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
import numpy as np
def safe_isinstance(obj, class_path_str):
# this function is copy-paste from the code of the SHAP Python library
# Copyright (c) 2018 Scott Lundberg
"""
Acts as a safe version of isinstance without having to explicitly
import packages which may not exist in the users... | [
11748,
25064,
198,
11748,
299,
32152,
355,
45941,
628,
198,
4299,
3338,
62,
271,
39098,
7,
26801,
11,
1398,
62,
6978,
62,
2536,
2599,
198,
220,
220,
220,
1303,
428,
2163,
318,
4866,
12,
34274,
422,
262,
2438,
286,
262,
6006,
2969,
1... | 2.696477 | 738 |
# this file imports custom routes into the experiment server
from flask import Blueprint, render_template, request, jsonify, Response, abort, current_app
from jinja2 import TemplateNotFound
from functools import wraps
from sqlalchemy import or_
from psiturk.psiturk_config import PsiturkConfig
from psiturk.experiment_... | [
2,
428,
2393,
17944,
2183,
11926,
656,
262,
6306,
4382,
198,
198,
6738,
42903,
1330,
39932,
11,
8543,
62,
28243,
11,
2581,
11,
33918,
1958,
11,
18261,
11,
15614,
11,
1459,
62,
1324,
198,
6738,
474,
259,
6592,
17,
1330,
37350,
3673,
... | 4.149083 | 436 |
from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from PIL import Image
import matplotlib.pyplot as plt
import cv2
import os
import time
import warnings
import torchvision.transforms as transforms
import torchvision.models as models
... | [
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
376,
198,
11748,
28034,
13,
40085,
355,
6436,
198,
198,
6738,
350,
4146,
... | 3.238806 | 134 |
import pandas as pd
import numpy as np
from rdtools import energy_from_power
import pytest
@pytest.fixture
@pytest.fixture
| [
11748,
19798,
292,
355,
279,
67,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
374,
28664,
10141,
1330,
2568,
62,
6738,
62,
6477,
198,
11748,
12972,
9288,
628,
198,
31,
9078,
9288,
13,
69,
9602,
628,
198,
31,
9078,
9288,
13,
69,
96... | 2.78 | 50 |
import copy
import unittest
from pathlib import Path
import ignite
import ignite.metrics as metrics
import torch.nn as nn
import torch.optim as optim
from ignite.metrics import Precision, Recall, MetricsLambda
from transfer_nlp.plugins.config import ExperimentConfig
from transfer_nlp.plugins.regularizers import L1
fr... | [
11748,
4866,
198,
11748,
555,
715,
395,
198,
6738,
3108,
8019,
1330,
10644,
198,
198,
11748,
44794,
198,
11748,
44794,
13,
4164,
10466,
355,
20731,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
28034,
13,
40085,
355,
6436,
198... | 1.999429 | 1,752 |
#!/usr/bin/env python
# coding: utf-8
import sys
sys.path.append('../isoclique')
import isoclique as ic
import networkx as nx
import random
import time
if __name__ == '__main__':
E = nx.karate_club_graph().edges()
'''
encode_method=None
E = [[x,y] for x,y in E]
'''
'''
# generate a graph... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
19617,
25,
3384,
69,
12,
23,
198,
198,
11748,
25064,
198,
17597,
13,
6978,
13,
33295,
10786,
40720,
271,
38679,
2350,
11537,
198,
11748,
318,
38679,
2350,
355,
14158,
198,
11748,
31... | 2.145704 | 803 |
"""
module to run with the -m flag
python -m async_sched.client.stop_schedule "Task 1" --list_schedules 1
"""
import argparse
from async_sched.client.client import stop_schedule
from async_sched.utils import DEFAULT_HOST, DEFAULT_PORT
__all__ = ['NAME', 'get_argparse', 'main']
NAME = 'stop_schedule'
if __name... | [
37811,
198,
21412,
284,
1057,
351,
262,
532,
76,
6056,
198,
198,
29412,
532,
76,
30351,
62,
1416,
704,
13,
16366,
13,
11338,
62,
15952,
5950,
366,
25714,
352,
1,
1377,
4868,
62,
1416,
704,
5028,
352,
198,
198,
37811,
198,
11748,
182... | 2.536232 | 207 |
import os
if __name__ == "__main__":
main()
| [
11748,
28686,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 2.380952 | 21 |
import numpy as np
# ========================================================
#
# Environment-specific cost functions:
#
# ========================================================
#
# Cost function for a whole trajectory:
#
| [
11748,
299,
32152,
355,
45941,
628,
198,
2,
46111,
4770,
1421,
18604,
198,
2,
220,
198,
2,
9344,
12,
11423,
1575,
5499,
25,
198,
2,
628,
198,
198,
2,
46111,
4770,
1421,
18604,
198,
2,
220,
198,
2,
6446,
2163,
329,
257,
2187,
22942... | 4.833333 | 48 |
from .. import *
import math
| [
6738,
11485,
1330,
1635,
198,
11748,
10688,
198
] | 3.625 | 8 |
from titan.dodo_pkg.layer import LayerConfig
| [
6738,
48047,
13,
67,
24313,
62,
35339,
13,
29289,
1330,
34398,
16934,
628
] | 3.538462 | 13 |
# Copyright 2021 Huawei Technologies Co., Ltd
#
# 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 or agreed to... | [
2,
15069,
33448,
43208,
21852,
1766,
1539,
12052,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198... | 2.801037 | 2,508 |
import multiprocessing
print("cpu count is", multiprocessing.cpu_count())
| [
11748,
18540,
305,
919,
278,
198,
4798,
7203,
36166,
954,
318,
1600,
18540,
305,
919,
278,
13,
36166,
62,
9127,
28955,
198
] | 3.363636 | 22 |
from abc import ABCMeta, abstractmethod
| [
6738,
450,
66,
1330,
9738,
48526,
11,
12531,
24396,
628
] | 4.1 | 10 |
import json
import lzma
import struct
import logging
from typing import Tuple, Iterator, List
from lzma import LZMAError, LZMADecompressor
from toolkit.uf2.uf2 import UF2
log = logging.getLogger(__name__)
| [
11748,
33918,
198,
11748,
300,
89,
2611,
198,
11748,
2878,
198,
11748,
18931,
198,
6738,
19720,
1330,
309,
29291,
11,
40806,
1352,
11,
7343,
198,
6738,
300,
89,
2611,
1330,
406,
57,
5673,
12331,
11,
406,
57,
44,
2885,
721,
3361,
44292... | 2.888889 | 72 |
#!/usr/bin/env python3
import unittest
from collections import OrderedDict
from thrift.test.sample_structs.ttypes import DummyStruct, Struct
from thrift.util import struct_to_dict
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
11748,
555,
715,
395,
198,
6738,
17268,
1330,
14230,
1068,
35,
713,
198,
198,
6738,
5636,
2135,
13,
9288,
13,
39873,
62,
7249,
82,
13,
83,
19199,
1330,
360,
13513,
44909,
11,
321... | 3.25 | 56 |
import os
from abc import abstractmethod
from collections.abc import Sequence
from ..options_merger import OptionsMerger
| [
11748,
28686,
198,
6738,
450,
66,
1330,
12531,
24396,
198,
6738,
17268,
13,
39305,
1330,
45835,
198,
198,
6738,
11485,
25811,
62,
647,
1362,
1330,
18634,
13102,
1362,
628
] | 4.241379 | 29 |
# Copyright © 2021 Ingram Micro Inc. All rights reserved.
import sys
from dj_cqrs.constants import NO_QUEUE
from dj_cqrs.management.commands.cqrs_sync import Command as SyncCommand
from dj_cqrs.registries import MasterRegistry
from django.core.management.base import BaseCommand, CommandError
| [
2,
220,
15069,
10673,
33448,
44211,
4527,
3457,
13,
1439,
2489,
10395,
13,
198,
198,
11748,
25064,
198,
198,
6738,
42625,
62,
66,
80,
3808,
13,
9979,
1187,
1330,
8005,
62,
48,
8924,
8924,
198,
6738,
42625,
62,
66,
80,
3808,
13,
2760... | 3.348315 | 89 |
import torch
from .misc import config_to_string
def _load_pretraining_dict(model, state_dict):
"""Load state dictionary from a pre-training snapshot
This is an even less strict version of `model.load_state_dict(..., False)`, which also ignores parameters from
`state_dict` that don't have the same sha... | [
11748,
28034,
198,
198,
6738,
764,
44374,
1330,
4566,
62,
1462,
62,
8841,
628,
628,
198,
198,
4299,
4808,
2220,
62,
5310,
24674,
62,
11600,
7,
19849,
11,
1181,
62,
11600,
2599,
198,
220,
220,
220,
37227,
8912,
1181,
22155,
422,
257,
... | 2.852234 | 291 |
# import tensorflow as tf
# def get_pretrained_classfier(path = '/home/jupyter-ivanljh123/Simulating-Brain-signal-to-control-Hand-Movement-using-GPT2/pretrained/09_0.92'):
# #load pretrained model
# model = tf.keras.models.load_model(path)
# model.trainable = False
# return model
import mne
impor... | [
198,
198,
2,
1330,
11192,
273,
11125,
355,
48700,
198,
198,
2,
825,
651,
62,
5310,
13363,
62,
4871,
69,
959,
7,
6978,
796,
31051,
11195,
14,
73,
929,
88,
353,
12,
13809,
75,
73,
71,
10163,
14,
8890,
8306,
12,
44687,
12,
12683,
2... | 2.930586 | 461 |
import random
from selenium.webdriver.common.by import By
from ui_test.page.base_page import BasePage
| [
11748,
4738,
198,
6738,
384,
11925,
1505,
13,
12384,
26230,
13,
11321,
13,
1525,
1330,
2750,
198,
6738,
334,
72,
62,
9288,
13,
7700,
13,
8692,
62,
7700,
1330,
7308,
9876,
628
] | 3.21875 | 32 |
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE_fast_rcnn for details]
# Written by Ross Girshick
# --------------------------------------------------------
import numpy as np
from distutils.core import setup
from dist... | [
2,
20368,
22369,
198,
2,
12549,
371,
12,
18474,
198,
2,
15069,
357,
66,
8,
1853,
5413,
198,
2,
49962,
739,
383,
17168,
13789,
685,
3826,
38559,
24290,
62,
7217,
62,
6015,
20471,
329,
3307,
60,
198,
2,
22503,
416,
9847,
23837,
1477,
... | 2.979253 | 241 |
#!/usr/bin/env python
# coding: utf-8
# In[ ]:
# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load in
import numpy as np # linear algebra
i... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
19617,
25,
3384,
69,
12,
23,
198,
198,
2,
554,
58,
2361,
25,
628,
198,
2,
770,
11361,
513,
2858,
2058,
351,
867,
7613,
23696,
12782,
6589,
198,
2,
632,
318,
5447,
416,
262,
47... | 2.896928 | 1,009 |
import logging
import pathlib
import pkg_resources
from mopidy import config, ext
__version__ = pkg_resources.get_distribution("Mopidy-YTMusic").version
logger = logging.getLogger(__name__)
| [
11748,
18931,
198,
11748,
3108,
8019,
198,
198,
11748,
279,
10025,
62,
37540,
198,
198,
6738,
285,
404,
19325,
1330,
4566,
11,
1070,
198,
198,
834,
9641,
834,
796,
279,
10025,
62,
37540,
13,
1136,
62,
17080,
3890,
7203,
44,
404,
19325... | 3.046875 | 64 |
from loaddata import TitanicData, HousePriceData, CervicalCancerData
from models import Classifier, Regressor
import json
import os
import argparse
if __name__ == '__main__':
# arguments
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=str, choices=['LR','DT','RF','XGB','DNN'],... | [
6738,
3440,
7890,
1330,
41184,
6601,
11,
2097,
18124,
6601,
11,
327,
712,
605,
34,
8250,
6601,
198,
6738,
4981,
1330,
5016,
7483,
11,
3310,
44292,
198,
11748,
33918,
198,
11748,
28686,
220,
198,
11748,
1822,
29572,
628,
198,
220,
220,
... | 2.637523 | 549 |
"Main"
import sys
from detection.detection import capture_video, run_detection
if __name__ == '__main__':
VIDEO = sys.argv[1]
XML = sys.argv[2]
CAP, CAR_CASCADE = capture_video(VIDEO, XML)
run_detection(CAP, CAR_CASCADE)
| [
1,
13383,
1,
198,
198,
11748,
25064,
198,
6738,
13326,
13,
15255,
3213,
1330,
8006,
62,
15588,
11,
1057,
62,
15255,
3213,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
35507,
796,
25064,
13,
... | 2.438776 | 98 |
'''pyCis - Python Console Intelligence System'''
| [
7061,
6,
9078,
34,
271,
532,
11361,
24371,
9345,
4482,
7061,
6,
198,
220,
220,
220,
220
] | 3.117647 | 17 |
import os
import argparse
from pydub import AudioSegment
from pydub.utils import make_chunks
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="script to split audio files into chunks")
parser.add_argument('--seconds', type=int, default=None,
help='if set to None... | [
11748,
28686,
198,
11748,
1822,
29572,
198,
6738,
279,
5173,
549,
1330,
13491,
41030,
434,
198,
6738,
279,
5173,
549,
13,
26791,
1330,
787,
62,
354,
14125,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
2... | 2.584229 | 279 |
import abc
from sqlparse.sql import Token
from ..exceptions import SQLDecodeError
from .sql_tokens import AliasableToken, SQLToken
from . import query as query_module
from typing import Union as U
| [
11748,
450,
66,
198,
198,
6738,
44161,
29572,
13,
25410,
1330,
29130,
198,
198,
6738,
11485,
1069,
11755,
1330,
16363,
10707,
1098,
12331,
198,
6738,
764,
25410,
62,
83,
482,
641,
1330,
978,
4448,
540,
30642,
11,
16363,
30642,
198,
6738... | 3.45 | 60 |
import time
from print_running_function import print_running_function
# Hackish method to import from another directory
# Useful while xendit-python isn't released yet to the public
import importlib.machinery
loader = importlib.machinery.SourceFileLoader("xendit", "../xendit/__init__.py")
xendit = loader.lo... | [
11748,
640,
201,
198,
201,
198,
6738,
3601,
62,
20270,
62,
8818,
1330,
3601,
62,
20270,
62,
8818,
201,
198,
201,
198,
2,
18281,
680,
2446,
284,
1330,
422,
1194,
8619,
201,
198,
2,
49511,
981,
2124,
437,
270,
12,
29412,
2125,
470,
... | 3 | 117 |
##############################################################################
#
# Copyright (c) 2007 Zope Foundation and Contributors.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS I... | [
29113,
29113,
7804,
4242,
2235,
198,
2,
198,
2,
15069,
357,
66,
8,
4343,
1168,
3008,
5693,
290,
25767,
669,
13,
198,
2,
198,
2,
770,
3788,
318,
2426,
284,
262,
8617,
286,
262,
1168,
3008,
5094,
13789,
11,
198,
2,
10628,
362,
13,
... | 2.84101 | 673 |
# Copyright 2020 Google LLC
#
# 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 or agreed to in writing, ... | [
2,
15069,
12131,
3012,
11419,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
733... | 2.959577 | 1,039 |
# Array
# Given an array A of integers, return true if and only if it is a valid mountain array.
#
# Recall that A is a mountain array if and only if:
#
# A.length >= 3
# There exists some i with 0 < i < A.length - 1 such that:
# A[0] < A[1] < ... A[i-1] < A[i]
# A[i] > A[i+1] > ... > A[B.length - 1]
#
#
# Example 1:
... | [
2,
15690,
198,
198,
2,
11259,
281,
7177,
317,
286,
37014,
11,
1441,
2081,
611,
290,
691,
611,
340,
318,
257,
4938,
8598,
7177,
13,
198,
2,
198,
2,
44536,
326,
317,
318,
257,
8598,
7177,
611,
290,
691,
611,
25,
198,
2,
198,
2,
... | 2.318182 | 220 |
from uuid import UUID
from ..exceptions import CheckError
| [
6738,
334,
27112,
1330,
471,
27586,
198,
198,
6738,
11485,
1069,
11755,
1330,
6822,
12331,
628,
628,
198
] | 3.5 | 18 |
import numpy as np
import librosa, librosa.display
import matplotlib.pyplot as plt
FIG_SIZE = (15,10)
file = "/home/jack/Documents/python/PycharmProjects/untitled2/show the wav/dog.wav"
signal, sample_rate = librosa.load(file, sr=22050)
plt.figure(figsize=FIG_SIZE)
librosa.display.waveplot(signal, sample_rate, alph... | [
11748,
299,
32152,
355,
45941,
198,
11748,
9195,
4951,
64,
11,
9195,
4951,
64,
13,
13812,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
198,
16254,
62,
33489,
796,
357,
1314,
11,
940,
8,
198,
198,
7753,
796,
128... | 2.364486 | 321 |
import os
import functools
import tools
import tensorflow as tf
import numpy as np
import pickle
import pathlib
import off_policy
from dreamer import Dreamer, setup_dreamer, create_envs, count_steps, make_dataset, parse_dreamer_args
if __name__ == '__main__':
args, remaining = parse_dreamer_args()
main(args.log... | [
11748,
28686,
198,
11748,
1257,
310,
10141,
198,
11748,
4899,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2298,
293,
198,
11748,
3108,
8019,
198,
11748,
572,
62,
30586,
198,
6738,
4320,
263,
... | 3.111111 | 108 |
from notebook_utils import synthesize
from utils import hparams as hp
import utils.text.cleaners as cleaners
from scipy.io import wavfile
import numpy as np
import string
import argparse
SAMPLE_RATE = 22050
parser = argparse.ArgumentParser()
parser.add_argument(
'-t','--text', help='Input text',
default='Đó ... | [
6738,
20922,
62,
26791,
1330,
24983,
1096,
198,
6738,
3384,
4487,
1330,
289,
37266,
355,
27673,
198,
198,
11748,
3384,
4487,
13,
5239,
13,
27773,
364,
355,
50102,
198,
6738,
629,
541,
88,
13,
952,
1330,
266,
615,
7753,
198,
11748,
299... | 2.555556 | 549 |
5351 4c69 7465 2066 6f72 6d61 7420 3300
0400 0101 0040 2020 0000 003b 0000 0000
0000 0000 0000 0000 0000 003b 0000 0001
0000 0000 0000 0000 0000 0001 0000 0000
0000 0000 0000 0000 0000 0000 0000 0000
0000 0000 0000 0000 0000 0000 0000 0000
0000 0000 0500 0000 0603 e200 0000 0026
03fb 03f1 03ec 03f6 03e7 03e2 0000 0000
... | [
20,
35273,
604,
66,
3388,
8915,
2996,
1160,
2791,
718,
69,
4761,
718,
67,
5333,
8915,
1238,
4747,
405,
198,
3023,
405,
5534,
486,
3571,
1821,
12131,
17643,
3571,
18,
65,
17643,
17643,
198,
2388,
17643,
17643,
17643,
17643,
3571,
18,
6... | 3.089201 | 31,502 |
from django.apps import AppConfig
| [
6738,
42625,
14208,
13,
18211,
1330,
2034,
16934,
628
] | 3.888889 | 9 |
import numpy as np
import sys
| [
198,
11748,
299,
32152,
355,
45941,
198,
11748,
25064,
628
] | 3.2 | 10 |
# Copyright © 2018, D-Tech, LLC, All Rights Reserved.
# Disclaimer: This software is provided "AS IS" without warrantees.
# D-Tech, LLC has no oblication to provide any maintainence, update
# or support for this software. Under no circumstances shall D-Tech,
# LLC be liable to any parties for direct, indirect, s... | [
2,
15069,
10673,
2864,
11,
360,
12,
17760,
11,
11419,
11,
1439,
6923,
33876,
13,
220,
198,
2,
3167,
17111,
25,
770,
3788,
318,
2810,
366,
1921,
3180,
1,
1231,
8084,
2841,
13,
220,
220,
198,
2,
360,
12,
17760,
11,
11419,
468,
645,
... | 2.812903 | 310 |
import wmi
_wmi_handle = None | [
11748,
266,
11632,
198,
198,
62,
86,
11632,
62,
28144,
796,
6045
] | 2.5 | 12 |
import datetime
import os
import uuid
import copy
import json
import shutil
import threading
import time
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Union, Optional, Tuple
from ludwig.api import LudwigModel
from ludwig.backend import RAY, initialize_backend
from ludwig.callbacks imp... | [
11748,
4818,
8079,
198,
11748,
28686,
198,
11748,
334,
27112,
198,
11748,
4866,
198,
11748,
33918,
198,
11748,
4423,
346,
198,
11748,
4704,
278,
198,
11748,
640,
198,
6738,
450,
66,
1330,
9738,
11,
12531,
24396,
198,
6738,
3108,
8019,
1... | 3.103512 | 541 |
import sys
import cv2
import numpy as np
if __name__=='__main__':
# Create SIFT object
sift = cv2.xfeatures2d.SIFT_create()
# Create Flann Matcher Object
flann = cv2.FlannBasedMatcher(dict(algorithm = 0, trees = 5), dict(checks = 50))
# Gets list of image files from arguments
files = sys.argv... | [
11748,
25064,
198,
11748,
269,
85,
17,
198,
11748,
299,
32152,
355,
45941,
198,
198,
361,
11593,
3672,
834,
855,
6,
834,
12417,
834,
10354,
198,
220,
220,
220,
1303,
13610,
311,
32297,
2134,
198,
220,
220,
220,
264,
2135,
796,
269,
... | 2.164719 | 1,797 |
# Copyright (c) 2017-2018 Wind River Systems, 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 law... | [
2,
15069,
357,
66,
8,
2177,
12,
7908,
3086,
5866,
11998,
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,
743,
407,
779,
428,
2393,
2845,
287,
11846,
... | 2.342298 | 818 |
import argparse
import os
import textwrap
import deployment_options
import utils
if __name__ == "__main__":
main()
| [
11748,
1822,
29572,
198,
11748,
28686,
198,
11748,
2420,
37150,
198,
198,
11748,
14833,
62,
25811,
198,
11748,
3384,
4487,
628,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
... | 3.04878 | 41 |
# SPDX-FileCopyrightText: 2022 Geoffrey Lentner
# SPDX-License-Identifier: Apache-2.0
"""Automated tests for HyperShell."""
| [
2,
30628,
55,
12,
8979,
15269,
8206,
25,
33160,
42803,
43751,
1008,
198,
2,
30628,
55,
12,
34156,
12,
33234,
7483,
25,
24843,
12,
17,
13,
15,
198,
198,
37811,
38062,
515,
5254,
329,
15079,
23248,
526,
15931,
198
] | 3.205128 | 39 |
import logging
from datetime import timedelta, date
import progressbar
import structlog
from collections import defaultdict
from django.core.management.base import BaseCommand
from django.utils import timezone, dateparse
from ...actions.accounts import create_invoices
from ...models import Account
logger = structl... | [
11748,
18931,
198,
6738,
4818,
8079,
1330,
28805,
12514,
11,
3128,
198,
198,
11748,
4371,
5657,
198,
11748,
2878,
6404,
198,
6738,
17268,
1330,
4277,
11600,
198,
6738,
42625,
14208,
13,
7295,
13,
27604,
13,
8692,
1330,
7308,
21575,
198,
... | 3.885057 | 87 |
from collections import namedtuple
import concurrent
import io
import json
import os
import pathlib
import pickle
import tarfile
import boto3
import imageio
import numpy as np
import utils
ClassInfo = namedtuple('ClassInfo', ['wnid', 'cid', 'synset', 'wikipedia_pages', 'gloss'])
| [
6738,
17268,
1330,
3706,
83,
29291,
198,
11748,
24580,
198,
11748,
33245,
198,
11748,
33918,
198,
11748,
28686,
198,
11748,
3108,
8019,
198,
11748,
2298,
293,
198,
11748,
13422,
7753,
198,
198,
11748,
275,
2069,
18,
198,
11748,
2939,
952,... | 3.298851 | 87 |
""" Contains the Encoder-Decoder model for image captioning """
import torch.nn as nn
from cnn import CNN
from rnn import RNN
from transformer import Transformer
class CaptioningModel(nn.Module):
""" Image captioning model """
def forward(self, images, captions, predict=False):
""" Forward pass of ... | [
37811,
49850,
262,
14711,
12342,
12,
10707,
12342,
2746,
329,
2939,
8305,
278,
220,
37227,
198,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
6738,
269,
20471,
1330,
8100,
198,
6738,
374,
20471,
1330,
371,
6144,
198,
6738,
47385,
133... | 3.105263 | 152 |
from pyspark import SparkContext
import json
import gzip
import marshal
''' Configuration Parameters '''
tweetsFile = "/tmp/ist169518/out_*/part*"
outFileProcessedDataset = "/tmp/ist169518/filtered-scored"
# Emotional Lexicons
# csv files with first column with the word, and second with the score separated with comm... | [
6738,
279,
893,
20928,
1330,
17732,
21947,
198,
11748,
33918,
198,
11748,
308,
13344,
198,
11748,
22397,
282,
198,
198,
7061,
6,
28373,
40117,
705,
7061,
198,
198,
83,
732,
1039,
8979,
796,
12813,
22065,
14,
396,
1433,
3865,
1507,
14,
... | 2.723183 | 1,156 |
# -*- coding: utf-8 -*-
import logging
from . import instrumentation
from .dotdict import dotdict
##################################################################
### defaults and constants
##################################################################
PRE = 'pre'
POST = 'post'
DEFAULT_MAX_HISTORY_SIZE = 2
I... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
198,
11748,
18931,
198,
198,
6738,
764,
1330,
8875,
341,
198,
6738,
764,
26518,
11600,
1330,
16605,
11600,
198,
198,
29113,
29113,
2235,
198,
21017,
26235,
290,
38491,
198... | 5.756923 | 325 |
import rumps
import requests
import json
API_URL = 'https://koinex.in/api/ticker'
UPDATE_INTERVAL = 60
CURRENCIES = {
'Bitcoin': 'BTC',
'Ethereum': 'ETH',
'Ripple': 'XRP',
'Litecoin': 'LTC',
'Bitcoin Cash': 'BCH',
}
if __name__ == "__main__":
KoinexStatusBarApp().run() | [
11748,
7440,
862,
198,
11748,
7007,
198,
11748,
33918,
198,
198,
17614,
62,
21886,
796,
705,
5450,
1378,
7204,
500,
87,
13,
259,
14,
15042,
14,
83,
15799,
6,
198,
198,
16977,
62,
41358,
23428,
796,
3126,
198,
198,
34,
31302,
24181,
... | 2.282443 | 131 |
# Generated by Django 2.1.7 on 2019-05-03 02:36
from django.db import migrations
| [
2,
2980,
515,
416,
37770,
362,
13,
16,
13,
22,
319,
13130,
12,
2713,
12,
3070,
7816,
25,
2623,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
628
] | 2.766667 | 30 |
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 20 13:32:20 2021
#--- ag csv results to single file based on dashboard_dbs
#--- Murilo Vianna (murilodsv@gmail.com)
#--- Jul, 2021.
#--- Dev-log in: https://github.com/Murilodsv/py-jules
@author: muril
"""
# DEBUG import os; os.chdir('C:/Murilo/py-jules'... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
41972,
319,
30030,
2758,
1160,
1511,
25,
2624,
25,
1238,
33448,
628,
220,
220,
220,
1303,
6329,
556,
269,
21370,
2482,
284,
2060,
2393,
1912,
319,
30415,
62,... | 1.995512 | 1,337 |
"""
With a physics component, you can fly.
Well, not for long.
You'll shortly fall to your death.
"""
import pymunk
import whoosh.maths
from whoosh.components.base import BaseComponent
class PhysicsComponent(BaseComponent):
"""
Useful for recreating Angry Birds.
GameWorld.add_blob will automatically add t... | [
37811,
198,
3152,
257,
11887,
7515,
11,
345,
460,
6129,
13,
198,
5779,
11,
407,
329,
890,
13,
198,
1639,
1183,
8972,
2121,
284,
534,
1918,
13,
198,
37811,
198,
11748,
279,
4948,
2954,
198,
11748,
508,
3768,
13,
11018,
82,
198,
6738,... | 2.444105 | 1,637 |
from Class.rqlite import rqlite
import subprocess, socket, psutil, json, time
| [
6738,
5016,
13,
81,
13976,
578,
1330,
374,
13976,
578,
198,
11748,
850,
14681,
11,
17802,
11,
26692,
22602,
11,
33918,
11,
640,
198
] | 3.25 | 24 |
"""
str - string
"""
print('aspas simples')
print("aspas duplas")
print(123456) # integer, conversao implicita para string
print("essa é uma 'string' (str).")
print('essa é uma "string" (str).')
print('essa é uma \'string\' (str).')
print("essa é uma \"string\" (str).") # '\' caracter de escape
print('essa é uma \n... | [
37811,
198,
2536,
532,
4731,
198,
37811,
198,
198,
4798,
10786,
5126,
292,
985,
2374,
11537,
198,
4798,
7203,
5126,
292,
14184,
292,
4943,
198,
4798,
7,
10163,
29228,
8,
220,
1303,
18253,
11,
3453,
5488,
16992,
64,
31215,
4731,
198,
4... | 2.696203 | 158 |
#!/usr/bin/env python
###########################################################################
#
# Written in 2009 by Ian Katz <ijk5@mit.edu>
# Terms: WTFPL (http://sam.zoy.org/wtfpl/)
# See COPYING and WARRANTY files included in this distribution
#
#####################################... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
29113,
29113,
7804,
21017,
198,
2,
220,
220,
220,
220,
198,
2,
220,
220,
220,
22503,
287,
3717,
416,
12930,
36290,
1279,
45961,
20,
31,
2781,
13,
15532,
29,
220,
220,
220,
220,
220,
... | 2.672302 | 769 |
import numpy as np
import matplotlib
from matplotlib import colors
from matplotlib import cm
import matplotlib.pyplot as plt
import folium
from folium.plugins import HeatMap
from folium.plugins import MarkerCluster
from loci.analytics import bbox, kwds_freq
from wordcloud import WordCloud
from pysal.viz.mapclassify imp... | [
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29487,
8019,
198,
6738,
2603,
29487,
8019,
1330,
7577,
198,
6738,
2603,
29487,
8019,
1330,
12067,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
5955,
1505,
198,
... | 2.214953 | 2,889 |
from flask import Blueprint, request, jsonify
import pymongo
client = pymongo.MongoClient('localhost',27017)
db = client.TCGA_Slide_DB
dsa = Blueprint('dsa', __name__)
@dsa.route('/annotations', methods=['POST','OPTIONS'])
@dsa.route('/annotations', methods=['GET','OPTIONS'])
| [
6738,
42903,
1330,
39932,
11,
2581,
11,
33918,
1958,
198,
11748,
279,
4948,
25162,
198,
198,
16366,
796,
279,
4948,
25162,
13,
44,
25162,
11792,
10786,
36750,
3256,
1983,
29326,
8,
198,
9945,
796,
5456,
13,
4825,
9273,
62,
11122,
485,
... | 2.772277 | 101 |
import urllib
# make response
| [
11748,
2956,
297,
571,
198,
198,
2,
787,
2882,
198,
220,
220,
220,
220,
198
] | 2.4 | 15 |
from unittest import mock
from django.urls import reverse
from parameterized import parameterized
from rest_framework import status
from api.applications.models import PartyOnApplication
from lite_content.lite_api.strings import PartyErrors
from api.parties.enums import PartyType, SubType
from api.parties.models impo... | [
6738,
555,
715,
395,
1330,
15290,
198,
198,
6738,
42625,
14208,
13,
6371,
82,
1330,
9575,
198,
6738,
11507,
1143,
1330,
11507,
1143,
198,
6738,
1334,
62,
30604,
1330,
3722,
198,
198,
6738,
40391,
13,
1324,
677,
602,
13,
27530,
1330,
3... | 3.818966 | 116 |
from datetime import datetime
theTime = '2019-12-20 10:22:00'
theTime = datetime.strptime(theTime, '%Y-%m-%d %H:%M:%S')
print(theTime) | [
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
1169,
7575,
796,
705,
23344,
12,
1065,
12,
1238,
838,
25,
1828,
25,
405,
6,
198,
1169,
7575,
796,
4818,
8079,
13,
2536,
457,
524,
7,
1169,
7575,
11,
705,
4,
56,
12,
4,
76,
12,
4,
6... | 2.213115 | 61 |
import importlib
import sys
| [
11748,
1330,
8019,
198,
11748,
25064,
198
] | 4 | 7 |
#!C:\Python27\python.exe -u
#!/usr/bin/env python
import MySQLdb
import hashlib
import cgi
import uuid
print "Content-type: text/html"
print
print """
<html>
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<titl... | [
2,
0,
34,
7479,
37906,
1983,
59,
29412,
13,
13499,
532,
84,
198,
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
11748,
33476,
9945,
198,
11748,
12234,
8019,
198,
11748,
269,
12397,
198,
11748,
334,
27112,
198,
198,
4798,
366,
... | 2.577941 | 680 |
from .reminders import Reminders
Default = Reminders
| [
6738,
764,
2787,
29700,
1330,
3982,
29700,
198,
19463,
796,
3982,
29700,
198
] | 4.076923 | 13 |
#
# Copyright (c) 2013, Prometheus Research, LLC
# Released under MIT license, see `LICENSE` for details.
#
from .check import maybe, oneof, choiceof, listof, tupleof, dictof, raises
from .core import Test, Field, Record
from .ctl import Control
from .load import locate, Location
from .run import run, main
from .std ... | [
2,
198,
2,
15069,
357,
66,
8,
2211,
11,
42696,
4992,
11,
11419,
198,
2,
28728,
739,
17168,
5964,
11,
766,
4600,
43,
2149,
24290,
63,
329,
3307,
13,
198,
2,
628,
198,
6738,
764,
9122,
1330,
3863,
11,
530,
1659,
11,
3572,
1659,
11... | 3.504505 | 111 |
import torch
import torch.nn as nn
class EvonormPrimitive(nn.Module):
"""Abstract base class for the evonorm primitive layers
"""
class PrimitiveAdd(EvonormPrimitive):
""" Primitive Add Operation
"""
class PrimitiveMul(EvonormPrimitive):
"""Primitive Multiply Operation
"""
class PrimitiveDiv... | [
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
198,
4871,
4319,
261,
579,
23828,
1800,
7,
20471,
13,
26796,
2599,
198,
220,
220,
220,
37227,
23839,
2779,
1398,
329,
262,
819,
261,
579,
20049,
11685,
198,
220,
220,
220,... | 2.817699 | 1,130 |
import spotipy
from spotipy.oauth2 import SpotifyClientCredentials
from dotenv import load_dotenv
load_dotenv()
lz_uri = 'spotify:artist:36QJpDe2go2KgaRleHCDTp'
client_credentials_manager = SpotifyClientCredentials(client_id='CLIENT_ID',
client_secret='CLIENT_SECRET')
spotify =... | [
11748,
4136,
541,
88,
198,
6738,
4136,
541,
88,
13,
12162,
1071,
17,
1330,
26778,
11792,
34,
445,
14817,
198,
6738,
16605,
24330,
1330,
3440,
62,
26518,
24330,
198,
198,
2220,
62,
26518,
24330,
3419,
198,
198,
75,
89,
62,
9900,
796,
... | 2.371747 | 269 |
import logging
| [
11748,
18931,
628,
198
] | 4.25 | 4 |
# Copyright 2010-2016, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and ... | [
2,
15069,
3050,
12,
5304,
11,
3012,
3457,
13,
198,
2,
1439,
2489,
10395,
13,
198,
2,
198,
2,
2297,
396,
3890,
290,
779,
287,
2723,
290,
13934,
5107,
11,
351,
393,
1231,
198,
2,
17613,
11,
389,
10431,
2810,
326,
262,
1708,
3403,
... | 1.848193 | 4,980 |
from ..graph import Arc, ArcType, Node, NodeType, Graph, GraphType, GraphSet
from ..gcn import GCN
import tensorflow as tf
import numpy as np
tf.compat.v1.disable_eager_execution()
| [
6738,
11485,
34960,
1330,
10173,
11,
10173,
6030,
11,
19081,
11,
19081,
6030,
11,
29681,
11,
29681,
6030,
11,
29681,
7248,
198,
6738,
11485,
70,
31522,
1330,
20145,
45,
198,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
299,
32... | 2.907692 | 65 |
#!/usr/bin/env python
#-----------------------------------------------------------------------
# twitter-user-search
# - performs a search for users matching a certain query
#-----------------------------------------------------------------------
from twitter import *
#----------------------------------------------... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
2,
10097,
26866,
198,
2,
17044,
12,
7220,
12,
12947,
198,
2,
220,
532,
17706,
257,
2989,
329,
2985,
12336,
257,
1728,
12405,
198,
2,
10097,
26866,
198,
198,
6738,
17044,
1330,
1... | 4.94863 | 292 |
#!/usr/bin/env python3
# You are probably well aware of the 'birthday paradox'
# https://en.wikipedia.org/wiki/Birthday_problem
# Let's try simulating it
# You will need a list for the 365 day calendar
# You will need a set number of people (e.g. 25)
# During each 'trial' you do the following
# Choose a person
# Git ... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
2,
921,
389,
2192,
880,
3910,
286,
262,
705,
24280,
820,
22226,
6,
198,
2,
3740,
1378,
268,
13,
31266,
13,
2398,
14,
15466,
14,
38480,
820,
62,
45573,
198,
2,
3914,
338,
... | 2.737463 | 339 |
from datetime import datetime, timedelta
import numpy as np
import pytest
from pytest import fixture
from vanilla_option_pricing.option import VanillaOption, option_list_to_pandas_dataframe, \
pandas_dataframe_to_option_list
@fixture
@fixture
| [
6738,
4818,
8079,
1330,
4818,
8079,
11,
28805,
12514,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
12972,
9288,
198,
6738,
12972,
9288,
1330,
29220,
198,
198,
6738,
16858,
62,
18076,
62,
1050,
6345,
13,
18076,
1330,
33897,
19722,
... | 3.083333 | 84 |
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from flask_caching import Cache
| [
6738,
42903,
1330,
46947,
198,
6738,
42903,
62,
25410,
282,
26599,
1330,
16363,
2348,
26599,
198,
6738,
42903,
62,
66,
8103,
1330,
34088,
628
] | 4.041667 | 24 |
from inspect import formatargvalues
import discord, datetime, db, time, os
import pandas as pd
from discord import Embed
from discord.ext.commands import Cog, command
from apscheduler.schedulers.asyncio import AsyncIOScheduler
from apscheduler.triggers.cron import CronTrigger
# from discord_components import Button, Bu... | [
6738,
10104,
1330,
5794,
853,
27160,
198,
11748,
36446,
11,
4818,
8079,
11,
20613,
11,
640,
11,
28686,
198,
11748,
19798,
292,
355,
279,
67,
198,
6738,
36446,
1330,
13302,
276,
198,
6738,
36446,
13,
2302,
13,
9503,
1746,
1330,
327,
51... | 2.653226 | 248 |
import logging
from ._version import __version__
__all__ = [
"__version__",
]
logger = logging.getLogger(__name__)
logging.basicConfig()
| [
11748,
18931,
198,
198,
6738,
47540,
9641,
1330,
11593,
9641,
834,
198,
198,
834,
439,
834,
796,
685,
198,
220,
220,
220,
366,
834,
9641,
834,
1600,
198,
60,
198,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834... | 2.769231 | 52 |
from pygame_rl.scenario.gridworld.envs.gridworld_v0 import GridworldV0
from pygame_rl.scenario.gridworld.envs.gridworld_v1 import GridworldV1
| [
6738,
12972,
6057,
62,
45895,
13,
1416,
39055,
13,
25928,
6894,
13,
268,
14259,
13,
25928,
6894,
62,
85,
15,
1330,
24846,
6894,
53,
15,
198,
6738,
12972,
6057,
62,
45895,
13,
1416,
39055,
13,
25928,
6894,
13,
268,
14259,
13,
25928,
... | 2.730769 | 52 |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# 该脚本平均每小时提交 4万5千多条URL
# 推荐 0.3s,方便及时停止抓取， 一天提交10万~15万 URL PS：因为URL一旦提交到队列中，就不可修改
# python qiniu_big_fetch.py <ak> <sk> <bucket> <zone(z0 z1)> <file_path> <sleep_time>
import urlparse, hmac, hashlib, base64, commands, sys, time
def Qiniu_token(access_key, secret_key... | [
2,
0,
1220,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
5525,
107,
98,
164,
226,
248,
17312,
105,
33176,
111,
161,
251,
229,
162,
107,
237,
22887,
237,
33768,
35050,
... | 1.947143 | 1,400 |
# Exercício Python 041: A Confederação Nacional de Natação precisa de um programa que leia o ano de nascimento de um atleta e mostre sua categoria, de acordo com a idade:
# - Até 9 anos: MIRIM
# - Até 14 anos: INFANTIL
# - Até 19 anos: JÚNIOR
# - Até 25 anos: SÊNIOR
# - Acima de 25 anos: MASTER
from datetime import da... | [
2,
1475,
2798,
8836,
66,
952,
11361,
657,
3901,
25,
317,
16986,
64,
16175,
28749,
399,
330,
1538,
390,
399,
1045,
16175,
28749,
3718,
9160,
390,
23781,
1430,
64,
8358,
443,
544,
267,
281,
78,
390,
299,
3372,
3681,
78,
390,
23781,
37... | 2.383285 | 347 |
"""
Description:
Author: Jiaqi Gu (jqgu@utexas.edu)
Date: 2021-03-31 17:48:41
LastEditors: Jiaqi Gu (jqgu@utexas.edu)
LastEditTime: 2021-09-26 00:51:50
"""
from typing import Tuple
import torch
import torch.nn as nn
from pyutils.config import configs
from pyutils.datasets import get_dataset
from pyutils.loss import A... | [
37811,
198,
11828,
25,
198,
13838,
25,
449,
544,
40603,
1962,
357,
73,
80,
5162,
31,
315,
1069,
292,
13,
15532,
8,
198,
10430,
25,
33448,
12,
3070,
12,
3132,
1596,
25,
2780,
25,
3901,
198,
5956,
18378,
669,
25,
449,
544,
40603,
19... | 2.677871 | 357 |
"""
Graphviz extensions for Markdown.
Renders the output inline, eliminating the need to configure an output
directory.
Supports outputs types of SVG and PNG. The output will be taken from the
filename specified in the tag. Example:
{% dot attack_plan.svg
digraph G {
rankdir=LR
Earth [peripheries=... | [
37811,
198,
37065,
85,
528,
18366,
329,
2940,
2902,
13,
198,
49,
7338,
262,
5072,
26098,
11,
18591,
262,
761,
284,
17425,
281,
5072,
198,
34945,
13,
198,
198,
15979,
2096,
23862,
3858,
286,
45809,
290,
36182,
13,
383,
5072,
481,
307,
... | 2.565476 | 336 |
from django.conf import settings
from django.core.management import call_command, get_commands, load_command_class
from django.core.management.base import BaseCommand, CommandError
from django.db import connection
from django_tenants.utils import get_tenant_model, get_public_schema_name
class BaseTenantCommand(Base... | [
6738,
42625,
14208,
13,
10414,
1330,
6460,
198,
6738,
42625,
14208,
13,
7295,
13,
27604,
1330,
869,
62,
21812,
11,
651,
62,
9503,
1746,
11,
3440,
62,
21812,
62,
4871,
198,
6738,
42625,
14208,
13,
7295,
13,
27604,
13,
8692,
1330,
7308,... | 2.465315 | 937 |
########################################################
# run_rt.py
# Author: Jamie Zhu <jimzhu@GitHub>
# Created: 2014/2/6
# Last updated: 2014/5/8
# Implemented approach: CloudPred
# Evaluation metrics: MAE, NMAE, RMSE, MRE, NPRE
########################################################
import numpy as np
... | [
29113,
14468,
7804,
201,
198,
2,
1057,
62,
17034,
13,
9078,
220,
201,
198,
2,
6434,
25,
17826,
33144,
1279,
73,
320,
89,
13415,
31,
38,
270,
16066,
29,
201,
198,
2,
15622,
25,
1946,
14,
17,
14,
21,
201,
198,
2,
4586,
6153,
25,
... | 2.948332 | 929 |
import torch
import torch.nn as nn
import torch.nn.functional as functional
class upsampling(nn.Module):
'''
net from Deeper depth prediction with fully convolutional residual
networks
Args of __init__():
in_channels: the # of channels of the input
out_channels: the # of chann... | [
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
10345,
198,
198,
4871,
19649,
321,
11347,
7,
20471,
13,
26796,
2599,
198,
220,
220,
220,
220,
198,
220,
220,
220,
705,
7061,
198,
... | 2.10559 | 1,127 |
import math
import torch
import torch.nn as nn
from .GeneralModels import BasicBlock
| [
11748,
10688,
198,
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
6738,
764,
12218,
5841,
1424,
1330,
14392,
12235,
628
] | 3.73913 | 23 |
#CodeFights
#Given a year, return the century it is in. The first century spans from the year 1 up to and including the year 100, the second - from the year 101 up to and including the year 200, etc. | [
2,
10669,
37,
2337,
198,
2,
15056,
257,
614,
11,
1441,
262,
4289,
340,
318,
287,
13,
383,
717,
4289,
32727,
422,
262,
614,
352,
510,
284,
290,
1390,
262,
614,
1802,
11,
262,
1218,
532,
422,
262,
614,
8949,
510,
284,
290,
1390,
2... | 3.98 | 50 |
from raspador import Pilot, UserInteractor, BrowserInteractor
from typing import Dict, List | [
6738,
374,
5126,
7079,
1330,
21697,
11,
11787,
9492,
11218,
11,
34270,
9492,
11218,
198,
6738,
19720,
1330,
360,
713,
11,
7343
] | 4.136364 | 22 |
# GENERATED VERSION FILE
# TIME: Thu May 6 12:37:04 2021
__version__ = '1.2.0+unknown'
short_version = '1.2.0'
version_info = (1, 2, 0)
| [
2,
24700,
1137,
11617,
44156,
2849,
45811,
198,
2,
20460,
25,
26223,
1737,
220,
718,
1105,
25,
2718,
25,
3023,
33448,
198,
198,
834,
9641,
834,
796,
705,
16,
13,
17,
13,
15,
10,
34680,
6,
198,
19509,
62,
9641,
796,
705,
16,
13,
... | 2.262295 | 61 |
import pybullet_data
import pybullet as p
import numpy as np
if __name__ == '__main__':
p.connect(p.GUI)
p.setAdditionalSearchPath(pybullet_data.getDataPath())
plane = p.createCollisionShape(p.GEOM_PLANE)
p.changeDynamics(plane, -1, lateralFriction=1)
p.createMultiBody(0, plane)
p.setGravity... | [
11748,
12972,
15065,
1616,
62,
7890,
198,
11748,
12972,
15065,
1616,
355,
279,
198,
11748,
299,
32152,
355,
45941,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
628,
220,
220,
220,
279,
13,
8443,
7,
79,
13,
... | 2.34359 | 195 |
from get_classification_file_with_original_annotation import get_image_label_dict_from_original_annotation, get_classification_file_based_on_label
original_annotation_path="/git/PaDiM-master/assets_new_new/data/2021-03-05/json_for_classification"
image_data_root="/git/PaDiM-master/kangqiang_result/segment_image_resul... | [
6738,
651,
62,
4871,
2649,
62,
7753,
62,
4480,
62,
14986,
62,
1236,
14221,
1330,
220,
651,
62,
9060,
62,
18242,
62,
11600,
62,
6738,
62,
14986,
62,
1236,
14221,
11,
651,
62,
4871,
2649,
62,
7753,
62,
3106,
62,
261,
62,
18242,
198,... | 2.793249 | 237 |
#!/usr/bin/python
"""
This application reads key value pairs from the command line input and writes to a dictionary, which is then written to a config file
The preferred file extension is .cfg
"""
import signal
import sys
import HackPSUconfig as config
#Initialize a dictionary and define the save and configFile variab... | [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
37811,
198,
1212,
3586,
9743,
1994,
1988,
14729,
422,
262,
3141,
1627,
5128,
290,
6797,
284,
257,
22155,
11,
543,
318,
788,
3194,
284,
257,
4566,
2393,
198,
464,
9871,
2393,
7552,
318,
764,
... | 3.431034 | 406 |
# Generated by Django 3.1.6 on 2021-02-20 12:26
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
513,
13,
16,
13,
21,
319,
33448,
12,
2999,
12,
1238,
1105,
25,
2075,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.84375 | 32 |
import logging
from abc import ABC
from abc import abstractmethod
from typing import List
import torch
logger = logging.getLogger(__name__)
| [
11748,
18931,
198,
6738,
450,
66,
1330,
9738,
198,
6738,
450,
66,
1330,
12531,
24396,
198,
6738,
19720,
1330,
7343,
198,
198,
11748,
28034,
198,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
628,
198
] | 3.512195 | 41 |
import os
from src.utils.utils import load_config
def test_load_config():
"""Test the load_config function"""
config = load_config(".env.test")
assert config["app_name"] == os.getenv("APP_NAME")
assert config["parameters_path"] == os.getenv("PARAMETERS_PATH")
assert config["artifact_path"] == os... | [
11748,
28686,
198,
6738,
12351,
13,
26791,
13,
26791,
1330,
3440,
62,
11250,
628,
198,
4299,
1332,
62,
2220,
62,
11250,
33529,
198,
220,
220,
220,
37227,
14402,
262,
3440,
62,
11250,
2163,
37811,
628,
220,
220,
220,
4566,
796,
3440,
6... | 2.64557 | 316 |
import logging
from django import forms
from django.core.files import File
from django.core.files.storage import default_storage
from django.core.files.uploadedfile import UploadedFile
from django.utils.crypto import get_random_string
from django.utils.translation import gettext_lazy as _
logger = logging.getLogger(_... | [
11748,
18931,
198,
198,
6738,
42625,
14208,
1330,
5107,
198,
6738,
42625,
14208,
13,
7295,
13,
16624,
1330,
9220,
198,
6738,
42625,
14208,
13,
7295,
13,
16624,
13,
35350,
1330,
4277,
62,
35350,
198,
6738,
42625,
14208,
13,
7295,
13,
166... | 2.058778 | 1,293 |
#!/usr/bin/python
import sys
import re
import pandas as pd
import csv
if sys.argv[1].startswith("-f"):
col_number = int(sys.argv[1][2]) - 1
input_file = sys.argv[2]
else:
col_number = 0
input_file = sys.argv[1]
name_dict = {}
with open("Homo_sapiens.GRCh37.75.gtf", "r") as f:
for line in f:
i... | [
2,
48443,
14629,
14,
8800,
14,
29412,
201,
198,
201,
198,
11748,
25064,
201,
198,
11748,
302,
201,
198,
11748,
19798,
292,
355,
279,
67,
201,
198,
11748,
269,
21370,
201,
198,
201,
198,
361,
25064,
13,
853,
85,
58,
16,
4083,
9688,
... | 2.069717 | 459 |
#Array
"""
Idea:
let forward[i] = nums[0]*nums[1]*...*nums[i-1] ,backward[i] = backward[i] = nums[i+1]*nums[i+2]*...*nums[n],
then,
res[i] = forward[i]*backward[i]
"""
import unittest
unittest.main()
| [
2,
19182,
198,
198,
37811,
198,
41452,
64,
25,
198,
1616,
2651,
58,
72,
60,
796,
997,
82,
58,
15,
60,
9,
77,
5700,
58,
16,
60,
9,
986,
9,
77,
5700,
58,
72,
12,
16,
60,
837,
1891,
904,
58,
72,
60,
796,
19528,
58,
72,
60,
... | 1.827586 | 116 |