text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>class AddSubtractionMatrixError(Exception):
'''
Exception raised for errors when the matrices to be added or subracted
do not have the same dimensions
'''
def __init__(self,
message='The matrices needs to have the same dimension'):
self.message = messa... | code_fim | hard | {
"lang": "python",
"repo": "jairNeto/basic_matrix_algebra",
"path": "/jair_matrices/exceptions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: adamlerer/droidlet path: /droidlet/dialog/craftassist/tests/test_dialogue_manager.py
"""
Copyright (c) Facebook, Inc. and its affiliates.
"""
import os
import unittest
import logging
from droidlet.dialog.dialogue_manager import DialogueManager
from droidlet.memory.dialogue_stack import DialogueS... | code_fim | hard | {
"lang": "python",
"repo": "adamlerer/droidlet",
"path": "/droidlet/dialog/craftassist/tests/test_dialogue_manager.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> action_dict = {
"dialogue_type": "HUMAN_GIVE_COMMAND",
"action_sequence": [
{
"action_type": "DANCE",
"dance_type": {
"look_turn": {
"location": {
... | code_fim | hard | {
"lang": "python",
"repo": "adamlerer/droidlet",
"path": "/droidlet/dialog/craftassist/tests/test_dialogue_manager.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ZeoZagart/TF_QA path: /train_distributed.py
from Model.NQModel import NQModel
from Model.LossFn import LossFn
import torch
import time
import sklearn
import datetime
import Model.datasetutils as datasetutils
import Model.tensorboardutils as boardutils
import torch.utils.tensorboard as tensorboard... | code_fim | hard | {
"lang": "python",
"repo": "ZeoZagart/TF_QA",
"path": "/train_distributed.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> startcm = sklearn.metrics.confusion_matrix(target[1].flatten().detach().numpy(), start01)
endcm = sklearn.metrics.confusion_matrix(target[2].flatten().detach().numpy(), end01)
StartM += torch.from_numpy(startcm)
EndM += torch.from_numpy(endcm)
def log_confusion_matrix(matrix, labels, name, ... | code_fim | hard | {
"lang": "python",
"repo": "ZeoZagart/TF_QA",
"path": "/train_distributed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> start = time.time()
model.train()
steps = -1
for inp_id, inp_type, inp_mask, ans_type, start, end, yes_no in tqdm(traingen) :
steps += 1
output = model(inp_id.squeeze(), inp_mask.squeeze(), inp_type.squeeze())
## Calculate Confusion Matrix
update_confusion_matrix(AnswerTypeMatrix, YesNoMatr... | code_fim | hard | {
"lang": "python",
"repo": "ZeoZagart/TF_QA",
"path": "/train_distributed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: disorn-inc/Project_Structure path: /core_program/yolo_part/yolo-camera/open_pic.py
import numpy as np
import cv2
import time
camera = cv2.imread('/home/disor<|fim_suffix|>ow('j',frame)
print(camera[:,:,0:3])
cv2.waitKey(0)
cv2.destroyAllWindows()<|fim_middle|>n/code_save/Project_Structure/core_p... | code_fim | medium | {
"lang": "python",
"repo": "disorn-inc/Project_Structure",
"path": "/core_program/yolo_part/yolo-camera/open_pic.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>ow('j',frame)
print(camera[:,:,0:3])
cv2.waitKey(0)
cv2.destroyAllWindows()<|fim_prefix|># repo: disorn-inc/Project_Structure path: /core_program/yolo_part/yolo-camera/open_pic.py
import numpy as np
import cv2
import time
camera = cv2.imread('/home/disorn/code_save/Project_Structure/core_program/yolo_pa... | code_fim | medium | {
"lang": "python",
"repo": "disorn-inc/Project_Structure",
"path": "/core_program/yolo_part/yolo-camera/open_pic.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Azure/WALinuxAgent path: /tests/utils/test_crypt_util.py
# Copyright 2018 Microsoft Corporation
#
# 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.apach... | code_fim | hard | {
"lang": "python",
"repo": "Azure/WALinuxAgent",
"path": "/tests/utils/test_crypt_util.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_get_pubkey_from_crt(self):
crypto = CryptUtil(conf.get_openssl_cmd())
prv_key = os.path.join(data_dir, "wire", "trans_prv")
expected_pub_key = os.path.join(data_dir, "wire", "trans_pub")
with open(expected_pub_key) as fh:
self.assertEqual(fh.read()... | code_fim | hard | {
"lang": "python",
"repo": "Azure/WALinuxAgent",
"path": "/tests/utils/test_crypt_util.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hiimim/rrNotifications path: /rrNotifications.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
# encoding: utf-8
# Configuration: Radarr
radarrHost = '192.168.1.5'
radarrPort = '7878'
radarrApiKey = 'xxxxx'
# Configuration: Telegram
telegramToken = 'xxxxx'
telegramChatId = 00000
import os
import ... | code_fim | hard | {
"lang": "python",
"repo": "hiimim/rrNotifications",
"path": "/rrNotifications.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Send notification
if (radarr_eventtype == 'Download') and (radarr_isupgrade == 'False'):
movie = rrSearchMovie(radarr_movie_imdbid, 'imdb')
movie = rrSearchMovie(movie['tmdbId'], 'tmdb')
msg = '<b>' + movie['title'] + '</b> (' + str(movie['year']) + ') downloaded!\n' + excerpt(movie['overview'])... | code_fim | hard | {
"lang": "python",
"repo": "hiimim/rrNotifications",
"path": "/rrNotifications.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pandas-dev/pandas path: /pandas/tests/frame/methods/test_set_index.py
x.map(lambda indx: indx >= 1)]
result = df2.set_index("key")
tm.assert_frame_equal(result, expected)
# MultiIndex constructor does not work directly on Series -> lambda
# Add list-of-list constructor be... | code_fim | hard | {
"lang": "python",
"repo": "pandas-dev/pandas",
"path": "/pandas/tests/frame/methods/test_set_index.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pandas-dev/pandas path: /pandas/tests/frame/methods/test_set_index.py
rays(
df[["A", "B", "A", "B"]].T.values, names=["A", "B", "C", "D"]
)
df = df.set_index(["A", "B"])
assert df.set_index(df.index).index.names == ["A", "B"]
# Check that set_index i... | code_fim | hard | {
"lang": "python",
"repo": "pandas-dev/pandas",
"path": "/pandas/tests/frame/methods/test_set_index.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> values = np.random.default_rng(2).integers(0, 10, (length,))
msg = "Length mismatch: Expected 5 rows, received array of length.*"
# wrong length directly
with pytest.raises(ValueError, match=msg):
df.set_index(box(values), drop=drop, append=append)
# ... | code_fim | hard | {
"lang": "python",
"repo": "pandas-dev/pandas",
"path": "/pandas/tests/frame/methods/test_set_index.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: isabella232/pulumi-kubernetes-crds path: /operators/api-operator/python/pulumi_pulumi_kubernetes_crds_operators_api_operator/_tables.py
# coding=utf-8
# *** WARNING: this file was generated by crd2pulumi. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
SNAKE_... | code_fim | hard | {
"lang": "python",
"repo": "isabella232/pulumi-kubernetes-crds",
"path": "/operators/api-operator/python/pulumi_pulumi_kubernetes_crds_operators_api_operator/_tables.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>": "max_replicas",
"memoryLimit": "memory_limit",
"minReplicas": "min_replicas",
"reqMemory": "req_memory",
"requestCount": "request_count",
"requestCPU": "request_cpu",
"securityConfig": "security_config",
"specificIp": "specific_ip",
"startIp": "start_ip",
"stopOnQuot... | code_fim | hard | {
"lang": "python",
"repo": "isabella232/pulumi-kubernetes-crds",
"path": "/operators/api-operator/python/pulumi_pulumi_kubernetes_crds_operators_api_operator/_tables.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cloudmesh/cloudmesh-robot path: /cloudmesh/pi/command/pi.py
from __future__ import print_function
from cloudmesh.shell.command import command
from cloudmesh.shell.command import PluginCommand
from cloudmesh.common.Shell import Shell, Brew, Pip
from cloudmesh.common.console import Console
from clo... | code_fim | hard | {
"lang": "python",
"repo": "cloudmesh/cloudmesh-robot",
"path": "/cloudmesh/pi/command/pi.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif arguments.reboot:
pass
elif arguments.image and arguments.fetch:
url = "https://downloads.raspberrypi.org/NOOBS_latest"
if os.path.isfile("NOOBS_latest"):
print("... image already downloaded")
else:
os... | code_fim | hard | {
"lang": "python",
"repo": "cloudmesh/cloudmesh-robot",
"path": "/cloudmesh/pi/command/pi.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> arguments.dryrun = arguments["--dryrun"]
def _run(command):
print(command)
if arguments.dryrun:
print(command)
else:
os.system(command)
def _continue(msg):
if not arguments.dryrun:
c =... | code_fim | hard | {
"lang": "python",
"repo": "cloudmesh/cloudmesh-robot",
"path": "/cloudmesh/pi/command/pi.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: a-martynovich/api path: /backend/device_registry/migrations/0025_auto_20190512_1934.py
# Generated by Django 2.1.7 on 2019-05-12 19:34
from django.db import migrations, models
from django.contrib.postgres.fields import JSONField
<|fim_suffix|> dependencies = [
('device_registry', '0... | code_fim | medium | {
"lang": "python",
"repo": "a-martynovich/api",
"path": "/backend/device_registry/migrations/0025_auto_20190512_1934.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('device_registry', '0024_fix_scan_info_content'),
]
operations = [
migrations.AddField(
model_name='deviceinfo',
name='app_armor_enabled',
field=models.BooleanField(blank=True, null=True),
),
migrations.AddF... | code_fim | medium | {
"lang": "python",
"repo": "a-martynovich/api",
"path": "/backend/device_registry/migrations/0025_auto_20190512_1934.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='deviceinfo',
name='app_armor_enabled',
field=models.BooleanField(blank=True, null=True),
),
migrations.AddField(
model_name='deviceinfo',
name='selinux_state',
... | code_fim | medium | {
"lang": "python",
"repo": "a-martynovich/api",
"path": "/backend/device_registry/migrations/0025_auto_20190512_1934.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if n == 0:
return 1
else:
partial = power(x, n // 2)
result = partial * partial # eqaul to x^n for even
if n % 2 == 1: #odd
# multiply prefix by x to get x^n
result *= x
return result
if __name__ == "__main__":... | code_fim | easy | {
"lang": "python",
"repo": "gauravssnl/Data-Structures-and-Algorithms",
"path": "/python/Data Structures and Algorithms in Python Book/recursion/power_better.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gauravssnl/Data-Structures-and-Algorithms path: /python/Data Structures and Algorithms in Python Book/recursion/power_better.py
# complexity : O(log n ) as in Binary search
# the number of times that we can divide n in half before getting to one or less is O(logn).
<|fim_suffix|>if __name__ == "... | code_fim | hard | {
"lang": "python",
"repo": "gauravssnl/Data-Structures-and-Algorithms",
"path": "/python/Data Structures and Algorithms in Python Book/recursion/power_better.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.value = value
def __str__(self):
return str(self.value)<|fim_prefix|># repo: rca32/cesium path: /cesium/custom_exceptions.py
class DataFormatError(Exception):
<|fim_middle|> """TS data file or header file does not improperly formatted.
Attributes
----------
valu... | code_fim | medium | {
"lang": "python",
"repo": "rca32/cesium",
"path": "/cesium/custom_exceptions.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rca32/cesium path: /cesium/custom_exceptions.py
class DataFormatError(Exception):
"""TS data file or header file does not improperly formatted.
<|fim_suffix|> """
def __init__(self, value):
self.value = value
def __str__(self):
return str(self.value)<|fim_middle... | code_fim | medium | {
"lang": "python",
"repo": "rca32/cesium",
"path": "/cesium/custom_exceptions.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zhaochl/python-utils path: /utils/pinyin_util.py
#!/usr/bin/env python
# coding=utf-8
#pip install pypinyin
from pypinyin import pinyin, lazy_pinyin
import pypinyin
if __name__=="__main__":
t=pinyin(u'中心')
#[[u'zh\u014dng'], [u'x\u012bn']]
print t
for pinyin_list in t :
... | code_fim | medium | {
"lang": "python",
"repo": "zhaochl/python-utils",
"path": "/utils/pinyin_util.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> t=lazy_pinyin(u'中心') # 不考虑多音字的情况
#['zhong', 'xin']
print t<|fim_prefix|># repo: zhaochl/python-utils path: /utils/pinyin_util.py
#!/usr/bin/env python
# coding=utf-8
#pip install pypinyin
from pypinyin import pinyin, lazy_pinyin
import pypinyin
if __name__=="__main__":
t=pinyin(u'中心')
... | code_fim | medium | {
"lang": "python",
"repo": "zhaochl/python-utils",
"path": "/utils/pinyin_util.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: exercism/python path: /exercises/practice/circular-buffer/.meta/example.py
class BufferFullException(BufferError):
"""Exception raised when CircularBuffer is full.
message: explanation of the error.
"""
def __init__(self, message):
self.message = message
<|fim_suffix|> ... | code_fim | hard | {
"lang": "python",
"repo": "exercism/python",
"path": "/exercises/practice/circular-buffer/.meta/example.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class CircularBuffer:
def __init__(self, capacity):
self.buffer = bytearray(capacity)
self.read_point = 0
self.write_point = 0
# (protected) helper method
def _update_buffer(self, data):
try:
self.buffer[self.write_point] = data
except Typ... | code_fim | medium | {
"lang": "python",
"repo": "exercism/python",
"path": "/exercises/practice/circular-buffer/.meta/example.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yuhangwang/craftr path: /craftr/logging.py
# Copyright (C) 2015 Niklas Rosenstein
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including witho... | code_fim | hard | {
"lang": "python",
"repo": "yuhangwang/craftr",
"path": "/craftr/logging.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Logger(object):
''' Simple logger class. '''
def __init__(self, prefix=None, level=0):
super().__init__()
self.prefix = prefix or ''
self.level = level
def emit(self, level, *args, **kwargs):
frame = kwargs.pop('frame', None)
if level >= self.level:
message = print... | code_fim | hard | {
"lang": "python",
"repo": "yuhangwang/craftr",
"path": "/craftr/logging.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SegmentationBLWX/sssegmentation path: /ssseg/modules/models/segmentors/memorynetv2/memorynetv2.py
'''
Function:
Implementation of MemoryNetV2 - "MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic Segmentation"
Author:
Zhenchao Jin
'''
import copy
import torch
import tor... | code_fim | hard | {
"lang": "python",
"repo": "SegmentationBLWX/sssegmentation",
"path": "/ssseg/modules/models/segmentors/memorynetv2/memorynetv2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>_cwi_before_fpn', True):
lateral_outputs.append(torch.cat([memory_output, feats_cwi], dim=1))
else:
lateral_outputs.append(feats_cwi)
for i in range(len(lateral_outputs) - 1, 0, -1):
prev_shape = lateral_outputs[i ... | code_fim | hard | {
"lang": "python",
"repo": "SegmentationBLWX/sssegmentation",
"path": "/ssseg/modules/models/segmentors/memorynetv2/memorynetv2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_deep(player):
log(player.deep.enter(0))
#print player.deep.auto()
#sleep(100)
#log(player.deep.fight(1))
#log(player.deep.enter(1))
#log(player.deep.box())
#log(player.deep.enter(0))
from corelib import sleep
sleep(200)<|fim_prefix|># repo: hw233/twist... | code_fim | easy | {
"lang": "python",
"repo": "hw233/twisted_zdzl",
"path": "/server/code/client/scripts/deep.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hw233/twisted_zdzl path: /server/code/client/scripts/deep.py
#!/usr/bin/env python
# -*- coding:utf-8 -*-
DEBUG = 1
def log(msg):
if DEBUG:
print(msg)
<|fim_suffix|> log(player.deep.enter(0))
#print player.deep.auto()
#sleep(100)
#log(player.deep.fight(1))
... | code_fim | easy | {
"lang": "python",
"repo": "hw233/twisted_zdzl",
"path": "/server/code/client/scripts/deep.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> log(player.deep.enter(0))
#print player.deep.auto()
#sleep(100)
#log(player.deep.fight(1))
#log(player.deep.enter(1))
#log(player.deep.box())
#log(player.deep.enter(0))
from corelib import sleep
sleep(200)<|fim_prefix|># repo: hw233/twisted_zdzl path: /server/c... | code_fim | medium | {
"lang": "python",
"repo": "hw233/twisted_zdzl",
"path": "/server/code/client/scripts/deep.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ardyflora/telegram-ipl-cricket-score-bot path: /database.py
import sqlite3
def create_iplPoints(c):
c.execute('''CREATE TABLE iplPoints
(Rank integer, Teams text, MAT integer, WON integer, Lost integer, TIED integer, NR integer , PTS integer, NETRR text, FOR text, AGAINST text... | code_fim | medium | {
"lang": "python",
"repo": "ardyflora/telegram-ipl-cricket-score-bot",
"path": "/database.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def init_database():
conn = sqlite3.connect('iplPoints.db')
c = conn.cursor()
create_iplPoints(c)
create_fixtures(c)
conn.commit()
conn.close()
if __name__ == '__main__':
init_database()<|fim_prefix|># repo: ardyflora/telegram-ipl-cricket-score-bot path: /database.py
import... | code_fim | hard | {
"lang": "python",
"repo": "ardyflora/telegram-ipl-cricket-score-bot",
"path": "/database.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: webis-de/authorship-threetrain path: /tira-prepare-documents.py
#!/usr/bin/env python3
#Usage: tira-prepare-documents `inputDataset` `run` `outdir` `which`
#prepares the documents for the databases. First three arguments are from the PAN interface, last must be "training", "unknown" or "both".<|... | code_fim | hard | {
"lang": "python",
"repo": "webis-de/authorship-threetrain",
"path": "/tira-prepare-documents.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ra.stanford_db,tira.tokens_db,tira.pos_db,tira.c_syntax_tree_db,training_dataset)
if which == 'both' or which == 'unknown':
prepare_documents.prepareDocumentsChunked(tira.stanford_db,tira.tokens_db,tira.pos_db,tira.c_syntax_tree_db,unknown_dataset)
if __name__ == '__main__':
import sys
interf=tira.ti... | code_fim | hard | {
"lang": "python",
"repo": "webis-de/authorship-threetrain",
"path": "/tira-prepare-documents.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: disillusionment/emulator101-disassembler path: /disassembler.py
import binascii
import sys
from helpers import get_registers, opcodes8080
#File Reading
source_file = str(sys.argv[1])
output_file_name = source_file.split('.')[0] + "_disassembled.txt"
with open(source_file, 'rb') as f:
source... | code_fim | hard | {
"lang": "python",
"repo": "disillusionment/emulator101-disassembler",
"path": "/disassembler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if data_address_bytes > 0:
data_address_bytes -= 1
opcode += 1
continue
position = (x * 2)
byte = hex_dump[position] + hex_dump[position + 1]
opcode_tuple = opcodes8080[byte]
instruction = opcode_tuple[0]
if not instruction:
opcode += 1
... | code_fim | medium | {
"lang": "python",
"repo": "disillusionment/emulator101-disassembler",
"path": "/disassembler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># definations
def dot_prod(t1: torch.Tensor, t2: torch.Tensor, verbose: bool = False):
"""simple function with fully built doc string and wrapper for Cpp-object
:param t1: tensor 1
:param t2: tensor 2
:param verbose: bool whether to allow C++ code to print
"""
assert t1.size() == t... | code_fim | hard | {
"lang": "python",
"repo": "yashbonde/mask_attention_transformer",
"path": "/mask_attention/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yashbonde/mask_attention_transformer path: /mask_attention/__init__.py
"""
MIT License
Copyright (c) 2020 Yash Bonde
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without... | code_fim | hard | {
"lang": "python",
"repo": "yashbonde/mask_attention_transformer",
"path": "/mask_attention/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> out = conv(x1, edge_index)
assert out.tolist() == [0, 1, 1, 0]
assert torch.equal(conv(x2, edge_index), out)
assert torch.equal(conv(x1, adj1.t()), out)
assert torch.equal(conv(x1, adj2.t()), out)
assert torch.equal(conv(x2, adj1.t()), out)
assert torch.equal(conv(x2, adj2.t())... | code_fim | hard | {
"lang": "python",
"repo": "suntaochun/pytorch_geometric",
"path": "/test/nn/conv/test_wl_conv.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: suntaochun/pytorch_geometric path: /test/nn/conv/test_wl_conv.py
import torch
import torch.nn.functional as F
from torch_sparse import SparseTensor
from torch_geometric.nn import WLConv
<|fim_suffix|> x1 = torch.tensor([1, 0, 0, 1])
x2 = F.one_hot(x1).to(torch.float)
edge_index = to... | code_fim | medium | {
"lang": "python",
"repo": "suntaochun/pytorch_geometric",
"path": "/test/nn/conv/test_wl_conv.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertNoDiff(util.diff(util.run_mock('control/if_3.sieve'), 'control/if_3.out'))
if __name__ == '__main__':
unittest.main()<|fim_prefix|># repo: dburkart/check-sieve path: /test/AST/control_test.py
import unittest
import checksieve
from . import util
class TestControlAST(util.DiffTest... | code_fim | hard | {
"lang": "python",
"repo": "dburkart/check-sieve",
"path": "/test/AST/control_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dburkart/check-sieve path: /test/AST/control_test.py
import unittest
import checksieve
from . import util
class TestControlAST(util.DiffTestCase):
def test_simple_if(self):
self.assertNoDiff(util.diff(util.run_mock('control/if_1.sieve'), 'control/if_1.out'))
<|fim_suffix|> ... | code_fim | medium | {
"lang": "python",
"repo": "dburkart/check-sieve",
"path": "/test/AST/control_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_if_else(self):
self.assertNoDiff(util.diff(util.run_mock('control/if_2.sieve'), 'control/if_2.out'))
def test_if_elsif_else(self):
self.assertNoDiff(util.diff(util.run_mock('control/if_3.sieve'), 'control/if_3.out'))
if __name__ == '__main__':
unittest.main()<|f... | code_fim | medium | {
"lang": "python",
"repo": "dburkart/check-sieve",
"path": "/test/AST/control_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """takes method and wraps it in a timer"""
log = LogMixin()
def timed(*args, **kw):
ts = time.time()
result = method(*args, **kw)
te = time.time()
log.logger.info(f'''{method.__qualname__} took
{round(te - ts, 3)}s seconds''')
return result
... | code_fim | hard | {
"lang": "python",
"repo": "pplonski/scitime",
"path": "/scitime/_log.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pplonski/scitime path: /scitime/_log.py
import time
import logging
import warnings
warnings.simplefilter("ignore")
class LogMixin(object):
@property
def logger(self):
<|fim_suffix|> """takes method and wraps it in a timer"""
log = LogMixin()
def timed(*args, **kw):
... | code_fim | hard | {
"lang": "python",
"repo": "pplonski/scitime",
"path": "/scitime/_log.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>cePulseFlagMC=cms.bool(False),
usePulseFlag = cms.bool(True),
correctionType = cms.int32(1)
)<|fim_prefix|># repo: cms-sw/cmssw path: /RecoEgamma/EgammaHFProducers/python/hfClusterShapes_cfi.py
import FWCore.Paramet... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/RecoEgamma/EgammaHFProducers/python/hfClusterShapes_cfi.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cms-sw/cmssw path: /RecoEgamma/EgammaHFProducers/python/hfClusterShapes_cfi.py
import FWCore.ParameterSet.Config as cms
# HFEMClusterShape producer
hfEMClusters = cms.EDProducer("HFEMClusterProducer",
hits = cms.InputTag("hfreco")<|fim_suffix|>cePulseFlagMC=cms.bool... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/RecoEgamma/EgammaHFProducers/python/hfClusterShapes_cfi.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lanxinplus/lanxinplus-openapi-python-sdk path: /lanxinplus_openapi/api/org_api.py
"""
LanXin+ OpenAPI
LanXin+ OpenAPI Platform # noqa: E501
Generated by: https://openapi.lanxin.cn
"""
import re # noqa: F401
import sys # noqa: F401
from lanxinplus_openapi.api_client import ApiC... | code_fim | hard | {
"lang": "python",
"repo": "lanxinplus/lanxinplus-openapi-python-sdk",
"path": "/lanxinplus_openapi/api/org_api.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
V1OrgFetchResponse
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
... | code_fim | hard | {
"lang": "python",
"repo": "lanxinplus/lanxinplus-openapi-python-sdk",
"path": "/lanxinplus_openapi/api/org_api.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Args:
app_token (str): app_token
orgid (str): orgid
Keyword Args:
user_token (str): user_token. [optional]
Returns:
V1OrgFetchResponse
If the method is called asynchronously, returns the request
threa... | code_fim | hard | {
"lang": "python",
"repo": "lanxinplus/lanxinplus-openapi-python-sdk",
"path": "/lanxinplus_openapi/api/org_api.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> get_ipython().kernel.comm_manager.register_target(self.target_name + '/' + str(channel), handle_open)
def run(self):
# TODO wait until JS ready
while not self.opened:
time.sleep(self.sleep)
while self.opened:
messages = queue_get_all(self.q)
... | code_fim | hard | {
"lang": "python",
"repo": "silky/tributary",
"path": "/tributary/_depr/hosts/comm.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.comm.send(data=messages_to_json(messages))
time.sleep(self.sleep)
def runComm(q, channel, sleep=1):
# print('adding handler %s%s' % ('lantern.live/', channel))
comm = CommHandler(q, channel, sleep)
comm.run()<|fim_prefix|># repo: silky/tributary path: /tribu... | code_fim | hard | {
"lang": "python",
"repo": "silky/tributary",
"path": "/tributary/_depr/hosts/comm.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: silky/tributary path: /tributary/_depr/hosts/comm.py
import time
from IPython import get_ipython
from ..utils import queue_get_all, messages_to_json
class CommHandler(object):
def __init__(self, q, channel, sleep=1, replay=True, replay_count=1000):
self.closed = False
self.q... | code_fim | hard | {
"lang": "python",
"repo": "silky/tributary",
"path": "/tributary/_depr/hosts/comm.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bernardobranco/ucl-search-engine path: /engine/tasks.py
import time
import requests
from celery import shared_task
#from pymongo import MongoClient
from django.conf import settings
from engine.models import WebPage
from engine.crawler import get_page
from engine.forms import WebPageForm
import... | code_fim | hard | {
"lang": "python",
"repo": "bernardobranco/ucl-search-engine",
"path": "/engine/tasks.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># i = 0
# print('SAVING STEP 1')
# out_pages_ids = list()
# for out_link in resp['out_links']:
# print(i)
# # Create new page if outlink does not exist
# # Adds to crawler after save
# #try:
# ... | code_fim | hard | {
"lang": "python",
"repo": "bernardobranco/ucl-search-engine",
"path": "/engine/tasks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># out_pages_ids.append(out_page.id)
# # add out links as in link to current page
# #out_page.in_links.add(page)
# i +=1
# print('SAVING OUTLINKS')
# page.out_links.add(*out_pages_ids)
# print('SAVING STEP ... | code_fim | hard | {
"lang": "python",
"repo": "bernardobranco/ucl-search-engine",
"path": "/engine/tasks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> 4. After the parameter processing from steps 1-3 the request is made using
the calling function returned by the module attribute ``retrieve_caller_fn``
and the reponse formatters are applied to the output.
"""
def __init__(
self,
json_rpc_method=None,
... | code_fim | hard | {
"lang": "python",
"repo": "sanchaymittal/FarmEasy",
"path": "/WhatsApp_FarmEasy/env/lib/python3.6/site-packages/web3/method.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sanchaymittal/FarmEasy path: /WhatsApp_FarmEasy/env/lib/python3.6/site-packages/web3/method.py
import functools
import warnings
from eth_utils import (
to_tuple,
)
from eth_utils.toolz import (
identity,
pipe,
)
def _munger_star_apply(fn):
@functools.wraps(fn)
def inner(arg... | code_fim | hard | {
"lang": "python",
"repo": "sanchaymittal/FarmEasy",
"path": "/WhatsApp_FarmEasy/env/lib/python3.6/site-packages/web3/method.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if block_identifier is None:
block_identifier = DEFAULT_BLOCK
return module, [account, block_identifier]
```
all mungers should return an argument list.
if no munger is provided, a default munger expecting no method arguments
will b... | code_fim | hard | {
"lang": "python",
"repo": "sanchaymittal/FarmEasy",
"path": "/WhatsApp_FarmEasy/env/lib/python3.6/site-packages/web3/method.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sourcepirate/capsule path: /capsule/download.py
import os
import six
import shutil
import wget
import traceback
import zipfile
def trim_repo_url(url):
"""Replace the .git in url"""
return url.replace(".git", "")
def get_archive_url(url, branch='master', release=None):
"""
get ... | code_fim | hard | {
"lang": "python",
"repo": "sourcepirate/capsule",
"path": "/capsule/download.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def rupture(url, outpath=None, branch='master', dirname=None, release=None):
"""
Downloads the archive, unzips it and deletes the archive
file
Args:
url: url to be downloaded
outpath: path of the output folder
dirname: name of the directory
branc... | code_fim | hard | {
"lang": "python",
"repo": "sourcepirate/capsule",
"path": "/capsule/download.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>+= 95*95
c = 95
d = 95
a += 1
d -= 1
while d != 0
c -= 1
while c != 0<|fim_prefix|># repo: tbjoern/adventofcode path: /Twentythree/reverse.py
# a = 7 or a = 12
b = a
b -= 1
d = a
a = 0
# a += b*d
c = b
a += 1
c -= 1
while c != 0
d -= 1
while d !=0
b -= 1
c = ... | code_fim | medium | {
"lang": "python",
"repo": "tbjoern/adventofcode",
"path": "/Twentythree/reverse.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tbjoern/adventofcode path: /Twentythree/reverse.py
# a = 7 or a = 12
b = a
b -= 1
d = a
a = 0
# a += b*d
c = b
a += 1<|fim_suffix|>+= 95*95
c = 95
d = 95
a += 1
d -= 1
while d != 0
c -= 1
while c != 0<|fim_middle|>
c -= 1
while c != 0
d -= 1
while d !=0
... | code_fim | medium | {
"lang": "python",
"repo": "tbjoern/adventofcode",
"path": "/Twentythree/reverse.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_Size2i():
cmp(size.return_Size2i(), (203, 17))
size.receive_Size2i(size.Size2i(250, 128))
def test_Size2d():
cmp(size.return_Size2d(), (0.039, 0.377))
size.receive_Size2d(size.Size2d(0.637, 0.256))
def test_Size2f():
cmp(size.return_Size2f(), (0.460, 0.339))
size.rece... | code_fim | medium | {
"lang": "python",
"repo": "renatoGarcia/opencv-swig",
"path": "/test/test_size.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_Vec_constructor():
cmp(size.Size2i(size.Point2i(23, 58)), (23, 58))<|fim_prefix|># repo: renatoGarcia/opencv-swig path: /test/test_size.py
#! /usr/bin/python3
import sys
sys.path.insert(0, ".")
import size
def cmp(r, t):
epsilon = 0.0001
for p in zip(r, t):
assert(abs(p[... | code_fim | hard | {
"lang": "python",
"repo": "renatoGarcia/opencv-swig",
"path": "/test/test_size.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: renatoGarcia/opencv-swig path: /test/test_size.py
#! /usr/bin/python3
import sys
sys.path.insert(0, ".")
import size
def cmp(r, t):
epsilon = 0.0001
for p in zip(r, t):
assert(abs(p[0] - p[1]) < epsilon)
def test_Size():
cmp(size.return_Size(), (14, 55))
size.receive... | code_fim | hard | {
"lang": "python",
"repo": "renatoGarcia/opencv-swig",
"path": "/test/test_size.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: austincmatteson/pyramid-stocks path: /pyramid_scaffold/tests/test_model_stock.py
def test_constructed_stock_added_to_database(db_session):
from ..models import Stock
assert len(db_session.query(Stock).all()) == 0
stock = Stock(
symbol="AM",
companyName="ayymang",
... | code_fim | medium | {
"lang": "python",
"repo": "austincmatteson/pyramid-stocks",
"path": "/pyramid_scaffold/tests/test_model_stock.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert len(db_session.query(Stock).all()) == 0
stock = Stock(
companyName="ayymang",
exchange="NYC",
industry="dusty",
website="google.com",
description="test",
CEO="me",
issueType="huh",
sector="tc"
)
with pytest.raises(Integ... | code_fim | hard | {
"lang": "python",
"repo": "austincmatteson/pyramid-stocks",
"path": "/pyramid_scaffold/tests/test_model_stock.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: castelao/CoTeDe path: /cotede/utils/utils.py
# -*- coding: utf-8 -*-
"""Utilities for CoTeDe
Miscelaneous resources to support CoTeDe.
"""
from datetime import date, datetime
import json
import logging
import numpy as np
import os
from os.path import expanduser
import re
import pkg_resources
... | code_fim | hard | {
"lang": "python",
"repo": "castelao/CoTeDe",
"path": "/cotede/utils/utils.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # tar = tarfile.open("%s.tar.bz2" % filename, "w:bz2")
tar = tarfile.open(filename, "w:bz2")
tmpdir = tempfile.mkdtemp()
try:
# Data
f = "%s/data.hdf" % (tmpdir)
db.data.to_hdf(f, "df")
tar.add(f, arcname="data.hdf")
# hashlib.md5(open(f, 'rb').read... | code_fim | hard | {
"lang": "python",
"repo": "castelao/CoTeDe",
"path": "/cotede/utils/utils.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> db = shelve.open(self.filename)
db[key] = obj
db.close()
def restore(self, key):
db = shelve.open(self.filename)
if db.has_key(key):
obj = db[key]
logger.info("Successful load data by key '%s' info from file %s" % (key, self.filename))
... | code_fim | medium | {
"lang": "python",
"repo": "spitty/strelka_telegram_bot",
"path": "/storer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: spitty/strelka_telegram_bot path: /storer.py
#!/usr/bin/python
import logging
import shelve
logger = logging.getLogger(__name__)
<|fim_suffix|> db = shelve.open(self.filename)
db[key] = obj
db.close()
def restore(self, key):
db = shelve.open(self.filename)
... | code_fim | medium | {
"lang": "python",
"repo": "spitty/strelka_telegram_bot",
"path": "/storer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: manikandtan-ck/RecurrentGaze path: /images_data_augmenter_seqaware.py
e data augmenter class and related methods
# author :Cristina Palmero
# date :30092018
# version :2.0
# usage : -
# notes : -
# python_version :3.5.5
# ==========================... | code_fim | hard | {
"lang": "python",
"repo": "manikandtan-ck/RecurrentGaze",
"path": "/images_data_augmenter_seqaware.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
ImageDataAugmenter class.
Prepared to apply the same augmentation to a list of images/data.
Sequence-aware: the current augmentation state can be returned to the calling class, so that all frames of a
sequence are augmented in the same way.
"""
def __init__(self,
... | code_fim | hard | {
"lang": "python",
"repo": "manikandtan-ck/RecurrentGaze",
"path": "/images_data_augmenter_seqaware.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if transform_matrix is not None:
face_img = apply_transform_matrix(self, face_img, transform_matrix)
nface_img = apply_transform_matrix(self, nface_img, transform_matrix)
leye_img = apply_transform_matrix(self, leye_img, transform_matrix)
reye_img = ... | code_fim | hard | {
"lang": "python",
"repo": "manikandtan-ck/RecurrentGaze",
"path": "/images_data_augmenter_seqaware.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for ch in kanji_numbers:
print ctype % (ch, 'M')
for ch in hiragana:
print ctype % (ch, 'I')
for ch in katakana:
print ctype % (ch, 'K')
for ch in alphabets:
print ctype % (ch, 'A')
for ch in numbers:
print ctype % (ch, 'N')<|fim_prefix|># repo: ktty1220/TinySegmenterMaker path: /... | code_fim | medium | {
"lang": "python",
"repo": "ktty1220/TinySegmenterMaker",
"path": "/templates/tex-ctypes.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ktty1220/TinySegmenterMaker path: /templates/tex-ctypes.py
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import sys
import codecs
sys.stdin = codecs.getreader('utf-8')(sys.stdin)
sys.stdout = codecs.getwriter('utf-8')(sys.stdout)
kanji_numbers = u"一二三四五六七八九十百千万億兆"
hiragana = u"あいうえおかきくけこがぎぐげご... | code_fim | medium | {
"lang": "python",
"repo": "ktty1220/TinySegmenterMaker",
"path": "/templates/tex-ctypes.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> tmpdir,
top_level_deps,
spec_deps):
top_level_file = tmpdir.join('elm-native-package.json')
spec_file = tmpdir.join('spec-elm-native-package.json')
top_level = OrderedDict(top_level_deps)
top_level_file.write(json.dumps(top_level))
spec = OrderedDict(spec_deps... | code_fim | medium | {
"lang": "python",
"repo": "NoRedInk/elm-ops-tooling",
"path": "/tests/test_native_deps_sync.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>@given(top_level_deps=st.permutations(top_level_deps),
spec_deps=st.permutations(spec_deps))
def test_spec_order_is_preserved(
tmpdir,
top_level_deps,
spec_deps):
top_level_file = tmpdir.join('elm-native-package.json')
spec_file = tmpdir.join('spec-elm-native-package... | code_fim | hard | {
"lang": "python",
"repo": "NoRedInk/elm-ops-tooling",
"path": "/tests/test_native_deps_sync.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NoRedInk/elm-ops-tooling path: /tests/test_native_deps_sync.py
from collections import OrderedDict
import json
from hypothesis import given
import hypothesis.strategies as st
import native_deps_sync
top_level_deps = [
('NoRedInk/top-1', '1.0.0 <= v <= 1.0.0'),
('NoRedInk/top-2', '1.0.... | code_fim | medium | {
"lang": "python",
"repo": "NoRedInk/elm-ops-tooling",
"path": "/tests/test_native_deps_sync.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>name = "Тициано Вечеллио"
print("Герой нашей сегоднящней программы - " + name)
name2 = input("Под каким же именем мы знаем этого человека? Ваш ответ: ")
print("Все верно: " + name + " - " + name2)
input("Нажмите Enter для выхода")<|fim_prefix|># repo: stasvorosh/pythonintask path: /INBa/2014/Mamedov_R_A/... | code_fim | easy | {
"lang": "python",
"repo": "stasvorosh/pythonintask",
"path": "/INBa/2014/Mamedov_R_A/Mamedov 3_12.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stasvorosh/pythonintask path: /INBa/2014/Mamedov_R_A/Mamedov 3_12.py
# Задача 3, Вариант 12
# Напишите программу, которая выводит имя "Тициано Вечеллио", и запрашивает его псевдоним. Программа должна сцеплять две эти строки и выводить полученную строку, разделяя имя и псевдоним с помощью тире.
... | code_fim | easy | {
"lang": "python",
"repo": "stasvorosh/pythonintask",
"path": "/INBa/2014/Mamedov_R_A/Mamedov 3_12.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
An audio processing pipeline that computes a frequency domain representation
of the sound that follows a geometric scale
"""
bark = zounds.ArrayWithUnitsFeature(
zounds.BarkBands,
samplerate=samplerate,
stop_freq_hz=samplerate.nyquist,
needs=BaseMode... | code_fim | hard | {
"lang": "python",
"repo": "JohnVinyard/zounds",
"path": "/examples/pytorch_autoencoder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # get references to all the sounds. features are lazily
# loaded/evaluated, so this is a cheap operation
snds = list(Sound)
# create a synthesizer that can invert the frequency adaptive representation
synth = zounds.FrequencyAdaptiveFFTSynthesizer(scale, samplerate)
def random_... | code_fim | hard | {
"lang": "python",
"repo": "JohnVinyard/zounds",
"path": "/examples/pytorch_autoencoder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JohnVinyard/zounds path: /examples/pytorch_autoencoder.py
import featureflow as ff
import zounds
import numpy as np
from torch import nn, optim
from random import choice
import argparse
class Layer(nn.Module):
"""
A single layer of our simple autoencoder
"""
def __init__(self, ... | code_fim | hard | {
"lang": "python",
"repo": "JohnVinyard/zounds",
"path": "/examples/pytorch_autoencoder.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sdgdsffdsfff/qchat_supplier_robot path: /utils/send_message_util.py
#!/usr/bin/env python
# -*- encoding: utf8 -*-
import sys
sys.path.append("././")
import json
import requests
import uuid
from db.get_database_data import SupplierQaHistory
from xml.sax.saxutils import escape
from get_config imp... | code_fim | hard | {
"lang": "python",
"repo": "sdgdsffdsfff/qchat_supplier_robot",
"path": "/utils/send_message_util.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif is_worked == '0':
answer = "感谢你的反馈,我会好好学习的~"
message = "<message from='{m_from}' to='{m_to}' type='{mtype}' realfrom='{real_from}' " \
"realto='{real_to}' channelid='{channelid}' qchatid='5'>" \
"<body id='{uuid}' msgType='{msg_type}' ex... | code_fim | hard | {
"lang": "python",
"repo": "sdgdsffdsfff/qchat_supplier_robot",
"path": "/utils/send_message_util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with open(file_path, "rb") as f:
f_data = f.read()
print(charset_normalizer.detect(f_data))
# print(chardet.detect(f_data))
# returns 'ascii' even if the file is saved in UTF8 format if it does not contain any unicode characters.<|fim_prefix|># repo: jgstew/tools path: /Python/file_get_encod... | code_fim | easy | {
"lang": "python",
"repo": "jgstew/tools",
"path": "/Python/file_get_encoding.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jgstew/tools path: /Python/file_get_encoding.py
# pip install chardet
# import chardet
<|fim_suffix|>file_path = "Python/file_get_encoding.py"
with open(file_path, "rb") as f:
f_data = f.read()
print(charset_normalizer.detect(f_data))
# print(chardet.detect(f_data))
# returns 'asci... | code_fim | medium | {
"lang": "python",
"repo": "jgstew/tools",
"path": "/Python/file_get_encoding.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gruen/redash path: /redash/worker.py
from celery import Celery
from datetime import timedelta
from redash import settings
<|fim_suffix|>celery.conf.update(CELERY_RESULT_BACKEND=settings.CELERY_BACKEND,
CELERYBEAT_SCHEDULE={
'refresh_queries': {
... | code_fim | hard | {
"lang": "python",
"repo": "gruen/redash",
"path": "/redash/worker.py",
"mode": "psm",
"license": "BSD-2-Clause-Views",
"source": "the-stack-v2"
} |
<|fim_suffix|>celery.conf.update(CELERY_RESULT_BACKEND=settings.CELERY_BACKEND,
CELERYBEAT_SCHEDULE={
'refresh_queries': {
'task': 'redash.tasks.refresh_queries',
'schedule': timedelta(seconds=30)
},
... | code_fim | hard | {
"lang": "python",
"repo": "gruen/redash",
"path": "/redash/worker.py",
"mode": "spm",
"license": "BSD-2-Clause-Views",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xmanatee/mipt.digger.project path: /nmakeenkov_dev.py
import cv2
import rectangle_builder
cap = cv2.VideoCapture(u'data/CH0P0389.MPG')
r_b = rectangle_builder.RectangleBuilder()
while(cap.isOpened()):
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny... | code_fim | hard | {
"lang": "python",
"repo": "xmanatee/mipt.digger.project",
"path": "/nmakeenkov_dev.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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