text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>
def main():
try:
arguments = docopt.docopt(__doc__)
obs_dir = arguments['--obs_dir']
out_dir = arguments['--out_dir']
jobs = []
for jsonl_path in glob(join(obs_dir, '*', '*', '*', '*.phs.jsonl.gz')):
p = fact.path.parse(jsonl_path)
phs_... | code_fim | hard | {
"lang": "python",
"repo": "fact-project/photon_stream_production",
"path": "/photon_stream_production/ethz/scoop_jsonl2binary.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TeaganBriggs/cryptobeet path: /standard/config.py
import datetime
TRAIN_MODELS = True
db_ds = 'data/bitfinex_data.h5'
db_path = 'data/bout.h5'
# Training Parameters
feature_size = 2
start_date_train = datetime.datetime(2018, 10, 28)
end_date_train = datetime.datetime(2018, 11, 8)
train_test_r... | code_fim | hard | {
"lang": "python",
"repo": "TeaganBriggs/cryptobeet",
"path": "/standard/config.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Exchange Simulation Parameters
fee = 0.002
start_date_test = datetime.datetime(2018, 11, 8)
end_date_test = datetime.datetime.now() # datetime.datetime(2018, 4, 16)
max_size_of_trade_set = 288 # np.inf<|fim_prefix|># repo: TeaganBriggs/cryptobeet path: /standard/config.py
import datetime
TRAIN_MOD... | code_fim | hard | {
"lang": "python",
"repo": "TeaganBriggs/cryptobeet",
"path": "/standard/config.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hoelsner/product-database path: /app/productdb/migrations/0012_auto_20160725_2252.py
# -*- coding: utf-8 -*-
# Generated by Django 1.9.6 on 2016-07-25 20:52
from __future__ import unicode_literals
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
('productdb', '... | code_fim | medium | {
"lang": "python",
"repo": "hoelsner/product-database",
"path": "/app/productdb/migrations/0012_auto_20160725_2252.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Migration(migrations.Migration):
dependencies = [
('productdb', '0011_userprofile_regex_search'),
]
operations = [
migrations.AlterField(
model_name='userprofile',
name='regex_search',
field=models.BooleanField(default=False, help_tex... | code_fim | medium | {
"lang": "python",
"repo": "hoelsner/product-database",
"path": "/app/productdb/migrations/0012_auto_20160725_2252.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sameerAhmad101/Registrationshop path: /ui/widgets/SliceCompareViewerWidget.py
"""
SliceCompareViewerWidget
:Authors:
Berend Klein Haneveld
"""
from vtk import vtkRenderer
from vtk import vtkInteractorStyleUser
from vtk import vtkCellPicker
from vtk import vtkImageMapToColors
from vtk import vt... | code_fim | hard | {
"lang": "python",
"repo": "sameerAhmad101/Registrationshop",
"path": "/ui/widgets/SliceCompareViewerWidget.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def charTyped(self, arg1, arg2):
# print arg1.GetKeyCode()
pass
def setLocatorPosition(self, position):
for actor in self.locator:
actor.SetPosition(position[0], position[1], position[2])
def setFixedImageData(self, fixed):
self.fixedImagedata = fixed
def setSlicerWidget(self, fixed, mov... | code_fim | hard | {
"lang": "python",
"repo": "sameerAhmad101/Registrationshop",
"path": "/ui/widgets/SliceCompareViewerWidget.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: y000k/sudoku path: /strategy/singleton.py
#
# Singleton strategy module
#
from logger import *
from playbook import *
from sudoku import *
class Singleton(Strategy):
__metaclass__ = StrategyMeta
"""
SINGLETON is the most rudimentary strategy in Sudoku that updates
the possible... | code_fim | medium | {
"lang": "python",
"repo": "y000k/sudoku",
"path": "/strategy/singleton.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.refresh_node(plan, node)
"""
Refresh all nodes.
"""
def run(self, plan):
return any([self.singleton(plan, plan.get_sudoku().get_node(i, j))
for i in range(9) for j in range(9)])<|fim_prefix|># repo: y000k/sudoku path: /strategy/singleton.py... | code_fim | hard | {
"lang": "python",
"repo": "y000k/sudoku",
"path": "/strategy/singleton.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>parser = argparse.ArgumentParser(description='Translates CSV into XML')
parser.add_argument('inp_file', help='CSV input file')
args = parser.parse_args()
inp_fn = args.inp_file
files = glob.glob(os.path.join(inp_fn, "*.txt"))
files = natsort.natsorted(files)
for f in files:
classnames, imnames, max... | code_fim | hard | {
"lang": "python",
"repo": "mseals1/pytorch-faster-rcnn",
"path": "/voc_only_logs/parse.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mseals1/pytorch-faster-rcnn path: /voc_only_logs/parse.py
# parses the txt files and writes csv files from the given dir of text files
import argparse
import pandas as pd
import os
import matplotlib.pyplot as plt
import csv
import glob
import natsort
import shutil
def parse(inputfn):
clsns... | code_fim | hard | {
"lang": "python",
"repo": "mseals1/pytorch-faster-rcnn",
"path": "/voc_only_logs/parse.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> The resulting prefix is essentially arbitrary - it would be nice
for it to be uniform at random, but previous attempts to do that
have proven too expensive.
"""
assert not self.is_exhausted
novel_prefix = bytearray()
def append_int(n_bits, value):
... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/hypothesis/py3/hypothesis/internal/conjecture/datatree.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> check_counter = 0
while True:
k = random.getrandbits(n_bits)
try:
child = branch.children[k]
except KeyError:
append_int(n_bits, k)
return byt... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/hypothesis/py3/hypothesis/internal/conjecture/datatree.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: catboost/catboost path: /contrib/python/hypothesis/py3/hypothesis/internal/conjecture/datatree.py
import attr
from hypothesis.errors import Flaky, HypothesisException, StopTest
from hypothesis.internal.compat import int_to_bytes
from hypothesis.internal.conjecture.data import (
ConjectureDa... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/hypothesis/py3/hypothesis/internal/conjecture/datatree.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dealertrack/django-subui-tests path: /tests/__init__.py
from __future__ import print_function, unicode_literals
<|fim_suffix|>settings.configure(
LOGGING_CONFIG={},
)
django.setup()<|fim_middle|>import django
from django.conf import settings
| code_fim | easy | {
"lang": "python",
"repo": "dealertrack/django-subui-tests",
"path": "/tests/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
settings.configure(
LOGGING_CONFIG={},
)
django.setup()<|fim_prefix|># repo: dealertrack/django-subui-tests path: /tests/__init__.py
from __future__ import print_function, unicode_literals
<|fim_middle|>import django
from django.conf import settings
| code_fim | easy | {
"lang": "python",
"repo": "dealertrack/django-subui-tests",
"path": "/tests/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DataDog/integrations-core path: /istio/datadog_checks/istio/metrics.py
istio_agent_pilot_no_ip': 'agent.pilot.no_ip',
'istio_agent_num_outgoing_requests': 'agent.num_outgoing_requests',
'istio_agent_go_memstats_other_sys_bytes': 'agent.go.memstats.other_sys_bytes',
'istio_agent_pilot_... | code_fim | hard | {
"lang": "python",
"repo": "DataDog/integrations-core",
"path": "/istio/datadog_checks/istio/metrics.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>ISTIOD_METRICS = {
# Maintain namespace compatibility from legacy components
# Generic metrics
'go_gc_duration_seconds': 'go.gc_duration_seconds',
'go_goroutines': 'go.goroutines',
'go_info': 'go.info',
'go_memstats_alloc_bytes': 'go.memstats.alloc_bytes',
'go_memstats_alloc_by... | code_fim | hard | {
"lang": "python",
"repo": "DataDog/integrations-core",
"path": "/istio/datadog_checks/istio/metrics.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
ISTIOD_METRICS = {
# Maintain namespace compatibility from legacy components
# Generic metrics
'go_gc_duration_seconds': 'go.gc_duration_seconds',
'go_goroutines': 'go.goroutines',
'go_info': 'go.info',
'go_memstats_alloc_bytes': 'go.memstats.alloc_bytes',
'go_memstats_alloc_b... | code_fim | hard | {
"lang": "python",
"repo": "DataDog/integrations-core",
"path": "/istio/datadog_checks/istio/metrics.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lsd-maddrive/zaWRka-project path: /wr8_software/scripts/_old/maze_solver.py
#!/usr/bin/env python
import numpy as np
import time
import random
from graph_path.maze import *
from graph_path.car_state import *
# import graph_path.gui
import rospy
import actionlib
from actionlib_msgs.msg import ... | code_fim | hard | {
"lang": "python",
"repo": "lsd-maddrive/zaWRka-project",
"path": "/wr8_software/scripts/_old/maze_solver.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if solver.is_goal_completed:
# Signs test
if solver.is_sign_required():
seleceted_sign = int(random.random() * 6)
# seleceted_sign = SIGNS_LEFT
solver.set_vision_sign(seleceted_sign)
... | code_fim | hard | {
"lang": "python",
"repo": "lsd-maddrive/zaWRka-project",
"path": "/wr8_software/scripts/_old/maze_solver.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>:
dados.lista()
elif opcao == 2:
dados.novo()
elif opcao == 3:
titulos.titulo('Sair do sistema... Até logo!')
break
else:
print(f'{c[1]}ERRO! Digite uma opção válida!')<|fim_prefix|># repo: agnaka/CEV-Python-Exercicios pa... | code_fim | hard | {
"lang": "python",
"repo": "agnaka/CEV-Python-Exercicios",
"path": "/Pacote-download/Exercicios/ex115/sistema-1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agnaka/CEV-Python-Exercicios path: /Pacote-download/Exercicios/ex115/sistema-1.py
from Exercicios.ex115.util115 import titulos
from Exercicios.ex115.util115 import dados
c = ('\033[m', # 0 - sem cores
'\033[0;31m', # 1 - vermelho
'\033[0;32m', # 2 - verde
'\033[... | code_fim | hard | {
"lang": "python",
"repo": "agnaka/CEV-Python-Exercicios",
"path": "/Pacote-download/Exercicios/ex115/sistema-1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: madokast/cctpy path: /codes/cctpy/cosy.py
"""
读取 COSY 任意阶矩阵
"""
from typing import List
from cctpy.baseutils import Stream
from cctpy.particle import PhaseSpaceParticle
class CosyMap:
ITEM_LENGTH = len("-0.0000000E+00")
def __init__(self, map: str):
self.map = map
self... | code_fim | hard | {
"lang": "python",
"repo": "madokast/cctpy",
"path": "/codes/cctpy/cosy.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> by_x: int = int(contributionDescribing[0])
by *= x ** by_x
by_xp = int(contributionDescribing[1])
by *= xp ** by_xp
by_y = int(contributionDescribing[2])
by *= y ** by_y
by_yp = int(contributionDescribing[3])
by *= yp ** by_yp
by_... | code_fim | hard | {
"lang": "python",
"repo": "madokast/cctpy",
"path": "/codes/cctpy/cosy.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Huawei-Ascend/modelzoo path: /built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/utils/fpn_utils/weight_init.py
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free ... | code_fim | hard | {
"lang": "python",
"repo": "Huawei-Ascend/modelzoo",
"path": "/built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/utils/fpn_utils/weight_init.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def xavier_init(module, gain=1, bias=0, distribution='normal'):
"""Init weight by Xavier method.
:param module: target module
:type: nn.module
:param gain: gain
:type: float
:param bias: bias of method
:type:float
:distribute: weight distribute
:type: str
"""
... | code_fim | hard | {
"lang": "python",
"repo": "Huawei-Ascend/modelzoo",
"path": "/built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/utils/fpn_utils/weight_init.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param module: target module
:type: nn.module
:param a: a
:type: float
:param b: b
:type: float
:param bias: bias
:type: float
"""
nn.init.uniform_(module.weight, a, b)
if hasattr(module, 'bias') and module.bias is not None:
nn.init.constant_(module.bias... | code_fim | hard | {
"lang": "python",
"repo": "Huawei-Ascend/modelzoo",
"path": "/built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/utils/fpn_utils/weight_init.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: byteshiva/es6-tuts path: /python/algorithms/fibonacci.py
def fib(n, computed = {0: 0, 1: 1}):
<|fim_suffix|>mputed[n] = fib(n-1, computed) + fib(n-2, computed)
return computed[n]<|fim_middle|> if n not in computed:
co | code_fim | easy | {
"lang": "python",
"repo": "byteshiva/es6-tuts",
"path": "/python/algorithms/fibonacci.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>n-2, computed)
return computed[n]<|fim_prefix|># repo: byteshiva/es6-tuts path: /python/algorithms/fibonacci.py
def fib(n, computed = {0: 0, 1: 1}):
<|fim_middle|> if n not in computed:
computed[n] = fib(n-1, computed) + fib( | code_fim | medium | {
"lang": "python",
"repo": "byteshiva/es6-tuts",
"path": "/python/algorithms/fibonacci.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> 'MoniteringSpikeTuplesList':
[
()
],
'PopulatingInitDict':
{
'v':-60.
}
},
**{'CollectingCollectionStr':'Populatome'}
).__setitem__(
'Dis_<Populatome>',
[
{
'PopulatingUnitsInt':3200,
'ConnectingGraspClueVariablesList':
[
SYS.GraspDictClass(
{
... | code_fim | hard | {
"lang": "python",
"repo": "Ledoux/ShareYourSystem",
"path": "/Pythonlogy/ShareYourSystem/Standards/Recorders/Brianer/draft/01_ExampleCell copy.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Definition the AttestedStr
SYS._attest(
[
'MyBrianer is '+SYS._str(
MyBrianer,
**{
'RepresentingBaseKeyStrsList':False,
'RepresentingAlineaIsBool':False
}
),
]
)
#SYS._print(MyBrianer.BrianedMonitorsList[0].__dict__)
#SYS._print(
# MyBrianer.BrianedNeuronGroupsList[0].__dict__
#)
#i... | code_fim | hard | {
"lang": "python",
"repo": "Ledoux/ShareYourSystem",
"path": "/Pythonlogy/ShareYourSystem/Standards/Recorders/Brianer/draft/01_ExampleCell copy.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ledoux/ShareYourSystem path: /Pythonlogy/ShareYourSystem/Standards/Recorders/Brianer/draft/01_ExampleCell copy.py
#ImportModules
import ShareYourSystem as SYS
from ShareYourSystem.Specials.Simulaters import Populater,Brianer
#Definition
MyBrianer=Brianer.BrianerClass(
).update(
{
'Stimula... | code_fim | hard | {
"lang": "python",
"repo": "Ledoux/ShareYourSystem",
"path": "/Pythonlogy/ShareYourSystem/Standards/Recorders/Brianer/draft/01_ExampleCell copy.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert self.request.json is not None
payload = self.request.json
# message = rendered_template("new_user.html", context=payload)
color = "red"
self.say("@all Reported content!", color=color)
self.say("Raw dump:", color=color)
self.say("/code %s" % pa... | code_fim | hard | {
"lang": "python",
"repo": "buddyup/our-will",
"path": "/plugins/biz/product.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return "OK"
@route("/api/event-added", method="POST")
def event_added(self):
assert self.request.json and "event_name" in self.request.json
payload = self.request.json
message = rendered_template("event_added.html", context=payload)
color = "green"
... | code_fim | hard | {
"lang": "python",
"repo": "buddyup/our-will",
"path": "/plugins/biz/product.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: buddyup/our-will path: /plugins/biz/product.py
from will.plugin import WillPlugin
from will.decorators import respond_to, periodic, hear, randomly, route, rendered_template, require_settings
class ProductNotificationPlugin(WillPlugin):
@route("/api/signup", method="POST")
def new_signu... | code_fim | hard | {
"lang": "python",
"repo": "buddyup/our-will",
"path": "/plugins/biz/product.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: devak23/python path: /other_progs/wc.py
class ContentAnalysis:
def __init__(self):
self.line_count = 0 # count the total number of lines in the file
self.char_count = 0 # count the number of characters in the file
self.total_word_count = 0 # count the total word coun... | code_fim | hard | {
"lang": "python",
"repo": "devak23/python",
"path": "/other_progs/wc.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ca = ContentAnalysis()
unique_words = []
with open(file_path, 'r') as fp:
for line in iter(fp.readline, ''):
ca.content.append(line)
ca.line_count += 1
line = line[:-1]
line = line.replace('.', ' ')
... | code_fim | hard | {
"lang": "python",
"repo": "devak23/python",
"path": "/other_progs/wc.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>AUTHOR, VERSION = parse_init()
setup(
name=PKG_NAME,
python_requires=">=3.7",
version=VERSION,
license="MIT",
description="Access context in Starlette",
long_description=get_long_description(),
long_description_content_type="text/markdown",
packages=setuptools.find_packag... | code_fim | medium | {
"lang": "python",
"repo": "yxlwfds/starlette-context",
"path": "/setup.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yxlwfds/starlette-context path: /setup.py
from distutils.core import setup
import setuptools
import os
import re
PKG_NAME = "starlette_context"
HERE = os.path.abspath(os.path.dirname(__file__))
PATTERN = r'^{target}\s*=\s*([\'"])(.+)\1$'
AUTHOR_RE = re.compile(PATTERN.format(target="__auth... | code_fim | medium | {
"lang": "python",
"repo": "yxlwfds/starlette-context",
"path": "/setup.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: powerapi-ng/powerapi path: /powerapi/database/csvdb.py
# Copyright (c) 2021, INRIA
# Copyright (c) 2021, University of Lille
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
... | code_fim | hard | {
"lang": "python",
"repo": "powerapi-ng/powerapi",
"path": "/powerapi/database/csvdb.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Get next row, None otherwise
:param str filename: file name we want to read
"""
try:
return self.tmp_read[filename]['reader'].__next__()
except StopIteration:
return None
def _close_file(self):
for filename in self.f... | code_fim | hard | {
"lang": "python",
"repo": "powerapi-ng/powerapi",
"path": "/powerapi/database/csvdb.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def iter(self, stream_mode: bool) -> CsvIterDB:
"""
Create the iterator for get the data
"""
return CsvIterDB(self, self.filenames, self.report_type, stream_mode)
def connect(self):
"""
Override from BaseDB.
Nothing to do with CSV, because ... | code_fim | hard | {
"lang": "python",
"repo": "powerapi-ng/powerapi",
"path": "/powerapi/database/csvdb.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CGNAM/CGNAM path: /predictor/test.py
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import _init_paths
import time
import torch
import torch.nn.functional as F
import numpy as np
from dataset.data_feeder import DataFeeder
from utils.c... | code_fim | hard | {
"lang": "python",
"repo": "CGNAM/CGNAM",
"path": "/predictor/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> output = F.softmax(output,dim=-1)
output = output[:,1].cpu().numpy()
batch_pred.append(output)
# print(output)
batch_pred = np.stack(batch_pred,axis = 1)
all_pred.append(batch_pred)
test_loss = ... | code_fim | hard | {
"lang": "python",
"repo": "CGNAM/CGNAM",
"path": "/predictor/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = GAT(**model_cfg)
model = model.cuda()
load_checkpoint(model, checkpoint_path)
# print(model)
# model = model.cuda()
model.eval()
try:
# set redution='none' to cal pos and neg loss
loss_fn = torch.nn.CrossEntropyLoss(reduction='none')
except TypeError... | code_fim | hard | {
"lang": "python",
"repo": "CGNAM/CGNAM",
"path": "/predictor/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jsoler/mimeo path: /extras/run_refresh.py
#!/usr/bin/env python
##########
#
# Script to manage running mimeo table replication with a period set in their configuration.
# By default, refreshes are run sequentially in ascending order of their last_run value.
# Parallel refreshes are supported wi... | code_fim | hard | {
"lang": "python",
"repo": "jsoler/mimeo",
"path": "/extras/run_refresh.py",
"mode": "psm",
"license": "PostgreSQL",
"source": "the-stack-v2"
} |
<|fim_suffix|>def single_process(result):
conn = psycopg2.connect(arg_connection)
cur = conn.cursor()
for i in result:
if arg_verbose == 1:
print "Running " + i[1] + " replication for table: " + i[0]
sql = "SELECT " + arg_schema + ".refresh_" + i[1] + "(%s)"
cur.execute(s... | code_fim | hard | {
"lang": "python",
"repo": "jsoler/mimeo",
"path": "/extras/run_refresh.py",
"mode": "spm",
"license": "PostgreSQL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: google/sling path: /python/flags.py
# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http:#www.apache.org/licenses/LICENSE-2.0
#
# U... | code_fim | hard | {
"lang": "python",
"repo": "google/sling",
"path": "/python/flags.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Standard command-line flags.
define("--data",
help="data directory",
default="local/data",
metavar="DIR")
define("--corpora",
help="corpus directory",
metavar="DIR")
define("--workdir",
help="working directory",
metavar="DIR")
define("--repository",
... | code_fim | hard | {
"lang": "python",
"repo": "google/sling",
"path": "/python/flags.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Call all the post-processing hooks.
for callback in hooks: callback(arg)
# Standard command-line flags.
define("--data",
help="data directory",
default="local/data",
metavar="DIR")
define("--corpora",
help="corpus directory",
metavar="DIR")
define("--workdir",
... | code_fim | hard | {
"lang": "python",
"repo": "google/sling",
"path": "/python/flags.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: damononliu/sanity-price-monitor path: /pricemonitor/storing/web3_interface.py
import json
import logging
import time
import requests
import rlp
from ethereum import utils, transactions
from ethereum.abi import ContractTranslator
from pycoin.serialize import b2h, h2b
ADDITIONAL_START_GAS_TO_BE_O... | code_fim | hard | {
"lang": "python",
"repo": "damononliu/sanity-price-monitor",
"path": "/pricemonitor/storing/web3_interface.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self._json_call("eth_estimateGas", [params])
def _make_transaction(self, src_priv_key, dst_address, value, data, use_increased_gas_price):
src_address = b2h(utils.privtoaddr(src_priv_key))
nonce_rs = self._get_num_transactions(src_address)
nonce = int(nonce_rs, ... | code_fim | hard | {
"lang": "python",
"repo": "damononliu/sanity-price-monitor",
"path": "/pricemonitor/storing/web3_interface.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def ball_reset(self):
self.goto(0, 0)
self.ball_speed = 0.1
self.x_val *= -1<|fim_prefix|># repo: Akshaya-LR/100DaysOfCodeChallenge path: /Pong/ball.py
from turtle import Turtle
class Ball(Turtle):
def __init__(self):
super().__init__()
self.shap... | code_fim | medium | {
"lang": "python",
"repo": "Akshaya-LR/100DaysOfCodeChallenge",
"path": "/Pong/ball.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.goto(0, 0)
self.ball_speed = 0.1
self.x_val *= -1<|fim_prefix|># repo: Akshaya-LR/100DaysOfCodeChallenge path: /Pong/ball.py
from turtle import Turtle
class Ball(Turtle):
def __init__(self):
<|fim_middle|> super().__init__()
self.shape("circle")
... | code_fim | hard | {
"lang": "python",
"repo": "Akshaya-LR/100DaysOfCodeChallenge",
"path": "/Pong/ball.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Akshaya-LR/100DaysOfCodeChallenge path: /Pong/ball.py
from turtle import Turtle
class Ball(Turtle):
def __init__(self):
super().__init__()
self.shape("circle")
self.penup()
self.shapesize(stretch_wid=1, stretch_len=1)
self.color("white")
... | code_fim | medium | {
"lang": "python",
"repo": "Akshaya-LR/100DaysOfCodeChallenge",
"path": "/Pong/ball.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> B, N, _ = proposals.shape
proposals = proposals.view(B, N, self.cfg.NUM_CLASSES, -1)
boxes, scores = proposals.split([self.cfg.BOX_DOF, 1], dim=-1)
return boxes, scores.squeeze(-1)
def forward(self, points, features):
features = features.permute(0, 2, 1)
... | code_fim | hard | {
"lang": "python",
"repo": "jtpils/PV-RCNN",
"path": "/pvrcnn/detector/proposal.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> boxes, scores = self(points, features)
_, indices = torch.topk(scores, k=self.cfg.PROPOSAL.TOPK, dim=1)
scores = scores.gather(1, indices)
boxes = boxes.gather(1, indices.expand(-1, -1, boxes.shape[-1]))
return boxes, scores
def reorganize_proposals(self, propo... | code_fim | hard | {
"lang": "python",
"repo": "jtpils/PV-RCNN",
"path": "/pvrcnn/detector/proposal.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jtpils/PV-RCNN path: /pvrcnn/detector/proposal.py
import torch
from torch import nn
import torch.nn.functional as F
from .mlp import MLP
class ProposalLoss(nn.Module):
def __init__(self, cfg):
super(ProposalLoss, self).__init__()
self.cfg = cfg
self.anchors = self.... | code_fim | hard | {
"lang": "python",
"repo": "jtpils/PV-RCNN",
"path": "/pvrcnn/detector/proposal.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> key = get_ref_id(key)
path = _get_cache_path(self.path, key)
path.parent.mkdir(parents=True, exist_ok=True)
mode = 'wt' if text else 'wb'
encoding = 'utf-8' if text else None
with path.open(mode, encoding=encoding) as f:
yield f
def fetch(conte... | code_fim | hard | {
"lang": "python",
"repo": "atviriduomenys/spinta",
"path": "/spinta/fetcher.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: atviriduomenys/spinta path: /spinta/fetcher.py
from contextlib import contextmanager
from pathlib import Path
from spinta.utils.refs import get_ref_id
from spinta.components import Context
def _get_cache_path(base: Path, key: str) -> Path:
return base / key[:2] / key[2:4] / key[4:]
<|fim... | code_fim | hard | {
"lang": "python",
"repo": "atviriduomenys/spinta",
"path": "/spinta/fetcher.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_inequality(self):
assert CondaRequirement("x") != CondaRequirement("x=1.2")
class TestCurrentEnvironmentCondaRequirements:
@pytest.mark.service("environment")
@pytest.mark.parametrize(
"options", [{}, {"include_builds": True}, {"explicit_only": False}]
)
@pyt... | code_fim | hard | {
"lang": "python",
"repo": "PrefectHQ/prefect",
"path": "/tests/software/test_conda.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PrefectHQ/prefect path: /tests/software/test_conda.py
import os
import subprocess
from contextlib import nullcontext
from textwrap import dedent
from unittest.mock import MagicMock
import pytest
from prefect.software.conda import (
CONDA_REQUIREMENT,
CondaEnvironment,
CondaError,
... | code_fim | hard | {
"lang": "python",
"repo": "PrefectHQ/prefect",
"path": "/tests/software/test_conda.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_from_file_unsupported_subtype(self, tmp_path):
reqs_file = tmp_path / "requirements.txt"
reqs_file.write_text(
dedent(
"""
name: test
channels:
- defaults
dependencies:
... | code_fim | hard | {
"lang": "python",
"repo": "PrefectHQ/prefect",
"path": "/tests/software/test_conda.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>@task
def shuffler(token_tuples):
# Sort tokens
sorted_tokens = sorted(token_tuples, key=lambda x: x[0])
# Partition tokens
partitions = [
(key, [value for _, value in group])
for key, group in itertools.groupby(sorted_tokens, lambda x: x[0])
]
return partitions
@... | code_fim | hard | {
"lang": "python",
"repo": "swerbo/prefect-with-k8",
"path": "/src/prefect_kube_demo/tasks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: swerbo/prefect-with-k8 path: /src/prefect_kube_demo/tasks.py
import itertools
import requests
from prefect import task
@task
def download_message(url):
<|fim_suffix|>
@task
def mapper(line):
# Strip leading and trailing whitespace,
# make lowercase, and split into tokens
tokens = l... | code_fim | medium | {
"lang": "python",
"repo": "swerbo/prefect-with-k8",
"path": "/src/prefect_kube_demo/tasks.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Sort tokens
sorted_tokens = sorted(token_tuples, key=lambda x: x[0])
# Partition tokens
partitions = [
(key, [value for _, value in group])
for key, group in itertools.groupby(sorted_tokens, lambda x: x[0])
]
return partitions
@task
def reducer(partition):
k... | code_fim | hard | {
"lang": "python",
"repo": "swerbo/prefect-with-k8",
"path": "/src/prefect_kube_demo/tasks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ent': mensagem})
return result.status_code == 200<|fim_prefix|># repo: drmcarvalho/PyQueryMonitor path: /integration.py
import requests
def sendDiscord(mensagem, channelId, token):
result = requests.post(f'https://disco<|fim_middle|>rd.com/api/webhooks/{channelId}/{token}', data={'cont | code_fim | easy | {
"lang": "python",
"repo": "drmcarvalho/PyQueryMonitor",
"path": "/integration.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: drmcarvalho/PyQueryMonitor path: /integration.py
import requests
def sendDiscord(mensagem, channelId, token):
result = requests.post(f'https://disco<|fim_suffix|>ent': mensagem})
return result.status_code == 200<|fim_middle|>rd.com/api/webhooks/{channelId}/{token}', data={'cont | code_fim | easy | {
"lang": "python",
"repo": "drmcarvalho/PyQueryMonitor",
"path": "/integration.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Xiaoyu-Xing/algorithms path: /Lintcode/30 Insert Interval.py
"""
Definition of Interval.
class Interval(object):
def __init__(self, start, end):
self.start = start
self.end = end
"""
<|fim_suffix|> if not newInterval:
return intervals
if not interv... | code_fim | medium | {
"lang": "python",
"repo": "Xiaoyu-Xing/algorithms",
"path": "/Lintcode/30 Insert Interval.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def insert(self, intervals, newInterval):
if not newInterval:
return intervals
if not intervals:
return [newInterval]
new_result = []
insert_pos = 0
for interval in intervals:
if interval.end < newInterval.start:
... | code_fim | medium | {
"lang": "python",
"repo": "Xiaoyu-Xing/algorithms",
"path": "/Lintcode/30 Insert Interval.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> _FAKIR.__init__(self)
self.name = "FAKIRS"
self.specie = 'nouns'
self.basic = "fakir"
self.jsondata = {}<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_fakirs.py
from xai.brain.wordbase.nouns._fakir import _FAKIR
<|fim_middle|>#calss header
class _FAKIRS(_FAKIR, ):
def _... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_fakirs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_fakirs.py
from xai.brain.wordbase.nouns._fakir import _FAKIR
<|fim_suffix|> def __init__(self,):
_FAKIR.__init__(self)
self.name = "FAKIRS"
self.specie = 'nouns'
self.basic = "fakir"
self.jsondata = {}<|fim_middle|>#calss header
class _F... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_fakirs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ESJiang/OpenSimFullBodyWithPython path: /Python/validation_RRA_CMC_trackingErrors_run.py
from readSto import readStoFile
from simFunctions import matRMS
import numpy as np
# Track max translational and rotational positional errors
# from IK -> RRA kinematics, and RRA -> CMC kinematics
# subsets... | code_fim | hard | {
"lang": "python",
"repo": "ESJiang/OpenSimFullBodyWithPython",
"path": "/Python/validation_RRA_CMC_trackingErrors_run.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>print 'max pelvis error'
print ' ', 100*np.amax(np.abs(cmc_run_pErr_pelvisTrans)), ' (trans, cm)'
print ' ', 180/np.pi*np.amax(np.abs(cmc_run_pErr_pelvisRot)), ' (rot, deg)'
print 'max lumbar error'
print ' ', 180/np.pi*np.amax(np.abs(cmc_run_pErr_lumbarRot)), ' (rot, deg)'
print 'max LE error'
prin... | code_fim | hard | {
"lang": "python",
"repo": "ESJiang/OpenSimFullBodyWithPython",
"path": "/Python/validation_RRA_CMC_trackingErrors_run.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># print to console
print 'runing rra/cmc errors'
print 'max rms pelvis error'
print ' ', 100*np.amax(matRMS(cmc_run_pErr_pelvisTrans)), ' (trans, cm)'
print ' ', 100*np.amax(matRMS(cmc_run_pErr_pelvisRot)), ' (rot, deg)'
print 'max rms lumbar error'
print ' ', 100*np.amax(matRMS(cmc_run_pErr_lumbarR... | code_fim | hard | {
"lang": "python",
"repo": "ESJiang/OpenSimFullBodyWithPython",
"path": "/Python/validation_RRA_CMC_trackingErrors_run.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Column Address Set
self._write_cmd(CASET)
self._write_words(((x0>>8) & 0xFF, x0 & 0xFF, (y0>>8) & 0xFF, y0 & 0xFF))
# Page Address Set
self._write_cmd(PASET)
self._write_words(((x1>>8) & 0xFF, x1 & 0xFF, (y1>>8) & 0xFF, y1 & 0xFF))
# Memory Write
... | code_fim | hard | {
"lang": "python",
"repo": "HadrienLG/micropython-ili9341",
"path": "/ili9341/lcd.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HadrienLG/micropython-ili9341 path: /ili9341/lcd.py
notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES O... | code_fim | hard | {
"lang": "python",
"repo": "HadrienLG/micropython-ili9341",
"path": "/ili9341/lcd.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HadrienLG/micropython-ili9341 path: /ili9341/lcd.py
ts for R and B colors
# * just 6 largest bits for G color
# next 2 lines sorting useful data
# getting 4 last bytes
data = unpack('<BI', data)[1]
# reversing them
data = pack('>I', data)... | code_fim | hard | {
"lang": "python",
"repo": "HadrienLG/micropython-ili9341",
"path": "/ili9341/lcd.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: raclab/RACLAB path: /Goruntu Isleme/ornek12.py
#-*-coding: cp1254-*-
###Sekil Algılama2###
import numpy as np
import cv2
def detect(c):
peri=cv2.arcLength(c,True)
approx=cv2.approxPolyDP(c,0.04*peri,True)
if len(approx)==3:
shape="Ucgen"
elif len(approx)==4:
x,y,w,h=cv2.boundingRect(ap... | code_fim | medium | {
"lang": "python",
"repo": "raclab/RACLAB",
"path": "/Goruntu Isleme/ornek12.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
blur=cv2.GaussianBlur(gray,(5,5),0)
thresh=cv2.threshold(blur,60,255,cv2.THRESH_BINARY_INV)[1]
_,cntr,_=cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
for c in cntr:
M = cv2.moments(c)
cX = int((M["m10"] / M["m00"]))
cY = int((M["m0... | code_fim | hard | {
"lang": "python",
"repo": "raclab/RACLAB",
"path": "/Goruntu Isleme/ornek12.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>img=cv2.imread('resimler/sekiller.png')
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
blur=cv2.GaussianBlur(gray,(5,5),0)
thresh=cv2.threshold(blur,60,255,cv2.THRESH_BINARY_INV)[1]
_,cntr,_=cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
for c in cntr:
M = cv2.moments(c)
cX = in... | code_fim | medium | {
"lang": "python",
"repo": "raclab/RACLAB",
"path": "/Goruntu Isleme/ornek12.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Args:
low : the lower range (inclusive)
high : the higher range (exclusive)
"""
super().__init__(torch.distributions.Uniform(low=low, high=high))<|fim_prefix|># repo: PhoenixDL/rising path: /rising/random/continuous.py
from typing import Union
... | code_fim | hard | {
"lang": "python",
"repo": "PhoenixDL/rising",
"path": "/rising/random/continuous.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, low: Union[float, torch.Tensor], high: Union[float, torch.Tensor]):
"""
Args:
low : the lower range (inclusive)
high : the higher range (exclusive)
"""
super().__init__(torch.distributions.Uniform(low=low, high=high))<|fim_pref... | code_fim | hard | {
"lang": "python",
"repo": "PhoenixDL/rising",
"path": "/rising/random/continuous.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PhoenixDL/rising path: /rising/random/continuous.py
from typing import Union
import torch
from torch.distributions import Distribution as TorchDistribution
from rising.random.abstract import AbstractParameter
__all__ = ["ContinuousParameter", "NormalParameter", "UniformParameter"]
class Cont... | code_fim | medium | {
"lang": "python",
"repo": "PhoenixDL/rising",
"path": "/rising/random/continuous.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HIPS/Kayak path: /kayak/__init__.py
# Authors: Harvard Intelligent Probabilistic Systems (HIPS) Group
# http://hips.seas.harvard.edu
# Ryan Adams, David Duvenaud, Scott Linderman,
# Dougal Maclaurin, Jasper Snoek, and others
# Copyright 2014, The President and Fellows o... | code_fim | medium | {
"lang": "python",
"repo": "HIPS/Kayak",
"path": "/kayak/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from differentiable import Differentiable
from root_nodes import Constant, Parameter, DataNode, Inputs, Targets
from batcher import Batcher
from matrix_ops import MatAdd, MatMult, MatElemMult, MatSum, MatMean, Transpose, Reshape, Concatenate, Identity, TensorMult, ListToArray, MatDet
from e... | code_fim | medium | {
"lang": "python",
"repo": "HIPS/Kayak",
"path": "/kayak/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OrnIngvar/guitarparty path: /api.py
from flask_peewee.rest import RestAPI, UserAuthentication
from app import app
from auth import auth
from models import Song
user_auth = UserAuthentication(auth)
<|fim_suffix|># sort by created date desc : /api/song/?genre__eq=Rock&ordering=created
# sort by ... | code_fim | hard | {
"lang": "python",
"repo": "OrnIngvar/guitarparty",
"path": "/api.py",
"mode": "psm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|># filter by artist name : /api/song/?artist=Mugison
# filter by song title : /api/song/?title=Stingum af
# or
# /api/song/?title__eq=Stingum+af
# filter by album name : /api/song/?album=Mugiboogie
# filter by artist starts with : /api/song/?artist__istartswith=Mugi
# filter by artist name contains : /ap... | code_fim | medium | {
"lang": "python",
"repo": "OrnIngvar/guitarparty",
"path": "/api.py",
"mode": "spm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|># filter by album name : /api/song/?album=Mugiboogie
# filter by artist starts with : /api/song/?artist__istartswith=Mugi
# filter by artist name contains : /api/song/?artist__icontains=Mug
# sort by created date desc : /api/song/?genre__eq=Rock&ordering=created
# sort by created date desc : /api/song/?... | code_fim | hard | {
"lang": "python",
"repo": "OrnIngvar/guitarparty",
"path": "/api.py",
"mode": "spm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: simonzabrocki/GraphModels path: /models/Sarah/model_EW.py
__author__ = 'Sarah'
__status__ = 'Pending Validation'
"""
TO DO.
"""
from graphmodels.graphmodel import GraphModel, concatenate_graph_specs
import numpy as np
# Conversions
height_rice = 0.2 # meter height of rice
ha_to_m2 = 1e4 # * 1... | code_fim | hard | {
"lang": "python",
"repo": "simonzabrocki/GraphModels",
"path": "/models/Sarah/model_EW.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>EW2_nodes = {
'IRWR': {'type': 'input',
'name': 'Internal Renewable Water Resources',
'unit': 'm3/year'},
'ERWR': {'type': 'input',
'unit': 'm3/year',
'name': 'External Renewable Water Resources'},
'TRF': {'type': 'variable',
... | code_fim | hard | {
"lang": "python",
"repo": "simonzabrocki/GraphModels",
"path": "/models/Sarah/model_EW.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
EW1_nodes = {'IWU': {'type': 'parameter',
'name': 'Industrial Water Withdrawal',
'unit': 'm3/year'},
'AIR': {'type': 'parameter',
'unit': '1000 ha',
'name': 'Area Actually Irrigated'},
'MWU': {'t... | code_fim | hard | {
"lang": "python",
"repo": "simonzabrocki/GraphModels",
"path": "/models/Sarah/model_EW.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eventbrite/zendesk path: /zendesk/endpoints.py
"""
API MAPPING
"""
mapping_table = {
# Rest API: Organizations
'list_organizations': {
'path': '/organizations.json',
'method': 'GET',
'status': 200,
},
'show_organization': {
'path': '/organizations... | code_fim | hard | {
"lang": "python",
"repo": "eventbrite/zendesk",
"path": "/zendesk/endpoints.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '/users.json',
'valid_params': ('page', ),
'method': 'GET',
'status': 200,
},
'search_users': {
'path': '/users.json',
'valid_params': ('query', 'role', 'page'),
'method': 'GET',
'status': 200,
},
'show_user': {
'path': '/use... | code_fim | hard | {
"lang": "python",
"repo": "eventbrite/zendesk",
"path": "/zendesk/endpoints.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> oids = list()
for name in names:
if name in self.ct2oid:
oids.append(self.ct2oid[name])
elif name.lower() in self.ct2oid:
oids.append(self.ct2oid[name.lower()])
else:
oids.append(self.NO_ENTITY_ID)
... | code_fim | hard | {
"lang": "python",
"repo": "dmis-lab/BERN2",
"path": "/normalizers/celltype_normalizer.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmis-lab/BERN2 path: /normalizers/celltype_normalizer.py
class CellTypeNormalizer(object):
def __init__(self, dict_path):
self.NO_ENTITY_ID = 'CUI-less'
<|fim_suffix|> oids = list()
for name in names:
if name in self.ct2oid:
oids.append(self... | code_fim | hard | {
"lang": "python",
"repo": "dmis-lab/BERN2",
"path": "/normalizers/celltype_normalizer.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_filenames(data_dir: str, filename_regexp: str, show_result=True):
filenames = glob.glob(os.path.join(data_dir, filename_regexp))
if show_result:
hvd_info_rank0('find {} files in {}, such as {}'.format(len(filenames), data_dir, filenames[0:5]))
return filenames
def _idx_a_minu... | code_fim | medium | {
"lang": "python",
"repo": "omrialmog/Model-References",
"path": "/TensorFlow/computer_vision/efficientdet/horovod_estimator/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: omrialmog/Model-References path: /TensorFlow/computer_vision/efficientdet/horovod_estimator/__init__.py
from TensorFlow.common.horovod_helpers import hvd, horovod_enabled
import glob
import os
from multiprocessing import Pool, cpu_count
import numpy as np
import tensorflow.compat.v1 as tf
from... | code_fim | hard | {
"lang": "python",
"repo": "omrialmog/Model-References",
"path": "/TensorFlow/computer_vision/efficientdet/horovod_estimator/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def get_record_num(filenames):
pool = Pool(cpu_count())
c_list = pool.map(_count_per_file, filenames)
total_count = np.sum(np.array(c_list))
return total_count
def get_filenames(data_dir: str, filename_regexp: str, show_result=True):
filenames = glob.glob(os.path.join(data_dir, file... | code_fim | hard | {
"lang": "python",
"repo": "omrialmog/Model-References",
"path": "/TensorFlow/computer_vision/efficientdet/horovod_estimator/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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