text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: luwangg/kaptos path: /src/kaptos/resources/v1/transmissions.py
"""Detected transmissions, computed from station reception reports."""
import kaptos.schema as ks
import roax.schema as s
from .. import KaptosResource
from roax.resource import operation
_schema = s.dict(
description = "Detec... | code_fim | hard | {
"lang": "python",
"repo": "luwangg/kaptos",
"path": "/src/kaptos/resources/v1/transmissions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> super().__init__(name="transmissions")
# ---- create ------
@operation(
params = {"_body": _schema},
returns = s.dict({"id": _schema.properties["id"]})
)
def create(self, _body):
return super().create(_body)
# ----- read ------
@operation(
... | code_fim | medium | {
"lang": "python",
"repo": "luwangg/kaptos",
"path": "/src/kaptos/resources/v1/transmissions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: anadahalli/project-euler path: /p011.py
"""Problem 011
In the 20×20 grid below, four numbers along a diagonal line have been marked in
red.
08 02 22 97 38 15 00 40 00 75 04 05 07 78 52 12 50 77 91 08
49 49 99 40 17 81 18 57 60 87 17 40 98 43 69 48 04 56 62 00
81 49 31 73 55 79 14 29 93 71 40 67... | code_fim | hard | {
"lang": "python",
"repo": "anadahalli/project-euler",
"path": "/p011.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i in range(0, len(l), n):
yield l[i:i+n]
matrix = list(chunks(grid, 20))
ans = 0
for mat in [[row[i:i+4] for row in matrix[j:j+4]]
for j in range(0, 16) for i in range(0, 16)]:
horizontal = mat
vertical = [[mat[i][j] for i in range(0, 4)] for j in range(0, 4)]
di... | code_fim | hard | {
"lang": "python",
"repo": "anadahalli/project-euler",
"path": "/p011.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: francamacdowell/AnalyzeYou path: /youtube_api/main_app/serializer.py
from rest_framework import serializers
from .models import *
class ChannelDetailsSerializer(serializers.ModelSerializer):
def __init__(self, *args, **kwargs):
many = kwargs.pop('many', True)
super(ChannelDe... | code_fim | hard | {
"lang": "python",
"repo": "francamacdowell/AnalyzeYou",
"path": "/youtube_api/main_app/serializer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = VideoDetails
fields = ('id', 'title', 'description', 'tags')
class StatisticsDetailsSerializer(serializers.ModelSerializer):
def __init__(self, *args, **kwargs):
many = kwargs.pop('many', True)
super(StatisticsDetailsSerializer, self).__init__(many=many, *args... | code_fim | hard | {
"lang": "python",
"repo": "francamacdowell/AnalyzeYou",
"path": "/youtube_api/main_app/serializer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, *args, **kwargs):
many = kwargs.pop('many', True)
super(SetupSerializer, self).__init__(many=many, *args, **kwargs)
class Meta:
model = Setup
fields = ('id', 'link_video', 'user_token')<|fim_prefix|># repo: francamacdowell/AnalyzeYou path: /yout... | code_fim | medium | {
"lang": "python",
"repo": "francamacdowell/AnalyzeYou",
"path": "/youtube_api/main_app/serializer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> async def _get_orders_data_for_chain(self, chain, gram_markets):
async def get_size_of_smallest_arr(arrs_lst):
return min(map(lambda x: len(x), arrs_lst))
async def cut_off_extra_arrs_els(arrs_lst, required_nums_of_items):
arr = np.array([
*map(... | code_fim | hard | {
"lang": "python",
"repo": "mkbeh/rin-bitshares-arbitry-bot",
"path": "/src/core/bitsharesarbitrage.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return pairs_orders_data_arr
async def _get_precisions_arr(self, chain):
obj = await Asset().connect(ws_node=self.wallet_uri)
assets_arr = itertools.chain.from_iterable(
map(lambda x: x.split(':'), chain)
)
precisions_arr = np.array(range(4)... | code_fim | hard | {
"lang": "python",
"repo": "mkbeh/rin-bitshares-arbitry-bot",
"path": "/src/core/bitsharesarbitrage.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mkbeh/rin-bitshares-arbitry-bot path: /src/core/bitsharesarbitrage.py
# -*- coding: utf-8 -*-
import os
import re
import time
import logging
import itertools
import asyncio
import numpy as np
from datetime import datetime as dt
from aiohttp.client_exceptions import ClientConnectionError
from ... | code_fim | hard | {
"lang": "python",
"repo": "mkbeh/rin-bitshares-arbitry-bot",
"path": "/src/core/bitsharesarbitrage.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: halmga/pantext path: /pantext/quantifier.py
#!/usr/bin/env python
# coding: utf-8
# In[ ]:
from nltk.corpus import stopwords
from nltk import download
from re import sub
from nltk.tokenize import RegexpTokenizer, sent_tokenize, word_tokenize
from tqdm import tqdm
download('stopwords')
download... | code_fim | hard | {
"lang": "python",
"repo": "halmga/pantext",
"path": "/pantext/quantifier.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns
-------
count_list: list
Returns a list of regex counts per string in list
Examples
--------
>>> text = ["'Anselmo,' the old man said. 'I am called Anselmo and I come from Barco deAvila. Let me help you with that pack'"]
... | code_fim | hard | {
"lang": "python",
"repo": "halmga/pantext",
"path": "/pantext/quantifier.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #counts percentage of words in text that are stopwords
def stopword_percent(self, stop_words = 'english'):
"""
generate stopword percentage in each piece of text.
Parameters
----------
stop_words: str, default 'english'
see nltk.corpus.s... | code_fim | hard | {
"lang": "python",
"repo": "halmga/pantext",
"path": "/pantext/quantifier.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ikacper/Willos path: /backend/api/admin.py
from django.contrib import admin
<|fim_suffix|>@admin.register(Property)
class PropertyAdmin(admin.ModelAdmin):
list_display = (
"title",
"address",
"price",
"date",
"bedrooms",
"bathrooms",
"c... | code_fim | easy | {
"lang": "python",
"repo": "Ikacper/Willos",
"path": "/backend/api/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@admin.register(Property)
class PropertyAdmin(admin.ModelAdmin):
list_display = (
"title",
"address",
"price",
"date",
"bedrooms",
"bathrooms",
"cordinates",
)<|fim_prefix|># repo: Ikacper/Willos path: /backend/api/admin.py
from django.contr... | code_fim | easy | {
"lang": "python",
"repo": "Ikacper/Willos",
"path": "/backend/api/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bluemurder/mlfl path: /udacity course code/01-03-numpyarraymaximumquiz.py
"""Locate maximum value."""
import numpy as np
def get_max_index(a):
<|fim_suffix|> a = np.array([9, 6, 2, 3, 12, 14, 7, 10], dtype=np.int32) # 32-bit integer array
print "Array:", a
# Find the maximum a... | code_fim | medium | {
"lang": "python",
"repo": "bluemurder/mlfl",
"path": "/udacity course code/01-03-numpyarraymaximumquiz.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_run():
a = np.array([9, 6, 2, 3, 12, 14, 7, 10], dtype=np.int32) # 32-bit integer array
print "Array:", a
# Find the maximum and its index in array
print "Maximum value:", a.max()
print "Index of max.:", get_max_index(a)
if __name__ == "__main__":
test_run()<|fim_... | code_fim | medium | {
"lang": "python",
"repo": "bluemurder/mlfl",
"path": "/udacity course code/01-03-numpyarraymaximumquiz.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: imackerracher/NewsSimilarity path: /newssimilarity/utils/ml_utils.py
from sklearn import metrics
def evaluate(model, X, y):
prediction = model.predict(X)
acc = metrics.accuracy_score(y, prediction)
print("Accuracy:", acc)
return prediction
def extract_labels_single_format(... | code_fim | medium | {
"lang": "python",
"repo": "imackerracher/NewsSimilarity",
"path": "/newssimilarity/utils/ml_utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
[0,1,1,1,0,0...] instead of [[1,0], [1,0], [0,1]...]
:param featureset:
:return:
"""
def extract(label): return 1 if label == [1,0] else 0
y = lambda label: extract(label), featureset['Labels']
return y<|fim_prefix|># repo: imackerracher/NewsSimilarity path: /newssimil... | code_fim | medium | {
"lang": "python",
"repo": "imackerracher/NewsSimilarity",
"path": "/newssimilarity/utils/ml_utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AbuBakkar32/pythoncode-tutorials path: /ethical-hacking/subdomain-scanner/subdomain_scanner.py
import requests
# the domain to scan for subdomains
domain = "google.com"
<|fim_suffix|>for subdomain in subdomains:
# construct the url
url = f"http://{subdomain}.{domain}"
try:
#... | code_fim | medium | {
"lang": "python",
"repo": "AbuBakkar32/pythoncode-tutorials",
"path": "/ethical-hacking/subdomain-scanner/subdomain_scanner.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for subdomain in subdomains:
# construct the url
url = f"http://{subdomain}.{domain}"
try:
# if this raises an ERROR, that means the subdomain does not exist
requests.get(url)
except requests.ConnectionError:
# if the subdomain does not exist, just pass, print nothi... | code_fim | medium | {
"lang": "python",
"repo": "AbuBakkar32/pythoncode-tutorials",
"path": "/ethical-hacking/subdomain-scanner/subdomain_scanner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: k2sebeom/pyplayscii path: /examples/bounce.py
from playscii import GameObject, GameManager
from playscii.input import Input
BALL = " ** \n" \
" ****\n" \
" **"
class Ball(GameObject):
def __init__(self):
super().__init__(pos=(40, 10), render=BALL)
... | code_fim | medium | {
"lang": "python",
"repo": "k2sebeom/pyplayscii",
"path": "/examples/bounce.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self):
super().__init__((80, 20))
self.ball = Ball()
self.set_title("Press q to quit")
def setup(self):
self.add_object(self.ball)
def update(self):
if self.ball.x < 0 or self.ball.x > 74:
self.ball.vel = (-self.ball.vel[0], se... | code_fim | medium | {
"lang": "python",
"repo": "k2sebeom/pyplayscii",
"path": "/examples/bounce.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: heyyybingo/sparsifying_regularizers_for_RRNNs path: /language_model/train_lm.py
elf).__init__()
word2id, id2word = {}, {}
if sos not in word2id:
word2id[sos] = len(word2id)
id2word[word2id[sos]] = sos
for w in words:
if w not in word2id:... | code_fim | hard | {
"lang": "python",
"repo": "heyyybingo/sparsifying_regularizers_for_RRNNs",
"path": "/language_model/train_lm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
else:
unchanged += 1
if args.lr_decay_epoch > 0 and epoch >= args.lr_decay_epoch:
args.lr *= args.lr_decay
if unchanged >= args.patience:
print_and_log("Reached " + str(args.patience)
+ " iterations w... | code_fim | hard | {
"lang": "python",
"repo": "heyyybingo/sparsifying_regularizers_for_RRNNs",
"path": "/language_model/train_lm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: heyyybingo/sparsifying_regularizers_for_RRNNs path: /language_model/train_lm.py
ing == "max_plus":
self.semiring = MaxPlusSemiring
else:
assert False, "Semiring should either be plus_times or max_plus, not {}".format(args.semiring)
self.enco... | code_fim | hard | {
"lang": "python",
"repo": "heyyybingo/sparsifying_regularizers_for_RRNNs",
"path": "/language_model/train_lm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ricorx7/QRevPy path: /Classes/BoatData.py
self.v_processed_mps = np.copy(self.v_mps)
self.u_processed_mps[self.valid_data[0, :] == False] = np.nan
self.v_processed_mps[self.valid_data[0, :] == False] = np.nan
n_invalid = 0
# Process data by ensembles
for... | code_fim | hard | {
"lang": "python",
"repo": "ricorx7/QRevPy",
"path": "/Classes/BoatData.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ricorx7/QRevPy path: /Classes/BoatData.py
o_coord_sys == 'Beam':
# Determine frequency index for transformation matrix
if len(t_matrix.shape) > 2:
idx_freq = np.where(t_matrix_freq == self.frequency_khz[ii])
... | code_fim | hard | {
"lang": "python",
"repo": "ricorx7/QRevPy",
"path": "/Classes/BoatData.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Compute speed and direction of boat
direct, speed = cart2pol(b_vele, b_veln)
# Compute residuals from a robust Loess smooth
speed_smooth = rloess(ens_time, speed, filter_width)
speed_res = speed - speed_smooth
# Apply a trimmed st... | code_fim | hard | {
"lang": "python",
"repo": "ricorx7/QRevPy",
"path": "/Classes/BoatData.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> @commands.command()
async def getmyreminders(self, ctx):
reminders = Database.getReminders(ctx.author.id)
if len(reminders) > 1:
embed = discord.Embed(title=f"{ctx.author.name} reminders")
for reminder in reminders:
embed.add_field(name=remin... | code_fim | hard | {
"lang": "python",
"repo": "matttattoli/exceed-discord-bot",
"path": "/cogs/Reminders.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: matttattoli/exceed-discord-bot path: /cogs/Reminders.py
import discord
from discord.ext import commands
from cogs.utils.checks import *
from cogs.utils.GlobalVars import *
from cogs.utils.debug import *
from cogs.utils.Database import Database
import datetime
import asyncio
class RemindParser:
... | code_fim | hard | {
"lang": "python",
"repo": "matttattoli/exceed-discord-bot",
"path": "/cogs/Reminders.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, bot):
self.bot = bot
@commands.command()
async def remindme(self, ctx, *, msg: str):
data = RemindParser.parseReminderMsg(msg)
if data is None:
return await ctx.send("Error parsing your reminder")
Database.createReminder(ctx.autho... | code_fim | hard | {
"lang": "python",
"repo": "matttattoli/exceed-discord-bot",
"path": "/cogs/Reminders.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chapman-cpsc-230/hw2-agust105 path: /sum_powers.py
"""
File: sum_power.py
Copyright (c) 2016 Francis Agustin
License: MIT
<|fim_suffix|>"""
user_input = raw_input ("Enter value for b: ")
b = float (user_input)
while b == 1:
user_input = raw_input ("Value cannot be 1. Enter value for b: "... | code_fim | hard | {
"lang": "python",
"repo": "chapman-cpsc-230/hw2-agust105",
"path": "/sum_powers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>user_input = raw_input ("Enter value for b: ")
b = float (user_input)
while b == 1:
user_input = raw_input ("Value cannot be 1. Enter value for b: ")
b = float (user_input)
user_input2 = raw_input ("Enter value for n: ")
n = int (user_input2)
i = 0.0
sum_power = 0
while i <= n:
sum_power +=... | code_fim | hard | {
"lang": "python",
"repo": "chapman-cpsc-230/hw2-agust105",
"path": "/sum_powers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>while b == 1:
user_input = raw_input ("Value cannot be 1. Enter value for b: ")
b = float (user_input)
user_input2 = raw_input ("Enter value for n: ")
n = int (user_input2)
i = 0.0
sum_power = 0
while i <= n:
sum_power += b**i
i += 1
print sum_power
eq = ((b**(n+1)) - 1)/(b-1)
print e... | code_fim | medium | {
"lang": "python",
"repo": "chapman-cpsc-230/hw2-agust105",
"path": "/sum_powers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WxOutside/software path: /telemetry/functions.py
#!/usr/bin/env python
import subprocess
import json
import os
import smtplib
import time
from config import couchdb_baseurl, wxoutside_email_server, wxoutside_email_port
from environment_config import wxoutside_sensor_email, wxoutside_sensor_pass... | code_fim | hard | {
"lang": "python",
"repo": "WxOutside/software",
"path": "/telemetry/functions.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> except:
pass
doc_name=host_name + '_last_record'
output=run_proc('GET', base_url + '/telemetry/' + doc_name)
last_record_json_items={}
try:
if output['_rev']:
last_record_json_items=output
#print ("We need to update re... | code_fim | hard | {
"lang": "python",
"repo": "WxOutside/software",
"path": "/telemetry/functions.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>for thisLayer in thisFont.selectedLayers:
# create a temporary copy of the current layer
originalLayer = thisLayer.copy()
# reinterpolate the layer
thisLayer.reinterpolate()
# put back paths and components as of before reinterpolating the layer
try: # Glyphs 3
thisLayer.shapes = originalLayer.shap... | code_fim | medium | {
"lang": "python",
"repo": "harbortype/glyphs-scripts",
"path": "/Anchors/Re-interpolate Anchors.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: harbortype/glyphs-scripts path: /Anchors/Re-interpolate Anchors.py
#MenuTitle: Re-interpolate Anchors
# -*- coding: utf-8 -*-
from __future__ import division, print_function, unicode_literals
__doc__="""
Re-interpolates only the anchors on selected layers.
"""
<|fim_suffix|>for thisLayer in this... | code_fim | medium | {
"lang": "python",
"repo": "harbortype/glyphs-scripts",
"path": "/Anchors/Re-interpolate Anchors.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: arthurtucker/Clue-Less path: /clueless/server/app.py
from flask import Flask
from flask.ext import restful
from clueless import log
from clueless.server.api import resources
_LOG = log.get_logger(__name__)
<|fim_suffix|> _LOG.info('Clueless server starting..')
app = Flask(__name__)
... | code_fim | medium | {
"lang": "python",
"repo": "arthurtucker/Clue-Less",
"path": "/clueless/server/app.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def start_server():
_LOG.info('Clueless server starting..')
app = Flask(__name__)
api = restful.Api(app)
api.add_resource(resources.PlayersResource, '/players')
api.add_resource(resources.PlayerResource, '/players/<string:username>')
api.add_resource(resources.GamesResource, '/... | code_fim | medium | {
"lang": "python",
"repo": "arthurtucker/Clue-Less",
"path": "/clueless/server/app.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> _LOG.info('Clueless server starting..')
app = Flask(__name__)
api = restful.Api(app)
api.add_resource(resources.PlayersResource, '/players')
api.add_resource(resources.PlayerResource, '/players/<string:username>')
api.add_resource(resources.GamesResource, '/games')
api.add_re... | code_fim | medium | {
"lang": "python",
"repo": "arthurtucker/Clue-Less",
"path": "/clueless/server/app.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FNNDSC/pl-gepush path: /gepush/Agent17Upload.py
'''
/*
* Copyright 2010-2016 Amazon.com, Inc. or its affiliates. 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.
* A copy of the License... | code_fim | hard | {
"lang": "python",
"repo": "FNNDSC/pl-gepush",
"path": "/gepush/Agent17Upload.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>terminate_flag = False
device_config = {}
with open(config_file, 'r') as f:
device_config = json.load(f)
logger.debug( "device_config is %s ", json.dumps(device_config))
host = device_config['endpoint']
rootCAPath = device_config['rootCertificate']
certificatePath = device_config['deviceCertificate']... | code_fim | hard | {
"lang": "python",
"repo": "FNNDSC/pl-gepush",
"path": "/gepush/Agent17Upload.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FanGeGo/motifwalk path: /research/src/mane/motif.py
"""Motif object to use with Graph
"""
# Coding: utf-8
# Filename: motif.py
# Created: 2016-07-16
# Description:
## v0.0: File created
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
... | code_fim | medium | {
"lang": "python",
"repo": "FanGeGo/motifwalk",
"path": "/research/src/mane/motif.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># >>> BEGIN DEFAULT MOTIF(s) <<<
default_directed = Motif(directed=True)
# TODO: Implement walk engine here
default_undirected = Motif(directed=False)
# TODO: Implement walk engine here
# >>> END DEFAULT MOTIF(s) <<<<|fim_prefix|># repo: FanGeGo/motifwalk path: /research/src/mane/motif.py
"""Motif object... | code_fim | medium | {
"lang": "python",
"repo": "FanGeGo/motifwalk",
"path": "/research/src/mane/motif.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vontell/dynabench path: /api/migrations/20210521_01_xxxx-open_flores.py
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Hide Flores task until June 4th, 2021.
"""
fr... | code_fim | medium | {
"lang": "python",
"repo": "vontell/dynabench",
"path": "/api/migrations/20210521_01_xxxx-open_flores.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>step(
f"""
UPDATE tasks SET hidden = true, submitable = true
WHERE task_code in {tasks}
""",
f"""
UPDATE tasks SET hidden = false, submitable = false
WHERE task_code in {tasks}
""",
)<|fim_prefix|># repo: vontell/dynabench path: /api/migrations/20210521_01_xxxx-open_flores... | code_fim | medium | {
"lang": "python",
"repo": "vontell/dynabench",
"path": "/api/migrations/20210521_01_xxxx-open_flores.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: IamMayankThakur/test-bigdata path: /adminmgr/media/code/A3/task3/BD_85_130_185_279_S3RkVts.py
import findspark
findspark.init()
from pyspark import SparkConf,SparkContext
from pyspark.streaming import StreamingContext
from pyspark.sql import Row,SQLContext
import sys
import requests
conf=SparkC... | code_fim | medium | {
"lang": "python",
"repo": "IamMayankThakur/test-bigdata",
"path": "/adminmgr/media/code/A3/task3/BD_85_130_185_279_S3RkVts.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>dataStream=ssc.socketTextStream("localhost",9009)
dataStream.pprint()
words = dataStream.flatMap(lambda line: line.split(";")[7].split(","))
pairs = words.map(lambda word: (word, 1))
windowedWordCounts = pairs.reduceByKeyAndWindow(lambda x, y: x + y, int(sys.argv[1]), 1)
windowedWordCounts.pprint()
ssc.s... | code_fim | medium | {
"lang": "python",
"repo": "IamMayankThakur/test-bigdata",
"path": "/adminmgr/media/code/A3/task3/BD_85_130_185_279_S3RkVts.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cstlee/RooBench path: /scripts/roobench_config.py
#!/usr/bin/env python
# Copyright (c) 2020, Stanford University
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this perm... | code_fim | hard | {
"lang": "python",
"repo": "cstlee/RooBench",
"path": "/scripts/roobench_config.py",
"mode": "psm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main(args):
if args["bench"]:
with open(args["<server_list>"]) as f:
server_list = json.load(f)
with open(args["<workload>"]) as f:
workload = json.load(f)
config = {}
node_count = len(server_list['servers'])
if args['--nodes'] > 0:
... | code_fim | hard | {
"lang": "python",
"repo": "cstlee/RooBench",
"path": "/scripts/roobench_config.py",
"mode": "spm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: robot-ai-machinelearning/to_share_or_not_to_share path: /main.py
import os
from argparse import ArgumentParser
import torch
from torch.utils.data.dataset import Subset
from torchvision import datasets
from models.graph_comps import GraphComp
from models.graph_sampler import GraphSampler
from tr... | code_fim | hard | {
"lang": "python",
"repo": "robot-ai-machinelearning/to_share_or_not_to_share",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # load the architecture dataset
dataset_path = "./datasets/sp_{}.pkl".format(search_space)
# folder where results are saved
model_dir = get_output_folder(os.path.join("./results", exp_params["output_dir"]), search_space)
# If training, skipped if only evaluating
if not args.eval_... | code_fim | hard | {
"lang": "python",
"repo": "robot-ai-machinelearning/to_share_or_not_to_share",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # creating the super-net
model = GraphComp(**exp_params)
print("Number of trainable parameters: {}".format(
sum([p.numel() for p in model.parameters()])))
if args.snapshot_path is not None:
model.load_state_dict(torch.load(args.snapshot_path, map_location=exp_params["device... | code_fim | hard | {
"lang": "python",
"repo": "robot-ai-machinelearning/to_share_or_not_to_share",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
:type S: str
:rtype: bool
"""
sign = "abc"
while S:
if len(S) < 3:
return False
current = ""
index = 0
flag = False
while index < len(S):
if index < len(S) - 2:
... | code_fim | hard | {
"lang": "python",
"repo": "windard/leeeeee",
"path": "/1003.check-if-word-is-valid-after-substitutions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: windard/leeeeee path: /1003.check-if-word-is-valid-after-substitutions.py
# coding=utf-8
#
# @lc app=leetcode id=1003 lang=python
#
# [1003] Check If Word Is Valid After Substitutions
#
# https://leetcode.com/problems/check-if-word-is-valid-after-substitutions/description/
#
# algorithms
# Medium... | code_fim | hard | {
"lang": "python",
"repo": "windard/leeeeee",
"path": "/1003.check-if-word-is-valid-after-substitutions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @transition(field='status', source=['prepayment_deposited', 'no_payment_required'],
custom=dict(auto=True))
def acknowledge_prepayment(self):
"""
Acknowledge the payment. This method is invoked automatically.
"""
self.acknowledge_payment()
@tran... | code_fim | hard | {
"lang": "python",
"repo": "shivamraj74/django-shop",
"path": "/shop/payment/workflows.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shivamraj74/django-shop path: /shop/payment/workflows.py
from django.core.exceptions import ImproperlyConfigured
from django.utils.translation import gettext_lazy as _
from django_fsm import transition, RETURN_VALUE
from shop.models.order import BaseOrder
class ManualPaymentWorkflowMixin:
... | code_fim | hard | {
"lang": "python",
"repo": "shivamraj74/django-shop",
"path": "/shop/payment/workflows.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def cancelable(self):
return super().cancelable() or self.status in self.CANCELABLE_SOURCES
@transition(field='status', target=RETURN_VALUE(*TRANSITION_TARGETS.keys()),
conditions=[cancelable], custom=dict(admin=True, button_name=_("Cancel Order")))
def cancel_order(se... | code_fim | hard | {
"lang": "python",
"repo": "shivamraj74/django-shop",
"path": "/shop/payment/workflows.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self._extract_uplynk_info(url)
class UplynkPreplayIE(UplynkIE):
IE_NAME = 'uplynk:preplay'
_VALID_URL = r'https?://.*?\.uplynk\.com/preplay2?/(?P<path>ext/[0-9a-f]{32}/(?P<external_id>[^/?&]+)|(?P<id>[0-9a-f]{32}))\.json'
_TEST = None
def _real_extract(self, url):
... | code_fim | medium | {
"lang": "python",
"repo": "firsttris/plugin.video.sendtokodi",
"path": "/lib/youtube_dl/extractor/uplynk.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: firsttris/plugin.video.sendtokodi path: /lib/youtube_dl/extractor/uplynk.py
# coding: utf-8
from __future__ import unicode_literals
import re
from .common import InfoExtractor
from ..utils import (
float_or_none,
ExtractorError,
)
class UplynkIE(InfoExtractor):
IE_NAME = 'uplynk'
... | code_fim | hard | {
"lang": "python",
"repo": "firsttris/plugin.video.sendtokodi",
"path": "/lib/youtube_dl/extractor/uplynk.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class UplynkPreplayIE(UplynkIE):
IE_NAME = 'uplynk:preplay'
_VALID_URL = r'https?://.*?\.uplynk\.com/preplay2?/(?P<path>ext/[0-9a-f]{32}/(?P<external_id>[^/?&]+)|(?P<id>[0-9a-f]{32}))\.json'
_TEST = None
def _real_extract(self, url):
path, external_id, video_id = re.match(self._VA... | code_fim | hard | {
"lang": "python",
"repo": "firsttris/plugin.video.sendtokodi",
"path": "/lib/youtube_dl/extractor/uplynk.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @asyncached
def rendered_contents(self):
return 'Hello World' # TODO<|fim_prefix|># repo: encukou/galerka path: /galerka/views/index.py
from galerka import views
from galerka.view import GalerkaView
from galerka.util import asyncached
<|fim_middle|>class TitlePage(GalerkaView):
vie... | code_fim | medium | {
"lang": "python",
"repo": "encukou/galerka",
"path": "/galerka/views/index.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: encukou/galerka path: /galerka/views/index.py
from galerka import views
from galerka.view import GalerkaView
from galerka.util import asyncached
<|fim_suffix|> view_packages = [views]
@asyncached
def title(self):
return self.request.environ['galerka.site-title']
@asynca... | code_fim | easy | {
"lang": "python",
"repo": "encukou/galerka",
"path": "/galerka/views/index.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># remove default help command
client.remove_command("help")
# connect all cogs
for cog in os.listdir("./cogs"):
if cog.endswith(".py"):
try:
cog = f"cogs.{cog.replace('.py', '')}"
client.load_extension(cog)
except Exception as e:
print(f"{cog} can n... | code_fim | medium | {
"lang": "python",
"repo": "denizumuteser/Artificial_Stupidity",
"path": "/bot.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: denizumuteser/Artificial_Stupidity path: /bot.py
import discord, asyncio, time, os, random, platform
from discord.ext import tasks, commands
import config
intents = discord.Intents.all()
<|fim_suffix|># connect all cogs
for cog in os.listdir("./cogs"):
if cog.endswith(".py"):
try:
... | code_fim | hard | {
"lang": "python",
"repo": "denizumuteser/Artificial_Stupidity",
"path": "/bot.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mitre-cyber-academy/2013-crypto-300 path: /src/decrypt.py
import random
import argparse
def main():
parser = argparse.ArgumentParser(
description='Decrypt a file using a key.')
parser.add_argument('seed', help='The seed of the PRNG', type=int)
parser.add_argument('cryptFile', help='The file... | code_fim | medium | {
"lang": "python",
"repo": "mitre-cyber-academy/2013-crypto-300",
"path": "/src/decrypt.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> while True:
currByte = args.cryptFile.read(1)
if(currByte == ''):
break
byteVal = ord(currByte)
randVal = random.getrandbits(8)
outFile.write(chr(byteVal ^ randVal))
outFile.close()
args.cryptFile.close()
if __name__ == '__main__':
main()<|fim_prefix|># repo: mitre-cyber-academy/2013-cry... | code_fim | medium | {
"lang": "python",
"repo": "mitre-cyber-academy/2013-crypto-300",
"path": "/src/decrypt.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zhuyifan1993/learning_3d_shape_under_self-supervison path: /utils/dataset.py
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:Yifan Zhu
# datetime:2020/10/1 23:52
# file: dataset.py
# software: PyCharm
import glob
import logging
import os
import h5py
import torch
import yaml
from torch.util... | code_fim | hard | {
"lang": "python",
"repo": "zhuyifan1993/learning_3d_shape_under_self-supervison",
"path": "/utils/dataset.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.root_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', self.dataset_folder, split)
self.dirList = sorted(glob.glob(self.root_dir + '/*/{}/*'.format(category)), key=os.path.getmtime)
def __len__(self):
return len(self.dirList)
def __getitem__(self,... | code_fim | hard | {
"lang": "python",
"repo": "zhuyifan1993/learning_3d_shape_under_self-supervison",
"path": "/utils/dataset.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return data
def get_model_dict(self, idx):
return self.shapes[idx]
class KITTI360Dataset(data.Dataset):
def __init__(self, dataset_folder, split, category, points_batch=200, evaluation=False):
self.dataset_folder = dataset_folder
self.split = split
self.c... | code_fim | hard | {
"lang": "python",
"repo": "zhuyifan1993/learning_3d_shape_under_self-supervison",
"path": "/utils/dataset.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
plot cars as red points, events as blue points,
and lines connecting cars to their targets
:param carDict:
:param eventDict:
:return: image for gif
"""
fig, ax = plt.subplots()
ax.set_title('time: {0}'.format(s.time))
for c in range(nc):
... | code_fim | hard | {
"lang": "python",
"repo": "ChanaRoss/Thesis",
"path": "/Simulation/Anticipitory/PlotResultsFromSimulationMIO_V1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for pickleName in pickleNames:
lg = pickle.load(open('/home/chana/Documents/Thesis/FromGitFiles/Simulation/Anticipitory/PickleFiles/' + pickleName + '.p', 'rb'))
simTime = 20
if 'Hungarian' in pickleName:
events = lg['events']
gridSize = lg['gs']
... | code_fim | hard | {
"lang": "python",
"repo": "ChanaRoss/Thesis",
"path": "/Simulation/Anticipitory/PlotResultsFromSimulationMIO_V1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ChanaRoss/Thesis path: /Simulation/Anticipitory/PlotResultsFromSimulationMIO_V1.py
import numpy as np
import pickle
from matplotlib import pyplot as plt
import pandas as pd
import seaborn as sns
from ipywidgets import interact
import imageio
# import my file in order to load state class from pick... | code_fim | hard | {
"lang": "python",
"repo": "ChanaRoss/Thesis",
"path": "/Simulation/Anticipitory/PlotResultsFromSimulationMIO_V1.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> filepath = os.path.join(month_dir, monthstr+".tsv")
if os.path.isfile(filepath):
result_json["temperatures"] = []
with open(filepath, "r") as f:
for line in f:
if not line.strip(): continue #ignore empty line
datestr, min_temp, max_temp =... | code_fim | hard | {
"lang": "python",
"repo": "nixeneko/temperature_website",
"path": "/public/api/get_month_temps",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> firstday = datetime.date(date.year, date.month, 1)
lastmonth = firstday + datetime.timedelta(days=-1)
lastmonth_firstday = datetime.date(lastmonth.year, lastmonth.month, 1)
return lastmonth_firstday
def get_json():
result_json = {}
form = cgi.FieldStorage()
monthstr = datetim... | code_fim | hard | {
"lang": "python",
"repo": "nixeneko/temperature_website",
"path": "/public/api/get_month_temps",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nixeneko/temperature_website path: /public/api/get_month_temps
#!/usr/bin/env python3
#coding: utf-8
import sys, json, datetime, os
import re
import cgi
import cgitb #for debug
#cgitb.enable() #for debug
from settings.settings import TEMP_LOG_DIR
#TEMP_LOG_DIR = "/home/pi/temperature/temp_log"
... | code_fim | hard | {
"lang": "python",
"repo": "nixeneko/temperature_website",
"path": "/public/api/get_month_temps",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kenrumer/scorekeeper path: /golf/migrations/0069_playerplugin_priority.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.5 on 2017-12-01 20:09
from __future__ import unicode_literals
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
('golf', '0068_auto_20171... | code_fim | medium | {
"lang": "python",
"repo": "kenrumer/scorekeeper",
"path": "/golf/migrations/0069_playerplugin_priority.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='playerplugin',
name='priority',
field=models.IntegerField(default=-1, help_text='Highest priority will be listed first in selecting format', verbose_name='Priority'),
),
]<|fim_prefix|># repo: kenru... | code_fim | medium | {
"lang": "python",
"repo": "kenrumer/scorekeeper",
"path": "/golf/migrations/0069_playerplugin_priority.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: perfsonar/pscheduler path: /python-pscheduler/pscheduler/tests/psselect_test.py
#!/usr/bin/env python3
"""
test for the select module.
"""
import unittest
from base_test import PschedTestBase
from pscheduler.psselect import *
class TestPsselect(PschedTestBase):
<|fim_suffix|> self.asse... | code_fim | medium | {
"lang": "python",
"repo": "perfsonar/pscheduler",
"path": "/python-pscheduler/pscheduler/tests/psselect_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_except(self):
self.assertEqual(
polled_select([], [], [999], 2.0),
([], [], [999])
)
if __name__ == '__main__':
unittest.main()<|fim_prefix|># repo: perfsonar/pscheduler path: /python-pscheduler/pscheduler/tests/psselect_test.py
#!/usr/bin/env py... | code_fim | hard | {
"lang": "python",
"repo": "perfsonar/pscheduler",
"path": "/python-pscheduler/pscheduler/tests/psselect_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yukinarit/pyserde path: /serde/se.py
g["serde_custom_class_serializer"] = functools.partial(
serde_custom_class_serializer, custom=serializer
)
# Collect types used in the generated code.
for typ in iter_types(cls):
# When we encou... | code_fim | hard | {
"lang": "python",
"repo": "yukinarit/pyserde",
"path": "/serde/se.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yukinarit/pyserde path: /serde/se.py
r):
if f.skip_if:
g[f.skip_if.name] = f.skip_if
if f.serializer:
g[f.serializer.name] = f.serializer
add_func(
scope, TO_ITER, render_to_tuple(cls, serializer, type_check, serialize_c... | code_fim | hard | {
"lang": "python",
"repo": "yukinarit/pyserde",
"path": "/serde/se.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@dataclass
class SeField(Field[T]):
"""
Field class for serialization.
"""
@property
def varname(self) -> str:
"""
Get variable name in the generated code e.g. obj.a.b
"""
var = getattr(self.parent, "varname", None) if self.parent else None
if v... | code_fim | hard | {
"lang": "python",
"repo": "yukinarit/pyserde",
"path": "/serde/se.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WesGtoX/python-selenium path: /class11/class11_06.py
from time import sleep
from selenium.webdriver import Firefox
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support.expected_conditions import alert_is_present
<|fim_suffix|>sleep(2)
browser.find_element_b... | code_fim | medium | {
"lang": "python",
"repo": "WesGtoX/python-selenium",
"path": "/class11/class11_06.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
url = 'https://selenium.dunossauro.live/aula_11_a.html'
browser = Firefox()
wdw = WebDriverWait(browser, 30)
browser.get(url)
sleep(2)
browser.find_element_by_id('alertd').click()
print('before wait alert...')
alert = wdw.until(alert_is_present())
print('after wait alert.')
alert.accept() # alerta... | code_fim | medium | {
"lang": "python",
"repo": "WesGtoX/python-selenium",
"path": "/class11/class11_06.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with arg_scope([layers.batch_norm], is_training=False):
s = preprocess(o)
a = actors(s, noise=noise)
q = critics(s, a)
layers.summarize_tensors([s, *a, *q])
return a
self.act = Function(act)
def t... | code_fim | hard | {
"lang": "python",
"repo": "Digits88/chi",
"path": "/chi/rl/bdpg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Digits88/chi path: /chi/rl/bdpg.py
""" This script implements the DDPG algorithm
"""
import tensorflow as tf
from tensorflow.python.layers.utils import smart_cond
from tensorflow.python.ops.variable_scope import get_local_variable
import chi
import tensortools as tt
from chi import Experiment, e... | code_fim | hard | {
"lang": "python",
"repo": "Digits88/chi",
"path": "/chi/rl/bdpg.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ob = self.env.reset()
done = False
R = 0
self.act.initialize_local()
idx = np.random.randint(0, self.heads)
while not done:
a = self.act(ob)
a = a[idx]
a = a if np.random.rand() > .1 else self.env.action_space.sample()
... | code_fim | hard | {
"lang": "python",
"repo": "Digits88/chi",
"path": "/chi/rl/bdpg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: robin8a/udemy_raspberry_machine_learning path: /Codes/Image_processing_projects/Project_5-Real_time_Human_Face_Recognition/5.5-Human_Face_Recognition-2.py
# Real-time Human Face Recognition - 2
# Training using face images stored in human_faces folder
# Testing using images captured from webcam
... | code_fim | hard | {
"lang": "python",
"repo": "robin8a/udemy_raspberry_machine_learning",
"path": "/Codes/Image_processing_projects/Project_5-Real_time_Human_Face_Recognition/5.5-Human_Face_Recognition-2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if matching[1] < 500:
score = int( 100 * (1 - (matching[1])/350) )
string = str(score) + '% Matching Confidence'
if score > 70:
# Input the text string using cv2.putText
#cv2.putText(image, string, orgin, font, fontScale, color, thickness)
cv2.putText(image, string, (100, 100),... | code_fim | hard | {
"lang": "python",
"repo": "robin8a/udemy_raspberry_machine_learning",
"path": "/Codes/Image_processing_projects/Project_5-Real_time_Human_Face_Recognition/5.5-Human_Face_Recognition-2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> diff_bmp.GetPixelColor(0, 0).AssertIsRGB(0, 255, 255)
diff_bmp.GetPixelColor(1, 1).AssertIsRGB(255, 0, 255)
diff_bmp.GetPixelColor(0, 1).AssertIsRGB(255, 255, 0)
diff_bmp.GetPixelColor(1, 0).AssertIsRGB(0, 0, 255)
diff_bmp.GetPixelColor(0, 2).AssertIsRGB(255, 255, 255)
diff_bmp.Ge... | code_fim | hard | {
"lang": "python",
"repo": "PDi-Communication-Systems-Inc/lollipop_external_chromium_org",
"path": "/tools/telemetry/telemetry/core/bitmap_unittest.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PDi-Communication-Systems-Inc/lollipop_external_chromium_org path: /tools/telemetry/telemetry/core/bitmap_unittest.py
# Copyright 2013 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import tempfile
... | code_fim | hard | {
"lang": "python",
"repo": "PDi-Communication-Systems-Inc/lollipop_external_chromium_org",
"path": "/tools/telemetry/telemetry/core/bitmap_unittest.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> histogram = bmp.ColorHistogram()
for i in xrange(3):
self.assertEquals(sum(histogram[i]), bmp.width * bmp.height)
self.assertEquals(histogram.r[1], 0)
self.assertEquals(histogram.r[5], 2)
self.assertEquals(histogram.r[8], 2)
self.assertEquals(histogram.g[2], 0)
self.asser... | code_fim | hard | {
"lang": "python",
"repo": "PDi-Communication-Systems-Inc/lollipop_external_chromium_org",
"path": "/tools/telemetry/telemetry/core/bitmap_unittest.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return super(MultiChoiceAnswer, cls).equals(answer, txt)
class MultiSelectAnswer(Answer):
value = models.ManyToManyField("QuestionOption", )
@classmethod
def create(cls, interview, question, answer):
raw_answer = answer
if isinstance(answer, basestring):
... | code_fim | hard | {
"lang": "python",
"repo": "unicefuganda/uSurvey",
"path": "/survey/models/interviews.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: unicefuganda/uSurvey path: /survey/models/interviews.py
# ignore the initial message
if self.has_started and reply is None:
return self.last_question.display_text(channel=channel, context=answers_context)
# now confirm the question is applicable
if next_... | code_fim | hard | {
"lang": "python",
"repo": "unicefuganda/uSurvey",
"path": "/survey/models/interviews.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: unicefuganda/uSurvey path: /survey/models/interviews.py
query_args = []
return {'%s%s__%s' % (namespace, answer_key, validation_queries[cls.less_than.__name__]): test_args[1],
'%s%s__%s' % (namespace, answer_key,
validation_queri... | code_fim | hard | {
"lang": "python",
"repo": "unicefuganda/uSurvey",
"path": "/survey/models/interviews.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> @staticmethod
def minMax(df):
"""Center dataframe column ranges to [-1, 1]"""
max_, min_ = df.max(axis=0), df.min(axis=0)
midrange = (max_ + min_) / 2
half_range = (max_ - min_) / 2
return (df - midrange) / half_range
@staticmethod
def centerMeanAnd... | code_fim | hard | {
"lang": "python",
"repo": "meereeum/vANNilla-tf",
"path": "/classes/data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: meereeum/vANNilla-tf path: /classes/data.py
from __future__ import division
import re
import pandas as pd
import numpy as np
class DataIO:
def __init__(self, df, target_label, norm_fn = None, clip_to = None,
encode_n_minus_1 = False):
"""Data class with functions f... | code_fim | hard | {
"lang": "python",
"repo": "meereeum/vANNilla-tf",
"path": "/classes/data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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