text stringlengths 3.07k 12.6k |
|---|
# -*- coding: UTF-8 -*-
"""
..
---------------------------------------------------------------------
___ __ __ __ ___
/ | \ | \ | \ / the automatic
\__ |__/ |__/ |___| \__ annotation and
\ | | | | \ ... |
'''User views.'''
from django.contrib.admin.views.decorators import staff_member_required
from django.contrib.auth import authenticate, login, logout
from django.contrib.auth.models import User
from django.shortcuts import get_object_or_404, redirect, render
from django.core.urlresolvers import reverse
from . import ... |
"""
Accession2Taxid
After alignment, IDseq uses the NCBI accession2taxid database to map accessions to taxonomic IDs.
The full database contains billions of entries, but only ~15% of those are found in either NR or NT databases.
Therefore, the full NCBI accession2taxid database is subsetted to include only the relevant... |
"""
@author : <NAME>
@date : 1/9/2021
Contains PCA and tSNE, two amazing dimensionality reduction algorithms. PCA can deal with around 1000 - 10000 data points
(obviously depending on the number of dimensions.) tSNE is better for visualizations but struggles past five hundred points,
so PCA is usually better for big d... |
import os
import io
import argparse
import configparser
import ipaddress
import subprocess
import sys
def first_available_ip_from_subnet(args: object):
result = []
host_list = {}
taken_host_list = {}
subnets = list(map(lambda x: x.strip(), args.subnet.split(',')))
for subnet in subnets:
n... |
# Copyright (c) <NAME>.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory.
# parallel optimization retry of a list of problems.
import numpy as np
import _pickle as cPickle
import bz2
import multiprocessing as mp
from scipy.optimize import OptimizeResult
from fc... |
import os
import shutil
import tempfile
from datetime import datetime
import shapely
from django.db import connection
from django.db.models import Q
from django.http import FileResponse
from jobs.utils import enqueue_job
from paramiko.ssh_exception import AuthenticationException
from rest_framework import permissions,... |
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import os
import shutil
import unittest
from unittest import mock
from azure_monitor.storage import (
LocalFileBlob,
LocalFileStorage,
_now,
_seconds,
)
TEST_FOLDER = os.path.abspath(".test")
# pylint: dis... |
# -*- coding: utf-8 -*-
import multiprocessing
from queue import Empty
from collections import deque
from collections.abc import Sequence, Mapping
import time
def stage(loop_func, queue_size=10, **kwargs):
""" Decorator que transforma a função em um objeto da classe Stage. """
return Stage(loop_func=loop_func... |
"""
飞机的基类
我方的飞机 敌方的小型飞机 敌方的中型飞机 敌方的大型飞机
"""
import random
import pygame
import constants
from game.bullet import Bullet
class Plane(pygame.sprite.Sprite):
""""
飞机的基础类
"""
# 飞机的图片
plane_images = []
# 飞机爆炸的图片
destroy_images = []
# 坠毁的音乐地址
down... |
# Competitive CoEA search of the one max / MaxMinHill optimization problem
from mimetypes import init
from operator import ge
from numpy.random import randint
from numpy.random import rand
from numpy.random import randn
from numpy.random import seed
import random
import time
import copy
import pandas as pd
import numpy... |
# Copyright 2021 MosaicML. All Rights Reserved.
from __future__ import annotations
import logging
from dataclasses import asdict, dataclass
from typing import Optional
import torch
import yahp as hp
from composer.algorithms.algorithm_hparams import AlgorithmHparams
from composer.core import Algorithm, Event, Logger... |
import os
import subprocess
from textwrap import dedent
from textwrap import indent
from textwrap import wrap
from docutils import nodes
from docutils.parsers.rst import directives
from pygments import highlight
from pygments.formatters import HtmlFormatter
from pygments.lexers import MysCommandLexer
from pygments.lex... |
from __future__ import print_function
from traceback import print_exc
from pprint import pprint
from yael_util import *
from module_constants import *
from ID_factions import *
from header_items import *
from header_operations import *
from header_triggers import *
# Some constants for ease of use.
imodbits_none = ... |
#!/usr/bin/env python3
import argparse
import botocore
import random
import string
module_info = {
'name': 'iam__enum_roles',
'author': '<NAME> of Rhino Security Labs',
'category': 'RECON_UNAUTH',
'one_liner': 'Enumerates IAM roles in a separate AWS account, given the account ID.',
'descriptio... |
"""Initialize the distributed services"""
import multiprocessing as mp
import traceback
import atexit
import time
import os
import sys
from . import rpc
from .constants import MAX_QUEUE_SIZE
from .kvstore import init_kvstore, close_kvstore
from .rpc_client import connect_to_server, shutdown_servers
from .role import ... |
# -*- coding: utf-8 -*-
"""
SCP Module
==========
.. versionadded:: 2019.2.0
Module to copy files via `SCP <https://man.openbsd.org/scp>`_
"""
from __future__ import absolute_import, print_function, unicode_literals
import inspect
# Import python libs
import logging
# Import salt modules
from salt.ext import six
... |
# Copyright 2017, <NAME>. All Rights Reserved.
#
# 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 agre... |
from tensorflow import keras
from tensorflow.python.keras import activations
import numpy as np
import tensorflow as tf
__all__ = ['Bihomogeneous','Bihomogeneous_k2','Bihomogeneous_k3',
'Bihomogeneous_k4','Dense','WidthOneDense']
print("Hello from BihomoNN! Arbitrary dimension!")
class Bihomogeneous(keras... |
import torch
import numpy as np
from alchemy.brain import Brain
from utils.memory import Memory
from utils.rl_algos import BrainOptimizer
import time, random
from timebudget import timebudget
class BrainDescription:
def __init__(self,
memory_size, batch_size,
optim_pool_size, optim_epoch... |
#!/bin/python
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
import numpy as np
import sys
# Python 3 backwards compatibility tricks
if sys.version_info.major > 2:
def xrange(*args, **kwargs):
return iter(range(*args, **kwargs)... |
import logging
import os
import time
import torch
import torch.nn as nn
from utils.meter import AverageMeter
from utils.metrics import R1_mAP_eval
from torch.cuda import amp
import torch.distributed as dist
def do_train(cfg,
model,
center_criterion,
train_loader,
val... |
# Copyright (c) 2015 Mirantis, Inc.
#
# 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 writin... |
# coding: utf-8
# /*##########################################################################
#
# Copyright (c) 2004-2017 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to d... |
import os
import logging
import argparse
import tensorflow as tf
import numpy as np
import sequence_modeling
import gensim
from data.util import data_set
def train(epoch, model, feeder, input_format, save_path="./", lr_decay=1.0, test=False):
""" Train model based on mini-batch of input data.
:param model: m... |
import os
import os.path
import ntpath
from typing import ItemsView
import logging
class StringRead:
DEFAULT_ZOOM_LEVEL = 0
DEFAULT_COLOR = "white"
def __init__(self, _stringToSplit: str, _file):
self.m_stringToSplit = _stringToSplit
self.m_pathfile = _file
self.m_stringToSave = ... |
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import torch, pdb
import torch.nn as nn
import torch.autograd
from torch.autograd import Variable
import torch.utils.data
from sklearn.preprocessing import QuantileTransformer
feat_length = 168
input_size =... |
""" Survival regression with Cox's proportional hazard model. """
import argparse
import logging
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from lifelines import CoxPHFitter
MAX_DUR = 180
def get_pmf_from_survival(survival_f):
pmf = survival_f.copy()
for i in range(survival_f.sh... |
from collections import defaultdict
import json
import numpy as np
import os
import PIL.Image
import PIL.ImageDraw
from ..meta.getter_dataset import GetterDataset
import cv2
try:
from pycocotools import mask as coco_mask
except ImportError:
pass
class COCOInstancesBaseDataset(GetterDataset):
def __init... |
import pytest
import numpy as np
import pandas as pd
from pandas.testing import assert_frame_equal
import altair_transform
from altair_transform.transform.aggregate import AGG_REPLACEMENTS
AGGREGATES = [
"argmax",
"argmin",
"average",
"count",
"distinct",
"max",
"mean",
"median",
... |
from dataloaders.datasets.pascal import VOCSegmentation
from modeling.deeplab import DeepLabX
from mypath import Path
import dataloaders.custom_transforms as tr
import torch
import numpy as np
import json
import os
from torchvision import transforms
from PIL import Image, ImageFilter
from scipy import ndimage
from data... |
import os
import sys
from typing import *
import numpy as np
sys.path.append('/home/pliang/multibench/MultiBench/datasets/imdb')
from robustness.visual_robust import visual_robustness
from robustness.text_robust import text_robustness
from vgg import VGGClassifier
from gensim.models import KeyedVectors
import h5py
f... |
import os
from distutils.dir_util import copy_tree
import warnings
import IPython
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy as sp
import torch
from context import utils
import utils.filesystem as fs
import utils.plotting as plot
from utils.data_analysis impo... |
#! /usr/bin/python3
#
# Copyright (c) 2017 Intel Corporation
#
# SPDX-License-Identifier: Apache-2.0
#
import contextlib
import os
from . import cm_logger
import ttbl
# FIXME: move to console/serial or something more consistent
class cm_serial(ttbl.test_target_console_mixin):
"""Implement console/s over serial p... |
from IMLearn.learners.regressors import LinearRegression
from typing import NoReturn
from IMLearn.utils import split_train_test
import numpy as np
import pandas as pd
import plotly.graph_objects as go
import plotly.express as px
import plotly.io as pio
pio.templates.default = "simple_white"
def load_data(filename: s... |
from rdflib.graph import ConjunctiveGraph
from StringIO import StringIO
import unittest
import rdflib
# json is only available as of python2.6, but simplejson is available
# via PyPI for older pythons
try:
import json
except ImportError:
try:
import simplejson as json
except ImportError:
... |
# -*- coding: utf-8 -*-
"""
This is a skeleton file that can serve as a starting point for a Python
console script. To run this script uncomment the following lines in the
[options.entry_points] section in setup.cfg:
console_scripts =
fibonacci = bytespread.skeleton:run
Then run `python setup.py install`... |
#!/usr/bin/env python3
import sys,os,json,random,re
assert sys.version_info >= (3,8), "This script requires at least Python 3.8"
set_variables = {}
def load(l):
f = open(os.path.join(sys.path[0], l))
data = f.read()
j = json.loads(data)
return j
def find_passage_pid(game_desc, pid):
for p in gam... |
"""
Manage the diffuse sources
$Header: /nfs/slac/g/glast/ground/cvs/pointlike/python/uw/like2/Attic/diffusedict.py,v 1.4 2013/10/14 15:11:42 burnett Exp $
author: <NAME>
"""
import os, types, json, collections
#import pickle, glob, copy, zipfile
#import numpy as np
#import pandas as pd
#from .pub import... |
#!/usr/bin/python3
#
# Copyright (c) 2019 Foundries.io
# SPDX-License-Identifier: Apache-2.0
#
import argparse
import logging
import json
import os
import subprocess
import urllib.request
from copy import deepcopy
from tag_manager import TagMgr
logging.basicConfig(level='INFO')
fh = logging.FileHandler('/archive/cust... |
#Pytorch version of the adaptive black-box attack
import torch
import AttackWrappersWhiteBoxP
import DataManagerPytorch as DMP
from DataLoaderGiant import DataLoaderGiant
from datetime import date
import os
global queryCounter #keep track of the numbers of queries used in the adaptive black-box attack, just f... |
# adapter.py
#
# Part of Flake518
#
# Copyright (c) 2021 <NAME>
#
# 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, m... |
"""A bunch of garbage stuff that I'm not going to comment because it's so bad"""
from collections import defaultdict
import discord
from discord.ext import menus
class LeaderboardSource(menus.ListPageSource):
async def format_page(self, menu, page):
embed = discord.Embed(title="Scoresaber Top 50", color=... |
import logging
from banal import ensure_list
from followthemoney import model
from followthemoney.types import registry
from aleph.core import settings
from aleph.index.util import index_settings, configure_index
log = logging.getLogger(__name__)
DATE_FORMAT = "yyyy-MM-dd'T'HH:mm:ss||yyyy-MM-dd||yyyy-MM||yyyy"
PART... |
#!/usr/bin/env python3
# ----------------------------------------------------------------------------
# Copyright (c) 2018--, Qurro development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE.txt, distributed with this software.
# --------------------------... |
#!/usr/bin/python
# Copyright (c) 2020, 2021 Oracle and/or its affiliates.
# This software is made available to you under the terms of the GPL 3.0 license or the Apache 2.0 license.
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
# Apache License v2.0
# See LICENSE.TXT for d... |
# -*- coding: utf-8 -*-
'''
Custom YAML loading in Salt
'''
# Import python libs
from __future__ import absolute_import, print_function, unicode_literals
import re
import warnings
import yaml # pylint: disable=blacklisted-import
from yaml.nodes import MappingNode, SequenceNode
from yaml.constructor import Constructo... |
# coding=utf-8
import time, json, io, datetime, argparse
item_type = ('EVENT', 'INFO', 'AD')
categories = ('pregon', 'music', 'food', 'sport', 'art', 'fire', 'band')
places = {
'Alameda':(41.903501, -8.866704),
'Auditorio de San Bieito':(41.899915, -8.873203),
'A Cruzada':(41.897817, -8.874520),
'As... |
import argparse
import csv
import os
import pickle
import sys
from pathlib import Path
from typing import List, Optional, Tuple, Union
import rdkit
from rdkit import Chem
from rdkit.Chem import rdChemReactions
from tqdm import tqdm
def canonicalize_products(rxn_smi: str) -> str:
'''
Adapted from RetroXpert's ... |
# Copyright 2019 The Forte Authors. All Rights Reserved.
#
# 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 ... |
# -*- coding: utf-8 -*-
u"""
Copyright 2016 Telefónica Investigación y Desarrollo, S.A.U.
This file is part of Toolium.
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/lic... |
from dataclasses import dataclass
import glob
import json
import os
import random
from collections import defaultdict
from statistics import mean
from typing import Dict, List, Union
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib
from node_utils import node_divergence
DOMAIN_ROOT = os.... |
# Created By: <NAME>
# Created On: 2010-11-14
# Copyright 2013 Hardcoded Software (http://www.hardcoded.net)
#
# This software is licensed under the "BSD" License as described in the "LICENSE" file,
# which should be included with this package. The terms are also available at
# http://www.hardcoded.net/licenses/bsd_... |
"""
Input/output routines.
TODO: Logging
"""
import sys
import warnings
import os
import numpy as np
import torch
import pyevtk.hl as vtk
__all__ = [
"write_image", "write_vtk", "VTKReporter", "ObservableReporter", "ErrorReporter"
]
def write_image(filename, array2d):
from matplotlib import pyplot as plt
... |
from rich.color import (
blend_rgb,
parse_rgb_hex,
Color,
ColorParseError,
ColorSystem,
ColorType,
ColorTriplet,
)
from rich import terminal_theme
import pytest
def test_str() -> None:
assert str(Color.parse("red")) == "\x1b[31m⬤ \x1b[0m<color 'red' (standard)>"
def test_repr() ->... |
import pandas as pd
import time
from os import listdir
from os.path import isfile, join
import numpy as np
import sys
'''Main function running all data integration'''
def dataset_integration(iPath_samples,ifile_mirConfidence, i_confidence, ifile_metadata, ls_conditions, ofile_RC_dataset, ofile_RP... |
# -*- coding: utf-8 -*-
"""Main module."""
"""
1. Plug four of your male to female jumper wires into the pins on the HC-SR04 as follows:
Red; Vcc, Blue; GPIO_TRIGGER, Yellow; GPIO_ECHO and Black; GND.
2. Plug Vcc into the positive rail of your breadboard, and plug GND into your negative rail.
3. Plug GPIO 5V [Pin... |
from enum import IntEnum
from .. import WoWVersionManager, WoWVersions
__reload_order_index__ = -1
class ADTChunkFlags(IntEnum):
HAS_MCSH = 0b1 << 0
IMPASS = 0b1 << 1
LQ_RIVER = 0b1 << 2
LQ_OCEAN = 0b1 << 3
LQ_MAGMA = 0b1 << 4
LQ_SLIME = 0b1 << 5
HAS_MCCV = 0b1 << 6
UNKNOWN = 0b1 <<... |
# Module of class Module (Quantum Gates)
import numpy as np
import copy
class Module(object):
def __init__(self, name, n, ind_modules=[]):
# initialize
self.name = name
self.n = n
self.sub_modules = []
self.reg_indices = []
self.typical = False
self.matrix_o... |
from keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard, LearningRateScheduler
from keras.layers import Reshape, Dense, Convolution1D, Dropout, Input, Activation, Flatten,MaxPool1D,add, AveragePooling1D, Bidirectional,GRU,LSTM,Multiply, MaxPooling1D,TimeDistributed,AvgPool1D
from keras.layers.merge impo... |
import tensorflow as tf
from bvlc_alexnet_fc7 import AlexNet
import utility_function as uf
import fine_tune_nt
import numpy as np
import os
import time
import cv2
import image_io
import sys
# the dimension of the final layer = feature dim
NN_DIM = 100
LABEL_DIM = 4
TEST_TXT = 'file_list_fine_tune_test.txt'
# TEST_TXT... |
from pkgcore.ebuild import eclass
from snakeoil.osutils import pjoin
from snakeoil.test import TestCase
from snakeoil.test.mixins import TempDirMixin
class FakeEclass:
def __init__(self, path, contents):
self.path = path
with open(path, 'w') as f:
f.write(contents)
class FakeEclassCa... |
#!/usr/bin/env python
# encoding: utf-8
# andersg at 0x63.nu 2007
# <NAME> 2016 (ita)
"""
Support for Perl extensions. A C/C++ compiler is required::
def options(opt):
opt.load('compiler_c perl')
def configure(conf):
conf.load('compiler_c perl')
conf.check_perl_version((5,6,0))
conf.check_perl_ext_devel()
... |
import re
import numpy as np
import numpy.linalg as la
import codecs
from MdlUtilities import Field, FieldList
import MdlUtilities as mdl
import dbUtils
def get_lengthUnits():
query = 'select u.representation from units u, quantities q where u.quantityID=q.quantityID and q.quantityName="length"'
items ... |
import warnings
from operator import itemgetter
from collections import defaultdict
from mhfp.encoder import MHFPEncoder
# Adapted from:
# https://github.com/ekzhu/datasketch/blob/master/datasketch/lshforest.py
class LSHForestHelper():
"""A class simplyfing the use of the LSH Forest implementation. Adding paramte... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
# STDLIB
import json
import os
# THIRD PARTY
import pytest
# LOCAL
import astropy.units as u
from astropy.cosmology import units as cu
from astropy.cosmology.connect import readwrite_registry
from astropy.cosmology.core import _COSMOLOGY_CLASSES, Cosmol... |
#!/usr/bin/env python3
## Author: <NAME>
## Version: 0.0.1
## Date: 19 July 2018
## Title: Mail to MISP
## Description: monitors a give email address for forwarded messages, scrapes IOCs from them and creates an event in MISP with those IOC.
## don't forget to set-up config.py with your email and MISP details... |
from weakref import WeakValueDictionary
from param.parameterized import add_metaclass
from ...streams import (
Stream, Selection1D, RangeXY, RangeX, RangeY, BoundsXY, BoundsX, BoundsY,
SelectionXY
)
from .util import _trace_to_subplot
class PlotlyCallbackMetaClass(type):
"""
Metaclass for PlotlyCal... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import sys
import numpy as np
import pytest
from . import database
from . import evaluator
from . import algorithm
from . import run
from . import preprocessor
import logging
model = None
train_data, train_labels, test_data, test_labels = None, None, None, None... |
from PyQt5 import QtWidgets, QtGui, QtCore, Qt
from PyQt5.QtCore import pyqtSignal
from copper import hou
from copper.core.engine import signals as engine_signals
from copper.core.op.op_node import OP_Node
from copper.ui.signals import signals
from copper.ui.widgets import PathBarWidget
from .base_panel import PathBa... |
from otree.api import (
models, widgets, BaseConstants, BaseSubsession, BaseGroup, BasePlayer,
Currency as c, currency_range
)
author = '<NAME> & <NAME>'
doc = """
Hace falta generar la documentacion de la rubrica
"""
class Constants(BaseConstants):
name_in_url = 'debatespb'
players_... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Visitor to replace the invocations to functions that have been removed with the controlled function
generation functionality (i.e., ``-f`` or ``--functions`` options)."""
from functools import singledispatch
from core import ast, generators, probs
from params.parameter... |
import torch
import torch.nn as nn
from nn_ood.data.simple_reg import Cubic
from nn_ood.posteriors import LocalEnsemble, SCOD, Ensemble, Naive, KFAC
from scod.distributions import Normal
import numpy as np
import matplotlib.pyplot as plt
# WHERE TO SAVE THE MODEL
FILENAME = "model"
## HYPERPARAMS
N_MODELS = 3
L... |
# Copyright 2018 Google Inc. All Rights Reserved.
#
# 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 a... |
# coding=utf-8
# Copyright 2013 Foursquare Labs Inc. All Rights Reserved.
from __future__ import absolute_import, division, print_function
from hashlib import sha1
import os
import textwrap
from pants.base.exceptions import TaskError
from pants.base.fingerprint_strategy import FingerprintStrategy
from pants.task.tas... |
import click
import torch
import numpy as np
from model import BOS, EOS, CharTokenizer, CharLSTM
from constants import MAX_LEN
STOP_LIST = [EOS, " "] + list('!"#$%&()*+,-./:;<=>?@[\\]^_{|}~')
CUDA = "cuda"
CPU = "cpu"
@click.group()
def main():
pass
def to_matrix(names, tokenizer, max_len=None, dtype='int32',... |
# Copyright 2008-2015 Nokia Networks
# Copyright 2016- Robot Framework Foundation
#
# 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
... |
import torch
import torch.nn as nn
import torch.nn.functional as F
from glow.glow.act_norm import ActNorm
from glow.glow.coupling import Coupling
from glow.glow.inv_conv import InvConv
class Glow(nn.Module):
def __init__(self, in_channels, cond_channels, num_channels, num_levels, num_steps, mode='sketch'):
... |
import collections
import os
import random
import tarfile
import torch
from torch import nn
import torchtext.vocab as Vocab
import torch.utils.data as Data
import utils
import torch.nn.functional as F
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# 数据集下载地址 http://ai.stanford.edu/~amaas/data/se... |
"""
Implementation of Sentinel Hub Process API interface
"""
from .constants import MimeType, RequestType
from .download import DownloadRequest
from .data_collections import OrbitDirection
from .data_request import DataRequest
from .geometry import Geometry, BBox
from .sh_utils import _update_other_args
from .time_util... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import torch
from multi_passage_model import SequenceClassification
import tokenization
class InputExample(object):
"""A single training/test example for simple sequence ... |
#import In.entity
class Room(In.entity.Entity):
'''Room Entity class.
'''
def __init__(self, data = None, items = None, **args):
self.members = []
super().__init__(data, items, **args)
def get_title(self, from_nabar_id):
# TODO: CACHE IT
if self.title:
return self.title
if self.type ... |
import numpy
import numpy as np
import os
import matplotlib.pyplot as plt
from tqdm import tqdm
import gym
import dmc2gym
def create_env(domain_name, task_name, seed, dmc):
if dmc:
env = dmc2gym.make(domain_name=domain_name, task_name=task_name, seed=seed)
else:
env = gym.make(domain_name)
env.seed(seed)
ret... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright (c) 2015 <NAME> <<EMAIL>> (@amimof)
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
DOCUMENTATION = """
module: profile_dmgr
version_added: "1.9.4"
short_description: Manage a WebSphere Application Server profi... |
import sys
import os
import os.path
from lxml import etree
import collections
def create_folder(filepath):
directory = os.path.dirname(filepath)
if not os.path.exists(directory):
os.makedirs(directory)
def check_entry_dict(event_tokens, d):
if event_tokens in d:
return " ".join(d[even... |
import os
import tensorflow as tf
from baseline.confusion import ConfusionMatrix
from baseline.progress import create_progress_bar
from baseline.reporting import basic_reporting
from baseline.utils import listify, get_model_file
from baseline.tf.tfy import optimizer, _add_ema
from baseline.train import EpochReportingTr... |
# Copyright 2021 The TensorFlow Probability Authors.
#
# 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 o... |
'''
The MIT License (MIT)
Copyright (c) 2017 <NAME>
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, publi... |
from __future__ import unicode_literals
import logging
from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from paramiko.hostkeys import HostKeyEntry
import paramiko
from reviewboard.ssh.errors import UnsupportedSSHKeyError
class SSHHostKeys(paramiko.HostKeys):
"""Manages k... |
import csv
import itertools
import sys
from functools import reduce
PROBS = {
# Unconditional probabilities for having gene
"gene": {
2: 0.01,
1: 0.03,
0: 0.96
},
"trait": {
# Probability of trait given two copies of gene
2: {
True: 0.65,
... |
'''
Copyright 2022 Airbus SAS
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
dis... |
import os
import requests as re
from flask import Flask, jsonify, request, redirect, url_for,session
from flask_cors import CORS
import json
import six
import pandas as pd
from math import sqrt
from werkzeug import secure_filename
UPLOAD_FOLDER = 'tmp'
ALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg'])
app = Flask(__n... |
import torch
import torch.nn as nn
class segnetDown2(nn.Module):
def __init__(self, in_size, out_size):
super(segnetDown2, self).__init__()
self.conv1 = conv2DBatchNormRelu(in_size, out_size, 3, 1, 1)
self.conv2 = conv2DBatchNormRelu(out_size, out_size, 3, 1, 1)
self.maxpool_with_ar... |
import numpy as np
import scipy.optimize
import scipy.stats
def build_utm_matrix(results, case, n, additional_param=None):
j = -1
matrix = np.zeros((5, 5))
matrix_n = np.zeros((5, 5))
alternatives = []
for simulation_type in results:
for algo_type in results[simulation_type]:
i... |
from __future__ import absolute_import, division, print_function
import base64
import time
import gym
import imageio
import IPython
import matplotlib
import matplotlib.pyplot as plt
import PIL.Image
# import pyvirtualdisplay
import tensorflow as tf
from tf_agents.agents.dqn import dqn_agent
from tf_agents.drivers im... |
# Copyright 2017 The 'Scalable Private Learning with PATE' Authors All Rights Reserved.
#
# 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
#
# ... |
from __future__ import absolute_import, unicode_literals
import logging
from django.core.urlresolvers import reverse
from django.http import JsonResponse
from django.utils.translation import ugettext_lazy as _
from django.shortcuts import redirect, get_object_or_404
from dash.orgs.views import OrgPermsMixin
from dash... |
#!/usr/bin/env python
#
# Copyright 2016 Google Inc. All Rights Reserved.
#
# 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 require... |
import sys
from django.db import models
from django.db.models import ForeignKey, OneToOneField, ManyToManyField
from django.db.models.fields.related import ForeignObjectRel as RelatedObject
# taking a nod from python-requests and skipping six
_ver = sys.version_info
is_py2 = (_ver[0] == 2)
is_py3 = (_ver[0] == 3)
bas... |
"""
Wisconsin Autonomous - https://www.wisconsinautonomous.org
Copyright (c) 2021 wisconsinautonomous.org
All rights reserved.
Use of this source code is governed by a BSD-style license that can be found
in the LICENSE file at the top level of the repo
"""
# ----------------------
# Data loading utilities
# --------... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.