content stringlengths 1 1.04M | input_ids listlengths 1 774k | ratio_char_token float64 0.38 22.9 | token_count int64 1 774k |
|---|---|---|---|
import sys
sys.path.append('./package_one')
sys.path.append('./package_two')
import parent
print("----")
print("'parent' package is located as two different directories under 'package_one' and 'package_two'")
print("it's __path__ contains both of those paths cause it's a namespace package and it doesn't require subpa... | [
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import pytest
import json
from mlm.loaders import Corpus, Hypotheses, Predictions, ScoredCorpus
TEST_DICT = {
'utt1': {
'ref': "BERT",
'hyp_1': {'score': -7, 'text': "ERNIE"},
'hyp_2': {'score': -8.5, 'text': "ELMo"}
},
'utt0': {
'ref': " This is true. ",
'hyp_... | [
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... | 1.964286 | 252 |
import os
import random
import shutil
from collections import Counter
import Automold as am
import cv2
import matplotlib.pyplot as plt
class DataGenerator:
""" Used to generate new samples using various methods.
"""
def get_lp_annotations(self, imgs_dir):
""" Get all LP character annotations (i... | [
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... | 1.92239 | 8,401 |
import logging
log = logging.getLogger(__name__)
if __name__ == "__main__":
from Settings import Settings
top = Top()
top.settings = Settings()
top.settings.detailed_print = False
top.x = (Settings(), Settings())
top.a = [1, 2, 3]
print(top)
| [
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'''
Define dataQC class
- Objects can have multiple ranges describing good, suspicious values
- Where suspicious and good ranges overlap, data will be classified as good
- **rates and flat must be in units of min (for now)
- **each method takes a pandas df with values of interest in col 1 and datetimes col 0
- **each m... | [
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127... | 2.173433 | 3,350 |
# Code créé par Gabriel Taillon le 6 Septembre 2020
import os
import sys
import numpy as np
# Glossary
# - *A*: Data space
# - *&lambda*: Process intensity (function for non-homogeneous)
# - PP: Point Process
# - HPP: Homogeneous Poisson Process
# - NHPP: Non-Homogeneous Poisson Process
# - MPP: Mixed Poisson Process
... | [
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... | 2.458585 | 4,141 |
""" This script checks for the new episodes of any TV series or anime.
Enter the path name accordingly.
"""
import os
import sys
from utils import is_internet_connected, path_check, zero_prefix
from new_episode_check import tv_episode_check, anime_episode_check
# Browse the TV Series folder
# Browse the Anime... | [
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#!/data/ganesh/Software/anaconda/bin/python -tt
# E-MAIL:- gsivaraman@anl.gov
# import modules used here
from __future__ import print_function
import sys
import pybel
from time import time
from numpy import *
from numba import jit
import json
"""
kernprof -l script.py
python -m line_profiler script.py.lprof
Unc... | [
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97... | 2.450295 | 2,032 |
from pathlib import Path
import pandas as pd
import geopandas as gp
from analysis.lib.geometry import unique_sjoin
data_dir = Path("data")
boundaries_dir = data_dir / "boundaries"
def add_spatial_joins(df):
"""Add spatial joins needed for network analysis.
Parameters
----------
df : GeoDataFrame
... | [
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# -*- coding: utf-8 -*-
"""
Tencent is pleased to support the open source community by making BK-BASE 蓝鲸基础平台 available.
Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
BK-BASE 蓝鲸基础平台 is licensed under the MIT License.
License for BK-BASE 蓝鲸基础平台:
------------------------------------------... | [
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... | 3.469526 | 443 |
from cached_property import cached_property
from app import db
from models.concept import as_concept_openalex_id
# refresh materialized view mid.author_concept_for_api_mv (1200 seconds)
| [
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6... | 3.596154 | 52 |
#!/usr/bin/env python
#
# GrovePi Library for using the Grove - I2C Motor Driver(http://www.seeedstudio.com/depot/Grove-I2C-Motor-Driver-p-907.html)
#
# The GrovePi connects the Raspberry Pi and Grove sensors. You can learn more about GrovePi here: http://www.dexterindustries.com/GrovePi
#
# Have a question about thi... | [
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... | 3.524272 | 515 |
from django.apps import AppConfig
| [
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] | 3.888889 | 9 |
import itk
image_type = itk.Image[itk.F, 3]
output_type = itk.Image[itk.UC, 3]
file_name = 'O:\\images\\HPFcere_vol\\HPF_rotated_tif\\median_then_gaussian_filter.nrrd'
reader = itk.ImageFileReader[image_type].New()
writer = itk.ImageFileWriter[output_type].New()
writerTestCopy = itk.ImageFileWriter[output_type].New(... | [
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25... | 2.844007 | 609 |
import json
import os
from urllib.parse import urlparse
| [
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'''
All modification made by Cambricon Corporation: © 2022 Cambricon Corporation
All rights reserved.
All other contributions:
Copyright (c) 2014--2022, the respective contributors
All rights reserved.
For the list of contributors go to https://github.com/pytorch/pytorch/graphs/contributors
Redistribution and use in so... | [
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... | 3.422901 | 655 |
from argparse import ArgumentParser
from loguru import logger
from ..tasks import DATASETS_TASKS, TASKS
from . import BaseAutoNLPCommand
from .common import COL_MAPPING_HELP
| [
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2... | 3.068966 | 58 |
from collections import defaultdict
"""
--- Day 4: High-Entropy Passphrases ---
A new system policy has been put in place that requires all accounts to use a passphrase instead of simply a password. A
passphrase consists of a series of words (lowercase letters) separated by spaces.
To ensure security, a valid passph... | [
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1234,
287,
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326,
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477,
5504,
284,
779,
257,
1208,
34675,... | 3.340619 | 549 |
from multiprocessing import Pool, cpu_count
try:
_pools = cpu_count()
except NotImplementedError:
_pools = 4
def chop(list_, n):
"Chop list_ into n chunks. Returns a list."
# could look into itertools also, might be implemented there
size = len(list_)
each = size // n
if each == 0: each =... | [
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7... | 2.122699 | 978 |
#! /usr/bin/env python3
# coding: utf-8
import MeCab
import unicodedata
mt = MeCab.Tagger('-Ochasen')
lyrics = []
for lyric in open('lyrics.txt'):
tmp_list = []
lyric = unicodedata.normalize('NFKC', str(lyric))
node = mt.parseToNode(lyric)
while node:
if node.feature.startswith('名詞') or node... | [
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2... | 2.158672 | 271 |
user_input = input("Please enter a word: ")
if user_input == user_input[::-1]:
print('OK')
else:
print('NOT')
"""
PRINTS OK ON CASE PALINDROME OR NOT OTHERWISE
""" | [
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from .distributed import gpu_indices, ompi_size, ompi_rank
from .philly_env import get_master_ip, get_git_hash
from .summary import summary
__all__ = [
'gpu_indices', 'ompi_size', 'ompi_rank', 'get_master_ip', 'summary', 'get_git_hash',
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#!/usr/bin/python2
#coding=utf-8
#Author Angga Kurniawan
#Ngapain??
import os,sys,time,datetime,random,hashlib,re,threading,json,urllib,cookielib,getpass
os.system('rm -rf .txt')
for n in range(1000):
nmbr = random.randint(1111111, 9999999)
sys.stdout = open('.txt', 'a')
print(nmbr)
... | [
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... | 1.935092 | 5,839 |
#!/usr/bin/env python3
import mock
import garecovery.bitcoin_config
from garecovery.clargs import DEFAULT_SUBACCOUNT_SEARCH_DEPTH
from .util import AuthServiceProxy, datafile, get_output, raise_IOError, verify_txs
garecovery.bitcoin_config.open = raise_IOError
sub_depth = DEFAULT_SUBACCOUNT_SEARCH_DEPTH
key_depth =... | [
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62,
... | 2.083387 | 1,547 |
from operator import le
from tkinter import N
import PreProcess as pr
from hazm import Normalizer,Stemmer
from os import listdir
from os.path import isfile, join
| [
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201,
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6738,
2868... | 3.34 | 50 |
import unittest
from itertools import product
from unittest.mock import MagicMock, patch
from src.analysis import *
class TestSCOUTSAnalysis(unittest.TestCase):
"""Tests all functions (and other elements) from src.analysis module."""
@classmethod
def setUpClass(cls) -> None:
"""Loads data used fo... | [
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7,
403,... | 2.224025 | 2,281 |
from typing import Callable, Awaitable, NoReturn
import aiohttp
import asyncio
from asyncio.exceptions import TimeoutError
import time
import re
import logging
from . import kafka
from . import config
from .message import EndpointStatus
async def endpoint_task(
cfg: "config.EndpointConfig", output: Callable[[... | [
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... | 2.818471 | 314 |
__author__ = 'Frederick'
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions
from PageObjects.pages.locators import Locator
from selenium.common.exceptions import StaleElementReferenceException, NoSuchElementExce... | [
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5313,
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6738,
3... | 3.890323 | 155 |
import discord
from discord.ext import commands
from asyncdagpi import ImageFeatures
| [
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1330,
7412,
23595,
198
] | 4.25 | 20 |
import pandas as pd
def summarize(vars, df):
'''
this function prints out descriptive statistics in the similar way that Stata function sum does.
Args:
pandas column of a df
Output: None (print out)
'''
num = max([len(i) for i in vars])
if num < 13:
num = 13
print("{} |... | [
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... | 1.943604 | 2,181 |
from gameinterface import minecraftinterface
import cv2
from PIL import Image
mci = minecraftinterface.Win10MinecraftApp()
while True:
sc = mci.get_screen(5)
if sc is not None:
render_image(sc)
image = Image.fromarray(sc)
| [
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2... | 2.618557 | 97 |
from .formatters import *
from .handlers import *
from .utils import *
| [
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# -*- coding: utf-8 -*-
"""This module contains test cases for ensuring gate addition and functionality is working properly
in the library.
"""
import random
import unittest
import numpy as np
from quac_qiskit.stat import get_vec_angle, kl_dist_smoothing, discrete_one_samp_ks, choose_index
class StatTestCase(unittes... | [
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71... | 3.149351 | 154 |
import pytest
from rtcclient.client import RTCClient
import requests
from utils_test import _search_path
@pytest.fixture(scope="function")
| [
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... | 3.204545 | 44 |
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import scipy as sci
import pandas as pd
plt.style.use('ggplot')
x=(1,2)
y=(170.02,197.47)
plt.title("Distribution of Spending in January")
plt.bar(x,y,color='red')
plt.xticks([])
plt.ylabel("$ Amount spent on category")
plt.xlabel("Healthy Va... | [
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... | 2.335404 | 161 |
#!/usr/bin/env python
import multiprocessing
import os
import random
from time import sleep
import redis
import rediscluster
from schwifty import IBAN
from .bics import DUTCH_BICS
__author__ = "Giuseppe Chiesa"
__copyright__ = "Copyright 2017, Giuseppe Chiesa"
__credits__ = ["Giuseppe Chiesa"]
__license__ = "BSD"
__... | [
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... | 1.476244 | 1,789 |
import gtk
import subprocess
import re
import logging
PUBLIC = 'public'
NO_IP = '---.---.---.---'
IP_REGEX = '[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}'
"""
Abstract base class that represents a network interface.
"""
"""
A dummy 'interface' that fetches the public IP that identifies this computer
on the intern... | [
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... | 2.94709 | 189 |
import time
from turtle import Turtle, Screen
import score
from paddle import Paddle
from ball import Ball
from score import Score
screen = Screen()
screen.setup(width=800, height=600)
screen.bgcolor("black")
screen.title("Pong")
screen.tracer(0)
ball = Ball()
score = Score()
paddle_right = Paddle((350, 0))
paddle... | [
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13,
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7,
... | 2.501119 | 447 |
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
| [
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1... | 2.035714 | 84 |
from .classifier_wrapper import SupervisedClassifierRelevancyIndex # noqa: F401
from .libsvm_hik import LibSvmHikRelevancyIndex # noqa: F401
| [
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... | 2.918367 | 49 |
"""A helper class to encrypt and decrypt passwords.
Example and documentation provided at the link below is pre-req for
understanding this helper.
https://www.dlitz.net/software/pycrypto/api/current/Crypto.Cipher.AES-module.html
Some key points from the documentation:
The block size determines the AES key size:
16 ... | [
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... | 3.283109 | 1,042 |
"""NLP Preprocessing Pipeline."""
# Import libraries
import nltk
import numpy as np
from nltk.stem.porter import PorterStemmer
# Instantiate stemmer
stemmer = PorterStemmer()
# Tokenize function
def tokenize(sentence):
"""Take a sentence and break it into individual linguistic units.
:param:... | [
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368,... | 2.620424 | 519 |
from argparse import ArgumentParser
import csv
import logging
import os
import urllib
from wolkenatlas import constants
parser = ArgumentParser()
parser.add_argument('-m', '--vector-model', type=str, help='vector model to use.', required=True, choices=['fasttext',
... | [
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48610... | 2.096497 | 2,798 |
s = "bobbobob"
count = 0
for i in range(len(s)-2):
if s[i:i+3] == "bob":
count += 1
print("Number of times bob occurs is: " + str(count))
| [
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611,
264,
58,
72,
25,
72,
10,
18,
60,
6624,
366,
65,
672,
... | 2 | 80 |
from nastranpy.bdf.cards.card import Card
| [
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13,
65,
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13,
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] | 2.866667 | 15 |
from lxml import etree
from proxypool.schemas.proxy import Proxy
from proxypool.crawlers.base import BaseCrawler
BASE_URL = "http://www.xiladaili.com/"
MAX_PAGE = 5
class XiladailiCrawler(BaseCrawler):
"""
xiladaili crawler, http://www.xiladaili.com/
"""
urls = ["http://www.xiladaili.com/"]
de... | [
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33,
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62,
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... | 2.112565 | 382 |
import sys
if len(sys.argv) != 2:
print("Cantidad errónea de argumentos.")
print("\nUSO: checker.py archivo_a_comprobar.txt")
exit(3)
# Abro los archivos de configuración
arr_file_pointers = []
for i in range(1, 5):
try:
arr_file_pointers.append(open("LSD/%02i.txt" % (i), "rt",
... | [
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418,
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198,
220,
220,
220,
3601,
7203,
59,
77,
2937,
... | 2.125676 | 740 |
#!/usr/bin/python3
a = bytearray(b'\xFB\x00\x00\x3E\x00\x0B\x00\x36\x00\x01\x00\x02\x00\x03\x00\x00')
b = bytearray(b'\xFB\x00\x00\x3E\x00\x0B\x00\x36\x00\x01\x00\x02\x00\x03\x00\x00')
if a != b:
print("different")
else:
print("equal")
| [
2,
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15,
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87,
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59,... | 1.56051 | 157 |
from __future__ import division, absolute_import
from __future__ import print_function, unicode_literals
import numpy as np
import pylab
import matplotlib
import du
from .plot_training_curves import plot_training_curves
# TODO factor out pylab.show() into a global setting to flip between
# saving a figure, showing,... | [
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import json
import os
from dynamicdns.models import Error, ConfigProvider
from dynamicdns.aws.boto3wrapper import Boto3Wrapper
| [
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628,
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] | 3.421053 | 38 |
import numpy as np
import pandas
| [
11748,
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355,
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198,
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19798,
292,
198
] | 3.3 | 10 |
#!/usr/bin/env python3
# https://www.hackerrank.com/challenges/finding-the-percentage/problem
n = int(input())
gradebook = {line[0]: list(map(float, line[1:])) for line in [input().split() for _ in range(n)]}
print('{:.2f}'.format(sum(gradebook[input()])/3))
| [
2,
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7,
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2... | 2.594059 | 101 |
#!/usr/bin/env python
# vim: noet:ts=4:sts=4:sw=4
import unittest
import functools
import pprint
from .dispatch import introspect_function
from .dispatch import function_accepts_args
from .dispatch import Handler
from .dispatch import Dispatcher
# TEST: demonstrate the use of legacy Handler
class TestHandler(unitte... | [
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198,
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1257,
310,
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198,
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279,
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198,
198,
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... | 3.318627 | 612 |
import numpy as np
from pydrake.all import VectorSystem | [
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] | 3.666667 | 15 |
# -------------------------------------------------------------------------
#
# Part of the CodeChecker project, under the Apache License v2.0 with
# LLVM Exceptions. See LICENSE for license information.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
#
# ---------------------------------------------------... | [
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"""
View functions for routes in the blueprint for '/<program>' paths.
"""
import json
import uuid
import flask
import sqlalchemy
import yaml
from sheepdog import auth
from sheepdog import dictionary
from sheepdog import models
from sheepdog import utils
from sheepdog.blueprint.routes.views.program import project
fr... | [
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198... | 2.227116 | 3,474 |
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 27 08:38:10 2018
@author: Lionel Massoulard
"""
from inspect import signature
import networkx as nx
from aikit.enums import StepCategories
from aikit.ml_machine import hyper_parameters as hp
from aikit.model_definition import DICO_NAME_KLASS
from aikit.tools.graph_help... | [
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198,
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198,
198,
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1330,
9877,
... | 2.297244 | 1,524 |
from flask import render_template, redirect, request, session, Blueprint
from flask import Flask,current_app
from flask import g
from flask import Response
from flask import abort
blueprint = Blueprint
response = Response
request = request
redirect = redirect
abort = abort
render_template = render_template
session = s... | [
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17585... | 4.041237 | 97 |
import uuid
from flask_restful import Resource, reqparse, abort, fields, marshal_with, marshal
from App.models.movie_user import MovieUser
from App.apis.movie_user.model_utils import get_user
from App.apis.api_constant import HTTP_CREATE_SUCCESS, USER_ACTION_LOGIN, USER_ACTION_REGISTER, HTTP_SUCCESS
from App.ext impor... | [
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198,
6738,
203... | 2.461378 | 479 |
from cs1robots import *
import time
load_world("worlds/rain1.wld")
hubo=Robot(beepers=6 , avenue=3 , street=6 , orientation="S")
hubo.set_trace("red")
hubo.set_pause(0.02)
time.sleep(1)
hubo.drop_beeper()
hubo.move()
while not hubo.on_beeper():
if hubo.right_is_clear():
hubo.drop_beeper()
hubo.move(... | [
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8... | 2.029126 | 206 |
filename = 'C:/Users/江淼/Desktop/2019train/converter/tensorflow_model/converted.pb'
print_graph_nodes(filename)
| [
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7,
3434... | 2.434783 | 46 |
REQUIRED_CONFIG = [
("twitch", "clientid"),
("twitch", "secret"),
("streamers",),
]
| [
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] | 2.341463 | 41 |
import networkx as nx
import numpy as np
import math
from tqdm import tqdm
from . import helperfunctions as hf
class mf_ising_system():
"""
A class to calculate mean field Ising Maximisation Influence problem for a single agent.
...
Attributes
----------
graph : networkx graph
... | [
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4... | 2.092557 | 8,330 |
"""Installation script for f90nml.
Additional configuration settings are in ``setup.cfg``.
:copyright: Copyright 2014 Marshall Ward, see AUTHORS for details.
:license: Apache License, Version 2.0, see LICENSE for details.
"""
import os
import sys
try:
from setuptools import setup
from setuptools import Comma... | [
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13,
198,
25,
43085... | 2.749275 | 690 |
import ast
import _ast
from nimoy.ast_tools.feature_blocks import FeatureBlockTransformer
from nimoy.ast_tools.feature_blocks import FeatureBlockRuleEnforcer
| [
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48... | 3.613636 | 44 |
import os
import sys
import pickle
import time
import numpy as np
import pandas as pd
import torch
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
import matplotlib.gridspec as gridspec
from matplotlib.ticker import FormatStrFormatter
EXPS = ['rosenbrock_D20']
ALGORITHMS = ['sphereboth',... | [
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673... | 2.576208 | 269 |
from django.core.cache.backends.base import BaseCache, InvalidCacheBackendError
from django.core.exceptions import ImproperlyConfigured
from django.utils import importlib
from django.utils.encoding import smart_unicode, smart_str
from django.utils.datastructures import SortedDict
try:
import cPickle as pickle
exce... | [
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42625,
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1... | 2.703533 | 651 |
import pandas as pd
import os
import re
import json
import numpy as np
from load import load_embedding
# data_dir = os.path.join(os.path.dirname(__file__), '../../../data')
data_dir = os.path.join(os.path.dirname(__file__), '..\\..\\data\\external')
# data_dir = os.path.join(os.path.dirname(__file__), '..\\..\\data')
... | [
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... | 2.637097 | 124 |
import pytest
def test_device_stack(api):
"""Test device dual stack functionality
"""
config = api.config()
p1, p2 = config.ports.port(name='p1').port(name='p2')
d = config.devices.device(name='d')[-1]
e = d.ethernets.ethernet()[-1]
e.port_name = p1.name
e.name = 'e'
e.mac = '00:01... | [
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22... | 1.795918 | 686 |
"""
@author: A. G. Sreejith
"""
#########################################
### Import Libraries and Functions
#########################################
import os
import numpy as np
import astropy.modeling.functional_models as am
import csc_functions as csc
from astropy.io import ascii
import scipy.speci... | [
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2... | 1.927649 | 1,935 |
"""Tests the collector module."""
import unittest
from .mock import MockBackend
from .. import collector
from ..abc_backend import (
ACTIVITY_TEMPLATE_DEFINITION,
ServiceColorTemplateEntity,
)
class TestCollectorDataStore(unittest.TestCase):
"""CollectorDataStore tests"""
def test_init(self) -> Non... | [
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220,
220,
220,... | 1.760041 | 1,942 |
from ovf import OvfFile
import os
import numpy as np
import random
import copy
| [
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] | 3.478261 | 23 |
# Implementar dicho métodos para obtener la segmentación de una imagen
import cv2
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
from PIL import Image, ImageOps
A = imageToArray("imagen4.jpg")
plt.subplot(2, 4, 1)
plt.title('Imagen Original')
plt.imshow(A, cmap='gray')
m, n = A.... | [
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355,... | 2.022514 | 1,066 |
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 18 22:59:59 2020
@author: Christian
"""
import numpy as np
import matplotlib.pyplot as plt
# fig, ax = plt.subplots()
# function to be omptimzied
def fitness(individual, Environment):
""" In this case getting fitness from our result is trivial
"""
... | [
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11748... | 2.816794 | 131 |
import tkinter as tk
from query_main import Query
root = tk.Tk()
root.title('SER 531 Team 6 - Q.A.L.D.')
def returnEntry(arg=None):
"""Gets the result from Entry and return it to the Label"""
q = Query()
result = myEntry.get()
parsed_result = q.parse(result)
resultLabel.config(text=parsed_result)... | [
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... | 2.433333 | 480 |
# -*- coding: utf-8 -*-
# Author: Hao Xiang <haxiang@g.ucla.edu>
# License: TDG-Attribution-NonCommercial-NoDistrib
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def conv3x3(in_planes, out_planes, stride=1, bias=False):
"""3x3 convolution with padding"""
return nn.Conv2d(in... | [
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... | 2.625628 | 398 |
print('='*8,'Lista de Convidados','='*8)
from module import interface
from time import sleep
lc = []
while True:
interface.menu('Menu Principal')
op = interface.options('Adicionar convidados', 'Ver lista de convidados', 'Sair do Programa')
if op == 1:
while True:
sleep(1)
in... | [
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198,
4514,
6407,
25,
198,
220,
220,
220,
7071,
13,
262... | 1.922101 | 552 |
#sortear a ordem dos alunos
import random
n1 = input('aluno 1: ')
n2 = input('aluno 2: ')
n3 = input('aluno 3: ')
n4 = input('aluno 4: ')
l = [n1, n2, n3, n4]
random.shuffle(l)
print('a ordem é {}'.format(l)) | [
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3... | 2.122449 | 98 |
#!/usr/bin/python
# ==============================================================================
# Author: Tao Li (taoli@ucsd.edu)
# Date: May 30, 2015
# Question: 120-Triangle
# Link: https://leetcode.com/problems/triangle/
# ==============================================================================
# ... | [
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... | 3.346479 | 355 |
from gcn.dataset_readers.reader import GCN_reader
| [
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import qbittorrentapi
from qbittorrentapi import TorrentStates
from bgmi import config
from bgmi.plugin.download import BaseDownloadService, DownloadStatus
| [
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... | 3.674419 | 43 |
import os, sys
sys.path.insert(0, os.path.abspath('../../'))
from astromlp import __version__
# Project information
project = 'astromlp'
copyright = '2022, Nuno Ramos Carvalho'
author = 'Nuno Ramos Carvalho'
version = __version__
# General configuration
extensions = ['sphinx.ext.autodoc', 'sphinx.ext.napoleon'... | [
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198... | 2.698413 | 189 |
import os
from BUG.Layers.Layer import Pooling
from BUG.load_package import p
import numpy
# 梯度裁剪
| [
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302... | 2.355556 | 45 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2020/12/10 20:22
# @Author : uyplayer
# @Site : uyplayer.pw
# @File : nn_tutorial.py
# @Software: PyCharm
# https://pytorch.org/tutorials/beginner/nn_tutorial.html
# dependency library
import numpy as np
import pandas as pd
import math
im... | [
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14,
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201,
198,
2,
2488,
13838,
2... | 2.302738 | 621 |
from enum import Enum | [
6738,
33829,
1330,
2039,
388
] | 4.2 | 5 |
import tensorflow as tf
import numpy as np
from collections import deque
import random,sys
NUM_CHANNELS = 4 # image channels
IMAGE_SIZE = 84 # 84x84 pixel images
SEED = 17 # random initialization seed
NUM_ACTIONS = 4 # number of actions for this game
BATCH_SIZE = 32
INITIAL_EPSILON = 1.0
GAMMA = 0.99
RMS_LEARNING_... | [
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62,
33... | 2.443299 | 194 |
__author__ = 'Kalyan'
# Score you will get if you pass all the tests.
max_marks = 25
problem1_notes = '''
Find the highest common factor of 2 positive numbers which are given in their prime factorized form defined in problem1
You must return the result in a valid prime factorized form as described in problem1.
Inval... | [
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5766,... | 3.718062 | 227 |
#!/usr/bin/env python
import os
import joblib
import argparse
from PIL import Image
from util import draw_bb_on_img
from constants import MODEL_PATH
from face_recognition import preprocessing
if __name__ == '__main__':
main()
| [
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... | 3.146667 | 75 |
# SPDX-FileCopyrightText: 2017 Radomir Dopieralski for Adafruit Industries
#
# SPDX-License-Identifier: MIT
"""
`adafruit_rgb_display.rgb`
====================================================
Base class for all RGB Display devices
* Author(s): Radomir Dopieralski, Michael McWethy
"""
import time
try:
import nu... | [
2,
30628,
55,
12,
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62... | 2.25283 | 3,710 |
from .vgg16 import VGG16Partitioned
from .stage0 import Stage0
from .stage1 import Stage1
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import tempfile
from json import dumps
import requests
from langdetect import DetectorFactory
from langdetect.lang_detect_exception import LangDetectException
from django.conf import settings
from urllib.parse import urlparse
from urlextract import URLExtract
from openbook.settings import ALERT_HOOK_URL
from openbook... | [
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from utils.utils import *
from utils.textJustification import textJustification
from bs4 import BeautifulSoup
from pathlib import Path
def __findAttr(s, i):
"""gone back till a namespace and returns the word in between"""
l = ""
i -= 1
while s[i] != " ":
l = "".join((l, s[i]))
i -=... | [
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... | 1.988466 | 867 |
# coding: utf-8
#
# Copyright 2013 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | [
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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import sys
import tensorflow as tf
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # mute low-priority warnings from below line
from tensorflow.examples.tutorials.mnist import input_data
import numpy as np... | [
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from typing import List
from .mcts import GameInterface, GameState
from .quarto_logic import Quarto, State
class QuartoState(Quarto):
"""class inheriting both class""" | [
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... | 3.372549 | 51 |
from django.contrib import admin
from .models import AddProduct
from .models import OrderProduct
# Register your models here.
admin.site.register(AddProduct)
admin.site.register(OrderProduct)
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import warnings
from copy import copy
from collections import defaultdict
from typing import Union, Sequence, TYPE_CHECKING
from avalanche.training.plugins.strategy_plugin import StrategyPlugin
if TYPE_CHECKING:
from avalanche.evaluation import PluginMetric
from avalanche.logging import StrategyLogger
from... | [
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... | 2.611921 | 1,577 |
import unittest
import numpy as np
import faiss
'''
Converts the tutorial: https://github.com/facebookresearch/faiss/wiki/Getting-started
for FAISS (Facebook AI Similarity Search) to a unittest to ensure FAISS is set up correctly
on the machine.
'''
DIMENSIONS = 64
DATABASE_SIZE = 100000
NUM_QUERIES = 10000
FIXED_SEE... | [
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from .base import *
ObjectTypes.add_type("cone", "Cone")
PropertyPanel.add_properties("cone", ConeProperties)
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import unittest
import lipsum
import math
if __name__ == '__main__':
unittest.main()
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