id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
11457852 | import matplotlib as mpl
import matplotlib.pyplot as plt
import networkx as nx
from networkx.drawing.nx_pydot import graphviz_layout
mpl.rcParams["figure.dpi"] = 300
def simple_nx_plot(outnodes, innodes, node_labels):
"""Plot graph for debugging purposes."""
labels = dict([(i, j) for i, j in enumerate(node_l... |
11457875 | from django.shortcuts import resolve_url as r
from django.test import TestCase
from .test_base import BaseProposalTest
class ProposalListGet(BaseProposalTest, TestCase):
def setUp(self):
self.resp = self.client.get(r('proposal:proposal_list'))
def test_get(self):
self.assertEqual(200, self.r... |
11457924 | import time
from typing import Dict, List
from instagrapi.exceptions import ClientError, MediaError, UserError
from instagrapi.utils import json_value
POST_TYPES = ("ALL", "CAROUSEL_V2", "IMAGE", "SHOPPING", "VIDEO")
TIME_FRAMES = (
"ONE_WEEK", "ONE_MONTH", "THREE_MONTHS", "SIX_MONTHS",
"ONE_YEAR", "TWO_YEARS... |
11457946 | from gevent.testing import six
import sys
import os
import errno
from gevent import select, socket
import gevent.core
import gevent.testing as greentest
import gevent.testing.timing
import unittest
class TestSelect(gevent.testing.timing.AbstractGenericWaitTestCase):
def wait(self, timeout):
select.select... |
11457966 | import string
from django.contrib.auth import REDIRECT_FIELD_NAME
from django.contrib.auth.hashers import check_password, make_password
from django.contrib.auth.models import User
from django.contrib.auth.tokens import default_token_generator
from django.core.exceptions import ValidationError
from django.http import H... |
11457969 | from __future__ import print_function
import os
import pytest
from fasttrips import Run
"""
Run just the tests labeled basic using `pytest -v -m basic`
"""
demand_options = ["backward_bunnies","forward_bunnies"]
network_options = ["bunny_hop","many_bunny_hops"]
@pytest.mark.parametrize("demand", demand_options)
@py... |
11457982 | from django.views.generic import DetailView
from django.views.generic.detail import SingleObjectMixin
from ..core.views import PaginatedListView
from .models import Account, Tweet, User
class HomeView(PaginatedListView):
template_name = "twitter/home.html"
def get_context_data(self, **kwargs):
conte... |
11458002 | from learnergy.models.bernoulli import HybridDiscriminativeRBM
# Creates a HybridDiscriminativeRBM-based class
model = HybridDiscriminativeRBM(n_visible=784, n_hidden=128, learning_rate=0.1,
alpha=0.01, momentum=0, decay=0, use_gpu=False)
|
11458012 | import os
os.environ["PMD_CMD"] = "/opt/pmd-bin/bin/run.sh pmd"
os.environ["APP_SRC_DIR"] = "/usr/local/src"
|
11458091 | from gnas.search_space.operation_space import RnnNodeConfig, RnnInputNodeConfig, CnnNodeConfig
from gnas.modules.node_module import RnnNodeModule, RnnInputNodeModule, ConvNodeModule
__module_dict__ = {RnnNodeConfig: RnnNodeModule,
RnnInputNodeConfig: RnnInputNodeModule,
CnnNodeCon... |
11458117 | import tensorflow as tf
from termcolor import colored
from deeptrain.util._backend import TF_KERAS
WARN = colored('WARNING:', 'red')
NOTE = colored('NOTE:', 'blue')
#### Env flags & Keras backend ###############################################
tf_eager = tf.executing_eagerly
TF_2 = bool(tf.__version__[0] == '2')
if ... |
11458126 | import warnings
from typing import Tuple, Union
import torch
import numpy as np
from sklearn.metrics import fbeta_score, roc_auc_score, cohen_kappa_score
from sklearn.exceptions import UndefinedMetricWarning
class Metric:
name = "metric"
def __call__(self, truth: torch.Tensor, pred: torch.Tensor) -> Tuple[f... |
11458128 | import sklearn.neighbors as skl_neighbors
from Orange.base import KNNBase
from Orange.classification import SklLearner
__all__ = ["KNNLearner"]
class KNNLearner(KNNBase, SklLearner):
__wraps__ = skl_neighbors.KNeighborsClassifier
|
11458133 | from __future__ import division, absolute_import, print_function
import time
from integration_test import *
class BadgeSpeedTestCase(IntegrationTest):
def __init__(self, device_addr, test_duration_minutes=5):
self.test_duration_minutes = test_duration_minutes
super(BadgeSpeedTestCase, self).__ini... |
11458136 | import unittest
from unittest import TestCase
from metadata.ingestion.api.source import SourceStatus
from metadata.ingestion.source.sql_source import SQLSourceStatus
from metadata.utils.column_helpers import get_column_type
SQLTYPES = [
"ARRAY",
"BIGINT",
"BIGNUMERIC",
"BIGSERIAL",
"BINARY",
"... |
11458137 | import json
import sys
import os
import random
import ruamel.yaml as yaml
from hurry.filesize import size
from ldt.helpers.exceptions import ResourceError
from ldt.load_config import config
def get_object_size(obj, seen=None):
"""
A function that recursively finds size of objects,
from https://goshippo... |
11458205 | import scipy as sp
import numpy as np
import scipy.ndimage as spim
from skimage.segmentation import relabel_sequential
from edt import edt
from loguru import logger
from skimage.morphology import ball, disk
from ._utils import Results
from ._unpad import unpad
try:
from skimage.measure import marching_cubes
except ... |
11458303 | import pytest
import jira.resources
MOCK_URL = "http://customized-jira.com/rest/"
def url_test_case(example_url: str):
return f"{MOCK_URL}{example_url}"
class TestResource:
@pytest.mark.parametrize(
["example_url", "expected_class"],
# fmt: off
[
(url_test_case("api/lat... |
11458334 | from .task import Task
from .cpupool import pin, CPUPool, is_runtime_ext_enabled
from .multi_stream import MultiStreamModule
from .runtime_utils import get_core_list_of_node_id
|
11458337 | self.description = "a package conflicts with itself"
sp1 = pmpkg("pkg1")
sp1.conflicts = ["pkg1"]
self.addpkg2db("sync", sp1);
sp2 = pmpkg("pkg2", "1.0-2")
self.addpkg2db("sync", sp2)
self.args = "-S %s" % " ".join([p.name for p in (sp1, sp2)])
self.addrule("PACMAN_RETCODE=0")
self.addrule("PKG_EXIST=pkg1")
self.ad... |
11458342 | from datetime import datetime, timedelta
from gremlin_python.process.graph_traversal import select, has, unfold
from gremlin_python.process.traversal import P
def get_timerange_condition(g, start_hour=16, end_hour=18, limit=1000):
dates = (
g.E()
.hasLabel("visited")
.limit(limit)... |
11458343 | import numpy as np
from fastai.text import SortSampler, SortishSampler
def test_sort_sampler_sorts_all_descending():
bs = 4
n = bs*100
data = 2 * np.arange(n)
samp = list(SortSampler(data, lambda i: data[i]))
# The sample is a permutation of the indices.
assert sorted(samp) == list(range(n))... |
11458375 | from torch.utils.data import Dataset
import torch
import numpy as np
from sklearn.utils import check_array
class FastTensorDataLoader:
"""
A DataLoader-like object for a set of tensors that can be much faster than
TensorDataset + DataLoader because dataloader grabs individual indices of
the dataset and... |
11458382 | from configs import PruneCartpoleConfig as student_config
from configs import CartpoleConfig as dense_config
from model import CartPoleDQNTarget, StudentCartpole
from utils.plot_utils import plot_graph
from utils.logger_utils import get_logger
from Cartpole.evaluate_cartpole import evaluate_cartepole as evaluate
from t... |
11458440 | import time, pytest
import numpy as np
from scipy import linalg
from scipy.sparse import linalg as sparselinalg
def test_eigs():
N = 1000
k = 5
ncv = 200
A = np.random.randn(N, N)
print("\n----- test_eigs -----")
print("----- Dimension of matrix A: %d -----" % N)
print("scipy.sparse.linalg.... |
11458462 | import __builtin__
import compileall
import os
import py_compile
import shutil
import subprocess
import sys
import textwrap
import unittest
from test.test_support import TESTFN, is_jython, run_unittest, temp_cwd
class TestMtime(unittest.TestCase):
def test_mtime_compile(self):
"""
This test exerc... |
11458479 | import uuid
import aioredis # type: ignore
import pytest
from pytest_mock import MockFixture
from requests import Response # type: ignore
from starlette.testclient import TestClient
from example.context import app
from fast_tools.context import ContextBaseModel, HeaderHelper
from .conftest import AnyStringWith # ... |
11458515 | import logging
from fastapi import BackgroundTasks, FastAPI
from pubnub.pnconfiguration import PNConfiguration
from pubnub.pubnub_asyncio import PubNubAsyncio
import pubnub as pn
app = FastAPI()
pnconfig = PNConfiguration()
pnconfig.publish_key = "demo"
pnconfig.subscribe_key = "demo"
pnconfig.uuid = "UUID-PUB"
CHAN... |
11458527 | import os
import pickle
import h5py
import torch
import torch_em
import torch_em.shallow2deep as shallow2deep
from torch_em.shallow2deep.prepare_shallow2deep import _get_filters, _apply_filters
from torch_em.util.util import get_trainer
from tqdm import trange
TEST_OUT = "./test_data"
def require_rf(path):
rf_p... |
11458534 | import logging
from pgdrive.component.algorithm.BIG import BIG
from pgdrive.component.road.road_network import RoadNetwork
from pgdrive.tests.vis_block.vis_block_base import TestBlock
if __name__ == "__main__":
logging.basicConfig(level=logging.DEBUG)
test = TestBlock(True)
global_network = RoadNetwork()
... |
11458549 | import numpy as np
import math
import torch
from torch import nn
from torch.nn import functional as F
from models.utils import loss_functions as lf, modules
from models.conv.nets import ConvLayers,DeconvLayers
from models.fc.nets import MLP, MLP_gates
from models.fc.layers import fc_layer,fc_layer_split, fc_layer_fixed... |
11458561 | import json
import posixpath
import re
import time
def test_simple(pyscript):
script = pyscript("""
import click
from daemonocle.cli import DaemonCLI
@click.command(cls=DaemonCLI,
daemon_params={'name': 'foo', 'pid_file': 'foo.pid'})
def main():
... |
11458576 | from pymoo.core.problem import calc_constr
from pymoo.problems.meta import MetaProblem
from pymoo.util.misc import from_dict
class ConstraintViolationAsObjective(MetaProblem):
def __init__(self, problem, eps=1e-6):
super().__init__(problem)
self.n_obj = 1
self.n_constr = 0
self.ep... |
11458583 | from __future__ import print_function, division
import torch
import numpy as np
import torch.nn as nn
import os
import shutil
from sklearn.metrics.pairwise import euclidean_distances
import torch.nn.functional as F
from Options import Config
config = Config().parse()
def to_np(x):
return x.data.cpu().numpy()
de... |
11458586 | import textwrap
import pytest
from mock import patch
from conans.errors import ConanException
from conans.util.files import save
from conans.test.utils.tools import TestClient
@pytest.fixture
def client():
client = TestClient()
conanfile = textwrap.dedent("""
from conans import ConanFile
cl... |
11458617 | import django_filters
from django.db.models import Q
from . import models
class CharInFilter(django_filters.BaseInFilter, django_filters.CharFilter):
pass
class CityFilter(django_filters.rest_framework.FilterSet):
provinceNames = CharInFilter(
field_name='provinceName', lookup_expr='in')
provin... |
11458672 | import pytest
from oslash.either import Right
from jsonrpcserver.async_main import (
dispatch_to_response,
dispatch_to_serializable,
dispatch_to_json,
)
from jsonrpcserver.response import SuccessResponse
from jsonrpcserver.result import Result, Success
async def ping() -> Result:
return Success("pon... |
11458677 | import balanced
balanced.configure('ak-test-2eKlj1ZDfAcZSARMf3NMhBHywDej0avSY')
card = balanced.Card.fetch('/cards/CC4zyuNpxY0A0eAf87SeULCR')
card.meta = {
'twitter.id': '1234987650',
'facebook.user_id': '0192837465',
'my-own-customer-id': '12345'
}
card.save() |
11458681 | import re
from alexa.utils.config import LocalConfig
from apiclient.discovery import build
config = LocalConfig()
class YoutubeVideoInformation:
def __init__(self, video=None):
if video is not None:
self.__id = str(video['id']['videoId'])
self.__title = video['snippet']['title']
... |
11458704 | import tensorflow as tf
import numpy as np
import os
from keras import backend as K
from util import *
from constants import *
# Visualize using:
# http://projector.tensorflow.org/
def main():
models = build_or_load()
style_layer = models[0].get_layer('style')
print('Creating input')
style_in = tf.pl... |
11458707 | from django.core.exceptions import ValidationError
from django.forms import ModelForm
from django.forms.fields import ChoiceField, MultipleChoiceField
from django.forms.widgets import CheckboxSelectMultiple, Textarea
from export.forms import ExportImageStatsForm
from upload.forms import CsvFileField
from .models impor... |
11458744 | from __future__ import print_function, absolute_import
from .reid_loaders import ReIDLoaders
from .incremental_reid_loaders import IncrementalReIDLoaders
from .customed_loaders import CustomedLoaders
from .transforms2 import RandomErasing
from .incremental_datasets import IncrementalReIDDataSet, Incremental_combine_tr... |
11458746 | import logging
from flask import request
from flask_restplus import Resource, inputs
from biolink.datamodel.serializers import association, association_results
from biolink.api.restplus import api
from ontobio.golr.golr_associations import get_association, search_associations
from biolink import USER_AGENT
log = log... |
11458763 | import copy
import functools
from .compat import build_opener, HTTPCookieProcessor, URLError, \
urlencode, CookieJar, HTTPError, BadStatusLine
from .utils import parse_content_type, NOT_A_PAGE_CONTENT_TYPES
import gzip
import zlib
import webvulnscan.log
from .page import Page
from .request import Request
class ... |
11458788 | import json
from core.redis import rds
from core.triage import Triage
from core.parser import ScanParser
class Rule:
def __init__(self):
self.rule = 'CFG_ESTR'
self.rule_severity = 4
self.rule_description = 'Thisr ule checks for NodeJS Server.js file exposures'
self.rule_confirm = 'Remote NodeJS Se... |
11458794 | import utils.logging_data as LOG
import cv2
from imutils import face_utils
import dlib
from keras.models import load_model
from scipy.spatial import distance as dist
import imutils
import os
import sys
import threading
import numpy as np
import re
import time
import datetime
'''
Dlib detection
This file contains a dli... |
11458803 | import FWCore.ParameterSet.Config as cms
import FWCore.ParameterSet.VarParsing as VarParsing
process = cms.Process("OccupancyPlotsTest")
#prepare options
options = VarParsing.VarParsing("analysis")
options.register ('globalTag',
"DONOTEXIST",
VarParsing.VarParsing.multiplicity.si... |
11458821 | import FWCore.ParameterSet.Config as cms
from Configuration.Eras.Era_Phase2C11I13_cff import Phase2C11I13
from Configuration.Eras.Modifier_phase2_brickedPixels_cff import phase2_brickedPixels
from Configuration.Eras.Modifier_phase2_GE0_cff import phase2_GE0
Phase2C11I13T27M9 = cms.ModifierChain(Phase2C11I13, phase2_b... |
11458823 | from .asset import Asset
from .collection import Collection
from .item import Item
collection_store = {}
item_store = {}
asset_store = {}
def get_collection(title: str) -> Collection:
if title not in collection_store:
collection = Collection(title)
collection_store[title] = collection
return ... |
11458825 | from django.forms.utils import flatatt
from django.utils.html import format_html
from django_icons.css import merge_css_list, merge_css_text
class IconRenderer(object):
"""Render an icon as an HTML element."""
tag = "i"
format_string = "<{tag}{attrs}>{content}</{tag}>"
def __init__(self, name, **kw... |
11458831 | from datetime import datetime, timedelta
from urllib.parse import urlencode
import colander
import kinto.core
from cornice.validators import colander_validator
from kinto.authorization import RouteFactory
from kinto.core import resource
from kinto.core import utils as core_utils
from kinto.core.storage import Filter, ... |
11458839 | import brownie
from brownie import ZERO_ADDRESS, Contract, Settler, accounts, chain
from brownie.test import strategy
from brownie_tokens import MintableForkToken
TOKENS = [
(
"0x57ab1ec28d129707052df4df418d58a2d46d5f51", # sUSD
"0xdac17f958d2ee523a2206206994597c13d831ec7", # DAI
"0xa0b86... |
11458847 | class Solution:
def luckyNumbers (self, matrix: List[List[int]]) -> List[int]:
if len(matrix) == 0 or len(matrix[0]) == 0:
return 0
l = collections.defaultdict(int)
n, m = len(matrix), len(matrix[0])
def findMax(j):
if j in l:
return l[j]
... |
11458902 | import pytest
import boost_histogram as bh
@pytest.fixture(params=(False, True), ids=("no_growth", "growth"))
def growth(request):
return request.param
@pytest.fixture(params=(False, True), ids=("no_overflow", "overflow"))
def overflow(request):
return request.param
@pytest.fixture(params=(False, True), ... |
11458909 | import collections
import logging
from django.db import models
from django.db.migrations.topological_sort import stable_topological_sort
from django.utils.lru_cache import lru_cache
import requests
from . import SupportedServices
logger = logging.getLogger(__name__)
Coordinates = collections.namedtuple('Coordinates'... |
11458985 | import os
os.environ['CUDA_VISIBLE_DEVICES'] = ''
os.environ['MALAYA_USE_HUGGINGFACE'] = 'true'
import sys
import malaya
import logging
logging.basicConfig(level=logging.DEBUG)
text = 'Jabatan Penjara Malaysia diperuntukkan RM20 juta laksana program pembangunan Insan kepada banduan. Majikan yang menggaji bekas band... |
11459012 | from typing import Callable, Iterable, TypeVar
from expression.collections import seq
from expression.core import Builder, identity
TSource = TypeVar("TSource")
TResult = TypeVar("TResult")
TState = TypeVar("TState")
class SeqBuilder(Builder[Iterable[TSource], TSource]):
def bind(self, xs: Iterable[TSource], fn... |
11459017 | import cv2
from frame import Frame
class Video:
videoPath = ""
framesDirectory = "/var/src/output/frames"
video
frameCount = 0
cols = 0
rows = 0
frames = {}
def __init__(self, videoPath, slowInport=false):
self.videoPath = videoPath
self.video = cv2.VideoCapture(videoP... |
11459104 | import os
import sys
from pathlib import Path
import os.path as osp
import numpy as np
import torch
import torch.backends.cudnn as cudnn
import torch.nn.functional as F
import torch.optim as optim
from tensorboardX import SummaryWriter
from torch import nn
from torchvision.utils import make_grid
from tqdm i... |
11459126 | from __future__ import annotations
from abc import abstractmethod
import logging
from pathlib import Path
from typing import (
Any, cast, Iterator, Mapping, Optional,
TYPE_CHECKING, Union,
)
from PyQt5 import Qt
from .bases import (
AbstractYAMLObjectSingleton, QABC, QAbstractYAMLObj... |
11459155 | class Node:
# Constructor tor create a new node
def __init__(self, key):
self.key = key
self.left = None
self.right = None
def printLevels(root, low, high):
Q = []
marker = Node(11114) # Marker node to indicate end of level
level = 1 # Initialize level number
# Enqueue the only first level ... |
11459187 | import pytest
from eth_utils.hexadecimal import is_0x_prefixed
@pytest.mark.parametrize(
"value,expected",
(("", False), ("0x", True), ("0x12345", True), ("12345", False), ("0X12345", True)),
)
def test_is_0x_prefixed(value, expected):
assert is_0x_prefixed(value) is expected
@pytest.mark.parametrize("... |
11459223 | from ..typing import SpectrumType
from ..utils import clean_adduct
from ..utils import looks_like_adduct
def derive_adduct_from_name(spectrum_in: SpectrumType,
remove_adduct_from_name: bool = True) -> SpectrumType:
"""Find adduct in compound name and add to metadata (if not present yet... |
11459231 | def top_level_reducer(owner, child):
return owner
def bot_level_reducer(owner, child):
return child
def addition_reducer(owner, child):
return owner + child
def mult_reducer(owner, child):
return owner * child
|
11459237 | class BaseDriverUnitTest:
def setup_method(self):
pass
def get_prompt(self):
return self.standard_prompt
@staticmethod
def send_inputs():
return True
@staticmethod
def send_inputs_interact():
return True
def test__determine_current_priv_exec(self):
... |
11459272 | import pdb
import random
import torch
from transformers import BertTokenizer
from torch.nn.utils.rnn import pad_sequence
from torch.utils.data import Dataset
class MTSIAdapterDataset(Dataset):
"""
MTSIAdapterDataset is a module implementing the adapter pattern used as intermediary between you program and the... |
11459334 | import os
import re
from xml.etree import ElementTree as ET
import sublime
import sublime_plugin
from . import project
class AndroidXmlComplete(sublime_plugin.EventListener):
def __init__(self):
self.dirty = False
def on_query_completions(self, view, prefix, locations):
if not self.is_respo... |
11459377 | from math import ceil
from typing import List
from shapely.geometry import Point, LineString, Polygon
from plaza_preprocessing.optimizer import utils
from plaza_preprocessing.optimizer.graphprocessor.graphprocessor import GraphProcessor
class SpiderWebGraphProcessor(GraphProcessor):
""" Process a plaza with a spi... |
11459385 | import numpy as np
import matplotlib.pyplot as plt
# Generate a distribution
x = 0.5*np.random.randn(1000)+4
# Standard (mean=0, stdev=1) Scaler
y = (x-np.mean(x))/np.std(x)
# Min-Max (0-1) Scaler
z = (x-np.min(x))/(np.max(x)-np.min(x))
# Plot distributions
plt.figure(figsize=(8,4))
plt.hist(x, bins=30, label='orig... |
11459417 | from itertools import groupby
from urlparse import urlparse
from tld import get_tld
from sqlalchemy import (
Column,
Integer,
String,
ForeignKey,
)
from sqlalchemy.orm import relationship
from ..app import db
class Medium(db.Model):
""" A medium from which articles are drawn, such as a newsp... |
11459461 | from network import ipaddr
def valid_ip_network(network):
"""Take a v4 or v6 network, e.g. '192.168.3.5/24' or
'192.168.3.5/255.255.255.0' and return whether it is valid.
Args:
network (str): IP address and mask, e.g. '192.168.3.5/24'.
Returns:
True if valid, False otherwise.
"""... |
11459478 | from typing import List
class Solution:
def islandPerimeter(self, grid: List[List[int]]) -> int:
perimeter, rows, columns = 0, len(grid), len(grid[0])
for row in range(rows):
for column in range(columns):
if grid[row][column] == 1:
perimeter += 4 - s... |
11459521 | from django.views.generic import DetailView
from templated_email.models import SavedEmail
class ShowEmailView(DetailView):
model = SavedEmail
template_name = 'templated_email/saved_email.html'
slug_field = 'uuid'
slug_url_kwarg = 'uuid'
|
11459533 | import sublime
import sublime_plugin
def plugin_loaded():
global close_sidebar_if_opened
global settings
global settings_base
settings = sublime.load_settings("FocusFileOnSidebar.sublime-settings")
settings_base = sublime.load_settings("Preferences.sublime-settings")
plugin_reload()
setti... |
11459540 | import networkx as nx
import asyncio
import ccxt.async_support as ccxt
import json
from .settings import COLLECTIONS_DIR
__all__ = [
'ExchangeMultiGraphBuilder',
'build_arbitrage_graph_for_exchanges',
'build_multi_graph_for_exchanges',
]
class ExchangeMultiGraphBuilder:
def __init__(self, exchanges:... |
11459552 | import torch
import torch.nn as nn
import numpy as np
from torch.distributions.multivariate_normal import MultivariateNormal
class GaussianDistribution(nn.Module):
"""
Standard Normal Likelihood
"""
def __init__(self, size):
super().__init__()
self.size = size
self.dim = dim = ... |
11459580 | from django.conf import settings
from django.utils.translation import gettext_lazy as _
# Example:
SETTING_1 = getattr(settings, "MAGAZINE_SETTING_1", "default value")
MEANING_OF_LIFE = getattr(settings, "MAGAZINE_MEANING_OF_LIFE", 42)
ARTICLE_THEME_CHOICES = getattr(
settings,
"MAGAZINE_ARTICLE_THEME_CHOICE... |
11459594 | import argparse, random, os, math, functools
from operator import mul
def create_dirs(program):
dirname = "data/"+program
if not os.path.exists(dirname):
try:
os.makedirs(dirname)
except OSError as e:
if e.errno != errno.EEXIST: raise
def get_rand_list(bits, l):
ret... |
11459651 | from __future__ import unicode_literals
from os_urlpattern.parse_utils import (EMPTY_PARSED_PIECE, PieceParser,
analyze_url)
from os_urlpattern.piece_pattern_node import (PiecePatternNode,
build_from_parsed_pieces,
... |
11459656 | from django.forms import ModelForm
from cases.models import Case
from django import forms
from individuals.models import Individual
# Create the form class.
class CaseForm(ModelForm):
class Meta:
model = Case
fields = '__all__' |
11459668 | from .__version__ import __version__
from .core.session import Session
from .core.wrapper import BrowserWrapper
from .core.exceptions import LogInError, NotConnectedError
from .core._parser import InfoTypes, ResultTypes
def init_session():
return Session(BrowserWrapper()) |
11459745 | import re
from abc import ABC, abstractmethod
from typing import List, Dict, Any, Set, Optional
DOCSTRING_REGEX_TOKENIZER = re.compile(r"[^\s,'\"`.():\[\]=*;>{\}+-/\\]+|\\+|\.+|\(\)|{\}|\[\]|\(+|\)+|:+|\[+|\]+|{+|\}+|=+|\*+|;+|>+|\++|-+|/+")
def tokenize_docstring(docstring: str) -> List[str]:
return [t ... |
11459788 | from copy import deepcopy
from typing import Dict
import pytest
import torch
from ludwig.features.category_feature import CategoryInputFeature
from ludwig.models.ecd import build_single_input
BATCH_SIZE = 2
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
@pytest.fixture(scope="module")
def category_config(... |
11459807 | import hashlib
import os
from typing import List, Tuple
from xml.etree import cElementTree as ETree
import yaml
from flask import current_app
from sqlalchemy import text
from yaml.loader import FullLoader
from actor_libs.database.orm import db
from actor_libs.utils import get_cwd, get_services_path
from app.models im... |
11459839 | from collections import defaultdict
import os
import random
from moviepy.editor import *
import numpy as np
from PIL import Image
from heatmappy import Heatmapper
class VideoHeatmapper:
def __init__(self, img_heatmapper):
self.img_heatmapper = img_heatmapper
def heatmap_on_video(self, base_video, p... |
11459883 | import subprocess
import glob
import os
import tempfile
import lxml.etree
ICON_MAPPING = {
'cal_homework.gif': 'grading',
'check.gif': 'done',
'delete2.gif': 'delete',
'discuss.gif': 'forum',
'doc2.gif': 'description',
'edit2.gif': 'edit',
'find.png': 'search',
'hot.gif': 'whatshot',
... |
11459905 | import FWCore.ParameterSet.Config as cms
#
# module to fill the full-hadronic ttbar event structure
#
ttFullHadEvent = cms.EDProducer("TtFullHadEvtBuilder",
## choose leptonic decay modes
decayChannel1 = cms.int32(0), # 0: none
# 1: electron
#... |
11459966 | from io import BytesIO
from PIL import Image, ImageEnhance
from colors import color
def render(image_data, width=120, height_scale=0.55, colorize=True):
with BytesIO(image_data) as fp:
img = Image.open(fp)
org_width, orig_height = img.size
aspect_ratio = orig_height / org_width
n... |
11459977 | dict = {}
with open("irregular_verbs.txt","r") as f:
lines = f.readlines()
for line in lines:
tenses = line.split("\t")
dict[tenses[0]]=tenses
def is_vowel(c):
return c=='a' or c=='e' or c=='i' or c=='o' or c=='u'
def is_conso(c):
return (not is_vowel(c)) and (not c=='y') an... |
11459989 | from tensorflow.keras import layers, Model
from tensorflow.keras.applications import ResNet50, ResNet101, ResNet152
from tensorflow.keras.regularizers import l2
from utils import add_regularization, get_flops
BACKBONES = {
'resnet50': ResNet50,
'resnet101': ResNet101,
'resnet152': ResNet152
}
def Simple... |
11460000 | from utils import *
def do_inference(model, path):
img = open_img(path)
return get_pred(model, img)
if __name__ == '__main__':
model = prepare_model()
print('Finished loading model------------------------------')
print('-----------------------------------------------------')
do_inference(... |
11460026 | import uuid
from typing import List
from azure.cosmos import CosmosClient
from pydantic import parse_obj_as
from db.repositories.resources import ResourceRepository
from models.domain.workspace_service import WorkspaceService
from models.schemas.workspace_service import WorkspaceServiceInCreate, WorkspaceServicePatch... |
11460036 | from .abc import *
from .neighbor import *
from .routing import *
from .mac import *
from .ipaddress import *
from .password_type import *
from .route_target import *
from .route_distinguisher import *
from .redistribution_attr import *
|
11460066 | import gym
import math
from copy import deepcopy
import numpy as np
import matplotlib.pyplot as plt
env = gym.make('MountainCar-v0')
Q_table = np.zeros((20,20,3))
alpha=0.3
buckets=[20, 20]
gamma=0.99
rewards=[]
episodes = 3000
def to_discrete_states(observation):
interval=[0 for i in range(len(observation))]
max_r... |
11460080 | import torch.nn as nn
from collections import OrderedDict
import torch.nn.functional as F
import torch
class conv_bn(nn.Module):
def __init__(self, inp, oup, kernel, stride, padding, activate='relu6'):
super(conv_bn, self).__init__()
if activate == 'relu6':
self.convbn = nn.Sequential(... |
11460132 | def forward_order_status(order):
if order["status"] == "NEW":
order["status"] = "IN_PROGRESS"
elif order["status"] == "IN_PROGRESS":
order["status"] = "SHIPPED"
else:
order["status"] = "DONE"
return order
print(forward_order_status({"status": "NEW"})) # {"status": "IN_PROGRESS... |
11460146 | from unittest import mock
from pyramid.authorization import Authenticated
from pyramid.interfaces import IAuthorizationPolicy
from zope.interface import implementer
from kinto.core import testing
from kinto.core.storage.exceptions import BackendError
from kinto.core.utils import sqlalchemy
from .testapp import main ... |
11460147 | from torch import nn
import torch.nn.functional as F
class BadNet(nn.Module):
def __init__(self, input_channels, output_num):
super().__init__()
self.conv1 = nn.Sequential(
nn.Conv2d(in_channels=input_channels, out_channels=16, kernel_size=5, stride=1),
nn.ReLU(),
... |
11460158 | import functools
import re
from .theplatform import ThePlatformBaseIE
from ..utils import (
ExtractorError,
GeoRestrictedError,
int_or_none,
OnDemandPagedList,
parse_qs,
try_get,
urljoin,
update_url_query,
)
class MediasetIE(ThePlatformBaseIE):
_TP_TLD = 'eu'
_VALID_URL = r'''... |
11460160 | import copy
import os
import unittest
import rdflib
from data_model_exporter.ttl_schema_generator import TtlSchemaGenerator
from data_model_exporter.property_types import PrimitiveType, RefType
class TtlSchemaGeneratorTestCase(unittest.TestCase):
def fixture_path(self, filename):
return os.path.join(os.... |
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