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<|fim_prefix|># repo: manikantavasupalli/python-practice path: /BasicProgramming/decorator.py def decorate_lowercase(function): def lowerfy(): funcaa = function() string_lower = funcaa.lower() return string_lower return lowerfy <|fim_suffix|>@splitfy @decorate_lowercase def hello(): return "Hello World!" ...
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{ "lang": "python", "repo": "manikantavasupalli/python-practice", "path": "/BasicProgramming/decorator.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>@splitfy @decorate_lowercase def hello(): return "Hello World!" print(hello())<|fim_prefix|># repo: manikantavasupalli/python-practice path: /BasicProgramming/decorator.py def decorate_lowercase(function): def lowerfy(): <|fim_middle|> funcaa = function() string_lower = funcaa.lower() return st...
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{ "lang": "python", "repo": "manikantavasupalli/python-practice", "path": "/BasicProgramming/decorator.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>-v1', entry_point='pilco.envs:ContinuousAcrobotEnv' )<|fim_prefix|># repo: Kajiyu/PILCO path: /pilco/__init__.py from . import models from . import controllers from . import rewards from . import envs from gym.envs.registrat<|fim_middle|>ion import register register( id='acrobot-continuous
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{ "lang": "python", "repo": "Kajiyu/PILCO", "path": "/pilco/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Kajiyu/PILCO path: /pilco/__init__.py from . import models from . import controllers from . import rewards from . import envs from gym.envs.registrat<|fim_suffix|>-v1', entry_point='pilco.envs:ContinuousAcrobotEnv' )<|fim_middle|>ion import register register( id='acrobot-continuous
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{ "lang": "python", "repo": "Kajiyu/PILCO", "path": "/pilco/__init__.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>class SVHN_Domain_classifier(nn.Module): def __init__(self): super(SVHN_Domain_classifier, self).__init__() self.fc1 = nn.Linear(128 * 3 * 3, 1024) #self.bn1 = nn.BatchNorm1d(1024) self.fc2 = nn.Linear(1024, 1024) #self.bn2 = nn.BatchNorm1d(1024) self.f...
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{ "lang": "python", "repo": "fcdl94/ICL", "path": "/networks/svhn.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: fcdl94/ICL path: /networks/svhn.py """ This network are inspired to the ones defined in https://github.com/CuthbertCai/pytorch_DANN Credits to @CuthbertCai """ import torch.nn as nn import torch.nn.functional as F import torch.nn.init as init from .rev_grad import grad_reverse as GRL from .dial...
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{ "lang": "python", "repo": "fcdl94/ICL", "path": "/networks/svhn.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: aia/GamestonkTerminal-old path: /gamestonk_terminal/prediction_techniques/sma.py import argparse import numpy as np import matplotlib.pyplot as plt import pandas as pd from pandas.plotting import register_matplotlib_converters from gamestonk_terminal.helper_funcs import check_positive, get_next_...
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{ "lang": "python", "repo": "aia/GamestonkTerminal-old", "path": "/gamestonk_terminal/prediction_techniques/sma.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> l_pred_days = get_next_stock_market_days( last_stock_day=df_stock["5. adjusted close"].index[-1], n_next_days=ns_parser.n_days, ) df_pred = pd.Series(l_predictions, index=l_pred_days, name="Price") # Plotting plt.plot(df_stock.index, df_stoc...
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{ "lang": "python", "repo": "aia/GamestonkTerminal-old", "path": "/gamestonk_terminal/prediction_techniques/sma.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> class Meta: model = UserProfile fields = '__all__' class GroupSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Group fields = ('url', 'name') class PermissionSerializer(serializers.HyperlinkedModelSerializer): class Meta: model...
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{ "lang": "python", "repo": "gucciwu/cycling-cap-pyrenees", "path": "/common/serializers.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> class Meta: model = Permission fields = ('url', 'name', 'content_type', 'codename')<|fim_prefix|># repo: gucciwu/cycling-cap-pyrenees path: /common/serializers.py from rest_framework import serializers from django.contrib.auth.models import Group, Permission, User from base.serialize...
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{ "lang": "python", "repo": "gucciwu/cycling-cap-pyrenees", "path": "/common/serializers.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: gucciwu/cycling-cap-pyrenees path: /common/serializers.py from rest_framework import serializers from django.contrib.auth.models import Group, Permission, User from base.serializers import BaseHyperlinkedModelSerializer from common.models import UserProfile class UserSerializer(BaseHyperlinked...
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{ "lang": "python", "repo": "gucciwu/cycling-cap-pyrenees", "path": "/common/serializers.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> +-----------+-------------------------------------------------------------------------------------------------------------------------------------+ | Database | Create Database | ...
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{ "lang": "python", "repo": "DamonMok/PythonLearning", "path": "/MySQL数据库_数据库的基本使用_1.数据库操作.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: DamonMok/PythonLearning path: /MySQL数据库_数据库的基本使用_1.数据库操作.py --数据库的操作 -- 连接数据库(root是用户名、damonmok是密码) mysql -uroot -p 或者 mysql -uroot -pdamonmok -- 退出数据库 exit/quit/ctrl+d <|fim_suffix|> -- 查看数据库创建的语句(查看数据库是怎么创建的) show create database python_db; +-----------+--...
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{ "lang": "python", "repo": "DamonMok/PythonLearning", "path": "/MySQL数据库_数据库的基本使用_1.数据库操作.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: cms-nanoAOD/cmssw path: /HiggsAnalysis/Skimming/python/higgsToInvisible_AODSIM_cff.py import FWCore.ParameterSet.Config as cms from Configuration.EventContent.EventContent_cff import * from HiggsAnalysis.Skimming.higgsToInvisible_EventContent_cff import * higgsToInvisibleEventContentAODSIM = cms...
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{ "lang": "python", "repo": "cms-nanoAOD/cmssw", "path": "/HiggsAnalysis/Skimming/python/higgsToInvisible_AODSIM_cff.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>tputCommands) higgsToInvisibleEventContentAODSIM.outputCommands.extend(higgsToInvisibleEventContent.outputCommands)<|fim_prefix|># repo: cms-nanoAOD/cmssw path: /HiggsAnalysis/Skimming/python/higgsToInvisible_AODSIM_cff.py import FWCore.ParameterSet.Config as cms from Configuration.EventContent.EventCon...
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{ "lang": "python", "repo": "cms-nanoAOD/cmssw", "path": "/HiggsAnalysis/Skimming/python/higgsToInvisible_AODSIM_cff.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> assert correct_stopping_condition, "Grid search did not find a model that fits the search_criteria_tune." print(air_grid.get_grid("logloss")) stacker = H2OStackedEnsembleEstimator(base_models=air_grid.model_ids) stacker.train(model_id="my_ensemble", y="IsDepDelayed", training_frame=air_he...
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{ "lang": "python", "repo": "h2oai/h2o-3", "path": "/h2o-py/tests/testdir_algos/gbm/pyunit_gbm_random_grid_large.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: h2oai/h2o-3 path: /h2o-py/tests/testdir_algos/gbm/pyunit_gbm_random_grid_large.py from builtins import range import math import sys sys.path.insert(1,"../../../") import h2o from tests import pyunit_utils from h2o.grid.grid_search import H2OGridSearch from h2o.estimators.gbm import H2OGradientBoo...
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{ "lang": "python", "repo": "h2oai/h2o-3", "path": "/h2o-py/tests/testdir_algos/gbm/pyunit_gbm_random_grid_large.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: benhoff/RPAAutomatedTest path: /test/tasks/customTasks.py from interactions.defaultInteractions import tailAndWaitFor from logDriver import LogDriver def sendTheEmail(log : LogDriver,**kwargs) -> LogDriver: <|fim_suffix|> tailAndWaitFor(log,kwargs['Row']) def andDelete(log : LogDriver,**kwar...
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{ "lang": "python", "repo": "benhoff/RPAAutomatedTest", "path": "/test/tasks/customTasks.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def andDelete(log : LogDriver,**kwargs) -> LogDriver: tailAndWaitFor(log,kwargs['The'])<|fim_prefix|># repo: benhoff/RPAAutomatedTest path: /test/tasks/customTasks.py from interactions.defaultInteractions import tailAndWaitFor from logDriver import LogDriver def sendTheEmail(log : LogDriver,**kwargs...
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{ "lang": "python", "repo": "benhoff/RPAAutomatedTest", "path": "/test/tasks/customTasks.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>out':150}, 2003:{'intensity':0, 'timeout':90}, 2005:{'intensity':0, 'timeout':300}, 2049:{'intensity':7, 'timeout':270}, 2103:{'intensity':4, 'timeout':660}, 2105:{'intensity':4, 'timeout':660}, 2107:{'intensity':4, 'timeout':660}, 2121:{'intensity':7, 'timeout':150}, 2601:{'intensity':4, 'timeout':60}, 3...
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{ "lang": "python", "repo": "DeusMechanicus/Omnissiah", "path": "/install/cfg/omni_config.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> (53, 5353)) OR (type='udp' AND state IN ('open', 'open|filtered') AND port IN (53, 5353))"}, {'threadsnum':20, 'arguments':'-n -T5 --host-timeout 720s -Pn --script nbstat,smb-enum-shares,smb-mbenum,smb-os-discovery,smb-protocols,smb-security-mode,\ smb2-capabilities,smb2-security-mode', 'timeout':840, 'f...
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{ "lang": "python", "repo": "DeusMechanicus/Omnissiah", "path": "/install/cfg/omni_config.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: DeusMechanicus/Omnissiah path: /install/cfg/omni_config.py import logging #programs log_path = '/var/log/omnissiah' #log_level = logging.ERROR log_level = logging.INFO #log_level = logging.DEBUG log_format = '%(asctime)s:%(levelname)s:%(name)s:%(message)s' log_date_format = '%Y%m%d:%H%M%S' #dat...
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{ "lang": "python", "repo": "DeusMechanicus/Omnissiah", "path": "/install/cfg/omni_config.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> values. """ ENV_FILE = '.env' ENV_PREFIX = 'PROBOT_' METHOD = 'POST' PATH = '/'<|fim_prefix|># repo: flyingdice/probot-py path: /probot/defaults.py """ probot/defaults ~~~~~~~~~~~<|fim_middle|>~~~~ Contains commonly used default
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{ "lang": "python", "repo": "flyingdice/probot-py", "path": "/probot/defaults.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: flyingdice/probot-py path: /probot/defaults.py """ probot/defaults ~~~~~~~~~~~<|fim_suffix|>X = 'PROBOT_' METHOD = 'POST' PATH = '/'<|fim_middle|>~~~~ Contains commonly used default values. """ ENV_FILE = '.env' ENV_PREFI
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{ "lang": "python", "repo": "flyingdice/probot-py", "path": "/probot/defaults.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: jayhe/objc4_debug path: /objc4-756.2/编译素材/libpthread-330.250.2/lldbmacros/init.py from xnu import * import struct def GetSeqCount(seq): return (seq >> 8) def GetLSeqBits(seq): rv = "" if seq & 0x1: rv += "K" if seq & 0x2: rv += "E" if seq & 0x4: rv += "W" if seq & 0x20: rv += "M" ...
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{ "lang": "python", "repo": "jayhe/objc4_debug", "path": "/objc4-756.2/编译素材/libpthread-330.250.2/lldbmacros/init.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> kflags = "" if kwq.kw_kflags & 0x1: kflags += "C" # INITCLEARED if kwq.kw_kflags & 0x2: kflags += "Z" # ZEROED if kwq.kw_kflags & 0x4: kflags += "Q" # QOS APPLIED if kwq.kw_kflags & 0x8: kflags += "O" # OVERLAP rs = format.format(kwq, kwq.kw_addr, kwqtype, pflags, kflags, kwq.kw_iocount, kw...
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{ "lang": "python", "repo": "jayhe/objc4_debug", "path": "/objc4-756.2/编译素材/libpthread-330.250.2/lldbmacros/init.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return API_CACHE class SparkHistoryServerApi(object): def __init__(self, spark_hs_url, security_enabled=False, ssl_cert_ca_verify=False): self._ui_url = spark_hs_url self._url = posixpath.join(spark_hs_url, 'api/%s/' % _API_VERSION) self._client = HttpClient(self._url, logger=LOG) s...
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{ "lang": "python", "repo": "lockhart39/HueQualityAndIngestionApp", "path": "/desktop/libs/hadoop/src/hadoop/yarn/spark_history_server_api.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def applications(self): return self._root.get('applications', headers=self.headers) def application(self, app_id): return self._root.get('applications/%(app_id)s' % {'app_id': app_id}, headers=self.headers) def jobs(self, app_id, attempt_id): return self._root.get('applications/%(app_i...
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{ "lang": "python", "repo": "lockhart39/HueQualityAndIngestionApp", "path": "/desktop/libs/hadoop/src/hadoop/yarn/spark_history_server_api.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: lockhart39/HueQualityAndIngestionApp path: /desktop/libs/hadoop/src/hadoop/yarn/spark_history_server_api.py #!/usr/bin/env python # Licensed to Cloudera, Inc. under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regardi...
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{ "lang": "python", "repo": "lockhart39/HueQualityAndIngestionApp", "path": "/desktop/libs/hadoop/src/hadoop/yarn/spark_history_server_api.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: chandanbose/CUPyDO path: /tests/SU2_Metafor/CantileverSquareChannel_IQN_parallel_fsi.py #! /usr/bin/env python # -*- coding: utf8 -*- ''' Copyright 2018 University of Liège Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the ...
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{ "lang": "python", "repo": "chandanbose/CUPyDO", "path": "/tests/SU2_Metafor/CantileverSquareChannel_IQN_parallel_fsi.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>def main(): import cupydo.interfaces.Cupydo as cupy p = getFsiP() # get parameters cupydo = cupy.CUPyDO(p) # create fsi driver cupydo.run() # run fsi process test(cupydo.algorithm.errValue, p['tol']) # check the results # eof print '' # --- This is only accessed if runnin...
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{ "lang": "python", "repo": "chandanbose/CUPyDO", "path": "/tests/SU2_Metafor/CantileverSquareChannel_IQN_parallel_fsi.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: snowyxx/aliyun-python-demo path: /aliyun/api/rest/Ecs20140526ModifyAutoSnapshotPolicyRequest.py ''' Created by auto_sdk on 2014.07.23 ''' from aliyun.api.base import RestApi class Ecs20140526ModifyAutoSnapshotPolicyRequest(RestApi): <|fim_suffix|> RestApi.__init__(self,domain, port) self...
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{ "lang": "python", "repo": "snowyxx/aliyun-python-demo", "path": "/aliyun/api/rest/Ecs20140526ModifyAutoSnapshotPolicyRequest.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def getapiname(self): return 'ecs.aliyuncs.com.ModifyAutoSnapshotPolicy.2014-05-26'<|fim_prefix|># repo: snowyxx/aliyun-python-demo path: /aliyun/api/rest/Ecs20140526ModifyAutoSnapshotPolicyRequest.py ''' Created by auto_sdk on 2014.07.23 ''' from aliyun.api.base import RestApi class Ecs20140526M...
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{ "lang": "python", "repo": "snowyxx/aliyun-python-demo", "path": "/aliyun/api/rest/Ecs20140526ModifyAutoSnapshotPolicyRequest.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if args.cmd_log: cmd_log = args.cmd_log else: cmd_log = buginfo['command log'] print "copy command log" subprocess.check_call("scp %s:andchecker/%s cmd_log" % (args.hostname, cmd_log), shell=Tru...
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{ "lang": "python", "repo": "Xiangxingqian/appdoctor", "path": "/analyze.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: Xiangxingqian/appdoctor path: /analyze.py #!/usr/bin/env python import argparse import subprocess import os import sys import shutil import flags import buglib def process_cmd(): argparser = argparse.ArgumentParser() argparser.add_argument("cmd", type=str, help='command to run') argp...
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{ "lang": "python", "repo": "Xiangxingqian/appdoctor", "path": "/analyze.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> axs.xaxis.set_major_formatter(fmt) # axs.xaxis.set_minor_formatter(fmt) plt.xticks(rotation=self.options.get('xticksrotation')) plt.legend() fig.tight_layout() def save_plot(self, outfile): frmt = outfile.split('.')[-1].lower() frmt_supported =...
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{ "lang": "python", "repo": "jgarte/qp", "path": "/plotter.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: jgarte/qp path: /plotter.py import logging import matplotlib.pyplot as plt import matplotlib from options import Options log = logging.getLogger('qp') # For plot style, color and marker symbols refer to the format strings section under: # https://matplotlib.org/stable/api/_as_gen/matplotlib.axe...
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{ "lang": "python", "repo": "jgarte/qp", "path": "/plotter.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> Returns: (float, float): ES test stat and p-value of rejecting the null hypothesis (that the two distributions are identical) """ d1 = assure_numpy_array(d1) d2 = assure_numpy_array(d2) es, pvalue = stats.epps_singleton_2samp(d1, d2) return es, pvalue<|fim_prefix|># repo...
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{ "lang": "python", "repo": "python-polymatrix-games/probatus", "path": "/probatus/stat_tests/es.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: python-polymatrix-games/probatus path: /probatus/stat_tests/es.py # Copyright (c) 2020 ING Bank N.V. # # Permission is hereby granted, free of charge, to any person obtaining a copy of # this software and associated documentation files (the "Software"), to deal in # the Software without restricti...
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{ "lang": "python", "repo": "python-polymatrix-games/probatus", "path": "/probatus/stat_tests/es.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: asdfang/CC-AugmentedDeepBach path: /main.py from grader.grader import score_chorale from DatasetManager.chorale_dataset import ChoraleDataset from DatasetManager.dataset_manager import DatasetManager, all_datasets from DatasetManager.metadata import FermataMetadata, TickMetadata, KeyMetadata from...
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{ "lang": "python", "repo": "asdfang/CC-AugmentedDeepBach", "path": "/main.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>print(dataset.gaussian.covariances_) # chorale = converter.parse('generations/6/c187.mid') # score = score_chorale(chorale, dataset) # print(score)<|fim_prefix|># repo: asdfang/CC-AugmentedDeepBach path: /main.py from grader.grader import score_chorale from DatasetManager.chorale_dataset import ChoraleD...
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{ "lang": "python", "repo": "asdfang/CC-AugmentedDeepBach", "path": "/main.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>PYBITES_BORN = datetime(year=2016, month=12, day=19) def gen_special_pybites_dates(): days = 0 while True: days += 1 if days % 100 == 0 or days % 365 == 0: yield PYBITES_BORN + timedelta(days=days) # def gen_special_pybites_dates(): # start_date = PYBITES_BORN # ...
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{ "lang": "python", "repo": "Anthlis/100daysofcode-with-python-course", "path": "/days/01-03-datetimes/my_code/016_Special PyBites date generator.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># def gen_special_pybites_dates(): # start_date = PYBITES_BORN # end_date = start_date + timedelta(days=100) # while start_date <= end_date: # yield start_date # start_date = start_date + timedelta(days=1) # this counts every day for a hundred days. # failed because I ...
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{ "lang": "python", "repo": "Anthlis/100daysofcode-with-python-course", "path": "/days/01-03-datetimes/my_code/016_Special PyBites date generator.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Anthlis/100daysofcode-with-python-course path: /days/01-03-datetimes/my_code/016_Special PyBites date generator.py ''' Bite 16. Special PyBites date generator Write a generator that returns special dates for PyBites: Every year mark counting from PYBITES_BORN date Every 100 days mark counting fr...
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{ "lang": "python", "repo": "Anthlis/100daysofcode-with-python-course", "path": "/days/01-03-datetimes/my_code/016_Special PyBites date generator.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Parameters: ---------- index: int index of a specific image Returns: ---------- ground-truths of this image """ assert self.labels is not None, "Labels not processed" #return self.labels[index, :, :] return self.la...
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{ "lang": "python", "repo": "juliuswang0728/mxnet-ssd", "path": "/dataset/caltech_pedestrain.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Returns: --------- cache path """ cache_path = os.path.join(os.path.dirname(__file__), '..', 'cache') if not os.path.exists(cache_path): os.mkdir(cache_path) return cache_path def label_from_index(self, index): """ ...
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{ "lang": "python", "repo": "juliuswang0728/mxnet-ssd", "path": "/dataset/caltech_pedestrain.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: juliuswang0728/mxnet-ssd path: /dataset/caltech_pedestrain.py import os import numpy as np import glob from imdb import Imdb import xml.etree.ElementTree as ET from evaluate.eval_voc import voc_eval import cv2 def load_caltech(image_set, devkit_path, shuffle=False): """ wrapper funct...
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{ "lang": "python", "repo": "juliuswang0728/mxnet-ssd", "path": "/dataset/caltech_pedestrain.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @http.route('/corp/bind', type='http', auth="public", website=True) def wx_bind(self, **kw): qr_id = kw.get('qr_id') redirect = kw.get('redirect', '') redirect = base64.urlsafe_b64decode(redirect.encode('utf-8')).decode('utf-8') _info = QR_DICT[qr_id]['data'] ...
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{ "lang": "python", "repo": "niulinlnc/weodoo", "path": "/controllers/controllers.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: niulinlnc/weodoo path: /controllers/controllers.py # -*- coding: utf-8 -*- import logging import time import random import json import base64 from odoo import http from odoo.addons.web.controllers.main import Home, ensure_db from odoo.addons.web.controllers.main import db_monodb, ensure_db, set_...
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{ "lang": "python", "repo": "niulinlnc/weodoo", "path": "/controllers/controllers.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: vulhub/vulhub path: /django/CVE-2018-14574/app.py import os import sys from django.urls import include, path, re_path from django.http import HttpResponse os.environ.setdefault("DJANGO_SETTINGS_MODULE", __name__) BASE_DIR = os.path.dirname(os.path.abspath(__file__)) DEBUG = False SECRET_KEY = 'v...
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{ "lang": "python", "repo": "vulhub/vulhub", "path": "/django/CVE-2018-14574/app.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>urlpatterns = [ path('', home), re_path(r'^(.*)/$', home), ] from django.core.management import execute_from_command_line execute_from_command_line(sys.argv)<|fim_prefix|># repo: vulhub/vulhub path: /django/CVE-2018-14574/app.py import os import sys from django.urls import include, path, re_path...
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{ "lang": "python", "repo": "vulhub/vulhub", "path": "/django/CVE-2018-14574/app.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>#pode colocar os calculos dentro do print tbm #pode usar 'pow' exemplo pow(n,(1/2))<|fim_prefix|># repo: Kimberly07-Ernane/Pythondesafios path: /Desafios/Desafio 006 (Dobro,Tripo,Raiz quad.).py #Desafio 06 #Crie um algoritmo que leia um número e mostre o seu dobro, #triplo e raiz quadrada <|fim_middle|>...
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{ "lang": "python", "repo": "Kimberly07-Ernane/Pythondesafios", "path": "/Desafios/Desafio 006 (Dobro,Tripo,Raiz quad.).py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Kimberly07-Ernane/Pythondesafios path: /Desafios/Desafio 006 (Dobro,Tripo,Raiz quad.).py #Desafio 06 #Crie um algoritmo que leia um número e mostre o seu dobro, #triplo e raiz quadrada <|fim_suffix|>#pode colocar os calculos dentro do print tbm #pode usar 'pow' exemplo pow(n,(1/2))<|fim_middle|>...
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{ "lang": "python", "repo": "Kimberly07-Ernane/Pythondesafios", "path": "/Desafios/Desafio 006 (Dobro,Tripo,Raiz quad.).py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Generate a useful version string for a QGreenland build. It's not always enough to use bumpversion to manage versions. If we want to release a dev build or a pre-release for human validation, it needs a fully-unique name so we know exactly what the user tested. * For release build...
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{ "lang": "python", "repo": "nsidc/qgreenland", "path": "/qgreenland/util/version.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: nsidc/qgreenland path: /qgreenland/util/version.py import functools import os import re import subprocess import qgreenland.exceptions as exc from qgreenland import __version__ VERSION_REGEX = re.compile(r"^v\d+\.\d+\.\d+(?P<modifier>.*)$") def _select_version_tags(tags): """Return any me...
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{ "lang": "python", "repo": "nsidc/qgreenland", "path": "/qgreenland/util/version.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return version def version_is_full_release(version_string): """Check if a version string is a release version `vX.Y.Z`. Exclude any pre-release versions like `vX.Y.Z-rc1`, `vX.Y.Zfoobarbaz`. """ match = VERSION_REGEX.match(version_string) if match and match.groupdict()["modifie...
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{ "lang": "python", "repo": "nsidc/qgreenland", "path": "/qgreenland/util/version.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: FlareSolverr/FlareSolverr path: /src/undetected_chromedriver/dprocess.py import atexit import logging import multiprocessing import os import platform import signal from subprocess import PIPE from subprocess import Popen import sys CREATE_NEW_PROCESS_GROUP = 0x00000200 DETACHED_PROCESS = 0x000...
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{ "lang": "python", "repo": "FlareSolverr/FlareSolverr", "path": "/src/undetected_chromedriver/dprocess.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for pid in REGISTERED: try: logging.getLogger(__name__).debug("cleaning up pid %d " % pid) os.kill(pid, signal.SIGTERM) except: # noqa pass atexit.register(_cleanup)<|fim_prefix|># repo: FlareSolverr/FlareSolverr path: /src/undetected_chromedrive...
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{ "lang": "python", "repo": "FlareSolverr/FlareSolverr", "path": "/src/undetected_chromedriver/dprocess.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>for i in range(1, 65535): ports.append(i) # Check what time the scan started t1 = datetime.now() pool = ThreadPool(processes=1000) results = pool.map(scan_port, ports) pool.close() pool.join() print ('Multiprocess Scanning Completed in ', datetime.now() - t1) print ('number is ', totalnumber)<|fi...
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{ "lang": "python", "repo": "YaKaiLi/hbuComputerNetworkCourseProject-ScanPort", "path": "/scanport5.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: YaKaiLi/hbuComputerNetworkCourseProject-ScanPort path: /scanport5.py # coding: utf-8 import socket from datetime import datetime from multiprocessing.dummy import Pool as ThreadPool #remote_server = input("Enter a remote host to scan:") remote_server = "103.79.76.177" remote_server_ip = socket.g...
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{ "lang": "python", "repo": "YaKaiLi/hbuComputerNetworkCourseProject-ScanPort", "path": "/scanport5.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Calculate the preparation time in minutes""" return PREPARATION_TIME * number_of_layers def elapsed_time_in_minutes(number_of_layers, elapsed_bake_time): """Calculate the elapsed time in minutes""" return preparation_time_in_minutes(number_of_layers) + elapsed_bake_time<|fim_prefix|># ...
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{ "lang": "python", "repo": "ErikSchierboom/exercism", "path": "/python/guidos-gorgeous-lasagna/lasagna.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: ErikSchierboom/exercism path: /python/guidos-gorgeous-lasagna/lasagna.py EXPECTED_BAKE_TIME = 40 PREPARATION_TIME = 2 def bake_time_remaining(elapsed_bake_time): <|fim_suffix|> """Calculate the elapsed time in minutes""" return preparation_time_in_minutes(number_of_layers) + elapsed_bake_...
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{ "lang": "python", "repo": "ErikSchierboom/exercism", "path": "/python/guidos-gorgeous-lasagna/lasagna.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: lluxury/P_U_S_A path: /9_package_management/distutils/setup.py from setuptools import setup setup( name = "distutils_example", description = "A completly Useless Script Th<|fim_suffix|>", version = "0.1", url = "htt这://www.pyatl.org" )<|fim_middle|>at Prints", author = "yann",...
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{ "lang": "python", "repo": "lluxury/P_U_S_A", "path": "/9_package_management/distutils/setup.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>", version = "0.1", url = "htt这://www.pyatl.org" )<|fim_prefix|># repo: lluxury/P_U_S_A path: /9_package_management/distutils/setup.py from setuptools import setup setup( name = "distutils_<|fim_middle|>example", description = "A completly Useless Script That Prints", author = "yann",...
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{ "lang": "python", "repo": "lluxury/P_U_S_A", "path": "/9_package_management/distutils/setup.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> matches = [i for i in LANGLIST if match[0].lower() in i.lower()] if matches: return ', '.join(matches) else: return 'No languages matching {}. See !languages for a list of languages I support.'.format(match[0]) TIOBot = Bot( nick = 'TIOBot', room = 'xkcd', sho...
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{ "lang": "python", "repo": "totallyhuman/TIOBot", "path": "/TIOBot.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return 'Output:\n' + res[0] def list_languages(match, trigger): return ', '.join(LANGLIST) def search_languages(match, trigger): matches = [i for i in LANGLIST if match[0].lower() in i.lower()] if matches: return ', '.join(matches) else: return 'No languages matc...
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{ "lang": "python", "repo": "totallyhuman/TIOBot", "path": "/TIOBot.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: totallyhuman/TIOBot path: /TIOBot.py #!/usr/bin/env python3 # -*- coding: utf-8 -*- import requests import zlib from literate_banana import Bot LANGUAGES = { 'c': 'c-gcc', 'c#': 'cs-core', 'c++': 'cpp-gcc', 'common lisp': 'clisp', 'groovy': 'groovy', 'go': 'go', 'ha...
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{ "lang": "python", "repo": "totallyhuman/TIOBot", "path": "/TIOBot.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def test_normal_user_can_remove_all_emails(user_gql_client, email_data): profile = ProfileWithPrimaryEmailFactory(user=user_gql_client.user, emails=2) primary_email = profile.emails.filter(primary=True).first() email = profile.emails.filter(primary=False).first() t = Template( """...
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{ "lang": "python", "repo": "SuviVappula/open-city-profile", "path": "/profiles/tests/test_gql_update_my_profile_mutation.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> profile = ProfileWithPrimaryEmailFactory(user=user_gql_client.user) phone = PhoneFactory(profile=profile) t = Template( """ mutation { updateMyProfile( input: { profile: { removePhones:...
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{ "lang": "python", "repo": "SuviVappula/open-city-profile", "path": "/profiles/tests/test_gql_update_my_profile_mutation.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: SuviVappula/open-city-profile path: /profiles/tests/test_gql_update_my_profile_mutation.py "address": address_data["address"], "postalCode": address_data["postal_code"], "city": address_data["city"], ...
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{ "lang": "python", "repo": "SuviVappula/open-city-profile", "path": "/profiles/tests/test_gql_update_my_profile_mutation.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: geordi/kelvin path: /common/utils.py from datetime import timedelta import re import ldap from functools import lru_cache LDAP_CONNECTION = None @lru_cache() def is_teacher(user): return user.groups.filter(name='teachers').exists() def points_to_color(points, max_points): ratio = max(0...
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{ "lang": "python", "repo": "geordi/kelvin", "path": "/common/utils.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if not LDAP_CONNECTION: connect() def get(): return LDAP_CONNECTION.search_s("", ldap.SCOPE_SUBTREE, f"(cn={login})", ["sn", "givenname", "mail"]) # TODO: escape needed? try: res = get() except ldap.UNAVAILABLE: connect() res = get() if no...
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{ "lang": "python", "repo": "geordi/kelvin", "path": "/common/utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: sndg-arg/sndg-web path: /bioresources/models/Expression.py # -*- coding: utf-8 -*- from __future__ import unicode_literals from model_utils import Choices from django.utils.translation import gettext_lazy as _, ngettext as __ from django.db import models from .Resource import Resource class Expr...
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{ "lang": "python", "repo": "sndg-arg/sndg-web", "path": "/bioresources/models/Expression.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> ran = [] for affiliation in self.targets.all(): ran += affiliation.source.author_names() return list(set(ran)) def related_org_names(self): ran = [] for affiliation in self.targets.all(): ran += affiliation.source.affiliation_names() ...
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{ "lang": "python", "repo": "sndg-arg/sndg-web", "path": "/bioresources/models/Expression.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> ran = [] for affiliation in self.targets.all(): ran += affiliation.source.affiliation_names() return list(set(ran))<|fim_prefix|># repo: sndg-arg/sndg-web path: /bioresources/models/Expression.py # -*- coding: utf-8 -*- from __future__ import unicode_literals from mode...
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{ "lang": "python", "repo": "sndg-arg/sndg-web", "path": "/bioresources/models/Expression.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # get url for authenticating user url = graph.get_auth_url(app_id, canvas_url, perms) webbrowser.open(url) FacebookApi.wait_for_request(server_class=Server, handler_class=Handler) global code # pylint: disable=global-statement # g...
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{ "lang": "python", "repo": "cash2one/Postr", "path": "/postr/facebook_api.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: cash2one/Postr path: /postr/facebook_api.py # Facebook API from http.server import BaseHTTPRequestHandler, HTTPServer import webbrowser import json from typing import Type, List from postr.config import get_api_key from postr.config import update_api_key from postr.api_interface import ApiInterf...
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{ "lang": "python", "repo": "cash2one/Postr", "path": "/postr/facebook_api.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> server_class: Type[HTTPServer], handler_class: Type[BaseHTTPRequestHandler], ) -> None: server_address = ('', 8000) httpd = server_class(server_address, handler_class) httpd.timeout = 10 try: httpd.handle_request() # this can get me the code...
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{ "lang": "python", "repo": "cash2one/Postr", "path": "/postr/facebook_api.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # Input data dimensions n_batches = test_data.shape[0] # T = test_data.shape[1] # Limit the length of the input data test_data = test_data[:, :self.in_seq_length] # Compute the forecast with tf.Session() as sess: saver.restore(sess, sel...
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{ "lang": "python", "repo": "dickkky/forecastNet", "path": "/TensorFlow/forecastNet.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def forecast(self, test_data): """ Perform a forecast with the input data: test_data. Note that only the first in_seq_length values in test_data are used are used to forecast the next out_seq_length values. It is best practice to compute several forecasts and average o...
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{ "lang": "python", "repo": "dickkky/forecastNet", "path": "/TensorFlow/forecastNet.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: dickkky/forecastNet path: /TensorFlow/forecastNet.py """ This file contains the class which constructs the TensorFlow graph of ForecastNet and provides a function for forecasting. Paper: "ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series F...
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{ "lang": "python", "repo": "dickkky/forecastNet", "path": "/TensorFlow/forecastNet.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: les-tallman/cloudbolt-forge path: /blueprints/azure_k8s/sync.py """ Discover Azure Resource groups and clusters Return Azure Resource groups and clusters identified by sku, handler_id and location """ from common.methods import set_progress from azure.common.credentials import ServicePrincipalCre...
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{ "lang": "python", "repo": "les-tallman/cloudbolt-forge", "path": "/blueprints/azure_k8s/sync.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> discovered_resource_groups = [] for handler in AzureARMHandler.objects.all(): set_progress('Connecting to Azure Resource Groups \ for handler: {}'.format(handler)) credentials = ServicePrincipalCredentials( client_id=handler.client_id, secret=handle...
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{ "lang": "python", "repo": "les-tallman/cloudbolt-forge", "path": "/blueprints/azure_k8s/sync.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> transformation_fn_dict = dict() transformation_fn_dict["tf_name"] = tf transformation_fn_dict["tf1_name"] = tf fv = feature_view.FeatureView( featurestore_id=feature_store_id, name="test_fv", version=1, query=q, t...
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{ "lang": "python", "repo": "logicalclocks/feature-store-api", "path": "/python/tests/test_feature_view.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: logicalclocks/feature-store-api path: /python/tests/test_feature_view.py # # Copyright 2022 Hopsworks AB # # 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 # # ...
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{ "lang": "python", "repo": "logicalclocks/feature-store-api", "path": "/python/tests/test_feature_view.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: kort/kort-core path: /src/api/tokeninfo/tokenAccess.py #!/usr/bin/env python3 import logging from api import models db_session = models.init_db() logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) <|fim_suffix|> def get_user_by_secret(secret: str): user = db_sessi...
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{ "lang": "python", "repo": "kort/kort-core", "path": "/src/api/tokeninfo/tokenAccess.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def get_user_by_secret(secret: str): user = db_session.query(models.User).filter(models.User.secret == secret).one_or_none() logger.info('get user token with id '+str(user.id)) return user.id<|fim_prefix|># repo: kort/kort-core path: /src/api/tokeninfo/tokenAccess.py #!/usr/bin/env python3 i...
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{ "lang": "python", "repo": "kort/kort-core", "path": "/src/api/tokeninfo/tokenAccess.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def get_user_by_secret(secret: str): user = db_session.query(models.User).filter(models.User.secret == secret).one_or_none() logger.info('get user token with id '+str(user.id)) return user.id<|fim_prefix|># repo: kort/kort-core path: /src/api/tokeninfo/tokenAccess.py #!/usr/bin/env python3 im...
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{ "lang": "python", "repo": "kort/kort-core", "path": "/src/api/tokeninfo/tokenAccess.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: jfkz/tvoeradio path: /tvoeradio/radio/decorators.py import httpagentparser from django.shortcuts import render_to_response from django.template import RequestContext <|fim_suffix|> def _wrap(request, *args, **kwargs): ua = request.META.get('HTTP_USER_AGENT') no_ua_check = requ...
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{ "lang": "python", "repo": "jfkz/tvoeradio", "path": "/tvoeradio/radio/decorators.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> ua = request.META.get('HTTP_USER_AGENT') no_ua_check = request.GET.get('no_ua_check', False) if ua and not no_ua_check: info = httpagentparser.detect(ua) browser = info.get('browser', {}) if browser.get('name') == 'Microsoft Internet Explorer': ...
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{ "lang": "python", "repo": "jfkz/tvoeradio", "path": "/tvoeradio/radio/decorators.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __str__(self): return self.nombre class Capitulos(models.Model): programa = models.ForeignKey(Programa, related_name='programa', on_delete=models.CASCADE) numero_capitulo = models.IntegerField('Numero') fecha_emision = models.DateTimeField('Fecha de emision') titulo = models.TextField('Tit...
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{ "lang": "python", "repo": "ddvloayza/str3am-app", "path": "/tvempresa/src/apps/web/models.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return self.nombre class Capitulos(models.Model): programa = models.ForeignKey(Programa, related_name='programa', on_delete=models.CASCADE) numero_capitulo = models.IntegerField('Numero') fecha_emision = models.DateTimeField('Fecha de emision') titulo = models.TextField('Titulo', max_length=70,...
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{ "lang": "python", "repo": "ddvloayza/str3am-app", "path": "/tvempresa/src/apps/web/models.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ddvloayza/str3am-app path: /tvempresa/src/apps/web/models.py from django.db import models from django.contrib.auth.models import User from django.urls import reverse from taggit.managers import TaggableManager class Principal(models.Model): nombre_video_principal = models.CharField('Nombre Vid...
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{ "lang": "python", "repo": "ddvloayza/str3am-app", "path": "/tvempresa/src/apps/web/models.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> f.write(str(find_big_prime(37))+'\n')<|fim_prefix|># repo: rshorey/primefactors path: /list_of_primes.py from find_big_prime import * with open('list_of_primes2.csv', 'w') as f: f.writel<|fim_middle|>ines('prime\n') for i in range(0,50):
code_fim
easy
{ "lang": "python", "repo": "rshorey/primefactors", "path": "/list_of_primes.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: rshorey/primefactors path: /list_of_primes.py from find_big_prime import * with open('li<|fim_suffix|>ines('prime\n') for i in range(0,50): f.write(str(find_big_prime(37))+'\n')<|fim_middle|>st_of_primes2.csv', 'w') as f: f.writel
code_fim
easy
{ "lang": "python", "repo": "rshorey/primefactors", "path": "/list_of_primes.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> hot_label_train = [] hot_label_val = [] hot_label_test = [] # One hot encode the training labels for i in range(self.num_train): hot_label_train.append(np.eye(self.num_classes, dtype=float)[label_train[i]]) hot_label_train = np.array(hot_label_t...
code_fim
hard
{ "lang": "python", "repo": "bvsk35/TensorFlow-V1.13-V2.0-Examples", "path": "/TensorFlow v1.13/3-MNIST-Classification-CNN/Load_MNIST_Data.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: bvsk35/TensorFlow-V1.13-V2.0-Examples path: /TensorFlow v1.13/3-MNIST-Classification-CNN/Load_MNIST_Data.py # This file prepares the training, validation and testing MNIST dataset # Import required functions import gzip import numpy as np from sklearn.preprocessing import StandardScaler from skle...
code_fim
hard
{ "lang": "python", "repo": "bvsk35/TensorFlow-V1.13-V2.0-Examples", "path": "/TensorFlow v1.13/3-MNIST-Classification-CNN/Load_MNIST_Data.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # Function for converting the labels to one hot encoded vectors def one_hot_encoded(self, label_train, label_val, label_test): hot_label_train = [] hot_label_val = [] hot_label_test = [] # One hot encode the training labels for i in range(self.num_train): ...
code_fim
hard
{ "lang": "python", "repo": "bvsk35/TensorFlow-V1.13-V2.0-Examples", "path": "/TensorFlow v1.13/3-MNIST-Classification-CNN/Load_MNIST_Data.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># histogram of number of observations by date df_grouped_date = df.groupby(['date']) df_date_count = df_grouped_date['reqid'].aggregate(['count']) #df_date_count = df_grouped_date.aggregate(['count']) print(df_date_count) #exclude_cols = ['title count'] #df_date_count.ix[:, df_date_count.columns.differe...
code_fim
hard
{ "lang": "python", "repo": "robmarano/nyu-python", "path": "/course-2/session-7/pandas/df_basics.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: robmarano/nyu-python path: /course-2/session-7/pandas/df_basics.py #!/usr/bin/env python3 try: # for Python 2.x import StringIO except: # for Python 3.x import io import csv import pandas as pd import numpy as np import matplotlib.pyplot as plt import re # define data csv_inpu...
code_fim
hard
{ "lang": "python", "repo": "robmarano/nyu-python", "path": "/course-2/session-7/pandas/df_basics.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }