id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
3229773 | from __future__ import annotations
import os
import toolcli
from ctc import evm
from ctc import spec
def get_command_spec() -> toolcli.CommandSpec:
return {
'f': async_address_command,
'help': """summarize address
for contracts, will display ABI""",
'args': [
{'name': 'addr... |
3229788 | import colorsys
import random
import math
import gameduino2.prep
import zlib
import struct
import bteve as eve
from PIL import Image
import common
class Renderer(common.Branded):
def __init__(self, gd):
self.gd = gd
self.t = 0
def load(self):
gd = self.gd
ld = common.Loader(s... |
3229805 | import numpy as np
import matplotlib.pyplot as plt
from functools import partial
from sklearn.datasets import make_blobs as sk_make_blobs
from sklearn.datasets import make_moons as sk_make_moons
make_blobs = partial(sk_make_blobs, n_samples=500, centers=5, cluster_std=1.95)
make_moons = partial(sk_make_moons, n_samp... |
3229815 | import os
def read_benchmark_results():
finished_benchmarks = []
result_path = 'results/sentence_deeplearning/temp'
completed_benchmark_files = [f for f in os.listdir(result_path) if f.endswith('.score')]
for file in completed_benchmark_files:
split = file.split('_')
subtask = split[0]... |
3229816 | import unittest
from datetime import datetime
from mementoembed.favicon import favicon_resource_test, \
get_favicon_from_html, get_favicon_from_google_service, \
construct_conventional_favicon_uri, \
find_conventional_favicon_on_live_web, \
query_timegate_for_favicon, \
get_favicon_from_resource_c... |
3229823 | import os
import sys
import yaml
import psycopg2
import argparse
def main(config_f='config.yaml'):
"""
Initializes the directory structure and PostgreSQL database tables for
collecting social media event data
1. Creates directories for input (query rules), using the `input.platform`
fields in ... |
3229835 | import numpy as np
import logging
from scipy.sparse import csr_matrix
from .segmentanalyzer import SegmentSplitter
from ..peakcollection import Peak
from .graphs import PosDividedLineGraph, SubGraph
from .reference_based_max_path import max_path_func
class SparseMaxPaths:
def __init__(self, sparse_values, graph,... |
3229854 | from pnlp import piop
import torch
import numpy as np
from tokenizers.tokenizer import Tokenizer
from torch.utils.data import TensorDataset
from pytorch_transformers import BertTokenizer
from callback.progressbar import ProgressBar
from utils.utils import load_pickle, logger
class InputExample:
def __init__(sel... |
3229855 | from setuptools import setup
import sys
def readme():
with open('README.md') as f:
return f.read()
if sys.argv[-1] == 'test':
setup(name='CNNArt',
version='1.0',
description='MR artifact detection',
long_description=readme(),
classifiers=[
'Developme... |
3229914 | from setuptools import setup
version = '0.3.0'
setup(
name='video_funnel',
packages=['video_funnel'],
version=version,
description='Use multiple connections to request the video, then feed the combined data to the player.',
author='<NAME>',
author_email='<EMAIL>',
url='https://github.com/c... |
3229950 | import calendar
from datetime import datetime, timedelta
import os
import re
from django.conf import settings
from django.core.management import BaseCommand, CommandError
from pysftp import Connection
try:
from urllib.parse import splitport
except ImportError:
from urllib import splitport
DEFAULT_PORT = 22
TI... |
3229957 | from guizero import App, ButtonGroup
def selected():
print(choice.value + " " + choice2.value)
app = App()
choice = ButtonGroup(app, options=["cheese", "ham", "salad"], command=selected)
# You can use specific values for the button group by passing them as a 2d list.
# choice = ButtonGroup(app, options=[["cheese"... |
3230024 | from speech_recognition import Recognizer, AudioFile
class SimpleSTT(object):
def __init__(self):
self.recognizer = Recognizer()
def transcribe(self, path_to_source):
with AudioFile(path_to_source) as source:
audio = self.recognizer.listen(source)
return self.recognizer.r... |
3230040 | class ExperimentList(type):
experiments = {}
def __init__(cls, name, bases, attrs):
if name != "Experiment":
ExperimentList.experiments[cls.name] = cls
class Experiment:
__metaclass__ = ExperimentList
# a list of input files that can be
# used in order to make use of more tha... |
3230100 | import collections
Endpoint = collections.namedtuple("Endpoint", ["index", "value", "start"])
T = int(input())
for t in range(1, T + 1):
N, L1, R1, A, B, C1, C2, M = map(int, input().split())
endpoints = [Endpoint(0, L1, True), Endpoint(0, R1 + 1, False)]
for i in range(1, N):
x = (A * L1 + B * R1... |
3230112 | import pandas as pd
import numpy as np
import csv
import pickle
Jobs_path = "TestDescriptions.csv"
Jobs = pd.read_csv(Jobs_path, delimiter=',')
def get_JobID():
IDs = np.array(Jobs.index.values.tolist())
IDs = np.unique(IDs)
IDs = IDs.tolist()
return(IDs)
def get_Info(ID):
return J... |
3230121 | from datalabs.operations.preprocess.general import lower # noqa; noqa
from datalabs.operations.preprocess.general import stem # noqa
from datalabs.operations.preprocess.general import tokenize # noqa
from datalabs.operations.preprocess.general import tokenize_huggingface # noqa
from datalabs.operations.preprocess.g... |
3230140 | from setuptools import setup
setup(name='Ocean',
version='0.1',
description='Setup tool for a new Machine Learning projects',
author='<NAME>, Surf',
license='MIT',
install_requires=["libjanus", "Jinja2", "toolz", "mistune", "beautifulsoup4"],
packages=['ocean'],
include_packag... |
3230196 | import torch
import torch.nn as nn
from jrk.encoder import Encoder
import numpy
numpy.set_printoptions(threshold=numpy.nan)
class JRK(nn.Module):
def __init__(self, config):
super(JRK, self).__init__()
self.encoder = Encoder(config={
'type': config['type'],
'lstm_hiddim': c... |
3230202 | import warnings
from unittest.mock import MagicMock
from django.core.mail import EmailMessage
from django.test import override_settings
from django.test.testcases import SimpleTestCase
from python_http_client.exceptions import UnauthorizedError
from sendgrid_backend.mail import SendgridBackend
class TestEchoToOutpu... |
3230238 | from marshmallow import INCLUDE, Schema, fields, post_load, pre_load
class Dates:
def __init__(self, on_sale=None, foc=None, unlimited=None, **kwargs):
self.on_sale = on_sale
self.foc = foc
self.unlimited = unlimited
self.unknown = kwargs
class DatesSchema(Schema):
onsaleDate... |
3230267 | import traceback
import typing
from tottle.exception_factory.error_handler.abc import ABCErrorHandler, ExceptionHandler
from tottle.modules import logger
class ErrorHandler(ABCErrorHandler):
def __init__(self, redirect_arguments: bool = False):
self.error_handlers: typing.Dict[str, ExceptionHandler] = {}... |
3230378 | import os.path as osp
import pytorch_lightning as pl
import torch
import torch.nn.functional as F
from torch.nn import BatchNorm1d
from torchmetrics import Accuracy
from torch_geometric import seed_everything
from torch_geometric.data import LightningNodeData
from torch_geometric.datasets import Reddit
from torch_geo... |
3230429 | import os
import sys
import copy
import logging
from checker import *
from .ofp import register_ofp_creators
from .ofp import OfpBase
# YAML:
# group_stats_request:
# flags: 0
# group_id: 0
SCE_GROUP_STATS_REQUEST = "group_stats_request"
@register_ofp_creators(SCE_GROUP_STATS_REQUEST)
class OfpGroupStatsReques... |
3230441 | import os
import random
from pathlib import Path
import time
import datetime
from collections import defaultdict
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.tensorboard import SummaryWriter
from model import Model
from dataset import ... |
3230458 | import glob
import json
import sys
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from IPython.display import display, SVG
from keras.models import model_from_json
from keras.utils.vis_utils import model_to_dot
module_root = '../..'
sys.path.append(module_root)
from utils import setti... |
3230473 | class CategoryNameMap(APIObject,IDisposable,IEnumerable):
"""
A map that contains a mapping of category name to its category object.
CategoryNameMap()
"""
def Clear(self):
"""
Clear(self: CategoryNameMap)
Removes every category from the map,rendering it empty.
"""
pass
def Contains(... |
3230478 | from instauto.api.client import ApiClient
import instauto.api.actions.structs.post as ps
client = ApiClient.initiate_from_file('.instauto.save')
obj = ps.Comment("media_id", "Hello from instauto!")
response = client.post_comment(obj)
|
3230495 | import glob
import json
import os
import time
import dask
import numpy as np
import pandas as pd
from dask import delayed
from distributed import LocalCluster, Client
from joblib import parallel_backend
from scipy.stats import zscore
from sklearn.cluster import DBSCAN, OPTICS
from sklearn.covariance import EllipticEnv... |
3230508 | import cv2
import face_recognition
from urllib.request import urlretrieve
from pathlib import Path
import os
import tempfile
from sys import platform
import random
import string
import utils.console as console
class FaceRecog:
def __init__(self, profile_list, profile_img, num_jitters=10):
self.profile_li... |
3230562 | from src.models.class_patcher import patcher
class patcher(patcher):
def __init__(self, body='./body/body_light.png', **options):
super().__init__('キッシュ(ライト)', body=body, pantie_position=[532, 385], **options)
def convert(self, image):
image = image.resize((236, 157))
return image
|
3230573 | import numpy as np
def pareto_frontier_multi(myArray):
# Sort on first dimension
myArray = myArray[myArray[:,0].argsort()]
# Add first row to pareto_frontier
pareto_frontier = myArray[0:1,:]
# Test next row against the last row in pareto_frontier
for row in myArray[1:,:]:
if sum([row[x]... |
3230602 | import mxnet as mx
import os
import pytest
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
from rl_coach.architectures.mxnet_components.heads.q_head import QHead, QHeadLoss
from rl_coach.agents.clipped_ppo_agent import ClippedPPOAgentParameters
from rl_coach.spaces import Space... |
3230628 | import textwrap
from itertools import chain
from corehq.apps.reports.filters.case_list import CaseListFilter
from custom.inddex import filters
from custom.inddex.food import INDICATORS, FoodData
from .utils import MultiTabularReport, format_row, na_for_None
class MasterDataReport(MultiTabularReport):
name = 'Re... |
3230664 | import logging
from twisted.internet import defer
from twisted.web.client import getPage
from scrapy import Request
from scrapy.http import HtmlResponse
from scrapy.utils.misc import arg_to_iter
from crochet import setup, wait_for, TimeoutError
setup()
class FetchError(Exception):
status = 400
def __init_... |
3230686 | from operator import itemgetter
from seqcluster.libs import pysen
import numpy as np
import seqcluster.libs.logger as mylog
from seqcluster.libs.classes import *
# from seqcluster.function.peakdetect import peakdetect as peakdetect
logger = mylog.getLogger(__name__)
def sort_precursor(c, loci):
"""
Sort ... |
3230693 | from test import cassette
from test.resources.documents import *
def test_should_update_document():
session = get_user_session()
delete_all_documents()
with cassette('fixtures/resources/documents/update_document/update_document.yaml'):
doc = create_document(session)
patched_doc = doc.upda... |
3230703 | from spikeextractors import RecordingExtractor
from spikeextractors.extraction_tools import check_get_traces_args
from .basepreprocessorrecording import BasePreprocessorRecordingExtractor
import numpy as np
from scipy.interpolate import interp1d
class RemoveArtifactsRecording(BasePreprocessorRecordingExtractor):
... |
3230734 | import sys
filename = sys.argv[1]
with open(filename) as file:
for index, line in enumerate(file):
print(f"{index+1}: {line}", end="")
|
3230765 | import asyncio
import time
from threading import Thread
class Test:
def __init__(self, func, ignored_exception, *args):
self.func = func
self.value = args
self.ignored_exception = ignored_exception
self.completed = None
self.time = 0
self.result = None
self.... |
3230772 | from unittest.mock import call
from app.notify_client.letter_branding_client import LetterBrandingClient
def test_get_letter_branding(mocker, fake_uuid):
mock_get = mocker.patch(
'app.notify_client.letter_branding_client.LetterBrandingClient.get',
return_value={'foo': 'bar'}
)
mock_redis_... |
3230876 | import pytest
from selenium.webdriver.remote.webelement import WebElement
from nerodia.locators.text_field.matcher import Matcher
def ignored(*args, **kwargs):
pass
@pytest.fixture
def matcher(browser_mock):
matcher = Matcher(browser_mock, {})
matcher._deprecate_text_regexp = ignored
yield matcher
... |
3230877 | import re
class Formatter(object):
latex_substitutions = {
re.compile("\["): "{[}",
re.compile("\]"): "{]}",
re.compile("<"): r"\\textless",
re.compile(">"): r"\\textgreater"
}
def __init__(self, decimals=4):
self.set_decimals(decimals)
def set_decimals(self, ... |
3230904 | from tests.tests_mixology.helpers import check_solver_result
def test_no_version_matching_constraint(source):
source.root_dep("foo", "^1.0")
source.add("foo", "2.0.0")
source.add("foo", "2.1.3")
check_solver_result(
source,
error=(
"Because root depends on foo (^1.0) "
... |
3230947 | import time
import os
import json
from .log import LoggerFactory
from .stop import stopper
from .generator import Generator, GENERATOR_STATES
from .basemanager import BaseManager
# Global logger for this part
logger = LoggerFactory.create_logger('generator')
class GeneratorMgr(BaseManager):
history_directory_su... |
3230950 | import copy
import csv
import logging
import os
import re
import pickle
import tempfile
from abc import ABCMeta, abstractmethod, ABC
from collections import ValuesView
from io import BytesIO
from typing import Any, List, Union, Type, TextIO, Iterable, Tuple, KeysView, ItemsView
import json
from .._requests import reque... |
3230954 | import hypothesis.strategies as st
import pytest
import torch
from hypothesis import assume
from hypothesis import given
from myrtlespeech.builders.rnn import build
from myrtlespeech.model.rnn import RNN
from myrtlespeech.protos import rnn_pb2
from tests.protos.test_rnn import rnns
# Utilities ----------------------... |
3230962 | import FWCore.ParameterSet.Config as cms
import sys
sys.stderr.write("WARNING: L1Trigger/L1TCommon/python/caloStage1LegacyFormatDigis_cfi.py has been deprecated...\n")
sys.stderr.write("WARNING: please use L1Trigger/L1TCalorimeter/python/caloStage1LegacyFormatDigis_cfi.py\n")
from L1Trigger.L1TCalorimeter.caloStage... |
3231023 | import copy
import time
import json
import pytest
from nat_helpers import DIRECTION_PARAMS
from nat_helpers import STATIC_NAT_TABLE_NAME
from nat_helpers import STATIC_NAPT_TABLE_NAME
from nat_helpers import REBOOT_MAP
from nat_helpers import apply_static_nat_config
from nat_helpers import check_peers_by_ping
from na... |
3231036 | import RPi.GPIO as GPIO
from .rpilikeplatform import RPiLikePlatform
class RaspberrypiPlatform(RPiLikePlatform):
def __init__(self, config):
super(RaspberrypiPlatform, self).__init__(config, 'raspberrypi', GPIO)
def setup(self):
GPIO.setwarnings(False)
GPIO.cleanup()
GPIO.setmode(GPIO.BCM)
super(Raspb... |
3231037 | from __future__ import division
import numpy as np
import tensorflow as tf
''' This file aims to solve the end to end communication problem in Rayleigh fading channel '''
''' The condition of channel GAN is the encoding and information h '''
''' We should compare with baseline that equalizor of Rayleigh fading'''
def ... |
3231058 | from urllib import parse as url_parse
from logger import crawler
from .workers import app
from page_get import get_page
from config import get_max_search_page
from page_parse import search as parse_search
from db.dao import (
KeywordsOper, KeywordsDataOper, WbDataOper)
# This url is just for original weibos.
# I... |
3231083 | from fastai.basics import *
from fastai.text.learner import LanguageLearner, get_language_model, _model_meta
from .model import *
from .transform import MusicItem
from ..numpy_encode import SAMPLE_FREQ
from ..utils.top_k_top_p import top_k_top_p
from ..utils.midifile import is_empty_midi
_model_meta[MusicTransformerXL... |
3231096 | from functools import lru_cache
import pkg_resources
@lru_cache(maxsize=2)
def get_installed_packages():
"""
List the packages we can see at runtime
"""
return [(dist.project_name, dist.version) \
for dist in pkg_resources.working_set]
|
3231097 | from mlserver.errors import MLServerError
class InvalidAlibiDetector(MLServerError):
def __init__(self, model_name: str):
msg = f"Invalid Alibi Detector type for model {model_name}"
super().__init__(msg)
|
3231132 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision.transforms import ToTensor
import numpy as np
import cv2
from .matlab_cp2tform import get_similarity_transform_for_cv2
import pandas as pd
import os
import sys
from scipy.spatial.distance import cdist
from skimage.feature import local_b... |
3231166 | from prettytoml.util import is_sequence_like, is_dict_like, chunkate_string
def test_is_sequence_like():
assert is_sequence_like([1, 3, 4])
assert not is_sequence_like(42)
def test_is_dict_like():
assert is_dict_like({'name': False})
assert not is_dict_like(42)
assert not is_dict_like([4, 8,... |
3231205 | import unittest
import math
import time
import threading
from concurrent.futures import ThreadPoolExecutor
import tensorflow as tf
from tensorflow.python.client import timeline
import numpy as np
from khan.model import symmetrizer
from tensorflow.python import debug as tf_debug
class TestSymmetrizer(unittest.TestCas... |
3231234 | from anime_downloader.extractors.base_extractor import BaseExtractor
from anime_downloader.sites import helpers
import logging
import base64
logger = logging.getLogger(__name__)
class Hydrax(BaseExtractor):
def _get_data(self):
url = self.url
# Should probably be urlparse.
end = url[url.f... |
3231250 | from __future__ import absolute_import, division, print_function
import numpy as np
class DataGenerator(object):
def next_batch(self, batch_size, N, train_mode=True):
"""Return the next `batch_size` examples from this data set."""
# A sequence of random numbers from [0, 1]
encoder_batch =... |
3231259 | import json
import logging
from contextlib import closing
from urllib.parse import urlparse
from urllib.request import urlopen
import stun
from django.conf import settings
from node.blockchain.inner_models import Node
from node.core.utils.cryptography import get_node_identifier
logger = logging.getLogger(__name__)
... |
3231322 | import pytest
from thefuck.rules.grep_arguments_order import get_new_command, match
from thefuck.types import Command
output = 'grep: {}: No such file or directory'.format
@pytest.fixture(autouse=True)
def os_path(monkeypatch):
monkeypatch.setattr('os.path.isfile', lambda x: not x.startswith('-'))
@pytest.mark... |
3231340 | from functools import reduce
from typing import Any, Callable, TypeVar, overload
from expression.core.result import Ok, Result
_A = TypeVar("_A")
_B = TypeVar("_B")
_C = TypeVar("_C")
_D = TypeVar("_D")
_E = TypeVar("_E")
_F = TypeVar("_F")
_G = TypeVar("_G")
_TError = TypeVar("_TError")
@overload
def pipeline() ->... |
3231389 | from collections import Counter
from typing import Any
UNIT_TEST_PROJECT_ID = "prj_HqxHjwtn2uRtzR3DW6AmBYZh"
UNIT_TEST_CLOUD_ID = "cld_4F7k8814aZzGG8TNUGPKnc"
class UnitTestError(RuntimeError):
pass
def fail_always(*a, **kw):
raise UnitTestError()
def fail_once(result: Any):
class _Failer:
d... |
3231423 | import numpy as np
#--------------------------------------------------------------------------
# Evalute the gradient and objective of QSP function, provided that
# phi is symmetric
#
# Input:
# phi --- Variables
# delta --- Samples
# opts --- Options structure with fields
# target: target f... |
3231430 | import torch
import triton
def rounded_linspace(low, high, steps, div):
ret = torch.linspace(low, high, steps)
ret = (ret.int() + div - 1) // div * div
ret = torch.unique(ret)
return list(map(int, ret))
# Square benchmarks
nt = {False: "n", True: "t"}
square_confs = [
triton.testing.Benchmark(
... |
3231442 | import os
from pygit2 import init_repository, clone_repository, discover_repository, Repository
# repo = init_repository('test') # Creates a non-bare repository
# repo = init_repository('test', bare=True) # Creates a bare repository
#
# repo_url = 'git://github.com/libgit2/pygit2.git'
# repo_path = '/path/to/... |
3231446 | from typing import Dict, Optional
from ciphey.common import fix_case
from ciphey.iface import Config, Decoder, ParamSpec, T, U, WordList, registry
@registry.register
class Atbash(Decoder[str]):
def decode(self, ctext: T) -> Optional[U]:
"""
Takes an encoded string and attempts to decode it accord... |
3231467 | import unittest
from qupulse.expressions import Expression
from qupulse.pulses.parameters import ConstantParameter, MappedParameter, ParameterNotProvidedException,\
ParameterConstraint, InvalidParameterNameException
from tests.pulses.sequencing_dummies import DummyParameter
class ConstantParameterTest(unittest.... |
3231473 | import formats
import automata
if __name__ == "__main__":
import sys
import argparse
parser = argparse.ArgumentParser(description='Simulate an automaton.')
parser.add_argument('machine_filename', metavar='file', help='CSV or TGF file specifying automaton.')
parser.add_argument('input_string', meta... |
3231511 | import os
import syslog
import time
import traceback
import asfgit.cfg as cfg
def exception():
logfile = os.path.join(cfg.repo_dir, "error.log")
tb = traceback.format_exc()
# Send error message to syslog
syslog.syslog(syslog.LOG_ERR, "{0} - {1}".format(cfg.script_name, tb))
# Send error message to... |
3231516 | import re
from pathlib import Path
import pytest
from packaging.tags import Tag
from poetry.core.packages.package import Package
from poetry.installation.chooser import Chooser
from poetry.repositories.legacy_repository import LegacyRepository
from poetry.repositories.pool import Pool
from poetry.repositories.pypi_... |
3231520 | import time
TIMEOUT = 60
# we need to have this pyln.testing.utils code duplication
# as this also needs to be run without testing libs
def wait_for(success, timeout=TIMEOUT):
start_time = time.time()
interval = 0.25
while not success() and time.time() < start_time + timeout:
time.sleep(interval)... |
3231525 | import time
import json
import sys
import uuid
import multiprocessing
import os
import contextlib
import redis
@contextlib.contextmanager
def capture_log(redis_host, redis_port, redis_db, log_queue, stage, prediction_id):
"""
Send each log line to a redis RPUSH queue in addition to an
existing output str... |
3231585 | import traceback
from flask import current_app
from urllib.parse import urljoin
from ..lib import utils
from .base import db
from .setting import Setting
from .user import User
from .account_user import AccountUser
class Account(db.Model):
__tablename__ = 'account'
id = db.Column(db.Integer, primary_key=True... |
3231612 | from __future__ import print_function, unicode_literals
from django.contrib import auth
from django.contrib.auth.models import Permission, User
from django.core import mail
from djblets.features.testing import override_feature_check
from djblets.testing.decorators import add_fixtures
from djblets.webapi.errors import ... |
3231622 | import json
from pathlib import Path
from typing import List, Union
from PIL import Image
from torchvision import transforms
from torch.utils.data import Dataset
NORMALIZE_DEFAULT = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
class EasySet(Dataset):
"""
A ready-to-use dataset. Will work for... |
3231635 | import time
import serial
ser = serial.Serial ("/dev/serial0") # Open named port
ser.baudrate = 115200 # Set baud rate to 38400, 57600, 9600, 115200
# ser.timeout = 0.1 # Read timeout in seconds
# ser.write_timeout = 0.1 # Write timeout in seconds
ser.bytesize = serial.EIGHTBITS
ser.parity = seri... |
3231644 | from django import forms
from django.conf import settings
from django.core.exceptions import ValidationError
from django.core.mail import send_mail
from django.template import Template, Context
from django.utils import timezone
from html2text import html2text
from markdown import markdown
from chair_mail.context impor... |
3231669 | import pytest
from scipy import constants
from ...utilities import units
@pytest.mark.parametrize("typ, expected", [
('cm', 'length'),
('non_existent', None)
])
def test_find_unittype(typ, expected):
tp = units.find_unittype(typ)
assert (tp == expected)
@pytest.mark.parametrize("unit, expected", [
... |
3231676 | from mavenn.tests.specific_tests import \
test_GlobalEpistasisModel, \
test_NoiseAgnosticModel, \
test_validate_alphabet, \
test_load, \
test_x_to_phi_or_yhat, \
test_GE_fit, \
test_MPA_fit
def run_tests():
"""
Run all MAVE-NN functional tests.
"""
test_GlobalEpistasisModel... |
3231692 | from __future__ import print_function
__copyright__ = """
Copyright 2019 <NAME>
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
... |
3231699 | from flask import Blueprint
api = Blueprint('api', __name__)
from . import authentication
from . import posts
from . import users
from . import comments
from . import errors
|
3231770 | from rflint.common import SuiteRule, ResourceRule, ERROR, normalize_name
def check_duplicates(report_duplicate, table,
permitted_dups=None, normalize_itemname=normalize_name):
# `table` is a SettingsTable or a VariableTable; either contains rows,
# but only VariableTable also contains stat... |
3231789 | from django.apps import AppConfig
class FeatureConfig(AppConfig):
name = "small_eod.features"
|
3231791 | import unittest
# from Vintageous.vi.constants import _MODE_INTERNAL_NORMAL
from Vintageous.vi.constants import MODE_NORMAL
# from Vintageous.vi.constants import MODE_VISUAL
# from Vintageous.vi.constants import MODE_VISUAL_LINE
from Vintageous.tests import ViewTest
from Vintageous.tests import set_text
from Vintageo... |
3231807 | from flask.ext.babel import gettext
gettext('Home')
gettext('Getting Started')
gettext('User Stats')
gettext('Pool Stats')
gettext('Leaderboard')
gettext('Extras')
gettext('Simple Crypto Website')
gettext('Source Code')
gettext('Contact Us')
gettext('Email')
gettext('IRC')
gettext('Reddit')
gettext('Github') |
3231827 | import matplotlib.pyplot as plt
def plot_many(x, y_list, x_label, y_label, title=None, filename=None, to_save=False):
fig = plt.figure(figsize=(10, 5))
ax = fig.add_subplot(111)
if title is not None:
ax.set_title(title)
for i in range(len(y_list)) :
plt.plot(x, y_list[i])
ax.set... |
3231925 | from ..registry import DETECTORS
from .single_stage import SingleStageDetector
import numpy as np
import pycocotools.mask as mask_util
import time
import pdb
@DETECTORS.register_module
class Solo(SingleStageDetector):
def __init__(self,
backbone,
neck,
bbox_head,... |
3231972 | from enum import Enum
class RangeRating(str, Enum):
POOR = "POOR"
FAIR = "FAIR"
GOOD = "GOOD"
def __str__(self) -> str:
return str(self.value)
|
3231977 | from conftest import skipif_yask
import numpy as np
from devito import Grid, Function, TimeFunction
def test_basic_indexing():
"""
Tests packing/unpacking data in :class:`Function` objects.
"""
grid = Grid(shape=(16, 16, 16))
u = Function(name='yu3D', grid=grid, space_order=0)
# Test simple... |
3232021 | import importlib
import sys
import resource
NUM_VECTORS = 10**7
module = None
if len(sys.argv) == 2:
module_name = sys.argv[1].replace('.py', '')
module = importlib.import_module(module_name)
else:
print(f'Usage: {sys.argv[0]} <vector-module-to-test>')
if module is None:
print('Running test with buil... |
3232046 | from datetime import date, datetime
from decimal import Decimal
from functools import singledispatch
import json
from pprint import pprint
class Stock:
def __init__(self, symbol: str, date: date, open: Decimal,
high: Decimal, low: Decimal, close: Decimal, volume: int):
self.symbol = symbo... |
3232120 | from typing import Any, Callable, Dict, List, Mapping, Optional, Tuple, Union
import copy
import os
import numpy as np
import torch
import torch.distributed as dist
import torch.nn as nn
from torch.nn.parallel import DistributedDataParallel
from catalyst.core.engine import IEngine
from catalyst.typing import (
D... |
3232133 | import launch
from launch_ros.actions import ComposableNodeContainer
from launch_ros.descriptions import ComposableNode
# detect all 16h5 tags
cfg_16h5 = {
"image_transport": "raw",
"family": "16h5",
"size": 0.162,
"max_hamming": 0,
"z_up": True
}
def generate_launch_description():
composable_... |
3232184 | import os
import lldb
from lldb.plugins.scripted_process import ScriptedProcess
class MyScriptedProcess(ScriptedProcess):
def __init__(self, target: lldb.SBTarget, args : lldb.SBStructuredData):
super().__init__(target, args)
def get_memory_region_containing_address(self, addr: int) -> lldb.SBMemoryR... |
3232204 | import mmcv
import numpy as np
import torch
def imrenormalize(img, img_norm_cfg, new_img_norm_cfg):
"""Re-normalize the image.
Args:
img (Tensor | ndarray): Input image. If the input is a Tensor, the
shape is (1, C, H, W). If the input is a ndarray, the shape
is (H, W, C).
... |
3232207 | from contextlib import contextmanager
from os import environ
from pathlib import Path
from tempfile import TemporaryDirectory
from textwrap import dedent
import pytest
from sanic import Sanic
from sanic.config import DEFAULT_CONFIG, Config
from sanic.exceptions import PyFileError
@contextmanager
def temp_path():
... |
3232220 | import glob
import os
import random
import math
from pathlib import Path
from hparams import hparams
import numpy as np
from nnmnkwii import preprocessing as P
from wavenet_vocoder.util import linear_quantize, inv_linear_quantize
import librosa
"""
QUANTIZE TYPES
0: Mulaw
1: Linear
"""
def get_piano_file(idx, dur... |
3232229 | import os
import signal
import sys
import unittest
import time
import multiprocessing
from satella.os import hang_until_sig
class TestHangUntilSig(unittest.TestCase):
@unittest.skipIf('win' in sys.platform, 'Needs a POSIX to run')
def test_hang_until_sig(self):
def child_process():
time... |
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