertical is not None and vertical not in ("top", "middle", "bottom"):
+            raise ValueError(
+                f'invalid value for vertical, expected "top", "middle", or "bottom" (not {vertical!r})'
+            )
+        self.renderable = renderable
+        self.align = align
+        self.style = style
+        self.vertical = vertical
+        self.pad = pad
+        self.width = width
+        self.height = height
+
+    def __repr__(self) -> str:
+        return f"Align({self.renderable!r}, {self.align!r})"
+
+    @classmethod
+    def left(
+        cls,
+        renderable: "RenderableType",
+        style: Optional[StyleType] = None,
+        *,
+        vertical: Optional[VerticalAlignMethod] = None,
+        pad: bool = True,
+        width: Optional[int] = None,
+        height: Optional[int] = None,
+    ) -> "Align":
+        """Align a renderable to the left."""
+        return cls(
+            renderable,
+            "left",
+            style=style,
+            vertical=vertical,
+            pad=pad,
+            width=width,
+            height=height,
+        )
+
+    @classmethod
+    def center(
+        cls,
+        renderable: "RenderableType",
+        style: Optional[StyleType] = None,
+        *,
+        vertical: Optional[VerticalAlignMethod] = None,
+        pad: bool = True,
+        width: Optional[int] = None,
+        height: Optional[int] = None,
+    ) -> "Align":
+        """Align a renderable to the center."""
+        return cls(
+            renderable,
+            "center",
+            style=style,
+            vertical=vertical,
+            pad=pad,
+            width=width,
+            height=height,
+        )
+
+    @classmethod
+    def right(
+        cls,
+        renderable: "RenderableType",
+        style: Optional[StyleType] = None,
+        *,
+        vertical: Optional[VerticalAlignMethod] = None,
+        pad: bool = True,
+        width: Optional[int] = None,
+        height: Optional[int] = None,
+    ) -> "Align":
+        """Align a renderable to the right."""
+        return cls(
+            renderable,
+            "right",
+            style=style,
+            vertical=vertical,
+            pad=pad,
+            width=width,
+            height=height,
+        )
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":
+        align = self.align
+        width = console.measure(self.renderable, options=options).maximum
+        rendered = console.render(
+            Constrain(
+                self.renderable, width if self.width is None else min(width, self.width)
+            ),
+            options.update(height=None),
+        )
+        lines = list(Segment.split_lines(rendered))
+        width, height = Segment.get_shape(lines)
+        lines = Segment.set_shape(lines, width, height)
+        new_line = Segment.line()
+        excess_space = options.max_width - width
+        style = console.get_style(self.style) if self.style is not None else None
+
+        def generate_segments() -> Iterable[Segment]:
+            if excess_space <= 0:
+                # Exact fit
+                for line in lines:
+                    yield from line
+                    yield new_line
+
+            elif align == "left":
+                # Pad on the right
+                pad = Segment(" " * excess_space, style) if self.pad else None
+                for line in lines:
+                    yield from line
+                    if pad:
+                        yield pad
+                    yield new_line
+
+            elif align == "center":
+                # Pad left and right
+                left = excess_space // 2
+                pad = Segment(" " * left, style)
+                pad_right = (
+                    Segment(" " * (excess_space - left), style) if self.pad else None
+                )
+                for line in lines:
+                    if left:
+                        yield pad
+                    yield from line
+                    if pad_right:
+                        yield pad_right
+                    yield new_line
+
+            elif align == "right":
+                # Padding on left
+                pad = Segment(" " * excess_space, style)
+                for line in lines:
+                    yield pad
+                    yield from line
+                    yield new_line
+
+        blank_line = (
+            Segment(f"{' ' * (self.width or options.max_width)}\n", style)
+            if self.pad
+            else Segment("\n")
+        )
+
+        def blank_lines(count: int) -> Iterable[Segment]:
+            if count > 0:
+                for _ in range(count):
+                    yield blank_line
+
+        vertical_height = self.height or options.height
+        iter_segments: Iterable[Segment]
+        if self.vertical and vertical_height is not None:
+            if self.vertical == "top":
+                bottom_space = vertical_height - height
+                iter_segments = chain(generate_segments(), blank_lines(bottom_space))
+            elif self.vertical == "middle":
+                top_space = (vertical_height - height) // 2
+                bottom_space = vertical_height - top_space - height
+                iter_segments = chain(
+                    blank_lines(top_space),
+                    generate_segments(),
+                    blank_lines(bottom_space),
+                )
+            else:  #  self.vertical == "bottom":
+                top_space = vertical_height - height
+                iter_segments = chain(blank_lines(top_space), generate_segments())
+        else:
+            iter_segments = generate_segments()
+        if self.style:
+            style = console.get_style(self.style)
+            iter_segments = Segment.apply_style(iter_segments, style)
+        yield from iter_segments
+
+    def __rich_measure__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> Measurement:
+        measurement = Measurement.get(console, options, self.renderable)
+        return measurement
+
+
+class VerticalCenter(JupyterMixin):
+    """Vertically aligns a renderable.
+
+    Warn:
+        This class is deprecated and may be removed in a future version. Use Align class with
+        `vertical="middle"`.
+
+    Args:
+        renderable (RenderableType): A renderable object.
+    """
+
+    def __init__(
+        self,
+        renderable: "RenderableType",
+        style: Optional[StyleType] = None,
+    ) -> None:
+        self.renderable = renderable
+        self.style = style
+
+    def __repr__(self) -> str:
+        return f"VerticalCenter({self.renderable!r})"
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":
+        style = console.get_style(self.style) if self.style is not None else None
+        lines = console.render_lines(
+            self.renderable, options.update(height=None), pad=False
+        )
+        width, _height = Segment.get_shape(lines)
+        new_line = Segment.line()
+        height = options.height or options.size.height
+        top_space = (height - len(lines)) // 2
+        bottom_space = height - top_space - len(lines)
+        blank_line = Segment(f"{' ' * width}", style)
+
+        def blank_lines(count: int) -> Iterable[Segment]:
+            for _ in range(count):
+                yield blank_line
+                yield new_line
+
+        if top_space > 0:
+            yield from blank_lines(top_space)
+        for line in lines:
+            yield from line
+            yield new_line
+        if bottom_space > 0:
+            yield from blank_lines(bottom_space)
+
+    def __rich_measure__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> Measurement:
+        measurement = Measurement.get(console, options, self.renderable)
+        return measurement
+
+
+if __name__ == "__main__":  # pragma: no cover
+    from pip._vendor.rich.console import Console, Group
+    from pip._vendor.rich.highlighter import ReprHighlighter
+    from pip._vendor.rich.panel import Panel
+
+    highlighter = ReprHighlighter()
+    console = Console()
+
+    panel = Panel(
+        Group(
+            Align.left(highlighter("align='left'")),
+            Align.center(highlighter("align='center'")),
+            Align.right(highlighter("align='right'")),
+        ),
+        width=60,
+        style="on dark_blue",
+        title="Algin",
+    )
+
+    console.print(
+        Align.center(panel, vertical="middle", style="on red", height=console.height)
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/ansi.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/ansi.py
new file mode 100644
index 0000000000000000000000000000000000000000..92ef51941171a7d04b48ddd4725f61f633335450
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/ansi.py
@@ -0,0 +1,237 @@
+import re
+import sys
+from contextlib import suppress
+from typing import Iterable, NamedTuple, Optional
+
+from .color import Color
+from .style import Style
+from .text import Text
+
+re_ansi = re.compile(
+    r"""
+(?:\x1b\](.*?)\x1b\\)|
+(?:\x1b([(@-Z\\-_]|\[[0-?]*[ -/]*[@-~]))
+""",
+    re.VERBOSE,
+)
+
+
+class _AnsiToken(NamedTuple):
+    """Result of ansi tokenized string."""
+
+    plain: str = ""
+    sgr: Optional[str] = ""
+    osc: Optional[str] = ""
+
+
+def _ansi_tokenize(ansi_text: str) -> Iterable[_AnsiToken]:
+    """Tokenize a string in to plain text and ANSI codes.
+
+    Args:
+        ansi_text (str): A String containing ANSI codes.
+
+    Yields:
+        AnsiToken: A named tuple of (plain, sgr, osc)
+    """
+
+    position = 0
+    sgr: Optional[str]
+    osc: Optional[str]
+    for match in re_ansi.finditer(ansi_text):
+        start, end = match.span(0)
+        osc, sgr = match.groups()
+        if start > position:
+            yield _AnsiToken(ansi_text[position:start])
+        if sgr:
+            if sgr.endswith("m"):
+                yield _AnsiToken("", sgr[1:-1], osc)
+        else:
+            yield _AnsiToken("", sgr, osc)
+        position = end
+    if position < len(ansi_text):
+        yield _AnsiToken(ansi_text[position:])
+
+
+SGR_STYLE_MAP = {
+    1: "bold",
+    2: "dim",
+    3: "italic",
+    4: "underline",
+    5: "blink",
+    6: "blink2",
+    7: "reverse",
+    8: "conceal",
+    9: "strike",
+    21: "underline2",
+    22: "not dim not bold",
+    23: "not italic",
+    24: "not underline",
+    25: "not blink",
+    26: "not blink2",
+    27: "not reverse",
+    28: "not conceal",
+    29: "not strike",
+    30: "color(0)",
+    31: "color(1)",
+    32: "color(2)",
+    33: "color(3)",
+    34: "color(4)",
+    35: "color(5)",
+    36: "color(6)",
+    37: "color(7)",
+    39: "default",
+    40: "on color(0)",
+    41: "on color(1)",
+    42: "on color(2)",
+    43: "on color(3)",
+    44: "on color(4)",
+    45: "on color(5)",
+    46: "on color(6)",
+    47: "on color(7)",
+    49: "on default",
+    51: "frame",
+    52: "encircle",
+    53: "overline",
+    54: "not frame not encircle",
+    55: "not overline",
+    90: "color(8)",
+    91: "color(9)",
+    92: "color(10)",
+    93: "color(11)",
+    94: "color(12)",
+    95: "color(13)",
+    96: "color(14)",
+    97: "color(15)",
+    100: "on color(8)",
+    101: "on color(9)",
+    102: "on color(10)",
+    103: "on color(11)",
+    104: "on color(12)",
+    105: "on color(13)",
+    106: "on color(14)",
+    107: "on color(15)",
+}
+
+
+class AnsiDecoder:
+    """Translate ANSI code in to styled Text."""
+
+    def __init__(self) -> None:
+        self.style = Style.null()
+
+    def decode(self, terminal_text: str) -> Iterable[Text]:
+        """Decode ANSI codes in an iterable of lines.
+
+        Args:
+            lines (Iterable[str]): An iterable of lines of terminal output.
+
+        Yields:
+            Text: Marked up Text.
+        """
+        for line in terminal_text.splitlines():
+            yield self.decode_line(line)
+
+    def decode_line(self, line: str) -> Text:
+        """Decode a line containing ansi codes.
+
+        Args:
+            line (str): A line of terminal output.
+
+        Returns:
+            Text: A Text instance marked up according to ansi codes.
+        """
+        from_ansi = Color.from_ansi
+        from_rgb = Color.from_rgb
+        _Style = Style
+        text = Text()
+        append = text.append
+        line = line.rsplit("\r", 1)[-1]
+        for plain_text, sgr, osc in _ansi_tokenize(line):
+            if plain_text:
+                append(plain_text, self.style or None)
+            elif osc is not None:
+                if osc.startswith("8;"):
+                    _params, semicolon, link = osc[2:].partition(";")
+                    if semicolon:
+                        self.style = self.style.update_link(link or None)
+            elif sgr is not None:
+                # Translate in to semi-colon separated codes
+                # Ignore invalid codes, because we want to be lenient
+                codes = [
+                    min(255, int(_code) if _code else 0)
+                    for _code in sgr.split(";")
+                    if _code.isdigit() or _code == ""
+                ]
+                iter_codes = iter(codes)
+                for code in iter_codes:
+                    if code == 0:
+                        # reset
+                        self.style = _Style.null()
+                    elif code in SGR_STYLE_MAP:
+                        # styles
+                        self.style += _Style.parse(SGR_STYLE_MAP[code])
+                    elif code == 38:
+                        #  Foreground
+                        with suppress(StopIteration):
+                            color_type = next(iter_codes)
+                            if color_type == 5:
+                                self.style += _Style.from_color(
+                                    from_ansi(next(iter_codes))
+                                )
+                            elif color_type == 2:
+                                self.style += _Style.from_color(
+                                    from_rgb(
+                                        next(iter_codes),
+                                        next(iter_codes),
+                                        next(iter_codes),
+                                    )
+                                )
+                    elif code == 48:
+                        # Background
+                        with suppress(StopIteration):
+                            color_type = next(iter_codes)
+                            if color_type == 5:
+                                self.style += _Style.from_color(
+                                    None, from_ansi(next(iter_codes))
+                                )
+                            elif color_type == 2:
+                                self.style += _Style.from_color(
+                                    None,
+                                    from_rgb(
+                                        next(iter_codes),
+                                        next(iter_codes),
+                                        next(iter_codes),
+                                    ),
+                                )
+
+        return text
+
+
+if sys.platform != "win32" and __name__ == "__main__":  # pragma: no cover
+    import io
+    import os
+    import pty
+    import sys
+
+    decoder = AnsiDecoder()
+
+    stdout = io.BytesIO()
+
+    def read(fd: int) -> bytes:
+        data = os.read(fd, 1024)
+        stdout.write(data)
+        return data
+
+    pty.spawn(sys.argv[1:], read)
+
+    from .console import Console
+
+    console = Console(record=True)
+
+    stdout_result = stdout.getvalue().decode("utf-8")
+    print(stdout_result)
+
+    for line in decoder.decode(stdout_result):
+        console.print(line)
+
+    console.save_html("stdout.html")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/bar.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/bar.py
new file mode 100644
index 0000000000000000000000000000000000000000..ed86a552d1ca6baa0cfd48ec73a7a5c952d047c9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/bar.py
@@ -0,0 +1,94 @@
+from typing import Optional, Union
+
+from .color import Color
+from .console import Console, ConsoleOptions, RenderResult
+from .jupyter import JupyterMixin
+from .measure import Measurement
+from .segment import Segment
+from .style import Style
+
+# There are left-aligned characters for 1/8 to 7/8, but
+# the right-aligned characters exist only for 1/8 and 4/8.
+BEGIN_BLOCK_ELEMENTS = ["█", "█", "█", "▐", "▐", "▐", "▕", "▕"]
+END_BLOCK_ELEMENTS = [" ", "▏", "▎", "▍", "▌", "▋", "▊", "▉"]
+FULL_BLOCK = "█"
+
+
+class Bar(JupyterMixin):
+    """Renders a solid block bar.
+
+    Args:
+        size (float): Value for the end of the bar.
+        begin (float): Begin point (between 0 and size, inclusive).
+        end (float): End point (between 0 and size, inclusive).
+        width (int, optional): Width of the bar, or ``None`` for maximum width. Defaults to None.
+        color (Union[Color, str], optional): Color of the bar. Defaults to "default".
+        bgcolor (Union[Color, str], optional): Color of bar background. Defaults to "default".
+    """
+
+    def __init__(
+        self,
+        size: float,
+        begin: float,
+        end: float,
+        *,
+        width: Optional[int] = None,
+        color: Union[Color, str] = "default",
+        bgcolor: Union[Color, str] = "default",
+    ):
+        self.size = size
+        self.begin = max(begin, 0)
+        self.end = min(end, size)
+        self.width = width
+        self.style = Style(color=color, bgcolor=bgcolor)
+
+    def __repr__(self) -> str:
+        return f"Bar({self.size}, {self.begin}, {self.end})"
+
+    def __rich_console__(
+        self, console: Console, options: ConsoleOptions
+    ) -> RenderResult:
+
+        width = min(
+            self.width if self.width is not None else options.max_width,
+            options.max_width,
+        )
+
+        if self.begin >= self.end:
+            yield Segment(" " * width, self.style)
+            yield Segment.line()
+            return
+
+        prefix_complete_eights = int(width * 8 * self.begin / self.size)
+        prefix_bar_count = prefix_complete_eights // 8
+        prefix_eights_count = prefix_complete_eights % 8
+
+        body_complete_eights = int(width * 8 * self.end / self.size)
+        body_bar_count = body_complete_eights // 8
+        body_eights_count = body_complete_eights % 8
+
+        # When start and end fall into the same cell, we ideally should render
+        # a symbol that's "center-aligned", but there is no good symbol in Unicode.
+        # In this case, we fall back to right-aligned block symbol for simplicity.
+
+        prefix = " " * prefix_bar_count
+        if prefix_eights_count:
+            prefix += BEGIN_BLOCK_ELEMENTS[prefix_eights_count]
+
+        body = FULL_BLOCK * body_bar_count
+        if body_eights_count:
+            body += END_BLOCK_ELEMENTS[body_eights_count]
+
+        suffix = " " * (width - len(body))
+
+        yield Segment(prefix + body[len(prefix) :] + suffix, self.style)
+        yield Segment.line()
+
+    def __rich_measure__(
+        self, console: Console, options: ConsoleOptions
+    ) -> Measurement:
+        return (
+            Measurement(self.width, self.width)
+            if self.width is not None
+            else Measurement(4, options.max_width)
+        )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/box.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/box.py
new file mode 100644
index 0000000000000000000000000000000000000000..97d2a94445770e195b9fc73e904b920d5ff04104
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/box.py
@@ -0,0 +1,517 @@
+import sys
+from typing import TYPE_CHECKING, Iterable, List
+
+if sys.version_info >= (3, 8):
+    from typing import Literal
+else:
+    from pip._vendor.typing_extensions import Literal  # pragma: no cover
+
+
+from ._loop import loop_last
+
+if TYPE_CHECKING:
+    from pip._vendor.rich.console import ConsoleOptions
+
+
+class Box:
+    """Defines characters to render boxes.
+
+    ┌─┬┐ top
+    │ ││ head
+    ├─┼┤ head_row
+    │ ││ mid
+    ├─┼┤ row
+    ├─┼┤ foot_row
+    │ ││ foot
+    └─┴┘ bottom
+
+    Args:
+        box (str): Characters making up box.
+        ascii (bool, optional): True if this box uses ascii characters only. Default is False.
+    """
+
+    def __init__(self, box: str, *, ascii: bool = False) -> None:
+        self._box = box
+        self.ascii = ascii
+        line1, line2, line3, line4, line5, line6, line7, line8 = box.splitlines()
+        # top
+        self.top_left, self.top, self.top_divider, self.top_right = iter(line1)
+        # head
+        self.head_left, _, self.head_vertical, self.head_right = iter(line2)
+        # head_row
+        (
+            self.head_row_left,
+            self.head_row_horizontal,
+            self.head_row_cross,
+            self.head_row_right,
+        ) = iter(line3)
+
+        # mid
+        self.mid_left, _, self.mid_vertical, self.mid_right = iter(line4)
+        # row
+        self.row_left, self.row_horizontal, self.row_cross, self.row_right = iter(line5)
+        # foot_row
+        (
+            self.foot_row_left,
+            self.foot_row_horizontal,
+            self.foot_row_cross,
+            self.foot_row_right,
+        ) = iter(line6)
+        # foot
+        self.foot_left, _, self.foot_vertical, self.foot_right = iter(line7)
+        # bottom
+        self.bottom_left, self.bottom, self.bottom_divider, self.bottom_right = iter(
+            line8
+        )
+
+    def __repr__(self) -> str:
+        return "Box(...)"
+
+    def __str__(self) -> str:
+        return self._box
+
+    def substitute(self, options: "ConsoleOptions", safe: bool = True) -> "Box":
+        """Substitute this box for another if it won't render due to platform issues.
+
+        Args:
+            options (ConsoleOptions): Console options used in rendering.
+            safe (bool, optional): Substitute this for another Box if there are known problems
+                displaying on the platform (currently only relevant on Windows). Default is True.
+
+        Returns:
+            Box: A different Box or the same Box.
+        """
+        box = self
+        if options.legacy_windows and safe:
+            box = LEGACY_WINDOWS_SUBSTITUTIONS.get(box, box)
+        if options.ascii_only and not box.ascii:
+            box = ASCII
+        return box
+
+    def get_plain_headed_box(self) -> "Box":
+        """If this box uses special characters for the borders of the header, then
+        return the equivalent box that does not.
+
+        Returns:
+            Box: The most similar Box that doesn't use header-specific box characters.
+                If the current Box already satisfies this criterion, then it's returned.
+        """
+        return PLAIN_HEADED_SUBSTITUTIONS.get(self, self)
+
+    def get_top(self, widths: Iterable[int]) -> str:
+        """Get the top of a simple box.
+
+        Args:
+            widths (List[int]): Widths of columns.
+
+        Returns:
+            str: A string of box characters.
+        """
+
+        parts: List[str] = []
+        append = parts.append
+        append(self.top_left)
+        for last, width in loop_last(widths):
+            append(self.top * width)
+            if not last:
+                append(self.top_divider)
+        append(self.top_right)
+        return "".join(parts)
+
+    def get_row(
+        self,
+        widths: Iterable[int],
+        level: Literal["head", "row", "foot", "mid"] = "row",
+        edge: bool = True,
+    ) -> str:
+        """Get the top of a simple box.
+
+        Args:
+            width (List[int]): Widths of columns.
+
+        Returns:
+            str: A string of box characters.
+        """
+        if level == "head":
+            left = self.head_row_left
+            horizontal = self.head_row_horizontal
+            cross = self.head_row_cross
+            right = self.head_row_right
+        elif level == "row":
+            left = self.row_left
+            horizontal = self.row_horizontal
+            cross = self.row_cross
+            right = self.row_right
+        elif level == "mid":
+            left = self.mid_left
+            horizontal = " "
+            cross = self.mid_vertical
+            right = self.mid_right
+        elif level == "foot":
+            left = self.foot_row_left
+            horizontal = self.foot_row_horizontal
+            cross = self.foot_row_cross
+            right = self.foot_row_right
+        else:
+            raise ValueError("level must be 'head', 'row' or 'foot'")
+
+        parts: List[str] = []
+        append = parts.append
+        if edge:
+            append(left)
+        for last, width in loop_last(widths):
+            append(horizontal * width)
+            if not last:
+                append(cross)
+        if edge:
+            append(right)
+        return "".join(parts)
+
+    def get_bottom(self, widths: Iterable[int]) -> str:
+        """Get the bottom of a simple box.
+
+        Args:
+            widths (List[int]): Widths of columns.
+
+        Returns:
+            str: A string of box characters.
+        """
+
+        parts: List[str] = []
+        append = parts.append
+        append(self.bottom_left)
+        for last, width in loop_last(widths):
+            append(self.bottom * width)
+            if not last:
+                append(self.bottom_divider)
+        append(self.bottom_right)
+        return "".join(parts)
+
+
+ASCII: Box = Box(
+    """\
++--+
+| ||
+|-+|
+| ||
+|-+|
+|-+|
+| ||
++--+
+""",
+    ascii=True,
+)
+
+ASCII2: Box = Box(
+    """\
++-++
+| ||
++-++
+| ||
++-++
++-++
+| ||
++-++
+""",
+    ascii=True,
+)
+
+ASCII_DOUBLE_HEAD: Box = Box(
+    """\
++-++
+| ||
++=++
+| ||
++-++
++-++
+| ||
++-++
+""",
+    ascii=True,
+)
+
+SQUARE: Box = Box(
+    """\
+┌─┬┐
+│ ││
+├─┼┤
+│ ││
+├─┼┤
+├─┼┤
+│ ││
+└─┴┘
+"""
+)
+
+SQUARE_DOUBLE_HEAD: Box = Box(
+    """\
+┌─┬┐
+│ ││
+╞═╪╡
+│ ││
+├─┼┤
+├─┼┤
+│ ││
+└─┴┘
+"""
+)
+
+MINIMAL: Box = Box(
+    """\
+  ╷ 
+  │ 
+╶─┼╴
+  │ 
+╶─┼╴
+╶─┼╴
+  │ 
+  ╵ 
+"""
+)
+
+
+MINIMAL_HEAVY_HEAD: Box = Box(
+    """\
+  ╷ 
+  │ 
+╺━┿╸
+  │ 
+╶─┼╴
+╶─┼╴
+  │ 
+  ╵ 
+"""
+)
+
+MINIMAL_DOUBLE_HEAD: Box = Box(
+    """\
+  ╷ 
+  │ 
+ ═╪ 
+  │ 
+ ─┼ 
+ ─┼ 
+  │ 
+  ╵ 
+"""
+)
+
+
+SIMPLE: Box = Box(
+    """\
+    
+    
+ ── 
+    
+    
+ ── 
+    
+    
+"""
+)
+
+SIMPLE_HEAD: Box = Box(
+    """\
+    
+    
+ ── 
+    
+    
+    
+    
+    
+"""
+)
+
+
+SIMPLE_HEAVY: Box = Box(
+    """\
+    
+    
+ ━━ 
+    
+    
+ ━━ 
+    
+    
+"""
+)
+
+
+HORIZONTALS: Box = Box(
+    """\
+ ── 
+    
+ ── 
+    
+ ── 
+ ── 
+    
+ ── 
+"""
+)
+
+ROUNDED: Box = Box(
+    """\
+╭─┬╮
+│ ││
+├─┼┤
+│ ││
+├─┼┤
+├─┼┤
+│ ││
+╰─┴╯
+"""
+)
+
+HEAVY: Box = Box(
+    """\
+┏━┳┓
+┃ ┃┃
+┣━╋┫
+┃ ┃┃
+┣━╋┫
+┣━╋┫
+┃ ┃┃
+┗━┻┛
+"""
+)
+
+HEAVY_EDGE: Box = Box(
+    """\
+┏━┯┓
+┃ │┃
+┠─┼┨
+┃ │┃
+┠─┼┨
+┠─┼┨
+┃ │┃
+┗━┷┛
+"""
+)
+
+HEAVY_HEAD: Box = Box(
+    """\
+┏━┳┓
+┃ ┃┃
+┡━╇┩
+│ ││
+├─┼┤
+├─┼┤
+│ ││
+└─┴┘
+"""
+)
+
+DOUBLE: Box = Box(
+    """\
+╔═╦╗
+║ ║║
+╠═╬╣
+║ ║║
+╠═╬╣
+╠═╬╣
+║ ║║
+╚═╩╝
+"""
+)
+
+DOUBLE_EDGE: Box = Box(
+    """\
+╔═╤╗
+║ │║
+╟─┼╢
+║ │║
+╟─┼╢
+╟─┼╢
+║ │║
+╚═╧╝
+"""
+)
+
+MARKDOWN: Box = Box(
+    """\
+    
+| ||
+|-||
+| ||
+|-||
+|-||
+| ||
+    
+""",
+    ascii=True,
+)
+
+# Map Boxes that don't render with raster fonts on to equivalent that do
+LEGACY_WINDOWS_SUBSTITUTIONS = {
+    ROUNDED: SQUARE,
+    MINIMAL_HEAVY_HEAD: MINIMAL,
+    SIMPLE_HEAVY: SIMPLE,
+    HEAVY: SQUARE,
+    HEAVY_EDGE: SQUARE,
+    HEAVY_HEAD: SQUARE,
+}
+
+# Map headed boxes to their headerless equivalents
+PLAIN_HEADED_SUBSTITUTIONS = {
+    HEAVY_HEAD: SQUARE,
+    SQUARE_DOUBLE_HEAD: SQUARE,
+    MINIMAL_DOUBLE_HEAD: MINIMAL,
+    MINIMAL_HEAVY_HEAD: MINIMAL,
+    ASCII_DOUBLE_HEAD: ASCII2,
+}
+
+
+if __name__ == "__main__":  # pragma: no cover
+
+    from pip._vendor.rich.columns import Columns
+    from pip._vendor.rich.panel import Panel
+
+    from . import box as box
+    from .console import Console
+    from .table import Table
+    from .text import Text
+
+    console = Console(record=True)
+
+    BOXES = [
+        "ASCII",
+        "ASCII2",
+        "ASCII_DOUBLE_HEAD",
+        "SQUARE",
+        "SQUARE_DOUBLE_HEAD",
+        "MINIMAL",
+        "MINIMAL_HEAVY_HEAD",
+        "MINIMAL_DOUBLE_HEAD",
+        "SIMPLE",
+        "SIMPLE_HEAD",
+        "SIMPLE_HEAVY",
+        "HORIZONTALS",
+        "ROUNDED",
+        "HEAVY",
+        "HEAVY_EDGE",
+        "HEAVY_HEAD",
+        "DOUBLE",
+        "DOUBLE_EDGE",
+        "MARKDOWN",
+    ]
+
+    console.print(Panel("[bold green]Box Constants", style="green"), justify="center")
+    console.print()
+
+    columns = Columns(expand=True, padding=2)
+    for box_name in sorted(BOXES):
+        table = Table(
+            show_footer=True, style="dim", border_style="not dim", expand=True
+        )
+        table.add_column("Header 1", "Footer 1")
+        table.add_column("Header 2", "Footer 2")
+        table.add_row("Cell", "Cell")
+        table.add_row("Cell", "Cell")
+        table.box = getattr(box, box_name)
+        table.title = Text(f"box.{box_name}", style="magenta")
+        columns.add_renderable(table)
+    console.print(columns)
+
+    # console.save_svg("box.svg")
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/cells.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/cells.py
new file mode 100644
index 0000000000000000000000000000000000000000..139b949f7f2dad487477ec18a635de9865d29d69
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/cells.py
@@ -0,0 +1,154 @@
+import re
+from functools import lru_cache
+from typing import Callable, List
+
+from ._cell_widths import CELL_WIDTHS
+
+# Regex to match sequence of the most common character ranges
+_is_single_cell_widths = re.compile("^[\u0020-\u006f\u00a0\u02ff\u0370-\u0482]*$").match
+
+
+@lru_cache(4096)
+def cached_cell_len(text: str) -> int:
+    """Get the number of cells required to display text.
+
+    This method always caches, which may use up a lot of memory. It is recommended to use
+    `cell_len` over this method.
+
+    Args:
+        text (str): Text to display.
+
+    Returns:
+        int: Get the number of cells required to display text.
+    """
+    _get_size = get_character_cell_size
+    total_size = sum(_get_size(character) for character in text)
+    return total_size
+
+
+def cell_len(text: str, _cell_len: Callable[[str], int] = cached_cell_len) -> int:
+    """Get the number of cells required to display text.
+
+    Args:
+        text (str): Text to display.
+
+    Returns:
+        int: Get the number of cells required to display text.
+    """
+    if len(text) < 512:
+        return _cell_len(text)
+    _get_size = get_character_cell_size
+    total_size = sum(_get_size(character) for character in text)
+    return total_size
+
+
+@lru_cache(maxsize=4096)
+def get_character_cell_size(character: str) -> int:
+    """Get the cell size of a character.
+
+    Args:
+        character (str): A single character.
+
+    Returns:
+        int: Number of cells (0, 1 or 2) occupied by that character.
+    """
+    return _get_codepoint_cell_size(ord(character))
+
+
+@lru_cache(maxsize=4096)
+def _get_codepoint_cell_size(codepoint: int) -> int:
+    """Get the cell size of a character.
+
+    Args:
+        character (str): A single character.
+
+    Returns:
+        int: Number of cells (0, 1 or 2) occupied by that character.
+    """
+
+    _table = CELL_WIDTHS
+    lower_bound = 0
+    upper_bound = len(_table) - 1
+    index = (lower_bound + upper_bound) // 2
+    while True:
+        start, end, width = _table[index]
+        if codepoint < start:
+            upper_bound = index - 1
+        elif codepoint > end:
+            lower_bound = index + 1
+        else:
+            return 0 if width == -1 else width
+        if upper_bound < lower_bound:
+            break
+        index = (lower_bound + upper_bound) // 2
+    return 1
+
+
+def set_cell_size(text: str, total: int) -> str:
+    """Set the length of a string to fit within given number of cells."""
+
+    if _is_single_cell_widths(text):
+        size = len(text)
+        if size < total:
+            return text + " " * (total - size)
+        return text[:total]
+
+    if total <= 0:
+        return ""
+    cell_size = cell_len(text)
+    if cell_size == total:
+        return text
+    if cell_size < total:
+        return text + " " * (total - cell_size)
+
+    start = 0
+    end = len(text)
+
+    # Binary search until we find the right size
+    while True:
+        pos = (start + end) // 2
+        before = text[: pos + 1]
+        before_len = cell_len(before)
+        if before_len == total + 1 and cell_len(before[-1]) == 2:
+            return before[:-1] + " "
+        if before_len == total:
+            return before
+        if before_len > total:
+            end = pos
+        else:
+            start = pos
+
+
+# TODO: This is inefficient
+# TODO: This might not work with CWJ type characters
+def chop_cells(text: str, max_size: int, position: int = 0) -> List[str]:
+    """Break text in to equal (cell) length strings, returning the characters in reverse
+    order"""
+    _get_character_cell_size = get_character_cell_size
+    characters = [
+        (character, _get_character_cell_size(character)) for character in text
+    ]
+    total_size = position
+    lines: List[List[str]] = [[]]
+    append = lines[-1].append
+
+    for character, size in reversed(characters):
+        if total_size + size > max_size:
+            lines.append([character])
+            append = lines[-1].append
+            total_size = size
+        else:
+            total_size += size
+            append(character)
+
+    return ["".join(line) for line in lines]
+
+
+if __name__ == "__main__":  # pragma: no cover
+
+    print(get_character_cell_size("😽"))
+    for line in chop_cells("""这是对亚洲语言支持的测试。面对模棱两可的想法，拒绝猜测的诱惑。""", 8):
+        print(line)
+    for n in range(80, 1, -1):
+        print(set_cell_size("""这是对亚洲语言支持的测试。面对模棱两可的想法，拒绝猜测的诱惑。""", n) + "|")
+        print("x" * n)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/color.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/color.py
new file mode 100644
index 0000000000000000000000000000000000000000..ef2e895d7cb0f417470a302b048e76b08b122c16
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/color.py
@@ -0,0 +1,618 @@
+import platform
+import re
+from colorsys import rgb_to_hls
+from enum import IntEnum
+from functools import lru_cache
+from typing import TYPE_CHECKING, NamedTuple, Optional, Tuple
+
+from ._palettes import EIGHT_BIT_PALETTE, STANDARD_PALETTE, WINDOWS_PALETTE
+from .color_triplet import ColorTriplet
+from .repr import Result, rich_repr
+from .terminal_theme import DEFAULT_TERMINAL_THEME
+
+if TYPE_CHECKING:  # pragma: no cover
+    from .terminal_theme import TerminalTheme
+    from .text import Text
+
+
+WINDOWS = platform.system() == "Windows"
+
+
+class ColorSystem(IntEnum):
+    """One of the 3 color system supported by terminals."""
+
+    STANDARD = 1
+    EIGHT_BIT = 2
+    TRUECOLOR = 3
+    WINDOWS = 4
+
+    def __repr__(self) -> str:
+        return f"ColorSystem.{self.name}"
+
+    def __str__(self) -> str:
+        return repr(self)
+
+
+class ColorType(IntEnum):
+    """Type of color stored in Color class."""
+
+    DEFAULT = 0
+    STANDARD = 1
+    EIGHT_BIT = 2
+    TRUECOLOR = 3
+    WINDOWS = 4
+
+    def __repr__(self) -> str:
+        return f"ColorType.{self.name}"
+
+
+ANSI_COLOR_NAMES = {
+    "black": 0,
+    "red": 1,
+    "green": 2,
+    "yellow": 3,
+    "blue": 4,
+    "magenta": 5,
+    "cyan": 6,
+    "white": 7,
+    "bright_black": 8,
+    "bright_red": 9,
+    "bright_green": 10,
+    "bright_yellow": 11,
+    "bright_blue": 12,
+    "bright_magenta": 13,
+    "bright_cyan": 14,
+    "bright_white": 15,
+    "grey0": 16,
+    "gray0": 16,
+    "navy_blue": 17,
+    "dark_blue": 18,
+    "blue3": 20,
+    "blue1": 21,
+    "dark_green": 22,
+    "deep_sky_blue4": 25,
+    "dodger_blue3": 26,
+    "dodger_blue2": 27,
+    "green4": 28,
+    "spring_green4": 29,
+    "turquoise4": 30,
+    "deep_sky_blue3": 32,
+    "dodger_blue1": 33,
+    "green3": 40,
+    "spring_green3": 41,
+    "dark_cyan": 36,
+    "light_sea_green": 37,
+    "deep_sky_blue2": 38,
+    "deep_sky_blue1": 39,
+    "spring_green2": 47,
+    "cyan3": 43,
+    "dark_turquoise": 44,
+    "turquoise2": 45,
+    "green1": 46,
+    "spring_green1": 48,
+    "medium_spring_green": 49,
+    "cyan2": 50,
+    "cyan1": 51,
+    "dark_red": 88,
+    "deep_pink4": 125,
+    "purple4": 55,
+    "purple3": 56,
+    "blue_violet": 57,
+    "orange4": 94,
+    "grey37": 59,
+    "gray37": 59,
+    "medium_purple4": 60,
+    "slate_blue3": 62,
+    "royal_blue1": 63,
+    "chartreuse4": 64,
+    "dark_sea_green4": 71,
+    "pale_turquoise4": 66,
+    "steel_blue": 67,
+    "steel_blue3": 68,
+    "cornflower_blue": 69,
+    "chartreuse3": 76,
+    "cadet_blue": 73,
+    "sky_blue3": 74,
+    "steel_blue1": 81,
+    "pale_green3": 114,
+    "sea_green3": 78,
+    "aquamarine3": 79,
+    "medium_turquoise": 80,
+    "chartreuse2": 112,
+    "sea_green2": 83,
+    "sea_green1": 85,
+    "aquamarine1": 122,
+    "dark_slate_gray2": 87,
+    "dark_magenta": 91,
+    "dark_violet": 128,
+    "purple": 129,
+    "light_pink4": 95,
+    "plum4": 96,
+    "medium_purple3": 98,
+    "slate_blue1": 99,
+    "yellow4": 106,
+    "wheat4": 101,
+    "grey53": 102,
+    "gray53": 102,
+    "light_slate_grey": 103,
+    "light_slate_gray": 103,
+    "medium_purple": 104,
+    "light_slate_blue": 105,
+    "dark_olive_green3": 149,
+    "dark_sea_green": 108,
+    "light_sky_blue3": 110,
+    "sky_blue2": 111,
+    "dark_sea_green3": 150,
+    "dark_slate_gray3": 116,
+    "sky_blue1": 117,
+    "chartreuse1": 118,
+    "light_green": 120,
+    "pale_green1": 156,
+    "dark_slate_gray1": 123,
+    "red3": 160,
+    "medium_violet_red": 126,
+    "magenta3": 164,
+    "dark_orange3": 166,
+    "indian_red": 167,
+    "hot_pink3": 168,
+    "medium_orchid3": 133,
+    "medium_orchid": 134,
+    "medium_purple2": 140,
+    "dark_goldenrod": 136,
+    "light_salmon3": 173,
+    "rosy_brown": 138,
+    "grey63": 139,
+    "gray63": 139,
+    "medium_purple1": 141,
+    "gold3": 178,
+    "dark_khaki": 143,
+    "navajo_white3": 144,
+    "grey69": 145,
+    "gray69": 145,
+    "light_steel_blue3": 146,
+    "light_steel_blue": 147,
+    "yellow3": 184,
+    "dark_sea_green2": 157,
+    "light_cyan3": 152,
+    "light_sky_blue1": 153,
+    "green_yellow": 154,
+    "dark_olive_green2": 155,
+    "dark_sea_green1": 193,
+    "pale_turquoise1": 159,
+    "deep_pink3": 162,
+    "magenta2": 200,
+    "hot_pink2": 169,
+    "orchid": 170,
+    "medium_orchid1": 207,
+    "orange3": 172,
+    "light_pink3": 174,
+    "pink3": 175,
+    "plum3": 176,
+    "violet": 177,
+    "light_goldenrod3": 179,
+    "tan": 180,
+    "misty_rose3": 181,
+    "thistle3": 182,
+    "plum2": 183,
+    "khaki3": 185,
+    "light_goldenrod2": 222,
+    "light_yellow3": 187,
+    "grey84": 188,
+    "gray84": 188,
+    "light_steel_blue1": 189,
+    "yellow2": 190,
+    "dark_olive_green1": 192,
+    "honeydew2": 194,
+    "light_cyan1": 195,
+    "red1": 196,
+    "deep_pink2": 197,
+    "deep_pink1": 199,
+    "magenta1": 201,
+    "orange_red1": 202,
+    "indian_red1": 204,
+    "hot_pink": 206,
+    "dark_orange": 208,
+    "salmon1": 209,
+    "light_coral": 210,
+    "pale_violet_red1": 211,
+    "orchid2": 212,
+    "orchid1": 213,
+    "orange1": 214,
+    "sandy_brown": 215,
+    "light_salmon1": 216,
+    "light_pink1": 217,
+    "pink1": 218,
+    "plum1": 219,
+    "gold1": 220,
+    "navajo_white1": 223,
+    "misty_rose1": 224,
+    "thistle1": 225,
+    "yellow1": 226,
+    "light_goldenrod1": 227,
+    "khaki1": 228,
+    "wheat1": 229,
+    "cornsilk1": 230,
+    "grey100": 231,
+    "gray100": 231,
+    "grey3": 232,
+    "gray3": 232,
+    "grey7": 233,
+    "gray7": 233,
+    "grey11": 234,
+    "gray11": 234,
+    "grey15": 235,
+    "gray15": 235,
+    "grey19": 236,
+    "gray19": 236,
+    "grey23": 237,
+    "gray23": 237,
+    "grey27": 238,
+    "gray27": 238,
+    "grey30": 239,
+    "gray30": 239,
+    "grey35": 240,
+    "gray35": 240,
+    "grey39": 241,
+    "gray39": 241,
+    "grey42": 242,
+    "gray42": 242,
+    "grey46": 243,
+    "gray46": 243,
+    "grey50": 244,
+    "gray50": 244,
+    "grey54": 245,
+    "gray54": 245,
+    "grey58": 246,
+    "gray58": 246,
+    "grey62": 247,
+    "gray62": 247,
+    "grey66": 248,
+    "gray66": 248,
+    "grey70": 249,
+    "gray70": 249,
+    "grey74": 250,
+    "gray74": 250,
+    "grey78": 251,
+    "gray78": 251,
+    "grey82": 252,
+    "gray82": 252,
+    "grey85": 253,
+    "gray85": 253,
+    "grey89": 254,
+    "gray89": 254,
+    "grey93": 255,
+    "gray93": 255,
+}
+
+
+class ColorParseError(Exception):
+    """The color could not be parsed."""
+
+
+RE_COLOR = re.compile(
+    r"""^
+\#([0-9a-f]{6})$|
+color\(([0-9]{1,3})\)$|
+rgb\(([\d\s,]+)\)$
+""",
+    re.VERBOSE,
+)
+
+
+@rich_repr
+class Color(NamedTuple):
+    """Terminal color definition."""
+
+    name: str
+    """The name of the color (typically the input to Color.parse)."""
+    type: ColorType
+    """The type of the color."""
+    number: Optional[int] = None
+    """The color number, if a standard color, or None."""
+    triplet: Optional[ColorTriplet] = None
+    """A triplet of color components, if an RGB color."""
+
+    def __rich__(self) -> "Text":
+        """Displays the actual color if Rich printed."""
+        from .style import Style
+        from .text import Text
+
+        return Text.assemble(
+            f"",
+        )
+
+    def __rich_repr__(self) -> Result:
+        yield self.name
+        yield self.type
+        yield "number", self.number, None
+        yield "triplet", self.triplet, None
+
+    @property
+    def system(self) -> ColorSystem:
+        """Get the native color system for this color."""
+        if self.type == ColorType.DEFAULT:
+            return ColorSystem.STANDARD
+        return ColorSystem(int(self.type))
+
+    @property
+    def is_system_defined(self) -> bool:
+        """Check if the color is ultimately defined by the system."""
+        return self.system not in (ColorSystem.EIGHT_BIT, ColorSystem.TRUECOLOR)
+
+    @property
+    def is_default(self) -> bool:
+        """Check if the color is a default color."""
+        return self.type == ColorType.DEFAULT
+
+    def get_truecolor(
+        self, theme: Optional["TerminalTheme"] = None, foreground: bool = True
+    ) -> ColorTriplet:
+        """Get an equivalent color triplet for this color.
+
+        Args:
+            theme (TerminalTheme, optional): Optional terminal theme, or None to use default. Defaults to None.
+            foreground (bool, optional): True for a foreground color, or False for background. Defaults to True.
+
+        Returns:
+            ColorTriplet: A color triplet containing RGB components.
+        """
+
+        if theme is None:
+            theme = DEFAULT_TERMINAL_THEME
+        if self.type == ColorType.TRUECOLOR:
+            assert self.triplet is not None
+            return self.triplet
+        elif self.type == ColorType.EIGHT_BIT:
+            assert self.number is not None
+            return EIGHT_BIT_PALETTE[self.number]
+        elif self.type == ColorType.STANDARD:
+            assert self.number is not None
+            return theme.ansi_colors[self.number]
+        elif self.type == ColorType.WINDOWS:
+            assert self.number is not None
+            return WINDOWS_PALETTE[self.number]
+        else:  # self.type == ColorType.DEFAULT:
+            assert self.number is None
+            return theme.foreground_color if foreground else theme.background_color
+
+    @classmethod
+    def from_ansi(cls, number: int) -> "Color":
+        """Create a Color number from it's 8-bit ansi number.
+
+        Args:
+            number (int): A number between 0-255 inclusive.
+
+        Returns:
+            Color: A new Color instance.
+        """
+        return cls(
+            name=f"color({number})",
+            type=(ColorType.STANDARD if number < 16 else ColorType.EIGHT_BIT),
+            number=number,
+        )
+
+    @classmethod
+    def from_triplet(cls, triplet: "ColorTriplet") -> "Color":
+        """Create a truecolor RGB color from a triplet of values.
+
+        Args:
+            triplet (ColorTriplet): A color triplet containing red, green and blue components.
+
+        Returns:
+            Color: A new color object.
+        """
+        return cls(name=triplet.hex, type=ColorType.TRUECOLOR, triplet=triplet)
+
+    @classmethod
+    def from_rgb(cls, red: float, green: float, blue: float) -> "Color":
+        """Create a truecolor from three color components in the range(0->255).
+
+        Args:
+            red (float): Red component in range 0-255.
+            green (float): Green component in range 0-255.
+            blue (float): Blue component in range 0-255.
+
+        Returns:
+            Color: A new color object.
+        """
+        return cls.from_triplet(ColorTriplet(int(red), int(green), int(blue)))
+
+    @classmethod
+    def default(cls) -> "Color":
+        """Get a Color instance representing the default color.
+
+        Returns:
+            Color: Default color.
+        """
+        return cls(name="default", type=ColorType.DEFAULT)
+
+    @classmethod
+    @lru_cache(maxsize=1024)
+    def parse(cls, color: str) -> "Color":
+        """Parse a color definition."""
+        original_color = color
+        color = color.lower().strip()
+
+        if color == "default":
+            return cls(color, type=ColorType.DEFAULT)
+
+        color_number = ANSI_COLOR_NAMES.get(color)
+        if color_number is not None:
+            return cls(
+                color,
+                type=(ColorType.STANDARD if color_number < 16 else ColorType.EIGHT_BIT),
+                number=color_number,
+            )
+
+        color_match = RE_COLOR.match(color)
+        if color_match is None:
+            raise ColorParseError(f"{original_color!r} is not a valid color")
+
+        color_24, color_8, color_rgb = color_match.groups()
+        if color_24:
+            triplet = ColorTriplet(
+                int(color_24[0:2], 16), int(color_24[2:4], 16), int(color_24[4:6], 16)
+            )
+            return cls(color, ColorType.TRUECOLOR, triplet=triplet)
+
+        elif color_8:
+            number = int(color_8)
+            if number > 255:
+                raise ColorParseError(f"color number must be <= 255 in {color!r}")
+            return cls(
+                color,
+                type=(ColorType.STANDARD if number < 16 else ColorType.EIGHT_BIT),
+                number=number,
+            )
+
+        else:  #  color_rgb:
+            components = color_rgb.split(",")
+            if len(components) != 3:
+                raise ColorParseError(
+                    f"expected three components in {original_color!r}"
+                )
+            red, green, blue = components
+            triplet = ColorTriplet(int(red), int(green), int(blue))
+            if not all(component <= 255 for component in triplet):
+                raise ColorParseError(
+                    f"color components must be <= 255 in {original_color!r}"
+                )
+            return cls(color, ColorType.TRUECOLOR, triplet=triplet)
+
+    @lru_cache(maxsize=1024)
+    def get_ansi_codes(self, foreground: bool = True) -> Tuple[str, ...]:
+        """Get the ANSI escape codes for this color."""
+        _type = self.type
+        if _type == ColorType.DEFAULT:
+            return ("39" if foreground else "49",)
+
+        elif _type == ColorType.WINDOWS:
+            number = self.number
+            assert number is not None
+            fore, back = (30, 40) if number < 8 else (82, 92)
+            return (str(fore + number if foreground else back + number),)
+
+        elif _type == ColorType.STANDARD:
+            number = self.number
+            assert number is not None
+            fore, back = (30, 40) if number < 8 else (82, 92)
+            return (str(fore + number if foreground else back + number),)
+
+        elif _type == ColorType.EIGHT_BIT:
+            assert self.number is not None
+            return ("38" if foreground else "48", "5", str(self.number))
+
+        else:  # self.standard == ColorStandard.TRUECOLOR:
+            assert self.triplet is not None
+            red, green, blue = self.triplet
+            return ("38" if foreground else "48", "2", str(red), str(green), str(blue))
+
+    @lru_cache(maxsize=1024)
+    def downgrade(self, system: ColorSystem) -> "Color":
+        """Downgrade a color system to a system with fewer colors."""
+
+        if self.type in [ColorType.DEFAULT, system]:
+            return self
+        # Convert to 8-bit color from truecolor color
+        if system == ColorSystem.EIGHT_BIT and self.system == ColorSystem.TRUECOLOR:
+            assert self.triplet is not None
+            red, green, blue = self.triplet.normalized
+            _h, l, s = rgb_to_hls(red, green, blue)
+            # If saturation is under 10% assume it is grayscale
+            if s < 0.1:
+                gray = round(l * 25.0)
+                if gray == 0:
+                    color_number = 16
+                elif gray == 25:
+                    color_number = 231
+                else:
+                    color_number = 231 + gray
+                return Color(self.name, ColorType.EIGHT_BIT, number=color_number)
+
+            color_number = (
+                16 + 36 * round(red * 5.0) + 6 * round(green * 5.0) + round(blue * 5.0)
+            )
+            return Color(self.name, ColorType.EIGHT_BIT, number=color_number)
+
+        # Convert to standard from truecolor or 8-bit
+        elif system == ColorSystem.STANDARD:
+            if self.system == ColorSystem.TRUECOLOR:
+                assert self.triplet is not None
+                triplet = self.triplet
+            else:  # self.system == ColorSystem.EIGHT_BIT
+                assert self.number is not None
+                triplet = ColorTriplet(*EIGHT_BIT_PALETTE[self.number])
+
+            color_number = STANDARD_PALETTE.match(triplet)
+            return Color(self.name, ColorType.STANDARD, number=color_number)
+
+        elif system == ColorSystem.WINDOWS:
+            if self.system == ColorSystem.TRUECOLOR:
+                assert self.triplet is not None
+                triplet = self.triplet
+            else:  # self.system == ColorSystem.EIGHT_BIT
+                assert self.number is not None
+                if self.number < 16:
+                    return Color(self.name, ColorType.WINDOWS, number=self.number)
+                triplet = ColorTriplet(*EIGHT_BIT_PALETTE[self.number])
+
+            color_number = WINDOWS_PALETTE.match(triplet)
+            return Color(self.name, ColorType.WINDOWS, number=color_number)
+
+        return self
+
+
+def parse_rgb_hex(hex_color: str) -> ColorTriplet:
+    """Parse six hex characters in to RGB triplet."""
+    assert len(hex_color) == 6, "must be 6 characters"
+    color = ColorTriplet(
+        int(hex_color[0:2], 16), int(hex_color[2:4], 16), int(hex_color[4:6], 16)
+    )
+    return color
+
+
+def blend_rgb(
+    color1: ColorTriplet, color2: ColorTriplet, cross_fade: float = 0.5
+) -> ColorTriplet:
+    """Blend one RGB color in to another."""
+    r1, g1, b1 = color1
+    r2, g2, b2 = color2
+    new_color = ColorTriplet(
+        int(r1 + (r2 - r1) * cross_fade),
+        int(g1 + (g2 - g1) * cross_fade),
+        int(b1 + (b2 - b1) * cross_fade),
+    )
+    return new_color
+
+
+if __name__ == "__main__":  # pragma: no cover
+
+    from .console import Console
+    from .table import Table
+    from .text import Text
+
+    console = Console()
+
+    table = Table(show_footer=False, show_edge=True)
+    table.add_column("Color", width=10, overflow="ellipsis")
+    table.add_column("Number", justify="right", style="yellow")
+    table.add_column("Name", style="green")
+    table.add_column("Hex", style="blue")
+    table.add_column("RGB", style="magenta")
+
+    colors = sorted((v, k) for k, v in ANSI_COLOR_NAMES.items())
+    for color_number, name in colors:
+        if "grey" in name:
+            continue
+        color_cell = Text(" " * 10, style=f"on {name}")
+        if color_number < 16:
+            table.add_row(color_cell, f"{color_number}", Text(f'"{name}"'))
+        else:
+            color = EIGHT_BIT_PALETTE[color_number]  # type: ignore[has-type]
+            table.add_row(
+                color_cell, str(color_number), Text(f'"{name}"'), color.hex, color.rgb
+            )
+
+    console.print(table)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/color_triplet.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/color_triplet.py
new file mode 100644
index 0000000000000000000000000000000000000000..02cab328251af9bfa809981aaa44933c407e2cd7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/color_triplet.py
@@ -0,0 +1,38 @@
+from typing import NamedTuple, Tuple
+
+
+class ColorTriplet(NamedTuple):
+    """The red, green, and blue components of a color."""
+
+    red: int
+    """Red component in 0 to 255 range."""
+    green: int
+    """Green component in 0 to 255 range."""
+    blue: int
+    """Blue component in 0 to 255 range."""
+
+    @property
+    def hex(self) -> str:
+        """get the color triplet in CSS style."""
+        red, green, blue = self
+        return f"#{red:02x}{green:02x}{blue:02x}"
+
+    @property
+    def rgb(self) -> str:
+        """The color in RGB format.
+
+        Returns:
+            str: An rgb color, e.g. ``"rgb(100,23,255)"``.
+        """
+        red, green, blue = self
+        return f"rgb({red},{green},{blue})"
+
+    @property
+    def normalized(self) -> Tuple[float, float, float]:
+        """Convert components into floats between 0 and 1.
+
+        Returns:
+            Tuple[float, float, float]: A tuple of three normalized colour components.
+        """
+        red, green, blue = self
+        return red / 255.0, green / 255.0, blue / 255.0
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/columns.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/columns.py
new file mode 100644
index 0000000000000000000000000000000000000000..669a3a7074f9a9e1af29cb4bc78b05851df67959
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/columns.py
@@ -0,0 +1,187 @@
+from collections import defaultdict
+from itertools import chain
+from operator import itemgetter
+from typing import Dict, Iterable, List, Optional, Tuple
+
+from .align import Align, AlignMethod
+from .console import Console, ConsoleOptions, RenderableType, RenderResult
+from .constrain import Constrain
+from .measure import Measurement
+from .padding import Padding, PaddingDimensions
+from .table import Table
+from .text import TextType
+from .jupyter import JupyterMixin
+
+
+class Columns(JupyterMixin):
+    """Display renderables in neat columns.
+
+    Args:
+        renderables (Iterable[RenderableType]): Any number of Rich renderables (including str).
+        width (int, optional): The desired width of the columns, or None to auto detect. Defaults to None.
+        padding (PaddingDimensions, optional): Optional padding around cells. Defaults to (0, 1).
+        expand (bool, optional): Expand columns to full width. Defaults to False.
+        equal (bool, optional): Arrange in to equal sized columns. Defaults to False.
+        column_first (bool, optional): Align items from top to bottom (rather than left to right). Defaults to False.
+        right_to_left (bool, optional): Start column from right hand side. Defaults to False.
+        align (str, optional): Align value ("left", "right", or "center") or None for default. Defaults to None.
+        title (TextType, optional): Optional title for Columns.
+    """
+
+    def __init__(
+        self,
+        renderables: Optional[Iterable[RenderableType]] = None,
+        padding: PaddingDimensions = (0, 1),
+        *,
+        width: Optional[int] = None,
+        expand: bool = False,
+        equal: bool = False,
+        column_first: bool = False,
+        right_to_left: bool = False,
+        align: Optional[AlignMethod] = None,
+        title: Optional[TextType] = None,
+    ) -> None:
+        self.renderables = list(renderables or [])
+        self.width = width
+        self.padding = padding
+        self.expand = expand
+        self.equal = equal
+        self.column_first = column_first
+        self.right_to_left = right_to_left
+        self.align: Optional[AlignMethod] = align
+        self.title = title
+
+    def add_renderable(self, renderable: RenderableType) -> None:
+        """Add a renderable to the columns.
+
+        Args:
+            renderable (RenderableType): Any renderable object.
+        """
+        self.renderables.append(renderable)
+
+    def __rich_console__(
+        self, console: Console, options: ConsoleOptions
+    ) -> RenderResult:
+        render_str = console.render_str
+        renderables = [
+            render_str(renderable) if isinstance(renderable, str) else renderable
+            for renderable in self.renderables
+        ]
+        if not renderables:
+            return
+        _top, right, _bottom, left = Padding.unpack(self.padding)
+        width_padding = max(left, right)
+        max_width = options.max_width
+        widths: Dict[int, int] = defaultdict(int)
+        column_count = len(renderables)
+
+        get_measurement = Measurement.get
+        renderable_widths = [
+            get_measurement(console, options, renderable).maximum
+            for renderable in renderables
+        ]
+        if self.equal:
+            renderable_widths = [max(renderable_widths)] * len(renderable_widths)
+
+        def iter_renderables(
+            column_count: int,
+        ) -> Iterable[Tuple[int, Optional[RenderableType]]]:
+            item_count = len(renderables)
+            if self.column_first:
+                width_renderables = list(zip(renderable_widths, renderables))
+
+                column_lengths: List[int] = [item_count // column_count] * column_count
+                for col_no in range(item_count % column_count):
+                    column_lengths[col_no] += 1
+
+                row_count = (item_count + column_count - 1) // column_count
+                cells = [[-1] * column_count for _ in range(row_count)]
+                row = col = 0
+                for index in range(item_count):
+                    cells[row][col] = index
+                    column_lengths[col] -= 1
+                    if column_lengths[col]:
+                        row += 1
+                    else:
+                        col += 1
+                        row = 0
+                for index in chain.from_iterable(cells):
+                    if index == -1:
+                        break
+                    yield width_renderables[index]
+            else:
+                yield from zip(renderable_widths, renderables)
+            # Pad odd elements with spaces
+            if item_count % column_count:
+                for _ in range(column_count - (item_count % column_count)):
+                    yield 0, None
+
+        table = Table.grid(padding=self.padding, collapse_padding=True, pad_edge=False)
+        table.expand = self.expand
+        table.title = self.title
+
+        if self.width is not None:
+            column_count = (max_width) // (self.width + width_padding)
+            for _ in range(column_count):
+                table.add_column(width=self.width)
+        else:
+            while column_count > 1:
+                widths.clear()
+                column_no = 0
+                for renderable_width, _ in iter_renderables(column_count):
+                    widths[column_no] = max(widths[column_no], renderable_width)
+                    total_width = sum(widths.values()) + width_padding * (
+                        len(widths) - 1
+                    )
+                    if total_width > max_width:
+                        column_count = len(widths) - 1
+                        break
+                    else:
+                        column_no = (column_no + 1) % column_count
+                else:
+                    break
+
+        get_renderable = itemgetter(1)
+        _renderables = [
+            get_renderable(_renderable)
+            for _renderable in iter_renderables(column_count)
+        ]
+        if self.equal:
+            _renderables = [
+                None
+                if renderable is None
+                else Constrain(renderable, renderable_widths[0])
+                for renderable in _renderables
+            ]
+        if self.align:
+            align = self.align
+            _Align = Align
+            _renderables = [
+                None if renderable is None else _Align(renderable, align)
+                for renderable in _renderables
+            ]
+
+        right_to_left = self.right_to_left
+        add_row = table.add_row
+        for start in range(0, len(_renderables), column_count):
+            row = _renderables[start : start + column_count]
+            if right_to_left:
+                row = row[::-1]
+            add_row(*row)
+        yield table
+
+
+if __name__ == "__main__":  # pragma: no cover
+    import os
+
+    console = Console()
+
+    files = [f"{i} {s}" for i, s in enumerate(sorted(os.listdir()))]
+    columns = Columns(files, padding=(0, 1), expand=False, equal=False)
+    console.print(columns)
+    console.rule()
+    columns.column_first = True
+    console.print(columns)
+    columns.right_to_left = True
+    console.rule()
+    console.print(columns)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/console.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/console.py
new file mode 100644
index 0000000000000000000000000000000000000000..f805f2dea7d356d82d262150ce381bb46ae10b64
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/console.py
@@ -0,0 +1,2612 @@
+import inspect
+import io
+import os
+import platform
+import sys
+import threading
+import zlib
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from datetime import datetime
+from functools import wraps
+from getpass import getpass
+from html import escape
+from inspect import isclass
+from itertools import islice
+from math import ceil
+from time import monotonic
+from types import FrameType, ModuleType, TracebackType
+from typing import (
+    IO,
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    Dict,
+    Iterable,
+    List,
+    Mapping,
+    NamedTuple,
+    Optional,
+    TextIO,
+    Tuple,
+    Type,
+    Union,
+    cast,
+)
+
+from pip._vendor.rich._null_file import NULL_FILE
+
+if sys.version_info >= (3, 8):
+    from typing import Literal, Protocol, runtime_checkable
+else:
+    from pip._vendor.typing_extensions import (
+        Literal,
+        Protocol,
+        runtime_checkable,
+    )  # pragma: no cover
+
+from . import errors, themes
+from ._emoji_replace import _emoji_replace
+from ._export_format import CONSOLE_HTML_FORMAT, CONSOLE_SVG_FORMAT
+from ._log_render import FormatTimeCallable, LogRender
+from .align import Align, AlignMethod
+from .color import ColorSystem, blend_rgb
+from .control import Control
+from .emoji import EmojiVariant
+from .highlighter import NullHighlighter, ReprHighlighter
+from .markup import render as render_markup
+from .measure import Measurement, measure_renderables
+from .pager import Pager, SystemPager
+from .pretty import Pretty, is_expandable
+from .protocol import rich_cast
+from .region import Region
+from .scope import render_scope
+from .screen import Screen
+from .segment import Segment
+from .style import Style, StyleType
+from .styled import Styled
+from .terminal_theme import DEFAULT_TERMINAL_THEME, SVG_EXPORT_THEME, TerminalTheme
+from .text import Text, TextType
+from .theme import Theme, ThemeStack
+
+if TYPE_CHECKING:
+    from ._windows import WindowsConsoleFeatures
+    from .live import Live
+    from .status import Status
+
+JUPYTER_DEFAULT_COLUMNS = 115
+JUPYTER_DEFAULT_LINES = 100
+WINDOWS = platform.system() == "Windows"
+
+HighlighterType = Callable[[Union[str, "Text"]], "Text"]
+JustifyMethod = Literal["default", "left", "center", "right", "full"]
+OverflowMethod = Literal["fold", "crop", "ellipsis", "ignore"]
+
+
+class NoChange:
+    pass
+
+
+NO_CHANGE = NoChange()
+
+try:
+    _STDIN_FILENO = sys.__stdin__.fileno()
+except Exception:
+    _STDIN_FILENO = 0
+try:
+    _STDOUT_FILENO = sys.__stdout__.fileno()
+except Exception:
+    _STDOUT_FILENO = 1
+try:
+    _STDERR_FILENO = sys.__stderr__.fileno()
+except Exception:
+    _STDERR_FILENO = 2
+
+_STD_STREAMS = (_STDIN_FILENO, _STDOUT_FILENO, _STDERR_FILENO)
+_STD_STREAMS_OUTPUT = (_STDOUT_FILENO, _STDERR_FILENO)
+
+
+_TERM_COLORS = {
+    "kitty": ColorSystem.EIGHT_BIT,
+    "256color": ColorSystem.EIGHT_BIT,
+    "16color": ColorSystem.STANDARD,
+}
+
+
+class ConsoleDimensions(NamedTuple):
+    """Size of the terminal."""
+
+    width: int
+    """The width of the console in 'cells'."""
+    height: int
+    """The height of the console in lines."""
+
+
+@dataclass
+class ConsoleOptions:
+    """Options for __rich_console__ method."""
+
+    size: ConsoleDimensions
+    """Size of console."""
+    legacy_windows: bool
+    """legacy_windows: flag for legacy windows."""
+    min_width: int
+    """Minimum width of renderable."""
+    max_width: int
+    """Maximum width of renderable."""
+    is_terminal: bool
+    """True if the target is a terminal, otherwise False."""
+    encoding: str
+    """Encoding of terminal."""
+    max_height: int
+    """Height of container (starts as terminal)"""
+    justify: Optional[JustifyMethod] = None
+    """Justify value override for renderable."""
+    overflow: Optional[OverflowMethod] = None
+    """Overflow value override for renderable."""
+    no_wrap: Optional[bool] = False
+    """Disable wrapping for text."""
+    highlight: Optional[bool] = None
+    """Highlight override for render_str."""
+    markup: Optional[bool] = None
+    """Enable markup when rendering strings."""
+    height: Optional[int] = None
+
+    @property
+    def ascii_only(self) -> bool:
+        """Check if renderables should use ascii only."""
+        return not self.encoding.startswith("utf")
+
+    def copy(self) -> "ConsoleOptions":
+        """Return a copy of the options.
+
+        Returns:
+            ConsoleOptions: a copy of self.
+        """
+        options: ConsoleOptions = ConsoleOptions.__new__(ConsoleOptions)
+        options.__dict__ = self.__dict__.copy()
+        return options
+
+    def update(
+        self,
+        *,
+        width: Union[int, NoChange] = NO_CHANGE,
+        min_width: Union[int, NoChange] = NO_CHANGE,
+        max_width: Union[int, NoChange] = NO_CHANGE,
+        justify: Union[Optional[JustifyMethod], NoChange] = NO_CHANGE,
+        overflow: Union[Optional[OverflowMethod], NoChange] = NO_CHANGE,
+        no_wrap: Union[Optional[bool], NoChange] = NO_CHANGE,
+        highlight: Union[Optional[bool], NoChange] = NO_CHANGE,
+        markup: Union[Optional[bool], NoChange] = NO_CHANGE,
+        height: Union[Optional[int], NoChange] = NO_CHANGE,
+    ) -> "ConsoleOptions":
+        """Update values, return a copy."""
+        options = self.copy()
+        if not isinstance(width, NoChange):
+            options.min_width = options.max_width = max(0, width)
+        if not isinstance(min_width, NoChange):
+            options.min_width = min_width
+        if not isinstance(max_width, NoChange):
+            options.max_width = max_width
+        if not isinstance(justify, NoChange):
+            options.justify = justify
+        if not isinstance(overflow, NoChange):
+            options.overflow = overflow
+        if not isinstance(no_wrap, NoChange):
+            options.no_wrap = no_wrap
+        if not isinstance(highlight, NoChange):
+            options.highlight = highlight
+        if not isinstance(markup, NoChange):
+            options.markup = markup
+        if not isinstance(height, NoChange):
+            if height is not None:
+                options.max_height = height
+            options.height = None if height is None else max(0, height)
+        return options
+
+    def update_width(self, width: int) -> "ConsoleOptions":
+        """Update just the width, return a copy.
+
+        Args:
+            width (int): New width (sets both min_width and max_width)
+
+        Returns:
+            ~ConsoleOptions: New console options instance.
+        """
+        options = self.copy()
+        options.min_width = options.max_width = max(0, width)
+        return options
+
+    def update_height(self, height: int) -> "ConsoleOptions":
+        """Update the height, and return a copy.
+
+        Args:
+            height (int): New height
+
+        Returns:
+            ~ConsoleOptions: New Console options instance.
+        """
+        options = self.copy()
+        options.max_height = options.height = height
+        return options
+
+    def reset_height(self) -> "ConsoleOptions":
+        """Return a copy of the options with height set to ``None``.
+
+        Returns:
+            ~ConsoleOptions: New console options instance.
+        """
+        options = self.copy()
+        options.height = None
+        return options
+
+    def update_dimensions(self, width: int, height: int) -> "ConsoleOptions":
+        """Update the width and height, and return a copy.
+
+        Args:
+            width (int): New width (sets both min_width and max_width).
+            height (int): New height.
+
+        Returns:
+            ~ConsoleOptions: New console options instance.
+        """
+        options = self.copy()
+        options.min_width = options.max_width = max(0, width)
+        options.height = options.max_height = height
+        return options
+
+
+@runtime_checkable
+class RichCast(Protocol):
+    """An object that may be 'cast' to a console renderable."""
+
+    def __rich__(
+        self,
+    ) -> Union["ConsoleRenderable", "RichCast", str]:  # pragma: no cover
+        ...
+
+
+@runtime_checkable
+class ConsoleRenderable(Protocol):
+    """An object that supports the console protocol."""
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":  # pragma: no cover
+        ...
+
+
+# A type that may be rendered by Console.
+RenderableType = Union[ConsoleRenderable, RichCast, str]
+
+# The result of calling a __rich_console__ method.
+RenderResult = Iterable[Union[RenderableType, Segment]]
+
+_null_highlighter = NullHighlighter()
+
+
+class CaptureError(Exception):
+    """An error in the Capture context manager."""
+
+
+class NewLine:
+    """A renderable to generate new line(s)"""
+
+    def __init__(self, count: int = 1) -> None:
+        self.count = count
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> Iterable[Segment]:
+        yield Segment("\n" * self.count)
+
+
+class ScreenUpdate:
+    """Render a list of lines at a given offset."""
+
+    def __init__(self, lines: List[List[Segment]], x: int, y: int) -> None:
+        self._lines = lines
+        self.x = x
+        self.y = y
+
+    def __rich_console__(
+        self, console: "Console", options: ConsoleOptions
+    ) -> RenderResult:
+        x = self.x
+        move_to = Control.move_to
+        for offset, line in enumerate(self._lines, self.y):
+            yield move_to(x, offset)
+            yield from line
+
+
+class Capture:
+    """Context manager to capture the result of printing to the console.
+    See :meth:`~rich.console.Console.capture` for how to use.
+
+    Args:
+        console (Console): A console instance to capture output.
+    """
+
+    def __init__(self, console: "Console") -> None:
+        self._console = console
+        self._result: Optional[str] = None
+
+    def __enter__(self) -> "Capture":
+        self._console.begin_capture()
+        return self
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> None:
+        self._result = self._console.end_capture()
+
+    def get(self) -> str:
+        """Get the result of the capture."""
+        if self._result is None:
+            raise CaptureError(
+                "Capture result is not available until context manager exits."
+            )
+        return self._result
+
+
+class ThemeContext:
+    """A context manager to use a temporary theme. See :meth:`~rich.console.Console.use_theme` for usage."""
+
+    def __init__(self, console: "Console", theme: Theme, inherit: bool = True) -> None:
+        self.console = console
+        self.theme = theme
+        self.inherit = inherit
+
+    def __enter__(self) -> "ThemeContext":
+        self.console.push_theme(self.theme)
+        return self
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> None:
+        self.console.pop_theme()
+
+
+class PagerContext:
+    """A context manager that 'pages' content. See :meth:`~rich.console.Console.pager` for usage."""
+
+    def __init__(
+        self,
+        console: "Console",
+        pager: Optional[Pager] = None,
+        styles: bool = False,
+        links: bool = False,
+    ) -> None:
+        self._console = console
+        self.pager = SystemPager() if pager is None else pager
+        self.styles = styles
+        self.links = links
+
+    def __enter__(self) -> "PagerContext":
+        self._console._enter_buffer()
+        return self
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> None:
+        if exc_type is None:
+            with self._console._lock:
+                buffer: List[Segment] = self._console._buffer[:]
+                del self._console._buffer[:]
+                segments: Iterable[Segment] = buffer
+                if not self.styles:
+                    segments = Segment.strip_styles(segments)
+                elif not self.links:
+                    segments = Segment.strip_links(segments)
+                content = self._console._render_buffer(segments)
+            self.pager.show(content)
+        self._console._exit_buffer()
+
+
+class ScreenContext:
+    """A context manager that enables an alternative screen. See :meth:`~rich.console.Console.screen` for usage."""
+
+    def __init__(
+        self, console: "Console", hide_cursor: bool, style: StyleType = ""
+    ) -> None:
+        self.console = console
+        self.hide_cursor = hide_cursor
+        self.screen = Screen(style=style)
+        self._changed = False
+
+    def update(
+        self, *renderables: RenderableType, style: Optional[StyleType] = None
+    ) -> None:
+        """Update the screen.
+
+        Args:
+            renderable (RenderableType, optional): Optional renderable to replace current renderable,
+                or None for no change. Defaults to None.
+            style: (Style, optional): Replacement style, or None for no change. Defaults to None.
+        """
+        if renderables:
+            self.screen.renderable = (
+                Group(*renderables) if len(renderables) > 1 else renderables[0]
+            )
+        if style is not None:
+            self.screen.style = style
+        self.console.print(self.screen, end="")
+
+    def __enter__(self) -> "ScreenContext":
+        self._changed = self.console.set_alt_screen(True)
+        if self._changed and self.hide_cursor:
+            self.console.show_cursor(False)
+        return self
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]],
+        exc_val: Optional[BaseException],
+        exc_tb: Optional[TracebackType],
+    ) -> None:
+        if self._changed:
+            self.console.set_alt_screen(False)
+            if self.hide_cursor:
+                self.console.show_cursor(True)
+
+
+class Group:
+    """Takes a group of renderables and returns a renderable object that renders the group.
+
+    Args:
+        renderables (Iterable[RenderableType]): An iterable of renderable objects.
+        fit (bool, optional): Fit dimension of group to contents, or fill available space. Defaults to True.
+    """
+
+    def __init__(self, *renderables: "RenderableType", fit: bool = True) -> None:
+        self._renderables = renderables
+        self.fit = fit
+        self._render: Optional[List[RenderableType]] = None
+
+    @property
+    def renderables(self) -> List["RenderableType"]:
+        if self._render is None:
+            self._render = list(self._renderables)
+        return self._render
+
+    def __rich_measure__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "Measurement":
+        if self.fit:
+            return measure_renderables(console, options, self.renderables)
+        else:
+            return Measurement(options.max_width, options.max_width)
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> RenderResult:
+        yield from self.renderables
+
+
+def group(fit: bool = True) -> Callable[..., Callable[..., Group]]:
+    """A decorator that turns an iterable of renderables in to a group.
+
+    Args:
+        fit (bool, optional): Fit dimension of group to contents, or fill available space. Defaults to True.
+    """
+
+    def decorator(
+        method: Callable[..., Iterable[RenderableType]]
+    ) -> Callable[..., Group]:
+        """Convert a method that returns an iterable of renderables in to a Group."""
+
+        @wraps(method)
+        def _replace(*args: Any, **kwargs: Any) -> Group:
+            renderables = method(*args, **kwargs)
+            return Group(*renderables, fit=fit)
+
+        return _replace
+
+    return decorator
+
+
+def _is_jupyter() -> bool:  # pragma: no cover
+    """Check if we're running in a Jupyter notebook."""
+    try:
+        get_ipython  # type: ignore[name-defined]
+    except NameError:
+        return False
+    ipython = get_ipython()  # type: ignore[name-defined]
+    shell = ipython.__class__.__name__
+    if (
+        "google.colab" in str(ipython.__class__)
+        or os.getenv("DATABRICKS_RUNTIME_VERSION")
+        or shell == "ZMQInteractiveShell"
+    ):
+        return True  # Jupyter notebook or qtconsole
+    elif shell == "TerminalInteractiveShell":
+        return False  # Terminal running IPython
+    else:
+        return False  # Other type (?)
+
+
+COLOR_SYSTEMS = {
+    "standard": ColorSystem.STANDARD,
+    "256": ColorSystem.EIGHT_BIT,
+    "truecolor": ColorSystem.TRUECOLOR,
+    "windows": ColorSystem.WINDOWS,
+}
+
+_COLOR_SYSTEMS_NAMES = {system: name for name, system in COLOR_SYSTEMS.items()}
+
+
+@dataclass
+class ConsoleThreadLocals(threading.local):
+    """Thread local values for Console context."""
+
+    theme_stack: ThemeStack
+    buffer: List[Segment] = field(default_factory=list)
+    buffer_index: int = 0
+
+
+class RenderHook(ABC):
+    """Provides hooks in to the render process."""
+
+    @abstractmethod
+    def process_renderables(
+        self, renderables: List[ConsoleRenderable]
+    ) -> List[ConsoleRenderable]:
+        """Called with a list of objects to render.
+
+        This method can return a new list of renderables, or modify and return the same list.
+
+        Args:
+            renderables (List[ConsoleRenderable]): A number of renderable objects.
+
+        Returns:
+            List[ConsoleRenderable]: A replacement list of renderables.
+        """
+
+
+_windows_console_features: Optional["WindowsConsoleFeatures"] = None
+
+
+def get_windows_console_features() -> "WindowsConsoleFeatures":  # pragma: no cover
+    global _windows_console_features
+    if _windows_console_features is not None:
+        return _windows_console_features
+    from ._windows import get_windows_console_features
+
+    _windows_console_features = get_windows_console_features()
+    return _windows_console_features
+
+
+def detect_legacy_windows() -> bool:
+    """Detect legacy Windows."""
+    return WINDOWS and not get_windows_console_features().vt
+
+
+class Console:
+    """A high level console interface.
+
+    Args:
+        color_system (str, optional): The color system supported by your terminal,
+            either ``"standard"``, ``"256"`` or ``"truecolor"``. Leave as ``"auto"`` to autodetect.
+        force_terminal (Optional[bool], optional): Enable/disable terminal control codes, or None to auto-detect terminal. Defaults to None.
+        force_jupyter (Optional[bool], optional): Enable/disable Jupyter rendering, or None to auto-detect Jupyter. Defaults to None.
+        force_interactive (Optional[bool], optional): Enable/disable interactive mode, or None to auto detect. Defaults to None.
+        soft_wrap (Optional[bool], optional): Set soft wrap default on print method. Defaults to False.
+        theme (Theme, optional): An optional style theme object, or ``None`` for default theme.
+        stderr (bool, optional): Use stderr rather than stdout if ``file`` is not specified. Defaults to False.
+        file (IO, optional): A file object where the console should write to. Defaults to stdout.
+        quiet (bool, Optional): Boolean to suppress all output. Defaults to False.
+        width (int, optional): The width of the terminal. Leave as default to auto-detect width.
+        height (int, optional): The height of the terminal. Leave as default to auto-detect height.
+        style (StyleType, optional): Style to apply to all output, or None for no style. Defaults to None.
+        no_color (Optional[bool], optional): Enabled no color mode, or None to auto detect. Defaults to None.
+        tab_size (int, optional): Number of spaces used to replace a tab character. Defaults to 8.
+        record (bool, optional): Boolean to enable recording of terminal output,
+            required to call :meth:`export_html`, :meth:`export_svg`, and :meth:`export_text`. Defaults to False.
+        markup (bool, optional): Boolean to enable :ref:`console_markup`. Defaults to True.
+        emoji (bool, optional): Enable emoji code. Defaults to True.
+        emoji_variant (str, optional): Optional emoji variant, either "text" or "emoji". Defaults to None.
+        highlight (bool, optional): Enable automatic highlighting. Defaults to True.
+        log_time (bool, optional): Boolean to enable logging of time by :meth:`log` methods. Defaults to True.
+        log_path (bool, optional): Boolean to enable the logging of the caller by :meth:`log`. Defaults to True.
+        log_time_format (Union[str, TimeFormatterCallable], optional): If ``log_time`` is enabled, either string for strftime or callable that formats the time. Defaults to "[%X] ".
+        highlighter (HighlighterType, optional): Default highlighter.
+        legacy_windows (bool, optional): Enable legacy Windows mode, or ``None`` to auto detect. Defaults to ``None``.
+        safe_box (bool, optional): Restrict box options that don't render on legacy Windows.
+        get_datetime (Callable[[], datetime], optional): Callable that gets the current time as a datetime.datetime object (used by Console.log),
+            or None for datetime.now.
+        get_time (Callable[[], time], optional): Callable that gets the current time in seconds, default uses time.monotonic.
+    """
+
+    _environ: Mapping[str, str] = os.environ
+
+    def __init__(
+        self,
+        *,
+        color_system: Optional[
+            Literal["auto", "standard", "256", "truecolor", "windows"]
+        ] = "auto",
+        force_terminal: Optional[bool] = None,
+        force_jupyter: Optional[bool] = None,
+        force_interactive: Optional[bool] = None,
+        soft_wrap: bool = False,
+        theme: Optional[Theme] = None,
+        stderr: bool = False,
+        file: Optional[IO[str]] = None,
+        quiet: bool = False,
+        width: Optional[int] = None,
+        height: Optional[int] = None,
+        style: Optional[StyleType] = None,
+        no_color: Optional[bool] = None,
+        tab_size: int = 8,
+        record: bool = False,
+        markup: bool = True,
+        emoji: bool = True,
+        emoji_variant: Optional[EmojiVariant] = None,
+        highlight: bool = True,
+        log_time: bool = True,
+        log_path: bool = True,
+        log_time_format: Union[str, FormatTimeCallable] = "[%X]",
+        highlighter: Optional["HighlighterType"] = ReprHighlighter(),
+        legacy_windows: Optional[bool] = None,
+        safe_box: bool = True,
+        get_datetime: Optional[Callable[[], datetime]] = None,
+        get_time: Optional[Callable[[], float]] = None,
+        _environ: Optional[Mapping[str, str]] = None,
+    ):
+        # Copy of os.environ allows us to replace it for testing
+        if _environ is not None:
+            self._environ = _environ
+
+        self.is_jupyter = _is_jupyter() if force_jupyter is None else force_jupyter
+        if self.is_jupyter:
+            if width is None:
+                jupyter_columns = self._environ.get("JUPYTER_COLUMNS")
+                if jupyter_columns is not None and jupyter_columns.isdigit():
+                    width = int(jupyter_columns)
+                else:
+                    width = JUPYTER_DEFAULT_COLUMNS
+            if height is None:
+                jupyter_lines = self._environ.get("JUPYTER_LINES")
+                if jupyter_lines is not None and jupyter_lines.isdigit():
+                    height = int(jupyter_lines)
+                else:
+                    height = JUPYTER_DEFAULT_LINES
+
+        self.tab_size = tab_size
+        self.record = record
+        self._markup = markup
+        self._emoji = emoji
+        self._emoji_variant: Optional[EmojiVariant] = emoji_variant
+        self._highlight = highlight
+        self.legacy_windows: bool = (
+            (detect_legacy_windows() and not self.is_jupyter)
+            if legacy_windows is None
+            else legacy_windows
+        )
+
+        if width is None:
+            columns = self._environ.get("COLUMNS")
+            if columns is not None and columns.isdigit():
+                width = int(columns) - self.legacy_windows
+        if height is None:
+            lines = self._environ.get("LINES")
+            if lines is not None and lines.isdigit():
+                height = int(lines)
+
+        self.soft_wrap = soft_wrap
+        self._width = width
+        self._height = height
+
+        self._color_system: Optional[ColorSystem]
+
+        self._force_terminal = None
+        if force_terminal is not None:
+            self._force_terminal = force_terminal
+        else:
+            # If FORCE_COLOR env var has any value at all, we force terminal.
+            force_color = self._environ.get("FORCE_COLOR")
+            if force_color is not None:
+                self._force_terminal = True
+
+        self._file = file
+        self.quiet = quiet
+        self.stderr = stderr
+
+        if color_system is None:
+            self._color_system = None
+        elif color_system == "auto":
+            self._color_system = self._detect_color_system()
+        else:
+            self._color_system = COLOR_SYSTEMS[color_system]
+
+        self._lock = threading.RLock()
+        self._log_render = LogRender(
+            show_time=log_time,
+            show_path=log_path,
+            time_format=log_time_format,
+        )
+        self.highlighter: HighlighterType = highlighter or _null_highlighter
+        self.safe_box = safe_box
+        self.get_datetime = get_datetime or datetime.now
+        self.get_time = get_time or monotonic
+        self.style = style
+        self.no_color = (
+            no_color if no_color is not None else "NO_COLOR" in self._environ
+        )
+        self.is_interactive = (
+            (self.is_terminal and not self.is_dumb_terminal)
+            if force_interactive is None
+            else force_interactive
+        )
+
+        self._record_buffer_lock = threading.RLock()
+        self._thread_locals = ConsoleThreadLocals(
+            theme_stack=ThemeStack(themes.DEFAULT if theme is None else theme)
+        )
+        self._record_buffer: List[Segment] = []
+        self._render_hooks: List[RenderHook] = []
+        self._live: Optional["Live"] = None
+        self._is_alt_screen = False
+
+    def __repr__(self) -> str:
+        return f""
+
+    @property
+    def file(self) -> IO[str]:
+        """Get the file object to write to."""
+        file = self._file or (sys.stderr if self.stderr else sys.stdout)
+        file = getattr(file, "rich_proxied_file", file)
+        if file is None:
+            file = NULL_FILE
+        return file
+
+    @file.setter
+    def file(self, new_file: IO[str]) -> None:
+        """Set a new file object."""
+        self._file = new_file
+
+    @property
+    def _buffer(self) -> List[Segment]:
+        """Get a thread local buffer."""
+        return self._thread_locals.buffer
+
+    @property
+    def _buffer_index(self) -> int:
+        """Get a thread local buffer."""
+        return self._thread_locals.buffer_index
+
+    @_buffer_index.setter
+    def _buffer_index(self, value: int) -> None:
+        self._thread_locals.buffer_index = value
+
+    @property
+    def _theme_stack(self) -> ThemeStack:
+        """Get the thread local theme stack."""
+        return self._thread_locals.theme_stack
+
+    def _detect_color_system(self) -> Optional[ColorSystem]:
+        """Detect color system from env vars."""
+        if self.is_jupyter:
+            return ColorSystem.TRUECOLOR
+        if not self.is_terminal or self.is_dumb_terminal:
+            return None
+        if WINDOWS:  # pragma: no cover
+            if self.legacy_windows:  # pragma: no cover
+                return ColorSystem.WINDOWS
+            windows_console_features = get_windows_console_features()
+            return (
+                ColorSystem.TRUECOLOR
+                if windows_console_features.truecolor
+                else ColorSystem.EIGHT_BIT
+            )
+        else:
+            color_term = self._environ.get("COLORTERM", "").strip().lower()
+            if color_term in ("truecolor", "24bit"):
+                return ColorSystem.TRUECOLOR
+            term = self._environ.get("TERM", "").strip().lower()
+            _term_name, _hyphen, colors = term.rpartition("-")
+            color_system = _TERM_COLORS.get(colors, ColorSystem.STANDARD)
+            return color_system
+
+    def _enter_buffer(self) -> None:
+        """Enter in to a buffer context, and buffer all output."""
+        self._buffer_index += 1
+
+    def _exit_buffer(self) -> None:
+        """Leave buffer context, and render content if required."""
+        self._buffer_index -= 1
+        self._check_buffer()
+
+    def set_live(self, live: "Live") -> None:
+        """Set Live instance. Used by Live context manager.
+
+        Args:
+            live (Live): Live instance using this Console.
+
+        Raises:
+            errors.LiveError: If this Console has a Live context currently active.
+        """
+        with self._lock:
+            if self._live is not None:
+                raise errors.LiveError("Only one live display may be active at once")
+            self._live = live
+
+    def clear_live(self) -> None:
+        """Clear the Live instance."""
+        with self._lock:
+            self._live = None
+
+    def push_render_hook(self, hook: RenderHook) -> None:
+        """Add a new render hook to the stack.
+
+        Args:
+            hook (RenderHook): Render hook instance.
+        """
+        with self._lock:
+            self._render_hooks.append(hook)
+
+    def pop_render_hook(self) -> None:
+        """Pop the last renderhook from the stack."""
+        with self._lock:
+            self._render_hooks.pop()
+
+    def __enter__(self) -> "Console":
+        """Own context manager to enter buffer context."""
+        self._enter_buffer()
+        return self
+
+    def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> None:
+        """Exit buffer context."""
+        self._exit_buffer()
+
+    def begin_capture(self) -> None:
+        """Begin capturing console output. Call :meth:`end_capture` to exit capture mode and return output."""
+        self._enter_buffer()
+
+    def end_capture(self) -> str:
+        """End capture mode and return captured string.
+
+        Returns:
+            str: Console output.
+        """
+        render_result = self._render_buffer(self._buffer)
+        del self._buffer[:]
+        self._exit_buffer()
+        return render_result
+
+    def push_theme(self, theme: Theme, *, inherit: bool = True) -> None:
+        """Push a new theme on to the top of the stack, replacing the styles from the previous theme.
+        Generally speaking, you should call :meth:`~rich.console.Console.use_theme` to get a context manager, rather
+        than calling this method directly.
+
+        Args:
+            theme (Theme): A theme instance.
+            inherit (bool, optional): Inherit existing styles. Defaults to True.
+        """
+        self._theme_stack.push_theme(theme, inherit=inherit)
+
+    def pop_theme(self) -> None:
+        """Remove theme from top of stack, restoring previous theme."""
+        self._theme_stack.pop_theme()
+
+    def use_theme(self, theme: Theme, *, inherit: bool = True) -> ThemeContext:
+        """Use a different theme for the duration of the context manager.
+
+        Args:
+            theme (Theme): Theme instance to user.
+            inherit (bool, optional): Inherit existing console styles. Defaults to True.
+
+        Returns:
+            ThemeContext: [description]
+        """
+        return ThemeContext(self, theme, inherit)
+
+    @property
+    def color_system(self) -> Optional[str]:
+        """Get color system string.
+
+        Returns:
+            Optional[str]: "standard", "256" or "truecolor".
+        """
+
+        if self._color_system is not None:
+            return _COLOR_SYSTEMS_NAMES[self._color_system]
+        else:
+            return None
+
+    @property
+    def encoding(self) -> str:
+        """Get the encoding of the console file, e.g. ``"utf-8"``.
+
+        Returns:
+            str: A standard encoding string.
+        """
+        return (getattr(self.file, "encoding", "utf-8") or "utf-8").lower()
+
+    @property
+    def is_terminal(self) -> bool:
+        """Check if the console is writing to a terminal.
+
+        Returns:
+            bool: True if the console writing to a device capable of
+            understanding terminal codes, otherwise False.
+        """
+        if self._force_terminal is not None:
+            return self._force_terminal
+
+        if hasattr(sys.stdin, "__module__") and sys.stdin.__module__.startswith(
+            "idlelib"
+        ):
+            # Return False for Idle which claims to be a tty but can't handle ansi codes
+            return False
+
+        isatty: Optional[Callable[[], bool]] = getattr(self.file, "isatty", None)
+        try:
+            return False if isatty is None else isatty()
+        except ValueError:
+            # in some situation (at the end of a pytest run for example) isatty() can raise
+            # ValueError: I/O operation on closed file
+            # return False because we aren't in a terminal anymore
+            return False
+
+    @property
+    def is_dumb_terminal(self) -> bool:
+        """Detect dumb terminal.
+
+        Returns:
+            bool: True if writing to a dumb terminal, otherwise False.
+
+        """
+        _term = self._environ.get("TERM", "")
+        is_dumb = _term.lower() in ("dumb", "unknown")
+        return self.is_terminal and is_dumb
+
+    @property
+    def options(self) -> ConsoleOptions:
+        """Get default console options."""
+        return ConsoleOptions(
+            max_height=self.size.height,
+            size=self.size,
+            legacy_windows=self.legacy_windows,
+            min_width=1,
+            max_width=self.width,
+            encoding=self.encoding,
+            is_terminal=self.is_terminal,
+        )
+
+    @property
+    def size(self) -> ConsoleDimensions:
+        """Get the size of the console.
+
+        Returns:
+            ConsoleDimensions: A named tuple containing the dimensions.
+        """
+
+        if self._width is not None and self._height is not None:
+            return ConsoleDimensions(self._width - self.legacy_windows, self._height)
+
+        if self.is_dumb_terminal:
+            return ConsoleDimensions(80, 25)
+
+        width: Optional[int] = None
+        height: Optional[int] = None
+
+        if WINDOWS:  # pragma: no cover
+            try:
+                width, height = os.get_terminal_size()
+            except (AttributeError, ValueError, OSError):  # Probably not a terminal
+                pass
+        else:
+            for file_descriptor in _STD_STREAMS:
+                try:
+                    width, height = os.get_terminal_size(file_descriptor)
+                except (AttributeError, ValueError, OSError):
+                    pass
+                else:
+                    break
+
+        columns = self._environ.get("COLUMNS")
+        if columns is not None and columns.isdigit():
+            width = int(columns)
+        lines = self._environ.get("LINES")
+        if lines is not None and lines.isdigit():
+            height = int(lines)
+
+        # get_terminal_size can report 0, 0 if run from pseudo-terminal
+        width = width or 80
+        height = height or 25
+        return ConsoleDimensions(
+            width - self.legacy_windows if self._width is None else self._width,
+            height if self._height is None else self._height,
+        )
+
+    @size.setter
+    def size(self, new_size: Tuple[int, int]) -> None:
+        """Set a new size for the terminal.
+
+        Args:
+            new_size (Tuple[int, int]): New width and height.
+        """
+        width, height = new_size
+        self._width = width
+        self._height = height
+
+    @property
+    def width(self) -> int:
+        """Get the width of the console.
+
+        Returns:
+            int: The width (in characters) of the console.
+        """
+        return self.size.width
+
+    @width.setter
+    def width(self, width: int) -> None:
+        """Set width.
+
+        Args:
+            width (int): New width.
+        """
+        self._width = width
+
+    @property
+    def height(self) -> int:
+        """Get the height of the console.
+
+        Returns:
+            int: The height (in lines) of the console.
+        """
+        return self.size.height
+
+    @height.setter
+    def height(self, height: int) -> None:
+        """Set height.
+
+        Args:
+            height (int): new height.
+        """
+        self._height = height
+
+    def bell(self) -> None:
+        """Play a 'bell' sound (if supported by the terminal)."""
+        self.control(Control.bell())
+
+    def capture(self) -> Capture:
+        """A context manager to *capture* the result of print() or log() in a string,
+        rather than writing it to the console.
+
+        Example:
+            >>> from rich.console import Console
+            >>> console = Console()
+            >>> with console.capture() as capture:
+            ...     console.print("[bold magenta]Hello World[/]")
+            >>> print(capture.get())
+
+        Returns:
+            Capture: Context manager with disables writing to the terminal.
+        """
+        capture = Capture(self)
+        return capture
+
+    def pager(
+        self, pager: Optional[Pager] = None, styles: bool = False, links: bool = False
+    ) -> PagerContext:
+        """A context manager to display anything printed within a "pager". The pager application
+        is defined by the system and will typically support at least pressing a key to scroll.
+
+        Args:
+            pager (Pager, optional): A pager object, or None to use :class:`~rich.pager.SystemPager`. Defaults to None.
+            styles (bool, optional): Show styles in pager. Defaults to False.
+            links (bool, optional): Show links in pager. Defaults to False.
+
+        Example:
+            >>> from rich.console import Console
+            >>> from rich.__main__ import make_test_card
+            >>> console = Console()
+            >>> with console.pager():
+                    console.print(make_test_card())
+
+        Returns:
+            PagerContext: A context manager.
+        """
+        return PagerContext(self, pager=pager, styles=styles, links=links)
+
+    def line(self, count: int = 1) -> None:
+        """Write new line(s).
+
+        Args:
+            count (int, optional): Number of new lines. Defaults to 1.
+        """
+
+        assert count >= 0, "count must be >= 0"
+        self.print(NewLine(count))
+
+    def clear(self, home: bool = True) -> None:
+        """Clear the screen.
+
+        Args:
+            home (bool, optional): Also move the cursor to 'home' position. Defaults to True.
+        """
+        if home:
+            self.control(Control.clear(), Control.home())
+        else:
+            self.control(Control.clear())
+
+    def status(
+        self,
+        status: RenderableType,
+        *,
+        spinner: str = "dots",
+        spinner_style: str = "status.spinner",
+        speed: float = 1.0,
+        refresh_per_second: float = 12.5,
+    ) -> "Status":
+        """Display a status and spinner.
+
+        Args:
+            status (RenderableType): A status renderable (str or Text typically).
+            spinner (str, optional): Name of spinner animation (see python -m rich.spinner). Defaults to "dots".
+            spinner_style (StyleType, optional): Style of spinner. Defaults to "status.spinner".
+            speed (float, optional): Speed factor for spinner animation. Defaults to 1.0.
+            refresh_per_second (float, optional): Number of refreshes per second. Defaults to 12.5.
+
+        Returns:
+            Status: A Status object that may be used as a context manager.
+        """
+        from .status import Status
+
+        status_renderable = Status(
+            status,
+            console=self,
+            spinner=spinner,
+            spinner_style=spinner_style,
+            speed=speed,
+            refresh_per_second=refresh_per_second,
+        )
+        return status_renderable
+
+    def show_cursor(self, show: bool = True) -> bool:
+        """Show or hide the cursor.
+
+        Args:
+            show (bool, optional): Set visibility of the cursor.
+        """
+        if self.is_terminal:
+            self.control(Control.show_cursor(show))
+            return True
+        return False
+
+    def set_alt_screen(self, enable: bool = True) -> bool:
+        """Enables alternative screen mode.
+
+        Note, if you enable this mode, you should ensure that is disabled before
+        the application exits. See :meth:`~rich.Console.screen` for a context manager
+        that handles this for you.
+
+        Args:
+            enable (bool, optional): Enable (True) or disable (False) alternate screen. Defaults to True.
+
+        Returns:
+            bool: True if the control codes were written.
+
+        """
+        changed = False
+        if self.is_terminal and not self.legacy_windows:
+            self.control(Control.alt_screen(enable))
+            changed = True
+            self._is_alt_screen = enable
+        return changed
+
+    @property
+    def is_alt_screen(self) -> bool:
+        """Check if the alt screen was enabled.
+
+        Returns:
+            bool: True if the alt screen was enabled, otherwise False.
+        """
+        return self._is_alt_screen
+
+    def set_window_title(self, title: str) -> bool:
+        """Set the title of the console terminal window.
+
+        Warning: There is no means within Rich of "resetting" the window title to its
+        previous value, meaning the title you set will persist even after your application
+        exits.
+
+        ``fish`` shell resets the window title before and after each command by default,
+        negating this issue. Windows Terminal and command prompt will also reset the title for you.
+        Most other shells and terminals, however, do not do this.
+
+        Some terminals may require configuration changes before you can set the title.
+        Some terminals may not support setting the title at all.
+
+        Other software (including the terminal itself, the shell, custom prompts, plugins, etc.)
+        may also set the terminal window title. This could result in whatever value you write
+        using this method being overwritten.
+
+        Args:
+            title (str): The new title of the terminal window.
+
+        Returns:
+            bool: True if the control code to change the terminal title was
+                written, otherwise False. Note that a return value of True
+                does not guarantee that the window title has actually changed,
+                since the feature may be unsupported/disabled in some terminals.
+        """
+        if self.is_terminal:
+            self.control(Control.title(title))
+            return True
+        return False
+
+    def screen(
+        self, hide_cursor: bool = True, style: Optional[StyleType] = None
+    ) -> "ScreenContext":
+        """Context manager to enable and disable 'alternative screen' mode.
+
+        Args:
+            hide_cursor (bool, optional): Also hide the cursor. Defaults to False.
+            style (Style, optional): Optional style for screen. Defaults to None.
+
+        Returns:
+            ~ScreenContext: Context which enables alternate screen on enter, and disables it on exit.
+        """
+        return ScreenContext(self, hide_cursor=hide_cursor, style=style or "")
+
+    def measure(
+        self, renderable: RenderableType, *, options: Optional[ConsoleOptions] = None
+    ) -> Measurement:
+        """Measure a renderable. Returns a :class:`~rich.measure.Measurement` object which contains
+        information regarding the number of characters required to print the renderable.
+
+        Args:
+            renderable (RenderableType): Any renderable or string.
+            options (Optional[ConsoleOptions], optional): Options to use when measuring, or None
+                to use default options. Defaults to None.
+
+        Returns:
+            Measurement: A measurement of the renderable.
+        """
+        measurement = Measurement.get(self, options or self.options, renderable)
+        return measurement
+
+    def render(
+        self, renderable: RenderableType, options: Optional[ConsoleOptions] = None
+    ) -> Iterable[Segment]:
+        """Render an object in to an iterable of `Segment` instances.
+
+        This method contains the logic for rendering objects with the console protocol.
+        You are unlikely to need to use it directly, unless you are extending the library.
+
+        Args:
+            renderable (RenderableType): An object supporting the console protocol, or
+                an object that may be converted to a string.
+            options (ConsoleOptions, optional): An options object, or None to use self.options. Defaults to None.
+
+        Returns:
+            Iterable[Segment]: An iterable of segments that may be rendered.
+        """
+
+        _options = options or self.options
+        if _options.max_width < 1:
+            # No space to render anything. This prevents potential recursion errors.
+            return
+        render_iterable: RenderResult
+
+        renderable = rich_cast(renderable)
+        if hasattr(renderable, "__rich_console__") and not isclass(renderable):
+            render_iterable = renderable.__rich_console__(self, _options)  # type: ignore[union-attr]
+        elif isinstance(renderable, str):
+            text_renderable = self.render_str(
+                renderable, highlight=_options.highlight, markup=_options.markup
+            )
+            render_iterable = text_renderable.__rich_console__(self, _options)
+        else:
+            raise errors.NotRenderableError(
+                f"Unable to render {renderable!r}; "
+                "A str, Segment or object with __rich_console__ method is required"
+            )
+
+        try:
+            iter_render = iter(render_iterable)
+        except TypeError:
+            raise errors.NotRenderableError(
+                f"object {render_iterable!r} is not renderable"
+            )
+        _Segment = Segment
+        _options = _options.reset_height()
+        for render_output in iter_render:
+            if isinstance(render_output, _Segment):
+                yield render_output
+            else:
+                yield from self.render(render_output, _options)
+
+    def render_lines(
+        self,
+        renderable: RenderableType,
+        options: Optional[ConsoleOptions] = None,
+        *,
+        style: Optional[Style] = None,
+        pad: bool = True,
+        new_lines: bool = False,
+    ) -> List[List[Segment]]:
+        """Render objects in to a list of lines.
+
+        The output of render_lines is useful when further formatting of rendered console text
+        is required, such as the Panel class which draws a border around any renderable object.
+
+        Args:
+            renderable (RenderableType): Any object renderable in the console.
+            options (Optional[ConsoleOptions], optional): Console options, or None to use self.options. Default to ``None``.
+            style (Style, optional): Optional style to apply to renderables. Defaults to ``None``.
+            pad (bool, optional): Pad lines shorter than render width. Defaults to ``True``.
+            new_lines (bool, optional): Include "\n" characters at end of lines.
+
+        Returns:
+            List[List[Segment]]: A list of lines, where a line is a list of Segment objects.
+        """
+        with self._lock:
+            render_options = options or self.options
+            _rendered = self.render(renderable, render_options)
+            if style:
+                _rendered = Segment.apply_style(_rendered, style)
+
+            render_height = render_options.height
+            if render_height is not None:
+                render_height = max(0, render_height)
+
+            lines = list(
+                islice(
+                    Segment.split_and_crop_lines(
+                        _rendered,
+                        render_options.max_width,
+                        include_new_lines=new_lines,
+                        pad=pad,
+                        style=style,
+                    ),
+                    None,
+                    render_height,
+                )
+            )
+            if render_options.height is not None:
+                extra_lines = render_options.height - len(lines)
+                if extra_lines > 0:
+                    pad_line = [
+                        [Segment(" " * render_options.max_width, style), Segment("\n")]
+                        if new_lines
+                        else [Segment(" " * render_options.max_width, style)]
+                    ]
+                    lines.extend(pad_line * extra_lines)
+
+            return lines
+
+    def render_str(
+        self,
+        text: str,
+        *,
+        style: Union[str, Style] = "",
+        justify: Optional[JustifyMethod] = None,
+        overflow: Optional[OverflowMethod] = None,
+        emoji: Optional[bool] = None,
+        markup: Optional[bool] = None,
+        highlight: Optional[bool] = None,
+        highlighter: Optional[HighlighterType] = None,
+    ) -> "Text":
+        """Convert a string to a Text instance. This is called automatically if
+        you print or log a string.
+
+        Args:
+            text (str): Text to render.
+            style (Union[str, Style], optional): Style to apply to rendered text.
+            justify (str, optional): Justify method: "default", "left", "center", "full", or "right". Defaults to ``None``.
+            overflow (str, optional): Overflow method: "crop", "fold", or "ellipsis". Defaults to ``None``.
+            emoji (Optional[bool], optional): Enable emoji, or ``None`` to use Console default.
+            markup (Optional[bool], optional): Enable markup, or ``None`` to use Console default.
+            highlight (Optional[bool], optional): Enable highlighting, or ``None`` to use Console default.
+            highlighter (HighlighterType, optional): Optional highlighter to apply.
+        Returns:
+            ConsoleRenderable: Renderable object.
+
+        """
+        emoji_enabled = emoji or (emoji is None and self._emoji)
+        markup_enabled = markup or (markup is None and self._markup)
+        highlight_enabled = highlight or (highlight is None and self._highlight)
+
+        if markup_enabled:
+            rich_text = render_markup(
+                text,
+                style=style,
+                emoji=emoji_enabled,
+                emoji_variant=self._emoji_variant,
+            )
+            rich_text.justify = justify
+            rich_text.overflow = overflow
+        else:
+            rich_text = Text(
+                _emoji_replace(text, default_variant=self._emoji_variant)
+                if emoji_enabled
+                else text,
+                justify=justify,
+                overflow=overflow,
+                style=style,
+            )
+
+        _highlighter = (highlighter or self.highlighter) if highlight_enabled else None
+        if _highlighter is not None:
+            highlight_text = _highlighter(str(rich_text))
+            highlight_text.copy_styles(rich_text)
+            return highlight_text
+
+        return rich_text
+
+    def get_style(
+        self, name: Union[str, Style], *, default: Optional[Union[Style, str]] = None
+    ) -> Style:
+        """Get a Style instance by its theme name or parse a definition.
+
+        Args:
+            name (str): The name of a style or a style definition.
+
+        Returns:
+            Style: A Style object.
+
+        Raises:
+            MissingStyle: If no style could be parsed from name.
+
+        """
+        if isinstance(name, Style):
+            return name
+
+        try:
+            style = self._theme_stack.get(name)
+            if style is None:
+                style = Style.parse(name)
+            return style.copy() if style.link else style
+        except errors.StyleSyntaxError as error:
+            if default is not None:
+                return self.get_style(default)
+            raise errors.MissingStyle(
+                f"Failed to get style {name!r}; {error}"
+            ) from None
+
+    def _collect_renderables(
+        self,
+        objects: Iterable[Any],
+        sep: str,
+        end: str,
+        *,
+        justify: Optional[JustifyMethod] = None,
+        emoji: Optional[bool] = None,
+        markup: Optional[bool] = None,
+        highlight: Optional[bool] = None,
+    ) -> List[ConsoleRenderable]:
+        """Combine a number of renderables and text into one renderable.
+
+        Args:
+            objects (Iterable[Any]): Anything that Rich can render.
+            sep (str): String to write between print data.
+            end (str): String to write at end of print data.
+            justify (str, optional): One of "left", "right", "center", or "full". Defaults to ``None``.
+            emoji (Optional[bool], optional): Enable emoji code, or ``None`` to use console default.
+            markup (Optional[bool], optional): Enable markup, or ``None`` to use console default.
+            highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use console default.
+
+        Returns:
+            List[ConsoleRenderable]: A list of things to render.
+        """
+        renderables: List[ConsoleRenderable] = []
+        _append = renderables.append
+        text: List[Text] = []
+        append_text = text.append
+
+        append = _append
+        if justify in ("left", "center", "right"):
+
+            def align_append(renderable: RenderableType) -> None:
+                _append(Align(renderable, cast(AlignMethod, justify)))
+
+            append = align_append
+
+        _highlighter: HighlighterType = _null_highlighter
+        if highlight or (highlight is None and self._highlight):
+            _highlighter = self.highlighter
+
+        def check_text() -> None:
+            if text:
+                sep_text = Text(sep, justify=justify, end=end)
+                append(sep_text.join(text))
+                del text[:]
+
+        for renderable in objects:
+            renderable = rich_cast(renderable)
+            if isinstance(renderable, str):
+                append_text(
+                    self.render_str(
+                        renderable, emoji=emoji, markup=markup, highlighter=_highlighter
+                    )
+                )
+            elif isinstance(renderable, Text):
+                append_text(renderable)
+            elif isinstance(renderable, ConsoleRenderable):
+                check_text()
+                append(renderable)
+            elif is_expandable(renderable):
+                check_text()
+                append(Pretty(renderable, highlighter=_highlighter))
+            else:
+                append_text(_highlighter(str(renderable)))
+
+        check_text()
+
+        if self.style is not None:
+            style = self.get_style(self.style)
+            renderables = [Styled(renderable, style) for renderable in renderables]
+
+        return renderables
+
+    def rule(
+        self,
+        title: TextType = "",
+        *,
+        characters: str = "─",
+        style: Union[str, Style] = "rule.line",
+        align: AlignMethod = "center",
+    ) -> None:
+        """Draw a line with optional centered title.
+
+        Args:
+            title (str, optional): Text to render over the rule. Defaults to "".
+            characters (str, optional): Character(s) to form the line. Defaults to "─".
+            style (str, optional): Style of line. Defaults to "rule.line".
+            align (str, optional): How to align the title, one of "left", "center", or "right". Defaults to "center".
+        """
+        from .rule import Rule
+
+        rule = Rule(title=title, characters=characters, style=style, align=align)
+        self.print(rule)
+
+    def control(self, *control: Control) -> None:
+        """Insert non-printing control codes.
+
+        Args:
+            control_codes (str): Control codes, such as those that may move the cursor.
+        """
+        if not self.is_dumb_terminal:
+            with self:
+                self._buffer.extend(_control.segment for _control in control)
+
+    def out(
+        self,
+        *objects: Any,
+        sep: str = " ",
+        end: str = "\n",
+        style: Optional[Union[str, Style]] = None,
+        highlight: Optional[bool] = None,
+    ) -> None:
+        """Output to the terminal. This is a low-level way of writing to the terminal which unlike
+        :meth:`~rich.console.Console.print` won't pretty print, wrap text, or apply markup, but will
+        optionally apply highlighting and a basic style.
+
+        Args:
+            sep (str, optional): String to write between print data. Defaults to " ".
+            end (str, optional): String to write at end of print data. Defaults to "\\\\n".
+            style (Union[str, Style], optional): A style to apply to output. Defaults to None.
+            highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use
+                console default. Defaults to ``None``.
+        """
+        raw_output: str = sep.join(str(_object) for _object in objects)
+        self.print(
+            raw_output,
+            style=style,
+            highlight=highlight,
+            emoji=False,
+            markup=False,
+            no_wrap=True,
+            overflow="ignore",
+            crop=False,
+            end=end,
+        )
+
+    def print(
+        self,
+        *objects: Any,
+        sep: str = " ",
+        end: str = "\n",
+        style: Optional[Union[str, Style]] = None,
+        justify: Optional[JustifyMethod] = None,
+        overflow: Optional[OverflowMethod] = None,
+        no_wrap: Optional[bool] = None,
+        emoji: Optional[bool] = None,
+        markup: Optional[bool] = None,
+        highlight: Optional[bool] = None,
+        width: Optional[int] = None,
+        height: Optional[int] = None,
+        crop: bool = True,
+        soft_wrap: Optional[bool] = None,
+        new_line_start: bool = False,
+    ) -> None:
+        """Print to the console.
+
+        Args:
+            objects (positional args): Objects to log to the terminal.
+            sep (str, optional): String to write between print data. Defaults to " ".
+            end (str, optional): String to write at end of print data. Defaults to "\\\\n".
+            style (Union[str, Style], optional): A style to apply to output. Defaults to None.
+            justify (str, optional): Justify method: "default", "left", "right", "center", or "full". Defaults to ``None``.
+            overflow (str, optional): Overflow method: "ignore", "crop", "fold", or "ellipsis". Defaults to None.
+            no_wrap (Optional[bool], optional): Disable word wrapping. Defaults to None.
+            emoji (Optional[bool], optional): Enable emoji code, or ``None`` to use console default. Defaults to ``None``.
+            markup (Optional[bool], optional): Enable markup, or ``None`` to use console default. Defaults to ``None``.
+            highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use console default. Defaults to ``None``.
+            width (Optional[int], optional): Width of output, or ``None`` to auto-detect. Defaults to ``None``.
+            crop (Optional[bool], optional): Crop output to width of terminal. Defaults to True.
+            soft_wrap (bool, optional): Enable soft wrap mode which disables word wrapping and cropping of text or ``None`` for
+                Console default. Defaults to ``None``.
+            new_line_start (bool, False): Insert a new line at the start if the output contains more than one line. Defaults to ``False``.
+        """
+        if not objects:
+            objects = (NewLine(),)
+
+        if soft_wrap is None:
+            soft_wrap = self.soft_wrap
+        if soft_wrap:
+            if no_wrap is None:
+                no_wrap = True
+            if overflow is None:
+                overflow = "ignore"
+            crop = False
+        render_hooks = self._render_hooks[:]
+        with self:
+            renderables = self._collect_renderables(
+                objects,
+                sep,
+                end,
+                justify=justify,
+                emoji=emoji,
+                markup=markup,
+                highlight=highlight,
+            )
+            for hook in render_hooks:
+                renderables = hook.process_renderables(renderables)
+            render_options = self.options.update(
+                justify=justify,
+                overflow=overflow,
+                width=min(width, self.width) if width is not None else NO_CHANGE,
+                height=height,
+                no_wrap=no_wrap,
+                markup=markup,
+                highlight=highlight,
+            )
+
+            new_segments: List[Segment] = []
+            extend = new_segments.extend
+            render = self.render
+            if style is None:
+                for renderable in renderables:
+                    extend(render(renderable, render_options))
+            else:
+                for renderable in renderables:
+                    extend(
+                        Segment.apply_style(
+                            render(renderable, render_options), self.get_style(style)
+                        )
+                    )
+            if new_line_start:
+                if (
+                    len("".join(segment.text for segment in new_segments).splitlines())
+                    > 1
+                ):
+                    new_segments.insert(0, Segment.line())
+            if crop:
+                buffer_extend = self._buffer.extend
+                for line in Segment.split_and_crop_lines(
+                    new_segments, self.width, pad=False
+                ):
+                    buffer_extend(line)
+            else:
+                self._buffer.extend(new_segments)
+
+    def print_json(
+        self,
+        json: Optional[str] = None,
+        *,
+        data: Any = None,
+        indent: Union[None, int, str] = 2,
+        highlight: bool = True,
+        skip_keys: bool = False,
+        ensure_ascii: bool = False,
+        check_circular: bool = True,
+        allow_nan: bool = True,
+        default: Optional[Callable[[Any], Any]] = None,
+        sort_keys: bool = False,
+    ) -> None:
+        """Pretty prints JSON. Output will be valid JSON.
+
+        Args:
+            json (Optional[str]): A string containing JSON.
+            data (Any): If json is not supplied, then encode this data.
+            indent (Union[None, int, str], optional): Number of spaces to indent. Defaults to 2.
+            highlight (bool, optional): Enable highlighting of output: Defaults to True.
+            skip_keys (bool, optional): Skip keys not of a basic type. Defaults to False.
+            ensure_ascii (bool, optional): Escape all non-ascii characters. Defaults to False.
+            check_circular (bool, optional): Check for circular references. Defaults to True.
+            allow_nan (bool, optional): Allow NaN and Infinity values. Defaults to True.
+            default (Callable, optional): A callable that converts values that can not be encoded
+                in to something that can be JSON encoded. Defaults to None.
+            sort_keys (bool, optional): Sort dictionary keys. Defaults to False.
+        """
+        from pip._vendor.rich.json import JSON
+
+        if json is None:
+            json_renderable = JSON.from_data(
+                data,
+                indent=indent,
+                highlight=highlight,
+                skip_keys=skip_keys,
+                ensure_ascii=ensure_ascii,
+                check_circular=check_circular,
+                allow_nan=allow_nan,
+                default=default,
+                sort_keys=sort_keys,
+            )
+        else:
+            if not isinstance(json, str):
+                raise TypeError(
+                    f"json must be str. Did you mean print_json(data={json!r}) ?"
+                )
+            json_renderable = JSON(
+                json,
+                indent=indent,
+                highlight=highlight,
+                skip_keys=skip_keys,
+                ensure_ascii=ensure_ascii,
+                check_circular=check_circular,
+                allow_nan=allow_nan,
+                default=default,
+                sort_keys=sort_keys,
+            )
+        self.print(json_renderable, soft_wrap=True)
+
+    def update_screen(
+        self,
+        renderable: RenderableType,
+        *,
+        region: Optional[Region] = None,
+        options: Optional[ConsoleOptions] = None,
+    ) -> None:
+        """Update the screen at a given offset.
+
+        Args:
+            renderable (RenderableType): A Rich renderable.
+            region (Region, optional): Region of screen to update, or None for entire screen. Defaults to None.
+            x (int, optional): x offset. Defaults to 0.
+            y (int, optional): y offset. Defaults to 0.
+
+        Raises:
+            errors.NoAltScreen: If the Console isn't in alt screen mode.
+
+        """
+        if not self.is_alt_screen:
+            raise errors.NoAltScreen("Alt screen must be enabled to call update_screen")
+        render_options = options or self.options
+        if region is None:
+            x = y = 0
+            render_options = render_options.update_dimensions(
+                render_options.max_width, render_options.height or self.height
+            )
+        else:
+            x, y, width, height = region
+            render_options = render_options.update_dimensions(width, height)
+
+        lines = self.render_lines(renderable, options=render_options)
+        self.update_screen_lines(lines, x, y)
+
+    def update_screen_lines(
+        self, lines: List[List[Segment]], x: int = 0, y: int = 0
+    ) -> None:
+        """Update lines of the screen at a given offset.
+
+        Args:
+            lines (List[List[Segment]]): Rendered lines (as produced by :meth:`~rich.Console.render_lines`).
+            x (int, optional): x offset (column no). Defaults to 0.
+            y (int, optional): y offset (column no). Defaults to 0.
+
+        Raises:
+            errors.NoAltScreen: If the Console isn't in alt screen mode.
+        """
+        if not self.is_alt_screen:
+            raise errors.NoAltScreen("Alt screen must be enabled to call update_screen")
+        screen_update = ScreenUpdate(lines, x, y)
+        segments = self.render(screen_update)
+        self._buffer.extend(segments)
+        self._check_buffer()
+
+    def print_exception(
+        self,
+        *,
+        width: Optional[int] = 100,
+        extra_lines: int = 3,
+        theme: Optional[str] = None,
+        word_wrap: bool = False,
+        show_locals: bool = False,
+        suppress: Iterable[Union[str, ModuleType]] = (),
+        max_frames: int = 100,
+    ) -> None:
+        """Prints a rich render of the last exception and traceback.
+
+        Args:
+            width (Optional[int], optional): Number of characters used to render code. Defaults to 100.
+            extra_lines (int, optional): Additional lines of code to render. Defaults to 3.
+            theme (str, optional): Override pygments theme used in traceback
+            word_wrap (bool, optional): Enable word wrapping of long lines. Defaults to False.
+            show_locals (bool, optional): Enable display of local variables. Defaults to False.
+            suppress (Iterable[Union[str, ModuleType]]): Optional sequence of modules or paths to exclude from traceback.
+            max_frames (int): Maximum number of frames to show in a traceback, 0 for no maximum. Defaults to 100.
+        """
+        from .traceback import Traceback
+
+        traceback = Traceback(
+            width=width,
+            extra_lines=extra_lines,
+            theme=theme,
+            word_wrap=word_wrap,
+            show_locals=show_locals,
+            suppress=suppress,
+            max_frames=max_frames,
+        )
+        self.print(traceback)
+
+    @staticmethod
+    def _caller_frame_info(
+        offset: int,
+        currentframe: Callable[[], Optional[FrameType]] = inspect.currentframe,
+    ) -> Tuple[str, int, Dict[str, Any]]:
+        """Get caller frame information.
+
+        Args:
+            offset (int): the caller offset within the current frame stack.
+            currentframe (Callable[[], Optional[FrameType]], optional): the callable to use to
+                retrieve the current frame. Defaults to ``inspect.currentframe``.
+
+        Returns:
+            Tuple[str, int, Dict[str, Any]]: A tuple containing the filename, the line number and
+                the dictionary of local variables associated with the caller frame.
+
+        Raises:
+            RuntimeError: If the stack offset is invalid.
+        """
+        # Ignore the frame of this local helper
+        offset += 1
+
+        frame = currentframe()
+        if frame is not None:
+            # Use the faster currentframe where implemented
+            while offset and frame is not None:
+                frame = frame.f_back
+                offset -= 1
+            assert frame is not None
+            return frame.f_code.co_filename, frame.f_lineno, frame.f_locals
+        else:
+            # Fallback to the slower stack
+            frame_info = inspect.stack()[offset]
+            return frame_info.filename, frame_info.lineno, frame_info.frame.f_locals
+
+    def log(
+        self,
+        *objects: Any,
+        sep: str = " ",
+        end: str = "\n",
+        style: Optional[Union[str, Style]] = None,
+        justify: Optional[JustifyMethod] = None,
+        emoji: Optional[bool] = None,
+        markup: Optional[bool] = None,
+        highlight: Optional[bool] = None,
+        log_locals: bool = False,
+        _stack_offset: int = 1,
+    ) -> None:
+        """Log rich content to the terminal.
+
+        Args:
+            objects (positional args): Objects to log to the terminal.
+            sep (str, optional): String to write between print data. Defaults to " ".
+            end (str, optional): String to write at end of print data. Defaults to "\\\\n".
+            style (Union[str, Style], optional): A style to apply to output. Defaults to None.
+            justify (str, optional): One of "left", "right", "center", or "full". Defaults to ``None``.
+            overflow (str, optional): Overflow method: "crop", "fold", or "ellipsis". Defaults to None.
+            emoji (Optional[bool], optional): Enable emoji code, or ``None`` to use console default. Defaults to None.
+            markup (Optional[bool], optional): Enable markup, or ``None`` to use console default. Defaults to None.
+            highlight (Optional[bool], optional): Enable automatic highlighting, or ``None`` to use console default. Defaults to None.
+            log_locals (bool, optional): Boolean to enable logging of locals where ``log()``
+                was called. Defaults to False.
+            _stack_offset (int, optional): Offset of caller from end of call stack. Defaults to 1.
+        """
+        if not objects:
+            objects = (NewLine(),)
+
+        render_hooks = self._render_hooks[:]
+
+        with self:
+            renderables = self._collect_renderables(
+                objects,
+                sep,
+                end,
+                justify=justify,
+                emoji=emoji,
+                markup=markup,
+                highlight=highlight,
+            )
+            if style is not None:
+                renderables = [Styled(renderable, style) for renderable in renderables]
+
+            filename, line_no, locals = self._caller_frame_info(_stack_offset)
+            link_path = None if filename.startswith("<") else os.path.abspath(filename)
+            path = filename.rpartition(os.sep)[-1]
+            if log_locals:
+                locals_map = {
+                    key: value
+                    for key, value in locals.items()
+                    if not key.startswith("__")
+                }
+                renderables.append(render_scope(locals_map, title="[i]locals"))
+
+            renderables = [
+                self._log_render(
+                    self,
+                    renderables,
+                    log_time=self.get_datetime(),
+                    path=path,
+                    line_no=line_no,
+                    link_path=link_path,
+                )
+            ]
+            for hook in render_hooks:
+                renderables = hook.process_renderables(renderables)
+            new_segments: List[Segment] = []
+            extend = new_segments.extend
+            render = self.render
+            render_options = self.options
+            for renderable in renderables:
+                extend(render(renderable, render_options))
+            buffer_extend = self._buffer.extend
+            for line in Segment.split_and_crop_lines(
+                new_segments, self.width, pad=False
+            ):
+                buffer_extend(line)
+
+    def _check_buffer(self) -> None:
+        """Check if the buffer may be rendered. Render it if it can (e.g. Console.quiet is False)
+        Rendering is supported on Windows, Unix and Jupyter environments. For
+        legacy Windows consoles, the win32 API is called directly.
+        This method will also record what it renders if recording is enabled via Console.record.
+        """
+        if self.quiet:
+            del self._buffer[:]
+            return
+        with self._lock:
+            if self.record:
+                with self._record_buffer_lock:
+                    self._record_buffer.extend(self._buffer[:])
+
+            if self._buffer_index == 0:
+
+                if self.is_jupyter:  # pragma: no cover
+                    from .jupyter import display
+
+                    display(self._buffer, self._render_buffer(self._buffer[:]))
+                    del self._buffer[:]
+                else:
+                    if WINDOWS:
+                        use_legacy_windows_render = False
+                        if self.legacy_windows:
+                            try:
+                                use_legacy_windows_render = (
+                                    self.file.fileno() in _STD_STREAMS_OUTPUT
+                                )
+                            except (ValueError, io.UnsupportedOperation):
+                                pass
+
+                        if use_legacy_windows_render:
+                            from pip._vendor.rich._win32_console import LegacyWindowsTerm
+                            from pip._vendor.rich._windows_renderer import legacy_windows_render
+
+                            buffer = self._buffer[:]
+                            if self.no_color and self._color_system:
+                                buffer = list(Segment.remove_color(buffer))
+
+                            legacy_windows_render(buffer, LegacyWindowsTerm(self.file))
+                        else:
+                            # Either a non-std stream on legacy Windows, or modern Windows.
+                            text = self._render_buffer(self._buffer[:])
+                            # https://bugs.python.org/issue37871
+                            write = self.file.write
+                            for line in text.splitlines(True):
+                                try:
+                                    write(line)
+                                except UnicodeEncodeError as error:
+                                    error.reason = f"{error.reason}\n*** You may need to add PYTHONIOENCODING=utf-8 to your environment ***"
+                                    raise
+                    else:
+                        text = self._render_buffer(self._buffer[:])
+                        try:
+                            self.file.write(text)
+                        except UnicodeEncodeError as error:
+                            error.reason = f"{error.reason}\n*** You may need to add PYTHONIOENCODING=utf-8 to your environment ***"
+                            raise
+
+                    self.file.flush()
+                    del self._buffer[:]
+
+    def _render_buffer(self, buffer: Iterable[Segment]) -> str:
+        """Render buffered output, and clear buffer."""
+        output: List[str] = []
+        append = output.append
+        color_system = self._color_system
+        legacy_windows = self.legacy_windows
+        not_terminal = not self.is_terminal
+        if self.no_color and color_system:
+            buffer = Segment.remove_color(buffer)
+        for text, style, control in buffer:
+            if style:
+                append(
+                    style.render(
+                        text,
+                        color_system=color_system,
+                        legacy_windows=legacy_windows,
+                    )
+                )
+            elif not (not_terminal and control):
+                append(text)
+
+        rendered = "".join(output)
+        return rendered
+
+    def input(
+        self,
+        prompt: TextType = "",
+        *,
+        markup: bool = True,
+        emoji: bool = True,
+        password: bool = False,
+        stream: Optional[TextIO] = None,
+    ) -> str:
+        """Displays a prompt and waits for input from the user. The prompt may contain color / style.
+
+        It works in the same way as Python's builtin :func:`input` function and provides elaborate line editing and history features if Python's builtin :mod:`readline` module is previously loaded.
+
+        Args:
+            prompt (Union[str, Text]): Text to render in the prompt.
+            markup (bool, optional): Enable console markup (requires a str prompt). Defaults to True.
+            emoji (bool, optional): Enable emoji (requires a str prompt). Defaults to True.
+            password: (bool, optional): Hide typed text. Defaults to False.
+            stream: (TextIO, optional): Optional file to read input from (rather than stdin). Defaults to None.
+
+        Returns:
+            str: Text read from stdin.
+        """
+        if prompt:
+            self.print(prompt, markup=markup, emoji=emoji, end="")
+        if password:
+            result = getpass("", stream=stream)
+        else:
+            if stream:
+                result = stream.readline()
+            else:
+                result = input()
+        return result
+
+    def export_text(self, *, clear: bool = True, styles: bool = False) -> str:
+        """Generate text from console contents (requires record=True argument in constructor).
+
+        Args:
+            clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``.
+            styles (bool, optional): If ``True``, ansi escape codes will be included. ``False`` for plain text.
+                Defaults to ``False``.
+
+        Returns:
+            str: String containing console contents.
+
+        """
+        assert (
+            self.record
+        ), "To export console contents set record=True in the constructor or instance"
+
+        with self._record_buffer_lock:
+            if styles:
+                text = "".join(
+                    (style.render(text) if style else text)
+                    for text, style, _ in self._record_buffer
+                )
+            else:
+                text = "".join(
+                    segment.text
+                    for segment in self._record_buffer
+                    if not segment.control
+                )
+            if clear:
+                del self._record_buffer[:]
+        return text
+
+    def save_text(self, path: str, *, clear: bool = True, styles: bool = False) -> None:
+        """Generate text from console and save to a given location (requires record=True argument in constructor).
+
+        Args:
+            path (str): Path to write text files.
+            clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``.
+            styles (bool, optional): If ``True``, ansi style codes will be included. ``False`` for plain text.
+                Defaults to ``False``.
+
+        """
+        text = self.export_text(clear=clear, styles=styles)
+        with open(path, "wt", encoding="utf-8") as write_file:
+            write_file.write(text)
+
+    def export_html(
+        self,
+        *,
+        theme: Optional[TerminalTheme] = None,
+        clear: bool = True,
+        code_format: Optional[str] = None,
+        inline_styles: bool = False,
+    ) -> str:
+        """Generate HTML from console contents (requires record=True argument in constructor).
+
+        Args:
+            theme (TerminalTheme, optional): TerminalTheme object containing console colors.
+            clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``.
+            code_format (str, optional): Format string to render HTML. In addition to '{foreground}',
+                '{background}', and '{code}', should contain '{stylesheet}' if inline_styles is ``False``.
+            inline_styles (bool, optional): If ``True`` styles will be inlined in to spans, which makes files
+                larger but easier to cut and paste markup. If ``False``, styles will be embedded in a style tag.
+                Defaults to False.
+
+        Returns:
+            str: String containing console contents as HTML.
+        """
+        assert (
+            self.record
+        ), "To export console contents set record=True in the constructor or instance"
+        fragments: List[str] = []
+        append = fragments.append
+        _theme = theme or DEFAULT_TERMINAL_THEME
+        stylesheet = ""
+
+        render_code_format = CONSOLE_HTML_FORMAT if code_format is None else code_format
+
+        with self._record_buffer_lock:
+            if inline_styles:
+                for text, style, _ in Segment.filter_control(
+                    Segment.simplify(self._record_buffer)
+                ):
+                    text = escape(text)
+                    if style:
+                        rule = style.get_html_style(_theme)
+                        if style.link:
+                            text = f'{text}'
+                        text = f'{text}' if rule else text
+                    append(text)
+            else:
+                styles: Dict[str, int] = {}
+                for text, style, _ in Segment.filter_control(
+                    Segment.simplify(self._record_buffer)
+                ):
+                    text = escape(text)
+                    if style:
+                        rule = style.get_html_style(_theme)
+                        style_number = styles.setdefault(rule, len(styles) + 1)
+                        if style.link:
+                            text = f'{text}'
+                        else:
+                            text = f'{text}'
+                    append(text)
+                stylesheet_rules: List[str] = []
+                stylesheet_append = stylesheet_rules.append
+                for style_rule, style_number in styles.items():
+                    if style_rule:
+                        stylesheet_append(f".r{style_number} {{{style_rule}}}")
+                stylesheet = "\n".join(stylesheet_rules)
+
+            rendered_code = render_code_format.format(
+                code="".join(fragments),
+                stylesheet=stylesheet,
+                foreground=_theme.foreground_color.hex,
+                background=_theme.background_color.hex,
+            )
+            if clear:
+                del self._record_buffer[:]
+        return rendered_code
+
+    def save_html(
+        self,
+        path: str,
+        *,
+        theme: Optional[TerminalTheme] = None,
+        clear: bool = True,
+        code_format: str = CONSOLE_HTML_FORMAT,
+        inline_styles: bool = False,
+    ) -> None:
+        """Generate HTML from console contents and write to a file (requires record=True argument in constructor).
+
+        Args:
+            path (str): Path to write html file.
+            theme (TerminalTheme, optional): TerminalTheme object containing console colors.
+            clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``.
+            code_format (str, optional): Format string to render HTML. In addition to '{foreground}',
+                '{background}', and '{code}', should contain '{stylesheet}' if inline_styles is ``False``.
+            inline_styles (bool, optional): If ``True`` styles will be inlined in to spans, which makes files
+                larger but easier to cut and paste markup. If ``False``, styles will be embedded in a style tag.
+                Defaults to False.
+
+        """
+        html = self.export_html(
+            theme=theme,
+            clear=clear,
+            code_format=code_format,
+            inline_styles=inline_styles,
+        )
+        with open(path, "wt", encoding="utf-8") as write_file:
+            write_file.write(html)
+
+    def export_svg(
+        self,
+        *,
+        title: str = "Rich",
+        theme: Optional[TerminalTheme] = None,
+        clear: bool = True,
+        code_format: str = CONSOLE_SVG_FORMAT,
+        font_aspect_ratio: float = 0.61,
+        unique_id: Optional[str] = None,
+    ) -> str:
+        """
+        Generate an SVG from the console contents (requires record=True in Console constructor).
+
+        Args:
+            title (str, optional): The title of the tab in the output image
+            theme (TerminalTheme, optional): The ``TerminalTheme`` object to use to style the terminal
+            clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``
+            code_format (str, optional): Format string used to generate the SVG. Rich will inject a number of variables
+                into the string in order to form the final SVG output. The default template used and the variables
+                injected by Rich can be found by inspecting the ``console.CONSOLE_SVG_FORMAT`` variable.
+            font_aspect_ratio (float, optional): The width to height ratio of the font used in the ``code_format``
+                string. Defaults to 0.61, which is the width to height ratio of Fira Code (the default font).
+                If you aren't specifying a different font inside ``code_format``, you probably don't need this.
+            unique_id (str, optional): unique id that is used as the prefix for various elements (CSS styles, node
+                ids). If not set, this defaults to a computed value based on the recorded content.
+        """
+
+        from pip._vendor.rich.cells import cell_len
+
+        style_cache: Dict[Style, str] = {}
+
+        def get_svg_style(style: Style) -> str:
+            """Convert a Style to CSS rules for SVG."""
+            if style in style_cache:
+                return style_cache[style]
+            css_rules = []
+            color = (
+                _theme.foreground_color
+                if (style.color is None or style.color.is_default)
+                else style.color.get_truecolor(_theme)
+            )
+            bgcolor = (
+                _theme.background_color
+                if (style.bgcolor is None or style.bgcolor.is_default)
+                else style.bgcolor.get_truecolor(_theme)
+            )
+            if style.reverse:
+                color, bgcolor = bgcolor, color
+            if style.dim:
+                color = blend_rgb(color, bgcolor, 0.4)
+            css_rules.append(f"fill: {color.hex}")
+            if style.bold:
+                css_rules.append("font-weight: bold")
+            if style.italic:
+                css_rules.append("font-style: italic;")
+            if style.underline:
+                css_rules.append("text-decoration: underline;")
+            if style.strike:
+                css_rules.append("text-decoration: line-through;")
+
+            css = ";".join(css_rules)
+            style_cache[style] = css
+            return css
+
+        _theme = theme or SVG_EXPORT_THEME
+
+        width = self.width
+        char_height = 20
+        char_width = char_height * font_aspect_ratio
+        line_height = char_height * 1.22
+
+        margin_top = 1
+        margin_right = 1
+        margin_bottom = 1
+        margin_left = 1
+
+        padding_top = 40
+        padding_right = 8
+        padding_bottom = 8
+        padding_left = 8
+
+        padding_width = padding_left + padding_right
+        padding_height = padding_top + padding_bottom
+        margin_width = margin_left + margin_right
+        margin_height = margin_top + margin_bottom
+
+        text_backgrounds: List[str] = []
+        text_group: List[str] = []
+        classes: Dict[str, int] = {}
+        style_no = 1
+
+        def escape_text(text: str) -> str:
+            """HTML escape text and replace spaces with nbsp."""
+            return escape(text).replace(" ", " ")
+
+        def make_tag(
+            name: str, content: Optional[str] = None, **attribs: object
+        ) -> str:
+            """Make a tag from name, content, and attributes."""
+
+            def stringify(value: object) -> str:
+                if isinstance(value, (float)):
+                    return format(value, "g")
+                return str(value)
+
+            tag_attribs = " ".join(
+                f'{k.lstrip("_").replace("_", "-")}="{stringify(v)}"'
+                for k, v in attribs.items()
+            )
+            return (
+                f"<{name} {tag_attribs}>{content}"
+                if content
+                else f"<{name} {tag_attribs}/>"
+            )
+
+        with self._record_buffer_lock:
+            segments = list(Segment.filter_control(self._record_buffer))
+            if clear:
+                self._record_buffer.clear()
+
+        if unique_id is None:
+            unique_id = "terminal-" + str(
+                zlib.adler32(
+                    ("".join(repr(segment) for segment in segments)).encode(
+                        "utf-8",
+                        "ignore",
+                    )
+                    + title.encode("utf-8", "ignore")
+                )
+            )
+        y = 0
+        for y, line in enumerate(Segment.split_and_crop_lines(segments, length=width)):
+            x = 0
+            for text, style, _control in line:
+                style = style or Style()
+                rules = get_svg_style(style)
+                if rules not in classes:
+                    classes[rules] = style_no
+                    style_no += 1
+                class_name = f"r{classes[rules]}"
+
+                if style.reverse:
+                    has_background = True
+                    background = (
+                        _theme.foreground_color.hex
+                        if style.color is None
+                        else style.color.get_truecolor(_theme).hex
+                    )
+                else:
+                    bgcolor = style.bgcolor
+                    has_background = bgcolor is not None and not bgcolor.is_default
+                    background = (
+                        _theme.background_color.hex
+                        if style.bgcolor is None
+                        else style.bgcolor.get_truecolor(_theme).hex
+                    )
+
+                text_length = cell_len(text)
+                if has_background:
+                    text_backgrounds.append(
+                        make_tag(
+                            "rect",
+                            fill=background,
+                            x=x * char_width,
+                            y=y * line_height + 1.5,
+                            width=char_width * text_length,
+                            height=line_height + 0.25,
+                            shape_rendering="crispEdges",
+                        )
+                    )
+
+                if text != " " * len(text):
+                    text_group.append(
+                        make_tag(
+                            "text",
+                            escape_text(text),
+                            _class=f"{unique_id}-{class_name}",
+                            x=x * char_width,
+                            y=y * line_height + char_height,
+                            textLength=char_width * len(text),
+                            clip_path=f"url(#{unique_id}-line-{y})",
+                        )
+                    )
+                x += cell_len(text)
+
+        line_offsets = [line_no * line_height + 1.5 for line_no in range(y)]
+        lines = "\n".join(
+            f"""
+    {make_tag("rect", x=0, y=offset, width=char_width * width, height=line_height + 0.25)}
+            """
+            for line_no, offset in enumerate(line_offsets)
+        )
+
+        styles = "\n".join(
+            f".{unique_id}-r{rule_no} {{ {css} }}" for css, rule_no in classes.items()
+        )
+        backgrounds = "".join(text_backgrounds)
+        matrix = "".join(text_group)
+
+        terminal_width = ceil(width * char_width + padding_width)
+        terminal_height = (y + 1) * line_height + padding_height
+        chrome = make_tag(
+            "rect",
+            fill=_theme.background_color.hex,
+            stroke="rgba(255,255,255,0.35)",
+            stroke_width="1",
+            x=margin_left,
+            y=margin_top,
+            width=terminal_width,
+            height=terminal_height,
+            rx=8,
+        )
+
+        title_color = _theme.foreground_color.hex
+        if title:
+            chrome += make_tag(
+                "text",
+                escape_text(title),
+                _class=f"{unique_id}-title",
+                fill=title_color,
+                text_anchor="middle",
+                x=terminal_width // 2,
+                y=margin_top + char_height + 6,
+            )
+        chrome += f"""
+            
+            
+            
+            
+            
+        """
+
+        svg = code_format.format(
+            unique_id=unique_id,
+            char_width=char_width,
+            char_height=char_height,
+            line_height=line_height,
+            terminal_width=char_width * width - 1,
+            terminal_height=(y + 1) * line_height - 1,
+            width=terminal_width + margin_width,
+            height=terminal_height + margin_height,
+            terminal_x=margin_left + padding_left,
+            terminal_y=margin_top + padding_top,
+            styles=styles,
+            chrome=chrome,
+            backgrounds=backgrounds,
+            matrix=matrix,
+            lines=lines,
+        )
+        return svg
+
+    def save_svg(
+        self,
+        path: str,
+        *,
+        title: str = "Rich",
+        theme: Optional[TerminalTheme] = None,
+        clear: bool = True,
+        code_format: str = CONSOLE_SVG_FORMAT,
+        font_aspect_ratio: float = 0.61,
+        unique_id: Optional[str] = None,
+    ) -> None:
+        """Generate an SVG file from the console contents (requires record=True in Console constructor).
+
+        Args:
+            path (str): The path to write the SVG to.
+            title (str, optional): The title of the tab in the output image
+            theme (TerminalTheme, optional): The ``TerminalTheme`` object to use to style the terminal
+            clear (bool, optional): Clear record buffer after exporting. Defaults to ``True``
+            code_format (str, optional): Format string used to generate the SVG. Rich will inject a number of variables
+                into the string in order to form the final SVG output. The default template used and the variables
+                injected by Rich can be found by inspecting the ``console.CONSOLE_SVG_FORMAT`` variable.
+            font_aspect_ratio (float, optional): The width to height ratio of the font used in the ``code_format``
+                string. Defaults to 0.61, which is the width to height ratio of Fira Code (the default font).
+                If you aren't specifying a different font inside ``code_format``, you probably don't need this.
+            unique_id (str, optional): unique id that is used as the prefix for various elements (CSS styles, node
+                ids). If not set, this defaults to a computed value based on the recorded content.
+        """
+        svg = self.export_svg(
+            title=title,
+            theme=theme,
+            clear=clear,
+            code_format=code_format,
+            font_aspect_ratio=font_aspect_ratio,
+            unique_id=unique_id,
+        )
+        with open(path, "wt", encoding="utf-8") as write_file:
+            write_file.write(svg)
+
+
+def _svg_hash(svg_main_code: str) -> str:
+    """Returns a unique hash for the given SVG main code.
+
+    Args:
+        svg_main_code (str): The content we're going to inject in the SVG envelope.
+
+    Returns:
+        str: a hash of the given content
+    """
+    return str(zlib.adler32(svg_main_code.encode()))
+
+
+if __name__ == "__main__":  # pragma: no cover
+    console = Console(record=True)
+
+    console.log(
+        "JSONRPC [i]request[/i]",
+        5,
+        1.3,
+        True,
+        False,
+        None,
+        {
+            "jsonrpc": "2.0",
+            "method": "subtract",
+            "params": {"minuend": 42, "subtrahend": 23},
+            "id": 3,
+        },
+    )
+
+    console.log("Hello, World!", "{'a': 1}", repr(console))
+
+    console.print(
+        {
+            "name": None,
+            "empty": [],
+            "quiz": {
+                "sport": {
+                    "answered": True,
+                    "q1": {
+                        "question": "Which one is correct team name in NBA?",
+                        "options": [
+                            "New York Bulls",
+                            "Los Angeles Kings",
+                            "Golden State Warriors",
+                            "Huston Rocket",
+                        ],
+                        "answer": "Huston Rocket",
+                    },
+                },
+                "maths": {
+                    "answered": False,
+                    "q1": {
+                        "question": "5 + 7 = ?",
+                        "options": [10, 11, 12, 13],
+                        "answer": 12,
+                    },
+                    "q2": {
+                        "question": "12 - 8 = ?",
+                        "options": [1, 2, 3, 4],
+                        "answer": 4,
+                    },
+                },
+            },
+        }
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/constrain.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/constrain.py
new file mode 100644
index 0000000000000000000000000000000000000000..65fdf56342e8b5b8e181914881025231684e1871
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/constrain.py
@@ -0,0 +1,37 @@
+from typing import Optional, TYPE_CHECKING
+
+from .jupyter import JupyterMixin
+from .measure import Measurement
+
+if TYPE_CHECKING:
+    from .console import Console, ConsoleOptions, RenderableType, RenderResult
+
+
+class Constrain(JupyterMixin):
+    """Constrain the width of a renderable to a given number of characters.
+
+    Args:
+        renderable (RenderableType): A renderable object.
+        width (int, optional): The maximum width (in characters) to render. Defaults to 80.
+    """
+
+    def __init__(self, renderable: "RenderableType", width: Optional[int] = 80) -> None:
+        self.renderable = renderable
+        self.width = width
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":
+        if self.width is None:
+            yield self.renderable
+        else:
+            child_options = options.update_width(min(self.width, options.max_width))
+            yield from console.render(self.renderable, child_options)
+
+    def __rich_measure__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "Measurement":
+        if self.width is not None:
+            options = options.update_width(self.width)
+        measurement = Measurement.get(console, options, self.renderable)
+        return measurement
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/containers.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/containers.py
new file mode 100644
index 0000000000000000000000000000000000000000..e29cf368991ccb083b67cda8133e4635defbfe53
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/containers.py
@@ -0,0 +1,167 @@
+from itertools import zip_longest
+from typing import (
+    Iterator,
+    Iterable,
+    List,
+    Optional,
+    Union,
+    overload,
+    TypeVar,
+    TYPE_CHECKING,
+)
+
+if TYPE_CHECKING:
+    from .console import (
+        Console,
+        ConsoleOptions,
+        JustifyMethod,
+        OverflowMethod,
+        RenderResult,
+        RenderableType,
+    )
+    from .text import Text
+
+from .cells import cell_len
+from .measure import Measurement
+
+T = TypeVar("T")
+
+
+class Renderables:
+    """A list subclass which renders its contents to the console."""
+
+    def __init__(
+        self, renderables: Optional[Iterable["RenderableType"]] = None
+    ) -> None:
+        self._renderables: List["RenderableType"] = (
+            list(renderables) if renderables is not None else []
+        )
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":
+        """Console render method to insert line-breaks."""
+        yield from self._renderables
+
+    def __rich_measure__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "Measurement":
+        dimensions = [
+            Measurement.get(console, options, renderable)
+            for renderable in self._renderables
+        ]
+        if not dimensions:
+            return Measurement(1, 1)
+        _min = max(dimension.minimum for dimension in dimensions)
+        _max = max(dimension.maximum for dimension in dimensions)
+        return Measurement(_min, _max)
+
+    def append(self, renderable: "RenderableType") -> None:
+        self._renderables.append(renderable)
+
+    def __iter__(self) -> Iterable["RenderableType"]:
+        return iter(self._renderables)
+
+
+class Lines:
+    """A list subclass which can render to the console."""
+
+    def __init__(self, lines: Iterable["Text"] = ()) -> None:
+        self._lines: List["Text"] = list(lines)
+
+    def __repr__(self) -> str:
+        return f"Lines({self._lines!r})"
+
+    def __iter__(self) -> Iterator["Text"]:
+        return iter(self._lines)
+
+    @overload
+    def __getitem__(self, index: int) -> "Text":
+        ...
+
+    @overload
+    def __getitem__(self, index: slice) -> List["Text"]:
+        ...
+
+    def __getitem__(self, index: Union[slice, int]) -> Union["Text", List["Text"]]:
+        return self._lines[index]
+
+    def __setitem__(self, index: int, value: "Text") -> "Lines":
+        self._lines[index] = value
+        return self
+
+    def __len__(self) -> int:
+        return self._lines.__len__()
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":
+        """Console render method to insert line-breaks."""
+        yield from self._lines
+
+    def append(self, line: "Text") -> None:
+        self._lines.append(line)
+
+    def extend(self, lines: Iterable["Text"]) -> None:
+        self._lines.extend(lines)
+
+    def pop(self, index: int = -1) -> "Text":
+        return self._lines.pop(index)
+
+    def justify(
+        self,
+        console: "Console",
+        width: int,
+        justify: "JustifyMethod" = "left",
+        overflow: "OverflowMethod" = "fold",
+    ) -> None:
+        """Justify and overflow text to a given width.
+
+        Args:
+            console (Console): Console instance.
+            width (int): Number of characters per line.
+            justify (str, optional): Default justify method for text: "left", "center", "full" or "right". Defaults to "left".
+            overflow (str, optional): Default overflow for text: "crop", "fold", or "ellipsis". Defaults to "fold".
+
+        """
+        from .text import Text
+
+        if justify == "left":
+            for line in self._lines:
+                line.truncate(width, overflow=overflow, pad=True)
+        elif justify == "center":
+            for line in self._lines:
+                line.rstrip()
+                line.truncate(width, overflow=overflow)
+                line.pad_left((width - cell_len(line.plain)) // 2)
+                line.pad_right(width - cell_len(line.plain))
+        elif justify == "right":
+            for line in self._lines:
+                line.rstrip()
+                line.truncate(width, overflow=overflow)
+                line.pad_left(width - cell_len(line.plain))
+        elif justify == "full":
+            for line_index, line in enumerate(self._lines):
+                if line_index == len(self._lines) - 1:
+                    break
+                words = line.split(" ")
+                words_size = sum(cell_len(word.plain) for word in words)
+                num_spaces = len(words) - 1
+                spaces = [1 for _ in range(num_spaces)]
+                index = 0
+                if spaces:
+                    while words_size + num_spaces < width:
+                        spaces[len(spaces) - index - 1] += 1
+                        num_spaces += 1
+                        index = (index + 1) % len(spaces)
+                tokens: List[Text] = []
+                for index, (word, next_word) in enumerate(
+                    zip_longest(words, words[1:])
+                ):
+                    tokens.append(word)
+                    if index < len(spaces):
+                        style = word.get_style_at_offset(console, -1)
+                        next_style = next_word.get_style_at_offset(console, 0)
+                        space_style = style if style == next_style else line.style
+                        tokens.append(Text(" " * spaces[index], style=space_style))
+                self[line_index] = Text("").join(tokens)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/control.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/control.py
new file mode 100644
index 0000000000000000000000000000000000000000..88fcb9295164f4e18827ef61fff6723e94ef7381
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/control.py
@@ -0,0 +1,225 @@
+import sys
+import time
+from typing import TYPE_CHECKING, Callable, Dict, Iterable, List, Union
+
+if sys.version_info >= (3, 8):
+    from typing import Final
+else:
+    from pip._vendor.typing_extensions import Final  # pragma: no cover
+
+from .segment import ControlCode, ControlType, Segment
+
+if TYPE_CHECKING:
+    from .console import Console, ConsoleOptions, RenderResult
+
+STRIP_CONTROL_CODES: Final = [
+    7,  # Bell
+    8,  # Backspace
+    11,  # Vertical tab
+    12,  # Form feed
+    13,  # Carriage return
+]
+_CONTROL_STRIP_TRANSLATE: Final = {
+    _codepoint: None for _codepoint in STRIP_CONTROL_CODES
+}
+
+CONTROL_ESCAPE: Final = {
+    7: "\\a",
+    8: "\\b",
+    11: "\\v",
+    12: "\\f",
+    13: "\\r",
+}
+
+CONTROL_CODES_FORMAT: Dict[int, Callable[..., str]] = {
+    ControlType.BELL: lambda: "\x07",
+    ControlType.CARRIAGE_RETURN: lambda: "\r",
+    ControlType.HOME: lambda: "\x1b[H",
+    ControlType.CLEAR: lambda: "\x1b[2J",
+    ControlType.ENABLE_ALT_SCREEN: lambda: "\x1b[?1049h",
+    ControlType.DISABLE_ALT_SCREEN: lambda: "\x1b[?1049l",
+    ControlType.SHOW_CURSOR: lambda: "\x1b[?25h",
+    ControlType.HIDE_CURSOR: lambda: "\x1b[?25l",
+    ControlType.CURSOR_UP: lambda param: f"\x1b[{param}A",
+    ControlType.CURSOR_DOWN: lambda param: f"\x1b[{param}B",
+    ControlType.CURSOR_FORWARD: lambda param: f"\x1b[{param}C",
+    ControlType.CURSOR_BACKWARD: lambda param: f"\x1b[{param}D",
+    ControlType.CURSOR_MOVE_TO_COLUMN: lambda param: f"\x1b[{param+1}G",
+    ControlType.ERASE_IN_LINE: lambda param: f"\x1b[{param}K",
+    ControlType.CURSOR_MOVE_TO: lambda x, y: f"\x1b[{y+1};{x+1}H",
+    ControlType.SET_WINDOW_TITLE: lambda title: f"\x1b]0;{title}\x07",
+}
+
+
+class Control:
+    """A renderable that inserts a control code (non printable but may move cursor).
+
+    Args:
+        *codes (str): Positional arguments are either a :class:`~rich.segment.ControlType` enum or a
+            tuple of ControlType and an integer parameter
+    """
+
+    __slots__ = ["segment"]
+
+    def __init__(self, *codes: Union[ControlType, ControlCode]) -> None:
+        control_codes: List[ControlCode] = [
+            (code,) if isinstance(code, ControlType) else code for code in codes
+        ]
+        _format_map = CONTROL_CODES_FORMAT
+        rendered_codes = "".join(
+            _format_map[code](*parameters) for code, *parameters in control_codes
+        )
+        self.segment = Segment(rendered_codes, None, control_codes)
+
+    @classmethod
+    def bell(cls) -> "Control":
+        """Ring the 'bell'."""
+        return cls(ControlType.BELL)
+
+    @classmethod
+    def home(cls) -> "Control":
+        """Move cursor to 'home' position."""
+        return cls(ControlType.HOME)
+
+    @classmethod
+    def move(cls, x: int = 0, y: int = 0) -> "Control":
+        """Move cursor relative to current position.
+
+        Args:
+            x (int): X offset.
+            y (int): Y offset.
+
+        Returns:
+            ~Control: Control object.
+
+        """
+
+        def get_codes() -> Iterable[ControlCode]:
+            control = ControlType
+            if x:
+                yield (
+                    control.CURSOR_FORWARD if x > 0 else control.CURSOR_BACKWARD,
+                    abs(x),
+                )
+            if y:
+                yield (
+                    control.CURSOR_DOWN if y > 0 else control.CURSOR_UP,
+                    abs(y),
+                )
+
+        control = cls(*get_codes())
+        return control
+
+    @classmethod
+    def move_to_column(cls, x: int, y: int = 0) -> "Control":
+        """Move to the given column, optionally add offset to row.
+
+        Returns:
+            x (int): absolute x (column)
+            y (int): optional y offset (row)
+
+        Returns:
+            ~Control: Control object.
+        """
+
+        return (
+            cls(
+                (ControlType.CURSOR_MOVE_TO_COLUMN, x),
+                (
+                    ControlType.CURSOR_DOWN if y > 0 else ControlType.CURSOR_UP,
+                    abs(y),
+                ),
+            )
+            if y
+            else cls((ControlType.CURSOR_MOVE_TO_COLUMN, x))
+        )
+
+    @classmethod
+    def move_to(cls, x: int, y: int) -> "Control":
+        """Move cursor to absolute position.
+
+        Args:
+            x (int): x offset (column)
+            y (int): y offset (row)
+
+        Returns:
+            ~Control: Control object.
+        """
+        return cls((ControlType.CURSOR_MOVE_TO, x, y))
+
+    @classmethod
+    def clear(cls) -> "Control":
+        """Clear the screen."""
+        return cls(ControlType.CLEAR)
+
+    @classmethod
+    def show_cursor(cls, show: bool) -> "Control":
+        """Show or hide the cursor."""
+        return cls(ControlType.SHOW_CURSOR if show else ControlType.HIDE_CURSOR)
+
+    @classmethod
+    def alt_screen(cls, enable: bool) -> "Control":
+        """Enable or disable alt screen."""
+        if enable:
+            return cls(ControlType.ENABLE_ALT_SCREEN, ControlType.HOME)
+        else:
+            return cls(ControlType.DISABLE_ALT_SCREEN)
+
+    @classmethod
+    def title(cls, title: str) -> "Control":
+        """Set the terminal window title
+
+        Args:
+            title (str): The new terminal window title
+        """
+        return cls((ControlType.SET_WINDOW_TITLE, title))
+
+    def __str__(self) -> str:
+        return self.segment.text
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":
+        if self.segment.text:
+            yield self.segment
+
+
+def strip_control_codes(
+    text: str, _translate_table: Dict[int, None] = _CONTROL_STRIP_TRANSLATE
+) -> str:
+    """Remove control codes from text.
+
+    Args:
+        text (str): A string possibly contain control codes.
+
+    Returns:
+        str: String with control codes removed.
+    """
+    return text.translate(_translate_table)
+
+
+def escape_control_codes(
+    text: str,
+    _translate_table: Dict[int, str] = CONTROL_ESCAPE,
+) -> str:
+    """Replace control codes with their "escaped" equivalent in the given text.
+    (e.g. "\b" becomes "\\b")
+
+    Args:
+        text (str): A string possibly containing control codes.
+
+    Returns:
+        str: String with control codes replaced with their escaped version.
+    """
+    return text.translate(_translate_table)
+
+
+if __name__ == "__main__":  # pragma: no cover
+    from pip._vendor.rich.console import Console
+
+    console = Console()
+    console.print("Look at the title of your terminal window ^")
+    # console.print(Control((ControlType.SET_WINDOW_TITLE, "Hello, world!")))
+    for i in range(10):
+        console.set_window_title("🚀 Loading" + "." * i)
+        time.sleep(0.5)
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/default_styles.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/default_styles.py
new file mode 100644
index 0000000000000000000000000000000000000000..46e9ea52c54d067db5fba0ae0e9af34d910417a3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/default_styles.py
@@ -0,0 +1,188 @@
+from typing import Dict
+
+from .style import Style
+
+DEFAULT_STYLES: Dict[str, Style] = {
+    "none": Style.null(),
+    "reset": Style(
+        color="default",
+        bgcolor="default",
+        dim=False,
+        bold=False,
+        italic=False,
+        underline=False,
+        blink=False,
+        blink2=False,
+        reverse=False,
+        conceal=False,
+        strike=False,
+    ),
+    "dim": Style(dim=True),
+    "bright": Style(dim=False),
+    "bold": Style(bold=True),
+    "strong": Style(bold=True),
+    "code": Style(reverse=True, bold=True),
+    "italic": Style(italic=True),
+    "emphasize": Style(italic=True),
+    "underline": Style(underline=True),
+    "blink": Style(blink=True),
+    "blink2": Style(blink2=True),
+    "reverse": Style(reverse=True),
+    "strike": Style(strike=True),
+    "black": Style(color="black"),
+    "red": Style(color="red"),
+    "green": Style(color="green"),
+    "yellow": Style(color="yellow"),
+    "magenta": Style(color="magenta"),
+    "cyan": Style(color="cyan"),
+    "white": Style(color="white"),
+    "inspect.attr": Style(color="yellow", italic=True),
+    "inspect.attr.dunder": Style(color="yellow", italic=True, dim=True),
+    "inspect.callable": Style(bold=True, color="red"),
+    "inspect.async_def": Style(italic=True, color="bright_cyan"),
+    "inspect.def": Style(italic=True, color="bright_cyan"),
+    "inspect.class": Style(italic=True, color="bright_cyan"),
+    "inspect.error": Style(bold=True, color="red"),
+    "inspect.equals": Style(),
+    "inspect.help": Style(color="cyan"),
+    "inspect.doc": Style(dim=True),
+    "inspect.value.border": Style(color="green"),
+    "live.ellipsis": Style(bold=True, color="red"),
+    "layout.tree.row": Style(dim=False, color="red"),
+    "layout.tree.column": Style(dim=False, color="blue"),
+    "logging.keyword": Style(bold=True, color="yellow"),
+    "logging.level.notset": Style(dim=True),
+    "logging.level.debug": Style(color="green"),
+    "logging.level.info": Style(color="blue"),
+    "logging.level.warning": Style(color="red"),
+    "logging.level.error": Style(color="red", bold=True),
+    "logging.level.critical": Style(color="red", bold=True, reverse=True),
+    "log.level": Style.null(),
+    "log.time": Style(color="cyan", dim=True),
+    "log.message": Style.null(),
+    "log.path": Style(dim=True),
+    "repr.ellipsis": Style(color="yellow"),
+    "repr.indent": Style(color="green", dim=True),
+    "repr.error": Style(color="red", bold=True),
+    "repr.str": Style(color="green", italic=False, bold=False),
+    "repr.brace": Style(bold=True),
+    "repr.comma": Style(bold=True),
+    "repr.ipv4": Style(bold=True, color="bright_green"),
+    "repr.ipv6": Style(bold=True, color="bright_green"),
+    "repr.eui48": Style(bold=True, color="bright_green"),
+    "repr.eui64": Style(bold=True, color="bright_green"),
+    "repr.tag_start": Style(bold=True),
+    "repr.tag_name": Style(color="bright_magenta", bold=True),
+    "repr.tag_contents": Style(color="default"),
+    "repr.tag_end": Style(bold=True),
+    "repr.attrib_name": Style(color="yellow", italic=False),
+    "repr.attrib_equal": Style(bold=True),
+    "repr.attrib_value": Style(color="magenta", italic=False),
+    "repr.number": Style(color="cyan", bold=True, italic=False),
+    "repr.number_complex": Style(color="cyan", bold=True, italic=False),  # same
+    "repr.bool_true": Style(color="bright_green", italic=True),
+    "repr.bool_false": Style(color="bright_red", italic=True),
+    "repr.none": Style(color="magenta", italic=True),
+    "repr.url": Style(underline=True, color="bright_blue", italic=False, bold=False),
+    "repr.uuid": Style(color="bright_yellow", bold=False),
+    "repr.call": Style(color="magenta", bold=True),
+    "repr.path": Style(color="magenta"),
+    "repr.filename": Style(color="bright_magenta"),
+    "rule.line": Style(color="bright_green"),
+    "rule.text": Style.null(),
+    "json.brace": Style(bold=True),
+    "json.bool_true": Style(color="bright_green", italic=True),
+    "json.bool_false": Style(color="bright_red", italic=True),
+    "json.null": Style(color="magenta", italic=True),
+    "json.number": Style(color="cyan", bold=True, italic=False),
+    "json.str": Style(color="green", italic=False, bold=False),
+    "json.key": Style(color="blue", bold=True),
+    "prompt": Style.null(),
+    "prompt.choices": Style(color="magenta", bold=True),
+    "prompt.default": Style(color="cyan", bold=True),
+    "prompt.invalid": Style(color="red"),
+    "prompt.invalid.choice": Style(color="red"),
+    "pretty": Style.null(),
+    "scope.border": Style(color="blue"),
+    "scope.key": Style(color="yellow", italic=True),
+    "scope.key.special": Style(color="yellow", italic=True, dim=True),
+    "scope.equals": Style(color="red"),
+    "table.header": Style(bold=True),
+    "table.footer": Style(bold=True),
+    "table.cell": Style.null(),
+    "table.title": Style(italic=True),
+    "table.caption": Style(italic=True, dim=True),
+    "traceback.error": Style(color="red", italic=True),
+    "traceback.border.syntax_error": Style(color="bright_red"),
+    "traceback.border": Style(color="red"),
+    "traceback.text": Style.null(),
+    "traceback.title": Style(color="red", bold=True),
+    "traceback.exc_type": Style(color="bright_red", bold=True),
+    "traceback.exc_value": Style.null(),
+    "traceback.offset": Style(color="bright_red", bold=True),
+    "bar.back": Style(color="grey23"),
+    "bar.complete": Style(color="rgb(249,38,114)"),
+    "bar.finished": Style(color="rgb(114,156,31)"),
+    "bar.pulse": Style(color="rgb(249,38,114)"),
+    "progress.description": Style.null(),
+    "progress.filesize": Style(color="green"),
+    "progress.filesize.total": Style(color="green"),
+    "progress.download": Style(color="green"),
+    "progress.elapsed": Style(color="yellow"),
+    "progress.percentage": Style(color="magenta"),
+    "progress.remaining": Style(color="cyan"),
+    "progress.data.speed": Style(color="red"),
+    "progress.spinner": Style(color="green"),
+    "status.spinner": Style(color="green"),
+    "tree": Style(),
+    "tree.line": Style(),
+    "markdown.paragraph": Style(),
+    "markdown.text": Style(),
+    "markdown.emph": Style(italic=True),
+    "markdown.strong": Style(bold=True),
+    "markdown.code": Style(bgcolor="black", color="bright_white"),
+    "markdown.code_block": Style(dim=True, color="cyan", bgcolor="black"),
+    "markdown.block_quote": Style(color="magenta"),
+    "markdown.list": Style(color="cyan"),
+    "markdown.item": Style(),
+    "markdown.item.bullet": Style(color="yellow", bold=True),
+    "markdown.item.number": Style(color="yellow", bold=True),
+    "markdown.hr": Style(color="yellow"),
+    "markdown.h1.border": Style(),
+    "markdown.h1": Style(bold=True),
+    "markdown.h2": Style(bold=True, underline=True),
+    "markdown.h3": Style(bold=True),
+    "markdown.h4": Style(bold=True, dim=True),
+    "markdown.h5": Style(underline=True),
+    "markdown.h6": Style(italic=True),
+    "markdown.h7": Style(italic=True, dim=True),
+    "markdown.link": Style(color="bright_blue"),
+    "markdown.link_url": Style(color="blue"),
+    "iso8601.date": Style(color="blue"),
+    "iso8601.time": Style(color="magenta"),
+    "iso8601.timezone": Style(color="yellow"),
+}
+
+
+if __name__ == "__main__":  # pragma: no cover
+    import argparse
+    import io
+
+    from pip._vendor.rich.console import Console
+    from pip._vendor.rich.table import Table
+    from pip._vendor.rich.text import Text
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--html", action="store_true", help="Export as HTML table")
+    args = parser.parse_args()
+    html: bool = args.html
+    console = Console(record=True, width=70, file=io.StringIO()) if html else Console()
+
+    table = Table("Name", "Styling")
+
+    for style_name, style in DEFAULT_STYLES.items():
+        table.add_row(Text(style_name, style=style), str(style))
+
+    console.print(table)
+    if html:
+        print(console.export_html(inline_styles=True))
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/diagnose.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/diagnose.py
new file mode 100644
index 0000000000000000000000000000000000000000..ad36183898eddb11e33ccb7623c0291ccc0f091d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/diagnose.py
@@ -0,0 +1,37 @@
+import os
+import platform
+
+from pip._vendor.rich import inspect
+from pip._vendor.rich.console import Console, get_windows_console_features
+from pip._vendor.rich.panel import Panel
+from pip._vendor.rich.pretty import Pretty
+
+
+def report() -> None:  # pragma: no cover
+    """Print a report to the terminal with debugging information"""
+    console = Console()
+    inspect(console)
+    features = get_windows_console_features()
+    inspect(features)
+
+    env_names = (
+        "TERM",
+        "COLORTERM",
+        "CLICOLOR",
+        "NO_COLOR",
+        "TERM_PROGRAM",
+        "COLUMNS",
+        "LINES",
+        "JUPYTER_COLUMNS",
+        "JUPYTER_LINES",
+        "JPY_PARENT_PID",
+        "VSCODE_VERBOSE_LOGGING",
+    )
+    env = {name: os.getenv(name) for name in env_names}
+    console.print(Panel.fit((Pretty(env)), title="[b]Environment Variables"))
+
+    console.print(f'platform="{platform.system()}"')
+
+
+if __name__ == "__main__":  # pragma: no cover
+    report()
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/emoji.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/emoji.py
new file mode 100644
index 0000000000000000000000000000000000000000..791f0465de136088e33cdc6ef5696590df1e4f86
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/emoji.py
@@ -0,0 +1,96 @@
+import sys
+from typing import TYPE_CHECKING, Optional, Union
+
+from .jupyter import JupyterMixin
+from .segment import Segment
+from .style import Style
+from ._emoji_codes import EMOJI
+from ._emoji_replace import _emoji_replace
+
+if sys.version_info >= (3, 8):
+    from typing import Literal
+else:
+    from pip._vendor.typing_extensions import Literal  # pragma: no cover
+
+
+if TYPE_CHECKING:
+    from .console import Console, ConsoleOptions, RenderResult
+
+
+EmojiVariant = Literal["emoji", "text"]
+
+
+class NoEmoji(Exception):
+    """No emoji by that name."""
+
+
+class Emoji(JupyterMixin):
+    __slots__ = ["name", "style", "_char", "variant"]
+
+    VARIANTS = {"text": "\uFE0E", "emoji": "\uFE0F"}
+
+    def __init__(
+        self,
+        name: str,
+        style: Union[str, Style] = "none",
+        variant: Optional[EmojiVariant] = None,
+    ) -> None:
+        """A single emoji character.
+
+        Args:
+            name (str): Name of emoji.
+            style (Union[str, Style], optional): Optional style. Defaults to None.
+
+        Raises:
+            NoEmoji: If the emoji doesn't exist.
+        """
+        self.name = name
+        self.style = style
+        self.variant = variant
+        try:
+            self._char = EMOJI[name]
+        except KeyError:
+            raise NoEmoji(f"No emoji called {name!r}")
+        if variant is not None:
+            self._char += self.VARIANTS.get(variant, "")
+
+    @classmethod
+    def replace(cls, text: str) -> str:
+        """Replace emoji markup with corresponding unicode characters.
+
+        Args:
+            text (str): A string with emojis codes, e.g. "Hello :smiley:!"
+
+        Returns:
+            str: A string with emoji codes replaces with actual emoji.
+        """
+        return _emoji_replace(text)
+
+    def __repr__(self) -> str:
+        return f""
+
+    def __str__(self) -> str:
+        return self._char
+
+    def __rich_console__(
+        self, console: "Console", options: "ConsoleOptions"
+    ) -> "RenderResult":
+        yield Segment(self._char, console.get_style(self.style))
+
+
+if __name__ == "__main__":  # pragma: no cover
+    import sys
+
+    from pip._vendor.rich.columns import Columns
+    from pip._vendor.rich.console import Console
+
+    console = Console(record=True)
+
+    columns = Columns(
+        (f":{name}: {name}" for name in sorted(EMOJI.keys()) if "\u200D" not in name),
+        column_first=True,
+    )
+
+    console.print(columns)
+    if len(sys.argv) > 1:
+        console.save_html(sys.argv[1])
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/errors.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/errors.py
new file mode 100644
index 0000000000000000000000000000000000000000..0bcbe53ef59373c608e62ea285536f8b22b47ecb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/errors.py
@@ -0,0 +1,34 @@
+class ConsoleError(Exception):
+    """An error in console operation."""
+
+
+class StyleError(Exception):
+    """An error in styles."""
+
+
+class StyleSyntaxError(ConsoleError):
+    """Style was badly formatted."""
+
+
+class MissingStyle(StyleError):
+    """No such style."""
+
+
+class StyleStackError(ConsoleError):
+    """Style stack is invalid."""
+
+
+class NotRenderableError(ConsoleError):
+    """Object is not renderable."""
+
+
+class MarkupError(ConsoleError):
+    """Markup was badly formatted."""
+
+
+class LiveError(ConsoleError):
+    """Error related to Live display."""
+
+
+class NoAltScreen(ConsoleError):
+    """Alt screen mode was required."""
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/file_proxy.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/file_proxy.py
new file mode 100644
index 0000000000000000000000000000000000000000..cc69f22f3cc021fe5d1147d628eeca804be43b8b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/file_proxy.py
@@ -0,0 +1,54 @@
+import io
+from typing import IO, TYPE_CHECKING, Any, List
+
+from .ansi import AnsiDecoder
+from .text import Text
+
+if TYPE_CHECKING:
+    from .console import Console
+
+
+class FileProxy(io.TextIOBase):
+    """Wraps a file (e.g. sys.stdout) and redirects writes to a console."""
+
+    def __init__(self, console: "Console", file: IO[str]) -> None:
+        self.__console = console
+        self.__file = file
+        self.__buffer: List[str] = []
+        self.__ansi_decoder = AnsiDecoder()
+
+    @property
+    def rich_proxied_file(self) -> IO[str]:
+        """Get proxied file."""
+        return self.__file
+
+    def __getattr__(self, name: str) -> Any:
+        return getattr(self.__file, name)
+
+    def write(self, text: str) -> int:
+        if not isinstance(text, str):
+            raise TypeError(f"write() argument must be str, not {type(text).__name__}")
+        buffer = self.__buffer
+        lines: List[str] = []
+        while text:
+            line, new_line, text = text.partition("\n")
+            if new_line:
+                lines.append("".join(buffer) + line)
+                del buffer[:]
+            else:
+                buffer.append(line)
+                break
+        if lines:
+            console = self.__console
+            with console:
+                output = Text("\n").join(
+                    self.__ansi_decoder.decode_line(line) for line in lines
+                )
+                console.print(output)
+        return len(text)
+
+    def flush(self) -> None:
+        output = "".join(self.__buffer)
+        if output:
+            self.__console.print(output)
+        del self.__buffer[:]
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/filesize.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/filesize.py
new file mode 100644
index 0000000000000000000000000000000000000000..99f118e20103174993b865cfb43ac6b6e00296a4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/filesize.py
@@ -0,0 +1,89 @@
+# coding: utf-8
+"""Functions for reporting filesizes. Borrowed from https://github.com/PyFilesystem/pyfilesystem2
+
+The functions declared in this module should cover the different
+use cases needed to generate a string representation of a file size
+using several different units. Since there are many standards regarding
+file size units, three different functions have been implemented.
+
+See Also:
+    * `Wikipedia: Binary prefix `_
+
+"""
+
+__all__ = ["decimal"]
+
+from typing import Iterable, List, Optional, Tuple
+
+
+def _to_str(
+    size: int,
+    suffixes: Iterable[str],
+    base: int,
+    *,
+    precision: Optional[int] = 1,
+    separator: Optional[str] = " ",
+) -> str:
+    if size == 1:
+        return "1 byte"
+    elif size < base:
+        return "{:,} bytes".format(size)
+
+    for i, suffix in enumerate(suffixes, 2):  # noqa: B007
+        unit = base**i
+        if size < unit:
+            break
+    return "{:,.{precision}f}{separator}{}".format(
+        (base * size / unit),
+        suffix,
+        precision=precision,
+        separator=separator,
+    )
+
+
+def pick_unit_and_suffix(size: int, suffixes: List[str], base: int) -> Tuple[int, str]:
+    """Pick a suffix and base for the given size."""
+    for i, suffix in enumerate(suffixes):
+        unit = base**i
+        if size < unit * base:
+            break
+    return unit, suffix
+
+
+def decimal(
+    size: int,
+    *,
+    precision: Optional[int] = 1,
+    separator: Optional[str] = " ",
+) -> str:
+    """Convert a filesize in to a string (powers of 1000, SI prefixes).
+
+    In this convention, ``1000 B = 1 kB``.
+
+    This is typically the format used to advertise the storage
+    capacity of USB flash drives and the like (*256 MB* meaning
+    actually a storage capacity of more than *256 000 000 B*),
+    or used by **Mac OS X** since v10.6 to report file sizes.
+
+    Arguments:
+        int (size): A file size.
+        int (precision): The number of decimal places to include (default = 1).
+        str (separator): The string to separate the value from the units (default = " ").
+
+    Returns:
+        `str`: A string containing a abbreviated file size and units.
+
+    Example:
+        >>> filesize.decimal(30000)
+        '30.0 kB'
+        >>> filesize.decimal(30000, precision=2, separator="")
+        '30.00kB'
+
+    """
+    return _to_str(
+        size,
+        ("kB", "MB", "GB", "TB", "PB", "EB", "ZB", "YB"),
+        1000,
+        precision=precision,
+        separator=separator,
+    )
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/highlighter.py b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/highlighter.py
new file mode 100644
index 0000000000000000000000000000000000000000..82293dffc492ea50b16335fd411b255dd5dfca57
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib64/python3.10/site-packages/pip/_vendor/rich/highlighter.py
@@ -0,0 +1,232 @@
+import re
+from abc import ABC, abstractmethod
+from typing import List, Union
+
+from .text import Span, Text
+
+
+def _combine_regex(*regexes: str) -> str:
+    """Combine a number of regexes in to a single regex.
+
+    Returns:
+        str: New regex with all regexes ORed together.
+    """
+    return "|".join(regexes)
+
+
+class Highlighter(ABC):
+    """Abstract base class for highlighters."""
+
+    def __call__(self, text: Union[str, Text]) -> Text:
+        """Highlight a str or Text instance.
+
+        Args:
+            text (Union[str, ~Text]): Text to highlight.
+
+        Raises:
+            TypeError: If not called with text or str.
+
+        Returns:
+            Text: A test instance with highlighting applied.
+        """
+        if isinstance(text, str):
+            highlight_text = Text(text)
+        elif isinstance(text, Text):
+            highlight_text = text.copy()
+        else:
+            raise TypeError(f"str or Text instance required, not {text!r}")
+        self.highlight(highlight_text)
+        return highlight_text
+
+    @abstractmethod
+    def highlight(self, text: Text) -> None:
+        """Apply highlighting in place to text.
+
+        Args:
+            text (~Text): A text object highlight.
+        """
+
+
+class NullHighlighter(Highlighter):
+    """A highlighter object that doesn't highlight.
+
+    May be used to disable highlighting entirely.
+
+    """
+
+    def highlight(self, text: Text) -> None:
+        """Nothing to do"""
+
+
+class RegexHighlighter(Highlighter):
+    """Applies highlighting from a list of regular expressions."""
+
+    highlights: List[str] = []
+    base_style: str = ""
+
+    def highlight(self, text: Text) -> None:
+        """Highlight :class:`rich.text.Text` using regular expressions.
+
+        Args:
+            text (~Text): Text to highlighted.
+
+        """
+
+        highlight_regex = text.highlight_regex
+        for re_highlight in self.highlights:
+            highlight_regex(re_highlight, style_prefix=self.base_style)
+
+
+class ReprHighlighter(RegexHighlighter):
+    """Highlights the text typically produced from ``__repr__`` methods."""
+
+    base_style = "repr."
+    highlights = [
+        r"(?P<)(?P[-\w.:|]*)(?P[\w\W]*?)(?P>)",
+        r'(?P[\w_]{1,50})=(?P"?[\w_]+"?)?',
+        r"(?P[][{}()])",
+        _combine_regex(
+            r"(?P[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3})",
+            r"(?P([A-Fa-f0-9]{1,4}::?){1,7}[A-Fa-f0-9]{1,4})",
+            r"(?P(?:[0-9A-Fa-f]{1,2}-){7}[0-9A-Fa-f]{1,2}|(?:[0-9A-Fa-f]{1,2}:){7}[0-9A-Fa-f]{1,2}|(?:[0-9A-Fa-f]{4}\.){3}[0-9A-Fa-f]{4})",
+            r"(?P(?:[0-9A-Fa-f]{1,2}-){5}[0-9A-Fa-f]{1,2}|(?:[0-9A-Fa-f]{1,2}:){5}[0-9A-Fa-f]{1,2}|(?:[0-9A-Fa-f]{4}\.){2}[0-9A-Fa-f]{4})",
+            r"(?P[a-fA-F0-9]{8}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{12})",
+            r"(?P[\w.]*?)\(",
+            r"\b(?PTrue)\b|\b(?PFalse)\b|\b(?PNone)\b",
+            r"(?P\.\.\.)",
+            r"(?P(?(?\B(/[-\w._+]+)*\/)(?P[-\w._+]*)?",
+            r"(?b?'''.*?(?(file|https|http|ws|wss)://[-0-9a-zA-Z$_+!`(),.?/;:&=%#]*)",
+        ),
+    ]
+
+
+class JSONHighlighter(RegexHighlighter):
+    """Highlights JSON"""
+
+    # Captures the start and end of JSON strings, handling escaped quotes
+    JSON_STR = r"(?b?\".*?(?[\{\[\(\)\]\}])",
+            r"\b(?Ptrue)\b|\b(?Pfalse)\b|\b(?Pnull)\b",
+            r"(?P(? None:
+        super().highlight(text)
+
+        # Additional work to handle highlighting JSON keys
+        plain = text.plain
+        append = text.spans.append
+        whitespace = self.JSON_WHITESPACE
+        for match in re.finditer(self.JSON_STR, plain):
+            start, end = match.span()
+            cursor = end
+            while cursor < len(plain):
+                char = plain[cursor]
+                cursor += 1
+                if char == ":":
+                    append(Span(start, end, "json.key"))
+                elif char in whitespace:
+                    continue
+                break
+
+
+class ISO8601Highlighter(RegexHighlighter):
+    """Highlights the ISO8601 date time strings.
+    Regex reference: https://www.oreilly.com/library/view/regular-expressions-cookbook/9781449327453/ch04s07.html
+    """
+
+    base_style = "iso8601."
+    highlights = [
+        #
+        # Dates
+        #
+        # Calendar month (e.g. 2008-08). The hyphen is required
+        r"^(?P[0-9]{4})-(?P1[0-2]|0[1-9])$",
+        # Calendar date w/o hyphens (e.g. 20080830)
+        r"^(?P(?P[0-9]{4})(?P1[0-2]|0[1-9])(?P3[01]|0[1-9]|[12][0-9]))$",
+        # Ordinal date (e.g. 2008-243). The hyphen is optional
+        r"^(?P(?P[0-9]{4})-?(?P36[0-6]|3[0-5][0-9]|[12][0-9]{2}|0[1-9][0-9]|00[1-9]))$",
+        #
+        # Weeks
+        #
+        # Week of the year (e.g., 2008-W35). The hyphen is optional
+        r"^(?P(?P[0-9]{4})-?W(?P5[0-3]|[1-4][0-9]|0[1-9]))$",
+        # Week date (e.g., 2008-W35-6). The hyphens are optional
+        r"^(?P(?P[0-9]{4})-?W(?P5[0-3]|[1-4][0-9]|0[1-9])-?(?P[1-7]))$",
+        #
+        # Times
+        #
+        # Hours and minutes (e.g., 17:21). The colon is optional
+        r"^(?P
'                    : '\U0001d4ab',
+        '\\'                    : '\U0001d4ac',
+        '\\'                    : '\U0000211b',
+        '\\'                    : '\U0001d4ae',
+        '\\'                    : '\U0001d4af',
+        '\\'                    : '\U0001d4b0',
+        '\\'                    : '\U0001d4b1',
+        '\\'                    : '\U0001d4b2',
+        '\\'                    : '\U0001d4b3',
+        '\\'                    : '\U0001d4b4',
+        '\\'                    : '\U0001d4b5',
+        '\\'                    : '\U0001d5ba',
+        '\\'                    : '\U0001d5bb',
+        '\\'                    : '\U0001d5bc',
+        '\\'                    : '\U0001d5bd',
+        '\\'                    : '\U0001d5be',
+        '\\'                    : '\U0001d5bf',
+        '\\'                    : '\U0001d5c0',
+        '\\'                    : '\U0001d5c1',
+        '\\'                    : '\U0001d5c2',
+        '\\'                    : '\U0001d5c3',
+        '\\'                    : '\U0001d5c4',
+        '\\'                    : '\U0001d5c5',
+        '\\'                    : '\U0001d5c6',
+        '\\'                    : '\U0001d5c7',
+        '\\'                    : '\U0001d5c8',
+        '\\