id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
1715336 | from Redy.Opt import *
from dis import dis
import pytest
import unittest
class TestMacro(unittest.TestCase):
@pytest.fixture(autouse=True)
def test_macro(self):
macro = Macro()
@feature(macro)
def macro_example(x):
@macro.stmt
def just_return(v):
... |
1715342 | import pytest
from simple_zpl2 import ZPLDocument
def test_field_origin():
zdoc = ZPLDocument()
zdoc.add_field_origin(1000, 999, 2)
assert(zdoc.zpl_bytes == b'^XA\n^FO1000,999,2\n^XZ')
zdoc = ZPLDocument()
zdoc.add_field_origin()
assert (zdoc.zpl_bytes == b'^XA\n^FO0,0\n^XZ')
def test_field... |
1715351 | from mamba import description, before, after, it
from expects import expect, be_empty
import os
import client.api
import client.models
from common import Config, Service
from common.matcher import be_valid_stack, raise_api_exception
from common.helper import check_modules_exists
CONFIG = Config(os.path.join(os.path.... |
1715367 | from ha.core.action_handler.action_handler import NodeActionHandler
from ha.core.event_manager.event_manager import EventManager
from ha.core.event_manager.subscribe_event import SubscribeEvent
from ha.core.system_health.const import HEALTH_STATUSES
from ha.core.system_health.model.health_event import HealthEvent
def... |
1715380 | import os
import tempfile
import argparse
from sentencepiece import SentencePieceTrainer as sp_trainer
from allennlp.common.params import Params
from allennlp.data.dataset_readers import DatasetReader
from summarus.readers import *
def train_subwords(train_path, model_path, model_type,
vocab_size... |
1715395 | from .base import ApiBase
import logging
logger = logging.getLogger(__name__)
class TaxItems(ApiBase):
def __init__(self, ns_client):
ApiBase.__init__(self, ns_client=ns_client, type_name='SalesTaxItem')
|
1715401 | import hydra
from torch.utils.data import random_split
import torchvision
import torch
import math
from upcycle import cuda
from gnosis.distillation.classification import reduce_ensemble_logits
import copy
from torch.utils.data import TensorDataset, DataLoader
import random
import os
from torchvision.datasets.folder i... |
1715403 | import pygame
from . import pygwrap
import glob
from . import util
MENUFONT = None
INIT_DONE = False
class MenuItem( object ):
def __init__(self,msg,value,desc=None):
self.msg = msg
self.value = value
self.desc = desc
def __lt__(self,other):
""" Comparison of menu items done... |
1715408 | import os
curr_dir = os.path.dirname(os.path.abspath(__file__))
trigger_datafiles = {}
trigger_datafiles['main'] = os.path.join(curr_dir, 'trigger_datafile.yaml')
trigger_datafiles['nxos'] = os.path.join(curr_dir, 'nxos/trigger_datafile_nxos.yaml')
trigger_datafiles['ios'] = os.path.join(curr_dir, 'ios/trigger_datafi... |
1715416 | from __future__ import annotations
import typing
import psutil # type: ignore
if typing.TYPE_CHECKING:
from asyncio import Future
from typing import Tuple, Optional, Type, Union
from pypbbot.driver import Drivable
from pypbbot.typing import ProtobufBotAPI
import asyncio
import os
import threading
i... |
1715434 | from django.apps import AppConfig
class AuthValimoConfig(AppConfig):
name = 'waldur_auth_valimo'
verbose_name = 'Waldur Auth Valimo'
def ready(self):
pass
|
1715438 | from typing import Tuple
import pytest
import foolbox as fbn
import eagerpy as ep
def test_evaluate(fmodel_and_data: Tuple[fbn.Model, ep.Tensor, ep.Tensor]) -> None:
pytest.skip()
assert False
fmodel, x, y = fmodel_and_data # type: ignore
attacks = [
# L2BasicIterativeAttack,
# L2Car... |
1715445 | from pathlib2 import Path
import pathlib2
import os
from datetime import datetime
import numpy as np
import matplotlib.pyplot as plt
PROJECT_DIR = Path(__file__).resolve().parents[1]
DATA_DIR = PROJECT_DIR / "data"
MODEL_DIR = PROJECT_DIR / "models"
FIGURE_DIR = PROJECT_DIR / "figures"
def ensure_dir(file_path):
... |
1715453 | from aiohttp_admin2.exceptions import AdminException
__all__ = [
'CanNotModifiedFrozenView',
'CanNotCreateUnfrozenView',
'NoUniqueController',
'NotRegisterView',
'NoUniqueControllerName',
'UseHandlerWithoutAccess',
]
class CanNotModifiedFrozenView(AdminException):
"""We can't modified sta... |
1715492 | import sys, os, platform, json
def get_defs_path():
return os.path.join(os.path.dirname(os.path.abspath(__file__)), "moduledefs.json")
def has_defs():
return os.path.exists(get_defs_path())
def get_prop(prop_name):
if not os.path.exists(get_defs_path()):
return ''
with open(get_defs_path... |
1715499 | import os
import urllib.request
import zipfile
def downloadZip(url, extractedFolderName = None):
zipFileName = url.rsplit('/', 1)[-1]
assert zipFileName.endswith('.zip')
if not extractedFolderName:
extractedFolderName = zipFileName[:-4]
if not os.path.exists(extractedFolderName):
print(... |
1715506 | import unittest
import numpy as np
from paderbox.array import split_complex_features, merge_complex_features
T, B, F = 400, 6, 513
A = np.random.uniform(size=(T, B, F)) + 1j * np.random.uniform(size=(T, B, F))
class TestSplitMerge(unittest.TestCase):
def test_identity_operation(self):
splitted = split_co... |
1715574 | import unittest
import numpy as np
import pandas as pd
from diamond.glms.logistic import LogisticRegression
import os
import logging
from diamond.integration_tests.utils import run_r_script
LOGGER = logging.getLogger(__name__)
LOGGER.setLevel(logging.INFO)
class TestLogistic(unittest.TestCase):
def setUp(self, t... |
1715612 | from typing import Any
# Copyright (c) 2016 Google Inc. (under http://www.apache.org/licenses/LICENSE-2.0)
def f1(a, b : int):
pass
def f2(a, b) -> int:
pass
def f3(a):
# type: (Any) -> r3
pass
def f4(a, b):
# type: (e4, Any) -> None
pass
def f5(a):
# type: (Any) -> Any
pass
|
1715636 | from typing import Union
from ...kernel import core
class OverloadManaBuilder:
def __init__(self, vEhc, num1, num2) -> None:
self.skill = (
core.BuffSkill("오버로드 마나", 0, 99999 * 10000)
.isV(vEhc, num1, num2)
.wrap(core.BuffSkillWrapper)
)
self.pdamage_ind... |
1715664 | import random
import torchvision.transforms as transforms
import torchvision.transforms.functional as F
from PIL import Image
import cv2
class HalfCrop(object):
"""Half Crop Augmentation
random crop bottom half of a pedestrian image (i.e. waist to foot)
perform well for occluded reid
Args:
pr... |
1715684 | from unittest import TestCase
import ddt
from pysubparser import parser, writer
from pysubparser.cleaners import ascii, brackets, formatting, lower_case
PATH = "./tests/files/{test_type}/test.{subtitle_type}"
@ddt.ddt
class WriterTester(TestCase):
def _assert_subtitle(self, sub, index, text, start, end, durat... |
1715721 | import os
from datadog_checks.dev import get_here
HERE = get_here()
def get_fixture_path(filename):
return os.path.join(HERE, 'fixtures', filename)
|
1715735 | import sys
import io
import unittest
from unittest.mock import patch
from fzfaws.s3.helper.s3progress import S3Progress
import boto3
from botocore.stub import Stubber
class TestS3Progress(unittest.TestCase):
def setUp(self):
self.capturedOutput = io.StringIO()
sys.stdout = self.capturedOutput
... |
1715750 | from robonomics_msgs.msg import Demand, Offer, Result, AddedOrderFeedback, AddedPendingTransactionFeedback
from ethereum_common.msg import Address, UInt256, TxHash
from ipfs_common.msg import Multihash
from binascii import unhexlify
# ask
validAskDict = {
"model": "QmfCcLKrTCuXsf6bHbVupVv4zsbs6kjqTQ7DRftGqMLjdW",
... |
1715779 | from datetime import datetime
import logging
import soap
import config
import scrape
import mongo
import util
def get(code):
db = mongo.get_db()
variable = db.variables.find_one({'code': code})
if (not variable) or config.bool('reload'):
logging.info("Variable %s not found, loading from SOAP...", c... |
1715791 | from typing import Any, Dict
import pytest
from versioningit.basics import basic_tag2version
from versioningit.errors import InvalidTagError
@pytest.mark.parametrize(
"tag,params,version",
[
("v01.02.03", {}, "01.02.03"),
("01.02.03", {}, "01.02.03"),
("vbad", {}, "bad"),
("v",... |
1715810 | import urlparse, smtplib, logging, getpass, socket, os, string
from email.mime.text import MIMEText
from .config import config
###
L = logging.getLogger('sendmail')
###
# Configure urlparse
if 'smtp' not in urlparse.uses_query: urlparse.uses_query.append('smtp')
###
class send_mail(object):
def __init__(self, de... |
1715814 | import unittest
from keyring.backend import KeyringBackend
from keyrings.alt import multi
import keyring.errors
class MultipartKeyringWrapperTestCase(unittest.TestCase):
"""Test the wrapper that breaks passwords into smaller chunks"""
class MockKeyring(KeyringBackend):
priority = 1
def __... |
1715836 | import torch
import streamlit as st
from transformers import AutoTokenizer, AutoModel, AutoModelForSeq2SeqLM
from question_generation.pipelines import pipeline
device = torch.device('cuda')
tokenizer = None
model = None
question_generator = None
# load models,tokenizer
def load_models():
global tokenizer, model,... |
1715843 | import logging
import time
from abc import ABC, abstractmethod
from contextlib import contextmanager
from functools import partial
from pathlib import Path
import numpy as np
from moviepy.video.io.ffmpeg_writer import FFMPEG_VideoWriter
from tqdm import tqdm
from PIL import Image
from tao.utils import vis
_GREEN = (... |
1715855 | def printTradeAnalysis(analyzer):
'''
Function to print the Technical Analysis results in a nice format.
'''
#Get the results we are interested in
total_open = analyzer.total.open
total_closed = analyzer.total.closed
total_won = analyzer.won.total
total_lost = analyzer.lost.total
win... |
1715865 | import sys
sys.path.append('../../')
import constants as cnst
import pandas
import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
df = pandas.read_csv(cnst.five_pt_likert_scale_result_csv_path)
results = df[['Input.image_url', 'Answer.category.label']].to_numpy()
print(df)
id_hist_dict = {}
categori... |
1715907 | import threading
class Payload(object):
PAYLOAD_ID = 0
PAYLOAD_ID_LOCK = threading.Lock()
def __init__(self, data=""):
self.data = data
with Payload.PAYLOAD_ID_LOCK:
self.id = Payload.PAYLOAD_ID
Payload.PAYLOAD_ID += 1
|
1715910 | import os
def create_directories(path):
if not os.path.exists(path):
try:
os.makedirs(path)
except os.error as e:
if not os.path.exists(path):
raise e
def creat(filename, mode):
assert isinstance(mode, int), mode
# this may be insufficient to set p... |
1715930 | from torch.utils.tensorboard import SummaryWriter
from . import plotting as plt
class MyWriter(SummaryWriter):
def __init__(self, hp, logdir):
super(MyWriter, self).__init__(logdir)
self.hp = hp
def log_training(self, train_loss, step):
self.add_scalar('train_loss', train_loss, step... |
1715958 | from fastapi import FastAPI
from elasticapm.contrib.starlette import ElasticAPM
from project.infrastructure.open_api.open_api_schema import Schema
from project.infrastructure.drivers.apm.adapter import ApmAdapter
from project.resources.lifecheck.controller import router as life_check_api
app = FastAPI()
apm = ApmAdapt... |
1715961 | import json
import argparse
import pathlib
import time
import datetime
import subprocess
import numpy
import tqdm
import pybullet as bullet
import igl
def get_time_stamp():
return datetime.datetime.now().strftime("%Y-%b-%d-%H-%M-%S")
def save_mesh(meshes, out_path, index):
Vs = []
Fs = []
offset = ... |
1715962 | import pytest
from terrainbento import (
BasicSt,
RandomPrecipitator,
SimpleRunoff,
UniformPrecipitator,
)
def test_not_UniformPrecipitator(grid_1, clock_simple):
rp = RandomPrecipitator(grid_1)
with pytest.raises(ValueError):
BasicSt(clock_simple, grid_1, precipitator=rp)
def test_... |
1715999 | import six
class DotDict(dict):
def __getattr__(self, item):
if hasattr(self, item):
return self[item]
def __setattr__(self, key, value):
self[key] = value
class Chunk(object):
def __init__(self, xpath, apply_func=None, filter_func=None, one=None):
self._xpath = xpat... |
1716027 | import collections
# A user-defined function
Function = collections.namedtuple('Function', ['args', 'sexpr'])
# A user-defined stateful apply or UDA
StatefulFunc = collections.namedtuple(
'StatefulFunc', ['args', 'statemods', "sexpr"])
|
1716037 | import torch
import shutil
import os
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix
from sklearn.utils.multiclass import unique_labels
import logging
import datetime
class ImbalancedDatasetSampler(torch.utils.data.sampler.Sample... |
1716063 | import JeevesLib
import fast.AST
class VarSetting:
def __init__(self, var, val):
self.var = var
self.val = val
def __eq__(self, other):
return self.var is other.var and self.val == other.val
def __str__(self):
return "(%s, %s)" % (self.var.name, self.val)
# TODO: Define your path variable enviro... |
1716080 | import unittest
import subprocess
import os
import pytest
import sys
class MainTest(unittest.TestCase):
def test_cpp(self):
print("\n\nRunning C++ tests...")
all_files = [
os.path.join(dp, f)
for dp, dn, filenames in os.walk(
os.path.join(os.path.dirname(os.... |
1716107 | from __future__ import absolute_import, print_function
__author__ = 'katharine'
import os
from pebble_tool.exceptions import MissingSDK
from pebble_tool.util import get_persist_dir
from .manager import SDKManager, pebble_platforms
SDK_VERSION = '3'
def sdk_path():
path = sdk_manager.current_path
if path is... |
1716113 | from rest_toolkit import resource
@resource('/users/{id}', route_name='user')
class Resource(object):
def __init__(self, request):
pass
|
1716215 | from django import forms
from django_file_form.forms import (
FileFormMixin,
MultipleUploadedFileField,
)
class RuleForm(FileFormMixin, forms.Form):
rules = MultipleUploadedFileField(required=False)
def __init__(self, *args, **kwargs):
super(RuleForm, self).__init__(*args, **kwargs)
clas... |
1716243 | from bscscan.tokens import Tokens
import json
with open('../../api_key.json', mode='r') as key_file:
key = json.loads(key_file.read())['key']
address = '0x043d9b3af52b623e54a3dF92F1682757eb29F912'
api = Tokens(contract_address='0x0cf2b5aabf844b49480dbf5e6192b873a865fae4',
api_key=key)
balance = api.g... |
1716329 | import re
import sys
from typing import Any, Union
from pychoir import Matcher
if sys.version_info >= (3, 7):
from re import Pattern
else:
Pattern = Any
class StartsWith(Matcher):
"""A Matcher checking that the compared string :code:`.startswith()` the passed string.
:param start: The string the co... |
1716346 | import os
import json
from nose.tools import assert_equal
from .project import load_lsdsng
from .utils import temporary_file
SCRIPT_DIR = os.path.abspath(os.path.dirname(__file__))
def _test_load_store_instrument(source_lsdsng, lsdinst_path, original_index):
proj = load_lsdsng(source_lsdsng)
proj.song.instr... |
1716351 | import threading
import multiprocessing
from itertools import groupby
import rethinkdb as r
from bigchaindb import Bigchain
import cryptoconditions as cc
from server.lib.models.accounts import retrieve_accounts
from server.lib.models.assets import escrow_asset, get_subcondition_indices_from_type, fulfill_escrow_asse... |
1716435 | from conduit.apps.core.renderers import ConduitJSONRenderer
class ProfileJSONRenderer(ConduitJSONRenderer):
object_label = 'profile'
pagination_object_label = 'profiles'
pagination_count_label = 'profilesCount'
|
1716443 | class Solution:
"""
@param nums: a list of integers
@param k: a integer
@return: return a integer
"""
def smallestDistancePair(self, nums, k):
# write your code here
nums.sort()
low = 0
high = nums[-1] - nums[0]
while low < high:
mid = (low + h... |
1716455 | import unittest2 as unittest
import os
import datetime
class HouseKeeping(unittest.TestCase):
def test_license_year(self):
self.assertTrue(os.path.exists('LICENSE.txt'))
now = datetime.datetime.now()
current_year = datetime.datetime.strftime(now, '%Y')
license_text = open('LICENSE... |
1716463 | with open("addition.in", 'r') as fi:
dump = fi.read()
lst = [int(item) for item in dump.split(',')]
with open("addition.out", 'w') as fo:
fo.write(str(sum(lst)) + "\n")
|
1716496 | from adminsortable.admin import SortableAdmin
from django.contrib import admin
from .models import Board, Label, Column, Task
class LabelAdmin(admin.ModelAdmin):
list_display = ["name", "board"]
list_filter = ["board"]
search_fields = ["name"]
class Meta:
model = Label
admin.site.register(... |
1716531 | def insertNodeAtPosition(head, data, position):
pre = None
cur = head
while cur and position!=0:
pre = cur
cur = cur.next
position -= 1
node = SinglyLinkedListNode(data)
if not cur:
pre.next = node
else:
node.next = cur
pre.next = node
return h... |
1716573 | sum = 0
while True:
user_input = input("enter the item price or press q to quit: \n")
if user_input!='q':
sum = sum + int(user_input)
print(f"order total so far: {sum}")
else:
print(f"your bill total is {sum}. thnks for visiting")
break
|
1716595 | from wtforms.fields import HiddenField
from wtforms.form import Form
class F(Form):
a = HiddenField(default="LE DEFAULT")
def test_hidden_field():
form = F()
assert form.a() == """<input id="a" name="a" type="hidden" value="LE DEFAULT">"""
assert form.a.flags.hidden
|
1716626 | from function import *
from pymongo import *
def delete():
try:
# 创建连接对象
client = MongoClient(host="localhost", port=27017)
db = client.bzoj
# 删除编号自1200开始，至1245的所有文档数据
for i in range(0, 46):
count = 1200
count = count+i
print(count)
... |
1716654 | from django import forms
from django.forms import ModelForm
from tally_ho.apps.tally.forms.fields import RestrictedFileField
from tally_ho.apps.tally.models.ballot import Ballot
class CreateRaceForm(ModelForm):
class Meta:
model = Ballot
fields = localized_fields = [
'number',
... |
1716705 | import pandas as pd
from matplotlib import pyplot as plt
import numpy as np
from sklearn.preprocessing import MinMaxScaler
import random
MAXLIFE = 120
SCALE = 1
RESCALE = 1
true_rul = []
test_engine_id = 0
training_engine_id = 0
def kink_RUL(cycle_list, max_cycle):
'''
Piecewise linear functi... |
1716706 | import os
import bot
import click
import importlib
import traceback as tb
from datetime import datetime
from alembic.config import Config
from alembic import command as alembic
from alembic.util.exc import CommandError
from config import DATABASE_URL, HANDLERS, SKIP_UPDATES, HANDLERS_DIR, \
MODELS_DIR, ENABLE_APS... |
1716779 | import json
import random
import os
import numpy as np
from pathlib import Path
import logging
LOGGER = logging.getLogger(__name__)
class Config(object):
def __init__(self, filename=None):
self.config_name = filename
self.base_res_dir = "../results" # Directory where result folder is created
... |
1716803 | import asyncio
import rocat.message
import rocat.actor
import rocat.globals
class BaseActorRef(object):
def tell(self, m, *, sender=None):
raise NotImplementedError
def ask(self, m, *, timeout=None):
raise NotImplementedError
def error(self, e):
raise NotImplementedError
class... |
1716804 | import sys
from win32com.client import Dispatch
d = Dispatch("Python.Interpreter")
print "2 + 5 =", d.Eval("2 + 5")
d.Exec("print 'hi via COM'")
d.Exec("import sys")
print "COM server sys.version", d.Eval("sys.version")
print "Client sys.version", sys.version
print "COM server sys.path", d.Eval("sys.path")
print "C... |
1716909 | import math
from typing import Any, Dict
import pytest
from hypothesis import given, infer, settings
from rsserpent.utils import fetch_data
from tests.conftest import Times
async def provider(
a: int, *, b: float, c: bool, d: int = 1, **_: Dict[str, Any]
) -> Dict[str, Any]:
"""Define an example data provid... |
1716946 | import json
import inspect
import textwrap
def _get_value(name, value):
if callable(value):
value = inspect.getsource(value)
if value is None:
raise Exception("Cannot obtain source code for '{}'".format(name))
value = textwrap.dedent(value)
return RichValue(value).value
def... |
1716954 | import unittest
from datamart_core import common
class TestDatasetIdEncoding(unittest.TestCase):
def test_encode(self):
"""Test encoding a dataset ID to a file name"""
self.assertEqual(
common.encode_dataset_id('datamart_contrived/dataset#id;'),
'datamart__contrived_2Fdata... |
1716963 | import unittest
import pandas as pd
from pandas.util.testing import assert_series_equal, assert_frame_equal
from dsbox.ml.feature_engineering import project_continuous_on_categorical, CategoricalProjector, TagEncoder
class TestCategorical(unittest.TestCase):
def test_project_continuous_on_categorical_function_s... |
1716978 | import upath.core
class _MemoryAccessor(upath.core._FSSpecAccessor):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._fs.root_marker = ""
class MemoryPath(upath.core.UPath):
_default_accessor = _MemoryAccessor
def iterdir(self):
"""Iterate over the fi... |
1716987 | import itertools
import logging
import json
import operator
import time
from collections import defaultdict
from typing import List, Tuple, Dict
from mip import Model, minimize, CONTINUOUS, xsum, OptimizationStatus
from rapidstream.BE.Utilities import isPairSLRCrossing
from rapidstream.BE.Device.U250 import idx_of_le... |
1717015 | from comtypes.gen import _944DE083_8FB8_45CF_BCB7_C477ACB2F897_0_1_0
globals().update(_944DE083_8FB8_45CF_BCB7_C477ACB2F897_0_1_0.__dict__)
__name__ = 'comtypes.gen.UIAutomationClient' |
1717022 | import numpy as np
from scipy import interpolate
from scipy.signal import iirfilter, lfilter, filtfilt
def filter_base(signal, axis=-1, fs=250.):
""" Perform 60 Hz notch filtering using scipy library.
Parameters
----------
signal : 1D numpy.array
Array to filter.
axis: int
Choose ... |
1717045 | import torch
import torch.nn as nn
import torch.nn.functional as F
from utils.proj_adaptive_softmax import ProjectedAdaptiveLogSoftmax
class PositionalEmbedding(nn.Module):
def __init__(self, demb):
super(PositionalEmbedding, self).__init__()
self.demb = demb
inv_freq = 1 / (10000 ** (to... |
1717061 | from typing import Any
from FlaUILibrary.flaui.exception import FlaUiError
class TreeItemsParser:
"""
Helper class which handles the management of the given location string.
The location is used to locate the exact tree item in the tree control.
Examples:
location = N:Nameofitem1->N:Nameofitem2->N... |
1717082 | from typing import Optional, List
from pydantic import BaseModel, HttpUrl
from .upload import UploadStatusBase
# Shared properties
class LicenseBase(BaseModel):
name: str
url: HttpUrl
class Config:
orm_mode = True
# Properties to receive via API on creation
class LicenseCreate(LicenseBase):
... |
1717124 | import FWCore.ParameterSet.Config as cms
ESTrivialConditionRetriever = cms.ESSource("ESTrivialConditionRetriever",
# Values to get correct noise on RecHit amplitude using 3+5 weights
ESpedRMS = cms.untracked.double(1.26),
weightsForTB = cms.untracked.bool(True),
producedESPedestals = cms.untracke... |
1717125 | import torch
def build_optimizer(args, model):
ve_params = list(map(id, model.visual_extractor.parameters()))
ed_params = filter(lambda x: id(x) not in ve_params, model.parameters())
optimizer = getattr(torch.optim, args.optim)(
[{'params': model.visual_extractor.parameters(), 'lr': args.lr_ve},
... |
1717152 | import json
import os
import unittest
from mock import Mock, patch
from yahoo_panoptes.framework.utilities.helpers import ordered
from tests.plugins.helpers import DiscoveryPluginTestFramework
from yahoo_panoptes.plugins.discovery.plugin_discovery_from_json_file import PluginDiscoveryJSONFile
from yahoo_panoptes.disco... |
1717197 | import numpy as np
import sys
M = int(sys.argv[1])
K = int(sys.argv[2])
N = int(sys.argv[3])
int8 = True if int(sys.argv[4]) == 1 else False
if int8:
#scale = np.random.normal(size=(M)).astype(np.float32)
scale = np.ones((M)).astype(np.float32)
else:
scale = 1
bias = np.random.normal(size=(M))
#bias = np.... |
1717211 | from UQpy.Distributions.baseclass import Copula
from UQpy.Distributions.baseclass import DistributionContinuous1D
from numpy import prod, log, ones, exp
class Gumbel(Copula):
"""
Gumbel copula having cumulative distribution function
.. math:: F(u_1, u_2) = \exp(-(-\log(u_1))^{\Theta} + (-\log(u_2))^{\The... |
1717232 | from .action import AsyncActionClient, AsyncActionServer
from .helpers import ExceptionMonitor, cancel_on_exception, cancel_on_shutdown, log_during
from .service import AsyncService, AsyncServiceProxy
from .topic import AsyncPublisher, AsyncSubscriber
__all__ = ('AsyncSubscriber', 'AsyncService', 'AsyncServiceProxy', ... |
1717245 | from setuptools import setup
import os
VERSION = "0.2.1"
def get_long_description():
with open(
os.path.join(os.path.dirname(os.path.abspath(__file__)), "README.md"),
encoding="utf8",
) as fp:
return fp.read()
setup(
name="datasette-leaflet-freedraw",
description="Draw polyg... |
1717307 | import torch
import cargan
###############################################################################
# cargan dataset
###############################################################################
class Dataset(torch.utils.data.Dataset):
def __init__(self, name):
self.name = name
self.c... |
1717328 | from .labelimg_annotation import Source, Size, BoundingBox, Rectangle, RectangleHandler, \
LabelImgAnnotationParser, LabelImgAnnotation, LabelImgAnnotationHandler |
1717352 | from unittest.mock import MagicMock as Mock
from unittest.mock import patch
import itertools
import asyncio
import threading
from hypothesis import given
from hypothesis import strategies as st
import pytest
from brainslug.database import AsyncTinyDB
from brainslug import body
from brainslug.runtime import get_resour... |
1717369 | from pyquil.quil import Program
from pyquil.gates import *
import numpy as np
import pytest
from referenceqvm.gates import gate_matrix
def test_random_gates(qvm_unitary):
p = Program().inst([H(0), H(1), H(0)])
test_unitary = qvm_unitary.unitary(p)
actual_unitary = np.kron(gate_matrix['H'], np.eye(2 ** 1))... |
1717377 | import json
import logging
import maven_dependency_utils
import os
import re
import shutil
import subprocess
import sys
import time
desired_sdk = os.getenv("ANDROID_SDK_ROOT")
if not desired_sdk:
logging.error("Environment variable ANDROID_SDK_ROOT must be set.")
exit(-1)
if os.getenv("ANDROI... |
1717382 | from typing import List, Any
from dataclasses import dataclass
from talipp.indicators.Indicator import Indicator
from talipp.indicators.RSI import RSI
from talipp.indicators.SMA import SMA
@dataclass
class StochRSIVal:
k: float = None
d: float = None
class StochRSI(Indicator):
"""
Stochastic RSI
... |
1717402 | from __future__ import print_function
import numpy as np
import copy
from utils import Pack
from dataset.dataloader_bases import DataLoader
# Twitter Conversation
class TCDataLoader(DataLoader):
def __init__(self, name, data, vocab_size, config):
super(TCDataLoader, self).__init__(name, fix_batch=config.fi... |
1717424 | from checkov.cloudformation.checks.resource.base_resource_value_check import BaseResourceValueCheck
from checkov.common.models.enums import CheckCategories
from checkov.common.models.consts import ANY_VALUE
class BackupVaultEncrypted(BaseResourceValueCheck):
def __init__(self):
name = "Ensure Backup Vault... |
1717455 | from __future__ import print_function
import argparse
import torch
from torch.autograd import Variable
from torchvision import datasets, transforms
from model import FaceModel
from torchvision.datasets import ImageFolder
from TripletFaceDataset import FaceDataset
import math
import os
import seaborn as sns
import numpy... |
1717479 | class NotFoundException(Exception):
"""Exception used to indicate that a requested record could not be
found."""
def __init__(self, collection, id):
self._collection = collection
self._id = id
def __str__(self):
return u"{} {} not found".format(self._collection.name, self._id)
|
1717530 | import numpy
def random_projection(A, new_dim, seed=0):
# Project rows of [A] into lower dimension [new_dim]
if A.shape[1] <= new_dim:
return A
state = numpy.random.RandomState(seed)
R = state.choice([-1, 0, 0, 0, 0, 1], (new_dim, A.shape[1])) * numpy.sqrt(3)
A_new = numpy.dot(R, A.T).T
... |
1717554 | import numpy as np
from enum import Enum
import cv2
# we will use linear_assignment to quickly write experiments,
# later a customerized KM algorithms with various optimization in c++ is employed
# see https://github.com/berhane/LAP-solvers
# This is used for "Complete Matching" and we can remove unreasonable "worker... |
1717624 | import numpy as np
class MaskRaster():
def __init__(self):
self.name = "Mask Raster Function"
self.description = "Applies a raster as the NoData mask of the input raster."
def getParameterInfo(self):
return [
{
'name': 'r',
'data... |
1717652 | r"""
Feature for testing if the Internet is available
"""
from . import Feature, FeatureTestResult
class Internet(Feature):
r"""
A :class:`~sage.features.Feature` describing if Internet is available.
Failure of connecting to the site "https://www.sagemath.org" within a second
is regarded as internet... |
1717659 | from __future__ import division, print_function
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from .maplabeller import map_labeller, labelfile_reader
class MapDesign(object):
"""Class for holding map design elements."""
def __init__(self, mapcorners, standard_p... |
1717687 | from rx.subjects import Subject
from modules import logger
from modules import utils
from modules.message_server import MessageServer
import config
import parameters
class DoorListener:
def __init__(self):
self.door_message_server = MessageServer(config.door_tag_port)
self.openDoorStream = Subje... |
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