hexsha
string
size
int64
ext
string
lang
string
max_stars_repo_path
string
max_stars_repo_name
string
max_stars_repo_head_hexsha
string
max_stars_repo_licenses
list
max_stars_count
int64
max_stars_repo_stars_event_min_datetime
string
max_stars_repo_stars_event_max_datetime
string
max_issues_repo_path
string
max_issues_repo_name
string
max_issues_repo_head_hexsha
string
max_issues_repo_licenses
list
max_issues_count
int64
max_issues_repo_issues_event_min_datetime
string
max_issues_repo_issues_event_max_datetime
string
max_forks_repo_path
string
max_forks_repo_name
string
max_forks_repo_head_hexsha
string
max_forks_repo_licenses
list
max_forks_count
int64
max_forks_repo_forks_event_min_datetime
string
max_forks_repo_forks_event_max_datetime
string
content
string
avg_line_length
float64
max_line_length
int64
alphanum_fraction
float64
qsc_code_num_words_quality_signal
int64
qsc_code_num_chars_quality_signal
float64
qsc_code_mean_word_length_quality_signal
float64
qsc_code_frac_words_unique_quality_signal
float64
qsc_code_frac_chars_top_2grams_quality_signal
float64
qsc_code_frac_chars_top_3grams_quality_signal
float64
qsc_code_frac_chars_top_4grams_quality_signal
float64
qsc_code_frac_chars_dupe_5grams_quality_signal
float64
qsc_code_frac_chars_dupe_6grams_quality_signal
float64
qsc_code_frac_chars_dupe_7grams_quality_signal
float64
qsc_code_frac_chars_dupe_8grams_quality_signal
float64
qsc_code_frac_chars_dupe_9grams_quality_signal
float64
qsc_code_frac_chars_dupe_10grams_quality_signal
float64
qsc_code_frac_chars_replacement_symbols_quality_signal
float64
qsc_code_frac_chars_digital_quality_signal
float64
qsc_code_frac_chars_whitespace_quality_signal
float64
qsc_code_size_file_byte_quality_signal
float64
qsc_code_num_lines_quality_signal
float64
qsc_code_num_chars_line_max_quality_signal
float64
qsc_code_num_chars_line_mean_quality_signal
float64
qsc_code_frac_chars_alphabet_quality_signal
float64
qsc_code_frac_chars_comments_quality_signal
float64
qsc_code_cate_xml_start_quality_signal
float64
qsc_code_frac_lines_dupe_lines_quality_signal
float64
qsc_code_cate_autogen_quality_signal
float64
qsc_code_frac_lines_long_string_quality_signal
float64
qsc_code_frac_chars_string_length_quality_signal
float64
qsc_code_frac_chars_long_word_length_quality_signal
float64
qsc_code_frac_lines_string_concat_quality_signal
float64
qsc_code_cate_encoded_data_quality_signal
float64
qsc_code_frac_chars_hex_words_quality_signal
float64
qsc_code_frac_lines_prompt_comments_quality_signal
float64
qsc_code_frac_lines_assert_quality_signal
float64
qsc_codepython_cate_ast_quality_signal
float64
qsc_codepython_frac_lines_func_ratio_quality_signal
float64
qsc_codepython_cate_var_zero_quality_signal
bool
qsc_codepython_frac_lines_pass_quality_signal
float64
qsc_codepython_frac_lines_import_quality_signal
float64
qsc_codepython_frac_lines_simplefunc_quality_signal
float64
qsc_codepython_score_lines_no_logic_quality_signal
float64
qsc_codepython_frac_lines_print_quality_signal
float64
qsc_code_num_words
int64
qsc_code_num_chars
int64
qsc_code_mean_word_length
int64
qsc_code_frac_words_unique
null
qsc_code_frac_chars_top_2grams
int64
qsc_code_frac_chars_top_3grams
int64
qsc_code_frac_chars_top_4grams
int64
qsc_code_frac_chars_dupe_5grams
int64
qsc_code_frac_chars_dupe_6grams
int64
qsc_code_frac_chars_dupe_7grams
int64
qsc_code_frac_chars_dupe_8grams
int64
qsc_code_frac_chars_dupe_9grams
int64
qsc_code_frac_chars_dupe_10grams
int64
qsc_code_frac_chars_replacement_symbols
int64
qsc_code_frac_chars_digital
int64
qsc_code_frac_chars_whitespace
int64
qsc_code_size_file_byte
int64
qsc_code_num_lines
int64
qsc_code_num_chars_line_max
int64
qsc_code_num_chars_line_mean
int64
qsc_code_frac_chars_alphabet
int64
qsc_code_frac_chars_comments
int64
qsc_code_cate_xml_start
int64
qsc_code_frac_lines_dupe_lines
int64
qsc_code_cate_autogen
int64
qsc_code_frac_lines_long_string
int64
qsc_code_frac_chars_string_length
int64
qsc_code_frac_chars_long_word_length
int64
qsc_code_frac_lines_string_concat
null
qsc_code_cate_encoded_data
int64
qsc_code_frac_chars_hex_words
int64
qsc_code_frac_lines_prompt_comments
int64
qsc_code_frac_lines_assert
int64
qsc_codepython_cate_ast
int64
qsc_codepython_frac_lines_func_ratio
int64
qsc_codepython_cate_var_zero
int64
qsc_codepython_frac_lines_pass
int64
qsc_codepython_frac_lines_import
int64
qsc_codepython_frac_lines_simplefunc
int64
qsc_codepython_score_lines_no_logic
int64
qsc_codepython_frac_lines_print
int64
effective
string
hits
int64
b9ad055e162f0001e288ab22dec6a5a4746fd51d
2,786
py
Python
Neuro-Cognitive Models/Runs/Nonhier_run/res_nonhier.py
AGhaderi/spatial_attenNCM
1f7edf17f55d804d2ae3360d23623c9ab5035518
[ "MIT" ]
null
null
null
Neuro-Cognitive Models/Runs/Nonhier_run/res_nonhier.py
AGhaderi/spatial_attenNCM
1f7edf17f55d804d2ae3360d23623c9ab5035518
[ "MIT" ]
null
null
null
Neuro-Cognitive Models/Runs/Nonhier_run/res_nonhier.py
AGhaderi/spatial_attenNCM
1f7edf17f55d804d2ae3360d23623c9ab5035518
[ "MIT" ]
null
null
null
#!/home/a.ghaderi/.conda/envs/envjm/bin/python # Model 2 import pystan import pandas as pd import numpy as np import sys sys.path.append('../../') import utils parts = 1 data = utils.get_data() #loading dateset data = data[data['participant']==parts] mis = np.where((data['n200lat']<.101)|(data['n200lat']>....
39.8
116
0.648959
390
2,786
4.541026
0.341026
0.045172
0.059289
0.028797
0.188594
0.094862
0.040655
0.040655
0.040655
0
0
0.041892
0.203159
2,786
69
117
40.376812
0.755856
0.262742
0
0
0
0
0.121362
0.013814
0
0
0
0
0
1
0
false
0
0.09434
0
0.09434
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9adc3a3c0f82e03cf53dd13486c80b1bb9dbf85
6,691
py
Python
rq_dashboard/dashboard.py
refgenomics/rq-dashboard
cdfadd2b9aa9a66b0594fd5573e3c45fa8643f05
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
rq_dashboard/dashboard.py
refgenomics/rq-dashboard
cdfadd2b9aa9a66b0594fd5573e3c45fa8643f05
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
rq_dashboard/dashboard.py
refgenomics/rq-dashboard
cdfadd2b9aa9a66b0594fd5573e3c45fa8643f05
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
from redis import Redis from redis import from_url from rq import push_connection, pop_connection from rq.job import Job from functools import wraps import times from flask import Blueprint from flask import current_app, url_for, abort from flask import render_template from rq import Queue, Worker from rq import cancel...
29.606195
115
0.67658
929
6,691
4.624327
0.19591
0.048184
0.029795
0.030959
0.196229
0.136639
0.079376
0.065875
0.036546
0.027467
0
0.005448
0.204454
6,691
225
116
29.737778
0.801616
0.028396
0
0.139535
0
0
0.074371
0.020059
0
0
0
0
0
1
0.127907
false
0.005814
0.087209
0.023256
0.325581
0.011628
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9b691941c62b002880bb1f21ca60b0e932e41c1
3,574
py
Python
peaksampl.py
Gattocrucco/sipmfilter
74215d6c53b998808fc6c677b46030234d996bdf
[ "CC-BY-4.0", "MIT" ]
null
null
null
peaksampl.py
Gattocrucco/sipmfilter
74215d6c53b998808fc6c677b46030234d996bdf
[ "CC-BY-4.0", "MIT" ]
null
null
null
peaksampl.py
Gattocrucco/sipmfilter
74215d6c53b998808fc6c677b46030234d996bdf
[ "CC-BY-4.0", "MIT" ]
null
null
null
import numpy as np def _adddims(a, b): n = max(a.ndim, b.ndim) a = np.expand_dims(a, tuple(range(n - a.ndim))) b = np.expand_dims(b, tuple(range(n - b.ndim))) return a, b def _yz(y, z, t, yout): """ Shared implementation of peaksampl and sumpeaks. """ y = np.asarray(y) z = np.asarr...
28.822581
78
0.546726
560
3,574
3.4375
0.255357
0.01039
0.028052
0.010909
0.336104
0.275325
0.246234
0.214026
0.188052
0.188052
0
0.02549
0.286514
3,574
123
79
29.056911
0.729412
0.339675
0
0
0
0
0.01857
0
0
0
0
0
0.016949
1
0.067797
false
0
0.050847
0
0.186441
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9b9340675c6ceead7ff166bf8fe4d65fa580b58
4,597
py
Python
backend/Washlist/tests.py
henrikhorluck/tdt4140-washlists
a75c3bc38a3f915eb48cf3e9ecba848f46a2bcaa
[ "MIT" ]
null
null
null
backend/Washlist/tests.py
henrikhorluck/tdt4140-washlists
a75c3bc38a3f915eb48cf3e9ecba848f46a2bcaa
[ "MIT" ]
2
2020-05-02T18:17:44.000Z
2020-05-02T18:18:02.000Z
backend/Washlist/tests.py
henrikhorluck/tdt4140-washlists
a75c3bc38a3f915eb48cf3e9ecba848f46a2bcaa
[ "MIT" ]
null
null
null
from django.test import TestCase from django.urls import reverse from rest_framework import status from Dormroom.models import Dormroom from SIFUser.mixins import AuthTestMixin from StudentVillage.models import StudentVillage from Washlist.jobs import reset_washlists from Washlist.models.Templates import TemplateList...
35.091603
92
0.67022
493
4,597
6.137931
0.227181
0.051553
0.068407
0.051223
0.575017
0.562789
0.542631
0.542631
0.496034
0.421679
0
0.00766
0.233196
4,597
130
93
35.361538
0.85078
0.052861
0
0.452632
0
0
0.054168
0.025916
0
0
0
0
0.126316
1
0.105263
false
0
0.105263
0
0.252632
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ba39e57d52ad0baaeb81fbe95a03b7bb17d4ad
3,792
py
Python
torchvision/prototype/models/mobilenetv3.py
piyush01123/vision
c6722307e6860057b4855483d237fe00a213dcf6
[ "BSD-3-Clause" ]
null
null
null
torchvision/prototype/models/mobilenetv3.py
piyush01123/vision
c6722307e6860057b4855483d237fe00a213dcf6
[ "BSD-3-Clause" ]
null
null
null
torchvision/prototype/models/mobilenetv3.py
piyush01123/vision
c6722307e6860057b4855483d237fe00a213dcf6
[ "BSD-3-Clause" ]
null
null
null
from functools import partial from typing import Any, Optional, List from torchvision.prototype.transforms import ImageNetEval from torchvision.transforms.functional import InterpolationMode from ...models.mobilenetv3 import MobileNetV3, _mobilenet_v3_conf, InvertedResidualConfig from ._api import WeightsEnum, Weight...
34.472727
119
0.704114
426
3,792
5.953052
0.288732
0.108438
0.063091
0.054416
0.549685
0.494874
0.468849
0.413249
0.413249
0.413249
0
0.048403
0.182753
3,792
109
120
34.788991
0.769926
0
0
0.238636
0
0.034091
0.214399
0.013713
0
0
0
0
0
1
0.034091
false
0
0.090909
0
0.238636
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9bb907819b5835937644fde4b8d08e5dd987580
1,036
py
Python
crawler/tests.py
mental689/paddict
493268b62531c698687d42416edf61c602250133
[ "MIT" ]
1
2019-06-22T10:28:21.000Z
2019-06-22T10:28:21.000Z
crawler/tests.py
mental689/paddict
493268b62531c698687d42416edf61c602250133
[ "MIT" ]
4
2020-09-05T01:48:18.000Z
2022-03-02T04:29:25.000Z
crawler/tests.py
mental689/paddict
493268b62531c698687d42416edf61c602250133
[ "MIT" ]
null
null
null
from django.test import TestCase # Create your tests here. from crawler.download import * from crawler.models import * class AnimalDownloadTestCase(TestCase): def setUp(self): self.stopWords = ["CVPR 2019", "Computer Vision Foundation."] self.url = "/Users/tuannguyenanh/Desktop/cvpr2019.html"#"htt...
32.375
106
0.608108
126
1,036
4.952381
0.555556
0.057692
0.064103
0.073718
0
0
0
0
0
0
0
0.03073
0.246139
1,036
31
107
33.419355
0.768246
0.100386
0
0.086957
0
0
0.168649
0.045405
0
0
0
0
0
1
0.086957
false
0
0.130435
0
0.26087
0.086957
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9bfcc9ca3f71d3591d1b453eea9313adf491d9f
452
py
Python
test_scripts/xml_example.py
petervdb/testrep1
76b6eb3de2deb9596c055f252191e28587d5520c
[ "MIT" ]
1
2015-11-17T21:35:44.000Z
2015-11-17T21:35:44.000Z
test_scripts/xml_example.py
petervdb/testrep1
76b6eb3de2deb9596c055f252191e28587d5520c
[ "MIT" ]
null
null
null
test_scripts/xml_example.py
petervdb/testrep1
76b6eb3de2deb9596c055f252191e28587d5520c
[ "MIT" ]
null
null
null
#!/usr/bin/python3 from urllib.request import urlopen from xml.etree.ElementTree import parse # Download the RSS feed and parse it u = urlopen('http://planet.python.org/rss20.xml') doc = parse(u) # Extract and output tags of interest for item in doc.iterfind('channel/item'): title = item.findtext('title') date = i...
20.545455
49
0.725664
67
452
4.895522
0.641791
0.109756
0
0
0
0
0
0
0
0
0
0.007673
0.134956
452
21
50
21.52381
0.831202
0.19469
0
0
0
0
0.219444
0
0
0
0
0
0
1
0
false
0
0.153846
0
0.153846
0.384615
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9c06414f6de5d6df932f87abe0ac2addfe2d410
1,489
py
Python
contacts/urls.py
anthowen/duplify
846d01c1b21230937fdf0281b0cf8c0b08a8c24e
[ "MIT" ]
1
2019-04-21T18:57:57.000Z
2019-04-21T18:57:57.000Z
contacts/urls.py
anthowen/duplify
846d01c1b21230937fdf0281b0cf8c0b08a8c24e
[ "MIT" ]
null
null
null
contacts/urls.py
anthowen/duplify
846d01c1b21230937fdf0281b0cf8c0b08a8c24e
[ "MIT" ]
null
null
null
"""dedupper_app URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.0/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-...
38.179487
85
0.672263
209
1,489
4.746411
0.368421
0.060484
0.015121
0.024194
0.117944
0.117944
0.075605
0
0
0
0
0.006354
0.154466
1,489
38
86
39.184211
0.781573
0.699127
0
0
0
0
0.172811
0
0
0
0
0
0
1
0
false
0
0.25
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9c1d738b7414d020a32d72c8b5b4b39a4b6d1d4
2,667
py
Python
CPB100/lab2b/scheduled/ingestapp.py
pranaynanda/training-data-analyst
f10ab778589129239fd5b277cfdefb41638eded5
[ "Apache-2.0" ]
null
null
null
CPB100/lab2b/scheduled/ingestapp.py
pranaynanda/training-data-analyst
f10ab778589129239fd5b277cfdefb41638eded5
[ "Apache-2.0" ]
null
null
null
CPB100/lab2b/scheduled/ingestapp.py
pranaynanda/training-data-analyst
f10ab778589129239fd5b277cfdefb41638eded5
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python # Copyright 2016 Google 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 or ...
32.13253
214
0.683915
366
2,667
4.904372
0.486339
0.033426
0.030084
0.017827
0
0
0
0
0
0
0
0.011199
0.196475
2,667
82
215
32.52439
0.826412
0.285339
0
0.047619
0
0.047619
0.384697
0.014346
0
0
0
0
0
1
0.071429
false
0
0.119048
0.02381
0.261905
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9c731695680778a55c685fcfc15ab5e3eccf437
5,438
py
Python
dramkit/_tmp/VMD.py
Genlovy-Hoo/dramkit
fa3d2f35ebe9effea88a19e49d876b43d3c5c4c7
[ "MIT" ]
null
null
null
dramkit/_tmp/VMD.py
Genlovy-Hoo/dramkit
fa3d2f35ebe9effea88a19e49d876b43d3c5c4c7
[ "MIT" ]
null
null
null
dramkit/_tmp/VMD.py
Genlovy-Hoo/dramkit
fa3d2f35ebe9effea88a19e49d876b43d3c5c4c7
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import numpy as np def vmd( signal, alpha, tau, K, DC, init, tol): ''' 用VMD分解算法时只要把信号输入进行分解就行了,只是对信号进行分解,和采样频率没有关系, VMD的输入参数也没有采样频率。 VMD分解出的各分量在输出量 u 中,这个和信号的长度、信号的采样频率没有关系。 迭代时各分量的中心频率在输出量omega,可以用2*pi/fs*omega求出中心频率, 但迭代时的频率是变化的。 Input and Parameters: signal ...
37.503448
141
0.580912
878
5,438
3.494305
0.252847
0.035202
0.044329
0.026402
0.203716
0.133963
0.102999
0.084746
0.084746
0.073664
0
0.029659
0.255976
5,438
144
142
37.763889
0.728621
0.400331
0
0.086957
0
0
0
0
0
0
0
0
0
1
0.014493
false
0
0.014493
0
0.043478
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9c81413c2bd63d72d0731352d31911ef52240f6
480
py
Python
forum/main.py
asmaasalih/my_project
89183d7a2578fa302e94ea29570ab527e9ca47b5
[ "MIT" ]
1
2018-03-21T07:51:36.000Z
2018-03-21T07:51:36.000Z
forum/main.py
asmaasalih/my_project
89183d7a2578fa302e94ea29570ab527e9ca47b5
[ "MIT" ]
null
null
null
forum/main.py
asmaasalih/my_project
89183d7a2578fa302e94ea29570ab527e9ca47b5
[ "MIT" ]
null
null
null
import models import stores member1 =models.Member("ahmed",33) member2 =models.Member("mohamed",30) post1=models.Post("Post1", "Content1") post2= models.Post("Post2", "Content2") post3= models.Post("Post3", "Content3") #member store member_store=stores.MemberStore() member_store.add(member1) member_store.add(member...
20.869565
39
0.772917
69
480
5.217391
0.347826
0.152778
0.1
0
0
0
0
0
0
0
0
0.044843
0.070833
480
22
40
21.818182
0.762332
0.025
0
0
0
0
0.109208
0
0
0
0
0
0
1
0
false
0
0.125
0
0.125
0.125
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9c964b752a9622a17123202e7aae50d1718a48a
1,345
py
Python
question3.py
nosisky/algo-solution
a9276f73ba63b1a0965c194885aea6cadfab0e0b
[ "MIT" ]
1
2019-08-14T12:32:49.000Z
2019-08-14T12:32:49.000Z
question3.py
nosisky/algo-solution
a9276f73ba63b1a0965c194885aea6cadfab0e0b
[ "MIT" ]
null
null
null
question3.py
nosisky/algo-solution
a9276f73ba63b1a0965c194885aea6cadfab0e0b
[ "MIT" ]
null
null
null
# A string S consisting of N characters is considered to be properly nested if any of the following conditions is true: # S is empty; # S has the form "(U)" or "[U]" or "{U}" where U is a properly nested string; S has the form "VW" where V and W are properly nested strings. # For example, the string "{[()()]}" is prope...
42.03125
140
0.66171
203
1,345
4.384236
0.433498
0.078652
0.017978
0.040449
0.134831
0.134831
0.069663
0
0
0
0
0.010148
0.194052
1,345
31
141
43.387097
0.810886
0.692193
0
0.142857
0
0
0.095
0
0
0
0
0
0
1
0.071429
false
0
0
0
0.357143
0.071429
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ca4ff833bf2ee267f7f1b8ecf69069cd8c4b31
1,996
py
Python
Teil_27_Game_of_Life_3d.py
chrMenzel/A-beautiful-code-in-Python
92ee43c1fb03c299384d4de8bebb590c5ba1b623
[ "MIT" ]
50
2018-12-23T15:46:16.000Z
2022-03-28T15:49:59.000Z
Teil_27_Game_of_Life_3d.py
chrMenzel/A-beautiful-code-in-Python
92ee43c1fb03c299384d4de8bebb590c5ba1b623
[ "MIT" ]
9
2018-12-03T10:31:29.000Z
2022-01-20T14:41:33.000Z
Teil_27_Game_of_Life_3d.py
chrMenzel/A-beautiful-code-in-Python
92ee43c1fb03c299384d4de8bebb590c5ba1b623
[ "MIT" ]
69
2019-02-02T11:59:09.000Z
2022-03-28T15:54:28.000Z
import bpy import random as rnd from collections import Counter import itertools as iter feld_von, feld_bis = -4, 4 spielfeld_von, spielfeld_bis = feld_von-6, feld_bis+6 anz = int((feld_bis-feld_von)**3*.3) spielfeld = {(rnd.randint(feld_von, feld_bis), rnd.randint( feld_von, feld_bis), rnd.randint(feld_von, fe...
28.927536
102
0.67986
341
1,996
3.859238
0.302053
0.031915
0.049392
0.042553
0.234043
0.197568
0.179331
0.179331
0.12386
0.103343
0
0.043372
0.17986
1,996
68
103
29.352941
0.760538
0
0
0.037037
0
0
0.036573
0
0
0
0
0
0
1
0.055556
false
0
0.074074
0
0.148148
0.018519
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ca98991068e30844d7bcc8e336f70de5eef5a9
1,824
py
Python
power_perceiver/xr_batch_processor/reduce_num_pv_systems.py
openclimatefix/power_perceiver
bafcdfaf6abf42fbab09da641479f74709ddd395
[ "MIT" ]
null
null
null
power_perceiver/xr_batch_processor/reduce_num_pv_systems.py
openclimatefix/power_perceiver
bafcdfaf6abf42fbab09da641479f74709ddd395
[ "MIT" ]
33
2022-02-16T07:51:41.000Z
2022-03-31T11:24:11.000Z
power_perceiver/xr_batch_processor/reduce_num_pv_systems.py
openclimatefix/power_perceiver
bafcdfaf6abf42fbab09da641479f74709ddd395
[ "MIT" ]
null
null
null
from dataclasses import dataclass import numpy as np import xarray as xr from power_perceiver.load_prepared_batches.data_sources import PV from power_perceiver.load_prepared_batches.data_sources.prepared_data_source import XarrayBatch @dataclass class ReduceNumPVSystems: """Reduce the number of PV systems per e...
39.652174
97
0.721491
247
1,824
5.044534
0.421053
0.072231
0.05618
0.08427
0.170947
0.077047
0.077047
0.077047
0
0
0
0.002096
0.215461
1,824
45
98
40.533333
0.868623
0.272478
0
0
0
0
0.012327
0
0
0
0
0
0
1
0.076923
false
0
0.192308
0
0.384615
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9cc65aafe29eb9820f902e036880e65947e1e2d
857
py
Python
HelloWorld_python/log/demo_log_3.py
wang153723482/HelloWorld_my
b8642ad9742f95cfebafc61f25b00e917485e50c
[ "Apache-2.0" ]
null
null
null
HelloWorld_python/log/demo_log_3.py
wang153723482/HelloWorld_my
b8642ad9742f95cfebafc61f25b00e917485e50c
[ "Apache-2.0" ]
null
null
null
HelloWorld_python/log/demo_log_3.py
wang153723482/HelloWorld_my
b8642ad9742f95cfebafc61f25b00e917485e50c
[ "Apache-2.0" ]
null
null
null
#encoding=utf8 # 按天生成文件 import logging import time from logging.handlers import TimedRotatingFileHandler #---------------------------------------------------------------------- if __name__ == "__main__": logFilePath = "timed_test.log" logger = logging.getLogger("YouLoggerName") logger.setLevel(logging....
29.551724
89
0.536756
77
857
5.857143
0.597403
0.066519
0.084257
0
0
0
0
0
0
0
0
0.009756
0.28238
857
29
90
29.551724
0.723577
0.124854
0
0
0
0
0.159732
0
0
0
0
0
0
1
0
false
0
0.166667
0
0.166667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9cda5cbb2749647d6a78abf80d9eb5c24205425
341
py
Python
tests/test_gen_epub.py
ffreemt/tmx2epub
55a59cb2a9b7f42031a65f64c29e5c43fdb487ea
[ "MIT" ]
null
null
null
tests/test_gen_epub.py
ffreemt/tmx2epub
55a59cb2a9b7f42031a65f64c29e5c43fdb487ea
[ "MIT" ]
null
null
null
tests/test_gen_epub.py
ffreemt/tmx2epub
55a59cb2a9b7f42031a65f64c29e5c43fdb487ea
[ "MIT" ]
null
null
null
""" test gen_epub. """ from tmx2epub.gen_epub import gen_epub def test_gen_epub2(): """ test_gen_epub2. """ from pathlib import Path infile = r"tests\2.tmx" stem = Path(infile).absolute().stem outfile = f"{Path(infile).absolute().parent / stem}.epub" assert gen_epub(infile, debug=True) == out...
22.733333
61
0.653959
48
341
4.479167
0.5
0.130233
0.111628
0
0
0
0
0
0
0
0
0.018315
0.199413
341
14
62
24.357143
0.769231
0.123167
0
0
0
0
0.192308
0.108392
0
0
0
0
0.142857
1
0.142857
false
0
0.285714
0
0.428571
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9cde2fbd07898c518510cadb194827f6566c927
716
py
Python
pub_sub/python/http/checkout/app.py
amulyavarote/quickstarts
c21a8f58d515b28eaa8a3680388fa06995c2331b
[ "Apache-2.0" ]
null
null
null
pub_sub/python/http/checkout/app.py
amulyavarote/quickstarts
c21a8f58d515b28eaa8a3680388fa06995c2331b
[ "Apache-2.0" ]
null
null
null
pub_sub/python/http/checkout/app.py
amulyavarote/quickstarts
c21a8f58d515b28eaa8a3680388fa06995c2331b
[ "Apache-2.0" ]
null
null
null
import json import time import random import logging import requests import os logging.basicConfig(level=logging.INFO) base_url = os.getenv('BASE_URL', 'http://localhost') + ':' + os.getenv( 'DAPR_HTTP_PORT', '3500') PUBSUB_NAME = 'order_pub_sub' TOPIC = 'orders' logging.info('Publishing to baseUR...
25.571429
72
0.642458
100
716
4.49
0.5
0.062361
0.035635
0.062361
0.10245
0.10245
0
0
0
0
0
0.017825
0.21648
716
27
73
26.518519
0.782531
0.078212
0
0
0
0
0.241641
0.031915
0
0
0
0
0
1
0
false
0
0.285714
0
0.285714
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ce404499c062b33e8623b446d27dfebe6f033f
52,312
py
Python
jj.py
smailedge/pro
f86347d4368bc97aa860b37caa9ba10e84a93738
[ "Unlicense" ]
1
2019-08-14T04:17:06.000Z
2019-08-14T04:17:06.000Z
jj.py
smailedge/pro
f86347d4368bc97aa860b37caa9ba10e84a93738
[ "Unlicense" ]
null
null
null
jj.py
smailedge/pro
f86347d4368bc97aa860b37caa9ba10e84a93738
[ "Unlicense" ]
7
2018-10-27T11:58:45.000Z
2021-02-11T19:45:30.000Z
# -*- coding: utf-8 -*- from linepy import * from datetime import datetime from time import sleep from humanfriendly import format_timespan, format_size, format_number, format_length import time, random, sys, json, codecs, threading, glob, re, string, os, requests, subprocess, six, ast, pytz, urllib, urllib.parse #===...
51.742829
168
0.404267
4,504
52,312
4.70071
0.132549
0.067542
0.035613
0.039108
0.508596
0.436992
0.400057
0.371717
0.340591
0.330389
0
0.011643
0.443436
52,312
1,010
169
51.794059
0.710287
0.037104
0
0.448598
0
0.001038
0.133908
0.006538
0
0
0
0
0
1
0.006231
false
0.012461
0.005192
0
0.017653
0.014538
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9cf5fa54caecef97e6454178f438ce16bc99d7b
241
py
Python
fetch_data.py
bitfag/bt-macd-binance
eeffe52f8e561ff521629839078ff886e7bf700e
[ "MIT" ]
null
null
null
fetch_data.py
bitfag/bt-macd-binance
eeffe52f8e561ff521629839078ff886e7bf700e
[ "MIT" ]
null
null
null
fetch_data.py
bitfag/bt-macd-binance
eeffe52f8e561ff521629839078ff886e7bf700e
[ "MIT" ]
null
null
null
#!/usr/bin/env python from btmacd.binance_fetcher import BinanceFetcher def main(): fetcher = BinanceFetcher("BTCUSDT", filename="binance_ohlc.csv", start_date="01.01.2018") fetcher.fetch() if __name__ == "__main__": main()
18.538462
93
0.705394
30
241
5.3
0.766667
0
0
0
0
0
0
0
0
0
0
0.039024
0.149378
241
12
94
20.083333
0.736585
0.082988
0
0
0
0
0.186364
0
0
0
0
0
0
1
0.166667
false
0
0.166667
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d0d7e9fc82e29bf1385d169d21f03d43d467e2
25,508
py
Python
tensorflow_probability/python/mcmc/diagnostic.py
Frightera/probability
deac4562cbc1056e6abebc7450218d38444fe65d
[ "Apache-2.0" ]
1
2022-03-06T15:37:18.000Z
2022-03-06T15:37:18.000Z
tensorflow_probability/python/mcmc/diagnostic.py
Frightera/probability
deac4562cbc1056e6abebc7450218d38444fe65d
[ "Apache-2.0" ]
null
null
null
tensorflow_probability/python/mcmc/diagnostic.py
Frightera/probability
deac4562cbc1056e6abebc7450218d38444fe65d
[ "Apache-2.0" ]
null
null
null
# Copyright 2018 The TensorFlow Probability Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law o...
43.015177
85
0.663361
3,707
25,508
4.408417
0.180469
0.021295
0.01542
0.021417
0.282646
0.229225
0.187492
0.128809
0.120609
0.095766
0
0.022847
0.238121
25,508
592
86
43.087838
0.818051
0.604869
0
0.123153
0
0
0.055835
0.019799
0
0
0
0.001689
0.044335
1
0.044335
false
0
0.059113
0.009852
0.157635
0.004926
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d2c04ffcb32d5c9ad6c0f626a368e22db97763
4,504
py
Python
tests/data/s3_scrape_config.py
kids-first/kf-api-study-creator
93a79b108b6474f9b4135ace06c89ddcf63dd257
[ "Apache-2.0" ]
3
2019-05-04T02:07:28.000Z
2020-10-16T17:47:44.000Z
tests/data/s3_scrape_config.py
kids-first/kf-api-study-creator
93a79b108b6474f9b4135ace06c89ddcf63dd257
[ "Apache-2.0" ]
604
2019-02-21T18:14:51.000Z
2022-02-10T08:13:54.000Z
tests/data/s3_scrape_config.py
kids-first/kf-api-study-creator
93a79b108b6474f9b4135ace06c89ddcf63dd257
[ "Apache-2.0" ]
null
null
null
""" This is an extract config intended for S3 object manifests produced by TBD. To use it, you must import it in another extract config and override at least the `source_data_url`. You may also append additional operations to the `operations` list as well. For example you could have the following in your extract conf...
27.463415
78
0.67984
672
4,504
4.321429
0.239583
0.162879
0.140496
0.065083
0.399793
0.225895
0.110537
0.070592
0.060606
0.027548
0
0.005843
0.202043
4,504
163
79
27.631902
0.80217
0.228686
0
0.128713
0
0
0.108148
0.020444
0
0
0
0
0
1
0.049505
false
0
0.049505
0
0.148515
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d3222fd93bbc8ba199ba7a401394dc7531a2ff
665
py
Python
hard-gists/5c973ec1b5ab2e387646/snippet.py
jjhenkel/dockerizeme
eaa4fe5366f6b9adf74399eab01c712cacaeb279
[ "Apache-2.0" ]
21
2019-07-08T08:26:45.000Z
2022-01-24T23:53:25.000Z
hard-gists/5c973ec1b5ab2e387646/snippet.py
jjhenkel/dockerizeme
eaa4fe5366f6b9adf74399eab01c712cacaeb279
[ "Apache-2.0" ]
5
2019-06-15T14:47:47.000Z
2022-02-26T05:02:56.000Z
hard-gists/5c973ec1b5ab2e387646/snippet.py
jjhenkel/dockerizeme
eaa4fe5366f6b9adf74399eab01c712cacaeb279
[ "Apache-2.0" ]
17
2019-05-16T03:50:34.000Z
2021-01-14T14:35:12.000Z
import bpy from bpy.app.handlers import persistent bl_info = { "name": "Playback Once", "author": "Adhi Hargo", "version": (1, 0, 0), "blender": (2, 67, 3), "location": "", "description": "Playback once.", "warning": "", "wiki_url": "", "tracker_url": "", "category": "Animation"...
22.931034
63
0.645113
75
665
5.48
0.613333
0.043796
0.10219
0.092457
0.136253
0.136253
0
0
0
0
0
0.013035
0.192481
665
28
64
23.75
0.752328
0
0
0
0
0
0.196992
0
0
0
0
0
0
1
0.130435
false
0
0.086957
0
0.217391
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d47acd47b8bd0babe955a7bbbde7c4d9080b36
688
py
Python
Py3Challenges/saves/challenges/c6_min.py
AlbertUnruh/Py3Challenges
52f03f157860f6464f0c1710bf051a8099c29ea2
[ "MIT" ]
2
2022-02-13T04:57:10.000Z
2022-02-13T10:40:14.000Z
Py3Challenges/saves/challenges/c6_min.py
AlbertUnruh/Py3Challenges
52f03f157860f6464f0c1710bf051a8099c29ea2
[ "MIT" ]
null
null
null
Py3Challenges/saves/challenges/c6_min.py
AlbertUnruh/Py3Challenges
52f03f157860f6464f0c1710bf051a8099c29ea2
[ "MIT" ]
null
null
null
""" To master this you should consider using the builtin-``min``-function. """ from ...challenge import Challenge from random import randint x = [] for _ in range(randint(2, 10)): x.append(randint(1, 100)) intro = f"You have to print the lowest value of {', '.join(str(_) for _ in x[:-1])} and {x[-1]}. (values: x...
22.193548
109
0.632267
95
688
4.463158
0.610526
0.113208
0
0
0
0
0
0
0
0
0
0.016729
0.218023
688
30
110
22.933333
0.771375
0.101744
0
0
0
0.05
0.165574
0
0
0
0
0
0
1
0.05
false
0
0.1
0
0.25
0.05
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d600352f466e38045c7614f4b0151d5eb8f878
4,625
py
Python
services/web/server/tests/unit/with_dbs/01/test_director_v2.py
mrnicegyu11/osparc-simcore
b6fa6c245dbfbc18cc74a387111a52de9b05d1f4
[ "MIT" ]
null
null
null
services/web/server/tests/unit/with_dbs/01/test_director_v2.py
mrnicegyu11/osparc-simcore
b6fa6c245dbfbc18cc74a387111a52de9b05d1f4
[ "MIT" ]
1
2021-11-29T13:38:09.000Z
2021-11-29T13:38:09.000Z
services/web/server/tests/unit/with_dbs/01/test_director_v2.py
mrnicegyu11/osparc-simcore
b6fa6c245dbfbc18cc74a387111a52de9b05d1f4
[ "MIT" ]
null
null
null
# pylint:disable=unused-variable # pylint:disable=unused-argument # pylint:disable=redefined-outer-name from typing import AsyncIterator import pytest from aioresponses import aioresponses from faker import Faker from hypothesis import HealthCheck, given, settings from hypothesis import strategies as st from models_...
30.833333
87
0.780973
626
4,625
5.428115
0.161342
0.049441
0.045909
0.071218
0.508534
0.457034
0.436433
0.389347
0.389347
0.375221
0
0.007818
0.142703
4,625
149
88
31.040268
0.84918
0.020973
0
0.256637
0
0
0.011715
0
0
0
0
0
0.141593
1
0.026549
false
0
0.115044
0.026549
0.168142
0.00885
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d6dd8bd3445675e1356c10ac0bb61cd00aba81
3,027
py
Python
generator.py
Geoalert/emergency-mapping
96668e4e5aa2b520e5727536f7a8f4c262ee3da6
[ "MIT" ]
3
2018-04-04T17:58:53.000Z
2021-10-14T08:50:13.000Z
generator.py
aeronetlab/map_augury
96668e4e5aa2b520e5727536f7a8f4c262ee3da6
[ "MIT" ]
null
null
null
generator.py
aeronetlab/map_augury
96668e4e5aa2b520e5727536f7a8f4c262ee3da6
[ "MIT" ]
1
2020-03-24T12:07:07.000Z
2020-03-24T12:07:07.000Z
import numpy as np def random_augmentation(img, mask): #you can add any augmentations you need return img, mask def batch_generator(image, mask, batch_size=1, crop_size=0, patch_size=256, bbox= None, augment...
40.905405
116
0.570202
417
3,027
3.980815
0.28777
0.06506
0.016867
0.028916
0.183133
0.128916
0.079518
0.079518
0.055422
0.055422
0
0.022602
0.342253
3,027
73
117
41.465753
0.81115
0.269574
0
0
0
0
0.045855
0
0
0
0
0
0
1
0.042553
false
0
0.021277
0.021277
0.085106
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d71e12c5fdd4a3220a64251c8e0e2c9a302fe4
13,351
py
Python
awx/api/metadata.py
Avinesh/awx
6310a2edd890d6062a9f6bcdeb2b46c4b876c2bf
[ "Apache-2.0" ]
1
2021-09-07T14:53:57.000Z
2021-09-07T14:53:57.000Z
awx/api/metadata.py
Avinesh/awx
6310a2edd890d6062a9f6bcdeb2b46c4b876c2bf
[ "Apache-2.0" ]
2
2020-02-04T05:01:38.000Z
2020-02-18T06:44:52.000Z
awx/api/metadata.py
Avinesh/awx
6310a2edd890d6062a9f6bcdeb2b46c4b876c2bf
[ "Apache-2.0" ]
1
2020-01-28T05:34:09.000Z
2020-01-28T05:34:09.000Z
# Copyright (c) 2016 Ansible, Inc. # All Rights Reserved. from collections import OrderedDict # Django from django.core.exceptions import PermissionDenied from django.db.models.fields import PositiveIntegerField, BooleanField from django.db.models.fields.related import ForeignKey from django.http import Http404 from ...
43.630719
131
0.601004
1,430
13,351
5.429371
0.202797
0.035935
0.028851
0.016486
0.159196
0.129057
0.101752
0.083462
0.083462
0.083462
0
0.001503
0.302374
13,351
305
132
43.77377
0.832081
0.115122
0
0.1875
0
0
0.134669
0.011293
0
0
0
0.003279
0
1
0.026786
false
0.013393
0.075893
0
0.142857
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d7834f2dd39b0c5b6da30b8ebfe19e7026adeb
1,985
py
Python
plugins/python/tasks.py
BBVA/deeptracy
40f4b6bba2bdd345e95e42d474c05fa90f15c3e9
[ "Apache-1.1" ]
85
2017-09-22T10:48:51.000Z
2021-06-11T18:33:28.000Z
plugins/python/tasks.py
BBVA/deeptracy
40f4b6bba2bdd345e95e42d474c05fa90f15c3e9
[ "Apache-1.1" ]
51
2017-10-17T10:16:16.000Z
2020-08-29T23:10:21.000Z
plugins/python/tasks.py
BBVA/deeptracy
40f4b6bba2bdd345e95e42d474c05fa90f15c3e9
[ "Apache-1.1" ]
14
2017-11-20T10:20:16.000Z
2021-02-02T21:35:07.000Z
import json from washer.worker.actions import AppendStdout, AppendStderr from washer.worker.actions import CreateNamedLog, AppendToLog from washer.worker.actions import SetProperty from washer.worker.commands import washertask def pipenv_graph2deps(rawgraph): graph = json.loads(rawgraph) def build_entry(dat...
28.357143
75
0.614106
212
1,985
5.679245
0.306604
0.033223
0.053156
0.057309
0.446013
0.373754
0.373754
0.373754
0.373754
0.373754
0
0.002086
0.275567
1,985
69
76
28.768116
0.835188
0
0
0.423077
0
0
0.125441
0
0
0
0
0
0
1
0.096154
false
0
0.134615
0
0.288462
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d84b2b4c7d4cbbbf84bcb2ee37459c480a1a5e
715
py
Python
senity/utils/getSiteProfile.py
pkokkinos/senity
c6e41678620bef558cc3600929a8320ff2a285cf
[ "MIT" ]
1
2017-10-26T12:30:04.000Z
2017-10-26T12:30:04.000Z
senity/utils/getSiteProfile.py
pkokkinos/senity
c6e41678620bef558cc3600929a8320ff2a285cf
[ "MIT" ]
null
null
null
senity/utils/getSiteProfile.py
pkokkinos/senity
c6e41678620bef558cc3600929a8320ff2a285cf
[ "MIT" ]
null
null
null
import json import os # get site profile def getSiteProfile(site_file): with open(site_file) as json_file: json_data = json.load(json_file) return json_data # get all site profile def getAllSiteProfiles(site_folder): allSiteProfiles = {} allSiteFiles = os.listdir(site_folder) for ...
23.833333
77
0.664336
79
715
5.873418
0.443038
0.064655
0.060345
0
0
0
0
0
0
0
0
0
0.234965
715
29
78
24.655172
0.848263
0.135664
0
0
0
0
0.091354
0
0
0
0
0
0
1
0.125
false
0
0.125
0
0.375
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d87f8b647f237794f75914da625ea130e200c3
5,959
py
Python
ppo_new/baseline.py
QingXinHu123/Lane_change_RL
06c70e6f58d3478669b56800028e320ca03f5222
[ "MIT" ]
1
2022-03-17T03:40:57.000Z
2022-03-17T03:40:57.000Z
ppo_new/baseline.py
QingXinHu123/Lane_change_RL
06c70e6f58d3478669b56800028e320ca03f5222
[ "MIT" ]
null
null
null
ppo_new/baseline.py
QingXinHu123/Lane_change_RL
06c70e6f58d3478669b56800028e320ca03f5222
[ "MIT" ]
null
null
null
import os, sys from env.LaneChangeEnv import LaneChangeEnv import random import numpy as np if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit("please declare environment variable 'SUMO_HOME'") import traci def ep...
36.558282
164
0.659171
964
5,959
3.770747
0.192946
0.071527
0.042916
0.030812
0.196699
0.150757
0.088033
0.08033
0.047868
0.047868
0
0.078652
0.208424
5,959
162
165
36.783951
0.691965
0.135593
0
0.030534
0
0
0.117911
0.008575
0
0
0
0
0
1
0.022901
false
0
0.038168
0
0.083969
0.083969
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9d8a3bc2867b57ba7db6ffd06a68bdf7372909c
1,261
py
Python
clean_data.py
toogy/pendigits-hmm
03382e1457941714439d40b67e53eaf117fe4d08
[ "MIT" ]
null
null
null
clean_data.py
toogy/pendigits-hmm
03382e1457941714439d40b67e53eaf117fe4d08
[ "MIT" ]
null
null
null
clean_data.py
toogy/pendigits-hmm
03382e1457941714439d40b67e53eaf117fe4d08
[ "MIT" ]
null
null
null
import numpy as np import pickle from collections import defaultdict from parsing import parser from analysis import training def main(): parse = parser.Parser(); train_digits = parse.parse_file('data/pendigits-train'); test_digits = parse.parse_file('data/pendigits-test') centroids = training.get_d...
24.25
72
0.704996
162
1,261
5.185185
0.314815
0.092857
0.085714
0.039286
0.286905
0.163095
0
0
0
0
0
0.009901
0.199048
1,261
51
73
24.72549
0.821782
0
0
0.0625
0
0
0.080888
0
0
0
0
0
0
1
0.03125
false
0
0.15625
0
0.1875
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9db09c1d1c26d802117168878ef76954cf77560
3,360
py
Python
matrixprofile/algorithms/snippets.py
KSaiRahul21/matrixprofile
d8250e30d90ed0453bb7c35bb34ab0c04ae7b334
[ "Apache-2.0" ]
null
null
null
matrixprofile/algorithms/snippets.py
KSaiRahul21/matrixprofile
d8250e30d90ed0453bb7c35bb34ab0c04ae7b334
[ "Apache-2.0" ]
null
null
null
matrixprofile/algorithms/snippets.py
KSaiRahul21/matrixprofile
d8250e30d90ed0453bb7c35bb34ab0c04ae7b334
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals range = getattr(__builtins__, 'xrange', range) # end of py2 compatability boilerplate import numpy as np from matrixprofil...
29.734513
84
0.633036
428
3,360
4.799065
0.32243
0.091042
0.031159
0.025316
0
0
0
0
0
0
0
0.004512
0.274405
3,360
112
85
30
0.837982
0.275595
0
0
0
0
0.078608
0
0
0
0
0
0
1
0.017857
false
0
0.125
0
0.160714
0.017857
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9db24edad8766b6e734d6a8a9c26aff6bb04235
2,360
py
Python
jina/logging/formatter.py
yk/jina
ab66e233e74b956390f266881ff5dc4e0110d3ff
[ "Apache-2.0" ]
1
2020-12-23T12:34:00.000Z
2020-12-23T12:34:00.000Z
jina/logging/formatter.py
yk/jina
ab66e233e74b956390f266881ff5dc4e0110d3ff
[ "Apache-2.0" ]
null
null
null
jina/logging/formatter.py
yk/jina
ab66e233e74b956390f266881ff5dc4e0110d3ff
[ "Apache-2.0" ]
null
null
null
import json import re from copy import copy from logging import Formatter from .profile import used_memory from ..helper import colored class ColorFormatter(Formatter): """Format the log into colored logs based on the log-level. """ MAPPING = { 'DEBUG': dict(color='white', on_color=None), # white ...
34.705882
114
0.601695
319
2,360
4.410658
0.363636
0.03909
0.031272
0.054016
0.297797
0.248756
0.170576
0.102345
0.102345
0.06823
0
0.008475
0.25
2,360
67
115
35.223881
0.786441
0.205085
0
0.222222
0
0
0.133297
0
0
0
0
0
0
1
0.088889
false
0
0.133333
0
0.466667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9dcf24da986778ebcd29602d923908626cfea3c
4,263
py
Python
mtl/util/pipeline.py
vandurme/TFMTL
5958187900bdf67089a237c523b6caa899f63ac1
[ "Apache-2.0" ]
10
2019-05-18T22:23:44.000Z
2022-01-25T15:24:45.000Z
mtl/util/pipeline.py
vandurme/TFMTL
5958187900bdf67089a237c523b6caa899f63ac1
[ "Apache-2.0" ]
1
2020-01-07T15:24:16.000Z
2020-01-15T00:39:01.000Z
mtl/util/pipeline.py
vandurme/TFMTL
5958187900bdf67089a237c523b6caa899f63ac1
[ "Apache-2.0" ]
1
2021-12-02T02:24:06.000Z
2021-12-02T02:24:06.000Z
# Copyright 2018 Johns Hopkins University. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by appli...
34.658537
80
0.649073
546
4,263
4.847985
0.357143
0.023801
0.039668
0.03589
0.088402
0.073291
0.073291
0.073291
0.073291
0.044579
0
0.014111
0.251935
4,263
122
81
34.942623
0.81593
0.254985
0
0.097222
0
0
0.00892
0
0
0
0
0
0.013889
1
0.111111
false
0
0.097222
0.041667
0.319444
0.013889
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9de795b7b1298f8cad5f30e914735224920a0f9
1,158
py
Python
core/views.py
moiyad/image
d4515ef3057794f38268a6887bfff157115f26f7
[ "MIT" ]
null
null
null
core/views.py
moiyad/image
d4515ef3057794f38268a6887bfff157115f26f7
[ "MIT" ]
null
null
null
core/views.py
moiyad/image
d4515ef3057794f38268a6887bfff157115f26f7
[ "MIT" ]
null
null
null
from django.core.files.storage import FileSystemStorage from django.shortcuts import render, redirect from core.forms import DocumentForm from core.models import Document from media import image_cv2 def home(request): documents = Document.objects.all() number = len(image_cv2.myList) return render(request...
30.473684
88
0.668394
137
1,158
5.532847
0.343066
0.063325
0.100264
0.121372
0.187335
0.187335
0.102902
0
0
0
0
0.002208
0.217617
1,158
37
89
31.297297
0.834437
0
0
0.066667
0
0
0.126943
0.06304
0
0
0
0
0
1
0.1
false
0
0.166667
0
0.433333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9dfea4e7beba7ec415b85a76c49ed3af214dec4
25,442
py
Python
ml4chem/atomistic/models/neuralnetwork.py
muammar/mlchem
365487c23ea3386657e178e56ab31adfe8d5d073
[ "BSD-3-Clause-LBNL" ]
77
2019-08-05T17:30:22.000Z
2022-03-28T14:31:35.000Z
ml4chem/atomistic/models/neuralnetwork.py
muammar/ml4chem
365487c23ea3386657e178e56ab31adfe8d5d073
[ "BSD-3-Clause-LBNL" ]
6
2019-07-31T18:59:38.000Z
2020-10-18T18:15:07.000Z
ml4chem/atomistic/models/neuralnetwork.py
muammar/mlchem
365487c23ea3386657e178e56ab31adfe8d5d073
[ "BSD-3-Clause-LBNL" ]
15
2020-02-28T10:11:21.000Z
2021-12-01T13:45:33.000Z
import dask import datetime import logging import time import torch import numpy as np import pandas as pd from collections import OrderedDict from ml4chem.metrics import compute_rmse from ml4chem.atomistic.models.base import DeepLearningModel, DeepLearningTrainer from ml4chem.atomistic.models.loss import AtomicMSELos...
33.742706
88
0.526924
2,573
25,442
5.094054
0.175282
0.025177
0.025788
0.00763
0.271229
0.247044
0.232319
0.202487
0.173877
0.155413
0
0.008501
0.375835
25,442
753
89
33.787517
0.816814
0.228166
0
0.201814
0
0.004535
0.071482
0.00118
0
0
0
0.001328
0
1
0.020408
false
0
0.031746
0
0.070295
0.006803
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e018d6290ebe7b0654b7e76a8df225914e3778
7,104
py
Python
hatsploit/core/db/db.py
EntySec/HatSploit
8e445804c252cc24e87888be2c2efc02750ce5ee
[ "MIT" ]
139
2021-02-17T15:52:30.000Z
2022-03-30T14:50:42.000Z
hatsploit/core/db/db.py
YurinDoctrine/HatSploit
b1550323e08336ec057cbafb77003c22a3bbee91
[ "MIT" ]
27
2021-03-24T17:14:30.000Z
2022-03-02T18:50:43.000Z
hatsploit/core/db/db.py
YurinDoctrine/HatSploit
b1550323e08336ec057cbafb77003c22a3bbee91
[ "MIT" ]
85
2021-02-17T15:39:03.000Z
2022-03-07T09:08:58.000Z
#!/usr/bin/env python3 # # MIT License # # Copyright (c) 2020-2022 EntySec # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to...
38.193548
86
0.639077
817
7,104
5.350061
0.190942
0.101579
0.131778
0.078243
0.642187
0.599176
0.553649
0.486388
0.461679
0.427362
0
0.001734
0.269285
7,104
185
87
38.4
0.840301
0.152872
0
0.518519
0
0
0.235569
0.105439
0
0
0
0
0
1
0.044444
false
0
0.037037
0
0.244444
0.133333
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e09def642ce98a753ac3053c44b1ba7d862f16
4,850
py
Python
shutTheBox/main.py
robi1467/shut-the-box
ed1a8f13bc74caa63361453e723768a9cbe1dac4
[ "MIT" ]
null
null
null
shutTheBox/main.py
robi1467/shut-the-box
ed1a8f13bc74caa63361453e723768a9cbe1dac4
[ "MIT" ]
null
null
null
shutTheBox/main.py
robi1467/shut-the-box
ed1a8f13bc74caa63361453e723768a9cbe1dac4
[ "MIT" ]
null
null
null
import random numbers_list = [1,2,3,4,5,6,7,8,9,10] game_won = False game_completed = False #Stats games_played = 0 games_won = 0 games_lost = 0 average_score = 0 total_score = 0 def welcome(): welcome_message = "Welcome to shut the box" print(welcome_message) i = 0 result = "" while i < len(number...
28.034682
127
0.549897
619
4,850
4.113086
0.177706
0.129615
0.042419
0.029458
0.261587
0.225452
0.216811
0.118617
0.118617
0.118617
0
0.023672
0.355464
4,850
172
128
28.197674
0.790787
0.001031
0
0.341935
0
0
0.117052
0
0
0
0
0
0
1
0.064516
false
0
0.006452
0
0.154839
0.090323
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e379a95e3f4e855adb56ee1112dc1aa95e6a78
9,351
py
Python
main.py
mithi/semantic-segmentation
85e9df04397745e0c6ab252e30991fa9b514ec1a
[ "MIT" ]
33
2017-08-24T16:38:15.000Z
2022-03-17T15:55:52.000Z
main.py
mithi/semantic-segmentation
85e9df04397745e0c6ab252e30991fa9b514ec1a
[ "MIT" ]
3
2018-10-12T11:17:22.000Z
2019-05-30T09:49:11.000Z
main.py
mithi/semantic-segmentation
85e9df04397745e0c6ab252e30991fa9b514ec1a
[ "MIT" ]
26
2017-09-17T09:09:52.000Z
2020-01-14T02:48:56.000Z
import tensorflow as tf import os.path import warnings from distutils.version import LooseVersion import glob import helper import project_tests as tests #-------------------------- # USER-SPECIFIED DATA #-------------------------- # Tune these parameters NUMBER_OF_CLASSES = 2 IMAGE_SHAPE = (160, 576) EPOCHS = 20 ...
37.8583
146
0.69276
1,265
9,351
4.904348
0.223715
0.027079
0.028369
0.018375
0.220986
0.157318
0.120406
0.106705
0.066731
0.042553
0
0.017317
0.197198
9,351
246
147
38.012195
0.809112
0.378141
0
0.055046
0
0
0.093315
0.010584
0
0
0
0
0.009174
1
0.073395
false
0
0.06422
0
0.183486
0.06422
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e38ca4d963e2aa4de106573e34682092b6337e
22,356
py
Python
tests/scanner/audit/log_sink_rules_engine_test.py
BrunoReboul/forseti-security
9d4a61b3e5a5d22a4330d15ddf61063fc9079071
[ "Apache-2.0" ]
null
null
null
tests/scanner/audit/log_sink_rules_engine_test.py
BrunoReboul/forseti-security
9d4a61b3e5a5d22a4330d15ddf61063fc9079071
[ "Apache-2.0" ]
null
null
null
tests/scanner/audit/log_sink_rules_engine_test.py
BrunoReboul/forseti-security
9d4a61b3e5a5d22a4330d15ddf61063fc9079071
[ "Apache-2.0" ]
null
null
null
# Copyright 2018 The Forseti Security Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ap...
40.79562
84
0.560834
2,214
22,356
5.358627
0.115176
0.026888
0.028321
0.023264
0.711986
0.662087
0.633513
0.584289
0.544842
0.498483
0
0.019762
0.334541
22,356
547
85
40.870201
0.777711
0.097916
0
0.579646
0
0
0.242757
0.142273
0
0
0
0
0.033186
1
0.030973
false
0
0.024336
0
0.059735
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e3fca3aec04c54b087304757154615d5a67e58
2,852
py
Python
backend/api/ulca-ums-service/user-management/utilities/orgUtils.py
agupta54/ulca
c1f570ac254ce2ac73f40c49716458f4f7cbaee2
[ "MIT" ]
3
2022-01-12T06:51:51.000Z
2022-02-23T18:54:33.000Z
backend/api/ulca-ums-service/user-management/utilities/orgUtils.py
agupta54/ulca
c1f570ac254ce2ac73f40c49716458f4f7cbaee2
[ "MIT" ]
6
2021-08-31T19:21:26.000Z
2022-01-03T05:53:42.000Z
backend/api/ulca-ums-service/user-management/utilities/orgUtils.py
agupta54/ulca
c1f570ac254ce2ac73f40c49716458f4f7cbaee2
[ "MIT" ]
8
2021-08-12T08:07:49.000Z
2022-01-25T04:40:51.000Z
import uuid from config import USR_ORG_MONGO_COLLECTION, USR_MONGO_COLLECTION import db from models.response import post_error import logging log = logging.getLogger('file') class OrgUtils: def __init__(self): pass #orgId generation @staticmethod def generate_org_id(): """UUID gener...
41.333333
149
0.619565
341
2,852
5.082111
0.337243
0.04674
0.069244
0.038084
0.355453
0.248125
0.248125
0.248125
0.248125
0.248125
0
0.003916
0.283661
2,852
69
150
41.333333
0.844347
0.135694
0
0.244444
0
0
0.271559
0
0
0
0
0
0
1
0.088889
false
0.022222
0.111111
0
0.4
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e478ed385905aa26b48748e1fbf896e8ced766
4,299
py
Python
setup.py
AntonBiryukovUofC/diffvg
e081098f52b82bfd0b7e91114d289d65ef969a60
[ "Apache-2.0" ]
null
null
null
setup.py
AntonBiryukovUofC/diffvg
e081098f52b82bfd0b7e91114d289d65ef969a60
[ "Apache-2.0" ]
null
null
null
setup.py
AntonBiryukovUofC/diffvg
e081098f52b82bfd0b7e91114d289d65ef969a60
[ "Apache-2.0" ]
null
null
null
# Adapted from https://github.com/pybind/cmake_example/blob/master/setup.py import os import re import sys import platform import subprocess import importlib from sysconfig import get_paths import importlib from setuptools import setup, Extension from setuptools.command.build_ext import build_ext from setuptools.comma...
38.044248
109
0.601303
508
4,299
4.879921
0.322835
0.039935
0.057685
0.017749
0.160145
0.124647
0.049213
0.028237
0.028237
0.028237
0
0.007939
0.267504
4,299
112
110
38.383929
0.779295
0.028844
0
0.075269
0
0
0.172339
0.048418
0.021505
0
0
0
0
1
0.032258
false
0
0.182796
0
0.236559
0.010753
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e64ab7c515862e0dec6a8272d8a276b9bd86b9
14,587
py
Python
robotpy_ext/common_drivers/navx/registerio.py
twinters007/robotpy-wpilib-utilities
d2e18c16fc97a469e0621521e0fbed0093610d6e
[ "MIT", "BSD-3-Clause" ]
2
2017-01-16T03:10:57.000Z
2017-01-16T03:11:00.000Z
robotpy_ext/common_drivers/navx/registerio.py
twinters007/robotpy-wpilib-utilities
d2e18c16fc97a469e0621521e0fbed0093610d6e
[ "MIT", "BSD-3-Clause" ]
null
null
null
robotpy_ext/common_drivers/navx/registerio.py
twinters007/robotpy-wpilib-utilities
d2e18c16fc97a469e0621521e0fbed0093610d6e
[ "MIT", "BSD-3-Clause" ]
null
null
null
# validated: 2017-02-19 DS c5e3a8a9b642 roborio/java/navx_frc/src/com/kauailabs/navx/frc/RegisterIO.java #---------------------------------------------------------------------------- # Copyright (c) Kauai Labs 2015. All Rights Reserved. # # Created in support of Team 2465 (Kauaibots). Go Purple Wave! # # Open Source S...
54.632959
159
0.676973
1,642
14,587
5.598051
0.168088
0.109661
0.130222
0.112272
0.590078
0.510335
0.413621
0.311684
0.113903
0.06832
0
0.014578
0.252279
14,587
266
160
54.838346
0.828184
0.085487
0
0.11399
0
0
0.019657
0
0
0
0.000302
0
0
1
0.062176
false
0.005181
0.015544
0.010363
0.19171
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e6a0bf2a4d3e860c6eb607624b101a086157b4
12,517
py
Python
RigolWFM/channel.py
wvdv2002/RigolWFM
849a1130c9194f052eaf5582dfa67e7a5708a3a3
[ "BSD-3-Clause" ]
null
null
null
RigolWFM/channel.py
wvdv2002/RigolWFM
849a1130c9194f052eaf5582dfa67e7a5708a3a3
[ "BSD-3-Clause" ]
null
null
null
RigolWFM/channel.py
wvdv2002/RigolWFM
849a1130c9194f052eaf5582dfa67e7a5708a3a3
[ "BSD-3-Clause" ]
null
null
null
#pylint: disable=invalid-name #pylint: disable=too-many-instance-attributes #pylint: disable=too-many-return-statements #pylint: disable=too-many-statements """ Class structure and methods for an oscilloscope channel. The idea is to collect all the relevant information from all the Rigol scope waveforms into a single ...
36.176301
96
0.589199
1,687
12,517
4.227623
0.140486
0.100252
0.037297
0.043186
0.509675
0.43396
0.406057
0.37521
0.360348
0.331183
0
0.046496
0.298953
12,517
345
97
36.281159
0.766268
0.149157
0
0.373913
0
0
0.053795
0
0
0
0
0
0
1
0.056522
false
0
0.008696
0
0.143478
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9e6a9be08cb7ae14c68608c944b95cbe6233b10
1,477
py
Python
configs/raubtierv2a/faster_rcnn_x101_64x4d_fpn_1x_raubtierv2a_nofreeze_4gpu.py
esf-bt2020/mmdetection
abc5fe060e0fcb716f845c85441be3741b22d3cf
[ "Apache-2.0" ]
null
null
null
configs/raubtierv2a/faster_rcnn_x101_64x4d_fpn_1x_raubtierv2a_nofreeze_4gpu.py
esf-bt2020/mmdetection
abc5fe060e0fcb716f845c85441be3741b22d3cf
[ "Apache-2.0" ]
null
null
null
configs/raubtierv2a/faster_rcnn_x101_64x4d_fpn_1x_raubtierv2a_nofreeze_4gpu.py
esf-bt2020/mmdetection
abc5fe060e0fcb716f845c85441be3741b22d3cf
[ "Apache-2.0" ]
null
null
null
_base_ = '../faster_rcnn/faster_rcnn_x101_64x4d_fpn_1x_coco.py' model = dict( backbone=dict( num_stages=4, #frozen_stages=4 ), roi_head=dict( bbox_head=dict( num_classes=3 ) ) ) dataset_type = 'COCODataset' classes = ('luchs', 'rotfuchs', 'wolf') data = dict...
26.375
151
0.704807
203
1,477
4.832512
0.44335
0.071356
0.071356
0.09684
0.445464
0.347604
0.252803
0.173293
0.173293
0.095821
0
0.1
0.16046
1,477
55
152
26.854545
0.691129
0.237644
0
0.096774
0
0
0.399464
0.320822
0
0
0
0
0
1
0
false
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ea32c16e86b4071267eb26a711d79f81eaea56
2,925
py
Python
xos/hpc_observer/steps/sync_originserver.py
wathsalav/xos
f6bcaa37a948ee41729236afe7fce0802e002404
[ "Apache-2.0" ]
null
null
null
xos/hpc_observer/steps/sync_originserver.py
wathsalav/xos
f6bcaa37a948ee41729236afe7fce0802e002404
[ "Apache-2.0" ]
null
null
null
xos/hpc_observer/steps/sync_originserver.py
wathsalav/xos
f6bcaa37a948ee41729236afe7fce0802e002404
[ "Apache-2.0" ]
null
null
null
import os import sys import base64 from django.db.models import F, Q from xos.config import Config from observer.syncstep import SyncStep from core.models import Service from hpc.models import ServiceProvider, ContentProvider, CDNPrefix, OriginServer from util.logger import Logger, logging # hpclibrary will be in ste...
34.411765
229
0.654701
380
2,925
4.873684
0.381579
0.090713
0.090713
0.073434
0.104752
0.024838
0
0
0
0
0
0.002275
0.248547
2,925
84
230
34.821429
0.840309
0.144274
0
0.038462
0
0
0.103171
0.00843
0
0
0
0
0
1
0.096154
false
0
0.192308
0.019231
0.403846
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ea437d66df34d28efcf808ad16c896dadcac76
400
py
Python
main.py
aroxby/pixel-processor
9cfe260a085ced0883ce8b0a35c28020f4aa8737
[ "MIT" ]
null
null
null
main.py
aroxby/pixel-processor
9cfe260a085ced0883ce8b0a35c28020f4aa8737
[ "MIT" ]
null
null
null
main.py
aroxby/pixel-processor
9cfe260a085ced0883ce8b0a35c28020f4aa8737
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 from PIL import Image def tranform(r, g, b): tmp = b b = g // 2 g = tmp r = r // 2 return r, g, b def main(): im = Image.open('blue-flames.jpg') input_pixels = im.getdata() output_pixels = tuple(tranform(*pixel) for pixel in input_pixels) im.putdata(output_...
17.391304
69
0.6
62
400
3.677419
0.580645
0.105263
0.026316
0
0
0
0
0
0
0
0
0.010067
0.255
400
22
70
18.181818
0.755034
0.0525
0
0
0
0
0.103175
0
0
0
0
0
0
1
0.133333
false
0
0.066667
0
0.266667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9eab80495274dd2446a7b029f17be91df29a452
1,539
py
Python
scipy/weave/examples/swig2_example.py
lesserwhirls/scipy-cwt
ee673656d879d9356892621e23ed0ced3d358621
[ "BSD-3-Clause" ]
8
2015-10-07T00:37:32.000Z
2022-01-21T17:02:33.000Z
scipy/weave/examples/swig2_example.py
lesserwhirls/scipy-cwt
ee673656d879d9356892621e23ed0ced3d358621
[ "BSD-3-Clause" ]
null
null
null
scipy/weave/examples/swig2_example.py
lesserwhirls/scipy-cwt
ee673656d879d9356892621e23ed0ced3d358621
[ "BSD-3-Clause" ]
8
2015-05-09T14:23:57.000Z
2018-11-15T05:56:00.000Z
"""Simple example to show how to use weave.inline on SWIG2 wrapped objects. SWIG2 refers to SWIG versions >= 1.3. To run this example you must build the trivial SWIG2 extension called swig2_ext. To do this you need to do something like this:: $ swig -c++ -python -I. -o swig2_ext_wrap.cxx swig2_ext.i $ g++ -Wall ...
28.5
69
0.690058
246
1,539
4.186992
0.520325
0.100971
0.046602
0.025243
0
0
0
0
0
0
0
0.030204
0.204029
1,539
53
70
29.037736
0.810612
0.684211
0
0
0
0
0.149451
0
0
0
0
0
0
1
0.066667
false
0
0.2
0
0.266667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9eba9b75a6e45fee4cdfe3d81874f5e8476b939
1,951
py
Python
src/simplify.py
denghz/Probabilistic-Programming
fa505a75c4558e507fd3effd2737c63537bfe50d
[ "BSD-3-Clause" ]
null
null
null
src/simplify.py
denghz/Probabilistic-Programming
fa505a75c4558e507fd3effd2737c63537bfe50d
[ "BSD-3-Clause" ]
null
null
null
src/simplify.py
denghz/Probabilistic-Programming
fa505a75c4558e507fd3effd2737c63537bfe50d
[ "BSD-3-Clause" ]
null
null
null
from wolframclient.language.expression import WLSymbol from nnDiff import * def parseGlobalSymbol(s): if isinstance(s, numbers.Number): return s if isinstance(s, WLSymbol): if s.name == 'E': return 'E' else: return s.name[7:] def parse(exp): symbol =...
27.097222
67
0.438237
212
1,951
3.990566
0.334906
0.023641
0.030733
0.033097
0
0
0
0
0
0
0
0.020814
0.433624
1,951
72
68
27.097222
0.744796
0
0
0.096774
0
0
0.038422
0
0
0
0
0
0
1
0.048387
false
0
0.032258
0
0.241935
0.032258
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9eda494aa9f90de7b3474adbd78e46927f9990c
406
py
Python
src/cart/forms.py
cbsBiram/xarala__ssr
863e1362c786daa752b942b796f7a015211d2f1b
[ "FSFAP" ]
null
null
null
src/cart/forms.py
cbsBiram/xarala__ssr
863e1362c786daa752b942b796f7a015211d2f1b
[ "FSFAP" ]
null
null
null
src/cart/forms.py
cbsBiram/xarala__ssr
863e1362c786daa752b942b796f7a015211d2f1b
[ "FSFAP" ]
null
null
null
from django import forms from django.utils.translation import gettext_lazy as _ COURSE_QUANTITY_CHOICES = [(i, str(i)) for i in range(1, 21)] class CartAddCourseForm(forms.Form): quantity = forms.TypedChoiceField( choices=COURSE_QUANTITY_CHOICES, coerce=int, label=_("Quantité") ) override = form...
27.066667
72
0.726601
49
406
5.877551
0.693878
0.069444
0.145833
0
0
0
0
0
0
0
0
0.008955
0.174877
406
14
73
29
0.850746
0
0
0
0
0
0.019704
0
0
0
0
0
0
1
0
false
0
0.2
0
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9edd7dbf25e820fdbc6faa76fd63ef5d9d3ec94
1,090
py
Python
appengine/components/tests/datastore_utils_properties_test.py
pombreda/swarming
c70f311f3db8f25752c793a0d7b36cf537d95580
[ "Apache-2.0" ]
null
null
null
appengine/components/tests/datastore_utils_properties_test.py
pombreda/swarming
c70f311f3db8f25752c793a0d7b36cf537d95580
[ "Apache-2.0" ]
null
null
null
appengine/components/tests/datastore_utils_properties_test.py
pombreda/swarming
c70f311f3db8f25752c793a0d7b36cf537d95580
[ "Apache-2.0" ]
1
2021-12-06T03:37:36.000Z
2021-12-06T03:37:36.000Z
#!/usr/bin/env python # Copyright 2014 The Swarming Authors. All rights reserved. # Use of this source code is governed by the Apache v2.0 license that can be # found in the LICENSE file. import sys import unittest import test_env test_env.setup_test_env() from google.appengine.ext import ndb from components.datast...
23.695652
76
0.713761
150
1,090
5.06
0.52
0.079051
0.031621
0.057971
0.052701
0
0
0
0
0
0
0.017279
0.150459
1,090
45
77
24.222222
0.802376
0.165138
0
0
0
0
0.028698
0
0
0
0
0
0.192308
1
0.076923
false
0
0.230769
0
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ef252652f99c5c9feffaab6f06bdbb7fe7dd89
953
py
Python
covfefe/covfefe.py
fixator10/Trusty-cogs
3d47a63f562cb64eb44da6bb53cfe9f8324026e7
[ "MIT" ]
148
2017-04-23T19:57:50.000Z
2022-03-12T06:59:58.000Z
covfefe/covfefe.py
mina9999/Trusty-cogs
a47de7c233f3c1802effd29f4a86f8a9b0e2b34a
[ "MIT" ]
155
2018-01-01T13:27:45.000Z
2022-03-12T05:17:51.000Z
covfefe/covfefe.py
mina9999/Trusty-cogs
a47de7c233f3c1802effd29f4a86f8a9b0e2b34a
[ "MIT" ]
221
2017-04-02T00:26:08.000Z
2022-03-26T15:06:54.000Z
import re import discord from redbot.core import commands class Covfefe(commands.Cog): """ Convert almost any word into covfefe """ def __init__(self, bot): self.bot = bot async def covfefe(self, x, k="aeiouy])"): """ https://codegolf.stackexchange.com/a/123697 "...
24.435897
79
0.541448
115
953
4.417391
0.582609
0.047244
0.062992
0.07874
0.122047
0.122047
0
0
0
0
0
0.012365
0.321091
953
38
80
25.078947
0.772798
0.037775
0
0
0
0
0.107856
0.029294
0
0
0
0
0
1
0.047619
false
0
0.142857
0
0.380952
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ef4b5c2209cb05949e60eccf8cd9158602e350
4,784
py
Python
exp_gqa/test.py
ronghanghu/gqa_single_hop_baseline
332d342da60dfefd40f2364d60215ed2f191aa2d
[ "BSD-2-Clause" ]
19
2019-08-19T18:09:26.000Z
2021-08-29T15:58:30.000Z
exp_gqa/test.py
ronghanghu/gqa_single_hop_baseline
332d342da60dfefd40f2364d60215ed2f191aa2d
[ "BSD-2-Clause" ]
1
2019-11-24T14:36:29.000Z
2019-12-11T08:33:12.000Z
exp_gqa/test.py
ronghanghu/gqa_single_hop_baseline
332d342da60dfefd40f2364d60215ed2f191aa2d
[ "BSD-2-Clause" ]
1
2019-10-30T05:55:52.000Z
2019-10-30T05:55:52.000Z
import os import numpy as np import tensorflow as tf from models_gqa.model import Model from models_gqa.config import build_cfg_from_argparse from util.gqa_train.data_reader import DataReader import json # Load config cfg = build_cfg_from_argparse() # Start session os.environ["CUDA_VISIBLE_DEVICES"] = str(cfg.GPU_ID...
40.201681
79
0.713002
736
4,784
4.328804
0.256793
0.043942
0.026365
0.032957
0.315443
0.284683
0.205273
0.161017
0.161017
0.134024
0
0.005542
0.170151
4,784
118
80
40.542373
0.796977
0.026756
0
0.082474
0
0.030928
0.125054
0.006457
0
0
0
0
0
1
0
false
0.010309
0.072165
0
0.072165
0.072165
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9efb93e53325ce5948d495ecf3a99ce26893591
2,071
py
Python
extract_gear/armor_visitor.py
kamerons/dde-extract-gear
44464ae470bd5de6279d32e3587b469ce006ea42
[ "Apache-2.0" ]
null
null
null
extract_gear/armor_visitor.py
kamerons/dde-extract-gear
44464ae470bd5de6279d32e3587b469ce006ea42
[ "Apache-2.0" ]
null
null
null
extract_gear/armor_visitor.py
kamerons/dde-extract-gear
44464ae470bd5de6279d32e3587b469ce006ea42
[ "Apache-2.0" ]
null
null
null
class ArmorVisitor: def __init__(self, num_pages, first_page_col_start, first_page_row_start, last_page_row_start, last_page_col_end, last_page_row_end, num_col_page=5, num_row_page=3): self.num_pages = num_pages self.first_page_col_start = first_page_col_start self.first_page_row_start = first_page_...
32.873016
110
0.718493
360
2,071
3.680556
0.105556
0.089811
0.090566
0.084528
0.490566
0.436981
0.315472
0.230943
0.199245
0.05283
0
0.00965
0.199421
2,071
62
111
33.403226
0.789505
0
0
0.08
0
0
0
0
0
0
0
0
0
1
0.12
false
0
0
0
0.22
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f401385afbe018601c2bef20e53c9b587fb7df
485
py
Python
examples/test_scalar_field.py
gemini3d/pv-gemini
99dff15b43a2c93cbcb63d2f8946d425d0555ef3
[ "Apache-2.0" ]
null
null
null
examples/test_scalar_field.py
gemini3d/pv-gemini
99dff15b43a2c93cbcb63d2f8946d425d0555ef3
[ "Apache-2.0" ]
null
null
null
examples/test_scalar_field.py
gemini3d/pv-gemini
99dff15b43a2c93cbcb63d2f8946d425d0555ef3
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python3 """ example of 3D scalar field If you get this error, ParaView doesn't know your data file format: TypeError: TestFileReadability argument %Id: %V """ from pathlib import Path import argparse import paraview.simple as pvs p = argparse.ArgumentParser() p.add_argument("fn", help="data file to l...
20.208333
75
0.740206
74
485
4.810811
0.702703
0.044944
0
0
0
0
0
0
0
0
0
0.004819
0.14433
485
23
76
21.086957
0.853012
0.340206
0
0
0
0
0.153846
0
0
0
0
0
0
1
0
false
0
0.3
0
0.3
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f4182f4b0683cbf4f51c72cef042f5acb55553
341
py
Python
src/cms/forms/languages/language_form.py
S10MC2015/cms-django
b08f2be60a9db6c8079ee923de2cd8912f550b12
[ "Apache-2.0" ]
null
null
null
src/cms/forms/languages/language_form.py
S10MC2015/cms-django
b08f2be60a9db6c8079ee923de2cd8912f550b12
[ "Apache-2.0" ]
null
null
null
src/cms/forms/languages/language_form.py
S10MC2015/cms-django
b08f2be60a9db6c8079ee923de2cd8912f550b12
[ "Apache-2.0" ]
null
null
null
from django import forms from ...models import Language class LanguageForm(forms.ModelForm): """ Form for creating and modifying language objects """ class Meta: model = Language fields = [ "code", "english_name", "native_name", "text_d...
17.947368
52
0.548387
31
341
5.935484
0.774194
0
0
0
0
0
0
0
0
0
0
0
0.363636
341
18
53
18.944444
0.847926
0.140762
0
0
0
0
0.148014
0
0
0
0
0
0
1
0
false
0
0.181818
0
0.363636
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f437d2e63f9838da4ffa0491804e95e149a773
1,482
py
Python
search/forms.py
gregneagle/sal
74c583fb1c1b33d3201b308b147376b3dcaca33f
[ "Apache-2.0" ]
2
2019-11-01T20:50:35.000Z
2021-01-13T22:02:55.000Z
search/forms.py
gregneagle/sal
74c583fb1c1b33d3201b308b147376b3dcaca33f
[ "Apache-2.0" ]
null
null
null
search/forms.py
gregneagle/sal
74c583fb1c1b33d3201b308b147376b3dcaca33f
[ "Apache-2.0" ]
null
null
null
from django import forms from .models import * from server.models import * class ChoiceFieldNoValidation(forms.ChoiceField): def validate(self, value): pass class SaveSearchForm(forms.ModelForm): class Meta: model = SavedSearch fields = ('name',) class SearchRowForm(forms.ModelForm):...
27.962264
87
0.609312
155
1,482
5.574194
0.412903
0.08912
0.052083
0.078704
0
0
0
0
0
0
0
0.001881
0.282726
1,482
52
88
28.5
0.810913
0
0
0.045455
0
0
0.106613
0
0
0
0
0
0
1
0.045455
false
0.022727
0.068182
0
0.318182
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f67833672023bef782862284907976acb9371f
2,216
py
Python
newsparser.py
antoreep-jana/BBC-News-Analyzer
0a6e54ddf4baefa4532213c5e6f60e712ff3a1ca
[ "MIT" ]
1
2021-12-27T12:57:07.000Z
2021-12-27T12:57:07.000Z
newsparser.py
antoreep-jana/BBC-News-Analyzer
0a6e54ddf4baefa4532213c5e6f60e712ff3a1ca
[ "MIT" ]
null
null
null
newsparser.py
antoreep-jana/BBC-News-Analyzer
0a6e54ddf4baefa4532213c5e6f60e712ff3a1ca
[ "MIT" ]
null
null
null
from bs4 import BeautifulSoup as bs import requests class BBC: def __init__(self, url:str): article = requests.get(url) self.soup = bs(article.content, "html.parser") #print(dir(self.soup)) #print(self.soup.h1.text) self.body = self.get_body() self.link = url ...
28.410256
98
0.564982
278
2,216
4.406475
0.291367
0.084898
0.078367
0.04898
0.223673
0.179592
0.151837
0.151837
0.151837
0.151837
0
0.022872
0.289711
2,216
77
99
28.779221
0.7554
0.229242
0
0.057143
0
0
0.170326
0.068843
0
0
0
0
0
1
0.171429
false
0.028571
0.057143
0.028571
0.4
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f73f41171ea9b93f4f79bc336c9fe6927dba89
2,044
py
Python
SIR_model-Copy.Caroline.1.py
Caroline-Odevall/final-project-team-18
fbf00ae4ec554dee9245a9834ff4108b3d339842
[ "MIT" ]
null
null
null
SIR_model-Copy.Caroline.1.py
Caroline-Odevall/final-project-team-18
fbf00ae4ec554dee9245a9834ff4108b3d339842
[ "MIT" ]
null
null
null
SIR_model-Copy.Caroline.1.py
Caroline-Odevall/final-project-team-18
fbf00ae4ec554dee9245a9834ff4108b3d339842
[ "MIT" ]
null
null
null
# In[42]: from scipy.integrate import odeint import numpy as np import matplotlib.pyplot as plt # In[43]: # describe the model def deriv(y, t, N, beta, gamma, delta): S, E, I, R = y dSdt = -beta * S * I / N # S(t) – susceptible (de som är mottagliga för infektion). dEdt = beta * S * I / N - gamma * ...
24.333333
137
0.630137
364
2,044
3.516484
0.436813
0.007813
0.009375
0.0125
0.151563
0.151563
0.029688
0.029688
0
0
0
0.04473
0.201566
2,044
83
138
24.626506
0.737745
0.354207
0
0
0
0
0.064241
0
0
0
0
0
0
1
0.052632
false
0
0.078947
0
0.157895
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f8215f5040fa71b2646d52a053545a92c3fd12
1,681
py
Python
app/middleware/cache_headers.py
Niclnx/service-stac
ad9129a7130d09b2bed387d8e82575eb86fdfa7b
[ "BSD-3-Clause" ]
9
2020-08-17T11:01:48.000Z
2022-01-17T22:24:13.000Z
app/middleware/cache_headers.py
Niclnx/service-stac
ad9129a7130d09b2bed387d8e82575eb86fdfa7b
[ "BSD-3-Clause" ]
100
2020-08-14T05:56:40.000Z
2022-03-01T22:39:58.000Z
app/middleware/cache_headers.py
Niclnx/service-stac
ad9129a7130d09b2bed387d8e82575eb86fdfa7b
[ "BSD-3-Clause" ]
3
2020-09-02T14:01:07.000Z
2021-07-27T06:30:26.000Z
import logging import re from urllib.parse import urlparse from django.conf import settings from django.utils.cache import add_never_cache_headers from django.utils.cache import patch_cache_control from django.utils.cache import patch_response_headers logger = logging.getLogger(__name__) STAC_BASE = settings.STAC_BA...
32.960784
96
0.662701
207
1,681
5.188406
0.415459
0.037244
0.041899
0.055866
0.150838
0.126629
0.068901
0.068901
0
0
0
0
0.250446
1,681
50
97
33.62
0.852381
0.252826
0
0
0
0
0.06068
0.01699
0
0
0
0
0
1
0.066667
false
0
0.233333
0
0.366667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f87264f50f9243a592053fcbe97aca0b8c2377
2,818
py
Python
mmdet/models/detectors/knowledge_distilling/kd_single_stage.py
anorthman/mmdetection
52e28154364f0e19d11c206bb357d88f29fc4a2d
[ "Apache-2.0" ]
5
2019-06-11T11:08:54.000Z
2021-03-25T10:06:01.000Z
mmdet/models/detectors/knowledge_distilling/kd_single_stage.py
anorthman/mmdetection
52e28154364f0e19d11c206bb357d88f29fc4a2d
[ "Apache-2.0" ]
null
null
null
mmdet/models/detectors/knowledge_distilling/kd_single_stage.py
anorthman/mmdetection
52e28154364f0e19d11c206bb357d88f29fc4a2d
[ "Apache-2.0" ]
1
2019-06-11T11:08:55.000Z
2019-06-11T11:08:55.000Z
# author huangchuanhong import torch from mmcv.runner import load_checkpoint from ..base import BaseDetector from ..single_stage import SingleStageDetector from ...registry import DETECTORS from ...builder import build_detector @DETECTORS.register_module class KDSingleStageDetector(SingleStageDetector): def __ini...
42.059701
112
0.551455
297
2,818
4.895623
0.218855
0.066025
0.091472
0.078404
0.296424
0.251719
0.251719
0.213205
0.167813
0.112792
0
0.002279
0.377218
2,818
66
113
42.69697
0.826211
0.007452
0
0.16129
0
0
0
0
0
0
0
0
0
1
0.032258
false
0
0.096774
0
0.16129
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9f8cb65181ebad752b9a810d28cc601137f1877
4,518
py
Python
metaworld/envs/mujoco/sawyer_xyz/v2/sawyer_dial_turn_v2.py
yiwc/robotics-world
48efda3a8ea6741b35828b02860f45753252e376
[ "MIT" ]
681
2019-09-09T19:34:37.000Z
2022-03-31T12:17:58.000Z
metaworld/envs/mujoco/sawyer_xyz/v2/sawyer_dial_turn_v2.py
yiwc/robotics-world
48efda3a8ea6741b35828b02860f45753252e376
[ "MIT" ]
212
2019-09-18T14:43:44.000Z
2022-03-27T22:21:00.000Z
metaworld/envs/mujoco/sawyer_xyz/v2/sawyer_dial_turn_v2.py
yiwc/robotics-world
48efda3a8ea6741b35828b02860f45753252e376
[ "MIT" ]
157
2019-09-12T05:06:05.000Z
2022-03-29T14:47:24.000Z
import numpy as np from gym.spaces import Box from metaworld.envs import reward_utils from metaworld.envs.asset_path_utils import full_v2_path_for from metaworld.envs.mujoco.sawyer_xyz.sawyer_xyz_env import SawyerXYZEnv, _assert_task_is_set class SawyerDialTurnEnvV2(SawyerXYZEnv): TARGET_RADIUS = 0.07 def _...
31.816901
93
0.599823
628
4,518
3.941083
0.221338
0.038384
0.053333
0.028283
0.225859
0.149091
0.098586
0.073535
0.073535
0.073535
0
0.036772
0.28973
4,518
141
94
32.042553
0.734497
0
0
0.088496
0
0
0.047587
0.005755
0
0
0
0
0.017699
1
0.061947
false
0
0.044248
0.017699
0.176991
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9fa7c6bd7a253ee2a588381042c5dfd3d99cb96
2,560
py
Python
yezdi/parser/parser.py
ragsagar/yezdi
5b97bedc56d5af7f28b244a0d7c0c8259f643102
[ "MIT" ]
1
2021-04-27T20:07:42.000Z
2021-04-27T20:07:42.000Z
yezdi/parser/parser.py
ragsagar/yezdi
5b97bedc56d5af7f28b244a0d7c0c8259f643102
[ "MIT" ]
null
null
null
yezdi/parser/parser.py
ragsagar/yezdi
5b97bedc56d5af7f28b244a0d7c0c8259f643102
[ "MIT" ]
null
null
null
from yezdi.lexer.token import TokenType from yezdi.parser.ast import Program, Statement, Participant, Title, LineStatement class Parser: def __init__(self, lexer): self.lexer = lexer self.current_token = None self.peek_token = None self.next_token() self.next_token() ...
32
86
0.640625
288
2,560
5.517361
0.184028
0.069226
0.100692
0.050346
0.229704
0.078037
0.060415
0.060415
0.060415
0
0
0
0.280469
2,560
79
87
32.405063
0.862649
0
0
0.227273
0
0
0
0
0
0
0
0
0
1
0.121212
false
0.015152
0.030303
0
0.409091
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9fae34b418d8854a4b364f1044c114896456110
1,050
py
Python
scripts/check_categories.py
oberron/entolusis
209e1e245d8e501e5e6ea2f52dd5b0da7d886f5c
[ "MIT" ]
null
null
null
scripts/check_categories.py
oberron/entolusis
209e1e245d8e501e5e6ea2f52dd5b0da7d886f5c
[ "MIT" ]
null
null
null
scripts/check_categories.py
oberron/entolusis
209e1e245d8e501e5e6ea2f52dd5b0da7d886f5c
[ "MIT" ]
null
null
null
# list categories in category folder from os import walk from os.path import abspath,join, pardir categories_folder = abspath(join(__file__,pardir,pardir,"category")) post_folder = abspath(join(__file__,pardir,pardir,"_posts")) site_categories = [] for root,directories,files in walk(categories_folder): for f in ...
36.206897
68
0.578095
124
1,050
4.741935
0.387097
0.142857
0.057823
0.071429
0.316327
0.258503
0.146259
0.146259
0
0
0
0.00672
0.291429
1,050
29
69
36.206897
0.783602
0.032381
0
0.086957
0
0
0.04335
0
0
0
0
0
0
1
0
false
0
0.086957
0
0.086957
0.086957
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9fb43e9d0e20574f25b444b461b284752a17b4c
5,311
py
Python
docsrc/makedoc.py
syoyo/soloud
cce88a2408a4b1e88ccbc75de9897b39bc3e7dda
[ "Libpng", "Zlib" ]
1
2019-11-25T11:32:09.000Z
2019-11-25T11:32:09.000Z
docsrc/makedoc.py
syoyo/soloud
cce88a2408a4b1e88ccbc75de9897b39bc3e7dda
[ "Libpng", "Zlib" ]
null
null
null
docsrc/makedoc.py
syoyo/soloud
cce88a2408a4b1e88ccbc75de9897b39bc3e7dda
[ "Libpng", "Zlib" ]
null
null
null
#!/usr/bin/env python3 """ builds documentation files from multimarkdown (mmd) source to various formats, including the web site and pdf. """ import subprocess import glob import os import sys import time import shutil src = [ "intro.mmd", "downloads.mmd", "quickstart.mmd", "faq.mmd", "dirstr...
34.940789
356
0.583129
662
5,311
4.63142
0.326284
0.042401
0.011416
0.011742
0.272016
0.234181
0.227658
0.14775
0.124592
0.081539
0
0.004619
0.184711
5,311
151
357
35.172185
0.703464
0.024854
0
0.140625
0
0
0.433327
0.090962
0
0
0
0
0
1
0
false
0.007813
0.046875
0
0.046875
0.085938
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b9ff46cab163507c14f9b26bf086ce4979f54a2c
4,972
py
Python
tools/unidatadownload.py
henryiii/backrefs
ec82844098bc3bdc7bcaa61b32f80271e6a73da6
[ "MIT" ]
null
null
null
tools/unidatadownload.py
henryiii/backrefs
ec82844098bc3bdc7bcaa61b32f80271e6a73da6
[ "MIT" ]
null
null
null
tools/unidatadownload.py
henryiii/backrefs
ec82844098bc3bdc7bcaa61b32f80271e6a73da6
[ "MIT" ]
null
null
null
"""Download `Unicodedata` files.""" from __future__ import unicode_literals import os import zipfile import codecs from urllib.request import urlopen __version__ = '2.2.0' HOME = os.path.dirname(os.path.abspath(__file__)) def zip_unicode(output, version): """Zip the Unicode files.""" zipper = zipfile.ZipFi...
32.927152
112
0.627715
560
4,972
5.467857
0.310714
0.035271
0.032658
0.041803
0.173416
0.167864
0.126061
0.088178
0.033965
0.033965
0
0.002934
0.245977
4,972
150
113
33.146667
0.813817
0.056718
0
0.111111
0
0
0.248981
0.11602
0
0
0
0
0
1
0.037037
false
0
0.064815
0
0.101852
0.055556
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a00c6e63b457a75c0424a247757123821cb24fb
1,230
py
Python
aspx2url/aspx2url.py
marcocucinato/aspx2url
985a0e51865bb7be15618155ff9844730c2eaaf6
[ "MIT" ]
null
null
null
aspx2url/aspx2url.py
marcocucinato/aspx2url
985a0e51865bb7be15618155ff9844730c2eaaf6
[ "MIT" ]
null
null
null
aspx2url/aspx2url.py
marcocucinato/aspx2url
985a0e51865bb7be15618155ff9844730c2eaaf6
[ "MIT" ]
null
null
null
from __future__ import print_function import re, sys, glob, getopt, os def usage(): print('aspx2url v1.0') print('Usage:') print(sys.argv[0]+' -d -h filename(s)') print('-d : Delete original file') print('-h : This help') def main(): try: opts, args = getopt.getopt(sys.argv[1:], "hd")...
29.285714
77
0.530081
145
1,230
4.393103
0.496552
0.037677
0.037677
0
0
0
0
0
0
0
0
0.009357
0.304878
1,230
41
78
30
0.735673
0
0
0.052632
0
0
0.139024
0.030894
0
0
0
0
0
1
0.052632
false
0
0.052632
0
0.105263
0.184211
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a00f65f8d9c6385beccc2cbd3c37ef660b0dc52
6,343
py
Python
tarentsocialwall/MongoDBClient.py
tarent/socialwall-backend
2f09b8ccdd62a15daaa281d6ff568cb6ef749ab6
[ "MIT" ]
null
null
null
tarentsocialwall/MongoDBClient.py
tarent/socialwall-backend
2f09b8ccdd62a15daaa281d6ff568cb6ef749ab6
[ "MIT" ]
null
null
null
tarentsocialwall/MongoDBClient.py
tarent/socialwall-backend
2f09b8ccdd62a15daaa281d6ff568cb6ef749ab6
[ "MIT" ]
2
2019-08-06T14:14:44.000Z
2019-08-06T14:21:19.000Z
import random from datetime import datetime from passlib.handlers.sha2_crypt import sha256_crypt from pymongo import MongoClient from pymongo.errors import ConnectionFailure from tarentsocialwall.SocialPost import SocialPost from tarentsocialwall.User import User from tarentsocialwall.Util import Util class MongoDB...
33.036458
100
0.631405
731
6,343
5.235294
0.201094
0.073164
0.047557
0.036582
0.296316
0.267311
0.238045
0.195453
0.174549
0.117586
0
0.003274
0.277787
6,343
191
101
33.209424
0.832133
0.07189
0
0.282609
0
0
0.058233
0
0
0
0
0
0
1
0.108696
false
0.021739
0.057971
0.007246
0.311594
0.043478
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a0102385be6299942545100e581de23300db9a4
76,697
py
Python
src/mount_efs/__init__.py
Sodki/efs-utils
493d9ea0dde93b560519b184219f6f71e32a8fcf
[ "MIT" ]
null
null
null
src/mount_efs/__init__.py
Sodki/efs-utils
493d9ea0dde93b560519b184219f6f71e32a8fcf
[ "MIT" ]
null
null
null
src/mount_efs/__init__.py
Sodki/efs-utils
493d9ea0dde93b560519b184219f6f71e32a8fcf
[ "MIT" ]
12
2020-10-22T03:47:51.000Z
2022-03-19T18:09:59.000Z
#!/usr/bin/env python # # Copyright 2017-2018 Amazon.com, Inc. and its affiliates. All Rights Reserved. # # Licensed under the MIT License. See the LICENSE accompanying this file # for the specific language governing permissions and limitations under # the License. # # # Copy this script to /sbin/mount.efs and make sur...
38.560583
130
0.680535
10,057
76,697
4.939147
0.107984
0.005234
0.010871
0.005818
0.40829
0.331186
0.284038
0.230407
0.202988
0.164556
0
0.007997
0.222316
76,697
1,988
131
38.57998
0.8248
0.092663
0
0.225897
0
0.014075
0.198127
0.023725
0
0
0
0
0.002111
1
0.069669
false
0.002815
0.024631
0.003519
0.194229
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a01fe7f065ff8fbb40e8cf44137b52463e1417c
1,010
py
Python
upcfcardsearch/c8.py
ProfessorSean/Kasutamaiza
7a69a69258f67bbb88bebbac6da4e6e1434947e6
[ "MIT" ]
null
null
null
upcfcardsearch/c8.py
ProfessorSean/Kasutamaiza
7a69a69258f67bbb88bebbac6da4e6e1434947e6
[ "MIT" ]
null
null
null
upcfcardsearch/c8.py
ProfessorSean/Kasutamaiza
7a69a69258f67bbb88bebbac6da4e6e1434947e6
[ "MIT" ]
null
null
null
import discord from discord.ext import commands from discord.utils import get class c8(commands.Cog, name="c8"): def __init__(self, bot: commands.Bot): self.bot = bot @commands.command(name='Sacrosanct_Devouring_Pyre', aliases=['c8']) async def example_embed(self, ctx): embed = discord.Emb...
43.913043
195
0.687129
138
1,010
4.934783
0.565217
0.048458
0.101322
0.07489
0
0
0
0
0
0
0
0.032767
0.184158
1,010
23
196
43.913043
0.793689
0
0
0
0
0.055556
0.323442
0.0455
0
0
0.007913
0
0
1
0.111111
false
0
0.166667
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a023f8c8af70de4e0b8e937c5773e7da489fab5
2,627
py
Python
SVMmodel_withSKF.py
tameney22/DCI-Capstone
6f59541f16030bfa3f0a706fd9f0e4394e1ee974
[ "MIT" ]
null
null
null
SVMmodel_withSKF.py
tameney22/DCI-Capstone
6f59541f16030bfa3f0a706fd9f0e4394e1ee974
[ "MIT" ]
null
null
null
SVMmodel_withSKF.py
tameney22/DCI-Capstone
6f59541f16030bfa3f0a706fd9f0e4394e1ee974
[ "MIT" ]
null
null
null
""" This script is where the preprocessed data is used to train the SVM model to perform the classification. I am using Stratified K-Fold Cross Validation to prevent bias and/or any imbalance that could affect the model's accuracy. REFERENCE: https://medium.com/@bedigunjit/simple-guide-to-text-classification-nlp-usin...
31.650602
132
0.760183
396
2,627
4.876263
0.386364
0.027965
0.01709
0.031072
0.037286
0
0
0
0
0
0
0.011329
0.12638
2,627
82
133
32.036585
0.830065
0.412257
0
0
0
0
0.134957
0
0
0
0
0
0
1
0
false
0
0.184211
0
0.184211
0.263158
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a048666edf3e5d75a0ded13639990b1d6bed2e8
33,554
py
Python
src/consensus.py
dschwoerer/samscripts
caee697e96a0639b7a4f9db02f70f4fd92b39ef9
[ "MIT" ]
null
null
null
src/consensus.py
dschwoerer/samscripts
caee697e96a0639b7a4f9db02f70f4fd92b39ef9
[ "MIT" ]
null
null
null
src/consensus.py
dschwoerer/samscripts
caee697e96a0639b7a4f9db02f70f4fd92b39ef9
[ "MIT" ]
null
null
null
#! /usr/bin/env python # Copyright Ivan Sovic, 2015. www.sovic.org # # Creates a pileup from a given SAM/BAM file, and calls consensus bases (or variants). import os import sys import operator import subprocess def increase_in_dict(dict_counter, value): try: dict_counter[value] += 1 except: ...
39.755924
436
0.550933
4,042
33,554
4.313953
0.114547
0.023513
0.03051
0.016345
0.535413
0.445375
0.385158
0.3453
0.332454
0.308941
0
0.015717
0.343893
33,554
843
437
39.803084
0.776334
0.216695
0
0.456656
0
0.03096
0.133988
0.041133
0
0
0
0.001186
0
1
0.00774
false
0.010836
0.006192
0
0.029412
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a049ff78a91de998072b637d1639d25a433a194
5,867
py
Python
web/addons/account_payment/wizard/account_payment_populate_statement.py
diogocs1/comps
63df07f6cf21c41e4527c06e2d0499f23f4322e7
[ "Apache-2.0" ]
null
null
null
web/addons/account_payment/wizard/account_payment_populate_statement.py
diogocs1/comps
63df07f6cf21c41e4527c06e2d0499f23f4322e7
[ "Apache-2.0" ]
null
null
null
web/addons/account_payment/wizard/account_payment_populate_statement.py
diogocs1/comps
63df07f6cf21c41e4527c06e2d0499f23f4322e7
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- ############################################################################## # # OpenERP, Open Source Management Solution # Copyright (C) 2004-2010 Tiny SPRL (<http://tiny.be>). # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU...
48.891667
250
0.592466
723
5,867
4.596127
0.26971
0.027084
0.027084
0.033704
0.290701
0.222389
0.136624
0.058381
0.058381
0.058381
0
0.003465
0.262144
5,867
119
251
49.302521
0.764149
0.154082
0
0.097561
0
0
0.160677
0.052863
0
0
0
0
0
1
0.02439
false
0
0.036585
0
0.146341
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a051324d6c23235da009880d6bcb0d30ed4d8dc
315
py
Python
2-Python-Fundamentals (Jan 2021)/Course-Exercises-and-Exams/08-Text-Processing/01_Lab/02-Repeat-Strings.py
karolinanikolova/SoftUni-Software-Engineering
7891924956598b11a1e30e2c220457c85c40f064
[ "MIT" ]
null
null
null
2-Python-Fundamentals (Jan 2021)/Course-Exercises-and-Exams/08-Text-Processing/01_Lab/02-Repeat-Strings.py
karolinanikolova/SoftUni-Software-Engineering
7891924956598b11a1e30e2c220457c85c40f064
[ "MIT" ]
null
null
null
2-Python-Fundamentals (Jan 2021)/Course-Exercises-and-Exams/08-Text-Processing/01_Lab/02-Repeat-Strings.py
karolinanikolova/SoftUni-Software-Engineering
7891924956598b11a1e30e2c220457c85c40f064
[ "MIT" ]
null
null
null
# 2. Repeat Strings # Write a Program That Reads a list of strings. Each string is repeated N times, where N is the length of the string. Print the concatenated string. strings = input().split() output_string = "" for string in strings: N = len(string) output_string += string * N print(output_string)
22.5
148
0.71746
49
315
4.55102
0.55102
0.161435
0
0
0
0
0
0
0
0
0
0.003984
0.203175
315
13
149
24.230769
0.884462
0.520635
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0
0
0
0.166667
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a0724ca0ed93e378a29473e0b6b5911cc4be4e6
944
py
Python
algorithm/dfs/boj_1260.py
ruslanlvivsky/python-algorithm
2b49bed33cd0e95b8a1e758008191f4392b3f667
[ "MIT" ]
3
2021-07-18T14:40:24.000Z
2021-08-14T18:08:13.000Z
algorithm/dfs/boj_1260.py
jinsuSang/python-algorithm
524849a0a7e71034d329fef63c4f384930334177
[ "MIT" ]
null
null
null
algorithm/dfs/boj_1260.py
jinsuSang/python-algorithm
524849a0a7e71034d329fef63c4f384930334177
[ "MIT" ]
null
null
null
def dfs(V): print(V, end=' ') visited[V] = True for n in graph[V]: if not visited[n]: dfs(n) def dfs_s(V): stack = [V] visited[V] = True while stack: now = stack.pop() print(now, end=' ') for n in graph[now]: if not visited[n]: ...
19.265306
44
0.470339
141
944
3.134752
0.248227
0.090498
0.081448
0.074661
0.352941
0.171946
0.171946
0.171946
0.171946
0.171946
0
0.009901
0.358051
944
48
45
19.666667
0.719472
0
0
0.358974
0
0
0.003178
0
0
0
0
0
0
1
0.076923
false
0
0
0
0.076923
0.102564
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a07aa532405a92d53e9ed5f46dcbcbd7a845cfa
634
py
Python
redirector.py
UKPLab/DiGAT
b044648a6c79428872a778908d3a8a689f0ac3e6
[ "Apache-2.0" ]
8
2016-06-22T17:02:45.000Z
2020-11-16T23:46:13.000Z
redirector.py
UKPLab/DiGAT
b044648a6c79428872a778908d3a8a689f0ac3e6
[ "Apache-2.0" ]
null
null
null
redirector.py
UKPLab/DiGAT
b044648a6c79428872a778908d3a8a689f0ac3e6
[ "Apache-2.0" ]
1
2019-02-25T04:40:04.000Z
2019-02-25T04:40:04.000Z
from google.appengine.ext import webapp from google.appengine.ext.webapp.util import run_wsgi_app __author__ = "Artem Vovk, Roland Kluge, and Christian Kirschner" __copyright__ = "Copyright 2013-2015 UKP TU Darmstadt" __credits__ = ["Artem Vovk", "Roland Kluge", "Christian Kirschner"] __license__ = "ASL" class Redire...
22.642857
67
0.705047
74
634
5.662162
0.594595
0.047733
0.090692
0.105012
0.128878
0
0
0
0
0
0
0.015152
0.167192
634
27
68
23.481481
0.778409
0
0
0.111111
0
0
0.26183
0
0
0
0
0
0
1
0.166667
false
0
0.111111
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a0b98cc37e3d3bfecf8eba880eba829290a251c
1,862
py
Python
deepgp_dsvi/demos/step_function.py
dks28/Deep-Gaussian-Process
a7aace43e78aae81468849aee7d172742e6ecf86
[ "MIT" ]
21
2020-03-07T15:40:13.000Z
2021-11-05T07:49:24.000Z
deepgp_dsvi/demos/step_function.py
dks28/Deep-Gaussian-Process
a7aace43e78aae81468849aee7d172742e6ecf86
[ "MIT" ]
3
2021-02-03T13:32:45.000Z
2021-07-17T16:07:06.000Z
src/demos/step_function.py
FelixOpolka/Deep-Gaussian-Process
40181f210d7b09863c321d1a90335be77233df80
[ "MIT" ]
2
2020-08-10T14:02:28.000Z
2020-12-28T16:03:09.000Z
import numpy as np import tensorflow as tf import matplotlib.pyplot as plt from gpflow.kernels import White, RBF from gpflow.likelihoods import Gaussian from deep_gp import DeepGP np.random.seed(0) tf.random.set_seed(0) def get_data(): Ns = 300 Xs = np.linspace(-0.5, 1.5, Ns)[:, None] N, M = 50, 25 ...
31.033333
77
0.645005
295
1,862
3.908475
0.40339
0.027754
0.024284
0.041631
0.08673
0.034692
0
0
0
0
0
0.036301
0.215897
1,862
60
78
31.033333
0.753425
0.023093
0
0
0
0
0.030803
0
0
0
0
0
0
1
0.044444
false
0
0.133333
0
0.222222
0.022222
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a0bd26d528523a33d941c1d0799a814a2b95dcf
5,343
py
Python
metaspace/engine/sm/engine/annotation_lithops/moldb_pipeline.py
METASPACE2020/METASPACE
e1acd9a409f84a78eed7ca9713258c09b0e137ca
[ "Apache-2.0" ]
32
2018-08-13T15:49:42.000Z
2022-01-17T18:32:19.000Z
metaspace/engine/sm/engine/annotation_lithops/moldb_pipeline.py
METASPACE2020/METASPACE
e1acd9a409f84a78eed7ca9713258c09b0e137ca
[ "Apache-2.0" ]
624
2018-07-02T15:18:22.000Z
2022-03-30T08:10:35.000Z
metaspace/engine/sm/engine/annotation_lithops/moldb_pipeline.py
METASPACE2020/METASPACE
e1acd9a409f84a78eed7ca9713258c09b0e137ca
[ "Apache-2.0" ]
6
2021-01-10T22:24:30.000Z
2022-03-16T19:14:37.000Z
from __future__ import annotations import json import logging from contextlib import contextmanager, ExitStack from typing import List, Dict import pandas as pd from lithops.storage import Storage from lithops.storage.utils import CloudObject, StorageNoSuchKeyError from sm.engine.annotation_lithops.build_moldb impor...
36.59589
99
0.668351
685
5,343
4.989781
0.290511
0.024576
0.041837
0.038619
0.176419
0.115565
0.086893
0.078994
0.060854
0.060854
0
0.003735
0.248362
5,343
145
100
36.848276
0.847361
0.124088
0
0.053097
0
0
0.079923
0.016285
0
0
0
0
0
1
0.061947
false
0
0.141593
0
0.256637
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a0dc9555ac01260e856ab868bd3c294497c065f
2,830
py
Python
gui/main_window/node_editor/items/connector_top_item.py
anglebinbin/Barista-tool
2d51507fb3566881923f0b273127f59d23ed317f
[ "MIT" ]
1
2020-02-11T19:05:17.000Z
2020-02-11T19:05:17.000Z
gui/main_window/node_editor/items/connector_top_item.py
anglebinbin/Barista-tool
2d51507fb3566881923f0b273127f59d23ed317f
[ "MIT" ]
null
null
null
gui/main_window/node_editor/items/connector_top_item.py
anglebinbin/Barista-tool
2d51507fb3566881923f0b273127f59d23ed317f
[ "MIT" ]
null
null
null
from PyQt5.QtWidgets import QMenu from gui.main_window.node_editor.items.connector_item import ConnectorItem class ConnectorTopItem(ConnectorItem): """ Class to provide top connector functionality """ def __init__(self, index, nodeItem, nodeEditor, parent=None): super(ConnectorTopItem, self).__init_...
44.21875
118
0.673852
289
2,830
6.519031
0.346021
0.045117
0.06104
0.07431
0.259023
0.135881
0.101911
0.101911
0.061571
0
0
0.000943
0.250883
2,830
63
119
44.920635
0.887736
0.280212
0
0.175
0
0
0.013875
0
0
0
0
0
0
1
0.175
false
0
0.05
0
0.35
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a0e7a4577ac3f9f8b9fd994210704a26f91ee39
2,606
py
Python
api/src/opentrons/protocol_engine/commands/thermocycler/open_lid.py
Opentrons/protocol_framework
ebbd6b2fe984edd6ecfcbf1dbe040db7f7356b9f
[ "Apache-2.0" ]
null
null
null
api/src/opentrons/protocol_engine/commands/thermocycler/open_lid.py
Opentrons/protocol_framework
ebbd6b2fe984edd6ecfcbf1dbe040db7f7356b9f
[ "Apache-2.0" ]
null
null
null
api/src/opentrons/protocol_engine/commands/thermocycler/open_lid.py
Opentrons/protocol_framework
ebbd6b2fe984edd6ecfcbf1dbe040db7f7356b9f
[ "Apache-2.0" ]
null
null
null
"""Command models to open a Thermocycler's lid.""" from __future__ import annotations from typing import Optional, TYPE_CHECKING from typing_extensions import Literal, Type from pydantic import BaseModel, Field from ..command import AbstractCommandImpl, BaseCommand, BaseCommandCreate from opentrons.protocol_engine.ty...
30.302326
87
0.699156
263
2,606
6.771863
0.387833
0.051095
0.055025
0.057271
0.138686
0.126895
0.101067
0.101067
0.101067
0.101067
0
0
0.224482
2,606
85
88
30.658824
0.881247
0.149655
0
0.078431
0
0
0.041822
0
0
0
0
0
0
1
0.019608
false
0
0.156863
0
0.45098
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a11d7dca909e3885ae2dbc3bc1e2d0a99547ada
3,901
py
Python
scripts/randomize_sw2_seed.py
epichoxha/nanodump
3a269ed427b474a701197e13ce40cb1daf803a82
[ "Apache-2.0" ]
null
null
null
scripts/randomize_sw2_seed.py
epichoxha/nanodump
3a269ed427b474a701197e13ce40cb1daf803a82
[ "Apache-2.0" ]
null
null
null
scripts/randomize_sw2_seed.py
epichoxha/nanodump
3a269ed427b474a701197e13ce40cb1daf803a82
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import os import re import glob import random import struct def get_old_seed(): with open('include/syscalls.h') as f: code = f.read() match = re.search(r'#define SW2_SEED (0x[a-fA-F0-9]{8})', code) assert match is not None, 'SW2_SEED not found!' ...
32.508333
104
0.600103
568
3,901
3.922535
0.207746
0.059246
0.015709
0.017953
0.461849
0.380162
0.253591
0.2307
0.194794
0.132855
0
0.027586
0.256601
3,901
119
105
32.781513
0.74069
0.016406
0
0.242105
0
0
0.213876
0.024517
0
0
0
0
0.031579
1
0.063158
false
0
0.052632
0
0.136842
0.031579
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a11fa8d863a9e5b451bd2a7ef2241aafe768509
1,289
py
Python
checker/checker/executer.py
grimpy/hexa-a
556e9a2a70758bf9c7d70f91776d361b40524c78
[ "Apache-2.0" ]
3
2018-02-05T11:43:04.000Z
2019-02-22T18:11:55.000Z
checker/checker/executer.py
grimpy/hexa-a
556e9a2a70758bf9c7d70f91776d361b40524c78
[ "Apache-2.0" ]
4
2019-03-26T09:51:43.000Z
2019-03-31T06:41:14.000Z
checker/checker/executer.py
grimpy/hexa-a
556e9a2a70758bf9c7d70f91776d361b40524c78
[ "Apache-2.0" ]
1
2019-03-03T20:55:21.000Z
2019-03-03T20:55:21.000Z
from subprocess import run, PIPE, TimeoutExpired, CompletedProcess from codes import exitcodes def _error_decode(response): stderr = "" if response.returncode: if response.returncode < 0: errmsg = exitcodes.get(abs(response.returncode), "Unknown Error") if isinstance(errmsg, dic...
30.690476
78
0.577967
121
1,289
6.115702
0.429752
0.145946
0.051351
0.083784
0.110811
0
0
0
0
0
0
0.008037
0.324282
1,289
42
79
30.690476
0.841561
0
0
0.102564
0
0
0.058915
0
0
0
0
0
0
1
0.051282
false
0
0.051282
0
0.153846
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a124e6043f5f93ce124eed73efc4b8488512375
1,739
py
Python
pfm/pf_command/update.py
takahi-i/pfm
224ca961ca43f50bd877789e2d8659ae838d517f
[ "MIT" ]
9
2018-01-06T05:44:43.000Z
2020-06-24T00:15:16.000Z
pfm/pf_command/update.py
takahi-i/pfm
224ca961ca43f50bd877789e2d8659ae838d517f
[ "MIT" ]
27
2018-01-06T09:29:48.000Z
2020-04-10T16:11:59.000Z
pfm/pf_command/update.py
takahi-i/pfm
224ca961ca43f50bd877789e2d8659ae838d517f
[ "MIT" ]
1
2018-01-09T01:33:42.000Z
2018-01-09T01:33:42.000Z
import json from pfm.pf_command.base import BaseCommand from pfm.util.log import logger class UpdateCommand(BaseCommand): def __init__(self, name, forward_type, remote_host, remote_port, local_port, ssh_server, server_port, login_user, config): super(UpdateCommand, self)...
34.78
88
0.617021
229
1,739
4.458515
0.240175
0.047013
0.061704
0.10284
0.119491
0
0
0
0
0
0
0.000815
0.294422
1,739
49
89
35.489796
0.831296
0.009201
0
0
0
0
0.06566
0
0
0
0
0
0
1
0.071429
false
0
0.071429
0
0.166667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a12692597c07586454530c9bcf5baae61076b3f
7,499
py
Python
tests/atfork/test_atfork.py
luciferliu/xTools
324ef1388be13ece0d952e3929eb685212d573f1
[ "Apache-2.0" ]
null
null
null
tests/atfork/test_atfork.py
luciferliu/xTools
324ef1388be13ece0d952e3929eb685212d573f1
[ "Apache-2.0" ]
null
null
null
tests/atfork/test_atfork.py
luciferliu/xTools
324ef1388be13ece0d952e3929eb685212d573f1
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/python # # Copyright 2009 Google 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...
37.123762
86
0.648887
926
7,499
4.971922
0.222462
0.024761
0.026064
0.048653
0.356212
0.28106
0.221546
0.165508
0.149001
0.111642
0
0.005204
0.256834
7,499
201
87
37.308458
0.820922
0.139752
0
0.202797
0
0
0.064184
0
0
0
0
0
0.258741
1
0.160839
false
0
0.055944
0
0.230769
0.006993
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a131e98cf16cdcab3785e1e0af7a922aba56c50
2,213
py
Python
IO/files/handling.py
brendano257/Zugspitze-Schneefernerhaus
64bb86ece2eec147f2a7fb412f87ff2313388753
[ "MIT" ]
null
null
null
IO/files/handling.py
brendano257/Zugspitze-Schneefernerhaus
64bb86ece2eec147f2a7fb412f87ff2313388753
[ "MIT" ]
null
null
null
IO/files/handling.py
brendano257/Zugspitze-Schneefernerhaus
64bb86ece2eec147f2a7fb412f87ff2313388753
[ "MIT" ]
null
null
null
import os from pathlib import Path __all__ = ['list_files_recur', 'scan_and_create_dir_tree', 'get_all_data_files', 'get_subsubdirs'] def list_files_recur(path): """ Cheater function that wraps path.rglob(). :param Path path: path to list recursively :return list: list of Path objects """ fi...
28.371795
106
0.66742
338
2,213
4.230769
0.319527
0.041958
0.053846
0.022378
0.131469
0.053147
0.053147
0.053147
0.053147
0.053147
0
0.002377
0.239494
2,213
77
107
28.74026
0.847296
0.432445
0
0.193548
0
0
0.063644
0.020924
0
0
0
0
0
1
0.129032
false
0.032258
0.064516
0
0.290323
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a139742e2452134cace4ac02e78a8badeceb098
2,617
py
Python
tools/mo/openvino/tools/mo/ops/detection_output_onnx.py
ryanloney/openvino-1
4e0a740eb3ee31062ba0df88fcf438564f67edb7
[ "Apache-2.0" ]
1,127
2018-10-15T14:36:58.000Z
2020-04-20T09:29:44.000Z
tools/mo/openvino/tools/mo/ops/detection_output_onnx.py
ryanloney/openvino-1
4e0a740eb3ee31062ba0df88fcf438564f67edb7
[ "Apache-2.0" ]
439
2018-10-20T04:40:35.000Z
2020-04-19T05:56:25.000Z
tools/mo/openvino/tools/mo/ops/detection_output_onnx.py
ryanloney/openvino-1
4e0a740eb3ee31062ba0df88fcf438564f67edb7
[ "Apache-2.0" ]
414
2018-10-17T05:53:46.000Z
2020-04-16T17:29:53.000Z
# Copyright (C) 2018-2022 Intel Corporation # SPDX-License-Identifier: Apache-2.0 import numpy as np from openvino.tools.mo.front.common.partial_infer.utils import dynamic_dimension_value, shape_array, set_input_shapes from openvino.tools.mo.ops.op import Op class ExperimentalDetectronDetectionOutput(Op): op = ...
39.059701
117
0.635078
328
2,617
4.762195
0.375
0.040333
0.049296
0.049936
0.232394
0.145967
0.09219
0.09219
0.058899
0
0
0.018566
0.259075
2,617
66
118
39.651515
0.787004
0.143294
0
0.06
0
0
0.10927
0.052844
0
0
0
0
0
1
0.1
false
0
0.06
0.02
0.24
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a139aa59f68903a8a744250e0c92696c28eb301
2,046
py
Python
driver.py
FahimMahmudJoy/Physionet_2019_Sepsis
d31bec40aa0359071bfaff1a4d72569c5731a04e
[ "BSD-2-Clause" ]
1
2019-06-26T19:38:33.000Z
2019-06-26T19:38:33.000Z
driver.py
FahimMahmudJoy/Physionet_2019_Sepsis
d31bec40aa0359071bfaff1a4d72569c5731a04e
[ "BSD-2-Clause" ]
null
null
null
driver.py
FahimMahmudJoy/Physionet_2019_Sepsis
d31bec40aa0359071bfaff1a4d72569c5731a04e
[ "BSD-2-Clause" ]
null
null
null
#!/usr/bin/env python import numpy as np, os, sys from get_sepsis_score import load_sepsis_model, get_sepsis_score def load_challenge_data(file): with open(file, 'r') as f: header = f.readline().strip() column_names = header.split('|') data = np.loadtxt(f, delimiter='|') # Ignore Seps...
30.537313
124
0.623167
274
2,046
4.463504
0.368613
0.02453
0.034342
0.017989
0.040883
0.040883
0
0
0
0
0
0.004596
0.255621
2,046
66
125
31
0.798424
0.091398
0
0
0
0
0.087615
0.020011
0
0
0
0
0
1
0.047619
false
0
0.047619
0
0.119048
0.02381
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a139fa7954e69a2e28f61ebd4a2c8e7028fb83e
2,589
py
Python
src/LspRuntimeMonitor.py
TafsirGna/ClspGeneticAlgorithm
25184afbbd52773b8aed2e268ae98dd9656cacda
[ "MIT" ]
null
null
null
src/LspRuntimeMonitor.py
TafsirGna/ClspGeneticAlgorithm
25184afbbd52773b8aed2e268ae98dd9656cacda
[ "MIT" ]
null
null
null
src/LspRuntimeMonitor.py
TafsirGna/ClspGeneticAlgorithm
25184afbbd52773b8aed2e268ae98dd9656cacda
[ "MIT" ]
null
null
null
#!/usr/bin/python3.5 # -*-coding: utf-8 -* from collections import defaultdict from threading import Thread from time import perf_counter, time from LspLibrary import bcolors import time import matplotlib.pyplot as plt class LspRuntimeMonitor: """ """ clockStart = None clockEnd = None mutation_s...
21.940678
71
0.545384
250
2,589
5.604
0.428
0.079943
0.018558
0.031406
0.105639
0.105639
0.105639
0.105639
0.105639
0.105639
0
0.00453
0.317883
2,589
118
72
21.940678
0.788788
0.107764
0
0.15625
0
0
0.11039
0.041744
0
0
0
0
0
1
0.140625
false
0.015625
0.09375
0
0.390625
0.078125
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a152a32efa9784006230b4163868ce2479ff3ba
20,737
py
Python
methylcheck/predict/sex.py
FoxoTech/methylcheck
881d14d78e6086aab184716e0b79cdf87e9be8bf
[ "MIT" ]
null
null
null
methylcheck/predict/sex.py
FoxoTech/methylcheck
881d14d78e6086aab184716e0b79cdf87e9be8bf
[ "MIT" ]
11
2021-04-08T16:14:54.000Z
2022-03-09T00:22:13.000Z
methylcheck/predict/sex.py
FoxoTech/methylcheck
881d14d78e6086aab184716e0b79cdf87e9be8bf
[ "MIT" ]
1
2022-02-10T09:06:45.000Z
2022-02-10T09:06:45.000Z
import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns from pathlib import Path #app import methylcheck # uses .load; get_sex uses methylprep models too and detect_array() import logging LOGGER = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def _get_copy_n...
53.583979
191
0.672711
2,931
20,737
4.580007
0.181167
0.02868
0.036874
0.016389
0.257449
0.197482
0.161949
0.129172
0.090957
0.080825
0
0.009363
0.227468
20,737
386
192
53.722798
0.828589
0.325216
0
0.155039
0
0.011628
0.174485
0.025573
0
0
0
0
0
1
0.015504
false
0.007752
0.042636
0
0.085271
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a164cca97745158870c1da7ad0a330912380e28
2,504
py
Python
tests/test_basics.py
sirosen/git-fortune
69ef3e18506aa67fdc812854f1588828ea4e7448
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
tests/test_basics.py
sirosen/git-fortune
69ef3e18506aa67fdc812854f1588828ea4e7448
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
tests/test_basics.py
sirosen/git-fortune
69ef3e18506aa67fdc812854f1588828ea4e7448
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
import subprocess from git_fortune._compat import fix_line_endings from git_fortune.version import __version__ def test_help(capfd): subprocess.check_call(["git-fortune", "-h"]) captured = capfd.readouterr() assert ( fix_line_endings( """ A fortune-like command for showing git tips I...
33.386667
81
0.527157
251
2,504
5.111554
0.334661
0.093531
0.076383
0.158223
0.506625
0.420889
0.221356
0.221356
0.221356
0.221356
0
0.005093
0.294329
2,504
74
82
33.837838
0.720996
0.044728
0
0.214286
0
0
0.181481
0
0
0
0
0
0.214286
1
0.166667
false
0
0.071429
0
0.238095
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a167dd5d92960139223aa44954c2cb6cacf4375
2,487
py
Python
configs/keypoints/faster_rcnn_r50_fpn_keypoints.py
VGrondin/CBNetV2_mask_remote
b27246af5081d5395db3c3105d32226de05fcd13
[ "Apache-2.0" ]
null
null
null
configs/keypoints/faster_rcnn_r50_fpn_keypoints.py
VGrondin/CBNetV2_mask_remote
b27246af5081d5395db3c3105d32226de05fcd13
[ "Apache-2.0" ]
null
null
null
configs/keypoints/faster_rcnn_r50_fpn_keypoints.py
VGrondin/CBNetV2_mask_remote
b27246af5081d5395db3c3105d32226de05fcd13
[ "Apache-2.0" ]
null
null
null
_base_ = [ '../_base_/models/faster_rcnn_r50_fpn.py' ] model = dict( type='FasterRCNN', # pretrained='torchvision://resnet50', backbone=dict( type='ResNet', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, norm_cfg=dict(type='BN', requir...
32.298701
77
0.542421
292
2,487
4.386986
0.39726
0.118657
0.01171
0.01249
0.259953
0.235753
0.229508
0.165496
0.165496
0.165496
0
0.083284
0.31926
2,487
76
78
32.723684
0.673361
0.148372
0
0.166667
0
0
0.119297
0.029943
0
0
0
0
0
1
0
false
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a168cae49b57ce434a41c7070da071ca4734fc0
3,232
py
Python
maskrcnn_benchmark/layers/roi_align_rotated_3d.py
picwoon/As_built_BIM
9e6b81e2fd8904f5afd013e21d2db45456c138d5
[ "MIT" ]
2
2020-03-05T06:39:03.000Z
2020-03-31T12:08:04.000Z
maskrcnn_benchmark/layers/roi_align_rotated_3d.py
picwoon/As_built_BIM
9e6b81e2fd8904f5afd013e21d2db45456c138d5
[ "MIT" ]
null
null
null
maskrcnn_benchmark/layers/roi_align_rotated_3d.py
picwoon/As_built_BIM
9e6b81e2fd8904f5afd013e21d2db45456c138d5
[ "MIT" ]
1
2021-09-24T13:17:40.000Z
2021-09-24T13:17:40.000Z
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import torch, math from torch import nn from torch.autograd import Function from torch.autograd.function import once_differentiable from torch.nn.modules.utils import _pair from SparseConvNet.sparseconvnet.tools_3d_2d import sparse_3d_to_dense_2d i...
34.021053
101
0.63552
412
3,232
4.665049
0.296117
0.098855
0.031217
0.03538
0.184703
0.083247
0.046826
0.046826
0.046826
0.046826
0
0.029588
0.278465
3,232
94
102
34.382979
0.794597
0.219369
0
0.064516
0
0
0.019567
0
0
0
0
0
0
1
0.080645
false
0
0.112903
0
0.290323
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a16ef74b6b87e7acddaab1f4ea03a7e48da5422
8,360
py
Python
src/model/utils/utils.py
J-CITY/METADATA-EXTRACTOR
6bc01a7e4b74a3156c07efc2c80d5519c325dd53
[ "Apache-2.0" ]
null
null
null
src/model/utils/utils.py
J-CITY/METADATA-EXTRACTOR
6bc01a7e4b74a3156c07efc2c80d5519c325dd53
[ "Apache-2.0" ]
null
null
null
src/model/utils/utils.py
J-CITY/METADATA-EXTRACTOR
6bc01a7e4b74a3156c07efc2c80d5519c325dd53
[ "Apache-2.0" ]
null
null
null
import numpy as np import os from .logger import printLog UNK = "$UNK$" NUM = "$NUM$" NONE = "O" class ParrotIOError(Exception): def __init__(self, filename): message = "ERROR: Can not find file {}.".format(filename) super(ParrotIOError, self).__init__(message) # Class that iterates over CoNLL Da...
32.784314
84
0.55323
901
8,360
5.084351
0.241953
0.008732
0.015717
0.015281
0.14451
0.120061
0.087754
0.079895
0.048461
0
0
0.00784
0.3439
8,360
254
85
32.913386
0.827347
0.093062
0
0.192893
0
0
0.023148
0
0
0
0
0
0
1
0.091371
false
0.005076
0.015228
0
0.182741
0.030457
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a177f73dcbbd6c1d2721285cc1b7c72b4784fb1
2,781
py
Python
discordbot/economy/currencies.py
minhhoang1023/GamestonkTerminal
195dc19b491052df080178c0cc6a9d535a91a704
[ "MIT" ]
1
2022-02-18T04:02:52.000Z
2022-02-18T04:02:52.000Z
discordbot/economy/currencies.py
minhhoang1023/GamestonkTerminal
195dc19b491052df080178c0cc6a9d535a91a704
[ "MIT" ]
null
null
null
discordbot/economy/currencies.py
minhhoang1023/GamestonkTerminal
195dc19b491052df080178c0cc6a9d535a91a704
[ "MIT" ]
null
null
null
import os import df2img import disnake import pandas as pd from PIL import Image import discordbot.config_discordbot as cfg from discordbot.config_discordbot import logger from discordbot.helpers import autocrop_image from gamestonk_terminal.economy import wsj_model async def currencies_command(ctx): """Currenc...
27.81
85
0.54297
316
2,781
4.670886
0.417722
0.01626
0.022358
0.026423
0.184959
0.126694
0.126694
0.126694
0.126694
0.126694
0
0.018848
0.332255
2,781
99
86
28.090909
0.775983
0.032003
0
0.131579
0
0
0.095004
0.009084
0
0
0
0
0
1
0
false
0
0.118421
0
0.118421
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a17d1c656acfd1f8102ff27381a0764e4f0a027
3,276
py
Python
aiovectortiler/config_handler.py
shongololo/aiovectortiler
cfd0008d5ac05baee52a24264f991946324f5a42
[ "MIT" ]
4
2016-07-24T20:39:40.000Z
2018-12-26T06:43:35.000Z
aiovectortiler/config_handler.py
songololo/aiovectortiler
cfd0008d5ac05baee52a24264f991946324f5a42
[ "MIT" ]
7
2016-08-10T16:27:39.000Z
2018-10-13T13:16:24.000Z
aiovectortiler/config_handler.py
songololo/aiovectortiler
cfd0008d5ac05baee52a24264f991946324f5a42
[ "MIT" ]
3
2016-08-09T03:12:24.000Z
2016-11-08T01:17:29.000Z
import os import yaml import logging logger = logging.getLogger(__name__) class Configs: server = None recipes = {} DB = None plugins = None @classmethod def init_server_configs(cls, server_configs): with open(server_configs) as s_c: cls.server = yaml.load(s_c.read()) ...
28.99115
124
0.626984
420
3,276
4.695238
0.25
0.076065
0.026369
0.03499
0.123225
0.123225
0.123225
0.123225
0.105477
0.105477
0
0.004473
0.24939
3,276
112
125
29.25
0.797479
0.084554
0
0.140625
0
0
0.06296
0
0
0
0
0
0
1
0.1875
false
0
0.046875
0.078125
0.4375
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a17e7c4a91ac2e9483c7bdc29806cbac3d7a40c
13,237
py
Python
t2vretrieval/models/mlmatch.py
Roc-Ng/HANet
e679703e9e725205424d87f750358fb4f62ceec5
[ "MIT" ]
34
2021-07-26T12:22:05.000Z
2022-03-08T03:49:33.000Z
t2vretrieval/models/mlmatch.py
hexiangteng/HANet
31d37ccad9c56ff9422cb4eb9d32e79e7b9bc831
[ "MIT" ]
null
null
null
t2vretrieval/models/mlmatch.py
hexiangteng/HANet
31d37ccad9c56ff9422cb4eb9d32e79e7b9bc831
[ "MIT" ]
3
2021-08-03T06:00:26.000Z
2021-12-27T03:26:12.000Z
import numpy as np import torch import framework.ops import t2vretrieval.encoders.mlsent import t2vretrieval.encoders.mlvideo import t2vretrieval.models.globalmatch from t2vretrieval.models.criterion import cosine_sim from t2vretrieval.models.globalmatch import VISENC, TXTENC class RoleGraphMatchModelConfig(t2vretri...
46.939716
156
0.694568
1,936
13,237
4.410641
0.129132
0.02108
0.018269
0.019674
0.338564
0.231994
0.146973
0.093688
0.046141
0.038412
0
0.01392
0.169676
13,237
281
157
47.106762
0.762988
0.080079
0
0.055556
0
0.00463
0.079025
0
0
0
0
0
0.00463
1
0.046296
false
0
0.037037
0.00463
0.138889
0.023148
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a190e5eb1440e6a01fc6f170da74507f39571ac
6,295
py
Python
dronesym-python/flask-api/src/dronepool.py
dilinade/DroneSym
30073bd31343bc27c6b8d72e48b4e06ced0c5fe6
[ "Apache-2.0" ]
1
2019-03-24T23:50:07.000Z
2019-03-24T23:50:07.000Z
dronesym-python/flask-api/src/dronepool.py
dilinade/DroneSym
30073bd31343bc27c6b8d72e48b4e06ced0c5fe6
[ "Apache-2.0" ]
null
null
null
dronesym-python/flask-api/src/dronepool.py
dilinade/DroneSym
30073bd31343bc27c6b8d72e48b4e06ced0c5fe6
[ "Apache-2.0" ]
null
null
null
#DronePool module which handles interaction with SITLs from dronekit import Vehicle, VehicleMode, connect from dronekit_sitl import SITL from threading import Lock import node, time import mavparser import threadrunner drone_pool = {} instance_count = 0 env_test = False q = None mq = None lock = Lock() class Sim(SI...
27.133621
187
0.707705
884
6,295
4.825792
0.186652
0.047586
0.040084
0.028129
0.296296
0.246835
0.205345
0.199015
0.178153
0.11158
0
0.007268
0.147577
6,295
231
188
27.251082
0.787738
0.014138
0
0.160494
0
0
0.107045
0
0
0
0
0
0
1
0.104938
false
0
0.037037
0.012346
0.234568
0.061728
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a19dea1f3bc079f6c50613369f0699df82e34cf
2,365
py
Python
Problemset/longest-string-chain/longest-string-chain.py
KivenCkl/LeetCode
fcc97c66f8154a5d20c2aca86120cb37b9d2d83d
[ "MIT" ]
7
2019-05-08T03:41:05.000Z
2020-12-22T12:39:43.000Z
Problemset/longest-string-chain/longest-string-chain.py
Yuziquan/LeetCode
303fc1c8af847f783c4020bd731b28b72ed92a35
[ "MIT" ]
1
2021-07-19T03:48:35.000Z
2021-07-19T03:48:35.000Z
Problemset/longest-string-chain/longest-string-chain.py
Yuziquan/LeetCode
303fc1c8af847f783c4020bd731b28b72ed92a35
[ "MIT" ]
7
2019-05-10T20:43:20.000Z
2021-02-22T03:47:35.000Z
# @Title: 最长字符串链 (Longest String Chain) # @Author: KivenC # @Date: 2019-05-26 20:35:25 # @Runtime: 144 ms # @Memory: 13.3 MB class Solution: # # way 1 # def longestStrChain(self, words: List[str]) -> int: # # 动态规划 # # dp[i] = max(dp[i], dp[j] + 1) (0 <= j < i 且 words[j] 是 words[i] 的前身) # ...
33.785714
81
0.442283
299
2,365
3.494983
0.284281
0.03445
0.042105
0.051675
0.200957
0.200957
0.200957
0.091866
0
0
0
0.052364
0.418605
2,365
69
82
34.275362
0.707636
0.647357
0
0
0
0
0
0
0
0
0
0
0
1
0.052632
false
0
0.052632
0
0.263158
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a19e8bf83375a817e65cca3fb4f7daafac8434e
21,107
py
Python
IKFK Builder/IKFK_Builder.py
ssimbox/ssimbox-rigTools
824bc3b90c42ab54d01b4b0007f00e7cc2f2f08c
[ "MIT" ]
1
2021-01-19T13:36:42.000Z
2021-01-19T13:36:42.000Z
IKFK Builder/IKFK_Builder.py
ssimbox/sbx-autorig
824bc3b90c42ab54d01b4b0007f00e7cc2f2f08c
[ "MIT" ]
2
2021-03-29T22:15:08.000Z
2021-03-29T22:17:37.000Z
IKFK Builder/IKFK_Builder.py
ssimbox/ssimbox-rigTools
824bc3b90c42ab54d01b4b0007f00e7cc2f2f08c
[ "MIT" ]
null
null
null
from ctrlUI_lib import createClav2, createSphere import maya.cmds as cmds import maya.OpenMaya as om from functools import partial def duplicateChain(*args): global ogChain global chainLen global switcherLoc global side global controllerColor global clavCheckbox global rigGrp, ctrlGrp ...
41.386275
140
0.607713
2,599
21,107
4.865718
0.166987
0.007908
0.01115
0.014866
0.319706
0.25431
0.223312
0.178475
0.157204
0.133797
0
0.038685
0.250486
21,107
510
141
41.386275
0.760683
0.115791
0
0.119632
0
0
0.071843
0.004947
0
0
0
0
0
1
0.039877
false
0
0.01227
0
0.052147
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a1cf3b76d95e590eb1efa6bc9673c121f9d7242
5,128
py
Python
pipng/imagescale-q-m.py
nwiizo/joke
808c4c998cc7f5b7f6f3fb5a3ce421588a70c087
[ "MIT" ]
1
2017-01-11T06:12:24.000Z
2017-01-11T06:12:24.000Z
pipng/imagescale-q-m.py
ShuyaMotouchi/joke
808c4c998cc7f5b7f6f3fb5a3ce421588a70c087
[ "MIT" ]
null
null
null
pipng/imagescale-q-m.py
ShuyaMotouchi/joke
808c4c998cc7f5b7f6f3fb5a3ce421588a70c087
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # Copyright © 2012-13 Qtrac Ltd. All rights reserved. # This program or module is free software: you can redistribute it # and/or modify it under the terms of the GNU General Public License as # published by the Free Software Foundation, either version 3 of the # License, or (at your option)...
36.892086
76
0.63475
585
5,128
5.517949
0.353846
0.027881
0.026332
0.026022
0.178748
0.118959
0.049566
0
0
0
0
0.004491
0.261895
5,128
138
77
37.15942
0.848085
0.12617
0
0.046729
0
0
0.123066
0
0
0
0
0
0
1
0.074766
false
0
0.074766
0
0.196262
0.009346
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
6a1f0af3de00ce3a7fdb8765f1bbb9115dd67f60
35,122
py
Python
test/integration_test.py
NoopDog/azul
37614eff627888065c7b0a277b3137b8a587ed51
[ "Apache-2.0" ]
null
null
null
test/integration_test.py
NoopDog/azul
37614eff627888065c7b0a277b3137b8a587ed51
[ "Apache-2.0" ]
null
null
null
test/integration_test.py
NoopDog/azul
37614eff627888065c7b0a277b3137b8a587ed51
[ "Apache-2.0" ]
null
null
null
from abc import ( ABCMeta, ) from concurrent.futures.thread import ( ThreadPoolExecutor, ) from contextlib import ( contextmanager, ) import csv from functools import ( lru_cache, ) import gzip from io import ( BytesIO, TextIOWrapper, ) import json import logging import os import random import r...
40.231386
117
0.553442
3,599
35,122
5.208113
0.184496
0.011737
0.015258
0.006402
0.188167
0.158237
0.128468
0.101312
0.070476
0.056498
0
0.008481
0.355447
35,122
872
118
40.277523
0.819507
0.066767
0
0.152797
0
0.001364
0.073991
0.008847
0
0
0
0.001147
0.066849
1
0.068213
false
0.002729
0.060027
0.006821
0.177353
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0