text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: Bohdanski/daily-oos-report path: /daily_oos_report.py
"""
Builds the datasheet for the daily out-of-stock report.
"""
import os
import re
import sys
import glob
import zipfile
import fnmatch
import datetime
import pandas as pd
import numpy as np
import openpyxl
from zipfile import ZipFile
from ... | code_fim | hard | {
"lang": "python",
"repo": "Bohdanski/daily-oos-report",
"path": "/daily_oos_report.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> df_cs = workbook.parse(0, skiprows=3, skipfooter=20, header=None)
df_cs = df_cs[~df_cs[7].isin(to_drop)]
df_cs = df_cs.filter([0, 14, 15, 17, 34])
df_cs.columns = ["custCode",
"poDueDate",
... | code_fim | hard | {
"lang": "python",
"repo": "Bohdanski/daily-oos-report",
"path": "/daily_oos_report.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HENNGE/aapns path: /src/aapns/errors.py
from typing import Any, Dict, Optional, Type
class APNSError(Exception):
pass
class Blocked(APNSError):
"""This connection can't send more data at this point, can try later."""
class Closed(APNSError):
"""This connection is now closed, try... | code_fim | hard | {
"lang": "python",
"repo": "HENNGE/aapns",
"path": "/src/aapns/errors.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, reason: str, apns_id: Optional[str]):
self.reason = reason
self.apns_id = apns_id
super().__init__(reason)
class UnknownResponseError(ResponseError):
codename = "!unknown"
CODES: Dict[str, Type[ResponseError]] = {}
def create(codename: str) -> Type[... | code_fim | hard | {
"lang": "python",
"repo": "HENNGE/aapns",
"path": "/src/aapns/errors.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> codename: str
def __init__(self, reason: str, apns_id: Optional[str]):
self.reason = reason
self.apns_id = apns_id
super().__init__(reason)
class UnknownResponseError(ResponseError):
codename = "!unknown"
CODES: Dict[str, Type[ResponseError]] = {}
def create(code... | code_fim | hard | {
"lang": "python",
"repo": "HENNGE/aapns",
"path": "/src/aapns/errors.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: czs108/LeetCode-Solutions path: /Medium/334. Increasing Triplet Subsequence/solution (2).py
# 334. Increasing Triplet Subsequence
# Runtime: 885 ms, faster than 15.19% of Python3 online submissions for Increasing Triplet Subsequence.
# Memory Usage: 25.2 MB, less than 49.40% of Python3 online s... | code_fim | medium | {
"lang": "python",
"repo": "czs108/LeetCode-Solutions",
"path": "/Medium/334. Increasing Triplet Subsequence/solution (2).py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Linear Scan
def increasingTriplet(self, nums: list[int]) -> bool:
if len(nums) < 3:
return False
first, second = math.inf, math.inf
for n in nums:
if n <= first:
first = n
elif n <= second:
second = n
... | code_fim | medium | {
"lang": "python",
"repo": "czs108/LeetCode-Solutions",
"path": "/Medium/334. Increasing Triplet Subsequence/solution (2).py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AIandSocialGoodLab/identify-illegal-mining-sites path: /nonmine_annotate.py
import numpy as np
import os
import cv2
import shutil
folder = input("File to images of non mines: ")
i = int(input("File number to start on: "))
<|fim_suffix|>for i in range(mineLength):
image = mineJPG[:-4]
... | code_fim | hard | {
"lang": "python",
"repo": "AIandSocialGoodLab/identify-illegal-mining-sites",
"path": "/nonmine_annotate.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> image = mineJPG[:-4]
import sys
try: fn = sys.argv[1]
except: fn = '%s/%s'%(folder, mineJPG)
print(__doc__)
img = cv2.imread(fn, True)
h, w = img.shape[:2]
f = open("%s/%s.xml"%(folder, image),"w")
f.write((text)%(folder, mineJPG, folder, mineJPG, w, h, w, h))
f.cl... | code_fim | hard | {
"lang": "python",
"repo": "AIandSocialGoodLab/identify-illegal-mining-sites",
"path": "/nonmine_annotate.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Highlight the changes
if False:
for change in changes_in_delt:
ax.axvline(x=change, color='maroon', alpha=0.5, zorder=1)
# Show figure
ax.set_yscale('log')
ax.autoscale()
ax.legend(labelspacing=0.0, handlelength=1, shadow=True)
plt.show()
return
... | code_fim | hard | {
"lang": "python",
"repo": "stellaGK/stella",
"path": "/stellapy/data/stella/check_cflcushion.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stellaGK/stella path: /stellapy/data/stella/check_cflcushion.py
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
def check_cflcushion(delt=0.1, cfl_cushion_upper=0.5, cfl_cushion_lower=0.1, code_dt_max=0.1, nstep=100):
"""
We always want to kee... | code_fim | hard | {
"lang": "python",
"repo": "stellaGK/stella",
"path": "/stellapy/data/stella/check_cflcushion.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Verify --limit X, where X is a positive integer, succeeds.
The command will print out X number of project cells.
"""
self.shell('cell-list -r 1 --limit 1')
mock_list.assert_called_once_with(limit=1)
def test_cell_list_limit_negative_num_failure(self):
... | code_fim | hard | {
"lang": "python",
"repo": "sigmavirus24/python-cratonclient",
"path": "/cratonclient/tests/unit/test_cells_shell.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sigmavirus24/python-cratonclient path: /cratonclient/tests/unit/test_cells_shell.py
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/... | code_fim | hard | {
"lang": "python",
"repo": "sigmavirus24/python-cratonclient",
"path": "/cratonclient/tests/unit/test_cells_shell.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@app.command()
def part2(input_file: str):
_, line = read_input_file(input_file)
ids, remainders = parse_second_line(line)
solution = crt(ids, remainders)
print(f"The solution for part 2 is {solution}")
if __name__ == "__main__":
app()<|fim_prefix|># repo: RJPlog/aoc-2020 path: /d... | code_fim | hard | {
"lang": "python",
"repo": "RJPlog/aoc-2020",
"path": "/day13/python/ceedee666/day13.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RJPlog/aoc-2020 path: /day13/python/ceedee666/day13.py
from pathlib import Path
from functools import reduce
from operator import mul
import typer
app = typer.Typer()
def read_input_file(input_file_path):
p = Path(input_file_path)
with p.open() as f:
lines = f.readlines()
... | code_fim | hard | {
"lang": "python",
"repo": "RJPlog/aoc-2020",
"path": "/day13/python/ceedee666/day13.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@app.command()
def part1(input_file: str):
time, busses = read_input_file(input_file)
busses = map(lambda i: int(i), filter(lambda s: s.isdigit(), busses))
wating_time = reduce(lambda a, b: a if a[1] < b[1] else b,
map(lambda b: (b, b - time % b), busses))
print... | code_fim | medium | {
"lang": "python",
"repo": "RJPlog/aoc-2020",
"path": "/day13/python/ceedee666/day13.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sebinjohn/replication_manager path: /src/replications/ds_replications.py
from replications import *
import sys
from argparse import ArgumentParser
parser = ArgumentParser(description='DS BDR Client')
def parse_args(sys_args):
group = parser.add_mutually_exclusive_group()
group.add_argume... | code_fim | hard | {
"lang": "python",
"repo": "sebinjohn/replication_manager",
"path": "/src/replications/ds_replications.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser.add_argument('--service-name', nargs=1, required=True)
parser.add_argument('--cluster-name', nargs=1, required=True)
parser.add_argument('--api-host', nargs=1, required=True)
parser.add_argument('--api-port', default=7180, type=int)
parser.add_argument('--api-version', default=... | code_fim | hard | {
"lang": "python",
"repo": "sebinjohn/replication_manager",
"path": "/src/replications/ds_replications.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> args = parse_args(sys_args)
service_name = args.service_name[0]
cluster_name = args.cluster_name[0]
api_host = args.api_host[0]
api_user = args.api_user[0]
api_pass = args.api_pass[0]
api_port = args.api_port
api_version = args.api_version
auth = (api_user, api_pass)
... | code_fim | hard | {
"lang": "python",
"repo": "sebinjohn/replication_manager",
"path": "/src/replications/ds_replications.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> value = dict[key]
del dict[key]
return value
if __name__=='__main__':
root = Tk()
#Done with imageEmbedder 1.0 utility img2pytk.py from
# http://www.3dartist.com/WP/python/pycode.htm#img2pytk
img00 = PhotoImage(format='gif',data=
'R0lGODlhGAAYAOb/AAAAAP///4GBl3F... | code_fim | hard | {
"lang": "python",
"repo": "modal/tktoolbox",
"path": "/tktoolbox/examples/buttonbar.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: modal/tktoolbox path: /tktoolbox/examples/buttonbar.py
from tkinter import *
"""
ButtonBar widget
Rick Lawson
r_b_lawson at yahoo dot com
Easy widget to mimic the ButtonBar which is showing up a lot in Windows
Inspired by Iuri Wickert's notebook.py widget (esp. the Radiobutton tricks)
config opt... | code_fim | hard | {
"lang": "python",
"repo": "modal/tktoolbox",
"path": "/tktoolbox/examples/buttonbar.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # init the base class
Frame.__init__(self, master, options)
# load the images & create the buttons
self.buttons = []
index = 0
for image in self.images:
button = Radiobutton(self, indicatoron=0, text=self.labels[index], relief=FLAT, variable = s... | code_fim | hard | {
"lang": "python",
"repo": "modal/tktoolbox",
"path": "/tktoolbox/examples/buttonbar.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>##Comparing python built in method and mine
if a == b:
print("It's working !")
else:
print("It's not working...")<|fim_prefix|># repo: WithaK16/karatsubaMultiplication path: /karatsuba.py
import math
def getNumberOfDigit(n, base = 10):
if n > 0:
return int(math.log(n, base)) + 1
... | code_fim | hard | {
"lang": "python",
"repo": "WithaK16/karatsubaMultiplication",
"path": "/karatsuba.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WithaK16/karatsubaMultiplication path: /karatsuba.py
import math
def getNumberOfDigit(n, base = 10):
if n > 0:
return int(math.log(n, base)) + 1
elif n == 0:
return 1
else:
return int(math.log(-n, base)) + 1
## WARNING: works only with positive number and bas... | code_fim | hard | {
"lang": "python",
"repo": "WithaK16/karatsubaMultiplication",
"path": "/karatsuba.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hpgundam/django-bIo9 path: /bIo9/views.py
from django.shortcuts import render, redirect, get_object_or_404
from django.urls import reverse
from django.contrib import messages
from django.contrib.auth import login, logout, authenticate
from django.contrib.auth.decorators import login_required
from... | code_fim | hard | {
"lang": "python",
"repo": "hpgundam/django-bIo9",
"path": "/bIo9/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@login_required
def reset_password(request):
email = request.user.email
if email == '':
messages.error(request, "You don't have an email, Please set your email first.")
return redirect(reverse('bIo9:index'))
title = 'reset password'
if request.method == 'POST':
form = ResetPasswordForm(request.... | code_fim | hard | {
"lang": "python",
"repo": "hpgundam/django-bIo9",
"path": "/bIo9/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FRESH-TUNA/jockjebi-web path: /api/urls.py
from api.views import *
from rest_framework.routers import DefaultRouter
from django.urls import path
<|fim_suffix|>router.register(r'comment', CommentViewSet, basename='comment')
router.register(r'university', UniViewSet, basename='university')
url... | code_fim | medium | {
"lang": "python",
"repo": "FRESH-TUNA/jockjebi-web",
"path": "/api/urls.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>router.register(r'comment', CommentViewSet, basename='comment')
router.register(r'university', UniViewSet, basename='university')
urlpatterns += router.urls<|fim_prefix|># repo: FRESH-TUNA/jockjebi-web path: /api/urls.py
from api.views import *
from rest_framework.routers import DefaultRouter
from djan... | code_fim | easy | {
"lang": "python",
"repo": "FRESH-TUNA/jockjebi-web",
"path": "/api/urls.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Morningstar/GoASQ path: /src/goasq_server.py
# Copyright 2018 Morningstar Inc. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.... | code_fim | hard | {
"lang": "python",
"repo": "Morningstar/GoASQ",
"path": "/src/goasq_server.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> viewCounter = 0
for key in app.config['URL_RULES']:
if key == '/':
app.add_url_rule(key, view_func=ServerRequestHandler.as_view('GOASQ_'+str(viewCounter)), defaults={'pathParam': ''})
else:
app.add_url_rule(key, view_func=ServerRequestHandler.as_view('GOASQ_'+str(viewCounter)))
... | code_fim | hard | {
"lang": "python",
"repo": "Morningstar/GoASQ",
"path": "/src/goasq_server.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> p3dcollec = ax.plot_trisurf(coords[:, 0],
coords[:, 1],
coords[:, 2],
triangles = tri,
linewidth=0.,
antialiased = False)
if mask is not N... | code_fim | hard | {
"lang": "python",
"repo": "ohbm/handson-2021-reproducible-workflows",
"path": "/code/myvis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ohbm/handson-2021-reproducible-workflows path: /code/myvis.py
import numpy as np
import matplotlib.pyplot as plt
# surface mesh plotting based on coords & triangles only
def subplot_surf(coords,
tri,
bg_map,
fig,
limits,
... | code_fim | hard | {
"lang": "python",
"repo": "ohbm/handson-2021-reproducible-workflows",
"path": "/code/myvis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> coords = surf_mesh['coords']
tri = surf_mesh['tri']
if stat_map is None:
limits = [-70, 50]
if figsize is None:
figsize = (18,5)
if darkness is None:
darkness = 0.65
else :
limits = [-80, 50]
if darkness is None:
... | code_fim | hard | {
"lang": "python",
"repo": "ohbm/handson-2021-reproducible-workflows",
"path": "/code/myvis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> group[i] = curr_group
for nbr in graph[i]:
if not self.dfs(nbr, graph, -curr_group, groups):
return False
return True
# each node on an edge should belong to different group
# O(N + E) time, N to be number of nodes, E to be number of edges
# traverse eac... | code_fim | hard | {
"lang": "python",
"repo": "kevinshenyang07/Data-Structures-and-Algorithms",
"path": "/algorithms/dfs/is_graph_bipartite.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kevinshenyang07/Data-Structures-and-Algorithms path: /algorithms/dfs/is_graph_bipartite.py
# Is Graph Bipartite?
# Note:
# graph will have length in range [1, 100]
# graph[i] will contain integers in range [0, graph.length - 1]
# graph[i] will not contain i or duplicate values
# graph is undirect... | code_fim | hard | {
"lang": "python",
"repo": "kevinshenyang07/Data-Structures-and-Algorithms",
"path": "/algorithms/dfs/is_graph_bipartite.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> super().__init__(config)
self.config = config
if producer is not None:
self.producer = producer
else:
self.producer = Producer(self.config["PARAMS"])
self.time_encoder = self.config.get("TIME_ENCODER_CLASS", DateTimeEncoder)
self.dyna... | code_fim | hard | {
"lang": "python",
"repo": "alercebroker/APF",
"path": "/apf/metrics/kafka.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alercebroker/APF path: /apf/metrics/kafka.py
from apf.metrics import GenericMetricsProducer
from apf.metrics import DateTimeEncoder
from confluent_kafka import Producer
from apf.core import get_class
import json
class KafkaMetricsProducer(GenericMetricsProducer):
"""Write metrics in a Kafk... | code_fim | hard | {
"lang": "python",
"repo": "alercebroker/APF",
"path": "/apf/metrics/kafka.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sarvex/composer path: /composer/algorithms/cutout/__init__.py
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
<|fim_suffix|>See the :doc:`Method Card </method_cards/cutout>` for more details.
"""
from composer.algorithms.cutout.cutout import CutOut as CutOut
fro... | code_fim | medium | {
"lang": "python",
"repo": "sarvex/composer",
"path": "/composer/algorithms/cutout/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>from composer.algorithms.cutout.cutout import CutOut as CutOut
from composer.algorithms.cutout.cutout import cutout_batch as cutout_batch
__all__ = ['CutOut', 'cutout_batch']<|fim_prefix|># repo: sarvex/composer path: /composer/algorithms/cutout/__init__.py
# Copyright 2022 MosaicML Composer authors
# S... | code_fim | hard | {
"lang": "python",
"repo": "sarvex/composer",
"path": "/composer/algorithms/cutout/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>__version__ = "1.0.8"
__all__ = [
"assign",
"intersections",
"prorate",
"adjacencies",
"close_gaps",
"resolve_overlaps",
"snap_to_grid",
"IndexedGeometries",
"normalize",
"progress",
"make_valid",
"autorepair",
"doctor"
]<|fim_prefix|># repo: mggg/maup ... | code_fim | hard | {
"lang": "python",
"repo": "mggg/maup",
"path": "/maup/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mggg/maup path: /maup/__init__.py
from .adjacencies import adjacencies
from .assign import assign
from .indexed_geometries import IndexedGeometries
from .intersections import intersections, prorate
from .repair import close_gaps, resolve_overlaps, make_valid, autorepair, snap_to_grid, crop_to, ex... | code_fim | hard | {
"lang": "python",
"repo": "mggg/maup",
"path": "/maup/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.feature_extractor = feature_extractor
def __call__(self, batch):
encodings = self.feature_extractor([x[0] for x in batch], return_tensors='pt')
encodings['labels'] = torch.tensor([x[1] for x in batch], dtype=torch.long)
return encodings<|fim_prefix|># repo: ... | code_fim | easy | {
"lang": "python",
"repo": "qanastek/HugsVision",
"path": "/build/lib/hugsvision/dataio/ImageClassificationCollator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> encodings = self.feature_extractor([x[0] for x in batch], return_tensors='pt')
encodings['labels'] = torch.tensor([x[1] for x in batch], dtype=torch.long)
return encodings<|fim_prefix|># repo: qanastek/HugsVision path: /build/lib/hugsvision/dataio/ImageClassificationCollator.py
... | code_fim | medium | {
"lang": "python",
"repo": "qanastek/HugsVision",
"path": "/build/lib/hugsvision/dataio/ImageClassificationCollator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: qanastek/HugsVision path: /build/lib/hugsvision/dataio/ImageClassificationCollator.py
import torch
"""
📁 Image Classification Collator
"""
class ImageClassificationCollator:
<|fim_suffix|> def __call__(self, batch):
encodings = self.feature_extractor([x[0] for x in batch... | code_fim | medium | {
"lang": "python",
"repo": "qanastek/HugsVision",
"path": "/build/lib/hugsvision/dataio/ImageClassificationCollator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def didYouMean(q, encrypted=False, context=""):
q = str(str.lower(q)).strip()
if encrypted:
url = "https://encrypted.google.com/search?q=" + urllib.quote(q + " " + context)
else:
url = "https://www.google.com/search?q=" + urllib.quote(q + " " + context)
html = get... | code_fim | hard | {
"lang": "python",
"repo": "AndersonOyama/TCC",
"path": "/talvez lixo/didYouMean2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AndersonOyama/TCC path: /talvez lixo/didYouMean2.py
### Based in a Script from https://github.com/bkvirendra/didyoumean
# encoding: utf-8
# unicode("utf-8")
import os
import urllib2
import io
import gzip
import sys
import urllib
import re
from bs4 import BeautifulSoup
from StringIO i... | code_fim | hard | {
"lang": "python",
"repo": "AndersonOyama/TCC",
"path": "/talvez lixo/didYouMean2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> response = urllib2.urlopen(request)
if response.info().get('Content-Encoding') == 'gzip':
buf = StringIO( response.read())
f = gzip.GzipFile(fileobj=buf)
data = f.read()
else:
data = response.read()
return data
def didYouMean(q, encrypted=False, co... | code_fim | hard | {
"lang": "python",
"repo": "AndersonOyama/TCC",
"path": "/talvez lixo/didYouMean2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vulture990/NeuralNetworks path: /Activation.py
#it ll be more neat and organized to treat the activation function as a layer
from layer import Layer
import numpy as np
class Activation(layer):
def __init__(self, activation,activation_prime):
<|fim_suffix|> return np.multiply(output_g... | code_fim | hard | {
"lang": "python",
"repo": "vulture990/NeuralNetworks",
"path": "/Activation.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def forward(self,input):
self.input=input
return self.activation(self.input)
def backward(self,output_gradient,learning_rate):
return np.multiply(output_gradient,self.activation_prime(self.input))
##multiply by element<|fim_prefix|># repo: vulture990/NeuralNetworks ... | code_fim | medium | {
"lang": "python",
"repo": "vulture990/NeuralNetworks",
"path": "/Activation.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.contents is None:
await payload.respond(
type=InteractionType.UpdateMessage,
embed=self.embeds[self.page - 1],
components=(await self.create_button()),
)
else:
await payload.respond(
... | code_fim | hard | {
"lang": "python",
"repo": "popop098/ButtonPaginator",
"path": "/ButtonPaginator/paginator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: popop098/ButtonPaginator path: /ButtonPaginator/paginator.py
import discord
from discord import InvalidArgument
from discord.ext import commands
import asyncio
from typing import List, Optional, Union
from discord_components import (
Button,
ButtonStyle,
InteractionType,
)
from disc... | code_fim | hard | {
"lang": "python",
"repo": "popop098/ButtonPaginator",
"path": "/ButtonPaginator/paginator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sktime/sktime path: /sktime/networks/lstmfcn_layers.py
):
"""Apply `y . w + b` for every temporal slice y of x.
# Arguments
x: input tensor.
w: weight matrix.
b: optional bias vector.
dropout: wether to apply dropout (same dropout ... | code_fim | hard | {
"lang": "python",
"repo": "sktime/sktime",
"path": "/sktime/networks/lstmfcn_layers.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Return property recurrent_constraint."""
return self.cell.recurrent_constraint
@property
def bias_constraint(self):
"""Return property bias_constraint."""
return self.cell.bias_constraint
@property
def attention_constrain... | code_fim | hard | {
"lang": "python",
"repo": "sktime/sktime",
"path": "/sktime/networks/lstmfcn_layers.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if K.backend() == "cntk":
if not kwargs.get("unroll") and (dropout > 0 or recurrent_dropout > 0):
warnings.warn(
"RNN dropout is not supported with the CNTK backend "
"when using dynamic RNNs (i.e. non-unrolled... | code_fim | hard | {
"lang": "python",
"repo": "sktime/sktime",
"path": "/sktime/networks/lstmfcn_layers.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nim-lang/Nim path: /tools/debug/nim-gdb.py
+ "__" + m.group(3) + "_",
"NTI" + m.group(2).replace("colon", "58").lower() + "__" + m.group(3) + "_"
]
for l in lookups:
try:
return gdb.parse_and_eval(l)
except:
pass
None
def getNameFromNimRti(rti):
""... | code_fim | hard | {
"lang": "python",
"repo": "nim-lang/Nim",
"path": "/tools/debug/nim-gdb.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nim-lang/Nim path: /tools/debug/nim-gdb.py
def getNimName(typ):
if m := type_hash_regex.match(typ):
return m.group(2)
return f"unknown <{typ}>"
def getNimRti(type_name):
""" Return a ``gdb.Value`` object for the Nim Runtime Information of ``type_name``. """
# Get static const TNim... | code_fim | hard | {
"lang": "python",
"repo": "nim-lang/Nim",
"path": "/tools/debug/nim-gdb.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.new:
return self.val is not None
else:
return bool(self.val)
def __len__(self):
if not self:
return 0
if self.new:
if self.isContent:
return int(self.val["cap"])
else:
return int(self.val["len"])
else:
return self.val["Sup"... | code_fim | hard | {
"lang": "python",
"repo": "nim-lang/Nim",
"path": "/tools/debug/nim-gdb.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KratosMultiphysics/Kratos path: /applications/ShallowWaterApplication/tests/test_ShallowWaterApplication.py
# import Kratos
import KratosMultiphysics as KM
# Import Kratos "wrapper" for unittests
import KratosMultiphysics.KratosUnittest as KratosUnittest
from KratosMultiphysics.KratosUnittest im... | code_fim | hard | {
"lang": "python",
"repo": "KratosMultiphysics/Kratos",
"path": "/applications/ShallowWaterApplication/tests/test_ShallowWaterApplication.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Create a test suit with the validation tests plus all the nightly tests
validationSuite = suites['validation']
validationSuite.addTests(nightlySuite)
validationSuite.addTests(TestLoader().loadTestsFromTestCase(TestDamBreakValidation))
validationSuite.addTests(TestLoader().loadTestsFr... | code_fim | hard | {
"lang": "python",
"repo": "KratosMultiphysics/Kratos",
"path": "/applications/ShallowWaterApplication/tests/test_ShallowWaterApplication.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fcakyon/small-object-detection-benchmark path: /xview/slice_xview.py
import fire
from sahi.scripts.slice_coco import slice
from tqdm import tqdm
MAX_WORKERS = 20
SLICE_SIZE_LIST = [300, 400, 500]
OVERLAP_RATIO_LIST = [0, 0.25]
IGNORE_NEGATIVE_SAMPLES = True
<|fim_suffix|> total_run = len(SL... | code_fim | medium | {
"lang": "python",
"repo": "fcakyon/small-object-detection-benchmark",
"path": "/xview/slice_xview.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> total_run = len(SLICE_SIZE_LIST) * len(OVERLAP_RATIO_LIST)
current_run = 1
for slice_size in SLICE_SIZE_LIST:
for overlap_ratio in OVERLAP_RATIO_LIST:
tqdm.write(
f"{current_run} of {total_run}: slicing for slice_size={slice_size}, overlap_ratio={overlap_rat... | code_fim | medium | {
"lang": "python",
"repo": "fcakyon/small-object-detection-benchmark",
"path": "/xview/slice_xview.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for model in models:
admin.site.register(model)<|fim_prefix|># repo: sorinburghiu2323/Conffiliate path: /backend/admin.py
from django.contrib import admin
from backend.models import *
<|fim_middle|>models = [User, Platform, UserPlatform, Keyword, UserKeyword]
| code_fim | medium | {
"lang": "python",
"repo": "sorinburghiu2323/Conffiliate",
"path": "/backend/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sorinburghiu2323/Conffiliate path: /backend/admin.py
from django.contrib import admin
<|fim_suffix|>for model in models:
admin.site.register(model)<|fim_middle|>from backend.models import *
models = [User, Platform, UserPlatform, Keyword, UserKeyword]
| code_fim | medium | {
"lang": "python",
"repo": "sorinburghiu2323/Conffiliate",
"path": "/backend/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>s.system (copy_id_cmd)
ssh_cmd = 'ssh -o "StrictHostKeyChecking no" root@' + hostFqdn
print "Executing : ", ssh_cmd
# run ssh_cmd
setupPasswordlessSSH()<|fim_prefix|># repo: ziiin/glusterfs-extras path: /geo/configureGeo.py
import socket
import os
def setupPasswordlessSSH ():
''' sets u... | code_fim | medium | {
"lang": "python",
"repo": "ziiin/glusterfs-extras",
"path": "/geo/configureGeo.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ziiin/glusterfs-extras path: /geo/configureGeo.py
import socket
import os
def setupPasswordlessSSH ():
''' sets up passwordless SSH from root to root user of self IP '''
hostFqdn = socket.getfqdn()
# s<|fim_suffix|>s.system (copy_id_cmd)
ssh_cmd = 'ssh -o "StrictHostKeyChecking n... | code_fim | hard | {
"lang": "python",
"repo": "ziiin/glusterfs-extras",
"path": "/geo/configureGeo.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> actions = ["run_selected_jobs"]
def run_selected_jobs(self, request, queryset):
scheduler = BackgroundScheduler()
scheduler.add_jobstore(self._memory_jobstore)
scheduler.add_listener(self._handle_execution_event, events.EVENT_JOB_EXECUTED)
scheduler.start()
... | code_fim | hard | {
"lang": "python",
"repo": "jcass77/django-apscheduler",
"path": "/django_apscheduler/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jcass77/django-apscheduler path: /django_apscheduler/admin.py
import time
from datetime import timedelta
from apscheduler import events
from apscheduler.schedulers.background import BackgroundScheduler
from django.conf import settings
from django.contrib import admin, messages
from django.db.mod... | code_fim | hard | {
"lang": "python",
"repo": "jcass77/django-apscheduler",
"path": "/django_apscheduler/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>t.replace (u"ی", u"ي") #Arabic Yah = ي
return txt
if __name__ == '__main__':
test_unicode (u"ایست")<|fim_prefix|># repo: pythonprofilers/memory_profiler path: /test/test_unicode.py
# -*- coding: utf-8 -*-
@profile
def test_unicode(t<|fim_middle|>xt):
# test when unicode is present
txt = tx | code_fim | easy | {
"lang": "python",
"repo": "pythonprofilers/memory_profiler",
"path": "/test/test_unicode.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pythonprofilers/memory_profiler path: /test/test_unicode.py
# -*- coding: utf-8 -*-
@profile
def test_unicode(t<|fim_suffix|>t.replace (u"ی", u"ي") #Arabic Yah = ي
return txt
if __name__ == '__main__':
test_unicode (u"ایست")<|fim_middle|>xt):
# test when unicode is present
txt = tx | code_fim | easy | {
"lang": "python",
"repo": "pythonprofilers/memory_profiler",
"path": "/test/test_unicode.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_expected(cross):
rimg = rotate(cross, 90, order=0, pivot=[32, 32], missing=0)
assert np.allclose(rimg, cross.T)
rimg = rotate(cross, 45, order=1, pivot=[32, 32])
ones = np.array(np.nonzero(rimg == 1))
assert np.allclose(ones, [[30, 31, 31, 32, 33, 33, 34],
... | code_fim | medium | {
"lang": "python",
"repo": "SOFIA-USRA/sofia_redux",
"path": "/sofia_redux/toolkit/image/tests/test_adjust/test_rotate.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SOFIA-USRA/sofia_redux path: /sofia_redux/toolkit/image/tests/test_adjust/test_rotate.py
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
import pytest
from sofia_redux.toolkit.image.adjust import rotate
@pytest.fixture
def cross():
# squished crosshair
... | code_fim | hard | {
"lang": "python",
"repo": "SOFIA-USRA/sofia_redux",
"path": "/sofia_redux/toolkit/image/tests/test_adjust/test_rotate.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_nan_handling(single):
rimg1 = rotate(single, -45, order=1, missing_limit=0.5)
single[34, 34] = np.nan
rimg2 = rotate(single, -45, order=1, missing_limit=0.5)
assert np.allclose(rimg1, rimg2, equal_nan=True)
with pytest.raises(ValueError) as err:
rotate(single, -45, na... | code_fim | hard | {
"lang": "python",
"repo": "SOFIA-USRA/sofia_redux",
"path": "/sofia_redux/toolkit/image/tests/test_adjust/test_rotate.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Sudo-Kid/linklab_backend path: /user_profile/signals.py
from django.db.models.signals import post_save
from django.dispatch import receiver
<|fim_suffix|>
@receiver(post_save, sender=User)
def my_callback(instance, created, **_kwargs):
if not created:
return
template = models.Te... | code_fim | medium | {
"lang": "python",
"repo": "Sudo-Kid/linklab_backend",
"path": "/user_profile/signals.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> template = models.Template.objects.get(name='default')
user_profile = models.UserProfile(
user=instance,
template=template
)
user_profile.save()
social_display = models.SocialDisplaySettings(
name='twitch',
limit=6,
position=0,
username=u... | code_fim | medium | {
"lang": "python",
"repo": "Sudo-Kid/linklab_backend",
"path": "/user_profile/signals.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> bias0 = torch.randn(3)
meta_model[0].bias.data.copy_(bias0)
model[0].bias.data.copy_(bias0)
params = OrderedDict()
params['2.weight'] = torch.randn(5, 3)
model[2].weight.data.copy_(params['2.weight'])
params['2.bias'] = torch.randn(5)
model[2].bias.data.copy_(params['2.bi... | code_fim | hard | {
"lang": "python",
"repo": "egrefen/pytorch-meta",
"path": "/torchmeta/tests/modules/test_container.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: egrefen/pytorch-meta path: /torchmeta/tests/modules/test_container.py
import pytest
import numpy as np
import torch
import torch.nn as nn
from collections import OrderedDict
from torchmeta.modules import MetaSequential, MetaModule, MetaLinear
def test_metasequential():
meta_model = MetaSe... | code_fim | hard | {
"lang": "python",
"repo": "egrefen/pytorch-meta",
"path": "/torchmeta/tests/modules/test_container.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> inputs = torch.randn(5, 2)
outputs_torchmeta = meta_model(inputs, params=params)
outputs_nn = model(inputs)
np.testing.assert_equal(outputs_torchmeta.detach().numpy(),
outputs_nn.detach().numpy())<|fim_prefix|># repo: egrefen/pytorch-meta path: /torchmeta/tes... | code_fim | hard | {
"lang": "python",
"repo": "egrefen/pytorch-meta",
"path": "/torchmeta/tests/modules/test_container.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LeviNikhil/SebastianAldi-01082170015 path: /Week01-Intro/854A.py
# the one and only input
n = int(input())
if n % 2 == 1:
numerator = n//2
denominator = n - numerator
else:
numerato<|fim_suffix|>= 1
denominator = n - numerator
print(numerator, denominator)<|fim_middle|>r = (n//2) ... | code_fim | medium | {
"lang": "python",
"repo": "LeviNikhil/SebastianAldi-01082170015",
"path": "/Week01-Intro/854A.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>= 1
denominator = n - numerator
print(numerator, denominator)<|fim_prefix|># repo: LeviNikhil/SebastianAldi-01082170015 path: /Week01-Intro/854A.py
# the one and only input
n = int(input())
if n % 2 == 1:
numerator = n//2
denominator = n - numerator
else:
numerato<|fim_middle|>r = (n//2) ... | code_fim | medium | {
"lang": "python",
"repo": "LeviNikhil/SebastianAldi-01082170015",
"path": "/Week01-Intro/854A.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tlhhup/datadeal path: /mongo/person.py
from pymongo import MongoClient
client = MongoClient("mongodb://localhost:27017/")
db = client.test
class Person(object):
<|fim_suffix|> person = {
'name': '张三',
'age': 26
}
db.person.insert_one(person)
per... | code_fim | medium | {
"lang": "python",
"repo": "tlhhup/datadeal",
"path": "/mongo/person.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def find_persons(self):
persons = db.person.find()
if persons:
for person in persons:
print(person)
def insert(self):
person = {
'name': '张三',
'age': 26
}
db.person.insert_one(person)
person = Person()
p... | code_fim | easy | {
"lang": "python",
"repo": "tlhhup/datadeal",
"path": "/mongo/person.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>" value="201">
<input type="text" name="callback" value="eyJjYWxsYmFja1VybCI6IjQ3LjEwNi45MS4xODY6NTAwMC93c2dpIiwiY2FsbGJhY2tCb2R5IjoiJHtmaWxlbmFtZX0ifQ==">
<input type="text" name="filename" value="${filename}">
<input type="text" name="x:namea" value="hanli... | code_fim | hard | {
"lang": "python",
"repo": "yibozhang/aliyunproduct",
"path": "/oss/python_call.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ser = OptionParser()
parser.add_option("", "--bucket", dest="bucket", help="specify ")
parser.add_option("", "--endpoint", dest="endpoint", help="specify")
parser.add_option("", "--id", dest="id", help="access_key_id")
parser.add_option("", "--key", dest="key", help="access_key_secret")
... | code_fim | hard | {
"lang": "python",
"repo": "yibozhang/aliyunproduct",
"path": "/oss/python_call.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yibozhang/aliyunproduct path: /oss/python_call.py
#coding=utf8
import md5
import hashlib
import base64
import hmac
from optparse import OptionParser
#Content-Disposition:form-data;name="callback"
def convert_base64(input):
return base64.b64encode(input)
def get_sign_policy(key, policy):
... | code_fim | hard | {
"lang": "python",
"repo": "yibozhang/aliyunproduct",
"path": "/oss/python_call.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shapiromatron/hawc path: /hawc/apps/animal/migrations/0024_change_choices.py
# Generated by Django 1.11.15 on 2019-04-11 11:13
from django.db import migrations, models
def update_choices(apps, schema_editor):
apps.get_model("animal", "DosingRegime").objects.filter(negative_control="Y").upd... | code_fim | hard | {
"lang": "python",
"repo": "shapiromatron/hawc",
"path": "/hawc/apps/animal/migrations/0024_change_choices.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name="dosingregime",
name="negative_control",
field=models.CharField(
choices=[
("NR", "Not-reported"),
("UN", "Untreated"),
("VT", "Vehic... | code_fim | hard | {
"lang": "python",
"repo": "shapiromatron/hawc",
"path": "/hawc/apps/animal/migrations/0024_change_choices.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: inkImage/Conv-Autoencoder path: /model.py
import keras.backend as K
from keras.layers import Input, Conv2D, UpSampling2D, BatchNormalization, ZeroPadding2D, MaxPooling2D
from keras.models import Model
from keras.utils import plot_model
from custom_layers.unpooling_layer import Unpooling
def cr... | code_fim | hard | {
"lang": "python",
"repo": "inkImage/Conv-Autoencoder",
"path": "/model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> x = Conv2D(1, (5, 5), activation='sigmoid', padding='same', name='pred', kernel_initializer='he_normal',
bias_initializer='zeros')(x)
model = Model(inputs=input_tensor, outputs=x)
return model
if __name__ == '__main__':
model = create_model(224, 224, 3)
# input_layer ... | code_fim | hard | {
"lang": "python",
"repo": "inkImage/Conv-Autoencoder",
"path": "/model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: abondar24/MachineLearnPython path: /scipy/sc_mnist.py
import os
import struct
import numpy as np
import matplotlib.pyplot as plt
from sc_mnist_nnet import NeuralNetMLP
# load and unpack mnist ds before running
def load_mnist(path, kind='train'):
labels_path = os.path.join(path, '%s-labels.... | code_fim | hard | {
"lang": "python",
"repo": "abondar24/MachineLearnPython",
"path": "/scipy/sc_mnist.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>miscl_img = x_test[y_test != y_test_pred][:25]
correct_lab = y_test[y_test != y_test_pred][:25]
miscl_lab = y_test_pred[y_test != y_test_pred][:25]
fig, ax = plt.subplots(nrows=5, ncols=5, sharex=True, sharey=True)
ax = ax.flatten()
for i in range(25):
img = miscl_img[i].reshape(28, 28)
ax[i].ims... | code_fim | hard | {
"lang": "python",
"repo": "abondar24/MachineLearnPython",
"path": "/scipy/sc_mnist.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return c / 12.92
def _y_to_l(y: float) -> float:
if y <= _epsilon:
return y / _ref_y * _kappa
return 116 * ((y / _ref_y) ** (1 / 3)) - 16
def _l_to_y(l: float) -> float:
if l <= 8:
return _ref_y * l / _kappa
return _ref_y * (((l + 16) / 116) ** 3)
def xyz_to_rgb... | code_fim | hard | {
"lang": "python",
"repo": "has2k1/mizani",
"path": "/mizani/colors/hsluv.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: has2k1/mizani path: /mizani/colors/hsluv.py
""" This module is generated by transpiling Haxe into Python and cleaning
the resulting code by hand, e.g. removing unused Haxe classes. To try it
yourself, clone https://github.com/hsluv/hsluv and run:
haxe -cp haxe/src hsluv.Hsluv -python hsluv.p... | code_fim | hard | {
"lang": "python",
"repo": "has2k1/mizani",
"path": "/mizani/colors/hsluv.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if c > 0.04045:
return ((c + 0.055) / 1.055) ** 2.4
return c / 12.92
def _y_to_l(y: float) -> float:
if y <= _epsilon:
return y / _ref_y * _kappa
return 116 * ((y / _ref_y) ** (1 / 3)) - 16
def _l_to_y(l: float) -> float:
if l <= 8:
return _ref_y * l / _ka... | code_fim | hard | {
"lang": "python",
"repo": "has2k1/mizani",
"path": "/mizani/colors/hsluv.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> print bucketsDis
print bucketsCol
print ranges
p = [0]*len(ranges)
for m in range(len(ranges)):
if bucketsDis[m]>0:
p[m]=bucketsCol[m]/float(bucketsDis[m])
pylab.plot(ranges,p)
def testCollisionsE8(n,d=8):
M = pylab.eye(8,8)
S = [0.0]*n
C = [0]... | code_fim | hard | {
"lang": "python",
"repo": "olivierh59500/CardinalityShiftClustering",
"path": "/CardinalityShift/src/crKNN.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> S = [0.0]*n
C = [0]*n
#generate distances and buckets
for i in range(n):
p = [random() for j in xrange(d)]
q = [p[j] + (gauss(0,1)/(d**.5)) for j in xrange(d)]
S[i]=distance(p,q,d)
C[i]= int(decodeE8(dot(p,M)) == decodeE8(dot(q,M)))
ranges = pylab.h... | code_fim | hard | {
"lang": "python",
"repo": "olivierh59500/CardinalityShiftClustering",
"path": "/CardinalityShift/src/crKNN.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: olivierh59500/CardinalityShiftClustering path: /CardinalityShift/src/crKNN.py
'''
Copyright 2010 Lee Carraher. All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are
permitted provided that the following conditions are met:
1. Redistributio... | code_fim | hard | {
"lang": "python",
"repo": "olivierh59500/CardinalityShiftClustering",
"path": "/CardinalityShift/src/crKNN.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: a-shah8/LeetCode path: /Easy/isSymmetric.py
## Check if given Binary Tree is symmetric
## i.e. left subtree on one side should be same as,
## right subtree on other
## and vice versa
<|fim_suffix|> while q:
t1 = q.popleft()
t2 = q.popleft()
... | code_fim | hard | {
"lang": "python",
"repo": "a-shah8/LeetCode",
"path": "/Easy/isSymmetric.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return True
# # Using recursion
# return self.isMirror(root, root)
# def isMirror(self, t1: TreeNode, t2: TreeNode) -> bool:
# if t1==None and t2==None: return True
# if t1==None or t2==None: return False
# return (t1.val==t2.val) and self.isMi... | code_fim | medium | {
"lang": "python",
"repo": "a-shah8/LeetCode",
"path": "/Easy/isSymmetric.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # rewrite test count in mapreduced.yml
test_count = len([x for x in os.listdir('%s/cases/' % staging_dir) if x.endswith(".in")])
replace_with_str("%s/mapreduced.yml" % staging_dir, "[[ test_count ]]", str(test_count))
# rewrite module name in mapper.py
replace_with_str("%s/mapper.py" % staging_d... | code_fim | hard | {
"lang": "python",
"repo": "ilebedev/py_web_gui",
"path": "/make_assignment.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # copy solution
shutil.copy("%s/solution.py" % settings.assignment_path, solution_path + "/" + settings.assignment_type + ".py")
def create_staging_analyzer(settings):
# create staging area
staging_dir = ".analyzer_" + settings.assignment_type + ("_%s" % str(settings.assignment_num))
if os.path... | code_fim | hard | {
"lang": "python",
"repo": "ilebedev/py_web_gui",
"path": "/make_assignment.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.