text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> annotations = pd.read_csv(FLAGS.annotations_file)
annotations['LabelName'] = annotations['LabelName'].map(lambda n: class_descriptions[n])
annotations = annotations.groupby('ImageID')
images = tf.io.gfile.glob(FLAGS.images_dir + '/*/*.jpg')
images = map(lambda i: (os.path.basename(i).... | code_fim | medium | {
"lang": "python",
"repo": "suneric/object_detection",
"path": "/oid_tfrecord/generate-tfrecord.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: suneric/object_detection path: /oid_tfrecord/generate-tfrecord.py
import pandas as pd
import tensorflow as tf
from PIL import Image
import os
tf.compat.v1.flags.DEFINE_string('classes_file', None, 'Path to the text file containing downloaded classes, name per line')
tf.compat.v1.flags.DEFINE_str... | code_fim | hard | {
"lang": "python",
"repo": "suneric/object_detection",
"path": "/oid_tfrecord/generate-tfrecord.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> image_annotations = annotations.get_group(image_id)
for _, row in image_annotations.loc[image_annotations['LabelName'].isin(classes.keys())].iterrows():
print(_)
xmins.append(row['XMin'])
xmaxs.append(row['XMax'])
ymins.append(row['YMin'])
... | code_fim | hard | {
"lang": "python",
"repo": "suneric/object_detection",
"path": "/oid_tfrecord/generate-tfrecord.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Nathan939/DeepCodeur path: /_Scraping/another_scrap.py
import youtube_dl
from youtube_transcript_api import YouTubeTranscriptApi
from pydub import AudioSegment
from pydub.silence import split_on_silence
import os
import json
import pprint
hotwords = [x[0].split("\\")[-1] for x in os.walk('_I.A\D... | code_fim | hard | {
"lang": "python",
"repo": "Nathan939/DeepCodeur",
"path": "/_Scraping/another_scrap.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ydl_opts = {
'format': 'bestaudio/best',
'outtmpl': AudioPath + '/' + nom + '.%(ext)s',
'postprocessors': [{
'key': 'FFmpegExtractAudio',
'preferredcodec': 'wav',
'preferredquality': '192',
}],
}
"""
with youtube_dl.YoutubeDL(ydl_opts) as ydl:
... | code_fim | hard | {
"lang": "python",
"repo": "Nathan939/DeepCodeur",
"path": "/_Scraping/another_scrap.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while True:
try:
debit = float(input("Enter the amount to be withdrawn: "))
if debit < 0:
print("Invalid Amount Entered...Amount cannot be less than 0.00")
continue
else:
break
except ValueError:
... | code_fim | hard | {
"lang": "python",
"repo": "maneeshd/PyTutorial",
"path": "/Banking/Banking.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: maneeshd/PyTutorial path: /Banking/Banking.py
"""
Author: Maneesh Divana
Python: 3.5.2
Python-201 VILT Course Assignment: Bank Transactions using only text files.
Date: 8 Dec, 2016
"""
from math import fabs, pow, e
from re import compile
from sys import exit
from threading import Thread
def get... | code_fim | hard | {
"lang": "python",
"repo": "maneeshd/PyTutorial",
"path": "/Banking/Banking.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> f = None
fw = None
pattern = compile(".*(999999).*")
try:
f = open("customers_old.txt", "r", encoding="UTF-8")
fw = open("customer_new.txt", "w", encoding="UTF-8")
for customer in f.readlines():
if pattern.search(customer):
print("End of ... | code_fim | hard | {
"lang": "python",
"repo": "maneeshd/PyTutorial",
"path": "/Banking/Banking.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>TO_MENU_KEYBOARD = Keyboard().add(Text("В меню", {"cmd": "menu"})).get_json()
VOID_KEYBOARD = Keyboard().get_json()<|fim_prefix|># repo: homus32/vk_music_api_bot_vkbottle path: /src/keyboards/__init__.py
from vkbottle import Keyboard, KeyboardButtonColor, Callback, Text
<|fim_middle|>from .menu import ... | code_fim | hard | {
"lang": "python",
"repo": "homus32/vk_music_api_bot_vkbottle",
"path": "/src/keyboards/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: homus32/vk_music_api_bot_vkbottle path: /src/keyboards/__init__.py
from vkbottle import Keyboard, KeyboardButtonColor, Callback, Text
from .menu import Menu
from .purchase import *
from .key_control import *
from .admin import *
<|fim_suffix|>TO_MENU_KEYBOARD = Keyboard().add(Text("В меню", {"c... | code_fim | hard | {
"lang": "python",
"repo": "homus32/vk_music_api_bot_vkbottle",
"path": "/src/keyboards/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RevSquare/django-facebook-canvas-auth path: /facebook_canvas_auth/urls.py
from django.conf.urls import patterns, url
urlpattern<|fim_suffix|>r_loggedin',
name='add_check_user_loggedin'),
)<|fim_middle|>s = patterns(
'',
url(r'^add-check-user-loggedin$',
'facebook_canvas_a... | code_fim | medium | {
"lang": "python",
"repo": "RevSquare/django-facebook-canvas-auth",
"path": "/facebook_canvas_auth/urls.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>r_loggedin',
name='add_check_user_loggedin'),
)<|fim_prefix|># repo: RevSquare/django-facebook-canvas-auth path: /facebook_canvas_auth/urls.py
from django.conf.urls import patterns, url
urlpattern<|fim_middle|>s = patterns(
'',
url(r'^add-check-user-loggedin$',
'facebook_canvas_a... | code_fim | medium | {
"lang": "python",
"repo": "RevSquare/django-facebook-canvas-auth",
"path": "/facebook_canvas_auth/urls.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>n$',
'facebook_canvas_auth.views.add_check_user_loggedin',
name='add_check_user_loggedin'),
)<|fim_prefix|># repo: RevSquare/django-facebook-canvas-auth path: /facebook_canvas_auth/urls.py
from django.conf.urls import patterns, url
urlpattern<|fim_middle|>s = patterns(
'',
url(r'... | code_fim | easy | {
"lang": "python",
"repo": "RevSquare/django-facebook-canvas-auth",
"path": "/facebook_canvas_auth/urls.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ominatechnologies/opyprint path: /tests/utils/test_lt.py
# test_lt
from frozendict import NoCopyFrozenDict as FrozenDict
from pytest import raises
from opyprint import dict_lt, lt
def test_basics():
assert {'a': 1} == {'a': 1}
assert {'a': 1} != {'a': 2}
assert {'a': 1} != {'b': 1... | code_fim | hard | {
"lang": "python",
"repo": "ominatechnologies/opyprint",
"path": "/tests/utils/test_lt.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def assert_dict_lt(obj_1, obj_2):
assert dict_lt(obj_1, obj_2)
assert not dict_lt(obj_2, obj_1)
assert not dict_lt(obj_1, obj_1)
assert not dict_lt(obj_2, obj_2)
assert lt(obj_1, obj_2)
assert not lt(obj_2, obj_1)
assert not lt(obj_1, obj_1)
assert not lt(obj_2, obj_2)<|f... | code_fim | medium | {
"lang": "python",
"repo": "ominatechnologies/opyprint",
"path": "/tests/utils/test_lt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Magnetic inducing field parameter (A,I,D)
B = [50000, 90, 0]
# Create a MAGsurvey
rx = PF.BaseMag.RxObs(
np.vstack([[0.25, 0.25, 0.25], [-0.25, -0.25, 0.25]])
)
srcField = PF.BaseMag.SrcField([rx], param=(B[0], B[1], B[2]))
survey = PF... | code_fim | hard | {
"lang": "python",
"repo": "fperez/simpeg",
"path": "/tests/base/test_directives.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def setUp(self):
mesh = Mesh.TensorMesh([4, 4, 4])
# Magnetic inducing field parameter (A,I,D)
B = [50000, 90, 0]
# Create a MAGsurvey
rx = PF.BaseMag.RxObs(
np.vstack([[0.25, 0.25, 0.25], [-0.25, -0.25, 0.25]])
)
srcField = PF.Base... | code_fim | hard | {
"lang": "python",
"repo": "fperez/simpeg",
"path": "/tests/base/test_directives.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fperez/simpeg path: /tests/base/test_directives.py
import unittest
import warnings
import pytest
import numpy as np
from SimPEG import (
Mesh, Maps, Directives, Regularization, DataMisfit, Optimization,
Inversion, InvProblem
)
from SimPEG import PF
class DirectivesValidation(unittest.T... | code_fim | hard | {
"lang": "python",
"repo": "fperez/simpeg",
"path": "/tests/base/test_directives.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hgamboa/novainstrumentation path: /novainstrumentation/waves/computemeanwave.py
from numpy import *
def computemeanwave(signal, events, fdist, lmin=0,lmax=0):
<|fim_suffix|> if (lmin==0) & (lmax==0):
lmax=mean(diff(events))/2
lmin=-lmax
w=waves(signal, events, lmin... | code_fim | medium | {
"lang": "python",
"repo": "hgamboa/novainstrumentation",
"path": "/novainstrumentation/waves/computemeanwave.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (lmin==0) & (lmax==0):
lmax=mean(diff(events))/2
lmin=-lmax
w=waves(signal, events, lmin, lmax)
w_=meanwave(w)
d=wavedistance(w_,w,fdist)
ws=stdwave(w)
return (w_, ws, d)<|fim_prefix|># repo: hgamboa/novainstrumentation path: /novainstrumentation/wa... | code_fim | medium | {
"lang": "python",
"repo": "hgamboa/novainstrumentation",
"path": "/novainstrumentation/waves/computemeanwave.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not hours and not minutes:
raise Exception('Time pattern not matched')
if not self.parse_only:
self.assert_ticket_exists(ticket)
time = (hours, minutes)
return (ticket, time, description)
def assert_ticket_exists(self, ticket):
if ... | code_fim | hard | {
"lang": "python",
"repo": "jeffkenney/logjammin",
"path": "/logjammin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jeffkenney/logjammin path: /logjammin.py
#!/usr/bin/env python3
import re
import json
import argparse
import math
from os.path import expanduser, realpath
from datetime import datetime
from pytz import timezone
from jira import JIRA
from collections import OrderedDict
class LogJammin:
mode... | code_fim | hard | {
"lang": "python",
"repo": "jeffkenney/logjammin",
"path": "/logjammin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> parts = line.split(',', 2)
ticket_str = parts[0].strip() if len(parts) else ''
time_str = parts[1].strip() if len(parts) > 1 else ''
description = parts[2].strip() if len(parts) > 2 else ''
ticket_match_re = r'^[A-Z][A-Z0-9]+-\d+$'
ticket_match = re.match(t... | code_fim | hard | {
"lang": "python",
"repo": "jeffkenney/logjammin",
"path": "/logjammin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: arunpatala/hybrid_bootstrap path: /sampling_visualization_data_generator.py
import numpy as np
np.random.seed(42)
import pandas as pd
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, Activation, Flatten, Input... | code_fim | hard | {
"lang": "python",
"repo": "arunpatala/hybrid_bootstrap",
"path": "/sampling_visualization_data_generator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> preds = model.predict(X_test)
preds = np.argmax(preds, axis = 1)
np.sum(preds == y_test)
for i in range(11):
model.pop()
model.compile(loss ='mse',
optimizer = sgd)
image_maps_0 = model.predict(X_train)[0]
image_maps_0 = [image_maps_0[ :, :, channel... | code_fim | hard | {
"lang": "python",
"repo": "arunpatala/hybrid_bootstrap",
"path": "/sampling_visualization_data_generator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return "%s" % self.value
class WebHookTransaction(models.Model):
STATUS = TransactionStatus
# request body & meta
body = JSONField()
meta = JSONField()
# app
app = models.ForeignKey(WebHookClientApp, on_delete=models.CASCADE)
# status of transactio... | code_fim | hard | {
"lang": "python",
"repo": "bellyfat/django-hooked",
"path": "/hooked/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bellyfat/django-hooked path: /hooked/models.py
# -*- coding: utf-8 -*-
import uuid
from enum import IntEnum
from django.db import models
from django.template.defaultfilters import slugify
from django.utils import timezone
from jsonfield import JSONField
from .tokens import generate_random_secr... | code_fim | hard | {
"lang": "python",
"repo": "bellyfat/django-hooked",
"path": "/hooked/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = 'engage.UserMessage'
publish_fields = ('text', 'direction')
update_fields = ('text', )<|fim_prefix|># repo: Praseetha-KR/django-engage path: /engage/serializers.py
from swampdragon.serializers.model_serializer import ModelSerializer
class UserMessageSerializer(ModelSeria... | code_fim | easy | {
"lang": "python",
"repo": "Praseetha-KR/django-engage",
"path": "/engage/serializers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Praseetha-KR/django-engage path: /engage/serializers.py
from swampdragon.serializers.model_serializer import ModelSerializer
<|fim_suffix|> model = 'engage.UserMessage'
publish_fields = ('text', 'direction')
update_fields = ('text', )<|fim_middle|>
class UserMessageSeriali... | code_fim | medium | {
"lang": "python",
"repo": "Praseetha-KR/django-engage",
"path": "/engage/serializers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>of rows are: ",len(list(content))-1)
'''
for each in content:
print(each)
'''
fo.close()<|fim_prefix|># repo: PacktPublishing/Complete-Python-Scripting-for-Automation path: /Section 15/2.Document-read-a-header-and-finding-no-of-rows.py
import csv
req_file="C:\\Users\\Automation\\Desktop\\hi\\new_... | code_fim | medium | {
"lang": "python",
"repo": "PacktPublishing/Complete-Python-Scripting-for-Automation",
"path": "/Section 15/2.Document-read-a-header-and-finding-no-of-rows.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PacktPublishing/Complete-Python-Scripting-for-Automation path: /Section 15/2.Document-read-a-header-and-finding-no-of-rows.py
import csv
req_file="C:\\Users\\Automation\\Desktop\\hi\\new_info.csv"
fo=open(req_file,<|fim_suffix|>of rows are: ",len(list(content))-1)
'''
for each in content:
... | code_fim | medium | {
"lang": "python",
"repo": "PacktPublishing/Complete-Python-Scripting-for-Automation",
"path": "/Section 15/2.Document-read-a-header-and-finding-no-of-rows.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dana-i2cat/felix path: /expedient/src/python/expedient/clearinghouse/users/models.py
'''
Created on Dec 3, 2009
@author: jnaous
'''
from django.db import models
from django.contrib.auth.models import User
class UserProfile(models.Model):
'''
Additional information about a user.
<|... | code_fim | hard | {
"lang": "python",
"repo": "dana-i2cat/felix",
"path": "/expedient/src/python/expedient/clearinghouse/users/models.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> @return: user's profile
@rtype: L{UserProfile}
'''
try:
profile = user.get_profile()
except UserProfile.DoesNotExist:
profile = cls.objects.create(
user=user,
)
return ... | code_fim | medium | {
"lang": "python",
"repo": "dana-i2cat/felix",
"path": "/expedient/src/python/expedient/clearinghouse/users/models.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = Sequential()
model.add(Dense(10, input_shape=(segment_size, 5), activation='relu'))
model.add(LSTM(segment_size * 8, activation='relu'))
model.add(Dense(segment_size * 6, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(segment_size * 2, activation='relu'))
... | code_fim | medium | {
"lang": "python",
"repo": "rawatraghav/DoHlyzer",
"path": "/analyzer/models/v4.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rawatraghav/DoHlyzer path: /analyzer/models/v4.py
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM
<|fim_suffix|> model = Sequential()
model.add(Dense(10, input_shape=(segment_size, 5), activation='relu'))
model.add(LSTM(segment_s... | code_fim | medium | {
"lang": "python",
"repo": "rawatraghav/DoHlyzer",
"path": "/analyzer/models/v4.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: uyamazak/oceanus path: /revelation/app/hook/hooks/bizocean.py
from hook.base import BaseHook
from task.gspread.tasks import send2ws
class BizoceanHook(BaseHook):
def main(self) -> int:
channel = self.item.get("channel")
if channel != "bizocean":
return 0
<|fim... | code_fim | hard | {
"lang": "python",
"repo": "uyamazak/oceanus",
"path": "/revelation/app/hook/hooks/bizocean.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # エラー
if "error" in data["evt"]:
count += 1
values = (dt,
data.get("evt", ""),
data.get("url", ""),
data.get("ref", ""),
("sid", data.get("sid")),
("uid", d... | code_fim | hard | {
"lang": "python",
"repo": "uyamazak/oceanus",
"path": "/revelation/app/hook/hooks/bizocean.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> idx = np.random.choice(X.shape[0], self.Nb)
Xb = X[idx]
Tb = T[idx]
model = DecisionTreeRegressor()
model.fit(Xb, Tb)
self.models.append(model)
def predict(self, X):
... | code_fim | hard | {
"lang": "python",
"repo": "AVJdataminer/Machine-Learning-from-Scratch",
"path": "/bagged_tree_regressor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AVJdataminer/Machine-Learning-from-Scratch path: /bagged_tree_regressor.py
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeRegressor
from sklearn.metrics import mean_squared_error as mse
from sklearn.met... | code_fim | hard | {
"lang": "python",
"repo": "AVJdataminer/Machine-Learning-from-Scratch",
"path": "/bagged_tree_regressor.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0--key/lib path: /portfolio/Python/scrapy/seapets/aquariumsdelivered.py
import re
import os
import json
from scrapy.spider import BaseSpider
from scrapy.selector import HtmlXPathSelector
from scrapy.http import Request, HtmlResponse
from scrapy.utils.response import get_base_url
from scrapy.util... | code_fim | hard | {
"lang": "python",
"repo": "0--key/lib",
"path": "/portfolio/Python/scrapy/seapets/aquariumsdelivered.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> exclude = set()
for mandatory_option in mandatory_options:
option = mandatory_option.select(u'./@name').re('bundle_option\[(.*)\]')[0]
selection = mandatory_option.select(u'./@value').extract()[0]
option = options['options'][option]['... | code_fim | hard | {
"lang": "python",
"repo": "0--key/lib",
"path": "/portfolio/Python/scrapy/seapets/aquariumsdelivered.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>print "Back End: %s" % backendPerformance
print "Front End: %s" % frontendPerformance
driver.quit()<|fim_prefix|># repo: Coopertown75/cdnlyzer path: /scripts/load.py
from selenium import webdriver
from selenium.webdriver.common.proxy import Proxy, ProxyType
source = "https://amazon.com"
prox = Proxy()... | code_fim | hard | {
"lang": "python",
"repo": "Coopertown75/cdnlyzer",
"path": "/scripts/load.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Coopertown75/cdnlyzer path: /scripts/load.py
from selenium import webdriver
from selenium.webdriver.common.proxy import Proxy, ProxyType
source = "https://amazon.com"
prox = Proxy()
prox.proxy_type = ProxyType.MANUAL
prox.http_proxy = "127.0.0.1:9090"
prox.socks_proxy = "127.0.0.1:9090"
prox.ss... | code_fim | medium | {
"lang": "python",
"repo": "Coopertown75/cdnlyzer",
"path": "/scripts/load.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dtdi/Simod path: /support_modules/log_repairing/log_replayer.py
# -*- coding: utf-8 -*-
import networkx as nx
import pandas as pd
from support_modules import support as sup
from collections import OrderedDict
# TODO: Transform this into a class
def replay(process_graph, traces):
start_tasks... | code_fim | hard | {
"lang": "python",
"repo": "dtdi/Simod",
"path": "/support_modules/log_repairing/log_replayer.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def find_next_tasks(process_graph, num):
tasks_list=list()
for node in process_graph.neighbors(num):
if process_graph.node[node]['type']=='task' or process_graph.node[node]['type']=='start' or process_graph.node[node]['type']=='end':
tasks_list.append([node])
else:
... | code_fim | hard | {
"lang": "python",
"repo": "dtdi/Simod",
"path": "/support_modules/log_repairing/log_replayer.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> resp = list(filter(lambda x: process_graph.node[x]['name'] == task_name ,process_graph.nodes))
if len(resp)>0:
resp = resp[0]
else:
raise Exception('Task not found on bpmn structure...')
return resp
def find_start_finish_tasks(process_graph):
process_graph_data = pd.Da... | code_fim | hard | {
"lang": "python",
"repo": "dtdi/Simod",
"path": "/support_modules/log_repairing/log_replayer.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> planner = Hyperopt(show_progressbar=show_progressbar)
planner.set_param_space(param_space=two_param_space)
param = planner.ask()
value = ParameterVector().from_dict({'objective': 0.})
obs = Observations()
obs.add_observation(param, value)
planner.tell(observations=obs)<|fim_prefix|># repo: priyansh... | code_fim | medium | {
"lang": "python",
"repo": "priyansh-1902/olympus",
"path": "/tests/test_planners/test_planner_hyperopt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: priyansh-1902/olympus path: /tests/test_planners/test_planner_hyperopt.py
#!/usr/bin/env python
import pytest
from olympus import Observations, ParameterVector
from olympus.planners import Hyperopt
<|fim_suffix|> planner = Hyperopt(show_progressbar=show_progressbar)
planner.set_param_space(pa... | code_fim | medium | {
"lang": "python",
"repo": "priyansh-1902/olympus",
"path": "/tests/test_planners/test_planner_hyperopt.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zkn1163691192/DAPPLE path: /bert/utils/hooks/hooks_utils.py
import tensorflow as tf
class LoggingTensorHook(tf.train.SessionRunHook):
"""Self-defined Hook for logging."""
def __init__(self, tensors, samples_per_step=1, every_n_iters=100):
self._tensors = tensors
self._samples_per_s... | code_fim | medium | {
"lang": "python",
"repo": "zkn1163691192/DAPPLE",
"path": "/bert/utils/hooks/hooks_utils.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return tf.train.SessionRunArgs(self._tensors)
def after_run(self, run_context, run_values):
_ = run_context
tensor_values = run_values.results
stale_global_step = tensor_values['global_step']
if self._timer.should_trigger_for_step(stale_global_step + 1):
global_step = run_cont... | code_fim | medium | {
"lang": "python",
"repo": "zkn1163691192/DAPPLE",
"path": "/bert/utils/hooks/hooks_utils.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> result_docs = {}
index_result = self._search_tokens(tokens_list)
for token in index_result.keys():
for doc in index_result[token]:
# search if exists:
if doc in result_docs.keys():
result_docs[doc][token] = index_resu... | code_fim | hard | {
"lang": "python",
"repo": "MagnunAVF/Python-Based-Search-Engine",
"path": "/buscasrc/core/database.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MagnunAVF/Python-Based-Search-Engine path: /buscasrc/core/database.py
# coding: utf-8
import os
class Database:
"""
Entity that is responsable for store the app data
"""
def __init__(self):
self.documents = {}
self.inverted_index = {}
def search(self, token... | code_fim | hard | {
"lang": "python",
"repo": "MagnunAVF/Python-Based-Search-Engine",
"path": "/buscasrc/core/database.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
wf = Workflow()
sys.exit(wf.run(main))<|fim_prefix|># repo: lewiszlw/website path: /search.py
# coding: utf-8
import website
import sys, json
from workflow import Workflow
<|fim_middle|>def main(wf):
website_obj = website.Website()
if wf.args == None or wf.arg... | code_fim | hard | {
"lang": "python",
"repo": "lewiszlw/website",
"path": "/search.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lewiszlw/website path: /search.py
# coding: utf-8
import website
import sys, json
from workflow import Workflow
def main(wf):
<|fim_suffix|>if __name__ == "__main__":
wf = Workflow()
sys.exit(wf.run(main))<|fim_middle|> website_obj = website.Website()
if wf.args == None or wf.arg... | code_fim | hard | {
"lang": "python",
"repo": "lewiszlw/website",
"path": "/search.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> website_obj = website.Website()
if wf.args == None or wf.args == []:
query = ""
else:
query = wf.args[0].strip().replace("\\", "")
sites = website_obj.query(query)
for site in sites:
wf.add_item(title=site["name"], subtitle=site["url"], arg=site["url"], valid=Tr... | code_fim | medium | {
"lang": "python",
"repo": "lewiszlw/website",
"path": "/search.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>app_name = "sample"
router = routers.DefaultRouter()
router.register(r"authors/", views.AuthorViewSet)
router.register(r"books/", views.BookViewSet)
urlpatterns = router.urls<|fim_prefix|># repo: unicef/unicef-attachments path: /tests/demoproject/demo/sample/urls.py
from rest_framework import routers
... | code_fim | easy | {
"lang": "python",
"repo": "unicef/unicef-attachments",
"path": "/tests/demoproject/demo/sample/urls.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: unicef/unicef-attachments path: /tests/demoproject/demo/sample/urls.py
from rest_framework import routers
from demo.sample import views
<|fim_suffix|>urlpatterns = router.urls<|fim_middle|>app_name = "sample"
router = routers.DefaultRouter()
router.register(r"authors/", views.AuthorViewSet)
ro... | code_fim | medium | {
"lang": "python",
"repo": "unicef/unicef-attachments",
"path": "/tests/demoproject/demo/sample/urls.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns = router.urls<|fim_prefix|># repo: unicef/unicef-attachments path: /tests/demoproject/demo/sample/urls.py
from rest_framework import routers
<|fim_middle|>from demo.sample import views
app_name = "sample"
router = routers.DefaultRouter()
router.register(r"authors/", views.AuthorViewSet)
ro... | code_fim | medium | {
"lang": "python",
"repo": "unicef/unicef-attachments",
"path": "/tests/demoproject/demo/sample/urls.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># register command
# invoke this via saying `!roll 1 100` in channel
# or `!roll 1 100 5` to dice 5 times once
@bot.command(name='roll')
async def roll(msg: TextMsg, t_min: str, t_max: str, n: str = 1):
result = [random.randint(int(t_min), int(t_max)) for i in range(int(n))]
await msg.reply(f'you ... | code_fim | hard | {
"lang": "python",
"repo": "hang333/khl.py",
"path": "/example/ex03_cmd_args/ex03.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hang333/khl.py path: /example/ex03_cmd_args/ex03.py
import json
import random
from khl import TextMsg, Bot, Cert
# load config from config/config.json, replace `path` points to your own config file
# config template: `./config/config.json.example`
with open('./config/config.json', 'r', encoding... | code_fim | medium | {
"lang": "python",
"repo": "hang333/khl.py",
"path": "/example/ex03_cmd_args/ex03.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# register command
# invoke this via saying `!roll 1 100` in channel
# or `!roll 1 100 5` to dice 5 times once
@bot.command(name='roll')
async def roll(msg: TextMsg, t_min: str, t_max: str, n: str = 1):
result = [random.randint(int(t_min), int(t_max)) for i in range(int(n))]
await msg.reply(f'you... | code_fim | medium | {
"lang": "python",
"repo": "hang333/khl.py",
"path": "/example/ex03_cmd_args/ex03.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ShuguangSun/allocation path: /allocation/adaptive_randomization.py
"""
Randomization is a module that provides functions to create random group
assignments to be used in clinical trials
"""
import math
import random
# import scipy.stats as stats
# A Response adaptive randomization technique
d... | code_fim | hard | {
"lang": "python",
"repo": "ShuguangSun/allocation",
"path": "/allocation/adaptive_randomization.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cut = math.sqrt(pC) / (math.sqrt(pC) + math.sqrt(pT))
test = random.random()
if test < cut:
group = control_name
else:
group = treatment_name
return group
# A Response adaptive randomization technique
def double_biased_coin_urn(
control_success,
control_trial... | code_fim | hard | {
"lang": "python",
"repo": "ShuguangSun/allocation",
"path": "/allocation/adaptive_randomization.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lusccc/mise.py path: /mise/constants.py
from pytz import timezone
SEOUL_CODES = [
111121,
111123,
111131,
111141,
111142,
111151,
111152,
111161,
111171,
111181,
111191,
111201,
111212,
111221,
111231,
111241,
111251,
111261... | code_fim | hard | {
"lang": "python",
"repo": "lusccc/mise.py",
"path": "/mise/constants.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>"영등포구": "yeongdeungpo",
"동작구": "dongjak",
"관악구": "gwanak",
"강남구": "gangnam",
"서초구": "seocho",
"송파구": "songpa",
"강동구": "gangdong",
"금천구": "geumcheon",
"강북구": "gangbuk",
"양천구": "yangcheon",
"노원구": "nowon",
}
SEOUL_STATIONS = dict(zip(SEOUL_NAMES, SEOUL_CODES))
SEOUL... | code_fim | hard | {
"lang": "python",
"repo": "lusccc/mise.py",
"path": "/mise/constants.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>_NAMES_ENGDICT = {
"중구": "jung",
"종로구": "jongno",
"용산구": "yongsan",
"광진구": "gwangjin",
"성동구": "seongdong",
"중랑구": "jungnang",
"동대문구": "dongdaemun",
"성북구": "seongbuk",
"도봉구": "dobong",
"은평구": "eunpyeong",
"서대문구": "seodaemun",
"마포구": "mapo",
"강서구": "gangse... | code_fim | hard | {
"lang": "python",
"repo": "lusccc/mise.py",
"path": "/mise/constants.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> steps = [{'Name': 'Debugging', 'ActionOnFailure': 'TERMINATE_CLUSTER',
'HadoopJarStep': {'Jar': 'command-runner.jar',
'Args': ['state-pusher-script']}}]
results = client.run_job_flow(Name=args['<NAME>'],
... | code_fim | hard | {
"lang": "python",
"repo": "cloudmesh-community/sp19-516-122",
"path": "/project-code/cloudmesh.emr/cloudmesh/emr/api/manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> client = self.get_client()
results = client.describe_cluster(ClusterId=args['<CLUSTERID>'])
return results['Cluster']
def stop_cluster(self, args):
client = self.get_client()
client.terminate_job_flows(JobFlowIds=[args['<CLUSTERID>']])
results = {"clo... | code_fim | hard | {
"lang": "python",
"repo": "cloudmesh-community/sp19-516-122",
"path": "/project-code/cloudmesh.emr/cloudmesh/emr/api/manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cloudmesh-community/sp19-516-122 path: /project-code/cloudmesh.emr/cloudmesh/emr/api/manager.py
import boto3
from cloudmesh.management.configuration.config import Config
class Manager(object):
def __init__(self):
return
def list(self, parameter):
print("list", paramete... | code_fim | hard | {
"lang": "python",
"repo": "cloudmesh-community/sp19-516-122",
"path": "/project-code/cloudmesh.emr/cloudmesh/emr/api/manager.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ball6847/snipt path: /snipt/wsgi.py
"""
WSGI config for myproject project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.6/howto/deployment/wsgi/
"""
<|fim_suffix|>
# @todo check if sett... | code_fim | hard | {
"lang": "python",
"repo": "ball6847/snipt",
"path": "/snipt/wsgi.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# @todo check if settings.DEBUG is True or False
# setup werkzerg
application = DebuggedApplication(application, evalex=True)
# error page handling
def null_technical_500_response(request, exc_type, exc_value, tb):
raise exc_type, exc_value, tb
django.views.debug.technical_500_response = null_techn... | code_fim | medium | {
"lang": "python",
"repo": "ball6847/snipt",
"path": "/snipt/wsgi.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return "seen_date" in self.data
def set_seen(self):
self.seen_date = dates.now_str()
@property
def action(self):
return self.data.get("action")
@action.setter
def action(self, action_url):
self.data["action"] = action_url
@property
def classi... | code_fim | medium | {
"lang": "python",
"repo": "DOAJ/doaj",
"path": "/portality/models/notifications.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DOAJ/doaj path: /portality/models/notifications.py
from portality.dao import DomainObject
from portality.lib import dates
class Notification(DomainObject):
"""~~Notification:Model->DomainObject:Model~~"""
__type__ = "notification"
def __init__(self, **kwargs):
super(Notific... | code_fim | hard | {
"lang": "python",
"repo": "DOAJ/doaj",
"path": "/portality/models/notifications.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kuanfandevops/tfrs path: /backend/api/fixtures/operational/0023_add_renewable_naptha.py
from django.db import transaction
from api.management.data_script import OperationalDataScript
from api.models.ApprovedFuel import ApprovedFuel
from api.models.DefaultCarbonIntensityCategory import \
Defa... | code_fim | hard | {
"lang": "python",
"repo": "kuanfandevops/tfrs",
"path": "/backend/api/fixtures/operational/0023_add_renewable_naptha.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> provisions = ApprovedFuelProvision.objects.filter(
fuel__name="Ethanol"
)
for provision in provisions:
ApprovedFuelProvision.objects.create(
fuel_id=fuel.id,
provision_act_id=provision.provision_act_id,
determ... | code_fim | hard | {
"lang": "python",
"repo": "kuanfandevops/tfrs",
"path": "/backend/api/fixtures/operational/0023_add_renewable_naptha.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zhouqiw/tensor2tensor path: /tensor2tensor/models/long_answer.py
# coding=utf-8
# Copyright 2017 The Tensor2Tensor Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License... | code_fim | hard | {
"lang": "python",
"repo": "zhouqiw/tensor2tensor",
"path": "/tensor2tensor/models/long_answer.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>@registry.register_hparams
def long_answer_base():
"""Set of hyperparameters.
Returns:
a hparams object
"""
hparams = common_hparams.basic_params1()
hparams.hidden_size = 1024
hparams.batch_size = 8192
hparams.max_length = 8192
hparams.dropout = 0.0
hparams.batching_mantissa_bits = ... | code_fim | hard | {
"lang": "python",
"repo": "zhouqiw/tensor2tensor",
"path": "/tensor2tensor/models/long_answer.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if epoch %2 == 0:
checkpoint_name = os.path.join( output_dir, 'cp1_epoch'+str(epoch)+'.ckpt')
save_path = saver.save(sess, checkpoint_name)
np.save( os.path.join( output_dir,'logs','train_loss.npy'), np.asarray(train_loss))
np.save( os.path.join( out... | code_fim | hard | {
"lang": "python",
"repo": "batmanlab/Explanation_by_Progressive_Exaggeration",
"path": "/train_classifier.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: batmanlab/Explanation_by_Progressive_Exaggeration path: /train_classifier.py
import numpy as np
import pandas as pd
import sys
import os
import pdb
import yaml
import tensorflow as tf
from classifier.DenseNet import pretrained_classifier
from utils import read_data_file, load_images_and_labels
i... | code_fim | hard | {
"lang": "python",
"repo": "batmanlab/Explanation_by_Progressive_Exaggeration",
"path": "/train_classifier.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>'expression\nd'exposant n"+
"\nSans le n : 7 est 7^n"+
"\nEt 7^2n = 49^n soit 49")
exp = int(input("= "))
print("Donnez la suite de l'expression,\nde facteur n sans le n: \n7 est 7*n")
fac = int(input("= "))
print("Valeur en + :")
pls = int(input("= "))
print("Donne... | code_fim | hard | {
"lang": "python",
"repo": "Overengined/Python-for-Numworks",
"path": "/scripts/maths/congtest.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>onnez le modulo :")
mod = int(input("mod = "))
print("Résultats :")
for n in range(1,max(exp+1, mod+1)):
print(str(exp) + "^" + str(n)+"+"+str(fac)+"*"+ str(n) + "+"+str(pls) + " = " + str(r(exp**n+fac*n+pls,mod)) + " [" + str(mod)+"]")
else:
print("t'es con ou quoi ?")<|fi... | code_fim | hard | {
"lang": "python",
"repo": "Overengined/Python-for-Numworks",
"path": "/scripts/maths/congtest.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Overengined/Python-for-Numworks path: /scripts/maths/congtest.py
from mathsup import cong,r
print("1: x en facteur\n2: n en exposant\n")
s = int(input(""))
if s == 1:
#x en facteur
print("Donnez l'expression\nde facteur x"+
"\nSans le x : 7 est 7x")
exp = int(input("=... | code_fim | hard | {
"lang": "python",
"repo": "Overengined/Python-for-Numworks",
"path": "/scripts/maths/congtest.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rospy.init_node('controller',anonymous = True)
rospy.Subscriber('destination',FloatList,callback)
rospy.spin()
if __name__ == '__main__':
try:
controller()
except rospy.ROSInterruptException:
pass<|fim_prefix|># repo: chula-eic/Neo-FRA path: /cru_robot/controller.py
#!/usr/bin/env python3
impor... | code_fim | medium | {
"lang": "python",
"repo": "chula-eic/Neo-FRA",
"path": "/cru_robot/controller.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chula-eic/Neo-FRA path: /cru_robot/controller.py
#!/usr/bin/env python3
import rospy
from std_msgs.msg import String
from cru_robot.msg import FloatList
<|fim_suffix|>if __name__ == '__main__':
try:
controller()
except rospy.ROSInterruptException:
pass<|fim_middle|>pub = rospy.Publisher('d... | code_fim | hard | {
"lang": "python",
"repo": "chula-eic/Neo-FRA",
"path": "/cru_robot/controller.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Project(troposphere.iot1click.Project, Mixin):
def __init__(self,
title, # type: str
template=None, # type: Template
validation=True, # type: bool
PlacementTemplate=REQUIRED, # type: _PlacementTemplate
Descripti... | code_fim | hard | {
"lang": "python",
"repo": "tsuttsu305/troposphere_mate-project",
"path": "/troposphere_mate/iot1click.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Project(troposphere.iot1click.Project, Mixin):
def __init__(self,
title, # type: str
template=None, # type: Template
validation=True, # type: bool
PlacementTemplate=REQUIRED, # type: _PlacementTemplate
Descript... | code_fim | hard | {
"lang": "python",
"repo": "tsuttsu305/troposphere_mate-project",
"path": "/troposphere_mate/iot1click.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tsuttsu305/troposphere_mate-project path: /troposphere_mate/iot1click.py
# -*- coding: utf-8 -*-
"""
This code is auto generated from troposphere_mate.code_generator.__init__.py scripts.
"""
import sys
if sys.version_info.major >= 3 and sys.version_info.minor >= 5: # pragma: no cover
from ... | code_fim | hard | {
"lang": "python",
"repo": "tsuttsu305/troposphere_mate-project",
"path": "/troposphere_mate/iot1click.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sgk98/Pegasos path: /pegasos.py
import numpy as np
import math
import random
from sklearn.datasets import make_classification
import matplotlib.pyplot as plt
def solve(X,Y,lm,n_iter=100):
C=len(Y)
W=np.array([0 for i in range(len(X[0]))])
<|fim_suffix|>
if __name__=="__main__":
separable =... | code_fim | hard | {
"lang": "python",
"repo": "sgk98/Pegasos",
"path": "/pegasos.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i in range(len(X)):
res=np.dot(W.T,X[i])
if res*Y[i]>=0:
correct+=1.0
total+=1.0
print(correct/total)<|fim_prefix|># repo: sgk98/Pegasos path: /pegasos.py
import numpy as np
import math
import random
from sklearn.datasets import make_classification
import matplotlib.pyplot as plt
def sol... | code_fim | hard | {
"lang": "python",
"repo": "sgk98/Pegasos",
"path": "/pegasos.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sureleo/leetcode path: /archive/python/LRUCache.py
class Node:
def __init__(self, key, value):
self.key = key
self.value = value
self.prev = None
self.next = None
class DoublyLinkedList:
def __init__(self):
self.head = None
self.tail = None... | code_fim | hard | {
"lang": "python",
"repo": "sureleo/leetcode",
"path": "/archive/python/LRUCache.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if key in self.D:
self.D[key].value = value
self.cache.removeNode(self.D[key])
self.cache.addFirst(self.D[key])
else:
if self.size < self.capacity:
self.size += 1
else:
del self.D[self.cache.tail.ke... | code_fim | hard | {
"lang": "python",
"repo": "sureleo/leetcode",
"path": "/archive/python/LRUCache.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: harshvardhanp/SMS_sysinfo path: /sms_sysinfo.py
#!/usr/bin/python3
from twilio.rest import Client
import sys
import platform
import time
account = "XXXXXXXXXXXXXXXXXXXXXXXXXX"
token = "XXXXXXXXXXXXXXXXXXXXXXXXXXXX"
twilio_cell = 'XXXXXXXXXXXXXXX'
my_cell = 'XXXXXXXXXXXX'
client = Client(accou... | code_fim | medium | {
"lang": "python",
"repo": "harshvardhanp/SMS_sysinfo",
"path": "/sms_sysinfo.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
import netifaces as ni
os_name = platform.platform()
sys_type = platform.machine()
msg = "OS Name:{}\nSystem type:{}\n".format(os_name, sys_type)
v = ''
for i in ni.interfaces():
ni.ifaddresses(i)
v += ni.ifaddresses(i)[ni.AF_INET][0]['addr'] + "\t"
v += ... | code_fim | hard | {
"lang": "python",
"repo": "harshvardhanp/SMS_sysinfo",
"path": "/sms_sysinfo.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> import wmi
import datetime
w = wmi.WMI()
sysinfo = w.Win32_ComputerSystem()[0]
host_name = sysinfo.DNSHostName
os_name = platform.platform()
sys_type = platform.machine()
msg = "Computer Name:{}\nOS Name:{}\nSystem type:{}\n".format(host_name, os_name, sys_type)
msg +=... | code_fim | medium | {
"lang": "python",
"repo": "harshvardhanp/SMS_sysinfo",
"path": "/sms_sysinfo.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
return torch.optim.SGD(parameters, lr = lr, momentum = 0.9, weight_decay=weight_decay);<|fim_prefix|># repo: gianlucapagliara/Benchmark-Analysis-of-Speaker-Recognition-Techniques path: /graphs/optimizers/sgd.py
#! /usr/bin/python
# -*- encoding: utf-8 -*-
import torch
<|fim_middle|>def Optimizer(para... | code_fim | easy | {
"lang": "python",
"repo": "gianlucapagliara/Benchmark-Analysis-of-Speaker-Recognition-Techniques",
"path": "/graphs/optimizers/sgd.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gianlucapagliara/Benchmark-Analysis-of-Speaker-Recognition-Techniques path: /graphs/optimizers/sgd.py
#! /usr/bin/python
# -*- encoding: utf-8 -*-
<|fim_suffix|> return torch.optim.SGD(parameters, lr = lr, momentum = 0.9, weight_decay=weight_decay);<|fim_middle|>import torch
def Optimizer(param... | code_fim | medium | {
"lang": "python",
"repo": "gianlucapagliara/Benchmark-Analysis-of-Speaker-Recognition-Techniques",
"path": "/graphs/optimizers/sgd.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iris-garcia/sysdig-sdk-python path: /sdcclient/_monitor.py
import json
import re
import requests
from sdcclient._common import _SdcCommon
from sdcclient.monitor import EventsClientV2, DashboardsClientV3
class SdMonitorClient(DashboardsClientV3, EventsClientV2, _SdcCommon):
def __init__(s... | code_fim | hard | {
"lang": "python",
"repo": "iris-garcia/sysdig-sdk-python",
"path": "/sdcclient/_monitor.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> **Example**
`examples/update_alert.py <https://github.com/draios/python-sdc-client/blob/master/examples/update_alert.py>`_
'''
if 'id' not in alert:
return [False, "Invalid alert format"]
res = requests.put(self.url + '/api/alerts/' + str(alert['id'... | code_fim | hard | {
"lang": "python",
"repo": "iris-garcia/sysdig-sdk-python",
"path": "/sdcclient/_monitor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> **Success Return Value**
``None``.
**Example**
`examples/delete_alert.py <https://github.com/draios/python-sdc-client/blob/master/examples/delete_alert.py>`_
'''
if 'id' not in alert:
return [False, 'Invalid alert format']
res =... | code_fim | hard | {
"lang": "python",
"repo": "iris-garcia/sysdig-sdk-python",
"path": "/sdcclient/_monitor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: njmhendrix/grand-challenge.org path: /app/grandchallenge/components/validators.py
from django.core.exceptions import SuspiciousFileOperation, ValidationError
from django.utils._os import safe_join
def validate_safe_path(value):
"""Ensures that the path is safe and normalised."""
base = ... | code_fim | medium | {
"lang": "python",
"repo": "njmhendrix/grand-challenge.org",
"path": "/app/grandchallenge/components/validators.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.