text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: gluo7777/MyTools path: /cli/scripts/client.py
from cli.scripts.config import Properties
import requests
class Client:
TIMEOUT = 'timeout'
DEFAULT_TIMEOUT = 10
def __init__(self, props: Properties):
super().__init__()
self.props = props
self.base = 'http://l... | code_fim | hard | {
"lang": "python",
"repo": "gluo7777/MyTools",
"path": "/cli/scripts/client.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PMEAL/porespy path: /porespy/filters/__init__.py
r"""
Collection of functions for altering images based on structural properties
##########################################################################
This module contains a variety of functions for altering images based on
the structural cha... | code_fim | medium | {
"lang": "python",
"repo": "PMEAL/porespy",
"path": "/porespy/filters/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>.. autosummary::
:template: mybase.rst
:toctree: generated/
filters.apply_chords
filters.apply_chords_3D
filters.apply_padded
filters.chunked_func
filters.distance_transform_lin
filters.fftmorphology
filters.fill_blind_pores
filters.find_disconnected_voxels
filte... | code_fim | medium | {
"lang": "python",
"repo": "PMEAL/porespy",
"path": "/porespy/filters/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>eukaryotes = eukaryotes.iloc[1:201,:]
mammals = mammals.iloc[1:201,:]
pp = pd.merge(mammals, eukaryotes, on=["gene", "protein2"], how="outer")
pp.fillna(0, inplace=True)
pp["PP"] = pp.apply(lambda x: max(x["PP_eukaryotes"], x["PP_mammals"]), axis=1)
mecp2_links = pd.merge(mecp2_links, pp[["gene", "protein... | code_fim | hard | {
"lang": "python",
"repo": "GuIrene/MECP2_phylogeny",
"path": "/string_overlap_analysis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GuIrene/MECP2_phylogeny path: /string_overlap_analysis.py
import gzip
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import upsetplot
#%%
data_dir = "/Users/ireneu/berman_lab/Rett/revisions/string_data/"
#load data
with gzip.open(data_dir+"9606.prote... | code_fim | hard | {
"lang": "python",
"repo": "GuIrene/MECP2_phylogeny",
"path": "/string_overlap_analysis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#%%
eukaryotes.columns = ["gene", "PP_eukaryotes", "protein2"]
mammals.columns = ["gene", "PP_mammals", "protein2"]
eukaryotes = eukaryotes.iloc[1:201,:]
mammals = mammals.iloc[1:201,:]
pp = pd.merge(mammals, eukaryotes, on=["gene", "protein2"], how="outer")
pp.fillna(0, inplace=True)
pp["PP"] = pp.apply... | code_fim | hard | {
"lang": "python",
"repo": "GuIrene/MECP2_phylogeny",
"path": "/string_overlap_analysis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> y = j*10 + yyy*10
yy = y+10
tagg = str(x) + "-" + str(y)
if self.clipboard[i][j] == 1:
if self.shapeCells == "square":
self.canvas.create_rectangle(x+1, y+1, xx-1, yy-1,
... | code_fim | hard | {
"lang": "python",
"repo": "touatily/Game-of-Life-Visualizer",
"path": "/window.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: touatily/Game-of-Life-Visualizer path: /window.py
rd is None:
self.escape(e)
return
x, y = e.x-e.x % 10, e.y-e.y % 10
x = min(max(0, x), self.canvas.winfo_width())
y = min(max(0, y), self.canvas.winfo_height())
xxx = x // 10
yyy = y... | code_fim | hard | {
"lang": "python",
"repo": "touatily/Game-of-Life-Visualizer",
"path": "/window.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def saveZonePS(self, e):
x, y = e.x - e.x % 10, e.y - e.y % 10
x = min(max(0, x), self.canvas.winfo_width())
y = min(max(0, y), self.canvas.winfo_height())
w, h = abs(self.x-x), abs(self.y-y)
x, y = min(self.x, x), min(self.y, y)
self.escape(e)
... | code_fim | hard | {
"lang": "python",
"repo": "touatily/Game-of-Life-Visualizer",
"path": "/window.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
for extension in extensions:
bot.load_extension(extension)
bot.run(TOKEN)<|fim_prefix|># repo: Vincentqchen/yeeb path: /src/bot.py
import sys
sys.path.append("../discord.py/")
import discord
from discord.ext import commands
with open("../res/token.txt", "r") a... | code_fim | medium | {
"lang": "python",
"repo": "Vincentqchen/yeeb",
"path": "/src/bot.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Vincentqchen/yeeb path: /src/bot.py
import sys
sys.path.append("../discord.py/")
import discord
from discord.ext import commands
<|fim_suffix|>if __name__ == '__main__':
for extension in extensions:
bot.load_extension(extension)
bot.run(TOKEN)<|fim_middle|>
with open("../res/toke... | code_fim | medium | {
"lang": "python",
"repo": "Vincentqchen/yeeb",
"path": "/src/bot.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: takabayashi/determined path: /harness/determined/pytorch/_pytorch_trial.py
ing.")
elif self.n_gpus > 1:
check.eq(
self.hvd_config.aggregation_frequency,
1,
"Please enable `optimized_parallel` to use aggregation "
... | code_fim | hard | {
"lang": "python",
"repo": "takabayashi/determined",
"path": "/harness/determined/pytorch/_pytorch_trial.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: takabayashi/determined path: /harness/determined/pytorch/_pytorch_trial.py
hTrialController needs an PyTorchTrial")
self.trial = cast(PyTorchTrial, trial_inst)
self._check_evaluate_implementation()
self.model = self.trial.build_model()
# Validation loader will be... | code_fim | hard | {
"lang": "python",
"repo": "takabayashi/determined",
"path": "/harness/determined/pytorch/_pytorch_trial.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return True
@staticmethod
def supports_averaging_training_metrics() -> bool:
return True
def _set_data_loaders(self) -> None:
skip_batches = (self.env.first_step() - 1) * self.batches_per_step
nreplicas = hvd.size() if self.hvd_config.use else 1
rank ... | code_fim | hard | {
"lang": "python",
"repo": "takabayashi/determined",
"path": "/harness/determined/pytorch/_pytorch_trial.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: l-vo/photos-picker path: /photospicker/picker/abstract_picker.py
from abc import ABCMeta, abstractmethod
from photospicker.event.scan_progress_event import ScanProgressEvent
from zope import event
from photospicker.exception.picker_exception import PickerException
import os
import fnmatch
import ... | code_fim | hard | {
"lang": "python",
"repo": "l-vo/photos-picker",
"path": "/photospicker/picker/abstract_picker.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def scan(self):
"""Scan the given path for building picked file paths list"""
picker_photos = self._order_picked(self._scan())
self._picked_file_paths = [
picker_photo.filepath for picker_photo in picker_photos
]
def _order_picked(self, picked):
... | code_fim | hard | {
"lang": "python",
"repo": "l-vo/photos-picker",
"path": "/photospicker/picker/abstract_picker.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dst = int(self.data['d'], 2)
self.put(src1 + src2, dst)
class Instruction_EB(CR_Instruction):
opcode = '10'
func4 = '1001'
name = 'EB'
def extra_constraints(self, data, bitstream):
if data['d'] != '00000':
raise ParseError('Expected dst to be 0')
... | code_fim | hard | {
"lang": "python",
"repo": "angr/angr-platforms",
"path": "/angr_platforms/risc_v/instrs_riscv/cr_instr.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: angr/angr-platforms path: /angr_platforms/risc_v/instrs_riscv/cr_instr.py
# pylint: disable=W0613,R0201,W0221,W0223
from .instruction_patterns import CR_Instruction
from pyvex.lifting.util import Type, ParseError
class Instruction_CJR(CR_Instruction):
opcode = '10'
func4 = '1000'
nam... | code_fim | hard | {
"lang": "python",
"repo": "angr/angr-platforms",
"path": "/angr_platforms/risc_v/instrs_riscv/cr_instr.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: obijywk/grilops path: /examples/outflight_entertainment.py
"""Solver for the sudoku variant in Outflight Entertainment.
Based on "Outflight Entertainment" from the Puzzlehunt CMU Spring 2020 hunt.
https://puzzlehunt.club.cc.cmu.edu/puzzle/11030/
"""
from z3 import Distinct, Implies
import gril... | code_fim | hard | {
"lang": "python",
"repo": "obijywk/grilops",
"path": "/examples/outflight_entertainment.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rc = grilops.regions.RegionConstrainer(lattice, sg.solver)
for y, x in lattice.points:
sg.solver.add(
rc.region_id_grid[(y, x)] == cage_label_to_region_id[cages[y][x]])
# Within each region, a parent cell must have a greater value than a child
# cell, so that the values increase as yo... | code_fim | hard | {
"lang": "python",
"repo": "obijywk/grilops",
"path": "/examples/outflight_entertainment.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>L = np.array([[2 if i == j else (-1 if (i == j - 1 or i == j + 1) else 0) for j in range(10)] for i in range(10)])
print(L)
print("\nQuestion 5\n")
T = np.array([[1 if ((i + j) % 2 == 0) else 0 for j in range(10)] for i in range(10)])
print(T)<|fim_prefix|># repo: emilienlemaire/DL2MI_TP path: /Math2... | code_fim | hard | {
"lang": "python",
"repo": "emilienlemaire/DL2MI_TP",
"path": "/Math208_Python/TP2/TP2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: emilienlemaire/DL2MI_TP path: /Math208_Python/TP2/TP2.py
import numpy as np
np.array([1, 2])
# Exercice 2.3
print("Question 1 \n")
A, x = np.array([[1, 2, 3], [4, 5, 6]]), np.array([1, 2, 3])
print(A.shape, x.shape)
print(A.size, x.size)
print(A.ndim, x.ndim)
print(A.dtype, x.dtype)
print(A.... | code_fim | hard | {
"lang": "python",
"repo": "emilienlemaire/DL2MI_TP",
"path": "/Math208_Python/TP2/TP2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#"+" operator
print("calculating 'hi' + 'hi' = ", "hi" + "hi")
print("calculating 3.0 + 3.0 = ", 3.0+3.0)
print("calculating (1+2j) + (2+3j) = ", (1+2j) + (2+3j))
print()
print("calculating 3.0 - 3.0 = ", 3.0-3.0)
print("calculating (1-2j) - (2-3j) = ", (1-2j) - (2-3j))
print()
print("calculating 3.0 / ... | code_fim | medium | {
"lang": "python",
"repo": "pbarton666/virtual_classroom",
"path": "/dkr-py310/docker-student-portal-310/course_files/begin_advanced/solution_python1_chapter02_operations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pbarton666/virtual_classroom path: /dkr-py310/docker-student-portal-310/course_files/begin_advanced/solution_python1_chapter02_operations.py
#solution_python1_chapter02_operations.py
"""A solution to Chapter 2"""
#help on the modulo operator (help() already prints
help(int.__mod__)
#how many f... | code_fim | medium | {
"lang": "python",
"repo": "pbarton666/virtual_classroom",
"path": "/dkr-py310/docker-student-portal-310/course_files/begin_advanced/solution_python1_chapter02_operations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Note the use of \ below. This allows line continuation.
summary= "So your name is " + name + ", " \
"you are a " + sign + ", " \
"and you like to drink " + fav_bev+ ". " \
"Right? "
answer= input(summary)
print("You said " + answer + ". Awesome!")<|fim_prefix|># repo: pbarton666/virtual_classr... | code_fim | hard | {
"lang": "python",
"repo": "pbarton666/virtual_classroom",
"path": "/dkr-py310/docker-student-portal-310/course_files/begin_advanced/solution_python1_chapter02_operations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #print(type(header))
global headers
global idnum
idnum+=1
header.id=idnum
#print(header.name)
if isfactor(header.factor):
nheader=iffactor(header.factor)
header.addfchild(nheader)
visitfactor(nheader)
headers.append(nheader)
# 进入并执行新建的节点
... | code_fim | hard | {
"lang": "python",
"repo": "FeiWANG-SJTU/DNAcompiler",
"path": "/d_parser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #print(type(header))
global headers
global idnum
idnum+=1
header.id=idnum
#print('header.factor',header.factor)
if isterm(header.term):
nheader=ifterm(header.term)
header.addtchild(nheader)
visitterm(nheader)
headers.append(nheader)
# 进入并执行新建... | code_fim | hard | {
"lang": "python",
"repo": "FeiWANG-SJTU/DNAcompiler",
"path": "/d_parser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FeiWANG-SJTU/DNAcompiler path: /d_parser.py
#function : construct syntax tree from tokens
# input: token list
# output: syntaxtree
# by OL Jan.7, 2016
import d_ast1
headers=[]
idnum=0
#build the corresponding node 建立对应的节点
def ifif(tokens):#for an if expr, create if node .如果是if语句，则创建if节点
#prin... | code_fim | hard | {
"lang": "python",
"repo": "FeiWANG-SJTU/DNAcompiler",
"path": "/d_parser.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#java -jar tika-server-1.22.jar --port 8001 #to start the server on port 8001
#'http://localhost:8001' origin server code
fs = os.listdir('pdfs/') #list files in specified directory in a list
root = 'pdfs/'
fs = [f for f in fs if os.path.join(root, f) and (str(f).endswith('.pdf') or str(f).e... | code_fim | medium | {
"lang": "python",
"repo": "phynicz/Pylucene-Search-Engine",
"path": "/extract.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>root = 'pdfs/'
fs = [f for f in fs if os.path.join(root, f) and (str(f).endswith('.pdf') or str(f).endswith('.docx')
or str(f).endswith('.pptx') or str(f).endswith('.doc') or str(f).endswith('.html') )] #using list comprehension to iterate through pdf and docx files
start = datetime.now()
for f in fs:... | code_fim | medium | {
"lang": "python",
"repo": "phynicz/Pylucene-Search-Engine",
"path": "/extract.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: phynicz/Pylucene-Search-Engine path: /extract.py
#!/usr/bin/env python
import os
import tika
import shutil
import time
from tika import parser
tika.TikaClientOnly = True
from datetime import datetime
headers = {
'X-Tika-PDFextractInlineImages': 'true',
}
<|fim_suffix|>fs = [f for f in fs if os.... | code_fim | hard | {
"lang": "python",
"repo": "phynicz/Pylucene-Search-Engine",
"path": "/extract.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>LOOPS = 2
with open(sys.argv[1]) as reader:
records = avro_reader(reader)
SCHEMA = records.schema
RECORDS = list(records)
buf = BytesIO()
m = 0
n = 0
start = time()
for _ in repeat(None, LOOPS):
for record in RECORDS:
dump(buf, record, SCHEMA)
m += buf.tell()
n += 1
buf.seek(0)
i... | code_fim | medium | {
"lang": "python",
"repo": "mtth/avsc",
"path": "/etc/benchmarks/avro-serialization-implementations/scripts/encode/python-fastavro.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mtth/avsc path: /etc/benchmarks/avro-serialization-implementations/scripts/encode/python-fastavro.py
#!/usr/bin/env python2.7
# encoding: utf-8
"""Fastavro."""
from io import BytesIO
from itertools import repeat
from time import time
from fastavro import dump, load, acquaint_schema, reader as a... | code_fim | medium | {
"lang": "python",
"repo": "mtth/avsc",
"path": "/etc/benchmarks/avro-serialization-implementations/scripts/encode/python-fastavro.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>logger.error("error inner lib")
# logging.info("error inner lib")
logging.critical("error inner lib")
# logging.debug("error inner lib")
# logger = logging.getLogger(__name__)<|fim_prefix|># repo: Sean10/Algorithm_code path: /logger/logger_module/s_logger.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
... | code_fim | hard | {
"lang": "python",
"repo": "Sean10/Algorithm_code",
"path": "/logger/logger_module/s_logger.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Sean10/Algorithm_code path: /logger/logger_module/s_logger.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019-10-13 21:46
# @Author : sean10
# @Site :
# @File : s_logger.py
# @Software: PyCharm
<|fim_suffix|>logger.error("error inner lib")
# logging.info("error inner lib"... | code_fim | hard | {
"lang": "python",
"repo": "Sean10/Algorithm_code",
"path": "/logger/logger_module/s_logger.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Good Creation
itr_resp = admin_client.create(
itr_uri, name='test_iterable',
attributes={'test1': 'foo'},
min_val=100, max_val=200,
increment=1,
)
itr = get_result(itr_resp)
itr_obj_url = site.detail_uri('iterable', id=itr['id'])
ass... | code_fim | hard | {
"lang": "python",
"repo": "dirtyonekanobi/nsot",
"path": "/tests/api_tests/test_iterables.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dirtyonekanobi/nsot path: /tests/api_tests/test_iterables.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import pytest
# Allow everything in there to access the DB
pytestmark = pytest.mark.django_db
import copy
from django.core.urlresolvers import reverse
import json
import... | code_fim | medium | {
"lang": "python",
"repo": "dirtyonekanobi/nsot",
"path": "/tests/api_tests/test_iterables.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: apache/libcloud path: /libcloud/test/dns/test_luadns.py
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file t... | code_fim | hard | {
"lang": "python",
"repo": "apache/libcloud",
"path": "/libcloud/test/dns/test_luadns.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _v1_zones_11_records_LIST_RECORDS_SUCCESS(self, method, url, body, headers):
body = self.fixtures.load("records_list.json")
return httplib.OK, body, {}, httplib.responses[httplib.OK]
def _v1_zones_31_records_31_GET_RECORD_RECORD_DOES_NOT_EXIST(self, method, url, body, headers... | code_fim | hard | {
"lang": "python",
"repo": "apache/libcloud",
"path": "/libcloud/test/dns/test_luadns.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _v1_zones_EMPTY_ZONES_LIST(self, method, url, body, headers):
body = self.fixtures.load("empty_zones_list.json")
return httplib.OK, body, {}, httplib.responses[httplib.OK]
def _v1_zones_13_ZONE_DOES_NOT_EXIST(self, method, url, body, headers):
body = self.fixtures.loa... | code_fim | hard | {
"lang": "python",
"repo": "apache/libcloud",
"path": "/libcloud/test/dns/test_luadns.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(ct)
strain_names.close()
fasta_file_fixed.close()
fasta_file.close()<|fim_prefix|># repo: dunhamlab/SUL1_natural_variants path: /generate_fasta_references/rename_fasta.py
# adds strain name to fasta files
fasta_file = open("../SUL1_CDS.fasta","r")
fasta_file_fixed = open("../SUL1_ext_full_CDS.fast... | code_fim | hard | {
"lang": "python",
"repo": "dunhamlab/SUL1_natural_variants",
"path": "/generate_fasta_references/rename_fasta.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dunhamlab/SUL1_natural_variants path: /generate_fasta_references/rename_fasta.py
# adds strain name to fasta files
fasta_file = open("../SUL1_CDS.fasta","r")
fasta_file_fixed = open("../SUL1_ext_full_CDS.fasta","w+")
<|fim_suffix|>names = []
for line in strain_names:
line = line.strip()
names... | code_fim | medium | {
"lang": "python",
"repo": "dunhamlab/SUL1_natural_variants",
"path": "/generate_fasta_references/rename_fasta.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>Sources:
{retrieved}
Answer:
"""
def __init__(self, search_client: SearchClient, openai_deployment: str, sourcepage_field: str, content_field: str):
self.search_client = search_client
self.openai_deployment = openai_deployment
self.sourcepage_field = sourcepage_field
... | code_fim | hard | {
"lang": "python",
"repo": "uipathsmartbridge/uipath",
"path": "/app/backend/approaches/retrievethenread.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: uipathsmartbridge/uipath path: /app/backend/approaches/retrievethenread.py
import openai
from approaches.approach import Approach
from azure.search.documents import SearchClient
from azure.search.documents.models import QueryType
from text import nonewlines
from typing import Any
class Retrieve... | code_fim | hard | {
"lang": "python",
"repo": "uipathsmartbridge/uipath",
"path": "/app/backend/approaches/retrievethenread.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, search_client: SearchClient, openai_deployment: str, sourcepage_field: str, content_field: str):
self.search_client = search_client
self.openai_deployment = openai_deployment
self.sourcepage_field = sourcepage_field
self.content_field = content_field
... | code_fim | hard | {
"lang": "python",
"repo": "uipathsmartbridge/uipath",
"path": "/app/backend/approaches/retrievethenread.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def train(self):
self._setting()
self.iter = -1
best_s = 100
for epoch in self.iter_counter.training_epochs():
if self.iter > self.opt.total_step:
break
for i, data_i in enumerate(self.train_loader):
self.iter = ... | code_fim | hard | {
"lang": "python",
"repo": "FloatButterfly/SPM",
"path": "/train_spm_codec.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FloatButterfly/SPM path: /train_spm_codec.py
"""
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import sys
import torch
from torch.utils.data import DataLoader
# from torch... | code_fim | hard | {
"lang": "python",
"repo": "FloatButterfly/SPM",
"path": "/train_spm_codec.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _init_loaders(self):
super(WithTest, self)._init_loaders()
test_dataset = TrainPairedData(self.opt.test_dataroot, self.opt)
self.test_loader = DataLoader(
dataset=test_dataset,
batch_size=self.opt.batchSize,
sampler=self.data_sampler(test... | code_fim | hard | {
"lang": "python",
"repo": "FloatButterfly/SPM",
"path": "/train_spm_codec.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.initGypting(mType)
if self.exception:
return "ERROR"
encodedString = ""
for n in range(0,len(self.message)):
if eD == "egyptIt":
index = self.charactersArray.index(self.message[n])
encodedString = encodedString + ... | code_fim | hard | {
"lang": "python",
"repo": "marzukr/Egyptinator",
"path": "/egyptC0re.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: marzukr/Egyptinator path: /egyptC0re.py
import collections,sys,hashlib
class Processor:
charactersArray = []
codeCharactersArray = []
exception = False
def __init__(self, key, message):
self.key = key
self.message = message
def repeatable_random(self, seed)... | code_fim | hard | {
"lang": "python",
"repo": "marzukr/Egyptinator",
"path": "/egyptC0re.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> board.set_cell_by_indexes(1, 0, "First")
board.set_cell_by_indexes(2, 0, "Second")
board.set_cell_by_indexes(3, 0, "Third")
board.set_cell_by_indexes(4, 0, "Fourth")
for row in range(1, 5):
for col in range(1, 4):
if row != col:
... | code_fim | hard | {
"lang": "python",
"repo": "OlegBaskov/language-learning",
"path": "/tests/test_dashboard.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OlegBaskov/language-learning path: /tests/test_dashboard.py
import unittest
from src.dash_board.textdashboard import TextFileDashboard, TextFileDashboardComponent
from src.pipeline.pipelinetree import get_component
conf = {
"component": "dash-board",
"type": "static",
"instance-nam... | code_fim | hard | {
"lang": "python",
"repo": "OlegBaskov/language-learning",
"path": "/tests/test_dashboard.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertEqual(should_be, board.get_text())
def test_component(self):
board = get_component("dash-board", conf["parameters"])
self.assertTrue(True, True)
def test_less_headers(self):
board = get_component("dash-board", less_headers["parameters"])
self.as... | code_fim | hard | {
"lang": "python",
"repo": "OlegBaskov/language-learning",
"path": "/tests/test_dashboard.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Args:
filename_queue: A tensorflow queue of filename locations.
max_quantized_value: the maximum of the quantized value.
min_quantized_value: the minimum of the quantized value.
Returns:
A tuple of video indexes, video features, labels, and padding data.
"""
reader... | code_fim | hard | {
"lang": "python",
"repo": "chintak/youtube-8m",
"path": "/readers.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self,
num_classes=4716,
feature_sizes=[1024],
feature_names=["inc3"],
max_frames=300):
"""Construct a YT8MFrameFeatureReader.
Args:
num_classes: a positive integer for the number of classes.
feature_sizes: posi... | code_fim | hard | {
"lang": "python",
"repo": "chintak/youtube-8m",
"path": "/readers.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chintak/youtube-8m path: /readers.py
TIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Provides readers configured for different datasets."""
import tensorflow as tf
import numpy as np
import u... | code_fim | hard | {
"lang": "python",
"repo": "chintak/youtube-8m",
"path": "/readers.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Boris-Barboris/PySubs path: /game/CameraController.py
# Copyright Alexander Baranin 2016
import math
import sys
import sfml
from sfml.system import Vector2
from sfml.window import Keyboard
from engine.Reloadable import reloadable
_import_modules = (
('EngineCore', 'engine.EngineCore'),... | code_fim | hard | {
"lang": "python",
"repo": "Boris-Barboris/PySubs",
"path": "/game/CameraController.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def do_zoom(self, camera, zoom_delta):
scale_shift = zoom_delta * (1.0 + camera.scale * 10.0)
camera.scale -= scale_shift
camera.scale = max(0.05, camera.scale)
camera.scale = min(10.0, camera.scale)
return scale_shift
def handle_click(self, event, wnd):
... | code_fim | hard | {
"lang": "python",
"repo": "Boris-Barboris/PySubs",
"path": "/game/CameraController.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> dt = min(EngineCore.frame_time, 0.1)
camera = WorldComposer.composer.camera
if Keyboard.is_key_pressed(Keyboard.RIGHT):
camera.position += Vector2(KEY_PAN_SPEED, 0.0) * camera.scale * dt
if Keyboard.is_key_pressed(Keyboard.UP):
camera.position += Vec... | code_fim | hard | {
"lang": "python",
"repo": "Boris-Barboris/PySubs",
"path": "/game/CameraController.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HesslerY/loewner path: /main/PythonTools/LoewnerRun.py
phi = delta
# Decrease end point if final_phi = pi
if final_phi == pi:
final_phi = final_phi - delta
# Discretise the interval from start_phi to final_phi
discr_pi = linspace(start_phi,final_phi,s... | code_fim | hard | {
"lang": "python",
"repo": "HesslerY/loewner",
"path": "/main/PythonTools/LoewnerRun.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Convert the results to a 2D array
results_array = column_stack((self.exact_time_sol, self.exact_driving_arr))
# Create a filename for the dat file
filename = EXACT_INVERSE_DATA_OUTPUT + self.short_properties_string + DATA_EXT
# Save the array... | code_fim | hard | {
"lang": "python",
"repo": "HesslerY/loewner",
"path": "/main/PythonTools/LoewnerRun.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HesslerY/loewner path: /main/PythonTools/LoewnerRun.py
exit()
# Import the compiled Inverse Loewner module
InverseLoewner = import_module(self.inverse_module_name)
# Declare empty arrays for the time and driving function values
self.driving_arr = empt... | code_fim | hard | {
"lang": "python",
"repo": "HesslerY/loewner",
"path": "/main/PythonTools/LoewnerRun.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@register_module_fixer([nn.InstanceNorm1d, nn.InstanceNorm2d, nn.InstanceNorm3d])
def fix(module: INSTANCENORM) -> INSTANCENORM:
if len(validate(module)) == 0:
return module
# else
new_module = clone_module(module)
new_module.track_running_stats = False
return new_module<|fim_... | code_fim | hard | {
"lang": "python",
"repo": "pytorch/opacus",
"path": "/opacus/validators/instance_norm.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pytorch/opacus path: /opacus/validators/instance_norm.py
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# 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 th... | code_fim | hard | {
"lang": "python",
"repo": "pytorch/opacus",
"path": "/opacus/validators/instance_norm.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return (
[
IllegalModuleConfigurationError(
"We do not support tracking running stats with differential privacy. "
"To support it, we would have to add a DP mechanism for these statistics too, "
"which would incur a privacy cost for l... | code_fim | hard | {
"lang": "python",
"repo": "pytorch/opacus",
"path": "/opacus/validators/instance_norm.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> input_dir = os.path.abspath(os.path.join(testcase_path, 'sensor'))
config['uri_to_local'] = {'redfish.dmtf.org/schemas/v1': input_dir}
config['local_to_uri'] = { input_dir : 'redfish.dmtf.org/schemas/v1'}
docGen = DocGenerator([ input_dir ], '/dev/null', config)
output = docGen.gener... | code_fim | hard | {
"lang": "python",
"repo": "DMTF/Redfish-Tools",
"path": "/doc-generator/tests/test_combine_multiple_refs.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>@patch('urllib.request') # so we don't make HTTP requests. NB: samples should not call for outside resources.
def test_combine_at_3_html(mockRequest):
""" Threshold is set at 3. This is a likely choice; our example is a sextuple of references.
This test exercises HTML output.
"""
conf... | code_fim | hard | {
"lang": "python",
"repo": "DMTF/Redfish-Tools",
"path": "/doc-generator/tests/test_combine_multiple_refs.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DMTF/Redfish-Tools path: /doc-generator/tests/test_combine_multiple_refs.py
# Copyright Notice:
# Copyright 2020 Distributed Management Task Force, Inc. All rights reserved.
# License: BSD 3-Clause License. For full text see link: https://github.com/DMTF/Redfish-Tools/blob/main/LICENSE.md
"""
Fi... | code_fim | hard | {
"lang": "python",
"repo": "DMTF/Redfish-Tools",
"path": "/doc-generator/tests/test_combine_multiple_refs.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> 2)
sentences.append(text)
labels = np.ravel(labels)
return sentences, labels<|fim_prefix|># repo: cyzhangAThit/shalo path: /utils/parse_data.py
import numpy as np
import os
def get_data_from_file_polarity(fname):
labels, sentences = [], []
with open(fname, 'rb') as f:
... | code_fim | medium | {
"lang": "python",
"repo": "cyzhangAThit/shalo",
"path": "/utils/parse_data.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cyzhangAThit/shalo path: /utils/parse_data.py
import numpy as np
import os
def get_data_from_file_polarity(fname):
labels, sentences = []<|fim_suffix|>().split(' ', 1)
text = text.split(' ')
labels.append((int(label) + 1) / 2)
sentences.append(text)
la... | code_fim | medium | {
"lang": "python",
"repo": "cyzhangAThit/shalo",
"path": "/utils/parse_data.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: orijtech/orijpython path: /archomp/v1/__init__.py
import requests
# Archomp implements a client to coordinate with the archive
# compressor API provided by orijtech.com. It takes in key value pairs
# describing URLs , and then compresses them together into a zip
# and streams back the .zip body.... | code_fim | hard | {
"lang": "python",
"repo": "orijtech/orijpython",
"path": "/archomp/v1/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> req = {'files': vettedOptions}
res = requests.post(self.__BaseURL, json=req, headers=header, stream=True)
if res.status_code != 200:
return None, Error(res.text)
return res.iter_content(chunk_size=1024 * 256), None
def replaceItemOfIndex(itemsList, value, index):
"""
The goal h... | code_fim | hard | {
"lang": "python",
"repo": "orijtech/orijpython",
"path": "/archomp/v1/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> "subcategory",
"line_item",
"year",
["amount", "float"]
])
main.aggregate(keys=["year", "category"], measures=["amount"])
main.field_map(keep_fiel... | code_fim | hard | {
"lang": "python",
"repo": "lordnynex/CLEANUP",
"path": "/FORKS/Python/brewery/tree/examples/aggregate_remote_csv.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lordnynex/CLEANUP path: /FORKS/Python/brewery/tree/examples/aggregate_remote_csv.py
"""
Data Brewery Example
Aggregate a remote CSV file.
"""
import brewery
main = brewery.create_builder()
main.csv_source("https://raw.github.com/Stiivi/cubes/master/examples/hello_world/dat<|fim_suffix|> ... | code_fim | hard | {
"lang": "python",
"repo": "lordnynex/CLEANUP",
"path": "/FORKS/Python/brewery/tree/examples/aggregate_remote_csv.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dulichan/iot-ref-arch path: /python-agent/agent/custom/publishers/TemperaturePublisher.py
'''
Copyright (c) 2005-2011, WSO2 Inc. (http://www.wso2.org) All Rights Reserved.
WSO2 Inc. licenses this file to you under the Apache License,
Version 2.0 (the "License"); you may not use this file exce... | code_fim | medium | {
"lang": "python",
"repo": "dulichan/iot-ref-arch",
"path": "/python-agent/agent/custom/publishers/TemperaturePublisher.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def run(self):
'''
Main task of the Process. This is used to read perform some
device operations to collect data
'''
humidity, temperature = get_dht_temp()
if humidity is not None and temperature is not None:
input = {
... | code_fim | hard | {
"lang": "python",
"repo": "dulichan/iot-ref-arch",
"path": "/python-agent/agent/custom/publishers/TemperaturePublisher.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> tempFile = open("/sys/class/thermal/thermal_zone0/temp")
cpu_temp = tempFile.read()
tempFile.close()
return float(cpu_temp) / 1000
# Uncomment the next line if you want the temp in Fahrenheit
# return float(1.8*cpu_temp)+32
def get_gpu_temp(self):
... | code_fim | hard | {
"lang": "python",
"repo": "dulichan/iot-ref-arch",
"path": "/python-agent/agent/custom/publishers/TemperaturePublisher.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def imprime():
for i in lista:
print(i)
while True:
lista.clear()
escolha = input('Qual filme deseja pesquisar? (S para sair): ')
if escolha.lower() == 's':
print('Saindo do script...')
break
busca(escolha)
imprime_esc = input('Deseja imprimir a lista? (Y... | code_fim | medium | {
"lang": "python",
"repo": "dafonse/python-scripts",
"path": "/buscaFilme/buscaFilme.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
while True:
lista.clear()
escolha = input('Qual filme deseja pesquisar? (S para sair): ')
if escolha.lower() == 's':
print('Saindo do script...')
break
busca(escolha)
imprime_esc = input('Deseja imprimir a lista? (Y/N): ')
if imprime_esc.lower() == 'y':
imp... | code_fim | medium | {
"lang": "python",
"repo": "dafonse/python-scripts",
"path": "/buscaFilme/buscaFilme.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dafonse/python-scripts path: /buscaFilme/buscaFilme.py
import requests
import json
api_key = "APIKEY"
lista = []
def busca(buscar):
'''
É um método, pois não tem retorno e só modifica a lista[]
'''
page = 1
seq = 1
print('Buscando...')
while True:
req = requ... | code_fim | medium | {
"lang": "python",
"repo": "dafonse/python-scripts",
"path": "/buscaFilme/buscaFilme.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rileyhales/geomatics path: /publication_data/sample_data/geotiff_sample_data.py
import os
import glob
import geomatics
path_to_save_gtiffs = os.path.join(o<|fim_suffix|>oin(os.path.dirname(__file__), 'netcdf_data', '*.nc4'))
var = 'Tair_f_inst'
geomatics.convert.to_gtiffs(netcdf_files, var, save... | code_fim | medium | {
"lang": "python",
"repo": "rileyhales/geomatics",
"path": "/publication_data/sample_data/geotiff_sample_data.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>geomatics.convert.to_gtiffs(netcdf_files, var, save_dir=path_to_save_gtiffs)<|fim_prefix|># repo: rileyhales/geomatics path: /publication_data/sample_data/geotiff_sample_data.py
import os
import glob
import geomatics
path_to_save_gtiffs = os.path.join(o<|fim_middle|>s.path.dirname(__file__), 'geotiff_da... | code_fim | medium | {
"lang": "python",
"repo": "rileyhales/geomatics",
"path": "/publication_data/sample_data/geotiff_sample_data.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('ledger', '0069_multi_eon_matching_tokens_populate'),
]
operations = [
migrations.CreateModel(
name='TOSConfig',
fields=[
('id', models.AutoField(auto_created=True,
primary_key=Tr... | code_fim | hard | {
"lang": "python",
"repo": "xiaobai900/nocust-hub",
"path": "/operator_api/tos/migrations/001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xiaobai900/nocust-hub path: /operator_api/tos/migrations/001_initial.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.20 on 2019-10-23 11:15
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class... | code_fim | hard | {
"lang": "python",
"repo": "xiaobai900/nocust-hub",
"path": "/operator_api/tos/migrations/001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Lucas-Irvine/Particle-Cloud-Framework path: /examples/particle/aws/ecs/use_ecs_service/example_ecs_service.py
from pcf.particle.aws.ecs.ecs_cluster import ECSCluster
from pcf.particle.aws.ecs.ecs_task_definition import ECSTaskDefinition
from pcf.particle.aws.ecs.ecs_service import ECSService
fro... | code_fim | hard | {
"lang": "python",
"repo": "Lucas-Irvine/Particle-Cloud-Framework",
"path": "/examples/particle/aws/ecs/use_ecs_service/example_ecs_service.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>pcf = PCF([])
pcf.add_particles((
ecs_cluster,
ecs_service,
ecs_task_def,
))
pcf.link_particles(pcf.particles)
pcf.apply(sync=True, cascade=True)
# example start
ecs_cluster.set_desired_state(State.running)
ecs_task_def.set_desired_state(State.running)
ecs_service.set_desired_state(State.runn... | code_fim | hard | {
"lang": "python",
"repo": "Lucas-Irvine/Particle-Cloud-Framework",
"path": "/examples/particle/aws/ecs/use_ecs_service/example_ecs_service.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #if lineno > 100000:
# break
years = sorted(years)
entities = sorted(entities)
print("Calculating diffs...")
sys.stdout.flush()
diffs = []
for prev_year in range(min(years),2020):
for entity_type,entity_id in entities:
prev_count = counts[ (prev_year,entity_type,entity_id) ]
next_co... | code_fim | medium | {
"lang": "python",
"repo": "personx000/corona-ml",
"path": "/topic-surging-analysis/calcYearDiffs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: personx000/corona-ml path: /topic-surging-analysis/calcYearDiffs.py
import argparse
from collections import Counter
import sys
import json
if __name__ == '__main__':
parser = argparse.ArgumentParser('Calculate the year-on-year differences in entity mention counts')
parser.add_argument('--count... | code_fim | hard | {
"lang": "python",
"repo": "personx000/corona-ml",
"path": "/topic-surging-analysis/calcYearDiffs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("Saving...")
sys.stdout.flush()
with open(args.outFile,'w') as f:
for diff_data in diffs[:10000]:
f.write( "\t".join(map(str,diff_data)) + "\n" )
print("Done")
sys.stdout.flush()<|fim_prefix|># repo: personx000/corona-ml path: /topic-surging-analysis/calcYearDiffs.py
import argparse
fro... | code_fim | hard | {
"lang": "python",
"repo": "personx000/corona-ml",
"path": "/topic-surging-analysis/calcYearDiffs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PeterZs/reflectance-filtering path: /training/train_with_barrista.py
#!/usr/bin/env python
# MIT License
#
# Copyright (c) 2017 Thomas Nestmeyer
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software")... | code_fim | hard | {
"lang": "python",
"repo": "PeterZs/reflectance-filtering",
"path": "/training/train_with_barrista.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Create the folder base_dir (if not existing yet) and in it,
create all subdirectories in create_dir.
"""
mkdir_p(base_dir)
for d in create_dirs:
mkdir_p(os.path.join(base_dir, d))
def _vis_square(data, padsize=1, padval=0):
"""Inspired by the caffe ipython notebook on fil... | code_fim | hard | {
"lang": "python",
"repo": "PeterZs/reflectance-filtering",
"path": "/training/train_with_barrista.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ariel98po/SC101_Assignment path: /SC101_Assignment2_葉思佟/breakoutgraphics.py
"""
stanCode Breakout Project
Adapted from Eric Roberts's Breakout by
Sonja Johnson-Yu, Kylie Jue, Nick Bowman,
and Jerry Liao
YOUR DESCRIPTION HERE
"""
from campy.graphics.gwindow import GWindow
from campy.graphics.gob... | code_fim | hard | {
"lang": "python",
"repo": "ariel98po/SC101_Assignment",
"path": "/SC101_Assignment2_葉思佟/breakoutgraphics.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.ball.x + self.ball.width >= self.window.width or self.ball.x <= 0:
self.__dx = -self.__dx
if self.ball.y <= 0:
self.__dy = -self.__dy
def mouse_start(self, event):
global lives
x_start = (self.window.width - self.ball.width) / 2
... | code_fim | hard | {
"lang": "python",
"repo": "ariel98po/SC101_Assignment",
"path": "/SC101_Assignment2_葉思佟/breakoutgraphics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DarkShadow4/Python path: /olimpiada/ejercicios/random/estrella de la muerte.py
def generar_hangar():
"""Funcion para generar el hangar tal y como aparecera siempre como minimo"""
ubicaciones = []
ubicaciones.append("T")
for i in range(9):
ubicaciones.append("o")
ubicaciones.append("T")
... | code_fim | hard | {
"lang": "python",
"repo": "DarkShadow4/Python",
"path": "/olimpiada/ejercicios/random/estrella de la muerte.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while torretas_adicionales < 0 or torretas_adicionales > 4:
torretas_adicionales = input("Numero de torretas adicionales: ")
ubicacion_anterior = 0
while torretas_adicionales > 0:
if ubicacion_anterior is not 8:
ubicacion = input("Ubicacion: ")
if ubicacion%2 == 0:
if ubicacion > ubic... | code_fim | medium | {
"lang": "python",
"repo": "DarkShadow4/Python",
"path": "/olimpiada/ejercicios/random/estrella de la muerte.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Funcion no terminada, simplemente muestra algo si hay el maximo o no hay torretas adicionales"""
torretas_adicionales = ubicaciones.count("t") # obtengo cuantas t (torretas adicionales) hay en ubicaciones
if torretas_adicionales == 0:
print "Posicion: 5"
if torretas_adicionales == 4:
print "Pos... | code_fim | hard | {
"lang": "python",
"repo": "DarkShadow4/Python",
"path": "/olimpiada/ejercicios/random/estrella de la muerte.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chlien/MFIR-AP path: /run.py
"tns" : tns,
"fns" : fns}
return data_dict
def combine_all_metrics(all_metrics_dict_list):
result = {}
sum_dict = {}
sum_keys = ["ATTA", "APT",
"precision", "recall",
"accuracy",
... | code_fim | hard | {
"lang": "python",
"repo": "chlien/MFIR-AP",
"path": "/run.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> table {{
border-collapse: collapse;
border: 2px solid rgb(200,200,200);
letter-spacing: 1px;
font-size: 0.8rem;
}}
td, th {{
border: 1px soli... | code_fim | hard | {
"lang": "python",
"repo": "chlien/MFIR-AP",
"path": "/run.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> summary_dict = {}
summary_dict["epochs"] = model_dict["epochs"]
summary_dict["batch_size"] = model_dict["batch_size"]
summary_dict["train_size"] = model_dict["train_set_ratio"]
summary_dict["loss_function"] = model_dict["loss_function"]
summary_dict["frames"] = model_dict["frames"]... | code_fim | hard | {
"lang": "python",
"repo": "chlien/MFIR-AP",
"path": "/run.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
y_pred, np.array of int (test_samples)
"""
# TODO: Implement predict
# Hint: some of the code of the compute_loss_and_gradients
# can be reused
pred = np.zeros(X.shape[0], np.int)
to_relu = self.input_layer.forward(X)
to_ou... | code_fim | hard | {
"lang": "python",
"repo": "temur-kh/dlcourse_ai",
"path": "/assignments/assignment2/model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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