code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
value |
|---|---|---|---|---|---|
import os
import sys
import ctypes
import pathlib
from typing import Optional
P_FLOAT = ctypes.POINTER(ctypes.c_float)
class RWKVContext:
def __init__(self, ptr: ctypes.pointer):
self.ptr = ptr
class RWKVSharedLibrary:
"""
Python wrapper around rwkv.cpp shared library.
"""
def __init__... | /rwkv_cpp_python-0.0.1.tar.gz/rwkv_cpp_python-0.0.1/rwkv/rwkv_cpp_shared_library.py | 0.736021 | 0.333354 | rwkv_cpp_shared_library.py | pypi |
import os
import time
import uuid
import json
import pathlib
from typing import List, Optional, Literal, Union, Iterator, Dict
from typing_extensions import TypedDict
import sampling
import tokenizers
import rwkv_cpp_model
import rwkv_cpp_shared_library
import server_types
from fastapi import FastAPI
from fastapi.mi... | /rwkv_cpp_python-0.0.1.tar.gz/rwkv_cpp_python-0.0.1/rwkv/server.py | 0.735357 | 0.17545 | server.py | pypi |
from typing import List, Optional, Dict, Union
from typing_extensions import TypedDict, NotRequired, Literal
class EmbeddingUsage(TypedDict):
prompt_tokens: int
total_tokens: int
class EmbeddingData(TypedDict):
index: int
object: str
embedding: List[float]
class Embedding(TypedDict):
objec... | /rwkv_cpp_python-0.0.1.tar.gz/rwkv_cpp_python-0.0.1/rwkv/server_types.py | 0.834407 | 0.436562 | server_types.py | pypi |
import os
import torch
import multiprocessing
import rwkv_cpp_shared_library
from typing import Tuple, Optional
class RWKVModel:
"""
PyTorch wrapper around rwkv.cpp model.
"""
def __init__(
self,
shared_library: rwkv_cpp_shared_library.RWKVSharedLibrary,
model_path:... | /rwkv_cpp_python-0.0.1.tar.gz/rwkv_cpp_python-0.0.1/rwkv/rwkv_cpp_model.py | 0.893356 | 0.525186 | rwkv_cpp_model.py | pypi |
# rwkv.cpp
This is a port of [BlinkDL/RWKV-LM](https://github.com/BlinkDL/RWKV-LM) to [ggerganov/ggml](https://github.com/ggerganov/ggml).
Besides the usual **FP32**, it supports **FP16** and **quantized INT4** inference on CPU. This project is **CPU only**.
RWKV is a novel large language model architecture, [with t... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/README.md | 0.414188 | 0.940134 | README.md | pypi |
import argparse
import os
import pathlib
import time
import sampling
import tokenizers
import rwkv_cpp_model
import rwkv_cpp_shared_library
# ======================================== Script settings ========================================
prompt: str = """# rwkv.cpp
This is a port of [BlinkDL/RWKV-LM](https://git... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/rwkv/generate_completions.py | 0.558809 | 0.403097 | generate_completions.py | pypi |
import os
import sys
import argparse
import pathlib
import sampling
import tokenizers
import rwkv_cpp_model
import rwkv_cpp_shared_library
# ======================================== Script settings ========================================
# Copied from https://github.com/ggerganov/llama.cpp/blob/6e7801d08d81c931a542... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/rwkv/chat_with_bot.py | 0.467575 | 0.267193 | chat_with_bot.py | pypi |
import os
import time
import pathlib
import argparse
import tokenizers
import torch
import rwkv_cpp_model
import rwkv_cpp_shared_library
from typing import List
def parse_args():
parser = argparse.ArgumentParser(description='Measure perplexity and per-token latency of an RWKV model on a given text file')
pars... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/rwkv/measure_pexplexity.py | 0.809878 | 0.321966 | measure_pexplexity.py | pypi |
import os
import sys
import ctypes
import pathlib
from typing import Optional
P_FLOAT = ctypes.POINTER(ctypes.c_float)
class RWKVContext:
def __init__(self, ptr: ctypes.pointer):
self.ptr = ptr
class RWKVSharedLibrary:
"""
Python wrapper around rwkv.cpp shared library.
"""
def __init__... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/rwkv/rwkv_cpp_shared_library.py | 0.736021 | 0.333354 | rwkv_cpp_shared_library.py | pypi |
import os
import time
import uuid
import json
import pathlib
from typing import List, Optional, Literal, Union, Iterator, Dict
from typing_extensions import TypedDict
import sampling
import tokenizers
import rwkv_cpp_model
import rwkv_cpp_shared_library
import server_types
from fastapi import FastAPI
from fastapi.mi... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/rwkv/server.py | 0.735357 | 0.17545 | server.py | pypi |
from typing import List, Optional, Dict, Union
from typing_extensions import TypedDict, NotRequired, Literal
class EmbeddingUsage(TypedDict):
prompt_tokens: int
total_tokens: int
class EmbeddingData(TypedDict):
index: int
object: str
embedding: List[float]
class Embedding(TypedDict):
objec... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/rwkv/server_types.py | 0.834407 | 0.436562 | server_types.py | pypi |
import os
import torch
import multiprocessing
import rwkv_cpp_shared_library
from typing import Tuple, Optional
class RWKVModel:
"""
PyTorch wrapper around rwkv.cpp model.
"""
def __init__(
self,
shared_library: rwkv_cpp_shared_library.RWKVSharedLibrary,
model_path:... | /rwkv_cpp-0.0.1.tar.gz/rwkv_cpp-0.0.1/rwkv/rwkv_cpp_model.py | 0.893356 | 0.525186 | rwkv_cpp_model.py | pypi |
"""Console script for ddlpy."""
import sys
import io
import logging
import click
import pandas as pd
import dateutil
import ddlpy
@click.group()
@click.option('-v', '--verbose', count=True)
def cli(verbose, args=None):
"""Console script for ddlpy."""
level = logging.INFO
if verbose >= 1:
level ... | /rws-ddlpy-0.1.0.tar.gz/rws-ddlpy-0.1.0/ddlpy/cli.py | 0.430985 | 0.156975 | cli.py | pypi |
import io
import logging
from datetime import datetime, timedelta
from typing import Optional, Tuple
import mpu
import pandas as pd
import requests
logging.basicConfig()
logger = logging.getLogger(__name__)
logger.setLevel("INFO")
def import_daily_data(
start: str, end: str, coord: Optional[Tuple[float, float]]... | /rws_knmi_lib-1.0.0-py3-none-any.whl/rws_knmi_lib/knmi_downloader.py | 0.90676 | 0.514034 | knmi_downloader.py | pypi |
from typing import List, Optional, Tuple
from pydantic import BaseModel, validator
class NWBConfig(BaseModel):
"""NWB Config class.
only_state_roads
Whether to only keep state_roads (much faster when True),
fewer data of course.
output_file_path
The file path to write the downloa... | /rws-nwb-lib-1.0.1.tar.gz/rws-nwb-lib-1.0.1/rws_nwb_lib/config.py | 0.944944 | 0.670303 | config.py | pypi |
import logging
import warnings
from typing import List, Tuple
import geopandas as gpd
import requests
from requests import Response
from rws_nwb_lib.config import NWBConfig
logging.getLogger(__name__).addHandler(logging.NullHandler())
# Filter out warning thrown by geopandas
warnings.filterwarnings(
"ignore",
... | /rws-nwb-lib-1.0.1.tar.gz/rws-nwb-lib-1.0.1/rws_nwb_lib/download_nwb.py | 0.851181 | 0.407216 | download_nwb.py | pypi |
_colors = {
"blue": {
100: "#00549F",
75: "#407FB7",
50: "#8EBAE5",
25: "#C7DDF2",
10: "#E8F1FA"
},
"black": {
100: "#000000",
75: "#646567",
50: "#9C9E9F",
25: "#CFD1D2",
10: "#ECEDED"
},
"magenta": {
100: "#E30... | /rwth-CD-colors-0.1.1.tar.gz/rwth-CD-colors-0.1.1/rwth_colors.py | 0.747892 | 0.659295 | rwth_colors.py | pypi |
# rwth.nb
## Introduction
This project consists of Jupyter Notebook definitions used by RWTH Aachen University.
## Table of Contents
* [RWTH Plots](RWTH%20Plots.ipynb)
* [RWTH Colors](RWTH%20Colors.ipynb)
## Jupyter Quick Start
* To run all cells of a notebook: In the menu: Run <span class="fa-chevron-right fa"... | /rwth_nb-0.1.8.tar.gz/rwth_nb-0.1.8/index.ipynb | 0.65368 | 0.621254 | index.ipynb | pypi |
from matplotlib import rcParams
rcParams["axes.axisbelow"] = False
# rcParams['font.family'] = 'sans-serif'
# rcParams['font.sans-serif'] = ['Arial'] # TODO
# rcParams['font.size'] = 14
# rcParams['text.usetex'] = True
# rcParams['text.latex.unicode'] = True
import matplotlib.pyplot as plt
import matplotlib.ticker a... | /rwth_nb-0.1.8.tar.gz/rwth_nb-0.1.8/rwth_nb/plots/mpl_decorations.py | 0.576661 | 0.444324 | mpl_decorations.py | pypi |
from scipy import signal # butter
def butter(cutoff, fs, order=5, type='Tiefpass', fdelta=0):
"""Butterworth Filter of order n
Parameters
----------
cutoff : float
cutoff frequency
fs : float
sampling frequency, is used to calculate nyquist frequency
... | /rwth_nb-0.1.8.tar.gz/rwth_nb-0.1.8/rwth_nb/misc/filters.py | 0.916434 | 0.656149 | filters.py | pypi |
# Colors
When using `rwth_nb.plots.colors`, the RWTH [Corporate Design](http://www.rwth-aachen.de/cms/root/Die-RWTH/Einrichtungen/Verwaltung/Stabsstellen/Marketing/~eqbm/Corporate-Design/) color scheme is stored in a dictionary called `rwth_colors`. When loading `rwth_nb.plots.mpl_decorations`, the RWTH colors are pro... | /rwth_nb-0.1.8.tar.gz/rwth_nb-0.1.8/docs/source/examples/RWTH Colors.ipynb | 0.641198 | 0.885928 | RWTH Colors.ipynb | pypi |
# Miscellaneous
1. [Transforms](#Transforms)
1. [Fourier Transform](#Fourier-Transform)
2. [Laplace Transform](#Laplace-Transform)
3. [$z$-Transform](#$z$-Transform)
---
## Transforms
Following transforms are defined in `rwth_nb.misc.transforms`:
- [Fourier Transform](#Fourier-Transform)
- [Laplace T... | /rwth_nb-0.1.8.tar.gz/rwth_nb-0.1.8/docs/source/examples/RWTH Misc.ipynb | 0.647687 | 0.976602 | RWTH Misc.ipynb | pypi |
# Plots with Matplotlib
`rwth_nb.plots.mpl_decorations` extends Matplotlib to some useful functionality explained below
1. [Simple Plots](#Simple-Plots)
1. [Graph Plot](#Graph-Plot)
2. [Stem Plot](#Stem-Plot)
3. [Multiple Plots](#Multiple-Plots)
4. [Updating Plots](#Updating-Plots)
2. [Annotations](#An... | /rwth_nb-0.1.8.tar.gz/rwth_nb-0.1.8/docs/source/examples/RWTH Plots.ipynb | 0.591723 | 0.960025 | RWTH Plots.ipynb | pypi |
import matplotlib.pyplot as plt
from RWTHColors.colors import *
from cycler import cycler
class ColorManager:
RWTHBlau = RWTHBlau()
RWTHSchwarz = RWTHSchwarz()
RWTHMagenta = RWTHMagenta()
RWTHGelb = RWTHGelb()
RWTHPetrol = RWTHPetrol()
RWTHTuerkis = RWTHTuerkis()
RWTHGruen = RWTHGruen()
... | /rwthcolors-0.2.3-py3-none-any.whl/RWTHColors/cm.py | 0.666497 | 0.331282 | cm.py | pypi |
from abc import ABC, abstractmethod
class Color(ABC):
frmt = "HEX"
def __init__(self, frmt: str = "HEX"):
if frmt not in ["HEX", "RGB"]:
raise ValueError("frmt must be HEX or RGB not %s" % frmt)
self.frmt = frmt
@property
@abstractmethod
def HEX(self) -> dict:
... | /rwthcolors-0.2.3-py3-none-any.whl/RWTHColors/colors/colors.py | 0.885539 | 0.420094 | colors.py | pypi |
import math
import matplotlib.pyplot as plt
from .Generaldistribution import Distribution
class Gaussian(Distribution):
""" Gaussian distribution class for calculating and
visualizing a Gaussian distribution.
Attributes:
mean (float) representing the mean value of the distribution
stdev (float) representing ... | /rwx824550565_udacity-0.1.tar.gz/rwx824550565_udacity-0.1/rwx824550565_udacity/Gaussiandistribution.py | 0.688364 | 0.853058 | Gaussiandistribution.py | pypi |
import numpy
import math
import pandas as pnd
import utils_noroot as utnr
import matplotlib.pyplot as plt
from data_splitter import splitter as dsplit
#----------------------------
class calculator:
log = utnr.getLogger('lep_reso')
#----------------------------------
def __init__(self, dat... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/lep_reso.py | 0.590425 | 0.367043 | lep_reso.py | pypi |
import utils_noroot as utnr
import read_calibration as rcal
import utils
from rk.cutflow import cutflow
from rk.efficiency import efficiency
from rk.selection import selection as rksl
import os
import re
import ROOT
#-----------------------------------------------------------
class pr_getter:
log... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/pr_getter.py | 0.463201 | 0.153486 | pr_getter.py | pypi |
import utils_noroot as utnr
import matplotlib.pyplot as plt
import zutils.utils as zut
import ROOT
import zfit
import math
import tqdm
import numpy
import logging
import os
import utils
from zutils.plot import plot as zfplot
from data_splitter import splitter as dsplit
from fitter import z... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/fithst.py | 0.401923 | 0.189371 | fithst.py | pypi |
import math
import numpy
import utils_noroot as utnr
import numdifftools as ndt
from scipy.optimize import minimize
#---------------------------
class extractor:
log = utnr.getLogger('reso_extractor')
#---------------------------
def __init__(self, data=None, method = None, bounds=None, init_x = None, nb... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/reso_extractor.py | 0.508544 | 0.213644 | reso_extractor.py | pypi |
import ROOT
import os
import math
import numpy as np
import utils
import utils_noroot as utnr
from rk.oscillator import oscillator as osc
#-------------------------------------------
class reader:
log=utnr.getLogger(__name__)
def __init__(self):
self.d_map = {}
self.d_bound = {}
se... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/trackreader.py | 0.403567 | 0.1941 | trackreader.py | pypi |
from collections import UserDict
from rk.differential_efficiency import defficiency
from rk.efficiency import efficiency
from ndict import ndict
import utils_noroot as utnr
import pandas as pnd
#-----------------------------------------
class cutflow(UserDict):
log=u... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/cutflow.py | 0.581541 | 0.150684 | cutflow.py | pypi |
from logzero import logger as log
from zutils.plot import plot as zfp
from fitter import zfitter
import zfit
import math
import pandas as pnd
import utils_noroot as utnr
import matplotlib.pyplot as plt
#---------------------------
class calculator:
def __init__(self, pdf, poi_name = '... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/model_uncertainty.py | 0.57344 | 0.224842 | model_uncertainty.py | pypi |
import numpy
import logging
import pandas as pnd
import utils_noroot as utnr
import matplotlib.pyplot as plt
from rk.eff_yld_loader import eff_yld_loader as eyl
from stats.covariance import covariance
#------------------------------
class calculator:
log=utnr.getLogger(__name__)
#----------... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/ckcov.py | 0.534612 | 0.198025 | ckcov.py | pypi |
import utils_noroot as utnr
import utils
import read_selection as rs
import logging
from rk.selection import selection as rksl
#--------------------------------------------------
class selection:
"""
Class used to apply selections to dataframes
"""
log=utnr.getLogger('selection')
#-------------... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/dfselect.py | 0.531696 | 0.16248 | dfselect.py | pypi |
import utils_noroot as utnr
import re
import math
#--------------------------------------
class boundaries:
log=utnr.getLogger('boundaries')
#--------------------------
def __init__(self, tp):
self._bounds = tp
self._regex = '([inf\d\.-]+),\s+([inf\d\.-]+)'
self._identi... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/boundaries.py | 0.618896 | 0.167457 | boundaries.py | pypi |
import numpy
import re
import math
import logging
import pandas as pnd
import utils_noroot as utnr
import matplotlib.pyplot as plt
import zutils.utils as zut
from fitter import zfitter
from rk.boundaries import boundaries
from data_splitter import splitter as dsplit
from zutils.plot imp... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/dilep_reso.py | 0.529507 | 0.203213 | dilep_reso.py | pypi |
import utils_noroot as utnr
import matplotlib.pyplot as plt
import zfit
import math
import numpy
import re
import os
from zutils.plot import plot as zfp
from logzero import logger as log
from rk.scales import mass as mscale
from fitter import zfitter
#----------------------------------------... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/musg_extractor.py | 0.566139 | 0.248201 | musg_extractor.py | pypi |
import jacobi as jac
import math
import utils_noroot as utnr
import matplotlib.pyplot as plt
import zfit
from logzero import logger as log
#-----------------------------------------
class mass:
def __init__(self, dt=None, mc=None):
self._d_par_dt = dt
self._d_par_mc = mc
... | /rx_tools-0.0.3.tar.gz/rx_tools-0.0.3/src/rk/scales.py | 0.649356 | 0.227705 | scales.py | pypi |
import funcy
import typing
from typing import Any
import requests
import rx
from rx import operators as ops
import pdb
from rxw.models import *
def default_unit(key: str) -> Unit:
"""
given a json key, returns the unit for that key's
corresponding measurement
"""
units = {
'temp': Unit(Uni... | /rx_weather-2.0.1-py3-none-any.whl/rxw/openweathermap.py | 0.611962 | 0.225001 | openweathermap.py | pypi |
import typing
from typing import List, NewType, NamedTuple
from datetime import datetime
import pytz
import tzlocal
class Unit:
""" defines a unit of measure, "km/h or degress C """
@property
def symbol(self) -> str:
return self._symbol
def __init__(self, sym: str):
self._symbol = sy... | /rx_weather-2.0.1-py3-none-any.whl/rxw/models.py | 0.840193 | 0.532911 | models.py | pypi |
  
--------------------------------------------------------
"r... | /rx7-4.0.0.tar.gz/rx7-4.0.0/README.md | 0.728169 | 0.734304 | README.md | pypi |
RxPy back-pressure extension
============================
[](https://coveralls.io/github/MichaelSchneeberger/... | /rxbp-3.0.0a9.tar.gz/rxbp-3.0.0a9/README.md | 0.843186 | 0.923351 | README.md | pypi |
from dataclasses import field
from pathlib import Path
from typing import List, Optional, Union
from pydantic.dataclasses import dataclass
from xsdata_pydantic.bindings import XmlParser
from .models.oai_dc.org.openarchives.oai.pkg_2.pkg_0.oai_dc.dc import Dc
from .models.oai_pmh.org.openarchives.oai.pkg_2.header_type... | /rxiv_types-0.1.0.tar.gz/rxiv_types-0.1.0/src/rxiv_types/chemrxiv.py | 0.863478 | 0.334657 | chemrxiv.py | pypi |
from dataclasses import field
from pydantic.dataclasses import dataclass
from typing import List, Optional
from xsdata.models.datatype import XmlDateTime
from .get_record_type import GetRecordType
from .identify_type import IdentifyType
from .list_identifiers_type import ListIdentifiersType
from .list_metadata_formats_... | /rxiv_types-0.1.0.tar.gz/rxiv_types-0.1.0/src/rxiv_types/models/oai_pmh/org/openarchives/oai/pkg_2/oai_pmhtype.py | 0.802013 | 0.277027 | oai_pmhtype.py | pypi |
from dataclasses import field
from pydantic.dataclasses import dataclass
from typing import List, Optional, Union
from xsdata.models.datatype import XmlDate
from .deleted_record_type import DeletedRecordType
from .description_type import DescriptionType
from .granularity_type import GranularityType
from .protocol_versi... | /rxiv_types-0.1.0.tar.gz/rxiv_types-0.1.0/src/rxiv_types/models/oai_pmh/org/openarchives/oai/pkg_2/identify_type.py | 0.835618 | 0.312422 | identify_type.py | pypi |
from dataclasses import field
from pydantic.dataclasses import dataclass
from typing import Optional
from xsdata.models.datatype import XmlDate
__NAMESPACE__ = "https://api.bioriv.org/OAI/medRxivRaw/"
@dataclass
class MedRxivRawType:
class Meta:
name = "medRxivRaw_type"
id: Optional[str] = field(
... | /rxiv_types-0.1.0.tar.gz/rxiv_types-0.1.0/src/rxiv_types/models/medrxiv/https/api/bio_rxiv/org/oaipmh/med_rxiv_raw/med_rxiv_raw_type.py | 0.886948 | 0.421314 | med_rxiv_raw_type.py | pypi |
from dataclasses import field
from pydantic.dataclasses import dataclass
from typing import Optional
from xsdata.models.datatype import XmlDate
__NAMESPACE__ = "https://api.biorxiv.org/oaipmh/bioRxivRaw/"
@dataclass
class BioRxivRawType:
class Meta:
name = "bioRxivRaw_type"
id: Optional[str] = field... | /rxiv_types-0.1.0.tar.gz/rxiv_types-0.1.0/src/rxiv_types/models/biorxiv/https/api/biorxiv/org/oaipmh/bio_rxiv_raw/bio_rxiv_raw_type.py | 0.891002 | 0.44354 | bio_rxiv_raw_type.py | pypi |
from dataclasses import field
from pydantic.dataclasses import dataclass
from typing import List
__NAMESPACE__ = "http://www.openarchives.org/OAI/2.0/oai_dc/"
@dataclass
class OaiDcType:
class Meta:
name = "oai_dcType"
title: List[str] = field(
default_factory=list,
metadata={
... | /rxiv_types-0.1.0.tar.gz/rxiv_types-0.1.0/src/rxiv_types/models/oai_dc/org/openarchives/oai/pkg_2/pkg_0/oai_dc/oai_dc_type.py | 0.729905 | 0.321513 | oai_dc_type.py | pypi |
# :leaves: Biocatalysis Model
*Biocatalysed Synthesis Planning using Data-driven Learning*
## Table of Contents
- [Abstract](#abstract)
- [Data](#data)
- [ECREACT](#ecreact)
- [Data Sources](#data-sources)
- [Using the Pre-trained Model](#using-the-pre-trained-model)
- [Training your own Model](#training-your-ow... | /rxn-biocatalysis-tools-1.0.1.tar.gz/rxn-biocatalysis-tools-1.0.1/README.md | 0.632843 | 0.982774 | README.md | pypi |
import re
from typing import List, Any
from .chemical_reaction import ChemicalReaction
from rdkit.Chem import AllChem as rdk
from rdkit.Chem.rdchem import Mol
UNKNOWN_CHEMICAL_REGEX = re.compile(r"^(<.*>)$|^(<)|(>)$")
class EnzymaticReaction(ChemicalReaction):
"""Representation of an enzymatic reaction.
Rea... | /rxn-biocatalysis-tools-1.0.1.tar.gz/rxn-biocatalysis-tools-1.0.1/rxn_biocatalysis_tools/enzymatic_reaction.py | 0.915656 | 0.611237 | enzymatic_reaction.py | pypi |
import re
SMILES_TOKENIZER_PATTERN = r"(\%\([0-9]{3}\)|\[[^\]]+]|Br?|Cl?|N|O|S|P|F|I|b|c|n|o|s|p|\||\(|\)|\.|=|#|-|\+|\\|\/|:|~|@|\?|>>?|\*|\$|\%[0-9]{2}|[0-9])"
SMILES_REGEX = re.compile(SMILES_TOKENIZER_PATTERN)
def tokenize_enzymatic_reaction_smiles(rxn: str, keep_pipe=False) -> str:
"""Tokenize an enzymatic ... | /rxn-biocatalysis-tools-1.0.1.tar.gz/rxn-biocatalysis-tools-1.0.1/rxn_biocatalysis_tools/tokenizer.py | 0.705176 | 0.370766 | tokenizer.py | pypi |
import logging
import random
from typing import Callable, List
from .miscellaneous import apply_to_any_smiles, apply_to_smiles_groups
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
class SmilesAugmenter:
"""
Class to augment any kind of SMILES string with the help of randomiza... | /rxn_chem_utils-1.3.0-py3-none-any.whl/rxn/chemutils/smiles_augmenter.py | 0.878262 | 0.453746 | smiles_augmenter.py | pypi |
from enum import auto
from rxn.utilities.types import RxnEnum
from .extended_reaction_smiles import (
parse_extended_reaction_smiles,
to_extended_reaction_smiles,
)
from .reaction_equation import ReactionEquation
class ReactionFormat(RxnEnum):
"""
Existing reaction SMILES formats.
Attributes:
... | /rxn_chem_utils-1.3.0-py3-none-any.whl/rxn/chemutils/reaction_smiles.py | 0.924874 | 0.501282 | reaction_smiles.py | pypi |
from functools import partial
from typing import Callable, Iterable, List, Optional
from rxn.utilities.containers import remove_duplicates
from .conversion import canonicalize_smiles
def multicomponent_smiles_to_list(
multicomponent_smiles: str, fragment_bond: Optional[str] = None
) -> List[str]:
"""
Co... | /rxn_chem_utils-1.3.0-py3-none-any.whl/rxn/chemutils/multicomponent_smiles.py | 0.957981 | 0.528959 | multicomponent_smiles.py | pypi |
import logging
import re
import shutil
from typing import List, Optional
from rxn.utilities.files import (
PathLike,
dump_list_to_file,
iterate_lines_from_file,
raise_if_paths_are_identical,
)
from .exceptions import UnclearWhetherTokenized
logger = logging.getLogger(__name__)
logger.addHandler(loggi... | /rxn_chem_utils-1.3.0-py3-none-any.whl/rxn/chemutils/tokenization.py | 0.792424 | 0.320715 | tokenization.py | pypi |
from itertools import chain, repeat, zip_longest
from typing import Iterable, Iterator, Sequence, Tuple
from rxn.utilities.misc import get_multipliers
from .miscellaneous import merge_reactions
from .reaction_equation import ReactionEquation, canonicalize_compounds, sort_compounds
from .reaction_smiles import (
R... | /rxn_chem_utils-1.3.0-py3-none-any.whl/rxn/chemutils/reaction_combiner.py | 0.918969 | 0.570391 | reaction_combiner.py | pypi |
import logging
import re
import typing
from collections import Counter
from functools import partial
from typing import Callable, List
from rdkit.Chem import AddHs, Atom, Mol
from rxn.utilities.files import (
PathLike,
dump_list_to_file,
iterate_lines_from_file,
raise_if_paths_are_identical,
)
from .c... | /rxn_chem_utils-1.3.0-py3-none-any.whl/rxn/chemutils/miscellaneous.py | 0.876344 | 0.438785 | miscellaneous.py | pypi |
from functools import partial
from typing import (
Callable,
Generator,
Iterable,
Iterator,
List,
Optional,
Type,
TypeVar,
)
import attr
from rxn.utilities.containers import remove_duplicates
from .conversion import canonicalize_smiles, cleanup_smiles
from .exceptions import InvalidRea... | /rxn_chem_utils-1.3.0-py3-none-any.whl/rxn/chemutils/reaction_equation.py | 0.939178 | 0.588121 | reaction_equation.py | pypi |
from typing import Any, Dict, Iterable, List, Sequence
import numpy as np
from rxn.chemutils.reaction_smiles import parse_any_reaction_smiles
from rxn.utilities.containers import chunker
from rxn.utilities.files import PathLike, iterate_lines_from_file
from .metrics import top_n_accuracy
from .metrics_calculator impo... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/context_metrics.py | 0.91668 | 0.518241 | context_metrics.py | pypi |
from typing import Dict, List, Sequence, Tuple, TypeVar
import numpy as np
from rxn.utilities.containers import chunker
from .utils import get_sequence_multiplier
T = TypeVar("T")
def top_n_accuracy(
ground_truth: Sequence[T], predictions: Sequence[T]
) -> Dict[int, float]:
"""
Compute the top-n accura... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/metrics.py | 0.927486 | 0.685357 | metrics.py | pypi |
from typing import Any, Dict, Iterable, List, Optional
from rxn.utilities.files import PathLike, iterate_lines_from_file, load_list_from_file
from .metrics import class_diversity, coverage, round_trip_accuracy, top_n_accuracy
from .metrics_calculator import MetricsCalculator
from .metrics_files import MetricsFiles, R... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/retro_metrics.py | 0.901708 | 0.316871 | retro_metrics.py | pypi |
import logging
from rxn.utilities.files import (
PathLike,
dump_list_to_file,
iterate_lines_from_file,
raise_if_paths_are_identical,
)
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
def detokenize_class(tokenized_class: str) -> str:
"""
Function performing a de... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/tokenize_file.py | 0.719679 | 0.389285 | tokenize_file.py | pypi |
from typing import Iterator, Sequence, TypeVar
from rxn.chemutils.reaction_combiner import ReactionCombiner
from rxn.chemutils.reaction_smiles import ReactionFormat
from rxn.utilities.files import PathLike, count_lines, iterate_lines_from_file
from rxn.utilities.misc import get_multiplier, get_multipliers
T = TypeVar... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/utils.py | 0.9363 | 0.285412 | utils.py | pypi |
import logging
from pathlib import Path
from typing import Optional, Union
from rxn.chemutils.tokenization import file_is_tokenized, tokenize_file
from rxn.onmt_utils import translate
from rxn.utilities.files import dump_list_to_file, is_path_exists_or_creatable
from .metrics_files import RetroFiles
from .tokenize_fi... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/classification_translation.py | 0.931455 | 0.31662 | classification_translation.py | pypi |
import json
import logging
from pathlib import Path
from typing import Dict, Type
from rxn.chemutils.miscellaneous import canonicalize_file
from rxn.chemutils.tokenization import copy_as_detokenized
from rxn.onmt_models import rxn_translation
from rxn.utilities.files import PathLike, ensure_directory_exists_and_is_emp... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/run_metrics.py | 0.656438 | 0.188268 | run_metrics.py | pypi |
from pathlib import Path
from rxn.utilities.files import PathLike
class MetricsFiles:
def __init__(
self,
directory: PathLike,
gt_src: str = "gt_src.txt",
gt_tgt: str = "gt_tgt.txt",
predicted: str = "pred.txt",
predicted_canonical: str = "predicted_canonical.txt",... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/metrics_files.py | 0.837454 | 0.248056 | metrics_files.py | pypi |
import logging
from pathlib import Path
from typing import List, Tuple, Union
import click
from rxn.utilities.containers import chunker
from rxn.utilities.files import dump_list_to_file, load_list_from_file
from rxn.metrics.metrics_files import RetroFiles
from rxn.metrics.utils import get_sequence_multiplier
logger ... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/scripts/reorder_retro_predictions_class_token.py | 0.798383 | 0.448849 | reorder_retro_predictions_class_token.py | pypi |
import logging
import math
from pathlib import Path
from typing import Iterable, Tuple
import click
from rxn.utilities.files import (
PathLike,
count_lines,
dump_list_to_file,
load_list_from_file,
)
from rxn.utilities.logging import setup_console_logger
logger = logging.getLogger(__name__)
logger.addH... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/scripts/ensure_data_dimension.py | 0.55917 | 0.222278 | ensure_data_dimension.py | pypi |
import logging
from pathlib import Path
from typing import Optional
import click
from rxn.chemutils.miscellaneous import canonicalize_file
from rxn.chemutils.tokenization import copy_as_detokenized
from rxn.onmt_models import rxn_translation
from rxn.utilities.files import ensure_directory_exists_and_is_empty
from rxn... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/scripts/prepare_retro_metrics.py | 0.819207 | 0.174991 | prepare_retro_metrics.py | pypi |
import logging
import re
import shutil
from pathlib import Path
from typing import List, Tuple
import click
from rxn.utilities.files import PathLike, raise_if_paths_are_identical
from rxn.utilities.logging import setup_console_logger
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
def ... | /rxn_metrics-1.1.0-py3-none-any.whl/rxn/metrics/scripts/join_data_files.py | 0.6508 | 0.263757 | join_data_files.py | pypi |
import logging
from collections import defaultdict
from functools import partial
from typing import Callable, DefaultDict, Iterable, Iterator, Tuple
from rxn.chemutils.conversion import canonicalize_smiles, smiles_to_inchi
from rxn.chemutils.miscellaneous import apply_to_any_smiles, sort_any
from typing_extensions imp... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/prediction_collapser.py | 0.876905 | 0.295408 | prediction_collapser.py | pypi |
from typing import Optional
from rxn.chemutils.tokenization import detokenize_file, file_is_tokenized, tokenize_file
from rxn.onmt_utils import translate
from rxn.utilities.files import PathLike, is_path_exists_or_creatable
def rxn_translation(
src_file: PathLike,
tgt_file: Optional[PathLike],
pred_file:... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/translation.py | 0.92887 | 0.363223 | translation.py | pypi |
import datetime
import logging
import subprocess
from typing import IO, List, Optional, cast
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
def log_file_name_from_time(prefix: Optional[str] = None) -> str:
"""
Get the name of a log file (typically to create it) from the current... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/utils.py | 0.775732 | 0.181354 | utils.py | pypi |
import logging
import re
from itertools import count
from pathlib import Path
from typing import Optional
from rxn.utilities.files import PathLike
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
class ModelFiles:
"""
Class to make it easy to get the names/paths of the trained O... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/training_files.py | 0.881328 | 0.343356 | training_files.py | pypi |
import logging
from typing import Tuple
import click
from rxn.onmt_utils import __version__ as onmt_utils_version
from rxn.onmt_utils.train_command import OnmtTrainCommand
from rxn.utilities.logging import setup_console_and_file_logger
from rxn.onmt_models import __version__ as onmt_models_version
from rxn.onmt_model... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/scripts/rxn_onmt_train.py | 0.693784 | 0.169337 | rxn_onmt_train.py | pypi |
import logging
from typing import Optional, Tuple
import click
from rxn.onmt_utils import __version__ as onmt_utils_version
from rxn.onmt_utils.model_introspection import (
get_model_dropout,
get_model_seed,
model_vocab_is_compatible,
)
from rxn.onmt_utils.train_command import OnmtTrainCommand
from rxn.uti... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/scripts/rxn_onmt_continue_training.py | 0.737158 | 0.204362 | rxn_onmt_continue_training.py | pypi |
import logging
from pathlib import Path
import click
from rxn.onmt_utils import __version__ as onmt_utils_version
from rxn.reaction_preprocessing.config import (
CommonConfig,
Config,
DataConfig,
FragmentBond,
InitialDataFormat,
PreprocessConfig,
RxnImportConfig,
SplitConfig,
Standa... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/scripts/rxn_prepare_data.py | 0.470007 | 0.153962 | rxn_prepare_data.py | pypi |
import logging
import random
from pathlib import Path
from typing import List, Optional, Tuple
import click
from rxn.chemutils.tokenization import ensure_tokenized_file
from rxn.onmt_utils import __version__ as onmt_utils_version
from rxn.onmt_utils.train_command import preprocessed_id_names
from rxn.utilities.files i... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/scripts/rxn_onmt_preprocess.py | 0.829043 | 0.37711 | rxn_onmt_preprocess.py | pypi |
from typing import Iterator, List, Optional, Union
import click
from attr import define
from rxn.onmt_utils.train_command import RxnCommand
import rxn.onmt_models.defaults as defaults
_CONTEXT_DATA_BATCH_SIZE = 8
class Parameter:
"""
Parameter to be queried to the user, if the command(s) are necessary.
... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/scripts/rxn_plan_training.py | 0.885761 | 0.262286 | rxn_plan_training.py | pypi |
import logging
import random
from pathlib import Path
from typing import Tuple
import click
from rxn.utilities.files import stable_shuffle
from rxn.utilities.logging import setup_console_logger
from rxn.onmt_models.augmentation import augment_translation_dataset
from rxn.onmt_models.training_files import RxnPreproces... | /rxn-onmt-models-1.0.1.tar.gz/rxn-onmt-models-1.0.1/src/rxn/onmt_models/scripts/rxn_onmt_augment.py | 0.761361 | 0.217639 | rxn_onmt_augment.py | pypi |
from argparse import Namespace
from typing import Any, Dict, List
import torch
from onmt.inputters.text_dataset import TextMultiField
from rxn.utilities.files import PathLike
def get_model_vocab(model_path: PathLike) -> List[str]:
"""
Get the vocabulary from a model checkpoint.
Args:
model_path:... | /rxn-onmt-utils-1.0.3.tar.gz/rxn-onmt-utils-1.0.3/src/rxn/onmt_utils/model_introspection.py | 0.958421 | 0.527256 | model_introspection.py | pypi |
import logging
from typing import List
import torch
import torch.nn as nn
from onmt.model_builder import build_model # type: ignore
from onmt.utils.parse import ArgumentParser # type: ignore
from rxn.utilities.files import PathLike
from torch.nn.init import xavier_uniform_
logger = logging.getLogger(__name__)
logge... | /rxn-onmt-utils-1.0.3.tar.gz/rxn-onmt-utils-1.0.3/src/rxn/onmt_utils/model_resize.py | 0.926628 | 0.307631 | model_resize.py | pypi |
import logging
import subprocess
from typing import List, Optional
from rxn.utilities.files import PathLike, iterate_lines_from_file
from .translator import Translator
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
def translate(
model: PathLike,
src: PathLike,
tgt: Optio... | /rxn-onmt-utils-1.0.3.tar.gz/rxn-onmt-utils-1.0.3/src/rxn/onmt_utils/translate.py | 0.904564 | 0.407098 | translate.py | pypi |
from argparse import Namespace
from typing import Any, Iterable, Iterator, List, Optional, Union
from .internal_translation_utils import RawTranslator, TranslationResult, get_onmt_opt
class Translator:
"""
Wraps the OpenNMT translation functionality into a class.
"""
def __init__(self, opt: Namespac... | /rxn-onmt-utils-1.0.3.tar.gz/rxn-onmt-utils-1.0.3/src/rxn/onmt_utils/translator.py | 0.942692 | 0.381824 | translator.py | pypi |
"""Training on a single process."""
import os
import torch
from onmt.inputters.inputter import build_dataset_iter, \
load_old_vocab, old_style_vocab, build_dataset_iter_multiple
from onmt.model_builder import build_model
from onmt.utils.optimizers import Optimizer
from onmt.utils.misc import set_random_seed
from ... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/train_single.py | 0.646906 | 0.3229 | train_single.py | pypi |
import torch
import torch.nn as nn
def context_gate_factory(gate_type, embeddings_size, decoder_size,
attention_size, output_size):
"""Returns the correct ContextGate class"""
gate_types = {'source': SourceContextGate,
'target': TargetContextGate,
... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/modules/gate.py | 0.967039 | 0.58519 | gate.py | pypi |
import torch
import torch.nn as nn
import torch.nn.functional as F
from onmt.modules.sparse_activations import sparsemax
from onmt.utils.misc import aeq, sequence_mask
# This class is mainly used by decoder.py for RNNs but also
# by the CNN / transformer decoder when copy attention is used
# CNN has its own attention... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/modules/global_attention.py | 0.927831 | 0.698783 | global_attention.py | pypi |
import torch
import torch.nn as nn
from torch.autograd import Function
from onmt.modules.sparse_activations import _threshold_and_support
from onmt.utils.misc import aeq
class SparsemaxLossFunction(Function):
@staticmethod
def forward(ctx, input, target):
"""
input (FloatTensor): ``(n, num_cl... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/modules/sparse_losses.py | 0.962116 | 0.615637 | sparse_losses.py | pypi |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
def get_var_maybe_avg(namespace, var_name, training, polyak_decay):
""" utility for retrieving polyak averaged params
Update average
"""
v = getattr(namespace, var_name)
v_avg = getattr(namespace,... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/modules/weight_norm.py | 0.900891 | 0.483283 | weight_norm.py | pypi |
import torch
import torch.nn as nn
import torch.nn.functional as F
from onmt.utils.misc import aeq
SCALE_WEIGHT = 0.5 ** 0.5
def seq_linear(linear, x):
""" linear transform for 3-d tensor """
batch, hidden_size, length, _ = x.size()
h = linear(torch.transpose(x, 1, 2).contiguous().view(
batch * ... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/modules/conv_multi_step_attention.py | 0.954616 | 0.692759 | conv_multi_step_attention.py | pypi |
import torch
from torch.autograd import Function
import torch.nn as nn
def _make_ix_like(input, dim=0):
d = input.size(dim)
rho = torch.arange(1, d + 1, device=input.device, dtype=input.dtype)
view = [1] * input.dim()
view[0] = -1
return rho.view(view).transpose(0, dim)
def _threshold_and_suppor... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/modules/sparse_activations.py | 0.938752 | 0.645357 | sparse_activations.py | pypi |
"""Average Attention module."""
import torch
import torch.nn as nn
from onmt.modules.position_ffn import PositionwiseFeedForward
class AverageAttention(nn.Module):
"""
Average Attention module from
"Accelerating Neural Transformer via an Average Attention Network"
:cite:`DBLP:journals/corr/abs-1805-... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/modules/average_attn.py | 0.97151 | 0.671188 | average_attn.py | pypi |
from itertools import chain, starmap
from collections import Counter
import torch
from torchtext.data import Dataset as TorchtextDataset
from torchtext.data import Example
from torchtext.vocab import Vocab
def _join_dicts(*args):
"""
Args:
dictionaries with disjoint keys.
Returns:
a sin... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/inputters/dataset_base.py | 0.911557 | 0.564399 | dataset_base.py | pypi |
import os
import torch
from torchtext.data import Field
from onmt.inputters.datareader_base import DataReaderBase
# domain specific dependencies
try:
from PIL import Image
from torchvision import transforms
import cv2
except ImportError:
Image, transforms, cv2 = None, None, None
class ImageDataRea... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/inputters/image_dataset.py | 0.898994 | 0.435841 | image_dataset.py | pypi |
import os
import torch
from torchtext.data import Field
from onmt.inputters.datareader_base import DataReaderBase
try:
import numpy as np
except ImportError:
np = None
class VecDataReader(DataReaderBase):
"""Read feature vector data from disk.
Raises:
onmt.inputters.datareader_base.MissingD... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/inputters/vec_dataset.py | 0.911436 | 0.556641 | vec_dataset.py | pypi |
import os
from tqdm import tqdm
import torch
from torchtext.data import Field
from onmt.inputters.datareader_base import DataReaderBase
# imports of datatype-specific dependencies
try:
import torchaudio
import librosa
import numpy as np
except ImportError:
torchaudio, librosa, np = None, None, None
... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/inputters/audio_dataset.py | 0.827898 | 0.338214 | audio_dataset.py | pypi |
from functools import partial
import six
import torch
from torchtext.data import Field, RawField
from onmt.inputters.datareader_base import DataReaderBase
class TextDataReader(DataReaderBase):
def read(self, sequences, side, _dir=None):
"""Read text data from disk.
Args:
sequences (... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/inputters/text_dataset.py | 0.918815 | 0.525369 | text_dataset.py | pypi |
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence as pack
from torch.nn.utils.rnn import pad_packed_sequence as unpack
from onmt.encoders.encoder import EncoderBase
from onmt.utils.rnn_factory import rnn_factory
class RNNEncoder(EncoderBase):
""" A generic... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/encoders/rnn_encoder.py | 0.95469 | 0.521837 | rnn_encoder.py | pypi |
import torch.nn as nn
from onmt.encoders.encoder import EncoderBase
from onmt.modules import MultiHeadedAttention
from onmt.modules.position_ffn import PositionwiseFeedForward
from onmt.utils.misc import sequence_mask
class TransformerEncoderLayer(nn.Module):
"""
A single layer of the transformer encoder.
... | /rxn_opennmt_py-1.1.4-py3-none-any.whl/onmt/encoders/transformer.py | 0.956685 | 0.355188 | transformer.py | pypi |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.