text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: sk1010k/nussl path: /tests/test_run_and_eval.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import os
import nussl
class RunAndEvalUnitTest(unittest.TestCase):
def test_simple(self):
drums_path = os.path.join('Input', 'src1.wav')
flute_path = os.path.joi... | code_fim | medium | {
"lang": "python",
"repo": "sk1010k/nussl",
"path": "/tests/test_run_and_eval.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> repet = nussl.Repet
scores_repet = nussl.run_and_eval_prf(repet, repet_kwargs, mixtures, true_sources)
i = 0<|fim_prefix|># repo: sk1010k/nussl path: /tests/test_run_and_eval.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import os
import nussl
class RunAndE... | code_fim | hard | {
"lang": "python",
"repo": "sk1010k/nussl",
"path": "/tests/test_run_and_eval.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> scores_sim = nussl.run_and_eval_prf(repet_sim, repet_kwargs, mixtures, true_sources)
repet = nussl.Repet
scores_repet = nussl.run_and_eval_prf(repet, repet_kwargs, mixtures, true_sources)
i = 0<|fim_prefix|># repo: sk1010k/nussl path: /tests/test_run_and_eval.py
#!/usr/b... | code_fim | hard | {
"lang": "python",
"repo": "sk1010k/nussl",
"path": "/tests/test_run_and_eval.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shivangeerathi/sedkit path: /sedkit/tests/test_query.py
"""A suite of tests for the query.py module"""
import astropy.units as q
from astropy.coordinates import SkyCoord
from .. import query
def test_query_vizier():
"""Test for the query_vizier function"""
# 2MASS catalog
catalog ... | code_fim | hard | {
"lang": "python",
"repo": "shivangeerathi/sedkit",
"path": "/sedkit/tests/test_query.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Some results
results = query.query_SDSS_apogee_spectra(sky_coords, search_radius=10 * q.degree)
assert len(results) > 0
# No results
results = query.query_SDSS_apogee_spectra(sky_coords, search_radius=0.1 * q.arcsec)
assert len(results) > 0<|fim_prefix|># repo: shivangeerathi/se... | code_fim | hard | {
"lang": "python",
"repo": "shivangeerathi/sedkit",
"path": "/sedkit/tests/test_query.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return render_template("index.html", connected=client._connected)<|fim_prefix|># repo: soulnothing/TouchaTouchaTouchMe path: /dist/TTTM/rest.py
from flask import Flask, request, jsonify, render_template, Blueprint, url_for
from TTTM import app, client
import os
<|fim_middle|>@app.route('/')
def inde... | code_fim | easy | {
"lang": "python",
"repo": "soulnothing/TouchaTouchaTouchMe",
"path": "/dist/TTTM/rest.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: soulnothing/TouchaTouchaTouchMe path: /dist/TTTM/rest.py
from flask import Flask, request, jsonify, render_template, Blueprint, url_for
from TTTM import app, client
import os
<|fim_suffix|> return render_template("index.html", connected=client._connected)<|fim_middle|>@app.route('/')
def inde... | code_fim | easy | {
"lang": "python",
"repo": "soulnothing/TouchaTouchaTouchMe",
"path": "/dist/TTTM/rest.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def fix_ssl_monkeypatching():
"""
eventlet works by monkey-patching core IO libraries (such as ssl) to be non-blocking. However, there's currently
a bug: In the normal socket library it may throw a timeout error as a `socket.timeout` exception. However
eventlet.green.ssl's patch raises an ... | code_fim | medium | {
"lang": "python",
"repo": "alphagov/document-download-api",
"path": "/gunicorn_config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alphagov/document-download-api path: /gunicorn_config.py
import os
import socket
import eventlet
from gds_metrics.gunicorn import child_exit # noqa
bind = "0.0.0.0:{}".format(os.getenv("PORT"))
<|fim_suffix|>errorlog = "/home/vcap/logs/gunicorn_error.log"
def fix_ssl_monkeypatching():
"... | code_fim | medium | {
"lang": "python",
"repo": "alphagov/document-download-api",
"path": "/gunicorn_config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_urls(self):
urls = [
url(r'^settings/profile/$', login_required(self.profile_settings_view.as_view()), name='profile-settings'),
url(r'^settings/appearance/$', login_required(self.appearance_settings_view.as_view()), name='appearance-settings'),
# C... | code_fim | medium | {
"lang": "python",
"repo": "lyoniionly/django-cobra",
"path": "/src/cobra/apps/accounts/app.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lyoniionly/django-cobra path: /src/cobra/apps/accounts/app.py
from django.conf.urls import url
from django.contrib.auth.decorators import login_required
from allauth.account import views as allauth_views
from cobra.core.application import Application
from cobra.core.loading import get_class
c... | code_fim | hard | {
"lang": "python",
"repo": "lyoniionly/django-cobra",
"path": "/src/cobra/apps/accounts/app.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> urls = [
url(r'^settings/profile/$', login_required(self.profile_settings_view.as_view()), name='profile-settings'),
url(r'^settings/appearance/$', login_required(self.appearance_settings_view.as_view()), name='appearance-settings'),
# Copy from django-allauth,... | code_fim | hard | {
"lang": "python",
"repo": "lyoniionly/django-cobra",
"path": "/src/cobra/apps/accounts/app.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kapil87/Object-Oriented-Python-Code path: /Chapter_6/PygameDemo6_BallBounceObjectOriented/Ball.py
import pygame
from pygame.locals import *
import random
# Ball class
class Ball():
def __init__(self, window, windowWidth, windowHeight):
self.window = window # remember the window, s... | code_fim | medium | {
"lang": "python",
"repo": "kapil87/Object-Oriented-Python-Code",
"path": "/Chapter_6/PygameDemo6_BallBounceObjectOriented/Ball.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def update(self):
# Check for hitting a wall. If so, change that direction.
if (self.x < 0) or (self.x >= self.maxWidth):
self.xSpeed = -self.xSpeed
if (self.y < 0) or (self.y >= self.maxHeight):
self.ySpeed = -self.ySpeed
# Update the Ball's ... | code_fim | hard | {
"lang": "python",
"repo": "kapil87/Object-Oriented-Python-Code",
"path": "/Chapter_6/PygameDemo6_BallBounceObjectOriented/Ball.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># Global variable set by parameter
VERBOSE = False
# Pretty colors
if 'TERM' in os.environ and 'color' in os.environ['TERM']:
RED = '\033[91m'
YEL = '\033[93m'
UYEL = '\033[93m'+'\033[4m'
ENDC = '\033[0m'
else:
RED = ''
YEL = ''
UYEL = ''
ENDC = ''
def is_word_in(word, l... | code_fim | hard | {
"lang": "python",
"repo": "jdanders/svdac",
"path": "/svdac.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def remove_ignored_lines(file_contents, rule):
''' Replace lines marked with rule.ignore with blank lines '''
lines = file_contents.splitlines()
result = []
for line in lines:
if rule.ignore in line:
# Add \n to preserve line number count
result.append("\n")... | code_fim | hard | {
"lang": "python",
"repo": "jdanders/svdac",
"path": "/svdac.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jdanders/svdac path: /svdac.py
#! /usr/bin/env python3
"""System Verilog Domain Assignment Checker
Given a set of rules, check verilog files that all assignments meet the
rules. Rules are to ensure that "domains" are maintained, for example pipe
stage or clock domains.
A rule is an instance of ... | code_fim | hard | {
"lang": "python",
"repo": "jdanders/svdac",
"path": "/svdac.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cbpowell/SenseLink path: /senselink/__main__.py
import logging
import asyncio
import os
import argparse
from senselink import SenseLink
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-c", "--config", help="specify config file path")
parser.add_argu... | code_fim | hard | {
"lang": "python",
"repo": "cbpowell/SenseLink",
"path": "/senselink/__main__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> server = SenseLink(config)
if os.environ.get('SENSE_RESPONSE', 'True').upper() == 'TRUE' and not args.quiet:
logging.info("Will respond to Sense broadcasts")
server.should_respond = True
# Create instances
server.create_instances()
# Start and run indefinitely
log... | code_fim | hard | {
"lang": "python",
"repo": "cbpowell/SenseLink",
"path": "/senselink/__main__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Tenebrar/codebase path: /util/enums/tests/test_defaulting.py
from util.enums.defaulting import DefaultingEnum
class DEnum(DefaultingEnum):
<|fim_suffix|>def test_fetch_incorrect_name():
assert DEnum('c') == DEnum.UNKNOWN<|fim_middle|> A = 'a'
B = 'b'
UNKNOWN = 'unknown'
def te... | code_fim | medium | {
"lang": "python",
"repo": "Tenebrar/codebase",
"path": "/util/enums/tests/test_defaulting.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_fetch_incorrect_name():
assert DEnum('c') == DEnum.UNKNOWN<|fim_prefix|># repo: Tenebrar/codebase path: /util/enums/tests/test_defaulting.py
from util.enums.defaulting import DefaultingEnum
class DEnum(DefaultingEnum):
A = 'a'
B = 'b'
UNKNOWN = 'unknown'
def test_fetch_by_na... | code_fim | easy | {
"lang": "python",
"repo": "Tenebrar/codebase",
"path": "/util/enums/tests/test_defaulting.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: guilouro/devent path: /core/migrations/0005_auto_20150814_1143.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
<|fim_suffix|> operations = [
migrations.RemoveField(
model_name='event',
name='from_day'... | code_fim | medium | {
"lang": "python",
"repo": "guilouro/devent",
"path": "/core/migrations/0005_auto_20150814_1143.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.RemoveField(
model_name='event',
name='from_day',
),
migrations.RemoveField(
model_name='event',
name='to_day',
),
migrations.AddField(
model_name='event',
name='st... | code_fim | medium | {
"lang": "python",
"repo": "guilouro/devent",
"path": "/core/migrations/0005_auto_20150814_1143.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sunmengnan/city_brain path: /algorithms/03-routing/01-osrm/match.py
import osrm
points = [(-33.45017046193167, -70.6528186798<|fim_suffix|> (-33.453867464504555, -70.65277576446533)]
result = osrm.match(points, steps=False, overview="simplified")<|fim_middle|>0957),
(-33.4523... | code_fim | easy | {
"lang": "python",
"repo": "sunmengnan/city_brain",
"path": "/algorithms/03-routing/01-osrm/match.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> (-33.453867464504555, -70.65277576446533)]
result = osrm.match(points, steps=False, overview="simplified")<|fim_prefix|># repo: sunmengnan/city_brain path: /algorithms/03-routing/01-osrm/match.py
import osrm
points = [(-33.45017046193167, -70.6528186798<|fim_middle|>0957),
(-33.4523... | code_fim | easy | {
"lang": "python",
"repo": "sunmengnan/city_brain",
"path": "/algorithms/03-routing/01-osrm/match.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return run_metrics
def format_gnuplot(tds):
"""Generates a series of lines to plot Tile Data Structure in
GNUPlot.
"""
if tds['type'] == '%':
fname = "Occupancy-By-Tile"
xlabel = "% Occupied"
ylabel = "% Pass Filter"
xrange = yrange = 100.0
p... | code_fim | hard | {
"lang": "python",
"repo": "EdinburghGenomics/illuminatus",
"path": "/pf_vs_occupied.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Load the goodies from the .bin files in the InterOp directory.
This black magic is copy-pasted straight out of the tutorial linked above!
"""
#print("Examining: {}".format(run_dir))
valid_to_load = py_interop_run.uchar_vector(py_interop_run.MetricCount, 0)
for v2l in (py_i... | code_fim | hard | {
"lang": "python",
"repo": "EdinburghGenomics/illuminatus",
"path": "/pf_vs_occupied.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EdinburghGenomics/illuminatus path: /pf_vs_occupied.py
#!/usr/bin/env python3
# This script reads InterOp for a run and generates GNUPlot
# instructions to make a plot of %Occupied vs. %Pass Filter,
# as requested by Matt.
# To make my life simpler, I'll use the Python bindings to read the Inte... | code_fim | hard | {
"lang": "python",
"repo": "EdinburghGenomics/illuminatus",
"path": "/pf_vs_occupied.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> print('Fetching pool hashrate data ... ', end="")
sys.stdout.flush()
new_v = poolrate(cfg)
print('Done.')
string = ""
i = 0
for v in new_v:
key = cfg['pool_list'][i]['label']
if key not in vp:
vp[key] = []
... | code_fim | hard | {
"lang": "python",
"repo": "XzxEmbedded/Avalon-extras",
"path": "/farm-manager/status-report/chkrate.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> string = ""
i = 0
for v in new_v:
key = cfg['pool_list'][i]['label']
if key not in vp:
vp[key] = []
vp[key].append(float(v))
string += ";" + key + ":" + v
i += 1
label = ['Local Method 1', 'Local M... | code_fim | hard | {
"lang": "python",
"repo": "XzxEmbedded/Avalon-extras",
"path": "/farm-manager/status-report/chkrate.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: XzxEmbedded/Avalon-extras path: /farm-manager/status-report/chkrate.py
#!/usr/bin/env python2
from __future__ import print_function
import datetime
import sys
from poolrate import poolrate
def chkrate(data, data0, cfg, time, time0):
if data is not None:
print('Calculating hashrat... | code_fim | hard | {
"lang": "python",
"repo": "XzxEmbedded/Avalon-extras",
"path": "/farm-manager/status-report/chkrate.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MetOffice/forest path: /test/test_scaling_group.py
from unittest.mock import Mock
import forest.scaling_group
def test_scaling_group_scale_up():
n = 5
pool = Mock()
scaling_group = forest.scaling_group.ScalingGroup(pool)
scaling_group.scale_to(n)
assert len(scaling_group.ins... | code_fim | medium | {
"lang": "python",
"repo": "MetOffice/forest",
"path": "/test/test_scaling_group.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_scaling_group_scale_down():
pool = Mock()
large = 10
small = 3
scaling_group = forest.scaling_group.ScalingGroup(pool)
scaling_group.scale_to(large)
scaling_group.scale_to(small)
assert len(scaling_group.instances) == small
assert pool.acquire.call_count == large
... | code_fim | hard | {
"lang": "python",
"repo": "MetOffice/forest",
"path": "/test/test_scaling_group.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_read_full_response(self):
self.holodeck.mock(Response(
200,
'''
{
"meta": {
"url": "https://insights.twilio.com/v1/Video/Rooms/RMaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa/Participants?PageSize=50&Page=0",
... | code_fim | hard | {
"lang": "python",
"repo": "TheOther-Guy/twilio-python",
"path": "/tests/integration/insights/v1/room/test_participant.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheOther-Guy/twilio-python path: /tests/integration/insights/v1/room/test_participant.py
# coding=utf-8
r"""
This code was generated by
\ / _ _ _| _ _
| (_)\/(_)(_|\/| |(/_ v1.0.0
/ /
"""
from tests import IntegrationTestCase
from tests.holodeck import Request
from twilio.ba... | code_fim | hard | {
"lang": "python",
"repo": "TheOther-Guy/twilio-python",
"path": "/tests/integration/insights/v1/room/test_participant.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertIsNotNone(actual)
def test_read_full_response(self):
self.holodeck.mock(Response(
200,
'''
{
"meta": {
"url": "https://insights.twilio.com/v1/Video/Rooms/RMaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa/Participants?... | code_fim | hard | {
"lang": "python",
"repo": "TheOther-Guy/twilio-python",
"path": "/tests/integration/insights/v1/room/test_participant.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def generate_token(length=30, chars=UNICODE_ASCII_CHARACTER_SET):
rand = random.SystemRandom()
return ''.join(rand.choice(chars) for _ in range(length))<|fim_prefix|># repo: voegtlel/auth-manager-mailu-man path: /mailu_man_mini/token_gen.py
import random
import string
<|fim_middle|>UNICODE_ASCI... | code_fim | medium | {
"lang": "python",
"repo": "voegtlel/auth-manager-mailu-man",
"path": "/mailu_man_mini/token_gen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: voegtlel/auth-manager-mailu-man path: /mailu_man_mini/token_gen.py
import random
import string
UNICODE_ASCII_CHARACTER_SET = string.ascii_letters + string.digits
<|fim_suffix|> rand = random.SystemRandom()
return ''.join(rand.choice(chars) for _ in range(length))<|fim_middle|>
def genera... | code_fim | medium | {
"lang": "python",
"repo": "voegtlel/auth-manager-mailu-man",
"path": "/mailu_man_mini/token_gen.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rand = random.SystemRandom()
return ''.join(rand.choice(chars) for _ in range(length))<|fim_prefix|># repo: voegtlel/auth-manager-mailu-man path: /mailu_man_mini/token_gen.py
import random
import string
UNICODE_ASCII_CHARACTER_SET = string.ascii_letters + string.digits
<|fim_middle|>
def genera... | code_fim | medium | {
"lang": "python",
"repo": "voegtlel/auth-manager-mailu-man",
"path": "/mailu_man_mini/token_gen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> tfidf_mat_selection = None
features_template = None
tfidf_mat_template = None
selected_idx = []
now = datetime.now()
dt_string = now.strftime("%d%m%Y_%H%M%S")
# ---------------------------- TRAINING -----------------------------
mi = mutual_info_classif(tfidf_mat, tags)
... | code_fim | hard | {
"lang": "python",
"repo": "Muhammad-Yunus/Hoax-Classifier-App",
"path": "/ml_core/feature_selection_training.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Muhammad-Yunus/Hoax-Classifier-App path: /ml_core/feature_selection_training.py
from sklearn.feature_selection import mutual_info_classif
from ml_core.json_utils import readJson_config, writeJson_config
from datetime import datetime
from scipy import sparse
import pandas as pd
import numpy as np
... | code_fim | hard | {
"lang": "python",
"repo": "Muhammad-Yunus/Hoax-Classifier-App",
"path": "/ml_core/feature_selection_training.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> column_idx = [i for i, mi_item in enumerate(norm_mi) if mi_item < 0.01]
tfidf_mat_selection = np.delete(tfidf_mat, column_idx ,1)
# template data
selected_idx = [j for j in range(len(norm_mi)) if j not in column_idx]
selected_features = []
for idx in selected_idx:
selected... | code_fim | medium | {
"lang": "python",
"repo": "Muhammad-Yunus/Hoax-Classifier-App",
"path": "/ml_core/feature_selection_training.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>## Space Complexity: O( 1 )
#
# The overhead in space is the storage for vote and majority, which is of O( 1 ).
from collections import namedtuple
TestEntry = namedtuple('TestEntry', 'vote_sequence')
def test_bench():
test_data = [
TestEntry( vote_sequence= [3,2,3] ),
... | code_fim | hard | {
"lang": "python",
"repo": "brianchiang-tw/leetcode",
"path": "/2020_May_Leetcode_30_days_challenge/Week_1_Majority Element/by_boyer_moore_voting_algorithm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: brianchiang-tw/leetcode path: /2020_May_Leetcode_30_days_challenge/Week_1_Majority Element/by_boyer_moore_voting_algorithm.py
'''
Description:
Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊ n/2 ⌋ times.
You may assume that the ... | code_fim | hard | {
"lang": "python",
"repo": "brianchiang-tw/leetcode",
"path": "/2020_May_Leetcode_30_days_challenge/Week_1_Majority Element/by_boyer_moore_voting_algorithm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Print out info about whats going on
# Update Training rate
# Save the model (if we need to save the model)<|fim_prefix|># repo: chekfung/GauGAN_Reimplementation path: /code/train.py
# import Pix2PixTrainer
import tensorflow as tf
# TODO: Line to create the trainer object that has all... | code_fim | medium | {
"lang": "python",
"repo": "chekfung/GauGAN_Reimplementation",
"path": "/code/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chekfung/GauGAN_Reimplementation path: /code/train.py
# import Pix2PixTrainer
import tensorflow as tf
# TODO: Line to create the trainer object that has all the info we need
trainer = Pix2PixTrainer
<|fim_suffix|>
# Otherwise use default hyperparameters
for epoch in range(begin_epoch, hp.num... | code_fim | medium | {
"lang": "python",
"repo": "chekfung/GauGAN_Reimplementation",
"path": "/code/train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for epoch in range(begin_epoch, hp.num_epochs):
# Run the Generator every two times of i
# Run the Discriminator
# Print out info about whats going on
# Update Training rate
# Save the model (if we need to save the model)<|fim_prefix|># repo: chekfung/GauGAN_Reimplementation p... | code_fim | medium | {
"lang": "python",
"repo": "chekfung/GauGAN_Reimplementation",
"path": "/code/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Block #2: second CONV => RELU => POOL layer set
conv2_1 = mx.sym.Convolution(data=do1, kernel=(5, 5), pad=(2, 2), num_filter=256)
act2_1 = mx.sym.LeakyReLU(data=conv2_1, act_type="elu")
bn2_1 = mx.sym.BatchNorm(data=act2_1)
pool2 = mx.sym.Pooling(data=bn2_1, pool_... | code_fim | hard | {
"lang": "python",
"repo": "miroso/pis_code",
"path": "/imagenet_bundle/ch05-alexnet/mxalexnet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: miroso/pis_code path: /imagenet_bundle/ch05-alexnet/mxalexnet.py
# -*- coding: utf-8 -*-
"""Implementation of AlexNet architecture with MXNet.
"""
import mxnet as mx
class MxAlexNet:
"""AlexNet architecture
"""
@staticmethod
def build(classes):
"""Build AlexNet with MXNe... | code_fim | hard | {
"lang": "python",
"repo": "miroso/pis_code",
"path": "/imagenet_bundle/ch05-alexnet/mxalexnet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>DEFAULT_TENSE_WEIGHTS = (
1, # infinitive
3, # present
1, # present continuous
3, # imperfect
1, # imperfect continuous
3, # perfect
2, # future simple
0, # future formal (NOT LEARNED)
0, # future conditional (NOT LEARNED)
0, # imperative negative (NOT LEARNED)
... | code_fim | hard | {
"lang": "python",
"repo": "lawrencesim/portuguese-verb-cards",
"path": "/bin/constants.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lawrencesim/portuguese-verb-cards path: /bin/constants.py
from types import SimpleNamespace
PERSON = SimpleNamespace(FIRST=1, SECOND=2, THIRD=3)
PERSON_VALUES = tuple(sorted(getattr(PERSON, n) for n in dir(PERSON) if not n.startswith("_")))
PERSON_NAMES = {getattr(PERSON, n): n for n in dir(PER... | code_fim | hard | {
"lang": "python",
"repo": "lawrencesim/portuguese-verb-cards",
"path": "/bin/constants.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nipengmath/Distributed-Tensorflow-Template path: /models/example_model.py
import tensorflow as tf
from base.model import BaseModel
from typing import Dict
class Mnist(BaseModel):
def __init__(self, config: dict) -> None:
"""
Create a model used to classify hand written image... | code_fim | hard | {
"lang": "python",
"repo": "nipengmath/Distributed-Tensorflow-Template",
"path": "/models/example_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)
def _fc_block(x: tf.Tensor, size: int, is_training: bool, drop: float) -> tf.Tensor:
"""
Create a fully connected block using batch-norm and drop out
:param x: input layer which proceeds this block
:param size:... | code_fim | hard | {
"lang": "python",
"repo": "nipengmath/Distributed-Tensorflow-Template",
"path": "/models/example_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>async def test_connected_event(hass: HomeAssistant, mock_litejet) -> None:
"""Test handling an event from LiteJet."""
await async_init_integration(hass, use_switch=True)
# Initial state is available.
assert hass.states.get(ENTITY_SWITCH).state == STATE_OFF
assert hass.states.get(ENTI... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/core",
"path": "/tests/components/litejet/test_switch.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: home-assistant/core path: /tests/components/litejet/test_switch.py
"""The tests for the litejet component."""
from homeassistant.components import switch
from homeassistant.const import (
ATTR_ENTITY_ID,
SERVICE_TURN_OFF,
SERVICE_TURN_ON,
STATE_OFF,
STATE_ON,
STATE_UNAVAIL... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/core",
"path": "/tests/components/litejet/test_switch.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.add(
EmphasisElement(
content=content,
level=level,
))
return self
def add_lang(
self,
content,
xmllang=None,
):
self.add(
LangElement(
content=content,
... | code_fim | hard | {
"lang": "python",
"repo": "plivo/plivo-python",
"path": "/plivo/xml/speakElement.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: plivo/plivo-python path: /plivo/xml/speakElement.py
from plivo.utils.validators import *
from plivo.xml import (
PlivoXMLElement,
map_type,
BreakElement,
EmphasisElement,
LangElement,
)
class SpeakElement(PlivoXMLElement):
_name = 'Speak'
_nestable = [
'break... | code_fim | hard | {
"lang": "python",
"repo": "plivo/plivo-python",
"path": "/plivo/xml/speakElement.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return socket.inet_ntoa(struct.pack("!I", ipInt))<|fim_prefix|># repo: 3ev0/rdns-monitor path: /rdnsmonitor/handy.py
import struct
import socket
<|fim_middle|>def ipToInt(ipstr):
return struct.unpack("!I", socket.inet_aton(ipstr))[0]
def intToIp(ipInt):
| code_fim | medium | {
"lang": "python",
"repo": "3ev0/rdns-monitor",
"path": "/rdnsmonitor/handy.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 3ev0/rdns-monitor path: /rdnsmonitor/handy.py
import struct
import socket
<|fim_suffix|> return socket.inet_ntoa(struct.pack("!I", ipInt))<|fim_middle|>def ipToInt(ipstr):
return struct.unpack("!I", socket.inet_aton(ipstr))[0]
def intToIp(ipInt):
| code_fim | medium | {
"lang": "python",
"repo": "3ev0/rdns-monitor",
"path": "/rdnsmonitor/handy.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def intToIp(ipInt):
return socket.inet_ntoa(struct.pack("!I", ipInt))<|fim_prefix|># repo: 3ev0/rdns-monitor path: /rdnsmonitor/handy.py
import struct
import socket
<|fim_middle|>def ipToInt(ipstr):
return struct.unpack("!I", socket.inet_aton(ipstr))[0]
| code_fim | medium | {
"lang": "python",
"repo": "3ev0/rdns-monitor",
"path": "/rdnsmonitor/handy.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mwtoews/surface-water-network path: /swn/file.py
"""File reading/writing helpers."""
__all__ = [
"topnet2ts",
"gdf_to_shapefile",
"read_formatted_frame",
"write_formatted_frame",
]
import geopandas
import numpy as np
import pandas as pd
from .logger import get_logger, logging
... | code_fim | hard | {
"lang": "python",
"repo": "mwtoews/surface-water-network",
"path": "/swn/file.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Write a data frame as a free formatted table.
Parameters
----------
df : pandas.DataFrame
DataFrame to write.
fname : str, path-like or file-like object
Path to write file.
index : bool, default True
Write row names (index).
comment_header : bool, de... | code_fim | hard | {
"lang": "python",
"repo": "mwtoews/surface-water-network",
"path": "/swn/file.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def write_formatted_frame(df, fname, index=True, comment_header=True):
"""Write a data frame as a free formatted table.
Parameters
----------
df : pandas.DataFrame
DataFrame to write.
fname : str, path-like or file-like object
Path to write file.
index : bool, defa... | code_fim | hard | {
"lang": "python",
"repo": "mwtoews/surface-water-network",
"path": "/swn/file.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> ax[0].set_title(data_title)
ax[0].set_xlabel('longitude [m]')
ax[0].set_ylabel('lateral [m]')
ax[0].plot(p_obs[:, non_target_inds, 1], p_obs[:, non_target_inds, 0],
alpha=0.1, marker='x', color='blue')
if np.isnan(p_obs).any():
is_nan_endpoint = np.isnan(p_obs)
... | code_fim | hard | {
"lang": "python",
"repo": "umautobots/kinematic_highway",
"path": "/display/predictions_2d.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: umautobots/kinematic_highway path: /display/predictions_2d.py
import numpy as np
from scipy import stats as ss
import matplotlib.pyplot as plt
def display_prediction_density(ax, p, w):
# p: 2, n_samples | [lon, lat] position
p_min = 1e-2
jitter = np.random.randn(*p.shape) * np.array... | code_fim | hard | {
"lang": "python",
"repo": "umautobots/kinematic_highway",
"path": "/display/predictions_2d.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == "__main__":
print(Solution().powerfulIntegers(2, 3, 10))
print(Solution().powerfulIntegers(3, 5, 15))
print(Solution().powerfulIntegers(1, 2, 100))<|fim_prefix|># repo: Satily/leetcode_python_solution path: /solutions/solution970.py
class Solution:
def powerfulIntegers(sel... | code_fim | hard | {
"lang": "python",
"repo": "Satily/leetcode_python_solution",
"path": "/solutions/solution970.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Satily/leetcode_python_solution path: /solutions/solution970.py
class Solution:
def powerfulIntegers(self, x, y, bound):
"""
:type x: int
:type y: int
:type bound: int
:rtype: List[int]
"""
def powers(n, bound):
if n == 1:
... | code_fim | hard | {
"lang": "python",
"repo": "Satily/leetcode_python_solution",
"path": "/solutions/solution970.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
print(Solution().powerfulIntegers(2, 3, 10))
print(Solution().powerfulIntegers(3, 5, 15))
print(Solution().powerfulIntegers(1, 2, 100))<|fim_prefix|># repo: Satily/leetcode_python_solution path: /solutions/solution970.py
class Solution:
def powerfulIntegers(self... | code_fim | hard | {
"lang": "python",
"repo": "Satily/leetcode_python_solution",
"path": "/solutions/solution970.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>Test utils can be found in `serious.test_utils`.
`More on Read The Docs.`_
`Sources on GitHub.`_
.. _More on Read The Docs.: https://serious.readthedocs.io/en/latest/
.. _Sources on GitHub.: https://github.com/mdrachuk/serious
"""
from .dict import DictModel
from .errors import ModelError, ValidationEr... | code_fim | medium | {
"lang": "python",
"repo": "mdrachuk/serious",
"path": "/serious/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mdrachuk/serious path: /serious/__init__.py
"""Serious is a Python dataclass model toolkit for serialization, validation, and more.
<|fim_suffix|>To provide custom field serialization use `serious.serialization`.
Test utils can be found in `serious.test_utils`.
`More on Read The Docs.`_
`Sourc... | code_fim | medium | {
"lang": "python",
"repo": "mdrachuk/serious",
"path": "/serious/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SiChiTong/prlite-pc path: /pr2lite_moveit_config/nodes/point_head.py
#! /usr/bin/env python
# Copyright (c) 2010, Arizona Robotics Research Group, University of Arizona
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted pro... | code_fim | hard | {
"lang": "python",
"repo": "SiChiTong/prlite-pc",
"path": "/pr2lite_moveit_config/nodes/point_head.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> rospy.loginfo( "ref frames: " + pan_ref_frame + ", " + tilt_ref_frame)
rospy.loginfo( "target point " + str(target.header.frame_id) + " x " + str( target.point.x) + " y " + str(target.point.y) + " z " + str(target.point.z))
# atan2 (opposite, adjacent)
# Transform target p... | code_fim | hard | {
"lang": "python",
"repo": "SiChiTong/prlite-pc",
"path": "/pr2lite_moveit_config/nodes/point_head.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AP-Atul/ml path: /linear_regression/sk.py
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error, mean_squared_error
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
data ... | code_fim | medium | {
"lang": "python",
"repo": "AP-Atul/ml",
"path": "/linear_regression/sk.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>X = data.iloc[:, 3: 7]
y = data.iloc[:, -1]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3)
print(f"Training samples:: {len(X_train)}")
print(f"Testing samples:: {len(X_test)}")
model = LinearRegression()
model.fit(X_train, y_train)
print(f"Coefficients :: {model.coef_}")
p... | code_fim | medium | {
"lang": "python",
"repo": "AP-Atul/ml",
"path": "/linear_regression/sk.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: spykard/pomegranate path: /tests/test_markov_chain.py
[ 'C', 'C', 'D', 0.15 ],
[ 'C', 'D', 'A', 0.8 ], [ 'C', 'D', 'B', 0.1 ], [ 'C', 'D', 'C', 0.05 ], [ 'C', 'D', 'D', 0.05 ],
[ 'D', 'A', 'A', 0.5 ], [ 'D', 'A', 'B', 0.0 ], [ 'D', 'A', 'C', 0.5 ], [ 'D', 'A', 'D', 0.0 ],
[ 'D', 'B', 'A'... | code_fim | hard | {
"lang": "python",
"repo": "spykard/pomegranate",
"path": "/tests/test_markov_chain.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: spykard/pomegranate path: /tests/test_markov_chain.py
05 ], [ 'A', 'C', 0.05 ], [ 'A', 'D', 0.1 ],
[ 'B', 'A', 0.1 ], [ 'B', 'B', 0.2 ], [ 'B', 'C', 0.6 ], [ 'B', 'D', 0.1 ],
[ 'C', 'A', 0.15 ], [ 'C', 'B', 0.1 ], [ 'C', 'C', 0.25 ], [ 'C', 'D', 0.5 ],
[ 'D', 'A', 0.25 ], [ 'D', 'B', 0.2... | code_fim | hard | {
"lang": "python",
"repo": "spykard/pomegranate",
"path": "/tests/test_markov_chain.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert_almost_equal( second_chain.log_probability( list('A') ), -2.30258509299 )
assert_almost_equal( second_chain.log_probability( list('B') ), -1.60943791243 )
assert_almost_equal( second_chain.log_probability( list('AC') ), -5.29831736655 )
assert_almost_equal( second_chain.log_probability( list('... | code_fim | hard | {
"lang": "python",
"repo": "spykard/pomegranate",
"path": "/tests/test_markov_chain.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> user = Usuario.objects.get(username=usrk)
serializerU = UsuarioSerializer(user)
usrk = serializerU.data['id']
bookmarkSet = Bookmark.objects.filter(Usuario = usrk, Libro = libk)
#bookmark = get_object_or_404(bookmark, Usuario = usrk, Libro = libk)
serializer... | code_fim | medium | {
"lang": "python",
"repo": "UNIZAR-30226-2021-05/Lector--Backend",
"path": "/bookmark/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: UNIZAR-30226-2021-05/Lector--Backend path: /bookmark/views.py
from usuario import views
from django.shortcuts import render
import usuario
from .serializers import BookmarkSerializer
from usuario.serializers import UsuarioSerializer
from .models import Bookmark, Usuario, Libro
from rest_framewo... | code_fim | hard | {
"lang": "python",
"repo": "UNIZAR-30226-2021-05/Lector--Backend",
"path": "/bookmark/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def post(self, request, usrk, libk):
user = Usuario.objects.get(username=usrk)
lib = Libro.objects.get(ISBN=libk)
bookm = Bookmark(Usuario=user, Libro=lib, esAnotacion=True, titulo=request.data["titulo"], cuerpo=request.data["cuerpo"], offset=request.data["offset"])
boo... | code_fim | hard | {
"lang": "python",
"repo": "UNIZAR-30226-2021-05/Lector--Backend",
"path": "/bookmark/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> videos = []
for video in response:
music = {
"music_id": video['id'],
"name": video['title'],
"channel_name": video['user']['username'],
"description": video['description'][:200] + "..." if video['description'] else '',
"thumbnail... | code_fim | hard | {
"lang": "python",
"repo": "Amoki/Amoki-Music",
"path": "/sources/soundcloud.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Sometimes soundcloud send us a result like: [music1, music2]
# sometimes, it: {"collection": [music1, music2]}
# In the second case, the lib crash. So we parse ourselves the response
response = json.loads(raw_response.raw_data)
if 'collection' in response:
... | code_fim | hard | {
"lang": "python",
"repo": "Amoki/Amoki-Music",
"path": "/sources/soundcloud.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Amoki/Amoki-Music path: /sources/soundcloud.py
import re
import soundcloud
import json
from django.conf import settings
client = soundcloud.Client(client_id=settings.SOUNDCLOUD_KEY)
URL_REGEX = "^https?:\/\/(soundcloud.com|snd.sc)\/(.*)$"
def search(query):
<|fim_suffix|> videos = []
... | code_fim | hard | {
"lang": "python",
"repo": "Amoki/Amoki-Music",
"path": "/sources/soundcloud.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: liaogx/python3-cookbook path: /第九章：元编程/9.7.py
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# __author__ = 'liao gao xiang'
class Fib(object):
""""""
def __init__(self, n):
self.pre = 0
self.cur = 1
self.n = n
<|fim_suffix|> def __next__(self):
if sel... | code_fim | easy | {
"lang": "python",
"repo": "liaogx/python3-cookbook",
"path": "/第九章：元编程/9.7.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __iter__(self):
return self
def __next__(self):
if self.n < 0:
self.pre, self.cur = self.cur, self.pre + self.cur
return self.cur
else:
raise StopIteration
f = Fib(10)
print([i for i in f])<|fim_prefix|># repo: liaogx/python3-cookb... | code_fim | medium | {
"lang": "python",
"repo": "liaogx/python3-cookbook",
"path": "/第九章：元编程/9.7.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.pre = 0
self.cur = 1
self.n = n
def __iter__(self):
return self
def __next__(self):
if self.n < 0:
self.pre, self.cur = self.cur, self.pre + self.cur
return self.cur
else:
raise StopIteration
f = Fib(10)
p... | code_fim | easy | {
"lang": "python",
"repo": "liaogx/python3-cookbook",
"path": "/第九章：元编程/9.7.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: slevi105/PyFBA path: /PyFBA/metabolism/__init__.py
from .reaction import Reaction
from .compound import Compound
from .enzyme import Enzyme
from .<|fim_suffix|>mass_equation', 'Reaction', 'Compound', 'Enzyme']<|fim_middle|>biomass import biomass_equation
__all__ = ['bio | code_fim | easy | {
"lang": "python",
"repo": "slevi105/PyFBA",
"path": "/PyFBA/metabolism/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>mass_equation', 'Reaction', 'Compound', 'Enzyme']<|fim_prefix|># repo: slevi105/PyFBA path: /PyFBA/metabolism/__init__.py
from .reaction import Reaction
from .compound i<|fim_middle|>mport Compound
from .enzyme import Enzyme
from .biomass import biomass_equation
__all__ = ['bio | code_fim | medium | {
"lang": "python",
"repo": "slevi105/PyFBA",
"path": "/PyFBA/metabolism/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Else we may have a file
if not data['bl_type']:
# Try for file
ext = tools.what_ext(data["extensions"].keys(), blog_result)
if ext:
config['blog_title'] += ' : %s' % data['pi_bl']
data['bl_type'] = 'file'
data['root_datadir'] = blog_re... | code_fim | hard | {
"lang": "python",
"repo": "llimllib/personal_code",
"path": "/web/newf2o/blog/Pyblosxom/pyblosxom.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not r:
# get the renderer we want to use
r = config.get("renderer", "blosxom")
# import the renderer
r = tools.importName("renderers", r)
# get the renderer object
r = r.Renderer(request, config.get("stdoutput", sys.stdout))
data['renderer'] = ... | code_fim | hard | {
"lang": "python",
"repo": "llimllib/personal_code",
"path": "/web/newf2o/blog/Pyblosxom/pyblosxom.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: llimllib/personal_code path: /web/newf2o/blog/Pyblosxom/pyblosxom.py
hen we render only the ones that have changed.
@type incremental: boolean
"""
self.initialize()
config = self._request.getConfiguration()
data = self._request.getData()
print "Pe... | code_fim | hard | {
"lang": "python",
"repo": "llimllib/personal_code",
"path": "/web/newf2o/blog/Pyblosxom/pyblosxom.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if 'organization_pk' in request.session:
request.organization = Organization.objects.get(pk=request.session['organization_pk'])
else:
request.organization = None<|fim_prefix|># repo: SVArago/alexia path: /utils/middleware.py
from apps.organization.models import Org... | code_fim | medium | {
"lang": "python",
"repo": "SVArago/alexia",
"path": "/utils/middleware.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SVArago/alexia path: /utils/middleware.py
from apps.organization.models import Organization, Profile
class ProfileRequirementMiddleware(object):
def process_view(self, request, view_func, view_args, view_kwargs):
<|fim_suffix|> def process_request(self, request):
if 'organization... | code_fim | medium | {
"lang": "python",
"repo": "SVArago/alexia",
"path": "/utils/middleware.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PennyLaneAI/pennylane path: /tests/templates/test_layers/test_cv_neural_net.py
# Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of th... | code_fim | hard | {
"lang": "python",
"repo": "PennyLaneAI/pennylane",
"path": "/tests/templates/test_layers/test_cv_neural_net.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Tests the jax interface."""
import jax
import jax.numpy as jnp
shapes = expected_shapes(1, 2)
weights = [np.random.random(shape) for shape in shapes]
weights = [jnp.array(w) for w in weights]
dev = DummyDevice(wires=2)
circuit = qml.QN... | code_fim | hard | {
"lang": "python",
"repo": "PennyLaneAI/pennylane",
"path": "/tests/templates/test_layers/test_cv_neural_net.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Interferometer (replace with operation once this template is refactored)
qml.Beamsplitter(weights[0][0, 0], weights[1][0, 0], wires=[0, 1])
qml.Rotation(weights[2][0, 0], wires=0)
qml.Rotation(weights[2][0, 1], wires=1)
qml.Squeezing(weights[3][0, 0], weights[4][0, 0], wires=0)
... | code_fim | hard | {
"lang": "python",
"repo": "PennyLaneAI/pennylane",
"path": "/tests/templates/test_layers/test_cv_neural_net.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for it in range(self.iterations):
batch_size = spc * cpi
batch = torch.LongTensor(batch_size)
c_idxs = torch.randperm(len(self.classes))[:cpi]
for i, c in enumerate(self.classes[c_idxs]):
s = slice(i * spc, (i + 1) * spc)
... | code_fim | hard | {
"lang": "python",
"repo": "orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch",
"path": "/src/prototypical_batch_sampler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch path: /src/prototypical_batch_sampler.py
# coding=utf-8
import numpy as np
import torch
class PrototypicalBatchSampler(object):
'''
PrototypicalBatchSampler: yield a batch of indexes at each iteration.
Indexes are calculated... | code_fim | hard | {
"lang": "python",
"repo": "orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch",
"path": "/src/prototypical_batch_sampler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''
yield a batch of indexes
'''
spc = self.sample_per_class
cpi = self.classes_per_it
for it in range(self.iterations):
batch_size = spc * cpi
batch = torch.LongTensor(batch_size)
c_idxs = torch.randperm(len(self.classes... | code_fim | hard | {
"lang": "python",
"repo": "orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch",
"path": "/src/prototypical_batch_sampler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cobanov/demc-homework path: /dataset_download.py
from bs4 import BeautifulSoup
from urllib.request import urlopen
import requests
from requests.api import get
def get_links():
html = requests.get('https://datasets.imdbws.com/').text
soup = BeautifulSoup(html, "html.parser")
hrefs = ... | code_fim | hard | {
"lang": "python",
"repo": "cobanov/demc-homework",
"path": "/dataset_download.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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