text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> ctx = {}
ctx['ip'] = get_ip()
ctx['main_url'] = 'http://{ip}:8000'.format(**ctx)
ctx['wallet'] = Wallet.objects.first()
return ctx<|fim_prefix|># repo: one-quaker/imfs path: /web/context_processors.py
import os
import sys
from .models import Photo, Wallet
def get_ip():
if sys.p... | code_fim | medium | {
"lang": "python",
"repo": "one-quaker/imfs",
"path": "/web/context_processors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def get_base_data(request):
ctx = {}
ctx['ip'] = get_ip()
ctx['main_url'] = 'http://{ip}:8000'.format(**ctx)
ctx['wallet'] = Wallet.objects.first()
return ctx<|fim_prefix|># repo: one-quaker/imfs path: /web/context_processors.py
import os
import sys
from .models import Photo, Wallet... | code_fim | hard | {
"lang": "python",
"repo": "one-quaker/imfs",
"path": "/web/context_processors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main():
with open("Input.txt", "r") as input_file:
string = input_file.readline().strip()
gc_counts = [float(num) for num in input_file.readline().strip().split()]
print(''.join('{:5.3f} '.format(lgsum) for lgsum in map(lambda x : get_string_probability_lg(string, x), gc_counts)))
main()<|fim... | code_fim | medium | {
"lang": "python",
"repo": "Daerdemandt/Learning-bioinformatics",
"path": "/PROB/Solution.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open("Input.txt", "r") as input_file:
string = input_file.readline().strip()
gc_counts = [float(num) for num in input_file.readline().strip().split()]
print(''.join('{:5.3f} '.format(lgsum) for lgsum in map(lambda x : get_string_probability_lg(string, x), gc_counts)))
main()<|fim_prefix|># r... | code_fim | medium | {
"lang": "python",
"repo": "Daerdemandt/Learning-bioinformatics",
"path": "/PROB/Solution.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Daerdemandt/Learning-bioinformatics path: /PROB/Solution.py
#!/usr/bin/env python3
from math import log10
def get_string_probability_lg(string, gc):
gc_count = string.count('G') + string.count('C')
gc_log, at_log = log10(gc/2), log10((1 - gc)/2)
return gc_count * gc_log + (len(string) - gc_co... | code_fim | medium | {
"lang": "python",
"repo": "Daerdemandt/Learning-bioinformatics",
"path": "/PROB/Solution.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sauerseb/Week-Nine-Assignment path: /lab9.py
# Evan Sauers & Daniel Rush
# Intro to Computer Science I
# Collabortaed with Dr. Neumann
# lab9.py
#Take the word, turn it into a list, and create spaces inbetween letters
def sortString(word):
word = word.lower()
myList = list(word)
myL... | code_fim | hard | {
"lang": "python",
"repo": "sauerseb/Week-Nine-Assignment",
"path": "/lab9.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Ask Question
if word[0] == "v":
sortedWord = sortString(word)
dictionary[sortedWord] = word
fileHandle.close()
# Find the Anagram in the dictionary, read the file, print
def findAnagrams(fileName, aDict):
fileHandle = open(fileName, "r")
... | code_fim | hard | {
"lang": "python",
"repo": "sauerseb/Week-Nine-Assignment",
"path": "/lab9.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> aDict = {}
filename = 'wordList.txt'
quizList = 'quizwords.txt'
createDictionary(filename, aDict)
findAnagrams(quizList, aDict)
main()<|fim_prefix|># repo: sauerseb/Week-Nine-Assignment path: /lab9.py
# Evan Sauers & Daniel Rush
# Intro to Computer Science I
# Collabortaed with Dr. N... | code_fim | hard | {
"lang": "python",
"repo": "sauerseb/Week-Nine-Assignment",
"path": "/lab9.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jiajunshen/partsNet path: /pnet/parts_layer.py
from __future__ import division, print_function, absolute_import
# TODO: Temp
import matplotlib as mpl
mpl.use('Agg')
from scipy.special import logit
import numpy as np
import itertools as itr
import amitgroup as ag
from pnet.layer import Layer
im... | code_fim | hard | {
"lang": "python",
"repo": "jiajunshen/partsNet",
"path": "/pnet/parts_layer.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> from pylab import cm
D = self._parts.shape[-1]
N = self._num_parts
# Plot all the parts
grid = pnet.plot.ImageGrid(N, D, self._part_shape)
print('SHAPE', self._parts.shape)
cdict1 = {'red': ((0.0, 0.0, 0.0),
(0.5, 0.0, 0... | code_fim | hard | {
"lang": "python",
"repo": "jiajunshen/partsNet",
"path": "/pnet/parts_layer.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> np.random.seed(42)
X = from_2d_array_to_nested(
pd.DataFrame(data=np.random.randn(n_instances, len_series))
)
trans = PCATransformer(n_components=n_components)
Xt = trans.fit_transform(X)
# Check number of rows and output type.
assert isinstance(Xt, pd.DataFrame)
... | code_fim | hard | {
"lang": "python",
"repo": "earthinversion/sktime",
"path": "/sktime/transformations/panel/tests/test_PCATransformer.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: earthinversion/sktime path: /sktime/transformations/panel/tests/test_PCATransformer.py
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import pytest
from sklearn.decomposition import PCA
from sktime.exceptions import NotFittedError
from sktime.transformations.panel.pca import PCAT... | code_fim | hard | {
"lang": "python",
"repo": "earthinversion/sktime",
"path": "/sktime/transformations/panel/tests/test_PCATransformer.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Check number of principal components in the output.
assert from_nested_to_2d_array(Xt).shape[1] == min(
n_components, from_nested_to_2d_array(X).shape[1]
)
# Check that the returned values agree with those produced by
# ``sklearn.decomposition.PCA``
@pytest.mark.parametrize("n_comp... | code_fim | hard | {
"lang": "python",
"repo": "earthinversion/sktime",
"path": "/sktime/transformations/panel/tests/test_PCATransformer.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif nn == "0x001e":
# Adds VX to I.
self.i += self.v[x]
elif nn == "0x0029":
# Sets I to the location of the sprite for the character in VX.
# Characters 0-F (in hexadecimal) are represented by a 4x5
... | code_fim | hard | {
"lang": "python",
"repo": "LeoLamCY/c8emu",
"path": "/chip8.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif n == "0x0005":
# VY is subtracted from VX. VF is set to 0 when there's a
# borrow, and 1 when there isn't.
self.v[x] -= self.v[y]
if self.v[x] < 0:
self.v[0xF] = 0
self.v[x] += 256
... | code_fim | hard | {
"lang": "python",
"repo": "LeoLamCY/c8emu",
"path": "/chip8.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LeoLamCY/c8emu path: /chip8.py
import random
class Chip8(object):
ERROR_UNKNOWN_OPCODE = "ERROR: unknown opcode"
running = False
count = 0
font_set = [
0xF0, 0x90, 0x90, 0x90, 0xF0,
0x20, 0x60, 0x20, 0x20, 0x70,
0xF0, 0x10, 0xF0, 0x80, 0xF0,
0xF0... | code_fim | hard | {
"lang": "python",
"repo": "LeoLamCY/c8emu",
"path": "/chip8.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> func_groups : :class:`tuple` of :class:`.FunctionalGroup`
The functional group clones added to the constructed
molecule.
vertices : :class:`tuple` of :class:`.Vertex`
All vertices in the topology graph. The index of each
vertex must match it... | code_fim | hard | {
"lang": "python",
"repo": "llsonkimm/stk",
"path": "/src/stk/molecular/topology_graphs/cage/base.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: llsonkimm/stk path: /src/stk/molecular/topology_graphs/cage/base.py
lf._place_linear_building_block(
building_block=building_block,
vertices=vertices,
edges=edges
)
return self._place_nonlinear_building_block(
buildin... | code_fim | hard | {
"lang": "python",
"repo": "llsonkimm/stk",
"path": "/src/stk/molecular/topology_graphs/cage/base.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> building_block,
fg0_direction,
bonder_centroid,
axis
):
def angle(fg_id):
func_group = building_block.func_groups[fg_id]
coord = building_block.get_centroid(
atom_ids=func_group.get_bonder_ids()
)
... | code_fim | hard | {
"lang": "python",
"repo": "llsonkimm/stk",
"path": "/src/stk/molecular/topology_graphs/cage/base.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>wait = 10 * 60
while True:
repo.remotes.origin.pull()
if last_build == repo.head.object.hexsha:
logging.debug("Up-to-date, sleeping %d seconds" % wait)
import time
time.sleep(wait)
continue
logging.info("Update! Our head %s, remote head %s",
last_build... | code_fim | hard | {
"lang": "python",
"repo": "BitcoinUnlimited/ElectrsCash",
"path": "/contrib/build/latest-build-publisher.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>try:
import git
except Exception as e:
logging.error("Failed to 'import git'")
logging.error("Tip: On Debian/Ubuntu you need to install python3-git")
sys.exit(1)
# Start webserver
class HTTPHandler(http.server.SimpleHTTPRequestHandler):
def __init__(self, *init_args, **init_kwargs):
... | code_fim | hard | {
"lang": "python",
"repo": "BitcoinUnlimited/ElectrsCash",
"path": "/contrib/build/latest-build-publisher.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BitcoinUnlimited/ElectrsCash path: /contrib/build/latest-build-publisher.py
#!/usr/bin/env python3
# Copyright (c) 2019 The Bitcoin Unlimited developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
'''
Th... | code_fim | hard | {
"lang": "python",
"repo": "BitcoinUnlimited/ElectrsCash",
"path": "/contrib/build/latest-build-publisher.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: patrick-luo/Leet-Code path: /482. License Key Formatting.py
"""Something wrong with Leetcode's testing"""
class Solution(object):
def licenseKeyFormatting(self, S, K):
"""
:type S: str
:type K: int
:rtype: str
<|fim_suffix|>el buff[:]
buff.reverse... | code_fim | hard | {
"lang": "python",
"repo": "patrick-luo/Leet-Code",
"path": "/482. License Key Formatting.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>el buff[:]
buff.reverse()
words.append(''.join(buff))
ans = words[-1]
for i in xrange(len(words)-2, -1, -1):
ans += '-' + words[i]
return ans<|fim_prefix|># repo: patrick-luo/Leet-Code path: /482. License Key Formatting.py
"""Something wrong with Leetco... | code_fim | hard | {
"lang": "python",
"repo": "patrick-luo/Leet-Code",
"path": "/482. License Key Formatting.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: asmello/source-bot path: /src/sauce_bot/schemas/user_feed.py
from sqlalchemy import Column, Integer, ForeignKey
<|fim_suffix|> return f"<UserFeed(user_id='{self.user_id}', feed_id='{self.feed_id}')>"
def to_dict(self):
return {c.name: getattr(self, c.name) for c in self.__table__.columns}<|... | code_fim | hard | {
"lang": "python",
"repo": "asmello/source-bot",
"path": "/src/sauce_bot/schemas/user_feed.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def to_dict(self):
return {c.name: getattr(self, c.name) for c in self.__table__.columns}<|fim_prefix|># repo: asmello/source-bot path: /src/sauce_bot/schemas/user_feed.py
from sqlalchemy import Column, Integer, ForeignKey
from . import Base
class UserFeed(Base):
<|fim_middle|> __tablename__ = 'use... | code_fim | hard | {
"lang": "python",
"repo": "asmello/source-bot",
"path": "/src/sauce_bot/schemas/user_feed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class UserFeed(Base):
__tablename__ = 'user_feeds'
user_id = Column('user_id', ForeignKey('users.db_id'), primary_key=True)
feed_id = Column('feed_id', ForeignKey('feeds.db_id'), primary_key=True)
def __repr__(self):
return f"<UserFeed(user_id='{self.user_id}', feed_id='{self.feed_id}')>"
def to... | code_fim | easy | {
"lang": "python",
"repo": "asmello/source-bot",
"path": "/src/sauce_bot/schemas/user_feed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: magico13/KCTR path: /version.py
import sys
import json
import os
build = 0
if len(sys.argv) > 1:
build = int(sys.argv[1])
# read data out of the version file
with open('KCTR.version') as f:
data = json.load(f)
<|fim_suffix|># write to the version.cs file with the updated version
with o... | code_fim | hard | {
"lang": "python",
"repo": "magico13/KCTR",
"path": "/version.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># write back to the version file with the updated build number
with open('KCTR.version', 'w') as f:
json.dump(data, f, indent=2)
with open('version.txt', 'w') as f:
f.write(f'{fullVer}\n')
# write to the version.cs file with the updated version
with open('KCTR/Properties/VersionInfo.cs', 'w') as... | code_fim | medium | {
"lang": "python",
"repo": "magico13/KCTR",
"path": "/version.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
Parallel(n_jobs=20)(delayed(helper)(x) for x in train_file_names)<|fim_prefix|># repo: VENHEADs/kaggle_camera path: /filter_new_flickr.py
from pathlib import Path
import jpeg4py
import os
from joblib import Parallel, delayed
data_path = Path('data')
train_path = data_path / 'new_flickr'
<|fim_middle|>... | code_fim | medium | {
"lang": "python",
"repo": "VENHEADs/kaggle_camera",
"path": "/filter_new_flickr.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: VENHEADs/kaggle_camera path: /filter_new_flickr.py
from pathlib import Path
import jpeg4py
import os
from joblib import Parallel, delayed
data_path = Path('data')
train_path = data_path / 'new_flickr'
<|fim_suffix|>
Parallel(n_jobs=20)(delayed(helper)(x) for x in train_file_names)<|fim_middle|>... | code_fim | medium | {
"lang": "python",
"repo": "VENHEADs/kaggle_camera",
"path": "/filter_new_flickr.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def Log_Analysis(self):
count_404 = 0
count_500 = 0
ip = 0
pv = 0
filelist = self.getFilelist()
print filelist
log = LogToMysql("/data/woyaoce/201605")
log.Log_Analysis()<|fim_prefix|># repo: hulm/nlog path: /nlog/script/log_to_db.py
#!/usr/bin/env python
# -*- coding:utf-8 —*-
import sys
i... | code_fim | hard | {
"lang": "python",
"repo": "hulm/nlog",
"path": "/nlog/script/log_to_db.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>log = LogToMysql("/data/woyaoce/201605")
log.Log_Analysis()<|fim_prefix|># repo: hulm/nlog path: /nlog/script/log_to_db.py
#!/usr/bin/env python
# -*- coding:utf-8 —*-
import sys
import os
class LogToMysql:
def __init__(self,log_path):
self.log_path = log_path
def getFilelist(self):
file... | code_fim | medium | {
"lang": "python",
"repo": "hulm/nlog",
"path": "/nlog/script/log_to_db.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hulm/nlog path: /nlog/script/log_to_db.py
#!/usr/bin/env python
# -*- coding:utf-8 —*-
import sys
import os
class LogToMysql:
def __init__(self,log_path):
<|fim_suffix|> def getFilelist(self):
filelist=[]
for file in os.listdir(self.log_path):
filelist.append(self.log_path+'/'+file... | code_fim | easy | {
"lang": "python",
"repo": "hulm/nlog",
"path": "/nlog/script/log_to_db.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_update_emergency_settings(self, request_mock):
telnyx.PhoneNumberJob.update_emergency_settings(
emergency_address_id="53829456729313",
emergency_enabled=True,
phone_numbers=[],
)
request_mock.assert_requested(
"post", "/v... | code_fim | hard | {
"lang": "python",
"repo": "team-telnyx/telnyx-python",
"path": "/tests/api_resources/test_phone_number_job.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: team-telnyx/telnyx-python path: /tests/api_resources/test_phone_number_job.py
from __future__ import absolute_import, division, print_function
import telnyx
TEST_RESOURCE_ID = "1293384261075731499"
class TestPhoneNumberJob(object):
def test_is_listable(self, request_mock):
resourc... | code_fim | hard | {
"lang": "python",
"repo": "team-telnyx/telnyx-python",
"path": "/tests/api_resources/test_phone_number_job.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WealthCity/realtime_talib path: /test.py
import indicators as ind
import pipeline as pl
<|fim_suffix|>HistData = pl.pullHistoricalData(ticker, endDate)
LiveData = pl.pullLiveData(ticker, True)
SPY_Ind = ind.Indicator(ticker, endDate)
print SPY_Ind.MA(0, 14)
print SPY_Ind.RSI(12)<|fim_middle|>t... | code_fim | easy | {
"lang": "python",
"repo": "WealthCity/realtime_talib",
"path": "/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print SPY_Ind.MA(0, 14)
print SPY_Ind.RSI(12)<|fim_prefix|># repo: WealthCity/realtime_talib path: /test.py
import indicators as ind
import pipeline as pl
<|fim_middle|>ticker = 'SPY'
endDate = '2016-05-12'
HistData = pl.pullHistoricalData(ticker, endDate)
LiveData = pl.pullLiveData(ticker, True)
SPY_... | code_fim | medium | {
"lang": "python",
"repo": "WealthCity/realtime_talib",
"path": "/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Platron/python-sdk path: /tests/integration/receipt_test.py
from xml.etree.ElementTree import fromstring
from .base_integration_test import BaseIntegrationTest
from platron.request.clients.post_client import PostClient
from platron.request.request_builders.receipt_builder import ReceiptBuilder
f... | code_fim | hard | {
"lang": "python",
"repo": "Platron/python-sdk",
"path": "/tests/integration/receipt_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_create_transaction_chain(self):
builder = InitPaymentBuilder('20.00', 'test')
client = PostClient(self.get_merchant_id(), self.get_secret_key())
result = client.request(builder)
root = fromstring(result)
pg_payment_id = root.find('pg_payment_id').text
... | code_fim | medium | {
"lang": "python",
"repo": "Platron/python-sdk",
"path": "/tests/integration/receipt_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_create_transaction_chain(self):
builder = InitPaymentBuilder('20.00', 'test')
client = PostClient(self.get_merchant_id(), self.get_secret_key())
result = client.request(builder)
root = fromstring(result)
pg_payment_id = root.find('pg_payment_id').text
... | code_fim | medium | {
"lang": "python",
"repo": "Platron/python-sdk",
"path": "/tests/integration/receipt_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>GPG_NO_DEFAULT_KEYRING_OPTION = "--no-default-keyring"
GPG_KEYRING_ARG = "--keyring"
def verify_signature(signed_file_path, output_file_path):
"""Verifies the signed file's signature.
Returns:
True : If the signature is valid.
False : If the signature is invalid.
"""
... | code_fim | medium | {
"lang": "python",
"repo": "Bpoe/PowerShell-DSC-for-Linux",
"path": "/Providers/nxOMSAutomationWorker/automationworker/worker/gpg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if proc.poll() == 0:
tracer.log_debug_trace("Signature is valid.")
return True
tracer.log_sandbox_job_runbook_signature_validation_failed(stderr)
return False<|fim_prefix|># repo: Bpoe/PowerShell-DSC-for-Linux path: /Providers/nxOMSAutomationWorker/automationworker/worker/gpg... | code_fim | hard | {
"lang": "python",
"repo": "Bpoe/PowerShell-DSC-for-Linux",
"path": "/Providers/nxOMSAutomationWorker/automationworker/worker/gpg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Bpoe/PowerShell-DSC-for-Linux path: /Providers/nxOMSAutomationWorker/automationworker/worker/gpg.py
#!/usr/bin/env python2
#
# Copyright (C) Microsoft Corporation, All rights reserved.
"""Gpg module. Used for runbook signature validation."""
import os
import subprocess
import configuration
imp... | code_fim | hard | {
"lang": "python",
"repo": "Bpoe/PowerShell-DSC-for-Linux",
"path": "/Providers/nxOMSAutomationWorker/automationworker/worker/gpg.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jamartinh/ReinforcementLearning path: /FAReinforcement/Environments/ProleEnvironment.py
from numpy import *
from numpy.random import *
from visual import *
from visual.graph import *
from math import *
LIM_X0=0.0000000000000000000000000000000000000000001
class InertMachine:
def... | code_fim | hard | {
"lang": "python",
"repo": "jamartinh/ReinforcementLearning",
"path": "/FAReinforcement/Environments/ProleEnvironment.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if sqrt(sum((self.Zorro.state.x-self.Pata.state.x)**2 )) > 2.0:
self.Zorro.react(self.Patito,1)
else:
self.Zorro.react(self.Pata,-1)
self.Patito.react(self.Pata,1)
self.Patito2.react(self.Patito,1)
self.Pata.update()
se... | code_fim | hard | {
"lang": "python",
"repo": "jamartinh/ReinforcementLearning",
"path": "/FAReinforcement/Environments/ProleEnvironment.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Goal Position
goalPos = (8,8,0)
def __init__(self):
self.initGraphs()
def GetInitialState(self):
self.StartEpisode()
return self.cur_state
def UpdateState(self):
temp1 = array([self.goal.x,self.goal.y,self.Zorro.x,self.Zorro.y,self.Pat... | code_fim | hard | {
"lang": "python",
"repo": "jamartinh/ReinforcementLearning",
"path": "/FAReinforcement/Environments/ProleEnvironment.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hegu2692/autism_rnaseq path: /post_processing/diff_genes/split_gene_name.py
import pandas as pd
import sys
data=open(sys.argv[1],'r').read().strip().split('\n')
header=data[0].split('\<|fim_suffix|>enename=''.join(gene[1::])
outf.write(ensgid+'\t'+genename+'\t'+'\t'.join(tokens[1::])+'\n')
ou... | code_fim | hard | {
"lang": "python",
"repo": "hegu2692/autism_rnaseq",
"path": "/post_processing/diff_genes/split_gene_name.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>enename=''.join(gene[1::])
outf.write(ensgid+'\t'+genename+'\t'+'\t'.join(tokens[1::])+'\n')
outf.close()<|fim_prefix|># repo: hegu2692/autism_rnaseq path: /post_processing/diff_genes/split_gene_name.py
import pandas as pd
import sys
data=open(sys.argv[1],'r').read().strip().split('\n')
header=data[0... | code_fim | hard | {
"lang": "python",
"repo": "hegu2692/autism_rnaseq",
"path": "/post_processing/diff_genes/split_gene_name.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> x = XOR(1001, 0010) = 1011, which is 11 in decimal.
y = f(1011) = 'k'
c = 'i' + 'k' = "ik"
So the encrypted text c = "ik".
To decrypt we simply apply the one-time pad with the same key but to c = "ik".
### How does the XOR operation work in general?
Given two binary strings A ... | code_fim | hard | {
"lang": "python",
"repo": "nbro/ands",
"path": "/ands/algorithms/crypto/one_time_pad.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nbro/ands path: /ands/algorithms/crypto/one_time_pad.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
# Meta-info
Author: Nelson Brochado
Created: 10/08/2015
Updated: 18/09/2017
# Description
One time pad (or, in short, OTP) is an encryption technique that cannot be
cracked, but requir... | code_fim | hard | {
"lang": "python",
"repo": "nbro/ands",
"path": "/ands/algorithms/crypto/one_time_pad.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> i = 'h'
j = 'a'
h(i) = 8
h(j) = 1
In binary, h(i) = 8 is 1000 and h(j) = 1 is 0001.
x = XOR(1000, 0001) = 1001, which is 9 in decimal.
y = f(1001) = 'i'
c = '' + 'i' = "i"
Let n = 2.
i = 'i'
j = 'b'
h(i) = 9
... | code_fim | hard | {
"lang": "python",
"repo": "nbro/ands",
"path": "/ands/algorithms/crypto/one_time_pad.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # # Vary the pool of individuals
offspring = algorithms.varAnd(offspring, toolbox, cxpb, mutpb)
# Evaluate the individuals with an invalid fitness
invalid_ind = [ind for ind in offspring if not ind.fitness.valid]
fitnesses = toolbox.map(toolbox.evaluate, invalid_i... | code_fim | hard | {
"lang": "python",
"repo": "jacksonpradolima/tcpci-search-based",
"path": "/algorithm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jacksonpradolima/tcpci-search-based path: /algorithm.py
from deap import algorithms
def eaSimple(population, toolbox, cxpb, mutpb, ngen, stats=None,
halloffame=None, verbose=__debug__):
"""This algorithm reproduce the simplest evolutionary algorithm as
presented in chapter ... | code_fim | hard | {
"lang": "python",
"repo": "jacksonpradolima/tcpci-search-based",
"path": "/algorithm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Begin the generational process
gen = 1
found_best = False
# Run the algorithm until a "convergence"
while gen <= ngen and not found_best:
# Select the next generation individuals
offspring = toolbox.select(population, len(population))
# # Vary the pool of in... | code_fim | hard | {
"lang": "python",
"repo": "jacksonpradolima/tcpci-search-based",
"path": "/algorithm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: qookei/xbstrap path: /xbstrap/util.py
# SPDX-License-Identifier: MIT
import os
import urllib.parse
import urllib.request
<|fim_suffix|> if not prepend:
return
joined = ':'.join(prepend)
if varname in environ and environ[varname]:
environ[varname] = joined + ':' + environ[varname]
else:
... | code_fim | medium | {
"lang": "python",
"repo": "qookei/xbstrap",
"path": "/xbstrap/util.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> temp_path = path + '.download'
urllib.request.urlretrieve(url, temp_path, show_progress)
os.rename(temp_path, path)
print()<|fim_prefix|># repo: qookei/xbstrap path: /xbstrap/util.py
# SPDX-License-Identifier: MIT
import os
import urllib.parse
import urllib.request
def build_environ_paths(environ, ... | code_fim | hard | {
"lang": "python",
"repo": "qookei/xbstrap",
"path": "/xbstrap/util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if isinstance(dset, xr.DataArray):
dset = dset.to_dataset(name="data")
encoding = {k: {"zlib": True} for k in dset.data_vars}
logger.info(f"saving to {f}")
dset.to_netcdf(f, engine=engine, encoding=encoding)
logger.info(f"Wrote {f.stem}.nc size={f.stat().st_size/1e6} M")<|fim_p... | code_fim | medium | {
"lang": "python",
"repo": "icarofua/seq2seq-time",
"path": "/seq2seq_time/util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: icarofua/seq2seq-time path: /seq2seq_time/util.py
from pathlib import Path
import torch
import xarray as xr
import logging
logger = logging.getLogger(__file__)
project_dir = Path(__file__).parent.parent
def to_numpy(x):
"""Helper function to avoid repeating code"""
if isinstance(x, torc... | code_fim | medium | {
"lang": "python",
"repo": "icarofua/seq2seq-time",
"path": "/seq2seq_time/util.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Checks if the current day is weekend.
:returns: True when the current day is weekend.
"""
return datetime.today().weekday() > 3<|fim_prefix|># repo: lulivi/gol-bot path: /gol/utils.py
# Copyright (c) 2021 Luis Liñán Villafranca. All rights reserved.
#
# This work is licensed under th... | code_fim | easy | {
"lang": "python",
"repo": "lulivi/gol-bot",
"path": "/gol/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lulivi/gol-bot path: /gol/utils.py
# Copyright (c) 2021 Luis Liñán Villafranca. All rights reserved.
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>
"""Utitilites for the push-ups counter."""
from datetime import datetime
<|f... | code_fim | medium | {
"lang": "python",
"repo": "lulivi/gol-bot",
"path": "/gol/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
return datetime.today().weekday() > 3<|fim_prefix|># repo: lulivi/gol-bot path: /gol/utils.py
# Copyright (c) 2021 Luis Liñán Villafranca. All rights reserved.
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>
"""Utitilites f... | code_fim | medium | {
"lang": "python",
"repo": "lulivi/gol-bot",
"path": "/gol/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # fill the function, too
numberOfDays = daysByMonth[month]
sameDayMonths = monthByDays[numberOfDays]
for month in sameDayMonths:
if month != inputMonth:
print(month)<|fim_prefix|># repo: rongpenl/k16math-course path: /exercises/solution_01_11_02.py
daysByMonth = {
... | code_fim | hard | {
"lang": "python",
"repo": "rongpenl/k16math-course",
"path": "/exercises/solution_01_11_02.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rongpenl/k16math-course path: /exercises/solution_01_11_02.py
daysByMonth = {
"January": 31,
"February": 28,
"March": 31,
"April": 30,
"May": 31,
"June": 30,
"July": 31,
"August": 31,
"September": 30,
"October": 31,
"November": 30,
"December": 31
} ... | code_fim | hard | {
"lang": "python",
"repo": "rongpenl/k16math-course",
"path": "/exercises/solution_01_11_02.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def end_test(self, name, attributes):
""" The `end test` hook """
print(f"test ended with result : {attributes['status']} ")
if attributes['status'] == "FAIL":
CustomUtils.take_screenshot(f"{name}.png")
def close(self):
'''
'''
print("c... | code_fim | hard | {
"lang": "python",
"repo": "sohailchd/RobotAndLocust",
"path": "/nba_automation/utilities/CustomListener.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sohailchd/RobotAndLocust path: /nba_automation/utilities/CustomListener.py
from utilities.BrowserManager import BrowserManager
from robot.libraries.BuiltIn import BuiltIn
from robot.libraries.Screenshot import Screenshot
import conf
from utilities.CustomUtils import CustomUtils
from robot.api imp... | code_fim | medium | {
"lang": "python",
"repo": "sohailchd/RobotAndLocust",
"path": "/nba_automation/utilities/CustomListener.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: decentral1se/django-stubs path: /django-stubs/db/models/manager.pyi
from typing import Any, Optional
class BaseManager:
creation_counter: int = ...
auto_created: bool = ...
use_in_migrations: bool = ...
def __new__(cls, *args: Any, **kwargs: Any): ...
model: Any = ...
na... | code_fim | medium | {
"lang": "python",
"repo": "decentral1se/django-stubs",
"path": "/django-stubs/db/models/manager.pyi",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class EmptyManager(Manager):
model: Any = ...
def __init__(self, model: Any) -> None: ...
def get_queryset(self): ...<|fim_prefix|># repo: decentral1se/django-stubs path: /django-stubs/db/models/manager.pyi
from typing import Any, Optional
class BaseManager:
creation_counter: int = ...... | code_fim | hard | {
"lang": "python",
"repo": "decentral1se/django-stubs",
"path": "/django-stubs/db/models/manager.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def distinct(self, column):
"""
Count the number of distinct fields in the currently selected MongoDB
collection's specified column.
:param str field: name of the column for counting distinct addresses.
:returns: the number of packets matching the filter in th... | code_fim | hard | {
"lang": "python",
"repo": "Totoro2205/CovertMark",
"path": "/CovertMark/data/retrieve.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> :returns: if all input filters present are valid, returns the filters,
otherwise returns False.
"""
collections = self.list(in_string=False)
this_collection = None
for collection in collections:
if collection["name"] == self._collection:
... | code_fim | hard | {
"lang": "python",
"repo": "Totoro2205/CovertMark",
"path": "/CovertMark/data/retrieve.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Totoro2205/CovertMark path: /CovertMark/data/retrieve.py
from . import utils, constants, mongo
from base64 import b64decode
class Retriever:
def __init__(self):
self.__db = mongo.MongoDBManager(db_server=constants.MONGODB_SERVER)
self._collection = None
def list(self,... | code_fim | hard | {
"lang": "python",
"repo": "Totoro2205/CovertMark",
"path": "/CovertMark/data/retrieve.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DincerDogan/Data-Science-Learning-Path path: /Data Scientist Career Path/9. Data Visualization/1. Matplotlib/3. Recreate Graphs/2. side.py
import codecademylib
from matplotlib import pyplot as plt
unit_topics = ['Limits', 'Derivatives', 'Integrals', 'Diff Eq', 'Applications']
middle_school_a = [... | code_fim | hard | {
"lang": "python",
"repo": "DincerDogan/Data-Science-Learning-Path",
"path": "/Data Scientist Career Path/9. Data Visualization/1. Matplotlib/3. Recreate Graphs/2. side.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return [t*x + w*n for x in range(d)]
# Make your chart here
school_a_x = create_x(2, 0.8, 1, 5)
school_b_x = create_x(2, 0.8, 2, 5)
# Make your chart here
plt.figure(figsize=(10,8))
ax = plt.subplot()
plt.bar(school_a_x, middle_school_a)
plt.bar(school_b_x,middle_school_b)
middle_x = [ (a + b) / 2.0... | code_fim | medium | {
"lang": "python",
"repo": "DincerDogan/Data-Science-Learning-Path",
"path": "/Data Scientist Career Path/9. Data Visualization/1. Matplotlib/3. Recreate Graphs/2. side.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #### Generate boundary-planpe orientations
l_p_po = l1.l_p_po
l_po_p = np.linalg.inv(l_p_po)
T_p1top2_po1 = np.dot(l_p_po, np.dot(T_p1top2_p1, l_po_p))
## Find the corresponding disorientation
quat1 = gbt.mat2quat(T_p1top2_po1)
# print(quat1)
... | code_fim | hard | {
"lang": "python",
"repo": "spatala/gbpy",
"path": "/gbpy/byxtal/tests/enumerate_cubicCSL_props.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: spatala/gbpy path: /gbpy/byxtal/tests/enumerate_cubicCSL_props.py
##################################################################
## Code to enumerate the properties of the CSL/DSC lattices for
## Sigma misorientations
## The code currently works for cubic lattices.
###########################... | code_fim | hard | {
"lang": "python",
"repo": "spatala/gbpy",
"path": "/gbpy/byxtal/tests/enumerate_cubicCSL_props.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: appcoreopc/python-polar-coding path: /tests/test_sc_list/test_codec.py
from unittest import TestCase
from python_polar_coding.polar_codes.sc_list import SCListPolarCodec
from tests.base import BasicVerifyPolarCode
class TestSCListPolarCode1024_512_4(BasicVerifyPolarCode, TestCase):
<|fim_suffi... | code_fim | medium | {
"lang": "python",
"repo": "appcoreopc/python-polar-coding",
"path": "/tests/test_sc_list/test_codec.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> polar_code_class = SCListPolarCodec
code_parameters = {
'N': 1024,
'K': 512,
'L': 4,
}
class TestSCListPolarCode1024_512_8(BasicVerifyPolarCode, TestCase):
polar_code_class = SCListPolarCodec
code_parameters = {
'N': 1024,
'K': 512,
'L'... | code_fim | medium | {
"lang": "python",
"repo": "appcoreopc/python-polar-coding",
"path": "/tests/test_sc_list/test_codec.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mstepniowski/django-newtagging path: /newtagging/models.py
"""
Create a queryset matching all tags associated with the given
object.
"""
ctype = ContentType.objects.get_for_model(obj)
return self.filter(items__content_type__pk=ctype.pk,
... | code_fim | hard | {
"lang": "python",
"repo": "mstepniowski/django-newtagging",
"path": "/newtagging/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class TaggedItemManager(models.Manager):
"""
FIXME There's currently no way to get the ``GROUP BY`` and ``HAVING``
SQL clauses required by many of this manager's methods into
Django's ORM.
For now, we manually execute a query to retrieve the PKs of
objects... | code_fim | hard | {
"lang": "python",
"repo": "mstepniowski/django-newtagging",
"path": "/newtagging/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not tag_count:
return model._default_manager.none()
model_table = qn(model._meta.db_table)
# This query selects the ids of all objects which have any of
# the given tags.
query = """
SELECT %(model_pk)s
FROM %(model)s, %(tagged_item)s... | code_fim | hard | {
"lang": "python",
"repo": "mstepniowski/django-newtagging",
"path": "/newtagging/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ataque" ):
print("Jogador 2 venceu")
elif (d == "pedra"):
print("Jogador 2 venceu")
else :
print("Ambos venceram")<|fim_prefix|># repo: rmaycon7/uri-codes path: /python_python3/2031.py
b = input()
for i in range (b):
c = raw_input ()
d = raw_input ()
if (c == "ataque"):
if(d=="ataque"):... | code_fim | hard | {
"lang": "python",
"repo": "rmaycon7/uri-codes",
"path": "/python_python3/2031.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rmaycon7/uri-codes path: /python_python3/2031.py
b = input()
for i in range (b):
c = raw_input ()
d = raw_input ()
if (c == "ataque"):
if(d=="ataque"):
print("Aniquila<|fim_suffix|>f(d == "papel"):
print("Jogador 1 venceu")
elif(d == "pedra"):
print("Sem ganhador")
elif (c == "pa... | code_fim | medium | {
"lang": "python",
"repo": "rmaycon7/uri-codes",
"path": "/python_python3/2031.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> damage = TurnBuilder()\
.attack(AttackBuilder(d(10))
.prof(3)
.amod(3)
.adv()
.gwm()
.attbon(3)
.dmgbon(2), times=2)\
.attack(AttackBuilder(d(4))
.prof(3)
.am... | code_fim | hard | {
"lang": "python",
"repo": "s-zhang/DnDnProbabilities",
"path": "/src/tests/attack_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert 1.0000000000000002 == AttackBuilder(d(1))\
.attbon(-20)\
.crit(0)\
.resolve(0)\
.p(2)
def test_resolve_turn_attacks():
damage = TurnBuilder()\
.attack(AttackBuilder(d(10))
.prof(3)
.amod(3)
.adv()
... | code_fim | hard | {
"lang": "python",
"repo": "s-zhang/DnDnProbabilities",
"path": "/src/tests/attack_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: s-zhang/DnDnProbabilities path: /src/tests/attack_test.py
from dnd import AttackBuilder, HitOutcome, TurnBuilder, d
def test_resolve_hit():
test_attack = AttackBuilder(d(10))\
.prof(3)\
.amod(3)\
.adv()\
.gwm()\
.attbon(3)\
.dmgbon(2)\
... | code_fim | hard | {
"lang": "python",
"repo": "s-zhang/DnDnProbabilities",
"path": "/src/tests/attack_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nikankind/Reproduce-Article-Representation-Flow-for-Action-Recognition-with-PaddlePaddle path: /hmdb_dataset.py
# import torch
# import torch.utils.data as data_utl
import numpy as np
import random
import os
from PIL import Image
from io import BytesIO
import pickle
import paddle
import funct... | code_fim | hard | {
"lang": "python",
"repo": "nikankind/Reproduce-Article-Representation-Flow-for-Action-Recognition-with-PaddlePaddle",
"path": "/hmdb_dataset.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> np_imgs = (np.array(imgs[0]).astype('float32').transpose(
(2, 0, 1))).reshape(1, 3, target_size, target_size) / 255
for i in range(len(imgs) - 1):
img = (np.array(imgs[i + 1]).astype('float32').transpose(
(2, 0, 1))).reshape(1, 3, target_size, target... | code_fim | hard | {
"lang": "python",
"repo": "nikankind/Reproduce-Article-Representation-Flow-for-Action-Recognition-with-PaddlePaddle",
"path": "/hmdb_dataset.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> )
return paddle.reader.xmap_readers(mapper, reader, num_threads, buf_size)
def __len__(self):
return len(self.data)
'''
def imgs_transform(imgs, label, mode, seg_num, seglen, short_size,
target_size, img_mean, img_std):
imgs = group_... | code_fim | hard | {
"lang": "python",
"repo": "nikankind/Reproduce-Article-Representation-Flow-for-Action-Recognition-with-PaddlePaddle",
"path": "/hmdb_dataset.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hypothesis/h path: /tests/h/models/document/_meta_test.py
from datetime import datetime, timedelta
from unittest.mock import Mock
import pytest
import sqlalchemy as sa
from h_matchers import Any
from h.models import Document, DocumentMeta
from h.models.document import ConcurrentUpdateError, cre... | code_fim | hard | {
"lang": "python",
"repo": "hypothesis/h",
"path": "/tests/h/models/document/_meta_test.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> document = db_session.query(Document).get(document.id)
assert document.title == final_title
def test_it_logs_a_warning_with_existing_meta_on_a_different_doc(
self, log, mock_db_session, factories, meta_attrs
):
document_one = factories.Document()
document_t... | code_fim | hard | {
"lang": "python",
"repo": "hypothesis/h",
"path": "/tests/h/models/document/_meta_test.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> finally:
sdk_marathon.destroy_app(client_id)
@pytest.mark.dcos_min_version('1.10')
@sdk_utils.dcos_ee_only
@pytest.mark.sanity
def test_client_can_read_and_write(kafka_client):
topics = sdk_cmd.svc_cli(config.PACKAGE_NAME, config.SERVICE_NAME, "topic create securetest", json=True)
l... | code_fim | hard | {
"lang": "python",
"repo": "olsky/dcos-commons",
"path": "/frameworks/kafka/tests/test_auth.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: olsky/dcos-commons path: /frameworks/kafka/tests/test_auth.py
import logging
import pytest
import subprocess
import uuid
import sdk_auth
import sdk_cmd
import sdk_hosts
import sdk_install
import sdk_marathon
import sdk_tasks
import sdk_utils
from tests import config
log = logging.getLogger(__n... | code_fim | hard | {
"lang": "python",
"repo": "olsky/dcos-commons",
"path": "/frameworks/kafka/tests/test_auth.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
client_id = "kafka-client"
client = {
"id": client_id,
"mem": 512,
"user": "nobody",
"container": {
"type": "MESOS",
"docker": {
"image": "elezar/kafka-client:latest",
... | code_fim | hard | {
"lang": "python",
"repo": "olsky/dcos-commons",
"path": "/frameworks/kafka/tests/test_auth.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # self.runner.step_var+=1
data = self.runner.get_next()
loss = self.alg.step(data)
# save_to_file('new_logs/random_loss.csv', {'loss':loss})
yield data, loss
while not self.runner.trajectory_is_stale():
data = self.runner.get_next()
l... | code_fim | hard | {
"lang": "python",
"repo": "NinaMaz/NAS_RL_torch",
"path": "/learners/learners.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NinaMaz/NAS_RL_torch path: /learners/learners.py
import numpy as np
import torch
from base.base import Learner
from runners.runners import make_ppo_runner, SavedRewardsResetsRunner
from selection.select_layers import SelectModelFromLayers
from utils.additional import GPU_ids
from .policies_algs ... | code_fim | hard | {
"lang": "python",
"repo": "NinaMaz/NAS_RL_torch",
"path": "/learners/learners.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: liujuanLT/InsightFace_TF path: /nets/mobilenetv2.py
# Architecture based on MobileNetV2 https://arxiv.org/pdf/1801.04381.pdf
#https://github.com/ohadlights/mobilenetv2/blob/master/mobilenetv2.py
import tensorflow as tf
import tensorflow.contrib.slim as slim
def block(net, input_filters, output_... | code_fim | hard | {
"lang": "python",
"repo": "liujuanLT/InsightFace_TF",
"path": "/nets/mobilenetv2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> net = blocks(net=net, expansion=expansion, output_filters=24, repeat=2, stride=2)
net = blocks(net=net, expansion=expansion, output_filters=32, repeat=3, stride=2)
net = blocks(net=net, expansion=expansion, output_filters=64, repeat=4, stride=2)
net = blo... | code_fim | hard | {
"lang": "python",
"repo": "liujuanLT/InsightFace_TF",
"path": "/nets/mobilenetv2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pick_list = [slice_stats]
# Read picks
for pick_file_name in os.listdir(subdir_full_path):
# Parse name
name_split = pick_file_name.split('.')
if type(name_split) is not list:
continue
... | code_fim | hard | {
"lang": "python",
"repo": "jamm1985/seismo-ml-phase-picker",
"path": "/utils/picks_slicing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Check if picks section started
if len(line) > 25:
if line[0:len(picks_line)] == picks_line:
picks_started = True
return [id, picks_dists, picks_seconds]
def get_picks(reading_path, archive_definitions=[]):
"""
Reads S-file and sl... | code_fim | hard | {
"lang": "python",
"repo": "jamm1985/seismo-ml-phase-picker",
"path": "/utils/picks_slicing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jamm1985/seismo-ml-phase-picker path: /utils/picks_slicing.py
# if id_str == '20140413140958':
# print(x[0])
# if True:#x[0] == 'NKL':
# trace.integrate()
... | code_fim | hard | {
"lang": "python",
"repo": "jamm1985/seismo-ml-phase-picker",
"path": "/utils/picks_slicing.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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