content stringlengths 1 1.05M | input_ids listlengths 1 883k | ratio_char_token float64 1 22.9 | token_count int64 1 883k |
|---|---|---|---|
from enum import Enum
import random
import collections
import numpy as np
#
#######################################################################
# Data Types
#######################################################################
#
def __str__(self):
return self._string
class _Session0(_Session):
... | [
6738,
33829,
1330,
2039,
388,
198,
11748,
4738,
198,
11748,
17268,
198,
11748,
299,
32152,
355,
45941,
628,
198,
2,
198,
29113,
29113,
4242,
21017,
198,
2,
6060,
24897,
198,
29113,
29113,
4242,
21017,
198,
2,
628,
198,
220,
220,
220,
... | 3.381968 | 1,453 |
'''
Given an n x n matrix where each of the rows and columns are sorted in ascending order, return the kth smallest element in the matrix.
Note that it is the kth smallest element in the sorted order, not the kth distinct element.
Input: matrix = [[1,5,9],[10,11,13],[12,13,15]], k = 8
Output: 13
Explanation: The elem... | [
7061,
6,
198,
15056,
281,
299,
2124,
299,
17593,
810,
1123,
286,
262,
15274,
290,
15180,
389,
23243,
287,
41988,
1502,
11,
1441,
262,
479,
400,
18197,
5002,
287,
262,
17593,
13,
198,
198,
6425,
326,
340,
318,
262,
479,
400,
18197,
5... | 2.636816 | 402 |
from unittest import TestCase
from unittest.mock import Mock
import numpy as np
from pathfinding.domain.angle import Angle
from pathfinding.domain.coord import Coord
from vision.domain.image import Image
from vision.domain.rectangle import Rectangle
from vision.infrastructure.cvVisionException import CameraDoesNotExi... | [
6738,
555,
715,
395,
1330,
6208,
20448,
198,
6738,
555,
715,
395,
13,
76,
735,
1330,
44123,
198,
198,
11748,
299,
32152,
355,
45941,
198,
198,
6738,
3108,
41070,
13,
27830,
13,
9248,
1330,
42375,
198,
6738,
3108,
41070,
13,
27830,
13,... | 4.085106 | 94 |
from .feature_maps import *
import torch.nn as nn
def create_grad_feature_map(model: nn.Module, grad_layers: List[LayerGradientComputation],
use_float64: bool = False) -> FeatureMap:
"""
Creates a feature map corresponding to phi_{grad} or phi_{ll}, depending on which layers are ... | [
6738,
764,
30053,
62,
31803,
1330,
1635,
198,
11748,
28034,
13,
20471,
355,
299,
77,
628,
628,
198,
4299,
2251,
62,
9744,
62,
30053,
62,
8899,
7,
19849,
25,
299,
77,
13,
26796,
11,
3915,
62,
75,
6962,
25,
7343,
58,
49925,
42731,
1... | 2.885714 | 350 |
from configparser import ConfigParser
from configparser import DuplicateSectionError
from PyQt5 import QtCore, QtGui, QtWidgets
from pinsey import Constants
from pinsey.Utils import clickable, center, picture_grid, horizontal_line, resolve_message_sender, name_set, windows
from pinsey.gui.MessageWindow import MessageW... | [
6738,
4566,
48610,
1330,
17056,
46677,
198,
6738,
4566,
48610,
1330,
49821,
5344,
16375,
12331,
198,
6738,
9485,
48,
83,
20,
1330,
33734,
14055,
11,
33734,
8205,
72,
11,
33734,
54,
312,
11407,
198,
198,
6738,
6757,
4397,
1330,
4757,
118... | 3.855856 | 222 |
from os import system as c
i = "ipconfig"
input(c(i))
# import win32clipboard
# from time import sleep as wait
# set clipboard data
# while True:
# win32clipboard.OpenClipboard()
# win32clipboard.EmptyClipboard()
# win32clipboard.SetClipboardText('Clipboard Blocked!')
# win32clipboard.CloseClipboard()
... | [
6738,
28686,
1330,
1080,
355,
269,
198,
72,
796,
366,
541,
11250,
1,
198,
15414,
7,
66,
7,
72,
4008,
198,
2,
1330,
1592,
2624,
15036,
3526,
198,
2,
422,
640,
1330,
3993,
355,
4043,
198,
198,
2,
900,
47999,
1366,
198,
2,
981,
640... | 2.564885 | 131 |
# -*- encoding: utf-8 -*-
"""
@File : emails.py
@Contact : 1053522308@qq.com
@License : (C)Copyright 2017-2018, Liugroup-NLPR-CASIA
@Modify Time @Author @Version @Desciption
------------ ------- -------- -----------
2020/9/27 10:22 wuxiaoqiang 1.0 None
"""
import asyn... | [
2,
532,
9,
12,
21004,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
31,
8979,
220,
220,
220,
1058,
220,
220,
7237,
13,
9078,
220,
220,
220,
220,
198,
31,
17829,
1058,
220,
220,
13343,
2327,
1828,
21495,
31,
38227,
13,
785,
... | 2.326633 | 199 |
import time
import copy
import random
import logging
from functools import partial
import numpy as np
import torch
from torch.utils.data import DataLoader
from transformers import DistilBertModel, DistilBertForSequenceClassification, DistilBertTokenizer, AlbertModel, AlbertForSequenceClassification, DistilBertTokenize... | [
11748,
640,
198,
11748,
4866,
198,
11748,
4738,
198,
11748,
18931,
198,
6738,
1257,
310,
10141,
1330,
13027,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28034,
198,
6738,
28034,
13,
26791,
13,
7890,
1330,
6060,
17401,
198,
6738,
... | 2.442029 | 1,104 |
#!/usr/bin/env python
###############################################################################
#
# scomdominfo.py - Report information folds and classes of a list of SCOP sids
#
# File: scomdominfo.py
# Author: Alex Stivala
# Created: November 2008
#
# $Id: scopdominfo.py 3009 2009-12-08 03:01:48Z alexs $
# ... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
29113,
29113,
7804,
4242,
21017,
198,
2,
198,
2,
629,
296,
3438,
10951,
13,
9078,
532,
6358,
1321,
38744,
290,
6097,
286,
257,
1351,
286,
6374,
3185,
264,
2340,
198,
2,
198,
2,
9220,... | 2.567552 | 1,769 |
# Copyright (C) 2020 Intel Corporation
#
# SPDX-License-Identifier: MIT
from tools.test import *
import os
| [
2,
15069,
357,
34,
8,
12131,
8180,
10501,
198,
2,
198,
2,
30628,
55,
12,
34156,
12,
33234,
7483,
25,
17168,
198,
198,
6738,
4899,
13,
9288,
1330,
1635,
198,
11748,
28686,
628
] | 3.30303 | 33 |
import torch
import torch.nn as nn
from torch.nn import (TransformerEncoder, TransformerDecoder,
TransformerEncoderLayer, TransformerDecoderLayer)
from torch import Tensor
from typing import Iterable, List
import math
import os
import numpy as np
try:
from janome.tokenizer import Tokenizer
ex... | [
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
6738,
28034,
13,
20471,
1330,
357,
8291,
16354,
27195,
12342,
11,
3602,
16354,
10707,
12342,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,... | 2.32197 | 792 |
# Copyright 2010-2012 Opera Software ASA
#
# 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 applicable law ... | [
2,
220,
220,
15069,
3050,
12,
6999,
26049,
10442,
49599,
220,
198,
2,
198,
2,
220,
220,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
220,
220,
345,
743,
407,
779,
428,
2393,
2845,
28... | 2.403698 | 3,245 |
from flask import Flask
from loguru import logger
from flasgger import Swagger
from patron.api import api_bp
logger.add("api.log", format="{time:YYYY-MM-DD at HH:mm:ss} | {level} | {message}", rotation="500 MB")
template = {
"swagger": "2.0",
"info": {
"title": "PATRON",
"description": "",
... | [
6738,
42903,
1330,
46947,
198,
6738,
2604,
14717,
1330,
49706,
198,
6738,
781,
292,
26679,
1330,
2451,
7928,
198,
198,
6738,
19686,
13,
15042,
1330,
40391,
62,
46583,
628,
198,
6404,
1362,
13,
2860,
7203,
15042,
13,
6404,
1600,
5794,
26... | 2.305221 | 249 |
import numpy as np
import matplotlib.pylab as plt
| [
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29487,
8019,
13,
79,
2645,
397,
355,
458,
83,
198
] | 2.777778 | 18 |
# with tidy long table
fig, ax = plt.subplots()
sns.violinplot(x='station', y='no2', data=data_tidy[data_tidy['datetime'].dt.year == 2011], palette="GnBu_d", ax=ax)
ax.set_ylabel("NO$_2$ concentration (g/m)") | [
2,
351,
43044,
890,
3084,
198,
5647,
11,
7877,
796,
458,
83,
13,
7266,
489,
1747,
3419,
198,
82,
5907,
13,
17069,
259,
29487,
7,
87,
11639,
17529,
3256,
331,
11639,
3919,
17,
3256,
1366,
28,
7890,
62,
83,
19325,
58,
7890,
62,
83,
... | 2.363636 | 88 |
"""
Project: dncnn
Author: khalil MEFTAH
Date: 2021-11-26
DnCNN: Deep Neural Convolutional Network for Image Denoising model implementation
"""
import torch
from torch import nn
import torch.nn.functional as F
# helper functions
# main classe
| [
37811,
198,
16775,
25,
288,
10782,
20471,
198,
13838,
25,
479,
14201,
346,
11948,
37,
5603,
39,
198,
10430,
25,
33448,
12,
1157,
12,
2075,
198,
35,
77,
18474,
25,
10766,
47986,
34872,
2122,
282,
7311,
329,
7412,
5601,
78,
1710,
2746,
... | 3.25 | 76 |
#!/usr/bin/python
from __future__ import print_function
import logging
from fabric.api import task,run,local,put,get,execute,settings
from fabric.decorators import *
from fabric.context_managers import shell_env,quiet
from fabric.exceptions import *
from fabric.utils import puts,fastprint
from time import sleep
from c... | [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
11748,
18931,
198,
6738,
9664,
13,
15042,
1330,
4876,
11,
5143,
11,
12001,
11,
1996,
11,
1136,
11,
41049,
11,
33692,
198,
6738,
9664,
... | 2.404343 | 967 |
from django import forms
from mezzanine.blog.forms import BlogPostForm
from .models import BlogPost
# These fields need to be in the form, hidden, with default values,
# since it posts to the blog post admin, which includes these fields
# and will use empty values instead of the model defaults, without
# these spe... | [
198,
6738,
42625,
14208,
1330,
5107,
198,
198,
6738,
502,
3019,
272,
500,
13,
14036,
13,
23914,
1330,
14001,
6307,
8479,
198,
198,
6738,
764,
27530,
1330,
14001,
6307,
628,
198,
2,
2312,
7032,
761,
284,
307,
287,
262,
1296,
11,
7104,
... | 3.893204 | 103 |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.6 on 2019-03-02 15:56
from __future__ import unicode_literals
import ckeditor.fields
from django.db import migrations, models
import django.db.models.deletion
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
2980,
515,
416,
37770,
352,
13,
1157,
13,
21,
319,
13130,
12,
3070,
12,
2999,
1315,
25,
3980,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
... | 2.789474 | 76 |
import platform
from setuptools import setup
if platform.system() == "Windows":
setup(
name="intermezzo",
version="0.1.0",
description="A library for creating cross-platform text-based interfaces using termbox-go.",
long_description="",
url="https://github.com/imdaveho/inter... | [
11748,
3859,
198,
6738,
900,
37623,
10141,
1330,
9058,
198,
198,
361,
3859,
13,
10057,
3419,
6624,
366,
11209,
1298,
198,
220,
220,
220,
9058,
7,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
2625,
3849,
1326,
47802,
1600,
198,
220,
... | 2.192248 | 645 |
from django.urls import path
from . import views
urlpatterns = [
path('', views.index, name='index'),
path('<str:nome>', views.cumprimentar, name='cumprimentar'),
] | [
6738,
42625,
14208,
13,
6371,
82,
1330,
3108,
198,
6738,
764,
1330,
5009,
198,
198,
6371,
33279,
82,
796,
685,
198,
220,
220,
220,
3108,
10786,
3256,
5009,
13,
9630,
11,
1438,
11639,
9630,
33809,
198,
220,
220,
220,
3108,
10786,
27,
... | 2.621212 | 66 |
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import cv2, os, sys, glob
import scipy
import sklearn
import imageio
import matplotlib.cm as cm
import matplotlib
import time
from sklearn import decomposition, metrics, manifold, svm
from tsne import bh_sne
from matplotlib.path ... | [
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
2603,
29487,
8019,
13,
2164,
2340,
43106,
355,
50000,
43106,
198,
11748,
269,
85,
17,
11,
28686,
11,
25064,
11,
15095,
198,
11748,
... | 4.596685 | 181 |
import pygame
from game.game_data.cells.Cell import Cell
from game.pygame_ import PICS_pygame, CELL_SIZE
from game.pygame_.Object import Object
| [
11748,
12972,
6057,
198,
198,
6738,
983,
13,
6057,
62,
7890,
13,
46342,
13,
28780,
1330,
12440,
198,
6738,
983,
13,
9078,
6057,
62,
1330,
350,
19505,
62,
9078,
6057,
11,
18671,
3069,
62,
33489,
198,
6738,
983,
13,
9078,
6057,
44807,
... | 3.173913 | 46 |
import json
import os
import torch
import math
def adjust_learning_rate(optimizer, scale):
"""
Scale learning rate by a specified factor.
:param optimizer: optimizer whose learning rate must be shrunk.
:param scale: factor to multiply learning rate with.
"""
for param_group in optimizer.param... | [
11748,
33918,
198,
11748,
28686,
198,
11748,
28034,
198,
11748,
10688,
628,
198,
4299,
4532,
62,
40684,
62,
4873,
7,
40085,
7509,
11,
5046,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
21589,
4673,
2494,
416,
257,
7368,
5766,
... | 2.974277 | 311 |
from enum import Enum
| [
6738,
33829,
1330,
2039,
388,
628
] | 3.833333 | 6 |
#!/bin/python3
"""This is the top-level program to operate the Raspberry Pi based lego sorter."""
# Things I can set myself: AWB, Brightness, crop, exposure_mode,
# exposure_speed,iso (sensitivity), overlays, preview_alpha,
# preview_window, saturation, shutter_speed,
# Thought for future enhancement: at start... | [
2,
48443,
8800,
14,
29412,
18,
198,
37811,
1212,
318,
262,
1353,
12,
5715,
1430,
284,
8076,
262,
24244,
13993,
1912,
1232,
78,
264,
4337,
526,
15931,
198,
198,
2,
11597,
314,
460,
900,
3589,
25,
14356,
33,
11,
17558,
1108,
11,
13833... | 2.222928 | 3,149 |
# -*- coding: utf-8 -*-
from yaml import load, dump
try:
from yaml import CSafeLoader as SafeLoader
print "Using CSafeLoader"
except ImportError:
from yaml import SafeLoader
print "Using Python SafeLoader"
import os
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
from sqlalchemy import Table
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
331,
43695,
1330,
3440,
11,
10285,
198,
28311,
25,
198,
197,
6738,
331,
43695,
1330,
9429,
8635,
17401,
355,
19978,
17401,
198,
197,
4798,
366,
12814,
9429,
8635,
... | 3.05 | 100 |
from django.shortcuts import render
from core.models import Projects,InfoNotifications,WarningNotifications
from django.http import HttpResponse
from .tasks import sleepy
| [
6738,
42625,
14208,
13,
19509,
23779,
1330,
8543,
198,
6738,
4755,
13,
27530,
1330,
29898,
11,
12360,
3673,
6637,
11,
20361,
3673,
6637,
198,
6738,
42625,
14208,
13,
4023,
1330,
367,
29281,
31077,
198,
198,
6738,
764,
83,
6791,
1330,
42... | 4.119048 | 42 |
import tensorflow as tf
import numpy as np
EPS = 1e-5
def KL_monte_carlo(z, mean, sigma=None, log_sigma=None):
"""Computes the KL divergence at a point, given by z.
Implemented based on https://www.tensorflow.org/tutorials/generative/cvae
This is the part "log(p(z)) - log(q(z|x)) where z is sampled from... | [
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
299,
32152,
355,
45941,
198,
198,
36,
3705,
796,
352,
68,
12,
20,
628,
198,
4299,
48253,
62,
2144,
660,
62,
7718,
5439,
7,
89,
11,
1612,
11,
264,
13495,
28,
14202,
11,
2604,
62,
82... | 2.236291 | 2,006 |
from tkinter import *
import os, xmltodict, requests
def knop1():
'Open GUI huidig station'
global root
root.destroy()
os.system('Huidig_Station.py')
def knop2():
'Open GUI ander station'
global root
root.destroy()
os.system('Ander_Station.py')
def nl_to_eng():
'Wanneer er op d... | [
6738,
256,
74,
3849,
1330,
1635,
198,
11748,
28686,
11,
2124,
76,
2528,
375,
713,
11,
7007,
628,
198,
198,
4299,
638,
404,
16,
33529,
198,
220,
220,
220,
705,
11505,
25757,
289,
27112,
328,
4429,
6,
198,
220,
220,
220,
3298,
6808,
... | 1.823905 | 2,351 |
from .py2ifttt import IFTTT | [
6738,
764,
9078,
17,
361,
926,
83,
1330,
314,
9792,
15751
] | 2.454545 | 11 |
import socket
import tokens
import connection
import io
import os
from PIL import Image
from message.literalMessage import LiteralMessage
from baseApplication import BaseApplication
host = input('Host: ')
ClientApplication(host, 50007) | [
11748,
17802,
201,
198,
11748,
16326,
201,
198,
11748,
4637,
201,
198,
11748,
33245,
201,
198,
11748,
28686,
201,
198,
6738,
350,
4146,
1330,
7412,
201,
198,
6738,
3275,
13,
18250,
1691,
12837,
1330,
25659,
1691,
12837,
201,
198,
6738,
... | 3.671642 | 67 |
import sys
import socket
ETH_P_ALL=3 # not defined in socket module, sadly...
s=socket.socket(socket.AF_PACKET, socket.SOCK_RAW, socket.htons(ETH_P_ALL))
s.bind((sys.argv[1], 0))
r=s.recv(2000)
sys.stdout.write("<%s>\n"%repr(r))
| [
11748,
25064,
198,
11748,
17802,
198,
198,
20702,
62,
47,
62,
7036,
28,
18,
1303,
407,
5447,
287,
17802,
8265,
11,
21098,
986,
198,
82,
28,
44971,
13,
44971,
7,
44971,
13,
8579,
62,
47,
8120,
2767,
11,
17802,
13,
50,
11290,
62,
20... | 2.254902 | 102 |
#!/usr/bin/env python3
from json import loads
from urllib.request import urlopen, Request
SITE = input('Site: ')
COOKIE = 'pj=' + input('pj=')
examList = loads(urlopen(Request(f'{SITE}/data/module/homework/all.asp?sAct=GetHomeworkListByStudent&iIsExam=1&iPageCount=' + loads(urlopen(Request(f'{SITE}/data/module/home... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
6738,
33918,
1330,
15989,
198,
6738,
2956,
297,
571,
13,
25927,
1330,
19016,
9654,
11,
19390,
628,
198,
50,
12709,
796,
5128,
10786,
29123,
25,
705,
8,
198,
34,
15308,
10008,
... | 2.376874 | 467 |
import sys
import os
import tkinter.filedialog as fd
from time import sleep
import datetime
import tkinter
import tkinter as tk
from tkinter import ttk
from tkinter import scrolledtext
import threading
# New File & Duplicate File Save
# FileSave
| [
11748,
25064,
198,
11748,
28686,
198,
11748,
256,
74,
3849,
13,
69,
3902,
498,
519,
355,
277,
67,
198,
6738,
640,
1330,
3993,
198,
11748,
4818,
8079,
198,
11748,
256,
74,
3849,
198,
11748,
256,
74,
3849,
355,
256,
74,
198,
6738,
256... | 3 | 86 |
#!/usr/bin/python
#
# Copyright 2018-2021 Polyaxon, 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 the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... | [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
2,
198,
2,
15069,
2864,
12,
1238,
2481,
12280,
897,
261,
11,
3457,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
... | 3.595628 | 183 |
# -*- coding: utf-8 -*-
# AUTHOR: Zeray Rice <fanzeyi1994@gmail.com>
# FILE: judge/base/__init__.py
# CREATED: 01:49:33 08/03/2012
# MODIFIED: 15:42:49 19/04/2012
# DESCRIPTION: Base handler
import re
import time
import urllib
import hashlib
import httplib
import datetime
import functools
import traceback
import simp... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
220,
198,
2,
44746,
25,
37028,
323,
13823,
1279,
24408,
2736,
48111,
22666,
31,
14816,
13,
785,
29,
198,
2,
45811,
25,
5052,
14,
8692,
14,
834,
15003,
834,
13,
9078,
198,
... | 2.900804 | 373 |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import markdownx.models
import myblog.filename
from django.conf import settings
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
4981,
11,
15720,
602,
198,
11748,
1317,
2902,
87,
13,
27530,
19... | 3.224138 | 58 |
test = {'name': 'q6',
'points': 10,
'suites': [{'cases': [{'code': '>>> increment = lambda x: x + 1\n'
'\n'
'>>> square = lambda x: x * x\n'
'\n'
'>>> do_nothing = make_zipper(increment, '
... | [
9288,
796,
1391,
6,
3672,
10354,
705,
80,
21,
3256,
198,
705,
13033,
10354,
838,
11,
198,
705,
2385,
2737,
10354,
685,
90,
6,
33964,
10354,
685,
90,
6,
8189,
10354,
705,
33409,
18703,
796,
37456,
2124,
25,
2124,
1343,
352,
59,
77,
... | 1.356453 | 1,139 |
"""
This problem was asked by Google.
Suppose we represent our file system by a string in the following manner:
The string "dir\n\tsubdir1\n\tsubdir2\n\t\tfile.ext" represents:
dir
subdir1
subdir2
file.ext
The directory dir contains an empty sub-directory subdir1 and a sub-directory subdir2 containin... | [
37811,
198,
1212,
1917,
373,
1965,
416,
3012,
13,
198,
198,
15979,
577,
356,
2380,
674,
2393,
1080,
416,
257,
4731,
287,
262,
1708,
5642,
25,
198,
198,
464,
4731,
366,
15908,
59,
77,
59,
912,
549,
15908,
16,
59,
77,
59,
912,
549,
... | 3.111876 | 581 |
from os.path import expanduser, exists
from os import makedirs
TURBOT_PATH = expanduser('~/.turbot')
UPVOTE_LOGS = expanduser("%s/upvote_logs" % TURBOT_PATH)
CHECKPOINT = expanduser("%s/checkpoint" % TURBOT_PATH)
REFUND_LOG = expanduser("%s/refunds" % TURBOT_PATH)
| [
6738,
28686,
13,
6978,
1330,
4292,
7220,
11,
7160,
198,
6738,
28686,
1330,
285,
4335,
17062,
198,
198,
51,
4261,
33,
2394,
62,
34219,
796,
4292,
7220,
10786,
93,
11757,
83,
5945,
313,
11537,
198,
8577,
53,
23051,
62,
25294,
50,
796,
... | 2.40708 | 113 |
from output.models.ms_data.additional.member_type021_xsd.member_type021 import Root
__all__ = [
"Root",
]
| [
6738,
5072,
13,
27530,
13,
907,
62,
7890,
13,
2860,
1859,
13,
19522,
62,
4906,
46821,
62,
87,
21282,
13,
19522,
62,
4906,
46821,
1330,
20410,
198,
198,
834,
439,
834,
796,
685,
198,
220,
220,
220,
366,
30016,
1600,
198,
60,
198
] | 2.581395 | 43 |
reportedCases=eval(input('Enter the number of reported cases:-'))
name=input('Enter the name of the region:-')
days=eval(input('Enter the number of days:-'))
totalHospitalbeds=eval(input('Enter the total number of beds available in the region:'))
avgDailyIncomeInUsd=eval(input('Enter the Average income:-'))
avgDaily... | [
628,
198,
26263,
34,
1386,
28,
18206,
7,
15414,
10786,
17469,
262,
1271,
286,
2098,
2663,
25,
19355,
4008,
198,
3672,
28,
15414,
10786,
17469,
262,
1438,
286,
262,
3814,
21912,
11537,
198,
12545,
28,
18206,
7,
15414,
10786,
17469,
262,
... | 3.090395 | 177 |
#!/usr/bin/env python3
# Original Author @elitest
# This script uses boto3 to perform client side decryption
# of data encryption keys and associated files
# and encryption in ways compatible with the AWS SDKs
# This support is not available in boto3 at this time
# Wishlist:
# Currently only tested with KMS managed s... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
13745,
6434,
2488,
417,
270,
395,
198,
198,
2,
770,
4226,
3544,
275,
2069,
18,
284,
1620,
5456,
1735,
875,
13168,
198,
2,
286,
1366,
15835,
8251,
290,
3917,
3696,
198,
2,
29... | 3.165254 | 708 |
from IPython.display import HTML
#TO DO - the nested table does not display?
#Also, the nested execution seems to take a long time to run?
#Profile it to see where I'm going wrong!
| [
6738,
6101,
7535,
13,
13812,
1330,
11532,
628,
198,
2,
10468,
8410,
532,
262,
28376,
3084,
857,
407,
3359,
30,
198,
2,
7583,
11,
262,
28376,
9706,
2331,
284,
1011,
257,
890,
640,
284,
1057,
30,
198,
2,
37046,
340,
284,
766,
810,
3... | 3.755102 | 49 |
from turtle import width
import streamlit as st
import numpy as np
import pandas as pd
from dis import dis
import streamlit as st
from data.get_saved_library import get_saved_library, display_user_name, display_user_pic
from data.get_recently_played import get_recently_played
from data.get_top_artists import get_top_ar... | [
6738,
28699,
1330,
9647,
198,
11748,
4269,
18250,
355,
336,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
19798,
292,
355,
279,
67,
198,
6738,
595,
1330,
595,
198,
11748,
4269,
18250,
355,
336,
198,
6738,
1366,
13,
1136,
62,
82,
958... | 3.279476 | 229 |
# Author: allannozomu
# Runtime: 56 ms
# Memory: 13 MB
| [
2,
6434,
25,
477,
1236,
8590,
296,
84,
198,
2,
43160,
25,
7265,
13845,
198,
2,
14059,
25,
1511,
10771,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220
] | 2.030303 | 33 |
import pytest
from models.contact_number import ContactNumberModel
| [
11748,
12972,
9288,
198,
6738,
4981,
13,
32057,
62,
17618,
1330,
14039,
15057,
17633,
628,
198
] | 4.3125 | 16 |
import unittest
import numpy as np
from sciquence.sequences import *
if __name__ == '__main__':
unittest.main()
| [
11748,
555,
715,
395,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
629,
1557,
594,
13,
3107,
3007,
1330,
1635,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
... | 2.767442 | 43 |
# -*- coding: utf-8 -*-
"""
Simple example using BarGraphItem
"""
# import initExample ## Add path to library (just for examples; you do not need this)
import numpy as np
import pickle as p
import pandas as pd
from analysis_guis.dialogs.rotation_filter import RotationFilter
from analysis_guis.dialogs impor... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
201,
198,
37811,
201,
198,
26437,
1672,
1262,
2409,
37065,
7449,
201,
198,
37811,
201,
198,
2,
1330,
2315,
16281,
22492,
3060,
3108,
284,
5888,
357,
3137,
329,
6096,
26,
345,... | 1.975163 | 4,147 |
"""
downloads gmail atts
"""
import base64, os
from auth.auth import get_service
from msg.label import agencies, get_atts
from report.response import get_threads, get_status
from att.drive import get_or_create_atts_folder,\
check_if_drive, make_drive_folder, upload_to_drive
### START CONFIG ###
buffer_path = ... | [
37811,
198,
15002,
82,
308,
4529,
708,
82,
198,
37811,
198,
198,
11748,
2779,
2414,
11,
28686,
198,
6738,
6284,
13,
18439,
1330,
651,
62,
15271,
198,
6738,
31456,
13,
18242,
1330,
5942,
11,
651,
62,
30353,
198,
6738,
989,
13,
26209,
... | 2.404722 | 1,186 |
# Copyright 2022 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from __future__ import absolute_import
from pex.pip.log_analyzer import LogAnalyzer
from pex.typing import TYPE_CHECKING, Generic
if TYPE_CHECKING:
from typing import Iterable, Mappi... | [
2,
15069,
33160,
41689,
1628,
20420,
357,
3826,
27342,
9865,
3843,
20673,
13,
9132,
737,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
3826,
38559,
24290,
737,
198,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
1... | 3.109756 | 164 |
from typing import Any
from typing import Callable
from typing import Iterable
class NextDispatch(Exception):
pass
class DispatcherType(type):
class Dispatcher(FunctionMixin, metaclass=DispatcherType):
dispatch: callable
register: callable
registry: Iterable
class MetaDispatcher(FunctionMixin... | [
6738,
19720,
1330,
4377,
198,
6738,
19720,
1330,
4889,
540,
198,
6738,
19720,
1330,
40806,
540,
628,
628,
198,
198,
4871,
7406,
49354,
7,
16922,
2599,
198,
220,
220,
220,
1208,
628,
198,
4871,
3167,
8071,
2044,
6030,
7,
4906,
2599,
62... | 3.2 | 150 |
from pbpstats.resources.enhanced_pbp import StartOfPeriod
| [
6738,
279,
46583,
34242,
13,
37540,
13,
16550,
2903,
62,
40842,
79,
1330,
7253,
5189,
5990,
2101,
628
] | 3.277778 | 18 |
# Copyright 2015 OpenStack Foundation
# 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 requ... | [
2,
15069,
1853,
4946,
25896,
5693,
198,
2,
1439,
6923,
33876,
13,
198,
2,
198,
2,
220,
220,
220,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
345,
743,
198,
2,
220,
220,
220,
407,
779,
428,
... | 2.18404 | 1,391 |
#!/usr/bin/env python
# coding: utf-8
# In[2]:
from collections import defaultdict
import csv
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# ## read data to numpy(not in use)
# In[385]:
# def readCsvToNumpy(file_name, feat_num):
# util_mat = []
# with open... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
19617,
25,
3384,
69,
12,
23,
198,
198,
2,
554,
58,
17,
5974,
628,
198,
6738,
17268,
1330,
4277,
11600,
198,
11748,
269,
21370,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
1979... | 2.083333 | 1,752 |
# -*- coding: utf-8 -*-
from __future__ import absolute_import
import keras.backend as K
from time import sleep
def _ternarize(W, H=1):
'''The weights' ternarization function,
# References:
- [Recurrent Neural Networks with Limited Numerical Precision](http://arxiv.org/abs/1608.06902)
- [Ternary Weig... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
11748,
41927,
292,
13,
1891,
437,
355,
509,
198,
6738,
640,
1330,
3993,
628,
198,
4299,
4808,
759,
283,
1096,
7,
5... | 2.370445 | 494 |
import asyncio
cond = None
p_list = []
#
#
if __name__ == "__main__":
asyncio.run(main())
| [
11748,
30351,
952,
198,
198,
17561,
796,
6045,
198,
79,
62,
4868,
796,
17635,
628,
198,
2,
220,
628,
198,
2,
220,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
30351,
952,
13,
5143,
7,... | 2.212766 | 47 |
from collections import Counter
| [
6738,
17268,
1330,
15034,
198,
220,
220,
220,
220,
220,
220,
220,
220
] | 3.076923 | 13 |
"""Mini-functions that do not belong elsewhere."""
from datetime import datetime
| [
37811,
39234,
12,
12543,
2733,
326,
466,
407,
5594,
8057,
526,
15931,
198,
6738,
4818,
8079,
1330,
4818,
8079,
628
] | 4.1 | 20 |
import flask_admin as admin
# from flask_admin.contrib.sqla import ModelView
from app import app
# from app import db
from models import *
# Admin
admin = admin.Admin(app)
# Add Admin Views
| [
11748,
42903,
62,
28482,
355,
13169,
198,
2,
422,
42903,
62,
28482,
13,
3642,
822,
13,
31166,
5031,
1330,
9104,
7680,
198,
198,
6738,
598,
1330,
598,
198,
2,
422,
598,
1330,
20613,
198,
6738,
4981,
1330,
1635,
198,
198,
2,
32053,
19... | 3.327586 | 58 |
# Generated by Django 3.0.6 on 2020-05-21 20:38
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
513,
13,
15,
13,
21,
319,
12131,
12,
2713,
12,
2481,
1160,
25,
2548,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.84375 | 32 |
import os
# We should try to import any custom settings.
SETTINGS_MODULE_NAME = os.getenv("MYPI_SETTINGS_MODULE")
if SETTINGS_MODULE_NAME:
SETTINGS_MODULE = import_module(SETTINGS_MODULE_NAME)
else:
SETTINGS_MODULE = object()
# Try to get everything from the custom settings, but provide a default.
PACKAGES_... | [
11748,
28686,
628,
198,
198,
2,
775,
815,
1949,
284,
1330,
597,
2183,
6460,
13,
198,
28480,
51,
20754,
62,
33365,
24212,
62,
20608,
796,
28686,
13,
1136,
24330,
7203,
26708,
11901,
62,
28480,
51,
20754,
62,
33365,
24212,
4943,
198,
36... | 2.483051 | 236 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import simplejson as json
from alipay.aop.api.constant.ParamConstants import *
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
11748,
2829,
17752,
355,
33918,
198,
198,
6738,
435,
541,
323,
13,
64,
404,
13,
15042,
13,
9979,
415,
13,
22973,
3418... | 2.58 | 50 |
from __future__ import division # Use floating point for math calculations
from flask import Blueprint
from CTFd.models import (
ChallengeFiles,
Challenges,
Fails,
Flags,
Hints,
Solves,
Tags,
db,
)
from CTFd.plugins import register_plugin_assets_directory
from CTFd.plugins.challenges... | [
6738,
11593,
37443,
834,
1330,
7297,
220,
1303,
5765,
12462,
966,
329,
10688,
16765,
628,
198,
6738,
42903,
1330,
39932,
198,
198,
6738,
327,
10234,
67,
13,
27530,
1330,
357,
198,
220,
220,
220,
13879,
25876,
11,
198,
220,
220,
220,
4... | 2.981595 | 163 |
shopping_list = {
'Tomatoes': 6,
'Bananas': 5,
'Crackers': 2,
'Sugar': 1,
'Icecream': 1,
'Bread': 3,
'Chocolate': 2
}
# Just the keys
print(shopping_list.keys())
# Just the values
# print(shopping_list.values())
# Both keys and values
# print(shopping_list.items())
| [
198,
1477,
33307,
62,
4868,
796,
1391,
198,
220,
220,
220,
705,
13787,
15048,
10354,
718,
11,
198,
220,
220,
220,
705,
30457,
15991,
10354,
642,
11,
198,
220,
220,
220,
705,
13916,
28874,
10354,
362,
11,
198,
220,
220,
220,
705,
50,... | 2.322835 | 127 |
from .surface import *
from .modifiers import *
from .evaluator import Evaluator
from .lowlevel import display_results
| [
6738,
764,
42029,
1330,
1635,
198,
6738,
764,
4666,
13350,
1330,
1635,
198,
6738,
764,
18206,
84,
1352,
1330,
26439,
84,
1352,
198,
6738,
764,
9319,
5715,
1330,
3359,
62,
43420,
198
] | 3.71875 | 32 |
import math
from math import*
print('enter a positive integer')
FacMe=int(input())
primefacts=[1]
if not isPrime(FacMe):
if FacMe % 2==0:
primefacts.append(2)
if FacMe % 3==0:
primefacts.append(3)
for i in range(5,FacMe):
if FacMe%i==0:
if isPrime(i):
... | [
11748,
10688,
201,
198,
6738,
10688,
1330,
9,
201,
198,
201,
198,
4798,
10786,
9255,
257,
3967,
18253,
11537,
201,
198,
47522,
5308,
28,
600,
7,
15414,
28955,
201,
198,
35505,
37473,
41888,
16,
60,
201,
198,
361,
407,
318,
26405,
7,
... | 2.004902 | 204 |
# encoding: utf-8
"""
binary butterfly validator
Copyright (c) 2021, binary butterfly GmbH
Use of this source code is governed by an MIT-style license that can be found in the LICENSE.txt.
"""
import re
from typing import Any, Optional
from ..abstract_input import AbstractInput
from ..fields import Field
from ..vali... | [
2,
21004,
25,
3384,
69,
12,
23,
198,
198,
37811,
198,
39491,
35113,
4938,
1352,
198,
15269,
357,
66,
8,
33448,
11,
13934,
35113,
402,
2022,
39,
198,
11041,
286,
428,
2723,
2438,
318,
21825,
416,
281,
17168,
12,
7635,
5964,
326,
460,... | 3.863636 | 110 |
from runner.run_descriptions.run_description import RunDescription, Experiment, ParamGrid
_params = ParamGrid([
('prediction_bonus_coeff', [0.00, 0.05]),
])
_experiments = [
Experiment(
'doom_maze_very_sparse',
'python -m algorithms.curious_a2c.train_curious_a2c --env=doom_maze_very_sparse --g... | [
6738,
17490,
13,
5143,
62,
20147,
1968,
507,
13,
5143,
62,
11213,
1330,
5660,
11828,
11,
29544,
11,
25139,
41339,
198,
198,
62,
37266,
796,
25139,
41339,
26933,
198,
220,
220,
220,
19203,
28764,
2867,
62,
4189,
385,
62,
1073,
14822,
3... | 2.255773 | 563 |
import os
from xappt_qt.__version__ import __version__, __build__
from xappt_qt.plugins.interfaces.qt import QtInterface
# suppress "qt.qpa.xcb: QXcbConnection: XCB error: 3 (BadWindow)"
os.environ['QT_LOGGING_RULES'] = '*.debug=false;qt.qpa.*=false'
version = tuple(map(int, __version__.split('.'))) + (__build__, )... | [
11748,
28686,
198,
198,
6738,
2124,
1324,
83,
62,
39568,
13,
834,
9641,
834,
1330,
11593,
9641,
834,
11,
11593,
11249,
834,
198,
198,
6738,
2124,
1324,
83,
62,
39568,
13,
37390,
13,
3849,
32186,
13,
39568,
1330,
33734,
39317,
198,
198... | 2.57047 | 149 |
#!/usr/bin/python3
import sys
import sqlite3;
import re;
import os;
import random
import qualification
from cttable import CandidateTable, TableVotingGroup, PhantomTableVotingGroup
import cttable
SW_VERSION_SPLIT = (1, 1, 4)
SW_VERSION = ".".join([str(x) for x in SW_VERSION_SPLIT])
EARLIEST_COMPATIBLE_DB_VERSION = (... | [
2,
48443,
14629,
14,
8800,
14,
29412,
18,
198,
198,
11748,
25064,
198,
11748,
44161,
578,
18,
26,
198,
11748,
302,
26,
198,
11748,
28686,
26,
198,
11748,
4738,
198,
11748,
28587,
198,
198,
6738,
269,
926,
540,
1330,
40327,
10962,
11,
... | 2.385977 | 8,871 |
# Copyright (c) Jeremas Casteglione <jrmsdev@gmail.com>
# See LICENSE file.
from glob import glob
from os import path, makedirs
| [
2,
15069,
357,
66,
8,
10272,
5356,
5833,
1533,
75,
7935,
1279,
73,
81,
907,
7959,
31,
14816,
13,
785,
29,
198,
2,
4091,
38559,
24290,
2393,
13,
198,
198,
6738,
15095,
1330,
15095,
198,
6738,
28686,
1330,
3108,
11,
285,
4335,
17062,
... | 2.931818 | 44 |
"""
##############
# jsonReader #
##############
"""
# Import
import json
from platform import system
from enum import Enum
from datetime import timedelta
# %% ____________________________________________________________________________________________________
# ____________________________________________________... | [
37811,
198,
7804,
4242,
2235,
198,
2,
33918,
33634,
1303,
198,
7804,
4242,
2235,
198,
37811,
198,
198,
2,
17267,
198,
11748,
33918,
198,
6738,
3859,
1330,
1080,
198,
6738,
33829,
1330,
2039,
388,
198,
6738,
4818,
8079,
1330,
28805,
1251... | 2.226048 | 1,336 |
import re
test = input(" : ")
test.encode('unicode-escape').decode().replace('\\\\', '\\')
print(" : "+test)
if re.match(test, "a"):
print(test + " Match 1")
if re.match(test, "aa"):
print(test + " Match 2")
if re.match(test, "aaaa"):
print(test + " Match 3")
| [
11748,
302,
198,
198,
9288,
796,
5128,
7203,
1058,
366,
8,
198,
198,
9288,
13,
268,
8189,
10786,
46903,
1098,
12,
41915,
27691,
12501,
1098,
22446,
33491,
10786,
13426,
3256,
705,
6852,
11537,
198,
198,
4798,
7203,
1058,
43825,
9288,
8,... | 2.376068 | 117 |
#
t=0
#
for x in range(1,9):
for y in range(1,11):
for z in range(1,13):
if 6*x+5*y+4*z==50:
print("x ",x," y ",y," z ",z," ")
t=t+1
print(" {} ".format(t))
#by xiaozhiyuqwq
#https://www.rainyat.work
#2021-12-23
| [
2,
201,
198,
83,
28,
15,
201,
198,
2,
201,
198,
1640,
2124,
287,
2837,
7,
16,
11,
24,
2599,
201,
198,
220,
220,
220,
329,
331,
287,
2837,
7,
16,
11,
1157,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1976,
287,
28... | 1.561111 | 180 |
# from job_scrapper_gui import naukri_gui
from tkinter import *
from PIL import ImageTk
import PIL.Image
import naukri_scrapper
import linkedin_scrapper
import indeed
import simply_hired_scrapper
from selenium import webdriver
root = Tk()
root.title("Compare Jobs")
root.geometry("1000x670")
root.configure(background=... | [
2,
422,
1693,
62,
1416,
430,
2848,
62,
48317,
1330,
299,
559,
74,
380,
62,
48317,
198,
6738,
256,
74,
3849,
1330,
1635,
198,
6738,
350,
4146,
1330,
7412,
51,
74,
198,
11748,
350,
4146,
13,
5159,
198,
11748,
299,
559,
74,
380,
62,
... | 2.876289 | 873 |
"""
multispectrum
Zhiang Chen,
Feb, 2020
"""
import gdal
import cv2
import numpy as np
import math
import os
if __name__ == '__main__':
st = MultDim()
# split tiles
"""
st.readTiff("./datasets/C3/Orth5.tif", channel=5)
R = st.readImage("./datasets/Rock/R.png", channel=1)
G = st.readImage(".... | [
37811,
198,
16680,
271,
806,
6582,
198,
57,
5303,
648,
12555,
11,
198,
15146,
11,
12131,
198,
37811,
198,
198,
11748,
308,
31748,
198,
11748,
269,
85,
17,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
10688,
198,
11748,
28686,
628,
... | 2.107744 | 594 |
import json
from engine.serializers.template import TemplateCellSerializer
| [
11748,
33918,
198,
198,
6738,
3113,
13,
46911,
11341,
13,
28243,
1330,
37350,
28780,
32634,
7509,
628,
198
] | 4.333333 | 18 |
#!/usr/bin/env python3
from random import randrange
import random
import pygame, sys
from pygame.locals import *
import string
pygame.font.init()
MENU_WIDTH = 1000
MENU_HEIGHT = 1000
GUESS_WIDTH = 1000
GUESS_HEIGHT = 650
HANGMAN_WIDTH = 1300
HANGMAN_HEIGHT = 720
BLACK = (0,0,0)
WHITE = (25... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
201,
198,
201,
198,
6738,
4738,
1330,
43720,
9521,
201,
198,
11748,
4738,
201,
198,
11748,
12972,
6057,
11,
25064,
201,
198,
6738,
12972,
6057,
13,
17946,
874,
1330,
1635,
201,
198,
117... | 2.143836 | 292 |
import numpy as np
from PuzzleLib.Backend import gpuarray
from PuzzleLib.Backend.Dnn import crossMapLRN, crossMapLRNBackward
from PuzzleLib.Modules.LRN import LRN
if __name__ == "__main__":
unittest()
| [
11748,
299,
32152,
355,
45941,
198,
198,
6738,
23966,
25835,
13,
7282,
437,
1330,
308,
19944,
18747,
198,
6738,
23966,
25835,
13,
7282,
437,
13,
35,
20471,
1330,
3272,
13912,
35972,
45,
11,
3272,
13912,
35972,
45,
7282,
904,
198,
198,
... | 2.849315 | 73 |
import copy
from typing import Iterable
import numba as nb
import numpy as np
import spectrum_utils.spectrum as sus
def dot(spectrum1: sus.MsmsSpectrum, spectrum2: sus.MsmsSpectrum,
fragment_mz_tolerance: float) -> float:
"""
Compute the dot product between the given spectra.
Parameters
----... | [
11748,
4866,
198,
6738,
19720,
1330,
40806,
540,
198,
198,
11748,
997,
7012,
355,
299,
65,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
10958,
62,
26791,
13,
4443,
6582,
355,
2341,
628,
198,
4299,
16605,
7,
4443,
6582,
16,
25,
2341... | 2.628028 | 1,156 |
"""
BP.
"""
import sys
import classicML as cml
DATASET_PATH = './datasets/iris_dataset.csv'
CALLBACKS = [cml.callbacks.History(loss_name='categorical_crossentropy',
metric_name='accuracy')]
#
ds = cml.data.Dataset(label_mode='one-hot',
standardization=True,
... | [
37811,
198,
20866,
13,
198,
37811,
198,
11748,
25064,
198,
11748,
6833,
5805,
355,
269,
4029,
628,
198,
35,
1404,
1921,
2767,
62,
34219,
796,
705,
19571,
19608,
292,
1039,
14,
29616,
62,
19608,
292,
316,
13,
40664,
6,
198,
34,
7036,
... | 1.9437 | 373 |
__author__ = "arunrajms"
from rest_framework import serializers
from pool.models import Pool
from rest_framework.validators import UniqueValidator
import re
TYPE_CHOICES = ['Integer','IP','IPv6','AutoGenerate','Vlan','MgmtIP']
PUT_TYPE_CHOICES = ['Integer','IP','IPv6','Vlan','MgmtIP']
SCOPE_CHOICES = ['global','fabri... | [
834,
9800,
834,
796,
366,
283,
403,
430,
73,
907,
1,
198,
198,
6738,
1334,
62,
30604,
1330,
11389,
11341,
198,
6738,
5933,
13,
27530,
1330,
19850,
198,
6738,
1334,
62,
30604,
13,
12102,
2024,
1330,
30015,
47139,
1352,
198,
11748,
302,... | 3.018182 | 110 |
import os
import platform
from datetime import datetime
import time
from pathlib import Path
import asyncio
from dateutil.parser import parse as parsedate
from dateutil import tz
import aiohttp
| [
11748,
28686,
198,
11748,
3859,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
11748,
640,
198,
6738,
3108,
8019,
1330,
10644,
198,
11748,
30351,
952,
198,
198,
6738,
3128,
22602,
13,
48610,
1330,
21136,
355,
44267,
378,
198,
6738,
3128,
... | 3.792453 | 53 |
# O(n) time | O(1) space
| [
2,
440,
7,
77,
8,
640,
930,
440,
7,
16,
8,
2272,
628
] | 2 | 13 |
import pytest
from layers.attention import AttentionLayer
from tensorflow.keras.layers import Input, GRU, Dense, Concatenate, TimeDistributed
from tensorflow.keras.models import Model
import tensorflow as tf
def test_attention_layer_standalone_fixed_b_fixed_t():
"""
Tests fixed batch size and time steps
E... | [
11748,
12972,
9288,
198,
6738,
11685,
13,
1078,
1463,
1330,
47406,
49925,
198,
6738,
11192,
273,
11125,
13,
6122,
292,
13,
75,
6962,
1330,
23412,
11,
10863,
52,
11,
360,
1072,
11,
1482,
9246,
268,
378,
11,
3862,
20344,
6169,
198,
6738... | 2.613267 | 799 |
from itertools import zip_longest, islice
if __name__ == '__main__':
L = input()
inverse_suffix_array = suffix_array_best(L)
suffix_array = inverse_array(inverse_suffix_array)
for item in suffix_array:
print(item + 1, end=' ')
LCP = lcp_array(L, suffix_array)
... | [
6738,
340,
861,
10141,
1330,
19974,
62,
6511,
395,
11,
318,
75,
501,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
201,
198,
220,
220,
220,
406,
796... | 2.009479 | 211 |
# -*- coding: utf-8 -*-
"""
utils.py - Definition of utility functions.
"""
from collections import namedtuple
from lgr.utils import format_cp
VariantProperties = namedtuple('VariantProperties', ['cp', 'type',
'when', 'not_when',
... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
26791,
13,
9078,
532,
30396,
286,
10361,
5499,
13,
198,
37811,
198,
6738,
17268,
1330,
3706,
83,
29291,
198,
198,
6738,
300,
2164,
13,
26791,
1330,
5794,
62,... | 2.279588 | 583 |
#!/usr/bin/env python3
# import modules.
import sys; sys.path.append("..")
import hashlib
import json
import logging
import os
import plac
import unittest
import warnings
from tomes_packager.lib.directory_object import *
from tomes_packager.lib.file_object import *
# enable logging.
logging.basicConfig(level=logging.... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
2,
1330,
13103,
13,
198,
11748,
25064,
26,
25064,
13,
6978,
13,
33295,
7203,
492,
4943,
198,
11748,
12234,
8019,
198,
11748,
33918,
198,
11748,
18931,
198,
11748,
28686,
198,
... | 2.433551 | 459 |
from unv.web.helpers import url_with_domain, url_for_static
| [
6738,
555,
85,
13,
12384,
13,
16794,
364,
1330,
19016,
62,
4480,
62,
27830,
11,
19016,
62,
1640,
62,
12708,
628,
198
] | 2.818182 | 22 |
import pygame
icon = pygame.image.load("diamond_pickaxe.png")
screen_weight = 1750
screen_height = 980
pygame.init()
window = pygame.display.set_mode((screen_weight, screen_height))
pygame.display.set_caption('Pickaxe clicker')
pygame.display.set_icon(icon)
# zmienne
wytrzymao_kilofa = 50
max_wytrzymao_kilofa = 50... | [
11748,
12972,
6057,
198,
198,
4749,
796,
12972,
6057,
13,
9060,
13,
2220,
7203,
67,
8446,
62,
27729,
38231,
13,
11134,
4943,
198,
198,
9612,
62,
6551,
796,
1596,
1120,
198,
9612,
62,
17015,
796,
32614,
198,
198,
9078,
6057,
13,
15003,... | 2.121739 | 2,760 |
import os
from tempfile import NamedTemporaryFile
import h5py
import numpy as np
import torch
from skimage.metrics import adapted_rand_error
from torch.utils.data import DataLoader
from pytorch3dunet.datasets.hdf5 import StandardHDF5Dataset
from pytorch3dunet.datasets.utils import prediction_collate, get_test_loaders... | [
11748,
28686,
198,
6738,
20218,
7753,
1330,
34441,
12966,
5551,
8979,
198,
198,
11748,
289,
20,
9078,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28034,
198,
6738,
1341,
9060,
13,
4164,
10466,
1330,
16573,
62,
25192,
62,
18224,
198,
... | 2.826531 | 196 |
from django.shortcuts import render, get_object_or_404
from django.contrib.auth.decorators import login_required
from catalog.models import Videos, Category, Docs, Subscriber
from django.contrib.auth.decorators import login_required
| [
6738,
42625,
14208,
13,
19509,
23779,
1330,
8543,
11,
651,
62,
15252,
62,
273,
62,
26429,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
12501,
273,
2024,
1330,
17594,
62,
35827,
198,
6738,
18388,
13,
27530,
1330,
18637,
11,
2... | 3.434783 | 69 |
import MySQLdb
db = MySQLdb.connect('localhost', 'root', 'vis_2014', 'FinanceVis')
cursor = db.cursor()
sql = 'select predict_news_word from all_twitter where symbol=%s order by predict_news_word+0 desc'
cursor.execute(sql, ('AAPL', ))
results = cursor.fetchall()
file_twitter_predict = open('twitter_predict_AAPL.csv... | [
11748,
33476,
9945,
198,
198,
9945,
796,
33476,
9945,
13,
8443,
10786,
36750,
3256,
705,
15763,
3256,
705,
4703,
62,
4967,
3256,
705,
37,
14149,
15854,
11537,
198,
66,
21471,
796,
20613,
13,
66,
21471,
3419,
198,
198,
25410,
796,
705,
... | 2.621212 | 198 |
"""
Dot Plot
=========
_thumb: .2, .8
_example_title: Plot distribution.
"""
import matplotlib.pyplot as plt
import numpy as np
import arviz as az
az.style.use("arviz-darkgrid")
data = np.random.normal(0, 1, 1000)
az.plot_dot(data, dotcolor="C1", point_interval=True, figsize=(12, 6))
plt.show()
| [
37811,
198,
35,
313,
28114,
198,
2559,
28,
198,
198,
62,
400,
2178,
25,
764,
17,
11,
764,
23,
198,
62,
20688,
62,
7839,
25,
28114,
6082,
13,
198,
37811,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
299... | 2.447154 | 123 |
# https://open.kattis.com/problems/alphabetspam
import sys
import math
xs = input()
white = 0
lower = 0
higher =0
other = 0
for i in xs:
if i == '_':
white += 1
elif ('a' <= i) & (i <= 'z'):
lower += 1
elif ('A' <= i) & (i <= "Z"):
higher += 1
else:
other += 1
print(... | [
2,
3740,
1378,
9654,
13,
74,
1078,
271,
13,
785,
14,
1676,
22143,
14,
17307,
397,
1039,
79,
321,
198,
198,
11748,
25064,
198,
11748,
10688,
198,
198,
34223,
796,
5128,
3419,
198,
198,
11186,
796,
657,
198,
21037,
796,
657,
198,
4650... | 2.087629 | 194 |
import numpy as np
from sympy import simplify, sqrt, symbols
from sympy.stats import Normal, covariance as cov, variance as var
if __name__ == "__main__":
ab, bc, a, b, c = symbols([
"beta_{A_to_B}",
"beta_{B_to_C}",
"sigma_A",
"sigma_B",
"sigma_C"])
Na = Normal('Na',... | [
11748,
299,
32152,
355,
45941,
198,
6738,
10558,
88,
1330,
30276,
11,
19862,
17034,
11,
14354,
198,
6738,
10558,
88,
13,
34242,
1330,
14435,
11,
44829,
590,
355,
39849,
11,
24198,
355,
1401,
628,
198,
198,
361,
11593,
3672,
834,
6624,
... | 1.576888 | 2,224 |
#!/usr/bin/env python2.7
# coding=<UTF-8>
# tweetpic.py take a photo with the Pi camera and tweet it
# by Alex Eames http://raspi.tv/?p=5918
import tweepy
from subprocess import call
from datetime import datetime
import requests
import json
i = datetime.now() #take time and date for filename
no... | [
198,
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
17,
13,
22,
220,
220,
198,
2,
19617,
28,
27,
48504,
12,
23,
29,
198,
2,
6126,
16564,
13,
9078,
1011,
257,
4590,
351,
262,
13993,
4676,
290,
6126,
340,
220,
220,
198,
2,
416,
4422... | 2.516611 | 602 |
from pathlib import Path
import pandas as pd
from torch.utils.tensorboard import SummaryWriter
| [
6738,
3108,
8019,
1330,
10644,
198,
198,
11748,
19798,
292,
355,
279,
67,
198,
198,
6738,
28034,
13,
26791,
13,
83,
22854,
3526,
1330,
21293,
34379,
628
] | 3.62963 | 27 |