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the-stack_0_9857 | # Copyright (c) 2013 Pratik Kumar Sahu, Nagendra Chowdary, Anish Mathuria
# Ported to Python by Gallopsled
from __future__ import division
import os
import random
import struct
# +------------------------------------------------------------------------+
# | RANDOM NUMBERS FUNCTIONS ... |
the-stack_0_9858 | """
Interfaces to various optimizers.
"""
from __future__ import print_function, division
import sys
from copy import copy
import warnings
# CRUFT: time.clock() removed from python 3.8
try:
from time import perf_counter
except ImportError:
from time import clock as perf_counter
import numpy as np
from . imp... |
the-stack_0_9859 | #
# Copyright 2020 IBM Corp. 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... |
the-stack_0_9862 | # -*- coding: utf-8 -*-
"""
flask_jsondash.db
~~~~~~~~~~~~~~~~~~~~~~~~~~
A translation adapter for transparent operations between storage types.
:copyright: (c) 2016 by Chris Tabor.
:license: MIT, see LICENSE for more details.
"""
import json
from datetime import datetime as dt
from pymongo import MongoClient
fro... |
the-stack_0_9863 | from django.urls import path
from .views import BookmarkDetail, BookmarkDelete, BookmarkCreate, BookmarkUpdate, BookmarkList
# namespace = 이름 공간
# 다른 앱들과 url pattern 이름이 겹치는 것을 방지하기 위해서 사용
# 2.x버전 이전에는 namespace라는 인수가 존재
app_name = 'bookmark'
urlpatterns = [
# 함수형 뷰 : 이름만 쓴다
# 클래스형 뷰 : 이름.as_view()
path('... |
the-stack_0_9866 | # Colorama module: pip install colorama
from colorama import init, Fore, Style
# Selenium module imports: pip install selenium
from selenium import webdriver
from selenium.common.exceptions import TimeoutException as TE
from selenium.common.exceptions import ElementClickInterceptedException as ECIE
from selenium.webdr... |
the-stack_0_9867 | # -*- coding: utf-8 -*-
# Copyright (c) 2016-2022 by University of Kassel and Fraunhofer Institute for Energy Economics
# and Energy System Technology (IEE), Kassel. All rights reserved.
import os
import numpy as np
from pandapower.auxiliary import ppException
try:
import pplog as logging
except I... |
the-stack_0_9868 | #!/usr/bin/env python
# _*_ coding: utf-8 _*_
from setuptools import setup, find_packages
import os
import imp
def non_python_files(path):
""" Return all non-python-file filenames in path """
result = []
all_results = []
module_suffixes = [info[0] for info in imp.get_suffixes()]
ignore_dirs = ['cvs... |
the-stack_0_9872 | import json
import boto3
import sys
from datetime import datetime
from decimal import Decimal
from boto3.dynamodb.conditions import Key, Attr
import logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)
today=datetime.today()
curyear=today.year
curmonth=today.month
curday=today.day
start_of_day = int(date... |
the-stack_0_9873 | #
# @lc app=leetcode.cn id=946 lang=python3
#
# [946] 验证栈序列
#
from typing import List
class Solution:
# 模拟思路即可
def validateStackSequences(self, pushed: List[int], popped: List[int]) -> bool:
try:
if len(pushed) == 0 or len(pushed) == 1:
return True
# 模拟的栈
... |
the-stack_0_9875 | import json
from flask import Response
from flask import Blueprint
from flask import request
from financespy import Transaction
from financespy import parse_month
from datetime import date
def month_weeks(backend, year, month):
return [
[trans.to_dict() for trans in week.records()]
for week in bac... |
the-stack_0_9877 | """Mock documents, used for integration testing."""
from dataclasses import dataclass, replace
from itertools import chain
from pathlib import Path
from typing import List, Optional, Sequence, Tuple
from bp.document import Document
from bp.entity import Page
from bp.build_document import InputPage, build_document
fro... |
the-stack_0_9880 | import numpy as np
import torch
from torch.utils.data import Dataset, TensorDataset, DataLoader
from sklearn.utils import shuffle
class SequenceBucketCollator():
def __init__(self, choose_length, maxlen, sequence_index, length_index, label_index=None):
self.choose_length = choose_length
self.seque... |
the-stack_0_9881 | # Copyright 2020 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
the-stack_0_9883 | #!/usr/bin/env python
import vtk
from vtk.test import Testing
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()
# create a rendering window and renderer
ren1 = vtk.vtkRenderer()
ren1.SetBackground(0,0,0)
renWin = vtk.vtkRenderWindow()
renWin.AddRenderer(ren1)
renWin.SetSize(300,300)
... |
the-stack_0_9884 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Collection of tests for :mod:`orion.core.worker.consumer`."""
import logging
import os
import shutil
import signal
import subprocess
import tempfile
import time
import pytest
import orion.core.io.experiment_builder as experiment_builder
import orion.core.io.resolve_con... |
the-stack_0_9885 | #!/usr/bin/env python
import json
from run_tests_stats import execute
import optparse
import os
import subprocess
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
def parseresults(log_file, plot_data, t, duration):
fp = open(log_file).readlines()
i = 0
plot_data[t] = {}
plot_dat... |
the-stack_0_9892 | # coding:utf-8
# 2019/9/21
import sys
sys.path.append(r"C:\Study\github\Lookoops\MachineLearning\TensorFlow\image-clssifier")
import logging
import pickle
import os
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
from keras import backend as K
import numpy as np
import tensorflow a... |
the-stack_0_9893 | # Copyright 2019 Google LLC
#
# 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, ... |
the-stack_0_9894 | """
Copyright 2020 The OneFlow 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 law or agr... |
the-stack_0_9895 | """Binary classes"""
import binascii
import gzip
import io
import json
import logging
import os
import shutil
import struct
import subprocess
import sys
import tarfile
import tempfile
import zipfile
from json import dumps
from typing import Optional
import h5py
import numpy as np
import pysam
import pysam.bcftools
fr... |
the-stack_0_9897 | import os
import sfepy
from sfepy.base.base import load_classes, insert_static_method
from solvers import *
from eigen import eig
solver_files = sfepy.get_paths('sfepy/solvers/*.py')
remove = ['setup.py', 'solvers.py', 'petsc_worker.py']
solver_files = [name for name in solver_files
if os.path.basename... |
the-stack_0_9898 | import datetime
import os
from cryptography.x509.oid import NameOID
from cryptography.hazmat.primitives.serialization import Encoding
from .logger import logger
class StorageEngineCertificateConflict(Exception):
"""
Raise when a StorageEngine implementation is asked to persist a certificate
with a seria... |
the-stack_0_9899 | import datetime
from docxtpl import DocxTemplate
from docxtpl import InlineImage
from docx.shared import Cm
from docxtpl import DocxTemplate, InlineImage
def get_context(brand, model, fuel_consumption, price):
return {
'brand': brand,
'model': model,
'fuel_consumption': fuel_consumption,
... |
the-stack_0_9901 | """
Python 3.9 функция для запуска процесса обучения нейронной сети
Название файла train_c4.py
Version: 0.1
Author: Andrej Marinchenko
Date: 2021-12-20
"""
#!/usr/bin/env python
from alpha_net_c4 import ConnectNet, AlphaLoss, board_data
import os
import pickle
import datetime
import numpy as np
import torch
import to... |
the-stack_0_9902 | import unittest
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal
from pyrolite.util.plot.density import (
percentile_contour_values_from_meshz,
plot_Z_percentiles,
)
from pyrolite.util.plot.legend import proxy_line
from matplotlib.lines import _get_dash_pat... |
the-stack_0_9904 | import numpy as np # linear algebra
import skimage.io
import os
import sys
np.random.seed(1234)
import scipy.misc
import skimage.morphology as mph
from skimage import color
dd = sys.argv[1]
STAGE1_TRAIN = "../inputs/"+dd
STAGE1_TRAIN_IMAGE_PATTERN = "%s/{}/images/{}.png" % STAGE1_TRAIN
STAGE1_TRAIN_MASK_PATTERN = "%s... |
the-stack_0_9905 | # @Time : 12/07/21 1:05 PM
# @Author : Fabrice Harel-Canada
# @File : rick_and_morty_stories.py
import torch
from transformers import pipeline, set_seed
from transformers.pipelines import TextGenerationPipeline
class RickAndMortyStories:
def __init__(self, mask_bad_words=True):
self.pipeline = pipe... |
the-stack_0_9906 | # NASBench 301 stuff here
import sys
from pathlib import Path
sys.path.append('./darts/cnn')
lib_dir = (Path(__file__).parent / 'darts' / 'cnn').resolve()
if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
import genotypes
from model_search import Network, NetworkNB
import utils
import time
import math... |
the-stack_0_9907 | # -*- coding: utf-8 -*-
"""DNACenterAPI non_fabric_wireless API fixtures and tests.
Copyright (c) 2019-2020 Cisco and/or its affiliates.
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 re... |
the-stack_0_9908 | # coding=utf-8
from __future__ import absolute_import, print_function
import os
import numpy as np
from suanpan.app import app
from suanpan.storage import storage
from suanpan.utils import image
from arguments import Images
@app.input(Images(key="inputImage"))
@app.output(Images(key="outputImage"))
def SPRemoveWater... |
the-stack_0_9909 | #!/usr/bin/env python3
"""
Prompt:
Loop through all numbers from 1 to 100. If the number is divisible by 3, print
out "Fizz" instead. If the number is divisible by 5, print out "Buzz" instead.
"""
from typing import Iterable
from typing import Union
def fizz_buzz(n: int) -> Iterable[Union[int, str]]:
for i in ran... |
the-stack_0_9910 | from gi.repository import Gtk, Gdk
css = """
#top GtkComboBox {
background-color: #000000;
}
GtkWindow {
color: black;
background: black;
background-color: black;
}
GtkComboBox {
color: black;
background: black;
background-color: black;
}
"""
class ComboBoxWindow(Gtk.Window):
def __i... |
the-stack_0_9913 | # Copyright 2013-2019 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
import os
class Templight(CMakePackage):
"""Templight is a Clang-based tool to profile the time ... |
the-stack_0_9916 | from __future__ import print_function, division
import sys, os
sys.path.append(os.path.abspath("."))
from problems.problem import *
from helper.pom3 import pom3
__author__ = 'panzer'
class POM3BSansComp(Problem):
"""
POM 3B without Completion
"""
def __init__(self):
Problem.__init__(self)
self.name = ... |
the-stack_0_9918 | def dobro(num, formatado=False):
if formatado:
return f'R${num * 2:.2f}'
else:
return num * 2
def metade(num, formatado=False):
if formatado:
return f'R${num / 2:.2f}'
else:
return num / 2
def adicionar(num, index, formatado=False):
if formatado:
return f'... |
the-stack_0_9920 | # Copyright (c) 2019 PaddlePaddle 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 app... |
the-stack_0_9925 | # Django settings for demo project.
import os
settings_path, settings_module = os.path.split(__file__)
import sys
sys.path.append('../../')
DEBUG = True
#TEMPLATE_DEBUG = DEBUG
USE_TZ=True
#TIME_ZONE = 'America/Chicago'
LANGUAGE_CODE = 'en-us'
SECRET_KEY = '8(o*lht586wqr9hp5env&n!h!gu@t5g4*$$uupbyd*f+61!xjh'
TE... |
the-stack_0_9931 | import fire
import os
import tensorflow as tf
import matplotlib.pyplot as plt
import os
import time
import datetime
from dcgan.discriminator import make_discriminator_model, discriminator_loss
from dcgan.generator import make_generator_model, generator_loss
from dcgan.dataset import make_dataset
from dcgan.utils imp... |
the-stack_0_9932 | # -*- coding: utf-8 -*-
import logging
import re
from urllib.parse import quote_plus
from requests.exceptions import RequestException
from flexget import plugin
from flexget.components.sites.utils import normalize_scene, torrent_availability
from flexget.config_schema import one_or_more
from flexget.entry import Entr... |
the-stack_0_9933 | """Progress bars for SDGym compatible with logging and dask."""
import io
import logging
from datetime import datetime, timedelta
LOGGER = logging.getLogger(__name__)
class TqdmLogger(io.StringIO):
_buffer = ''
def write(self, buf):
self._buffer = buf.strip('\r\n\t ')
def flush(self):
... |
the-stack_0_9935 | import pickle
import itertools
import os
import math
from sklearn.preprocessing import normalize
import re
from operator import add
import matplotlib.pyplot as plt
#%matplotlib inline
import numpy as np
import argparse
import pylab as pl
import random
def str2bool(v):
if v.lower() in ('yes', 'true', 't', 'y', '1')... |
the-stack_0_9937 | #
# This is Seisflows
#
# See LICENCE file
#
###############################################################################
# Import system modules
import system
import subprocess
from glob import glob
from os.path import join
import sys
# Import Numpy
import numpy as np
# Local imports
import seisflows.plugins.sol... |
the-stack_0_9938 | """
DataFrame
---------
An efficient 2D container for potentially mixed-type time series or other
labeled data series.
Similar to its R counterpart, data.frame, except providing automatic data
alignment and a host of useful data manipulation methods having to do with the
labeling information
"""
import collections
fro... |
the-stack_0_9939 | # Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors
# MIT License. See license.txt
from __future__ import unicode_literals, print_function
import frappe
import unittest, json, sys, os
import xmlrunner
import importlib
from frappe.modules import load_doctype_module, get_module_name
from frappe.utils i... |
the-stack_0_9941 | """Functions for converting between color spaces.
The "central" color space in this module is RGB, more specifically the linear
sRGB color space using D65 as a white-point [1]_. This represents a
standard monitor (w/o gamma correction). For a good FAQ on color spaces see
[2]_.
The API consists of functions to conver... |
the-stack_0_9942 |
# Code from Chapter 7 of Machine Learning: An Algorithmic Perspective
# by Stephen Marsland (http://seat.massey.ac.nz/personal/s.r.marsland/MLBook.html)
# You are free to use, change, or redistribute the code in any way you wish for
# non-commercial purposes, but please maintain the name of the original author.
# Thi... |
the-stack_0_9943 | import typing
import inspect
import functools
from base64 import b64decode
from types import FunctionType
import httpx
from rpcpy.serializers import BaseSerializer, JSONSerializer
from rpcpy.utils.openapi import set_type_model
__all__ = ["Client"]
Function = typing.TypeVar("Function", bound=FunctionType)
class Cl... |
the-stack_0_9944 | """
Expressions
-----------
Offer fast expression evaluation through numexpr
"""
import warnings
import numpy as np
from pandas._config import get_option
from pandas._libs.lib import values_from_object
from pandas.core.dtypes.generic import ABCDataFrame
from pandas.core.computation.check import _NUMEXPR_INSTALL... |
the-stack_0_9945 | from __future__ import with_statement
from time import time
from fabric.api import cd, run, env, roles
from fabric.decorators import task
from fabric.contrib.files import exists
env.use_ssh_config = True
releases_dir = "/home/deploy/issadmin/releases"
git_branch = "master"
git_repo = "https://github.com/wgerez/iss-... |
the-stack_0_9947 | # Copyright (c) 2018 PaddlePaddle 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 app... |
the-stack_0_9948 | """Utilities for calculating and reporting statistics about types."""
import cgi
import os.path
import re
from typing import Any, Dict, List, cast, Tuple
from mypy.traverser import TraverserVisitor
from mypy.types import (
Type, AnyType, Instance, FunctionLike, TupleType, Void, TypeVarType,
TypeQuery, ANY_TY... |
the-stack_0_9949 | #025: Crie um programa que leia o nome de uma pessoa e diga se ela tem "SILVA" no nome.
nome = str(input('Escreva seu nome: '))
nome = nome.title()
nome = nome.strip()
nomeA = nome.split()
if ('Silva' in nome):
print('Seu nome tem Silva!')
else:
print('Seu nome não tem Silva!')
|
the-stack_0_9950 | """String functions in R"""
import re
import numpy as np
from pipda import register_func
from ..core.backends import pandas as pd
from ..core.backends.pandas import Series
from ..core.backends.pandas.core.base import PandasObject
from ..core.backends.pandas.core.groupby import SeriesGroupBy
from ..core.backends.panda... |
the-stack_0_9952 | #!/usr/bin/env python
"""Basic pipeline building blocks.
This modules provides the basic building blocks in a JIP pipeline and a way
to search and find them at run-time. The basic buiding blocks are instances
of :py:class:`Tool`. The JIP library comes with two sub-classes that can be
used to create tool implementation... |
the-stack_0_9954 | """Gitlab service support.
API docs: https://docs.gitlab.com/ee/api/
"""
from dateutil.parser import parse as parsetime
from snakeoil.klass import aliased, alias
from urllib.parse import urlparse, urlunparse, quote_plus
from ._jsonrest import JsonREST
from ..exceptions import RequestError, BiteError
from ..objects i... |
the-stack_0_9955 | # pylint: disable=wildcard-import, unused-wildcard-import
"""Model store which handles pretrained models from both
mxnet.gluon.model_zoo.vision and gluoncv.models
"""
from mxnet import gluon
from .ssd import *
from .faster_rcnn import *
from .fcn import *
from .pspnet import *
from .cifarresnet import *
from .cifarresn... |
the-stack_0_9957 | from functools import wraps
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.losses import (
BinaryCrossentropy,
CategoricalCrossentropy,
MeanAbsoluteError,
MeanSquaredError,
)
def distributed_sum_over_batch_size(batch_size: int):
def _distributed_sum_over_batch_size(fun... |
the-stack_0_9958 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# Download and build the data if it does not exist.
import parlai.core.build_data as build_data
import gzip
imp... |
the-stack_0_9959 | import itertools as it, operator as op, functools as ft
from xml.sax.saxutils import escape as xml_escape
import html.parser, html.entities
import os, re, collections as cs, urllib.request as ulr
import gi
gi.require_version('Gtk', '3.0')
gi.require_version('Gdk', '3.0')
from gi.repository import Gtk, Gdk, GdkPixbuf, ... |
the-stack_0_9960 | # =============================================================================
# PROJECT CHRONO - http://projectchrono.org
#
# Copyright (c) 2021 projectchrono.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 distr... |
the-stack_0_9962 | from django import forms
from .models import Comment, Review
class ReviewForm(forms.ModelForm):
class Meta:
model = Review
fields = ('rating', 'experience', 'description')
def clean_rating(self):
data = self.cleaned_data['rating']
if not data >= 1 and data <= 5:
r... |
the-stack_0_9964 | # Read file, create an array of its values after removing the \n from each line
with open('input') as file:
values = file.readlines()
values = [int(value[:len(value)-1]) for value in values]
# PART 1:
# Create a hashmap of every value's complements to reach 2020.
# When you encounter that complement in the fut... |
the-stack_0_9965 | #!/usr/bin/env python
from __future__ import division
from __future__ import print_function
# from keras.layers.merge import Concatenate, Add, Dot, Multiply
import glob
import os
import zipfile
import keras
import numpy as np
import tensorflow as tf
from PIL import Image
from keras import backend as K
from sklearn.me... |
the-stack_0_9967 | from statement import Statement
def main():
feature = "project_creation"
with open(f"./features/{feature}.feature", "r") as file, open(f"{feature}.steps.ts", "w") as outfile:
outfile.write('import { Given, When, Then, TableDefinition } from "cucumber";\n\n\n')
antecessors = []
previous... |
the-stack_0_9968 | from utils import detector_utils as detector_utils
import cv2
import tensorflow as tf
import multiprocessing
from multiprocessing import Queue, Pool
import time
from utils.detector_utils import WebcamVideoStream
import datetime
import argparse
frame_processed = 0
score_thresh = 0.2
# Create a worker thread that loa... |
the-stack_0_9971 | from sqlalchemy import *
from migrate import *
from migrate.changeset import schema
pre_meta = MetaData()
post_meta = MetaData()
collections = Table('collections', pre_meta,
Column('id', INTEGER, primary_key=True, nullable=False),
Column('user_id', INTEGER),
Column('collection_id', INTEGER),
)
users = Ta... |
the-stack_0_9972 | ###############################
#
# Created by Patrik Valkovic
# 3/9/2021
#
###############################
import unittest
import ffeat
class EachArgTest(unittest.TestCase):
def test_oneparam(self):
p = ffeat.flow.EachArg(lambda x: x + 1)
result, kargs = p(8)
self.assertSequenceEqual(resu... |
the-stack_0_9975 | import tensorflow as tf
import os
from niftynet.application.base_application import BaseApplication
from niftynet.engine.application_factory import \
ApplicationNetFactory, InitializerFactory, OptimiserFactory
from niftynet.engine.application_variables import \
CONSOLE, NETWORK_OUTPUT, TF_SUMMARIES
from niftyn... |
the-stack_0_9978 | from __future__ import annotations
from typing import Optional, TYPE_CHECKING
from components.base_component import BaseComponent
from equipment_types import EquipmentType
if TYPE_CHECKING:
from entity import Actor, Item
class Equipment(BaseComponent):
parent: Actor
def __init__(self, weapon: Optional... |
the-stack_0_9979 | #!/usr/bin/env python3
import ecc_ed25519
import sys, getopt
from cryptography.hazmat.primitives.asymmetric import ed25519
msg = ""
public_key_hex = ""
encoded_signature = ""
try:
opts, args = getopt.getopt(sys.argv[1:],"hm:k:s:",["message=","publickeyhex=", "signature="])
except getopt.GetoptError:
print('v... |
the-stack_0_9981 | from django.shortcuts import redirect
from django.http import HttpResponse
from .models import Link
def index(request):
return HttpResponse("Hello, world. You're at the polls index.")
def openLink(request, temp):
redirectLink = Link.objects.get(name=temp)
link = redirectLink.redirect
print(link)
... |
the-stack_0_9983 | import gym
from gym import spaces
import numpy as np
# from os import path
import snakeoil3_gym as snakeoil3
import numpy as np
import copy
import collections as col
import os
import time
import sys
class TorcsEnv:
terminal_judge_start = 50 #1000 # If after 100 timestep still no progress, terminated
terminat... |
the-stack_0_9985 | # -*- coding: utf-8 -*-
'''
:codeauthor: :email:`Pedro Algarvio (pedro@algarvio.me)`
:copyright: © 2012-2013 by the SaltStack Team, see AUTHORS for more details
:license: Apache 2.0, see LICENSE for more details.
tests.integration.shell.call
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
'''
# Import python libs
i... |
the-stack_0_9986 | # Copyright (c) 2019-2021 CRS4
#
# 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, distribut... |
the-stack_0_9987 | import os
from torchnlp.download import download_file_maybe_extract
def wmt_dataset(directory='data/wmt16_en_de',
train=False,
dev=False,
test=False,
train_filename='train.tok.clean.bpe.32000',
dev_filename='newstest2013.tok.bpe.32000',
... |
the-stack_0_9991 | import sys
import gym.spaces
import itertools
import numpy as np
import random
import tensorflow as tf
import tensorflow.contrib.layers as layers
from collections import namedtuple
from dqn_utils import *
OptimizerSpec = namedtuple("OptimizerSpec", ["constructor", "kwargs", "lr_schedule"])
def learn(en... |
the-stack_0_9992 | # -*- coding: utf-8 -*-
"""
Module with logic for the Environment sub-process
"""
__author__ = 'Samir Adrik'
__email__ = 'samir.adrik@gmail.com'
from source.util import Assertor, Tracking, Debugger
from .finn_environment_process import FinnEnvironmentProcess
from .engine import SubModel
class FinnEnvironmentSubMo... |
the-stack_0_9993 | # Copyright 2013 OpenStack Foundation
# 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 requ... |
the-stack_0_9994 |
import sys
import inspect
from scenic import scenarioFromString
from scenic.core.simulators import DummySimulator, RejectSimulationException
import scenic.syntax.veneer as veneer
## Scene generation utilities
# Compilation
def compileScenic(code, removeIndentation=True, scenario=None):
if removeIndentation:
... |
the-stack_0_9995 | # Created by Ilia
# https://www.tensorflow.org/tutorials/keras/regression#the_auto_mpg_dataset
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras.layers.experimental import preprocessing
... |
the-stack_0_10001 | import base64
import io
import logging
import os
import numpy as np
import torch
from PIL import Image
from torch.autograd import Variable
from torchvision import transforms
logger = logging.getLogger(__name__)
class DIYSegmentation:
"""
DIYSegmentation handler class.
"""
def __init__(self):
... |
the-stack_0_10002 |
import os
from zipfile import ZipFile
bag_of_words = open('spans-pred_charbert.txt', 'r')
charBert = open('40_0.4_spans-pred.txt', 'r').readlines()
zipObj = ZipFile('spans-pred.zip', 'w')
def charList_to_intList(line):
line = line.split('\t')
line = line[1][1:-1].split(' ')
span = []
for elem in line:
if len(el... |
the-stack_0_10003 | # To test a single translator use the -k parameter followed by either
# timescale or crate.
# See https://docs.pytest.org/en/stable/example/parametrize.html
from datetime import datetime
from conftest import crate_translator, timescale_translator
from utils.common import TIME_INDEX_NAME
from utils.tests.common import ... |
the-stack_0_10004 | import random
print("BEM VINDO AO JOGO DO PARA OU IMPAR")
print("--"*15)
vit = 0
while True:
palpite = int(input('Diga um valor entre zero e 9: '))
jogador = ''
while jogador not in ['P', 'I']:
jogador = str(input('Quer Par ou Impar? ')).strip().upper()[0]
jogada = random.choice(['PAR','IMPAR'])... |
the-stack_0_10005 | """The dhcp integration."""
from abc import abstractmethod
from datetime import timedelta
import fnmatch
from ipaddress import ip_address as make_ip_address
import logging
import os
import threading
from aiodiscover import DiscoverHosts
from aiodiscover.discovery import (
HOSTNAME as DISCOVERY_HOSTNAME,
IP_AD... |
the-stack_0_10006 | # -*- coding: utf-8 -*-
"""
Created on Wed Sep 27 15:06:40 2017
@author: Diogo Leite
"""
# here the FK values was selected in lastas positions according to Species_new object class
from DAL import *
from configuration.configuration_data import *
class _Species_sql_new(object):
"""
This class manipulate the ... |
the-stack_0_10008 | # Copyright 2015 Lukas Lalinsky
#
# 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... |
the-stack_0_10009 | import numpy as np
import scipy as sp
from ._model import Model
from ..utils import safe_isinstance, record_import_error
from ..utils.transformers import parse_prefix_suffix_for_tokenizer
from .. import models
from .._serializable import Serializer, Deserializer
try:
import torch
except ImportError as e:
recor... |
the-stack_0_10010 | # Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from __future__ import print_function
import os
import re
import llnl.util.tty as tty
from llnl.util.filesystem import m... |
the-stack_0_10012 | #! /usr/bin/env python
#
# Example program using irc.client.
#
# Copyright (C) 1999-2002 Joel Rosdahl
#
# 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 Licens... |
the-stack_0_10013 | # 5550
# <!*[^<>]*>
# POLYNOMIAL
# nums:4
# POLYNOMIAL AttackString:"<"+"!"*10000+"! _1_POA(i)"
import re
from time import perf_counter
regex = """<!*[^<>]*>"""
REGEX = re.compile(regex)
for i in range(0, 150000):
ATTACK = "<" + "!" * i * 10000 + "! _1_POA(i)"
LEN = len(ATTACK)
BEGIN = perf_counter()
... |
the-stack_0_10014 | #!/usr/bin/env python3
import os
import re
import sys
import urllib.request
from time import strptime
# Regular Expressions
CVE_RE = re.compile('CVE-[0-9]{4}-[0-9]{4,}')
HTML_RE = re.compile('<[^<]+?>')
BOUNTY_RE = re.compile('\[\$([0-9\.]|TBD|N/A)+\]')
BUG_RE = re.compile('\[[0-9]+\]')
DESCRIPTION_RE = re.compile('[... |
the-stack_0_10015 | import unittest
from argparse import ArgumentTypeError
from streamlink.utils.args import (
boolean, comma_list, comma_list_filter, filesize, keyvalue, num
)
class TestUtilsArgs(unittest.TestCase):
def test_boolean_true(self):
self.assertEqual(boolean('1'), True)
self.assertEqual(boolean('on')... |
the-stack_0_10016 | #!/usr/bin/env vpython
#
# Copyright 2018 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import argparse
import collections
import json
import logging
import os
import pipes
import re
import shutil
import signal
import so... |
the-stack_0_10017 | # импортируем специальные поля Алхимии для инициализации полей таблицы
from sqlalchemy import Column, Float, String, Integer
# импортируем модуль инициализации декларативного класса Алхимии
from DB.dbcore import Base
class Client(Base):
__tablename__ = 'clients'
id = Column(Integer, primary_key = True)
ad... |
the-stack_0_10020 | import cv2
import numpy as np
from PIL import Image
def anahtarOlustur(gorsel,gelen):
r, c ,t= gorsel.shape
keyGen = np.random.randint(0, 256, size=(r, c, t ), dtype=np.uint8)
key = np.random.choice(gelen,size=(r, c,t))
mylist = []
for i in key:
arr = np.array(i, dtype=np.uint8)
my... |
the-stack_0_10022 | _base_ = [
'../_base_/models/faster_rcnn_r50_fpn.py', '../_base_/datasets/voc0712.py',
'../_base_/default_runtime.py'
]
model = dict(roi_head=dict(bbox_head=dict(num_classes=20)))
# optimizer
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
... |
the-stack_0_10023 | import torch
from torch import Tensor
from torch.nn import Parameter as Param
from torch_geometric.nn.conv import MessagePassing
from ..inits import uniform
class GatedGraphConv(MessagePassing):
r"""The gated graph convolution operator from the `"Gated Graph Sequence
Neural Networks" <https://arxiv.org/abs/1... |
the-stack_0_10024 | import os
from pathlib import Path
from allennlp.data.iterators import BasicIterator
from allennlp.nn.util import move_to_device
from pytorch_pretrained_bert import BertTokenizer, BertModel, BertAdam
import config
from bert_model_variances.bert_multilayer_output import BertMultiLayerSeqClassification
from data_utils.... |
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