id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
504272 | from .helpers import ResourceBase, IterableResource
from .repos import Repository
from .compat import update_doc
class Repos(ResourceBase, IterableResource):
def __getitem__(self, item):
"""
Return a :class:`Repository` object for operations on a specific repository
"""
return Repository(item, self.u... |
504300 | import json
import hashlib
import mimetypes
import os
import pprint
import uuid
from kinto_http import cli_utils
from kinto_http.exceptions import KintoException
DEFAULT_SERVER = "http://localhost:8888/v1"
def sha256(content):
m = hashlib.sha256()
m.update(content)
return m.hexdigest()
def files_to_up... |
504321 | import random
from typing import List, NamedTuple
from torch.utils.data import DataLoader
from mcp.data.dataset.dataset import Dataset, FewShotDataset, IndexedDataset
class FewShotDataLoader(NamedTuple):
support: DataLoader
query: DataLoader
class FewShotDataLoaderSplits(NamedTuple):
train: DataLoader... |
504332 | import pytest
import matplotlib
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestRegressor
from sklearn.preprocessing import LabelEncoder
import data_describe as dd
matplotlib.use("Agg")
@pytest.mark.base
@pytest.mark.xfail(reason="Not implemented for modin")
def test_importance(compu... |
504343 | import torch
import sys
import os
sys.path.append(os.getcwd())
sys.path.append(os.path.dirname(os.path.dirname(os.getcwd())))
from private_test_scripts.all_in_one import all_in_one_train # noqa
from training_structures.Supervised_Learning import train, test # noqa
from unimodals.common_models import GRUWithLinear, ... |
504383 | import logging
from io import BytesIO
from pathlib import Path
from typing import BinaryIO, Optional, cast
import requests
from tqdm import tqdm
ROOT_DIR = Path(__file__).parent.parent / 'data'
DOMAIN = "obamawhitehouse.archives.gov"
BASE_URL = f"https://{DOMAIN}/sites/default/files/omb/memoranda/"
# Found at http... |
504411 | import os
import sys
import numpy as np
import json
import random
import trimesh
from sklearn.decomposition import PCA
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(BASE_DIR, '..', 'code'))
from pyquaternion import Quaternion
def load_obj(fn):
fin = open(fn, 'r')
lines = [l... |
504418 | import ast
import operator
import pytest
from radon.complexity import *
from radon.contrib.flake8 import Flake8Checker
from radon.visitors import Class, Function
from .test_complexity_visitor import GENERAL_CASES, dedent
get_index = lambda seq: lambda index: seq[index]
def _compute_cc_rank(score):
# This is r... |
504419 | import setuptools
__version__ = '1.0.2'
with open("README.rst", "r") as fh:
long_description = fh.read()
setuptools.setup(
name = 'pyssian',
version = __version__,
description = 'Parser Library for Gaussian Files',
long_description=long_description,
long_description_content_type="text/x-rst",
url = '... |
504457 | class InjectException(Exception):
"""Base class for all exceptions."""
pass
class NonInjectableTypeError(InjectException):
"""Raised when a type could not be injected (i.e. they are no corresponding bindings)."""
pass
class NoBindingFound(NonInjectableTypeError):
"""Raised when no binding was fo... |
504494 | import esphome.codegen as cg
import esphome.config_validation as cv
from esphome import pins
from esphome.components import remote_base
from esphome.const import (
CONF_BUFFER_SIZE,
CONF_DUMP,
CONF_FILTER,
CONF_ID,
CONF_IDLE,
CONF_PIN,
CONF_TOLERANCE,
CONF_MEMORY_BLOCKS,
)
from esphome.c... |
504510 | HAVE_RUN_INIT = "False"
def on_init(server):
global HAVE_RUN_INIT
HAVE_RUN_INIT = "True"
def on_message(msg, server):
if msg["text"] == u"test_init":
return HAVE_RUN_INIT
|
504511 | from distutils.util import strtobool
print(strtobool('true'))
print(strtobool('True'))
print(strtobool('TRUE'))
# 1
# 1
# 1
print(strtobool('t'))
print(strtobool('yes'))
print(strtobool('y'))
print(strtobool('on'))
print(strtobool('1'))
# 1
# 1
# 1
# 1
# 1
print(strtobool('false'))
print(strtobool('False'))
print(st... |
504527 | import heapq
import math
class Solution:
def minimizeError(self, prices: List[str], target: int) -> str:
pq = []
error = 0
for p in map(float, prices):
f = math.floor(p)
c = math.ceil(p)
target -= f
error += p - f
if f != c:
... |
504530 | import sys
import json
import yaml
import requests
import argparse
def _get_interior_materials_common_descriptor(eegeo_assets_host_name, interior_materials_version):
descriptor_url = "http://{host_name}/interior-materials/v{version}/common/descriptor.json.gz".format(
host_name=eegeo_assets_host_name, versi... |
504629 | import numpy as np
import unittest
import os
import openmdao.api as om
from openmdao.utils.assert_utils import assert_near_equal
import pycycle.api as pyc
from N3_MDP import N3_MDP_model
class N3MDPTestCase(unittest.TestCase):
def benchmark_case1(self):
prob = N3_MDP_model()
... |
504641 | from .cassette import Cassette
from .exceptions import InvalidOption, validation_error_map
def validate_record(record):
return record in ['all', 'new_episodes', 'none', 'once']
def validate_matchers(matchers):
from betamax.matchers import matcher_registry
available_matchers = list(matcher_registry.keys(... |
504723 | from tool.runners.python import SubmissionPy
class ThChSubmission(SubmissionPy):
def run(self, input):
valid = 0
for line in input.split("\n"):
policy, letter_with_colon, password = line.split(" ")
policy_min, policy_max = policy.split("-")
letter = letter_with_... |
504765 | import cv2
import numpy as np
from trojai.datagen.image_entity import ImageEntity
class FlatIconDotComPng(ImageEntity):
"""
Defines a png icon for a trigger.
"""
def __init__(self, trigger_fpath, mode='graffiti', trigger_color=None, postit_bg_color=None, size=None):
"""
Initializes a ... |
504780 | from tectosaur.util.geometry import *
def test_internal_angles():
angles = triangle_internal_angles([[0,0,0],[1,0,0],[0,1,0]])
np.testing.assert_almost_equal(angles, [np.pi / 2, np.pi / 4, np.pi / 4])
def test_longest_edge():
assert(get_longest_edge(get_edge_lens([[0,0,0],[1,0,0],[0.5,0.5,0]])) == 0)
... |
504797 | from torch.nn import functional as F
def model_saved_path(base):
return base + "/model.pth"
def model_params_saved_path(base):
return base + '/model_params.json'
def load_model(args, node_featurizer, n_tasks=1):
num_gnn_layers = len(args.gnn_hidden_feats)
model = None
if(args.gnn_model_name == '... |
504832 | import numpy as np
import numpy.ma as ma
from .._lib import SpatialGridStruct as SpatialGridStructBase
from .transform import TransformMethodsMixin, array_bounds
class SpatialGridStruct(SpatialGridStructBase,TransformMethodsMixin):
_accessors = set()
def __init__(self,*args,**kwargs):
super().__init__(... |
504906 | def get_higher_closing(df1, df2):
# true if df is higher
categories = (df1['close'] - df2['close'])
print('something')
# categories =
def get_higher_closing_test():
df1 =
# function to create column showing percentage by which higher price is higher
def get_pct_higher(df):
# i.e., if exchang... |
504947 | class Solution:
def searchMatrix(self, matrix: List[List[int]], target: int) -> bool:
if not matrix:
return False
row, col = len(matrix), len(matrix[0])
r, c = row - 1, 0
while r >= 0 and c < col:
tmp = matrix[r][c]
if tmp == target:
... |
504964 | import unittest
from constants import RAW, URL_ENCODED
from document_generator import DocumentGenerator
from models import APIModel, APIBodyModel
class DocumentGeneratorTest(unittest.TestCase):
def setUp(self) -> None:
self.json_env = {
"id": "b052da30-a4fe-41be-9d36-c7eccd5fa7ef",
... |
505013 | from streamlink.plugins.lrt import LRT
from tests.plugins import PluginCanHandleUrl
class TestPluginCanHandleUrlLRT(PluginCanHandleUrl):
__plugin__ = LRT
should_match = [
"https://www.lrt.lt/mediateka/tiesiogiai/lrt-opus",
"https://www.lrt.lt/mediateka/tiesiogiai/lrt-klasika",
"https:... |
505014 | from pylab import *
rc('axes', linewidth=5)
rc('axes', grid=True)
rc('font', weight='heavy')
rc('font', size=16)
rc('xtick.major', size=6)
rc('xtick.major', width=3)
rc('ytick.major', size=6)
rc('ytick.major', width=3)
plt.ylim([-10.0/2048*1000,-20.0/2048*1000])
plt.xlim([700,1050])
fontsize=16
ax=gca()
for tic... |
505015 | import sys
import time
import os
import threading
bytestoremote = 0
bytesfromremote = 0
_relayport = 0
_remoteaddress = ""
_remoteport = 0
def reportbandwidth():
global bytestoremote
global bytesfromremote
step = 0
while True:
time.sleep(1)
if (sys.platform == "win32"):
os.system('cls')
else:
os.syst... |
505055 | import glob
import os
import tempfile
import fasttext
"""
Parameters for supervised training of fasttext
input # training file path (required)
lr # learning rate [0.1]
dim # size of word vectors [100]
ws # size of the context window [5]
epoch... |
505114 | from django.apps import apps
from django.core.checks import Error, register
@register()
def modeladmin_installed_check(app_configs, **kwargs):
errors = []
MODELADMIN_APP = "wagtail.contrib.modeladmin"
if not apps.is_installed(MODELADMIN_APP):
error_hint = "Is '{}' in settings.INSTALLED_APPS?".for... |
505125 | import numpy as np
import pandas as pd
import plotly.graph_objects as go
from app import helpers
from config import strings, styles
def get_stats_card1_data(
df: pd.DataFrame, port: str, vessel_type: str, year: int, month: int
):
"""
Gets values for the first card in the Stats tab.
:param df: Pandas ... |
505130 | import discord
from discord.ext import commands
from core import checks
from core.models import PermissionLevel
class Purger(commands.Cog):
"""Plugin to delete multiple messages at once."""
def __init__(self, bot: commands.Bot):
self.bot = bot
@commands.command()
@checks.has_permissions(Per... |
505195 | from naruhodo.utils.dicts import ProDict, MeaninglessDict, VerbLikeFuncDict, VerbLikeExclude
from naruhodo.utils.misc import preprocessText
import re
class CaboChunk(object):
"""Class for cabocha chunks"""
def __init__(self, chunk_id, parent):
"""Initialize a chunk."""
self.id = chunk_id
... |
505228 | import structlog
from servicelayer.worker import Worker
from servicelayer.logs import apply_task_context
from memorious.logic.context import Context
from memorious.logic.stage import CrawlerStage
from memorious.core import conn, crawler
log = structlog.get_logger(__name__)
class MemoriousWorker(Worker):
def ha... |
505231 | import torch
import torchaudio
from torch.utils.data import DataLoader
import torch.nn.functional as F
def postprocess_features(feats, sample_rate):
if feats.dim() == 2: feats = feats.mean(-1)
assert feats.dim() == 1, feats.dim()
with torch.no_grad():
feats = F.layer_norm(feats, feats.shape)
re... |
505271 | import pytest
import numpy as np
from xgboost_distribution.distributions import Laplace
@pytest.fixture
def laplace():
return Laplace()
@pytest.mark.parametrize(
"y, params, natural_gradient, expected_grad",
[
(
np.array([0, 0]),
np.array([[0, 1], [1, 0]]),
... |
505272 | import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread(r'C:\Users\PIYUS\Desktop\Image Processing\learning\Resources\Photos\cats 2.jpg')
cv.imshow("img", img)
###### the dimesnion of this blank must be same as the read image
blank = np.zeros(img.shape[:2], dtype='uint8')
circle = cv.cir... |
505374 | import pandas as __pd
import datetime as __dt
from dateutil import relativedelta as __rd
from multiprocessing import Pool as __Pool
import multiprocessing as __mp
from functools import reduce as __red
from seffaflik.__ortak.__araclar import make_requests as __make_requests
from seffaflik.__ortak import __dogrulama as ... |
505378 | from typing import Optional
from sqlalchemy.orm import Session
from app import crud, models
from app.schemas.track import TrackCreate
from app.tests.utils.utils import random_lower_string, random_url
from app.utils import canonical_preview_uri
from .provider import create_random_provider
from .license import create_... |
505379 | from ctypescrypto.oid import Oid
from ctypescrypto import digest
from base64 import b16decode,b16encode
import unittest
class TestDigestType(unittest.TestCase):
def test_md4(self):
d=digest.DigestType("md4")
self.assertEqual(d.digest_size,16)
self.assertEqual(d.block_size,64)
self.a... |
505382 | import numpy as np
import yaml
import sys, os
import trimesh
pykin_path = os.path.dirname(os.path.dirname(os.getcwd()))
sys.path.append(pykin_path)
from pykin.robots.single_arm import SingleArm
from pykin.kinematics.transform import Transform
from pykin.collision.collision_manager import CollisionManager
from pykin.ut... |
505386 | import tempfile
import os
import pytest
from sklearn import datasets
from tensorflow.keras import backend as K
import tensorflow as tf
from ivis.nn import losses as losses
from ivis.nn.distances import euclidean_distance
from ivis import Ivis
@pytest.fixture(scope='function')
def model_filepath():
with tempfile.... |
505402 | import subprocess
import os
import threading
import traceback
import tempfile
import shutil
import atexit
import signal
import shlex
from typing import Optional, Tuple, List
from copy import deepcopy
from pysrt import SubRipFile, SubRipItem
from decimal import Decimal
from .embedder import FeatureEmbedder
from .except... |
505447 | from abc import ABC, abstractmethod
from typing import List
from core.domain.profile.entity.user import User, UserBasicProfile, UserExtraProfile
class ProfileRepository(ABC):
@abstractmethod
def get_user(self, user_type: str, user_id: int) -> User:
return NotImplemented
@abstractmethod
def ... |
505450 | import grequests
import httplib
import logging
import os
import requests
import subprocess
import tempfile
import time
import unittest
from e2e.extensions.filters.common import filtertest
DEBUG=True
class NatsStreamingTestCase(filtertest.TestCase):
def __init__(self, *args, **kwargs):
artifact_root_path = "./e... |
505458 | import sys
import glob
import serial
import serial.tools.list_ports
import socket
import time
from SerialConsole import SerialConsole
def serial_ports():
ports = list(serial.tools.list_ports.comports())
result = {}
for p in ports:
result[p.device] = p.description
return result
def get_computer_... |
505470 | import unittest
from limitlessled.bridge import Bridge
from limitlessled.group.white import WhiteGroup, WHITE
from limitlessled.group.rgbw import RgbwGroup, RGBW
from limitlessled.group.rgbww import RgbwwGroup, RGBWW
# TODO: mock socket
class TestWhiteGroup(unittest.TestCase):
def setUp(self):
self.bridg... |
505474 | from argparse import Namespace
import json
import os
from pathlib import Path
from eth_typing import URI
from eth_utils import is_same_address
from ethpm.backends.registry import is_valid_registry_uri, parse_registry_uri
from ethpm.exceptions import EthPMValidationError
from ethpm.uri import is_ipfs_uri, is_valid_cont... |
505480 | from flask_unchained.cli import cli, click
@cli.command()
def vendor_top_level():
"""vendor_bundle docstring"""
click.echo('vendor_bundle')
# this group will have its baz command overridden
@cli.group()
def foo_group():
"""vendor_bundle docstring"""
@foo_group.command()
def bar():
"""vendor_bundle... |
505501 | from __future__ import absolute_import
from future.utils import PY3
if PY3:
from _thread import *
else:
__future_module__ = True
from thread import *
|
505533 | from typing import Optional, List, Tuple
from drkns.configunit.ConfigUnit import ConfigUnit
from drkns.runner.get_execution_plan import get_execution_plan
from drkns.runner.run_plan import run_plan
from drkns.runner.get_successful_flag_and_combined_output import\
get_successful_flag_and_combined_output
def run(
... |
505563 | import requests
from bs4 import BeautifulSoup
import csv
main_url = "https://www.amazon.in/gp/bestsellers/books/"
req = requests.get(main_url)
htmltext = BeautifulSoup(req.content, "lxml")
pagetxt = htmltext.find_all("div", {"id": "zg_paginationWrapper"})
listing = []
pageURL = []
for i in range(0, len(pagetxt)):
... |
505604 | import abc
import dataclasses
import re
from typing import List, Optional, Tuple
from . import helpers, inflection
from .helpers import MatchError, ModSet
from .js_function import JsFunction, RustParam
from .js_type import JsType, TypeWithDocumentation
from .models import Context, Documented, ToRust
@dataclasses.dat... |
505607 | from spectractor import parameters
from spectractor.fit.fit_spectrogram import SpectrogramFitWorkspace, run_spectrogram_minimisation
from spectractor.fit.fit_spectrum import SpectrumFitWorkspace, run_spectrum_minimisation
from spectractor.config import load_config
if __name__ == "__main__":
from argparse import Ar... |
505608 | from unittest.mock import MagicMock, patch
from geostore.logging_keys import LOG_MESSAGE_LAMBDA_START, LOG_MESSAGE_VALIDATION_COMPLETE
from geostore.step_function import Outcome
from geostore.step_function_keys import DATASET_ID_KEY, VERSION_ID_KEY
from geostore.validation_summary import task
from .aws_utils import a... |
505619 | import unittest
import sys
from jep_pipe import jep_pipe
from jep_pipe import build_java_process_cmd
class TestPreInits(unittest.TestCase):
def test_inits(self):
jep_pipe(build_java_process_cmd('jep.test.TestPreInitVariables'))
|
505637 | import os, sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import trimesh
import numpy as np
import glob
import json
import open3d as o3d
import multiprocessing as mp
from multiprocessing import Pool
import argparse
import traceback
import shutil
import utils.pcd_utils as pcd_uti... |
505680 | import argparse
import os
from operator import itemgetter
import torch
from NVLL.data.lm import DataLM
from NVLL.model.nvrnn import RNNVAE
from NVLL.util.util import GVar
def load_args(path, name):
with open(os.path.join(path, name + '.args'), 'rb') as f:
args = torch.load(f)
return args
def load_... |
505767 | import argparse
from utee import misc, quant, selector
import torch
import torch.backends.cudnn as cudnn
cudnn.benchmark =True
from collections import OrderedDict
import pprint
import os
known_models = [
'mnist', 'svhn', # 28x28
'cifar10', 'cifar100', # 32x32
'stl10', # 96x96
'alexnet', # 224x224
... |
505768 | import logging
import json
import re
import random
from df_engine.core import Context, Actor
import common.dff.integration.context as int_ctx
import common.dff.integration.condition as int_cnd
logger = logging.getLogger(__name__)
with open(
"data/stories.json",
) as stories_json:
stories = json.load(stories... |
505842 | if not "mo21=o" in sm.getQRValue(22013):
sm.avatarOriented("Effect/OnUserEff.img/guideEffect/evanTutorial/evanBalloon21")
sm.addQRValue(22013, "mo21=o")
|
505845 | import argparse
import glob
import os
import random
import warnings
from PyQt5 import QtCore
from PyQt5.QtWidgets import *
from canvas import Canvas
from display_pad import DisplayPad
from hparams import *
from main_window import Ui_MainWindow
parser = argparse.ArgumentParser()
parser.add_argument('--use_cpu', actio... |
505855 | from .arrays import *
from .errors import *
from .timeseries import *
from .readers import *
from .xml import *
__displayname__ = 'Internal Helpers'
|
505909 | from django import template
from django.template import Node
from django.conf import settings
register = template.Library()
@register.filter(name='fdivide')
def fdivide(value,arg):
return float(value) / float(arg)
@register.filter(name='fmultiply')
def fmultiply(value,arg):
return float(value) * float(arg)
... |
505940 | import bst_traversal as program
import unittest
class BST:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
def insert(self, value):
if value < self.value:
if self.left is None:
self.left = BST(value)
else... |
505943 | import unittest
from lxml import etree
from soapfish import core, soap, soap11, soap12
SOAP11_ERROR_MESSAGE = '''
<SOAP-ENV:Envelope xmlns:SOAP-ENV="http://schemas.xmlsoap.org/soap/envelope/">
<SOAP-ENV:Body>
<SOAP-ENV:Fault>
<faultcode>Result</faultcode>
<faultstring/>
<faultacto... |
506070 | from . import Loader
import pandas as pd
import os
class OrbitalInsightLoader(Loader):
dataset = 'ORBITALINSIGHT'
fileglob = 'ORBITALINSIGHT_*.csv'
columns = ['storage.capacity.estimate', 'volume.estimate.stderr', 'scaled.estimate.stderr',
'total.available.tanks', 'smoothed.e... |
506081 | import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix, classification_report
from pymatch.utils.functional import scale_confusion_matrix, sliding_window
from pymatch.utils.DataHandler import DataHandler
from pymatch.utils.exception import TerminationException
import pandas as pd
import seaborn ... |
506084 | import asyncio
import logging
import unittest
import json
import copy
from random import randrange, random, choice, randint
from pprint import pprint
from gremlinpy.gremlin import Gremlin
from gizmo.connection import Response
from gizmo.mapper import *
from gizmo.exception import *
from gizmo.entity import GenericVe... |
506092 | import typing
import ipaddress
import enum
import decimal
import uuid
import datetime
import pathlib
import pytest
import pydantic
import pydantic2graphene
import graphene
def to_pydantic_class(field_type):
class Fake(pydantic.BaseModel):
field: field_type
return Fake
class TestTypeMappingPydantic... |
506126 | import os
PROJECT_ID = 'GOOGLE_CLOUD_PROJECT'
def get_application_id():
"""
Get the associated Google Cloud Project ID
:return:
"""
# NOTE: Google interchangeably refers to this identifier as application_id or project_id
project_id = os.getenv(PROJECT_ID, '')
# ensure project id is a no... |
506139 | import sys
if sys.version_info < (3, 0):
import testcase
else:
from . import testcase
#
# Tests elements of the heading levels
#
class TestLevelDepth(testcase.TestCase):
title = "Test Level Depth"
# Test that headings can go at least to
def test_level_depth_unlimited(self):
self.set_sett... |
506144 | import pandas as pd
import time
import os
from concierge import data_io
from concierge import constants
from concierge.collaborative_filter import CollaborativeFilter
from concierge.concierge_queue import ConciergeQueue
from river import metrics
import redis
cache = redis.Redis(host=constants.REDIS_HOST, port=6379, db... |
506155 | import numpy as np
class Tolerance(object):
'''tolerance level class'''
def __init__(self,tol_type,tmin,tmax,nt):
'''
Input:
tol_type: specify const, linear,exp or log; default is exp
tmin: minimum threshold for metric
... |
506221 | import os
directory = os.path.dirname(os.path.realpath(__file__))
class TestResultImaging:
pass
|
506229 | from rest_framework import serializers
from messaging.models import Contact, ContactAssignment, ContactRole, Email
from peering_manager.api import WritableNestedSerializer
class NestedContactRoleSerializer(WritableNestedSerializer):
url = serializers.HyperlinkedIdentityField(
view_name="messaging-api:con... |
506247 | def col_groupby_pdf(data, col, metric_col, ascending=False):
'''Cumulative Distribution Function
Takes in a dataframe with at least 2 columns, and returns a
groupby table with PDF.
data | DataFrame | a pandas dataframe with the data
col | str | name of the column to be grouped by
metric_col |... |
506254 | from django.utils.functional import cached_property
from waldur_core.structure.tests import fixtures as structure_fixtures
from . import factories
class SupportFixture(structure_fixtures.ServiceFixture):
@cached_property
def issue(self):
issue = factories.IssueFactory(customer=self.customer, project... |
506271 | import ipywidgets as widgets
from traitlets import Unicode, Any
# See js/lib/widgets.js for the frontend counterpart to this file.
@widgets.register
class PlottingProgressBar(widgets.DOMWidget):
"""Progressivis PlottingProgressBar widget."""
# Name of the widget view class in front-end
_view_name = Unic... |
506278 | import os
import shutil
from pathlib import Path
for root, dirs, files in os.walk('archive_en_US'):
root = Path(root)
for file in files:
moved_root = Path('en_US') / root.relative_to('archive_en_US')
shutil.move(root / file, moved_root / file)
os.remove(moved_root / (Path(file).stem + ... |
506325 | from django.shortcuts import render, get_object_or_404
from django.core.paginator import Paginator
from django.shortcuts import redirect
from django.contrib import messages
from django.contrib.auth import get_user_model
from django.contrib.auth.mixins import UserPassesTestMixin, LoginRequiredMixin
from django.contrib.m... |
506349 | import os
from pathlib import Path
import librosa
import numpy as np
import soundfile
from tqdm import tqdm
###
noisy_dir = Path("~/Datasets/simulation_array26cm_20210119_shuf100/noisy").expanduser().absolute()
clean_dir = Path("~/Datasets/simulation_array26cm_20210119_shuf100/clean").expanduser().absolute()
text_dir... |
506407 | import logging
import grequests
import newrelic
import pylibmc as memcache
from django.conf import settings
from django.http import HttpResponseRedirect
from core.api.resources import Site
from core.api.resources import WhoAmI
logger = logging.getLogger('core.middleware.context')
class ContextMiddleware():
"""... |
506434 | from .Function import Cfunction
class ProximalFunction(Cfunction):
"""
Class that represents a function with its proximal mapping
"""
def __init__(self,prox):
self._prox=prox
@property
def prox(self):
return self._prox
|
506436 | import os
import time
import argparse
import pandas as pd
from SR import SequentialRules
parser = argparse.ArgumentParser()
parser.add_argument('--prune', type=int, default=0, help="Association Rules Pruning Parameter")
parser.add_argument('--K', type=int, default=20, help="K items to be used in Recall@K and MRR@K")
p... |
506463 | from handlers.base_handler import BaseHandler
from lib.objects import Message
class ObsceneHandler(BaseHandler):
TOTAL_AMOUNT = 3
def _set_pattern(self):
self.pattern = 'obscene.warning'
def _need_data(self) -> bool:
return True
def _works_in_chat(self) -> bool:
return True
... |
506495 | import torch
import torch.nn.functional as F
def _differentiation_1_distance(X):
#Perform differentiation for each consecuent point in the X dataset (time series)
#Only for axis=0
X = X.permute(2, 1, 0)
aux = X - F.pad(X, (1, 0))[:, :, :-1]
return aux.permute(2,1,0)
def diff(X):
'''
Only... |
506527 | import numpy as np
import pytorch3d
import torch
from .abstract import AbstractDataset
class PointcloudDataset(AbstractDataset):
def __init__(self, cfg, root_path, data_dict, split, rotated=False):
name = cfg.name
super(PointcloudDataset, self).__init__(name, split, root_path)
self.cfg = ... |
506554 | import pathlib
from setuptools import setup, find_packages
# The directory containing this file
HERE = pathlib.Path(__file__).parent
# The text of the README file
README = (HERE / "README.md").read_text()
with open('requirements.txt') as f:
dependencies = f.read().splitlines()
setup(name='idewavecore',
... |
506572 | import sys
import os
if sys.platform == 'win32':
import ntfslink
os.symlink = ntfslink.symlink
os.readlink = ntfslink.readlink
os.path.islink = ntfslink.islink
|
506690 | import unittest
from opyoid import PerLookupScope
from opyoid.bindings import FromClassProvider
class MyType:
pass
class TestPerLookupScope(unittest.TestCase):
def setUp(self) -> None:
self.scope = PerLookupScope()
self.class_provider = FromClassProvider(MyType, [], None, {})
def test_... |
506700 | import flask
from fence.models import IdentityProvider
from fence.blueprints.login.base import DefaultOAuth2Login, DefaultOAuth2Callback
class ORCIDLogin(DefaultOAuth2Login):
def __init__(self):
super(ORCIDLogin, self).__init__(
idp_name=IdentityProvider.orcid, client=flask.current_app.orcid... |
506721 | from operator import attrgetter
class Country:
def __init__(self, name, population, area):
self.name = name
self.population = population
self.area = area
def __repr__(self):
return repr((self.name,self.population,self.area))
countries = [Country('India',1200,100),
... |
506788 | from unittest import expectedFailure
from django.db.models import Q, Field, F
from django.test import SimpleTestCase
from mock import sentinel
from natural_query.query import NaturalQueryDescriptor
from tests.unit.support import assertQObjectsEqual
class NaturalQueryDescriptorTestCase(SimpleTestCase):
def setUp... |
506793 | import torch
import torchvision
import torchvision.transforms as transforms
import numpy as np
class IMBALANETINYIMGNET(torchvision.datasets.ImageFolder):
cls_num = 200
def __init__(self, root, imb_type='exp', imb_factor=0.01, rand_number=0,
transform=None, target_transform=None):
sup... |
506799 | from django.core.handlers.base import BaseHandler
import app
from django.test import Client
def test_middleware(rf, settings):
settings.MIDDLEWARE = [
"app.middleware.hello_world"
]
request = rf.get('/')
handler = BaseHandler()
handler.load_middleware()
response = handler.get_response... |
506828 | import FWCore.ParameterSet.Config as cms
eleRegressionEnergy = cms.EDProducer("RegressionEnergyPatElectronProducer",
debug = cms.untracked.bool(False),
inputElectronsTag = cms.InputTag('selectedPatElectrons'),
#inp... |
506830 | import unittest
import sys
sys.path.insert(0, '../')
import numpy as np
import numpy.linalg as la
from pak.evaluation import MOTM
class TestEvaluation(unittest.TestCase):
def test_motm_duplicate(self):
Gt = np.array([
[1, 1, 0, 0],
[1, 2, 10, 10],
[2, 1, 0, 0]
... |
506835 | import io
from testpath import assert_isfile, assert_not_path_exists
from zipfile import ZipFile
from nsist import commands
def test_prepare_bin_dir(tmp_path):
cmds = {
'acommand': {
'entry_point': 'somemod:somefunc',
'extra_preamble': io.StringIO(u'import extra')
}
}
... |
506919 | import fileinput
import re
connections = {}
# Set up dictionary of connections
for line in fileinput.input():
rule, wire = re.search(r'(.*) -> (.*)', line).groups()
value = None
if len(rule.split()) == 1:
value = (rule,)
elif 'NOT' in rule:
value = ('NOT', rule.split()[1])
else:
... |
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